nwo stringlengths 5 106 | sha stringlengths 40 40 | path stringlengths 4 174 | language stringclasses 1
value | identifier stringlengths 1 140 | parameters stringlengths 0 87.7k | argument_list stringclasses 1
value | return_statement stringlengths 0 426k | docstring stringlengths 0 64.3k | docstring_summary stringlengths 0 26.3k | docstring_tokens list | function stringlengths 18 4.83M | function_tokens list | url stringlengths 83 304 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
blurstudio/cross3d | 277968d1227de740fc87ef61005c75034420eadf | cross3d/abstract/abstractscenewrapper.py | python | AbstractSceneWrapper.property | (self, key, default=None) | return self._scene._fromNativeValue(self._nativeProperty(key, default)) | Return the value of the property defined by the inputed key | Return the value of the property defined by the inputed key | [
"Return",
"the",
"value",
"of",
"the",
"property",
"defined",
"by",
"the",
"inputed",
"key"
] | def property(self, key, default=None):
"""
Return the value of the property defined by the inputed key
"""
return self._scene._fromNativeValue(self._nativeProperty(key, default)) | [
"def",
"property",
"(",
"self",
",",
"key",
",",
"default",
"=",
"None",
")",
":",
"return",
"self",
".",
"_scene",
".",
"_fromNativeValue",
"(",
"self",
".",
"_nativeProperty",
"(",
"key",
",",
"default",
")",
")"
] | https://github.com/blurstudio/cross3d/blob/277968d1227de740fc87ef61005c75034420eadf/cross3d/abstract/abstractscenewrapper.py#L202-L207 | |
aim-uofa/AdelaiDet | fffb2ca1fbca88ec4d96e9ebc285bffe5027a947 | adet/modeling/MEInst/LME/utils.py | python | inverse_sigmoid | (x) | return y | Apply the inverse sigmoid operation.
y = -ln(1-x/x) | Apply the inverse sigmoid operation.
y = -ln(1-x/x) | [
"Apply",
"the",
"inverse",
"sigmoid",
"operation",
".",
"y",
"=",
"-",
"ln",
"(",
"1",
"-",
"x",
"/",
"x",
")"
] | def inverse_sigmoid(x):
"""Apply the inverse sigmoid operation.
y = -ln(1-x/x)
"""
y = -1 * np.log((1-x)/x)
return y | [
"def",
"inverse_sigmoid",
"(",
"x",
")",
":",
"y",
"=",
"-",
"1",
"*",
"np",
".",
"log",
"(",
"(",
"1",
"-",
"x",
")",
"/",
"x",
")",
"return",
"y"
] | https://github.com/aim-uofa/AdelaiDet/blob/fffb2ca1fbca88ec4d96e9ebc285bffe5027a947/adet/modeling/MEInst/LME/utils.py#L14-L19 | |
iiau-tracker/SPLT | a196e603798e9be969d9d985c087c11cad1cda43 | lib/object_detection/exporter.py | python | _write_frozen_graph | (frozen_graph_path, frozen_graph_def) | Writes frozen graph to disk.
Args:
frozen_graph_path: Path to write inference graph.
frozen_graph_def: tf.GraphDef holding frozen graph. | Writes frozen graph to disk. | [
"Writes",
"frozen",
"graph",
"to",
"disk",
"."
] | def _write_frozen_graph(frozen_graph_path, frozen_graph_def):
"""Writes frozen graph to disk.
Args:
frozen_graph_path: Path to write inference graph.
frozen_graph_def: tf.GraphDef holding frozen graph.
"""
with gfile.GFile(frozen_graph_path, 'wb') as f:
f.write(frozen_graph_def.SerializeToString())
logging.info('%d ops in the final graph.', len(frozen_graph_def.node)) | [
"def",
"_write_frozen_graph",
"(",
"frozen_graph_path",
",",
"frozen_graph_def",
")",
":",
"with",
"gfile",
".",
"GFile",
"(",
"frozen_graph_path",
",",
"'wb'",
")",
"as",
"f",
":",
"f",
".",
"write",
"(",
"frozen_graph_def",
".",
"SerializeToString",
"(",
")"... | https://github.com/iiau-tracker/SPLT/blob/a196e603798e9be969d9d985c087c11cad1cda43/lib/object_detection/exporter.py#L225-L234 | ||
OpenMined/PySyft | f181ca02d307d57bfff9477610358df1a12e3ac9 | packages/syft/src/syft/ast/attribute.py | python | Attribute.properties | (self) | return out | Extract all properties from the current node attributes.
Returns:
The list of properties in the current AST node attributes. | Extract all properties from the current node attributes. | [
"Extract",
"all",
"properties",
"from",
"the",
"current",
"node",
"attributes",
"."
] | def properties(self) -> List["ast.property.Property"]:
"""Extract all properties from the current node attributes.
Returns:
The list of properties in the current AST node attributes.
"""
out = []
if isinstance(self, ast.property.Property):
out.append(self)
self._extract_attr_type(out, "properties")
return out | [
"def",
"properties",
"(",
"self",
")",
"->",
"List",
"[",
"\"ast.property.Property\"",
"]",
":",
"out",
"=",
"[",
"]",
"if",
"isinstance",
"(",
"self",
",",
"ast",
".",
"property",
".",
"Property",
")",
":",
"out",
".",
"append",
"(",
"self",
")",
"s... | https://github.com/OpenMined/PySyft/blob/f181ca02d307d57bfff9477610358df1a12e3ac9/packages/syft/src/syft/ast/attribute.py#L114-L126 | |
inkandswitch/livebook | 93c8d467734787366ad084fc3566bf5cbe249c51 | public/pypyjs/modules/pydoc.py | python | render_doc | (thing, title='Python Library Documentation: %s', forceload=0) | return title % desc + '\n\n' + text.document(object, name) | Render text documentation, given an object or a path to an object. | Render text documentation, given an object or a path to an object. | [
"Render",
"text",
"documentation",
"given",
"an",
"object",
"or",
"a",
"path",
"to",
"an",
"object",
"."
] | def render_doc(thing, title='Python Library Documentation: %s', forceload=0):
"""Render text documentation, given an object or a path to an object."""
object, name = resolve(thing, forceload)
desc = describe(object)
module = inspect.getmodule(object)
if name and '.' in name:
desc += ' in ' + name[:name.rfind('.')]
elif module and module is not object:
desc += ' in module ' + module.__name__
if type(object) is _OLD_INSTANCE_TYPE:
# If the passed object is an instance of an old-style class,
# document its available methods instead of its value.
object = object.__class__
elif not (inspect.ismodule(object) or
inspect.isclass(object) or
inspect.isroutine(object) or
inspect.isgetsetdescriptor(object) or
inspect.ismemberdescriptor(object) or
isinstance(object, property)):
# If the passed object is a piece of data or an instance,
# document its available methods instead of its value.
object = type(object)
desc += ' object'
return title % desc + '\n\n' + text.document(object, name) | [
"def",
"render_doc",
"(",
"thing",
",",
"title",
"=",
"'Python Library Documentation: %s'",
",",
"forceload",
"=",
"0",
")",
":",
"object",
",",
"name",
"=",
"resolve",
"(",
"thing",
",",
"forceload",
")",
"desc",
"=",
"describe",
"(",
"object",
")",
"modu... | https://github.com/inkandswitch/livebook/blob/93c8d467734787366ad084fc3566bf5cbe249c51/public/pypyjs/modules/pydoc.py#L1545-L1568 | |
tylerlaberge/PyPattyrn | 6561e9927553a9074d0a71247a1b1e933f2ec423 | pypattyrn/behavioral/memento.py | python | Originator.rollback | (self, memento) | Rollback this objects state to a previous state.
@param memento: The memento object holding the state to rollback to.
@type memento: Memento | Rollback this objects state to a previous state. | [
"Rollback",
"this",
"objects",
"state",
"to",
"a",
"previous",
"state",
"."
] | def rollback(self, memento):
"""
Rollback this objects state to a previous state.
@param memento: The memento object holding the state to rollback to.
@type memento: Memento
"""
self.__dict__ = memento.state | [
"def",
"rollback",
"(",
"self",
",",
"memento",
")",
":",
"self",
".",
"__dict__",
"=",
"memento",
".",
"state"
] | https://github.com/tylerlaberge/PyPattyrn/blob/6561e9927553a9074d0a71247a1b1e933f2ec423/pypattyrn/behavioral/memento.py#L40-L47 | ||
jamiecaesar/securecrt-tools | f3cbb49223a485fc9af86e9799b5c940f19e8027 | securecrt_tools/sessions.py | python | Session.end_cisco_session | (self) | End the session by returning the device's terminal parameters that were modified by start_session() to their
previous values.
This should always be called before a disconnect (assuming that start_cisco_session was called after connect) | End the session by returning the device's terminal parameters that were modified by start_session() to their
previous values. | [
"End",
"the",
"session",
"by",
"returning",
"the",
"device",
"s",
"terminal",
"parameters",
"that",
"were",
"modified",
"by",
"start_session",
"()",
"to",
"their",
"previous",
"values",
"."
] | def end_cisco_session(self):
"""
End the session by returning the device's terminal parameters that were modified by start_session() to their
previous values.
This should always be called before a disconnect (assuming that start_cisco_session was called after connect)
"""
pass | [
"def",
"end_cisco_session",
"(",
"self",
")",
":",
"pass"
] | https://github.com/jamiecaesar/securecrt-tools/blob/f3cbb49223a485fc9af86e9799b5c940f19e8027/securecrt_tools/sessions.py#L194-L201 | ||
TencentCloud/tencentcloud-sdk-python | 3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2 | tencentcloud/tbaas/v20180416/models.py | python | GetLatesdTransactionListResponse.__init__ | (self) | r"""
:param TotalCount: 交易总数量
:type TotalCount: int
:param TransactionList: 交易列表
:type TransactionList: list of TransactionItem
:param RequestId: 唯一请求 ID，每次请求都会返回。定位问题时需要提供该次请求的 RequestId。
:type RequestId: str | r"""
:param TotalCount: 交易总数量
:type TotalCount: int
:param TransactionList: 交易列表
:type TransactionList: list of TransactionItem
:param RequestId: 唯一请求 ID，每次请求都会返回。定位问题时需要提供该次请求的 RequestId。
:type RequestId: str | [
"r",
":",
"param",
"TotalCount",
":",
"交易总数量",
":",
"type",
"TotalCount",
":",
"int",
":",
"param",
"TransactionList",
":",
"交易列表",
":",
"type",
"TransactionList",
":",
"list",
"of",
"TransactionItem",
":",
"param",
"RequestId",
":",
"唯一请求",
"ID，每次请求都会返回。定位问题时... | def __init__(self):
r"""
:param TotalCount: 交易总数量
:type TotalCount: int
:param TransactionList: 交易列表
:type TransactionList: list of TransactionItem
:param RequestId: 唯一请求 ID，每次请求都会返回。定位问题时需要提供该次请求的 RequestId。
:type RequestId: str
"""
self.TotalCount = None
self.TransactionList = None
self.RequestId = None | [
"def",
"__init__",
"(",
"self",
")",
":",
"self",
".",
"TotalCount",
"=",
"None",
"self",
".",
"TransactionList",
"=",
"None",
"self",
".",
"RequestId",
"=",
"None"
] | https://github.com/TencentCloud/tencentcloud-sdk-python/blob/3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2/tencentcloud/tbaas/v20180416/models.py#L1937-L1948 | ||
aws/sagemaker-python-sdk | 9d259b316f7f43838c16f35c10e98a110b56735b | src/sagemaker/workflow/conditions.py | python | ConditionGreaterThan.__init__ | (
self,
left: Union[ConditionValueType, PrimitiveType],
right: Union[ConditionValueType, PrimitiveType],
) | Construct an instance of ConditionGreaterThan for greater than comparisons.
Args:
left (Union[ConditionValueType, PrimitiveType]): The execution variable,
parameter, property, or Python primitive value to use in the comparison.
right (Union[ConditionValueType, PrimitiveType]): The execution
variable, parameter, property, or Python primitive value to compare to. | Construct an instance of ConditionGreaterThan for greater than comparisons. | [
"Construct",
"an",
"instance",
"of",
"ConditionGreaterThan",
"for",
"greater",
"than",
"comparisons",
"."
] | def __init__(
self,
left: Union[ConditionValueType, PrimitiveType],
right: Union[ConditionValueType, PrimitiveType],
):
"""Construct an instance of ConditionGreaterThan for greater than comparisons.
Args:
left (Union[ConditionValueType, PrimitiveType]): The execution variable,
parameter, property, or Python primitive value to use in the comparison.
right (Union[ConditionValueType, PrimitiveType]): The execution
variable, parameter, property, or Python primitive value to compare to.
"""
super(ConditionGreaterThan, self).__init__(ConditionTypeEnum.GT, left, right) | [
"def",
"__init__",
"(",
"self",
",",
"left",
":",
"Union",
"[",
"ConditionValueType",
",",
"PrimitiveType",
"]",
",",
"right",
":",
"Union",
"[",
"ConditionValueType",
",",
"PrimitiveType",
"]",
",",
")",
":",
"super",
"(",
"ConditionGreaterThan",
",",
"self... | https://github.com/aws/sagemaker-python-sdk/blob/9d259b316f7f43838c16f35c10e98a110b56735b/src/sagemaker/workflow/conditions.py#L110-L124 | ||
cloudera/hue | 23f02102d4547c17c32bd5ea0eb24e9eadd657a4 | desktop/core/ext-py/zope.interface-4.5.0/src/zope/interface/common/mapping.py | python | IWriteMapping.__delitem__ | (key) | Delete a value from the mapping using the key. | Delete a value from the mapping using the key. | [
"Delete",
"a",
"value",
"from",
"the",
"mapping",
"using",
"the",
"key",
"."
] | def __delitem__(key):
"""Delete a value from the mapping using the key.""" | [
"def",
"__delitem__",
"(",
"key",
")",
":"
] | https://github.com/cloudera/hue/blob/23f02102d4547c17c32bd5ea0eb24e9eadd657a4/desktop/core/ext-py/zope.interface-4.5.0/src/zope/interface/common/mapping.py#L46-L47 | ||
nottombrown/rl-teacher | b2c2201e9d2457b13185424a19da7209364f23df | agents/pposgd-mpi/pposgd_mpi/run_mujoco.py | python | train_pposgd_mpi | (make_env, num_timesteps, seed, predictor=None) | [] | def train_pposgd_mpi(make_env, num_timesteps, seed, predictor=None):
from pposgd_mpi import mlp_policy, pposgd_simple
U.make_session(num_cpu=1).__enter__()
logger.session().__enter__()
set_global_seeds(seed)
env = make_env()
def policy_fn(name, ob_space, ac_space):
return mlp_policy.MlpPolicy(name=name, ob_space=ob_space, ac_space=ac_space,
hid_size=64, num_hid_layers=2)
env = bench.Monitor(env, osp.join(logger.get_dir(), "monitor.json"))
env.seed(seed)
gym.logger.setLevel(logging.WARN)
pposgd_simple.learn(env, policy_fn,
max_timesteps=num_timesteps,
timesteps_per_batch=2048*8,
clip_param=0.2, entcoeff=0.0,
optim_epochs=10, optim_stepsize=3e-4, optim_batchsize=64,
gamma=0.99, lam=0.95,
predictor=predictor
)
env.close() | [
"def",
"train_pposgd_mpi",
"(",
"make_env",
",",
"num_timesteps",
",",
"seed",
",",
"predictor",
"=",
"None",
")",
":",
"from",
"pposgd_mpi",
"import",
"mlp_policy",
",",
"pposgd_simple",
"U",
".",
"make_session",
"(",
"num_cpu",
"=",
"1",
")",
".",
"__enter... | https://github.com/nottombrown/rl-teacher/blob/b2c2201e9d2457b13185424a19da7209364f23df/agents/pposgd-mpi/pposgd_mpi/run_mujoco.py#L10-L32 | ||||
astropy/astroquery | 11c9c83fa8e5f948822f8f73c854ec4b72043016 | astroquery/utils/tap/gui/login.py | python | LoginDialog.__init__ | (self, host) | [] | def __init__(self, host):
self.__interna_init()
self.__host = host
self.__initialized = False
if TKTk is not None:
self.__create_content()
self.__initialized = True | [
"def",
"__init__",
"(",
"self",
",",
"host",
")",
":",
"self",
".",
"__interna_init",
"(",
")",
"self",
".",
"__host",
"=",
"host",
"self",
".",
"__initialized",
"=",
"False",
"if",
"TKTk",
"is",
"not",
"None",
":",
"self",
".",
"__create_content",
"("... | https://github.com/astropy/astroquery/blob/11c9c83fa8e5f948822f8f73c854ec4b72043016/astroquery/utils/tap/gui/login.py#L46-L52 | ||||
wbond/asn1crypto | 9ae350f212532dfee7f185f6b3eda24753249cf3 | asn1crypto/core.py | python | Sequence.__delitem__ | (self, key) | Allows deleting optional or default fields by name or index
:param key:
A unicode string of the field name, or an integer of the field index
:raises:
ValueError - when a field name or index is invalid, or the field is not optional or defaulted | Allows deleting optional or default fields by name or index | [
"Allows",
"deleting",
"optional",
"or",
"default",
"fields",
"by",
"name",
"or",
"index"
] | def __delitem__(self, key):
"""
Allows deleting optional or default fields by name or index
:param key:
A unicode string of the field name, or an integer of the field index
:raises:
ValueError - when a field name or index is invalid, or the field is not optional or defaulted
"""
# We inline this check to prevent method invocation each time
if self.children is None:
self._parse_children()
if not isinstance(key, int_types):
if key not in self._field_map:
raise KeyError(unwrap(
'''
No field named "%s" defined for %s
''',
key,
type_name(self)
))
key = self._field_map[key]
name, _, params = self._fields[key]
if not params or ('default' not in params and 'optional' not in params):
raise ValueError(unwrap(
'''
Can not delete the value for the field "%s" of %s since it is
not optional or defaulted
''',
name,
type_name(self)
))
if 'optional' in params:
self.children[key] = VOID
if self._native is not None:
self._native[name] = None
else:
self.__setitem__(key, None)
self._mutated = True | [
"def",
"__delitem__",
"(",
"self",
",",
"key",
")",
":",
"# We inline this check to prevent method invocation each time",
"if",
"self",
".",
"children",
"is",
"None",
":",
"self",
".",
"_parse_children",
"(",
")",
"if",
"not",
"isinstance",
"(",
"key",
",",
"int... | https://github.com/wbond/asn1crypto/blob/9ae350f212532dfee7f185f6b3eda24753249cf3/asn1crypto/core.py#L3593-L3636 | ||
google/grr | 8ad8a4d2c5a93c92729206b7771af19d92d4f915 | grr/server/grr_response_server/cronjobs.py | python | CronManager.__init__ | (self, max_threads=10) | [] | def __init__(self, max_threads=10):
super().__init__()
if max_threads <= 0:
raise ValueError("max_threads should be >= 1")
self.max_threads = max_threads | [
"def",
"__init__",
"(",
"self",
",",
"max_threads",
"=",
"10",
")",
":",
"super",
"(",
")",
".",
"__init__",
"(",
")",
"if",
"max_threads",
"<=",
"0",
":",
"raise",
"ValueError",
"(",
"\"max_threads should be >= 1\"",
")",
"self",
".",
"max_threads",
"=",
... | https://github.com/google/grr/blob/8ad8a4d2c5a93c92729206b7771af19d92d4f915/grr/server/grr_response_server/cronjobs.py#L200-L206 | ||||
pwnieexpress/pwn_plug_sources | 1a23324f5dc2c3de20f9c810269b6a29b2758cad | src/metagoofil/hachoir_core/stream/input.py | python | FileFromInputStream.read | (self, size=None) | [] | def read(self, size=None):
def read(address, size):
shift, data, missing = self.stream.read(8 * address, 8 * size)
if shift:
raise InputStreamError("TODO: handle non-byte-aligned data")
return data
if self._size or size is not None and not self._from_end:
# We don't want self.tell() to read anything
# and the size must be known if we read until the end.
pos = self.tell()
if size is None or None < self._size < pos + size:
size = self._size - pos
if size <= 0:
return ''
data = read(pos, size)
self._offset += len(data)
return data
elif self._from_end:
# TODO: not tested
max_size = - self._offset
if size is None or max_size < size:
size = max_size
if size <= 0:
return ''
data = '', ''
self._offset = max(0, self.stream._current_size // 8 + self._offset)
self._from_end = False
bs = max(max_size, 1 << 16)
while True:
d = read(self._offset, bs)
data = data[1], d
self._offset += len(d)
if self._size:
bs = self._size - self._offset
if not bs:
data = data[0] + data[1]
d = len(data) - max_size
return data[d:d+size]
else:
# TODO: not tested
data = [ ]
size = 1 << 16
while True:
d = read(self._offset, size)
data.append(d)
self._offset += len(d)
if self._size:
size = self._size - self._offset
if not size:
return ''.join(data) | [
"def",
"read",
"(",
"self",
",",
"size",
"=",
"None",
")",
":",
"def",
"read",
"(",
"address",
",",
"size",
")",
":",
"shift",
",",
"data",
",",
"missing",
"=",
"self",
".",
"stream",
".",
"read",
"(",
"8",
"*",
"address",
",",
"8",
"*",
"size"... | https://github.com/pwnieexpress/pwn_plug_sources/blob/1a23324f5dc2c3de20f9c810269b6a29b2758cad/src/metagoofil/hachoir_core/stream/input.py#L69-L118 | ||||
google-research/rigl | f18abc7d82ae3acc6736068408a0186c9efa575c | rigl/rigl_tf2/interpolate.py | python | test_model | (model, d_test, batch_size=1000) | return test_loss.result().numpy(), test_accuracy.result().numpy() | Tests the model and calculates cross entropy loss and accuracy. | Tests the model and calculates cross entropy loss and accuracy. | [
"Tests",
"the",
"model",
"and",
"calculates",
"cross",
"entropy",
"loss",
"and",
"accuracy",
"."
] | def test_model(model, d_test, batch_size=1000):
"""Tests the model and calculates cross entropy loss and accuracy."""
test_loss = tf.keras.metrics.Mean(name='test_loss')
test_accuracy = tf.keras.metrics.SparseCategoricalAccuracy(
name='test_accuracy')
loss_object = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True)
for x, y in d_test.batch(batch_size):
predictions = model(x, training=False)
batch_loss = loss_object(y, predictions)
test_loss.update_state(batch_loss)
test_accuracy.update_state(y, predictions)
logging.info('Test loss: %f', test_loss.result().numpy())
logging.info('Test accuracy: %f', test_accuracy.result().numpy())
return test_loss.result().numpy(), test_accuracy.result().numpy() | [
"def",
"test_model",
"(",
"model",
",",
"d_test",
",",
"batch_size",
"=",
"1000",
")",
":",
"test_loss",
"=",
"tf",
".",
"keras",
".",
"metrics",
".",
"Mean",
"(",
"name",
"=",
"'test_loss'",
")",
"test_accuracy",
"=",
"tf",
".",
"keras",
".",
"metrics... | https://github.com/google-research/rigl/blob/f18abc7d82ae3acc6736068408a0186c9efa575c/rigl/rigl_tf2/interpolate.py#L62-L75 | |
oaubert/python-vlc | 908ffdbd0844dc1849728c456e147788798c99da | generated/3.0/distribute_setup.py | python | _build_install_args | (options) | return install_args | Build the arguments to 'python setup.py install' on the distribute package | Build the arguments to 'python setup.py install' on the distribute package | [
"Build",
"the",
"arguments",
"to",
"python",
"setup",
".",
"py",
"install",
"on",
"the",
"distribute",
"package"
] | def _build_install_args(options):
"""
Build the arguments to 'python setup.py install' on the distribute package
"""
install_args = []
if options.user_install:
if sys.version_info < (2, 6):
log.warn("--user requires Python 2.6 or later")
raise SystemExit(1)
install_args.append('--user')
return install_args | [
"def",
"_build_install_args",
"(",
"options",
")",
":",
"install_args",
"=",
"[",
"]",
"if",
"options",
".",
"user_install",
":",
"if",
"sys",
".",
"version_info",
"<",
"(",
"2",
",",
"6",
")",
":",
"log",
".",
"warn",
"(",
"\"--user requires Python 2.6 or... | https://github.com/oaubert/python-vlc/blob/908ffdbd0844dc1849728c456e147788798c99da/generated/3.0/distribute_setup.py#L515-L525 | |
awslabs/deeplearning-benchmark | 3e9a906422b402869537f91056ae771b66487a8e | word_language_model/word_language_model_train.py | python | eval | (data_source, ctx) | return total_L / ntotal | [] | def eval(data_source, ctx):
total_L = 0.0
ntotal = 0
hidden_states = [
model.begin_state(func=mx.nd.zeros, batch_size=args.batch_size/len(ctx), ctx=ctx[i])
for i in range(len(ctx))
]
for i in range(0, data_source.shape[0] - 1, args.bptt):
data_batch, target_batch = get_batch(data_source, i)
data = gluon.utils.split_and_load(data_batch, ctx_list=ctx, batch_axis=1)
target = gluon.utils.split_and_load(target_batch, ctx_list=ctx, batch_axis=1)
for (d, t) in zip(data, target):
hidden = hidden_states[d.context.device_id]
output, hidden = model(d, hidden)
L = loss(output, t.reshape((-1,)))
total_L += mx.nd.sum(L).asscalar()
ntotal += L.size
return total_L / ntotal | [
"def",
"eval",
"(",
"data_source",
",",
"ctx",
")",
":",
"total_L",
"=",
"0.0",
"ntotal",
"=",
"0",
"hidden_states",
"=",
"[",
"model",
".",
"begin_state",
"(",
"func",
"=",
"mx",
".",
"nd",
".",
"zeros",
",",
"batch_size",
"=",
"args",
".",
"batch_s... | https://github.com/awslabs/deeplearning-benchmark/blob/3e9a906422b402869537f91056ae771b66487a8e/word_language_model/word_language_model_train.py#L90-L107 | |||
tp4a/teleport | 1fafd34f1f775d2cf80ea4af6e44468d8e0b24ad | server/www/packages/packages-darwin/x64/psutil/_pssunos.py | python | disk_partitions | (all=False) | return retlist | Return system disk partitions. | Return system disk partitions. | [
"Return",
"system",
"disk",
"partitions",
"."
] | def disk_partitions(all=False):
"""Return system disk partitions."""
# TODO - the filtering logic should be better checked so that
# it tries to reflect 'df' as much as possible
retlist = []
partitions = cext.disk_partitions()
for partition in partitions:
device, mountpoint, fstype, opts = partition
if device == 'none':
device = ''
if not all:
# Differently from, say, Linux, we don't have a list of
# common fs types so the best we can do, AFAIK, is to
# filter by filesystem having a total size > 0.
if not disk_usage(mountpoint).total:
continue
ntuple = _common.sdiskpart(device, mountpoint, fstype, opts)
retlist.append(ntuple)
return retlist | [
"def",
"disk_partitions",
"(",
"all",
"=",
"False",
")",
":",
"# TODO - the filtering logic should be better checked so that",
"# it tries to reflect 'df' as much as possible",
"retlist",
"=",
"[",
"]",
"partitions",
"=",
"cext",
".",
"disk_partitions",
"(",
")",
"for",
"... | https://github.com/tp4a/teleport/blob/1fafd34f1f775d2cf80ea4af6e44468d8e0b24ad/server/www/packages/packages-darwin/x64/psutil/_pssunos.py#L215-L233 | |
pschanely/CrossHair | 11702dda7cbd47cb7ac978844094a26fb12d296c | crosshair/libimpl/builtinslib.py | python | tracing_iter | (itr: Iterable[_T]) | Selectively re-enable tracing only during iteration. | Selectively re-enable tracing only during iteration. | [
"Selectively",
"re",
"-",
"enable",
"tracing",
"only",
"during",
"iteration",
"."
] | def tracing_iter(itr: Iterable[_T]) -> Iterable[_T]:
"""Selectively re-enable tracing only during iteration."""
assert not is_tracing()
itr = iter(itr)
while True:
try:
with ResumedTracing():
value = next(itr)
except StopIteration:
return
yield value | [
"def",
"tracing_iter",
"(",
"itr",
":",
"Iterable",
"[",
"_T",
"]",
")",
"->",
"Iterable",
"[",
"_T",
"]",
":",
"assert",
"not",
"is_tracing",
"(",
")",
"itr",
"=",
"iter",
"(",
"itr",
")",
"while",
"True",
":",
"try",
":",
"with",
"ResumedTracing",
... | https://github.com/pschanely/CrossHair/blob/11702dda7cbd47cb7ac978844094a26fb12d296c/crosshair/libimpl/builtinslib.py#L2119-L2129 | ||
spywhere/Javatar | e273ec40c209658247a71b109bb90cd126984a29 | core/java_utils.py | python | _JavaUtils.normalize_package_path | (self, class_path) | return RE().get("normalize_package_path", "^\\.*|\\.*$").sub(
"", class_path
) | Returns a dot-trimmed class path
@param class_path: a class path to be trimmed | Returns a dot-trimmed class path | [
"Returns",
"a",
"dot",
"-",
"trimmed",
"class",
"path"
] | def normalize_package_path(self, class_path):
"""
Returns a dot-trimmed class path
@param class_path: a class path to be trimmed
"""
return RE().get("normalize_package_path", "^\\.*|\\.*$").sub(
"", class_path
) | [
"def",
"normalize_package_path",
"(",
"self",
",",
"class_path",
")",
":",
"return",
"RE",
"(",
")",
".",
"get",
"(",
"\"normalize_package_path\"",
",",
"\"^\\\\.*|\\\\.*$\"",
")",
".",
"sub",
"(",
"\"\"",
",",
"class_path",
")"
] | https://github.com/spywhere/Javatar/blob/e273ec40c209658247a71b109bb90cd126984a29/core/java_utils.py#L207-L215 | |
cocrawler/cocrawler | a9be74308fe666130cb9ca3dd64e18f4c30d2894 | cocrawler/datalayer.py | python | Datalayer.memory | (self) | return {'seen_set': seen_set, 'robots': robots} | Return a dict summarizing the datalayer's memory usage | Return a dict summarizing the datalayer's memory usage | [
"Return",
"a",
"dict",
"summarizing",
"the",
"datalayer",
"s",
"memory",
"usage"
] | def memory(self):
'''Return a dict summarizing the datalayer's memory usage'''
seen_set = {}
seen_set['bytes'] = memory.total_size(self.seen_set)
seen_set['len'] = len(self.seen_set)
robots = {}
robots['bytes'] = memory.total_size(self.robots)
robots['len'] = len(self.robots)
return {'seen_set': seen_set, 'robots': robots} | [
"def",
"memory",
"(",
"self",
")",
":",
"seen_set",
"=",
"{",
"}",
"seen_set",
"[",
"'bytes'",
"]",
"=",
"memory",
".",
"total_size",
"(",
"self",
".",
"seen_set",
")",
"seen_set",
"[",
"'len'",
"]",
"=",
"len",
"(",
"self",
".",
"seen_set",
")",
"... | https://github.com/cocrawler/cocrawler/blob/a9be74308fe666130cb9ca3dd64e18f4c30d2894/cocrawler/datalayer.py#L52-L60 | |
openshift/openshift-tools | 1188778e728a6e4781acf728123e5b356380fe6f | openshift/installer/vendored/openshift-ansible-3.9.40/roles/lib_openshift/library/oc_image.py | python | OpenShiftCLIConfig.to_option_list | (self, ascommalist='') | return self.stringify(ascommalist) | return all options as a string
if ascommalist is set to the name of a key, and
the value of that key is a dict, format the dict
as a list of comma delimited key=value pairs | return all options as a string
if ascommalist is set to the name of a key, and
the value of that key is a dict, format the dict
as a list of comma delimited key=value pairs | [
"return",
"all",
"options",
"as",
"a",
"string",
"if",
"ascommalist",
"is",
"set",
"to",
"the",
"name",
"of",
"a",
"key",
"and",
"the",
"value",
"of",
"that",
"key",
"is",
"a",
"dict",
"format",
"the",
"dict",
"as",
"a",
"list",
"of",
"comma",
"delim... | def to_option_list(self, ascommalist=''):
'''return all options as a string
if ascommalist is set to the name of a key, and
the value of that key is a dict, format the dict
as a list of comma delimited key=value pairs'''
return self.stringify(ascommalist) | [
"def",
"to_option_list",
"(",
"self",
",",
"ascommalist",
"=",
"''",
")",
":",
"return",
"self",
".",
"stringify",
"(",
"ascommalist",
")"
] | https://github.com/openshift/openshift-tools/blob/1188778e728a6e4781acf728123e5b356380fe6f/openshift/installer/vendored/openshift-ansible-3.9.40/roles/lib_openshift/library/oc_image.py#L1436-L1441 | |
hzlzh/AlfredWorkflow.com | 7055f14f6922c80ea5943839eb0caff11ae57255 | Sources/Workflows/jc-weather/requests/packages/urllib3/util.py | python | make_headers | (keep_alive=None, accept_encoding=None, user_agent=None,
basic_auth=None) | return headers | Shortcuts for generating request headers.
:param keep_alive:
If ``True``, adds 'connection: keep-alive' header.
:param accept_encoding:
Can be a boolean, list, or string.
``True`` translates to 'gzip,deflate'.
List will get joined by comma.
String will be used as provided.
:param user_agent:
String representing the user-agent you want, such as
"python-urllib3/0.6"
:param basic_auth:
Colon-separated username:password string for 'authorization: basic ...'
auth header.
Example: ::
>>> make_headers(keep_alive=True, user_agent="Batman/1.0")
{'connection': 'keep-alive', 'user-agent': 'Batman/1.0'}
>>> make_headers(accept_encoding=True)
{'accept-encoding': 'gzip,deflate'} | Shortcuts for generating request headers. | [
"Shortcuts",
"for",
"generating",
"request",
"headers",
"."
] | def make_headers(keep_alive=None, accept_encoding=None, user_agent=None,
basic_auth=None):
"""
Shortcuts for generating request headers.
:param keep_alive:
If ``True``, adds 'connection: keep-alive' header.
:param accept_encoding:
Can be a boolean, list, or string.
``True`` translates to 'gzip,deflate'.
List will get joined by comma.
String will be used as provided.
:param user_agent:
String representing the user-agent you want, such as
"python-urllib3/0.6"
:param basic_auth:
Colon-separated username:password string for 'authorization: basic ...'
auth header.
Example: ::
>>> make_headers(keep_alive=True, user_agent="Batman/1.0")
{'connection': 'keep-alive', 'user-agent': 'Batman/1.0'}
>>> make_headers(accept_encoding=True)
{'accept-encoding': 'gzip,deflate'}
"""
headers = {}
if accept_encoding:
if isinstance(accept_encoding, str):
pass
elif isinstance(accept_encoding, list):
accept_encoding = ','.join(accept_encoding)
else:
accept_encoding = 'gzip,deflate'
headers['accept-encoding'] = accept_encoding
if user_agent:
headers['user-agent'] = user_agent
if keep_alive:
headers['connection'] = 'keep-alive'
if basic_auth:
headers['authorization'] = 'Basic ' + \
b64encode(six.b(basic_auth)).decode('utf-8')
return headers | [
"def",
"make_headers",
"(",
"keep_alive",
"=",
"None",
",",
"accept_encoding",
"=",
"None",
",",
"user_agent",
"=",
"None",
",",
"basic_auth",
"=",
"None",
")",
":",
"headers",
"=",
"{",
"}",
"if",
"accept_encoding",
":",
"if",
"isinstance",
"(",
"accept_e... | https://github.com/hzlzh/AlfredWorkflow.com/blob/7055f14f6922c80ea5943839eb0caff11ae57255/Sources/Workflows/jc-weather/requests/packages/urllib3/util.py#L182-L231 | |
robotlearn/pyrobolearn | 9cd7c060723fda7d2779fa255ac998c2c82b8436 | pyrobolearn/tools/interfaces/sensors/myo/myo_raw.py | python | MyoRaw.start_raw | (self) | Sending this sequence for v1.0 firmware seems to enable both raw data and
pose notifications. | Sending this sequence for v1.0 firmware seems to enable both raw data and
pose notifications. | [
"Sending",
"this",
"sequence",
"for",
"v1",
".",
"0",
"firmware",
"seems",
"to",
"enable",
"both",
"raw",
"data",
"and",
"pose",
"notifications",
"."
] | def start_raw(self):
"""Sending this sequence for v1.0 firmware seems to enable both raw data and
pose notifications.
"""
self.write_attr(0x28, b'\x01\x00') # EMG?
# self.write_attr(0x19, b'\x01\x03\x01\x01\x00')
self.write_attr(0x19, b'\x01\x03\x01\x01\x01') | [
"def",
"start_raw",
"(",
"self",
")",
":",
"self",
".",
"write_attr",
"(",
"0x28",
",",
"b'\\x01\\x00'",
")",
"# EMG?",
"# self.write_attr(0x19, b'\\x01\\x03\\x01\\x01\\x00')",
"self",
".",
"write_attr",
"(",
"0x19",
",",
"b'\\x01\\x03\\x01\\x01\\x01'",
")"
] | https://github.com/robotlearn/pyrobolearn/blob/9cd7c060723fda7d2779fa255ac998c2c82b8436/pyrobolearn/tools/interfaces/sensors/myo/myo_raw.py#L376-L383 | ||
zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_hxb2/lib/python3.5/site-packages/django/core/mail/utils.py | python | CachedDnsName.__str__ | (self) | return self.get_fqdn() | [] | def __str__(self):
return self.get_fqdn() | [
"def",
"__str__",
"(",
"self",
")",
":",
"return",
"self",
".",
"get_fqdn",
"(",
")"
] | https://github.com/zhl2008/awd-platform/blob/0416b31abea29743387b10b3914581fbe8e7da5e/web_hxb2/lib/python3.5/site-packages/django/core/mail/utils.py#L11-L12 | |||
oilshell/oil | 94388e7d44a9ad879b12615f6203b38596b5a2d3 | Python-2.7.13/Lib/xml/dom/minidom.py | python | Element.removeAttributeNS | (self, namespaceURI, localName) | [] | def removeAttributeNS(self, namespaceURI, localName):
try:
attr = self._attrsNS[(namespaceURI, localName)]
except KeyError:
raise xml.dom.NotFoundErr()
self.removeAttributeNode(attr) | [
"def",
"removeAttributeNS",
"(",
"self",
",",
"namespaceURI",
",",
"localName",
")",
":",
"try",
":",
"attr",
"=",
"self",
".",
"_attrsNS",
"[",
"(",
"namespaceURI",
",",
"localName",
")",
"]",
"except",
"KeyError",
":",
"raise",
"xml",
".",
"dom",
".",
... | https://github.com/oilshell/oil/blob/94388e7d44a9ad879b12615f6203b38596b5a2d3/Python-2.7.13/Lib/xml/dom/minidom.py#L754-L759 | ||||
sabnzbd/sabnzbd | 52d21e94d3cc6e30764a833fe2a256783d1a8931 | sabnzbd/misc.py | python | find_on_path | (targets) | return None | Search the PATH for a program and return full path | Search the PATH for a program and return full path | [
"Search",
"the",
"PATH",
"for",
"a",
"program",
"and",
"return",
"full",
"path"
] | def find_on_path(targets):
"""Search the PATH for a program and return full path"""
if sabnzbd.WIN32:
paths = os.getenv("PATH").split(";")
else:
paths = os.getenv("PATH").split(":")
if isinstance(targets, str):
targets = (targets,)
for path in paths:
for target in targets:
target_path = os.path.abspath(os.path.join(path, target))
if os.path.isfile(target_path) and os.access(target_path, os.X_OK):
return target_path
return None | [
"def",
"find_on_path",
"(",
"targets",
")",
":",
"if",
"sabnzbd",
".",
"WIN32",
":",
"paths",
"=",
"os",
".",
"getenv",
"(",
"\"PATH\"",
")",
".",
"split",
"(",
"\";\"",
")",
"else",
":",
"paths",
"=",
"os",
".",
"getenv",
"(",
"\"PATH\"",
")",
"."... | https://github.com/sabnzbd/sabnzbd/blob/52d21e94d3cc6e30764a833fe2a256783d1a8931/sabnzbd/misc.py#L859-L874 | |
datacenter/acitoolkit | 629b84887dd0f0183b81efc8adb16817f985541a | acitoolkit/aciphysobject.py | python | Linecard._populate_from_attributes | (self, attributes) | Fills in an object with the desired attributes.
Overridden by inheriting classes to provide the specific attributes
when getting objects from the APIC. | Fills in an object with the desired attributes.
Overridden by inheriting classes to provide the specific attributes
when getting objects from the APIC. | [
"Fills",
"in",
"an",
"object",
"with",
"the",
"desired",
"attributes",
".",
"Overridden",
"by",
"inheriting",
"classes",
"to",
"provide",
"the",
"specific",
"attributes",
"when",
"getting",
"objects",
"from",
"the",
"APIC",
"."
] | def _populate_from_attributes(self, attributes):
"""Fills in an object with the desired attributes.
Overridden by inheriting classes to provide the specific attributes
when getting objects from the APIC.
"""
self.serial = str(attributes['ser'])
self.model = str(attributes['model'])
self.descr = str(attributes['descr'])
self.num_ports = str(attributes['numP'])
self.hardware_version = str(attributes['hwVer'])
self.hardware_revision = str(attributes['rev'])
self.type = str(attributes['type'])
self.oper_st = str(attributes['operSt'])
self.dn = str(attributes['dn'])
self.modify_time = str(attributes['modTs']) | [
"def",
"_populate_from_attributes",
"(",
"self",
",",
"attributes",
")",
":",
"self",
".",
"serial",
"=",
"str",
"(",
"attributes",
"[",
"'ser'",
"]",
")",
"self",
".",
"model",
"=",
"str",
"(",
"attributes",
"[",
"'model'",
"]",
")",
"self",
".",
"des... | https://github.com/datacenter/acitoolkit/blob/629b84887dd0f0183b81efc8adb16817f985541a/acitoolkit/aciphysobject.py#L349-L363 | ||
replit-archive/empythoned | 977ec10ced29a3541a4973dc2b59910805695752 | cpython/Lib/pdb.py | python | Pdb.user_line | (self, frame) | This function is called when we stop or break at this line. | This function is called when we stop or break at this line. | [
"This",
"function",
"is",
"called",
"when",
"we",
"stop",
"or",
"break",
"at",
"this",
"line",
"."
] | def user_line(self, frame):
"""This function is called when we stop or break at this line."""
if self._wait_for_mainpyfile:
if (self.mainpyfile != self.canonic(frame.f_code.co_filename)
or frame.f_lineno<= 0):
return
self._wait_for_mainpyfile = 0
if self.bp_commands(frame):
self.interaction(frame, None) | [
"def",
"user_line",
"(",
"self",
",",
"frame",
")",
":",
"if",
"self",
".",
"_wait_for_mainpyfile",
":",
"if",
"(",
"self",
".",
"mainpyfile",
"!=",
"self",
".",
"canonic",
"(",
"frame",
".",
"f_code",
".",
"co_filename",
")",
"or",
"frame",
".",
"f_li... | https://github.com/replit-archive/empythoned/blob/977ec10ced29a3541a4973dc2b59910805695752/cpython/Lib/pdb.py#L150-L158 | ||
CGCookie/retopoflow | 3d8b3a47d1d661f99ab0aeb21d31370bf15de35e | retopoflow/updater.py | python | addon_updater_update_now.poll | (cls, context) | return True | [] | def poll(cls, context):
# return False
if retopoflow_version_git: return False # do not allow update if under git version control
if updater.invalid_updater: return False # something bad happened; bail!
if not updater.update_ready: return False # update not ready, yet
return True | [
"def",
"poll",
"(",
"cls",
",",
"context",
")",
":",
"# return False",
"if",
"retopoflow_version_git",
":",
"return",
"False",
"# do not allow update if under git version control",
"if",
"updater",
".",
"invalid_updater",
":",
"return",
"False",
"# something bad happened;... | https://github.com/CGCookie/retopoflow/blob/3d8b3a47d1d661f99ab0aeb21d31370bf15de35e/retopoflow/updater.py#L263-L268 | |||
LinkedInAttic/indextank-service | 880c6295ce8e7a3a55bf9b3777cc35c7680e0d7e | nebu/flaptor/indextank/rpc/Indexer.py | python | Client.updateCategories | (self, docid, categories) | Parameters:
- docid
- categories | Parameters:
- docid
- categories | [
"Parameters",
":",
"-",
"docid",
"-",
"categories"
] | def updateCategories(self, docid, categories):
"""
Parameters:
- docid
- categories
"""
self.send_updateCategories(docid, categories)
self.recv_updateCategories() | [
"def",
"updateCategories",
"(",
"self",
",",
"docid",
",",
"categories",
")",
":",
"self",
".",
"send_updateCategories",
"(",
"docid",
",",
"categories",
")",
"self",
".",
"recv_updateCategories",
"(",
")"
] | https://github.com/LinkedInAttic/indextank-service/blob/880c6295ce8e7a3a55bf9b3777cc35c7680e0d7e/nebu/flaptor/indextank/rpc/Indexer.py#L215-L222 | ||
KhronosGroup/OpenXR-SDK-Source | 76756e2e7849b15466d29bee7d80cada92865550 | external/python/jinja2/sandbox.py | python | SandboxedEnvironment.getattr | (self, obj, attribute) | return self.undefined(obj=obj, name=attribute) | Subscribe an object from sandboxed code and prefer the
attribute. The attribute passed *must* be a bytestring. | Subscribe an object from sandboxed code and prefer the
attribute. The attribute passed *must* be a bytestring. | [
"Subscribe",
"an",
"object",
"from",
"sandboxed",
"code",
"and",
"prefer",
"the",
"attribute",
".",
"The",
"attribute",
"passed",
"*",
"must",
"*",
"be",
"a",
"bytestring",
"."
] | def getattr(self, obj, attribute):
"""Subscribe an object from sandboxed code and prefer the
attribute. The attribute passed *must* be a bytestring.
"""
try:
value = getattr(obj, attribute)
except AttributeError:
try:
return obj[attribute]
except (TypeError, LookupError):
pass
else:
if self.is_safe_attribute(obj, attribute, value):
return value
return self.unsafe_undefined(obj, attribute)
return self.undefined(obj=obj, name=attribute) | [
"def",
"getattr",
"(",
"self",
",",
"obj",
",",
"attribute",
")",
":",
"try",
":",
"value",
"=",
"getattr",
"(",
"obj",
",",
"attribute",
")",
"except",
"AttributeError",
":",
"try",
":",
"return",
"obj",
"[",
"attribute",
"]",
"except",
"(",
"TypeErro... | https://github.com/KhronosGroup/OpenXR-SDK-Source/blob/76756e2e7849b15466d29bee7d80cada92865550/external/python/jinja2/sandbox.py#L382-L397 | |
debian-calibre/calibre | 020fc81d3936a64b2ac51459ecb796666ab6a051 | src/calibre/db/fields.py | python | Field.for_book | (self, book_id, default_value=None) | Return the value of this field for the book identified by book_id.
When no value is found, returns ``default_value``. | Return the value of this field for the book identified by book_id.
When no value is found, returns ``default_value``. | [
"Return",
"the",
"value",
"of",
"this",
"field",
"for",
"the",
"book",
"identified",
"by",
"book_id",
".",
"When",
"no",
"value",
"is",
"found",
"returns",
"default_value",
"."
] | def for_book(self, book_id, default_value=None):
'''
Return the value of this field for the book identified by book_id.
When no value is found, returns ``default_value``.
'''
raise NotImplementedError() | [
"def",
"for_book",
"(",
"self",
",",
"book_id",
",",
"default_value",
"=",
"None",
")",
":",
"raise",
"NotImplementedError",
"(",
")"
] | https://github.com/debian-calibre/calibre/blob/020fc81d3936a64b2ac51459ecb796666ab6a051/src/calibre/db/fields.py#L120-L125 | ||
OpenMDAO/OpenMDAO1 | 791a6fbbb7d266f3dcbc1f7bde3ae03a70dc1317 | openmdao/examples/sellar_MDF_optimize.py | python | SellarDis1.linearize | (self, params, unknowns, resids) | return J | Jacobian for Sellar discipline 1. | Jacobian for Sellar discipline 1. | [
"Jacobian",
"for",
"Sellar",
"discipline",
"1",
"."
] | def linearize(self, params, unknowns, resids):
""" Jacobian for Sellar discipline 1."""
J = {}
J['y1','y2'] = -0.2
J['y1','z'] = np.array([[2*params['z'][0], 1.0]])
J['y1','x'] = 1.0
return J | [
"def",
"linearize",
"(",
"self",
",",
"params",
",",
"unknowns",
",",
"resids",
")",
":",
"J",
"=",
"{",
"}",
"J",
"[",
"'y1'",
",",
"'y2'",
"]",
"=",
"-",
"0.2",
"J",
"[",
"'y1'",
",",
"'z'",
"]",
"=",
"np",
".",
"array",
"(",
"[",
"[",
"2... | https://github.com/OpenMDAO/OpenMDAO1/blob/791a6fbbb7d266f3dcbc1f7bde3ae03a70dc1317/openmdao/examples/sellar_MDF_optimize.py#L36-L44 | |
shubhtuls/factored3d | 1bb77c7ae7dbaba7056e94cb99fdd6c9cc73c7cd | experiments/suncg/box3d.py | python | Box3dTrainer.forward | (self) | [] | def forward(self):
opts = self.opts
self.codes_pred = self.model.forward((self.input_imgs_fine, self.input_imgs, self.rois))
self.total_loss, self.loss_factors = loss_utils.code_loss(
self.codes_pred, self.codes_gt,
pred_voxels=opts.pred_voxels,
classify_rot=opts.classify_rot,
shape_wt=opts.shape_loss_wt,
scale_wt=opts.scale_loss_wt,
quat_wt=opts.quat_loss_wt,
trans_wt=opts.trans_loss_wt
)
for k in self.smoothed_factor_losses.keys():
self.smoothed_factor_losses[k] = 0.99*self.smoothed_factor_losses[k] + 0.01*self.loss_factors[k].data[0] | [
"def",
"forward",
"(",
"self",
")",
":",
"opts",
"=",
"self",
".",
"opts",
"self",
".",
"codes_pred",
"=",
"self",
".",
"model",
".",
"forward",
"(",
"(",
"self",
".",
"input_imgs_fine",
",",
"self",
".",
"input_imgs",
",",
"self",
".",
"rois",
")",
... | https://github.com/shubhtuls/factored3d/blob/1bb77c7ae7dbaba7056e94cb99fdd6c9cc73c7cd/experiments/suncg/box3d.py#L243-L257 | ||||
lyft/cartography | 921a790d686c679ab5d8936b07e167fd424ee8d6 | cartography/graph/statement.py | python | GraphStatement.as_dict | (self) | return {
"query": self.query,
"parameters": self.parameters,
"iterative": self.iterative,
"iterationsize": self.iterationsize,
} | Convert statement to a dictionary. | Convert statement to a dictionary. | [
"Convert",
"statement",
"to",
"a",
"dictionary",
"."
] | def as_dict(self):
"""
Convert statement to a dictionary.
"""
return {
"query": self.query,
"parameters": self.parameters,
"iterative": self.iterative,
"iterationsize": self.iterationsize,
} | [
"def",
"as_dict",
"(",
"self",
")",
":",
"return",
"{",
"\"query\"",
":",
"self",
".",
"query",
",",
"\"parameters\"",
":",
"self",
".",
"parameters",
",",
"\"iterative\"",
":",
"self",
".",
"iterative",
",",
"\"iterationsize\"",
":",
"self",
".",
"iterati... | https://github.com/lyft/cartography/blob/921a790d686c679ab5d8936b07e167fd424ee8d6/cartography/graph/statement.py#L74-L83 | |
fonttools/fonttools | 892322aaff6a89bea5927379ec06bc0da3dfb7df | Lib/fontTools/ttLib/tables/otConverters.py | python | ValueRecord.xmlWrite | (self, xmlWriter, font, value, name, attrs) | [] | def xmlWrite(self, xmlWriter, font, value, name, attrs):
if value is None:
pass # NULL table, ignore
else:
value.toXML(xmlWriter, font, self.name, attrs) | [
"def",
"xmlWrite",
"(",
"self",
",",
"xmlWriter",
",",
"font",
",",
"value",
",",
"name",
",",
"attrs",
")",
":",
"if",
"value",
"is",
"None",
":",
"pass",
"# NULL table, ignore",
"else",
":",
"value",
".",
"toXML",
"(",
"xmlWriter",
",",
"font",
",",
... | https://github.com/fonttools/fonttools/blob/892322aaff6a89bea5927379ec06bc0da3dfb7df/Lib/fontTools/ttLib/tables/otConverters.py#L708-L712 | ||||
ManiacalLabs/BiblioPixel | afb993fbbe56e75e7c98f252df402b0f3e83bb6e | bibliopixel/builder/runner.py | python | Runner.instance | (cls) | return cls._INSTANCE and cls._INSTANCE() | Return the unique instance of Runner, if any, or None | Return the unique instance of Runner, if any, or None | [
"Return",
"the",
"unique",
"instance",
"of",
"Runner",
"if",
"any",
"or",
"None"
] | def instance(cls):
"""Return the unique instance of Runner, if any, or None"""
return cls._INSTANCE and cls._INSTANCE() | [
"def",
"instance",
"(",
"cls",
")",
":",
"return",
"cls",
".",
"_INSTANCE",
"and",
"cls",
".",
"_INSTANCE",
"(",
")"
] | https://github.com/ManiacalLabs/BiblioPixel/blob/afb993fbbe56e75e7c98f252df402b0f3e83bb6e/bibliopixel/builder/runner.py#L46-L48 | |
tanghaibao/jcvi | 5e720870c0928996f8b77a38208106ff0447ccb6 | jcvi/projects/tgbs.py | python | count | (args) | %prog count cdhit.consensus.fasta
Scan the headers for the consensus clusters and count the number of reads. | %prog count cdhit.consensus.fasta | [
"%prog",
"count",
"cdhit",
".",
"consensus",
".",
"fasta"
] | def count(args):
"""
%prog count cdhit.consensus.fasta
Scan the headers for the consensus clusters and count the number of reads.
"""
from jcvi.graphics.histogram import stem_leaf_plot
from jcvi.utils.cbook import SummaryStats
p = OptionParser(count.__doc__)
p.add_option("--csv", help="Write depth per contig to file")
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
(fastafile,) = args
csv = open(opts.csv, "w") if opts.csv else None
f = Fasta(fastafile, lazy=True)
sizes = []
for desc, rec in f.iterdescriptions_ordered():
if desc.startswith("singleton"):
sizes.append(1)
continue
# consensus_for_cluster_0 with 63 sequences
if "with" in desc:
name, w, size, seqs = desc.split()
if csv:
print("\t".join(str(x) for x in (name, size, len(rec))), file=csv)
assert w == "with"
sizes.append(int(size))
# MRD85:00603:02472;size=167;
else:
name, size, tail = desc.split(";")
sizes.append(int(size.replace("size=", "")))
if csv:
csv.close()
logging.debug("File written to `%s`.", opts.csv)
s = SummaryStats(sizes)
print(s, file=sys.stderr)
stem_leaf_plot(s.data, 0, 100, 20, title="Cluster size") | [
"def",
"count",
"(",
"args",
")",
":",
"from",
"jcvi",
".",
"graphics",
".",
"histogram",
"import",
"stem_leaf_plot",
"from",
"jcvi",
".",
"utils",
".",
"cbook",
"import",
"SummaryStats",
"p",
"=",
"OptionParser",
"(",
"count",
".",
"__doc__",
")",
"p",
... | https://github.com/tanghaibao/jcvi/blob/5e720870c0928996f8b77a38208106ff0447ccb6/jcvi/projects/tgbs.py#L279-L323 | ||
EventGhost/EventGhost | 177be516849e74970d2e13cda82244be09f277ce | lib27/site-packages/tornado/concurrent.py | python | Future.result | (self, timeout=None) | return self._result | If the operation succeeded, return its result. If it failed,
re-raise its exception.
This method takes a ``timeout`` argument for compatibility with
`concurrent.futures.Future` but it is an error to call it
before the `Future` is done, so the ``timeout`` is never used. | If the operation succeeded, return its result. If it failed,
re-raise its exception. | [
"If",
"the",
"operation",
"succeeded",
"return",
"its",
"result",
".",
"If",
"it",
"failed",
"re",
"-",
"raise",
"its",
"exception",
"."
] | def result(self, timeout=None):
"""If the operation succeeded, return its result. If it failed,
re-raise its exception.
This method takes a ``timeout`` argument for compatibility with
`concurrent.futures.Future` but it is an error to call it
before the `Future` is done, so the ``timeout`` is never used.
"""
self._clear_tb_log()
if self._result is not None:
return self._result
if self._exc_info is not None:
raise_exc_info(self._exc_info)
self._check_done()
return self._result | [
"def",
"result",
"(",
"self",
",",
"timeout",
"=",
"None",
")",
":",
"self",
".",
"_clear_tb_log",
"(",
")",
"if",
"self",
".",
"_result",
"is",
"not",
"None",
":",
"return",
"self",
".",
"_result",
"if",
"self",
".",
"_exc_info",
"is",
"not",
"None"... | https://github.com/EventGhost/EventGhost/blob/177be516849e74970d2e13cda82244be09f277ce/lib27/site-packages/tornado/concurrent.py#L220-L234 | |
securityclippy/elasticintel | aa08d3e9f5ab1c000128e95161139ce97ff0e334 | whois_lambda/requests/sessions.py | python | Session.close | (self) | Closes all adapters and as such the session | Closes all adapters and as such the session | [
"Closes",
"all",
"adapters",
"and",
"as",
"such",
"the",
"session"
] | def close(self):
"""Closes all adapters and as such the session"""
for v in self.adapters.values():
v.close() | [
"def",
"close",
"(",
"self",
")",
":",
"for",
"v",
"in",
"self",
".",
"adapters",
".",
"values",
"(",
")",
":",
"v",
".",
"close",
"(",
")"
] | https://github.com/securityclippy/elasticintel/blob/aa08d3e9f5ab1c000128e95161139ce97ff0e334/whois_lambda/requests/sessions.py#L646-L649 | ||
VisionLearningGroup/DA_Detection | 730eaca8528d22ed3aa6b4dbc1965828a697cf9a | lib/model/utils/blob.py | python | prep_im_for_blob | (im, pixel_means, target_size, max_size) | return im, im_scale | Mean subtract and scale an image for use in a blob. | Mean subtract and scale an image for use in a blob. | [
"Mean",
"subtract",
"and",
"scale",
"an",
"image",
"for",
"use",
"in",
"a",
"blob",
"."
] | def prep_im_for_blob(im, pixel_means, target_size, max_size):
"""Mean subtract and scale an image for use in a blob."""
im = im.astype(np.float32, copy=False)
im -= pixel_means
# im = im[:, :, ::-1]
im_shape = im.shape
im_size_min = np.min(im_shape[0:2])
im_size_max = np.max(im_shape[0:2])
im_scale = float(target_size) / float(im_size_min)
# Prevent the biggest axis from being more than MAX_SIZE
#if np.round(im_scale * im_size_max) > max_size:
# im_scale = float(max_size) / float(im_size_max)
# im = imresize(im, im_scale)
im = cv2.resize(im, None, None, fx=im_scale, fy=im_scale,
interpolation=cv2.INTER_LINEAR)
return im, im_scale | [
"def",
"prep_im_for_blob",
"(",
"im",
",",
"pixel_means",
",",
"target_size",
",",
"max_size",
")",
":",
"im",
"=",
"im",
".",
"astype",
"(",
"np",
".",
"float32",
",",
"copy",
"=",
"False",
")",
"im",
"-=",
"pixel_means",
"# im = im[:, :, ::-1]",
"im_shap... | https://github.com/VisionLearningGroup/DA_Detection/blob/730eaca8528d22ed3aa6b4dbc1965828a697cf9a/lib/model/utils/blob.py#L35-L52 | |
saltstack/salt | fae5bc757ad0f1716483ce7ae180b451545c2058 | salt/cloud/clouds/aliyun.py | python | destroy | (name, call=None) | return node | Destroy a node.
CLI Example:
.. code-block:: bash
salt-cloud -a destroy myinstance
salt-cloud -d myinstance | Destroy a node. | [
"Destroy",
"a",
"node",
"."
] | def destroy(name, call=None):
"""
Destroy a node.
CLI Example:
.. code-block:: bash
salt-cloud -a destroy myinstance
salt-cloud -d myinstance
"""
if call == "function":
raise SaltCloudSystemExit(
"The destroy action must be called with -d, --destroy, -a or --action."
)
__utils__["cloud.fire_event"](
"event",
"destroying instance",
"salt/cloud/{}/destroying".format(name),
args={"name": name},
sock_dir=__opts__["sock_dir"],
transport=__opts__["transport"],
)
instanceId = _get_node(name)["InstanceId"]
# have to stop instance before del it
stop_params = {"Action": "StopInstance", "InstanceId": instanceId}
query(stop_params)
params = {"Action": "DeleteInstance", "InstanceId": instanceId}
node = query(params)
__utils__["cloud.fire_event"](
"event",
"destroyed instance",
"salt/cloud/{}/destroyed".format(name),
args={"name": name},
sock_dir=__opts__["sock_dir"],
transport=__opts__["transport"],
)
return node | [
"def",
"destroy",
"(",
"name",
",",
"call",
"=",
"None",
")",
":",
"if",
"call",
"==",
"\"function\"",
":",
"raise",
"SaltCloudSystemExit",
"(",
"\"The destroy action must be called with -d, --destroy, -a or --action.\"",
")",
"__utils__",
"[",
"\"cloud.fire_event\"",
"... | https://github.com/saltstack/salt/blob/fae5bc757ad0f1716483ce7ae180b451545c2058/salt/cloud/clouds/aliyun.py#L966-L1010 | |
brython-dev/brython | 9cba5fb7f43a9b52fff13e89b403e02a1dfaa5f3 | www/src/Lib/cmath.py | python | log10 | (x) | return complex(_real, _imag) | Return the base-10 logarithm of x.
This has the same branch cut as log(). | Return the base-10 logarithm of x. | [
"Return",
"the",
"base",
"-",
"10",
"logarithm",
"of",
"x",
"."
] | def log10(x):
"""
Return the base-10 logarithm of x.
This has the same branch cut as log().
"""
ret = log(x)
_real = ret.real / _M_LN10
_imag = ret.imag / _M_LN10
return complex(_real, _imag) | [
"def",
"log10",
"(",
"x",
")",
":",
"ret",
"=",
"log",
"(",
"x",
")",
"_real",
"=",
"ret",
".",
"real",
"/",
"_M_LN10",
"_imag",
"=",
"ret",
".",
"imag",
"/",
"_M_LN10",
"return",
"complex",
"(",
"_real",
",",
"_imag",
")"
] | https://github.com/brython-dev/brython/blob/9cba5fb7f43a9b52fff13e89b403e02a1dfaa5f3/www/src/Lib/cmath.py#L554-L563 | |
dimagi/commcare-hq | d67ff1d3b4c51fa050c19e60c3253a79d3452a39 | corehq/tabs/utils.py | python | sidebar_to_dropdown | (sidebar_items, domain=None, current_url=None) | Formats sidebar_items as dropdown items
Sample input:
[(u'Application Users',
[{'description': u'Create and manage users for CommCare and CloudCare.',
'show_in_dropdown': True,
'subpages': [{'title': <function commcare_username at 0x109869488>,
'urlname': 'edit_commcare_user'},
{'title': u'Bulk Upload',
'urlname': 'upload_commcare_users'},
{'title': 'Confirm Billing Information',],
'title': u'Mobile Workers',
'url': '/a/sravan-test/settings/users/commcare/'},
(u'Project Users',
[{'description': u'Grant other CommCare HQ users access
to your project and manage user roles.',
'show_in_dropdown': True,
'subpages': [{'title': u'Invite Web User',
'urlname': 'invite_web_user'},
{'title': <function web_username at 0x10982a9b0>,
'urlname': 'user_account'},
{'title': u'My Information',
'urlname': 'domain_my_account'}],
'title': <django.utils.functional.__proxy__ object at 0x106a5c790>,
'url': '/a/sravan-test/settings/users/web/'}])]
Sample output:
[{'data_id': None,
'html': None,
'is_divider': False,
'is_header': True,
'title': u'Application Users',
'url': None},
{'data_id': None,
'html': None,
'is_divider': False,
'is_header': False,
'title': u'Mobile Workers',
'url': '/a/sravan-test/settings/users/commcare/'},
{'data_id': None,
'html': None,
'is_divider': False,
'is_header': False,
'title': u'Groups',
'url': '/a/sravan-test/settings/users/groups/'},
{'data_id': None,
'html': None,
'is_divider': False,
'is_header': True,
'title': u'Project Users',
'url': None},] | Formats sidebar_items as dropdown items
Sample input:
[(u'Application Users',
[{'description': u'Create and manage users for CommCare and CloudCare.',
'show_in_dropdown': True,
'subpages': [{'title': <function commcare_username at 0x109869488>,
'urlname': 'edit_commcare_user'},
{'title': u'Bulk Upload',
'urlname': 'upload_commcare_users'},
{'title': 'Confirm Billing Information',],
'title': u'Mobile Workers',
'url': '/a/sravan-test/settings/users/commcare/'},
(u'Project Users',
[{'description': u'Grant other CommCare HQ users access
to your project and manage user roles.',
'show_in_dropdown': True,
'subpages': [{'title': u'Invite Web User',
'urlname': 'invite_web_user'},
{'title': <function web_username at 0x10982a9b0>,
'urlname': 'user_account'},
{'title': u'My Information',
'urlname': 'domain_my_account'}],
'title': <django.utils.functional.__proxy__ object at 0x106a5c790>,
'url': '/a/sravan-test/settings/users/web/'}])]
Sample output:
[{'data_id': None,
'html': None,
'is_divider': False,
'is_header': True,
'title': u'Application Users',
'url': None},
{'data_id': None,
'html': None,
'is_divider': False,
'is_header': False,
'title': u'Mobile Workers',
'url': '/a/sravan-test/settings/users/commcare/'},
{'data_id': None,
'html': None,
'is_divider': False,
'is_header': False,
'title': u'Groups',
'url': '/a/sravan-test/settings/users/groups/'},
{'data_id': None,
'html': None,
'is_divider': False,
'is_header': True,
'title': u'Project Users',
'url': None},] | [
"Formats",
"sidebar_items",
"as",
"dropdown",
"items",
"Sample",
"input",
":",
"[",
"(",
"u",
"Application",
"Users",
"[",
"{",
"description",
":",
"u",
"Create",
"and",
"manage",
"users",
"for",
"CommCare",
"and",
"CloudCare",
".",
"show_in_dropdown",
":",
... | def sidebar_to_dropdown(sidebar_items, domain=None, current_url=None):
"""
Formats sidebar_items as dropdown items
Sample input:
[(u'Application Users',
[{'description': u'Create and manage users for CommCare and CloudCare.',
'show_in_dropdown': True,
'subpages': [{'title': <function commcare_username at 0x109869488>,
'urlname': 'edit_commcare_user'},
{'title': u'Bulk Upload',
'urlname': 'upload_commcare_users'},
{'title': 'Confirm Billing Information',],
'title': u'Mobile Workers',
'url': '/a/sravan-test/settings/users/commcare/'},
(u'Project Users',
[{'description': u'Grant other CommCare HQ users access
to your project and manage user roles.',
'show_in_dropdown': True,
'subpages': [{'title': u'Invite Web User',
'urlname': 'invite_web_user'},
{'title': <function web_username at 0x10982a9b0>,
'urlname': 'user_account'},
{'title': u'My Information',
'urlname': 'domain_my_account'}],
'title': <django.utils.functional.__proxy__ object at 0x106a5c790>,
'url': '/a/sravan-test/settings/users/web/'}])]
Sample output:
[{'data_id': None,
'html': None,
'is_divider': False,
'is_header': True,
'title': u'Application Users',
'url': None},
{'data_id': None,
'html': None,
'is_divider': False,
'is_header': False,
'title': u'Mobile Workers',
'url': '/a/sravan-test/settings/users/commcare/'},
{'data_id': None,
'html': None,
'is_divider': False,
'is_header': False,
'title': u'Groups',
'url': '/a/sravan-test/settings/users/groups/'},
{'data_id': None,
'html': None,
'is_divider': False,
'is_header': True,
'title': u'Project Users',
'url': None},]
"""
dropdown_items = []
more_items_in_sidebar = False
for side_header, side_list in sidebar_items:
dropdown_header = dropdown_dict(side_header, is_header=True)
current_dropdown_items = []
for side_item in side_list:
show_in_dropdown = side_item.get("show_in_dropdown", False)
if show_in_dropdown:
second_level_dropdowns = subpages_as_dropdowns(
side_item.get('subpages', []), level=2, domain=domain)
dropdown_item = dropdown_dict(
side_item['title'],
url=side_item['url'],
second_level_dropdowns=second_level_dropdowns,
)
current_dropdown_items.append(dropdown_item)
first_level_dropdowns = subpages_as_dropdowns(
side_item.get('subpages', []), level=1, domain=domain
)
current_dropdown_items = current_dropdown_items + first_level_dropdowns
else:
more_items_in_sidebar = True
if current_dropdown_items:
dropdown_items.extend([dropdown_header] + current_dropdown_items)
if dropdown_items and more_items_in_sidebar and current_url:
return dropdown_items + divider_and_more_menu(current_url)
else:
return dropdown_items | [
"def",
"sidebar_to_dropdown",
"(",
"sidebar_items",
",",
"domain",
"=",
"None",
",",
"current_url",
"=",
"None",
")",
":",
"dropdown_items",
"=",
"[",
"]",
"more_items_in_sidebar",
"=",
"False",
"for",
"side_header",
",",
"side_list",
"in",
"sidebar_items",
":",... | https://github.com/dimagi/commcare-hq/blob/d67ff1d3b4c51fa050c19e60c3253a79d3452a39/corehq/tabs/utils.py#L20-L100 | ||
tensorflow/model-analysis | e38c23ce76eff039548ce69e3160ed4d7984f2fc | tensorflow_model_analysis/metrics/example_count.py | python | example_count | (
name: str = EXAMPLE_COUNT_NAME,
model_names: Optional[List[str]] = None,
output_names: Optional[List[str]] = None,
sub_keys: Optional[List[metric_types.SubKey]] = None,
example_weighted: bool = False) | return computations | Returns metric computations for example count. | Returns metric computations for example count. | [
"Returns",
"metric",
"computations",
"for",
"example",
"count",
"."
] | def example_count(
name: str = EXAMPLE_COUNT_NAME,
model_names: Optional[List[str]] = None,
output_names: Optional[List[str]] = None,
sub_keys: Optional[List[metric_types.SubKey]] = None,
example_weighted: bool = False) -> metric_types.MetricComputations:
"""Returns metric computations for example count."""
computations = []
for model_name in model_names or ['']:
for output_name in output_names or ['']:
keys = []
for sub_key in sub_keys or [None]:
key = metric_types.MetricKey(
name=name,
model_name=model_name,
output_name=output_name,
sub_key=sub_key,
example_weighted=example_weighted)
keys.append(key)
# Note: This cannot be implemented based on the weight stored in
# calibration because weighted example count is used with multi-class, etc
# models that do not use calibration metrics.
computations.append(
metric_types.MetricComputation(
keys=keys,
preprocessor=None,
combiner=_ExampleCountCombiner(model_name, output_name, keys,
example_weighted)))
return computations | [
"def",
"example_count",
"(",
"name",
":",
"str",
"=",
"EXAMPLE_COUNT_NAME",
",",
"model_names",
":",
"Optional",
"[",
"List",
"[",
"str",
"]",
"]",
"=",
"None",
",",
"output_names",
":",
"Optional",
"[",
"List",
"[",
"str",
"]",
"]",
"=",
"None",
",",
... | https://github.com/tensorflow/model-analysis/blob/e38c23ce76eff039548ce69e3160ed4d7984f2fc/tensorflow_model_analysis/metrics/example_count.py#L59-L88 | |
IronLanguages/ironpython3 | 7a7bb2a872eeab0d1009fc8a6e24dca43f65b693 | Src/StdLib/Lib/modulefinder.py | python | ModuleFinder.any_missing_maybe | (self) | return missing, maybe | Return two lists, one with modules that are certainly missing
and one with modules that *may* be missing. The latter names could
either be submodules *or* just global names in the package.
The reason it can't always be determined is that it's impossible to
tell which names are imported when "from module import *" is done
with an extension module, short of actually importing it. | Return two lists, one with modules that are certainly missing
and one with modules that *may* be missing. The latter names could
either be submodules *or* just global names in the package. | [
"Return",
"two",
"lists",
"one",
"with",
"modules",
"that",
"are",
"certainly",
"missing",
"and",
"one",
"with",
"modules",
"that",
"*",
"may",
"*",
"be",
"missing",
".",
"The",
"latter",
"names",
"could",
"either",
"be",
"submodules",
"*",
"or",
"*",
"j... | def any_missing_maybe(self):
"""Return two lists, one with modules that are certainly missing
and one with modules that *may* be missing. The latter names could
either be submodules *or* just global names in the package.
The reason it can't always be determined is that it's impossible to
tell which names are imported when "from module import *" is done
with an extension module, short of actually importing it.
"""
missing = []
maybe = []
for name in self.badmodules:
if name in self.excludes:
continue
i = name.rfind(".")
if i < 0:
missing.append(name)
continue
subname = name[i+1:]
pkgname = name[:i]
pkg = self.modules.get(pkgname)
if pkg is not None:
if pkgname in self.badmodules[name]:
# The package tried to import this module itself and
# failed. It's definitely missing.
missing.append(name)
elif subname in pkg.globalnames:
# It's a global in the package: definitely not missing.
pass
elif pkg.starimports:
# It could be missing, but the package did an "import *"
# from a non-Python module, so we simply can't be sure.
maybe.append(name)
else:
# It's not a global in the package, the package didn't
# do funny star imports, it's very likely to be missing.
# The symbol could be inserted into the package from the
# outside, but since that's not good style we simply list
# it missing.
missing.append(name)
else:
missing.append(name)
missing.sort()
maybe.sort()
return missing, maybe | [
"def",
"any_missing_maybe",
"(",
"self",
")",
":",
"missing",
"=",
"[",
"]",
"maybe",
"=",
"[",
"]",
"for",
"name",
"in",
"self",
".",
"badmodules",
":",
"if",
"name",
"in",
"self",
".",
"excludes",
":",
"continue",
"i",
"=",
"name",
".",
"rfind",
... | https://github.com/IronLanguages/ironpython3/blob/7a7bb2a872eeab0d1009fc8a6e24dca43f65b693/Src/StdLib/Lib/modulefinder.py#L504-L548 | |
microsoft/Cognitive-Face-Python | 13017a13000ee1200b5b2487b38823ff787da447 | cognitive_face/large_face_list_face.py | python | add | (image, large_face_list_id, user_data=None, target_face=None) | return util.request(
'POST', url, headers=headers, params=params, json=json, data=data) | Add a face to a large face list.
The input face is specified as an image with a `target_face` rectangle. It
returns a `persisted_face_id` representing the added face, and
`persisted_face_id` will not expire.
Args:
image: A URL or a file path or a file-like object represents an image.
large_face_list_id: Valid character is letter in lower case or digit or
'-' or '_', maximum length is 64.
user_data: Optional parameter. User-specified data about the large face
list for any purpose. The maximum length is 1KB.
target_face: Optional parameter. A face rectangle to specify the target
face to be added into the large face list, in the format of
"left,top,width,height". E.g. "10,10,100,100". If there are more
than one faces in the image, `target_face` is required to specify
which face to add. No `target_face` means there is only one face
detected in the entire image.
Returns:
A new `persisted_face_id`. | Add a face to a large face list. | [
"Add",
"a",
"face",
"to",
"a",
"large",
"face",
"list",
"."
] | def add(image, large_face_list_id, user_data=None, target_face=None):
"""Add a face to a large face list.
The input face is specified as an image with a `target_face` rectangle. It
returns a `persisted_face_id` representing the added face, and
`persisted_face_id` will not expire.
Args:
image: A URL or a file path or a file-like object represents an image.
large_face_list_id: Valid character is letter in lower case or digit or
'-' or '_', maximum length is 64.
user_data: Optional parameter. User-specified data about the large face
list for any purpose. The maximum length is 1KB.
target_face: Optional parameter. A face rectangle to specify the target
face to be added into the large face list, in the format of
"left,top,width,height". E.g. "10,10,100,100". If there are more
than one faces in the image, `target_face` is required to specify
which face to add. No `target_face` means there is only one face
detected in the entire image.
Returns:
A new `persisted_face_id`.
"""
url = 'largefacelists/{}/persistedFaces'.format(large_face_list_id)
headers, data, json = util.parse_image(image)
params = {
'userData': user_data,
'targetFace': target_face,
}
return util.request(
'POST', url, headers=headers, params=params, json=json, data=data) | [
"def",
"add",
"(",
"image",
",",
"large_face_list_id",
",",
"user_data",
"=",
"None",
",",
"target_face",
"=",
"None",
")",
":",
"url",
"=",
"'largefacelists/{}/persistedFaces'",
".",
"format",
"(",
"large_face_list_id",
")",
"headers",
",",
"data",
",",
"json... | https://github.com/microsoft/Cognitive-Face-Python/blob/13017a13000ee1200b5b2487b38823ff787da447/cognitive_face/large_face_list_face.py#L10-L41 | |
sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/combinat/root_system/cartan_matrix.py | python | CartanMatrix.cartan_type | (self) | return self._cartan_type | Return the Cartan type of ``self`` or ``self`` if unknown.
EXAMPLES::
sage: C = CartanMatrix(['A',4,1])
sage: C.cartan_type()
['A', 4, 1]
If the Cartan type is unknown::
sage: C = CartanMatrix([[2,-1,-2], [-1,2,-1], [-2,-1,2]])
sage: C.cartan_type()
[ 2 -1 -2]
[-1 2 -1]
[-2 -1 2] | Return the Cartan type of ``self`` or ``self`` if unknown. | [
"Return",
"the",
"Cartan",
"type",
"of",
"self",
"or",
"self",
"if",
"unknown",
"."
] | def cartan_type(self):
"""
Return the Cartan type of ``self`` or ``self`` if unknown.
EXAMPLES::
sage: C = CartanMatrix(['A',4,1])
sage: C.cartan_type()
['A', 4, 1]
If the Cartan type is unknown::
sage: C = CartanMatrix([[2,-1,-2], [-1,2,-1], [-2,-1,2]])
sage: C.cartan_type()
[ 2 -1 -2]
[-1 2 -1]
[-2 -1 2]
"""
if self._cartan_type is None:
return self
if is_borcherds_cartan_matrix(self) and not is_generalized_cartan_matrix(self):
return self
return self._cartan_type | [
"def",
"cartan_type",
"(",
"self",
")",
":",
"if",
"self",
".",
"_cartan_type",
"is",
"None",
":",
"return",
"self",
"if",
"is_borcherds_cartan_matrix",
"(",
"self",
")",
"and",
"not",
"is_generalized_cartan_matrix",
"(",
"self",
")",
":",
"return",
"self",
... | https://github.com/sagemath/sage/blob/f9b2db94f675ff16963ccdefba4f1a3393b3fe0d/src/sage/combinat/root_system/cartan_matrix.py#L534-L556 | |
recipy/recipy | d8f8fe8ace3659f1d700bb454e68a8db453e84f4 | recipy/log.py | python | add_file_diff_to_db | (filename, tempfilename, db) | [] | def add_file_diff_to_db(filename, tempfilename, db):
diffs = db.table('filediffs')
diffs.insert({'run_id': RUN_ID,
'filename': filename,
'tempfilename': tempfilename}) | [
"def",
"add_file_diff_to_db",
"(",
"filename",
",",
"tempfilename",
",",
"db",
")",
":",
"diffs",
"=",
"db",
".",
"table",
"(",
"'filediffs'",
")",
"diffs",
".",
"insert",
"(",
"{",
"'run_id'",
":",
"RUN_ID",
",",
"'filename'",
":",
"filename",
",",
"'te... | https://github.com/recipy/recipy/blob/d8f8fe8ace3659f1d700bb454e68a8db453e84f4/recipy/log.py#L254-L258 | ||||
liaohuqiu/btcbot-open | bb46896b5e24449bc41f65a876d8d7c886a340c1 | src/btfxwss/client.py | python | BtfxWssClient.funding_loan_cancel | (self) | return self.queue_processor.account['Funding Loan Cancel'] | Return queue containing canceled funding loan associated with the user account.
:return: Queue() | Return queue containing canceled funding loan associated with the user account. | [
"Return",
"queue",
"containing",
"canceled",
"funding",
"loan",
"associated",
"with",
"the",
"user",
"account",
"."
] | def funding_loan_cancel(self):
"""Return queue containing canceled funding loan associated with the user account.
:return: Queue()
"""
return self.queue_processor.account['Funding Loan Cancel'] | [
"def",
"funding_loan_cancel",
"(",
"self",
")",
":",
"return",
"self",
".",
"queue_processor",
".",
"account",
"[",
"'Funding Loan Cancel'",
"]"
] | https://github.com/liaohuqiu/btcbot-open/blob/bb46896b5e24449bc41f65a876d8d7c886a340c1/src/btfxwss/client.py#L185-L190 | |
home-assistant/core | 265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1 | homeassistant/components/recorder/statistics.py | python | delete_duplicates | (instance: Recorder, session: scoped_session) | Identify and delete duplicated statistics.
A backup will be made of duplicated statistics before it is deleted. | Identify and delete duplicated statistics. | [
"Identify",
"and",
"delete",
"duplicated",
"statistics",
"."
] | def delete_duplicates(instance: Recorder, session: scoped_session) -> None:
"""Identify and delete duplicated statistics.
A backup will be made of duplicated statistics before it is deleted.
"""
deleted_statistics_rows, non_identical_duplicates = _delete_duplicates_from_table(
session, Statistics
)
if deleted_statistics_rows:
_LOGGER.info("Deleted %s duplicated statistics rows", deleted_statistics_rows)
if non_identical_duplicates:
isotime = dt_util.utcnow().isoformat()
backup_file_name = f"deleted_statistics.{isotime}.json"
backup_path = instance.hass.config.path(STORAGE_DIR, backup_file_name)
os.makedirs(os.path.dirname(backup_path), exist_ok=True)
with open(backup_path, "w", encoding="utf8") as backup_file:
json.dump(
non_identical_duplicates,
backup_file,
indent=4,
sort_keys=True,
cls=JSONEncoder,
)
_LOGGER.warning(
"Deleted %s non identical duplicated %s rows, a backup of the deleted rows "
"has been saved to %s",
len(non_identical_duplicates),
Statistics.__tablename__,
backup_path,
)
if deleted_statistics_rows >= MAX_DUPLICATES:
_LOGGER.warning(
"Found more than %s duplicated statistic rows, please report at "
'https://github.com/home-assistant/core/issues?q=is%%3Aissue+label%%3A"integration%%3A+recorder"+',
MAX_DUPLICATES - 1,
)
deleted_short_term_statistics_rows, _ = _delete_duplicates_from_table(
session, StatisticsShortTerm
)
if deleted_short_term_statistics_rows:
_LOGGER.warning(
"Deleted duplicated short term statistic rows, please report at "
'https://github.com/home-assistant/core/issues?q=is%%3Aissue+label%%3A"integration%%3A+recorder"+'
) | [
"def",
"delete_duplicates",
"(",
"instance",
":",
"Recorder",
",",
"session",
":",
"scoped_session",
")",
"->",
"None",
":",
"deleted_statistics_rows",
",",
"non_identical_duplicates",
"=",
"_delete_duplicates_from_table",
"(",
"session",
",",
"Statistics",
")",
"if",... | https://github.com/home-assistant/core/blob/265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1/homeassistant/components/recorder/statistics.py#L359-L406 | ||
Spacelog/Spacelog | 92df308be5923765607a89b022acb57c041c86b3 | ext/xappy-0.5-sja-1/xappy/searchconnection.py | python | SearchConnection._get_prefix_from_term | (self, term) | return term | Get the prefix of a term.
Prefixes are any initial capital letters, with the exception that R always
ends a prefix, even if followed by capital letters. | Get the prefix of a term.
Prefixes are any initial capital letters, with the exception that R always
ends a prefix, even if followed by capital letters. | [
"Get",
"the",
"prefix",
"of",
"a",
"term",
".",
"Prefixes",
"are",
"any",
"initial",
"capital",
"letters",
"with",
"the",
"exception",
"that",
"R",
"always",
"ends",
"a",
"prefix",
"even",
"if",
"followed",
"by",
"capital",
"letters",
"."
] | def _get_prefix_from_term(self, term):
"""Get the prefix of a term.
Prefixes are any initial capital letters, with the exception that R always
ends a prefix, even if followed by capital letters.
"""
for p in xrange(len(term)):
if term[p].islower():
return term[:p]
elif term[p] == 'R':
return term[:p+1]
return term | [
"def",
"_get_prefix_from_term",
"(",
"self",
",",
"term",
")",
":",
"for",
"p",
"in",
"xrange",
"(",
"len",
"(",
"term",
")",
")",
":",
"if",
"term",
"[",
"p",
"]",
".",
"islower",
"(",
")",
":",
"return",
"term",
"[",
":",
"p",
"]",
"elif",
"t... | https://github.com/Spacelog/Spacelog/blob/92df308be5923765607a89b022acb57c041c86b3/ext/xappy-0.5-sja-1/xappy/searchconnection.py#L1546-L1558 | |
holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/networkx/classes/multidigraph.py | python | MultiDiGraph.in_edges | (self) | return InMultiEdgeView(self) | An InMultiEdgeView of the Graph as G.in_edges or G.in_edges().
in_edges(self, nbunch=None, data=False, keys=False, default=None)
Parameters
----------
nbunch : single node, container, or all nodes (default= all nodes)
The view will only report edges incident to these nodes.
data : string or bool, optional (default=False)
The edge attribute returned in 3-tuple (u, v, ddict[data]).
If True, return edge attribute dict in 3-tuple (u, v, ddict).
If False, return 2-tuple (u, v).
keys : bool, optional (default=False)
If True, return edge keys with each edge.
default : value, optional (default=None)
Value used for edges that don't have the requested attribute.
Only relevant if data is not True or False.
Returns
-------
in_edges : InMultiEdgeView
A view of edge attributes, usually it iterates over (u, v)
or (u, v, k) or (u, v, k, d) tuples of edges, but can also be
used for attribute lookup as `edges[u, v, k]['foo']`.
See Also
--------
edges | An InMultiEdgeView of the Graph as G.in_edges or G.in_edges(). | [
"An",
"InMultiEdgeView",
"of",
"the",
"Graph",
"as",
"G",
".",
"in_edges",
"or",
"G",
".",
"in_edges",
"()",
"."
] | def in_edges(self):
"""An InMultiEdgeView of the Graph as G.in_edges or G.in_edges().
in_edges(self, nbunch=None, data=False, keys=False, default=None)
Parameters
----------
nbunch : single node, container, or all nodes (default= all nodes)
The view will only report edges incident to these nodes.
data : string or bool, optional (default=False)
The edge attribute returned in 3-tuple (u, v, ddict[data]).
If True, return edge attribute dict in 3-tuple (u, v, ddict).
If False, return 2-tuple (u, v).
keys : bool, optional (default=False)
If True, return edge keys with each edge.
default : value, optional (default=None)
Value used for edges that don't have the requested attribute.
Only relevant if data is not True or False.
Returns
-------
in_edges : InMultiEdgeView
A view of edge attributes, usually it iterates over (u, v)
or (u, v, k) or (u, v, k, d) tuples of edges, but can also be
used for attribute lookup as `edges[u, v, k]['foo']`.
See Also
--------
edges
"""
return InMultiEdgeView(self) | [
"def",
"in_edges",
"(",
"self",
")",
":",
"return",
"InMultiEdgeView",
"(",
"self",
")"
] | https://github.com/holzschu/Carnets/blob/44effb10ddfc6aa5c8b0687582a724ba82c6b547/Library/lib/python3.7/site-packages/networkx/classes/multidigraph.py#L600-L630 | |
windelbouwman/ppci | 915c069e0667042c085ec42c78e9e3c9a5295324 | ppci/wasm/ppci2wasm.py | python | IrToWasmCompiler.do_block | (self, ir_block) | Generate code for the given block | Generate code for the given block | [
"Generate",
"code",
"for",
"the",
"given",
"block"
] | def do_block(self, ir_block):
""" Generate code for the given block """
self.logger.debug("Generating %s", ir_block)
block_trees = self.ds.split_group_into_trees(
self.sdag, self.fi, ir_block
)
for tree in block_trees:
# print(tree)
self.do_tree(tree) | [
"def",
"do_block",
"(",
"self",
",",
"ir_block",
")",
":",
"self",
".",
"logger",
".",
"debug",
"(",
"\"Generating %s\"",
",",
"ir_block",
")",
"block_trees",
"=",
"self",
".",
"ds",
".",
"split_group_into_trees",
"(",
"self",
".",
"sdag",
",",
"self",
"... | https://github.com/windelbouwman/ppci/blob/915c069e0667042c085ec42c78e9e3c9a5295324/ppci/wasm/ppci2wasm.py#L368-L376 | ||
edublancas/sklearn-evaluation | bdf721b20c42d8cfde0f8716ab1ed6ae1029a2ea | src/sklearn_evaluation/util.py | python | _product | (k, v) | return list(product(k, v)) | Perform the product between two objects
even if they don't support iteration | Perform the product between two objects
even if they don't support iteration | [
"Perform",
"the",
"product",
"between",
"two",
"objects",
"even",
"if",
"they",
"don",
"t",
"support",
"iteration"
] | def _product(k, v):
"""
Perform the product between two objects
even if they don't support iteration
"""
if not _can_iterate(k):
k = [k]
if not _can_iterate(v):
v = [v]
return list(product(k, v)) | [
"def",
"_product",
"(",
"k",
",",
"v",
")",
":",
"if",
"not",
"_can_iterate",
"(",
"k",
")",
":",
"k",
"=",
"[",
"k",
"]",
"if",
"not",
"_can_iterate",
"(",
"v",
")",
":",
"v",
"=",
"[",
"v",
"]",
"return",
"list",
"(",
"product",
"(",
"k",
... | https://github.com/edublancas/sklearn-evaluation/blob/bdf721b20c42d8cfde0f8716ab1ed6ae1029a2ea/src/sklearn_evaluation/util.py#L90-L99 | |
SHI-Labs/Decoupled-Classification-Refinement | 16202b48eb9cbf79a9b130a98e8c209d4f24693e | faster_rcnn/core/module.py | python | MutableModule.data_shapes | (self) | return self._curr_module.data_shapes | [] | def data_shapes(self):
assert self.binded
return self._curr_module.data_shapes | [
"def",
"data_shapes",
"(",
"self",
")",
":",
"assert",
"self",
".",
"binded",
"return",
"self",
".",
"_curr_module",
".",
"data_shapes"
] | https://github.com/SHI-Labs/Decoupled-Classification-Refinement/blob/16202b48eb9cbf79a9b130a98e8c209d4f24693e/faster_rcnn/core/module.py#L773-L775 | |||
zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/whoosh/codec/plaintext.py | python | PlainTermsReader._find_field | (self, fieldname) | [] | def _find_field(self, fieldname):
self._find_root("TERMS")
if self._find_line(1, "TERMFIELD", fn=fieldname) is None:
raise TermNotFound("No field %r" % fieldname) | [
"def",
"_find_field",
"(",
"self",
",",
"fieldname",
")",
":",
"self",
".",
"_find_root",
"(",
"\"TERMS\"",
")",
"if",
"self",
".",
"_find_line",
"(",
"1",
",",
"\"TERMFIELD\"",
",",
"fn",
"=",
"fieldname",
")",
"is",
"None",
":",
"raise",
"TermNotFound"... | https://github.com/zhl2008/awd-platform/blob/0416b31abea29743387b10b3914581fbe8e7da5e/web_flaskbb/lib/python2.7/site-packages/whoosh/codec/plaintext.py#L353-L356 | ||||
kubernetes-client/python | 47b9da9de2d02b2b7a34fbe05afb44afd130d73a | kubernetes/client/models/v1_daemon_set_list.py | python | V1DaemonSetList.__ne__ | (self, other) | return self.to_dict() != other.to_dict() | Returns true if both objects are not equal | Returns true if both objects are not equal | [
"Returns",
"true",
"if",
"both",
"objects",
"are",
"not",
"equal"
] | def __ne__(self, other):
"""Returns true if both objects are not equal"""
if not isinstance(other, V1DaemonSetList):
return True
return self.to_dict() != other.to_dict() | [
"def",
"__ne__",
"(",
"self",
",",
"other",
")",
":",
"if",
"not",
"isinstance",
"(",
"other",
",",
"V1DaemonSetList",
")",
":",
"return",
"True",
"return",
"self",
".",
"to_dict",
"(",
")",
"!=",
"other",
".",
"to_dict",
"(",
")"
] | https://github.com/kubernetes-client/python/blob/47b9da9de2d02b2b7a34fbe05afb44afd130d73a/kubernetes/client/models/v1_daemon_set_list.py#L200-L205 | |
gkrizek/bash-lambda-layer | 703b0ade8174022d44779d823172ab7ac33a5505 | bin/docutils/utils/math/math2html.py | python | HybridSize.getsize | (self, function) | return eval(sizestring) | Read the size for a function and parse it. | Read the size for a function and parse it. | [
"Read",
"the",
"size",
"for",
"a",
"function",
"and",
"parse",
"it",
"."
] | def getsize(self, function):
"Read the size for a function and parse it."
sizestring = self.configsizes[function.command]
for name in function.params:
if name in sizestring:
size = function.params[name].value.computesize()
sizestring = sizestring.replace(name, str(size))
if '$' in sizestring:
Trace.error('Unconverted variable in hybrid size: ' + sizestring)
return 1
return eval(sizestring) | [
"def",
"getsize",
"(",
"self",
",",
"function",
")",
":",
"sizestring",
"=",
"self",
".",
"configsizes",
"[",
"function",
".",
"command",
"]",
"for",
"name",
"in",
"function",
".",
"params",
":",
"if",
"name",
"in",
"sizestring",
":",
"size",
"=",
"fun... | https://github.com/gkrizek/bash-lambda-layer/blob/703b0ade8174022d44779d823172ab7ac33a5505/bin/docutils/utils/math/math2html.py#L5052-L5062 | |
online-ml/river | 3732f700da72642afe54095d4b252b05c5018c7d | river/base/regressor.py | python | Regressor.predict_one | (self, x: dict) | Predicts the target value of a set of features `x`.
Parameters
----------
x
A dictionary of features.
Returns
-------
The prediction. | Predicts the target value of a set of features `x`. | [
"Predicts",
"the",
"target",
"value",
"of",
"a",
"set",
"of",
"features",
"x",
"."
] | def predict_one(self, x: dict) -> base.typing.RegTarget:
"""Predicts the target value of a set of features `x`.
Parameters
----------
x
A dictionary of features.
Returns
-------
The prediction.
""" | [
"def",
"predict_one",
"(",
"self",
",",
"x",
":",
"dict",
")",
"->",
"base",
".",
"typing",
".",
"RegTarget",
":"
] | https://github.com/online-ml/river/blob/3732f700da72642afe54095d4b252b05c5018c7d/river/base/regressor.py#L33-L45 | ||
materialsproject/pymatgen | 8128f3062a334a2edd240e4062b5b9bdd1ae6f58 | pymatgen/cli/pmg_config.py | python | configure_pmg | (args) | Handle configure command.
:param args: | Handle configure command. | [
"Handle",
"configure",
"command",
"."
] | def configure_pmg(args):
"""
Handle configure command.
:param args:
"""
if args.potcar_dirs:
setup_potcars(args)
elif args.install:
install_software(args)
elif args.var_spec:
add_config_var(args) | [
"def",
"configure_pmg",
"(",
"args",
")",
":",
"if",
"args",
".",
"potcar_dirs",
":",
"setup_potcars",
"(",
"args",
")",
"elif",
"args",
".",
"install",
":",
"install_software",
"(",
"args",
")",
"elif",
"args",
".",
"var_spec",
":",
"add_config_var",
"(",... | https://github.com/materialsproject/pymatgen/blob/8128f3062a334a2edd240e4062b5b9bdd1ae6f58/pymatgen/cli/pmg_config.py#L207-L218 | ||
golismero/golismero | 7d605b937e241f51c1ca4f47b20f755eeefb9d76 | golismero/managers/importmanager.py | python | ImportManager.orchestrator | (self) | return self.__orchestrator | :returns: Orchestrator instance.
:rtype: Orchestrator | :returns: Orchestrator instance.
:rtype: Orchestrator | [
":",
"returns",
":",
"Orchestrator",
"instance",
".",
":",
"rtype",
":",
"Orchestrator"
] | def orchestrator(self):
"""
:returns: Orchestrator instance.
:rtype: Orchestrator
"""
return self.__orchestrator | [
"def",
"orchestrator",
"(",
"self",
")",
":",
"return",
"self",
".",
"__orchestrator"
] | https://github.com/golismero/golismero/blob/7d605b937e241f51c1ca4f47b20f755eeefb9d76/golismero/managers/importmanager.py#L100-L105 | |
jina-ai/jina | c77a492fcd5adba0fc3de5347bea83dd4e7d8087 | jina/parsers/hubble/new.py | python | mixin_hub_new_parser | (parser) | Add the arguments for hub new to the parser
:param parser: the parser configure | Add the arguments for hub new to the parser
:param parser: the parser configure | [
"Add",
"the",
"arguments",
"for",
"hub",
"new",
"to",
"the",
"parser",
":",
"param",
"parser",
":",
"the",
"parser",
"configure"
] | def mixin_hub_new_parser(parser):
"""Add the arguments for hub new to the parser
:param parser: the parser configure
"""
gp = add_arg_group(parser, title='Create Executor')
gp.add_argument(
'--name',
help='the name of the Executor',
type=str,
)
gp.add_argument(
'--path',
help='the path to store the Executor',
type=str,
)
gp.add_argument(
'--advance-configuration',
help='If set, always set up advance configuration like description, keywords and url',
action='store_true',
)
gp.add_argument(
'--description',
help='the short description of the Executor',
type=str,
)
gp.add_argument(
'--keywords',
help='some keywords to help people search your Executor (separated by comma)',
type=str,
)
gp.add_argument(
'--url',
help='the URL of your GitHub repo',
type=str,
)
gp.add_argument(
'--add-dockerfile',
help='If set, add a Dockerfile to the created Executor bundle',
action='store_true',
) | [
"def",
"mixin_hub_new_parser",
"(",
"parser",
")",
":",
"gp",
"=",
"add_arg_group",
"(",
"parser",
",",
"title",
"=",
"'Create Executor'",
")",
"gp",
".",
"add_argument",
"(",
"'--name'",
",",
"help",
"=",
"'the name of the Executor'",
",",
"type",
"=",
"str",... | https://github.com/jina-ai/jina/blob/c77a492fcd5adba0fc3de5347bea83dd4e7d8087/jina/parsers/hubble/new.py#L6-L51 | ||
CastagnaIT/plugin.video.netflix | 5cf5fa436eb9956576c0f62aa31a4c7d6c5b8a4a | resources/lib/common/kodi_ops.py | python | json_rpc | (method, params=None) | return response['result'] | Executes a JSON-RPC in Kodi
:param method: The JSON-RPC method to call
:type method: string
:param params: The parameters of the method call (optional)
:type params: dict
:returns: dict -- Method call result | Executes a JSON-RPC in Kodi | [
"Executes",
"a",
"JSON",
"-",
"RPC",
"in",
"Kodi"
] | def json_rpc(method, params=None):
"""
Executes a JSON-RPC in Kodi
:param method: The JSON-RPC method to call
:type method: string
:param params: The parameters of the method call (optional)
:type params: dict
:returns: dict -- Method call result
"""
request_data = {'jsonrpc': '2.0', 'method': method, 'id': 1,
'params': params or {}}
request = json.dumps(request_data)
LOG.debug('Executing JSON-RPC: {}', request)
raw_response = xbmc.executeJSONRPC(request)
# debug('JSON-RPC response: {}'.format(raw_response))
response = json.loads(raw_response)
if 'error' in response:
raise IOError(f'JSONRPC-Error {response["error"]["code"]}: {response["error"]["message"]}')
return response['result'] | [
"def",
"json_rpc",
"(",
"method",
",",
"params",
"=",
"None",
")",
":",
"request_data",
"=",
"{",
"'jsonrpc'",
":",
"'2.0'",
",",
"'method'",
":",
"method",
",",
"'id'",
":",
"1",
",",
"'params'",
":",
"params",
"or",
"{",
"}",
"}",
"request",
"=",
... | https://github.com/CastagnaIT/plugin.video.netflix/blob/5cf5fa436eb9956576c0f62aa31a4c7d6c5b8a4a/resources/lib/common/kodi_ops.py#L37-L56 | |
holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/astropy-4.0-py3.7-macosx-10.9-x86_64.egg/astropy/io/fits/scripts/fitsheader.py | python | HeaderFormatter._parse_internal | (self, hdukeys, keywords, compressed) | return ''.join(result) | The meat of the formatting; in a separate method to allow overriding. | The meat of the formatting; in a separate method to allow overriding. | [
"The",
"meat",
"of",
"the",
"formatting",
";",
"in",
"a",
"separate",
"method",
"to",
"allow",
"overriding",
"."
] | def _parse_internal(self, hdukeys, keywords, compressed):
"""The meat of the formatting; in a separate method to allow overriding.
"""
result = []
for idx, hdu in enumerate(hdukeys):
try:
cards = self._get_cards(hdu, keywords, compressed)
except ExtensionNotFoundException:
continue
if idx > 0: # Separate HDUs by a blank line
result.append('\n')
result.append(f'# HDU {hdu} in {self.filename}:\n')
for c in cards:
result.append(f'{c}\n')
return ''.join(result) | [
"def",
"_parse_internal",
"(",
"self",
",",
"hdukeys",
",",
"keywords",
",",
"compressed",
")",
":",
"result",
"=",
"[",
"]",
"for",
"idx",
",",
"hdu",
"in",
"enumerate",
"(",
"hdukeys",
")",
":",
"try",
":",
"cards",
"=",
"self",
".",
"_get_cards",
... | https://github.com/holzschu/Carnets/blob/44effb10ddfc6aa5c8b0687582a724ba82c6b547/Library/lib/python3.7/site-packages/astropy-4.0-py3.7-macosx-10.9-x86_64.egg/astropy/io/fits/scripts/fitsheader.py#L148-L163 | |
openshift/openshift-tools | 1188778e728a6e4781acf728123e5b356380fe6f | openshift/installer/vendored/openshift-ansible-3.10.0-0.29.0/roles/lib_vendored_deps/library/oc_version.py | python | Yedit.parse_value | (inc_value, vtype='') | return inc_value | determine value type passed | determine value type passed | [
"determine",
"value",
"type",
"passed"
] | def parse_value(inc_value, vtype=''):
'''determine value type passed'''
true_bools = ['y', 'Y', 'yes', 'Yes', 'YES', 'true', 'True', 'TRUE',
'on', 'On', 'ON', ]
false_bools = ['n', 'N', 'no', 'No', 'NO', 'false', 'False', 'FALSE',
'off', 'Off', 'OFF']
# It came in as a string but you didn't specify value_type as string
# we will convert to bool if it matches any of the above cases
if isinstance(inc_value, str) and 'bool' in vtype:
if inc_value not in true_bools and inc_value not in false_bools:
raise YeditException('Not a boolean type. str=[{}] vtype=[{}]'.format(inc_value, vtype))
elif isinstance(inc_value, bool) and 'str' in vtype:
inc_value = str(inc_value)
# There is a special case where '' will turn into None after yaml loading it so skip
if isinstance(inc_value, str) and inc_value == '':
pass
# If vtype is not str then go ahead and attempt to yaml load it.
elif isinstance(inc_value, str) and 'str' not in vtype:
try:
inc_value = yaml.safe_load(inc_value)
except Exception:
raise YeditException('Could not determine type of incoming value. ' +
'value=[{}] vtype=[{}]'.format(type(inc_value), vtype))
return inc_value | [
"def",
"parse_value",
"(",
"inc_value",
",",
"vtype",
"=",
"''",
")",
":",
"true_bools",
"=",
"[",
"'y'",
",",
"'Y'",
",",
"'yes'",
",",
"'Yes'",
",",
"'YES'",
",",
"'true'",
",",
"'True'",
",",
"'TRUE'",
",",
"'on'",
",",
"'On'",
",",
"'ON'",
",",... | https://github.com/openshift/openshift-tools/blob/1188778e728a6e4781acf728123e5b356380fe6f/openshift/installer/vendored/openshift-ansible-3.10.0-0.29.0/roles/lib_vendored_deps/library/oc_version.py#L643-L669 | |
oilshell/oil | 94388e7d44a9ad879b12615f6203b38596b5a2d3 | Python-2.7.13/Lib/compiler/misc.py | python | Stack.top | (self) | return self.stack[-1] | [] | def top(self):
return self.stack[-1] | [
"def",
"top",
"(",
"self",
")",
":",
"return",
"self",
".",
"stack",
"[",
"-",
"1",
"]"
] | https://github.com/oilshell/oil/blob/94388e7d44a9ad879b12615f6203b38596b5a2d3/Python-2.7.13/Lib/compiler/misc.py#L39-L40 | |||
eborboihuc/SoundNet-tensorflow | b603cd4584a9c95a613580eef85750981214c3ae | main.py | python | Model.load_from_npy | (self) | return True | [] | def load_from_npy(self):
if self.param_G is None: return False
data_dict = self.param_G
for key in data_dict:
with tf.variable_scope(self.config['name_scope'] + '/'+ key, reuse=True):
for subkey in data_dict[key]:
try:
var = tf.get_variable(subkey)
self.sess.run(var.assign(data_dict[key][subkey]))
print('Assign pretrain model {} to {}'.format(subkey, key))
except:
print('Ignore {}'.format(key))
self.param_G.clear()
return True | [
"def",
"load_from_npy",
"(",
"self",
")",
":",
"if",
"self",
".",
"param_G",
"is",
"None",
":",
"return",
"False",
"data_dict",
"=",
"self",
".",
"param_G",
"for",
"key",
"in",
"data_dict",
":",
"with",
"tf",
".",
"variable_scope",
"(",
"self",
".",
"c... | https://github.com/eborboihuc/SoundNet-tensorflow/blob/b603cd4584a9c95a613580eef85750981214c3ae/main.py#L230-L244 | |||
beeware/toga | 090370a943bdeefcdbe035b1621fbc7caeebdf1a | src/dummy/toga_dummy/utils.py | python | LoggedObject._get_value | (self, attr, default=None) | return self._sets.get(attr, [default])[-1] | Get a value on the dummy object.
Logs the request for the attribute, and returns the value as stored on
a local attribute.
Args:
attr: The name of the attribute to get
default: The default value for the attribute if it hasn't already been set.
Returns:
The value of the attribute, or ``default`` if the value has not been set. | Get a value on the dummy object. | [
"Get",
"a",
"value",
"on",
"the",
"dummy",
"object",
"."
] | def _get_value(self, attr, default=None):
"""Get a value on the dummy object.
Logs the request for the attribute, and returns the value as stored on
a local attribute.
Args:
attr: The name of the attribute to get
default: The default value for the attribute if it hasn't already been set.
Returns:
The value of the attribute, or ``default`` if the value has not been set.
"""
EventLog.log(EventLog.GET_VALUE, instance=self, attr=attr)
self._gets.add(attr)
return self._sets.get(attr, [default])[-1] | [
"def",
"_get_value",
"(",
"self",
",",
"attr",
",",
"default",
"=",
"None",
")",
":",
"EventLog",
".",
"log",
"(",
"EventLog",
".",
"GET_VALUE",
",",
"instance",
"=",
"self",
",",
"attr",
"=",
"attr",
")",
"self",
".",
"_gets",
".",
"add",
"(",
"at... | https://github.com/beeware/toga/blob/090370a943bdeefcdbe035b1621fbc7caeebdf1a/src/dummy/toga_dummy/utils.py#L132-L147 | |
FabriceSalvaire/CodeReview | c48433467ac2a9a14b9c9026734f8c494af4aa95 | CodeReview/Diff/RawTextDocument.py | python | RawTextDocument.light_view | (self, slice_) | return RawTextDocumentLightView(self, flat_slice) | Return a :class:`RawTextDocumentLightView` instance for the corresponding slice. | Return a :class:`RawTextDocumentLightView` instance for the corresponding slice. | [
"Return",
"a",
":",
"class",
":",
"RawTextDocumentLightView",
"instance",
"for",
"the",
"corresponding",
"slice",
"."
] | def light_view(self, slice_):
"""Return a :class:`RawTextDocumentLightView` instance for the corresponding slice."""
flat_slice = self.to_flat_slice(slice_)
return RawTextDocumentLightView(self, flat_slice) | [
"def",
"light_view",
"(",
"self",
",",
"slice_",
")",
":",
"flat_slice",
"=",
"self",
".",
"to_flat_slice",
"(",
"slice_",
")",
"return",
"RawTextDocumentLightView",
"(",
"self",
",",
"flat_slice",
")"
] | https://github.com/FabriceSalvaire/CodeReview/blob/c48433467ac2a9a14b9c9026734f8c494af4aa95/CodeReview/Diff/RawTextDocument.py#L380-L386 | |
StanfordVL/taskonomy | 9f814867b5fe4165860862211e8e99b0f200144d | code/lib/data/load_ops.py | python | resize_rescale_image_low_sat_2 | (img, new_dims, new_scale, interp_order=1, current_scale=None, no_clip=False) | return img | Resize an image array with interpolation, and rescale to be
between
Parameters
----------
im : (H x W x K) ndarray
new_dims : (height, width) tuple of new dimensions.
new_scale : (min, max) tuple of new scale.
interp_order : interpolation order, default is linear.
Returns
-------
im : resized ndarray with shape (new_dims[0], new_dims[1], K) | Resize an image array with interpolation, and rescale to be
between
Parameters
----------
im : (H x W x K) ndarray
new_dims : (height, width) tuple of new dimensions.
new_scale : (min, max) tuple of new scale.
interp_order : interpolation order, default is linear.
Returns
-------
im : resized ndarray with shape (new_dims[0], new_dims[1], K) | [
"Resize",
"an",
"image",
"array",
"with",
"interpolation",
"and",
"rescale",
"to",
"be",
"between",
"Parameters",
"----------",
"im",
":",
"(",
"H",
"x",
"W",
"x",
"K",
")",
"ndarray",
"new_dims",
":",
"(",
"height",
"width",
")",
"tuple",
"of",
"new",
... | def resize_rescale_image_low_sat_2(img, new_dims, new_scale, interp_order=1, current_scale=None, no_clip=False):
"""
Resize an image array with interpolation, and rescale to be
between
Parameters
----------
im : (H x W x K) ndarray
new_dims : (height, width) tuple of new dimensions.
new_scale : (min, max) tuple of new scale.
interp_order : interpolation order, default is linear.
Returns
-------
im : resized ndarray with shape (new_dims[0], new_dims[1], K)
"""
img = skimage.img_as_float( img )
img = resize_image( img, new_dims, interp_order )
img = np.clip(img, 0.2, 0.8)
# low_sat_scale = [0.05, 0.95]
# img = rescale_image( img, low_sat_scale, current_scale=current_scale, no_clip=no_clip )
img = rescale_image( img, new_scale, current_scale=current_scale, no_clip=no_clip )
return img | [
"def",
"resize_rescale_image_low_sat_2",
"(",
"img",
",",
"new_dims",
",",
"new_scale",
",",
"interp_order",
"=",
"1",
",",
"current_scale",
"=",
"None",
",",
"no_clip",
"=",
"False",
")",
":",
"img",
"=",
"skimage",
".",
"img_as_float",
"(",
"img",
")",
"... | https://github.com/StanfordVL/taskonomy/blob/9f814867b5fe4165860862211e8e99b0f200144d/code/lib/data/load_ops.py#L188-L208 | |
WeblateOrg/weblate | 8126f3dda9d24f2846b755955132a8b8410866c8 | weblate/vcs/mercurial.py | python | HgRepository.is_valid | (self) | return os.path.exists(os.path.join(self.path, ".hg", "requires")) | Check whether this is a valid repository. | Check whether this is a valid repository. | [
"Check",
"whether",
"this",
"is",
"a",
"valid",
"repository",
"."
] | def is_valid(self):
"""Check whether this is a valid repository."""
return os.path.exists(os.path.join(self.path, ".hg", "requires")) | [
"def",
"is_valid",
"(",
"self",
")",
":",
"return",
"os",
".",
"path",
".",
"exists",
"(",
"os",
".",
"path",
".",
"join",
"(",
"self",
".",
"path",
",",
"\".hg\"",
",",
"\"requires\"",
")",
")"
] | https://github.com/WeblateOrg/weblate/blob/8126f3dda9d24f2846b755955132a8b8410866c8/weblate/vcs/mercurial.py#L57-L59 | |
PaddlePaddle/PaddleX | 2bab73f81ab54e328204e7871e6ae4a82e719f5d | paddlex/cv/models/classifier.py | python | HRNet_W18_C.__init__ | (self, num_classes=1000, **params) | [] | def __init__(self, num_classes=1000, **params):
super(HRNet_W18_C, self).__init__(
model_name='HRNet_W18_C', num_classes=num_classes, **params) | [
"def",
"__init__",
"(",
"self",
",",
"num_classes",
"=",
"1000",
",",
"*",
"*",
"params",
")",
":",
"super",
"(",
"HRNet_W18_C",
",",
"self",
")",
".",
"__init__",
"(",
"model_name",
"=",
"'HRNet_W18_C'",
",",
"num_classes",
"=",
"num_classes",
",",
"*",... | https://github.com/PaddlePaddle/PaddleX/blob/2bab73f81ab54e328204e7871e6ae4a82e719f5d/paddlex/cv/models/classifier.py#L760-L762 | ||||
OpenXenManager/openxenmanager | 1cb5c1cb13358ba584856e99a94f9669d17670ff | src/OXM/window_vm_snapshot.py | python | oxcWindowVMSnapshot.on_m_snap_newvm_activate | (self, widget, data=None) | Function called when you press "Take snapshot" | Function called when you press "Take snapshot" | [
"Function",
"called",
"when",
"you",
"press",
"Take",
"snapshot"
] | def on_m_snap_newvm_activate(self, widget, data=None):
# print self.selected_snap_ref
# TODO -> select vm with name_label
"""
Function called when you press "Take snapshot"
"""
self.on_m_newvm_activate(widget, data) | [
"def",
"on_m_snap_newvm_activate",
"(",
"self",
",",
"widget",
",",
"data",
"=",
"None",
")",
":",
"# print self.selected_snap_ref",
"# TODO -> select vm with name_label",
"self",
".",
"on_m_newvm_activate",
"(",
"widget",
",",
"data",
")"
] | https://github.com/OpenXenManager/openxenmanager/blob/1cb5c1cb13358ba584856e99a94f9669d17670ff/src/OXM/window_vm_snapshot.py#L54-L60 | ||
CoinAlpha/hummingbot | 36f6149c1644c07cd36795b915f38b8f49b798e7 | hummingbot/connector/exchange/liquid/liquid_api_order_book_data_source.py | python | LiquidAPIOrderBookDataSource._inner_messages | (self,
ws: websockets.WebSocketClientProtocol) | Generator function that returns messages from the web socket stream
:param ws: current web socket connection
:returns: message in AsyncIterable format | Generator function that returns messages from the web socket stream
:param ws: current web socket connection
:returns: message in AsyncIterable format | [
"Generator",
"function",
"that",
"returns",
"messages",
"from",
"the",
"web",
"socket",
"stream",
":",
"param",
"ws",
":",
"current",
"web",
"socket",
"connection",
":",
"returns",
":",
"message",
"in",
"AsyncIterable",
"format"
] | async def _inner_messages(self,
ws: websockets.WebSocketClientProtocol) -> AsyncIterable[str]:
"""
Generator function that returns messages from the web socket stream
:param ws: current web socket connection
:returns: message in AsyncIterable format
"""
# Terminate the recv() loop as soon as the next message timed out, so the outer loop can reconnect.
try:
while True:
try:
msg: str = await asyncio.wait_for(ws.recv(), timeout=Constants.MESSAGE_TIMEOUT)
yield msg
except asyncio.TimeoutError:
pong_waiter = await ws.ping()
await asyncio.wait_for(pong_waiter, timeout=Constants.PING_TIMEOUT)
except asyncio.TimeoutError:
self.logger().warning("WebSocket ping timed out. Going to reconnect...")
return
except ConnectionClosed:
return
finally:
await ws.close() | [
"async",
"def",
"_inner_messages",
"(",
"self",
",",
"ws",
":",
"websockets",
".",
"WebSocketClientProtocol",
")",
"->",
"AsyncIterable",
"[",
"str",
"]",
":",
"# Terminate the recv() loop as soon as the next message timed out, so the outer loop can reconnect.",
"try",
":",
... | https://github.com/CoinAlpha/hummingbot/blob/36f6149c1644c07cd36795b915f38b8f49b798e7/hummingbot/connector/exchange/liquid/liquid_api_order_book_data_source.py#L247-L269 | ||
mrkipling/maraschino | c6be9286937783ae01df2d6d8cebfc8b2734a7d7 | lib/jinja2/environment.py | python | Environment._compile | (self, source, filename) | return compile(source, filename, 'exec') | Internal hook that can be overriden to hook a different compile
method in.
.. versionadded:: 2.5 | Internal hook that can be overriden to hook a different compile
method in. | [
"Internal",
"hook",
"that",
"can",
"be",
"overriden",
"to",
"hook",
"a",
"different",
"compile",
"method",
"in",
"."
] | def _compile(self, source, filename):
"""Internal hook that can be overriden to hook a different compile
method in.
.. versionadded:: 2.5
"""
return compile(source, filename, 'exec') | [
"def",
"_compile",
"(",
"self",
",",
"source",
",",
"filename",
")",
":",
"return",
"compile",
"(",
"source",
",",
"filename",
",",
"'exec'",
")"
] | https://github.com/mrkipling/maraschino/blob/c6be9286937783ae01df2d6d8cebfc8b2734a7d7/lib/jinja2/environment.py#L445-L451 | |
IOActive/XDiFF | 552d3394e119ca4ced8115f9fd2d7e26760e40b1 | xdiff_analyze.py | python | Analyze.analyze_canary_token_code | (self, output, toplimit) | return rows | Find canary tokens of code executed in the stdout or in the stderr | Find canary tokens of code executed in the stdout or in the stderr | [
"Find",
"canary",
"tokens",
"of",
"code",
"executed",
"in",
"the",
"stdout",
"or",
"in",
"the",
"stderr"
] | def analyze_canary_token_code(self, output, toplimit):
"""Find canary tokens of code executed in the stdout or in the stderr"""
title = "Analyze Presence of Canary Tokens Code - analyze_canary_token_code"
columns = ["Testcase", "Software", "Type", "OS", "Stdout", "Stderr"]
function_risk = 3
if not self.check_minimum_risk(function_risk, title):
return False
if output:
self.settings['logger'].info(title)
rows = []
results = self.settings['db'].analyze_string_disclosure("canarytokencode")
for result in results:
if toplimit is not None and len(rows) >= toplimit:
break
rows.append([(result[0][:self.settings['testcase_limit']], result[1], result[2], result[3], result[4], result[5])])
self.dump.general(output, title, columns, rows)
return rows | [
"def",
"analyze_canary_token_code",
"(",
"self",
",",
"output",
",",
"toplimit",
")",
":",
"title",
"=",
"\"Analyze Presence of Canary Tokens Code - analyze_canary_token_code\"",
"columns",
"=",
"[",
"\"Testcase\"",
",",
"\"Software\"",
",",
"\"Type\"",
",",
"\"OS\"",
"... | https://github.com/IOActive/XDiFF/blob/552d3394e119ca4ced8115f9fd2d7e26760e40b1/xdiff_analyze.py#L536-L555 | |
caiiiac/Machine-Learning-with-Python | 1a26c4467da41ca4ebc3d5bd789ea942ef79422f | MachineLearning/venv/lib/python3.5/site-packages/pandas/core/missing.py | python | mask_missing | (arr, values_to_mask) | return mask | Return a masking array of same size/shape as arr
with entries equaling any member of values_to_mask set to True | Return a masking array of same size/shape as arr
with entries equaling any member of values_to_mask set to True | [
"Return",
"a",
"masking",
"array",
"of",
"same",
"size",
"/",
"shape",
"as",
"arr",
"with",
"entries",
"equaling",
"any",
"member",
"of",
"values_to_mask",
"set",
"to",
"True"
] | def mask_missing(arr, values_to_mask):
"""
Return a masking array of same size/shape as arr
with entries equaling any member of values_to_mask set to True
"""
dtype, values_to_mask = infer_dtype_from_array(values_to_mask)
try:
values_to_mask = np.array(values_to_mask, dtype=dtype)
except Exception:
values_to_mask = np.array(values_to_mask, dtype=object)
na_mask = isnull(values_to_mask)
nonna = values_to_mask[~na_mask]
mask = None
for x in nonna:
if mask is None:
# numpy elementwise comparison warning
if is_numeric_v_string_like(arr, x):
mask = False
else:
mask = arr == x
# if x is a string and arr is not, then we get False and we must
# expand the mask to size arr.shape
if is_scalar(mask):
mask = np.zeros(arr.shape, dtype=bool)
else:
# numpy elementwise comparison warning
if is_numeric_v_string_like(arr, x):
mask |= False
else:
mask |= arr == x
if na_mask.any():
if mask is None:
mask = isnull(arr)
else:
mask |= isnull(arr)
return mask | [
"def",
"mask_missing",
"(",
"arr",
",",
"values_to_mask",
")",
":",
"dtype",
",",
"values_to_mask",
"=",
"infer_dtype_from_array",
"(",
"values_to_mask",
")",
"try",
":",
"values_to_mask",
"=",
"np",
".",
"array",
"(",
"values_to_mask",
",",
"dtype",
"=",
"dty... | https://github.com/caiiiac/Machine-Learning-with-Python/blob/1a26c4467da41ca4ebc3d5bd789ea942ef79422f/MachineLearning/venv/lib/python3.5/site-packages/pandas/core/missing.py#L26-L70 | |
cronyo/cronyo | cd5abab0871b68bf31b18aac934303928130a441 | cronyo/vendor/yaml/constructor.py | python | FullConstructor.find_python_module | (self, name, mark, unsafe=False) | return sys.modules[name] | [] | def find_python_module(self, name, mark, unsafe=False):
if not name:
raise ConstructorError("while constructing a Python module", mark,
"expected non-empty name appended to the tag", mark)
if unsafe:
try:
__import__(name)
except ImportError as exc:
raise ConstructorError("while constructing a Python module", mark,
"cannot find module %r (%s)" % (name, exc), mark)
if not name in sys.modules:
raise ConstructorError("while constructing a Python module", mark,
"module %r is not imported" % name, mark)
return sys.modules[name] | [
"def",
"find_python_module",
"(",
"self",
",",
"name",
",",
"mark",
",",
"unsafe",
"=",
"False",
")",
":",
"if",
"not",
"name",
":",
"raise",
"ConstructorError",
"(",
"\"while constructing a Python module\"",
",",
"mark",
",",
"\"expected non-empty name appended to ... | https://github.com/cronyo/cronyo/blob/cd5abab0871b68bf31b18aac934303928130a441/cronyo/vendor/yaml/constructor.py#L506-L519 | |||
naftaliharris/tauthon | 5587ceec329b75f7caf6d65a036db61ac1bae214 | Lib/idlelib/PyShell.py | python | ModifiedInterpreter.showsyntaxerror | (self, filename=None) | Extend base class method: Add Colorizing
Color the offending position instead of printing it and pointing at it
with a caret. | Extend base class method: Add Colorizing | [
"Extend",
"base",
"class",
"method",
":",
"Add",
"Colorizing"
] | def showsyntaxerror(self, filename=None):
"""Extend base class method: Add Colorizing
Color the offending position instead of printing it and pointing at it
with a caret.
"""
text = self.tkconsole.text
stuff = self.unpackerror()
if stuff:
msg, lineno, offset, line = stuff
if lineno == 1:
pos = "iomark + %d chars" % (offset-1)
else:
pos = "iomark linestart + %d lines + %d chars" % \
(lineno-1, offset-1)
text.tag_add("ERROR", pos)
text.see(pos)
char = text.get(pos)
if char and char in IDENTCHARS:
text.tag_add("ERROR", pos + " wordstart", pos)
self.tkconsole.resetoutput()
self.write("SyntaxError: %s\n" % str(msg))
else:
self.tkconsole.resetoutput()
InteractiveInterpreter.showsyntaxerror(self, filename)
self.tkconsole.showprompt() | [
"def",
"showsyntaxerror",
"(",
"self",
",",
"filename",
"=",
"None",
")",
":",
"text",
"=",
"self",
".",
"tkconsole",
".",
"text",
"stuff",
"=",
"self",
".",
"unpackerror",
"(",
")",
"if",
"stuff",
":",
"msg",
",",
"lineno",
",",
"offset",
",",
"line... | https://github.com/naftaliharris/tauthon/blob/5587ceec329b75f7caf6d65a036db61ac1bae214/Lib/idlelib/PyShell.py#L709-L735 | ||
home-assistant/core | 265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1 | homeassistant/components/tolo/fan.py | python | ToloFan.turn_on | (
self,
speed: str | None = None,
percentage: int | None = None,
preset_mode: str | None = None,
**kwargs: Any,
) | Turn on sauna fan. | Turn on sauna fan. | [
"Turn",
"on",
"sauna",
"fan",
"."
] | def turn_on(
self,
speed: str | None = None,
percentage: int | None = None,
preset_mode: str | None = None,
**kwargs: Any,
) -> None:
"""Turn on sauna fan."""
self.coordinator.client.set_fan_on(True) | [
"def",
"turn_on",
"(",
"self",
",",
"speed",
":",
"str",
"|",
"None",
"=",
"None",
",",
"percentage",
":",
"int",
"|",
"None",
"=",
"None",
",",
"preset_mode",
":",
"str",
"|",
"None",
"=",
"None",
",",
"*",
"*",
"kwargs",
":",
"Any",
",",
")",
... | https://github.com/home-assistant/core/blob/265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1/homeassistant/components/tolo/fan.py#L44-L52 | ||
osmr/imgclsmob | f2993d3ce73a2f7ddba05da3891defb08547d504 | pytorch/pytorchcv/models/efficientnet.py | python | efficientnet_b3b | (in_size=(300, 300), **kwargs) | return get_efficientnet(version="b3", in_size=in_size, tf_mode=True, bn_eps=1e-3, model_name="efficientnet_b3b",
**kwargs) | EfficientNet-B3-b (like TF-implementation) model from 'EfficientNet: Rethinking Model Scaling for Convolutional
Neural Networks,' https://arxiv.org/abs/1905.11946.
Parameters:
----------
in_size : tuple of two ints, default (300, 300)
Spatial size of the expected input image.
pretrained : bool, default False
Whether to load the pretrained weights for model.
root : str, default '~/.torch/models'
Location for keeping the model parameters. | EfficientNet-B3-b (like TF-implementation) model from 'EfficientNet: Rethinking Model Scaling for Convolutional
Neural Networks,' https://arxiv.org/abs/1905.11946. | [
"EfficientNet",
"-",
"B3",
"-",
"b",
"(",
"like",
"TF",
"-",
"implementation",
")",
"model",
"from",
"EfficientNet",
":",
"Rethinking",
"Model",
"Scaling",
"for",
"Convolutional",
"Neural",
"Networks",
"https",
":",
"//",
"arxiv",
".",
"org",
"/",
"abs",
"... | def efficientnet_b3b(in_size=(300, 300), **kwargs):
"""
EfficientNet-B3-b (like TF-implementation) model from 'EfficientNet: Rethinking Model Scaling for Convolutional
Neural Networks,' https://arxiv.org/abs/1905.11946.
Parameters:
----------
in_size : tuple of two ints, default (300, 300)
Spatial size of the expected input image.
pretrained : bool, default False
Whether to load the pretrained weights for model.
root : str, default '~/.torch/models'
Location for keeping the model parameters.
"""
return get_efficientnet(version="b3", in_size=in_size, tf_mode=True, bn_eps=1e-3, model_name="efficientnet_b3b",
**kwargs) | [
"def",
"efficientnet_b3b",
"(",
"in_size",
"=",
"(",
"300",
",",
"300",
")",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"get_efficientnet",
"(",
"version",
"=",
"\"b3\"",
",",
"in_size",
"=",
"in_size",
",",
"tf_mode",
"=",
"True",
",",
"bn_eps",
"="... | https://github.com/osmr/imgclsmob/blob/f2993d3ce73a2f7ddba05da3891defb08547d504/pytorch/pytorchcv/models/efficientnet.py#L693-L708 | |
funcwj/conv-tasnet | f3333b0e3b20a15dfaff2a41e7abdadc0e1ff932 | nnet/libs/audio.py | python | read_wav | (fname, normalize=True, return_rate=False) | return samps | Read wave files using scipy.io.wavfile(support multi-channel) | Read wave files using scipy.io.wavfile(support multi-channel) | [
"Read",
"wave",
"files",
"using",
"scipy",
".",
"io",
".",
"wavfile",
"(",
"support",
"multi",
"-",
"channel",
")"
] | def read_wav(fname, normalize=True, return_rate=False):
"""
Read wave files using scipy.io.wavfile(support multi-channel)
"""
# samps_int16: N x C or N
# N: number of samples
# C: number of channels
samp_rate, samps_int16 = wf.read(fname)
# N x C => C x N
samps = samps_int16.astype(np.float)
# tranpose because I used to put channel axis first
if samps.ndim != 1:
samps = np.transpose(samps)
# normalize like MATLAB and librosa
if normalize:
samps = samps / MAX_INT16
if return_rate:
return samp_rate, samps
return samps | [
"def",
"read_wav",
"(",
"fname",
",",
"normalize",
"=",
"True",
",",
"return_rate",
"=",
"False",
")",
":",
"# samps_int16: N x C or N",
"# N: number of samples",
"# C: number of channels",
"samp_rate",
",",
"samps_int16",
"=",
"wf",
".",
"read",
"(",
"fname",
... | https://github.com/funcwj/conv-tasnet/blob/f3333b0e3b20a15dfaff2a41e7abdadc0e1ff932/nnet/libs/audio.py#L31-L49 | |
WerWolv/EdiZon_CheatsConfigsAndScripts | d16d36c7509c01dca770f402babd83ff2e9ae6e7 | Scripts/lib/python3.5/email/message.py | python | Message.__getitem__ | (self, name) | return self.get(name) | Get a header value.
Return None if the header is missing instead of raising an exception.
Note that if the header appeared multiple times, exactly which
occurrence gets returned is undefined. Use get_all() to get all
the values matching a header field name. | Get a header value. | [
"Get",
"a",
"header",
"value",
"."
] | def __getitem__(self, name):
"""Get a header value.
Return None if the header is missing instead of raising an exception.
Note that if the header appeared multiple times, exactly which
occurrence gets returned is undefined. Use get_all() to get all
the values matching a header field name.
"""
return self.get(name) | [
"def",
"__getitem__",
"(",
"self",
",",
"name",
")",
":",
"return",
"self",
".",
"get",
"(",
"name",
")"
] | https://github.com/WerWolv/EdiZon_CheatsConfigsAndScripts/blob/d16d36c7509c01dca770f402babd83ff2e9ae6e7/Scripts/lib/python3.5/email/message.py#L383-L392 | |
cherrypy/cherrypy | a7983fe61f7237f2354915437b04295694100372 | cherrypy/process/plugins.py | python | SimplePlugin.subscribe | (self) | Register this object as a (multi-channel) listener on the bus. | Register this object as a (multi-channel) listener on the bus. | [
"Register",
"this",
"object",
"as",
"a",
"(",
"multi",
"-",
"channel",
")",
"listener",
"on",
"the",
"bus",
"."
] | def subscribe(self):
"""Register this object as a (multi-channel) listener on the bus."""
for channel in self.bus.listeners:
# Subscribe self.start, self.exit, etc. if present.
method = getattr(self, channel, None)
if method is not None:
self.bus.subscribe(channel, method) | [
"def",
"subscribe",
"(",
"self",
")",
":",
"for",
"channel",
"in",
"self",
".",
"bus",
".",
"listeners",
":",
"# Subscribe self.start, self.exit, etc. if present.",
"method",
"=",
"getattr",
"(",
"self",
",",
"channel",
",",
"None",
")",
"if",
"method",
"is",
... | https://github.com/cherrypy/cherrypy/blob/a7983fe61f7237f2354915437b04295694100372/cherrypy/process/plugins.py#L44-L50 | ||
misterch0c/shadowbroker | e3a069bea47a2c1009697941ac214adc6f90aa8d | windows/Resources/Python/Core/Lib/lib2to3/fixer_base.py | python | BaseFix.new_name | (self, template='xxx_todo_changeme') | return name | Return a string suitable for use as an identifier
The new name is guaranteed not to conflict with other identifiers. | Return a string suitable for use as an identifier
The new name is guaranteed not to conflict with other identifiers. | [
"Return",
"a",
"string",
"suitable",
"for",
"use",
"as",
"an",
"identifier",
"The",
"new",
"name",
"is",
"guaranteed",
"not",
"to",
"conflict",
"with",
"other",
"identifiers",
"."
] | def new_name(self, template='xxx_todo_changeme'):
"""Return a string suitable for use as an identifier
The new name is guaranteed not to conflict with other identifiers.
"""
name = template
while name in self.used_names:
name = template + unicode(self.numbers.next())
self.used_names.add(name)
return name | [
"def",
"new_name",
"(",
"self",
",",
"template",
"=",
"'xxx_todo_changeme'",
")",
":",
"name",
"=",
"template",
"while",
"name",
"in",
"self",
".",
"used_names",
":",
"name",
"=",
"template",
"+",
"unicode",
"(",
"self",
".",
"numbers",
".",
"next",
"(",... | https://github.com/misterch0c/shadowbroker/blob/e3a069bea47a2c1009697941ac214adc6f90aa8d/windows/Resources/Python/Core/Lib/lib2to3/fixer_base.py#L96-L106 | |
ChineseGLUE/ChineseGLUE | 1591b85cf5427c2ff60f718d359ecb71d2b44879 | baselines/models/ernie/conlleval.py | python | evaluate | (iterable, options=None) | return counts | [] | def evaluate(iterable, options=None):
if options is None:
options = parse_args([]) # use defaults
counts = EvalCounts()
num_features = None # number of features per line
in_correct = False # currently processed chunks is correct until now
last_correct = 'O' # previous chunk tag in corpus
last_correct_type = '' # type of previously identified chunk tag
last_guessed = 'O' # previously identified chunk tag
last_guessed_type = '' # type of previous chunk tag in corpus
for line in iterable:
line = line.rstrip('\r\n')
if options.delimiter == ANY_SPACE:
features = line.split()
else:
features = line.split(options.delimiter)
if num_features is None:
num_features = len(features)
elif num_features != len(features) and len(features) != 0:
raise FormatError('unexpected number of features: %d (%d)' %
(len(features), num_features))
if len(features) == 0 or features[0] == options.boundary:
features = [options.boundary, 'O', 'O']
if len(features) < 3:
raise FormatError('unexpected number of features in line %s' % line)
guessed, guessed_type = parse_tag(features.pop())
correct, correct_type = parse_tag(features.pop())
first_item = features.pop(0)
if first_item == options.boundary:
guessed = 'O'
end_correct = end_of_chunk(last_correct, correct,
last_correct_type, correct_type)
end_guessed = end_of_chunk(last_guessed, guessed,
last_guessed_type, guessed_type)
start_correct = start_of_chunk(last_correct, correct,
last_correct_type, correct_type)
start_guessed = start_of_chunk(last_guessed, guessed,
last_guessed_type, guessed_type)
if in_correct:
if (end_correct and end_guessed and
last_guessed_type == last_correct_type):
in_correct = False
counts.correct_chunk += 1
counts.t_correct_chunk[last_correct_type] += 1
elif (end_correct != end_guessed or guessed_type != correct_type):
in_correct = False
if start_correct and start_guessed and guessed_type == correct_type:
in_correct = True
if start_correct:
counts.found_correct += 1
counts.t_found_correct[correct_type] += 1
if start_guessed:
counts.found_guessed += 1
counts.t_found_guessed[guessed_type] += 1
if first_item != options.boundary:
if correct == guessed and guessed_type == correct_type:
counts.correct_tags += 1
counts.token_counter += 1
last_guessed = guessed
last_correct = correct
last_guessed_type = guessed_type
last_correct_type = correct_type
if in_correct:
counts.correct_chunk += 1
counts.t_correct_chunk[last_correct_type] += 1
return counts | [
"def",
"evaluate",
"(",
"iterable",
",",
"options",
"=",
"None",
")",
":",
"if",
"options",
"is",
"None",
":",
"options",
"=",
"parse_args",
"(",
"[",
"]",
")",
"# use defaults",
"counts",
"=",
"EvalCounts",
"(",
")",
"num_features",
"=",
"None",
"# numb... | https://github.com/ChineseGLUE/ChineseGLUE/blob/1591b85cf5427c2ff60f718d359ecb71d2b44879/baselines/models/ernie/conlleval.py#L64-L143 | |||
celery/django-celery | c679b05b2abc174e6fa3231b120a07b49ec8f911 | djcelery/backends/database.py | python | DatabaseBackend._store_result | (self, task_id, result, status,
traceback=None, request=None) | return result | Store return value and status of an executed task. | Store return value and status of an executed task. | [
"Store",
"return",
"value",
"and",
"status",
"of",
"an",
"executed",
"task",
"."
] | def _store_result(self, task_id, result, status,
traceback=None, request=None):
"""Store return value and status of an executed task."""
self.TaskModel._default_manager.store_result(
task_id, result, status,
traceback=traceback, children=self.current_task_children(request),
)
return result | [
"def",
"_store_result",
"(",
"self",
",",
"task_id",
",",
"result",
",",
"status",
",",
"traceback",
"=",
"None",
",",
"request",
"=",
"None",
")",
":",
"self",
".",
"TaskModel",
".",
"_default_manager",
".",
"store_result",
"(",
"task_id",
",",
"result",
... | https://github.com/celery/django-celery/blob/c679b05b2abc174e6fa3231b120a07b49ec8f911/djcelery/backends/database.py#L28-L35 | |
openid/python-openid | afa6adacbe1a41d8f614c8bce2264dfbe9e76489 | openid/consumer/discover.py | python | normalizeXRI | (xri) | return xri | Normalize an XRI, stripping its scheme if present | Normalize an XRI, stripping its scheme if present | [
"Normalize",
"an",
"XRI",
"stripping",
"its",
"scheme",
"if",
"present"
] | def normalizeXRI(xri):
"""Normalize an XRI, stripping its scheme if present"""
if xri.startswith("xri://"):
xri = xri[6:]
return xri | [
"def",
"normalizeXRI",
"(",
"xri",
")",
":",
"if",
"xri",
".",
"startswith",
"(",
"\"xri://\"",
")",
":",
"xri",
"=",
"xri",
"[",
"6",
":",
"]",
"return",
"xri"
] | https://github.com/openid/python-openid/blob/afa6adacbe1a41d8f614c8bce2264dfbe9e76489/openid/consumer/discover.py#L313-L317 | |
JustDoPython/python-100-day | 4e75007195aa4cdbcb899aeb06b9b08996a4606c | day-033/enum_extend.py | python | EnumExtend.test_extending | (self) | [] | def test_extending(self):
class Color(Enum):
red = 1
green = 2
blue = 3
# TypeError: Cannot extend enumerations
with self.assertRaises(TypeError):
class MoreColor(Color):
cyan = 4
magenta = 5
yellow = 6 | [
"def",
"test_extending",
"(",
"self",
")",
":",
"class",
"Color",
"(",
"Enum",
")",
":",
"red",
"=",
"1",
"green",
"=",
"2",
"blue",
"=",
"3",
"# TypeError: Cannot extend enumerations",
"with",
"self",
".",
"assertRaises",
"(",
"TypeError",
")",
":",
"clas... | https://github.com/JustDoPython/python-100-day/blob/4e75007195aa4cdbcb899aeb06b9b08996a4606c/day-033/enum_extend.py#L7-L18 | ||||
nullism/pycnic | fe6cc4a06a18656fea875517aef508989da2a8e9 | pycnic/cli.py | python | class_sort | (routes, verbose=False) | Sort routes alphabetically by their class name. | Sort routes alphabetically by their class name. | [
"Sort",
"routes",
"alphabetically",
"by",
"their",
"class",
"name",
"."
] | def class_sort(routes, verbose=False):
"""Sort routes alphabetically by their class name."""
routes.sort(key=lambda x: full_class_name(x[2]))
max_route_length = 5 # Length of the word "route"
max_method_length = 6 # Length of the word "method"
# Determine justified string lengths
for route in routes:
methods_str = ', '.join(route[1])
max_route_length = max(max_route_length, len(route[0]))
max_method_length = max(max_method_length, len(methods_str))
ljust_method_word = 'Method'.ljust(max_method_length)
ljust_route_word = 'Route'.ljust(max_route_length)
print(ljust_route_word + ' ' + ljust_method_word + ' Class')
print('')
# Print justified strings
for route in routes:
ljust_route = route[0].ljust(max_route_length)
methods_str = ', '.join(route[1]).upper()
ljust_methods = methods_str.ljust(max_method_length)
route_cls_name = full_class_name(route[2])
print(' '.join([ljust_route, ljust_methods, route_cls_name]))
if verbose:
print_description(route[2], max_route_length, max_method_length) | [
"def",
"class_sort",
"(",
"routes",
",",
"verbose",
"=",
"False",
")",
":",
"routes",
".",
"sort",
"(",
"key",
"=",
"lambda",
"x",
":",
"full_class_name",
"(",
"x",
"[",
"2",
"]",
")",
")",
"max_route_length",
"=",
"5",
"# Length of the word \"route\"",
... | https://github.com/nullism/pycnic/blob/fe6cc4a06a18656fea875517aef508989da2a8e9/pycnic/cli.py#L84-L108 | ||
jgagneastro/coffeegrindsize | 22661ebd21831dba4cf32bfc6ba59fe3d49f879c | App/dist/coffeegrindsize.app/Contents/Resources/lib/python3.7/matplotlib/axis.py | python | Axis.get_ticklabel_extents | (self, renderer) | return bbox, bbox2 | Get the extents of the tick labels on either side
of the axes. | Get the extents of the tick labels on either side
of the axes. | [
"Get",
"the",
"extents",
"of",
"the",
"tick",
"labels",
"on",
"either",
"side",
"of",
"the",
"axes",
"."
] | def get_ticklabel_extents(self, renderer):
"""
Get the extents of the tick labels on either side
of the axes.
"""
ticks_to_draw = self._update_ticks(renderer)
ticklabelBoxes, ticklabelBoxes2 = self._get_tick_bboxes(ticks_to_draw,
renderer)
if len(ticklabelBoxes):
bbox = mtransforms.Bbox.union(ticklabelBoxes)
else:
bbox = mtransforms.Bbox.from_extents(0, 0, 0, 0)
if len(ticklabelBoxes2):
bbox2 = mtransforms.Bbox.union(ticklabelBoxes2)
else:
bbox2 = mtransforms.Bbox.from_extents(0, 0, 0, 0)
return bbox, bbox2 | [
"def",
"get_ticklabel_extents",
"(",
"self",
",",
"renderer",
")",
":",
"ticks_to_draw",
"=",
"self",
".",
"_update_ticks",
"(",
"renderer",
")",
"ticklabelBoxes",
",",
"ticklabelBoxes2",
"=",
"self",
".",
"_get_tick_bboxes",
"(",
"ticks_to_draw",
",",
"renderer",... | https://github.com/jgagneastro/coffeegrindsize/blob/22661ebd21831dba4cf32bfc6ba59fe3d49f879c/App/dist/coffeegrindsize.app/Contents/Resources/lib/python3.7/matplotlib/axis.py#L986-L1004 | |
keiffster/program-y | 8c99b56f8c32f01a7b9887b5daae9465619d0385 | src/programy/admin/tool.py | python | AdminTool.delete_folder_contents | (folder) | [] | def delete_folder_contents(folder):
shutil.rmtree(folder) | [
"def",
"delete_folder_contents",
"(",
"folder",
")",
":",
"shutil",
".",
"rmtree",
"(",
"folder",
")"
] | https://github.com/keiffster/program-y/blob/8c99b56f8c32f01a7b9887b5daae9465619d0385/src/programy/admin/tool.py#L59-L60 | ||||
pyvista/pyvista | 012dbb95a9aae406c3cd4cd94fc8c477f871e426 | examples/99-advanced/warp-by-vector-eigenmodes.py | python | make_cijkl_E_nu | (E=200, nu=0.3) | return cijkl, cij | Makes cijkl from E and nu.
Default values for steel are: E=200 GPa, nu=0.3. | Makes cijkl from E and nu.
Default values for steel are: E=200 GPa, nu=0.3. | [
"Makes",
"cijkl",
"from",
"E",
"and",
"nu",
".",
"Default",
"values",
"for",
"steel",
"are",
":",
"E",
"=",
"200",
"GPa",
"nu",
"=",
"0",
".",
"3",
"."
] | def make_cijkl_E_nu(E=200, nu=0.3):
"""Makes cijkl from E and nu.
Default values for steel are: E=200 GPa, nu=0.3."""
lambd = E * nu / (1 + nu) / (1 - 2 * nu)
mu = E / 2 / (1 + nu)
cij = np.zeros((6, 6))
cij[(0, 1, 2), (0, 1, 2)] = lambd + 2 * mu
cij[(0, 0, 1, 1, 2, 2), (1, 2, 0, 2, 0, 1)] = lambd
cij[(3, 4, 5), (3, 4, 5)] = mu
# check symmetry
assert np.allclose(cij, cij.T)
# convert to order 4 tensor
coord_mapping = {(1, 1): 1,
(2, 2): 2,
(3, 3): 3,
(2, 3): 4,
(1, 3): 5,
(1, 2): 6,
(2, 1): 6,
(3, 1): 5,
(3, 2): 4}
cijkl = np.zeros((3, 3, 3, 3))
for i in range(3):
for j in range(3):
for k in range(3):
for l in range(3):
u = coord_mapping[(i + 1, j + 1)]
v = coord_mapping[(k + 1, l + 1)]
cijkl[i, j, k, l] = cij[u - 1, v - 1]
return cijkl, cij | [
"def",
"make_cijkl_E_nu",
"(",
"E",
"=",
"200",
",",
"nu",
"=",
"0.3",
")",
":",
"lambd",
"=",
"E",
"*",
"nu",
"/",
"(",
"1",
"+",
"nu",
")",
"/",
"(",
"1",
"-",
"2",
"*",
"nu",
")",
"mu",
"=",
"E",
"/",
"2",
"/",
"(",
"1",
"+",
"nu",
... | https://github.com/pyvista/pyvista/blob/012dbb95a9aae406c3cd4cd94fc8c477f871e426/examples/99-advanced/warp-by-vector-eigenmodes.py#L39-L69 | |
holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/pandas-0.24.2-py3.7-macosx-10.9-x86_64.egg/pandas/core/reshape/merge.py | python | _groupby_and_merge | (by, on, left, right, _merge_pieces,
check_duplicates=True) | return result, lby | groupby & merge; we are always performing a left-by type operation
Parameters
----------
by: field to group
on: duplicates field
left: left frame
right: right frame
_merge_pieces: function for merging
check_duplicates: boolean, default True
should we check & clean duplicates | groupby & merge; we are always performing a left-by type operation | [
"groupby",
"&",
"merge",
";",
"we",
"are",
"always",
"performing",
"a",
"left",
"-",
"by",
"type",
"operation"
] | def _groupby_and_merge(by, on, left, right, _merge_pieces,
check_duplicates=True):
"""
groupby & merge; we are always performing a left-by type operation
Parameters
----------
by: field to group
on: duplicates field
left: left frame
right: right frame
_merge_pieces: function for merging
check_duplicates: boolean, default True
should we check & clean duplicates
"""
pieces = []
if not isinstance(by, (list, tuple)):
by = [by]
lby = left.groupby(by, sort=False)
# if we can groupby the rhs
# then we can get vastly better perf
try:
# we will check & remove duplicates if indicated
if check_duplicates:
if on is None:
on = []
elif not isinstance(on, (list, tuple)):
on = [on]
if right.duplicated(by + on).any():
right = right.drop_duplicates(by + on, keep='last')
rby = right.groupby(by, sort=False)
except KeyError:
rby = None
for key, lhs in lby:
if rby is None:
rhs = right
else:
try:
rhs = right.take(rby.indices[key])
except KeyError:
# key doesn't exist in left
lcols = lhs.columns.tolist()
cols = lcols + [r for r in right.columns
if r not in set(lcols)]
merged = lhs.reindex(columns=cols)
merged.index = range(len(merged))
pieces.append(merged)
continue
merged = _merge_pieces(lhs, rhs)
# make sure join keys are in the merged
# TODO, should _merge_pieces do this?
for k in by:
try:
if k in merged:
merged[k] = key
except KeyError:
pass
pieces.append(merged)
# preserve the original order
# if we have a missing piece this can be reset
from pandas.core.reshape.concat import concat
result = concat(pieces, ignore_index=True)
result = result.reindex(columns=pieces[0].columns, copy=False)
return result, lby | [
"def",
"_groupby_and_merge",
"(",
"by",
",",
"on",
",",
"left",
",",
"right",
",",
"_merge_pieces",
",",
"check_duplicates",
"=",
"True",
")",
":",
"pieces",
"=",
"[",
"]",
"if",
"not",
"isinstance",
"(",
"by",
",",
"(",
"list",
",",
"tuple",
")",
")... | https://github.com/holzschu/Carnets/blob/44effb10ddfc6aa5c8b0687582a724ba82c6b547/Library/lib/python3.7/site-packages/pandas-0.24.2-py3.7-macosx-10.9-x86_64.egg/pandas/core/reshape/merge.py#L55-L129 | |
omz/PythonistaAppTemplate | f560f93f8876d82a21d108977f90583df08d55af | PythonistaAppTemplate/PythonistaKit.framework/pylib_ext/matplotlib/dviread.py | python | Dvi.close | (self) | Close the underlying file if it is open. | Close the underlying file if it is open. | [
"Close",
"the",
"underlying",
"file",
"if",
"it",
"is",
"open",
"."
] | def close(self):
"""
Close the underlying file if it is open.
"""
if not self.file.closed:
self.file.close() | [
"def",
"close",
"(",
"self",
")",
":",
"if",
"not",
"self",
".",
"file",
".",
"closed",
":",
"self",
".",
"file",
".",
"close",
"(",
")"
] | https://github.com/omz/PythonistaAppTemplate/blob/f560f93f8876d82a21d108977f90583df08d55af/PythonistaAppTemplate/PythonistaKit.framework/pylib_ext/matplotlib/dviread.py#L92-L97 | ||
securityclippy/elasticintel | aa08d3e9f5ab1c000128e95161139ce97ff0e334 | ingest_feed_lambda/numpy/lib/npyio.py | python | load | (file, mmap_mode=None, allow_pickle=True, fix_imports=True,
encoding='ASCII') | Load arrays or pickled objects from ``.npy``, ``.npz`` or pickled files.
Parameters
----------
file : file-like object, string, or pathlib.Path
The file to read. File-like objects must support the
``seek()`` and ``read()`` methods. Pickled files require that the
file-like object support the ``readline()`` method as well.
mmap_mode : {None, 'r+', 'r', 'w+', 'c'}, optional
If not None, then memory-map the file, using the given mode (see
`numpy.memmap` for a detailed description of the modes). A
memory-mapped array is kept on disk. However, it can be accessed
and sliced like any ndarray. Memory mapping is especially useful
for accessing small fragments of large files without reading the
entire file into memory.
allow_pickle : bool, optional
Allow loading pickled object arrays stored in npy files. Reasons for
disallowing pickles include security, as loading pickled data can
execute arbitrary code. If pickles are disallowed, loading object
arrays will fail.
Default: True
fix_imports : bool, optional
Only useful when loading Python 2 generated pickled files on Python 3,
which includes npy/npz files containing object arrays. If `fix_imports`
is True, pickle will try to map the old Python 2 names to the new names
used in Python 3.
encoding : str, optional
What encoding to use when reading Python 2 strings. Only useful when
loading Python 2 generated pickled files on Python 3, which includes
npy/npz files containing object arrays. Values other than 'latin1',
'ASCII', and 'bytes' are not allowed, as they can corrupt numerical
data. Default: 'ASCII'
Returns
-------
result : array, tuple, dict, etc.
Data stored in the file. For ``.npz`` files, the returned instance
of NpzFile class must be closed to avoid leaking file descriptors.
Raises
------
IOError
If the input file does not exist or cannot be read.
ValueError
The file contains an object array, but allow_pickle=False given.
See Also
--------
save, savez, savez_compressed, loadtxt
memmap : Create a memory-map to an array stored in a file on disk.
lib.format.open_memmap : Create or load a memory-mapped ``.npy`` file.
Notes
-----
- If the file contains pickle data, then whatever object is stored
in the pickle is returned.
- If the file is a ``.npy`` file, then a single array is returned.
- If the file is a ``.npz`` file, then a dictionary-like object is
returned, containing ``{filename: array}`` key-value pairs, one for
each file in the archive.
- If the file is a ``.npz`` file, the returned value supports the
context manager protocol in a similar fashion to the open function::
with load('foo.npz') as data:
a = data['a']
The underlying file descriptor is closed when exiting the 'with'
block.
Examples
--------
Store data to disk, and load it again:
>>> np.save('/tmp/123', np.array([[1, 2, 3], [4, 5, 6]]))
>>> np.load('/tmp/123.npy')
array([[1, 2, 3],
[4, 5, 6]])
Store compressed data to disk, and load it again:
>>> a=np.array([[1, 2, 3], [4, 5, 6]])
>>> b=np.array([1, 2])
>>> np.savez('/tmp/123.npz', a=a, b=b)
>>> data = np.load('/tmp/123.npz')
>>> data['a']
array([[1, 2, 3],
[4, 5, 6]])
>>> data['b']
array([1, 2])
>>> data.close()
Mem-map the stored array, and then access the second row
directly from disk:
>>> X = np.load('/tmp/123.npy', mmap_mode='r')
>>> X[1, :]
memmap([4, 5, 6]) | Load arrays or pickled objects from ``.npy``, ``.npz`` or pickled files. | [
"Load",
"arrays",
"or",
"pickled",
"objects",
"from",
".",
"npy",
".",
"npz",
"or",
"pickled",
"files",
"."
] | def load(file, mmap_mode=None, allow_pickle=True, fix_imports=True,
encoding='ASCII'):
"""
Load arrays or pickled objects from ``.npy``, ``.npz`` or pickled files.
Parameters
----------
file : file-like object, string, or pathlib.Path
The file to read. File-like objects must support the
``seek()`` and ``read()`` methods. Pickled files require that the
file-like object support the ``readline()`` method as well.
mmap_mode : {None, 'r+', 'r', 'w+', 'c'}, optional
If not None, then memory-map the file, using the given mode (see
`numpy.memmap` for a detailed description of the modes). A
memory-mapped array is kept on disk. However, it can be accessed
and sliced like any ndarray. Memory mapping is especially useful
for accessing small fragments of large files without reading the
entire file into memory.
allow_pickle : bool, optional
Allow loading pickled object arrays stored in npy files. Reasons for
disallowing pickles include security, as loading pickled data can
execute arbitrary code. If pickles are disallowed, loading object
arrays will fail.
Default: True
fix_imports : bool, optional
Only useful when loading Python 2 generated pickled files on Python 3,
which includes npy/npz files containing object arrays. If `fix_imports`
is True, pickle will try to map the old Python 2 names to the new names
used in Python 3.
encoding : str, optional
What encoding to use when reading Python 2 strings. Only useful when
loading Python 2 generated pickled files on Python 3, which includes
npy/npz files containing object arrays. Values other than 'latin1',
'ASCII', and 'bytes' are not allowed, as they can corrupt numerical
data. Default: 'ASCII'
Returns
-------
result : array, tuple, dict, etc.
Data stored in the file. For ``.npz`` files, the returned instance
of NpzFile class must be closed to avoid leaking file descriptors.
Raises
------
IOError
If the input file does not exist or cannot be read.
ValueError
The file contains an object array, but allow_pickle=False given.
See Also
--------
save, savez, savez_compressed, loadtxt
memmap : Create a memory-map to an array stored in a file on disk.
lib.format.open_memmap : Create or load a memory-mapped ``.npy`` file.
Notes
-----
- If the file contains pickle data, then whatever object is stored
in the pickle is returned.
- If the file is a ``.npy`` file, then a single array is returned.
- If the file is a ``.npz`` file, then a dictionary-like object is
returned, containing ``{filename: array}`` key-value pairs, one for
each file in the archive.
- If the file is a ``.npz`` file, the returned value supports the
context manager protocol in a similar fashion to the open function::
with load('foo.npz') as data:
a = data['a']
The underlying file descriptor is closed when exiting the 'with'
block.
Examples
--------
Store data to disk, and load it again:
>>> np.save('/tmp/123', np.array([[1, 2, 3], [4, 5, 6]]))
>>> np.load('/tmp/123.npy')
array([[1, 2, 3],
[4, 5, 6]])
Store compressed data to disk, and load it again:
>>> a=np.array([[1, 2, 3], [4, 5, 6]])
>>> b=np.array([1, 2])
>>> np.savez('/tmp/123.npz', a=a, b=b)
>>> data = np.load('/tmp/123.npz')
>>> data['a']
array([[1, 2, 3],
[4, 5, 6]])
>>> data['b']
array([1, 2])
>>> data.close()
Mem-map the stored array, and then access the second row
directly from disk:
>>> X = np.load('/tmp/123.npy', mmap_mode='r')
>>> X[1, :]
memmap([4, 5, 6])
"""
own_fid = False
if isinstance(file, basestring):
fid = open(file, "rb")
own_fid = True
elif is_pathlib_path(file):
fid = file.open("rb")
own_fid = True
else:
fid = file
if encoding not in ('ASCII', 'latin1', 'bytes'):
# The 'encoding' value for pickle also affects what encoding
# the serialized binary data of NumPy arrays is loaded
# in. Pickle does not pass on the encoding information to
# NumPy. The unpickling code in numpy.core.multiarray is
# written to assume that unicode data appearing where binary
# should be is in 'latin1'. 'bytes' is also safe, as is 'ASCII'.
#
# Other encoding values can corrupt binary data, and we
# purposefully disallow them. For the same reason, the errors=
# argument is not exposed, as values other than 'strict'
# result can similarly silently corrupt numerical data.
raise ValueError("encoding must be 'ASCII', 'latin1', or 'bytes'")
if sys.version_info[0] >= 3:
pickle_kwargs = dict(encoding=encoding, fix_imports=fix_imports)
else:
# Nothing to do on Python 2
pickle_kwargs = {}
try:
# Code to distinguish from NumPy binary files and pickles.
_ZIP_PREFIX = b'PK\x03\x04'
N = len(format.MAGIC_PREFIX)
magic = fid.read(N)
# If the file size is less than N, we need to make sure not
# to seek past the beginning of the file
fid.seek(-min(N, len(magic)), 1) # back-up
if magic.startswith(_ZIP_PREFIX):
# zip-file (assume .npz)
# Transfer file ownership to NpzFile
tmp = own_fid
own_fid = False
return NpzFile(fid, own_fid=tmp, allow_pickle=allow_pickle,
pickle_kwargs=pickle_kwargs)
elif magic == format.MAGIC_PREFIX:
# .npy file
if mmap_mode:
return format.open_memmap(file, mode=mmap_mode)
else:
return format.read_array(fid, allow_pickle=allow_pickle,
pickle_kwargs=pickle_kwargs)
else:
# Try a pickle
if not allow_pickle:
raise ValueError("allow_pickle=False, but file does not contain "
"non-pickled data")
try:
return pickle.load(fid, **pickle_kwargs)
except:
raise IOError(
"Failed to interpret file %s as a pickle" % repr(file))
finally:
if own_fid:
fid.close() | [
"def",
"load",
"(",
"file",
",",
"mmap_mode",
"=",
"None",
",",
"allow_pickle",
"=",
"True",
",",
"fix_imports",
"=",
"True",
",",
"encoding",
"=",
"'ASCII'",
")",
":",
"own_fid",
"=",
"False",
"if",
"isinstance",
"(",
"file",
",",
"basestring",
")",
"... | https://github.com/securityclippy/elasticintel/blob/aa08d3e9f5ab1c000128e95161139ce97ff0e334/ingest_feed_lambda/numpy/lib/npyio.py#L266-L432 | ||
JetBrains/python-skeletons | 95ad24b666e475998e5d1cc02ed53a2188036167 | datetime.py | python | date.replace | (self, year=None, month=None, day=None) | return _datetime.date(0, 0, 0) | Return a date with the same value, except for those parameters given
new values by whichever keyword arguments are specified.
:type year: numbers.Integral
:type month: numbers.Integral
:type day: numbers.Integral
:rtype: _datetime.date | Return a date with the same value, except for those parameters given
new values by whichever keyword arguments are specified. | [
"Return",
"a",
"date",
"with",
"the",
"same",
"value",
"except",
"for",
"those",
"parameters",
"given",
"new",
"values",
"by",
"whichever",
"keyword",
"arguments",
"are",
"specified",
"."
] | def replace(self, year=None, month=None, day=None):
"""Return a date with the same value, except for those parameters given
new values by whichever keyword arguments are specified.
:type year: numbers.Integral
:type month: numbers.Integral
:type day: numbers.Integral
:rtype: _datetime.date
"""
return _datetime.date(0, 0, 0) | [
"def",
"replace",
"(",
"self",
",",
"year",
"=",
"None",
",",
"month",
"=",
"None",
",",
"day",
"=",
"None",
")",
":",
"return",
"_datetime",
".",
"date",
"(",
"0",
",",
"0",
",",
"0",
")"
] | https://github.com/JetBrains/python-skeletons/blob/95ad24b666e475998e5d1cc02ed53a2188036167/datetime.py#L189-L198 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.