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elbayadm/attn2d
|
982653439dedc7306e484e00b3dfb90e2cd7c9e1
|
examples/pervasive/modules/archive/dilated_resnet.py
|
python
|
DilatedResnet.forward
|
(self, x,
encoder_mask=None,
decoder_mask=None,
incremental_state=None)
|
return add_up
|
Input : N, Tt, Ts, C
Output : N, Tt, Ts, C
|
Input : N, Tt, Ts, C
Output : N, Tt, Ts, C
|
[
"Input",
":",
"N",
"Tt",
"Ts",
"C",
"Output",
":",
"N",
"Tt",
"Ts",
"C"
] |
def forward(self, x,
encoder_mask=None,
decoder_mask=None,
incremental_state=None):
"""
Input : N, Tt, Ts, C
Output : N, Tt, Ts, C
"""
if self.reduce_channels is not None:
x = self.reduce_channels(x)
add_up = self.add_up_scale * x
for layer in self.residual_blocks:
x = layer(x,
encoder_mask=encoder_mask,
decoder_mask=decoder_mask,
incremental_state=incremental_state)
add_up += self.add_up_scale * x
return add_up
|
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https://github.com/elbayadm/attn2d/blob/982653439dedc7306e484e00b3dfb90e2cd7c9e1/examples/pervasive/modules/archive/dilated_resnet.py#L50-L67
|
|
holzschu/Carnets
|
44effb10ddfc6aa5c8b0687582a724ba82c6b547
|
Library/lib/python3.7/site-packages/pip/_internal/vcs/subversion.py
|
python
|
Subversion.is_commit_id_equal
|
(cls, dest, name)
|
return False
|
Always assume the versions don't match
|
Always assume the versions don't match
|
[
"Always",
"assume",
"the",
"versions",
"don",
"t",
"match"
] |
def is_commit_id_equal(cls, dest, name):
"""Always assume the versions don't match"""
return False
|
[
"def",
"is_commit_id_equal",
"(",
"cls",
",",
"dest",
",",
"name",
")",
":",
"return",
"False"
] |
https://github.com/holzschu/Carnets/blob/44effb10ddfc6aa5c8b0687582a724ba82c6b547/Library/lib/python3.7/site-packages/pip/_internal/vcs/subversion.py#L229-L231
|
|
google/coursebuilder-core
|
08f809db3226d9269e30d5edd0edd33bd22041f4
|
coursebuilder/modules/analytics/clustering.py
|
python
|
_has_right_side
|
(dim)
|
return dim.get(DIM_HIGH) != None and dim.get(DIM_HIGH) != ''
|
Returns True if the value of dim[DIM_HIGH] is not None or ''.
|
Returns True if the value of dim[DIM_HIGH] is not None or ''.
|
[
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"[",
"DIM_HIGH",
"]",
"is",
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"None",
"or",
"."
] |
def _has_right_side(dim):
"""Returns True if the value of dim[DIM_HIGH] is not None or ''."""
return dim.get(DIM_HIGH) != None and dim.get(DIM_HIGH) != ''
|
[
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"!=",
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".",
"get",
"(",
"DIM_HIGH",
")",
"!=",
"''"
] |
https://github.com/google/coursebuilder-core/blob/08f809db3226d9269e30d5edd0edd33bd22041f4/coursebuilder/modules/analytics/clustering.py#L188-L190
|
|
twilio/twilio-python
|
6e1e811ea57a1edfadd5161ace87397c563f6915
|
twilio/rest/studio/v2/flow/__init__.py
|
python
|
FlowInstance.delete
|
(self)
|
return self._proxy.delete()
|
Deletes the FlowInstance
:returns: True if delete succeeds, False otherwise
:rtype: bool
|
Deletes the FlowInstance
|
[
"Deletes",
"the",
"FlowInstance"
] |
def delete(self):
"""
Deletes the FlowInstance
:returns: True if delete succeeds, False otherwise
:rtype: bool
"""
return self._proxy.delete()
|
[
"def",
"delete",
"(",
"self",
")",
":",
"return",
"self",
".",
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".",
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"(",
")"
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https://github.com/twilio/twilio-python/blob/6e1e811ea57a1edfadd5161ace87397c563f6915/twilio/rest/studio/v2/flow/__init__.py#L523-L530
|
|
KalleHallden/AutoTimer
|
2d954216700c4930baa154e28dbddc34609af7ce
|
env/lib/python2.7/site-packages/pip/_vendor/distlib/locators.py
|
python
|
PyPIJSONLocator.get_distribution_names
|
(self)
|
Return all the distribution names known to this locator.
|
Return all the distribution names known to this locator.
|
[
"Return",
"all",
"the",
"distribution",
"names",
"known",
"to",
"this",
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] |
def get_distribution_names(self):
"""
Return all the distribution names known to this locator.
"""
raise NotImplementedError('Not available from this locator')
|
[
"def",
"get_distribution_names",
"(",
"self",
")",
":",
"raise",
"NotImplementedError",
"(",
"'Not available from this locator'",
")"
] |
https://github.com/KalleHallden/AutoTimer/blob/2d954216700c4930baa154e28dbddc34609af7ce/env/lib/python2.7/site-packages/pip/_vendor/distlib/locators.py#L461-L465
|
||
fredrik-johansson/mpmath
|
c11db84b3237bd8fc6721f5a0c5d7c0c98a24dc1
|
mpmath/math2.py
|
python
|
erfc
|
(x)
|
return 1.0 - _erf_taylor(x)
|
erfc of a real number.
|
erfc of a real number.
|
[
"erfc",
"of",
"a",
"real",
"number",
"."
] |
def erfc(x):
"""
erfc of a real number.
"""
x = float(x)
if x != x:
return x
if x < 0.0:
if x < -6.0:
return 2.0
return 2.0-erfc(-x)
if x > 9.0:
return _erfc_asymp(x)
if x >= 1.0:
return _erfc_mid(x)
return 1.0 - _erf_taylor(x)
|
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https://github.com/fredrik-johansson/mpmath/blob/c11db84b3237bd8fc6721f5a0c5d7c0c98a24dc1/mpmath/math2.py#L440-L455
|
|
napari/napari
|
dbf4158e801fa7a429de8ef1cdee73bf6d64c61e
|
napari/utils/context/_expressions.py
|
python
|
parse_expression
|
(expr: str)
|
Parse string expression into an :class:`Expr` instance.
Parameters
----------
expr : str
Expression to parse.
Returns
-------
Expr
Instance of `Expr`.
Raises
------
SyntaxError
If the provided string is not an expression (e.g. it's a statement), or
if it uses any forbidden syntax components (e.g. Call, Attribute,
Containers, Indexing, Slicing, f-strings, named expression,
comprehensions.)
|
Parse string expression into an :class:`Expr` instance.
|
[
"Parse",
"string",
"expression",
"into",
"an",
":",
"class",
":",
"Expr",
"instance",
"."
] |
def parse_expression(expr: str) -> Expr:
"""Parse string expression into an :class:`Expr` instance.
Parameters
----------
expr : str
Expression to parse.
Returns
-------
Expr
Instance of `Expr`.
Raises
------
SyntaxError
If the provided string is not an expression (e.g. it's a statement), or
if it uses any forbidden syntax components (e.g. Call, Attribute,
Containers, Indexing, Slicing, f-strings, named expression,
comprehensions.)
"""
try:
# mode='eval' means the expr must consist of a single expression
tree = ast.parse(expr, mode='eval')
if not isinstance(tree, ast.Expression):
raise SyntaxError # pragma: no cover
return ExprTranformer().visit(tree.body)
except SyntaxError as e:
raise SyntaxError(
trans._(
"{expr} is not a valid expression: ({error}).",
deferred=True,
expr=f"{expr!r}",
error=e,
)
) from None
|
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https://github.com/napari/napari/blob/dbf4158e801fa7a429de8ef1cdee73bf6d64c61e/napari/utils/context/_expressions.py#L59-L94
|
||
djaodjin/djaodjin-saas
|
17f66871bd571741b06d93876da401a05a2cc162
|
saas/utils.py
|
python
|
get_user_serializer
|
()
|
return import_string(settings.USER_SERIALIZER)
|
Returns the user serializer model that is active in this project.
|
Returns the user serializer model that is active in this project.
|
[
"Returns",
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"user",
"serializer",
"model",
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"is",
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"."
] |
def get_user_serializer():
"""
Returns the user serializer model that is active in this project.
"""
from . import settings
return import_string(settings.USER_SERIALIZER)
|
[
"def",
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"import",
"settings",
"return",
"import_string",
"(",
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"USER_SERIALIZER",
")"
] |
https://github.com/djaodjin/djaodjin-saas/blob/17f66871bd571741b06d93876da401a05a2cc162/saas/utils.py#L195-L200
|
|
NVIDIA/NeMo
|
5b0c0b4dec12d87d3cd960846de4105309ce938e
|
nemo/collections/asr/parts/submodules/multi_head_attention.py
|
python
|
MultiHeadAttention.__init__
|
(self, n_head, n_feat, dropout_rate)
|
Construct an MultiHeadedAttention object.
|
Construct an MultiHeadedAttention object.
|
[
"Construct",
"an",
"MultiHeadedAttention",
"object",
"."
] |
def __init__(self, n_head, n_feat, dropout_rate):
"""Construct an MultiHeadedAttention object."""
super(MultiHeadAttention, self).__init__()
assert n_feat % n_head == 0
# We assume d_v always equals d_k
self.d_k = n_feat // n_head
self.h = n_head
self.linear_q = nn.Linear(n_feat, n_feat)
self.linear_k = nn.Linear(n_feat, n_feat)
self.linear_v = nn.Linear(n_feat, n_feat)
self.linear_out = nn.Linear(n_feat, n_feat)
self.dropout = nn.Dropout(p=dropout_rate)
|
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https://github.com/NVIDIA/NeMo/blob/5b0c0b4dec12d87d3cd960846de4105309ce938e/nemo/collections/asr/parts/submodules/multi_head_attention.py#L55-L66
|
||
google/trax
|
d6cae2067dedd0490b78d831033607357e975015
|
trax/layers/base.py
|
python
|
Layer._settable_attrs
|
(self)
|
return ('weights', 'state', 'rng')
|
We only allow to set these attributes in Trax layers to prevent typos.
|
We only allow to set these attributes in Trax layers to prevent typos.
|
[
"We",
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"to",
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"these",
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] |
def _settable_attrs(self):
"""We only allow to set these attributes in Trax layers to prevent typos."""
return ('weights', 'state', 'rng')
|
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https://github.com/google/trax/blob/d6cae2067dedd0490b78d831033607357e975015/trax/layers/base.py#L676-L678
|
|
pyvista/pyvista
|
012dbb95a9aae406c3cd4cd94fc8c477f871e426
|
pyvista/plotting/charts.py
|
python
|
StackPlot.update
|
(self, x, ys)
|
Update the locations and/or size of the stacks (areas) in this plot.
Parameters
----------
x : array_like
The new x coordinates of the stacks (areas) to draw.
ys : list or tuple of array_like
The new sizes of the stacks (areas) to draw.
Examples
--------
Create a stack plot.
>>> import pyvista
>>> chart = pyvista.Chart2D()
>>> plot = chart.stack([0, 1, 2], [[2, 1, 3],[1, 2, 1]])
>>> chart.show()
Update the stack sizes.
>>> plot.update([0, 1, 2], [[3, 1, 2], [0, 3, 1]])
>>> chart.show()
|
Update the locations and/or size of the stacks (areas) in this plot.
|
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"Update",
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"or",
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"this",
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] |
def update(self, x, ys):
"""Update the locations and/or size of the stacks (areas) in this plot.
Parameters
----------
x : array_like
The new x coordinates of the stacks (areas) to draw.
ys : list or tuple of array_like
The new sizes of the stacks (areas) to draw.
Examples
--------
Create a stack plot.
>>> import pyvista
>>> chart = pyvista.Chart2D()
>>> plot = chart.stack([0, 1, 2], [[2, 1, 3],[1, 2, 1]])
>>> chart.show()
Update the stack sizes.
>>> plot.update([0, 1, 2], [[3, 1, 2], [0, 3, 1]])
>>> chart.show()
"""
if len(x) > 0:
if not isinstance(ys[0], (Sequence, np.ndarray)):
ys = (ys,)
y_data = {f"y{i}": np.array(ys[i], copy=False) for i in range(len(ys))}
self._table.update({"x": np.array(x, copy=False), **y_data})
self.visible = True
else:
self.visible = False
|
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https://github.com/pyvista/pyvista/blob/012dbb95a9aae406c3cd4cd94fc8c477f871e426/pyvista/plotting/charts.py#L2669-L2702
|
||
pymedusa/Medusa
|
1405fbb6eb8ef4d20fcca24c32ddca52b11f0f38
|
ext/boto/elasticache/layer1.py
|
python
|
ElastiCacheConnection.describe_reserved_cache_nodes
|
(self, reserved_cache_node_id=None,
reserved_cache_nodes_offering_id=None,
cache_node_type=None, duration=None,
product_description=None,
offering_type=None, max_records=None,
marker=None)
|
return self._make_request(
action='DescribeReservedCacheNodes',
verb='POST',
path='/', params=params)
|
The DescribeReservedCacheNodes operation returns information
about reserved cache nodes for this account, or about a
specified reserved cache node.
:type reserved_cache_node_id: string
:param reserved_cache_node_id: The reserved cache node identifier
filter value. Use this parameter to show only the reservation that
matches the specified reservation ID.
:type reserved_cache_nodes_offering_id: string
:param reserved_cache_nodes_offering_id: The offering identifier filter
value. Use this parameter to show only purchased reservations
matching the specified offering identifier.
:type cache_node_type: string
:param cache_node_type: The cache node type filter value. Use this
parameter to show only those reservations matching the specified
cache node type.
:type duration: string
:param duration: The duration filter value, specified in years or
seconds. Use this parameter to show only reservations for this
duration.
Valid Values: `1 | 3 | 31536000 | 94608000`
:type product_description: string
:param product_description: The product description filter value. Use
this parameter to show only those reservations matching the
specified product description.
:type offering_type: string
:param offering_type: The offering type filter value. Use this
parameter to show only the available offerings matching the
specified offering type.
Valid values: `"Light Utilization" | "Medium Utilization" | "Heavy
Utilization" `
:type max_records: integer
:param max_records: The maximum number of records to include in the
response. If more records exist than the specified `MaxRecords`
value, a marker is included in the response so that the remaining
results can be retrieved.
Default: 100
Constraints: minimum 20; maximum 100.
:type marker: string
:param marker: An optional marker returned from a prior request. Use
this marker for pagination of results from this operation. If this
parameter is specified, the response includes only records beyond
the marker, up to the value specified by MaxRecords .
|
The DescribeReservedCacheNodes operation returns information
about reserved cache nodes for this account, or about a
specified reserved cache node.
|
[
"The",
"DescribeReservedCacheNodes",
"operation",
"returns",
"information",
"about",
"reserved",
"cache",
"nodes",
"for",
"this",
"account",
"or",
"about",
"a",
"specified",
"reserved",
"cache",
"node",
"."
] |
def describe_reserved_cache_nodes(self, reserved_cache_node_id=None,
reserved_cache_nodes_offering_id=None,
cache_node_type=None, duration=None,
product_description=None,
offering_type=None, max_records=None,
marker=None):
"""
The DescribeReservedCacheNodes operation returns information
about reserved cache nodes for this account, or about a
specified reserved cache node.
:type reserved_cache_node_id: string
:param reserved_cache_node_id: The reserved cache node identifier
filter value. Use this parameter to show only the reservation that
matches the specified reservation ID.
:type reserved_cache_nodes_offering_id: string
:param reserved_cache_nodes_offering_id: The offering identifier filter
value. Use this parameter to show only purchased reservations
matching the specified offering identifier.
:type cache_node_type: string
:param cache_node_type: The cache node type filter value. Use this
parameter to show only those reservations matching the specified
cache node type.
:type duration: string
:param duration: The duration filter value, specified in years or
seconds. Use this parameter to show only reservations for this
duration.
Valid Values: `1 | 3 | 31536000 | 94608000`
:type product_description: string
:param product_description: The product description filter value. Use
this parameter to show only those reservations matching the
specified product description.
:type offering_type: string
:param offering_type: The offering type filter value. Use this
parameter to show only the available offerings matching the
specified offering type.
Valid values: `"Light Utilization" | "Medium Utilization" | "Heavy
Utilization" `
:type max_records: integer
:param max_records: The maximum number of records to include in the
response. If more records exist than the specified `MaxRecords`
value, a marker is included in the response so that the remaining
results can be retrieved.
Default: 100
Constraints: minimum 20; maximum 100.
:type marker: string
:param marker: An optional marker returned from a prior request. Use
this marker for pagination of results from this operation. If this
parameter is specified, the response includes only records beyond
the marker, up to the value specified by MaxRecords .
"""
params = {}
if reserved_cache_node_id is not None:
params['ReservedCacheNodeId'] = reserved_cache_node_id
if reserved_cache_nodes_offering_id is not None:
params['ReservedCacheNodesOfferingId'] = reserved_cache_nodes_offering_id
if cache_node_type is not None:
params['CacheNodeType'] = cache_node_type
if duration is not None:
params['Duration'] = duration
if product_description is not None:
params['ProductDescription'] = product_description
if offering_type is not None:
params['OfferingType'] = offering_type
if max_records is not None:
params['MaxRecords'] = max_records
if marker is not None:
params['Marker'] = marker
return self._make_request(
action='DescribeReservedCacheNodes',
verb='POST',
path='/', params=params)
|
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",",
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")"
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https://github.com/pymedusa/Medusa/blob/1405fbb6eb8ef4d20fcca24c32ddca52b11f0f38/ext/boto/elasticache/layer1.py#L1007-L1087
|
|
openshift/openshift-tools
|
1188778e728a6e4781acf728123e5b356380fe6f
|
openshift/installer/vendored/openshift-ansible-3.9.40/roles/lib_vendored_deps/library/oc_group.py
|
python
|
OCGroup.needs_update
|
(self)
|
return not Utils.check_def_equal(self.config.data, self.group.yaml_dict, skip_keys=['users'], debug=True)
|
verify an update is needed
|
verify an update is needed
|
[
"verify",
"an",
"update",
"is",
"needed"
] |
def needs_update(self):
''' verify an update is needed '''
return not Utils.check_def_equal(self.config.data, self.group.yaml_dict, skip_keys=['users'], debug=True)
|
[
"def",
"needs_update",
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"self",
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"check_def_equal",
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",",
"skip_keys",
"=",
"[",
"'users'",
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",",
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")"
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https://github.com/openshift/openshift-tools/blob/1188778e728a6e4781acf728123e5b356380fe6f/openshift/installer/vendored/openshift-ansible-3.9.40/roles/lib_vendored_deps/library/oc_group.py#L1541-L1543
|
|
benedekrozemberczki/role2vec
|
d43fc337d00f8fe50475165c0e3695ba795df89a
|
src/walkers.py
|
python
|
alias_setup
|
(probs)
|
return J, q
|
Compute utility lists for non-uniform sampling from discrete distributions.
Refer to https://hips.seas.harvard.edu/blog/2013/03/03/the-alias-method-efficient-sampling-with-many-discrete-outcomes/
for details
|
Compute utility lists for non-uniform sampling from discrete distributions.
Refer to https://hips.seas.harvard.edu/blog/2013/03/03/the-alias-method-efficient-sampling-with-many-discrete-outcomes/
for details
|
[
"Compute",
"utility",
"lists",
"for",
"non",
"-",
"uniform",
"sampling",
"from",
"discrete",
"distributions",
".",
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"https",
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"//",
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".",
"seas",
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"harvard",
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"blog",
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"2013",
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"03",
"/",
"03",
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"-",
"sampling",
"-",
"with",
"-",
"many",
"-",
"discrete",
"-",
"outcomes",
"/",
"for",
"details"
] |
def alias_setup(probs):
"""
Compute utility lists for non-uniform sampling from discrete distributions.
Refer to https://hips.seas.harvard.edu/blog/2013/03/03/the-alias-method-efficient-sampling-with-many-discrete-outcomes/
for details
"""
K = len(probs)
q = np.zeros(K)
J = np.zeros(K, dtype=np.int)
smaller = []
larger = []
for kk, prob in enumerate(probs):
q[kk] = K*prob
if q[kk] < 1.0:
smaller.append(kk)
else:
larger.append(kk)
while len(smaller) > 0 and len(larger) > 0:
small = smaller.pop()
large = larger.pop()
J[small] = large
q[large] = q[large] + q[small] - 1.0
if q[large] < 1.0:
smaller.append(large)
else:
larger.append(large)
return J, q
|
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",",
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] |
https://github.com/benedekrozemberczki/role2vec/blob/d43fc337d00f8fe50475165c0e3695ba795df89a/src/walkers.py#L118-L148
|
|
GalSim-developers/GalSim
|
a05d4ec3b8d8574f99d3b0606ad882cbba53f345
|
galsim/nfw_halo.py
|
python
|
NFWHalo.getMagnification
|
(self, pos, z_s, units=arcsec)
|
return self._getMagnification(pos_x, pos_y, z_s)
|
Calculate magnification of halo at specified positions.
Parameters:
pos: Position(s) of the source(s), assumed to be post-lensing!
Valid ways to input this:
- single `Position` instance
- tuple of floats: (x,y)
- list/array of `Position` instances
- tuple of lists/arrays: ( xlist, ylist )
z_s: Source redshift(s).
units: Angular units of coordinates. [default: galsim.arcsec]
Returns:
the magnification mu
If the input ``pos`` is given a single position, mu is the magnification value.
If the input ``pos`` is given a list/array of positions, mu is a NumPy array.
|
Calculate magnification of halo at specified positions.
|
[
"Calculate",
"magnification",
"of",
"halo",
"at",
"specified",
"positions",
"."
] |
def getMagnification(self, pos, z_s, units=arcsec):
"""Calculate magnification of halo at specified positions.
Parameters:
pos: Position(s) of the source(s), assumed to be post-lensing!
Valid ways to input this:
- single `Position` instance
- tuple of floats: (x,y)
- list/array of `Position` instances
- tuple of lists/arrays: ( xlist, ylist )
z_s: Source redshift(s).
units: Angular units of coordinates. [default: galsim.arcsec]
Returns:
the magnification mu
If the input ``pos`` is given a single position, mu is the magnification value.
If the input ``pos`` is given a list/array of positions, mu is a NumPy array.
"""
# Convert to numpy arrays for internal usage:
pos_x, pos_y = utilities._convertPositions(pos, units, 'getMagnification')
return self._getMagnification(pos_x, pos_y, z_s)
|
[
"def",
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",",
"pos",
",",
"z_s",
",",
"units",
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"_getMagnification",
"(",
"pos_x",
",",
"pos_y",
",",
"z_s",
")"
] |
https://github.com/GalSim-developers/GalSim/blob/a05d4ec3b8d8574f99d3b0606ad882cbba53f345/galsim/nfw_halo.py#L391-L414
|
|
cunjian/pytorch_face_landmark
|
f575be168a24af6f4807c852173fdfedf6d2c67d
|
FaceBoxes/utils/box_utils.py
|
python
|
intersect
|
(box_a, box_b)
|
return inter[:, :, 0] * inter[:, :, 1]
|
We resize both tensors to [A,B,2] without new malloc:
[A,2] -> [A,1,2] -> [A,B,2]
[B,2] -> [1,B,2] -> [A,B,2]
Then we compute the area of intersect between box_a and box_b.
Args:
box_a: (tensor) bounding boxes, Shape: [A,4].
box_b: (tensor) bounding boxes, Shape: [B,4].
Return:
(tensor) intersection area, Shape: [A,B].
|
We resize both tensors to [A,B,2] without new malloc:
[A,2] -> [A,1,2] -> [A,B,2]
[B,2] -> [1,B,2] -> [A,B,2]
Then we compute the area of intersect between box_a and box_b.
Args:
box_a: (tensor) bounding boxes, Shape: [A,4].
box_b: (tensor) bounding boxes, Shape: [B,4].
Return:
(tensor) intersection area, Shape: [A,B].
|
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"B",
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"area",
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":",
"[",
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"B",
"]",
"."
] |
def intersect(box_a, box_b):
""" We resize both tensors to [A,B,2] without new malloc:
[A,2] -> [A,1,2] -> [A,B,2]
[B,2] -> [1,B,2] -> [A,B,2]
Then we compute the area of intersect between box_a and box_b.
Args:
box_a: (tensor) bounding boxes, Shape: [A,4].
box_b: (tensor) bounding boxes, Shape: [B,4].
Return:
(tensor) intersection area, Shape: [A,B].
"""
A = box_a.size(0)
B = box_b.size(0)
max_xy = torch.min(box_a[:, 2:].unsqueeze(1).expand(A, B, 2),
box_b[:, 2:].unsqueeze(0).expand(A, B, 2))
min_xy = torch.max(box_a[:, :2].unsqueeze(1).expand(A, B, 2),
box_b[:, :2].unsqueeze(0).expand(A, B, 2))
inter = torch.clamp((max_xy - min_xy), min=0)
return inter[:, :, 0] * inter[:, :, 1]
|
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https://github.com/cunjian/pytorch_face_landmark/blob/f575be168a24af6f4807c852173fdfedf6d2c67d/FaceBoxes/utils/box_utils.py#L31-L49
|
|
TobyPDE/FRRN
|
20041107a4625106d6acef1dcc903d4352220d3e
|
check_dependencies.py
|
python
|
check_python
|
()
|
Issues a warning if you're not running P2.7 or P3.4.
|
Issues a warning if you're not running P2.7 or P3.4.
|
[
"Issues",
"a",
"warning",
"if",
"you",
"re",
"not",
"running",
"P2",
".",
"7",
"or",
"P3",
".",
"4",
"."
] |
def check_python():
"""Issues a warning if you're not running P2.7 or P3.4."""
version = sys.version[:3]
if version != "2.7" and version != "3.4":
logging.warning("You are running Python {}. We only officially support "
"Python 2.7 and 3.4. This software may "
"or may not run.".format(version))
else:
logging.info("Found supported Python version {}.".format(version))
|
[
"def",
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"(",
")",
":",
"version",
"=",
"sys",
".",
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"[",
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"3",
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"\"You are running Python {}. We only officially support \"",
"\"Python 2.7 and 3.4. This software may \"",
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"\"Found supported Python version {}.\"",
".",
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"version",
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")"
] |
https://github.com/TobyPDE/FRRN/blob/20041107a4625106d6acef1dcc903d4352220d3e/check_dependencies.py#L99-L107
|
||
pyparsing/pyparsing
|
1ccf846394a055924b810faaf9628dac53633848
|
examples/booleansearchparser.py
|
python
|
BooleanSearchParser.evaluateQuotes
|
(self, argument)
|
return self.GetQuotes(" ".join(search_terms), r)
|
Evaluate quoted strings
First is does an 'and' on the individual search terms, then it asks the
function GetQuoted to only return the subset of ID's that contain the
literal string.
|
Evaluate quoted strings
|
[
"Evaluate",
"quoted",
"strings"
] |
def evaluateQuotes(self, argument):
"""Evaluate quoted strings
First is does an 'and' on the individual search terms, then it asks the
function GetQuoted to only return the subset of ID's that contain the
literal string.
"""
# r = set()
r = False
search_terms = []
for item in argument:
search_terms.append(item[0])
r = r and self.evaluate(item)
return self.GetQuotes(" ".join(search_terms), r)
|
[
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"# r = set()",
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"search_terms",
".",
"append",
"(",
"item",
"[",
"0",
"]",
")",
"r",
"=",
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"evaluate",
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"item",
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"return",
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".",
"GetQuotes",
"(",
"\" \"",
".",
"join",
"(",
"search_terms",
")",
",",
"r",
")"
] |
https://github.com/pyparsing/pyparsing/blob/1ccf846394a055924b810faaf9628dac53633848/examples/booleansearchparser.py#L220-L233
|
|
chainer/chainercv
|
7159616642e0be7c5b3ef380b848e16b7e99355b
|
chainercv/links/model/faster_rcnn/faster_rcnn_train_chain.py
|
python
|
FasterRCNNTrainChain.__init__
|
(self, faster_rcnn, rpn_sigma=3., roi_sigma=1.,
anchor_target_creator=AnchorTargetCreator(),
proposal_target_creator=ProposalTargetCreator())
|
[] |
def __init__(self, faster_rcnn, rpn_sigma=3., roi_sigma=1.,
anchor_target_creator=AnchorTargetCreator(),
proposal_target_creator=ProposalTargetCreator()):
super(FasterRCNNTrainChain, self).__init__()
with self.init_scope():
self.faster_rcnn = faster_rcnn
self.rpn_sigma = rpn_sigma
self.roi_sigma = roi_sigma
self.anchor_target_creator = anchor_target_creator
self.proposal_target_creator = proposal_target_creator
self.loc_normalize_mean = faster_rcnn.loc_normalize_mean
self.loc_normalize_std = faster_rcnn.loc_normalize_std
|
[
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",",
"faster_rcnn",
",",
"rpn_sigma",
"=",
"3.",
",",
"roi_sigma",
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"loc_normalize_mean",
"self",
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"loc_normalize_std",
"=",
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".",
"loc_normalize_std"
] |
https://github.com/chainer/chainercv/blob/7159616642e0be7c5b3ef380b848e16b7e99355b/chainercv/links/model/faster_rcnn/faster_rcnn_train_chain.py#L48-L61
|
||||
mongodb/mongo-python-driver
|
c760f900f2e4109a247c2ffc8ad3549362007772
|
pymongo/client_session.py
|
python
|
_reraise_with_unknown_commit
|
(exc)
|
Re-raise an exception with the UnknownTransactionCommitResult label.
|
Re-raise an exception with the UnknownTransactionCommitResult label.
|
[
"Re",
"-",
"raise",
"an",
"exception",
"with",
"the",
"UnknownTransactionCommitResult",
"label",
"."
] |
def _reraise_with_unknown_commit(exc):
"""Re-raise an exception with the UnknownTransactionCommitResult label."""
exc._add_error_label("UnknownTransactionCommitResult")
raise
|
[
"def",
"_reraise_with_unknown_commit",
"(",
"exc",
")",
":",
"exc",
".",
"_add_error_label",
"(",
"\"UnknownTransactionCommitResult\"",
")",
"raise"
] |
https://github.com/mongodb/mongo-python-driver/blob/c760f900f2e4109a247c2ffc8ad3549362007772/pymongo/client_session.py#L400-L403
|
||
NeuromorphicProcessorProject/snn_toolbox
|
a85ada7b5d060500703285ef8a68f06ea1ffda65
|
snntoolbox/simulation/backends/inisim/temporal_pattern.py
|
python
|
SpikeDense.build
|
(self, input_shape)
|
Creates the layer neurons and connections.
Parameters
----------
input_shape: Union[list, tuple, Any]
Keras tensor (future input to layer) or list/tuple of Keras tensors
to reference for weight shape computations.
|
Creates the layer neurons and connections.
|
[
"Creates",
"the",
"layer",
"neurons",
"and",
"connections",
"."
] |
def build(self, input_shape):
"""Creates the layer neurons and connections.
Parameters
----------
input_shape: Union[list, tuple, Any]
Keras tensor (future input to layer) or list/tuple of Keras tensors
to reference for weight shape computations.
"""
Dense.build(self, input_shape)
self.init_neurons(input_shape)
|
[
"def",
"build",
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"self",
",",
"input_shape",
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":",
"Dense",
".",
"build",
"(",
"self",
",",
"input_shape",
")",
"self",
".",
"init_neurons",
"(",
"input_shape",
")"
] |
https://github.com/NeuromorphicProcessorProject/snn_toolbox/blob/a85ada7b5d060500703285ef8a68f06ea1ffda65/snntoolbox/simulation/backends/inisim/temporal_pattern.py#L243-L255
|
||
lesscpy/lesscpy
|
1172a1693df2f4bc929a88b1bebb920e666c0c9f
|
lesscpy/lessc/color.py
|
python
|
Color.darken
|
(self, color, diff, *args)
|
Darken a color
args:
color (str): color
diff (str): percentage
returns:
str
|
Darken a color
args:
color (str): color
diff (str): percentage
returns:
str
|
[
"Darken",
"a",
"color",
"args",
":",
"color",
"(",
"str",
")",
":",
"color",
"diff",
"(",
"str",
")",
":",
"percentage",
"returns",
":",
"str"
] |
def darken(self, color, diff, *args):
""" Darken a color
args:
color (str): color
diff (str): percentage
returns:
str
"""
if color and diff:
return self._ophsl(color, diff, 1, operator.sub)
raise ValueError('Illegal color values')
|
[
"def",
"darken",
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",",
"color",
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"diff",
",",
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",",
"operator",
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"sub",
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"raise",
"ValueError",
"(",
"'Illegal color values'",
")"
] |
https://github.com/lesscpy/lesscpy/blob/1172a1693df2f4bc929a88b1bebb920e666c0c9f/lesscpy/lessc/color.py#L240-L250
|
||
DataDog/integrations-core
|
934674b29d94b70ccc008f76ea172d0cdae05e1e
|
hyperv/datadog_checks/hyperv/config_models/defaults.py
|
python
|
instance_min_collection_interval
|
(field, value)
|
return 15
|
[] |
def instance_min_collection_interval(field, value):
return 15
|
[
"def",
"instance_min_collection_interval",
"(",
"field",
",",
"value",
")",
":",
"return",
"15"
] |
https://github.com/DataDog/integrations-core/blob/934674b29d94b70ccc008f76ea172d0cdae05e1e/hyperv/datadog_checks/hyperv/config_models/defaults.py#L53-L54
|
|||
ajinabraham/OWASP-Xenotix-XSS-Exploit-Framework
|
cb692f527e4e819b6c228187c5702d990a180043
|
bin/x86/Debug/scripting_engine/Lib/site-packages/lxml/html/html5parser.py
|
python
|
fragment_fromstring
|
(html, create_parent=False,
guess_charset=False, parser=None)
|
return result
|
Parses a single HTML element; it is an error if there is more than
one element, or if anything but whitespace precedes or follows the
element.
If create_parent is true (or is a tag name) then a parent node
will be created to encapsulate the HTML in a single element. In
this case, leading or trailing text is allowed.
|
Parses a single HTML element; it is an error if there is more than
one element, or if anything but whitespace precedes or follows the
element.
|
[
"Parses",
"a",
"single",
"HTML",
"element",
";",
"it",
"is",
"an",
"error",
"if",
"there",
"is",
"more",
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"one",
"element",
"or",
"if",
"anything",
"but",
"whitespace",
"precedes",
"or",
"follows",
"the",
"element",
"."
] |
def fragment_fromstring(html, create_parent=False,
guess_charset=False, parser=None):
"""Parses a single HTML element; it is an error if there is more than
one element, or if anything but whitespace precedes or follows the
element.
If create_parent is true (or is a tag name) then a parent node
will be created to encapsulate the HTML in a single element. In
this case, leading or trailing text is allowed.
"""
if not isinstance(html, _strings):
raise TypeError('string required')
accept_leading_text = bool(create_parent)
elements = fragments_fromstring(
html, guess_charset=guess_charset, parser=parser,
no_leading_text=not accept_leading_text)
if create_parent:
if not isinstance(create_parent, _strings):
create_parent = 'div'
new_root = Element(create_parent)
if elements:
if isinstance(elements[0], _strings):
new_root.text = elements[0]
del elements[0]
new_root.extend(elements)
return new_root
if not elements:
raise etree.ParserError('No elements found')
if len(elements) > 1:
raise etree.ParserError('Multiple elements found')
result = elements[0]
if result.tail and result.tail.strip():
raise etree.ParserError('Element followed by text: %r' % result.tail)
result.tail = None
return result
|
[
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")",
"result",
".",
"tail",
"=",
"None",
"return",
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] |
https://github.com/ajinabraham/OWASP-Xenotix-XSS-Exploit-Framework/blob/cb692f527e4e819b6c228187c5702d990a180043/bin/x86/Debug/scripting_engine/Lib/site-packages/lxml/html/html5parser.py#L92-L130
|
|
Fizzadar/pyinfra
|
ff0913d6a172966760b63fe59e55dff9ea852e0d
|
pyinfra/api/connectors/ssh.py
|
python
|
rsync
|
(
state, host, src, dest, flags,
print_output=False, print_input=False,
sudo=False,
sudo_user=None,
**ignored_kwargs
)
|
return True
|
[] |
def rsync(
state, host, src, dest, flags,
print_output=False, print_input=False,
sudo=False,
sudo_user=None,
**ignored_kwargs
):
hostname = host.data.ssh_hostname or host.name
user = ''
if host.data.ssh_user:
user = '{0}@'.format(host.data.ssh_user)
ssh_flags = []
port = host.data.ssh_port
if port:
ssh_flags.append('-p {0}'.format(port))
ssh_key = host.data.ssh_key
if ssh_key:
ssh_flags.append('-i {0}'.format(ssh_key))
remote_rsync_command = 'rsync'
if sudo:
remote_rsync_command = 'sudo rsync'
if sudo_user:
remote_rsync_command = 'sudo -u {0} rsync'.format(sudo_user)
rsync_command = (
'rsync {rsync_flags} '
"--rsh 'ssh -o BatchMode=yes -o StrictHostKeyChecking=no {ssh_flags}' "
"--rsync-path '{remote_rsync_command}' "
'{src} {user}{hostname}:{dest}'
).format(
rsync_flags=' '.join(flags),
ssh_flags=' '.join(ssh_flags),
remote_rsync_command=remote_rsync_command,
user=user, hostname=hostname,
src=src, dest=dest,
)
if print_input:
click.echo('{0}>>> {1}'.format(host.print_prefix, rsync_command), err=True)
return_code, combined_output = run_local_process(
rsync_command,
print_output=print_output,
print_prefix=host.print_prefix,
)
status = return_code == 0
if not status:
_, stderr = split_combined_output(combined_output)
raise IOError('\n'.join(stderr))
return True
|
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")",
")",
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] |
https://github.com/Fizzadar/pyinfra/blob/ff0913d6a172966760b63fe59e55dff9ea852e0d/pyinfra/api/connectors/ssh.py#L523-L579
|
|||
facebookresearch/detectron2
|
cb92ae1763cd7d3777c243f07749574cdaec6cb8
|
projects/DensePose/densepose/data/build.py
|
python
|
has_inference_based_loaders
|
(cfg: CfgNode)
|
return len(cfg.BOOTSTRAP_DATASETS) > 0
|
Returns True, if at least one inferense-based loader must
be instantiated for training
|
Returns True, if at least one inferense-based loader must
be instantiated for training
|
[
"Returns",
"True",
"if",
"at",
"least",
"one",
"inferense",
"-",
"based",
"loader",
"must",
"be",
"instantiated",
"for",
"training"
] |
def has_inference_based_loaders(cfg: CfgNode) -> bool:
"""
Returns True, if at least one inferense-based loader must
be instantiated for training
"""
return len(cfg.BOOTSTRAP_DATASETS) > 0
|
[
"def",
"has_inference_based_loaders",
"(",
"cfg",
":",
"CfgNode",
")",
"->",
"bool",
":",
"return",
"len",
"(",
"cfg",
".",
"BOOTSTRAP_DATASETS",
")",
">",
"0"
] |
https://github.com/facebookresearch/detectron2/blob/cb92ae1763cd7d3777c243f07749574cdaec6cb8/projects/DensePose/densepose/data/build.py#L679-L684
|
|
francisck/DanderSpritz_docs
|
86bb7caca5a957147f120b18bb5c31f299914904
|
Python/Core/Lib/rfc822.py
|
python
|
Message.__getitem__
|
(self, name)
|
return self.dict[name.lower()]
|
Get a specific header, as from a dictionary.
|
Get a specific header, as from a dictionary.
|
[
"Get",
"a",
"specific",
"header",
"as",
"from",
"a",
"dictionary",
"."
] |
def __getitem__(self, name):
"""Get a specific header, as from a dictionary."""
return self.dict[name.lower()]
|
[
"def",
"__getitem__",
"(",
"self",
",",
"name",
")",
":",
"return",
"self",
".",
"dict",
"[",
"name",
".",
"lower",
"(",
")",
"]"
] |
https://github.com/francisck/DanderSpritz_docs/blob/86bb7caca5a957147f120b18bb5c31f299914904/Python/Core/Lib/rfc822.py#L387-L389
|
|
pypa/setuptools
|
9f37366aab9cd8f6baa23e6a77cfdb8daf97757e
|
pkg_resources/__init__.py
|
python
|
WorkingSet._build_master
|
(cls)
|
return ws
|
Prepare the master working set.
|
Prepare the master working set.
|
[
"Prepare",
"the",
"master",
"working",
"set",
"."
] |
def _build_master(cls):
"""
Prepare the master working set.
"""
ws = cls()
try:
from __main__ import __requires__
except ImportError:
# The main program does not list any requirements
return ws
# ensure the requirements are met
try:
ws.require(__requires__)
except VersionConflict:
return cls._build_from_requirements(__requires__)
return ws
|
[
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".",
"_build_from_requirements",
"(",
"__requires__",
")",
"return",
"ws"
] |
https://github.com/pypa/setuptools/blob/9f37366aab9cd8f6baa23e6a77cfdb8daf97757e/pkg_resources/__init__.py#L560-L577
|
|
awslabs/aws-data-wrangler
|
548f5197bacd91bd50ebc66a0173eff9c56f69b1
|
awswrangler/redshift.py
|
python
|
copy_from_files
|
( # pylint: disable=too-many-locals,too-many-arguments
path: str,
con: redshift_connector.Connection,
table: str,
schema: str,
iam_role: Optional[str] = None,
aws_access_key_id: Optional[str] = None,
aws_secret_access_key: Optional[str] = None,
aws_session_token: Optional[str] = None,
parquet_infer_sampling: float = 1.0,
mode: str = "append",
overwrite_method: str = "drop",
diststyle: str = "AUTO",
distkey: Optional[str] = None,
sortstyle: str = "COMPOUND",
sortkey: Optional[List[str]] = None,
primary_keys: Optional[List[str]] = None,
varchar_lengths_default: int = 256,
varchar_lengths: Optional[Dict[str, int]] = None,
serialize_to_json: bool = False,
path_suffix: Optional[str] = None,
path_ignore_suffix: Optional[str] = None,
use_threads: Union[bool, int] = True,
lock: bool = False,
commit_transaction: bool = True,
boto3_session: Optional[boto3.Session] = None,
s3_additional_kwargs: Optional[Dict[str, str]] = None,
)
|
Load Parquet files from S3 to a Table on Amazon Redshift (Through COPY command).
https://docs.aws.amazon.com/redshift/latest/dg/r_COPY.html
Note
----
If the table does not exist yet,
it will be automatically created for you
using the Parquet metadata to
infer the columns data types.
Note
----
In case of `use_threads=True` the number of threads
that will be spawned will be gotten from os.cpu_count().
Parameters
----------
path : str
S3 prefix (e.g. s3://bucket/prefix/)
con : redshift_connector.Connection
Use redshift_connector.connect() to use "
"credentials directly or wr.redshift.connect() to fetch it from the Glue Catalog.
table : str
Table name
schema : str
Schema name
iam_role : str, optional
AWS IAM role with the related permissions.
aws_access_key_id : str, optional
The access key for your AWS account.
aws_secret_access_key : str, optional
The secret key for your AWS account.
aws_session_token : str, optional
The session key for your AWS account. This is only needed when you are using temporary credentials.
parquet_infer_sampling : float
Random sample ratio of files that will have the metadata inspected.
Must be `0.0 < sampling <= 1.0`.
The higher, the more accurate.
The lower, the faster.
mode : str
Append, overwrite or upsert.
overwrite_method : str
Drop, cascade, truncate, or delete. Only applicable in overwrite mode.
"drop" - ``DROP ... RESTRICT`` - drops the table. Fails if there are any views that depend on it.
"cascade" - ``DROP ... CASCADE`` - drops the table, and all views that depend on it.
"truncate" - ``TRUNCATE ...`` - truncates the table, but immediatly commits current
transaction & starts a new one, hence the overwrite happens in two transactions and is not atomic.
"delete" - ``DELETE FROM ...`` - deletes all rows from the table. Slow relative to the other methods.
diststyle : str
Redshift distribution styles. Must be in ["AUTO", "EVEN", "ALL", "KEY"].
https://docs.aws.amazon.com/redshift/latest/dg/t_Distributing_data.html
distkey : str, optional
Specifies a column name or positional number for the distribution key.
sortstyle : str
Sorting can be "COMPOUND" or "INTERLEAVED".
https://docs.aws.amazon.com/redshift/latest/dg/t_Sorting_data.html
sortkey : List[str], optional
List of columns to be sorted.
primary_keys : List[str], optional
Primary keys.
varchar_lengths_default : int
The size that will be set for all VARCHAR columns not specified with varchar_lengths.
varchar_lengths : Dict[str, int], optional
Dict of VARCHAR length by columns. (e.g. {"col1": 10, "col5": 200}).
serialize_to_json : bool
Should Wrangler add SERIALIZETOJSON parameter into the COPY command?
SERIALIZETOJSON is necessary to load nested data
https://docs.aws.amazon.com/redshift/latest/dg/ingest-super.html#copy_json
path_suffix: Union[str, List[str], None]
Suffix or List of suffixes to be scanned on s3 for the schema extraction
(e.g. [".gz.parquet", ".snappy.parquet"]).
Only has effect during the table creation.
If None, will try to read all files. (default)
path_ignore_suffix: Union[str, List[str], None]
Suffix or List of suffixes for S3 keys to be ignored during the schema extraction.
(e.g. [".csv", "_SUCCESS"]).
Only has effect during the table creation.
If None, will try to read all files. (default)
use_threads : bool, int
True to enable concurrent requests, False to disable multiple threads.
If enabled os.cpu_count() will be used as the max number of threads.
If integer is provided, specified number is used.
lock : bool
True to execute LOCK command inside the transaction to force serializable isolation.
commit_transaction: bool
Whether to commit the transaction. True by default.
boto3_session : boto3.Session(), optional
Boto3 Session. The default boto3 session will be used if boto3_session receive None.
s3_additional_kwargs:
Forwarded to botocore requests.
e.g. s3_additional_kwargs={'ServerSideEncryption': 'aws:kms', 'SSEKMSKeyId': 'YOUR_KMS_KEY_ARN'}
Returns
-------
None
None.
Examples
--------
>>> import awswrangler as wr
>>> con = wr.redshift.connect("MY_GLUE_CONNECTION")
>>> wr.redshift.copy_from_files(
... path="s3://bucket/my_parquet_files/",
... con=con,
... table="my_table",
... schema="public",
... iam_role="arn:aws:iam::XXX:role/XXX"
... )
>>> con.close()
|
Load Parquet files from S3 to a Table on Amazon Redshift (Through COPY command).
|
[
"Load",
"Parquet",
"files",
"from",
"S3",
"to",
"a",
"Table",
"on",
"Amazon",
"Redshift",
"(",
"Through",
"COPY",
"command",
")",
"."
] |
def copy_from_files( # pylint: disable=too-many-locals,too-many-arguments
path: str,
con: redshift_connector.Connection,
table: str,
schema: str,
iam_role: Optional[str] = None,
aws_access_key_id: Optional[str] = None,
aws_secret_access_key: Optional[str] = None,
aws_session_token: Optional[str] = None,
parquet_infer_sampling: float = 1.0,
mode: str = "append",
overwrite_method: str = "drop",
diststyle: str = "AUTO",
distkey: Optional[str] = None,
sortstyle: str = "COMPOUND",
sortkey: Optional[List[str]] = None,
primary_keys: Optional[List[str]] = None,
varchar_lengths_default: int = 256,
varchar_lengths: Optional[Dict[str, int]] = None,
serialize_to_json: bool = False,
path_suffix: Optional[str] = None,
path_ignore_suffix: Optional[str] = None,
use_threads: Union[bool, int] = True,
lock: bool = False,
commit_transaction: bool = True,
boto3_session: Optional[boto3.Session] = None,
s3_additional_kwargs: Optional[Dict[str, str]] = None,
) -> None:
"""Load Parquet files from S3 to a Table on Amazon Redshift (Through COPY command).
https://docs.aws.amazon.com/redshift/latest/dg/r_COPY.html
Note
----
If the table does not exist yet,
it will be automatically created for you
using the Parquet metadata to
infer the columns data types.
Note
----
In case of `use_threads=True` the number of threads
that will be spawned will be gotten from os.cpu_count().
Parameters
----------
path : str
S3 prefix (e.g. s3://bucket/prefix/)
con : redshift_connector.Connection
Use redshift_connector.connect() to use "
"credentials directly or wr.redshift.connect() to fetch it from the Glue Catalog.
table : str
Table name
schema : str
Schema name
iam_role : str, optional
AWS IAM role with the related permissions.
aws_access_key_id : str, optional
The access key for your AWS account.
aws_secret_access_key : str, optional
The secret key for your AWS account.
aws_session_token : str, optional
The session key for your AWS account. This is only needed when you are using temporary credentials.
parquet_infer_sampling : float
Random sample ratio of files that will have the metadata inspected.
Must be `0.0 < sampling <= 1.0`.
The higher, the more accurate.
The lower, the faster.
mode : str
Append, overwrite or upsert.
overwrite_method : str
Drop, cascade, truncate, or delete. Only applicable in overwrite mode.
"drop" - ``DROP ... RESTRICT`` - drops the table. Fails if there are any views that depend on it.
"cascade" - ``DROP ... CASCADE`` - drops the table, and all views that depend on it.
"truncate" - ``TRUNCATE ...`` - truncates the table, but immediatly commits current
transaction & starts a new one, hence the overwrite happens in two transactions and is not atomic.
"delete" - ``DELETE FROM ...`` - deletes all rows from the table. Slow relative to the other methods.
diststyle : str
Redshift distribution styles. Must be in ["AUTO", "EVEN", "ALL", "KEY"].
https://docs.aws.amazon.com/redshift/latest/dg/t_Distributing_data.html
distkey : str, optional
Specifies a column name or positional number for the distribution key.
sortstyle : str
Sorting can be "COMPOUND" or "INTERLEAVED".
https://docs.aws.amazon.com/redshift/latest/dg/t_Sorting_data.html
sortkey : List[str], optional
List of columns to be sorted.
primary_keys : List[str], optional
Primary keys.
varchar_lengths_default : int
The size that will be set for all VARCHAR columns not specified with varchar_lengths.
varchar_lengths : Dict[str, int], optional
Dict of VARCHAR length by columns. (e.g. {"col1": 10, "col5": 200}).
serialize_to_json : bool
Should Wrangler add SERIALIZETOJSON parameter into the COPY command?
SERIALIZETOJSON is necessary to load nested data
https://docs.aws.amazon.com/redshift/latest/dg/ingest-super.html#copy_json
path_suffix: Union[str, List[str], None]
Suffix or List of suffixes to be scanned on s3 for the schema extraction
(e.g. [".gz.parquet", ".snappy.parquet"]).
Only has effect during the table creation.
If None, will try to read all files. (default)
path_ignore_suffix: Union[str, List[str], None]
Suffix or List of suffixes for S3 keys to be ignored during the schema extraction.
(e.g. [".csv", "_SUCCESS"]).
Only has effect during the table creation.
If None, will try to read all files. (default)
use_threads : bool, int
True to enable concurrent requests, False to disable multiple threads.
If enabled os.cpu_count() will be used as the max number of threads.
If integer is provided, specified number is used.
lock : bool
True to execute LOCK command inside the transaction to force serializable isolation.
commit_transaction: bool
Whether to commit the transaction. True by default.
boto3_session : boto3.Session(), optional
Boto3 Session. The default boto3 session will be used if boto3_session receive None.
s3_additional_kwargs:
Forwarded to botocore requests.
e.g. s3_additional_kwargs={'ServerSideEncryption': 'aws:kms', 'SSEKMSKeyId': 'YOUR_KMS_KEY_ARN'}
Returns
-------
None
None.
Examples
--------
>>> import awswrangler as wr
>>> con = wr.redshift.connect("MY_GLUE_CONNECTION")
>>> wr.redshift.copy_from_files(
... path="s3://bucket/my_parquet_files/",
... con=con,
... table="my_table",
... schema="public",
... iam_role="arn:aws:iam::XXX:role/XXX"
... )
>>> con.close()
"""
autocommit_temp: bool = con.autocommit
con.autocommit = False
try:
with con.cursor() as cursor:
created_table, created_schema = _create_table(
df=None,
path=path,
parquet_infer_sampling=parquet_infer_sampling,
path_suffix=path_suffix,
path_ignore_suffix=path_ignore_suffix,
con=con,
cursor=cursor,
table=table,
schema=schema,
mode=mode,
overwrite_method=overwrite_method,
diststyle=diststyle,
sortstyle=sortstyle,
distkey=distkey,
sortkey=sortkey,
primary_keys=primary_keys,
varchar_lengths_default=varchar_lengths_default,
varchar_lengths=varchar_lengths,
index=False,
dtype=None,
use_threads=use_threads,
boto3_session=boto3_session,
s3_additional_kwargs=s3_additional_kwargs,
)
if lock and table == created_table:
# Lock before copy if copying into target (not temp) table
_lock(cursor, [table], schema=schema)
_copy(
cursor=cursor,
path=path,
table=created_table,
schema=created_schema,
iam_role=iam_role,
aws_access_key_id=aws_access_key_id,
aws_secret_access_key=aws_secret_access_key,
aws_session_token=aws_session_token,
boto3_session=boto3_session,
serialize_to_json=serialize_to_json,
)
if table != created_table: # upsert
if lock:
_lock(cursor, [table], schema=schema)
_upsert(cursor=cursor, schema=schema, table=table, temp_table=created_table, primary_keys=primary_keys)
if commit_transaction:
con.commit()
except Exception as ex:
con.rollback()
_logger.error(ex)
raise
finally:
con.autocommit = autocommit_temp
|
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https://github.com/awslabs/aws-data-wrangler/blob/548f5197bacd91bd50ebc66a0173eff9c56f69b1/awswrangler/redshift.py#L1133-L1329
|
||
ctxis/canape
|
5f0e03424577296bcc60c2008a60a98ec5307e4b
|
CANAPE.Scripting/Lib/imputil.py
|
python
|
ImportManager.uninstall
|
(self)
|
Restore the previous import mechanism.
|
Restore the previous import mechanism.
|
[
"Restore",
"the",
"previous",
"import",
"mechanism",
"."
] |
def uninstall(self):
"Restore the previous import mechanism."
self.namespace['__import__'] = self.previous_importer
|
[
"def",
"uninstall",
"(",
"self",
")",
":",
"self",
".",
"namespace",
"[",
"'__import__'",
"]",
"=",
"self",
".",
"previous_importer"
] |
https://github.com/ctxis/canape/blob/5f0e03424577296bcc60c2008a60a98ec5307e4b/CANAPE.Scripting/Lib/imputil.py#L49-L51
|
||
windelbouwman/ppci
|
915c069e0667042c085ec42c78e9e3c9a5295324
|
ppci/lang/c/semantics.py
|
python
|
CSemantics.init_store
|
(self, init_cursor, value)
|
Store an initial value at position pointed by cursor.
|
Store an initial value at position pointed by cursor.
|
[
"Store",
"an",
"initial",
"value",
"at",
"position",
"pointed",
"by",
"cursor",
"."
] |
def init_store(self, init_cursor, value):
""" Store an initial value at position pointed by cursor. """
if init_cursor.at_end():
self.warning("Excess elements!", value.location)
# Determine if we need implicit init levels:
target_typ = init_cursor.at_typ()
while not self.equal_types(value.typ, target_typ):
# If we are at a complex type, implicit descend otherwise cast:
if target_typ.is_compound:
init_cursor.enter_compound(target_typ, value.location, True)
target_typ = init_cursor.at_typ()
else:
value = self.pointer(value)
value = self.coerce(value, target_typ)
break
self.logger.debug("Storing %s at cursor %s", value, init_cursor)
# Retrieve current value to check overwrite:
previous_value = init_cursor.get_value()
if previous_value:
self.warning(
"This overwrites other initial value.", value.location
)
self.warning("previously defined here.", previous_value.location)
init_cursor.set_value(value)
|
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"\"Storing %s at cursor %s\"",
",",
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"# Retrieve current value to check overwrite:",
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https://github.com/windelbouwman/ppci/blob/915c069e0667042c085ec42c78e9e3c9a5295324/ppci/lang/c/semantics.py#L201-L228
|
||
buke/GreenOdoo
|
3d8c55d426fb41fdb3f2f5a1533cfe05983ba1df
|
runtime/python/lib/python2.7/site-packages/docutils/utils/math/math2html.py
|
python
|
TaggedBit.complete
|
(self, contents, tag, breaklines = False)
|
return self
|
Set the constant and the tag
|
Set the constant and the tag
|
[
"Set",
"the",
"constant",
"and",
"the",
"tag"
] |
def complete(self, contents, tag, breaklines = False):
"Set the constant and the tag"
self.contents = contents
self.output = TaggedOutput().settag(tag, breaklines)
return self
|
[
"def",
"complete",
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"self",
",",
"contents",
",",
"tag",
",",
"breaklines",
"=",
"False",
")",
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"output",
"=",
"TaggedOutput",
"(",
")",
".",
"settag",
"(",
"tag",
",",
"breaklines",
")",
"return",
"self"
] |
https://github.com/buke/GreenOdoo/blob/3d8c55d426fb41fdb3f2f5a1533cfe05983ba1df/runtime/python/lib/python2.7/site-packages/docutils/utils/math/math2html.py#L2540-L2544
|
|
adafruit/Adafruit_Python_BluefruitLE
|
a01dec2c88fa38143afb855e1df4f9ac774156b7
|
Adafruit_BluefruitLE/services/colorific.py
|
python
|
Colorific.set_color
|
(self, r, g, b)
|
Set the red, green, blue color of the bulb.
|
Set the red, green, blue color of the bulb.
|
[
"Set",
"the",
"red",
"green",
"blue",
"color",
"of",
"the",
"bulb",
"."
] |
def set_color(self, r, g, b):
"""Set the red, green, blue color of the bulb."""
# See more details on the bulb's protocol from this guide:
# https://learn.adafruit.com/reverse-engineering-a-bluetooth-low-energy-light-bulb/overview
command = '\x58\x01\x03\x01\xFF\x00{0}{1}{2}'.format(chr(r & 0xFF),
chr(g & 0xFF),
chr(b & 0xFF))
self._color.write_value(command)
|
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"r",
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"g",
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"# See more details on the bulb's protocol from this guide:",
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https://github.com/adafruit/Adafruit_Python_BluefruitLE/blob/a01dec2c88fa38143afb855e1df4f9ac774156b7/Adafruit_BluefruitLE/services/colorific.py#L47-L54
|
||
nltk/nltk
|
3f74ac55681667d7ef78b664557487145f51eb02
|
nltk/classify/naivebayes.py
|
python
|
NaiveBayesClassifier.__init__
|
(self, label_probdist, feature_probdist)
|
:param label_probdist: P(label), the probability distribution
over labels. It is expressed as a ``ProbDistI`` whose
samples are labels. I.e., P(label) =
``label_probdist.prob(label)``.
:param feature_probdist: P(fname=fval|label), the probability
distribution for feature values, given labels. It is
expressed as a dictionary whose keys are ``(label, fname)``
pairs and whose values are ``ProbDistI`` objects over feature
values. I.e., P(fname=fval|label) =
``feature_probdist[label,fname].prob(fval)``. If a given
``(label,fname)`` is not a key in ``feature_probdist``, then
it is assumed that the corresponding P(fname=fval|label)
is 0 for all values of ``fval``.
|
:param label_probdist: P(label), the probability distribution
over labels. It is expressed as a ``ProbDistI`` whose
samples are labels. I.e., P(label) =
``label_probdist.prob(label)``.
|
[
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] |
def __init__(self, label_probdist, feature_probdist):
"""
:param label_probdist: P(label), the probability distribution
over labels. It is expressed as a ``ProbDistI`` whose
samples are labels. I.e., P(label) =
``label_probdist.prob(label)``.
:param feature_probdist: P(fname=fval|label), the probability
distribution for feature values, given labels. It is
expressed as a dictionary whose keys are ``(label, fname)``
pairs and whose values are ``ProbDistI`` objects over feature
values. I.e., P(fname=fval|label) =
``feature_probdist[label,fname].prob(fval)``. If a given
``(label,fname)`` is not a key in ``feature_probdist``, then
it is assumed that the corresponding P(fname=fval|label)
is 0 for all values of ``fval``.
"""
self._label_probdist = label_probdist
self._feature_probdist = feature_probdist
self._labels = list(label_probdist.samples())
|
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https://github.com/nltk/nltk/blob/3f74ac55681667d7ef78b664557487145f51eb02/nltk/classify/naivebayes.py#L64-L83
|
||
CGATOxford/cgat
|
326aad4694bdfae8ddc194171bb5d73911243947
|
CGAT/scripts/gtfs2graph.py
|
python
|
CounterGenes.run
|
(self, filename1, filename2)
|
count overlap between two gtf files.
|
count overlap between two gtf files.
|
[
"count",
"overlap",
"between",
"two",
"gtf",
"files",
"."
] |
def run(self, filename1, filename2):
"""count overlap between two gtf files."""
E.info("counting started for %s versus %s" % (filename1, filename2))
idx2 = self.buildIndex(filename2)
self._run(filename1, idx2)
|
[
"def",
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",",
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https://github.com/CGATOxford/cgat/blob/326aad4694bdfae8ddc194171bb5d73911243947/CGAT/scripts/gtfs2graph.py#L204-L210
|
||
sympy/sympy
|
d822fcba181155b85ff2b29fe525adbafb22b448
|
sympy/categories/diagram_drawing.py
|
python
|
DiagramGrid._build_skeleton
|
(morphisms)
|
return edges
|
Creates a dictionary which maps edges to corresponding
morphisms. Thus for a morphism `f:A\rightarrow B`, the edge
`(A, B)` will be associated with `f`. This function also adds
to the list those edges which are formed by juxtaposition of
two edges already in the list. These new edges are not
associated with any morphism and are only added to assure that
the diagram can be decomposed into triangles.
|
Creates a dictionary which maps edges to corresponding
morphisms. Thus for a morphism `f:A\rightarrow B`, the edge
`(A, B)` will be associated with `f`. This function also adds
to the list those edges which are formed by juxtaposition of
two edges already in the list. These new edges are not
associated with any morphism and are only added to assure that
the diagram can be decomposed into triangles.
|
[
"Creates",
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"that",
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"diagram",
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"be",
"decomposed",
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"triangles",
"."
] |
def _build_skeleton(morphisms):
"""
Creates a dictionary which maps edges to corresponding
morphisms. Thus for a morphism `f:A\rightarrow B`, the edge
`(A, B)` will be associated with `f`. This function also adds
to the list those edges which are formed by juxtaposition of
two edges already in the list. These new edges are not
associated with any morphism and are only added to assure that
the diagram can be decomposed into triangles.
"""
edges = {}
# Create edges for morphisms.
for morphism in morphisms:
DiagramGrid._add_edge_append(
edges, frozenset([morphism.domain, morphism.codomain]), morphism)
# Create new edges by juxtaposing existing edges.
edges1 = dict(edges)
for w in edges1:
for v in edges1:
wv = DiagramGrid._juxtapose_edges(w, v)
if wv and wv not in edges:
edges[wv] = []
return edges
|
[
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] |
https://github.com/sympy/sympy/blob/d822fcba181155b85ff2b29fe525adbafb22b448/sympy/categories/diagram_drawing.py#L372-L396
|
|
taylorlu/Speaker-Diarization
|
ed0985950cbac6dc699bf54f58dbbc813110d3f7
|
uisrnn/utils.py
|
python
|
enforce_cluster_id_uniqueness
|
(cluster_ids)
|
return new_cluster_ids
|
Enforce uniqueness of cluster id across sequences.
Args:
cluster_ids: a list of 1-dim list/numpy.ndarray of strings
Returns:
a new list with same length of cluster_ids
Raises:
TypeError: if cluster_ids or its element has wrong type
|
Enforce uniqueness of cluster id across sequences.
|
[
"Enforce",
"uniqueness",
"of",
"cluster",
"id",
"across",
"sequences",
"."
] |
def enforce_cluster_id_uniqueness(cluster_ids):
"""Enforce uniqueness of cluster id across sequences.
Args:
cluster_ids: a list of 1-dim list/numpy.ndarray of strings
Returns:
a new list with same length of cluster_ids
Raises:
TypeError: if cluster_ids or its element has wrong type
"""
if not isinstance(cluster_ids, list):
raise TypeError('cluster_ids must be a list')
new_cluster_ids = []
for cluster_id in cluster_ids:
sequence_id = generate_random_string()
if isinstance(cluster_id, np.ndarray):
cluster_id = cluster_id.tolist()
if not isinstance(cluster_id, list):
raise TypeError('Elements of cluster_ids must be list or numpy.ndarray')
new_cluster_id = ['_'.join([sequence_id, s]) for s in cluster_id]
new_cluster_ids.append(new_cluster_id)
return new_cluster_ids
|
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https://github.com/taylorlu/Speaker-Diarization/blob/ed0985950cbac6dc699bf54f58dbbc813110d3f7/uisrnn/utils.py#L55-L78
|
|
gradientinstitute/aboleth
|
53a3de23dce4d607ffec92be936e83d2dd7ebb3c
|
aboleth/layers.py
|
python
|
MaxPool2D._build
|
(self, X)
|
return Net, KL
|
Build the graph of this layer.
|
Build the graph of this layer.
|
[
"Build",
"the",
"graph",
"of",
"this",
"layer",
"."
] |
def _build(self, X):
"""Build the graph of this layer."""
Net = tf.map_fn(lambda inputs: tf.nn.max_pool(inputs,
ksize=self.ksize,
strides=self.strides,
padding=self.padding), X)
KL = 0.
return Net, KL
|
[
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https://github.com/gradientinstitute/aboleth/blob/53a3de23dce4d607ffec92be936e83d2dd7ebb3c/aboleth/layers.py#L228-L235
|
|
CLUEbenchmark/CLUE
|
5bd39732734afecb490cf18a5212e692dbf2c007
|
baselines/models/roberta_wwm_ext/run_classifier.py
|
python
|
input_fn_builder
|
(features, seq_length, is_training, drop_remainder)
|
return input_fn
|
Creates an `input_fn` closure to be passed to TPUEstimator.
|
Creates an `input_fn` closure to be passed to TPUEstimator.
|
[
"Creates",
"an",
"input_fn",
"closure",
"to",
"be",
"passed",
"to",
"TPUEstimator",
"."
] |
def input_fn_builder(features, seq_length, is_training, drop_remainder):
"""Creates an `input_fn` closure to be passed to TPUEstimator."""
all_input_ids = []
all_input_mask = []
all_segment_ids = []
all_label_ids = []
for feature in features:
all_input_ids.append(feature.input_ids)
all_input_mask.append(feature.input_mask)
all_segment_ids.append(feature.segment_ids)
all_label_ids.append(feature.label_id)
def input_fn(params):
"""The actual input function."""
batch_size = params["batch_size"]
num_examples = len(features)
# This is for demo purposes and does NOT scale to large data sets. We do
# not use Dataset.from_generator() because that uses tf.py_func which is
# not TPU compatible. The right way to load data is with TFRecordReader.
d = tf.data.Dataset.from_tensor_slices({
"input_ids":
tf.constant(
all_input_ids, shape=[num_examples, seq_length],
dtype=tf.int32),
"input_mask":
tf.constant(
all_input_mask,
shape=[num_examples, seq_length],
dtype=tf.int32),
"segment_ids":
tf.constant(
all_segment_ids,
shape=[num_examples, seq_length],
dtype=tf.int32),
"label_ids":
tf.constant(all_label_ids, shape=[num_examples], dtype=tf.int32),
})
if is_training:
d = d.repeat()
d = d.shuffle(buffer_size=100)
d = d.batch(batch_size=batch_size, drop_remainder=drop_remainder)
return d
return input_fn
|
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"drop_remainder",
"=",
"drop_remainder",
")",
"return",
"d",
"return",
"input_fn"
] |
https://github.com/CLUEbenchmark/CLUE/blob/5bd39732734afecb490cf18a5212e692dbf2c007/baselines/models/roberta_wwm_ext/run_classifier.py#L640-L689
|
|
xonsh/xonsh
|
b76d6f994f22a4078f602f8b386f4ec280c8461f
|
xonsh/completers/path.py
|
python
|
_normpath
|
(p)
|
return p
|
Wraps os.normpath() to avoid removing './' at the beginning
and '/' at the end. On windows it does the same with backslashes
|
Wraps os.normpath() to avoid removing './' at the beginning
and '/' at the end. On windows it does the same with backslashes
|
[
"Wraps",
"os",
".",
"normpath",
"()",
"to",
"avoid",
"removing",
".",
"/",
"at",
"the",
"beginning",
"and",
"/",
"at",
"the",
"end",
".",
"On",
"windows",
"it",
"does",
"the",
"same",
"with",
"backslashes"
] |
def _normpath(p):
"""
Wraps os.normpath() to avoid removing './' at the beginning
and '/' at the end. On windows it does the same with backslashes
"""
initial_dotslash = p.startswith(os.curdir + os.sep)
initial_dotslash |= xp.ON_WINDOWS and p.startswith(os.curdir + os.altsep)
p = p.rstrip()
trailing_slash = p.endswith(os.sep)
trailing_slash |= xp.ON_WINDOWS and p.endswith(os.altsep)
p = os.path.normpath(p)
if initial_dotslash and p != ".":
p = os.path.join(os.curdir, p)
if trailing_slash:
p = os.path.join(p, "")
if xp.ON_WINDOWS and XSH.env.get("FORCE_POSIX_PATHS"):
p = p.replace(os.sep, os.altsep)
return p
|
[
"def",
"_normpath",
"(",
"p",
")",
":",
"initial_dotslash",
"=",
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".",
"startswith",
"(",
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"curdir",
"+",
"os",
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"sep",
")",
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"|=",
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")",
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"ON_WINDOWS",
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"get",
"(",
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":",
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"replace",
"(",
"os",
".",
"sep",
",",
"os",
".",
"altsep",
")",
"return",
"p"
] |
https://github.com/xonsh/xonsh/blob/b76d6f994f22a4078f602f8b386f4ec280c8461f/xonsh/completers/path.py#L91-L108
|
|
JBakamovic/cxxd
|
142c19649b036bd6f6bdcd4684de735ea11a6c94
|
services/source_code_model/indexer/symbol_database.py
|
python
|
SymbolDatabase.delete_all_entries
|
(self)
|
[] |
def delete_all_entries(self):
try:
self.db_connection.cursor().execute('DELETE FROM symbol')
self.db_connection.cursor().execute('DELETE FROM diagnostics')
except:
logging.error(sys.exc_info())
|
[
"def",
"delete_all_entries",
"(",
"self",
")",
":",
"try",
":",
"self",
".",
"db_connection",
".",
"cursor",
"(",
")",
".",
"execute",
"(",
"'DELETE FROM symbol'",
")",
"self",
".",
"db_connection",
".",
"cursor",
"(",
")",
".",
"execute",
"(",
"'DELETE FROM diagnostics'",
")",
"except",
":",
"logging",
".",
"error",
"(",
"sys",
".",
"exc_info",
"(",
")",
")"
] |
https://github.com/JBakamovic/cxxd/blob/142c19649b036bd6f6bdcd4684de735ea11a6c94/services/source_code_model/indexer/symbol_database.py#L312-L317
|
||||
UDST/urbansim
|
0db75668ada0005352b7c7e0a405265f78ccadd7
|
urbansim/utils/misc.py
|
python
|
compute_range
|
(travel_data, attr, travel_time_attr, dist, agg=np.sum)
|
return travel_data.groupby(level=0).attr.apply(agg)
|
Compute a zone-based accessibility query using the urbansim format
travel data dataframe.
Parameters
----------
travel_data : dataframe
The dataframe of urbansim format travel data. Has from_zone_id as
first index, to_zone_id as second index, and different impedances
between zones as columns.
attr : series
The attr to aggregate. Should be indexed by zone_id and the values
will be aggregated.
travel_time_attr : string
The column name in travel_data to use as the impedance.
dist : float
The max distance to aggregate up to
agg : function, optional, np.sum by default
The numpy function to use for aggregation
|
Compute a zone-based accessibility query using the urbansim format
travel data dataframe.
|
[
"Compute",
"a",
"zone",
"-",
"based",
"accessibility",
"query",
"using",
"the",
"urbansim",
"format",
"travel",
"data",
"dataframe",
"."
] |
def compute_range(travel_data, attr, travel_time_attr, dist, agg=np.sum):
"""
Compute a zone-based accessibility query using the urbansim format
travel data dataframe.
Parameters
----------
travel_data : dataframe
The dataframe of urbansim format travel data. Has from_zone_id as
first index, to_zone_id as second index, and different impedances
between zones as columns.
attr : series
The attr to aggregate. Should be indexed by zone_id and the values
will be aggregated.
travel_time_attr : string
The column name in travel_data to use as the impedance.
dist : float
The max distance to aggregate up to
agg : function, optional, np.sum by default
The numpy function to use for aggregation
"""
travel_data = travel_data.reset_index(level=1)
travel_data = travel_data[travel_data[travel_time_attr] < dist]
travel_data["attr"] = attr.reindex(travel_data.to_zone_id, fill_value=0).values
return travel_data.groupby(level=0).attr.apply(agg)
|
[
"def",
"compute_range",
"(",
"travel_data",
",",
"attr",
",",
"travel_time_attr",
",",
"dist",
",",
"agg",
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",",
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"groupby",
"(",
"level",
"=",
"0",
")",
".",
"attr",
".",
"apply",
"(",
"agg",
")"
] |
https://github.com/UDST/urbansim/blob/0db75668ada0005352b7c7e0a405265f78ccadd7/urbansim/utils/misc.py#L118-L142
|
|
aws/aws-parallelcluster
|
f1fe5679a01c524e7ea904c329bd6d17318c6cd9
|
awsbatch-cli/src/awsbatch/awsbout.py
|
python
|
main
|
()
|
Command entrypoint.
|
Command entrypoint.
|
[
"Command",
"entrypoint",
"."
] |
def main():
"""Command entrypoint."""
try:
# parse input parameters and config file
args = _get_parser().parse_args()
_validate_parameters(args)
log = config_logger(args.log_level)
log.info("Input parameters: %s", args)
config = AWSBatchCliConfig(log=log, cluster=args.cluster)
boto3_factory = Boto3ClientFactory(region=config.region, proxy=config.proxy)
AWSBoutCommand(log, boto3_factory).run(
job_id=args.job_id, head=args.head, tail=args.tail, stream=args.stream, stream_period=args.stream_period
)
except KeyboardInterrupt:
print("Exiting...")
sys.exit(0)
except Exception as e:
fail("Unexpected error. Command failed with exception: %s" % e)
|
[
"def",
"main",
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")",
":",
"try",
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"# parse input parameters and config file",
"args",
"=",
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"Exception",
"as",
"e",
":",
"fail",
"(",
"\"Unexpected error. Command failed with exception: %s\"",
"%",
"e",
")"
] |
https://github.com/aws/aws-parallelcluster/blob/f1fe5679a01c524e7ea904c329bd6d17318c6cd9/awsbatch-cli/src/awsbatch/awsbout.py#L194-L213
|
||
beeware/ouroboros
|
a29123c6fab6a807caffbb7587cf548e0c370296
|
ouroboros/calendar.py
|
python
|
Calendar.yeardays2calendar
|
(self, year, width=3)
|
return [months[i:i+width] for i in range(0, len(months), width) ]
|
Return the data for the specified year ready for formatting (similar to
yeardatescalendar()). Entries in the week lists are
(day number, weekday number) tuples. Day numbers outside this month are
zero.
|
Return the data for the specified year ready for formatting (similar to
yeardatescalendar()). Entries in the week lists are
(day number, weekday number) tuples. Day numbers outside this month are
zero.
|
[
"Return",
"the",
"data",
"for",
"the",
"specified",
"year",
"ready",
"for",
"formatting",
"(",
"similar",
"to",
"yeardatescalendar",
"()",
")",
".",
"Entries",
"in",
"the",
"week",
"lists",
"are",
"(",
"day",
"number",
"weekday",
"number",
")",
"tuples",
".",
"Day",
"numbers",
"outside",
"this",
"month",
"are",
"zero",
"."
] |
def yeardays2calendar(self, year, width=3):
"""
Return the data for the specified year ready for formatting (similar to
yeardatescalendar()). Entries in the week lists are
(day number, weekday number) tuples. Day numbers outside this month are
zero.
"""
months = [
self.monthdays2calendar(year, i)
for i in range(January, January+12)
]
return [months[i:i+width] for i in range(0, len(months), width) ]
|
[
"def",
"yeardays2calendar",
"(",
"self",
",",
"year",
",",
"width",
"=",
"3",
")",
":",
"months",
"=",
"[",
"self",
".",
"monthdays2calendar",
"(",
"year",
",",
"i",
")",
"for",
"i",
"in",
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"(",
"January",
",",
"January",
"+",
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")",
"]",
"return",
"[",
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"[",
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"in",
"range",
"(",
"0",
",",
"len",
"(",
"months",
")",
",",
"width",
")",
"]"
] |
https://github.com/beeware/ouroboros/blob/a29123c6fab6a807caffbb7587cf548e0c370296/ouroboros/calendar.py#L233-L244
|
|
HymanLiuTS/flaskTs
|
286648286976e85d9b9a5873632331efcafe0b21
|
flasky/lib/python2.7/site-packages/setuptools/msvc.py
|
python
|
SystemInfo._find_dot_net_versions
|
(self, bits=32)
|
return frameworkver
|
Find Microsoft .NET Framework versions.
Parameters
----------
bits: int
Platform number of bits: 32 or 64.
|
Find Microsoft .NET Framework versions.
|
[
"Find",
"Microsoft",
".",
"NET",
"Framework",
"versions",
"."
] |
def _find_dot_net_versions(self, bits=32):
"""
Find Microsoft .NET Framework versions.
Parameters
----------
bits: int
Platform number of bits: 32 or 64.
"""
# Find actual .NET version
ver = self.ri.lookup(self.ri.vc, 'frameworkver%d' % bits) or ''
# Set .NET versions for specified MSVC++ version
if self.vc_ver >= 12.0:
frameworkver = (ver, 'v4.0')
elif self.vc_ver >= 10.0:
frameworkver = ('v4.0.30319' if ver.lower()[:2] != 'v4' else ver,
'v3.5')
elif self.vc_ver == 9.0:
frameworkver = ('v3.5', 'v2.0.50727')
if self.vc_ver == 8.0:
frameworkver = ('v3.0', 'v2.0.50727')
return frameworkver
|
[
"def",
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",",
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"=",
"32",
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":",
"# Find actual .NET version",
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":",
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"=",
"(",
"'v3.0'",
",",
"'v2.0.50727'",
")",
"return",
"frameworkver"
] |
https://github.com/HymanLiuTS/flaskTs/blob/286648286976e85d9b9a5873632331efcafe0b21/flasky/lib/python2.7/site-packages/setuptools/msvc.py#L716-L738
|
|
AppScale/gts
|
46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9
|
AppServer/lib/django-1.2/django/contrib/gis/db/models/query.py
|
python
|
GeoQuerySet._spatial_attribute
|
(self, att, settings, field_name=None, model_att=None)
|
return self.extra(select={model_att : fmt % settings['procedure_args']},
select_params=settings['select_params'])
|
DRY routine for calling a spatial stored procedure on a geometry column
and attaching its output as an attribute of the model.
Arguments:
att:
The name of the spatial attribute that holds the spatial
SQL function to call.
settings:
Dictonary of internal settings to customize for the spatial procedure.
Public Keyword Arguments:
field_name:
The name of the geographic field to call the spatial
function on. May also be a lookup to a geometry field
as part of a foreign key relation.
model_att:
The name of the model attribute to attach the output of
the spatial function to.
|
DRY routine for calling a spatial stored procedure on a geometry column
and attaching its output as an attribute of the model.
|
[
"DRY",
"routine",
"for",
"calling",
"a",
"spatial",
"stored",
"procedure",
"on",
"a",
"geometry",
"column",
"and",
"attaching",
"its",
"output",
"as",
"an",
"attribute",
"of",
"the",
"model",
"."
] |
def _spatial_attribute(self, att, settings, field_name=None, model_att=None):
"""
DRY routine for calling a spatial stored procedure on a geometry column
and attaching its output as an attribute of the model.
Arguments:
att:
The name of the spatial attribute that holds the spatial
SQL function to call.
settings:
Dictonary of internal settings to customize for the spatial procedure.
Public Keyword Arguments:
field_name:
The name of the geographic field to call the spatial
function on. May also be a lookup to a geometry field
as part of a foreign key relation.
model_att:
The name of the model attribute to attach the output of
the spatial function to.
"""
# Default settings.
settings.setdefault('desc', None)
settings.setdefault('geom_args', ())
settings.setdefault('geom_field', None)
settings.setdefault('procedure_args', {})
settings.setdefault('procedure_fmt', '%(geo_col)s')
settings.setdefault('select_params', [])
connection = connections[self.db]
backend = connection.ops
# Performing setup for the spatial column, unless told not to.
if settings.get('setup', True):
default_args, geo_field = self._spatial_setup(att, desc=settings['desc'], field_name=field_name,
geo_field_type=settings.get('geo_field_type', None))
for k, v in default_args.iteritems(): settings['procedure_args'].setdefault(k, v)
else:
geo_field = settings['geo_field']
# The attribute to attach to the model.
if not isinstance(model_att, basestring): model_att = att
# Special handling for any argument that is a geometry.
for name in settings['geom_args']:
# Using the field's get_placeholder() routine to get any needed
# transformation SQL.
geom = geo_field.get_prep_value(settings['procedure_args'][name])
params = geo_field.get_db_prep_lookup('contains', geom, connection=connection)
geom_placeholder = geo_field.get_placeholder(geom, connection)
# Replacing the procedure format with that of any needed
# transformation SQL.
old_fmt = '%%(%s)s' % name
new_fmt = geom_placeholder % '%%s'
settings['procedure_fmt'] = settings['procedure_fmt'].replace(old_fmt, new_fmt)
settings['select_params'].extend(params)
# Getting the format for the stored procedure.
fmt = '%%(function)s(%s)' % settings['procedure_fmt']
# If the result of this function needs to be converted.
if settings.get('select_field', False):
sel_fld = settings['select_field']
if isinstance(sel_fld, GeomField) and backend.select:
self.query.custom_select[model_att] = backend.select
if connection.ops.oracle:
sel_fld.empty_strings_allowed = False
self.query.extra_select_fields[model_att] = sel_fld
# Finally, setting the extra selection attribute with
# the format string expanded with the stored procedure
# arguments.
return self.extra(select={model_att : fmt % settings['procedure_args']},
select_params=settings['select_params'])
|
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"in",
"default_args",
".",
"iteritems",
"(",
")",
":",
"settings",
"[",
"'procedure_args'",
"]",
".",
"setdefault",
"(",
"k",
",",
"v",
")",
"else",
":",
"geo_field",
"=",
"settings",
"[",
"'geo_field'",
"]",
"# The attribute to attach to the model.",
"if",
"not",
"isinstance",
"(",
"model_att",
",",
"basestring",
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":",
"model_att",
"=",
"att",
"# Special handling for any argument that is a geometry.",
"for",
"name",
"in",
"settings",
"[",
"'geom_args'",
"]",
":",
"# Using the field's get_placeholder() routine to get any needed",
"# transformation SQL.",
"geom",
"=",
"geo_field",
".",
"get_prep_value",
"(",
"settings",
"[",
"'procedure_args'",
"]",
"[",
"name",
"]",
")",
"params",
"=",
"geo_field",
".",
"get_db_prep_lookup",
"(",
"'contains'",
",",
"geom",
",",
"connection",
"=",
"connection",
")",
"geom_placeholder",
"=",
"geo_field",
".",
"get_placeholder",
"(",
"geom",
",",
"connection",
")",
"# Replacing the procedure format with that of any needed",
"# transformation SQL.",
"old_fmt",
"=",
"'%%(%s)s'",
"%",
"name",
"new_fmt",
"=",
"geom_placeholder",
"%",
"'%%s'",
"settings",
"[",
"'procedure_fmt'",
"]",
"=",
"settings",
"[",
"'procedure_fmt'",
"]",
".",
"replace",
"(",
"old_fmt",
",",
"new_fmt",
")",
"settings",
"[",
"'select_params'",
"]",
".",
"extend",
"(",
"params",
")",
"# Getting the format for the stored procedure.",
"fmt",
"=",
"'%%(function)s(%s)'",
"%",
"settings",
"[",
"'procedure_fmt'",
"]",
"# If the result of this function needs to be converted.",
"if",
"settings",
".",
"get",
"(",
"'select_field'",
",",
"False",
")",
":",
"sel_fld",
"=",
"settings",
"[",
"'select_field'",
"]",
"if",
"isinstance",
"(",
"sel_fld",
",",
"GeomField",
")",
"and",
"backend",
".",
"select",
":",
"self",
".",
"query",
".",
"custom_select",
"[",
"model_att",
"]",
"=",
"backend",
".",
"select",
"if",
"connection",
".",
"ops",
".",
"oracle",
":",
"sel_fld",
".",
"empty_strings_allowed",
"=",
"False",
"self",
".",
"query",
".",
"extra_select_fields",
"[",
"model_att",
"]",
"=",
"sel_fld",
"# Finally, setting the extra selection attribute with",
"# the format string expanded with the stored procedure",
"# arguments.",
"return",
"self",
".",
"extra",
"(",
"select",
"=",
"{",
"model_att",
":",
"fmt",
"%",
"settings",
"[",
"'procedure_args'",
"]",
"}",
",",
"select_params",
"=",
"settings",
"[",
"'select_params'",
"]",
")"
] |
https://github.com/AppScale/gts/blob/46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9/AppServer/lib/django-1.2/django/contrib/gis/db/models/query.py#L492-L569
|
|
salopensource/sal
|
464414a2666e39bdf5b4b0033a84d5129c93c053
|
sal/plugin.py
|
python
|
BasePlugin.checkin_processor
|
(self, machine, report_data)
|
Process checkin data prior to recording in DB.
The default implementation does nothing.
Plugins can define a checkin processor method by overriding
this. This processor is run at the conclusion of the
client checkin, and includes the report data processed during
that run.
Args:
machine (server.models.Machine): The machine checking in.
report_data (dict): All of the report data.
|
Process checkin data prior to recording in DB.
|
[
"Process",
"checkin",
"data",
"prior",
"to",
"recording",
"in",
"DB",
"."
] |
def checkin_processor(self, machine, report_data):
"""Process checkin data prior to recording in DB.
The default implementation does nothing.
Plugins can define a checkin processor method by overriding
this. This processor is run at the conclusion of the
client checkin, and includes the report data processed during
that run.
Args:
machine (server.models.Machine): The machine checking in.
report_data (dict): All of the report data.
"""
pass
|
[
"def",
"checkin_processor",
"(",
"self",
",",
"machine",
",",
"report_data",
")",
":",
"pass"
] |
https://github.com/salopensource/sal/blob/464414a2666e39bdf5b4b0033a84d5129c93c053/sal/plugin.py#L266-L280
|
||
facebookresearch/mobile-vision
|
f40401a44e86bb3ba9c1b66e7700e15f96b880cb
|
runtime_lut/code/api.py
|
python
|
OpLut.add_op
|
(self, op_record)
|
Add a new record to the OpLut
Args:
op_record: a LUTSchema instance to be added
|
Add a new record to the OpLut
Args:
op_record: a LUTSchema instance to be added
|
[
"Add",
"a",
"new",
"record",
"to",
"the",
"OpLut",
"Args",
":",
"op_record",
":",
"a",
"LUTSchema",
"instance",
"to",
"be",
"added"
] |
def add_op(self, op_record):
"""
Add a new record to the OpLut
Args:
op_record: a LUTSchema instance to be added
"""
assert isinstance(op_record, LUTSchema)
if self.find_op(op_record) != []:
print("Operator already exists.")
return
self.ops.append(op_record)
|
[
"def",
"add_op",
"(",
"self",
",",
"op_record",
")",
":",
"assert",
"isinstance",
"(",
"op_record",
",",
"LUTSchema",
")",
"if",
"self",
".",
"find_op",
"(",
"op_record",
")",
"!=",
"[",
"]",
":",
"print",
"(",
"\"Operator already exists.\"",
")",
"return",
"self",
".",
"ops",
".",
"append",
"(",
"op_record",
")"
] |
https://github.com/facebookresearch/mobile-vision/blob/f40401a44e86bb3ba9c1b66e7700e15f96b880cb/runtime_lut/code/api.py#L97-L108
|
||
tensorflow/lingvo
|
ce10019243d954c3c3ebe739f7589b5eebfdf907
|
lingvo/core/conv_layers_with_time_padding.py
|
python
|
CausalConv2DLayerWithPadding.zero_state
|
(self, batch_size)
|
return py_utils.NestedMap(context=context)
|
Returns the initial state given the batch size.
Args:
batch_size: the batch size.
Returns:
state0: A NestedMap of tensors including:
- context: A Tensor of shape [b, filter_shape[0]-1, 1, c].
|
Returns the initial state given the batch size.
|
[
"Returns",
"the",
"initial",
"state",
"given",
"the",
"batch",
"size",
"."
] |
def zero_state(self, batch_size):
"""Returns the initial state given the batch size.
Args:
batch_size: the batch size.
Returns:
state0: A NestedMap of tensors including:
- context: A Tensor of shape [b, filter_shape[0]-1, 1, c].
"""
p = self.params
assert p.filter_shape[1] == 1, (
'zero_state() only supports 1d causal convolution.')
context = tf.zeros(
shape=[batch_size] +
[p.filter_shape[0] - 1, p.filter_shape[1], p.filter_shape[2]],
dtype=py_utils.FPropDtype(p))
return py_utils.NestedMap(context=context)
|
[
"def",
"zero_state",
"(",
"self",
",",
"batch_size",
")",
":",
"p",
"=",
"self",
".",
"params",
"assert",
"p",
".",
"filter_shape",
"[",
"1",
"]",
"==",
"1",
",",
"(",
"'zero_state() only supports 1d causal convolution.'",
")",
"context",
"=",
"tf",
".",
"zeros",
"(",
"shape",
"=",
"[",
"batch_size",
"]",
"+",
"[",
"p",
".",
"filter_shape",
"[",
"0",
"]",
"-",
"1",
",",
"p",
".",
"filter_shape",
"[",
"1",
"]",
",",
"p",
".",
"filter_shape",
"[",
"2",
"]",
"]",
",",
"dtype",
"=",
"py_utils",
".",
"FPropDtype",
"(",
"p",
")",
")",
"return",
"py_utils",
".",
"NestedMap",
"(",
"context",
"=",
"context",
")"
] |
https://github.com/tensorflow/lingvo/blob/ce10019243d954c3c3ebe739f7589b5eebfdf907/lingvo/core/conv_layers_with_time_padding.py#L503-L521
|
|
napalm-automation/napalm
|
ad1ff72000d0de59f25c8847694f51a4ad5aca86
|
docs/conf.py
|
python
|
build_getters_support_matrix
|
(app)
|
Build the getters support matrix.
|
Build the getters support matrix.
|
[
"Build",
"the",
"getters",
"support",
"matrix",
"."
] |
def build_getters_support_matrix(app):
"""Build the getters support matrix."""
status = subprocess.call("./test.sh", stdout=sys.stdout, stderr=sys.stderr)
if status != 0:
print("Something bad happened when processing the test reports.")
sys.exit(-1)
drivers = set()
matrix = {
m: defaultdict(dict)
for m in dir(NetworkDriver)
if not (m.startswith("_") or m in EXCLUDE_METHODS)
}
regex_name = re.compile(r"(?P<driver>\w+)\/.*::test_(?P<getter>\w+)")
filename = "./support/tests/report.json"
with open(filename, "r") as f:
data = json.loads(f.read())
for test in data["report"]["tests"]:
match = regex_name.search(test["name"])
if match:
driver = match.group("driver")
drivers.add(driver)
method = match.group("getter")
else:
continue
if method in EXCLUDE_IN_REPORT:
continue
result = test["outcome"]
if method in METHOD_ALIASES.keys():
method = METHOD_ALIASES[method]
intermediate_result = matrix[method].get(driver, None)
matrix[method][driver] = _merge_results(result, intermediate_result)
sorted_methods = sorted(matrix.keys())
drivers = sorted(drivers)
env = Environment(loader=FileSystemLoader("."))
template_file = env.get_template("matrix.j2")
rendered_template = template_file.render(
matrix=matrix, drivers=drivers, sorted_methods=sorted_methods
)
with open("support/matrix.rst", "w") as f:
f.write(rendered_template)
|
[
"def",
"build_getters_support_matrix",
"(",
"app",
")",
":",
"status",
"=",
"subprocess",
".",
"call",
"(",
"\"./test.sh\"",
",",
"stdout",
"=",
"sys",
".",
"stdout",
",",
"stderr",
"=",
"sys",
".",
"stderr",
")",
"if",
"status",
"!=",
"0",
":",
"print",
"(",
"\"Something bad happened when processing the test reports.\"",
")",
"sys",
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"exit",
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"-",
"1",
")",
"drivers",
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"set",
"(",
")",
"matrix",
"=",
"{",
"m",
":",
"defaultdict",
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"dict",
")",
"for",
"m",
"in",
"dir",
"(",
"NetworkDriver",
")",
"if",
"not",
"(",
"m",
".",
"startswith",
"(",
"\"_\"",
")",
"or",
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"in",
"EXCLUDE_METHODS",
")",
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"regex_name",
"=",
"re",
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"compile",
"(",
"r\"(?P<driver>\\w+)\\/.*::test_(?P<getter>\\w+)\"",
")",
"filename",
"=",
"\"./support/tests/report.json\"",
"with",
"open",
"(",
"filename",
",",
"\"r\"",
")",
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"json",
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"read",
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"data",
"[",
"\"report\"",
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"[",
"\"tests\"",
"]",
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"match",
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"test",
"[",
"\"name\"",
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"method",
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"[",
"driver",
"]",
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"_merge_results",
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",",
"intermediate_result",
")",
"sorted_methods",
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"sorted",
"(",
"matrix",
".",
"keys",
"(",
")",
")",
"drivers",
"=",
"sorted",
"(",
"drivers",
")",
"env",
"=",
"Environment",
"(",
"loader",
"=",
"FileSystemLoader",
"(",
"\".\"",
")",
")",
"template_file",
"=",
"env",
".",
"get_template",
"(",
"\"matrix.j2\"",
")",
"rendered_template",
"=",
"template_file",
".",
"render",
"(",
"matrix",
"=",
"matrix",
",",
"drivers",
"=",
"drivers",
",",
"sorted_methods",
"=",
"sorted_methods",
")",
"with",
"open",
"(",
"\"support/matrix.rst\"",
",",
"\"w\"",
")",
"as",
"f",
":",
"f",
".",
"write",
"(",
"rendered_template",
")"
] |
https://github.com/napalm-automation/napalm/blob/ad1ff72000d0de59f25c8847694f51a4ad5aca86/docs/conf.py#L359-L406
|
||
bungnoid/glTools
|
8ff0899de43784a18bd4543285655e68e28fb5e5
|
utils/boundingBox.py
|
python
|
getBoundingBox
|
(geometry,worldSpace=True)
|
return glTools.utils.base.getMBoundingBox(geometry,worldSpace=worldSpace)
|
Return bounding box for the specified geometry.
@param geometry: Geometry to return bounding box for
@type geometry: str
@param worldSpace: Calculate bounding box in world or local space
@type worldSpace: bool
|
Return bounding box for the specified geometry.
|
[
"Return",
"bounding",
"box",
"for",
"the",
"specified",
"geometry",
"."
] |
def getBoundingBox(geometry,worldSpace=True):
'''
Return bounding box for the specified geometry.
@param geometry: Geometry to return bounding box for
@type geometry: str
@param worldSpace: Calculate bounding box in world or local space
@type worldSpace: bool
'''
return glTools.utils.base.getMBoundingBox(geometry,worldSpace=worldSpace)
|
[
"def",
"getBoundingBox",
"(",
"geometry",
",",
"worldSpace",
"=",
"True",
")",
":",
"return",
"glTools",
".",
"utils",
".",
"base",
".",
"getMBoundingBox",
"(",
"geometry",
",",
"worldSpace",
"=",
"worldSpace",
")"
] |
https://github.com/bungnoid/glTools/blob/8ff0899de43784a18bd4543285655e68e28fb5e5/utils/boundingBox.py#L59-L67
|
|
lad1337/XDM
|
0c1b7009fe00f06f102a6f67c793478f515e7efe
|
site-packages/jinja2/utils.py
|
python
|
LRUCache.iteritems
|
(self)
|
return iter(self.items())
|
Iterate over all items.
|
Iterate over all items.
|
[
"Iterate",
"over",
"all",
"items",
"."
] |
def iteritems(self):
"""Iterate over all items."""
return iter(self.items())
|
[
"def",
"iteritems",
"(",
"self",
")",
":",
"return",
"iter",
"(",
"self",
".",
"items",
"(",
")",
")"
] |
https://github.com/lad1337/XDM/blob/0c1b7009fe00f06f102a6f67c793478f515e7efe/site-packages/jinja2/utils.py#L500-L502
|
|
openstack/kuryr-kubernetes
|
513ada72685ef02cd9f3aca418ac1b2e0dc1b8ba
|
kuryr_kubernetes/os_vif_util.py
|
python
|
_make_vif_subnets
|
(neutron_port, subnets)
|
return list(vif_subnets.values())
|
Gets a list of os-vif Subnet objects for port.
:param neutron_port: dict containing port information as returned by
neutron client's 'show_port' or
openstack.network.v2.port.Port object
:param subnets: subnet mapping as returned by PodSubnetsDriver.get_subnets
:return: list of os-vif Subnet object
|
Gets a list of os-vif Subnet objects for port.
|
[
"Gets",
"a",
"list",
"of",
"os",
"-",
"vif",
"Subnet",
"objects",
"for",
"port",
"."
] |
def _make_vif_subnets(neutron_port, subnets):
"""Gets a list of os-vif Subnet objects for port.
:param neutron_port: dict containing port information as returned by
neutron client's 'show_port' or
openstack.network.v2.port.Port object
:param subnets: subnet mapping as returned by PodSubnetsDriver.get_subnets
:return: list of os-vif Subnet object
"""
vif_subnets = {}
try:
fixed_ips = neutron_port.get('fixed_ips', [])
port_id = neutron_port.get('id')
except TypeError:
fixed_ips = neutron_port.fixed_ips
port_id = neutron_port.get.id
for neutron_fixed_ip in fixed_ips:
subnet_id = neutron_fixed_ip['subnet_id']
ip_address = neutron_fixed_ip['ip_address']
if subnet_id not in subnets:
continue
try:
subnet = vif_subnets[subnet_id]
except KeyError:
subnet = _make_vif_subnet(subnets, subnet_id)
vif_subnets[subnet_id] = subnet
subnet.ips.objects.append(osv_fixed_ip.FixedIP(address=ip_address))
if not vif_subnets:
raise k_exc.IntegrityError(_(
"No valid subnets found for port %(port_id)s") % {
'port_id': port_id})
return list(vif_subnets.values())
|
[
"def",
"_make_vif_subnets",
"(",
"neutron_port",
",",
"subnets",
")",
":",
"vif_subnets",
"=",
"{",
"}",
"try",
":",
"fixed_ips",
"=",
"neutron_port",
".",
"get",
"(",
"'fixed_ips'",
",",
"[",
"]",
")",
"port_id",
"=",
"neutron_port",
".",
"get",
"(",
"'id'",
")",
"except",
"TypeError",
":",
"fixed_ips",
"=",
"neutron_port",
".",
"fixed_ips",
"port_id",
"=",
"neutron_port",
".",
"get",
".",
"id",
"for",
"neutron_fixed_ip",
"in",
"fixed_ips",
":",
"subnet_id",
"=",
"neutron_fixed_ip",
"[",
"'subnet_id'",
"]",
"ip_address",
"=",
"neutron_fixed_ip",
"[",
"'ip_address'",
"]",
"if",
"subnet_id",
"not",
"in",
"subnets",
":",
"continue",
"try",
":",
"subnet",
"=",
"vif_subnets",
"[",
"subnet_id",
"]",
"except",
"KeyError",
":",
"subnet",
"=",
"_make_vif_subnet",
"(",
"subnets",
",",
"subnet_id",
")",
"vif_subnets",
"[",
"subnet_id",
"]",
"=",
"subnet",
"subnet",
".",
"ips",
".",
"objects",
".",
"append",
"(",
"osv_fixed_ip",
".",
"FixedIP",
"(",
"address",
"=",
"ip_address",
")",
")",
"if",
"not",
"vif_subnets",
":",
"raise",
"k_exc",
".",
"IntegrityError",
"(",
"_",
"(",
"\"No valid subnets found for port %(port_id)s\"",
")",
"%",
"{",
"'port_id'",
":",
"port_id",
"}",
")",
"return",
"list",
"(",
"vif_subnets",
".",
"values",
"(",
")",
")"
] |
https://github.com/openstack/kuryr-kubernetes/blob/513ada72685ef02cd9f3aca418ac1b2e0dc1b8ba/kuryr_kubernetes/os_vif_util.py#L126-L164
|
|
fofix/fofix
|
7730d1503c66562b901f62b33a5bd46c3d5e5c34
|
fofix/core/Font.py
|
python
|
Font.drawSquare
|
(self, w, h, tw, th)
|
New drawing relaying only on pygame.font.render
Use arrays to increase performance
:param w: width
:param h: height
:param tw: texture width
:param th: texture height
|
New drawing relaying only on pygame.font.render
Use arrays to increase performance
|
[
"New",
"drawing",
"relaying",
"only",
"on",
"pygame",
".",
"font",
".",
"render",
"Use",
"arrays",
"to",
"increase",
"performance"
] |
def drawSquare(self, w, h, tw, th):
"""
New drawing relaying only on pygame.font.render
Use arrays to increase performance
:param w: width
:param h: height
:param tw: texture width
:param th: texture height
"""
self.square_prim[1, 0] = self.square_prim[3, 0] = w
self.square_prim[2, 1] = self.square_prim[3, 1] = h
self.square_tex[0, 1] = self.square_tex[1, 1] = th
self.square_tex[1, 0] = self.square_tex[3, 0] = tw
cmgl.draw_arrays(GL_TRIANGLE_STRIP, vertices=self.square_prim, texcoords=self.square_tex)
|
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"square_prim",
",",
"texcoords",
"=",
"self",
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"square_tex",
")"
] |
https://github.com/fofix/fofix/blob/7730d1503c66562b901f62b33a5bd46c3d5e5c34/fofix/core/Font.py#L148-L162
|
||
fabioz/PyDev.Debugger
|
0f8c02a010fe5690405da1dd30ed72326191ce63
|
third_party/pep8/autopep8.py
|
python
|
get_encoding
|
()
|
return locale.getpreferredencoding() or sys.getdefaultencoding()
|
Return preferred encoding.
|
Return preferred encoding.
|
[
"Return",
"preferred",
"encoding",
"."
] |
def get_encoding():
"""Return preferred encoding."""
return locale.getpreferredencoding() or sys.getdefaultencoding()
|
[
"def",
"get_encoding",
"(",
")",
":",
"return",
"locale",
".",
"getpreferredencoding",
"(",
")",
"or",
"sys",
".",
"getdefaultencoding",
"(",
")"
] |
https://github.com/fabioz/PyDev.Debugger/blob/0f8c02a010fe5690405da1dd30ed72326191ce63/third_party/pep8/autopep8.py#L3752-L3754
|
|
microsoft/botbuilder-python
|
3d410365461dc434df59bdfeaa2f16d28d9df868
|
libraries/botbuilder-schema/botbuilder/schema/_models_py3.py
|
python
|
Activity.create_event_activity
|
()
|
return Activity(type=ActivityTypes.event)
|
Creates an instance of the :class:`Activity` class as an EventActivity object.
:returns: The new event activity.
|
Creates an instance of the :class:`Activity` class as an EventActivity object.
|
[
"Creates",
"an",
"instance",
"of",
"the",
":",
"class",
":",
"Activity",
"class",
"as",
"an",
"EventActivity",
"object",
"."
] |
def create_event_activity():
"""
Creates an instance of the :class:`Activity` class as an EventActivity object.
:returns: The new event activity.
"""
return Activity(type=ActivityTypes.event)
|
[
"def",
"create_event_activity",
"(",
")",
":",
"return",
"Activity",
"(",
"type",
"=",
"ActivityTypes",
".",
"event",
")"
] |
https://github.com/microsoft/botbuilder-python/blob/3d410365461dc434df59bdfeaa2f16d28d9df868/libraries/botbuilder-schema/botbuilder/schema/_models_py3.py#L584-L590
|
|
ales-tsurko/cells
|
4cf7e395cd433762bea70cdc863a346f3a6fe1d0
|
packaging/macos/python/lib/python3.7/importlib/abc.py
|
python
|
ResourceReader.open_resource
|
(self, resource)
|
Return an opened, file-like object for binary reading.
The 'resource' argument is expected to represent only a file name
and thus not contain any subdirectory components.
If the resource cannot be found, FileNotFoundError is raised.
|
Return an opened, file-like object for binary reading.
|
[
"Return",
"an",
"opened",
"file",
"-",
"like",
"object",
"for",
"binary",
"reading",
"."
] |
def open_resource(self, resource):
"""Return an opened, file-like object for binary reading.
The 'resource' argument is expected to represent only a file name
and thus not contain any subdirectory components.
If the resource cannot be found, FileNotFoundError is raised.
"""
raise FileNotFoundError
|
[
"def",
"open_resource",
"(",
"self",
",",
"resource",
")",
":",
"raise",
"FileNotFoundError"
] |
https://github.com/ales-tsurko/cells/blob/4cf7e395cd433762bea70cdc863a346f3a6fe1d0/packaging/macos/python/lib/python3.7/importlib/abc.py#L355-L363
|
||
makerdao/pymaker
|
9245b3e22bcb257004d54337df6c2b0c9cbe42c8
|
pymaker/sai.py
|
python
|
Tub.approve
|
(self, approval_function)
|
Approve the `Tub` to access our GEM, SKR, SAI and GOV balances.
For available approval functions (i.e. approval modes) see `directly` and `via_tx_manager`
in `pymaker.approval`.
Args:
approval_function: Approval function (i.e. approval mode).
|
Approve the `Tub` to access our GEM, SKR, SAI and GOV balances.
|
[
"Approve",
"the",
"Tub",
"to",
"access",
"our",
"GEM",
"SKR",
"SAI",
"and",
"GOV",
"balances",
"."
] |
def approve(self, approval_function):
"""Approve the `Tub` to access our GEM, SKR, SAI and GOV balances.
For available approval functions (i.e. approval modes) see `directly` and `via_tx_manager`
in `pymaker.approval`.
Args:
approval_function: Approval function (i.e. approval mode).
"""
assert(callable(approval_function))
approval_function(ERC20Token(web3=self.web3, address=self.gem()), self.address, 'Tub')
approval_function(ERC20Token(web3=self.web3, address=self.skr()), self.address, 'Tub')
approval_function(ERC20Token(web3=self.web3, address=self.sai()), self.address, 'Tub')
approval_function(ERC20Token(web3=self.web3, address=self.gov()), self.address, 'Tub')
|
[
"def",
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"(",
")",
")",
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".",
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",",
"'Tub'",
")"
] |
https://github.com/makerdao/pymaker/blob/9245b3e22bcb257004d54337df6c2b0c9cbe42c8/pymaker/sai.py#L104-L118
|
||
cloudera/hue
|
23f02102d4547c17c32bd5ea0eb24e9eadd657a4
|
desktop/core/ext-py/ply-3.11/example/ansic/cparse.py
|
python
|
p_direct_declarator_5
|
(t)
|
direct_declarator : direct_declarator LPAREN identifier_list RPAREN
|
direct_declarator : direct_declarator LPAREN identifier_list RPAREN
|
[
"direct_declarator",
":",
"direct_declarator",
"LPAREN",
"identifier_list",
"RPAREN"
] |
def p_direct_declarator_5(t):
'direct_declarator : direct_declarator LPAREN identifier_list RPAREN '
pass
|
[
"def",
"p_direct_declarator_5",
"(",
"t",
")",
":",
"pass"
] |
https://github.com/cloudera/hue/blob/23f02102d4547c17c32bd5ea0eb24e9eadd657a4/desktop/core/ext-py/ply-3.11/example/ansic/cparse.py#L351-L353
|
||
rq/rq
|
c5a1ef17345e17269085e7f72858ac9bd6faf1dd
|
rq/local.py
|
python
|
LocalProxy.__getattr__
|
(self, name)
|
return getattr(self._get_current_object(), name)
|
[] |
def __getattr__(self, name):
if name == '__members__':
return dir(self._get_current_object())
return getattr(self._get_current_object(), name)
|
[
"def",
"__getattr__",
"(",
"self",
",",
"name",
")",
":",
"if",
"name",
"==",
"'__members__'",
":",
"return",
"dir",
"(",
"self",
".",
"_get_current_object",
"(",
")",
")",
"return",
"getattr",
"(",
"self",
".",
"_get_current_object",
"(",
")",
",",
"name",
")"
] |
https://github.com/rq/rq/blob/c5a1ef17345e17269085e7f72858ac9bd6faf1dd/rq/local.py#L318-L321
|
|||
facebookresearch/votenet
|
2f6d6d36ff98d96901182e935afe48ccee82d566
|
sunrgbd/sunrgbd_utils.py
|
python
|
SUNRGBD_Calibration.project_upright_camera_to_upright_depth
|
(self, pc)
|
return flip_axis_to_depth(pc)
|
[] |
def project_upright_camera_to_upright_depth(self, pc):
return flip_axis_to_depth(pc)
|
[
"def",
"project_upright_camera_to_upright_depth",
"(",
"self",
",",
"pc",
")",
":",
"return",
"flip_axis_to_depth",
"(",
"pc",
")"
] |
https://github.com/facebookresearch/votenet/blob/2f6d6d36ff98d96901182e935afe48ccee82d566/sunrgbd/sunrgbd_utils.py#L119-L120
|
|||
pabigot/pyxb
|
14737c23a125fd12c954823ad64fc4497816fae3
|
pyxb/xmlschema/structures.py
|
python
|
_NamedComponent_mixin.__new__
|
(cls, *args, **kw)
|
return rv
|
Pickling support.
Normally, we just create a new instance of this class.
However, if we're unpickling a reference in a loadable schema,
we need to return the existing component instance by looking
up the name in the component map of the desired namespace. We
can tell the difference because no normal constructors that
inherit from this have positional arguments; only invocations
by unpickling with a value returned in __getnewargs__ do.
This does require that the dependent namespace already have
been validated (or that it be validated here). That shouldn't
be a problem, except for the dependency loop resulting from
use of xml:lang in the XMLSchema namespace. For that issue,
see pyxb.namespace._XMLSchema.
|
Pickling support.
|
[
"Pickling",
"support",
"."
] |
def __new__ (cls, *args, **kw):
"""Pickling support.
Normally, we just create a new instance of this class.
However, if we're unpickling a reference in a loadable schema,
we need to return the existing component instance by looking
up the name in the component map of the desired namespace. We
can tell the difference because no normal constructors that
inherit from this have positional arguments; only invocations
by unpickling with a value returned in __getnewargs__ do.
This does require that the dependent namespace already have
been validated (or that it be validated here). That shouldn't
be a problem, except for the dependency loop resulting from
use of xml:lang in the XMLSchema namespace. For that issue,
see pyxb.namespace._XMLSchema.
"""
if 0 == len(args):
rv = super(_NamedComponent_mixin, cls).__new__(cls)
return rv
( object_reference, scope, icls ) = args
object_reference = _PickledAnonymousReference.FromPickled(object_reference)
# Explicitly validate here: the lookup operations won't do so,
# but will abort if the namespace hasn't been validated yet.
object_reference.validateComponentModel()
rv = None
if isinstance(scope, (tuple, _PickledAnonymousReference)):
# Scope is the expanded name of the complex type in which the
# named value can be located.
scope_ref = _PickledAnonymousReference.FromPickled(scope)
if object_reference.namespace() != scope_ref.namespace():
scope_ref.validateComponentModel()
assert 'typeDefinition' in scope_ref.namespace().categories()
scope_ctd = scope_ref.typeDefinition()
if scope_ctd is None:
raise pyxb.SchemaValidationError('Unable to resolve local scope %s' % (scope_ref,))
if issubclass(icls, AttributeDeclaration):
rv = scope_ctd.lookupScopedAttributeDeclaration(object_reference)
elif issubclass(icls, ElementDeclaration):
rv = scope_ctd.lookupScopedElementDeclaration(object_reference)
if rv is None:
raise pyxb.SchemaValidationError('Unable to resolve %s as %s in scope %s' % (object_reference, icls, scope_ref))
elif _ScopedDeclaration_mixin.ScopeIsGlobal(scope) or _ScopedDeclaration_mixin.ScopeIsIndeterminate(scope):
if (issubclass(icls, SimpleTypeDefinition) or issubclass(icls, ComplexTypeDefinition)):
rv = object_reference.typeDefinition()
elif issubclass(icls, AttributeGroupDefinition):
rv = object_reference.attributeGroupDefinition()
elif issubclass(icls, ModelGroupDefinition):
rv = object_reference.modelGroupDefinition()
elif issubclass(icls, AttributeDeclaration):
rv = object_reference.attributeDeclaration()
elif issubclass(icls, ElementDeclaration):
rv = object_reference.elementDeclaration()
elif issubclass(icls, IdentityConstraintDefinition):
rv = object_reference.identityConstraintDefinition()
if rv is None:
raise pyxb.SchemaValidationError('Unable to resolve %s as %s' % (object_reference, icls))
if rv is None:
raise pyxb.SchemaValidationError('Unable to resolve reference %s, scope %s ns %s type %s, class %s' % (object_reference, scope, (scope is None and "<unknown>" or scope.targetNamespace()), type(scope), icls))
return rv
|
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https://github.com/pabigot/pyxb/blob/14737c23a125fd12c954823ad64fc4497816fae3/pyxb/xmlschema/structures.py#L706-L768
|
|
googleapis/python-dialogflow
|
e48ea001b7c8a4a5c1fe4b162bad49ea397458e9
|
google/cloud/dialogflow_v2/services/intents/async_client.py
|
python
|
IntentsAsyncClient.list_intents
|
(
self,
request: Union[intent.ListIntentsRequest, dict] = None,
*,
parent: str = None,
language_code: str = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: float = None,
metadata: Sequence[Tuple[str, str]] = (),
)
|
return response
|
r"""Returns the list of all intents in the specified
agent.
Args:
request (Union[google.cloud.dialogflow_v2.types.ListIntentsRequest, dict]):
The request object. The request message for
[Intents.ListIntents][google.cloud.dialogflow.v2.Intents.ListIntents].
parent (:class:`str`):
Required. The agent to list all intents from. Format:
``projects/<Project ID>/agent`` or
``projects/<Project ID>/locations/<Location ID>/agent``.
Alternatively, you can specify the environment to list
intents for. Format:
``projects/<Project ID>/agent/environments/<Environment ID>``
or
``projects/<Project ID>/locations/<Location ID>/agent/environments/<Environment ID>``.
Note: training phrases of the intents will not be
returned for non-draft environment.
This corresponds to the ``parent`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
language_code (:class:`str`):
Optional. The language used to access language-specific
data. If not specified, the agent's default language is
used. For more information, see `Multilingual intent and
entity
data <https://cloud.google.com/dialogflow/docs/agents-multilingual#intent-entity>`__.
This corresponds to the ``language_code`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
retry (google.api_core.retry.Retry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.cloud.dialogflow_v2.services.intents.pagers.ListIntentsAsyncPager:
The response message for
[Intents.ListIntents][google.cloud.dialogflow.v2.Intents.ListIntents].
Iterating over this object will yield results and
resolve additional pages automatically.
|
r"""Returns the list of all intents in the specified
agent.
|
[
"r",
"Returns",
"the",
"list",
"of",
"all",
"intents",
"in",
"the",
"specified",
"agent",
"."
] |
async def list_intents(
self,
request: Union[intent.ListIntentsRequest, dict] = None,
*,
parent: str = None,
language_code: str = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: float = None,
metadata: Sequence[Tuple[str, str]] = (),
) -> pagers.ListIntentsAsyncPager:
r"""Returns the list of all intents in the specified
agent.
Args:
request (Union[google.cloud.dialogflow_v2.types.ListIntentsRequest, dict]):
The request object. The request message for
[Intents.ListIntents][google.cloud.dialogflow.v2.Intents.ListIntents].
parent (:class:`str`):
Required. The agent to list all intents from. Format:
``projects/<Project ID>/agent`` or
``projects/<Project ID>/locations/<Location ID>/agent``.
Alternatively, you can specify the environment to list
intents for. Format:
``projects/<Project ID>/agent/environments/<Environment ID>``
or
``projects/<Project ID>/locations/<Location ID>/agent/environments/<Environment ID>``.
Note: training phrases of the intents will not be
returned for non-draft environment.
This corresponds to the ``parent`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
language_code (:class:`str`):
Optional. The language used to access language-specific
data. If not specified, the agent's default language is
used. For more information, see `Multilingual intent and
entity
data <https://cloud.google.com/dialogflow/docs/agents-multilingual#intent-entity>`__.
This corresponds to the ``language_code`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
retry (google.api_core.retry.Retry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.cloud.dialogflow_v2.services.intents.pagers.ListIntentsAsyncPager:
The response message for
[Intents.ListIntents][google.cloud.dialogflow.v2.Intents.ListIntents].
Iterating over this object will yield results and
resolve additional pages automatically.
"""
# Create or coerce a protobuf request object.
# Sanity check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([parent, language_code])
if request is not None and has_flattened_params:
raise ValueError(
"If the `request` argument is set, then none of "
"the individual field arguments should be set."
)
request = intent.ListIntentsRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if parent is not None:
request.parent = parent
if language_code is not None:
request.language_code = language_code
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = gapic_v1.method_async.wrap_method(
self._client._transport.list_intents,
default_timeout=None,
client_info=DEFAULT_CLIENT_INFO,
)
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
)
# Send the request.
response = await rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
# This method is paged; wrap the response in a pager, which provides
# an `__aiter__` convenience method.
response = pagers.ListIntentsAsyncPager(
method=rpc, request=request, response=response, metadata=metadata,
)
# Done; return the response.
return response
|
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",",
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"=",
"metadata",
",",
")",
"# Done; return the response.",
"return",
"response"
] |
https://github.com/googleapis/python-dialogflow/blob/e48ea001b7c8a4a5c1fe4b162bad49ea397458e9/google/cloud/dialogflow_v2/services/intents/async_client.py#L170-L271
|
|
windelbouwman/ppci
|
915c069e0667042c085ec42c78e9e3c9a5295324
|
ppci/programs/ir_program.py
|
python
|
IrProgram.to_x86
|
(self, **options)
|
return self._new('x86', [ob])
|
Compile to X86 machine code.
Status: ...
|
Compile to X86 machine code.
|
[
"Compile",
"to",
"X86",
"machine",
"code",
"."
] |
def to_x86(self, **options):
""" Compile to X86 machine code.
Status: ...
"""
if options.get('win', ''):
arch = get_arch('x86_64:wincc')
else:
arch = get_arch('x86_64')
# todo: don't we want to be able to pass debug_db here?
ppci_modules = [m for m in self.items]
if self.debugdb:
ob = ir_to_object(ppci_modules, arch, debug=True)
else:
ob = ir_to_object(ppci_modules, arch, debug=False)
return self._new('x86', [ob])
|
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"self",
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"(",
"'x86'",
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"[",
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"]",
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] |
https://github.com/windelbouwman/ppci/blob/915c069e0667042c085ec42c78e9e3c9a5295324/ppci/programs/ir_program.py#L41-L59
|
|
francisck/DanderSpritz_docs
|
86bb7caca5a957147f120b18bb5c31f299914904
|
Python/Core/Lib/lib-tk/Tkinter.py
|
python
|
IntVar.__init__
|
(self, master=None, value=None, name=None)
|
Construct an integer variable.
MASTER can be given as master widget.
VALUE is an optional value (defaults to 0)
NAME is an optional Tcl name (defaults to PY_VARnum).
If NAME matches an existing variable and VALUE is omitted
then the existing value is retained.
|
Construct an integer variable.
MASTER can be given as master widget.
VALUE is an optional value (defaults to 0)
NAME is an optional Tcl name (defaults to PY_VARnum).
If NAME matches an existing variable and VALUE is omitted
then the existing value is retained.
|
[
"Construct",
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"variable",
".",
"MASTER",
"can",
"be",
"given",
"as",
"master",
"widget",
".",
"VALUE",
"is",
"an",
"optional",
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"variable",
"and",
"VALUE",
"is",
"omitted",
"then",
"the",
"existing",
"value",
"is",
"retained",
"."
] |
def __init__(self, master=None, value=None, name=None):
"""Construct an integer variable.
MASTER can be given as master widget.
VALUE is an optional value (defaults to 0)
NAME is an optional Tcl name (defaults to PY_VARnum).
If NAME matches an existing variable and VALUE is omitted
then the existing value is retained.
"""
Variable.__init__(self, master, value, name)
|
[
"def",
"__init__",
"(",
"self",
",",
"master",
"=",
"None",
",",
"value",
"=",
"None",
",",
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":",
"Variable",
".",
"__init__",
"(",
"self",
",",
"master",
",",
"value",
",",
"name",
")"
] |
https://github.com/francisck/DanderSpritz_docs/blob/86bb7caca5a957147f120b18bb5c31f299914904/Python/Core/Lib/lib-tk/Tkinter.py#L291-L301
|
||
kubernetes-client/python
|
47b9da9de2d02b2b7a34fbe05afb44afd130d73a
|
kubernetes/client/models/v1beta1_flow_schema_list.py
|
python
|
V1beta1FlowSchemaList.__repr__
|
(self)
|
return self.to_str()
|
For `print` and `pprint`
|
For `print` and `pprint`
|
[
"For",
"print",
"and",
"pprint"
] |
def __repr__(self):
"""For `print` and `pprint`"""
return self.to_str()
|
[
"def",
"__repr__",
"(",
"self",
")",
":",
"return",
"self",
".",
"to_str",
"(",
")"
] |
https://github.com/kubernetes-client/python/blob/47b9da9de2d02b2b7a34fbe05afb44afd130d73a/kubernetes/client/models/v1beta1_flow_schema_list.py#L189-L191
|
|
ysrc/xunfeng
|
40d40ecf55910019b8b904ef70ae1eebb6b6d26f
|
vulscan/vuldb/crack_supervisor_web.py
|
python
|
get_plugin_info
|
()
|
return plugin_info
|
[] |
def get_plugin_info():
plugin_info = {
"name": "Supervisor CVE-2017-11610",
"info": "Supervisor 接口未授权访问、弱口令、代码执行漏洞",
"level": "高危",
"type": "弱口令",
"author": "unknown",
"url": "https://github.com/Medicean/VulApps/blob/master/s/supervisor/1/",
"keyword": "port:9001",
"source": 1
}
return plugin_info
|
[
"def",
"get_plugin_info",
"(",
")",
":",
"plugin_info",
"=",
"{",
"\"name\"",
":",
"\"Supervisor CVE-2017-11610\"",
",",
"\"info\"",
":",
"\"Supervisor 接口未授权访问、弱口令、代码执行漏洞\",",
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",",
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":",
"\"port:9001\"",
",",
"\"source\"",
":",
"1",
"}",
"return",
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] |
https://github.com/ysrc/xunfeng/blob/40d40ecf55910019b8b904ef70ae1eebb6b6d26f/vulscan/vuldb/crack_supervisor_web.py#L8-L19
|
|||
DEAP/deap
|
2f63dcf6aaa341b8fe5d66d99e9e003a21312fef
|
deap/benchmarks/gp.py
|
python
|
salustowicz_2d
|
(data)
|
return exp(-data[0]) * data[0]**3 * cos(data[0]) * sin(data[0]) * (cos(data[0]) * sin(data[0])**2 - 1) * (data[1] - 5)
|
Salustowicz benchmark function.
.. list-table::
:widths: 10 50
:stub-columns: 1
* - Range
- :math:`\mathbf{x} \in [0, 7]^2`
* - Function
- :math:`f(\mathbf{x}) = e^{-x_1} x_1^3 \cos(x_1) \sin(x_1) (\cos(x_1) \sin^2(x_1) - 1) (x_2 -5)`
|
Salustowicz benchmark function.
|
[
"Salustowicz",
"benchmark",
"function",
"."
] |
def salustowicz_2d(data):
"""Salustowicz benchmark function.
.. list-table::
:widths: 10 50
:stub-columns: 1
* - Range
- :math:`\mathbf{x} \in [0, 7]^2`
* - Function
- :math:`f(\mathbf{x}) = e^{-x_1} x_1^3 \cos(x_1) \sin(x_1) (\cos(x_1) \sin^2(x_1) - 1) (x_2 -5)`
"""
return exp(-data[0]) * data[0]**3 * cos(data[0]) * sin(data[0]) * (cos(data[0]) * sin(data[0])**2 - 1) * (data[1] - 5)
|
[
"def",
"salustowicz_2d",
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"-",
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"(",
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"[",
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"-",
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] |
https://github.com/DEAP/deap/blob/2f63dcf6aaa341b8fe5d66d99e9e003a21312fef/deap/benchmarks/gp.py#L46-L58
|
|
rwth-i6/returnn
|
f2d718a197a280b0d5f0fd91a7fcb8658560dddb
|
returnn/import_/common.py
|
python
|
_normalize_pkg_name
|
(name)
|
return name
|
:param str name:
:rtype: str
|
:param str name:
:rtype: str
|
[
":",
"param",
"str",
"name",
":",
":",
"rtype",
":",
"str"
] |
def _normalize_pkg_name(name):
"""
:param str name:
:rtype: str
"""
name = name.replace(".", "_")
name = name.replace("-", "_")
return name
|
[
"def",
"_normalize_pkg_name",
"(",
"name",
")",
":",
"name",
"=",
"name",
".",
"replace",
"(",
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"name",
"=",
"name",
".",
"replace",
"(",
"\"-\"",
",",
"\"_\"",
")",
"return",
"name"
] |
https://github.com/rwth-i6/returnn/blob/f2d718a197a280b0d5f0fd91a7fcb8658560dddb/returnn/import_/common.py#L128-L135
|
|
rwth-i6/returnn
|
f2d718a197a280b0d5f0fd91a7fcb8658560dddb
|
returnn/util/basic.py
|
python
|
NativeCodeCompiler.__init__
|
(self, base_name, code_version, code,
is_cpp=True, c_macro_defines=None, ld_flags=None,
include_paths=(), include_deps=None,
static_version_name=None, should_cleanup_old_all=True, should_cleanup_old_mydir=False,
use_cxx11_abi=False, log_stream=None, verbose=False)
|
:param str base_name: base name for the module, e.g. "zero_out"
:param int|tuple[int] code_version: check for the cache whether to reuse
:param str code: the source code itself
:param bool is_cpp: if False, C is assumed
:param dict[str,str|int]|None c_macro_defines: e.g. {"TENSORFLOW": 1}
:param list[str]|None ld_flags: e.g. ["-lblas"]
:param list[str]|tuple[str] include_paths:
:param list[str]|None include_deps: if provided and an existing lib file, we will check if any dependency is newer
and we need to recompile. we could also do it automatically via -MD but that seems overkill and too slow.
:param str|None static_version_name: normally, we use .../base_name/hash as the dir
but this would use .../base_name/static_version_name.
:param bool should_cleanup_old_all: whether we should look in the cache dir
and check all ops if we can delete some old ones which are older than some limit (self._cleanup_time_limit_days)
:param bool should_cleanup_old_mydir: whether we should delete our op dir before we compile there.
:param typing.TextIO|None log_stream: file stream for print statements
:param bool verbose: be slightly more verbose
|
:param str base_name: base name for the module, e.g. "zero_out"
:param int|tuple[int] code_version: check for the cache whether to reuse
:param str code: the source code itself
:param bool is_cpp: if False, C is assumed
:param dict[str,str|int]|None c_macro_defines: e.g. {"TENSORFLOW": 1}
:param list[str]|None ld_flags: e.g. ["-lblas"]
:param list[str]|tuple[str] include_paths:
:param list[str]|None include_deps: if provided and an existing lib file, we will check if any dependency is newer
and we need to recompile. we could also do it automatically via -MD but that seems overkill and too slow.
:param str|None static_version_name: normally, we use .../base_name/hash as the dir
but this would use .../base_name/static_version_name.
:param bool should_cleanup_old_all: whether we should look in the cache dir
and check all ops if we can delete some old ones which are older than some limit (self._cleanup_time_limit_days)
:param bool should_cleanup_old_mydir: whether we should delete our op dir before we compile there.
:param typing.TextIO|None log_stream: file stream for print statements
:param bool verbose: be slightly more verbose
|
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def __init__(self, base_name, code_version, code,
is_cpp=True, c_macro_defines=None, ld_flags=None,
include_paths=(), include_deps=None,
static_version_name=None, should_cleanup_old_all=True, should_cleanup_old_mydir=False,
use_cxx11_abi=False, log_stream=None, verbose=False):
"""
:param str base_name: base name for the module, e.g. "zero_out"
:param int|tuple[int] code_version: check for the cache whether to reuse
:param str code: the source code itself
:param bool is_cpp: if False, C is assumed
:param dict[str,str|int]|None c_macro_defines: e.g. {"TENSORFLOW": 1}
:param list[str]|None ld_flags: e.g. ["-lblas"]
:param list[str]|tuple[str] include_paths:
:param list[str]|None include_deps: if provided and an existing lib file, we will check if any dependency is newer
and we need to recompile. we could also do it automatically via -MD but that seems overkill and too slow.
:param str|None static_version_name: normally, we use .../base_name/hash as the dir
but this would use .../base_name/static_version_name.
:param bool should_cleanup_old_all: whether we should look in the cache dir
and check all ops if we can delete some old ones which are older than some limit (self._cleanup_time_limit_days)
:param bool should_cleanup_old_mydir: whether we should delete our op dir before we compile there.
:param typing.TextIO|None log_stream: file stream for print statements
:param bool verbose: be slightly more verbose
"""
if self.CollectedCompilers is not None:
self.CollectedCompilers.append(self)
self.verbose = verbose
self.cache_dir = "%s/%s" % (get_cache_dir(), self.CacheDirName)
self._include_paths = list(include_paths)
self.base_name = base_name
self.code_version = code_version
self.code = code
self.is_cpp = is_cpp
self.c_macro_defines = c_macro_defines or {}
self.ld_flags = ld_flags or []
self.include_deps = include_deps
self.static_version_name = static_version_name
self._code_hash = self._make_code_hash()
self._info_dict = self._make_info_dict()
self._hash = self._make_hash()
self._ctypes_lib = None
if should_cleanup_old_all:
self._cleanup_old()
self._should_cleanup_old_mydir = should_cleanup_old_mydir
self.use_cxx11_abi = use_cxx11_abi
self._log_stream = log_stream
if self.verbose:
print("%s: %r" % (self.__class__.__name__, self), file=log_stream)
|
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https://github.com/rwth-i6/returnn/blob/f2d718a197a280b0d5f0fd91a7fcb8658560dddb/returnn/util/basic.py#L3327-L3373
|
||
pymedusa/Medusa
|
1405fbb6eb8ef4d20fcca24c32ddca52b11f0f38
|
ext/trakt/sync.py
|
python
|
Scrobbler.update
|
(self, progress)
|
Update the scobbling progress of this :class:`Scrobbler`'s *media*
object
|
Update the scobbling progress of this :class:`Scrobbler`'s *media*
object
|
[
"Update",
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"of",
"this",
":",
"class",
":",
"Scrobbler",
"s",
"*",
"media",
"*",
"object"
] |
def update(self, progress):
"""Update the scobbling progress of this :class:`Scrobbler`'s *media*
object
"""
self.progress = progress
self.start()
|
[
"def",
"update",
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":",
"self",
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"progress",
"=",
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"start",
"(",
")"
] |
https://github.com/pymedusa/Medusa/blob/1405fbb6eb8ef4d20fcca24c32ddca52b11f0f38/ext/trakt/sync.py#L475-L480
|
||
EricSteinberger/PokerRL
|
e02ea667061b96912e424231da071b6f20a262f7
|
PokerRL/game/_/rl_env/base/PokerEnv.py
|
python
|
PokerEnv._get_step_reward
|
(self, is_terminal)
|
return [(p.stack - p.starting_stack_this_episode) / self.REWARD_SCALAR for p in self.seats]
|
[] |
def _get_step_reward(self, is_terminal):
if not is_terminal:
return np.zeros(shape=self.N_SEATS, dtype=np.float32)
return [(p.stack - p.starting_stack_this_episode) / self.REWARD_SCALAR for p in self.seats]
|
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] |
https://github.com/EricSteinberger/PokerRL/blob/e02ea667061b96912e424231da071b6f20a262f7/PokerRL/game/_/rl_env/base/PokerEnv.py#L1069-L1072
|
|||
MaslowCNC/GroundControl
|
294a05dea5b9753383e24b07ea47d78e76e49422
|
CalibrationWidgets/computeCalibrationSteps.py
|
python
|
ComputeCalibrationSteps.on_Enter
|
(self)
|
This function runs when the step is entered
|
This function runs when the step is entered
|
[
"This",
"function",
"runs",
"when",
"the",
"step",
"is",
"entered"
] |
def on_Enter(self):
'''
This function runs when the step is entered
'''
self.setupListOfSteps()
Clock.schedule_once(self.loadNextStep, 5)
|
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"(",
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"loadNextStep",
",",
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")"
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https://github.com/MaslowCNC/GroundControl/blob/294a05dea5b9753383e24b07ea47d78e76e49422/CalibrationWidgets/computeCalibrationSteps.py#L16-L24
|
||
replit-archive/empythoned
|
977ec10ced29a3541a4973dc2b59910805695752
|
dist/lib/python2.7/lib2to3/refactor.py
|
python
|
RefactoringTool.processed_file
|
(self, new_text, filename, old_text=None, write=False,
encoding=None)
|
Called when a file has been refactored, and there are changes.
|
Called when a file has been refactored, and there are changes.
|
[
"Called",
"when",
"a",
"file",
"has",
"been",
"refactored",
"and",
"there",
"are",
"changes",
"."
] |
def processed_file(self, new_text, filename, old_text=None, write=False,
encoding=None):
"""
Called when a file has been refactored, and there are changes.
"""
self.files.append(filename)
if old_text is None:
old_text = self._read_python_source(filename)[0]
if old_text is None:
return
equal = old_text == new_text
self.print_output(old_text, new_text, filename, equal)
if equal:
self.log_debug("No changes to %s", filename)
return
if write:
self.write_file(new_text, filename, old_text, encoding)
else:
self.log_debug("Not writing changes to %s", filename)
|
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https://github.com/replit-archive/empythoned/blob/977ec10ced29a3541a4973dc2b59910805695752/dist/lib/python2.7/lib2to3/refactor.py#L502-L520
|
||
omz/PythonistaAppTemplate
|
f560f93f8876d82a21d108977f90583df08d55af
|
PythonistaAppTemplate/PythonistaKit.framework/pylib_ext/sympy/polys/factortools.py
|
python
|
dmp_zz_wang_lead_coeffs
|
(f, T, cs, E, H, A, u, K)
|
return f, HHH, CCC
|
Wang/EEZ: Compute correct leading coefficients.
|
Wang/EEZ: Compute correct leading coefficients.
|
[
"Wang",
"/",
"EEZ",
":",
"Compute",
"correct",
"leading",
"coefficients",
"."
] |
def dmp_zz_wang_lead_coeffs(f, T, cs, E, H, A, u, K):
"""Wang/EEZ: Compute correct leading coefficients. """
C, J, v = [], [0]*len(E), u - 1
for h in H:
c = dmp_one(v, K)
d = dup_LC(h, K)*cs
for i in reversed(xrange(len(E))):
k, e, (t, _) = 0, E[i], T[i]
while not (d % e):
d, k = d//e, k + 1
if k != 0:
c, J[i] = dmp_mul(c, dmp_pow(t, k, v, K), v, K), 1
C.append(c)
if any(not j for j in J):
raise ExtraneousFactors # pragma: no cover
CC, HH = [], []
for c, h in zip(C, H):
d = dmp_eval_tail(c, A, v, K)
lc = dup_LC(h, K)
if K.is_one(cs):
cc = lc//d
else:
g = K.gcd(lc, d)
d, cc = d//g, lc//g
h, cs = dup_mul_ground(h, d, K), cs//d
c = dmp_mul_ground(c, cc, v, K)
CC.append(c)
HH.append(h)
if K.is_one(cs):
return f, HH, CC
CCC, HHH = [], []
for c, h in zip(CC, HH):
CCC.append(dmp_mul_ground(c, cs, v, K))
HHH.append(dmp_mul_ground(h, cs, 0, K))
f = dmp_mul_ground(f, cs**(len(H) - 1), u, K)
return f, HHH, CCC
|
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https://github.com/omz/PythonistaAppTemplate/blob/f560f93f8876d82a21d108977f90583df08d55af/PythonistaAppTemplate/PythonistaKit.framework/pylib_ext/sympy/polys/factortools.py#L672-L723
|
|
ajinabraham/OWASP-Xenotix-XSS-Exploit-Framework
|
cb692f527e4e819b6c228187c5702d990a180043
|
external/Scripting Engine/Xenotix Python Scripting Engine/packages/IronPython.StdLib.2.7.4/content/Lib/code.py
|
python
|
InteractiveInterpreter.write
|
(self, data)
|
Write a string.
The base implementation writes to sys.stderr; a subclass may
replace this with a different implementation.
|
Write a string.
|
[
"Write",
"a",
"string",
"."
] |
def write(self, data):
"""Write a string.
The base implementation writes to sys.stderr; a subclass may
replace this with a different implementation.
"""
sys.stderr.write(data)
|
[
"def",
"write",
"(",
"self",
",",
"data",
")",
":",
"sys",
".",
"stderr",
".",
"write",
"(",
"data",
")"
] |
https://github.com/ajinabraham/OWASP-Xenotix-XSS-Exploit-Framework/blob/cb692f527e4e819b6c228187c5702d990a180043/external/Scripting Engine/Xenotix Python Scripting Engine/packages/IronPython.StdLib.2.7.4/content/Lib/code.py#L164-L171
|
||
cloudera/hue
|
23f02102d4547c17c32bd5ea0eb24e9eadd657a4
|
desktop/core/ext-py/ply-3.11/example/ansic/cparse.py
|
python
|
p_equality_expression_2
|
(t)
|
equality_expression : equality_expression EQ relational_expression
|
equality_expression : equality_expression EQ relational_expression
|
[
"equality_expression",
":",
"equality_expression",
"EQ",
"relational_expression"
] |
def p_equality_expression_2(t):
'equality_expression : equality_expression EQ relational_expression'
pass
|
[
"def",
"p_equality_expression_2",
"(",
"t",
")",
":",
"pass"
] |
https://github.com/cloudera/hue/blob/23f02102d4547c17c32bd5ea0eb24e9eadd657a4/desktop/core/ext-py/ply-3.11/example/ansic/cparse.py#L817-L819
|
||
MushroomRL/mushroom-rl
|
a0eaa2cf8001e433419234a9fc48b64170e3f61c
|
mushroom_rl/approximators/parametric/cmac.py
|
python
|
CMAC.diff
|
(self, state, action=None)
|
return super().diff(phi, action)
|
Compute the derivative of the output w.r.t. ``state``, and ``action``
if provided.
Args:
state (np.ndarray): the state;
action (np.ndarray, None): the action.
Returns:
The derivative of the output w.r.t. ``state``, and ``action``
if provided.
|
Compute the derivative of the output w.r.t. ``state``, and ``action``
if provided.
|
[
"Compute",
"the",
"derivative",
"of",
"the",
"output",
"w",
".",
"r",
".",
"t",
".",
"state",
"and",
"action",
"if",
"provided",
"."
] |
def diff(self, state, action=None):
"""
Compute the derivative of the output w.r.t. ``state``, and ``action``
if provided.
Args:
state (np.ndarray): the state;
action (np.ndarray, None): the action.
Returns:
The derivative of the output w.r.t. ``state``, and ``action``
if provided.
"""
phi = self._phi(state)
return super().diff(phi, action)
|
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"def",
"diff",
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"self",
",",
"state",
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"=",
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"return",
"super",
"(",
")",
".",
"diff",
"(",
"phi",
",",
"action",
")"
] |
https://github.com/MushroomRL/mushroom-rl/blob/a0eaa2cf8001e433419234a9fc48b64170e3f61c/mushroom_rl/approximators/parametric/cmac.py#L85-L101
|
|
google/grr
|
8ad8a4d2c5a93c92729206b7771af19d92d4f915
|
grr/core/grr_response_core/lib/casing.py
|
python
|
SnakeToCamel
|
(snake_str: str)
|
return words[0] + "".join(map(str.capitalize, words[1:]))
|
Convert a snake_case string representing one identifier to lowerCamelCase.
The function uses a best-effort approach to convert the given string to a
valid lowerCamelCase string, meaning that it converts even strings that use
multiple consecutive underscores between words and/or that start/end with an
underscore.
Args:
snake_str: A snake_case string representing a single identifier.
Returns:
A lowerCamelCase representation of the given string.
|
Convert a snake_case string representing one identifier to lowerCamelCase.
|
[
"Convert",
"a",
"snake_case",
"string",
"representing",
"one",
"identifier",
"to",
"lowerCamelCase",
"."
] |
def SnakeToCamel(snake_str: str) -> str:
"""Convert a snake_case string representing one identifier to lowerCamelCase.
The function uses a best-effort approach to convert the given string to a
valid lowerCamelCase string, meaning that it converts even strings that use
multiple consecutive underscores between words and/or that start/end with an
underscore.
Args:
snake_str: A snake_case string representing a single identifier.
Returns:
A lowerCamelCase representation of the given string.
"""
# Extract the words from the snake_case string.
words = [word for word in snake_str.split("_") if word]
if not words:
return ""
words[:] = map(str.lower, words)
return words[0] + "".join(map(str.capitalize, words[1:]))
|
[
"def",
"SnakeToCamel",
"(",
"snake_str",
":",
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")",
"->",
"str",
":",
"# Extract the words from the snake_case string.",
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"[",
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",",
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"[",
"1",
":",
"]",
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")"
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https://github.com/google/grr/blob/8ad8a4d2c5a93c92729206b7771af19d92d4f915/grr/core/grr_response_core/lib/casing.py#L6-L27
|
|
microsoft/unilm
|
65f15af2a307ebb64cfb25adf54375b002e6fe8d
|
xtune/src/transformers/modeling_tf_openai.py
|
python
|
TFOpenAIGPTMainLayer._prune_heads
|
(self, heads_to_prune)
|
Prunes heads of the model.
heads_to_prune: dict of {layer_num: list of heads to prune in this layer}
|
Prunes heads of the model.
heads_to_prune: dict of {layer_num: list of heads to prune in this layer}
|
[
"Prunes",
"heads",
"of",
"the",
"model",
".",
"heads_to_prune",
":",
"dict",
"of",
"{",
"layer_num",
":",
"list",
"of",
"heads",
"to",
"prune",
"in",
"this",
"layer",
"}"
] |
def _prune_heads(self, heads_to_prune):
""" Prunes heads of the model.
heads_to_prune: dict of {layer_num: list of heads to prune in this layer}
"""
raise NotImplementedError
|
[
"def",
"_prune_heads",
"(",
"self",
",",
"heads_to_prune",
")",
":",
"raise",
"NotImplementedError"
] |
https://github.com/microsoft/unilm/blob/65f15af2a307ebb64cfb25adf54375b002e6fe8d/xtune/src/transformers/modeling_tf_openai.py#L227-L231
|
||
Mailu/Mailu
|
1e53530164e9eaf77a89c322e34bff447ace5a28
|
core/admin/migrations/env.py
|
python
|
run_migrations_online
|
()
|
Run migrations in 'online' mode.
In this scenario we need to create an Engine
and associate a connection with the context.
|
Run migrations in 'online' mode.
|
[
"Run",
"migrations",
"in",
"online",
"mode",
"."
] |
def run_migrations_online():
"""Run migrations in 'online' mode.
In this scenario we need to create an Engine
and associate a connection with the context.
"""
# this callback is used to prevent an auto-migration from being generated
# when there are no changes to the schema
# reference: http://alembic.readthedocs.org/en/latest/cookbook.html
def process_revision_directives(context, revision, directives):
if getattr(config.cmd_opts, 'autogenerate', False):
script = directives[0]
if script.upgrade_ops.is_empty():
directives[:] = []
logger.info('No changes in schema detected.')
engine = engine_from_config(
config.get_section(config.config_ini_section),
prefix = 'sqlalchemy.',
poolclass = pool.NullPool
)
@tenacity.retry(
stop = tenacity.stop_after_attempt(100),
wait = tenacity.wait_random(min=2, max=5),
before = tenacity.before_log(logging.getLogger('tenacity.retry'), logging.DEBUG),
before_sleep = tenacity.before_sleep_log(logging.getLogger('tenacity.retry'), logging.INFO),
after = tenacity.after_log(logging.getLogger('tenacity.retry'), logging.DEBUG)
)
def try_connect(db):
return db.connect()
with try_connect(engine) as connection:
context.configure(
connection = connection,
target_metadata = target_metadata,
process_revision_directives = process_revision_directives,
**current_app.extensions['migrate'].configure_args
)
with context.begin_transaction():
context.run_migrations()
connection.close()
|
[
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"# when there are no changes to the schema",
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")",
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"close",
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")"
] |
https://github.com/Mailu/Mailu/blob/1e53530164e9eaf77a89c322e34bff447ace5a28/core/admin/migrations/env.py#L48-L94
|
||
rhinstaller/anaconda
|
63edc8680f1b05cbfe11bef28703acba808c5174
|
pyanaconda/modules/payloads/source/harddrive/initialization.py
|
python
|
SetUpHardDriveSourceTask.run
|
(self)
|
Run Hard drive installation source setup.
Always sets up two mount points: First for the device, and second for the ISO image or a
bind for unpacked ISO. These depend on each other, and must be destroyed in the correct
order again.
:raise: SourceSetupError
:return: named tuple with path to the install tree and name of ISO if set or empty string
:rtype: SetupHardDriveResult instance
|
Run Hard drive installation source setup.
|
[
"Run",
"Hard",
"drive",
"installation",
"source",
"setup",
"."
] |
def run(self):
"""Run Hard drive installation source setup.
Always sets up two mount points: First for the device, and second for the ISO image or a
bind for unpacked ISO. These depend on each other, and must be destroyed in the correct
order again.
:raise: SourceSetupError
:return: named tuple with path to the install tree and name of ISO if set or empty string
:rtype: SetupHardDriveResult instance
"""
log.debug("Setting up Hard drive source")
for mount_point in [self._device_mount, self._iso_mount]:
if os.path.ismount(mount_point):
raise SourceSetupError("The mount point {} is already in use.".format(
mount_point
))
if not find_and_mount_device(self._partition, self._device_mount):
raise SourceSetupError(
"Could not mount device specified as {}".format(self._partition)
)
full_path_on_mounted_device = os.path.normpath(
"{}/{}".format(self._device_mount, self._directory)
)
iso_name = find_and_mount_iso_image(full_path_on_mounted_device, self._iso_mount)
if iso_name:
log.debug("Using the ISO '%s' mounted at '%s'.", iso_name, self._iso_mount)
return SetupHardDriveResult(self._iso_mount, iso_name)
if verify_valid_repository(full_path_on_mounted_device):
log.debug("Using the directory at '%s'.", full_path_on_mounted_device)
return SetupHardDriveResult(full_path_on_mounted_device, "")
# nothing found unmount the existing device
unmount(self._device_mount)
raise SourceSetupError(
"Nothing useful found for Hard drive ISO source at partition={} directory={}".format(
self._partition, self._directory))
|
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",",
"self",
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"_directory",
")",
")"
] |
https://github.com/rhinstaller/anaconda/blob/63edc8680f1b05cbfe11bef28703acba808c5174/pyanaconda/modules/payloads/source/harddrive/initialization.py#L51-L93
|
||
bruderstein/PythonScript
|
df9f7071ddf3a079e3a301b9b53a6dc78cf1208f
|
PythonLib/full/http/cookiejar.py
|
python
|
Cookie.__str__
|
(self)
|
return "<Cookie %s for %s>" % (namevalue, limit)
|
[] |
def __str__(self):
if self.port is None: p = ""
else: p = ":"+self.port
limit = self.domain + p + self.path
if self.value is not None:
namevalue = "%s=%s" % (self.name, self.value)
else:
namevalue = self.name
return "<Cookie %s for %s>" % (namevalue, limit)
|
[
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"__str__",
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":",
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"(",
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",",
"limit",
")"
] |
https://github.com/bruderstein/PythonScript/blob/df9f7071ddf3a079e3a301b9b53a6dc78cf1208f/PythonLib/full/http/cookiejar.py#L817-L825
|
|||
SteveDoyle2/pyNastran
|
eda651ac2d4883d95a34951f8a002ff94f642a1a
|
pyNastran/bdf/cards/material_deps.py
|
python
|
MATT2.uncross_reference
|
(self)
|
Removes cross-reference links
|
Removes cross-reference links
|
[
"Removes",
"cross",
"-",
"reference",
"links"
] |
def uncross_reference(self) -> None:
"""Removes cross-reference links"""
self.mid = self.Mid()
self.g11_table = self.G11_table()
self.g12_table = self.G12_table()
self.g13_table = self.G13_table()
self.g22_table = self.G22_table()
self.g23_table = self.G23_table()
self.g33_table = self.G33_table()
self.rho_table = self.Rho_table()
self.a1_table = self.A1_table()
self.a2_table = self.A2_table()
self.a3_table = self.A3_table()
self.ge_table = self.Ge_table()
self.st_table = self.St_table()
self.sc_table = self.Sc_table()
self.ss_table = self.Ss_table()
self.mid_ref = None
|
[
"def",
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"(",
")",
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"=",
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] |
https://github.com/SteveDoyle2/pyNastran/blob/eda651ac2d4883d95a34951f8a002ff94f642a1a/pyNastran/bdf/cards/material_deps.py#L697-L714
|
||
Azure/azure-cli
|
6c1b085a0910c6c2139006fcbd8ade44006eb6dd
|
src/azure-cli/azure/cli/command_modules/apim/_format.py
|
python
|
_get_value_as_str
|
(item, *args)
|
Get a nested value from a dict.
:param dict item: The dict object
|
Get a nested value from a dict.
:param dict item: The dict object
|
[
"Get",
"a",
"nested",
"value",
"from",
"a",
"dict",
".",
":",
"param",
"dict",
"item",
":",
"The",
"dict",
"object"
] |
def _get_value_as_str(item, *args):
"""Get a nested value from a dict.
:param dict item: The dict object
"""
try:
for arg in args:
item = item[arg]
return str(item) if item else ' '
except (KeyError, TypeError, IndexError):
return ' '
|
[
"def",
"_get_value_as_str",
"(",
"item",
",",
"*",
"args",
")",
":",
"try",
":",
"for",
"arg",
"in",
"args",
":",
"item",
"=",
"item",
"[",
"arg",
"]",
"return",
"str",
"(",
"item",
")",
"if",
"item",
"else",
"' '",
"except",
"(",
"KeyError",
",",
"TypeError",
",",
"IndexError",
")",
":",
"return",
"' '"
] |
https://github.com/Azure/azure-cli/blob/6c1b085a0910c6c2139006fcbd8ade44006eb6dd/src/azure-cli/azure/cli/command_modules/apim/_format.py#L43-L52
|
||
buke/GreenOdoo
|
3d8c55d426fb41fdb3f2f5a1533cfe05983ba1df
|
runtime/python/lib/python2.7/site-packages/docutils/writers/__init__.py
|
python
|
Writer.write
|
(self, document, destination)
|
return output
|
Process a document into its final form.
Translate `document` (a Docutils document tree) into the Writer's
native format, and write it out to its `destination` (a
`docutils.io.Output` subclass object).
Normally not overridden or extended in subclasses.
|
Process a document into its final form.
|
[
"Process",
"a",
"document",
"into",
"its",
"final",
"form",
"."
] |
def write(self, document, destination):
"""
Process a document into its final form.
Translate `document` (a Docutils document tree) into the Writer's
native format, and write it out to its `destination` (a
`docutils.io.Output` subclass object).
Normally not overridden or extended in subclasses.
"""
self.document = document
self.language = languages.get_language(
document.settings.language_code,
document.reporter)
self.destination = destination
self.translate()
output = self.destination.write(self.output)
return output
|
[
"def",
"write",
"(",
"self",
",",
"document",
",",
"destination",
")",
":",
"self",
".",
"document",
"=",
"document",
"self",
".",
"language",
"=",
"languages",
".",
"get_language",
"(",
"document",
".",
"settings",
".",
"language_code",
",",
"document",
".",
"reporter",
")",
"self",
".",
"destination",
"=",
"destination",
"self",
".",
"translate",
"(",
")",
"output",
"=",
"self",
".",
"destination",
".",
"write",
"(",
"self",
".",
"output",
")",
"return",
"output"
] |
https://github.com/buke/GreenOdoo/blob/3d8c55d426fb41fdb3f2f5a1533cfe05983ba1df/runtime/python/lib/python2.7/site-packages/docutils/writers/__init__.py#L65-L82
|
|
ceph/teuthology
|
6fc2011361437a9dfe4e45b50de224392eed8abc
|
teuthology/report.py
|
python
|
ResultsReporter.get_run
|
(self, run_name, fields=None)
|
return response.json()
|
Query the results server for a run
:param run_name: The name of the run
:param fields: Optional. A list of fields to include in the result.
Defaults to returning all fields.
|
Query the results server for a run
|
[
"Query",
"the",
"results",
"server",
"for",
"a",
"run"
] |
def get_run(self, run_name, fields=None):
"""
Query the results server for a run
:param run_name: The name of the run
:param fields: Optional. A list of fields to include in the result.
Defaults to returning all fields.
"""
uri = "{base}/runs/{name}".format(base=self.base_uri, name=run_name)
if fields:
uri += "?fields=" + ','.join(fields)
response = self.session.get(uri)
response.raise_for_status()
return response.json()
|
[
"def",
"get_run",
"(",
"self",
",",
"run_name",
",",
"fields",
"=",
"None",
")",
":",
"uri",
"=",
"\"{base}/runs/{name}\"",
".",
"format",
"(",
"base",
"=",
"self",
".",
"base_uri",
",",
"name",
"=",
"run_name",
")",
"if",
"fields",
":",
"uri",
"+=",
"\"?fields=\"",
"+",
"','",
".",
"join",
"(",
"fields",
")",
"response",
"=",
"self",
".",
"session",
".",
"get",
"(",
"uri",
")",
"response",
".",
"raise_for_status",
"(",
")",
"return",
"response",
".",
"json",
"(",
")"
] |
https://github.com/ceph/teuthology/blob/6fc2011361437a9dfe4e45b50de224392eed8abc/teuthology/report.py#L376-L389
|
|
hakril/PythonForWindows
|
61e027a678d5b87aa64fcf8a37a6661a86236589
|
windows/winobject/bits.py
|
python
|
BitsCopyCallbackSetEvent.JobError
|
(self, this, job, error)
|
return True
|
[] |
def JobError(self, this, job, error):
job = BitsCopyJob(job)
error = BitsCopyError(error)
errcode, errctx = error.error
print("Copy failed with error code <{0:#x}> (ctx={1})".format(errcode, errctx))
print("see <https://msdn.microsoft.com/en-us/library/windows/desktop/aa362823(v=vs.85).aspx>")
self.event.set()
return True
|
[
"def",
"JobError",
"(",
"self",
",",
"this",
",",
"job",
",",
"error",
")",
":",
"job",
"=",
"BitsCopyJob",
"(",
"job",
")",
"error",
"=",
"BitsCopyError",
"(",
"error",
")",
"errcode",
",",
"errctx",
"=",
"error",
".",
"error",
"print",
"(",
"\"Copy failed with error code <{0:#x}> (ctx={1})\"",
".",
"format",
"(",
"errcode",
",",
"errctx",
")",
")",
"print",
"(",
"\"see <https://msdn.microsoft.com/en-us/library/windows/desktop/aa362823(v=vs.85).aspx>\"",
")",
"self",
".",
"event",
".",
"set",
"(",
")",
"return",
"True"
] |
https://github.com/hakril/PythonForWindows/blob/61e027a678d5b87aa64fcf8a37a6661a86236589/windows/winobject/bits.py#L48-L55
|
|||
openhatch/oh-mainline
|
ce29352a034e1223141dcc2f317030bbc3359a51
|
vendor/packages/twisted/twisted/news/nntp.py
|
python
|
NNTPClient.fetchGroup
|
(self, group)
|
Get group information for the specified group from the server. gotGroup()
is called on success, getGroupFailed() on failure.
|
Get group information for the specified group from the server. gotGroup()
is called on success, getGroupFailed() on failure.
|
[
"Get",
"group",
"information",
"for",
"the",
"specified",
"group",
"from",
"the",
"server",
".",
"gotGroup",
"()",
"is",
"called",
"on",
"success",
"getGroupFailed",
"()",
"on",
"failure",
"."
] |
def fetchGroup(self, group):
"""
Get group information for the specified group from the server. gotGroup()
is called on success, getGroupFailed() on failure.
"""
self.sendLine('GROUP %s' % (group,))
self._newState(None, self.getGroupFailed, self._headerGroup)
|
[
"def",
"fetchGroup",
"(",
"self",
",",
"group",
")",
":",
"self",
".",
"sendLine",
"(",
"'GROUP %s'",
"%",
"(",
"group",
",",
")",
")",
"self",
".",
"_newState",
"(",
"None",
",",
"self",
".",
"getGroupFailed",
",",
"self",
".",
"_headerGroup",
")"
] |
https://github.com/openhatch/oh-mainline/blob/ce29352a034e1223141dcc2f317030bbc3359a51/vendor/packages/twisted/twisted/news/nntp.py#L226-L232
|
||
pyscf/pyscf
|
0adfb464333f5ceee07b664f291d4084801bae64
|
pyscf/scf/hf.py
|
python
|
get_ovlp
|
(mol)
|
return mol.intor_symmetric('int1e_ovlp')
|
Overlap matrix
|
Overlap matrix
|
[
"Overlap",
"matrix"
] |
def get_ovlp(mol):
'''Overlap matrix
'''
return mol.intor_symmetric('int1e_ovlp')
|
[
"def",
"get_ovlp",
"(",
"mol",
")",
":",
"return",
"mol",
".",
"intor_symmetric",
"(",
"'int1e_ovlp'",
")"
] |
https://github.com/pyscf/pyscf/blob/0adfb464333f5ceee07b664f291d4084801bae64/pyscf/scf/hf.py#L327-L330
|
|
sahana/eden
|
1696fa50e90ce967df69f66b571af45356cc18da
|
modules/s3/codecs/pdf.py
|
python
|
S3html2pdf.parse
|
(self, html)
|
return result
|
Entry point for class
|
Entry point for class
|
[
"Entry",
"point",
"for",
"class"
] |
def parse(self, html):
"""
Entry point for class
"""
result = self.select_tag(html)
return result
|
[
"def",
"parse",
"(",
"self",
",",
"html",
")",
":",
"result",
"=",
"self",
".",
"select_tag",
"(",
"html",
")",
"return",
"result"
] |
https://github.com/sahana/eden/blob/1696fa50e90ce967df69f66b571af45356cc18da/modules/s3/codecs/pdf.py#L1834-L1840
|
|
bugcrowd/HUNT
|
ed3e1adee724bf6c98750f377f6c40cd656c82d3
|
Burp/lib/scanner_table_models.py
|
python
|
ScannerTableModels.set_scanner_table_model
|
(self, scanner_issue, issue_name, issue_param, vuln_param)
|
[] |
def set_scanner_table_model(self, scanner_issue, issue_name, issue_param, vuln_param):
key = issue_name + "." + vuln_param
scanner_issue_id = str(scanner_issue.getRequestResponse()).split("@")[1]
scanner_table_model = self.scanner_table_models[key]
# Using the addRow() method requires that the data type being passed to be of type
# Vector() or Object(). Passing a Python object of type list in addRow causes a type
# conversion error of sorts which presents as an ArrayOutOfBoundsException. Therefore,
# row is an instantiation of Object() to avoid this error.
row = Object()
row = [False, issue_param, scanner_issue.getHttpService().getHost(), scanner_issue.getPath(), scanner_issue_id]
try:
scanner_table_model.addRow(row)
except Exception as e:
print(e)
|
[
"def",
"set_scanner_table_model",
"(",
"self",
",",
"scanner_issue",
",",
"issue_name",
",",
"issue_param",
",",
"vuln_param",
")",
":",
"key",
"=",
"issue_name",
"+",
"\".\"",
"+",
"vuln_param",
"scanner_issue_id",
"=",
"str",
"(",
"scanner_issue",
".",
"getRequestResponse",
"(",
")",
")",
".",
"split",
"(",
"\"@\"",
")",
"[",
"1",
"]",
"scanner_table_model",
"=",
"self",
".",
"scanner_table_models",
"[",
"key",
"]",
"# Using the addRow() method requires that the data type being passed to be of type",
"# Vector() or Object(). Passing a Python object of type list in addRow causes a type",
"# conversion error of sorts which presents as an ArrayOutOfBoundsException. Therefore,",
"# row is an instantiation of Object() to avoid this error.",
"row",
"=",
"Object",
"(",
")",
"row",
"=",
"[",
"False",
",",
"issue_param",
",",
"scanner_issue",
".",
"getHttpService",
"(",
")",
".",
"getHost",
"(",
")",
",",
"scanner_issue",
".",
"getPath",
"(",
")",
",",
"scanner_issue_id",
"]",
"try",
":",
"scanner_table_model",
".",
"addRow",
"(",
"row",
")",
"except",
"Exception",
"as",
"e",
":",
"print",
"(",
"e",
")"
] |
https://github.com/bugcrowd/HUNT/blob/ed3e1adee724bf6c98750f377f6c40cd656c82d3/Burp/lib/scanner_table_models.py#L26-L41
|
||||
pinax/django-user-accounts
|
e83effdd4a23cd8d830169904c261ff6677ee3e6
|
account/auth_backends.py
|
python
|
EmailAuthenticationBackend.authenticate
|
(self, request, username=None, password=None, **kwargs)
|
Authenticate the user based email
|
Authenticate the user based email
|
[
"Authenticate",
"the",
"user",
"based",
"email"
] |
def authenticate(self, request, username=None, password=None, **kwargs):
"""Authenticate the user based email"""
qs = EmailAddress.objects.filter(Q(primary=True) | Q(verified=True))
if username is None or password is None:
return None
try:
email_address = qs.get(email__iexact=username)
except EmailAddress.DoesNotExist:
return None
user = email_address.user
if user.check_password(password):
return user
|
[
"def",
"authenticate",
"(",
"self",
",",
"request",
",",
"username",
"=",
"None",
",",
"password",
"=",
"None",
",",
"*",
"*",
"kwargs",
")",
":",
"qs",
"=",
"EmailAddress",
".",
"objects",
".",
"filter",
"(",
"Q",
"(",
"primary",
"=",
"True",
")",
"|",
"Q",
"(",
"verified",
"=",
"True",
")",
")",
"if",
"username",
"is",
"None",
"or",
"password",
"is",
"None",
":",
"return",
"None",
"try",
":",
"email_address",
"=",
"qs",
".",
"get",
"(",
"email__iexact",
"=",
"username",
")",
"except",
"EmailAddress",
".",
"DoesNotExist",
":",
"return",
"None",
"user",
"=",
"email_address",
".",
"user",
"if",
"user",
".",
"check_password",
"(",
"password",
")",
":",
"return",
"user"
] |
https://github.com/pinax/django-user-accounts/blob/e83effdd4a23cd8d830169904c261ff6677ee3e6/account/auth_backends.py#L48-L62
|
||
wzzheng/HDML
|
fa03ef0eb0be2256df7aab928bcc596c41d44fb3
|
lib/nn_Ops.py
|
python
|
weight_variable
|
(shape, name, wd=True)
|
return weight
|
A function to create weight variables
:param shape: The shape of weight
:param name: The name of the weight
:param wd: Whether or not this variable should be weight decade
:return: A weight-variable
|
A function to create weight variables
:param shape: The shape of weight
:param name: The name of the weight
:param wd: Whether or not this variable should be weight decade
:return: A weight-variable
|
[
"A",
"function",
"to",
"create",
"weight",
"variables",
":",
"param",
"shape",
":",
"The",
"shape",
"of",
"weight",
":",
"param",
"name",
":",
"The",
"name",
"of",
"the",
"weight",
":",
"param",
"wd",
":",
"Whether",
"or",
"not",
"this",
"variable",
"should",
"be",
"weight",
"decade",
":",
"return",
":",
"A",
"weight",
"-",
"variable"
] |
def weight_variable(shape, name, wd=True):
"""
A function to create weight variables
:param shape: The shape of weight
:param name: The name of the weight
:param wd: Whether or not this variable should be weight decade
:return: A weight-variable
"""
initializer = tf.glorot_uniform_initializer()#tf.contrib.layers.xavier_initializer() # tf.truncated_normal_initializer(stddev=0.1)
if wd:
weight = tf.get_variable(name='weight'+name, shape=shape,
initializer=initializer,
collections=[tf.GraphKeys.WEIGHTS, tf.GraphKeys.GLOBAL_VARIABLES])
else:
weight = tf.get_variable(name='weight' + name, shape=shape,
initializer=initializer,
collections=[tf.GraphKeys.GLOBAL_VARIABLES])
return weight
|
[
"def",
"weight_variable",
"(",
"shape",
",",
"name",
",",
"wd",
"=",
"True",
")",
":",
"initializer",
"=",
"tf",
".",
"glorot_uniform_initializer",
"(",
")",
"#tf.contrib.layers.xavier_initializer() # tf.truncated_normal_initializer(stddev=0.1)",
"if",
"wd",
":",
"weight",
"=",
"tf",
".",
"get_variable",
"(",
"name",
"=",
"'weight'",
"+",
"name",
",",
"shape",
"=",
"shape",
",",
"initializer",
"=",
"initializer",
",",
"collections",
"=",
"[",
"tf",
".",
"GraphKeys",
".",
"WEIGHTS",
",",
"tf",
".",
"GraphKeys",
".",
"GLOBAL_VARIABLES",
"]",
")",
"else",
":",
"weight",
"=",
"tf",
".",
"get_variable",
"(",
"name",
"=",
"'weight'",
"+",
"name",
",",
"shape",
"=",
"shape",
",",
"initializer",
"=",
"initializer",
",",
"collections",
"=",
"[",
"tf",
".",
"GraphKeys",
".",
"GLOBAL_VARIABLES",
"]",
")",
"return",
"weight"
] |
https://github.com/wzzheng/HDML/blob/fa03ef0eb0be2256df7aab928bcc596c41d44fb3/lib/nn_Ops.py#L10-L28
|
|
ialbert/biostar-central
|
2dc7bd30691a50b2da9c2833ba354056bc686afa
|
biostar/forum/markdown.py
|
python
|
BiostarInlineLexer.output_anchor_link
|
(self, m)
|
return f'<a href="{link}">{title}</a>'
|
[] |
def output_anchor_link(self, m):
uid = m.group("uid")
link = m.group(0)
post = Post.objects.filter(uid=uid).first()
title = post.root.title if post else "Post not found"
return f'<a href="{link}">{title}</a>'
|
[
"def",
"output_anchor_link",
"(",
"self",
",",
"m",
")",
":",
"uid",
"=",
"m",
".",
"group",
"(",
"\"uid\"",
")",
"link",
"=",
"m",
".",
"group",
"(",
"0",
")",
"post",
"=",
"Post",
".",
"objects",
".",
"filter",
"(",
"uid",
"=",
"uid",
")",
".",
"first",
"(",
")",
"title",
"=",
"post",
".",
"root",
".",
"title",
"if",
"post",
"else",
"\"Post not found\"",
"return",
"f'<a href=\"{link}\">{title}</a>'"
] |
https://github.com/ialbert/biostar-central/blob/2dc7bd30691a50b2da9c2833ba354056bc686afa/biostar/forum/markdown.py#L269-L274
|
|||
openstack/trove
|
be86b79119d16ee77f596172f43b0c97cb2617bd
|
trove/guestagent/datastore/postgres/query.py
|
python
|
UserQuery.update_password
|
(cls, name, password, encrypt_password=None)
|
return cls.alter_user(name, password, encrypt_password)
|
Query to update the password for a user.
|
Query to update the password for a user.
|
[
"Query",
"to",
"update",
"the",
"password",
"for",
"a",
"user",
"."
] |
def update_password(cls, name, password, encrypt_password=None):
"""Query to update the password for a user."""
return cls.alter_user(name, password, encrypt_password)
|
[
"def",
"update_password",
"(",
"cls",
",",
"name",
",",
"password",
",",
"encrypt_password",
"=",
"None",
")",
":",
"return",
"cls",
".",
"alter_user",
"(",
"name",
",",
"password",
",",
"encrypt_password",
")"
] |
https://github.com/openstack/trove/blob/be86b79119d16ee77f596172f43b0c97cb2617bd/trove/guestagent/datastore/postgres/query.py#L116-L119
|
|
tensorflow/kfac
|
fe90e36c3e0b42c73e4a34835a66f6d45e2a442d
|
kfac/python/ops/fisher_factors.py
|
python
|
ConvInputSUAKroneckerFactor.instantiate_inv_variables
|
(self)
|
Makes the internal "inverse" variable(s).
|
Makes the internal "inverse" variable(s).
|
[
"Makes",
"the",
"internal",
"inverse",
"variable",
"(",
"s",
")",
"."
] |
def instantiate_inv_variables(self):
"""Makes the internal "inverse" variable(s)."""
for (exp, damping_id) in self._matpower_registrations:
if exp != -1.:
raise ValueError("ConvInputSUAKroneckerFactor only supports inverse"
"computation")
exp_string = scalar_or_tensor_to_string(exp)
damping_func = self._damping_funcs_by_id[damping_id]
damping_string = graph_func_to_string(damping_func)
with tf.variable_scope(self._var_scope):
matpower = tf.get_variable(
"matpower_exp{}_damp{}".format(exp_string, damping_string),
initializer=inverse_initializer,
shape=self._cov_shape,
trainable=False,
dtype=self._dtype,
use_resource=True)
assert (exp, damping_id) not in self._matpower_by_exp_and_damping
self._matpower_by_exp_and_damping[(exp, damping_id)] = matpower
self._damping_var_by_id[damping_id] = tf.get_variable(
"damping_var_{}_{}".format(exp_string, damping_string),
initializer=tf.zeros_initializer(),
shape=(),
trainable=False,
dtype=self._dtype,
use_resource=True)
if not ASSUME_ZERO_MEAN_ACTIVATIONS:
self._cov_inv_mu_by_damping_id[damping_id] = tf.get_variable(
"cov_inv_mu_{}_{}".format(exp_string, damping_string),
initializer=tf.zeros_initializer(),
shape=(self._in_channels, 1),
trainable=False,
dtype=self._dtype,
use_resource=True)
self._rank_one_update_scale_by_damping_id[damping_id] = tf.get_variable(
"rank_one_update_scale_{}_{}".format(exp_string, damping_string),
initializer=tf.zeros_initializer(),
shape=(),
trainable=False,
dtype=self._dtype,
use_resource=True)
|
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] |
https://github.com/tensorflow/kfac/blob/fe90e36c3e0b42c73e4a34835a66f6d45e2a442d/kfac/python/ops/fisher_factors.py#L2247-L2293
|
||
bikalims/bika.lims
|
35e4bbdb5a3912cae0b5eb13e51097c8b0486349
|
bika/lims/exportimport/setupdata/__init__.py
|
python
|
Invoice_Batches.Import
|
(self)
|
[] |
def Import(self):
folder = self.context.invoices
for row in self.get_rows(3):
obj = _createObjectByType("InvoiceBatch", folder, tmpID())
if not row['title']:
message = _("InvoiceBatch has no Title")
raise Exception(t(message))
if not row['start']:
message = _("InvoiceBatch has no Start Date")
raise Exception(t(message))
if not row['end']:
message = _("InvoiceBatch has no End Date")
raise Exception(t(message))
obj.edit(
title=row['title'],
BatchStartDate=row['start'],
BatchEndDate=row['end'],
)
renameAfterCreation(obj)
|
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] |
https://github.com/bikalims/bika.lims/blob/35e4bbdb5a3912cae0b5eb13e51097c8b0486349/bika/lims/exportimport/setupdata/__init__.py#L2262-L2280
|
||||
bikalims/bika.lims
|
35e4bbdb5a3912cae0b5eb13e51097c8b0486349
|
bika/lims/validators.py
|
python
|
InterimFieldsValidator.__call__
|
(self, value, *args, **kwargs)
|
return True
|
[] |
def __call__(self, value, *args, **kwargs):
instance = kwargs['instance']
fieldname = kwargs['field'].getName()
request = kwargs.get('REQUEST', {})
form = request.form
interim_fields = form.get(fieldname, [])
translate = getToolByName(instance, 'translation_service').translate
bsc = getToolByName(instance, 'bika_setup_catalog')
# We run through the validator once per form submit, and check all
# values
# this value in request prevents running once per subfield value.
key = instance.id + fieldname
if instance.REQUEST.get(key, False):
return True
for x in range(len(interim_fields)):
row = interim_fields[x]
keys = row.keys()
if 'title' not in keys:
instance.REQUEST[key] = to_utf8(
translate(_("Validation failed: title is required")))
return instance.REQUEST[key]
if 'keyword' not in keys:
instance.REQUEST[key] = to_utf8(
translate(_("Validation failed: keyword is required")))
return instance.REQUEST[key]
if not re.match(r"^[A-Za-z\w\d\-\_]+$", row['keyword']):
instance.REQUEST[key] = _(
"Validation failed: keyword contains invalid characters")
return instance.REQUEST[key]
# keywords and titles used once only in the submitted form
keywords = {}
titles = {}
for field in interim_fields:
if 'keyword' in field:
if field['keyword'] in keywords:
keywords[field['keyword']] += 1
else:
keywords[field['keyword']] = 1
if 'title' in field:
if field['title'] in titles:
titles[field['title']] += 1
else:
titles[field['title']] = 1
for k in [k for k in keywords.keys() if keywords[k] > 1]:
msg = _("Validation failed: '${keyword}': duplicate keyword",
mapping={'keyword': safe_unicode(k)})
instance.REQUEST[key] = to_utf8(translate(msg))
return instance.REQUEST[key]
for t in [t for t in titles.keys() if titles[t] > 1]:
msg = _("Validation failed: '${title}': duplicate title",
mapping={'title': safe_unicode(t)})
instance.REQUEST[key] = to_utf8(translate(msg))
return instance.REQUEST[key]
# check all keywords against all AnalysisService keywords for dups
services = bsc(portal_type='AnalysisService', getKeyword=value)
if services:
msg = _("Validation failed: '${title}': "
"This keyword is already in use by service '${used_by}'",
mapping={'title': safe_unicode(value),
'used_by': safe_unicode(services[0].Title)})
instance.REQUEST[key] = to_utf8(translate(msg))
return instance.REQUEST[key]
# any duplicated interimfield titles must share the same keyword
# any duplicated interimfield keywords must share the same title
calcs = bsc(portal_type='Calculation')
keyword_titles = {}
title_keywords = {}
for calc in calcs:
if calc.UID == instance.UID():
continue
calc = calc.getObject()
for field in calc.getInterimFields():
keyword_titles[field['keyword']] = field['title']
title_keywords[field['title']] = field['keyword']
for field in interim_fields:
if field['keyword'] != value:
continue
if 'title' in field and \
field['title'] in title_keywords.keys() and \
title_keywords[field['title']] != field['keyword']:
msg = _("Validation failed: column title '${title}' "
"must have keyword '${keyword}'",
mapping={'title': safe_unicode(field['title']),
'keyword': safe_unicode(
title_keywords[field['title']])})
instance.REQUEST[key] = to_utf8(translate(msg))
return instance.REQUEST[key]
if 'keyword' in field and \
field['keyword'] in keyword_titles.keys() and \
keyword_titles[field['keyword']] != field['title']:
msg = _("Validation failed: keyword '${keyword}' "
"must have column title '${title}'",
mapping={'keyword': safe_unicode(field['keyword']),
'title': safe_unicode(
keyword_titles[field['keyword']])})
instance.REQUEST[key] = to_utf8(translate(msg))
return instance.REQUEST[key]
instance.REQUEST[key] = True
return True
|
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] |
https://github.com/bikalims/bika.lims/blob/35e4bbdb5a3912cae0b5eb13e51097c8b0486349/bika/lims/validators.py#L247-L352
|
|||
JiYou/openstack
|
8607dd488bde0905044b303eb6e52bdea6806923
|
chap19/monitor/python-monitorclient-1.1/build/lib.linux-x86_64-2.7/monitorclient/openstack/common/memorycache.py
|
python
|
Client.incr
|
(self, key, delta=1)
|
return new_value
|
Increments the value for a key.
|
Increments the value for a key.
|
[
"Increments",
"the",
"value",
"for",
"a",
"key",
"."
] |
def incr(self, key, delta=1):
"""Increments the value for a key."""
value = self.get(key)
if value is None:
return None
new_value = int(value) + delta
self.cache[key] = (self.cache[key][0], str(new_value))
return new_value
|
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https://github.com/JiYou/openstack/blob/8607dd488bde0905044b303eb6e52bdea6806923/chap19/monitor/python-monitorclient-1.1/build/lib.linux-x86_64-2.7/monitorclient/openstack/common/memorycache.py#L84-L91
|
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