body_hash stringlengths 64 64 | body stringlengths 23 109k | docstring stringlengths 1 57k | path stringlengths 4 198 | name stringlengths 1 115 | repository_name stringlengths 7 111 | repository_stars float64 0 191k | lang stringclasses 1
value | body_without_docstring stringlengths 14 108k | unified stringlengths 45 133k |
|---|---|---|---|---|---|---|---|---|---|
cf234fff51e0edb360a9a997a56a6ad0f57b0f053a63bbb8842f1f89c282e7de | def test_artifacttype_create_not_logged_in(self):
' test create view '
destination = ('/login/?next=' + urllib.parse.quote('/artifacts/artifacttype/create/', safe=''))
response = self.client.get('/artifacts/artifacttype/create/', follow=True)
self.assertRedirects(response, destination, status_code=302, ... | test create view | dfirtrack_artifacts/tests/artifacttype/test_artifacttype_views.py | test_artifacttype_create_not_logged_in | FabFaeb/dfirtrack | 1 | python | def test_artifacttype_create_not_logged_in(self):
' '
destination = ('/login/?next=' + urllib.parse.quote('/artifacts/artifacttype/create/', safe=))
response = self.client.get('/artifacts/artifacttype/create/', follow=True)
self.assertRedirects(response, destination, status_code=302, target_status_code... | def test_artifacttype_create_not_logged_in(self):
' '
destination = ('/login/?next=' + urllib.parse.quote('/artifacts/artifacttype/create/', safe=))
response = self.client.get('/artifacts/artifacttype/create/', follow=True)
self.assertRedirects(response, destination, status_code=302, target_status_code... |
c824bfc835345661618c146c1df659e25e3933a3a7d4d396ba0638cf8f12f292 | def test_artifacttype_create_logged_in(self):
' test create view '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
response = self.client.get('/artifacts/artifacttype/create/')
self.assertEqual(response.status_code, 200) | test create view | dfirtrack_artifacts/tests/artifacttype/test_artifacttype_views.py | test_artifacttype_create_logged_in | FabFaeb/dfirtrack | 1 | python | def test_artifacttype_create_logged_in(self):
' '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
response = self.client.get('/artifacts/artifacttype/create/')
self.assertEqual(response.status_code, 200) | def test_artifacttype_create_logged_in(self):
' '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
response = self.client.get('/artifacts/artifacttype/create/')
self.assertEqual(response.status_code, 200)<|docstring|>test create view<|endoftext|> |
7bcc8437211c438285537d4134ad5a7fc4cf4bf0184bcbdd3d81e2d3eae21d67 | def test_artifacttype_create_template(self):
' test create view '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
response = self.client.get('/artifacts/artifacttype/create/')
self.assertTemplateUsed(response, 'dfirtrack_artifacts/artifacttype/artifacttype_add.html') | test create view | dfirtrack_artifacts/tests/artifacttype/test_artifacttype_views.py | test_artifacttype_create_template | FabFaeb/dfirtrack | 1 | python | def test_artifacttype_create_template(self):
' '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
response = self.client.get('/artifacts/artifacttype/create/')
self.assertTemplateUsed(response, 'dfirtrack_artifacts/artifacttype/artifacttype_add.html') | def test_artifacttype_create_template(self):
' '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
response = self.client.get('/artifacts/artifacttype/create/')
self.assertTemplateUsed(response, 'dfirtrack_artifacts/artifacttype/artifacttype_add.html')<|docstring|>tes... |
be0a507634320737bb2e85c88cdc734aad6f31d36aed42c88ccd428817d74431 | def test_artifacttype_create_get_user_context(self):
' test create view '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
response = self.client.get('/artifacts/artifacttype/create/')
self.assertEqual(str(response.context['user']), 'testuser_artifacttype') | test create view | dfirtrack_artifacts/tests/artifacttype/test_artifacttype_views.py | test_artifacttype_create_get_user_context | FabFaeb/dfirtrack | 1 | python | def test_artifacttype_create_get_user_context(self):
' '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
response = self.client.get('/artifacts/artifacttype/create/')
self.assertEqual(str(response.context['user']), 'testuser_artifacttype') | def test_artifacttype_create_get_user_context(self):
' '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
response = self.client.get('/artifacts/artifacttype/create/')
self.assertEqual(str(response.context['user']), 'testuser_artifacttype')<|docstring|>test create vi... |
ca511b041f4ede01e572e50d133b4f6649b36ae68cc9a9f2f8ab93ec2b5fdb2a | def test_artifacttype_create_redirect(self):
' test create view '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
destination = urllib.parse.quote('/artifacts/artifacttype/create/', safe='/')
response = self.client.get('/artifacts/artifacttype/create', follow=True)
... | test create view | dfirtrack_artifacts/tests/artifacttype/test_artifacttype_views.py | test_artifacttype_create_redirect | FabFaeb/dfirtrack | 1 | python | def test_artifacttype_create_redirect(self):
' '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
destination = urllib.parse.quote('/artifacts/artifacttype/create/', safe='/')
response = self.client.get('/artifacts/artifacttype/create', follow=True)
self.assertRe... | def test_artifacttype_create_redirect(self):
' '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
destination = urllib.parse.quote('/artifacts/artifacttype/create/', safe='/')
response = self.client.get('/artifacts/artifacttype/create', follow=True)
self.assertRe... |
2341b5e754a63d66e04f3308b9be55b770187afdea5fcfae1c365baabf3988e6 | def test_artifacttype_create_post_redirect(self):
' test create view '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
data_dict = {'artifacttype_name': 'artifacttype_create_post_test'}
response = self.client.post('/artifacts/artifacttype/create/', data_dict)
art... | test create view | dfirtrack_artifacts/tests/artifacttype/test_artifacttype_views.py | test_artifacttype_create_post_redirect | FabFaeb/dfirtrack | 1 | python | def test_artifacttype_create_post_redirect(self):
' '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
data_dict = {'artifacttype_name': 'artifacttype_create_post_test'}
response = self.client.post('/artifacts/artifacttype/create/', data_dict)
artifacttype_id = A... | def test_artifacttype_create_post_redirect(self):
' '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
data_dict = {'artifacttype_name': 'artifacttype_create_post_test'}
response = self.client.post('/artifacts/artifacttype/create/', data_dict)
artifacttype_id = A... |
fa6a8e538b04b87a7256cba85cbfac1bef5536f40061c3c7992fe72109dc61a5 | def test_artifacttype_create_post_invalid_reload(self):
' test create view '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
data_dict = {}
response = self.client.post('/artifacts/artifacttype/create/', data_dict)
self.assertEqual(response.status_code, 200) | test create view | dfirtrack_artifacts/tests/artifacttype/test_artifacttype_views.py | test_artifacttype_create_post_invalid_reload | FabFaeb/dfirtrack | 1 | python | def test_artifacttype_create_post_invalid_reload(self):
' '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
data_dict = {}
response = self.client.post('/artifacts/artifacttype/create/', data_dict)
self.assertEqual(response.status_code, 200) | def test_artifacttype_create_post_invalid_reload(self):
' '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
data_dict = {}
response = self.client.post('/artifacts/artifacttype/create/', data_dict)
self.assertEqual(response.status_code, 200)<|docstring|>test crea... |
76e07b7a995bca521b93644bac1b53dc55c442934b0d88f25dc22d224d460065 | def test_artifacttype_create_post_invalid_template(self):
' test create view '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
data_dict = {}
response = self.client.post('/artifacts/artifacttype/create/', data_dict)
self.assertTemplateUsed(response, 'dfirtrack_ar... | test create view | dfirtrack_artifacts/tests/artifacttype/test_artifacttype_views.py | test_artifacttype_create_post_invalid_template | FabFaeb/dfirtrack | 1 | python | def test_artifacttype_create_post_invalid_template(self):
' '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
data_dict = {}
response = self.client.post('/artifacts/artifacttype/create/', data_dict)
self.assertTemplateUsed(response, 'dfirtrack_artifacts/artifact... | def test_artifacttype_create_post_invalid_template(self):
' '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
data_dict = {}
response = self.client.post('/artifacts/artifacttype/create/', data_dict)
self.assertTemplateUsed(response, 'dfirtrack_artifacts/artifact... |
41a42085b5c96273ceb58ea08cc853700d39008ecea30c60c7f1c89ab04f5fe9 | def test_artifacttype_update_not_logged_in(self):
' test update view '
artifacttype_1 = Artifacttype.objects.get(artifacttype_name='artifacttype_1')
destination = ('/login/?next=' + urllib.parse.quote((('/artifacts/artifacttype/update/' + str(artifacttype_1.artifacttype_id)) + '/'), safe=''))
response =... | test update view | dfirtrack_artifacts/tests/artifacttype/test_artifacttype_views.py | test_artifacttype_update_not_logged_in | FabFaeb/dfirtrack | 1 | python | def test_artifacttype_update_not_logged_in(self):
' '
artifacttype_1 = Artifacttype.objects.get(artifacttype_name='artifacttype_1')
destination = ('/login/?next=' + urllib.parse.quote((('/artifacts/artifacttype/update/' + str(artifacttype_1.artifacttype_id)) + '/'), safe=))
response = self.client.get((... | def test_artifacttype_update_not_logged_in(self):
' '
artifacttype_1 = Artifacttype.objects.get(artifacttype_name='artifacttype_1')
destination = ('/login/?next=' + urllib.parse.quote((('/artifacts/artifacttype/update/' + str(artifacttype_1.artifacttype_id)) + '/'), safe=))
response = self.client.get((... |
197dfbcdfa76a55db5f16796825190def63595cadd86a0e66aacca1faef291f0 | def test_artifacttype_update_logged_in(self):
' test update view '
artifacttype_1 = Artifacttype.objects.get(artifacttype_name='artifacttype_1')
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
response = self.client.get((('/artifacts/artifacttype/update/' + str(artif... | test update view | dfirtrack_artifacts/tests/artifacttype/test_artifacttype_views.py | test_artifacttype_update_logged_in | FabFaeb/dfirtrack | 1 | python | def test_artifacttype_update_logged_in(self):
' '
artifacttype_1 = Artifacttype.objects.get(artifacttype_name='artifacttype_1')
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
response = self.client.get((('/artifacts/artifacttype/update/' + str(artifacttype_1.artifa... | def test_artifacttype_update_logged_in(self):
' '
artifacttype_1 = Artifacttype.objects.get(artifacttype_name='artifacttype_1')
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
response = self.client.get((('/artifacts/artifacttype/update/' + str(artifacttype_1.artifa... |
f09ef5ba21b030447c52d1415ee0417ab2d68ed31fe3601eb2e16865e9c6bc21 | def test_artifacttype_update_template(self):
' test update view '
artifacttype_1 = Artifacttype.objects.get(artifacttype_name='artifacttype_1')
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
response = self.client.get((('/artifacts/artifacttype/update/' + str(artifa... | test update view | dfirtrack_artifacts/tests/artifacttype/test_artifacttype_views.py | test_artifacttype_update_template | FabFaeb/dfirtrack | 1 | python | def test_artifacttype_update_template(self):
' '
artifacttype_1 = Artifacttype.objects.get(artifacttype_name='artifacttype_1')
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
response = self.client.get((('/artifacts/artifacttype/update/' + str(artifacttype_1.artifac... | def test_artifacttype_update_template(self):
' '
artifacttype_1 = Artifacttype.objects.get(artifacttype_name='artifacttype_1')
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
response = self.client.get((('/artifacts/artifacttype/update/' + str(artifacttype_1.artifac... |
32ca13109ab71f04f8f8f26c7a52d0ab2b04acef3b8eeef1e46c070c1b58c77f | def test_artifacttype_update_get_user_context(self):
' test update view '
artifacttype_1 = Artifacttype.objects.get(artifacttype_name='artifacttype_1')
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
response = self.client.get((('/artifacts/artifacttype/update/' + st... | test update view | dfirtrack_artifacts/tests/artifacttype/test_artifacttype_views.py | test_artifacttype_update_get_user_context | FabFaeb/dfirtrack | 1 | python | def test_artifacttype_update_get_user_context(self):
' '
artifacttype_1 = Artifacttype.objects.get(artifacttype_name='artifacttype_1')
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
response = self.client.get((('/artifacts/artifacttype/update/' + str(artifacttype_1... | def test_artifacttype_update_get_user_context(self):
' '
artifacttype_1 = Artifacttype.objects.get(artifacttype_name='artifacttype_1')
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
response = self.client.get((('/artifacts/artifacttype/update/' + str(artifacttype_1... |
a43cb36161f98f61a74b9a6f8ccef1e33f7a8fb14e49a982b67e5577038d5e66 | def test_artifacttype_update_redirect(self):
' test update view '
artifacttype_1 = Artifacttype.objects.get(artifacttype_name='artifacttype_1')
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
destination = urllib.parse.quote((('/artifacts/artifacttype/update/' + str(... | test update view | dfirtrack_artifacts/tests/artifacttype/test_artifacttype_views.py | test_artifacttype_update_redirect | FabFaeb/dfirtrack | 1 | python | def test_artifacttype_update_redirect(self):
' '
artifacttype_1 = Artifacttype.objects.get(artifacttype_name='artifacttype_1')
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
destination = urllib.parse.quote((('/artifacts/artifacttype/update/' + str(artifacttype_1.a... | def test_artifacttype_update_redirect(self):
' '
artifacttype_1 = Artifacttype.objects.get(artifacttype_name='artifacttype_1')
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
destination = urllib.parse.quote((('/artifacts/artifacttype/update/' + str(artifacttype_1.a... |
5cbc9602f4731c4dab50a0317c24701c55127d5a4e25d0ca971e835b9adf197b | def test_artifacttype_update_post_redirect(self):
' test update view '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
artifacttype_id = Artifacttype.objects.create(artifacttype_name='artifacttype_update_post_test_1').artifacttype_id
data_dict = {'artifacttype_name':... | test update view | dfirtrack_artifacts/tests/artifacttype/test_artifacttype_views.py | test_artifacttype_update_post_redirect | FabFaeb/dfirtrack | 1 | python | def test_artifacttype_update_post_redirect(self):
' '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
artifacttype_id = Artifacttype.objects.create(artifacttype_name='artifacttype_update_post_test_1').artifacttype_id
data_dict = {'artifacttype_name': 'artifacttype_u... | def test_artifacttype_update_post_redirect(self):
' '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
artifacttype_id = Artifacttype.objects.create(artifacttype_name='artifacttype_update_post_test_1').artifacttype_id
data_dict = {'artifacttype_name': 'artifacttype_u... |
f09e1fda69752d5af34f3c1d76ffe7e3b6f7fa89192f7b81c178ef38370ef34f | def test_artifacttype_update_post_invalid_reload(self):
' test update view '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
artifacttype_id = Artifacttype.objects.get(artifacttype_name='artifacttype_1').artifacttype_id
data_dict = {}
response = self.client.post(... | test update view | dfirtrack_artifacts/tests/artifacttype/test_artifacttype_views.py | test_artifacttype_update_post_invalid_reload | FabFaeb/dfirtrack | 1 | python | def test_artifacttype_update_post_invalid_reload(self):
' '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
artifacttype_id = Artifacttype.objects.get(artifacttype_name='artifacttype_1').artifacttype_id
data_dict = {}
response = self.client.post((('/artifacts/ar... | def test_artifacttype_update_post_invalid_reload(self):
' '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
artifacttype_id = Artifacttype.objects.get(artifacttype_name='artifacttype_1').artifacttype_id
data_dict = {}
response = self.client.post((('/artifacts/ar... |
336e244bd3b54d646caca3466083ed78f2c9e0856e53ade78108b17d6b27a1bb | def test_artifacttype_update_post_invalid_template(self):
' test update view '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
artifacttype_id = Artifacttype.objects.get(artifacttype_name='artifacttype_1').artifacttype_id
data_dict = {}
response = self.client.pos... | test update view | dfirtrack_artifacts/tests/artifacttype/test_artifacttype_views.py | test_artifacttype_update_post_invalid_template | FabFaeb/dfirtrack | 1 | python | def test_artifacttype_update_post_invalid_template(self):
' '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
artifacttype_id = Artifacttype.objects.get(artifacttype_name='artifacttype_1').artifacttype_id
data_dict = {}
response = self.client.post((('/artifacts/... | def test_artifacttype_update_post_invalid_template(self):
' '
self.client.login(username='testuser_artifacttype', password='5HxLPaA1wWbphTcd2C3S')
artifacttype_id = Artifacttype.objects.get(artifacttype_name='artifacttype_1').artifacttype_id
data_dict = {}
response = self.client.post((('/artifacts/... |
e8d4aa371b8e934e2d0ccd46c1c9eb1a14fe03e00c1801b468f3530669d4d7a5 | def run_mash(seqids, output_dir):
'\n Use MASH to determine the genus of strains when the requested analysis has a genus-specific database\n :return: dictionary of MASH-calculated genera\n '
genus_dict = dict()
for seqid in seqids:
screen_file = os.path.join(output_dir, '{seqid}_screen.tab'... | Use MASH to determine the genus of strains when the requested analysis has a genus-specific database
:return: dictionary of MASH-calculated genera | automators_dev/geneseekr.py | run_mash | forestdussault/OLCRedmineAutomator | 0 | python | def run_mash(seqids, output_dir):
'\n Use MASH to determine the genus of strains when the requested analysis has a genus-specific database\n :return: dictionary of MASH-calculated genera\n '
genus_dict = dict()
for seqid in seqids:
screen_file = os.path.join(output_dir, '{seqid}_screen.tab'... | def run_mash(seqids, output_dir):
'\n Use MASH to determine the genus of strains when the requested analysis has a genus-specific database\n :return: dictionary of MASH-calculated genera\n '
genus_dict = dict()
for seqid in seqids:
screen_file = os.path.join(output_dir, '{seqid}_screen.tab'... |
fabb3836cf49bbc8526ec566ddbd2889b67e3f7187518161bf57d714a8c46f51 | def verify_fasta_files_present(seqid_list, fasta_dir):
'\n Makes sure that FASTQ files specified in seqid_list have been successfully copied/linked to directory specified\n by fastq_dir.\n :param seqid_list: List with SEQIDs.\n :param fasta_dir: Directory to which FASTA files should have been linked\n ... | Makes sure that FASTQ files specified in seqid_list have been successfully copied/linked to directory specified
by fastq_dir.
:param seqid_list: List with SEQIDs.
:param fasta_dir: Directory to which FASTA files should have been linked
:return: List of SEQIDs that did not have files associated with them. | automators_dev/geneseekr.py | verify_fasta_files_present | forestdussault/OLCRedmineAutomator | 0 | python | def verify_fasta_files_present(seqid_list, fasta_dir):
'\n Makes sure that FASTQ files specified in seqid_list have been successfully copied/linked to directory specified\n by fastq_dir.\n :param seqid_list: List with SEQIDs.\n :param fasta_dir: Directory to which FASTA files should have been linked\n ... | def verify_fasta_files_present(seqid_list, fasta_dir):
'\n Makes sure that FASTQ files specified in seqid_list have been successfully copied/linked to directory specified\n by fastq_dir.\n :param seqid_list: List with SEQIDs.\n :param fasta_dir: Directory to which FASTA files should have been linked\n ... |
b15b69790c26b3602d85212b1339674b6947a989d98f5b1b6dcd0ab689f4ae22 | def make_executable(path):
'\n Takes a shell script and makes it executable (chmod +x)\n :param path: path to shell script\n '
mode = os.stat(path).st_mode
mode |= ((mode & 292) >> 2)
os.chmod(path, mode) | Takes a shell script and makes it executable (chmod +x)
:param path: path to shell script | automators_dev/geneseekr.py | make_executable | forestdussault/OLCRedmineAutomator | 0 | python | def make_executable(path):
'\n Takes a shell script and makes it executable (chmod +x)\n :param path: path to shell script\n '
mode = os.stat(path).st_mode
mode |= ((mode & 292) >> 2)
os.chmod(path, mode) | def make_executable(path):
'\n Takes a shell script and makes it executable (chmod +x)\n :param path: path to shell script\n '
mode = os.stat(path).st_mode
mode |= ((mode & 292) >> 2)
os.chmod(path, mode)<|docstring|>Takes a shell script and makes it executable (chmod +x)
:param path: path to s... |
605408a92572375c120d313f255f5828fb95cf1d9b265b4af28bf3d8998527c2 | def zip_folder(results_path, output_dir, output_filename):
'\n Compress a folder\n :param results_path: The path of the folder to be compressed\n :param output_dir: The output directory\n :param output_filename: The output file name\n :return:\n '
output_path = os.path.join(output_dir, output_... | Compress a folder
:param results_path: The path of the folder to be compressed
:param output_dir: The output directory
:param output_filename: The output file name
:return: | automators_dev/geneseekr.py | zip_folder | forestdussault/OLCRedmineAutomator | 0 | python | def zip_folder(results_path, output_dir, output_filename):
'\n Compress a folder\n :param results_path: The path of the folder to be compressed\n :param output_dir: The output directory\n :param output_filename: The output file name\n :return:\n '
output_path = os.path.join(output_dir, output_... | def zip_folder(results_path, output_dir, output_filename):
'\n Compress a folder\n :param results_path: The path of the folder to be compressed\n :param output_dir: The output directory\n :param output_filename: The output file name\n :return:\n '
output_path = os.path.join(output_dir, output_... |
dc20e953fd38ba5d72c18c2053e6e1130821c2cfc72491679eb04f658be04148 | def __init__(self, protobuf_map_path: str, world_to_ecef: np.ndarray):
'\n Interface to the raw protobuf map file with the following features:\n - access to element using ID is O(1);\n - access to coordinates in world ref system for a set of elements is O(1) after first access (lru cache)\n ... | Interface to the raw protobuf map file with the following features:
- access to element using ID is O(1);
- access to coordinates in world ref system for a set of elements is O(1) after first access (lru cache)
- object support iteration using __getitem__ protocol
Args:
protobuf_map_path (str): path to the protobu... | l5kit/l5kit/data/map_api.py | __init__ | ronamit/l5kit | 1 | python | def __init__(self, protobuf_map_path: str, world_to_ecef: np.ndarray):
'\n Interface to the raw protobuf map file with the following features:\n - access to element using ID is O(1);\n - access to coordinates in world ref system for a set of elements is O(1) after first access (lru cache)\n ... | def __init__(self, protobuf_map_path: str, world_to_ecef: np.ndarray):
'\n Interface to the raw protobuf map file with the following features:\n - access to element using ID is O(1);\n - access to coordinates in world ref system for a set of elements is O(1) after first access (lru cache)\n ... |
c90528fc5e3bdf6315951f11c34a22bad14efcb4974a6caf2e91d414b52529d0 | @staticmethod
def from_cfg(data_manager: DataManager, cfg: dict) -> 'MapAPI':
'Build a MapAPI object starting from a config file and a data manager\n\n :param data_manager: a data manager object ot resolve paths\n :param cfg: the config dict\n :return: a MapAPI object\n '
raster_cfg ... | Build a MapAPI object starting from a config file and a data manager
:param data_manager: a data manager object ot resolve paths
:param cfg: the config dict
:return: a MapAPI object | l5kit/l5kit/data/map_api.py | from_cfg | ronamit/l5kit | 1 | python | @staticmethod
def from_cfg(data_manager: DataManager, cfg: dict) -> 'MapAPI':
'Build a MapAPI object starting from a config file and a data manager\n\n :param data_manager: a data manager object ot resolve paths\n :param cfg: the config dict\n :return: a MapAPI object\n '
raster_cfg ... | @staticmethod
def from_cfg(data_manager: DataManager, cfg: dict) -> 'MapAPI':
'Build a MapAPI object starting from a config file and a data manager\n\n :param data_manager: a data manager object ot resolve paths\n :param cfg: the config dict\n :return: a MapAPI object\n '
raster_cfg ... |
6cd3c9fcb934ece77f7c57f03319d768f96ff89590ac7499978d1a7ac16ed558 | @staticmethod
@no_type_check
def id_as_str(element_id: GlobalId) -> str:
'\n Get the element id as a string.\n Elements ids are stored as a variable len sequence of bytes in the protobuf\n\n Args:\n element_id (GlobalId): the GlobalId in the protobuf\n\n Returns:\n ... | Get the element id as a string.
Elements ids are stored as a variable len sequence of bytes in the protobuf
Args:
element_id (GlobalId): the GlobalId in the protobuf
Returns:
str: the id as a str | l5kit/l5kit/data/map_api.py | id_as_str | ronamit/l5kit | 1 | python | @staticmethod
@no_type_check
def id_as_str(element_id: GlobalId) -> str:
'\n Get the element id as a string.\n Elements ids are stored as a variable len sequence of bytes in the protobuf\n\n Args:\n element_id (GlobalId): the GlobalId in the protobuf\n\n Returns:\n ... | @staticmethod
@no_type_check
def id_as_str(element_id: GlobalId) -> str:
'\n Get the element id as a string.\n Elements ids are stored as a variable len sequence of bytes in the protobuf\n\n Args:\n element_id (GlobalId): the GlobalId in the protobuf\n\n Returns:\n ... |
bcf76b8d1a8106d55e0ed495ae1134fd4d324a6cd8de9a7dbd785e59bfb23dfd | @staticmethod
def _undo_e7(value: float) -> float:
'\n Latitude and longitude are stored as value*1e7 in the protobuf for efficiency and guaranteed accuracy.\n Convert them back to float.\n\n Args:\n value (float): the scaled value\n\n Returns:\n float: the unscaled... | Latitude and longitude are stored as value*1e7 in the protobuf for efficiency and guaranteed accuracy.
Convert them back to float.
Args:
value (float): the scaled value
Returns:
float: the unscaled value | l5kit/l5kit/data/map_api.py | _undo_e7 | ronamit/l5kit | 1 | python | @staticmethod
def _undo_e7(value: float) -> float:
'\n Latitude and longitude are stored as value*1e7 in the protobuf for efficiency and guaranteed accuracy.\n Convert them back to float.\n\n Args:\n value (float): the scaled value\n\n Returns:\n float: the unscaled... | @staticmethod
def _undo_e7(value: float) -> float:
'\n Latitude and longitude are stored as value*1e7 in the protobuf for efficiency and guaranteed accuracy.\n Convert them back to float.\n\n Args:\n value (float): the scaled value\n\n Returns:\n float: the unscaled... |
ae29d551314c690243ebb1fc642d6d9eb3ab5ac97923036b6149882043861365 | @no_type_check
def unpack_deltas_cm(self, dx: Sequence[int], dy: Sequence[int], dz: Sequence[int], frame: GeoFrame) -> np.ndarray:
'\n Get coords in world reference system (local ENU->ECEF->world).\n See the protobuf annotations for additional information about how coordinates are stored\n\n Ar... | Get coords in world reference system (local ENU->ECEF->world).
See the protobuf annotations for additional information about how coordinates are stored
Args:
dx (Sequence[int]): X displacement in centimeters in local ENU
dy (Sequence[int]): Y displacement in centimeters in local ENU
dz (Sequence[int]): Z d... | l5kit/l5kit/data/map_api.py | unpack_deltas_cm | ronamit/l5kit | 1 | python | @no_type_check
def unpack_deltas_cm(self, dx: Sequence[int], dy: Sequence[int], dz: Sequence[int], frame: GeoFrame) -> np.ndarray:
'\n Get coords in world reference system (local ENU->ECEF->world).\n See the protobuf annotations for additional information about how coordinates are stored\n\n Ar... | @no_type_check
def unpack_deltas_cm(self, dx: Sequence[int], dy: Sequence[int], dz: Sequence[int], frame: GeoFrame) -> np.ndarray:
'\n Get coords in world reference system (local ENU->ECEF->world).\n See the protobuf annotations for additional information about how coordinates are stored\n\n Ar... |
d59eef78ae5d05ab08e636376fac1ecc499549b46a2abd899b232c7399aa1d74 | @staticmethod
@no_type_check
def is_lane(element: MapElement) -> bool:
'\n Check whether an element is a valid lane\n\n Args:\n element (MapElement): a proto element\n\n Returns:\n bool: True if the element is a valid lane\n '
return bool(element.element.HasFiel... | Check whether an element is a valid lane
Args:
element (MapElement): a proto element
Returns:
bool: True if the element is a valid lane | l5kit/l5kit/data/map_api.py | is_lane | ronamit/l5kit | 1 | python | @staticmethod
@no_type_check
def is_lane(element: MapElement) -> bool:
'\n Check whether an element is a valid lane\n\n Args:\n element (MapElement): a proto element\n\n Returns:\n bool: True if the element is a valid lane\n '
return bool(element.element.HasFiel... | @staticmethod
@no_type_check
def is_lane(element: MapElement) -> bool:
'\n Check whether an element is a valid lane\n\n Args:\n element (MapElement): a proto element\n\n Returns:\n bool: True if the element is a valid lane\n '
return bool(element.element.HasFiel... |
f77d139d92f5f9bd96e7b381716bc6b064a426e2fdddbc5ddc1b3a30aef99065 | @lru_cache(maxsize=CACHE_SIZE)
def get_lane_coords(self, element_id: str) -> dict:
'\n Get XYZ coordinates in world ref system for a lane given its id\n lru_cached for O(1) access\n\n Args:\n element_id (str): lane element id\n\n Returns:\n dict: a dict with the two... | Get XYZ coordinates in world ref system for a lane given its id
lru_cached for O(1) access
Args:
element_id (str): lane element id
Returns:
dict: a dict with the two boundaries coordinates as (Nx3) XYZ arrays | l5kit/l5kit/data/map_api.py | get_lane_coords | ronamit/l5kit | 1 | python | @lru_cache(maxsize=CACHE_SIZE)
def get_lane_coords(self, element_id: str) -> dict:
'\n Get XYZ coordinates in world ref system for a lane given its id\n lru_cached for O(1) access\n\n Args:\n element_id (str): lane element id\n\n Returns:\n dict: a dict with the two... | @lru_cache(maxsize=CACHE_SIZE)
def get_lane_coords(self, element_id: str) -> dict:
'\n Get XYZ coordinates in world ref system for a lane given its id\n lru_cached for O(1) access\n\n Args:\n element_id (str): lane element id\n\n Returns:\n dict: a dict with the two... |
26d4bf11717bef333b360404acb6bac8924e73f876a68f719c82b9041e94358d | @staticmethod
def interpolate(xyz: np.ndarray, step: float, method: InterpolationMethod) -> np.ndarray:
'\n Interpolate points based on cumulative distances from the first one. Two modes are available:\n INTER_METER: interpolate using step as a meter value over cumulative distances (variable len resul... | Interpolate points based on cumulative distances from the first one. Two modes are available:
INTER_METER: interpolate using step as a meter value over cumulative distances (variable len result)
INTER_ENSURE_LEN: interpolate using a variable step such that we always get step values
Args:
xyz (np.ndarray): XYZ coord... | l5kit/l5kit/data/map_api.py | interpolate | ronamit/l5kit | 1 | python | @staticmethod
def interpolate(xyz: np.ndarray, step: float, method: InterpolationMethod) -> np.ndarray:
'\n Interpolate points based on cumulative distances from the first one. Two modes are available:\n INTER_METER: interpolate using step as a meter value over cumulative distances (variable len resul... | @staticmethod
def interpolate(xyz: np.ndarray, step: float, method: InterpolationMethod) -> np.ndarray:
'\n Interpolate points based on cumulative distances from the first one. Two modes are available:\n INTER_METER: interpolate using step as a meter value over cumulative distances (variable len resul... |
ae1eebabd7a6761fa75db5b8f73d77adfdae9c33292abdf0b8084c17f26a224e | @lru_cache(maxsize=CACHE_SIZE)
def get_lane_as_interpolation(self, element_id: str, step: float, method: InterpolationMethod) -> dict:
'\n Perform an interpolation of the left and right lanes and compute the midlane.\n See interpolate for details about the different interpolation methods\n\n Ar... | Perform an interpolation of the left and right lanes and compute the midlane.
See interpolate for details about the different interpolation methods
Args:
element_id (str): lane id
step (float): step param for the method
method (InterpolationMethod): one of the accepted methods
Returns:
dict: same as `... | l5kit/l5kit/data/map_api.py | get_lane_as_interpolation | ronamit/l5kit | 1 | python | @lru_cache(maxsize=CACHE_SIZE)
def get_lane_as_interpolation(self, element_id: str, step: float, method: InterpolationMethod) -> dict:
'\n Perform an interpolation of the left and right lanes and compute the midlane.\n See interpolate for details about the different interpolation methods\n\n Ar... | @lru_cache(maxsize=CACHE_SIZE)
def get_lane_as_interpolation(self, element_id: str, step: float, method: InterpolationMethod) -> dict:
'\n Perform an interpolation of the left and right lanes and compute the midlane.\n See interpolate for details about the different interpolation methods\n\n Ar... |
928556c086b752d6d071bcee2c4418b9952b0f68d8ec7636413a43278a959dee | @staticmethod
@no_type_check
def is_crosswalk(element: MapElement) -> bool:
'\n Check whether an element is a valid crosswalk\n\n Args:\n element (MapElement): a proto element\n\n Returns:\n bool: True if the element is a valid crosswalk\n '
if (not element.elem... | Check whether an element is a valid crosswalk
Args:
element (MapElement): a proto element
Returns:
bool: True if the element is a valid crosswalk | l5kit/l5kit/data/map_api.py | is_crosswalk | ronamit/l5kit | 1 | python | @staticmethod
@no_type_check
def is_crosswalk(element: MapElement) -> bool:
'\n Check whether an element is a valid crosswalk\n\n Args:\n element (MapElement): a proto element\n\n Returns:\n bool: True if the element is a valid crosswalk\n '
if (not element.elem... | @staticmethod
@no_type_check
def is_crosswalk(element: MapElement) -> bool:
'\n Check whether an element is a valid crosswalk\n\n Args:\n element (MapElement): a proto element\n\n Returns:\n bool: True if the element is a valid crosswalk\n '
if (not element.elem... |
9be309a750594552ef4bba6298d29aebe92c994ff66c2199e4ed8ec6ea7e1f3a | @lru_cache(maxsize=CACHE_SIZE)
def get_crosswalk_coords(self, element_id: str) -> dict:
'\n Get XYZ coordinates in world ref system for a crosswalk given its id\n lru_cached for O(1) access\n\n Args:\n element_id (str): crosswalk element id\n\n Returns:\n dict: a di... | Get XYZ coordinates in world ref system for a crosswalk given its id
lru_cached for O(1) access
Args:
element_id (str): crosswalk element id
Returns:
dict: a dict with the polygon coordinates as an (Nx3) XYZ array | l5kit/l5kit/data/map_api.py | get_crosswalk_coords | ronamit/l5kit | 1 | python | @lru_cache(maxsize=CACHE_SIZE)
def get_crosswalk_coords(self, element_id: str) -> dict:
'\n Get XYZ coordinates in world ref system for a crosswalk given its id\n lru_cached for O(1) access\n\n Args:\n element_id (str): crosswalk element id\n\n Returns:\n dict: a di... | @lru_cache(maxsize=CACHE_SIZE)
def get_crosswalk_coords(self, element_id: str) -> dict:
'\n Get XYZ coordinates in world ref system for a crosswalk given its id\n lru_cached for O(1) access\n\n Args:\n element_id (str): crosswalk element id\n\n Returns:\n dict: a di... |
5c29685644e9ef62340aeb2951a3b7fb85f4db25af5ed605dcbf84f94180a0d5 | def is_traffic_light(self, element_id: str) -> bool:
'\n Check if the element is a traffic light\n Args:\n element_id (str): the id (utf-8 encode) of the element\n\n Returns:\n True if the element is a traffic light\n '
element = self[element_id]
if (not ele... | Check if the element is a traffic light
Args:
element_id (str): the id (utf-8 encode) of the element
Returns:
True if the element is a traffic light | l5kit/l5kit/data/map_api.py | is_traffic_light | ronamit/l5kit | 1 | python | def is_traffic_light(self, element_id: str) -> bool:
'\n Check if the element is a traffic light\n Args:\n element_id (str): the id (utf-8 encode) of the element\n\n Returns:\n True if the element is a traffic light\n '
element = self[element_id]
if (not ele... | def is_traffic_light(self, element_id: str) -> bool:
'\n Check if the element is a traffic light\n Args:\n element_id (str): the id (utf-8 encode) of the element\n\n Returns:\n True if the element is a traffic light\n '
element = self[element_id]
if (not ele... |
a0a06cb21830c30a6abd16ea395c7ec27e7268954ed7ce1ea59f97954edd6faf | @lru_cache(maxsize=CACHE_SIZE)
def is_traffic_face(self, element_id: str) -> bool:
'\n Check if the element is a traffic light face (of any color)\n\n Args:\n element_id (str): the id (utf-8 encode) of the element\n Returns:\n True if the element is a traffic light face, F... | Check if the element is a traffic light face (of any color)
Args:
element_id (str): the id (utf-8 encode) of the element
Returns:
True if the element is a traffic light face, False otherwise | l5kit/l5kit/data/map_api.py | is_traffic_face | ronamit/l5kit | 1 | python | @lru_cache(maxsize=CACHE_SIZE)
def is_traffic_face(self, element_id: str) -> bool:
'\n Check if the element is a traffic light face (of any color)\n\n Args:\n element_id (str): the id (utf-8 encode) of the element\n Returns:\n True if the element is a traffic light face, F... | @lru_cache(maxsize=CACHE_SIZE)
def is_traffic_face(self, element_id: str) -> bool:
'\n Check if the element is a traffic light face (of any color)\n\n Args:\n element_id (str): the id (utf-8 encode) of the element\n Returns:\n True if the element is a traffic light face, F... |
45c0ef3cade29803062f04ddeb2f6f87155904c142bc5dbb233ad0d6a554cbc7 | def is_traffic_face_color(self, element_id: str, color: str) -> bool:
'\n Check if the element is a traffic light face of the given color\n\n Args:\n element_id (str): the id (utf-8 encode) of the element\n color (str): the color to check\n Returns:\n True if th... | Check if the element is a traffic light face of the given color
Args:
element_id (str): the id (utf-8 encode) of the element
color (str): the color to check
Returns:
True if the element is a traffic light face with the given color | l5kit/l5kit/data/map_api.py | is_traffic_face_color | ronamit/l5kit | 1 | python | def is_traffic_face_color(self, element_id: str, color: str) -> bool:
'\n Check if the element is a traffic light face of the given color\n\n Args:\n element_id (str): the id (utf-8 encode) of the element\n color (str): the color to check\n Returns:\n True if th... | def is_traffic_face_color(self, element_id: str, color: str) -> bool:
'\n Check if the element is a traffic light face of the given color\n\n Args:\n element_id (str): the id (utf-8 encode) of the element\n color (str): the color to check\n Returns:\n True if th... |
b70049f7e9bc78ad6bbd861f28586bc689e9664e746fbf9e6fc8c46c87d14cbb | @lru_cache(maxsize=CACHE_SIZE)
def get_color_for_face(self, face_id: str) -> str:
'\n Utility function. It calls `is_traffic_face_color` for a set of colors until it gets an answer.\n If no color is found, then `face_id` is not the id of a traffic light face (and we raise ValueError).\n\n Args:... | Utility function. It calls `is_traffic_face_color` for a set of colors until it gets an answer.
If no color is found, then `face_id` is not the id of a traffic light face (and we raise ValueError).
Args:
face_id (str): the element id
Returns:
str: the color as string for this traffic face | l5kit/l5kit/data/map_api.py | get_color_for_face | ronamit/l5kit | 1 | python | @lru_cache(maxsize=CACHE_SIZE)
def get_color_for_face(self, face_id: str) -> str:
'\n Utility function. It calls `is_traffic_face_color` for a set of colors until it gets an answer.\n If no color is found, then `face_id` is not the id of a traffic light face (and we raise ValueError).\n\n Args:... | @lru_cache(maxsize=CACHE_SIZE)
def get_color_for_face(self, face_id: str) -> str:
'\n Utility function. It calls `is_traffic_face_color` for a set of colors until it gets an answer.\n If no color is found, then `face_id` is not the id of a traffic light face (and we raise ValueError).\n\n Args:... |
c3583171bb425013a3459258af8ed3a34ce248071586f4bb0ff8ebd28e6699e5 | def get_tl_feature_for_lane(self, lane_id: str, active_tl_face_to_color: dict) -> int:
' Get traffic light feature for a lane given its active tl faces and a constant priority map.\n '
tl_color_to_priority_idx = {'unknown': 0, 'green': 1, 'yellow': 2, 'red': 3, 'none': 4}
lane_tces = self.get_lane_tr... | Get traffic light feature for a lane given its active tl faces and a constant priority map. | l5kit/l5kit/data/map_api.py | get_tl_feature_for_lane | ronamit/l5kit | 1 | python | def get_tl_feature_for_lane(self, lane_id: str, active_tl_face_to_color: dict) -> int:
' \n '
tl_color_to_priority_idx = {'unknown': 0, 'green': 1, 'yellow': 2, 'red': 3, 'none': 4}
lane_tces = self.get_lane_traffic_control_ids(lane_id)
lane_tls = [tce for tce in lane_tces if self.is_traffic_ligh... | def get_tl_feature_for_lane(self, lane_id: str, active_tl_face_to_color: dict) -> int:
' \n '
tl_color_to_priority_idx = {'unknown': 0, 'green': 1, 'yellow': 2, 'red': 3, 'none': 4}
lane_tces = self.get_lane_traffic_control_ids(lane_id)
lane_tls = [tce for tce in lane_tces if self.is_traffic_ligh... |
11c14799c02a9b049fedbf675f6194b05f7b61389c4a36bb860aa4cf9e361b1e | def get_bounds(self) -> dict:
'\n For each elements of interest returns bounds [[min_x, min_y],[max_x, max_y]] and proto ids\n Coords are computed by the MapAPI and, as such, are in the world ref system.\n\n Returns:\n dict: keys are classes of elements, values are dict with `bounds`... | For each elements of interest returns bounds [[min_x, min_y],[max_x, max_y]] and proto ids
Coords are computed by the MapAPI and, as such, are in the world ref system.
Returns:
dict: keys are classes of elements, values are dict with `bounds` and `ids` keys | l5kit/l5kit/data/map_api.py | get_bounds | ronamit/l5kit | 1 | python | def get_bounds(self) -> dict:
'\n For each elements of interest returns bounds [[min_x, min_y],[max_x, max_y]] and proto ids\n Coords are computed by the MapAPI and, as such, are in the world ref system.\n\n Returns:\n dict: keys are classes of elements, values are dict with `bounds`... | def get_bounds(self) -> dict:
'\n For each elements of interest returns bounds [[min_x, min_y],[max_x, max_y]] and proto ids\n Coords are computed by the MapAPI and, as such, are in the world ref system.\n\n Returns:\n dict: keys are classes of elements, values are dict with `bounds`... |
b7f41ac407f5fa37c88412ea9507b56426a84029c98ca3790c868cec884124ec | def __init__(self):
'The constructor'
self._set_fields()
self._module = AnsibleModule(argument_spec=self._fields, supports_check_mode=True) | The constructor | technologies/servicenow/library/snow_create_ticket.py | __init__ | agold-rh/ansible-programming-howto | 0 | python | def __init__(self):
self._set_fields()
self._module = AnsibleModule(argument_spec=self._fields, supports_check_mode=True) | def __init__(self):
self._set_fields()
self._module = AnsibleModule(argument_spec=self._fields, supports_check_mode=True)<|docstring|>The constructor<|endoftext|> |
45091651b6eece997b946357d986dda758be64ccb2b935cdd671ee58220bbb42 | def _set_fields(self):
'Configure module input'
self._fields = {'short_description': {'required': True, 'type': 'str'}, 'assignment_group': {'required': True, 'type': 'str'}, 'remediation': {'required': True, 'type': 'str'}, 'serviceName': {'required': True, 'type': 'str'}, 'server': {'required': True, 'type': ... | Configure module input | technologies/servicenow/library/snow_create_ticket.py | _set_fields | agold-rh/ansible-programming-howto | 0 | python | def _set_fields(self):
self._fields = {'short_description': {'required': True, 'type': 'str'}, 'assignment_group': {'required': True, 'type': 'str'}, 'remediation': {'required': True, 'type': 'str'}, 'serviceName': {'required': True, 'type': 'str'}, 'server': {'required': True, 'type': 'str'}, 'host': {'requir... | def _set_fields(self):
self._fields = {'short_description': {'required': True, 'type': 'str'}, 'assignment_group': {'required': True, 'type': 'str'}, 'remediation': {'required': True, 'type': 'str'}, 'serviceName': {'required': True, 'type': 'str'}, 'server': {'required': True, 'type': 'str'}, 'host': {'requir... |
65a480fcde19f130d140aa75653dff9ce12a8a07f3cf43c5b7854e61390c1bbd | def work(self):
'Main application logic'
short_description = self._module.params['short_description']
assignment_group = self._module.params['assignment_group']
remediation = self._module.params['remediation']
serviceName = self._module.params['serviceName']
server = self._module.params['server'... | Main application logic | technologies/servicenow/library/snow_create_ticket.py | work | agold-rh/ansible-programming-howto | 0 | python | def work(self):
short_description = self._module.params['short_description']
assignment_group = self._module.params['assignment_group']
remediation = self._module.params['remediation']
serviceName = self._module.params['serviceName']
server = self._module.params['server']
host = self._modul... | def work(self):
short_description = self._module.params['short_description']
assignment_group = self._module.params['assignment_group']
remediation = self._module.params['remediation']
serviceName = self._module.params['serviceName']
server = self._module.params['server']
host = self._modul... |
092a7e5817b5c7ba03413c5d5ae3ec676375c7b72af0b32e20d38cd022c39553 | def run(self):
'Application entry point'
is_changed = False
retval = {'notice': 'check_mode so no records created'}
if (not self._module.check_mode):
retval = self.work()
is_changed = True
self._module.exit_json(changed=is_changed, meta=retval) | Application entry point | technologies/servicenow/library/snow_create_ticket.py | run | agold-rh/ansible-programming-howto | 0 | python | def run(self):
is_changed = False
retval = {'notice': 'check_mode so no records created'}
if (not self._module.check_mode):
retval = self.work()
is_changed = True
self._module.exit_json(changed=is_changed, meta=retval) | def run(self):
is_changed = False
retval = {'notice': 'check_mode so no records created'}
if (not self._module.check_mode):
retval = self.work()
is_changed = True
self._module.exit_json(changed=is_changed, meta=retval)<|docstring|>Application entry point<|endoftext|> |
aef0bc164a7a56d6ab528b856633c0991ebffbbcede45dd824a0233d555c1700 | @pytest.mark.usefixtures('os', 'scheduler', 'instance')
def test_additional_sg_and_ssh_from(region, custom_security_group, pcluster_config_reader, clusters_factory):
'\n Test when additional_sg ssh_from are provided in the config file\n\n The additional security group should be added to the head and compute n... | Test when additional_sg ssh_from are provided in the config file
The additional security group should be added to the head and compute nodes. The | tests/integration-tests/tests/networking/test_security_groups.py | test_additional_sg_and_ssh_from | mrgum/aws-parallelcluster | 279 | python | @pytest.mark.usefixtures('os', 'scheduler', 'instance')
def test_additional_sg_and_ssh_from(region, custom_security_group, pcluster_config_reader, clusters_factory):
'\n Test when additional_sg ssh_from are provided in the config file\n\n The additional security group should be added to the head and compute n... | @pytest.mark.usefixtures('os', 'scheduler', 'instance')
def test_additional_sg_and_ssh_from(region, custom_security_group, pcluster_config_reader, clusters_factory):
'\n Test when additional_sg ssh_from are provided in the config file\n\n The additional security group should be added to the head and compute n... |
a37f7a742f665b76762ead6077bc7d392cdfb7ec7bb8a5d7a34636e26540869e | @pytest.mark.usefixtures('os', 'instance')
def test_overwrite_sg(region, scheduler, custom_security_group, pcluster_config_reader, clusters_factory):
'Test vpc_security_group_id overwrites pcluster default sg on head and compute nodes, efs, fsx'
custom_security_group_id = custom_security_group.cfn_resources['Se... | Test vpc_security_group_id overwrites pcluster default sg on head and compute nodes, efs, fsx | tests/integration-tests/tests/networking/test_security_groups.py | test_overwrite_sg | mrgum/aws-parallelcluster | 279 | python | @pytest.mark.usefixtures('os', 'instance')
def test_overwrite_sg(region, scheduler, custom_security_group, pcluster_config_reader, clusters_factory):
custom_security_group_id = custom_security_group.cfn_resources['SecurityGroupResource']
cluster_config = pcluster_config_reader(vpc_security_group_id=custom_... | @pytest.mark.usefixtures('os', 'instance')
def test_overwrite_sg(region, scheduler, custom_security_group, pcluster_config_reader, clusters_factory):
custom_security_group_id = custom_security_group.cfn_resources['SecurityGroupResource']
cluster_config = pcluster_config_reader(vpc_security_group_id=custom_... |
4942d8626560a68f943a930eb9c64f4bf3656a7aef3552b8d54aa32dceb69dd7 | def parse_args():
' Parsed command line. '
parser = argparse.ArgumentParser(description='Find running files.')
parser.add_argument('pattern', nargs='?', help='Pattern of program name to terminate.')
parser.add_argument('--test', help='Run tests', action='store_true')
args = parser.parse_args()
i... | Parsed command line. | source/blockchain_backup/config/killmatch.py | parse_args | denova-com/blockchain-backup | 0 | python | def parse_args():
' '
parser = argparse.ArgumentParser(description='Find running files.')
parser.add_argument('pattern', nargs='?', help='Pattern of program name to terminate.')
parser.add_argument('--test', help='Run tests', action='store_true')
args = parser.parse_args()
if (len(args.pattern)... | def parse_args():
' '
parser = argparse.ArgumentParser(description='Find running files.')
parser.add_argument('pattern', nargs='?', help='Pattern of program name to terminate.')
parser.add_argument('--test', help='Run tests', action='store_true')
args = parser.parse_args()
if (len(args.pattern)... |
4e2074c74cebb9632155abbf4aada0bcba472d4d7007cbdc9156615fe874a69a | def make_vector(wordQuery, vocab_all):
'\n\n :param wordQuery:\n :param vocab_all:\n :return:\n '
clean_query = w3.prepro_base(wordQuery)
token_query = clean_query.split()
vector = ([0] * len(vocab_all))
for word in token_query:
if (word in vocab_all):
vector[vocab_al... | :param wordQuery:
:param vocab_all:
:return: | _scripts/w6.py | make_vector | dandyarir/SearchEngine | 0 | python | def make_vector(wordQuery, vocab_all):
'\n\n :param wordQuery:\n :param vocab_all:\n :return:\n '
clean_query = w3.prepro_base(wordQuery)
token_query = clean_query.split()
vector = ([0] * len(vocab_all))
for word in token_query:
if (word in vocab_all):
vector[vocab_al... | def make_vector(wordQuery, vocab_all):
'\n\n :param wordQuery:\n :param vocab_all:\n :return:\n '
clean_query = w3.prepro_base(wordQuery)
token_query = clean_query.split()
vector = ([0] * len(vocab_all))
for word in token_query:
if (word in vocab_all):
vector[vocab_al... |
451f3fa79d9a565d82e7b3d87047f0ba2c37557aa94fba5cd4032f99c39377f6 | def get_job_content(remote_files, operator, biz_cc_id):
'\n 根据ip、文件路径获取远程服务器的以base64编码的文件内容\n @param remote_files: 文件集合 [{"file_path":"", "ip":"只支持单个ip", "job_account":""}]\n @param operator: 操作人员\n @param biz_cc_id: 业务id\n @return: {\n "success": [\n {"file_name": "... | 根据ip、文件路径获取远程服务器的以base64编码的文件内容
@param remote_files: 文件集合 [{"file_path":"", "ip":"只支持单个ip", "job_account":""}]
@param operator: 操作人员
@param biz_cc_id: 业务id
@return: {
"success": [
{"file_name": "file_name", "content": "content", "ip": "1.1.1.2"}
],
"failure": [
... | pipeline_plugins/components/utils/job.py | get_job_content | Chace-wang/bk-sops | 881 | python | def get_job_content(remote_files, operator, biz_cc_id):
'\n 根据ip、文件路径获取远程服务器的以base64编码的文件内容\n @param remote_files: 文件集合 [{"file_path":, "ip":"只支持单个ip", "job_account":}]\n @param operator: 操作人员\n @param biz_cc_id: 业务id\n @return: {\n "success": [\n {"file_name": "file... | def get_job_content(remote_files, operator, biz_cc_id):
'\n 根据ip、文件路径获取远程服务器的以base64编码的文件内容\n @param remote_files: 文件集合 [{"file_path":, "ip":"只支持单个ip", "job_account":}]\n @param operator: 操作人员\n @param biz_cc_id: 业务id\n @return: {\n "success": [\n {"file_name": "file... |
59b42221a15c6e509fd8fdc8d3a9969b8eeba485d9be246425411d3be8063e01 | def get_job_instance_log(job_instance_record, operator, bk_biz_id):
'\n 轮询job执行结果\n @param job_instance_record: [({"file_name": file_name, "ip": remote_file["ip"]}, job_instant_id)]\n @param operator: admin\n @param bk_biz_id: 123\n @return:\n '
client = get_client_by_user(operator)
get_jo... | 轮询job执行结果
@param job_instance_record: [({"file_name": file_name, "ip": remote_file["ip"]}, job_instant_id)]
@param operator: admin
@param bk_biz_id: 123
@return: | pipeline_plugins/components/utils/job.py | get_job_instance_log | Chace-wang/bk-sops | 881 | python | def get_job_instance_log(job_instance_record, operator, bk_biz_id):
'\n 轮询job执行结果\n @param job_instance_record: [({"file_name": file_name, "ip": remote_file["ip"]}, job_instant_id)]\n @param operator: admin\n @param bk_biz_id: 123\n @return:\n '
client = get_client_by_user(operator)
get_jo... | def get_job_instance_log(job_instance_record, operator, bk_biz_id):
'\n 轮询job执行结果\n @param job_instance_record: [({"file_name": file_name, "ip": remote_file["ip"]}, job_instant_id)]\n @param operator: admin\n @param bk_biz_id: 123\n @return:\n '
client = get_client_by_user(operator)
get_jo... |
d932bd95b1b1e6514754eeecac9fe9197ba606d07889ed4d9dfc6701dd37923a | def ExpandQName(qname, refNode=None, namespaces=None):
'\n Expand the given QName in the context of the given node,\n or in the given namespace dictionary\n '
nss = {}
if refNode:
nss = xml.dom.ext.GetAllNs(refNode)
elif namespaces:
nss = namespaces
(prefix, local) = xml.dom... | Expand the given QName in the context of the given node,
or in the given namespace dictionary | backend/src/gloader/xml/xpath/Util.py | ExpandQName | ikaier/gini5 | 11 | python | def ExpandQName(qname, refNode=None, namespaces=None):
'\n Expand the given QName in the context of the given node,\n or in the given namespace dictionary\n '
nss = {}
if refNode:
nss = xml.dom.ext.GetAllNs(refNode)
elif namespaces:
nss = namespaces
(prefix, local) = xml.dom... | def ExpandQName(qname, refNode=None, namespaces=None):
'\n Expand the given QName in the context of the given node,\n or in the given namespace dictionary\n '
nss = {}
if refNode:
nss = xml.dom.ext.GetAllNs(refNode)
elif namespaces:
nss = namespaces
(prefix, local) = xml.dom... |
c9084a34b062890e4e7c8be785d9b37212ffacfbaf5034ef32e97ee1738a9d01 | def __recurseSort(test, toSort):
'Check whether any of the nodes in toSort are in the list test, and if so, sort them into the result list'
result = []
for node in test:
toSort = filter((lambda x, n=node: (x != n)), toSort)
if (node in toSort):
result.append(node)
if (nod... | Check whether any of the nodes in toSort are in the list test, and if so, sort them into the result list | backend/src/gloader/xml/xpath/Util.py | __recurseSort | ikaier/gini5 | 11 | python | def __recurseSort(test, toSort):
result = []
for node in test:
toSort = filter((lambda x, n=node: (x != n)), toSort)
if (node in toSort):
result.append(node)
if (node.nodeType == Node.ELEMENT_NODE):
attrList = node.attributes.values()
result = (re... | def __recurseSort(test, toSort):
result = []
for node in test:
toSort = filter((lambda x, n=node: (x != n)), toSort)
if (node in toSort):
result.append(node)
if (node.nodeType == Node.ELEMENT_NODE):
attrList = node.attributes.values()
result = (re... |
01ae1bd3ff27a596d95b952439b507bb412bbf2a5b31c85b0728bbe73b5e1aea | def NormalizeNode(node):
'NormalizeNode is used to prepare a DOM for XPath evaluation.\n\n 1. Convert CDATA Sections to Text Nodes.\n 2. Normalize all text nodes\n '
node = node.firstChild
while node:
if (node.nodeType == Node.CDATA_SECTION_NODE):
if (node.nextSibling and (nod... | NormalizeNode is used to prepare a DOM for XPath evaluation.
1. Convert CDATA Sections to Text Nodes.
2. Normalize all text nodes | backend/src/gloader/xml/xpath/Util.py | NormalizeNode | ikaier/gini5 | 11 | python | def NormalizeNode(node):
'NormalizeNode is used to prepare a DOM for XPath evaluation.\n\n 1. Convert CDATA Sections to Text Nodes.\n 2. Normalize all text nodes\n '
node = node.firstChild
while node:
if (node.nodeType == Node.CDATA_SECTION_NODE):
if (node.nextSibling and (nod... | def NormalizeNode(node):
'NormalizeNode is used to prepare a DOM for XPath evaluation.\n\n 1. Convert CDATA Sections to Text Nodes.\n 2. Normalize all text nodes\n '
node = node.firstChild
while node:
if (node.nodeType == Node.CDATA_SECTION_NODE):
if (node.nextSibling and (nod... |
5e91da8ed00bf37214a3a003e29554571a6891162d228486a591f4b4b880fd67 | def raw_rewards(self, obs):
'\n Return (unnormalized) reward for each frame of a single segment\n from each member of the ensemble.\n '
assert_equal(obs.shape[1:], (84, 84, 4))
n_steps = obs.shape[0]
feed_dict = {}
for rp in self.rps:
feed_dict[rp.training] = False
... | Return (unnormalized) reward for each frame of a single segment
from each member of the ensemble. | reward_predictor.py | raw_rewards | unghee/learning-from-human-preferences | 189 | python | def raw_rewards(self, obs):
'\n Return (unnormalized) reward for each frame of a single segment\n from each member of the ensemble.\n '
assert_equal(obs.shape[1:], (84, 84, 4))
n_steps = obs.shape[0]
feed_dict = {}
for rp in self.rps:
feed_dict[rp.training] = False
... | def raw_rewards(self, obs):
'\n Return (unnormalized) reward for each frame of a single segment\n from each member of the ensemble.\n '
assert_equal(obs.shape[1:], (84, 84, 4))
n_steps = obs.shape[0]
feed_dict = {}
for rp in self.rps:
feed_dict[rp.training] = False
... |
efcd0d424556ceda2b3530e354c15544b74cee1c6fb594e9666fd2a4c39c63bd | def reward(self, obs):
'\n Return (normalized) reward for each frame of a single segment.\n\n (Normalization involves normalizing the rewards from each member of the\n ensemble separately, then averaging the resulting rewards across all\n ensemble members.)\n '
assert_equal(ob... | Return (normalized) reward for each frame of a single segment.
(Normalization involves normalizing the rewards from each member of the
ensemble separately, then averaging the resulting rewards across all
ensemble members.) | reward_predictor.py | reward | unghee/learning-from-human-preferences | 189 | python | def reward(self, obs):
'\n Return (normalized) reward for each frame of a single segment.\n\n (Normalization involves normalizing the rewards from each member of the\n ensemble separately, then averaging the resulting rewards across all\n ensemble members.)\n '
assert_equal(ob... | def reward(self, obs):
'\n Return (normalized) reward for each frame of a single segment.\n\n (Normalization involves normalizing the rewards from each member of the\n ensemble separately, then averaging the resulting rewards across all\n ensemble members.)\n '
assert_equal(ob... |
027f61f7d7892ecc7a59ac2873c5b2d0266735d8a0f8adb5960a9749f90d6a9b | def preferences(self, s1s, s2s):
'\n Predict probability of human preferring one segment over another\n for each segment in the supplied batch of segment pairs.\n '
feed_dict = {}
for rp in self.rps:
feed_dict[rp.s1] = s1s
feed_dict[rp.s2] = s2s
feed_dict[rp.trai... | Predict probability of human preferring one segment over another
for each segment in the supplied batch of segment pairs. | reward_predictor.py | preferences | unghee/learning-from-human-preferences | 189 | python | def preferences(self, s1s, s2s):
'\n Predict probability of human preferring one segment over another\n for each segment in the supplied batch of segment pairs.\n '
feed_dict = {}
for rp in self.rps:
feed_dict[rp.s1] = s1s
feed_dict[rp.s2] = s2s
feed_dict[rp.trai... | def preferences(self, s1s, s2s):
'\n Predict probability of human preferring one segment over another\n for each segment in the supplied batch of segment pairs.\n '
feed_dict = {}
for rp in self.rps:
feed_dict[rp.s1] = s1s
feed_dict[rp.s2] = s2s
feed_dict[rp.trai... |
69412bf52efd0a105adf0501f47684a1bdef259ee2f591156814df1191f172f5 | def train(self, prefs_train, prefs_val, val_interval):
'\n Train all ensemble members for one epoch.\n '
print(('Training/testing with %d/%d preferences' % (len(prefs_train), len(prefs_val))))
start_steps = self.n_steps
start_time = time.time()
for (_, batch) in enumerate(batch_iter(pr... | Train all ensemble members for one epoch. | reward_predictor.py | train | unghee/learning-from-human-preferences | 189 | python | def train(self, prefs_train, prefs_val, val_interval):
'\n \n '
print(('Training/testing with %d/%d preferences' % (len(prefs_train), len(prefs_val))))
start_steps = self.n_steps
start_time = time.time()
for (_, batch) in enumerate(batch_iter(prefs_train.prefs, batch_size=32, shuffle=T... | def train(self, prefs_train, prefs_val, val_interval):
'\n \n '
print(('Training/testing with %d/%d preferences' % (len(prefs_train), len(prefs_val))))
start_steps = self.n_steps
start_time = time.time()
for (_, batch) in enumerate(batch_iter(prefs_train.prefs, batch_size=32, shuffle=T... |
bf2b0de74a675b57961fc8afccc2c347c324e7c337fc19b24011972890ff8f9d | def correct_motion_on_peaks(peaks, peak_locations, times, motion, temporal_bins, spatial_bins, direction='y', progress_bar=False):
'\n Given the output of estimate_motion(), apply inverse motion on peak location.\n\n Parameters\n ----------\n peaks: np.array\n peaks vector\n peak_locations: np... | Given the output of estimate_motion(), apply inverse motion on peak location.
Parameters
----------
peaks: np.array
peaks vector
peak_locations: np.array
peaks location vector
times: np.array
times vector of recording
motion: np.array 2D
motion.shape[0] equal temporal_bins.shape[0]
motion.shape[1] ... | spikeinterface/sortingcomponents/motion_correction.py | correct_motion_on_peaks | tfoutz99/spikeinterface | 0 | python | def correct_motion_on_peaks(peaks, peak_locations, times, motion, temporal_bins, spatial_bins, direction='y', progress_bar=False):
'\n Given the output of estimate_motion(), apply inverse motion on peak location.\n\n Parameters\n ----------\n peaks: np.array\n peaks vector\n peak_locations: np... | def correct_motion_on_peaks(peaks, peak_locations, times, motion, temporal_bins, spatial_bins, direction='y', progress_bar=False):
'\n Given the output of estimate_motion(), apply inverse motion on peak location.\n\n Parameters\n ----------\n peaks: np.array\n peaks vector\n peak_locations: np... |
af57c0112a4921c0fe747efb5c779aec6ca6c0135b4c6a81e2684c076e71c25e | def correct_motion_on_traces(traces, times, channel_locations, motion, temporal_bins, spatial_bins, direction=1):
'\n Apply inverse motion with spatial interpolation on traces.\n\n Traces can be full traces, but also waveforms snippets.\n\n Parameters\n ----------\n traces : np.array\n Trace s... | Apply inverse motion with spatial interpolation on traces.
Traces can be full traces, but also waveforms snippets.
Parameters
----------
traces : np.array
Trace snippet (num_samples, num_channels)
channel_location: np.array 2d
Channel location with shape (n, 2) or (n, 3)
motion: np.array 2D
motion.shape[0... | spikeinterface/sortingcomponents/motion_correction.py | correct_motion_on_traces | tfoutz99/spikeinterface | 0 | python | def correct_motion_on_traces(traces, times, channel_locations, motion, temporal_bins, spatial_bins, direction=1):
'\n Apply inverse motion with spatial interpolation on traces.\n\n Traces can be full traces, but also waveforms snippets.\n\n Parameters\n ----------\n traces : np.array\n Trace s... | def correct_motion_on_traces(traces, times, channel_locations, motion, temporal_bins, spatial_bins, direction=1):
'\n Apply inverse motion with spatial interpolation on traces.\n\n Traces can be full traces, but also waveforms snippets.\n\n Parameters\n ----------\n traces : np.array\n Trace s... |
167f4b669611c5d325246c9ffa7235382722647d36941500f701cc717bb2c2a4 | def channel_motions_over_time_OLD(times, channel_locations, motion, temporal_bins, spatial_bins, direction=1):
'\n Interpolate the channel motion over time given motion matrix.\n\n Parameters\n ----------\n times: np.array 1d\n Times vector\n channel_location: np.array 2d\n Channel loca... | Interpolate the channel motion over time given motion matrix.
Parameters
----------
times: np.array 1d
Times vector
channel_location: np.array 2d
Channel location with shape (n, 2) or (n, 3)
motion: np.array 2D
motion.shape[0] equal temporal_bins.shape[0]
motion.shape[1] equal 1 when "rigid" motion
... | spikeinterface/sortingcomponents/motion_correction.py | channel_motions_over_time_OLD | tfoutz99/spikeinterface | 0 | python | def channel_motions_over_time_OLD(times, channel_locations, motion, temporal_bins, spatial_bins, direction=1):
'\n Interpolate the channel motion over time given motion matrix.\n\n Parameters\n ----------\n times: np.array 1d\n Times vector\n channel_location: np.array 2d\n Channel loca... | def channel_motions_over_time_OLD(times, channel_locations, motion, temporal_bins, spatial_bins, direction=1):
'\n Interpolate the channel motion over time given motion matrix.\n\n Parameters\n ----------\n times: np.array 1d\n Times vector\n channel_location: np.array 2d\n Channel loca... |
9cce05252e3f54af17465c0246accbeb0fa007bb45813e2ea6cd29296f619976 | def correct_motion_on_traces_OLD(traces, times, channel_locations, motion, temporal_bins, spatial_bins, direction=1):
'\n Apply inverse motion with spatial interpolation on traces.\n\n Traces can be full traces, but also waveforms snippets.\n\n Parameters\n ----------\n traces : np.array\n Tra... | Apply inverse motion with spatial interpolation on traces.
Traces can be full traces, but also waveforms snippets.
Parameters
----------
traces : np.array
Trace snippet (num_samples, num_channels)
channel_location: np.array 2d
Channel location with shape (n, 2) or (n, 3)
motion: np.array 2D
motion.shape[0... | spikeinterface/sortingcomponents/motion_correction.py | correct_motion_on_traces_OLD | tfoutz99/spikeinterface | 0 | python | def correct_motion_on_traces_OLD(traces, times, channel_locations, motion, temporal_bins, spatial_bins, direction=1):
'\n Apply inverse motion with spatial interpolation on traces.\n\n Traces can be full traces, but also waveforms snippets.\n\n Parameters\n ----------\n traces : np.array\n Tra... | def correct_motion_on_traces_OLD(traces, times, channel_locations, motion, temporal_bins, spatial_bins, direction=1):
'\n Apply inverse motion with spatial interpolation on traces.\n\n Traces can be full traces, but also waveforms snippets.\n\n Parameters\n ----------\n traces : np.array\n Tra... |
b7bbff2155fbb1257f8c1753a6904144061ca89d79cd0a73e479af8b8f470518 | @abc.abstractmethod
def prepare_port_filter(self, port):
'Prepare filters for the port.\n\n This method should be called before the port is created.\n ' | Prepare filters for the port.
This method should be called before the port is created. | neutron/agent/firewall.py | prepare_port_filter | tankertyp/openstack-neutron | 0 | python | @abc.abstractmethod
def prepare_port_filter(self, port):
'Prepare filters for the port.\n\n This method should be called before the port is created.\n ' | @abc.abstractmethod
def prepare_port_filter(self, port):
'Prepare filters for the port.\n\n This method should be called before the port is created.\n '<|docstring|>Prepare filters for the port.
This method should be called before the port is created.<|endoftext|> |
8eaf5df6b95a48eda951a8445e46c01d58d52ae05f6367e60685b04cd6547143 | def apply_port_filter(self, port):
"Apply port filter.\n\n Once this method returns, the port should be firewalled\n appropriately. This method should as far as possible be a\n no-op. It's vastly preferred to get everything set up in\n prepare_port_filter.\n "
raise NotImpleme... | Apply port filter.
Once this method returns, the port should be firewalled
appropriately. This method should as far as possible be a
no-op. It's vastly preferred to get everything set up in
prepare_port_filter. | neutron/agent/firewall.py | apply_port_filter | tankertyp/openstack-neutron | 0 | python | def apply_port_filter(self, port):
"Apply port filter.\n\n Once this method returns, the port should be firewalled\n appropriately. This method should as far as possible be a\n no-op. It's vastly preferred to get everything set up in\n prepare_port_filter.\n "
raise NotImpleme... | def apply_port_filter(self, port):
"Apply port filter.\n\n Once this method returns, the port should be firewalled\n appropriately. This method should as far as possible be a\n no-op. It's vastly preferred to get everything set up in\n prepare_port_filter.\n "
raise NotImpleme... |
744673d3916edd994d08362fcf44ec8358ae33e258dcb503886f714fcb9bfdf2 | @abc.abstractmethod
def update_port_filter(self, port):
'Refresh security group rules from data store\n\n Gets called when a port gets added to or removed from\n the security group the port is a member of or if the\n group gains or looses a rule.\n ' | Refresh security group rules from data store
Gets called when a port gets added to or removed from
the security group the port is a member of or if the
group gains or looses a rule. | neutron/agent/firewall.py | update_port_filter | tankertyp/openstack-neutron | 0 | python | @abc.abstractmethod
def update_port_filter(self, port):
'Refresh security group rules from data store\n\n Gets called when a port gets added to or removed from\n the security group the port is a member of or if the\n group gains or looses a rule.\n ' | @abc.abstractmethod
def update_port_filter(self, port):
'Refresh security group rules from data store\n\n Gets called when a port gets added to or removed from\n the security group the port is a member of or if the\n group gains or looses a rule.\n '<|docstring|>Refresh security group ru... |
4e207ee5dae87040b78974a4cd4cda7710424de98fbdd9071c6cfddbdc503ae5 | def remove_port_filter(self, port):
'Stop filtering port.'
raise NotImplementedError() | Stop filtering port. | neutron/agent/firewall.py | remove_port_filter | tankertyp/openstack-neutron | 0 | python | def remove_port_filter(self, port):
raise NotImplementedError() | def remove_port_filter(self, port):
raise NotImplementedError()<|docstring|>Stop filtering port.<|endoftext|> |
6c1bfeddec8c8f80cdeb6a75bad4ea09dbd950b6c1d70925075c1c9451a823b5 | def filter_defer_apply_on(self):
'Defer application of filtering rule.'
pass | Defer application of filtering rule. | neutron/agent/firewall.py | filter_defer_apply_on | tankertyp/openstack-neutron | 0 | python | def filter_defer_apply_on(self):
pass | def filter_defer_apply_on(self):
pass<|docstring|>Defer application of filtering rule.<|endoftext|> |
9da369fbd00abc2feec49fae9516b6240d648f09ffc82c87c9ae8a49a033ed4e | def filter_defer_apply_off(self):
'Turn off deferral of rules and apply the rules now.'
pass | Turn off deferral of rules and apply the rules now. | neutron/agent/firewall.py | filter_defer_apply_off | tankertyp/openstack-neutron | 0 | python | def filter_defer_apply_off(self):
pass | def filter_defer_apply_off(self):
pass<|docstring|>Turn off deferral of rules and apply the rules now.<|endoftext|> |
e1dc9b55e4e99b8d1b10d3bbdb1b73eb02cd907bd6ad5baae1509e91122f7a47 | @property
def ports(self):
'Returns filtered ports.'
pass | Returns filtered ports. | neutron/agent/firewall.py | ports | tankertyp/openstack-neutron | 0 | python | @property
def ports(self):
pass | @property
def ports(self):
pass<|docstring|>Returns filtered ports.<|endoftext|> |
b5f64e470ad20b705c68c9254a8824d9dce7b0f0be3686d4aa865d5dde558d96 | @contextlib.contextmanager
def defer_apply(self):
'Defer apply context.'
self.filter_defer_apply_on()
try:
(yield)
finally:
self.filter_defer_apply_off() | Defer apply context. | neutron/agent/firewall.py | defer_apply | tankertyp/openstack-neutron | 0 | python | @contextlib.contextmanager
def defer_apply(self):
self.filter_defer_apply_on()
try:
(yield)
finally:
self.filter_defer_apply_off() | @contextlib.contextmanager
def defer_apply(self):
self.filter_defer_apply_on()
try:
(yield)
finally:
self.filter_defer_apply_off()<|docstring|>Defer apply context.<|endoftext|> |
6a87609fb74bfab580d4c057e4a6ddfce36be52d007eaff2b7714dba8b91b9fe | def update_security_group_members(self, sg_id, ips):
'Update group members in a security group.'
raise NotImplementedError() | Update group members in a security group. | neutron/agent/firewall.py | update_security_group_members | tankertyp/openstack-neutron | 0 | python | def update_security_group_members(self, sg_id, ips):
raise NotImplementedError() | def update_security_group_members(self, sg_id, ips):
raise NotImplementedError()<|docstring|>Update group members in a security group.<|endoftext|> |
1ccc06a3d66487e65402626cd2aee141dab35153f6bcfb045ae07de3da286048 | def update_security_group_rules(self, sg_id, rules):
'Update rules in a security group.'
raise NotImplementedError() | Update rules in a security group. | neutron/agent/firewall.py | update_security_group_rules | tankertyp/openstack-neutron | 0 | python | def update_security_group_rules(self, sg_id, rules):
raise NotImplementedError() | def update_security_group_rules(self, sg_id, rules):
raise NotImplementedError()<|docstring|>Update rules in a security group.<|endoftext|> |
66d77543efb136ebe2d606a6e3bd85a85b1a865a297dd70f575028d768533807 | def security_group_updated(self, action_type, sec_group_ids, device_id=None):
'Called when a security group is updated.\n\n Note: This method needs to be implemented by the firewall drivers\n which use enhanced RPC for security_groups.\n '
raise NotImplementedError() | Called when a security group is updated.
Note: This method needs to be implemented by the firewall drivers
which use enhanced RPC for security_groups. | neutron/agent/firewall.py | security_group_updated | tankertyp/openstack-neutron | 0 | python | def security_group_updated(self, action_type, sec_group_ids, device_id=None):
'Called when a security group is updated.\n\n Note: This method needs to be implemented by the firewall drivers\n which use enhanced RPC for security_groups.\n '
raise NotImplementedError() | def security_group_updated(self, action_type, sec_group_ids, device_id=None):
'Called when a security group is updated.\n\n Note: This method needs to be implemented by the firewall drivers\n which use enhanced RPC for security_groups.\n '
raise NotImplementedError()<|docstring|>Called when... |
aafcbf16670e0ba1234a198ead48b91f5399c266709aa03472bdad4dcda6457d | def process_trusted_ports(self, port_ids):
"Process ports that are trusted and shouldn't be filtered."
pass | Process ports that are trusted and shouldn't be filtered. | neutron/agent/firewall.py | process_trusted_ports | tankertyp/openstack-neutron | 0 | python | def process_trusted_ports(self, port_ids):
pass | def process_trusted_ports(self, port_ids):
pass<|docstring|>Process ports that are trusted and shouldn't be filtered.<|endoftext|> |
f380e52b722a1649ec55130e825b099d099069d8fee9b4e294cc9e23ff54ca64 | def setup_multicast_traffic(self, phy_br_ofports, tun_br_ofports, enable_tunneling):
'Setup filters for multicast traffic'
pass | Setup filters for multicast traffic | neutron/agent/firewall.py | setup_multicast_traffic | tankertyp/openstack-neutron | 0 | python | def setup_multicast_traffic(self, phy_br_ofports, tun_br_ofports, enable_tunneling):
pass | def setup_multicast_traffic(self, phy_br_ofports, tun_br_ofports, enable_tunneling):
pass<|docstring|>Setup filters for multicast traffic<|endoftext|> |
a4b09c15b1031b7ff3d509e4dfe6819224669fd827e37f4d0b9c1ba630e98fbb | def averaging(self, properties, combinations={}, **constants):
'\n Calls :func:`~sample.averaging` for all samples in the list.\n\n Parameters\n ----------\n : Same as in :func:`sample.averaging`.\n\n Returns\n -------\n pandas.DataFrame\n A da... | Calls :func:`~sample.averaging` for all samples in the list.
Parameters
----------
: Same as in :func:`sample.averaging`.
Returns
-------
pandas.DataFrame
A data frame containing the computed averages and combinations,
as well as their estimated standard errors, for all samples. | src/mics/pooledsamples.py | averaging | craabreu/MICS | 4 | python | def averaging(self, properties, combinations={}, **constants):
'\n Calls :func:`~sample.averaging` for all samples in the list.\n\n Parameters\n ----------\n : Same as in :func:`sample.averaging`.\n\n Returns\n -------\n pandas.DataFrame\n A da... | def averaging(self, properties, combinations={}, **constants):
'\n Calls :func:`~sample.averaging` for all samples in the list.\n\n Parameters\n ----------\n : Same as in :func:`sample.averaging`.\n\n Returns\n -------\n pandas.DataFrame\n A da... |
b3049db7d8aa5330559f8200c283fcf9df3de041b2d24d2f365fdfa232b6b90a | def mixture(self, engine):
'\n Generates a :class:`mixture` object.\n\n Parameters\n ----------\n engine: :class:`MICS` or :class:`MBAR`\n\n Returns\n -------\n :class:`mixture`\n\n '
return mics.mixture(self, engine) | Generates a :class:`mixture` object.
Parameters
----------
engine: :class:`MICS` or :class:`MBAR`
Returns
-------
:class:`mixture` | src/mics/pooledsamples.py | mixture | craabreu/MICS | 4 | python | def mixture(self, engine):
'\n Generates a :class:`mixture` object.\n\n Parameters\n ----------\n engine: :class:`MICS` or :class:`MBAR`\n\n Returns\n -------\n :class:`mixture`\n\n '
return mics.mixture(self, engine) | def mixture(self, engine):
'\n Generates a :class:`mixture` object.\n\n Parameters\n ----------\n engine: :class:`MICS` or :class:`MBAR`\n\n Returns\n -------\n :class:`mixture`\n\n '
return mics.mixture(self, engine)<|docstring|>Generates a :class... |
cffb6a4489e78e649c5b80edebcefe194201271f27b359724437b5347a6ef5ee | def subsampling(self, integratedACF=True):
'\n Calls :func:`~sample.subsampling` for all samples in the list.\n\n Parameters\n ----------\n : Same as in :func:`sample.subsampling`.\n\n Returns\n -------\n :class:`pooledsample`\n Although the su... | Calls :func:`~sample.subsampling` for all samples in the list.
Parameters
----------
: Same as in :func:`sample.subsampling`.
Returns
-------
:class:`pooledsample`
Although the subsampling is done in line, the new pooled sample
is returned for chaining purposes. | src/mics/pooledsamples.py | subsampling | craabreu/MICS | 4 | python | def subsampling(self, integratedACF=True):
'\n Calls :func:`~sample.subsampling` for all samples in the list.\n\n Parameters\n ----------\n : Same as in :func:`sample.subsampling`.\n\n Returns\n -------\n :class:`pooledsample`\n Although the su... | def subsampling(self, integratedACF=True):
'\n Calls :func:`~sample.subsampling` for all samples in the list.\n\n Parameters\n ----------\n : Same as in :func:`sample.subsampling`.\n\n Returns\n -------\n :class:`pooledsample`\n Although the su... |
2b3c8ff832ae8ba7e1b7beb63f7ae3f68a3f033e103f31decf09e5ed0c19de62 | def show_2dboxes(im, bdbs, color_list=[], random_color=True, scale=1.0):
"\n Visualize the bounding boxes with the image\n\n Parameters\n ----------\n im : numpy array (W, H, 3)\n bdbs : list of dicts\n Keys: {'x1', 'y1', 'x2', 'y2', 'classname'}\n The (x1, y1) posi... | Visualize the bounding boxes with the image
Parameters
----------
im : numpy array (W, H, 3)
bdbs : list of dicts
Keys: {'x1', 'y1', 'x2', 'y2', 'classname'}
The (x1, y1) position is at the top left corner,
the (x2, y2) position is at the bottom right corner
color_list: list of colors | utils/vis_utils.py | show_2dboxes | Jerrypiglet/cooperative_scene_parsing | 2 | python | def show_2dboxes(im, bdbs, color_list=[], random_color=True, scale=1.0):
"\n Visualize the bounding boxes with the image\n\n Parameters\n ----------\n im : numpy array (W, H, 3)\n bdbs : list of dicts\n Keys: {'x1', 'y1', 'x2', 'y2', 'classname'}\n The (x1, y1) posi... | def show_2dboxes(im, bdbs, color_list=[], random_color=True, scale=1.0):
"\n Visualize the bounding boxes with the image\n\n Parameters\n ----------\n im : numpy array (W, H, 3)\n bdbs : list of dicts\n Keys: {'x1', 'y1', 'x2', 'y2', 'classname'}\n The (x1, y1) posi... |
3b6c299f0462f4bd150fb2c9556eda23f754c8640eb274c89ed75528b0ce3d28 | def show_3d_box(boxes):
'\n :param box: 8 x 3 numpy array\n '
fig = plt.figure()
ax = Axes3D(fig)
for box in boxes:
plot_cuboid(ax, box[0], box[1], box[2], box[3], box[4], box[5], box[6], box[7], 'r-')
plt.show() | :param box: 8 x 3 numpy array | utils/vis_utils.py | show_3d_box | Jerrypiglet/cooperative_scene_parsing | 2 | python | def show_3d_box(boxes):
'\n \n '
fig = plt.figure()
ax = Axes3D(fig)
for box in boxes:
plot_cuboid(ax, box[0], box[1], box[2], box[3], box[4], box[5], box[6], box[7], 'r-')
plt.show() | def show_3d_box(boxes):
'\n \n '
fig = plt.figure()
ax = Axes3D(fig)
for box in boxes:
plot_cuboid(ax, box[0], box[1], box[2], box[3], box[4], box[5], box[6], box[7], 'r-')
plt.show()<|docstring|>:param box: 8 x 3 numpy array<|endoftext|> |
e15f17fd5590325180b5b876fa31a0c2c6c04b97d4c27f870cc22bb962ef92cb | @staticmethod
def buildTargetsFromArgs(urls: List[str], method: Union[(str, List[str])], body: str) -> List[dict]:
'Build the targets from arguments\n\n @type urls: List[str]\n @param urls: The target URLs\n @type method: str | List[str]\n @param method: The request methods\n @typ... | Build the targets from arguments
@type urls: List[str]
@param urls: The target URLs
@type method: str | List[str]
@param method: The request methods
@type body: str
@param body: The raw request body data
@returns dict: The targets data builded into a dictionary | src/fuzzingtool/interfaces/ArgumentBuilder.py | buildTargetsFromArgs | NESCAU-UFLA/FuzzingTool | 131 | python | @staticmethod
def buildTargetsFromArgs(urls: List[str], method: Union[(str, List[str])], body: str) -> List[dict]:
'Build the targets from arguments\n\n @type urls: List[str]\n @param urls: The target URLs\n @type method: str | List[str]\n @param method: The request methods\n @typ... | @staticmethod
def buildTargetsFromArgs(urls: List[str], method: Union[(str, List[str])], body: str) -> List[dict]:
'Build the targets from arguments\n\n @type urls: List[str]\n @param urls: The target URLs\n @type method: str | List[str]\n @param method: The request methods\n @typ... |
22f9e473ee695c9693c69697fc1375a5f0c60a27b707d434ff57acc93edcbae2 | @staticmethod
def buildTargetsFromRawHttp(rawHttpFilenames: List[str], scheme: str) -> List[dict]:
'Build the targets from raw http files\n\n @type rawHttpFilenames: list\n @param rawHttpFilenames: The list with the raw http filenames\n @type scheme: str\n @param scheme: The scheme used ... | Build the targets from raw http files
@type rawHttpFilenames: list
@param rawHttpFilenames: The list with the raw http filenames
@type scheme: str
@param scheme: The scheme used in the URL
@returns List[dict]: The targets data builded into a list of dictionary | src/fuzzingtool/interfaces/ArgumentBuilder.py | buildTargetsFromRawHttp | NESCAU-UFLA/FuzzingTool | 131 | python | @staticmethod
def buildTargetsFromRawHttp(rawHttpFilenames: List[str], scheme: str) -> List[dict]:
'Build the targets from raw http files\n\n @type rawHttpFilenames: list\n @param rawHttpFilenames: The list with the raw http filenames\n @type scheme: str\n @param scheme: The scheme used ... | @staticmethod
def buildTargetsFromRawHttp(rawHttpFilenames: List[str], scheme: str) -> List[dict]:
'Build the targets from raw http files\n\n @type rawHttpFilenames: list\n @param rawHttpFilenames: The list with the raw http filenames\n @type scheme: str\n @param scheme: The scheme used ... |
c7c9994d1e6af688ef2a84f79d2e4be3729f8f683b1d4f77ea430bdb2a1ee567 | def buildHeaderFromRawHttp(headerList: List[deque]) -> Dict[(str, str)]:
'Get the HTTP header\n\n @tyoe headerList: List[deque]\n @param headerList: The list with HTTP header\n @returns Dict[str, str]: The HTTP header parsed into a dict\n '
headers = {}
i = 0
... | Get the HTTP header
@tyoe headerList: List[deque]
@param headerList: The list with HTTP header
@returns Dict[str, str]: The HTTP header parsed into a dict | src/fuzzingtool/interfaces/ArgumentBuilder.py | buildHeaderFromRawHttp | NESCAU-UFLA/FuzzingTool | 131 | python | def buildHeaderFromRawHttp(headerList: List[deque]) -> Dict[(str, str)]:
'Get the HTTP header\n\n @tyoe headerList: List[deque]\n @param headerList: The list with HTTP header\n @returns Dict[str, str]: The HTTP header parsed into a dict\n '
headers = {}
i = 0
... | def buildHeaderFromRawHttp(headerList: List[deque]) -> Dict[(str, str)]:
'Get the HTTP header\n\n @tyoe headerList: List[deque]\n @param headerList: The list with HTTP header\n @returns Dict[str, str]: The HTTP header parsed into a dict\n '
headers = {}
i = 0
... |
64c9e6adbb9fbc95d66df01fc786e8bac2eb3ac56af0728032fb1d4694006b4f | def annotation(self, xdata: InstrXData) -> str:
'data format a:vxa\n\n vars[0]: lhs\n xprs[0]: rhs\n xprs[1]: address of memory location\n '
lhs = str(xdata.vars[0])
rhs = str(xdata.xprs[0])
if ((lhs == '?') and (len(xdata.xprs) == 2)):
lhs = derefstr(xdata.xprs[1])
... | data format a:vxa
vars[0]: lhs
xprs[0]: rhs
xprs[1]: address of memory location | chb/mips/opcodes/MIPSStoreDoubleWordFromFP.py | annotation | sipma/CodeHawk-Binary | 0 | python | def annotation(self, xdata: InstrXData) -> str:
'data format a:vxa\n\n vars[0]: lhs\n xprs[0]: rhs\n xprs[1]: address of memory location\n '
lhs = str(xdata.vars[0])
rhs = str(xdata.xprs[0])
if ((lhs == '?') and (len(xdata.xprs) == 2)):
lhs = derefstr(xdata.xprs[1])
... | def annotation(self, xdata: InstrXData) -> str:
'data format a:vxa\n\n vars[0]: lhs\n xprs[0]: rhs\n xprs[1]: address of memory location\n '
lhs = str(xdata.vars[0])
rhs = str(xdata.xprs[0])
if ((lhs == '?') and (len(xdata.xprs) == 2)):
lhs = derefstr(xdata.xprs[1])
... |
5ff789409112166206184508d623ca801a1054cf8723589cfc1d8b759c733c3d | def __init__(self, userdata=None):
'\n Store userdata\n\n :param userdata: Userdata file to be sent to AWS instances\n :type userdata: str, list, optional\n\n :return: A new UserdataCreator instance\n :rtype: UserdataCreator\n '
if (userdata is None):
userdata =... | Store userdata
:param userdata: Userdata file to be sent to AWS instances
:type userdata: str, list, optional
:return: A new UserdataCreator instance
:rtype: UserdataCreator | ci/awsPseudoCi/userdata_creator.py | __init__ | mikkowus/BESSPIN-Tool-Suite | 0 | python | def __init__(self, userdata=None):
'\n Store userdata\n\n :param userdata: Userdata file to be sent to AWS instances\n :type userdata: str, list, optional\n\n :return: A new UserdataCreator instance\n :rtype: UserdataCreator\n '
if (userdata is None):
userdata =... | def __init__(self, userdata=None):
'\n Store userdata\n\n :param userdata: Userdata file to be sent to AWS instances\n :type userdata: str, list, optional\n\n :return: A new UserdataCreator instance\n :rtype: UserdataCreator\n '
if (userdata is None):
userdata =... |
c23c336e4dcdaa75cc6f88a4755345fda9cc8d170728801ccf68716c82b283db | @classmethod
@log_assertion_fails
@debug_wrap
def default(cls, credentials, name, index, branch=None, binaries_branch=None, key_path='~/.ssh/id_rsa', runMode='fett'):
"\n Add userdata to start with BESSPIN at specific branch and binaries branch\n\n :param credentials: AWS credentials.\n :type c... | Add userdata to start with BESSPIN at specific branch and binaries branch
:param credentials: AWS credentials.
:type credentials: AWSCredentials
:param name: Job name
:type name: str
:param index: BESSPIN index
:type index: int
:param branch: What branch of BESSPIN-Tool-Suite to run on AWS instances, defaults to 'm... | ci/awsPseudoCi/userdata_creator.py | default | mikkowus/BESSPIN-Tool-Suite | 0 | python | @classmethod
@log_assertion_fails
@debug_wrap
def default(cls, credentials, name, index, branch=None, binaries_branch=None, key_path='~/.ssh/id_rsa', runMode='fett'):
"\n Add userdata to start with BESSPIN at specific branch and binaries branch\n\n :param credentials: AWS credentials.\n :type c... | @classmethod
@log_assertion_fails
@debug_wrap
def default(cls, credentials, name, index, branch=None, binaries_branch=None, key_path='~/.ssh/id_rsa', runMode='fett'):
"\n Add userdata to start with BESSPIN at specific branch and binaries branch\n\n :param credentials: AWS credentials.\n :type c... |
51caeaa149a3c9ad63e15e24b26ddf228a7174b6d171720345be566d2e767c88 | @debug_wrap
def append(self, ul=''):
"\n Convenience to append to self._userdata\n\n :param ul: Script to append to userdata, defaults to ''\n :type ul: str, list, optional\n "
if (not isinstance(ul, str)):
self._userdata += ul
else:
self._userdata.append(ul) | Convenience to append to self._userdata
:param ul: Script to append to userdata, defaults to ''
:type ul: str, list, optional | ci/awsPseudoCi/userdata_creator.py | append | mikkowus/BESSPIN-Tool-Suite | 0 | python | @debug_wrap
def append(self, ul=):
"\n Convenience to append to self._userdata\n\n :param ul: Script to append to userdata, defaults to \n :type ul: str, list, optional\n "
if (not isinstance(ul, str)):
self._userdata += ul
else:
self._userdata.append(ul) | @debug_wrap
def append(self, ul=):
"\n Convenience to append to self._userdata\n\n :param ul: Script to append to userdata, defaults to \n :type ul: str, list, optional\n "
if (not isinstance(ul, str)):
self._userdata += ul
else:
self._userdata.append(ul)<|docstri... |
0d0eacd9f8b2ac34dcf3591899d9ecd47c4e23acf7526efe5fef2b810fb7b263 | @debug_wrap
@log_assertion_fails
def append_file(self, dest, path):
'\n Add file contents of path to userdata\n\n :param dest: Destination of file contents\n :type dest: str\n\n :param path: Filepath\n :type path: str\n '
assert os.path.exists(path)
self.append(f'ca... | Add file contents of path to userdata
:param dest: Destination of file contents
:type dest: str
:param path: Filepath
:type path: str | ci/awsPseudoCi/userdata_creator.py | append_file | mikkowus/BESSPIN-Tool-Suite | 0 | python | @debug_wrap
@log_assertion_fails
def append_file(self, dest, path):
'\n Add file contents of path to userdata\n\n :param dest: Destination of file contents\n :type dest: str\n\n :param path: Filepath\n :type path: str\n '
assert os.path.exists(path)
self.append(f'ca... | @debug_wrap
@log_assertion_fails
def append_file(self, dest, path):
'\n Add file contents of path to userdata\n\n :param dest: Destination of file contents\n :type dest: str\n\n :param path: Filepath\n :type path: str\n '
assert os.path.exists(path)
self.append(f'ca... |
e98f6ae6464572a7184c01e7d584a106b7f072d5eea56bcaf00d404ba36957e9 | @debug_wrap
def to_file(self, fname):
'\n Write userdata to a userdata file\n\n :param fname: Filename\n :type fname: str\n '
with open(fname, 'w') as fp:
ud = [f"runuser -l centos -c 'touch {self.indicator_filepath()}'"]
fp.write('\n'.join(ud))
log.info(f"Userdat... | Write userdata to a userdata file
:param fname: Filename
:type fname: str | ci/awsPseudoCi/userdata_creator.py | to_file | mikkowus/BESSPIN-Tool-Suite | 0 | python | @debug_wrap
def to_file(self, fname):
'\n Write userdata to a userdata file\n\n :param fname: Filename\n :type fname: str\n '
with open(fname, 'w') as fp:
ud = [f"runuser -l centos -c 'touch {self.indicator_filepath()}'"]
fp.write('\n'.join(ud))
log.info(f"Userdat... | @debug_wrap
def to_file(self, fname):
'\n Write userdata to a userdata file\n\n :param fname: Filename\n :type fname: str\n '
with open(fname, 'w') as fp:
ud = [f"runuser -l centos -c 'touch {self.indicator_filepath()}'"]
fp.write('\n'.join(ud))
log.info(f"Userdat... |
6f829df46b4d738f0fc30865d25b970a8aed7dc0c1a3ebfd8b5cf1de1079afd6 | @property
def userdata(self):
'\n Userdata getter\n\n :return: Userdata\n :rtype: str\n '
return '\n'.join(self._userdata) | Userdata getter
:return: Userdata
:rtype: str | ci/awsPseudoCi/userdata_creator.py | userdata | mikkowus/BESSPIN-Tool-Suite | 0 | python | @property
def userdata(self):
'\n Userdata getter\n\n :return: Userdata\n :rtype: str\n '
return '\n'.join(self._userdata) | @property
def userdata(self):
'\n Userdata getter\n\n :return: Userdata\n :rtype: str\n '
return '\n'.join(self._userdata)<|docstring|>Userdata getter
:return: Userdata
:rtype: str<|endoftext|> |
05b38efc04c87a6abbc340c57ba4203742ab8322203f91b925c0395de50df8d1 | def iuwt_decomposition(in1, scale_count, scale_adjust=0, mode='ser', core_count=2, store_smoothed=False):
"\n This function serves as a handler for the different implementations of the IUWT decomposition. It allows the\n different methods to be used almost interchangeably.\n\n INPUTS:\n in1 ... | This function serves as a handler for the different implementations of the IUWT decomposition. It allows the
different methods to be used almost interchangeably.
INPUTS:
in1 (no default): Array on which the decomposition is to be performed.
scale_count (no default): Maximum scale to... | vip_hci/exlib/iuwt.py | iuwt_decomposition | ChrisDelaX/VIP | 2 | python | def iuwt_decomposition(in1, scale_count, scale_adjust=0, mode='ser', core_count=2, store_smoothed=False):
"\n This function serves as a handler for the different implementations of the IUWT decomposition. It allows the\n different methods to be used almost interchangeably.\n\n INPUTS:\n in1 ... | def iuwt_decomposition(in1, scale_count, scale_adjust=0, mode='ser', core_count=2, store_smoothed=False):
"\n This function serves as a handler for the different implementations of the IUWT decomposition. It allows the\n different methods to be used almost interchangeably.\n\n INPUTS:\n in1 ... |
60c9d3c4668ea6a8aeca6272f5730b8bffd28fe04c7e6b48e1d633797d6d5d0f | def iuwt_recomposition(in1, scale_adjust=0, mode='ser', core_count=1, store_on_gpu=False, smoothed_array=None):
"\n This function serves as a handler for the different implementations of the IUWT recomposition. It allows the\n different methods to be used almost interchangeably.\n\n INPUTS:\n in1 ... | This function serves as a handler for the different implementations of the IUWT recomposition. It allows the
different methods to be used almost interchangeably.
INPUTS:
in1 (no default): Array on which the decomposition is to be performed.
scale_adjust (no default): Number of omitte... | vip_hci/exlib/iuwt.py | iuwt_recomposition | ChrisDelaX/VIP | 2 | python | def iuwt_recomposition(in1, scale_adjust=0, mode='ser', core_count=1, store_on_gpu=False, smoothed_array=None):
"\n This function serves as a handler for the different implementations of the IUWT recomposition. It allows the\n different methods to be used almost interchangeably.\n\n INPUTS:\n in1 ... | def iuwt_recomposition(in1, scale_adjust=0, mode='ser', core_count=1, store_on_gpu=False, smoothed_array=None):
"\n This function serves as a handler for the different implementations of the IUWT recomposition. It allows the\n different methods to be used almost interchangeably.\n\n INPUTS:\n in1 ... |
6687a8f6a8bcb4f2b71ac6272b513f2eabe8e3952e94995a5112b121a96dd45a | def ser_iuwt_decomposition(in1, scale_count, scale_adjust, store_smoothed):
'\n This function calls the a trous algorithm code to decompose the input into its wavelet coefficients. This is\n the isotropic undecimated wavelet transform implemented for a single CPU core.\n\n INPUTS:\n in1 ... | This function calls the a trous algorithm code to decompose the input into its wavelet coefficients. This is
the isotropic undecimated wavelet transform implemented for a single CPU core.
INPUTS:
in1 (no default): Array on which the decomposition is to be performed.
scale_count (no default): ... | vip_hci/exlib/iuwt.py | ser_iuwt_decomposition | ChrisDelaX/VIP | 2 | python | def ser_iuwt_decomposition(in1, scale_count, scale_adjust, store_smoothed):
'\n This function calls the a trous algorithm code to decompose the input into its wavelet coefficients. This is\n the isotropic undecimated wavelet transform implemented for a single CPU core.\n\n INPUTS:\n in1 ... | def ser_iuwt_decomposition(in1, scale_count, scale_adjust, store_smoothed):
'\n This function calls the a trous algorithm code to decompose the input into its wavelet coefficients. This is\n the isotropic undecimated wavelet transform implemented for a single CPU core.\n\n INPUTS:\n in1 ... |
ac784d662475f6226a5d77540db3ddffa23485e8884b952d66f903873ebc4c45 | def ser_iuwt_recomposition(in1, scale_adjust, smoothed_array):
'\n This function calls the a trous algorithm code to recompose the input into a single array. This is the\n implementation of the isotropic undecimated wavelet transform recomposition for a single CPU core.\n\n INPUTS:\n in1 (no... | This function calls the a trous algorithm code to recompose the input into a single array. This is the
implementation of the isotropic undecimated wavelet transform recomposition for a single CPU core.
INPUTS:
in1 (no default): Array containing wavelet coefficients.
scale_adjust (no default): Indica... | vip_hci/exlib/iuwt.py | ser_iuwt_recomposition | ChrisDelaX/VIP | 2 | python | def ser_iuwt_recomposition(in1, scale_adjust, smoothed_array):
'\n This function calls the a trous algorithm code to recompose the input into a single array. This is the\n implementation of the isotropic undecimated wavelet transform recomposition for a single CPU core.\n\n INPUTS:\n in1 (no... | def ser_iuwt_recomposition(in1, scale_adjust, smoothed_array):
'\n This function calls the a trous algorithm code to recompose the input into a single array. This is the\n implementation of the isotropic undecimated wavelet transform recomposition for a single CPU core.\n\n INPUTS:\n in1 (no... |
735ac0304cb9c82feb22c37085c8aae962a8803977bd930ccd026b0708960a77 | def ser_a_trous(C0, filter, scale):
'\n The following is a serial implementation of the a trous algorithm. Accepts the following parameters:\n\n INPUTS:\n filter (no default): The filter-bank which is applied to the components of the transform.\n C0 (no default): The current array on w... | The following is a serial implementation of the a trous algorithm. Accepts the following parameters:
INPUTS:
filter (no default): The filter-bank which is applied to the components of the transform.
C0 (no default): The current array on which filtering is to be performed.
scale (no default): ... | vip_hci/exlib/iuwt.py | ser_a_trous | ChrisDelaX/VIP | 2 | python | def ser_a_trous(C0, filter, scale):
'\n The following is a serial implementation of the a trous algorithm. Accepts the following parameters:\n\n INPUTS:\n filter (no default): The filter-bank which is applied to the components of the transform.\n C0 (no default): The current array on w... | def ser_a_trous(C0, filter, scale):
'\n The following is a serial implementation of the a trous algorithm. Accepts the following parameters:\n\n INPUTS:\n filter (no default): The filter-bank which is applied to the components of the transform.\n C0 (no default): The current array on w... |
562ca9e0e621ae38eb4275b11e5e09b3dc732a65ef9f755086771bc098023434 | def mp_iuwt_decomposition(in1, scale_count, scale_adjust, store_smoothed, core_count):
'\n This function calls the a trous algorithm code to decompose the input into its wavelet coefficients. This is\n the isotropic undecimated wavelet transform implemented for multiple CPU cores. NOTE: Python is not well sui... | This function calls the a trous algorithm code to decompose the input into its wavelet coefficients. This is
the isotropic undecimated wavelet transform implemented for multiple CPU cores. NOTE: Python is not well suited
to multiprocessing - this may not improve execution speed.
INPUTS:
in1 (no default... | vip_hci/exlib/iuwt.py | mp_iuwt_decomposition | ChrisDelaX/VIP | 2 | python | def mp_iuwt_decomposition(in1, scale_count, scale_adjust, store_smoothed, core_count):
'\n This function calls the a trous algorithm code to decompose the input into its wavelet coefficients. This is\n the isotropic undecimated wavelet transform implemented for multiple CPU cores. NOTE: Python is not well sui... | def mp_iuwt_decomposition(in1, scale_count, scale_adjust, store_smoothed, core_count):
'\n This function calls the a trous algorithm code to decompose the input into its wavelet coefficients. This is\n the isotropic undecimated wavelet transform implemented for multiple CPU cores. NOTE: Python is not well sui... |
2ec56be4c4693695c7d2164a08c06bc28132d8c54662827e88f03633f4e7333b | def mp_iuwt_recomposition(in1, scale_adjust, core_count, smoothed_array):
'\n This function calls the a trous algorithm code to recompose the input into a single array. This is the\n implementation of the isotropic undecimated wavelet transform recomposition for multiple CPU cores.\n\n INPUTS:\n in1 ... | This function calls the a trous algorithm code to recompose the input into a single array. This is the
implementation of the isotropic undecimated wavelet transform recomposition for multiple CPU cores.
INPUTS:
in1 (no default): Array containing wavelet coefficients.
scale_adjust (no default): Indic... | vip_hci/exlib/iuwt.py | mp_iuwt_recomposition | ChrisDelaX/VIP | 2 | python | def mp_iuwt_recomposition(in1, scale_adjust, core_count, smoothed_array):
'\n This function calls the a trous algorithm code to recompose the input into a single array. This is the\n implementation of the isotropic undecimated wavelet transform recomposition for multiple CPU cores.\n\n INPUTS:\n in1 ... | def mp_iuwt_recomposition(in1, scale_adjust, core_count, smoothed_array):
'\n This function calls the a trous algorithm code to recompose the input into a single array. This is the\n implementation of the isotropic undecimated wavelet transform recomposition for multiple CPU cores.\n\n INPUTS:\n in1 ... |
e2b6e272346938dba12253f059b9fca0234e5a17770278949d209c880e3e7dcb | def mp_a_trous(C0, wavelet_filter, scale, core_count):
'\n This is a reimplementation of the a trous filter which makes use of multiprocessing. In particular,\n it divides the input array of dimensions NxN into M smaller arrays of dimensions (N/M)xN, where M is the\n number of cores which are to be used.\n... | This is a reimplementation of the a trous filter which makes use of multiprocessing. In particular,
it divides the input array of dimensions NxN into M smaller arrays of dimensions (N/M)xN, where M is the
number of cores which are to be used.
INPUTS:
C0 (no default): The current array which is to be dec... | vip_hci/exlib/iuwt.py | mp_a_trous | ChrisDelaX/VIP | 2 | python | def mp_a_trous(C0, wavelet_filter, scale, core_count):
'\n This is a reimplementation of the a trous filter which makes use of multiprocessing. In particular,\n it divides the input array of dimensions NxN into M smaller arrays of dimensions (N/M)xN, where M is the\n number of cores which are to be used.\n... | def mp_a_trous(C0, wavelet_filter, scale, core_count):
'\n This is a reimplementation of the a trous filter which makes use of multiprocessing. In particular,\n it divides the input array of dimensions NxN into M smaller arrays of dimensions (N/M)xN, where M is the\n number of cores which are to be used.\n... |
2b20851b145f4a373be3343ddf508b29509668e4df4f15ad47f52b8962068a2d | def mp_a_trous_kernel(C0, wavelet_filter, scale, slice_ind, slice_width, r_or_c='row'):
'\n This is the convolution step of the a trous algorithm.\n\n INPUTS:\n C0 (no default): The current array which is to be decomposed.\n wavelet_filter (no default): The filter-bank which is... | This is the convolution step of the a trous algorithm.
INPUTS:
C0 (no default): The current array which is to be decomposed.
wavelet_filter (no default): The filter-bank which is applied to the elements of the transform.
scale (no default): The scale at which decomposition is ... | vip_hci/exlib/iuwt.py | mp_a_trous_kernel | ChrisDelaX/VIP | 2 | python | def mp_a_trous_kernel(C0, wavelet_filter, scale, slice_ind, slice_width, r_or_c='row'):
'\n This is the convolution step of the a trous algorithm.\n\n INPUTS:\n C0 (no default): The current array which is to be decomposed.\n wavelet_filter (no default): The filter-bank which is... | def mp_a_trous_kernel(C0, wavelet_filter, scale, slice_ind, slice_width, r_or_c='row'):
'\n This is the convolution step of the a trous algorithm.\n\n INPUTS:\n C0 (no default): The current array which is to be decomposed.\n wavelet_filter (no default): The filter-bank which is... |
1f67bb4e9cd3bcfbcfa2e1e46a4fc950932e43ea6b31ad058be503b35092393f | def list_to_sql_string(lst: Tuple[str]) -> str:
'turns python lists into a string that can be put into a postgres tuple and serve as a list in postgres\n\n :param lst: a list of strings like ``[\'pg_catalog\',\'information_schema\']``\n\n :return: a string of items in SQL format ``"\'pg_catalog\',\'informatio... | turns python lists into a string that can be put into a postgres tuple and serve as a list in postgres
:param lst: a list of strings like ``['pg_catalog','information_schema']``
:return: a string of items in SQL format ``"'pg_catalog','information_schema','hi'"`` | plpy_wrapper/utilities.py | list_to_sql_string | skamensky/plpy-wrapper | 5 | python | def list_to_sql_string(lst: Tuple[str]) -> str:
'turns python lists into a string that can be put into a postgres tuple and serve as a list in postgres\n\n :param lst: a list of strings like ``[\'pg_catalog\',\'information_schema\']``\n\n :return: a string of items in SQL format ``"\'pg_catalog\',\'informatio... | def list_to_sql_string(lst: Tuple[str]) -> str:
'turns python lists into a string that can be put into a postgres tuple and serve as a list in postgres\n\n :param lst: a list of strings like ``[\'pg_catalog\',\'information_schema\']``\n\n :return: a string of items in SQL format ``"\'pg_catalog\',\'informatio... |
8ad90e9e33145ac5310155e7a43cc7142a25a3e57c96658e8023af74faac1509 | def make_qualified_schema_name(schema_name: str, table_name: str) -> str:
'produces a qualified schema name given a schema and table\n\n :param schema_name: the schema name\n :param table_name: the table name\n :return: a quoted dot separated qualified schema name\n '
return '"{s}"."{t}"'.format(s=s... | produces a qualified schema name given a schema and table
:param schema_name: the schema name
:param table_name: the table name
:return: a quoted dot separated qualified schema name | plpy_wrapper/utilities.py | make_qualified_schema_name | skamensky/plpy-wrapper | 5 | python | def make_qualified_schema_name(schema_name: str, table_name: str) -> str:
'produces a qualified schema name given a schema and table\n\n :param schema_name: the schema name\n :param table_name: the table name\n :return: a quoted dot separated qualified schema name\n '
return '"{s}"."{t}"'.format(s=s... | def make_qualified_schema_name(schema_name: str, table_name: str) -> str:
'produces a qualified schema name given a schema and table\n\n :param schema_name: the schema name\n :param table_name: the table name\n :return: a quoted dot separated qualified schema name\n '
return '"{s}"."{t}"'.format(s=s... |
8a44dc6080956053f842c1690066f525ea15c9b37d14bede246ad59893bd5b7a | def check_nth_arg_is_of_type(n: int, type_to_check: type):
'this decorator allows us to do some basic type checking\n\n :param n: the "nth" argument of the decorated function\n :param type_to_check: the type to ensure that the "nth" value is of\n :raises: :class:`plpy_wrapper.exceptions.TypeException`\n ... | this decorator allows us to do some basic type checking
:param n: the "nth" argument of the decorated function
:param type_to_check: the type to ensure that the "nth" value is of
:raises: :class:`plpy_wrapper.exceptions.TypeException` | plpy_wrapper/utilities.py | check_nth_arg_is_of_type | skamensky/plpy-wrapper | 5 | python | def check_nth_arg_is_of_type(n: int, type_to_check: type):
'this decorator allows us to do some basic type checking\n\n :param n: the "nth" argument of the decorated function\n :param type_to_check: the type to ensure that the "nth" value is of\n :raises: :class:`plpy_wrapper.exceptions.TypeException`\n ... | def check_nth_arg_is_of_type(n: int, type_to_check: type):
'this decorator allows us to do some basic type checking\n\n :param n: the "nth" argument of the decorated function\n :param type_to_check: the type to ensure that the "nth" value is of\n :raises: :class:`plpy_wrapper.exceptions.TypeException`\n ... |
5acf84b3f04f1b3868ad064579572a3d7a49f1dae88ec247aee4b839fb5ea8da | def create_plpython_triggers(plpy_wrapper: 'plpy_wrapper.PLPYWrapper', schema: str, table_name: str, trigger_template_path: Union[(str, Path, None)]=Path(Path(__file__).parent, 'trigger_process_template.txt'), trigger_func_definition: Union[(str, None)]='', trigger_func_name: Union[(str, None)]=''):
'\n sets up ... | sets up triggers and the trigger function for a table.
After running this function, triggers will now be routed to the custom function where you can run arbitrary python inside of the :class:`plpython.trigger.Trigger` methods.
Should be executed from the DB like so::
do $$
import plpy_wrapper
wrapper = plp... | plpy_wrapper/utilities.py | create_plpython_triggers | skamensky/plpy-wrapper | 5 | python | def create_plpython_triggers(plpy_wrapper: 'plpy_wrapper.PLPYWrapper', schema: str, table_name: str, trigger_template_path: Union[(str, Path, None)]=Path(Path(__file__).parent, 'trigger_process_template.txt'), trigger_func_definition: Union[(str, None)]=, trigger_func_name: Union[(str, None)]=):
'\n sets up trig... | def create_plpython_triggers(plpy_wrapper: 'plpy_wrapper.PLPYWrapper', schema: str, table_name: str, trigger_template_path: Union[(str, Path, None)]=Path(Path(__file__).parent, 'trigger_process_template.txt'), trigger_func_definition: Union[(str, None)]=, trigger_func_name: Union[(str, None)]=):
'\n sets up trig... |
f2c6b88b4919b24e5cd2a43010745f134a4475c80956aa0bf3aa4ba1bbc3a341 | def get_all_tables(plpy_wrapper: 'plpy_wrapper.PLPYWrapper', exclude_schemas: Tuple[str]=(), exclude_tables: Tuple[str]=()) -> 'plpy_wrapper.ResultSet':
'Queries postgres for all tables\n\n :param plpy_wrapper: PLPYWrapper instance\n :param exclude_schemas: schemas to exclude from the query\n :param exclud... | Queries postgres for all tables
:param plpy_wrapper: PLPYWrapper instance
:param exclude_schemas: schemas to exclude from the query
:param exclude_tables: tables to exclude from the query
:return: | plpy_wrapper/utilities.py | get_all_tables | skamensky/plpy-wrapper | 5 | python | def get_all_tables(plpy_wrapper: 'plpy_wrapper.PLPYWrapper', exclude_schemas: Tuple[str]=(), exclude_tables: Tuple[str]=()) -> 'plpy_wrapper.ResultSet':
'Queries postgres for all tables\n\n :param plpy_wrapper: PLPYWrapper instance\n :param exclude_schemas: schemas to exclude from the query\n :param exclud... | def get_all_tables(plpy_wrapper: 'plpy_wrapper.PLPYWrapper', exclude_schemas: Tuple[str]=(), exclude_tables: Tuple[str]=()) -> 'plpy_wrapper.ResultSet':
'Queries postgres for all tables\n\n :param plpy_wrapper: PLPYWrapper instance\n :param exclude_schemas: schemas to exclude from the query\n :param exclud... |
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