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def test_install_package_with_prefix(script, data): prefix_path = (script.scratch_path / 'prefix') result = script.pip('install', '--prefix', prefix_path, '-f', data.find_links, '--no-binary', 'simple', '--no-index', 'simple==1.0') if hasattr(sys, 'pypy_version_info'): path = (script.scratch / 'prefix') else: path = (((script.scratch / 'prefix') / 'lib') / 'python{0}'.format(pyversion)) install_path = ((path / 'site-packages') / 'simple-1.0-py{0}.egg-info'.format(pyversion)) assert (install_path in result.files_created), str(result)
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test installing a package using pip install --prefix .
train
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def _require_user(username, fullname, password=None, is_superuser=False, email=None, alt_src_lang=None): from accounts.utils import verify_user from django.contrib.auth import get_user_model User = get_user_model() criteria = {'username': username, 'full_name': fullname, 'is_active': True, 'is_superuser': is_superuser} (user, created) = User.objects.get_or_create(**criteria) if created: if (password is None): user.set_unusable_password() else: user.set_password(password) if email: user.email = email user.save() if email: verify_user(user) if (alt_src_lang is not None): user.alt_src_langs.add(alt_src_lang()) return user
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helper to get/create a new user .
train
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def shutdown_hard(): return shutdown(timeout=0)
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shutdown a running system with no timeout or warning .
train
false
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def user_passes_test(test_func, login_url=LOGIN_URL): def _dec(view_func): def _checklogin(request, *args, **kwargs): if test_func(request.user): return view_func(request, *args, **kwargs) return HttpResponseRedirect(('%s?%s=%s' % (login_url, REDIRECT_FIELD_NAME, quote(request.get_full_path())))) _checklogin.__doc__ = view_func.__doc__ _checklogin.__dict__ = view_func.__dict__ return _checklogin return _dec
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decorator for views that checks that the user passes the given test .
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def _TestGenerateAccessToken(action, tester, device_dict, auth_info_dict, user_cookie=None, use_short_token=True): response_dict = _GenerateAccessToken(action, tester, device_dict, auth_info_dict, user_cookie, use_short_token=use_short_token) (identity_type, value) = Identity.SplitKey(auth_info_dict['identity']) expected_digits = (4 if (use_short_token or (identity_type == 'Phone')) else 9) assert (response_dict['token_digits'] == expected_digits), response_dict identity = tester._RunAsync(Identity.Query, tester.validator.client, auth_info_dict['identity'], None) tester.validator.ValidateUpdateDBObject(Identity, key=auth_info_dict['identity'], authority='Viewfinder', user_id=identity.user_id, access_token=identity.access_token, expires=identity.expires) return identity
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invokes the auth api that triggers the email of a viewfinder access token .
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@non_atomic_requests def site_series(request, format, group, start, end, field): (start, end) = get_daterange_or_404(start, end) group = ('date' if (group == 'day') else group) series = [] (full_series, keys) = _site_query(group, start, end, field, request) for row in full_series: if (field in row['data']): series.append({'date': row['date'], 'count': row['data'][field], 'data': {}}) if (format == 'csv'): (series, fields) = csv_fields(series) return render_csv(request, None, series, (['date', 'count'] + list(fields)), title=('%s week Site Statistics' % settings.DOMAIN), show_disclaimer=True) return render_json(request, None, series)
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pull a single field from the site_query data .
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def add_dummy_padding(x, depth, boundary): for (k, v) in boundary.items(): if (v == 'none'): d = depth[k] empty_shape = list(x.shape) empty_shape[k] = d empty_chunks = list(x.chunks) empty_chunks[k] = (d,) empty = wrap.empty(empty_shape, chunks=empty_chunks, dtype=x.dtype) out_chunks = list(x.chunks) ax_chunks = list(out_chunks[k]) ax_chunks[0] += d ax_chunks[(-1)] += d out_chunks[k] = ax_chunks x = concatenate([empty, x, empty], axis=k) x = x.rechunk(out_chunks) return x
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pads an array which has none as the boundary type .
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def rand_text_alpha_upper(length, bad=''): return rand_base(length, bad, set(upperAlpha))
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generate a random upper string with alpha chars .
train
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def deferToThread(f, *args, **kwargs): from twisted.internet import reactor return deferToThreadPool(reactor, reactor.getThreadPool(), f, *args, **kwargs)
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run a function in a thread and return the result as a deferred .
train
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def getIntFromFloatString(value): floatString = str(value).strip() if (floatString == ''): return None dotIndex = floatString.find('.') if (dotIndex < 0): return int(value) return int(round(float(floatString)))
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get the int from the string .
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def _get_processor_decline_html(params): payment_support_email = configuration_helpers.get_value('payment_support_email', settings.PAYMENT_SUPPORT_EMAIL) return _format_error_html(_('Sorry! Our payment processor did not accept your payment. The decision they returned was {decision}, and the reason was {reason}. You were not charged. Please try a different form of payment. Contact us with payment-related questions at {email}.').format(decision='<span class="decision">{decision}</span>'.format(decision=params['decision']), reason='<span class="reason">{reason_code}:{reason_msg}</span>'.format(reason_code=params['reason_code'], reason_msg=REASONCODE_MAP.get(params['reason_code'])), email=payment_support_email))
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return html indicating that the users payment was declined .
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def _fix_osmesa_gl_lib_if_testing(): test_name = os.getenv('_VISPY_TESTING_APP', None) if (test_name == 'osmesa'): from ...util.osmesa_gl import fix_osmesa_gl_lib fix_osmesa_gl_lib()
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this functions checks if we a running test with the osmesa backends and fix the gl library if needed .
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def all_correlations_book_version(bait, target): return np.array([np.corrcoef(bait, c)[(0, 1)] for c in target])
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corrs = all_correlations corrs[i] is the correlation between bait and target[i] .
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def allow_remote_invocation(func, method='auto'): setattr(func, 'allow_rmi', method) return func
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all methods which shall be callable through a given ajax action must be decorated with @allowed_action .
train
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def dic(trace, model=None): model = modelcontext(model) mean_deviance = ((-2) * np.mean([model.logp(pt) for pt in trace])) free_rv_means = {rv.name: trace[rv.name].mean(axis=0) for rv in model.free_RVs} deviance_at_mean = ((-2) * model.logp(free_rv_means)) return ((2 * mean_deviance) - deviance_at_mean)
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calculate the deviance information criterion of the samples in trace from model read more theory here - in a paper by some of the leading authorities on model selection - dx .
train
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def getMax(first, second): return max(first, second)
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get the max .
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def get_limit(): return _limit[0]
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get current connection pool limit .
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def rar_extract(rarfile_path, numrars, one_folder, nzo, setname, extraction_path): fail = 0 new_files = None rars = [] passwords = get_all_passwords(nzo) for password in passwords: if password: logging.debug('Trying unrar with password "%s"', password) msg = (T('Trying unrar with password "%s"') % unicoder(password)) nzo.fail_msg = msg nzo.set_unpack_info('Unpack', msg) (fail, new_files, rars) = rar_extract_core(rarfile_path, numrars, one_folder, nzo, setname, extraction_path, password) if (fail != 2): break if (fail == 2): logging.error('%s (%s)', T('Unpacking failed, archive requires a password'), os.path.split(rarfile_path)[1]) return (fail, new_files, rars)
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unpack single rar set rarfile to extraction_path .
train
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def post_order_list(node, filter_func=no_filter): (l, stack) = ([], []) (poped, index) = (0, 0) while node: if filter_func(node): if (node.children and (not poped)): stack.append((node, index)) index = 0 node = node.children[0] else: l.append(node) index += 1 try: node = stack[(-1)][0].children[index] except IndexError: node = None else: node = None poped = 0 if ((node is None) and stack): (node, index) = stack.pop() poped = 1 return l
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create a list with tree nodes for which the <filter> function returned true in a post order fashion .
train
false
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def do_votes_by_user(parser, token): bits = token.contents.split() if (len(bits) != 6): raise template.TemplateSyntaxError(("'%s' tag takes exactly four arguments" % bits[0])) if (bits[2] != 'on'): raise template.TemplateSyntaxError(("second argument to '%s' tag must be 'on'" % bits[0])) if (bits[4] != 'as'): raise template.TemplateSyntaxError(("fourth argument to '%s' tag must be 'as'" % bits[0])) return VotesByUserNode(bits[1], bits[3], bits[5])
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retrieves the votes cast by a user on a list of objects as a dictionary keyed with object ids and stores it in a context variable .
train
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def testNames(tests): names = [] for test in _iterateTests(tests): names.append(test.id()) return names
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return the id of each test within the given test suite or case .
train
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def get_category_value(label): return _get_array_element('category', label, ('animal', 'human', 'airplane', 'truck', 'car', 'blank'))
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returns the category name represented by a category label int .
train
false
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def get_data_cache_dir(data_dir, subdir=None): data_cache_dir = os.environ.get('NEON_DATA_CACHE_DIR') if (data_cache_dir is None): data_cache_dir = data_dir if subdir: subdir = (subdir if isinstance(subdir, list) else [subdir]) data_cache_dir = os.path.join(data_cache_dir, *subdir) if (not os.path.exists(data_cache_dir)): os.makedirs(data_cache_dir) return data_cache_dir
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function for getting cache directory to store data cache files .
train
false
19,188
def _lessbroken_deepcopy(a): from theano.gof.type import _cdata_type if (type(a) in (numpy.ndarray, numpy.memmap)): rval = a.copy() elif (type(a) is _cdata_type): rval = a else: rval = copy.deepcopy(a) assert (type(rval) == type(a)), (type(rval), type(a)) if isinstance(rval, numpy.ndarray): assert (rval.dtype == a.dtype) return rval
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parameters a any object returns object a copy of a that shares no internal storage with the original .
train
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def fast_relpath(path, start): if (not path.startswith(start)): raise ValueError(u'{} is not a prefix of {}'.format(start, path)) if (len(path) == len(start)): return u'' elif (len(start) == 0): return path elif (start[(-1)] == u'/'): return path[len(start):] elif (path[len(start)] == u'/'): return path[(len(start) + 1):] else: raise ValueError(u'{} is not a directory containing {}'.format(start, path))
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a prefix-based relpath .
train
false
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def isInf(value): return ((_exponent(value) == 2047) and _zero_mantissa(value))
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determine if the argument is an infinite ieee 754 value .
train
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@forum.route('/post/<int:post_id>') def view_post(post_id): post = Post.query.filter_by(id=post_id).first_or_404() post_in_topic = Post.query.filter((Post.topic_id == post.topic_id), (Post.id <= post_id)).order_by(Post.id.asc()).count() page = math.ceil((post_in_topic / float(flaskbb_config['POSTS_PER_PAGE']))) return redirect((post.topic.url + ('?page=%d#pid%s' % (page, post.id))))
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returns post data .
train
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def get_memcached(key): data = cache.get(key) if (not data): set_memcached(key, {}) obj = cPickle.loads(cache.get(key)) return obj
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return deserialize object from memcached .
train
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def _create_and_add_option(option): global _current_option _current_option = Option() (type_, params) = _expand_one_key_dictionary(option) _current_option.type = type_ _create_and_add_parameters(params) _current_statement.add_child(_current_option)
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parses the configuration and creates an option instance .
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def check_modify_host_locking(host, update_data): locked = update_data.get('locked', None) if (locked is not None): if (locked and host.locked): raise model_logic.ValidationError({'locked': ('Host already locked by %s on %s.' % (host.locked_by, host.lock_time))}) if ((not locked) and (not host.locked)): raise model_logic.ValidationError({'locked': 'Host already unlocked.'})
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checks when locking/unlocking has been requested if the host is already locked/unlocked .
train
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@handle_response_format @treeio_login_required def dashboard_widget_arrange(request, panel='left', response_format='html'): user = request.user.profile if ((panel == 'left') or (not panel)): shift = (-100) else: shift = 100 if (request.GET and ('id_widget[]' in request.GET)): widget_ids = request.GET.getlist('id_widget[]') widgets = Widget.objects.filter(user=user, pk__in=widget_ids) for widget in widgets: if (unicode(widget.id) in widget_ids): widget.weight = (shift + widget_ids.index(unicode(widget.id))) widget.save() return HttpResponseRedirect(reverse('core_dashboard_index'))
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arrange widgets with ajax request .
train
false
19,198
@given(u'a run having mixed text content') def given_a_run_having_mixed_text_content(context): r_xml = (u' <w:r %s>\n <w:t>abc</w:t>\n <w:tab/>\n <w:t>def</w:t>\n <w:cr/>\n <w:t>ghi</w:t>\n <w:drawing/>\n <w:br/>\n <w:t>jkl</w:t>\n </w:r>' % nsdecls(u'w')) r = parse_xml(r_xml) context.run = Run(r, None)
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mixed here meaning it contains <w:tab/> .
train
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def chi_square_test(observed, expected, alpha=0.05, df=None): if (df is None): df = (observed.size - 1) if (alpha == 0.01): alpha_idx = 0 elif (alpha == 0.05): alpha_idx = 1 else: raise ValueError('support only alpha == 0.05 or 0.01') chi_square = numpy.sum((((observed - expected) ** 2) / expected)) return (chi_square < chi_square_table[alpha_idx][df])
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testing goodness-of-fit test with pearsons chi-squared test .
train
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def insert_pure_function(module, fnty, name): fn = module.get_or_insert_function(fnty, name=name) fn.attributes.add('readonly') fn.attributes.add('nounwind') return fn
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insert a pure function in the given module .
train
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def security_group_count_by_project(context, project_id, session=None): return IMPL.security_group_count_by_project(context, project_id, session=session)
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count number of security groups in a project .
train
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def get_listing_content_type(req): query_format = get_param(req, 'format') if query_format: req.accept = FORMAT2CONTENT_TYPE.get(query_format.lower(), FORMAT2CONTENT_TYPE['plain']) out_content_type = req.accept.best_match(['text/plain', 'application/json', 'application/xml', 'text/xml']) if (not out_content_type): raise HTTPNotAcceptable(request=req) return out_content_type
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determine the content type to use for an account or container listing response .
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false
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def tag_(name, image, force=False): image_id = inspect_image(name)['Id'] (repo_name, repo_tag) = _get_repo_tag(image) response = _client_wrapper('tag', image_id, repo_name, tag=repo_tag, force=force) _clear_context() return response
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tag an image into a repository and return true .
train
false
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def setup_redis(): pools = {} for (name, config) in settings.STREAM_REDIS_CONFIG.items(): pool = redis.ConnectionPool(host=config['host'], port=config['port'], password=config.get('password'), db=config['db'], decode_responses=True) pools[name] = pool return pools
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generate config for redis cache .
train
false
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def get_job_info(name=None): if (not name): raise SaltInvocationError('Required parameter `name` is missing.') server = _connect() if (not job_exists(name)): raise SaltInvocationError('Job `{0}` does not exist.'.format(name)) job_info = server.get_job_info(name) if job_info: return job_info return False
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return information about the jenkins job .
train
true
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def decorated_with_abc(func): if func.decorators: for node in func.decorators.nodes: try: infered = next(node.infer()) except astroid.InferenceError: continue if (infered and (infered.qname() in ABC_METHODS)): return True
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determine if the func node is decorated with abc decorators .
train
false
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def post_save_profile(instance, sender, **kwargs): if ((not instance.is_superuser) and kwargs['created'] and (not kwargs['raw']) and (instance.username != 'AnonymousUser')): current_site = Site.objects.get_current() SitePeople.objects.get(site=current_site).people.add(instance)
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signal to ensure that every created user is assigned to the current site only .
train
false
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def check_boolean_field_default_value(): fields = [] for cls in models.get_models(): opts = cls._meta for f in opts.local_fields: if (isinstance(f, models.BooleanField) and (not f.has_default())): fields.append((u'%s.%s: "%s"' % (opts.app_label, opts.object_name, f.name))) if fields: fieldnames = u', '.join(fields) message = [u'You have not set a default value for one or more BooleanFields:', (u'%s.' % fieldnames), u'In Django 1.6 the default value of BooleanField was changed from', u"False to Null when Field.default isn't defined. See", u'https://docs.djangoproject.com/en/1.6/ref/models/fields/#booleanfield', u'for more information.'] return u' '.join(message)
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checks if there are any booleanfields without a default value .
train
false
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def test_finally_execution(): segBad = FakeWalSegment((('1' * 8) * 3)) segOK = FakeWalSegment((('2' * 8) * 3)) class CleanupCheckingUploader(object, ): def __init__(self): self.cleaned_up = False def __call__(self, segment): if (segment is segOK): try: while True: gevent.sleep(0.1) finally: self.cleaned_up = True elif (segment is segBad): raise Explosion('fail') else: assert False, 'Expect only two segments' segment._uploaded = True return segment uploader = CleanupCheckingUploader() group = worker.WalTransferGroup(uploader) group.start(segOK) group.start(segBad) with pytest.raises(Explosion): group.join() assert (uploader.cleaned_up is True)
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when one segment fails ensure parallel segments clean up .
train
false
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def accept_vpc_peering_connection(conn_id='', name='', region=None, key=None, keyid=None, profile=None, dry_run=False): if (not _exactly_one((conn_id, name))): raise SaltInvocationError('One (but not both) of vpc_peering_connection_id or name must be provided.') conn = _get_conn3(region=region, key=key, keyid=keyid, profile=profile) if name: conn_id = _vpc_peering_conn_id_for_name(name, conn) if (not conn_id): raise SaltInvocationError('No ID found for this VPC peering connection! ({0}) Please make sure this VPC peering connection exists or invoke this function with a VPC peering connection ID'.format(name)) try: log.debug('Trying to accept vpc peering connection') conn.accept_vpc_peering_connection(DryRun=dry_run, VpcPeeringConnectionId=conn_id) return {'msg': 'VPC peering connection accepted.'} except botocore.exceptions.ClientError as err: log.error('Got an error while trying to accept vpc peering') return {'error': salt.utils.boto.get_error(err)}
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request a vpc peering connection between two vpcs .
train
true
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def test_empty_locale_html(): s = helpers.locale_html(None) assert (not s), 'locale_html on None must be empty.'
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locale_html must still work if field is none .
train
false
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def can_access_others_blocks(requesting_user, course_key): return has_access(requesting_user, CourseStaffRole.ROLE, course_key)
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returns whether the requesting_user can access the blocks for other users in the given course .
train
false
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def olympus_special_mode(v): mode1 = {0: 'Normal', 1: 'Unknown', 2: 'Fast', 3: 'Panorama'} mode2 = {0: 'Non-panoramic', 1: 'Left to right', 2: 'Right to left', 3: 'Bottom to top', 4: 'Top to bottom'} if ((v[0] not in mode1) or (v[2] not in mode2)): return v return ('%s - sequence %d - %s' % (mode1[v[0]], v[1], mode2[v[2]]))
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decode olympus specialmode tag in makernote .
train
false
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def _openstack_logged_method(method_name, original_name): def _run_with_logging(self, *args, **kwargs): original = getattr(self, original_name) method = getattr(original, method_name) with OPENSTACK_ACTION(operation=[method_name, args, kwargs]): try: return method(*args, **kwargs) except NovaClientException as e: NOVA_CLIENT_EXCEPTION(code=e.code, message=e.message, details=e.details, request_id=e.request_id, url=e.url, method=e.method).write() raise except KeystoneHttpError as e: KEYSTONE_HTTP_ERROR(code=e.http_status, message=e.message, details=e.details, request_id=e.request_id, url=e.url, method=e.method, response=e.response.text).write() raise return _run_with_logging
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run a method and log additional information about any exceptions that are raised .
train
false
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def col(loc, strg): return ((((loc < len(strg)) and (strg[loc] == '\n')) and 1) or (loc - strg.rfind('\n', 0, loc)))
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return a symbolic column variable .
train
true
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def _str_extract_frame(arr, pat, flags=0): from pandas import DataFrame regex = re.compile(pat, flags=flags) groups_or_na = _groups_or_na_fun(regex) names = dict(zip(regex.groupindex.values(), regex.groupindex.keys())) columns = [names.get((1 + i), i) for i in range(regex.groups)] if (len(arr) == 0): return DataFrame(columns=columns, dtype=object) try: result_index = arr.index except AttributeError: result_index = None return DataFrame([groups_or_na(val) for val in arr], columns=columns, index=result_index, dtype=object)
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for each subject string in the series .
train
true
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def printout(queries, things, default=None, f=sys.stdout, **kwargs): results = denorm(queries, things, default=None) fields = set(itertools.chain(*(x.keys() for x in results))) W = csv.DictWriter(f=f, fieldnames=fields, **kwargs) W.writeheader() for r in results: W.writerow(r)
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will print header and objects **kwargs go to csv .
train
false
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def printable_name(string, code_style=False): if (code_style and ('_' in string)): string = string.replace('_', ' ') parts = string.split() if (code_style and (len(parts) == 1) and (not (string.isalpha() and string.islower()))): parts = _split_camel_case(parts[0]) return ' '.join(((part[0].upper() + part[1:]) for part in parts))
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generates and returns printable name from the given string .
train
false
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@raises(ValueError) def test_desaturation_prop(): utils.desaturate('blue', 50)
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test that pct outside of [0 .
train
false
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def _sh_real_to_complex(shs, order): if (order == 0): return shs[0] else: return ((shs[0] + ((1j * np.sign(order)) * shs[1])) / np.sqrt(2.0))
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convert real spherical harmonic pair to complex .
train
false
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def save_backend_configuration(dataset_backend_name, dataset_backend_configuration): dataset_path = FilePath(mkdtemp()).child('dataset-backend.yml') print 'Saving dataset backend config to: {}'.format(dataset_path.path) dataset_path.setContent(yaml.safe_dump({dataset_backend_name.name: dataset_backend_configuration})) return dataset_path
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saves the backend configuration to a local file for consumption by the trial process .
train
false
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def req_items_for_inv(site_id, quantity_type): if (not settings.has_module('req')): return Storage() table = s3db.req_req itable = s3db.req_req_item query = (((((((table.site_id == site_id) & (table.id == itable.req_id)) & (itable.item_pack_id == itable.item_pack_id)) & (itable[('quantity_%s' % quantity_type)] < itable.quantity)) & (table.cancel == False)) & (table.deleted == False)) & (itable.deleted == False)) req_items = db(query).select(itable.id, itable.req_id, itable.item_id, itable.quantity, itable[('quantity_%s' % quantity_type)], itable.item_pack_id, orderby=(table.date_required | table.date)) req_item_ids = [] unique_req_items = Storage() for req_item in req_items: if (req_item.item_id not in req_item_ids): unique_req_items[req_item.item_id] = Storage(req_item.as_dict()) req_item_ids.append(req_item.item_id) return unique_req_items
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used by recv_process & send_process returns a dict of unique req items key = item_id .
train
false
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def str_distance(a, b): (n, m) = (len(a), len(b)) if (n > m): (a, b) = (b, a) (n, m) = (m, n) current = range((n + 1)) for i in range(1, (m + 1)): (previous, current) = (current, ([i] + ([0] * n))) for j in range(1, (n + 1)): (add, delete) = ((previous[j] + 1), (current[(j - 1)] + 1)) change = previous[(j - 1)] if (a[(j - 1)] != b[(i - 1)]): change += 1 current[j] = min(add, delete, change) return current[n]
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calculates the levenshtein distance between a and b .
train
true
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def line_collection_2d_to_3d(col, zs=0, zdir=u'z'): segments3d = paths_to_3d_segments(col.get_paths(), zs, zdir) col.__class__ = Line3DCollection col.set_segments(segments3d)
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convert a linecollection to a line3dcollection object .
train
false
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def load_grammar(gt='Grammar.txt', gp=None, save=True, force=False, logger=None): if (logger is None): logger = logging.getLogger() if (gp is None): (head, tail) = os.path.splitext(gt) if (tail == '.txt'): tail = '' gp = (((head + tail) + '.'.join(map(str, sys.version_info))) + '.pickle') if (force or (not _newer(gp, gt))): logger.info('Generating grammar tables from %s', gt) g = pgen.generate_grammar(gt) if save: logger.info('Writing grammar tables to %s', gp) try: g.dump(gp) except IOError as e: logger.info(('Writing failed:' + str(e))) else: g = grammar.Grammar() g.load(gp) return g
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load the grammar .
train
true
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def file_move_safe(old_file_name, new_file_name, chunk_size=(1024 * 64), allow_overwrite=False): if _samefile(old_file_name, new_file_name): return try: os.rename(old_file_name, new_file_name) return except OSError: pass old_file = open(old_file_name, 'rb') try: fd = os.open(new_file_name, (((os.O_WRONLY | os.O_CREAT) | getattr(os, 'O_BINARY', 0)) | (((not allow_overwrite) and os.O_EXCL) or 0))) try: locks.lock(fd, locks.LOCK_EX) current_chunk = None while (current_chunk != ''): current_chunk = old_file.read(chunk_size) os.write(fd, current_chunk) finally: locks.unlock(fd) os.close(fd) finally: old_file.close() copystat(old_file_name, new_file_name) try: os.remove(old_file_name) except OSError as e: if ((getattr(e, 'winerror', 0) != 32) and (getattr(e, 'errno', 0) != 13)): raise
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moves a file from one location to another in the safest way possible .
train
false
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def _urljoin(base, url): parsed = urlparse(base) scheme = parsed.scheme return urlparse(urljoin(parsed._replace(scheme='http').geturl(), url))._replace(scheme=scheme).geturl()
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construct a full url by combining a "base url" with another url .
train
true
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def advance_rest(clock): clock.advance((EXPIRATION_TIME.total_seconds() - 1))
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train
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def get_updated_cache_time(): cache_mtime = get_cache_mtime() mtimestamp = datetime.datetime.fromtimestamp(cache_mtime) updated_cache_time = int(time.mktime(mtimestamp.timetuple())) return (mtimestamp, updated_cache_time)
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return the mtime time stamp and the updated cache time .
train
false
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def public_factory(target, location): if isinstance(target, type): fn = target.__init__ callable_ = target doc = ('Construct a new :class:`.%s` object. \n\nThis constructor is mirrored as a public API function; see :func:`~%s` for a full usage and argument description.' % (target.__name__, location)) else: fn = callable_ = target doc = ('This function is mirrored; see :func:`~%s` for a description of arguments.' % location) location_name = location.split('.')[(-1)] spec = compat.inspect_getfullargspec(fn) del spec[0][0] metadata = format_argspec_plus(spec, grouped=False) metadata['name'] = location_name code = ('def %(name)s(%(args)s):\n return cls(%(apply_kw)s)\n' % metadata) env = {'cls': callable_, 'symbol': symbol} exec code in env decorated = env[location_name] decorated.__doc__ = fn.__doc__ decorated.__module__ = ('sqlalchemy' + location.rsplit('.', 1)[0]) if (compat.py2k or hasattr(fn, '__func__')): fn.__func__.__doc__ = doc else: fn.__doc__ = doc return decorated
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produce a wrapping function for the given cls or classmethod .
train
false
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def systemInformationType2(): a = L2PseudoLength(l2pLength=22) b = TpPd(pd=6) c = MessageType(mesType=26) d = NeighbourCellsDescription() e = NccPermitted() f = RachControlParameters() packet = (((((a / b) / c) / d) / e) / f) return packet
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system information type 2 section 9 .
train
true
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def transaction_teardown_request(error=None): if view_has_annotation(NO_AUTO_TRANSACTION_ATTR): return if ((error is not None) and current_atomic): current_atomic.__exit__(error.__class__, error, None)
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rollback transaction on uncaught error .
train
false
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def is_scriptable(application): if os.path.isdir(application): plistfile = os.path.join(application, 'Contents', 'Info.plist') if (not os.path.exists(plistfile)): return False plist = plistlib.Plist.fromFile(plistfile) return plist.get('NSAppleScriptEnabled', False) currf = CurResFile() try: refno = macresource.open_pathname(application) except MacOS.Error: return False UseResFile(refno) n_terminology = (((Count1Resources('aete') + Count1Resources('aeut')) + Count1Resources('scsz')) + Count1Resources('osiz')) CloseResFile(refno) UseResFile(currf) return (n_terminology > 0)
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return true if the application is scriptable .
train
false
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def get_example_data(fname): datadir = os.path.join(get_data_path(), 'example') fullpath = os.path.join(datadir, fname) if (not os.path.exists(fullpath)): raise IOError(('could not find matplotlib example file "%s" in data directory "%s"' % (fname, datadir))) return file(fullpath, 'rb')
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return a filehandle to one of the example files in mpl-data/example *fname* the name of one of the files in mpl-data/example .
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def get_gssapi_token(principal, host, domain): if (not HAS_GSSAPI): raise ImportError('The gssapi library is not imported.') service = '{0}/{1}@{2}'.format(principal, host, domain) log.debug('Retrieving gsspi token for service {0}'.format(service)) service_name = gssapi.Name(service, gssapi.C_NT_USER_NAME) ctx = gssapi.InitContext(service_name) in_token = None while (not ctx.established): out_token = ctx.step(in_token) if out_token: encoded_token = base64.b64encode(out_token) return encoded_token if ctx.established: break if (not in_token): raise salt.exceptions.CommandExecutionError("Can't receive token, no response from server") raise salt.exceptions.CommandExecutionError("Context established, but didn't receive token")
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get the gssapi token for kerberos connection principal the service principal host host url where we would like to authenticate domain kerberos user domain .
train
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@pytest.fixture(autouse=True) def unpin_db(request): request.addfinalizer(pinning.unpin_this_thread)
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unpin the database from master in the current db .
train
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def get_numpy_dtype(obj): if (ndarray is not FakeObject): import numpy as np if (isinstance(obj, np.generic) or isinstance(obj, np.ndarray)): try: return obj.dtype.type except (AttributeError, RuntimeError): return
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return numpy data type associated to obj return none if numpy is not available or if obj is not a numpy array or scalar .
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def make_character(info, value, in_set=False): if in_set: return Character(value) return Character(value, case_flags=make_case_flags(info))
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makes a character literal .
train
false
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def get_pem_entries(glob_path): ret = {} for path in glob.glob(glob_path): if os.path.isfile(path): try: ret[path] = get_pem_entry(text=path) except ValueError: pass return ret
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returns a dict containing pem entries in files matching a glob glob_path: a path to certificates to be read and returned .
train
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def read_raw_brainvision(vhdr_fname, montage=None, eog=('HEOGL', 'HEOGR', 'VEOGb'), misc='auto', scale=1.0, preload=False, response_trig_shift=0, event_id=None, verbose=None): return RawBrainVision(vhdr_fname=vhdr_fname, montage=montage, eog=eog, misc=misc, scale=scale, preload=preload, response_trig_shift=response_trig_shift, event_id=event_id, verbose=verbose)
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reader for brain vision eeg file .
train
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def upload_template(filename, destination, context=None, use_jinja=False, template_dir=None, use_sudo=False, backup=True, mirror_local_mode=False, mode=None, pty=None, keep_trailing_newline=False, temp_dir=''): func = ((use_sudo and sudo) or run) if (pty is not None): func = partial(func, pty=pty) with settings(hide('everything'), warn_only=True): if func(('test -d %s' % _expand_path(destination))).succeeded: sep = ('' if destination.endswith('/') else '/') destination += (sep + os.path.basename(filename)) if (mirror_local_mode and (mode is None)): mode = os.stat(apply_lcwd(filename, env)).st_mode mirror_local_mode = False text = None if use_jinja: try: template_dir = (template_dir or os.getcwd()) template_dir = apply_lcwd(template_dir, env) from jinja2 import Environment, FileSystemLoader jenv = Environment(loader=FileSystemLoader(template_dir), keep_trailing_newline=keep_trailing_newline) text = jenv.get_template(filename).render(**(context or {})) text = text.encode('utf-8') except ImportError: import traceback tb = traceback.format_exc() abort((tb + '\nUnable to import Jinja2 -- see above.')) else: if template_dir: filename = os.path.join(template_dir, filename) filename = apply_lcwd(filename, env) with open(os.path.expanduser(filename)) as inputfile: text = inputfile.read() if context: text = (text % context) if (backup and exists(destination)): func(('cp %s{,.bak}' % _expand_path(destination))) return put(local_path=StringIO(text), remote_path=destination, use_sudo=use_sudo, mirror_local_mode=mirror_local_mode, mode=mode, temp_dir=temp_dir)
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upload a template file .
train
false
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def update_language_names(): with open(frappe.get_app_path(u'frappe', u'geo', u'languages.json'), u'r') as f: data = json.loads(f.read()) for l in data: frappe.db.set_value(u'Language', l[u'code'], u'language_name', l[u'name'])
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update frappe/geo/languages .
train
false
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def test_locale_html_xss(): testfield = Mock() testfield.locale = '<script>alert(1)</script>' s = helpers.locale_html(testfield) assert ('<script>' not in s) assert ('&lt;script&gt;alert(1)&lt;/script&gt;' in s)
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test for nastiness-removal in the transfields locale .
train
false
19,258
def writeOutputFileHeader(output_file, session_metadata_columns, log_entry_names): allcols = ((session_metadata_columns + log_entry_names) + session_uservar_columns) output_file.write(' DCTB '.join(allcols)) output_file.write('\n')
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writes the header line at the top of the log file .
train
false
19,259
def datastore_fields(resource, valid_field_types): data = {'resource_id': resource['id'], 'limit': 0} fields = toolkit.get_action('datastore_search')({}, data)['fields'] return [{'value': f['id'], 'text': f['id']} for f in fields if (f['type'] in valid_field_types)]
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return a list of all datastore fields for a given resource .
train
false
19,260
def reflection_from_matrix(matrix): M = numpy.array(matrix, dtype=numpy.float64, copy=False) (w, V) = numpy.linalg.eig(M[:3, :3]) i = numpy.where((abs((numpy.real(w) + 1.0)) < 1e-08))[0] if (not len(i)): raise ValueError('no unit eigenvector corresponding to eigenvalue -1') normal = numpy.real(V[:, i[0]]).squeeze() (w, V) = numpy.linalg.eig(M) i = numpy.where((abs((numpy.real(w) - 1.0)) < 1e-08))[0] if (not len(i)): raise ValueError('no unit eigenvector corresponding to eigenvalue 1') point = numpy.real(V[:, i[(-1)]]).squeeze() point /= point[3] return (point, normal)
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return mirror plane point and normal vector from reflection matrix .
train
true
19,261
def unicode(s): if PY3: return s else: return __builtin__.unicode(s, 'utf-8')
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force conversion of s to unicode .
train
false
19,262
def _xml_escape(data): from_symbols = '&><"\'' to_symbols = ((('&' + s) + ';') for s in 'amp gt lt quot apos'.split()) for (from_, to_) in zip(from_symbols, to_symbols): data = data.replace(from_, to_) return data
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escape & .
train
true
19,266
def test_oldstyle_getattr(): class C: def __getattr__(self, name): return globals()[name] a = C()
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verify we dont access __getattr__ while creating an old style class .
train
false
19,267
def load_configuration(arg_list, log_printer, arg_parser=None): cli_sections = parse_cli(arg_list=arg_list, arg_parser=arg_parser) check_conflicts(cli_sections) if (bool(cli_sections['default'].get('find_config', 'False')) and (str(cli_sections['default'].get('config')) == '')): cli_sections['default'].add_or_create_setting(Setting('config', re.escape(find_user_config(os.getcwd())))) targets = [] for item in list(cli_sections['default'].contents.pop('targets', '')): targets.append(item.lower()) if bool(cli_sections['default'].get('no_config', 'False')): sections = cli_sections else: base_sections = load_config_file(Constants.system_coafile, log_printer) user_sections = load_config_file(Constants.user_coafile, log_printer, silent=True) default_config = str(base_sections['default'].get('config', '.coafile')) user_config = str(user_sections['default'].get('config', default_config)) config = os.path.abspath(str(cli_sections['default'].get('config', user_config))) try: save = bool(cli_sections['default'].get('save', 'False')) except ValueError: save = True coafile_sections = load_config_file(config, log_printer, silent=save) sections = merge_section_dicts(base_sections, user_sections) sections = merge_section_dicts(sections, coafile_sections) sections = merge_section_dicts(sections, cli_sections) for section in sections: if (section != 'default'): sections[section].defaults = sections['default'] str_log_level = str(sections['default'].get('log_level', '')).upper() log_printer.log_level = LOG_LEVEL.str_dict.get(str_log_level, LOG_LEVEL.INFO) return (sections, targets)
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load a yaml rule file and fill in the relevant fields with objects .
train
false
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def ratsimp(expr): (f, g) = cancel(expr).as_numer_denom() try: (Q, r) = reduced(f, [g], field=True, expand=False) except ComputationFailed: return (f / g) return (Add(*Q) + cancel((r / g)))
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put an expression over a common denominator .
train
false
19,270
def check_lowercase_bucketname(n): if (not (n + 'a').islower()): raise BotoClientError('Bucket names cannot contain upper-case characters when using either the sub-domain or virtual hosting calling format.') return True
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bucket names must not contain uppercase characters .
train
false
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def get_ipython_cmd(as_string=False): ipython_cmd = [sys.executable, '-m', 'IPython'] if as_string: ipython_cmd = ' '.join(ipython_cmd) return ipython_cmd
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return appropriate ipython command line name .
train
false
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def sz_margin_details(date='', retry_count=3, pause=0.001): for _ in range(retry_count): time.sleep(pause) try: request = Request((rv.MAR_SZ_MX_URL % (ct.P_TYPE['http'], ct.DOMAINS['szse'], ct.PAGES['szsefc'], date))) lines = urlopen(request, timeout=10).read() if (len(lines) <= 200): return pd.DataFrame() df = pd.read_html(lines, skiprows=[0])[0] df.columns = rv.MAR_SZ_MX_COLS df['stockCode'] = df['stockCode'].map((lambda x: str(x).zfill(6))) df['opDate'] = date except Exception as e: print e else: return df raise IOError(ct.NETWORK_URL_ERROR_MSG)
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parameters date:string 明细数据日期 format:yyyy-mm-dd 默认为空 retry_count : int .
train
false
19,274
def _ancestors_to_call(klass_node, method='__init__'): to_call = {} for base_node in klass_node.ancestors(recurs=False): try: to_call[base_node] = next(base_node.igetattr(method)) except astroid.InferenceError: continue return to_call
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return a dictionary where keys are the list of base classes providing the queried method .
train
true
19,276
def _find_yaml_path(): (current, last) = (os.getcwd(), None) while (current != last): for yaml_name in FILENAMES: yaml_path = os.path.join(current, yaml_name) if os.path.exists(yaml_path): return yaml_path last = current (current, last) = (os.path.dirname(current), current) return None
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traverse directory trees to find conf .
train
false
19,277
def setExtendedPoint(lineSegmentEnd, pointOriginal, x): if ((x > min(lineSegmentEnd.point.real, pointOriginal.real)) and (x < max(lineSegmentEnd.point.real, pointOriginal.real))): lineSegmentEnd.point = complex(x, pointOriginal.imag)
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set the point in the extended line segment .
train
false
19,278
def create_bootstrap_script(extra_text, python_version=''): filename = __file__ if filename.endswith('.pyc'): filename = filename[:(-1)] with codecs.open(filename, 'r', encoding='utf-8') as f: content = f.read() py_exe = ('python%s' % python_version) content = ((('#!/usr/bin/env %s\n' % py_exe) + '## WARNING: This file is generated\n') + content) return content.replace('##EXTEND##', extra_text)
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creates a bootstrap script .
train
true
19,279
def _parse_ipv6(a): (l, _, r) = a.partition('::') l_groups = list(chain(*[divmod(int(x, 16), 256) for x in l.split(':') if x])) r_groups = list(chain(*[divmod(int(x, 16), 256) for x in r.split(':') if x])) zeros = ([0] * ((16 - len(l_groups)) - len(r_groups))) return tuple(((l_groups + zeros) + r_groups))
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parse ipv6 address .
train
false
19,281
def _build_config_tree(name, configuration): (type_, id_, options) = _get_type_id_options(name, configuration) global _INDENT, _current_statement _INDENT = '' if (type_ == 'config'): _current_statement = GivenStatement(options) elif (type_ == 'log'): _current_statement = UnnamedStatement(type='log') _parse_log_statement(options) else: if _is_statement_unnamed(type_): _current_statement = UnnamedStatement(type=type_) else: _current_statement = NamedStatement(type=type_, id=id_) _parse_statement(options)
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build the configuration tree .
train
true
19,282
def _MakeDispatchListIntoYaml(application, dispatch_list): statements = [('application: %s' % application), 'dispatch:'] for entry in dispatch_list: statements += entry.ToYaml() return ('\n'.join(statements) + '\n')
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converts list of dispatchentry objects into a yaml string .
train
false
19,283
def load_pyopenssl_private_key(*names): loader = _guess_loader(names[(-1)], OpenSSL.crypto.FILETYPE_PEM, OpenSSL.crypto.FILETYPE_ASN1) return OpenSSL.crypto.load_privatekey(loader, load_vector(*names))
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load pyopenssl private key .
train
false
19,284
def findlinestarts(code): byte_increments = [ord(c) for c in code.co_lnotab[0::2]] line_increments = [ord(c) for c in code.co_lnotab[1::2]] lastlineno = None lineno = code.co_firstlineno addr = 0 for (byte_incr, line_incr) in zip(byte_increments, line_increments): if byte_incr: if (lineno != lastlineno): (yield (addr, lineno)) lastlineno = lineno addr += byte_incr lineno += line_incr if (lineno != lastlineno): (yield (addr, lineno))
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find the offsets in a byte code which are start of lines in the source .
train
true
19,286
def _genLoggingFilePath(): appName = (os.path.splitext(os.path.basename(sys.argv[0]))[0] or 'UnknownApp') appLogDir = os.path.abspath(os.path.join(os.environ['NTA_LOG_DIR'], ('numenta-logs-%s' % (os.environ['USER'],)), appName)) appLogFileName = ('%s-%s-%s.log' % (appName, long(time.mktime(time.gmtime())), os.getpid())) return os.path.join(appLogDir, appLogFileName)
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generate a filepath for the calling app .
train
true
19,287
def load_lua(filename, **kwargs): with open(filename, 'rb') as f: reader = T7Reader(f, **kwargs) return reader.read()
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loads the given t7 file using default settings; kwargs are forwarded to t7reader .
train
false
19,289
@pytest.mark.parametrize('parallel', [True, False]) def test_include_names(parallel, read_basic): table = read_basic('A B C D\n1 2 3 4\n5 6 7 8', include_names=['A', 'D'], parallel=parallel) expected = Table([[1, 5], [4, 8]], names=('A', 'D')) assert_table_equal(table, expected)
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if include_names is not none .
train
false