body stringlengths 26 98.2k | body_hash int64 -9,222,864,604,528,158,000 9,221,803,474B | docstring stringlengths 1 16.8k | path stringlengths 5 230 | name stringlengths 1 96 | repository_name stringlengths 7 89 | lang stringclasses 1
value | body_without_docstring stringlengths 20 98.2k |
|---|---|---|---|---|---|---|---|
def _trusted_commit(self, committer_id, commit_type, commit_message, commit_cmds):
'Record the event to the commit log after the model commit.\n\n Note that this extends the superclass method.\n\n Args:\n committer_id: str. The user_id of the user who committed the\n change.\... | 8,086,757,080,571,136,000 | Record the event to the commit log after the model commit.
Note that this extends the superclass method.
Args:
committer_id: str. The user_id of the user who committed the
change.
commit_type: str. The type of commit. Possible values are in
core.storage.base_models.COMMIT_TYPE_CHOICES.
com... | core/domain/activity_jobs_one_off_test.py | _trusted_commit | AnanyaNegi/oppia | python | def _trusted_commit(self, committer_id, commit_type, commit_message, commit_cmds):
'Record the event to the commit log after the model commit.\n\n Note that this extends the superclass method.\n\n Args:\n committer_id: str. The user_id of the user who committed the\n change.\... |
def _trusted_commit(self, committer_id, commit_type, commit_message, commit_cmds):
'Record the event to the commit log after the model commit.\n\n Note that this extends the superclass method.\n\n Args:\n committer_id: str. The user_id of the user who committed the\n change.\... | 3,609,551,769,068,114,400 | Record the event to the commit log after the model commit.
Note that this extends the superclass method.
Args:
committer_id: str. The user_id of the user who committed the
change.
commit_type: str. The type of commit. Possible values are in
core.storage.base_models.COMMIT_TYPE_CHOICES.
com... | core/domain/activity_jobs_one_off_test.py | _trusted_commit | AnanyaNegi/oppia | python | def _trusted_commit(self, committer_id, commit_type, commit_message, commit_cmds):
'Record the event to the commit log after the model commit.\n\n Note that this extends the superclass method.\n\n Args:\n committer_id: str. The user_id of the user who committed the\n change.\... |
def _run_one_off_job(self):
'Runs the one-off MapReduce job.'
job_id = activity_jobs_one_off.AddContentUserIdsContentJob.create_new()
activity_jobs_one_off.AddContentUserIdsContentJob.enqueue(job_id)
self.assertEqual(self.count_jobs_in_mapreduce_taskqueue(taskqueue_services.QUEUE_NAME_ONE_OFF_JOBS), 1)
... | -5,408,814,941,831,667,000 | Runs the one-off MapReduce job. | core/domain/activity_jobs_one_off_test.py | _run_one_off_job | AnanyaNegi/oppia | python | def _run_one_off_job(self):
job_id = activity_jobs_one_off.AddContentUserIdsContentJob.create_new()
activity_jobs_one_off.AddContentUserIdsContentJob.enqueue(job_id)
self.assertEqual(self.count_jobs_in_mapreduce_taskqueue(taskqueue_services.QUEUE_NAME_ONE_OFF_JOBS), 1)
self.process_and_flush_pendin... |
def _run_one_off_job(self):
'Runs the one-off MapReduce job.'
job_id = activity_jobs_one_off.AddCommitCmdsUserIdsMetadataJob.create_new()
activity_jobs_one_off.AddCommitCmdsUserIdsMetadataJob.enqueue(job_id)
self.assertEqual(self.count_jobs_in_mapreduce_taskqueue(taskqueue_services.QUEUE_NAME_ONE_OFF_JO... | 5,209,690,579,846,129,000 | Runs the one-off MapReduce job. | core/domain/activity_jobs_one_off_test.py | _run_one_off_job | AnanyaNegi/oppia | python | def _run_one_off_job(self):
job_id = activity_jobs_one_off.AddCommitCmdsUserIdsMetadataJob.create_new()
activity_jobs_one_off.AddCommitCmdsUserIdsMetadataJob.enqueue(job_id)
self.assertEqual(self.count_jobs_in_mapreduce_taskqueue(taskqueue_services.QUEUE_NAME_ONE_OFF_JOBS), 1)
self.process_and_flus... |
def _run_one_off_job(self):
'Runs the one-off MapReduce job.'
job_id = activity_jobs_one_off.AuditSnapshotMetadataModelsJob.create_new()
activity_jobs_one_off.AuditSnapshotMetadataModelsJob.enqueue(job_id)
self.assertEqual(self.count_jobs_in_mapreduce_taskqueue(taskqueue_services.QUEUE_NAME_ONE_OFF_JOBS... | -3,907,230,091,904,724,000 | Runs the one-off MapReduce job. | core/domain/activity_jobs_one_off_test.py | _run_one_off_job | AnanyaNegi/oppia | python | def _run_one_off_job(self):
job_id = activity_jobs_one_off.AuditSnapshotMetadataModelsJob.create_new()
activity_jobs_one_off.AuditSnapshotMetadataModelsJob.enqueue(job_id)
self.assertEqual(self.count_jobs_in_mapreduce_taskqueue(taskqueue_services.QUEUE_NAME_ONE_OFF_JOBS), 1)
self.process_and_flush_... |
def _run_one_off_job(self):
'Runs the one-off MapReduce job.'
job_class = activity_jobs_one_off.ValidateSnapshotMetadataModelsJob
job_id = job_class.create_new()
activity_jobs_one_off.ValidateSnapshotMetadataModelsJob.enqueue(job_id)
self.assertEqual(self.count_jobs_in_mapreduce_taskqueue(taskqueue_... | 9,207,150,648,411,642,000 | Runs the one-off MapReduce job. | core/domain/activity_jobs_one_off_test.py | _run_one_off_job | AnanyaNegi/oppia | python | def _run_one_off_job(self):
job_class = activity_jobs_one_off.ValidateSnapshotMetadataModelsJob
job_id = job_class.create_new()
activity_jobs_one_off.ValidateSnapshotMetadataModelsJob.enqueue(job_id)
self.assertEqual(self.count_jobs_in_mapreduce_taskqueue(taskqueue_services.QUEUE_NAME_ONE_OFF_JOBS)... |
def clean_str(string):
'\n Tokenization/string cleaning for all datasets except for SST.\n Original taken from https://github.com/yoonkim/CNN_sentence/blob/master/process_data.py\n '
string = re.sub("[^A-Za-z0-9(),!?\\'\\`]", ' ', string)
string = re.sub("\\'s", " 's", string)
string = re.sub("... | 6,380,898,887,572,334,000 | Tokenization/string cleaning for all datasets except for SST.
Original taken from https://github.com/yoonkim/CNN_sentence/blob/master/process_data.py | data_helpers.py | clean_str | pychuang/ist557-data-mining-cnn | python | def clean_str(string):
'\n Tokenization/string cleaning for all datasets except for SST.\n Original taken from https://github.com/yoonkim/CNN_sentence/blob/master/process_data.py\n '
string = re.sub("[^A-Za-z0-9(),!?\\'\\`]", ' ', string)
string = re.sub("\\'s", " 's", string)
string = re.sub("... |
def load_data_and_labels(data_file):
'\n Loads MR polarity data from files, splits the data into words and generates labels.\n Returns split sentences and labels.\n '
datapoints = load_datapoints(data_file)
x_text = extract_phrases_in_datapoints(datapoints)
y = [int(dp.Sentiment) for dp in data... | 4,745,854,949,447,349,000 | Loads MR polarity data from files, splits the data into words and generates labels.
Returns split sentences and labels. | data_helpers.py | load_data_and_labels | pychuang/ist557-data-mining-cnn | python | def load_data_and_labels(data_file):
'\n Loads MR polarity data from files, splits the data into words and generates labels.\n Returns split sentences and labels.\n '
datapoints = load_datapoints(data_file)
x_text = extract_phrases_in_datapoints(datapoints)
y = [int(dp.Sentiment) for dp in data... |
def batch_iter(data, batch_size, num_epochs, shuffle=True):
'\n Generates a batch iterator for a dataset.\n '
data = np.array(data)
data_size = len(data)
num_batches_per_epoch = (int((len(data) / batch_size)) + 1)
for epoch in range(num_epochs):
if shuffle:
shuffle_indices ... | 6,353,081,854,038,388,000 | Generates a batch iterator for a dataset. | data_helpers.py | batch_iter | pychuang/ist557-data-mining-cnn | python | def batch_iter(data, batch_size, num_epochs, shuffle=True):
'\n \n '
data = np.array(data)
data_size = len(data)
num_batches_per_epoch = (int((len(data) / batch_size)) + 1)
for epoch in range(num_epochs):
if shuffle:
shuffle_indices = np.random.permutation(np.arange(data_si... |
def test_tabs(self):
'Test tabs functionality'
text = '\t\tHello'
expected = '\t\t'
got = get_leading_whitespace(text)
assert (expected == got) | -2,184,680,040,339,133,400 | Test tabs functionality | tests/test_utils.py | test_tabs | lukerm48/dyc | python | def test_tabs(self):
text = '\t\tHello'
expected = '\t\t'
got = get_leading_whitespace(text)
assert (expected == got) |
def test_whitespace(self):
'Test whitespace functionality'
space = ' '
text = '{space}Such a long whitespace'.format(space=space)
expected = space
got = get_leading_whitespace(text)
assert (expected == got) | 4,380,228,456,149,272,600 | Test whitespace functionality | tests/test_utils.py | test_whitespace | lukerm48/dyc | python | def test_whitespace(self):
space = ' '
text = '{space}Such a long whitespace'.format(space=space)
expected = space
got = get_leading_whitespace(text)
assert (expected == got) |
def test_valid_comments(self):
'Testing valid comments'
text = '# Hello World'
assert (is_comment(text, ['#']) == True) | -3,741,295,515,058,425,000 | Testing valid comments | tests/test_utils.py | test_valid_comments | lukerm48/dyc | python | def test_valid_comments(self):
text = '# Hello World'
assert (is_comment(text, ['#']) == True) |
def test_invalid_comments(self):
'Testing invalid comments'
text = '# Hello World'
assert (is_comment(text, ['//']) == False) | -2,414,815,970,119,370,000 | Testing invalid comments | tests/test_utils.py | test_invalid_comments | lukerm48/dyc | python | def test_invalid_comments(self):
text = '# Hello World'
assert (is_comment(text, ['//']) == False) |
def load_preprocessed_data(self):
'\n raw_data is a list that has three components\n component1) trajectory data for training\n component2) trajectory data for validation and visualization\n '
f = open(self.dataset_path, 'rb')
raw_data = pickle.load(f)
f.close()
counter =... | -470,723,059,986,581,900 | raw_data is a list that has three components
component1) trajectory data for training
component2) trajectory data for validation and visualization | kitti_utils.py | load_preprocessed_data | d1024choi/trajpred_irl | python | def load_preprocessed_data(self):
'\n raw_data is a list that has three components\n component1) trajectory data for training\n component2) trajectory data for validation and visualization\n '
f = open(self.dataset_path, 'rb')
raw_data = pickle.load(f)
f.close()
counter =... |
def preprocess_sequence(self, seq, isValid, isDiff):
'\n dataset id (0)\n object id (1)\n target pose (2~3)\n neighbor pose (4~63)\n '
seq_len = seq.shape[0]
seq_tpose = np.copy(seq[:, 2:4])
seq_npose = np.copy(seq[:, 4:64]).reshape(seq_len, 30, 2)
dataset_index = ... | 4,740,553,938,265,372,000 | dataset id (0)
object id (1)
target pose (2~3)
neighbor pose (4~63) | kitti_utils.py | preprocess_sequence | d1024choi/trajpred_irl | python | def preprocess_sequence(self, seq, isValid, isDiff):
'\n dataset id (0)\n object id (1)\n target pose (2~3)\n neighbor pose (4~63)\n '
seq_len = seq.shape[0]
seq_tpose = np.copy(seq[:, 2:4])
seq_npose = np.copy(seq[:, 4:64]).reshape(seq_len, 30, 2)
dataset_index = ... |
def next_batch(self):
'\n Read a batch randomly\n :x_batch: <batch size x seq_length x input_dim>\n :y_batch: <batch size x seq_length x input_dim>\n :d_batch: <batch size x seq_length>\n '
x_batch = []
y_batch = []
sg_batch = []
map_batch = []
d_batch = []
... | -7,187,001,706,206,327,000 | Read a batch randomly
:x_batch: <batch size x seq_length x input_dim>
:y_batch: <batch size x seq_length x input_dim>
:d_batch: <batch size x seq_length> | kitti_utils.py | next_batch | d1024choi/trajpred_irl | python | def next_batch(self):
'\n Read a batch randomly\n :x_batch: <batch size x seq_length x input_dim>\n :y_batch: <batch size x seq_length x input_dim>\n :d_batch: <batch size x seq_length>\n '
x_batch = []
y_batch = []
sg_batch = []
map_batch = []
d_batch = []
... |
def next_batch_valid(self):
'\n Read a batch randomly for validation during training\n :x_batch: <batch size x seq_length x input_dim>\n :y_batch: <batch size x seq_length x input_dim>\n :d_batch: <batch size x seq_length>\n '
x_batch = []
y_batch = []
sg_batch = []
... | -2,475,856,481,739,356,000 | Read a batch randomly for validation during training
:x_batch: <batch size x seq_length x input_dim>
:y_batch: <batch size x seq_length x input_dim>
:d_batch: <batch size x seq_length> | kitti_utils.py | next_batch_valid | d1024choi/trajpred_irl | python | def next_batch_valid(self):
'\n Read a batch randomly for validation during training\n :x_batch: <batch size x seq_length x input_dim>\n :y_batch: <batch size x seq_length x input_dim>\n :d_batch: <batch size x seq_length>\n '
x_batch = []
y_batch = []
sg_batch = []
... |
def next_sequence_valid(self):
'\n\n dataset id (0)\n object id (1)\n target pose (2~3)\n neighbor pose (4~63)\n\n Read a batch randomly for validation and visualization\n :x_batch: <batch size x seq_length x input_dim>\n :y_batch: <batch size x seq_length x input_di... | 7,151,321,459,105,572,000 | dataset id (0)
object id (1)
target pose (2~3)
neighbor pose (4~63)
Read a batch randomly for validation and visualization
:x_batch: <batch size x seq_length x input_dim>
:y_batch: <batch size x seq_length x input_dim>
:d_batch: <batch size x seq_length> | kitti_utils.py | next_sequence_valid | d1024choi/trajpred_irl | python | def next_sequence_valid(self):
'\n\n dataset id (0)\n object id (1)\n target pose (2~3)\n neighbor pose (4~63)\n\n Read a batch randomly for validation and visualization\n :x_batch: <batch size x seq_length x input_dim>\n :y_batch: <batch size x seq_length x input_di... |
def _load_from_socket(port, auth_secret):
'\n Load data from a given socket, this is a blocking method thus only return when the socket\n connection has been closed.\n '
(sockfile, sock) = local_connect_and_auth(port, auth_secret)
sock.settimeout(None)
write_int(BARRIER_FUNCTION, sockfile)
... | 4,420,216,276,343,981,000 | Load data from a given socket, this is a blocking method thus only return when the socket
connection has been closed. | python/pyspark/taskcontext.py | _load_from_socket | 2RedSquares/spark | python | def _load_from_socket(port, auth_secret):
'\n Load data from a given socket, this is a blocking method thus only return when the socket\n connection has been closed.\n '
(sockfile, sock) = local_connect_and_auth(port, auth_secret)
sock.settimeout(None)
write_int(BARRIER_FUNCTION, sockfile)
... |
def __new__(cls):
'Even if users construct TaskContext instead of using get, give them the singleton.'
taskContext = cls._taskContext
if (taskContext is not None):
return taskContext
cls._taskContext = taskContext = object.__new__(cls)
return taskContext | 3,980,086,144,201,819,600 | Even if users construct TaskContext instead of using get, give them the singleton. | python/pyspark/taskcontext.py | __new__ | 2RedSquares/spark | python | def __new__(cls):
taskContext = cls._taskContext
if (taskContext is not None):
return taskContext
cls._taskContext = taskContext = object.__new__(cls)
return taskContext |
@classmethod
def _getOrCreate(cls):
'Internal function to get or create global TaskContext.'
if (cls._taskContext is None):
cls._taskContext = TaskContext()
return cls._taskContext | 6,418,743,054,464,887,000 | Internal function to get or create global TaskContext. | python/pyspark/taskcontext.py | _getOrCreate | 2RedSquares/spark | python | @classmethod
def _getOrCreate(cls):
if (cls._taskContext is None):
cls._taskContext = TaskContext()
return cls._taskContext |
@classmethod
def get(cls):
'\n Return the currently active TaskContext. This can be called inside of\n user functions to access contextual information about running tasks.\n\n .. note:: Must be called on the worker, not the driver. Returns None if not initialized.\n '
return cls._tas... | 1,419,744,605,024,734,200 | Return the currently active TaskContext. This can be called inside of
user functions to access contextual information about running tasks.
.. note:: Must be called on the worker, not the driver. Returns None if not initialized. | python/pyspark/taskcontext.py | get | 2RedSquares/spark | python | @classmethod
def get(cls):
'\n Return the currently active TaskContext. This can be called inside of\n user functions to access contextual information about running tasks.\n\n .. note:: Must be called on the worker, not the driver. Returns None if not initialized.\n '
return cls._tas... |
def stageId(self):
'The ID of the stage that this task belong to.'
return self._stageId | -8,501,152,381,933,950,000 | The ID of the stage that this task belong to. | python/pyspark/taskcontext.py | stageId | 2RedSquares/spark | python | def stageId(self):
return self._stageId |
def partitionId(self):
'\n The ID of the RDD partition that is computed by this task.\n '
return self._partitionId | 4,923,525,649,721,193,000 | The ID of the RDD partition that is computed by this task. | python/pyspark/taskcontext.py | partitionId | 2RedSquares/spark | python | def partitionId(self):
'\n \n '
return self._partitionId |
def attemptNumber(self):
'"\n How many times this task has been attempted. The first task attempt will be assigned\n attemptNumber = 0, and subsequent attempts will have increasing attempt numbers.\n '
return self._attemptNumber | 8,904,765,901,230,001,000 | "
How many times this task has been attempted. The first task attempt will be assigned
attemptNumber = 0, and subsequent attempts will have increasing attempt numbers. | python/pyspark/taskcontext.py | attemptNumber | 2RedSquares/spark | python | def attemptNumber(self):
'"\n How many times this task has been attempted. The first task attempt will be assigned\n attemptNumber = 0, and subsequent attempts will have increasing attempt numbers.\n '
return self._attemptNumber |
def taskAttemptId(self):
"\n An ID that is unique to this task attempt (within the same SparkContext, no two task\n attempts will share the same attempt ID). This is roughly equivalent to Hadoop's\n TaskAttemptID.\n "
return self._taskAttemptId | -2,749,768,595,232,958,500 | An ID that is unique to this task attempt (within the same SparkContext, no two task
attempts will share the same attempt ID). This is roughly equivalent to Hadoop's
TaskAttemptID. | python/pyspark/taskcontext.py | taskAttemptId | 2RedSquares/spark | python | def taskAttemptId(self):
"\n An ID that is unique to this task attempt (within the same SparkContext, no two task\n attempts will share the same attempt ID). This is roughly equivalent to Hadoop's\n TaskAttemptID.\n "
return self._taskAttemptId |
def getLocalProperty(self, key):
'\n Get a local property set upstream in the driver, or None if it is missing.\n '
return self._localProperties.get(key, None) | -8,642,961,275,192,264,000 | Get a local property set upstream in the driver, or None if it is missing. | python/pyspark/taskcontext.py | getLocalProperty | 2RedSquares/spark | python | def getLocalProperty(self, key):
'\n \n '
return self._localProperties.get(key, None) |
def resources(self):
'\n Resources allocated to the task. The key is the resource name and the value is information\n about the resource.\n '
return self._resources | -8,342,268,450,500,635,000 | Resources allocated to the task. The key is the resource name and the value is information
about the resource. | python/pyspark/taskcontext.py | resources | 2RedSquares/spark | python | def resources(self):
'\n Resources allocated to the task. The key is the resource name and the value is information\n about the resource.\n '
return self._resources |
@classmethod
def _getOrCreate(cls):
'\n Internal function to get or create global BarrierTaskContext. We need to make sure\n BarrierTaskContext is returned from here because it is needed in python worker reuse\n scenario, see SPARK-25921 for more details.\n '
if (not isinstance(cls._... | 2,762,703,837,966,486,500 | Internal function to get or create global BarrierTaskContext. We need to make sure
BarrierTaskContext is returned from here because it is needed in python worker reuse
scenario, see SPARK-25921 for more details. | python/pyspark/taskcontext.py | _getOrCreate | 2RedSquares/spark | python | @classmethod
def _getOrCreate(cls):
'\n Internal function to get or create global BarrierTaskContext. We need to make sure\n BarrierTaskContext is returned from here because it is needed in python worker reuse\n scenario, see SPARK-25921 for more details.\n '
if (not isinstance(cls._... |
@classmethod
def get(cls):
'\n .. note:: Experimental\n\n Return the currently active :class:`BarrierTaskContext`.\n This can be called inside of user functions to access contextual information about\n running tasks.\n\n .. note:: Must be called on the worker, not the driver. Retu... | 8,051,729,507,975,203,000 | .. note:: Experimental
Return the currently active :class:`BarrierTaskContext`.
This can be called inside of user functions to access contextual information about
running tasks.
.. note:: Must be called on the worker, not the driver. Returns None if not initialized. | python/pyspark/taskcontext.py | get | 2RedSquares/spark | python | @classmethod
def get(cls):
'\n .. note:: Experimental\n\n Return the currently active :class:`BarrierTaskContext`.\n This can be called inside of user functions to access contextual information about\n running tasks.\n\n .. note:: Must be called on the worker, not the driver. Retu... |
@classmethod
def _initialize(cls, port, secret):
'\n Initialize BarrierTaskContext, other methods within BarrierTaskContext can only be called\n after BarrierTaskContext is initialized.\n '
cls._port = port
cls._secret = secret | -1,927,426,430,799,265,000 | Initialize BarrierTaskContext, other methods within BarrierTaskContext can only be called
after BarrierTaskContext is initialized. | python/pyspark/taskcontext.py | _initialize | 2RedSquares/spark | python | @classmethod
def _initialize(cls, port, secret):
'\n Initialize BarrierTaskContext, other methods within BarrierTaskContext can only be called\n after BarrierTaskContext is initialized.\n '
cls._port = port
cls._secret = secret |
def barrier(self):
'\n .. note:: Experimental\n\n Sets a global barrier and waits until all tasks in this stage hit this barrier.\n Similar to `MPI_Barrier` function in MPI, this function blocks until all tasks\n in the same stage have reached this routine.\n\n .. warning:: In a b... | -5,306,368,122,698,499,000 | .. note:: Experimental
Sets a global barrier and waits until all tasks in this stage hit this barrier.
Similar to `MPI_Barrier` function in MPI, this function blocks until all tasks
in the same stage have reached this routine.
.. warning:: In a barrier stage, each task much have the same number of `barrier()`
cal... | python/pyspark/taskcontext.py | barrier | 2RedSquares/spark | python | def barrier(self):
'\n .. note:: Experimental\n\n Sets a global barrier and waits until all tasks in this stage hit this barrier.\n Similar to `MPI_Barrier` function in MPI, this function blocks until all tasks\n in the same stage have reached this routine.\n\n .. warning:: In a b... |
def getTaskInfos(self):
'\n .. note:: Experimental\n\n Returns :class:`BarrierTaskInfo` for all tasks in this barrier stage,\n ordered by partition ID.\n\n .. versionadded:: 2.4.0\n '
if ((self._port is None) or (self._secret is None)):
raise Exception(('Not supported ... | 855,620,321,117,693,600 | .. note:: Experimental
Returns :class:`BarrierTaskInfo` for all tasks in this barrier stage,
ordered by partition ID.
.. versionadded:: 2.4.0 | python/pyspark/taskcontext.py | getTaskInfos | 2RedSquares/spark | python | def getTaskInfos(self):
'\n .. note:: Experimental\n\n Returns :class:`BarrierTaskInfo` for all tasks in this barrier stage,\n ordered by partition ID.\n\n .. versionadded:: 2.4.0\n '
if ((self._port is None) or (self._secret is None)):
raise Exception(('Not supported ... |
def run_test(self):
'Main test logic'
cli_response = self.nodes[0].cli('-version').send_cli()
assert ('Deepcoin Core RPC client version' in cli_response)
self.log.info('Compare responses from gewalletinfo RPC and `deepcoin-cli getwalletinfo`')
cli_response = self.nodes[0].cli.getwalletinfo()
rpc... | 1,788,795,389,587,930,000 | Main test logic | test/functional/interface_deepcoin_cli.py | run_test | deepcoindev2/Deepcoin | python | def run_test(self):
cli_response = self.nodes[0].cli('-version').send_cli()
assert ('Deepcoin Core RPC client version' in cli_response)
self.log.info('Compare responses from gewalletinfo RPC and `deepcoin-cli getwalletinfo`')
cli_response = self.nodes[0].cli.getwalletinfo()
rpc_response = self.... |
def __init__(self):
'FlatLocales - a model defined in OpenAPI'
self.discriminator = None | 2,601,218,367,010,354,000 | FlatLocales - a model defined in OpenAPI | flat_api/models/flat_locales.py | __init__ | FlatIO/api-client-python | python | def __init__(self):
self.discriminator = None |
def to_dict(self):
'Returns the model properties as a dict'
result = {}
for (attr, _) in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map((lambda x: (x.to_dict() if hasattr(x, 'to_dict') else x)), value))
e... | 8,442,519,487,048,767,000 | Returns the model properties as a dict | flat_api/models/flat_locales.py | to_dict | FlatIO/api-client-python | python | def to_dict(self):
result = {}
for (attr, _) in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map((lambda x: (x.to_dict() if hasattr(x, 'to_dict') else x)), value))
elif hasattr(value, 'to_dict'):
... |
def to_str(self):
'Returns the string representation of the model'
return pprint.pformat(self.to_dict()) | 5,849,158,643,760,736,000 | Returns the string representation of the model | flat_api/models/flat_locales.py | to_str | FlatIO/api-client-python | python | def to_str(self):
return pprint.pformat(self.to_dict()) |
def __repr__(self):
'For `print` and `pprint`'
return self.to_str() | -8,960,031,694,814,905,000 | For `print` and `pprint` | flat_api/models/flat_locales.py | __repr__ | FlatIO/api-client-python | python | def __repr__(self):
return self.to_str() |
def __eq__(self, other):
'Returns true if both objects are equal'
if (not isinstance(other, FlatLocales)):
return False
return (self.__dict__ == other.__dict__) | 8,377,921,118,189,592,000 | Returns true if both objects are equal | flat_api/models/flat_locales.py | __eq__ | FlatIO/api-client-python | python | def __eq__(self, other):
if (not isinstance(other, FlatLocales)):
return False
return (self.__dict__ == other.__dict__) |
def __ne__(self, other):
'Returns true if both objects are not equal'
return (not (self == other)) | 7,764,124,047,908,058,000 | Returns true if both objects are not equal | flat_api/models/flat_locales.py | __ne__ | FlatIO/api-client-python | python | def __ne__(self, other):
return (not (self == other)) |
def child(self, index):
'Returns the child HDPrivateKey at a particular index.\n Hardened children return for indices >= 0x8000000.\n '
if (index >= 2147483648):
data = (int_to_big_endian(self.private_key.secret, 33) + int_to_big_endian(index, 4))
else:
data = (self.private_key... | 7,838,682,160,407,161,000 | Returns the child HDPrivateKey at a particular index.
Hardened children return for indices >= 0x8000000. | session6/hd.py | child | jimmysong/pw-exercises | python | def child(self, index):
'Returns the child HDPrivateKey at a particular index.\n Hardened children return for indices >= 0x8000000.\n '
if (index >= 2147483648):
data = (int_to_big_endian(self.private_key.secret, 33) + int_to_big_endian(index, 4))
else:
data = (self.private_key... |
def traverse(self, path):
"Returns the HDPrivateKey at the path indicated.\n Path should be in the form of m/x/y/z where x' means\n hardened"
current = self
components = path.split('/')[1:]
for child in components:
if child.endswith("'"):
index = (int(child[:(- 1)]) + 2... | 924,929,705,790,682,600 | Returns the HDPrivateKey at the path indicated.
Path should be in the form of m/x/y/z where x' means
hardened | session6/hd.py | traverse | jimmysong/pw-exercises | python | def traverse(self, path):
"Returns the HDPrivateKey at the path indicated.\n Path should be in the form of m/x/y/z where x' means\n hardened"
current = self
components = path.split('/')[1:]
for child in components:
if child.endswith("'"):
index = (int(child[:(- 1)]) + 2... |
def _prv(self, version):
'Returns the base58-encoded x/y/z prv.\n Expects a 4-byte version.'
raw = self.raw_serialize(version)
return encode_base58_checksum(raw) | 2,242,973,465,055,090,200 | Returns the base58-encoded x/y/z prv.
Expects a 4-byte version. | session6/hd.py | _prv | jimmysong/pw-exercises | python | def _prv(self, version):
'Returns the base58-encoded x/y/z prv.\n Expects a 4-byte version.'
raw = self.raw_serialize(version)
return encode_base58_checksum(raw) |
@classmethod
def parse(cls, s):
'Returns a HDPrivateKey from an extended key string'
raw = raw_decode_base58(s)
if (len(raw) != 78):
raise ValueError('Not a proper extended key')
stream = BytesIO(raw)
return cls.raw_parse(stream) | -3,830,092,010,722,180,600 | Returns a HDPrivateKey from an extended key string | session6/hd.py | parse | jimmysong/pw-exercises | python | @classmethod
def parse(cls, s):
raw = raw_decode_base58(s)
if (len(raw) != 78):
raise ValueError('Not a proper extended key')
stream = BytesIO(raw)
return cls.raw_parse(stream) |
@classmethod
def raw_parse(cls, s):
'Returns a HDPrivateKey from a stream'
version = s.read(4)
if (version in (TESTNET_XPRV, TESTNET_YPRV, TESTNET_ZPRV)):
testnet = True
elif (version in (MAINNET_XPRV, MAINNET_YPRV, MAINNET_ZPRV)):
testnet = False
else:
raise ValueError('not ... | 1,832,675,882,951,446,000 | Returns a HDPrivateKey from a stream | session6/hd.py | raw_parse | jimmysong/pw-exercises | python | @classmethod
def raw_parse(cls, s):
version = s.read(4)
if (version in (TESTNET_XPRV, TESTNET_YPRV, TESTNET_ZPRV)):
testnet = True
elif (version in (MAINNET_XPRV, MAINNET_YPRV, MAINNET_ZPRV)):
testnet = False
else:
raise ValueError('not an xprv, yprv or zprv: {}'.format(vers... |
def _get_address(self, purpose, account=0, external=True, address=0):
"Returns the proper address among purposes 44', 49' and 84'.\n p2pkh for 44', p2sh-p2wpkh for 49' and p2wpkh for 84'."
if (purpose not in ("44'", "49'", "84'")):
raise ValueError('Cannot create an address without a proper purpo... | 5,953,938,896,022,769,000 | Returns the proper address among purposes 44', 49' and 84'.
p2pkh for 44', p2sh-p2wpkh for 49' and p2wpkh for 84'. | session6/hd.py | _get_address | jimmysong/pw-exercises | python | def _get_address(self, purpose, account=0, external=True, address=0):
"Returns the proper address among purposes 44', 49' and 84'.\n p2pkh for 44', p2sh-p2wpkh for 49' and p2wpkh for 84'."
if (purpose not in ("44'", "49'", "84'")):
raise ValueError('Cannot create an address without a proper purpo... |
@classmethod
def from_mnemonic(cls, mnemonic, password=b'', path='m', testnet=False):
'Returns a HDPrivateKey object from the mnemonic.'
words = mnemonic.split()
if (len(words) not in (12, 15, 18, 21, 24)):
raise ValueError('you need 12, 15, 18, 21, or 24 words')
number = 0
for word in words... | 5,686,827,912,756,427,000 | Returns a HDPrivateKey object from the mnemonic. | session6/hd.py | from_mnemonic | jimmysong/pw-exercises | python | @classmethod
def from_mnemonic(cls, mnemonic, password=b, path='m', testnet=False):
words = mnemonic.split()
if (len(words) not in (12, 15, 18, 21, 24)):
raise ValueError('you need 12, 15, 18, 21, or 24 words')
number = 0
for word in words:
index = WORD_LOOKUP[word]
number =... |
def fingerprint(self):
"Fingerprint is the hash160's first 4 bytes"
return self.hash160()[:4] | 2,325,837,346,603,048,000 | Fingerprint is the hash160's first 4 bytes | session6/hd.py | fingerprint | jimmysong/pw-exercises | python | def fingerprint(self):
return self.hash160()[:4] |
def child(self, index):
'Returns the child HDPrivateKey at a particular index.\n Raises ValueError for indices >= 0x8000000.\n '
if (index >= 2147483648):
raise ValueError('child number should always be less than 2^31')
data = (self.point.sec() + int_to_big_endian(index, 4))
h = hm... | 2,450,639,498,486,831,000 | Returns the child HDPrivateKey at a particular index.
Raises ValueError for indices >= 0x8000000. | session6/hd.py | child | jimmysong/pw-exercises | python | def child(self, index):
'Returns the child HDPrivateKey at a particular index.\n Raises ValueError for indices >= 0x8000000.\n '
if (index >= 2147483648):
raise ValueError('child number should always be less than 2^31')
data = (self.point.sec() + int_to_big_endian(index, 4))
h = hm... |
def traverse(self, path):
'Returns the HDPublicKey at the path indicated.\n Path should be in the form of m/x/y/z.'
current = self
components = path.split('/')[1:]
for child in components:
if (child[(- 1):] == "'"):
raise ValueError('HDPublicKey cannot get hardened child')
... | -492,497,757,683,349,200 | Returns the HDPublicKey at the path indicated.
Path should be in the form of m/x/y/z. | session6/hd.py | traverse | jimmysong/pw-exercises | python | def traverse(self, path):
'Returns the HDPublicKey at the path indicated.\n Path should be in the form of m/x/y/z.'
current = self
components = path.split('/')[1:]
for child in components:
if (child[(- 1):] == "'"):
raise ValueError('HDPublicKey cannot get hardened child')
... |
def _pub(self, version):
'Returns the base58-encoded x/y/z pub.\n Expects a 4-byte version.'
raw = self._serialize(version)
return encode_base58_checksum(raw) | -8,777,945,254,099,310,000 | Returns the base58-encoded x/y/z pub.
Expects a 4-byte version. | session6/hd.py | _pub | jimmysong/pw-exercises | python | def _pub(self, version):
'Returns the base58-encoded x/y/z pub.\n Expects a 4-byte version.'
raw = self._serialize(version)
return encode_base58_checksum(raw) |
@classmethod
def parse(cls, s):
'Returns a HDPublicKey from an extended key string'
raw = raw_decode_base58(s)
if (len(raw) != 78):
raise ValueError('Not a proper extended key')
stream = BytesIO(raw)
return cls.raw_parse(stream) | -348,898,283,253,583,100 | Returns a HDPublicKey from an extended key string | session6/hd.py | parse | jimmysong/pw-exercises | python | @classmethod
def parse(cls, s):
raw = raw_decode_base58(s)
if (len(raw) != 78):
raise ValueError('Not a proper extended key')
stream = BytesIO(raw)
return cls.raw_parse(stream) |
@classmethod
def raw_parse(cls, s):
'Returns a HDPublicKey from a stream'
version = s.read(4)
if (version in (TESTNET_XPUB, TESTNET_YPUB, TESTNET_ZPUB)):
testnet = True
elif (version in (MAINNET_XPUB, MAINNET_YPUB, MAINNET_ZPUB)):
testnet = False
else:
raise ValueError('not a... | 7,748,026,601,330,876,000 | Returns a HDPublicKey from a stream | session6/hd.py | raw_parse | jimmysong/pw-exercises | python | @classmethod
def raw_parse(cls, s):
version = s.read(4)
if (version in (TESTNET_XPUB, TESTNET_YPUB, TESTNET_ZPUB)):
testnet = True
elif (version in (MAINNET_XPUB, MAINNET_YPUB, MAINNET_ZPUB)):
testnet = False
else:
raise ValueError('not an xpub, ypub or zpub: {} {}'.format(s... |
@cached_property
def additional_properties_type():
'\n This must be a method because a model may have properties that are\n of type self, this must run after the class is loaded\n '
lazy_import()
return (bool, date, datetime, dict, float, int, list, str, none_type) | 1,702,168,743,392,494,600 | This must be a method because a model may have properties that are
of type self, this must run after the class is loaded | cryptoapis/model/list_assets_details_e400.py | additional_properties_type | Crypto-APIs/Crypto_APIs_2.0_SDK_Python | python | @cached_property
def additional_properties_type():
'\n This must be a method because a model may have properties that are\n of type self, this must run after the class is loaded\n '
lazy_import()
return (bool, date, datetime, dict, float, int, list, str, none_type) |
@cached_property
def openapi_types():
'\n This must be a method because a model may have properties that are\n of type self, this must run after the class is loaded\n\n Returns\n openapi_types (dict): The key is attribute name\n and the value is attribute type.\n ... | -5,576,899,373,819,436,000 | This must be a method because a model may have properties that are
of type self, this must run after the class is loaded
Returns
openapi_types (dict): The key is attribute name
and the value is attribute type. | cryptoapis/model/list_assets_details_e400.py | openapi_types | Crypto-APIs/Crypto_APIs_2.0_SDK_Python | python | @cached_property
def openapi_types():
'\n This must be a method because a model may have properties that are\n of type self, this must run after the class is loaded\n\n Returns\n openapi_types (dict): The key is attribute name\n and the value is attribute type.\n ... |
@classmethod
@convert_js_args_to_python_args
def _from_openapi_data(cls, *args, **kwargs):
'ListAssetsDetailsE400 - a model defined in OpenAPI\n\n Keyword Args:\n _check_type (bool): if True, values for parameters in openapi_types\n will be type checked and a TypeErr... | 2,020,670,956,389,146,600 | ListAssetsDetailsE400 - a model defined in OpenAPI
Keyword Args:
_check_type (bool): if True, values for parameters in openapi_types
will be type checked and a TypeError will be
raised if the wrong type is input.
Defaults to True
_path_to_... | cryptoapis/model/list_assets_details_e400.py | _from_openapi_data | Crypto-APIs/Crypto_APIs_2.0_SDK_Python | python | @classmethod
@convert_js_args_to_python_args
def _from_openapi_data(cls, *args, **kwargs):
'ListAssetsDetailsE400 - a model defined in OpenAPI\n\n Keyword Args:\n _check_type (bool): if True, values for parameters in openapi_types\n will be type checked and a TypeErr... |
@convert_js_args_to_python_args
def __init__(self, *args, **kwargs):
'ListAssetsDetailsE400 - a model defined in OpenAPI\n\n Keyword Args:\n _check_type (bool): if True, values for parameters in openapi_types\n will be type checked and a TypeError will be\n ... | -423,784,295,900,482,900 | ListAssetsDetailsE400 - a model defined in OpenAPI
Keyword Args:
_check_type (bool): if True, values for parameters in openapi_types
will be type checked and a TypeError will be
raised if the wrong type is input.
Defaults to True
_path_to_... | cryptoapis/model/list_assets_details_e400.py | __init__ | Crypto-APIs/Crypto_APIs_2.0_SDK_Python | python | @convert_js_args_to_python_args
def __init__(self, *args, **kwargs):
'ListAssetsDetailsE400 - a model defined in OpenAPI\n\n Keyword Args:\n _check_type (bool): if True, values for parameters in openapi_types\n will be type checked and a TypeError will be\n ... |
def __init__(self):
'\n Creates the himesis graph representing the AToM3 model HMM10_then1_IsolatedLHS.\n '
self.is_compiled = True
super(HMM10_then1_IsolatedLHS, self).__init__(name='HMM10_then1_IsolatedLHS', num_nodes=0, edges=[])
self.add_edges([])
self['mm__'] = ['MT_pre__F... | 8,705,714,719,552,520,000 | Creates the himesis graph representing the AToM3 model HMM10_then1_IsolatedLHS. | UMLRT2Kiltera_MM/Properties/from_thesis/HMM10_then1_IsolatedLHS.py | __init__ | levilucio/SyVOLT | python | def __init__(self):
'\n \n '
self.is_compiled = True
super(HMM10_then1_IsolatedLHS, self).__init__(name='HMM10_then1_IsolatedLHS', num_nodes=0, edges=[])
self.add_edges([])
self['mm__'] = ['MT_pre__FamiliesToPersonsMM', 'MoTifRule']
self['MT_constraint__'] = "#=============... |
def constraint(self, PreNode, graph):
'\n Executable constraint code.\n @param PreNode: Function taking an integer as parameter\n and returns the node corresponding to that label.\n '
return True | -9,135,366,208,570,063,000 | Executable constraint code.
@param PreNode: Function taking an integer as parameter
and returns the node corresponding to that label. | UMLRT2Kiltera_MM/Properties/from_thesis/HMM10_then1_IsolatedLHS.py | constraint | levilucio/SyVOLT | python | def constraint(self, PreNode, graph):
'\n Executable constraint code.\n @param PreNode: Function taking an integer as parameter\n and returns the node corresponding to that label.\n '
return True |
def read_symbols(executable, imports=True):
'\n Parse an ELF executable and return a list of (symbol,version) tuples\n for dynamic, imported symbols.\n '
p = subprocess.Popen([READELF_CMD, '--dyn-syms', '-W', executable], stdout=subprocess.PIPE, stderr=subprocess.PIPE, stdin=subprocess.PIPE)
(stdou... | -1,495,590,509,076,206,600 | Parse an ELF executable and return a list of (symbol,version) tuples
for dynamic, imported symbols. | contrib/devtools/symbol-check.py | read_symbols | bitcoinemxmx/GCX | python | def read_symbols(executable, imports=True):
'\n Parse an ELF executable and return a list of (symbol,version) tuples\n for dynamic, imported symbols.\n '
p = subprocess.Popen([READELF_CMD, '--dyn-syms', '-W', executable], stdout=subprocess.PIPE, stderr=subprocess.PIPE, stdin=subprocess.PIPE)
(stdou... |
def build(classifier, X, y=None):
'\n Inner build function that builds a single model.\n '
if isinstance(classifier, type):
classifier = classifier()
model = Pipeline([('preprocessor', NLTKPreprocessor()), ('vectorizer', TfidfVectorizer(tokenizer=identity, preprocessor=None, lowercase=... | 4,710,342,378,621,694,000 | Inner build function that builds a single model. | analyzer/build.py | build | shobhitagarwal1612/Emotion-Analysis | python | def build(classifier, X, y=None):
'\n \n '
if isinstance(classifier, type):
classifier = classifier()
model = Pipeline([('preprocessor', NLTKPreprocessor()), ('vectorizer', TfidfVectorizer(tokenizer=identity, preprocessor=None, lowercase=False)), ('classifier', classifier)])
model.... |
def test_toolchains(self):
'Try each toolchain'
for toolchain in fpgaperf.toolchains.keys():
(device, package) = def_devpack(toolchain)
fpgaperf.run(family='ice40', device=device, package=package, toolchain=toolchain, project=fpgaperf.get_project('oneblink'), verbose=self.verbose) | 8,048,555,090,105,903,000 | Try each toolchain | test/test_all.py | test_toolchains | arn4ud/fpga-tool-perf | python | def test_toolchains(self):
for toolchain in fpgaperf.toolchains.keys():
(device, package) = def_devpack(toolchain)
fpgaperf.run(family='ice40', device=device, package=package, toolchain=toolchain, project=fpgaperf.get_project('oneblink'), verbose=self.verbose) |
def test_pcf(self):
'Try each toolchain with a pcf'
for toolchain in fpgaperf.toolchains.keys():
(device, package) = def_devpack(toolchain)
if ('radiant' in toolchain):
pcf = (fpgaperf.root_dir + '/project/FIXME.pcf')
else:
pcf = (fpgaperf.root_dir + '/project/one... | -8,995,371,934,689,438,000 | Try each toolchain with a pcf | test/test_all.py | test_pcf | arn4ud/fpga-tool-perf | python | def test_pcf(self):
for toolchain in fpgaperf.toolchains.keys():
(device, package) = def_devpack(toolchain)
if ('radiant' in toolchain):
pcf = (fpgaperf.root_dir + '/project/FIXME.pcf')
else:
pcf = (fpgaperf.root_dir + '/project/oneblink_lp8k-cm81.pcf')
f... |
def test_seed(self):
'Try seeding, where possible'
random.seed(1234)
for toolchain in fpgaperf.get_seedable():
seed = random.randint(1, 2147483647)
(device, package) = def_devpack(toolchain)
fpgaperf.run(family='ice40', device=device, package=package, toolchain=toolchain, project=fpg... | 6,710,430,323,428,870,000 | Try seeding, where possible | test/test_all.py | test_seed | arn4ud/fpga-tool-perf | python | def test_seed(self):
random.seed(1234)
for toolchain in fpgaperf.get_seedable():
seed = random.randint(1, 2147483647)
(device, package) = def_devpack(toolchain)
fpgaperf.run(family='ice40', device=device, package=package, toolchain=toolchain, project=fpgaperf.get_project('oneblink')... |
def __init__(self, config, wsas_params, tmp_dir, nonstandard_residue_files, nonstandard_residue, ligand_topology, options=None, parameters=None):
'Wrapper for freesasa\n\n config: str\n Path to configuration file containing residue composition\n and atomic parameters - freesasa format.\... | 4,610,078,083,853,016,600 | Wrapper for freesasa
config: str
Path to configuration file containing residue composition
and atomic parameters - freesasa format.
options: dict, optional
Options to change how PDBs are parsed by freesasa.
parameters: dict, optional
Parameters to alter how freesasa computes surface area. | bac/analyse/wsas/freesasa_utils.py | __init__ | UCL-CCS/BAC2 | python | def __init__(self, config, wsas_params, tmp_dir, nonstandard_residue_files, nonstandard_residue, ligand_topology, options=None, parameters=None):
'Wrapper for freesasa\n\n config: str\n Path to configuration file containing residue composition\n and atomic parameters - freesasa format.\... |
def run(self, pdb):
'Run freesasa on provided PDB file\n\n Parameters\n ----------\n\n pdb: str\n Path to input PDB file\n\n Returns\n -------\n list\n SASA values for each atom of every model in the input PDB.\n\n '
structure_array = freesa... | 2,183,696,454,969,197,300 | Run freesasa on provided PDB file
Parameters
----------
pdb: str
Path to input PDB file
Returns
-------
list
SASA values for each atom of every model in the input PDB. | bac/analyse/wsas/freesasa_utils.py | run | UCL-CCS/BAC2 | python | def run(self, pdb):
'Run freesasa on provided PDB file\n\n Parameters\n ----------\n\n pdb: str\n Path to input PDB file\n\n Returns\n -------\n list\n SASA values for each atom of every model in the input PDB.\n\n '
structure_array = freesa... |
def _update_sasa_config(self, config, parameters, tmp_dir, nonstandard_residue_files, nonstandard_residue, ligand_topology):
'\n Add non-standard residues (including the ligand if a topology is\n provided for it) to the freesasa config file.\n\n Parameters\n ----------\n\n Notes\n... | -3,815,972,230,154,587,000 | Add non-standard residues (including the ligand if a topology is
provided for it) to the freesasa config file.
Parameters
----------
Notes
-----
Edited config files is saved in self.tmp_dir and
self.freesasa_config_file is updated to reflect this.
Returns
------- | bac/analyse/wsas/freesasa_utils.py | _update_sasa_config | UCL-CCS/BAC2 | python | def _update_sasa_config(self, config, parameters, tmp_dir, nonstandard_residue_files, nonstandard_residue, ligand_topology):
'\n Add non-standard residues (including the ligand if a topology is\n provided for it) to the freesasa config file.\n\n Parameters\n ----------\n\n Notes\n... |
@staticmethod
def _create_freesasa_section_text(new_residues, sasa_atom_params):
'\n Create text to add to freesasa configuration file to incorporate new residue.\n\n Parameters\n ----------\n new_residues : dict\n Non-standard residues to add to the freesasa config file.\n ... | 8,965,076,196,579,469,000 | Create text to add to freesasa configuration file to incorporate new residue.
Parameters
----------
new_residues : dict
Non-standard residues to add to the freesasa config file.
keys = residue names, values = atom name to type mapping (dict).
sasa_atom_params: dict
Maps atom type to properties needed by fr... | bac/analyse/wsas/freesasa_utils.py | _create_freesasa_section_text | UCL-CCS/BAC2 | python | @staticmethod
def _create_freesasa_section_text(new_residues, sasa_atom_params):
'\n Create text to add to freesasa configuration file to incorporate new residue.\n\n Parameters\n ----------\n new_residues : dict\n Non-standard residues to add to the freesasa config file.\n ... |
def _add_residues_freesasa_config_file(self, new_residues, new_filename, atom_params, orig_filename):
'\n Create a new freesasa config file that adds specified residue to the\n content of an existing copy.\n\n Parameters\n ----------\n new_residues : dict\n Non-standard... | 3,335,320,457,434,036,700 | Create a new freesasa config file that adds specified residue to the
content of an existing copy.
Parameters
----------
new_residues : dict
Non-standard residues to add to the freesasa config file.
keys = residue names, values = atom name to type mapping (dict).
new_filename: str
Filename to be used for th... | bac/analyse/wsas/freesasa_utils.py | _add_residues_freesasa_config_file | UCL-CCS/BAC2 | python | def _add_residues_freesasa_config_file(self, new_residues, new_filename, atom_params, orig_filename):
'\n Create a new freesasa config file that adds specified residue to the\n content of an existing copy.\n\n Parameters\n ----------\n new_residues : dict\n Non-standard... |
def splitlines_parser(data):
'A test parser that returns the input data, split by line.'
return data.splitlines() | 8,821,445,958,649,442,000 | A test parser that returns the input data, split by line. | tests/integrations/subprocess/test_Subprocess__parse_output.py | splitlines_parser | pybee/briefcase | python | def splitlines_parser(data):
return data.splitlines() |
def second_line_parser(data):
'A test parser that returns the second line of input.'
try:
return data.splitlines()[1]
except IndexError:
raise ParseError('Input does not contain 2 lines') | 5,938,198,887,935,977,000 | A test parser that returns the second line of input. | tests/integrations/subprocess/test_Subprocess__parse_output.py | second_line_parser | pybee/briefcase | python | def second_line_parser(data):
try:
return data.splitlines()[1]
except IndexError:
raise ParseError('Input does not contain 2 lines') |
def third_line_parser(data):
'A test parser that returns the third line of input.'
try:
return data.splitlines()[2]
except IndexError:
raise ParseError('Input does not contain 3 lines') | 1,768,642,836,130,958,300 | A test parser that returns the third line of input. | tests/integrations/subprocess/test_Subprocess__parse_output.py | third_line_parser | pybee/briefcase | python | def third_line_parser(data):
try:
return data.splitlines()[2]
except IndexError:
raise ParseError('Input does not contain 3 lines') |
def test_call(mock_sub, capsys):
'A simple call to check_output will be invoked.'
output = mock_sub.parse_output(splitlines_parser, ['hello', 'world'])
mock_sub._subprocess.check_output.assert_called_with(['hello', 'world'], text=True)
assert (capsys.readouterr().out == '')
assert (output == ['some ... | -9,145,021,900,062,871,000 | A simple call to check_output will be invoked. | tests/integrations/subprocess/test_Subprocess__parse_output.py | test_call | pybee/briefcase | python | def test_call(mock_sub, capsys):
output = mock_sub.parse_output(splitlines_parser, ['hello', 'world'])
mock_sub._subprocess.check_output.assert_called_with(['hello', 'world'], text=True)
assert (capsys.readouterr().out == )
assert (output == ['some output line 1', 'more output line 2']) |
def test_call_with_arg(mock_sub, capsys):
'Any extra keyword arguments are passed through as-is to check_output.'
output = mock_sub.parse_output(splitlines_parser, ['hello', 'world'], extra_arg='asdf')
mock_sub._subprocess.check_output.assert_called_with(['hello', 'world'], extra_arg='asdf', text=True)
... | -6,034,261,138,534,564,000 | Any extra keyword arguments are passed through as-is to check_output. | tests/integrations/subprocess/test_Subprocess__parse_output.py | test_call_with_arg | pybee/briefcase | python | def test_call_with_arg(mock_sub, capsys):
output = mock_sub.parse_output(splitlines_parser, ['hello', 'world'], extra_arg='asdf')
mock_sub._subprocess.check_output.assert_called_with(['hello', 'world'], extra_arg='asdf', text=True)
assert (capsys.readouterr().out == )
assert (output == ['some outpu... |
def test_call_with_parser_success(mock_sub, capsys):
"Parser returns expected portion of check_output's output."
output = mock_sub.parse_output(second_line_parser, ['hello', 'world'])
mock_sub._subprocess.check_output.assert_called_with(['hello', 'world'], text=True)
assert (output == 'more output line ... | -8,240,593,146,039,259,000 | Parser returns expected portion of check_output's output. | tests/integrations/subprocess/test_Subprocess__parse_output.py | test_call_with_parser_success | pybee/briefcase | python | def test_call_with_parser_success(mock_sub, capsys):
output = mock_sub.parse_output(second_line_parser, ['hello', 'world'])
mock_sub._subprocess.check_output.assert_called_with(['hello', 'world'], text=True)
assert (output == 'more output line 2') |
def test_call_with_parser_error(mock_sub, capsys):
'Parser errors on output from check_output.'
with pytest.raises(CommandOutputParseError, match='Unable to parse command output: Input does not contain 3 lines'):
mock_sub.parse_output(third_line_parser, ['hello', 'world'])
mock_sub._subprocess.check... | -4,493,378,662,148,309,000 | Parser errors on output from check_output. | tests/integrations/subprocess/test_Subprocess__parse_output.py | test_call_with_parser_error | pybee/briefcase | python | def test_call_with_parser_error(mock_sub, capsys):
with pytest.raises(CommandOutputParseError, match='Unable to parse command output: Input does not contain 3 lines'):
mock_sub.parse_output(third_line_parser, ['hello', 'world'])
mock_sub._subprocess.check_output.assert_called_with(['hello', 'world'... |
@pytest.mark.parametrize('in_kwargs, kwargs', [({}, {'text': True}), ({'text': True}, {'text': True}), ({'text': False}, {'text': False}), ({'universal_newlines': False}, {'universal_newlines': False}), ({'universal_newlines': True}, {'universal_newlines': True})])
def test_text_eq_true_default_overriding(mock_sub, in_... | -8,395,795,399,331,432,000 | if text or universal_newlines is explicitly provided, those should
override text=true default. | tests/integrations/subprocess/test_Subprocess__parse_output.py | test_text_eq_true_default_overriding | pybee/briefcase | python | @pytest.mark.parametrize('in_kwargs, kwargs', [({}, {'text': True}), ({'text': True}, {'text': True}), ({'text': False}, {'text': False}), ({'universal_newlines': False}, {'universal_newlines': False}), ({'universal_newlines': True}, {'universal_newlines': True})])
def test_text_eq_true_default_overriding(mock_sub, in_... |
def _execute(self, state: GlobalState) -> None:
'\n\n :param state:\n :return:\n '
if (state.get_current_instruction()['address'] in self.cache):
return
issues = self._analyze_state(state)
for issue in issues:
self.cache.add(issue.address)
self.issues.extend(issu... | -3,896,410,076,598,750,000 | :param state:
:return: | mythril/analysis/module/modules/dependence_on_predictable_vars.py | _execute | marcuswin/mythril | python | def _execute(self, state: GlobalState) -> None:
'\n\n :param state:\n :return:\n '
if (state.get_current_instruction()['address'] in self.cache):
return
issues = self._analyze_state(state)
for issue in issues:
self.cache.add(issue.address)
self.issues.extend(issu... |
@staticmethod
def _analyze_state(state: GlobalState) -> list:
'\n\n :param state:\n :return:\n '
issues = []
if is_prehook():
opcode = state.get_current_instruction()['opcode']
if (opcode in final_ops):
for annotation in state.annotations:
if ... | -7,975,389,300,939,921,000 | :param state:
:return: | mythril/analysis/module/modules/dependence_on_predictable_vars.py | _analyze_state | marcuswin/mythril | python | @staticmethod
def _analyze_state(state: GlobalState) -> list:
'\n\n :param state:\n :return:\n '
issues = []
if is_prehook():
opcode = state.get_current_instruction()['opcode']
if (opcode in final_ops):
for annotation in state.annotations:
if ... |
def test_sksurgerytextoverlay():
' Basic test to run the widget and make sure everything loads OK.'
if (sys.platform == 'darwin'):
pytest.skip('Test not working on Mac runner')
input_file = 'tests/data/test_video.avi'
gui = TextOverlayDemo(input_file)
gui.start() | 6,263,612,313,655,906,000 | Basic test to run the widget and make sure everything loads OK. | tests/test_sksurgerytextoverlay.py | test_sksurgerytextoverlay | SciKit-Surgery/scikit-surgeryutils | python | def test_sksurgerytextoverlay():
' '
if (sys.platform == 'darwin'):
pytest.skip('Test not working on Mac runner')
input_file = 'tests/data/test_video.avi'
gui = TextOverlayDemo(input_file)
gui.start() |
@skipIf((PSYCOPG2_VERSION < (2, 7)), 'SQL string composition not available in psycopg2<2.7')
def test_composed_query(self):
'Checks whether execution of composed SQL string is traced'
query = SQL(' union all ').join([SQL('select {} as x').format(Literal('one')), SQL('select {} as x').format(Literal('two'))])
... | 4,491,225,874,725,807,600 | Checks whether execution of composed SQL string is traced | tests/contrib/psycopg/test_psycopg.py | test_composed_query | discord/dd-trace-py | python | @skipIf((PSYCOPG2_VERSION < (2, 7)), 'SQL string composition not available in psycopg2<2.7')
def test_composed_query(self):
query = SQL(' union all ').join([SQL('select {} as x').format(Literal('one')), SQL('select {} as x').format(Literal('two'))])
db = self._get_conn()
with db.cursor() as cur:
... |
@skipIf((PSYCOPG2_VERSION < (2, 7)), 'SQL string composition not available in psycopg2<2.7')
def test_composed_query_identifier(self):
'Checks whether execution of composed SQL string is traced'
db = self._get_conn()
with db.cursor() as cur:
cur.execute('CREATE TEMP TABLE test (id serial PRIMARY KEY... | 6,862,115,182,421,737,000 | Checks whether execution of composed SQL string is traced | tests/contrib/psycopg/test_psycopg.py | test_composed_query_identifier | discord/dd-trace-py | python | @skipIf((PSYCOPG2_VERSION < (2, 7)), 'SQL string composition not available in psycopg2<2.7')
def test_composed_query_identifier(self):
db = self._get_conn()
with db.cursor() as cur:
cur.execute('CREATE TEMP TABLE test (id serial PRIMARY KEY, name varchar(12) NOT NULL UNIQUE);')
cur.execute(... |
@snapshot()
@skipIf((PSYCOPG2_VERSION < (2, 7)), 'SQL string composition not available in psycopg2<2.7')
def test_composed_query_encoding(self):
'Checks whether execution of composed SQL string is traced'
import logging
logger = logging.getLogger()
logger.level = logging.DEBUG
query = SQL(' union al... | 8,238,151,430,507,487,000 | Checks whether execution of composed SQL string is traced | tests/contrib/psycopg/test_psycopg.py | test_composed_query_encoding | discord/dd-trace-py | python | @snapshot()
@skipIf((PSYCOPG2_VERSION < (2, 7)), 'SQL string composition not available in psycopg2<2.7')
def test_composed_query_encoding(self):
import logging
logger = logging.getLogger()
logger.level = logging.DEBUG
query = SQL(' union all ').join([SQL("select 'one' as x"), SQL("select 'two' as x... |
@TracerTestCase.run_in_subprocess(env_overrides=dict(DD_SERVICE='mysvc'))
def test_user_specified_app_service(self):
'\n When a user specifies a service for the app\n The psycopg integration should not use it.\n '
from ddtrace import config
assert (config.service == 'mysvc')
con... | 4,316,217,354,407,632,400 | When a user specifies a service for the app
The psycopg integration should not use it. | tests/contrib/psycopg/test_psycopg.py | test_user_specified_app_service | discord/dd-trace-py | python | @TracerTestCase.run_in_subprocess(env_overrides=dict(DD_SERVICE='mysvc'))
def test_user_specified_app_service(self):
'\n When a user specifies a service for the app\n The psycopg integration should not use it.\n '
from ddtrace import config
assert (config.service == 'mysvc')
con... |
def dcan2fmriprepx(dcan_dir, out_dir, sub_id):
'\n dcan2fmriprep(dcan_dir,out_dir)\n '
sess = glob.glob((((dcan_dir + '/') + sub_id) + '/s*'))
ses_id = []
ses_id = [j.split('ses-')[1] for j in sess]
for ses in ses_id:
anat_dirx = (((((dcan_dir + '/') + sub_id) + '/ses-') + ses) + '/fil... | 8,666,387,277,339,448,000 | dcan2fmriprep(dcan_dir,out_dir) | xcp_abcd/utils/dcan2fmriprep.py | dcan2fmriprepx | PennLINC/xcp_abcd | python | def dcan2fmriprepx(dcan_dir, out_dir, sub_id):
'\n \n '
sess = glob.glob((((dcan_dir + '/') + sub_id) + '/s*'))
ses_id = []
ses_id = [j.split('ses-')[1] for j in sess]
for ses in ses_id:
anat_dirx = (((((dcan_dir + '/') + sub_id) + '/ses-') + ses) + '/files/MNINonLinear/')
anat... |
def copyfileobj_example(source, dest, buffer_size=((1024 * 1024) * 1024)):
' \n Copy a file from source to dest. source and dest\n must be file-like objects, i.e. any object with a read or\n write method, like for example StringIO.\n '
while True:
copy_buffer = source.read(buffer_size)
... | -4,312,684,828,816,021,500 | Copy a file from source to dest. source and dest
must be file-like objects, i.e. any object with a read or
write method, like for example StringIO. | xcp_abcd/utils/dcan2fmriprep.py | copyfileobj_example | PennLINC/xcp_abcd | python | def copyfileobj_example(source, dest, buffer_size=((1024 * 1024) * 1024)):
' \n Copy a file from source to dest. source and dest\n must be file-like objects, i.e. any object with a read or\n write method, like for example StringIO.\n '
while True:
copy_buffer = source.read(buffer_size)
... |
def forward(self, imgs, bboxes, labels, scale):
'Forward Faster R-CNN and calculate losses.\n\n Here are notations used.\n\n * :math:`N` is the batch size.\n * :math:`R` is the number of bounding boxes per image.\n\n Currently, only :math:`N=1` is supported.\n\n Args:\n ... | -7,758,097,655,763,915,000 | Forward Faster R-CNN and calculate losses.
Here are notations used.
* :math:`N` is the batch size.
* :math:`R` is the number of bounding boxes per image.
Currently, only :math:`N=1` is supported.
Args:
imgs (~torch.autograd.Variable): A variable with a batch of images.
bboxes (~torch.autograd.Variable): A b... | baseline/fast_rcnn/trainer.py | forward | ITMO-NSS-team/LightObjRecEnsembler | python | def forward(self, imgs, bboxes, labels, scale):
'Forward Faster R-CNN and calculate losses.\n\n Here are notations used.\n\n * :math:`N` is the batch size.\n * :math:`R` is the number of bounding boxes per image.\n\n Currently, only :math:`N=1` is supported.\n\n Args:\n ... |
def save(self, save_optimizer=False, save_path=None, **kwargs):
"serialize models include optimizer and other info\n return path where the model-file is stored.\n\n Args:\n save_optimizer (bool): whether save optimizer.state_dict().\n save_path (string): where to save model, if i... | -2,786,790,712,384,780,000 | serialize models include optimizer and other info
return path where the model-file is stored.
Args:
save_optimizer (bool): whether save optimizer.state_dict().
save_path (string): where to save model, if it's None, save_path
is generate using time str and info from kwargs.
Returns:
save_path(str):... | baseline/fast_rcnn/trainer.py | save | ITMO-NSS-team/LightObjRecEnsembler | python | def save(self, save_optimizer=False, save_path=None, **kwargs):
"serialize models include optimizer and other info\n return path where the model-file is stored.\n\n Args:\n save_optimizer (bool): whether save optimizer.state_dict().\n save_path (string): where to save model, if i... |
def get_object(self):
'\n retrieve auhtenticated user\n '
return self.request.user | -7,649,043,722,026,112,000 | retrieve auhtenticated user | app/user/views.py | get_object | xemperforya/recipe-app-api | python | def get_object(self):
'\n \n '
return self.request.user |
@distributed_trace
def list(self, **kwargs: Any) -> Iterable['_models.ManagedClusterSnapshotListResult']:
'Gets a list of managed cluster snapshots in the specified subscription.\n\n Gets a list of managed cluster snapshots in the specified subscription.\n\n :keyword callable cls: A custom type or fun... | -806,864,483,680,052,100 | Gets a list of managed cluster snapshots in the specified subscription.
Gets a list of managed cluster snapshots in the specified subscription.
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either ManagedClusterSnapshotListResult or the ... | src/aks-preview/azext_aks_preview/vendored_sdks/azure_mgmt_preview_aks/v2022_03_02_preview/operations/_managed_cluster_snapshots_operations.py | list | Hamster-Huey/azure-cli-extensions | python | @distributed_trace
def list(self, **kwargs: Any) -> Iterable['_models.ManagedClusterSnapshotListResult']:
'Gets a list of managed cluster snapshots in the specified subscription.\n\n Gets a list of managed cluster snapshots in the specified subscription.\n\n :keyword callable cls: A custom type or fun... |
@distributed_trace
def list_by_resource_group(self, resource_group_name: str, **kwargs: Any) -> Iterable['_models.ManagedClusterSnapshotListResult']:
'Lists managed cluster snapshots in the specified subscription and resource group.\n\n Lists managed cluster snapshots in the specified subscription and resour... | 6,987,555,572,338,603,000 | Lists managed cluster snapshots in the specified subscription and resource group.
Lists managed cluster snapshots in the specified subscription and resource group.
:param resource_group_name: The name of the resource group. The name is case insensitive.
:type resource_group_name: str
:keyword callable cls: A custom t... | src/aks-preview/azext_aks_preview/vendored_sdks/azure_mgmt_preview_aks/v2022_03_02_preview/operations/_managed_cluster_snapshots_operations.py | list_by_resource_group | Hamster-Huey/azure-cli-extensions | python | @distributed_trace
def list_by_resource_group(self, resource_group_name: str, **kwargs: Any) -> Iterable['_models.ManagedClusterSnapshotListResult']:
'Lists managed cluster snapshots in the specified subscription and resource group.\n\n Lists managed cluster snapshots in the specified subscription and resour... |
@distributed_trace
def get(self, resource_group_name: str, resource_name: str, **kwargs: Any) -> '_models.ManagedClusterSnapshot':
'Gets a managed cluster snapshot.\n\n Gets a managed cluster snapshot.\n\n :param resource_group_name: The name of the resource group. The name is case insensitive.\n ... | 3,540,760,310,827,036,000 | Gets a managed cluster snapshot.
Gets a managed cluster snapshot.
:param resource_group_name: The name of the resource group. The name is case insensitive.
:type resource_group_name: str
:param resource_name: The name of the managed cluster resource.
:type resource_name: str
:keyword callable cls: A custom type or fu... | src/aks-preview/azext_aks_preview/vendored_sdks/azure_mgmt_preview_aks/v2022_03_02_preview/operations/_managed_cluster_snapshots_operations.py | get | Hamster-Huey/azure-cli-extensions | python | @distributed_trace
def get(self, resource_group_name: str, resource_name: str, **kwargs: Any) -> '_models.ManagedClusterSnapshot':
'Gets a managed cluster snapshot.\n\n Gets a managed cluster snapshot.\n\n :param resource_group_name: The name of the resource group. The name is case insensitive.\n ... |
@distributed_trace
def create_or_update(self, resource_group_name: str, resource_name: str, parameters: '_models.ManagedClusterSnapshot', **kwargs: Any) -> '_models.ManagedClusterSnapshot':
'Creates or updates a managed cluster snapshot.\n\n Creates or updates a managed cluster snapshot.\n\n :param re... | 3,594,859,589,582,269,400 | Creates or updates a managed cluster snapshot.
Creates or updates a managed cluster snapshot.
:param resource_group_name: The name of the resource group. The name is case insensitive.
:type resource_group_name: str
:param resource_name: The name of the managed cluster resource.
:type resource_name: str
:param paramet... | src/aks-preview/azext_aks_preview/vendored_sdks/azure_mgmt_preview_aks/v2022_03_02_preview/operations/_managed_cluster_snapshots_operations.py | create_or_update | Hamster-Huey/azure-cli-extensions | python | @distributed_trace
def create_or_update(self, resource_group_name: str, resource_name: str, parameters: '_models.ManagedClusterSnapshot', **kwargs: Any) -> '_models.ManagedClusterSnapshot':
'Creates or updates a managed cluster snapshot.\n\n Creates or updates a managed cluster snapshot.\n\n :param re... |
@distributed_trace
def update_tags(self, resource_group_name: str, resource_name: str, parameters: '_models.TagsObject', **kwargs: Any) -> '_models.ManagedClusterSnapshot':
'Updates tags on a managed cluster snapshot.\n\n Updates tags on a managed cluster snapshot.\n\n :param resource_group_name: The ... | -3,153,889,745,219,867,000 | Updates tags on a managed cluster snapshot.
Updates tags on a managed cluster snapshot.
:param resource_group_name: The name of the resource group. The name is case insensitive.
:type resource_group_name: str
:param resource_name: The name of the managed cluster resource.
:type resource_name: str
:param parameters: P... | src/aks-preview/azext_aks_preview/vendored_sdks/azure_mgmt_preview_aks/v2022_03_02_preview/operations/_managed_cluster_snapshots_operations.py | update_tags | Hamster-Huey/azure-cli-extensions | python | @distributed_trace
def update_tags(self, resource_group_name: str, resource_name: str, parameters: '_models.TagsObject', **kwargs: Any) -> '_models.ManagedClusterSnapshot':
'Updates tags on a managed cluster snapshot.\n\n Updates tags on a managed cluster snapshot.\n\n :param resource_group_name: The ... |
@distributed_trace
def delete(self, resource_group_name: str, resource_name: str, **kwargs: Any) -> None:
'Deletes a managed cluster snapshot.\n\n Deletes a managed cluster snapshot.\n\n :param resource_group_name: The name of the resource group. The name is case insensitive.\n :type resource_g... | -6,312,127,759,750,229,000 | Deletes a managed cluster snapshot.
Deletes a managed cluster snapshot.
:param resource_group_name: The name of the resource group. The name is case insensitive.
:type resource_group_name: str
:param resource_name: The name of the managed cluster resource.
:type resource_name: str
:keyword callable cls: A custom type... | src/aks-preview/azext_aks_preview/vendored_sdks/azure_mgmt_preview_aks/v2022_03_02_preview/operations/_managed_cluster_snapshots_operations.py | delete | Hamster-Huey/azure-cli-extensions | python | @distributed_trace
def delete(self, resource_group_name: str, resource_name: str, **kwargs: Any) -> None:
'Deletes a managed cluster snapshot.\n\n Deletes a managed cluster snapshot.\n\n :param resource_group_name: The name of the resource group. The name is case insensitive.\n :type resource_g... |
@property
def is_terminal(self) -> bool:
'True if the current state is a terminal state.'
if (self.life_cycle_state not in RUN_LIFE_CYCLE_STATES):
raise AirflowException('Unexpected life cycle state: {}: If the state has been introduced recently, please check the Databricks user guide for troubleshootin... | 358,714,069,093,355,900 | True if the current state is a terminal state. | airflow/providers/databricks/hooks/databricks.py | is_terminal | AMS-Kepler/airflow | python | @property
def is_terminal(self) -> bool:
if (self.life_cycle_state not in RUN_LIFE_CYCLE_STATES):
raise AirflowException('Unexpected life cycle state: {}: If the state has been introduced recently, please check the Databricks user guide for troubleshooting information'.format(self.life_cycle_state))
... |
@property
def is_successful(self) -> bool:
'True if the result state is SUCCESS'
return (self.result_state == 'SUCCESS') | 4,436,874,940,241,474,000 | True if the result state is SUCCESS | airflow/providers/databricks/hooks/databricks.py | is_successful | AMS-Kepler/airflow | python | @property
def is_successful(self) -> bool:
return (self.result_state == 'SUCCESS') |
def run_now(self, json: dict) -> int:
'\n Utility function to call the ``api/2.0/jobs/run-now`` endpoint.\n\n :param json: The data used in the body of the request to the ``run-now`` endpoint.\n :return: the run_id as an int\n :rtype: str\n '
response = self._do_api_call(RUN_N... | -1,929,148,863,777,814,500 | Utility function to call the ``api/2.0/jobs/run-now`` endpoint.
:param json: The data used in the body of the request to the ``run-now`` endpoint.
:return: the run_id as an int
:rtype: str | airflow/providers/databricks/hooks/databricks.py | run_now | AMS-Kepler/airflow | python | def run_now(self, json: dict) -> int:
'\n Utility function to call the ``api/2.0/jobs/run-now`` endpoint.\n\n :param json: The data used in the body of the request to the ``run-now`` endpoint.\n :return: the run_id as an int\n :rtype: str\n '
response = self._do_api_call(RUN_N... |
def submit_run(self, json: dict) -> int:
'\n Utility function to call the ``api/2.0/jobs/runs/submit`` endpoint.\n\n :param json: The data used in the body of the request to the ``submit`` endpoint.\n :return: the run_id as an int\n :rtype: str\n '
response = self._do_api_call... | 6,492,600,274,998,970,000 | Utility function to call the ``api/2.0/jobs/runs/submit`` endpoint.
:param json: The data used in the body of the request to the ``submit`` endpoint.
:return: the run_id as an int
:rtype: str | airflow/providers/databricks/hooks/databricks.py | submit_run | AMS-Kepler/airflow | python | def submit_run(self, json: dict) -> int:
'\n Utility function to call the ``api/2.0/jobs/runs/submit`` endpoint.\n\n :param json: The data used in the body of the request to the ``submit`` endpoint.\n :return: the run_id as an int\n :rtype: str\n '
response = self._do_api_call... |
def list_jobs(self, limit: int=25, offset: int=0, expand_tasks: bool=False) -> List[Dict[(str, Any)]]:
'\n Lists the jobs in the Databricks Job Service.\n\n :param limit: The limit/batch size used to retrieve jobs.\n :param offset: The offset of the first job to return, relative to the most rec... | -2,245,901,606,107,715,300 | Lists the jobs in the Databricks Job Service.
:param limit: The limit/batch size used to retrieve jobs.
:param offset: The offset of the first job to return, relative to the most recently created job.
:param expand_tasks: Whether to include task and cluster details in the response.
:return: A list of jobs. | airflow/providers/databricks/hooks/databricks.py | list_jobs | AMS-Kepler/airflow | python | def list_jobs(self, limit: int=25, offset: int=0, expand_tasks: bool=False) -> List[Dict[(str, Any)]]:
'\n Lists the jobs in the Databricks Job Service.\n\n :param limit: The limit/batch size used to retrieve jobs.\n :param offset: The offset of the first job to return, relative to the most rec... |
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